EPA/600/R-090/052F | September 2011 | www.epa.gov
United States
Environmental Protection
Agency
Exposure Factors Handbook: 2011 Edition
Office of Research and Development, Washington, DC 20460
National Center for Environmental Assessment
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EPA/600/R-09/052F
September 2011
EXPOSURE FACTORS HANDBOOK:
2011 EDITION
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC 20460
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Exposure Factors Handbook
Front Matter
DISCLAIMER
This document has been reviewed in accordance with U.S. Environmental Protection Agency policy and
approved for publication. Mention of trade names or commercial products does not constitute endorsement or
recommendation for use.
Preferred Citation:
U.S. EPA (Environmental Protection Agency). (2011) Exposure factors handbook: 2011 edition. National Center
for Environmental Assessment, Washington, DC; EPA/600/R-09/052F. Available from the National Technical
Information Service, Springfield, VA, and online at http://www.epa.gov/ncea/efh.
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FOREWORD
The U.S. Environmental Protection Agency (U.S. EPA), Office of Research and Development (ORD),
National Center for Environmental Assessment's (NCEA) mission is to provide guidance and risk assessments
aimed at protecting human health and the environment. To accomplish this mission, NCEA works to develop and
improve the models, databases, tools, assumptions, and extrapolations used in risk assessments. NCEA established
the Exposure Factors Program to develop tools and databases that improve the scientific basis of exposure and risk
assessment by (1) identifying exposure factors needs in consultation with clients, and exploring ways for filling data
gaps; (2) compiling existing data on exposure factors needed for assessing exposures/risks; and (3) assisting clients
in the use of exposure factors data. The Exposure Factors Handbook and the Child-Specific Exposure Factors
Handbook, as well as other companion documents such as Example Exposure Scenarios, are products of the
Exposure Factors Program.
The Exposure Factors Handbook provides information on various physiological and behavioral factors
commonly used in assessing exposure to environmental chemicals. The handbook was first published in 1989 and
was updated in 1997. Since then, new data have become available. This updated edition incorporates data available
since 1997 up to July 2011. It also reflects the revisions made to the Child-Specific Exposure Factors Handbook,
which was updated and published in 2008. This edition of the handbook supersedes the information presented in the
2008 Child-Specific Exposure Factors Handbook. Each chapter in the 2011 edition of the Exposure Factors
Handbook presents recommended values for the exposure factors covered in the chapter as well as a discussion of
the underlying data used in developing the recommendations. These recommended values are based solely on
NCEA's interpretations of the available data. In many situations, different values may be appropriate to use in
consideration of policy, precedent, or other factors.
David Bussard
Director, Washington Division
National Center for Environmental Assessment
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
The National Center for Environmental Assessment (NCEA), Office of Research and Development was
responsible for the preparation of this handbook. Jacqueline Moya served as the Work Assignment Manager for the
current updated edition, providing overall direction and technical assistance, and is a contributing author. The
current draft was prepared by Westat Inc. under contract with the U.S. EPA (contract number GS-23F-8144H).
Earlier drafts of this report were prepared by Versar, Inc.
AUTHORS
U.S. EPA
Jacqueline Moya
Linda Phillips
Laurie Schuda
Versar. Inc.
Patricia Wood
Adria Diaz
Ron Lee
Westat Inc.
Robert Clickner
Rebecca Jeffries Birch
Naa Adjei
Peter Blood
Kathleen Chapman
Rey de Castro
Kathryn Mahaffey
WORD PROCESSING
Versar. Inc.
Malikah Moore
Westat Inc.
Annmarie Winkler
ECFlex. Inc.
Debbie Kleiser
Crystal Lewis
Lana Wood
IntelliTech Systems. Inc.
Kathleen Secor
TECHNICAL EDITNG
ECFlex. Inc.
Heidi Click
IntelliTech Systems. Inc.
Cristopher Boyles
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AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued)
REVIEWERS
The following U.S. EPA individuals reviewed earlier drafts of this document and provided valuable
comments:
Ted Berner, NCEA
Heidi Bethel, OW
Margot Brown, OCHP
Lisa Conner, OAQPS
Mark Corrales, OPEI
Dave Crawford, OSWER
Becky Cuthbertson, OSW
Lynn Delpire, OPPTS
Cathy Fehrenbacher, OPPTS
Gary Foureman, NCEA (retired)
Ann Johnson, OPEI
Henry Kahn, NCEA
Youngmoo Kim, Region 6
Lon Kissinger, Region 10
JohnLangstaff, OAQPS
Sarah Levinson, Region 1
Matthew Lorber, NCEA
TomMcCurdy, NERL
Robert McGaughy, NCEA (retired)
Marian Olsen, Region 2
David Riley, Region 6
Rita Schoeny, OW
Marc Stifelman, Region 10
Zachary Pekar, OAQPS
Aaron Yeow, OSWER
Linda Watson, Region 3
Valerie Zartarian, NERL
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AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued)
This document was reviewed by an external panel of experts. The panel was composed of the following
individuals:
• Henry Anderson, MD, Wisconsin Division of Public Health, Madison
• Paloma Beamer, PhD, Environmental Health Sciences, University of Arizona
• Deborah H. Bennett, PhD, Department of Public Health Sciences, University of California, Davis
• Robert J. Blaisdell, PhD, Office of Environmental Health Hazard Assessment, California Environmental
Protection Agency
• Alesia Ferguson, PhD, College of Public Health, University of Arkansas Medical Services
• Brent L. Finley, PhD, ChemRisk
• David W. Gaylor, PhD, Gaylor and Associates, LLC
• Panos G. Georgopoulus, PhD, Robert Wood Johnson Medical School, University of Medicine and
Dentistry of New Jersey
• Annette Guiseppi-Ellie, PhD, Dupont Engineering, Corporate Remediation Group
• Michael D. Lebowitz, PhC, PhD, University of Arizona, Tucson, AZ
• Agnes B. Lobscheid, PhD, Environmental Energy Technologies Division, Indoor Air Department,
Lawrence Berkeley National Laboratory
• P. Barry Ryan, PhD, Rollins School of Public Health, Emory University
• Alan H. Stern, PhD, Independent Consultant
• Nga L. Tran, PhD, Health Sciences Center for Chemical Regulation and Food Safety, Exponent,
Washington, DC
• Rosemary T. Zaleski, PhD, Occupational and Public Health Division, ExxonMobil Biomedical Sciences,
Inc.
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AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued)
ACKNOWLEDGMENTS
The authors wish to acknowledge the important contributions of the following U.S. EPA individuals who
conducted additional analyses for the revisions of this handbook:
• David Hrdy, Office of Pesticide Programs
• Henry Kahn, National Center for Environmental Assessment
• David Miller, Office of Pesticide Programs
• James Nguyen, Office of Pesticide Programs
• Aaron Niman, Office of Pesticide Programs
• Allison Nowotarski, Office of Pesticide Programs
• Sheila Piper, Office of Pesticide Programs
• Kristin Rury, Office of Pesticide Programs
• Bernard Schneider, Office of Pesticide Programs
• Nicolle Tulve, National Exposure Research Laboratory
• Julie Van Alstine, Office of Pesticide Programs
• Philip Villanueva, Office of Pesticide Programs
In addition, the U.S. EPA, ORD, National Exposure Research Laboratory (NERL) made an important
contribution to this handbook by conducting additional analyses of the National Human Activity Pattern Survey
(NHAPS) data. U.S. EPA input to the NHAPS data analysis came from Karen A. Hammerstrom and Jacqueline
Moya from NCEA-Washington Division, William C. Nelson from NERL-Research Triangle Park, and Stephen C.
Hern, Joseph V. Behar (retired), and William H. Englemann from NERL-Las Vegas.
The U.S. EPA Office of Water and Office of Pesticide Programs made important contributions by
conducting an analysis of the U.S. Department of Agriculture (USDA) Continuing Survey of Food Intakes by
Individual (CSFII) data in previous versions of the handbook. More recently, the Office of Pesticide Programs
conducted an analysis of the National Health and Nutrition Examination Survey (NHANES) 2063006 to update
the Food Commodity Intake Database (FCID) and food consumption chapters of this edition of the handbook.
The authors also want to acknowledge the following individuals in NCEA: Terri Konoza for
managing the document production activities and copy editing, Vicki Soto for copy editing, and Maureen
Johnson for developing and managing the Web page.
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EXECUTIVE SUMMARY
Some of the steps for performing an exposure assessment are (1) identifying the source of the
environmental contamination and the media that transports the contaminant; (2) determining the contaminant
concentration; (3) determining the exposure scenarios, and pathways and routes of exposure; (4) determining the
exposure factors related to human behaviors that define time, frequency, and duration of exposure; and
(5) identifying the exposed population. Exposure factors are factors related to human behavior and characteristics
that help determine an individual's exposure to an agent. This Exposure Factors Handbook has been prepared to
provide information and recommendations on various factors used in assessing exposure to both adults and children.
The purpose of the Exposure Factors Handbook is to (1) summarize data on human behaviors and characteristics
that affect exposure to environmental contaminants, and (2) recommend values to use for these factors. This
handbook provides nonchemical-specific data on the following exposure factors:
• Ingestion of water and other selected liquids (see Chapter 3),
• Non-dietary ingestion factors (see Chapter 4),
• Ingestion of soil and dust (see Chapter 5),
• Inhalation rates (see Chapter 6),
• Dermal factors (see Chapter 7),
• Body weight (see Chapter 8),
• Intake of fruits and vegetables (see Chapter 9),
• Intake offish and shellfish (see Chapter 10),
• Intake of meat, dairy products, and fats (see Chapter 11),
• Intake of grain products (see Chapter 12),
• Intake of home-produced food (see Chapter 13),
• Total food intake (see Chapter 14),
• Human milk intake (see Chapter 15),
• Activity factors (see Chapter 16),
• Consumer products (see Chapter 17),
• Lifetime (see Chapter 18), and
• Building characteristics (see Chapter 19).
The handbook was first published in 1989 and was revised in 1997 (U.S. EPA, 1989, 1997). Recognizing
that exposures among infants, toddlers, adolescents, and teenagers can vary significantly, the U.S. EPA published
the Child-Specific Exposure Factors Handbook in 2002 (U.S. EPA, 2002) and its revision in 2008 (U.S. EPA,
2008). The 2008 revision of the Child-Specific Exposure Factors Handbook as well as this 2011 edition of the
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Exposure Factors Handbook reflect the age categories recommended in the U.S. EPA Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005). This
2011 edition of the Exposure Factors Handbook also incorporates new factors and data provided in the 2008 Child-
Specific Exposure Factors Handbook (and other relevant information published through July 2011. The information
presented in this 2011 edition of the Exposure Factors Handbook supersedes the 2008 Child-Specific Exposure
Factors Handbook.
The data presented in this handbook have been compiled from various sources, including government
reports and information presented in the scientific literature. The data presented are the result of analyses by the
individual study authors. However, in some cases, the U.S. EPA conducted additional analysis of published primary
data to present results in a way that will be useful to exposure assessors and/or in a manner that is consistent with the
recommended age groups. Studies presented in this handbook were chosen because they were seen as useful and
appropriate for estimating exposure factors based on the following considerations: (1) soundness (adequacy of
approach and minimal or defined bias); (2) applicability and utility (focus on the exposure factor of interest,
representativeness of the population, currency of the information, and adequacy of the data collection period);
(3) clarity and completeness (accessibility, reproducibility, and quality assurance); (4) variability and uncertainty
(variability in the population and uncertainty in the results); and (5) evaluation and review (level of peer review and
number and agreement of studies). Generally, studies were designated as "key" or "relevant" studies. Key studies
were considered the most up-to-date and scientifically sound for deriving recommendations; while relevant studies
provided applicable or pertinent data, but not necessarily the most important for a variety of reasons (e.g., data were
outdated, limitations in study design). The recommended values for exposure factors are based on the results of key
studies. The U.S. EPA also assigned confidence ratings of low, medium, or high to each recommended value based
on the evaluation elements described above. These ratings are not intended to represent uncertainty analyses; rather,
they represent the U.S. EP A's judgment on the quality of the underlying data used to derive the recommendations.
Key recommendations from the handbook are summarized in Table ES-1. Additional recommendations and
detailed supporting information for these recommendations can be found in the individual chapters of this handbook.
In providing recommendations for the various exposure factors, an attempt was made to present percentile values
that are consistent with the exposure estimators defined in the Guidelines for Exposure Assessment (U.S. EPA,
1992) (i.e., mean and upper percentile). However, this was not always possible because the data available were
limited for some factors, or the authors of the study did not provide such information. As used throughout this
handbook, the term "upper percentile" is intended to represent values in the upper tail (i.e., between 90th and 99.9th
percentile) of the distribution of values for a particular exposure factor. The 95th percentile was used throughout the
handbook to represent the upper tail because it is the middle of the range between 90th and 99th percentile. Other
percentiles are presented, where available, in the tables at the end of each chapter. It should be noted that users of
the handbook may use the exposure metric that is most appropriate for their particular situation.
The recommendations provided in this handbook are not legally binding on any U.S. EPA program and
should be interpreted as suggestions that program offices or individual exposure/risk assessors can consider and
modify as needed based on their own evaluation of a given risk assessment situation. In certain cases, different
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values may be appropriate in consideration of policy, precedent, strategy, or other factors (e.g., more up-to-date data
of better quality or more representative of the population of concern).
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REFERENCES FOR THE EXECUTIVE SUMMARY
NCHS (National Center for Health Statistics). (1993) Joint policy on variance estimation and statistical reporting
standards onNHANES III and CSFII reports: HNIS/NCHS Analytic Working Group recommendations. In:
Analytic and reporting guidelines: the third National Health and Nutrition Examination Survey, NHANES
III (1988-94). Centers for Disease Control and Prevention, Hyattsville, MD, pp. 39-45. Available online at
http://www.cdc.gov/nchs/data/nhanes/nhanes3/nh3gui.pdf.
U.S. EPA (Environmental Protection Agency). (1989) Exposure factors handbook. Exposure Assessment Group,
Office of Research and Development, Washington, DC; EPA/600/8-89/043. Available online at
http://rais.ornl.gov/documents/EFH_1989_EP A600889043.pdf.
U.S. EPA (Environmental Protection Agency). (1992) Guidelines for exposure assessment. Risk Assessment Forum,
Washington, DC; EPA/600/Z-92/001. Available online at http://cfpub.epa.gov/ncea/cfm/.cfm?deid=15263.
U.S. EPA (Environmental Protection Agency). (1997) Exposure factors handbook. Office of Research and
Development, Washington, DC; EPA/600/P-95/002Fa,b,c. Available online at
http://www.epa.gov/ncea/pdfs/efh/efh-complete.pdf.
U.S. EPA (Environmental Protection Agency). (2002) Child-specific exposure factors handbook Interim final.
National Center for Environmental Assessment, Washington, DC; EPA/P-00/002B. Available online at
http://cfpub.epa. gov/ncea/cfm/recordisplay.cfm?deid=55145.
U.S. EPA (Environmental Protection Agency). (2005) Guidance on selecting age groups for monitoring and
assessing childhood exposures to environmental contaminants. Risk Assessment Forum, Washington, DC;
EPA/630/P-03/003F. Available online at http://www.epa.gov/raf/publications/pdfs/AGEGROUPS.PDF.
U.S. EPA (Environmental Protection Agency) (2008) Child-specific exposure factors handbook. National Center for
Environmental Assessment Washington, DC; EPA/600/R-06/096F. Available online at
http://cfpub.epa. gov/ncea/cfm/recordisplay.cfm?deid= 199243.
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Table ES-1. Summary of Exposure Factor Recommendations
Chapter 3
Children
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <18 years
18 to<21 years
Adults
>21 years
>65 years
Pregnant women
Lactatina women
PER CAPITA INGESTION OF CONSUMERS-ONLY INGESTION OF
DRINKING WATER DRINKING WATER
Mean 95th Percentile Mean 95th Percentile
mlVday mL/kg-day mL/day mL/kg-day mlVday mlVkg-day mlVday mlVkg-day
184 52 839a 232a 470a 137a 858a 238a
227a 48 896a 205a 552 119 l,053a 285a
362a 52 1,056 159 556 80 1,171" 173a
360 41 1,055 126 467 53 1,147 129
271 23 837 71 308 27 893 75
317 23 877 60 356 26 912 62
327 18 959 51 382 21 999 52
414 14 1,316 43 511 17 1,404 47
520 10 1,821 32 637 12 1,976 35
573 9 1,783 28 702 10 1,883 30
681 9 2,368 35 816 11 2,818 36
1,043 13 2,958 40 1,227 16 3,092 42
1,046 14 2,730 40 1,288 18 2,960 43
819a 13a 2,503a 43a 872a 14a 2,589a 43a
l,379a 21a 3,434a 55a l,665a 26a 3,588a 55a
a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical
Reporting Standards on NHANES III andCSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Chapter 3
Children
Adults
INGESTION OF WATER WHILE SWIMMING
Mean Upper Percentile
mL/eventa mL/hour mlVevent mlVhour
37 49 90" 120"
16 21 53 c 71 c
a Participants swam for 45 minutes.
b 97th percentile
c Based on maximum value.
Chapter 4
MOUTHING FREQUENCY AND DURATION
Hand-to-Mouth Object-to-Mouth
Indoor Frequency Outdoor Frequency Indoor Frequency Outdoor Frequency
Mean 95th Mean 95th Percentile Mean 95th Percentile Mean 95th Percentile
contacts/ Percentile contacts/ contacts/hour contacts/ contacts/ contacts/ contacts/
hour contacts/ hour hour hour hour hour
hour
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
28 65 - - 11 32
19 52 15 47 20 38 -
20 63 14 42 14 34 8.8 21
13 37 5 20 9.9 24 8.1 40
15 54 9 36 10 39 8.3 30
7 21 3 12 1.1 3.2 1.9 9.1
Object-to-Mouth
Duration
Mean minute/hour 95th Percentile minute/hour
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
11 26
9 19
7 22
10 11
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No data.
Chapter 5
6 weeks to <1 year
1 to <6 years
3 to <6 years
6to<21 years
Adult
Table
ES-1. Summary of Exposure
Factor Recommendations (continued)
SOIL AND DUST INGESTION
Gen
Popu
Cer
Tenc
mg/
eral
Soil
Dust
Soil +
Dust
High End
, , General
itral „ . .
Population
ency 51
, J Upper
day „ ...
J Percentile
mg/day
30
50
50
20
200
Soil-Pica
mg/day
1,000
1,000
Geophagy
mg/day
50,000
50,000
50,000
Central
Tendency
mg/day
30
60
60
30
General General General
Population Population Population
Upper Central Upper
Percentile Tendency Percentile
mg/day mg/day mg/day
100
60
100
100
50
200
No data.
Chapter 6
INHALATION
Long-Term Inhalation
Rates
Mean
m3/day
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
Birth to 81 years
3.6
3.5
4.1
5.4
5.4
8.0
8.9
10.1
12.0
15.2
16.3
15.7
16.0
16.0
15.7
14.2
12.9
12.2
Short-Term Inhalation
Sleep or Nap
Birth to 81 years
Mean
m3/
minute
3.0E-03
4.5E-03
4.6E-03
4.3E-03
4.5E-03
5.0E-03
4.9E-03
4.3E-03
4.6E-03
5.0E-03
5.2E-03
5.2E-03
5.3E-03
5.2E-03
95th
m3/
minute
4.6E-03
6.4E-03
6.4E-03
5.8E-03
6.3E-03
7.4E-03
7.1E-03
6.5E-03
6.6E-03
7.1E-03
7.5E-03
7.2E-03
7.2E-03
7.0E-03
Sedentary/Passive
Mean
m3/
minute
3.1E-03
4.7E-03
4.8E-03
4.5E-03
4.8E-03
5.4E-03
5.3E-03
4.2E-03
4.3E-03
4.8E-03
5.0E-03
4.9E-03
5.0E-03
4.9E-03
95th
m3/
minute
4.7E-03
6.5E-03
6.5E-03
5.8E-03
6.4E-03
7.5E-03
7.2E-03
6.5E-03
6.6E-03
7.0E-03
7.3E-03
7.3E-03
7.2E-03
7.0E-03
95th Percentile
mVday
7.1
5.8
6.1
8.0
9.2
12.8
13.7
13.8
16.6
21.9
24.6
21.3
21.4
21.2
21.3
18.1
16.6
15.7
Rates, by Activity Level
Light Intensity
Mean
m3/
minute
7.6E-03
1.2E-02
1.2E-02
1.1E-02
1.1E-02
1.3E-02
1.2E-02
1.2E-02
1.2E-02
1.3E-02
1.3E-02
1.2E-02
1.2E-02
1.2E-02
95th
m3/
minute
1.1E-02
1.6E-02
1.6E-02
1.4E-02
1.5E-02
1.7E-02
1.6E-02
1.6E-02
1.6E-02
1.6E-02
1.7E-02
1.6E-02
1.5E-02
1.5E-02
Moderate Intensity
Mean
m3/
minute
1.4E-02
2.1E-02
2.1E-02
2.1E-02
2.2E-02
2.5E-02
2.6E-02
2.6E-02
2.7E-02
2.8E-02
2.9E-02
2.6E-02
2.5E-02
2.5E-02
95th
m3/
minute
2.2E-02
2.9E-02
2.9E-02
2.7E-02
2.9E-02
3.4E-02
3.7E-02
3.8E-02
3.7E-02
3.9E-02
4.0E-02
3.4E-02
3.2E-02
3.1E-02
High Intensity
Mean
m3/
minute
2.6E-02
3.8E-02
3.9E-02
3.7E-02
4.2E-02
4.9E-02
4.9E-02
5.0E-02
4.9E-02
5.2E-02
5.3E-02
4.7E-02
4.7E-02
4.8E-02
95th
m3/
minute
4.1E-02
5.2E-02
5.3E-02
4.8E-02
5.9E-02
7.0E-02
7.3E-02
7.6E-02
7.2E-02
7.6E-02
7.8E-02
6.6E-02
6.5E-02
6.8E-02
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Table ES-1. Summary of Exposure Factor Recommendations
Chapter 7
SURFACE
AREA
(continued)
Total Surface Area
Mean
m2
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Adult Males
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
>80 years
Adult Females
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
>80 years
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
2.05
2.10
2.15
2.11
2.08
2.05
1.92
1.81
1.85
1.88
1.89
1.88
1.77
1.69
95th Percentile
m2
0.34
0.38
0.44
0.51
0.61
0.70
0.95
1.48
2.06
2.33
2.52
2.50
2.56
2.55
2.46
2.45
2.22
2.25
2.31
2.36
2.38
2.34
2.13
1.98
Percent Surface Area of Body Parts
Head
Trunk
Arms
Hands
Legs
Feet
Mean Percent of Total Surface Area
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Adult Males >21
Adult Females >21
18.2
18.2
18.2
18.2
16.5
8.4
8.0
6.1
4.6
4.1
6.6
6.2
35.7
35.7
35.7
35.7
35.5
41.0
41.2
39.6
39.6
41.2
40.1
35.4
13.7
13.7
13.7
13.7
13.0
14.4
14.0
14.0
14.3
14.6
15.2
12.8
5.3
5.3
5.3
5.3
5.7
4.7
4.9
4.7
4.5
4.5
5.2
4.8
20.6
20.6
20.6
20.6
23.1
25.3
25.7
28.8
30.4
29.5
33.1
32.3
6.5
6.5
6.5
6.5
6.3
6.3
6.4
6.8
6.6
6.1
6.7
6.6
Surface Area of Body Parts
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Adult Males >21
Adult Females >21
Head
Mean
m2
0.053
0.060
0.069
0.082
0.087
0.051
0.060
0.066
0.073
0.076
0.136
0.114
Trunk
95th
m2
0.062
0.069
0.080
0.093
0.101
0.059
0.076
0.090
0.095
0.096
0.154
0.121
Mean
m2
0.104
0.118
0.136
0.161
0.188
0.250
0.313
0.428
0.630
0.759
0.827
0.654
95th
m2
0.121
0.136
0.157
0.182
0.217
0.287
0.391
0.586
0.816
0.961
1.10
0.850
Mean
m2
0.040
0.045
0.052
0.062
0.069
0.088
0.106
0.151
0.227
0.269
0.314
0.237
Arms
95th
m2
0.047
0.052
0.060
0.070
0.079
0.101
0.133
0.207
0.295
0.340
0.399
0.266
Hands
Mean 95th
m2 m2
0.015 0.018
0.017 0.020
0.020 0.023
0.024 0.027
0.030 0.035
0.028 0.033
0.037 0.046
0.051 0.070
0.072 0.093
0.083 0.105
0.107 0.131
0.089 0.106
Mean
m2
0.060
0.068
0.078
0.093
0.122
0.154
0.195
0.311
0.483
0.543
0.682
0.598
Legs
95th
m2
0.070
0.078
0.091
0.105
0.141
0.177
0.244
0.426
0.626
0.687
0.847
0.764
Feet
Mean
m2
0.019
0.021
0.025
0.029
0.033
0.038
0.049
0.073
0.105
0.112
0.137
0.122
95th
m2
0.022
0.025
0.029
0.033
0.038
0.044
0.061
0.100
0.136
0.142
0.161
0.146
Page
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September 2011
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Exposure Factors Handbook
Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Chapter 7 MEAN SOLID ADEHERENCE TO SKIN (mg/cm2)
Face Arms Hands Legs Feet
Children
Residential (indoors)8
Daycare (indoors and outdoors/1
Outdoor sports'
Indoor sports'1
Activities with soile
Playing in mudf
Playing in sediment8
Adults
Outdoor sports'
Activities with soil11
Construction activities'
-
-
0.012
-
0.054
-
0.040
0.0314
0.0240
0.0982
0.0041
0.024
0.011
0.0019
0.046
11
0.17
0.0872
0.0379
0.1859
0.0011
0.099
0.11
0.0063
0.17
47
0.49
0.1336
0.1595
0.2763
0.0035
0.020
0.031
0.0020
0.051
23
0.70
0.1223
0.0189
0.0660
0.010
0.071
-
0.0022
0.20
15
21
-
0.1393
-
Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to 13 years; N= 10) playing indoors.
Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years; N= 21) playing both
indoors and outdoors.
Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer.
Based on geometric mean soil loadings of 6 children (ages >8 years) and 1 adult engaging in Tae Kwon Do.
Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years).
Based on weighted average of geometric mean soil loadings of 2 groups of children (age 9 to 14 years; N= 12) playing in mud.
Based on geometric mean soil loadings of 9 children (ages 7 to 12 years) playing in tidal flats.
Based on weighted average of geometric mean soil loadings of 3 groups of adults(ages 23 to 33 years) playing rugby and 2 groups of
adults (ages 24 to 34) playing soccer.
Based on weighted average of geometric mean soil loadings for 69 gardeners, farmers, groundskeepers, landscapers, and archeologists
(ages 16 to 64 years) for faces, arms and hands; 65 gardeners, farmers, groundskeepers, and archeologists (ages 16 to 64 years) for
legs; and 36 gardeners, groundskeepers, and archeologists (ages 16 to 62) for feet.
Based on weighted average of geometric mean soil loadings for 27 construction workers, utility workers and equipment operators (ages
21 to 54) for faces, arms, and hands; and based on geometric mean soil loadings for 8 construction workers (ages 21 to 30 years) for
legs.
No data.
Chapter 8 BODY WEIGHT
Mean
Kg
Birth to 1 month 4.8
1 to <3 months 5.9
3 to <6 months 7.4
6 to <12 months 9.2
1 to <2 years 11.4
2 to <3 years 13.8
3 to <6 years 18.6
6to
-------
Exposure Factors Handbook
Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Chapter 9
FRUIT AND VEGETABLE INTAKE
Per Capita
Consumers-Only
Mean
g/kg-day
95th Percentile
g/kg-day
Mean
g/kg-day
95th Percentile
g/kg-day
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
Total Fruits
6.2
7.8
7.8
4.6
2.3
0.9
0.9
0.9
1.4
23.0a
21.3a
21.3a
14.9
8.7
3.5
3.5
3.7
4.4
10.1
8.1
8.1
4.7
2.5
1.1
1.1
1.1
1.5
25. 8a
21.4a
21.4a
15.1
9.2
3.8
3.8
3.8
4.6
Total Vegetables
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
5.0
6.7
6.7
5.4
3.7
2.3
2.3
2.5
2.6
16.2a
15.6a
15.6a
13.4
10.4
5.5
5.5
5.9
6.1
6.8
6.7
6.7
5.4
3.7
2.3
2.3
2.5
2.6
18.1a
15.6a
15.6a
13.4
10.4
5.5
5.5
5.9
6.1
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Chapter 10
FISH INTAKE
Per Capita
Consumers-Only
Mean
g/kg-day
95th Percentile
g/kg-day
Mean
g/kg-day
95th Percentile
g/kg-day
General Population — Finfish
All
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
21 to <50 years
Females 13 to 49 years
>50 years
0.16
0.03
0.22
0.22
0.19
0.16
0.10
0.10
0.15
0.14
0.20
1.1
0.0a
1.2"
1.2a
1.4
1.1
0.7
0.7
1.0
0.9
1.2
0.73
1.3
1.6
1.6
1.3
1.1
0.66
0.66
0.65
0.62
0.68
2.2
2.9a
4.9a
4.9a
3.6a
2.9a
1.7
1.7
2.1
1.8
2.0
General Population — Shellfish
All
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
21 to <50 years
Females 13 to 49 years
>50 years
0.06
0.00
0.04
0.04
0.05
0.05
0.03
0.03
0.08
0.06
0.05
0.4
0.0a
0.0a
0.0a
0.0
0.2
0.0
0.0
0.5
0.3
0.4
0.57
0.42
0.94
0.94
1.0
0.72
0.61
0.61
0.63
0.53
0.41
1.9
2.3a
3.5a
3.5a
2.9a
2.0a
1.9
1.9
2.2
1.8
1.2
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September 2011
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Exposure Factors Handbook
Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
General Population—Total Finfish and Shellfish
All
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
Females 13 to 49 years
>50 years
0.22
0.04
0.26
0.26
0.24
0.21
0.13
0.13
0.23
0.19
0.25
1.3
0.0a
1.6a
1.6a
1.6a
1.4
1.0
1.0
1.3
1.2
1.4
0.78
1.2
1.5
1.5
1.3
0.99
0.69
0.69
0.76
0.68
0.71
2.4
2.9a
5.9a
5.9a
3.6a
2.7a
1.8
1.8
2.5
1.9
2.1
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Recreational Population—Marine Fish—Atlantic
Mean g/day
95th Percentile g/day
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
2.5
2.5
3.4
2.8
5.6
8.6
13
6.6
18
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
Recreational Population—Marine Fish—Gulf
3.2
3.3
4.4
3.5
7.2
13
12
18
9.5
26
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
Recreational Population—Marine Fish—Pacific
0.9
0.9
1.2
1.0
2.0
3.3
3.2
4.8
2.5
Recreational Population—Freshwater Fish—See Chapter 10
Native American Population—See Chapter 10
Other Populations—See Chapter 10
Chapter 11
MEATS, DAIRY PRODUCTS, AND FAT INTAKE
Per Capita
Consumers-Only
Mean
g/kg-day
95th Percentile
g/kg-day
Mean
g/kg-day
95th Percentile
g/kg-day
Total Meats
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
1.2
4.0
4.0
3.9
2.8
2.0
2.0
1.8
1.4
5.4a
10.0a
10.0a
8.5
6.4
4.7
4.7
4.1
3.1
2.7
4.1
4.1
3.9
2.8
2.0
2.0
1.8
1.4
8.1a
10. la
10. r
8.6
6.4
4.7
4.7
4.1
3.1
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
Total Dairy Products
10.1
43.2
43.2
24.0
12.9
5.5
5.5
3.5
3.3
43.2a
94.7a
94.7a
51.1
31.8
16.4
16.4
10.3
9.6
11.7
43.2
43.2
24.0
12.9
5.5
5.5
3.5
3.3
44.7a
94.7a
94.7a
51.1
31.8
16.4
16.4
10.3
9.6
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Total Fats
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to<31 years
31 to <41 years
41 to <51 years
51 to<61 years
61 to<71 years
71 to<81 years
>81 years
5.2
4.5
4.1
3.7
4.0
3.6
3.4
2.6
1.6
1.3
1.2
1.1
1.0
0.9
0.9
0.8
0.9
16
12
8.2
7.0
7.1
6.4
5.8
4.2
3.0
2.7
2.3
2.1
1.9
1.7
1.7
1.5
1.5
7.8
6.0
4.4
3.7
4.0
3.6
3.4
2.6
1.6
1.3
1.2
1.1
1.0
0.9
0.9
0.8
0.9
16
12
8.3
7.0
7.1
6.4
5.8
4.2
3.0
2.7
2.3
2.1
1.9
1.7
1.7
1.5
1.5
a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Chapter 12 GRAINS INTAKE
Per Capita
Consumers-Only
Mean
g/kg-day
95th Percentile
g/kg-day
Mean
g/kg-day
95th Percentile
g/kg-day
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
3.1
6.4
6.4
6.2
4.4
2.4
2.4
2.2
1.7
9.5a
12.4a
12.4a
11.1
8.2
5.0
5.0
4.6
3.5
4.1
6.4
6.4
6.2
4.4
2.4
2.4
2 2
1.7
10.3a
12.4a
12.4a
11.1
8.2
5.0
5.0
4.6
3.5
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Chapter 13
HOME-PRODUCED FOOD INTAKE
Mean
g/kg-day
95th Percentile
g/kg-day
Consumer-Only Home-Produced Fruits, Unadjusted"
1 to 2 years
3 to 5 years
6 to 11 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
8.7
4.1
3.6
1.9
2.0
2.7
2.3
60.6
8.9
15.8
8.3
6.8
13.0
8.7
Consumer-Only Home-Produced Vegetables, Unadjusted8
1 to 2 years
3 to 5 years
6 to 11 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
5.2
2.5
2.0
1.5
1.5
2.1
2.5
19.6
7.7
6.2
6.0
4.9
6.9
8.2
Consumer-Only Home-Produced Meats, Unadjusted"
1 to 2 years
3 to 5 years
6 to 11 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
3.7
3.6
3.7
1.7
1.8
1.7
1.4
10.0
9.1
14.0
4.3
6.2
5.2
3.5
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Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Consumer-Only Home-Caught Fish, Unadjusted"
1 to 2 years
3 to 5 years
6 to 11 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
2.8
1.5
1.9
1.8
1.2
7.1
4.7
4.5
4.4
3.7
Per Capita for Populations that Garden or (Farm)
Home-Produced Fruits
Home-Produced Vegetables
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to<21 years
21 to <50 years
50+ years
Mean
g/kg-day
95th Percentile
g/kg-day
Mean
g/kg-day
95th Percentile
g/kg-day
1.0(1.4)
1.0(1.4)
0.78(1.0)
0.40 (0.52)
0.13(0.17)
0.13(0.17)
0.15 (0.20)
0.24(0.31)
4.8(9.1)
4.8(9.1)
3.6(6.8)
1.9(3.5)
0.62(1.2)
0.62(1.2)
0.70(1.3)
1.1(2.1)
1.3(2.7)
1.3(2.7)
1.1(2.3)
0.80(1.6)
0.56(1.1)
0.56(1.1)
0.56(1.1)
0.60(1.2)
7.1(14)
7.1(14)
6.1(12)
4.2(8.1)
3.0 (5.7)
3.0 (5.7)
3.0 (5.7)
3.2(6.1)
Per Capita for Populations that Farm or (Raise Animals)
Home-Produced Meats
Mean
g/kg-day
95th Percentile
g/kg-day
Home-Produced Dairy
Mean
g/kg-day
95th Percentile
g/kg-day
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
50+ years
1.4(1.4)
1.4(1.4)
1.4(1.4)
1.0(1.0)
0.71 (0.73)
0.71 (0.73)
0.65 (0.66)
0.51(0.52)
5.8 (6.0)
5.8 (6.0)
5.8 (6.0)
4.1 (4.2)
3.0(3.1)
3.0(3.1)
2.7 (2.8)
2.1 (2.2)
11(13)
11(13)
6.7(8.3)
3.9(4.8)
1.6(2.0)
1.6(2.0)
0.95(1.2)
0.92(1.1)
76 (92)
76 (92)
48 (58)
28 (34)
12(14)
12(14)
6.9(8.3)
6.7(8.0)
Not adjusted to account for preparation and post cooking losses.
Adjusted for preparation and post cooking losses.
No data.
Chapter 14
TOTAL PER CAPITA FOOD INTAKE
Birth to 1 year
1 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
>50 years
Mean
g/kg-day
95th Percentile
g/kg-day
91
113
79
47
28
28
29
29
185a
137
92
56
56
63
59
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Chapter 15 HUMAN MILK AND LIPID INTAKE
Mean
Upper Percentile
mlVday
mL/kg-day
mlVday
mI7kg-day
Human Milk Intake
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <12 months
510
690
770
620
150
140
110
83
950
980
1,000
1,000
220
190
150
130
Lipid Intake
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <12 months
20
27
30
25
6.0
5.5
4.2
3.3
38
40
42
42
8.7
8.0
6.1
5.2
Exposure Factors Handbook
September 2011
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Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Chapter 16
ACTIVITY FACTORS
Time Indoors (total)
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <1 2 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
18 to <64 years
>64 years
Birth to 64 years
Mean
1,440
1,432
1,414
1,301
-
1,353
1,316
1,278
1,244
1,260
1,248
1,159
1,142
Mean
15
20
22
17
18
18
20
-
-
minutes/day
95th Percentile
-
-
-
-
-
-
-
-
-
-
-
-
-
Showering
minutes/day
95th Percentile
-
-
44
34
41
40
45
-
-
Playing on Sand/Gravel
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
18 to <64 years
>64 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
1 1 to <16 years
16 to <21 years
18 to <64 years
>64 years
Mean
18
43
53
60
67
67
83
0 (median)
0 (median)
minutes/day
95th Percentile
-
121
121
121
121
121
-
121
-
Mean
96
105
116
137
151
139
145
45(median)
40(median)
Time Outdoors (total)
minutes/day
Mean 95th
0
8
26
139
-
36
76
107
132
100
102
281
298
Bathing
minutes/day
Mean 95th
19
23
23
24
24
25
33
-
-
Playing on Grass
minutes/day
Mean 95th
52
68
62
79
73
75
60
60 (median)
121 (median)
Swimming
minutes/month
Percentile
-
-
-
-
-
-
-
-
-
-
-
-
-
Time Indoors (at residence)
minutes/day
Mean 95th
-
-
-
-
1,108
1,065
979
957
893
889
833
948
1,175
Percentile
-
-
-
-
1,440
1,440
1,296
1,355
1,275
1,315
1,288
1,428
1,440
Bathing/Showering
Percentile
30
32
45
60
46
43
60
-
-
minutes/day
Mean 95th
-
-
-
-
-
-
-
17
17
Percentile
-
-
-
-
-
-
-
-
-
Playing on Dirt
Percentile
-
121
121
121
121
121
-
121
-
minutes/day
Mean 95th
33
56
47
63
63
49
30
0 (median)
0 (median)
95th Percentile
-
-
181
181
181
181
181
181
181
Percentile
-
121
121
121
121
120
-
120
-
Page
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Front Matter
Table ES-1. Summary of Exposure Factor Recommendations (continued)
Occupational Mobility
Median Tenure (years) Median Tenure (years)
Men Women
All ages, >16 years
16 to 24 years
25 to 29 years
30 to 34 years
35 to 3 9 years
40 to 44 years
45 to 49 years
50 to 54 years
55 to 59 years
60 to 64 years
65 to 69 years
>70 years
7.9
2.0
4.6
7.6
10.4
13.8
17.5
20.0
21.9
23.9
26.9
30.5
5.4
1.9
4.1
6.0
7.0
8.0
10.0
10.8
12.4
14.5
15.6
18.8
Population Mobility
Residential Occupancy Period (years) Current Residence Time (years)
Mean
All 12
95th Percentile Mean
33 13
95th Percentile
46
No data.
Chapter 17
Chapter 18
CONSUMER PRODUCTS - See Chapter 17
LIFE EXPECTANCY
Years
Total
Males
Females
Chapter 19
Volume of Residence (m3)
Air Exchange Rate (air changes/hour)
78
75
80
BUILDING CHARACTERISTICS
Residential Buildings
Mean
492
0.45
10th Percentile
154
0.18
Non-Residential Buildings
Volume of Non-residential Buildings (m3)
Vacant
Office
Laboratory
Non-refrigerated warehouse
Food sales
Public order and safety
Outpatient healthcare
Refrigerated warehouse
Religious worship
Public assembly
Education
Food service
Inpatient healthcare
Nursing
Lodging
Strip shopping mall
Enclosed mall
Retail other than mall
Service
Other
All Buildings
Air Exchange Rate (air changes/hour)
Mean (Standard Deviation)
4,789
5,036
24,681
9,298
1,889
5,253
3,537
19,716
3,443
4,839
8,694
1,889
82,034
15,522
11,559
7,891
287,978
3,310
2,213
5,236
5,575
1.5 (0.87)
Range 0.3^.1
10th Percentile
408
510
2,039
1,019
476
816
680
1,133
612
595
527
442
17,330
1,546
527
1,359
35,679
510
459
425
527
0.60
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Front Matter
1. INTRODUCTION -3
1.1. BACKGROUND AND PURPOSE -3
1.2. INTENDED AUDIENCE -3
1.3. SCOPE -3
1.4. UPDATES TO PREVIOUS VERSIONS OF THE HANDBOOK -4
1.5. SELECTION OF STUDIES FOR THE HANDBOOK AND DATA PRESENTATION -4
1.5.1. General Assessment Factors -5
1.5.2. Selection Criteria -5
1.6. APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
FACTORS 1-7
1.7. SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS
HANDBOOK 1-9
1.8. THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE 1-10
1.9. CONSIDERING LIFE STAGE WHEN CALCULATING EXPOSURE AND RISK 1-11
1.10. FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT 1-13
1.10.1. Exposure and Dose Equations 1-15
1.10.2. Use of Exposure Factors Data in Probabilistic Analyses 1-17
1.11. AGGREGATE AND CUMULATIVE EXPOSURES 1-18
1.12. ORGANIZATION OF THE HANDBOOK 1-19
1.13. REFERENCES FOR CHAPTER 1 1-20
APPENDIX 1A RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND
DOSE RESPONSE INFORMATION FROM THE INTEGRATED RISK INFORMATION
SYSTEM (IRIS) 1A-1
Table 1-1. Availability of Various Exposure Metrics in Exposure Factors Data 1-27
Table 1-2. Criteria Used to Rate Confidence in Recommended Values 1-28
Table 1 -3. Age-Dependent Potency Adjustment Factor by Age Group for Mutagenic Carcinogens 1-29
Figure 1-1. Conceptual Drawing of Exposure and Dose Relationship (Zartarian et al., 2007) 1-13
Figure 1-2. Exposure-Dose-Effect Continuum 1-30
Figure 1-3. Schematic Diagram of Exposure Pathways, Factors, and Routes 1-31
Figure 1-4. Road Map to Exposure Factor Recommendations 1-32
Page
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Front Matter
VARIABILITY AND UNCERTAINTY 2-1
2.1. VARIABILITY VERSUS UNCERTAINTY 2-1
2.2. TYPES OF VARIABILITY 2-2
2.3. ADDRESSING VARIABILITY 2-2
2.4. TYPES OF UNCERTAINTY 2-3
2.5. REDUCING UNCERTAINTY 2-4
2.6. ANALYZING VARIABILITY AND UNCERTAINTY 2-4
2.7. LITERATURE REVIEW OF VARIABILITY AND UNCERTAINTY ANALYSIS 2-5
2.8. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSES 2-7
2.9. REFERENCES FOR CHAPTER 2 2-8
Exposure Factors Handbook Page
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Exposure Factors Handbook
Front Matter
3. INGESTION OF WATER AND OTHER SELECT LIQUIDS 3-1
3.1. INTRODUCTION 3-1
3.2. RECOMMENDATIONS 3-2
3.2.1. Water Ingestion from Consumption of Water as a Beverage and from Food and
Drink 3-2
3.2.2. Pregnant and Lactating Women 3-2
3.2.3. Water Ingestion While Swimming or Diving 3-2
3.3. DRINKING WATER INGESTION STUDIES 3-9
3.3.1. Key Drinking Water Ingestion Study 3-9
3.3.1.1. KahnandStralka(2008a) 3-9
3.3.1.2. U.S. EPA Analysis of NHANES 2003-2006 Data 3-10
3.3.2. Relevant Drinking Water Ingestion Studies 3-11
3.3.2.1. Wolf (1958) 3-11
3.3.2.2. National Research Council (1977) 3-11
3.3.2.3. Hopkins and Ellis (1980) 3-12
3.3.2.4. Canadian Ministry of National Health and Welfare (1981) 3-12
3.3.2.5. Gillies and Paulin (1983) 3-13
3.3.2.6. Pennington(1983) 3-13
3.3.2.7. U.S. EPA(1984) 3-14
3.3.2.8. Cantor etal. (1987) 3-14
3.3.2.9. Ershow and Cantor (1989) 3-15
3.3.2.10.RoseberryandBurmaster(1992) 3-15
3.3.2.11.Levy etal. (1995) 3-16
3.3.2.12.USDA(1995) 3-16
3.3.2.13.U.S. EPA (1996) 3-17
3.3.2.14. Heller etal. (2000) 3-17
3.3.2.15.Sichert-Hellertetal. (2001) 3-18
3.3.2.16.Sohnetal. (2001) 3-18
3.3.2.17.Hilbigetal. (2002) 3-19
3.3.2.18.Marshalletal. (2003a) 3-19
3.3.2.19.Marshalletal. (2003b) 3-20
3.3.2.20. Skinner etal. (2004) 3-20
3.4. PREGNANT AND LACTATING WOMEN 3-21
3.4.1. Key Study on Pregnant and Lactating Women 3-21
3.4.1.1. KahnandStralka(2008b) 3-21
3.4.2. Relevant Studies on Pregnant and Lactating Women 3-21
3.4.2.1. Ershow etal. (1991) 3-21
3.4.2.2. Forssenetal. (2007) 3-22
3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES 3-22
3.5.1. Relevant Studies on High Activity Levels/Hot Climates 3-22
3.5.1.1. McNall and Schlegel (1968) 3-22
3.5.1.2. U.S. Army (1983) 3-23
3.6. WATER INGESTION WHILE SWIMMING AND DIVING 3-23
3.6.1. Key Study on Water Ingestion While Swimming 3-23
3.6.1.1. Dufour et al. (2006) 3-23
3.6.2. Relevant Studies on Water Ingestion While Swimming, Diving, or Engaging in
Recreational Water Activities 3-24
3.6.2.1. Schijvenand de RodaHusman (2006) 3-24
3.6.2.2. Schets etal. (2011) 3-24
3.6.2.3. Dorevitchetal. (2011) 3-25
3.7. REFERENCES FOR CHAPTER 3 3-25
Table 3-1. Recommended Values for Drinking Water Ingestion Rates 3-3
Page Exposure Factors Handbook
xxvi September 2011
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Front Matter
Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates
Table 3-3. Recommended Values for Water Ingestion Rates of Community Water for Pregnant and
Lactating Women
Table 3-4. Confidence in Recommendations for Water Ingestion for Pregnant/Lactating Women
Table 3-5. Recommended Values for Water Ingestion While Swimming
Table 3-6. Confidence in Recommendations for Water Ingestion While Swimming
Table 3-7. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Community Water (mL/day)
Table 3-8. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Bottled Water (mL/day)
Table 3-9. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Other Sources (mL/day)
Table 3-10. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: All Sources (mL/day)
Table 3-11. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Community Water (mL/kg-day)
Table 3-12. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Bottled Water (mL/kg-day)
Table 3-13. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: Other Sources (mL/kg-day)
Table 3-14. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 1994
1996, 1998 CSFII: All Sources (mL/kg-day)
Table 3-15. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/day)
Table 3-16. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/day)
Table 3-17. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/day)
Table 3-18. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/day)
Table 3-19. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Community Water (mL/kg-day)
Table 3-20. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Bottled Water (mL/kg-day)
Table 3-21. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Other Sources (mL/kg-day)
Table 3-22. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: All Sources (mL/kg-day)
Table 3-23. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day)
Table 3-24. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES
2003-2006: Bottled Water (mL/day)
Table 3-25. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day)
Table 3-26. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day)
Table 3-27. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/day)
Table 3-28. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/kg-day)
Table 3-29. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES
2003-2006: Bottled Water (mL/kg-day)
Table 3-30. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/kg-day)
3-4
3-5
3-6
3-7
3-8
.3-28
.3-29
.3-30
.3-31
.3-32
.3-33
.3-34
.3-35
.3-36
.3-37
.3-38
.3-39
.3-40
.3-41
.3-42
.3-43
.3-44
.3-45
.3-46
.3-47
....3-48
....3-49
....3-50
....3-51
Exposure Factors Handbook
September 2011
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Front Matter
Table 3-31. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/kg-day) 3-52
Table 3-32. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/kg-day) 3-53
Table 3-33. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day) 3-54
Table 3-34. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Bottled Water (mL/day) 3-55
Table 3-35. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day) 3-56
Table 3-36. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day) 3-57
Table 3-37. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/day) 3-58
Table 3-38. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: Community Water (mL/kg-day) 3-59
Table 3-39. Consumers-Only Estimates of Direct Water Ingestion Based on NHANES 2003-2006:
Bottled Water (mL/kg-day) 3-60
Table 3-40. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: Other Sources (mL/kg-day) 3-61
Table 3-41. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: All Sources (mL/kg-day) 3-62
Table 3-42. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th
Percentiles: All Sources (mL/kg-day) 3-63
Table 3-43. Assumed Tap Water Content of Beverages in Great Britain 3-64
Table 3-44. Intake of Total Liquid, Total Tap Water, and Various Beverages (L/day) by the British
Population 3-65
Table 3-45. Summary of Total Liquid and Total Tap Water Intake for Males and Females (L/day) in
Great Britain 3-66
Table 3-46. Daily Total Tap Water Intake Distribution for Canadians, by Age Group (Approx. 0.20-L
increments, both sexes, combined seasons) 3-67
Table 3-47. Average Daily Tap Water Intake of Canadians (expressed as mL/kg body weight) 3-68
Table 3-48. Average Daily Total Tap Water Intake of Canadians, by Age and Season (L/day) 3-68
Table 3-49. Average Daily Total Tap Water Intake of Canadians as a Function of Level of Physical
Activity at Work and in Spare Time (16 years and older, combined seasons, L/day) 3-69
Table 3-50. Average Daily Tap Water Intake by Canadians, Apportioned Among Various Beverages
(Both sexes, by age, combined seasons, L/day) 3-69
Table 3-51. Intake Rates of Total Fluids and Total Tap Water by Age Group 3-70
Table 3-52. Mean and Standard Error for the Daily Intake of Beverages and Tap Water by Age 3-70
Table 3-53. Average Total Tap Water Intake Rate by Sex, Age, and Geographic Area 3-71
Table 3-54. Frequency Distribution of Total Tap Water Intake Rates 3-71
Table 3-55. Total Tap Water Intake (mL/day) for Both Sexes Combined 3-72
Table 3-56. Total Tap Water Intake (mL/kg-day) for Both Sexes Combined 3-73
Table 3-57. Summary of Tap Water Intake by Age 3-74
Table 3-58. Total Tap Water Intake (as %of total water intake) by Broad Age Category 3-74
Table 3-59. General Dietary Sources of Tap Water for Both Sexes 3-75
Table 3-60. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates 3-76
Table 3-61. Estimated Quantiles and Means for Total Tap Water Intake Rates (mL/day) 3-76
Table 3-62 . Water Ingested (mL/day) from Water by Itself and Water Added to Other Beverages and
Foods 3-77
Table 3-63. Mean Per Capita Drinking Water Intake Based on USD A, CSFII Data From 1989-1991
(mL/day) 3-78
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Table 3-64. Number of Respondents that Consumed Tap Water at a Specified Daily Frequency 3-79
Table 3-65. Number of Respondents that Consumed Juice Reconstituted with Tap Water at a
Specified Daily Frequency 3-80
Table 3-66. Mean and (standard error) Water and Drink Consumption (mL/kg-day) by Race/Ethnicity 3-81
Table 3-67. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and
Poverty Category 3-82
Table 3-68. Intake of Water from Various Sources in 2-to 13-Year-Old Participants of the DONALD
Study, 1985 1999 3-83
Table 3-69. Mean (±standard error) Fluid Intake (mL/kg-day) by Children Aged 1 to 10 years,
NHANESIII, 1988-1994 3-83
Table 3-70. Estimated Mean (±standard error) Amount of Total Fluid and Plain Water Intake Among
Children Aged 1 to 10 Years by Age, Sex, Race/Ethnicity, Poverty Income Ratio,
Region, and Urbanicity (NHANESIII, 1988-1994) 3-84
Table 3-71. Tap Water Intake in Breast-Fed and Formula-Fed Infants and Mixed-Fed Young Children
at Different Age Points 3-85
Table 3-72. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes
(mL/day) for Children with Returned Questionnaires 3-86
Table 3-73. Mean (±standard deviation) Daily Beverage Intakes Reported on Beverage Frequency
Questionnaire and 3-Day Food and Beverage Diaries 3-87
Table 3-74. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) 3-88
Table 3-75. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-89
Table 3-76. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-90
Table 3-77. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-90
Table 3-78. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-91
Table 3-79. Estimates of Consumers Only Direct and Indirect Water Intake from All Sources by
Pregnant, Lactating, and Childbearing Age Women (mL/kg-day) 3-91
Table 3-80. Estimates of Consumers-Only Direct and Indirect Water Intake from All Sources by
Pregnant, Lactating, and Childbearing Age Women (mL/day) 3-92
Table 3-81. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-92
Table 3-82. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-93
Table 3-83. Total Fluid Intake of Women 15 to 49 Years Old 3-93
Table 3-84. Total Tap Water Intake of Women 15 to 49 Years Old 3-94
Table 3-85. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15 to
49 Years 3-94
Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women (L/day) 3-95
Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water by
Pregnant Women 3-97
Table 3-88. Water Intake at Various Activity Levels (L/hour) 3-99
Table 3-89. Planning Factors for Individual Tap Water Consumption 3-99
Table 3-90. Pool Water Ingestion by Swimmers 3-100
Table 3-91. Arithmetic Mean (Maximum) Number of Dives per Diver and Volume of Water Ingested
(mL/dive) 3-100
Table 3-92. Exposure Parameters for Swimmers in Swimming Pools, Freshwater, and Seawater 3-101
Table 3-93. Estimated Water Ingestion During Water Recreation Activities (mL/hr) 3-101
Exposure Factors Handbook
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4. NON-DIETARY INGESTION FACTORS 4-1
4.1. INTRODUCTION 4-1
4.2. RECOMMENDATIONS 4-2
4.3. NON-DIETARY INGESTION—MOUTHING FREQUENCY STUDIES 4-5
4.3.1. Key Studies of Mouthing Frequency 4-5
4.3.1.1. Zartarianet al. (1997a)/Zartarianetal. (1997b)/Zartarianetal. (1998) 4-5
4.3.1.2. Reed etal. (1999) 4-5
4.3.1.3. Freeman etal. (2001) 4-6
4.3.1.4. Tulve et al. (2002) 4-6
4.3.1.5. AuYeung et al. (2004) 4-7
4.3.1.6. Black et al. (2005) 4-7
4.3.1.7. Xue et al. (2007) 4-8
4.3.1.8. Beamer et al. (2008) 4-9
4.3.1.9. Xue etal. (2010) 4-9
4.3.2. Relevant Studies of Mouthing Frequency 4-10
4.3.2.1. Davis etal. (1995) 4-10
4.3.2.2. Lew and Butterworth( 1997) 4-11
4.3.2.3. Tudella et al. (2000) 4-11
4.3.2.4. Ko et al. (2007) 4-11
4.3.2.5. Nicas and Best (2008) 4-12
4.4. NON-DIETARY INGESTION—MOUTHING DURATION STUDIES 4-12
4.4.1. Key Mouthing Duration Studies 4-12
4.4.1.1. Jubergetal. (2001) 4-12
4.4.1.2. Greene (2002) 4-13
4.4.1.3. Beamer et al. (2008) 4-14
4.4.2. Relevant Mouthing Duration Studies 4-14
4.4.2.1. Barretal. (1994) 4-14
4.4.2.2. Zartarian et al. (1997a)/Zartarianetal. (1997b)/Zartarianetal. (1998) 4-15
4.4.2.3. Grootetal. (1998) 4-15
4.4.2.4. Smith and Norris (2003)/Norris and Smith (2002) 4-16
4.4.2.5. AuYeung et al. (2004) 4-17
4.5. MOUTHING PREVALENCE STUDIES 4-17
4.5.1. Staneketal. (1998) 4-17
4.5.2. Warren etal. (2000) 4-18
4.6. REFERENCES FOR CHAPTER 4 4-18
Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration 4-3
Table 4-2. Confidence in Mouthing Frequency and Duration Recommendations 4-4
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-Transcription 4-21
Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age 4-21
Table 4-5. Video-Transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
(contacts/hour), by Age 4-21
Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour) 4-22
Table 4-7. Indoor Mouthing Frequency (Contacts per contacts/hour), Video-Transcription of
9 Children by Age 4-23
Table 4-8. Outdoor Mouthing Frequency (Contacts per contacts/hour), Video-Transcription of
38 Children, by Age 4-23
Table 4-9. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD), by
Age 4-24
Table 4-10. Indoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-24
Table 4-11. Outdoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-24
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Table 4-12. Object/Surface to Mouth Contact Frequency for Infants and Toddlers (events/hour) 4-25
Table 4-13. Distributions Mouthing Frequency and Duration for Non-Dietary Objects with
Significant Differences (p < 0.05) Between Infants and Toddlers 4-26
Table 4-14. Indoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-27
Table 4-15. Outdoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-27
Table 4-16. Survey-Reported Mouthing Behaviors for 92 Washington State Children 4-28
Table 4-17. Number of Hand Contacts Observed in Adults During a Continuous 3-Hour Period 4-28
Table 4-18. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
Other Objects 4-29
Table 4-19. Percent of Houston-Area and Chicago-Area Children Observed Mouthing, by Category
and Child's Age 4-29
Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers
(minutes/hour), by Age 4-30
Table 4-21. Object/Surface to Hands and Mouth Contact Duration for Infants and Toddlers
(minutes/hour) (N = 23) 4-31
Table 4-22. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without
Pacifier (minutes/day), by Age 4-31
Table 4-23. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys,
and Other Objects (hours:minutes:seconds) 4-31
Table 4-24. Outdoor Median Mouthing Duration (seconds/contact), Video-Transcription of
38 Children, by Age 4-31
Table 4-25. Indoor Mouthing Duration (minutes/hour), Video-Transcription of Nine Children with
>15 minutes in View Indoors 4-31
Table 4-26. Outdoor Mouthing Duration (minutes/hour), Video-Transcription of 38 Children, by Age 4-31
Table 4-27. Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
Behaviors 4-31
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5. SOIL AND DUST INGESTION 5-1
5.1. INTRODUCTION 5-1
5.2. RECOMMENDATIONS 5-3
5.3. KEY AND RELEVANT STUDIES 5-7
5.3.1. Methodologies Used in Key Studies 5-7
5.3.1.1. Tracer Element Methodology 5-7
5.3.1.2. Biokinetic Model Comparison Methodology 5-8
5.3.1.3. Activity Pattern Methodology 5-8
5.3.2. Key Studies of Primary Analysis 5-9
5.3.2.1. Vermeer and Frate (1979) 5-9
5.3.2.2. Calabrese et al. (1989)/Barnes (1990)/Calabrese et al. (1991) 5-9
5.3.2.3. Van Wijnenetal. (1990 5-10
5.3.2.4. Davis etal. (1990) 5-10
5.3.2.5. Calabrese etal. (1997a) 5-11
5.3.2.6. Stanek et al. (1998) /Calabrese et al. (1997b) 5-12
5.3.2.7. Davis and Mirick (2006) 5-12
5.3.3. Key Studies of Secondary Analysis 5-13
5.3.3.1. Wong (1988)/Calabrese and Stanek (1993) 5-13
5.3.3.2. Calabrese and Stanek (1995) 5-14
5.3.3.3. Stanek and Calabrese (1995a) 5-14
5.3.3.4. Hoganetal. (1998) 5-15
5.3.3.5. Ozkaynaketal. (2010) 5-16
5.3.4. Relevant Studies of Primary Analysis 5-16
5.3.4.1. Dickins and Ford (1942) 5-17
5.3.4.2. Ferguson and Keaton( 1950) 5-17
5.3.4.3. Cooper (1957) 5-17
5.3.4.4. Barltrop (1966) 5-17
5.3.4.5. Bruhnand Pangborn (1971) 5-17
5.3.4.6. Robischon(1971) 5-18
5.3.4.7. Bronstein and Dollar (1974) 5-18
5.3.4.8. Hook (1978) 5-18
5.3.4.9. Binder etal. (1986) 5-18
5.3.4.10.Clausingetal. (1987) 5-19
5.3.4.11.Calabrese etal. (1990) 5-20
5.3.4.12.Cooksey(1995) 5-20
5.3.4.13.Smulianetal. (1995) 5-20
5.3.4.14.Grigsby etal. (1999) 5-21
5.3.4.15. Ward and Kutner (1999) 5-21
5.3.4.16. Simpson etal. (2000) 5-21
5.3.4.17.Obialo etal. (2001) 5-22
5.3.4.18.Klitzmanetal. (2002) 5-22
5.3.5. Relevant Studies of Secondary Analysis 5-22
5.3.5.1. Stanek and Calabrese (1995b) 5-22
5.3.5.2. Calabrese and Stanek (1992b) 5-23
5.3.5.3. Calabrese etal. (1996) 5-23
5.3.5.4. Stanek etal. (1999) 5-23
5.3.5.5. Stanek and Calabrese (2000) 5-23
5.3.5.6. Stanek etal. (200 la) 5-23
5.3.5.7. Stanek etal. (200 Ib) 5-24
5.3.5.8. Von Lindern et al. (2003) 5-24
5.3.5.9. Gavrelis etal. (2011) 5-24
5.4. LIMITATIONS OF STUDY METHODOLOGIES 5-25
5.4.1. Tracer Element Methodology 5-25
5.4.2. Biokinetic Model Comparison Methodology 5-28
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5.4.3. Activity Pattern Methodology 5-28
5.4.4. Key Studies: Representativeness of U.S. Population 5-29
5.5. SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES 5-31
5.6. DERIVATION OF RECOMMENDED SOIL AND DUST INGESTION VALUES 5-31
5.6.1. Central Tendency Soil and Dust Ingestion Recommendations 5-31
5.6.2. Upper Percentile, Soil Pica, and Geophagy Recommendations 5-33
5.7. REFERENCES FOR CHAPTER 5 5-34
Table 5-1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion (mg/day) 5-5
Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust 5-6
Table 5-3. Soil, Dust, and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
Children 5-39
Table 5-4. Amherst, Massachusetts Soil-Pica Child's Daily Ingestion Estimates by Tracer and by
Week (mg/day) 5-40
Table 5-5. Van Wijnen et al. (1990) Limiting Tracer Method (LTM) Soil Ingestion Estimates for
Sample of Dutch Children 5-40
Table 5-6. Estimated Geometric Mean Limiting Tracer Method (LTM) Soil Ingestion Values of
Children Attending Daycare Centers According to Age, Weather Category, and Sampling
Period 5-41
Table 5-7. Estimated Soil Ingestion for Sample of Washington State Children 5-41
Table 5-8. Soil Ingestion Estimates for 64 Anaconda Children 5-42
Table 5-9. Soil Ingestion Estimates for Massachusetts Children Displaying Soil Pica Behavior
(mg/day) 5-42
Table 5-10. Average Daily Soil and Dust Ingestion Estimate (mg/day) 5-43
Table 5-11. Mean and Median Soil Ingestion (mg/day) by Family Member 5-43
Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children 5-44
Table 5-13. Positive/Negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
Study: Effect on Mean Soil Ingestion Estimate (mg/day) 5-44
Table 5-14. Predicted Soil and Dust Ingestion Rates for Children Age 3 to <6 Years (mg/day) 5-45
Table 5-15. Estimated Daily Soil Ingestion for East Helena, Montana Children 5-45
Table 5-16. Estimated Soil Ingestion for Sample of Dutch Nursery School Children 5-46
Table 5-17. Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children 5-46
Table 5-18. Items Ingested by Low-Income Mexican-Born Women Who Practiced Pica During
Pregnancy in the United States (N = 46) 5-47
Table 5-19. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children
(mg/day) 5-47
Table 5-20. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for
64 Subjects Projected over 365 Days 5-48
Table 5-21. Prevalence of Non-Food Consumption by Substance for NHANES I and NHANES II 5-48
Table 5-22. Summary of Estimates of Soil and Dust Ingestion by Adults and Children (0.5 to 14 years
old) from Key Studies (mg/day) 5-49
Table 5-23. Comparison of Hogan et al. (1998) Study Subjects' Predicted Blood Lead Levels with
Actual Measured Blood Lead Levels, and Default Soil + Dust Intakes Used in IEUBK
Modeling 5-49
Figure 5-1. Prevalence of Non-Food Substance Consumption by Age, NHANES I and NHANES II 5-50
Figure 5-2. Prevalence of Non-Food Substance Consumption by Race, NHANES I and NHANES II 5-51
Figure 5-3. Prevalence of Non-Food Substance Consumption by Income, NHANES I and NHANES
II 5-52
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6. INHALATION RATES 6-1
6.1. INTRODUCTION 6-1
6.2. RECOMMENDATIONS 6-2
6.3. KEY INHALATION RATE STUDIES 6-7
6.3.1. Brochu et al. (2006a) 6-7
6.3.2. Arcus Arth and Blaisdell (2007) 6-7
6.3.3. Stifelman (2007) 6-9
6.3.4. U.S. EPA (2009) 6-9
6.3.5. Key Studies Combined 6-10
6.4. RELEVANT INHALATION RATE STUDIES 6-10
6.4.1. International Commission on Radiological Protection (ICRP) (1981) 6-10
6.4.2. U.S. EPA (1985) 6-11
6.4.3. Shamooetal. (1990) 6-11
6.4.4. Shamooetal. (1991) 6-12
6.4.5. Linn etal. (1992) 6-13
6.4.6. Shamooetal. (1992) 6-14
6.4.7. Spier etal. (1992) 6-14
6.4.8. Adams (1993) 6-15
6.4.9. Layton(1993) 6-16
6.4.10. Linn etal. (1993) 6-17
6.4.11. Rusconietal. (1994) 6-18
6.4.12. Price et al. (2003) 6-19
6.4.13. Brochu et al. (2006b) 6-19
6.4.14. Allan et al. (2009) 6-20
6.5. REFERENCES FOR CHAPTER 6 6-21
Table 6-1. Recommended Long Term Exposure Values for Inhalation (Males and Females
Combined) 6-1
Table 6-2. Recommended Short Term Exposure Values for Inhalation (Males and Females
Combined) 6-4
Table 6-3. Confidence in Recommendations for Long and Short Term Inhalation Rates 6-6
Table 6-4. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (nrYday) for
Free Living Normal Weight Males and Females Aged 2.6 Months to 96 Years 6-24
Table 6-5. Mean and 95th Percentile Inhalation Rate Values (nrYday) for Free Living Normal Weight
Males, Females, and Males and Females Combined 6-25
Table 6-6. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/day) for
Free Living Normal Weight and Overweight/Obese Males and Females Aged 4 to
96 Years 6-27
Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) per Unit of
Body Weight (nrVkg day) for Free Living Normal Weight Males and Females Aged
2.6 Months to 96 Years 6-28
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/kg day) for
Free Living Normal Weight and Overweight/Obese Males and Females Aged 4 to
96 Years 6-29
Table 6-9. Physiological Daily Inhalation Rates (PDIRs) for Newborns Aged 1 Month or Less 6-30
Table 6-10. Non-Normalized Daily Inhalation Rates (m3/day) Derived Using Layton's (1993) Method
and CSFII Energy Intake Data 6-31
Table 6-11. Mean and 95th Percentile Inhalation Rate Values (nrVday) for Males and Females
Combined 6-32
Table 6-12. Summary of Institute of Medicine (IOM) Energy Expenditure Recommendations for
Active and Very Active People with Equivalent Inhalation Rates 6-33
Table 6-13. Mean Inhalation Rate Values (nrVday) for Males, Females, and Males and Females
Combined 6-34
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Table 6-14. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category 6-35
Table 6-15. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category 6-36
Table 6-16. Mean and 95th Percentile Inhalation Rate Values (nrVday) for Males, Females, and Males
and Females Combined 6-37
Table 6-17. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Males by Age
Category 6-39
Table 6-18. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Males by Age
Category 6-43
Table 6-19. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Females by Age
Category 6-47
Table 6-20. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Females by Age
Category 6-48
Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
Within the Specified Activity Category, by Age for Males 6-48
Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
Within the Specified Activity Category, by Age for Females 6-48
Table 6-23. Mean Inhalation Rate Values (m3/day) from Key Studies for Males and Females
Combined 6-48
Table 6-24. 95th Percentile Inhalation Rate Values (m3/day) from Key Studies for Males and Females
Combined 6-48
Table 6-25. Concordance of Age Groupings Among Key Studies 6-48
Table 6-26. Time Weighted Average of Daily Inhalation Rates (DIRs) Estimated from Daily
Activities 6-48
Table 6-27. Selected Inhalation Rate Values During Different Activity Levels Obtained from Various
Literature Sources 6-48
Table 6-28. Summary of Human Inhalation Rates by Activity Level (m3/hour) 6-48
Table 6-29. Estimated Minute Ventilation Associated with Activity Level for Average Male Adult 6-48
Table 6-30. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for All
Age Groups 6-48
Table 6-31. Summary of Daily Inhalation Rates (DIRs) Grouped by Age and Activity Level 6-48
Table 6-32. Distribution Pattern of Predicted Ventilation Rate (VR) and Equivalent Ventilation Rate
(EVR) for 20 Outdoor Workers 6-48
Table 6-3 3. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor
Workers 6-48
Table 6-34. Calibration and Field Protocols for Self Monitoring of Activities Grouped by Subject
Panels 6-48
Table 6-35. Subject Panel Inhalation Rates by Mean Ventilation Rate (VR), Upper Percentiles, and
Self Estimated Breathing Rates 6-48
Table 6-36. Actual Inhalation Rates Measured at Four Ventilation Levels 6-48
Table 6-37. Distribution of Predicted Inhalation Rates by Location and Activity Levels for
Elementary and High School Students 6-48
Table 6-38. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary
and High School Students 6-48
Table 6-39. Distribution Patterns of Daily Inhalation Rates (DIRs) for Elementary (EL) and High
School (HS) Students Grouped by Activity Level 6-48
Table 6-40. Mean Minute Inhalation Rate (nfYminute) by Group and Activity for Laboratory
Protocols 6-48
Table 6-41. Mean Minute Inhalation Rate (nrVminute) by Group and Activity for Field Protocols 6-48
Table 6-42. Summary of Average Inhalation Rates (nrVhour) by Age Group and Activity Levels for
Laboratory Protocols 6-48
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Table 6-43. Summary of Average Inhalation Rates (m3/hour) by Age Group And Activity Levels in
Field Protocols 6-48
Table 6-44. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food Energy
Intakes (EFDs) for Individuals Sampled in the 1977-1978 NFCS 6-48
Table 6-45. Daily Inhalation Rates (DIRs) Calculated from Food Energy Intakes (EFDs) 6-48
Table 6-46. Statistics of the Age/Sex Cohorts Used to Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR) 6-48
Table 6-47. Daily Inhalation Rates (DIRs) Obtained from the Ratios of Total Energy Expenditure to
Basal Metabolic Rate (BMR) 6-48
Table 6-48. Daily Inhalation Rates (DIRs) Based on Time Activity Survey 6-48
Table 6-49. Inhalation Rates for Short Term Exposures 6-48
Table 6-50. Distributions of Individual and Group Inhalation/Ventilation Rate (VR) for Outdoor
Workers 6-48
Table 6-51. Individual Mean Inhalation Rate (m3/hour) by Self Estimated Breathing Rate or Job
Activity Category for Outdoor Workers 6-48
Table 6-52. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in
618 Infants and Children Grouped in Classes of Age 6-48
Table 6-53. Distribution of Physiological Daily Inhalation Rate (PDIR) (nrVday) Percentiles for Free
Living Underweight Adolescents and Women Aged 11 to 55 Years During Pregnancy
and Postpartum Weeks 6-48
Table 6-54. Distribution of Physiological Daily Inhalation Rate (PDIR) (nrYday) Percentiles for Free
Living Normal Weight Adolescents and Women Aged 11 to 55 Years During Pregnancy
and Postpartum Weeks 6-48
Table 6-55. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/day) Percentiles for Free
Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years During
Pregnancy and Postpartum Weeks 6-48
Table 6-56. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg day) Percentiles for
Free Living Underweight Adolescents and Women Aged 11 to 55 Years During
Pregnancy and Postpartum Weeks 6-48
Table 6-57. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg day) Percentiles for
Free Living Normal Weight and Women Aged 11 to 55 Years During Pregnancy and
Postpartum Weeks 6-48
Table 6-58. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg day) Percentiles for
Free Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years During
Pregnancy and Postpartum Weeks 6-48
Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centilesby Age in Awake Subjects 6-48
Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Asleep Subjects 6-48
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1. DERMAL EXPOSURE FACTORS 7-1
7.1. INTRODUCTION 7-1
7.2. RECOMMENDATIONS 7-2
7.2.1. Body Surface Area 7-2
7.2.2. Adherence of Solids to Skin 7-3
7.2.3. Film Thickness of Liquids on Skin 7-4
7.2.4. Residue Transfer 7-4
7.3. SURFACE AREA 7-13
7.3.1. Key Body Surface Area Studies 7-13
7.3.1.1. U.S. EPA (1985) 7-13
7.3.1.2. Boniol et al. (2007) 7-13
7.3.1.3. U.S. EPAAnalysis of NHANES 2005-2006 and 1999-2006 Data 7-14
7.3.2. Relevant Body Surface Area Studies 7-15
7.3.2.1. Murray and Burmaster( 1992) 7-15
7.3.2.2. Phillips etal. (1993) 7-15
7.3.2.3. Garlocketal. (1999) 7-16
7.3.2.4. Wong et al. (2000) 7-16
7.3.2.5. AuYeung et al. (2008) 7-16
7.4. ADHERENCE OF SOLIDS TO SKIN 7-17
7.4.1. Key Adherence of Solids to Skin Studies 7-17
7.4.1.1. Kissel etal. (1996a) 7-17
7.4.1.2. Holmes etal. (1999) 7-17
7.4.1.3. Shoaf etal. (2005) 7-18
7.4.2. Relevant Adherence of Solids to Skin Studies 7-18
7.4.2.1. Harger(1979) 7-18
7.4.2.2. QueHee etal. (1985) 7-19
7.4.2.3. Driver etal. (1989) 7-19
7.4.2.4. Sedman(1989) 7-19
7.4.2.5. Finley etal. (1994) 7-20
7.4.2.6. Kissel etal. (1996b) 7-20
7.4.2.7. Holmes etal. (1996) 7-20
7.4.2.8. Kissel etal. (1998) 7-21
7.4.2.9. Rodesetal. (2001) 7-21
7.4.2.10.Edwards and Lioy (2001) 7-22
7.4.2.ll.Choate etal. (2006) 7-22
7.4.2.12.Yamamoto etal. (2006) 7-23
7.4.2.13.Ferguson etal. (2008, 2009a,b,c) 7-23
7.5. FILM THICKNESS OF LIQUIDS ON SKIN 7-24
7.5.1. U.S. EPA(1987)/U.S. EPA(1992c) 7-24
7.6. RESIDUE TRANSFER 7-24
7.6.1. Residue Transfer Studies 7-25
7.6.1.1. Ross etal. (1990) 7-25
7.6.1.2. Ross etal. (1991) 7-26
7.6.1.3. Formoli (1996) 7-26
7.6.
7.6.
7.6.
7.6.
7.6.
7.6.
.4. Krieger et al. (2000) 7-26
.5. Clothier (2000) 7-27
.6. Bernard etal. (2001) 7-27
.7. Cohen-Hubal et al. (2005) 7-28
.8. Cohen-Hubal et al. (2008) 7-28
.9. Beameretal. (2009) 7-28
7.7. OTHER FACTORS 7-29
7.7.1. Frequency and Duration of Dermal (Hand) Contact 7-29
7.7.1.1. Zartarianetal. (1997) 7-29
7.7.1.2. Reed etal. (1999) 7-29
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7.7.1.3. Freemanetal. (2001) 7-29
7.7.1.4. Freeman et al. (2005) 7-30
7.7.1.5. AuYeung et al. (2006) 7-30
7.7.1.6. Ko et al. (2007) 7-30
7.7.1.7. Beamer et al. (2008) 7-31
7.7.2. Thickness of the Skin 7-31
7.8. REFERENCES FOR CHAPTER 7 7-32
APPENDIX 7A FORMULAS FOR TOTAL BODY SURFACE AREA 7A-1
Table 7-1. Recommended Values for Total Body Surface Area, For Children (Sexes Combined) and
Adults by Sex 7-5
Table 7-2. Recommended Values for Surface Area of Body Parts 7-6
Table 7-3. Confidence in Recommendations for Body Surface Area 7-8
Table 7-4. Recommended Values for Mean Solids Adherence to Skin 7-10
Table 7-5. Confidence in Recommendations for Solids Adherence to Skin 7-11
Table 7-6. Percentage of Total Body Surface Area by Body Part for Children (sexes combined) and
Adults by Sex 7-37
Table 7-7. Summary of Equation Parameters for Calculating Adult Body Surface Area 7-38
Table 7-8. Mean Proportion (%) of Children's Total Skin Surface Area, by Body Part 7-39
Table 7-9. Mean and Percentile Skin Surface Area (m2) 7-40
Table 7-10. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of
NHANES 1999-2006 for Children <21 Years and NHANES 2005-2006 for Adults
>21 Years, Male 7-41
Table 7-11. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of
NHANES 1999-2006 for Children <21 Years and NHANES 2005-2006 for Adults
>21 Years, Female 7-42
Table 7-12. Surface Area of Adult Male (21 years and older) in Square Meters 7-43
Table 7-13. Surface Area of Adult Females (21 years and older) in Square Meters 7-44
Table 7-14. Statistical Results for Total Body Surface Area Distributions (m2), for Adults 7-45
Table 7-15. Descriptive Statistics for Surface Area/Body Weight (SA/BW) Ratios (m2/kg) 7-46
Table 7-16. Estimated Percent of Adult Skin Surface Exposed During Outdoor Activities 7-47
Table 7-17. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 7-47
Table 7-18. Median Per Contact Outdoor Fractional Surface Areas of the Hands, by Object, Both
Hands Combined 7-48
Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates 7-49
Table 7-20. Geometric Mean and Geometric Standard Deviations of Solids Adherence by Activity
and Body Region 7-52
Table 7-21. Summary of Controlled Greenhouse Trials 7-54
Table 7-22. Dermal Transfer Factors for Selected Contact Surface Types and Skin Wetness, Using
<80 urn Tagged ATD 7-54
Table 7-23. Comparison of Adherence (mg/cm2) for Contact with Carpet and Aluminum Surfaces,
Averaged Across Pressure, Contact Time, Soil Type, and Soil Particle Size 7-55
Table 7-24. Film Thickness Values of Selected Liquids Under Various Experimental Conditions
(10-3cm) 7-56
Table 7-25. Mean Transfer Efficiencies (%) 7-57
Table 7-26. Transfer Efficiencies (%) for Dry, Water-Wetted, and Saliva-Wetted Palms and PUF
Roller 7-57
Table 7-27. Incremental and Overall Surface to Hand Transfer Efficiencies (%) 7-58
Table 7-28. Lognormal Distributions for Modeling Transfer Efficiencies (fraction) 7-59
Table 7-29. Hand-to-Object/Surface Contact—Frequency (contacts/hour) 7-59
Table 7-30. Hand-to-Objects/Surfaces—Frequency (contacts/hour) 7-60
Table 7-31. Median (mean ± SD) Hand Contact Frequency with Clothing, Surfaces, or Objects
(contacts/hour) 7-60
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Table 7-32. Hand Contact with Objects/Surfaces—Frequency (contacts/hour) 7-60
Table 7-33. Outdoor Hand Contact with Object/Surfaces, Children 1 to 6 Years 7-61
Table 7-34. Indoor Hand Contact with Object/Surfaces—Frequency, Children 1 to 6 Years (median
contacts/hour) 7-62
Table 7-35. Outdoor Hand Contact with Surfaces—Frequency, Children 1 to 5 Years (contacts/hour) 7-62
Table 7-36. Hand Contact with Object/Surfaces, Infants and Toddlers 7-63
Figure 7-1. Frequency Distributions for the Surface Area of Men and Women 7-64
Figure 7-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults Transplanting
Plants and Children Playing in Wet Soils 7-65
Figure 7-3. Gravimetric Loading vs. Body Part for Adults Transplanting Plants in Wet Soil and
Children Playing in Wet and Dry Soils 7-65
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BODY-WEIGHT STUDIES 8-1
8.1. INTRODUCTION 8-1
8.2. RECOMMENDATIONS 8-1
8.3. KEY BODY-WEIGHT STUDY 8-4
8.3.1. U.S. EPAAnalysis of NHANES 1999-2006 Data 8-4
8.4. RELEVANT GENERAL POPULATION BODY-WEIGHT STUDIES 8-4
8.4.1. National Center for Health Statistics (NCHS) (1987) 8-4
8.4.2. Brainard and Burmaster( 1992) 8-5
8.4.3. Burmaster and Crouch (1997) 8-5
8.4.4. U.S. EPA (2000) 8-6
8.4.5. Kuczmarski et al. (2002) 8-6
8.4.6. U.S. EPA(2004) 8-6
8.4.7. Ogden et al. (2004) 8-7
8.4.8. Freedman et al. (2006) 8-7
8.4.9. Martin et al. (2007) 8-7
8.4.10. Portier et al. (2007) 8-8
8.4.11. Kahn and Stralka (2008) 8-8
8.5. RELEVANT STUDIES—PREGNANT WOMEN BODY-WEIGHT STUDIES 8-8
8.5.1. Carmichael et al. (1997) 8-8
8.5.2. U.S. EPAAnalysis of 1999 -2006 NHANES Data on Body Weight of Pregnant
Women 8-9
RELEVANT FETAL WEIGHT STUDIES 8-9
8.6.1. Brenner etal. (1976) 8-9
8.6.2. Doubiletetal. (1997) 8-10
REFERENCES FOR CHAPTER 8 8-10
Table 8-1. Recommended Values for Body Weight 8-2
Table 8-2. Confidence in Recommendations for Body Weight 8-3
Table 8-3. Mean and Percentile Body Weights (kg) Derived from NHANES (1999-2006) 8-12
Table 8-4. Mean and Percentile Body Weights (kg) for Male Derived from NHANES (1999-2006) 8-13
Table 8-5. Mean and Percentile Body Weights (kg) for Female Derived from NHANES
(1999-2006) 8-14
Table 8-6. Weight in Kilograms for Male 2 Months-21 Years of Age—Number Examined, Mean,
and Selected Percentiles, by Age Category: United States, 1976-1980 8-15
Table 8-7. Weight in Kilograms for Female 6 Months-21 Years of Age—Number Examined, Mean,
and Selected Percentiles, by Age Category: United States, 1976-1980 8-16
Table 8-8. Statistics for Probability Plot Regression Analyses: Female Body Weights 6 Months to
70 Years of Age 8-17
Table 8-9. Statistics for Probability Plot Regression Analyses: Male Body Weights 6 Months to
70 Years of Age 8-18
Table 8-10. Body-Weight Estimates (kg) by Age and Sex, U.S. Population Derived from NHANES
111(1988-1994) 8-19
Table 8-11. Body-Weight Estimates (in kg) by Age, U.S. Population Derived From NHANES III
(1988-1994) 8-20
Table 8-12. Observed Mean, Standard Deviation, and Selected Percentiles for Weight (kg) by Sex
and Age: Birth to 36 Months 8-21
Table 8-13. Estimated Distribution of Body Weight by Fine Age Categories All Individuals, Male
and Female Combined (kg) 8-22
Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys 8-23
Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys 8-25
Table 8-16. Mean Body Mass Index (kg/m2) by Age and Sex Across Multiple Surveys 8-27
Table 8-17. Sample Sizes by Age, Sex, Race, and Examination 8-29
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Table 8-18. Mean BMI (kg/m ) Levels and Change in the Mean Z Scores by Race Ethnicity and Sex
(Ages 2 to 17) 8-30
Table 8-19. Mean Body Mass Index (kg/m2) by Survey, Sex, Race/Ethnicity, and Age Group;
Adults:United States 8-31
Table 8-20. Prevalence of Overweight and Obesity Among Children 8-32
Table 8-21. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very
Low Birth Weights, by Race, and Hispanic Origin of Mother: United States, 2005 8-33
Table 8-22. Estimated Mean Body Weights of Male and Female by Single Year Age Groups Using
NHANESIIData 8-34
Table 8-23. Estimated Mean Body Weights of Male and Female by Single Year Age Groups Using
NHANES III Data 8-36
Table 8-24. Estimated Mean Body Weights of Male and Female by Single Year Age Groups Using
NHANES IV Data 8-38
Table 8-25. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk
Assessments 8-40
Table 8-26. Estimated Percentile Distribution of Body Weight by Fine Age Categories 8-41
Table 8-27. Estimated Percentile Distribution of Body Weight by Fine Age Categories with
Confidence Interval 8-42
Table 8-28. Distribution of 1st Trimester Weight Gain and 2nd and 3rd Trimesters Rates of Gain in
Women with Good Pregnancy Outcomes 8-43
Table 8-29. Estimated Body Weights of Pregnant Women—NHANES (1999-2006) 8-44
Table 8-30. Fetal Weight (g) Percentiles Throughout Pregnancy 8-45
Table 8-31. Neonatal Weight by Gestational Age for Male andFemale Combined 8-46
Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months 8-47
Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months 8-48
Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months 8-49
Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months 8-50
Figure 8-5. Body Mass Index for-Age Percentiles: Boys, 2 to 20 Years 8-51
Figure 8-6. Body Mass Index for-Age Percentiles: Girls, 2 to 20 Years 8-52
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9. INTAKE OF FRUITS AND VEGETABLES 9-1
9.1. INTRODUCTION 9-1
9.2. RECOMMENDATIONS 9-2
9.3. INTAKE STUDIES 9-5
9.3.1. Key Fruits and Vegetables Intake Study 9-5
9.3.1.1. U.S. EPAAnalysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 9-5
9.3.2. Relevant Fruit and Vegetable Intake Studies 9-7
9.3.2.1. U.S. Department of Agriculture (USDA) (1980, 1992, 1996a,b) 9-7
9.3.2.2. U.S. Department of Agriculture (USDA) (1999a) 9-7
9.3.2.3. U.S. Department of Agriculture (USDA) (1999b) 9-7
9.3.2.4. U.S. EPAAnalysis of Continuing Survey of Food Intake Among
Individuals (CSFII) 1994-1996, 1998 Based on U.S. Department of
Agriculture (USDA) (2000) and U.S. EPA (2000) 9-8
9.3.2.5. Smiciklas Wright et al. (2002) 9-9
9.3.2.6. Vitolins et al. (2002) 9-9
9.3.2.7. Fox et al. (2004) 9-10
9.3.2.8. Ponza et al. (2004) 9-11
9.3.2.9. Fox et al. (2006) 9-11
9.3.2.10.Menellaetal. (2006) 9-11
9.4. CONVERSION BETWEEN WET-AND DRY WEIGHT INTAKE RATES 9-12
9.5. REFERENCES FOR CHAPTER 9 9-12
Table 9-1. Recommended Values for Intake of Fruits and Vegetables, Edible Portion, Uncooked 9-3
Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables 9-4
Table 9-3. Per Capita Intake of Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day,
edible portion, uncooked weight) 9-14
Table 9-4. Consumer Only Intake of Fruits and Vegetables Based on the 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 9-15
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 9-16
Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables Based on the 2003-2006
NHANES (g/kg-day, edible portion, uncooked weight) 9-24
Table 9-7. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
(1977-1978) 9-31
Table 9-8. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
(1987-1988, 1994, and 1995) 9-32
Table 9-9. Per Capita Consumption of Fresh Fruits and Vegetables in 1997 9-33
Table 9-10. Mean Quantities of Vegetables Consumed Daily by Sex and Age, for Children, Per
Capita (g/day, as-consumed) 9-34
Table 9-11. Percentage of Individuals Consuming Vegetables, by Sex and Age, for Children (%) 9-35
Table 9-12. Mean Quantities of Fruits Consumed Daily by Sex and Age, for Children, Per Capita
(g/day, as-consumed) 9-36
Table 9-13. Percentage of Individuals Consuming, Fruits by Sex and Age, for Children (%) 9-37
Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day,
edible portion, uncooked weight) 9-38
Table 9-15. Consumer Only Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg
day, edible portion, uncooked weight) 9-40
Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 9-42
Table 9-17. Consumer Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998
CSFII (g/kg-day, edible portion, uncooked weight) 9-51
Table 9-18. Per Capita Intake of Exposed Fruits Based on 1994-1996 CSFII (g/kg-day, as-consumed) 9-58
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Table 9-19. Per Capita Intake of Protected Fruits Based on 1994-1996 CSFII (g/kg-day, as
consumed) 9-59
Table 9-20. Per Capita Intake of Exposed Vegetables (g/kg-day, as-consumed) 9-60
Table 9-21. Per Capita Intake of Protected Vegetables Based on 1994-1996 CSFII (g/kg-day, as
consumed) 9-61
Table 9-22. Per Capita Intake of Root Vegetables Based on 1994-1996 CSFII (g/kg-day, as
consumed) 9-62
Table 9-23. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and the
Percentage of Individuals Consuming These Foods in Two Days 9-63
Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and
Percentage of Individuals Consuming These Foods in Two Days, by Food 9-64
Table 9-25. Consumption of Major Food Groups: Median Servings (and Ranges) by Demographic
and Health Characteristics, for Older Adults 9-66
Table 9-26. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 9-67
Table 9-27. Percentage of Infants and Toddlers Consuming Different Types of Vegetables 9-68
Table 9-28. Top Five Vegetables Consumed by Infants and Toddlers 9-69
Table 9-29. Percentage of Infants and Toddlers Consuming Different Types of Fruits 9-70
Table 9-30. Top Five Fruits Consumed by Infants and Toddlers 9-71
Table 9-31. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants
(Percentages) 9-72
Table 9-32. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
Participation Status 9-73
Table 9-3 3. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 9-74
Table 9-34. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 9-75
Table 9-35. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Fruits and Vegetables on a Given Day 9-76
Table 9-36. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants and
Toddlers Per Age Group 9-77
Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible
Portions 9-78
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10. INTAKE OF FISH AND SHELLFISH 10-1
10.1. INTRODUCTION 10-1
10.2. RECOMMENDATIONS 10-4
10.2.1. Recommendations—General Population 10-4
10.2.2. Recommendations—Recreational Marine Anglers 10-5
10.2.3. Recommendations—Recreational Freshwater Anglers 10-5
10.2.4. Recommendations—Native American Populations 10-6
10.3. GENERAL POPULATION STUDIES 10-15
10.3.1. Key General Population Study 10-15
10.3.1.1. U.S. EPAAnalysis of Consumption Data from 2003-2006 NHANES 10-15
10.3.2. Relevant General Population Studies 10-16
10.3.2.1. Javitz (1980) 10-16
10.3.2.2.Paoetal. (1982) 10-17
10.3.2.3.USDA(1992a) 10-17
10.3.2.4.U.S. EPA(1996) 10-18
10.3.2.5.Sternetal. (1996) 10-18
10.3.2.6.U.S. EPA(2002) 10-19
10.3.2.7. Westat (2006) 10-20
10.3.2.8.Moyaetal. (2008) 10-21
10.3.2.9.Mahaffey etal. (2009) 10-21
10.4. MARINE RECREATIONAL STUDIES 10-21
10.4.1. Key Marine Recreational Study 10-21
10.4.1.1.National Marine Fisheries Service (1986a,b,c, 1993) 10-21
10.4.2. Relevant Marine Recreational Studies 10-23
10.4.2.1.Pierce etal. (1981) 10-23
10.4.2.2. Puffer etal. (1981) 10-24
10.4.2.3.Burger and Gochfeld (1991) 10-25
10.4.2.4. Burger etal. (1992) 10-26
10.4.2.5.Moya and Phillips (2001) 10-26
10.4.2.6.KCAResearchDivision(1994) 10-27
10.4.2.7. Santa Monica Bay Restoration Project (SMBRP) (1994) 10-27
10.4.2.8.U.S. DHHS (1995) 10-28
10.4.2.9. Alcoa (1998) 10-29
10.4.2.10. Burger etal. (1998) 10-30
10.4.2.11. Chiang (1998) 10-30
10.4.2.12. San Francisco Estuary Institute (SFEI) (2000) 10-31
10.4.2.13. Burger (2002a) 10-31
10.4.2.14. Mayfield et al. (2007) 10-32
10.5. FRESHWATER RECREATIONAL STUDIES 10-32
10.5.1. Fiore etal. (1989) 10-32
10.5.2. West etal. (1989) 10-33
10.5.3. Chemrisk (1992) 10-35
10.5.4. Connelly etal. (1992) 10-37
10.5.5. Hudson River Sloop Clearwater, Inc. (1993) 10-37
10.5.6. West etal. (1993) 10-38
10.5.7. Alabama Dept. of Environmental Management (ADEM) (1994) 10-39
10.5.8. Connelly etal. (1996) 10-39
10.5.9. Balcometal. (1999) 10-40
10.5.10. Burger etal. (1999) 10-41
10.5.11. Williams etal. (1999) 10-42
10.5.12. Burger (2000) 10-42
10.5.13. Williams et al. (2000) 10-43
10.5.14. Benson etal. (2001) 10-43
10.5.15. Moya and Phillips (2001) 10-44
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10.5.16. Campbell et al. (2002) 10-44
10.5.17. Burger (2002b) 10-45
10.5.18. Mayfield et al. (2007) 10-45
10.6. NATIVE AMERICAN STUDIES 10-46
10.6.1. Wolfe and Walker (1987) 10-46
10.6.2. Columbia River Inter-Tribal Fish Commission (CRITFC) (1994) 10-47
10.6.3. Petersonetal. (1994) 10-48
10.6.4. Fitzgerald etal. (1995) 10-49
10.6.5. Fortietal. (1995) 10-50
10.6.6. Toy etal. (1996) 10-51
10.6.7. Duncan (2000) 10-52
10.6.8. Westat(2006) 10-53
10.6.9. Polissar et al. (2006) 10-53
10.7. OTHER POPULATION STUDIES 10-54
10.7.1. U.S. EPA(1999) 10-54
10.8. SERVING SIZE STUDIES 10-55
10.8.1. Pao etal. (1982) 10-55
10.8.2. Smiciklas-Wright et al. (2002) 10-56
10.9. OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION 10-56
10.9.1. Conversion between Wet and Dry Weight 10-56
10.9.2. Conversion Between Wet-Weight and Lipid-Weight Intake Rates 10-57
10.10. REFERENCES FOR CHAPTER 10 10-57
APPENDIX 10A: RESOURCE UTILIZATION DISTRIBUTION 10A-1
APPENDIX 10B: FISH PREPARATION AND COOKING METHODS 10B-1
Table 10-1. Recommended Per Capita and Consumer-Only Values for Fish Intake (g/kg-day),
Uncooked Fish Weight, by Age 10-7
Table 10-2. Confidence in Recommendations for General Population Fish Intake 10-8
Table 10-3. Recommended Values for Recreational Marine Fish Intake 10-9
Table 10-4. Confidence in Recommendations for Recreational Marine Fish Intake 10-10
Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake 10-11
Table 10-6. Summary of Relevant Studies on Native American Fish Intake 10-13
Table 10-7. Per Capita Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-62
Table 10-8. Consumer-Only Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-63
Table 10-9. Per Capita Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-64
Table 10-10. Consumers-Only Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-65
Table 10-11. Per Capita Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion,
Uncooked Fish Weight 10-66
Table 10-12. Consumer-Only Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible
Portion, Uncooked Fish Weight 10-67
Table 10-13. Total Fish Consumption, Consumers Only, by Demographic Variables 10-68
Table 10-14. Percent Distribution of Total Fish Consumption for Females and Males by Age 10-70
Table 10-15. Mean Total Fish Consumption by Species 10-71
Table 10-16. Best Fits of Lognormal Distributions Using the Non-Linear Optimization Method 10-72
Table 10-17. Mean Fish Intake in a Day, by Sex and Age 10-72
Table 10-18. Percent of Respondents That Responded Yes, No, or Don't Know to Eating Seafood in
1 Month (including shellfish, eels, or squid) 10-73
Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of
Seafood in 1 Month 10-75
Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was
Purchased or Caught by Someone They Knew 10-77
Table 10-21. Distribution of Fish Meals Reported by NJ Consumers During the Recall Period 10-78
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Table 10-22. Selected Species Among All Reported Meals by NJ Consumers During the Recall Period 10-79
Table 10-23. Cumulative Probability Distribution of Average Daily Fish Consumption (g/day) 10-79
Table 10-24. Distribution of the Usual Frequency of Fish Consumption 10-79
Table 10-25. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
Population, as Prepared 10-80
Table 10-26. Daily Average Per Capita Estimates of Fish Consumption: U.S. Population—Mean
Consumption by Species Within Habitat, as Prepared 10-81
Table 10-27. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
Population, Uncooked Fish Weight 10-82
Table 10-28. Daily Average Per Capita Estimates of Fish Consumption U.S. Population—Mean
Consumption by Species Within Habitat, Uncooked Fish Weight 10-83
Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepared 10-84
Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared 10-86
Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish
Weight 10-88
Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
Weight 10-90
Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepared 10-92
Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as
Prepared 10-94
Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked
Fish Weight 10-96
Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day),
Uncooked Fish Weight 10-98
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics (g/kg-day, as-consumed) 10-100
Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics (g/kg-day, as-consumed) 10-104
Table 10-39. Fish Consumption per kg Body Weight, all Respondents by State, Acquisition Method,
(g/kg-day, as-consumed) 10-108
Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method
(g/kg-day, as-consumed) 10-111
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day) 10-114
Table 10^2. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics, Uncooked (g/kg-day) 10-118
Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition Method,
Uncooked (g/kg-day) 10-122
Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,
Uncooked (g/kg-day) 10-125
Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and
Sex (g/kg-day, as-consumed) 10-128
Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex 10-130
Table 10-47. Fish Consumption Among General Population in Four States, Consumers Only
(g/kg-day, as-consumed) 10-133
Table 10-48. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion... 10-135
Table 10-49. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational
Fishermen, by Wave and Subregion 10-136
Table 10-50. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status 10-137
Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B l)a by Marine Recreational
Fishermen, by Species Group and Subregion 10-138
Table 10-52. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement
Bay, Washington 10-139
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Table 10-53. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler
Populations Based on the Re-Analysis of the Puffer et al. (1981) and Pierce et al. (1981)
Data 10-139
Table 10-54. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their
Family/Living Group 10-140
Table 10-55. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport
Fishermen in the Metropolitan Los Angeles Area 10-140
Table 10-56. Catch Information for Primary Fish Species Kept by Sport Fishermen (N = 1,059) 10-141
Table 10-57. Fishing and Crabbing Behavior of Fishermen at Humacao, Puerto Rico 10-141
Table 10-58. Fish Consumption of Delaware Recreational Fishermen and Their Households 10-142
Table 10-59. Seafood Consumption Rates of All Fish by Ethnic and Income Groups of Santa Monica
Bay 10-143
Table 10-60. Means and Standard Deviations of Selected Characteristics by Population Groups in
Everglades, Florida 10-143
Table 10-61. Grams per Day of Self-Caught Fish Consumed by Recreational Anglers—Alcoa/Lavaca
Bay 10-144
Table 10-62. Number of Meals and Portion Sizes of Serf-Caught Fish Consumed by Recreational
Anglers Lavaca Bay, Texas 10-145
Table 10-63. Consumption Patterns of People Fishing and Crabbing in Barnegat Bay, New Jersey 10-146
Table 10-64. Fish Intake Rates of Members of the Laotian Community of West Contra Costa County,
California 10-146
Table 10-65. Consumption Rates (g/day) Among Recent Consumers by Demographic Factor 10-147
Table 10-66. Mean + SD Consumption Rates for Individuals Who Fish or Crab in the Newark Bay
Area 10-148
Table 10-67. Consumption Rates (g/day) for Marine Recreational Anglers in King County, WA 10-148
Table 10-68. Percentile and Mean Intake Rates for Wisconsin Sport Anglers (all respondents) 10-149
Table 10-69. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households with
Recreational Fish Consumption 10-149
Table 10-70. Comparison of 7-Day Recall and Estimated Seasonal Frequency for Fish Consumption 10-150
Table 10-71. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and
Consumed Recreationally Caught Fish 10-150
Table 10-72. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989-1990
Ice Fishing or 1990 Open-Water Seasons 10-151
Table 10-73. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day) 10-152
Table 10-74. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the
1990 Season 10-152
Table 10-75. Socio-Demographic Characteristics of Respondents 10-153
Table 10-76. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish
Consumption Study, 1991-1992 10-154
Table 10-77. Mean Per Capita Freshwater Fish Intake of Alabama Anglers 10-155
Table 10-78. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) for
1992 Lake Ontario Anglers 10-155
Table 10-79. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by
Socio-Demographic Characteristics 10-156
Table 10-80. Seafood Consumption Rates of Nine Connecticut Population Groups 10-156
Table 10-81. Fishing Patterns and Consumption Rates of People Fishing Along the Savannah River
(Mean±SE) 10-157
Table 10-82. Fish Consumption Rates for Indiana Anglers—Mail Survey (g/day) 10-158
Table 10-83. Fish Consumption Rates for Indiana Anglers—On-Site Survey (g/day) 10-158
Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North Dakota
Residents (g/day) 10-159
Table 10-85. Fishing Patterns and Consumption Rates of Anglers Along the Clinch River Arm of
Watts Bar Reservoir (Mean ± SE) 10-161
Table 10-86. Daily Consumption of Wild-Caught Fish, Consumers Only (g/kg-day, as-consumed) 10-161
Table 10-87. Consumption Rates (g/day) for Freshwater Recreational Anglers in King County, WA 10-162
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Table 10-88. Number of Grams per Day of Fish Consumed by All Adult Respondents (consumers and
non-consumers combined)—Throughout the Year 10-162
Table 10-89. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents 10-163
Table 10-90. Fish Consumption Rates Among Native American Children (Age 5 Years and Under) 10-163
Table 10-91. Number of Fish Meal Eaten per Month and Fish Intake Among Native American
Children Who Consume Particular Species 10-164
Table 10-92. Socio-Demographic Factors and Recent Fish Consumption 10-164
Table 10-93. Number of Local Fish Meals Consumed per Year by Time Period for All Respondents 10-165
Table 10-94. Mean Number of Local Fish Meals Consumed per Year by Time Period for All
Respondents and Consumers Only 10-165
Table 10-95. Mean Number of Local Fish Meals Consumed per Year by Time Period and Selected
Characteristics for All Respondents (Mohawk, N = 97; Control, N = 154) 10-166
Table 10-96. Fish Consumption Rates for Mohawk Native Americans (g/day) 10-166
Table 10-97. Percentiles and Mean of Adult Tribal Member Consumption Rates (g/kg-day) 10-167
Table 10-98. Median and Mean Consumption Rates by Sex (g/kg-day) within Each Tribe 10-168
Table 10-99. Median Consumption Rate for Total Fish by Sex and Tribe (g/day) 10-168
Table 10-100. Percentiles of Adult Consumption Rates by Age (g/kg-day) 10-169
Table 10-101. Median Consumption Rates by Income (g/kg-day) within Each Tribe 10-170
Table 10-102. Mean, 50th, and 90th Percentiles of Consumption Rates for Children Age Birth to 5 Years
(g/kg-day) 10-171
Table 10-103. Adult Consumption Rate (g/kg-day): Individual Finfish and Shellfish and Fish Groups 10-172
Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only 10-173
Table 10-105. Adult Consumption Rate (g/kg-day) by Sex 10-176
Table 10-106. Adult Consumption Rate (g/kg-day) by Age 10-177
Table 10-107. Consumption Rates for Native American Children (g/kg-day), All Children (including
non-consumers): Individual Finfish and Shellfish and Fish Groups 10-179
Table 10-108. Consumption Rates for Native American Children (g/kg-day), Consumers Only:
Individual Finfish and Shellfish and Fish Groups 10-180
Table 10-109. Percentiles and Mean of Consumption Rates for Adult Consumers Only (g/kg-day) 10-181
Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only
(g/kg-day) 10-182
Table 10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consumers
Only—Squaxin Island Tribe (g/kg-day) 10-184
Table 10-112. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only—Tulalip
Tribe (g/kg-day) 10-186
Table 10-113. Percentiles and Mean of Consumption Rates for Child Consumers Only (g/kg-day) 10-187
Table 10-114. Percentiles and Mean of Consumption Rates by Sex for Child Consumers Only
(g/kg-day) 10-188
Table 10-115. Consumption Rates of API Community Members 10-189
Table 10-116. Demographic Characteristics of "Higher" and "Lower" Seafood Consumers 10-190
Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community
(g/kg-day) 10-191
Table 10-118. Consumption Rates by Sex for All Asian and Pacific Islander Community 10-195
Table 10-119. Types of Seafood Consumed/Respondents Who Consumed (%) 10-196
Table 10-120. Mean, Median and 95th Percentile Fish Intake Rates for Different Groups (g/day) 10-198
Table 10-121. Distribution of Quantity of Fish Consumed (in grams) per Eating Occasion, by Age and
Sex 10-199
Table 10-122. Distribution of Quantity of Canned Tuna Consumed (grams) per Eating Occasion, by
Age and Sex 10-200
Table 10-123. Distribution of Quantity of Other Finfish Consumed (grams) per Eating Occasion, by
Age and Sex 10-201
Table 10-124. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies 10-202
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species 10-203
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Figure 10-1. Locations of Freshwater Fish Consumption Surveys in the United States 10-12
Figure 10-2. Species and Frequency of Meals Consumed by Geographic Residence 10-208
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11. INTAKE OF MEATS, DAIRY PRODUCTS, AND FATS 11-1
11.1. INTRODUCTION 11-1
11.2. RECOMMENDATIONS 11-1
11.3. INTAKE OF MEAT AND DAIRY PRODUCTS 11-6
11.3.1. Key Meat and Dairy Intake Studies 11-6
11.3.1.1.U.S. EPAAnalysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 11-6
11.3.2. Relevant Meat and Dairy Intake Studies 11-7
11.3.2.1.USDA(1980, 1992, 1996a, b) 11-7
11.3.2.2.USDA(1999a) 11-8
11.3.2.3.U.S. EPA Analysis of CSFII1994-1996, 1998 Based on USD A (2000)
and U.S. EPA (2000) 11-8
11.3.2.4. Smiciklas Wright etal. (2002) 11-9
11.3.2.5. Vitolinsetal. (2002) 11-10
11.3.2.6. Fox etal. (2004) 11-10
11.3.2.7.Ponzaetal. (2004) 11-11
11.3.2.8.Mennellaetal. (2006) 11-11
11.3.2.9. Fox etal. (2006) 11-11
11.4. INTAKE OF FAT 11-12
11.4.1. Key Fat Intake Study 11-12
11.4.1.1.U.S. EPA(2007) 11-12
11.4.2. Relevant Fat Intake Studies 11-13
11.4.2.1.Cresantaetal. (1988)/Nicklas etal. (1993)/and Frank etal. (1986) 11-13
11.5. CONVERSION BETWEEN WET-AND DRY-WEIGHT INTAKE RATES 11-13
11.6. CONVERSION BETWEEN WET WEIGHT AND LIPID-WEIGHT INTAKE RATES 11-13
11.7. REFERENCES FOR CHAPTER 11 11-14
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion,
Uncooked 11-3
Table 11-2. Confidence in Recommendations for Intake of Meats, Dairy Products, and Fats 11-5
Table 11-3. Per Capita Intake of Total Meat and Total Dairy Products Based on 2003-2006
NHANES (g/kgday, edible portion, uncooked weight) 11-16
Table 11-4. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 2003-2006
NHANES (g/kgday, edible portion, uncooked weight) 11-17
Table 11-5. Per Capita Intake of Individual Meats and Dairy Products Based on 2003-2006
NHANES (g/kgday, edible portion, uncooked weight) 11-18
Table 11-6. Consumer-Only Intake of Individual Meats and Dairy Products Based on 2003-2006
NHANES (g/kgday, edible portion, uncooked weight) 11-19
Table 11-7. Mean Meat Intakes per Individual in a Day, by Sex and Age (g/day, as consumed) for
1977-1978 11-20
Table 11-8. Mean Meat Intakes Per Capita in a Day, by Sex and Age (g/day, as consumed) for
1987-1988 11-21
Table 11-9. Mean Meat Intakes Per Capita in a Day, by Sex and Age (g/day, as consumed) for 1994
and 1995 11-22
Table 11-10. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as consumed)
for 1977-1978 11-23
Table 11-11. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as consumed)
for 1987-1988 11-24
Table 11-12. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as consumed)
for 1994 and 1995 11-24
Table 11-13. Mean Quantities of Meat and Eggs Consumed Daily by Sex and Age, Per Capita (g/day,
as consumed) 11-25
Table 11-14. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%) 11-26
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Table 11-15. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day,
as consumed) 11-27
Table 11-16. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) 11-28
Table 11-17. Per Capita Intake of Total Meat and Total Dairy Products (g/kg day edible portion,
uncooked weight) 11-29
Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 1994-1996,
1998 CSFII (g/kg day, edible portion, uncooked weight) 11-31
Table 11-19. Per Capita Intake of Individual Meats and Dairy Products Based on 1994-1996, 1998
CSFII (g/kg day, edible portion, uncooked weight) 11-33
Table 11-20. Consumer-Only Intake of Individual Meats and Dairy Products Based on 1994-1996,
1998 CSFII (g/kg day, edible portion, uncooked weight) 11-34
Table 11-21. Quantity (as consumed) of Meat and Dairy Products Consumed per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days 11-35
Table 11-22. Consumption of Milk, Yogurt, and Cheese: Median Daily Servings (and ranges) by
Demographic and Health Characteristics 11-37
Table 11-23. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 11-38
Table 11-24. Percentage of Infants and Toddlers Consuming Milk, Meat, or Other Protein Sources 11-39
Table 11-25. Characteristics of WIC Participants and Non Participants (percentages) 11 -40
Table 11-26. Food Choices for Infants and Toddlers by WIC Participation Status 11-41
Table 11-27. Percentage of Hispanic and Non Hispanic Infants and Toddlers Consuming Different
Types of Milk, Meats, or Other Protein Sources on a Given Day 11-41
Table 11-28. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 11 -42
Table 11-29. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 11-42
Table 11-30. Per Capita Total Fat Intake (g/day) 11-43
Table 11-31. Per Capita Total Fat Intake (g/kg day) 11-45
Table 11-32. Consumers-Only Total Fat Intake (g/day) 11-47
Table 11-33. Consumers-Only Total Fat Intake (g/kg day) 11-49
Table 11-34. Consumers-Only Total Fat Intake—Top 10% of Animal Fat Consumers (g/day) 11-51
Table 11-35. Consumers-Only Total Fat Intake—Top 10% of Animal Fat Consumers (g/kg day) 11-53
Table 11-36. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982
(g/day) 11-55
Table 11-37. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982
(g/kg day) 11-56
Table 11-38. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products 11-57
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12.
INTAKE OF GRAIN PRODUCTS 12-1
12.1. INTRODUCTION 12-1
12.2. RECOMMENDATIONS 12-1
12.3. INTAKE STUDIES 12-4
12.3.1. Key Grain Intake Study 12-4
12.3.1.1.U.S. EPAAnalysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 12-4
12.3.2. Relevant Grain Intake Studies 12-5
12.3.2.1.USDA (1980, 1992, 1996a,b) 12-5
12.3.2.2.USDA(1999a) 12-6
12.3.2.3.USDA (1999b) 12-6
12.3.2.4.U.S. EPAAnalysis of Continuing Survey of Food Intake by Individuals
(CSFII) 1994-1996, 1998 12-7
12.3.2.5.Smiciklas Wright etal. (2002) 12-8
12.3.2.6. Vitolinsetal. (2002) 12-8
12.3.2.7.Foxetal. (2004) 12-9
12.3.2.8.Ponzaetal. (2004) 12-9
12.3.2.9.Foxetal. (2006) 12-10
12.3.2.10.Mennellaetal. (2006) 12-10
12.4. CONVERSION BETWEEN WET-AND DRY-WEIGHT INTAKE RATES 12-10
12.5. REFERENCES FOR CHAPTER 12 12-11
Table 12-1. Recommended Values for Intake of Grains, Edible Portion, Uncooked 12-2
Table 12-2. Confidence in Recommendations for Intake of Grain Products 12-3
Table 12-3. Per Capita Intake of Total Grains Based 2003-2006 NHANES (g/kg-day, edible portion,
uncooked weight) 12-13
Table U-4. Consumer-Only Intake of Total Grains Based 2003-2006 NHANES (g/kg-day, edible
portion, uncooked weight) 12-14
Table 12-5. Per Capita Intake of Individual Grain Products Based 2003-2006 NHANES (g/kg-day,
edible portion, uncooked weight) 12-15
Table 12-6. Consumer-Only Intake of Individual Grain Products Based 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 12-16
Table 12-7. Mean Grain Intake per Individual in a Day by Sex and Age (g/day as-consumed) for
1977-1978 12-17
Table 12-8. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed) for
1987-1988 12-18
Table 12-9. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed) for
1994-1995 12-18
Table 12-10. Per Capita Consumption of Flour and Cereal Products in 1997 12-19
Table 12-11. Mean Quantities of Grain Products Consumed by Children Under 20 Years of Age, by
Sex and Age, Per Capita (g/day, as-consumed) 12-20
Table 12-12. Percentage of Individuals Under 20 Years of Age Consuming Grain Products, by Sex and
Age(%) 12-21
Table 12-13. Per Capita Intake of Total Grains Based on 1994-1996, 1998 CSFII (g/kg-day, edible
portion, uncooked weight) 12-22
Table 12-14. Consumer-Only Intake of Total Grains Based on 1994-1996, 1998 CSFII (g/kg-day,
edible portion, uncooked weight) 12-23
Table 12-15. Per Capita Intake of Individual Grain Products Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 12-24
Table 12-16. Consumer-Only Intake of Individual Grain Products Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 12-25
Table 12-17. Per Capita Intake of Breads Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-26
Table 12-18. Per Capita Intake of Sweets Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-27
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Table 12-19. Per Capita Intake of Snacks Containing Grains Based on 1994-1996, 1998 CSFII
(g/kg-day, as-consumed) 12-28
Table 12-20. Per Capita Intake of Breakfast Foods Based on 1994-1996, 1998 CSFII (g/kg-day, as
consumed) 12-29
Table 12-21. Per Capita Intake of Pasta Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-30
Table 12-22. Per Capita Intake of Cooked Cereals Based on 1994-1996, 1998 CSFII (g/kg-day, as
consumed) 12-31
Table 12-23. Per Capita Intake of Ready-to-Eat Cereals Based on 1994-1996, 1998 CSFII (g/kg-day,
as-consumed) 12-32
Table 12-24. Per Capita Intake of Baby Cereals Based on 1994-1996, 1998 CSFII (g/kg-day, as
consumed) 12-33
Table 12-25. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and the
Percentage of Individuals Using These Foods in 2 Days 12-34
Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and
Percentage of Individuals Using These Foods in 2 Days, by Sex and Age 12-35
Table 12-27. Consumption of Major Food Groups by Older Adults: Median Daily Servings (and
Ranges) by Demographic and Health Characteristics 12-37
Table 12-28. Characteristics of the Feeding Infant and Toddlers Study (FITS) Sample Population 12-38
Table 12-29. Percentage of Infants and Toddlers Consuming Different Types of Grain Products 12-39
Table 12-30. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants
(percentages) 12-40
Table 12-31. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
Participation Status 12-41
Table 12-32. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study 12-42
Table 12-33. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study 12-42
Table 12-34. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Grain Products ona Given Day 12-43
Table 12-35. Mean Moisture Content of Selected Grain Products Expressed as Percentages of Edible
Portions (grams per 100 grams of edible portion) 12-44
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13. INTAKE OF HOME-PRODUCED FOODS 13-1
13.1. INTRODUCTION 13-1
13.2. RECOMMENDATIONS 13-1
13.3. KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS 13-5
13.3.1. U.S. EPA Analysis of NFCS 1987-1988; Moya and Phillips (2001) Analysis of
Consumption of Home-Produced Foods 13-5
13.3.2. Phillips and Moya (2011) 13-9
13.4. RELEVANT STUDY FOR INTAKE OF HOME-PRODUCED FOODS 13-10
13.4.1. National Gardening Association (2009) 13-10
13.5. REFERENCES FOR CHAPTER 13 13-10
APPENDIX 13A FOOD CODES AND DEFINITIONS OF MAJOR FOOD GROUPS USED IN
THE ANALYSIS 13A-1
APPENDIX 13B 1987-1988 NFCS FOOD CODES AND DEFINITIONS OF INDIVIDUAL
FOOD ITEMS USED IN ESTIMATING THE FRACTION OF HOUSEHOLD FOOD
INTAKE THAT IS HOME-PRODUCED 13B-1
Table 13-1. Summary of Recommended Values for Intake of Home-Produced Foods 13-2
Table 13-2. Confidence in Recommendations for Intake of Home-Produced Foods 13-4
Table 13-3. Subcategory Codes, Definitions, and Descriptions 13-12
Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in
Analysis of Food Intake 13-13
Table 13-5. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—All Regions Combined 13-14
Table 13-6. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Northeast 13-15
Table 13-7. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Midwest 13-16
Table 13-8. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—South 13-17
Table 13-9. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—West 13-18
Table 13-10. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—All Regions
Combined 13-19
Table 13-11. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Northeast 13 -20
Table 13-12. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Midwest 13-21
Table 13-13. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—South 13-22
Table 13-14. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—West 13-23
Table 13-15. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—All Regions Combined 13-24
Table 13-16. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Northeast 13-25
Table 13-17. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Midwest 13-26
Table 13-18. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—South 13-27
Table 13-19. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—West 13-28
Table 13-20. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—All Regions Combined 13-29
Table 13-21. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Northeast 13-30
Table 13-22. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Midwest 13-31
Table 13-23. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—South 13-32
Table 13-24. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—West 13-33
Table 13-25. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—All Regions 13-34
Table 13-26. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Northeast 13-35
Table 13-27. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Midwest 13-36
Table 13-28. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—South 13-37
Table 13-29. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—West 13-38
Table 13-30. Seasonally Adjusted Consumer-Only Home-Produced Intake (g/kg-day) 13-39
Table 13-31. Consumer-Only Intake of Home-Produced Apples (g/kg-day) 13-40
Table 13-32. Consumer-Only Intake of Home-Produced Asparagus (g/kg-day) 13-41
Table 13-33. Consumer-Only Intake of Home-Produced Beef (g/kg-day) 13-42
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Table 13-34. Consumer-Only Intake of Home-Produced Beets (g/kg-day) 13-43
Table 13-35. Consumer-Only Intake of Home-Produced Broccoli (g/kg-day) 13-44
Table 13-36. Consumer-Only Intake of Home-Produced Cabbage (g/kg-day) 13-45
Table 13-37. Consumer-Only Intake of Home-Produced Carrots (g/kg-day) 13-46
Table 13-38. Consumer-Only Intake of Home-Produced Corn (g/kg-day) 13-47
Table 13-39. Consumer-Only Intake of Home-Produced Cucumbers (g/kg-day) 13-48
Table 13-40. Consumer-Only Intake of Home-Produced Eggs (g/kg-day) 13-49
Table 13-41. Consumer-Only Intake of Home-Produced Game (g/kg-day) 13-50
Table 13-42. Consumer-Only Intake of Home-Produced Lettuce (g/kg-day) 13-51
Table 13-43. Consumer-Only Intake of Home-Produced Lima Beans (g/kg-day) 13-52
Table 13^4. Consumer-Only Intake of Home-Produced Okra (g/kg-day) 13-53
Table 13-45. Consumer-Only Intake of Home-Produced Onions (g/kg-day) 13-54
Table 13-46. Consumer-Only Intake of Home-Produced Other Berries (g/kg-day) 13-55
Table 13-47. Consumer-Only Intake of Home-Produced Peaches (g/kg-day) 13-56
Table 13-48. Consumer-Only Intake of Home-Produced Pears (g/kg-day) 13-57
Table 13-49. Consumer-Only Intake of Home-Produced Peas (g/kg-day) 13-58
Table 13-50. Consumer-Only Intake of Home-Produced Peppers (g/kg-day) 13-59
Table 13-51. Consumer-Only Intake of Home-Produced Pork (g/kg-day) 13-60
Table 13-52. Consumer-Only Intake of Home-Produced Poultry (g/kg-day) 13-61
Table 13-53. Consumer-Only Intake of Home-Produced Pumpkins (g/kg-day) 13-62
Table 13-54. Consumer-Only Intake of Home-Produced Snap Beans (g/kg-day) 13-63
Table 13-55. Consumer-Only Intake of Home-Produced Strawberries (g/kg-day) 13-64
Table 13-56. Consumer-Only Intake of Home-Produced Tomatoes (g/kg-day) 13-65
Table 13-57. Consumer-Only Intake of Home-Produced White Potatoes (g/kg-day) 13-66
Table 13-58. Consumer-Only Intake of Home-Produced Exposed Fruit (g/kg-day) 13-67
Table 13-59. Consumer-Only Intake of Home-Produced Protected Fruits (g/kg-day) 13-68
Table 13-60. Consumer-Only Intake of Home-Produced Exposed Vegetables (g/kg-day) 13-69
Table 13-61. Consumer-Only Intake of Home-Produced Protected Vegetables (g/kg-day) 13 -70
Table 13-62. Consumer-Only Intake of Home-Produced Root Vegetables (g/kg-day) 13-71
Table 13-63. Consumer-Only Intake of Home-Produced Dark Green Vegetables (g/kg-day) 13 -72
Table 13-64. Consumer-Only Intake of Home-Produced Deep Yellow Vegetables (g/kg-day) 13-73
Table 13-65. Consumer-Only Intake of Home-Produced Other Vegetables (g/kg-day) 13 -74
Table 13-66. Consumer-Only Intake of Home-Produced Citrus (g/kg-day) 13-75
Table 13-67. Consumer-Only Intake of Home-Produced Other Fruit (g/kg-day) 13-76
Table 13-68. Fraction of Food Intake That Is Home-Produced 13-77
Table 13-69. Percent Weight Losses from Food Preparation 13-81
Table 13-70. Estimated Age-Specific Per Capita Home-Produced Intake (adjusted; g/kg-day) 13-82
Table 13-71. 2008 Food Gardening by Demographic Factors 13-83
Table 13-72. Percentage of Gardening Households Growing Different Vegetables in 2008 13-84
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14.
TOTAL FOOD INTAKE 14-1
14.1. INTRODUCTION 14-1
14.2. RECOMMENDATIONS 14-1
14.3. STUDIES OF TOTAL FOOD INTAKE 14-4
14.3.1. U.S. EPA Re-Analysis of 1994-1996, 1998 Continuing Survey of Food Intake
by Individuals (CSFII), Based on U.S. EPA (2007) 14-4
14.3.2. U.S. EPA Analysis of National Health and Nutrition Examination Survey
(NHANES) 2003-2006 Data 14-5
14.4. REFERENCES FOR CHAPTER 14 14-6
Table 14-1. Recommended Values for Per Capita Total Food Intake, Edible Portion, Uncooked
Weight 14-2
Table 14-2. Confidence in Recommendations for Total Food Intake 14-3
Table 14-3. Per Capita Total Food Intake, Edible Portion, Uncooked 14-7
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion,
uncooked) 14-8
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible
portion, uncooked) 14-12
Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Food Intake 14-16
Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Meat Intake 14-20
Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Meat and Dairy
Intake 14-24
Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Fish Intake 14-28
Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Fruit and
Vegetable Intake 14-33
Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid Range, and High-End Total Dairy Intake 14-37
Table 14-12. Intake of Total Food (g/kg-day), Edible Portion, Uncooked Weight 14-41
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15. HUMAN MILK INTAKE 15-1
15.1. INTRODUCTION 15-1
15.2. RECOMMENDATIONS 15-1
15.2.1. Human Milk Intake 15-2
15.2.2. Lipid Content and Lipid Intake 15-2
15.3. KEY STUDIES ON HUMAN MILK INTAKE 15-9
15.3.1. Paoetal. (1980) 15-9
15.3.2. Dewey and Lonnerdal (1983) 15-9
15.3.3. Butteetal. (1984) 15-9
15.3.4. Neville etal. (1988) 15-10
15.3.5. Dewey etal. (1991a,b) 15-10
15.3.6. Butte et al. (2000) 15-11
15.3.7. Arcus-Arthetal. (2005) 15-11
15.4. KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK 15-12
15.4.1. Butteetal. (1984) 15-12
15.4.2. Mitoulas et al. (2002) 15-13
15.4.3. Mitoulas et al. (2003) 15-13
15.4.4. Arcus-Arth et al. (2005) 15-14
15.4.5. Kent et al. (2006) 15-14
15.5. RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK 15-14
15.5.1. Maxwell and Burmaster (1993) 15-14
15.6. OTHER FACTORS 15-15
15.6.1. Population of Nursing Infants 15-15
15.6.2. Intake Rates Based on Nutritional Status 15-17
15.6.3. Frequency and Duration of Feeding 15-18
15.7. REFERENCES FOR CHAPTER 15 15-18
Table 15-1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breast-
Fed Infants 15-3
Table 15-2. Confidence in Recommendations for Human Milk Intake 15-4
Table 15-3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/day) 15-5
Table 15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/kgday) 15-6
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/day) 15-7
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/kg-day) 15-8
Table 15-7. Daily Intakes of HumanMilk 15-21
Table 15-8. HumanMilk Intakes for Infants Aged 1-6 Months 15-21
Table 15-9. Human Milk Intake Among Exclusively Breast-Fed Infants During the First 4 Months of
Life 15-21
Table 15-10. Human Milk Intake During a 24-Hour Period 15-22
Table 15-11. Human Milk Intake Estimated by the Darling Study 15-23
Table 15-12. Mean Breast-Fed Infants Characteristics 15-23
Table 15-13. Mean Human Milk Intake of Breast-Fed Infants (mL/day) 15-23
Table 15-14. Feeding Practices by Percent of Infants 15-24
Table 15-15. Body Weight of Breast-Fed Infants 15-24
Table 15-16. AAP Data Set Milk Intake Rates at Different Ages 15-25
Table 15-17. Average Daily Human Milk Intake (mL/kg-day) 15-25
Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively
Breast-Fed Infants 15-26
Table 15-19. Human Milk Production and Composition During the First 12 Months of Lactation 15-26
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Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content During the First
Year of Lactation 15-27
Table 15-21. Changes in Fatty Acid Composition of Human Milk During the First Year of Lactation
(g/100 g total fatty acids) 15-27
Table 15-22. Comparison Daily Lipid Intake Based on Lipid Content Assumptions (mL/kg-day) 15-28
Table 15-23. Distribution of Average Daily Lipid Intake (mL/kg-day) Assuming 4% Milk Lipid
Content 15-28
Table 15-24. Predicted Lipid Intakes for Breast-Fed Infants Under 12 Months of Age 15-28
Table 15-25. Socioeconomic Characteristics of Exclusively Breast-Fed Infants Born in 2004 15-29
Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children Born in 2006 15-30
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants
0-6 Months Old 15-32
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants
6-12 Months Old 15-33
Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
During the Previous 24 Hours 15-34
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, NHANES III
(1988-1994) 15-35
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk
at 6 Months (NHANES III, 1988-1994) 15-37
Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at
4 Months (NHANES III, 1991-1994) 15-39
Table 15-33. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants at
5 or 6 Months of Age in the United States in 1989 and 1995, by Ethnic Background and
Selected Demographic Variables 15-41
Table 15-34. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants at 6
and 12 Months of Age in the United States in 2003, by Ethnic Background and Selected
Demographic Variables 15-42
Table 15-35. Number of Meals Per Day 15-43
Table 15-36. Comparison of Breast-Feeding Patterns Between Age and Groups (Mean± SD) 15-43
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16. ACTIVITY FACTORS 16-1
16.1. INTRODUCTION 16-1
16.2. RECOMMENDATIONS 16-1
16.2.1. Activity Patterns 16-1
16.2.2. Occupational Mobility 16-2
16.2.3. Population Mobility 16-2
16.3. ACTIVITY PATTERNS 16-11
16.3.1. Key Activity Pattern Studies 16-11
16.3.1.1. Wiley etal. (1991) 16-11
16.3.1.2.U.S. EPA (1996) 16-12
16.3.2. Relevant Activity Pattern Studies 16-13
16.3.2.1.Hill (1985) 16-13
16.3.2.2.Timmeretal. (1985) 16-14
16.3.2.3.Robinson and Thomas (1991) 16-15
16.3.2.4.Funketal. (1998) 16-15
16.3.2.5.CohenHubaletal. (2000) 16-16
16.3.2.6. Wong etal. (2000) 16-17
16.3.2.7. Graham and McCurdy (2004) 16-18
16.3.2.8.Justeretal. (2004) 16-18
16.3.2.9.Vandewateretal. (2004) 16-19
16.3.2.10.U.S. Department of Labor (2007) 16-19
16.3.2.11.Naderetal. (2008) 16-20
16.4. OCCUPATIONAL MOBILITY 16-20
16.4.1. Key Occupational Mobility Studies 16-20
16.4.1.I.Carey (1988) 16-20
16.4.1.2.Carey(1990) 16-21
16.5. POPULATION MOBILITY 16-21
16.5.1. Key Population Mobility Studies 16-21
16.5.1.1. Johnson and Capel (1992) 16-21
16.5.1.2.U.S. Census Bureau (2008a) 16-22
16.5.2. Relevant Population Mobility Studies 16-22
16.5.2.1.Israeli and Nelson (1992) 16-22
16.5.2.2.National Association of Realtors (NAR) (1993) 16-22
16.5.2.3.U.S. Census Bureau (2008b) 16-23
16.6. REFERENCES FOR CHAPTER 16 16-23
Table 16-1. Recommended Values for Activity Patterns 16-3
Table 16-2. Confidence in Recommendations for Activity Patterns 16-6
Table 16-3. Recommended Values for Occupational Mobility 16-7
Table 16-4. Confidence in Recommendations for Occupational Mobility 16-8
Table 16-5. Recommended Values for Population Mobility 16-9
Table 16-6. Confidence in Recommendations for Population Mobility 16-10
Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, for All Respondents and Doers 16-26
Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, by Age and Sex 16-27
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, Grouped by Seasons and Regions 16-28
Table 16-10. Time (minutes/day) Children Under 12 Years of Age Spent in 6 Major Location
Categories, for All Respondents and Doers 16-28
Table 16-11. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 6 Location
Categories, Grouped by Age and Sex 16-29
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Table 16-12. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 6 Location
Categories, Grouped by Season and Region 16-30
Table 16-13. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Proximity to
2 Potential Sources of Exposure, Grouped by All Respondents, Age, and Sex 16-30
Table 16-14. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
Grouped by Age and Sex 16-31
Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only, Children <21 years 16-32
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined,
Doers Only 16-35
Table 16-17. Time Spent (minutes/day) at Selected Indoor Locations Whole Population and Doers
Only, Children <21 years 16-43
Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only 16-44
Table 16-19. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population and Doers
Only, Children <21 years 16-51
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only 16-52
Table 16-21. Mean Time Spent (minutes/day) Inside and Outside, by Age Category, Children
<21 years 16-58
Table 16-22. Mean Time Spent (minutes/day) Outside and Inside, Adults 18 Years and Older, Doers
Only 16-58
Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined Whole
Population and Doers Only, Children <21 Years 16-59
Table 16-24. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined, Doers Only 16-61
Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only,
Children <21 Years 16-65
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only 16-68
Table 16-27. Number of Showers Taken per Day, by Children <21 Years 16-79
Table 16-28. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately After Bathing
and Showering, Children <21 Years 16-80
Table 16-29. Mean Time Spent (minutes/day) and Bathing/Showering, Adults 18 Years and Older,
Doers Only 16-81
Table 16-30. Number of Times Respondent Took Shower or Bathed, Doers Only 16-82
Table 16-31. Time Spent (minutes/day) Bathing and Showering, Doers Only 16-84
Table 16-32. Number of Times Washing the Hands at Specified Daily Frequencies, Children
<21 Years 16-85
Table 16-33. Number of Times Washing the Hands at Specified Daily Frequencies, Doers Only 16-86
Table 16-34. Number of Times Swimming in a Month in Freshwater Swimming Pool, Children
<21 Years 16-87
Table 16-35. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool, Children
<21 Years 16-87
Table 16-36. Number of Times Swimming in a Month in Freshwater Swimming Pool, Doers Only 16-88
Table 16-37. Time Spent (minutes/month) in Freshwater Swimming Pool, Doers Only 16-90
Table 16-38. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population and
Doers only, Children <21 Years 16-91
Table 16-39. Number of Minutes Spent Playing on Selected Outdoor Surfaces (minutes/day), Doers
Only 16-92
Table 16-40. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Children
<21 Years 16-95
Table 16-41. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Doers Only 16-96
Table 16-42. Time Spent (minutes/day) with Smokers Present, Children <21 Years 16-97
Table 16-43. Time Spent (minutes/day) with Smokers Present, Doers Only 16-98
Table 16-44. Mean Time Spent (hours/week) a in Ten Major Activity Categories Grouped by Regions 16-99
Table 16-45. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by
Type of Day 16-99
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Table 16-46. Mean Time Spent (minutes/day) in Ten Major Activity Categories During 4 Waves of
Interviews 16-100
Table 16-47. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Sex 16-100
Table 16-48. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of
Day 16-101
Table 16-49. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for 5 Different Age
Groups 16-102
Table 16-50. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week 16-103
Table 16-51. Mean Time Spent (minutes/day) in Various Microenvironments by Age Group (years) for
the National and California Surveys 16-104
Table 16-52. Mean Time Spent in Ten Major Activity Categories Grouped by Total Sample and Sex
for the CARB and National Studies (age 18-64 years) 16-105
Table 16-53. Total Mean Time Spent at 3 Major Locations Grouped by Total Sample and Sex for the
CARB and National Study (age 18-64 years) 16-105
Table 16-54. Mean Time Spent at 3 Locations for both CARB and National Studies (ages 12 years and
older) 16-106
Table 16-55. Sample Sizes for Sex and Age Groups 16-106
Table 16-56. Assignment of At Home Activities to Inhalation Rate Levels for All Individuals 16-107
Table 16-57. Aggregate Time Spent (minutes/day) At Home in Activity Groups 16-108
Table 16-58. Comparison of Mean Time Spent (minutes/day) At Home, by Sex 16-108
Table 16-59. Comparison of Mean Time Spent (minutes/day) At Home, by Sex and Age for Children 16-109
Table 16-60. Number of Person-Days/Individuals for Children Less than 12 Years in CHAD Database.... 16-109
Table 16-61. Time Spent (hours/day) in Various Microenvironments, by Age 16-110
Table 16-62. Mean Time Children Spent (hours/day) Doing Various Macroactivities While Indoors at
Home 16-110
Table 16-63. Time Children Spent (hours/day) in Various Microenvironments, by Age Recast into
New Standard Age Categories 16-111
Table 16-64. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
Recast Into New Standard Age Categories 16-111
Table 16-65. Number and Percentage of Respondents with Children and Those Reporting Outdoor
Playa Activities in Both Warm and Cold Weather 16-112
Table 16-66. Play Frequency and Duration for All Child Players (from SCS-II data) 16-112
Table 16-67. Hand Washing and Bathing Frequency for all Child Players (from SCS-II data) 16-112
Table 16-68. NHAPS and SCS-II Play Duration Comparison (Children Only) 16-113
Table 16-69. NHAPS and SCS-II Hand Wash Frequency Comparison (Children only) 16-113
Table 16-70. Time Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only) 16-114
Table 16-71. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Sex and Age
Cohort (Doers Only) 16-115
Table 16-72. Time Spent (minutes/day) Indoors Based on CHAD Data (Doers Only) 16-116
Table 16-73. Time Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only) 16-117
Table 16-74. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday
(Children Only) 16-118
Table 16-75. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day
(Children Only) 16-119
Table 16-76. Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to
17 Years 16-120
Table 16-77. Time Spent (minutes/2-day period) in Various Activities by Children Participating in the
Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement (CDS) 16-121
Table 16-78. Annual Average Time Spent (hours/day) on Various Activities According to Age, Race,
Ethnicity, Marital Status, and Educational Level (Ages 15 Years and Over) 16-122
Table 16-79. Annual Average Time Use by the U.S. Civilian Population, Ages 15 Years and Older 16-123
Table 16-80. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years 16-124
Table 16-81. Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity (Children
Only) 16-125
Table 16-82. Occupational Tenure of Employed Individuals by Age and Sex 16-125
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Table 16-83. Occupational Tenure for Employed Individuals Grouped by Sex and Race 16-126
Table 16-84. Occupational Tenure for Employed Individuals Grouped by Sex and Employment Status 16-126
Table 16-85. Occupational Tenure of Employed Individuals Grouped by Major Occupational Groups
and Age 16-126
Table 16-86. Voluntary Occupational Mobility Rates for Workers Age 16 Years and Older 16-127
Table 16-87. Descriptive Statistics for Residential Occupancy Period (years) 16-128
Table 16-88. Descriptive Statistics for Both Sexes by Current Age 16-129
Table 16-89. Residence Time of Owner/Renter Occupied Units 16-130
Table 16-90. Percent of Householders Living in Houses for Specified Ranges of Time, and Statistics
for Years Lived in Current Home 16-130
Table 16-91. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group
in Survey 16-131
Table 16-92. Total Residence Time, T (years), Corresponding to Selected Values of R(t) by Housing
Category 16-131
Table 16-93. Summary of Residence Time of Recent Ho me Buyers (1993) 16-132
Table 16-94. Tenure in Previous Home (percentage distribution) 16-132
Table 16-95. Number of Miles Moved (percentage distribution) 16-132
Table 16-96. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational
Attainment, Marital Status, Nativity, Tenure, and Poverty Level: 2006 to 2007 (numbers
in thousands) 16-133
Table 16-97. Distance of Intercounty Move, by Sex, Age, Race and Hispanic Origin, Educational
Attainment, Marital Status, Nativity, Tenure, Poverty Status, Reason for Move, and State
of Residence 1 Year Ago: 2006 to 2007 16-135
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17.
CONSUMER PRODUCTS.
17.1. INTRODUCTION
17.1.1. Background
17.1.2. Additional Sources of Information.
17.2. RECOMMENDATIONS
17.3. CONSUMER PRODUCTS USE STUDIES.
17.3.1. CTFA(1983)
17.3.2. Westat (1987a)
17.3.3. Westat (1987b)
17.3.4. Westat (1987c)
17.3.5. Abt(1992)
17.3.6. U.S. EPA(1996)
17.3.7. Bass et al. (2001)
17.3.8. Weegels and van Veen (2001)
17.3.9. Loretz et al. (2005)
17.3.10. Loretz et al. (2006)
17.3.11. Halletal. (2007)
17.3.12. Loretz et al. (2008)
17.3.13. Sathyanarayana et al. (2008)
17.4. REFERENCES FOR CHAPTER 17
.17-1
.17-1
.17-1
.17-1
.17-2
.17-2
.17-2
.17-2
.17-3
.17-4
.17-4
.17-5
.17-6
.17-6
.17-6
.17-7
.17-7
.17-8
.17-8
.17-8
Table 17-1. Consumer Products Commonly Found in Some U.S. Households
Table 17-2. List of Product Categories in the Simmons Study of Media and Markets
Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products
Table 17-4. Frequency of Use for Household Solvent Products (users only)
Table 17-5. Exposure Time of Use for Household Solvent Products (users only)
Table 17-6. Amount of Products Used for Household Solvent Products (users only)
Table 17-7. Time Exposed After Duration of Use for Household Solvent Products (users only)
Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household
Cleaning Products
Table 17-9. Percentile Rankings for Total Exposure Time in Performing Household Tasks
Table 17-10. Mean Percentile Rankings for Frequency of Performing Household Tasks
Table 17-11. Mean and Percentile Rankings for Exposure Time per Event of Performing Household
Tasks
Table 17-12. Total Exposure Time for Ten Product Groups Most Frequently Used for Household
Cleaning
Table 17-13. Total Exposure Time of Painting Activity of Interior Painters (hours)
Table 17-14. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of
Occasions Spent Painting per Year
Table 17-15. Amount of Paint Used by Interior Painters
Table 17-16. Frequency of Use and Amount of Product Used for Adhesive Removers
Table 17-17. Adhesive Remover Usage by Sex
Table 17-18. Frequency of Use and Amount of Product Used for Spray Paint
Table 17-19. Spray Paint Usage by Sex
Table 17-20. Frequency of Use and Amount of Product Used for Paint Removers/Strippers
Table 17-21. Paint Stripper Usage by Sex
Table 17-22. Number of Minutes Spent Using Any Microwave Oven (minutes/day)
Table 17-23. Number of Minutes Spent in Activities Working With or Near Freshly Applied Paints
(minutes/day)
Table 17-24. Number of Minutes Spent in Activities Working With or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day)
Table 17-25. Number of Minutes Spent in Activities (at home or elsewhere) Working with or Near
Floorwax, Furniture Wax, or Shoe Polish (minutes/day)
.17-10
.17-12
.17-13
.17-16
.17-17
.17-18
.17-19
.17-20
.17-22
.17-23
.17-24
.17-24
.17-25
.17-25
.17-25
.17-26
.17-26
.17-27
.17-27
.17-28
.17-28
.17-29
.17-29
.17-29
.17-30
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Table 17-26. Number of Minutes Spent in Activities Working with or Near Glue (minutes/day) 17-30
Table 17-27. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes, or Strong
Smelling Chemicals (minutes/day) 17-30
Table 17-28. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers
(minutes/day) 17-31
Table 17-29. Number of Minutes Spent in Activities Working with or Near Gasoline or Diesel-
Powered Equipment, Besides Automobiles (minutes/day) 17-31
Table 17-30. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug
Sprays or Bug Strips (minutes/day) 17-31
Table 17-31. Number of Respondents Using Cologne, Perfume, Aftershave, or Other Fragrances at
Specified Daily Frequencies 17-32
Table 17-32. Number of Respondents Using Any Aerosol Spray Product or Personal Care Item Such
as Deodorant or Hair Spray at Specified Daily Frequencies 17-32
Table 17-33. Number of Respondents Using a Humidifier at Home 17-32
Table 17-34. Number of Respondents Indicating Pesticides Were Applied by a Professional at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-33
Table 17-35. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-33
Table 17-36. Household Demographics and Pesticide Types, Characteristics, and Frequency of
Pesticide Use 17-34
Table 17-37. Amount and Frequency of Use of Household Products 17-35
Table 17-38. Frequency of Use of Cosmetic Products 17-36
Table 17-39. Amount of Test Product Used (grams) for Lipstick, Body Lotion, and Face Cream 17-37
Table 17-40. Frequency of Use of Personal Care Products 17-39
Table 17-41. Average Amount of Product Applied per Application (grams) 17-40
Table 17-42. Average Amount of Product Applied per Use Day (grams) 17-41
Table 17-43. Body Lotion Exposure for Consumers Only (male and female) 17-42
Table 17-44. Deodorant/Antiperspirant Spray Exposure for Consumers Only (male and
female)—Under Arms Only 17-43
Table 17-45. Deodorant/Antiperspirant Spray Exposure for Consumers Only (male and female) Using
Product Over Torso and Under Arms 17-44
Table 17-46. Deodorant/Antiperspirant Non-Spray for Consumers Only (male and female) 17-45
Table 17-47. Lipstick Exposure for Consumers Only (female) 17-46
Table 17-48. Facial Moisturizer Exposure for Consumers Only (male and female) 17-47
Table 17-49. Shampoo Exposure for Consumers Only (male and female) 17-48
Table 17-50. Toothpaste Exposure for Consumers Only (male and female) 17-49
Table 17-51. Average Number of Applications per Use Day 17-50
Table 17-52. Average Amount of Product Applied per Use Day (grams) 17-51
Table 17-53. Average Amount of Product Applied per Application (grams) 17-52
Table 17-54. Characteristics of the Study Population and the Percentage Using Selected Baby Care
Products 17-53
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18. LIFETIME 18-1
18.1. INTRODUCTION 18-1
18.2. RECOMMENDATIONS 18-1
18.3. KEY LIFETIME STUDY 18-3
18.3.1. Xuetal. (2010) 18-3
18.4. RELEVANT LIFETIME STUDY 18-3
18.4.1. U.S. Census Bureau (2008) 18-3
18.5. REFERENCES FOR CHAPTER 18 18-3
Table 18-1. Recommended Values for Expectation of Life at Birth: 2007 18-1
Table 18-2. Confidence in Lifetime Expectancy Recommendations 18-2
Table 18-3. Expectation of Life at Birth, 1970 to 2007 (years) 18-4
Table 18-4. Expectation of Life by Race, Sex, and Age: 2007 18-5
Table 18-5. Projected Life Expectancy at Birth by Sex, Race, and Hispanic Origin for the United
States: 2010 to 2050 18-6
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19. BUILDING CHARACTERISTICS 19-1
19.1. INTRODUCTION 19-1
19.2. RECOMMENDATIONS 19-2
19.3. RESIDENTIAL BUILDING CHARACTERISTICS STUDIES 19-9
19.3.1. Key Study of Volumes of Residences 19-9
19.3.1.1.U.S. DOE (2008a) 19-9
19.3.2. Relevant Studies of Volumes of Residences 19-9
19.3.2.1. Versar (1990) 19-9
19.3.2.2.Murray (1996) 19-9
19.3.2.3.U.S. Census Bureau (2010) 19-10
19.3.3. Other Factors 19-10
19.3.3.1. Surface Area and Room Volumes 19-10
19.3.3.2.Products and Materials 19-10
19.3.3.3.Loading Ratios 19-11
19.3.3.4.Mechanical System Configurations 19-11
19.3.3.5.Type of Foundation 19-12
19.3.3.5.1. Lucas etal. (1992) 19-12
19.3.3.5.2. U.S. DOE (2008a) 19-13
19.4. NON-RESIDENTIAL BUILDING CHARACTERISTICS STUDIES 19-13
19.4.1. U.S. DOE (2008b) 19-13
19.5. TRANSPORT RATE STUDIES 19-14
19.5.1. Air Exchange Rates 19-14
19.5.1.1. Key Study of Residential Air Exchange Rates 19-15
19.5.1.1.1. Koontz and Rector (1995) 19-15
19.5.1.2. Relevant Studies of Residential Air Exchange Rates 19-15
19.5.1.2.1. Nazaroff etal. (1988) 19-15
19.5.1.2.2. Versar (1990) 19-15
19.5.1.2.3. Murray and Burmaster( 1995) 19-16
19.5.1.2.4. Diamond etal. (1996) 19-16
19.5.1.2.5. Graham et al. (2004) 19-16
19.5.1.2.6. Price et al. (2006) 19-16
19.5.1.2.7. Yamamoto etal. (2010) 19-17
19.5.1.3. Key Study of Non-Residential Air Exchange Rates 19-17
19.5.1.3.1. Turk etal. (1987) 19-17
19.5.2. Indoor Air Models 19-17
19.5.3. Infiltration Models 19-18
19.5.4. Vapor Intrusion 19-19
19.5.5. Deposition and Filtration 19-19
19.5.5.1.Deposition 19-19
19.5.5.1.1. Thatcher and Layton( 1995) 19-20
19.5.5.1.2. Wallace (1996) 19-20
19.5.5.1.3. Thatcher et al. (2002) 19-20
19.5.5.1.4. He et al. (2005) 19-20
19.5.5.2.Filtration 19-20
19.5.6. Interzonal Airflows 19-20
19.5.7. House Dust and Soil Loadings 19-21
19.5.7.I.Roberts etal. (1991) 19-21
19.5.7.2. Thatcher and Layton (1995) 19-21
19.6. CHARACTERIZING INDOOR SOURCES 19-21
19.6.1. Source Descriptions for Airborne Contaminants 19-22
19.6.2. Source Descriptions for Waterborne Contaminants 19-23
19.6.3. Soil and House Dust Sources 19-24
19.7. ADVANCED CONCEPTS 19-24
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19.7.1. Uniform Mixing Assumption 19-24
19.7.2. Reversible Sinks 19-24
19.8. REFERENCES FOR CHAPTER 19 19-25
Table 19-1. Summary of Recommended Values for Residential Building Parameters 19-3
Table 19-2. Confidence in Residential Volume Recommendations 19-4
Table 19-3. Summary of Recommended Values for Non-Residential Building Parameters 19-5
Table 19-4. Confidence in Non-Residential Volume Recommendations 19-6
Table 19-5. Confidence in Air Exchange Rate Recommendations for Residential and Non-Residential
Buildings 19-7
Table 19-6. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership 19-31
Table 19-7. Residential Volumes in Relation to Year of Construction 19-31
Table 19-8. Summary of Residential Volume Distributions Based on U.S. DOE (2008a) 19-32
Table 19-9. Summary of Residential Volume Distributions Based on Versar( 1990) 19-32
Table 19-10. Number of Residential Single Detached and Mobile Homes by Volume 19-33
Table 19-11. Dimensional Quantities for Residential Rooms 19-33
Table 19-12. Examples of Products and Materials Associated with Floor and Wall Surfaces in
Residences 19-34
Table 19-13. Residential Heating Characteristics by U.S. Census Region 19-35
Table 19-14. Residential Heating Characteristics by Urban/Rural Location 19-36
Table 19-15. Residential Air Conditioning Characteristics by U.S. Census Region 19-37
Table 19-16. Percent of Residences with Basement, by Census Region and U.S. EPA Region 19-37
Table 19-17. Percent of Residences with Basement, by Census Region 19-38
Table 19-18. States Associated with U.S. EPA Regions and Census Regions 19-39
Table 19-19. Percent of Residences with Certain Foundation Types by Census Region 19-40
Table 19-20. Average Estimated Volumes of U.S. Commercial Buildings, by Primary Activity 19-41
Table 19-21. Non-Residential Buildings: Hours Per Week Open and Number of Employees 19-42
Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings 19-43
Table 19-23. Non-Residential Air Conditioning Energy Sources for Non-Mall Buildings 19-45
Table 19-24. Summary Statistics for Residential Air Exchange Rates (in ACH), by Region 19-46
Table 19-25. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database 19-47
Table 19-26. Distributions of Residential Air Exchange Rates (in ACH) by Climate Region and Season 19-48
Table 19-27. Air Exchange Rates in Commercial Buildings by Building Type 19-48
Table 19-28. Statistics of Estimated Normalized Leakage Distribution Weighted for All Dwellings in
the United States 19-49
Table 19-29. Particle Deposition During Normal Activities 19-49
Table 19-30. Deposition Rates for Indoor Particles 19-49
Table 19-31. Measured Deposition Loss Rate Coefficients 19-50
Table 19-32. Total Dust Loading for Carpeted Areas 19-50
Table 19-33. Particle Deposition and Resuspension During Normal Activities 19-51
Table 19-34. Dust Mass Loading after 1 Week without Vacuum Cleaning 19-51
Table 19-35. Simplified Source Descriptions for Airborne Contaminants 19-52
Figure 19-1. Elements of Residential Exposure 19-53
Figure 19-2. Configuration for Residential Forced-Air Systems 19-53
Figure 19-3. Idealized Patterns of Particle Deposition Indoors 19-54
Figure 19-4. Air Flows for Multiple-Zone Systems 19-55
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Front Matter
ACRONYMS AND ABBREVIATIONS
AAP = American Academy of Pediatrics
ACH = Air Changes per Hour
ADAFs = Age Dependent Adjustment Factors
ADD = Average Daily Dose
AF = Adherence Factor
AHS = American Housing Survey
AIR = Acid Insoluble Residue
API = Asian and Pacific Islander
ASHRAE = American Society of Heating, Refrigeration, and Air Conditioning Engineers
ASTM = American Society for Testing and Materials
ARS = Agricultural Research Service
ASCII = American Standard Code for Information Interchange
ATD = Arizona Test Dust
ATSDR = Agency for Toxic Substances and Disease Registry
ATUS = American Time Use Survey
BI = Bootstrap Interval
BMD = Benchmark Dose
BMI = Body Mass Index
BMR = Basal Metabolic Rate
BTM = Best Tracer Method
BW = Body Weight
C = Concentration
CATI = Computer-Assisted Telephone Interviewing
CDC = Centers for Disease Control and Prevention
CDF A = California Department of Food and Drugs
CDS = Child Development Supplement
CHAD = Consolidated Human Activity Database
CI = Confidence Interval
cm2 = Square Centimeter
cm3 = Cubic Centimeter
CNRC = Children's Nutrition Research Center
CRITFC = Columbia River Inter-Tribal Fish Commission
CSFII = Continuing Survey of Food Intake by Individuals
CT = Central Tendency
CTFA = Cosmetic, Toiletry, and Fragrance Association
CV = Coefficient of Variation
DAF = Dosimetry Adjustment Factor
DARLING = Davis Area Research on Lactation, Infant Nutrition and Growth
DHHS = Department of Health and Human Services
DIR = Daily Inhalation Rate
DIY = Do-It-Yourself
DK = Respondent Replied "Don't Know"
DLW = Doubly Labeled Water
DOE = Department of Energy
DONALD = Dortmund Nutritional and Anthropometric Longitudinally Designed
E or EE = Energy Expenditure
EBF = Exclusively Breastfed
ECG = Energy Cost of Growth
ED = Exposure Duration
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Front Matter
ACRONYMS AND ABBREVIATIONS (continued)
EFAST
El
EPA
ERV
EVR
F
fc
FCID
FITS
F/S
g
GAP
GM
GSD
H
HEC
HR
HRV
USHUD
I
L
I-BEAM
ICRP
IEUBK
IPS
IOM
IPCS
IR
IRIS
IUR
Kcal
KJ
K-S
kg
L
Li
L2
LADD
LCL
LTM
m2
nr
MCCEM
MEC
mg
MJ
mL
METS
MOA
MSA
MVPA
Exposure and Fate Assessment Screening Tool
Energy Intake
Environmental Protection Agency
Energy Recovery Ventilator
Equivalent Ventilation Rate
Fahrenheit
Breathing Frequency
Food Commodity Intake Database
Feeding Infant and Toddler Study
Food/Soil
Gram
General Assessment Factor
Geometric Mean
Geometric Standard Deviation
Oxygen Uptake Factor
Human Equivalent Exposure Concentrations
Heart Rate
Heat Recovery Ventilator
United States Department of Housing and Urban Development
Tabulated Intake Rate
Adjusted Intake Rate
Indoor Air Quality Building and Assessment Model
International Commission on Radiological Protection
Integrated Exposure and Uptake Biokinetic Model
Iowa Fluoride Study
Institute of Medicine
International Programme on Chemical Safety
Intake Rate/Inhalation Rate
Integrated Risk Information System
Inhalation Unit Risk
Kilocalories
Kilo Joules
Kolmogorov-Smirnov
Kilogram
Liter
Cooking or Preparation Loss
Post-cooking Loss
Lifetime Average Daily Dose
Lower Confidence Limit
Limiting Tracer Method
Square Meter
Cubic Meter
Multi-Chamber Concentration and Exposure Model
Mobile Examination Center
Milligram
Mega Joules
Milliliter
Metabolic Equivalents of Work
Mode of Action
Metropolitan Statistical Area
Moderate-to-Vigorous Physical Activity
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Front Matter
N
Number of Subjects or Respondents
ACRONYMS AND ABBREVIATIONS (continued)
Nc = Weighted Number of Individuals Consuming Homegrown Food Item
NT = Weighted Total Number of Individuals Surveyed
NAS = National Academy of Sciences
NCEA = National Center for Environmental Assessment
NCHS = National Center for Health Statistics
NERL = National Exposure Research Laboratory
NFCS = Nationwide Food Consumption Survey
NHANES = National Health and Nutrition Examination Survey
NHAPS = National Human Activity Pattern Survey
NHES = National Health Examination Survey
NIS = National Immunization Survey
NLO = Non-Linear Optimization
NMFS = National Marine Fisheries Service
NOAEL = No-Observed-Adverse-Effect-Level
NOPES = Non-Occupational Pesticide Exposure Study
NR = Not Reported
NRC = National Research Council
NS = No Statistical Difference
OPP = Office of Pesticide Programs
ORD = Office of Research and Development
PBPK = Physiologically-Based Pharmacokinetic
PC = Percent Consuming
PDIR = Physiological Daily Inhalation Rate
PFT = Perfluorocarbon Tracer
PSID = Panel Study of Income Dynamics
PTEAM = Particle Total Exposure Assessment Methodology
RAGS = Risk Assessment Guidance for Superfund
ROD = Random Digit Dial
RECS = Residential Energy Conservation Survey
RfD = Reference Dose
RfC = Reference Concentration
ROP = Residential Occupancy Period
RTF = Ready to Feed
SA = Surface Area
SA/BW = Surface Area to Body Weight Ratio
SAS = Statistical Analysis Software
SCS = Soil Contact Survey
SD = Standard Deviation
SDA = Soaps and Detergent Association
SE = Standard Error
SEM = Standard Error of the Mean
SES = Socioeconomic Status
SHEDS = Stochastic Human Exposure and Dose Simulation Model
SMBRP = Santa Monica Bay Restoration Project
SMRB = Simmons Market Research Bureau
SOCAL = Southern California
SPS = Statistical Processing System
t = Exposure Time
TDEE = Total Daily Energy Expenditure
TRF = Tuna Research Foundation
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Front Matter
ACRONYMS AND ABBREVIATIONS (continued)
UCL = Upper Confidence Limit
USDA = United States Department of Agriculture
USDL = United States Department of Labor
VE = Volume of Air Breathed per Day
VCh = Oxygen Consumption Rate
VOC = Volatile Organic Compounds
VQ = Ventilatory Equivalent
VR = Ventilation Rate
VT = Tidal Volume
WHO = World Health Organization
WIC = USDA's Women, Infants, and Children Program
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Exposure Factors Handbook
Chapter 1—Introduction
TABLE OF CONTENTS
LIST OF TABLES 1-ii
LIST OF FIGURES 1-ii
1. INTRODUCTION 1-3
1.1. BACKGROUND AND PURPOSE 1-3
1.2. INTENDED AUDIENCE 1-3
1.3. SCOPE 1-3
1.4. UPDATES TO PREVIOUS VERSIONS OF THE HANDBOOK 1-4
1.5. SELECTION OF STUDIES FOR THE HANDBOOK AND DATA PRESENTATION 1-4
1.5.1. General Assessment Factors 1-5
1.5.2. Selection Criteria 1-5
1.6. APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
FACTORS 1-7
1.7. SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS
HANDBOOK 1-9
1.8. THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE 1-10
1.9. CONSIDERING LIFE STAGE WHEN CALCULATING EXPOSURE AND RISK 1-11
1.10. FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT 1-13
1.10.1. Exposure and Dose Equations 1-15
1.10.2. Use of Exposure Factors Data in Probabilistic Analyses 1-17
1.11. AGGREGATE AND CUMULATIVE EXPOSURES 1-18
1.12. ORGANIZATION OF THE HANDBOOK 1-19
1.13. REFERENCES FOR CHAPTER 1 1-20
APPENDIX 1A RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND
DOSE-RESPONSE INFORMATION FROM THE INTEGRATED RISK INFORMATION
SYSTEM (IRIS) 1A-1
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Exposure Factors Handbook
Chapter 1—Introduction
LIST OF TABLES
Table 1-1. Availability of Various Exposure Metrics in Exposure Factors Data 1-27
Table 1-2. Criteria Used to Rate Confidence in Recommended Values 1-28
Table 1 -3. Age-Dependent Potency Adjustment Factor by Age Group for Mutagenic Carcinogens 1-29
LIST OF FIGURES
Figure 1-1. Conceptual Drawing of Exposure and Dose Relationship (Zartarian et al., 2007) 1-13
Figure 1-2. Exposure-Dose-Effect Continuum 1-30
Figure 1-3. Schematic Diagram of Exposure Pathways, Factors, and Routes 1-31
Figure 1-4. Road map to Exposure Factor Recommendations 1-32
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Exposure Factors Handbook
Chapter 1—Introduction
1. INTRODUCTION exposure/risk assessors with recommended values for
1.1. BACKGROUND AND PURPOSE theSC fff^f ^ SH"** t0 ^ eXP°SUre
among both adults and children.
Some of the steps for performing an exposure
assessment are (1) identifying the source of the 1.2. INTENDED AUDIENCE
environmental contamination and the media that ™ ^ „ , „ „ , . . , , , ,,
, . ... , . . , The Exposure r actors Handbook is intended for
transports the contaminant; (2) determining the , , . , , ., ... . ,
. • A; j • • i, use by exposure and nsk assessors both within and
contaminant concentration; (3) determining the . ., ., TT 0 T^A c *. \ * •
, ' ^ ' , 5 - outside the U.S. EPA as a reference tool and primary
exposure scenarios, and pathways and routes of ,- r- , • r- ,• Ti u j
F ,,,,/..,, f source of exposure factor information. It may be used
exposure; (4) determining the exposure factors , . .. . . . , ., . . . ,
, t , 1 / , , . ,.,-• • by scientists, economists, and other interested parties
related to human behaviors that define time, f ^ ± J/TTO T-T^A j +•
. , , . . , ' as a source of data and/or U.S. EPA recommendations
frequency, and duration of exposure; and (5) . ,- . \, • * j
., \... /' ., , i *• -V f <. on numenc estimates for behavioral and
identifying the exposed population. Exposure factors , . , . , , . . .. jJt t-t
/ ° i ^ j : i it- j physiological charactenstics needed to estimate
are factors related to human behavior and . . . ,
, ^ . ^. „ , , , exposure to environmental agents.
charactenstics that help
determine an individual's Exposure factors are factors related to 13 SCOpE
exposure to an agent. The human behavior wd characteristics that help
National Academy of deterrnine an individuars exposure to an This handbook incorporates
Sciences (NAS) report on agent the changes in nsk assessment
Risk Assessment in the
Federal Government:
J practices that were first presented
• __ ,1 T T O T7Ti A ' _ /~< , _ —
in the U.S. EPA's Cancer
Managing the Process and Guidelines, regarding the need to
subsequent publication of the U.S. Environmental consider life stages rather than subpopulations (U.S.
Protection Agency's (EPA) exposure guidelines in EPA, 2005a, b). A life stage "refers to a
1986 identified the need for summarizing exposure distinguishable time frame in an individual's life
factors data necessary for characterizing some of the characterized by unique and relatively stable
steps outlined above (NAS, 1983; U.S. EPA, 1986a). behavioral and/or physiological characteristics that
Around the same time, the U.S. EPA published a are associated with development and growth"
report entitled Development of Statistical (U.S. EPA, 2005c). The handbook emphasizes a
Distributions or Ranges of Standard Factors Used in major recommendation in U.S. EPA's Supplemental
Exposure Assessment to support the 1986 exposure Guidance for Assessing Susceptibility from Early-Life
guidelines and to promote consistency in U.S. EPA's Exposure to Carcinogens (U.S. EPA, 2005b) to sum
exposure assessment activities (U.S. EPA, 1985). The exposures and risks across life stages rather than
exposure assessment field relying on the use of a lifetime
continued to evolve and so average adult exposure to
did the need for more Purpose: calculate risk. This handbook also
comprehensive data on (1) summarize data on human behavioral uses updated information to
exposure factors. The and physiological characteristics incorporate any new exposure
Exposure Factors (2) provide exposure/risk assessors with factors data/research that have
recommended values for these factors become available since it was last
revised in 1997 and is consistent
with the U.S. EPA's new set of
Handbook was first
published in 1989 and
updated in 1997 in
response to this need standardized childhood age
(U.S. EPA, 1989a, 1997a). This cunent edition is the groups (U.S. EPA, 2005c), which are recommended
update of the 1997 handbook (U.S. EPA, 1997a), and for use in exposure assessments. Available data
it incorporates data from the Child-Specific Exposure through July 2011 are included in the handbook.
Factors Handbook (U.S. EPA, 2008a) that was The recommendations presented in this
published in September 2008. The information handbook are not legally binding on any U.S. EPA
presented in this handbook supersedes the Child- program and should be interpreted as suggestions that
Specific Exposure Factors Handbook published in program offices or individual exposure assessors can
2008 (U.S. EPA, 2008a). consider and modify as needed. The
The purpose of the Exposure Factors Handbook recommendations provided in this handbook do not
is to (1) summarize data on human behavioral and supersede standards or guidance established by
physiological characteristics that affect exposure to U.S. EPA program offices, states, or other risk
environmental contaminants, and (2) provide assessment organizations outside the Agency (e.g.,
Exposure Factors Handbook Page
September 2011 1-3
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Exposure Factors Handbook
Chapter 1—Introduction
World Health Organization, National Research
Council). Many of these factors are best quantified on
a site- or situation-specific basis. The decision as to
whether to use site-specific or national values for an
assessment may depend on the quality of the
competing data sets as well as on the purpose of the
specific assessment. The handbook has strived to
include full discussions of the issues that assessors
should consider in deciding how to use these data and
recommendations.
This document does not include
chemical-specific data or information on
physiological parameters that may be needed for
exposure assessments involving physiologically
based pharmacokinetic (PBPK) modeling.
Information on the application of PBPK models and
supporting data are found in U.S. EPA (2006a, b).
1.4. UPDATES TO PREVIOUS VERSIONS
OF THE HANDBOOK
All chapters have been revised to include
published literature up to July 2011. Some of the
main revisions are highlighted below:
Added food and water intake data obtained
from the National Health and Nutrition
Examination Survey (NHANES) 2003-2006;
Added fat intake data and total
food intake data;
Added new chapter on non-dietary factors;
Updated soil ingestion rates for
children and adults;
Updated data on dermal exposure and added
information on other factors such as film
thickness of liquids to skin, transfer of
residue, and skin thickness;
Updated fish intake rates for the general
population using data obtained from
NHANES 2003-2006;
Updated body-weight data with National
Health and Nutrition Examination Survey
1999-2006;
Added body-weight data for
pregnant/lactating women and fetal weight;
Updated children's factors with new
recommended age groupings (U.S. EPA,
2005c);
Updated life expectancy data with U.S.
Census Bureau data 2006;
Updated data on human milk ingestion and
prevalence of breast-feeding; and
Expanded residential characteristics chapter to
include data from commercial buildings.
1.5. SELECTION OF STUDIES FOR THE
HANDBOOK AND DATA
PRESENTATION
Many scientific studies were reviewed for
possible inclusion in this handbook. Although
systematic literature searches were initially
conducted for every chapter, much of the literature
was identified through supplementary targeted
searches and from personal communications with
researchers in the various fields. Information in this
handbook has been summarized from studies
documented in the scientific literature and other
publicly available sources. As such, this handbook is
a compilation of data from a variety of different
sources. Most of the data presented in this handbook
are derived from studies that target (1) the general
population (e.g., Center for Disease Control and
Prevention [CDC] NHANES) or (2) a sample
population from a specific area or group (e.g., fish
consumption among Native American children). With
very few exceptions, the data presented are the
analyses of the individual study authors. Since the
studies included in this handbook varied in terms of
their objectives, design, scope, presentation of
results, etc., the level of detail, statistics, and
terminology may vary from study to study and from
factor to factor. For example, some authors used
geometric means to present their results, while others
used arithmetic means or distributions. Authors have
sometimes used different terms to describe the same
racial/ethnic populations. Within the constraint of
presenting the original material as accurately as
possible, the U.S. EPA has made an effort to present
discussions and results in a consistent manner and
using consistent terminology. The strengths and
limitations of each study are discussed to provide the
reader with a better understanding of the uncertainties
associated with the values derived from the study.
If it is necessary to characterize a population that
is not directly covered by the data in this handbook,
the risk or exposure assessor may need to evaluate
whether these data may be used as suitable
substitutes for the population of interest or whether
there is a need to seek additional population-specific
data. If information is needed for identifying and
enumerating populations who may be at risk for
greater contaminant exposures or who exhibit a
heightened sensitivity to particular chemicals, refer to
Socio-demographic Data Used for Identifying
Potentially Highly Exposed Populations (U.S. EPA,
1999).
Studies were chosen that were seen as useful and
appropriate for estimating exposure factors for both
adults and children. In conjunction with the Guidance
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Chapter 1—Introduction
on Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005c), this handbook
adopted the age group notation "X to 21 years old) are presented using the age groups
defined by the authors of the individual studies. No
attempt was made to reanalyze the data using a
consistent set of age groups. Therefore, in cases
where data were analyzed by the U.S. EPA, age
categories were defined as finely as possible based on
adequacy of sample size. It is recognized that adults'
activity patterns will vary with many factors
including age, especially in the older adult
population.
Certain studies described in this handbook are
designated as "key," that is, the most up-to-date and
scientifically sound for deriving recommendations for
exposure factors. The recommended values for all
exposure factors are based on the results of the key
studies (see Section 1.6). Other studies are designated
"relevant," meaning applicable or pertinent, but not
necessarily the most important. As new data or
analyses are published, "key" studies may be moved
to the "relevant" category in future revisions because
they are replaced by more up-to-date data or an
analysis of improved quality. Studies may be
classified as "relevant" for one or more of the
following reasons: (1) they provide supporting data
(e.g., older studies on food intake that may be useful
for trend analysis); (2) they provide information
related to the factor of interest (e.g., data on
prevalence of breast-feeding); (3) the study design or
approach makes the data less applicable to the
population of interest (e.g., studies with small sample
size, studies not conducted in the United States).
It is important to note that studies were evaluated
based on their ability to represent the population for
which the study was designed. The users of the
handbook will need to evaluate the studies'
applicability to their population of interest.
1.5.1. General Assessment Factors
The Agency recognizes the need to evaluate the
quality and relevance of scientific and technical
information used in support of Agency actions
(U.S. EPA, 2002, 2003a, 2006c). When evaluating
scientific and technical information, the U.S. EPA's
Science Policy Council recommends using five
General Assessment Factors (GAFs): (1) soundness,
(2) applicability and utility, (3) clarity and
completeness, (4) uncertainty and variability, and (5)
evaluation and review (U.S. EPA, 2003a). These
GAFs were adapted and expanded to include specific
considerations deemed to be important during
evaluation of exposure factors data and were used to
judge the quality of the underlying data used to
derive recommendations.
1.5.2. Selection Criteria
The confidence ratings for the various exposure
factor recommendations, and selection of the key
studies that form the basis for these
recommendations, were based on specific criteria
within each of the five GAFs, as follows:
1) Soundness: Scientific and technical
procedures, measures, methods, or models
employed to generate the information are
reasonable for, and consistent with, the
intended application. The soundness of the
experimental procedures or approaches in the
study designs of the available studies was
evaluated according to the following:
a) Adequacy of the Study Approach Used:
In general, more confidence was placed
on experimental procedures or approaches
that more likely or closely captured the
desired measurement. Direct exposure
data collection techniques, such as direct
observation, personal monitoring devices,
or other known methods were preferred
where available. If studies utilizing direct
measurement were not available, studies
were selected that relied on validated
indirect measurement methods such as
surrogate measures (such as heart rate for
inhalation rate), and use of questionnaires.
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Chapter 1—Introduction
If questionnaires or surveys were used,
proper design and procedures include an
adequate sample size for the population
under consideration, a response rate large
enough to avoid biases, and avoidance of
bias in the design of the instrument and
interpretation of the results. More
confidence was placed in exposure factors
that relied on studies that gave appropriate
consideration to these study design issues.
Studies were also deemed preferable if
based on primary data, but studies based
on secondary sources were also included
where they offered an original analysis. In
general, higher confidence was placed on
exposure factors based on primary data.
b) Minimal (or Defined) Bias in Study
Design: Studies were sought that were
designed with minimal bias, or at least if
biases were suspected to be present, the
direction of the bias (i.e., an overestimate
or underestimate of the parameter) was
either stated or apparent from the study
design. More confidence was placed on
exposure factors based on studies that
minimized bias.
2) Applicability and Utility: The information is
relevant for the Agency's intended use. The
applicability and utility of the available
studies were evaluated based on the following
criteria:
a) Focus on Exposure Factor of Interest:
Studies were preferred that directly
addressed the exposure factor of interest
or addressed related factors that have
significance for the factor under
consideration. As an example of the latter
case, a selected study contained useful
ancillary information concerning fat
content in fish, although it did not directly
address fish consumption.
b) Representativeness of the Population:
More confidence was placed in studies
that addressed the U.S. population. Data
from populations outside the United
States were sometimes included if
behavioral patterns or other characteristics
of exposure were similar. Studies seeking
to characterize a particular region or
demographic characteristic were selected,
if appropriately representative of that
population. In cases where data were
limited, studies with limitations in this
area were included, and limitations were
noted in the handbook. Higher confidence
ratings were given to exposure factors
where the available data were
representative of the population of
interest. The risk or exposure assessor
may need to evaluate whether these data
may be used as suitable substitutes for
their population of interest or whether
there is a need to seek additional
population-specific data.
c) Currency of Information: More
confidence was placed in studies that were
sufficiently recent to represent current
exposure conditions. This is an important
consideration for those factors that change
with time. Older data were evaluated and
considered in instances where the
variability of the exposure factor over
time was determined to be insignificant or
unimportant. In some cases, recent data
were very limited. Therefore, the data
provided in these instances were the only
available data. Limitations on the age of
the data were noted. Recent studies are
more likely to use state-of-the-art
methodologies that reflect advances in the
exposure assessment field. Consequently,
exposure factor recommendations based
on current data were given higher
confidence ratings than those based on
older data, except in cases where the age
of the data would not affect the
recommended values.
d) Adequacy of Data Collection Period:
Because most users of the handbook are
primarily addressing chronic exposures,
studies were sought that utilized the most
appropriate techniques for collecting data
to characterize long-term behavior. Higher
confidence ratings were given to exposure
factor recommendations that were based
on an adequate data collection period.
3) Clarity and Completeness: The degree of
clarity and completeness with which the data,
assumptions, methods, quality assurance,
sponsoring organizations and analyses
employed to generate the information is
documented. Clarity and completeness were
evaluated based on the following criteria:
a) Accessibility: Studies that the user could
access in their entirety, if needed, were
preferred.
b) Reproducibilitv: Studies that contained
sufficient information so that methods
could be reproduced, or could be
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evaluated, based on the details of the
author's work, were preferred.
c) Quality Assurance: Studies with
documented quality assurance/quality
control measures were preferred. Higher
confidence ratings were given to exposure
factors that were based on studies where
appropriate quality assurance/quality
control measures were used.
4) Variability and Uncertainty: The variability
and uncertainty (quantitative and qualitative)
in the information or the procedures,
measures, methods, or models are evaluated
and characterized. Variability arises from true
heterogeneity across people, places, or time
and can affect the precision of exposure
estimates and the degree to which they can be
generalized. The types of variability include
spatial, temporal, and inter-individual.
Uncertainty represents a lack of knowledge
about factors affecting exposure or risk and
can lead to inaccurate or biased estimates of
exposure. Increasingly probabilistic methods
are being utilized to analyze variability and
uncertainty independently as well as
simultaneously. It is sometimes challenging to
distinguish between variability and parameter
uncertainty in this context as both can involve
the distributions of a random variable. The
types of uncertainty include scenario,
parameter, and model. More information on
variability and uncertainty is provided in
Chapter 2 of this handbook. The uncertainty
and variability associated with the studies
were evaluated based on the following
criteria:
a) Variability in the Population: Studies
were sought that characterized any
variability within populations. The
variability associated with the
recommended exposure factors is
described in Section 1.6. Higher
confidence ratings were given to exposure
factors that were based on studies where
variability was well characterized.
b) Uncertainty: Studies were sought with
minimal uncertainty in the data, which
was judged by evaluating all the
considerations listed above. Studies were
preferred that identified uncertainties,
such as those due to possible
measurement error. Higher confidence
ratings were given to exposure factors
based on studies where uncertainty had
been minimized.
5) Evaluation and Review: The information or
the procedures, measures, methods, or models
are independently verified, validated, and peer
reviewed. Relevant factors that were
considered included:
a) Peer Review: Studies selected were those
from the peer-reviewed literature and final
government reports. Unpublished and
internal or interim reports were avoided,
where possible, but were used in some
cases to supplement information in
published literature or government
reports.
b) Number and Agreement of Studies:
Higher confidence was placed on
recommendations where data were
available from more than one key study,
and there was good agreement between
studies.
1.6. APPROACH USED TO DEVELOP
RECOMMENDATIONS FOR
EXPOSURE FACTORS
As discussed above, the U.S. EPA first reviewed
the literature pertaining to a factor and determined
key studies. These key studies were used to derive
recommendations for the values of each factor. The
recommended values were derived solely from the
U.S. EPA's interpretation of the available data.
Different values may be appropriate for the user in
consideration of policy, precedent, strategy, or other
factors such as site-specific information. The
U.S. EPA's procedure for developing
recommendations was as follows:
1) Study Review and Evaluation: Key studies
were evaluated in terms of both quality and
relevance to specific populations (general
U.S. population, age groups, sex, etc.).
Section 1.5 describes the criteria for
assessing the quality of studies.
2) Selection of One versus Multiple Key
Studies: If only one study was classified as
key for a particular factor, the mean value
from that study was selected as the
recommended central value for that
population. If multiple key studies with
reasonably equal quality, relevance, and
study design information were available, a
weighted mean (if appropriate, considering
sample size and other statistical factors) of
the studies was chosen as the recommended
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mean value. Recommendations for upper
percentiles, when multiple studies were
available, were calculated as the mid-point of
the range of upper percentile values of the
studies for each age group where data were
available. It is recognized that the mid-point
of the range of upper percentiles may not
provide the best estimate, but in the absence
of raw data, more sophisticated analysis
could not be performed.
3) Assessing Variability: The variability of the
factor across the population is discussed. For
recommended values, as well as for each of
the studies on which the recommendations
are based, variability was characterized in
one or more of three ways: (1) as a table with
various percentiles or ranges of values; (2) as
analytical distributions with specified
parameters; and/or (3) as a qualitative
discussion. Analyses to fit standard or
parametric distributions (e.g., normal,
lognormal) to the exposure data have not
been performed by the authors of this
handbook, but have been reproduced as they
were found in the literature.
Recommendations on the use of these
distributions were made where appropriate
based on the adequacy of the supporting data.
Table 1-1 presents the list of exposure factors
and the way in which variability in the
population has been characterized throughout
this handbook (i.e., average, median, upper
percentiles, multiple percentiles).
In providing recommendations for the
various exposure factors, an attempt was
made to present percentile values that are
consistent with the exposure estimators
defined in Guidelines for Exposure
Assessment (U.S. EPA, 1992a) (i.e., mean,
50th, 90th, 95th, 98th, and 99.9th percentiles).
However, this was not always possible,
because the data available were limited for
some factors, or the authors of the study did
not provide such information. It is important
to note, however, that these percentiles were
discussed in the guidelines within the context
of risk descriptors and not individual
exposure factors. For example, the guidelines
state that the assessor may derive a high-end
estimate of exposure by using maximum or
near maximum values for one or more
sensitive exposure factors, leaving others at
their mean value. The term "upper
percentile" is used throughout this handbook,
and it is intended to represent values in the
upper tail (i.e., between 90tt
and
99.9th percentiles) of the distribution of
values for a particular exposure factor. Tables
providing summaries of recommendations at
the beginning of each chapter generally
present a mean and an upper percentile value.
The 95th percentile was used as the upper
percentile in these tables, if available,
because it is the middle of the range between
the 90th and 99.9th percentiles. Other
percentiles are presented, where available, in
the tables at the end of the chapters. Users of
the handbook should employ the exposure
metric that is most appropriate for their
particular situation.
4) Assessing Uncertainty: Uncertainties are
discussed in terms of data limitations, the
range of circumstances over which the
estimates were (or were not) applicable,
possible biases in the values themselves, a
statement about parameter uncertainties
(measurement error, sampling error), and
model or scenario uncertainties if models or
scenarios were used to derive the
recommended value. A more detailed
discussion of variability and uncertainty for
exposure factors is presented in Chapter 2 of
this handbook.
5) Assigning Confidence Ratings: Finally, the
U.S. EPA assigned a confidence rating of low,
medium, or high to each recommended value
in each chapter. This qualitative rating is not
intended to represent an uncertainty analysis;
rather, it represents the U.S. EPAs judgment
on the quality of the underlying data used to
derive the recommendation. This judgment
was made using the GAFs described in
Section 1.5. Table 1-2 provides an adaptation
of the GAFs, as they pertain to the
confidence ratings for the exposure factor
recommendations. Clearly, there is a
continuum from low to high, and judgment
was used to assign a rating to each factor. It is
important to note that these confidence
ratings are based on the strengths and
limitations of the underlying data and not on
how these data may be used in a particular
exposure assessment.
The study elements listed in Table 1-2 do
not have the same weight when arriving at
the overall confidence rating for the various
exposure factors. The relative weight of each
of these elements for the various factors was
subjective and based on the professional
judgment of the authors of this handbook.
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Also, the relative weights depend on the
exposure factor of interest. For example, the
adequacy of the data collection period may
be more important when determining usual
intake of foods in a population, but it is not as
important for factors where long-term
variability may be small, such as tap water
intake. In the case of tap water intake, the
currency of the data was a critical element in
determining the final rating. In general, most
studies ranked high with regard to "level of
peer review," "accessibility," "focus on the
factor of interest," and "data pertinent to the
United States" because the U.S. EPA
specifically sought studies for the handbook
that met these criteria.
The confidence rating is also a reflection
of the ease at which the exposure factor of
interest could be measured. This is taken into
consideration under the soundness criterion.
For example, soil ingestion by children can
be estimated by measuring, in feces, the
levels of certain elements found in soil. Body
weight, however, can be measured directly,
and it is, therefore, a more reliable
measurement than estimation of soil
ingestion. The fact that soil ingestion is more
difficult to measure than body weight is
reflected in the overall confidence rating
given to both of these factors. In general, the
better the methodology used to measure the
exposure factor, the higher the confidence in
the value.
Some exposure factors recommendations
may have different confidence ratings
depending on the population of interest. For
example a lower confidence rating may be
noted for some age groups for which sample
sizes are small. As another example, a lower
confidence rating was assigned to the
recommendations as they would apply to
long-term chronic exposures versus acute
exposures because of the short-term nature of
the data collection period. To the extent
possible, these caveats were noted in the
confidence rating tables.
6) Recommendation Tables: The U.S. EPA
developed a table at the beginning of each
chapter that summarizes the recommended
values for the relevant factor. Table ES-1 of
the Executive Summary of this handbook
summarizes the principal exposure factors
addressed in this handbook and provides the
confidence ratings for each exposure factor.
1.7. SUGGESTED REFERENCES FOR USE
IN CONJUNCTION WITH THIS
HANDBOOK
Many of the issues related to characterizing
exposure from selected exposure pathways have been
addressed in a number of existing U.S. EPA
documents. Some of these provide guidance while
others demonstrate various aspects of the exposure
process. These include, but are not limited to, the
following references listed in chronological order:
Methods for Assessing Exposure to
Chemical Substances, Volumes 1-13
(U.S. EPA, 1983-1989);
Standard Scenarios for Estimating Exposure
to Chemical Substances During Use of
Consumer Products (U.S. EPA, 1986b);
Selection Criteria for Mathematical Models
Used in Exposure Assessments: Surface
Water Models (U.S. EPA, 1987);
Selection Criteria for Mathematical Models
Used in Exposure Assessments:
Groundwater Models (U.S. EPA, 1988);
Risk Assessment Guidance for Superfund,
Volume I, Part A, Human Health Evaluation
Manual (U.S. EPA, 1989b);
Methodology for Assessing Health Risks
Associated with Indirect Exposure to
Combustor Emissions (U.S. EPA, 1990);
Risk Assessment Guidance for Superfund,
Volume I, Part B, Development of
Preliminary Remediation Goals (U.S. EPA,
1991a);
Risk Assessment Guidance for Superfund,
Volume I, Part C, Risk Evaluation of
Remedial Alternatives (U.S. EPA, 1991b);
Guidelines for Exposure Assessment
(U.S. EPA, 1992a);
Dermal Exposure Assessment: Principles
and Applications (U.S. EPA, 1992b);
Soil Screening Guidance (U.S. EPA, 1996a);
Series 875 Occupational and Residential
Exposure Test Guidelines—Final Guidelines
—Group A—Application Exposure
Monitoring Test Guidelines (U.S. EPA,
1996b);
Series 875 Occupational and Residential
Exposure Test Guidelines—Group B—Post
Application Exposure Monitoring Test
Guidelines (U.S. EPA, 1996c);
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Policy for Use of Probabilistic Analysis in
Risk Assessment at the U.S. Environmental
Protection Agency (U.S. EPA, 1997b);
Guiding Principles for Monte Carlo
Analysis (U.S. EPA, 1997c);
Sociodemographic Data for Identifying
Potentially Highly Exposed Populations
(U.S. EPA, 1999);
Options for Developing Parametric
Probability Distributions for Exposure
Factors (U.S. EPA, 2000a);
Risk Assessment Guidance for Superfund,
Volume I, Part D, Standardized Planning,
Reporting, and Review of Superfund Risk
Assessments (U.S. EPA, 200la);
Risk Assessment Guidance for Superfund
Volume III, Part A, Process for Conducting
Probabilistic Risk Assessments (U.S. EPA,
2001b);
Framework for Cumulative Risk Assessment
(U.S. EPA, 2003b);
Example Exposure Scenarios (U.S. EPA,
2003c);
Exposure and Human Health Reassessment
of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin
(TCDD) and Related Compounds National
Academy Sciences Review Draft (U.S. EPA,
2003d);
Risk Assessment Guidance for Superfund,
Volume I, Part E, Supplemental Guidance
for Dermal Risk Assessment (U.S. EPA,
2004);
Cancer Guidelines for Carcinogen Risk
Assessment (U.S. EPA, 2005a);
Supplemental Guidance for Assessing
Susceptibility from Early-Life Exposure to
Carcinogens (U.S. EPA, 2005b);
Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005c);
Protocol for Human Health Risk Assessment
Hazardous Waste Combustion Facilities
(U.S. EPA, 2005d);
Aging and Toxic Response: Issues Relevant
to Risk Assessment (U.S. EPA, 2005e);
A Framework for Assessing Health Risk of
Environmental Exposures to Children
(U.S. EPA, 2006d);
Dermal Exposure Assessment: A Summary
of EPA Approaches (U.S. EPA, 2007a);
Child-Specific Exposure Factors Handbook
(U.S. EPA, 2008a);
Concepts, Methods, and Data Sources For
Cumulative Health Risk Assessment of
Multiple Chemicals, Exposures and Effects:
A Resource Document (U.S. EPA, 2008b);
Physiological Parameters Database for
Older Adults (Beta 1.1) (U.S. EPA, 2008c);
Risk Assessment Guidance for Superfund
Volume I: Human Health Evaluation
Manual Part F, Supplemental Guidance for
Inhalation Risk Assessment (U.S. EPA,
2009a);
Draft Technical Guidelines Standard
Operating Procedures for Residential
Pesticide Exposure Assessment (U.S. EPA,
2009b);
Stochastic Human Exposure and Dose
Simulation (SHEDS)-Multimedia. Details of
SHEDS-Multimedia Version 3: ORD/NERL's
Model to Estimate Aggregate and
Cumulative Exposures to Chemicals
(U.S. EPA, 2009c); and
Recommended Use of Body Weight3'4 (BW3M)
as the Default Method in Derivation of the
Oral Reference Dose (RfD) (U.S. EPA,
2011).
These documents may serve as valuable
information resources to assist in the assessment of
exposure. Refer to them for more detailed discussion.
1.8. THE USE OF AGE GROUPINGS
WHEN ASSESSING EXPOSURE
When this handbook was published in 1997, no
specific guidance existed with regard to which age
groupings should be used when assessing children's
exposure. Age groupings varied from case to case and
among Program Offices within the U.S. EPA. They
depended on availability of data and were often based
on professional judgment. More recently, the U.S.
EPA has established a consistent set of age groupings
and published guidance on this topic (U.S. EPA,
2005c). This revision of the handbook attempts to
present data in a manner consistent with the U.S.
EPA's recommended set of age groupings for
children. The presentation of data for these fine age
categories does not necessarily mean that every age
category needs to be the subject of a particular
assessment. It will depend on the objectives of the
assessment and communications with toxicologists to
identify the critical windows of susceptibility.
The development of standardized age bins for
children was the subject of discussion in a 2000
workshop sponsored by the U.S. EPA Risk
Assessment Forum. The workshop was titled Issues
Associated with Considering Developmental Changes
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in Behavior and Anatomy When Assessing Exposure
to Children (U.S. EPA, 2000b). The purpose of this
workshop was to gain insight and input into factors
that need to be considered when developing
standardized age bins and to identify future research
necessary to accomplish these goals.
Based upon consideration of the findings of the
technical workshop, as well as analysis of available
data, U.S. EPA developed guidance that established a
set of recommended age groups for development of
exposure factors for children entitled Guidance for
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005c). This revision of the
handbook for individuals <21 years of age presents
exposure factors data in a manner consistent with
U.S. EPA's recommended set of childhood age
groupings. The recommended age groups (U.S. EPA,
2005c) are as follows:
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
1.9. CONSIDERING LIFE STAGE WHEN
CALCULATING EXPOSURE AND
RISK
In recent years, there has been an increased
concern regarding the potential impact of
environmental exposures to children and other
susceptible populations such as older adults and
pregnant/lactating women. As a result, the U.S. EPA
and others have developed policy and guidance and
undertaken research to better incorporate life stage
data into human health risk assessment (Brown et al.,
2008). The Child-Specific Exposure Factors
Handbook was published in 2008 to address the need
to characterize children's exposures at various life
stages (U.S. EPA, 2008a). Children are of special
concern because (1) they consume more of certain
foods and water per unit of body weight than adults;
(2) they have a higher ratio of body surface area to
volume than adults; and (3) they experience
important, rapid changes in behavior and physiology
that may lead to differences in exposure (Moya et al.,
2004). Many studies have shown that young children
can be exposed to various contaminants, including
pesticides, during normal oral exploration of their
environment (i.e., hand-to-mouth behavior) and by
touching floors, surfaces, and objects such as toys
(Eskenazi et al., 1999; Gurunathan et al., 1998; Lewis
et al., 1999; Nishioka et al., 1999; Garry, 2004). Dust
and tracked-in soil accumulate in carpets, where
young children spend a significant amount of time
(Lewis et al., 1999). Children living in agricultural
areas may experience higher exposures to pesticides
than do other children (Curwin et al., 2007). They
may play in nearby fields or be exposed via
consumption of contaminated human milk from their
farmworker mothers (Eskenazi et al., 1999).
In terms of risk, children may also differ from
adults in their vulnerability to environmental
pollutants because of toxicodynamic differences (e.g.,
when exposures occur during periods of enhanced
susceptibility) and/or toxicokinetic differences (i.e.,
differences in absorption, metabolism, and excretion)
(U.S. EPA, 2000b). The immaturity of metabolic
enzyme systems and clearance mechanisms in young
children can result in longer half-lives of
environmental contaminants (Ginsberg et al., 2002;
Clewell et al., 2004). The cellular immaturity of
children and the ongoing growth processes account
for elevated risk (AAP, 1997). Toxic chemicals in the
environment can cause neurodevelopmental
disabilities, and the developing brain can be
particularly sensitive to environmental contaminants.
For example, elevated blood lead levels and prenatal
exposures to even relatively low levels of lead can
result in behavior disorders and reductions of
intellectual function in children (Landrigan et al.,
2005). Exposure to high levels of methylmercury can
result in developmental disabilities (e.g., intellectual
deficiency, speech disorders, and sensory
disturbances) among children (Myers et al., 2000).
Other authors have described the importance of
exposure timing (i.e., pre-conceptional, prenatal, and
postnatal) and how it affects the outcomes observed
(Selevan et al., 2000). Exposures during these critical
windows of development and age-specific behaviors
and physiological factors can lead to differences in
response (Makri et al., 2004). Fetal exposures can
occur from the mobilization of chemicals of maternal
body burden and transfer of those chemicals across
the placenta (Makri et al., 2004). Absorption through
the gastrointestinal tract is more efficient in neonates
and infants, making ingestion exposures a significant
route of exposure during the first year of age (Makri
et al., 2004).
It has also been suggested that higher levels of
exposure to indoor air pollution and allergens among
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inner-city children compared to non-inner-city
children may explain the difference in asthma levels
between these two groups (Breysee et al, 2005).
With respect to contaminants that are carcinogenic
via a mutagenic mode of action (MOA), the U.S. EPA
has found that childhood is a particularly sensitive
period of development in which cancer potencies per
year of exposure can be an order of magnitude higher
than during adulthood (U.S. EPA, 2005b).
A framework for considering life stages in
human health risk assessments was developed by the
U.S. EPA in the report entitled A Framework for
Assessing Health Risks of Environmental Exposures
to Children (U.S. EPA, 2006d). Life stages are
defined as "temporal stages (or intervals) of life that
have distinct anatomical, physiological, behavioral,
and/or functional characteristics that contribute to
potential differences in environmental exposures"
(Brown et al., 2008). One way to understand the
differential exposures among life stages is to study
the data using age binning or age groups as it is the
recommendation for childhood exposures. Although
the framework discusses the importance of
incorporating life stages in the evaluation of risks to
children, the approach can also be applied to other
life stages that may have their own unique
susceptibilities. For example, older individuals may
experience differential exposures and risks to
environmental contaminants due to biological
changes that occur during aging, disease status, drug
interactions, different exposure patterns, and
activities. More information on the toxicokinetic and
toxicodynamic impact of environmental agents in
older adults can be found in U.S. EPA's document
entitled Aging and Toxic Response: Issues Relevant to
Risk Assessment (U.S. EPA, 2005e). The need to
better characterize differential exposures of the older
adult population to environmental agents was
recognized at the U.S. EPA's workshop on the
development of exposure factors for the aging
(U.S. EPA, 2007b). A panel of experts in the fields of
gerontology, physiology, exposure assessment, risk
assessment, and behavioral science discussed existing
data, data gaps, and current relevant research on the
behavior and physiology of older adults, as well as
practical considerations of the utility of developing
an exposure factors handbook for the aging
(U.S. EPA, 2007b). Pregnant and lactating women
may also be a life stage of concern due to
physiological changes during pregnancy and
lactation. For example, lead is mobilized from the
maternal skeleton during pregnancy and the
postpartum period, increasing the chances for fetal
lead exposure (Gulson et al., 2004).
The U.S. EPA encourages the consideration of all
life stages and endpoints to ensure that vulnerabilities
during specific time periods are taken into account
(Brown et al., 2008). Although the importance of
assessing risks from environmental exposures to all
susceptible populations is recognized, most of the
guidance developed thus far relates to children.
Furthermore, it is recognized that there is a lack of
dose-response data to evaluate differential responses
at various life stages (e.g., age groups,
pregnant/lactating mothers, older populations). A key
component of U.S. EPA's Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005c) involves the need to sum
age-specific exposures across time when assessing
long-term exposure, as well as integrating these
age-specific exposures with age-specific differences
in toxic potency in those cases where information
exists to describe such differences: an example is
carcinogens that act via a mutagenic mode of action
(Supplemental Guidance for Assessing Susceptibility
from Early-Life Exposure to Carcinogens -
[U.S. EPA, 2005b]). When assessing chronic risks
(i.e., exposures greater than 10% of human lifespan),
rather than assuming a constant level of exposure for
70 years (usually consistent with an adult level of
exposure), the Agency is now recommending that
assessors calculate chronic exposures by summing
time-weighted exposures that occur at each life stage;
this handbook provides data arrayed by childhood
age in order to follow this new guidance (U.S. EPA,
2005b). This approach is expected to increase the
accuracy of risk assessments, because it will take into
account life stage differences in exposure. Depending
on whether body-weight-adjusted childhood
exposures are either smaller or larger compared to
those for adults, calculated risks could either decrease
or increase when compared with the historical
approach of assuming a lifetime of a constant adult
level of exposure.
The Supplemental Guidance report also
recommended that in those cases where age-related
differences in toxicity were also found to occur,
differences in both toxicity and exposure would need
to be integrated across all relevant age intervals
(U.S. EPA, 2005b). This guidance describes such a
case for carcinogens that act via a mutagenic mode of
action, where age dependent adjustments factors
(ADAFs) of 10 x and 3* are recommended for
children ages birth to <2 years, and 2 to <16 years,
respectively, when there is exposure during those
years, and available data are insufficient to derive
chemical-specific adjustment factors.
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Table 1-3, along with Chapter 6 of the
Supplemental Guidance (U.S. EPA, 2005b) report,
have been developed to help the reader understand
how to use the new sets of exposure and potency age
groupings when calculating risk through the
integration of life stage specific changes in exposure
and potency for mutagenic carcinogens.
Thus, Table 1-3 presents Lifetime Cancer Risk
(for a population with average life expectancy of 70
years) = Z (Exposure x Duration/70 years x Potency
x ADAF) summed across all the age groups. This is a
departure from the way cancer risks have historically
been calculated based upon the premise that risk is
proportional to the daily average of the long-term
adult dose.
1.10. FUNDAMENTAL PRINCIPLES OF
EXPOSURE ASSESSMENT
An exposure assessment is the "process of
estimating or measuring the magnitude, frequency,
and duration of exposure to an agent, along with the
number and characteristics of the population
exposed" (Zartarian et al., 2007). The definition of
exposure as used by the International Program on
Chemical Safety (IPCS, 2001) is the "contact of an
organism with a chemical or physical agent,
quantified as the amount of chemical available at the
exchange boundaries of the organism and available
for absorption." The term "agent" refers to a
chemical, biological, or physical entity that contacts a
target. The "target" refers to any physical, biological,
or ecological object exposed to an agent. In the case
of human exposures, the contact occurs with the
visible exterior of a person (i.e., target) such as the
skin, and openings such as the mouth, nostrils, and
lesions. The process by which an agent crosses an
outer exposure surface of a target without passing an
absorption barrier (i.e., through ingestion or
inhalation) is called an intake. The resulting dose is
the intake dose. The intake dose is sometimes
referred to in the literature as the administered dose
or potential dose.
The terms "exposure" and "dose" are very
closely related and, therefore, are often confused
(Zartarian et al., 2007). Dose is the amount of agent
that enters a target in a specified period of time after
crossing a contact boundary. An exposure does not
necessarily leads to a dose. However, there can be no
dose without a corresponding exposure (Zartarian et
al., 2007). Figure 1-1 illustrates the relationship
between exposure and dose.
AGENT
Figure 1-1. Conceptual Drawing of Exposure and
Dose Relationship (Zartarian et al., 2007).
In other words, the process of an agent entering
the body can be described in two steps: contact
(exposure) followed by entry (crossing the
boundary). In the context of environmental risk
assessment, risk to an individual or population can be
represented as a continuum from the source through
exposure to dose to effect as shown in Figure 1-2
(U.S. EPA, 2003e; IPCS, 2006; Ott, 2007). The
process begins with a chemical or agent released
from a source into the environment. Once in the
environment, the agent can be transformed and
transported through the environment via air, water,
soil, dust, and diet (i.e., exposure pathway). Fate and
transport mechanisms result in various chemical
concentrations with which individuals may come in
contact. Individuals encounter the agent either
through inhalation, ingestion, or skin/eye contact
(i.e., exposure route). The individual's activity
patterns as well as the concentration of the agent will
determine the magnitude, frequency, and duration of
the exposure. The exposure becomes an absorbed
dose when the agent crosses an absorption barrier
(e.g., skin, lungs, gut). Other terms used in the
literature to refer to absorbed dose include internal
dose, bioavailable dose, delivered dose, applied dose,
active dose, and biologically effective dose (Zartarian
et al., 2007). When an agent or its metabolites
interact with a target tissue, it becomes a target tissue
dose, which may lead to an adverse health outcome.
The text under the boxes in Figure 1-2 indicates the
specific information that may be needed to
characterize each box.
This approach has been used historically in
exposure assessments and exposure modeling. It is
usually referred to as source-to-dose approach. In
recent years, person-oriented approaches and models
have gained popularity. This approach is aimed at
accounting for cumulative and aggregate exposures
to individuals (Georgopoulos, 2008; Price et al.,
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2003a). The person-oriented approach can also take
advantage of information about the individual's
susceptibility to environmental factors (e.g., genetic
differences) (Georgopoulos, 2008).
There are three approaches to calculate
exposures: (1) the point-of-contact approach, (2) the
scenario evaluation approach, and (3) the dose
reconstruction approach (U.S EPA, 1992a). The data
presented in this handbook are generally useful for
evaluating exposures using the scenario approach.
There are advantages and disadvantages associated
with each approach. Although it is not the purpose of
this handbook to provide guidance on how to conduct
an exposure assessment, a brief description of the
approaches is provided below.
The point-of-contact approach, or direct
approach, involves measurements of chemical
concentrations at the point where exposure occurs
(i.e., at the interface between the person and the
environment). This chemical concentration is coupled
with information on the length of contact with each
chemical to calculate exposure. The scenario
evaluation approach, or the indirect approach, utilizes
data on chemical concentration, frequency, and
duration of exposure as well as information on the
behaviors and characteristics of the exposed life
stage. The third approach, dose reconstruction, allows
exposure to be estimated from dose, which can be
reconstructed through the measurement of
biomarkers of exposure. A biomarker of exposure is a
chemical, its metabolite, or the product of an
interaction between a chemical and some target
molecule or cell that is measured in a compartment in
an organism (NAS, 2006). Biomonitoring is
becoming a tool for identifying, controlling, and
preventing human exposures to environmental
chemicals (NAS, 2006). For example, blood lead
concentrations and the associated health effects were
used by the U.S. EPA in its efforts to reduce exposure
to lead in gasoline. The Centers for Disease Control
and Prevention conducts biomonitoring studies to
help identify chemicals that are both present in the
environment and in human tissues (NAS, 2006).
Biomonitoring studies also assist public health
officials in studying distributions of exposure in a
population and how they change overtime.
Biomonitoring data can be converted to exposure
using pharmacokinetic modeling (NAS, 2006).
Although biomonitoring can be a powerful tool,
interpretation of the data is difficult. Unlike the other
two approaches, biomonitoring provides information
on internal doses integrated across environmental
pathways and media. Interpretation of these data
requires knowledge and understanding of how the
chemicals are absorbed, excreted, and metabolized in
the biological system, as well as the properties of the
chemicals and their metabolites (NAS, 2006). The
interpretation of biomarker data can be further
improved by the development of other cellular and
molecular approaches to include advances in
genomics, proteomics, and other approaches that
make use of molecular-environmental interactions
(Lioy et al., 2005). Physiological parameters can also
vary with life stage, age, sex, and other demographic
information (Price et al., 2003b). Physiologic and
metabolic factors and how they vary with life stage
have been the subject of recent research.
Pharmacokinetic models are frequently developed
from data obtained from young adults. Therapeutic
drugs have been used as surrogates to study
pharmacokinetic differences in fetuses, children, and
adults (Ginsberg et al., 2004). Specific considerations
of susceptibilities for other populations (e.g.,
children, older adults) require knowledge of the
physiological parameters that most influence the
disposition of the chemicals in the body (Thompson
et al., 2009). Physiological parameters include
alveolar ventilation, cardiac output, organ and tissue
weights and volumes, blood flows to organs and
tissues, clearance parameters, and body composition
(Thompson et al., 2009). Price et al. (2003b)
developed a tool for capturing the correlation
between organs and tissue and compartment volumes,
blood flows, body weight, sex, and other
demographic information. A database that records
key, age-specific pharmacokinetic model inputs for
healthy older adults and for older adults with
conditions such as diabetes, chronic obstructive
pulmonary disease, obesity, heart disease, and renal
disease has been developed by the U.S. EPA
(Thompson et al., 2009; U.S. EPA, 2008c).
Computational exposure models can play an
important role in estimating exposures to
environmental chemicals (Sheldon and Cohen-Hubal,
2009). In general, these models combine
measurements of the concentration of the chemical
agent in the environment (e.g., air, water, soil, food)
with information about the individual's activity
patterns to estimate exposure (IPCS, 2005). Several
models have been developed and may be used to
support risk management decisions. For example, the
U.S. EPA SHEDS model is a probabilistic model that
simulates daily activities to predict distributions of
daily exposures in a population (U.S. EPA, 2009c).
Other models such as the Modeling Environment for
Total Risk Studies incorporates and expands the
approach used by SHEDS and considers multiple
routes of exposure (Georgopoulos and Lioy, 2006).
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1.10.1. Exposure and Dose Equations
Exposure can be quantified by multiplying the
concentration of an agent times the duration of the
contact. Exposure can be instantaneous when the
contact between an agent and a target occurs at a
single point in time and space (Zartarian et al., 2007).
The summation of instantaneous exposures over the
exposure duration is called the time-integrated
exposure (Zartarian et al., 2007). Equation 1-1 shows
the time-integrated exposure.
'2
E = jC(t)dt
(Eqn. 1-1)
where:
E = Time-integrated exposure
(mass/volume),
t2-t\ = Exposure duration (ED) (time),
and
C = Exposure concentration as a
function of time (mass/volume).
Dividing the time-integrated exposure by the
exposure duration, results in the time-averaged
exposure (Zartarian et al., 2007).
Dose can be classified as an intake dose or an
absorbed dose (U.S. EPA, 1992a). Starting with a
general integral equation for exposure, several dose
equations can be derived depending upon boundary
assumptions. One of the more useful of these derived
equations is the average daily dose (ADD). The
ADD, which is used for many non-cancer effects,
averages exposures or doses over the period of time
exposure occurred. The ADD can be calculated by
averaging the intake dose over body weight and an
averaging time as shown in Equations 1-2 and 1-3.
ADD = •
Intake Dose
Body Weight x AveragingTime
(Eqn. 1-2)
The exposure can be expressed as follows:
Intake Dose = C x IR x ED (Eqn. 1-3)
where:
C = Concentration of the Agent
(mass/volume),
IR = Intake Rate (mass/time), and
ED = Exposure Duration (time).
Concentration of the agent is the mass of the
agent in the medium (air, food, soil, etc.) per unit
volume contacting the body and has units of
mass/volume or mass/mass.
The intake rate refers to the rates of inhalation,
ingestion, and dermal contact, depending on the route
of exposure. For ingestion, the intake rate is simply
the amount of contaminated food ingested by an
individual during some specific time period (units of
mass/time). Much of this handbook is devoted to
rates of ingestion for some broad classes of food. For
inhalation, the intake rate is that at which
contaminated air is inhaled. Factors presented in this
handbook that affect dermal exposure are skin
surface area and estimates of the amount of solids
that adheres to the skin, film thickness of liquids to
skin, transfer of residues, and skin thickness. It is
important to note that there are other key factors in
the calculation of dermal exposures that are not
covered in this handbook (e.g., chemical-specific
absorption factors).
The exposure duration is the length of time of
contact with an agent. For example, the length of
time a person lives in an area, frequency of bathing,
time spent indoors versus outdoors, and in various
microenvironments, all affect the exposure duration.
Chapter 16, Activity Factors, gives some examples of
population behavior and macro and micro activities
that may be useful for estimating exposure durations.
When the above parameter values IR and ED
remain constant over time, they are substituted
directly into the dose equation. When they change
with time, a summation approach is needed to
calculate dose. In either case, the exposure duration is
the length of time exposure occurs at the
concentration and the intake rate specified by the
other parameters in the equation.
Note that the advent of childhood age groupings
means that separate ADDs should be calculated for
each age group considered. Chronic exposures can
then be calculated by summing across each life
stage-specific ADD.
Cancer risks have traditionally been calculated in
those cases where a linear non-threshold model is
assumed, in terms of lifetime probabilities by
utilizing dose values presented in terms of lifetime
ADDs (LADDs). The LADD takes the form of
Equation 1-2, with lifetime replacing averaging time.
While the use of LADDs may be appropriate when
developing screening-level estimates of cancer risk,
the U.S. EPA recommends that risks should be
calculated by integrating exposures or risks
throughout all life stages (U.S. EPA, 1992a).
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For some types of analyses, dose can be
expressed as a total amount (with units of mass, e.g.,
mg) or as a dose rate in terms of mass/time (e.g.,
mg/day), or as a rate normalized to body mass (e.g.,
with units of mg of chemical per kg of body weight
per day [mg/kg-day]). The LADD is usually
expressed in terms of mg/kg-day or other
mass/mass-time units.
In most cases (inhalation and ingestion
exposures), the dose-response parameters for
carcinogenic risks have been adjusted for the
difference in absorption across body barriers between
humans and the experimental animals used to derive
such parameters. Therefore, the exposure assessment
in these cases is based on the intake dose, with no
explicit correction for the fraction absorbed.
However, the exposure assessor needs to make such
an adjustment when calculating dermal exposure and
in other specific cases when current information
indicates that the human absorption factor used in the
derivation of the dose-response factor is
inappropriate.
For carcinogens, the duration of a lifetime has
traditionally been assigned the nominal value of
70 years as a reasonable approximation. For dose
estimates to be used for assessments other than
carcinogenic risk, various averaging periods have
been used. For acute exposures, the doses are usually
averaged over a day or a single event. For non-
chronic non-cancer effects, the time period used is
the actual period of exposure (exposure duration).
The objective in selecting the exposure averaging
time is to express the dose in a way that can be
combined with the dose-response relationship to
calculate risk.
The body weight to be used in Equation 1-2
depends on the units of the exposure data presented
in this handbook. For example, for food ingestion, the
body weights of the surveyed populations were
known in the USDA and NHANES surveys, and they
were explicitly factored into the food intake data in
order to calculate the intake as g/kg body weight-day.
In this case, the body weight has already been
included in the "intake rate" term in Equation 1-3,
and the exposure assessor does not need to explicitly
include body weight.
The units of intake in this handbook for the
incidental ingestion of soil and dust are not
normalized to body weight. In this case, the exposure
assessor will need to use (in Equation 1-2) the
average weight of the exposed population during the
time when the exposure actually occurs. When
making body-weight assumptions, care must be taken
that the values used for the population parameters in
the dose-response analysis are consistent with the
population parameters used in the exposure analysis.
Intraspecies adjustments based on life stage can be
made using a correction factor (CF) (U.S. EPA,
2006d, 2011). Appendix 1A of this chapter discusses
these adjustments in more detail. Some of the
parameters (primarily concentrations) used in
estimating exposure are exclusively site specific, and,
therefore, default recommendations should not be
used. It should be noted that body weight is
correlated with food consumption rates, body surface
area, and inhalation rates (for more information, see
Chapters 6, 7, 9, 10, 11, 12, 13, and 14).
The link between the intake rate value and the
exposure duration value is a common source of
confusion in defining exposure scenarios. It is
important to define the duration estimate so that it is
consistent with the intake rate:
The intake rate can be based on an
individual event (e.g., serving size per
event). The duration should be based on the
number of events or, in this case, meals.
The intake rate also can be based on a
long-term average, such as 10 g/day. In this
case, the duration should be based on the
total time interval over which the exposure
occurs.
The objective is to define the terms so that, when
multiplied, they give the appropriate estimate of mass
of agent contacted. This can be accomplished by
basing the intake rate on either a long-term average
(chronic exposure) or an event (acute exposure)
basis, as long as the duration value is selected
appropriately.
Inhalation dosimetry is employed to derive the
human equivalent exposure concentrations on which
inhalation unit risks (lURs), and reference
concentrations (RfCs), are based (U.S. EPA, 1994).
U.S. EPA has traditionally approximated children's
respiratory exposure by using adult values, although
a recent review (Ginsberg et al., 2005) concluded that
there may be some cases where young children's
greater inhalation rate per body weight or pulmonary
surface area as compared to adults can result in
greater exposures than adults. The implications of
this difference for inhalation dosimetry and children's
risk assessment were discussed at a peer involvement
workshop hosted by the U.S. EPA in 2006 (Foos et
al., 2008).
Consideration of life stage-particular
physiological characteristics in the dosimetry analysis
may result in a refinement to the human equivalent
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concentration (HEC) to ensure relevance in risk
assessment across life stages, or might conceivably
conclude with multiple HECs, and corresponding
IUR values (e.g., separate for childhood and
adulthood) (U.S. EPA, 2005b). The RfC
methodology, which is described in Methods for
Derivation of Inhalation Reference Concentrations
and Applications of Inhalation Dosimetry (U.S. EPA,
1994), allows the user to incorporate population-
specific assumptions into the models. Refer to U.S.
EPA guidance (U.S. EPA, 1994) on how to make
these adjustments.
There are no specific exposure factor
assumptions in the derivation of RfDs for susceptible
populations. With regard to childhood exposures for a
susceptible population, for example, the assessment
of the potential for adverse health effects in infants
and children is part of the overall hazard and dose-
response assessment for a chemical. Available data
pertinent to children's health risks are evaluated
along with data on adults and the no-observed-
adverse-effect level (NOAEL) or benchmark dose
(BMD) for the most sensitive critical effect(s), based
on consideration of all health effects. By doing this,
protection of the health of children will be considered
along with that of other sensitive populations. In
some cases, it is appropriate to evaluate the potential
hazard to a susceptible population (e.g., children)
separately from the assessment for the general
population or other population groups. For more
information regarding life stage-specific
considerations for assessing children exposures, refer
to the U.S. EPA report entitled Framework for
Assessing Environmental Exposures to Children
(U.S. EPA, 2006d).
1.10.2. Use of Exposure Factors Data in
Probabilistic Analyses
Probabilistic risk assessment provides a range
and likelihood estimate of risk rather than a single
point estimate. It is a tool that can provide additional
information to risk managers to improve decision
making. Although this handbook is not intended to
provide complete guidance on the use of Monte Carlo
and other probabilistic analyses, some of the data in
this handbook may be appropriate for use in
probabilistic assessments. More detailed information
on treating variability and uncertainty is discussed in
Chapter 2 of this handbook. The use of Monte Carlo
or other probabilistic analysis requires
characterization of the variability of exposure factors
and requires the selection of distributions or
histograms for the input parameters of the dose
equations presented in Section 1.10.1. The following
suggestions are provided for consideration when
using such techniques:
• The exposure assessor should only consider
using probabilistic analysis when there are
credible distribution data (or ranges) for the
factor under consideration. Even if these
distributions are known, it may not be
necessary to apply this technique. For
example, if only average exposure values are
needed, these can often be computed
accurately by using average values for each of
the input parameters unless a non-linear model
is used. Generally, exposure assessments
follow a tiered approach to ensure the efficient
use of resources. They may start with very
simple techniques and move to more
sophisticated models. The level of assessment
needed can be determined initially during the
problem formulation. There is also a tradeoff
between the level of sophistication and the
need to make timely decisions (NAS, 2009).
Probabilistic analysis may not be necessary
when conducting assessments for the first tier,
which is typically done for screening purposes,
i.e., to determine if unimportant pathways can
be eliminated. In this case, bounding estimates
can be calculated using maximum or near
maximum values for each of the input
parameters. Alternatively, the assessor may use
the maximum values for those parameters that
have the greatest variance.
• The selection of distributions can be highly
site-specific and dependent on the purpose of
the assessment. In some cases, the selection of
distributions is driven by specific legislation. It
will always involve some degree of judgment.
Distributions derived from national data may
not represent local conditions. Also,
distributions may be representative of some
age groups, but not representative when finer
age categories are used. The assessor should
evaluate the distributional data to ensure that it
is representative of the population that needs
to be characterized. In cases where
site-specific data are available, the assessor
may need to evaluate their quality and
applicability. The assessor may decide to use
distributional data drawn from the national or
other surrogate population. In this case, it is
important that the assessor address the extent
to which local conditions may differ from the
surrogate data.
• It is also important to consider the
independence/dependence of variables and
data used in a simulation. For example, it may
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be reasonable to assume that ingestion rate and
contaminant concentration in foods are
independent variables, but ingestion rate and
body weight may or may not be independent.
In addition to a qualitative statement of
uncertainty, the representativeness assumption should
be appropriately addressed as part of a sensitivity
analysis. Distribution functions used in probabilistic
analysis may be derived by fitting an appropriate
function to empirical data. In doing this, it should be
recognized that in the lower and upper tails of the
distribution, the data are scarce, so that several
functions, with radically different shapes in the
extreme tails, may be consistent with the data. To
avoid introducing errors into the analysis by the
arbitrary choice of an inappropriate function, several
techniques can be used. One technique is to avoid the
problem by using the empirical data themselves
rather than an analytic function. Another is to do
separate analyses with several functions that have
adequate fit but form upper and lower bounds to the
empirical data. A third way is to use truncated
analytical distributions. Judgment must be used in
choosing the appropriate goodness-of-fit test.
Information on the theoretical basis for fitting
distributions can be found in a standard statistics text,
(e.g., Gilbert [1987], among others). Off-the-shelf
computer software can be used to statistically
determine the distributions that fit the data. Other
software tools are available to identify outliers and
for conducting Monte Carlo simulations.
If only a range of values is known for
an exposure factor, the assessor has several options.
These options include:
keep that variable constant at its central value;
assume several values within the range of
values for the exposure factor;
calculate a point estimate(s) instead of using
probabilistic analysis; and
assume a distribution. (The rationale for the
selection of a distribution should be discussed
at length.) The effects of selecting a different,
but equally probable distribution should be
discussed. There are, however, cases where
assuming a distribution may introduce
considerable amount of uncertainty. These
include:
o data are missing or very limited for a key
parameter;
o data were collected over a short time
period and may not represent long-term
1.11.
trends (the respondent's usual behavior)—
examples include food consumption
surveys; activity pattern data;
o data are not representative of the
population of interest because sample size
was small or the population studied was
selected from a local area and was,
therefore, not representative of the area of
interest; for example, soil ingestion by
children; and
o ranges for a key variable are uncertain due
to experimental error or other limitations
in the study design or methodology; for
example, soil ingestion by children.
AGGREGATE AND CUMULATIVE
EXPOSURES
The U.S. EPA recognizes that individuals may be
exposed to mixtures of chemicals both indoors and
outdoors through more than one pathway. New
directions in risk assessments in the U.S. EPA put
more emphasis on total exposures via multiple
pathways (U.S. EPA, 2003e, 2008b). Assessments
that evaluate a single agent or stressor across multiple
routes are not considered cumulative risk
assessments. These are defined by the Food Quality
Protection Act as aggregate risk assessments and can
provide useful information to cumulative assessments
(U.S. EPA, 2003e). Concepts and considerations to
conduct aggregate risk assessments are provided in
the U.S. EPA document entitled General Principles
for Performing Aggregate Exposure and Risk
Assessments (U.S. EPA, 2001c).
Cumulative exposure is defined as the exposure
to multiple agents or stressors via multiple routes. In
the context of risk assessment, it means that risks
from multiple routes and agents need to be combined,
not necessarily added (U.S. EPA, 2003b). Analysis
needs to be conducted on how the various agents and
stressors interact (U.S. EPA, 2003b).
In order to achieve effective risk assessment and
risk management decisions, all media and routes of
exposure should be assessed (NAS, 1991, 2009).
Over the last several years, the U.S. EPA has
developed a methodology for assessing risk from
multiple chemicals (U.S. EPA, 1986c, 2000c). For
more information, refer to the U.S. EPA's Framework
for Cumulative Risk Assessment (U.S. EPA, 2003b).
The recent report by the NAS also recommends the
development of approaches to incorporate the
interactions between chemical and non-chemical
stressors (NAS, 2009).
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1.12. ORGANIZATION OF THE
HANDBOOK
All the chapters of this handbook have been
organized in a similar fashion. An introduction is
provided that discusses some general background
information about the exposure factor. This
discussion is followed by the recommendations for
that exposure factor including summary tables of the
recommendations and confidence ratings. The goal of
the summary tables is to present the data in a
simplified fashion by providing mean and upper
percentile estimates and referring the reader to more
detailed tables with more percentile estimates or
other demographic information (e.g., sex) at the end
of the chapter. Because of the large number of tables
in this handbook, tables that include information
other than the recommendations and confidence
ratings are presented at the end of each chapter,
before the appendices, if any. Following the
recommendations, the key studies are summarized.
Relevant data on the exposure factor are also
provided. These data are presented to provide the
reader with added perspective on the current state-of-
knowledge pertaining to the exposure factor of
interest. Summaries of the key and relevant studies
include discussions about their strengths and
limitations. Note that because the studies often were
performed for reasons unrelated to developing the
factor of interest, the attributes that were
characterized as limitations might not be limitations
when viewed in the context of the study's original
purpose.
The handbook is organized as follows:
Chapter 1 Introduction—includes discussions
about general concepts in exposure
assessments as well as the purpose,
scope, and contents of the handbook.
Chapter 2 Variability and Uncertainty—
provides a brief overview of the
concepts of variability and
uncertainty and directs the reader to
other references for more in-depth
information.
Chapter 3 Ingestion of Water and Other Select
Liquids—provides information on
drinking water consumption and data
on intake of select liquids for the
general population and various
demographic groups; also provides
data on intake of water while
swimming.
Chapter 4 Non-dietary Ingestion—presents data
on mouthing behavior necessary to
estimate non-dietary exposures.
Chapters Soil and Dust Ingestion—provides
information on soil and dust
ingestion for both adults and
children.
Chapter 6 Inhalation Rates—presents data on
average daily inhalation rates and
activity-specific inhalation rates for
the general population and various
demographic groups.
Chapter? Dermal Exposure Factors—presents
information on body surface area and
solids adherence to the skin, as well
as data on other
non-chemical-specific factors that
may affect dermal exposure.
Chapter 8 Body Weight—provides data on body
weight for the general population and
various demographic groups.
Chapter 9 Intake of Fruits and Vegetables—
provides information on total fruit
and vegetable consumption as well as
intake of individual fruits and
vegetables for the general population
and various demographic groups.
Chapter 10 Intake of Fish and Shellfish-
provides information on fish
consumption for the general
population, recreational freshwater
and marine populations, and various
demographic groups.
Chapter 11 Intake of Meats, Dairy Products, and
Fats—provides information on meat,
dairy products, and fats consumption
for the general population and
various demographic groups.
Chapter 12 Intake of Grain Products—provides
information on grain consumption for
the general population and various
demographic groups.
Chapter 13 Intake of Home-produced Foods—
provides information on
home-produced food consumption
for the general population and
various demographic groups.
Chapter 14 Total Food Intake—provides
information on total food
consumption for the general
population and various demographic
groups; information on the
composition of the diet is also
provided.
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Chapter 15 Human Milk Intake—presents data
on human milk consumption for
infants at various life stages.
Chapter 16 Activity Factors—presents data on
activity patterns for the general
population and various demographic
groups.
Chapter 17 Consumer Products—provides
information on frequency, duration,
and amounts of consumer products
used.
Chapter 18 Life Expectancy—presents data on
the projected length of a lifetime,
based on age and demographic
factors.
Chapter 19 Building Characteristics—presents
information on both residential and
commercial building characteristics
necessary to assess exposure to
indoor air pollutants.
Figure 1-3 provides a schematic diagram that
shows the linkages of a select number of exposure
pathways with the exposure factors presented in this
handbook and the corresponding exposure routes.
Figure 1-4 provides a roadmap to assist users of this
handbook in locating recommended values and
confidence ratings for the various exposure factors
presented in these chapters.
1.13. REFERENCES FOR CHAPTER 1
AAP (American Academy of Pediatrics). (1997)
Child health issues for the second session of
the 106th Congress. Department of Federal
Affairs, Washington, DC.
Breysee, PN; Buckley, TJ; Williams, D; Beck, CM;
Jo, S; Merriman, B; Kanchanaraksa, S;
Swartz, LJ; Callahan, KA; Butz, AM; Rand,
CS; Diette, GB; Krishman, JA; Moseley,
AM; Curlin-Brosnan, J; Durkin, NB;
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Exposure Factors Handbook
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Exposure Factors Handbook
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Exposure Factors Handbook
Chapter 1—Introduction
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Exposure Factors Handbook
Chapter 1—Introduction
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Table 1-1. Availability of Various
Exposure Factors
Ingestion of water and other select liquids (Chapter 3)
Non-dietary ingestion
Soil and dust ingestion
Inhalation rate
Surface area
Soil adherence
Body weight
Intake of fruits and vegetables
Intake of fish and shellfish
Intake of meats, dairy products, and fats
Intake of grain products
Intake of home produced foods
Total food intake
Human milk intake
Total time indoors
Total time outdoors
Time showering
Time bathing
Time swimming
Time playing on sand/gravel
Time playing on grass
Time playing on dirt
Occupational mobility
Population mobility
Life expectancy
Volume of residence or building
Air exchange rates
Exposure Metrics in Exposure Factors Data
Chapter Average Median Upper Percentile Multiple Percentiles
3 ^ ^ ^ ^
4 ^ ^ ^ ^
5 •/ ->/a
6 v' •/ •/ •/
1 S
8 •/ S S S
9 S V V V
10 •/ •/ •/ •/
11 S S S S
\2 •/ •/ •/ •/
13 ^ ^ ^ ^
14 •/•/•/' •/
15 S •/
16 S
16 S
16 •/ •/ •/ •/
16 •/ •/ •/ •/
16 •/ •/ •/ •/
16 •/ •/ •/ •/
16 •/ •/ •/ •/
16 •/ •/ •/ •/
16 S
16 •/ •/ •/ •/
18 S
19 S ^
19 ^ ^b
•S = Data available.
a Including soil pica and geophagy.
b Lower percentile.
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Exposure Factors Handbook
Chapter 1—Introduction
Table 1-2. Criteria Used to Rate Confidence in Recommended Values
General Assessment Factors
Elements Increasing Confidence
Elements Decreasing Confidence
Soundness
Adequacy of Approach
Minimal (or defined) Bias
The studies used the best available
methodology and capture the
measurement of interest.
As the sample size relative to that of
the target population increases, there
is greater assurance that the results
are reflective of the target population.
The response rate is greater than 80%
for in-person interviews and
telephone surveys, or greater than
70% for mail surveys.
The studies analyzed primary data.
The study design minimizes
measurement errors.
There are serious limitations with the
approach used; study design does not
accurately capture the measurement of
interest.
Sample size too small to represent the
population of interest.
The response rate is less than 40%.
The studies are based on secondary
sources.
Uncertainties with the data exist due to
measurement error.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The studies focused on the exposure
factor of interest.
The studies focused on the U.S.
population.
The studies represent current
exposure conditions.
The data collection period is
sufficient to estimate long-term
behaviors.
The purpose of the studies was to
characterize a related factor.
Studies are not representative of the U.S.
population.
Studies may not be representative of
current exposure conditions.
Shorter data collection periods may not
represent long-term exposures.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The study data are publicly available.
The results can be reproduced, or
methodology can be followed and
evaluated.
The studies applied and documented
quality assurance/quality control
measures.
Access to the primary data set was limited.
The results cannot be reproduced, the
methodology is hard to follow, and the
author(s) cannot be located.
Information on quality assurance/control
was limited or absent.
Page
1-28
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 1—Introduction
Table 1-2. Criteria Used to Rate Confidence in Recommended Values (continued)
General Assessment Factors
Increasing Confidence
Decreasing Confidence
Variability and Uncertainty
Variability in Population
Uncertainty
The studies characterize variability in
the population studied.
The uncertainties are minimal and
can be identified. Potential bias in the
studies are stated or can be
determined from the study design.
The characterization of variability is
limited.
Estimates are highly uncertain and cannot
be characterized. The study design
introduces biases in the results.
Evaluation and Review
Peer Review
Number and Agreement of
Studies
The studies received a high level of
peer review (e.g., they are published
in peer-reviewed journals).
The number of studies is greater than
three. The results of studies from
different researchers are in
agreement.
The studies received limited peer review.
The number of studies is one. The results
of studies from different researchers are in
disagreement.
Table 1-3. Age-Dependent Potency Adjustment Factor by Age Group for Mutagenic Carcinogens
Exposure Age Group3
Birth to <1 month
1 <3 months
3 <6 months
6 <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
>21 years (21 to <70 years)
Exposure Duration (year)
0.083
0.167
0.25
0.5
1
1
3
5
5
5
49
Age-Dependent Potency Adjustment Factor
10x
10x
10x
10x
10x
3x
3x
3x
3x
lx
lx
a U.S. EPA's recommended childhood age groups (excluding ages >21 years).
Exposure Factors Handbook
September 2011
Page
1-29
-------
Exposure Factors Handbook
Chapter 1—Introduction
SOURCE/STRESSOR
FORMATION
DISEASE
Chemical
Physical
Microbial
Magnitude
Duration
Timing
1
r
TRANSPORT/
TRANSFORMATION
ALTERED STRUCTURE/
FUNCTION
Dispersion
Ki netics
Thermodynamics
Distributions
Meteorology
s
1
ENVIRONMENTAL
CHARACTERIZATION
Cancer
Asthma
Infertility etc.
EARLY BIOLOGICAL
EFFECT
Edema
Arrhythmia
Enzymuria
Necrosis etc.
Air
Water
Diet
Soil and Dust
EXPOSURE
Pathway
Route
Duration
Frequency
Magnitude
Molecular
Biochemical
Cellular
Organ
Organism
Individual
Community
Population
Absorbed
Target
Internal
Biologically Effective
Statistical Profile
Reference Population
Susceptible Individual
Susceptible Populations
Population Distributions
Figure 1-2. Exposure-Dose-Effect Continuum.
Source: Redrawn from U.S. EPA, 2003e; IPCS, 2006; Ott, 2007.
The exposure-dose-effect continuum depicts the trajectory of an agent from its source to an effect. The
agent can be transformed and transported through the environment via air, water, soil, dust, and diet.
Individuals can become in contact with the agent through inhalation, ingestion, or skin/eye contact. The
individual's physiology, behavior, and activity patterns as well as the concentration of the agent will
determine the magnitude, frequency, and duration of the exposure. The exposure becomes an absorbed dose
once the agent crosses the absorption barrier (i.e., skin, lungs, eyes, gastrointestinal tract, placenta).
Interactions of the chemical or its metabolites with a target tissue may lead to an adverse health outcome.
The text under the boxes indicates the specific information that may be needed to characterize each step in
the exposure-dose-effect continuum.
Page
1-30
Exposure Factors Handbook
September 2011
-------
It
"t
ft
3
1=
s
I
Environmental Pathways
Exposure Factors
Exposure Route
Time Indoors (Ch. 16)
Volume of Residence (Ch. 19)
Building Characteristics (Ch. 19)
Air Exchange Rates (Ch. 19)
Inhalation Rate (Ch. 6)
Time Outdoors (Ch. If:)
Non-Dietary Ingestion (Ch. 4)
Soil and Dust Ingestion (Ch. 5)
Time Playing on Sand/Gravel, Grass, and Dirt (Ch. 16)
Body Surface Area (Ch. 7)
SoMAdherencefCh. 7)
Inhalation
Ingestion
Dermal Contact
Q
I
I
a
I
rs
£5
1=
I
Time Swimming (Ch. 16)
Body Surface Area (Ch. 7)
Inhalation Rate ifh. f,i
Time Showering/Bathing (Ch, 16)
Human Milk Intake (Ch. 15)
Ingestion of Water and other Select Liquids (Ch. 3)
}
Ingest ton inhalation Dermal
Dermal Contact
Inhalation
Inhalation Dermal Contact
Ingestion
Intake of Fruits and Vegetables (Ch. 9)
Intake of Grain Products (Ch. 12)
Total Food Intake (Ch. 14)
Intake of Home Produced Foods (Ch. 13)
Human Milk Intake (Ch. 15)
Intake of Meats, Dairy Products and Fats (Ch. 11)
Intake of Fish and Shellfish (Ch. 10)
Human Milk Intake (Ch. 15)
Total Food Intake (Ch. 14)
Ingestion
Ingestion
Notes:
The pathways presented are selected pathways- This diagram is not meant to be comprehensive.
Consumer Products (Ch. 17), such as perfume, are not shown on this diagram. Humans can be exposed to consumer products through all pathways and routes.
Body Weight {Ch. 8) and Lifetime (Ch. 13} potentially modify all exposure pathways.
Figure 1-3. Schematic Diagram of Exposure Pathways, Factors, and Routes.
Ss
-------
Figure 1-4. Road Map to Exposure Factor Recommendations.
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ineestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
Adults
Children
Pregnant Women
RECOMMENDATIONS
TABLE/RATINGS TABLE
3-1/3-2
3-3 / 3-4
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
Frequency
Duration
RECOMMENDATIONS
TABLE/RATINGS TABLE
4-1/4-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
5-1/5-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
9-1 / 9-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
General Population
Marine Recreational
Freshwater Recreational
Native American Populations
10
10-1 / 10-2
10-3 / 10-4
10-5
10-6
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
11
11-1/11-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
12
12-1 / 12-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
13
13-1/13-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
14
14-1 / 14-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Exclusively Breastfed Infants
15
15-1/15-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
EXPOSURE FACTOR
Drinking Water Intake
Mouthing
Soil/Dust Intake
Fruit and Vegetable Intake
Fish and Shellfish Intake
Meat and Dairy Intake
Grain Intake
Home Produced Food Intake
Total Food Intake
Human Milk Intake
Time Swimming
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Adults
Children
16
16-1 / 16-2
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Inhalation Rate
Long Term
Short Term
Adults
Children
Adults
Children
6-1/6-3
6-2 / 6-3
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
Body Surface Area
Adherence of Solids
Adults
Children
Adults
Children
7-1,7-2/7-3
7-4 / 7-5
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Adults
Children
8-1 / 8-2
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Males
Females
18
18-1/18-2
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
Activity Patterns
Occupational Mobility
Population Mobility
Adults
Children
Adults
Adults
Children
16
16-1 / 16-2
16-3 / 16-4
16-5 / 16-6
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
Frequency of Use
Amount Used
Duration
General Population
17
No Recommendations
-------
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
CHAPTER
RECOMMENDATIONS
TABLE/RATINGS TABLE
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Building Characteristics
Air Exchange Rates
Building Volume
Residential Buildings
Commercial Buildings
Residential Buildings
Commercial Buildings
19
19-1/19-2
19-3/19-4
19-1/19-2
19-3/19-4
-------
Exposure Factors Handbook
Chapter 1—Introduction
APPENDIX 1A
RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND DOSE-RESPONSE
INFORMATION FROM THE INTEGRATED RISK INFORMATION SYSTEM (IRIS)
Exposure Factors Handbook Page
September 2011 1A-1
-------
Exposure Factors Handbook
Chapter 1—Introduction
APPENDIX 1A—RISK CALCULATIONS
USING EXPOSURE FACTORS HANDBOOK
DATA AND DOSE-RESPONSE INFORMATION
FROM THE INTEGRATED RISK
INFORMATION SYSTEM (IRIS)
1A-1. INTRODUCTION
When estimating risk to a specific population
from chemical exposure, whether it is the entire
national population or some smaller population of
interest, exposure data (either from this handbook or
from other sources) must be combined with dose-
response information. The dose-response information
typically comes from the Integrated Risk Information
System (IRIS) database, which maintains a list of
toxicity (i.e., dose-response) values for a number of
chemical agents (www.epa.gov/iris). Care must be
taken to ensure that population parameters from the
dose-response assessment are consistent with the
population parameters used in the exposure analysis.
This appendix discusses procedures for ensuring this
consistency.
The U.S. EPA's approach to estimating risks
associated with toxicity from non-cancer effects is
fundamentally different from its approach to
estimating risks associated with toxicity from
carcinogenic effects. One difference is that different
assumptions are made regarding the mode of action
that is involved in the generation of these two types
of effects. For non-cancer effects, the Agency
assumes that these effects are produced through a
non-linear (e.g., "threshold") mode of action (i.e.,
there exists a dose below which effects do not occur)
(U.S. EPA, 1993). For carcinogenic effects, deemed
to operate through a mutagenic mode of action or for
which the mode of action is unknown, the Agency
assumes there is the absence of a "threshold" (i.e.,
there exists no level of exposure that does not pose a
small, but finite, probability of generating a
carcinogenic response).
For carcinogens, quantitative estimates of risks
for the oral route of exposure are generated using
cancer slope factors. The cancer slope factor is an
upper bound estimate of the increase in cancer risk
per unit of dose and is typically expressed in units of
(mg/kg-day)"1. Because dose-response assessment
typically involves extrapolating from laboratory
animals to humans, a human equivalent dose (HED)
is calculated from the animal data in order to derive a
cancer slope factor that is appropriately expressed in
human equivalents. The Agency endorses a hierarchy
of approaches to derive human equivalent oral
exposures from data in laboratory animal species,
with the preferred approach being physiologically
based toxicokinetic (PBTK) modeling. In the absence
of PBTK modeling, U.S. EPA advocates using body
weight to the 3/4 power (BW3/4) as the default scaling
factor for extrapolating lexicologically equivalent
doses of orally administered agents from animals to
humans (U.S. EPA, 2011).
Application of the BW3/4 scaling factor is based
on adult animal and human body weights to adjust for
dosimetric differences (predominantly toxicokinetic)
between adult animals and humans (U.S. EPA, 2011).
The internal dosimetry of other life stages (e.g.,
children, pregnant or lactating mothers) may be
different from that of an adult (U.S. EPA, 2011). In
some cases where data are available on effects in
infants or children, adult PBTK models (if available)
could be parameterized in order to predict the dose
metric in children, as described in U.S. EPA's report,
A Framework for Assessing Health Risk of
Environmental Exposures to Children (U.S. EPA,
2006, 2011). However, more research is needed to
develop models for children's dosimetric adjustments
across life stages and experimental animal species
(U.S. EPA, 2006).
In Summary:
• No correction factors are applied to
RfDs, RfCs, cancer slope factors, and
inhalation unit risks when combined with
exposure information from specific
populations of interest.
• ADAFs are applied to oral slope factors
for chemicals with a mutagenic mode of
action as in Table 1A-1.
• Correction factors are applied to water
unit risks for both body weight and water
intake rate for specific populations of
interest. \
For cancer data from chronic animal studies, no
explicit lifetime adjustment is necessary when
extrapolating to humans because the assumption is
that events occurring in a lifetime animal bioassay
will occur with equal probability in a human lifetime.
For cancer data from human studies (either
occupational or general population), the Agency
typically makes no explicit assumptions regarding
body weight or human lifetime. For both of these
parameters, there is an implicit assumption that the
exposed population of interest has the same
characteristics as the population analyzed by the
Agency in deriving its dose-response information. In
the rare situation where this assumption is known to
be violated, the Agency has made appropriate
Page
1A-2
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 1—Introduction
corrections so that the dose-response parameters are
representative of the national average population.
For carcinogens acting through a mutagenic
MO A, where chemical-specific data concerning early
life susceptibility are lacking, early life susceptibility
should be assumed, and the following ADAFs should
be applied to the cancer slope factor as described in
the Supplemental Guidance for Assessing
Susceptibility from Early-Life Exposure to
Carcinogens (U.S. EPA, 2005) and summarized in
Section 1.9 of this handbook:
10-fold for exposures occurring before 2
years of age;
3-fold for exposures occurring between the
ages of 2 and 16 years of age; and
no adjustment for exposures occurring after
16 years of age.
In addition to cancer slope factors, dose-response
measures for carcinogens are also expressed as
increased cancer risk per unit concentration for
estimating risks from exposure to substances found in
air or water (U.S. EPA, 1992). For exposure via
inhalation, this dose-response value is referred to as
an IUR and is typically expressed in units of
(ug/m3)"1. For exposure via drinking water, this dose-
response value is termed the unit risk for drinking
water (oral) (U.S. EPA, 1992). These unit risk
estimates implicitly assume standard adult intake
rates (i.e., 2 L/day of drinking water; 20-m3/day
inhalation rate). It is generally not appropriate to
adjust the inhalation unit risk for different body
weights or inhalation rates because the amount of
chemical that reaches the target site is not a simple
function of two parameters (U.S. EPA, 2009). For
drinking water unit risks, however, it would be
appropriate for risk assessors to replace the standard
intake rates with values representative of the exposed
population of interest, as described in Section 1A-2
and Table 1A-1 below (U.S. EPA, 2005).
As indicated above, for non-cancer effects, dose-
response assessment is based on a threshold
hypothesis, which holds that there is a dose above
which effects (or their precursors) begin to occur. The
U.S. EPA defines the RfD as "an estimate of a daily
oral exposure for a given duration to the human
population (including susceptible subgroups) that is
likely to be without an appreciable risk of adverse
health effects over a lifetime. It is derived from a
benchmark dose lower confidence limit (BMDL), a
no-observed-adverse-effect level, a
lowest-observed-adverse-effect level, or another
suitable point of departure, with
uncertainty/variability factors applied to reflect
limitations of the data used." The point of departure
on which the RfD is based can come directly from
animal dosing experiments or occasionally from
human studies followed by application of uncertainty
factors to reflect uncertainties such as extrapolating
from subchronic to chronic exposure, extrapolating
from animals to humans, and deficiencies in the
toxicity database. Consistent with the derivation of
oral cancer slope factors noted above, the U.S. EPA
prefers the use of PBTK modeling to derive HEDs to
extrapolate from data in laboratory animal species,
but in the absence of a PBTK model, endorses the use
of BW3/4 as the appropriate default scaling factor for
use in calculating HEDs for use in derivation of the
oral RfD (U.S. EPA, 2011). Body-weight scaling
using children's body weight may not be appropriate
in the derivation of the RfD because RfDs are already
intended to be protective of the entire population
including susceptible populations such as children
and other life stages (U.S. EPA, 2011). Uncertainty
factors are used to account for intraspecies variation
in susceptibility (U.S. EPA, 2011). As indicated
above, body-weight scaling is meant to
predominantly address toxicokinetic differences
between animals and humans and can be viewed as a
dosimetric adjustment factor (DAF). Data on
toxicodynamic processes needed to assess the
appropriateness of body-weight scaling for early life
stages are not currently available (U.S. EPA, 2011).
The procedure for deriving dose-response values
for non-cancer effects resulting from the inhalation
route of exposure (i.e., RfCs) differs from the
procedure used for deriving dose-response values for
non-cancer effects resulting from the oral route of
exposure (i.e., RfDs). The difference lies primarily in
the source of the DAFs that are employed. As with
the RfD, the U.S. EPA prefers the application of
PBTK modeling in order to extrapolate laboratory
animal exposure concentrations to HECs for the
derivation of an RfC. In the absence of a PBTK
model, the U.S. EPA advocates the use of a default
procedure for deriving HECs that involve application
of DAFs. This procedure uses species-specific
physiologic and anatomic factors relevant to the
physical form of the pollutant (i.e., paniculate or gas)
and categorizes the pollutant with regard to whether
it elicits a response either locally (i.e., within the
respiratory tract) or remotely (i.e., extrarespiratory).
These factors are combined in determining an
appropriate DAF. The default dosimetric adjustments
and physiological parameters used in RfC derivations
assume an adult male with an air intake rate of 20
mVday and a body weight of 70 kg (U.S. EPA, 1994).
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Assumptions for extrathoracic, tracheobronchial, and
pulmonary surface areas are also made based on an
adult male (U.S. EPA, 1994). For gases, the
parameters needed for deriving a DAF include
species-to-species ratios of blood:gas partition
coefficients. For particulates, the DAF is termed the
regional deposition dose ratio and is derived from
parameters that include region-specific surface areas,
the ratio of animal-to-human minute volumes, and
the ratio of animal-to-human regional fractional
deposition. If DAFs are not available, simple
ventilation rate adjustments can be made in
generating HECs for use in derivation of the RfC
(U.S. EPA, 2006). Toxicity values (RfCs) derived
using the default approach from the inhalation
dosimetry methodology described in U.S. EPA (1994)
are developed for the human population as a whole,
including sensitive groups. Therefore, no quantitative
adjustments of these toxicity values are needed to
account for different ventilation rates or body weights
of specific age groups (U.S. EPA, 2009).
1A-2. CORRECTIONS FOR DOSE-RESPONSE
PARAMETERS
The correction factors for the dose-response
values tabulated in the IRIS database for non-cancer
and carcinogenic effects are summarized in Table 1A-
1. Use of these correction parameters is necessary to
avoid introducing errors into the risk analysis. This
table is applicable in most cases that will be
encountered, but it is not applicable when (a) the
effective dose has been derived with a PBTK model,
and (b) the dose-response data have been derived
from human data. In the former case, the population
parameters need to be incorporated into the model. In
the latter case, the correction factor for the
dose-response parameter must be evaluated on a
case-by case basis by examining the specific data and
assumptions employed in the derivation of the
parameter.
It is important to note that the 2 L/day per capita
water intake assumption is closer to a 90th percentile
intake value than an average value. If an average
measure of exposure in adults is of interest, the
drinking water unit risk can be adjusted by
multiplying it by 1.0/2 or 0.5, where 1.0 L/day is the
average per capita water intake for adults >21 years
old (see Chapter 3 of this handbook). If the
population of interest is children, rather than adults,
then a body-weight adjustment is also necessary. For
example, the average water intake for children 3 to
<6 years of age is 0.33 L/day (see Chapter 3 of this
handbook), and the average body weight in this age
group is 18.6 kg (see Chapter 8 of this handbook).
The water unit risk then needs to be adjusted by
multiplying it by an adjustment factor derived from
these age-group-specific values and calculated using
the formula from Table 1 A-l as follows:
Water unit risk correction factor =
033(L/day)
2(L/day)
= 0.6 (Eqn. 1A-1)
1A-3. REFERENCES FOR APPENDIX 1A
U.S. EPA (Environmental Protection Agency). (1992)
EPA's approach for assessing the risks
associated with chronic exposure to
carcinogens. Background Document 2.
National Center for Environmental
Assessment, Office of Research and
Development, Washington, DC. Available
online at
http: //www. epa. gov/iris/carcino. htm.
U.S. EPA (Environmental Protection Agency). (1993)
Reference dose (RfD): Description and use
in health risk assessments. Background
Document 1A. National Center for
Environmental Assessment, Office of
Research and Development, Washington,
DC. Available online at
http: //www. epa. gov/iris/rfd. htm.
U.S. EPA (Environmental Protection Agency). (1994)
Methods for derivation of inhalation
reference concentration and application of
inhalation dosimetry. Office of Research
and Development, Office of Health and
Environmental Assessment, Washington,
DC; EPA/600/8-90/066F Available online at
http://cfpub.epa.gOv/ncea/cfm/recordisplay.c
fm?deid=71993.
U.S. EPA (Environmental Protection Agency).
(2005) Supplemental guidance for assessing
susceptibility from early-life exposure to
carcinogens. National Center for
Environmental Assessment, Office of
Research and Development, Washington,
DC; EPA/630/P-03/001F. Available online
http://www.epa.gov/raf/publications/pdfs/chi
ldrens_supplement_final.pdfhttp://www.epa.
gov/raf/publications/pdfs/CANCER_GUIDE
LINES FINAL 3-25-05.PDF.
Page
1A-4
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U.S. EPA (Environmental Protection Agency). (2006)
A framework for assessing health risks of
environmental exposures to children.
National Center for Environmental
Assessment, Office of Research and
Development, Washington, DC; EPA/600/R-
05/093F. Available online at
http://cfpub.epa.gOv/ncea/cfm/recordisplay.c
fm?deid=158363.
U.S. EPA (Environmental Protection Agency). (2009)
Risk assessment guidance for superfund,
Volume I: Human health evaluation manual
(PartF, supplemental guidance for
inhalation risk assessment). Office of Solid
Waste and Emergency Response,
Washington, DC; EPA-540-R-070-002.
Available online at
http://www.epa.gov/oswer/riskassessment/ra
gsf/pdf/l-partf_20090 l_cover.pdf.
U.S. EPA (Environmental Protection Agency). (2011)
Recommended use of body weight374 as the
default method in derivation of the oral
reference dose. Risk Assessment Forum,
Washington, DC; EPA/100/R-ll/OOOl.
Available online at
http ://www. epa. gov/raf/publications/interspe
cies-extrapolation.htm.
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Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-Standard Populations
IRIS Risk Measure [Units] Correction Factor (CF) for modifying IRIS Risk Measures3
RfD No correction factor needed
RfC No correction factor needed
Slope Factor [mg/(kg-day)]"1 No correction factor needed except for chemicals with mutagenic MO A. ADAFs
are applied as follows:
. 10-fold for exposure occurring before 2 years of age
• 3-fold for exposure occurring between the ages of 2 and 16
• no adjustment for exposures occurring after 16 years of age
Water Unit Risk [ug/Lf1 [///2] x [70/(^)]
Air Unit Risk [ug/m3]"1 No correction factor needed
a Modified risk measure = (CF) x IRIS value.
W = Body weight (kg)
Iw = Drinking water intake (liters per day)
V^, IWF = Denote non-standard parameters from the actual population of interest
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TABLE OF CONTENTS
VARIABILITY AND UNCERTAINTY 2-1
2.1. VARIABILITY VERSUS UNCERTAINTY 2-1
2.2. TYPES OF VARIABILITY 2-2
2.3. ADDRESSING VARIABILITY 2-2
2.4. TYPES OF UNCERTAINTY 2-3
2.5. REDUCING UNCERTAINTY 2-4
2.6. ANALYZING VARIABILITY AND UNCERTAINTY 2-4
2.7. LITERATURE REVIEW OF VARIABILITY AND UNCERTAINTY ANALYSIS 2-5
2.8. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSES 2-7
2.9. REFERENCES FOR CHAPTER 2 2-8
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2. VARIABILITY AND UNCERTAINTY
Accounting for variability and uncertainty is
fundamental to exposure assessment and risk
analysis. While more will be said about the
distinction between variability and uncertainty in
Section 2.1, it is useful at this point to motivate the
treatment of variability and uncertainty in exposure
assessment. Given that exposure and susceptibility to
exposure is usually not uniform across a population,
accounting for variability is the means by which a
risk assessor properly accounts for risk to the
population as a whole. However, a risk assessment
usually involves uncertainties about the precision of a
risk estimate. A heuristic distinction between
variability and uncertainty is to consider uncertainty
as a lack of knowledge about factors affecting
exposure or risk, whereas variability arises from
heterogeneity across people, places, or time.
Properly addressing variability and uncertainty
will increase the likelihood that results of an
assessment or analysis will be used in an appropriate
manner. Characterizing and communicating
variability and uncertainty should be done throughout
all the components of the risk assessment process
(NRC, 1994). Thus, careful consideration of the
variability and uncertainty associated with the
exposure factors information used in an exposure
assessment is of utmost importance. Proper
characterization of variability and uncertainty will
also support effective communication of risk
estimates to risk managers and the public.
This chapter provides an overview of variability
and uncertainty in the context of exposure analysis
and is not intended to present specific methodological
guidance. It is intended to acquaint the exposure
assessor with some of the fundamental concepts of
variability and uncertainty as they relate to exposure
assessment and the exposure factors presented in this
handbook. It also provides summary descriptions of
methods and considerations for evaluating and
presenting the uncertainty associated with exposure
estimates and a bibliography of references on a wide
range of methodologies concerned with the
application of variability and uncertainty analysis in
exposure assessment. Subsequent sections in this
chapter are devoted to the following topics:
2.1 Variability versus uncertainty;
2.2 Types of variability;
2.3 Addressing variability;
2.4 Types of uncertainty;
2.5 Reducing uncertainty;
2.6 Analyzing variability and uncertainty;
2.7
Literature review of variability and
uncertainty analysis;
Presenting results of variability and
uncertainty analyses; and
2.9 References.
2.8
There are numerous ongoing efforts in the U.S.
Environmental Protection Agency (EPA) and
elsewhere to further improve the characterization of
variability and uncertainty. The U.S. EPA's Risk
Assessment Forum has established guidelines for the
use of probabilistic techniques (e.g.,, Monte Carlo
analysis) to better assess and communicate risk
(U.S. EPA, 1997a, b). The U.S. EPA's Science Policy
Council is developing white papers on the use of
expert elicitation for characterizing uncertainty in
risk assessments. Expert judgment has been used in
the past by some regulatory agencies when limited
data or knowledge results in large uncertainties
(NRC, 2009). The International Program on
Chemical Safety (IPCS) has developed guidance on
characterizing and communicating uncertainty in
exposure assessment (WHO, 2008). Suggestions for
further reading on variability and uncertainty include
Babendreier and Castleton (2005), U.S. EPA (2008),
Saltelli and Annoni (2010), Bogen et al. (2009), and
Refsgaard (2007).
2.1. VARIABILITY VERSUS UNCERTAINTY
While some authors have treated variability as a
specific type or component of uncertainty, the U.S.
EPA (1995), following the NRC (1994)
recommendation, has advised the risk assessor to
distinguish between variability and uncertainty.
Variability is a quantitative description of the range
or spread of a set of values. Common measures
include variance, standard deviation, and interquartile
range. Variability arises from heterogeneity across
individuals, places, or time. Uncertainty can be
defined as a lack of precise knowledge, either
qualitative or quantitative. In the context of exposure
assessment, data uncertainty refers to the lack of
knowledge about factors affecting exposure.
The key difference between uncertainty and
variability is that variability cannot be reduced, only
better characterized (NRC, 2009).
We will describe a brief example of human water
consumption in relation to lead poisoning to help
distinguish between variability and parameter
uncertainty (a particular type of uncertainty). We
might characterize the variability of water
consumption across individuals by sampling from a
population and measuring water consumption. From
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this sample, we obtain useful statistics on the
variability of water consumption, which we assume
here represents the population of interest. There may
be similar statistics on the variability in the
concentration of lead in the water consumed. A risk
model may include a factor (i.e., dose response,
representing the absorption of lead from ingested
water to blood). The dose response may be
represented by a constant in a risk model. However,
knowledge about the dose response may be uncertain,
motivating an uncertainty analysis. Dose response
values are often relatively uncertain compared to
exposure parameters. Therefore, in the above
example, a high uncertainty surrounds the absorption
of lead, whereas there is less uncertainty associated
with the parameters of water consumption (i.e.,
population mean and standard deviation). One
challenge in modeling dose-response uncertainty is
the lack of consensus on its treatment.
Most of the data presented in this handbook
concern variability. Factors contributing to variability
in risk include variability in exposure potential (e.g.,
differing behavioral patterns, location), variability in
susceptibility due to endogenous factors (e.g., age,
sex, genetics, pre-existing disease), variability in
susceptibility due to exogenous factors (e.g.,
exposures to other agents) (NRC, 2009).
2.2. TYPES OF VARIABILITY
Variability in exposure is dependent on
contaminant concentrations as well as variability in
human exposure factors. Human exposure factors
may vary because of an individual's location, specific
exposure time, or behavior. However, even if all of
those factors were constant across a set of
individuals, there could still be variability in risk
because of variability in susceptibilities. Variations in
contaminant concentrations and human exposure
factors are not necessarily independent. For example,
contaminant concentrations and behavior might be
correlated.
A useful way to think about sources of variability
is to consider these four broad categories:
1) Spatial variability: variability across
locations;
2) Temporal variability: variability over time;
3) Intra-individual variability: variability within
an individual; and
4) Inter-individual variability: variability across
individuals.
Spatial variability refers to differences that may
occur because of location. For example, outdoor
pollutant levels can be affected at the regional level
by industrial activities and at the local level by
activities of individuals. In general, higher exposures
tend to be associated with closer proximity to a
pollutant source, whether it is an industrial plant or
related to a personal activity such as showering or
gardening. Susceptibilities may vary across locations,
for example, some areas have particularly high
concentrations of a younger or older population.
Temporal variability refers to variations over
time, whether long- or short-term. Different seasons
may cause varied exposure to pesticides, bacteria, or
indoor air pollution, each of which might be
considered an example of long-term variability.
Examples of short-term variability are differences in
industrial or personal activities on weekdays versus
weekends or at different times of the day.
Intra-individual variability is a function of
fluctuations in an individual's physiologic (e.g., body
weight), or behavioral characteristics (e.g., ingestion
rates or activity patterns). For example, patterns of
food intake change from day to day and may do so
significantly over a lifetime. Intra-individual
variability may be associated with spatial or temporal
variability. For example, because an individual's
dietary intake may reflect local food sources, intake
patterns may change if place of residence changes.
Also, physical activity may vary depending upon the
season, life stage, or other factors associated with
temporal variability.
Inter-individual variability refers to variation
across individuals. Three broad categories include the
following:
1) individual characteristics such as sex, age, race,
height, or body weight (including any obesity),
phenotypic genetic expression, and
pathophysiological conditions;
2) individual behaviors such as activity patterns,
and ingestion rates; and
3) susceptibilities due to such things as life stage
or genetic predispositions.
Inter-individual variability may also be
related to spatial and temporal factors.
2.3. ADDRESSING VARIABILITY
In this handbook, variability is addressed by
presenting data on the exposure factors in one of the
following three ways: (1) as tables with percentiles or
ranges of values for various age groups or other
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populations, (2) as probability distributions with
specified parameter estimates and related confidence
intervals, or (3) as a qualitative discussion. One
approach to exposure assessment is to assume a
single value for a given exposure level, often the
mean or median, in order to calculate a single point
estimate of risk. Often however, individuals vary in
their exposure, and an exposure assessment would be
remiss to exclude other possible exposure levels.
Thus, an exposure assessment often involves a
quantification of the exposure at high levels of the
exposure factor, i.e., 90th, 95th, and 99th percentiles,
and not only the mean or median exposure. Where
possible, confidence limits for estimated percentiles
should be provided. The U.S. EPA's approach to
variability assessment is described in Risk Assessment
Principles and Practices: Staff Paper (U.S. EPA,
2004). Accounting for variability in an exposure
assessment may be limited to a deterministic model
in which high-end values are used or may involve a
probabilistic approach, e.g., Monte Carlo Analysis
(U.S. EPA, 1997a).
Populations are by nature heterogeneous.
Characterizing the variability in the population can
assist in focusing analysis on segments of the
population that may be at higher risk from
environmental exposure. Although population
variability cannot be reduced, data variability can be
lessened by disaggregating the population into
segments with similar characteristics.
Although much of this handbook is concerned
with variability in exposure, it is critical to note that
there are also important variations among individuals
in a population with respect to susceptibility. As
noted in NRC (2009), people differ in susceptibility
to the toxic effects of a given chemical exposure
because of such factors as genetics, lifestyle,
predisposition to diseases and other medical
conditions, and other chemical exposures that
influence underlying toxic processes. Susceptibility is
also a function of life stages, e.g., children may be at
risk of high exposure relative to adults. Susceptibility
factors are broadly considered to include any factor
that increases (or decreases) the response of an
individual to a dose relative to a typical individual in
the population. The distribution of disease in a
population can result not only from differences in
susceptibility, but from differing exposures of
individuals and target groups in a population. Taken
together, variations in disease susceptibility and
exposure potential give rise to potentially important
variations in vulnerability to the effects of
environmental chemicals (NRC, 2009).
2.4. TYPES OF UNCERTAINTY
Uncertainty in exposure analysis is related to the
lack of knowledge concerning one or more
components of the assessment process. The U.S. EPA
(1992) has classified uncertainty in exposure
assessment into three broad categories: (1) scenario
uncertainty, (2) parameter uncertainty, and (3) model
uncertainty.
Scenario uncertainty
Scenario uncertainty arises from descriptive
errors, aggregation errors, errors in professional
judgment, and incomplete analysis. Descriptive
errors are errors in information that translate into
errors in the development of exposure pathways,
scenarios, exposed population, and exposure
estimates. Aggregation errors occur as a result of
lumping approximations. These include, for
example, assuming a homogeneous population, and
spatial and temporal assumptions. Uncertainty can
also arise from errors in professional judgment.
These errors affect how an exposure scenario is
defined, the selection of exposure parameters,
exposure routes and pathways, populations of
concern, chemicals of concern, and the selection of
appropriate models. An incomplete analysis can also
be a source of uncertainty because important
exposure scenarios and susceptible populations may
be overlooked.
Parameter uncertainty
Risk assessments depict reality interpreted
through mathematical representations that describe
major processes and relationships. Process or
mechanistic models use equations to describe the
processes that an environmental agent undergoes in
the environment in traveling from the source to the
target organism. Mechanistic models have also been
developed to represent the toxicokinetic and
toxicodynamic processes that take place inside the
organism, leading to the toxic endpoint. The specific
parameters of the equations found in these models are
factors that influence the release, transport, and
transformation of the environmental agent, the
exposure of the target organism to the agent, transport
and metabolism of the agent in the body, and
interactions on the cellular and molecular levels.
Empirical models are also used to define
relationships between two values, such as the dose
and the response. Uncertainty in parameter estimates
stem from a variety of sources, including the
following:
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a. Measurement errors:
1. Random errors in analytical devices (e.g.,
imprecision of continuous monitors that
measure stack emissions).
2. Systemic bias (e.g., estimating inhalation
from indoor ambient air without
considering the effect of volatilization of
contaminants from hot water during
showers).
b. Use of surrogate data for a parameter instead
of direct analysis of it (e.g., use of standard
emission factors for industrialized processes).
c. Misclassification (e.g., incorrect assignment
of exposures of subjects in historical
epidemiologic studies due to faulty or
ambiguous information).
d. Random sampling error (e.g., variation in
estimates due to who was randomly selected).
e. Non-representativeness with regard to
specified criteria (e.g., developing emission
factors for dry cleaners based on a sample of
"dirty" plants that do not represent the overall
population of plants).
Model uncertainty
Model uncertainties arise because of gaps in the
scientific theory that is required to make predictions
on the basis of causal inferences. Common types of
model uncertainties in various risk assessment-related
activities include the following:
a. Relationship errors (e.g., incorrectly inferring
the basis of correlations between chemical
structure and biological activity).
b. Oversimplified representations of reality (e.g.,
representing a three-dimensional aquifer with
a two-dimensional mathematical model).
c. Incompleteness, i.e., exclusion of one or more
relevant variables (e.g., relating asbestos to
lung cancer without considering the effect of
smoking on both those exposed to asbestos
and those unexposed).
d. Use of surrogate variables for ones that cannot
be measured (e.g., using wind speed at the
nearest airport as a proxy for wind speed at
the facility site).
e. Failure to account for correlations that cause
seemingly unrelated events to occur more
frequently than expected by chance (e.g., two
separate components of a nuclear plant are
both missing a particular washer because the
same newly hired assembler put them
together).
f. Extent of (dis)aggregation used in the model
(e.g., whether to break up the fat compartment
into subcutaneous and abdominal fat in a
physiologically based pharmacokinetic, or
PBPK, model).
Although difficult to quantify, model uncertainty
is inherent in risk assessment that seeks to capture the
complex processes impacting release, environmental
fate and transport, exposure, and exposure response.
2.5. REDUCING UNCERTAINTY
Identification of the sources of uncertainty in an
exposure assessment is the first step in determining
how to reduce uncertainty. Because uncertainty in
exposure assessments is fundamentally tied to a lack
of knowledge concerning important exposure factors,
strategies for reducing uncertainty often involve the
application of more resources to gather either more or
targeted data. Example strategies to reduce
uncertainty include (1) collecting new data,
(2) implementing an unbiased sample design,
(3) identifying a more direct measurement method or
a more appropriate target population, (4) using
models to estimate missing values, (5) using
surrogate data, (6) using default assumptions,
(7) narrowing the scope of the assessment, and
(8) obtaining expert elicitation. The best strategy
likely depends on a combination of resource
availability, time constraints, and the degree of
confidence necessary in the results.
2.6. ANALYZING VARIABILITY AND
UNCERTAINTY
There are different strategies available for
addressing variability and uncertainty that vary in
their level of sophistication. The level of effort
required to conduct the analysis needs to be balanced
against the need for transparency and timeliness.
Exposure assessments are often developed in a
tiered approach. The initial tier usually screens out
the exposure scenarios or pathways that are not
expected to pose much risk, to eliminate them from
more detailed, resource-intensive review. Screening-
level assessments typically examine exposures on the
high end of the expected exposure distribution.
Because screening-level analyses usually are
included in the final exposure assessment, it may
contain scenarios that differ in sophistication, data
quality, and amenability to quantitative expressions
of variability or uncertainty. Several approaches can
be used to analyze uncertainty in parameter values.
When uncertainty is high, for example, an assessor
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may set order-of-magnitude bounding estimates of
parameter ranges (e.g., from 0.1 to 10 liters for daily
water intake). Another method may involve setting a
range for each parameter as well as point estimates
for certain parameters determined by available data
or professional judgment.
A sensitivity analysis can be used to determine
which parameters and exposures have the most
impact on an exposure assessment. General concepts
in sensitivity analysis are described in Saltelli et al.
(2008). The International Program on Chemical
Safety proposes a four-tier approach for addressing
uncertainty and variability (WHO, 2006). The four
tiers are similar to those proposed in U.S. EPA (1992)
and include the use of default assumptions; a
qualitative, systematic identification and
characterization of uncertainty; a qualitative
evaluation of uncertainty using bounding estimates,
interval analysis, and sensitivity analysis; and a more
sophisticated one- or two-stage probabilistic analysis
(WHO, 2006).
Practical considerations regarding an uncertainty
analysis include whether uncertainty would affect the
results in a non-trivial way; an issue might be
addressed by an initial sensitivity analysis in which a
range of values are explored. An initial analysis of
this sort might be facilitated by use of Microsoft
Excel. Probabilistic risk analysis techniques are
becoming more widely applied and are increasing in
the level of sophistication. Bedford and Cooke (2001)
describe in more detail the main tools and modeling
techniques available for probabilistic risk analysis
(Bedford and Cooke, 2001). If a probabilistic
approach is pursued, another consideration is the
choice of a software package. Popular software
packages for Monte Carlo analysis range from the
more general: Fortran, Mathematica, R, and SAS to
the more specific: Crystal Ball, @Risk (Palisade
Corporation), RISKMAN (PLG Inc.), and SimLab
(Saltelli et al., 2004).
Increasingly, probabilistic methods are being
utilized to analyze variability and uncertainty
independently as well as simultaneously. It is
sometimes challenging to distinguish between
variability and parameter uncertainty in this context
as both can involve the distributions of a random
variable. For instance, parameter uncertainty can be
estimated by the standard error of a random variable
(itself a function of variability). Note that in this case,
increasing the sample size necessarily reduces the
parameter uncertainty (i.e., standard error).
More sophisticated techniques that attempt to
simultaneously model both variability and
uncertainty by sampling from their respective
probability distributions are known as two-stage
probabilistic analysis, or two-stage Monte Carlo
analysis, which is discussed in great detail in Bogen
and Spear (1987), Bogen (1990), Chapter 11 and
Appendix 1-3 of NRC (1994), and U.S. EPA (2001).
These methods assume a probabilistic distribution for
certain specified parameters. Random samples are
drawn from each probabilistic distribution in a
simulation and are used as input into a deterministic
model. Analysis of the results from the simulations
characterizes either the variability or uncertainty (or
both) of the exposure assessment.
Through the implementation of computationally
efficient Markov Chain Monte Carlo algorithms like
Metropolis-Hastings, Bayesian methods offer an
alternative approach to uncertainty analysis that is
attractive in part because of increasing usability of
software. For more on Bayesian methods, see
Gelman et al. (2003), Gilks et al. (1995), Robert and
Casella (2004).
The U.S. EPA has made significant efforts to use
probabilistic techniques to characterize uncertainty.
These efforts have resulted in documents such as the
March 1997 Guiding Principles for Monte Carlo
Analysis (U.S. EPA, 1997a), the May 1997 Policy
Statement (U.S. EPA, 1997b), and the December
2001 Superfund document Risk Assessment Guidance
for Superfund: Volume III—Part A, Process for
Conducting Probabilistic Risk Assessment (U.S. EPA,
2001).
2.7. LITERATURE REVIEW OF
VARIABILITY AND UNCERTAINTY
ANALYSIS
There has been a great deal of recent scholarly
research in the area of uncertainty with the
widespread use of computer simulation. Some of this
research also incorporates issues related to variability.
The purpose of the literature review below is to give
a brief description of notable developments. Section
2.9 provides references for further research.
Cox (1999) argues that, based on information
theory, models with greater complexity lead to more
certain risk estimates. This may only be true if there
is some degree of certainty in the assumptions used
by the model. Uncertainties associated with the
model need to be evaluated (NRC, 2009). These
methods were discussed in Bogen and Spear (1987),
Cox and Baybutt (1981), Rish and Marnicio (1988),
and U.S. EPA (1985). Seiler (1987) discussed the
analysis of error propagation with respect to general
mathematical formulations typically found in risk
assessment, such as linear combinations, powers of
one variable, and multiplicative normally distributed
variables. Even for large and uncertain errors, the
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formulations in Seiler (1987) are demonstrated to
have practical value. Iman and Helton (1988)
compared three methodologies for uncertainty and
sensitivity analysis: (1) response surface analysis, (2)
Latin hypercube sampling (with and without
regression analysis), and (3) differential analysis.
They found that Latin hypercube sampling with
regression analysis had the best performance in terms
of flexibility, estimate-ability, and ease of use. Saltelli
(2002) and Frey (2002) offer views on the role of
sensitivity analysis in risk assessment, and Frey and
Patil (2002) compare methods for sensitivity analysis
and recommend that two or more different sensitivity
assessment methods should be used in order to obtain
robust results. A Bayesian perspective on sensitivity
analysis is described in Greenland (2001), who
recommends that sensitivity analysis and Monte
Carlo risk analysis should begin with specification of
prior distributions, as in Bayesian analysis. Bayesian
approaches to uncertainty analysis are described in
Nayak and Kundu (2001).
Price et al. (1999) review the history of the
inter-individual variability factor, as well as the
relative merits of the sensitive population conceptual
model versus the finite sample size model in
determining the magnitude of the variability factor.
They found that both models represent different
sources of uncertainty and that both should be
considered when developing inter-individual
uncertainty factors. Uncertainties related to inter-
individual and inter-species variability are treated in
Hattis (1997) and Meek (2001), respectively. And
Renwick (1999) demonstrates how inter-species and
inter-individual uncertainty factors can be
decomposed into kinetic and dynamic defaults by
taking into account toxicodynamic and toxicokinetic
differences. Burin and Saunders (1999) evaluate the
robustness of the intra-species uncertainty factor and
recommend intra-species uncertainty factoring in the
range of 1-10.
Based on Monte Carlo analysis, Shlyakhter
(1994) recommends inflation of estimated
uncertainties by default safety factors in order to
account for unsuspected uncertainties.
Jayjock (1997) defines uncertainty as either
natural variability or lack of knowledge and also
provides a demonstration of uncertainty and
sensitivity analysis utilizing computer simulation.
Additional approaches for coping with uncertainties
in exposure modeling and monitoring are addressed
by Nicas and Jayjock (2002).
Distributional risk assessment should be
employed when data are available that support its
use. Fayerweather et al. (1999) describe distributional
risk assessment, as well as its strengths and
weaknesses. Exposure metrics for distributional risk
assessment using log-normal distributions of time
spent showering (Burmaster, 1998a), water intake
(Burmaster, 1998b), and body weight (Burmaster and
Crouch, 1997; Burmaster, 1998c) have been
developed. The lognormal distribution provides a
succinct mathematical form that facilitates exposure
and risk analyses. The fitted lognormal distribution is
an approximation that should be carefully evaluated.
One approach is to compare the lognormal
distribution with other distributions (e.g., Weibull,
Gamma). This is the approach used by Jacobs et al.
(1998) and U.S. EPA (2002) in developing estimates
of fish consumption and U.S. EPA (2004) and Kahn
and Stralka (2008a) for estimates of water ingestion.
These estimates were derived from the Continuing
Survey of Food Intake by Individuals (CSFII), which
was a Nationwide statistical survey of the population
of the United States conducted by the U.S.
Department of Agriculture. The CSFII collected
extensive information on food and beverage intake
from a sample that represented the population of the
United States, and the sample weights provided with
the data supported the estimation of empirical
distributions of intakes for the entire population and
various target populations such as intake distributions
by various age categories. Kahn and Stralka (2008b)
used the CSFII data to estimate empirical
distributions of water ingestion by pregnant and
lactating women and compared the results to those
presented by Burmaster (1998b). The comparison
highlights the differences between the older data used
by Burmaster and the CSFII and the differences
between fitted approximate lognormal distributions
and empirical distributions. The CSFII also collected
data on body weight self-reported by respondents that
supported the estimation of body-weight distributions
by age categories, which are presented in Kahn and
Stralka (2008a). Detailed summary tables of results
based on the CSFII data used by Kahn and Stralka
(2008a) are presented in Kahn (2008) personal
communication (Kahn, 2008).
When sensitivity analysis or uncertainty
propagation analysis indicates that a parameter
profoundly influences exposure estimates, the
assessor should, if possible, develop a probabilistic
description of its range. It is also possible to use
estimates derived from a large-scale survey such as
the CSFII as a basis for alternative parameter values
that may be used in a sensitivity analysis. The CSFII
provides the basis for an objective point of reference
for food and beverage intake variables, which are
critical components of many risk and exposure
assessments. For example, an assumed value for a
mean or upper percentile could be compared to a
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suitable value from the CSFII to assess sensitivity.
Deterministic and probabilistic approaches to risk
assessment are reviewed for non-carcinogenic health
effects in Karlbelah et al. (2003), with attention to
quantifying sources of uncertainty. Kelly and
Campbell (2000) review guidance for conducting
Monte Carlo analysis and clarify the distinction
between variability and uncertainty. This distinction
is represented by two-stage Monte Carlo simulation,
where a probability distribution represents variability
in a population, while a separate distribution for
uncertainty defines the degree of variation in the
parameters of the population variability distribution.
Another example of two-stage Monte Carlo
simulation is given in Xue et al. (2006). Price et al.
(1997) utilize a Monte Carlo approach to characterize
uncertainties for a method aimed at estimating the
probability of adverse, non-cancer health effects for
exposures exceeding the reference dose. Their
method relies on general toxicologic information for
a compound, such as the no-observed-adverse-effect-
level dose (NOAEL). Semple et al. (2003) examine
uncertainty arising in reconstructed exposure
estimates using Monte Carlo methods. Uncertainty in
PBPK models is discussed in Simon (1997) and Bois
(2010). Slob and Pieters (1998) propose replacing
uncertainty factors with probabilistic uncertainty
distributions and discuss how uncertainties may be
quantified for animal NOAELs and extrapolation
factors. Zheng and Frey (2005) demonstrate the use
of Monte Carlo methods for characterizing
uncertainty and emphasize that uncertainty estimates
will be biased if contributions from sampling error
and measurement error are not accounted for
separately.
Distributional biometric data for probabilistic risk
assessment are available for some exposure factors.
Empirical distributions are provided in this handbook
when available. If the data are unavailable or
otherwise inadequate, expert judgment can be used to
generate a subjective probabilistic representation.
Such judgments should be developed in a consistent,
well-documented manner. Morgan and Henrion
(1990) and Rish (1988) describe techniques to solicit
expert judgment, while Weiss (2001) demonstrates
use of a Web-based survey.
Standard statistical methods may be less
cumbersome than a probabilistic approach and may
be preferred, if there are enough data to justify their
use and they are sufficient to support the
environmental decision needed. Epidemiologic
analyses may, for example, be used to estimate
variability in human populations, as in Peretz et al.
(1997), who describe variation in exposure time.
Sources of variation and uncertainty may also be
explored and quantified using a linear regression
modeling framework, as in Robinson and Hurst
(1997). A general framework for statistical
assessment of uncertainty and variance is given for
additive and multiplicative models in Rai et al.
(1996) and Rai and Krewski (1998), respectively.
Wallace and Williams (2005) describe a robust
method for estimating long-term exposures based on
short-term measurements.
In addition to the use of defaults and quantitative
analysis, exposure and risk assessors often rely on
expert judgment when information is insufficient to
establish uncertainty bounds (NRC, 2009). There are,
however, some biases introduced during expert
elicitation. Some of these include availability,
anchoring and adjustment, representativeness,
disqualification, belief in "law of small numbers,"
and overconfidence (NRC, 2009). Availability refers
to the tendency to assign greater probability to
commonly encountered or frequently mentioned
events (NRC, 2009). Anchoring and adjustment is the
tendency to be over-influenced by the first
information seen or provided (NRC, 2009).
Representativeness is the tendency to judge an event
by reference to another (NRC, 2009).
Disqualification is the tendency to ignore data or
evidence that contradicts strongly held convictions
(NRC, 2009). The belief in the "law of small
numbers" is to believe that small samples from a
population are more representative than is justified
(NRC, 2009). Overconfidence is the tendency of
experts to belief that their answers are correct (NRC,
2009).
2.8. PRESENTING RESULTS OF
VARIABILITY AND UNCERTAINTY
ANALYSES
The risk assessor is advised to distinguish
between variability of exposure and associated
uncertainties. A risk assessment should include three
components involving elements of variability and
uncertainty: (1) the estimated risk itself (X), (2) the
level of confidence (Y) that the risk is no higher than
X, and (3) the percent of the population (Z) that X is
intended to apply to in a variable population (NRC,
1994). This information will provide risk managers
with a better understanding of how exposures are
distributed over the population and of the certainty of
the exposure assessment.
Sometimes analyzing all exposure scenarios is
unfeasible. At minimum, the assessor should describe
the rationale for excluding reasonable exposure
scenarios; characterize the uncertainty in these
decisions as high, medium, or low; and state whether
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they were based on data, analogy, or professional
judgment. Where uncertainty is high, a sensitivity
analysis can be used to estimate upper limits on
exposure by way of a series of "what if' questions.
Although assessors have historically used
descriptors (e.g., high-end, worst case, average) to
communicate risk variability, the 1992 Guidelines for
Exposure Assessment (U.S. EPA, 1992) established
quantitative definitions for these risk descriptors. The
data presented in this handbook are one of the tools
available to exposure assessors to construct the
various risk descriptors. A thorough risk assessment
should include particular assumptions about human
behavior and biology that are a result of variability. A
useful example is given in NRC (1994):
"...a poor risk characterization for a
hazardous air pollutant might say 'The risk
number R is a plausible upper bound.'" A
better characterization would say, "The
risk number R applies to a person of
reasonably high-end behavior living at the
fenceline 8 hours a day for 35 years."
In addition to presenting variability in exposure,
frequently, exposure assessments include an
uncertainty analysis. An exposure assessment will
include assumptions about the contaminant,
contaminant exposure routes and pathways, location,
time, population characteristics, and susceptibilities.
Each of these assumptions may be associated with
uncertainties. Uncertainties may be presented using a
variety of techniques, depending on the requirements
of the assessment, the amount of data available, and
the audience. Simple techniques include risk
designations, i.e., high, medium, or low
(uncertainties. Sophisticated techniques may include
quantitative descriptions of the uncertainty analysis
or graphical representations.
The exposure assessor may need to make many
decisions regarding the use of existing information in
constructing scenarios and setting up the exposure
equations. In presenting the scenario results, the
assessor should strive for a balanced and impartial
treatment of the evidence bearing on the conclusions
with the key assumptions highlighted. For these key
assumptions, one should cite data sources and explain
any adjustments of the data.
The exposure assessor should describe the
rationale for any conceptual or mathematical models.
This discussion should address their verification and
validation status, how well they represent the
situation being assessed (e.g., average versus
high-end estimates), and any plausible alternatives in
terms of their acceptance by the scientific
community.
To the extent possible, this handbook provides
information that can be used in a risk assessment to
characterize variability, and to some extent,
uncertainty. In general, variability is addressed by
providing probability distributions, where available,
or qualitative discussions of the data sets used.
Uncertainty is addressed by applying confidence
ratings to the recommendations provided for the
various factors, along with detailed discussions of
any limitations of the data presented.
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Chapter 3—Ingestion of Water and Other Select Liquids
TABLE OF CONTENTS
LIST OF TABLES 3-iii
3. INGESTION OF WATER AND OTHER SELECT LIQUIDS 3-1
3.1. INTRODUCTION 3-1
3.2. RECOMMENDATIONS 3-2
3.2.1. Water Ingestion from Consumption of Water as a Beverage and from Food and
Drink 3-2
3.2.2. Pregnant and Lactating Women 3-2
3.2.3. Water Ingestion While Swimming or Diving 3-2
3.3. DRINKING WATER INGESTION STUDIES 3-9
3.3.1. Key Drinking Water Ingestion Study 3-9
3.3.1.1. Kahn and Stralka (2008a) 3-9
3.3.1.2. U.S. EPA Analysis of NHANES 2003-2006 Data 3-10
3.3.2. Relevant Drinking Water Ingestion Studies 3-11
3.3.2.1. Wolf (1958) 3-11
3.3.2.2. National Research Council (1977) 3-11
3.3.2.3. Hopkins and Ellis (1980) 3-12
3.3.2.4. Canadian Ministry of National Health and Welfare (1981) 3-12
3.3.2.5. Gillies and Paulin( 1983) 3-13
3.3.2.6. Pennington(1983) 3-13
3.3.2.7. U.S. EPA (1984) 3-14
3.3.2.8. Cantor etal. (1987) 3-14
3.3.2.9. Ershow and Cantor (1989) 3-15
3.3.2.10.RoseberryandBurmaster(1992) 3-15
3.3.2.11.Levy etal. (1995) 3-16
3.3.2.12.USDA(1995) 3-16
3.3.2.13.U.S. EPA (1996) 3-17
3.3.2.14.Helleretal. (2000) 3-17
3.3.2.15.Sichert-Hellertetal. (2001) 3-18
3.3.2.16.Sohnetal. (2001) 3-18
3.3.2.17.Hilbigetal. (2002) 3-19
3.3.2.18.Marshalletal. (2003a) 3-19
3.3.2.19.Marshalletal. (2003b) 3-20
3.3.2.20. Skinner etal. (2004) 3-20
3.4. PREGNANT AND LACTATING WOMEN 3-21
3.4.1. Key Study on Pregnant and Lactating Women 3-21
3.4.1.1. Kahn and Stralka (2008b) 3-21
3.4.2. Relevant Studies on Pregnant and Lactating Women 3-21
3.4.2.1. Ershow etal. (1991) 3-21
3.4.2.2. Forssenetal. (2007) 3-22
3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES 3-22
3.5.1. Relevant Studies on High Activity Levels/Hot Climates 3-22
3.5.1.1. McNall and Schlegel (1968) 3-22
3.5.1.2. U.S. Army (1983) 3-23
3.6. WATER INGESTION WHILE SWIMMING AND DIVING 3-23
3.6.1. Key Study on Water Ingestion While Swimming 3-23
3.6.1.1. Dufour et al. (2006) 3-23
3.6.2. Relevant Studies on Water Ingestion While Swimming, Diving, or Engaging in
Recreational Water Activities 3-24
3.6.2.1. Schijvenand de RodaHusman (2006) 3-24
3.6.2.2. Schets etal. (2011) 3-24
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Chapter 3—Ingestion of Water and Other Select Liquids
TABLE OF CONTENTS (continued)
3.6.2.3. Dorevitchetal. (2011) 3-25
3.7. REFERENCES FOR CHAPTER 3 3-25
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Chapter 3—Ingestion of Water and Other Select Liquids
LIST OF TABLES
Table 3-1. Recommended Values for Drinking Water Ingestion Rates 3-3
Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates 3-4
Table 3-3. Recommended Values for Water Ingestion Rates of Community Water for Pregnant and
Lactating Women 3-5
Table 3 -4. Confidence in Recommendations for Water Ingestion for Pregnant/Lactating Women 3-6
Table 3-5. Recommended Values for Water Ingestion While Swimming 3-7
Table 3-6. Confidence in Recommendations for Water Ingestion While Swimming 3-8
Table 3-7. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/day) 3-28
Table 3-8. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/day) 3-29
Table 3-9. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/day) 3-30
Table 3-10. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/day) 3-31
Table 3-11. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/kg-day) 3-32
Table 3-12. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/kg-day) 3-33
Table 3-13. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/kg-day) 3-34
Table 3-14. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/kg-day) 3-35
Table 3-15. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/day) 3-36
Table 3-16. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/day) 3-37
Table 3-17. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/day) 3-38
Table 3-18. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/day) 3-39
Table 3-19. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Community Water (mL/kg-day) 3-40
Table 3-20. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Bottled Water (mL/kg-day) 3-41
Table 3-21. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: Other Sources (mL/kg-day) 3-42
Table 3-22. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on 1994-1996,
1998 CSFII: All Sources (mL/kg-day) 3-43
Table 3 -23. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day) 3-44
Table 3-24. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES 2003-
2006: Bottled Water (mL/day) 3-45
Table 3 -25. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day) 3-46
Table 3-26. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day) 3-47
Table 3-27. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/day) 3-48
Table 3-28. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/kg-day) 3-49
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Chapter 3—Ingestion of Water and Other Select Liquids
LIST OF TABLES (continued)
Table 3-29. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES 2003-
2006: Bottled Water (mL/kg-day) 3-50
Table 3-30. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/kg-day) 3-51
Table 3-31. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/kg-day) 3-52
Table 3-32. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/kg-day) 3-53
Table 3-33. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day) 3-54
Table 3-34. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Bottled Water (mL/day) 3-55
Table 3-35. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day) 3-56
Table 3-36. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day) 3-57
Table 3-37. Consumers-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
NHANES 2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and
95th Percentiles: All Sources (mL/day) 3-58
Table 3-38. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: Community Water (mL/kg-day) 3-59
Table 3-39. Consumers-Only Estimates of Direct Water Ingestion Based on NHANES 2003-2006:
Bottled Water (mL/kg-day) 3-60
Table 3-40. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: Other Sources (mL/kg-day) 3-61
Table 3-41. Consumers-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006: All Sources (mL/kg-day) 3-62
Table 3-42. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
2003-2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th
Percentiles: All Sources (mL/kg-day) 3-63
Table 3-43. Assumed Tap Water Content of Beverages in Great Britain 3-64
Table 3-44. Intake of Total Liquid, Total Tap Water, and Various Beverages (L/day) by the British
Population 3-65
Table 3-45. Summary of Total Liquid and Total Tap Water Intake for Males and Females (L/day) in
Great Britain 3-66
Table 3-46. Daily Total Tap Water Intake Distribution for Canadians, by Age Group (Approx. 0.20-L
increments, both sexes, combined seasons) 3-67
Table 3-47. Average Daily Tap Water Intake of Canadians (expressed as mL/kg body weight) 3-68
Table 3-48. Average Daily Total Tap Water Intake of Canadians, by Age and Season (L/day) 3-68
Table 3-49. Average Daily Total Tap Water Intake of Canadians as a Function of Level of Physical
Activity at Work and in Spare Time (16 years and older, combined seasons, L/day) 3-69
Table 3-50. Average Daily Tap Water Intake by Canadians, Apportioned Among Various Beverages
(Both sexes, by age, combined seasons, L/day) 3-69
Table 3-51. Intake Rates of Total Fluids and Total Tap Water by Age Group 3-70
Table 3-52. Mean and Standard Error for the Daily Intake of Beverages and Tap Water by Age 3-70
Table 3-53. Average Total Tap Water Intake Rate by Sex, Age, and Geographic Area 3-71
Table 3-54. Frequency Distribution of Total Tap Water Intake Rates 3-71
Table 3-55. Total Tap Water Intake (mL/day) for Both Sexes Combined 3-72
Table 3-56. Total Tap Water Intake (mL/kg-day) for Both Sexes Combined 3-73
Table 3-57. Summary of Tap Water Intake by Age 3-74
Table 3-58. Total Tap Water Intake (as % of total water intake) by Broad Age Category 3-74
Table 3-59. General Dietary Sources of Tap Water for Both Sexes 3-75
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Chapter 3—Ingestion of Water and Other Select Liquids
LIST OF TABLES (continued)
Table 3-60. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates 3-76
Table 3-61. Estimated Quantiles and Means for Total Tap Water Intake Rates (mL/day) 3-76
Table 3-62 . Water Ingested (mL/day) from Water by Itself and Water Added to Other Beverages and
Foods 3-77
Table 3-63. Mean Per Capita Drinking Water Intake Based on USD A, CSFII Data From 1989-1991
(mL/day) 3-78
Table 3-64. Number of Respondents that Consumed Tap Water at a Specified Daily Frequency 3-79
Table 3-65. Number of Respondents that Consumed Juice Reconstituted with Tap Water at a
Specified Daily Frequency 3-80
Table 3 -66. Mean and (standard error) Water and Drink Consumption (mL/kg-day) by Race/Ethnicity 3-81
Table 3-67. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and
Poverty Category 3-82
Table 3-68. Intake of Water from Various Sources in 2- to 13-Year-Old Participants of the DONALD
Study, 1985-1999 3-83
Table 3-69. Mean (±standard error) Fluid Intake (mL/kg-day) by Children Aged 1 to 10 years,
NHANESIII, 1988-1994 3-83
Table 3 -70. Estimated Mean (±standard error) Amount of Total Fluid and Plain Water Intake Among
Children Aged 1 to 10 Years by Age, Sex, Race/Ethnicity, Poverty Income Ratio, Region,
and Urbanicity (NHANES III, 1988-1994) 3-84
Table 3-71. Tap Water Intake in Breast-Fed and Formula-Fed Infants and Mixed-Fed Young Children
at Different Age Points 3-85
Table 3-72. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes
(mL/day) for Children with Returned Questionnaires 3-86
Table 3-73. Mean (±standard deviation) Daily Beverage Intakes Reported on Beverage Frequency
Questionnaire and 3-Day Food and Beverage Diaries 3-87
Table 3-74. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) 3-88
Table 3-75. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-89
Table 3-76. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-90
Table 3-77. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-90
Table 3-78. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-91
Table 3-79. Estimates of Consumers Only Direct and Indirect Water Intake from All Sources by
Pregnant, Lactating, and Childbearing Age Women (mL/kg-day) 3-91
Table 3-80. Estimates of Consumers-Only Direct and Indirect Water Intake from All Sources by
Pregnant, Lactating, and Childbearing Age Women (mL/day) 3-92
Table 3-81. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day) 3-92
Table 3-82. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day) 3-93
Table 3-83. Total Fluid Intake of Women 15 to 49 Years Old 3-93
Table 3-84. Total Tap Water Intake of Women 15 to 49 Years Old 3-94
Table 3-85. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15 to 49
Years 3-94
Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women (L/day) 3-95
Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water by
Pregnant Women 3-97
Table 3-88. Water Intake at Various Activity Levels (L/hour) 3-99
Table 3-89. Planning Factors for Individual Tap Water Consumption 3-99
Table 3-90. Pool Water Ingestion by Swimmers 3-100
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Chapter 3—Ingestion of Water and Other Select Liquids
LIST OF TABLES (continued)
Table 3-91. Arithmetic Mean (Maximum) Number of Dives per Diver and Volume of Water Ingested
(mL/dive) 3-100
Table 3-92. Exposure Parameters for Swimmers in Swimming Pools, Freshwater, and Seawater 3-101
Table 3-93. Estimated Water Ingestion During Water Recreation Activities (mL/hr) 3-101
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Chapter 3—Ingestion of Water and Other Select Liquids
3. INGESTION OF WATER AND OTHER
SELECT LIQUIDS
3.1. INTRODUCTION
Water ingestion is another pathway of exposure
to environmental chemicals. Contamination of water
may occur at the water supply source (ground water
or surface water); during treatment (for example,
toxic by-products may be formed during
chlorination); or post-treatment (such as leaching of
lead or other materials from plumbing systems).
People may be exposed to contaminants in water
when consuming water directly as a beverage,
indirectly from foods and drinks made with water, or
incidentally while swimming. Estimating the
magnitude of the potential dose of toxics from water
ingestion requires information on the quantity of
water consumed. The purpose of this section is to
describe key and relevant published studies that
provide information on water ingestion for various
populations and to provide recommended ingestion
rate values for use in exposure assessments. The
studies described in this section provide information
on ingestion of water consumed as a beverage,
ingestion of other select liquids, and ingestion of
water while swimming. Historically, the U.S.
Environmental Protection Agency (EPA) has assumed
a drinking water ingestion rate of 2 L/day for adults
and 1 L/day for infants and children under 10 years
of age (U.S. EPA, 2000). This rate includes water
consumed in the form of juices and other beverages
containing tap water. The National Research Council
(NRC, 1977) estimated that daily consumption of
water may vary with levels of physical activity and
fluctuations in temperature and humidity. It is
reasonable to assume that people engaging in
physically-demanding activities or living in warmer
regions may have higher levels of water ingestion.
However, there is limited information on the effects
of activity level and climatic conditions on water
ingestion.
The U.S. EPA selected the analysis by Kahn and
Stralka (2008a) and Kahn (2008) of the (USDAs)
1994-1996, 1998 Continuing Survey of Food Intake
by Individuals (CSFII) as a key study of drinking
water ingestion for the general population of children
<3 years of age. U.S. EPAs 2010 analysis of
2003-2006 data from the National Health and
Nutrition Examination Survey (NHANES) was
selected as a key study of drinking water ingestion
for the general population of individuals >3 years of
age. Although NHANES 2003-2006 contains the
most up-to-date information on water intake rates,
estimates for children <3 years of age obtained from
the NHANES survey are less reliable due to sample
size limitations. Kahn and Stralka (2008b) was
selected as a key study of drinking water ingestion
for pregnant and lactating women. Kahn and Stralka
(2008b) used data from U.S. Department of
Agriculture's (USDAs) 1994-1996, 1998 Continuing
Survey of Food Intake by Individuals (CSFII). The
2010 U.S. EPA analysis of NHANES data and the
analyses by Kahn (2008) and Kahn and Stralka
(2008a, b) generated ingestion rates for direct and
indirect ingestion of water. Direct ingestion is defined
as direct consumption of water as a beverage, while
indirect ingestion includes water added during food
preparation but not water intrinsic to purchased foods
(i.e., water that is naturally contained in foods) (Kahn
and Stralka, 2008a, b). Data for consumption of water
from various sources (i.e., the community water
supply, bottled water, and other sources) are also
presented. It is noted that the type of water people are
drinking has changed in the last decade, as evidenced
by the increase in bottled water consumption.
However, the majority of the U.S. population
consumes water from public (i.e., community) water
distribution systems; about 15% of the U.S.
population obtains their water from private (i.e.,
household) wells, cisterns, or springs (U.S. EPA,
2002). Regardless of the source of the water, the
physiological need for water should be the same
among populations using community or private water
systems. For the purposes of exposure assessments
involving site-specific contaminated drinking water,
ingestion rates based on the community supply are
most appropriate. Given the assumption that bottled
water, and purchased foods and beverages that
contain water are widely distributed and less likely to
contain source-specific water, the use of total water
ingestion rates may overestimate the potential
exposure to toxic substances present only in local
water supplies; therefore, tap water ingestion of
community water, rather than total water ingestion, is
emphasized in this section.
The key studies on water ingestion for the
general population (CSFII and NHANES) and the
population of pregnant/lactating women (CSFII) are
both based on short-term survey data (2 days).
Although short-term data may be suitable for
obtaining mean or median ingestion values that are
representative of both short- and long-term ingestion
distributions, upper- and lower-percentile values may
be different for short-term and long-term data. It
should also be noted that most currently available
water ingestion surveys are based on respondent
recall. This may be a source of uncertainty in the
estimated ingestion rates because of the subjective
nature of this type of survey technique. Percentile
distributions for water ingestion are presented in this
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Chapter 3—Ingestion of Water and Other Select Liquids
handbook, where sufficient data are available. Data
are not provided for the location of water
consumption (i.e., home, school, daycare center, etc.).
Limited information was available regarding
incidental ingestion of water while swimming. A
recent pilot study (Dufour et al., 2006) has provided
some quantitative experimental data on water
ingestion among swimmers. These data are provided
in this chapter.
Section 3.2 provides the recommendations and
confidence ratings for water ingestion among the
general population and pregnant and lactating
women, and among swimmers. Section 3.3.1
provides the key studies for general water ingestion
rates, Section 3.4.1 provides ingestion rates for
pregnant and lactating women, and Section 3.6.1
provides ingestion rates for swimming. For water
ingestion at high activity levels or hot climates, no
recommendations are provided, but Section 3.5
includes relevant studies. Relevant studies on all
subcategories of water ingestion are also presented to
provide the reader with added perspective on the
current state-of-knowledge pertaining to ingestion of
water and select liquids.
3.2. RECOMMENDATIONS
3.2.1. Water Ingestion from Consumption of
Water as a Beverage and from Food and
Drink
The recommended water ingestion from the
consumption of water as a beverage and from foods
and drinks are based on Kahn and Stralka (2008a)
and Kahn (2008) for children <3 years of age and on
U.S. EPA's 2010 analysis of NHANES data from
2003-2006 for individuals >3 years of age. Table 3-1
presents a summary of the recommended values for
direct and indirect ingestion of community water. Per
capita mean and 95th percentile values range from
184 mL/day to 1,046 mL/day and 837 mL/day to
2,958 mL/day, respectively, depending on the age
group. Consumer-only mean and 95th percentile
values range from 308 mL/day to 1,288 mL/day and
858 mL/day to 3,092 mL/day, respectively,
depending on the age group. Per capita intake rates
represent intake that has been averaged over the
entire population (including those individuals that
reported no intake). In general, per capita intake rates
are appropriate for use in exposure assessments for
which average daily dose estimates are of interest
because they represent both individuals who drank
water during the survey period and individuals who
may drink water at some time but did not consume it
during the survey period. Consumer-only intake rates
represent the quantity of water consumed only by
individuals who reported water intake during the
survey period. Table 3-2 presents a characterization
of the overall confidence in the accuracy and
appropriateness of the recommendations for drinking
water intake.
3.2.2. Pregnant and Lactating Women
Based upon the results of Kahn and Stralka
(2008b), per capita mean and 95th percentile values
for ingestion of drinking water among pregnant
women were 819 mL/day and 2,503 mL/day,
respectively. The per capita mean and 95th percentile
values for lactating women were 1,379 mL/day and
3,434 mL/day, respectively. Table 3-3 presents a
summary of the recommended values for water
ingestion rates. Table 3-4 presents the confidence
ratings for these recommendations.
3.2.3. Water Ingestion While Swimming or
Diving
Based on the results of the Dufour et al. (2006)
study, mean water ingestion rates of 49 mL/hour for
children under 18 years of age and 21 mL/hour for
adults are recommended for exposure scenarios
involving swimming activities. Although these
estimates were derived from swimming pool
experiments, Dufour et al. (2006) noted that
swimming behavior of recreational pool swimmers
may be similar to freshwater swimmers. Estimates
may be different for salt water swimmers and
competitive swimmers. The recommended upper
percentile water ingestion rate for swimming
activities among children is based on the
97 percentile value of
120
mL/hour
(90 mL/0.75 hour) from Dufour et al. (2006).
Because the data set for adults is limited, the
maximum value observed in the Dufour et al. (2006)
study is used as an upper percentile value for adults:
71 mL/hour (53 mL/0.75 hour). Table 3-5 presents a
summary of the recommended values for water
ingestion rates. Table 3-6 presents the confidence
ratings for these recommendations. Data on the
amount of time spent swimming can be found in
Chapter 16 (see Table 16-1) of this handbook.
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Chapter 3 — Ingestion of Water and Other Select Liquids
Table 3-1. Recommended Values for Drinking Water Ingestion Rates"
Mean 95th Percentile
mL/day mL/kg-day mL/day mL/kg-day Multiple Percentiles
Per Capita11
Birth to <1 month0 184 52 839d 232d
1 to <3 months' 227 48 896d 205d
3 to <6 months' 362 52 1,056 159
6 to <12 months' 360 41 1,055 126
1 to <2 years' 271 23 837 71
2 to <3 years' 317 23 877 60
See Tables
3 to <6 years 327 18 959 51 3-7 and 3-11 for children
<3 years old and Tables 3-23
6to3 years old.
16 to <18 years 573 9 1,783 28
18 to <21 years 681 9 2,368 35
>21 years 1,043 13 2,958 40
>65 years 1,046 14 2,730 40
All ages' 869 14 2,717 42
Consumers-Only1
Birth to <1 month' 470d 137d 858d 238d
1 to <3 months' 552 119 1,053d 285d
3 to <6 months' 556 80 l,171d 173d
6to<12 months' 467 53 1,147 129
1 to <2 years' 308 27 893 75
2 to <3 years' 356 26 912 62
See Tables
3 to <6 years 382 21 999 52 3-15 and 3-19 for children
<3 years old and Tables 3-33
6 to < 11 years 511 17 1,404 47 and 3-38 for individuals
11 to <16 years 637 12 1,976 35 >3 years old.
16 to <18 years 702 10 1,883 30
18 to <21 years 816 11 2,818 36
>21 years 1,227 16 3,092 42
>65 years 1,288 18 2,960 43
All ages' 1,033 16 2,881 44
a Ingestion rates for combined direct and indirect water from community water supply.
b Per capita intake rates are generated by averaging consumer-only intakes over the entire population (including
those individuals that reported no intake).
' Based on Kahn and Stralka (2008a) and Kahn (2008).
d Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation
and Statistical Reporting Standards on NHANES 111 and CSF11 Reports: NHIS/NCHS Analytical Working
Group Recommendations (NCHS, 1993).
Based on U.S. EPA analysis of NHANES 2003-2006 data.
f Consumer-only intake represents the quantity of water consumed only by individuals that reported consuming
water during the survey period.
Source: Kahn and Stralka (2008a); Kahn (2008); U.S. EPA analysis of NHANES 2003-2006 data.
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
The survey methodology and data analysis were adequate.
The surveys sampled approximately 20,000 individuals
(CSFII) and 18,000 (NHANES) individuals; sample size
varied with age.
No physical measurements were taken. The method relied
on recent recall of standardized volumes of drinking water
containers.
Medium to High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key studies were directly relevant to water ingestion.
The data were demographically representative (based on
stratified random sample). Sample sizes for some age
groups were limited.
Data were collected between 1994 and 1998 for CSFII
and between 2003 and 2006 for NHANES.
Data were collected for 2 non-consecutive days.
However, long-term variability may be small. Use of a
short-term average as a chronic ingestion measure can be
assumed.
High
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The CSFII and NHANES data are publicly available.
The methodology was clearly presented; enough
information was included to reproduce the results.
CSFII and NHANES data collection follow strict QA/QC
procedures. Quality control of the secondary data analysis
was not well described.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were developed.
Except for data collection based on recall, sources of
uncertainty were minimal.
High
Evaluation and Review
Peer Review
Number and Agreement of Studies
The CSFII and NHANES surveys received a high level of
peer review. The CSFII data were published in the peer-
reviewed literature. The U.S. EPA analysis of NHANES
has not been peer-reviewed outside the Agency.
There were two key studies for drinking water ingestion
among the general population.
Medium
Overall Rating
Medium to High,
Low for footnote
"d" on Table 3-1
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-3. Recommended Values for Water Ingestion Rates of Community Water
for Pregnant and Lactating Women"
Per Capitab
Mean 95th Percentile
Gioup
mL/day mL/kg-day mL/day mL/kg-day
Pregnant women 819C 13C 2,503C 43C
Lactating women 1,379C 21C 3,434C 55C
Consumers-Only"1
Mean 95th Percentile
Group
mL/day mL/kg-day mL/day mL/kg-day
Pregnant women 872C 14C 2,589C 43C
Lactating women 1,665C 26C 3,588C 55C
a Ingestion rates for combined direct and indirect water from community water
supply.
b Per capita intake rates are generated by averaging consumer-only intakes over
the entire population (including those individuals that reported no intake).
0 Estimates are less statistically reliable based on guidance published in the Joint Policy
on Variance Estimation and Statistical Reporting Standards on NHANES III and
CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
1993).
d Consumer-only intake represents the quantity of water consumed only by
individuals that reported consuming water during the survey period.
Source: Kahn and Stralka, 2008b.
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Table 3-4. Confidence in Recommendations for Water Ingestion for Pregnant/Lactating Women
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Low
The survey methodology and data analysis were
adequate. The sample size was small, approximately
99 pregnant and lactating women.
No physical measurements were taken. The method
relied on recent recall of standardized volumes of
drinking water containers.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Low to Medium
The key study was directly relevant to water ingestion.
The data were demographically representative (based
on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for 2 non-consecutive days.
However, long-term variability may be small. Use of a
short-term average as a chronic ingestion measure can
be assumed.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The CSFII data are publicly available. The Kahn and
Stralka (2008b) analysis of the CSFII 1994-1996,
1998 data was published in a peer-reviewed journal.
The methodology was clearly presented; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were given in a separate document
(Kahn, 2008).
Except for data collection based on recall, sources of
uncertainty were minimal.
Low
Evaluation and Review
Peer Review
Number and Agreement of Studies
The USDA CSFII survey received a high level of peer
review. The Kahn and Stralka (2008b) study was
published in a peer-reviewed journal.
There was one key study for pregnant/lactating
women water ingestion.
Medium
Overall Rating
Low
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Table 3-5. Recommended Values for Water Ingestion
While Swimming
Ag
Children
Adults
a
b
c
Source:
Mean
3 Gioup
mL/eventa mL/hour
37 49
16 21
Participants swam for 45 minutes.
97th percentile.
Based on maximum value.
Dufour et al., 2006.
Upper Percentile
mL/eventa mL/hour
90b 120b
530 ?1c
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Table 3-6. Confidence in Recommendations for Water Ingestion While Swimming
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The approach appears to be appropriate given that
cyanuric acid (a tracer used in treated pool water) is not
metabolized, but the sample size was small (41 children
and 12 adults). The Dufour et al. (2006) study analyzed
primary data on water ingestion during swimming.
Data were collected over a period of 45 minutes; this may
not accurately reflect the time spent by a recreational
swimmer.
The key study was directly relevant to water ingestion
while swimming.
The sample was not representative of the U.S. population.
Data cannot be divided into by age categories.
It appears that the study was conducted in 2005.
Data were collected over a period of 45 minutes.
The Dufour et al. (2006) study was published in a peer-
reviewed journal.
The methodology was clearly presented; enough
information was included to reproduce the results.
Quality assurance methods were not described in the
study.
Full distributions were not available. Data were not
broken out by age groups.
There were multiple sources of uncertainty (e.g., sample
population may not reflect swimming practices for all
swimmers, rates based on swimming duration of
45 minutes, differences by age group not defined).
Dufour et al. (2006) was published in a peer-reviewed
journal.
There was one key study for ingestion of water when
swimming.
Rating
Medium
Low to Medium
Medium
Low
Medium
Low
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Chapter 3—Ingestion of Water and Other Select Liquids
3.3.
DRINKING
STUDIES
WATER INGESTION
3.3.1. Key Drinking Water Ingestion Study
3.3.1.1. Kahn and Stralka (2008a)—Estimated
Daily Average Per Capita Water
Ingestion by Child and Adult Age
Categories Based on USDA's 1994-1996
and 1998 Continuing Survey of Food
Intakes by Individuals and Supplemental
Data, Kahn (2008)
Kahn and Stralka (2008a) analyzed the combined
1994-1996 and 1998 CSFII data sets to examine
water ingestion rates of more than 20,000 individuals
surveyed, including approximately 10,000 under age
21 and 9,000 under age 11. USD A surveyed
households in the United States and District of
Columbia and collected food and beverage recall data
as part of the CSFII (USDA, 1998). Data were
collected by an in-home interviewer. The Day 2
interview was conducted 3 to 10 days later and on a
different day of the week. Each individual in the
survey was assigned a sample weight based on his or
her demographic data. These weights were taken into
account when calculating mean and percentile water
ingestion rates from various sources. Kahn and
Stralka (2008a) derived mean and percentile
estimates of daily average water ingestion for the
following age categories: <1 month, 1 to <3 months,
3 to <6 months, 6 to <12 months, 1 to <2 years of
age, 2 to <3 years, 3 to <6 years, 6 to <11 years, 11 to
<16 years, 16 to <18 years, 18 to <21 years of age,
21 years and older, 65 years and older, and all ages.
The increased sample size for children younger than
11 years of age (from 4,339 in the initial 1994-1996
survey to 9,643 children in the combined 1994-1996,
1998 survey) enabled water ingestion estimates to be
categorized into the finer age categories
recommended by U.S. EPA (2005). Consumer-only
and per capita water ingestion estimates were
reported in the Kahn and Stralka (2008a) study for
two water source categories: all sources and
community water. "All sources" included water from
all supply sources such as community water supply
(i.e., tap water), bottled water, other sources, and
missing sources. "Community water" included tap
water from a community or municipal water supply.
Other sources included wells, springs, and cisterns;
missing sources represented water sources that the
survey respondent was unable to identify. The water
ingestion estimates included both water ingested
directly as a beverage (direct water) and water added
to foods and beverages during final preparation at
home or by local food service establishments such as
school cafeterias and restaurants (indirect water).
Commercial water added by a manufacturer (i.e.,
water contained in soda or beer) and intrinsic water in
foods and liquids (i.e., milk and natural undiluted
juice) were not included in the estimates. Kahn and
Stralka (2008a) only reported the mean and 90th and
95th percentile estimates of per capita and
consumers-only ingestion. The full distributions of
ingestion estimates were provided by the author
(Kahn, 2008). Tables 3-7 to 3-22 presents full
distributions for the various water source categories
(community water, bottled water, other sources, and
all sources). Tables 3-7 to 3-10 provide per capita
ingestion estimates of total water (combined direct
and indirect water) in mL/day for the various water
source categories (i.e., community, bottled, other, and
all sources). Tables 3-11 to 3-14 present the same
information as Tables 3-7 to 3-10 but in units of
mL/kg-day. Tables 3-15 to 3-18 provide
consumers-only combined direct and indirect water
ingestion estimates in mL/day for the various source
categories. Tables 3-19 to 3-22 present the same
information as Tables 3-15 to 3-18 but in units of
mL/kg-day. Estimates that do not meet the minimum
sample size requirements as described in the Joint
Policy on Variance Estimation and Statistical
Reporting Standards on NHANES III and CSFII
Reports: NHIS/NCHS Analytical Working Group
Recommendations (NCHS, 1993) are flagged in the
tables.
The CSFII 1994-1996, 1998 data have both
strengths and limitations with regard to estimating
water ingestion. These are discussed in detail in
U.S. EPA (2004) and Kahn and Stralka (2008a). The
principal advantages of this survey are that (1) it was
designed to be representative of the United States
population, including children and low income
groups, (2) sample weights were provided that
facilitated proper analysis of the data and accounted
for non-response; and (3) the number of individuals
sampled (more than 20,000) is sufficient to allow
categorization within narrowly defined age
categories. One limitation of this survey is that data
were collected for only 2 days. As discussed in
Section 3.3.1.2 with regard to U.S. EPA's analysis of
NHANES data, short-term data may not accurately
reflect long-term intake patterns, especially at the
extremes (i.e., tails) of the distribution of water
intake. This study is considered key because the
sample size for children less than 3 years of age are
larger than in the most up-to-date information from
NHANES 2003-2006 (see Section 3.3.1.2).
Therefore, recommendations for these age groups are
based on this analysis.
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3.3.1.2. U.S. EPA Analysis of NHANES 2003-
2006 Data
In 2010, U.S. EPA analyzed the combined
2003-2004 and 2005-2006 NHANES data sets to
examine water ingestion rates for the general
population. The 2003-2006 data set included
information on more than 18,000 individuals
surveyed, including approximately 10,000 under age
21 and 5,000 under age 11. The U.S. Centers for
Disease Control and Prevention surveyed households
across the United States and collected food and
beverage recall data as part of the NHANES. The
first dietary recall interview was conducted in-person
in a Mobile Examination Center, and the second was
collected by telephone 3 to 10 days later on a
different day of the week. Each individual in the
survey was assigned a sample weight based on his or
her demographic data. These weights were taken into
account when calculating mean and percentile water
ingestion rates from various sources.
In 2010, U.S. EPA, Office of Pesticide Programs
used NHANES 2003-2006 data to update the Food
Commodity Intake Database (FCID) that was
developed in earlier analyses of data from the
USDA's CSFII (USDA, 2000; U.S. EPA, 2000). In
FCID, NHANES data on the foods people reported
eating were converted to the quantities of agricultural
commodities eaten, including water that was added in
the preparation of foods and beverages. FCID was
used in the U.S. EPA analysis to derive estimates of
water that was ingested from the consumption of
foods and beverages.
U.S. EPA derived mean and percentile estimates
of daily average water ingestion for the following age
categories: Birth to <1 month, 1 to <3 months, 3 to
<6 months, 6 to <12 months, 1 to <2 years of age,
2 to <3 years, 3 to <6 years, 6 to <11 years, 11 to
<16 years, 16 to <18 years, and 18 to <21 years of
age, 21 years and older, 65 years and older, and all
ages.
Consumer-only and per capita water ingestion
estimates were generated for four water source
categories: community water, bottled water, other
sources, and all sources. Consumer-only intake
represents the quantity of water consumed by
individuals during the survey period. These data are
generated by averaging intake across only the
individuals in the survey who reported consumption
of water. Per capita intake rates are generated by
averaging consumer-only intakes over the entire
population (including those individuals that reported
no intake). In general, per capita intake rates are
appropriate for use in exposure assessments for
which average dose estimates are of interest because
they represent both individuals who drank water
during the survey period and individuals who may
drink water at some time but did not consume it
during the survey period. "All sources" included
water from all supply sources such as community
water supply (i.e., tap water), bottled water, other
sources, and missing/unknown sources. "Community
water" included tap water from a community or
municipal water supply. "Other sources" included
wells, springs, cisterns, other non-specified sources,
and missing/unknown sources that the survey
respondent was unable to identify. The water
ingestion estimates included both water ingested
directly as a beverage (direct water) and water added
to foods and beverages during final preparation at
home or by local food service establishments such as
school cafeterias and restaurants (indirect water).
Commercial water added by a manufacturer (i.e.,
water contained in soda or beer) and intrinsic water in
foods and liquids (i.e., milk and natural undiluted
juice) were not included in the estimates. NHANES
water consumption respondent data were averaged
over both days of dietary data when they were
available; otherwise, 1-day data were used. Intake
rate distributions were provided in units of mL/day
and mL/kg-day. The body weights of survey
participants were used in developing intake rate
estimates in units of mL/kg-day.
Tables 3-23 to 3-42 present full distributions for
the various water source categories (community
water, bottled water, other sources, and all sources).
Tables 3-23 to 3-26 provide per capita ingestion
estimates of total water (combined direct and indirect
water) in mL/day for the various water source
categories (i.e., community, bottled, other, and all
sources). Table 3-27 presents the 90% confidence
intervals (CIs) around the estimated means and the
90% bootstrap intervals (Bis) around the 90th and
95th percentiles of total water ingestion from all water
sources. Tables 3-28 to 3-32 present the same
information as Tables 3-23 to 3-27 but in units of
mL/kg-day. Tables 3-33 to 3-36 provide
consumers-only combined direct and indirect water
ingestion estimates in mL/day for the various source
categories. Table 3-37 presents confidence and
bootstrap intervals for total water ingestion estimates
by consumers-only from all sources. Tables 3-38 to
3-42 present the same information as Tables 3-33 to
3-37 but in units of mL/kg-day. Estimates that do not
meet the minimum sample size as described in the
Joint Policy on Variance Estimation and Statistical
Reporting Standards on NHANES III and CSFII
Reports: NHIS/NCHS Analytical Working Group
Recommendations (NCHS, 1993), are flagged in the
tables. The design effect used to determine the
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minimum required sample size was domain specific
(i.e., calculated separately for various age groups).
The data show that the total quantity of water
ingested from all sources per unit mass of body
weight was at a maximum in the first half year of life
and decreased with increasing age. When indexed to
body weight, the per capita ingestion rate of water
from all sources combined for children under
6 months of age was approximately 2.5 times higher
than that of adults >21 years (see Table 3-31), and
consumers younger than 6 months of age ingested
approximately 3.5 times the amount of water (all
sources combined) as adults (see Table 3-41). The
pattern of decreasing water ingestion per unit of body
weight was also observed in consumers-only
estimates of community water (see Table 3-38), and
other sources (see Table 3-40). However, this trend
was not observed in per capita estimates of
community water, bottled water, and other sources
due to the lack of available responses under these age
and water source categories.
It should be noted that per capita estimates of
water intake from all sources using the NHANES
2003-2006 data are higher than estimates derived
previously from CSFII 1994-1996, 1998 for adults
(see Section 3.3.1.1). Among adults, total per-capita
water consumption increased by 234 mL, or 16%.
Per-capita bottled water consumption among adults
nearly doubled, from 189 to 375 mL/day. Among
infants, there appear to be erratic changes in water
consumption patterns. In particular, ingestion rate
estimates of bottled water for children <12 months
old are considerably less when compared to values
obtained from CSFII. This is due to the fact that
NHANES does not allow for the allocation of any
bottled water consumed indirectly in the preparation
of foods and beverages. This may have an impact on
the bottled water consumption for infants whose
formula is prepared with bottled water. Among older
children and adolescents, overall water consumption
increased by 0% to 10%, and bottled water
consumption increased 25% to 211%. Almost none of
the NHANES—CSFII differences are statistically
significant, except for all adults and all respondents,
which have very large sample sizes.
The advantages of U.S. EPA's analysis of the
2003-2006 NHANES surveys are (1) that the surveys
were designed to obtain statistically valid sample of
the civilian non-institutionalized U.S. population
(i.e., the sampling frame was organized using 2000
U.S. population census estimates); (2) NHANES
oversampled low income persons, adolescents
12-19 years, persons 60 years and older, Blacks, and
Mexican Americans; (3) several sets of sampling
weights were available for use with the intake data to
facilitate proper analysis of the data; (4) the sample
size was sufficient to allow categorization within
narrowly defined age categories, and the large sample
provided useful information on the overall
distribution of ingestion by the population and should
adequately reflect the range among respondent
variability; (5) the survey was conducted over
2 non-consecutive days, which improved the variance
over consecutive days of consumption; and (6) the
most current data set was used. One limitation of the
data is that the data were collected over only 2 days
and do not necessarily represent "usual" intake.
"Usual dietary intake" refers to the long-term average
of daily intakes by an individual. Thus, water
ingestion estimates based on short-term data may
differ from long-term rates, especially at the tails of
the distribution. There are, however, several
limitations associated with these data. Water intake
estimates for children under 3 years of age are less
statistically reliable due to sample size. In addition,
NHANES does not allow for the allocation of
indirect water intake in the estimation of bottled
water consumption. Another limitation of these data
is that the survey design, while being well-tailored
for the overall population of the United States and
conducted throughout the year to account for
seasonal variation, is of limited utility for assessing
small and potentially at-risk populations based on
ethnicity, medical status, geography/climate, or other
factors such as activity level.
3.3.2. Relevant Drinking Water Ingestion
Studies
3.3.2.1. Wolf (1958)—Body Water Content
Wolf (1958) provided information on the water
content of human bodies. Wolf (1958) stated that a
newborn baby is about 77% water while an adult
male is about 60% water by weight. An adult male
gains and loses about 2,750 mL of water each day.
Water intake in dissimilar mammals varies according
to 0.88 power of body weight.
3.3.2.2. National Research Council (1977)—
Drinking Water and Health
NRC (1977) calculated the average per capita
water (liquid) consumption per day to be 1.63 L. This
figure was based on a survey of the following
literature sources: Evans (1941); Bourne and Kidder
(1953); Walker et al. (1957); Wolf (1958); Guyton
(1968); McNall and Schlegel (1968); Randall (1973);
NRC (1974); and Pike and Brown (1975), as cited in
NRC (1977). Although the calculated average intake
rate was 1.63 L/day, NRC (1977) adopted a larger
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rate (2 L/day) to represent the intake of the majority
of water consumers. This value is relatively
consistent with the total tap water intakes rate
estimated from the key study presented previously.
However, the use of the term "liquid" was not clearly
defined in this study, and it is not known whether the
populations surveyed are representative of the adult
U.S. population. Consequently, the results of this
study are of limited use in recommending total tap
water intake rates, and this study is not considered a
key study.
3.3.2.3. Hopkins and Ellis (1980)—Drinking
Water Consumption in Great Britain
A study conducted in Great Britain over a
6-week period during September and October 1978,
estimated the drinking water consumption rates of
3,564 individuals from 1,320 households in England,
Scotland, and Wales (Hopkins and Ellis, 1980). The
participants were selected randomly and were asked
to complete a questionnaire and a diary indicating the
type and quantity of beverages consumed over a
1-week period. Total liquid intake included total tap
water taken at home and away from home; purchased
alcoholic beverages; and non-tap water-based drinks.
Total tap water included water content of tea, coffee,
and other hot water drinks; homemade alcoholic
beverages; and tap water consumed directly as a
beverage. Table 3-43 presents the assumed tap water
contents for these beverages. Based on responses
from 3,564 participants, the mean intake rates and
frequency distribution data for various beverage
categories were estimated by Hopkins and Ellis
(1980). Table 3-44 lists these data. The mean per
capita total liquid intake rate for all individuals
surveyed was 1.59 L/day, and the mean per capita
total tap water intake rate was 0.96 L/day, with a
90th percentile value of about 1.57 L/day. Liquid
intake rates were also estimated for males and
females in various age groups. Table 3-45
summarizes the total liquid and total tap water intake
rates for 1,758 males and 1,800 females grouped into
six age categories (Hopkins and Ellis, 1980). The
mean and 90th percentile total tap water intake values
for adults over age 18 years are, respectively,
1.07 L/day and 1.87 L/day, as determined by pooling
data for males and females for the three adult age
ranges in Table 3-45. This calculation assumes, as
does Table 3-44 and 3-45, that the underlying
distribution is normal and not lognormal.
The advantage of these data is that the responses
were not generated on a recall basis but by recording
daily intake in diaries. The latter approach may result
in more accurate responses being generated. Diaries
were maintained for 1 week, which is longer than
other surveys (e.g., CSFII). The use of total liquid
and total tap water was well defined in this study.
Also, these data were based on the population of
Great Britain and not the United States. Drinking
patterns may differ among these populations as a
result of varying weather conditions and
socioeconomic factors. For these reasons, this study
is not considered a key study in this document.
3.3.2.4. Canadian Ministry of National Health
and Welfare (1981)—Tap Water
Consumption in Canada
In a study conducted by the Canadian Ministry
of National Health and Welfare, 970 individuals from
295 households were surveyed to determine the per
capita total tap water intake rates for various age/sex
groups during winter and summer seasons (Canadian
Ministry of National Health and Welfare, 1981).
Intake rate was also evaluated as a function of
physical activity. The population that was surveyed
matched the Canadian 1976 census with respect to
the proportion in different age, regional, community
size, and dwelling type groups. Participants
monitored water intake for a 2-day period
(1 weekday, and 1 weekend day) in both late summer
of 1977 and winter of 1978. All 970 individuals
participated in both the summer and winter surveys.
The amount of tap water consumed was estimated
based on the respondents' identification of the type
and size of beverage container used, compared to
standard-sized vessels. The survey questionnaires
included a pictorial guide to help participants in
classifying the sizes of the vessels. For example, a
small glass of water was assumed to be equivalent to
4.0 ounces of water, and a large glass was assumed to
contain 9.0 ounces of water. The study also accounted
for water derived from ice cubes and popsicles, and
water in soups, infant formula, and juices. The survey
did not attempt to differentiate between tap water
consumed at home and tap water consumed away
from home. The survey also did not attempt to
estimate intake rates for fluids other than tap water.
Consequently, no intake rates for total fluids were
reported.
Table 3-46 presents daily consumption
distribution patterns for various age groups. For
adults (over 18 years of age) only, the average total
tap water intake rate was 1.38 L/day, and the
90th percentile rate was 2.41 L/day as determined by
graphical interpolation. These data follow a
lognormal distribution. Table 3-47 presents the intake
data for males, females, and both sexes combined as
a function of age and expressed in units of mL/kg
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body weight. The tap water survey did not include
body weights of the participants, but the body-weight
information was taken from a Canadian health survey
dated 1981; it averaged 65.1 kg for males and 55.6 kg
for females. Table 3-48 presents intake rates for
specific age groups and seasons. The average daily
total tap water intake rate for all ages and seasons
combined was 1.34 L/day, and the 90th percentile rate
was 2.36 L/day. The summer intake rates are nearly
the same as the winter intake rates. The authors
speculate that the reason for the small seasonal
variation is that in Canada, even in the summer, the
ambient temperature seldom exceeded 20°C, and
marked increase in water consumption with high
activity levels has been observed in other studies only
when the ambient temperature has been higher than
20°C. Table 3-49 presents average daily total tap
water intake rates as a function of the level of
physical activity, as estimated subjectively.
Table 3-50 presents the amounts of tap water
consumed that are derived from various foods and
beverages. Note that the consumption of direct "raw"
tap water is almost constant across all age groups
from school-age children through the oldest ages. The
increase in total tap water consumption beyond
school age is due to coffee and tea consumption.
This survey may be more representative of total
tap water consumption than some other less
comprehensive surveys because it included data for
some tap water-containing items not covered by other
studies (i.e., ice cubes, popsicles, and infant formula).
One potential source of error in the study is that
estimated intake rates were based on identification of
standard vessel sizes; the accuracy of this type of
survey data is not known. The cooler climate of
Canada may have reduced the importance of large tap
water intakes resulting from high activity levels,
therefore making the study less applicable to the
United States. The authors were not able to explain
the surprisingly large variations between regional tap
water intakes; the largest regional difference was
between Ontario (1.18 L/day) and Quebec
(1.55 L/day).
3.3.2.5. Gillies and Paulin (1983)—Variability of
Mineral Intakes from Drinking Water
Gillies and Paulin (1983) conducted a study to
evaluate variability of mineral intake from drinking
water. A study population of 109 adults (75 females;
34 males) ranging in age from 16 to 80 years (mean
age = 44 years) in New Zealand was asked to collect
duplicate samples of water consumed directly from
the tap or used in beverage preparation during a
24-hour period. Participants were asked to collect the
samples on a day when all of the water consumed
would be from their own home. Individuals were
selected based on their willingness to participate and
their ability to comprehend the collection procedures.
The mean total tap water intake rate for this
population was 1.25 (±0.39) L/day, and the
90th percentile rate was 1.90 L/day. The median total
tap water intake rate (1.26 L/day) was very similar to
the mean intake rate. The reported range was 0.26 to
2.80 L/day.
The advantage of these data is that they were
generated using duplicate sampling techniques.
Because this approach is more objective than recall
methods, it may result in more accurate responses.
However, these data are based on a short-term survey
that may not be representative of long-term behavior,
the population surveyed is small, and the procedures
for selecting the survey population were not designed
to be representative of the New Zealand population,
and the results may not be applicable to the United
States. For these reasons, the study is not regarded as
a key study in this document.
3.3.2.6. Pennington (1983)—Revision of the
Total Diet Study Food List and Diets
Based on data from the U.S. Food and Drug
Administration's Total Diet Study, Pennington (1983)
reported average intake rates for various foods and
beverages for five age groups of the population. The
Total Diet Study is conducted annually to monitor the
nutrient and contaminant content of the U.S. food
supply and to evaluate trends in consumption.
Representative diets were developed based on
24-hour recall and 2-day diary data from the
1977-1978 USD A Nationwide Food Consumption
Survey (NFCS) and 24-hour recall data from the
Second National Health and Nutrition Examination
Survey (NHANES II). The numbers of participants in
NFCS and NHANES II were approximately 30,000
and 20,000, respectively. The diets were developed to
"approximate 90% or more of the weight of the foods
usually consumed" (Pennington, 1983). The source of
water (bottled water as distinguished from tap water)
was not stated in the Pennington study. For the
purposes of this report, the consumption rates for the
food categories defined by Pennington (1983) were
used to calculate total fluid and total water intake
rates for five age groups. Total water includes water,
tea, coffee, soft drinks, and soups and frozen juices
that are reconstituted with water. Reconstituted soups
were assumed to be composed of 50% water, and
juices were assumed to contain 75% water. Total
fluids include total water in addition to milk,
ready-to-use infant formula, milk-based soups,
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carbonated soft drinks, alcoholic beverages, and
canned fruit juices. Table 3-51 presents these intake
rates. Based on the average intake rates for total
water for the two adult age groups, 1.04 and
1.26L/day, the average adult intake rate is about
1.15 L/day. These rates should be more representative
of the amount of source-specific water consumed
than are total fluid intake rates. Because this study
was designed to measure food intake, and it used
both USDA 1978 data and NHANES II data, there
was not necessarily a systematic attempt to define tap
water intake per se, as distinguished from bottled
water. For this reason, it is not considered a key tap
water study in this document.
3.3.2.7. U.S. EPA (1984)—An Estimation of the
Daily Average Food Intake by Age and
Sex for Use in Assessing the
RadwnucU.de Intake of the General
Population
Using data collected by USDA in the 1977-1978
NFCS, U.S. EPA (1984) determined daily food and
beverage intake levels by age to be used in assessing
radionuclide intake through food consumption. Tap
water, water-based drinks, and soups were identified
subcategories of the total beverage category.
Table 3-52 presents daily intake rates for tap water,
water-based drinks, soup, and total beverages. As
seen in Table 3-52, mean tap water intake for
different adult age groups (age 20 years and older)
ranged from 0.62 to 0.76 L/day, water-based drinks
intake ranged from 0.34 to 0.69 L/day, soup intake
ranged from 0.04 to 0.06 L/day, and mean total
beverage intake levels ranged from 1.48 to
1.73 L/day. Total tap water intake rates were
estimated by combining the average daily intakes of
tap water, water-based drinks, and soups for each age
group. For adults (ages 20 years and older), mean
total tap water intake rates range from 1.04 to
1.47 L/day, and for children (ages <1 to 19 years),
mean intake rates range from 0.19 to 0.90 L/day. The
total tap water intake rates, derived by combining
data on tap water, water-based drinks, and soup
should be more representative of source-specific
drinking water intake than the total beverage intake
rates reported in this study. The chief limitation of the
study is that the data were collected in 1978 and do
not reflect the expected increase in the U.S.
consumption of soft drinks and bottled water or
changes in the diet within the last three decades.
Since the data were collected for only a 3-day period,
the extrapolation to chronic intake is uncertain. Also,
these intake rates do not include reconstituted infant
formula.
3.3.2.8. Cantor et al. (1987)—Bladder Cancer,
Drinking Water Source, and Tap Water
Consumption
The National Cancer Institute, in a
population-based, case control study investigating the
possible relationship between bladder cancer and
drinking water, interviewed approximately
8,000 adult White individuals, 21 to 84 years of age
(2,805 cases and 5,258 controls) in their homes, using
a standardized questionnaire (Cantor et al., 1987).
The cases and controls resided in one of five
metropolitan areas (Atlanta, Detroit, New Orleans,
San Francisco, and Seattle) and five States
(Connecticut, Iowa, New Jersey, New Mexico, and
Utah). The individuals interviewed were asked to
recall the level of intake of tap water and other
beverages in a typical week during the winter prior to
the interview. Total beverage intake was divided into
the following two components: (1) beverages derived
from tap water; and (2) beverages from other sources.
Tap water used in cooking foods and in ice cubes was
apparently not considered. Participants also supplied
information on the primary source of the water
consumed (i.e., private well, community supply,
bottled water, etc.). The control population was
randomly selected from the general population and
frequency matched to the bladder cancer case
population in terms of age, sex, and geographic
location of residence. The case population consisted
of Whites only and had no people under the age of
21 years; 57% were over the age of 65 years. The
fluid intake rates for the bladder cancer cases were
not used because their participation in the study was
based on selection factors that could bias the intake
estimates for the general population. Based on
responses from 5,258 White controls (3,892 males;
1,366 females), average tap water intake rates for a
"typical" week were compiled by sex, age group, and
geographic region. Table 3-53 lists these rates. The
average total fluid intake rate was 2.01 L/day for men
of which 70% (1.4 L/day) was derived from tap
water, and 1.72 L/day for women of which 79%
(1.35 L/day) was derived from tap water. Table 3-54
presents frequency distribution data for the
5,228 controls, for which the authors had information
on both tap water consumption and cigarette smoking
habits. These data follow a lognormal distribution
having an average value of 1.30 L/day and an upper
90th percentile value of approximately 2.40 L/day.
These values were determined by graphically
interpolating the data of Table 3-54 after plotting it
on log probability graph paper. These values
represent the usual level of intake for this population
of adults in the winter. Limitations associated with
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this data set are that the population surveyed was
older than the general population and consisted
exclusively of Whites. Also, the intake data are based
on recall of behavior during the winter only.
Extrapolation of the data to other seasons is difficult.
The authors presented data on person-years of
residence with various types of water supply sources
(municipal versus private, chlorinated versus non-
chlorinated, and surface versus well water).
Unfortunately, these data cannot be used to draw
conclusions about the national average apportionment
of surface versus groundwater since a large fraction
(24%) of municipal water intake in this survey could
not be specifically attributed to either ground or
surface water.
3.3.2.9. Ershow and Cantor (1989)—Total Water
and Tap Water Intake in the U.S.:
Population-Based Estimates of Quantities
and Sources
Ershow and Cantor (1989) estimated water
intake rates based on data collected by the USDA
1977-1978 NFCS. The survey was conducted
through interviews and diary entries. Daily intake
rates for tap water and total water were calculated for
various age groups for males, females, and both sexes
combined. Tap water was defined as "all water from
the household tap consumed directly as a beverage or
used to prepare foods and beverages." Total water
was defined as tap water plus "water intrinsic to
foods and beverages" (i.e., water contained in
purchased food and beverages). The authors showed
that the age, sex, and racial distribution of the
surveyed population closely matched the estimated
1977 U.S. population.
Table 3-55 presents daily total tap water intake
rates, expressed as mL/day by age group. These data
follow a lognormal distribution. Table 3-56 presents
the same data, expressed as mL per kg body weight
per day. Table 3-57 presents a summary of these
tables, showing the mean, the 10th and 90th percentile
intakes, expressed as both mL/day and mL/kg-day as
a function of age. This shows that the mean and
90th percentile intake rates for adults (ages 20 to 65+)
are approximately 1,410 mL/day and 2,280 mL/day,
and for all ages, the mean and 90th percentile intake
rates are 1,193 mL/day and 2,092 mL/day. Note that
older adults have greater intakes than do adults
between age 20 and 64, an observation bearing on the
interpretation of the Cantor et al. (1987) study, which
surveyed a population that was older than the
national average (see Section 3.3.2.8).
Ershow and Cantor (1989) also measured total
water intake for the same age groups and concluded
that it averaged 2,070 mL/day for all groups
combined and that tap water intake (1,190 mL/day) is
55% of the total water intake. (Table 3-58 presents
the detailed intake data for various age groups).
Ershow and Cantor (1989) also concluded that, for all
age groups combined, the proportion of tap water
consumed as drinking water, or used to prepare foods
and beverages is 54, 10, and 36%, respectively.
(Table 3-59 presents the detailed data on proportion
of tap water consumed for various age groups).
Ershow and Cantor (1989) also observed that males
of all age groups had higher total water and tap water
consumption rates than females; the variation of each
from the combined-sexes mean was about 8%.
With respect to region of the country, the
northeast states had slightly lower average tap water
intake (1,200 mL/day) than the three other regions
(which were approximately equal at 1,400 mL/day).
This survey has an adequately large size
(26,446 individuals), and it is a representative sample
of the U.S. population with respect to age distribution
and residential location. The data are more than
20 years old and may not be entirely representative of
current patterns of water intake, but, in general, the
rates are similar to those presented in the key
drinking water study in this chapter.
3.3.2.10. Roseberry and Burmaster (1992)—
Lognormal Distributions for Water
Intake
Roseberry and Burmaster (1992) fit lognormal
distributions to the water intake data population-wide
distributions for total fluid and total tap water intake
based on proportions of the population in each age
group. Their publication shows the data and the fitted
lognormal distributions graphically. The mean was
estimated as the zero intercept, and the standard
deviation (SD) was estimated as the slope of the best-
fit line for the natural logarithm of the intake rates
plotted against their corresponding z-scores
(Roseberry and Burmaster, 1992). Least squares
techniques were used to estimate the best-fit straight
lines for the transformed data. Table 3-60 presents
summary statistics for the best-fit lognormal
distribution. In this table, the simulated balanced
population represents an adjustment to account for
the difference in the age distribution of the U.S.
population in 1988 from the age distribution in 1978
when Ershow and Cantor (1989) collected their data.
Table 3-61 summarizes the quantiles and means of
tap water intake as estimated from the best-fit
distributions. The mean total tap water intake rates
for the two adult populations (ages 20 to 65 years,
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and 65+ years) were estimated to be 1.27 and
1.34L/day.
These intake rates were based on the data
originally presented by Ershow and Cantor (1989).
Consequently, the same advantages and
disadvantages associated with the Ershow and Cantor
(1989) study apply to this data set.
3.3.2.11. Levy et al (1995)—Infant Fluoride
Intake from Drinking Water Added to
Formula, Beverages, and Food
Levy et al. (1995) conducted a study to
determine fluoride intake by infants through drinking
water and other beverages prepared with water and
baby foods. The study was longitudinal and covered
the ages from birth to 9 months old. A total of
192 mothers, recruited from the post partum wards of
two hospitals in Iowa City, completed mail
questionnaires and 3-day beverage and food diaries
for their infants at ages 6 weeks, and 3, 6, and
9 months (Levy et al., 1995). The questionnaire
addressed feeding habits, water sources and
ingestion, and the use of dietary fluoride supplements
during the preceding week (Levy et al., 1995). Data
on the quantity of water consumed by itself or as an
additive to infant formula, other beverages, or foods
were obtained. In addition, the questionnaire
addressed the infants' ingestion of cows' milk, breast
milk, ready-to-feed (RTF) infant products (formula,
juices, beverages, baby food), and table foods.
Mothers were contacted for any clarifications of
missing data and discrepancies (Levy et al., 1995).
Levy et al. (1995) assessed non-response bias and
found no significant differences in the reported
number of adults or children in the family, water
sources, or family income at 3, 6, or 9 months.
Table 3-62 provides the range of water ingestion from
water by itself and from addition to selected foods
and beverages. The percentage of infants ingesting
water by itself increased from 28% at 6 weeks to
66% at 9 months, respectively, and the mean intake
increased slightly over this time frame. During this
time frame, the largest proportion of the infants'
water ingestion (i.e., 36% at 9 months to 48% at
6 months) came from the addition of water to
formula. Levy et al. (1995) noted that 32% of the
infants at age 6 weeks and 23% of the infants at age
3 months did not receive any water from any of the
sources studied. Levy et al. (1995) also noted that the
proportion of children ingesting some water from all
sources gradually increased with age.
The advantages of this study are that it provides
information on water ingestion of infants starting at
6 weeks old, and the data are for water only and for
water added to beverages and foods. The limitations
of the study are that the sample size was small for
each age group, it captured information from a select
geographical location, and data were collected
through self-reporting. The authors noted, however,
that the 3-day diary has been shown to be a valid
assessment tool. Levy et al. (1995) also stated that
(1) for each time period, the ages of the infants varied
by a few days to a few weeks, and are, therefore, not
exact and could, at early ages, have an effect on
age-specific intake patterns, and (2) the same number
of infants were not available at each of the four time
periods.
3.3.2.12. USDA (1995)—Food and Nutrient
Intakes by Individuals in the United
States, 1 Day, 1989-1991
USDA (1995) collected data on the quantity of
"plain drinking water" and various other beverages
consumed by individuals in one day during 1989
through 1991. The data were collected as part of
USDA's CSFII. The data used to estimate mean per
capita intake rates combined 1-day dietary recall data
from three survey years: 1989, 1990, and 1991 during
which 15,128 individuals supplied 1-day intake data.
Individuals from all income levels in the
48 conterminous states and Washington D.C. were
included in the sample. A complex 3-stage sampling
design was employed, and the overall response rate
for the study was 58%. To minimize the biasing
effects of the low response rate and adjust for the
seasonality, a series of weighting factors was
incorporated into the data analysis. Table 3-63
presents the intake rates based on this study.
Table 3-63 includes data for (a) "plain drinking
water," which might be assumed to mean tap water
directly consumed rather than bottled water;
(b) coffee and tea, which might be assumed to be
constituted from tap water; (c) fruit drinks and ades,
which might be assumed to be reconstituted from tap
water rather than canned products; and (d) the total of
the three sources. With these assumptions, the mean
per capita total intake of water is estimated to be
1,416 mL/day for adult males (i.e., 20 years of age
and older), 1,288 mL/day for adult females (i.e.,
20 years of age and older), and 1,150 mL/day for all
ages and both sexes combined. Although these
assumptions appear reasonable, a close reading of the
definitions used by USDA (1995) reveals that the
word "tap water" does not occur, and this uncertainty
prevents the use of this study as a key study of tap
water intake.
The advantages of using these data are that
(1) the survey had a large sample size; and (2) the
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authors attempted to represent the general U.S.
population by oversampling low-income groups and
by weighting the data to compensate for low response
rates. The disadvantages are that (1) the word "tap
water" was not defined, and the assumptions that
must be used in order to compare the data with the
other tap water studies might not be valid; (2) the
data collection period reflects only a 1-day intake
period and may not reflect long-term drinking water
intake patterns; (3) data on the percentiles of the
distribution of intakes were not given; and (4) the
data are almost 20 years old and may not be entirely
representative of current intake patterns.
3.3.2.13. U.S. EPA (1996)— Descriptive Statistics
from a Detailed Analysis of the National
Human Activity Pattern Survey (NHAPS)
Responses
The U.S. EPA collected information on the
number of glasses of drinking water and juice
reconstituted with tap water consumed by the general
population as part of the National Human Activity
Pattern Survey (NHAPS) (U.S. EPA, 1996). NHAPS
was conducted between October 1992 and September
1994. Over 9,000 individuals in the 48 contiguous
United States provided data on the duration and
frequency of selected activities and the time spent in
selected microenvironments via 24-hour diaries. Over
4,000 NHAPS respondents also provided information
on the number of 8-ounce glasses of water and the
number of 8-ounce glasses of juice reconstituted with
water that they drank during the 24-hour survey
period (see Tables 3-64 and 3-65). The median
number of glasses of tap water consumed was 1-2,
and the median number of glasses of juice with tap
water consumed was 1-2.
For both individuals who drank tap water and
individuals who drank juices reconstituted with tap
water, the number of glasses consumed in a day
ranged from 1 to 20 glasses. The highest percentage
of the population (37.1%) who drank tap water,
consumed in the range of 3-5 glasses a day, and the
highest percentage of the population (51.5%) who
consumed juice reconstituted with tap water
consumed 1-2 glasses in a day. Based on the
assumption that each glass contained 8 ounces of
water (226.4 mL), the total volume of tap water and
juice with tap water consumed would range from
0.23 L/day (1 glass) to 4.5 L/day (20 glasses) for
respondents who drank tap water. Using the same
assumption, the volume of tap water consumed for
the population who consumed 3-5 glasses would be
0.68 L/day to 1.13 L/day, and the volume of juice
with tap water consumed for the population who
consumed 1-2 glasses would be 0.23-0.46 L/day.
Assuming that the average individual consumes
3-5 glasses of tap water plus 1-2 glasses of juice with
tap water, the range of total tap water intake for this
individual would range from 0.9 L/day to 1.64 L/day.
These values are consistent with the average intake
rates observed in other studies.
The advantages of NHAPS are that the data were
collected for a large number of individuals and that
the data are representative of the U.S. population.
However, evaluation of drinking water intake rates
was not the primary purpose of the study, and the
data do not reflect the total volume of tap water
consumed. In addition, using the assumptions
described above, the estimated drinking water intake
rates from this study are within the same ranges
observed for other drinking water studies.
3.3.2.14. Heller et al (2000)—Water Consumption
and Nursing Characteristics of Infants by
Race and Ethnicity
Heller et al. (2000) analyzed data from the
1994-1996 CSFII to evaluate racial/ethnic differences
in the ingestion rates of water in children younger
than 2 years old. Using data from 946 children in this
age group, the mean amounts of water consumed
from eight sources were determined for various
racial/ethnic groups, including Black non-Hispanic,
White non-Hispanic, Hispanic, and "other" (Asian,
Pacific Islander, American Indian, Alaskan Native,
and other non-specified racial/ethnic groups). The
sources analyzed included (1) plain tap water,
(2) milk and milk drinks, (3) reconstituted powdered
or liquid infant formula made from drinking water,
(4) ready-to-feed and other infant formula, (5) baby
food, (6) carbonated beverages, (7) fruit and
vegetable juices and other non-carbonated drinks, and
(8) other foods and beverages. In addition, Heller et
al. (2000) calculated mean plain water and total water
ingestion rates for children by age, sex, region,
urbanicity, and poverty category. Ages were defined
as less than 12 months and 12 to 24 months. Regions
were categorized as Northeast, Midwest, South, and
West. The states represented by each of these regions
were not reported in Heller et al. (2000). However, it
is likely that these regions were defined in the same
way as in Sohn et al. (2001). See Section 3.3.2.16 for
a discussion on the Sohn et al. (2001) study.
Urbanicity of the residence was defined as urban (i.e.,
being in a Metropolitan Statistical Area [MSA],
suburban [outside of an MSA], or rural [being in a
non-MSA]). Poverty category was derived from the
poverty income ratio. In this study, a poverty income
ratio was calculated by dividing the family's annual
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income by the federal poverty threshold for that size
household. The poverty categories used were 0-1.30,
1.31 to 3.50, and greater than 3.50 times the federal
poverty level (Heller et al., 2000).
Table 3-66 provides water ingestion estimates for
the eight water sources evaluated, for each of the
race/ethnic groups. Heller et al. (2000) reported that
Black non-Hispanic children had the highest mean
plain tap water intake (21 mL/kg-day), and White
non-Hispanic children had the lowest mean plain tap
water intake (13 mL/kg-day). The only statistically
significant difference between the racial/ethnic
groups was found to be in plain tap water
consumption and total water consumption.
Reconstituted baby formula made up the highest
proportion of total water intake for all race/ethnic
groups. Table 3-67 presents tap water and total water
ingestion by age, sex, region, urbanicity, and poverty
category. On average, children younger than
12 months of age consumed less plain tap water
(11 mL/kg-day) than children aged 12-24 months
(18 mL/kg-day). There were no significant
differences in plain tap water consumption by sex,
region, or urbanicity. Heller et al. (2000) reported a
significant association between higher income and
lower plain tap water consumption. For total water
consumption, ingestion per kg body weight was
lower for the 12-24 month-old children than for
those younger than 12 months of age. Urban children
consumed more plain tap water and total water than
suburban and rural children. In addition, plain tap
water and total water ingestion was found to decrease
with increasing poverty category (i.e., higher wealth).
A major strength of the Heller et al. (2000) study
is that it provides information on tap water and total
water consumption by race, age, sex, region,
urbanicity, and family income. The weaknesses in the
CSFII data set have been discussed under Kahn and
Stralka (2008a) and U.S. EPA (2004) and include
surveying participants for only 2 days.
3.3.2.15. Sichert-Hellert et al. (2001)—Fifteen-
Year Trends in Water Intake in German
Children and Adolescents: Results of the
DONALD Study
Water and beverage consumption was evaluated
by Sichert-Hellert et al. (2001) using 3-day dietary
records of 733 children, ages 2 to 13 years, enrolled
in the Dortmund Nutritional and Anthropometric
Longitudinally Designed Study (DONALD study).
The DONALD study is a cohort study, conducted in
Germany, that collects data on diet, metabolism,
growth, and development from healthy subjects
between infancy and adulthood (Sichert-Hellert et al.,
2001). Beginning in 1985, approximately 40 to
50 infants were enrolled in the study annually.
Mothers of the participants were recruited in hospital
maternity wards. Older children and parents of
younger children were asked to keep dietary records
for 3 days by recording and weighing (to the nearest
1 gram) all foods and fluids, including water,
consumed.
Sichert-Hellert et al. (2001) evaluated
3,736 dietary records from 733 subjects (354 males
and 379 females) collected between 1985 and 1999.
Total water ingestion was defined as the sum of water
content from food (intrinsic water), beverages, and
oxidation. Beverages included milk, mineral water,
tap water, juice, soft drinks, and coffee and tea.
Table 3-68 presents the mean water ingestion rates
for these different sources, as well as mean total
water ingestion rates for three age ranges of children
(aged 2 to 3 years, aged 4 to 8 years, and aged 9 to
13 years). According to Sichert-Hellert et al. (2001),
mean total water ingestion increased with age from
1,114 mL/day in the 2- to 3-year-old subjects to 1,891
and 1,676 mL/day in 9- to 13-year-old boys and girls,
respectively. However, mean total water intake per
body weight decreased with age. Sichert-Hellert et al.
(2001) observed that the most important source of
total water ingestion was mineral water for all
children, except the 2- to 3-year-olds. For these
children, the most important source of total water
ingestion was milk.
One of the limitations of this study is that it
evaluated water and beverage consumption in
German children and, as such, it may not be
representative of consumption patterns of U.S.
children.
3.3.2.16. Sohn et al (2001)—Fluid Consumption
Related to Climate Among Children in
the United States
Sohn et al. (2001) investigated the relationship
between fluid consumption among children aged 1 to
10 years and local climate using data from the third
National Health and Nutrition Examination Survey
(NHANES III, 1988-1994). Children aged 1 to
10 years who completed the 24-hour dietary
interview (or proxy interview for the younger
children) during the NHANES III survey were
selected for the analysis. Breast-fed children were
excluded from the analysis. Among 8,613 children
who were surveyed, 688 (18%) were excluded due to
incomplete data. A total of 7,925 eligible children
remained. Since data for climatic conditions were not
collected in the NHANES III survey, the mean daily
maximum temperature from 1961 to 1990, averaged
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for the month during which the NHANES III survey
was conducted, was obtained for each survey location
from the U.S. Local Climate Historical Database. Of
the 7,925 eligible children with complete dietary
data, temperature information was derived for only
3,869 children (48.8%) since detailed information on
survey location, in terms of county and state, was
released only for counties with a population of more
than a hah0 million.
Sohn et al. (2001) calculated the total amount of
fluid intake for each child by adding the fluid intake
from plain drinking water and the fluid intake from
foods and beverages other than plain drinking water
provided by NHANES III. Sohn et al. (2001)
identified major fluid sources as milk (and milk
drinks), juice (fruit and vegetable juices and other
non-carbonated drinks), carbonated drinks, and plain
water. Fluid intake from sources other than these
major sources was grouped into other foods and
beverages. Other foods and beverages included
bottled water, coffee, tea, baby food, soup,
water-based beverages, and water used for dilution of
food. Table 3-69 presents mean fluid ingestion rates
of selected fluids for the total sample population and
for the subsets of the sample population with and
without temperature information. The estimated mean
total fluid and plain water ingestion rates for the
3,869 children for whom temperature information
was obtained are presented in Table 3-70 according to
age (years), sex, race/ethnicity, poverty/income ratio,
region, and urbanicity. Poverty/income ratio was
defined as the ratio of the reported family income to
the federal poverty level. The following categories
were assigned low socioeconomic status (SES) =
0.000 to 1.300 times the poverty/income ratio;
medium SES = 1.301 to 3.500 times the
poverty/income level; and high SES = 3.501 or
greater times the poverty/income level. Regions were
as Northeast, Midwest, South, and West, as defined
by the U.S. Census (see Table 3-70). Sohn et al.
(2001) did not find a significant association between
mean daily maximum temperature and total fluid or
plain water ingestion, either before or after
controlling for sex, age, SES, and race or ethnicity.
However, significant associations between fluid
ingestion and age, sex, socioeconomic status, and
race and ethnicity were reported.
The main strength of the Sohn et al. (2001) study
is the evaluation of water intake as it relates to
weather data. The main limitations of this study were
that northeast and western regions were over-
represented since temperature data were only
available for counties with populations in excess of a
half million. In addition, Whites were under-
represented compared to other racial or ethnic
groups. Other limitations include lack of data for
children from extremely cold or hot weather
conditions.
3.3.2.17. Hilbig et al (2002)—Measured
Consumption of Tap Water in German
Infants and Young Children as
Background for Potential Health Risk
Assessment: Data of the DONALD Study
Hilbig et al. (2002) estimated tap water ingestion
rates based on 3-day dietary records of 504 German
children aged 3, 6, 9, 12, 18, 24, and 36 months. The
data were collected between 1990 and 1998 as part of
the DONALD study. Details of data collection for the
DONALD study have been provided previously
under the Sichert-Hellert et al. (2001) study in
Section 3.3.2.15 of this handbook. Tap water
ingestion rates were calculated for three subgroups of
children: (1) breast-fed infants <12 months of age
(exclusive and partial breast-fed infants),
(2) formula-fed infants <12 months of age (no human
milk, but including weaning food), and (3) mixed-fed
young children aged 18 to 36 months. Hilbig et al.
(2002) defined "total tap water from household" as
water from the tap consumed as a beverage or used in
food preparation. "Tap water from food
manufacturing" was defined as water used in
industrial production of foods, and "Total Tap Water"
was defined as tap water consumed from both the
household and that used in manufacturing.
Table 3-71 summarizes total tap water ingestion
(in mL/day and mL/kg-day) and tap water ingestion
from household and manufacturing sources (in
mL/kg-day) for breast-fed, formula-fed, and
mixed-fed children. Mean total tap water intake was
higher in formula-fed infants (53 mL/kg-day) than in
breast-fed infants (17 g/kg-day) and mixed-fed young
children (19 g/kg-day). Tap water from household
sources constituted 66 to 97% of total tap water
ingestion in the different age groups.
The major limitation of this study is that the
study sample consists of families from an upper
social background in Germany (Hilbig et al., 2002).
Because the study was conducted in Germany, the
data may not be directly applicable to the U.S.
population.
3.3.2.18. Marshall et al (2003a)—Patterns of
Beverage Consumption during the
Transition Stage of Infant Nutrition
Marshall et al. (2003a) investigated beverage
ingestion during the transition stage of infant
nutrition. Mean ingestion of infant formula, cows'
milk, combined juice and juice drinks, water, and
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other beverages was estimated using a frequency
questionnaire. A total of 701 children, aged 6 months
through 24 months, participated in the Iowa Fluoride
Study (IPS). Mothers of newborns were recruited
from 1992 through 1995. The parents were sent
questionnaires when the children were 6, 9, 12, 16,
20, and 24 months old. Of the 701 children, 470
returned all six questionnaires, 162 returned five, 58
returned four, and 11 returned three, with the
minimum criteria being three questionnaires to be
included in the data set (Marshall et al., 2003a). The
questionnaire was designed to assess the type and
quantity of the beverages consumed during the
previous week. The validity of the questionnaire was
assessed using a 3-day food diary for reference
(Marshall et al., 2003a). Table 3-72 presents the
percentage of subjects consuming beverages and
mean daily beverage ingestion for children with
returned questionnaires. Human milk ingestion was
not quantified, but the percent of children consuming
human milk was provided at each age category (see
Table 3-72). Juice (100%) and juice drinks were not
distinguished separately but categorized as juice and
juice drinks. Water used to dilute beverages beyond
normal dilution and water consumed alone were
combined. Based on Table 3-72, 97% of the children
consumed human milk, formula, or cows' milk
throughout the study period, and the percentage of
infants consuming human milk decreased with age,
while the percent consuming water increased
(Marshall et al., 2003a). Marshall et al. (2003a)
observed that, in general, lower family incomes were
associated with less breast-feeding and increased
ingestion of other beverages.
The advantage of this study is that it provides
mean ingestion data for various beverages.
Limitations of the study are that it is based on
samples gathered in one geographical area and may
not be reflective of the general population. The
authors also noted the following limitations: the
parents were not asked to differentiate between 100%
juice and juice drinks; the data are parent-reported
and could reflect perceptions of appropriate ingestion
instead of actual ingestion, and a substantial number
of the infants from well educated, economically
secure households dropped out during the initial
phase.
3.3.2.19. Marshall et al (2003b)—Relative
Validation of a Beverage Frequency
Questionnaire in Children Aged
6 Months through 5 Years Using 3-Day
Food and Beverage Diaries
Marshall et al. (2003b) conducted a study based
on data taken from 700 children in the IPS. This
study compared estimated beverage ingestion rates
reported in questionnaires for the preceding week and
diaries for the following week. Packets were sent
periodically (every 4 to 6 months) to parents of
children aged 6 weeks through 5 years of age. This
study analyzed data from children, aged 6 and
12 months, and 2 and 5 years of age. Beverages were
categorized as human milk, infant formula, cows'
milk, juice and juice drinks, carbonated and
rehydration beverages, prepared drinks (from
powder) and water. The beverage questionnaire was
completed by parents and summarized the average
amount of each beverage consumed per day by their
children. The data collection for the diaries
maintained by parents included 1 weekend day and
2 weekdays and included detailed information about
beverages consumed. Table 3-73 presents the mean
ingestion rates of all beverages for children aged 6
and 12 months and 3 and 5 years. Marshall et al.
(2003b) concluded that estimates of beverage
ingestion derived from quantitative questionnaires are
similar to those derived from diaries. They found that
it is particularly useful to estimate ingestion of
beverages consumed frequently using quantitative
questionnaires.
The advantage of this study is that the survey
was conducted in two different forms (questionnaire
and diary), and that diaries for recording beverage
ingestion were maintained by parents for 3 days. The
main limitation is the lack of information regarding
whether the diaries were populated on consecutive or
non-consecutive days. The IPS survey participants
may not be representative of the general population
of the United States since participants were primarily
White, and from affluent and well-educated families
in one geographic region of the country.
3.3.2.20. Skinner et al. (2004)—Transition in
Infants' and Toddlers' Beverage Patterns
Skinner et al. (2004) investigated the pattern of
beverage consumption by infants and children
participating in the Feeding Infant and Toddlers
Study (FITS) sponsored by Gerber Products
Company. The FITS is a cross-sectional study
designed to collect and analyze data on feeding
practices, food consumption, and usual nutrient
intake of U.S. infants and toddlers (Devaney et al.,
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2004). It included a stratified random sample of
3,022 infants and toddlers between 4 and 24 months
of age. Parents or primary caregivers of sampled
infants and toddlers completed a single 24-hour
dietary recall of all foods and beverages consumed by
the child on the previous day by telephone interview.
All recalls were completed between March and July
2002. Detailed information on data collection,
coding, and analyses related to FITS is provided in
Devaney et al. (2004).
Beverages consumed by FITS participants were
identified as total milks (i.e., human milk, infant
formulas, cows' milk, soy milk, goats' milk), 100%
juices, fruit drinks, carbonated beverages, water, and
"other" drinks (i.e., tea, cocoa, dry milk mixtures,
and electrolyte replacement beverages). There were
six age groupings in the FITS study: 4 to 6, 7 to 8, 9
to 11, 12 to 14, 15 to 18, and 19 to 24 months.
Skinner et al. (2004) calculated the percentage of
children in each age group consuming any amount in
a beverage category and the mean amounts
consumed. Table 3-74 provides the mean beverage
consumption rates in mL/day for the six age
categories. Skinner et al. (2004) found that some
form of milk beverage was consumed by almost all
children at each age; however, total milk ingestion
decreased with increasing age. Water consumption
also doubled with age, from 163 mL/day in children
aged 4 to 6 months old to 337 mL/day in children
aged 19 to 24 months old. The percentages of
children consuming water increased from 34% at 4 to
6 months of age to 77% at 19 to 24 months of age.
A major strength of the Skinner et al. (2004)
study is the large sample size (3,022 children).
However, beverage ingestion estimates are based on
1 day of dietary recall data and human milk quantity
derived from studies that weighed infants before and
after each feeding to determine the quantity of human
milk consumed (Devaney et al., 2004); therefore,
estimates of total milk ingestion may not be accurate.
3.4. PREGNANT AND LACTATING WOMEN
3.4.1. Key Study on Pregnant and Lactating
Women
3.4.1.1. Kahn and Stralka (2008b)—Estimates of
Water Ingestion for Women in Pregnant,
Lactating and Non-Pregnant and
Non-Lactating Child Bearing Age
Groups Based on USDA's 1994-1996,
1998 CSFII
The combined 1994-1996 and 1998 CSFII data
sets were analyzed to examine the ingestion of water
by various segments of the U.S. population as
described in Section 3.3.1.1. Kahn and Stralka
(2008b) provided water intake data for pregnant,
lactating, and child-bearing age women. Mean and
upper percentile distribution data were provided.
Lactating women had an estimated per capita mean
community water ingestion of 1.38 L/day, the highest
water ingestion rates of any identified subpopulation.
The mean consumer-only population was 1.67 L/day.
Tables 3-75 through 3-82 provide estimated drinking
water intakes for pregnant and lactating women, and
non-pregnant, non-lactating women aged 15^4 years
old. The same advantages and disadvantages
discussed in Section 3.3.1.1 apply to these data.
3.4.2. Relevant Studies on Pregnant and
Lactating Women
3.4.2.1. Ershow et al (1991)—Intake of Tap
Water and Total Water by Pregnant and
Lactating Women
Ershow et al. (1991) used data from the
1977-1978 USDA NFCS to estimate total fluid and
total tap water intake among pregnant and lactating
women (ages 15-49 years). Data for 188 pregnant
women, 77 lactating women, and
6,201 non-pregnant, non-lactating control women
were evaluated. The participants were interviewed
based on 24-hour recall and then asked to record a
food diary for the next 2 days. "Tap water" included
tap water consumed directly as a beverage and tap
water used to prepare food and tap water-based
beverages. "Total water" was defined as all water
from tap water and non-tap water sources, including
water contained in food. Tables 3-83 and 3-84 present
estimated total fluid and total tap water intake rates
for the three groups, respectively. Lactating women
had the highest mean total fluid intake rate
(2.24 L/day) compared with both pregnant women
(2.08 L/day) and control women (1.94 L/day).
Lactating women also had a higher mean total tap
water intake rate (1.31 L/day) than pregnant women
(1.19 L/day) and control women (1.16 L/day). The
tap water distributions are neither normal nor
lognormal, but lactating women had a higher mean
tap water intake than controls and pregnant women.
Ershow et al. (1991) also reported that rural women
(N = 1,885) consumed more total water (1.99 L/day)
and tap water (1.24 L/day) than urban/suburban
women (N = 4,581, 1.93 and 1.13 L/day,
respectively). Total water and tap water intake rates
were lowest in the northeastern region of the United
States (1.82 and 1.03 L/day) and highest in the
western region of the United States (2.06 L/day and
1.21 L/day). Mean intake per unit body weight was
highest among lactating women for both total fluid
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and total tap water intake. Total tap water intake
accounted for over 50% of mean total fluid in all
three groups of women (see Table 3-84). Drinking
water accounted for the largest single proportion of
the total fluid intake for control (30%), pregnant
(34%), and lactating women (30%) (see Table 3-85).
All other beverages combined accounted for
approximately 46%, 43%, and 45% of the total water
intake for control, pregnant, and lactating women,
respectively. Food accounted for the remaining
portion of total water intake.
The same advantages and limitations associated
with the Ershow and Cantor (1989) data also apply to
these data sets (see Section 3.3.2.9). A further
advantage of this study is that it provides information
on estimates of total water and tap water intake rates
for pregnant and lactating women. This topic has
rarely been addressed in the literature.
3.4.2.2. Forssen et al (2007)—Predictors of Use
and Consumption of Public Drinking
Water Among Pregnant Women
Forssen et al. (2007) evaluated the demographic
and behavioral characteristics that would be
important in predicting water consumption among
pregnant women in the United States. Data were
collected through telephone interviews with
2,297 pregnant women in three geographical areas in
the southern United States. Women 18 years old and
<12 weeks pregnant were recruited from the local
communities and from both private and public
prenatal care facilities in the southern United States.
Variables studied included demographic, health status
and history (e.g., diabetes, pregnancy history),
behavioral (e.g., exercise, smoking, caffeine
consumption), and some physiological characteristics
(e.g., pre-pregnancy weight). Daily amount of water
ingestion was estimated based on cup sizes defined in
the interview. Water consumption was reported as
cold tap water (filtered and unfiltered) and bottled
water. Other behavioral information on water use
such as showering and bathing habits, use of
swimming pools, hot tubs, and Jacuzzis was
collected. The overall mean tap water ingested was
1.7 L/day (percentiles: 25th = 0.5 L/day,
50th=1.4L/day, 75th = 2.4 L/day, and
90th = 3.8 L/day). The overall mean bottled water
ingested was 0.6 L/day (percentiles: 25th =0.1 L/day,
50th = 0.2 L/day, 75^ = 0.6 L/day, and
90th = 1.8 L/day). Table 3-86 presents water ingestion
by the different variables studied, and Table 3-87
presents the percentage of ingested tap water that is
filtered and unfiltered by various variables. The
advantage of this study is that it investigated water
consumption in relation to multiple variables.
However, the study population was not random and
not representative of the entire United States. There
are also limitations associated with recall bias.
3.5. HIGH ACTIVITY
CLIMATES
LEVELS/HOT
3.5.1. Relevant Studies on High Activity
Levels/Hot Climates
3.5.1.1. McNall and Schlegel (1968)—Practical
Thermal Environmental Limits for
Young Adult Males Working in Hot,
Humid Environments
McNall and Schlegel (1968) conducted a study
that evaluated the physiological tolerance of adult
males working under varying degrees of physical
activity. Subjects were required to operate
pedal-driven propeller fans for 8-hour work cycles
under varying environmental conditions. The activity
pattern for each individual was cycled as 15 minutes
of pedaling and 15 minutes of rest for each 8-hour
period. Two groups of eight subjects each were used.
Work rates were divided into three categories as
follows: high activity level (0.15 horsepower [hp] per
person), medium activity level (0.1 hp per person),
and low activity level (0.05 hp per person). Evidence
of physical stress (i.e., increased body temperature,
blood pressure, etc.) was recorded, and individuals
were eliminated from further testing if certain stress
criteria were met. The amount of water consumed by
the test subjects during the work cycles was also
recorded. Water was provided to the individuals on
request.
Table 3-88 presents the water intake rates
obtained at the three different activity levels and the
various environmental temperatures. The data
presented are for test subjects with continuous data
only (i.e., those test subjects who were not eliminated
at any stage of the study as a result of stress
conditions). Water intake was the highest at all
activity levels when environmental temperatures
were increased. The highest intake rate was observed
at the low activity level at 100T (0.65 L/hour);
however, there were no data for higher activity levels
at 100°F. It should be noted that this study estimated
intake on an hourly basis during various levels of
physical activity. These hourly intake rates cannot be
converted to daily intake rates by multiplying by
24 hours/day because they are only representative of
intake during the specified activity levels, and the
intake rates for the rest of the day are not known.
Therefore, comparison of intake rate values from this
study cannot be made with values from the
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previously described studies on drinking water
intake.
3.5.1.2. U.S. Army (1983)—Water Consumption
Planning Factors Study
The U.S. Army has developed water
consumption planning factors to enable them to
transport an adequate amount of water to soldiers in
the field under various conditions (U.S. Army, 1983).
Both climate and activity levels were used to
determine the appropriate water consumption needs.
Consumption factors have been established for the
following uses: (1) drinking, (2) heat treatment,
(3) personal hygiene, (4) centralized hygiene,
(5) food preparation, (6) laundry, (7) medical
treatment, (8) vehicle and aircraft maintenance,
(9) graves registration, and (10) construction. Only
personal drinking water consumption factors are
described here. Drinking water consumption planning
factors are based on the estimated amount of water
needed to replace fluids lost by urination,
perspiration, and respiration. It assumes that water
lost to urinary output averages 1 quart/day
(0.9 L/day), and perspiration losses range from
almost nothing in a controlled environment to
1.5 quarts/day (1.4 L/day) in a very hot climate where
individuals are performing strenuous work. Water
losses to respiration are typically very low except in
extreme cold where water losses can range from 1 to
3 quarts/day (0.9 to 2.8 L/day). This occurs when the
humidity of inhaled air is near zero, but expired air is
98% saturated at body temperature (U.S. Army,
1983).
Drinking water is defined by the U.S. Army
(1983) as "all fluids consumed by individuals to
satisfy body needs for internal water." This includes
soups, hot and cold drinks, and tap water. Planning
factors have been established for hot, temperate, and
cold climates based on the following mixture of
activities among the workforce: 15% of the force
performing light work, 65% of the force performing
medium work, and 20% of the force performing
heavy work. Hot climates are defined as tropical and
arid areas where the temperature is greater than SOT.
Temperate climates are defined as areas where the
mean daily temperature ranges from 32°F to 80°F.
Cold regions are areas where the mean daily
temperature is less than 32°F. Table 3-89 presents
drinking water consumption factors for these three
climates. These factors are based on research on
individuals and small unit training exercises. The
estimates are assumed to be conservative because
they are rounded up to account for the subjective
nature of the activity mix and minor water losses that
are not considered (U.S. Army, 1983).
The advantage of using these data is that they
provide a conservative estimate of drinking water
intake among individuals performing at various
levels of physical activity in hot, temperate, and cold
climates. However, the planning factors described
here are based on assumptions about water loss from
urination, perspiration, and respiration, and are not
based on survey data or actual measurements.
3.6. WATER INGESTION
SWIMMING AND DIVING
WHILE
3.6.1. Key Study on Water Ingestion While
Swimming
3.6.1.1. Dufour et al (2006)— Water Ingestion
during Swimming Activities in a Pool: A
Pilot Study
Dufour et al. (2006) estimated the amount of
water ingested while swimming, using cyanuric acid
as an indicator of pool water ingestion exposure.
Cyanuric acid is a breakdown product of
chloroisocyanates, which are commonly used as
disinfectant stabilizers in recreational water
treatment. Because ingested cyanuric acid passes
through the body unmetabolized, the volume of water
ingested can be estimated based on the amount of
cyanuric acid measured in the pool water and in the
urine of swimmers, as follows:
* pool water ingested ~ * urine
. J-i)
where:
Vpooi water ingested = volume of pool water
ingested (mL),
Vunne = volume of urine collected
over a 24-hour period
(mL),
CAunne = concentration of cyanuric
acid in urine (mg/L), and
CAp00i = concentration of cyanuric
acid in pool water (mg/L).
According to Dufour et al. (2006), dermal
absorption of cyanuric acid has been shown to be
negligible. Thus, the concentration in urine is
assumed to represent the amount ingested. Dufour et
al. (2006) estimated pool water intake among
53 swimmers that participated in a pilot study at an
outdoor swimming pool treated with
chloroisocyanate. This pilot study population
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included 12 adults (4 males and 8 females) and
41 children under 18 years of age (20 males and
21 females). The study participants were asked not to
swim for 24 hours before or after a 45-minute period
of active swimming in the pool. Pool water samples
were collected prior to the start of swimming
activities, and swimmers' urine was collected for
24 hours after the swimming event ended. The pool
water and urine sample were analyzed for cyanuric
acid.
Table 3-90 presents the results of this pilot study.
The mean volumes of water ingested over a
45-minute period were 16 mL for adults and 37 mL
for children. The maximum volume of water ingested
by adults was 53 mL, and by children, was
154 mL/45 minutes, as found in the
recommendations table for water ingestion while
swimming (see Table 3-5). The 97th percentile
volume of water ingested by children was
approximately 90 mL/45 minutes (see Table 3-5).
The advantage of this study is that it is one of the
first attempts to measure water ingested while
swimming. However, the number of study
participants was low, and data cannot be broken out
by the recommended age categories. As noted by
Dufour et al. (2006), swimming behavior of pool
swimmers may be similar to freshwater swimmers
but may differ from salt water swimmers.
Based on the results of the Dufour et al. (2006)
study, the recommended mean water ingestion rates
for exposure scenarios involving swimming activities
are 21 mL/hour for adults and 49 mL/hour for
children under 18 years of age. Because the data set
is limited, upper percentile water ingestion rates for
swimming are based on the 97th percentile value for
children and the maximum value for adults from the
Dufour et al. (2006) study. These values are
71 mL/hour for adults and 120 mL/hour for children
(see Table 3-5). Also, competitive swimmers may
swallow more water than the recreational swimmers
observed in this study (Dufour et al., 2006).
3.6.2. Relevant Studies on Water Ingestion
While Swimming, Diving, or Engaging in
Recreational Water Activities
3.6.2.1. Schijven and de Roda Husman (2006)—
A Survey of Diving Behavior and
Accidental Occupational and Sport
Divers to Assess the Risk of Infection
with Waterborne Pathogenic
Microorganisms
Schijven and de Roda Husman (2006) estimated
the amount of water ingested by occupational and
sports divers in The Netherlands. Questionnaires
were used to obtain information on the number of
dives for various types of water bodies, and the
approximate volume of water ingested per dive.
Estimates of the amount of water ingested were made
by comparing intake to common volumes (i.e., a few
drops = 2.75 mL; shot glass = 25 mL; coffee
cup =100 mL; soda glass =190 mL). The study was
conducted among occupational divers in 2002 and
among sports divers in 2003 and included responses
from more than 500 divers. Table 3-91 provides the
results of this study. On average, occupational divers
ingested 9.8 mL/dive marine water and 5.7 mL/dive
freshwater. Sports divers wearing an ordinary diving
mask ingested 9.0 mL/dive marine water and
13 mL/dive fresh recreational water. Sports divers
who wore full face masks ingested less water. The
main limitation of this study is that no measurements
were taken. It relies on estimates of the perceived
amount of water ingested by the divers.
3.6.2.2. Schets et al (2011)—Exposure
Assessment for Swimmers in Bathing
Waters and Swimming Pools
Schets et al. (2011) collected exposure data for
swimmers in freshwater, seawater, and swimming
pools in 2007 and 2009. Information on the
frequency, duration, and amount of water swallowed
were collected via questionnaires administered to
nearly 10,000 people in The Netherlands. Individuals
15 years of age and older were considered to be
adults and answered questions for themselves, and a
parent answered the questions for their eldest child
under 15 years of age. Survey participants estimated
the amount of water that they swallowed while
swimming by responding in one of four ways:
(1) none or only a few drops; (2) one or two
mouthfuls; (3) three to five mouthfuls; or (4) six to
eight mouthfuls. Schets et al. (2011) conducted a
series of experiments to measure the amount of water
that corresponded to a mouthful of water and
converted the data in the four response categories to
volumes of water ingested. Monte Carlo analyses
were used to combine the distribution of volume (i.e.,
mouthful) measurements with the distribution of
responses in the four response categories to generate
distributions of the amount of water swallowed per
event for adult men and women, and children less
than 15 year of age. Table 3-92 presents the means
and 95% confidence intervals for the duration of
swimming and amount of water ingested during
swimming. Frequency data were also provided by
Schets et al. (2011), but these data are not presented
here because they are for the population of The
Netherlands and may not be representative of
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swimming frequency in the U.S. According to Schets
et al. (2011), the mean volume of water ingested by
children (<15 years) during an average swimming
pool event lasting 81 minutes was 51 mL or
0.63 mL/min (38 mL/hour). The values for children
were slightly lower for swimming in freshwater and
seawater. For adults, the mean volume of water
ingested ranged from 0.5 to 0.6 mL/min (30 to
36 mL/hour) for men and 0.3 to 0.4 mL/min (20 to
26 mL/hour) for women (see Table 3-92).
The advantages of this study are that it is based
on a relatively large sample size and that data are
provided for various types of swimming
environments (i.e., pools, freshwater, and seawater).
However, the data were collected from a population
in The Netherlands and may not be entirely
representative of the United States. While the
ingestion data are based primarily on self-reported
estimates, the mean values reported in this study are
similar to those based on measurements of cyanuric
acid in the urine of swimmers as reported by Dufour
et al. (2006).
3.6.2.3. Dorevitch et al. (2011)—Water Ingestion
during Water Recreation
Dorevitch et al. (2011) estimated the volumes of
water ingested during "limited contact water
recreation activities." These activities included such
as canoeing, fishing, kayaking, motor boating,
rowing, wading and splashing, and walking. Full
contact scenarios (i.e., swimming and immersion)
were also evaluated. Dorevitch et al. (2011) estimated
water intake among individuals greater than 6 years
of age using two different methods in studies
conducted in 2009. In the first surface water study,
serf-reported estimates of ingestion were obtained via
interview from 2,705 individuals after they engaged
in recreation activities in Chicago area surface
waters. A total of 2,705 participants reported whether
they swallowed no water, a drop or two, a teaspoon,
or one or more mouthfuls of water during one of the
five limited contact recreational activities (i.e.,
canoeing, fishing, kayaking, motor boating, and
rowing). A second study was conducted in swimming
pools where 662 participants engaged in limited
contact scenarios (i.e., canoeing, simulated fishing,
kayaking, motor boating, rowing, wading/splashing,
and walking), as well as full contact activities such as
swimming and immersion. Participants were
interviewed after performing their water activity and
reported on their estimated water ingestion. In
addition, 24-hour urine samples were collected for
analysis of cyanuric acid, a tracer of swimming pool
water. Translation factors for each of the reported
categories of ingestion (e.g., none, drop/teaspoon,
mouthful) were developed using the results of the
urine analyses. These translation factors were used to
estimate the volume of water ingested for the various
water activities evaluated in this study (Dorevitch et
al., 2011). Table 3-93 presents the estimated volumes
of water ingested for the limited and full contact
scenarios. Swimmers had the highest estimated water
intake (mean = 10 mL/hr; 95% upper confidence
limit =35 mL/hr) among the activities evaluated.
The advantage of this study is that it provides
information on the estimated volume of water
ingested during both limited and full contact
recreational activities. However, the data are based on
serf-reporting, and data are not provided for
individual age groups of the population.
3.7. REFERENCES FOR CHAPTER 3
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Ershow, AG; Cantor, KP. (1989) Total water and tap
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Ershow, AG; Brown, LM; Cantor, KP. (1991) Intake
of tap water and total water by pregnant and
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
lactating women. Amer J Pub Health
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Evans, CL; ed. (1941) Starling's principles of human
physiology, 8th ed. Philadelphia, PA: Lea
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Forssen, UM; Herring, AH; Savitz, DA;
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PC; Wright, JM. (2007) Predictors of use
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Gillies, ME; Paulin, HV. (1983) Variability of mineral
intakes from drinking water: a possible
explanation for the controversy over the
relationship of water quality to
cardiovascular disease. Int J Epid 12(1):45-
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Guyton, AC. (1968) Textbook of medical physiology,
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Heller, K; Sohn, W; Burt, B; Feigal, R. (2000) Water
consumption and nursing characteristics of
infants by race and ethnicity. J Public
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Hilbig, A; Kersting, M; Sichert-Hellert, W. (2002)
Measured consumption of tap water in
German infants and young children as
background for potential health risk
assessment: data of the DONALD study.
Food Addit Contam 19(9):829-836.
Hopkins, SM; Ellis, JC. (1980) Drinking water
consumption in Great Britain: a survey of
drinking habits with special reference to tap-
water-based beverages. Technical Report
137, Water Research Centre, Wiltshire Great
Britain.
Kahn, H. (2008). Letter from Henry Kahn to
Jacqueline Moya, U.S. EPA, providing
supplemental data to "Estimated daily
average per capita water ingestion by child
and adult age categories based on USDA's
1994-96 and 1998 continuing survey of
food intakes by individuals" (September 18,
2008).
Kahn, H; Stralka, K. (2008a) Estimated daily average
per capita water ingestion by child and adult
age categories based on USDA's 1994-1996
and 1998 continuing survey of food intakes
by individuals. J Expo Sci Environ
Epidemiol 19(4):396-404.
Kahn, H; Stralka, K. (2008b) Estimates of water
ingestion for women in pregnant, lactating,
and non-pregnant and non-lactating child-
bearing age groups based on USDA's 1994-
96, 1998 continuing survey of food intake
by individuals. Hum Ecol Risk Assess
14(6): 1273-1290.
Levy, SM; Kohout, FJ; Guha-Chowdhury, N; Kiritsy,
MC; Heilman, JR; Wefel, JS. (1995) Infants'
fluoride intake from drinking water alone,
and from water added to formula, beverages,
and food. J Dent Res 74(7): 1399-1407.
LSRO (Life Sciences Research Office ). (1995) Third
report on nutrition monitoring in the United
States: Volume 1. Prepared by Federation of
American Societies for Experimental
Biology for the Interagency Board for
Nutrition Monitoring and Related Research.
Washington, DC: U.S. Government Printing
Office.
Marshall, T; Levy, S; Broffitt, B; Eichenberger-
Gilmore, J; Stumbo, P. (2003a) Patterns of
beverage consumption during the transition
stage of infant nutrition. J Amer Diet Assoc
103(10):1350-1353.
Marshall, T; Eichenberger Gilmore, J; Broffitt, B;
Levy, S; Stumbo, P. (2003b) Relative
validation of a beverage frequency
questionnaire in children ages 6 months
through 5 years using 3-day food and
beverage diaries. J Amer Diet Assoc
103(6):714-720.
McNall, PE; Schlegel, JC. (1968) Practical thermal
environmental limits for young adult males
working in hot, humid environments.
ASHRAE Transactions 74:225-235.
NCHS (National Center for Health Statistics). (1993)
Joint policy on variance estimation and
statistical reporting standards on NHANES
III and CSFII reports: HNIS/NCHS analytic
working group recommendations. Human
Nutrition Information Service
(HNIS)/Analytic Working Group. Available
from: Agricultural Research Service, Survey
Systems/Food Consumption Laboratory,
4700 River Road, Unit 83, Riverdale, MD.
NRC (National Research Council). (1974)
Recommended dietary allowances, 8th ed.
Washington, DC: National Academies Press.
NRC (National Research Council). (1977) Drinking
water and health. Vol. 1. Washington, DC:
National Academies Press.
Pennington, JAT (1983) Revision of the total diet
study food list and diets. J Amer Diet Assoc
82(2):166-173.
Pike, RL; Brown, M. (1975) Minerals and water in
nutrition—an integrated approach, 2nd ed.
New York, NY: John Wiley and Sons.
Randall, HT (1973) Water, electrolytes and acid base
balance. In: Goodhart, RS; Shils, ME, eds.
Page
3-26
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-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Modern nutrition in health and disease.
Philadelphia, PA: Lea and Febiger.
Roseberry, AM; Burmaster, DE. (1992) Lognormal
distribution for water intake by children and
adults. Risk Anal 12:99-104.
Schets, FM; Schijven, JF; Husman, AM. (2011)
Exposure assessment for swimmers in
bathing waters and swimming pools. Water
Res 45(7):2392-2400.
Schijven, J; de Roda Husman, AM. (2006) A survey
of diving behavior and accidental water
ingestion among Dutch occupational and
sport divers to assess the risk of infection
with waterborne pathogenic
microorganisms. Environ Health Perspect
114(5):712-717.
Sichert-Hellert, W; Kersting, M; Manz, F. (2001)
Fifteen year trends in water intake in
German children and adolescents: results of
the DONALD study. Acta Paediatr
90(7):732-737.
Skinner, J; Ziegler, P; Ponza, M. (2004) Transition in
infants' and toddlers' beverage patterns. J
AmerDiet Assoc 104(Suppl 1):S45-S50.
Sohn, W; Heller, KE.; Burt, BA. (2001) Fluid
consumption related to climate among
children in the United States. J Public
Health Dent 61(2):99-106.
U.S. Army. (1983) Water consumption planning
factors study. Directorate of Combat
Developments, United States Army
Quartermaster School, Fort Lee, VA.
USDA (Department of Agriculture). (1995) Food and
nutrient intakes by individuals in the United
States, 1 day, 1989-91. United States
Department of Agriculture, Agricultural
Research Service, Beltsville, MD. NFS
Report No. 91-2. Available online at
http://www.ars.usda.gov/SP2UserFiles/Place
/12355000/pdf/csfii8991_rep_91-2.pdf.
USDA (Department of Agriculture). (1998)
Continuing survey of food intakes by
individuals: 1994-96, 1998. U.S.
Department of Agriculture, Agricultural
Research Service, Beltsville, MD.
USDA (Department of Agriculture). (2000) 1994-96,
1998 Continuing survey of food intakes by
individuals (CSFII). CD-ROM.
Agricultural Research Service, Human
Nutrition Research Center, Beltsville, MD.
Available from the National Technical
Information Service, Springfield, VA; PB-
2000-500027.
U.S. EPA (Environmental Protection Agency). (1984)
An estimation of the daily average food
intake by age and sex for use in assessing
the radionuclide intake of individuals in the
general population. Office of Radiation
Programs, Washington, DC; EPA-520/1-
84/021.
U.S. EPA (Environmental Protection Agency). (1996)
Descriptive statistics from a detailed
analysis of the National Human Activity
Pattern Survey (NHAPS) responses. Office
of Research and Development, Washington,
DC; EPA/600/R-96/148.
U.S. EPA (Environmental Protection Agency). (2000)
Methodology for deriving ambient water
quality criteria for the protection of human
health (2000). Office of Water, Washington,
DC; EPA/822-00/004. Available online at
http://water.epa.gov/scitech/swguidance/stan
dards/upload/2005_05_06_criteria_humanhe
alth_method_complete .pdf.
U.S. EPA (Environmental Protection Agency). (2002)
Drinking water from household wells.
Office of Water, Washington, DC;
EPA/816/K-02/003.
U.S. EPA (Environmental Protection Agency). (2004)
Estimated per capita water ingestion and
body weight in the United States— an
update: based on data collected by the
United States Department of Agriculture's
1994-96 and 1998 Continuing Survey of
Food Intakes by Individuals. Office of
Water, Washington, DC; EPA-822-R-00-
001. Available online at
http://water.epa.gov/action/advisories/drinki
ng/upload/2005_05_06_criteria_drinking_pe
rcapita_2004.pdf.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Office of Research and Development,
Washington, DC; EPA/630/P-03/003F.
Available online at
http ://www. epa. gov/raf/publications/guidanc
e-on-selecting-age-groups.htm.
Walker, BS; Boyd, WC; Asimov, I. (1957)
Biochemistry and human metabolism, 2nd
ed. Baltimore, MD: Williams and Wilkins
Co.
Wolf, AV. (1958) Body water content. Sci Am
199(5): 125-126.
Exposure Factors Handbook
September 2011
Page
3-27
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-7. Per
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18 to <21 years
>21
>65
All
a
b
c
-
*
years
years0
ages
Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/day)
Sample , ,
. Mean
size
91
253
428
714
1,040
1,056
4,391
1,670
1,005
363
389
9,207
2,170
20,607
184
227
362
360
271
317
380
447
606
731
826
1,104
1,127
926
10
-
-
-
-
-
-
4
22
30
16
24
69
16
30
25
-
-
-
17
60
78
98
133
182
194
236
422
50
-
-
148
218
188
246
291
350
459
490
628
928
545 1,067
263
710
Percentile
75
322
456
695
628
402
479
547
648
831
961
1,119
1,530
1,601
1,311
Includes all participants whether or not they ingested any water from the
period.
Direct water is defined as water ingested directly as a beverage; indirect
added in the preparation
U.S. EPA, 2004.
= Zero.
The sample
Monitoring
Source: Kahn, 2008
of food
90
687*
804
928
885
624
683
834
980
1,387
1,562
1,770
2,230
2,139
2,014
95
839*
896*
1,056
1,055
837
877
1,078
1,235
1,727
1,983*
2,540*
2,811
3,551
2,544
99
860*
1,
1,
1
1,
1,
1
1,
2,
3,
3,
4
3
4
165*
424*
511*
215*
364*
,654
870*
568*
720*
889*
,523
,661
,242
source during survey
water is defined as water
or beverages.
size does not meet minimum
in the United States" (LSRO,
requirements
1995).
as described in the "Third Report on Nutrition
(based on 1994-1996, 1998 USDA CSFII).
Page
3-28
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-8. Per
Age
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
18to<21years
>21 years
>65 years0
All ages
Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/day)
Sample , , Percentile
Mean
Slze 10 25 50 75
91 104 - - - 18
253 106 -
428 120 -
714 120 - - - 53
1,040 59
1,056 76
4,391 84
1,670 84
1,005 111 -
363 109 -
389 185 -
9,207 189 -
2,170 136 -
20,607 163 -
a Includes all participants whether or not they ingested any water from the
period.
b Direct water is defined as water ingested directly as a beverage; indirect
90
437*
541
572
506
212
280
325
330
382
426
514
754
591
592
95
556*
771*
774
761
350
494
531
532
709
680*
1,141*
1,183
1,038
1,059
99
1,007*
1,056*
1,443*
1,284*
801*
1,001*
1,031*
1,079*
1,431*
1,605*
2,364*
2,129
1,957
2,007
source during survey
water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
* The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum requirements as described in the Third Report on
in the United States (LSRO, 1995).
(Based on 1994-1996, 1998 USDA CSFII).
Nutrition
Exposure Factors Handbook
September 2011
Page
3-29
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-9. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/day)
Sample „ Percentile
Slze 10 25 50 75
Birth to <1 month 91 13 -
1 to <3 months 253 35 -
3 to <6 months 428 45 -
6 to <12 months 714 45 -
1 to <2 years 1,040 22
2 to <3 years 1,056 39
3 to <6 years 4,391 43
6to21 years 9,207 156 -
>65 years' 2,170 171
All ages 20,607 128 -
90 95 99
393*
367* 687*
365 938*
31 406 963*
118 482*
52 344 718*
58 343 830
181 468 1,047*
344 786 1,698*
295 740* 1,760*
246* 1,047*
541 1,257 2,381
697 1,416 2,269
345 1,008 2,151
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
* The sample size does not meet minimum requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008 (Based on 1994-1996, 1998 USDA CSFII).
Page
3-30
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3 — Ingestion of Water and Other Select Liquids
Table 3-10. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/day)
. Sample
Age . Mean
Slze 10 25 50
Birth to <1 month 91 301 - - 135
1 to <3 months 253 368 - - 267
3 to <6 months 428 528 - 89 549
6 to <12 months 714 530 37 181 505
1 to <2 years 1,040 358 68 147 287
2 to <3 years 1,056 437 104 211 372
3 to <6 years 4,391 514 126 251 438
6to21 years 9,207 1,466 500 828 1,278
>65 years' 2,170 1,451 651 935 1,344
All ages 20,607 1,233 285 573 1,038
Percentile
75
542
694
812
771
477
588
681
803
1,099
1,273
1,394
1,871
1,832
1,633
90 95
846* 877* 1,
889 1,020* 1,
1,025 1,303 1,
1,029 1,278 1,
735 961 1,
825 999 1,
980 1,200 1
1,130 1,409 2,
1,649 1,960 3,
1,842 2,344* 3,
2,117 2,985* 4,
2,553 3,195 5
2,323 2,708 3
2,341 2,908 4
99
088*
265*
509*
690*
281*
662*
,794
167*
179*
854*
955*
,174
,747
,805
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
* The sample size does not meet minimum requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008 (Based on 1994-1996, 1998 USDA CSFII).
Exposure Factors Handbook
September 2011
Page
3-31
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-11. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/kg-day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
-
*
years
years0
ages
Sample ,
size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
9,049
2,139
19,850
/lean
52
48
52
41
23
23
22
16
12
11
12
15
16
16
Percentile
10
-
-
-
-
-
-
-
1
1
-
1
1
-
1
25
-
-
-
2
5
6
6
5
4
3
4
6
7
5
50
-
-
20
24
17
17
17
12
9
8
10
12
15
12
75
101
91
98
71
34
33
31
22
16
15
16
21
23
21
90
196*
151
135
102
53
50
48
34
25
23
17
31
31
32
95
232*
205*
159
126
71
60
61
43
34
31*
35*
39
37
43
99
253*
310*
216*
185*
106*
113*
93
71*
54*
55*
63*
62
52
75
Includes all participants whether or not they ingested any water from the source during survey period.
Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States" (LSRO
(Based on 1994-1 996,
1998
requirements
1995).
USDA CSFII)
as described in the
"Third Report on
Nutrition
Page
3-32
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-12. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/kg-day)
Age
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
18to<21years
>21 years
>65 years0
All ages
Sample
size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
9.049
2,139
19,850
Percentile
Mean
10 25 50 75
33 - - - 6
22
16
13 - - - 4
5 ....
5 ....
5 ....
3 ....
2 - - - -
2 - - - -
3 ....
3 ....
2 - - - -
3 ....
90
131*
97
74
52
18
19
18
10
8
6
8
10
9
10
95
243*
161*
117
87
28
35
30
18
14
10*
19*
17
15
18
99
324*
242*
193*
139*
67*
84*
59
41*
26*
27*
34*
32
27
39
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
* The sample size does not meet minimum requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008
(Based on 1994-1996, 1998 USDA CSFII).
Exposure Factors Handbook
September 2011
Page
3-33
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-13. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/kg-day)
Age
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
18to<21years
>21 years
>65 years0
All ages
Includes all
period.
Sample
size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
9,049
2,139
19,850
participants
Percentile
Mean
10 25 50 75
4 ....
7 ....
7 ....
5 ....
2 - - - -
3 ....
2 - - - -
2 - - - -
2 - - - -
2 - - - -
1 ....
2 - - - -
2 - - - -
2 - - - -
whether or not they ingested any water from the
b Direct water is defined as water ingested directly as a beverage; indirect
added in the preparation
of food or beverages.
90
-
-
-
3
-
4
o
J
7
7
5
-
7
10
6
95
-
52*
55
35
11
23
19
16
14
11*
4*
17
20
16
99
122*
148*
155*
95*
45*
61*
48
36*
34*
27*
14*
33
35
35
source during survey
water
is defined as water
U.S. EPA, 2004.
= Zero.
* The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum requirements as described in the Third Report on Nutrition
in the United States (LSRO, 1995).
(Based on 1994-1996, 1998 USDA CSFII).
Page
3-34
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-14. Per Capita" Estimates
1994-1996,
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
-
*
years
years0
ages
Sample , ,
. r Mean -
size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
9,049
2,139
20,850
89
77
75
59
31
31
29
21
16
15
16
20
21
21
of Combined Direct and Indirect1" Water Ingestion Based on
1998 CSFII: All Sources (mL/kg-day)
10
-
-
-
4
6
7
7
6
4
4
3
7
9
6
25
-
-
9
20
13
15
14
10
8
6
6
11
13
10
50
21
46
73
53
24
26
25
18
13
12
12
17
19
17
Percentile
75
168
134
118
86
39
41
38
27
20
18
21
26
27
26
Includes all participants whether or not they ingested any water from the
period.
Direct water is defined as water ingested directly as a beverage; indirect
added in the preparation of food or beverages.
U.S. EPA, 2004.
= Zero.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States (LSRO,
(Based on 1994-1996, 1998
requirements
1995).
USDA CSFII)
as
90
235*
173
156
118
63
59
56
39
31
28
32
36
34
38
95
269*
246*
186
148
85
73
69
50
39
37*
41*
44
39
50
99
338*
336*
225*
194*
122*
130*
102
76*
60*
59*
73*
68
54
87
source during survey
water is defined as water
described in the Third Report on
Nutrition
Exposure Factors Handbook
September 2011
Page
3-35
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-15. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Community Water (mL/day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18 to <21 years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
40
114
281
562
916
934
3,960
1,555
937
341
364
8,505
1,958
18,509
Mean -
470*
552
556
467
308
356
417
480
652
792
895
1,183
1,242
1,000
Percentile
10
32*
67*
44
44
43
49
57
74
106
106
114
208
310
127
25
215*
339
180
105
107
126
146
177
236
266
295
529
704
355
50
482*
533
561
426
229
281
336
373
487
591
674
1,006
1,149
786
Excludes individuals who did not ingest water from the source
Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States" (LSRO
(Based on
1994-1996, 1998
75
692*
801
837
710
428
510
581
682
873
987
1,174
1,582
1,657
1,375
90
849*
943*
1,021
971
674
700
867
994
1,432
1,647
1,860
2,289
2,190
2,069
during the survey
; indirect water is
requirements as described in the
1995).
95
858*
1,053*
1,171*
1,147
893
912
1,099
1,251
1,744
2,002*
2,565*
2,848
2,604
2,601
99
919*
1,
1,
1,
1,
1,
1
2,
2,
3,
3,
264*
440*
586*
248*
388*
,684
024*
589*
804*
917*
4,665
3
4
,668
,274
period.
defined as water
"Third Report on Nutrition
USDA CSFII).
Page
3-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-16. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Bottled Water (mL/day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
25
64
103
200
229
232
1,021
332
192
63
97
1,893
302
4,451
Mean -
-
450*
507
425
262
352
380
430
570
615*
769
831
910
736
Percentile
10
-
31*
48*
47
45
57
72
88
116*
85*
118*
167
234
118
25
-
62*
88
114
88
116
149
168
229
198*
236
354
465
266
50
-
329*
493
353
188
241
291
350
414
446*
439
650
785
532
75
-
743*
747
630
324
471
502
557
719
779*
943
1,071
1,182
975
90
-
886*
1,041*
945*
600
736
796
850
1,162*
1,365*
1,788*
1,773
1,766
1,567
95
-
1,045*
1,436*
1,103*
709*
977*
958
1,081*
1,447*
1,613*
2,343*
2,093
2,074
1,964
1,
1,
1,
1,
1,
1,
1,
2,
2,
3,
3
2
3
99
-
562*
506*
413*
083*
665*
635*
823*
705*
639*
957*
,505
,548
,312
Excludes individuals who did not ingest water from the source during the survey period.
Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
Insufficient sample size to estimate mean and percentiles.
The sample size does not meet minimum requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008
(Based on 1994-1996, 1998
USDA CSFII).
Exposure Factors Handbook
September 2011
Page
3-37
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-17. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: Other Sources (mL/day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
3
19
38
73
98
129
533
219
151
53
33
1,386
323
2,735
Mean -
-
-
562*
407*
262
354
396
448
687
657*
569*
1,137
1,259
963
Percentile
10
-
-
59*
31*
18*
56*
59
89
171*
152*
103*
236
360
148
25
-
-
179*
121*
65
134
148
177
296
231*
142*
503
680
347
50
-
-
412*
300*
143
318
314
347
482
398*
371*
976
1,188
741
Excludes individuals who did not ingest water from the source
Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
Insufficient
The sample
Monitoring
Source: Kahn, 2008
75
-
-
739*
563*
371
472
546
682
947
823*
806*
1,533
1,660
1,344
90
-
-
983*
961*
602*
704*
796
931
1,356*
1,628*
1,160*
2,161
2,136
1,970
during the survey
; indirect water is
sample size to estimate means and percentiles.
size does not meet minimum requirements as described in the
in the United States (LSRO, 1995).
(Based on 1994-1996, 1998
95
-
-
1,205*
1,032*
899*
851*
1,019
1,090*
1,839*
1,887*
1,959*
2,739
2,470
2,468
2,
1,
1,
1,
1,
1,
2,
2,
1,
4
3,
3
99
-
-
264*
144*
204*
334*
543*
596*
891*
635*
962*
,673
707*
,814
period.
defined as water
Third Report on
Nutrition
USDA CSFII).
Page
3-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-18. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
1994-1996, 1998 CSFII: All Sources (mL/day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
58
178
363
667
1,017
1,051
4,350
1,659
1,000
357
383
9,178
2,167
20,261
Mean -
511*
555
629
567
366
439
518
603
837
983
1,094
1,472
1,453
1,242
Percentile
10
51*
68*
69
90
84
105
134
177
229
252
219
506
651
296
25
266*
275
384
250
159
213
255
310
404
395
424
829
939
585
50
520*
545
612
551
294
375
442
506
665
754
823
1,282
1,345
1,047
Excludes individuals who did not ingest water from the source
Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States (LSRO,
(Based on 1994-1996, 1998
75
713*
801
851
784
481
589
682
805
1,105
1,276
1,397
1,877
1,833
1,642
90
858*
946*
1,064
1,050
735
825
980
1,131
1,649
1,865
2,144
2,559
2,324
2,345
during the survey
; indirect water is
requirements as described in the
1995).
95
986*
1,072*
1,330*
1,303
978
1,001
1,206
1,409
1,961
2,346*
3,002*
3,195
2,708
2,923
1,
1,
1,
1,
1,
1,
1
2,
3,
3,
4,
5
3
4
99
274*
470*
522*
692*
281*
663*
,796
168*
184*
866*
967*
,175
,750
,808
period.
defined as water
Third Report on
Nutrition
USDA CSFII).
Exposure Factors Handbook
September 2011
Page
3-39
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-19. Consumers-Only" Estimates of Direct and Indirect11 Water Ingestion Based on 1994-1996,
1998 CSFII: Community Water (mL/kg-day)
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
37
108
269
534
880
879
3,703
1,439
911
339
361
8,355
1,927
17,815
Jvlean
137*
119
80
53
27
26
24
17
13
12
13
16
18
17
Percentile
10
11*
12*
7
5
4
4
3
3
2
1
2
3
5
3
25
65*
71
27
12
9
9
8
6
5
4
5
7
10
7
50
138*
107
77
47
20
21
19
13
10
9
10
13
16
13
Excludes individuals who did not ingest water from the source
Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States (LSRO,
(Based on
1994-1996,
1998
75
197*
151
118
81
36
36
33
23
17
16
17
22
24
22
90
235*
228*
148
112
56
52
49
35
26
24
29
32
32
33
during the survey
; indirect water is
requirements as described in the
1995).
95
238*
285*
173*
129
75
62
65
45
34
32*
35*
39
37
44
99
263*
345*
222*
186*
109*
121*
97
72*
54*
58*
63*
63
53
77
period.
defined as water
Third Report on
Nutrition
USDA CSFII).
Page
3-40
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-20. Consumers-Only" Estimates of Direct and Indirect11 Water Ingestion Based on 1994-1996,
1998 CSFII: Bottled Water (mL/kg-day)
A(rp Sample Mpcm Percentile
Slze 10 25 50
Birth to <1 month 25 - - - -
1 to <3 months 64 92* 7* 12* 76*
3 to <6 months 95 72 6* 15 69
6 to <12 months 185 47 5* 11 34
1 to <2 years 216 22 5 8 16
2 to <3 years 211 25 4 8 17
3 to <6 years 946 21 4 8 16
6to21 years 1,861 12 2 5 9
>65 years' 297 13 3 7 12
All ages 4,234 13 2 5 9
a Excludes individuals who did not ingest water from the source
b Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
75
-
151*
100
73
27
35
29
19
14
11*
14
16
17
17
90 95
-
164* 220*
149* 184*
104* 120*
49 66*
54 81*
45 57
30 42*
24* 27*
23* 27*
27* 30*
25 31
26 30
27 36
99
-
411*
213*
166*
103*
91*
90*
69*
44*
37*
54*
45
42*
72
during the survey period.
; indirect water is defined as water
Insufficient sample size to estimate means and percentiles.
* The sample size does not meet minimum requirements as described in the
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008 (Based on 1994-1996, 1998 USDA CSFII).
Third Report on
Nutrition
Exposure Factors Handbook
September 2011
Page
3-41
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-21. Consumers-Only" Estimates of Direct and Indirect11 Water Ingestion Based on 1994-1996,
1998 CSFII: Other Sources (mL/kg-day)
Sample „ Percentile
Slze 10 25 50 75
Birth to <1 month 3 - - - -
1 to <3 months 19 - - - -
3 to <6 months 38 80* 10* 23* 59* 106*
6 to <12 months 68 44* 4* 10* 33* 65*
1 to <2 years 95 23 1* 5 13 28
2 to <3 years 124 26 4* 10 21 34
3 to <6 years 505 22 3 8 17 30
6to21 years 1,365 15 3 6 13 21
>65 years' 322 18 5 9 16 24
All ages 2,657 16 3 6 12 21
90 95
-
-
170* 200*
95* 106*
46* 84*
55* 66*
46 56
32 39*
27* 36*
24* 29*
16* 27*
30 39
31 37
32 41
99
-
-
246*
147*
125*
114*
79*
62*
56*
43*
31*
58
50*
67
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
U.S. EPA, 2004.
Indicates insufficient sample size to estimate distribution percentiles.
* The sample size does not meet minimum requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: Kahn, 2008 (Based on 1994-1996, 1998 USDA CSFII).
Page
3-42
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-22. Consumers-Only
Age
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21years
>21
>65
All
a
b
c
*
years
years0
ages
Sample
size
55
172
346
631
980
989
4,072
1,542
970
354
378
9,020
2,136
19,509
a Estimates of Direct and Indirect11 Water Ingestion Based on 1994-1996,
1998 CSFII: All Sources (mL/kg-day)
Mean -
153*
116
90
63
31
31
29
21
16
15
16
20
21
21
Percentile
10
13*
12*
9
10
7
7
7
6
4
4
3
7
9
6
25
83*
50
52
27
14
15
15
10
8
7
6
11
13
11
50
142*
107
86
58
25
27
25
18
13
12
12
17
19
17
Excludes individuals who did not ingest water from the source
Direct water is defined as water ingested directly as a beverage
added in the preparation of food or beverages.
U.S. EPA, 2004.
The sample
Monitoring
Source: Kahn, 2008
size does not meet minimum
in the United States (LSRO,
(Based on
1994-1996, 1998
75
208*
161
125
88
40
41
38
27
20
18
21
26
27
26
90
269*
216*
161
120
64
59
56
39
31
29
32
36
34
38
during the survey
; indirect water is
requirements as described in the
1995).
95
273*
291*
195*
152
86
73
70
50
39
37*
41*
44
39
50
99
400*
361*
233*
198*
122*
130*
102*
76*
60*
60*
73*
68
54
87
period.
defined as water
Third Report on
Nutrition
USDA CSFII).
Exposure Factors Handbook
September 2011
Page
3-43
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-23. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 88 239*
1 to <3 months 143 282*
3 to <6 months 244 373*
6 to <12 months 466 303
1 to <2 years 611 223
2 to <3 years 571 265
3 to <6 years 1,091 327
6to21 years 8,673 1,043
>65 years 2,287 1,046
All ages 18,216 869
46
27
39
67
64
60
59
88
227
279
134
78*
41*
378*
199
134
160
245
297
329
375
355
787
886
560
473*
524*
630*
520
310
387
465
598
688
865
872
1,577
1,587
1,299
693*
784*
794*
757*
577*
657*
746
1,000
1,338
1,378
1,808
2,414
2,272
2,170
851*
962*
925*
866*
760*
861*
959
1,316
1,821
1,783
2,368
2,958
2,730
2,717
956*
1,102*
1,192*
1,150*
1,206*
1,354*
1,570*
2,056*
2,953
3,053
3,911
4,405
4,123
4,123
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-44
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-24. Per Capita" Estimates of Combined Directb Water Ingestion Based on NHANES
2003-2006: Bottled Water (mL/day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 88 6*
1 to <3 months 143 21*
3 to <6 months 244 12*
6 to <12 months 466 34
1 to <2 years 611 65
2 to <3 years 571 95
3 to <6 years 1,091 108
6to21 years 8,673 375
>65 years 2,287 152
All ages 18,216 321
26
82
81
118
172
259
428
497
518
9
399
46*
27*
118*
230*
303*
355
444
612
1,063
1,174
1,199
533
1,065
28*
122*
77*
187*
342*
575*
526
696
938
1,545
1,697
1,718
948
1,502
59*
336*
184*
422*
586*
1,136*
883*
1,138*
1,630
2,772
2,966
3,004
2,288
2,811
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water
added in the preparation of food or beverages, was not accounted for in the estimation of bottled
water intake.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-45
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-25. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day)
. Sample , ,
Age . Mean
size 10
Percentile
25
50
75
90
95
99
Birth to <1 month 88 51*
1 to <3 months 143 82*
3 to <6 months 244 141*
6 to <12 months 466 124
1 to <2 years 611 82
2 to <3 years 571 74
3 to <6 years 1,091 62
6to21 years 8,673 282
>65 years 2,287 301
All ages 18,216 237
75*
15
5
92*
146*
211*
173
50
45
38
66
94
105
72
151
186
123
166*
243*
274*
297*
271*
232*
179
386
495
603
432
972
1,248
747
229*
276*
329*
770*
479*
459*
433
659
1,030
1,231
1,154
1,831
1,765
1,480
265*
544*
1,045*
1,078*
867*
935*
883*
1,112*
2,242
2,581
2,474
3,289
2,645
3,095
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-46
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-26. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day)
Age
Sample , ,
. r Mean
size
Percentile
10
25
50
75
90
95
99
Birth to <1 month 88 295* - - 104* 504* 852* 954* 1,043*
1 to <3 months 143 385* - - 169* 732* 1,049* 1,084* 1,265*
3 to <6 months 244 527* - 24* 567* 889* 1,045* 1,192* 1,390*
6 to <12 months 466 461 50 124 379 761 995* 1,126* 1,521*
1 to <2 years 611 370 65 172 297 493 762* 912* 1,414*
2 to <3 years 571 435 88 190 340 585 920* 1,086* 1,447*
3 to <6 years 1,091 498 115 249 432 659 925 1,181 1,787*
6to21 years 8,673 1,700 491 922 1,509 2,257 3,085 3,727 5,252
>65 years 2,287 1,498 566 896 1,359 1,922 2,582 3,063 4,126
All ages 18,216 1,426 281 607 1,201 1,967 2,836 3,412 4,943
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-47
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I
•8
1=
Table 3-27. Per Capita3 Estimates of Combined Direct and Indirect11 Water Ingestion Based on NHANES 2003-2006,
Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/day)
Mean 90th percentile 95th percentile
^c Sample 90% CI 90% BI 90% BI
S1ZC Estimate Lower UPPer Estimate Lower UPPer Estimate Lower UPPer
Bound Bound Bound Bound Bound Bound
Birth to <1 month 88 295* 208* 382* 852* 635* 941* 954* 759* 1,037*
1 to <3 months 143 385* 325* 444* 1,049* 929* 1,074* 1,084* 1,036* 1,099*
3 to <6 months 244 527* 466* 588* 1,045* 1,023* 1,126* 1,190* 1,088* 1,250*
6 to <12 months 466 461 417 506 995* 903* 1,057* 1,126* 1,056* 1,212*
1 to <2 years 611 370 339 401 762* 673* 835* 912* 838* 1,084*
2 to <3 years 571 435 397 472 920* 836* 987* 1,086* 973* 1,235*
3 to <6 years 1,091 498 470 526 925 888 1,009 1,181 1,068 1,250
6to21 years 8,673 1,700 1,641 1,759 3,085 3,027 3,147 3,727 3,586 3,858
>65 years 2,287 1,498 1,442 1,555 2,582 2,470 2,671 3,063 2,961 3,328
All ages 18,216 1,426 1,377 1,474 2,836 2,781 2,896 3,412 3,352 3,499
a Includes all participants whether or not they ingested any water from the source during survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or
beverages. Does not include indirect consumption of bottled water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
CI = Confidence Interval.
BI = Bootstrap Interval.
Source: U.S. EPA analysis of NHANES 2003-2006 data.
n (?
r ^
>§ §
1 §
? Factors Handbook
3 — Water Ingestion
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-28. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/kg-day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 88 52*
1 to <3 months 143 49*
3 to <6 months 244 52*
6 to <12 months 466 34
1 to <2 years 611 20
2 to <3 years 571 19
3 to <6 years 1,091 18
6to21 years 8,673 13
>65 years 2,287 14
All ages 18,216 14
16*
5*
53*
21
12
12
13
9
6
6
5
10
12
9.4
94*
92*
85*
56
28
27
27
20
13
12
13
20
21
19
144*
134*
116*
85*
53*
48*
41
32
23
20
23
32
32
32
169*
164*
132*
103*
67*
61*
51
43
32
28
35
40
40
42
210*
200*
177*
133*
115*
102*
81*
75*
61
44
53
61
59
72
a Includes all participants whether or not they ingested any water from the source during survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-49
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Exposure Factors Handbook
Chapter 3— Ingestion of Water and Other Select Liquids
Table 3-29. Per Capita" Estimates of Combined Directb Water Ingestion Based on NHANES 2003-
2006: Bottled Water (mL/kg-day)
, Sample Tf Percentile
Age . Mean
Slze 10 25 50 75 90
Birth to <1 month 88 1* - - - 1*
1 to <3 months 143 4* - - - - 8*
3 to <6 months 244 2* - - - - 4*
6 to <12 months 466 4 - - - 3 13*
1 to <2 years 611 6 - - - 7 20*
2 to <3 years 571 7 - - - 6 21*
3 to <6 years 1,091 6 - - - 7 19
6to21 years 8,673 5 - - - 7 15
>65 years 2,287 2 - - - 0 7
All ages 18,216 5 - - - 6 15
95
7*
19*
11*
22*
30*
40*
31
24
17
24
24
22
13
22
99
18*
60*
24*
42*
49*
77*
53*
38*
25
42
45
39
29
40
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water
added in the preparation of food or beverages, was not accounted for in the estimation of bottled
water intake.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-50
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-30. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/kg-day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 88 11*
1 to <3 months 143 14*
3 to <6 months 244 20*
6 to <12 months 466 14
1 to <2 years 611 7
2 to <3 years 571 6
3 to <6 years 1,091 3
6to21 years 8,673 4
>65 years 2,287 4
All ages 18,216 4
9*
2
1
22*
30*
29*
18
5
o
J
2
2
2
1
1
2
o
J
2
34*
39*
44*
35*
24*
17*
11
13
9
9
5
12
17
12
45*
49*
60*
74*
43*
34*
22
23
16
19
15
23
23
23
53*
81*
142*
137*
75*
69*
47*
42*
35
32
34
45
37
45
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-51
-------
Exposure Factors Handbook
Chapter 3— Ingestion of Water and Other Select Liquids
Table 3-31. Per Capita" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/kg-day)
. Sample , ,
Age . Mean
size 10
Percentile
25
50
75
90
95
99
Birth to <1 month 88 65* - - 19* 120* 173* 195* 247*
1 to <3 months 143 67* - - 29* 123* 180* 194* 230*
3 to <6 months 244 74* - 4* 72* 116* 153* 179* 228*
6 to <12 months 466 52 6 14 42 84 113* 137* 181*
1 to <2 years 611 33 6 15 26 44 68* 80* 122*
2 to <3 years 571 32 6 15 25 42 67* 78* 123*
3 to <6 years 1,091 27 7 13 23 36 52 63 96*
6to21 years 8,673 22 6 11 19 29 41 50 70
>65 years 2,287 20 7 11 18 26 36 45 61
All ages 18,216 22 5 11 18 29 43 53 84
a Includes all participants whether or not they ingested any water from the source during survey
period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
= Zero.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-52
Exposure Factors Handbook
September 2011
-------
ft
||5
s
a1
1
1
^
^
5?
Table 3-32. Per Capita3 Estimates of Combined Direct and Indirect11 Water Ingestion Based on NHANES 2003-2006,
Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/kg-day)
Mean
A _ Sample 90% CI
Slze „ . Lower Upper
Estimate Bound Bound
Birth to <1 month 88 65* 45* 84*
1 to <3 months 143 67* 55* 78*
3 to <6 months 244 74* 65* 82*
6 to <12 months 466 52 47 57
1 to <2 years 611 33 30 36
2 to <3 years 571 32 29 35
3 to <6 years 1,091 27 25 29
6to21 years 8,673 22 21 23
>65 years 2,287 20 20 21
All ages 18,216 22 21 23
go^percentile
90% BI
Lower Upper
Estimate Bound Bound
173* 128* 195*
180* 152* 193*
153* 140* 178*
113* 105* 124*
68* 62* 73*
67* 59* 72*
52 47 54
42 39 46
33 30 37
33 29 35
36 33 39
41 40 42
36 34 38
43 42 44
95th percentile
90% BI
Lower Upper
Estimate Bound Bound
195* 168* 216*
194* 164* 204*
179* 157* 195*
137* 123* 145*
80* 73* 96*
78* 71* 91*
63 57 68
52 49 55
44 38 53
43 36 45
44 41 47
50 48 51
45 42 46
53 51 54
a Includes all participants whether or not they ingested any water from the source during survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or
beverages. Does not include indirect consumption of bottled water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
CI = Confidence Interval.
BI = Bootstrap Interval.
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Q
I
i1 &
s 43
I
.
§
I
|
I
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-33. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Community Water (mL/day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 51 409* 72* 172* 399* 492* 851* 852* 990*
1 to <3 months 85 531* 103* 341* 513* 745* 957* 1,019* 1,197*
3 to <6 months 192 520* 89* 312* 530* 739* 880* 929* 1,248*
6 to <12 months 416 356 43* 94 270 551 772* 948* 1,161*
1 to <2 years 534 277 36* 88 199 377 627* 781* 1,277*
2 to <3 years 508 321 43* 105 227 448 722* 911* 1,374*
3to<6years 985 382 53 137 316 515 778 999 1,592*
6to21 years 7,616 1,227 192 469 991 1,741 2,546 3,092 4,576
>65 years 1,974 1,288 325 628 1,137 1,760 2,395 2,960 4,137
All ages 15,940 1,033 124 333 743 1,474 2,318 2,881 4,312
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-54
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-34. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Bottled Water (mL/day)
Age
Sample , ,
. r Mean
Percentile
size
10
25
50
75
90
95
99
Birth to <1 month 11 55* 15* 20* 27* 46* 59* 190* 275*
1 to <3 months 28 135* 13* 31* 58* 145* 309* 347* 377*
3 to <6 months 65 69* 10* 15* 35* 84* 156* 202* 479*
6 to <12 months 190 111* 13* 30* 58* 147* 261* 359* 627*
1 to <2 years 247 193* 43* 73* 126* 277* 385* 474* 682*
2 to <3 years 220 276* 38* 74* 155* 333* 681* 1,000* 1,315*
3 to <6 years 430 297 72 118 207 389 615 825* 1,305*
6to21 years 3,836 840 162 281 637 1,137 1,777 2,363 3,665
>65 years 7,442 749 100 178 409 824 1,346 1,940 2,717
All ages 8,070 738 118 237 500 999 1,640 2,133 3,601
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water
added in the preparation of food or beverages, was not accounted for in the estimation of bottled
water intake.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-55
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-35. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: Other Sources (mL/day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 41 121* 25* 59* 112* 166* 234* 246* 269*
1 to <3 months 67 187* 33* 120* 177* 236* 278* 400* 612*
3 to <6 months 160 237* 42* 130* 194* 265* 325* 730* 1,184*
6 to <12 months 287 223* 15* 46* 139* 235* 736* 877* 1,203*
1 to <2 years 312 155 9* 20 47 196 474* 628* 1,047*
2 to <3 years 256 163* 9* 19* 50* 214* 482* 798* 1,070*
3 to <6 years 449 155 9 22 57 178 485 631* 999*
6to21 years 3,555 672 32 80 216 926 1,980 2,774 4,285
>65 years 834 816 64 143 546 1,319 1,923 2,309 3,283*
All ages 7,891 559 22 62 179 689 1,731 2,381 3,798
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Page
3-56
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-36. Consumers-Only" Estimates of Combined Direct and Indirect1" Water Ingestion Based on
NHANES 2003-2006: All Sources (mL/day)
. Sample , ,
Age . Mean
size 10
Percentile
25
50
75
90
95
99
Birth to <1 month 54 481* 74* 217* 473* 658* 921* 996* 1,165*
1 to <3 months 92 665* 103* 457* 704* 1,014* 1,076* 1,099* 1,328*
3 to <6 months 209 660* 55* 379* 685* 965* 1,101* 1,215* 1,450*
6 to <12 months 453 477 64* 152 393 765 1,021* 1,128* 1,526*
1 to <2 years 596 378 78* 173 300 497 772* 914* 1,421*
2 to <3 years 560 441 95* 203 341 589 920* 1,087* 1,450*
3 to <6 years 1,077 506 130 259 437 665 933 1,182 1,787*
6to21 years 8,608 1,712 509 934 1,516 2,258 3,091 3,733 5,253
>65 years 2,281 1,503 573 898 1,361 1,925 2,585 3,066 4,126
All ages 17,860 1,444 304 623 1,218 1,981 2,842 3,422 4,960
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-57
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V S>
I
Table 3-37. Consumers-Only" Estimates of Combined Direct and Indirect11 Water Ingestion Based on NHANES 2003-2006,
Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/day)
Mean
Age
Sample
size
QCrpercentile
95m percentile
90% CI
90% BI
90% BI
Estimate
Lower
Bound
Upper
Bound
Estimate Lower Upper
Bound Bound
Estimate Lower Upper
Bound Bound
Birth to <1 month 54 481* 396* 566* 921* 715* 993* 996* 853* 1,041*
1 to <3 months 92 665* 626* 704* 1,076* 1,030* 1,097* 1,099* 1,073* 1,215*
3 to <6 months 209 660* 596* 724* 1,101* 1,032* 1,189* 1,215* 1,137* 1,256*
6 to <12 months 453 477 432 523 1,021* 906* 1,057* 1,128* 1,057* 1,238*
1 to <2 years 596 378 347 409 772* 674* 838* 914* 837* 1,086*
2 to <3 years 560 441 403 479 920* 837* 994* 1,087* 970* 1,242*
3 to <6 years 1,077 506 479 534 933 898 1,017 1,182 1,078 1,253
6to21 years 8,608 1,712 1,654 1,771 3,091 3,034 3,149 3,733 3,585 3,861
>65 years 2,281 1,503 1,446 1,560 2,585 2,471 2,688 3,066 2,961 3,316
All ages 17,860 1,444 1,395 1,492 2,842 2,796 2,917 3,422 3,363 3,510
CI
BI
Excludes individuals who did not ingest water from the source during the survey period.
Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of
food or beverages. Does not include indirect consumption of bottled water.
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical
Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
1993).
= Confidence Interval.
= Bootstrap Interval.
Source: U.S. EPA analysis of NHANES 2003-2006 data.
3 I1
>§ 1
I,
I
I
I.
I
1=
-------
Exposure Factors Handbook
Chapter 3 — Ingestion of Water and Other Select Liquids
Table 3-38. Consumers-Only" Estimates of Direct and Indirect1" Water Ingestion Based on NHANES
2003-2006: Community Water (mL/kg-day)
Sample „ Percentile
Slze 10 25 50 75 90 95
Birth to <1 month 51 90* 13* 40* 89* 120* 167* 172*
1 to <3 months 85 93* 17* 62* 91* 118* 163* 186*
3 to <6 months 192 73* 10* 45* 74* 100* 128* 140*
6 to <12 months 416 40 5* 10 30 64 87* 104*
lto<2years 534 25 3* 8 17 31 56* 71*
2 to <3 years 508 23 3* 8 16 33 52* 62*
3 to <6 years 985 21 3 8 17 29 43 52
6to21 years 7,616 16 2 6 12 22 34 42
>65 years 1,974 18 4 8 15 23 34 43
All ages 15,940 16 2 6 12 22 35 44
99
228*
210*
191*
135*
117*
108*
83*
78*
62
47
58
64
60
76
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
Page
3-59
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-39. Consumers-Only" Estimates of Directb Water Ingestion Based on NHANES 2003-2006:
Bottled Water (mL/kg-day)
A(rp Sample Mpcm Percentile
Slze 10 25 50 75 90 95
Birth to <1 month 11 12* 3* 6* 7* 8* 17* 38*
1 to <3 months 28 24* 2* 6* 9* 23* 55* 63*
3 to <6 months 65 10* 2* 2* 5* 11* 21* 27*
6 to <12 months 190 12* 2* 4* 7* 16* 29* 36*
1 to <2 years 247 17* 4* 7* 13* 23* 35* 44*
2 to <3 years 220 20* 3* 5* 11* 23* 48* 68*
3 to <6 years 430 16 4 7 11 20 34 47*
6to21 years 3,836 11 2 3 8 14 23 29
>65 years 7,442 11 1 2 6 11 18 28
All ages 8,070 11 2 4 8 14 24 31
99
58*
68*
81*
63*
62*
111*
67*
60*
35
58*
52
51
41
54
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water
added in the preparation of food or beverages, was not accounted for in the estimation of bottled
water intake.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
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Exposure Factors Handbook
Chapter 3 — Ingestion of Water and Other Select Liquids
Table 3-40. Consumers-Only" Estimates of Direct and Indirect1" Water Ingestion Based on NHANES
2003-2006: Other Sources (mL/kg-day)
Sample „ Percentile
Slze 10 25 50 75 90 95
Birth to <1 month 41 26* 4* 13* 26* 33* 47* 51*
1 to <3 months 67 31* 5* 22* 32* 37* 49* 69*
3 to <6 months 160 33* 5* 17* 27* 36* 51* 113*
6 to <12 months 287 25* 2* 5* 16* 28* 69* 98*
1 to <2 years 312 14 1* 2 4 17 43* 54*
2 to <3 years 256 12* 1* 1* 4* 15* 35* 62*
3 to <6 years 449 8 0 1 3 11 24 28*
6to21 years 3,555 9 0 1 3 11 25 35
>65 years 834 11 1 2 7 18 25 33
All ages 7,891 9 0 1 3 11 25 35
99
55*
87*
179*
142*
97*
75*
54*
45*
41
42*
42*
53
42*
55
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-41. Consumers-Only" Estimates of Direct and Indirect1" Water Ingestion Based on NHANES
2003-2006: All Sources (mL/kg-day)
Age
Sample
size
Mean
Percentile
10
25
50
75
90
95
99
Birth to <1 month 54 105* 15* 46* 120* 141* 189* 211* 255*
1 to <3 months 92 115* 18* 71* 119* 160* 193* 201* 241*
3 to <6 months 209 92* 8* 50* 95* 132* 163* 186* 238*
6 to <12 months 453 54 7* 16 44 84 114* 137* 183*
1 to <2 years 596 34 7* 15 26 44 68* 82* 122*
2 to <3 years 560 32 7* 15 25 43 67* 78* 123*
3 to <6 years 1,077 27 7 14 24 37 52 63 96*
6to21 years 8,608 22 6 12 19 29 41 50 70
>65 years 2,281 20 7 12 18 26 36 45 61
All ages 17,860 22 6 11 19 29 43 53 84
a Excludes individuals who did not ingest water from the source during the survey period.
b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water
added in the preparation of food or beverages. Does not include indirect consumption of bottled
water.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
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Table 3-42. Consumer-Only" Estimates of Direct and Indirect11 Water Ingestion Based on NHANES 2003-2006,
Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/kg-day)
Mean
90th percentile
95th percentile
Age
Sample
size
90% CI
90% BI
90% BI
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Birth to <1 month 54 105* 86* 125* 189* 160* 211* 211* 174* 238*
1 to <3 months 92 115* 106* 125* 193* 164* 199* 201* 188* 222*
3 to <6 months 209 92* 84* 101* 163* 143* 179* 186* 171* 201*
6 to <12 months 453 54 49 59 114* 105* 126* 137* 124* 146*
1 to <2 years 596 34 31 37 68* 62* 74* 82* 74* 100*
2 to <3 years 560 32 29 35 67* 60* 72* 78* 72* 92*
3 to <6 years 1,077 27 26 29 52 48 54 63 57 70
6to21 years 8,608 22 21 23 41 40 43 50 48 51
>65 years 2,281 20 20 21 36 34 39 45 42 47
All ages 17,860 22 22 23 43 42 44 53 52 54
CI
BI
Excludes individuals who did not ingest water from the source during the survey period.
Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or
beverages. Does not include indirect consumption of bottled water.
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
= Confidence Interval.
= Bootstrap Interval.
Source: U.S. EPA analysis of NHANES 2003-2006 data.
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-43. Assumed Tap Water Content of Beverages in Great Britain
Beverage
% Tap Water
Cold Water
Home-made Beer/Cider/Lager
Home-made Wine
Other Hot Water Drinks
Ground/Instant Coffee:3
Black
White
Half Milk
All Milk
Tea
Hot Milk
Cocoa/Other Hot Milk Drinks
Water-based Fruit Drink
Fizzy Drinks
Fruit Juice Type lb
Fruit Juice Type 2b
Milk
Mineral Water0
Bought cider/beer/lager
Bought Wine
100
100
100
100
100
80
50
0
80
0
0
75
0
0
75
0
0
0
0
a Black—coffee with all water, milk not added; White—coffee with 80%
water, 20% milk; Half Milk—coffee with 50% water, 50% milk; All Milk-
coffee with all milk, water not added.
b Fruit juice: individuals were asked in the questionnaire if they consumed
ready-made fruit juice (Type 1 above), or the variety that is diluted (Type 2).
0 Information on volume of mineral water consumed was obtained only as
"number of bottles per week." A bottle was estimated at 500 mL, and the
volume was split so that 2/7 was assumed to be consumed on weekends, and
5/7 during the week.
Source: Hopkins and Ellis, 1980.
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Table 3-44.
Beverage
Total Liquid
Total Liquid
Home
Total Liquid
Away
Total Tap Water
Total Tap Water
Home
Total Tap Water
Away
Tea
Coffee
Other Hot
Water Drinks
Cold Water
Fruit Drinks
Non-Tap Water
Home-brew
Bought
Alcoholic
Beverages
Mean
Intake
1.589
1.104
0.484
0.955
0.754
0.201
0.584
0.19
0.011
0.103
0.057
0.427
0.01
0.206
a "Consumers-only"
Source: Hopkins and Ellis,
Intake of Total Liquid, Total Tap Water, and Various Beverages (L/day) by the British Population
Approx. Std.
Error of Mean
0.0203
0.0143
0.0152
0.0129
0.0116
0.0056
0.0122
0.0059
0.0015
0.0049
0.0027
0.0058
0.0017
0.0123
is defined as only those
1980.
All Individuals
Approx. 95%
Confidence
Interval for
Mean
1.547-1.629
1.075-1.133
0.454-0.514
0.929-0.981
0.731-0.777
0.190-0.212
0.560-0.608
0.178-0.202
0.008-0.014
0.093-0.113
0.052-0.062
0.415-0.439
0.007-0.013
0.181-0.231
10 and 90
Percentiles
0.77-2.57
0.49-1.79
0.00-1.15
0.39-1.57
0.26-1.31
0.00-0.49
0.01-1.19
0.00-0.56
0.00-0.00
0.00-0.31
0.00-0.19
0.20-0.70
0.00-0.00
0.00-0.68
individuals who reported consuming
1 and 99
Percentiles
0.34-4.50
0.23-3.10
0.00-2.89
0.10-2.60
0.02-2.30
0.00-0.96
0.00-2.03
0.00-1.27
0.00-0.25
0.00-0.85
0.00-0.49
0.06-1.27
0.00-0.20
0.00-2.33
Consumers-Only"
Percentage of
Total Number of
Individuals
100
100
89.9
99.8
99.4
79.6
90.9
63
9.2
51
46.2
99.8
7
43.5
the beverage during the survey period.
Mean
Intake
1.589
1.104
0.539
0.958
0.759
0.253
0.643
0.302
0.12
0.203
0.123
0.428
0.138
0.474
Approx.
Std. Error of
Mean
0.0203
0.0143
0.0163
0.0129
0.0116
0.0063
0.0125
0.0105
0.0133
0.0083
0.0049
0.0058
0.0209
0.025
Approx. 95%
Confidence
Interval for
Mean
1.547-1.629
1.075-1.133
0.506-0.572
0.932-0.984
0.736-0.782
0.240-0.266
0.618-0.668
0.281-0.323
0.093-0.147
0.186-0.220
0.113-0.133
0.416-0.440
0.096-0.180
0.424-0.524
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Table 3-45. Summary
Beverage
Total Liquid
Intake
Total Tap
Water Intake
Age
Group
(years)
Ito4
5 to 11
12 to 17
18 to 30
31 to 54
>55
Ito4
5 to 11
12 to 17
18 to 30
31 to 54
>55
Source: Hopkins and Ellis,
of Total Liquid and Total Tap
Number
Male
88
249
180
333
512
396
88
249
180
333
512
396
1980.
Female
75
201
169
350
551
454
75
201
169
350
551
454
Mean Intake
Male
0.853
0.986
1.401
2.184
2.112
1.83
0.477
0.55
0.805
1.006
1.201
1.133
Female
0.888
0.902
1.198
1.547
1.601
1.482
0.464
0.533
0.725
0.991
1.091
1.027
Water Intake for Males and Females (L/day) in Great Britain
Approx. Std. Error of
Mean
Male
0.0557
0.0296
0.0619
0.0691
0.0526
0.0498
0.0403
0.0223
0.0372
0.0363
0.0309
0.0347
Female
0.066
0.0306
0.0429
0.0392
0.0215
0.0356
0.0453
0.0239
0.0328
0.0304
0.024
0.0273
Approx 95% Confidence
Interval for Mean
Male
0.742-0.964
0.917-1.045
1.277-1.525
2.046-2.322
2.007-2.217
1.730-1.930
0.396-0.558
0.505-0.595
0.731-0.8790
0.933-1.079
1.139-1.263
1.064-1.202
Female
0.756-1.020
0.841-0.963
1.112-1.284
1.469-1.625
1.558-1.694
1.411-1.553
0.373-0.555
0.485-0.581
0.659-0.791
0.930-1.052
1.043-1.139
0.972-1.082
10 and 90 Percentiles
Male
0.38-1.51
0.54-1.48
0.75-2.27
1.12-3.49
1.15-3.27
1.03-2.77
0.17-0.85
0.22-0.90
0.29-1.35
0.45-1.62
0.64-1.88
0.62-1.72
Female
0.39-1.48
0.51-1.39
0.65-1.74
0.93-2.30
0.95-2.36
0.84-2.17
0.15-0.89
0.22-0.93
0.31-1.16
0.50-1.55
0.62-1.68
0.54-1.57
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-46. Daily Total Tap Water Intake Distribution for Canadians, by Age Group
(Approx. 0.20-L increments, both sexes, combined seasons)
Amount Consumed3
L/day
0.00-0.21
0.22-0.43
0.44-0.65
0.66-0.86
0.87-1.07
1.08-1.29
1.30-1.50
1.51-1.71
1.72-1.93
1.94-2.14
2.15-2.36
2.37-2.57
2.58-2.79
2.80-3.00
3.01-3.21
3.22-3.43
3.44-3.64
3.65-3.86
>3.86
TOTAL
a Includes tap water and
Age Group (years)
5 and Under
%
11.1
17.3
24.8
9.9
11.1
11.1
4.9
6.2
1.2
1.2
1.2
-
-
-
-
-
-
-
-
100.0
foods and beveraj
Number
9
14
20
8
9
9
4
5
1
1
1
0
0
0
0
0
0
0
0
81
*es derived
Source : Canadian Ministry of National Health and Welfare,
6 to 17
18 and Over
% Number %
2.8
10.0
13.2
13.6
14.4
14.8
9.6
6.8
2.4
1.2
4.0
0.4
2.4
2.4
0.4
-
-
-
1.6
100.0
from tap water.
1981.
7
25
33
34
36
37
24
17
6
3
10
1
6
6
1
0
0
0
4
250
0.5
1.9
5.9
8.5
13.1
14.8
15.3
12.1
6.9
5.6
3.4
3.1
2.7
1.4
1.1
0.9
0.8
-
2.0
100.0
Number
3
12
38
54
84
94
98
77
44
36
22
20
17
9
7
6
5
0
13
639
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-47. Average Daily Tap Water Intake of Canadians
(expressed as mL/kg body weight)
Age Group
(years)
<3
3 to 5
6 to 17
18 to 34
35 to 54
>55
Total Population
Source: Canadian
Average Daily Intake (mL/kg)
Females Males
53
49
24
23
25
24
24
Ministry
35
48
27
19
19
21
21
of National Health and
Both Sexes
45
48
26
21
22
22
22
Welfare, 1981.
Table 3-48. Average Daily Total Tap Water Intake of Canadians, by Age and Season
(L/day)a
Age (years)
Average
Summer
Winter
Summer/Winter
90th Percentile
Summer/Winter
a Includes tap water and
<3 3 to 5
0.57 0.86
0.66 0.88
0.61 0.87
1.5 1.5
6 to 17
1.14
1.13
1.14
2.21
foods and beverages derived from
18 to 34 35 to 54 >55
1.33 1.52 1.53
1.42 1.59 1.62
1.38 1.55 1.57
2.57 2.57 2.29
tap water.
All Ages
1.31
1.37
1.34
2.36
Source: Canadian Ministry of National Health and Welfare, 1981.
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-49. Average Daily Total Tap Water Intake of Canadians as a Function of
Level of Physical Activity at Work and in Spare Time
(16 years and older, combined seasons, L/day)
Work Spare Time
Activity Consumption13 Number of Respondents Consumption13 Number of Respondents
Level3 L/day L/day
Extremely Active 1.72 99 1.57 52
Very Active 1.47 244 1.51 151
Somewhat Active 1.47 217 1.44 302
Not Very Active 1.27 67 1.52 131
Not At All Active 1.3 16 1.35 26
Did Not State 1.3 45 1.31 26
TOTAL 688 688
a The levels of physical activity listed here were not defined any further by the survey report, and
categorization of activity level by survey participants is assumed to be subjective.
b Includes tap water and foods and beverages derived from tap water.
Source: Canadian Ministry of National Health and Welfare, 1981.
Table 3-50. Average Daily
Tap Water Intake by Canadians, Apportioned Among Various Beverages
(Both sexes, by age, combined seasons, L/day)a
Age Group (years)
Total Number in Group
Water
Ice/Mix
Tea
Coffee
"Other Type of Drink"
Reconstituted Milk
Soup
Homemade Beer/Wine
Homemade Popsicles
Baby Formula, etc.
TOTAL
a Includes tap water and
* Less than 0.01 L/day.
<3
34
0.14
0.01
*
0.01
0.21
0.1
0.04
*
0.01
0.09
0.61
foods and beveraj
3 to 5
47
0.31
0.01
0.01
*
0.34
0.08
0.08
*
0.03
*
0.86
*es derived
Source : Canadian Ministry of National Health and Welfare,
6 to 17
250
0.42
0.02
0.05
0.06
0.34
0.12
0.07
0.02
0.03
*
1.14
from tap water.
1981.
18 to 34
232
0.39
0.04
0.21
0.37
0.2
0.05
0.06
0.04
0.01
*
1.38
35 to 54
254
0.38
0.03
0.31
0.5
0.14
0.04
0.08
0.07
*
*
1.55
>55
153
0.38
0.02
0.42
0.42
0.11
0.08
0.11
0.03
*
*
1.57
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-51. Intake Rates of Total Fluids and Total Tap Water by
Age Group
Average Daily Consumption Rate (L/day)
Age Group Total Fluids3 Total Tap Waterb
6 to 11 months
2 years
14 to 16 years
25 to 30 years
60 to 65 years
0.80
0.99
1.47
1.76
1.63
0.20
0.50
0.72
1.04
1.26
a Includes milk, "ready-to-use" formula, milk-based soup,
carbonated soda, alcoholic beverages, canned juices, water,
coffee, tea, reconstituted juices, and reconstituted soups. Does
not include reconstituted infant formula.
b Includes water, coffee, tea, reconstituted juices, and
reconstituted soups.
Source:DerivedfromPennington, 1983.
Table 3-52. Mean and Standard Error for the Daily Intake of Beverages and Tap Water by Age
Age
All ages
<1
Ito4
5 to 9
10 to
15 to
20 to
25 to
30 to
40 to
>60
a
b
14
19
24
29
39
59
Source:
(years) Tap Water Intake
(mL)
662.5 ± 9.9
170.7 ±64.5
434.6 ±31.4
521.0 ±26.4
620.2 ± 24.7
664.7 ± 26.0
656.4 ±33.9
619.8 ±34.6
636.5 ±27.2
735.3 ±21.1
762.5 ±23.7
Includes water-based drinks such as coffee
included in this group.
Includes tap water and water-based drinks
fruitades, and alcoholic drinks.
U.S. EPA, 1984.
Water-Based
Drinks (mL)a
457.1 ±6.7
8.3 ±43.7
97.9 ±21.5
116
5
140.0
201.5
343.1
441.6
601
686
561
0
5
1
±18.0
±16.9
±17.7
±23.1
±23.6
±18.6
±14.4
±16.2
Soups Total Beverage Intakeb
(mL) (mL)
45.9
10.1
43.8
36.6
35.4
34.8
38.9
41.3
40.6
51.6
59.4
±
±
±
±
±
±
±
±
±
±
±
1.2
7.9
3.9
3.2
3.0
3.2
4.2
4.2
3.3
2.6
2.9
, etc. Reconstituted infant formula does not
such as coffee, tea, soups, and other drinks
1,434.0 ±13.7
307.0 ± 89.2
743.0 ±43.5
861.0 ±36.5
,025.0 ±34.2
,241.0 ±35.9
,484.0 ± 46.9
,531.0 ±48.0
,642.0 ± 37.7
,732.0 ±29.3
,547.0 ±32.8
appear to be
such as soft drinks,
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-53. Average
Sex, Age,
Total Tap Water Intake Rate by
and Geographic Area
„ ,„ , Number of
Group/Subgroup „ , .
Respondents
Total group
Sex
Males
Females
Age, years
21 to 44
45 to 64
65 to 84
Geographic area
Atlanta
Connecticut
Detroit
Iowa
New Jersey
New Mexico
New Orleans
San Francisco
Seattle
Utah
5,258
3,892
1,366
291
1,991
2,976
207
844
429
743
1,542
165
112
621
316
279
a Standard deviations not reported
(1987).
Average Total
Tap Water
Intake,a'b
T IAn
L/day
1.39
1.40
1.35
1.30
1.48
1.33
1.39
1.37
1.33
1.61
1.27
1.49
1.61
1.36
1.44
1.35
in Cantor et al.
b Total tap water defined as all water and
beverages derived from tap water.
Source: Cantor etal.,
1987.
Table 3-54. Frequency Distribution of Total
Tap Water Intake
Rates3
Consumption _ b /n/^ Cumulative
n „ /T ,j •, Frequency (%) „ b ,n/^
Rate (L/day) ^ J v ' Frequency (%)
<0.80 20.6
0 81 1 12 21 3
1.13-1.44 20.5
1.45-1.95 19.5
>1.96 18.1
20.6
41.9
62.4
81.9
100.0
a Represents consumption of tap water and
beverages derived from tap water in a
"typical" winter week.
b Extracted from Table 3 in the article by
Cantor etal. (1987).
Source: Cantor etal., 1987.
Exposure Factors Handbook
September 2011
Page
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Table 3-55.
A , \ Number of ,,
Age (years) _, , . Mean
Observations
<0.5 182
0.5 to 0.9 221
Ito3 1,498
4 to 6 1,702
7 to 10 2,405
11 to 14 2,803
15 to 19 2,998
20 to 44 7,171
45 to 64 4,560
65 to 74 1,663
>75 878
Infants (ages <1) 403
Children (ages 1 to 10) 5,605
Teens (ages 11 to 19) 5,801
Adults (ages 20 to 64) 11 ,73 1
Adults (ages >65) 2,541
All 26,081
272
328
646
742
787
925
999
1,255
1,546
1,500
1,381
302
736
965
1,366
1,459
1,193
Total Tap Water Intake (mL/day) for
SD
247
265
390
406
417
521
593
709
723
660
600
258
410
562
728
643
702
SE of Mean
18
18
10
10
9
10
11
8
11
16
20
13
5
7
7
13
4
1
*
*
33
68
68
76
55
105
335
301
279
0
56
67
148
299
80
a Total tap water is defined as "all water from the household tap consumed directly
* Value not reported due to insufficient number of observations.
SD = Standard deviation.
SE = Standard error.
Source: Ershow and Cantor, 1989.
Both Sexes Combined"
Percentile Distribution
5
0
0
169
204
241
244
239
337
591
611
568
0
192
240
416
598
286
10
0
0
240
303
318
360
348
483
745
766
728
0
286
353
559
751
423
25
80
117
374
459
484
561
587
766
1,057
1,044
961
113
442
574
870
1,019
690
50
240
268
567
660
731
838
897
1,144
1,439
1,394
1,302
240
665
867
1,252
1,367
1,081
75
332
480
820
972
1,016
1,196
1,294
1,610
1,898
1,873
1,706
424
960
1,246
1,737
1,806
1,561
90
640
688
1,162
1,302
1,338
1,621
1,763
2,121
2,451
2,333
2,170
649
1,294
1,701
2,268
2,287
2,092
95 99
800 *
764 *
1,419 1,899
1,520 1,932
1,556 1,998
1,924 2,503
2,134 2,871
2,559 3,634
2,870 3,994
2,693 3,479
2,476 3,087
775 1,102
1,516 1,954
2,026 2,748
2,707 3,780
2,636 3,338
2,477 3,415
as a beverage or used to prepare foods and beverages. "
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Table 3-56. Total Tap Water Intake (mL/kg-day)
Number of
Observations
Actual Weighted
Age (years) Count Count Mean
<0.5 182 201.2 52.4
0.5 to 0.9 221 243.2 36.2
Ito3 1,498 1,687.7 46.8
4 to 6 1,702 1,923.9 37.9
7 to 10 2,405 2,742.4 26.9
11 to 14 2,803 3,146.9 20.2
15 to 19 2,998 3,677.9 16.4
20 to 44 7,171 13,444.5 18.6
45 to 64 4,560 8,300.4 22
65 to 74 1,663 2,740.2 21.9
>75 878 1,401.8 21.6
Infants (ages <1) 403 444.3 43.5
Children (ages 1 to 10) 5,605 6,354.1 35.5
Teens (ages 11 to 19) 5,801 6,824.9 18.2
Adults (ages 20 to 64) 11,731 21,744.9 19.9
Adults (ages >65) 2,541 4,142.0 21.8
All 26,081 39,510.2 22.6
for Both
Sexes Combined"
Percentile Distribution
SD
53.2
29.2
28.1
21.8
15.3
11.6
9.6
10.7
10.8
9.9
9.5
42.5
22.9
10.8
10.8
9.8
15.4
SEof
Mean
3.9
2
0.7
0.5
0.3
0.2
0.2
0.1
0.2
0.2
0.3
2.1
0.3
0.1
0.1
0.2
0.1
1
*
*
2.7
3.4
2.2
1.5
1
1.6
4.4
4.6
3.8
0
2.7
1.2
2.2
4.5
1.7
a Total tap water is defined as "all water from the household tap consumed directly
* Value not reported due to insufficient number of observations.
SD = Standard deviation.
SE = Standard error.
Source: Ershow and Cantor, 1989.
5
0
0
11.8
10.3
7.4
4.9
3.9
4.9
8
8.7
8.8
0
8.3
4.3
5.9
8.7
5.8
10
0
0
17.8
14.9
10.3
7.5
5.7
7.1
10.3
10.9
10.7
0
12.5
6.5
8.0
10.9
8.2
25
14.8
15.3
27.2
21.9
16
11.9
9.6
11.2
14.7
15.1
15
15.3
19.6
10.6
12.4
15.0
13.0
50
37.8
32.2
41.4
33.3
24
18.1
14.8
16.8
20.2
20.2
20.5
35.3
30.5
16.3
18.2
20.3
19.4
75
66.1
48.1
60.4
48.7
35.5
26.2
21.5
23.7
27.2
27.2
27.1
54.7
46.0
23.6
25.3
27.1
28.0
90
128.3
69.4
82.1
69.3
47.3
35.7
29
32.2
35.5
35.2
33.9
101.8
64.4
32.3
33.7
34.7
39.8
95
155.6
102.9
101.6
81.1
55.2
41.9
35
38.4
42.1
40.6
38.6
126.5
79.4
38.9
40.0
40.0
50.0
99
*
*
140.6
103.4
70.5
55
46.3
53.4
57.8
51.6
47.2
220.5
113.9
52.6
54.8
51.3
79.8
as a beverage or used to prepare foods and beverages. "
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-57. Summary of Tap Water
Age Gioup
Infants (<1 year)
Children (1 to 10 years)
Teens (11 to 19 years)
Adults (20 to 64 years)
Adults (>65 years)
All ages
Source: Ershow and Cantor,
Mean
302
736
965
1,366
1,459
1,193
1989.
Intake (mL/day)
10th_90th Percentiles
0-649
286-1,294
353-1,701
559-2,268
751-2,287
423-2,092
Intake by Age
Intake
(mL/kg-day)
Mean 10^-90^ Percentiles
43.5
35.5
18.2
19.9
21.8
22.6
0-100
12.5-64.4
6.5-32.3
8.0-33.7
10.9-34.7
8.2-39.8
Table 3-58. Total Tap Water Intake (as % of total water intake) by Broad Age Category"
Age
<1
Ito 10
11 to 19
20 to 64
>65
a
b
0
Source:
(years)
Mean
26
45
47
59
65
b
Percentile Distribution
1
0
6
6
12
25
5 10 25 50
0 0 12 22
19 24 34 45
18 24 35 47
27 35 49 61
41 47 58 67
75
37
57
59
72
74
Does not include pregnant women, lactating women, or breast-fed children.
Total tap water is defined as "all water from the household tap consumed directly
prepare foods and beverages."
= Less than 0.5%.
Ershow
and Cantor, 1989.
90
55
67
69
79
81
95
62
72
74
83
84
as a beverage
99
82
81
83
90
90
or used to
Page
3-74
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-59.
General
Dietary Sources of Tap Water for Both Sexesa'b
% of Tap Water
Age
(years)
<1
Ito 10
11 to 19
20 to 64
>65
All
a
b
c
0
Source:
„ Standard
Source , , „ . ..
Mean Deviation
Foodc
Drinking Water
Other Beverages
All Sources
Foodc
Drinking Water
Other Beverages
All Sources
Foodc
Drinking Water
Other Beverages
All Sources
Foodc
Drinking Water
Other Beverages
All Sources
Foodc
Drinking Water
Other Beverages
All Sources
Foodc
Drinking Water
Other Beverages
All Sources
11
69
20
100
15
65
20
100
13
65
22
100
8
47
45
100
8
50
42
100
10
54
36
100
24
37
33
16
25
21
15
25
23
10
26
26
9
23
23
13
27
27
Does not include pregnant women, lactatinj
Individual values may not add to
Food category includes
= Less than 0.5%.
soups.
totals due
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
25
0
39
0
5
52
0
3
52
0
2
29
25
2
36
27
2
36
14
I women, or breast-fed
to rounding.
50
0
87
0
10
70
15
8
70
16
5
48
44
5
52
40
6
56
34
children.
75
10
100
22
19
84
32
17
85
34
11
67
63
11
66
57
13
75
55
95
70
100
100
44
96
63
38
98
68
25
91
91
23
87
85
31
95
87
99
100
100
100
100
100
93
100
100
96
49
100
100
38
99
100
64
100
100
Ershow and Cantor, 1989.
Exposure Factors Handbook
September 2011
Page
3-75
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-60. Summary Statistics
Group
(Age in Years)
<1
1 to <1 1
1 1 to <20
20 to <65
>65
All ages
Simulated balanced population
Group
(Age in Years)
<1
1 to <1 1
1 1 to <20
20 to <65
>65
All ages
Simulated balanced population
for Best-Fit Lognormal Distributions for Water Intake
Rates3
In Total
H
6.979
7.182
7.490
7.563
7.583
7.487
7.492
In Total
^
5.587
6.429
6.667
7.023
7.088
6.870
6.864
Fluid Intake Rate
a
0.291
0.340
0.347
0.400
0.360
0.405
0.407
Fluid Intake Rate
a
0.615
0.498
0.535
0.489
0.476
0.530
0.575
These values (mL/day) were used in the following equations to estimate the
averages for total tap water intake shown in Table 3-61.
97.5 percentile intake rate = exp [u + (1.96 x a)]
75 percentile intake rate = exp [^ + (0.6745 x a)]
50 percentile intake rate = exp [u]
25 percentile intake rate = exp [\i - (0.6745 x a)]
2.5 percentile intake rate = exp [^ - (1.96 x a)]
Mean intake rate - exp [u + 0.5 x a2)]
Source: Roseberry and Burmaster,
1992.
R2
0.996
0.953
0.966
0.977
0.988
0.984
1.000
R2
0.970
0.984
0.986
0.956
0.978
0.978
0.995
quantiles and
Table 3-61. Estimated Quantiles and Means for Total Tap Water Intake Rates (mL/day)a
Age Group
(years)
<1
1 to <1 1
1 1 to <20
20 to <65
> 65
All ages
Simulated Balanced Population
a Total tap water is defined as
prepare foods and beverages
2.5
80
233
275
430
471
341
310
"all
25
176
443
548
807
869
674
649
water from the
Percentile
50
267
620
786
1,122
1,198
963
957
75
404
867
1,128
1,561
1,651
1,377
1,411
household tap consumed directly
97.5
891
1,644
2,243
2,926
3,044
2,721
2,954
as a beveraj
Arithmetic
Average
323
701
907
1,265
1,341
1,108
1,129
ie or used to
Source: Roseberry and Burmaster, 1992.
Page
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Exposure Factors Handbook
September 2011
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Table 3-62 . Water Ingested (mL/day)a from Water by Itself and Water Added to Other Beverages
Category
Water by Itself Range
Per capita meanb ± SD
Consumer-only mean0
Percent consuming
Water Added to Formula- Range
Powdered Concentrate Per capita mean ± SD
Consumer-only mean
Percent consuming
Liquid Concentrate Range
Per capita mean ± SD
Consumer-only mean
Percent consuming
All Concentrated Formula Range
Per capita mean ± SD
Consumer-only mean
Percent consuming
Water Added to Juices Range
and Other Beverages Per capita mean ± SD
Consumer-only mean
Percent consuming
Water Added to Powdered Range
Baby Foods and Cereals Per capita mean ± SD
Consumer-only mean
Percent consuming
Water Added to Other Foods Range
(Soups, Jell-o, Puddings) Per capita mean ± SD
Consumer-only mean
Percent consuming
ALL SOURCES OF WATER Range
Per capita mean ± SD
Consumer-only mean
Percent consuming
6 Weeks
(N= 124)
0-355
30 ±89
89
28
0-1,242
177 ±296
473
39
0-621
89 ± 148
355
23
0-1,242
266 ± 296
444
60
0-118
<30 ± 30
89
3
0-30
<30 ± 30
30
2
0
0-1,242
296 ±325
414
68
3 Months
(A? =120)
0-355
30 ±59
89
24
0-1,242
266 ±384
621
42
0-680
237 ± 207
384
30
0-1,242
384±355
562
68
0-710
30 ±89
207
9
0-177
<30 ± 30
59
17
0-118
30 ±30
89
2
0-1,419
414±414
562
77
6 Months
(A? =99)
0-266
30 ±59
118
42
0-1,124
266 ±355
562
48
0-710
148 ± 207
414
35
0-1,123
414±325
532
81
0-473
30 ±89
148
18
0-266
59 ±59
89
64
0-118
<30 ± 30
59
8
0-1,123
473 ± 325
503
94
and Foods
9 Months
(JV=77)
0-473
89 ±89
118
66
0-1,064
207 ± 325
562
36
0-532
59 ± 148
325
21
0-1,064
266 ± 296
503
56
0-887
59 ± 148
207
32
0-177
30 ±59
89
43
0-355
30 ±59
118
29
0-1,745
444 ±355
473
97
a Converted from ounces/day; 1 fluid ounce = 29.57 mL.
b Mean intake among entire sample.
c Mean intake for only those ingesting water from the particular category.
d Percentage of infants receiving water from that individual source.
N = Number of observations.
SD = Standard Deviation.
Indicates there is insufficient sample size to estimate means.
Source: Levy et al., 1995.
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-63. Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data from 1989-1991
(mL/day)
Sex and Age Plain Drinking „ „.
/ \ TT7 j V^O-LLCC
(years) Water
Males and Females:
<1
Ito2
3 to 5
<5
Males:
6 to 11
12 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
70 to 79
>80
>20
Females:
6 to 11
12 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
70 to 79
>80
>20
All individuals
194
333
409
359
537
725
842
793
745
755
946
824
747
809
476
604
739
732
781
819
829
112
856
774
711
a Includes regular and low calorie
and frozen concentrate.
Source: USDA, 1995.
0
0.5
2
1
2
12
168
407
534
551
506
430
326
408
1
21
154
317
412
438
429
324
275
327
260
fruit drinks, punches,
Tea
0.5
9
26
17
44
95
136
136
149
168
115
115
165
139
40
87
120
136
174
137
124
161
149
141
114
Fruit Drinks
and Adesa
17
85
100
86
114
104
101
50
53
51
34
45
57
60
86
87
61
59
36
37
36
34
28
46
65
and ades, including those made
Total
211.5
427.5
537
463
697
936
,247
,386
,481
,525
,601
,414
,295
,416
603
799
,074
,244
,403
,431
,418
,291
,308
,288
1,150
from powdered mix
Excludes fruit juices and carbonated drinks.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-64. Number of Respondents That
Population Group
Overall
Sex
Male
Female
Refused
Age (years)
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full-time
Part-time
Not Employed
Refused
Education
-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-65. Number of Respondents That Consumed Juice Reconstituted with Tap Water at a
Daily Frequency
Population Group
Overall
Sex
Male
Female
Refused
Age (years)
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full-time
Part-time
Not Employed
Refused
Education
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Table 3-66. Mean and (standard
error) Water and Drink Consumption (mL/kg-day) by Race/Ethnicity
Race/Ethnic N Plain M^il^ld Reconstituted RTF
Group Tap Water _. . , Formula Formula
v v Drinks
Black non- 121 21
Hispanic (1.7)
White non- 620 13
Hispanic (0.8)
Hispanic 146 15
(1.2)
Other 59 21
(2.4)
24
(4.6)
23
(1.2)
23
(2.4)
19
(3.7)
a Totals may be slightly different from the
TV = Number of observations.
RTF = Ready -to-feed.
Note: Standard Error shown in parentheses.
Source: Heller etal., 2000.
35
(6.0)
29
(2.7)
38
(7.3)
31
(9.1)
sums of all
4
(2.0)
8
(1.5)
12
(4.0)
19
(11.2)
categories due
„ , Juices and
Baby „ , „ ,
„ , Carbonated
Food „ . .
Drinks
8 2
(1.6) (0.7)
10 1
(1.2) (0.2)
10 1
(1.4) (0.3)
7 1
(4.0) (0.5)
to rounding.
Non-
Carbonated
Drinks
14
(1.3)
11
(0.7)
10
(1.6)
8
(2.0)
Other
21
(1.7)
18
(0.8)
16
(1.4)
19
(3.2)
Total3
129
(5.7)
113
(2.6)
123
(5.2)
124
(10.6)
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-67. Plain Tap Water and Total Water Consumption
by Age, Sex, Region, Urbanicity, and
Poverty Category
Plain Tap Water
Variable
Age
<12 months
12 to 24 months
Sex
Male
Female
Region
Northeast
Midwest
South
West
Urbanicity
Urban
Suburban
Rural
Poverty category3
0-1.30
1.31-3.50
>3.50
Total
a Poverty category
times the federal
N
296
650
475
471
175
197
352
222
305
446
195
289
424
233
946
represents family's
poverty level.
(mL/kg-day)
Mean
11
18
15
15
13
14
15
17
16
13
15
19
14
12
15
SE
1.0
0.8
1.0
0.8
1.4
1.0
1.3
1.1
1.5
0.9
1.2
1.5
1.0
1.3
0.6
annual incomes of 0-1 .30
Total Water
(mL/kg-day)
Mean SE
130
108
116
119
121
120
113
119
123
117
109
128
117
109
118
1.31-3.50, and
4.6
1.7
4.1
3.2
6.3
3.1
3.7
4.6
3.5
3.1
3.9
2.6
4.2
3.5
2.3
greater than 3. 50
TV = Number of observations.
SE = Standard Error
Source: Heller et al., 2000.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-68. Intake of Water from Various Sources in 2- to 13-Year-Old Participants of the DONALD
Study, 1985-1999
Water Intake from
Boys and girls Boys and girls
2 to 3 years 4 to 8 years
/V=858b jV=l,795b
Boys
9 to 13 years
/V=541b
Girls
9 to 13 years
N=542b
Mean
Water in Food (mL/day)a
Beverages (mL/day)a
Milk (mL/day)a
Mineral water (mL/day)a
Tap water (mL/day)a
Juice (mL/day)a
Soft drinks (mL/day)a
Coffee/tea (mL/day)a
Total water intakea>d (mL/day)
Total water intakea'd (mL/kg-day)
Total water intakea'd (mL/kcal-day)
365 (33)c
614 (55)
191 (17)
130(12)
45(4)
114(10)
57(5)
77(7)
1,114 ±289
78 ±22
1.1±0.3
487 (36)
693 (51)
177 (13)
179 (13)
36(3)
122 (0)
111 (8)
69(5)
Mean±
1,363 ±333
61 ±13
0.9 ±0.2
673 (36)
969(51)
203 (11)
282 (15)
62(3)
133 (7)
203 (11)
87(4)
SD
1,891 ±428
49 ±11
1.0 ±0.2
634 (38)
823 (49)
144 (9)
242 (15)
56(3)
138 (8)
155 (9)
87(5)
1,676 ±386
43 ±10
1.0 ±0.2
a Converted from g/day, g/kg-day, or g/kcal-day; 1 g = 1 mL.
b N = Number of records.
0 Percent of total water shown in parentheses.
d Total water = water in food + beverages + oxidation.
SD = Standard deviation.
Source: Sichert-Hellert et al., 2001
Table 3-69. Mean (±standard error) Fluid Intake (mL/kg-day) by Children Aged 1 to 10 Years,
NHANES III, 1988-1994
Total fluid
Plain water
Milk
Carbonated drinks
Juice
Total Sample
(TV =7,925)
84 ± 1.0
27 ±0.8
18 ±0.3
6 ±0.2
12 ±0.3
Sample with
Temperature Information
(TV =3, 869)
84 ±1.0
27 ±1.0
18 ±0.6
5 ±0.3
11 ±0.6
Sample without
Temperature Information
(TV =4,056)
85 ±1.4
26 ±1.1
18 ±0.4
6 ±0.3
12 ±0.4
TV = Number of observations.
Source: Sohnetal., 2001.
Exposure Factors Handbook
September 2011
Page
3-83
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-70. Estimated Mean (±standard error) Amount of Total Fluid and Plain Water Intake
Among Children" Aged 1 to 10 Years by Age, Sex, Race/Ethnicity, Poverty Income Ratio, Region,
and Urbanicity (NHANES III, 1988-1994)
Total Fluid
Plain Water
mL/day
mL/kg-day
mL/day
mL/kg-day
Age (years)
1
2
3
4
5
6
7
9
10
578
579
502
511
465
255
235
247
254
243
1,393 ±31
1,446 ±31
1,548 ±75
1,601 ±41
1,670 ±54
1,855 ±125
1,808 ±66
1,792 ±37
2,113±78
2,051 ±97
124 ±2.9
107 ±2.3
100 ±4.6
91 ±2.8
84 ±2.3
81 ±4.9
71 ±2.3
61 ±1.8
65 ±2.1
58 ±2.4
298 ±19
430 ±26
482 ± 27
517±23
525 ± 36
718±118
674 ± 46
626 ± 37
878 ± 59
867 ± 74
26±1.8
32±1.9
31 ±1.8
29±1.3
26 ±1.7
31 ±4.7
26±1.9
21 ±1.2
26 ±1.4
24 ±2.0
Sex
Male
Female
Race/ethnicity
White
Black
Mexican American
Other
Poverty/income ratiob
Low
Medium
High
Regionc'd
Northeast
Midwest
South
West
Urban/rural11
Urban
Rural
Total
1,974
1,895
736
1,122
1,728
283
1,868
1,204
379
679
699
869
1,622
3,358
511
3,869
1,802 ±30
1,664 ±24
1,653 ±26
1,859 ±42
1,817±25
1,813 ±47
1,828 ±32
1,690 ±31
1,668 ±54
1,735 ±31
1,734 ±45
1,739 ±31
737 ± 25
1,736 ±18
1,737 ±19
1,737 ±15
86 ±1.8
81 ±1.5
79 ±1.8
88±1.8
89 ±1.7
90 ± 4.2
93 ±2.6
80 ±1.6
76 ±2.5
87 ±2.3
84 ±1.5
83 ±2.2
81 ±1.7
84 ±1.0
84 ±4. 3
84±1.1
636 ± 32
579 ± 26
552 ± 34
795 ± 36
633 ±23
565 ±39
662 ± 27
604 ± 35
533±41
568 ± 52
640 ± 54
613 ±24
624 ± 44
609 ±29
608 ± 20
609 ± 24
29 ±1.3
26 ±1.0
24 ±0.3
36±1.5
29 ±1.1
26 ±1.7
32±1.3
26 ±1.4
22 ±1.7
26 ±2.1
29 ±1.8
28±1.3
27±1.9
27±1.1
28 ±1.2
27 ±1.0
Children for whom temperature data were obtained.
Based on ratio of household income to federal poverty threshold. Low: <1.300; medium: 1.301-3.500;
high: >3.501.
All variables except for Region and Urban/rural showed statistically significant differences for both total
fluid and plain water intake by Bonferroni multiple comparison method.
Northeast = Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania,
Rhode Island, Vermont;
Midwest = Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio,
South Dakota, Wisconsin;
South = Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana,
Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West
Virginia;
West = Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon,
Utah, Washington, Wyoming.
= Number of observations.
Source: Sohnet al, 2001.
Page
3-84
Exposure Factors Handbook
September 2011
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I!
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Table 3-71. Tap Water Intake in Breast-Fed and Formula-Fed Infants and Mixed-Fed
Tap Water Intakeb (mL/day)
Age Na Total
Mean SD Median p95 Max
Breast-fed
1 year, total 300 130 180 50 525 1,172
3 months 111 67 167 0 493 746
6 months 124 136 150 68 479 634
9 months 47 254 218 207 656 1,172
12 months 18 144 170 85 649 649
Formula-fed
1 year, total 758 441 244 440 828 1,603
3 months 78 662 154 673 874 994
6 months 141 500 178 519 757 888
9 months 242 434 236 406 839 1,579
12 months 297 360 256 335 789 1,603
Mixed-fed
1 to 3 years, total 904 241 243 175 676 2,441
18 months 277 280 264 205 828 1,881
24 months 292 232 263 158 630 2,441
36 months 335 217 199 164 578 1,544
Young Children at
Different Age Points
Tap Water Intakeb (mL/kg-day)
Mean
17
10
18
30
15
53
107
63
49
37
19
25
18
14
a Numbers of 3-day diet records.
SD
24**
25**
20**
27**
18**
33
23
23
27
26
20
23
21
13
Total
Median p95
6
0
8
23
9
49
107
65
45
32
14
18
12
11
65
74
5' 8
77
66
115
147
99
94
83
56
70
49
36
Max
150
125
85
150
66
200
159
109
200
175
203
183
203
103
From Household0 From Manufacturingd
%e Mean SD %f Mean SD %f
17 15
10 10
18 14
28 26
19 13
51 49
93 103
64 59
50 44
39 33
24 15
28 22
23 15
22 9
b Total tap water = tap water from the household and tap water from food manufacturing. Converted from g/day
0 Tap water from household = tap water from the household tap consumed directly
23**
25**
19**
27**
18**
33
28
25
27
25
20
23
21
12
85
97
79
87
86
92
97
92
91
91
78
88
80
66
and g/kg-day; 1 {
as a beverage or used to prepare foods
2.4 4.7**
0.3
3.8
3.7
2.2
4.0
3.4
4.8
4.5
3.3
3.9
3.0
3.7
4.9
l=\ mL
1.9**
6.3*
3.4
2.1
8.0
17.9
8.0
6.3
3.7
5.5
4.1
5.0
6.6
15
3
21
13
14
8
3
8
9
9
22
12
20
34
and beverages.
d Tap water from food = manufacturing tap water from the industrial food production used for the preparation of foods (bread, butter/margarine,
fruit, vegetables and legumes, ready to serve meals, commercial
e Mean as a percentage of total water.
f Mean as a percentage of total tap water.
* Significantly different from formula-fed infants,/) < 0.05.
** Significantly different from formula-fed infants, p< 0.0001.
SD = Standard Deviation.
p95 = 95th percentile.
Source: Hilbig et al, 2002.
weaning
tinned
food) and mixed beverages (lemonade, soft drinks).
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Table 3-72. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day) for Children with
Returned Questionnaires
Age at Questionnaire 6 Months 9 Months 12 Months 16 Months
Actual Age (Months) 6.29 ±0.35 9.28 ±0.35 12.36 ±0.46 16.31 ±0.49
A/6 677 681 659 641
Human Milk11 30 19 11 5
Infant Formula'
%A 68 69 29 4
mL/da/ 798 ± 234 615 ±328 160 ±275 12 ±77
Cows' Milke
%A 5 25 79 91
mL/da/ 30 ±145 136 ±278 470 ±310 467 ±251
Formula and Cows' Milke
%d 70 81 88 92
mL/da/ 828 ±186 751 ±213 630 ± 245 479 ± 248
Juice and Juice Drinks
%A 55 73 89 94
mL/da/ 65 ± 95 103 ±112 169 ±151 228 ± 166
Water
"/o11 36 59 75 87
mL/da/ 27 ±47 53 ± 71 92 ±109 124 ±118
Other Beverages'
%A 1 9 23 42
mL/da/ 3 ±18 6 ± 27 27 ±71 53 ± 109
Total Beverages mL/daye'fJ 934 ±219 917 ±245 926 ± 293 887 ±310
20 Months
20.46 ±0.57
632
3
2
9 ±83
93
402 ± 237
94
411 ±237
95
269 ± 189
90
142 ± 127
62
83 ± 121
908 ±310
24 Months
24.41 ±0.53
605
0
0
97
358 ±225
98
358 ±228
93
228 ± 172
94
145 ± 148
86
89 ± 133
819 ±299
6 to 24 Months8
585C
-
678
207 ± 112
678
355 ± 163
678
562 ± 154
99h
183 ± 103
99h
109 ± 74
80h
44 ±59
920 ± 207
a Cumulative number of children and percentage of children consuming beverage and beverage intakes for the 6- through 24-month period.
b Number of children with returned questionnaires at each time period.
c Number of children with cumulative intakes for 6- through 24-month period.
11 Percentage of children consuming beverage.
e Children are not included when consuming human milk.
f Mean standard deviation of beverage intake. Converted from ounces/day; 1 fluid ounce = 29.57 mL.
8 Percentage of children consuming beverage during 6- through 24-month period. Children who consumed human milk are not included.
h Percentage of children consuming beverage during 6- through 24-month period.
' Other beverages include non-juice beverages (e.g., carbonated beverages, Kool-Aid).
' Total beverages includes all beverages except human milk.
Indicates there are insufficient data.
Source: Marshall et al., 2003a.
s
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Table 3-73. Mean (±Standard Deviation) Daily Beverage Intakes Reported on Beverage Frequency Questionnaire and 3-Day Food
and Beverage Diaries
Age
6 months (N= 240)
12 months (N= 192)
3 years (N= 129)
5 years (N= 112)
Beverage
Questionnaire Diary
mL/daya
%b
Questionnaire Diary
mL/daya
Questionnaire Diary
b mL/daya
Questionnaire Diary
mL/daya
Human milk
Infant formula
Cows' milk
Juice/juice drinks 56 ± 124
Liquid soft drinks 6 ± 68
204 ±373 195 ±358 28.0
609 ± 387 603 ± 364 85.8
24 ± 124 24 ± 124 6.7
33 ±59 57.5
0±0 1.3
NA
9 ±21 56 ±225 12.6 NAC NA - NA
180 ±290 139\ 25137.0 NA °^A - NA
429 ±349 408 ±331 90.4 316 ±216 358 ±216 100 319 ±198 325 ± 177 98.2
151 ±136 106 ±101 92.2 192 ±169 198 ±169 96.9 189 ±169 180 ±163 95.5
9 ±30 3 ±15 20.9 62 ±71 74 ±101 74.2 74 ± 95 101 ±121 82.1
drinks
Water
Total
0±18
0±0 0.4
12 ±47
3 ±18 10.5 62 ±115 47 ±101 51.2 74 ± 124 47 ± 95 52.7
44 ±80 30 ±53 61.7
940 ±319 896 ±195 100
127 ±136 80 ±109 84.9 177 ± 204 136 ±177 95.3 240 ± 242 169 ±183 99.1
905 ±387 804 ±284 100 795 ± 355 816 ±299 100 896 ± 399 819 ±302 100
a Mean standard deviation of all subjects. Converted from ounces/day; 1 fluid ounce = 29.57 mL.
b Percent of subjects consuming beverage on either questionnaire or diary.
0 NA = not applicable.
N = Number of observations.
Indicates there are insufficient data to calculate percentage.
Source: Marshall et al., 2003b.
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liable 3-14. Consumption of Beverages by Infants and Toddlers (feeding infants and toddlers study)
Age (months)
4 to 6 Months (N = 862) 7 to 8 Months (N = 483) 9 to 1 1 Months (A? = 679) 12 to 14 Months (N = 374) 15 to 18 Months (N = 308) 19 to 24 Months (N = 316)
Beverage
Category Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD
" mL/dayb " mL/dayb " mL/dayb " mL/dayb " mL/dayb " mL/dayb
Total Milks' 100 778 ± 257 100 692 ± 257 99.7 659 ± 284 98.2 618 ±293 94.2 580 ±305 93.4 532 ±281
100%Juicetl 21.3 121 ± 89 45.6 145 ± 109 55.3 160 ±127 56.2 186 ±145 57.8 275 ±189 61.6 281 ± 189
Fruit Drinks' 1.6 101 ±77° 7.1 98 ± 77 % 12.4 157±139% 29.1 231±186% 38.6 260±23f/0 42.6 305 ± 308
Carbonfjed 0.1 86 ± 0 1.1 6±9 1.7 89 ± 92 4.5 115±83 11.2 157±106 11.9 163 ± 172
Water 33.7 163 ±231 56.1 174 ±219 66.9 210 ±234 72.2 302 ±316 74.0 313 ±260 77.0 337 ±245
Otherf 1.4 201 ± 192 2.2 201 ±219 3.5 169 ±166 6.6 251 ±378 12.2 198 ±231 11.2 166 ±248
Total 100 863 ±254 100 866 ±310 100 911 ±361 100 1,017 ±399 100 1,079 ±399 100 1,097 ±482
beverages
a Weighted percentages, adjusted for over sampling, non-response, and under-representation of some racial and ethnic groups.
b Amounts consumed only by those children who had a beverage from this beverage category. Converted from ounces/day; 1 fluid ounce = 29.57 mL.
c Includes human milk, infant formula, cows' milk, soy milk, and goats' milk.
d Fruit or vegetable juices with no added sweeteners.
e Includes beverages with less than 100% juice and often with added sweeteners; some were fortified with one or more nutrients.
f "Other" beverages category included tea, cocoa, and similar dry milk beverages, and electrolyte replacement beverages for infants.
N = Number of observations.
SD = Standard Deviation.
Source : Skinner et al. , 2004.
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-------
Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-75. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample Estimate Lower Upper Estimate Lower Upper Estimate
Size Bound Bound Bound Bound
Lower
Bound
Upper
Bound
Pregnant
Lactating
69
40
21*
21*
19*
15*
22*
28*
39*
53*
33*
44*
46*
55*
44*
55*
38*
52*
46*
57*
Non-pregnant,
Non-lactating
Ages 15 to 44
years
2,166
19
19
20
35
35
36
46
47
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates
may involve aggregation of variance estimation units when data are too sparse to support estimation of the
variance; all estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile
estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Exposure Factors Handbook
September 2011
Page
3-89
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-76. Per Capita Estimates of Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample
Size
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Pregnant
Lactating
Non-pregnant,
Non-lactating
Aged 15 to 44
70
41
2,221
1,318* 1,199*
1,806* 1,374*
1,243 1,193
1,436*
2,238*
1,292
2,336*
3,021*
2,336
1,851*
2,722*
2,222
3,690*
3,794*
2,488
2,674*
3,767*
2,937
2,167* 3,690*
3,452* 3,803*
2,774 3,211
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may involve aggregation of
variance estimation units when data are too sparse to support estimation of the variance; all estimates exclude commercial and
biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile estimates using bootstrap
method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as described in the Third
Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Table 3-77. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women Categories Sample Estimate Lower
Size Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Pregnant
Lactating
Non-pregnant,
Non-lactating
Ages 15 to 44 years
69
40
2,166
13*
21*
14
11*
15*
14
14*
28*
15
31*
53*
31
28*
44*
30
46*
55*
32
43*
55*
38
33*
52*
36
46*
57*
39
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may involve
aggregation of variance estimation units when data are too sparse to support estimation of the variance; all estimates exclude
commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% B.I. = 90% Bootstrap intervals for percentile estimates using
bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as described in the Third
Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Page
3-90
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-78. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
Size Bound Bound Bound Bound Bound Bound
Pregnant
Lactating
Non-pregnant,
Non-lactating
Ages 15 to 44
years
70 819* 669* 969* 1,815* 1,479* 2,808* 2,503* 2,167* 3,690*
41 1,379* 1,021* 1,737* 2,872* 2,722* 3,452* 3,434* 2,987* 3,803*
2,221
916
882
951
1,953 1,854 2,065 2,575 2,403 2,908
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates
may involve aggregation of variance estimation units when data are too sparse to support estimation of the
variance; all estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile
estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Table 3-79. Estimates of Consumers Only Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day)
Mean
90m Percentile
95m Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample Estimate Lower Upper
Size Bound Bound
Estimate
Lower Upper Estimate Lower Upper
Bound Bound Bound Bound
Pregnant
Lactating
Non-pregnant,
Non-lactating
Ages 15 to 44
years
69
40
2,149
21*
28*
19
19*
19*
19
22*
38*
20
39*
53*
35
33* 46*
44* 57*
34
37
44*
57*
46
38*
52*
42
46*
58*
48
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may
involve aggregation of variance estimation units when data are too sparse to support estimation of the variance;
all estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile
estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Exposure Factors Handbook
September 2011
Page
3-91
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Exposure Factors Handbook
Chapter 3 — Ingestion of Water and Other Select Liquids
Table 3-80. Estimates of Consumers-Only Direct and Indirect Water Intake from All Sources by Pregnant,
Lactating, and Childbearing Age Women (mL/day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Pregnant
Lactating
Sample
Size
70
41
Estimate
1,318*
1,806*
Lower
Bound
1,199*
1,374*
Upper
Bound
1,436*
2,238*
Estimate
2,336*
3,021*
Lower
Bound
1,851*
2,722*
Upper
Bound
3,690*
3,794*
Estimate
2,674*
3,767*
Lower
Bound
2,167*
3,452*
Upper
Bound
3,690*
3,803*
Non-pregnant,
Non-lactating
Ages 15 to 44
years
2,203 1,252 1,202 1,303 2,338 2,256 2,404 2,941 2,834 3,179
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may
involve aggregation of variance estimation units when data are too sparse to support estimation of the variance; all
estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile
estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Table 3-81. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/kg-day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
Size Bound Bound Bound Bound Bound Bound
Pregnant
Lactating
65
33
14*
26*
12*
18*
15*
18*
33*
54*
29*
44*
46*
55*
43*
55*
33*
53*
46*
57*
Non-pregnant,
Non-lactating
Ages 15 to 44
years
2,028
15
14
16
32
31
33
38
36
42
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates
may involve aggregation of variance estimation units when data are too sparse to support estimation of the
variance; all estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile
estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as
described in the Third Report on Nutrition Monitoring in the United States, 1994-1996 (LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
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September 2011
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-82. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
Lactating, and Childbearing Age Women (mL/day)
Mean
90th Percentile
95th Percentile
90% CI
90% BI
90% BI
Women
Categories
Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
Size Bound Bound Bound Bound Bound Bound
Pregnant
Lactating
65
34
872*
1,665*
728*
1,181*
1,016*
2,148*
1
2
,844*
,959*
1,776*
2,722*
3,690*
3,452*
2,589*
3,588*
2,167*
2,987*
3,690*
4,026*
Non-pregnant,
Non-lactating 2,077
Ages 15 to 44
years
976
937
1,014 2,013 1,893 2,065 2,614 2,475 2,873
NOTE: Source of data: 1994-1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval
estimates may involve aggregation of variance estimation units when data are too sparse to support
estimation of the variance; all estimates exclude commercial and biological water.
90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for
percentile estimates using bootstrap method with 1,000 replications.
* The sample size does not meet minimum reporting requirements to make statistically reliable
estimates as described in the Third Report on Nutrition Monitoring in the United States, 1994-1996
(LSRO, 1995).
Source: Kahn and Stralka, 2008 (Based on CSFII 1994-1996 and 1998).
Table 3-83. Total Fluid Intake of Women 15 to 49 Years Old
Reproductive
Status3
mL/day
Control
Pregnant
Lactating
mL/kg-day
Control
Pregnant
Lactating
Mean
1,940
2,076
2,242
32.3
32.1
37.0
Standai
Deviati
686
743
658
12.3
11.8
11.6
a Number of observations :
Source: Ershowetal., 1991.
rd
m 5
995
1,085
1,185
15.8
16.4
19.6
non-pregnant,
Percentile Distribution
10
1,172
1,236
1,434
18.5
17.8
21.8
non-lactatin
25
1,467
1,553
1,833
23.8
17.8
21.8
g controls
50
1,835
1,928
2,164
30.5
30.5
35.1
(N=6,
75
2,305
2,444
2,658
38.7
40.4
45.0
201); pregnant
90
2,831
3,028
3,169
48.4
48.9
53.7
(N= 188);
95
3,186
3,475
3,353
55.4
53.5
59.2
lactating
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-84. Total Tap Water Intake of Women 15
Reproductive Status3
mL/day
Control
Pregnant
Lactating
mL/kg-day
Control
Pregnant
Lactating
Fraction of daily fluid
Control
Pregnant
Lactating
Mean
1,157
1,189
1,310
19.1
18.3
21.4
intake that
57.2
54.1
57.0
Standard
Deviation
635
699
591
10.8
10.4
9.8
is tap water (%)
18.0
18.2
15.8
to 49 Years Old
Percentile Distribution
5
310
274
430
5.2
4.9
7.4
24.6
21.2
27.4
a Number of observations: non-pregnant, non-lactatin;
Source: Ershow et al
,1991.
10
453
419
612
7.5
5.9
9.8
32.2
27.9
38.0
25
709
713
855
11.7
10.7
14.8
45.9
42.9
49.5
I controls (N= 6,201);
50
1,065
1,063
1,330
17.3
16.4
20.5
59.0
54.8
58.1
75
1,503
1,501
1,693
24.4
23.8
26.8
70.7
67.6
65.9
pregnant (N= 188);
90
1,983
2,191
1,945
33.1
34.5
35.1
79.0
76.6
76.4
lactating (N =
95
2,310
2,424
2,191
39.1
39.6
37.4
83.2
83.2
80.5
77).
Table 3-85. Total Fluid (mL/Day) Derived from Various Dietary Sources
Years3
Control Women
Sources
I
Drinking Water
Milk and Milk Drinks
Other Dairy Products
Meats, Poultry, Fish, Eggs
Legumes, Nuts, and Seeds
Grains and Grain Products
Citrus and Non-citrus Fruit Juices
Fruits, Potatoes, Vegetables, Tomatoes
Fats, Oils, Dressings, Sugars, Sweets
Tea
Coffee and Coffee Substitutes
Carbonated Soft Drinks0
Non-carbonated Soft Drinks0
Beer
Wine Spirits, Liqueurs, Mixed Drinks
All Sources
Vleanb
583
162
23
126
13
90
57
198
9
148
291
174
38
17
10
1,940
Percentile
50
480
107
8
114
0
65
0
171
3
0
159
110
0
0
0
NA
95
1,440
523
93
263
77
257
234
459
41
630
1,045
590
222
110
66
NA
by Women Aged 15 to
Pregnant Women
Meanb
695
308
24
121
18
98
69
212
9
132
197
130
48
7
5
2,076
a Number of observations: non-pregnant, non-lactating controls (N = 6,20 1 );
b Individual means may not add to all-sources total due to rounding.
Percentile
50
640
273
9
104
0
69
0
185
3
0
0
73
0
0
0
NA
95
1,760
749
93
252
88
246
280
486
40
617
955
464
257
0
25
NA
pregnant (N =
49
Lactating Women
Meanb
677
306
36
133
15
119
64
245
10
253
205
117
38
17
6
2,242
Percentile
50
560
285
27
117
0
82
0
197
6
77
80
57
0
0
0
NA
188); lactating (N
95
1,600
820
113
256
72
387
219
582
50
848
955
440
222
147
59
NA
= 77).
0 Includes regular, low-calorie, and non-calorie soft drinks.
NA: Not appropriate to sum the columns for the 50th and 95th percentiles of intake.
Source: Ershow et al., 1991.
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women (L/day)
Variables
Demographics
Home
Work
Total
Geographic Region
Sitel
Site 2
Site 3
Season
Winter
Spring
Summer
Fall
AgeatLMP*
17 to 25
26 to 30
31 to 35
>36
Education
4-year college
Race/ethnicity
White, non-Hispanic
Black, non-Hispanic
Hispanic, any race
Other
Marital Status
Single, never married
Married
Other
Annual Income ($)
<40,000
40,000-80,000
>80,000
Employment
No
Yes
BMI
Low
Normal
Overweight
Obese
Cold Tap Water
N
2,293
2,295
2,293
1,019
864
410
587
622
566
518
852
714
539
188
691
498
1,103
1,276
727
204
84
719
1,497
76
967
730
501
681
1,611
268
1,128
288
542
Mean (SD)
1.3(1.2)
0.4(0.6)
1.7(1.4)
1.8(1.4)
1.9(1.4)
1.1(1.3)
1.6(1.3)
1.7(1.4)
1.8(1.6)
1.8(1.5)
1.6(1.4)
1.8(1.5)
1.7(1.3)
1.8(1.4)
1.5(1.5)
1.7(1.5)
1.8(1.3)
1.8(1.4)
1.6(1.5)
1.1(1.3)
1.9(1.5)
1.6(1.5)
1.8(1.4)
1.7(1.9)
1.6(1.5)
1.8(1.4)
1.7(1.3)
1.7(1.5)
1.7(1.4)
1.6(1.3)
1.7(1.4)
1.7(1.5)
1.8(1.6)
Bottled Water
N
•
•
2,284
1,016
862
406
584
622
560
518
848
710
538
188
687
496
1,100
1,273
722
202
85
713
1,494
76
962
730
499
679
1,604
267
1,123
288
540
Mean (SD)
•
•
0.6 (0.9)
0.5 (0.9)
0.4 (0.7)
1.1(1.2)
0.6(1.0)
0.6(1.0)
0.6 (0.9)
0.5 (0.9)
0.6(1.0)
0.6(1.0)
0.5 (0.8)
0.5 (0.9)
0.6(1.0)
0.6(1.0)
0.5 (0.9)
0.5 (0.9)
0.6 (0.9)
1.1(1.2)
0.5 (0.9)
0.6(1.0)
0.5 (0.9)
0.5 (0.9)
0.6(1.0)
0.5 (0.9)
0.5 (0.9)
0.5 (0.9)
0.6(0.9)
0.6(1.0)
0.5 (0.9)
0.6(0.9)
0.6(1.0)
Exposure Factors Handbook
September 2011
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women
(L/day) (continued)
Diabetes
No diabetes
Regular diabetes
Gestational diabetes
Nausea during pregnancy
No
Yes
Pregnancy history
No prior pregnancy
Prior pregnancy with no SABC
Prior pregnancy with SAB
Caffeine
0 mg/day
1-150 mg/day
15 1-300 mg/day
>300 mg/day
Vitamin use
No
Yes
Smoking
Non-smoker
<10 cigarettes/day
>10 cigarettes/day
Alcohol use
No
Yes
Recreational exercise
No
Yes
Illicit drug use
No
Yes
Cold Tap Water
N
2,221
17
55
387
1,904
691
1,064
538
578
522
433
760
180
2,113
2,164
84
45
2,257
36
1,061
1,232
2,024
268
Mean (SD)
1.7(1.4)
2.6(2.1)
1.6(1.6)
1.6(1.4)
1.7(1.4)
1.7(1.4)
1.7(1.4)
1.8(1.5)
1.8(1.5)
1.6(1.3)
1.6(1.4)
1.7(1.5)
1.4(1.4)
1.7(1.4)
1.7(1.4)
1.8(1.5)
1.8(1.6)
1.7(1.4)
1.6(1.2)
1.5(1.4)
1.8(1.4)
1.7(1.4)
1.7(1.5)
Bottled Water
N
2,213
17
54
385
1,897
685
1,063
536
577
522
433
752
176
2,108
2,155
84
45
2,247
37
1,054
1,230
2,017
266
Mean (SD)
0.6 (0.9)
0.4(0.8)
0.6(1.0)
0.6(1.0)
0.6 (0.9)
0.6(1.0)
0.5 (0.9)
0.6(1.0)
0.6(1.0)
0.5(0.8)
0.6 (0.9)
0.6(1.0)
0.5(0.8)
0.6 (0.9)
0.6 (0.9)
0.8(1.3)
0.4(0.7)
0.6 (0.9)
0.6(0.8)
0.6 (0.9)
0.6(1.0)
0.6 (0.9)
0.6(1.0)
Data are not reported in the source document.
b LMP = Age of Last Menstrual Period.
c SAB = Spontaneous abortion.
N = Number of observations .
SD = Standard deviation.
Source: Forssen et al., 2007.
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water by Pregnant
Women
Variables
Total
Geographic Region
Site 1
Site 2
Site 3
Season
Winter
Spring
Summer
Fall
Age at IMP'
<25
26-30
31-35
>36
Education
4-year college
Race/ethnicity
White, non-Hispanic
Black, non-Hispanic
Hispanic, any race
Other
Marital Status
Single, never married
Married
Other
Annual Income ($)
<40,000
40,000-80,000
>80,000
Employment
No
Yes
BUI
Low
Normal
Cold Unfiltered Tap Water
N
2,280
1,014
860
406
583
621
559
517
845
709
538
188
685
495
1,099
1,272
720
202
84
711
1,492
76
960
728
499
678
1,601
266
1,121
%
52
46
67
37
52
53
50
54
55
49
51
53
56
53
49
50
60
37
48
57
50
57
56
51
45
52
52
50
51
Cold Filtered Tap
Water
%
19
28
13
10
19
19
20
19
11
22
27
22
8
16
27
26
9
9
27
9
25
9
11
24
29
21
19
21
22
Bottled Water
%
28
26
19
53
29
28
29
26
33
28
22
25
34
30
23
23
30
54
25
33
25
34
33
24
25
27
29
29
27
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September 2011
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water
by Pregnant Women (continued)
Variables
Cold Unfiltered Tap Water
Cold Filtered Tap
Water
Bottled Water
N % % %
Overweight
Obese
Diabetes
No diabetes
Regular diabetes
Gestational diabetes
Nausea during pregnancy
No
Yes
Pregnancy history
No prior pregnancy
Prior pregnancy with no SABb
Prior pregnancy with SAB
Caffeine
0 mg/day
1-150 mg/day
15 1-300 mg/day
>300 mg/day
Vitamin use
No
Yes
Smoking
Non-smoker
<10 cigarettes/day
>10 cigarettes/day
Alcohol use
No
Yes
Recreational exercise
No
Yes
Illicit drug use
No
Yes
287
540
2,209
17
54
385
1,893
685
1,060
535
577
520
432
751
176
2,104
2,151
84
45
2,244
36
1,053
1,227
2,013
266
53
56
52
69
50
54
52
48
54
53
50
53
52
53
57
52
51
60
66
52
58
54
51
51
56
18
14
19
15
22
18
20
21
18
20
22
17
17
19
8
20
20
10
7
19
19
14
24
20
12
28
29
28
16
27
28
28
31
27
26
27
29
30
27
34
28
28
28
22
28
23
31
26
28
31
a LMP = Age of Last Menstrual Period.
b SAB = spontaneous abortion.
BMI = body mass index.
Source: Forssen et al., 2007.
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-88. Water Intake at Various Activity Levels (L/hour)a
Room Temperature13 (°F)
a
b
c
d
Source:
100
95
90
85
80
Data expressed as
Humidity = 80%;
High (0.1 5
Nd
18
7
7
16
mean intake
air velocity =
Activity Level
hp/man)° Medium (0. 10 hp/man)° Low (0.05 hp/man)°
Intake TV Intake TV
15
0.540 12 0.345 6
(0.31) (0.59)
0.286 7 0.385 16
(0.26) (0.26)
0.218 16 0.213
(0.36) (0.20)
0.222
(0.14)
with standard deviation in parentheses.
60 ft/minute.
Intake
0.653
(0.75)
0.50
(0.31)
0.23
(0.20)
_
_
The symbol "hp" refers to horsepower.
Number of subjects with continuous data.
Data not reported in the source document.
McNall and Schle
gel, 1968.
Table 3-89. Planning Factors for Individual Tap Water Consumption
Environmental Condition
Recommended Planning Factor
(gal/day)a
Recommended Planning Factor
(L/day)a'b
Hot
Temperate
Cold
3.0C
1.5d
2.0s
11.4
5.7
7.6
Based on a mix of activities among the workforce as follows: 15% light work; 65% medium work; 20% heavy
work. These factors apply to the conventional battlefield where no nuclear, biological, or chemical weapons
are used.
b Converted from gal/day to L/day.
This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day-man for urination plus 6
quarts/12-hours light work/man, 9 quarts/12-hours moderate work/man, and 12 quarts/12-hours heavy
work/man.
d This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 1
quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/12-hours heavy
work/man.
e This assumes 1 quart/12-hour rest period/man for perspiration losses, 1 quart/day/man for urination, and 2
quarts/day/man for respiration losses plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate
work/man, and 6 quarts/6-hours heavy work/man.
Source: U.S. Army, 1983.
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September 2011
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-90. Pool Water Ingestion by Swimmers
Study Group
Children <18 years old
Males <18 years old
Females <18 years old
Adults (>1 8 years)
Men
Women
a Converted from
Number of Average Water Ingestion Rate
Participants (mL/45 -minute interval)
41
20
21
12
4
8
mL/45-minute interval.
37
45
30
16
22
12
Average Water Ingestion Rate
(mL/hour)a
49
60
43
21
29
16
Source: Dufour et al., 2006.
Table 3-91. Arithmetic Mean (Maximum) Number of Dives per Diver and Volume of Water Ingested
(mL/dive)
Divers and Locations
Occupational Divers (N= 35)
Open sea
Coastal water, USD <1 km
Coastal water, USD >1 km
Coastal water, USD unknown
Open sea and coastal combined
Freshwater, USD <1 km
Freshwater, USD >1 km
Freshwater, no USD
Freshwater, USD unknown
All freshwater combined
Sports Divers — ordinary mask (N = 482)
Open sea
Coastal water
Open sea and coastal combined
Fresh recreational water
Canals and rivers
City canals
Canals, rivers, city canals combined
Swimming pools
Sports Divers — full face mask (N = 482)
Open sea
Coastal water
Fresh recreational water
Canals and rivers
City canals
All surface water combined
Swimming pools
% of Divers
57
23
20
51
-
37
37
37
77
-
26
78
-
85
11
1.5
-
65
0.21
1.0
27
1.2
0.41
-
2.3
# of Dives
24(151)
3.2(36)
1.8(16)
16 (200)
-
8.3 (76)
16 (200)
16 (200)
45 (200)
-
2.1 (120)
14(114)
-
22 (159)
0.65 (62)
0.031 (4)
-
17(134)
0.012 (6)
0.10(34)
0.44 (80)
0.098(13)
0.010 (3)
-
0.21 (40)
Volume of Water Ingested
(mL)
8.7 (25)
9.7 (25)
8.3 (25)
12 (100)
9.8 (100)
5.5 (25)
5.5 (25)
4.8 (25)
6.0 (25)
5.7 (25)
7.7 (100)
9.9(190)
9.0(190)
13 (190)
3.4(100)
2.8(100)
3.2(100)
20 (190)
0.43 (2.8)
1.3(15)
1.3(15)
0.47 (2.8)
0.31 (2.8)
0.81 (25)
13 (190)
N = Number of divers .
USD = Upstream sewage discharge.
Source: Schijven and de Roda Husman, 2006.
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Chapter 3—Ingestion of Water and Other Select Liquids
Table 3-92. Exposure Parameters for Swimmers in Swimming Pools, Freshwater, and Seawater
Adults
Parameter
Swimming Duration (min)
Swimming Pool
Freshwater
Seawater
Volume Water Swallowed (mL)
Swimming Pool
Freshwater
Seawater
UCL = Upper confidence interval.
Source: Schets etal., 2011.
Men
Mean
68
54
45
34
27
27
95% UCI
180
200
160
170
140
140
Women
Mean
67
54
41
23
18
18
95% UCI
170
220
180
110
86
90
Children <1 5 years
Mean
81
79
65
51
37
31
95% UCI
200
270
240
200
170
140
Table 3-93. Estimated Water Ingestion During Water Recreation Activities (mL/hr)
Activity
Surface Water Study
N Median Mean UCL
N
Swimming Pool Study
Median
Mean
UCL
Limited Contact Scenarios
Boating
Canoeing
no capsize
with capsize
all activities
Fishing
Kayaking
no capsize
with capsize
all activities
Rowing
no capsize
with capsize
all activities
Wading/splashing
Walking
316
766
600
801
222
0
0
2.1
2.2
3.6
2.3
2.0
2.2
2.9
2.3
2.3
2.0
2.3
-
-
3.7
3.8
6.0
3.9
3.6
3.8
5.0
3.8
3.9
3.5
3.9
-
-
11.2
11.4
19.9
11.8
10.8
11.4
16.5
11.6
11.8
10.6
11.8
-
-
0
76
121
104
0
112
23
-
2.1
3.9
2.6
2.0
2.1
4.8
3.1
-
-
-
2.2
2.0
-
3.6
6.6
4.4
3.5
3.6
7.9
5.2
-
-
-
3.7
3.5
-
11.0
22.4
14.1
10.6
10.9
26.8
17.0
-
-
-
1.0
1.0
Full Contact Scenarios
Immersion
Swimming
TOTAL
0
0
2,705
-
-
-
-
-
-
112
114
662
3.2
6.0
5.1
10.0
15.3
34.8
N = Number of participants.
UCL = Upper confidence limit
= No data.
(i.e.
mean +1.96
x standard deviation).
Source: Dorevitch et al. , 2011.
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Chapter 4—Non-Dietary Ingestion Factors
TABLE OF CONTENTS
LIST OF TABLES 4-ii
4. NON-DIETARY INGESTION FACTORS 4-1
4.1. INTRODUCTION 4-1
4.2. RECOMMENDATIONS 4-2
4.3. NON-DIETARY INGESTION—MOUTHING FREQUENCY STUDIES 4-5
4.3.1. Key Studies of Mouthing Frequency 4-5
4.3.1.1. Zartarian et al. (1997a)/Zartarianetal. (1997b)/Zartarianetal. (1998) 4-5
4.3.1.2. Reed etal. (1999) 4-5
4.3.1.3. Freeman etal. (2001) 4-6
4.3.1.4. Tulve et al. (2002) 4-6
4.3.1.5. AuYeung et al. (2004) 4-7
4.3.1.6. Black et al. (2005) 4-7
4.3.1.7. Xue et al. (2007) 4-8
4.3.1.8. Beamer et al. (2008) 4-9
4.3.1.9. Xue etal. (2010) 4-9
4.3.2. Relevant Studies of Mouthing Frequency 4-10
4.3.2.1. Davis etal. (1995) 4-10
4.3.2.2. Lew and Butterworth( 1997) 4-11
4.3.2.3. Tudella et al. (2000) 4-11
4.3.2.4. Ko et al. (2007) 4-11
4.3.2.5. Nicas and Best (2008) 4-12
4.4. NON-DIETARY INGESTION—MOUTHING DURATION STUDIES 4-12
4.4.1. Key Mouthing Duration Studies 4-12
4.4.1.1. Jubergetal. (2001) 4-12
4.4.1.2. Greene (2002) 4-13
4.4.1.3. Beamer et al. (2008) 4-14
4.4.2. Relevant Mouthing Duration Studies 4-14
4.4.2.1. Barretal. (1994) 4-14
4.4.2.2. Zartarian et al. (1997a)/Zartarianetal. (1997b)/Zartarianetal. (1998) 4-15
4.4.2.3. Grootetal. (1998) 4-15
4.4.2.4. Smith and Norris (2003)/Norris and Smith (2002) 4-16
4.4.2.5. AuYeung et al. (2004) 4-17
4.5. MOUTHING PREVALENCE STUDIES 4-17
4.5.1. Staneketal. (1998) 4-17
4.5.2. Warren etal. (2000) 4-18
4.6. REFERENCES FOR CHAPTER 4 4-18
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Chapter 4—Non-Dietary Ingestion Factors
LIST OF TABLES
Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration 4-3
Table 4-2. Confidence in Mouthing Frequency and Duration Recommendations 4-4
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-Transcription 4-21
Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age 4-21
Table 4-5. Video-Transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
(contacts/hour), by Age 4-21
Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour) 4-22
Table 4-7. Indoor Mouthing Frequency (Contacts per contacts/hour), Video-Transcription of 9
Children by Age 4-23
Table 4-8. Outdoor Mouthing Frequency (Contacts per contacts/hour), Video-Transcription of 38
Children, by Age 4-23
Table 4-9. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD), by
Age 4-24
Table 4-10. Indoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-24
Table 4-11. Outdoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-24
Table 4-12. Object/Surface to Mouth Contact Frequency for Infants and Toddlers (events/hour)
(AT =23) 4-25
Table 4-13. Distributions Mouthing Frequency and Duration for Non-Dietary Objects with
Significant Differences (p < 0.05) Between Infants and Toddlers 4-26
Table 4-14. Indoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-27
Table 4-15. Outdoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various
Studies, by Age 4-27
Table 4-16. Survey-Reported Mouthing Behaviors for 92 Washington State Children 4-28
Table 4-17. Number of Hand Contacts Observed in Adults During a Continuous 3-Hour Period 4-28
Table 4-18. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
Other Objects 4-29
Table 4-19. Percent of Houston-Area and Chicago-Area Children Observed Mouthing, by Category
and Child's Age 4-29
Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers (minutes/hour),
by Age 4-30
Table 4-21. Object/Surface to Hands and Mouth Contact Duration for Infants and Toddlers
(minutes/hour) (N= 23) 4-32
Table 4-22. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without
Pacifier (minutes/day), by Age 4-33
Table 4-23. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, and
Other Objects (hours:minutes:seconds) 4-34
Table 4-24. Outdoor Median Mouthing Duration (seconds/contact), Video-Transcription of 38
Children, by Age 4-35
Table 4-25. Indoor Mouthing Duration (minutes/hour), Video-Transcription of Nine Children with
>15 minutes in View Indoors 4-35
Table 4-26. Outdoor Mouthing Duration (minutes/hour), Video-Transcription of 38 Children, by Age 4-36
Table 4-27. Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
Behaviors 4-37
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Chapter 4—Non-Dietary Ingestion Factors
4. NON-DIETARY INGESTION FACTORS
4.1. INTRODUCTION
Adults and children have the potential for
exposure to toxic substances through non-dietary
ingestion pathways other than soil and dust ingestion
(e.g., ingesting pesticide residues that have been
transferred from treated surfaces to the hands or
objects that are mouthed). Adults mouth objects such
as cigarettes, pens and pencils, or their hands. Young
children mouth objects, surfaces, or their fingers as
they explore their environment. Mouthing behavior
includes all activities in which objects, including
fingers, are touched by the mouth or put into the
mouth—except for eating and drinking—and
includes licking, sucking, chewing, and biting (Groot
et al., 1998). In addition, the sequence of events can
be important, such as when a handwashing occurs
relative to contact with soil and hand-to-mouth
contact. Videotaped observations of children's
mouthing behavior demonstrate the intermittent
nature of hand-to-mouth and object-to-mouth
behaviors in terms of the number of contacts
recorded per unit of time (Ko et al., 2007).
Adult and children's mouthing behavior can
potentially result in ingestion of toxic substances
(Lepow et al., 1975). Only one study was located that
provided data on mouthing frequency or duration for
adults, but Cannella et al. (2006) indicated that adults
with developmental disabilities frequently exhibit
excessive hand-mouthing behavior. In a large
non-random sample of children born in Iowa, parents
reported non-nutritive sucking behaviors to be very
common in infancy, and to continue for a substantial
proportion of children up to the 3rd and 4th birthdays
(Warren et al., 2000). Hand-to-mouth behavior has
been observed in both preterm and full-term infants
(Rochat et al., 1988; Blass et al., 1989; Takaya et al.,
2003). Infants are born with a sucking reflex for
breast-feeding, and within a few months, they begin
to use sucking or mouthing as a means to explore
their surroundings. Sucking also becomes a means of
comfort when a child is tired or upset. In addition,
teething normally causes substantial mouthing
behavior (i.e., sucking or chewing) to alleviate
discomfort in the gums (Groot et al., 1998).
There are three general approaches to gather data
on children's mouthing behavior: real-time hand
recording, in which trained observers manually
record information (Davis et al., 1995); video-
transcription, in which trained videographers tape a
child's activities and subsequently extract the
pertinent data manually or with computer software
(Zartarian et al., 1998, 1997a, b; Black et al., 2005);
and questionnaire, or survey response, techniques
(Stanek et al., 1998). With real-time hand recording,
observations made by trained professionals—rather
than parents—may offer the advantage of consistency
in interpreting visible behaviors and may be less
subjective than observations made by someone who
maintains a caregiving relationship to the child. On
the other hand, young children's behavior may be
influenced by the presence of unfamiliar people
(Davis et al., 1995). Groot et al. (1998) indicated that
parent observers perceived that deviating from their
usual care giving behavior by observing and
recording mouthing behavior appeared to have
influenced their children's behavior. With video-
transcription methodology, an assumption is made
that the presence of the videographer or camera does
not influence the child's behavior. This assumption
may result in minimal biases introduced when
filming newborns, or when the camera and
videographer are not visible to the child. However, if
the children being studied are older than newborns
and can see the camera or videographer, biases may
be introduced. Ferguson et al. (2006) described
apprehension caused by videotaping as well as
situations where a child's awareness of the
videotaping crew caused "play-acting" to occur, or
parents indicated that the child was behaving
differently during the taping session, although
children tend to ignore the presence of the camera
after some time has passed. Another possible source
of measurement error may be introduced when
children's movements or positions cause their
mouthing not to be captured by the camera. Data
transcription errors can bias results in either the
negative or positive direction. Finally, measurement
error can occur if situations arise in which caregivers
are absent during videotaping and researchers must
stop videotaping and intervene to prevent risky
behaviors (Zartarian et al., 1995). Meanwhile, survey
response studies rely on responses to questions about
a child's mouthing behavior posed to parents or
caregivers. Measurement errors from these studies
could occur for a number of different reasons,
including language/dialect differences between
interviewers and respondents, question wording
problems and lack of definitions for terms used in
questions, differences in respondents' interpretation
of questions, and recall/memory effects.
Some researchers express mouthing behavior as
the frequency of occurrence (e.g., contacts per hour
or contacts per minute). Others describe the duration
of specific mouthing events, expressed in units of
seconds or minutes. This chapter does not address
issues related to contaminant transfer from thumbs,
fingers, or objects or surfaces, into the mouth, and
subsequent ingestion. Examples of how to use
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Chapter 4—Non-Dietary Ingestion Factors
mouthing frequency and duration data can be found
in a U.S. Environmental Protection Agency
(U.S. EPA) Office of Pesticide Programs guidance
document for conducting residential exposure
assessments (U.S. EPA, 2009). This guidance
document provides a standard method for estimating
potential dose among toddlers from incidental
ingestion of pesticide residues from previously
treated turf. This scenario assumes that pesticide
residues are transferred to the skin of toddlers playing
on treated yards and are subsequently ingested as a
result of hand-to-mouth transfer. A second scenario
assumes that pesticide residues are transferred to a
child's toy and are subsequently ingested as a result
of object-to-mouth transfer. Neither scenario includes
residues ingested as a result of soil ingestion.
The recommendations for mouthing frequency
and duration for children only are provided in the
next section, along with a summary of the confidence
ratings for these recommendations. The
recommended values for children are based on key
studies identified by the U.S. EPA for this factor.
Although some studies in Sections 4.3.1 and 4.4.1 are
classified as key, they were not directly used to
provide the recommendations. They are included as
key because they were used by Xue et al. (2007) or
Xue et al. (2010) in meta-analyses, which are the
primary sources of the recommendations provided in
this chapter for hand-to-mouth and object-to-mouth
frequency, respectively. Following the
recommendations, key and relevant studies on
mouthing frequency (see Section 4.3) and duration
(see Section 4.4) are summarized and the
methodologies used in the key and relevant studies
are described. Information on the prevalence of
mouthing behavior is presented in Section 4.5.
4.2. RECOMMENDATIONS
The key studies described in Section 4.3 and
Section 4.4 were used to develop recommended
values for mouthing frequency and duration,
respectively, among children. Only one relevant study
was located that provided data on mouthing
frequency or duration for adults. The recommended
hand-to-mouth frequencies are based on data from
Xue et al. (2007). Xue et al. (2007) conducted a
secondary analysis of data from several of the studies
summarized in this chapter, as well as data from
unpublished studies. Xue et al. (2007) provided data
for the age groups in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005) and categorized the
data according to indoor and outdoor contacts. The
recommendations for frequency of object-to-mouth
contact are based on data from Xue et al. (2010). Xue
et al. (2010) conducted a secondary analysis of data
from several of the studies summarized in this
chapter, as well as data from an unpublished study.
Recommendations for duration of object-to-mouth
contacts are based on data from Juberg et al. (2001),
Greene (2002), and Beamer et al. (2008).
Recommendations on duration of object-to-mouth
contacts pre-dated the U.S. EPA's (2005) guidance on
age groups. For cases in which age groups of children
in the key studies did not correspond exactly to
U.S. EPA's recommended age groups, the closest age
group was used.
Table 4-1 shows recommended mouthing
frequencies, expressed in units of contacts per hour,
between either any part of the hand (including fingers
and thumbs) and the mouth or between an object or
surface and the mouth. Recommendations for hand-
to-mouth duration are not provided since the
algorithm to estimate exposures from this pathway is
not time dependent. Table 4-2 presents the confidence
ratings for the recommended values. The overall
confidence rating is low for both frequency and
duration of hand-to-mouth and object-to-mouth
contact.
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Chapter 4—Non-Dietary Ingestion Factors
Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration
Age Group
Hand-to-Mouth
Indoor Frequency (contacts/hour)
Outdoor Frequency (contacts/hour)
Mean
95th percentile
Mean
95th percentile
Source
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
28
19
20
13
15
7
65
52
63
37
54
21
15
14
5
9
3
47
42
20
36
12
Xueetal.,2007
Object-to-Mouth
Indoor Frequency (contacts/hour)
Outdoor Frequency (contacts/hour)
Mean
95th percentile
Mean
95th percentile
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
11
20
14
9.9
10
1.1
32
38
34
24
39
3.2
8.1
8.3
1.9
21
40
30
9.1
Xueetal.,2010
Mean Duration (minutes/hour)
95thpercentile Duration (minutes/hour)
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
9C
r
iof
26b
19"
22e
11s
Juberg et al., 2001; Greene,
2002; Beamer et al., 2008
Mean calculated from Juberg et al., 2001(0 to 18 months) and Greene, 2002 (3 to 12 months).
Calculated 95th percentile from Greene, 2002 (3 to 12 months).
Mean calculated from Juberg et al., 2001 (0 to 18 months), Greene, 2002 (3 to 12 months), and Beamer et al., 2008 (6 to 13
months).
Calculated 95th percentile from Greene, 2002 (3 to 12 months) and Beamer et al., 2008 (6 to 13 months).
Mean and 95th percentile from Greene, 2002 (12 to 24 months).
Mean calculated from Juberg et al., 2001 (19 to 36 months), Greene, 2002 (24 to 36 months), and Beamer et al., 2008 (20 to
26 months).
Calculated 95th percentile from Greene, 2002 (24 to 36 months) and Beamer et al., 2008 (20 to 26 months).
= No data.
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Chapter 4—Non-Dietary Ingestion Factors
Table 4-2. Confidence in Mouthing Frequency and Duration Recommendations
General Assessment Factor
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
The approaches for data collection and analysis used were adequate for
providing estimates of children's mouthing frequencies and durations.
Sample sizes were very small relative to the population of interest. Xue et
al., (2007) and (2010) meta-analysis of secondary data was considered to
be of suitable utility for the purposes for developing recommendations.
Bias in either direction likely exists in both frequency and duration
estimates; the magnitude of bias is unknown.
Low
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Key studies for older children focused on mouthing behavior while the
infant studies were designed to research developmental issues.
Most key studies were of samples of U.S. children, but, due to the small
sample sizes and small number of locations under study, the study subjects
may not be representative of the overall U.S. child population.
The studies were conducted over a wide range of dates. However, the
currency of the data is not expected to affect mouthing behavior
recommendations.
Extremely short data collection periods may not represent behaviors over
longer time periods.
Low
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The journal articles are in the public domain, but, in many cases, primary
data were unavailable.
Data collection methodologies were capable of providing results that were
reproducible within a certain range.
Several of the key studies applied and documented quality
assurance/quality control measures.
Low
Variability and Uncertainty
Variability in Population
Description of Uncertainty
The key studies characterized inter-individual variability to a limited
extent, and they did not characterize intra-individual variability over
diurnal or longer term time frames.
The study authors typically did not attempt to quantify uncertainties
inherent in data collection methodology (such as the influence of observers
on behavior), although some described these uncertainties qualitatively.
The study authors typically did attempt to quantify uncertainties in data
analysis methodologies (if video-transcription methods were used).
Uncertainties arising from short data collection periods typically were
unaddressed either qualitatively or quantitatively.
Low
Evaluation and Review
Peer Review
Number and Agreement of
Studies
All key studies appear in peer-review journals.
Several key studies were available for both frequency and duration, but
data were not available for all age groups. The results of studies from
different researchers are generally in agreement.
Medium
Overall rating
Low
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Chapter 4—Non-Dietary Ingestion Factors
4.3. NON-DIETARY INGESTION—
MOUTHING FREQUENCY STUDIES
4.3.1. Key Studies of Mouthing Frequency
4.3.1.1. Zartarian et al. (1997a)—Quantifying
Videotaped Activity Patterns: Video
Translation Software and Training
Technologies/Zartarian et al. (1997b)—
Quantified Dermal Activity Data from a
Four-Child Pilot Field Study/Zartarian et
al (1998)—Quantified Mouthing Activity
Data from a Four-Child Pilot Field Study
Zartarian et al. (1998, 1997a, b) conducted a pilot
study of the video-transcription methodology to
investigate the applicability of using videotaping for
gathering information related to children's activities,
dermal exposures, and mouthing behaviors. The
researchers had conducted studies using the real-time
hand recording methodology. These studies
demonstrated poor inter-observer reliability and
observer fatigue when working for long periods of
time. This prompted the investigation into using
videotaping with transcription of the children's
activities at a point in time after the videotaped
observations occurred.
Four Mexican American farm worker children in
the Salinas Valley of California each were videotaped
with a hand-held video camera during their waking
hours, excluding time spent in the bathroom, over
one day in September 1993. The boys were 2 years
10 months old and 3 years 9 months old; the girls
were 2 years and 5 months old, and 4 years and 2
months old. Time of videotaping was 6.0 hours for
the younger girl, 6.6 hours for the older girl, 8.4
hours for the younger boy and 10.1 hours for the
older boy. The videotaping gathered information on
detailed micro-activity patterns of children to be used
to evaluate software for videotaped activities and
translation training methods. The researchers reported
measures taken to assess inter-observer reliability and
several problems with the video-transcription
process.
The hourly data showed that non-dietary object
mouthing occurred in 30 of the 31 hours of tape time,
with one child eating during the hour in which no
non-dietary object mouthing occurred. Mean object-
to-mouth contacts for the four children were reported
to be 11 contacts per hour (median = 9 contacts per
hour), with an average per child range of 1 to
29 contacts per hour (Zartarian et al., 1998). Objects
mouthed included bedding/towels, clothes, dirt,
grass/vegetation, hard surfaces, hard toys, paper/card,
plush toy, and skin (Zartarian et al., 1998). Average
hand-to-mouth contacts for the four children were
13 contacts per hour (averaging the sum of left hand
and right hand-to-mouth contacts and averaging
across children, from Zartarian et al. [1997b]), with
the average per child ranging from 9 to 19 contacts
per hour.
This study's primary purpose was to develop and
evaluate the video-transcription methodology; a
secondary purpose was collection of mouthing
behavior data. The sample of children studied was
very small and not likely to be representative of the
national population. As with other video-transcription
studies, the presence of non-family-member
videographers and a video camera may have
influenced the children's behavior.
4.3.1.2. Reedetal. (1999)—Quantification of
Children's Hand and Mouthing Activities
through a Videotaping Methodology
In this study, Reed et al. (1999) used a video-
transcription methodology to quantify the frequency
and type of children's hand and mouth contacts, as
well as a survey response methodology, and
compared the videotaped behaviors with parents'
perceptions of those behaviors. Twenty children ages
3 to 6 years old selected randomly at a daycare center
in New Brunswick, NJ, and 10 children ages 2 to 5
years old at residences in Newark and Jersey City, NJ
who were not selected randomly, were studied (sex
not specified). For the video-transcription
methodology, inter-observer reliability tests were
performed during observer training and at four points
during the two years of the study. The researchers
compared the results of videotaping the ten children
in the residences with their parents' reports of the
children's daily activities. Mouthing behaviors
studied included hand-to-mouth and hand bringing
object-to-mouth.
Table 4-3 presents the video-transcription
mouthing contact frequency results. The authors
analyzed parents' responses on frequencies of their
children's mouthing behaviors and compared those
responses with the children's videotaped behaviors,
which revealed certain discrepancies: Parents'
reported hand-to-mouth contact of "almost never"
corresponded to overall somewhat lower videotaped
hand-to-mouth frequencies than those of children
whose parents reported "sometimes," but there was
little correspondence between parents' reports of
object-to-mouth frequency and videotaped behavior.
The advantages of this study were that it
compared the results of video-transcription with the
survey response methodology results and that it
described quality assurance steps taken to assure
reliability of transcribed videotape data. However,
only a small number of children were studied, some
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were not selected for observation randomly, and the
sample of children studied may not be representative
of either the locations studied or the national
population. Because of the children's ages, the
presence of unfamiliar persons following the children
with a video camera may influence the video-
transcription results. The parents' survey responses
also may be influenced by recall/memory effects and
other limitations of survey methodologies.
4.3.1.3. Freeman et al. (2001)—Quantitative
Analysis of Children's Micro-Activity
Patterns: The Minnesota Children's
Pesticide Exposure Study
Freeman et al. (2001) conducted a survey
response and video-transcription study of some of the
respondents in a phased study of children's pesticide
exposures in the summer and early fall of 1997. A
probability-based sample of 168 families with
children ages 3 to <14 years old in urban
(Minneapolis/St. Paul) and non-urban (Rice and
Goodhue Counties) areas of Minnesota answered
questions about children's mouthing of paint chips,
food-eating without utensils, eating of food dropped
on the floor, mouthing of non-food items, and
mouthing of thumbs and fingers. For the survey
response portion of the study, parents provided the
responses for children ages 3 and 4 years and
collaborated with or assisted older children with their
responses. Of the 168 families responding to the
survey, 102 were available, selected, and agreed to
measurements of pesticide exposure. Of these
102 families, 19 agreed to videotaping of the study
children's activities for a period of 4 consecutive
hours.
Based on the survey responses for 168 children,
the 3-year olds had significantly more positive
responses for all reported behavior compared to the
other age groups. The authors stated that they did not
know whether parent reporting of 3-year olds'
behavior influenced the responses given. Table 4-4
shows the percentage of children, grouped by age,
who were reported to exhibit non-food related
mouthing behaviors. Table 4-5 presents the mean and
median number of mouthing contacts by age for the
19 videotaped children. Among the four age
categories of these children, object-to-mouth
activities were significantly greater for the 3- and
4-year olds than any other age group, with a median
of 3 and a mean of 6 contacts per hour (p = 0.002,
Kruskal Wallis test comparison across four age
groups). Hand-to-mouth contacts had a median of 3.5
and mean of 4 contacts per hour for the three 3- and
4-year olds observed, median of 2.5 and mean of
8 contacts per hour for the seven 5- and 6-year olds
observed, median of 3 and mean of 5 contacts per
hour for the four 7- and 8-year olds observed, and
median of 2 and mean of 4 for the five 10-, 11-, and
12-year olds observed. Sex differences were observed
for some of the activities, with boys spending
significantly more time outdoors than girls. Hand-to-
mouth and object-to-mouth activities were less
frequent outdoors than indoors for both boys and
girls.
For the 19 children in the video-transcription
portion of the study, inter-observer reliability checks
and quality control checks were performed on
randomly sampled tapes. For four children's tapes,
comparison of the manual video-transcription with a
computerized transcription method (Zartarian et al.,
1995) also was performed; no significant differences
were found in the frequency of events recorded using
the two techniques. The frequency of six behaviors
(hand-to-mouth, hand-to-object, object-to-mouth,
hand-to-smooth surface, hand-to-textured surface,
and hand-to-clothing) was recorded. The amount of
time each child spent indoors, outdoors, and in
contact with soil or grass, as well as whether the child
was barefoot was also recorded. For the four children
whose tapes were analyzed with the computerized
transcription method, which calculates event
durations, the authors stated that most hand-to-mouth
and object-to-mouth activities were observed during
periods of lower physical activity, such as television
viewing.
An advantage to this study is that it included
results from two separate methodologies, and
included quality assurance steps taken to assure
reliability of transcribed videotape data. However, the
children in this study may not be representative of all
children in the United States. Variation in who
provided the survey responses (sometimes parents
only, sometimes children with parents) may have
influenced the responses given. Children studied
using the video-transcription methodology were not
chosen randomly from the survey response group.
The presence of unfamiliar persons following the
children with a video camera may have influenced
the video-transcription methodology results.
4.3.1.4. Tulve et al. (2002)—Frequency of
Mouthing Behavior in Young Children
Tulve et al. (2002) coded the unpublished Davis
et al. (1995) data for location (indoor and outdoor)
and activity type (quiet or active) and analyzed the
subset of the data that consisted of indoor mouthing
behavior during quiet activity (72 children, ranging in
age from 11 to 60 months). A total of one hundred
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eighty-six 15-minute observation periods were
included in the study, with the number of observation
periods per child ranging from 1 to 6. Tulve et al.
(2002) used the Davis et al. (1995) data from which
the children were selected randomly based on date of
birth through a combination of birth certificate
records and random digit dialing of residential
telephone numbers.
Results of the data analyses indicated that there
was no association between mouthing frequency and
sex, but a clear association between mouthing
frequency and age was observed. The analysis
indicated that children <24 months had the highest
frequency of mouthing behavior (81 events/hour) and
that children >24 months had the lowest
(42 events/hour) (see Table 4-6). Both groups of
children were observed to mouth toys and hands
more frequently than household surfaces or body
parts other than hands.
An advantage of this study is that the randomized
design may mean that the children studied were
relatively representative of young children living in
the study area, although they may not be
representative of the U.S. population. Due to the ages
of the children studied, the observers' use of
headphones and manual recording of mouthing
behavior on observation sheets may have influenced
the children's behavior.
4.3.1.5. AuYeungetal. (2004)—Young Children's
Mouthing Behavior: An Observational
Study via Videotaping in a Primarily
Outdoor Residential Setting
AuYeung et al. (2004) used a video-transcription
methodology to study a group of 38 children
(20 females and 18 males; ages 1 to 6 years), 37 of
whom were selected randomly via a telephone
screening survey of a 300 to 400 square mile portion
of the San Francisco, CA peninsula, along with one
child selected by convenience because of time
constraints. Families who lived in a residence with a
lawn and whose annual income was >$35,000 were
asked to participate. Videotaping took place between
August 1998 and May 1999 for approximately two
hours per child. Videotaping by one researcher was
supplemented with field notes taken by a second
researcher who also was present during taping. Most
of the videotaping took place during outdoor play,
however, data were included for several children (one
child <2 years old and eight children >2 years old)
who had more than 15 minutes of indoor play during
their videotaping sessions.
The videotapes were translated into American
Standard Code for Information Interchange (ASCII)
computer files using Virtual Timing Device™
software described in Zartarian et al. (1997a). Both
frequency and duration (see Section 4.4.2.5 of this
chapter) were analyzed. Between 5% and 10% of the
data files translated were randomly chosen for quality
control checks for inter-observer agreement.
Ferguson et al. (2006) described quality control
aspects of the study in detail.
For analysis, the mouthing contacts were divided
into indoor and outdoor locations and
16 object/surface categories. Mouthing frequency
was analyzed by age and sex separately and in
combination. Mouthing contacts were defined as
contact with the lips, inside of the mouth, and/or the
tongue; dietary contacts were ignored. Table 4-7
shows mouthing frequencies for indoor locations. For
the one child observed that was <24 months of age,
the total mouthing frequency was 84.8 contacts/hour;
for children >24 months, the median indoor mouthing
frequency was 19.5 contacts/hour. Outdoor median
mouthing frequencies (see Table 4-8) were very
similar for children <24 months of age
(13.9 contacts/hour) and >24 months
(14.6 contacts/hour).
Non-parametric tests, such as the Wilcoxon rank
sum test, were used for the data analyses. Both age
and sex were found to be associated with differences
in mouthing behavior. Girls had significantly higher
frequencies of mouthing contacts with the hands and
non-dietary objects than boys (p = 0.01 and p =
0.008, respectively).
This study provides distributions of outdoor
mouthing frequencies with a variety of objects and
surfaces. Although indoor mouthing data also were
included in this study, the results were based on a
small number of children (N = 9) and a limited
amount of indoor play. The sample of children may
be representative of certain socioeconomic strata in
the study area, but it is not likely to be representative
of the national population. Because of the children's
ages, the presence of unfamiliar persons following
the children with a video camera may have
influenced the video-transcription methodology
results.
4.3.1.6. Black et al. (2005)—Children's Mouthing
and Food-Handling Behavior in an
Agricultural Community on the
U.S./Mexico Border
Black et al. (2005) studied mouthing behavior of
children in a Mexican-American community along
the Rio Grande River in Texas, during the spring and
summer of 2000, using a survey response and a
video-transcription methodology. A companion study
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of this community (Shalat et al., 2003) identified
870 occupied households during the April 2000 U.S.
Census and contacted 643 of these via in-person
interview to determine the presence of children under
the age of 3 years. Of the 643 contacted, 91 had at
least one child under the age of 3 years (Shalat et al.,
2003). Of these 91 households, the mouthing and
food-handling behavior of 52 children (26 boys and
26 girls) from 29 homes was videotaped, and the
children's parents answered questions about
children's hygiene, mouthing and food-handling
activities (Black et al., 2005). The study was of
children ages 7 to 53 months, grouped into four age
categories: infants (7 to 12 months), 1-year olds (13
to 24 months), 2-year olds (25 to 36 months), and
preschoolers (37 to 53 months).
The survey asked questions about children's ages,
sexes, reported hand-washing, mouthing and food-
handling behavior (N = 52), and activities (N= 49).
Parental reports of thumb/finger placement in the
mouth showed decreases with age. The researchers
attempted to videotape each child for 4 hours. The
children were followed by the videographers through
the house and yard, except for times when they were
napping or using the bathroom. Virtual Timing
Device™ software, mentioned earlier, was used to
analyze the videotapes.
Based on the results of videotaping, most of the
children (49 of 52) spent the majority of their time
indoors. Of the 39 children who spent time both
indoors and outdoors, all three behaviors
(hand-to-mouth, object-to-mouth and food handling)
were more frequent and longer while the child was
indoors. Hand-to-mouth activity was recorded during
videotaping for all but one child, a 30 month old girl.
For the four age groups, the mean hourly hand-to-
mouth frequency ranged from 11.9 (2-year olds) to
22.1 (preschoolers), and the mean hourly
object-to-mouth frequency ranged from 7.8
(2-year olds) to 24.4 (infants). No significant linear
trends were seen with age or sex for hand-to-mouth
hourly frequency. A significant linear trend was
observed for hourly object-to-mouth frequency,
which decreased as age increased (adjusted
R2 = 0.179; p = 0.003). Table 4-9 shows the results of
this study.
Because parental survey reports were not strongly
correlated with videotaped hand or object mouthing,
the authors suggested that future research might
include alternative methods of asking about mouthing
behavior to improve the correlation of questionnaire
data with videotaped observations.
One advantage of this study is that it compared
survey responses with videotaped information on
mouthing behavior. A limitation is that the sample
was fairly small and was from a limited area (mid-
Rio Grande Valley) and is not likely to be
representative of the national population. Because of
the children's ages, the presence of unfamiliar
persons following the children with a video camera
may have influenced the video-transcription
methodology results.
4.3.1.7. Xue et al. (2007)—A Meta-Analysis of
Children's Hand-to-Mouth Frequency
Data for Estimating Non-Dietary Ingestion
Exposure
Xue et al. (2007) gathered hand-to-mouth
frequency data from nine available studies
representing 429 subjects and more than 2,000 hours
of behavior observation (Zartarian et al., 1998; Reed
et al., 1999; Leckie et al., 2000; Freeman et al., 2001;
Greene, 2002; Tulve et al., 2002; Hore, 2003; Black
et al., 2005, Beamer et al., 2008). Two of these
studies (i.e., Leckie et al., 2000; Hore, 2003) are
unpublished data sets and are not summarized in this
chapter. The remaining seven studies are summarized
elsewhere in this chapter. Xue et al. (2007) conducted
a meta-analysis to study differences in hand-to-mouth
behavior. The purpose of the analysis was to
1. examine differences across studies by age
(using the new U.S. EPA recommended age
groupings [U.S. EPA, 2005]), sex, and
indoor/outdoor location;
2. fit variability distributions to the available
hand-to-mouth frequency data for use in one-
dimensional Monte Carlo exposure
assessments;
3. fit uncertainty distributions to the available
hand-to-mouth frequency data for use in two-
dimensional Monte Carlo exposure
assessments; and
4. assess hand-to-mouth frequency data needs
using the new U.S. EPA recommended age
groupings (U.S. EPA, 2005).
The data were sorted into age groupings. Visual
inspection of the data and statistical methods (i.e.,
method of moments and maximum likelihood
estimation) were used, and goodness-of-fit tests were
applied to verify the selection among lognormal,
Weibull, and normal distributions (Xue et al., 2007).
Analyses to study inter- and intra-individual
variability of indoor and outdoor hand-to-mouth
frequency were conducted. It was found that age and
location (indoor vs. outdoor) were important factors
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contributing to hand-to-mouth frequency, but study
and sex were not (Xue et al., 2007). Distributions of
hand-to-mouth frequencies were developed for both
indoor and outdoor activities. Table 4-10 presents
distributions for indoor settings while Table 4-11
presents distributions for outdoor settings. Hand-to-
mouth frequencies decreased for both indoor and
outdoor activity as age increased, and they were
higher indoors than outdoors for all age groups (Xue
et al., 2007).
A strength of this study is that it is the first effort
to fit hand-to-mouth distributions of children in
different locations while using U.S. EPA's
recommended age groups. Limitations of the studies
used in this meta-analysis apply to the results from
the meta-analysis as well; the uncertainty analysis in
this study does not account for uncertainties arising
out of differences in approaches used in the various
studies used in the meta-analysis.
4.3.1.8. Beameretal. (2008)—Quantified Activity
Pattern Data from 6 to 27-Month-Old
Farmworker Children for Use in Exposure
Assessment
Beamer et al. (2008) conducted a follow-up to the
pilot study performed by Zartarian et al. (1997a, b,
1998), described in Sections 4.3.1.1 and 4.4.2.2. For
this study, a convenience sample of 23 children
residing in the farm worker community of Salinas
Valley, CA, was enrolled. Participants were 6- to
13-month-old infants or 20- to 26-month-old
toddlers. Two researchers videotaped each child's
activities for a minimum of 4 hours and kept a
detailed written log of locations visited and objects
and surfaces contacted by the child. A questionnaire
was administered to an adult in the household to
acquire demographic data, housing and cleaning
characteristics, eating patterns, and other information
pertinent to the child's potential pesticide exposure.
Table 4-12 presents the distribution of
object/surface contact frequency for infants and
toddlers in events/hour. The mean hand-to-mouth
frequency was 18.4 events/hour. The mean mouthing
frequency of non-dietary objects was
29.2 events/hour. Table 4-13 presents the
distributions for the mouthing frequency and duration
of non-dietary objects, and it highlights the
differences between infants and toddlers. Toddlers
had higher mouthing frequencies with non-dietary
items associated with pica (i.e., paper) while infants
had higher mouthing frequencies with other
non-dietary objects. In addition, boys had higher
mouthing frequencies than girls. The advantage of
this study is that it included both infants and toddlers.
Differences between the two age groups, as well as
sex differences, could be observed. As with other
video-transcription studies, the presence of
non-family-member videographers and a video
camera may have influenced the children's behavior.
4.3.1.9. Xue et al. (2010)—A Meta-Analysis of
Children's Object-to-Mouth Frequency
Data for Estimating Non-Dietary Ingestion
Exposure
Xue et al. (2010) gathered object-to-mouth
frequency data from 7 available studies representing
438 subjects and approximately 1,500 hours of
behavior observation. The studies used in this
analysis included six published studies that were also
individually summarized in this chapter (Reed et al.,
1999; Freeman et al., 2001; Greene, 2002; Tulve et
al., 2002; AuYeung et al., 2004, Beamer et al., 2008)
as well as one unpublished data set (Hore, 2003).
These data were used to conduct a meta-analysis to
study differences in object-to-mouth behavior. The
purpose of the analysis was to
1. "examine differences across studies by age
(using the new U.S. EPA recommended age
groupings [U.S. EPA, 2005]), sex, and
indoor/outdoor location;
2. fit variability distributions to the available
object to-mouth frequency data for use in one
dimensional Monte Carlo exposure
assessments;
3. fit uncertainty distributions to the available
object-to-mouth frequency data for use in two
dimensional Monte Carlo exposure
assessments; and
4. assess object-to-mouth frequency data needs
using the new U.S. EPA recommended age
groupings (U.S. EPA, 2005)."
The data were sorted into age groupings. Visual
inspection of the data and statistical methods (i.e.,
method of moments and maximum likelihood
estimation) were used, and goodness-of-fit tests were
applied to verify the selection among lognormal,
Weibull, and normal distributions (Xue et al., 2010).
Analyses to study inter- and intra-individual
variability of indoor and outdoor object-to-mouth
frequency were conducted. It was found that age,
location (indoor vs. outdoor), and study were
important factors contributing to object-to-mouth
frequency, but study and sex were not (Xue et al.,
2010). Distributions of object-to-mouth frequencies
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were developed for both indoor and outdoor
activities. Table 4-14 presents distributions for indoor
settings while Table 4-15 presents distributions for
outdoor settings. Object-to-mouth frequencies
decreased for both indoor and outdoor activity as age
increased (i.e., after age <6 to 12 months for indoor
activity; and after <3 to 6 years for outdoor activity),
and were higher indoors than outdoors for all age
groups (Xueetal., 2010).
A strength of this study is that it is the first effort
to fit object-to-mouth distributions of children in
different locations while using U.S. EPA's
recommended age groups. Limitations of the studies
used in this meta-analysis apply to the results from
the meta-analysis as well; the uncertainty analysis in
this study does not account for uncertainties arising
out of differences in approaches used in the various
studies used in the meta-analysis.
4.3.2. Relevant Studies of Mouthing Frequency
4.3.2.1. Davis et al. (1995)—Soil Ingestion in
Children with Pica: Final Report
In 1992, under a Cooperative Agreement with
U.S. EPA, the Fred Hutchinson Cancer Research
Center conducted a survey response and real-time
hand recording study of mouthing behavior data. The
study included 92 children (46 males, 46 females)
ranging in age from <12 months to 60 months, from
Richland, Kennewick, and Pasco, WA. The children
were selected randomly based on date of birth
through a combination of birth certificate records and
random digit dialing of residential telephone
numbers. For each child, data were collected in one
7-day period during January to April, 1992.
Eligibility included residence within the city limits,
residence duration >1 month, and at least one parent
or guardian who spoke English. Most of the adults
who responded to the survey reported their marital
status as being married (90%), their race as
Caucasian (89%), their household income in the
>$30,000 range (56%), or their housing status as
single-family home occupants (69%).
The survey asked questions about thumb-
sucking and frequency questions about pacifier use,
placing fingers, hands and feet in the mouth, and
mouthing of furniture, railings, window sills, floor,
dirt, sand, grass, rocks, mud, clothes, toys, crayons,
pens, and other items. Table 4-16 shows the survey
responses for the 92 study children. For most of the
children in the study, the mouthing behavior real-time
hand recording data were collected simultaneously by
parents and by trained observers who described and
quantified the mouthing behavior of the children in
their home environment. The observers recorded
mouth and tongue contacts with hands, other body
parts, natural objects, surfaces, and toys every
15 seconds during 15-minute observation periods
spread over 4 days. Parents and trained observers
wore headphones that indicated elapsed time (Davis
et al., 1995). If all attempted observation periods
were successful, each child would have a total of
sixteen 15-minute observation periods with sixty
15-second intervals per 15-minute observation
period, or nine hundred sixty 15-second intervals in
all. The number of successful intervals of observation
ranged from 0 to 840 per child. Comparisons of the
inter-observer reliability between the trained
observers and parents showed
"a high degree of correlation between the
overall degree of both mouth and tongue
activity recorded by parents and observers.
For total mouth activity, there was a
significant correlation between the rankings
obtained according to parents and observers,
and parents were able to identify the same
individuals as observers as being most and
least oral in 60% of the cases" (Davis et al.,
1995).
One advantage of this study is the simultaneous
observations by both, parents and trained observers,
that allow comparisons regarding the consistency of
the recorded observations. The random nature in
which the population was selected may provide a
representative population of the study area, within
certain limitations, but not of the national population.
In addition, this study was considered relevant
because the data were not analyzed for deriving
estimates of mouthing contact. These data were
analyzed by Tulve et al., 2002 (see Section 4.3.1.4).
Simultaneous collection of food, medication, fecal,
and urine samples that occurred as part of the overall
study (not described in this summary) may have
contributed a degree of deviation from normal
routines within the households during the 7 days of
data collection and may have influenced children's
usual behaviors. Wearing of headphones by parents
and trained observers during mouthing observations,
presence of non-family-member observers, and
parents' roles as observers as well as caregivers also
may have influenced the results; the authors state
"Having the child play naturally while being
observed was challenging. Usually the first day of
observation was the most difficult in this respect, and
by the third or fourth day of observation the child
generally paid little attention to the observers."
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4.3.2.2. Lew andButterworth (1997)—The
Development of Hand-Mouth Coordination
in 2- to 5-Month-Old Infants: Similarities
with Reaching and Grasping
Lew and Butterworth (1997) studied 14 infants
(10 males, 4 females; mostly first borns) in Stirling,
United Kingdom, in 1990 using a video-transcription
methodology. Attempts were made to study each
infant within 1 week of the infant's 2-, 3-, 4-, and
5-month birthdays. After becoming accustomed to the
testing laboratory, and with their mothers present,
infants were placed in semi-reclining seats and filmed
during an experimental protocol in which researchers
placed various objects into the infants' hands. Infants
were observed for two baseline periods of 2 minutes
each. The researchers coded all contacts to the face
and mouth that occurred during baseline periods
(prior to and after the object handling period) as well
as contacts occurring during the object handling
period. Hand-to-mouth contacts included contacts
that landed directly in or on the mouth as well as
those in which the hand landed on the face first and
then moved to the mouth. The researchers assessed
inter-observer agreement using a rater not involved
with the study, for a random proportion
(approximately 10%) of the movements documented
during the object handling period, and reported inter-
observer agreement of 0.90 using Cohen's kappa for
the location of contacts. The frequency of contacts
ranged between zero and one contact per minute.
The advantages of this study were that use of
video cameras could be expected to have minimal
effect on infant behavior for infants of these ages, and
the researchers performed tests of inter-observer
reliability. A disadvantage is that the study included
baseline observation periods of only 2 minutes'
duration, during which spontaneous hand-to-mouth
movements could be observed. The extent to which
these infants' behavior is representative of other
infants of these ages is unknown.
4.3.2.3. Tudella et al. (2000)—The Effect of Oral-
Gustatory, Tactile-Bucal, and Tactile-
Manual Stimulation on the Behavior of the
Hands in Newborns
Tudella et al. (2000) studied the frequency of
hand-to-mouth contact, as well as other behaviors, in
24 full-term Brazilian newborns (10 to 14 days old)
using a video-transcription methodology. Infants
were in an alert state, in their homes in silent and
previously heated rooms in a supine position and had
been fed between 1 and 1 1/2 hours before testing.
Infants were studied for a 4-minute baseline period
without stimuli before experimental stimuli were
administered. Results from the four-minute baseline
period, without stimuli, indicated that the mean
frequency of hand-to-mouth contact (defined as right
hand or left hand touching the lips or entering the
buccal cavity, either with or without rhythmic jaw
movements) was almost 3 right hand contacts and
slightly more than 1.5 left hand contacts, for a total
hand-to-mouth contact frequency of about 4 contacts
in the 4-minute period. The researchers performed
inter-observer reliability tests on the videotape data
and reported an inter-coder Index of Concordance of
93%.
The advantages of this study were that use of
video cameras could be expected to have virtually no
effect on newborns' behavior, and inter-observer
reliability tests were performed. However, the study
data may not represent newborn hand-to-mouth
contact during non-alert periods such as sleep. The
extent to which these infants' behavior is
representative of other full-term 10- to 14-day-old
infants' behavior is unknown.
4.3.2.4. Ko et al (2007)—Relationships of Video
Assessments of Touching and Mouthing
Behaviors During Outdoor Play in Urban
Residential Yards to Parental Perceptions
of Child Behaviors and Blood Lead Levels
Ko et al. (2007) compared parent survey
responses with results from a video-transcription
study of children's mouthing behavior in outdoor
settings, as part of a study of relationships between
children's mouthing behavior and other variables
with blood lead levels. A convenience sample of
37 children (51% males, 49% females) 14 to
69 months old was recruited via an urban health
center and direct contacts in the surrounding area,
apparently in Chicago, IL. Participating children
were primarily Hispanic (89%). The mouth area was
defined as within 1 inch of the mouth, including the
lips. Items passing beyond the lips were defined as in
the mouth. Placement of an object or food item in the
mouth along with part of the hand was counted as
both hand and food or hand and object in mouth.
Mouthing behaviors included hand-to-mouth area
both with and without food, hand-in-mouth with or
without food, and object-in-mouth including food,
drinks, toys, or other objects.
Survey responses for the 37 children who also
were videotaped included parents reporting children's
inserting hand, toys, or objects in mouth when
playing outside, and inserting dirt, stones, or sticks in
mouth. Video-transcription results of outdoor play for
these 37 children indicated 0 to 27 hand-in-mouth
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and 3 to 69 object-in-mouth touches per hour for the
13 children reported to frequently insert hand, toys,
or objects in mouth when playing outside; 0 to 67
hand-in-mouth, and 7 to 40 object-in-mouth touches
per hour for the 10 children reported to "sometimes"
perform this behavior; 0 to 30 hand-in-mouth and
0 to 125 object in mouth touches per hour for the
12 children reported to "hardly ever" perform this
behavior, and 1 to 8 hand-in-mouth and 3 to 6 object-
in-mouth touches per hour for the 2 children reported
to "never" perform this behavior.
Videotaping was attempted for 2 hours per child
over two or more play sessions, with videographers
trying to avoid interacting with the children. Children
played with their usual toys and partners, and no
instructions were given to parents regarding their
supervision of the children's play. The authors stated
that during some portion of the videotape time,
children's hands and mouths were out of camera
view. Videotape transcription was performed
manually, according to a modified version of the
protocol used in the Reed et al. (1999) study.
Inter-observer reliability between three
video-transcribers was checked with seven 30-minute
video segments.
One strength of this study is its comparison of
survey responses with results from the video-
transcription methodology. A limitation is that the
non-randomly selected sample of children studied is
unlikely to be representative of the national
population. Comparing results from this study with
results from other video-transcription studies may be
problematic because of inclusion of food handling
with hand-to-mouth and object-to-mouth frequency
counts. Due to the children's ages, their behavior may
have differed from normal patterns because of the
presence of strangers who videotaped them.
4.3.2.5. Nicas and Best (2008)—A Study
Quantifying the Hand-to-Face Contact
Rate and Its Potential Application to
Predicting Respiratory Tract Infection
Nicas and Best (2008) conducted an observational
study on adults (five women and five men; ages not
specified), in which individuals were videotaped
while performing office-type work for a 3-hour
period. The videotapes were viewed by the
investigators, who counted the number of
hand-to-face touches the subjects made while they
worked on a laptop computer, read, or wrote.
Following the observations, the sample mean and
standard deviation were computed for the number of
times each subject touched his or her eyes, nostrils,
and lips. For the three combinations of touch
frequencies (i.e., lips-eyes, lips-nostrils,
eyes-nostrils), Spearman rank correlation coefficients
were computed and tests of the hypothesis that the
rank correlation coefficients exceeded zero were
performed.
Table 4-17 shows the frequency of hand-to-face
contacts with the eyes, nostrils, and lips of the
subjects, and the sum of these counts. There was
considerable inter-individual variability among the
subjects. During the 3-hour continuous study period,
the total number of hand contacts with the eyes, lips
and nostrils ranged from 3 to 104 for individual
subjects, with a mean of 47. The mean per hour
contact rate was 15.7. There was a positive
correlation between the number of hand contacts with
lips and eyes and with lips and nostrils (subjects who
touched their lips frequently also touched their eyes
and nostrils frequently). The Spearman rank
correlation coefficients for contacts between different
facial targets were 0.76 for the lips and eyes; 0.66 for
the lips and nostrils, and 0.44 for the eyes and
nostrils.
The study's primary purpose was to quantify
hand-to-face contacts in order to determine the
application of this contact rate in predicting
respiratory tract infection. The authors developed an
algebraic model for estimating the dose of pathogens
transferred to target facial membranes during a
defined exposure period. The advantage of this study
is that it determined the frequency of hand-to-face
contacts for adults. A limitation of the study is that
there were very few subjects (five women and five
men) who may not have been representative of the
U.S. population. In addition, as with other video-
transcription studies, the presence of videographers
and a video camera may have influenced the subjects'
behaviors.
4.4. NON-DIETARY INGESTION—
MOUTHING DURATION STUDIES
4.4.1. Key Mouthing Duration Studies
4.4.1.1. Jubergetal. (2001)—An Observational
Study of Object Mouthing Behavior by
Young Children
Juberg et al. (2001) studied 385 children ages 0 to
36 months in western New York State, with parents
collecting real-time hand-recording mouthing
behavior data, primarily in the children's own home
environments. The study consisted of an initial pilot
study conducted in February 1998, a second phase
conducted in April 1998, and a third phase conducted
at an unspecified later time. The study's sample was
drawn from families identified in a child play
research center database or whose children attended a
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child care facility in the same general area; some
geographic variation within the local area was
obtained by selecting families with different zip
codes in the different study phases. The pilot phase
had 30 children who participated out of 150 surveys
distributed; the second phase had 187 children out of
approximately 300 surveys distributed, and the third
phase had 168 participants out of 300 surveys
distributed.
Parents were asked to observe their child's
mouthing of objects only; hand-to-mouth behavior
was not included. Data were collected on a single day
(pilot and second phases) or 5 days (third phase);
parents recorded the insertion of objects into the
mouth by noting the "time in" and "time out" and the
researchers summed the recorded data to tabulate
total times spent mouthing the various objects during
the days of observation. Thus, the study data were
presented as minutes per day of object mouthing
time. Mouthed items were classified as pacifiers,
teethers, plastic toys, or other objects.
Table 4-18 shows the results of the combined
pilot and second phase data. For both age groups,
mouthing time for pacifiers greatly exceeded
mouthing time for non-pacifiers, with the difference
more acute for the older age group than for the
younger age group. Histograms of the observed data
show a peak in the low end of the distribution (0 to
100 minutes per day) and a rapid decline at longer
durations.
A third phase of the study focused on children
between the ages of 3 and 18 months and included
only non-pacifier objects. Subjects were observed for
5 non-consecutive days over a 2-month period. A
total of 168 participants returned surveys for at least
one day, providing a total of 793 person-days of data.
The data yielded a mean non-pacifier object
mouthing duration of 36 minutes per day; the mean
was the same when calculated on the basis of
793 person-days of data as on the basis of 168 daily
average mouthing times.
One advantage of this study is the large sample
size (385 children); however, the children apparently
were not selected randomly, although some effort was
made to obtain local geographic variation among
study participants. There is no description of the
socioeconomic status or racial and ethnic identities of
the study participants. The authors do not describe
the methodology parents used to record mouthing
event durations (e.g., using stopwatches, analog or
digital clocks, or guesses). The authors stated that
using mouthing event duration units of minutes rather
than seconds may have yielded observations rounded
to the nearest minute.
4.4.1.2. Greene (2002)—A Mouthing Observation
Study of Children Under Six Years of Age
The U.S. Consumer Product Safety Commission
conducted a survey response and real-time hand
recording study between December 1999 and
February 2001 to quantify the cumulative time per
day that young children spend awake, not eating, and
mouthing objects. "Mouthing" was defined as
children sucking, chewing, or otherwise putting an
object on their lips or into their mouth. Participants
were recruited via a random digit dialing telephone
survey in urban and nearby rural areas of Houston,
TX and Chicago, IL. Of the 115,289 households
surveyed, 1,745 households had a child under the age
of 6 years and were willing to participate. In the
initial phase of the study, 491 children ages 3 to
81 months participated. Parents were instructed to
use watches with second hands or to count seconds to
estimate mouthing event durations. Parents also were
to record mouthing frequency and types of objects
mouthed. Parents collected data in four separate, non-
consecutive 15-minute observation periods. Initially,
parents were called back by the researchers and asked
to provide their data over the telephone. Of the
491 children, 43 children (8.8%) had at least one
15-minute observation period with mouthing event
durations recorded as exceeding 15 minutes. Due to
this data quality problem, the researchers excluded
the parent observation data from further analysis.
In a second phase, trained observers used
stopwatches to record the mouthing behaviors and
mouthing event durations of the subset of 109 of
these children ages 3 to 36 months and an additional
60 children (total in second phase, 169), on 2 hours
of each of 2 days. The observations were done at
different times of the day at the child's home and/or
child care facility. Table 4-19 shows the prevalence of
observed mouthing among the 169 children in the
second phase. All children were observed to mouth
during the 4 hours of observation time; 99% mouthed
parts of their anatomy. Pacifiers were mouthed by
27% in an age-declining pattern ranging from 47% of
children less than 12 months old to 10% of the 2- to
<3-year olds.
Table 4-20 provides the average mouthing time
by object category and age in minutes per hour. The
average mouthing time for all objects ranged from
5.3 to 10.5 minutes per hour, with the highest
mouthing time corresponding to children <1 year of
age and the lowest to the 2 to <3 years of age
category. Among the objects mouthed, pacifiers
represented about one third of the total mouthing
time, with 3.4 minutes per hour for the youngest
children, 2.6 minutes per hour for the children
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between 1 and 2 years and 1.8 minutes per hour for
children 2 to <3 years old. The next largest single
item category was anatomy. In this category, children
under 1 year of age spent 2.4 minutes per hour
mouthing fingers and thumbs; this behavior declined
with age to 1.2 minutes per hour for children 2 to <3
years old.
Of the 169 children in the second phase, data
were usable on the time awake and not eating (or
"exposure time") for only 109; data for the remaining
60 children were missing. Thus, in order to develop
extrapolated estimates of daily mouthing time for the
109 children, from the 2 hours of observation per day
for two days, the researchers developed a statistical
model that accounted for the children's demographic
characteristics, that estimated exposure times for the
60 children with missing data, and then computed
statistics for the extrapolated daily mouthing times
for all 169 children, using a "bootstrap" procedure.
Using this method, the estimated mean daily
mouthing time of objects other than pacifiers ranged
from 37 minutes/day to 70 minutes/day with the
lowest number corresponding to the 2 to <3-year-old
children and the largest number corresponding to the
3 to <12-month-old children.
The 551 child participants were 55% males,
45% females. The study's sample was drawn in an
attempt to duplicate the overall U.S. demographic
characteristics with respect to race, ethnicity,
socioeconomic status and urban/suburban/rural
settings. The sample families' reported annual
incomes were generally higher than those of the
overall U.S. population.
This study's strength was that it consisted of a
randomly selected sample of children from both
urban and non-urban areas in two different
geographic areas within the United States. However,
the observers' presence and use of a stopwatch to
time mouthing durations may have affected the
children's behavior.
4.4.1.3. Beameretal. (2008)—Quantified Activity
Pattern Data from 6- to 27-Month-Old
Farmworker Children for Use in Exposure
Assessment
Beamer et al. (2008) conducted a follow-up to the
pilot study performed by Zartarian et al. (1998,
1997a, b), described in Sections 4.3.1.1 and 4.4.2.2.
For this study, a convenience sample of 23 children
residing in the farm worker community of Salinas
Valley, CA was enrolled. Participants were 6- to
13-month-old infants or 20- to 26-month-old
toddlers. Two researchers videotaped each child's
activities for a minimum of 4 hours, and kept a
detailed written log of locations visited and objects
and surfaces contacted by the child. A questionnaire
was administered to an adult in the household to
acquire demographic data, housing and cleaning
characteristics, eating patterns, and other information
pertinent to the child's potential pesticide exposure.
Table 4-21 presents the object/surface hourly
contact duration in minutes/hour. The mean hourly
mouthing duration for hands and non-dietary objects
was 1.4 and 3.5 minutes/hour, respectively. Infants
had higher hourly mouthing duration with toys and
all non-dietary objects than toddlers. Girls had higher
contact durations than boys.
The advantage of this study is that it included
both infants and toddlers. Differences between the
two age groups, as well as sex differences, could be
observed. As with other video-transcription studies,
the presence of non-family-member videographers
and a video camera may have influenced the
children's behavior.
4.4.2. Relevant Mouthing Duration Studies
4.4.2.1. Barr et al (1994)—-Effects oflntra-Oral
Sucrose on Crying, Mouthing, and Hand-
Mouth Contact in Newborn and Six-Week-
Old Infants
Barr et al. (1994) studied hand-to-mouth contact,
as well as other behaviors, in 15 newborn
(eight males, seven females) and fifteen 5- to 7-week
old (eight males, seven females) full-term Canadian
infants using a video-transcription methodology. The
newborns were 2- to 3-days old, were in a quiet,
temperature-controlled room at the hospital, were in a
supine position and had been fed between 2 1/2 and
3 1/2 hours before testing. Barr et al. (1994) analyzed
a 1-minute baseline period, with no experimental
stimuli, immediately before a sustained crying
episode lasting 15 seconds. For the newborns,
reported durations of hand-to-mouth contact during
10-second intervals of the 1-minute baseline period
were in the range of 0 to 2%. The 5- to 7-week old
infants apparently were studied at primary care
pediatric facilities when they were in bassinets
inclined at an angle of 10 degrees. For these slightly
older infants, the baseline periods analyzed were less
than 20 seconds in length, but Barr et al. (1994)
reported similarly low mean percentages of the
10-second intervals (approximately 1% of the time
with hand-to-mouth contact). Hand-to-mouth contact
was defined as "any part of the hand touching the lips
and/or the inside of the mouth." The researchers
performed inter-observer reliability tests on the
videotape data and reported a mean inter-observer
reliability of 0.78 by Cohen's kappa.
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The advantages of this study were that use of
video cameras could be expected to have virtually no
effect on newborns' or five to seven week old infants'
behavior, and that inter-observer reliability tests were
performed. The study data did not represent newborn
or 5- to 7-week-old infant hand-to-mouth contact
during periods in which infants of these ages were in
a sleeping or other non-alert state, and data may only
represent behavior immediately prior to a state of
distress (sustained crying episode). The extent to
which these infants' behavior is representative of
other full-term infants of these ages is unknown.
4.4.2.2. Zartarian et al (1997a)—Quantifying
Videotaped Activity Patterns: Video
Translation Software and Training
Technologies/Zartarian et al. (1997b)—
Quantified Dermal Activity Data from a
Four-Child Pilot Field Study/Zartarian et
al. (1998)—Quantified Mouthing Activity
Data from a Four-Child Pilot Field Study
As described in Section 4.3.1.1, Zartarian et al.
(1998, 1997a, b) conducted a pilot study of the video-
transcription methodology to investigate the
applicability of using videotaping for gathering
information related to children's activities, dermal
exposures and mouthing behaviors. The researchers
had conducted studies using the real-time hand
recording methodology. These studies demonstrated
poor inter-observer reliability and observer fatigue
when attempted for long periods of time. This
prompted the investigation into using videotaping
with transcription of the children's activities at a
point in time after the videotaped observations
occurred.
Four Mexican-American farm worker children in
the Salinas Valley of California each were videotaped
with a hand-held videocamera during their waking
hours, excluding time spent in the bathroom, over
1 day in September 1993. The boys were 2 years
10 months old and 3 years 9 months old; the girls
were 2 years 5 months old and 4 years 2 months old.
Time of videotaping was 6.0 hours for the younger
girl, 6.6 hours for the older girl, 8.4 hours for the
younger boy and 10.1 hours for the older boy. The
videotaping gathered information on detailed
micro-activity patterns of children to be used to
evaluate software for videotaped activities and
translation training methods.
The four children mouthed non-dietary objects an
average of 4.35% (range 1.41 to 7.67%) of the total
observation time, excluding the time during which
the children were out of the camera's view (Zartarian
et al., 1998). Objects mouthed included
bedding/towels, clothes, dirt, grass/vegetation, hard
surfaces, hard toys, paper/card, plush toy, and skin
(Zartarian et al., 1998). Frequency distributions for
the four children's non-dietary object contact
durations were reported to be similar in shape.
Reported hand-to-mouth contact presumably is a
subset of the object-to-mouth contacts described in
Zartarian et al. (1997a), and is described in Zartarian
et al. (1997b). The four children mouthed their hands
an average of 2.35% (range 1.0 to 4.4%) of
observation time (Zartarian et al., 1997b). The
researchers reported measures taken to assess
inter-observer reliability and several problems with
the video-transcription process.
This study's primary purpose was to develop and
evaluate the video-transcription methodology; a
secondary purpose was collection of mouthing
behavior data. The sample of children studied was
very small and not likely to be representative of the
national population. Thus, U.S. EPA did not judge it
to be suitable for consideration as a key study of
children's mouthing behavior. As with other video-
transcription studies, the presence of non-family
member videographers and a video camera may have
influenced the children's behavior.
4.4.2.3. Groot et al (1998)—Mouthing Behavior of
Young Children: An Observational Study
In this study, Groot et al. (1998) examined the
mouthing behavior of 42 Dutch children (21 boys and
21 girls) between the ages of 3 and 36 months in late
July and August 1998. Parent observations were
made of children in 36 families. Parents were asked
to observe their children 10 times per day for
15-minute intervals (i.e., 150 minutes total per day)
for two days and measure mouthing times with a
stopwatch. In this study, mouthing was defined as "all
activities in which objects are touched by mouth or
put into the mouth except for eating and drinking.
This term includes licking as well as sucking,
chewing and biting."
For the study, a distinction was made between
toys meant for mouthing (e.g., pacifiers, teething
rings) and those not meant for mouthing. Inter- and
intra-observer reliability was measured by trained
observers who co-observed a portion of observation
periods in three families and who co-observed and
repeatedly observed some video transcriptions made
of one child. Another quality assurance procedure
performed for the extrapolated total mouthing time
data was to select 12 times per hour randomly during
the entire waking period of four children during
1 day, in which the researchers recorded activities
and total mouthing times.
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Although the sample size was relatively small, the
results provided estimates of mouthing times, other
than pacifier use, during 1 day. The results were
extrapolated to the entire day based on the
150 minutes of observation per day, and the mean
value for each child for the 2 days of observations
was interpreted as the estimate for that child.
Table 4-22 shows summary statistics. The standard
deviation in all four age categories except the 3- to
6-month old children exceeded the estimated mean.
The 3 to 6 month children (N = 5) were estimated to
have mean non-pacifier mouthing durations of
36.9 minutes per day, with toys as the most
frequently mouthed product category, while the 6 to
12 month children (N= 14) were estimated to have
44 minutes per day (fingers most frequently
mouthed). The 12- to 18-month olds' (N = 12)
estimated mean non-pacifier mouthing time was
16.4 minutes per day, with fingers most frequently
mouthed, and 18- to 36-month olds' (N = 11)
estimated mean non-pacifier mouthing time was
9.3 minutes per day (fingers most frequently
mouthed).
One strength of this study is that the researchers
recognized that observing children might affect their
behavior and emphasized to the parents the
importance of making observations under conditions
that were as normal as possible. In spite of these
efforts, many parents perceived that their children's
behavior was affected by being observed and that
observation interfered with caregiving
responsibilities such as comforting children when
they were upset. Other limitations included a small
sample size that was not representative of the Dutch
population and that also may not be representative of
U.S. children. Technical problems with the
stopwatches affected at least 14 of 36 parents' data.
4.4.2.4. Smith and Norris (2003)—Reducing the
Risk of Choking Hazards: Mouthing
Behavior of Children Aged 1 Month to
5 Years/Norris and Smith (2002)—
Research Into the Mouthing Behavior of
Children up to 5 Years Old
Smith and Norris (2003) conducted a real-time
hand recording study of mouthing behavior among
236 children (111 males, 125 females) in the United
Kingdom (exact locations not specified) who were
from 1 month to 5 years old. Children were observed
at home by parents, who used stopwatches to record
the time that mouthing began, the type of mouthing,
the type of object being mouthed, and the time that
mouthing ceased. Children were observed for a total
of 5 hours over a 2-week period; the observation time
consisted of twenty 15-minute periods spread over
different times and days during the child's waking
hours. Parents also recorded the times each child was
awake and not eating meals so that the researchers
could extrapolate estimates of total daily mouthing
time from the shorter observation periods. Mouthing
was defined as licking/lip touching, sucking/trying to
bite and biting or chewing, with a description of each
category, together with pictures, given to parents as
guidance for what to record.
Table 4-23 shows the results of the study. While
no overall pattern could be found in the different age
groups tested, a Kruskal-Wallis test on the data for all
items mouthed indicated that there was a significant
difference between the age groups. Across all age
groups and types of items, licking and sucking
accounted for 64% of all mouthing behavior.
Pacifiers and fingers exhibited less variety on
mouthing behavior (principally sucking), while other
items had a higher frequency of licking, biting, or
other mouthing.
The researchers randomly selected 25 of the
236 children for a single 15-minute observation of
each child (total observation time across all children:
375 minutes), to compare the mouthing frequency
and duration data obtained according to the real-time
hand recording and the video-transcription
methodologies, as well as the reliability of parent
observations versus those made by trained
professionals. For this group of 25 children, the total
number of mouthing behavior events recorded by
video (160) exceeded those recorded by parents (114)
and trained observers (110). Similarly, the total
duration recorded by video (24 minutes and 15
seconds) exceeded that recorded by observers
(parents and trained observers both recorded identical
totals of 19 minutes and 44 seconds). The mean and
standard deviation of observed mouthing time were
both lower when recorded by video versus real-time
hand recording. The maximum observed mouthing
time also was lower (6 minutes and 7 seconds by
video vs. 9 minutes and 43 seconds for both parents
and trained observers).
The strengths of this study were its comparison of
three types of observation (i.e., parents, trained
observers, and videotaping), and its detailed reporting
of mouthing behaviors by type, object/item mouthed,
and age group. However, the children studied may
not be representative of U.S. children. In addition, the
study design or approach made the data less
applicable for exposure assessment purposes
(e.g., data on mouthing behavior that was intended to
be used in reducing the risk of choking hazards).
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4.4.2.5. AuYeungetal (2004)—Young Children's
Mouthing Behavior: An Observational
Study via Videotaping in a Primarily
Outdoor Residential Setting
As described in Section 4.3.1.5, AuYeung et al.
(2004) used a video-transcription methodology to
study a group of 38 children (20 females and
18 males; ages 1 to 6 years), 37 of whom were
selected randomly via a telephone screening survey
of a 300- to 400-square-mile portion of the San
Francisco, CA peninsula, along with one child
selected by convenience because of time constraints.
Families who lived in a residence with a lawn and
whose annual income was >$35,000 were asked to
participate. Videotaping took place between August
1998 and May 1999 for approximately 2 hours per
child. Videotaping by one researcher was
supplemented with field notes taken by a second
researcher who was also present during taping. Most
of the videotaping took place during outdoor play,
however, data were included for several children (one
child <2 years old and 8 children >2 years old) who
had more than 15 minutes of indoor play during their
videotaping sessions.
The videotapes were translated into ASCII
computer files using VirtualTimingDevice™ software
described in Zartarian et al. (1997a). Both frequency
(see Section 4.3.1.5 of this chapter) and duration
were analyzed. Between 5 and 10% of the translated
data files were randomly chosen for quality control
checks for inter-observer agreement. Ferguson et al.
(2006) described quality control aspects of the study
in detail.
For analysis, the mouthing contacts were divided
into indoor and outdoor locations and
16 object/surface categories. Mouthing durations
were analyzed by age and sex separately and in
combination. Mouthing contacts were defined as
contact with the lips, inside of the mouth, and/or the
tongue; dietary contacts were ignored. Table 4-24
shows mouthing durations (outdoor locations). For
the children in all age groups, the median duration of
each mouthing contact was 1 to 2 seconds,
confirming the observations of other researchers that
children's mouthing contacts are of very short
duration. For the one child observed that was
<24 months, the total indoor mouthing duration was
11.1 minutes/hour; for children >24 months, the
median indoor mouthing duration was
0.9 minutes/hour (see Table 4-25). For outdoor
environments, median contact durations for these age
groups decreased to 0.8 and 0.6 minutes/hour,
respectively (see Table 4-26).
Non-parametric tests, such as the Wilcoxon rank
sum test, were used for the data analyses. Both age
and sex were found to be associated with differences
in mouthing behavior. Girls' hand-to-mouth contact
durations were significantly shorter than for boys (p
= 0.04).
This study provides distributions of outdoor
mouthing durations with various objects and surfaces.
Although indoor mouthing data were also included in
this study, the results were based on a small number
of children (N = 9) and a limited amount of indoor
play. The sample of children may be representative of
certain socioeconomic strata in the study area, but is
not likely to be representative of the national
population. Because of the children's ages, the
presence of unfamiliar persons following the children
with a video camera may have influenced the
video-transcription methodology results.
4.5. MOUTHING PREVALENCE STUDIES
4.5.1. Stanek et al. (1998)—Prevalence of Soil
Mouthing/Ingestion Among Healthy
Children Aged 1 to 6
Stanek et al. (1998) characterized the prevalence
of mouthing behavior among healthy children based
on a survey response study of parents or guardians of
533 children (289 females, 244 males) ages 1 to
6 years old. Study participants were attendees at
scheduled well-child visits at three clinics in western
Massachusetts in August through October, 1992.
Participants were questioned about the frequency of
28 mouthing behaviors of the children over the
preceding month in addition to exposure time
(e.g., time outdoors, play in sand or dirt) and
children's characteristics (e.g., teething).
Table 4-27 presents the prevalence of reported
non-food ingestion/mouthing behaviors by child's
age as the percentage of children whose parents
reported the behavior in the preceding month. The
table includes a column of data for the 3 to <6 year
age category; this column was calculated by
U.S. EPA as a weighted mean value of the individual
data for 3-, 4-, and 5-year olds in order to conform to
the standardized age categories used in this
handbook. Among all the age groups, 1-year olds had
the highest reported daily sucking of fingers/thumb;
the proportion dropped for 2-year olds, but rose
slightly for 3- and 4-year olds and declined again
after age 4. A similar pattern was reported for more
than weekly finger/thumb sucking, while more than
monthly finger/thumb sucking showed a very slight
increase for 6-year olds. Reported pacifier use was
highest for 1-year olds and declined with age for
daily and more than weekly use; for more than
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monthly use of a pacifier several 6-year olds were
reported to use pacifiers, which altered the
age-declining pattern for the daily and more than
weekly reported pacifier use. A pattern similar to
pacifier use existed with reported mouthing of
teething toys, with highest reported use for 1-year
olds, a decline with age until age 6 when reported use
for daily, more than weekly, and more than monthly
use of teething toys increased.
The authors developed an outdoor mouthing rate
for each child as the sum of rates for responses to
four questions on mouthing specific outdoor objects.
Survey responses were converted to mouthing rates
per week, using values of 0, 0.25, 1, and 7 for
responses of never, monthly, weekly, and daily
ingestion. Reported outdoor soil mouthing behavior
prevalence was found to be higher than reported
indoor dust mouthing prevalence, but both behaviors
had the highest reported prevalence among 1-year old
children and decreased for children 2 years and older.
The investigators conducted principal component
analyses on responses to four questions relating to
ingestion/mouthing of outdoor objects in an attempt
to characterize variability. Outdoor
ingestion/mouthing rates constructed from the survey
responses were that children 1-year old were reported
to mouth or ingest outdoor objects 4.73 times per
week while 2- to 6-year olds were reported to mouth
or ingest outdoor objects 0.44 times per week. The
authors developed regression models to identify
factors related to high outdoor mouthing rates. The
authors found that children who were reported to play
in sand or dirt had higher outdoor object
ingestion/mouthing rates.
A strength of this study is that it was a large
sample obtained in an area with urban and semi-
urban residents within various socioeconomic
categories and with varying racial and ethnic
identities. However, difficulties with parents' recall of
past events may have caused either over-estimates or
under-estimates of the behaviors studied.
4.5.2. Warren et al. (2000)—Non-Nutritive
Sucking Behaviors in Preschool Children:
A Longitudinal Study
Warren et al. (2000) conducted a survey
response study of a non-random cohort of children
born in certain Iowa hospitals from early 1992 to
early 1995 as part of a study of children's fluoride
exposure. For this longitudinal study of children's
non-nutritive sucking behaviors, 1,374 mothers were
recruited at the time of their newborns' birth, and
more than 600 were active in the study until the
children were at least 3 years old. Survey questions
on non-nutritive sucking behaviors were administered
to the mothers when the children were 6 weeks, and
3, 6, 9, 12, 16, and 24 months old, and then yearly
after age 24 months. Questions were posed regarding
the child's sucking behavior during the previous 3 to
12 months.
The authors reported that nearly all children
sucked non-nutritive items, including pacifiers,
thumbs or other fingers, and/or other objects, at some
point in their early years. The parent-reported sucking
behavior prevalence peaked at 91% for 3 month old
children. At 2 years of age, a majority (53%) retained
a sucking habit, while 29% retained the habit at age
3 years and 21% at age 4 years. Parent-reported
pacifier use was 28% for 1-year olds, 25% for 2-year
olds, and 10% for 3-year olds. The authors cautioned
against generalizing the results to other children
because of study design limitations.
Strengths of this study were its longitudinal
design and the large sample size. A limitation is that
the non-random selection of original study
participants and the self-selected nature of the cohort
of survey respondents who participated over time
means that the results may not be representative of
other U.S. children of these ages.
4.6. REFERENCES FOR CHAPTER 4
AuYeung, W; Canales, R; Beamer, P; Ferguson, AC;
Leckie, JO. (2004) Young children's
mouthing behavior: An observational study
via videotaping in a primarily outdoor
residential setting. J Child Health 2(3-
4):271-295.
Barr, RG; Quek, VSH; Cousineau, D; Oberlander,
TK; Brian, JA.; Young, SN. (1994) Effects
of Intra-oral sucrose on crying, mouthing
and hand-mouth contact in newborn and six-
week-old infants. Dev Med Child Neurol
36:608-618.
Beamer, P; Key, ME; Ferguson, AC; Canales, RA;
Auyeung, W; Leckie, JO. (2008) Quantified
activity pattern data from 6 to 27-month-old
farmworker children for use in exposure
assessment. Environ Res 108(2):239-246.
Black, K; Shalat, SL; Freeman, NCG; Jimenez, M;
Donnelly, KC; Calvin, JA. (2005) Children's
mouthing and food-handling behavior in an
agricultural community on the US/Mexico
border. J Expo Anal Environ Epidemiol
15:244-251.
Page
4-18
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September 2011
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Chapter 4—Non-Dietary Ingestion Factors
Blass, EM; Pillion, TJ; Rochat, P; Hoffmeyer, LB;
Metzger, MA. (1989) Sensorimotor and
motivational determinants of hand-mouth
coordination in 1-3-day-old human infants.
Dev Psych 25(6):963-975.
Cannella, HI; O'Reilly, MF; Lancioni, GE. (2006)
Treatment of hand mouthing in individuals
with severe to profound developmental
disabilities: A review of the literature. Res
Devel Disabil 27(5):529-544.
Davis, S; Myers, PA; Kohler, E; Wiggins, C. (1995).
Soil Ingestion ingestion in children with
pica: Final Report. U.S. EPA Cooperative
Agreement CR 816334-01. Seattle, WA:
Fred Hutchinson Cancer Research Center.
Ferguson, AC; Canales, RA; Beamer, P; AuYeung,
W; Key, M; Munninghoff, A; Lee, KTW;
Robertson, A; Leckie, JO. (2006) Video
methods in the quantification of children's
exposures. J Expo Sci Environ Epidemiol
16:287-298.
Freeman, CG; Jimenez, M; Reed, KJ; Gurunathan, S;
Edwards, RD; Roy, A; Adgate, JL;
Pellizzari, ED; Quackenboss, J; Sexton, K;
Lioy, PJ. (2001) Quantitative analysis of
children's microactivity patterns: The
Minnesota children's pesticide exposure
study. J Expo Anal Environ Epidemiol
11:501-509.
Greene, MA. (2002) Mouthing times for children
from the observational study. Bethesda, MD:
U.S. Consumer Product Safety Commission.
Groot, ME; Lekkerkerk, MC; Steenbekkers, LPA.
(1998) Mouthing behavior of young
children: An observational study.
Wageningen, the Netherlands: Wageningen
Agricultural University.
Hore, P. (2003) Pesticide accumulation patterns for
child accessible surfaces and objects and
urinary excretion by children for two weeks
after a professional crack and crevice
application. Ph.D. Unpublished PhD
dissertation, Rutgers University and the
University of Medicine and Dentistry of
New Jersey, Newark, NJ.
Juberg, DR; Alfano, K; Coughlin, RJ; Thompson,
KM. (2001) An observational study of
object mouthing behavior by young
children. Pediatrics 107(1): 135-142.
Ko, S; Schaefer, P; Vicario, C; Binns, HJ. (2007)
Relationships of video assessments of
touching and mouthing behaviors during
outdoor play in urban residential yards to
parental perceptions of child behaviors and
blood lead levels. J Expo Sci Environ
Epidemiol 17:47-57.
Leckie, JO; Naylor, KA; Canales, RA; Ferguson, AC;
Cabrera, NL; Hurtado, AL; Lee, K.; Lin,
AY; Ramirez, JD; Vieira VM. (2000).
Quantifying children's microlevel activity
data from existing videotapes. Contract
Report Submitted to U.S. EPA, ORD,
NERL; Reference No. U2F112OT-RT 2000.
Lepow, ML; Bruckman, L; Gillette, M; Markowitz,
S; Robino, R; Kapish, J. (1975)
Investigations into sources of lead in the
environment of urban children. Environ Res
10:415-426.
Lew, AR; Butterworth, G. (1997) The development of
hand-mouth coordination in 2- to 5-month-
old infants: Similarities with reaching and
grasping. Infant Behav Dev 20(l):59-69.
Nicas, M; Best, D. (2008) A study quantifying the
hand-to-face contact rate and its potential
application to predicting respiratory tract
infection. J Occ EnvironHyg 5:347-352.
Norris, B; Smith, S. (2002) Research into the
mouthing behaviour of children up to 5
years old. London, UK: Consumer and
Competition Policy Directorate, Department
of Trade and Industry.
Reed, K; Jimenez, M; Freeman, N; Lioy, P. (1999)
Quantification of children's hand and
mouthing activities through a videotaping
methodology. J Expo Anal Environ
Epidemiol 9:513-520.
Rochat, P; Blass, EM; Hoffmeyer, LB. (1988)
Oropharyngeal control of hand-mouth
coordination in newborn infants. Dev Psych
24(4):459^63.
Shalat, SL; Donnelly, KC; Freeman, NCG; Calvin,
JA; Ramesh, S; Jimenez, M; Black, K;
Coutinho, C; Needham, LL; Barr, DB;
Ramirez, J. (2003) Non-dietary ingestion of
pesticides by children in an agricultural
community on the U.S./Mexico border:
Preliminary results. J Expos Anal Environ
Epidemiol 13:42-50.
Smith, SA; Norris, B. (2003). Reducing the risk of
choking hazards: mouthing behavior of
children aged 1 month to 5 years. Injury
Contr Safety Promo 10(3):145-154.
Exposure Factors Handbook
September 2011
Page
4-19
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Chapter 4—Non-Dietary Ingestion Factors
Stanek, EJ; Calabrese, EJ; Mundt, K; Pekow, P;
Yeatts, KB. (1998) Prevalence of soil
mouthing/ingestion among healthy children
aged 1 to 6. J Soil Contam 7(2):227-242.
Takaya, R; Yukuo, K; Bos, AF; Einspieler, C. (2003)
Preterm to early postterm changes in the
development of hand-mouth contact and
other motor patterns. Early Hum Dev
75(Suppl):S193-S202.
Tudella, E; Oishi, J; Puglia Bermasco, NH. (2000)
The effect of oral-gustatory, tactile-buccal,
and tactile-manual stimulation on the
behavior of the hands in newborns. Dev
Psychobiol 37:82-89.
Tulve, NS; Suggs, JC; McCurdy, T; Cohen Hubal,
EA; Moya, J. (2002) Frequency of mouthing
behavior in young children. J Expo Anal
Environ Epidemiol 12:259-264.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Office of Research and Development,
Washington, DC; EPA/630/P-03/003F.
U.S. EPA (Environmental Protection Agency). (2009)
Standard operating procedures (SOPs) for
residential exposure assessment. Draft
technical guidelines. Office of Pesticide
Programs, Office of Prevention, Pesticides,
and Toxic Substances, Washington, DC.
Warren, JJ; Levy, SM; Nowak, AJ; Tang. S. (2000)
Non-nutritive sucking behaviors in
preschool children: A longitudinal study.
Pediatr Dent 22(3): 187-191.
Xue, J; Zartarian, V; Moya, J; Freeman, N; Beamer,
P; Black, K; Tulve, N; Shalat, S. (2007) A
meta-analysis of children's hand-to-mouth
frequency data for estimating non-dietary
ingestion exposure. Risk Anal
27(2) :411-420.
Xue, J; Zartarian, V; Tulve, N; Moya, J; Freeman, N;
AuYeung, W; Beamer, P. (2010) A meta-
analysis of children's object-to-mouth
frequency data for estimating non-dietary
ingestion exposure. J Expo Sci Environ
Epidemiol 20:536-545.
Zartarian, VG; Streicker, J; Rivera, A; Cornejo, CS;
Molina, S; Valadez, OF; Leckie, JO. (1995)
A pilot study to collect micro-activity data
of two- to four-year-old farm labor children
in Salinas Valley, California. J Expo Anal
Environ Epidemiol 5(l):21-34.
Zartarian VG; Ferguson AC; Ong, CG; Leckie J.
(1997a) Quantifying videotaped activity
patterns: Video translation software and
training methodologies. J Expo Anal
Environ Epidemiol 7(4):535-542.
Zartarian VG; Ferguson A; Leckie J. (1997b)
Quantified dermal activity data from a four-
child pilot field study. J Expo Anal Environ
Epidemiol 7(4):543-553.
Zartarian, VG; Ferguson, AC; Leckie, JO. (1998)
Quantified mouthing activity data from a
four-child pilot field study. J Expo Anal
Environ Epidemiol 8(4):543-553.
Page
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Chapter 4—Non-Dietary Ingestion Factors
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-Transcription
Category
Hand to mouth
Object to mouth
Minimum
0.4
0
Mean
9.5
16.3
Median
8.5
3.6
90th Percentile
20.1
77.1
Maximum
25.7
86.2
Source: Reed etal., 1999.
Table 4-4.
Age Group (years)
3
4
5
6
7
8
9
10
11
12
= No data.
Survey-Reported Percent of 168
Thumbs/Fingers in Mouth
71
63
33
30
28
33
43
38
33
33
Minnesota Children Exhibiting Behavior, by Age
Toes in Mouth Non-Food Items in Mouth
29 71
0 31
20
29
28
40
38
38
48
17
Source: Freeman et al, 2001 .
Table 4-5. Video-Transcription Median (Mean) Observed Mouthing in
(contacts/hour), by Age
Age Group (years) N Object to Moutha
3 to 4 3 3 (6)
5 to 6 7 0(1)
7 to 8 4 0(1)
10 to 12 5 0(1)
19 Minnesota Children
Hand to Mouth
3.5 (4)
2.5 (8)
3(5)
2(4)
a Kruskal Wallis test comparison across four age groups,/) = 0.002.
N = Number of observations.
Source: Freeman et al., 2001 .
Exposure Factors Handbook Page
September 2011 4-21
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Table 4-6. Variability
Variable
Mouth to body
Mouth to hand
Mouth to
surface
Mouth to toy
Total events
AP
186
186
186
186
186
All
Meanb
8
16
4
27
56
Subjects
Median
2
11
1
18
44
in Objects Mouthed by Washington State
95% CI°
2-3
9-14
0.8-1.2
14-23
36-52
<24
jV* Meanb
69 10
69 18
69 7
69 45
69 81
a Number of observations.
b Arithmetic mean.
0 The 95% confidence intervals (CI) apply to median. Values were calculated in loj
Source: Tulve et al
, 2002.
Months
Median
4
12
5
39
73
Children (contacts/hour"
>24
95% CIC jV Meanb
3-6
9-16
3-8
31-48
60-88
117
117
117
117
117
7
16
2
17
42
Months
Median
1
9
1
9
31
95% CIC
0.8-1.3
7-12
0.9-1.1
7-12
25-39
*s and converted to original units.
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-7. Indoor Mouthing
Age Group
13 to 84 months
<24 months
>24 months
Frequency
N
9
1
8
(Contacts per contacts/hour),
Age
Statistic
Mean
Median
Range
-
Mean
Median
Range
Video-Transcription
of 9 Children,
by
Hand Total Non-Dietary"
20.5
14.8
2.5-70.4
73.5
13.9
13.3
2.2-34.1
29.6
22.1
3.2-82.2
84.8
22.7
19.5
2.8-51.3
a Object/surface categories mouthed indoors included: clothes/towels, hands, metal, paper/wrapper, plastic, skin, toys,
and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Table 4-8. Outdoor Mouthing Frequency (Contacts per contacts/hour), Video-Transcription of 38 Children,
by Age
Age Group N
13 to 84 months 38
<24 months 8
>24 months 30
Statistic
Mean
5th percentile
25th percentile
50th percentile
75th percentile
95th percentile
99th percentile
Mean
Median
Range
Mean
5th percentile
25th percentile
50th percentile
75th percentile
95th percentile
99th percentile
a Object/surface categories mouthed outdoors included: animal,
paper/wrapper, plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hand Total Non-Dietary3
11.7
0.4
4.4
8.4
14.8
31.5
47.6
13.0
7.0
1.3-47.7
11.3
0.2
4.7
8.6
14.8
27.7
39.5
clothes/towels, fabric, hands, metal,
18.3
0.8
9.2
14.5
22.4
51.7
56.6
20.4
13.9
6.2-56.4
17.7
0.6
7.6
14.6
22.4
43.8
53.0
non-dietary water,
Exposure Factors Handbook
September 2011
Page
4-23
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-9. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD), by Age
Age N
7 to 12 months 13
13 to 24 months 12
25 to 36 months 18
37 to 53 months 9
Hand to Mouth
(contact/hour)
Median (Mean ± SD) Frequency
14 (19. 8 ±14. 5)
13. 3 (15. 8 ±8.7)
9.9(11. 9 ±9.3)
19.4 (22.1 ±22.1)
Object to Mouth
(contact/hour)
Median (Mean ± SD) Frequency
18.1 (24.4 ±11. 6)
8.4 (9.8 ±6. 3)
5.5 (7.8 ±5.8)
8.4 (10.1 ±12.4)
N = Number of subjects.
SD = Standard deviation.
Source: Black et al., 2005.
Table 4-10. Indoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions from Various Studies,
by Age
Weibull
Age Group Scale
Parameter
3 to <6 months 1.28
6 to <12 months 1.02
1 to <2 years 0.91
2 to <3 years 0.76
3 to <6 years 0.75
6to
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-12. Object/Surface to
Object/Surface
Animal
Body
Clothes/towel
Fabric
Floor
Food
Footwear
Hand/mouth
Metal
Non-dietary water
Paper/wrapper
Plastic
Rock/brick
Toy
Vegetation
Wood
Non-dietary object1
All objects/surfaces
Range
-
0.0-5.0
0.3-13.6
0.0-5.7
0.0-1.3
2.3-68.3
0.0-8.9
2.0-62.1
0.0-2.1
0.0-13.6
0.0-14.3
-
0.3-48.4
0.0-18.2
0.0-3.9
6.2-82.3
244-145.9
Mouth Contact Frequency for Infants and
Mean
-
1.5
5.4
1.1
0.2
28.9
0.7
18.4
0.3
2.1
2.0
-
14.7
0.8
0.5
29.2
76.5
Toddlers (events/hour)
(TV =23)
Percentiles
5m
-
0.0
1.1
0.0
0.0
11.1
0.0
6.6
0.0
0.0
0.0
-
1.9
0.0
0.0
8.1
28.7
a All object designations except for food and hand/mouth
No mouth contact with these objects/surfaces occurred.
Source: Beamer et al
,2008.
25th
-
0.4
2.6
0.0
0.0
17.8
0.0
10.0
0.0
0.3
0.4
-
6.8
0.0
0.0
15.9
58.7
50th
-
0.8
3.6
0.3
0.0
28.2
0.0
15.2
0.0
0.8
1.4
-
12.5
0.0
0.0
27.2
77.4
represent non-dietary
75th
-
2.4
6.9
2.2
0.4
34.8
0.0
22.8
0.1
2.1
2.3
-
20.6
0.0
0.5
38.0
94.5
objects.
95th
-
4.0
13.2
3.3
1.0
53.7
5.7
44.7
1.3
7.2
5.1
-
34.9
0.0
1.8
64.0
123.1
99th
-
4.8
13.5
5.2
1.2
65.2
8.3
58.6
1.9
12.2
12.3
-
45.6
14.2
3.4
78.8
141.2
Exposure Factors Handbook Page
September 2011 4-25
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Table 4-13. Distributions Mouthing Frequency and Duration for Non-Dietary Objects with Significant Differences (p < 0.05) Between Infants and
Toddlers
Object/Surface
Clothes/towel
Paper/wrapper
Toy
Non-dietary
object/surface
Infant (6 to 13 months) Mouthing Frequency (contacts/hour)
N Range Mean 5th 25th 50th 75th
13 2-13.3 6.8 2.7 4.8 6.3 7.2
13 0.0-7.2 1.1 0.0 0.2 0.7 0.8
13 6.5-48.4 21.1 7.3 14.4 20.2 25.5
13 14-82.3 37.8 20.0 28.3 35.2 38.6
95th
12.7
4.3
40.8
72.8
99th
12.1
6.6
46.9
64.0
Toddler (20-26 months) Mouthing Frequency (contacts/hour)
Clothes/towel
Paper/wrapper
Toy
Other non-dietary
object/surface3
N Range Mean 5th 25th 50th 75th
10 0.3-13.6 3.5 0.6 2.0 2.6 3.6
10 0.3-12.6 6.3 1.0 2.8 5.4 9.6
10 0.3-13.6 3.5 0.6 2.0 2.6 3.6
10 6.2-41.2 18.0 7.0 9.4 15.9 22.0
95th
9.1
12.5
9.1
35.2
a Excludes "clothes/towel," "paper/wrapper," and "toys;" includes all other non-dietary
No significant difference between infants and toddlers for this object/surface category
Source: Beamer et al., 2008 supplemental data.
99th
12.7
12.6
12.7
40.5
Infant (6 to 13
Range
0.0-0.7
0.7-17.9
1.1-18.4
Mean
0.1
3.6
4.5
months) Mouthing Duration (minutes/hour)
5th
0.0
0.8
1.2
25th
0.0
1.2
2.2
50th
0.0
1.7
2.8
75*
0.1
2.8
4.1
95th
0.4
11.6
12.6
99th
0.6
16.6
17.2
Toddler (20-26 months) Mouthing Duration (minutes/hour)
Range
0.0-0.8
0.0-6.8
0.3-6.9
objects/surfaces
Mean
0.2
1.5
2.1
5*
0.0
0.1
0.4
25th
0.0
0.2
0.7
50th
0.1
0.5
1.3
75th
0.2
0.7
1.8
95th
0.6
6.1
6.3
99th
0.7
6.6
6.7
shown in Table 4-12.
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-14. Indoor Object-to-Mouth Frequency (contacts/hour) Weibull
by Age
Weibull
Age Group Scale
Parameter
3 to <6 months 9.83
6 to <12 months 22.72
1 to <2 years 15.54
2 to <3 years 10.75
3 to <6 years 6.90
6to
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-16. Survey-Reported Mouthing Behaviors for 92 Washington State Children
Never
N
Hand/foot in mouth 4
Pacifier 74
Mouth on object 14
Non-food in mouth 5
Eat dirt/sand 37
N = Number of subjects.
Source: Davis etal., 1995.
%
4
81
15
5
40
Seldom
N
27
6
30
25
39
%
30
7
33
27
43
Occasionally
N
23
2
25
33
11
%
25
2
27
36
12
Frequently
N
31
9
19
24
4
%
34
10
21
26
4
Always
N
4
1
1
5
1
%
4
1
1
5
1
Unknown
N
3
0
3
0
0
%
3
0
3
0
0
Table 4-17.
Subject
1
2
3
4
5
6
7
8
9
10
Mean
Standard
Deviation
Number of Hand Contacts Observed
Continuous 3-Hour Period
Eye
0
4
2
1
10
13
17
6
9
12
7.4
5.7
in Adults
Lip Nostril
0
2
12
1
22
33
15
31
52
72
24
24
3
1
4
20
15
8
27
28
30
20
16
11
During a
Total
3
7
18
22
47
54
59
65
91
104
47
35
Source: Nicas and Best, 2008.
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-18. Estimated
Object Type
Pacifier
Teether
Plastic toy
Other objects
Daily Mean Mouthing Times of New York State Children, for Pacifiers and Other
Objects
Age 0 to
All Children
Minutes/Day
108 (AT =107)
6(N= 107)
17(Af=107)
9(N= 107)
18 Months
Only Children Who
Mouthed Object"
Minutes/Day
221 (N= 52)
20(jV=34)
28(W=66)
22 (AT =46)
Age 19 to 36 Months
All Children
Minutes/Day
126(Af=110)
0 (AT =110)
2 (AT =110)
2 (AT =110)
a Refers to means calculated for the subset of the sample children who mouthed the object
from the calculation of the mean).
jV = Number of children.
Source: Juberg et al., 2001 .
Only Children Who
Mouthed Object"
Minutes/Day
462(W=52)
30 (W = 1)
11(AT=21)
15(W=18)
stated (zeroes are eliminated
Table 4-19. Percent of Houston-Area
Object Category
All objects
Pacifier
Non-pacifier
Soft plastic food content item
Anatomy
Non-soft plastic toy, teether, and rattle
Other items
and Chicago-Area Children
Child's Age
All Ages <1 Year
100 100
27 43
100 100
28 13
99 100
91 94
98 98
Observed Mouthing, by
1 to 2 Years
100
27
100
30
97
91
97
Category and
2 to 3 Years
100
10
100
41
100
86
98
Source: Greene, 2002.
Exposure Factors Handbook Page
September 2011 4-29
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers
Age
Age Group
Mean (SD)
Median
95th Percentile
(minutes/hour), by
99th Percentile
All Items3
3 to <12 months
12 to <24 months
24 to <36 months
10.5 (7.3)
7.3 (6.8)
5.3(8.2)
9.6
5.5
2.4
26.2
22.0
15.6
39.8
28.8
47.8
Non-Pacifierb
3 to <12 months
12 to <24 months
24 to <36 months
7.1 (3.6)
4.7(3.7)
3.5(3.6)
6.9
3.6
2.3
13.1
12.8
12.8
14.4
18.9
15.6
All Soft Plastic Itemc
3 to <12 months
12 to <24 months
24 to <36 months
0.5 (0.6)
0.4 (0.4)
0.4 (0.6)
0.1
0.2
0.1
1.8
1.3
1.6
2.5
1.9
2.9
Soft Plastic Item Not Food Contact
3 to <12 months
12 to <24 months
24 to <36 months
0.4 (0.6)
0.3 (0.4)
0.2 (0.4)
0.1
0.1
0.0
1.8
1.1
1.3
2.0
1.5
1.8
Soft Plastic Toy, Teether, and Rattle
3 to <12 months
12 to <24 months
24 to <36 months
0.3 (0.5)
0.2 (0.3)
0.1 (0.2)
0.1
0.0
0.0
1.8
0.9
0.2
2.0
1.3
1.6
Soft Plastic Toy
3 to <12 months
12 to <24 months
24 to <36 months
0.1 (0.3)
0.2 (0.3)
0.1 (0.2)
0.0
0.0
0.0
0.7
0.9
0.2
1.1
1.3
1.6
Soft Plastic Teether and Rattle
3 to <12 months
12 to <24 months
24 to <36 months
0.2 (0.4)
0.0(0.1)
0.0(0.1)
0.0
0.0
0.0
1.0
0.1
0.0
2.0
0.6
1.0
Other Soft Plastic Item
3 to <12 months
12 to <24 months
24 to <36 months
0.1 (0.2)
0.1(0.1)
0.1 (0.3)
0.0
0.0
0.0
0.8
0.4
0.5
1.0
0.6
1.4
Soft Plastic Food Contact Item
3 to <12 months
12 to <24 months
24 to <36 months
0.0 (0.2)
0.1 (0.2)
0.2 (0.4)
0.0
0.0
0.0
0.3
0.7
1.2
0.9
1.2
1.9
Anatomy
3 to <12 months
12 to <24 months
24 to <36 months
2.4 (2.8)
1.7(2.7)
1.2(2.3)
1.5
0.8
0.4
10.1
8.3
5.1
12.2
14.8
13.6
Page
4-30
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers (minutes/hour), by
Age (continued)
Age Group Mean(SD) Median 95th Percentile 99th Percentile
Non-Soft Plastic Toy, Teether, and Rattle
3 to <12 months
12 to <24 months
24 to <36 months
1.8(1.8)
0.6 (0.8)
0.2 (0.4)
1.3
0.3
0.1
6.5
1.8
0.9
7.7
4.6
2.3
Other Item
3 to <12 months
12 to <24 months
24 to <36 months
2.5(2.1)
2.1 (2.0)
1.7(2.6)
2.1
1.4
0.7
7.8
6.6
7.1
8.1
9.0
14.3
Pacifier
3 to <12 months
12 to <24 months
24 to <36 months
3.4 (6.9)
2.6 (6.5)
1.8(7.9)
0.0
0.0
0.0
19.5
19.9
4.8
37.3
28.6
46.3
Object category "all items" is subdivided into pacifiers and non-pacifiers.
Object category "non-pacifiers" is subdivided into all soft plastic items, anatomy (which includes hair, skin, fingers
and hands), non-soft plastic toys/teethers/rattles, and other items.
Object category "all soft plastic items" is subdivided into food contact items, non-food contact items (toys, teethers,
and rattles) and other soft plastic.
SD = Standard deviation.
Source: Greene, 2002.
Exposure Factors Handbook Page
September 2011 4-31
-------
Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-21. Object/Surface to Hands and Mouth Contact Duration for Infants and Toddlers (minutes/hour)
(TV =23)
Object/Surface
Animal
Body
Clothe/towel
Fabric
Floor
Food
Footwear
Hand/mouth
Metal
Non-dietary water
Paper/wrapper
Plastic
Rock/brick
Toys
Vegetation
Wood
Non-dietary object3
All objects/surfaces
Range
-
0.0-0.3
0.0-0.9
0.0-0.2
0.0-0.1
0.3-15.0
0.0-1.4
0.2-5.4
0.0-0.2
-
0.0-0.8
0.0-0.6
-
0.0-17.9
0.0-0.2
0.0-0.3
0.3-18.4
2.2-33.6
Mean
-
0.1
0.3
0.0
0.0
4.7
0.1
1.4
0.0
-
0.1
0.1
-
2.7
0.0
0.0
3.5
9.6
Percentiles
5*
-
0.0
0.0
0.0
0.0
0.4
0.0
0.4
0.0
-
0.0
0.0
-
0.1
0.0
0.0
0.5
2.4
a All object designations except for food and hand/mouth
No mouth contact with these objects/surfaces occurred.
Source: Beamer et
al., 2008.
25th
-
0.0
0.1
0.0
0.0
1.8
0.0
0.5
0.0
-
0.0
0.0
-
0.6
0.0
0.0
1.2
5.1
50*
-
0.0
0.2
0.0
0.0
3.8
0.0
1.2
0.0
-
0.0
0.1
-
1.2
0.0
0.0
2.2
8.8
represent non-dietary
75th
-
0.1
0.4
0.1
0.0
6.6
0.0
1.8
0.0
-
0.1
0.1
-
2.8
0.0
0.0
3.9
12.0
objects.
95th
-
0.3
0.7
0.2
0.1
10.9
0.3
3.7
0.1
-
0.7
0.5
-
7.4
0.0
0.2
8.5
17.1
99th
-
0.3
0.9
0.2
0.1
14.1
1.1
5.0
0.2
-
0.8
0.6
-
15.6
0.2
0.3
16.3
30.0
Page
4-32
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-22. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without Pacifier
(minutes/day), by Age
Age Group
3 to 6 months
6 to 12 months
12 to 18 months
18 to 3 6 months
N
5
14
12
11
Note: The object most mouthed in all age
mouthed toys.
N = Number of children.
SD = Standard deviation.
Source: Grootetal., 1998.
Mean
36.9
44
16.4
9.3
groups was the fin£
SD
19.1
44.7
18.2
9.8
>ers, except for the 6 to
Minimum Maximum
14.5
2.4
0
0
12 month
67
171.5
53.2
30.9
group, which mostly
Exposure Factors Handbook
September 2011
Page
4-33
-------
Table
4-23. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, and Other Objects
(hours:minutes:seconds)
Age Group
Item
Mouthed
N =
Dummy (pacifier)
Finger
Toy
Other object
Not recorded
Total (all objects)
1 to 3 3 to 6
months months
9 14
0:47:13 0:27:45
0:18:22 0:49:03
0:00:14 0:28:20
0:05:14 0:12:29
0:00:45 0:00:24
1:11:48 1:57:41
6 to 9
months
15
0:14:36
0:16:54
0:39:10
0:24:30
0:00:00
1:35:11
9 to 12
months
17
0:41:39
0:14:07
0:23:04
0:16:25
0:00:01
1:35:16
12 to 15
months
16
1:00:15
0:08:24
0:15:18
0:12:02
0:00:02
1:36:01
15 to 18
months
14
0:25:22
0:10:07
0:16:34
0:23:01
0:00:08
0:15:13
18 to 21
Months
16
1:09:02
0:18:40
0:11:07
0:19:49
0:00:11
1:58:49
21 to 24
months
12
0:25:12
0:35:34
0:15:46
0:12:53
0:14:13
1:43:39
2
years
39
0:32:55
0:29:43
0:12:23
0:21:46
0:02:40
1:39:27
3
years
31
0:48:42
0:34:42
0:11:37
0:15:16
0:00:01
1:50:19
4
years
29
0:16:40
0:19:26
0:03:11
0:10:44
0:00:05
0:50:05
5
years
24
0:00:20
0:44:06
0:01:53
0:10:00
0:02:58
0:59:17
jV = Number of children in sample.
Source: Smith and Norris, 2003.
Q
I
I
I
I
»r
§
^ 5_
a a,
ri S<
-------
Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-24. Outdoor Median
Age Group
13 to 84 months
<24 months
>24 months
Mouthing Duration (seconds/contact),
Age
jV Statistic
Mean
5th percentile
25th percentile
38 50th percentile
75th percentile
95th percentile
99th percentile
Mean
8 Median
Range
Mean
5th percentile
25th percentile
30 50th percentile
75th percentile
95th percentile
99th percentile
Video-Transcription
Hand
3.5
0
1
1
2
12
41.6
9
3
0 to 136
2
0
1
1
2
5
17.4
of 38 Children, by
Total Non-Dietary3
3.4
0
1
1
3
11
40
7
2
0 to 136
2.4
0
1
1
2
7
24.6
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric, hands, metal, non-dietary water,
paper/wrapper, plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al, 2004.
Table 4-25. Indoor Mouthing Duration (minutes/hour), Video-Transcription of Nine Children with >15
minutes in View Indoors
Age Group N
13 to 84 months 9
<24 months 1
>24 months 8
a Object/surface categories mouthed
and wood.
jV = Number of subjects.
Source: AuYeung et al., 2004.
Statistic
Mean
Median
Range
Hand
1.8
0.7
0-10.7
Observation 10.7
Mean
Median
Range
indoors included:
0.7
0.7
0-1.9
Total Non-Dietary3
2.3
0.9
0-11.1
11.1
1.2
0.9
0-3.7
clothes/towels, hands, metal, paper/wrapper, plastic, skin, toys,
Exposure Factors Handbook
September 2011
Page
4-35
-------
Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-26. Outdoor Mouthing Duration (minutes/hour), Video-Transcription of 38 Children, by Age
Age Group N Statistic
Mean
5th percentile
25th percentile
50th percentile
13 to 84 months 38 75* percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25* percentile
,,. . ,. 0 50th percentile
<24 months 8 -,cth 4-1
75 percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25 percentile
,. ,. ,,„ Median
>24 months 30 _c(h ,.,
75 percentile
95th percentile
99th percentile
Range
Hand
0.9
0
0.1
0.2
0.6
2.6
11.2
0-15.5
2.7
0
0.2
0.4
1.5
11.5
14.7
0-15.5
0.4
0
0.1
0.2
0.4
1.2
2.2
0-2.4
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
paper/wrapper, plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al, 2004.
Total Non-Dietary3
1.2
0
0.2
0.6
1.2
2.9
11.5
0-15.8
3.1
0.2
0.2
0.8
3.1
11.7
15
0.2-15.8
0.7
0
0.2
0.6
1
2.1
2.5
0-2.6
hands, metal, non-dietary water,
Page Exposure Factors Handbook
4-36 September 2011
-------
Exposure Factors Handbook
Chapter 4—Non-Dietary Ingestion Factors
Table 4-27. Reported Daily
Object or Substance Mouthed
or Ingested
Grass, leaf, flower
Twig, stick, woodchip
Teething toy
Other toy
Blanket, cloth
Shoes, Footwear
Clothing
Crib, chair, furniture
Paper, cardboard, tissue
Crayon, pencil, eraser
Toothpaste
Soap, detergent, shampoo
Plastic, plastic wrap
Cigarette butt, tobacco
Suck finger/thumb
Suck feet or toe
Bite nail
Use pacifier
Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
Behaviors
Percent of Children Reported to Mouth/Ingest Daily
1 Year
N=ni
16
12
44
63
29
20
25
13
28
19
52
15
7
4
44
8
2
20
a Weighted mean of 3-, 4-, and 5-year-olds'
used in this handbook.
Source: Staneket al, 1998.
2 Years
jV=70
0
0
6
27
11
1
7
3
9
17
87
14
4
0
21
1
7
6
data calculated by
3 to <6 Yearsa 6
jV=265 A
1
0
2
12
10
0
9
1
5
5
89
2
1
1
24
0
10
2
U.S. EPA to conform to
Years
r=22
0
0
9
5
5
0
14
0
5
18
82
0
0
0
14
0
14
0
All Years
A' =528
6
4
17
30
16
7
14
5
13
12
77
8
3
2
30
3
7
9
standardized age categories
Exposure Factors Handbook
September 2011
Page
4-37
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
TABLE OF CONTENTS
LIST OF TABLES 5-iw
LIST OF FIGURES 5-v
5. SOIL AND DUST INGESTION 5-1
5.1. INTRODUCTION 5-1
5.2. RECOMMENDATIONS 5-3
5.3. KEY AND RELEVANT STUDIES 5-7
5.3.1. Methodologies Used in Key Studies 5-7
5.3.1.1. Tracer Element Methodology 5-7
5.3.1.2. Biokinetic Model Comparison Methodology 5-8
5.3.1.3. Activity Pattern Methodology 5-8
5.3.2. Key Studies of Primary Analysis 5-9
5.3.2.1. Vermeer and Frate (1979)—Geophagia in Rural Mississippi: Environmental and
Cultural Contexts and Nutritional Implications 5-9
5.3.2.2. Calabrese et al. (1989)—How Much Soil Do Young Children Ingest: An
Epidemiologic Study/Barnes (1990)—Childhood Soil Ingestion: How Much
Dirt Do Kids Eat?/Calabrese et al. (1991)—Evidence of Soil-Pica Behaviour
and Quantification of Soil Ingested 5-9
5.3.2.3. Van Wijnen et al. (1990)—Estimated Soil Ingestion by Children 5-10
5.3.2.4. Davis et al. (1990)—Quantitative Estimates of Soil Ingestion in Normal
Children between the Ages of 2 and 7 Years: Population-based Estimates Using
Aluminum, Silicon, and Titanium as Soil Tracer Elements 5-10
5.3.2.5. Calabrese et al. (1997a)—Soil Ingestion Estimates for Children Residing on a
Superfund Site 5-11
5.3.2.6. Stanek et al. (1998)—Prevalence of Soil Mouthing/Ingestion among Healthy
Children Aged One to Six/Calabrese et al. (1997b)—Soil Ingestion Rates in
Children Identified by Parental Observation as Likely High Soil Ingesters....5-12
5.3.2.7. Davis and Mirick (2006)—Soil ingestion in children and adults in the same
family 5-12
5.3.3. Key Studies of Secondary Analysis 5-13
5.3.3.1. Wong (1988)—The Role of Environmental and Host Behavioral Factors in
Determining Exposure to Infection with Ascaris lumbricoides and Trichuris
Trichiura/Calabrese and Stanek (1993)—Soil Pica: Not a Rare Event 5-13
5.3.3.2. Calabrese and Stanek (1995)—Resolving Intertracer Inconsistencies in Soil
Ingestion Estimation 5-14
5.3.3.3. Stanek and Calabrese (1995a)—Soil Ingestion Estimates for Use in Site
Evaluations Based on the Best Tracer Method 5-14
5.3.3.4. Hogan et al. (1998)—Integrated Exposure Uptake Biokinetic Model for Lead in
Children: Empirical Comparisons with Epidemiologic Data 5-15
5.3.3.5. Ozkaynak et al. (2010)—Modeled Estimates of Soil and Dust Ingestion Rates
for Children 5-16
5.3.4. Relevant Studies of Primary Analysis 5-16
5.3.4.1. Dickins and Ford (1942)—Geophagy (Dirt Eating) Among Mississippi Negro
Schoolchildren 5-17
5.3.4.2. Ferguson and Keaton (1950)—Studies of the Diets of Pregnant Women in
Mississippi: II Diet Patterns 5-17
5.3.4.3. Cooper (1957)—Pica: A Survey of the Historical Literature as well as Reports
from the Fields of Veterinary Medicine and Anthropology, the Present Study of
Pica in Young Children, and a Discussion of Its Pediatric and Psychological
Implications 5-17
5.3.4.4. Barltrop (1966)—The Prevalence of Pica 5-17
5.3.4.5. Bruhn and Pangborn (1971)—Reported Incidence of Pica among Migrant
Families 5-17
Exposure Factors Handbook Page
September 2011 5-i
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
TABLE OF CONTENTS (continued)
5.3.4.6. Robischon (1971)—Pica Practice and Other Hand-Mouth Behavior and
Children's Developmental Level 5-18
5.3.4.7. Bronstein and Dollar (1974)—Pica in Pregnancy 5-18
5.3.4.8. Hook (1978)—Dietary Cravings and Aversions During Pregnancy 5-18
5.3.4.9. Binder et al. (1986)—Estimating Soil Ingestion: The Use of Tracer Elements in
Estimating the Amount of Soil Ingested by Young Children 5-18
5.3.4.10. Clausing et al. (1987)—A Method for Estimating Soil Ingestion by Children5-19
5.3.4.11. Calabrese et al. (1990)—Preliminary Adult Soil Ingestion Estimates: Results of
a Pilot Study 5-20
5.3.4.12.Cooksey (1995)—Pica and Olfactory Craving of Pregnancy: How Deep Are the
Secrets? 5-20
5.3.4.13.Smulianetal. (1995)—Pica in a Rural Obstetric Population 5-20
5.3.4.14.Grigsby etal. (1999)—Chalk Eating in Middle Georgia: A Culture-Bound
Syndrome of Pica? 5-21
5.3.4.15. Ward and Kutner (1999)—Reported Pica Behavior in a Sample of Incident
Dialysis Patients 5-21
5.3.4.16. Simpson et al. (2000)—Pica During Pregnancy in Low-Income Women Born in
Mexico 5-21
5.3.4.17.Obialo et al. (2001)—Clay Pica Has No Hematologic or Metabolic Correlate to
Chronic Hemodialysis Patients 5-22
5.3.4.18. Klitzman et al. (2002)—Lead Poisoning Among Pregnant Women in New York
City: Risk Factors and Screening Practices 5-22
5.3.5. Relevant Studies of Secondary Analysis 5-22
5.3.5.1. Stanek and Calabrese (1995b)—Daily Estimates of Soil Ingestion in Children5-22
5.3.5.2. Calabrese and Stanek (1992b)—What Proportion of Household Dust is Derived
from Outdoor Soil? 5-23
5.3.5.3. Calabrese et al. (1996)—Methodology to Estimate the Amount and Particle Size
of Soil Ingested by Children: Implications for Exposure Assessment at Waste
Sites 5-23
5.3.5.4. Stanek et al. (1999)—Soil Ingestion Estimates for Children in Anaconda Using
Trace Element Concentrations in Different Particle Size Fractions 5-23
5.3.5.5. Stanek and Calabrese (2000)—Daily Soil Ingestion Estimates for Children at a
Superfund Site 5-23
5.3.5.6. Stanek et al. (2001a)—Biasing Factors for Simple Soil Ingestion Estimates in
Mass Balance Studies of Soil Ingestion 5-23
5.3.5.7. Stanek et al. (200Ib)—Soil Ingestion Distributions for Monte Carlo Risk
Assessment in Children 5-24
5.3.5.8. Von Lindern et al. (2003)—Assessing Remedial Effectiveness Through the
Blood Lead: Soil/Dust Lead Relationship at the Bunker Hill Superfund Site in
the Silver Valley of Idaho 5-24
5.3.5.9. Gavrelis et al. (2011)—An Analysis of the Proportion of the U.S. Population that
Ingests Soil or Other Non-Food Substances 5-24
5.4. LIMITATIONS OF STUDY METHODOLOGIES 5-25
5.4.1. Tracer Element Methodology 5-25
5.4.2. Biokinetic Model Comparison Methodology 5-28
5.4.3. Activity Pattern Methodology 5-28
5.4.4. Key Studies: Representativeness of U.S. Population 5-29
5.5. SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES 5-31
5.6. DERIVATION OF RECOMMENDED SOIL AND DUST INGESTION VALUES 5-31
5.6.1. Central Tendency Soil and Dust Ingestion Recommendations 5-31
5.6.2. Upper Percentile, Soil Pica, andGeophagy Recommendations 5-33
Page Exposure Factors Handbook
5-ii September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
TABLE OF CONTENTS (continued)
5.7. REFERENCES FOR CHAPTER 5 5-34
Exposure Factors Handbook Page
September 2011 5-iii
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
LIST OF TABLES
Table 5-1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion (mg/day) 5-5
Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust 5-6
Table 5-3. Soil, Dust, and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
Children 5-39
Table 5-4. Amherst, Massachusetts Soil-Pica Child's Daily Ingestion Estimates by Tracer and by
Week (mg/day) 5-40
Table 5-5. Van Wijnen et al. (1990) Limiting Tracer Method (LTM) Soil Ingestion Estimates for
Sample of Dutch Children 5-40
Table 5-6. Estimated Geometric Mean Limiting Tracer Method (LTM) Soil Ingestion Values of
Children Attending Daycare Centers According to Age, Weather Category, and Sampling
Period 5-41
Table 5-7. Estimated Soil Ingestion for Sample of Washington State Children 5-41
Table 5-8. Soil Ingestion Estimates for 64 Anaconda Children 5-42
Table 5-9. Soil Ingestion Estimates for Massachusetts Children Displaying Soil Pica Behavior
(mg/day) 5-42
Table 5-10. Average Daily Soil and Dust Ingestion Estimate (mg/day) 5-43
Table 5-11. Mean and Median Soil Ingestion (mg/day) by Family Member 5-43
Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children 5-44
Table 5-13. Positive/Negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
Study: Effect on Mean Soil Ingestion Estimate (mg/day) 5-44
Table 5-14. Predicted Soil and Dust Ingestion Rates for Children Age 3 to <6 Years (mg/day) 5-45
Table 5-15. Estimated Daily Soil Ingestion for East Helena, Montana Children 5-45
Table 5-16. Estimated Soil Ingestion for Sample of Dutch Nursery School Children 5-46
Table 5-17. Estimated Soil Ingestionfor Sample of Dutch Hospitalized, Bedridden Children 5-46
Table 5-18. Items Ingested by Low-Income Mexican-Born Women Who Practiced Pica During
Pregnancy in the United States (N= 46) 5-47
Table 5-19. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children
(mg/day) 5-47
Table 5-20. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64
Subjects Projected over 365 Days 5-48
Table 5-21. Prevalence of Non-Food Consumption by Substance forNHANES I andNHANES II 5-48
Table 5-22. Summary of Estimates of Soil and Dust Ingestion by Adults and Children (0.5 to 14 years
old) from Key Studies (mg/day) 5-49
Table 5-23. Comparison of Hogan et al. (1998) Study Subjects' Predicted Blood Lead Levels with
Actual Measured Blood Lead Levels, and Default Soil + Dust Intakes Used in IEUBK
Modeling 5-49
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LIST OF FIGURES
Figure 5-1. Prevalence of Non-Food Substance Consumption by Age, NHANES I and NHANES II 5-50
Figure 5-2. Prevalence of Non-Food Substance Consumption by Race, NHANES I and NHANES II 5-51
Figure 5-3. Prevalence of Non-Food Substance Consumption by Income, NHANES I and NHANES
II 5-52
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Chapter 5—Soil and Dust Ingestion
5. SOIL AND DUST INGESTION
5.1. INTRODUCTION
The ingestion of soil and dust is a potential route
of exposure for both adults and children to
environmental chemicals. Children, in particular, may
ingest significant quantities of soil due to their
tendency to play on the floor indoors and on the
ground outdoors and their tendency to mouth objects
or their hands. Children may ingest soil and dust
through deliberate hand-to-mouth movements, or
unintentionally by eating food that has dropped on
the floor. Adults may also ingest soil or dust particles
that adhere to food, cigarettes, or their hands. Thus,
understanding soil and dust ingestion patterns is an
important part of estimating overall exposures to
environmental chemicals.
At this point in time, knowledge of soil and dust
ingestion patterns within the United States is
somewhat limited. Only a few researchers have
attempted to quantify soil and dust ingestion patterns
in U.S. adults or children.
This chapter explains the concepts of soil
ingestion, soil pica, and geophagy, defines these
terms for the purpose of this handbook's exposure
factors, and presents available data from the literature
on the amount of soil and dust ingested.
The Centers for Disease Control and Prevention's
Agency for Toxic Substances and Disease Registry
(ATSDR) held a workshop in June 2000 in which a
panel of soil ingestion experts developed definitions
for soil ingestion, soil-pica, and geophagy, to
distinguish aspects of soil ingestion patterns that are
important from a research perspective (ATSDR,
2001). This chapter uses the definitions that are based
on those developed by participants in that workshop:
Soil ingestion is the consumption of soil. This
may result from various behaviors including,
but not limited to, mouthing, contacting dirty
hands, eating dropped food, or consuming soil
directly.
Soil-pica is the recurrent ingestion of unusually
high amounts of soil (i.e., on the order of
1,000-5,000 mg/day or more).
Geophagy is the intentional ingestion of earths
and is usually associated with cultural
practices.
Some studies are of a behavior known as "pica,"
and the subset of "pica" that consists of ingesting
soil. A general definition of the concept of pica is that
of ingesting non-food substances, or ingesting large
quantities of certain particular foods. Definitions of
pica often include references to recurring or repeated
ingestion of these substances. Soil-pica is specific to
ingesting materials that are defined as soil, such as
clays, yard soil, and flower-pot soil. Although soil-
pica is a fairly common behavior among children,
information about the prevalence of pica behavior is
limited. Gavrelis et al. (2010) reported that the
prevalence of non-food substance consumption varies
by age, race, and income level. The behavior was
most prevalent among children 1 to <3 years
(Gavrelis et al., 2010). Geophagy, on the other hand,
is an extremely rare behavior, especially among
children, as is soil-pica among adults. One distinction
between geophagy and soil-pica that may have public
health implications is the fact that surface soils
generally are not the main source of geophagy
materials. Instead, geophagy is typically the
consumption of clay from known, uncontaminated
sources, whereas soil-pica involves the consumption
of surface soils, usually the top 2-3 inches (ATSDR,
2001).
Researchers in many different disciplines have
hypothesized motivations for human soil-pica or
geophagy behavior, including alleviating nutritional
deficiencies, a desire to remove toxins or serf-
medicate, and other physiological or cultural
influences (Danford, 1982). Bruhn and Pangborn
(1971) and Harris and Harper (1997) suggest a
religious context for certain geophagy or soil
ingestion practices. Geophagy is characterized as an
intentional behavior, whereas soil-pica should not be
limited to intentional soil ingestion, primarily
because children can consume large amounts of soil
from their typical behaviors and because
differentiating intentional and unintentional behavior
in young children is difficult (ATSDR, 2001). Some
researchers have investigated populations that may be
more likely than others to exhibit soil-pica or
geophagy behavior on a recurring basis. These
populations might include pregnant women who
exhibit soil-pica behavior (Simpson et al., 2000),
adults and children who practice geophagy (Vermeer
and Frate, 1979), institutionalized children (Wong,
1988), and children with developmental delays
(Danford, 1983), autism (Kinnell, 1985), or celiac
disease (Korman, 1990). However, identifying
specific soil-pica and geophagy populations remains
difficult due to limited research on this topic. It has
been estimated that 33% of children ingest more than
10 grams of soil 1 or 2 days a year (ATSDR, 2001).
No information was located regarding the prevalence
of geophagy behavior.
Because some soil and dust ingestion may be a
result of hand-to-mouth behavior, soil properties may
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be important. For example, soil particle size, organic
matter content, moisture content, and other soil
properties may affect the adherence of soil to the
skin. Soil particle sizes range from 50-2,000 |j,m for
sand, 2-50 |am for silt, and are <2 |am for clay
(USDA, 1999), while typical atmospheric dust
particle sizes are in the range of 0.001-30 |am (U.S.
OSHA, 1987). Studies on particle size have indicated
that finer soil particles (generally <63 |am in
diameter) tend to be adhered more efficiently to
human hands, whereas adhered soil fractions are
independent of organic matter content or soil origin
(Choate et al., 2006; Yamamoto et al., 2006). More
large particle soil fractions have been shown to
adhere to the skin for soils with higher moisture
content (Choate et al., 2006).
In this handbook, soil, indoor settled dust and
outdoor settled dust are defined generally as the
following:
Soil. Particles of unconsolidated mineral and/or
organic matter from the earth's surface that
are located outdoors, or are used indoors to
support plant growth. It includes particles that
have settled onto outdoor objects and surfaces
(outdoor settled dust).
Indoor Settled Dust. Particles in building
interiors that have settled onto objects,
surfaces, floors, and carpeting. These particles
may include soil particles that have been
tracked or blown into the indoor environment
from outdoors as well as organic matter.
Outdoor Settled Dust. Particles that have settled
onto outdoor objects and surfaces due to either
wet or dry deposition. Note that it may not be
possible to distinguish between soil and
outdoor settled dust, since outdoor settled dust
generally would be present on the uppermost
surface layer of soil.
For the purposes of this handbook, soil ingestion
includes both soil and outdoor settled dust, and dust
ingestion includes indoor settled dust only.
There are several methodologies represented in
the literature related to soil and dust ingestion. Two
methodologies combine biomarker measurements
with measurements of the biomarker substance's
presence in environmental media. An additional
methodology offers modeled estimates of soil/dust
ingestion from activity pattern data from
observational studies (e.g., videography) or from the
responses to survey questionnaires about children's
activities, behaviors, and locations.
The first of the biomarker methodologies
measures quantities of specific elements present in
feces, urine, food and medications, yard soil, house
dust, and sometimes also community soil and dust,
and combines this information using certain
assumptions about the elements' behavior in the
gastrointestinal tract to produce estimates of soil and
dust quantities ingested (Davis et al., 1990). In this
chapter, this methodology is referred to as the "tracer
element" methodology. The second biomarker
methodology compares results from a biokinetic
model of lead exposure and uptake that predict blood
lead levels, with biomarker measurements of lead in
blood (Von Lindern et al., 2003). The model
predictions are made using assumptions about
ingested soil and dust quantities that are based, in
part, on results from early versions of the first
methodology. Therefore, the comparison with actual
measured blood lead levels serves to confirm, to
some extent, the assumptions about ingested soil and
dust quantities used in the biokinetic model. In this
chapter, this methodology is referred to as the
"biokinetic model comparison" methodology. Lead
isotope ratios have also been used as a biomarker to
study sources of lead exposures in children. This
technique involves measurements of different lead
isotopes in blood and/or urine, food, water, and house
dust and compares the ratio of different lead isotopes
to infer sources of lead exposure that may include
dust or other environmental exposures (Manton et al.,
2000). However, application of lead isotope ratios to
derive estimates of dust ingestion by children has not
been attempted. Therefore, it is not discussed any
further in this chapter.
The third, "activity pattern" methodology,
combines information from hand-to-mouth and
object-to-mouth behaviors with microenvironment
data (i.e., time spent at different locations) to derive
estimates of soil and dust ingestion. Behavioral
information often comes from data obtained using
videography techniques or from responses to survey
questions obtained from adults, caregivers, and/or
children. Surveys often include questions about hand-
to-mouth and object-to-mouth behaviors, soil and
dust ingestion behaviors, frequency, and sometimes
quantity (Barltrop, 1966).
Although not directly evaluated in this chapter, a
fourth methodology uses assumptions regarding
ingested quantities of soil and dust that are based on a
general knowledge of human behavior, and
potentially supplemented or informed by data from
other methodologies (Hawley, 1985; Kissel et al.,
1998; Wong etal., 2000).
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The recommendations for soil, dust, and soil +
dust ingestion rates are provided in the next section,
along with a summary of the confidence ratings for
these recommendations. The recommended values
are based on key studies identified by the U.S.
Environmental Protection Agency (U.S. EPA) for this
factor. Following the recommendations, a description
of the three methodologies used to estimate soil and
dust ingestion is provided, followed by a summary of
key and relevant studies. Because strengths and
limitations of each one of the key and relevant studies
relate to the strengths and limitations inherent of the
methodologies themselves, they are discussed at the
end of the key and relevant studies.
5.2. RECOMMENDATIONS
The key studies described in Section 5.3 were
used to recommend values for soil and dust ingestion
for adults and children. Table 5-1 shows the central
tendency recommendations for daily ingestion of soil,
dust, or soil + dust, in mg/day. It also shows the high
end recommendations for daily ingestion of soil, in
mg/day. The high end recommendations are
subdivided into a general population soil ingestion
rate, an ingestion rate for "soil-pica," and an estimate
for individuals who exhibit "geophagy." The soil pica
and geophagy recommendations are likely to
represent an acute high soil ingestion episode or
behaviors at an unknown point on the high end of the
distribution of soil ingestion. Published estimates
from the key studies have been rounded to one
significant figure.
The soil ingestion recommendations in Table 5-1
are intended to represent ingestion of a combination
of soil and outdoor settled dust, without
distinguishing between these two sources. The source
of the soil in these recommendations could be
outdoor soil, indoor containerized soil used to
support growth of indoor plants, or a combination of
both outdoor soil and containerized indoor soil. The
inhalation and subsequent swallowing of soil
particles is accounted for in these recommended
values, therefore, this pathway does not need to be
considered separately. These recommendations are
called "soil." The dust ingestion recommendations in
Table 5-1 include soil tracked into the indoor setting,
indoor settled dust, and air-suspended paniculate
matter that is inhaled and swallowed. Central
tendency "dust" recommendations are provided, in
the event that assessors need recommendations for an
indoor or inside a transportation vehicle scenario in
which dust, but not outdoor soil, is the exposure
medium of concern. The soil + dust recommendations
would include soil, either from outdoor or
containerized indoor sources, dust that is a
combination of outdoor settled dust, indoor settled
dust, and air-suspended paniculate matter that is
inhaled, subsequently trapped in mucous and moved
from the respiratory system to the gastrointestinal
tract, and a soil-origin material located on indoor
floor surfaces that was tracked indoors by building
occupants. Soil and dust recommendations exclude
the soil or dust's moisture content. In other words,
recommended values represent mass of ingested soil
or dust that is represented on a dry-weight basis.
Studies estimating adult soil ingestion are
extremely limited, and only two of these are
considered to be key studies (i.e., Vermeer and Frate,
1979; Davis and Mirick, 2006). In the Davis and
Mirick (2006) study, soil ingestion for adults and
children in the same family was calculated using a
mass-balance approach. The adult data were seen to
be more variable than for the children in the study,
possibly indicating an important occupational
contribution of soil ingestion in some of the adults.
For the aluminum and silicon tracers, soil ingestion
rates ranged from 23-92 mg/day (mean),
0-23 mg/day (median), and 138-814 mg/day
(maximum), with an overall mean value of
52 mg/day for the adults in the study. Based on this
value, the recommended mean value from the Davis
and Mirick (2006) study is estimated to be 50 mg/day
for adult soil and dust ingestion (see Table 5-1).
There are no available studies estimating the
ingestion of dust by adults, therefore, the assumption
used by U.S. EPA's Integrated Exposure and Uptake
Biokinetic (IEUBK) model for lead in children (i.e.,
45% soil, 55% dust contribution) was used to derive
estimates for soil and dust using the soil + dust value
derived from Davis and Mirick (2006). Rounded to
one significant figure, these estimates are 20 mg/day
and 30 mg/day for soil and dust respectively.
The key studies pre-dated the age groups
recommended for children by U.S. EPA (2005) and
were performed on groups of children of varying
ages. As a result, central tendency recommendations
can be used for the life stage categories of 6 to
< 12 months, 1 to <2 years, 2 to <3 years, 3 to
<6 years, and part of the 6 to <11 years categories.
Upper percentile recommendations can be used for
the life stage categories of 1 to <2 years, 2 to
<3 years, 3 to <6 years, 6 to <11 years, and part or all
of the 11 to < 16 years category.
The recommended central tendency soil + dust
ingestion estimate for infants from 6 weeks up to
their first birthday is 60 mg/day (Van Wijnen et al.,
1990; Hogan et al., 1998). If an estimate is needed for
soil only, from soil derived from outdoor or indoor
sources, or both outdoor and indoor sources, the
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recommendation is 30 mg/day (Van Wijnen et al,
1990). If an estimate for indoor dust only is needed,
that would include a certain quantity of tracked-in
soil from outside, the recommendation is 30 mg/day
(Hogan et al., 1998). This dust ingestion value is
based on the 30 mg/day value for soil ingestion for
this age group (Van Wijnen et al., 1990), and the
assumption that the soil and dust inhalation values
will be comparable, as were the Hogan et al. (1998)
values for the 1 to <6 year age group. The confidence
rating for this recommendation is low due to the
small numbers of study subjects in the IEUBK model
study on which the recommendation is in part based
and the inferences needed to develop a quantitative
estimate. Examples of these inferences include: an
assumption that the relative proportions of soil and
dust ingested by 6 week to <12 month old children
are the same as those ingested by older children
(45% soil, 55% dust, based on U.S. EPA, 1994a), and
the assumption that pre-natal or non-soil, non-dust
sources of lead exposure do not dominate these
children's blood lead levels.
When assessing risks for individuals who are not
expected to exhibit soil-pica or geophagy behavior,
the recommended central tendency soil + dust
ingestion estimate is 100 mg/day for children ages 1
to <21 years (Hogan et al., 1998). If an estimate for
soil only is needed, for exposure to soil such as
manufactured topsoil or potted-plant soil that could
occur in either an indoor or outdoor setting, or when
the risk assessment is not considering children's
ingestion of indoor dust (in an indoor setting) as well,
the recommendation is 50 mg/day (Hogan et al.,
1998). If an estimate for indoor dust only is needed,
the recommendation is 60 mg/day (Hogan et al.,
1998). Although these quantities add up to
110 mg/day, the sum is rounded to one significant
figure. Although there were no tracer element studies
or biokinetic model comparison studies performed
for children 6 to <21 years, as a group, their mean or
central tendency soil ingestion would not be zero. In
the absence of data that can be used to develop
specific central tendency soil and dust ingestion
recommendations for children aged 6 to <11 years, 11
to <16 years and 16 to <21 years, U.S. EPA
recommends using the same central tendency soil and
dust ingestion rates that are recommended for
children in the 1 to <6 year old age range.
No key studies are available estimating soil-pica
behavior in children less than 12 months of age or in
adults, therefore, no recommended values are
provided for these age groups. The upper percentile
recommendation for soil and dust ingestion among
the general population of children 3 to <6 years old is
200 mg/day and it is based on the 95th percentile
value obtained from modeling efforts from Ozkaynak
et al. (2010) and from 95th percentile estimates
derived by Stanek and Calabrese (1995a). When
assessing risks for children who may exhibit soil-pica
behavior, or a group of children that includes
individual children who may exhibit soil-pica
behavior, the soil-pica ingestion estimate in the
literature for children up to age 14 ranges from 400 to
41,000 mg/day (Barnes, 1990; Calabrese et al.,
1997a, b, 1991, 1989; Vermeer and Frate, 1979;
Wong, 1988; Stanek et al., 1998; Calabrese and
Stanek, 1993). Due to the definition of soil-pica used
in this chapter, that sets a lower bound on the quantity
referred to as "soil-pica" at 1,000 mg/day (ATSDR,
2001), and due to the significant number of
observations in the U.S. tracer element studies that
are at or exceed that quantity, the recommended soil-
pica ingestion rate is 1,000 mg/day. It should be
noted, however, that this value may be more
appropriate for acute exposures. Currently, no data
are available for soil-pica behavior for children ages
6 to <21 years. Because pica behavior may occur
among some children ages ~1 to 21 years old
(Hyman et al., 1990), it is prudent to assume that, for
some children, soil-pica behavior may occur at any
age up to 21 years.
The recommended geophagy soil estimate is
50,000 mg/day (50 grams) for both adults and
children (Vermeer and Frate, 1979). It is important to
note that this value may be more representative of
acute exposures. Risk assessors should use this value
for soil ingestion in areas where residents are known
to exhibit geophagy behaviors.
Table 5-2 shows the confidence ratings for these
recommendations. Section 5.4 gives a more detailed
explanation of the basis for the confidence ratings.
An important factor to consider when using these
recommendations is that they are limited to estimates
of soil and dust quantities ingested. The scope of this
chapter is limited to quantities of soil and dust taken
into the gastrointestinal tract, and does not extend to
issues regarding bioavailability of environmental
contaminants present in that soil and dust.
Information from other sources is needed to address
bioavailability. In addition, as more information
becomes available regarding gastrointestinal
absorption of environmental contaminants,
adjustments to the soil and dust ingestion exposure
equations may need to be made, to better represent
the direction of movement of those contaminants
within the gastrointestinal tract.
To place these recommendations into context, it is
useful to compare these soil ingestion rates to
common measurements. The central tendency
recommendation of 50 mg/day or 0.050 g/day, dry-
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weight basis, would be equivalent to approximately
1/6 of an aspirin tablet per day because the average
aspirin tablet is approximately 325 mg. The 50 g/day
ingestion rate recommended to represent geophagy
behavior would be roughly equivalent to 150 aspirin
tablets per day.
Table 5-1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion (nig/day)
Soil*
Dustb
Soil + Dust
General
High End
General General General General
Age Group
Population General Population Population Population Population
Central Population Soil-Pica6 Geophagy Central Upper Central Upper
Tendency0 Upper Tendency8 Percentile11 Tendency0 Percentile11
Percentilec
6 weeks to <1 year
1 to <6 years
3 to <6 years
6 to <21 years
Adult
30
50
1,000
50,000
30
60
60
1001
200
100
200
50
201
1,000 50,000 60
50,000 30>
100'
50
Includes soil and outdoor settled dust.
Includes indoor settled dust only.
Davis and Mirick, 2006; Hogan et al., 1998; Davis et al, 1990; Van Wijnen et al., 1990; Calabrese and Stanek, 1995.
Ozkaynak et al., 2010; Stanek and Calabrese, 1995a; rounded to one significant figure.
ATSDR, 2001; Stanek et al., 1998; Calabrese et al., 1997a,b, 1991, 1989; Calabrese and Stanek, 1993; Barnes, 1990;
Wong, 1988; Vermeer and Frate, 1979.
Vermeer and Frate, 1979.
Hogan etal, 1998.
Ozkaynak et al., 2010; rounded to one significant figure.
Total soil and dust ingestion rate is 110 mg/day; rounded to one significant figure it is 100 mg/day.
Estimates of soil and dust were derived from the soil + dust and assuming 45% soil and 55% dust.
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Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
The methodologies have significant limitations. The studies did not capture all of the
information needed (quantities ingested, frequency of high soil ingestion episodes,
prevalence of high soil ingestion). Six of the 12 key studies were of census or
randomized design. Sample selection may have introduced some bias in the results
(i.e., children near smelter or Superfund sites, volunteers in nursery schools). The total
number of adults and children in key studies were 122 and 1,203 (859 U.S. children,
292 Dutch, and 52 Jamaican children), respectively, while the target population
currently numbers more than 74 million (U.S. DOC, 2008). Modeled estimates were
based on 1,000 simulated individuals. The response rates for in-person interviews and
telephone surveys were often not stated in published articles. Primary data were
collected for 381 U.S. children and 292 Dutch children; secondary data for 478 U.S.
children and 52 Jamaican children. Two key studies provided data for adults.
Numerous sources of measurement error exist in the tracer element studies. Biokinetic
model comparison studies may contain less measurement error than tracer element
studies. Survey response study may contain measurement error. Some input variables
for the modeled estimates are uncertain.
Low
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Eleven of the 12 key studies focused on the soil exposure factor, with no or less focus
on the dust exposure factor. The biokinetic model comparison study did not focus
exclusively on soil and dust exposure factors.
The study samples may not be representative of the United States in terms of race,
ethnicity, socioeconomics, and geographical location; studies focused on specific
Studies results are likely to represent current conditions.
Tracer element studies' data collection periods may not represent long-term behaviors.
Biokinetic model comparison and survey response studies do represent longer term
behaviors. Data used in modeled simulation estimates may not represent long-term
behaviors.
Low
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Observations for individual children are available for only three of the 12 key studies.
For the methodologies used by more than one research group, reproducible results
were obtained in some instances. Some methodologies have been used by only one
research group and have not been reproduced by others.
For some studies, information on quality assurance/quality control was limited or
absent.
Low
Variability and Uncertainty
Variability in Population
Minimal Uncertainty
Tracer element and activity pattern methodology studies characterized variability
among study sample members; biokinetic model comparison and survey response
studies did not. Day-to-day and seasonal variability was not very well characterized.
Numerous factors that may influence variability have not been explored in detail.
Estimates are highly uncertain. Tracer element studies' design appears to introduce
biases in the results. Modeled estimates may be sensitive to input variables.
Low
Evaluation and Review
Peer Review
Number and Agreement of Studies
All key studies appeared in peer-review journals.
12 key studies. Some key studies are reanalysis of previously published data.
Researchers using similar methodologies obtained generally similar results; somewhat
general agreement between researchers using different methodologies.
Medium
Overall Rating
Low
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5.3. KEY AND RELEVANT STUDIES
The key tracer element, biokinetic model
comparison, and survey response studies are
summarized in the following sections. Certain studies
were considered "key" and were used as a basis for
developing the recommendations, using judgment
about the study's design features, applicability, and
utility of the data to U.S. soil and dust ingestion rates,
clarity and completeness, and characterization of
uncertainty and variability in ingestion estimates.
Because the studies often were performed for reasons
unrelated to developing soil and dust ingestion
recommendations, their attributes that were
characterized as "limitations" in this chapter might
not be limitations when viewed in the context of the
study's original purpose. However, when studies are
used for developing a soil or dust ingestion
recommendation, U.S. EPA has categorized some
studies' design or implementation as preferable to
others. In general, U.S. EPA chose studies designed
either with a census or randomized sample approach
over studies that used a convenience sample, or other
non-randomized approach, as well as studies that
more clearly explained various factors in the study's
implementation that affect interpretation of the
results. However, in some cases, studies that used a
non-randomized design contain information that is
useful for developing exposure factor
recommendations (for example, if they are the only
studies of children in a particular age category), and
thus may have been designated as "key" studies.
Other studies were considered "relevant" but not
"key" because they provide useful information for
evaluating the reasonableness of the data in the key
studies, but in U.S. EPA's judgment they did not meet
the same level of soundness, applicability and utility,
clarity and completeness, and characterization of
uncertainty and variability that the key studies did. In
addition, studies that did not contain information that
can be used to develop a specific recommendation for
mg/day soil and dust ingestion were classified as
relevant rather than key.
Some studies are re-analyses of previously
published data. For this reason, the sections that
follow are organized into key and relevant studies of
primary analysis (that is, studies in which researchers
have developed primary data pertaining to soil and
dust ingestion) and key and relevant studies of
secondary analysis (that is, studies in which
researchers have interpreted previously published
results, or data that were originally collected for a
different purpose).
5.3.1. Methodologies Used in Key Studies
5.3.1.1. Tracer Element Methodology
The tracer element methodology attempts to
quantify the amounts of soil ingested by analyzing
samples of soil and dust from residences and/or
children's play areas, and feces or urine. The soil,
dust, fecal, and urine samples are analyzed for the
presence and quantity of tracer elements—typically,
aluminum, silicon, titanium, and other elements. A
key underlying assumption is that these elements are
not metabolized into other substances in the body or
absorbed from the gastrointestinal tract in significant
quantities, and thus their presence in feces and urine
can be used to estimate the quantity of soil ingested
by mouth. Although they are sometimes called mass
balance studies, none of the studies attempt to
quantify amounts excreted in perspiration, tears,
glandular secretions, or shed skin, hair or finger- and
toenails, nor do they account for tracer element
exposure via the dermal or inhalation into the lung
routes, and thus they are not a complete "mass
balance" methodology. Early studies using this
methodology did not always account for the
contribution of tracer elements from non-soil
substances (food, medications, and non-food sources
such as toothpaste) that might be swallowed. U.S.
studies using this methodology in or after the mid to
late 1980s account for, or attempt to account for,
tracer element contributions from these non-soil
sources. Some study authors adjust their soil
ingestion estimate results to account for the potential
contribution of tracer elements found in household
dust as well as soil.
The general algorithm that is used to calculate the
quantity of soil or dust estimated to have been
ingested is as follows: the quantity of a given tracer
element, in milligrams, present in the feces and urine,
minus the quantity of that tracer element, in
milligrams, present in the food and medicine, the
result of which is divided by the tracer element's soil
or dust concentration, in milligrams of tracer per
gram of soil or dust, to yield an estimate of ingested
soil, in grams.
The U.S. tracer element researchers have all
assumed a certain offset, or lag time between
ingestion of food, medication, and soil, and the
resulting fecal and urinary output. The lag times used
are typically 24 or 28 hours; thus, these researchers
subtract the previous day's food and medication
tracer element quantity ingested from the current
day's fecal and urinary tracer element quantity that
was excreted. When compositing food, medication,
fecal and urine samples across the entire study
period, daily estimates can be obtained by dividing
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the total estimated soil ingestion by the number of
days in which fecal and/or urine samples were
collected. A variation of the algorithm that provides
slightly higher estimates of soil ingestion is to divide
the total estimated soil ingestion by the number of
days on which feces were produced, which by
definition would be equal to or less than the total
number of days of the study period's fecal sample
collection.
Substituting tracer element dust concentrations
for tracer element soil concentrations yields a dust
ingestion estimate. Because the actual non-food, non-
medication quantity ingested is a combination of soil
and dust, the unknown true soil and dust ingestion is
likely to be somewhere between the estimates that are
based on soil concentrations and estimates that are
based on dust concentrations. Tracer element
researchers have described ingestion estimates for
soil that actually represent a combination of soil and
dust, but were calculated based on tracer element
concentrations in soil. Similarly, they have described
ingestion estimates for dust that are actually for a
combination of soil and dust, but were calculated
based on tracer element concentrations in dust. Other
variations on these general soil and dust ingestion
algorithms have been published, in attempts to
account for time spent indoors, time spent away from
the house, etc. that could be expected to influence the
relative proportion of soil versus dust.
Each individual's soil and dust ingestion can be
represented as an unknown constant in a set of
simultaneous equations of soil or dust ingestion
represented by different tracer elements. To date, only
two of the U.S. research teams (Lasztity et al., 1989;
Barnes, 1990) have published estimates calculated for
pairs of tracer elements using simultaneous
equations.
The U.S. tracer element studies have been
performed for only short-duration study periods, and
only for 33 adults (Davis and Mirick, 2006) and
241 children (101 in Davis et al. [1990], 12 of whom
were studied again in Davis and Mirick [2006]; 64 in
Calabrese et al. [1989] and Barnes [1990]; 64 in
Calabrese et al. [1997a]; and 12 in Calabrese et al.
[1997b]). They provide information on quantities of
soil and dust ingested for the studied groups for short
time periods, but provide limited information on
overall prevalence of soil ingestion by U.S. adults
and children, and limited information on the
frequency of higher soil ingestion episodes.
The tracer element studies appear to contain
numerous sources of error that influence the
estimates upward and downward. Sometimes the
error sources cause individual soil or dust ingestion
estimates to be negative, which is not physically
possible. In some studies, for some of the tracers, so
many individual "mass balance" soil ingestion
estimates were negative that median or mean
estimates based on that tracer were negative. For soil
and dust ingestion estimates based on each particular
tracer, or averaged across tracers, the net impact of
these competing upward and downward sources of
error is unclear.
5.3.1.2. Biokinetic Model Comparison
Methodology
The Biokinetic Model Comparison methodology
compares direct measurements of a biomarker, such
as blood or urine levels of a toxicant, with predictions
from a biokinetic model of oral, dermal and
inhalation exposure routes with air, food, water, soil,
and dust toxicant sources. An example is to compare
measured children's blood lead levels with
predictions from the IEUBK model. Where
environmental contamination of lead in soil, dust, and
drinking water has been measured and those
measurements can be used as model inputs for the
children in a specific community, the model's
assumed soil and dust ingestion values can be
confirmed or refuted by comparing the model's
predictions of blood lead levels with those children's
measured blood lead levels. It should be noted,
however, that such confirmation of the predicted
blood lead levels would be confirmation of the net
impact of all model inputs, and not just soil and dust
ingestions. Under the assumption that the actual
measured blood lead levels of various groups of
children studied have minimal error, and those
measured blood lead levels roughly match biokinetic
model predictions for those groups of children, then
the model's default assumptions may be roughly
accurate for the central tendency, or typical, children
in an assessed group of children. The model's default
assumptions likely are not as useful for predicting
outcomes for highly exposed children.
5.3.1.3. Activity Pattern Methodology
The activity pattern methodology includes
observational studies as well as surveys of adults,
children's caretakers, or children themselves, via
in-person or mailed questionnaires that ask about
mouthing behavior and ingestion of various non-food
items and time spent in various microenvironments.
There are three general approaches to gather data on
children's mouthing behavior: real-time hand
recording, in which trained observers manually
record information (Davis et al., 1995);
video-transcription, in which trained videographers
tape a child's activities and subsequently extract the
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pertinent data manually or with computer software
(Black et al, 2005); and questionnaire, or survey
response, techniques (Stanek et al., 1998).
The activity-pattern methodology combines
information on hand-to-mouth and object-to-mouth
activities (microactivities) and time spent at various
locations (microenvironments) with assumptions
about transfer parameters (e.g., soil-to-skin
adherence, saliva removal efficiency) and other
exposure factors (e.g., frequency of hand washing) to
derive estimates of soil and dust ingestion. This
methodology has been used in U.S. EPA's Stochastic
Human Exposure and Dose Simulation (SHEDS)
model. The SHEDS model is a probabilistic model
that can simulate cumulative (multiple chemicals) or
aggregate (single chemical) residential exposures for
a population of interest over time via multiple routes
of exposure for different types of chemicals and
scenarios, including those involving soil ingestion
(U.S. EPA, 2010).
One of the limitations of this approach includes
the availability and quality of the input variables.
Ozkaynak et al. (2010) found that the model is most
sensitive to dust loadings on carpets and hard floor
surfaces, soil-to-skin adherence factors, hand
mouthing frequency, and hand washing frequency
(Ozkaynak etal., 2010).
5.3.2. Key Studies of Primary Analysis
5.3.2.1. Vermeer andFrate (1979)—Geophagia in
Rural Mississippi: Environmental and
Cultural Contexts and Nutritional
Implications
Vermeer and Frate (1979) performed a survey
response study in Holmes County, Mississippi in the
1970s (date unspecified). Questions about geophagy
(defined as regular consumption of clay over a period
of weeks) were asked of household members
(N= 229 in 50 households; 56 were women, 33 were
men, and 140 were children or adolescents) of a
subset of a random sample of nutrition survey
respondents. Caregiver responses to questions about
115 children under 13 indicate that geophagy was
likely to be practiced by a minimum of 18 (16%) of
these children; however, 16 of these 18 children were
1 to 4 years old, and only 2 of the 18 were older than
4 years. Of the 56 women, 32 (57%) reported eating
clay. There was no reported geophagy among 33 men
or 25 adolescent study subjects questioned.
In a separately administered survey, geophagy
and pica data were obtained from 142 pregnant
women over a period of 10 months. Geophagy was
reported by 40 of these women (28%), and an
additional 27 respondents (19%) reported other pica
behavior, including the consumption of laundry
starch, dry powdered milk, and baking soda.
The average daily amount of clay consumed was
reported to be about 50 grams, for the adult and child
respondents who acknowledged practicing geophagy.
Quantities were usually described as either portions
or multiples of the amount that could be held in a
single, cupped hand. Clays for consumption were
generally obtained from the B soil horizon, or subsoil
rather than an uppermost layer, at a depth of 50 to
130 centimeters.
5.3.2.2. Calabrese et al. (1989)—How Much Soil
Do Young Children Ingest: An
Epidemiologic Study/Barnes
(1990)—Childhood Soil Ingestion: How
Much Dirt Do Kids Eat?/Calabrese et al
(1991)—Evidence of Soil-Pica Behaviour
and Quantification of Soil Ingested
Calabrese et al. (1989) and Barnes (1990) studied
soil ingestion among children using eight tracer
elements—aluminum, barium, manganese, silicon,
titanium, vanadium, yttrium, and zirconium. A
non-random sample of 30 male and 34 female 1, 2,
and 3-year-olds from the greater Amherst,
Massachusetts area were studied, presumably in
1987. The children were predominantly from
two-parent households where the parents were highly
educated. The study was conducted over a period of
8 days spread over 2 weeks. During each week,
duplicate samples of food, beverages, medicines, and
vitamins were collected on Monday through
Wednesday, while excreta, excluding wipes and toilet
paper, were collected for four 24-hour cycles running
from Monday/Tuesday through Thursday/Friday. Soil
and dust samples were also collected from the child's
home and play area. Study participants were supplied
with toothpaste, baby cornstarch, diaper rash cream,
and soap with low levels of most of the tracer
elements.
Table 5-3 shows the published mean soil
ingestion estimates ranging from -294 mg/day based
on manganese to 459 mg/day based on vanadium,
median soil ingestion estimates ranging from
-261 mg/day based on manganese to 96 mg/day
based on vanadium, and 95th percentile estimates
ranged from 106 mg/day based on yttrium to
1,903 mg/day based on vanadium. Maximum daily
soil ingestion estimates ranged from 1,391 mg/day
based on zirconium to 7,281 mg/day based on
manganese. Dust ingestions calculated using tracer
concentrations in dust were often, but not always,
higher than soil ingestions calculated using tracer
concentrations in soil.
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Data for the uppermost 23 subject-weeks (the
highest soil ingestion estimates, averaged over the
4 days of excreta collection during each of the
2 weeks) were published in Calabrese et al. (1991).
One child's soil-pica behavior was estimated in
Barnes (1990) using both the subtraction/division
algorithm and the simultaneous equations method.
On two particular days during the second week of the
study period, the child's aluminum-based soil
ingestion estimates were 19 g/day (18,700 mg/day)
and 36 g/day (35,600 mg/day), silicon-based soil
ingestion estimates were 20 g/day (20,000 mg/day)
and 24 g/day (24,000), and simultaneous-equation
soil ingestion estimates were 20 g/day
(20,100 mg/day) and 23 g/day (23,100 mg/day)
(Barnes, 1990). By tracer, averaged across the entire
week, this child's estimates ranged from
approximately 10 to 14 g/day during the second week
of observation (Calabrese et al., 1991, shown in Table
5-4), and averaged 6 g/day across the entire study
period. Additional information about this child's
apparent ingestion of soil versus dust during the
study period was published in Calabrese and Stanek
(1992a).
5.3.2.3. Van Wijnen etal. (1990)—Estimated Soil
Ingestion by Children
In a tracer element study by Van Wijnen et al.
(1990), soil ingestion among Dutch children ranging
in age from 1 to 5 years was evaluated using a tracer
element methodology. Van Wijnen et al. (1990)
measured three tracers (titanium, aluminum, and acid
insoluble residue [AIR]) in soil and feces. The
authors estimated soil ingestion based on an
assumption called the Limiting Tracer Method
(LTM), which assumed that soil ingestion could not
be higher than the lowest value of the three tracers.
LTM values represented soil ingestion estimates that
were not corrected for dietary intake.
An average daily feces dry weight of 15 grams
was assumed. A total of 292 children attending
daycare centers were studied during the first of two
sampling periods and 187 children were studied in
the second sampling period; 162 of these children
were studied during both periods (i.e., at the
beginning and near the end of the summer of 1986).
A total of 78 children were studied at campgrounds.
The authors reported geometric mean LTM values
because soil ingestion rates were found to be skewed
and the log-transformed data were approximately
normally distributed. Geometric mean LTM values
were estimated to be 111 mg/day for children in
daycare centers and 174 mg/day for children
vacationing at campgrounds (see Table 5-5). For the
162 daycare center children studied during both
sampling periods the arithmetic mean LTM was
162 mg/day, and the median was 114 mg/day.
Fifteen hospitalized children were studied and
used as a control group. These children's LTM soil
ingestion estimates were 74 (geometric mean),
93 (mean), and 110 (median) mg/day. The authors
assumed the hospitalized children's soil ingestion
estimates represented dietary intake of tracer
elements, and used rounded 95% confidence limits
on the arithmetic mean, 70 to 120 mg/day, to correct
the daycare and campground children's LTM
estimates for dietary intake of tracers. Corrected soil
ingestion rates were 69 mg/day (162 mg/day minus
93 mg/day) for daycare children and 120 mg/day
(213 mg/day minus 93 mg/day) for campers.
Corrected geometric mean soil ingestion was
estimated to range from 0 to 90 mg/day, with a
90th percentile value of up to 190 mg/day for the
various age categories within the daycare group and
30 to 200 mg/day, with a 90th percentile value of up
to 300 mg/day for the various age categories within
the camping group.
AIR was the limiting tracer in about 80%of the
samples. Among children attending daycare centers,
soil ingestion was also found to be higher when the
weather was good (i.e., <2 days/week precipitation)
than when the weather was bad (i.e., >4 days/week
precipitation (see Table 5-6).
5.3.2.4. Davis et al. (1990)—Quantitative Estimates
of Soil Ingestion in Normal Children
between the Ages of 2 and 7 Years:
Population-based Estimates Using
Aluminum, Silicon, and Titanium as Soil
Tracer Elements
Davis et al. (1990) used a tracer element
technique to estimate soil ingestion among children.
In this study, 104 children between the ages of 2 and
7 years were randomly selected from a three-city area
in southeastern Washington State. Soil and dust
ingestion was evaluated by analyzing soil and house
dust, feces, urine, and duplicate food, dietary
supplement, medication and mouthwash samples for
aluminum, silicon, and titanium. Data were collected
for 101 of the 104 children during July, August, or
September, 1987. In each family, data were collected
over a 7-day period, with 4 days of excreta sample
collection. Participants were supplied with toothpaste
with known tracer element content. In addition,
information on dietary habits and demographics was
collected in an attempt to identify behavioral and
demographic characteristics that influence soil
ingestion rates among children. The amount of soil
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ingested on a daily basis was estimated using
Equation 5-1:
x Efd)
where:
DWf
DW
Eu
DWfd
Efd
=soil ingested for child /' based on
tracer e (grams);
=feces dry weight (grams);
=feces dry weight on toilet paper
(grams);
=tracer concentration in feces
=tracer amount in urine (ug);
=food dry weight (grams);
=tracer concentration in food
(ug/g); and
=tracer concentration in soil (ug/g).
The soil ingestion rates were corrected by adding
the amount of tracer in vitamins and medications to
the amount of tracer in food, and adjusting the food,
fecal and urine sample weights to account for missing
samples. Food, fecal and urine samples were
composited over a 4-day period, and estimates for
daily soil ingestion were obtained by dividing the
4-day composited tracer quantities by 4.
Soil ingestion rates were highly variable,
especially those based on titanium. Mean daily soil
ingestion estimates were 38.9 mg/day for aluminum,
82.4 mg/day for silicon and 245.5 mg/day for
titanium (see Table 5-7). Median values were
25 mg/day for aluminum, 59 mg/day for silicon, and
81 mg/day for titanium. The investigators also
evaluated the extent to which differences in tracer
concentrations in house dust and yard soil impacted
estimated soil ingestion rates. The value used in the
denominator of the soil ingestion estimate equation
was recalculated to represent a weighted average of
the tracer concentration in yard soil and house dust
based on the proportion of time the child spent
indoors and outdoors, using an assumption that the
likelihood of ingesting soil outdoors was the same as
that of ingesting dust indoors. The adjusted mean
soil/dust ingestion rates were 64.5 mg/day for
aluminum, 160.0 mg/day for silicon, and
268.4 mg/day for titanium. Adjusted median soil/dust
ingestion rates were: 51.8 mg/day for aluminum,
112.4 mg/day for silicon, and 116.6 mg/day for
titanium. The authors investigated whether nine
behavioral and demographic factors could be used to
predict soil ingestion, and found family income less
than $15,000/year and swallowing toothpaste to be
significant predictors with silicon-based estimates;
residing in one of the three cities to be a significant
predictor with aluminum-based estimates, and
washing the face before eating significant for
titanium-based estimates.
5.3.2.5. Calabrese et al. (1997a)—Soil Ingestion
Estimates for Children Residing on a
Superfund Site
Calabrese et al. (1997a) estimated soil ingestion
rates for children residing on a Superfund site using a
methodology in which eight tracer elements were
analyzed. The methodology used in this study is
similar to that employed in Calabrese et al. (1989),
except that rather than using barium, manganese, and
vanadium as three of the eight tracers, the researchers
replaced them with cerium, lanthanum, and
neodymium. A total of 64 children ages 1-3 years (36
male, 28 female) were selected for this study of the
Anaconda, Montana area. The study was conducted
for seven consecutive days during September or
September and October, apparently in 1992, shortly
after soil was removed and replaced in some
residential yards in the area. Duplicate samples of
meals, beverages, and over-the-counter medicines
and vitamins were collected over the 7 day period,
along with fecal samples. In addition, soil and dust
samples were collected from the children's home and
play areas. Toothpaste containing non-detectable
levels of the tracer elements, with the exception of
silica, was provided to all of the children. Infants
were provided with baby cornstarch, diaper rash
cream, and soap, which were found to contain low
levels of tracer elements.
Because of the high degree of intertracer
variability, Calabrese et al. (1997a) also derived
estimates based on the "Best Tracer Methodology"
(BTM). This BTM uses food/soil tracer concentration
ratios in order to correct for errors caused by
misalignment of tracer input and outputs, ingestion of
non-food sources, and non-soil sources (Stanek and
Calabrese, 1995a). A low food/soil ratio is desired
because it minimizes transit time errors. The BTM
did not use the results from Ce, La, and Nd despite
these tracers having low food/soil ratios because the
soil concentrations for these elements were found to
be affected by particle size and more susceptible to
source errors. Calabrese et al. (1997a) noted that
estimates based on Al, Si, and Y in this study may
result in lower soil ingestion estimates than the true
value because the apparent residual negative errors
found for these three tracers for a large majority of
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subjects. It was noted that soil ingestion estimates for
this population may be lower than estimates found by
previous studies in the literature because of families'
awareness of contamination from the Superfund site,
which may have resulted in altered behavior.
Soil ingestion estimates were also examined
based on various demographic characteristics. There
were no statistically significant differences in soil
ingestion based on age, sex, birth order, or house yard
characteristics (Calabrese et al., 1997a). Although not
statistically significant, soil ingestion rates were
generally higher for females, children with lower
birth number, children with parents employed as
laborers, or in service profession, homemakers, or
unemployed and for children with pets (Calabrese et
al., 1997a).
Table 5-8 shows the estimated soil and dust
ingestion by each tracer element and by the BTM.
Based on the BTM, the mean soil and dust ingestion
rates were 65.5 mg/day and 127.2 mg/day,
respectively.
5.3.2.6. Stanek et al (1998)—Prevalence of Soil
Mouthing/Ingestion among Healthy
Children Aged One to Six/Calabrese et al.
(1997b)—Soil Ingestion Rates in Children
Identified by Parental Observation as
Likely High Soil Ingesters
Stanek et al. (1998) conducted a survey response
study using in-person interviews of parents of
children attending well visits at three western
Massachusetts medical clinics in August, September,
and October of 1992. Of 528 children ages 1 to 7
with completed interviews, parents reported daily
mouthing or ingestion of sand and stones in 6%, daily
mouthing or ingestion of soil and dirt in 4%, and
daily mouthing or ingestion of dust, lint and dustballs
in 1%. Parents reported more than weekly mouthing
or ingestion of sand and stones in 16%, more than
weekly mouthing or ingestion of soil and dirt in 10%,
and more than weekly mouthing or ingestion of dust,
lint and dustballs in 3%. Parents reported more than
monthly mouthing or ingestion of sand and stones in
27%, more than monthly mouthing or ingestion of
soil and dirt in 18%, and more than monthly
mouthing or ingestion of dust, lint, and dustballs in
6%.
Calabrese and colleagues performed a follow-up
tracer element study (Calabrese et al., 1997b) for a
subset (N= 12) of the Stanek et al. (1998) children
whose caregivers had reported daily sand/soil
ingestion (N= 17). The time frame of the follow-up
tracer study relative to the original survey response
study was not stated; the study duration was 7 days.
Of the 12 children in Calabrese et al. (1997b), one
exhibited behavior that the authors believed was
clearly soil pica; Table 5-9 shows estimated soil
ingestion rates for this child during the study period.
Estimates ranged from -10 mg/day to 7,253 mg/day
depending on the tracer. Table 5-10 presents the
estimated average daily soil ingestion estimates for
the 12 children studied. Estimates calculated based
on soil tracer element concentrations only ranged
from -15 to +1,783 mg/day based on aluminum,
-46 to +931 mg/day based on silicon, and -47
to+3,581 mg/day based on titanium. Estimated
average daily dust ingestion estimates ranged from
-39 to +2,652 mg/day based on aluminum, -351
to+3,145 mg/day based on silicon, and -98
to +3,632 mg/day based on titanium. Calabrese et al.
(1997b) question the validity of retrospective
caregiver reports of soil pica on the basis of the tracer
element results.
5.3.2.7. Davis andMirick (2006)—Soil ingestion in
children and adults in the same family
Davis and Mirick (2006) calculated soil ingestion
for children and adults in the same family using a
tracer element approach. Data were collected in 1988,
one year after the Davis et al. (1990) study was
conducted. Samples were collected and prepared for
laboratory analysis and then stored for a 2-year
period prior to tracer element quantification with
laboratory analysis. Analytical recovery values for
spiked samples were within the quality control limits
of ±25%. The 20 families in this study were a non-
random subset of the 104 families who participated in
the soil ingestion study by Davis et al. (1990). Data
collection issues resulted in sufficiently complete
data for only 19 of the 20 families consisting of a
child participant from the Davis et al. (1990) study
ages 3 to 7, inclusive, and a female and male parent
or guardian living in the same house. Duplicate
samples of all food and medication items consumed,
and all feces excreted, were collected for
11 consecutive days. Urine samples were collected
twice daily for 9 of the 11 days; for the remaining
2 days, attempts were made to collect full 24-hour
urine specimens. Soil and house dust samples were
also collected. Only 12 children had sufficiently
complete data for use in the soil and dust ingestion
estimates.
Tracer elements for this study included aluminum,
silicon, and titanium. Toothpaste was supplied for use
by study participants. In addition, parents completed
a daily diary of activities for themselves and the
participant child for 4 consecutive days during the
study period.
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Table 5-11 shows soil ingestion rates for all three
family member participants. The mean and median
estimates for children for all three tracers ranged
from 36.7 to 206.9 mg/day and 26.4 to 46.7 mg/day,
respectively, and fall within the range of those
reported by Davis et al. (1990). Adult soil ingestion
estimates ranged from 23.2 to 624.9 mg/day for mean
values and from 0 to 259.5 mg/day for median
values. Adult soil ingestion estimates were more
variable than those of children in the study regardless
of the tracer. The authors believed that this higher
variability may have indicated an important
occupational contribution of soil ingestion in some,
but not all, of the adults. Similar to previous studies,
the soil ingestion estimates were the highest for
titanium. Although toothpaste is a known source of
titanium, the titanium content of the toothpaste used
by study participants was not determined.
Only three of a number of behaviors examined for
their relationship to soil ingestion were found to be
associated with increased soil ingestion in this study:
reported eating of dirt (for children);
occupational contact with soil (for adults); and
hand washing before meals (for both children
and adults).
Several typical childhood behaviors, however,
including thumb-sucking, furniture licking, and
carrying around a blanket or toy were not associated
with increased soil ingestion for the participating
children. Among both parents and children, neither
nail-biting nor eating unwashed fruits or vegetables
was correlated with increased soil ingestion.
However, because the study design required an equal
amount of any food consumed to be included in the
sample for analysis, eating unwashed fruits or
vegetables would not have contributed to an increase
in soil ingestion. Although eating unwashed fruits or
vegetables was not associated with soil ingestion in
either children or adults in this study, the authors
noted that it is a behavior that could lead to soil
ingestion. When investigating correlations within the
same family, a child's soil ingestion was not found to
be associated with either parent's soil ingestion, nor
did the mother and father's soil ingestion appear to be
correlated.
5.3.3. Key Studies of Secondary Analysis
5.3.3.1. Wong (1988)—The Role of Environmental
and Host Behavioral Factors in
Determining Exposure to Infection with
Ascaris lumbricoides and Trichuris
Trichiura/Calabrese and Stanek
(1993)—Soil Pica: Not a Rare Event
Calabrese and Stanek (1993) reviewed a tracer
element study that was conducted by Wong (1988) to
estimate the amount of soil ingested by two groups of
children. Wong (1988) studied a total of 52 children
in two government institutions in Jamaica. The
younger group included 24 children with an average
age of 3.1 years (range of 0.3 to 7.5 years). The older
group included 28 children with an average age of
7.2 years (range of 1.8 to 14 years). One fecal sample
was collected each month from each subject over the
4-month study period. The amount of silicon in dry
feces was measured to estimate soil ingestion.
An unspecified number of daily fecal samples
were collected from a hospital control group of
30 children with an average age of 4.8 years (range of
0.3 to 12 years). Dry feces were observed to contain
1.45% silicon, or 14.5 mg Si per gram of dry feces.
This quantity was used to correct measured fecal
silicon from dietary sources. Fecal silicon quantities
greater than 1.45% in the 52 studied children were
interpreted as originating from soil ingestion.
For the 28 children in the older group, soil
ingestion was estimated to be 58 mg/day, based on
the mean minus one outlier, and 1,520 mg/day, based
on the mean of all the children. The outlier was a
child with an estimated average soil ingestion rate of
41 g/day over the 4 months.
Estimates of soil ingestion were higher in the
younger group of 24 children. The mean soil
ingestion of all the children was 470 ± 370 mg/day.
Due to some sample losses, of the 24 children
studied, only 15 had samples for each of the 4 months
of the study. Over the entire 4-month study period, 9
of 84 samples (or 10.5%) yielded soil ingestion
estimates in excess of 1 g/day.
Of the 52 children studied, 6 had one-day
estimates of more than 1,000 mg/day. Table 5-12
shows the estimated soil ingestion for these six
children. The article describes 5 of 24 (or 20.8%) in
the younger group of children as having
a >1,000 mg/day estimate on at least one of the four
study days; in the older group one child is described
in this manner. A high degree of daily variability in
soil ingestion was observed among these six children;
three showed soil-pica behavior on 2, 3, and 4 days,
respectively, with the most consistent (4 out of
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4 days) soil-pica child having the highest estimated
soil ingestion, 3.8 to 60.7 g/day.
5.3.3.2. Calabrese and Stanek (1995)—Resolving
Intertracer Inconsistencies in Soil
Ingestion Estimation
Calabrese and Stanek (1995) explored sources
and magnitude of positive and negative errors in soil
ingestion estimates for children on a subject-week
and trace element basis. Calabrese and Stanek (1995)
identified possible sources of positive errors as
follows:
Ingestion of high levels of tracers before the
start of the study and low ingestion during the
study period; and
Ingestion of element tracers from a non-food
or non-soil source during the study period.
ranges were excluded from subsequent calculations,
and the median soil ingestion rates of the remaining
tracer elements were considered the best estimate for
that particular day. The magnitude of positive or
negative error for a specific tracer per day was
derived by determining the difference between the
value for the tracer and the median value.
Table 5-13 presents the estimated magnitude of
positive and negative error for six tracer elements in
the children's study (conducted by Calabrese et al.,
1989). The original non-negative mean soil ingestion
rates (see Table 5-3) ranged from a low of 21 mg/day
based on zirconium to a high of 459 mg/day based on
vanadium. The adjusted mean soil ingestion rate after
correcting for negative and positive errors ranged
from 97 mg/day based on yttrium to 208 mg/day
based on titanium. Calabrese and Stanek (1995)
concluded that correcting for errors at the individual
level for each tracer element provides more reliable
estimates of soil ingestion.
Possible sources of negative bias were identified
as follows:
Ingestion of tracers in food that are not
captured in the fecal sample either due to slow
lag time or not having a fecal sample available
on the final study day; and
Sample measurement errors that result in
diminished detection of fecal tracers, but not
in soil tracer levels.
The authors developed an approach that attempted
to reduce the magnitude of error in the individual
trace element ingestion estimates. Results from a
previous study conducted by Calabrese et al. (1989)
were used to quantify these errors based on the
following criteria: (1) a lag period of 28 hours was
assumed for the passage of tracers ingested in food to
the feces (this value was applied to all subject-day
estimates); (2) a daily soil ingestion rate was
estimated for each tracer for each 24-hour day a fecal
sample was obtained; (3) the median tracer-based soil
ingestion rate for each subject-day was determined;
and (4) negative errors due to missing fecal samples
at the end of the study period were also determined.
Also, upper- and lower-bound estimates were
determined based on criteria formed using an
assumption of the magnitude of the relative standard
deviation presented in another study conducted by
Stanek and Calabrese (1995b). Daily soil ingestion
rates for tracers that fell beyond the upper and lower
5.3.3.3. Stanek and Calabrese (1995a)—Soil
Ingestion Estimates for Use in Site
Evaluations Based on the Best Tracer
Method
Stanek and Calabrese (1995a) recalculated soil
ingestion rates for adults and children from two
previous studies, using data for eight tracers from
Calabrese et al. (1989) and three tracers from Davis
et al. (1990). Recalculations were performed using
the BTM. This method selected the "best" tracer(s),
by dividing the total amount of tracer in a particular
child's duplicate food sample by tracer concentration
in that child's soil sample to yield a food/soil (F/S)
ratio. The F/S ratio was small when the tracer
concentration in food was low compared to the tracer
concentration in soil. Small F/S ratios were desirable
because they lessened the impact of transit time error
(the error that occurs when fecal output does not
reflect food ingestion, due to fluctuation in
gastrointestinal transit time) in the soil ingestion
calculation.
For adults, Stanek and Calabrese (1995a) used
data for eight tracers from the Calabrese et al. (1989)
study to estimate soil ingestion by the BTM. The
lowest F/S ratios were Zr and Al and the element
with the highest F/S ratio was Mn. For soil ingestion
estimates based on the median of the lowest four F/S
ratios, the tracers contributing most often to the soil
ingestion estimates were Al, Si, Ti, Y, V, and Zr.
Using the median of the soil ingestion rates based on
the best four tracer elements, the average adult soil
ingestion rate was estimated to be 64 mg/day with a
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median of 87 mg/day. The 95th percentile soil
ingestion estimate was 142 mg/day. These estimates
are based on 18 subject weeks for the six adult
volunteers described in Calabrese et al. (1989).
The BTM used a ranking scheme of F/S ratios to
determine the best tracers for use in the ingestion rate
calculation. To reduce the impact of biases that may
occur as a result of sources of fecal tracers other than
food or soil, the median of soil ingestion estimates
based on the four lowest F/S ratios was used to
represent soil ingestion.
Using the lowest four F/S ratios for each
individual, calculated on a per-week ("subject-week")
basis, the median of the soil ingestion estimates from
the Calabrese et al. (1989) study most often included
aluminum, silicon, titanium, yttrium, and zirconium.
Based on the median of soil ingestion estimates from
the best four tracers, the mean soil ingestion rate for
children was 132 mg/day and the median was
33 mg/day. The 95thpercentile value was 154 mg/day.
For the 101 children in the Davis et al. (1990) study,
the mean soil ingestion rate was 69 mg/day and the
median soil ingestion rate was 44 mg/day. The
95th percentile estimate was 246 mg/day. These data
are based on the three tracers (i.e., aluminum, silicon,
and titanium) from the Davis et al. (1990) study.
When the results for the 128 subject-weeks in
Calabrese et al. (1989) and 101 children in Davis et
al. (1990) were combined, soil ingestion for children
was estimated to be 104 mg/day (mean); 37 mg/day
(median); and 217 mg/day (95th percentile), using the
BTM.
5.3.3.4. Hogan et al. (1998)—Integrated Exposure
Uptake Biokinetic Model for Lead in
Children: Empirical Comparisons with
Epidemiologic Data
Hogan et al. (1998) used the biokinetic model
comparison methodology to review the measured
blood lead levels of 478 children. These children
were a subset of the entire population of children
living in three historic lead smelting communities
(Palmerton, Pennsylvania; Madison County, Illinois;
and southeastern Kansas/southwestern Missouri),
whose environmental lead exposures (soil and dust
lead levels) had been studied as part of public health
evaluations in these communities. The study
populations were, in general, random samples of
children 6 months to 7 years of age. Children who
had lived in their residence for less than 3 months or
those reported by their parents to be away from home
more than 10 hours per week (>20 hours/week for the
Pennsylvania data set) were excluded due to lack of
information regarding lead exposure at the secondary
location. The nature of the soil and dust exposures for
the residential study population were typical, with the
sample size considered sufficiently large to ensure
that a wide enough range of children's behavior
would be spanned by the data. Comparisons were
made for a number of exposure factors, including
age, location, time spent away from home, time spent
outside, and whether or not children took food
outside to eat.
The IEUBK model is a biokinetic model for
predicting children's blood lead levels that uses
measurements of lead content in house dust, soil,
drinking water, food, and air, and child-specific
estimates of intake for each exposure medium (dust,
soil, drinking water, food and air). Model users can
also use default assumptions for the lead contents and
intake rates for each exposure medium when they do
not have specific information for each child.
Hogan et al. (1998) compared children's
measured blood lead levels with biokinetic model
predictions (IEUBK version 0.99d) of blood lead
levels, using the children's measured drinking water,
soil, and dust lead contamination levels together with
default IEUBK model inputs for soil and dust
ingestion, relative proportions of soil and dust
ingestion, lead bioavailability from soil and dust, and
other model parameters. Thus, the default soil and
dust ingestion rates in the model, and other default
assumptions in the model, were tested by comparing
measured blood lead levels with the model's
predictions for those children's blood lead levels.
Most IEUBK model kinetic and intake parameters
were drawn independently from published literature
(White et al., 1998; U.S. EPA, 1994b). Elimination
parameters in particular had relatively less literature
to draw upon (few data in children) and were fixed
through a calibration exercise using a data set with
children's blood lead levels paired with measured
environmental lead exposures in and around their
homes, while holding the other model parameters
constant.
For Palmerton, Pennsylvania (TV =34), the
community-wide geometric mean measured blood
lead levels (6.8 ug/dL) were slightly over-predicted
by the model (7.5 ug/dL); for southeastern
Kansas/southwestern Missouri (N= 111), the blood
lead levels (5.2 ug/dL) were slightly under-predicted
(4.6 ug/dL), and for Madison County, Illinois
(N= 333), the geometric mean measured blood lead
levels matched the model predictions (5.9 ug/dL
measured and predicted), with very slight differences
in the 95% confidence interval. Although there may
be uncertainty in these estimates, these results
suggest that the default soil and dust ingestion rates
used in this version of the IEUBK model
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(approximately 50 mg/day soil and 60 mg/day dust
for a total soil + dust ingestion of 110 mg/day,
averaged over children ages 1 through 6) may be
roughly accurate in representing the central tendency
soil and dust ingestion rates of residence-dwelling
children in the three locations studied.
5.3.3.5. Ozkaynak et al. (2010)—Modeled
Estimates of Soil and Dust Ingestion Rates
for Children
Ozkaynak et al. (2010) developed soil and dust
ingestion rates for children 3 to <6 years of age using
U.S. EPA's SHEDS model for multimedia pollutants
(SHEDS-Multimedia). The authors had two main
objectives for this research: (1) to demonstrate an
application of the SHEDS model while identifying
and quantifying the key factors contributing to the
predicted variability and uncertainty in the soil and
dust ingestion exposure estimates, and (2) to compare
the modeled results to existing tracer-element field
measurements. The SHEDS model is a physically
based probabilistic exposure model, which combines
diary information on sequential time spent in
different locations and activities drawn from
U.S. EPA's Consolidated Human Activity Database
(CHAD), with micro-activity data (e.g., hand-to-
mouth frequency, hand-to-surface frequency),
surface/object soil or dust loadings, and other
exposure factors (e.g., soil-to-skin adherence, saliva
removal efficiency). The SHEDS model generates
simulated individuals, who are then followed through
time, generally up to one year. The model computes
changes to their exposure at the diary event level.
For this study, an indirect modeling approach
was used, in which soil and dust were assumed to
first adhere to the hands, and remain until washed off
or ingested by mouthing. The object-to-mouth
pathway for soil/dust ingestion was also addressed.
For this application of the SHEDS model, however,
other avenues of soil/dust ingestion were not
considered. Outdoor matter was designated as "soil"
and indoor matter as "dust." Estimates for the
distributions of exposure factors such as activity, time
outdoors, environmental concentrations, soil-skin and
dust-skin transfer, hand washing frequency and
efficiency, hand-mouthing frequency, area of object
or hand mouthed, mouthing removal rates, and other
variables were obtained from the literature. These
input variables were used in this SHEDS model
application to generate estimates of soil and dust
ingestion rates for a simulated population of 1,000.
Both sensitivity and uncertainty analyses were
conducted. Based on the sensitivity analysis, the
model results are the most sensitive to dust loadings
on carpet and hard floor surfaces; soil-skin adherence
factor; hand mouthing frequency, and; mean number
of hand washes per day. Based on 200 uncertainty
simulations that were conducted, the modeling
uncertainties were seen to be asymmetrically
distributed around the 50th (median) or the central
variability distribution.
Table 5-14 shows the predicted soil- and
dust-ingestion rates. Mean total soil and dust
ingestion was predicted to be 68 mg/day, with
approximately 60% originating from soil ingestion,
30% from dust on hands, and 10% from dust on
objects. Hand-to-mouth soil and dust ingestion was
found to be the most important pathway, followed by
hand-to-mouth dust ingestion, then object-to-mouth
dust ingestion. The authors noted that these modeled
estimates were found to be consistent with other
soil/dust ingestion values in the literature, but slightly
lower than the central tendency value of 100 mg/day
recommended in U.S. EPA's Child-Specific Exposure
Factors Handbook (U.S. EPA, 2008).
The advantages of this study include the fact that
the SHEDS methodology can be applied to specific
study populations of interest, a wide range of input
parameters can be applied, and a full range of
distributions can be generated. The primary limitation
of this study is the lack of data for some of the input
variables. Data needs include additional information
on the activities and environments of children in
younger age groups, including children with high
hand-to-mouth, object-to-mouth, and pica behaviors,
and information on skin adherence and dust loadings
on indoor objects and floors. In addition, other age
groups of interest were not included because of lack
of data for some of the input variables.
5.3.4. Relevant Studies of Primary Analysis
The following studies are classified as relevant
rather than key. The tracer element studies described
in this section are not designated as key because the
methodology to account for non-soil tracer exposures
was not as well-developed as the methodology in the
U.S. tracer element studies described in Sections
5.3.2 and 5.3.3, or because they do not provide a
quantitative estimate of soil ingestion. However, the
method of Clausing et al. (1987) was used in
developing biokinetic model default soil and dust
ingestion rates (U.S. EPA, 1994a) used in the Hogan
et al. (1998) study, which was designated as key. In
the survey response studies, in most cases the studies
were of a non-randomized design, insufficient
information was provided to determine important
details regarding study design, or no data were
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provided to allow quantitative estimates of soil and/or
dust ingestion rates.
5.3.4.1. Dickins and Ford (1942)—Geophagy (Dirt
Eating) Among Mississippi Negro School
Children
Dickens and Ford conducted a survey response
study of rural Black school children (4th grade and
above) in Oktibbeha County, Mississippi in
September 1941. A total of 52 of 207 children (18 of
69 boys and 34 of 138 girls) studied gave positive
responses to questions administered in a test-taking
format regarding having eaten dirt in the previous 10
to 16 days. The authors stated that the study sample
likely was more representative of the higher
socioeconomic levels in the community, because
older children from lower socioeconomic levels
sometimes left school in order to work, and because
children in the lower grades, who were more
socioeconomically representative of the overall
community, were excluded from the study. Clay was
identified as the predominant type of soil eaten.
5.3.4.2. Ferguson and Keaton (1950)—Studies of
the Diets of Pregnant Women in
Mississippi: II Diet Patterns
Ferguson and Keaton (1950) conducted a survey
response study of a group of 361 pregnant women
receiving health care at the Mississippi State Board
of Health, who were interviewed regarding their diet,
including the consumption of clay or starch. All of
the women were from the lowest economic and
educational level in the area, and 92% were Black. Of
the Black women, 27% reported clay-eating and
41% starch-eating. In the group of White women, 7
and 10% reporting clay- and starch-eating,
respectively. The amount of starch eaten ranged from
2-3 small lumps to 3 boxes (24 ounces) per day. The
amount of clay eaten ranged from one tablespoon to
one cup per day.
5.3.4.3. Cooper (1957)—Pica: A Survey of the
Historical Literature as well as Reports
from the Fields of Veterinary Medicine and
Anthropology, the Present Study of Pica in
Young Children, and a Discussion of Its
Pediatric and Psychological Implications
Cooper (1957) conducted a non-randomized
survey response study in the 1950s of children age
7 months or older referred to a Baltimore, Maryland
mental hygiene clinic. For 86 out of 784 children
studied, parents or caretakers gave positive responses
to the question, "Does your child have a habit, or did
he ever have a habit, of eating dirt, plaster, ashes,
etc.?" and identified dirt, or dirt combined with other
substances, as the substance ingested. Cooper (1957)
described a pattern of pica behavior, including
ingesting substances other than soil, being most
common between ages 2 and 4 or 5 years, with one of
the 86 children ingesting clay at age 10 years and
9 months.
5.3.4.4. Barltrop (1966)—The Prevalence of Pica
Barltrop (1966) conducted a randomized survey
response study of children born in Boston,
Massachusetts between 1958 and 1962, inclusive,
whose parents resided in Boston and who were
neither illegitimate nor adopted. A stratified random
subsample of 500 of these children was contacted for
in-person caregiver interviews, in which a total of
186 families (37%) participated. A separate stratified
subsample of 1,000 children was selected for a
mailed survey, in which 277 (28%) of the families
participated. Interview-obtained data regarding
care-giver reports of pica (in this study is defined as
placing non-food items in the mouth and swallowing
them) behavior in all children ages 1 to 6 years in the
186 families (N = 439) indicated 19 had ingested dirt
(defined as yard dirt, house dust, plant-pot soil,
pebbles, ashes, cigarette ash, glass fragments, lint,
and hair combings) in the preceding 14 days. It does
not appear that these data were corrected for unequal
selection probability in the stratified random sample,
nor were they corrected for non-response bias.
Interviews were conducted in the March/April time
frame, presumably in 1964. Mail-survey obtained
data regarding caregiver reports of pica in the
preceding 14 days indicated that 39 of 277 children
had ingested dirt, presumably using the same
definition as above. Barltrop (1966) mentions several
possible limitations of the study, including non-
participation bias and respondents' memory, or recall,
effects.
5.3.4.5. Bruhn andPangborn (1971)—Reported
Incidence of Pica among Migrant Families
Bruhn and Pangborn (1971) conducted a survey
among 91 low income families of migrant
agricultural workers in California in May through
August 1969. Families were of Mexican descent in
two labor camps (Madison camp, 10 miles west of
Woodland, and Davis camp, 10 miles east of Davis)
and were "Anglo" families at the Harney Lane camp
17 miles north of Stockton. Participation was 34 of
50 families at the Madison camp, 31 of 50 families at
the Davis camp, and 26 of 26 families at the Harney
Lane camp. Respondents for the studied families
(primarily wives) gave positive responses to open-
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ended questions such as "Do you know of anyone
who eats dirt or laundry starch?" Bruhn and
Pangborn (1971) apparently asked a modified version
of this question pertaining to the respondents' own or
relatives' families. They reported 18% (12 of 65) of
Mexican families' respondents as giving positive
responses for consumption of "dirt" among children
within the Mexican respondents' own or relatives'
families. They reported 42% (11 of 26) of "Anglo"
families' respondents as giving positive responses for
consumption of "dirt" among children within the
Anglo respondents' own or relatives' families.
5.3.4.6. Robischon (1971)—Pica Practice and
Other Hand-Mouth Behavior and
Children's Developmental Level
A survey response sample of 19- to 24-month old
children examined at an urban well-child clinic in the
late 1960s or 1970 in an unspecified location
indicated that 48 of the 130 children whose
caregivers were interviewed, exhibited pica behavior
(defined as "ate non-edibles more than once a
week"). The specific substances eaten were reported
for 30 of the 48 children. All except 2 of the 30
children habitually ate more than one non-edible
substance. The soil and dust-like substances reported
as eaten by these 30 children were: ashes (17),
"earth" (5), dust (3), fuzz from rugs (2), clay (1), and
pebbles/stones (1). Caregivers for some of the study
subjects (between 0 and 52 of the 130 subjects, exact
number not specified) reported that the children "ate
non-edibles less than once a week."
5.3.4.7. Bronstein and Dollar (1974)—Pica in
Pregnancy
The frequency and effects of pica behavior was
investigated by Bronstein and Dollar (1974) in
410 pregnant, low-income women from both urban
(N= 201) and rural (N = 209) areas in Georgia. The
women selected were part of the Nutrition
Demonstration Project, a study investigating the
effect of nutrition on the outcome of the pregnancy,
conducted at the Eugene Talmadge Memorial
Hospital and University Hospital in Augusta,
Georgia. During their initial prenatal visit, each
patient was interviewed by a nutrition counselor who
questioned her food frequency, social and dietary
history, and the presence of pica. Patients were
categorized by age, parity, and place of residence
(rural or urban).
Of the 410 women interviewed, 65 (16%) stated
that they practiced pica. A variety of substances were
ingested, with laundry starch being the most
common. There was no significant difference in the
practice of pica between rural and urban women,
although older rural women (20-35 years) showed a
greater tendency to practice pica than younger rural
or urban women (<20 years). The number of previous
pregnancies did not influence the practice of pica.
The authors noted that the frequency of pica among
rural patients had declined from a previous study
conducted 8 years earlier, and attributed the reduction
to a program of intensified nutrition education and
counseling provided in the area. No specific
information on the amount of pica substances
ingested was provided by this study, and the data are
more than 30 years old.
5.3.4.8. Hook (1978)—Dietary Cravings and
Aversions During Pregnancy
Hook (1978) conducted interviews of 250 women
who had each delivered a live infant at two New York
hospitals; the interviews took place in 1975. The
mothers were first asked about any differences in
consumption of seven beverages during their
pregnancy, and the reasons for any changes. They
were then asked, without mentioning specific items,
about any cravings or aversions for other foods or
non-food items that may have developed at any time
during their pregnancy.
Non-food items reportedly ingested during
pregnancy were ice, reported by three women, and
chalk from a river clay bank, reported by one woman.
In addition, one woman reported an aversion to
non-food items (specific non-food item not reported).
No quantity data were provided by this study.
5.3.4.9. Binder et al (1986)—Estimating Soil
Ingestion: The Use of Tracer Elements in
Estimating the Amount of Soil Ingested by
Young Children
Binder et al. (1986) used a tracer technique
modified from a method previously used to measure
soil ingestion among grazing animals to study the
ingestion of soil among children 1 to 3 years of age
who wore diapers. The children were studied during
the summer of 1984 as part of a larger study of
residents living near a lead smelter in East Helena,
Montana. Soiled diapers were collected over a 3-day
period from 65 children (42 males and 23 females),
and composited samples of soil were obtained from
the children's yards. Both excreta and soil samples
were analyzed for aluminum, silicon, and titanium.
These elements were found in soil but were thought
to be poorly absorbed in the gut and to have been
present in the diet only in limited quantities. Excreta
measurements were obtained for 59 of the children.
Soil ingestion by each child was estimated on the
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basis of each of the three tracer elements using a
standard assumed fecal dry weight of 15 g/day, and
the following equation (5-2):
(Eqn. 5-2)
where:
A.
F,
"ie
estimated soil ingestion for child i
based on element e (g/day),
concentration of element e in fecal
sample of child i (mg/g),
fecal dry weight (g/day), and
concentration of element e in child i's
yard soil (mg/g).
The analysis assumed that (1) the tracer elements
were neither lost nor introduced during sample
processing; (2) the soil ingested by children
originates primarily from their own yards; and
(3) that absorption of the tracer elements by children
occurred in only small amounts. The study did not
distinguish between ingestion of soil and house dust,
nor did it account for the presence of the tracer
elements in ingested foods or medicines.
The arithmetic mean quantity of soil ingested by
the children in the Binder et al. (1986) study was
estimated to be 181 mg/day (range 25 to 1,324) based
on the aluminum tracer; 184 mg/day (range 31 to
799) based on the silicon tracer; and 1,834 mg/day
(range 4 to 17,076) based on the titanium tracer (see
Table 5-15). The overall mean soil ingestion estimate,
based on the minimum of the three individual tracer
estimates for each child, was 108 mg/day (range 4 to
708). The median values were 121 mg/day,
136 mg/day, and 618 mg/day for aluminum, silicon,
and titanium, respectively. The 95th percentile values
for aluminum, silicon, and titanium were 584 mg/day,
578 mg/day, and 9,590 mg/day, respectively. The 95th
percentile value based on the minimum of the three
individual tracer estimates for each child was
386 mg/day.
The authors were not able to explain the
difference between the results for titanium and for the
other two elements, but they speculated that
unrecognized sources of titanium in the diet or in the
laboratory processing of stool samples may have
accounted for the increased levels. The frequency
distribution graph of soil ingestion estimates based on
titanium shows that a group of 21 children had
particularly high titanium values
(i.e., >1,000 mg/day). The remainder of the children
showed titanium ingestion estimates at lower levels,
with a distribution more comparable to that of the
other elements.
5.3.4.10. Clausing et al. (1987)—A Method for
Estimating Soil Ingestion by Children
Clausing et al. (1987) conducted a soil ingestion
study with Dutch children using a tracer element
methodology. Clausing et al. (1987) measured
aluminum, titanium, and acid-insoluble residue
contents of fecal samples from children aged 2 to
4 years attending a nursery school, and for samples of
playground dirt at that school. Over a 5-day period,
27 daily fecal samples were obtained for 18 children.
Using the average soil concentrations present at the
school, and assuming a standard fecal dry weight of
10 g/day, soil ingestion was estimated for each tracer.
Six hospitalized, bedridden children served as a
control group, representing children who had very
limited access to soil; eight daily fecal samples were
collected from the hospitalized children.
Without correcting for the tracer element
contribution from background sources, represented
by the hospitalized children's soil ingestion estimates,
the aluminum-based soil ingestion estimates for the
school children in this study ranged from 23 to
979 mg/day, the AIR-based estimates ranged from 48
to 362 mg/day, and the titanium-based estimates
ranged from 64 to 11,620 mg/day. As in the Binder et
al. (1986) study, a fraction of the children (6/18)
showed titanium values above 1,000 mg/day, with
most of the remaining children showing substantially
lower values. Calculating an arithmetic mean
quantity of soil ingested based on each fecal sample
yielded 230 mg/day for aluminum; 129 mg/day for
AIR, and 1,430 mg/day for titanium (see Table 5-16).
Based on the LTM and averaging across each fecal
sample, the arithmetic mean soil ingestion was
estimated to be 105 mg/day with a population
standard deviation of 67 mg/day (range 23 to
362 mg/day); geometric mean soil ingestion was
estimated to be 90 mg/day. Use of the LTM assumed
that "the maximum amount of soil ingested
corresponded with the lowest estimate from the three
tracers" (Clausing et al., 1987).
The hospitalized children's arithmetic mean
aluminum-based soil ingestion estimate was
56 mg/day; titanium-based estimates included
estimates for three of the six children that exceeded
1,000 mg/day, with the remaining three children in
the range of 28 to 58 mg/day (see Table 5-17). AIR
measurements were not reported for the hospitalized
children. Using the LTM method, the mean soil
ingestion rate was estimated to be 49 mg/day with a
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population standard deviation of 22 mg/day (range 26
to 84 mg/day). The geometric mean soil ingestion
rate was 45 mg/day. The hospitalized children's data
suggested a major non-soil source of titanium for
some children and a background non-soil source of
aluminum. However, conditions specific to
hospitalization (e.g., medications) were not
considered.
Clausing et al. (1987) estimated that the average
soil ingestion of the nursery school children was
56 mg/day, after subtracting the mean LTM soil
ingestion for the hospitalized children (49 mg/day)
from the nursery school children's mean LTM soil
ingestion (105 mg/day), to account for background
tracer intake from dietary and other non-soil sources.
5.3.4.11. Calabrese et al. (1990)—Preliminary Adult
Soil Ingestion Estimates: Results of a Pilot
Study
Calabrese et al. (1990) studied six adults to
evaluate the extent to which they ingest soil. This
adult study was originally part of the children soil
ingestion study (Calabrese et al., 1989) and was used
to validate part of the analytical methodology used in
the children's study. The participants were six healthy
adults, three males and three females, 25-41 years
old. Each volunteer ingested one empty gelatin
capsule at breakfast and one at dinner Monday,
Tuesday, and Wednesday during the first week of the
study. During the second week, they ingested
50 milligrams of sterilized soil within a gelatin
capsule at breakfast and at dinner (a total of
100 milligrams of sterilized soil per day) for 3 days.
For the third week, the participants ingested
250 milligrams of sterilized soil in a gelatin capsule
at breakfast and at dinner (a total of 500 milligrams
of soil per day) during the 3 days. Duplicate meal
samples (food and beverage) were collected from the
six adults. The sample included all foods ingested
from breakfast Monday, through the evening meal
Wednesday during each of the 3 weeks. In addition,
all medications and vitamins ingested by the adults
were collected. Total excretory output was collected
from Monday noon through Friday midnight over
3 consecutive weeks.
Data obtained from the first week, when empty
gelatin capsules were ingested, were used to estimate
soil intake by adults. On the basis of recovery values,
Al, Si, Y, and Zr were considered the most valid
tracers. The mean values for these four tracers were:
Al, 110 milligrams; Si, 30 milligrams; Y,
63 milligrams; and Zr, 134 mg. A limitation of this
study is the small sample size.
5.3.4.12. Cooksey (1995)—Pica and Olfactory
Craving of Pregnancy: How Deep Are the
Secrets?
Postpartum interviews were conducted between
1992 and 1994 of 300 women at a mid-western
hospital, to document their experiences of pica
behavior. The majority of women were Black and
low-income, and ranged in age from 13 to 42 years.
In addition to questions regarding nutrition, each
woman was asked if during her pregnancy she
experienced a craving to eat ice or other things that
are not food.
Of the 300 women, 194 (65%) described
ingesting one or more pica substances during their
pregnancy, and the majority (78%) ate ice/freezer
frost alone or in addition to other pica substances.
Reported quantities of items ingested on a daily basis
were three to four 8-pound bags of ice, two to three
boxes of cornstarch, two cans of baking powder, one
cereal bowl of dirt, five quarts of freezer frost, and
one large can of powdered cleanser.
5.3.4.13. Smulian et al (1995)—Pica in a Rural
Obstetric Population
In 1992, Smulian et al. (1995) conducted a survey
response study of pica in a convenience sample of
125 pregnant women in Muscogee County, Georgia,
who ranged in age from 12 to 37 years. Of these, 73
were Black, 47 were White, 4 were Hispanic, and 1
was Asian. Interviews were conducted at the time of
the first prenatal visit, using non-directive
questionnaires to obtain information regarding
substances ingested as well as patterns of pica
behavior and influences on pica behavior. Only
women ingesting non-food items were considered to
have pica. Ingestion of ice was included as a pica
behavior only if the ice was reported to be ingested
multiple times per day, if the ice was purchased
solely for ingestion, or if the ice was obtained from
an unusual source such as freezer frost.
The overall prevalence of pica behavior in this
study was 14.4% (18 of 125 women), and was
highest among Black women (17.8%). There was no
significant difference between groups with respect to
age, race, weight, or gestational age at the time of
enrollment in the study. The most common form of
pica was ice eating (pagophagia), reported by 44.4%
of the patients. Nine of the women reported
information on the frequency and amount of the
substances they were ingesting. Of these women,
66.7% reported daily consumption and 33.3%
reported pica behavior three times per week. Soap,
paint chips, or burnt matches were reportedly
ingested 3 days per week. One patient ate ice
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60 times per week. Women who ate dirt or clay
reported ingesting 0.5-1 pound per week. The largest
amount of ice consumed was five pounds per day.
5.3.4.14. Grigsby et al. (1999)—Chalk Eating in
Middle Georgia: A Culture-Bound
Syndrome of Pica?
Grigsby et al. (1999) investigated the ingestion of
kaolin, also known as white dirt, chalk, or white clay,
in the central Georgia Piedmont area as a
culture-bound syndrome. A total of 21 individuals
who consumed kaolin at the time or had a history of
consuming kaolin were interviewed, using a
seven-item, one-page interview protocol. All of those
interviewed were Black, ranging in age from 28 to
88 years (mean age of 46.5 years), and all were
female except for one.
Reasons for eating kaolin included liking the
taste, being pregnant, craving it, and to gain weight.
Eight respondents indicated that they obtained the
kaolin from others, five reported getting it directly
from the earth, four purchased it from a store, and
two obtained it from a kaolin pit mine. The majority
of the respondents reported that they liked the taste
and feel of the kaolin as they ate it. Only three
individuals reported knowing either males or White
persons who consumed kaolin. Most individuals were
not forthcoming in discussing their ingestion of
kaolin and recognized that their behavior was
unusual.
The study suggests that kaolin-eating is primarily
practiced by Black women who were introduced to
the behavior by family members or friends, during
childhood or pregnancy. The authors concluded that
kaolin ingestion is a culturally-transmitted form of
pica, not associated with any other psychopathology.
Although information on kaolin eating habits and
attitudes were provided by this study, no quantitative
information on consumption was included, and the
sample population was small and non-random.
5.3.4.15. Ward and Kutner (1999)—Reported Pica
Behavior in a Sample of Incident Dialysis
Patients
Structured interviews were conducted with a
sample of 226 dialysis patients in the metropolitan
Atlanta, Georgia area from September 1996 to
September 1997. Interviewers were trained in
nutrition data collection methods, and patients also
received a 3-day diet diary that they were asked to
complete and return by mail. If a subject reported a
strong past or current food or non-food craving, a
separate form was used to collect information to
determine if this was a pica behavior.
Pica behavior was reported by 37 of the dialysis
patients studied (16%), and most of these patients (31
of 37) reported that they were currently practicing
some form of pica behavior. The patients' race and
sex were significantly associated with pica behavior,
with Black patients and women making up 86% and
84% of those reporting pica, respectively. Those
reporting pica behavior were also younger than the
remainder of the sample, and approximately 2
described a persistent craving for ice. Other pica
items reportedly consumed included starch, dirt,
flour, or aspirin.
5.3.4.16. Simpson et al. (2000)—Pica During
Pregnancy in Low-Income Women Born in
Mexico
Simpson et al. (2000) interviewed
225 Mexican-born women, aged 18-42 years (mean
age of 25 years), using a questionnaire administered
in Spanish. Subjects were recruited by approaching
women in medical facilities that served low-income
populations in the cities of Ensenada, Mexico
(N = 75), and Santa Ana, Bakersfield, and East Los
Angeles, California (N = 150). Criteria for
participation were that the women had to be
Mexican-born, speak Spanish as their primary
language, and be pregnant or have been pregnant
within the past year. Only data for U.S. women are
included in this handbook.
Pica behavior was reported in 31% of the women
interviewed in the United States. Table 5-18 shows
the items ingested and the number of women
reporting the pica behavior. Of the items ingested,
only ice was said to be routinely eaten outside of
pregnancy, and was only reported by U.S. women,
probably because none of the low-income women
interviewed in Mexico owned a refrigerator.
Removing the 12 women who reported eating only
ice from the survey lowers the percentage of U.S.
women who reported pica behavior to 23%. Women
said they engaged in pica behavior because of the
taste, smell, or texture of the items, for medicinal
purposes, or because of advice from someone, and
one woman reported eating clay for religious reasons.
Magnesium carbonate, a pica item not found to be
previously reported in the literature, was reportedly
consumed by 17% of women. The amount of
magnesium carbonate ingested ranged from a quarter
of a block to five blocks per day; the blocks were
approximately the size of a 3 5-mm film box. No
specific quantity information on the amounts of pica
substances ingested was provided in the study.
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5.3.4.17. Obialo et al (2001)—Clay Pica Has No
Hematologic or Metabolic Correlate to
Chronic Hemodialysis Patients
A total of 138 dialysis patients at the Morehouse
School of Medicine, Atlanta, Georgia, were
interviewed about their unusual cravings or food
habits. The patients were Black and ranged in age
from 37 to 78 years.
Thirty of the patients (22%) reported some form
of pica behavior, while 13 patients (9.4%) reported
clay pica. The patients with clay pica reported daily
consumption of 225-450 grams of clay.
5.3.4.18. Klitzman et al (2002)—Lead Poisoning
Among Pregnant Women in New York
City: Risk Factors and Screening Practices
Klitzman et al. (2002) interviewed 33 pregnant
women whose blood lead levels were >20 ug/dL as
reported to the New York City Department of Health
between 1996 and 1999. The median age of the
women was 24 years (range of 15 to 43 years), and
the majority were foreign born. The women were
interviewed regarding their work, reproductive and
lead exposure history. A home visit was also
conducted and included a visual inspection and a
colorimetric swab test; consumable items suspected
to contain lead were sent to a laboratory for analysis.
There were 13 women (39%) who reported pica
behavior during their current pregnancies. Of these,
10 reported eating soil, dirt or clay, 2 reported
pulverizing and eating pottery, and 1 reported eating
soap. One of the women reported eating
approximately one quart of dirt daily from her
backyard for the past three months. No other quantity
data were reported.
5.3.5. Relevant Studies of Secondary Analysis
The secondary analysis literature on soil and dust
ingestion rates gives important insights into
methodological strengths and limitations. The tracer
element studies described in this section are grouped
to some extent according to methodological issues
associated with the tracer element methodology.
These methodological issues include attempting to
determine the origins of apparent positive and
negative bias in the methodologies, including: food
input/fecal output misalignment; missed fecal
samples; assumptions about children's fecal weights;
particle sizes of, and relative contributions of soils
and dusts to total soil and dust ingestion; and
attempts to identify a "best" tracer element or
combination of tracer elements. Potential error from
using short-term studies' estimates for long term soil
and dust ingestion behavior estimates is also
discussed.
5.3.5.1. Stanek and Calabrese (1995b)—Daily
Estimates of Soil Ingestion in Children
Stanek and Calabrese (1995b) presented a
methodology that links the physical passage of food
and fecal samples to construct daily soil ingestion
estimates from daily food and fecal trace-element
concentrations. Soil ingestion data for children
obtained from the Amherst study (Calabrese et al.,
1989) were reanalyzed by Stanek and Calabrese
(1995b). A lag period of 28 hours between food
intake and fecal output was assumed for all
respondents. Day 1 for the food sample corresponded
to the 24-hour period from midnight on Sunday to
midnight on Monday of a study week; day 1 of the
fecal sample corresponded to the 24-hour period from
noon on Monday to noon on Tuesday. Based on these
definitions, the food soil equivalent was subtracted
from the fecal soil equivalent to obtain an estimate of
soil ingestion for a trace element. A daily overall
ingestion estimate was constructed for each child as
the median of trace element values remaining after
tracers falling outside of a defined range around the
overall median were excluded.
Table 5-19 presents adjusted estimates, modified
according to the input/output misalignment
correction, of mean daily soil ingestion per child
(mg/day) for the 64 study participants. The approach
adopted in this paper led to changes in ingestion
estimates from those presented in Calabrese et al.
(1989).
Estimates of children's soil ingestion projected
over a period of 365 days were derived by fitting
lognormal distributions to the overall daily soil
ingestion estimates using estimates modified
according to the input/output misalignment correction
(see Table 5-20). The estimated median value of the
64 respondents' daily soil ingestion averaged over a
year was 75 mg/day, while the 95th percentile was
1,751 mg/day. In developing the 365-day soil
ingestion estimates, data that were obtained over a
short period of time (as is the case with all available
soil ingestion studies) were extrapolated over a year.
The 2-week study period may not reflect variability
in tracer element ingestion over a year. While Stanek
and Calabrese (1995b) attempted to address this
through modeling of the long term ingestion, new
uncertainties were introduced through the parametric
modeling of the limited subject day data.
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5.3.5.2. Calabrese and Stanek (1992b)—What
Proportion of Household Dust is Derived
from Outdoor Soil?
Calabrese and Stanek (1992b) estimated the
amount of outdoor soil in indoor dust using statistical
modeling. The model used soil and dust data from the
60 households that participated in the Calabrese et al.
(1989) study, by preparing scatter plots of each
tracer's concentration in soil versus dust. Correlation
analysis of the scatter plots was performed. The
scatter plots showed little evidence of a consistent
relationship between outdoor soil and indoor dust
concentrations. The model estimated the proportion
of outdoor soil in indoor dust using the simplifying
assumption that the following variables were
constants in all houses: the amount of dust produced
every day from both indoor and outdoor sources; the
proportion of indoor dust due to outdoor soil; and the
concentration of the tracer element in dust produced
from indoor sources. Using these assumptions, the
model predicted that 31.3% by weight of indoor dust
came from outdoor soil. This model was then used to
adjust the soil ingestion estimates from Calabrese et
al. (1989).
5.3.5.3. Calabrese et al (1996)—Methodology to
Estimate the Amount and Particle Size of
Soil Ingested by Children: Implications for
Exposure Assessment at Waste Sites
Calabrese et al. (1996) examined the hypothesis
that one cause of the variation between tracers seen in
soil ingestion studies could be related to differences
in soil tracer concentrations by particle size. This
study, published prior to the Calabrese et al. (1997a)
primary analysis study results, used laboratory
analytical results for the Anaconda, Montana soil's
tracer concentration after it had been sieved to a
particle size of <250 um in diameter (it was sieved
to <2 mm soil particle size in Calabrese et al.
[1997a]). The smaller particle size was examined
based on the assumption that children principally
ingest soil of small particle size adhering to fingertips
and under fingernails. For five of the tracers used in
the original study (aluminum, silicon, titanium,
yttrium, and zirconium), soil concentration was not
changed by particle size. However, the soil
concentrations of three tracers (lanthanum, cerium,
and neodymium) were increased 2- to 4-fold at the
smaller soil particle size. Soil ingestion estimates for
these three tracers were decreased by approximately
60% at the 95th percentile compared to the Calabrese
et al. (1997a) results.
5.3.5.4. Stanek et al. (1999)—Soil Ingestion
Estimates for Children in Anaconda Using
Trace Element Concentrations in Different
Particle Size Fractions
Stanek et al. (1999) extended the findings from
Calabrese et al. (1996) by quantifying trace element
concentrations in soil based on sieving to particle
sizes of 100-250 um and to particle sizes of 53 to
<100 um. The earlier study (Calabrese et al., 1996)
used particle sizes of 0-2 um and 1-250 um. This
study used the data from soil concentrations from the
Anaconda, Montana site reported by Calabrese et al.
(1997a). Results of the study indicated that soil
concentrations of aluminum, silicon, and titanium did
not increase at the two finer particle size ranges
measured. However, soil concentrations of cerium,
lanthanum, and neodymium increased by a factor of
2.5 to 4.0 in the 100-250 um particle size range
when compared with the 0-2 um particle size range.
There was not a significant increase in concentration
in the 53-100 um particle size range.
5.3.5.5. Stanek and Calabrese (2000)—Daily Soil
Ingestion Estimates for Children at a
Superfund Site
Stanek and Calabrese (2000) reanalyzed the soil
ingestion data from the Anaconda study. The authors
assumed a lognormal distribution for the soil
ingestion estimates in the Anaconda study to predict
average soil ingestion for children over a longer time
period. Using "best linear unbiased predictors," the
authors predicted 95th percentile soil ingestion values
over time periods of 7 days, 30 days, 90 days, and
365 days. The 95th percentile soil ingestion values
were predicted to be 133 mg/day over 7 days,
112 mg/day over 30 days, 108 mg/day over 90 days,
and 106 mg/day over 365 days. Based on this
analysis, estimates of the distribution of longer term
average soil ingestion are expected to be narrower,
with the 95th percentile estimates being as much as
25% lower (Stanek and Calabrese, 2000).
5.3.5.6. Stanek et al. (2001a)—Biasing Factors for
Simple Soil Ingestion Estimates in Mass
Balance Studies of Soil Ingestion
In order to identify and evaluate biasing factors
for soil ingestion estimates, the authors developed a
simulation model based on data from previous soil
ingestion studies. The soil ingestion data used in this
model were taken from Calabrese et al. (1989) (the
Amherst study); Davis et al. (1990) (southeastern
Washington State); Calabrese et al. (1997a) (the
Anaconda study); and Calabrese et al. (1997b)
(soil-pica in Massachusetts), and relied only on the
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aluminum and silicon trace element estimates
provided in these studies.
Of the biasing factors explored, the impact of
study duration was the most striking, with a positive
bias of more than 100% for 95th percentile estimates
in a 4-day tracer element study. A smaller bias was
observed for the impact of absorption of trace
elements from food. Although the trace elements
selected for use in these studies are believed to have
low absorption, whatever amount is not accounted for
will result in an underestimation of the soil ingestion
distribution. In these simulations, the absorption of
trace elements from food of up to 30% was shown to
negatively bias the estimated soil ingestion
distribution by less than 20 mg/day. No biasing effect
was found for misidentifying play areas for soil
sampling (i.e., ingested soil from a yard other than
the subject's yard).
5.3.5.7. Staneketal (2001 b)—Soil Ingestion
Distributions for Monte Carlo Risk
Assessment in Children
Stanek et al. (200 Ib) developed "best linear
unbiased predictors" to reduce the biasing effect of
short-term soil ingestion estimates. This study
estimated the long-term average soil ingestion
distribution using daily soil ingestion estimates from
children who participated in the Anaconda, Montana
study. In this long-term (annual) distribution, the soil
ingestion estimates were: mean 31, median 24,
75th percentile 42, 90th percentile 75, and
95th percentile 91 mg/day.
5.3.5.8. Von Lindern et al. (2003)—Assessing
Remedial Effectiveness Through the Blood
Lead: Soil/Dust Lead Relationship at the
Bunker Hill Superfund Site in the Silver
Valley of Idaho
Similar to Hogan et al. (1998), Von Lindern et al.
(2003) used the IEUBK model to predict blood lead
levels in a non-random sample of several hundred
children ages 0-9 years in an area of northern Idaho
from 1989-1998 during community-wide soil
remediation. Von Lindern et al. (2003) used the
IEUBK default soil and dust ingestion rates together
with observed house dust/soil lead levels (and
imputed values based on community soil and dust
lead levels, when observations were missing). The
authors compared the predicted blood lead levels
with observed blood lead levels and found that the
default IEUBK soil and dust ingestion rates and lead
bioavailability value over-predicted blood lead levels,
with the over-prediction decreasing as the community
soil remediation progressed. The authors stated that
the over-prediction may have been caused either by a
default soil and dust ingestion that was too high, a
default bioavailability value for lead that was too
high, or some combination of the two. They also
noted under-predictions for some children, for whom
follow up interviews revealed exposures to lead
sources not accounted for by the model, and noted
that the study sample included many children with a
short residence time within the community.
Von Lindern et al. (2003) developed a statistical
model that apportioned the contributions of
community soils, yard soils of the residence, and
house dust to lead intake; the models' results
suggested that community soils contributed more
(50%) than neighborhood soils (28%) or yard soils
(22%) to soil found in house dust of the studied
children.
5.3.5.9. Gavrelis et al. (2011)—An Analysis of the
Proportion of the U.S. Population that
Ingests Soil or Other Non-Food
Substances.
Gavrelis et al. (2011) evaluated the prevalence of
the U.S. population that ingests non-food substances
such as soil, clay, starch, paint, or plaster. Data were
compiled from the National Health and Nutrition
Examination Survey (NHANES) collected from
1971-1975 (NHANES I) and 1976-1980
(NHANES II), which represent a complex, stratified,
multistage, probability-cluster design and include
nationwide probability samples of approximately
21,000 and 25,000 study participants, respectively.
NHANES I surveyed people aged 1 to 74 years and
NHANES II surveyed those 6 months to 74 years.
The study population included women of
childbearing age, people with low income status, the
elderly, and preschool children, who represented an
oversampling of specific groups in the population
that were believed to have high risks for malnutrition.
The survey questions were demographic,
socioeconomic, dietary, and health-related queries,
and included specific questions regarding soil and
non-food substance ingestion. Survey questions for
children under 12 years asked whether they
consumed non-food substances including dirt or clay,
starch, paint or plaster, and other materials
(NHANES I) or about consumption of clay, starch,
paint or plaster, dirt, and other materials
(NHANES II). For participants over 12 years of age,
the survey questions asked only about consumption
of dirt or clay, starch, and other materials
(NHANES I) or about non-food substances including
clay, starch, and other materials (NHANES II). Age
groupings used in this analysis vary slightly from the
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age group categories established by U.S. EPA and
described in Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Other demographic parameters included sex
(including pregnant and non-pregnant females); race
(White, Black, and other); geography (urban and
rural, with "urban" defined as populations >2,500);
income level (ranging from $0-$9,999 up
to >$20,000, or not stated); and highest grade head of
household (population under 18 years) or respondent
(population >18 years) attended. For statistical
analysis, frequency estimates were generated for the
proportion of the total U.S. population that reported
consumption of dirt, clay, starch, paint or plaster, or
other materials "considered unusual" using the
appropriate NCHS sampling weights and responses
to the relevant questions in NHANES I and II.
NHANES I and II were evaluated separately, because
the data sets did not provide components of the
weight variable separately (i.e., probability of
selection, non-response adjustment weight, and
post-stratification weight).
Although the overall prevalence estimates were
higher in NHANES I compared with NHANES II,
similar patterns were generally observed across
substance types and demographic groups studied. For
NHANES I, the estimated prevalence of all non-food
substance consumption in the United States for all
ages combined was 2.5% (95% Confidence Interval
[CI]: 2.2-2.9%), whereas for NHANES II, the
estimated prevalence of all non-food substance
consumption in the United States for all ages
combined was 1.1% (95% CI: 1.0-1.2%). Table 5-21
provides the prevalence estimates by type of
substance consumed for all ages combined. By type
of substance, the estimated prevalence was greatest
for dirt and clay consumption and lowest for starch.
Figures 5-1, 5-2 and 5-3, respectively, show the
prevalence of non-food substance consumption by
age, race, and income. The most notable differences
were seen across age, race (Black versus White), and
income groups. For both NHANES I and II,
prevalence for the ingestion of all non-food
substances decreased with increasing age, was higher
among Blacks (5.7%; 95% CI: 4.4-7.0%) as
compared to Whites (2.1%; 95% CI: 1.8-2.5%), and
was inversely related to income level, with
prevalence of non-food consumption decreasing as
household income increased. The estimated
prevalence of all non-food substances for the 1 to
<3 year age category was at least twice that of the
next oldest category (3 to <6 years). Prevalence
estimates were 22.7% (95% CI: 20.1-25.3%) for the
1 to <3 year age group based on NHANES I and
12% based on NHANES II. In contrast, prevalence
estimates for the >21 year age group was 0.7%
(95% CI: 0.5-1.0%) and 0.4% (95% CI: 0.3-0.5%)
for NHANES I and NHANES II, respectively. Other
differences related to geography (i.e., urban and
rural), highest grade level of the household head, and
sex were less remarkable. For NHANES I, for
example, the estimated prevalence of non-food
substance consumption was only slightly higher
among females (2.9%; CI: 2.3-3.5%) compared to
males (2.1%; CI: 1.8-2.5%) of all ages. For pregnant
females, prevalence estimates (2.5%;
95% CI: 0.0-5.6%) for those 12 years and over were
more than twice those for non-pregnant females
(1.0%; 95% CI: 0.7-1.4%).
5.4. LIMITATIONS OF STUDY
METHODOLOGIES
The three types of information needed to provide
recommendations to exposure assessors on soil and
dust ingestion rates among U.S. children include
quantities of soil and dust ingested, frequency of high
soil and dust ingestion episodes, and prevalence of
high soil and dust ingesters. The methodologies
provide different types of information: the tracer
element, biokinetic model comparison, and activity
pattern methodologies provide information on
quantities of soil and dust ingested; the tracer element
methodology provides limited evidence of the
frequency of high soil ingestion episodes; the survey
response methodology can shed light on prevalence
of high soil ingesters and frequency of high soil
ingestion episodes. The methodologies used to
estimate soil and dust ingestion rates and prevalence
of soil and dust ingestion behaviors have certain
limitations, when used for the purpose of developing
recommended soil and dust ingestion rates. These
limitations may not have excluded specific studies
from use in the development of recommended
ingestion rates, but have been noted throughout this
handbook. This section describes some of the known
limitations, presents an evaluation of the current state
of the science for U.S. children's soil and dust
ingestion rates, and describes how the limitations
affect the confidence ratings given to the
recommendations.
5.4.1. Tracer Element Methodology
This section describes some previously identified
limitations of the tracer element methodology as it
has been implemented by U.S. researchers, as well as
additional potential limitations that have not been
explored. Some of these same limitations would also
apply to the Dutch and Jamaican studies that used a
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control group of hospitalized children to account for
dietary and pharmaceutical tracer intakes.
Binder et al. (1986) described some of the major
and obvious limitations of the early U.S. tracer
element methodology as follows:
[T]he algorithm assumes that children ingest
predominantly soil from their own yards and
that concentrations of elements in composite
soil samples from front and back yards are
representative of overall concentrations in the
yards....children probably eat a combination of
soil and dust; the algorithm used does not
distinguish between soil and dust
ingestion....fecal sample weights...were much
lower than expected...the assumption that
aluminum, silicon and titanium are not
absorbed is not entirely true....dietary intake of
aluminum, silicon and titanium is not
negligible when compared with the potential
intake of these elements from soil....Before
accepting these estimates as true values of soil
ingestion in toddlers, we need a better
understanding of the metabolisms of
aluminum, silicon and titanium in children,
and the validity of the assumptions we made
in our calculations should be explored further.
The subsequent U.S. tracer element studies
(Calabrese et al., 1997a, 1989; Barnes, 1990; Davis et
al., 1990; Davis and Mirick, 2006) made some
progress in addressing some of the Binder et al.
(1986) study's stated limitations.
Regarding the issue of non-yard
(community-wide) soil as a source of ingested soil,
one study (Calabrese et al., 1989; Barnes, 1990)
addressed this issue to some extent, by including
samples of children's daycare center soil in the
analysis. Calabrese et al. (1997a) attempted to
address the issue by excluding children in daycare
from the study sample frame. Homogeneity of
community soils' tracer element content would play a
role in whether this issue is an important biasing
factor for the tracer element studies' estimates. Davis
et al. (1990) evaluated community soils' aluminum,
silicon, and titanium content and found little variation
among 101 yards throughout the three-city area.
Stanek et al. (200la) concluded that there was
"minimal impact" on estimates of soil ingestion due
to mis-specifying a child's play area.
Regarding the issue of soil and dust both
contributing to measured tracer element quantities in
excreta samples, the key U.S. tracer element studies
all attempted to address the issue by including
samples of household dust in the analysis, and in
some cases estimates are presented in the published
articles that adjust soil ingestion estimates on the
basis of the measured tracer elements found in the
household dust. The relationship between soil
ingestion rates and indoor settled dust ingestion rates
has been evaluated in some of the secondary studies
(Calabrese and Stanek, 1992b). An issue similar to
the community-wide soil exposures in the previous
paragraph could also exist with community-wide
indoor dust exposures (such as dust found in schools
and community buildings occupied by study subjects
during or prior to the study period). A portion of the
community-wide indoor dust exposures (due to
occupying daycare facilities) was addressed in the
Calabrese et al. (1989) and Barnes (1990) studies, but
not in the other three key tracer element studies. In
addition, if the key studies' vacuum cleaner collection
method for household and daycare indoor settled dust
samples influenced tracer element composition of
indoor settled dust samples, the dust sample
collection method would be another area of
uncertainty with the key studies' indoor dust related
estimates. The survey response studies suggest that
some young children may prefer ingesting dust to
ingesting soil. The existing literature on soil versus
dust sources of children's lead exposure may provide
useful information that has not yet been compiled for
use in soil and dust ingestion recommendations.
Regarding the issue of fecal sample weights and
the related issue of missing fecal and urine samples,
the key tracer element studies have varying strengths
and limitations. The Calabrese et al. (1989) article
stated that wipes and toilet paper were not collected
by the researchers, and thus underestimates of fecal
quantities may have occurred. Calabrese et al. (1989)
stated that cotton cloth diapers were supplied for use
during the study; commodes apparently were used to
collect both feces and urine for those children who
were not using diapers. Barnes (1990) described
cellulose and polyester disposable diapers with
significant variability in silicon and titanium content
and suggested that children's urine was not included
in the analysis. Thus, it is unclear to what extent
complete fecal and urine output was obtained, for
each study subject. The Calabrese et al. (1997a) study
did not describe missing fecal samples and did not
state whether urinary tracer element quantities were
used in the soil and dust ingestion estimates, but
stated that wipes and toilet paper were not collected.
Missing fecal samples may have resulted in negative
bias in the estimates from both of these studies. Davis
et al. (1990) and Davis and Mirick (2006) were
limited to children who no longer wore diapers.
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Missed fecal sample adjustments might affect those
studies' estimates in either a positive or negative
direction, due to the assumptions the authors made
regarding the quantities of feces and urine in missed
samples. Adjustments for missing fecal and urine
samples could introduce errors sufficient to cause
negative estimates if missed samples were heavier
than the collected samples used in the soil and dust
ingestion estimate calculations.
Regarding the issue of dietary intake, the key U.S.
tracer element studies have all addressed dietary (and
non-dietary, non-soil) intake by subtracting calculated
estimates of these sources of tracer elements from
excreta tracer element quantities, or by providing
study subjects with personal hygiene products that
were low in tracer element content. Applying the
food and non-dietary, non-soil corrections required
subtracting the tracer element contributions from
these non-soil sources from the measured fecal/urine
tracer element quantities. To perform this correction
required assumptions to be made regarding the
gastrointestinal transit time, or the time lag between
inputs (food, non-dietary non-soil, and soil) and
outputs (fecal and urine). The gastrointestinal transit
time assumption introduced a new potential source of
bias that some authors (Stanek and Calabrese, 1995b)
called input/output misalignment or transit time error.
Stanek and Calabrese (1995a) attempted to correct
for this transit time error by using the BTM and
focusing estimates on those tracers that had a low
food/soil tracer concentration ratios. The lag time
may also be a function of age. Davis et al. (1990) and
Davis and Mirick (2006) assumed a 24-hour lag time
in contrast to the 28-hour lag times used in Calabrese
et al. (1989); Barnes (1990); and Calabrese et al.
(1997a). ICRP (2002) suggested a lag time of
37 hours for one year old children and 5 to 15 year
old children. Stanek and Calabrese (1995b) describe
a method designed to reduce bias from this error
source.
Regarding gastrointestinal absorption, the authors
of three of the studies appeared to agree that the
presence of silicon in urine represented evidence that
silicon was being absorbed from the gastrointestinal
tract (Davis et al., 1990; Calabrese et al., 1989;
Barnes, 1990; Davis and Mirick, 2006). There was
some evidence of aluminum absorption in Calabrese
et al. (1989); Barnes (1990); Davis and Mirick (2006)
stated that aluminum and titanium did not appear to
have been absorbed, based on low urinary levels.
Davis et al. (1990) stated that silicon appears to have
been absorbed to a greater degree than aluminum and
titanium, based on urine concentrations.
Aside from the gastrointestinal absorption, lag
time, and missed fecal sample issues, Davis and
Mirick (2006) offered another possible explanation
for the negative soil and dust ingestion rates
estimated for some study participants. Negative
values result when the tracer amount in food and
medicine is greater than that in urine/fecal matter.
Given that some analytical error may occur, any
overestimation of tracer amounts in the food samples
would be greater than an overestimation in
urine/feces, since the food samples were many times
heavier than the urine and fecal samples.
Another limitation on accuracy of tracer element-
based estimates of soil and dust ingestion relates to
inaccuracies inherent in environmental sampling and
laboratory analytical techniques. The "percent
recovery" of different tracer elements varies
(according to validation of the study methodology
performed with adults who swallowed gelatin
capsules with known quantities of sterilized soil, as
part of the Calabrese et al. [1989, 1997a] studies).
Estimates based on a particular tracer element with a
lower or higher recovery than the expected 100% in
any of the study samples would be influenced in
either a positive or negative direction, depending on
the recoveries in the various samples and their degree
of deviation from 100% (Calabrese et al., 1989).
Soil/dust size fractions, and digestion/extraction
methods of sample analysis may be additional
limitations.
Davis et al. (1990) offered an assessment of the
impact of swallowed toothpaste on the tracer-based
estimates by adjusting estimates for those children
whose caregivers reported that they had swallowed
toothpaste. Davis et al. (1990) had supplied study
children with toothpaste that had been pre-analyzed
for its tracer element content, but it is not known to
what extent the children actually used the supplied
toothpaste. Similarly, Calabrese et al. (1989, 1997a)
supplied children in the Amherst, Massachusetts and
Anaconda, Montana studies with toothpaste
containing low levels of most tracers, but it is unclear
to what extent those children used the supplied
toothpaste.
Other research suggests additional possible
limitations that have not yet been explored. First,
lymph tissue structures in the gastrointestinal tract
might serve as reservoirs for titanium dioxide food
additives and soil particles, which could bias
estimates either upward or downward depending on
tracers' entrapment within, or release from, these
reservoirs during the study period (ICRP, 2002;
Shepherd et al., 1987; Powell et al., 1996). Second,
gastrointestinal uptake of silicon may have occurred,
which could bias those estimates downward.
Evidence of silicon's role in bone formation (Carlisle,
1980) supported by newer research on dietary silicon
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uptake (Jugdaohsingh et al., 2002); Van Dyck et al.
(2000) suggests a possible negative bias in the
silicon-based soil ingestion estimates, depending on
the quantities of silicon absorbed by growing
children. Third, regarding the potential for swallowed
toothpaste to bias soil ingestion estimates upward,
commercially available toothpaste may contain
quantities of titanium and perhaps silicon and
aluminum in the range that could be expected to
affect the soil and dust ingestion estimates. Fourth,
for those children who drank bottled or tap water
during the study period, and did not include those
drinking water samples in their duplicate food
samples, slight upward bias may exist in some of the
estimates for those children, since drinking water
may contain small, but relevant, quantities of silicon
and potentially other tracer elements. Fifth, the tracer
element studies conducted to date have not explored
the impact of soil properties' influence on toxicant
uptake or excretion within the gastrointestinal tract.
Nutrition researchers investigating influence of clay
geophagy behavior on human nutrition have begun
using in vitro models of the human digestion
(Dominy et al., 2003; Hooda et al., 2004). A recent
review (Wilson, 2003) covers a wide range of
geophagy research in humans and various hypotheses
proposed to explain soil ingestion behaviors, with
emphasis on the soil properties of geophagy
materials.
5.4.2. Biokinetic Model Comparison Methodology
It is possible that the IEUBK biokinetic model
comparison methodology contained sources of both
positive and negative bias, like the tracer element
studies, and that the net impact of the competing
biases was in either the positive or negative direction.
U.S. EPA's judgment about the major sources of bias
in biokinetic model comparison studies is that there
may be several significant sources of bias. The first
source of potential bias was the possibility that the
biokinetic model failed to account for sources of lead
exposure that are important for certain children. For
these children, the model might either under-predict,
or accurately predict, blood lead levels compared to
actual measured lead levels. However, this result may
actually mean that the default assumed lead intake
rates via either soil and dust ingestion, or another
lead source that is accounted for by the model, are
too high. A second source of potential bias was use of
the biokinetic model for predicting blood lead levels
in children who have not spent a significant amount
of time in the areas characterized as the main sources
of environmental lead exposure. Modeling this
population could result in either upward or downward
biases in predicted blood lead levels. Comparing
upward-biased predictions with actual measured
blood lead levels and finding a relatively good match
could lead to inferences that the model's default soil
and dust ingestion rates are accurate, when in fact the
children's soil and dust ingestion rates, or some other
lead source, were actually higher than the default
assumption. A third source of potential bias was the
assumption within the model itself regarding the
biokinetics of absorbed lead, which could result in
either positively or negatively biased predictions and
the same kinds of incorrect inferences as the second
source of potential bias.
In addition, there was no extensive sensitivity
analysis. The calibration step used to fix model
parameters limits the degree that most parameters can
reasonably be varied. Second, the IEUBK model was
not designed to predict blood lead levels greater than
25-30 ug/dL; there are few data to develop such
predictions and less to validate them. If there are site-
specific data that indicate soil ingestion rates (or
other ingestion/intake rates) are higher than the
defaults on average (not for specific children), the
site-specific data should be considered. U.S. EPA
considers the default IEUBK value of 30%
reasonable for most data sets/sites. Bioavailability
has been assayed for soils similar to those in the
calibration step and the empirical comparison data
sets; 30% was used in the calibration step, and is
therefore recommended for similar sites. The default
provides a reasonable substitute when there are no
specific data. Speciation of lead compounds for a
particular exposure scenario could support adjusting
bioavailability if they are known to differ strongly
from 30%. In general, U.S. EPA supports using
bioavailability rates determined for the particular
soils of interest if available.
5.4.3. Activity Pattern Methodology
The limitations associated with the activity
pattern methodology relate to the availability and
quality of the underlying data used to model soil
ingestion rates. Real-time hand recording, where
observations are made by trained professionals
(rather than parents), may offer the advantage of
consistency in interpreting visible behaviors and may
be less subjective than observations made by
someone who maintains a care giving relationship to
the child. On the other hand, young children's
behavior may be influenced by the presence of
unfamiliar people (Davis et al., 1995). Groot et al.
(1998) indicated that parent observers perceived that
deviating from their usual care giving behavior by
observing and recording mouthing behavior appeared
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to have influenced the children's behavior. With
video-transcription methodology, an assumption is
made that the presence of the videographer or camera
does not influence the child's behavior. This
assumption may result in minimal biases introduced
when filming newborns, or when the camera and
videographer are not visible to the child. However, if
the children being studied are older than newborns
and can see the camera or videographer, biases may
be introduced. Ferguson et al. (2006) described
apprehension caused by videotaping and described
situations where a child's awareness of the
videotaping crew caused "play-acting" to occur, or
parents indicated that the child was behaving
differently during the taping session. Another
possible source of measurement error may be
introduced when children's movements or positions
cause their mouthing not to be captured by the
camera. Data transcription errors can bias results in
either the negative or positive direction. Finally,
measurement error can occur if situations arise in
which care givers are absent during videotaping and
researchers must stop videotaping and intervene to
prevent risky behaviors (Zartarian et al., 1995).
Survey response studies rely on responses to
questions about a child's mouthing behavior posed to
parents or care givers. Measurement errors from
these studies could occur for a number of different
reasons, including language/dialect differences
between interviewers and respondents, question
wording problems and lack of definitions for terms
used in questions, differences in respondents'
interpretation of questions, and recall/memory
effects.
Other data collection methodologies (in-person
interview, mailed questionnaire, or questions
administered in "test" format in a school setting) may
have had specific limitations. In-person interviews
could result in either positive or negative response
bias due to distractions posed by young children,
especially when interview respondents
simultaneously care for young children and answer
questions. Other limitations include positive or
negative response bias due to respondents'
perceptions of a "correct" answer, question wording
difficulties, lack of understanding of definitions of
terms used, language and dialect differences between
investigators and respondents, respondents' desires to
avoid negative emotions associated with giving a
particular type of answer, and respondent memory
problems ("recall" effects) concerning past events.
Mailed questionnaires have many of the same
limitations as in-person interviews, but may allow
respondents to respond when they are not distracted
by childcare duties. An in-school test format is more
problematic than either interviews or mailed surveys,
because respondent bias related to teacher
expectations could influence responses.
One approach to evaluating the degree of bias in
survey response studies may be to make use of a
surrogate biomarker indicator providing suggestive
evidence of ingestion of significant quantities of soil
(although quantitative estimates would not be
possible). The biomarker technique measures the
presence of serum antibodies to Toxocara species, a
parasitic roundworm from cat and dog feces. Two
U.S. studies have found associations between
reported soil ingestion and positive serum antibody
tests for Toxocara infection (Marmor et al., 1987;
Glickman et al., 1981); a third (Nelson et al., 1996)
has not, but the authors state that reliability of survey
responses regarding soil ingestion may have been an
issue. Further refinement of survey response
methodologies, together with recent NHANES data
on U.S. prevalence of positive serum antibody status
regarding infection with Toxocara species, may be
useful.
5.4.4. Key Studies: Representativeness of U.S.
Population
The two key studies of Dutch and Jamaican
children may represent different conditions and
different study populations than those in the United
States; thus, it is unclear to what extent those
children's soil ingestion behaviors may differ from
U.S. children's soil ingestion behaviors. The subjects
in the Davis and Mirick (2006) study may not have
been representative of the general population since
they were selected for their high compliance with the
protocol from a previous study.
Limitations regarding the key studies performed
in the United States for estimating soil and dust
ingestion rates in the entire population of U.S.
children ages 0 to <21 years fall into the broad
categories of geographic range and demographics
(age, sex, race/ethnicity, socioeconomic status).
Regarding geographic range, the two most
obvious issues relate to soil types and climate. Soil
properties might influence the soil ingestion
estimates that are based on excreted tracer elements.
The Davis et al. (1990); Calabrese et al. (1989);
Barnes (1990); Davis and Mirick (2006); and
Calabrese et al. (1997a) tracer element studies were
in locations with soils that had sand content ranging
from 21-80%, silt content ranging from 16-71%, and
clay content ranging from 3-20% by weight, based
on data from USDA (2008). The location of children
in the Calabrese et al. (1997b) study was not
specified, but due to the original survey response
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study's occurrence in western Massachusetts, the soil
types in the vicinity of the Calabrese et al. (1997b)
study are likely to be similar to those in the Calabrese
et al. (1989) and Barnes (1990) study.
The Hogan et al. (1998) study included locations
in the central part of the United States (an area along
the Kansas/Missouri border, and an area in western
Illinois) and one in the eastern United States
(Palmerton, Pennsylvania). The only key study
conducted in the southern part of the United States
was Vermeer and Frate (1979).
Children might be outside and have access to soil
in a very wide range of weather conditions (Wong et
al., 2000). In the parts of the United States that
experience moderate temperatures year-round, soil
ingestion rates may be fairly evenly distributed
throughout the year. During conditions of deep snow
cover, extreme cold, or extreme heat, children could
be expected to have minimal contact with outside
soil. All children, regardless of location, could ingest
soils located indoors in plant containers, soil derived
particulates transported into dwellings as ambient
airborne particulates, or outdoor soil tracked inside
buildings by human or animal building occupants.
Davis et al. (1990) did not find a clear or consistent
association between the number of hours spent
indoors per day and soil ingestion, but reported a
consistent association between spending a greater
number of hours outdoors and high (defined as the
uppermost tertile) soil ingestion levels across all three
tracers used.
The key tracer element studies all took place in
northern latitudes. The temperature and precipitation
patterns that occurred during these four studies' data
collection periods were difficult to discern due to no
mention of specific data collection dates in the
published articles. The Calabrese et al. (1989) and
Barnes (1990) study apparently took place in mid to
late September 1987 in and near Amherst,
Massachusetts; Calabrese et al. (1997a) apparently
took place in late September and early October 1992,
in Anaconda, Montana; Davis et al. (1990) took place
in July, August, and September 1987, in Richland,
Kennewick, and Pasco, Washington; and Davis and
Mirick (2006) took place in the same Washington
state location in late July, August, and very early
September 1988 (raw data). Inferring exact data
collection dates, a wide range of temperatures may
have occurred during the four studies' data collection
periods (daily lows from 22-60°F and 25-48°F, and
daily highs from 53-81 F and 55-88 F in Calabrese
et al. [1989] and Calabrese et al. [1997a],
respectively, and daily lows from 51-72°F and
51-67°F, and daily highs from 69-103°F and
80-102°F in Davis et al. [1990] and Davis and Mirick
[2006], respectively) (NCDC, 2008). Significant
amounts of precipitation occurred during Calabrese et
al. (1989) (more than 0.1 inches per 24-hour period)
on several days; somewhat less precipitation was
observed during Calabrese et al. (1997a);
precipitation in Kennewick and Richland during the
data collection periods of Davis et al. (1990) was
almost non-existent; there was no recorded
precipitation in Kennewick or Richland during the
data collection period for Davis and Mirick (2006)
(NCDC, 2008).
The key biokinetic model comparison study
(Hogan et al., 1998) targeted three locations in more
southerly latitudes (Pennsylvania, southern Illinois,
and southern Kansas/Missouri) than the tracer
element studies. The biokinetic model comparison
methodology had an advantage over the tracer
element studies in that the study represented long-
term environmental exposures over periods up to
several years that would include a range of seasons
and climate conditions.
A brief review of the representativeness of the key
studies' samples with respect to sex and age
suggested that males and females were represented
roughly equally in those studies for which study
subjects' sex was stated. Children up to age 8 years
were studied in seven of the nine studies, with an
emphasis on younger children. Wong (1988);
Calabrese and Stanek. (1993); and Vermeer and Frate
(1979) are the only studies with children 8 years or
older.
A brief review of the representativeness of the key
studies' samples with respect to socioeconomic status
and racial/ethnic identity suggested that there were
some discrepancies between the study subjects and
the current U.S. population of children age 0 to
<21 years. The single survey response study
(Vermeer and Frate, 1979) was specifically targeted
toward a predominantly rural Black population in a
particular county in Mississippi. The tracer element
studies are of predominantly White populations,
apparently with limited representation from other
racial and ethnic groups. The Amherst, Massachusetts
study (Calabrese et al., 1989; Barnes, 1990) did not
publish the study participants' socioeconomic status
or racial and ethnic identities. The socioeconomic
level of the Davis et al. (1990) studied children was
reported to be primarily of middle to high income.
Self-reported race and ethnicity of relatives of the
children studied (in most cases, they were the parents
of the children studied) in Davis et al. (1990) were
White (86.5%), Asian (6.7%), Hispanic (4.8%),
Native American (1.0%), and Other (1.0%), and the
91 married or living-as-married respondents
identified their spouses as White (86.8%), Hispanic
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(7.7%), Asian (4.4%), and Other (1.1%). Davis and
Mirick (2006) did not state the race and ethnicity of
the follow-up study participants, who were a subset
of the original study participants from Davis et al.
(1990). For the Calabrese et al. (1997a) study in
Anaconda, Montana, population demographics were
not presented in the published article. The study
sample appeared to have been drawn from a door-to-
door census of Anaconda residents that identified
642 toilet trained children who were less than
72 months of age. Of the 414 children participating in
a companion study (out of the 642 eligible children
identified), 271 had complete study data for that
companion study, and of these 271, 97.4% were
identified as White and the remaining 2.6% were
identified as Native American, Black, Asian, and
Hispanic (Hwang et al., 1997). The 64 children in the
Calabrese et al. (1997a) study apparently were a
stratified random sample (based on such factors as
behavior during a previous study, the existence of a
disability, or attendance in daycare) drawn from the
642 children identified in the door-to-door census.
Presumably these children identified as similar races
and ethnicities to the Hwang et al. (1997) study
children. The Calabrese et al. (1997b) study indicated
that 11 of the 12 children studied were White.
In summary, the geographic range of the key
study populations was somewhat limited. Of those
performed in the United States, locations included
Massachusetts, Kansas, Montana, Missouri, Illinois,
Washington, and Pennsylvania. The two most
obvious issues regarding geographic range relate to
soil types and climate. Soil types were not always
described, so the representativeness of the key studies
related to soil types and properties is unclear. The key
tracer element studies all took place in northern
latitudes. The only key study conducted in the
southern part of the United States was Vermeer and
Frate (1979).
In terms of sex and age, males and females were
represented roughly equally in those studies for
which study subjects' sex was stated, while the
majority of children studied were under the age of
eight. The tracer element studies are of
predominantly White populations, with a single
survey response study (Vermeer and Frate, 1979)
targeted toward a rural Black population. Other racial
and ethnic identities were not well reported among
the key studies, nor was socioeconomic status. The
socioeconomic level of the Davis et al. (1990) studied
children was reported to be primarily of middle to
high income.
5.5. SUMMARY OF SOIL AND DUST
INGESTION ESTIMATES FROM KEY
STUDIES
Table 5-22 summarizes the soil and dust ingestion
estimates from the 12 key studies in chronological
order. For the U.S. tracer element studies, in order to
compare estimates that were calculated in a similar
manner, the summary is limited to estimates that use
the same basic algorithm of ([fecal and urine tracer
content] - [food and medication tracer content] )/[soil
or dust tracer concentration]. Note that several of the
published reanalyses suggest different variations on
these algorithms, or suggest adjustments that should
be made for various reasons (Calabrese and Stanek,
1995; Stanek and Calabrese, 1995a). Other
reanalyses suggest that omitting some of the data
according to statistical criteria would be a worthwhile
exercise. Due to the current state of the science
regarding soil and dust ingestion estimates, U.S. EPA
does not advise omitting an individual's soil or dust
ingestion estimate, based on statistical criteria, at this
point in time.
There is a wide range of estimated soil and dust
ingestion across key studies. Note that some of the
soil-pica ingestion estimates from the tracer element
studies were consistent with the estimated mean soil
ingestion from the survey response study of
geophagy behavior. The biokinetic model comparison
methodology's confirmation of central tendency soil
and dust ingestion default assumptions corresponded
roughly with some of the central tendency tracer
element study estimates. Also note that estimates
based on the activity pattern methodology are
comparable with estimates derived from the tracer
element methodology.
5.6. DERIVATION OF RECOMMENDED
SOIL AND DUST INGESTION VALUES
As stated earlier in this chapter, the key studies
were used as the basis for developing the soil and
dust ingestion recommendations shown in Table 5-1.
The following sections describe in more detail how
the recommended soil and dust ingestion values were
derived.
5.6.1. Central Tendency Soil and Dust Ingestion
Recommendations
For the central tendency recommendations shown
in Table 5-1, Van Wijnen et al. (1990) published soil
ingestion "LTM" estimates based on infants older
than 6 weeks but less than 1 year old (exact ages
unspecified). During "bad" weather (>4 days per
week of precipitation), the geometric mean estimated
LTM values were 67 and 94 milligrams soil
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(dry weight)/day; during "good" weather
(<2 days/week of precipitation) the geometric mean
estimated LTM values were 102 milligrams soil
(dry weight)/day (VanWijnen et al., 1990). These
values were not corrected to exclude dietary intake of
the tracers on which they were based. The developers
of the IEUBK model used these data as the basis for
the default soil and dust intakes for the 6 to
<12 month old infants in the IEUBK model
(U.S. EPA, 1994b) of 38.25 milligrams soil/day and
46.75 mg house dust/day, for a total soil + dust intake
default assumption of 85 mg/day for this age group
(U.S. EPA, 1994a).
Further evidence of dust intake by infants has
been conducted in the context of evaluating blood
lead levels and the potential contributions of lead
from three sources: bone turnover, food sources, and
environmental exposures such as house dust. Manton
et al. (2000) conducted a study with older infants and
young children, and concluded that appreciable
quantities of dust were ingested by infants. Gulson et
al. (2001) studied younger infants than Manton et al.
(2000) and did not explicitly include dust sources, but
the authors acknowledged that, based on ratios of
different isotopes of lead found in infants' blood and
urine, there appeared to be a non-food, non-bone
source of lead of environmental origin that
contributed "minimally," relative to food intakes and
bone turnover in 0- to 6-month-old infants.
The Hogan et al. (1998) data for 38 infants (one
group N = 7 and one group N = 31) indicated that the
IEUBK default soil and dust estimate for 6 to
<12 month olds (85 mg/day) over-predicted blood
lead levels in this group, suggesting that applying an
85 mg soil + dust (38 mg soil + 47 mg house dust)
per day estimate for 6 months' exposure may be too
high for this life stage.
For the larger of two groups of infants aged 6 to
<12 months in the Hogan et al. (1998) study (N=31),
the default IEUBK value of 85 mg/day predicted
geometric mean blood lead levels of 5.2 ug/dL versus
3.8 ug/dL actual measured blood lead level (a ratio of
1.37). It is possible that the other major sources of
lead accounted for in the IEUBK model (dietary and
drinking water lead) are responsible for part of the
over-prediction seen with the Hogan et al. (1998)
study. Rounded to the ones place, the default assumed
daily lead intakes were (dietary) 6 ug/day and
(drinking water) 1 ug/day, compared to the soil lead
intake of 8 ug/day and house dust lead intake of
9 ug/day (U.S. EPA, 1994b). The dietary lead intake
default assumption thus might be expected to be
responsible for the over-predictions as well as the soil
and dust intake, since these three sources (diet, soil,
and dust) comprise the majority of the total lead
intake in the model. Data from Manton et al. (2000)
suggest that the default assumption for dietary lead
intake might be somewhat high (reported geometric
mean daily lead intake from food in Manton et al.,
2000 was 3.2 ug/day, arithmetic mean 3.3 ug/day).
Making use of the epidemiologic data from the
larger group of 31 infants in the Hogan et al. (1998)
study, it is possible to develop an extremely rough
estimate of soil + dust intake by infants 6 weeks
to <12 months of age. The ratio of the geometric
mean lEUBK-predicted to actual measured blood
lead levels in 31 infants was 1.37. This value may be
used to adjust the soil and dust intake rate for the 6 to
<12 month age range. Using the inverse of 1.37
(0.73) and multiplying the 85 mg/day soil + house
dust intake rate by this value, gives an adjusted value
of 62 mg/day soil + dust, rounded to one significant
figure at 60 mg/day. The 38 mg soil/day intake rate,
multiplied by the 0.73 adjustment factor, yields
28 mg soil per day (rounding to 30 mg soil per day);
the 47 mg house dust/day intake rate multiplied by
0.73 yields 34 mg house dust per day (rounding to
30 mg house dust per day). These values, adjusted
from the IEUBK default values, are the basis for the
soil (30 mg/day) and dust (30 mg/day)
recommendations for children aged 6 weeks to
12 months.
For children age 1 to <6 years, the IEUBK default
values used in the Hogan et al. (1998) study were:
135 mg/day for 1, 2, and 3 year olds; 100 mg/day for
4 year olds; 90 mg/day for 5 year olds; and
85 mg/day for 6 year olds. These values were based
on an assumption of 45% soil, 55% dust (U.S. EPA,
1994a). The time-averaged daily soil + dust ingestion
rate for these 6 years of life is 113 mg/day,
dry-weight basis. The Hogan et al. (1998) study
found the following over- and under-predictions of
blood lead levels, compared to actual measured blood
lead levels, using the default values shown in Table
5-23. Apportioning the 113 mg/day, on average, into
45% soil and 55% dust (U.S. EPA, 1994a), yields an
average for this age group of 51 mg/day soil,
62 mg/day dust. Rounded to one significant figure,
these values are 50 and 60 mg/day, respectively. The
60 mg/day dust would be comprised of a combination
of outdoor soil tracked indoors onto floors, indoor
dust on floors, indoor settled dust on non-floor
surfaces, and probably a certain amount of inhaled
suspended dust that is swallowed and enters the
gastrointestinal tract. Soil ingestion rates were
assumed to be comparable for children age 1 to <6
years and 6 to <21 years, and therefore the same
recommended values were used for both age groups.
Estimates derived by Ozkaynak et al. (2010) suggest
soil and dust ingestion rates comparable to other
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estimates in the literature based on tracer element
methodology (i.e., a mean value of 68 mg/day).
The recommended soil and dust ingestion rate of
50 mg/day for adults was taken from the overall
mean value of 52 mg/day for the adults in the Davis
and Mirick (2006) study. Based on this value, the
recommended adult soil and dust ingestion value is
estimated to be 50 mg/day. There are no available
studies estimating the ingestion of dust by adults,
therefore, the recommended values for soil and dust
were derived from the soil + dust ingestion, assuming
45% soil and 55% dust contribution.
5.6.2. Upper Percentile, Soil Pica, and Geophagy
Recommendations
Upper percentile estimates for children 3 to
<6 years old were derived from Ozkaynak et al.
(2010) and Stanek and Calabrese (1995a). These two
studies had similar estimates of 95th percentile value
(i.e., 224 mg/day and 207 mg/day, respectively).
Rounding to one significant figure, the recommended
upper percentile estimate of soil and dust ingestion is
200 mg/day. Soil and dust ingestion
recommendations were obtained from Ozkaynak et
al. (2010). For the upper percentile soil pica and
geophagy recommendations shown in Table 5-1, two
primary lines of evidence suggest that at least some
U.S. children exhibit soil-pica behavior at least once
during childhood. First, the survey response studies
of reported soil ingestion behavior that were
conducted in numerous U.S. locations and of
different populations consistently yield a certain
proportion of respondents who acknowledge soil
ingestion by children. The surveys typically did not
ask explicit and detailed questions about the soil
ingestion incidents reported by the care givers who
acknowledged soil ingestion in children. Responses
conceivably could fall into three categories:
(1) responses in which care givers interpret visible
dirt on children's hands, and subsequent
hand-to-mouth behavior, as soil ingestion;
(2) responses in which care givers interpret
intentional ingestion of clay, "dirt" or soil as soil
ingestion; and (3) responses in which care givers
regard observations of hand-to-mouth behavior of
visible quantities of soil as soil ingestion. Knowledge
of soils' bulk density allows inferences to be made
that these latter observed hand-to-mouth soil
ingestion incidents are likely to represent a quantity
of soil that meets the quantity part of the definition of
soil-pica used in this chapter, or 1,000 mg.
Occasionally, what is not known from survey
response studies is whether the latter type of survey
responses include responses regarding repeated soil
ingestion that meets the definition of soil-pica used in
this chapter. The second category probably does
represent ingestion that would satisfy the definition
of soil-pica as well as geophagy. The first category
may represent relatively small amounts that appear to
be ingested by many children based on the Hogan et
al. (1998) study and the tracer element studies.
Second, the U.S. tracer studies report a wide range of
soil ingestion values. Due to averaging procedures
used, for 4, 7, or 8 day periods, the rounded range of
these estimates of soil ingestion behavior that
apparently met the definition of soil-pica used in this
chapter is from 400 to 41,000 mg/day. The
recommendation of 1,000 mg/day for soil-pica is
based on this range.
Although there were no tracer element studies or
biokinetic model comparison studies performed for
children 15 to <21 years, in which soil-pica behavior
of children in this age range has been investigated,
U.S. EPA is aware of one study documenting pica
behavior in a group that includes children in this age
range (Hyman et al., 1990). The study was not
specific regarding whether soil-pica (versus other
pica substances) was observed, nor did it identify the
specific ages of the children observed to practice
pica. In the absence of data that can be used to
develop specific soil-pica soil ingestion
recommendations for children aged 15 years and 16
to <21 years, U.S. EPA recommends that risk
assessors who need to assess risks via soil and dust
ingestion to children ages 15 to <21 years use the
same soil ingestion rate as that recommended for
younger children, in the 1 to <6, 6 to <11, and 11 to
<16 year old age categories.
Researchers who have studied human geophagy
behavior around the world typically have studied
populations in specific locations, and often include
investigations of soil properties as part of the
research (Wilson, 2003; Aufreiter et al., 1997). Most
studies of geophagy behavior in the United States
were survey response studies of residents in specific
locations who acknowledged eating clays. Typically,
study subjects were from a relatively small area such
as a county, or a group of counties within the same
state. Although geophagy behavior may have been
studied in only a single county in a given state,
documentation of geophagy behavior by some
residents in one or more counties of a given state may
suggest that the same behavior also occurs elsewhere
within that state.
A qualitative description of amounts of soil
ingested by geophagy practitioners was provided by
Vermeer and Frate (1979) with an estimated mean
amount, 50 g/day, that apparently was averaged over
32 adults and 18 children. The 18 children whose
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caregivers acknowledged geophagy (or more
specifically, eating of clay) were (N= 16) ages 1 to 4
and (N=2) ages 5 to 12 years. The definition of
geophagy used included consumption of clay "on a
regular basis over a period of weeks." U.S. EPA is
recommending this 50 g/day value for geophagy. This
mean quantity is roughly consistent with a median
quantity reported by Geissler et al. (1998) in a survey
response study of geophagy in primary school
children in Nyanza Province, Kenya (28 g/day, range
8 to 108 g/day; interquartile range 13 to 42 g/day).
Recent studies of pica among pregnant women in
various U.S. locations (Rainville, 1998; Corbett et al.,
2003; Smulian et al., 1995) suggest that clay
geophagy among pregnant women may include
children less than 21 years old (Smulian et al., 1995;
Corbett et al., 2003). Smulian provides a quantitative
estimate of clay consumption of approximately
200-500 g/week, for the very small number of
geophagy practitioners (N= 4) in that study's sample
(N= 125). If consumed on a daily basis, this quantity
(approximately 30 to 70 g/day) is roughly consistent
with the Vermeer and Frate (1979) estimated mean of
50 g/day.
Johns and Duquette (1991) describe use of clays
in baking bread made from acorn flour, in a ratio of
1 part clay to 10 or 20 parts acorn flour, by volume,
in a Native American population in California, and in
Sardinia (~12 grams clay suspended in water added
to 100 grams acorn). Either preparation method
would add several grams of clay to the final prepared
food; daily ingestion of the food would amount to
several grams of clay ingested daily.
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aged 1 to 6. J Soil Contam 7(2):227-242.
Stanek, EJ; Calabrese, EJ; Barnes, R. (1999) Soil
ingestion estimates for children in Anaconda
using trace element concentrations in
different particle size fractions. Hum Ecol
Risk Assess 5(3):547-558.
Stanek, EJ; Calabrese, EJ; Zorn, M. (200la) Biasing
factors for simple soil ingestion estimates in
mass balance studies of soil ingestion. Hum
Ecol Risk Assess 7(2):329-355.
Stanek, EJ; Calabrese, EJ; Zorn, M. (200 Ib) Soil
ingestion distributions for Monte Carlo risk
assessment in children. Hum Ecol Risk
Assess 7(2):357-368.
USDA (U.S. Department of Agriculture). (1999) Soil
taxonomy: a basic system of soil
classification for making and interpreting
soil surveys. National Resources
Conservation Service, Agriculture
Handbook No. 436. Available online at
http://soils.usda.gov/technical/classification/
taxonomy/.
USDA (United States Department of Agriculture).
(2008) Web soil survey. Natural Resources
Conservation Service. Available online at
http://websoilsurvey.nrcs.usda.gov/app/Hom
ePage.htm. Accessed on February 25, 2008.
U.S. DOC (Department of Commerse) (2008)
Table 2: Annual Estimates of the Population
by Sex and Selected Age Groups for the
United States: April 1, 2000 to July 1, 2007
(NC-EST2007-02). Bureau of the Census,
Population Division, Washington, DC.
U.S. EPA (Environmental Protection Agency).
(1994a) Guidance manual for the IEUBK
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Waste and Emergency Response
Washington, DC; EPA 540/R-93/081.
U.S. EPA (Environmental Protection Agency).
(1994b) Technical support document:
parameters and equations used in the
integrated exposure uptake biokinetic
(IEUBK) model for lead in children
(v 0.99d). Technical Review Workgroup for
Lead, Washington, DC and the
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EPA/540/R-94/040. Available online at
http ://www. epa. gov/superfund/lead/products
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U.S. EPA. (Environmental Protection Agency).
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EPA/630/P-03/003F. Available online at
http ://www. epa. gov/raf/publications/pdfs/A
GEGROUPS.PDF
U.S. EPA. (Environmental Protection Agency).
(2010) The stochastic human exposure and
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
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Page
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Chapter 5—Soil and Dust Ingestion
Table 5-3. Soil, Dust, and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study Children
Tracer Element
Aluminum
soil
dust
soil/dust combined
Barium
soil
dust
soil/dust combined
Manganese
soil
dust
soil/dust combined
Silicon
soil
dust
soil/dust combined
Vanadium
soil
dust
soil//dust combined
Yttrium
soil
dust
soil/dust combined
Zirconium
soil
dust
soil/dust combined
Titanium
soil
dust
soil/dust combined
N
64
64
64
64
64
64
64
64
64
64
64
64
62
64
62
62
64
62
62
64
62
64
64
64
Mean
153
317
154
32
31
29
-294
-1,289
-496
154
964
483
459
453
456
85
62
65
21
27
23
218
163
170
Median
29
31
30
-37
-18
-19
-261
-340
-340
40
49
49
96
127
123
9
15
11
16
12
11
55
28
30
Ingestion (mg/day)
SD
852
1,272
629
1,002
860
868
1,266
9,087
1,974
693
6,848
3,105
1,037
1,005
1,013
890
687
717
209
133
138
1,150
659
691
95th Percentile
223
506
478
283
337
331
788
2,916
3,174
276
692
653
1,903
1,918
1,783
106
169
159
110
160
159
1,432
1,266
1,059
Maximum
6,837
8,462
4,929
6,773
5,480
5,626
7,281
20,575
4,189
5,549
54,870
24,900
5,676
6,782
6,736
6,736
5,096
5,269
1,391
789
838
6,707
3,354
3,597
SD = Standard deviation.
N = Number of subjects.
Source: Calabrese et al.,
1989.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table
5-4. Amherst, Massachusetts
Tracer
element
Al
Ba
Mn
Si
Ti
V
Y
Zr
Soil-Pica Child's Daily Ingestion
(mg/day)
Estimated Soil
Weekl
74
458
2,221
142
1,543
1,269
147
86
Estimates by Tracer and by Week
Ingestion (mg/day)
Week 2
13,600
12,088
12,341
10,955
11,870
10,071
13,325
2,695
Source: Calabrese et al., 1991.
Table 5-5. Van Wijnen et al. (1990) Limiting Tracer Method (LTM) Soil Ingestion Estimates for Sample of Dutch
Children
Daycare Center
Age (years) Sex
Birth to <1
lto<2
2to<3
3to<4
4to<5
All girls
All boys
Total
b
N
GM
LTM
GSD
NA
Source:
JV
Girls 3
Boys 1
Girls 20
Boys 17
Girls 34
Boys 17
Girls 26
Boys 29
Girls 1
Boys 4
86
72
162a
Age and/or sex not registered for 8 children;
Age not registered for 7 children; geometric
= Number of subjects.
= Geometric mean.
= Limiting tracer method.
= Geometric standard deviation.
= Not available.
Adapted from Van Wijnen et al., 1990.
GMLTM
(mg/day)
81
75
124
114
118
96
111
110
180
99
117
104
111
GSD LTM
(mg/day)
1.09
1.87
1.47
1.74
1.53
1.57
1.32
1.62
1.70
1.46
1.60
N
NA
NA
3
5
4
8
6
8
19
18
36
42
78b
Campground
GMLTM
(mg/day)
NA
NA
207
312
367
232
164
148
164
136
179
169
174
GSD LTM
(mg/day)
NA
NA
1.99
2.58
2.44
2.15
1.27
1.42
1.48
1.30
1.67
1.79
1.73
one untransformed value = 0.
mean LTM value =140.
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September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-6. Estimated Geometric Mean Limiting Tracer Method (LTM) Soil Ingestion Values of Children
Attending Daycare Centers According to Age, Weather Category, and Sampling Period
First Sampling Period
Weather Category Age (years)
Bad <1
(>4 days/week 1 to <2
precipitation) 2 to <3
4to<5
Reasonable <1
(2-3 days/week 1 to <2
precipitation) 2 to <3
3to<4
4to<5
Good <1
(<2 days/week 1 to <2
precipitation) 2 to <3
3to<4
4to<5
N = Number of subjects.
LTM = Limiting tracer method.
Source: Van Wijnen et al., 1990.
N
3
18
33
5
4
42
65
67
10
Estimated Geometric
Mean
LTM Value
(mg/day)
94
103
109
124
102
229
166
138
132
Second
N
3
33
48
6
1
10
13
19
1
Sampling Period
Estimated Geometric
Mean
LTM Value
(mg/day)
67
80
91
109
61
96
99
94
61
Table 5-7. Estimated Soil Ingestion for Sample of Washington
Mean
Element . , , .
(mg/day)
Aluminum
Silicon
Titanium
Minimum
Maximum
b
Source:
38.9
82.4
245.5
38.9
245.5
,, ,. Standard Error of the
Median
. , , . Mean
(mg/day) ,,
^ " " (mg/day)
25.3 14.4
59.4 12.2
81.3 119.7
25.3 12.2
81.3 119.7
State Children3
Range
(mg/day)b
-279.0 to 904. 5
^104.0 to 534.6
-5,820. 8 to 6, 182
-5,820.8
6,182.2
2
Excludes three children who did not provide any samples (N= 101).
Negative values occurred as a result of correction for non-soil sources of the tracer elements. For aluminum, lower end of range
published as 279.0 mg/day in article appears to be a typographical error that omitted the negative sign.
Adapted from Davis et al., 1990.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-8. Soil Ingestion Estimates for 64 Anaconda Children
Tracer
Al
Ce
La
Nd
Si
Ti
Y
Zr
BTM soil
BTM dust
P
SD
BTM
NA
Note:
Source:
Estimated Soil Ing
Pi
-202.8
-219.8
-10,673
-387.2
-128.8
-15,736
-441.3
-298.3
NA
NA
= Percentile.
= Standard deviation.
p50
-3.3
44.9
84.5
220.1
-18.2
11.9
32.1
-30.8
20.1
26.8
p75
17.7
164.6
247.9
410.5
1.4
398.2
85.0
17.7
68.9
198.1
p90
66.6
424.7
460.8
812.6
36.9
1,237.9
200.6
94.6
223.6
558.6
estion (mg/day)
p95
94.3
455.8
639.0
875.2
68.9
1,377.8
242.6
122.8
282.4
613.6
Max
461.1
862.2
1,089.7
993.5
262.3
4,066.6
299.3
376.1
609.9
1,499.4
Mean
2.7
116.9
8.6
269.6
-16.5
-544.4
42.3
-19.6
65.5
127.2
SD
95.8
186.1
1,377.2
304.8
57.3
2,509.0
113.7
92.5
120.3
299.1
= Best Tracer Methodology.
Not available.
Negative values are a result of limitations in the methodology.
Calabrese et al., 1997a
Table 5-9. Soil Ingestion Estimates for Massachusetts Children Displaying Soil Pica Behavior (mg/day)
Note:
Source:
Study day
1
2
3
4
5
6
7
Al-based estimate
53
7,253
2,755
725
5
1,452
238
Si-based estimate
9
2,704
1,841
534
-10
1,373
76
Ti-based estimate
153
5,437
2,007
801
21
794
84
Negative values are a result of limitations in the methodology.
Calabrese et al., 1997b.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-10. Average Daily
Type of Estimate
Mean
Median
SD
Range
SD
Note:
Source:
Al
168
7
510
-15 to +1,783
Soil Ingestion
Si
89
0
270
-46 to +931
Soil and Dust Ingestion Estimate (mg/day)
Dust Ingestion
Ti Al Si
448 260 297
32 13 2
1,056 759 907
-47to+3,581 -39to+2,652 -351to+3,145
Ti
415
66
1,032
-98 to +3,632
= Standard deviation.
Negative values are a result of limitations in the methodology.
Calabrese et al., 1997b.
Participant
Childb
Mother0
Father11
b
c
d
SD
Source:
Table 5-11. Mean
Tracer Element
Aluminum
Silicon
Titanium
Aluminum
Silicon
Titanium
Aluminum
Silicon
Titanium
and Median Soil
Ingestion (mg/day) by
Estimated Soil Ingestion8 (mg
Mean
36.7
38.1
206.9
92.1
23.2
359.0
68.4
26.1
624.9
Median
33.3
26.4
46.7
0
5.2
259.5
23.2
0.2
198.7
Family Member
/day)
SD
35.4
31.4
277.5
218.3
37.0
421.5
129.9
49.0
835.0
Maximum
107.9
95.0
808.3
813.6
138.1
1,394.3
537.4
196.8
2,899.1
For some study participants, estimated soil ingestion resulted in a negative value. These estimates have been set to 0 mg/day for
tabulation and analysis.
Results based on 12 children with complete food, excreta, and soil data.
Results based on 16 mothers with complete food, excreta, and soil data.
Results based on 17 fathers with complete food, excreta, and soil data.
= Standard deviation.
Davis and Mirick, 2006.
Exposure Factors Handbook
September 2011
Page
5-43
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-12. Estimated Soil Ingestion for Six High
Child Month
11 1
2
3
4
12 1
2
3
4
14 1
2
3
4
18 1
2
3
4
22 1
2
3
4
27 1
2
3
4
= No data.
Source: Calabrese and Stanek, 1993.
Soil Ingesting Jamaican Children
Estimated soil ingestion (mg/day)
55
1,447
22
40
0
0
7,924
192
1,016
464
2,690
898
30
10,343
4,222
1,404
0
-
5,341
0
48,314
60,692
51,422
3,782
Table 5-13. Positive/Negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989) Study: Effect
on Mean Soil Ingestion Estimate (mg/day)a
Negative Error
Tracer Lack of Fecal T° * i-KT ±- T° * i T, M-
lotal Negative lotal Positive ^T ^ ^ ,^- • ,*, A ,• + ,1,
Sample on Final Other Cause ^ ^ Net Error Original Mean Adjusted Mean
„; , „ Error Error
Study Day
Aluminum
Silicon
Titanium
Vanadium
Yttrium
Zirconium
14
15
82
66
8
6
11
6
187
55
26
91
25
21
269
121
34
97
43
41
282
432
22
5
+18
+20
+13
+311
-12
-92
153
154
218
459
85
21
136
133
208
148
97
113
a How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The cumulative total negative
error is estimated to bias the mean estimate by 25 mg/day downward. However, aluminum has positive error biasing the original
mean upward by 43 mg/day. The net bias in the original mean was 18 mg/day positive bias. Thus, the original 156 mg/day mean for
aluminum should be corrected downward to 136 mg/day.
b Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
Source: Calabrese and Stanek, 1995.
Page Exposure Factors Handbook
5-44 September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-14. Predicted
Dust ingestion/hand-
to-mouth
Dust ingestion/ 1 OOQ
object-to-mouth
Total dust ingestion3 1,000
Soil ingestion/hand- . „„„
to-mouth
Total ingestion 1,000
Soil and Dust Ingestion Rates for Children Age 3 to <6 Years (mg/day)
Mean
19.8
6.9
27
41.0
67.6
Email from Haluk Ozkaynak (NERL, U. S
Source: Ozkaynak et al., 2010.
Percentile
5
0.6
0.1
0.2
4.9
25 50
3
0
5
16
EPA) to Jacqueline
4 8.4
7 2.4
13
3 15.3
.8 37.8
75
21.3
7.4
44.9
83.2
95
73.7
27.2
109
175.6
224.0
100
649.3
252.7
360
1,367.4
1,369.7
Moya (NCEA, EPA) dated 3/8/11.
Table 5-15. Estimated Daily Soil Ingestion for East Helena, Montana Children
Estimation
Method
Aluminum
Silicon
Titanium
Minimum
Source: Binder etal.,
Mean
(mg/day)
181
184
1,834
108
1986.
Median
(mg/day)
121
136
618
88
Standard Deviation
(mg/day)
203
175
3,091
121
Range
(mg/day)
25-1,324
31-799
4-17,076
4-708
95th Percentile
(mg/day)
584
578
9,590
386
Geometric Mean
(mg/day)
128
130
401
65
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-16. Estimated Soil Ingestion for Sample of Dutch Nursery School Children
Child
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Arithmetic Mean
= No data.
Sample
Number
L3
L14
L25
L5
L13
L27
L2
L17
L4
Lll
L8
L21
L12
L16
L18
L22
LI
L6
L7
L9
L10
L15
L19
L20
L23
L24
L26
Soil Ingestion as
Calculated from Ti
(mg/day)
103
154
130
131
184
142
124
670
246
2,990
293
313
1,110
176
11,620
11,320
3,060
624
600
133
354
2,400
124
269
1,130
64
184
1,431
Soil Ingestion as
Calculated from Al
(mg/day)
300
211
23
_
103
81
42
566
62
65
_
-
693
-
_
77
82
979
200
-
195
-
71
212
51
566
56
232
Soil Ingestion as
Calculated from AIR
(mg/day)
107
172
-
71
82
84
84
174
145
139
108
152
362
145
120
-
96
111
124
95
106
48
93
274
84
-
-
129
Limiting Tracer
(mg/day)
103
154
23
71
82
81
42
174
62
65
108
152
362
145
120
77
82
111
124
95
106
48
71
212
51
64
56
105
AIR = Acid insoluble residue.
Source: Adapted from Clausing et al., 1987.
Table 5-17.
Child
1
2
3
4
5
6
Arithmetic Mean
Estimated Soil Ingestion
Sample
G5
G6
Gl
G2
G8
G3
G4
G7
for Sample of Dutch
Soil Ingestion as
Calculated from Ti
(mg/day)
3,290
4,790
28
6,570
2,480
28
1,100
58
2,293
Hospitalized, Bedridden Children
Soil Ingestion as
Calculated from Al
(mg/day)
57
71
26
94
57
77
30
38
56
Limiting Tracer
(mg/day)
57
71
26
84
57
28
30
38
49
Source: Adapted from Clausing et al., 1987.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-18. Items Ingested by Low-Income Mexican-Born
Pica During Pregnancy in the United States
Women Who Practiced
(TV =46)
Item Ingested Number (%) Ingesting Items
Dirt
Bean stones8
Magnesium carbonate
Ashes
Clay
Ice
Otherb
11(24)
17 (37)
8(17)
5(11)
4(9)
18(39)
17 (37)
a Little clods of dirt found among unwashed beans.
b Including eggshells, starch, paper, lipstick, pieces of clay pot, and adobe.
jV = Number of individuals reporting pica behavior.
Source: Simpson et al., 2000.
Table 5-19. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children"
(mg/day)
Type of Estimate
Overall
Al
Mn
Si
Ti
Zr
Number of Samples
64
64
33
19
63
56
52
61
62
Mean
25th Percentile
50th Percentile
75th Percentile
90th Percentile
95th Percentile
Maximum
179
10
45
88
186
208
7,703
122
10
19
73
131
254
4,692
655
28
65
260
470
518
17,991
1,053
35
121
319
478
17,374
17,374
139
5
32
94
206
224
4,975
271
8
31
93
154
279
12,055
112
8
47
177
340
398
845
165
0
15
47
105
144
8,976
23
0
15
41
87
117
208
a For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then evaluated for each
child. The values in the column "overall" correspond to percentiles of the distribution of these means over the 64 children. When
specific trace elements were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the specific
trace element were formed for 108 days for each subject. The mean soil ingestion estimate was again evaluated. The distribution of
these means for specific trace elements is shown.
Source: Stanek and Calabrese, 1995b.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
Table 5-20. Estimated Distribution of Individual Mean Daily Soil Ingestion Based
on Data for 64 Subjects Projected over 365 Days"
Range
50th Percentile (median)
90th Percentile
95th Percentile
a Based on fitting a lognormal distribution to model daily soil
b Subject with pica excluded.
Source: Stanekand Calabrese, 1995b.
1-2,268 mg/dayb
75 mg/day
1,1 90 mg/day
1,751 mg/day
ingestion values.
Table 5-21. Prevalence of Non-Food Consumption by Substance for NHANES I and NHANES II
NHANES I (age 1-74 years) NHANES II (age 6 months-74 years)
N (sample size) = 20,724 (unweighted); N (sample size) = 25,271 (unweighted);
193,716,939 (weighted) 203,432,944 (weighted)
Substance
Any Non-Food
Substance
Clay
Starch
Paint and
Plaster
Dirt
Dirt and Clay
Other
Unweighted
Weighted
a
b
d
Source:
N
Unweighted Prevalence8
(Weighted)
732 7 5<>/
(4,900,370)
(ssSoi) 03%
(1953764) °'5%b
385 1 3o/o
(2,466,210)
190
(1,488,327) °'8%
95% Confidence TT N. . ,
. . , Unweighted
Interval (Weighted)
2 2-2 9% 48°
(2,237,993)
46
(223,361)
0.2-0.40/0 (45061915)
°-3-°-7% (2135,588)
216
(772,714)
1.1-1.5%
0 1 Q
°-6-°-9% (1,008,476)
, a 95% Confidence
Prevalence T , ,
Interval
1.1% 1.0-1.2%
0.1% 0.1-0.2%
0.2% 0.1-0.3%
0.6%c 0.4-0.8%
2.1%d 1.7-2.5%
0.5% 0.4-0.6%
= Raw counts.
= Adjusted to account for the unequal selection probabilities caused by the cluster design, item non-response, and planned
oversampling of certain subgroups, and representative of the civilian non-institutionalized Census population in the coterminous
United States.
Prevalence = Frequency (n) (weighted)/Sample Size (N) (weighted).
NHANES I sample size (<12 years): 4,968 (unweighted); 40,463,951 (weighted).
NHANES II sample size (<12 years): 6,834 (unweighted); 37,697,059 (weighted).
For those aged <12 years only; question not prompted for those >12 years.
Gavrelisetal., 2011.
Page
5-48
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Chapter 5—Soil and Dust Ingestion
Table 5-22. Summary of Estimates of Soil and Dust Ingestion by Adults
and Children (0.5 to 14 years old)
from Key Studies (nig/day)
Sample , , ,
Size A8e(year)
140 1 to!3+
89 Adult
52 0.3tol4
64 1 to <4
292 O.ltoactual
14
104
0
N
prediction
-------
Exposure Factors Handbook
Chapter 5 — Soil and Dust Ingestion
30%
25%-
20%
g
i 15%
D.
10%
5%
0%
-:;:
-:--
S
•
i
I
6 to «1 2 months
1
HS;
1 to <3 years
i
1
I
3 to <6 years
i
:k
1
09
V
3
to
1
UltttNESI
BWMEBI
i i i i
& £ & £
?* ? S Si
V V V "
S S S
-------
Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
8.0%
7.0% -
6.0% -
£ 5.0% -
4.0% -
3.0% -
2.0% -
1.0% -
0.0%
m
CTJ
NHANES
NHANES II
Figure 5-2. Prevalence of Non-Food Substance Consumption by Race, NHANES I and NHANES II.
Source: Gavrelis et al.,2011.
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September 2011
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Exposure Factors Handbook
Chapter 5—Soil and Dust Ingestion
4.0%
3.5% -
3.0% -
- 2.5%
0)
i 2.0% -
3
1.5% -
1.0% -
0.5% -
0.0%
NHANESI
]$10000-$19999
j $20 000 and Up
Not stated
NHANES II
Figure 5-3. Prevalence of Non-Food Substance Consumption by Income, NHANES I and NHANES II.
Source: Gavrelis et al., 2011.
Page
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
TABLE OF CONTENTS
LIST OF TABLES 6-ii
LIST OF FIGURES 6-v
6. INHALATION RATES 6-1
6.1. INTRODUCTION 6-1
6.2. RECOMMENDATIONS 6-2
6.3. KEY INHALATION RATE STUDIES 6-7
6.3.1. Brochu et al. (2006a) 6-7
6.3.2. Arcus-Arth and Blaisdell (2007) 6-7
6.3.3. Stifelman (2007) 6-9
6.3.4. U.S. EPA (2009) 6-9
6.3.5. Key Studies Combined 6-10
6.4. RELEVANT INHALATION RATE STUDIES 6-10
6.4.1. International Commission on Radiological Protection (ICRP) (1981) 6-10
6.4.2. U.S. EPA (1985) 6-11
6.4.3. Shamooetal. (1990) 6-11
6.4.4. Shamooetal. (1991) 6-12
6.4.5. Linn etal. (1992) 6-13
6.4.6. Shamooetal. (1992) 6-14
6.4.7. Spier etal. (1992) 6-14
6.4.8. Adams (1993) 6-15
6.4.9. Layton(1993) 6-16
6.4.10. Linn etal. (1993) 6-18
6.4.11. Rusconietal. (1994) 6-18
6.4.12. Price et al. (2003) 6-19
6.4.13. Brochu et al. (2006b) 6-19
6.4.14. Allan et al. (2009) 6-20
6.5. REFERENCES FOR CHAPTER 6 6-21
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September 2011 6-i
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
LIST OF TABLES
Table 6-1. Recommended Long-Term Exposure Values for Inhalation (Males and Females
Combined) 6-1
Table 6-2. Recommended Short-Term Exposure Values for Inhalation (Males and Females
Combined) 6-4
Table 6-3. Confidence in Recommendations for Long- and Short-Term Inhalation Rates 6-6
Table 6-4. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (nrYday) for
Free-Living Normal-Weight Males and Females Aged 2.6 Months to 96 Years 6-24
Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-Living Normal-Weight
Males, Females, and Males and Females Combined 6-25
Table 6-6. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (nrVday) for
Free-Living Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96
Years 6-27
Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) per Unit of
Body Weight (nrVkg-day) for Free-Living Normal-Weight Males and Females
Aged 2.6 Months to 96 Years 6-28
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/kg-day) for
Free-Living Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96
Years 6-29
Table 6-9. Physiological Daily Inhalation Rates (PDIRs) for Newborns Aged 1 Month or Less 6-30
Table 6-10. Non-Normalized Daily Inhalation Rates (nrVday) Derived Using Layton's (1993) Method
and CSFII Energy Intake Data 6-31
Table 6-11. Mean and 95th Percentile Inhalation Rate Values (nrVday) for
Males and Females Combined 6-32
Table 6-12. Summary of Institute of Medicine (IOM) Energy Expenditure Recommendations for
Active and Very Active People with Equivalent Inhalation Rates 6-33
Table 6-13. Mean Inhalation Rate Values (nrVday) for Males, Females, and
Males and Females Combined 6-34
Table 6-14. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category 6-35
Table 6-15. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category 6-36
Table 6-16. Mean and 95th Percentile Inhalation Rate Values (nrVday) for Males, Females, and
Males and Females Combined 6-37
Table 6-17. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Males by Age Category 6-39
Table 6-18. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Males by Age Category 6-43
Table 6-19. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Females by Age
Category 6-47
Table 6-20. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
Performing Activities Within the Specified Activity Category, for Females by Age
Category 6-51
Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
Within the Specified Activity Category, by Age for Males 6-55
Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
Within the Specified Activity Category, by Age for Females 6-58
Table 6-23. Mean Inhalation Rate Values (nrVday) from Key Studies for
Males and Females Combined 6-61
Table 6-24. 95th Percentile Inhalation Rate Values (nrVday) from Key Studies for
Males and Females Combined 6-62
Table 6-25. Concordance of Age Groupings Among Key Studies 6-63
Table 6-26. Time Weighted Average of Daily Inhalation Rates (DIRs) Estimated from Daily Activities 6-64
Table 6-27. Selected Inhalation Rate Values During Different Activity Levels Obtained from Various
Literature Sources 6-65
Page
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Chapter 6—Inhalation Rates
LIST OF TABLES (continued)
Table 6-28. Summary of Human Inhalation Rates by Activity Level (m3/hour) 6-66
Table 6-29. Estimated Minute Ventilation Associated with Activity Level for Average Male Adult 6-66
Table 6-30. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for All
Age Groups 6-67
Table 6-31. Summary of Daily Inhalation Rates (DIRs) Grouped by Age and Activity Level 6-67
Table 6-32. Distribution Pattern of Predicted Ventilation Rate (VR) and Equivalent Ventilation Rate
(EVR) for 20 Outdoor Workers 6-68
Table 6-33. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor
Workers 6-69
Table 6-34. Calibration and Field Protocols for Self-Monitoring of Activities
Grouped by Subject Panels 6-70
Table 6-35. Subject Panel Inhalation Rates by Mean Ventilation Rate (VR), Upper Percentiles, and
Serf-Estimated Breathing Rates 6-71
Table 6-36. Actual Inhalation Rates Measured at Four Ventilation Levels 6-71
Table 6-37. Distribution of Predicted Inhalation Rates by Location and Activity Levels for
Elementary and High School Students 6-72
Table 6-38. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and
High School Students 6-73
Table 6-39. Distribution Patterns of Daily Inhalation Rates (DIRs) for Elementary (EL) and High
School (HS) Students Grouped by Activity Level 6-73
Table 6-40. Mean Minute Inhalation Rate (mVminute) by Group and Activity for
Laboratory Protocols 6-74
Table 6-41. Mean Minute Inhalation Rate (nrVminute) by Group and Activity for Field Protocols 6-74
Table 6-42. Summary of Average Inhalation Rates (m3/hour) by Age Group and Activity Levels for
Laboratory Protocols 6-75
Table 6-43. Summary of Average Inhalation Rates (m3/hour) by Age Group And Activity Levels in
Field Protocols 6-76
Table 6-44. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy
Intakes (EFDs) for Individuals Sampled in the 1977-1978 NFCS 6-77
Table 6-45. Daily Inhalation Rates (DIRs) Calculated from Food-Energy Intakes (EFDs) 6-78
Table 6-46. Statistics of the Age/Sex Cohorts Used to Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR) 6-79
Table 6-47. Daily Inhalation Rates (DIRs) Obtained from the Ratios of Total Energy
Expenditure to Basal Metabolic Rate (BMR) 6-79
Table 6-48. Daily Inhalation Rates (DIRs) Based on Time-Activity Survey 6-80
Table 6-49. Inhalation Rates for Short-Term Exposures 6-81
Table 6-50. Distributions of Individual and Group Inhalation/Ventilation Rate (VR) for
Outdoor Workers 6-82
Table 6-51. Individual Mean Inhalation Rate (m3/hour) by Serf-Estimated Breathing Rate or Job
Activity Category for Outdoor Workers 6-82
Table 6-52. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in
618 Infants and Children Grouped in Classes of Age 6-83
Table 6-53. Distribution of Physiological Daily Inhalation Rate (PDIR) (rrrVday) Percentiles for
Free-Living Underweight Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks 6-84
Table 6-54. Distribution of Physiological Daily Inhalation Rate (PDIR) (mVday) Percentiles for
Free-Living Normal-Weight Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks 6-85
Table 6-55. Distribution of Physiological Daily Inhalation Rate (PDIR) (mVday) Percentiles for
Free-Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks 6-86
Table 6-56. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for
Free-Living Underweight Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks 6-87
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
LIST OF TABLES (continued)
Table 6-57. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for
Free-Living Normal-Weight and Women Aged 11 to 55 Years During Pregnancy and
Postpartum Weeks 6-88
Table 6-58. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for
Free-Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years During
Pregnancy and Postpartum Weeks 6-89
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
LIST OF FIGURES
Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects 6-90
Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects 6-90
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
6. INHALATION RATES
6.1.
INTRODUCTION
Ambient and indoor air are potential sources of
exposure to toxic substances. Adults and children can
be exposed to contaminated air during a variety of
activities in different environments. They may be
exposed to contaminants in ambient air and may also
inhale chemicals from the indoor use of various
sources (e.g., stoves, heaters, fireplaces, and
consumer products) as well as from those that
infiltrate from ambient air.
The Agency defines exposure as the chemical
concentration at the boundary of the body (U.S. EPA,
1992). In the case of inhalation, the situation is
complicated by the fact that oxygen exchange with
carbon dioxide takes place in the distal portion of the
lung. The anatomy and physiology of the respiratory
system as well as the characteristics of the inhaled
agent diminishes the pollutant concentration in
inspired air (potential dose) such that the amount of a
pollutant that actually enters the body through the
upper respiratory tract (especially the
nasal-pharyngeal and tracheo-bronchial regions) and
lung (internal dose) is less than that measured at the
boundary of the body. A detailed discussion of this
concept can be found in Guidelines for Exposure
Assessment (U.S. EPA, 1992). Suggestions for further
reading on the anatomy and physiology of the
respiratory system include Phalen (2009), Bates
(1989), Cherniak (1972), Forster (1986), and West
(1974, 1987). When constructing risk assessments
that concern the inhalation route of exposure, one
must be aware of any adjustments that have been
employed in the estimation of the pollutant
concentration to account for this reduction in
potential dose.
There are also a number of resources available in
the literature describing various approaches and
techniques related to inhalation rate estimates,
including Ridley et al. (2008), Ridley and Olds
(2008), Speakman and Selman (2003), Thompson et
al. (2009), and Westerterp (2003).
Inclusion of this chapter in the Exposure Factors
Handbook does not imply that assessors will always
need to select and use inhalation rates when
evaluating exposure to air contaminants. For
example, it is unnecessary to calculate inhaled dose
when using dose-response factors from the Integrated
Risk Information System (IRIS) (U.S. EPA, 1994),
because the IRIS methodology accounts for
inhalation rates in the development of
"dose-response" relationships. Information in this
chapter may be used by toxicologists in their
derivation of human equivalent concentrations
(HECs), where adjustments are usually required to
account for differences in exposure scenarios or
populations (U.S. EPA, 1994). Inhalation dosimetry
and the factors affecting the disposition of particles
and gases that may be deposited or taken up in the
respiratory tract are discussed in more detail in the
U.S. Environmental Protection Agency's (EPA's)
report on Methods for Derivation of Inhalation
Reference Concentrations (RfCs) and Application of
Inhalation Dosimetry (U.S. EPA, 1994). When using
IRIS for inhalation risk assessments, "dose-response"
relationships require only an average air
concentration to evaluate health concerns:
• For non-carcinogens, IRIS uses Reference
Concentrations (RfCs), which are expressed in
concentration units. Hazard is evaluated by
comparing the inspired air concentration to the
RfC.
• For carcinogens, IRIS uses unit risk values,
which are expressed in inverse concentration
units. Risk is evaluated by multiplying the
unit risk by the inspired air concentration.
Detailed descriptions of the IRIS methodology for
derivation of inhalation RfCs can be found in two
methods manuals produced by the Agency
(U.S. EPA, 1992, 1994).
The Superfund Program has also updated its
approach for determining inhalation risk, eliminating
the use of inhalation rates when evaluating exposure
to air contaminants (U.S. EPA, 2008). The current
methodology recommends that risk assessors use the
concentration of the chemical in air as the exposure
metric (e.g., mg/m3), instead of the intake of a
contaminant in air based on inhalation rate and body
weight (e.g., mg/kg-day).
Due to their size, physiology, behavior, and
activity level, the inhalation rates of children differ
from those of adults. Infants and children have a
higher resting metabolic rate and oxygen
consumption rate per unit of body weight than adults
because of their rapid growth and relatively larger
lung surface area (SA) per unit of body weight. For
example, the oxygen consumption rate for a resting
infant between 1 week and 1 year of age is
7 milliliters per kilogram of body weight (mL/kg) per
minute, while the rate for an adult under the same
conditions is 3-5 mL/kg per minute (WHO, 1986).
Thus, while greater amounts of air and pollutants are
inhaled by adults than children over similar time
periods on an absolute basis, the relative volume of
air passing through the lungs of a resting infant is up
to twice that of a resting adult on a body-weight
basis. It should be noted that lung volume is
correlated, among other factors, with a person's
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
height. Also, people living in higher altitudes have
larger lung capacity than those living at sea level.
Children's inhalation dosimetry and health effects
were topics of discussion at a U.S. Environmental
Protection Agency workshop held in June 2006 (Foos
and Sonawane, 2008). Age-related differences in lung
structure and function, breathing patterns, and how
these affect the inhaled dose and the deposition of
particles in the lung are important factors in assessing
risks from inhalation exposures (Foos et al., 2008).
Children more often than adults, breathe through
their mouths and, therefore, may have a lesser nasal
contribution to breathing during rest and while
performing various activities. The uptake of particles
in the nasal airways is also less efficient in children
(Bennett et al., 2008). Thus, the deposition of
particles in the lower respiratory tract may be greater
in children (Foos et al., 2008). In addition, the rate of
fine particle deposition has been significantly
correlated with increased body mass index (BMI), an
important point as childhood obesity becomes a
greater issue (Bennett and Zeman, 2004).
Recommended inhalation rates (both long- and
short-term) for adults and children are provided in
Section 6.2, along with the confidence ratings for
these recommendations, which are based on four key
studies identified by U.S. EPA for this factor.
Long-term inhalation is repeated exposure for more
than 30 days, up to approximately 10% of the life
span in humans (more than 30 days). Long-term
inhalation rates for adults and children (including
infants) are presented as daily rates (nrVday).
Short-term exposure is repeated exposure for more
than 24 hours, up to 30 days. Short-term inhalation
rates are reported for adults and children (including
infants) performing various activities in mVminute.
Following the recommendations, the available studies
(both key and relevant studies) on inhalation rates are
summarized.
6.2.
RECOMMENDATIONS
The recommended inhalation rates for adults and
children are based on three recent studies (Brochu et
al., 2006a; Stifelman, 2007; U.S. EPA, 2009), as well
as an additional study of children (Arcus-Arth and
Blaisdell, 2007). These studies represent an
improvement upon those previously used for
recommended inhalation rates in earlier versions of
this handbook, because they use a large data set that
is representative of the United States as a whole and
consider the correlation between body weight and
inhalation rate.
The selection of inhalation rates to be used for
exposure assessments depends on the age of the
exposed population and the specific activity levels of
this population during various exposure scenarios.
Table 6-1 presents the recommended long-term
values for adults and children (including infants) for
use in various exposure scenarios. For children, the
age groups included are from U.S. EPA's Guidance
on Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005a). Section 6.3.5
describes how key studies were combined to derive
the mean and 95th percentile inhalation rate values
and the concordance between the age groupings used
for adults and children in this chapter and the original
age groups in the key studies.
As shown in Table 6-1, the daily average
inhalation rates for long-term exposures for children
(males and females combined, unadjusted for body
weight) range from 3.5 nrVday for children from 1 to
<3 months to 16.3 nrVday for children aged 16 to <21
years. Mean values for adults range from 12.2 nrVday
(81 years and older) to 16.0 nrVday (31 to <51 years).
The 95th percentile values for children range from
5.8 nrVday (1 to <3 months) to 24.6 nrVday (16 to
<21 years) and for adults range from 15.7 nrVday
(81 years and older) to 21.4 nrVday (31 to <41 years).
The mean and 95th percentile values shown in
Table 6-1 represent averages of the inhalation rate
data from the key studies for which data were
available for selected age groups.
It should be noted that there may be a high degree
of uncertainty associated with the upper percentiles.
These values represent unusually high estimates of
caloric intake per day and are not representative of
the average adult or child. For example, using
Layton's equation (Layton, 1993) for estimating
metabolically consistent inhalation rates to calculate
caloric equivalence (see Section 6.4.9), the
95th percentile value for 16 to <21-year-old children
is greater than 4,000 kcal/day (Stifelman, 2003). All
of the 95th percentile values listed in Table 6-1
represent unusually high inhalation rates for
long-term exposures, even for the upper end of the
distribution, but were included in this handbook to
provide exposure assessors a sense of the possible
range of inhalation rates for adults and children.
These values should be used with caution when
estimating long-term exposures.
Short-term mean and 95th percentile data in
nrVminute are provided in Table 6-2 for males and
females combined for adults and children for whom
activity patterns are known. These values represent
averages of the activity level data from the one key
study from which short-term inhalation rate data were
available (U.S. EPA, 2009).
Table 6-3 shows the confidence ratings for the
inhalation rate recommendations. Tables 6-4, 6-6
through 6-8, 6-10, 6-14, 6-15, and 6-17 through 6-20
provide multiple percentiles for long- and short-term
inhalation rates for both males and females.
Page
6-2
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Chapter 6 — Inhalation Rates
Table 6-1. Recommended Long- Term
Sources
Mean Used for
Age Group3 (nrVday) Means
Birth to <1 3.6 c
month
1 to <3 months 3.5 c, d
3 to <6 months 4.1 c, d
6 to <12 months 5.4 c, d
Birth to <1 year 5.4 c, d, e, f
1 to <2 years 8.0 c, d, e, f
2 to <3 years 8.9 c, d, e, f
3 to <6 years 10. 1 c, d, e, f
6to81 years 12.2 d, e
Exposure Values
Combined)
(nrVday)
7.1
5.8
6.1
8.0
9.2
12.8
13.7
13.8
16.6
21.9
24.6
21.3
21.4
21.2
21.3
18.1
16.6
15.7
for Inhalation
Sources Used
for 95th
Percentiles
c
c, d
c,d
c,d
c, d, e
c, d, e
c, d, e
c, d, e
c, d, e
c, d, e
c, d, e
d, e
d,e
d, e
d,e
d, e
d, e
d,e
(Males and Females
Multiple Percentiles
See Tables 6-4, 6-6
through 6-8, 6-10, 6-14,
6-15 (none available for
Stifelman, 2007)
3 When age groupings in the original reference did not match the U. S. EPA groupings used for this
handbook, means from all age groupings in the original reference that overlapped U.S. EPA's age
groupings by more than one year were averaged, weighted by the number of observations
contributed from each age group. Similar calculations were performed for the 95th percentiles.
See Table 6-25 for concordance with U.S. EPA age groupings.
b Some 95th percentile values may be unrealistically high and not representative of the average
person.
Arcus-Arth and Blaisdell, 2007.
d Brochu et al., 2006a.
U.S. EPA, 2009.
f Stifelman, 2007.
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Table 6-2. Recommended Short-Term
Activity Level
Sleep or Nap
Sedentary/
Passive
Light Intensity
Age Group
(years)
Birth to <1
lto<2
2to<3
3 to<6
6to81
Birth to <1
1 to<2
2to<3
3 to<6
6to81
Birth to <1
1 to<2
2to<3
3 to<6
6to
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Table 6-2. Recommended Short-Term
Activity Level
Light Intensity
(continued)
Moderate
Intensity
High Intensity
Source: U.S. EPA,
Age Group
(year)
21to<31
31to<41
41to<51
51 to<61
61to<71
71to<81
>81
Birth to <1
1 to<2
2to<3
3 to<6
6to81
Birth to <1
lto<2
2to<3
3 to<6
6to81
2009.
Exposure Values for Inhalation (Males and Females Combined)
(continued)
Mean
(m /minute)
1.2E-02
1.2E-02
1.3E-02
1.3E-02
1.2E-02
1.2E-02
1.2E-02
1.4E-02
2.1E-02
2.1E-02
2.1E-02
2.2E-02
2.5E-02
2.6E-02
2.6E-02
2.7E-02
2.8E-02
2.9E-02
2.6E-02
2.5E-02
2.5E-02
2.6E-02
3.8E-02
3.9E-02
3.7E-02
4.2E-02
4.9E-02
4.9E-02
5.0E-02
4.9E-02
5.2E-02
5.3E-02
4.7E-02
4.7E-02
4.8E-02
95th Percentile
(m /minute) Multiple Percentiles
1.6E-02
1.6E-02
1.6E-02
1.7E-02
1.6E-02
1.5E-02
1.5E-02
2.2E-02
2.9E-02
2.9E-02
2.7E-02
2.9E-02
3.4E-02
3.7E-02
3.8E-02
3.7E-02
3.9E-02
4.0E-02
3.4E-02
3.2E-02
3.1E-02
4.1E-02
5.2E-02
5.3E-02
4.8E-02
5.9E-02
7.0E-02
7.3E-02
7.6E-02
7.2E-02
7.6E-02
7.8E-02
6.6E-02
6.5E-02
6.8E-02
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Table 6-3. Confidence in Recommendations for Long- and Short-Term Inhalation Rates
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data-Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The survey methodology and data analysis was
adequate. Measurements were made by indirect
methods. The studies analyzed existing primary
data.
Potential bias within the studies was fairly well
documented.
The studies focused on inhalation rates and factors
influencing them.
The studies focused on the U.S. population. A wide
range of age groups were included.
The studies were published during 2006 and 2009
and represent current exposure conditions.
The data-collection period for the studies may not be
representative of long-term exposures.
All key studies are available from the peer-reviewed
literature.
The methodologies were clearly presented; enough
information was included to reproduce most results.
Information on ensuring data quality in the key
studies was limited.
In general, the key studies addressed variability in
inhalation rates based on age and activity level.
Although some factors affecting inhalation rate, such
as body mass, are discussed, other factors (e.g.,
ethnicity) are omitted.
Multiple sources of uncertainty exist for these
studies. Assumptions associated with energy
expenditure (EE)-based estimation procedures are a
source of uncertainty in inhalation rate estimates.
Three of the key studies appeared in peer-reviewed
journals, and one key study is a U.S. EPA peer-
reviewed report.
There are four key studies. The results of studies
from different researchers are in general agreement.
Rating
Medium
High
Medium
Medium
High
Medium
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6.3. KEY INHALATION RATE STUDIES
6.3.1. Brochu et al. (2006a)—Physiological
Daily Inhalation Rates for Free-Living
Individuals Aged 1 Month to 96 Years,
Using Data from Doubly Labeled Water
Measurements: A Proposal for Air
Quality Criteria, Standard Calculations,
and Health Risk Assessment
Brochu et al. (2006a) calculated physiological
daily inhalation rates (PDIRs) for 2,210 individuals
aged 3 weeks to 96 years using the reported
disappearance rates of oral doses of doubly labeled
water (DLW) (2H2O and H218O) in urine, monitored
by gas-isotope-ratio mass spectrometry for an
aggregate period of more than 30,000 days. DLW
data were complemented with indirect calorimetry
and nutritional balance measurements.
In the DLW method, the disappearance of the
stable isotopes deuterium (2H) and heavy oxygen-18
(18O) are monitored in urine, saliva, or blood samples
over a long period of time (from 7 to 21 days) after
subjects receive oral doses of 2H2O and H218O. The
disappearance rate of 2H reflects water output and
that of 18O represents water output plus carbon
dioxide (CO2) production rates. The CO2 production
rate is then calculated by finding the difference
between the two disappearance rates. Total daily
energy expenditures (TDEEs) are determined from
CO2 production rates using classic respirometry
formulas, in which values for the respiratory quotient
(RQ = CO2 produced/O2 consumed) are derived from the
composition of the diet during the period of time of
each study. The DLW method also allows for
measurement of the energy cost of growth (ECG).
TDEE and ECG measurements can be converted into
PDIR values using the following equation developed
by Layton (1993):
PDIR = (TDEE + ECG) x H x VQ x 10~3 (Eqn. 6-1)
where:
PDIR = physiological daily inhalation
rates (nrYday);
TDEE = total daily energy expenditure
(kcal/day);
ECG = stored daily energy cost for
growth (kcal/day);
H = oxygen uptake factor, volume
of 0.21 L of oxygen (at
standard temperature and
pressure, dry air) consumed to
produce 1 kcal of energy
expended;
VQ = ventilatory equivalent (ratio of
the minute volume [VE] at
body temperature pressure
saturation to the oxygen uptake
rate [VO2] at standard
temperature and pressure, dry
air) VE/VO2 = 27; and
10~3 = conversion factor (L/m3).
Brochu et al. (2006a) calculated daily inhalation
rates (DIRs) (expressed in nrYday and m3/kg-day) for
the following age groups and physiological
conditions: (1) healthy newborns aged 3 to 5 weeks
old (N = 33), (2) healthy normal-weight males and
females aged 2.6 months to 96 years (N = 1,252),
(3) low-BMI subjects (underweight women, TV = 17;
adults from less affluent societies N= 59) and
(4) overweight/obese individuals (N = 679), as well
as (5) athletes, explorers, and soldiers when reaching
very high energy expenditures (N = 170). Published
data on BMI, body weight, basal metabolic rate
(BMR), ECG, and TDEE measurements (based on
DLW method and indirect calorimetry) for subjects
aged 2.6 months to 96 years were used. Data for
underweight, healthy normal-weight, and
overweight/obese individuals were gathered and
defined according to BMI cutoffs. Data for newborns
were included regardless of BMI values because they
were clinically evaluated as being healthy infants.
Tables 6-4 to 6-8 present the distribution of daily
inhalation rates for normal-weight and
overweight/obese individuals by sex and age groups.
Table 6-9 presents mean inhalation rates for
newborns. Due to the insufficient number of subjects,
no distributions were derived for this group.
An advantage of this study is that data are
provided for age groups of less than 1 year. A
limitation of this study is that data for individuals
with pre-existing medical conditions were lacking.
6.3.2. Arcus-Arth and Blaisdell (2007)—
Statistical Distributions of Daily
Breathing Rates for Narrow Age Groups
of Infants and Children
Arcus-Arth and Blaisdell (2007) derived daily
breathing rates for narrow age ranges of children
using the metabolic conversion method of Layton
(1993) and energy intake (El) data adjusted to
represent the U.S. population from the Continuing
Survey of Food Intake for Individuals (CSFII)
1994-1996, 1998. Normalized (m3/kg-day) and non-
normalized (nrVday) breathing rates for children
0-18 years of age were derived using the general
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equation developed by Layton (1993) to calculate
energy-dependent inhalation rates:
VE = H x VQ x EE
where:
(Eqn. 6-2)
VE =
H =
VQ =
EE =
volume of air breathed per day
(nrVday),
volume of oxygen consumed to
produce 1 kcal of energy (m3/kcal),
ratio of the volume of air to the
volume of oxygen breathed per unit
time (unitless), and
energy (kcal) expended per day.
Arcus-Arth and Blaisdell (2007) calculated H
values of 0.22 and 0.21 for infants and non-infant
children, respectively, using the 1977-1978
Nationwide Food Consumption Survey (NFCS) and
CSFII data sets. Ventilatory equivalent (VQ) data,
including those for infants, were obtained from
13 studies that reported VQ data for children aged
4-8 years. Separate preadolescent (4-8 years) and
adolescent (9-18 years) VQ values were calculated in
addition to separate VQ values for adolescent boys
and girls. Two-day-averaged daily El values reported
in the CSFII data set were used as a surrogate for EE.
CSFII records that did not report body weight and
those for children who consumed breast milk or were
breast-fed were excluded from their analyses. The Els
of children 9 years of age and older were multiplied
by 1.2, the value calculated by Layton (1993) to
adjust for potential bias related to under-reporting of
dietary intakes by older children. For infants, El
values were adjusted by subtracting the amount of
energy put into storage by infants as estimated by
Scrimshaw et al. (1996). Serf-reported body weights
for each individual from the CSFII data set were used
to calculate non-normalized (nrYday) and normalized
(m3/kg-day) breathing rates, which decreased the
variability in the resulting breathing rate data. Daily
breathing rates were grouped into three 1-month
groups for infants, 1-year age groups for children 1 to
18 years of age, and the age groups recommended by
U.S. EPA Supplemental Guidance for Assessing
Susceptibility from Early-Life Exposure to
Carcinogens (U.S. EPA, 2005b) to receive greater
weighting for mutagenic carcinogens (0 to <2 years
of age, and 2 to <16 years of age). Data were also
presented for adolescent boys and girls, aged 9 to
18 years (see Table 6-10). For each age and age-sex
group, Arcus-Arth and Blaisdell (2007) calculated the
arithmetic mean, standard error of the mean,
percentiles (50th, 90th, and 95th), geometric mean,
standard deviation, and best-fit parametric models of
the breathing rate distributions. Overall, the
CSFII-derived non-normalized breathing rates
progressively increased with age from infancy
through 18 years of age, while normalized breathing
rates progressively decreased. The data are presented
in Table 6-11 in units of nrVday. There were
statistical differences between boys and girls 9 to
18 years of age, both for these years combined
(p < 0.00) and for each year of age separately
(p < 0.05). The authors reasoned that since the
fat-free mass (basically muscle mass) of boys
typically increases during adolescence, and because
fat-free mass is highly correlated to basal metabolism
which accounts for the majority of EE, non-
normalized breathing rates for adolescent boys may
be expected to increase with increasing age.
Table 6-11 presents the mean and 95th percentile
values for males and females combined, averaged to
fit within the standard U.S. EPA age groups.
The CSFII-derived mean breathing rates derived
by Arcus-Arth and Blaisdell (2007) were compared to
the mean breathing rates estimated in studies that
utilized DLW technique EE data that had been
coupled with the Layton (1993) method. Infants'
breathing rates estimated using the CSFII data were
15 to 27% greater than the comparison DLW EE
breathing rates. In contrast, the children's CSFII
breathing rates ranged from 23% less to 14% greater
than comparison rates. Arcus-Arth and Blaisdell
(2007) concluded that taking into account the
differences in methods, data, and some age
definitions between the two sets of breathing rates,
the CSFII and comparison rates were similar across
age groups.
An advantage of this study is that it provides
breathing rates specific to narrow age ranges, which
can be useful for assessing inhalation dose during
periods of greatest susceptibility. However, the study
is limited by the potential for misreporting,
underestimating, or overestimating of food intake
data in the CSFII. In addition to underreporting of
food intake by adolescents, El values for younger
children may be under- or overestimated. Overweight
children (or their parents) may also under-report food
intakes. In addition, adolescents who misreport food
intake may have also misreported body weights.
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6.3.3. Stifelman (2007)—Using Doubly-Labeled
Water Measurements of Human Energy
Expenditure to Estimate Inhalation Rates
Stifelman (2007) estimated inhalation rates using
DLW energy data. The DLW method administers two
forms of stable isotopically labeled water:
deuterium-labeled (2H2O) and 18oxy gen-labeled
(H218O). The difference in disappearance rates
between the two isotopes represents the energy
expended over a period of 1-3 half-lives of the
labeled water (Stifelman, 2007). The resulting
duration of observation is typically 1-3 weeks,
depending on the size and activity level.
The DLW database contains subjects from areas
around the world and represents diversity in ethnicity,
age, activity, body type, and fitness level. DLW data
have been compiled by the Institute of Medicine
(IOM) Panel on Macronutrients and the Food and
Agriculture Organization of the United Nations.
Stifelman (2007) used the equation of Layton (1993)
to convert the recommended energy levels of IOM
for the active to very-active people to their equivalent
inhalation rates. The IOM reports recommend energy
expenditure levels organized by sex, age, and body
size (Stifelman, 2007).
The equivalent inhalation rates are shown in
Table 6-12. Shown in Table 6-13 are the mean values
for the IOM "active" energy level category, averaged
to fit within the standard U.S. EPA age groups.
Stifelman (2007) noted that the estimates based on
the DLW are consistent with previous findings of
Layton (1993) and the Exposure Factors Handbook
(U.S. EPA, 1997) and that inhalation rates based on
the IOM active classification are consistent with the
mean inhalation rate in the handbook.
The advantages of this study are that the
inhalation rates were estimated using the DLW data
from a large data set. Stifelman (2007) noted that
DLW methods are advantageous; the data are robust,
measurements are direct and avoid errors associated
with indirect measurements (heart rate [HR]),
subjects are free-living, and the period of observation
is longer than what is possible from staged activity
measures. Observations over a longer period of time
reduce the uncertainties associated with using short
duration studies to infer long-term inhalation rates. A
limitation with the study is that the inhalation rates
that are presented are for active/very active persons
only.
6.3.4. U.S. EPA (2009)—Metabolically Derived
Human Ventilation Rates: A Revised
Approach Based Upon Oxygen
Consumption Rates
U.S. EPA (2009) conducted a study to ascertain
inhalation rates for children and adults. Specifically,
U.S. EPA sought to improve upon the methodology
used by Layton (1993) and other studies that relied
upon the VQ and a linear relationship between
oxygen consumption and fitness rate. A revised
approach, developed by U.S. EPA's National
Exposure Research Laboratory, was used, in which
an individual's inhalation rate was derived from his
or her assumed oxygen consumption rate. U.S. EPA
applied this revised approach using body-weight data
from the 1999-2002 National Health and Nutrition
Examination Survey (NHANES) and metabolic
equivalents of work (METS) data from U.S. EPA's
Consolidated Human Activity Database (CHAD). In
this database, metabolic cost is given in units of
"METS" or "metabolic equivalents of work," an
energy expenditure metric used by exercise
physiologists and clinical nutritionists to represent
activity levels. An activity's METS value represents a
dimensionless ratio of its metabolic rate (energy
expenditure) to a person's resting, or BMR.
NHANES provided age, sex, and body-weight
data for 19,022 individuals from throughout the
United States. From these data, BMR was estimated
using an age-specific linear equation used in the
Exposure Factors Handbook (U.S. EPA, 1997), and
in several other studies and reference works.
The CHAD database is a compilation of several
databases of human activity patterns. U.S. EPA used
one of these studies, the National Human Activity
Pattern Survey (NHAPS), as its source for METS
values because it was more representative of the
entire U.S. population than the other studies in the
database. The NHAPS data set included activity data
for 9,196 individuals, each of which provided
24 hours of activity pattern data using a diary-based
questionnaire. While NHAPS was identified as the
best available data source for activity patterns, there
were some shortcomings in the quality of the data.
Study respondents did not provide body weights;
instead, body weights were simulated using statistical
sampling. Also, the NHAPS data extracted from
CHAD could not be corrected to account for
non-random sampling of study participants and
survey days.
NHANES and NHAPS data were grouped
according to the age categories presented elsewhere
in this handbook, with the exception that children
under the age of 1 year were placed into a single
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category to preserve an adequate sample size within
the category. For each NHANES participant, a
"simulated" 24-hour activity pattern was generated
by randomly sampling activity patterns from the set
of NHAPS participants with the same sex and age
category as the NHANES participant. Twenty such
patterns were selected at random for each NHANES
participant, resulting in 480 hours of simulated
activity data for each NHANES participant. The data
were then scaled down to a 24-hour time frame to
yield an average 24-hour activity pattern for each of
the 19,022 NHANES individuals.
Each activity was assigned a METS value based
on statistical sampling of the distribution assigned by
CHAD to each activity code. For most codes, these
distributions were not age dependent, but age was a
factor for some activities for which intensity level
varies strongly with age. Using statistical software,
equations for METS based on normal, lognormal,
exponential, triangular, and uniform distributions
were generated as needed for the various activity
codes. The METS values were then translated into
EE by multiplying the METS by the BMR, which
was calculated as a linear function of body weight.
The oxygen consumption rate (VO2) was calculated
by multiplying EE by H, the volume of oxygen
consumed per unit of energy. VO2 was calculated
both as volume per time and as volume per time per
unit of body weight.
The inhalation rate for each activity within the
24-hour simulated activity pattern for each individual
was estimated as a function of VO2, body weight,
age, and sex. Following this, the average inhalation
rate was calculated for each individual for the entire
24-hour period, as well as for four separate classes of
activities based on METS value (sedentary/passive
[METS less than or equal to 1.5], light intensity
[METS greater than 1.5 and less than or equal to 3.0],
moderate intensity [METS greater than 3.0 and less
than or equal to 6.0], and high intensity [METS
greater than 6.0]). Data for individuals were then
used to generate summary tables based on sex and
age categories.
U.S. EPA (2009) also conducted a validation
exercise using the Air Pollutants Exposure Model to
estimate ventilation rates (VRs) and compared results
with recently published estimates of ventilation rates
from Brochu et al. (2006a, b) and Arcus-Arth and
Blaisdell (2007). The results compared reasonably
well when ventilation rates were normalized by BMI.
Tables 6-14 through 6-22 present data from this
study. Tables 6-14 and 6-15 present, for male and
female subjects, respectively, summary statistics for
daily average inhalation rate by age category on a
volumetric (m3/day) and body-weight adjusted
(m3/day-kg) basis. Table 6-16 presents the mean and
95th percentile values for males, females, and males
and females combined. Tables 6-17 through 6-20
present, for male and female subjects, respectively,
mean ventilation rates by age category on a
volumetric (nrVminute) and body-weight adjusted
(m3/minute-kg) basis for the five different activity
level ranges described above. Tables 6-21 and 6-22
present the number of hours spent per day at each
activity level by males and females.
An advantage of this study is the large sample
size. In addition, the data sets used, NHAPS and
NHANES, are representative of the U.S. general
population. One limitation is that the NHAPS data
are more than 15 years old. Also, day-to-day
variability cannot be characterized because data were
collected over a 24-hour period. There is also
uncertainty in the METs randomization, all of which
were noted by the authors. In addition, the approach
does not take into consideration correlations that may
exist between body weight and activity patterns.
Therefore, high physical activity levels can be
associated with individuals of high body weight,
leading to unrealistically high inhalation rates at the
upper percentile levels. The validation exercise
presented in U.S. EPA (2009) used normal-weight
individuals. It is unclear if similar results would be
obtained for overweight individuals.
6.3.5. Key Studies Combined
In order to provide the recommended long-term
inhalation rates shown in Table 6-1, data from the
four key studies were combined. Mean and
95th percentile inhalation rate values for the four key
studies are shown in Tables 6-23 and 6-24,
respectively. The data from each study were averaged
by sex and grouped according to the age groups
selected for use in this handbook, when possible.
Table 6-25 shows concordance between the age
groupings used in this handbook and the original age
groups in the key studies.
6.4. RELEVANT INHALATION RATE
STUDIES
6.4.1. International Commission on
Radiological Protection (ICRP) (1981)—
Report of the Task Group on Reference
Man
The International Commission on Radiological
Protection (ICRP, 1981) estimated daily inhalation
rates for reference adult males and females, children
(10 years old), infants (1 year old), and newborn
babies by using a time-activity-ventilation approach.
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This approach for estimating an inhalation rate over a
specified period of time was based on calculating a
time weighted average of inhalation rates associated
with physical activities of varying durations (see
Table 6-26). ICRP (1981) compiled reference values
(see Table 6-27) of minute volume/inhalation rates
from various literature sources. ICRP (1981) assumed
that the daily activities of a reference male, female,
and child (10 years of age) consisted of 8 hours of
rest and 16 hours of light activities. It was also
assumed that for adults only, the 16 hours of light
activities were divided evenly between occupational
and non-occupational activities. It was assumed that a
day consisted of 14 hours resting and 10 hours light
activity for an infant (1 year). A newborn's daily
activities consisted of 23 hours resting and 1-hour
light activity. The estimated inhalation rates were
22.8 nrVday for adult males, 21.1 m3/day for adult
females, 14.8 m3/day for children (age 10 years),
3.76 m3/day for infants (age 1 year), and 0.78 m3/day
for newborns (see Table 6-26).
The advantages of this study are that they account
fairly well for time and activity, and are sex specific.
A limitation associated with this study is that it is
almost 30 years old. In addition, the validity and
accuracy of the inhalation rate data used in the
compilation of reference values were not specified.
This introduces some degree of uncertainty in the
results obtained. Also, the approach used required
that assumptions be made regarding the hours spent
by various age/sex cohorts in specific activities.
These assumptions may over-/under-estimate the
inhalation rates obtained.
6.4.2. U.S. EPA (1985)—Development of
Statistical Distributions or Ranges of
Standard Factors Used in Exposure
Assessment
The U.S. EPA (1985) compiled measured values
of minute ventilation for various age/sex cohorts
from early studies. The data compiled by the
U.S. EPA (1985) for each of the age/sex cohorts were
obtained at various activity levels (see Table 6-28).
These levels were categorized as light, moderate, or
heavy according to the criteria developed by the
U.S. EPA Office of Environmental Criteria and
Assessment for the Ozone Criteria Document. These
criteria were developed for a reference male adult
with a body weight of 70kg (U.S. EPA, 1985).
Table 6-29 details the estimated minute ventilation
rates for adult males based on these activity level
categories.
Table 6-28 presents a summary of inhalation rates
by age and activity level. A description of activities
included in each activity level is also presented in
Table 6-28. Table 6-28 indicates that at rest, the
average adult inhalation rate is 0.5 m3/hour.
Table 6-28 indicates that at rest, the mean inhalation
rate for children, ages 6 and 10 years, is 0.4 m3/hour.
Table 6-30 presents activity pattern data aggregated
for three microenvironments by activity level for all
age groups. The total average hours spent indoors
was 20.4, outdoors was 1.77, and in a transportation
vehicle was 1.77. Based on the data presented in
Tables 6-28 and 6-30, a daily inhalation rate was
calculated for adults and children by using a
time-activity-ventilation approach. These data are
presented for adults and children in Table 6-31. The
calculated average daily inhalation rate is 16 nrVday
for adults. The average daily inhalation rate for 6-
and 10-year-old children is 16.74 and 21.02 m3/day,
respectively.
Limitations associated with this study are its age
and that many of the values used in the data
compilation were from early studies. The accuracy
and/or validity of the values used and data collection
method were not presented in U.S. EPA (1985). This
introduces uncertainty in the results obtained. An
advantage of this study is that the data are actual
measurement data for a large number of adults and
children.
6.4.3. Shamoo et al. (1990)—Improved
Quantitation of Air Pollution Dose Rates
by Improved Estimation of Ventilation
Rate
Shamoo et al. (1990) conducted a study to
develop and validate new methods to accurately
estimate ventilation rates for typical individuals
during their normal activities. Two practical
approaches were tested for estimating ventilation
rates indirectly: (1) volunteers were trained to
estimate their own VR at various controlled levels of
exercise; and (2) individual VR and HR relationships
were determined in another set of volunteers during
supervised exercise sessions (Shamoo et al., 1990). In
the first approach, the training session involved
9 volunteers (3 females and 6 males) from 21 to
37 years old. Initially the subjects were trained on a
treadmill with regularly increasing speeds. VR
measurements were recorded during the last minute
of the 3-minute interval at each speed. VR was
reported to the subjects as low (1.4 m3/hour), medium
(1.5-2.3 nrVhour), heavy (2.4-3.8 nrVhour), and very
heavy (3.8 nrVhour or higher) (Shamoo et al., 1990).
Following the initial test, treadmill training
sessions were conducted on a different day in which
7 different speeds were presented, each for 3 minutes
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in arbitrary order. VR was measured, and the subjects
were given feedback with the four ventilation ranges
provided previously. After resting, a treadmill testing
session was conducted in which seven speeds were
presented in different arbitrary order from the
training session. VR was measured, and each subject
estimated their own ventilation level at each speed.
The correct level was then revealed to each subject
after his/her own estimate. Subsequently, two 3-hour
outdoor supervised exercise sessions were conducted
in the summer on 2 consecutive days. Each hour
consisted of 15 minutes each of rest, slow walking,
jogging, and fast walking. The subjects' ventilation
level and VR were recorded; however, no feedback
was given to the subjects. Electrocardiograms were
recorded via direct connection or telemetry, and HR
was measured concurrently with ventilation
measurement for all treadmill sessions.
The second approach consisted of two protocol
phases (indoor/outdoor exercise sessions and field
testing). Twenty outdoor adult workers between 19
and 50 years old were recruited. Indoor and outdoor
supervised exercises similar to the protocols in the
first approach were conducted; however, there were
no feedbacks. Also, in this approach,
electrocardiograms were recorded, and HR was
measured concurrently with VR. During the field
testing phase, subjects were trained to record their
activities during three different 24-hour periods
during 1 week. These periods included their most
active working and non-working days. HR was
measured quasi-continuously during the 24-hour
periods that activities were recorded. The subjects
recorded in a diary all changes in physical activity,
location, and exercise levels during waking hours.
Serf-estimated activities in supervised exercises and
field studies were categorized as slow (resting, slow
walking or equivalent), medium (fast walking or
equivalent), and fast (jogging or equivalent).
Inhalation rates were not presented in this study.
In the first approach, about 68% of all self-estimates
were correct for the 9 subjects sampled (Shamoo et
al., 1990). Inaccurate serf-estimates occurred in the
younger male population who were highly physically
fit and were competitive aerobic trainers. This subset
of the sample population tended to underestimate
their own physical activity levels at higher VR
ranges. Shamoo et al. (1990) attributed this to a
"macho effect," in which these younger male subjects
were reluctant to report "very heavy" exercise even
when it was obvious to an observer, because they
considered it an admission of poor physical
condition. In the second approach, a regression
analysis was conducted that related the logarithm of
VR to HR. The logarithm of VR correlated better
with HR than VR itself (Shamoo et al., 1990).
Limitations associated with this study are its age
and that the population sampled is not representative
of the general U.S. population. Also, ventilation rates
were not presented. Training individuals to estimate
their VR may contribute to uncertainty in the results
because the estimates are subjective. Another
limitation is that calibration data were not obtained at
extreme conditions; therefore, the VR/HR
relationship obtained may be biased. An additional
limitation is that training subjects may be too
labor-intensive for widespread use in exposure
assessment studies. An advantage of this study is that
HR recordings are useful in predicting ventilation
rates, which, in turn, are useful in estimating
exposure.
6.4.4. Shamoo et al. (1991)—Activity Patterns in
a Panel of Outdoor Workers Exposed to
Oxidant Pollution
Shamoo et al. (1991) investigated summer
activity patterns in 20 adult volunteers with
potentially high exposure to ambient oxidant
pollution. The selected volunteer subjects were
15 men and 5 women ages 19-50 years from the Los
Angeles area. All volunteers worked outdoors at least
10 hours per week. The experimental approach
involved two stages: (1) indirect objective estimation
of VR from HR measurements, and
(2) serf-estimation of inhalation/ventilation rates
recorded by subjects in diaries during their normal
activities.
The approach consisted of calibrating the
relationship between VR and HR for each test subject
in controlled exercise; monitoring by subjects of their
own normal activities with diaries and electronic HR
recorders; and then relating VR with the activities
described in the diaries (Shamoo et al., 1991).
Calibration tests were conducted for indoor and
outdoor supervised exercises to determine individual
relationships between VR and HR. Indoors, each
subject was tested on a treadmill at rest and at
increasing speeds. HR and VR were measured at the
third minute at each 3-minute interval speed. In
addition, subjects were tested while walking a
90-meter course in a corridor at 3 serf-selected speeds
(normal, slower than normal, and faster than normal)
for 3 minutes.
Two outdoor testing sessions (1 hour each) were
conducted for each subject, 7 days apart. Subjects
exercised on a 260-meter asphalt course. A session
involved 15 minutes each of rest, slow walking,
jogging, and fast walking during the first hour. The
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sequence was also repeated during the second hour.
HR and VR measurements were recorded starting at
the 8th minute of each 15-minute segment. Following
the calibration tests, a field study was conducted in
which subjects self-monitored their activities by
filling out activity diary booklets, self-estimated their
breathing rates, and their HR. Breathing rates were
defined as sleep; slow (slow or normal walking);
medium (fast walking); and fast (running) (Shamoo
et al., 1991). Changes in location, activity, or
breathing rates during three 24-hour periods within a
week were recorded. These periods included their
most active working and non-working days. Each
subject wore Heart Watches, which recorded their HR
once per minute during the field study. Ventilation
rates were estimated for the following categories:
sleep, slow, medium, and fast.
Calibration data were fit to the equation log
(VR) = intercept + (slope x HR), each individual's
intercept and slope were determined separately to
provide a specific equation that predicts each
subject's VR from measured HR (Shamoo et al.,
1991). The average measured VRs were 0.48, 0.90,
1.68, and 4.02 m3/hour for rest, slow walking or
normal walking, fast walking, and jogging,
respectively (Shamoo et al., 1991). Collectively, the
diary recordings showed that sleep occupied about
33% of the subject's time; slow activity 59%;
medium activity 7%; and fast activity 1%. The diary
data covered an average of 69 hours per subject
(Shamoo et al., 1991). Table 6-32 presents the
distribution pattern of predicted ventilation rates and
equivalent ventilation rates (EVR) obtained at the
four activity levels. EVR was defined as the VR per
square meter of body surface area, and also as a
percentage of the subjects average VR over the entire
field monitoring period (Shamoo et al., 1991). The
overall mean predicted VR was 0.42 nrVhour for
sleep; 0.71 nrVhour for slow activity; 0.84 m3/hour
for medium activity; and 2.63 nrVhour for fast
activity.
Table 6-33 presents the mean predicted VR and
standard deviation, and the percentage of time spent
in each combination of VR, activity type (essential
and non-essential), and location (indoor and outdoor).
Essential activities include income-related work,
household chores, child care, study and other school
activities, personal care, and destination-oriented
travel. Non-essential activities include sports and
active leisure, passive leisure, some travel, and social
or civic activities (Shamoo et al., 1991). Table 6-33
shows that inhalation rates were higher outdoors than
indoors at slow, medium, and fast activity levels.
Also, inhalation rates were higher for outdoor
non-essential activities than for indoor non-essential
activity levels at slow, medium, and fast serf-reported
breathing rates (see Table 6-33).
An advantage of this study is that subjective
activity diary data can provide exposure modelers
with useful rough estimates of VR for groups of
generally healthy people. A limitation of this study is
its age and that the results obtained show high
within-person and between-person variability in VR
at each diary-recorded level, indicating that VR
estimates from diary reports could potentially be
substantially misleading in individual cases. Another
limitation of this study is that elevated HR data of
slow activity at the second hour of the exercise
session reflect persistent effects of exercise and/or
heat stress. Therefore, predictions of VR from the
VR/HR relationship may be biased.
6.4.5. Linn et al. (1992)—Documentation of
Activity Patterns in "High-risk" Groups
Exposed to Ozone in the Los Angeles
Area
Linn et al. (1992) conducted a study that
estimated the inhalation rates for "high-risk"
population groups exposed to ozone in their daily
activities in the Los Angeles area. The population
surveyed consisted of seven subject panels: Panel 1:
20 healthy outdoor workers (15 males, 5 females,
ages 19-50 years); Panel 2: 17 healthy elementary
school students (5 males, 12 females, ages
10-12 years); Panel 3: 19 healthy high school
students (7 males, 12 females, ages 13-17 years);
Panel 4: 49 asthmatic adults (clinically mild,
moderate, and severe, 15 males, 34 females, ages
18-50 years); Panel 5: 24 asthmatic adults from
2 neighborhoods of contrasting O3 air quality
(10 males, 14 females, ages 19-46 years); Panel 6:
13 young asthmatics (7 males, 6 females, ages
11-16 years); and Panel 7: construction workers
(7 males, ages 26-34 years). An initial calibration
test was conducted, followed by a training session.
Finally, a field study that involved the subjects
collecting their own HRs and diary data was
conducted. During the calibration tests, VR,
breathing rate, and HR were measured
simultaneously at each exercise level. From the
calibration data, an equation was developed using
linear regression analysis to predict VR from
measured HR.
In the field study, each subject (except
construction workers) recorded in diaries their daily
activities, change in locations (indoors, outdoors, or
in a vehicle), self-estimated breathing rates during
each activity/location, and time spent at each
activity/location. Healthy subjects recorded their HR
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once every 60 seconds using a Heart Watch, an
automated system consisting of a transmitter and
receiver worn on the body. Asthmatic subjects
recorded their diary information once every hour.
Subjective breathing rates were defined as slow
(walking at their normal pace), medium (faster than
normal walking), and fast (running or similarly
strenuous exercise). Table 6-34 presents the
calibration and field protocols for self-monitoring of
activities for each subject panel.
Table 6-35 presents the mean, 99th percentile, and
mean VR at each subjective activity level (slow,
medium, fast). The mean and 99th percentile VR were
derived from all HR recordings that appeared to be
valid, without considering the diary data. Each of the
three activity levels was determined from both the
concurrent diary data and HR recordings by direct
calculation or regression. The mean VR for healthy
adults was 0.78 m3/hour, while the mean VR for
asthmatic adults was 1.02 m3/hour (see Table 6-35).
The preliminary data for construction workers
indicated that during a 10-hour work shift, their mean
VR (1.50m3/hour) exceeded the VRs of all other
subject panels (see Table 6-35). The authors reported
that the diary data showed that on a typical day, most
individuals spent most of their time indoors at slow
activity level. During slow activity, asthmatic
subjects had higher VRs than healthy subjects (see
Table 6-35). The authors also reported that in every
panel, the predicted VR correlated significantly with
the subjective estimates of activity levels.
A limitation of this study is that calibration
data may overestimate the predictive power of HR
during actual field monitoring. The wide variety of
exercises in everyday activities may result in greater
variation of the VR-HR relationship than was
calibrated. Another limitation is the small sample size
of each population surveyed. An advantage of this
study is that diary data can provide rough estimates
of ventilation patterns, which are useful in exposure
assessments. Another advantage is that inhalation
rates were presented for various populations (i.e.,
healthy outdoor adult workers, healthy children,
asthmatics, and construction workers).
6.4.6. Shamoo et al. (1992)—Effectiveness of
Training Subjects to Estimate Their Level
of Ventilation
Shamoo et al. (1992) conducted a study where
nine non-sedentary subjects in good health were
trained on a treadmill to estimate their own
ventilation rates at four activity levels: low, medium,
heavy, and very heavy. The purpose of the study was
to train the subjects' self-estimation of ventilation in
the field and to assess the effectiveness of the training
(Shamoo et al., 1992). The subjects included
3 females and 6 males between 21 to 37 years of age.
The tests were conducted in four stages. First, an
initial treadmill pretest was conducted indoors at
various speeds until the four ventilation levels were
experienced by each subject; VR was measured and
feedback was given to the subjects. Second, two
treadmill training sessions, which involved seven
3-minute segments of varying speeds based on initial
tests, were conducted; VR was measured and
feedback was given to the subjects. Another similar
session was conducted; however, the subjects
estimated their own ventilation level during the last
20 seconds of each segment and VR was measured
during the last minute of each segment. Immediate
feedback was given to the subject's estimate; and the
third and fourth stages involved 2 outdoor sessions of
3 hours each. Each hour comprised 15 minutes each
of rest, slow walking, jogging, and fast walking. The
subjects estimated their own ventilation level at the
middle of each segment. The subject's estimate was
verified by a respirometer, which measured VR in the
middle of each 15-minute activity. No feedback was
given to the subject. The overall percent correct score
obtained for all ventilation levels was 68% (Shamoo
et al., 1992). Therefore, Shamoo et al. (1992)
concluded that this training protocol was effective in
training subjects to correctly estimate their minute
ventilation levels.
For this handbook, inhalation rates were analyzed
from the raw data provided by Shamoo et al. (1992).
Table 6-36 presents the mean inhalation rates
obtained from this analysis at four ventilation levels
in two microenvironments (i.e., indoors and
outdoors) for all subjects. The mean inhalation rates
for all subjects were 0.93, 1.92, 3.01, and 4.80
m3/hour for low, medium, heavy, and very heavy
activities, respectively.
Limitations of this study are its age and the
population sample size used in this study was small
and was not selected to represent the general U.S.
population. The training approach employed may not
be cost effective because it was labor intensive;
therefore, this approach may not be viable in field
studies especially for field studies within large
sample sizes.
6.4.7. Spier et al. (1992)—Activity Patterns in
Elementary and High School Students
Exposed to Oxidant Pollution
Spier et al. (1992) investigated the activity
patterns of 17 elementary school students
(10-12 years old) and 19 high school students
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(13-17 years old) in suburban Los Angeles from late
September to October (oxidant pollution season).
Calibration tests were conducted in supervised
outdoor exercise sessions. The exercise sessions
consisted of 5 minutes each of rest, slow walking,
jogging, and fast walking. HR and VR were
measured during the last 2 minutes of each exercise.
Individual VR and HR relationships for each
individual were determined by fitting a regression
line to HR values and log VR values. Each subject
recorded their daily activities, changes in location,
and breathing rates in diaries for 3 consecutive days.
Serf-estimated breathing rates were recorded as slow
(slow walking), medium (walking faster than
normal), and fast (running). HR was recorded once
per minute during the 3 days using a Heart Watch.
VR values for each serf-estimated breathing rate and
activity type were estimated from the HR recordings
by employing the VR and HR equation obtained from
the calibration tests.
The data shown in Table 6-37 represent HR
distribution patterns and corresponding predicted VR
for each age group during hours spent awake. At the
same serf-reported activity levels for both age groups,
inhalation rates were higher for outdoor activities
than for indoor activities. The total number of hours
spent indoors was higher for high school students
(21.2 hours) than for elementary school students
(19.6 hours). The converse was true for outdoor
activities: 2.7 hours for high school students and 4.4
hours for elementary school students (see
Table 6-38). Table 6-39 describes the distribution
patterns of daily inhalation rates for elementary and
high school students grouped by activity level.
A limitation of this study is the small sample size.
The results may not be representative of all children
in these age groups. Another limitation is that the
accuracy of the serf-estimated breathing rates
reported by younger age groups is uncertain. This
may affect the validity of the data set generated. An
advantage of this study is that inhalation rates were
determined for children and adolescents.
6.4.8. Adams (1993)—Measurement of
Breathing Rate and Volume in Routinely
Performed Daily Activities, Final Report
Adams (1993) conducted research to accomplish
two main objectives: (1) identification of mean and
ranges of inhalation rates for various age/sex cohorts
and specific activities, and (2) derivation of simple
linear and multiple regression equations that could be
used to predict inhalation rates through other
measured variables: breathing frequency (fB) and
oxygen consumption. A total of 160 subjects
participated in the primary study. There were four
age-dependent groups: (1) children 6 to 12.9 years
old, (2) adolescents between 13 and 18.9 years old,
(3) adults between 19 and 59.9 years old, and (4)
seniors >60 years old (Adams, 1993). An additional
40 children from 6 to 12.9 years old and 12 young
children from 3 to 5.9 years old were identified as
subjects for pilot testing purposes.
Resting protocols conducted in the laboratory for
all age groups consisted of three phases (25 minutes
each) of lying, sitting, and standing. The phases were
categorized as resting and sedentary activities. Two
active protocols—moderate (walking) and heavy
(jogging/running) phases—were performed on a
treadmill over a progressive continuum of intensity
levels made up of 6-minute intervals at three speeds
ranging from slow to moderately fast. All protocols
involved measuring VR, HR, fB, and VO2.
Measurements were taken in the last 5 minutes of
each phase of the resting protocol and the last 3
minutes of the 6-minute intervals at each speed
designated in the active protocols.
In the field, all children completed spontaneous
play protocols. The older adolescent population (16
to 18 years) completed car driving and riding, car
maintenance (males), and housework (females)
protocols. All adult females (19 to 60 years) and most
of the senior (60 to 77 years) females completed
housework, yardwork, and car driving and riding
protocols. Adult and senior males completed car
driving and riding, yardwork, and mowing protocols.
HR, VR, and^ were measured during each protocol.
Most protocols were conducted for 30 minutes. All
the active field protocols were conducted twice.
During all activities in either the laboratory or
field protocols, VR for the children's group revealed
no significant sex differences, but those for the adult
groups demonstrated sex differences. Therefore,
inhalation rate (IR) data presented in Tables 6-40 and
6-41 were categorized as young children, children
(no sex), and adult female, and adult male, and adult
combined by activity type (lying, sitting, standing,
walking, and running). These categorized data from
Tables 6-40 and 6-41 are summarized as inhalation
rates in Tables 6-42 and 6-43. Table 6-42 shows the
laboratory protocols. Table 6-43 presents the mean
inhalation rates by group and for moderate activity
levels in field protocols. A comparison of the data
shown in Tables 6-42 and 6-43 suggest that during
light and sedentary activities in laboratory and field
protocols, similar inhalation rates were obtained for
adult females and adult males. Accurate predictions
of inhalation rates across all population groups and
activity types were obtained by including body SA,
HR, and breathing frequency in multiple regression
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analysis (Adams, 1993). Adams (1993) calculated SA
from measured height and body weight using the
equation:
SA = Heigh f
Weight1
71.84 (Eqn. 6-3)
A limitation associated with this study is that the
population does not represent the general U.S.
population. Also, the classification of activity types
(i.e., laboratory and field protocols) into activity
levels may bias the inhalation rates obtained for
various age/sex cohorts. Age groups for which data
are provided are limited and do not conform to
U.S. EPA's recommended age groups for children.
The estimated rates were based on short-term data
and may not reflect long-term patterns.
6.4.9. Layton (1993)—Metabolically Consistent
Breathing Rates for Use in Dose
Assessments
Layton (1993) presented a method for estimating
metabolically consistent inhalation rates for use in
quantitative dose assessments of airborne
radionuclides. Generally, the approach for estimating
the breathing rate for a specified time frame was to
calculate a time-weighted-average of ventilation rates
associated with physical activities of varying
durations. However, in this study, breathing rates
were calculated on the basis of oxygen consumption
associated with energy expenditures for short (hours)
and long (weeks and months) periods of time, using
the following general equation to calculate
energy-dependent inhalation rates:
where:
(Eqn. 6-4)
VE = ventilation rate (m /minute or
nrVday);
E = energy expenditure rate;
[kilojoules/minute (KJ/minute) or
megajoules/hour (MJ/hour)];
H = volume of oxygen (at standard
temperature and pressure, dry air
consumed in the production of
1 kilojoule [KJ] of energy
expended [L/KJ or m3/MJ]); and
VQ = ventilatory equivalent (ratio of
minute volume [nrVminute] to
oxygen uptake [nrYminute])
unitless.
Layton (1993) used three approaches to estimate
daily chronic (long term) inhalation rates for different
age/sex cohorts of the U.S. population using this
methodology.
First Approach
Inhalation rates were estimated by multiplying
average daily food-energy intakes (EFDs) for
different age/sex cohorts, H, and VQ, as shown in the
equation above. The average food-energy intake data
(see Table 6-44) are based on approximately
30,000 individuals and were obtained from the
1977-1978 USDA-NFCS. The food-energy intakes
were adjusted upwards by a constant factor of 1.2 for
all individuals 9 years and older. This factor
compensated for a consistent bias in USDA-NFCS
that was attributed to under-reporting of the foods
consumed or the methods used to ascertain dietary
intakes. Layton (1993) used a weighted average
oxygen uptake of 0.05 L O2/KJ, which was
determined from data reported in the 1977-1978
USDA-NFCS and the second NHANES
(NHANES II). The survey sample for NHANES II
was approximately 20,000 participants. A VQ of 27
used in the calculations was calculated as the
geometric mean of VQ data that were obtained from
several studies.
The inhalation rate estimation techniques are
shown in the footnotes in Table 6-45. Table 6-46
presents the daily inhalation rate for each age/sex
cohort. As shown in Table 6-45, the highest daily
inhalation rates were 10 nrVday for children between
the ages of 6 and 8 years, 17 nrVday for males
between 15 and 18 years, and 13 nrYday for females
between 9 and 11 years. Estimated average lifetime
inhalation rates for males and females are 14 nrVday
and 10 nrVday, respectively (see Table 6-45).
Inhalation rates were also calculated for active and
inactive periods for the various age/sex cohorts.
The inhalation rate for inactive periods was
estimated by multiplying the BMR times H times
VQ. BMR was defined as "the minimum amount of
energy required to support basic cellular respiration
while at rest and not actively digesting food"
(Layton, 1993). The inhalation rate for active periods
was calculated by multiplying the inactive inhalation
rate by the ratio of the rate of energy expenditure
during active hours to the estimated BMR. This ratio
is presented as F in Table 6-45. Table 6-45 also
presents these data for active and inactive inhalation
rates. For children, inactive and active inhalation
rates ranged from 2.35 to 5.95 nrVday and from 6.35
to 13.09 nrVday, respectively. For adult males (19 to
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64 years old), the average inactive and active
inhalation rates were approximately 10 and
19 nrYday, respectively. Also, the average inactive
and active inhalation rates for adult females (19 to
64 years old) were approximately 8 and 12 nrYday,
respectively.
Second Approach
Inhalation rates were calculated as the product of
the BMR of the population cohorts, the ratio of total
daily energy expenditure to daily BMR, H, and VQ.
The BMR data obtained from the literature were
statistically analyzed, and regression equations were
developed to predict BMR from body weights of
various age/sex cohorts. Table 6-46 presents the
statistical data used to develop the regression
equations. Table 6-47 presents the data obtained from
the second approach. Inhalation rates for children
(6 months-10 years) ranged from 7.3-9.3 m3/day for
male and 5.6-8.6 nrVday for female children; for
older children (10-18 years), inhalation rates were 15
nrYday for males and 12 nrYday for females. Adult
females (18 years and older) ranged from 9.9-11
nrYday and adult males (18 years and older) ranged
from 13-17 nrYday. These rates are similar to the
daily inhalation rates obtained using the first
approach. Also, the inactive inhalation rates obtained
from the first approach are lower than the inhalation
rates obtained using the second approach. This may
be attributed to the BMR multiplier employed in the
equation of the second approach to calculate
inhalation rates.
Third Approach
Inhalation rates were calculated by multiplying
estimated energy expenditures associated with
different levels of physical activity engaged in over
the course of an average day by VQ and H for each
age/sex cohort. The energy expenditure associated
with each level of activity was estimated by
multiplying BMRs of each activity level by the MET
and by the time spent per day performing each
activity for each age/sex population. The
time-activity data used in this approach were
obtained from a survey conducted by Sallis et al.
(1985) (Layton, 1993). In that survey, the
physical-activity categories and associated MET
values used were sleep, MET=1; light-activity,
MET =1.5; moderate activity, MET = 4; hard
activity, MET = 6; and very hard activity, MET =10.
The physical activities were based on recall by the
test subject (Layton, 1993). The survey sample was
2,126 individuals (1,120 women and 1,006 men) ages
20-74 years that were randomly selected from four
communities in California. The body weights were
obtained from a study conducted by Najjar and
Rowland (1987) that randomly sampled individuals
from the U.S. population (Layton, 1993). Table 6-48
presents the daily inhalation rates (VE) in nrYday and
nrYhour for adult males and females aged
20-74 years at five physical activity levels. The total
daily inhalation rates ranged from 13-17 nrYday for
adult males and 11-15 nrYday for adult females.
The rates for adult females were higher when
compared with the other two approaches. Layton
(1993) reported that the estimated inhalation rates
obtained from the third approach were particularly
sensitive to the MET value that represented the
energy expenditures for light activities. Layton
(1993) stated further that in the original time-activity
survey (i.e., conducted by Sallis et al. [1985]), time
spent performing light activities was not presented.
Therefore, the time spent at light activities was
estimated by subtracting the total time spent at sleep,
moderate, heavy, and very heavy activities from
24 hours (Layton, 1993). The range of inhalation
rates for adult females were 9.6-11 nrYday,
9.9-11 nrYday, and 11-15 nrYday, for the first,
second, and third approaches, respectively. The
inhalation rates for adult males ranged from 13-16
nrYday for the first approach, and 13-17 nrYday for
the second and third approaches.
Inhalation rates were also obtained for short-term
exposures for various age/sex cohorts and five
energy-expenditure categories (rest, sedentary, light,
moderate, and heavy). BMRs were multiplied by the
product of MET, H, and VQ. Table 6-49 presents the
inhalation-rate data obtained for short-term
exposures.
The major strengths of the Layton (1993) study
are that it obtains similar results using three different
approaches to estimate inhalation rates in different
age groups and that the populations are large,
consisting of men, women, and children.
Explanations for differences in results due to
metabolic measurements, reported diet, or activity
patterns are supported by observations reported by
other investigators in other studies. Major limitations
of this study are (1) the estimated activity pattern
levels are somewhat subjective; (2) the explanation
that activity pattern differences are responsible for
the lower level obtained with the metabolic approach
(25%) compared to the activity pattern approach is
not well supported by the data; and (3) different
populations were used in each approach, which may
have introduced error.
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6.4.10. Linn et al. (1993)—Activity Patterns in
Ozone Exposed Construction Workers
Linn et al. (1993) estimated the inhalation rates of
19 construction workers who perform heavy outdoor
labor before and during a typical work shift. The
workers (laborers, iron workers, and carpenters) were
employed at a site on a hospital campus in suburban
Los Angeles. The construction site included a new
hospital building and a separate medical office
complex. The study was conducted between mid-July
and early November, 1991. During this period, ozone
(O3) levels were typically high. Initially, each subject
was calibrated with a 25-minute exercise test that
included slow walking, fast walking, jogging, lifting,
and carrying. All calibration tests were conducted in
the mornings. VR and HR were measured
simultaneously during the test. The data were
analyzed using least squares regression to derive an
equation for predicting VR at a given HR. Following
the calibration tests, each subject recorded the type of
activities to be performed during their work shift (i.e.,
sitting/standing, walking, lifting/carrying, and
"working at trade"—defined as tasks specific to the
individual's job classification). Location, and
serf-estimated breathing rates ("slow" similar to slow
walking, "medium" similar to fast walking, and
"fast" similar to running) were also recorded in the
diary. During work, an investigator recorded the diary
information dictated by the subjects. HR was
recorded minute by minute for each subject before
work and during the entire work shift. Thus, VR
ranges for each breathing rate and activity category
were estimated from the HR recordings by employing
the relationship between VR and HR obtained from
the calibration tests.
A total of 182 hours of HR recordings were
obtained during the survey from the 19 volunteers;
144 hours reflected actual working time according to
the diary records. The lowest actual working hours
recorded was 6.6 hours, and the highest recorded for
a complete work shift was 11.6 hours (Linn et al.,
1993). Table 6-50 presents summary statistics for
predicted VR distributions for outdoor workers, and
for job- or site-defined subgroups. The data reflect all
recordings before and during work, and at break
times. For all subjects, the mean inhalation rate was
1.68 m3/hour with a standard deviation of ±0.72 (see
Table 6-50). Also, for most subjects, the 1st and
99th percentiles of HR were outside of the calibration
range. Therefore, corresponding IR percentiles were
extrapolated using the calibration data (Linn et al.,
1993).
The data shown in Table 6-51 represent
distribution patterns of mean inhalation rate for each
subject, total subjects, and job- or site-defined
subgroups by self-estimated breathing rates (slow,
medium, or fast) or by type of job activity. All data
include working and non-working hours. The mean
inhalation rates for most individuals showed
statistically significant increases with higher
serf-estimated breathing rates or with increasingly
strenuous job activity (Linn et al., 1993). Inhalation
rates were higher in hospital site workers when
compared with office site workers (see Table 6-51).
In spite of their higher predicted VR workers at the
hospital site reported a higher percentage of slow
breathing time (31%) than workers at the office site
(20%), and a lower percentage of fast breathing time,
3% and 5%, respectively (Linn et al., 1993).
Therefore, individuals whose work was objectively
heavier than average (from VR predictions) tended to
describe their work as lighter than average (Linn et
al., 1993). Linn et al. (1993) also concluded that
during an O3 pollution episode, construction workers
should experience similar microenvironmental O3
exposure concentrations as other healthy outdoor
workers, but with approximately twice as high a VR.
Therefore, the inhaled dose of O3 should be almost
two times higher for typical heavy-construction
workers than for typical healthy adults performing
less strenuous outdoor jobs.
Limitations associated with this study are its age
and the small sample size. Another limitation of this
study is that calibration data were not obtained at
extreme conditions. Therefore, it was necessary to
predict inhalation rate values that were outside the
calibration range. This may introduce an unknown
amount of uncertainty to the data set. Subjective
serf-estimated breathing rates may be another source
of uncertainty in the inhalation rates estimated. An
advantage is that this study provides empirical data
useful in exposure assessments for a population
thought to be the most highly exposed common
occupational group (outdoor workers).
6.4.11. Rusconi et al. (1994)—Reference Values
for Respiratory Rate in the First 3 Years
of Life
Rusconi et al. (1994) examined a large number of
infants and children in Milano, Italy, in order to
determine the reference values for respiratory rate in
children aged 15 days to 3 years. A total of 618
infants and children (336 males and 282 females),
who did not have respiratory infections or any severe
disease, were included in the study. Of the 618, a
total of 309 were in good health and were observed in
daycare centers, while the remaining 309 were seen
in hospitals or as outpatients.
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Chapter 6—Inhalation Rates
Respiratory rates were recorded twice, 30 to
60 minutes apart, listening to breath sounds for
60 seconds with a stethoscope, when the child was
awake and calm and when the child was sleeping
quietly (sleep not associated with any spontaneous
movement, including eye movements or
vocalizations) (see Table 6-52). The children were
assessed for 1 year in order to determine the
repeatability of the recordings, to compare respiratory
rate counts obtained by stethoscope and by
observation, and to construct reference percentile
curves by age in a large number of subjects.
The authors plotted the differences between
respiratory rate counts determined by stethoscope at
30- to 60-minute intervals against their mean count in
waking and sleeping subjects. The standard deviation
of the differences between the two counts was 2.5
and 1.7 breaths/minute, respectively, for waking and
sleeping children. This standard deviation yielded
95% repeatability coefficients of 4.9 breaths/minute
when the infants and children were awake and
3.3 breaths/minute when they were asleep.
In both waking and sleeping states, the respiratory
rate counts determined by stethoscope were found to
be higher than those obtained by observation. The
mean difference was 2.6 and 1.8 breaths per minute,
respectively, in waking and sleeping states. The mean
respiratory rate counts were significantly higher in
infants and children at all ages when awake and calm
than when asleep. A decrease in respiratory rate with
increasing age was seen in waking and sleeping
infants and children. A scatter diagram of respiratory
rate counts by age in waking and sleeping subjects
showed that the pattern of respiratory rate decline
with age was similar in both states, but it was much
faster in the first few months of life. The authors
constructed centile curves by first log-transforming
the data and then applying a second degree
polynomial curve, which allowed excellent fitting to
observed data. Figures 6-1 and 6-2 show smoothed
percentiles by age in waking and sleeping subjects,
respectively. The variability of respiratory rate among
subjects was higher in the first few months of life,
which may be attributable to biological events that
occur during these months, such as maturation of the
neurologic control of breathing and changes in lung
and chest wall compliance and lung volumes.
An advantage of this study is that it provides
distribution data for respiratory rate for children from
infancy (less than 2 months) to 36 months old. The
main limitation of this study is that data are provided
in breaths/minute for awake and asleep subjects.
Activity pattern data for the awake subjects are
limited, which prevents characterization of breathing
rates for various levels of exertion. These data are not
U.S. data; U.S. distributions were not available.
Although, there is no reason to believe that the
respiratory rates for Italian children would be
different from that of U.S. children, this study only
provided data for a narrow range of activities.
6.4.12. Price et al. (2003)—Modeling
Intel-individual Variation in Physiological
Factors Used in PBPK Models of Humans
Price et al. (2003) developed a database of values
for physiological parameters often used in
physiologically based pharmacokinetic (PBPK)
models. The database consisted of approximately
31,000 records containing information on volumes
and masses of selected organs and tissues, blood
flows for the organ and tissues, and total resting
cardiac output and average inhalation rates. Records
were created based on data from the NHANES III
survey.
The study authors note that the database provides
a source of data for human physiological parameters
where the parameter values for an individual are
correlated with one another and capture
interindividual variation in populations of a specific
sex, race, and age range. A publicly available
computer program, Physiological Parameters for
PBPK Modeling, was also developed to randomly
retrieve records from the database for groups of
individuals of specified age ranges, sex, and
ethnicities (The Lifeline Group, 2007). Price et al.
(2003) recommends that output sets be used as inputs
to Monte Carlo-based PBPK models of
interindividual variation in dose. A limitation of this
study is that these data have not been validated
against actual physiological data. Ideally, the
database records would have been obtained from
detailed physiological analyses of individuals,
however, such a survey was not conducted for this
study.
6.4.13. Brochu et al. (2006b)—Physiological
Daily Inhalation Rates for Free-Living
Pregnant and Lactating Adolescents and
Women Aged 11 to 55 Years, Using Data
from Doubly Labeled Water
Measurements for Use in Health Risk
Assessment
PDIRs were determined by Brochu et al. (2006b)
for underweight, normal-weight, and
overweight/obese pregnant and lactating females
aged 11 to 55 years using published data on total
daily energy expenditures, and energy costs for
growth, pregnancy and lactation (breast-energy
output and maternal milk-energy synthesis) in
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Chapter 6—Inhalation Rates
free-living females. These data were obtained using
the DLW methodology in which disappearance rates
of predetermined doses of DLW (2H2O and H218O) in
urine from non-pregnant and non-lactating females
(N = 357) and normal-weight males (N = 131) as well
as saliva from gravid and breast-feeding females
(TV =91) were monitored by gas-isotope-ratio mass
spectrometry.
PDIRs were calculated for underweight,
normal-weight, and overweight/obese females aged
11 to 55 years in pre-pregnancy, at Weeks 9, 22, and
36 during pregnancy, and Weeks 6 and 27
postpartum. Weight groups were determined by BMI
cutoffs settled by the Institute of Medicine for pre-
pregnant females. Underweight, normal-weight, and
overweight/obese individuals were defined as those
having BMIs lower than 19.8 kg/m2, between 19.8
and 26 kg/m2, and greater than 26 kg/m2,
respectively. Parameters used for breast-energy
output and the extra energy cost for milk synthesis
were 539.29 ± 106.26 kcal/day and 107.86 ± 21.25
kcal/day, respectively. Monte Carlo simulations were
necessary to integrate total daily energy requirements
of non-pregnant and non-lactating females into
energy costs and weight changes at the 9th, 22nd, and
36th weeks of pregnancy and at the 6th and 27th
postpartum weeks. A total of 108 sets of 5,000
energetic data were run, resulting in a simulation of
540,000 data, pertaining to 45,000 simulated
subjects. Means, standard deviations, and percentiles
of energetic values in kcal/day and kcal/kg-day for
males and females were converted into PDIRs in
nrVday and m3/kg-day by using the equation
developed by Layton (1993).
Tables 6-53, 6-54, and 6-55 present the
distribution of physiological daily inhalation rate
percentiles in nrVday for underweight,
normal-weight, and overweight/obese females,
respectively, during pregnancy and postpartum
weeks. Tables 6-56, 6-57, and 6-58 present
physiological daily inhalation rate percentiles in
m3/kg-day for the same categories. PDIRs for under-,
normal-, and overweight/obese pregnant and lactating
females were higher than those for males reported in
Brochu et al. (2006a). In normal-weight subjects,
inhalation rates are higher by 18 to 41% throughout
pregnancy and 23 to 39% during postpartum weeks:
actual values were higher in females by 1.13 to
2.01 nrVday at the 9th week of pregnancy, 3.74 to
4.53 nrVday at the 22nd week, and 4.41 to 5.20 nrVday
at the 36th week, and by 4.43 to 5.30 nrVday at the
6th postpartum week and 4.22 to 5.11 nrVday at the
27th postpartum week. The highest 99th percentiles
were found to be 0.622 m3/kg-day in pregnant
females and 0.647 m3/kg-day in lactating females. By
comparison, the highest 99th percentile value for
individuals aged 2.6 months to 96 years was
determined to be 0.725 nrVkg-day (Brochu et al.,
2006a). The authors concluded that air quality criteria
and standard calculations based on the latter value for
non-carcinogenic toxic compounds should, therefore,
be protective for virtually all pregnant and lactating
females. Brochu et al. (2006b) also noted that the
default assumption used by IRIS to derive HECs
(total respiratory tract surface of an adult human male
of 54.3 m2 is exposed to a total daily air intake of 20
m3) would underestimate exposures to pregnant or
lactating females since approximately one pregnant
or lactating female out of two is exposed to a total
daily air intake of 20 m3 up to the highest 99th
percentile of 47.3 m3.
An advantage of this study is that it includes
pregnant and lactating females, and that data are
provided for adolescents aged 11 years and older. A
limitation of this study is that the study population
was partially drawn from Canada and may not
represent the general U.S. population. Also, age
groups for adolescents for which data are provided do
not conform to U.S. EPA's recommended age groups
for children.
6.4.14. Allan et al. (2009)—Inhalation Rates for
Risk Assessments Involving Construction
Workers in Canada
Allan et al. (2009) generated probability density
distributions by performing a Monte Carlo simulation
to describe inhalation rates for Canadian male and
female construction workers. Construction workers in
this study were those involved in the construction or
physical maintenance of buildings, structures, or
other facilities, and their ages ranged from 16 to 65
years. Information regarding activity patterns and/or
inhalation rates was obtained from published
literature and used to estimate male construction
workers' hourly inhalation rates. Female construction
worker inhalation rates were estimated using the ratio
of general public female-to-male inhalation rates and
male construction workers' hourly inhalation rates.
Published energy expenditure and inhalation rates
were compared by occupation within the construction
industry, and these data were used to develop
trade-specific scaling factors. All inhalation rates
were developed as probability density functions
through Monte Carlo simulation. Ten thousand
iterations of random sampling were performed, and at
the end of the simulation, the results for all 10,000
iterations were summarized into frequency
histograms. The mean, standard deviation, and
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Chapter 6—Inhalation Rates
percentiles were calculated based on the frequency
counts.
Inhalation rates for male construction workers
were represented by a log normal distribution, with a
mean rate of 1.40 + 0.51 nrVhour. Hourly inhalation
rates for female construction workers were scaled
down from those of their male counterparts, based on
relative awake-time inhalation rates for men and
women in the general public. Inhalation rates for
female construction workers were also represented by
a log normal distribution, with a mean rate of 1.25 +
0.66 nrVhour. Construction trade-specific scaling
factors were developed and ranged from 0.78 for
electricians to 1.11 for ironworkers.
An advantage of this study is that it provides
estimated inhalation rates for a population of
construction workers. A limitation of this study is that
the construction workers in this study were solely
male construction workers; no females were among
the cohorts monitored.
6.5.
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Table 6-4. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/day) for Free-Living
Normal- Weight Males and Females Aged 2.6 Months to 96 Years
Age Group
(years) N
Body Weight3
(kg)
Mean ± SD
Physiological Daily Inhalation Ratesb
(nrVday)
Percentile0
Mean ± SD
5th
10th
25th
50th
75th
90th
95th
99th
Males
0.22 to <0
0.5to
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-Living Normal-Weight
Males, Females, and Males and Females Combined
Age Group3' b
N
Mean0
95th' °
Males
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to < 16 years
16 to <21 years
21 to <31 years
31 to <41 years
41 to <51 years
51 to <61 years
61 to <71 years
71 to <81 years
>81 years
o ^
32
32
40
72
35
25
25
38
30
30
64
41
33
33
83
50
50
3.38
3.38
4.22
3.85
5.12
7.60
7.60
10.59
17.23
17.23
17.36
16.88
16.24
16.24
14.26
12.96
12.96
4.57
4.57
5.51
5.09
6.56
9.71
9.71
13.87
23.26
23.26
22.65
21.00
20.64
20.64
18.47
17.03
17.03
Females
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
21 to <31 years
31 to <41 years
41 to <51 years
51 to <61 years
61 to <71 years
71 to <81 years
>81 years
53
53
63
116
66
36
36
161
87
87
155
59
58
58
103
45
45
3.26
3.26
3.96
3.64
4.78
7.06
7.06
9.84
13.28
13.28
13.45
13.68
12.31
12.31
11.21
9.80
9.80
4.36
4.36
5.14
4.78
6.36
8.97
8.97
12.61
17.56
17.56
17.50
16.58
15.71
15.71
14.69
13.37
13.37
Exposure Factors Handbook
September 2011
Page
6-25
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-Living Normal-Weight
Males, Females, and Males and Females Combined (continued)
Age Groupa>b
N
Mean0
95th,c
Males and Females Combined
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 years
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to < 16 years
16 to <21 years
21 to <31 years
31 to <41 years
41 to <51 years
51 to <61 years
61 to <71 years
71to<81years
>81 years
85
85
103
188
101
61
61
199
117
117
219
100
91
91
186
95
95
3.31
3.31
4.06
3.72
4.90
7.28
7.28
9.98
14.29
14.29
14.59
14.99
13.74
13.74
12.57
11.46
11.46
a No other age groups from Table 6-4 (Brochu et al., 2006a) fit into the U.S. EPA age
b See Table 6-25 for concordance with U.S. EPA age groupings.
0 Weighted (where possible) average of reported study means and 95th percentiles.
TV = Number of individuals.
Source: Brochu et al., 2006a.
4.44
4.44
5.28
4.90
6.43
9.27
9.27
12.85
19.02
19.02
19.00
18.39
17.50
17.50
16.37
15.30
15.30
groupings.
Page Exposure Factors Handbook
6-26 September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-6. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/day) for Free-Living
Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96 Years
Physiological Daily Inhalation Rates (m /day)
Age Group
(years) N
Body Weight3
(kg)
Mean ± SD
Percentile0
Mean ± SD
10"
25"
50"
75"
90"
95"
99"
Males—No rm al-weight
4to<5.1
5.1to<9.1
9.1to<18.1
18.1 to<40.1
40.1 to<70.1
70.1to<96
77
52
36
98
34
38
19.0±1.9
22.6 ±3.5
41.4±12.1
71.3±6.1
70.0 ±7.8
68.9 ±6.8
7.90 ±0.97
9.14 ±1.44
13.69 ±3.95
17.41±2.70
15.60 ±2.89
12.69 ±2.33
6.31
6.77
7.19
12.96
10.85
8.85
6.66
7.29
8.63
13.94
11.89
9.70
7.25
8.17
11.02
15.58
13.65
11.11
7.90
9.14
13.69
17.41
15.60
12.69
8.56
10.11
16.35
9.15
10.99
9.50
11.51
18.75 20.19
19.23 20.87 21.85
17.54
14.26
15.6
10.16
12.49
22.88
23.69
19.30 20.34 22.31
16.53 18.12
Males—Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
18.1 to<40.1
40.1 to<70.1
70.1to<96
54
40
33
52
81
32
26.5 ±4.9
32.5 ±9.2
55.8 ±10.8
98.1 ±25.2
93.2 ±14.9
82.3 ±10.3
9.59 ±1.26
10.88 ±2.49
14.52 ±1.98
20.39 ± 3.62
17.96 ±3.71
14.23 ±2.94
7.52
6.78
11.25
14.44
11.85
9.40
7.98
7.69
11.98
15.75
13.20
10.46
8.74
9.20
13.18
17.95
15.45
12.25
9.59
10.88
14.52
10.44
12.56
15.85
11.21
14.07
17.06
11.66
14.98
17.78
20.39 22.83 25.03 26.35
17.96 20.46
14.23 16.21
22.71
18.00
24.06
12.52
16.68
19.13
28.81
26.59
19.06 21.07
Females—Normal-weight
4to<5.1
5.1to<9.1
9.1to<18.1
18.1 to<40.1
40.1 to<70.1
70.1to<96
82
151
124
135
79
24
18.7 ±2.0
25.5 ±4.1
42.7±11.1
59.1 ±6.3
59.1 ±5.3
54.8 ±7.5
7.41 ±0.91
9.39 ±1.62
12.04 ±2.86
13.73 ±2.01
11.93 ±2.16
8.87 ±1.79
5.92
6.72
7.34
10.41
8.38
5.92
6.25
7.31
8.38
11.15
9.16
6.57
6.80
8.30
10.11
12.37
10.47
7.66
7.41
9.39
12.04
13.73
11.93
8.87
8.02
10.48
13.97
15.09
13.38
10.07
8.57
11.47
15.70
16.31
14.69
11.16
8.90
12.05
16.74
17.04
15.48
11.81
9.52
13.16
18.68
18.41
16.95
13.03
Females—Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
18.1 to<40.1
40.1 to<70.1
70.1to<96
56
68
68
76
91
28
26.1 ±5.5
34.6 ±9.9
59.2 ±12.8
84.4 ±16.3
81.7±17.2
69.0 ±7.8
8.70 ±1.13
10.55 ±2.23
14.27 ±2.70
15.66±2.11
13.01 ±2.82
10.00 ±1.78
6.84
6.88
9.83
7.26
7.69
10.81
3.70
12.18 12.95
8.37 9.40
7.07 7.71
7.94
9.05
12.45 14.27
14.23
11.11
8.80
9.47
10.55 12.06
16.09
15.66 17.08
13.01 14.91
10.15 10.56 11.33
14.22 15.75
18.71 20.55
19.13 20.57
10.00
13.41
17.73
18.36
16.62 17.64 19.56
11.20 12.28 12.93 14.14
N
SD
Measured body weight. Normal-weight and overweight/obese males defined according to the BMI cut-offs.
Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) x H x (VEIVO2) x
10~3, where H= 0.21 L of O2/Kcal, VEIVO2 = 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day)
and£CG = stored daily energy cost for growth (kcal/day).
Percentiles based on a normal distribution assumption for age groups.
= Number of individuals.
= Standard deviation.
Source: Brochu et al, 2006a.
Exposure Factors Handbook
September 2011
Page
6-27
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) per Unit of Body
Weight (m3/kg-day) for Free-Living Normal- Weight Males and Females Aged 2.6 Months to 96 Years
Physiological Daily Inhalation Rates3 (m3/kg-day)
Age Group
(years)
Percentileb
Mean ± SD
5th
10th 25th
50th
75*
90th
95*
99th
Males
0.22 to <0.5
0.5to
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs)
Free-Living Normal- Weight and Overweight/Obese Males and Females Aged 4
Physiological Daily Inhalation Ratesa (m3/kg
-day)
(m3/kg-day) for
to 96 Years
Percentileb
Age Group (years) Mean ± SD
4to<5.1
5.1
9.1
18.
40.
70.
to<9.1
to<18.1
1 to <40
1 to <70
1 to <96
0.42 ± 0.04
0.41 ±0.06
0.33 ±0.05
1 0.25± 0.04
1 0.22 ± 0.04
0.19 ±0.03
5th
0.35
0.31
0.26
0.18
0.16
0.13
10th
Males —
0.36
0.34
0.27
0.20
0.17
0.14
25th
50th
75th
90th
95th
99th
Normal-weight
0.39
0.37
0.30
0.22
0.20
0.16
0.42
0.41
0.33
0.25
0.22
0.19
0.45
0.45
0.37
0.27
0.25
0.21
0.47
0.48
0.40
0.29
0.28
0.23
0.49
0.50
0.41
0.31
0.29
0.24
0
0
52
54
0.45
0
0
0
33
32
26
Males — Overweight/obese
4to<5.1
5.1
9.1
18.
40.
70.
to<9.1
to<18.1
1 to <40
1 to <70
1 to <96
0.37 ±0.04
0.35 ±0.08
0.27 ±0.04
1 0.21 ± 0.04
1 0.19 ±0.03
0.17 ±0.03
0.30
0.22
0.20
0.15
0.14
0.12
0.31
0.25
0.22
0.17
0.15
0.13
0.34
0.29
0.24
0.19
0.17
0.15
0.37
0.35
0.27
0.21
0.19
0.17
0.40
0.40
0.29
0.22
0.22
0.19
0.42
0.45
0.32
0.26
0.24
0.21
0.44
0.47
0.33
0.27
0.25
0.22
0.47
0
0
0
0
53
36
30
28
0.24
Females — Normal-weight
4to<5.1
5.1
9.1
18.
40.
70.
to<9.1
to<18.1
1 to <40
1 to <70
1 to <96
0.40 ±0.05
0.37 ±0.06
0.29 ±0.06
1 0.23 ± 0.04
1 0.20 ± 0.04
0.16 ±0.04
0.32
0.27
0.20
0.17
0.14
0.11
0.34
0.29
0.22
0.19
0.15
0.12
0.37
0.33
0.25
0.21
0.18
0.14
0.40
0.37
0.29
0.23
0.20
0.16
0.43
0.41
0.33
0.26
0.23
0.19
0.46
0.45
0.36
0.28
0.25
0.20
0.48
0.47
0.38
0.30
0.27
0.22
0
0
0
0
0
0
51
52
42
32
29
24
Females — Overweight/obese
4to<5.1
5.1
9.1
18.
40.
70.
a
b
SD
to<9.1
to<18.1
1 to <40
1 to <70
1 to <96
0.34 ±0.04
0.32 ±0.07
0.25 ±0.05
1 0.19 ±0.03
1 0.16 ±0.03
0.15 ±0.03
0.27
0.21
0.17
0.14
0.11
0.10
0.28
0.23
0.18
0.15
0.12
0.11
0.31
0.27
0.21
0.17
0.14
0.13
0.34
0.32
0.25
0.19
0.16
0.15
0.37
0.36
0.28
0.21
0.18
0.16
0.40
0.40
0.31
0.22
0.20
0.18
0.41
0.43
0.33
0.23
0.21
0.19
0
0
0
0
0
0
44
47
36
25
23
21
Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) x // x
(VE/VO2) x 10~3, where// = 0.21 L of O2/Kcal, VEIVO2 = 27 (Layton, 1993), TDEE = total daily energy
expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day).
Percentiles based on a normal distribution assumption for age groups.
=
Standard deviation.
Source: Brochu et al., 2006a.
Exposure Factors Handbook
September 2011
Page
6-29
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-9. Physiological Daily Inhalation Rates (PDIRs) for Newborns Aged
1 Month or Less
Physiological Daily Inhalation Rates3
21
32
33
a
A/Tpari +
Body Weight (kg)
Age Group TV Mean ± SD (m3/day)
days (3 weeks) 13b'c 1.2 ±0.2 0.85±0.17d
days (~1 month) 10e'f 4.7 ±0.7 2.45 ± 0.59g
days (~1 month) 10b'f 4.8 ±0.3 2.99 ± 0.47s
SD
iJl-f
(m3/kg-day)
0.74 ± 0.09d
0.53±0.10g
0.62 ±0.09g
Physiological daily inhalation rates were calculated using the following equation:
(TDEE + ECG) xffx (VEIVO2) x i(T3, where H = 0.21 L of O2/Kcal, VEIVO2 = 27 (Layton,
b
c
d
e
f
g
N
SD
1993), TDEE = total daily energy expenditure (kcal/day) and ECG = stored
growth (kcal/day).
Formula-fed infants.
Healthy infants with very low birth weight.
TDEEs based on nutritional balance measurements during 3 -day periods.
Breast-fed infants.
daily energy cost for
Infants evaluated as being clinically healthy and neither underweight or overweight.
TDEEs based on 2H2O and H218O disappearance rates from urine.
= Number of individuals.
= Standard deviation.
Source: Brochu et al., 2006a.
Page
6-30
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-10. Non-Normalized Daily Inhalation Rates (m3/day) Derived Using Layton's (1993) Method and
CSFH Energy Intake Data
Age
Sample Size
(Non-Weighted)
Mean
SEM
50th
Percentiles
90th
SE of 95th
95th Percentile
Infancy
0 to 2 months
3 to 5 months
6 to 8 months
9 to 1 1 months
0 to 1 1 months
182
294
261
283
1,020
3.63
4.92
6.09
7.41
5.70
0.14
0.14
0.15
0.20
0.10
3.30
4.56
5.67
6.96
5.32
5.44
6.86
8.38
10.21
8.74
7.10
7.72
9.76
11.77
9.95
0.64
0.48
0.86
-
0.55
Children
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
11 years
12 years
13 years
14 years
15 years
16 years
17 years
1 8 years
934
989
1,644
1,673
790
525
270
253
271
234
233
170
194
193
185
201
159
135
8.77
9.76
10.64
11.40
12.07
12.25
12.86
13.05
14.93
15.37
15.49
17.59
15.87
17.87
18.55
18.34
17.98
18.59
0.08
0.10
0.10
0.09
0.13
0.18
0.21
0.25
0.29
0.35
0.32
0.54
0.44
0.62
0.55
0.54
0.96
0.78
8.30
9.38
10.28
11.05
11.56
11.95
12.51
12.42
14.45
15.19
15.07
17.11
14.92
15.90
17.91
17.37
15.90
17.34
12.19
13.56
14.59
15.53
15.72
16.34
16.96
17.46
19.68
20.87
21.04
25.07a
22.81a
25.75a
28.11a
27.56
31.42a
28.80a
13.79
14.81
16.03
17.57
18.26
17.97
19.06
19.02
22.45a
22.90a
23.91a
29.17a
26.23a
29.45a
29.93a
31.01
36.69a
35.24a
0.25
0.35
0.27
0.23
0.47
0.87
1.27
1.08
1.35
1.02
1.62
1.61
1.11
4.38
1.79
2.07
-
4.24
Adolescent Boys
9 to 1 8 years
983
19.27
0.28
17.96
28.78
32.82
1.39
Adolescent Girls
9 to 1 8 years
992
14.27
0.22
U.S. EPA Cancer Guidelines' Age Groups
0 through 1 year
2 through 15 years
1,954
7,624
7.50
14.09
0.08
0.12
13.99
21.17
23.30
0.61
with Greater Weighting
7.19
13.13
11.50
20.99
12.86
23.88
a FASEB/LSRO (1995) convention, adopted by CSFII, denotes a value that might be less statistically
than other estimates due to small cell size.
0.17
0.50
reliable
Denotes unable to calculate.
SEM = Standard error of the mean.
SE = Standard error.
Source: Arcus-Arth and Blaisdell, 2007.
Exposure Factors Handbook
September 2011
Page
6-31
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-11. Mean and
Age Groupa'b
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to < 16 years
16 to <21 years
95th Percentile Inhalation Rate Values (m3/day) for Males and Females Combined
Sample Size
182
182
294
544
1,020
934
989
4,107
1,553
975
495
Mean0
3.63
3.63
4.92
6.78
5.70
8.77
9.76
11.22
13.42
16.98
18.29
a No other age groups from Table 6-10 (Arcus-Arth and Blaisdell, 2007) fit into the U
groupings.
b See Table 6-25 for concordance with U.S. EPA age g
0 Weighted (where possible) average of reported study
roupings.
means and 95th percentiles.
95th'0
7.10
7.10
7.72
10.81
9.95
13.79
14.81
17.09
19.86
27.53
33.99
S. EPA age
Source: Arcus-Arth and Blaisdell, 2007.
Page Exposure Factors Handbook
6-32 September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-12. Summary of Institute of Medicine (IOM) Energy Expenditure Recommendations
for Active and Very Active People with Equivalent Inhalation Rates
Males
Age
(years)
<1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19 to 30
31 to 50
51 to 70
Energy
Expenditure
(kcal/day)
607
869
1,050
1,485-1,683
1,566-1,783
1,658-1,894
1,742-1,997
1,840-2,115
1,931-2,225
2,043-2,359
2,149-2,486
2,279-2,640
2,428-2,817
2,618-3,038
2,829-3,283
3,013-3,499
3,152-3,663
3,226-3,754
2,823-3,804
3,015-3,490
2,862-3,338
2,671-3,147
Inhalation Rate
(nrVday)
3.4
4.9
5.9
8.4-9.5
8.8-10.1
9.4-10.7
9.8-11.3
10.4-11.9
10.9-12.6
11.5-13.3
12.1-14.0
12.9-14.9
13.7-15.9
14.8-17.2
16.0-18.5
17.0-19.8
17.8-20.7
18.2-21.2
18.4-21.5
17.0-19.7
16.2-18.9
15.1-17.8
Females
Energy Expenditure
(kcal/day)
607
869
977
1,395-1,649
1,475-1,750
1,557-1,854
1,642-1,961
1,719-2,058
1,810-2,173
1,890-2,273
1,972-2,376
2,071-2,500
2,183-2,640
2,281-2,762
2,334-2,831
2,362-2,870
2,368-2,883
2,353-2,871
2,336-2,858
2,373-2,683
2,263-2,573
2,124-2,435
Inhalation Rate
(nrVday)
3.4
4.9
5.5
7.9-9.3
8.3-9.9
8.8-10.5
9.3-11.1
9.7-11.6
10.2-12.3
10.7-12.8
11.1-13.4
11.7-14.1
12.3-14.9
12.9-15.6
13.2-16.0
13.3-16.2
13.4-16.3
13.3-16.2
13.2-16.1
13.4-15.2
12.8-14.5
12.0-13.8
Source: Stifelman, 2007.
Exposure Factors Handbook
September 2011
Page
6-33
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-13. Mean Inhalation Rate Values (m3/day) for Males, Females, and
Males and Females Combined"
Age Groupb>0 (years)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-14. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category"
Age Group
(years)
Daily Average Inhalation Rate, Unadjusted for Body Weight
(nrVday)
Percentiles
Mean
*
10t
th
25
th
50
th
75
th
90t
th
95
th
Maximum
Birth to <1
lto<2
2to<3
3 to<6
6to
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-15. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age
Category3
Daily Average Inhalation Rate, Unadjusted for Body Weight
(nrVday)
Age Group (years)
Birth to <1
1
2
3to<6
6to81
N
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
Mean
8.52
13.31
12.74
12.17
12.41
13.44
13.59
14.57
14.98
16.20
16.19
12.99
12.04
11.15
5th
4.84
9.09
8.91
9.88
9.99
10.47
9.86
10.15
11.07
12.11
12.33
10.40
9.89
9.19
10th
5.49
10.12
10.07
10.38
10.35
11.12
10.61
10.67
11.81
12.57
12.96
10.77
10.20
9.46
Daily Avera^
Age Group (years)
Birth to <1
1
2
3to<6
6to81
N
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
Mean
1.14
1.20
0.95
0.69
0.43
0.25
0.21
0.21
0.21
0.22
0.22
0.18
0.18
0.18
5th
0.91
0.97
0.82
0.48
0.28
0.19
0.16
0.14
0.14
0.15
0.15
0.14
0.14
0.14
a Individual daily averages are weighted by
when calculating the statistics in this table
10th
0.97
1.01
0.84
0.54
0.31
0.20
0.17
0.16
0.15
0.16
0.16
0.15
0.15
0.15
25th
6.84
11.25
11.38
11.20
11.02
12.04
11.78
11.94
13.02
14.16
14.07
11.78
10.89
10.14
Percentiles
50th
8.41
13.03
12.60
12.02
11.95
13.08
13.20
14.10
14.69
15.88
15.90
12.92
11.82
11.02
75th
9.78
14.64
13.95
13.02
13.42
14.54
15.02
16.62
16.32
17.96
17.80
13.91
12.96
11.87
90th
11.65
17.45
15.58
14.03
15.13
16.26
17.12
19.32
18.50
19.92
19.93
15.39
14.11
12.84
95th
12.66
18.62
16.36
14.93
16.34
17.41
18.29
21.14
20.45
21.34
21.21
16.14
15.19
13.94
Maximum
26.25
24.77
23.01
19.74
20.82
26.58
30.11
30.23
28.28
35.88
25.70
20.33
17.70
16.93
>e Inhalation Rate, Adjusted for Body Weight
(m /day -kg)
25th
1.04
1.10
0.89
0.60
0.36
0.22
0.19
0.18
0.18
0.19
0.18
0.16
0.16
0.16
Percentiles
50th
1.13
1.18
0.96
0.68
0.43
0.24
0.21
0.20
0.20
0.21
0.21
0.17
0.17
0.18
75th
1.24
1.30
1.01
0.77
0.49
0.28
0.23
0.23
0.23
0.25
0.24
0.19
0.19
0.20
90th
1.33
1.41
1.07
0.88
0.55
0.31
0.27
0.26
0.27
0.28
0.28
0.21
0.21
0.21
95th
1.38
1.46
1.10
0.92
0.58
0.34
0.28
0.28
0.30
0.31
0.30
0.22
0.23
0.22
Maximum
1.60
1.73
1.23
1.12
0.75
0.47
0.36
0.40
0.43
0.41
0.40
0.27
0.34
0.28
their 4-year sampling weights as assigned within NHANES 1 999-2002
Inhalation rate was estimated using a multiple linear regression model.
N = Number of individuals.
Source: U.S. EPA,
2009.
Page
6-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-16. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females, and
Males and Females Combined
Age Group (years)
N
Mean
95*
Males
Birth to <1
lto<2
2to<3
3 to<6
6to81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
8.76
13.49
13.23
12.64
13.42
15.32
17.21
18.82
20.29
20.94
20.91
17.94
16.34
15.15
12.69
17.90
17.71
15.41
17.73
21.21
23.37
27.13
28.90
28.37
29.09
23.50
20.42
18.69
Females
Birth to <1
lto<2
2to<3
3to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
8.52
13.31
12.74
12.17
12.41
13.44
13.59
14.57
14.98
16.20
16.19
12.99
12.04
11.15
12.66
18.62
16.36
14.93
16.34
17.41
18.29
21.14
20.45
21.34
21.21
16.14
15.19
13.94
Exposure Factors Handbook Page
September 2011 6-37
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-16. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females, and Males
and Females Combined (continued)
Age Group (years)
N
Males and Females
Birth to <1
lto<2
2to<3
3 to<6
6to81
a Weighted average of reported
TV = Number of individuals.
Source: U.S. EPA, 2009.
834
553
516
1,083
1,834
2,788
2,423
1,724
1,597
1,516
1,249
1,378
966
561
Mean
Combined"
8.64
13.41
12.99
12.40
12.93
14.34
15.44
16.30
17.40
18.55
18.56
15.43
14.25
12.97
95th
12.67
18.22
17.04
15.17
17.05
19.23
20.89
23.57
24.30
24.83
25.17
19.76
17.88
16.10
male and female means and 95th percentiles.
Page Exposure Factors Handbook
6-38 September 2011
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-17. Descriptive Statistics for Average Ventilation
the Specified Activity
Rate," Unadjusted for Body Weight, While Performing Activities Within
Category, for Males by Age Category
Average Ventilation Rate (m3/minute)
Age Group
(years)
Percentiles
N
Mean
5th
10th
25th
Sleep or nap (Activity ID
Birth to <1
1
2
3to<6
6to81
Birth to <1
1
2
3to<6
6to
-------
?> Si
;?•
2 a
Table 6-17
. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the
Activity Category, for Males by Age Category (continued)
Specified
Average Ventilation Rate (nrVminute)
Age Group
(years)
16to<21
21to<31
31to<41
41to<51
51 to<61
61 to <71
71 to <81
>81
N
1,241
701
728
753
627
678
496
255
Mean
5.76E-03
5.11E-03
5.57E-03
6.11E-03
6.27E-03
6.54E-03
6.65E-03
6.44E-03
5th
4.17E-03
3.76E-03
3.99E-03
4.65E-03
4.68E-03
5.02E-03
5.26E-03
5.09E-03
10th
4.42E-03
3.99E-03
4.42E-03
4.92E-03
5.06E-03
5.31E-03
5.55E-03
5.37E-03
25th
4.93E-03
4.33E-03
4.86E-03
5.37E-03
5.50E-03
5.85E-03
5.96E-03
5.82E-03
Light Intensity Activities (1.5
Birth to <1
1
2
3 to<6
6to81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
7.94E-03
1.16E-02
1.17E-02
1.14E-02
1.16E-02
1.32E-02
1.34E-02
1.30E-02
1.36E-02
1.44E-02
1.46E-02
1.41E-02
1.39E-02
1.38E-02
4.15E-03
8.66E-03
8.52E-03
9.20E-03
8.95E-03
9.78E-03
l.OOE-02
9.68
1.06E-02
1.12E-02
1.11E-02
1.11E-02
1.12E-02
1.10E-02
5.06E-03
8.99E-03
9.14E-03
9.55E-03
9.33E-03
1.03E-02
1.05E-02
1.02E-02
1.11E-02
1.18E-02
1.16E-02
1.17E-02
1.17E-02
1.17E-02
6.16E-03
9.89E-03
9.96E-03
1.02E-02
1.02E-02
1.13E-02
1.15E-02
1.13E-02
1.20E-02
1.30E-02
1.30E-02
1.27E-02
1.27E-02
1.26E-02
Percentiles
50th
5.60E-03
5.00E-03
5.45E-03
6.02E-03
6.16E-03
6.47E-03
6.59E-03
6.43E-03
< METS <3.0)
7.95E-03
1.14E-02
1.14E-02
1.11E-02
1.13E-02
1.28E-02
1.30E-02
1.24E-02
1.33E-02
1.41E-02
1.44E-02
1.39E-02
1.37E-02
1.38E-02
75*
6.43E-03
5.64E-03
6.17E-03
6.65E-03
6.89E-03
7.12E-03
7.18E-03
7.01E-03
9.57E-03
1.29E-02
1.30E-02
1.23E-02
1.28E-02
1.47E-02
1.50E-02
1.40E-02
1.48E-02
1.56E-02
1.59E-02
1.54E-02
1.50E-02
1.47E-02
90th
7.15E-03
6.42E-03
6.99E-03
7.46E-03
7.60E-03
7.87E-03
7.81E-03
7.57E-03
1.08E-02
1.44E-02
1.47E-02
1.34E-02
1.46E-02
1.64E-02
1.70E-02
1.65E-02
1.65E-02
1.74E-02
1.80E-02
1.69E-02
1.62E-02
1.60E-02
95th
7.76E-03
6.98E-03
7.43E-03
7.77E-03
8.14E-03
8.22E-03
8.26E-03
7.90E-03
1.19E-02
1.58E-02
1.53E-02
1.40E-02
1.56E-02
1.87E-02
1.80E-02
1.77E-02
1.81E-02
1.83E-02
1.94E-02
1.80E-02
1.69E-02
1.67E-02
Maximum
1.35E-02
1.03E-02
l.OOE-02
1.05E-02
1.04E-02
1.09E-02
9.9E-03
9.13E-03
1.55E-02
2.11E-02
1.90E-02
1.97E-02
2.18E-02
2.69E-02
2.91E-02
2.72E-02
2.55E-02
2.30E-02
2.55E-02
2.05E-02
2.00E-02
2.07E-02
s
I
I
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-17
. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the
Activity Category, for Males by Age Category (continued)
Average Ventilation Rate
Age Group
(years)
N
Mean
5th
10th
25th
Moderate Intensity Activities
Birth to 81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
1.45E-02
2.14E-02
2.15E-02
2.10E-02
2.23E-02
2.64E-02
2.90E-02
2.92E-02
3.03E-02
3.16E-02
3.27E-02
2.98E-02
2.93E-02
2.85E-02
7.41E-03
1.45E-02
1.54E-02
1.63E-02
1.64E-02
1.93E-02
2.03E-02
1.97E-02
2.14E-02
2.26E-02
2.24E-02
2.25E-02
2.28E-02
2.25E-02
8.81E-03
1.59E-02
1.67E-02
1.72E-02
1.72E-02
2.05E-02
2.17E-02
2.10E-02
2.27E-02
2.44E-02
2.40E-02
2.40E-02
2.39E-02
2.34E-02
1.15E-02
1.80E-02
1.84E-02
1.87E-02
1.93E-02
2.26E-02
2.45E-02
2.42E-02
2.51E-02
2.72E-02
2.80E-02
2.61E-02
2.61E-02
2.55E-02
Percentiles
50th
(3.0< METS
1.44E-02
2.06E-02
2.08E-02
2.06E-02
2.16E-02
2.54E-02
2.80E-02
2.79E-02
2.91E-02
3.04E-02
3.14E-02
2.92E-02
2.88E-02
2.82E-02
(nrVminute)
75*
<6.0)
1.70E-02
2.41E-02
2.41E-02
2.29E-02
2.50E-02
2.92E-02
3.17E-02
3.30E-02
3.41E-02
3.51E-02
3.70E-02
3.23E-02
3.20E-02
3.10E-02
90th
2.01E-02
2.69E-02
2.69E-02
2.56E-02
2.76E-02
3.38E-02
3.82E-02
3.88E-02
3.96E-02
4.03E-02
4.17E-02
3.69E-02
3.57E-02
3.34E-02
95th
2.25E-02
2.89E-02
2.97E-02
2.71E-02
2.95E-02
3.69E-02
4.21E-02
4.31E-02
4.35E-02
4.50E-02
4.58E-02
4.00E-02
3.73E-02
3.55E-02
Specified
Maximum
3.05E-02
3.99E-02
5.09E-02
3.49E-02
4.34E-02
5.50E-02
6.74E-02
7.17E-02
5.77E-02
6.34E-02
7.05E-02
5.23E-02
4.49E-02
4.11E-02
Q
I
t
§
1=
I
-------
6-17. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the Specified
Activity Category, for Males by Age Category (continued)
Average Ventilation Rate (nrVminute)
Age Group
(years) N
Percentiles
Mean
5th
10th
25th
50th
75*
90th
95th
Maximum
High Intensity (METS >6.0)
Birth to <1
1
2
3to<6
6to
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-18. Descriptive Statistics for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities Within
Specified Activity Category, for Males by Age Category
the
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
Percentiles
N
Mean
5th
10th
25th
Sleep or nap (Activity ID
Birth to 81
Birth to <1
1
2
3to<6
6to
-------
?> Si
;?•
2 a
Table 6-18. Descriptive Statistics
for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities
Activity Category, for Males by Age Category (continued)
Within the Specified
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
16to<21
21to<31
31to<41
41to<51
51 to<61
61 to <71
71 to <81
>81
N
1,241
701
728
753
627
678
496
255
Mean
7.70E-05
6.20E-05
6.60E-05
7.10E-05
7.20E-05
7.60E-05
8.20E-05
8.60E-05
5th
5.50E-05
4.70E-05
4.60E-05
5.40E-05
5.50E-05
6.10E-05
6.70E-05
7.10E-05
10th
6.00E-05
4.90E-05
5.00E-05
5.70E-05
5.80E-05
6.40E-05
7.00E-05
7.50E-05
25th
6.80E-05
5.50E-05
5.70E-05
6.20E-05
6.30E-05
6.90E-05
7.50E-05
8.00E-05
Light Intensity Activities (1.5
Birth to <1
1
2
3 to<6
6to81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
9.88E-04
1.02E-03
8.37E-04
6.33E-04
3.84E-04
2.46E-04
1.79E-04
1.58E-04
1.61E-04
1.66E-04
1.67E-04
1.64E-04
1.71E-04
1.85E-04
7.86E-04
8.36E-04
6.83E-04
4.41E-04
2.67E-04
1.76E-04
1.37E-04
1.24E-04
1.18E-04
1.26E-04
1.27E-04
1.37E-04
1.43E-04
1.52E-04
8.30E-04
8.59E-04
7.16E-04
4.80E-04
2.86E-04
1.87E-04
1.44E-04
1.30E-04
1.28E-04
1.33E-04
1.35E-04
1.41E-04
1.48E-04
1.60E-04
8.97E-04
9.18E-04
7.61E-04
5.44E-04
3.24E-04
2.09E-04
1.56E-04
1.42E-04
1.40E-04
1.47E-04
1.48E-04
1.50E-04
1.58E-04
1.68E-04
Percentiles
50th
7.60E-05
6.10E-05
6.50E-05
7.00E-05
7.10E-05
7.50E-05
8.10E-05
8.60E-05
< METS <3.0)
9.72E-04
1.01E-03
8.26E-04
6.26E-04
3.77E-04
2.38E-04
1.78E-04
1.54E-04
1.57E-04
1.64E-04
1.65E-04
1.63E-04
1.70E-04
1.83E-04
75*
8.50E-05
6.90E-05
7.40E-05
7.80E-05
7.90E-05
8.10E-05
8.80E-05
9.20E-05
1.07E-03
1.10E-03
8.87E-04
7.11E-04
4.37E-04
2.82E-04
1.99E-04
1.71E-04
1.77E-04
1.81E-04
1.83E-04
1.75E-04
1.82E-04
1.98E-04
90th
9.50E-05
7.70E-05
8.20E-05
8.60E-05
8.80E-05
8.90E-05
9.40E-05
9.90E-05
1.17E-03
1.22E-03
9.95E-04
7.94E-04
4.93E-04
3.11E-04
2.18E-04
1.90E-04
1.98E-04
2.00E-04
2.01E-04
1.87E-04
1.95E-04
2.12E-04
95th
1.02E-04
8.20E-05
8.60E-05
9.10E-05
9.20E-05
9.40E-05
9.80E-05
1.06E-04
1.20E-03
1.30E-03
1.03E-03
8.71E-04
5.29E-04
3.32E-04
2.30E-04
2.07E-04
2.09E-04
2.14E-04
2.16E-04
1.95E-04
2.03E-04
2.24E-04
Maximum
1.32E-04
1.18E-04
1.19E-04
1.29E-04
1.35E-04
1.11E-04
1.15E-04
1.15E-04
1.44E-03
1.49E-03
1.18E-03
1.08E-03
7.09E-04
4.42E-04
3.32E-04
2.90E-04
2.81E-04
3.32E-04
2.87E-04
2.69E-04
2.63E-04
2.47E-04
s
I
I
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-18. Descriptive Statistics
for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities
Activity Category, for Males by Age Category (continued)
Within the Specified
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
N
Mean
5th
10th
25th
Moderate Intensity Activities
Birth to 81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
1.80E-03
1.88E-03
1.55E-03
1.17E-03
7.36E-04
4.91E-04
3.87E-04
3.57E-04
3.57E-04
3.66E-04
3.76E-04
3.44E-04
3.60E-04
3.83E-04
1.40E-03
1.41E-03
1.21E-03
8.05E-04
5.03E-04
3.59E-04
2.81E-04
2.43E-04
2.42E-04
2.55E-04
2.59E-04
2.72E-04
2.91E-04
3.12E-04
1.49E-03
1.50E-03
1.28E-03
8.83E-04
5.45E-04
3.75E-04
2.96E-04
2.64E-04
2.65E-04
2.72E-04
2.78E-04
2.84E-04
3.06E-04
3.23E-04
1.62E-03
1.65E-03
1.40E-03
9.99E-04
6.18E-04
4.18E-04
3.34E-04
2.96E-04
3.00E-04
3.10E-04
3.13E-04
3.13E-04
3.28E-04
3.47E-04
Percentiles
50th
(3.0< METS
1.78E-03
1.82E-03
1.54E-03
1.12E-03
7.14E-04
4.73E-04
3.80E-04
3.45E-04
3.44E-04
3.53E-04
3.66E-04
3.42E-04
3.59E-04
3.77E-04
<6.0)
1
2
1
1
8
5
4
4
4
4
4
3
3
4
75*
94E-03
02E-03
66E-03
31E-03
34E-04
52E-04
31E-04
04E-04
OOE-04
08E-04
31E-04
71E-04
88E-04
16E-04
90th
2.18E-03
2.34E-03
1.84E-03
1.56E-03
9.58E-04
6.35E-04
4.86E-04
4.68E-04
4.71E-04
4.69E-04
4.82E-04
3.99E-04
4.18E-04
4.47E-04
95th
2.28E-03
2.53E-03
2.02E-03
1.68E-03
1.04E-03
6.81E-04
5.18E-04
5.09E-04
5.21E-04
5.18E-04
5.49E-04
4.24E-04
4.36E-04
4.70E-04
Maximum
3.01E-03
3.23E-03
2.29E-03
2.10E-03
1.43E-03
1.06E-03
7.11E-04
8.24E-04
7.62E-04
7.16E-04
7.64E-04
5.73E-04
5.49E-04
5.29E-04
Q
I
t
§
1=
I
-------
Table 6-18. Descriptive Statistics for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities Within the Specified
Activity Category, for Males by Age Category (continued)
Average Ventilation Rate (m3/minute-kg)
Age Group
(years) N
Percentiles
Mean
5th
10th
25th
50th
75*
90th
95th
Maximum
High Intensity (METS >6.0)
Birth to <1
1
2
3to<6
6to
-------
I!
l
(% ft
i!
1=
I
XI ft
Table 6-19. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within
the Specified Activity Category, for Females by Age Category
Average Ventilation Rate (m3/minute)
Age Group
(years)
Percentiles
N
Mean
5th
10th
25th
Sleep or nap (Activity ID
Birth to 81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
2.92E-03
4.59E-03
4.56E-03
4.18E-03
4.36E-03
4.81E-03
4.40E-03
3.89E-03
4.00E-03
4.40E-03
4.56E-03
4.47E-03
4.52E-03
4.49E-03
1
3
3
2
2
o
J
2
2
2
o
5
o
5
o
5
o
5
o
5
54E-03
02E-03
OOE-03
90E-03
97E-03
34E-03
78E-03
54E-03
66E-03
OOE-03
12E-03
22E-03
31E-03
17E-03
Sedentary and
Birth to <1
1
2
3to<6
6to
-------
?> Si
;?•
2 a
Table 6-19
. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the
Activity Category, for Females by Age Category (continued)
Specified
Average Ventilation Rate (nrVminute)
Age Group
(years)
16to<21
21to<31
31to<41
41to<51
51 to<61
61 to <71
71 to <81
>81
N
1,182
1,023
869
763
622
700
470
306
Mean
4.76E-03
4.19E-03
4.33E-03
4.75E-03
4.96E-03
4.89E-03
4.95E-03
4.89E-03
5th
3.26E-03
3.04E-03
3.22E-03
3.60E-03
3.78E-03
3.81E-03
4.07E-03
3.93E-03
10th
3.56E-03
3.19E-03
3.45E-03
3.82E-03
4.00E-03
4.02E-03
4.13E-03
4.10E-03
25th
4.03E-03
3.55E-03
3.77E-03
4.18E-03
4.36E-03
4.34E-03
4.41E-03
4.39E-03
Light Intensity Activities (1.5
Birth to <1
1
2
3 to<6
6to
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-19
. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the
Activity Category, for Females by Age Category (continued)
Average Ventilation Rate
Age Group
(years)
>81
N
306
Mean
1.04E-02
5th
8.69E-03
10th
8.84E-03
25th
9.36E-03
Moderate Intensity Activities
Birth to 81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
1.40E-02
2.10E-02
2.13E-02
2.00E-02
2.10E-02
2.36E-02
2.32E-02
2.29E-02
2.27E-02
2.45E-02
2.52E-02
2.14E-02
2.11E-02
2.09E-02
7.91E-03
1.56E-02
1.42E-02
1.53E-02
1.60E-02
1.82E-02
1.66E-02
1.56E-02
1.69E-02
1.76E-02
1.88E-02
1.69E-02
1.69E-02
1.65E-02
9.00E-03
1.63E-02
1.56E-02
1.63E-02
1.68E-02
1.95E-02
1.76E-02
1.67E-02
1.76E-02
1.89E-02
1.98E-02
1.77E-02
1.76E-02
1.75E-02
1.12E-02
1.79E-02
1.82E-02
1.78E-02
1.85E-02
2.08E-02
1.96E-02
1.90E-02
1.95E-02
2.08E-02
2.18E-02
1.92E-02
1.89E-02
1.91E-02
Percentiles
50th
1.03E-02
(3.0< METS
1.35E-02
2.01E-02
2.15E-02
1.98E-02
2.04E-02
2.30E-02
2.24E-02
2.19E-02
2.20E-02
2.39E-02
2.43E-02
2.09E-02
2.07E-02
2.06E-02
(nrVminute)
75*
1.14E-02
<6.0)
1.63E-02
2.35E-02
2.39E-02
2.16E-02
2.30E-02
2.54E-02
2.61E-02
2.60E-02
2.48E-02
2.74E-02
2.81E-02
2.32E-02
2.29E-02
2.25E-02
90th
1.21E-02
1.94E-02
2.71E-02
2.76E-02
2.38E-02
2.61E-02
2.84E-02
3.03E-02
3.00E-02
2.89E-02
3.08E-02
3.19E-02
2.57E-02
2.49E-02
2.46E-02
95th
1.26E-02
2.23E-02
2.93E-02
2.88E-02
2.59E-02
2.81E-02
3.14E-02
3.20E-02
3.28E-02
3.11E-02
3.36E-02
3.50E-02
2.73E-02
2.64E-02
2.60E-02
Specified
Maximum
1.61E-02
4.09E-02
3.45E-02
3.76E-02
3.29E-02
4.31E-02
4.24E-02
5.25E-02
5.42E-02
4.73E-02
5.07E-02
4.62E-02
3.55E-02
3.44E-02
2.93E-02
Q
I
t
§
s
1=
I
-------
f Si
Table 6-19. Descriptive Statistics for Average Ventilation Rate," Unadjusted for Body Weight, While Performing Activities Within the Specified
Activity Category, for Females by Age Category (continued)
Average Ventilation Rate (nrVminute)
Age Group
(years) N
Percentiles
Mean
5th
10th
25th
50th
75*
90th
95th
Maximum
High Intensity (METS >6.0)
Birth to <1
1
2
3to<6
6to
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-20. Descriptive Statistics for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities Within
Specified Activity Category, for Females by Age Category
the
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
Percentiles
N
Mean
5th
10th
25th
Sleep or nap (Activity ID
Birth to <1
1
2
3to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
3.91E-04
4.14E-04
3.42E-04
2.38E-04
1.51E-04
9.00E-05
6.90E-05
5.50E-05
5.60E-05
6.00E-05
6.10E-05
6.10E-05
6.60E-05
7.20E-05
2
3
2
1
8
5
4
o
J
o
J
o
J
o
J
4
4
5
80E-04
15E-04
58E-04
45E-04
90E-05
90E-05
40E-05
50E-05
40E-05
90E-05
90E-05
30E-05
70E-05
10E-05
Sedentary and
Birth to <1
1
2
3to<6
6to
-------
ift
•
a
Table 6-20. Descriptive Statistics
for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities
Activity Category, for Females by Age Category (continued)
Within the Specified
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
16to<21
21to<31
31to<41
41to<51
51 to<61
61 to <71
71 to <81
>81
N
1,182
1,023
869
763
622
700
470
306
Mean
7.50E-05
6.00E-05
6.00E-05
6.50E-05
6.70E-05
6.60E-05
7.20E-05
7.80E-05
5th
5.30E-05
4.30E-05
4.00E-05
4.40E-05
4.60E-05
5.20E-05
5.50E-05
6.30E-05
10th
5.70E-05
4.50E-05
4.20E-05
4.80E-05
5.10E-05
5.40E-05
6.00E-05
6.50E-05
25th
6.30E-05
5.10E-05
5.10E-05
5.50E-05
5.70E-05
5.90E-05
6.50E-05
7.00E-05
Light Intensity Activities (1.5
Birth to <1
1
2
3 to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
9.78E-04
1.05E-03
8.97E-04
6.19E-04
3.82E-04
2.25E-04
1.74E-04
1.49E-04
1.54E-04
1.61E-04
1.61E-04
1.47E-04
1.58E-04
1.67E-04
7.91E-04
8.45E-04
7.30E-04
4.48E-04
2.52E-04
1.63E-04
1.29E-04
1.16E-04
1.07E-04
1.14E-04
1.20E-04
1.17E-04
1.24E-04
1.31E-04
8.17E-04
8.68E-04
7.63E-04
4.84E-04
2.70E-04
1.74E-04
1.38E-04
1.23E-04
1.15E-04
1.23E-04
1.27E-04
1.22E-04
1.30E-04
1.38E-04
8.80E-04
9.49E-04
8.19E-04
5.37E-04
3.15E-04
1.96E-04
1.54E-04
1.34E-04
1.33E-04
1.38E-04
1.41E-04
1.32E-04
1.43E-04
1.50E-04
Percentiles
50th
7.40E-05
5.90E-05
5.90E-05
6.30E-05
6.50E-05
6.60E-05
7.10E-05
7.70E-05
< METS <3.0)
9.62E-04
1.04E-03
8.93E-04
5.99E-04
3.76E-04
2.17E-04
1.73E-04
1.49E-04
1.54E-04
1.58E-04
1.58E-04
1.45E-04
1.56E-04
1.64E-04
75*
8.50E-05
6.70E-05
6.90E-05
7.30E-05
7.60E-05
7.20E-05
7.80E-05
8.60E-05
1.05E-03
1.14E-03
9.64E-04
6.98E-04
4.42E-04
2.49E-04
1.93E-04
1.63E-04
1.76E-04
1.82E-04
1.80E-04
1.61E-04
1.69E-04
1.82E-04
90th
9.60E-05
7.50E-05
7.80E-05
8.30E-05
8.30E-05
7.80E-05
8.80E-05
9.30E-05
1.18E-03
1.25E-03
1.04E-03
7.83E-04
5.03E-04
2.84E-04
2.13E-04
1.78E-04
1.92E-04
2.03E-04
1.99E-04
1.73E-04
1.88E-04
1.97E-04
95th
1.04E-04
8.00E-05
8.30E-05
9.10E-05
9.00E-05
8.40E-05
9.20E-05
9.60E-05
1.23E-03
1.27E-03
1.10E-03
8.28E-04
5.39E-04
3.05E-04
2.24E-04
1.90E-04
2.02E-04
2.16E-04
2.10E-04
1.82E-04
2.02E-04
2.08E-04
Maximum
1.41E-04
9.90E-05
1.05E-04
1.14E-04
1.18E-04
1.04E-04
1.48E-04
1.12E-04
1.65E-03
1.64E-03
1.26E-03
1.02E-03
7.10E-04
3.96E-04
2.86E-04
2.27E-04
2.67E-04
2.83E-04
2.65E-04
2.44E-04
2.77E-04
2.34E-04
s
I
I
-------
I!
l
(% ft
i!
1=
I
ft
Table 6-20. Descriptive Statistics
for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities
Activity Category, for Females by Age Category (continued)
Within the Specified
Average Ventilation Rate (m3/minute-kg)
Age Group
(years)
N
Mean
5th
10th
25th
Moderate Intensity Activities
Birth to <1
1
2
3to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
1.87E-03
1.90E-03
1.60E-03
1.14E-03
7.23E-04
4.41E-04
3.65E-04
3.25E-04
3.16E-04
3.33E-04
3.39E-04
2.92E-04
3.08E-04
3.35E-04
1.47E-03
1.52E-03
1.27E-03
7.92E-04
4.62E-04
3.17E-04
2.67E-04
2.35E-04
2.13E-04
2.21E-04
2.35E-04
2.24E-04
2.40E-04
2.47E-04
1.52E-03
1.62E-03
1.31E-03
8.53E-04
5.12E-04
3.38E-04
2.82E-04
2.45E-04
2.31E-04
2.36E-04
2.54E-04
2.38E-04
2.50E-04
2.66E-04
1.67E-03
1.73E-03
1.44E-03
9.64E-04
5.98E-04
3.80E-04
3.10E-04
2.81E-04
2.68E-04
2.76E-04
2.83E-04
2.59E-04
2.70E-04
2.98E-04
Percentiles
50th
(3.0< METS
1.85E-03
1.87E-03
1.58E-03
1.11E-03
7.15E-04
4.31E-04
3.51E-04
3.16E-04
3.04E-04
3.25E-04
3.26E-04
2.85E-04
2.99E-04
3.33E-04
<6.0)
2
2
1
1
8
4
4
3
3
3
3
3
3
3
75*
01E-03
02E-03
75E-03
31E-03
38E-04
92E-04
07E-04
60E-04
50E-04
76E-04
83E-04
20E-04
40E-04
72E-04
90th
2.25E-03
2.24E-03
1.92E-03
1.45E-03
9.42E-04
5.51E-04
4.63E-04
4.16E-04
4.10E-04
4.41E-04
4.38E-04
3.51E-04
3.75E-04
4.02E-04
95th
2.40E-03
2.37E-03
2.02E-03
1.56E-03
1.01E-03
6.11E-04
4.94E-04
4.52E-04
4.60E-04
4.88E-04
4.86E-04
3.71E-04
4.07E-04
4.20E-04
Maximum
2.83E-03
3.24E-03
2.59E-03
1.93E-03
1.37E-03
9.86E-04
6.50E-04
6.57E-04
7.08E-04
6.20E-04
3.69E-04
5.11E-04
6.77E-04
5.20E-04
Q
I
t
§
1=
I
-------
f Si
Table 6-20. Descriptive Statistics for Average Ventilation Rate," Adjusted for Body Weight, While Performing Activities Within the Specified
Activity Category, for Females by Age Category (continued)
Average Ventilation Rate (m3/minute-kg)
Age Group
(years) N
Percentiles
Mean
5th
10th
25th
50th
75*
90th
95th
Maximum
High Intensity (METS >6.0)
Birth to <1
1
2
3to<6
6to
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing
Activities Within the Specified Activity Category, by Age for Males"
Duration (hours/day) Spent at Activity
Age Group
(years)
Percentiles
N
Mean
5th
10th
25th
50*
75*
90th
95th
Maximum
Sleep or nap (Activity ID = 14500)
Birth to <1
1
2
3to<6
6to81
Birth to <1
1
2
3 to<6
6to81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
13.51
12.61
12.06
11.18
10.18
9.38
8.69
8.36
8.06
7.89
7.96
8.31
8.51
9.24
Sedentary
14.95
14.27
14.62
14.12
13.51
13.85
13.21
12.41
12.31
12.32
13.06
14.49
15.90
16.58
12.63
11.89
11.19
10.57
9.65
8.84
7.91
7.54
7.36
7.15
7.29
7.65
7.80
8.48
12.78
12.15
11.45
10.70
9.75
8.94
8.08
7.70
7.50
7.30
7.51
7.78
8.02
8.64
and Passive Activities
13.82
13.22
13.52
13.01
12.19
12.39
11.39
10.69
10.73
10.56
11.47
12.96
14.22
15.13
14.03
13.33
13.67
13.18
12.45
12.65
11.72
11.06
10.98
11.00
11.86
13.24
14.67
15.45
13.19
12.34
11.80
10.94
9.93
9.15
8.36
8.02
7.77
7.58
7.69
8.01
8.27
8.97
(METS
14.49
13.76
14.11
13.54
12.86
13.06
12.32
11.74
11.61
11.67
12.36
13.76
15.25
15.92
13.53
12.61
12.07
11.18
10.19
9.38
8.67
8.36
8.06
7.88
7.96
8.30
8.53
9.25
<1.5—
14.88
14.25
14.54
14.03
13.30
13.61
13.08
12.39
12.24
12.30
13.03
14.48
15.94
16.64
13.88
12.89
12.39
11.45
10.39
9.61
9.03
8.67
8.36
8.17
8.23
8.6
8.74
9.54
Includes
15.44
14.74
15.11
14.53
13.85
14.30
13.97
13.09
12.98
12.95
13.72
15.16
16.65
17.21
14
13
12
11
10
9.
9.
9.
8.
8.
8.
8.
8.
9.
.24
.13
.65
.63
.59
83
34
03
59
48
48
83
99
74
14.46
13.29
12.75
11.82
10.72
9.95
9.50
9.23
8.76
8.68
8.66
9.01
9.10
9.96
15.03
13.79
13.40
12.39
11.24
10.33
10.44
9.77
9.82
9.38
9.04
9.66
9.89
10.69
Sleep or Nap)
15
15
15
15
14
15
.90
.08
.60
.26
.82
.41
14.83
13
13
13
14
15
17
.75
.63
.67
.38
.72
.11
17.7
16.12
15.38
15.77
15.62
15.94
16.76
15.44
14.16
14.05
13.98
14.76
16.24
17.46
18.06
17.48
16.45
17.28
17.29
19.21
18.79
18.70
15.35
15.58
15.48
15.95
17.50
18.47
18.76
Exposure Factors Handbook Page
September 2011 6-55
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-21
Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the
Specified Activity Category, by Age for Males" (continued)
Duration (hours/day) Spent at Activity
Age Group
(years)
Birth to <1
1
2
3 to<6
6to81
N
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
Mean
5.30
5.52
5.48
6.60
7.62
7.50
7.13
6.09
5.72
6.07
5.64
5.49
4.96
4.86
5th
Light
2.97
2.68
3.06
3.86
5.07
4.48
4.37
3.15
2.80
2.97
3.21
3.50
3.45
3.54
10th
25th
Intensity Activities
3.25
2.89
3.26
4.25
5.57
5.59
4.97
3.50
3.12
3.41
3.44
3.82
3.75
3.71
Moderate Intensity
Birth to <1
1
2
3to<6
6to81
419
308
261
540
940
1,337
1,241
701
728
753
627
678
496
255
3.67
4.04
3.83
3.15
2.66
2.35
3.35
5.24
5.69
5.40
5.00
3.73
2.87
2.35
0.63
0.45
0.59
0.55
0.65
0.88
1.13
1.15
1.26
1.21
1.29
1.62
1.56
1.32
0.97
0.59
0.76
0.75
0.92
1.09
1.42
1.58
1.65
1.55
1.63
1.97
1.83
1.45
3.71
3.37
3.85
5.16
6.63
6.75
6.00
4.20
3.70
3.92
4.03
4.58
4.29
4.17
Percentiles
50*
(1.5< METS
4.52
4.31
4.58
6.20
7.63
7.67
7.02
5.08
4.64
4.82
4.79
5.29
4.81
4.74
75*
<3.0)
7.29
8.23
7.58
8.26
8.72
8.51
8.29
8.49
8.34
8.56
7.59
6.41
5.59
5.39
90th
8.08
9.04
8.83
9.31
9.78
9.19
9.43
9.96
9.87
10.19
8.94
7.40
6.26
6.33
95th
8.50
9.73
9.04
9.70
10.12
9.63
10.03
10.47
10.49
10.79
9.75
7.95
6.59
6.59
Maximum
9.91
10.90
9.92
10.74
11.59
10.91
11.50
12.25
12.10
12.68
12.09
10.23
9.90
7.56
Activities (3.0< METS <6.0)
1.74
1.14
1.23
1.30
1.65
1.66
2.19
2.52
2.84
2.39
2.72
2.81
2.28
1.79
4.20
5.29
4.74
3.80
2.68
2.30
3.45
6.01
6.67
6.46
5.68
3.70
2.86
2.29
5.20
6.06
5.37
4.52
3.57
3.02
4.37
7.15
7.75
7.57
6.75
4.67
3.45
2.85
5.80
6.61
5.82
5.11
4.36
3.62
5.24
7.95
8.45
8.40
7.60
5.45
3.95
3.28
6.21
6.94
6.15
5.32
4.79
3.89
5.59
8.39
8.90
8.85
8.01
6.01
4.31
3.61
7.52
7.68
7.40
6.30
5.95
5.90
6.83
9.94
9.87
10.52
9.94
7.45
5.44
4.37
Page
6-56
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the
Specified Activity Category, by Age for Males" (continued)
Duration (hours/day) Spent at Activity
. „ Percentiles
Age Group
(years) N Mean 5th 10th 25th 50th 75th 90th 95th Maximum
High Intensity (METS >6.0)
Birth to <1 183 0.20 0.00 0.00 0.01 0.14 0.28 0.50 0.59 0.96
1 164 0.31 0.01 0.01 0.03 0.22 0.56 0.78 0.93 1.52
2 162 0.10 0.00 0.01 0.03 0.05 0.14 0.25 0.33 0.48
3to<6 263 0.27 0.02 0.03 0.04 0.13 0.33 0.75 1.16 1.48
6to81 168 0.32 0.02 0.03 0.08 0.25 0.47 0.71 0.88 1.76
a Individual measures are weighted by their 4-year sampling weights as assigned within NHANES
1999-2000 when calculating the statistics in this table. Ventilation rate was estimated using a multiple
linear regression model.
N = Number of individuals.
MET = Metabolic equivalent.
Source: U.S. EPA, 2009.
Exposure Factors Handbook Page
September 2011 6-57
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing
Activities Within the Specified Activity Category, by Age for Females"
Duration (hours/day)
Age Group
(years)
Birth to <1
1
2
3to<6
6to81
Spent at Activity
Percentiles
N
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
Mean
12.99
12.58
12.09
11.13
10.26
9.57
9.08
8.60
8.31
8.32
8.12
8.40
8.58
9.11
Sedentary and
Birth to <1
1
2
3to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
14.07
14.32
14.86
14.27
13.97
14.19
13.58
12.59
12.29
12.22
12.66
14.25
15.38
16.48
5th
Sleep
12.00
11.59
11.45
10.45
9.55
8.82
8.26
7.89
7.54
7.58
7.36
7.67
7.85
8.35
10th
or nap
12.16
11.88
11.68
10.70
9.73
8.97
8.44
7.99
7.70
7.75
7.53
7.88
8.01
8.53
25th
(Activity
12.53
12.29
11.86
10.92
10.01
9.27
8.74
8.26
7.98
7.99
7.81
8.15
8.26
8.84
Passive Activities (METS
12.86
13.02
13.81
12.88
12.49
12.38
11.80
10.97
10.91
10.78
11.08
12.89
13.66
14.87
13.05
13.25
13.95
13.15
12.74
12.76
12.17
11.29
11.14
11.08
11.40
13.16
14.20
15.09
13.53
13.73
14.44
13.56
13.22
13.34
12.79
11.88
11.61
11.56
12.08
13.68
14.76
15.80
50*
75*
90th
95th
Maximum
ID = 14500)
12.96
12.63
12.08
11.12
10.27
9.55
9.08
8.59
8.28
8.31
8.11
8.40
8.55
9.10
13.44
12.96
12.34
11.38
10.54
9.87
9.39
8.90
8.59
8.63
8.43
8.68
8.89
9.34
<1.5 — Includes
14.08
14.31
14.81
14.23
13.82
14.05
13.52
12.60
12.24
12.18
12.64
14.22
15.41
16.59
14.54
14.88
15.32
14.82
14.50
14.82
14.29
13.21
12.91
12.82
13.30
14.86
16.05
17.15
13.82
13.16
12.57
11.58
10.74
10.17
9.79
9.20
8.92
8.93
8.73
8.93
9.19
9.73
14.07
13.31
12.66
11.75
10.91
10.31
10.02
9.38
9.17
9.13
8.85
9.09
9.46
10.04
14.82
14.55
13.48
12.23
11.43
11.52
11.11
10.35
10.22
10.02
9.29
9.80
10.34
10.55
Sleep or Nap)
15.08
15.36
15.78
15.43
15.34
15.87
15.08
13.75
13.50
13.40
13.89
15.38
16.62
17.71
15.49
15.80
16.03
15.85
16.36
16.81
15.67
14.19
13.90
13.79
14.12
15.69
16.94
18.07
16.14
16.40
16.91
17.96
18.68
19.27
16.96
16.24
15.18
15.17
15.80
17.14
17.90
19.13
Page
6-58
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the
Specified Activity Category, by Age for Females" (continued)
Duration (hours/day) Spent at Activity
Age Group
(years)
Percentiles
N
Mean
5*
10*
25*
50*
75*
90th
95th
Maximum
Light Intensity Activities (1.5< METS <3.0)
Birth to <1
1
2
3 to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
6.00
5.61
5.78
6.25
7.27
7.55
6.98
6.42
6.51
6.56
6.52
6.23
5.96
5.3
3.49
2.83
3.20
3.78
4.63
4.89
4.60
3.66
4.06
3.99
4.09
4.40
4.22
3.67
3.70
2.94
3.54
4.10
5.46
5.62
5.08
4.09
4.33
4.30
4.42
4.74
4.51
3.96
Moderate Intensity
Birth to <1
1
2
3 to<6
6to81
415
245
255
543
894
1,451
1,182
1,023
869
763
622
700
470
306
3.91
4.02
3.27
3.35
2.57
2.01
3.26
4.80
5.00
5.05
4.58
3.31
2.48
2.06
0.53
0.52
0.50
0.70
0.65
0.89
1.27
1.62
1.71
1.75
1.71
1.65
1.19
1.01
0.74
0.73
0.78
0.89
0.95
1.08
1.48
1.94
2.06
2.00
2.13
1.97
1.36
1.25
4.26
3.46
4.29
4.79
6.33
6.75
5.91
4.84
5.06
4.97
5.19
5.47
5.24
4.63
Activities
1.10
1.08
1.22
1.61
1.82
1.45
2.21
2.78
3.09
2.97
3.10
2.56
1.82
1.55
5.01
4.39
5.33
5.84
7.17
7.67
6.85
5.82
5.98
5.90
6.05
6.23
5.92
5.16
(3.0<
4.87
5.14
4.01
3.88
2.66
1.96
3.39
5.37
5.41
5.48
4.79
3.34
2.48
1.99
8.43
8.28
7.48
7.86
8.34
8.55
7.96
8.18
8.14
8.40
7.95
6.96
6.63
6.00
9.31
9.03
8.46
8.84
9.42
9.27
9.16
9.56
9.46
9.75
9.12
7.67
7.46
6.70
9.77
9.39
8.74
9.38
9.79
9.57
9.57
10.14
9.93
10.18
9.43
8.17
7.91
7.01
10.53
10
9
10
11
.57
93
.32
.06
10.85
12
12
13
11
11
11
9
8.
.29
.11
.12
.83
.58
.13
43
78
METS <6.0)
5.77
6.10
4.88
4.71
3.41
2.51
4.24
6.42
6.60
6.66
5.98
4.01
2.99
2.51
6.27
7.00
5.35
5.29
3.95
3.03
4.74
7.19
7.31
7.50
6.89
4.61
3.64
3.07
6.54
7.37
5.57
5.65
4.32
3.28
5.07
7.52
7.58
7.97
7.14
5.01
4.01
3.44
7
8
6
7
6
4
6
9
9
68
07
93
58
10
96
68
21
59
10.16
8
6
5
4
97
90
63
68
Exposure Factors Handbook
September 2011
Page
6-59
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the
Specified Activity Category, by Age for Females" (continued)
Duration (hours/day) Spent at Activity
Age Group
(years)
Birth to <1
1
2
3 to<6
6to81
Percentiles
N
79
55
130
347
707
1,170
887
796
687
515
424
465
304
188
Mean
0.17
0.22
0.15
0.19
0.24
0.30
0.24
0.26
0.25
0.26
0.34
0.32
0.29
0.26
5*
High
0.03
0.03
0.00
0.01
0.02
0.03
0.01
0.03
0.03
0.03
0.03
0.03
0.03
0.02
10*
25*
50*
75*
90th
95th
Maximum
Intensity (METS >6.0)
0.05
0.05
0.01
0.02
0.03
0.04
0.03
0.05
0.05
0.04
0.04
0.04
0.05
0.03
0.09
0.09
0.03
0.05
0.06
0.08
0.08
0.10
0.09
0.09
0.12
0.10
0.10
0.09
0.14
0.18
0.08
0.10
0.12
0.19
0.18
0.19
0.19
0.20
0.28
0.23
0.25
0.21
0.21
0.35
0.16
0.22
0.26
0.40
0.34
0.36
0.33
0.36
0.50
0.46
0.43
0.38
0.33
0.40
0.48
0.46
0.67
0.66
0.51
0.56
0.52
0.55
0.74
0.68
0.60
0.59
0.40
0.43
0.65
0.73
0.98
0.96
0.60
0.67
0.72
0.68
0.85
0.89
0.71
0.71
0
0
1
1
1
3
1
1
1
1
1
1
1
1
58
48
01
43
71
16
61
40
40
49
58
77
24
23
a Individual measures are weighted by their 4-year sampling weights as assigned within NHANES
1999-2000 when calculating the statistics in this table. Ventilation rate was estimated using a multiple
linear regression model.
N = Number of individuals.
MET = Metabolic equivalent.
Source: U.S. EPA,
2009.
Page Exposure Factors Handbook
6-60 September 2011
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-23. Mean Inhalation Rate Values (m3/day) from Key Studies for Males and Females Combined
Age Group3
U.S. EPA(2009)b
Nc
Mean
Birth to <1
month
1 to <3 months
3 to <6 months
6 to <12 months
Birth
to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to
16 to
21 to
31 to
41 to
51 to
61 to
71 to
<16 years
<21 years
<3 1 years
<41 years
<5 1 years
<61 years
<71 years
<81 years
>81 years
a
b
c
d
834
553
516
1,083
1,834
2,788
2,423
1,724
1,597
1,516
1,249
1,378
966
561
8.64
13.41
12.99
12.40
12.93
14.34
15.44
16.30
17.40
18.55
18.56
15.43
14.25
12.97
Brochu et al. Arcus-Arth and
(2006a)b Blaisdell (2007)b
TV
85
85
103
188
101
61
61
199
117
117
219
100
91
91
186
95
95
Mean
3.31
3.31
4.06
3.72
4.90
7.28
7.28
9.98
14.29
14.29
14.59
14.99
13.74
13.74
12.57
11.46
11.46
TV
182
182
294
544
1,020
934
989
4,107
1,553
975
495
-
-
-
-
-
-
Mean
3.63
3.63
4.92
6.78
5.70
8.77
9.76
11.22
13.42
16.98
18.29
-
-
-
-
-
-
Combined Key
Stifelman (2007)c Studies'1
TV Mean
TV
182
267
379
647
3.4
4.9
5.7
9.3
11.5
15.0
17.0
16.3
15.6
15.6
14.7
14.7
-
2
1
1
5
3
3
3
1
1
1
1
1
1
,042
,588
,566
,251
,586
,880
,035
,943
,697
,607
,340
,564
,061
656
Mean
3.63
3.47
4.11
5.42
5.36
7.99
8.93
10.05
11.96
15.17
16.25
15.74
16.00
15.96
15.66
14.23
12.86
12.21
When age groupings in the original reference did not match the U.S. EPA groupings used for this
handbook, means from all age groupings in the original reference that overlapped U.S. EPA's age
groupings by more than 1 year were averaged, weighted by the number of observations contributed from
each age group. See Table 6-25 for concordance with U.S. EPA age groupings.
Weighted (where possible) average of reported study means.
The total number of subjects for Stifelman (2007) was 3,007.
Unweighted average of means from key studies.
Exposure Factors Handbook
September 2011
Page
6-61
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-24. 95th Percentile Inhalation Rate Values (m3/day) from
Males and Females Combined
Key Studies for
U.S. EPA Brochuetal. Arcus-Arth and Combined Key
Age Group3 (2009)b (2006a)b Blaisdell (2007)b Stifelman (2007)c Studies'1
If 95th N 95th N 95th N
Birth to <1 month -b 182 7.10
1 to <3 months - - 85 4.44 182 7.10
3 to <6 months - - 85 4.44 294 7.72
6 to <12 months - - 103 5.28 544 10.81
Birth to <1 year 834 12.67 188 4.90 1,020 9.95
1 to <2 years 553 18.22 101 6.43 934 13.79
2 to <3 years 516 17.04 61 9.27 989 14.81
3 to <6 years 1,083 15.17 61 9.27 4,107 17.09
6to81 years 561 16.10 95 15.30
95th N 95th
182 7.10
267 5.77
379 6.08
647 8.04
2,042 9.17
1,588 12.81
1,566 13.71
5,251 13.84
3,586 16.59
3,880 21.93
3,035 24.63
1,943 21.29
1,697 21.35
1,607 21.16
1,340 21.33
1,564 18.07
1,061 16.59
656 15.70
a When age groupings in the original reference did not match the U.S. EPA groupings used for this
handbook, 95th percentiles from all age groupings in the original reference that overlapped U.S. EPA's
age groupings by more than 1 year were averaged, weighted by the number of observations contributed
from each age group. See Table 6-25 for concordance with U.S. EPA age groupings.
b Weighted (where possible) average of reported study 95th percentiles.
The total number of subjects for Stifelman (2007) was 3,007.
d Unweighted average of 95th percentiles from key studies.
Page
6-62
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September 2011
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Exposure Factors Handbook
Chapter 6 — Inhalation Rates
Table 6-25. Concordance of Age Groupings Among Key Studies
Age Group8
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to<31 years
31 to<41 years
41 to<51 years
51 to<61 years
61 to <71 years
71 to<81 years
>81 years
U.S. EPA (2009)
—
—
—
—
—
Birth to <1 year
—
1 to <2 years
2 to <3 years
3 to <6 years
—
—
6 to <11 years
—
—
—
—
11 to <16 years
—
—
—
—
16 to <21 years
—
—
—
21 to<31 years
—
31 to<41 years
41 to <51 years
51 to<61 years
61 to <71 years
—
71 to<81 years
>81 years
Brochu (2006a)
—
0.22 to <0.5 year
0.22 to <0.5 year
0.5 to
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-26. Time Weighted Average of Daily Inhalation Rates (DIRs) Estimated from
Daily Activities"
Inhalation Rate (m3/hour)
Subject Resting Light Activity (m3/day)
Adult Man 0.45 1.2 22.8
Adult Woman 0.36 1.14 21.1
Child (10 years) 0.29 0.78 14.8
Infant (1 year) 0.09 0.25 3.76
Newborn 0.03 0.09 0.78
Assumptions made were based on 8 hr resting and 16 hr light activity for adults and children (10 years);
14 hr resting and 10 hr light activity for infants (1 year); 23 hr resting and 1 hr light activity for
newborns.
1 K
DIR=~yiR.t.
rp ^_f ' '
1 1=1
DIR = Daily Inhalation Rate,
IRi = Corresponding inhalation rate at 1th activity,
/,• = Hours spent during the 1th activity,
k = Number of activity periods, and
T = Total time of the exposure period (i.e., a day).
Source: ICRP, 1981.
Page Exposure Factors Handbook
6-64 September 2011
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II
il
I
Table 6-27. Selected Inhalation Rate Values During Different Activity Levels Obtained from Various Literature Sources
Subject
Adolescent
Male, 14-1 6 years
Male, 14-1 5 years
Female, 14-16 years
Female, 14-15 years; 164.9 cm L
Children
10 year; 140 cm L
Males, 10-11 years
Males, 10-11 years; 140.6 cmL
Females, 4-6 years
Females, 4-6 years; 111.6 cm L
Infant, 1 year
Newborn
20 hours- 13 weeks
9.6 hours
6.6 days
Adult
Man
1.7m2SA
30 years; 170 cmL
20-33 years
Woman
30 years; 160 cmL
20-25 years; 165. 8 cmL
Pregnant (8th month)
Calculated from V* =/x VT.
b Crying.
BW = body weights.
f = frequency (breaths/minute)
VT = tidal volume (mL).
V* = minute volume (L/minute).
cm L = length/height.
Source: ICRP, 1981.
BW(kg)
59.4
56
36.5
32.5
20.8
18.4
2.5
2.5-5.3
3.6
3.7
68.5
70.4
54
60.3
f
16
15
16
30
34
25
29
12
12
15
12
15
16
Resting Light Activity Heavy Work
VT V* f VT V* f VT V*
330 5.2
300 4.5
300 4.8 24 600 14
48 1.4a
15 0.5
21 0.5
21 0.6
750 7.4 17 1,670 29 21 2,030 43
500 6
500 7.5 16 1,250 20
340 4.5 19 860 16 30 880 25
400 6 20 940 19
650 10
Maximal Work
During Exercise
f VT V*
53 2,520 113
52 1,870 88
58 1,330 71
61 1,050 61
70 600 40
66 520 34
68b 51a'b 3.5b
40 3,050 111
46 2,100 90
Q
I
t
§
s
ri
1=
I
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-28. Summary of Human Inhalation Rates by Activity Level (m3/hour)a
Resting"
Lightd
Moderate6
Heavyf
Child, 6 years
Child, 10 years
Adult male
Adult female
Average adult
8
10
454
595
1,049
0.4
0.4
0.7
0.3
0.5
16
40
102
786
888
0.8
1.0
0.8
0.5
0.6
4
29
102
106
208
2.0
3.2
2.5
1.6
2.1
5
43
267
211
478
2.3
3.9
4.8
2.9
3.9
a Values of inhalation rates for children (male and female) presented in this table represent the mean of
values reported for each activity level in 1985.
b Number of observations at each activity level.
0 Includes watching television, reading, and sleeping.
d Includes most domestic work, attending to personal needs and care, hobbies, and conducting minor indoor
repairs and home improvements.
e Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs.
f Includes vigorous physical exercise and climbing stairs carrying a load.
Source: Adapted from U.S. EPA, 1985.
Table 6-29. Estimated Minute Ventilation Associated with Activity Level for
Average Male Adult"
Level of work L/minute
Light 13
Light 19
Light 25
Moderate 30
Moderate 35
Moderate 40
Heavy 55
Heavy 63
Very heavy 72
Very heavy 85
Severe 100+
a Average adult assumed
Representative activities
Level walking at 2 mph; washing clothes
Level walking at 3 mph; bowling; scrubbing floors
Dancing; pushing wheelbarrow with 15-kg load; simple construction; stacking
firewood
Easy cycling; pushing wheelbarrow with 75-kg load; using
Climbing stairs; playing tennis; digging with spade
Cycling at 13 mph; walking on snow; digging trenches
Cross-country skiing; rock climbing; stair climbing
with load; playing squash or handball; chopping
with axe
Level running at 10 mph; competitive cycling
Competitive long distance running; cross-country skiing
to weigh 70 kg.
sledgehammer
Source: Adapted from U.S. EPA, 1985.
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-30. Activity Pattern Data Aggregated for Three Microenvironments by
Activity Level for All Age Groups
Microenvironment
Indoors
Outdoors
In Transportation
Vehicle
Source: Adapted from U
Activity Level
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
S. EPA, 1985.
Average Hours Per Day in Each
Microenvironment at Each
Activity Level
9.82
9.82
0.71
0.10
20.4
0.51
0.51
0.65
0.12
1.77
0.86
0.86
0.05
0.0012
1.77
Table 6-31. Summary of Daily Inhalation Rates (DIRs) Grouped by Age and Activity Level
Daily Inhalation Rate (m3/day)a
Subject Resting Light Moderate Heavy
Child, 6 years 4.47 8.95 2.82 0.50
Child, lOyears 4.47 11.19 4.51 0.85
Adult Male 7.83 8.95 3.53 1.05
Adult Female 3.35 5.59 2.26 0.64
AdultAverage 5.60 6.71 2.96 0.85
a Daily inhalation rate was calculated using the following equation:
IR=±YlRt.
rp /_ , 1
1 i=\
IRt = Inhalation rate at r* activity,
tt = Hours spent per day during r* activity,
k = Number of activity periods, and
T = Total time of the exposure period (e.g., a day).
b Total daily inhalation rate was calculated by summing the specific activity (resting,
heavy) and dividing them by the total amount of time spent on all activities.
Source: Generated using the data from U.S. EPA, 1985 as shown in Tables 6-28 and 6-30.
Total Daily IRb
(m /day)
16.74
21.02
21.4
11.8
16
light, moderate,
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-32. Distribution Pattern
of Predicted Ventilation Rate (VR) and Equivalent Ventilation Rate (EVR)
for 20 Outdoor Workers
VR (m3/hour)a
Self-Reported
Activity Level TV0
Sleep
Slow
Medium
Fast
18,597
41,745
3,898
572
Arithmetic
Mean ± SD
0.42
0.71
0.84
2.63
±0.16
±0.4
±0.47
±2.16
Geometric
Mean ± SD
0.39 ±
0.65 ±
0.76 ±
1.87 ±
0.08
0.09
0.09
0.14
EVRb (m3/hour/m2 body surface)
Arithmetic
Mean ± SD
0.23 ±
0.38 ±
0.48 ±
1.42±
0.08
0.20
0.24
1.20
Geometric
Mean ± SD
0.22
0.35
0.44
1.00
±0.08
±0.09
±0.09
±0.14
Percentile Rankings, VR
Sleep
Slow
Medium
Fast
0
0
0
0
1
18
30
36
42
5
0.18
0.36
0.42
0.54
0
0
0
0
10
.24
.36
.48
.60
50
0.36
0.66
0.72
1.74
90
0.66
1.08
1.32
5.70
95
0.72
1.32
1.68
6.84
99
0.90
1.98
2.64
9.18
99.9
1
4
3
20
38
84
10.26
Percentile Rankings, EVR
Sleep
Slow
Medium
Fast
a
b
c
Source:
1
0.12
0.18
0.18
0
24
5
0.12
0.18
0.24
0.30
0
0
0
0
10
.12
.24
.30
.36
50
0.24
0.36
0.42
0.90
90
0.36
0.54
0.72
3.24
95
0.36
0.66
0.90
3.72
Data presented by Shamoo et al. (1991) in L/minute were converted to m3/hour.
EVR = VR per square meter of body surface area.
Number of minutes with valid appearing heart rate records and corresponding daily
rate.
Shamoo etal., 1991
99
0.48
1.08
1.38
4.86
99.9
0
2
2
5
60
40
28
52
records of breathing
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September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-33. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers
Location Activity Type3
Self-reported
Activity Level
% of Time
Inhalation rate
(m3/hour)b
±SD
%ofAvg.c
Indoor Essential
Sleep
Slow
Medium
Fast
28.7
29.5
2.4
0
0.42 ±0.12
0.72 ±0.36
0.72 ±0.30
0
69 ±15
106 ± 43
129 ±38
0
Indoor
Outdoor
Non-essential
Essential
Slow
Medium
Fast
Slow
Medium
Fast
20.4
0.9
0.2
11.3
1.8
0
0.66 ±0.36
0.78 ±0.30
1.86 ±0.96
0.78 ±0.36
0.84 ±0.54
0
98 ±36
120 ± 50
278 ±124
117 ±42
130 ±56
0
Outdoor
Non-essential
Slow
Medium
Fast
3.2
0.8
0.7
0.90 ±0.66
1.26 ±0.60
2.82 ±2.28
136 ± 90
213 ±91
362 ± 275
a Essential activities include income-related work, household chores, child care, study and other school
activities, personal care, and destination-oriented travel; Non-essential activities include sports and active
leisure, passive leisure, some travel, and social or civic activities.
b Data presented by Shamoo et al. (1991) in L/min were converted to mVhour.
0 Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall
average.
Source: Adapted from Shamoo et al., 1991.
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September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-34. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels
Panel
Panel 1: Healthy Outdoor
Workers — 15 female, 5 male,
age 19-50
Panel 2: Healthy Elementary
School Students — 5 male,
12 female, ages 10-12
Panel 3: Healthy High School
Students — 7 male, 12 female,
ages 13-17
Panel 4: Adult Asthmatics,
clinically mild, moderate, and
severe — 15 male, 34 female,
age 18-50
Panel 5: Adult Asthmatics from
2 neighborhoods of contrasting O3
air quality — 10 male, 14 female,
age 19-46
Panel 6: Young Asthmatics —
7 male, 6 female, ages 11-16
Panel 7: Construction Workers —
7 male, age 26-34
Calibration Protocol
Laboratory treadmill exercise
tests, indoor hallway walking tests
at different self-chosen speeds,
2 outdoor tests consisted of
1-hour cycles each of rest,
walking, and jogging.
Outdoor exercises each consisted
of 20 minute rest, slow walking,
jogging and fast walking.
Outdoor exercises each consisted
of 20 minute rest, slow walking,
jogging and fast walking.
Treadmill and hallway exercise
tests.
Treadmill and hallway exercise
tests.
Laboratory exercise tests on
bicycles and treadmills.
Performed similar exercises as
Panel 2 and 3, and also performed
job-related tests including lifting
and carrying a 9-kg pipe.
Field Protocol
3 days in 1 typical summer week
(included most active workday and
most active day off); HR
recordings and activity diary
during waking hours.
Saturday, Sunday and Monday
(school day) in early autumn; heart
rate recordings and activity diary
during waking hours and during
sleep.
Same as Panel 2, however, no heart
rate recordings during sleep for
most subjects.
1 typical summer week, 1 typical
winter week; hourly activity /health
diary during waking hours; lung
function tests 3 times daily; HR
recordings during waking hours on
at least 3 days (including most
active work day and day off).
Similar to Panel 4, personal NO2
and acid exposure monitoring
included. (Panels 4 and 5 were
studied in different years, and had
10 subjects in common).
Summer monitoring for
2 successive weeks, including
2 controlled exposure studies with
few or no observable respiratory
effects.
HR recordings and diary
information during 1 typical
summer work day.
Source: Linnetal., 1992.
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-35. Subject Panel Inhalation Rates by Mean Ventilation Rate (VR), Upper Percentiles, and
Self-Estimated Breathing Rates
Inhalation Rates (m3/hour)
Panel Number
and Description
MeanVR
99th Percentile
VR
Mean VR at Activity Levels
Slow Medium
Fast
Healthy
1—Adults 20 0.78
2—Elementary School Students 17 0.90
3—High School Students 19 0.84
7—Construction Workers' 7 1.50
Asthmatics
4—Adults 49 1.02
5—Adultsd 24 1.20
6—Elementary and High School 13 1.20
Students
2.46
1.98
2.22
4.26
1.92
2.40
2.40
0.72
0.84
0.78
1.26
1.02
1.20
1.20
1.02
0.96
1.14
1.50
1.68
2.04
1.20
3.06
1.14
1.62
1.68
2.46
4.02
1.50
VR
Number of individuals in each survey panel.
Some subjects did not report medium and/or fast activity. Group means were calculated from individual
means (i.e., give equal weight to each individual who recorded any time at the indicated activity level).
Construction workers recorded only on 1 day, mostly during work, while others recorded on >1 work or
school day and >1 day off.
Excluding subjects also in Panel 4.
= Ventilation rate.
Source: Linnetal., 1992.
Table 6-36. Actual Inhalation Rates Measured at Four Ventilation Levels
Subject
Mean Inhalation Rate" (m3/hour)
Location
Low
Medium
Heavy
Very Heavy
All Indoor (treadmill post) 1.23
subjects Outdoor 0.88
Total 0.93
1.83
1.96
1.92
3.13
2.93
3.01
4.13
4.90
4.80
a Original data were presented in L/minute. Conversion to m3/hour was obtained as follows:
L/minute x 0.001 m3/L x 60 minute/hour = m3/hour
Source: Adapted from Shamoo et al., 1992.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-37. Distribution of Predicted
Inhalation Rates by Location
High School Students
and Activity Levels
for Elementary
and
Inhalation Rates (m3/hour)
Ag
a
b
c
d
e
SD
e (years) Student Location
10-12 ELC Indoors
(Nd = 17)
Outdoors
13-17 HSC Indoors
(Nd = 19)
Outdoors
Activity
Level
slow
medium
fast
slow
medium
fast
slow
medium
fast
slow
medium
fast
% Recorded
Time3 N
49.6
23.6
2.4
8.9
11.2
4.3
70.7
10.9
1.4
8.2
7.4
1.4
Recorded time averaged about 23 hours per elementary
student over 72-hour periods.
Geometric means closely approximated 50th percentiles
HR, 1.5-1.8 for VR.
Elementary school student (EL) or high school student
Number of students that participated in survey.
Highest single value.
= Standard deviation.
0
0
1
0
1
1
0
0
1
0
1
1
Percentile Rankingsb
lean±SD
.84 ±0.36
.96 ±0.36
.02 ± 0.60
.96 ±0.54
.08 ±0.48
.14 ±0.60
.78 ±0.36
.96 ±0.42
.26 ± 0.66
.96 ±0.48
.26 ±0.78
.44 ±1.08
0
0
0
0
0
0
0
0
0
0
0
0
1st
.18
.24
.24
.36
.24
.48
.30
.42
.54
.42
.48
.48
50th
0.78
0.84
0.84
0
0
0
0
0
1
78
96
96
72
84
08
0.90
1.08
1.02
99.9th
2
2
3
4
3
3
3
4
6
5
5
5
school student and 33 hours per high school
; geometric standard deviations were 1.2-1.3
(HS).
.34
.58
.42
.32
.36
.60
.24
.02
84e
.28
.70
.94
for
Source: Spier et al., 1992.
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-38. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and
High School Students
Students
Elementary school,
ages 10 to 12 years
(N= 17)
High school,
ages 13 to 17 years
(N= 19)
Location
Indoors
Outdoors
Indoors
Outdoors
TV = Number of students that participated
Source: Spier et al., 1992.
Slow
16.3
2.2
19.5
1.2
in survey.
Activity Level _ . , _. „
J Tntal Timp Sp^nt
Medium Fast (hours/day)
2.9 0.4 19.6
1.7 0.5 4.4
1.5 0.2 21.2
1.3 0.2 2.7
Table 6-39. Distribution Patterns of Daily Inhalation Rates (DIRs) for Elementary (EL) and High School (HS)
Students Grouped by Activity Level
Ape Mean TRb
Students (years) Location Activity Type3 (nrVday)
EL(TV° =
EL
HS(TV =
HS
a
b
c
Source:
17) 10 to 12 Indoor Light 13.7
Moderate 2.8
Heavy 0.4
Outdoor Light 2.1
Moderate 1.84
Heavy 0.57
19) 13 to 17 Indoor Light 15.2
Moderate 1.4
Heavy 0.25
Outdoor Light 1.15
Moderate 1.64
Heavy 0.29
For this report, activity type presented in Tables 6-37 and 6-3
moderate activity for medium, and heavy activity for fast.
Daily inhalation rate was calculated by multiplying the hours
the corresponding inhalation rate (see Table 6-37).
Number of elementary (EL) and high school students (HS).
Percentile Rankings
1st
2.93
0.70
0.10
0.79
0.41
0.24
5.85
0.63
0.11
0.5
0.62
0.10
50th
12.71
2.44
0.34
1.72
1.63
0.48
14.04
1.26
0.22
1.08
1.40
0.20
8 was redefined as light activity
spent at each activity
level (see
99.9th
38.14
7.48
1.37
9.5
5.71
1.80
63.18
6.03
1.37
6.34
7.41
1.19
for slow,
Table 6-38) by
Adapted from Spier et al., 1992 (Generated using data from Tables 6-37 and 6-38).
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-40. Mean Minute Inhalation Rate (m /minute) by Group and Activity for Laboratory Protocols
Activity
Young Children3
Children3
Adult Females3 Adult Males3 Adults (combined)3
Lying
Sitting
Standing
Walking
1.5 mph
1.875 mph
2.0 mph
2.25 mph
2.5 mph
3.0 mph
3.3 mph
4.0 mph
Running
6.19E-03
6.48E-03
6.76E-03
1.03E-02
1.05E-02
DNP
1.17E-02
DNP
DNP
DNP
DNP
7.51E-03
7.28E-03
8.49E-03
DNPb
DNP
1.41E-02
DNP
1.56E-02
1.78E-02
DNP
DNP
7.12E-03
7.72E-03
8.36E-03
DNP
DNP
DNP
DNP
2.03E-02
2.42E-02
DNP
DNP
8.93E-03
9.30E-03
10.65E-03
DNP
DNP
DNP
DNP
2.41E-02
DNP
2.79E-02
3.65E-02
8.03E-03
8.51E-03
9.51E-03
DNP
DNP
DNP
DNP
2.22E-02
DNP
DNP
DNP
3.5 mph
4.0 mph
4.5 mph
5.0 mph
6.0 mph
DNP
DNP
DNP
DNP
DNP
2.68E-02
3.12E-02
3.72E-02
DNP
DNP
DNP
4.60E-02b
4.79E-02b
5.08E-02b
DNP
DNP
DNP
5.73E-02
5.85E-02
6.57E-02b
DNP
DNP
5.26E-02
5.47E-02
DNP
Young children, male and female 3-5.9 year olds; children, male and female 6-12.9 year olds; adult females,
adolescent, young to middle-aged, and older adult females; adult males, adolescent, young to middle-aged,
and older adult males. DNP, group did not perform this protocol or TV was too small for appropriate mean
comparisons.
Older adults not included in the mean value since they did not perform running protocol at particular speeds.
Source: Adams, 1993.
Table 6-41. Mean Minute Inhalation Rate (m3/minute) by Group and Activity for Field Protocols
Activity
Young Children3
Children3
Adult Females3
Adult Males3
Adults (combined)a
Play
Car Driving
Car Riding
Yardwork
Housework
Car Maintenance
Mowing
Woodworking
1.13E-02
DNP
DNP
DNP
DNP
DNP
DNP
DNP
1.79E-02
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
8.95E-03
8.19E-03
1.92E-02b
1.74E-02
DNP
DNP
DNP
DNP
1.08E-02
9.83E-03
2.61E-02c/3.19E-02d
DNP
2.32E-02e
3.66E-02b
2.44E-02b
DNP
9.87E-03
9.01E-03
2.27E-02c/2.56E-02d
DNP
DNP
DNP
DNP
Source:
Young children, male and female 3-5.9 year olds; children, male and female 6-12.9 year olds; adult females, adolescent,
young to middle-aged, and older adult females; adult males, adolescent, young to middle-aged, and older adult males;
DNP, group did not perform this protocol or jV was too small for appropriate mean comparisons.
Adolescents not included in mean value since they did not perform this activity.
Mean value for young to middle-aged adults only.
Mean value for older adults only.
Older adults not included in the mean value since they did not perform this activity.
Adams, 1993.
Page
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September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-42. Summary of Average Inhalation Rates (m /hour) by Age Group and Activity Levels for
Laboratory Protocols
Activity Level
Age Group
Resting3 Sedentary1
Light0
Moderate
Heavy6
Young Children 0.37
(3-5.9 years)
Average inhalation rate (m3/hour)
(N = 12, sex not specified)
Children 0.45
(6-12.9 years)
Average inhalation rate (m3/hour)
(N = 40, 20 male and 20 female)
Adults (females) 0.43
(Adolescent, young to middle aged, and
older adult females)
(TV =37)
Adults (males) 0.54
(Adolescent, young to middle aged, and
older adult males)
(TV =39)
Adults (combined) 0.49
(TV =76)
0.40
0.47
0.48
0.60
0.54
0.65
0.95
1.33
1.45
1.38
DNP
1.74
2.76
1.93
2.35
DNP
2.23
2.96g
3.30
a Resting defined as lying (see Table 6-40 for original data).
b Sedentary defined as sitting and standing (see Table 6-40 for original data).
0 Light defined as walking at speed level 1.5-3.0 mph (see Table 6-40 for original data).
d Moderate defined as fast walking (3.3-4.0 mph) and slow running (3.5-4.0 mph) (see Table 6-40 for original
data).
e Heavy defined as fast running (4.5-6.0 mph) (see Table 6-40 for original data).
f Group did not perform (DNP) this protocol or TV was too small for appropriate mean comparisons. All young
children did not run.
8 Older adults not included in mean value since they did not perform running protocols at particular speeds.
Source: Adapted from Adams, 1993.
Exposure Factors Handbook
September 2011
Page
6-75
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-43. Summary of Average Inhalation Rates (m3/hour) by Age Group And Activity Levels in
Field Protocols
Sedentary Light
b
Age Group Activity3 Activity Moderate Activity
Young Children (3 to 5.9 years) DNP DNPd 0.68
Average inhalation rate (m3/hour)
(N = 12, sex not specified)
Children (6 to 12.9 years) DNP DNP 1.07
Average inhalation rate (m3/hour)
(N = 40, 20 male and 20 female)
Adults (females) 0.51 1.10e DNP
(Adolescent, young to middle aged, and older adult females)
(TV =37)
Adults (males) 0.62 1.40 1.78f
(Adolescent, young to middle aged, and older adult males)
(N=39)
Adults (combined) 0.57 1.25 DNP
(N=16)
a Sedentary activity was defined as car driving and riding (both sexes) (see Table 6-41 for original data).
b Light activity was defined as car maintenance (males), housework (females), and yard work (females) (see
Table 6-41 for original data).
0 Moderate activity was defined as mowing (males); wood working (males); yard work (males); and play
(children) (see Table 6-41 for original data).
d DNP. Group did not perform this protocol or TV was too small for appropriate mean comparisons.
e Older adults not included in mean value since they did not perform this activity.
f Adolescents not included in mean value since they did not perform this activity.
TV = Number of individuals.
Source: Adams, 1993.
Page Exposure Factors Handbook
6-76 September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table
Cohor
(yea
6-44. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes
(EFDs) for Individuals Sampled in the 1977-1978 NFCS
I-/A op Body Weight
rs) (kg)
BMRa
MJ/dayb
Kcal/dayc
MJ/day
EFD
Kcal/day
Ratio
EFDd/BMR
Males and Females
<1
1 to 2
3 to 5
6 to 8
7.6
13
18
26
1.74
3.08
3.69
4.41
416
734
881
1,053
3.32
5.07
6.14
7.43
793
1,209
1,466
1,774
1.90
1.65
1.66
1.68
Males
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
36
50
66
74
79
82
80
76
71
5.42
6.45
7.64
7.56
7.87
7.59
7.49
6.18
5.94
1,293
1,540
1,823
1,804
1,879
1,811
1,788
1,476
1,417
8.55
9.54
10.8
10.0
10.1
9.51
9.04
8.02
7.82
2,040
2,276
2,568
2,395
2,418
2,270
2,158
1,913
1,866
1.58
1.48
1.41
1.33
1.29
1.25
1.21
1.30
1.32
Females
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
a
b
c
d
Source:
36
49
56
59
62
66
67
66
62
4.91
5.64
6.03
5.69
5.88
5.78
5.82
5.26
5.11
1,173
1,347
1,440
1,359
1,403
1,380
1,388
1,256
1,220
Calculated from the appropriate age and sex-based BMR equations
MJ/day = megajoules/day.
Kcal/day = kilocalories/day.
Food-energy intake (Kcal/day) or (MJ/day).
Layton, 1993.
7.75
7.72
7.32
6.71
6.72
6.34
6.40
5.99
5.94
1,849
1,842
1,748
1,601
1,603
1,514
1,528
1,430
1,417
1.58
1.37
1.21
1.18
1.14
1.10
1.10
1.14
1.16
given in Table 6-46.
Exposure Factors Handbook Page
September 2011 6-77
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-45. Daily Inhalation Rates (DIRs) Calculated from Food-Energy Intakes (EFDs)
MET8 Value
Inhalation Rates
Cohort/Age (years)
Daily Inhalation Rate0 Sleep
(m3/day) (hours)
Inactive'
(m3/day)
Active'
(mVday)
Males and Females
Ito2
3 to 5
6 to 8
4.5
6.8
8.3
10
11
11
10
10
1.9
1.6
1.7
1.7
2.7
2.2
2.2
2.2
2.35
4.16
4.98
5.95
6.35
9.15
10.96
13.09
Males
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Lifetime average8
3
3
4
4
11
16
14
10
1
14
15
17
16
16
15
15
13
11
14
1.9
1.8
1.7
1.6
1.5
1.5
1.4
1.6
1.6
2.5
2.2
2.1
1.9
1.8
1.8
1.7
1.8
1.9
7.32
8.71
10.31
10.21
10.62
10.25
10.11
8.34
8.02
18.3
19.16
21.65
19.4
19.12
18.45
17.19
15.01
15.24
Females
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Lifetime average8
3
3
4
4
11
16
14
10
1
13
12
12
11
11
10
10
9.7
9A
10
1.9
1.6
1.5
1.4
1.4
1.3
1.3
1.4
1.4
2.5
2.0
1.7
1.6
1.6
1.5
1.5
1.5
1.6
6.63
7.61
8.14
7.68
7.94
7.80
7.86
7.10
6.90
16.58
15.22
13.84
12.29
12.7
11.7
11.8
10.65
11.04
MET = Metabolic equivalent.
L is the number of years for each age cohort.
Daily inhalation rate was calculated by multiplying the EFD values (see Table 6-44) by H x VQ x (m3 1,000 L"1) for subjects under
9 years of age and by 1.2 x ff x VQ x (m3 1,000 L"1) (for subjects 9 years of age and older (see text for explanation).
where:
EFD
H
VQ
= (Kcal/day) or (MJ/day),
= Oxygen uptake = 0.05 L O2/KJ or 0.21 L O2/Kcal, and
= Ventilation equivalent = 27 = geometric mean of VQs (unitless).
For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (see Table 6-44) by the
factor 1.2 (see text for explanation).
F= (24A- S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated BMR (unitless).
where:
S
= Number of hours spent sleeping each day (hours).
Inhalation rate for inactive periods was calculated as BMR x H x VQ x (d 1,440 minute ) and for active periods by multiplying
inactive inactive inhalation rate by F (See footnote e); BMR values are from Table 6-44.
where:
BMR
= Basal metabolic rate (MJ/day) or (kg/hour).
Lifetime average was calculated by multiplying individual inhalation rate by corresponding L values summing the products across
cohorts and dividing the result by 75, the total of the cohort age spans.
Source: Layton, 1993.
Page
6-78
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-46. Statistics of the Age/Sex Cohorts
BMR
Sr*"
OCA,
Age (years) MJ cT1 SD
Males
Under 3 1.51 0.92
3to<10 4.14 0.50
10to<18 5.86 1.17
18to<30 6.87 0.84
30 to <60 6.75 0.87
>60 5.59 0.93
Females
Under 3 1.54 0.92
3to<10 3.85 0.49
10to<18 5.04 0.78
18to<30 5.33 0.72
30to<60 5.62 0.63
>60 4.85 0.61
Body weight (BW) in kg .
SD = Standard deviation.
CV = Coefficient of variation (SD/mean).
jV = Number of observations.
r = Coefficient of correlation.
Source: Layton, 1993.
Used to Develop Regression Equations for Predicting Basal Metabolic Rates
(BMR)
CV
0.61
0.12
0.20
0.12
0.13
0.17
0.59
0.13
0.15
0.14
0.11
0.12
Body Weigh!
(kg)
6.6
21
42
63
64
62
6.9
21
38
53
61
56
N
162
338
734
2,879
646
50
137
413
575
829
372
38
BMR Equation3
0.249 BW- 0.127
0.095 BW + 2.110
0.074 BW + 2.754
0.063 BW + 2.896
0.048 BW+ 3.653
0.049 BW + 2.459
0.244 BW- 0.130
0.085 BW + 2.033
0.056 BW + 2.898
0.062 BW + 2.036
0.034 BW+ 3.538
0.038 BW + 2.755
r
0.95
0.83
0.93
0.65
0.60
0.71
0.96
0.81
0.80
0.73
0.68
0.68
Table 6-47. Daily Inhalation Rates (DIRs) Obtained from the Ratios of Total Energy
Expenditure to Basal Metabolic Rate (BMR)
Sex/Age
(years)
Body Weight*
(kg)
BMRb
(MJ/day)
VQ
A
H
(m3O2/MJ)
Inhalation Rate, VE
(m3/day)d
Males
0.5to<3
3to<10
10to<18
18to<30
30 to <60
>60
14
23
53
76
80
75
3.4
4.3
6.7
7.7
7.5
6.1
27
27
27
27
27
27
1.6
1.6
1.7
1.59
1.59
1.59
0.05
0.05
0.05
0.05
0.05
0.05
7.3
9.3
15
17
16
13
Females
0.5to<3
3to<10
10to<18
18to<30
30 to <60
>60
11
23
50
62
68
67
2.6
4.0
5.7
5.9
5.8
5.3
27
27
27
27
27
27
1.6
1.6
1.5
1.38
1.38
1.38
0.05
0.05
0.05
0.05
0.05
0.05
5.6
8.6
12
11
11
9.9
Body weight was based on the average weights for age/sex cohorts in the U.S. population.
The BMRs are calculated using the respective body weights and BMR equations (see Table 6-46).
The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis et al. (1989)
study: male = 1.59, female = 1.38. For males and females under 10 years old, the mean BMR multiplier used was 1.6.
For males and females aged 10 to <18 years, the mean values for/4 given in Table 6-45 for 12-14 years and 15-18
years, age brackets for males and females were used: male =1.7 and female =1.5.
Inhalation rate = BMR x A x H x VQ, VQ = ventilation equivalent and H = oxygen uptake.
Source: Layton, 1993.
Exposure Factors Handbook
September 2011
Page
6-79
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§
s
CP a
ij§ a
Table 6-48. Daily Inhalation Rates (DIRs) Based on Time-Activity Survey
Age (years)
and Activity MET
20-34
Sleep 1
Light 1.5
Moderate 4
Hard 6
Very Hard 10
Totals
35-49
Sleep 1
Light \.5
Moderate 4
Hard 6
Very Hard 10
Totals
50-64
Sleep 1
Light \.5
Moderate 4
Hard 6
Very Hard 10
Totals
65-74
Sleep 1
Light 1.5
Moderate 4
Hard 6
Very Hard 10
Totals
Males
Body Weight* BMRb Duration0 Ed VEe VEf
(kg) (KJ/hour) (hour/day) (MJ/day) (nrVday) (nrVhour)
76 320 7.2 2.3 3.1 0.4
76 320 14.5 7.0 9.4 0.7
76 320 1.2 1.5 2.1 1.7
76 320 0.64 1.2 1.7 2.6
76 320 0.23 0.74 1.0 4.3
24 17 17
81 314 7.1 2.2 3.0 0.4
81 314 14.6 6.9 9.3 0.6
81 314 1.4 1.8 2.4 1.7
81 314 0.59 1.1 1.5 2.5
81 314 0.29 0.91 1.2 4.2
24 13 17
80 312 7.3 2.3 3.1 0.4
80 312 14.9 7.0 9.4 0.6
80 312 1.1 1.4 1.9 1.7
80 312 0.50 0.94 1.3 2.5
80 312 0.14 0.44 0.6 4.2
24 12 16
75 256 7.3 1.9 2.5 0.3
75 256 14.9 5.7 7.7 0.5
75 256 1.1 1.1 1.5 1.4
75 256 0.5 0.8 1.0 2.1
75 256 0.14 0.36 0.48 3.5
24 9.8 13
Females
Body Weight* BMRb Duration0 Ed VEe VEf
(kg) (KJ/hour) (hour/day) (MJ/day) (nrVday) (nrVhour
62 283 7.2 2.0 2.8 0.4
62 283 14.5 6.2 8.3 0.6
62 283 1.2 1.4 1.8 1.5
62 283 0.64 1.1 1.5 2.3
62 283 0.23 0.65 0.88 3.8
24 11 15
67 242 7.1 1.7 2.3 0.3
67 242 14.6 5.3 7.2 0.5
67 242 1.4 1.4 1.8 1.3
67 242 0.59 0.9 1.2 2.0
67 242 0.29 0.70 0.95 3.2
24 9.9 13
68 244 7.3 1.8 2.4 0.3
68 244 14.9 5.4 7.4 0.5
68 244 1.1 1.1 1.4 1.3
68 244 0.5 0.7 1.0 2.0
68 244 0.14 0.34 0.46 3.3
24 9.4 13
67 221 7.3 1.6 2.2 0.3
67 221 14.9 4.9 6.7 0.4
67 221 1.1 1.0 1.3 1.2
67 221 0.5 0.7 0.9 1.8
67 221 0.14 0.31 0.42 3.0
24 8.5 11
a Body weights were obtained from Najjar and Rowland (1 987).
b The BMRs for the age/sex cohorts were calculated using the respective body weights and the BMR equations (see Table 6-46).
0 Duration of activities were obtained from Sallis et al. (1985).
d Energy expenditure rate (K) was calculated by multiplying BMR (KJ/hour) x (MJ/1,000 KJ) x duration (hour/day) x MET.
e E (inhalation rate) was calculated by multiplying E (MJ/day) by H (0.05 m3 oxygen/MJ) by VQ (27).
f E (nrVhour) was calculated by multiplying BMR (KJ/hour) x (MJ/1,000 KJ) x MET x H (0.05 m3 oxygen/MJ) x VQ (27).
Source: Layton, 1993.
V
\
>
Chapter 6 - Inhalation Rates
I
§
ri
s
I
-------
Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-49. Inhalation Rates for Short-Term Exposures
Activity Type
Rest
Sedentary
Light
Moderate
Heavy
MET (BMR Multiplier)
Body
Sex/A.ge Weight
RMRb
1
(years) (kg)a (MJ/day)
Males
0.5 to
<3 14
3 to <10 23
10 to
18 to
30 to
>60
<18 53
<30 76
<60 80
75
3.40
4.30
6.70
7.70
7.50
6.10
3
4
6
7
7
5
.2E-03
.OE-03
.3E-03
.2E-03
.OE-03
.7E-03
1.2
2C
4d
10e
Inhalation Rate (nrVminute/'8
3.8E-03
4.8E-03
7.5E-03
8.7E-03
8.3E-03
6.8E-03
6.3E-03
8.2E-03
1.3E-02
1.4E-02
1.4E-02
1.1E-02
1.3E-02
1
2
2
2
2
6E-02
5E-02
9E-02
8E-02
3E-02
6
7
7
5
h
h
.3E-02
.2E-02
.OE-02
.7E-02
Females
0.5 to
<3 11
3 to <10 23
a
b
c
d
e
f
g
10 to
18 to
30 to
>60
<18 50
<30 62
<60 68
67
2.60
4.00
5.70
5.90
5.80
5.30
2
3
5
5
5
5
.4E-03
.8E-03
.3E-03
.5E-03
.3E-03
.OE-03
2.8E-03
4.5E-03
6.3E-03
6.7E-03
6.5E-03
6.0E-03
Body weights were based on average weights for age/sex cohorts
The BMRs for the age/sex cohorts were
equations (see Table 6-46).
Range = 1.5-2.5.
Range = 3-5.
Range = >5-20.
4.8E-03
7.5E-03
1.1E-02
1.1E-02
1.1E-02
9.8E-03
of the U.S.
calculated using the respective body
The inhalation rate was calculated as IR =
(day/1,440 minutes).
Original data were presented
in L/minute
BMR (MJ/day) *H(0.
05 L/KJ) x
1
1
2
2
2
OE-02
5E-02
1E-02
2E-02
2E-02
2.0E-02
5
5
5
5
h
h
3E-02
5E-02
4E-02
OE-02
population.
weights and the
MET
x VQ (27)
Conversion to nrYminute was obtained as follows
BMR
X
m
L
1000L nan
h
The maximum possible MET sustainable
for more
than 5 minutes does not reach 10 for females and males
until ages 13 and 12, respectively. Therefore, an MET of 10 is not possible for this age categ
Source:
Layton, 1993.
ory.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-50. Distributions of Individual and Group Inhalation/Ventilation Rate (VR) for Outdoor Workers
VR (m3/hour)
Percentile
Population Group and Subgroup3
All Subjects (N*= 19)
Job
GCWc/Laborers(jV=5)
IronWorkers (jV= 3)
Carpenters (7V= 11)
Site
Medical Office Site (N= 7)
Hospital Site (N= 12)
Mean ± SD
1.68 ±0.72
1.44 ±0.66
1.62 ±0.66
1.86 ±0.78
1.38 ±0.66
1.86 ±0.78
1st
0.66
0.48
0.60
0.78
0.60
0.72
50th
1.62
1.32
1.56
1.74
1.20
1.80
99th
3.90
3.66
3.24
4.14
3.72
3.96
a Each group or subgroup mean was calculated from individual means, not from pooled data.
b N= number of individuals performing specific jobs or number of individuals at survey sites.
0 GCW = general construction worker.
Source: Linnetal, 1993.
Table 6-51. Individual Mean Inhalation Rate (m3/hour) by Self-Estimated Breathing Rate or Job Activity
Category for Outdoor Workers
Self-Estimated
Breathing Rate (m3/hour)
Population Group and Subgroup
All Subjects (N= 19)
Job
GCWb/Laborers(Af=5)
IronWorkers (N = 3)
Carpenters (N= 11)
Site
Office Site (N= 12)
Hospital Site (N= 12)
Slow
1.44
1.20
1.38
1.62
1.14
1.62
Trade = "Working at Trade" (i.e., tasks
b GCW = general construction worker.
Source: Linnetal., 1993.
Medium
1.86
1.56
1.86
2.04
1.44
2.16
specific to
Fast
2.04
1.68
2.10
2.28
1.62
2.40
Job Activity Category (m3/hour)
Sit/Stand Walk Carry Trade3
1.56
1.26
1.62
1.62
1.14
1.80
the individual's job
1.80 2.10 1.92
1.44 1.74 1.56
1.74 1.98 1.92
1.92 2.28 2.04
1.38 1.68 1.44
2.04 2.34 2.16
classification).
Page
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
Table 6-52. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 618 Infants
and Children Grouped in Classes of Age
Inhalation Rate
Waking
Age (months)
<2
2to<6
6 to <12
12 to <18
18 to <24
24 to <30
30 to 36
N
104
106
126
77
65
79
61
Mean ± SD
48.0 ±9.1
44.1 ±9.9
39.1 ±8.5
34.5 ±5.8
32.0 ±4.8
30.0 ±6.2
27.1 ±4.1
Median
47
42
38
34
32
30
28
(breaths/minute)
Sleeping
Mean ± SD
39.8 ±8.7
33.4 ±7.0
29.6 ±7.0
27.2 ±5.6
25.3 ±4.6
23.1 ±4.6
21.5 ±3.7
Median
39
32
28
26
24
23
21
SD = Standard deviation.
TV = Number of individuals.
Source: Rusconi et
al, 1994.
Exposure Factors Handbook
September 2011
Page
6-83
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Table 6-53. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/day) Percentiles for Free-Living Underweij
During Pregnancy and Postpartum Weeks
Age Group Progression of the
(years) Reproductive Cycle
11 to <23
23 to <30
30 to 55
a
b
c
SD
Source:
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Number of
Subjects'1
NExp or
NSim
50
5,000
5,000
5,000
5,000
5,000
5,000
17
5,000
5,000
5,000
5,000
5,000
5,000
14
5,000
5,000
5,000
5,000
5,000
5,000
Physiological
Mean ± SD
12.18 ±2.08
12.27 ± 1.95
17.83 ±4.52
17.98 ± 4.77
18.68 ±4. 73
20.39 ±2.69
20.21 ±2.66
13.93 ±2.27
13.91 ±2.17
20.03 ±5.01
20.15 ±4.24
20.91 ± 5.37
22.45 ±2.91
22.25 ±2. 89
12.89 ± 1.40
12.91 ± 1.36
18.68 ±3.95
18.84 ±4.08
19.60 ±4.66
21.19± 1.96
21.01 ± 1.94
5th
8.76
9.35
13.20
13.19
13.44
16.31
16.17
10.20
11.41
15.83
15.81
15.97
18.70
18.53
10.58
10.85
15.33
15.30
15.54
18.30
18.14
10th
9.52
9.74
13.91
13.95
14.25
17.02
16.88
11.02
11.50
16.17
16.16
16.37
19.15
18.98
11.09
11.28
15.93
15.93
16.14
18.86
18.69
25th
10.78
10.79
15.40
15.47
15.96
18.47
18.31
12.40
12.08
17.08
17.07
17.56
20.14
19.96
11.94
11.99
16.79
16.80
17.03
19.79
19.62
;hta Adolescents and Women Aged 11 to 55 Years
Daily Inhalation Rates' (mVday)
Percentile
50th
12.18
12.18
17.34
17.46
17.88
20.31
20.14
13.93
13.92
19.75
19.80
20.29
22.23
22.04
12.89
12.49
18.05
18.07
18.73
20.92
20.74
75th
13.58
13.72
19.55
19.73
20.24
22.22
22.02
13.93
15.32
21.60
21.67
22.31
24.15
23.94
12.89
13.98
20.22
20.23
20.74
22.58
22.39
90th
14.84
14.63
21.38
22.09
23.01
23.79
23.58
16.83
16.01
23.76
24.49
26.42
25.65
25.42
14.69
14.99
21.39
21.52
23.04
23.98
23.77
95th
15.60
15.48
23.13
23.90
25.59
24.82
24.61
17.65
17.81
26.94
27.46
28.95
27.68
27.44
15.20
15.13
22.69
23.20
25.58
24.53
24.31
99th
17.02
16.90
27.40
30.69
34.45
26.62
26.39
19.20
19.97
34.21
32.69
38.26
30.57
30.30
16.16
15.18
27.38
30.80
34.26
25.28
25.07
Underweight females are defined as those having a body mass index lower than 19.8 kg/m2 in pre-pregnancy.
NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
Resulting total energy requirements (TDERs) from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and
lactation by Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER *H x (VE/VO2) x 10"3. TDER = total energy
requirement (ECG + TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy.
= Standard deviation.
Brochu et al., 2006b.
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Table 6-54. Distribution of Physiological Daily Inhalation Rate (PDIR) (nvVday) Percentiles for Free-Living Normal-Weight" Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks
Age Group Progression of the
(years) Reproductive Cycle
11 to <23
23 to <30
30 to 55
a
b
c
SD
Source:
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22nd week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Number of
Subjects'1
NExp or
NSim
57
5,000
5,000
5,000
5,000
5,000
5,000
54
5,000
5,000
5,000
5,000
5,000
5,000
61
5,000
5,000
5,000
5,000
5,000
5,000
Physiological Daily Inhalation Rates' (m3/day)
Percentile
Mean ± SD
14.55 ±2.70
14.55 ±2.69
19.99 ±3.89
22.59 ±4.83
23.27 ±4.63
23.28 ±3.60
23.08 ±3.56
13. 59 ±2.23
13.66 ±2.29
19.00 ±9.98
21.36 ±4.36
22. 14 ±4. 13
22.15 ±30.5
21.96 ±3.02
13.82 ± 1.91
13.79 ± 1.83
19.02 ±3.81
21. 53 ±4.06
22.20 ±3.68
22.31 ±2. 50
22. 12 ±2.48
5th
10.11
9.71
13.32
15.35
16.01
16.91
16.76
9.92
10.19
13.92
15.54
16.21
17.37
17.22
10.67
11.07
15.18
16.71
17.45
18.72
18.55
10th
11.09
10.83
14.84
17.09
17.76
18.36
18.20
10.73
10.64
14.55
16.70
17.34
18.26
18.10
11.37
11.48
15.74
17.56
18.19
19.35
19.18
25th
12.73
13.29
18.32
20.06
20.69
21.40
21.21
12.09
12.12
16.55
18.63
19.35
20.11
19.93
12.53
12.54
17.14
19.01
19.69
20.58
20.40
50th
14.55
14.78
20.26
22.27
23.10
23.56
23.36
13.59
13.73
18.76
20.89
21.69
22.11
21.91
13.82
13.61
18.63
20.85
21.73
22.09
21.90
75th
16.37
15.89
21.86
24.69
25.55
25.24
25.02
15.09
14.90
20.49
23.58
24.55
23.96
23.75
15.12
14.91
20.46
23.45
24.16
23.84
23.64
90th
18.01
17.34
23.86
28.25
28.77
27.17
26.93
16.45
16.49
22.80
26.59
27.59
26.21
25.98
16.28
16.40
22.45
26.03
26.78
25.70
25.47
95th
18.99
18.71
25.89
30.75
31.07
28.98
28.73
17.26
17.87
24.49
28.43
29.27
27.53
27.29
16.97
17.02
23.38
28.30
28.53
26.70
26.47
Normal- weight females are defined as those having a body mass index varying between 19.8 and 26 kg/m2 in pre-pregnancy.
NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
Resulting TDERs from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and lactation by
simulations were converted into physiological daily inhalation rates by the following equation: TDER x H x (VEfVO2) x 10"3. TDER = total energy requirement (ECG +
ECG = stored daily energy cost for growth; TDEE = total daily energy.
= Standard deviation.
Brochu et al., 2006b.
99th
20.83
20.91
28.75
35.88
35.65
31.80
31.52
18.78
19.09
27.04
33.98
32.77
29.21
28.96
18.28
18.32
27.39
33.44
32.75
28.39
28.14
Monte Carlo
TDEE).
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Table 6-55. Distribution of Physiological Daily Inhalation Rate (PDIR) (m'/day) Percentiles for Free-Living Overweight/Obese" Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks
Age Group Progression of the
(years) Reproductive Cycle
11 to <23
23 to <30
30 to 55
a
b
SD
Source:
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22nd week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Number
Subject
NExp o
NSim
15
5,000
5,000
5,000
5,000
5,000
5,000
25
5,000
5,000
5,000
5,000
5,000
5,000
64
5,000
5,000
5,000
5,000
5,000
5,000
"f
b
r
Mean ± SD
16.62 ±2.91
16.64 ±2.81
25. 51 ±6.48
26. 10 ±6.96
25.71 ± 8.09
25.93 ± 3.70
25.71 ±3.67
15.45 ±2.32
15.47 ±2.27
23.93 ± 5.94
24.44 ±6.24
24.15 ±6.82
24.47 ±3.04
24.25 ± 3.02
15. 87 ±2.52
15.83 ±2.46
24.47 ±5.68
25.02 ±6.65
24.46 ± 6.24
24.91 ±3.28
24.70 ± 3.25
Physiological Daily Inhalation
Rates' (m3/day)
Percentile
5th
11.82
10.21
16.11
16.38
15.67
17.94
17.79
11.63
11.94
17.75
18.06
17.60
19.31
19.14
11.72
11.92
17.87
18.13
17.67
19.82
19.65
10th
12.88
12.13
19.09
19.29
18.78
20.12
19.94
12.47
13.12
19.13
19.45
19.00
21.07
20.88
12.63
12.79
19.17
19.41
18.83
20.92
20.74
25th
14.65
15.52
23.04
23.12
22.73
24.52
24.30
13.88
14.36
21.08
21.32
20.91
22.80
22.60
14.17
14.30
21.38
21.44
20.92
22.82
22.63
50th
16.62
17.22
25.38
25.65
25.23
26.61
26.38
15.45
15.50
23.22
23.51
23.05
24.45
24.23
15.87
15.79
23.77
23.92
23.40
24.91
24.69
75th
18.58
18.52
27.85
28.17
27.84
28.38
28.13
17.02
16.86
25.62
26.44
26.02
26.16
25.93
17.57
17.19
26.37
26.93
26.37
26.81
26.58
90th
20.35
19.68
30.62
31.56
31.14
29.87
29.61
18.43
17.96
29.09
29.92
30.04
27.93
27.68
19.10
18.78
29.77
30.98
30.32
28.70
28.45
95th
21.41
20.06
33.32
34.93
34.95
30.53
30.26
19.27
19.46
31.77
33.49
34.18
29.43
29.17
20.01
19.47
33.08
35.01
34.27
29.75
29.50
Overweight/obese females are defined as those having a body mass index higher than 26 kg/m2 in pre-pregnancy.
NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
Resulting TDERs from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and lactation by
simulations were converted into physiological daily inhalation rates by the following equation: TDER x H x (VE/VO2) x 10"3. TDER = total energy requirement (ECG +
ECG = stored daily energy cost for growth; TDEE = total daily energy.
= Standard deviation.
Brochu et al., 2006b.
99th
23.39
20.16
41.61
45.94
46.76
31.27
31.00
20.86
20.41
40.74
44.56
47.31
31.08
30.81
21.73
22.03
41.49
46.88
45.08
32.94
32.65
Monte Carlo
TDEE).
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Exposure Factors Handbook Page
September 2011 6-87
Table 6-56. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Underweight" Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks
Physiological Daily Inhalation Rates' (m3/kg-day)
Subjects'1 Percentile
Age Group nv^icooivn vi me NExp or
(years) Reproductive Cycle NSim Mean±SD 5th 10th 25th 50th 75th 90th 95th 99th
llto<23 Non-pregnant females 50 0.277± 0.046 0.201 0.218 0.246 0.277 0.277 0.335 0.352 0.383
Pre-pregnancy 0 week 5,000 0.276 ±0.045 0.209 0.218 0.238 0.277 0.313 0.337 0.345 0.368
Pregnancy 9th week 5,000 0.385 ±0.110 0.278 0.291 0.327 0.377 0.428 0.474 0.504 0.622
Pregnancy 22nd week 5,000 0.343 ± 0.093 0.246 0.259 0.291 0.335 0.378 0.419 0.455 0.602
Pregnancy 36th week 5,000 0.323 ± 0.083 0.230 0.243 0.274 0.314 0.357 0.404 0.452 0.575
Postpartum 6th week 5,000 0.368 ±0.058 0.321 0.337 0.370 0.414 0.467 0.517 0.548 0.596
Postpartum 27th week 5,000 0.383 ±0.064 0.329 0.348 0.383 0.433 0.491 0.549 0.584 0.647
23to<30 Non-pregnant females 17 0.264 ±0.047 0.186 0.203 0.232 0.264 0.264 0.325 0.342 0.374
Pre-pregnancy 0 week 5,000 0.264 ±0.046 0.206 0.212 0.228 0.257 0.284 0.342 0.361 0.362
Pregnancy 9th week 5,000 0.366 ± 0.098 0.277 0.287 0.311 0.351 0.400 0.468 0.501 0.591
Pregnancy 22ntlweek 5,000 0.332 ± 0.076 0.250 0.260 0.282 0.318 0.362 0.421 0.452 0.532
Pregnancy 36th week 5,000 0.3 17 ±0.086 0.233 0.242 0.266 0.301 0.346 0.402 0.439 0.582
Postpartum 6th week 5,000 0.352 ±0.056 0.307 0.320 0.348 0.385 0.431 0.486 0.518 0.573
Postpartum 27thweek 5,000 0.364±0.061 0.316 0.330 0.357 0.397 0.449 0.508 0.545 0.606
30to55 Non-pregnant females 14 0.249±0.027 0.204 0.214 0.231 0.249 0.249 0.283 0.293 0.312
Pre-pregnancy 0 week 5,000 0.249 ±0.026 0.208 0.220 0.232 0.242 0.268 0.286 0.294 0.299
Pregnancy g^week 5,000 0.347±0.075 0.279 0.291 0.311 0.337 0.370 0.405 0.431 0.529
Pregnancy 22nd week 5,000 0.315 ±0.071 0.252 0.262 0.280 0.305 0.335 0.368 0.401 0.529
Pregnancy 36th week 5,000 0.301 ±0.074 0.233 0.243 0.260 0.287 0.321 0.360 0.404 0.529
Postpartum 6th week 5,000 0.337 ±0.038 0.312 0.326 0.347 0.376 0.408 0.439 0.457 0.489
Postpartum 27th week 5,000 0.349 ± 0.042 0.320 0.333 0.357 0.389 0.425 0.462 0.483 0.518
a Underweight females are defined as those having a body mass index lower than 19.8 kg/m in pre-pregnancy.
b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
c Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by
Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER x H x (V^/YC > 2) x 10" . TDER = total energy requirement
(ECG + TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure.
SD = Standard deviation.
Source: Brochu et al., 2006b.
Exposure Factors Handbook
Chapter 6 — Inhalation Rates
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Table 6-57. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Normal-Weight3 and Women Aged 11
During Pregnancy and Postpartum Weeks
Number of
Subjects'1
Age Group Progression of the NExp or
(years) Reproductive Cycle NSim
11 to <23
23 to <30
30 to 55
b
c
SD
Source:
Non-pregnant females 1 5
Pre-pregnancy 0 week 5,000
Pregnancy 9th week 5,000
Pregnancy 22nd week 5,000
Pregnancy 36th week 5,000
Postpartum 6th week 5,000
Postpartum 27th week 5,000
Non-pregnant females 54
Pre-pregnancy 0 week 5,000
Pregnancy 9th week 5,000
Pregnancy 22ntl week 5,000
Pregnancy 36th week 5,000
Postpartum 6th week 5,000
Postpartum 27th week 5,000
Non-pregnant females 6 1
Pre-pregnancy 0 week 5,000
Pregnancy 9th week 5,000
Pregnancy 22nd week 5,000
Pregnancy 36th week 5,000
Postpartum 6th week 5,000
Postpartum 27th week 5,000
Mean ± SD
0.252 ±0.051
0.252 ±0.051
0.344 ±0.074
0.360 ±0.085
0.329 ±0.072
0.342 ±0.062
0.352 ±0.067
0.221 ±0.035
0.222 ±0.035
0.308 ±0.189
0.321 ±0.067
0.297 ±0.056
0.309 ±0.045
0.317 ±0.049
0.229 ±0.035
0.229 ±0.035
0.314 ±0.069
0.330 ±0.069
0.303 ±0.057
0.316 ±0.046
0.325 ±0.050
Physiological Daily Inhalation Rates
to 55 Years
c (m3/kg-day)
Percentile
5th 10th
0.168 0.186
0.169 0.189
0.232 0.259
0.243 0.268
0.225 0.247
0.272 0.292
0.279 0.298
0.164 0.176
0.174 0.181
0.233 0.243
0.239 0.252
0.220 0.233
0.265 0.278
0.269 0.283
0.171 0.184
0.174 0.187
0.237 0.252
0.242 0.257
0.225 0.238
0.267 0.280
0.272 0.285
25th
0.217
0.218
0.297
0.304
0.281
0.327
0.334
0.197
0.199
0.269
0.277
0.258
0.302
0.309
0.206
0.202
0.276
0.285
0.264
0.307
0.314
50th
0.252
0.246
0.336
0.349
0.323
0.369
0.380
0.221
0.218
0.298
0.310
0.289
0.333
0.342
0.229
0.229
0.309
0.321
0.297
0.343
0.352
75th
0.286
0.282
0.388
0.406
0.372
0.418
0.433
0.244
0.242
0.333
0.351
0.328
0.368
0.380
0.253
0.253
0.346
0.365
0.336
0.382
0.394
90th
0.317
0.324
0.440
0.462
0.422
0.469
0.490
0.265
0.269
0.371
0.399
0.369
0.402
0.416
0.274
0.275
0.382
0.409
0.373
0.416
0.432
95th
0.336
0.339
0.468
0.500
0.453
0.499
0.527
0.278
0.285
0.395
0.433
0.399
0.425
0.441
0.287
0.287
0.400
0.439
0.401
0.434
0.453
99th
0.370
0.361
0.518
0.594
0.517
0.544
0.580
0.301
0.317
0.458
0.521
0.448
0.464
0.490
0.311
0.302
0.443
0.522
0.461
0.467
0.491
Normal- weight females are defined as those having a body mass index varying between 19.8 and 26 kg/m in pre-pregnancy.
NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by
Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER x H x (VJVC > 2) x 10" . TDER = total energy requirement (ECG
+ TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure.
= Standard deviation.
Brochu et al., 2006b.
Q
I
a, 3
&
&
1=
-------
S
*S
ft
I
I
ON
Oo
ft
Table 6-58. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Overweight/Obese" Adolescents and Women Aged 11 to 55 Years
During Pregnancy and Postpartum Weeks
Age Group Progression of the
(years) Reproductive Cycle
11 to <23
23 to <30
30 to 55
a
b
SD
Source:
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Non-pregnant females
Pre-pregnancy 0 week
Pregnancy 9th week
Pregnancy 22ntl week
Pregnancy 36th week
Postpartum 6th week
Postpartum 27th week
Number
Subject
NExp o
NSim
15
5,000
5,000
5,000
5,000
5,000
5,000
54
5,000
5,000
5,000
5,000
5,000
5,000
61
5,000
5,000
5,000
5,000
5,000
5,000
"f
b
r
Mean ± SD
0.206 ±0.033
0.207 ±0.032
0.302 ±0.075
0.287 ±0.079
0.270 ±0.090
0.280 ±0.050
0.285 ±0.053
0.186 ±0.025
0.186 ±0.025
0.274 ±0.068
0.261 ±0.069
0.245 ±0.074
0.256 ±0.042
0.260 ±0.046
0.184±0.031
0.184 ± 0.031
0.272 ±0.068
0.259 ±0.071
0.242 ±0.068
0.253 ±0.048
0.257 ±0.051
Physiological Daily Inhalation Rates' (m3/kg-day)
Percentile
5th
0.151
0.146
0.205
0.191
0.179
0.213
0.214
0.144
0.143
0.203
0.193
0.175
0.205
0.209
0.132
0.127
0.184
0.176
0.162
0.188
0.191
10th
0.163
0.153
0.223
0.206
0.193
0.230
0.233
0.153
0.155
0.217
0.205
0.185
0.217
0.222
0.144
0.141
0.203
0.194
0.177
0.205
0.208
25th
0.184
0.188
0.263
0.246
0.225
0.266
0.269
0.169
0.172
0.238
0.224
0.205
0.241
0.246
0.163
0.166
0.234
0.222
0.201
0.237
0.239
50th
0.206
0.214
0.298
0.279
0.259
0.301
0.307
0.186
0.183
0.263
0.248
0.231
0.271
0.277
0.184
0.185
0.263
0.249
0.230
0.270
0.273
75th
0.229
0.227
0.329
0.314
0.296
0.337
0.344
0.203
0.201
0.298
0.283
0.268
0.304
0.311
0.205
0.205
0.299
0.282
0.265
0.305
0.310
90th
0.249
0.240
0.368
0.357
0.337
0.372
0.381
0.218
0.222
0.337
0.323
0.314
0.338
0.349
0.224
0.221
0.343
0.322
0.313
0.340
0.348
95th
0.261
0.253
0.401
0.391
0.377
0.395
0.409
0.227
0.233
0.374
0.360
0.360
0.360
0.372
0.235
0.226
0.378
0.363
0.351
0.364
0.374
99th
0.284
0.259
0.515
0.512
0.521
0.444
0.464
0.244
0.236
0.476
0.466
0.498
0.406
0.426
0.257
0.246
0.465
0.490
0.455
0.404
0.430
Overweight/obese females are defined as those having a body mass index higher than 26 kg/m2 in pre-pregnancy.
NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females.
Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by
Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER x H x (VJVC > 2) x 10"3. TDER = total energy requirement (ECG
+ TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure.
= Standard deviation.
Brochu et al., 2006b.
Q
I
I
I
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Exposure Factors Handbook
Chapter 6—Inhalation Rates
70 T
6 9 12 15 18 21 24 27 30 33 3i
(months)
Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Awake Subjects.
RR = respiratory rate.
Source: Rusconi et al, 1994.
Figure 6-2.
0 3 6 9 12 15 18 21 24 27 30 33 36
Age (months)
5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Asleep Subjects.
RR = respiratory rate.
Source: Rusconi et al., 1994.
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Chapter 7—Dermal Exposure Factors
TABLE OF CONTENTS
LIST OF TABLES 7-iii
LIST OF FIGURES 7-iv
7. DERMAL EXPOSURE FACTORS 7-1
7.1. INTRODUCTION 7-1
7.2. RECOMMENDATIONS 7-2
7.2.1. Body Surface Area 7-2
7.2.2. Adherence of Solids to Skin 7-3
7.2.3. Film Thickness of Liquids on Skin 7-4
7.2.4. Residue Transfer 7-4
7.3. SURFACE AREA 7-13
7.3.1. Key Body Surface Area Studies 7-13
7.3.1.1. U.S. EPA (1985) 7-13
7.3.1.2. Boniol et al. (2007) 7-13
7.3.1.3. U.S. EPAAnalysis of NHANES 2005-2006 and 1999-2006 Data 7-14
7.3.2. RelevantBody Surface Area Studies 7-15
7.3.2.1. Murray and Burmaster (1992)—Estimated Distributions for Total Body Surface
Area of Men and Women in the United States 7-15
7.3.2.2. Phillips et al. (1993) 7-15
7.3.2.3. Garlocketal. (1999) 7-16
7.3.2.4. Wong et al. (2000) 7-16
7.3.2.5. AuYeung et al. (2008) 7-16
7.4. ADHERENCE OF SOLIDS TO SKIN 7-17
7.4.1. Key Adherence of Solids to Skin Studies 7-17
7.4.1.1. Kissel etal. (1996a) 7-17
7.4.1.2. Holmes et al. (1999) 7-17
7.4.1.3. Shoaf etal. (2005) 7-18
7.4.2. Relevant Adherence of Solids to Skin Studies 7-18
7.4.2.1. Harger(1979) 7-18
7.4.2.2. QueHeeetal. (1985) 7-19
7.4.2.3. Driver etal. (1989) 7-19
7.4.2.4. Sedman(1989) 7-19
7.4.2.5. Finley etal. (1994) 7-20
7.4.2.6. Kissel etal. (1996b) 7-20
7.4.2.7. Holmes et al. (1996) 7-20
7.4.2.8. Kissel etal. (1998) 7-21
7.4.2.9. Rodes etal. (2001) 7-21
7.4.2.10. Edwards and Lioy (2001) 7-22
7.4.2.11. Choate et al. (2006) 7-22
7.4.2.12. Yamamoto et al. (2006) 7-23
7.4.2.13. Ferguson et al. (2008, 2009a, b, c) 7-23
7.5. FILM THICKNESS OF LIQUIDS ON SKIN 7-24
7.5.1. U.S. EPA(1987)/U.S. EPA(1992c) 7-24
7.6. RESIDUE TRANSFER 7-24
7.6.1. Residue Transfer Studies 7-25
7.6.1.1. Ross etal. (1990) 7-25
7.6.1.2. Ross etal. (1991) 7-26
7.6.1.3. Formoli (1996) 7-26
7.6.1.4. Krieger et al. (2000) 7-26
7.6.1.5. Clothier (2000) 7-27
7.6.1.6. Bernard etal. (2001) 7-27
7.6.1.7. Cohen-Hubal et al. (2005) 7-28
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Chapter 7—Dermal Exposure Factors
TABLE OF CONTENTS (continued)
7.6.1.8. Cohen-Hubal et al. (2008) 7-28
7.6.1.9. Beamer et al. (2009) 7-28
7.7. OTHER FACTORS 7-29
7.7.1. Frequency and Duration of Dermal (Hand) Contact 7-29
7.7.1.1. Zartarianetal. (1997) 7-29
7.7.1.2. Reed etal. (1999) 7-29
7.7.1.3. Freeman etal. (2001) 7-29
7.7.1.4. Freeman et al. (2005) 7-30
7.7.1.5. AuYeung et al. (2006) 7-30
7.7.1.6. Ko et al. (2007) 7-30
7.7.1.7. Beamer et al. (2008) 7-31
7.7.2. Thickness of the Skin 7-31
7.8. REFERENCES FOR CHAPTER 7 7-32
APPENDIX 7A FORMULAS FOR TOTAL BODY SURFACE AREA 1
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Chapter 7—Dermal Exposure Factors
LIST OF TABLES
Table 7-1. Recommended Values for Total Body Surface Area, For Children (Sexes Combined) and
Adults by Sex 7-5
Table 7-2. Recommended Values for Surface Area of Body Parts 7-6
Table 7-3. Confidence in Recommendations for Body Surface Area 7-8
Table 7-4. Recommended Values for Mean Solids Adherence to Skin 7-10
Table 7-5. Confidence in Recommendations for Solids Adherence to Skin 7-11
Table 7-6. Percentage of Total Body Surface Area by Body Part for Children (sexes combined) and
Adults by Sex 7-37
Table 7-7. Summary of Equation Parameters for Calculating Adult Body Surface Area 7-38
Table 7-8. Mean Proportion (%) of Children's Total Skin Surface Area, by Body Part 7-39
Table 7-9. Mean and Percentile Skin Surface Area (m2) 7-40
Table 7-10. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of
NHANES 1999-2006 for Children <21 Years and NHANES 2005-2006 for Adults >21
Years, Male 7-41
Table 7-11. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of
NHANES 1999-2006 for Children <21 Years and NHANES 2005-2006 for Adults >21
Years, Female 7-42
Table 7-12. Surface Area of Adult Male (21 years and older) in Square Meters 7-43
Table 7-13. Surface Area of Adult Females (21 years and older) in Square Meters 7-44
Table 7-14. Statistical Results for Total Body Surface Area Distributions (m2), for Adults 7-45
Table 7-15. Descriptive Statistics for Surface Area/Body-Weight (S A/B W) Ratios (m2/kg) 7-46
Table 7-16. Estimated Percent of Adult Skin Surface Exposed During Outdoor Activities 7-47
Table 7-17. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 7-47
Table 7-18. Median Per Contact Outdoor Fractional Surface Areas of the Hands, by Object, Both
Hands Combined 7-48
Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates 7-49
Table 7-20. Geometric Mean and Geometric Standard Deviations of Solids Adherence by Activity
and Body Region 7-52
Table 7-21. Summary of Controlled Greenhouse Trials 7-54
Table 7-22. Dermal Transfer Factors for Selected Contact Surface Types and Skin Wetness, Using
<80 urn Tagged ATD 7-54
Table 7-23. Comparison of Adherence (mg/cm2) for Contact with Carpet and Aluminum Surfaces,
Averaged Across Pressure, Contact Time, Soil Type, and Soil Particle Size 7-55
Table 7-24. Film Thickness Values of Selected Liquids Under Various Experimental Conditions
(10~3cm) 7-56
Table 7-25. Mean Transfer Efficiencies (%) 7-57
Table 7-26. Transfer Efficiencies (%) for Dry, Water-Wetted, and Saliva-Wetted Palms and PUF
Roller 7-57
Table 7-27. Incremental and Overall Surface to Hand Transfer Efficiencies (%) 7-58
Table 7-28. Lognormal Distributions for Modeling Transfer Efficiencies (fraction) 7-59
Table 7-29. Hand-to-Object/Surface Contact—Frequency (contacts/hour) 7-59
Table 7-30. Hand-to-Objects/Surfaces—Frequency (contacts/hour) 7-60
Table 7-31. Median (mean ± SD) Hand Contact Frequency with Clothing, Surfaces, or Objects
(contacts/hour) 7-60
Table 7-32. Hand Contact with Objects/Surfaces—Frequency (contacts/hour) 7-60
Table 7-33. Outdoor Hand Contact with Object/Surfaces, Children 1 to 6 Years 7-61
Table 7-34. Indoor Hand Contact with Object/Surfaces—Frequency, Children 1 to 6 Years (median
contacts/hour) 7-62
Table 7-35. Outdoor Hand Contact with Surfaces—Frequency, Children 1 to 5 Years (contacts/hour) 7-62
Table 7-36. Hand Contact with Object/Surfaces, Infants and Toddlers 7-63
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Chapter 7—Dermal Exposure Factors
LIST OF FIGURES
Figure 7-1. Frequency Distributions for the Surface Area of Men and Women 7-64
Figure 7-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults Transplanting
Plants and Children Playing in Wet Soils 7-65
Figure 7-3. Gravimetric Loading vs. Body Part for Adults Transplanting Plants in Wet Soil and
Children Playing in Wet and Dry Soils 7-65
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Chapter 7—Dermal Exposure Factors
1. DERMAL EXPOSURE FACTORS
7.1. INTRODUCTION
Dermal exposure can occur during a variety of
activities in different environmental media and
microenvironments (U.S. Environmental Protection
Agency [U.S. EPA], 1992a, b, 2004). These include:
• water (e.g., bathing, washing, swimming);
• soil (e.g., outdoor recreation, gardening,
construction);
• sediment (e.g., wading, fishing);
• other liquids (e.g., use of commercial
products);
• vapors/fumes/gases (e.g., use of commercial
products); and
• other solids or residues (e.g., soil/dust or
chemical residues on carpets, floors, counter
tops, outdoor surfaces, or clothing).
Exposure via the dermal route may be estimated
in various ways, depending on the exposure media
and scenario of interest. For example, dermal
exposure to contaminants in soil, sediment, or dust
may be evaluated using information on the
concentration of contaminant in these materials in
conjunction with information on the amount of
material that adheres to the skin per unit surface area
and the total area of skin surface exposed. An
approach for estimating dermal exposure to
contaminants in liquids uses information on the
concentration of contaminant in the liquid in
conjunction with information on the film thickness of
liquid remaining on the skin after contact. When
assessing dermal exposure to water (e.g., bathing or
swimming) or to vapors and fumes, the concentration
of chemical in water or vapor with the total exposed
skin surface area may be considered. An approach for
estimating exposure to surface residues is to use
information on the rate of transfer of chemical
residues to the skin as a result of contact with the
surfaces. Dermal exposure also may result from
leaching of chemicals that are impregnated in
materials that come into contact with skin. For
example, Snodgrass (1992) evaluated transfer of
pesticides from treated clothing onto the skin. For
information on various methods used to estimate
dermal exposure, refer to Guidelines for Exposure
Assessment (U.S. EPA, 1992a), Dermal Exposure
Assessment: Principles and Applications (U.S. EPA,
1992b), and Dermal Exposures Assessment: A
Summary of EPA Approaches (U.S. EPA, 2007).
Additional scenario-specific information on dermal
exposure assessment is available in Risk Assessment
Guidance for Superfund (RAGS) Part E (U.S. EPA,
2004), Standard Operating Procedures for
Residential Pesticide Exposure Assessment, draft
(U.S. EPA, 2009), and Methods for Assessing
Exposure to Chemical Substances: Volume 7,
Methods for Assessing Consumer Exposure to
Chemical Substances (U.S. EPA, 1987). In general,
these methods for estimating dermal exposure require
information on the surface area of the skin that is
exposed. Some methods also require information on
the adherence of solids to the skin or information on
the film thickness of liquids on the skin. Others
utilize information on the transfer of residues from
contaminated surfaces to the skin surface and/or rate
of contact with objects or surfaces. This chapter
focuses on measurements of body surface area and
non-chemical-specific factors related to dermal
exposure (i.e., the deposition of contaminants onto
the skin), such as adherence of solids to the skin, film
thickness of liquids on the skin, and residue transfer
from contaminated surfaces to the skin. However, this
chapter only provides recommendations for surface
area and solids adherence to skin. According to Riley
et al. (2004), numerous factors may affect loading
and retention of chemicals on the skin, including the
form of the contaminant (particle, liquid, residue),
surface characteristics (hard, plush, porous, surface
loading, previous transfers), skin characteristics
(moisture, age, loading), contact mechanics (pressure,
duration, repetition), and environmental conditions
(temperature, relative humidity, air exchange). These
factors are discussed in this chapter, as reported by
the various study authors. Information on other
factors that may affect dermal exposure (e.g., contact
frequency and duration, and skin thickness) also is
provided in this chapter.
Factors that influence dermal uptake (i.e.,
absorption) and internal dose, including
chemical-specific factors, are not provided in this
handbook. These include factors such as the
concentration of chemical in contact with the skin,
weight fraction of chemicals in consumer products,
and characteristics of the chemical (i.e., lipophilicity,
polarity, volatility, solubility). Also, factors affecting
the rate of absorption of the chemical through the
skin at the site of application and the amount of
chemical delivered to the target organ are not covered
in this chapter. Absorption may be affected by the age
and condition of the skin, including presence of
perspiration (Williams etal., 2004, 2005). Also, the
thickness of the stratum corneum (outer layer of the
skin) varies over parts of the body and may affect
absorption. While not the primary focus of this
chapter, some limited information on skin thickness
Exposure Factors Handbook
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Chapter 7—Dermal Exposure Factors
is presented in Section 7.7—Other Factors. For
guidance on how to use information on factors
needed to assess dermal dose, refer to Dermal
Exposure Assessment: Principles and Applications
(U.S. EPA, 1992b) and Risk Assessment Guidelines
for Superfund (RAGs) Part E (U.S. EPA, 2004).
Frequency and duration of contact also may affect
dermal exposure and dose. Data on dermal contact
frequency and duration of hand contact with objects
and surfaces are presented in Section 7.7.1 of this
chapter. Additional information on consumer
products use and activity factors that may affect
dermal exposure is presented in Chapters 16 and 17.
Section 7.3 of this chapter provides data on
surface area of the human skin. Section 7.4 provides
data on adherence of solids to human skin.
Information on the film thickness of liquids on the
skin is limited. However, studies that estimated film
thickness of liquids on the skin are presented in
Section 7.5. Section 7.6 presents available
information on the transfer of residues from
contaminated surfaces to the skin. Section 7.7
provides information on other factors affecting
dermal exposure (e.g., frequency and duration of
dermal contact with objects and surfaces, and skin
thickness).
Recommendations for skin surface area and
dermal adherence of solids to skin are provided in the
next section, along with a summary of the confidence
ratings for these recommendations. The
recommended values are based on key studies
identified by U.S. EPA for these factors. Relevant
data on these and other factors also are presented in
this chapter to provide added perspective on the
state-of-knowledge pertaining to dermal exposure
factors.
7.2. RECOMMENDATIONS
7.2.1. Body Surface Area
Table 7-1 summarizes the recommended mean
and 95th percentile total body surface area values. For
children under 21 years of age, the recommendations
for total body surface area are based on the U.S. EPA
analysis of 1999-2006 data from the National Health
and Nutrition Examination Survey (NHANES).
These data are presented for the standard age
groupings recommended by U.S. EPA (2005) for
male and female children combined. For adults
21 years and over, the recommendations for total
body surface area are based on the U.S. EPA analysis
of NHANES (2005-2006) data. The U.S. EPA
analysis of NHANES data uses correlations with
body weight and height for deriving skin surface area
(see Section7.3.1.3 and Appendix 7A). NHANES
(1999-2006) used a statistically based survey design
that should ensure that the data are reasonably
representative of the general population for each
2-year interval (e.g., 1999 to 2000, 2001 to 2002).
Multiple NHANES study years, supplying a larger
sample size, were necessary for estimating surface
area for children given the multiple stratifications by
age. The advantage of using the NHANES data sets
to derive the total surface area recommendations is
that data are nationally representative and remain the
principal source of body-weight and height data
collected nationwide from a large number of subjects.
Note that differences between the surface area
recommendations presented here and those in the
previous Exposure Factors Handbook (U.S. EPA,
1997) reflect changes in the body weights used in
calculating these surface areas. If sex-specific data
for children, sex-combined data for adults, or data for
statistics other than the mean or 95th percentile are
needed, refer to Tables 7-9 through 7-13 of this
chapter.
Table 7-2 presents the recommendations for the
percentage of total body surface area represented by
individual body parts for children based on data from
U.S. EPA (1985) and Boniol etal. (2007) (see
Section 7.3.1). The data from Boniol et al. (2007) are
used for the recommendations for children greater
than 2 years of age because they are based on a larger
sample size than those in U.S. EPA (1985) for the
same age groups. Because the Boniol etal. (2007)
study does not include data for children less than
2 years of age, recommendations for this age group
are based on the data from U.S. EPA (1985). It should
be noted, however, that the sample size for the
percentages of the total body represented by various
body parts in this age group is very small. Table 7-2
also provides age-specific body part surface areas
(m2) for children. These values were obtained by
multiplying the age-specific mean body part
percentages (for males and females combined) by the
total body surface areas presented in Table 7-1. If
sex-specific data are needed for children equal to or
greater than_2 years of age, or if data for additional
body parts not summarized in Table 7-2 are needed,
refer to Table 7-8. The body part data in this table
may be applied to data in Tables 7-9 through 7-11 to
calculate surface area for the various body parts.
The recommendations for surface area of adult
body parts are based on the U.S. EPA Analysis of
NHANES 2005-2006 data and algorithms from
U.S. EPA (1985). The U.S. EPA Analysis of the
NHANES data was used to develop
recommendations for body parts because the data are
nationally representative and based on a large number
of subjects. Table 7-2 presents the data for adult
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Chapter 7—Dermal Exposure Factors
males and adult females (21+years of age). If sex-
combined data for adults or data for statistics other
than the mean and 95th percentile are needed, refer to
Tables 7-12 and 7-13. These tables present the
surface area of body parts for males and females,
respectively, 21 years of age and older. Table 7-3
presents the confidence ratings for the
recommendations for body surface area.
For swimming and bathing scenarios, past
exposure assessments have assumed that 75 to
100% of the skin surface is exposed (U.S. EPA,
1992b). More recent guidance recommends assuming
100% exposure for these scenarios (U.S. EPA, 2004).
For other exposure scenarios, it is reasonable to
assume that clothing reduces the contact area.
However, while it is generally assumed that
adherence of solids to skin only occurs to the areas of
the body not covered by clothing, it is important to
understand that soil and dust particles can get under
clothing and be deposited on skin to varying degrees
depending on the protective properties of the
clothing. Likewise, liquids or chemical residues on
surfaces may soak through clothing and contact
covered areas of the skin. Assessors should consider
these possibilities for the scenario of concern and
select skin areas that are judged appropriate. Also,
surface area of the body and body weight are highly
correlated (Phillips etal., 1993). The relationship
between these factors, therefore, should be
considered when selecting body weights for use with
the surface area data for estimating dermal exposure.
7.2.2. Adherence of Solids to Skin
The adherence factor (AF) describes the amount
of solid material that adheres to the skin per unit of
surface area. Although most research in this area has
focused on soils, a variety of other solid residues can
accumulate on skin, including household dust,
sediments, and commercial powders. Studies on soil
adherence have shown that (1) soil properties
influence adherence, (2) soil adherence varies
considerably across different parts of the body, and
(3) soil adherence varies with activity (U.S. EPA,
2004). It is recommended that exposure assessors use
adherence data derived from testing that matches the
exposure scenario of concern in terms of solid type,
exposed body parts, and activities as closely as
possible. Refer to the activities described in
Table 7-19 to select those that best represent the
exposure scenarios of concern and use the
corresponding adherence values from Table 7-20.
Table 7-19 also lists the age ranges covered by each
study. This may be used as a general guide to the ages
covered by these data.
Table 7-4 summarizes recommended mean AF
values according to common activities. The key
studies used to develop the recommendations for
adherence of solids to skin are those based on field
studies in which specific activities relevant to dermal
exposure were evaluated (compared to relevant
studies that evaluated adherence in controlled
laboratory trials using sieved or standardized soil).
Insufficient data were available to develop activity-
specific distributions or probability functions for
these studies. Also, the small number of subjects in
these studies prevented the development of
recommendations for the childhood specific age
groups recommended by U.S. EPA (2005).
U.S. EPA (2004) recommends that
scenario-specific adherence values be weighted
according to the body parts exposed. Weighted
adherence factors may be estimated according to the
following equation:
= (AF,)CSA,)
.... (AFJfSAJ
SA, + SA2 + . .. SA,
(Eqn. 7-1)
where:
AF
SA
weighted adherence factor,
adherence factor, and
surface area.
For the purposes of this calculation, the surface
area of the face may be assumed to be 1/3 that of the
head, forearms may be assumed to represent 45% of
the arms, and lower legs may be assumed to represent
40% of the legs (U.S. EPA, 2004).
The recommended dermal AFs represent the
amount of material on the skin at the time of
measurement. U.S. EPA (1992b) recommends
interpreting AFs as representative of contact events.
Assuming that the amount of solids measured on the
skin represents accumulation between washings, and
that people wash at least once per day, these
adherence values can be interpreted as daily contact
rates (U.S. EPA, 1992b). The rate of solids
accumulation on skin over time has not been well
studied but probably occurs fairly quickly. Therefore,
prorating the adherence values for exposure time
periods of less than 1 day is not recommended.
Table 7-5 shows the confidence ratings for these
AF recommendations. While the recommendations
are based on the best available estimates of activity-
specific adherence, they are based on limited data
from studies that have focused primarily on soil.
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Therefore, they have a high degree of uncertainty,
and considerable judgment must be used when
selecting them for an assessment. It also should be
noted that the skin-adherence studies on which these
recommendations are based have generally not
considered the influence of skin moisture on
adherence. Skin moisture varies depending on a
number of factors, including activity level and
ambient temperature/humidity. It is uncertain how
well this variability has been captured in the dermal-
adherence studies used for the recommendations.
7.2.3. Film Thickness of Liquids on Skin
The film thickness of liquids on skin represents
the amount of material that remains on the skin after
contact with a liquid (e.g., consumer product such as
cleaning solution or soap). The data on film thickness
of liquids on the hand are limited, and recommended
values are not provided in this chapter. Refer to
Section 7.5 for a description of the available data that
may be used to assess dermal contact with liquid
using the film thickness approach.
7.2.4. Residue Transfer
Several studies have developed methods for
quantifying the rates of transfer of chemical residues
to the skin of individuals performing activities on
contaminated surfaces. These studies have been
conducted primarily for the purpose of estimating
exposure to pesticides. Section 7.6 describes studies
that have estimated residue transfer to human skin.
Because use of residue transfer depends on the
specific conditions under which exposure occurs
(e.g., activity, contact surfaces, age), general
recommendations are not provided. Instead, refer to
Section 7.6 for a description of the available data
from which appropriate values may be selected.
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Table 7-1. Recommended Values for Total Body Surface Area,
For Children (Sexes Combined) and Adults by Sex
Age Group
Mean
95th Percentile
m2
Multiple
Percentiles
Source
Male and Female Children Combined
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
Adult Male
21 to 30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
80 years and over
Adult Female
21 to 30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
80 years and over
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
2.05
2.10
2.15
2.11
2.08
2.05
1.92
1.81
1.85
1.88
1.89
1.88
1.77
1.69
0.34
0.38
0.44
0.51
0.61
0.70
0.95
1.48
2.06
2.33
2.52
2.50
2.56
2.55
2.46
2.45
2.22
2.25
2.31
2.36
2.38
2.34
2.13
1.98
See Tables 7-9,
7-10, and 7-11
(for sex-specific
data)
See Tables 7-9
(for sex-
combined data)
and 7-10
See Tables 7-9
(for sex-
combined data)
and 7-11
U.S. EPA Analysis of
NHANES 1999-2006 data
U.S. EPA Analysis of
NHANES 2005-2006 data
U.S. EPA Analysis of
NHANES 2005-2006 data
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Age Group
Male and Female
Table 7-2.
Head
Recommended Values for Surface Area of Body Parts
Trunk3
Armsb
Hands
Legs'
Feet
Mean Percent of Total Surface Area
— Source
Children Combined
Birth to <1 monthd 18.2
1 to <3 months'1
3 to <6 months'1
6 to <12 months'1
1 to <2 years'1
2 to <3 years6
3 to <6 yearsf
6 to <11 years8
1 1 to < 16 years'1
16to<21years1
Adult Male
21+ years
Adult Female
21+ years
Male and Female
18.2
18.2
18.2
16.5
8.4
8.0
6.1
4.6
4.1
6.6
6.2
35.7
35.7
35.7
35.7
35.5
41.0
41.2
39.6
39.6
41.2
40.1
35.4
Mean
13.7
13.7
13.7
13.7
13.0
14.4
14.0
14.0
14.3
14.6
15.2
12.8
5.3
5.3
5.3
5.3
5.7
4.7
4.9
4.7
4.5
4.5
5.2
4.8
Surface Area by
m2
20.6
20.6
20.6
20.6
23.1
25.3
25.7
28.8
30.4
29.5
33.1
32.3
Body Part1
6.5
6.5
6.5
6.5
6.3
6.3
6.4
6.8
6.6
6.1
6.7
6.6
U.S. EPA, 1985
Bonioletal.,2007
(average of data for
males and females)
U.S. EPA Analysis
ofNHANES
2005-2006 data and
U.S. EPA, 1985
Children Combined
Birth to <1 monthd 0.053
1 to <3 months'1
3 to <6 months'1
6 to <12 months'1
1 to <2 years'1
2 to <3 years6
3 to <6 yearsf
6 to <11 years8
11 to <16 years'1
16 to <21 years1
Adult Male
21+ years
Adult Female
21+ years
0.060
0.069
0.082
0.087
0.051
0.061
0.066
0.073
0.075
0.136
0.114
0.104
0.118
0.136
0.161
0.188
0.250
0.313
0.428
0.630
0.759
0.827
0.654
0.040
0.045
0.052
0.062
0.069
0.088
0.106
0.151
0.227
0.269
0.314
0.237
0.015
0.017
0.020
0.024
0.030
0.028
0.037
0.051
0.072
0.083
0.107
0.089
0.060
0.068
0.078
0.093
0.122
0.154
0.195
0.311
0.483
0.543
0.682
0.598
0.019
0.021
0.025
0.029
0.033
0.038
0.049
0.073
0.105
0.112
0.137
0.122
U.S. EPA Analysis
ofNHANES
1999-2006 data and
U.S. EPA, 1985
U.S. EPA Analysis
ofNHANES
1999-2006 data and
Bonioletal.,2007
U.S. EPA Analysis
ofNHANES
2005-2006 data and
U.S. EPA, 1985
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Table 7-2. Recommended Values for Surface Area of Body Parts (continued)
Head Trunk3 Armsb Hands
Legs'
Feet
Age Group
95th Percentile Surface Area by Body Partk
m2
Source
Male and Female Children Combined
Birth to
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Table 7-3. Confidence in Recommendations for Body Surface Area
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Total surface area estimates were based on algorithms developed
using direct measurements and data from NHANES surveys. The
methods used for developing these algorithms were adequate. The
NHANES data and the secondary data analyses to estimate total
surface areas were appropriate. NHANES included large sample
sizes; sample size varied with age. Body-part percentages for
children <2 years of age were based on direct measurements from
a very small number of subjects (N = 4). Percentages for children
>2 years were based on 2,050 children; adult values were based
on 89 adults.
The data used to develop the algorithms for estimating surface
area from height and weight data were limited. NHANES
collected physical measurements of weight and height for a large
sample of the population.
Medium
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key studies were directly relevant to surface area estimates.
The direct measurement data used to develop the algorithms for
estimating total body surface area from weight and height may
not be representative of the U.S. population. However, NHANES
height and weight data were collected using a complex, stratified,
multi-stage probability cluster sampling design intended to be
representative of the U.S. population. Body part percentages for
children <2 years of age were based on direct measurements from
a very small number of subjects (N = 4). Percentages for children
>2 years were based on 2,050 children from various states in the
United States and are assumed to be representative of U.S.
children; adult values were based on 89 adults.
The U.S. EPA analysis used the most current NHANES data to
generate surface area data using algorithms based on older direct
measurements. The data on body part percentages were dated.
However, the age of the percentage data is not expected to affect
its utility if the percentages are applied to total surface area data
that has been updated based on the most recent NHANES
body-weight and height data.
The U.S. EPA analysis was based on four NHANES data sets
covering 1999-2006 for children and one NHANES data set,
2005-2006, for adults.
Medium
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Table 7-3. Confidence in Recommendations for Body Surface Area (continued)
General Assessment Factors
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The U.S. EPA analysis of the NHANES data is
unpublished, but used the same methodology as that
described in the 1997 Exposure Factors Handbook
(U.S. EPA, 1997). U.S. EPA (1985) is a U.S. EPA-
published report. Boniol et al. (2007) is a published
paper.
The methodology was clearly presented; enough
information was included to reproduce the results.
Quality assurance of NHANES data was good; quality
control of secondary data analysis was not well
described.
The full distributions were given for total surface area.
A source of uncertainty in total surface areas resulted
from the limitations in data used to develop the
algorithms for estimating total surface from height and
weight. Because of the small sample size for some
ages, there is uncertainty in the body part percentage
estimates for these age groups.
The NHANES surveys received a high level of peer
review. The U.S. EPA analysis was not published in a
peer-reviewed journal, but used the same methodology
as that described in the 1997 Exposure Factors
Handbook (\3S. EPA, 1997).
There is one key study for total surface area and
two key studies for the surface area of body parts.
Rating
Medium
Medium
Medium
Medium for Total
Surface Area and
Low for Surface
Area of Individual
Body Parts
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Table 7-4. Recommended Values for Mean Solids Adherence to Skin
Face Arms Hands Legs Feet
mg/cm2
Source
Children
Residential (indoors)3
Daycare (indoors and outdoors)13
Outdoor sports' 0.012
Indoor sportsd
Activities with soil6 0.054
Playing in mudf
Playing in sediment8 0.040
0.
0
0
0.
0
0041
.024
.011
0019
.046
11
0.17
0.011
0.099
0.11
0.0063
0.17
47
0.49
0.
0
0
0.
0
0035
.020
.031
0020
.051
23
0.70
0.010
0.071
-
0.0022
0.20
15
21
Holmes et al
Holmes et al
Kissel et al.,
Kissel et al.,
Holmes et al
Kissel et al.,
Shoaf etal.,
, 1999
, 1999
1996a
1996a
, 1999
1996a
2005
Adults
Outdoor sports'1
Activities with soil1
Construction activities'
0.0314 0.0872 0.1336 0.1223
0.0240 0.0379 0.1595 0.0189 0.1393
0.0982 0.1859 0.2763 0.0660
Holmes etal., 1999;
Kissel etal., 1996a
Holmes etal., 1999;
Kissel etal., 1996a
Holmes etal., 1999
Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to!3 years; N= 10)
playing indoors.
Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years;
N = 11) playing both indoors and outdoors.
Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer.
Based on geometric mean soil loadings of 6 children (ages >8 years) and one adult engaging in Tae Kwon Do.
Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years).
Based on weighted average of geometric mean soil loadings of 2 groups of children (age 9 to 14 years; N = 12)
playing in mud.
Based on geometric mean soil loadings of 9 children (ages 7 to 12 years) playing in tidal flats.
Based on weighted average of geometric mean soil loadings of 3 groups of adults (ages 23 to 33 years) playing
rugby and 2 groups of adults (ages 24 to 34) playing soccer.
Based on weighted average of geometric mean soil loadings for 69 gardeners, farmers, groundskeepers,
landscapers and archeologists (ages 16 to 64 years) for faces, arms and hands; 65 gardeners, farmers,
groundskeepers, and archeologists (ages 16 to 64 years) for legs; and 36 gardeners, groundskeepers and
archeologists (ages 16 to 62) for feet.
Based on weighted average of geometric mean soil loadings for 27 construction workers, utility workers and
equipment operators (ages 21 to 54) for faces, arms and hands; and based on geometric mean soil loadings for
8 construction workers (ages 21 to 30 years) for legs.
= No data.
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Table 7-5. Confidence in Recommendations for Solids Adherence to Skin
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Medium
The approach was adequate; the skin-rinsing technique is
widely employed for purposes similar to this. Small sample
sizes were used in the studies; the key studies directly
measured soil adherence to skin.
The studies attempted to measure soil adherence for selected
activities and conditions. The number of activities and study
participants was limited.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The studies were relevant to the factor of interest; the goal
was to determine soil adherence to skin.
The soil/dust studies were limited to the State of
Washington, and the sediment study was limited to Rhode
Island. The data may not be representative of other locales.
All three studies were conducted by researchers from a
laboratory where a similar methodology was used. This may
limit the representativeness of the data in terms of a wider
population.
The studies were published between 1996 and 2005.
Short-term data were collected. Seasonal factors may be
important, but have not been studied adequately.
Low
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Articles were published in widely circulated
journals/reports.
The reports clearly describe the experimental methods, and
enough information was provided to allow for the study to
be reproduced.
Quality control was not well described.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Variability in soil adherence is affected by many factors
including soil properties, activity and individual behavior
patterns. Not all age groups were represented in the sample.
The estimates are highly uncertain; the soil adherence values
were derived from a small number of observations for a
limited set of activities.
Low
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Table 7-5. Confidence in
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Recommendations for Solids Adherence to Skin (continued)
Rationale
The studies were reported in peer-reviewed journal articles.
There are three key studies that evaluated different activities
in children and adults.
Rating
Medium
Low
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7.3. SURFACE AREA
Surface area of the skin can be determined by
using measurement or estimation techniques.
Coating, triangulation, and surface integration are
direct measurement techniques that have been used to
measure total body surface area and the surface area
of specific body parts. The coating method consists
of coating either the whole body or specific body
regions with a substance of known density and
thickness. Triangulation consists of marking the area
of the body into geometric figures, then calculating
the figure areas from their linear dimensions. Surface
integration is performed by using a planimeter and
adding the areas. The results of studies conducted
using these various techniques have been
summarized in Development of Statistical
Distributions or Ranges of Standard Factors Used in
Exposure Assessments (U.S. EPA, 1985). Because of
the difficulties associated with direct measurements
of body surface area, the existing direct measurement
data are limited and dated. However, several
researchers have developed methods for estimating
body surface area from measurements of other body
dimensions (DuBois and DuBois, 1916; Boyd, 1935;
Gehan and George, 1970). Generally, these formulas
are based on the observation that body weight and
height are correlated with surface area and are
derived using multiple regression techniques.
U.S. EPA (1985) evaluated the various formulas for
estimating total body surface area. Appendix 7A
presents a discussion and comparison of formulas.
The key studies on body surface area that are
presented in Section 7.3.1 are based on these
formulas, as well as weight and height data from
NHANES.
7.3.1. Key Body Surface Area Studies
7.3.1.1. U.S. EPA (1985)—Development of
Statistical Distributions or Ranges of
Standard Factors Used in Exposure
Assessments
U.S. EPA (1985) summarized the direct
measurements of the surface area of adults' and
children's body parts provided by Boyd (1935) and
Van Graan (1969) as a percentage of total surface
area. Table 7-6 presents these percentages. A total of
21 children less than 18 years of age were included.
Because of the small sample size, it is unclear how
accurately these estimates represent averages for the
age groups. A total of 89 adults, 18 years and older,
were included in the analysis of body parts, providing
greater accuracy for the adult estimates. Note that the
proportion of total body surface area contributed by
the head decreases from childhood to adulthood,
whereas the proportion contributed by the leg
increases.
U.S. EPA (1985) analyzed the direct surface area
measurement data of Gehan and George (1970) using
the Statistical Processing System (SPS) software
package of Buhyoff et al. (1982). Gehan and George
(1970) selected 401 measurements made by Boyd
(1935) that were complete for surface area, height,
weight, and age for their analysis. Boyd (1935) had
reported surface area estimates for 1,114 individuals
using coating, triangulation, or surface integration
methods (U.S. EPA, 1985).
U.S. EPA (1985) used SPS to generate equations
to calculate surface area as a function of height and
weight. These equations were subsequently used by
U.S. EPA to calculate body surface area distributions
of the U.S. population using the height and weight
data obtained from the National Health and Nutrition
Examination Survey, 1999-2006 (CDC, 2006; see
Section 7.3.1.3).
The equation proposed by Gehan and George
(1970) was determined by U.S. EPA (1985) to be the
best choice for estimating total body surface area.
However, the paper by Gehan and George (1970)
gave insufficient information to estimate the standard
error about the regression. Therefore, U.S. EPA
(1985) used the 401 direct measurements of children
and adults and reanalyzed the data using the formula
of Dubois and Dubois (1916) and SPS to obtain the
standard error (U.S. EPA, 1985).
Regression equations were developed for specific
body parts using the Dubois and Dubois (1916)
formula and using the surface area of various body
parts provided by Boyd (1935) and Van Graan (1969)
in conjunction with SPS. Regression equations for
adults were developed for the head, trunk (including
the neck), upper extremities (arms and hands, upper
arms, and forearms) and lower extremities (legs and
feet, thighs, and lower legs) (U.S. EPA, 1985).
Table 7-7 presents a summary of the equation
parameters developed by U.S. EPA (1985) for
calculating surface area of adult body parts.
Equations to estimate the body part surface area of
children were not developed because of insufficient
data.
7.3.1.2. Boniol et al (2007)—Proportion of Skin
Surface Area of Children and Young
Adults from 2 to 18 Years Old
Boniol et al. (2007) applied measurement data for
87 body parts to a computer model to estimate the
surface area of body parts of children. The
measurement data were collected in the late 1970s by
Snyder et al. (1978) for the purpose of product safety
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design (e.g., toys and ergonomics) and represent
1,075 boys and 975 girls from various states in the
United States. A surface area module of the computer
model MAN3D was used to construct models of the
human body for children (ages 2, 4, 6, 8, 10, 12, 14,
16, and 18 years) to estimate surface area of 13 body
parts for use in treating skin lesions. The body parts
included head, neck, bosom, shoulders, abdomen,
back, genitals and buttocks, thighs, legs, feet, upper
arms, lower arms, and feet. The proportion of the skin
surface area of these body parts relative to total
surface area was computed. Table 7-8 presents these
data for the various ages of male and female children.
Except for the head, for which the percentages are
much lower in this study than in U.S. EPA (1985), the
body part proportions in this study appear to be
similar to those presented in U.S. EPA (1985). For
example, the proportions for hands range from 4.2 to
4.9% in this study and from 5.0 to 5.9% in U.S. EPA
(1985). Because this study provides additional body
parts that were not included in the U.S. EPA (1985)
study, it is necessary to combine some body parts for
the purpose of comparing their results. For example,
upper arms and lower arms can be combined to
represent total arms, and thighs plus legs can be
combined to represent total legs. Upper arms plus
lower arms for 4-year-olds from this study represent
14% of the total body surface, compared to 14.2% for
arms for 3- to 6-year-olds from U.S. EPA (1985).
Thighs plus legs for 2-year-olds from this study
represent 25.3% of the total surface, compared to
23.2% for 2- to 3-year-olds from U.S. EPA (1985).
Likewise, neck, bosom, shoulders, abdomen, back,
and genitals/buttocks can be combined to represent
the trunk.
The advantages of this study are that the data
represent a larger sample size of children and are
more recent than those used in U.S. EPA (1985). This
study also provides data for more body parts than
U.S. EPA (1985). However, the age groups presented
in this study differ from those recommended in
U.S. EPA (2005) and used elsewhere in this
handbook, and no data are available for children
1 year of age and younger.
7.3.1.3. U.S. EPA Analysis ofNHANES
2005-2006 and 1999-2006 Data
The U.S. EPA estimated total body surface areas
by using the empirical relationship shown in
Appendix 7A and U.S. EPA (1985), and body-weight
and height data from the 1999-2006 NHANES for
children and the 2005-2006 NHANES for adults.
NHANES is conducted annually by the Centers for
Disease Control (CDC) National Center of Health
Statistics. The survey's target population is the
civilian, non-institutionalized U.S. population. The
NHANES 1999-2006 survey was conducted on a
nationwide probability sample of approximately
40,000 people for all ages, of which approximately
20,000 were children. The survey is designed to
obtain nationally representative information on the
health and nutritional status of the population of the
United States through interviews and direct physical
examinations. A number of anthropometrical
measurements were taken for each participant in the
study, including body weight and height. Unit
non-response to the household interview was 19%,
and an additional 4% did not participate in the
physical examinations (including body-weight
measurements).
The NHANES 1999-2006 survey includes
oversampling of low-income persons, adolescents 12
to 19 years of age, persons 60+ years of age, African
Americans, and Mexican Americans. Sample data
were assigned weights to account both for the
disparity in sample sizes for these groups and for
other inadequacies in sampling, such as the presence
of non-respondents. For children's estimates, the
U.S. EPA utilized four NHANES data sets in its
analysis (NHANES 1999-2000, 2001-2002,
2003-2004, and 2005-2006) to ensure adequate
sample size for the age groupings of interest. Sample
weights were developed for the combined data set in
accordance with CDC guidance from the NHANES'
Web site (http://www.cdc.gov/nchs/about/major/
nhanes/nhanes20052006/faqs05_06.htm#question%2
012). For adult estimates, the U.S. EPA utilized
NHANES 2005-2006 in its estimates for currency
and the same analytical methodology as in the earlier
version of the Exposure Factors Handbook
(U.S. EPA, 1997).
Table 7-9 presents the mean and percentile
estimates of total body surface area by age category
for males and females combined. Tables 7-10 and
7-11 present the mean and percentiles of total body
surface area by age category for males and females,
respectively. Tables 7-12 and 7-13 present the mean
and percentile estimates of body surface area of
specific body parts for males and females 21 years
and older, respectively.
An advantage of using the NHANES data sets to
derive total surface area estimates is that data are
available for infants from birth and older. In addition,
the NHANES data are nationally representative and
remain the principal source of body-weight and
height data collected nationwide from a large number
of subjects. It should be noted that in the NHANES
surveys, height measurements for children less than
2 years of age were based on recumbent length
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whereas standing height information was collected
for children aged 2 years and older. Some studies
have reported differences between recumbent length
and standing height measurements for the same
individual, ranging from 0.5 to 2 cm, with recumbent
length being the larger of the two measurements
(Buyken et al., 2005). The use of height data obtained
from two different types of height measurements to
estimate surface area of children may potentially
introduce errors into the estimates.
7.3.2. Relevant Body Surface Area Studies
7.3.2.1. Murray and Burmaster
(1992)—Estimated Distributions for Total
Body Surface Area of Men and Women in
the United States
Murray and Burmaster (1992) generated
distributions of total body surface area for men and
women ages 18 to 74 years using Monte Carlo
simulations based on height and weight distribution
data. Four different formulae for estimating body
surface area as a function of height and weight were
employed: Dubois and Dubois (1916), Boyd (1935),
U.S. EPA (1985), and Costeff (1966). The formulae
of Dubois and Dubois (1916), Boyd (1935), and
U.S. EPA (1985) are based on height and weight. The
formula developed by Costeff (1966) is based on
220 observations that estimate body surface area
based on weight only. Formulae were compared, and
the effect of the correlation between height and
weight on the body surface area distribution was
analyzed.
Monte Carlo simulations were conducted to
estimate body surface area distributions. They were
based on the bivariate distributions estimated by
Brainard and Burmaster (1992) for height and natural
logarithm of weight and the formulae described
previously. A total of 5,000 random samples each for
men and women were selected from the
two correlated bivariate distributions. Body surface
area calculations were made for each sample, and for
each formula, resulting in body surface area
distributions. Murray and Burmaster (1992) found
that the body surface area frequency distributions
were similar for the four models (see Table 7-14).
Using the U.S. EPA (1985) formula, the median
surface area values were calculated to be 1.96 m2 for
men and 1.69 m2 for women. The median value for
women is identical to that generated by U.S. EPA
(1985) but differs for men by approximately
1%. Body surface area was found to have lognormal
distributions for both men and women (see
Figure 7-1). It also was found that assuming
correlation between height and weight influences the
final distribution by less than 1%.
The advantages of this study are that it compared
the various formulae for computing surface area and
confirmed that the formula used by the U.S. EPA in
its analysis—as described in Section7.3.1.3—is
appropriate. This study is considered relevant
because the height and weight data used in this
analysis predates the height and weight data used in
the more recent U.S. EPA analysis (see
Section 7.3.1.3).
7.3.2.2. Phillips et al (1993)—Distributions of
Total Skin Surf ace Area to Body-Weight
Ratios
Phillips et al. (1993) observed a strong correlation
(0.986) between body surface area and body weight
and studied the effect of using these factors as
independent variables in the lifetime average daily
dose (LADD) equation (see Chapter 1). The authors
suggested that, because of the correlation between
these two variables, the use of body surface area-to-
body-weight (SA/BW) ratios in human exposure
assessments may be more appropriate than treating
these factors as independent variables. Direct
measurement data from the scientific literature were
used to calculate SA/BW ratios for three age groups
of the population (infants age 0 to 2 years, children
age 2.1 to 17.9 years, and adults age 18 years and
older). These ratios were calculated by dividing body
surface areas by corresponding body weights for the
401 individuals analyzed by Gehan and George
(1970) and summarized by U.S. EPA (1985).
Distributions of SA/BW ratios were developed, and
summary statistics were calculated for the three age
groups and the combined data set.
Table 7-15 presents summary statistics for both
adults and children. The shapes of these SA/BW
distributions were determined using D'Agostino's
test, as described in D'Agostino etal. (1990). The
results indicate that the SA/BW ratios for infants
were lognormally distributed. The SA/BW ratios for
adults and all ages combined were normally
distributed. SA/BW ratios for children were neither
normally nor lognormally distributed. According to
Phillips etal. (1993), SA/BW ratios may be used to
calculate LADDs by replacing the body surface area
factor in the numerator of the LADD equation with
the SA/BW ratio and eliminating the body-weight
factor in the denominator of the LADD equation.
The effect of sex and age on SA/BW distribution
also was analyzed by classifying the 401 observations
by sex and age. Statistical analyses indicated no
significant differences between SA/BW ratios for
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males and females. SA/BW ratios were found to
decrease with increasing age.
The advantage of this study is that it studied
correlations between surface area and body weight.
However, data could not be broken out by finer age
categories.
7.3.2.3. Garlock et al (1999)—Adult Responses to
a Survey of Soil Contact Scenarios
Garlock etal. (1999) reported on a survey
conducted during the summer of 1996. The objective
of the study was to evaluate behaviors relevant to
dermal contact with soil and dust. Garlock etal.
(1999) conducted computer-aided telephone
interviews designed to be nationally representative of
the U.S. population. The survey response rate was
61.4%, with a sample size of 450. Adult respondents
were asked to provide information on what they
usually wore while engaging in the following
activities during warm or cold weather: gardening,
outdoor team sports (e.g., soccer, softball, football),
and home construction projects that include digging,
as well as whether they washed or bathed following
these activities. Information also was collected on
frequency and duration of these activities (see
Chapter 16). Similar information was collected for
children's outdoor activities and is reported in Wong
etal. (2000). Using the activity-specific clothing
choices reported for each survey participant and body
surface area data from U.S. EPA (1985), Garlock
et al. (1999) estimated the percentages of adult total
body surface areas that would be uncovered for each
of the warm weather and cold weather activities (see
Table 7-16). The median ranged from 28 to 33% for
warm weather activities and 3 to 8% for cold weather
activities.
The advantages of this study are that it provides
information on the percentage of adult total surface
area that may be exposed to soil during a variety of
outdoor activities. These data represent outdoor
activities only (no data are provided for exposure to
indoor surface dusts).
7.3.2.4. Wong et al (2000)—Adult Proxy
Responses to a Survey of Children's
Dermal Soil Contact Activities
Wong et al. (2000) reported on two national
phone surveys that gathered information on activity
patterns related to dermal contact with soil. The first
(also reported on by Garlock etal., 1999) was
conducted in 1996 using random digit dialing.
Information about 211 children was gathered from
adults more than 18 years of age. For older children
(those between the ages of 5 and 17 years),
information was gathered on their participation in
"gardening and yardwork," "outdoor sports," and
"outdoor play activities." For children less than
5 years of age, information was gathered on "outdoor
play activities," including whether the activity
occurred on a playground or yard with "bare dirt or
mixed grass and dirt" surfaces. Information on the
types of clothing worn while participating in these
play activities during warm weather months (April
through October) was obtained. The results of this
survey indicated that most children wore short pants,
a dress or skirt, short sleeve shirts, no socks, and
leather or canvas shoes during the outdoor play
activities of interest. Using the survey data on
clothing and total body surface area data from
U.S. EPA (1985), estimates were made of the skin
area exposed (expressed as percentages of total body
surface area) associated with various age ranges and
activities. Table 7-17 provides these estimates.
The advantage of this study is that it provides
information on the percentage of children's bodies
exposed to soil. These data reflect exposed skin areas
during warm weather for outdoor activities only.
7.3.2.5. AuYeung et al (2008)—The Fraction of
Total Hand Surface Area Involved in
Young Children's Outdoor Hand-to-
Mouth Contacts
AuYeung etal. (2008) videotaped a total of
38 children (20 girls and 18 boys) between the ages
of 1 and 6 years while they engaged in unstructured
play activities in outdoor residential locations. The
data were reviewed, and contact information was
recorded according to the objects contacted and the
associated contact configurations (e.g., full palm
press, closed hand grip, open hand grip, side hand
contact, partial palm, fingers only). The fraction of
the hand associated with each of the various
configuration categories then was estimated for a
convenience sample of children and adults using
hand traces and handprints consistent with the
various contact configurations. Statistical
distributions of the fraction of children's total hand
surface associated with outdoor contacts were
estimated by combining the information on
occurrence and configuration of contacts from the
videotaped activity study with the data on the fraction
of the hand associated with the various contact
configurations. Table 7-18 provides the per-contact
fractional surface areas for the various types of
objects contacted and for all objects combined. For
all objects contacted, fractional surface areas ranged
from 0.13 to 0.27. AuYeung etal. (2008) suggested
that "the majority of children's outdoor contacts with
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objects involve a relatively small fraction of the
hand's total surface area."
The advantage of this study is that it provides
information on the fraction of the hand that contacts
various surfaces and objects. However, the data are
for a relatively small sample size of children (ages 1
to 6 years). Similar data for adults and older children
were not provided.
7.4. ADHERENCE OF SOLIDS TO SKIN
Several field studies have been conducted to
estimate the adherence of solids to skin. These field
studies consider factors such as activity, sex, age,
field conditions, and clothing worn. Section 7.4.1
provides information on key studies that measured
adherence of solids to skin according to specific
activities. Section 7.4.2 provides relevant
information. Relevant studies provide additional
perspective on adherence, including information on
loading per contact event and the effects of soil/dust
type, particle size, soil organic and moisture content,
skin condition, and contact pressure and duration.
This information may be useful for models based on
individual contact events.
7.4.1. Key Adherence of Solids to Skin Studies
7.4.1.1. Kissel etaL (1996a)—Field Measurements
of Dermal Soil Loading Attributable to
Various Activities: Implications for
Exposure Assessment
Kissel etal. (1996a) collected direct
measurements of soil loading on the surface of the
skin of volunteers before and after activities expected
to result in soil contact. Soil adherence associated
with the following indoor and outdoor activities were
estimated: greenhouse gardening, Tae Kwon Do,
soccer, rugby, reed gathering, irrigation installation,
truck farming, outdoor gardening and landscaping
(groundskeepers), and playing in mud. Skin-surface
areas monitored included hands, forearms, lower
legs, faces, and feet (Kissel et al., 1996a).
Table 7-19 provides the activities, information on
their duration, sample size, and clothing worn by
participants. The subjects' body surfaces (forearms,
hands, lower legs for all sample groups; faces and/or
feet in some sample groups) were washed before and
after the monitored activities. Paired samples were
pooled into single ones. The mass recovered was
converted to soil loading by using allometric models
of surface area.
Table 7-20 presents geometric means for post-
activity soil adherence by activity and body region
for the four groups of volunteers evaluated. Children
playing in the mud had the highest soil loadings
among the groups evaluated. The results also indicate
that, in general, the amount of soil adherence to the
hands is higher than for other parts of the body
during the same activity.
An advantage of this study is that it provides
information on soil adherence to various body parts
resulting from unscripted activities. However, the
study authors noted that because the activities were
unstaged, "control of variables such as specific
behaviors within each activity, clothing worn by
participants, and duration of activity was limited." In
addition, soil adherence values were estimated based
on a small number of observations, and very young
children and indoor activities were under represented.
7.4.1.2. Holmes et al (1999)—Field
Measurements of Dermal Loadings in
Occupational and Recreational Activities
Holmes etal. (1999) collected pre- and
post-activity soil loadings on various body parts of
individuals within groups engaged in various
occupational and recreational activities. These groups
included children at a daycare center ("Daycare
Kids"), children playing indoors in a residential
setting ("Indoor Kids"), individuals removing
historical artifacts from a site ("Archeologists"),
individuals erecting a corrugated metal wall
("Construction Workers"), heavy equipment
operators ("Equipment Operators"), individuals
playing rugby ("Rugby Players"), utility workers
jack-hammering and excavating trenches ("Utility
Workers"), individuals conducting landscaping and
rockery ("Landscape/Rockery"), and individuals
performing gardening work ("Gardeners"). The study
was conducted as a follow-up to previous field
sampling of soil adherence on individuals
participating in various activities (Kissel etal.,
1996a). For this round of sampling, soil loading data
were collected utilizing the same methods used and
described in Kissel et al. (1996a). Table 7-19 presents
information regarding the groups studied and their
observed activities.
The daycare children studied were all at
one location, and measurements were taken on
three different days. The children freely played both
indoors in the house and outdoors in the backyard.
Table 7-19 describes the number of children within
each day's group and the clothing worn. For the
second observation day ("Daycare Kids No. 2"),
post-activity data were collected for five children. All
the activities on this day occurred indoors. For the
third daycare group ("Daycare Kids No. 3"),
four children were studied.
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On two separate days, children playing indoors in
a home environment were monitored. The first group
("Indoor Kids No. 1") had four children while the
second group ("Indoor Kids No. 2") had six. The play
area was described by the authors as being primarily
carpeted. Table 7-19 describes the clothing worn by
the children within each day's group.
Seven individuals ("Archeologists") were
monitored while excavating, screening, sorting, and
cataloging historical artifacts from an ancient Native
American site during a single event. Eight rugby
players were monitored on two occasions after
playing or practicing rugby. Eight volunteers from a
construction company were monitored for 1 day
while erecting corrugated metal walls.
Four volunteers ("Landscape/Rockery") were
monitored while relocating a rock wall in a park.
Four excavation workers ("Equipment Operators")
were monitored twice after operation of heavy
equipment. Utility workers were monitored while
cleaning and fixing water mains, jack-hammering,
and excavating trenches ("Utility Workers") on
2 days; five participated on the 1st day and four on the
2nd. Eight volunteers ("Gardeners") ages 16 to
35 years were monitored while performing gardening
activities (i.e., weeding, pruning, digging small
irrigation trenches, picking and cleaning fruit).
Table 7-19 describes the clothing worn by these
groups.
Table 7-20 summarizes the geometric means and
standard deviations (SDs) of the post-activity soil
adherence for each group of individuals and for each
body part. According to the authors, variations in the
soil loading data from the daycare participants reflect
differences in the weather and access to the outdoors.
An advantage of this study is that it provides a
supplement to soil-loading data collected in a
previous round of studies (Kissel et al., 1996a). Also,
the data support the assumption that hand loading can
be used as a conservative estimate of soil loading on
other body surfaces for the same activity. The
activities studied represent normal child play both
indoors and outdoors, as well as different
combinations of clothing. The small number of
participants is a disadvantage of this study. Also, the
children studied and the activity setting may not be
representative of the U.S. population.
7.4.1.3. Shoafetal (2005)—Child Dermal
Sediment Loads Following Play in a Tide
Flat
The purpose of the Shoaf et al. (2005) study was
to obtain sediment adherence data for children
playing in a tidal flat ("Shoreline Play"). The study
was conducted 1 day in late September 2003 at a tidal
flat in Jamestown, RI. A total of nine subjects
(three females and six males) ages 7 to 12 years
participated in the study. Table 7-19 presents
information on activity duration, sample size, and
clothing worn by participants. Participants' parents
completed questionnaires on their child's typical
activity patterns during tidal flat play, exposure
frequency and duration, clothing choices, bathing
practices, and clothes laundering.
This study reported direct measurements of
sediment loadings on five body parts (face, forearms,
hands, lower legs, and feet) after play in a tide flat.
Each of nine subjects participated in two timed
sessions, and pre- and post-activity sediment loading
data were collected. Geometric mean (geometric
standard deviations) dermal loadings (mg/cm2) on the
face, forearm, hands, lower legs, and feet for the
combined sessions, as shown in Table 7-20, were
0.04 (2.9), 0.17 (3.1), 0.49 (8.2), 0.70 (3.6), and 21
(1.9), respectively. Event duration did not appear to
be associated with sediment loading on the skin.
The primary advantage of this study is that it
provides adherence data specific to children and
sediments, which previously had been largely
unavailable. Results will be useful to risk assessors
considering exposure scenarios involving child
activities at a coastal shoreline or tidal flat. The
limited number of participants (nine) and sampling
during just 1 day and at one location, make
extrapolation to other situations uncertain.
7.4.2. Relevant Adherence of Solids to Skin
Studies
7.4.2.1. Harger (1979) A Model for the
Determination of an Action Level for
Removal ofCurene Contaminated Soil
U.S. EPA (1987, 1988, 1992b) reported on
experimental values for (soil-related) dust adherence
as estimated by Harger (1979). According to
U.S. EPA (1992b), "these estimates are based on
unpublished experiments by Dr. Rolf Hartung
(University of Michigan) as reported in a 1979
memorandum from J. Harger to P. Cole (both from
Michigan Toxic Substance Control Commission in
Lansing, MI). According to this memo, Dr. Hartung
measured adherence using his own hands and found:
2.77 mg/cm2 for kaolin with a SD of 0.66 and N = 6;
1.45 mg/cm2 for potting soil with SD = 0.36 and
7V= 6; and 3.44 mg/cm2 for sieved vacuum cleaner
dust (mesh 80) with SD = 0.80 and N = 6. The details
of the experimental procedures were not reported.
Considering the informality of the study and lack of
procedural details, the reliability of these estimates
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cannot be evaluated." Accordingly, these data are not
considered to be key for the purpose of developing
recommendations for soil adherence to the skin.
7.4.2.2. Que Hee et al. (1985)—Evolution of
Efficient Methods to Sample Lead
Sources, Such as House Dust and Hand
Dust, in the Homes of Children
Que Hee etal. (1985) used house dust having
particle sizes ranging from 44 to 833 um in diameter,
fractionated into six size ranges, to estimate the
amount that adhered to the palm of the hand of a
small adult. The amount of dust that adhered to skin
was determined by applying approximately 5 grams
of dust for each size fraction, removing excess dust
by shaking the hands, and then measuring the
difference in weight before and after application. Que
Hee etal. (1985) found no relationship between
particle size and adherence for house dusts with
particle sizes <246 um. For all six particle sizes, an
average of 63 ± 42 percent of applied dust adhered to
the palm of the hand. This represents 31.2 ± 16.6 mg
of soil. Excluding the two largest size fractions,
58 ±_29% of the applied dust adhered to the hand,
representing 28.9 ± 1.9 mg.
The limitation of these data is that they were
based on one adult hand and a single house dust
sample. Also, the data are for hands only and are not
linked to specific activities.
7.4.2.3. Driver et al (1989)—Soil Adherence to
Human Skin
Driver etal. (1989) conducted experiments to
evaluate the conditions that may affect soil adherence
to the skin of adult hands. Both top soils and subsoils
of five soil types (Hyde, Chapanoke, Panorama,
Jackland, and Montalto) were collected from sites in
Virginia. The organic content, clay mineralogy, and
particle size distribution of the soils were
characterized, and the soils were dry sieved to obtain
particle sizes of <250 um and <150 um. For each soil
type, the amount of soil adhering to adult male hands
when using both sieved and unsieved soils was
determined gravimetrically (i.e., measuring the
difference in soil sample weight before and after soil
application to the hands). An attempt was made to
measure only the minimal or "monolayer" of soil
adhering to the hands. This was done by mixing a
preweighed amount of soil over the entire surface
area of the hands for a period of approximately
30 seconds, followed by removing excess soil by
gently rubbing the hands together after contact with
the soil. Excess soil that was removed from the hands
was collected, weighed, and compared to the original
soil sample weight. Driver etal. (1989) measured
average adherence of 1.40 mg/cm2 for particle sizes
less than 150 um, 0.95 mg/cm2 for particle sizes less
than 250 um, and 0.58 mg/cm2 for unsieved soils.
Analysis of variance statistics showed that the most
important factor affecting adherence variability was
particle size (p < 0.001). The next most important
factor was soil type and subtype (p < 0.001), but the
interaction of soil type and particle size also was
significant (p < 0.01).
Driver etal. (1989) found statistically significant
increases in soil adherence with decreasing particle
size, whereas Que Hee etal. (1985) found that
different size particles of house dust <246 um
adhered equally well to hands.
The advantages of this study are that it provides
additional perspective on the effects of particle size
on adherence and that it evaluated several different
soil types. However, it is based on data for hands
only for a limited number of experimental
observations (i.e., one subject). Also, the data are not
activity based.
7.4.2.4. Sedman (1989)—The Development of
Applied Action Levels for Soil Contact: A
Scenario for the Exposure of Humans to
Soil in a Residential Setting
Sedman (1989) used estimates from Lepow et al.
(1975), Roels et al. (1980), and Que Hee et al. (1985)
to develop a maximum soil load that could occur on
the skin. Lepow etal. (1975) estimated that
approximately 0.5 mg of soil adhered to 1 cm2 of
skin. Roels et al. (1980) estimated that 159 mg of soil
adhered to the hand of an 11-year-old child.
Assuming that approximately 60% (185 cm2) of the
surface area of the hand was sampled, the amount of
soil adhering per unit area of skin was estimated to be
0.9 mg/cm2. Que Hee etal. (1985) estimated that
approximately 31.2 mg of housedust adhered to the
palm of a small adult. Assuming a hand surface area
of 160 cm2, Sedman (1989) estimated a soil loading
of 0.2 mg/cm2. A rounded arithmetic mean of
0.5 mg/cm2 was calculated from these three studies.
According to Sedman (1989), this was near the
maximum load of soil that could occur on the skin,
but it is unlikely that most skin surfaces would be
covered with this amount of soil (Sedman, 1989).
This study is considered relevant and not key
because it does not provide any new data, but uses
data from other studies and various assumptions to
estimate soil adherence.
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7.4.2.5. Finley et al. (1994)—Development of a
Standard Soil-to-Skin Adherence
Probability Density Function for Use in
Monte Carlo Analyses of Dermal
Exposure
Using data from several existing studies, Finley
etal. (1994) developed probability density functions
of soil-to-skin adherence. Finley etal. (1994)
reviewed studies that estimated adherence among
adults and children based on various gravimetric and
hand wiping/rinsing methods. Several of these studies
were originally conducted for the purpose of
estimating lead exposure from soil contact. By
combining data from four studies (Charney etal.,
1980; Roels etal., 1980; Gallacher etal., 1984; and
Duggan et al.; 1985), Finley et al. (1994) estimated a
mean± standard deviation soil adherence value for
children of 0.65 ± 1.2 mg soil/cm2-skin. (50th
percentile = 0.36 and 95th percentile = 2.4 mg
soil/cm2-skin). Using data from three studies
(Gallacher etal., 1984; Que Hee etal., 1985; and
Driver etal., 1989), Finley etal. (1994) estimated a
mean± standard deviation soil adherence value for
adults of 0.49 ± 0.54 mg soil/cm2-skin.
(50th percentile = 0.06 and 95th percentile = 1.6 mg
soil/cm2-skin). Because the distributions of
soil-to-skin adherence were similar for children and
adults, Finley etal. (1994) developed a probability
density function based on the combined data for
children and adults. The probability density function
is lognormally distributed with a mean± standard
deviation of 0.52 ± 0.9 mg soil/cm2-skin
(50th percentile = 0.25 and 95th percentile = 1.7 mg
soil/cm2-skin).
The advantage of this study is that it provides
distributions of soil adherence for children, adults,
and children and adults combined. However, it is
based on some older, relevant studies that are not
activity- or body-part specific.
7.4.2.6. Kissel et al (1996b)—Factors Affecting
Soil Adherence to Skin in Hand-Press
Trials: Investigation of Soil Contact and
Skin Coverage
Kissel etal. (1996b) conducted soil adherence
experiments to evaluate the effect of particle size and
soil moisture content on adherence to the skin.
Five soil types were obtained in the Seattle, WA, area
(sand, two types of loamy sand, sandy loam, and silt
loam) and were analyzed to determine composition.
Clay content ranged from 0.5 to 7.0%, and organic
carbon content ranged from 0.7 to 4.6%. Soils were
dry-sieved to obtain particle size ranges of <150,
150-250, and >250 um. For each soil type, the
amount of soil adhering to an adult female hand when
using both sieved and unsieved soils was determined
by measuring the soil sample weight before and after
the hand was pressed into a pan containing the test
soil. Loadings were estimated by dividing the
recovered soil mass by the total surface area of
one hand, although loading occurred primarily on
only one side of the hand. Results showed that
generally, soil adherence to hands was directly
correlated with moisture content, inversely correlated
with particle size, and independent of clay content or
organic carbon content. For dry soil, mean adherence
was the lowest for the largest particle sizes (i.e.,
>250 um) of dry soil (0.06 to 0.34 mg/cm2) and
highest for the smallest particle sizes (0.42 to
0.76 mg/cm2). Adherence values based on moisture
content ranged from 0.22 to 0.54 mg/cm2 for soils
with moisture contents of 9% or less, 0.39 to
3.09 mg/cm2for soils with moisture contents of 10 to
19%, and 1.64 to 14.8 mg/cm2 for soils with moisture
contents of 21 to 27%.
The advantage of this study is that it provides
information on how soil type can affect adherence to
the skin. However, the soil adherence data are for a
single subject, and the data are limited to five soil
samples.
7.4.2.7. Holmes et al. (1996)—Investigation of the
Influence of Oil on Soil Adherence to
Skin
Holmes etal. (1996) conducted experiments to
evaluate differences in adherence of soil to skin based
on soil type, moisture content, and the presence of oil
(i.e., petroleum contaminants) in the soil. Three soil
types (loamy sand, silt loam, and sand) treated with
three concentrations (0, 1, and 10%) of motor oil
were used, and the experiments were conducted
under wet and dry soil conditions. A single subject
pressed the right hand, palm down, into a pan
containing soil. The soil adhering to the hand was
collected by washing and then weighed. For dry soil
containing no oil, adherence values ranged from
0.29 mg/cm2 for sandy soil to 0.59 mg/cm2 for silt
loam. For wet soil containing no oil (13 to
15% moisture), adherence values were 0.25 mg/cm2
for silt loam, 1.6 mg/cm2 for sand, and 3.7 mg/cm2
for loamy sand. According to Holmes etal. (1996),
"high concentrations of petroleum contaminants can
increase the dermal adherence of soil, but the
magnitude of the effect is likely to be modest."
The advantage of this study is that it provides
additional perspective on the factors that affect soil
adherence to skin. However, it is based on limited
observations (i.e., one subject) for only the hand
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under experimental conditions (i.e., not
activity-based).
7.4.2.8. Kissel et al (1998)—Investigation of
Dermal Contact with Soil in Controlled
Trials
Kissel etal. (1998) measured dermal exposure to
soil from staged activities conducted in a greenhouse.
A fluorescent marker was mixed in soil so that soil
contact for a particular skin surface area could be
identified. The subjects were video-imaged under a
long-wave ultraviolet (UV) light before and after soil
contact. In this manner, soil contact on hands,
forearms, lower legs, and faces was assessed by
presence of fluorescence. In addition to fluorometric
data, gravimetric measurements for pre-activity and
post-activity were obtained from the different body
parts examined. The studied groups included adults
transplanting 14 plants for 9 to 18 minutes, children
playing for 20 minutes in a soil bed of varying
moisture content representing wet and dry soils, and
adults laying plastic pipes for 15, 30, or 45 minutes.
Table 7-21 summarizes the parameters describing
each of these activities. Before each trial, each
participant was washed to obtain a preactivity or
background gravimetric measurement.
For wet soil, post-activity fluorescence results
indicated that the hand had a much higher fractional
coverage than other body surfaces (see Figure 7-2).
As shown in Figure 7-3, post-activity gravimetric
measurements for children playing and adults
transplanting showed higher soil loading on hands
and much lower soil loading on other body surfaces.
This also was observed in adults laying pipe. The
arithmetic mean percent of hand surface area
fluorescing was 65% after 15 minutes laying pipe in
wet soil and 85% after 30 and 45 minutes laying pipe
in wet soil. The arithmetic mean percent of lower leg
surface area fluorescing was -20% after 15 minutes
of laying pipe in wet soil, 25% after 30 minutes, and
40% after 45 minutes. According to Kissel et al.
(1998), the relatively low loadings observed on
non-hand body parts may be a result of a more
limited area of contact for the body part rather than
lower localized loadings. Kissel etal. (1998)
observed geometric means of up to about 3 mg/cm2
on adults' hands after the 30-minute pipelaying
activity with wet soil. After children played and
adults transplanted in wet soil, geometric mean soil
loadings were 0.7 and 1.1 mg/cm2, respectively.
Mean loadings were lower on hands in the dry soil
trial and on lower legs, forearms, and faces in both
the wet and dry soil trials. Higher loadings were
observed for all body surfaces with the higher
moisture content soils.
This report is valuable in showing soil loadings
from soils of different moisture content and providing
evidence that dermal exposure to soil is not uniform
for various body surfaces. This study also provides
some evidence of the protective effect of clothing.
Disadvantages of the study include the small number
of study participants and the short activity duration.
7.4.2.9. Rodes et al. (2001)—Experimental
Methodologies and Preliminary Transfer
Factor Data for Estimation of Dermal
Exposure to Particles
Rodes etal. (2001) conducted a study using the
fluorescein-tagged Arizona Test Dust (ATD) as a
surrogate for house dust and evaluated particle mass
transfer from surfaces to the human skin of three test
subjects (one female and two males). Transfers to wet
and dry skin from stainless steel, vinyl, and carpeted
surfaces that had been preloaded with tagged ATD
were quantified. For carpets, experiments were
conducted in which particles were either embedded in
the carpet fibers or not embedded. Particles were
embedded into carpet by dragging a steel cylinder
across the carpet after loading. Controlled hand
(palm) press experiments were conducted, and the
amount of tagged ATD that had transferred to the skin
of the palm was measured using fluorometry. Surface
loadings that represented typical indoor conditions
were used in the study. Rodes etal. (2001) used
defined dust fractions (<80 um) to evaluate the
influence of particles size on transfer. For the
experiments with wet hands, a surrogate saliva
solution was used. The portion of the hand that
contacted the material also was estimated.
Dermal transfer factors were calculated as the
mass of particles on the hand (ug on hand/cm2 of
dermal contact area) divided by the mass of particles
on the surface contacts (ug on surface/cm2 of surface
contact). Table 7-22 shows the dermal transfer factors
(based on the mean of left and right hand presses) for
the various surface types and hand moisture contents.
The results indicate that for dry hands, transfer from
smooth surfaces (i.e., stainless steel) was higher than
for other materials (58.2 to 76.0%; mean = 69 + 9%).
Skin moisture content was shown to be a critical
factor in the proportion of particles to transfer (wet
hands resulted in 100% transfer from stainless steel).
As surface roughness increased, transfer tended to
decrease, with carpet surfaces having the lowest
transfer factors (3.4 to 16.9%). Embedding particles
into the carpet significantly reduced particle transfer.
Rodes etal. (2001) also observed that "only about
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l/3rd of the projected hand surface typically came in
contact with the smooth test surfaces during a
press....[and] consecutive presses decreased the
particle transfer by a factor of three as the skin
became loaded, requiring -100 presses to reach an
equilibrium transfer rate."
The advantage of this study is that it evaluated
particle transfer for a variety of surface types and
skin conditions. However, a small number of subjects
were involved in the study, and Rodes etal. (2001)
suggested that when using these data, the similarities
and differences in characteristics between ATD and
real house dust should be considered.
7.4.2.10. Edwards andLioy (2001)—Influence of
Sebum and Stratum Corneum Hydration
on Pesticide/Herbicide Collection
Efficiencies of the Human Hand
Edwards and Lioy (2001) studied the effects of
sebum/sweat and skin hydration on the transfer of
pesticide residues in dust to the hands. Under normal
conditions, the skin on the hand is covered by a layer
of sebum, a mixture of lipids secreted from the
sebaceous glands, and sweat that is secreted from
sweat ducts. Edwards and Lioy (2001) measured the
levels of sebum and moisture on the palm of the hand
of one subject prior to conducting hand press
experiments using house dust treated with a mixture
of four pesticides (atrazine, diazinon, malathion, and
chlorpyrifos). The house dust sample was obtained
from vacuum cleaner bags and was sieved to
<250 um. The dust was settled onto the sample
surfaces and sprayed with the pesticide mixture, and
the subject pressed one hand to the surface in a series
of trials conducted approximately 1 week apart. The
hand was rinsed with solvent to extract any
transferred pesticide/dust, and the solution was
analyzed for pesticide residues. Transfer efficiencies
(percentage) were calculated as the concentration of
residues measured in the hand rinse solution divided
by the concentration of pesticide on the sampling
surface times 100. The results of this study indicated
that the transfer efficiencies of two pesticides in dust
were negatively correlated with sebum levels (i.e.,
increased sebum levels resulted in a 13% reduction in
atrazine transfer and an 8% reduction in malathion
transfer) and transfer efficiencies of two pesticides in
dust were negatively correlated with skin hydration
(i.e., increased skin moisture resulted in a
7% reduction in diazinon transfer and 5% reduction
in chlorpyrifos transfer; Edwards and Lioy, 2001).
The advantage of this study is that it provides
additional perspective on factors that can affect
adherence of solids to the skin. However, it is
considered relevant and not key because the transfer
of dust was studied for the hands only and used
experimental conditions not based on
exposure-related activities.
7.4.2.11. Choateetal (2006)—Dermally Adhered
Soil: Amount and Particle Size
Distribution
Choate etal. (2006) investigated the soil
characteristics that affect particle adherence to human
skin. The factors considered included particle size,
organic carbon content, and soil moisture. Day-to-day
variability and differences based on whether or not
hands were washed before contacting the soil also
were examined. A total of 108 subjects (1/3 female)
between 18 and 30 years of age participated in one or
more of a series of soil adherence experiments. Some
of the experiments were conducted using clay loam
soil collected in Colorado, while others were
conducted using silty-clay loam soil collected in
Iowa. Soil moisture contents ranged from 1 to 10%.
Choate et al. (2006) used either preweighed adhesive
tape or hand washing with distilled water to remove
and collect soil that had adhered to the palm of
subjects' hands after contact with bulk soil under
controlled experimental conditions. Removed soil
was weighed, and the mass of soil per area of skin
surface was calculated for each sample.
Based on the adhesive tape tests, an average of
0.7 mg/cm2 of the Colorado soil adhered to the hand
(TV = 6 subjects each sampled using the right or left
hand on 10-12 study days). There were no significant
differences between the left and right hands, but there
were "large average variabilities . . . both between
subjects on a given day (±52%) and for an individual
subject on different days (±50%)." Differences
between soil adherence to hands that had or had not
been washed prior to soil contact were observed, with
hand washing resulting in a lower mean adherence
value (0.51 mg/cm2; TV =76) than non-washing
(1.1 mg/cm2; TV =72), when soil with a moisture
content of 4.7% was used. The authors suggested that
this is "probably due to the removal [during washing]
of oils from the skin that aid in the adherence of soil
particles." Soil adherence for the two types of soils
(i.e., from Colorado and Iowa) with low moisture
content (i.e., <2%) averaged 0.64 and 0.69 mg/cm2,
compared to 1.47 and 1.36 mg/cm2 for those with
high moisture content (9% to 10%). Large particle
fractions of the soils with higher moisture content
adhered more readily than those in soils with low or
medium moisture content. The "adhered fractions of
dry or moderately moist soils with wide distribution
of particle sizes generally consisted] of particles of
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diameters <63 um." The organic carbon content of
the soils did not appear to be an important contributor
to soil adherence.
The advantage of this study is that it provides
additional perspective on factors that affect soil
adherence to skin by using a larger number of
subjects compared to some of the earlier studies.
However, the data are based only on controlled
experimental conditions and may not be
representative of the specific types of activities in
which dermal exposure may occur.
7.4.2.12. Yamamoto et al. (2006)—Size Distribution
of Soil Particles Adhered to Children's
Hands
Yamamoto etal. (2006) conducted both
laboratory and field experiments that showed finer
soil particles adhered more readily to children's
hands than coarse particles. In the laboratory,
one female subject pressed her hand into a tray
containing reference soil. Her hand then was washed
in ultrapure water that was analyzed to determine the
size distributions and the amount of soil that had
adhered to the hand. Yamamoto etal. (2006)
observed that the mode diameter of soil adhering to
the hand (22.8 ± 0.0 urn) was less than that of the
reference soil (36.9 ± 4.9 um), indicating that finer
particles adhered more efficiently to the hand. The
effect of hand moisture was tested by moistening the
hand prior to pressing it onto the tray of soil.
Yamamoto etal. (2006) observed that while the
amount of soil that adhered to the hand increased
with hand moisture, the size distributions were not
greatly changed.
A separate field experiment was conducted in
which ten 4-year-old children (five males and
five females) attending a nursery school in Japan
participated. After playing in the playground and
sandbox for a morning or afternoon, the children's
hands were washed in bottles containing 500 mL
ultrapure water, and aliquots of the water were
analyzed to determine the size distributions and
amounts of particles that had adhered to the hands.
The particles sizes of soil samples collected from the
children's playing area (i.e., playground, field, and
sandbox) also were analyzed. The mean, median, and
maximum amounts of soil adhering to the children's
hands were 26.2, 15.2, and 162.5 mg/hand,
respectively. Assuming a surface area of the hand of
210cm2, the amounts are equivalent to 0.125, 0.73,
and 0.774 mg/cm2, respectively. Compared to the soil
in the children's play area, the soil adhering to the
children's hands was composed primarily of the finer
particles.
The advantage of this study is that both laboratory
and field measurements were used to evaluate
particle sizes of soil that adheres to the hands.
However, only one subject participated in the
laboratory study, and the children's activities in the
field portion were not indexed to the amount of time
spent performing soil contact activities.
7.4.2.13. Ferguson et al. (2008, 2009a, b, c)—Soil-
Skin Adherence: Computer-Controlled
Chamber Measurements
Ferguson et al. (2008, 2009a, b, c) conducted a
series of soil adherence experiments by using a
mechanical chamber designed to control and measure
pressure and time of contact with surfaces loaded
with soil. Adherence of play sand and lawn soil to
human cadaver skin and cotton sheet samples was
measured after contact with either loaded carpet or
aluminum surfaces. Multiple pressure levels (20 to
50 kPa), durations of contact (10 to 50 seconds), and
particle sizes (<139.7 um and >139.7 to <381.0 um)
were evaluated (Ferguson etal., 2008, 2009a, b).
Also, both single- and multiple-contact experiments
were conducted (Ferguson etal., 2009c). Soil
adherence was estimated by weighing the carpet or
aluminum samples loaded with play sand or lawn soil
both before and after controlled contacts occurred
and calculating the weight differences. Each
experiment, using different combinations of pressure,
contact duration, particle size, soil type, surface, and
contact material, was repeated multiple times.
Table 7-23 presents a comparison of the adherence
values for contact with carpet and aluminum
surfaces. Mean soil to skin adherence from contact
with aluminum surfaces (1.18 mg/cm2) was higher
than from carpet (0.71 mg/cm2). In general, soil
transfer increased as pressure increased, and contact
durations of 30 seconds or more did not appear to
result in higher adherence. For carpets, larger particle
size was associated with higher adherence, while
smaller particle size was associated with higher
adherence from aluminum (Ferguson et al., 2009b),
Based on a comparison of data from experiments
with multiple contacts, Ferguson et al. (2009c) found
that, "on average, 8% of the original transfer amount
will transfer during a second contact. Therefore,
attaching a soil/adherence transfer of the original
magnitude for every contact may result in
overestimates for exposure."
The advantages of these studies are that they
provide data from controlled experiments in which a
variety of conditions were tested. However, a single
carpet type was used, and transfer may differ based
on carpet type. Also, adherence may be different for
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different types of soil or house dust, as well as for
different skin types and conditions. Differences in the
nature of contact and the initial surface soil loadings
also may affect adherence.
7.5. FILM THICKNESS OF LIQUIDS ON
SKIN
Information on the thickness of liquids on human
skin is sometimes used to estimate dermal exposure
to contaminants in liquids that come into contact with
the skin. For example, these data are used to estimate
exposure to consumer products in U.S. EPA's
Exposure and Fate Assessment Screening Tool
(EFAST; Versar, 2007). Section 7.5.1 provides the
available data on film thickness of liquids on the
skin. However, these data are limited; therefore,
studies related to this factor have not been
categorized as key or relevant in this chapter, and
specific recommendations are not provided for this
factor.
7.5.1. U.S. EPA (1987)—Methods for Assessing
Consumer Exposure to Chemical
Substances; and U.S. EPA (1992c)—A
Laboratory Method to Determine the
Retention of Liquids on the Surface of
Hands
U.S. EPA (1987, 1992c) reported on experiments
that were conducted to measure the retention of
liquids on hands after contact with six different types
of liquids (mineral oil, cooking oil, water soluble
bath oil, 50:50 oil/water emulsion, water, and
50:50 water ethanol). These liquids were selected
because they were non-toxic and represented a range
of viscosities and likely retention on the hands.
Five exposure conditions were tested to simulate
activities in which consumers' hands may be exposed
to liquids, including (1) contact with dry skin (initial
contact), (2) contact with skin previously exposed to
the liquid and still wet (secondary contact),
(3) immersion of a hand into a liquid, (4) contact
from handling a wet rag, and (5) contact during spill
cleanup. For the initial contact scenario, a cloth
saturated with liquid was rubbed over the front and
back of both clean, dry hands for the first time during
an exposure event. For the secondary contact
scenario, a cloth saturated with liquid was rubbed
over the front and back of both hands for a
second time, after as much as possible of the liquid
that adhered to skin during the first contact event was
removed using a clean cloth. For the immersion
scenario, one hand was immersed in a container of
liquid and then removed; the liquid was allowed to
drip back into the container for 30 seconds
(60 seconds for cooking oil). For the scenario
involving the handling of a rag, a cloth saturated with
liquid was rubbed over the palms of both hands in a
manner simulating handling of a wet cloth. For the
spill cleanup scenario, a subject used a clean cloth to
wipe up 50 mL of liquid poured onto a plastic
laminate countertop. For each of the five scenarios,
retention was measured immediately after applying
the liquid to the hands and after partial and full
removal by wiping. Partial wiping was defined as
"lightly [wiping with a removal cloth] for 5 seconds
(superficially)." Full wiping was defined as
"thoroughly and completely as possible within
10 seconds removing as much liquid as possible."
Four human subjects were used in the experiments,
and multiple replicates (four to six) were conducted
for each subject and type of liquid and exposure
condition. Retention of liquids on the skin was
estimated by taking the difference between the
weight of the cloth(s) before and after wiping and
dividing by skin surface area. For the immersion
scenario, retention was estimated as the weight
difference in the immersion container before and
after immersion. Film thickness (cm) was estimated
as the amount of liquid retained on the skin (g/cm2)
divided by the density of the liquid (g/cm3) used in
the experiment.
Table 7-24 presents the estimated film thickness
data from these experiments. Film thickness data may
be used with information on the density of a liquid
and the weight fraction of the chemical in the liquid
to estimate the amount of contaminant retained on the
skin (i.e., amount retained on skin [g/cm2] = film
thickness of liquid on skin [cm] x density of liquid
[g/cm3] x weight fraction [unitless]). Dermal
exposure (g/event) may be estimated as the amount
retained on the skin (g/cm2) times the skin surface
area exposed (cm2/event).
The advantage of this study is that it provides data
for a factor for which information is very limited.
Data are provided for various types of liquids under
various conditions. However, the data are based on a
limited number of observations and may not be
representative of all types of exposure scenarios.
7.6. RESIDUE TRANSFER
Several methods have been developed to quantify
rates of residue transfer to the human skin of
individuals performing activities on treated surfaces.
These methods have been used to either develop
transfer efficiencies or estimate residue transfer
coefficients. Transfer efficiencies are the fraction (or
percentage) of surface residues transferred to the
skin. Transfer coefficients (cm2/hour) represent the
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ratio of the dermal exposure during a specified time
period (mg/hour) based on a specific exposure
activity (e.g., harvesting a crop or performing indoor
or outdoor activities) to the environmental
concentration of the pesticide (mg/cm2). Transfer
coefficients are estimated in studies in which
environmental residue levels are measured
concurrently with exposure levels for particular job
functions or activities. These studies have been
conducted primarily for the purpose of estimating
exposure to pesticides. Exposure levels are typically
measured using dosimeter clothing that is worn by
study subjects during the conduct of specific
activities and then removed and analyzed for
pesticide residues. Sometimes biomonitoring studies
(i.e., urine analyses) or other methods (e.g., hand
wash) are used to estimate exposure levels.
Environmental residues are estimated using various
techniques, including use of deposition coupons,
wipe samples, or a residue collection tool such as a
"drag sled" or roller on indoor or outdoor surfaces, as
described in U.S. EPA (1996).
Although chemical-specific transfer coefficients
are typically preferred for estimating exposure,
U.S. EPA (2009) has used data from published and
unpublished residue transfer studies to develop some
generic activity-specific transfer coefficient
assumptions to use in exposure assessments when
chemical-specific data are unavailable. Use of these
generic transfer coefficients for pesticides is based on
the assumption that the transfer of residues to human
skin is based primarily on the types of activities being
performed rather than on the specific characteristics
of the pesticide. This section presents data for
published residue transfer studies only (i.e.,
unpublished data are not included here).
A transfer coefficient, expressed in units of
cm2/hour, is used to estimate exposure to chemical
residues by combining it with the environmental
concentration (in units of mg/cm2) and an exposure
time in hours/days (e.g., exposure [mg/day] = transfer
coefficient [cm2/hour] x environmental concentration
[mg/cm2] x exposure time [hours/day]). When using
transfer co-efficients, it is important to ensure that the
residue levels used are consistent with the method for
developing the transfer coefficient (e.g., residue
levels based on deposition coupons should be used
with transfer co-efficients based on deposition
coupons; residue levels based on a residue collection
tool such as the California Roller should be used with
transfer coefficients based on the same type of tool).
Information on methods that may be used to estimate
transferable residues from indoor surfaces and
dislodgeable residues from turf may be found in Hsu
etal. (1990), Geno etal. (1996), Camann etal.
(1996), Fortune (1998a, b), and Fortune et al. (2000).
U.S. EPA (2009) describes the use of generic transfer
coefficients for a variety of activities involving
pesticides. Section 7.6.1 discusses the published data
on transfer efficiencies and transfer coefficients
gathered from the scientific literature. Because
residue transfer depends on the specific conditions
under which exposure occurs (e.g., activity, contact
surfaces, age), the studies described in Section 7.6.1
have not been categorized as key or relevant, and
specific recommendations are not provided for this
factor.
7.6.1. Residue Transfer Studies
7.6.1.1. Ross et al (1990)—Measuring Potential
Dermal Transfer of Surface Pesticide
Residue Generated from Indoor Fogger
Use: An Interim Report
Ross et al. (1990) utilized choreographed exercise
routines to measure the amount of pesticide residues
that may be transferred from carpets to adult skin.
Five adult volunteers wore dosimeter clothing (i.e.,
cotton tight, shirt, gloves, and socks) over the skin
areas that normally would be exposed and conducted
exercise routines for 18.2 minutes in hotel rooms
where pesticides (i.e., chlorpyrifos and d-trans-
allethrin) were applied (20 minutes total exposure to
account for entry and exit from the treated rooms).
The exercise routines were performed at times
ranging from 0 to 13 hours after pesticide application.
The routines included "substantial body contact
between the subject and treated carpet" and were
"intended to represent a person's day-long
(16 hours]) contact with pesticide-treated surfaces in
a home in which a total discharge fogger had been
used" (Kreiger etal., 2000). The dosimeter clothing
was assumed to retain the same amount of pesticide
as the skin (Kreiger et al., 2000). It was collected and
analyzed for pesticide residues to estimate the
amount of residues that had been transferred from the
carpet the skin. Environmental concentrations of the
pesticides were measured in the rooms where the
exercise routines took place by using gauze coupons
placed in the rooms prior to pesticide application.
Ross etal. (1990) found that the transfer of
pesticides (i.e., potential dermal exposure) differed
according to the body part exposed and declined with
time after pesticide application with a rapid decline in
pesticide transfer between 6 and 12 hours. Some of
the possible factors attributed to this decline were
loss of formulation inerts, absorption by or
adsorption to the carpet, breakdown to non-detected
materials, downward migration into non-contact
areas of the carpet or adsorption to dust particles, and
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volatilization. Table 7-25 provides the mean transfer
efficiencies (i.e., percent of pesticide residues
transferred to the various body parts from carpet),
based on the time after application. These
percentages represent the clothing residues divided
by the environmental concentrations—based on
deposition coupons—times 100 (Ross etal., 1990).
The study demonstrated the efficacy of using
choreographed activities to estimate pesticide residue
transfer. A limitation of this study is that the exercise
routines used may not be representative of other
types of indoor activities.
7.6.1.2. Ross et al (1991)—Measuring Potential
Dermal Transfer of Surface Pesticide
Residue Generated from Indoor Fogger
Use: Using the CDF A Roller Method:
Interim Report II
Ross etal. (1991) reported on the use of the
California Food and Drug Administration (CDFA)
roller to estimate pesticide transfer from carpet. This
study was conducted in parallel with the Ross et al.
(1990) study. The roller device was tested as a
surrogate for human subjects for measuring residue
transfer from indoor surfaces. The roller was a 12-kg,
foam-covered rolling cylinder equipped with
stationary handles. A cotton cloth covered with
plastic was placed over a pesticide-treated carpet, and
the device was rolled over it 10 times. The cloth then
was collected and analyzed for pesticide residues.
Environmental residue levels were measured using
gauze coupons placed on the carpet prior to pesticide
application. Mean gauze dosimeter residues were
compared to the amount of material transferred to the
roller sheet. The results showed that the carpet roller
method transferred 1 to 3% of carpet residue to the
roller sheet. As in the 1990 study, pesticide
transferability decreased with time and with contact
with the treated surface. Using the data from Ross
etal. (1990), which involved the collection of
pesticide residues on dosimeter clothing worn by
human subjects who engaged in choreographed
exercise routines, and the roller data from this study,
Ross etal. (1991) calculated residue transfer
coefficients as the total ug of residues transferred to
dosimetry clothing times hours of exposure/ug/cm2
residue transferred to the roller sheet. Mean transfer
coefficients were 200,000 ± 50,000 cm2/hr for
chlorpyrifos and 140,000 ± 30,000 cm2/hr for d-trans
allethrin. Ross et al. (1991) concluded that the use of
a carpet roller was a good surrogate for measuring
residue transfer.
A limitation of this study is that transfer of
surface residues from the carpet to CDFA roller may
not be representative of transfer of residues based on
various human activities.
7.6.1.3. Formoli (1996)—Estimation of Exposure
of Persons in California to Pesticide
Products that Contain Propetamphos
Formoli (1996) conducted a study to estimate
exposure to propetamphos that was applied to
carpets. Five adult subjects (two men and
three women) wore whole body dosimeters and
performed structured exercise routines for 20 minutes
on the treated carpet. The subjects' clothing was cut
up and analyzed for pesticide residues. Transferable
residues also were collected from the carpet by
moving a roller device over cotton cloth that was
subsequently analyzed for pesticide residues. Using
the dermal exposure data from the dosimeters and the
transferable residue data from the roller device,
Formoli (1996) calculated a transfer coefficient of
43,800 cm2/hr.
These data are useful because they provide
perspective on residue transfer data based on
controlled experimental conditions. However, the
limitations of this study are that the exercise routines
used may not be representative of all types of
activities in which transfer of surface residues occurs,
and the data are based on a single pesticide and a
limited number of observations.
7.6.1.4. Krieger et al. (2000)—Biomonitoring and
Whole Body Dosimetry to Estimate
Potential Human Dermal Exposure to
Semi-Volatile Chemicals
Krieger et al. (2000) conducted a study similar to
the Ross etal. (1990, 1991) studies. The purpose of
the Kreiger etal. (2000) study was to compare
dermal exposure estimated by four different methods.
The methods included (1) measurement of residues
deposited onto foil coupons that had been placed on
the carpet prior to pesticide application;
(2) measurement of residues transferred to cotton
cloth using the CDFA roller method, as described by
Ross etal. (1991); (3) measurement of residues
transferred to whole body cotton dosimeters during
structured exercise routines; and (4) analysis of
biomonitoring (urine) from subjects who participated
in structured activities wearing either cotton whole
body dosimeters or swimsuits. A total of 13 subjects
wore whole body dosimeters while 21 subjects wore
bathing suits. Foggers containing the pesticide
chlorpyrifos were discharged from the centers of
two identical rectangular meeting rooms at the
University of California, Riverside. The rooms were
kept unventilated for 2 hours and then were opened
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with a room divider removed during 30 minutes of
ventilation. Surface deposition and dislodgeable
residues were measured with three aluminum foil
coupons and cotton sheets placed at two, four, and
six feet from each fogger. The exercise routines were
the same as those used in Ross etal. (1990).
Biomonitoring was conducted by collecting
four successive 24-hour urine samples from each
subject 1 day prior to exposure and 3 days after
exposure to chlorpyrifos.
The average amounts of pesticide transferred to
the dosimeters were 0.27 ug/cm2 based on the CDFA
roller method and 0.73 ug/cm2 based on the whole
body dosimetry method. These transfer amounts
represent 7.5% and 20.2%, respectively, of the
average concentration of pesticide on the surface of
the carpet (3.6 ug/cm2) based on the deposition
coupons. Calculating the transfer coefficient in the
same way as Ross etal. (1991), the mean transfer
coefficient would be approximately 154,000 cm2/hr
(13,758 ug of residues transferred to dosimetry
clothing per 0.33 hour of exposure/0.27 ug/cm2
residue transferred to the roller sheet). Using the
concentration of residues on the deposition coupons
instead of those transferred to the roller cloth as the
environmental concentration would give a transfer
coefficient of approximately 12,000 cm2/hr
(13,758 ug of residues transferred to dosimetry
clothing per 0.33 hour of exposure/3.6 ug/cm2
residue deposited on the carpet). Absorbed doses and
biomonitoring data reported by Kreiger et al. (2000)
are not summarized because the data are specific to
the pesticide (chlorpyrifos) studied. However, the
biomonitoring data indicate that "both types of
dosimeters [roller cloth and whole body] removed
substantially more [pesticide] than was transferred
and absorbed by human skin" (Kreiger et al., 2000).
The advantage of this study is that it compared
estimates of pesticide residue transfer using a variety
of methods. However, the results are based on a
single pesticide and may not be representative of
other chemicals or activities that may result in
exposure.
7.6.1.5. Clothier (2000)—Dermal Transfer
Efficiency of Pesticides from New, Vinyl
Sheet Flooring to Dry and Wetted Palms
Clothier (2000) compared the transfer of pesticide
residues from vinyl flooring to dry, water-wetted, and
saliva-wetted hands. Three different pesticides were
used in the study (chlorpyrifos, piperonyl butoxide,
and pyrethrin). Three male subjects participated in
the study by pressing their hand palm down on the
vinyl surface. Prior to performing the hand presses,
the hands were either treated with a sample of their
own saliva or water or received no pretreatment (dry
hands). Transferable residues also were collected
using the polyurethane foam (PUF) roller method
described by Camann etal. (1996). Deposition
coupons also were used to measure the amount of
pesticide applied to the flooring. Transfer efficiencies
were estimated as the rate of transfer to hands or PUF
roller (ug/cm2) /mean surface loading (ug/cm2) times
100. Table 7-26 presents the transfer efficiencies
from this study. Transfer efficiencies were higher for
wetted palms than for dry palms and for the PUF
roller than for dry hands.
The advantage of this study is that it provides
perspective on the effects of hand moisture on residue
transfer. The data are based on three pesticides
applied to vinyl surfaces and a limited number of
subjects under controlled experimental conditions.
However, the data may not reflect transfer associated
with other chemicals or activities.
7.6.1.6. Bernard etal. (2001)—Environmental
Residues and Biomonitoring Estimates of
Human Insecticide Exposure from
Treated Residential Turf
Bernard et al. (2001) conducted a study similar to
those conducted by Ross etal. (1990) and Kreiger
et al. (2000), except that the exercise routines were
conducted on pesticide-treated turf instead of on
pesticide-treated carpets. Exposure was measured by
analyzing whole body dosimeters worn by female
participants during 20 minutes of exercise that
occurred approximately 3.5 hours after pesticide had
been applied to the turf. Pesticide deposition was
estimated by collecting and analyzing cotton coupons
present at the time of application. Dislodgeable
residues were measured by collecting and rinsing
foliage samples in an aqueous solution, and
transferable turf residues were estimated using the
CDFA roller 0, 1, and 3 days after application. Turf
residues based on spray deposition (i.e., coupons),
dislodgeable (aqueous wash) residues, and
transferable (roller) residues were 12, 3.4, and
0.085 ug/cm2, respectively. This suggests that
dislodgeable residues were approximately 28% of the
deposition residues, and transferable residues were
less than 1% of the deposition residues. Bernard et al.
(2001) estimated that exposures based on transferable
residues and those based on whole body dosimetry
would be similar because transferable residues based
on whole body dosimetry and those based on the
roller technique were similar.
This study provides perspective on residue
transfer from treated turf. However, the data are for a
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single pesticide and may not be representative of
other chemical substances or exposure conditions.
7.6.1.7. Cohen-Hubal et al.
(2005)—Characterizing Residue Transfer
Efficiencies Using a Fluorescent Imaging
Technique
Cohen-Hubal etal. (2005) used a fluorescent
tracer method to evaluate the factors that affect the
transfer of residues from indoor surfaces to the hands.
The non-toxic fluorescent tracer vitamin B2 riboflavin
was applied to carpet and laminate flooring.
Two levels of analyte loading were evaluated in the
study (2 ug/cm2 and 10 ug/cm2). Three adult subjects
participated in a series of controlled experiments in
which the hands contacted the treated surfaces using
one of two different levels of pressure for one of
two different durations. Transfer as a result of
multiple sequential contacts also was evaluated. The
hands were characterized as dry, moist, or sticky prior
to conducting the hand presses on the treated flooring
materials. To simulate moist hands, the hands were
placed under a cool mist vaporizer for 20 seconds; to
simulate sticky conditions, 1.2 grams of Karo Syrup
was applied to the hands. Dermal loading on the
hands was measured by using a fluorescence imaging
system. Transfer efficiencies were estimated by
dividing the mass of tracer on the hand per unit
surface area (ug/cm2) divided by the loading of tracer
on the carpet or laminate surface (ug/cm2) times 100.
Incremental transfer efficiency was calculated
separately for each individual contact, whereas
overall transfer efficiency was calculated
cumulatively for the series of contacts. Table 7-27
provides the incremental and overall transfer
efficiencies based on the hand conditions, the surface
type, the surface loading, and the number of contacts.
Based on the data in Table 7-27, the mean transfer
efficiency after a single contact ranged from 3 to 14%
for dry and sticky hands, respectively. According to
Cohen-Hubal et al. (2005), surface loading and skin
condition were important parameters in
characterizing transfer efficiency, but duration of
contact and pressure did not have a significant effect
on transfer.
An advantage of this study is that it uses a tracer
method to estimate transfer efficiency from surfaces
to human skin. It also provides perspective on various
conditions that may affect transfer efficiency. A
limitation is that the data may not reflect transfer
associated with specific chemicals or activities.
Chapter 7—Dermal Exposure Factors
7.6.1.8. Cohen-Hubal et al. (2008)—Comparing
Surface Residue Transfer Efficiencies to
Hands Using Polar and Non-Polar
Fluorescent Transfer
As a follow up to the Cohen-Hubal et al. (2005)
study, Cohen-Hubal etal. (2008) conducted a study
using a second fluorescent tracer, Uvitex OB, which
has different physical-chemical properties than
riboflavin. The fluorescent tracer, which was used as
a surrogate for pesticide residues, was applied to
carpet or laminate surfaces at two different loading
levels, and controlled hand transfer experiments were
conducted by using various pressures and motions
(i.e., press and smudge), numbers of contacts, and
different hand conditions (i.e., dry or moist). The
mass of tracer transferred to the hands was measured
using a fluorescent tracer imaging system. The results
indicated that "overall percent transfer ranged from
0.8 to 45.5% for the first contact and 0.6 to 19.4% for
the seventh contact," and dermal loadings increased
in a near linear fashion through the seventh contact.
"Transfer was greater for laminate (over carpet),
smudge (over press), and moist (over dry)"
(Cohen-Hubal etal., 2008). For lower surface
loadings, dermal transfer increased through the
seventh contact, suggesting that multiple contacts
may be required to reach an effective equilibrium
with the surface.
Similar to the previous study, the advantage of
these data is that they are based on tracers and
provide information on factors affecting residue
transfer. However, the data may or may not
accurately reflect transfer for specific chemicals or
activities.
7.6.1.9. Reamer et al. (2009)—Developing
Probability Distributions for Transfer
Efficiencies for Dermal Exposure
Beamer etal. (2009) combined data from
nine residue transfer studies and developed
distributions for three pesticides (chlorpyrifos,
pyrethrin I, and piperonyl butoxide) and three surface
types (foil, vinyl, and carpet). The studies used for
developing these distributions included Hsu etal.
(1990), Ross etal. (1991), Camann etal. (1995,
1996), Geno etal. (1996), Fortune (1998a, b),
Clothier (2000), and Kreiger et al. (2000). Beamer
etal. (2009) stratified the data by chemical and
surface type. Statistical methods were used to
develop the distributions, based on combined data
from studies that used different sampling methods,
surface concentrations, formulations, sampling time,
and skin conditions (i.e., dry or wet). Transfer
efficiencies were defined as the amount transferred to
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Chapter 7—Dermal Exposure Factors
skin or a transfer media used as a surrogate for skin
divided by the amount of pesticide applied to the
surface.
Table 7-28 presents the lognormal parameter
values for the three chemicals and three surface types
evaluated. The results of statistical analyses indicated
that the distributions of transfer efficiencies were
statistically different for the surface types and
chemicals shown in Table 7-28. Transfer efficiency
was highest for foil for all chemicals, followed by
vinyl and carpet. For example, the geometric mean
transfer efficiencies ranged from 0.01 to 0.02 (i.e., 1
to 2%) for carpet, 0.03 to 0.04 (3 to 4%) for vinyl,
and 0.83 to 0.86 (83 to 86%) for foil. According to
Beamer et al. (2009), these distributions can be used
for modeling transfer efficiencies.
An advantage of this data set is that it uses data
from several of the studies described in this chapter
to develop distributions for three pesticides and
three surface types. However, there is some
uncertainty with regard to the representativeness of
these data for other chemicals or exposure conditions.
7.7. OTHER FACTORS
7.7.1. Frequency and Duration of Dermal (Hand)
Contact
This section provides information from studies
that evaluated activities that may affect dermal
exposure. This includes information on the frequency
and duration of dermal contact with objects and
surfaces. Additional information on activities patterns
and consumer product use that affect the frequency
and duration of dermal contact is provided in
Chapters 16 and 17. Information on hand-to-mouth
contact frequency in presented in Chapter 4.
7.7.1.1. Zartarian et al (1997)—Quantified
Dermal Activity Data from a Four-Child
Pilot Field Study
Zartarian etal. (1997) conducted a pilot field
study in California in 1993 to estimate children's
dermal contact with objects in their environment.
Four Mexican American farm worker children ages 2
to 4 years were videotaped to record their activities
over a 1-day period. Five to 30% of the children's
time was spent outdoors, while the remainder was
spent indoors. Videotape data were obtained over 6 to
11 waking hours for the four children (i.e., a total of
33 hours of videotape). The videotapes were
translated to provide information about the objects
that the children contacted, as well as the frequency
and duration of contact. The data indicated that most
objects were contacted for approximately 2 to
3 seconds in duration, and hard surfaces and hard
toys were touched by children's hands for the longest
percent of the time (Zartarian et al., 1997). Table 7-29
provides the average contact frequency for the left
and right hands of the four children who participated
in the study. Frequency of contact was highest for
hard surfaces and hard toys (see Table 7-29).
The advantage of this study is that it was the first
in a series of papers that used video-transcription
methods to evaluate children's micro-activities
relative to potential dermal exposure. However, the
number of participants in this study (four children)
was small, and the results may not be representative
of all U.S. children.
7.7.1.2. Reed et al. (1999)—Quantification of
Children's Hand and Mouthing Activities
Through a Videotaping Methodology
Reed et al. (1999) used a videotaping
methodology similar to that used by Zartarian et al.
(1997) to quantify the hand contact activities of
30 children in New Jersey. A total of 20 children ages
3 to 6 years were observed in daycare facilities, while
an additional 10 children, ages 2 to 5 years were
observed in residential settings. Total videotaping
time ranged from 3 to 7 hours for the daycare
children and 5 to 6 hours for the residential children.
Frequency of hand contact with objects and surfaces
was quantified by recording touches with clothing,
dirt, objects, and smooth or textured surfaces, as
observed on video. According to Reed etal. (1999),
"comparison of activities of children in home settings
and daycare showed that rates of many of the
activities did not differ significantly between venues
and therefore, data from homes and daycare were
combined." Table 7-30 presents the hand contact
frequency data for the 30 children observed in this
study. High contact frequencies were observed for
clothing, objects, other, and smooth surfaces.
The advantages of this study are that more
children were observed than in the previous study,
and both daycare and residential children were
included. However, the children were from a single
location and may not be representative of all U.S.
children.
7.7.1.3. Freeman et al. (2001)—Quantitative
Analysis of Children's Micro-Activity
Patterns: The Minnesota Children's
Pesticide Exposure Study
Freeman etal. (2001) conducted a survey
response and video-transcription study of some of the
respondents in a phased study of children's pesticide
exposures in the summer and early fall of 1997. A
probability-based sample of 168 families with
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children ages 3 to <14 years old in urban
(Minneapolis/St. Paul) and non-urban (Rice and
Goodhue Counties) areas of Minnesota answered
questions about children's behaviors that might
contribute to exposure via dermal contact or
non-dietary ingestion. Of these 168 families, 19
agreed to videotaping of the study children's
activities for a period of 4 consecutive hours. The
videotaped children ranged in age from 3 to 12 years
of age but were divided into four age groups (3 to
4 years, 5 to 6 years, 7 to 8 years, and 10 to 12 years)
for the purposes of quantifying microactivities. The
frequency of touching clothing, textured surfaces
(e.g., carpets and upholstered furniture), smooth
surfaces (e.g., wood or plastic furniture, hardwood
floor), or objects (e.g., toys, pencils, or other things
that could be manipulated) was quantified by
observing the behaviors on the videotapes during a
4-hour observation period. Table 7-31 shows the
frequency of hand contacts per hour for the
19 children.
An advantage to this study is that it included
results for various ages of children. However, the
children in this study may not be representative of all
U.S. children. Also, the presence of unfamiliar
persons following the children with a video camera
may have influenced the video-transcription
methodology results.
7.7.1.4. Freeman et al (2005)—Contributions of
Children's Activities to Pesticide Hand
Loadings Following Residential Pesticide
Application
Freeman etal. (2005) gathered data on hand
contacts with surfaces and objects as part of a study
to evaluate pesticide exposure in residential settings.
A convenience sample of 10 children between the
ages of 24 and 55 months was selected for videotape
observation on the 2nd day after their homes were
treated with pesticides. The children were videotaped
during a 4-hour period (only three children spent time
outside the house, with outdoor times ranging from
21 to 57 minutes). The videotapes were transcribed to
quantify contact rates in terms of frequency and
duration. According to Freeman etal. (2005), "the
duration of contact of most contact events was very
short (2-3 seconds)," but contact with bottles, food,
and objects tended to be somewhat longer (median
durations ranged from 4.5 to 7.5 seconds for these
items). Table 7-32 presents the right-hand contact
rates (contacts per hour) for the various objects and
surfaces. High contact items include objects and
smooth surfaces.
The advantage of this study is that it provides
additional information on hand contact frequency.
However, the data are based on a limited number of
children and were collected over a relatively short
time period. Also, the presence of a video camera
may have affected the children's behavior.
7.7.1.5. AuYeung et al (2006)—Young Children's
Hand Contact Activities; an Observational
Study via Videotaping in Primarily
Outdoor Residential Settings
AuYeung et al. (2006) gathered data on children's
hand contact activities by videotaping them in
outdoor residential settings in 1998-1999. A total of
38 children ages 1 to 6 years from middle class
suburban families were recruited from the San
Francisco Bay peninsula area to participate in the
study. Each child was videotaped during 2 hours of
natural (i.e., unstructured) play in an outdoor location
(i.e., park, playground, outdoor residential area).
Videotapes then were translated using a software
package specially designed for this use. Contacts
were tabulated for 15 object surface categories and
for all non-dietary objects and all objects and
surfaces combined. Hourly contact frequency, median
duration per contact, and hourly contact duration
were calculated for each child for the left hand, right
hand, and both hands combined, and summary
statistics were developed for all children combined.
Table 7-33 provides the data for outdoor locations.
According to AuYeung etal. (2006), these data
suggest that children have a large number of
short-duration contacts with outdoor objects and
surfaces. AuYeung et al. (2006) also collected some
limited data for indoor locations. These data are
based on nine children who were videotaped for
15 minutes or more indoors. Table 7-34 provides
summary data for these children.
The advantage of this study is that it provides
dermal (hand) contact data for a wide variety of
outdoor objects and surfaces. The data for indoor
environments were limited, however, and the
presence of unfamiliar persons following the children
with a video camera may have influenced the
video-transcription methodology results.
7.7.1.6. Ko et al (2007)—Relationships of Video
Assessments of Touching and Mouthing
Behaviors During Outdoor Play in Urban
Residential Yards to Parental Perceptions
of Child Behaviors and Blood Lead Levels
Ko etal. (2007) used video observation and
transcription methods to assess children's hand
contacts with outdoor surfaces as part of a study to
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assess the relationship between blood level levels and
children's activities in urban environments. During
the summers of 2000 and 2001, a total of 37 children
ages 1 to 5 years were videotaped during 2-hour
periods while playing in outdoor urban residential
settings. The children were primarily from
low-income, Hispanic families. Ko et al. (2007)
tabulated surface contacts by reviewing the
videotapes and counting the number of times a
child's hands touched one of the following surfaces:
(1) cement, stone, or steel on the ground (cement);
(2) porch floor or porch steps (porch); (3) grass; and
(4) bare soil. Distributions of contact frequency
(contacts per hour) were developed using the data for
the 37 children for the four surface types and for all
surfaces combined. According to Ko et al. (2007), the
median contact frequency for all surfaces was
81 contacts per hour (geometric mean = 70 contacts
per hour), with several children touching surfaces
approximately 400 contacts per hour (see
Table 7-35).
Similar to the AuYeung etal. (2006) study
described in the previous section, the advantage of
this study is that it provides data for outdoor dermal
(hand) contacts with a variety of objects and surfaces.
These surface types are somewhat different from
those in AuYeung et al. (2006) but provide additional
perspective on contact with outdoor surfaces. As with
all studies that use videotape methods, however, the
presence of unfamiliar persons following the children
with a video camera may have influenced the results.
7.7.1.7. Beameretal. (2008)—Quantified Activity
Pattern Data from 6 to 27-Month-Old
Farmworker Children for Use in
Exposure Assessment
Beamer et al. (2008) conducted a study in which
children were videotaped to estimate contacts with
objects and surfaces in their environment. A
convenience sample of 23 children residing in the
farm worker community of Salinas Valley, CA,
participated in the study. Participants were 6- to
13-month-old infants and 20- to 26-month-old
toddlers. Two researchers videotaped each child's
activities for a minimum of 4 hours and kept a
detailed written log of locations visited and objects
and surfaces contacted by the child. A questionnaire
was administered to an adult in the household to
acquire demographic data, housing and cleaning
characteristics, eating patterns, and other information
pertinent to the child's potential pesticide exposure.
Table 7-36 presents the mean and median object
and surface contact frequency in events per hour. The
most frequently contacted objects included toys
(121 contacts per hour) and clothing/towels
(114 contacts per hour). The mean frequency of hand
contact of all objects and surfaces for both hands
combined was 686.3 contacts per hour. Table 7-36
also provides information on the duration of contact
with these objects and surfaces in minutes per hour
and in seconds per contact.
The advantage of this study is that it included
both infants and toddlers. Also, it provided data for a
wide variety of objects and surfaces. Differences
between the two age groups, as well as sex
differences, were observed. As with other
video-transcription studies, however, the presence of
non-family-member videographers and a video
camera may have influenced the children's behavior.
7.7.2. Thickness of the Skin
Although factors that influence dermal uptake
(i.e., absorption) and internal dose are not the focus
of this chapter, limited information on the
physiological characteristics of the skin (i.e.,
thickness of the skin on various body parts) is
presented here to provide some perspective on this
topic. It should be noted that this is only one factor
that may influence dermal uptake. Others include the
condition of the skin (e.g., Williams etal., 2004,
2005, suggested that the presence of perspiration on
the skin may affect uptake of contaminants) and
chemical-specific factors (e.g., concentration of
chemical in contact with the skin and characteristics
of the chemical that affect its rate of absorption).
The skin consists of two distinct layers: the
epidermis (outermost layer) and dermis. The
outermost layer of the epidermis is the stratum
corneum or horny layer. Because the stratum
corneum serves as the body's outermost boundary, it
is the layer where chemical exposures may occur.
According to the International Commission on
Radiological Protection (ICRP, 1994), the thickness
of the stratum corneum of adults is "approximately
one-tenth that of the epidermis except for palms [of
hands] and soles [of feet] where it may be much
thicker." Over most parts of the body, the stratum
corneum is estimated to range in thickness from
about 13 to 15 um, but it may vary by region of the
body, with the certain parts (e.g., the "horny pads") of
the palms and soles being as high as 600 um (ICRP,
1994). Holbrook and Odland (1974) used electron
microscopy to measure the thickness of the stratum
corneum from fixed tissues collected from the
abdomen, back, forearm, and thigh of six subjects
(three men and three women) ages 25 to 31 years old.
The mean thicknesses for these four body regions
were 8.2, 9.4, 12.9, and 10.9 um, respectively.
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Schwindt et al. (1998) estimated thickness using skin
at the same four sites in six women with a mean age
of 33.2 years. Based on calculations from
measurements of transepidermal water loss during
tape stripping, mean thicknesses were estimated to be
7.7 ± 1.7, 11.2 ± 2.6, 12.3 ± 3.6, and 13.1 ± 4.7 urn
for the abdomen, back, forearm, and thigh,
respectively (Schwindt etal., 1998). Using
two methods of calculating thickness, Pirot et al.
(1998) estimated the thickness of the stratum
corneum on the forearms of 13 subjects (2 men and
11 women) between the ages of 23 and 60 years. The
mean± standard deviation values were 11.3 ± 5.1 and
12.6 ± 5.3 urn. Russell etal. (2008) estimated the
thickness of the stratum corneum on the forearm to
be approximately 10 um, based on 18 adults (3 men
and 15 women) between the ages of 22 and 43 years.
Egawa etal. (2007) estimated the stratum corneum
thickness on five body parts of 15 Japanese adults
(6 men and 9 women) ages 23 to 49 years old.
Mean ± standard deviation thicknesses were 16.8 ±
2.8, 21.8 ± 3.6, 22.6 ± 4.3, 29.3 ± 6.8, and 173 ± 37.0
for the cheek, upper arm, forearm, back of hand, and
palm of hand, respectively (Egawa et al., 2007).
For newborn infants, the stratum corneum "is
extremely thin, but grows rapidly during the
first month" (ICRP, 1994). Based on measurements
of newborn skin that was fixed in formalin, thickness
of the stratum corneum was about 10 um on the back
and about 80 to 140 um on the sole of the foot of
newborns. Based on measurement using non-fixed,
fresh, frozen newborn skin, the thickness of the
stratum corneum ranged from 10 to 50 um for
portions of the buttocks and abdomen and most other
regions of the body except the hands and feet (ICRP,
1994).
7.8. REFERENCES FOR CHAPTER 7
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AC; Leckie, JO. (2006) Young children's
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AuYeung, W; Canales, RA; Leckie, JO. (2008) The
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Beamer, P; Key, ME; Ferguson, AC; Canales, RA;
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Camann, DE; Majundar, TK; Harding, HJ. (1995)
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Camann, D; Harding, H; Geno, PW; Agrawal, SR.
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Choate, LM; Ranville, JF; Bunge, AI; Macalady, DL.
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5
1=
Table 7-6. Percentage of Total Body Surface Area by Body Part for Children (sexes combined) and Adults by Sex
Age
: (years) N
M:F
Percent of Total
Head Trunk Arms Hands Legs Feet
Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean
Min-Max
Male and Female Children Combined
<1
1<2
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9<10
1K12
12<13
13<14
14<15
15<16
16<17
17<18
2:0
1:1
1:0
0:5
1:3
1:0
0:2
1:0
1:0
1:0
1:0
Male, 18+ years 32
Female,
a
b
N
Min
Max
Source:
18+ years 57
Sample size = 13.
Sample size = 12.
18.2 18.2-18.3 35.7 34.8-36.6 13.7 12.4-15.1 5.3 5.2-5.4 20.6 18.2-22.9 6.5
16.5 16.5-16.5 35.5 34.5-36.6 13.0 12.8-13.1 5.7 5.6-5.8 23.1 22.1-24.0 6.3
14.2 38.5 11.8 5.3 23.2 7.1
13.6 13.3-14.0 31.9 29.9-32.8 14.4 14.2-14.7 6.1 5.8-6.3 26.8 26.0-28.6 7.2
13.8 12.1-15.3 31.5 30.5-32.4 14.0 13.0-15.5 5.7 5.2-6.6 27.8 26.0-29.3 7.3
13.1 35.1 13.1 4.7 27.1 6.9
12.0 11.6-12.5 34.2 33.4-34.9 12.3 11.7-12.8 5.3 5.2-5.4 28.7 28.5-28.8 7.6
8.7 34.7 13.7 5.4 30.5 7.0
10.0 32.7 12.1 5.1 32.0 8.0
8.0 32.7 13.1 5.7 33.6 6.9
7.6 31.7 17.5 5.1 30.8 7.3
7.8 6.1-10.6 35.9 30.5-41.4 14.1 12.5-15.5 5.2 4.6-7.0 31.2 26.1-33.4 7.0
7.1 5.6-8.1 34.8 32.8-41.7 14.0a 12.4-14.8 5.1b 4.4-5.4 32.4a 29.8-35.3 6.5a
6.5-6.6
5.8-6.7
6.8-7.9
6.9-8.1
7.4-7.8
6.0-7.9
6.0-7.0
= Number of subjects, (M:F = male:female).
= Minimum percent.
= Maximum percent.
U.S. EPA, 1985.
X)
s
I
ri
I
1=
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-7. Summary of Equation Parameters for Calculating Adult Body Surface Area"
Body Part
Equation for surface areas (m )
Wal
Ha
SE
Head
Female 57 0.0256
Male 32 0.0492
Trunk
Female 57 0.188
Male 32 0.0240
Upper Extremities
Female 57 0.0288
Male 48 0.00329
Arms
Female 13 0.00223
Male 32 0.00111
Upper Arms
Male
Forearms
Male
Hands
Female 12
Male 32
Lower Extremities' 105 0.00286
Legs 45 0.00240
Thighs 45 0.00352
Lower legs 45 0.000276
Feet 45 0.000618
6 8.70
6 0.326
b 0.0131
0.0257
0.124
0.339
0.647
0.808
0.341
0.466
0.201
0.616
0.741
0.858
0.412
0.573
0.458
0.542
0.629
0.416
0.372
0.189 0.01
-0.0950 0.01
-0.304
-0.0131
0.175
0.524
0.0274
-0.218
0.696
0.626
0.379
0.973
0.725
0.001
0.001
0.001
0.001
0.748 0.01
0.561 0.001
-1.40 0.25
-0.895 0.05
0.1
0.001
0.001
0.001
0.001
0.001
0.001
0.302
0.222
0.877
0.894
0.526
0.821
0.731
0.892
0.447
0.575
0.802
0.780
0.739
0.727
0.651
0.00678
0.0202
0.00567
0.0118
0.00833
0.0101
0.00996
0.0177
0.576 0.0387
0.897 0.0207
0.0172
0.0187
0.00633
0.0130
0.0149
0.0149
0.0147
a SA= a0 Wal Ha2 where: W = Weight in kilograms; H = Height in centimeters; P = Level of significance; R2= Coefficient of
determination; SA= Surface Area; SE = Standard error; N= Number of observations.
b One observation for a female whose body weight exceeded the 95 percentile was not used.
c Although two separate regressions were marginally indicated by the F test, pooling was done for consistency with individual
components of lower extremities.
Source: U.S. EPA, 1985.
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Chapter 7—Dermal Exposure Factors
Table 7-8. Mean Proportion (%) of Children's
2
4
6
Total Skin Surface Area, by Body
Age (years)
8 10 12
14
Part
16
18
Male
N
Head
Neck
Bosom
Shoulders
Abdomen
Back
Genitals and Buttocks
Thighs
Legs
Feet
Upper Arms
Lower Arms
Hands
115
8.4
3.9
12.3
1.9
2.7
12.9
7.1
14.9
10.3
6.5
8.7
5.8
4.5
118
8.1
3.8
12.3
2.1
2.9
13.2
6.9
15.0
10.3
6.5
8.5
5.6
4.8
117
7.0
3.2
12.2
1.9
2.7
13.1
6.9
16.2
10.9
6.7
8.6
5.7
4.9
104
6
2
12
1
2
13
6
16
11
7
8
5
4
0
7
2
9
8
1
8
6
7
2
6
7
7
124
5.4
2.6
12.2
1.8
2.7
13.1
7.1
17.6
11.8
6.8
8.8
5.5
4.6
154
4.9
2.3
12.4
1.8
2.8
13.4
7.0
17.4
11.9
7.0
8.7
5.5
4.7
155
4.3
2.2
12.3
1.8
2.8
13.4
7.2
18.2
11.9
6.6
8.9
5.7
4.7
100
4
2
12
1
2
13
7
18
11
6
9
5
4
0
0
3
8
8
o
3
2
1
9
7
6
8
7
88
3.9
2.0
12.8
1.9
2.9
13.9
6.8
18.3
11.2
6.1
9.6
5.9
4.7
Female
N
Head
Neck
Bosom
Shoulders
Abdomen
Back
Genitals and Buttocks
Thighs
Legs
Feet
Upper Arms
Lower Arms
Hands
97
8.4
3.8
12.4
2.0
3.0
13.2
6.8
14.2
11.2
6.0
8.6
5.6
4.8
110
7.8
3.6
12.6
2.0
2.9
13.4
6.6
15.6
10.4
6.3
8.4
5.5
4.9
126
6.9
3.2
12.4
1.9
2.8
13.2
6.6
16.5
11.4
6.6
8.3
5.3
4.9
93
6
2
12
1
2
13
6
18
11
6
8
5
4
1
8
2
9
8
1
6
4
3
5
1
5
7
134
5.3
2.5
12.1
1.8
2.7
13.0
7.0
18.4
12.2
6.7
8.4
5.3
4.5
133
4.8
2.3
12.0
1.8
2.7
12.9
7.3
18.5
12.5
6.5
8.8
5.5
4.5
116
4.5
2.1
12.3
1.7
2.8
13.2
8.0
18.9
12.1
6.1
8.8
5.3
4.2
98
4
2
13
1
2
13
7
17
11
6
8
5
4
3
1
o
5
8
9
9
9
8
9
1
6
3
2
68
4.3
2.0
14.3
1.8
3.0
14.1
8.1
17.4
11.5
5.6
8.5
5.1
4.4
N = Number of observations.
Note: Sums of columns may
Source: Boniol et al., 2007.
equal
slightly
more or less
than 100% due to
rounding
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-9. Mean and Percentile Skin Surface Area (m2)
Derived from U.S. EPA Analysis of NHANES 1999-2006
Male and Female Combined for Children <21 Years and NHANES 2005-2006 for Adults >21 Years
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
80 years and over
TV Mean -
154
281
488
923
1,159
1,122
2,303
3,590
5,294
4,843
914
813
806
624
645
454
330
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
1.93
1.97
2.01
2.00
1.98
1.89
1.77
Percentiles
5*
0.24
0.27
0.33
0.38
0.45
0.52
0.61
0.81
1.19
1.47
1.51
1.55
1.59
1.57
1.58
1.48
1.45
10*
Male and
0.25
0.29
0.34
0.39
0.46
0.54
0.64
0.85
1.25
1.53
1.56
1.63
1.66
1.63
1.63
1.56
1.53
15th
Female
0.26
0.29
0.35
0.40
0.47
0.55
0.66
0.88
1.31
1.58
1.62
1.67
1.71
1.69
1.70
1.64
1.56
25th
Combined
0.27
0.31
0.36
0.42
0.49
0.57
0.68
0.93
1.4
1.65
1.73
1.77
1.80
1.80
1.78
1.72
1.62
50th
0.29
0.33
0.38
0.45
0.53
0.61
0.74
1.05
1.57
1.80
1.91
1.95
1.99
1.97
1.98
1.90
1.76
75*
0.31
0.35
0.40
0.48
0.56
0.64
0.81
1.21
1.75
1.99
2.09
2.16
2.21
2.19
2.15
2.05
1.92
85th
0.31
0.37
0.42
0.49
0.58
0.67
0.85
1.31
1.86
2.10
2.21
2.26
2.31
2.29
2.26
2.15
2.00
90th
0.33
0.37
0.43
0.50
0.59
0.68
0.89
1.36
1.94
2.21
2.29
2.31
2.40
2.37
2.33
2.22
2.05
95*
0.34
0.38
0.44
0.51
0.61
0.70
0.95
1.48
2.06
2.33
2.43
2.43
2.48
2.51
2.43
2.30
2.12
TV = Number of observations.
Source: U.S. EPA Analysis
of NHANES
1999-2006
data (children) NHANES
2005-2006
data
(adults).
Page
7-40
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-10. Mean and Percentile Skin Surface Area (m2)
Derived from U.S. EPA Analysis of NHANES 1999-2006 for
Children <21 Years and NHANES 2005-2006 for Adults >21 Years,
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to 30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
80 years and older
N
85
151
255
471
620
548
1,150
1,794
2,593
2,457
361
390
399
310
323
249
163
Mean —
0.29
0.33
0.39
0.45
0.53
0.62
0.76
1.09
1.61
1.94
2.05
2.10
2.15
2.11
2.08
2.05
1.92
Male
Percentiles
5th
0.24
0.28
0.34
0.39
0.46
0.54
0.61
0.82
1.17
1.61
1.70
1.74
1.78
1.68
1.72
1.71
1.67
10*
0.25
0.29
0.35
0.41
0.47
0.56
0.64
0.86
1.23
1.66
1.76
1.81
1.86
1.81
1.78
1.80
1.71
15th
Male
0.26
0.30
0.36
0.42
0.48
0.56
0.66
0.89
1.28
1.7
1.81
1.85
1.90
1.86
1.84
1.84
1.74
25th
0.27
0.31
0.37
0.43
0.50
0.58
0.69
0.94
1.39
1.76
1.87
1.93
1.97
1.94
1.94
1.92
1.80
50*
0.29
0.34
0.39
0.46
0.53
0.62
0.75
1.06
1.60
1.91
2.01
2.08
2.12
2.12
2.08
2.05
1.92
75th
0.31
0.36
0.41
0.48
0.57
0.65
0.82
1.21
1.79
2.08
2.18
2.24
2.29
2.26
2.25
2.18
2.02
85*
0.33
0.37
0.42
0.49
0.58
0.67
0.86
1.29
1.90
2.22
2.30
2.31
2.41
2.34
2.33
2.23
2.08
90th
0.34
0.37
0.43
0.50
0.59
0.68
0.89
1.34
1.99
2.30
2.39
2.39
2.47
2.46
2.37
2.31
2.13
95th
0.36
0.38
0.44
0.51
0.62
0.70
0.95
1.46
2.12
2.42
2.52
2.50
2.56
2.55
2.46
2.45
2.22
N = Number of observations.
Source: U.S. EPA Analysis
of NHANES
1999-2006
data (children)
NHANES
2005-2006
data (adults).
Exposure Factors Handbook
September 2011
Page
7-41
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-11. Mean and Percentile Skin Surface Area (m2)
Derived from U.S. EPA Analysis of NHANES 1999-2006 for
Children <21 Years and NHANES 2005-2006 for Adults >21 Years, Female
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to 30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
80 years and older
TV Mean —
69
130
233
452
539
574
1,153
1,796
2,701
2,386
553
423
407
314
322
205
167
0.28
0.32
0.38
0.44
0.52
0.60
0.75
1.08
1.57
1.73
1.81
1.85
1.88
1.89
1.88
1.77
1.69
Percentiles
5*
0.24
0.27
0.32
0.38
0.44
0.51
0.61
0.80
1.20
1.42
1.45
1.50
1.54
1.54
1.49
1.44
1.41
10*
0.25
0.28
0.33
0.39
0.46
0.53
0.64
0.85
1.28
1.47
1.51
1.55
1.59
1.58
1.59
1.48
1.46
15th
Female
0.26
0.29
0.34
0.40
0.47
0.54
0.66
0.87
1.34
1.51
1.54
1.61
1.63
1.62
1.62
1.55
1.51
25th
0.27
0.30
0.35
0.41
0.48
0.56
0.68
0.92
1.42
1.57
1.60
1.67
1.70
1.70
1.70
1.62
1.56
50th
0.28
0.31
0.38
0.44
0.52
0.59
0.74
1.04
1.55
1.69
1.79
1.82
1.83
1.85
1.85
1.77
1.68
75*
0.30
0.35
0.40
0.47
0.56
0.63
0.80
1.21
1.69
1.85
1.94
2.00
2.04
2.005
2.04
1.91
1.80
85th
0.30
0.36
0.40
0.48
0.57
0.66
0.84
1.33
1.8
1.98
2.08
2.13
2.19
2.19
2.14
1.99
1.86
90th
0.31
0.37
0.41
0.49
0.58
0.67
0.88
1.39
1.88
2.06
2.17
2.23
2.27
2.26
2.20
2.03
1.92
95*
0.33
0.37
0.43
0.51
0.59
0.70
0.94
1.51
2.00
2.17
2.25
2.31
2.36
2.38
2.34
2.13
1.98
N = Number of observations.
Source: U.S. EPA Analysis
of NHANES
1999-2006
data (children)
NHANES
2005-2006
data (adults).
Page
7-42
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-12. Surface Area of Adult
Body part
Male (21 years and older)
in Square Meters
Percentile
Mean
5*
10*
15*
25*
50*
75*
85*
90*
95th
Adult Male
Total
Head
Trunk3
Upper Extremities
Arms
Upper arms
Forearms
Hands
Lower Extremities
Legs
Thighs
Lower Legs
Feet
2.06
0.136
0.827
0.393
0.314
0.172
0.148
0.107
0.802
0.682
0.412
0.268
0.137
1.73
0.123
0.636
0.332
0.253
0.139
0.115
0.090
0.673
0.560
0.334
0.225
0.118
1.80
0.126
0.672
0.346
0.265
0.145
0.121
0.093
0.703
0.587
0.349
0.234
0.123
1
0
0
0
0
0
0
0
0
0
0
0
0
.84
128
701
354
274
149
125
096
721
603
360
241
125
1.93
0.131
0.74
0.369
0.289
0.156
0.132
0.100
0.752
0.634
0.379
0.252
0.130
2.07
0.136
0.820
0.395
0.316
0.169
0.146
0.107
0.808
0.686
0.4113
0.271
0.138
2.23
0.143
0.918
0.425
0.346
0.185
0.163
0.115
0.868
0.746
0.452
0.292
0.147
2.34
0.147
0.984
0.442
0.364
0.196
0.173
0.121
0.903
0.780
0.478
0.302
0.152
2.41
0.149
1.02
0.456
0.379
0.205
0.181
0.124
0.936
0.811
0.495
0.312
0.156
2.52
0.154
1.10
0.474
0.399
0.220
0.197
0.131
0.972
0.847
0.523
0.324
0.161
a Trunk includes neck.
Source: Based on U.S
EPA (1985)
and NHANES
2005-2006.
Exposure Factors Handbook
September 2011
Page
7-43
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-13. Surface Area
J30uy ran
of Adult Females (21 years and older) in Square Meters
Percentile
Mean
5th
10*
15*
25th
50*
75th
85th
90th
95th
Adult Female
Total
Head
Trunk3
Upper Extremities
Arms
Hands
Lower Extremities
Legs
Thighs
Lower Legs
Feet
1.85
0.114
0.654
0.304
0.237
0.089
0.707
0.598
0.364
0.233
0.122
1.49
0.108
0.511
0.266
0.213
0.076
0.579
0.474
0.281
0.191
0.103
1
0
0
0
0
0
0
0
0
0
0
.55
109
530
272
218
078
599
494
294
198
106
1.59
0.110
0.544
0.277
0.221
0.079
0.616
0.509
0.303
0.204
0.109
1.66
0.111
0.571
0.284
0.227
0.082
0.643
0.533
0.319
0.213
0.113
1.82
0.114
0.633
0.301
0.237
0.087
0.698
0.588
0.356
0.230
0.121
1.99
0.116
0.708
0.320
0.248
0.094
0.761
0.649
0.397
0.250
0.130
2.12
0.118
0.765
0.333
0.254
0.099
0.805
0.693
0.428
0.263
0.136
2.21
0.119
0.795
0.342
0.259
0.102
0.835
0.724
0.450
0.273
0.140
2.33
0.121
0.850
0.354
0.266
0.106
0.875
0.764
0.479
0.286
0.146
a Trunk includes neck.
Source: Based on U.S
EPA (1985) and
NHANES
2005-2006.
Page
7-44
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-14
Mean
Median
Mode
Standard Deviation
Skewness
Kurtosis
Mean
Median
Mode
Standard Deviation
Skewness
Kurtosis
Source: Murray and
Statistical Results for Total Body Surface Area Distributions (m2), for Adults
U.S. EPA
1.97
1.96
1.96
0.19
0.27
3.08
U.S. EPA
1.73
1.69
1.68
0.21
0.92
4.30
Burmaster, 1992.
Boyd
1.95
1.94
1.91
0.18
0.26
3.06
Boyd
1.71
1.68
1.62
0.20
0.88
4.21
Male
DuBois and DuBois
1.94
1.94
1.90
0.17
0.23
3.02
Female
DuBois and DuBois
1.69
1.67
1.60
0.18
0.77
4.01
Costeff
1.89
1.89
1.90
0.16
0.04
2.92
Costeff
1.71
1.68
1.66
0.21
0.69
3.52
Exposure Factors Handbook
September 2011
Page
7-45
-------
I
tl
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IS
* 1
Table 7-15. Descriptive Statistics for Surface Area/Body- Weight (SA/BW) Ratios (m2/kg)
Age (year) Mean
Ranee
A/T A/T SD SE
Min-Max ^th jgth
Percentiles
25th 50th 75th 90th 95th
Male and Female Combined
0 to 2 0.064
2.1 to 17.9 0.042
>18 0.028
All Ages 0.049
SD = Standard
SE = Standard
0.042-0.114 0.011 0.001 0.047 0.051
0.027-0.067 0.008 0.001 0.029 0.033
0.020-0.031 0.003 7.68e-6 0.024 0.024
0.020-0.114 0.019 9.33e-4 0.025 0.027
deviation.
error of the mean.
0.056 0.062 0.072 0.078 0.085
0.038 0.042 0.045 0.050 0.059
0.027 0.029 0.030 0.032 0.033
0.030 0.050 0.063 0.074 0.079
Source: Phillips etal, 1993.
s
I
ri
I
1=
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-16.
Gardening
Cold months
Warm months
Other Yard Work
Cold months
Warm months
Team Sports
Cold months
Warm months
Repair/Digging
Cold months
Warm months
Estimated Percent of Adult Skin Surface Exposed During Outdoor Activities
N
31
212
73
245
26
71
15
65
Skin Area Exposed
5th percentile
3
3
3
8
3
14
3
9
(% of total body surface area)
50th percentile
8
33
o
6
33
8
33
3
28
95th percentile
33
69
31
68
33
43
14
67
N = Number of observations.
Source: Garlock et al.,
1999.
Table 7-17. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities
Age (year)
N
Mean
Median
SD
TV = Number of observations.
SD = Standard deviation.
Source: Wong etal, 2000.
Play
<5
41
38.0
36.5
6.0
Skin Area Exposed (% of total body
Gardening/Yardwork
5 to 17
47
33.8
33.0
8.3
surface area)
Organized Team Sport
5 to 17
65
29.0
30.0
10.5
Exposure Factors Handbook
September 2011
Page
7-47
-------
V l"o
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Table 7-18. Median Per Contact Outdoor Fractional Surface Areas of the Hands, by Object, Both Hands Combined
Animal Body Clothes Fabric Floor Food Footwear Metal Non- Paper Plastic Rock Toy Vegetation Wood All
Dietary /Brick /Grass Objects
Water
N 12 38 38 19 37 26 30 38 9 27 36 16 37 37 38 38
Minimum 0.02 0.06 0.11 0.05 0.13 0.02 0.02 0.00 0.08 0.02 0.08 0.06 0.08 0.02 0.07 0.13
Maximum 0.27 0.27 0.30 0.30 1.00 1.00 0.25 0.27 1.00 0.30 0.30 0.30 0.27 0.30 0.30 0.27
Mean 0.18 0.15 0.22 0.16 0.24 0.16 0.11 0.14 0.52 0.13 0.17 0.20 0.15 0.17 0.20 0.16
S'percentile 0.04 0.07 0.14 0.11 0.13 0.03 0.03 0.11 0.10 0.03 0.13 0.07 0.13 0.03 0.11 0.13
25thpercentile 0.12 0.13 0.19 0.14 0.19 0.05 0.06 0.14 0.19 0.08 0.14 0.18 0.14 0.12 0.15 0.14
SO^percentile 0.20 0.16 0.22 0.15 0.24 0.11 0.10 0.14 0.31 0.13 0.15 0.23 0.14 0.16 0.18 0.15
75thpercentile 0.24 0.19 0.26 0.15 0.27 0.14 0.14 0.15 1.00 0.17 0.19 0.24 0.15 0.24 0.25 0.17
gs'percentile 0.26 0.24 0.30 0.24 0.30 0.80 0.21 0.19 1.00 0.25 0.28 0.28 0.24 0.30 0.30 0.26
gs'Vrcentile 0.26 0.26 0.30 0.29 0.75 1.00 0.25 0.26 1.00 0.29 0.30 0.30 0.26 0.30 0.30 0.27
N = Number of subjects.
Source: AuYeung et al., 2008.
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Table 7-19. Summary of Field
Activity
Month
Event*
(hours)
N
M
F
Studies That Estimated Activity-Specific Adherence Rates
Age (years)
Conditions
Clothing Study
Indoor
Tae Kwon Do
Greenhouse Worker
Indoor Kid No. 1
Indoor Kid No. 2
Daycare Kid No. la
Daycare Kid No. Ib
Daycare Kid No. 2b
Daycare Kid No. 3
Feb.
Mar.
Jan.
Feb.
Aug.
Aug.
Sept.
Nov.
1.5
5.25
2
2
3.5
4
8
8
1
2
4
6
6
6
5
4
6
1
3
4
5
5
4
3
1
1
1
2
1
1
1
1
8 to 42
37 to 39
6 to 13
3 to 13
1 to 6.5
1 to 6.5
Ito4
1 to 4.5
Carpeted floor
Plant watering, spraying,
soil blending, sterilization
Playing on carpeted floor
Playing on carpeted floor
Indoors: linoleum
surface; Outdoors: grass,
bare earth, barked area
Indoors: linoleum
surface; Outdoors: grass,
bare earth, barked area
Indoors: low napped
carpeting, linoleum
surfaces
Indoors: linoleum
surface, Outside: grass,
bare earth, barked area
All in long sleeve-long pants Kissel et al.,
martial arts uniform, sleeves 1996a
rolled back, barefoot
Long pants, elbow length short
sleeve shirt, no gloves
3 or 4 short pants, 2 of 4 short Holmes et al.,
sleeves, socks, no shoes 1999
5 of 6 long pants, 5 of 6 long
sleeves, socks, no shoes
4 of 6 long pants, 5 of 6 short
sleeves, socks, shoes
4 of 6 long pants, 5 of 6 short
sleeves, 3 of 6 barefoot all
afternoon, others barefoot half the
afternoon
4 of 5 long pants, 3 of 5 long
sleeves, all barefoot for part of the
day
All long pants, 3 of 4 long
sleeves, socks and shoes
Outdoor
Soccer No. 1
Soccer No. 2
Soccer No. 3
GroundskeeperNo. 1
GroundskeeperNo. 2
GroundskeeperNo. 3
Nov.
Mar.
Nov.
Mar.
Mar.
Mar.
0.67
1.5
1.5
1.5
4.25
8
8
8
7
2
5
7
8
0
0
1
3
5
0
8
7
1
2
2
13 to 15
24 to 34
24 to 34
29 to 52
22 to 37
30 to 62
Half grass/half bare
earth
All weather field (sand-
ground tires)
All weather field (sand-
ground tires)
Campus grounds, urban
horticulture center,
arboretum
Campus grounds, urban
horticulture center,
arboretum
Campus grounds, urban
horticulture center,
arboretum
6 of 8 long sleeves, 4 of 8 long Kissel et al.,
pants, 3 of 4 short pants and shin 1996a
guards
All in short sleeve shirts, shorts,
knee socks, shin guards
All in short sleeve shirts, shorts,
knee socks, shin guards
All in long pants, intermittent use
of gloves
All in long pants, intermittent use
of gloves
All in long pants, intermittent use
of gloves
ft
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a
A,
Table 7-19. Summary of Field
Activity
Month
Event3
(hours)
N
M
Studies that Estimated Activity-Specific Adherence Rates (continued)
F
Age (years)
Conditions
Clothing Study
Outdoor (continued)
GroundskeeperNo. 4
GroundskeeperNo. 5
Irrigation Installer
Rugby No. 1
Farmer No. 1
Farmer No. 2
Reed Gatherer
Kid-in-MudNo. 1
Kid-in-MudNo. 2
Gardener No. 1
Gardener No. 2
Rugby No. 2
Rugby No. 3
Archeologist
Construction Worker
Landscape/Rockery
Aug.
Aug.
Oct.
Mar.
May
July
Aug.
Sept.
Sept.
Aug.
Aug.
July
Sept.
July
Sept.
June
4.25
8
3
1.75
2
2
2
0.17
0.33
4
4
2
2.75
11.5
8
9
1
8
6
8
4
6
4
6
6
8
7
8
8
7
8
4
4
6
6
8
2
4
0
5
5
1
2
8
7
3
8
3
3
2
0
0
2
2
4
1
1
7
5
0
0
4
0
1
22 to 38
19 to 64
23 to 41
20 to 22
39 to 44
18 to 43
42 to 67
9 to 14
9 to 14
16 to 35
26 to 52
23 to 33
24 to 30
16 to 35
21 to 30
27 to 43
Campus grounds, urban
horticulture center,
arboretum
Campus grounds, urban
horticulture center,
arboretum
Landscaping, surface
restoration
Mixed grass-bare wet field
Manual weeding, mechanical
cultivation
Manual weeding, mechanical
cultivation
Tidal flats
Lake shoreline
Lake shoreline
Weeding, pruning, digging a
trench
Weeding, pruning, digging a
trench, picking fruit,
cleaning
Grass field (80% of time)
and all-weather field (mix of
gravel, sand, and clay) (20%
of time)
Compacted mixed grass and
bare earth field
Digging with trowel,
screening dirt, sorting
Mixed bare earth and
concrete surfaces, dust and
debris
Digging (manual and
mechanical), rock moving
5 of 7 in short sleeve shirts, Kissel
intermittent use of gloves et al.,
1996a
5 of 8 in short sleeve shirts,
intermittent use of gloves
All in long pants, 3 of 6 short
sleeve or sleeveless shirts
All in short sleeve shirts, shorts,
variable sock lengths
All in long pants, heavy shoes,
short sleeve shirts, no gloves
2 of 6 short, 4 of 6 long pants, 1 of
6 long sleeve shirt, no gloves
2 of 4 short sleeve shirts/knee
length pants, all wore shoes
All in short sleeve T-shirts, shorts,
barefoot
All in short sleeve T-shirts, shorts,
barefoot
6 of 8 long pants, 7 of 8 short Holmes
sleeves, 1 sleeveless, socks, shoes, et al., 1999
intermittent use of gloves
3 of 7 long pants, 5 of 7 short
sleeves, 1 sleeveless, socks, shoes,
no gloves
All in shorts, 7 of 8 in short sleeve
shirts, 6 of 8 in low socks
All short pants, 7 of 8 short or
rolled up sleeves, socks, shoes
6 of 7 short pants, all short sleeves,
3 no shoes or socks, 2 sandals
5 of 8 pants,7 of 8 short sleeves, all
socks and shoes
All long pants, 2 long sleeves, all
socks and boots
s
I
§
s
ri
I
1=
-------
a
£
1=
Table 7-19. Summary of Field
Activity Month
Event3 N M
(hours)
Studies that Estimated Activity-Specific Adherence Rates (continued)
F
Age (years)
Conditions
Clothing Study
Outdoor (continued)
Utility Worker No. 1 July
Utility Worker No . 2 Aug .
Equip. Operator No. 1 Aug.
Equip. Operator No. 2 Aug.
Shoreline Play Sept.
3 Event duration.
b Activities were confined to
N = Number of subjects.
M = Male.
F = Female.
9.5 5 5
9.5 6 6
8 44
8 44
0.33-1.0 9 6
the house.
0
0
0
0
3
24 to 45
23 to 44
21 to 54
21 to 54
7 to 12
Cleaning, fixing mains,
excavation (backhoe and
shovel)
Cleaning, fixing mains,
excavation (backhoe and
shovel)
Earth scraping with heavy
machinery, dusty conditions
Earth scraping with heavy
machinery, dusty conditions
Tidal flat
All long pants, short sleeves, socks, Holmes
boots, gloves sometimes et al., 1999
All long pants, 5 of 6 short sleeves,
socks, boots, gloves sometimes
All long pants, 3 of 4 short sleeves,
socks, boots, 2 of 4 gloves
All long pants, 3 of 4 short sleeves,
socks, boots, 1 gloves
No shirt or short sleeve T-shirts, Shoaf
shorts, barefoot et al., 2005
Q
I
§
ri
1=
I
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-20. Geometric Mean and Geometric Standard Deviations of Solids Adherence by Activity and Body
Region"
Activity
N
Post-Activity Dermal Solids Loadings (mg/cm2)
Hands
Arms
Legs
Faces
Feet
Indoor
Tae Kwon Do
Greenhouse Worker
Indoor Kid No. 1
Indoor Kid No. 2
Day care Kid No. la
Day care Kid No. Ib
Day care Kid No. 2
Day care Kid No. 3
7
2
4
6
6
6
5
4
0.0063
1.9
0.043
0.0073
1.9
0.014
1.5
0.11
1.9
0.15
2.1
0.073
1.6
0.036
1.3
0.0019
4.1
0.0064
0.0042
1.9
0.0041
2.0
0.026
1.9
0.031
1.8
0.023
1.4
0.012
1.2
0.0020
2.0
0.0015
0.0041
2.3
0.0031
1.5
0.030
1.7
0.023
1.2
0.011
1.4
0.014
3.0
0.0050
0.0022
2.1
0.012
1.4
0.0091
1.7
0.079
2.4
0.13
1.4
0.044
1.3
0.0053
5.1
Outdoor
Soccer No. 1
Soccer No. 2
Soccer No. 3
Groundskeeper No. 1
Groundskeeper No. 2
Groundskeeper No. 3
Groundskeeper No. 4
Groundskeeper No. 5
Irrigation Installer
8
8
7
2
5
7
7
8
6
0.11
1.8
0.035
3.9
0.019
1.5
0.15
0.098
2.1
0.030
2.3
0.045
1.9
0.032
1.7
0.19
1.6
0.011
2.0
0.0043
2.2
0.0029
2.2
0.005
0.0021
2.6
0.0022
1.9
0.014
1.8
0.022
2.8
0.018
3.2
0.031
3.8
0.014
5.3
0.0081
1.6
0.0010
1.5
0.0009
1.8
0.0008
1.9
0.0010
1.4
0.0054
1.8
0.012
1.5
0.016
1.5
0.012
1.6
0.0021
0.010
2.0
0.0044
2.6
0.0026
1.6
0.0039
2.1
0.0063
1.3
0.018
0.0040
0.018
Page
7-52
Exposure Factors Handbook
March 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-20.
Activity
Rugby No. 1
Farmers No. 1
Farmers No. 2
Reed Gatherer
Kid-in-Mud No. 1
Kid-in-MudNo. 2
Gardener No. 1
Gardener No. 2
Rugby No. 2
Rugby No. 3
Archeologist
Construction Worker
Landscape/Rockery
Utility Worker No. 1
Utility Worker No. 2
Equip. Operator No. 1
Equip. Operator No. 2
Shoreline Play
Geometric Mean and Geometric Standard Deviations of Solids Adherence by
Activity and Body Region" (continued)
Post-Activity Dermal Solids Loadings (mg/cm2)
TV
8
4
6
4
6
6
8
7
8
7
7
8
4
5
6
4
4
9
Hands
0.40
1.7
0.41
1.6
0.47
1.4
0.66
1.8
35
2.3
58
2.3
0.20
1.9
0.18
3.4
0.14
1.4
0.049
1.7
0.14
1.3
0.24
1.5
0.072
2.1
0.32
1.7
0.27
2.1
0.26
2.5
0.32
1.6
0.49
8.2
Arms
0.27
1.6
0.059
3.2
0.13
2.2
0.036
2.1
11
6.1
11
3.8
0.050
2.1
0.054
2.9
0.11
1.6
0.031
1.3
0.041
1.9
0.098
1.5
0.030
2.1
0.20
2.7
0.30
1.8
0.089
1.6
0.27
1.4
0.17
3.1
Legs
0.36
1.7
0.0058
2.7
0.037
3.9
0.16
9.2
36
2.0
9.5
2.3
0.072
0.022
2.0
0.15
1.6
0.057
1.2
0.028
4.1
0.066
1.4
0.70
3.6
a Means are presented above the standard deviations. The standard deviations
by large amounts indicating high variability in the data.
N = Number of subjects.
Sources: Kissel et al., 1996a; Holmes et al., 1999; Shoaf et al., 2005.
Faces
0.059
2.7
0.018
1.4
0.041
3.0
0.058
1.6
0.047
1.6
0.046
1.4
0.020
1.5
0.050
1.8
0.029
1.6
0.0057
1.9
0.10
1.5
0.10
1.5
0.10
1.4
0.23
1.7
0.04
2.9
generally
Feet
0.63
7.1
24
3.6
6.7
12.4
0.17
0.26
0.24
1.4
21
1.9
exceed the means
Exposure Factors Handbook
September 2011
Page
7-53
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-21. Summary of Controlled Greenhouse Trials
Activity Ages Duration (min)
(years)
Transplanting Adult
Playing 8 to 12
Pipe Laying Adult 15,
42b
20
30,45
3 L = long sleeves and long pants; S =
b Arithmetic mean (range was 9 to 18
than at a fixed time.
TV = Number of subjects.
Source: Kissel etal., 1998.
Soil Moisture
(%)
17-19
15-18
17-18
16-18
3-4
9-12
5-7
short sleeves and
minutes). Activity
Clothing3
L
S
L
S
S
S
S
N
4
13
4
9
5
7
6
Male
2
6
o
J
5
o
6
4
3
short pants.
was terminated after completion of the
Female
2
7
1
4
2
3
3
task rather
Table 7-22. Dermal Transfer Factors for Selected Contact Surface Types and Skin Wetness,
Using <80 urn Tagged ATP
Mean surface
Loading ug/cm2
Test Subject3
Contact Surface
Typeb
Skin Moisture
Levef
Dermal Transfer
Factord
36.3
39.1
32.0
45.0
42.6
23.8
30.6
30.5
32.7
3 8.9 (not embedded)
36.4 (embedded)
33.8 (not embedded)
33.3 (embedded)
Fl
Ml
Ml
Ml
M2
M2
M2
M2
M2
M2
M2
M2
M2
SS
SS
SS
SS
SS
SS
SS
Vinyl
Vinyl
Carpet
Carpet
Carpet
Carpet
Dry
Dry
Damp
Wet
Dry
Damp
Wet
Dry
Damp
Dry
Dry
Damp
Damp
0.760 (0.000)
0.716 (NA)
1.222 (NA)
1.447 (NA)
0.582 (0.059)
0.970 (NA)
1.148(NA)
0.554 (0.052)
0.485 (0.068)
0.087 (0.000)
0.034 (0.007)
0.190(0.002)
0.169(0.11)
3 Fl = female subject; Ml and M2 = male subjects.
b SS = stainless steel; vinyl linoleum; nylon carpet.
0 Dry = no added moisture; wet = synthetic saliva moistened (moisture visible but not excessive).
d Dermal transfer factor = ug on hand/cm2 of dermal contact area/ug on surface/cm2 of surface contact.
Based on mean of left and right hand presses. Standard deviation (SD) in parenthesis; NA = not available.
Source: Rodes etal., 2001.
Page
7-54
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-23. Comparison of Adherence (mg/cm2) for Contact with Carpet and Aluminum Surfaces,
Averaged Across Pressure, Contact Time, Soil Type, and Soil Particle Size"
Mean
Mean
Mean
Soil Adherence
Soil-Skin Adherence
Soil-Cloth Adherence
a Soil adherence values averaged
Source: Ferguson et al., 2009b.
Carpet
Transfer
0.37 ±0.4
0.71 ±0.5
0.20 ±0.3
across pressure, time,
Hard Surface
(aluminum)
Transfer
0.42 ±0.6
1.18 ±0.4
0.15 ±0.4
soil type, and soil size.
Combined
(carpet/aluminum)
Transfer
0.39 ±0.4
0.92 ±0.5
0.17 ±0.4
Exposure Factors Handbook Page
September 2011 7-55
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Mineral
Oif
Cooking
Oilb
Bath
Oilc
Oil/
Waterd
Water6
Water/
Ethanolf
No wipe
Partial wipe1
Full wipe"
Secondary Contactk
No wipe11
Partial wipe1
Full wipe"
1.56
0.62
0.27
1.40
0.47
0.06
2.25
0.82
0.34
1.87
0.52
0.07
1.74
0.59
0.20
1.56
0.48
0.08
2.03
1.55
1.38
1.60
1.19
0.92
2.34
1.83
1.97
2.05
1.39
1.32
3.25
2.93
3.12
2.95
2.67
2.60
Table 7-24. Film Thickness Values of Selected Liquids Under Various Experimental Conditions
(10"3cm)
Initial Contact8
No wipe11 11.87 6.55 6.90 9.81 4.99 6.55
Partial wipe1 2.00 1.46 1.55 2.42 2.14 2.93
Handling Rag111
No wipe11
Partial wipe1
Full wipe1
1.64
0.44
0.13
1.50
0.34
0.01
2.04
0.53
0.21
1.88
1.21
0.96
2.10
1.48
1.37
4.17
3.70
3.58
Spill Cleanup"
Nowipeh 1.23 0.73 0.89 1.19
Partial wipe1 0.55 0.51 0.48 1.36
Full wipe"
Density = 0.8720 g/cm3.
Density = 0.9161 g/cm3.
Density = 0.8660 g/cm .
d Density = 0.93 57 g/cm3; 50% water and 50% oil.
Density = 0.9989 g/cm3.
f Density = 0.9297 g/cm3; 50% water and 50% ethanol.
8 Initial contact = cloth saturated with liquid was rubbed over the front and back of both clean, dry
hands for the first time during an exposure event.
h Retention of liquid on the skin was estimated without any intentional removal of liquid by wiping.
1 Retention was measured after 'partial' removal of liquids on the skin by wiping. Partial wiping
was defined as "lightly [wiping with a removal cloth] for 5 seconds (superficially)."
J Retention was measured after 'full' removal of liquids on the skin by wiping. Full wiping was
defined as " thoroughly and completely as possible within 10 seconds removing as much liquid as
possible."
k Secondary contact = cloth saturated with liquid was rubbed over the front and back of both hands
for a second time, after as much as possible of the liquid that adhered to skin during the first
contact event was removed using a clean cloth.
1 Immersion = one hand immersed in a container of liquid, removed, and liquid allowed to drip back
into container for 30 seconds (60 seconds for cooking oil).
m Handling rag = cloth saturated with liquid was rubbed over the palms of both hands for the first
time during an exposure event in a manner simulating handling of a wet cloth.
11 Spill cleanup = subject used a clean cloth to wipe up 50 mL of liquid poured onto a plastic
laminate countertop.
= no data.
Note: Data for mineral oil, cooking oil, and bath oil for initial contact, secondary contact, and immersion
from U.S. EPA (1992c). All other data from U.S. EPA (1987).
Source: U.S. EPA, 1987 and U.S. EPA, 1992c.
Page Exposure Factors Handbook
7-56 September 2011
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-25.
Time After Legs
Application13 (tights)
0 hours
6 hours
chlorpyrifos 6. 6 ±1.6
allethrin 5. 9 ±1.5
chlorpyrifos 7.5 ± 4.6
allethrin 5.3 ± 2.0
Mean Transfer Efficiencies (%)a
Torso and Arms Feet
(shirt) (socks)
5.6 ±2.6
5.4 ±2.4
6.3 ±5.8
4.8 ±2.5
32.1 ±13.4
34.3 ±18.3
33. 3 ±12.9
27.1 ±8.8
Hands
(gloves)
17.4 ±8.6
22.4 ±12.6
16.9 ±11.0
17.9 ±9.1
12.5 hours
a
b
Source:
chlorpyrifos 4.0 ±1.3
allethrin 3.0 ±0.8
Clothing residue values divided by
After room was vented.
Ross et al., 1990.
3.1±0.5
2.8 ±0.5
floor residues and
20.3 ±3. 5
13.7 ±4.7
multiplied by 100.
8.1 ±1.9
8.3 ±2.7
Table 7-26. Transfer Efficiencies (%) for Dry, Water-Wetted, and Saliva-Wetted Palms and PUF Roller
Dry Palms
Chlorpyrifos
Mean
SD
Pyrethrin
Mean
SD
Piperonyl Butoxide
Mean
SD
SD = Standard deviation.
PUF = Polyurethane foam.
Source: Clothier, 2000.
1.53
0.73
3.64
2.21
1.41
0.73
Water- Wetted Palms
5.22
3.02
11.87
7.25
4.85
2.95
Saliva- Wetted Palms
4.38
2.83
8.89
4.66
4.06
2.64
PUF Roller
4.19
2.87
5.66
3.60
4.28
3.33
Exposure Factors Handbook Page
September 2011 7-57
-------
Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-27. Incremental and Overall Surface to Hand Transfer Efficiencies (%)
Hand Condition
Contact Dry Moist Sticky
Incremental transfer %, average (SD)
1 3.0(2.7) 7.1(6.1) 14(18)
2 2.5(4.0) 7.7(5.7) 7.5(18)
3 2.0(5.4) 4.0(7.3) 6.9(7.3)
4 0.9(3.1) 1.9(2.5) 2.3(8.0)
5 1.3 (2.2) 1.0 (3.7) 2.0 (5.3)
Surface Type
Carpet
6.4 (7.0)
8.0 (9.5)
3.8 (7.2)
1.1 (6.3)
1.7 (2.4)
Incremental transfer %, average (SD) without sticky hands
1 3.0(2.7) 7.1(6.1) - 4.9(5.3
2 2.5(4.0) 7.7(5.7) - 5.8(6.0)
3 2.0(5.4) 4.0(7.3) - 2.1(6.4)
4 0.9(3.1) 1.9(2.5) - 0.9(3.0)
5 1.3(2.3) 1.0(3.7) - 1.6(1.6)
Overall
1
2
3
4
5
Overall
1
2
3
4
5
SD
Source:
transfer %, average (SD)
3.0(2.7) 7.1(6.1) 14(18)
2.8 (2.5) 7.4 (5.2) 11 (9.7)
2.5 (2.9) 6.2 (4.7) 9.7 (7.6)
2.1(2.4) 5.3(4.0) 7.9(7.0)
1.6 (0.8) 4.2 (3.4) 8.2 (6.9)
transfer %, average (SD) without sticky hands
3.0(2.7) 7.1(6.1)
2.8 (2.5) 7.4 (5.2)
2.5 (2.9) 6.2 (4.7)
2.1 (2.4) 5.3 (4.0)
1.6 (0.8) 4.2 (3.4)
= Standard deviation.
Cohen-Hubaletal., 2005.
6.4 (7.0)
7.2 (7.6)
6.1 (6.3)
5.0 (5.7)
4.6 (5.3)
4.9(5.3)
5.4 (5.0)
4.3 (4.0)
3.3 (3.3)
2.8 (2.4)
Laminate
10 (16)
3.6(13)
4.8 (6.8)
2.3 (4.2)
1.3 (4.9)
5.2 (4.9)
4.2 (4.9)
4.0 (6.4)
1.9 (2.6)
0.7 (3.8)
10 (16)
6.9(7.1)
6.2 (6.0)
5.4 (5.4)
4.6(5.1)
5.2 (4.9)
4.7 (4.3)
4.4 (4.6)
3.9 (4.0)
2.8 (3.0)
Surface
High
3.9 (4.0)
3.7(3.5)
1.7(1.7)
0.9(1.8)
0.3(1.1)
2.6(2.1)
2.8 (3.0)
1.4(1.3)
1.0(1.8)
0.4(1.2)
3.9 (4.0)
3.8(3.1)
3.1(2.2)
2.5(1.7)
1.8(1.0)
2.6(2.1)
2.7(2.1)
2.3 (1.4)
1.9(1.1)
1.4 (0.5)
Loading
Low
13 (16)
8.1(16)
7.0 (9.0)
2.7 (7.4)
2.5 (5.0)
7.5 (6.0)
7.3 (6.6)
4.7 (8.8)
1.8(3.8)
1.9(3.9)
13 (16)
10 (8.8)
9.3 (7.2)
8.2 (6.6)
7.1 (6.0)
7.5 (6.0)
7.4(5.3)
6.5(5.1)
5.7 (4.4)
4.2 (3.2)
Page
7-58
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-28. Lognormal Distributions for Modeling Transfer Efficiencies (fraction)3
Chemical
Chlorpyrifos
Pyrethrin I
Piperonyl
butoxide
a Distributions
GM = Geometric
GSD = Geometric
Source: Beameretal.
Surface
Carpet
Vinyl
Foil
Carpet
Vinyl
Foil
Carpet
Vinyl
should be truncated
mean.
standard deviation.
, 2009.
H
-4.26
-3.30
-0.15
-3.86
-3.66
-0.19
-4.00
-3.63
at 1.0.
0
0.54
0.85
0.08
0.68
0.96
0.10
0.51
0.81
GM
0.01
0.04
0.86
0.02
0.03
0.83
0.02
0.03
GSD
1.70
2.34
1.08
1.97
2.61
1.11
1.67
2.25
Table 7-29. Hand-to-Object/Surface Contact — Frequency
Object/Surface
Bedding/Towel
Carpet/Rug
Dirt
Food
Footwear
Grass/Vegetation
Hair
Hard Floor
Hard Surface
Hard Toy
Paper/Card
Plush Toy
Upholstered Furniture
Water/Beverage
a Average = mean of average
Left Hand Average3
13.0
4.3
5.3
9.3
2.0
6.3
4.5
10.0
36.0
27.3
8.8
4.0
17.0
1.3
(contacts/hour)
Right Hand Average3
13.8
6.0
6.5
9.3
3.0
5.0
3.5
9.5
40.3
29.3
14.5
4.0
15.5
1.8
hourly contact rates of 4 children of farm workers, ages 2 to 4 years.
Source: Zartarianetal., 1997.
Exposure Factors Handbook Page
September 2011 7-59
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-30. Hand-to-Objects/Surfaces — Frequency (contacts/hour)
RntVi Hanrk3
Object/Surface
Clothing
Dirt
Object
Otherb
Smooth Surface
Textured Surface
3 Based on data for 30
b Other includes items
Source: Reedetal., 1999.
Range
22.8-129.2
0-146.3
56.2-312.0
8.3-243.6
13.6-190.4
0.2-68.7
children (20 daycare
such as paper, grass,
Mean
66.6
11.4
122.9
82.9
83.7
22.1
children and 10 residential
and pets.
Median
65.0
0.3
118.7
64.3
80.2
16.3
children) a|
90th Percentile
103.3
56.4
175.8
199.6
136.9
52.2
*es 2 to 6 years.
Table 7-31. Median (mean ± SD) Hand Contact Frequency with Clothing, Surfaces, or Objects (contacts/hour)3
Age 3 to 4 years
N 3
Touch Clothing 26 (34 ± 2 1 )
Touch Textured 40 (52 ± 6 1 )
Surface
Touch Smooth 1 34 (1 5 1 ± 62)
Surface
Touch Object 130 (153 ± 108)
5 to 6 years
7
22 (26 ± 23)
20 (32 ± 40)
111 (120 ±77)
117 (132 ±88)
7 to 8 years
4
50 (54 ± 43)
22 (58 ± 88)
120 (155 ±119)
111 (164 ±148)
10 to 12 years
5
35 (53 ±66)
16 (24 ±31)
94 (96 ± 50)
127 (179 ±126)
a Based on 4-hour observation period.
SD = Standard deviation.
N = Number of children observed.
Source: Freeman et al., 2001 .
Table 7-32. Hand Contact with Objects/Surfaces — Frequency (contacts/hour)
Object/Surface
Bottle
Carpet/Rug
Clothes
Food
Hair
Hard Floor
Object
Paper
Skin
Smooth Surface
Textured Surface
Upholstered Furniture
Only data for the right
SD = Standard deviation.
Source: Freeman et al., 2005.
Right Hand3
Mean (SD)
14.6(17.9)
6.3 (9.3)
38.0(16.4)
9.2 (6.6)
5.1(3.6)
9.5 (6.2)
97.7 (45.8)
22.9 (18.0)
31.5(15.3)
83.9 (38.0)
6.5 (5.7)
20.7 (15.2)
hand were reported; data for 10 children, ages 24 to 55
Median (range)
11.5(1.3-63.0)
1.1 (0-23.0)
41.9(12.8-66.8)
7.3 (3.0-20.8)
4.1 (1.3-11.8)
10.3 (1.3-17.5)
96.8 (25.0-176.4)
21.8(1.3-54.3)
26.4 (16.0-63.5)
88.0 (32.0-158.4)
4.1(1.0-20.7)
19.3 (6.8-55.5)
months.
Page Exposure Factors Handbook
7-60 September 2011
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a
£
1=
Table 7-33. Outdoor Hand Contact with Object/Surfaces, Children 1 to 6 Years3
Both Hands
Object/Surface
Range
Mean
Median
95th
Percentile
Frequency (contacts/hour)
Animal
Body
Clothes/Towel
Fabric
Floor
Food
Footwear
Metal
Non-Dietary Water
Paper /Wrapper
Plastic
Rock/Brick
Toy
Vegetation/Grass
Wood
Non-Dietary Object
All Objects/Surfaces
Based on 38
0-23.3
17-191.7
17-199.1
0-31.5
0-940.4
0-88.7
0-23.1
0.6-466.2
0.7.4
0-103.8
0-324.6
0-28
0-657.8
0-138.7
0.6-100.9
225.1-1,512.6
229.9-1,517.7
children aged 1
2.6
74.8
73.7
3.7
65.8
14.5
3.6
58.3
0.5
7.3
56.7
2.4
161.3
40.6
22.4
575.3
589.8
0
65.1
65.7
0.4
27.9
4.9
1.5
16
0
1.5
47
0
129.4
27.8
12.7
526.3
540.8
13.8
150.4
132
14.7
182.7
56.2
11.4
206.4
2.9
21.4
121.1
10.3
372.8
128.1
79.8
889.2
889.2
Range Mean
Median
95*
Percentile
Duration (seconds/contact)
1.5-7 3.2
1-4 2
1-5 2.5
0.5-23.5 5.9
0-13 3
0-28 7.6
0-12 3.3
0-109.5 7.3
0.5-9 3.3
0-53.5 9.4
1-21.5 5.1
1-9 2.8
0-25.5 6.5
0-11 3.7
0-9 3.7
0-5 3
0-5 3
2.5
2
2
3
2
6
2.5
3
2
4.3
4
2
6
3
3
3
3
6.5
3.2
4.6
15.4
6.5
20.8
8.1
15.8
8.2
28.1
12.8
7.5
13.5
9.1
8
4
4.2
Range
Mean
Median 95th
Percentile
Duration (minutes/hour)
0-2
0.6-17.8
1.4-26.3
0-6.6
0-16.4
0-17.3
0-5.6
0-36.3
0-1
0-27
0-26.3
0-3.7
0-63.1
0-21.5
0-27.8
42.6-101.7
42.6-102.2
0.2
5
6.7
0.7
4
3.9
0.5
7.4
0.1
1.8
8
0.2
29.8
5.1
3.2
72.9
76.8
0
4.1
4.8
0
2.4
0.4
0
3.2
0
0.4
6
0
28.4
2.9
1.2
72.3
77.5
1.6
11.2
18.2
3.9
12.2
17
2
27.3
0.6
7.8
20.6
1
57
17.9
12.8
94.2
99.3
to 6 years in parks, playgrounds, and outdoor residential areas in California.
Source: AuYeung et al., 2006.
Q
I
§
ri
1=
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-34. Indoor Hand Contact with
Object/Surface
Carpet
Clothing
Hard Floor
Paper
Skin
Upholstered Furniture
Smooth Surface
Textured Surfaces
Object/Surfaces — Frequency, Children 1 to 6 Years3 (median contacts/hour)
Left Hand
7.9
41
3.2
3.8
11.6
13.1
61.9
18.2
Right Hand
8.5
25.2
3.9
7.4
9.9
7.7
62.7
22.1
a Based on 9 children aged 1 to 6 years in indoor residential settings in California.
Source: AuYeung et al, 2006.
Table 7-35. Outdoor Hand Contact with Surfaces — Frequency, Children 1 to 5 Years3 (contacts/hour)
Object/Surface
N Range
Cement 37 0-240
Porch 22 0-104
Grass 34 0-183
Bare Soil 27 0-81
All Surfaces 37 3-405
Geometric Mean
27
12
8
6
70
a Based on observations of a total of 37 children aged 1 to
residential areas in Illinois.
N = Number of subj ects .
SD = Standard deviation of log-transformed contacts/hour.
Source: Ko etal.,2007.
Both Hands
SD
0.59
0.74
0.71
0.67
0.44
5 years (primarily
Median 90th Percentile
36
16
7
5
81
low-income,
107
86
71
71
193
Hispanic) in outdoor
Page
7-62
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Table 7-36. Hand Contact with Object/Surfaces, Infants
and Toddlers"
Both Hands
Object/Surface
Animal
Body
Clothes/Towel
Fabric
Floor
Food
Footwear
Metal
Non-Dietary Water
Paper/Wrapper
Plastic
Rock/Brick
Toy
Vegetation
Wood
Non-Dietary Object
All Objects/Surfaces
Based on 23
Range
Frequency
0.0-4.3
16.6-147.1
39.2-237.9
0.0-134.4
0.0-594.5
0.0-170.7
0.0-47.0
0.0-52.4
0.0-2.6
0.0-75.3
10.9-294.9
0.0-17.4
28.3-300.4
0.0-16.3
0.0-65.4
266.8-1,180.0
303.1-1,206.0
Mean
Median
(contacts/hour)
0.2
76.8
113.8
45.6
96.0
51.8
7.8
17.3
0.2
18.1
87.1
3.4
121.2
3.8
24.9
600.8
686.3
0.0
70.5
100.9
37.6
41.5
42.7
2.4
14.5
0.0
18.7
76.1
1.6
98.8
0.3
27.2
568.7
689.4
Range
Mean
Median
Duration (minutes/hour )b
0.0-0.2
1.6-21.9
4.5-31.0
2.1-21.6
0.0-32.2
0.0-37.1
0.0-7.7
0.0-5.2
o.o-o.o
0.0-13.9
0.9-50.6
0.0-1.8
9.8-54.1
0.0-2.2
0.0-10.6
62.6-106.2
76.4-124.1
0.0
7.5
13.1
10.3
7.0
14.2
1.1
2.0
0.0
3.7
13.5
0.3
25.2
0.3
3.5
83.1
99.1
0.0
5.9
12.4
9.1
4.3
12.1
0.3
1.9
0.0
3.1
10.9
0.1
9.8
0.0
3.9
83.2
100.5
Range
Mean
Median
Duration (seconds/contact)
1.5-2.0
1.0-3.0
1.0-4.0
2.0-9.0
0.5-5.0
2.0-24.0
1.0-11.0
0.8-9.0
0.5-1.0
1.5-11.5
0.5-8.0
1.0-5.0
3.0-11.5
0.5-4.0
1.5-8.0
2.0-5.0
2.0-5.0
1.8
2.3
2.9
3.6
2.3
7.1
3.8
3.4
0.8
4.4
3.8
2.7
5.8
2.7
3.8
3.2
3.3
1.8
2.0
3.0
3.0
2.5
7.0
3.0
3.0
0.8
4.0
4.0
3.0
5.0
3.0
3.0
3.0
3.0
farm worker children (ages 6 to 26 months) from California.
b Hourly contact duration for both hands is the sum of the hourly contact durations for the
left and right
hands
independently.
Source: Beameretal
, 2008.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
.00
1.00
.00
1.CXJ
Surface Area: Men
Frequency Distribution
I.SO
2.00
8.50
Area »n m2. n«S,QOO» LHS
Surface Area: Women
Frequency Distribution
1.50
(C
a.DO
Area in m2, n=5,OM, LHS
Figure 7-1. Frequency Distributions for the Surface Area of Men and Women.
Source: Murray and Burmaster, 1992.
Page
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September 2011
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Figure 7-2.
Hands
Lower legs/short pants
Forearms/short sleeves
Faces -
20
Percent
Skin Coverage as Determined by Fluorescence versus Body Part for Adults Transplanting
Plants and Children Playing in Wet Soils (Bars are Arithmetic Means and Corresponding
95% Confidence Intervals).
Source: Kissel etal., 1998.
Hands
adult
child, wet
f^ 1
C 1 ™!
o
-Sb
J3
60 _ ,
e 0,1 -
'•6
1
w 0.01 ^
0.001 -
T T
X
J_ 4 )>
1 }
,/%
1 •
.
4
<
T
>
1 ]
I i
1 x!'
X
child, dry
> T . T
?f 0
[
Legs
Arms
Faces
Figure 7-3. Gravimetric Loading Versus Body Part for Adults Transplanting Plants in Wet Soil and
Children Playing in Wet and Dry Soils (Symbols are Geometric Means and 95% Confidence
Intervals).
Source: Kissel etal., 1998.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
APPENDIX 7A
FORMULAS FOR TOTAL BODY SURFACE AREA
Exposure Factors Handbook Page
September 2011 7A-1
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
APPENDIX 7A—FORMULAS FOR TOTAL
BODY SURFACE AREA
Most formulas for estimating surface area relate
height to weight to surface area. The following
formula was proposed by Gehan and George (1970):
SA = KW2/3
(Eqn. 7A-1)
where:
SA = surface area in square meters,
W = weight in kg, and
K = constant.
While this equation has been criticized because
human bodies have different specific gravities and
because the surface area per unit volume differs for
individuals with different body builds, it gives a
reasonably good estimate of surface area.
A formula published in 1916 that still finds wide
acceptance and use is that of DuBois and DuBois
(1916). Their model can be written:
SA = aQH 1 W
(Eqn. 7A-2)
where:
SA = surface area in square meters,
H = height in centimeters, and
W = weight in kg.
The values of ao (0.007182), aj (0.725), and a2
(0.425) were estimated from a sample of only
nine individuals for whom surface area was directly
measured. Boyd (1935) stated that the Dubois
formula was considered a reasonably adequate
substitute for measuring surface area. Nomograms for
determining surface area from height and mass
presented in Volume I of the Geigy Scientific Tables
(1981) are based on the DuBois and DuBois formula.
Boyd (1935) developed new constants for the
DuBois and DuBois model based on 231 direct
measurements of body surface area found in the
literature. These data were limited to measurements
of surface area by coating methods (122 cases),
surface integration (93 cases), and triangulation
(16 cases). The subjects were Caucasians of normal
body build for whom data on weight, height, and age
(except for exact age of adults) were complete.
Resulting values for the constants in the DuBois and
DuBois model were ao= 0.01787, ^ = 0.500, and
a2 = 0.4838. Boyd also developed a formula based
exclusively on weight, which was inferior to the
DuBois and DuBois formula based on height and
weight.
Gehan and George (1970) proposed another set of
constants for the DuBois and DuBois model. The
constants were based on a total of 401 direct
measurements of surface area, height, and weight of
all postnatal subjects listed in Boyd (1935). The
methods used to measure these subjects were coating
(163 cases), surface integration (222 cases), and
triangulation (16 cases).
Gehan and George (1970) used a least-squares
method to identify the values of the constants. The
values of the constants chosen are those that
minimize the sum of the squared percentage errors of
the predicted values of surface area. This approach
was used because the importance of an error of
0.1 square meter depends on the surface area of the
individual. Gehan and George (1970) used the
401 observations summarized in Boyd (1935) in the
least-squares method. The following estimates of the
constants were obtained: a0= 0.02350, ai =0.42246,
and a2 = 0.51456. Hence, their equation for predicting
surface area is:
SA = 0.02350 H°-42246W°-51456
or in logarithmic form:
(Eqn. 7A-3)
In SA = -3.75080 + 0.42246 InH + 0.51456 InW
(Eqn. 7A-4)
where:
SA = surface area in square meters,
H = height in centimeters, and
W = weight in kg.
This prediction explains more than 99% of the
variations in surface area among the 401 individuals
measured (Gehan and George, 1970).
The equation proposed by Gehan and George
(1970) was determined by the U.S. EPA (1985) to be
the best choice for estimating total body surface area.
However, the paper by Gehan and George gave
insufficient information to estimate the standard error
about the regression. Therefore, the 401 direct
measurements of children and adults (i.e., Boyd,
1935) were reanalyzed in U.S. EPA (1985) using the
formula of Dubois and Dubois (1916) and the
Page
7A-2
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
Statistical Processing System (SPS) software package
to obtain the standard error.
The Dubois and Dubois (1916) formula uses
weight and height as independent variables to predict
total body surface area and can be written as:
SAj = a0 H°l W^ e. (Eqn. 7A-5)
or in logarithmic form:
In (SA)i = Ina0 + ctilnHj + a2lnWt + lnet (Eqn. 7A-6)
where:
SAt = surface area of the i-th
individual (m2),
Hj = height of the i-th individual
(cm),
Wi = weight of the i-th individual
(kg),
a0, ai, and a2 = parameters to be estimated,
and
et = a random error term with
mean zero and constant
variance.
Using the least squares procedure for the
401 observations, the following parameter estimates
and their standard errors were obtained:
a0 = -3.73 (0.18), a, = 0.417 (0.054), a2 = 0.517
(0.022)
The model is then:
SA = 0.0239 H°'417 W°'517 (Eqn. 7A-7)
or in logarithmic form:
In SA = -3.73 + 0.417 InH + 0.517 InW (Eqn. 7A-8;
with a standard error about the regression of 0.00374.
This model explains more than 99% of the total
variation in surface area among the observations, and
it is identical to two significant figures with the
model developed by Gehan and George (1970).
When natural logarithms of the measured surface
areas are plotted against natural logarithms of the
surface predicted by the equation, the observed
surface areas are symmetrically distributed around a
line of perfect fit with only a few large percentage
deviations. Only five subjects differed from the
measured value by 25% or more. Because each of the
five subjects weighed less than 13 pounds, the
amount of difference was small. Eighteen estimates
differed from measurements by 15 to 24%. Of these,
12 weighed less than 15 pounds each, one was
overweight (5 feet 7 inches, 172 pounds), one was
very thin (4 feet 11 inches, 78 pounds), and four were
of average build. Because the same observer
measured surface area for these four subjects, the
possibility of some bias in measured values cannot be
discounted (Gehan and George, 1970). Gehan and
George (1970) also considered separate constants for
different age groups: less than 5 years old, 5 years old
to less than 20 years old, and greater than 20 years
old. Table 7A-1 presents the different values for the
constants.
The surface areas estimated using the parameter
values for all ages were compared to surface areas
estimated by the values for each age group for
subjects at the 3rd, 50th, and 97th percentiles of weight
and height. Nearly all differences in surface area
estimates were less than 0.01 m2, and the largest
difference was 0.03 m2 for an 18-year-old at the
97th percentile. The authors concluded that there is no
advantage in using separate values of ao, ai, and a2 by
age interval.
Haycock etal. (1978), without knowledge of the
work by Gehan and George (1970), developed values
for the parameters ao, ai, and a2 for the DuBois and
DuBois model. Their interest in making the DuBois
and DuBois model more accurate resulted from their
work in pediatrics and the fact that DuBois and
DuBois (1916) included only one child in their study
group: a severely undernourished girl who weighed
only 13.8pounds at age 21 months. Haycock etal.
(1978) used their own geometric method for
estimating surface area from 34 body measurements
for 81 subjects. Their study included newborn infants
(10 cases), infants (12 cases), children (40 cases), and
adult members of the medical and secretarial staffs of
two hospitals (19 cases). The subjects all had grossly
normal body structure, but the sample included
subjects of widely varying physique ranging from
thin to obese. Black, Hispanic, and Caucasian
children were included in their sample. The values of
the model parameters were solved for the relationship
between surface area and height and weight by
multiple regression analysis. The least squares best fit
for this equation yielded the following values for the
three co-efficients: ao = 0.024265, aj = 0.3964, and
a2 = 0.5378. The result was the following equation
for estimating surface area:
Exposure Factors Handbook
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Exposure Factors Handbook
Chapter 7—Dermal Exposure Factors
SA = 0.024265H03964 W°'5178
expressed logarithmically as:
(Eqn. 7A-9)
In SA = In 0.024265 + 0.3964 In H + 0.5378 In W
(Eqn. 7A-10)
The co-efficients for this equation agree
remarkably with those obtained by Gehan and
George (1970) for 401 measurements.
George etal. (1979) agree that a model more
complex than the model of DuBois and DuBois for
estimating surface area is unnecessary. Based on
samples of direct measurements by Boyd (1935) and
Gehan and George (1970), and samples of geometric
estimates by Haycock etal. (1978), these authors
have obtained parameters for the DuBois and DuBois
model that are different than those originally
postulated in 1916. The DuBois and DuBois model
can be written logarithmically as:
InSA = Ina0 + a,InH + a2lnW (Eqn. 7A-11)
Table 7A-2 present the values for ao, ai, and a2
obtained by the various authors discussed in this
section.
The agreement between the model parameters
estimated by Gehan and George (1970) and Haycock
etal. (1978) is remarkable in view of the fact that
Haycock etal. (1978) were unaware of the previous
work. Haycock et al. (1978) used an entirely different
set of subjects and used geometric estimates of
surface area rather than direct measurements. It has
been determined that the Gehan and George model is
the formula of choice for estimating total surface area
of the body because it is based on the largest number
of direct measurements.
Sendroy and Cecchini (1954) proposed a method
of creating a nomogram, a diagram relating height
and weight to surface area. However, they do not give
an explicit model for calculating surface area. The
nomogram was developed empirically based on
252 cases, 127 of which were from the 401 direct
measurements reported by Boyd (1935). In the other
125 cases, the surface area was estimated using the
linear method of DuBois and DuBois (1916).
Because the Sendroy and Cecchini method is
graphical, it is inherently less precise and less
accurate than the formulas of other authors discussed
in this section.
7A.1. REFERENCES FOR APPENDIX 7A
Boyd, E. (1935) The growth of the surface area of the
human body. Minneapolis, MN: University
of Minnesota Press.
Dubois, D; Dubois, EF. (1916) A formula to estimate
the approximate surface area if height and
weight be known. Arch Intern Med
17:863-871.
Gehan, E; George, GL. (1970) Estimation of human
body surface area from height and weight.
Cancer Chemother Rep 54(4):225-235.
Geigy Scientific Tables. (1981) Nomograms for
determination of body surface area from
height and mass. Lentner, C. (ed.). West
Caldwell, NJ:CIBA-Geigy Corporation; pp.
226-227.
George, SL; Gehan, EA; Haycock, GB; etal. (1979)
Letters to the editor. J Pediatr 94(2):342.
Haycock, GB; Schwartz, GJ; Wisotsky, DH. (1978)
Geometric method for measuring body
surface area: A height-weight formula
validated in infants, children, and adults. J
Pediatr 93(l):62-66.
Sendroy, J; Cecchini, LP (1954) Determination of
human body surface area from height and
weight. J Appl Physiol 7(1):3-12.
U.S. EPA (Environmental Protection Agency). (1985)
Development of statistical distributions or
ranges of standard factors used in exposure
assessments. Office of Health and
Environmental Assessment, Washington,
DC; EPA 600/8-85-010. Available from:
NTIS, Springfield, VA; PB85-242667.
Page
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Chapter 7—Dermal Exposure Factors
Age
Group
All ages
<5 years old
>5 to <20 years old
>20 years old
Source: Gehanand
Table 7A-1. Estimated
Number
of Persons
401
229
42
30
George, 1970.
Parameter Values for Different Age Intervals
a0
0.02350
0.02667
0.03050
0.01545
ai
0.42246
0.38217
0.35129
0.54468
a2
0.51456
0.53937
0.54375
0.46336
Table 7A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model
Author
(year)
DuBois and DuBois (1916)
Boyd (1935)
Gehan and George (1970)
Hay cock etal. (1978)
Number
of Persons
9
231
401
81
a0
0.007184
0.01787
0.02350
0.024265
ai
0.725
0.500
0.42246
0.3964
a2
0.425
0.4838
0.51456
0.5378
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Chapter 8—Body Weight Studies
TABLE OF CONTENTS
LIST OF TABLES 8-ii
LIST OF FIGURES 8-iii
8. BODY-WEIGHT STUDIES 8-1
8.1. INTRODUCTION 8-1
8.2. RECOMMENDATIONS 8-1
8.3. KEY BODY-WEIGHT STUDY 8-4
8.3.1. U.S. EPAAnalysis of NHANES 1999-2006 Data 8-4
8.4. RELEVANT GENERAL POPULATION BODY-WEIGHT STUDIES 8-4
8.4.1. National Center for Health Statistics (NCHS) (1987)—Anthropometric Reference
Data and Prevalence of Overweight, United States, 1976-1980 8-4
8.4.2. Brainard and Burmaster (1992)—Bivariate Distributions for Height and Weight of
Men and Women in the United States 8-5
8.4.3. Burmaster and Crouch (1997)—Lognormal Distributions for Body Weight as a
Function of Age for Males and Females in the United States, 1976-1980 8-5
8.4.4. U.S. EPA (2000)—Body-Weight Estimates on NHANES III Data 8-6
8.4.5. Kuczmarski et al. (2002)—CDC Growth Charts for the United States: Methods and
Development 8-6
8.4.6. U.S. EPA (2004)—Estimated Per Capita Water Ingestion and Body Weight in the
United States—An Update 8-6
8.4.7. Ogden et al. (2004)—Mean Body Weight, Height, and Body Mass Index,
United States 1960-2002 8-7
8.4.8. Freedman et al. (2006)—Racial and Ethnic Differences in Secular Trends for
Childhood BMI, Weight, and Height 8-7
8.4.9. Martin et al. (2007)—Births: Final Data for 2005 8-7
8.4.10. Portieretal. (2007)—Body Weight Distributions for Risk Assessment 8-8
8.4.11. Kahn and Stralka (2008)—Estimated Daily Average Per Capita Water Ingestion by
Child and Adult Age Categories Based on USD As 1994-1996 and 1998 Continuing
Survey of Food Intakes 8-8
8.5. RELEVANT STUDIES—PREGNANT WOMEN BODY-WEIGHT STUDIES 8-8
8.5.1. Carmichael et al. (1997)—The Pattern of Maternal Weight Gain in Women with
Good Pregnancy Outcomes 8-8
8.5.2. U.S. EPAAnalysis of 1999-2006 NHANES Data on Body Weight of Pregnant
Women 8-9
8.6. RELEVANT FETAL WEIGHT STUDIES 8-9
8.6.1. Brenner et al. (1976)—A Standard of Fetal Growth for the United States of America... 8-9
8.6.2. Doubilet et al. (1997)—Improved Birth Weight Table for Neonates Developed from
Gestations Dated by Early Ultrasonography 8-10
8.7. REFERENCES FOR CHAPTER 8 8-10
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LIST OF TABLES
Table 8-1. Recommended Values for Body Weight 8-2
Table 8-2. Confidence in Recommendations for Body Weight 8-3
Table 8-3. Mean and Percentile Body Weights (kg) Derived from NHANES (1999-2006) 8-12
Table 8-4. Mean and Percentile Body Weights (kg) for Male Derived from NHANES (1999-2006) 8-13
Table 8-5. Mean and Percentile Body Weights (kg) for Female Derived from NHANES (1999-2006) 8-14
Table 8-6. Weight in Kilograms for Male 2 Months-21 Years of Age—Number Examined, Mean, and
Selected Percentiles, by Age Category: United States, 1976-19803 8-15
Table 8-7. Weight in Kilograms for Female 6 Months-21 Years of Age—Number Examined, Mean, and
Selected Percentiles, by Age Category: United States, 1976-19803 8-16
Table 8-8. Statistics for Probability Plot Regression Analyses: Female Body Weights 6 Months to 70 Years
of Age 8-17
Table 8-9. Statistics for Probability Plot Regression Analyses: Male Body Weights 6 Months to 70 Years of
Age 8-18
Table 8-10. Body-Weight Estimates (kg) by Age and Sex, U.S. Population Derived from NHANES III
(1988-1994) 8-19
Table 8-11. Body-Weight Estimates (in kg) by Age, U.S. Population Derived From NHANES III (1988-1994) 8-20
Table 8-12. Observed Mean, Standard Deviation, and Selected Percentiles for Weight (kg) by Sex and Age:
Birth to 36 Months 8-21
Table 8-13. Estimated Distribution of Body Weight by Fine Age Categories All Individuals, Male and Female
Combined (kg) 8-22
Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys 8-23
Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys 8-25
Table 8-16. Mean Body Mass Index (kg/m2) by Age and Sex Across Multiple Surveys 8-27
Table 8-17. Sample Sizes by Age, Sex, Race, and Examination 8-29
Table 8-18. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex
(Ages 2 to 17) 8-30
Table 8-19. Mean Body Mass Index (kg/m2) by Survey, Sex, Race/Ethnicity, and Age Group; Adults:
United States 8-31
Table 8-20. Prevalence of Overweight and Obesity3 Among Children 8-32
Table 8-21. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth
Weights, by Race, and Hispanic Origin of Mother: United States, 2005 8-33
Table 8-22. Estimated Mean Body Weights of Male and Female by Single-Year Age Groups Using
NHANES II Data 8-34
Table 8-23. Estimated Mean Body Weights of Male and Female by Single-Year Age Groups Using
NHANES III Data 8-36
Table 8-24. Estimated Mean Body Weights of Male and Female by Single-Year Age Groups Using
NHANES IV Data 8-38
Table 8-25. Estimated Body Weights of Typical Age Groups of Interest in U. S. EPA Risk Assessments3 8-40
Table 8-26. Estimated Percentile Distribution of Body Weight by Fine Age Categories 8-41
Table 8-27. Estimated Percentile Distribution of Body Weight by Fine Age Categories with Confidence
Interval 8-42
Table 8-28. Distribution of 1st Trimester Weight Gain and 2nd and 3rd Trimesters Rates of Gain in Women with
Good Pregnancy Outcomes 8-43
Table 8-29. Estimated Body Weights of Pregnant Women—NHANES (1999-2006) 8-44
Table 8-30. Fetal Weight (g) Percentiles Throughout Pregnancy 8-45
Table 8-31. Neonatal Weight by Gestational Age for Male and Female Combined 8-46
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LIST OF FIGURES
Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months 8-47
Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months 8-48
Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months 8-49
Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months 8-50
Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years 8-51
Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years 8-52
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8. BODY-WEIGHT STUDIES
8.1. INTRODUCTION
There are several physiological factors needed to
calculate potential exposures. These include skin
surface area (see Chapter?), inhalation rate (see
Chapter 6) life expectancy (see Chapter 18), and
body weight. The average daily dose (ADD) is a dose
that is typically normalized to the average body
weight of the exposed population. If exposure occurs
only during childhood years, the average child body
weight during the exposure period should be used to
estimate risk (U.S. EPA, 1989). Conversely, if adult
exposures are being evaluated, an adult body-weight
value should be used.
The purpose of this chapter is to describe
published studies on body weight in the general U.S.
population. The recommendations for body weight
are provided in the next section, along with a
summary of the confidence ratings for these
recommendations. The recommended values are
based on one key study identified by
U.S. Environmental Protection Agency (EPA) for
this factor. Following the recommendations, the key
study on body weight is summarized. Relevant data
on body weight are also provided. These relevant
data are included because they may be useful for
trend analysis. Since obesity is a growing concern
and may increase the risk of chronic diseases during
adulthood, information on body mass index (BMI)
and height is also provided.
8.2. RECOMMENDATIONS
The key study described in this section was used
in selecting recommended values for body weight.
The recommendations for body weight are
summarized in Table 8-1 and are based on data
derived from the National Health and Nutrition
Examination Survey (NHANES) 1999-2006. The
recommended values represent mean body weights in
kilograms for the age groups for children
recommended by U.S. EPA in Guidance for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005) and
for adults. Table 8-2 presents the confidence ratings
for the body-weight recommendations.
Table 8-1 shows the mean body weight for all
adults (male and female, all age groups) combined is
80 kg. Section 8.3 presents percentile data.
The mean recommended value for adults (80 kg)
is different from the 70 kg commonly assumed in
U.S. EPA risk assessments. Assessors are encouraged
to use values that most accurately reflect the exposed
population. When using values other than 70 kg,
however, the assessors should consider if the dose
estimate will be used to estimate risk by combining it
with a dose-response relationship that was derived
assuming a body weight of 70 kg. If such an
inconsistency exists, the assessor may need to adjust
the dose-response relationship as described in the
appendix to Chapter 1.
Use of upper percentile body-weight values are
not routinely recommended for calculating ADDs
because inclusion of an upper percentile value in the
denominator of the ADD equation would be a
non-conservative approach. However, Section 8.3
provides distributions of body-weight data. These
distributions may be useful if probabilistic methods
are used to assess exposure. Also, if sex-specific data
are needed, or if data for finer age bins are needed,
the reader should refer to the tables in Section 8.3.
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Table 8-1. Recommended Values for Body Weight
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <11 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
Adults
Mean (kg) Multiple Percentiles
4.8
5.9
7.4
9.2
1L4 Tables 8-3
13 g through 8-5
18.6
31.8
56.8
71.6
80.0
Source
U.S. EPA
analysis of
NHANES,
1999-2006 data
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Table 8-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Confidence in Recommendations for Body Weight
Rationale
The survey methodology and the secondary data analysis
were adequate. NHANES consisted of a large sample size;
sample size varied with age. Direct measurements were
taken during a physical examination.
No significant biases were apparent.
The key study is directly relevant to body weight.
NHANES was a nationally representative sample of the
U.S. population; participants are selected using a complex,
stratified, multi-stage probability cluster sampling design.
The U.S. EPA analysis used the most current NHANES
data.
The U.S. EPA analysis was based on four data sets of
NHANES data covering 1999-2006.
NHANES data are available from NCHS.
The methods used were well-described; enough information
was provided to allow for reproduction of results.
NHANES follows a strict QA/QC procedures; the U.S. EPA
analysis has only been reviewed internally.
The full distributions were given in the key study.
No significant biases were apparent in the NHANES data,
nor in the secondary analyses of the data.
NHANES received a high level of peer review. The
U.S. EPA analysis was not published in a peer-reviewed
journal.
The number of studies is 1 .
Rating
High
High
High
High
Medium
High
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8.3. KEY BODY-WEIGHT STUDY
8.3.1. U.S. EPA Analysis of NHANES
1999-2006 Data
The U.S. EPA analyzed data from the 1999-2006
NHANES to generate distributions of body weight
for various age ranges of children and adults.
NHANES is conducted annually by the Center for
Disease Control (CDC), National Center of Health
Statistics (NCHS). The survey's target population is
the civilian, non-institutionalized U.S. population.
The NHANES 1999-2006 survey was conducted on
a nationwide probability sample of approximately
40,000 persons for all ages, of which approximately
20,000 were children. The survey is designed to
obtain nationally representative information on the
health and nutritional status of the population of the
United States through interviews and direct physical
examinations. A number of anthropometric
measurements, including body weight, were taken for
each participant in the study. Unit non-response to
the household interview was 19%, and an additional
4% did not participate in the physical examinations
(including body-weight measurements).
The NHANES 1999-2006 survey includes
over-sampling of low-income persons, adolescents
12-19 years, persons 60+years of age, African
Americans and Mexican Americans. Sample data
were assigned weights to account both for the
disparity in sample sizes for these groups and for
other inadequacies in sampling, such as the presence
of non-respondents. Because the U.S. EPA utilized
four NHANES data sets in its analysis (NHANES
1999-2000, 2001-2002, 2003-2004, and
2005-2006) sample weights were developed for the
combined data set in accordance with CDC guidance
from the NHANES' website
(http://www.cdc.gov/nchs/about/major/nhanes/nhane
s2005-2006/faqs05_06.htm#question%2012).
Using the data and the weighting factors from the
four NHANES data sets, U.S. EPA calculated body-
weight statistics for the standard age categories. The
mean value for a given group was calculated using
the following formula:
X =
(Eqn. 8-1)
where:
= sample mean,
= the /'* observation, and
= sample weight assigned to observation xt.
Percentile values were generated by first
calculating the sum of the sample weights for all
observations in a given group and multiplying this
sum by the percentile of interest (e.g., multiplying by
0.25 to determine the 25th percentile). The
observations were then ordered from least to greatest,
and each observation was assigned a cumulative
sample weight, equal to its own sample weight plus
all sample weights listed before the observation. The
1st observation listed with a cumulative sample
weight greater than the value calculated for the
percentile of interest was selected.
Table 8-3 presents the body-weight means and
percentiles, by age category, for males and females
combined. Tables 8-4 and 8-5 present the body-
weight means and percentiles for males and females,
respectively.
The advantage of this study is that it provides
body-weight distributions ranging from infancy to
adults. A limitation of the study is that combining the
data from various years of NHANES beginning in
1999 through 2006 may underestimate current body
weights due to an observed upward trend in body
weights (Ogden et al., 2004). However, these data are
based on the most recent available NHANES data.
The NHANES data are nationally representative and
remain the principal source of body-weight data
collected nationwide from a large number of subjects.
8.4. RELEVANT GENERAL POPULATION
BODY-WEIGHT STUDIES
8.4.1. National Center for Health Statistics
(NCHS) (1987)—Anthropometric
Reference Data and Prevalence of
Overweight, United States, 1976-1980
The NCHS (1987) collected anthropometric
measurement data for body weight for the U.S.
population as part of the 2nd National Health and
Nutrition Examination Survey (NHANES II).
NHANES II began in February 1976 and was
completed in February 1980. The survey was
conducted on a nationwide probability sample of
27,801 persons aged six months to 74 years from the
civilian, non-institutionalized population of the
United States. A total of 20,322 individuals in the
sample were interviewed and examined, resulting in a
response rate of 73.1%. The sample was selected so
that certain subgroups thought to be at high risk of
malnutrition (persons with low incomes, preschool
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children, and the elderly) were over sampled. The
estimates were weighted to reflect national
population estimates. The weighting was
accomplished by inflating examination results for
each subject by the reciprocal of selection
probabilities, adjusting to account for those who were
not examined, and post-stratifying by race, age, and
sex.
NHANES II collected standard body
measurements of sample subjects, including height
and weight, that were made at various times of the
day and in different seasons of the year. This
technique was used because an individual's weight
may vary between winter and summer and may
fluctuate with patterns of food and water intake and
other daily activities (NCHS, 1987). NCHS (1987)
provided descriptive statistics of the body-weight
data. Tables 8-6 and 8-7 present means and
percentiles, by age category, for males and females,
respectively. Although the NHANES data are
nationally representative, a limitation of the study is
the age of the data used.
8.4.2. Brainard and Burmaster
(1992)—Bivariate Distributions for
Height and Weight of Men and Women in
the United States
Brainard and Burmaster (1992) examined data on
the height and weight of adults published by the U.S.
Public Health Service and fit bivariate distributions to
the tabulated values for men and women, separately.
Height and weight of 5,916 men and 6,588 women in
the age range of 18 to 74 years were taken from the
NHANES II (1976-1980) study and statistically
adjusted to represent the U.S. population aged 18 to
74 years with regard to age structure, sex, and race.
Estimation techniques were used to fit normal
distributions to the cumulative marginal data, and
goodness-of-fit tests were used to test the hypothesis
that height and lognormal weight follow a normal
distribution for each sex. It was found that the
marginal distributions of height and lognormal
weight for both men and women are Gaussian
(normal) in form. This conclusion was reached by
visual observation and the high R2 values for best-fit
lines obtained using linear regression. The R2 values
for men's height and lognormal weight were reported
to be 0.999. The R2 values for women's height and
lognormal weight were reported as 0.999 and 0.985,
respectively.
Brainard and Burmaster (1992) fit bivariate
distributions to estimated numbers of men and
women aged 18 to 74 years in cells representing one-
inch height intervals and 10-pound weight intervals.
Adjusted height and lognormal weight data for men
were fit to a single bivariate normal distribution with
an estimated mean height of 1.75 meters
(69.2 inches) and an estimated mean weight of
78.6kg (173.2 pounds). For women, height and
lognormal weight data were fit to a pair of
superimposed bivariate normal distributions
(Brainard and Burmaster, 1992). The average height
and weight for women were estimated from the
combined bivariate analyses. Mean height for women
was estimated to be 1.62 meters (63.8 inches), and
mean weight was estimated to be 65.8 kg
(145.0 pounds). For women, a calculation using a
single bivariate normal distribution gave poor results
(Brainard and Burmaster, 1992).
The advantage of this study is that it provides
distributions that are suitable for use in Monte Carlo
simulation. However, these distributions are now
based on dated information.
8.4.3. Burmaster and Crouch
(1997)—Lognormal Distributions for
Body Weight as a Function of Age for
Males and Females in the United States,
1976-1980
Burmaster and Crouch (1997) performed data
analysis to fit normal and lognormal distributions to
the body weights of females and males aged
9 months to 70 years. The data used in this analysis
were from NHANES II, which was based on a
national probability sample of 27,801 persons
6 months to 74 years of age in the United States.
(Burmaster and Crouch, 1997). The NHANES II data
had been statistically adjusted for non-response and
probability of selection, and stratified by age, sex,
and race to reflect the entire U.S. population prior to
reporting. Burmaster and Crouch (1997) conducted
exploratory and quantitative data analyses and fit
normal and lognormal distributions to percentiles of
body weights as a function of age. Cumulative
distribution functions were plotted for female and
male body weights on both linear and logarithmic
scales.
Burmaster and Crouch (1997) used "maximum
likelihood" estimation to fit lognormal distributions
to the data. Linear and quadratic regression lines
were fitted to the data. A number of goodness-of-fit
measures were conducted on the data generated. The
investigators found that lognormal distributions gave
strong fits to the data for each sex across all age
groups. Tables 8-8 and 8-9 present the statistics for
the lognormal probability plots for females and males
aged 9 months to 70 years, respectively. As indicated
in Burmaster and Crouch (1997), O2, and o2 are the
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Chapter 8—Body Weight Studies
mean and standard deviation of the logarithm of body
weight for an age group. The exponential of O2
provides an estimate of the median of body weight,
and o2 is approximately equal to the coefficient of
variation of the body weight. These data can be used
for further analyses of body-weight distribution (i.e.,
application of Monte Carlo analysis).
The advantage of this study is that NHANES data
were used for the analysis and the data are
representative nationally. It also provides statistics
for probability plot regression analyses for females
and males from 9 months to 70 years of age.
However, the analysis is based on an older set of
NHANES data.
8.4.4. U.S. EPA (2000)—Body-Weight
Estimates on NHANES III Data
U.S. EPA's Office of Water has estimated body
weights by age and sex using data from NHANES
III, which was conducted from 1988 to 1994.
NHANES III collected body-weight data for
approximately 30,000 individuals between the ages
of 2 months and 44 years. Table 8-10 presents the
body-weight estimates in kilograms by age and sex.
Table 8-11 shows the body-weight estimates for
infants 2 and 3 months of age.
The limitations of this analysis are that data were
not available for infants under 2 months old, and that
the data are roughly 15 to 20 years old. With the
upward trends in body weight from NHANES II
(1976-1980) to NHANES III, which may still be
valid, the data in Tables 8-10 and 8-11 may
underestimate current body weights. However, the
data are national in scope and represent the general
population.
8.4.5. Kuczmarski et al. (2002)—CDC Growth
Charts for the United States: Methods
and Development
NCHS published growth charts for infants, birth
to 36 months of age, and children and adolescents, 2
to 20 years of age (Kuczmarski et al., 2002). Growth
charts were developed with data from five national
health examination surveys: National Health
Examination Survey (NHES) II (1963-1965) for ages
6-11 years, NHES III (1966-1970) for ages
12-17 years, NHANES I (1971-1974) for ages
1-17 years, NHANES II (1976-1980) beginning at
6 months of age, and NHANES III (1988-1994)
beginning at 2 months of age. Data from these
national surveys were pooled because no single
survey had enough observations to develop these
charts. For the infant charts, a limited number of
additional data points were obtained from other
sources where national data were either not available
or insufficient. Birth weights <1,500 grams were
excluded when generating the charts for weights and
lengths. Also, the length-for-age charts exclude data
from NHANES III for ages <3.5 months.
Supplemental birth certificate data from the U.S. vital
statistics were used in the weight-for-age charts and
supplemental birth certificate data from Wisconsin
and Missouri vital statistics, CDC Pediatric Nutrition
Surveillance System data were used for ages 0.5, 1.5,
2.5, 3.5, and 4.5 months for the length-for-age charts.
The Missouri and Wisconsin birth certificate data
were also used to supplement the surveys for the
weight-for-length charts. Table 8-12 presents the
percentiles of weight by sex and age. Figures 8-1 and
8-2 present weight by age percentiles for boys and
girls, aged birth to 36 months, respectively.
Figures 8-3 and 8-4 present weight by length
percentiles for boys and girls, respectively.
Figures 8-5 and 8-6 provide the BMI for boys and
girls aged 2 to 20 years old.
The advantages of this analysis are that it is based
on a nationally representative sample of the U.S.
population and it provides body weight on a month-
by-month basis up to 36 months of age, as well as
BMI data for children through age 20 years. A
limitation of this analysis is that trends in the weight
data cannot be assessed because data from various
years were combined. Also, the analysis is based on
an older data set.
8.4.6. U.S. EPA (2004)—Estimated Per Capita
Water Ingestion and Body Weight in the
United States—An Update
U.S. EPA (2004) developed estimates from
empirical distributions of body weights based on data
from the U.S. Department of Agriculture (USDA's)
1994-1996 and the 1998 Continuing Survey of Food
Intake by Individuals (CSFII). The weights recorded
in the survey, and, consequently, the estimates
reported, are based on serf-reported data by the
participants.
When viewed across sexes and all age categories,
the average serf-reported body weight for individuals
in the United States during the 1994-1996 and 1998
period is 65 kg, or 143 Ib. The estimated median
body weight for all individuals is 67 kg (147 Ib).
Table 8-13 provides the estimated distribution of
body weights for all individuals.
For the fine age categories reported in the
summary data, the mean and median estimated body
weights are the same for children in categories less
than 2 years of age. This suggests that body weights
follow an approximately normal distribution. After
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the age of 2 years, estimated mean body weights are
higher than estimated median body weights as age
categories increase. This suggests that the
distributions of body weights are skewed to the right.
When viewed across ages, the estimated median body
weight is higher than the estimated mean body
weight. This suggests that the body-weight
distribution across the entire survey weighted sample
is slightly skewed to the left. The limitations of this
analysis are that body weights were serf-reported and
that it is based on an older data set.
8.4.7. Ogden et al. (2004)—Mean Body Weight,
Height, and Body Mass Index, United
States 1960-2002
Ogden et al. (2004) analyzed trends in body
weight measured by the NHES II and III, NHANES
I, II, and III, and NHANES 1999-2002. The surveys
covered the period from 1960 to 2002. Table 8-14
presents the measured body weights for various age
groups as measured in NHES and NHANES.
Tables 8-15 and 8-16 present the mean height and
BMI data for the same population, respectively. The
BMI data were calculated as weight (in kilograms)
divided by the square of height (in meters).
Population means were calculated using sample
weights to account for variation in sampling for
certain subsets of the U.S. population, non-response,
and non-coverage (Ogden etal., 2004). The data
indicate that mean body weight has increased over
the period analyzed.
There is some uncertainty inherent in such an
analysis, however, because of changes in sampling
methods during the 42-year time span covered by the
studies. This serves to illustrate the importance of the
use of timely data when analyzing body weight.
Because this study is based on an analysis of
NHANES data, its limitations are the same as those
for that study. Another limitation is that the data are
based on an older NHANES data set and may not be
entirely representative of current BMI values.
8.4.8. Freedman et al. (2006)—Racial and
Ethnic Differences in Secular Trends for
Childhood BMI, Weight, and Height
Freedman et al. (2006) examined sex and
race/ethnicity differences in secular trends for
childhood BMI, overweight, weight, and height in the
United States using data from NHANES I
(1971-1974), NHANES II (1976-1980), NHANES
III (1988-1994), and NHANES 1999-2002. The
analyses includes children 2 to 17 years old. Persons
with missing weight or height information were
excluded from the analyses (Freedman et al., 2006).
The authors categorized the data across the
four examinations and presented the data for
non-Hispanic White, non-Hispanic Black, or
Mexican American. Freedman et al. (2006) excluded
other categories of race/ethnicity, such as other
Hispanics, because the sample sizes were small.
Height and weight data were obtained for each
survey, and BMI was calculated as weight in
kilograms divided by height in meters square. Sex
specific z-scores and percentiles of weight-for-age,
height-for-age, and BMI-for-age were calculated.
Childhood overweight was defined as BMI-for-age
>95th percentile, and childhood obesity was defined
as children with a BMI-for-age >99* percentile.
In the analyses, sample weights were used to
account for differential probabilities, non-selection,
non-response, and non-coverage. Table 8-17 presents
the sample sizes used in the analyses by age, sex,
race, and survey. Table 8-18 provides mean BMI
levels for ages 2 to 17. Table 8-19 shows BMI mean
levels for adults 20 years and older (Ogden et al.,
2004). Table 8-18 shows that in the 1971-1974
survey total population, Mexican American children
had the highest mean BMI level (18.6 kg/m2).
However, the greatest increase throughout the survey
occurred among Black children, increasing from 17.8
to 20kg/m2 (Freedman etal., 2006). Table 8-20
shows the prevalence of overweight and obesity for
children 2 to 17 years old. These results show that 2
to 5 year-old White children had slightly larger
increases in overweight, but among the older
children, the largest increases were among the Black
and Mexican American children (Freedman et al.,
2006). Overall, in most sex-age groups, Mexican
Americans experienced the greater increase in BMI
and overweight than what was experienced by Black
and White children (Freedman etal., 2006). Black
children experienced larger secular increases in BMI,
weight, and height than did White children
(Freedman et al., 2006). According to Freedman et al.
(2006), racial/ethnicity differences were less marked
in the children aged two to five years old.
The advantages of the study are that the sample
size is large and the analysis was designed to
represent the general population of the racial and
ethnic groups studied. The disadvantage is that some
ethnic population groups were excluded because of
small sample sizes and that it is based on older
NHANES data sets.
8.4.9. Martin et al. (2007)—Births: Final Data
for 2005
Martin et al. (2007) provided statistics on the
percentage of live births categorized as having low or
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Chapter 8—Body Weight Studies
very low birth weights in the United States. Low
birth weight was defined as <2,500 grams (<5 pounds
8 ounces), and very low birth weight was defined as
<1,500 grams (
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Chapter 8—Body Weight Studies
Obstetrics, Gynecology and Reproductive Sciences
Perinatal Database at the University of California,
San Francisco. Distributions were derived for
4,218 women for whom complete data on pattern of
gain for all trimesters were obtained. The mean age
of the women was 27.7 years with a mean
pre-pregnancy weight of 57.6 kg.
Twenty-nine percent of the women were
underweight, 61% were of normal weight, 5% were
overweight, and 4% were obese, based on BMI
calculations. Total weight gain was calculated as the
difference between the self-reported pre-pregnancy
weight and the last measured weight. A linear
regression was applied to estimate the rate of gain in
the 2nd and 3rd trimesters. Table 8-28 presents the
distributions of weight gain in underweight, normal
weight, overweight, and obese women during the 1st,
2nd, and 3rd trimesters. The average weight gains for
the 1st, 2nd, and 3rd trimesters were 1.98kg, 6.73 kg,
and 6.37 kg, respectively. The weight gain for the 2nd
and 3rd trimesters was calculated by taking the gain
rate from Table 8-28 and multiplying it by 13 weeks.
These data can be used to calculate the average
weight of pregnant women for the 1st, 2nd, and
3rd trimesters by adding the average weight gain for
the 1st trimester to the average pre-pregnancy weight
of 57.6 kg and subsequently adding the average
weight gain for the 2nd and 3rd trimesters to the
resulting weight from the previous trimester. These
calculations result in a total weight of 59.6 kg,
66.3 kg, and 72.7 kg for the 1st, 2nd, and 3rd trimesters,
respectively.
The advantages of this study are that it has a large
sample size, and it provides distributional data. The
sample, however, may not be representative of the
United States. The sample also only included
pregnancies with good outcomes. The study did not
provide estimates of the weight for each trimester.
Instead, it provides weight gain for the 1st trimester
and the rates of weight gain for the 2nd and
3rd trimesters. The total weight was estimated by the
U.S. EPA based on the mean weight gain for each
trimester.
8.5.2. U.S. EPA Analysis of 1999-2006
NHANES Data on Body Weight of
Pregnant Women
In 2010, U.S. EPA analyzed the combined
1999-2006 NHANES data sets to examine body
weight of pregnant women. Data for 1,248 pregnant
women with weight measurements were extracted
based from the data set based on either a positive lab
pregnancy test or self-reporting of pregnancy at the
examination. The NHANES data included a few very
large and improbable body weights, as extreme as
186 kg from a respondent in the 1st trimester. These
outliers were removed from the database (N = 26)
using SAS. Table 8-29 presents the body-weight data
by trimester, based on the remaining
1,222 respondents. The statistically weighted average
body weight of all pregnant women was 75 kg. Due
to a few large weight (>90 kg) respondents with very
large sample weights (> 18,000), the weighted mean
body weight of 1st trimester women (76 kg) is larger
than that of 2nd trimester women (73 kg).
The advantage of this study is that by combining
eight years of the most recent NHANES data, an
adequate sample size was achieved to estimate body
weight of pregnant women by trimester. A limitation
of this analysis is that high-weight respondents with
large sample weight may result in uncertainties as
described above.
8.6. RELEVANT FETAL WEIGHT
STUDIES
8.6.1. Brenner et al. (1976)—A Standard of
Fetal Growth for the United States of
America
Brenner et al. (1976) determined fetal weights for
430 fetuses aborted at 8 to 20 weeks of gestation and
for 30,772 liveborn infants delivered at 21 to
44 weeks of gestation. Gestational age for the aborted
fetuses was determined through a combination of the
physician's estimate of uterine size and the patient's
stated last normal menstrual period. Data were not
used when these two estimates differed by more than
two weeks. To determine fetal growth, the fetuses
were weighed and measured (crown-to-rump and
crown-to-heel lengths). All abortions were legally
performed at Memorial Hospital, University of North
Carolina, at Chapel Hill, from 1972 to 1975. For the
liveborn infants, data were analyzed from single birth
deliveries with the infant living at the onset of labor,
among pregnancies not complicated by pre-
eclampsia, diabetes or other disorders. Infants were
weighed on a balance scale immediately after
delivery. The liveborn infants were delivered at
MacDonald House, University Hospitals of
Cleveland, OH, from 1962 to 1969.
Table 8-30 shows percentiles for fetal weight,
calculated from the data at each week of gestation.
The resulting percentile curves were smoothed with
two-point weighted means. Variables associated with
significant differences in fetal weight in the latter part
of pregnancy (after 34-38 weeks of gestation)
included maternal parity and race, and fetal sex.
The advantage of this study is the large sample
size. Limitations of the study are that the data were
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Chapter 8—Body Weight Studies
collected more than 30 years ago in only two U.S.
states. In addition, a number of variables that may
affect fetal weight (i.e., maternal smoking, disease,
nutrition, and addictions) were not evaluated in this
study.
8.6.2. Doubilet et al. (1997)—Improved Birth
Weight Table for Neonates Developed
from Gestations Dated by Early
Ultrasonography
Doubilet et al. (1997) matched a database of
obstetrical ultrasonograms over a period of five years
from 1988 to 1993 to birth records for 3,718 infants
(1,857 males and 1,861 females). The study
population included 1,514 Whites, 770 Blacks,
1,256 Hispanics, and 178 who were either
unclassified, or classified as "other." Birth weights
were obtained from hospital records, and a
gestational age was assigned based on the earliest
1st trimester sonogram. The database was screened
for possible outliers, defined as infants with birth
weights that exceeded 5,000 grams. Labor and
delivery records and mother-infant medical records
were retrieved to correct any errors in data entry for
infants with birth weights exceeding 5,000 grams.
The mean gestational age at initial sonogram was 9.5
± 2.3 weeks. Regression analysis techniques were
used to derive weight tables for neonates at each
gestational age for 25 weeks of gestation onward.
Weights for each gestational age were found to
conform to a natural logarithm distribution.
Polynomial equations were derived from the
regression analysis to estimate mean weight by
gestational age for males, females, and males and
females combined. Table 8-31 provides the
distribution of neonatal weights by gestational age
from 25 weeks of gestation onward. The advantage of
this study is that it provides body weights for
neonates based on a relatively large sample. A
limitation is the age of the data.
Risk
Anal
8.7.
REFERENCES FOR CHAPTER 8
Brainard, J; Burmaster, D. (1992) Bivariate
distributions for height and weight of men
and women in the United States. Risk Anal
12(2):267-275.
Brenner, WE; Edelman, DA; Hendricks, CH. (1976)
A standard of fetal growth for the United
States of America. Am J Obstet Gynecol
l:126(5):555-564.
Burmaster, DE; Crouch, EAC. (1997) Lognormal
distributions for body weight as a function
of age for males and females in the United
States, 1976-1980.
17(4):499-505.
Carmichael, S; Abrams, B; Selvin, S. (1997) The
pattern of maternal weight gain in women
with good pregnancy outcomes. Am J Pub
Health 87(12): 1984-1988.
Doubilet, PM; Benson, CB; Nadel, AS; Ringer, SA.
(1997) Improved birth weight table for
neonates developed from gestations dated by
early ultrasonography. J Ultrasound Med
16:241-249.
Freedman, D; Kettel, K; Serdula, M; Ogden, C;
Dietz, W. (2006) Racial and ethnic
differences in secular trends for childhood
BMI, weight, and height. Obesity
14(2):301-307.
Kahn, H; Stralka, K. (2008) Estimated daily average
per capita water ingestion by child and adult
age categories based on USDA's 1994-96
and 1998 continuing survey of food intakes
(CSFII). J Expo Sci Environ Epidemiol
19(4):396-404.
Kuczmarski, RJ; Ogden, CL; Quo, SS; et al. (2002)
2000 CDC growth charts for the United
States: methods and development. National
Center for Health Statistics. Vital Health
Stat 11(246). Available online at
http://www.cdc.gov/nchs/data/series/sr_ll/s
rll_246.pdf.
LSRO (Life Sciences Research Office). (1995) Third
report on nutrition monitoring in the United
States: Volume 1. Prepared by: Federation
of American Societies for Experimental
Biology, Life Sciences Research Office for
the Interagency Board for Nutrition
Monitoring and Related Research.
Washington, DC: U.S. Government Printing
Office.
Martin, J; Hamilton, B; Sutton, P; et al. (2007)
Births: final data for 2005. CDC National
Vital Statistics Report, Vol 56. No. 6.
NCHS (National Center for Health Statistics). (1987)
Anthropometric reference data and
prevalence of overweight, United States,
1976-80. Data from the National Health and
Nutrition Examination Survey, Series 11,
No. 238. U.S. Department of Health and
Human Services, Public Health Service,
National Center for Health Statistics,
Hyattsville, MD; DHHS Publication No.
(PHS) 87-1688.
Ogden, CL; Fryar, CD; Carroll, MD; Flegal, KM.
(2004) Mean body weight, height, and body
mass index, United States 1960-2002.
Advance data from Vital and Health
Page
8-10
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Exposure Factors Handbook
Chapter 8—Body Weight Studies
Statistics, No. 347, October 27, 2004. U.S.
Department of Health and Human Services,
Centers for Disease Control and Prevention,
National Center for Health Statistics,
Hyattsville, MD.
Portier K; Tolson, J; Roberts, S. (2007) Body weight
distributions for risk assessment. Risk Anal
27(1): 11-26.
U.S. EPA (Environmental Protection Agency).
(1989) Risk assessment guidance for
Superfund, Volume I: Human health
evaluation manual. Office of Emergency and
Remedial Response, Washington, DC;
EPA/540/1-89/002.
U.S. EPA (Environmental Protection Agency).
(2000) Memorandum entitled: Body weight
estimates on NHANES III data, revised,
Contract 68-C-99-242, Work Assignment 0-
1 from Bob Clickner, Westat Inc. to Helen
Jacobs, U.S. EPA dated March 3, 2000.
U.S. EPA (Environmental Protection Agency).
(2004) Estimated per capita water ingestion
in the United States-an update. Office of
Water, Washington, DC;
EPA/822/R 00/001.
U.S. EPA (Environmental Protection Agency).
(2005) Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants
Risk Assessment Forum, Washington, DC;
EPA/630/P-03/003F. Available online at
http://www.epa.gOv/raf/publications/pdfs/A
GEGROUPS.PDF.
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Table 8-3. Mean and Percentile Body Weights (kg) Derived from NHANES (1999-2006)
Male and Female Combined
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
Over 80 years
N
158
284
489
927
1,176
1,144
2,318
3,593
5,297
4,851
3,232
3,176
3,121
2,387
2,782
2,033
1,430
Mean
4.8
5.9
7.4
9.2
11.4
13.8
18.6
31.8
56.8
71.6
78.4
80.8
83.6
83.4
82.6
76.4
68.5
Percentiles
5th
3.6
4.5
5.7
7.1
8.9
10.9
13.5
19.7
34.0
48.2
50.8
53.5
54.3
54.7
55.2
52.0
46.9
10th
3.9
4.7
6.1
7.5
9.3
11.5
14.4
21.3
37.2
52.0
54.7
57.4
58.8
59.0
59.8
56.5
51.4
15th
4.1
4.9
6.3
7.9
9.7
11.9
14.9
22.3
40.6
54.5
57.9
60.1
62.1
62.8
63.3
59.7
53.8
25th
4.2
5.2
6.7
8.3
10.3
12.4
15.8
24.4
45.0
58.4
63.3
66.1
68.3
69.1
69.0
64.4
58.2
50th
4.8
5.9
7.3
9.1
11.3
13.6
17.8
29.3
54.2
67.6
75.2
77.9
81.4
80.8
80.5
74.9
67.4
75th
5.1
6.6
8.0
10.1
12.4
14.9
20.3
36.8
65.0
80.6
88.2
92.4
95.0
95.5
94.2
86.8
77.4
85th
5.5
6.9
8.4
10.5
13.0
15.8
22.0
42.1
73.0
90.8
98.5
101.0
104.0
104.0
103.0
93.8
82.6
90th
5.8
7.1
8.7
10.8
13.4
16.3
23.6
45.6
79.3
97.7
106.0
107.0
111.0
110.0
109.0
98.0
87.2
95th
6.2
7.3
9.1
11.3
14.0
17.1
26.2
52.5
88.8
108.0
118.0
118.0
122.0
120.0
116.0
106.0
93.6
Source: U.S. EPA Analysis of NHANES 1999~2006 data.
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Table 8-4. Mean and Percentile Body Weights (kg) for Male Derived from NHANES (1999-2006)
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to<21 years
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
Over 80 years
N
88
153
255
472
632
558
1,158
1,795
2,593
2,462
1,359
1,445
1,545
1,189
1,360
1,079
662
Mean
4.9
6.0
7.6
9.4
11.6
14.1
18.8
31.9
57.6
77.3
84.9
87.0
90.5
89.5
89.1
83.9
76.1
Percentiles
5*
3.6
4.6
5.9
7.3
9.0
11.4
13.5
20.0
33.6
54.5
58.7
61.1
64.9
64.1
63.4
60.6
56.7
10th
3.6
5.0
6.4
7.9
9.7
12.0
14.4
21.8
36.3
57.6
63.0
65.7
69.5
68.8
67.5
64.6
60.6
15*
4.0
5.1
6.6
8.2
10.0
12.2
14.9
22.9
38.9
60.0
66.2
68.7
73.0
71.4
71.6
68.3
63.9
25th
4.4
5.4
6.9
8.5
10.5
12.8
15.9
24.8
44.2
63.9
70.7
73.8
77.7
77.0
77.2
73.1
67.2
50th
4.8
6.1
7.5
9.4
11.5
14.0
18.1
29.6
55.5
73.1
81.2
84.0
87.4
87.8
86.9
82.1
75.1
75th
5.5
6.8
8.2
10.3
12.6
15.2
20.8
36.4
66.5
86.0
94.0
96.5
99.7
99.8
99.4
93.8
84.0
85th
5.8
7.0
8.6
10.6
13.2
15.9
22.6
41.2
75.5
96.8
103.0
104.0
109.0
107.0
108.0
98.6
89.4
90th
6.2
7.2
8.8
10.8
13.5
16.4
23.8
45.2
81.2
104.0
111.0
110.0
114.0
112.0
113.0
104.0
92.5
95th
6.8
7.3
9.1
11.5
14.3
17.0
26.2
51.4
91.8
113.0
123.0
124.0
125.0
123.0
120.0
113.0
100.0
Source: U.S. EPA Analysis of NHANES 1999-2006 data.
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Table 8-5. Mean and Percentile
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <30 years
30 to <40 years
40 to <50 years
50 to <60 years
60 to <70 years
70 to <80 years
Over 80 years
N
70
131
234
455
544
586
1,160
1,798
2,704
2,389
1,873
1,731
1,576
1,198
1,422
954
768
Mean
4.6
5.7
7.2
9.0
11.1
13.5
18.3
31.7
55.9
65.9
71.9
74.8
77.1
77.5
76.8
70.8
64.1
Source: U.S. EPA Analysis of NHANES
Body Weights (kg) for Female Derived from NHANES (1999-2006)
Percentiles
5th
3.6
4.3
5.5
7.1
8.7
10.5
13.5
19.3
34.9
46.2
48.0
50.9
51.7
52.2
51.9
49.6
45.5
10th
4.0
4.6
5.9
7.3
9.1
11.0
14.3
20.9
38.6
48.6
51.4
54.0
54.7
55.7
56.5
53.3
48.7
15th
4.1
4.74
6.2
7.6
9.4
11.5
14.7
22.0
41.6
51.1
53.8
56.2
57.3
57.9
59.2
55.7
51.3
25th
4.2
5.1
6.4
8.0
10.0
12.1
15.6
23.9
45.7
54.5
57.8
60.0
61.7
62.8
63.9
60.3
54.9
50th
4.6
5.5
7.2
8.9
11.1
13.2
17.5
29.0
53.3
61.5
67.9
70.2
72.7
73.6
73.9
69.0
62.8
75*
4.9
6.4
7.9
9.8
12.2
14.6
19.7
37.3
62.8
73.3
81.4
85.0
88.0
87.7
86.6
79.4
71.8
85*
5.0
6.6
8.2
10.3
12.9
15.5
21.3
43.1
70.7
83.4
90.2
95.1
97.8
97.7
95.4
85.6
77.0
90th
5.2
6.9
8.4
10.6
13.2
16.2
23.2
46.7
76.5
89.9
98.7
104.0
105.0
105.0
102.0
91.4
80.5
95th
5.9
7.3
9.0
11.2
13.7
17.1
26.2
53.4
86.3
99.7
109.0
113.0
118.0
117.0
112.0
98.2
89.1
1999-2006 data.
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ft
1=
Table 8-6. Weight in Kilograms for Male 2 Months-21 Years of Age — Number Examined, Mean, and Selected Percentiles, by
Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Number of
Persons Mean
Examined (kg)
-
-
103
287
589
613
627
1,556
1,373
1,037
890
-
-
6.6
7.7
9.4
11.7
13.7
18.0
30.7
55.2
71.8
5th
-
-
5.3
6.3
7.5
9.4
11.4
13.7
19.5
34.0
54.1
a Includes clothing weight, estimated as ranging from 0.09 to 0
No data available for infants less than 2 months old.
Source: NCHS,
1987.
10th
-
-
5.5
6.6
7.9
9.8
11.8
14.6
21.1
36.5
56.6
28kg.
15th
-
-
5.7
6.7
8.1
10.1
12.2
14.9
22.1
38.7
58.3
25th
-
-
5.9
7.0
8.6
10.8
12.6
15.7
24.0
42.8
61.8
Percentiles
50th
-
-
6.8
7.7
9.4
11.7
13.6
17.5
28.5
53.0
68.7
75th
-
-
7.2
8.4
10.2
12.6
14.6
19.7
35.2
63.0
77.9
85th
-
-
7.6
8.9
10.6
13.1
15.2
21.0
40.5
69.4
84.3
90th
-
-
7.8
9.2
10.9
13.7
15.8
22.0
43.5
74.8
89.7
95th
-
-
8.4
9.6
11.4
14.5
16.5
24.0
48.7
84.3
101.0
Q
I
i
I
8s
I
I
Ore
ft
-------
§
s
a
fcsi 1=
Table 8-7. Weight in Kilograms for Female 6 Months-21 Years of Age — Number Examined, Mean, and Selected Percentiles, by
Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Number of
Persons
Examined
-
-
131
269
574
617
597
1,658
1,321
1,144
1,001
Mean
(kg)
-
-
6.0
7.1
8.8
11.0
13.4
18.0
30.6
53.2
62.2
5th
-
-
4.7
5.8
7.2
9.1
10.8
13.3
19.0
34.1
46.7
10th
-
-
5.1
5.9
7.5
9.4
11.2
14.0
20.5
37.2
48.2
15th
-
-
5.2
6.1
7.7
9.6
11.6
14.5
21.3
40.4
49.7
Percentiles
25th *
-
50
5.6 6.0
6.4 7.1
8.0 8.7
9.9 10.9
12.1 13.2
15.4 17.2
23.4 28.9
45.2 51.6
52.2 58.9
75th
-
-
6.5
7.7
9.4
11.9
14.6
19.7
35.0
60.0
68.3
85th
-
-
7.1
7.9
10.1
12.6
15.4
21.1
39.6
67.2
74.7
90th
-
-
7.3
8.4
10.4
12.9
15.6
22.6
44.3
70.6
80.8
95th
-
-
7.8
8.7
10.8
13.4
16.3
25.1
50.2
78.2
92.6
a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kg.
No data available for infants less than 2 months old.
Source: NCHS,
1987.
Q
I
I
§
I
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-8. Statistics for Probability
Age Midpoint (years)
Plot Regression Analyses: Female Body Weights
of Age
Lognormal Probability Plots
Linear Curve
6 Months to 70 Years
H2a o2a
0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
21.5
30
40
50
60
70
2.16
2.38
2.56
2.69
2.83
2.98
3.10
3.19
3.31
3.46
3.57
3.71
3.82
3.92
3.99
4.00
4.05
4.08
4.07
4.10
4.10
4.15
4.19
4.20
4.20
4.18
0.145
0.129
0.112
0.136
0.134
0.164
0.174
0.174
0.156
0.214
0.199
0.226
0.213
0.215
0.187
0.156
0.167
0.165
0.147
0.149
0.168
0.204
0.207
0.208
0.205
0.198
a ®2, "2 — correspond to the mean and the standard deviation, respectively, of the logarithm of body weight (kg) for an age group.
Source: Burmaster and Crouch, 1997.
Exposure Factors Handbook Page
September 2011 8-17
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-9. Statistics for Probability Plot Regression Analyses: Male Body Weights 6 Months to
70 Years of Age
Age Midpoint (years)
Lognormal Probability Plots
Linear Curve
tf
0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
21.5
30
40
50
60
70
2.23
2.46
2.60
2.75
2.87
2.98
3.13
3.21
3.33
3.43
3.59
3.69
3.78
3.88
4.02
4.09
4.20
4.19
4.25
4.26
4.29
4.35
4.38
4.38
4.35
4.29
a (1)2, o2 — correspond to the mean and the standard deviation, respectively, of the logarithm of body
Source: Burmaster and Crouch, 1997.
0.131
0.120
0.120
0.114
0.133
0.138
0.145
0.151
0.181
0.165
0.195
0.252
0.224
0.215
0.181
0.159
0.168
0.167
0.159
0.154
0.163
0.163
0.165
0.166
0.157
0.174
weight (kg) for an age group.
Page Exposure Factors Handbook
8-18 September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-10. Body-Weight Estimates (kg) by Age and Sex, U.S. Population Derived from NHANES III
(1988-1994)
Age Group
2 to 6 months
7 to 12 months
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
1 1 years
12 years
13 years
14 years
15 years
16 years
17 years
>1 years
1 to 3 years
1 to 14 years
15 to 44 years
Source: U.S.
Sample Size
1,020
1,072
1,258
1,513
1,309
1,284
1,234
750
736
711
770
751
754
431
428
415
378
427
410
31,311
4,080
12,344
10,393
EPA, 2000.
Population
1,732,702
1,925,573
3,935,114
4,459,167
4,317,234
4,008,079
4,298,097
3,942,457
4,064,397
3,863,515
4,385,199
3,991,345
4,270,211
3,497,661
3,567,181
4,054,117
3,269,777
3,652,041
3,719,690
251,097,002
12,711,515
56,653,796
118,430,653
Male and Female
Median
7.4
9.4
11.3
13.2
15.3
17.2
19.6
21.3
25.0
27.4
31.8
35.2
40.6
47.2
53.0
56.9
59.6
63.2
65.1
66.5
13.2
24.9
70.8
Mean
7.4
9.4
11.4
12.9
15.1
17.1
19.4
21.7
25.5
28.1
32.7
35.6
41.5
46.9
55.1
61.1
62.8
65.8
67.5
64.5
13.1
29.9
73.5
Male
Median
7.6
9.7
11.7
13.5
15.5
17.2
19.7
21.5
25.4
27.2
32.0
35.9
38.8
48.1
52.6
61.3
62.6
66.6
70.0
73.9
13.4
25.1
77.5
Mean
7.7
9.7
11.7
13.1
15.2
17.0
19.3
22.1
25.5
28.4
32.3
36.0
40.0
49.1
54.5
64.5
66.9
69.4
72.4
89.0
13.4
30.0
80.2
Female
Median
7.0
9.1
10.9
13.0
15.1
17.3
19.6
20.9
24.1
27.9
31.1
34.3
43.4
45.7
53.7
53.7
57.1
56.3
60.7
80.8
13.0
24.7
63.2
Mean
7.0
9.1
11.0
12.5
14.9
17.2
19.4
21.3
25.6
27.9
33.0
35.2
42.8
48.6
55.9
57.9
59.2
61.6
62.2
80.3
12.9
29.7
67.3
Exposure Factors Handbook
September 2011
Page
8-19
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-11. Body-Weight Estimates
Age Group (months)
2
3
3 and younger
Sample Size
243
190
433
(in kg) by Age, U.S.
Population
408,837
332,823
741,660
Population Derived
Median
6.3
7.0
6.6
From NHANES
IH (1988-1994)
Male and Female
Mean 95% CI
6.3
6.9
6.6
6.1-6.4
6.7-7.1
6.4-6.7
CI = Confidence Interval.
Source: U.S. EPA, 2000.
Page Exposure Factors Handbook
8-20 September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-12. Observed Mean, Standard Deviation, and Selected Percentiles for Weight (kg) by Sex and
Age: Birth to 36 Months
Age Group
. . Mean
(mo)
SD
Percentile
10th
25th
50th
75th
90th
95th
Boys
Birth
Oto
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-13. Estimated Distribution of Body Weight by Fine Age Categories All
Individuals, Male and Female Combined (kg)
Ages
(years)
<0.5
0.5 to 0.9
Ito3
4 to 6
7 to 10
11 to 14
15 to 19
20 to 24
25 to 54
55 to 64
65+
Sample Size
744
678
3,645
2,988
1,028
790
816
676
4,830
1,516
2,139
Population
1,890,461
1,770,700
11,746,146
11,570,747
14,541,011
15,183,156
17,825,164
18,402,877
111,382,877
20,691,260
30,578,210
Percentiles
Mean
10th
6
9
14
21
32
51
67
72
77
77
72
3
7
10
16
22
35
50
53
54
57
54
25th
4
8
11
17
26
42
56
59
63
65
62
50th 75th
6
9
13
20
29
50
63
68
75
75
71
7
10
16
22
36
58
73
81
86
87
81
90th
8
11
18
26
43
68
85
94
100
99
93
95th
9
12
19
28
48
79
99
104
109
105
100
Summary Data
20 +
<2
2 to 15
15+
<6
6 to 15
All ages
9,161
2,424
7,449
9,977
7,530
2,343
19,850
181,055,224
7,695,535
49,006,686
198,880,388
23,160,174
33,542,047
255,582,609
Note: 757 individuals did not report body weight.
Source: U.S.
EPA, 2004 (based on
76
10
33
75
15
40
65
54
5
15
54
8
22
22
63
7
19
61
11
27
52
73
10
28
72
14
36
67
They represent 6,314,627 individuals
86
11
43
84
18
50
81
98
13
56
97
21
59
95
107
14
63
106
23
68
104
in the population.
1994-1996, 1998USDACSFII).
Page
8-22
Exposure Factors Handbook
September 2011
-------
Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys
Sex
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
IS
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II, 1963-1965
N Mean SE
-
-
575
632
618
603
576
595
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
22.0
24.7
27.8
31.2
33.7
38.2
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
0.1
0.2
0.2
0.4
0.3
0.3
-
-
-
-
-
-
-
-
-
-
-
-
-
-
NHES III, 1966-1970 NHANES II, 1976-1980
N Mean SE N Mean SE
-
-
-
-
-
-
-
-
643
626
618
613
556
458
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
42.9
50.0
56.7
61.6
64.8
68.1
-
-
-
-
-
-
-
-
370
421
405
393
146
150
145
141
165
153
0.4 147
0.5 165
0.6 188
0.4 180
0.6 180
0.4 183
156
150
1,261
871
695
691
2,086
-
13.4
15.5
17.6
19.7
22.8
24.9
28.0
30.7
36.2
39.7
44.1
49.5
56.4
61.2
66.5
66.7
71.1
71.8
76.3
79.8
81.7
80.0
76.1
-
0.1
0.1
0.1
0.1
0.4
0.4
0.6
0.6
0.7
0.9
1.0
1.2
0.9
1.0
1.2
0.8
1.2
0.8
0.5
0.4
0.5
0.6
0.5
-
NHANES III, 1988-1994
N Mean SE
644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168
1,638
1,468
1,220
851
1,683
895
13.6
15.8
17.6
20.1
23.2
26.3
30.2
34.4
37.3
42.5
49.1
54.0
64.1
66.9
68.7
72.9
71.3
73.0
78.4
82.9
85.1
86.0
82.2
75.4
0.1
0.2
0.2
0.2
0.6
0.4
0.8
1.0
0.9
0.9
1.1
1.0
3.6
1.9
1.6
1.3
1.7
2.2
0.6
0.9
0.8
0.5
0.5
0.7
NHANES, 1999-2002
N Mean SE
262
216
179
147
182
185
214
174
187
182
299
298
266
283
306
313
284
270
712
704
776
598
1,001
523
13.7
15.9
18.5
21.3
23.5
27.2
32.7
36.0
38.6
43.7
50.4
53.9
63.9
68.3
74.4
75.6
75.6
78.2
83.4
86.0
89.1
88.8
87.1
78.5
0.1
0.2
0.2
0.5
0.4
0.4
1.0
0.7
0.8
1.1
1.3
1.9
1.6
1.1
1.4
1.4
1.1
1.3
0.7
0.9
0.7
0.9
0.6
0.6
Q
I
i
I
8s
-------
I
§
s
Table 8-14. Mean Body Weight (kg) by Age
Sex
and Age
(years)
\j •**"•*/
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II, 1963-1965
N
.
.
.
-
536
609
613
581
584
525
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Mean SE
-
-
-
-
21.5 0.2
24.2 0.2
27.5 0.2
31.4 0.4
35.2 0.4
39.8 0.4
-
-
-
-
-
-
-
-
-
-
-
-
-
-
and Sex Across Multiple
NHES III, 1966-1970 NHANES II, 1976-1980
N Mean SE N
330
367
388
369
150
154
125
154
128
143
547 46.6 0.4 146
582 50.5 0.5 155
586 54.2 0.4 181
503 56.5 0.5 144
536 58.1 0.7 167
442 57.6 0.6 134
156
158
1,290
964
765
793
2,349
.
Mean
12.8
14.8
16.8
19.4
21.9
24.6
27.5
31.7
35.7
41.4
46.1
50.9
54.3
55.0
57.7
59.6
59.0
59.8
61.7
66.1
67.6
68.4
66.8
-
SE
0.1
0.1
0.2
0.3
0.4
0.5
0.4
0.7
0.6
0.9
0.9
1.2
1.0
0.8
0.9
1.0
1.0
1.0
0.5
0.6
0.6
0.6
0.4
-
Surveys (continued)
NHANES III, 1988-1994
N
624
587
537
554
272
274
248
280
258
275
236
220
218
191
208
201
175
177
1,663
1,773
1,355
996
1,674
1,022
Mean
13.2
15.4
17.9
20.2
22.6
26.4
29.9
34.4
37.9
44.1
49.0
55.8
58.5
58.1
61.3
62.4
61.2
63.2
64.4
70.2
71.6
74.3
70.1
63.4
SE
0.1
0.1
0.3
0.2
0.6
0.8
0.6
1.2
1.2
1.1
1.2
1.6
1.4
1.1
1.4
1.2
1.9
1.9
0.6
0.8
0.8
0.8
0.5
0.6
NHANES, 1999-2002
N
248
178
191
186
171
196
184
183
164
194
316
321
324
266
273
256
243
225
656
699
787
593
1,010
554
Mean
13.3
15.2
17.9
20.6
22.4
25.9
31.9
35.4
40.0
47.9
52.0
57.7
59.9
61.1
63.0
61.7
65.2
67.9
71.1
74.1
76.5
76.9
74.9
66.6
SE
0.1
0.2
0.3
0.6
0.5
0.5
1.2
0.7
1.0
1.3
1.1
1.4
1.0
1.7
1.2
1.2
1.5
1.2
0.9
0.9
1.1
1.1
0.6
0.9
= Data not available.
N
SE
Source:
= Number of individuals.
= Standard error.
Ogden et al.
2004.
Q
I
I
§
s
ft
45
I
5 §
•* ss
•— ST-
8s
1=
I
-------
Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys
Sex
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II, 1963-1965
N Mean SE
-
-
575
632
618
603
576
595
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
118.9
124.5
130.0
135.5
140.2
145.5
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
0.2
0.3
0.3
0.4
0.3
0.3
-
-
-
-
-
-
-
-
-
-
-
-
-
-
NHES III, 1966-1970
N Mean SE
-
-
-
-
-
-
-
-
643
626
618
613
556
458
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
152.3 0.4
159.8 0.4
166.7 0.5
171.4 0.3
174.3 0.4
175.6 0.4
-
-
-
-
-
-
-
-
NHANES II, 1976-1980
N Mean SE
350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150
1,261
871
695
691
2,086
-
91.1
98.7
105.5
112.3
119.1
124.5
129.6
135.0
141.3
145.5
152.5
158.3
166.8
171.2
173.4
174.8
177.3
176.1
177.1
176.3
175.9
174.7
172.1
-
0.2
0.3
0.4
0.3
0.5
0.5
0.7
0.6
0.6
0.6
0.7
0.8
0.6
0.7
0.5
0.5
0.6
0.5
0.3
0.3
0.3
0.3
0.2
-
NHANES III, 1988-1994
N Mean SE
589
513
551
497
283
270
269
280
297
285
207
190
191
188
197
196
176
169
1,639
1,468
1,220
851
1,684
895
90.9
98.8
105.2
112.3
118.9
125.9
131.3
137.7
142.0
147.4
155.5
161.6
169.0
172.8
175.0
176.5
177.3
175.5
176.1
176.6
176.3
175.8
173.6
170.7
0.2
0.3
0.4
0.3
0.7
0.6
0.6
0.7
1.1
0.7
1.1
0.8
0.9
1.0
0.9
0.9
1.0
0.6
0.3
0.3
0.3
0.3
0.2
0.3
NHANES, 1999-2002
N Mean SE
254
222
183
156
188
187
217
177
188
187
301
298
267
287
310
317
289
275
724
717
784
601
1,010
505
91.2
98.6
106.5
113.0
119.2
126.2
132.5
138.1
141.4
148.7
154.8
160.1
168.5
173.8
175.3
175.3
176.4
176.7
176.7
176.4
177.2
175.8
174.4
171.3
0.3
0.3
0.4
0.5
0.5
0.6
0.7
0.4
0.6
0.9
0.7
0.8
0.9
0.6
0.6
0.6
0.7
0.6
0.3
0.3
0.3
0.3
0.3
0.4
Q
I
i
I
8s
ft
-------
I
§
s
Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys (continued)
Sex
and Age
(years)
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II. 1963-1965 NHES III. 1966-1970
N
-
.
.
.
536
609
613
581
584
525
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Mean SE N Mean SE
.
.
.
.
117.8 0.3 - -
123.5 0.2 - -
129.4 0.3 - -
135.5 0.3 - -
140.9 0.3 - -
147.3 0.3 - -
547 46.6 0.3
582 50.5 0.3
586 54.2 0.3
503 56.5 0.5
536 58.1 0.3
442 57.6 0.3
.
.
.
.
.
.
.
.
NHANES II. 1976-1980
N
314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158
1,290
964
765
793
2,349
-
Mean
89.4
97.1
104.2
111.2
117.9
123.4
129.5
134.1
141.7
147.4
143.8
158.7
160.7
163.3
162.8
163.5
162.8
163.2
163.3
163.1
162.3
160.5
158.8
-
SE
0.3
0.2
0.4
0.4
0.6
0.7
0.5
0.5
0.6
0.7
0.6
0.5
0.7
0.5
0.5
0.6
0.5
0.4
0.2
0.2
0.3
0.3
0.2
-
NHANES III. 1988-1994
N
564
590
535
557
274
275
247
282
262
275
239
225
224
195
214
201
175
178
1,665
1,776
1,354
998
1,680
1,025
Mean
89.7
98.2
105.1
112.2
117.9
124.3
131.1
136.6
142.7
150.2
155.5
159.9
161.2
162.8
163.0
163.6
163.2
163.4
162.8
163.4
162.8
161.8
159.8
156.2
SE
0.2
0.2
0.3
0.5
0.6
0.7
0.6
0.7
0.6
0.7
0.7
0.9
0.7
0.6
0.7
0.6
0.9
0.7
0.2
0.3
0.3
0.3
0.2
0.4
NHANES. 1999-2002
N
233
187
195
190
172
200
184
189
164
194
318
324
326
271
275
258
249
231
663
708
794
601
1,004
538
Mean
90.1
97.6
105.9
112.4
117.1
124.4
130.9
136.9
143.3
151.4
156.0
159.1
161.8
162.0
161.9
163.2
163.0
163.1
162.8
163.0
163.4
162.3
160.0
157.4
SE
0.4
0.5
0.5
0.7
0.7
0.5
0.6
0.7
0.9
0.7
0.7
0.6
0.6
0.6
0.5
0.6
0.5
0.7
0.3
0.3
0.2
0.3
0.2
0.3
= Data not available.
N
SE
Source:
= Number of individuals.
= Standard error.
Ogden et al
, 2004.
Q
I
I
§
s
ft
45
I
5 §
•* ss
•— ST-
8s
1=
I
-------
Table 8-16. Mean Body
Sex
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II, 1963-1965 NHES III, 1966-1970
N Mean
-
-
575 15.6
632 15.9
618 16.3
603 16.9
576 17.1
595 17.9
-
-
-
-
-
-
-
-
-
-
-
-
-
-
SE N
-
-
0.1
0.1
0.1
0.2
0.1
0.1
643
626
618
613
556
458
-
-
-
-
-
-
-
-
Mean
-
-
-
-
-
-
-
-
18.4
19.4
20.2
20.9
21.3
22.1
-
-
-
-
-
-
-
-
SE
-
-
-
-
-
-
-
-
0.1
0.1
0.2
0.1
0.1
0.1
-
-
-
-
-
-
-
-
Mass Index (kg/m2) by Age and Sex Across Multiple
NHANES I, 1971-1974
N
298
308
304
273
179
164
152
169
184
178
200
174
174
171
169
176
124
136
986
654
715
717
1,920
-
Mean
16.3
16.0
15.7
15.6
15.7
15.8
15.8
17.1
17.3
18.0
18.7
19.6
20.2
20.5
21.8
21.9
23.7
23.3
24.5
26.1
26.2
26.0
25.4
-
SE
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.2
0.3
0.2
0.3
0.3
0.3
0.3
0.3
0.3
0.5
0.1
0.2
0.2
0.2
0.1
-
NHANES II, 1976-1980
N
350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150
1,261
871
695
691
2,086
-
Mean
16.2
15.9
15.8
15.6
16.0
16.0
16.5
16.8
18.0
18.6
18.8
19.5
20.2
20.8
22.0
21.8
22.6
23.1
24.3
25.6
26.4
26.2
25.7
-
SE
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.3
0.3
0.3
0.4
0.2
0.3
0.3
0.2
0.4
0.3
0.1
0.1
0.2
0.2
0.1
-
Surveys
NHANES III,
1988-1994
N
588
512
547
495
282
269
266
279
297
280
203
187
188
187
194
196
176
168
1,638
1,468
1,220
851
1,683
895
Mean
16.5
16.1
15.9
15.9
16.3
16.5
17.3
18.0
18.4
19.4
20.1
20.5
22.3
22.3
22.3
23.4
22.6
23.7
25.2
26.5
27.3
27.8
27.2
25.9
SE
0.1
0.2
0.1
0.1
0.3
0.2
0.4
0.7
0.3
0.3
0.3
0.3
1.1
0.5
0.5
0.4
0.5
0.6
0.2
0.2
0.2
0.2
0.2
0.2
NHANES, 1999-2002
N
225
209
178
147
182
185
214
174
187
182
299
298
266
283
306
313
284
269
712
704
774
594
991
487
Mean
16.6
16.2
16.3
16.5
16.4
17.0
18.4
18.7
19.1
19.6
20.7
20.7
22.3
22.5
24.1
24.5
24.2
24.9
26.6
27.5
28.4
28.7
28.6
26.8
SE
0.1
0.1
0.2
0.3
0.2
0.2
0.4
0.3
0.3
0.4
0.4
0.5
0.4
0.3
0.4
0.4
0.3
0.4
0.2
0.3
0.3
0.3
0.2
0.2
Q
I
i
I
8s
X)
-------
oo
QTQ
I
§
s
Table 8-16. Mean Body Mass Index (kg/m2) by Age
Sex
and Age
(years)
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 74
75+
NHES II, 1963-1965 NHES III, 1966-1970 NHANES I, 1971-1974
N
-
-
-
-
536
609
613
581
584
525
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Mean SE N Mean SE N
272
292
281
314
115.4 0.1 - - - 176
15.8 0.1 - - - 169
16.4 0.1 - - - 152
17.0 0.1 - - - 171
17.6 0.2 - - - 197
18.2 0.2 - - - 166
547 19.2 0.1 177
582 19.9 0.1 198
586 20.8 0.1 184
503 21.4 0.2 167
536 21.9 0.2 171
442 21.7 0.2 150
141
130
2,122
1,654
1,232
780
2,131
-
Mean
15.9
15.7
15.5
15.5
15.4
15.6
16.4
17.2
17.1
18.6
19.5
20.4
21.1
21.1
21.7
22.6
21.5
22.5
23.0
24.7
25.7
26.2
26.5
-
SE
0.1
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.3
0.4
0.3
0.3
0.3
0.3
0.5
0.3
0.6
0.1
0.2
0.2
0.2
0.2
-
and Sex
Across
Multiple Surveys (continued)
NHANES II, 1976-1980
N
314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158
1,290
964
765
793
2,349
-
Mean
16.1
15.6
15.5
15.6
15.6
16.1
16.3
17.5
17.7
18.9
19.3
20.1
21.0
20.6
21.8
22.3
22.3
22.4
23.1
24.9
25.7
26.5
26.5
-
SE
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.3
0.3
0.3
0.4
0.3
0.3
0.3
0.4
0.4
0.3
0.2
0.2
0.2
0.2
0.1
-
NHANES III,
1988-1994
N
562
582
533
554
272
274
247
280
258
275
236
220
218
191
208
201
175
177
1,663
1,773
1,354
996
1,673
1,021
Mean
16.5
15.9
16.0
15.9
16.1
16.9
17.3
18.2
18.4
19.4
20.2
21.8
22.4
21.9
23.0
23.3
22.9
23.7
24.3
26.3
27.1
28.4
27.4
25.9
SE
0.1
0.1
0.2
0.1
0.3
0.3
0.3
0.5
0.4
0.4
0.5
0.6
0.5
0.4
0.5
0.5
0.6
0.8
0.2
0.3
0.3
0.3
0.2
0.2
NHANES, 1999-2002
N
214
173
190
186
170
196
184
183
163
194
315
321
324
266
273
255
243
225
654
698
783
591
993
524
Mean
16.4
16.0
15.9
16.1
16.2
16.6
18.3
18.7
19.3
20.7
21.2
22.6
22.9
23.2
24.0
23.1
24.4
25.5
26.8
27.9
28.6
29.2
29.2
26.8
SE
0.1
0.1
0.2
0.3
0.2
0.2
0.5
0.3
0.3
0.4
0.4
0.4
0.4
0.5
0.4
0.4
0.5
0.4
0.3
0.3
0.4
0.4
0.2
0.4
= Data not available.
N
SE
Source:
= Number of individuals.
= Standard error.
Ogden et al
, 2004.
Q
I
I
§
s
ft
45
I
5 §
•* ss
•— ST-
8s
1=
I
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-17. Sample Sizes by Age, Sex, Race, and Examination
NHANES Examination
Age Group
(years)
Sex
Racea
11(1976-1980) 111(1988-1994)
1999-2002
Overall
(2 to 17)
2 to 5
6 to 11
12 to 17
20 to 39
40 to 59
60 and over0
Boys White
Black
Mexican American
Girls White
Black
Mexican American
Boys White
Black
Mexican American
Girls White
Black
Mexican American
Boys White
Black
Mexican American
Girls White
Black
Mexican American
Male White
Black
Mexican American
Female White
Black
Mexican American
Male White
Black
Mexican American
Female White
Black
Mexican American
Male White
Black
Mexican American
Female White
Black
Mexican American
6,395 (10.6)b
1,082(4.1)
273(4.1)
105 (4.2)
1,028 (4.0)
234 (4.0)
102 (4.2)
667 (9.0)
137(9.0)
60 (9.2)
631(9.1)
155(9.0)
40(9.3)
786(15.1)
155(15.1)
49(15.0)
695(15.1)
159(15.0)
37(15.2)
9,610(9.9)
605 (4.0)
693 (3.9)
732 (4.0)
639 (4.0)
684 (3.9)
800(3.9)
446 (8.9)
584 (9.0)
565 (9.0)
428(9.1)
538(9.0)
581 (8.9)
282 (14.9)
412(15.0)
406(15.0)
344(15.0)
450 (14.9)
421 (14.8)
6,710(10.1)
226 (3.9)
234 (4.0)
231 (3.9)
235 (4.1)
222 (4.0)
238(4.1
298(8.9)
371 (9.0)
384 (9.0)
293 (8.9)
363(9.1)
361 (9.0)
449(14.9)
543(14.9)
648(15.0)
456(14.9)
528(14.8)
631 (14.9)
607
279
399
569
298
358
676
289
310
632
297
332
866
256
318
862
275
329
a Race was recorded in the 1st two examinations (using data concerning ancestry/national origin) to create comparable
categories in all surveys.
b Mean ages are shown in parentheses. There are no mean ages available for the older age group data (ages 20 and
above).
0 Data from Ogden et al., 2004.
No data available.
Sources: Freeman et al., 2006; Ogden et al., 2004.
Exposure Factors Handbook
September 2011
Page
8-29
-------
Table 8-18. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex (Ages 2 to 17)
Examination Yeara
Overall
Sex
Boys
Girls
Age (years)
2 to 5
a
b
6 to 11
12 to 17
Race
White
Black
Mexican American
White
Black
Mexican American
White
Black
Mexican American
White
Black
Mexican American
White
Black
Mexican American
White
Black
Mexican American
1971-1974
18.0b
17.8
18.6
17.9
17.7
18.6
18.0
17.9
18.5
15.8
15.8
16.5
16.7
16.5
16.9
20.7
20.4
21.6
1976-1980
18.0
18.2
18.8
18.0
17.8
18.9
18.0
18.6
18.6
15.7
15.7
16.2
16.9
17.1
17.7
20.6
20.9
21.5
1988-1994
18.8
19.1
19.5
18.8
18.8
19.4
18.7
19.5
19.6
16.0
15.9
16.5
17.6
17.9
18.5
21.8
22.4
22.6
Secular trends for BMI, BMI-for-age, weight-for-age, and height- for-age were each
age, and weight also differed (p < 0.001) by race.
Mean BMI levels have been adjusted for differences in age and sex across exams.
1999-2002
19.0
20.0
20.1
19.0
19.6
20.3
19.0
20.4
19.9
16.2
16.2
16.5
17.9
18.7
18.8
22.0
23.7
24.0
Increase in Mean z-score
from 1971-1974 to 1999-2002
BMI
+0.33
+0.61
+0.32
+0.37
+0.53
+0.38
+0.30
+0.71
+0.25
+0.21
+0.34
-0.02
+0.42
+0.67
+0.50
+0.32
+0.72
+0.37
statistically significant at the 0.001
Weight
+0.36
+0.63
+0.52
+0.42
+0.58
+0.67
+0.32
+0.69
+0.35
+0.22
+0.32
+0.29
+0.47
+0.69
+0.65
+0.35
+9,77
+0.55
level. Trends
Height
+0.20
+0.31
+0.39
+0.25
+0.32
+0.57
+0.16
+0.30
+0.21
+0.13
+0.18
+0.43
+0.30
+0.36
+0.41
+0.15
+0.33
+0.34
in BMI, BMI-for-
Source: Freedmanetal.,2006.
I
§
Q
I
90
45
5 §
•* ss
>— ST-
I
1=
-------
g
S
*s
ft
Si
I
I
I
Table 8-19. Mean
Sex, Race/Ethnicity, and Age
(years)
Male
Non-Hispanic White:8
20 and over
20 to 39
40 to 59
60 and over
Non-Hispanic Black:
20 and over3
20 to 39 yra
40 to 59
60 and overa
Mexican American: a
20 and over
20 to 74
20 to 39
40 to 59
60 to 74
60 and over
Female
Non-Hispanic white :a
20 and over
20 to 39
40 to 59
60 and over
Non-Hispanic Black: a
20 and over
20 to 39
40 to 59
60 and over
Mexican American:
20 and over
20 to 74a
20 to 39a
40-to 59a
60 to 74a
60 and over
a Statistically significant
Data not available.
Sample
Size
-
-
-
-
-
-
-
-
-
2,273
1,133
856
284
-
-
-
_
_
-
-
_
-
-
3,039
1,482
1,159
398
-
Body Mass Index (kg/m ) by Survey, Sex, Race/Ethnicity,
HHANES, 1982-1984
Standard Error
Mean of the Mean
-
-
-
-
-
-
-
-
-
26.2 0.2
25.6 0.3
26.9 0.1
26.3 0.2
-
-
-
_
_
-
-
_
-
-
27.1 0.1
25.6 0.2
28.2 0.2
28.1 0.3
-
NHANES III,
Sample
Size
3,152
846
842
1,464
2,091
985
583
523
2,229
2,127
1,143
558
426
528
3,554
1,030
950
1,574
2,451
1,191
721
539
2,106
2,013
1,063
557
393
486
Mean
26.8
25.9
27.6
27.0
26.6
26.3
27.1
26.4
27.3
27.3
26.1
28.6
27.4
27.1
26.1
24.7
27.2
26.7
29.1
27.6
30.4
29.4
28.4
28.5
27.2
29.7
29.2
28.7
and Age Group; Adults: United States
1988-1994
Standard Error
of the Mean
0.1
0.2
0.2
0.1
0.1
0.2
0.2
0.3
0.1
0.1
0.2
0.2
0.3
0.3
0.2
0.2
0.3
0.2
0.2
0.3
0.3
0.4
0.2
0.2
0.2
0.3
0.4
0.4
NHANES, 1999-2002
Sample
Size
2,116
607
673
836
820
279
289
252
1,018
959
399
309
251
310
2,026
567
629
830
863
298
294
271
1,012
960
358
332
270
322
Mean
27.9
27.1
28.7
28.3
27.5
27.1
27.7
28.0
28.0
28.1
27.1
28.9
28.6
28.1
27.6
26.7
28.3
28.2
31.1
30.2
32.1
31.1
29.0
29.1
27.8
30.4
29.5
28.9
Standard Error
of the Mean
0.2
0.2
0.3
0.1
0.2
0.3
0.4
0.3
0.2
0.2
0.3
0.3
0.3
0.3
0.2
0.3
0.4
0.2
0.3
0.5
0.5
0.6
0.3
0.3
0.4
0.5
0.3
0.4
trend or difference/) < 0.05 for all years available.
Notes: BMI is calculated as weight in kilo
Source: Ogden et al, 2004.
grams divided by square of height in meters. HHANES: Hispanic Health and Nutrition Examination Survey.
Q
I
i
8s
-------
:*«
Table 8-20. Prevalence of Overweight and Obesity" Among Children
Examination Year
1971-1974 1976-1980 1988-1994
Overall
Sex
Age (yr)
a
b
Source:
White
Black
Mexican American
Boys White
Black
„ Mexican American
K fIPP
K&ils White
Black
Mexican American
2 to 5 White
Black
Mexican American
6 to 11 White
Black
Mexican American
12 to 17 White
Black
Mexican American
5%(l)b
6%(1)
8%(1)
5%(1)
6% (2)
8%(1)
5%(1)
6%(1)
8% (2)
4%(1)
7% (3)
10% (5)
4% (0)
4% (0)
6% (0)
6%(1)
8%(1)
9% (0)
Overweight is defined as a BMI >95ft percentile or >30 kg/m
Values are percentage of overweig
Freedman et al., 2006.
5%(1)
7% (2)
10% (1)
5%(1)
5%(1)
12% (1)
5%(1)
9% (2)
7% (0)
3%(1)
4% (0)
11% (3)
6%(1)
9% (3)
11% (0)
4% (0)
8%(1)
8%(1)
9% (2)
12% (3)
14% (4)
10% (2)
11% (3)
15% (4)
9% (2)
14% (3)
14% (3)
5%(1)
8% (3)
12% (5)
11% (3)
15% (3)
17% (4)
11% (2)
13% (3)
14% (2)
2; obesity is defined as a BMI
Increase in Prevalence from
1971-1974 to 1999-2002
1999-2002 Overweight
12% (3)
18% (5)
21% (5)
13% (4)
16% (5)
24% (4)
12% (2)
21% (6)
17% (4)
9% (3)
9% (4)
13% (5)
13% (4)
20% (5)
22% (5)
13% (2)
22% (6)
25% (5)
>99fh percentile or >40
+8
+12
+12
+8
+10
+16
+7
+14
+9
+5
+2
+3
+10
+15
+16
+7
+14
+15
kg/m2.
Obesity
+2
+4
+4
+3
+3
+6
+1
+5
+2
+2
+1
0
+3
+4
+5
+1
+5
+5
ht children (percentage of obese children).
Q
I
§
I
90
05
5 S
•* ss
>— ST-
I
1=
a
I-
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-21. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low
Birth Weights, by Race, and Hispanic Origin of Mother: United States, 2005
Total Births
Weight (g)
<500
500-999
1,000-1,499
1,500-1,999
2,000-2,499
2,500-2,999
3,000-3,499
3,500-3,999
4,000-4,499
4,500-4,999
>5,000
Not stated
All Races3
4,138,349
Non-Hispanic
Whiteb
2,279,768
Non-Hispanic
Blackb
583,759
Hispanic0
985,505
Number of Live Births
6,599
23,864
31,325
66,453
210,324
748,042
1,596,944
1,114,887
289,098
42,119
4,715
3,979
2,497
10,015
14,967
33,687
104,935
364,726
857,136
672,270
167,269
27,541
2,840
1,885
2,477
8,014
8,573
15,764
46,846
144,803
221,819
108,698
22,149
3,203
405
1,008
1,212
4,586
5,988
12,710
43,300
176,438
399,295
266,338
64,704
9,167
1,174
593
% of Total
Low Birth Weightd
8.2
Very Low Birth Weight6 1 . 5
7.3
1.2
14.0
3.3
6.9
1.2
a All Races includes White, Black, and races other than White and Black and origin not stated.
b Race categories are consistent with the 1 977 Office of Management and Budget standards.
0 Hispanic includes all persons of Hispanic origin of any race.
d Low birth weight is birth weight less than 2,500 g (5 Ib 8 oz).
e Very low birth weight is birth weight less than 1 ,500 g (3 Ib 4 oz).
Source: Martin ei
al, 2007.
Exposure Factors Handbook
September 2011
Page
8-33
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-22. Estimated Mean Body
Age Group3
(years)
Otol
Ito2
2 to 3
3 to 4
4 to 5
5 to 6
6 to 7
7 to 8
8 to 9
9 to 10
10 to 11
11 to 12
12 to 13
13 to 14
14 to 15
15 to 16
16 to 17
17 to 18
18 to 19
19 to 20
20 to 21
21 to 22
22 to 23
23 to 24
24 to 25
25 to 26
26 to 27
27 to 28
28 to 29
29 to 30
30 to 31
31 to 32
32 to 33
33 to 34
34 to 35
35 to 36
36 to 37
37 to 38
38 to 39
39 to 40
40 to 41
41 to 42
42 to 43
43 to 44
44 to 45
45 to 46
46 to 47
47 to 48
48 to 49
49 to 50
50 to 51
51 to 52
52 to 53
53 to 54
Mean
9.4
11.8
13.6
15.6
17.8
19.8
23.0
25.1
28.2
31.1
36.4
40.2
44.2
49.8
57.1
61.0
67.1
66.7
71.0
71.7
71.6
74.76
76.10
75.93
75.18
76.34
79.49
76.17
79.80
77.64
78.63
78.19
79.15
80.73
81.24
79.04
80.41
79.06
83.01
79.85
84.20
81.20
79.67
81.50
82.76
80.91
82.83
82.29
81.52
80.60
81.14
81.25
82.38
79.37
Male (kg)
SD
1.3
1.6
1.8
1.9
2.4
2.8
3.7
3.8
5.6
5.8
7.2
9.8
9.8
11.4
10.7
10.4
11.7
11.3
12.0
11.3
12.0
12.73
12.88
11.76
11.65
11.52
14.18
12.34
14.15
11.63
13.63
14.19
12.99
12.67
14.83
12.81
14.10
12.41
15.40
13.02
13.22
15.07
11.86
14.04
13.41
13.77
15.28
11.83
12.63
13.31
14.23
11.27
15.03
12.94
Weights of Male and Female by Single- Year Age Groups Using NHANES
II Data
Female (kg)
N
179
370
375
418
404
397
133
148
147
145
157
155
145
173
186
184
178
173
164
148
114
150
135
148
129
118
127
112
104
124
103
108
102
86
83
91
79
83
65
71
76
73
74
68
65
62
68
55
77
77
79
69
73
69
Mean
8.8
10.8
13.0
14.9
17.0
19.6
22.1
24.7
27.8
31.8
36.1
41.8
46.4
50.9
54.7
55.1
58.1
59.6
59.0
60.1
60.5
60.39
60.51
61.21
62.71
62.64
61.74
62.83
63.79
63.33
64.90
67.71
68.94
63.43
63.03
67.30
65.41
66.81
66.56
67.21
70.56
65.25
65.81
68.45
66.96
65.18
70.45
68.02
67.39
66.83
70.81
67.20
66.07
68.83
SD
1.3
1.4
1.5
2.1
2.3
3.2
3.9
4.6
4.8
7.3
7.7
10.1
10.1
11.2
10.7
9.0
9.6
10.4
10.2
10.1
10.7
11.14
10.11
11.48
13.44
12.46
11.77
12.18
14.34
12.92
13.71
14.45
17.51
11.77
14.43
15.62
11.27
13.08
15.72
13.85
17.70
12.91
12.14
14.89
15.19
14.78
15.91
13.67
15.71
14.54
14.67
11.99
14.58
14.83
N
111
336
336
366
396
364
135
157
123
149
136
140
147
162
178
145
170
134
170
158
162
170
150
133
123
120
118
130
138
122
139
116
104
92
91
113
84
97
71
79
77
70
98
84
71
65
82
73
67
79
98
67
88
73
Overall (kg)
Mean
9.1
11.3
13.3
15.2
17.4
19.7
22.5
24.8
28.1
31.4
36.2
41.0
45.4
50.4
55.9
58.0
62.4
63.3
64.6
65.3
65.2
66.71
67.30
68.43
68.43
68.80
70.57
68.24
69.79
69.97
70.44
72.33
73.43
71.82
70.91
72.24
72.03
71.82
74.14
73.19
76.49
73.47
71.23
73.38
73.70
72.33
75.24
73.42
74.28
73.07
75.12
73.81
72.70
73.71
SD
1.2
1.5
1.6
1.8
2.4
2.8
3.6
3.8
5.6
5.9
7.1
9.9
10.0
11.5
10.5
9.9
10.9
10.7
10.9
10.3
10.9
11.35
11.39
10.60
10.60
10.38
12.59
11.06
12.38
10.48
12.21
13.13
12.05
11.27
12.94
11.71
12.63
11.27
13.76
11.94
12.01
13.63
10.60
12.64
11.94
12.31
13.89
10.55
11.51
12.06
13.17
10.23
13.27
12.02
N
356
706
711
784
800
761
268
305
270
294
293
295
292
335
364
329
348
307
334
306
276
320
285
281
252
238
245
242
242
246
242
224
206
178
174
204
163
180
136
150
153
143
172
152
136
127
150
128
144
156
177
136
161
142
Page
8-34
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-22. Estimated Mean Body
Weights of Male and Female by Single- Year Age Groups Using NHANES
II Data (continued)
Age Group3 Male (k§)
(years) Mean
54 to 55
55 to 56
56 to 57
57 to 58
58 to 59
59 to 60
60 to 61
61 to 62
62 to 63
63 to 64
64 to 65
65 to 66
66 to 67
67 to 68
68 to 69
69 to 70
70 to 71
71 to 72
72 to 73
73 to 74
74+
a
SD
N
Source:
76.63
81.92
77.36
79.85
79.23
80.00
79.76
78.42
77.06
77.07
77.27
77.36
75.35
73.98
74.14
74.40
75.17
74.45
73.47
72.80
75.89
Data were converted
= Standard deviation
SD
13.36
15.12
11.28
13.02
12.52
12.47
12.92
11.75
12.33
11.31
13.63
13.25
13.21
12.82
14.60
13.20
13.03
12.60
12.36
12.17
13.38
N
61
62
69
64
73
72
183
169
188
162
185
158
138
143
124
129
128
115
100
82
82
from ages in months to
Female (kg)
Mean
67.62
71.93
70.82
66.87
68.73
64.43
67.28
68.12
66.09
66.41
67.45
68.48
67.36
65.98
68.87
65.59
65.04
65.62
64.89
65.59
67.20
ages in years.
SD
14
16
15
64
17
40
14.41
13
12
12
13
13
14
13
14
13
13
13
13
12
13
11
12
14
60
88
83
83
69
03
77
68
95
47
63
39
47
53
58
71
48
For instance,
N
71
90
67
99
70
70
218
176
184
178
177
185
182
149
161
119
136
139
135
108
102
age 1-2
Mean
71
75
73
71
73
71
72
72
71
70
72
71
52
32
59
60
28
45
75
68
00
72
26
84
70.40
69
71
69
69
69
68
68
70
19
02
37
32
00
17
36
55
yr represents a
Overall (kg
SD
12.47
13.90
10.73
11.68
11.58
11.14
11.79
10.89
11.36
10.38
12.74
12.30
12.34
11.99
13.98
12.30
12.01
11.67
11.46
11.43
12.44
ges from 12
N
132
152
136
163
143
142
401
345
372
340
362
343
320
292
285
248
264
254
235
190
184
to 23 mo.
= Number of individuals.
Portieretal.,2007.
Exposure Factors Handbook
September 2011
Page
8-35
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-23. Estimated Mean Body Weights of Male and Female by
III Data
Age Groupa
(years)
Otol
1 to 2
2 to 3
3 to 4
4 to 5
5 to 6
6 to 7
7 to 8
8 to 9
9 to 10
10 to 11
11 to 12
12 to 13
13 to 14
14 to 15
15 to 16
16 to 17
17 to 18
18 to 19
19 to 20
20 to 21
21 to 22
22 to 23
23 to 24
24 to 25
25 to 26
26 to 27
27 to 28
28 to 29
29 to 30
30 to 31
31 to 32
32 to 33
33 to 34
34 to 35
35 to 36
36 to 37
37 to 38
38 to 39
39 to 40
40 to 41
41 to 42
42 to 43
43 to 44
44 to 45
45 to 46
46 to 47
47 to 48
48 to 49
49 to 50
50 to 51
51 to 52
52 to 53
53 to 54
Mean
8.5
11.6
13.6
15.8
17.6
20.1
23.2
26.3
30.1
34.4
37.3
42.5
49.1
54.0
63.7
66.8
68.6
72.7
71.2
73.0
72.5
72.92
76.34
77.85
78.56
80.33
75.88
81.17
81.10
81.93
83.56
79.48
81.65
84.03
82.95
81.24
87.67
83.33
82.53
82.62
85.84
86.19
85.12
86.37
90.62
83.58
80.70
85.54
82.29
82.25
81.69
85.78
87.02
89.44
Male (kg)
SD
1.5
1.5
1.5
2.3
2.4
3.0
5.0
5.0
6.9
7.9
8.6
10.5
11.1
12.9
17.1
14.9
14.9
13.3
14.3
12.8
13.4
12.86
14.72
14.37
15.38
17.89
12.84
14.90
18.23
16.89
16.71
13.12
15.82
16.63
15.56
16.16
21.26
17.61
14.47
12.46
15.23
18.93
16.76
17.71
20.37
13.46
13.00
17.28
14.93
16.11
13.24
15.39
13.66
14.86
Single- Year Age Groups Using NHANES
Female (kg)
N
902
660
644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168
149
161
160
172
187
171
143
176
154
156
163
155
159
153
162
143
163
123
136
122
152
148
161
139
120
108
102
116
93
85
77
84
93
86
Mean
7.8
10.9
13.2
15.4
17.9
20.2
22.6
26.3
29.8
34.3
37.9
44.2
49.1
55.7
58.3
58.3
61.5
62.4
61.5
63.6
61.7
65.01
64.07
66.99
62.79
66.19
64.89
65.10
66.97
65.89
67.76
72.48
67.53
68.49
67.55
71.45
66.02
72.04
71.58
74.57
68.70
70.11
72.72
68.94
72.61
71.78
72.07
72.09
75.80
73.41
74.05
79.48
72.00
73.92
SD
1.6
1.4
1.8
2.2
3.2
3.5
4.7
6.2
6.7
9.0
9.5
10.5
11.6
13.2
11.8
10.1
12.8
11.9
14.2
14.5
12.9
16.03
13.61
16.24
12.62
16.05
15.19
14.43
15.26
13.65
16.85
19.32
17.22
16.03
14.27
17.47
14.29
17.69
17.43
19.41
15.80
13.80
19.46
15.35
17.15
15.76
15.53
15.98
16.09
18.26
18.03
19.60
16.86
17.08
N
910
647
624
587
537
554
272
274
248
280
258
275
236
220
220
197
215
217
193
193
180
188
193
205
200
157
184
184
190
177
202
204
179
176
186
188
180
202
183
157
198
183
171
123
152
125
113
102
95
106
118
85
100
97
Overall (kg)
Mean
8.17
11.2
13.4
15.6
17.8
20.2
22.9
26.4
30.0
34.4
37.7
43.4
49.1
54.8
60.6
61.7
65.2
67.6
66.4
68.3
66.1
69.24
69.48
72.72
70.16
74.11
69.73
73.33
73.28
73.33
75.11
77.04
74.33
75.09
76.47
76.02
77.32
76.42
76.85
79.34
75.55
78.34
79.25
77.80
79.13
78.22
76.30
79.28
79.21
77.95
77.31
83.81
79.97
81.86
SD
1.7
1.5
1.8
2.2
3.2
3.5
4.8
6.2
6.7
9.0
9.4
10.3
11.7
13.0
12.2
10.7
13.6
12.9
15.3
15.6
13.8
17.08
14.75
17.63
14.10
17.97
16.33
16.25
16.70
15.19
18.68
20.54
18.95
17.58
16.16
18.59
16.74
18.77
18.71
20.65
17.37
15.42
21.21
17.33
18.69
17.18
16.44
17.57
16.82
19.39
18.82
20.67
18.72
18.91
N
1,812
1,307
1,268
1,103
1,086
1,051
555
543
514
561
555
556
439
407
408
384
409
413
369
361
329
349
353
377
387
328
327
360
344
333
365
359
338
329
348
331
343
325
319
279
350
331
332
262
272
233
215
218
188
191
195
169
193
183
Page
8-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-23. Estimated Mean Body Weights of Male and Female by Single- Year Age Groups Using NHANES
III Data (continued)
Age Groupa Male (k§)
(years) Mean
54 to 55
55 to 56
56 to 57
57 to 58
58 to 59
59 to 60
60 to 61
61 to 62
62 to 63
63 to 64
64 to 65
65 to 66
66 to 67
67 to 68
68 to 69
69 to 70
70 to 71
71 to 72
72 to 73
73 to 74
74 to 75
75 to 76
76 to 77
77 to 78
78 to 79
79 to 80
80 to 81
81 to 82
82 to 83
83 to 84
84 to 85
85+
a
SD
N
Source:
86.02
83.10
87.16
86.31
83.54
87.93
83.54
81.91
81.98
84.15
84.28
85.10
81.43
84.35
80.60
84.81
80.18
79.34
78.97
82.07
79.32
77.18
79.30
80.70
75.21
78.75
76.94
73.70
73.25
72.10
72.09
70.08
Data were converted
= Standard deviation
SD
16.76
14.99
15.10
15.04
15.67
16.14
14.22
15.03
15.47
14.50
15.73
14.75
15.03
15.22
11.75
18.18
14.14
14.64
13.36
17.26
15.37
10.47
14.88
13.98
11.34
11.32
15.15
13.30
12.32
15.31
10.73
11.64
from a
N
86
82
96
89
81
74
130
119
116
118
116
127
102
117
98
113
92
126
119
109
84
75
64
64
50
45
108
96
81
63
62
189
ges in months to
Female (kg)
Mean
74.63
72.56
77.69
75.65
72.26
74.00
68.73
72.26
72.97
71.32
74.34
67.47
71.82
68.98
70.72
66.57
68.36
70.74
66.70
68.24
69.08
68.58
65.68
67.33
63.67
60.21
63.55
63.17
61.96
62.78
63.68
59.67
ages in years.
SD
19.97
14.06
16.74
17.87
16.47
15.33
13.60
15.42
17.54
14.48
17.40
16.08
14.58
15.22
16.56
11.74
15.72
17.89
13.89
14.14
13.67
13.50
13.88
14.16
14.31
14.41
13.10
12.70
12.01
12.23
11.43
11.69
For instance,
N
113
102
105
97
100
82
104
141
114
111
126
118
118
95
110
97
124
98
101
115
97
85
94
86
63
61
101
112
69
63
57
240
age 1-2
Overall (kg)
Mean
79.88
76.59
83.15
82.12
76.89
80.48
75.88
76.50
77.18
76.88
78.86
76.14
76.49
76.08
76.07
74.84
72.95
75.64
72.76
74.37
73.57
72.89
70.38
72.43
67.94
67.28
68.77
66.94
67.05
65.80
66.74
63.11
yr represents ages
SD
21.38
14.84
17.91
19.40
17.52
16.67
15.02
16.32
18.55
15.61
18.46
18.14
15.53
16.78
17.81
13.20
16.78
19.13
15.15
15.41
14.56
14.35
14.87
15.23
15.27
16.10
14.18
13.45
12.99
12.82
11.97
12.36
from 12
N
199
184
201
186
181
156
234
260
230
229
242
245
220
212
208
210
216
224
220
224
181
160
158
150
113
106
209
208
150
126
119
429
to 23 mo.
= Number of individuals.
Portieretal.,2007.
Exposure Factors Handbook
September 2011
Page
8-37
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-24. Estimated Mean Body Weights of Male and Female
NHANES IV Data
Age Groupa
(years)
Otol
Ito2
2 to 3
3 to 4
4 to 5
5 to 6
6 to 7
7to8
8 to 9
9 to 10
10 to 11
1 1 to 12
12 to 13
13 to 14
14 to 15
15 to 16
16 to 17
17 to 18
18 to 19
19 to 20
20 to 21
21 to 22
22 to 23
23 to 24
24 to 25
25 to 26
26 to 27
27 to 28
28 to 29
29 to 30
30 to 31
31 to 32
32 to 33
33 to 34
34 to 35
35 to 36
36 to 37
37 to 38
38 to 39
39 to 40
40 to 41
41 to 42
42 to 43
43 to 44
44 to 45
45 to 46
46 to 47
47 to 48
48 to 49
49 to 50
50 to 51
51 to 52
52 to 53
53 to 54
Mean
9.3
11.3
13.7
16.4
18.8
20.2
22.9
28.1
31.9
36.1
39.5
42.0
49.4
54.9
65.1
68.2
72.5
75.4
74.8
80.1
80.0
73.84
89.62
83.39
80.26
87.47
72.11
85.78
88.04
84.02
80.10
84.65
90.99
90.90
79.09
91.15
88.96
84.62
80.52
84.77
92.21
83.11
91.94
89.48
87.00
84.61
93.27
80.87
85.58
88.84
90.09
90.63
90.62
92.42
Male (kg)
SD
1.8
1.4
2.0
2.3
2.6
3.3
4.3
5.6
8.6
7.5
9.0
10.2
12.7
16.2
19.9
15.7
18.6
17.9
15.9
17.2
15.5
12.87
23.98
18.31
19.38
14.89
14.64
22.69
26.64
15.16
22.28
18.59
15.77
18.74
19.50
25.45
17.15
17.62
17.26
14.26
26.63
14.06
15.56
16.15
14.63
17.53
20.48
11.38
17.91
24.90
14.51
18.22
19.52
21.93
by Single- Year Age Groups Using
Female (kg)
N
116
144
130
105
95
65
94
100
100
76
92
84
158
161
137
142
153
146
131
129
37
33
37
36
20
27
33
30
36
35
29
33
35
37
33
33
29
47
29
37
40
37
46
40
34
33
28
29
21
28
26
35
24
28
Mean
9.3
11.5
13.3
15.2
18.1
20.7
22.0
26.0
30.8
36.0
39.4
47.2
51.6
59.8
59.9
63.4
63.4
59.9
65.0
68.7
66.3
65.89
67.27
73.58
71.81
71.64
78.09
72.48
76.18
71.88
74.00
79.12
77.53
76.60
73.26
79.91
72.10
70.75
80.86
78.08
73.87
75.91
82.03
71.59
74.86
81.15
74.94
68.24
82.10
75.55
83.22
76.89
80.89
76.12
SD
1.5
1.9
1.9
2.1
3.2
4.9
4.5
6.2
7.2
8.4
10.2
12.2
12.3
15.3
13.3
13.9
16.0
11.9
15.2
17.4
15.5
15.49
15.47
23.21
21.27
20.31
20.98
18.10
16.18
16.60
22.71
22.51
18.15
22.28
16.92
22.74
20.29
15.39
22.32
19.34
18.14
17.38
21.78
17.81
18.15
23.52
16.84
16.97
29.55
21.74
27.42
16.09
19.78
16.64
N
101
98
113
77
87
92
74
82
89
84
84
97
160
156
158
126
142
128
139
132
44
47
49
53
54
44
47
49
34
50
48
49
55
29
49
37
38
35
40
43
47
37
41
27
42
50
34
38
34
24
27
36
42
32
Overall (kg)
Mean
9.3
11.4
13.5
15.9
18.5
20.6
22.5
27.4
31.3
36.2
39.5
44.6
50.3
56.9
61.5
65.9
68.0
66.6
70.2
74.6
74.3
69.40
75.85
80.27
75.04
80.45
75.63
78.75
81.29
78.10
77.01
82.51
83.82
85.94
75.72
84.60
80.17
79.21
81.18
81.92
82.13
79.56
88.15
83.18
80.04
83.21
82.90
74.29
84.51
82.17
88.10
83.63
85.03
82.96
SD
1.5
1.8
2.0
2.2
3.3
4.9
4.6
6.5
7.3
8.5
10.2
11.6
11.9
14.6
13.7
14.4
17.1
13.2
16.4
19.0
17.4
16.32
17.44
25.32
22.23
22.80
20.32
19.67
17.26
18.04
23.63
23.48
19.62
25.00
17.49
24.07
22.55
17.23
22.41
20.29
20.17
18.21
23.41
20.69
19.41
24.12
18.63
18.48
30.42
23.64
29.03
17.50
20.79
18.13
N
217
242
243
182
182
157
168
182
189
160
176
181
318
317
295
268
295
274
270
261
81
80
86
89
74
71
80
79
70
85
77
82
90
66
82
70
67
82
69
80
87
74
87
67
76
83
62
67
55
52
53
71
66
60
Page
8-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-24. Estimated Mean Body Weights of Male and Female by
NHANES IV Data (continued)
Age Groupa Male (k§)
(years) Mean
54 to 55
55 to 56
56 to 57
57 to 58
58 to 59
59 to 60
60 to 61
61 to 62
62 to 63
63 to 64
64 to 65
65 to 66
66 to 67
67 to 68
68 to 69
69 to 70
70 to 71
71 to 72
72 to 73
73 to 74
74 to 75
75 to 76
76 to 77
77 to 78
78 to 79
79 to 80
80 to 81
81 to 82
82 to 83
83 to 84
84 to 85
85+
a
SD
N
Source:
90.51
84.84
84.48
86.02
89.11
83.82
89.53
86.04
84.46
86.51
91.45
89.46
90.40
85.34
84.48
92.35
81.91
79.65
84.67
89.70
80.85
84.26
86.13
81.68
81.99
80.18
75.90
73.77
81.01
76.07
73.06
74.10
SD
21.10
18.72
18.55
20.50
21.33
16.33
17.90
15.44
16.28
20.07
16.88
18.44
20.13
19.18
12.92
16.95
16.38
21.31
17.45
15.36
17.00
11.94
15.45
14.15
16.39
10.39
12.07
7.40
13.46
10.63
12.88
12.23
N
32
20
26
26
19
25
60
34
41
24
39
41
49
36
26
24
47
25
32
35
17
25
20
18
26
19
27
31
20
12
12
46
Data were converted from ages in months to a
23 mo.
= Standard deviation
Single- Year Age Groups Using
Female (kg)
Mean
75.19
79.87
80.68
73.07
71.21
76.28
75.97
77.01
75.78
77.95
76.75
72.95
79.00
77.76
73.28
69.94
70.50
66.22
76.89
72.75
69.21
68.61
67.42
78.35
72.30
67.95
60.97
68.76
62.93
66.24
66.29
59.68
ges in years.
SD
18.07
16.71
20.24
13.79
16.01
16.36
18.66
16.67
13.13
16.96
18.29
18.37
17.67
18.21
14.12
9.20
12.94
13.04
15.30
16.80
16.35
10.42
11.34
17.45
14.16
12.54
14.46
13.75
9.81
11.68
15.04
10.04
For instance,
N
36
25
32
24
17
17
43
37
45
39
42
41
26
35
35
32
32
35
21
27
31
21
25
21
17
21
23
25
20
12
17
59
age
Overall (kg^
Mean
81.46
82.39
82.72
80.20
79.97
80.76
83.70
81.12
79.50
80.73
83.98
80.38
86.09
81.18
78.20
80.53
76.06
68.99
81.08
81.69
73.34
75.14
73.62
80.09
77.77
73.39
65.39
71.28
68.51
70.90
68.79
64.45
1-2 yr represents aj
SD
19.58
17.24
20.75
15.13
17.97
17.32
20.56
17.56
13.78
17.56
20.01
20.24
19.26
19.01
15.07
10.59
13.96
13.58
16.13
18.87
17.32
11.41
12.38
17.84
15.23
13.54
15.51
14.25
10.68
12.50
15.60
10.84
;es from
N
68
45
58
50
36
42
103
71
86
63
81
82
75
71
61
56
79
60
53
62
48
46
45
39
43
40
50
56
40
24
29
105
12 to
= Number of individuals.
Portier et al., 2007.
Exposure Factors Handbook
September 2011
Page
8-39
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-25. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments"
Age Group ^^
(years)
Ito6
7 to 16
18 to 65
65+
a
SD
N
Source:
II
III
IV
II
III
IV
II
III
IV
II
III
IV
Male (kg)
Mean
17.0
16.9
17.1
45.2
49.3
47.9
78.65
82.19
85.47
74.45
79.42
83.50
SD
4.6
4.7
4.9
17.6
20.9
20.1
13.23
16.18
19.03
13.05
14.66
16.35
Estimates were weighted using the
= Standard deviation.
= Number of individuals.
Portieretal.,2007.
N
2,097
3,149
633
1,618
2,549
1,203
4,711
6,250
1,908
1,041
1,857
547
Female (kg)
Mean
16.3
16.5
17.5
43.9
46.8
47.9
65.47
69.45
74.55
66.26
66.76
69.59
SD
4.7
4.9
5.0
15.9
18.0
19.2
13.77
16.55
19.32
13.25
14.52
14.63
N
1,933
3,221
541
1,507
2,640
1,178
5,187
7,182
2,202
1,231
1,986
535
Overall (kg)
Mean
16.7
16.8
17.3
44.8
47.8
47.7
71.23
75.61
79.96
69.56
72.25
75.54
SD
4.
5.
5.
5
0
0
17.5
18.4
19.1
11.
18.
20.
12.
15.
15.
97
02
73
20
71
88
N
4,030
6,370
1,174
3,125
5,189
2,381
9,898
13,462
4,110
2,272
3,843
1,082
sample weights provided with each survey.
Page Exposure Factors Handbook
8-40 September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-26. Estimated Percentile Distribution of Body Weight b>
Derived from 1994-1996, 1998 CSFII
Fine Age Categories
Weight (kg)
Age Group
Birth to 1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
18to<21years
>21 years
>65 years
All ages
a Sample size
Monitoring
Sample
Size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
9,049
2,139
19,850
Meai
4
5
7
9
12
14
18
30
54
67
69
76
72
65
1 1st
la
2a
4a
6a
8a
10a
11
16a
29a
41a
45a
45
44
8
Percentile
5th
2a
3a
5
7
9
10
13
18
33
46a
48a
51
50
15
10th
3a
4
5
7
9
11
13
20
36
50
51
54
54
22
does meet minimum reporting requirements
in the United States (LSRO, 1995).
25th
3
4
6
8
10
12
16
23
44
56
58
63
62
52
50th 75th
3
5
7
9
11
14
18
27
52
63
66
74
71
67
as described
4
6
8
10
13
16
20
35
61
73
77
86
81
81
in the 3rd
90th
4a
6
9
11
14
18
23
41
72
86
89
99
93
95
95th
5a
7a
10
12
15
19
25
45
82
100a
100a
107
100
104
99th
5a
8a
12a
13a
19a
22a
32
57a
95a
114a
117a
126
113
122
Report on Nutrition
Source: Kahn and Stralka, 2008.
Exposure Factors Handbook
September 2011
Page
8-41
-------
§
s
a.
3!
Table 8-27. Estimated Percentile Distribution of Body Weight by Fine Age Categories with Confidence Interval
Weight (kg)
Age Group Sample Size
Birth to 1 month 88
1 to <3 months 245
3 to <6 months 411
6 to <12 months 678
1 to <2 years 1,002
2 to <3 years 994
3 to <6 years 4,112
6to21 years 9,049
>65 years 2,139
All ages 19,850
Mean
90% CI
Estimate T TT Estimate
Lower Upper
Bound Bound
4 3 4 4a
5 556
7 7 7 94
9 9 9 11
12 12 12 14
14 14 14 18
18 18 18 23
30 29 30 41
54 53 55 72
67 66 68 86
69 68 70 89
76 99
72 93
65 95
90th Percentile
95th Percentile
90% BI
Lower
Bound
a
6
95
11
14
17
23
41
70
84
88
-
-
-
Upper
Bound
a
7
95
11
15
18
23
43
75
95
95
-
-
-
90% BI
Estimate
Lower
Bound
a
ya
105
1Z7
15
19
25
45
82
100a
100a
107
100
104
a Sample size does meet minimum reporting requirements as described in the 3r Report on Nutrition Monitoring in the United States (Vol
Interval estimates may involve aggregation of variance estimation units when data are too sparse to support estimation of variance.
CI = Confidence interval.
BI = Percentile intervals estimated using percentile bootstrap method with 1,000 bootstrap replications.
= Data unavailable.
Source: Kahn and Stralka, 2008.
a
105
12
15
18
25
44
81
95a
95a
-
-
-
I) (LSRO,
Upper
Bound
a
7
10
12
16
19
25
48
84
109a
104a
-
-
-
1995).
Q
I
I
§
ri
I
-------
ft
1=
Table 8-28. Distribution of 1
Trimester
1st Trimester, kg
Underweight
Normal weight
Overweight
Obese
2nd Trimester, kg/wka
Underweight
Normal weight
Overweight
Obese
3rd Trimester, kg/wka
Underweight
Normal weight
Overweight
Obese
s* Trimester Weight Gain and 2nd and 3rd Trimesters Rates of Gain
Good Pregnancy Outcomes
in Women with
Percentile of Weight Gain
10*
-1.81
-2.21
-2.91
-3.08
0.33
0.31
0.21
0.06
0.26
0.26
0.21
0.19
a To calculate the distribution of total
table by 13 wk.
SD = Standard deviation.
Source: Carmichael et al., 1997.
25th
-0.14
-0.09
-0.59
-0.86
0.44
0.44
0.36
0.24
0.36
0.37
0.34
0.31
gain (kg)
50th
1.92
2.20
2.38
1.17
0.56
0.56
0.49
0.42
0.47
0.50
0.47
0.43
in the 2nd and
75th
3.78
4.37
4.63
3.89
0.69
0.71
0.65
0.56
0.60
0.64
0.63
0.64
3rd trimesters, multiply
90th
5.11
6.59
7.04
7.22
0.82
0.85
0.83
0.78
0.71
0.77
0.77
0.80
the values
Mean ± SD
1.92 ±3.06
2.19 ±3.47
2.16 ±3.95
1.65 ±3. 94
0.51 ±0.20
0.58 ±0.22
0.51 ±0.24
0.41 ±0.27
0.48 ±0.19
0.51 ±0.21
0.49 ±0.22
0.47 ±0.24
in the
Q
I
i
I
8s
I
I
-------
Table 8-29. Estimated Body Weights of Pregnant
Women— NHANES
(1999-2006)
Weight (kg)
Trimester Sample size
1
2
3
Ref/Dka
All
a
SD
Source:
204
430
402
186
1,222
Mean
Estimate
76
73
80
69
75
Refers to pregnant women who either refused to tell which trimester they
= Standard deviation.
U.S. EPA Analysis of NHANES 1999-2006 data.
Percentiles
SD
3
1
1
2
1
5th
48
50
60
46
50
10th
50
53
63
52
55
15th
55
57
65
55
59
25th *
6050 74
61 72
69 77
60 65
63 73
75th
91
83
88
77
85
85th
98
93
99
84
94
90th
106
95
104
87
99
95th
108
98
108
108
107
were in or didn't know or data were missing.
§
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ri
A.
3!
8s
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Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-30
Gestational Number of
Age (wk) Women
8 6
9 7
10 15
11 13
12 18
13 43
14 61
15 63
16 59
17 36
18 58
19 31
20 21
21 43
22 69
23 71
24 74
25 48
26 86
27 76
28 91
29 88
30 128
31 113
32 210
33 242
34 373
35 492
36 1,085
37 1,798
38 3,908
39 5,413
40 10,586
41 3,399
42 1,725
43 507
44 147
. Fetal Weight
10th
a
-
-
-
-
-
-
-
-
-
-
-
-
280
320
370
420
490
570
660
770
890
1,030
1,180
1,310
1,480
1,670
1,870
2,190
2,310
2,510
2,680
2,750
2,800
2,830
2,840
2,790
a Data not available.
b Median fetal weights may be overestimated
delivered at these gestational weeks.
Source: Brenner etal., 1976.
(g) Percentiles
25th
-
-
-
-
11
23
3,405
51
80
125
172
217
255
330
410
460
530
630
730
840
980
1,100
1,260
1,410
1,570
1,720
1,910
2,130
2,470
2,580
2,770
2,910
3,010
3,070
3,110
3,110
3,050
Throughout
50th
6.1"
7.3b
8.1b
11. 9b
21
35
51
77
117
166
220
283
325
410
480
550
640
740
860
990
1,150
1,310
1,460
1,630
1,810
2,010
2,220
2,430
2,650
2,870
3,030
3,170
3,280
3,360
3,410
3,420
3,390
They were derived from only a
Pregnancy
75th
-
-
-
-
34
55
77
108
151
212
298
394
460
570
630
690
780
890
1,020
1,160
1,350
1,530
1,710
1,880
2,090
2,280
2,510
2,730
2,950
3,160
3,320
3,470
3,590
3,680
3,740
3,780
3,770
90th
-
-
-
-
-
-
-
-
-
-
-
-
-
860
920
990
1,080
1,180
1,320
1,470
1,660
1,890
2,100
2,290
2,500
2,690
2,880
3,090
3,290
3,470
3,610
3,750
3,870
3,980
4,060
4,100
4,110
small proportion of the fetuses
Exposure Factors Handbook Page
September 2011 8-45
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
Table 8-31. Neonatal Weight by Gestational Age for Male and Female Combined
Gestational Age
(weeks)
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Source: Doubilet
5*
450
523
609
707
820
947
1,090
1,249
1,422
1,608
1,804
2,006
2,210
2,409
2,595
2,762
2,900
3,002
3,061
etal., 1997.
10*
490
568
660
765
884
1,020
1,171
1,338
1,519
1,714
1,919
2,129
2,340
2,544
2,735
2,904
3,042
3,142
3,195
25*
564
652
754
870
1,003
1,151
1,317
1,499
1,696
1,906
2,125
2,349
2,572
2,786
2,984
3,155
3,293
3,388
3,432
Weight (g)
50th
660
760
875
1,005
1,153
1,319
1,502
1,702
1,918
2,146
2,383
2,622
2,859
3,083
3,288
3,462
3,597
3,685
3,717
75th
772
885
1,015
1,162
1,327
1,511
1,713
1,933
2,169
2,416
2,671
2,927
3,177
3,412
3,622
3,798
3,930
4,008
4,026
90th
889
1,016
1,160
1,322
1,504
1,706
1,928
2,167
2,421
2,687
2,959
3,230
3,493
3,736
3,952
4,127
4,254
4,322
4,324
95th
968
1,103
1,257
1,430
1,623
1,836
2,070
2,321
2,587
2,865
3,148
3,428
3,698
3,947
4,164
4,340
4,462
4,523
4,515
Page
8-46
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
CDC Growth Charts: United States
W.
f-er
Weight-for-age percentiles:
Boys, birth to 36 months
VLL
12 15 18 21
Age (months)
Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months.
Source: Kuczmarski et aL 2002.
- 4 —
Ib
Exposure Factors Handbook
September 2011
Page
8-47
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
CDC Growth Charts: United States
Weight-for-age percent lies:
Girls, birth to 36 months
95lh. - 3B .
2t 24 27 30 33
Age (months)
Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months.
Source: Kuczmarski et al., 2002.
Page
8-48
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
CDC Growth Charts: United States
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Exposure Factors Handbook
Chapter 8—Body Weight Studies
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Exposure Factors Handbook
Chapter 8—Body Weight Studies
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kg/m3
Body mass index-for-age percentiles:
Boys, 2 to 20 years
V
23456
10 11 12 13 14 15
Age (years)
17 IS 19 20
Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years.
Source: Kuczmarski et al., 2002.
Exposure Factors Handbook
September 2011
Page
8-51
-------
Exposure Factors Handbook
Chapter 8—Body Weight Studies
CDC Growth Charts: United States
Body mass index-for-age percent!les:
Girls, 2 to 20 years
9 10 11 12 13 14 15 IS 17 18 19 20
Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years.
Source: Kuczmarski et aL 2002.
Page
8-52
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
TABLE OF CONTENTS
LIST OF TABLES 9-ii
9. INTAKE OF FRUITS AND VEGETABLES 9-1
9.1. INTRODUCTION 9-1
9.2. RECOMMENDATIONS 9-2
9.3. INTAKE STUDIES 9-5
9.3.1. Key Fruits and Vegetables Intake Study 9-5
9.3.1.1. U.S. EPA Analysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 9-5
9.3.2. Relevant Fruit and Vegetable Intake Studies 9-7
9.3.2.1. U.S. Department of Agriculture (USD A) (1980, 1992, 1996a,b) 9-7
9.3.2.2. U.S. Department of Agriculture (USDA) (1999a) 9-7
9.3.2.3. U.S. Department of Agriculture (USDA) (1999b) 9-7
9.3.2.4. U.S. EPA Analysis of Continuing Survey of Food Intake Among
Individuals (CSFII) 1994-1996, 1998 Based on U.S. Department of
Agriculture (USDA) (2000) and U.S. EPA (2000) 9-8
9.3.2.5. Smiciklas-Wright et al. (2002) 9-9
9.3.2.6. Vitolins et al. (2002) 9-9
9.3.2.7. Fox et al. (2004) 9-10
9.3.2.8. Ponza et al. (2004) 9-11
9.3.2.9. Fox et al. (2006) 9-11
9.3.2.10. Menella et al. (2006) 9-11
9.4. CONVERSION BETWEEN WET-AND DRY-WEIGHT INTAKE RATES 9-12
9.5. REFERENCES FOR CHAPTER 9 9-12
Exposure Factors Handbook Page
September 2011 9-i
-------
Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
LIST OF TABLES
Table 9-1. Recommended Values for Intake of Fruits and Vegetables, Edible Portion, Uncooked 9-3
Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables 9-4
Table 9-3. Per Capita Intake of Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day,
edible portion, uncooked weight) 9-14
Table 9-4. Consumer-Only Intake of Fruits and Vegetables Based on the 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 9-15
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 9-16
Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006
NHANES (g/kg-day, edible portion, uncooked weight) 9-24
Table 9-7. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
(1977-1978) 9-31
Table 9-8. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
(1987-1988, 1994, and 1995) 9-32
Table 9-9. Per Capita Consumption of Fresh Fruits and Vegetables in 1997 9-33
Table 9-10. Mean Quantities of Vegetables Consumed Daily by Sex and Age, for Children, Per Capita
(g/day, as-consumed) 9-34
Table 9-11. Percentage of Individuals Consuming Vegetables, by Sex and Age, for Children (%) 9-35
Table 9-12. Mean Quantities of Fruits Consumed Daily by Sex and Age, for Children, Per Capita
(g/day, as-consumed) 9-36
Table 9-13. Percentage of Individuals Consuming, Fruits by SexandAge, for Children (%) 9-37
Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day,
edible portion, uncooked weight) 9-38
Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 9-40
Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 9-42
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998
CSFII (g/kg-day, edible portion, uncooked weight) 9-51
Table 9-18. Per Capita Intake of Exposed Fruits Based on 1994-1996 CSFII (g/kg-day, as-consumed) 9-58
Table 9-19. Per Capita Intake of Protected Fruits Based on 1994-1996 CSFII (g/kg-day,
as-consumed) 9-59
Table 9-20. Per Capita Intake of Exposed Vegetables (g/kg-day, as-consumed) 9-60
Table 9-21. Per Capita Intake of Protected Vegetables Based on 1994-1996 CSFII (g/kg-day,
as-consumed) 9-61
Table 9-22. Per Capita Intake of Root Vegetables Based on 1994-1996 CSFII (g/kg-day,
as-consumed) 9-62
Table 9-23. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and the
Percentage of Individuals Consuming These Foods in Two Days 9-63
Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and
Percentage of Individuals Consuming These Foods in Two Days, by Food 9-64
Table 9-25. Consumption of Major Food Groups: Median Servings (and Ranges) by Demographic
and Health Characteristics, for Older Adults 9-66
Table 9-26. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 9-67
Table 9-27. Percentage of Infants and Toddlers Consuming Different Types of Vegetables 9-68
Table 9-28. Top Five Vegetables Consumed by Infants and Toddlers 9-69
Table 9-29. Percentage of Infants and Toddlers Consuming Different Types of Fruits 9-70
Table 9-30. Top Five Fruits Consumed by Infants and Toddlers 9-71
Table 9-31. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants
(Percentages) 9-72
Table 9-32. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
Participation Status 9-73
Page
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
LIST OF TABLES (continued)
Table 9-33. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 9-74
Table 9-34. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 9-75
Table 9-35. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Fruits and Vegetables on a Given Day 9-76
Table 9-36. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants and
Toddlers Per Age Group 9-77
Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions 9-78
Exposure Factors Handbook Page
September 2011 9-iii
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
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Page Exposure Factors Handbook
9-iv September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
9. INTAKE OF FRUITS AND
VEGETABLES
9.1. INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, fruits and vegetables may become
contaminated with toxic chemicals by several
different pathways. Ambient pollutants from the air
may be deposited on or absorbed by the plants or
dissolved in rainfall or irrigation waters that contact
the plants. Pollutants may also be absorbed through
plant roots from contaminated soil and ground water.
The addition of pesticides, soil additives, and
fertilizers may also result in contamination of fruits
and vegetables. To assess exposure through this
pathway, information on fruit and vegetable ingestion
rates is needed.
A variety of terms may be used to define intake of
fruits and vegetables (e.g., consumer-only intake, per
capita intake, total fruit intake, total vegetable intake,
as-consumed intake, dry-weight intake). These terms
are defined below to assist the reader in interpreting
and using the intake rates that are appropriate for the
exposure scenario being assessed.
Consumer-only intake is defined as the quantity
of fruits and vegetables consumed by individuals
during the survey period. These data are generated by
averaging intake across only the individuals in the
survey who consumed these food items. Per capita
intake rates are generated by averaging
consumer-only intakes over the entire population
(including those individuals that reported no intake).
In general, per capita intake rates are appropriate for
use in exposure assessments for which average dose
estimates are of interest because they represent both
individuals who ate the foods during the survey
period and individuals who may eat the food items at
some time, but did not consume them during the
survey period. Per capita intake, therefore, represents
an average across the entire population of interest,
but does so at the expense of underestimating
consumption for the subset of the population that
consumed the food in question. Total fruit intake
refers to the sum of all fruits consumed in a day
including canned, dried, frozen, and fresh fruits.
Likewise, total vegetable intake refers to the sum of
all vegetables consumed in a day including canned,
dried, frozen, and fresh vegetables.
Intake rates may be expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the
as-consumed weight. Some of the food ingestion
values provided in this chapter are expressed as
as-consumed intake rates because this is the fashion
in which data were reported by survey respondents.
Others are provided as uncooked weights based on
analyses of survey data that account for weight
changes that occur during cooking. This is of
importance because concentration data to be used in
the dose equation are often measured in uncooked
food samples. It should be recognized that cooking
can either increase or decrease food weight.
Similarly, cooking can increase the mass of
contaminant in food (due to formation reactions, or
absorption from cooking oils or water) or decrease
the mass of contaminant in food (due to vaporization,
fat loss, or leaching). The combined effects of
changes in weight and changes in contaminant mass
can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. It is important
for the assessor to be aware of these issues and
choose intake rate data that best match the
concentration data that are being used. For more
information on cooking losses and conversions
necessary to account for such losses, refer to
Chapter 13 of this handbook.
Sometimes contaminant concentrations in food
are reported on a dry-weight basis. When these data
are used in an exposure assessment, it is
recommended that dry-weight intake rates also be
used. Dry-weight food concentrations and intake
rates are based on the weight of the food consumed
after the moisture content has been removed. For
information on converting the intake rates presented
in this chapter to dry-weight intake rates, refer to
Section 9.4.
The purpose of this chapter is to provide intake
data for fruits and vegetables. The recommendations
for fruit and vegetable ingestion rates are provided in
the next section, along with a summary of the
confidence ratings for these recommendations. The
recommended values are based on the key study
identified by U.S. Environmental Protection Agency
(EPA) for this factor. Following the
recommendations, the key study on fruit and
vegetable ingestion is summarized. Relevant data on
ingestion of fruits and vegetables are also provided.
These data are presented to provide the reader with
added perspective on the current state-of-knowledge
pertaining to ingestion of fruits and vegetables.
Exposure Factors Handbook
September 2011
Page
9-1
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
9.2.
RECOMMENDATIONS
Table 9-1 presents a summary of the
recommended values for per capita and
consumer-only intake of fruits and vegetables.
Table 9-2 provides confidence ratings for the fruit
and vegetable intake recommendations.
The U.S. EPA analysis of data from the
2003-2006 National Health and Nutrition
Examination Survey (NHANES) was used in
selecting recommended intake rates for the general
population. The U.S. EPA analysis was conducted
using childhood age groups that differed slightly
from U.S. EPA's Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood Exposures
to Environmental Contaminants (U.S. EPA, 2005).
However, for the purposes of the recommendations
presented here, childhood data were placed in the
standardized age categories closest to those used in
the analysis.
The NHANES data on which the
recommendations are based are short-term survey
data and may not necessarily reflect the long-term
distribution of average daily intake rates. However,
since broad categories of food (i.e., total fruits and
total vegetables), are eaten on a daily basis
throughout the year with minimal seasonality, the
short-term distribution may be a reasonable
approximation of the long-term distribution, although
it will display somewhat increased variability. This
implies that the upper percentiles shown here may
tend to overestimate the corresponding percentiles of
the true long-term distribution. In general, the
recommended values based on U.S. EPA's analysis of
NHANES data represent the i.e., uncooked weight of
the edible portion of fruits and vegetables.
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Table 9-1. Recommended Values for Intake of Fruits and Vegetables, Edible Portion, Uncooked"
Age Group
(years)
Per Capita
Consumers Only
Mean
95th Percentile
Mean
95th Percentile
Multiple
Percentiles
Source
g/kg-day
g/kg-day
g/kg-day
g/kg-day
Total Fruits
Birth to 1
lto<2
2to<3
3to<6
6to50
6.2
7.8
7.8
4.6
2.3
0.9
0.9
0.9
1.4
23.0b
21.3b
21.3b
14.9
8.7
3.5
3.5
3.7
4.4
10.1
8.1
8.1
4.7
2.5
1.1
1.1
1.1
1.5
25.8b
21.4b
21.4b
15.1
9.2
3.8
3.8
3.8
4.6
U.S. EPA
See Tables Analysis of
9-3 and 9-4 NHANES
2003-2006
Total Vegetables
Birth to 1
1 to<2
2to<3
3to<6
6to50
5.0
6.7
6.7
5.4
3.7
2.3
2.3
2.5
2.6
16.2"
15.6b
15.6b
13.4
10.4
5.5
5.5
5.9
6.1
6.8
6.7
6.7
5.4
3.7
2.3
2.3
2.5
2.6
18.1"
15.6b
15.6b
13.4
10.4
5.5
5.5
5.9
6.1
U.S. EPA
See Tables Analysis of
9-3 and 9-4 NHANES
2003-2006
Individual Fruits and Vegetables—See Tables 9-5 and 9-6
Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on
Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA,
2005). Data were placed in the standardized age categories closest to those used in the analysis.
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and
Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group
Recommendations (NCHS, 1993).
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Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodology and data analysis were adequate.
The survey sampled more than 16,000 individuals. However,
sample sizes for some individual fruits and vegetables for
some of the age groups are small. An analysis of primary data
was conducted.
No physical measurements were taken. The method relied on
recent recall of fruits and vegetables eaten.
High for total fruits and
vegetables, low for some
individual fruits and
vegetables with small sample
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key study was directly relevant to fruit and vegetable
intake.
The data were demographically representative of the U.S.
population (based on stratified random sample).
Data were collected between 2003 and 2006.
Data were collected for two non-consecutive days.
High
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The NHANES data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
NHANES follows a strict QA/QC procedure. The U.S. EPA
analysis has only been reviewed internally, but the
methodology used has been peer reviewed in an analysis of
previous data.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were provided for total fruits and total
vegetables. Means were provided for individual fruits and
vegetables.
Data collection was based on recall of consumption for a
2-day period; the accuracy of using these data to estimate
long-term intake (especially at the upper percentiles) is
uncertain. However, use of short-term data to estimate
chronic ingestion can be assumed for broad categories of
foods such as total fruits and total vegetables. Uncertainty is
greater for individual fruits and vegetables.
Medium to high for averages,
low for long-term upper
percentiles; low for
individual fruits and
vegetables
Evaluation and Review
Peer Review
Number and Agreement of Studies
Medium
The NCHS NHANES survey received a high level of peer
review. The U.S. EPA analysis of these data has not been
peer reviewed outside the Agency, but the methodology used
has been peer reviewed in an analysis of previous data.
There was one key study.
Overall Rating
Medium to High confidence
in the averages; Low for
some individual fruits and
vegetables with small sample
size; Low confidence in the
long-term upper percentiles
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9.3.
INTAKE STUDIES
9.3.1. Key Fruits and Vegetables Intake Study
9.3.1.1. U.S. EPA Analysis of Consumption Data
from 2003-2006 National Health and
Nutrition Examination Survey (NHANES)
The key source of recent information on
consumption rates of fruits and vegetables is the U.S.
Centers for Disease Control and Prevention's
National Center for Health Statistics' (NCHS)
NHANES. Data from NHANES 2003-2006 have
been used by the U.S. EPA, Office of Pesticide
Programs (OPP) to generate per capita and consumer-
only intake rates for both individual fruits and
vegetables and total fruits and vegetables.
NHANES is designed to assess the health and
nutritional status of adults and children in the United
States. In 1999, the survey became a continuous
program that interviews a nationally representative
sample of approximately 7,000 persons each year and
examines a nationally representative sample of about
5,000 persons each year, located in counties across
the country, 15 of which are visited each year. Data
are released on a 2-year basis, thus, for example, the
2003 data are combined with the 2004 data to
produce NHANES 2003-2004.
The dietary interview component of NHANES is
called What We Eat in America and is conducted by
the U.S. Department of Agriculture (USDA) and the
U.S. Department of Health and Human Services
(DHHS). DHHS' NCHS is responsible for the sample
design and data collection, and USDA's Food
Surveys Research Group is responsible for the dietary
data collection methodology, maintenance of the
databases used to code and process the data, and data
review and processing. Beginning in 2003,
2 non-consecutive days of 24-hour intake data were
collected. The first day is collected in-person, and the
second day is collected by telephone 3 to 10 days
later. These data are collected using USDA's dietary
data collection instrument, the Automated Multiple
Pass Method. This method provides an efficient and
accurate means of collecting intakes for large-scale
national surveys. It is fully computerized and uses a
5-step interview. Details can be found at USDA's
Agriculture Research Service
(http://www.ars.usda.gov/ba/bhnrc/fsrg).
For NHANES 2003-2004, there were
12,761 persons selected; of these, 9,643 were
considered respondents to the mobile examination
center (MEC) examination and data collection.
However, only 9,034 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,354 provided complete dietary intakes for Day 2.
For NHANES 2005-2006, there were 12,862 persons
selected; of these, 9,950 were considered respondents
to the MEC examination and data collection.
However, only 9,349 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,429 provided complete dietary intakes for Day 2.
The 2003-2006 NHANES surveys are stratified,
multistage probability samples of the civilian
non-institutionalized U.S. population. The sampling
frame was organized using 2000 U.S. population
census estimates. NHANES oversamples low-income
persons, adolescents 12 to 19 years, persons 60 years
and older, African Americans, and Mexican
Americans. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all four years of the
surveys can be combined. Additional information on
NHANES can be obtained at
http://www.cdc.gov/nchs/nhanes.htm.
In 2010, U.S. EPA, OPP used NHANES
2003-2006 data to update the Food Commodity
Intake Database (FCID) that was developed in earlier
analyses of data from the USDA's Continuing Survey
of Food Intake among Individuals (CSFII) (USDA,
2000; U.S. EPA, 2000) (see Section 9.3.2.4),
NHANES data on the foods people reported eating
were converted to the quantities of agricultural
commodities eaten. "Agricultural commodity" is a
term used by U.S. EPA to mean plant (or animal)
parts consumed by humans as food; when such items
are raw or unprocessed, they are referred to as "raw
agricultural commodities." For example, an apple pie
may contain the commodities apples, flour, fat, sugar,
and spices. FCID contains approximately 558 unique
commodity names and 8-digit codes. The FCID
commodity names and codes were selected and
defined by U.S. EPA and were based on the U.S. EPA
Food Commodity Vocabulary
(http ://www. epa. gov/pesticides/foodfeed/).
Intake rates were generated for a variety of food
items/groups based on the agricultural commodities
included in the FCID. These intake rates represent
intake of all forms of the product (e.g., both home
produced and commercially produced) for individuals
who provided data for 2 days of the survey. Note that
if the person reported consuming food for only one
day, their 2-day average would be half the amount
reported for the one day of consumption. Individuals
who did not provide information on body weight or
for whom identifying information was unavailable
were excluded from the analysis. Two-day average
intake rates were calculated for all individuals in the
database for each of the food items/groups. These
average daily intake rates were divided by each
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individual's reported body weight to generate intake
rates in units of grams per kilogram of body weight
per day (g/kg-day). The data were weighted
according to the 4-year, 2-day sample weights
provided in NHANES 2003-2006 to adjust the data
for the sample population to reflect the national
population.
Summary statistics were generated on a
consumer-only and on a per capita basis. Summary
statistics, including: number of observations,
percentage of the population consuming the fruits or
vegetables being analyzed, mean intake rate, and
standard error of the mean intake rate were calculated
for total fruits, total vegetables, and selected
individual fruits and vegetables. Individual fruits and
vegetables were selected to be consistent with
Chapter 13, which was based on having at least
30 households reporting consumption for the
particular fruit or vegetable. Percentiles of the intake
rate distribution (i.e., 1st, 5th, 10th, 25th, 50th, 75th, 90th,
95th, 99th, and the maximum value) were also
provided for total fruits and total vegetables. Data
were provided for the following age groups: birth to
1 year, 1 to 2 years, 3 to 5 years, 6 to 12 years, 13 to
19 years, 20 to 49 years, and >50 years. Data for
females 13 to 49 years were also provided. Because
these data were developed for use in U.S. EPA's
pesticide registration program, the childhood age
groups used are slightly different than those
recommended in U.S. EPA's Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005).
Table 9-3 presents per capita intake data for total
fruits and total vegetables in g/kg-day; Table 9-4
provides consumer-only intake data for total fruits
and total vegetables in g/kg-day. Table 9-5 provides
per capita intake data for individual fruits and
vegetables in g/kg-day, and Table 9-6 provides
consumer-only intake data for individual fruits and
vegetables in g/kg-day. In general, these data
represent intake of the edible portions of uncooked
foods.
The results are presented in units of g/kg-day.
Thus, use of these data in calculating potential dose
does not require the body-weight factor to be
included in the denominator of the average daily dose
(ADD) equation. It should be noted that converting
these intake rates into units of g/day by multiplying
by a single average body weight is inappropriate,
because individual intake rates were indexed to the
reported body weights of the survey respondents.
Also, it should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) does not necessarily reflect the
long-term distribution of average daily intake rates.
The distributions generated from short-term and
long-term data will differ to the extent that each
individual's intake varies from day to day; the
distributions will be similar to the extent that
individuals' intakes are constant from day to day.
Day-to-day variation in intake among individuals will
be high for fruits and vegetables that are highly
seasonal and for fruits and vegetables that are eaten
year-round, but that are not typically eaten every day.
For these fruits and vegetables, the intake distribution
generated from short-term data will not be a good
reflection of the long-term distribution. On the other
hand, for broad categories of foods (e.g., total fruits
and total vegetables) that are eaten on a daily basis
throughout the year, the short-term distribution may
be a reasonable approximation of the true long-term
distribution, although it will show somewhat more
variability. In this chapter, distributions are provided
only for broad categories of fruits and vegetables
(i.e., total fruits and total vegetables). Because of the
increased variability of the short-term distribution,
the short-term upper percentiles shown here may
overestimate the corresponding percentiles of the
long-term distribution. For individual foods, only the
mean, standard error, and percent consuming are
provided.
An advantage of using the U.S. EPA's analysis of
NHANES data is that it provides distributions of
intake rates for various age groups of children and
adults, normalized by body weight. The data set was
designed to be representative of the U.S. population
and includes four years of intake data combined.
Another advantage is the currency of the data; the
NHANES data are from 2003-2006. However,
short-term dietary data may not accurately reflect
long-term eating patterns and may under-represent
infrequent consumers of a given food. This is
particularly true for the tails (extremes) of the
distribution of food intake. Because these are 2-day
averages, consumption estimates at the upper end of
the intake distribution may be underestimated if these
consumption values are used to assess acute (i.e.,
short-term) exposures, also, the analysis was
conducted using slightly different childhood age
groups than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, given the similarities in the age groups
used, the data should provide suitable intake
estimates for the age groups of interest.
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9.3.2. Relevant Fruit and Vegetable Intake
Studies
9.3.2.1. U.S. Department of Agriculture (USDA)
(1980,1992,1996a, b)—Food and Nutrient
Intakes of Individuals in One Day in the
United States
USDA calculated mean intake rates for total fruits
and total vegetables using data from the 1977-1978
and 1987-1988 Nationwide Food Consumption
Surveys (NFCS) (USDA, 1980, 1992) and CSFII data
from 1994 and 1995 (USDA, 1996a, b). Table 9-7
presents the mean per capita total intake rates for
total fruits and total vegetables from the 1977-1978
NFCS. Table 9-8 presents similar data from the
1987-1988 NFCS and the 1994 and 1995 CSFII.
Note that the age classifications used in these surveys
were slightly different than those used in the
1977-1978 NFCS. Tables 9-7 and 9-8 include both
per capita intake rates and intake rates for
consumers-only for various ages of individuals.
Intake rates for consumers-only were calculated by
dividing the per capita consumption rate by the
fraction of the population consuming vegetables or
fruits in a day.
The advantages of using these data are that they
provide intake estimates for all fruits or all
vegetables, combined. Again, these estimates are
based on one-day dietary data, which may not reflect
usual consumption patterns. These data are based on
older surveys and may not be entirely representative
of current eating patterns.
9.3.2.2. U.S. Department of Agriculture (USDA)
(1999a)—Food Consumption, Prices, and
Expenditures, 1970-1997
The USDA's Economic Research Service
calculates the amount of food available for human
consumption in the United States on an annual basis
(USDA, 1999a). Supply and utilization balance
sheets are generated based on the flow of food items
from production to end uses for the years 1970 to
1997. Total available supply is estimated as the sum
of production and imports (USDA, 1999a). The
availability of food for human use commonly termed
as "food disappearance" is determined by subtracting
exported foods from the total available supply
(USDA, 1999a). USDA (1999a) calculates the per
capita food consumption by dividing the total food
disappearance by the total U.S. population. USDA
(1999a) estimated per capita consumption data for
various fruit and vegetable products from
1970-1997. Table 9-9 presents retail weight per
capita data. These data have been derived from the
annual per capita values in units of pounds per year,
presented by USDA (1999a), by converting to units
of g/day.
An advantage of this study is that it provides per
capita consumption rates for fruits and vegetables
that are representative of long-term intake because
disappearance data are generated annually. One of the
limitations of this study is that disappearance data do
not account for losses from the food supply from
waste or spoilage. As a result, intake rates based on
these data may overestimate daily consumption
because they are based on the total quantity of
marketable commodity utilized. Thus, these data
represent bounding estimates of intake rates only. It
should also be noted that per capita estimates based
on food disappearance are not a direct measure of
actual consumption or quantity ingested; instead, the
data are used as indicators of changes in usage over
time (USDA, 1999a). These data are based on older
surveys and may not be entirely representative of
current consumption patterns.
9.3.2.3. U.S. Department of Agriculture (USDA)
(1999b)—Food and Nutrient Intakes by
Children 1994-1996,1998, Table Set 17
USDA (1999b) calculated national probability
estimates of food and nutrient intake by children
based on four years of the CSFII (1994-1996 and
1998) for children age nine years and under, and on
CSFII 1994-1996 only for children age 10 years and
over. The CSFII was a series of surveys designed to
measure the kinds and amounts of foods eaten by
Americans. Intake data, based on 24-hour dietary
recall, were collected through in-person interviews on
two non-consecutive days. Section 9.3.2.4 provides
additional information on these surveys.
USDA (1999b) used sample weights to adjust for
non-response, to match the sample to the U.S.
population in terms of demographic characteristics,
and to equalize intakes over the four quarters of the
year and the seven days of the week. A total of
503 breast-fed children were excluded from the
estimates, but both consumers and non-consumers
were included in the analysis.
USDA (1999b) provided data on the mean per
capita quantities (grams) of various food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods
in one day of the survey. Tables 9-10 through 9-13
present data on the mean quantities (grams) of fruits
and vegetables consumed per individual for one day,
and the percentage of survey individuals consuming
fruits and vegetables on that survey day. Data on
mean intakes or mean percentages are based on
respondents'Day-1 intakes.
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The advantage of the USD A (1999b) study is that
it uses the 1994-1996, 1998 CSFII data set, which
includes four years of intake data, combined, and
includes the supplemental data on children. These
data are expected to be generally representative of the
U.S. population, and they include data on a wide
variety of fruits and vegetables. The data set is one of
a series of USD A data sets that are publicly available.
One limitation of this data set is that it is based on
1 day, and short-term dietary data may not accurately
reflect long-term eating patterns. Other limitations of
this study are that it only provides mean values of
food intake rates, consumption is not normalized by
body weight, and presentation of results is not
consistent with U.S. EPA's recommended age groups.
These data are based on older surveys and may not be
entirely representative of current eating patterns.
9.3.2.4. U.S. EPA Analysis of Continuing Survey of
Food Intake Among Individuals (CSFII)
1994-1996,1998 Based on U.S.
Department of Agriculture (USDA) (2000)
and U.S. EPA (2000)
U.S. EPA/OPP, in cooperation with USDA's
Agricultural Research Service, used data from the
1994-1996, 1998 CSFII to develop the FCID
(U.S. EPA, 2000; USDA, 2000), as described in
Section 9.3.1.1. The CSFII 1994-1996 was
conducted between January 1994 and January 1997
with a target population of non-institutionalized
individuals in all 50 states and Washington, DC. In
each of the three survey years, data were collected for
a nationally representative sample of individuals of
all ages. The CSFII 1998 was conducted between
December 1997 and December 1998 and surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-1996 and was
intended to be merged with CSFII 1994-1996 to
increase the sample size for children. The merged
surveys are designated as CSFII 1994-1996, 1998
(USDA, 2000). Additional information on the CSFII
can be obtained at http://www.ars.usda.gov/Services/
docs.htm?docid=14531.
The CSFII 1994-1996, 1998 collected dietary
intake data through in-person interviews on
2 non-consecutive days. The data were based on
24-hour recall. A total of 21,662 individuals provided
data for the first day; of those individuals, 20,607
provided data for a second day. The 2-day response
rate for the 1994-1996 CSFII was approximately
76%. The 2-day response rate for CSFII 1998 was
82%. The CSFII 1994-1996, 1998 surveys were
based on a complex multistage area probability
sample design. The sampling frame was organized
using 1990 U.S. population census estimates, and the
stratification plan took into account geographic
location, degree of urbanization, and socioeconomic
characteristics. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all four years of the
surveys can be combined. USDA recommends that
all four years be combined in order to provide an
adequate sample size for children.
The fruits and vegetable items/groups selected for
the U.S. EPA analysis included total fruits and
vegetables, and various individual fruits and
vegetables. CSFII data on the foods people reported
eating were converted to the quantities of agricultural
commodities eaten. Intake rates for these food
items/groups were calculated, and summary statistics
were generated on both a per capita and a
consumer-only basis using the same general
methodology as in the U.S. EPA analysis of
2003-2006 NHANES data, as described in
Section 9.3.1.1. Because these data were developed
for use in U.S. EPA's pesticide registration program,
the childhood age groups used are slightly different
than those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005).
Table 9-14 presents per capita intake data for total
fruits and total vegetables in g/kg-day; Table 9-15
provides consumer-only intake data for total fruits
and total vegetables in g/kg-day. Table 9-16 provides
per capita intake data for individual fruits and
vegetables, and Table 9-17 provides consumer-only
intake data for individual fruits and vegetables. In
general, these data represent intake of the edible
portions of uncooked foods. Tables 9-18 through 9-22
present data for exposed/protected fruits and
vegetables and root vegetables. These five tables
were created using only CSFII 1994-1996. These
data represent as-consumed intake rates.
The results are presented in units of g/kg-day.
Thus, use of these data in calculating potential dose
does not require the body-weight factor to be
included in the denominator of the ADD equation.
The cautions concerning converting these intake rates
into units of g/day by multiplying by a single average
body weight and the discussion of the use of short
term data in the NHANES description in
Section 9.3.1.1, apply to the CSFII estimates as well.
A strength of U.S. EPA's analysis is that it provides
distributions of intake rates for various age groups of
children and adults, normalized by body weight. The
analysis uses the 1994-1996, 1998 CSFII data set,
which was designed to be representative of the U.S.
population. Also, the data set includes four years of
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intake data combined and is based on a 2-day survey
period. However, as discussed above, short-term
dietary data may not accurately reflect long-term
eating patterns and may under-represent infrequent
consumers of a given food. This is particularly true
for the tails (extremes) of the distribution of food
intake. Also, the analysis was conducted using
slightly different childhood age groups than those
recommended in U.S. EPA's Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the age groups used, the data should provide suitable
intake estimates for the age groups of interest. While
the CSFII data are older than the NHANES data, they
provide relevant information on consumption by
season, region of the United States, and urbanization,
breakdowns that are not available in the publicly
released NHANES data.
9.3.2.5. Smiciklas-Wright et al (2002)—Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating Occasion
and in a Day, 1994-1996
Using data gathered in the 1994-1996 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of fruits and
vegetables consumed per eating occasion by
members of the U.S. population (i.e., serving sizes).
The estimates of serving size were based on data
obtained from 14,262 respondents, ages 2 years and
above, who provided 2 days of dietary intake
information. Only dietary intake data from users of
the specified food were used in the analysis (i.e.,
consumer-only data).
Table 9-23 presents serving size data for selected
fruits and vegetables, and Table 9-24 presents serving
size data by age group. These data are presented on
an as-consumed basis (grams) and represent the
quantity of fruits and vegetables consumed per eating
occasion. These estimates may be useful for assessing
acute exposures to contaminants in specific foods, or
other assessments where the amount consumed per
eating occasion is necessary. Only the mean and
standard deviation serving size data and percent of
the population consuming the food during the 2-day
survey period are presented in this handbook.
Percentiles of serving sizes of the foods consumed by
these age groups of the U.S. population can be found
in Smiciklas-Wright et al. (2002).
The advantages of using these data are that they
were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002)
accounted for individual foods consumed as
ingredients of mixed foods. Mixed foods were
disaggregated via recipe files so that the individual
ingredients could be grouped together with similar
foods that were reported separately. Thus, weights of
foods consumed as ingredients were combined with
weights of foods reported separately to provide a
more thorough representation of consumption.
However, it should be noted that since the recipes for
the mixed foods consumed were not provided by the
respondents, standard recipes were used. As a result,
the estimates of quantity consumed for some food
types are based on assumptions about the types and
quantities of ingredients consumed as part of mixed
foods. This study used data from the 1994 to 1996
CSFII; data from the 1998 children's supplement
were not included.
9.3.2.6. Vitolins et al. (2002)—Quality of Diets
Consumed by Older Rural Adults
Vitolins et al. (2002) conducted a survey to
evaluate the dietary intake, by food groups, of older
(>70 years) rural adults. The sample consisted of
130 community dwelling residents from two rural
counties in North Carolina. Data on dietary intake
over the preceding year were obtained in face-to-face
interviews conducted in participants' homes, or in a
few cases, a senior center. The food frequency
questionnaire used in the survey was a modified
version of the National Cancer Institute Health Habits
and History Questionnaire; this modified version
included an expanded food list containing a greater
number of ethnic foods than the original food
frequency form. Demographic and personal data
collected included sex, ethnicity, age, education,
denture use, marital status, chronic disease, and
weight. Food items reported in the survey were
separated into food groups similar to the USDA Food
Guide Pyramid and the National Cancer Institute's
5 A Day for Better Health program. These groups are:
(1) fruits and vegetables; (2) bread, cereal, rice, and
pasta; (3) milk, yogurt, and cheese; (4) meat, fish,
poultry, beans, and eggs; and (5) fats, oils, sweets,
and snacks. Medians, ranges, frequencies, and
percentages were used to summarize intake of each
food group, broken down by demographic and health
characteristics. To assess the univariate associations
of these characteristics with consumption, Wilcoxon
rank-sum tests were used. In addition, multivariate
regression models were used to determine which
demographic and health factors were jointly
predictive of intake of each of the five food groups.
Thirty-four percent of the survey participants
were African American, 36% were European
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
American, and 30% were Native American.
Sixty-two percent were female, 62% were not
married at the time of the interview, and 65% had
some high school education or were high school
graduates. Almost all of the participants (95%) had
one or more chronic diseases. Sixty percent of the
respondents were between 70 and 79 years of age; the
median age was 78 years old. Table 9-25 presents the
median servings of fruits and vegetables broken
down by demographic and health characteristic. The
only variable predictive of fruit and vegetable intake
was ethnicity (p = 0.02), with European Americans
consuming significantly more than either African
Americans or Native Americans. The multiple
regression model indicated a statistically significant
interaction between sex and ethnicity (p = 0.04) and a
significant main effect for chronic disease (p = 0.04)
for fruit and vegetable consumption. Among males,
European Americans consumed significantly more
fruits and vegetables than either African Americans
or Native Americans. Men and women did not differ
significantly in their fruit and vegetable consumption,
except for African Americans, where women had a
significantly greater intake (p = 0.01).
An advantage of this study is that dietary
information was collected on older individuals
(>70 years of age). One limitation of the study, as
noted by the study authors, is that the study did not
collect information on the length of time the
participants had been practicing the dietary behaviors
reported in the survey. Also, the survey results are
based on dietary recall; the questionnaire required
participants to report the frequency of food
consumption during the past year. The study authors
noted that, currently, there are no dietary assessment
tools that allow collecting comprehensive dietary
data over years of food consumption. Another
limitation of the study is that the small sample size
used makes associations by sex and ethnicity
difficult.
9.3.2.7. Fox et al (2004)—Feeding Infants and
Toddlers Study: What Foods Are Infants
and Toddlers Eating
Fox et al. (2004) used data from the Feeding
Infants and Toddlers Study (FITS) to assess food
consumption patterns in infants and toddlers. The
FITS was sponsored by Gerber Products Company
and was conducted to obtain current information on
food and nutrient intakes of children, ages 4 to
24 months old, in the 50 states and the District of
Columbia. The FITS is described in detail in
Devaney et al. (2004). FITS was based on a random
sample of 3,022 infants and toddlers for which
dietary intake data were collected by telephone from
their parents or caregivers between March and
July 2002. An initial recruitment and household
interview was conducted, followed by an interview to
obtain information on intake based on 24-hour recall.
The interview also addressed growth, development,
and feeding patterns. A second dietary recall
interview was conducted for a subset of
703 randomly selected respondents. The study
over-sampled children in the 4 to 6 and 9 to
11 months age groups; sample weights were adjusted
for non-response, over-sampling, and under-coverage
of some population groups. The response rate for the
FITS was 73% for the recruitment interview. Of the
recruited households, there was a response rate of
94% for the dietary recall interviews (Devaney et al.,
2004). Table 9-26 shows the characteristics of the
FITS study population.
Fox et al. (2004) analyzed the first set of 24-hour
recall data collected from all study participants. For
this analysis, children were grouped into six age
categories: 4 to 6 months, 7 to 8 months, 9 to
11 months, 12 to 14 months, 15 to 18 months, and 19
to 24 months. Table 9-27 provides the percentage of
infants and toddlers consuming different types of
vegetables at least once in a day. The percentages of
children eating any type of vegetable ranged from
39.9% for 4 to 6 month olds to 81.6% for 19 to 24
month olds. Table 9-28 provides the top
five vegetables consumed by age group. Some of the
highest percentages ranged from baby food carrots
(9.6%) in the 4 to 6 month old group to French fries
(25.5%) in the 19 to 24 month old group. Table 9-29
provides the percentage of children consuming
different types of fruit at least once per day. The
percentages of children eating any type of fruit
ranged from 41.9% to 4 to 6 month olds to 77.2% for
12 to 14 month olds. Table 9-30 provides information
on the top five fruits eaten by infants and toddlers at
least once per day. The highest percentages were for
bananas among infants 9 to 24 months, and baby
food applesauce among infants 4 to 8 months old.
The advantages of this study are that the study
population represented the U.S. population and the
sample size was large. One limitation of the analysis
done by Fox et al. (2004) was that only frequency
data were provided; no information on actual intake
rates was included. In addition, Devaney et al. (2004)
noted several limitations associated with the FITS
data. For the FITS, a commercial list of infants and
toddlers was used to obtain the sample used in the
study. Since many of the households could not be
located and did not have children in the target
population, a lower response rate than would have
occurred in a true national sample was obtained
Page
9-10
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September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
(Devaney et al., 2004). In addition, the sample was
likely from a higher socioeconomic status when
compared with all U.S. infants in this age group (4 to
24 months old), and the use of a telephone survey
may have omitted lower-income households without
telephones (Devaney et al., 2004).
9.3.2.8. Ponza etaL (2004)—Nutrient Food Intakes
and Food Choices of Infants and Toddlers
Participating in Women, Infants, and
Children (WIC)
Ponza et al. (2004) conducted a study using
selected data from the FITS to assess feeding
patterns, food choices, and nutrient intake of infants
and toddlers participating in the Special
Supplemental Nutrition Program for Women, Infants,
and Children (WIC). Ponza et al. (2004) evaluated
FITS data for the following age groups: 4 to
6 months (N= 862), 7 to 11 months (N= 1,159), and
12 to 24 months (N=996). Table 9-31 shows the
total sample size described by WIC participants and
non-participants.
The foods consumed were analyzed by tabulating
the percentage of infants who consumed specific
foods/food groups per day (Ponza et al., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza et al., 2004). Table 9-31 presents the
demographic data for WIC participants and
non-participants. Table 9-32 provides information on
the food choices for the infants and toddlers studied.
There was little difference in vegetable choices
among WIC participants and non-participants (see
Table 9-32). However, there were some differences
for fruits.
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
were not provided. Other limitations are those
associated with the FITS data, as described
previously in Section 9.3.2.7.
9.3.2.9. Fox et al. (2006)—Average Portion of
Foods Commonly Eaten by Infants and
Toddlers in the United States
Fox et al. (2006) estimated average portion sizes
consumed per eating occasion by children 4 to
24 months of age who participated in the FITS.
Section 9.3.2.7 describes the FITS, which is a
cross-sectional study designed to collect and analyze
data on feeding practices, food consumption, and
usual nutrient intake of U.S. infants and toddlers. It
included a stratified random sample of 3,022 children
between 4 and 24 months of age.
Using the 24-hour recall data, Fox et al. (2006)
derived average portion sizes for major food groups,
including fruits and vegetables. Average portion sizes
for select individual foods within these major groups
were also estimated. For this analysis, children were
grouped into six age categories: 4 to 5 months, 6 to
8 months, 9 to 11 months, 12 to 14 months, 15 to
18 months, and 19 to 24 months. Tables 9-33 and
9-34 present the average portion sizes for fruits and
vegetables for infants and toddlers, respectively.
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children.
Limitations are those associated with the FITS data,
as described previously in Section 9.3.2.7.
9.3.2.W.Menella et al (2006)—Feeding Infants
and Toddlers Study: The Types of Foods
Fed to Hispanic Infants and Toddlers
Menella et al. (2006) investigated the types of
food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic
infants and toddlers in the United States. The FITS
2002 data for children between 4 and 24 months of
age were used for the study. The data represent a
random sample of 371 Hispanic and
2,367 non-Hispanic infants and toddlers (Menella
etal., 2006). Menella et al. (2006) grouped the
infants as follows: 4 to 5 months (N= 84 Hispanic;
538 non-Hispanic), 6 to 11 months (N= 163
Hispanic; 1,228 non-Hispanic), and 12 to 24 months
(7V= 124 Hispanic; 871 non-Hispanic) of age.
Table 9-35 provides the percentages of Hispanic
and non-Hispanic infants and toddlers consuming
fruits and vegetables. In most instances, the
percentages consuming the different types of fruits
and vegetables were similar. However, 4-to-5-month-
old Hispanic infants were more likely to eat fruits
than non-Hispanic infants in this age group.
Table 9-36 provides the top five fruits and vegetables
consumed and the percentage of children consuming
these foods at least once in a day. Apples and bananas
were the foods with the highest percent consuming
for both the Hispanic and non-Hispanic study groups.
Potatoes and carrots were the vegetables with the
highest percentage of infants and toddlers consuming
in both study groups.
The advantage of the study is that it provides
information on food preferences for Hispanic and
non-Hispanic infants and toddlers. A limitation is that
the study did not provide food intake data, but
provided frequency-of-use data instead. Other
limitations are those noted previously in
Section 9.3.2.7 for the FITS data.
Exposure Factors Handbook
September 2011
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9-11
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
9.4. CONVERSION BETWEEN WET- AND
DRY-WEIGHT INTAKE RATES
The intake data presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
edible portion uncooked fruits and vegetables
consumed per day or per eating occasion). However,
data on the concentration of contaminants in fruits
and vegetables may be reported in units of either wet
or dry weight (e.g., mg contaminant per gram dry
weight of fruits and vegetables). It is essential that
exposure assessors be aware of this difference so that
they may ensure consistency between the units used
for intake rates and those used for concentration data
(i.e., if the contaminant concentration is measured in
dry weight of fruits and vegetables, then the
dry-weight units should be used for their intake
values).
If necessary, wet-weight (e.g., as-consumed)
intake rates may be converted to dry-weight intake
rates using the moisture content percentages
presented in Table 9-37 (USDA, 2007) and the
following equation:
X)-EFl
100 J
(Eqn. 9-1)
where:
dry-weight intake rate,
wet-weight intake rate, and
percent water content.
Alternatively, dry-weight residue levels in fruits and
vegetables may be converted to wet-weight residue
levels for use with wet-weight (e.g., as-consumed)
intake rates as follows:
C1 = C1
^~"ww ^di
100 -W
100
(Eqn. 9-2)
where:
w
wet-weight concentration,
dry-weight concentration, and
percent water content.
Table 9-37 presents moisture data for selected fruits
and vegetables taken from USDA (2007).
9.5.
REFERENCES FOR CHAPTER 9
Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T;
Clusen, N.; Ziegler, P. (2004) Feeding
infants and toddlers study: overview of the
study design. J Am Diet Assoc 104(Suppl
1):S8-S13.
Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004)
Feeding infants and toddlers study: what
foods are infants and toddlers eating? J Am
Diet Assoc 104(Suppl):S22-S30.
Fox, MK; Reidy, K; Karwe, V; Ziegler, P. (2006)
Average portions of foods commonly eaten
by infants and toddlers in the United States.
J Am Diet Assoc 106(Suppl 1):S66-S76.
Mennella, J; Ziegler, P; Briefel, R; Novak, T. (2006)
Feeding infants and toddlers study: the types
of foods fed to Hispanic infants and
toddlers. J Am Diet Assoc 106 (Suppl
1):S96-S106.
National Center for Health Statistics (NCHS) (1993).
Joint Policy on Variance Estimation and
Statistical Reporting Standards on NHANES
III and CSFII Reports: HNIS/NCHS
Analytic Working Group Recommendations.
Human Nutrition Information Service
(HNIS)/Analytic Working Group. Available
from: Agricultural Research Service, Survey
Systems/Food Consumption Laboratory,
4700 River Road, Unit 83, Riverdale, MD
20737.
Ponza, M; Devaney, B; Ziegler, P; Reidy, K.;
Squatrito, C. (2004) Nutrient intakes and
food choices of infants and toddlers
participating in WIC. J Am Diet Assoc
104(Suppl):S71-S79.
Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ;
Cook, A.J.; Goldman, J.D. (2002) Foods
commonly eaten in the United States:
Quantities consumed per eating occasion
and in a day, 1994-1996. U.S. Department
of Agriculture NFS Report No. 96-5,
pre-publication version, 252 pp.
USDA (Department of Agriculture). (1980) Food and
nutrient intakes of individuals in one day in
the United States, Spring 1977. Nationwide
Food Consumption Survey 1977-1978.
Preliminary Report No. 2. Human Nutrition
Information Service, Beltsville, MD.
USDA (Department of Agriculture). (1992) Food and
nutrient intakes by individuals in the United
States, 1 day, 1987-88. Human Nutrition
Information Service, Beltsville, MD.
Page
9-12
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
USDA (Department of Agriculture). (1996a) Data
tables: results from USDA's 1994 continuing
survey of food intakes by individuals and
1994 diet and health knowledge survey.
Agricultural Research Service, Riverdale,
MD.
USDA (Department of Agriculture). (1996b) Data
tables: results from USDA's 1995
Continuing survey of food intakes by
individuals and 1995 diet and health
knowledge survey. Agricultural Research
Service, Riverdale, MD.
USDA (Department of Agriculture). (1999a) Food
consumption prices and expenditures
(1970-1997). Statistical Bulletin, No. 965.
Economic Research Service, Washington,
DC. Available online at
http://www.ars.usda.gov/SP2UserFiles/Place
/12355000/pdf/scs_all.pdf/.
USDA (Department of Agriculture). (1999b) Food
and nutrient intakes by children 1994-96,
1998: Table Set 17. Food Surveys Research
Group, Beltsville Human Nutrition Research
Center, Agricultural Research Service,
Beltsville, MD.
USDA (Department of Agriculture). (2000) 1994-96,
1998 continuing survey of food intakes by
individuals (CSFII). CD-ROM. Agricultural
Research Service, Beltsville Human
Nutrition Research Center, Beltsville, MD.
Available from the National Technical
Information Service, Springfield, VA; PB-
2000-500027.
USDA (Department of Agriculture). (2007) USDA
national nutrient database for standard
reference, release 20. Available online at
http://www.ars.usda.gov/ba/bhnrc/ndl.
U.S. EPA (Environmental Protection Agency). (2000)
Food commodity intake database [FCID raw
data file]. Office of Pesticide Programs,
Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Washington, DC; EPA/630/P-03/003F.
Vitolins, M; Quandt, S; Bell, R.; Arcury, T.; Case,
L.D. (2002) Quality of diets consumed by
older rural adults. J Rural Health
18(l):49-56.
Exposure Factors Handbook Page
September 2011 9-13
-------
§
s
£5 5.
11
a
A,
Table 9-3. Per Capita Intake of Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day,
Population Group
N
Percent
Consuming
edible portion, uncooked weight)
Percentiles
Mean
SE 1st 5th
10th
25th
50th
75th
90th
95th 99th
Max
Fruits
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 1 3 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
16,783
865
1,052
978
2,256
3,450
4,289
4,103
3,893
4,450
4,265
6,757
562
749
85
61
97
97
93
80
81
85
89
87
82
85
87
89
1.6
6.2
7.8
4.6
2.3
0.9
0.9
1.0
1.4
2.3
1.2
1.5
2.1
2.0
0.05 0.0 0.0
0.46 0.0* 0.0*
0.42 0.0* 0.0*
0.25 0.0* 0.0
0.12 0.0* 0.0
0.04 0.0 0.0
0.04 0.0 0.0
0.05 0.0 0.0
0.05 0.0 0.0
0.11 0.0 0.0
0.06 0.0 0.0
0.05 0.0 0.0
0.20 0.0* 0.0
0.13 0.0* 0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.2
0.9
0.1
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.1
0.7
2.2
5.6
3.2
1.3
0.2
0.3
0.4
0.9
1.1
0.2
0.7
1.0
0.9
2.0
10.2
11.7
6.6
3.2
1.3
1.3
1.4
2.0
2.7
1.3
1.9
2.8
2.6
4.0
17.6
16.8
11.1
6.4
2.6
2.6
2.8
3.4
5.8
3.2
3.8
4.9
5.2
6.1 14.6
23.0* 35.9*
21.3* 39.3*
14.9 20.0*
8.7 13.8*
3.5 6.1
3.7 6.2
3.7 6.4
4.4 6.5
9.6 18.3
5.0 12.4
5.5 14.0
7.1 19.5*
8.6 15.3*
65.6*
56.5*
65.6*
32.1*
24.4*
16.7*
15.9*
16.7*
17.3*
39.2*
39.1*
65.6*
32.7*
42.1*
Vegetables
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
Female 1 3 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N = Sample size.
SE = Standard error.
Max = Maximum value.
* Estimates are less statistically
16,783
865
1,052
978
2,256
3,450
4,289
4,103
3,893
4,450
4,265
6,757
562
749
100
73
100
100
100
100
100
100
100
99
100
100
99
100
reliable based on guidance
2.9
5.0
6.7
5.4
3.7
2.3
2.5
2.5
2.6
3.2
2.4
2.9
3.1
3.4
publishec
0.04 0.0 0.4
0.28 0.0* 00*
0.26 0.0* 1.0*
0.25 0.1* 0.6
0.18 0.1* 0.5
0.05 0.0 0.3
0.06 0.1 0.4
0.08 0.1 0.4
0.05 0.0 0.4
0.06 0.0 0.5
0.05 0.0 0.2
0.05 0.0 0.4
0.16 0.0* 0.2
0.20 0.1* 0.4
0.7
0.0
1.6
1.5
0.9
0.5
0.7
0.6
0.7
0.8
0.5
0.7
0.7
0.7
1.3
0.0
3.0
2.3
1.5
1.1
1.3
1.2
1.3
1.5
0.9
1.4
1.2
1.5
2.3
3.3
5.7
4.2
2.8
1.8
2.2
2.0
2.2
2.5
1.7
2.3
2.2
2.7
3.7
8.7
8.9
7.2
4.8
3.0
3.3
3.3
3.4
4.1
3.0
3.7
3.8
4.2
5.7
12.9
13.3
10.6
7.6
4.3
4.9
4.7
4.9
6.4
4.7
5.6
6.3
6.8
7.5 13.2
16.2* 22.7*
15.6* 28.7*
13.4 21.4*
10.4 14.8*
5.5 8.9
5.9 8.6
5.9 8.9
6.1 9.1
8.6 13.5
6.5 11.5
7.2 12.8
9.4 16.3*
9.3 15.6*
36.1*
36.1*
32.8*
30.3*
23.1*
20.0*
18.3*
18.3*
22.6*
36.1*
30.3*
29.5*
26.2*
32.8*
in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III
and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
1993).
Source: U.S. EPA analysis of the 2003-2006 NHANES.
Q
I
a
I
(%
-a,
I
a
a,
I
-------
5
1=
Table 9-4. Consumer-Only Intake of Fruits and Vegetables Based on
the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
Percentiles
Population Group
N
Mean
SE 1st 5th
10th
25th
50*
75th
90th
95*
99th
Max
Fruits
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
\3to 19 years
20 to 49 years
Female 1 3 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including
Multiple
14,362
536
1,002
924
2,077
2,830
3,529
3,508
3,464
3,835
3,595
5,795
478
659
1.9
10.1
8.1
4.7
2.5
1.1
1.1
1.2
\.5
2.6
1.4
1.8
2.5
2.3
0.05 0.0 0.0
0.59 0.0* 0.3*
0.43 0.0* 0.1*
0.24 0.0* 0.0
0.12 0.0* 0.0
0.04 0.0 0.0
0.05 0.0 0.0
0.06 0.0 0.0
0.05 0.0 0.0
0.12 0.0 0.0
0.07 0.0 0.0
0.05 0.0 0.0
0.23 0.0* 0.0
0.16 0.0* 0.0
0.0
*0.8
0.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
3.6
2.6
1.1
0.2
0.0
0.1
0.1
0.4
0.4
0.0
0.2
0.3
0.2
1.0
8.1
6.2
3.5
1.6
0.7
0.6
0.7
1.1
1.4
0.6
1.0
\.5
1.1
2.3
14.7
11.8
6.7
3.4
1.6
1.6
1.7
2.2
3.0
1.7
2.2
3.0
2.8
4.4
21.2*
16.8
11.3
6.6
2.9
2.9
3.1
3.6
6.3
3.8
4.1
5.0
6.0
6.7
25.8*
21.4*
15.1
9.2
3.8
3.8
4.1
4.6
10.6
5.7
6.1
8.6
9.4
15.2
43.7*
39.3*
20.0*
14.5*
6.2
6.7
6.5
6.7
19.3
12.9
14.5
19.5*
15.3*
65.6*
56.5*
65.6*
32.1*
24.4*
16.7*
15.9*
16.7*
17.3*
39.2*
39.1*
65.6*
32.7*
42.1*
Vegetables
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 1 3 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including
Multiple
N = Sample size.
SE = Standard error.
Max = Maximum value.
16,531
623
1,048
977
2,256
3,447
4,288
4,102
3,892
4,341
4,228
6,683
544
735
2.9
6.8
6.7
5.4
3.7
2.3
2.5
2.5
2.6
3.3
2.4
2.9
3.1
3.4
0.04 0.0 0.4
0.33 0.0* 0.1*
0.26 0.0* 1.0*
0.25 0.1* 0.6
0.18 0.1* 0.5
0.05 0.0 0.3
0.06 0.1 0.4
0.08 0.1 0.4
0.05 0.0 0.4
0.06 0.1 0.5
0.05 0.0 0.3
0.05 0.1 0.4
0.16 0.1* 0.3
0.21 0.2* 0.4
0.7
0.4*
1.7
\.5
0.9
0.5
0.7
0.6
0.7
0.8
0.5
0.7
0.7
0.7
* Estimates are less statistically reliable based on guidance published in the Joint Policy on
Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
1993).
1.3
2.6
3.0
2.3
\.5
1.1
1.3
1.2
1.3
\.5
0.9
1.4
1.3
\.5
2.3
5.5
5.7
4.2
2.8
1.8
2.2
2.0
2.2
2.5
1.7
2.3
2.2
2.7
3.7
10.1
8.9
7.2
4.8
3.0
3.3
3.3
3.4
4.1
3.0
3.7
3.8
4.3
5.7
14.5*
13.3
10.6
7.6
4.3
4.9
4.7
4.9
6.4
4.7
5.6
6.4
6.9
Variance Estimation and Statistical Reporting
7.5
18.1*
15.6*
13.4
10.4
5.5
5.9
5.9
6.1
8.6
6.5
7.2
9.4
9.3
Standards on
13.2
22.7*
28.7*
21.4*
14.8*
8.9
8.6
8.9
9.1
13.5
11.5
12.8
16.3*
15.6*
36.1*
36.1*
32.8*
30.3*
23.1*
20.0*
18.3*
18.3*
22.6*
36.1*
30.3*
29.5*
26.2*
32.8*
NHANES III and CSFII
Source: U.S. EPAanalysis of the 2003-2006 NHANES.
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Apples
33 0.41 0.01
39 2.23 0.24
50 1.96 0.14
42 1.21 0.10
39 0.74 0.06
27 0.27 0.02
28 0.21 0.02
29 0.23 0.02
38 0.28 0.02
33 0.58 0.03
27 0.31 0.02
35 0.40 0.02
32 0.47 0.06
32 0.47 0.04
Percent
Consuming Mean SE
Asparagus
2 0.01 0.00
1 0.00 0.00
2 0.03 0.01
1 0.01 0.01
1 0.01 0.00
1 0.00 0.00
2 0.01 0.00
2 0.01 0.00
3 0.02 0.00
1 0.00 0.00
0 0.00 0.00
3 0.02 0.00
1 0.00 0.00
3 0.01 0.00
Percent
Consuming Mean SE
Bananas
55 0.37 0.01
46 1.83 0.19
77 2.35 0.26
73 1.00 0.09
68 0.42 0.04
50 0.15 0.01
48 0.20 0.01
50 0.20 0.01
58 0.33 0.02
56 0.56 0.04
55 0.25 0.02
54 0.36 0.02
55 0.53 0.06
58 0.43 0.04
Percent
Consuming Mean SE
Beans
45 0.24 0.01
30 0.54 0.06
49 0.69 0.06
43 0.61 0.07
37 0.30 0.03
31 0.13 0.01
46 0.19 0.01
45 0.17 0.01
51 0.22 0.01
59 0.32 0.01
43 0.25 0.01
43 0.22 0.01
58 0.25 0.03
50 0.30 0.04
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Beets
3 0.01 0.00
5 0.00 0.00
1 0.00 0.00
1 0.01 0.01
0 0.00 0.00
1 0.00 0.00
2 0.01 0.00
2 0.01 0.00
5 0.01 0.00
1 0.00 0.00
1 0.00 0.00
4 0.01 0.00
3 0.00 0.00
1 0.00 0.00
Percent
Consuming Mean SE
Berries and Small Fruit
67 0.30 0.01
19 0.24 0.09
83 1.46 0.14
84 0.97 0.11
80 0.46 0.04
64 0.19 0.01
62 0.17 0.01
67 0.20 0.01
71 0.28 0.02
59 0.23 0.02
64 0.18 0.01
69 0.33 0.02
59 0.30 0.05
66 0.38 0.06
Percent
Consuming Mean SE
Broccoli
15 0.10 0.01
6 0.07 0.02
16 0.30 0.06
12 0.19 0.04
11 0.10 0.02
9 0.05 0.01
16 0.09 0.01
17 0.09 0.01
16 0.09 0.01
12 0.07 0.01
12 0.07 0.01
15 0.10 0.01
16 0.13 0.04
19 0.13 0.03
Percent
Consuming Mean SE
Bulb Vegetables
97 0.18 0.00
39 0.07 0.01
94 0.28 0.02
96 0.28 0.02
98 0.21 0.02
98 0.15 0.01
98 0.19 0.01
97 0.16 0.01
97 0.16 0.00
96 0.27 0.01
96 0.13 0.01
97 0.17 0.00
93 0.23 0.01
97 0.25 0.02
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4, 103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Cabbage
13 0.05 0.00
1 0.01 0.01
7 0.05 0.02
5 0.04 0.01
7 0.04 0.01
6 0.02 0.00
13 0.05 0.01
12 0.05 0.01
18 0.08 0.00
10 0.03 0.00
12 0.06 0.01
13 0.05 0.00
9 0.03 0.01
17 0.12 0.02
Percent
Consuming Mean SE
Carrots
47 0.14 0.00
15 0.17 0.05
50 0.47 0.04
45 0.32 0.05
43 0.21 0.03
35 0.08 0.01
46 0.11 0.01
46 0.11 0.01
54 0.12 0.01
45 0.15 0.01
36 0.08 0.01
49 0.14 0.01
49 0.17 0.02
52 0.23 0.02
Percent
Consuming Mean SE
Citrus Fruits
20 0.16 0.01
2 0.05 0.02
25 0.65 0.08
18 0.46 0.06
15 0.21 0.02
13 0.08 0.01
20 0.11 0.01
21 0.11 0.01
25 0.14 0.01
27 0.37 0.03
16 0.17 0.03
20 0.12 0.01
23 0.26 0.03
21 0.20 0.05
Percent
Consuming Mean SE
Corn
96 0.43 0.01
56 0.62 0.10
97 1.13 0.05
100 1.26 0.07
99 0.88 0.03
96 0.37 0.01
96 0.32 0.01
96 0.31 0.01
96 0.27 0.01
96 0.78 0.03
96 0.46 0.02
97 0.37 0.01
94 0.45 0.05
91 0.41 0.03
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Cucumbers
40 0.09 0.00
3 0.02 0.01
24 0.14 0.02
26 0.19 0.03
30 0.11 0.01
34 0.06 0.01
45 0.09 0.01
44 0.10 0.01
43 0.08 0.01
30 0.07 0.01
37 0.06 0.01
43 0.10 0.01
33 0.09 0.02
38 0.11 0.03
Percent
Consuming Mean SE
Cucurbits
48 0.34 0.03
20 0.64 0.09
37 1.01 0.18
36 0.66 0.08
38 0.56 0.11
40 0.20 0.02
52 0.26 0.03
51 0.30 0.04
54 0.31 0.02
42 0.27 0.02
42 0.18 0.02
51 0.37 0.03
41 0.25 0.05
47 0.44 0.14
Percent
Consuming Mean SE
Fruiting Vegetables
95 0.80 0.02
31 0.30 0.05
93 1.45 0.07
95 1.53 0.08
97 1.05 0.05
96 0.75 0.03
97 0.76 0.02
96 0.70 0.03
95 0.66 0.03
96 1.13 0.03
94 0.62 0.03
96 0.78 0.02
92 0.97 0.06
92 0.75 0.04
Percent
Consuming Mean SE
Leafy Vegetables
92 0.54 0.01
40 0.22 0.04
82 0.71 0.07
87 0.61 0.06
90 0.43 0.02
89 0.35 0.01
94 0.55 0.02
93 0.58 0.03
93 0.60 0.02
90 0.40 0.02
90 0.46 0.02
92 0.56 0.02
90 0.48 0.05
91 0.69 0.07
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Legumes
96 0.45 0.01
58 1.58 0.15
97 1.65 0.24
98 1.07 0.17
97 0.48 0.04
95 0.23 0.01
96 0.34 0.02
95 0.32 0.02
98 0.41 0.02
95 0.46 0.03
96 0.39 0.02
97 0.42 0.02
96 0.63 0.17
95 0.76 0.10
Percent
Consuming Mean SE
Lettuce
53 0.23 0.01
1 0.01 0.00
21 0.15 0.02
29 0.23 0.03
37 0.17 0.01
53 0.20 0.01
62 0.26 0.01
60 0.28 0.01
56 0.24 0.01
52 0.20 0.01
45 0.15 0.01
55 0.25 0.01
50 0.19 0.03
51 0.22 0.03
Percent
Consuming Mean SE
Onions
96 0.18 0.00
38 0.07 0.01
94 0.27 0.02
95 0.26 0.02
98 0.20 0.02
97 0.15 0.01
97 0.18 0.01
96 0.16 0.01
97 0.16 0.00
96 0.26 0.01
95 0.13 0.01
97 0.17 0.00
93 0.22 0.01
96 0.24 0.02
Percent
Consuming Mean SE
Peaches
49 0.11 0.01
27 0.77 0.09
70 0.55 0.08
68 0.31 0.05
67 0.13 0.02
45 0.05 0.01
43 0.04 0.01
46 0.05 0.01
51 0.10 0.01
44 0.12 0.02
52 0.09 0.01
50 0.11 0.01
38 0.09 0.03
46 0.09 0.02
Q
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Pears
10 0.09 0.01
19 0.70 0.10
25 0.44 0.07
25 0.32 0.06
17 0.13 0.02
8 0.03 0.00
6 0.04 0.01
8 0.04 0.01
9 0.07 0.01
10 0.13 0.02
9 0.05 0.01
10 0.08 0.01
8 0.07 0.02
11 0.16 0.05
Percent
Consuming Mean SE
Peas
19 0.07 0.00
36 0.66 0.07
27 0.29 0.04
17 0.17 0.02
13 0.06 0.01
13 0.04 0.01
18 0.05 0.00
18 0.05 0.00
23 0.07 0.00
15 0.05 0.01
20 0.08 0.01
19 0.07 0.00
19 0.07 0.02
27 0.13 0.02
Percent
Consuming Mean SE
Pome Fruit
38 0.50 0.02
45 2.94 0.29
61 2.40 0.15
54 1.53 0.11
48 0.87 0.06
31 0.30 0.02
31 0.25 0.02
32 0.28 0.02
42 0.35 0.02
39 0.71 0.04
31 0.36 0.02
39 0.48 0.02
35 0.54 0.08
36 0.63 0.06
Percent
Consuming Mean SE
Pumpkins
2 0.00 0.00
0 0.00 0.00
0 0.01 0.01
0 0.00 0.00
1 0.01 0.00
1 0.00 0.00
2 0.00 0.00
2 0.00 0.00
3 0.00 0.00
5 0.01 0.00
0 0.00 0.00
2 0.00 0.00
4 0.01 0.01
2 0.00 0.00
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 1 3 to 49 years 4, 1 03
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Root Tuber Vegetables
99 1.15 0.02
69 2.66 0.19
100 3.15 0.13
100 2.60 0.16
100 1.79 0.07
100 0.99 0.04
100 0.89 0.03
100 0.87 0.02
100 0.91 0.03
99 1.17 0.04
99 1.09 0.03
100 1.14 0.03
98 1.24 0.09
99 1.35 0.08
Percent
Consuming Mean SE
Stalk/Stem Vegetables
19 0.05 0.00
3 0.01 0.00
13 0.07 0.02
10 0.05 0.02
11 0.03 0.00
12 0.02 0.00
24 0.05 0.00
21 0.04 0.00
21 0.05 0.01
12 0.02 0.00
12 0.02 0.00
21 0.06 0.00
15 0.03 0.01
27 0.06 0.01
Percent
Consuming Mean SE
Stone Fruit
52 0.16 0.01
32 0.94 0.11
72 0.67 0.08
72 0.41 0.06
68 0.21 0.03
47 0.08 0.01
46 0.08 0.01
49 0.09 0.01
55 0.17 0.02
47 0.18 0.03
54 0.13 0.01
54 0.17 0.01
41 0.13 0.03
49 0.13 0.03
Percent
Consuming Mean SE
Strawberries
41 0.10 0.01
10 0.06 0.03
52 0.36 0.06
53 0.27 0.05
50 0.14 0.03
35 0.07 0.01
36 0.06 0.01
39 0.07 0.01
45 0.10 0.01
34 0.07 0.01
29 0.04 0.01
44 0.11 0.01
33 0.09 0.02
36 0.10 0.02
Q
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003-2006 (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group TV
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 978
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Female 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 562
Other Race — Including Multiple 749
Percent
Consuming Mean SE
Tomatoes
87 0.72 0.02
26 0.29 0.04
83 1.40 0.07
85 1.46 0.08
91 0.99 0.04
89 0.69 0.03
89 0.66 0.02
88 0.62 0.02
84 0.59 0.03
91 0.99 0.03
84 0.57 0.02
87 0.71 0.02
86 0.90 0.05
82 0.66 0.03
Percent
Consuming Mean SE
Tropical Fruits
66 0.46 0.02
48 1.97 0.20
83 2.65 0.28
81 1.19 0.09
75 0.52 0.04
59 0.22 0.02
61 0.27 0.02
64 0.28 0.02
68 0.40 0.02
70 0.73 0.05
64 0.32 0.03
65 0.42 0.02
71 0.86 0.09
68 0.59 0.04
Percent
Consuming Mean SE
White Potatoes
91 0.65 0.02
46 0.52 0.08
94 1.74 0.10
94 1.38 0.15
93 0.96 0.07
92 0.61 0.03
91 0.54 0.02
90 0.50 0.02
93 0.54 0.03
87 0.65 0.03
91 0.64 0.03
93 0.65 0.03
86 0.66 0.08
87 0.69 0.06
Percent
Consuming Mean SE
JV = Sample size.
SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables with higher
percentages consuming.
Source: U.S. EPA analysis of the 2003-2006 NHANES.
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
23(FloS49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
5,743 1.23 0.03
5.79 0.38
318
508 3'95 °'23
432 2.91 0.21
837 L88 °'12
93g 1.00 0.05
1,233 0.75 0.04
1,195 0.81 0.05
1,477 0.75 0.03
1,601 1.72 0.09
1,228 1.16 0.05
2,458 1.15 0.04
1.45 0.19
202
254 1.45 0.13
N Mean SE
Asparagus
2Q4 0.63 0.05
1 0.21
8 1.61 0.15
5 0.77 0.31
15 0.60 0.15
13 0.26 0.06
61 0.50 0.07
41 0.42 0.07
.„. 0.73 0.06
101
18 0.44 0.08
14 0.57 0.13
154 0.67 0.05
3 0.61 0.25
15 0.38 0.11
N Mean SE
Bananas
9,644 0.68 0.02
3.97 0.31
396
?95 3.04 0.34
716 °7 °'12
1,553 0.61 0.05
1,817 0.31 0.02
2,142 0.41 0.03
2,215 0.39 0.03
2,225 0.58 0.02
2,490 1.00 0.05
2,533 0.46 0.04
3,863 0.66 0.03
322 0.98 0.08
436 °'74 °-07
N Mean SE
Beans
7,635 0.53 0.01
235 1.80 0.20
530 1.41 0.10
461 1.42 0.13
936 0.79 0.05
1,264 0.41 0.02
2,141 0.41 0.01
1,845 0.39 0.01
2,068 0.43 0.01
2,482 0.54 0.02
1,722 0.58 0.03
2,809 0.52 0.02
291 0.44 0.05
331 0.61 0.06
N Mean SE
Beets
353 0.29 0.04
30 0.01 0.00
12 0.00 0.00
11 0.97 0.63
8 0.78 0.33
20 0.10 0.03
81 0.30 0.09
58 0.39 0.13
1Q1 0.28 0.05
191
55 0.07 0.04
42 0.21 0.04
235 0.31 0.05
12 0.12 0.04
9 0.11 0.07
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Berries and Small Fruit
10,981 0.45 0.02
1.26 0.42
166
839 L76 °'15
788 L15 °'12
1,751 0.57 0.05
2,210 0.30 0.02
2,601 0.27 0.01
2,705 0.31 0.02
2,626 0.40 0.02
2,563 0.38 0.02
2,899 0.28 0.02
4,686 0.47 0.02
0.51 0.08
333
500 °'58 °-10
N Mean SE
Broccoli
2,047 0.65 0.03
45 1.14 0.19
132 1.84 0.27
108 L5° °'25
228 °'96 °'12
289 °'53 °-04
664 0.53 0.03
560 °'54 °-04
581 °'56 °-02
456 0.61 0.07
.„. 0.61 0.04
474
925 0.65 0.04
82 0.85 0.22
uo 0.66 0.09
N Mean SE
Bulb Vegetables
15,773 0.19 0.00
346 °'19 °-03
1,003 0.30 0.02
94? 0.29 0.02
2,216 0.21 0.02
3,354 0.16 0.01
4,194 0.19 0.01
3,994 0.17 0.01
3,713 0.17 0.00
4,132 0.28 0.01
4,022 0.14 0.01
6,410 0.18 0.00
514 0.25 0.01
695 0.25 0.02
JV Mean SE
Cabbage
1,833 0.43 0.02
13 0.96 0.44
?2 0.73 0.26
6? 0.71 0.15
164 0.56 0.16
218 0.31 0.04
577 0.41 0.03
461 0.41 0.05
722 0.43 0.02
390 0.32 0.04
442 0.51 0.04
852 0.41 0.02
,„ 0.32 0.04
4o
101 0.70 0.08
N Mean SE
Carrots
7,231 0.30 0.01
,,, 1.13 0.23
166
525 0.93 0.08
449 0.71 0.09
912 0.49 0.05
1,152 0.24 0.02
1,948 0.24 0.01
1,755 0.24 0.01
2,079 0.23 0.01
1,912 0.33 0.02
1,471 0.22 0.01
3,220 0.29 0.01
2?2 0.34 0.05
356 °'44 °-04
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Citrus Fruits
3,398 0.77 0.04
3Q 2.90 0.96
256 2'61 °-30
191 2.50 0.29
440 1-39 0.09
M9 0.66 0.04
896 °'55 °-05
860 °'53 °-04
1,036 0.57 0.04
1,148 1.40 0.06
1.04 0.14
669
1,323 0.59 0.04
1.10 0.14
127
131 0.96 0.24
N Mean SE
Corn
15,899 0.44 0.01
465 L12 °'14
1,028 1.16 0.06
9?1 1.26 0.07
2,237 0.88 0.04
3,332 0.38 0.01
4,134 0.33 0.01
3,967 0.32 0.01
3,732 0.28 0.01
4,185 0.81 0.03
4,058 0.48 0.02
6,454 0.39 0.01
516 0.48 0.05
686 °'45 °-03
N Mean SE
Cucumbers
5,728 0.23 0.01
25 0.70 0.31
210 °'58 °-09
24? 0.74 0.12
666 °'37 °-03
1,191 0.18 0.01
1,827 0.20 0.01
1,596 0.24 0.01
1,562 0.19 0.01
1,218 0.25 0.02
1,471 0.17 0.01
2,627 0.23 0.01
166 °'26 °-05
246 °-29 °-06
JV Mean SE
Cucurbits
7,109 0.70 0.05
138 3.16 0.16
332 2.75 0.42
335 1.86 0.25
828 1.47 0.22
1,347 0.50 0.06
2,138 0.50 0.06
1,874 0.59 0.08
1,991 0.57 0.03
1,733 0.65 0.05
1,647 0.44 0.04
3,211 0.73 0.06
212 0.60 0.10
306 0.94 0.29
N Mean SE
Fruiting Vegetables
15,483 0.84 0.02
281 °'98 °-12
987 L56 °-07
926 L61 °-09
2,192 1.08 0.05
3,304 0.78 0.03
4,155 0.78 0.02
3,945 0.73 0.03
3,638 0.69 0.03
4,079 1.18 0.03
3,943 0.66 0.03
6,293 0.82 0.02
49g 1.05 0.06
,_„ 0.81 0.04
6 /O
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Leafy Vegetables
14,824 0.59 0.01
0.55 0.09
351
on, 0.86 0.08
oyo
„,. 0.70 0.06
oul
2,035 0.48 0.02
3,106 0.39 0.01
4,008 0.59 0.02
3,789 0.62 0.03
3,567 0.65 0.02
3;847 0.44 0.02
3,786 0.51 0.03
6,046 0.61 0.02
0.53 0.06
475
,_„ 0.76 0.07
6 /O
N Mean SE
Legumes
15,808 0.46 0.01
459 2.74 0.21
1,011 1.70 0.25
95? 1.09 0.17
2,198 0.49 0.04
3,256 0.24 0.01
4,135 0.35 0.02
3,915 0.34 0.02
3,792 0.42 0.02
4,089 0.49 0.03
4,044 0.41 0.02
6,454 0.44 0.02
51? 0.66 0.18
704 °'79 °-10
N Mean SE
Lettuce
7;946 0.44 0.01
17 0.34 0.16
216 °-70 °-09
29? 0.78 0.11
931 0.45 0.02
1,882 0.38 0.02
2,576 0.43 0.02
2,379 0.47 0.02
2,027 0.43 0.01
2,120 0.38 0.02
1,803 0.34 0.02
3,438 0.46 0.01
248 °39 °-05
33? 0.43 0.04
JV Mean SE
Onions
15,695 0.18 0.00
342 0.19 0.02
998 0.28 0.02
941 0.28 0.02
2,209 0.20 0.02
3,333 0.15 0.01
4,177 0.19 0.01
3,969 0.16 0.01
3,695 0.16 0.00
4,115 0.27 0.01
4,004 0.14 0.01
6,369 0.17 0.00
514 0.24 0.01
693 °-25 °-02
JV Mean SE
Peaches
8,542 0.22 0.01
215 2.80 0.31
700 °'79 °-10
676 °-45 °-07
1,517 0.20 0.03
1,675 0.11 0.02
1,845 0.10 0.01
1,996 0.11 0.01
1,914 0.21 0.02
1,951 0.28 0.04
2,432 0.18 0.02
3,530 0.22 0.01
25Q 0.25 0.08
3?9 0.19 0.04
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Pears
1,965 0.89 0.04
3.77 0.38
144
243 L79 °'21
221 L31 °'20
403 °'77 °'12
2?2 0.35 0.04
„„ 0.63 0.05
Z /O
323 0.56 0.07
0.72 0.06
404
1.25 0.14
518
0.61 0.07
489
0.84 0.05
807
54 0.90 0.12
97 1.51 0.32
N Mean SE
Peas
3,133 0.39 0.02
236 L83 °-U
25? 1.05 0.11
180 °'97 °'13
3Q9 0.51 0.06
416 °'34 °-04
-,„„ 0.26 0.02
/oU
675 °-27 °-02
955 0.29 0.01
644 0.37 0.04
812 °-42 °-04
1,364 0.38 0.02
U6 0.39 0.08
19? 0.49 0.07
N Mean SE
Pome Fruit
6,699 1.31 0.03
3?1 6.50 0.42
621 3'92 °-23
53? 2.82 0.18
1,071 1.82 0.10
1,085 0.98 0.05
1,362 0.81 0.04
1,352 0.87 0.05
1,652 0.84 0.04
1,851 1.81 0.09
1,512 1.15 0.05
2,821 1.23 0.03
223 1.55 0.21
292 1.78 0.16
JV Mean SE
Pumpkins
285 °-22 °-02
3 0.73 0.39
4 2.13 0.41
8 0.80 0.21
35 0.55 0.16
40 0.19 0.06
95 0.20 0.04
87 0.22 0.04
100 °'17 °-02
160 °-28 °-06
10 0.71 0.33
91 0.17 0.02
11 0.28 0.12
13 0.23 0.14
N Mean SE
Root Tuber Vegetables
16,478 1.16 0.02
583 3'88 °-24
1,050 3.15 0.13
9?8 2.60 0.16
2,256 1.79 0.07
3,447 0.99 0.04
4,278 0.90 0.03
4,097 0.87 0.02
3,886 0.92 0.03
4,316 1.18 0.04
4,218 1.10 0.03
6,667 1.15 0.03
544 !-26 °-09
733 1.36 0.08
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Stalk/Stem Vegetables
2,409 0.24 0.01
15 0.26 0.07
101 °'58 °-10
81 0.50 0.10
212 0.24 0.04
387 °'15 °-01
941 0.22 0.01
?19 0.20 0.01
0.26 0.03
672
0.18 0.02
411
0.15 0.01
409
1,336 0.26 0.02
?1 0.17 0.03
182 °'22 °-02
N Mean SE
Stone Fruit
8,966 0.30 0.02
235 2.98 0.33
721 0.92 0.10
691 0.56 0.08
1,545 0.31 0.04
1,719 0.16 0.02
1,961 0.17 0.02
2,101 0.18 0.02
2,094 0.30 0.03
2,043 0.38 0.05
2,497 0.24 0.02
3,753 0.31 0.02
270 0.31 0.08
403 0.27 0.04
N Mean SE
Strawberries
6,168 0.24 0.02
88 0.60 0.28
480 °-70 °'12
46o °-51 °-09
1,019 0.28 0.06
1,076 0.20 0.03
1,466 0.17 0.02
1,492 0.19 0.03
1,579 0.23 0.03
1,438 0.22 0.02
1,276 0.15 0.02
2,979 0.25 0.03
198 0.29 0.06
2?7 0.27 0.05
JV Mean SE
Tomatoes
14,240 0.83 0.02
246 L11 °'12
895 1.68 0.09
840 L72 °-09
2,071 1.09 0.05
3,093 0.77 0.03
3,894 0.74 0.02
3,679 0.71 0.02
3,201 0.70 0.03
3,897 1.09 0.03
3,547 0.68 0.02
5,714 0.82 0.02
47Q 1.05 0.06
,., 0.81 0.04
612
N Mean SE
Tropical Fruits
11,299 0.70 0.02
423 4.12 0.30
862 3'19 °33
800 L47 °-n
1,733 0.69 0.05
2,151 0.37 0.03
2,692 0.44 0.02
2,720 0.44 0.03
2,638 0.58 0.02
3,031 1.03 0.07
2,865 0.51 0.05
4,498 0.64 0.02
399 1.21 0.12
-„, 0.86 0.06
j06
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Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Female 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
White Potatoes
14,944 0.72 0.02
1.14 0.15
389
982 1.86 0.10
915 1.46 0.15
2,111 1.03 0.07
3,163 0.67 0.03
3,861 0.59 0.02
3,691 0.56 0.02
3,523 0.58 0.03
3,773 0.75 0.03
3,881 0.70 0.03
6,180 0.71 0.03
0.77 0.08
466
644 0.79 0.06
N Mean SE
N Mean SE
N Mean SE
JV Mean SE
N = Sample size.
SE = Standard error.
Source: U.S. EPAanalysis of the 2003-2006 NHANES.
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-7. Mean Total
Fruit and Total Vegetable
Intake (as-consumed) in a Day by
Sex and Age
(1977-1978)3
Age
(years)
Per Capita Intake
(g/day)
Percent of Population Consumer-Only Intake
Consuming in a Day
(g/day)b
Fruits
Male and Female
<1
Ito2
3 to 5
6 to 8
Male
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Female
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Male and Female
All ages
169
146
134
152
133
120
147
107
141
115
171
174
186
148
120
126
133
122
133
171
179
189
142
86.8
62.9
56.1
60.1
50.5
51.2
47.0
39.4
46.4
44.0
62.4
62.2
62.6
59.7
48.7
49.9
48.0
47.7
52.8
66.7
69.3
64.7
54.2
196
231
239
253
263
236
313
271
305
262
275
281
197
247
247
251
278
255
252
256
259
292
263
Vegetables
Male and Female
<1
Ito2
3 to 5
6 to 8
Male
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Female
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Male and Female
All ages
76
91
100
136
138
184
216
226
248
261
285
265
264
139
154
178
184
187
187
229
221
198
201
62.7
78.0
79.3
84.3
83.5
84.5
85.9
84.7
88.5
86.8
90.3
88.5
93.6
83.7
84.6
83.8
81.1
84.7
84.6
89.8
87.2
88.1
85.6
121
116
126
161
165
217
251
267
280
300
316
300
281
166
183
212
227
221
221
255
253
226
235
a Based on USDA Nationwide Food Consumption Survey (1977-1978) data for one day.
b Intake for users only was calculated by dividing the per capita
in a day.
Source: USDA, 1980.
intake rate by the fraction of the population
consuming fruit
Exposure Factors Handbook
September 2011
Page
9-31
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-8. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
(1987-1988, 1994, and 1995)a
Age
(years)
Male and Female
5 and under
Male
6 to 11
12 to 19
>20
Female
6 to 11
12 to 19
>20
Male and Female
All Ages
Male and Female
5 and under
Male
6 to 11
12 to 19
>20
Female
6 to 11
12 to 19
>20
Male and Female
All Ages
Per Capita Intake
(g/day)
1987-1988 1994 1995
Percent of Population
Consuming in 1 Day
1987-1988 1994 1995
Consumer-Only Intake (g/day)
1987-1988 1994 1995
Fruits
157 230 221
182 176 219
158 169 210
133 175 170
154 174 172
131 148 167
140 157 155
142 171 173
59.2 70.6 72.6
63.8 59.8 62.2
49.4 44.0 47.1
46.5 50.2 49.6
58.3 59.3 63.6
47.1 47.1 44.4
52.7 55.1 54.4
51.4 54.1 54.2
265 326 304
285 294 352
320 384 446
286 349 342
264 293 270
278 314 376
266 285 285
276 316 319
Vegetables
81 80 83
129 118 111
173 154 202
232 242 241
129 115 108
129 132 144
183 190 189
182 186 188
74.0 75.2 75.0
86.8 82.4 80.6
85.2 74.9 79.0
85.0 85.9 86.4
80.6 82.9 79.1
75.8 78.5 76.0
82.9 84.7 83.2
82.6 83.2 82.6
109 106 111
149 143 138
203 206 256
273 282 278
160 139 137
170 168 189
221 224 227
220 223 228
Based on USDANFCS (1987-1988) and CSFII (1994 and 1995) data for one day.
b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population consuming
fruits in a day.
Source: USDA, 1996a, b.
Page
9-32
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-9. Per Capita Consumption of Fresh Fruits and Vegetables in 1997"
Fresh Fruits
Fresh Vegetables
Food Item
Per Capita
Consumption
(g/day)b
Food Item
Per Capita
Consumption
(g/day)b
Citrus
Oranges (includes Temple oranges) 16.9
Tangerines and Tangelos 3.0
Lemons 3.4
Limes 1.4
Grapefruit 7.6
Total Fresh Citrus 32.2
Non-citrus
Apples 22.0
Apricots 0.1
Avocados 1.6
Bananas 34.5
Cherries 0.6
Cranberries 0.1
Grapes 9.1
Kiwi Fruit 0.5
Mangoes 1.7
Peaches and Nectarines 6.7
Pears 4.1
Pineapple 2.9
Papayas 0.6
Plums and Prunes 1.9
Strawberries 4.9
Melons 34.5
Total Fresh Non-citrus 125.6
Total Fresh Fruits 157.8
Artichokes
Asparagus
Bell Peppers
Broccoli
Brussel Sprouts
Cabbage
Carrots
Cauliflower
Celery
Sweet Com
Cucumber
Eggplant
Escarole/Endive
Garlic
Head Lettuce
Romaine Lettuce
Onions
Radishes
Snap Beans
Spinach
Tomatoes
Total Fresh Vegetables
0.6
0.7
8.3
6.0
0.4
11.8
15.1
1.9
7.0
9.2
7.2
0.5
0.2
2.1
28.1
7.0
20.9
0.5
1.6
0.6
20.0
149.8
Based on retail-weight equivalent. Includes imports; excludes exports and foods grown in home gardens. Data for
1997 were used.
Original data were presented in Ibs/year; data were converted to g/day by multiplying by a factor of 454 g/lb and
dividing by 365 day/year.
Source: USDA, 1999a.
Exposure Factors Handbook
September 2011
Page
9-33
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s,
Table 9-10. Mean Quantities of Vegetables Consumed
Daily by Sex and Age, for Children, Per Capita
(g/day,
White Potatoes
Age Group
(years) Sample Size Total
Total
Dark Green
Fried Vegetables
Deep Yellow
Vegetables
Tomatoes
Lettuce, Lettuce-
based Salads
Green
Beans
as-consumed)a
Corn, Green
Peas, Lima
Beans
Other
Vegetables
Male and Female
Under 1
1
1
3to2
4
5
3 to 5
<5
1,126 57
1,016 79
1,102 87
2,118 83
1,831 91
1,859 97
884 103
4,574 97
7,818 88
9
26
32
29
34
37
44
38
31
1 2
11 5
17 4
14 5
17 5
19 6
22 4
20 5
16 4
19
9
5
7
5
5
6
5
7
lb
7
11
9
13
11
12
12
10
b,c
1
2
1
2
3
3
3
2
6
8
7
7
5
5
6
5
6
5
9
10
9
11
12
12
11
10
16
16
17
17
16
18
17
17
17
Male
6 to 9
6 to 11
12 to 19
787 110
1,031 115
737 176
47
50
85
26 4
27 5
44 6
5
5
6
16
16
28
5
5
12
5
5
3b
11
11
10
16
18
Female
6 to 9
6 to 11
12 to 19
<9
<19
704 110
969 116
732 145
9,309 97
11,287 125
42
46
61
37
53
22 5
25 5
31 9
19 4
27 6
4
4
4
Male and Female
6
6
14
15
18
12
17
6
7
12
3
7
5
5
4
6
5
13
12
8
25
11
10
21
22
28
18
22
Based on data from 1994-1996. 1998 CSFII.
b Estimate is not statistically reliable due to small samples size reporting intake.
c
Note:
Source:
Value less than 0.5, but greater than 0.
Consumption amounts shown are representative of the first day of each participant's survey response.
USDA, 1999b.
f
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:
3
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N
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-------
Table 9-11. Percentage of Individuals Consuming Vegetables, by Sex and Age, for Children (%)a
Age Group . .
, . Sample Size
(years)
White Potatoes
Total
Total
Fried
Dark Green Deep Yellow
Vegetables Vegetables
Tomatoes
Lettuce, Lettuce-
based Salads
Green
Beans
Corn, Green
Peas, Lima
Beans
Other
Vegetables
Male and Female
Under 1
1
2
Ito2
3
4
5
3 to 5
<5
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
47.2
73.3
78.4
75.9
80.5
80.7
83.0
81.4
75.4
12.3
40.4
46.7
43.6
46.7
47.3
50.7
48.2
42.3
4.3
25.2
34.5
29.9
34.7
34.8
38.3
35.9
30.1
2.3
6.4
7.6
7.0
7.0
7.2
4.6
6.3
6.1
20.5
13.3
10.5
11.8
10.7
12.0
13.3
12.0
13.0
1.8
18.0
30.8
24.6
34.1
33.0
36.5
34.5
27.2
0.2b
3.9
7.5
5.7
8.3
10.0
13.4
10.6
7.6
7.8
13.7
11.5
12.6
10.1
9.0
10.4
9.9
10.5
8.5
17.6
15.0
16.2
14.6
16.4
16.1
15.7
15.0
14.8
19.4
22.3
20.9
24.7
26.5
28.8
26.7
23.3
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
78.8
79.3
78.2
47.9
48.7
49.5
38.0
38.4
38.6
6.3
6.1
3.6
12.5
12.4
8.0
38.2
38.7
43.0
13.1
13.9
23.8
7.8
6.7
3.5
15.0
13.8
7.4
29.7
30.8
33.2
Female
6 to 9
6 to 11
12 to 19
704
969
732
80.5
81.7
79.5
48.2
50.8
46.4
36.3
38.9
34.6
5.9
5.4
7.0
11.9
11.4
10.6
33.8
33.5
35.3
15.8
17.1
25.1
8.4
7.8
4.4
15.9
15.1
7.4
26.6
29.2
34.5
Male and Female
<9
b
Note:
Source:
9,309
11,287
77.1
78.3
44.6
46.8
32.9
35.3
6.1
5.6
12.7
11.2
30.7
34.6
10.3
16.6
9.6
7.0
15.2
11.9
25.2
29.4
Based on data from 1994-1996, 1998 CSFII.
Estimate is not statistically reliable due to small samples size reporting intake.
Consumption amounts shown are representative of the first day of each participant's survey response.
USDA, 1999b.
Q
•*•
a-
QTQ
I
I
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a
3
S
ri
!
I
I
-------
QTQ
a
A,
Table 9-12. Mean Quantities of Fruits Consumed
Daily by Sex
and Age, for Children, Per Capita (g/day, as-consumed)3
Citrus Fruits and Juices
Age Group
(years) SamPle Size
Total
Total
Juices
Dried
fruits Total
Apples
Other Fruits, Mixtures, and Juices
Bananas
Melons and
Other fruits
and mixtures
(mainly fruit)
Non-Citrus
juices and
nectars
Male and Female
Under 1
1
2
Ito2
3
4
5
3 to 5
<5
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
131
267
276
271
256
243
218
239
237
4
47
65
56
61
62
55
59
52
4
42
56
49
51
52
44
49
44
b,c
2
2
2
1
1
b,c
1
1
126
216
207
212
191
177
160
176
182
14
22
27
24
27
31
31
30
26
10
23
20
22
18
17
14
16
17
lb
8
10
9
13
14
13
13
10
39
29
20
24
24
22
24
23
26
61
134
130
132
110
92
78
93
103
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
194
183
174
58
67
102
51
60
94
b,c
b,c
1"
133
113
70
32
28
13
11
11
8
21
16
llb
20
19
10
50
40
29
Female
6 to 9
6 to 11
12 to 19
704
969
732
180
169
157
63
64
72
54
54
67
lb
_b,c
_b,c
113
103
83
23
21
13
10
8
5
10
8
15
25
23
14
46
42
35
Male and Female
<9
<19
a
b
c
9,309
11,287
217
191
55
70
47
62
1
1
159
118
27
21
15
11
12
12
24
19
81
56
Based on data from 1994-1996, 1998 CSFII.
Estimate is not statistically
reliable due to small samples size reporting intake.
Value less than 0.5, but greater than 0.
Indicates value as not statistically significant or less than 0.5, but
Note:
Source:
greater than 0.
Consumption amounts shown are representative of the first day of each participant
USDA, 1999b.
's survey response.
Q
I
a
I
ft
-a,
I
a
a,
I
-------
Table 9-13. Percentage of Individuals
Consuming, Fruits by Sex and Age, for Children (%)a
Citrus Fruits and Juices
Age Group
(years)
Sample Size
Total
Total
Juices
FJried
fruits
Total
Other Fruits, Mixtures, and Juices
Apples
Bananas
Melons and
Other fruits
and mixtures
(mainly fruit)
Non-Citrus
juices and
nectars
Male and Female
Under 1
1
2
Ito2
3
4
5
3 to 5
<5
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
59.7
81.0
76.6
78.8
74.5
72.6
67.6
71.6
72.6
3.6
23.6
30.6
27.2
27.9
28.0
26.9
27.6
24.6
2.7
19.0
23.4
21.3
21.4
21.8
19.5
20.9
18.8
0.4b
5.9
53
5.6
4.1
3.0
1.3"
2.8
3.5
59.0
73.0
64.7
68.8
64.2
62.1
56.9
61.0
63.5
15.7
23.4
24.0
23.7
22.4
23.7
21.9
22.7
22.2
13.3
25.1
20.2
22.6
17.5
15.7
12.6
15.3
17.6
1.8
6.9
8.5
7.7
7.8
7.6
7.4
7.6
6.9
29.9
26.5
19.4
22.9
20.1
20.0
19.0
19.7
22.0
33.0
43.2
37.0
40.0
33.3
30.8
24.5
29.5
33.5
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
59.0
56.5
44.5
24.8
25.2
24.7
20.5
21.6
21.7
0.8b
1.1"
1 Ob
49.1
44.2
27.1
20.3
18.2
8.2
8.7
8.0
6.0
7.3
6.6
4.1
16.8
15.4
7.1
15.5
12.7
8.2
Female
6 to 9
6 to 11
12 to 19
704
969
732
64.9
62.1
45.6
27.9
27.7
22.4
22.3
21.5
18.1
1.5b
1.1"
1 lb
50.4
47.2
30.2
17.3
16.2
8.2
8.8
7.3
4.4
7.4
7.4
6.0
20.4
19.0
11.3
17.3
14.9
9.7
Male and Female
<9
<19
a Based on data
9,309
11,287
68.3
57.8
25.2
24.8
19.8
20.1
2.5
1.8
58.0
44.4
20.9
15.2
14.0
9.7
7.1
6.2
20.6
15.5
26.7
17.9
from 1994-1996, 1998 CSFII.
b Estimate is not statistically
reliable due to small sample size reporting intake.
Note: Percentages shown are representative of the first day of each participant
Source: USDA, 1999b
's survey response.
Q
•*•
a-
QTQ
I
X)
-------
oo
QTQ
§
s
a
A,
Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFH (g/kg-day, edible portion, uncooked weight)
Population Group
N
Percent
Consuming
Mean
SE
Percentiles
1st
th
10th
25th
50th
75th
90th
95th
99th
Max
Fruits e
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan
Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
557
177
2,740
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
80.0
56.4
89.5
90.0
88.3
73.2
75.3
85.8
79.6
80.2
78.3
81.7
78.8
77.8
71.3
78.5
81.5
82.3
83.4
74.7
82.7
79.0
82.5
75.9
1.6
5.7
6.2
4.6
2.4
0.8
0.9
1.4
1.5
1.6
1.5
1.7
2.1
1.9
1.2
2.2
1.6
1.6
1.7
1.3
2.0
1.6
1.7
1.3
0.0
0.3
0.2
0.1
0.1
0.1
0.0
0.0
0.1
0.1
0.1
0.0
0.2
0.3
0.1
0.2
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.2
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
1.5
4.7
3.2
1.3
0.1
0.2
0.9
0.5
0.5
0.4
0.7
1.1
0.9
0.1
0.9
0.6
0.6
0.8
0.2
0.9
0.5
0.7
0.3
2.0
9.6
9.4
7.0
3.3
1.1
1.3
2.1
2.0
1.9
1.9
2.1
3.2
1.9
1.2
2.9
2.0
2.0
2.2
1.5
2.6
2.0
2.1
1.6
4.2
17.1
14.6
11.4
6.4
2.4
2.7
3.6
4.2
4.2
4.0
4.4
6.0
5.3
3.6
6.1
4.1
4.1
4.2
3.5
5.2
4.4
4.5
3.6
6.5
21.3
18.5
14.4
8.8
3.5
3.9
4.8
6.4
6.7
6.2
6.6
7.4
9.6
5.6
10.0
6.3
6.2
6.3
5.7
8.0
6.3
6.9
5.4
14.0
32.2
26.4
22.3
14.3
6.9
6.2
7.6
13.3
14.7
12.8
14.3
14.7
16.4
13.3
18.5
13.4
13.1
14.1
13.0
15.3
14.1
14.5
12.8
73.8
73.8
44.0
45.5
25.0
12.8
16.7
18.4
43.8
73.8
53.2
37.5
43.5
20.9
40.0
45.5
73.8
43.5
40.0
73.8
45.5
45.5
43.8
73.8
Q
I
a
I
ft
-a,
I
a
a,
I
-------
Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFH (g/kg-day, edible portion, uncooked
Population Group
N
Percent
Consuming
Mean
SE
weight) (continued)
Percentiles
1st
tn
10th
25th
50th
75th
90m
95th
99m Max
Vegetables
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan
Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N = 'Sample size.
SE = Standard error.
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
557
177
2,740
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
Source: U.S. EPA analysis of 1994-1996,
99.5
72.1
99.7
100.0
99.9
100.0
99.9
99.9
99.6
99.5
99.5
99.5
99.0
99.7
99.5
98.8
99.6
99.6
99.7
99.5
99.3
99.5
99.5
99.6
1998CSFII.
3.4
4.5
6.9
5.9
4.1
2.9
2.9
3.1
3.3
3.4
3.6
3.2
4.4
3.9
3.0
4.1
3.3
3.4
3.3
3.2
3.6
3.3
3.4
3.3
0.0
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.1
0.1
0.1
0.1
0.3
0.3
0.1
0.2
0.0
0.1
0.1
0.1
0.1
0.1
0.0
0.1
O.O3
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.7
0.8
0.6
0.4
0.5
0.5
0.5
0.4
0.4
0.5
0.8
0.5
0.2
0.5
0.5
0.5
0.4
0.4
0.5
0.4
0.5
0.5
0.8
0.0
1.5
1.4
1.0
0.7
0.8
0.9
0.8
0.8
0.8
0.9
1.3
0.8
0.5
0.9
0.8
0.8
0.7
0.8
0.9
0.7
0.9
0.8
1.6
0.0
3.2
2.8
1.8
1.4
1.5
1.6
1.6
1.5
1.6
1.6
2.3
1.6
1.2
1.7
1.6
1.6
1.5
1.6
1.7
1.5
1.6
1.6
2.7
2.7
5.6
4.7
3.2
2.4
2.5
2.6
2.7
2.6
2.9
2.6
3.9
2.8
2.1
3.0
2.7
2.7
2.6
2.6
2.9
2.7
2.7
2.6
4.3
7.4
9.3
7.7
5.3
3.8
3.8
4.0
4.3
4.2
4.6
4.2
5.6
5.2
3.9
5.1
4.3
4.3
4.3
4.1
4.6
4.3
4.3
4.2
6.4
12.2
13.9
11.7
7.8
5.5
5.4
5.7
6.2
6.6
7.2
5.8
8.2
8.1
6.2
8.2
6.2
6.5
6.2
6.2
7.0
6.4
6.5
6.4
8.3
14.8
17.1
14.7
9.9
6.9
6.8
7.0
7.6
8.8
9.5
7.5
10.2
9.8
8.4
11.6
8.0
8.6
8.2
7.9
8.8
8.5
8.3
8.1
14.8 58.2
25.3 56.8
26.5 58.2
23.4 50.9
17.4 53.7
11.4 29.5
10.0 42.7
10.6 38.7
13.0 58.2
16.0 53.7
15.8 50.9
12.8 56.8
15.9 32.3
18.4 34.5
16.1 56.8
21.1 58.2
13.5 50.9
14.1 53.7
14.4 42.7
14.2 58.2
15.5 50.9
15.3 58.2
14.0 53.7
14.9 49.4
Q
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§
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a
A,
Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based
Population Group
N
Mean
SE
on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
Percentiles
1st
th
10th
25th
50th
75th
90th
95th
99th
Max
Fruits
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan
Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
16,762
830
1,878
3,957
1,846
898
3,458
3,895
3,796
4,289
4,744
3,933
427
146
2,065
1,323
12,801
4,023
3,145
5,531
4,063
4,985
8,046
3,731
2.0
10.1
6.9
5.1
2.7
1.1
1.2
1.6
1.9
2.0
1.9
2.0
2.7
2.4
1.7
2.9
1.9
1.9
2.0
1.7
2.4
2.0
2.1
1.7
0.0
0.4
0.2
0.1
0.1
0.1
0.0
0.0
0.1
0.1
0.1
0.1
0.2
0.4
0.1
0.2
0.0
0.1
0.1
0.1
0.1
0.1
0.1
0.1
O.O5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
3.7
2.2
1.0
0.3
0.0
0.1
0.3
0.1
0.2
0.1
0.2
0.5
0.4
0.0
0.3
0.2
0.1
0.2
0.1
0.3
0.1
0.2
0.1
1.0
8.5
5.4
3.8
1.7
0.5
0.7
1.1
0.9
1.0
0.9
1.1
1.7
1.1
0.6
1.5
1.0
1.0
1.1
0.7
1.3
1.0
1.1
0.8
2.5
14.4
10.1
7.5
3.7
1.5
1.7
2.3
2.4
2.4
2.4
2.6
3.8
2.9
2.0
3.6
2.4
2.3
2.6
2.1
3.0
2.7
2.5
2.1
4.9
20.4
15.3
11.9
6.7
2.9
3.2
3.8
4.9
4.9
4.7
4.9
6.6
5.8
4.6
7.7
4.7
4.7
4.6
4.5
5.8
4.9
5.1
4.1
7.3
26.4
19.0
15.0
9.3
3.7
4.4
5.0
7.1
7.5
7.1
7.6
7.8
10.0
6.7
11.2
7.0
6.7
6.9
6.9
8.9
7.1
7.7
6.3
15.0
34.7
27.1
22.8
14.8
7.6
6.6
8.0
14.4
16.1
14.5
15.3
14.7
17.6
15.7
19.3
14.5
14.4
14.8
14.4
16.4
14.8
15.6
13.9
73.8
73.8
44.0
45.5
25.0
12.8
16.7
18.4
43.8
73.8
53.2
37.5
43.5
20.9
40.0
45.5
73.8
43.5
40.0
73.8
45.5
45.5
43.8
73.8
Q
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Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
A K
Mean
C1T7
SE
Percentiles
1st
th
10th
25th
50th
75th
90th
95th
99th
Max
Vegetables
Whole Population 20,163
Age Group
Birth to 1 year 1,062
1 to 2 years 2,090
3 to 5 years 4,389
6 to 12 years 2,087
13 to 19 years 1,222
20 to 49 years 4,673
>50 years 4,640
Season
Fall 4,606
Spring 5,185
Summer 5,740
Winter 4,632
Race
Asian, Pacific Islander 530
American Indian, Alaskan Native 1 74
Black 2,683
Other/NA 1.577
White 15,199
Region
Midwest 4,721
Northeast 3,634
South 7,078
West 4,730
Urbanization
City Center 6,029
Suburban 9=381
Non-metropolitan 4,753
N = Sample size.
SE = Standard error.
Source: U.S. EPA analysis of 1994-1996, 1998
3.4
6.2
6.9
5.9
4.1
2.9
2.9
3.1
3.3
3.4
3.6
3.2
4.4
3.9
3.1
4.2
3.3
3.4
3.3
3.3
3.6
3.4
3.4
3.3
CSFII.
0.0
0.3
0.2
0.1
0.1
0.1
0.0
0.0
0.1
0.1
0.1
0.1
0.3
0.3
0.1
0.2
0.0
0.1
0.1
0.1
0.1
0.1
0.0
0.1
0.0 5
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.0
0.1
0.0
0.1
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.1
0.0
0.1
0.0
0.5
0.1
0.7
0.8
0.6
0.4
0.5
0.5
0.5
0.5
0.4
0.6
1.0
0.5
0.2
0.6
0.5
0.5
0.4
0.5
0.5
0.4
0.5
0.5
0.8
0.1
1.5
1.4
1.0
0.7
0.8
0.9
0.8
0.8
0.8
0.9
1.4
0.9
0.5
0.9
0.9
0.8
0.8
0.8
0.9
0.8
0.9
0.9
1.6
2.0
3.2
2.8
1.8
1.4
1.5
1.6
1.6
1.5
1.7
1.6
2.4
1.7
1.2
1.8
1.6
1.6
1.5
1.6
1.7
1.5
1.7
1.6
2.7
4.9
5.6
4.7
3.2
2.4
2.5
2.6
2.8
2.6
2.9
2.7
3.9
2.9
2.1
3.0
2.7
2.7
2.6
2.6
2.9
2.7
2.8
2.7
4.3
9.4
9.3
7.7
5.3
3.8
3.8
4.0
4.3
4.2
4.6
4.2
5.6
5.2
3.9
5.2
4.3
4.3
4.3
4.1
4.6
4.3
4.4
4.2
6.4
13.4
13.9
11.7
7.8
5.5
5.4
5.7
6.2
6.7
7.2
5.9
8.2
8.1
6.2
8.3
6.2
6.5
6.2
6.2
7.1
6.4
6.5
6.4
8.4
16.1
17.1
14.7
9.9
6.9
6.8
7.0
7.7
8.8
9.5
7.5
10.2
9.8
8.4
11.7
8.0
8.6
8.2
7.9
8.9
8.6
8.4
8.1
14.8
26.4
26.5
23.4
17.4
11.4
10.0
10.6
13.0
16.0
15.8
12.8
15.9
18.4
16.1
21.3
13.6
14.2
14.4
14.2
15.6
15.4
14.0
14.9
58.2
56.8
58.2
50.9
53.7
29.5
42.7
38.7
58.2
53.7
50.9
56.8
32.3
34.5
56.8
58.2
50.9
53.7
42.7
58.2
50.9
58.2
53.7
49.4
Q
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2,740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
C't C nter 6'164
Sr)burT?anr 9,598
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Apples
30.5 0.45 0.01
34.6 2.32 0.13
44.8 1.79 0.09
44.6 1.64 0.05
38.2 0.83 0.05
22.5 0.20 0.02
25.7 0.21 0.01
34.5 0.32 0.02
35.0 0.55 0.03
29.6 0.45 0.02
25.5 0.34 0.02
32.2 0.46 0.02
33.5 0.53 0.06
31.0 0.60 0.12
22.0 0.36 0.02
27.7 0.55 0.05
32.0 0.45 0.01
34.5 0.47 0.02
32.7 0.48 0.03
25.3 0.36 0.01
32.7 0.55 0.02
28.9 0.42 0.02
33.2 0.49 0.02
27.0 0.39 0.02
Percent
„ . Mean SE
Consuming
Asparagus
1.4 0.01 0.00
0.2 0.01 0.00
0.8 0.02 0.01
0.5 0.01 0.00
0.7 0.01 0.00
0.6 0.00 0.00
1.3 0.01 0.00
2.5 0.02 0.00
1.2 0.01 0.00
1.9 0.02 0.00
0.9 0.01 0.00
1.6 0.02 0.00
1.0 0.01 0.00
2.5 0.02 0.01
0.4 0.00 0.00
0.2 0.00 0.00
1.7 0.01 0.00
1.5 0.01 0.00
1.3 0.01 0.00
1.1 0.01 0.00
1.9 0.01 0.00
1.7 0.01 0.00
1.1 0.01 0.00
1.5 0.01 0.00
Percent
„ . Mean SE
Consuming
Bananas
48.1 0.35 0.01
40.7 1.24 0.06
62.8 1.77 0.09
60.7 0.93 0.04
57.7 0.38 0.03
42.1 0.13 0.02
41.7 0.21 0.01
54.1 0.35 0.01
45.6 0.36 0.02
49.8 0.35 0.02
49.6 0.33 0.02
47.3 0.38 0.01
45.4 0.43 0.04
44.1 0.39 0.05
45.4 0.43 0.04
44.1 0.26 0.02
47.5 0.58 0.07
51.1 0.35 0.02
52.9 0.36 0.01
42.4 0.30 0.02
49.6 0.44 0.03
48.4 0.36 0.02
50.5 0.38 0.01
42.3 0.28 0.03
Percent
„ . Mean SE
Consuming
Beans
44.9 0.27 0.01
21.6 0.43 0.04
46.8 0.76 0.04
43.0 0.52 0.02
38.8 0.32 0.02
36.0 0.18 0.02
45.5 0.22 0.01
51.4 0.26 0.01
47.3 0.29 0.01
43.3 0.25 0.01
43.6 0.28 0.01
45.5 0.26 0.01
52.0 0.25 0.02
37.8 0.26 0.06
45.2 0.32 0.02
60.6 0.43 0.03
43.6 0.25 0.01
43.6 0.26 0.01
36.7 0.21 0.01
48.8 0.33 0.01
47.5 0.25 0.02
46.2 0.29 0.01
42.4 0.25 0.01
48.7 0.30 0.02
Q
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group jV
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
F n 4=687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2,740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
„. „ 6,164
Suburban* 9,598
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Beets
2.2 0.01 0.00
0.4 0.01 0.01
0.7 0.01 0.00
0.8 0.01 0.00
0.8 0.01 0.00
0.7 0.00 0.00
1.9 0.00 0.00
4.6 0.02 0.00
2.0 0.01 0.00
2.3 0.01 0.00
2.3 0.01 0.00
2.3 0.01 0.00
2.7 0.00 0.00
0.3 0.00 0.00
0.9 0.00 0.00
1.3 0.01 0.00
2.5 0.01 0.00
2.3 0.01 0.00
2.4 0.01 0.00
1.7 0.01 0.00
2.8 0.01 0.00
2.3 0.01 0.00
2.2 0.01 0.00
2.4 0.01 0.00
Percent
„ . Mean SE
Consuming
Berries and Small Fruit
58.7 0.23 0.01
16.5 0.13 0.02
66.2 0.91 0.05
72.7 0.72 0.03
73.4 0.40 0.03
55.4 0.15 0.02
53.1 0.14 0.01
63.0 0.19 0.01
57.4 0.18 0.01
60.6 0.27 0.02
60.4 0.29 0.02
56.6 0.20 0.01
41.7 0.28 0.06
49.6 0.13 0.02
50.6 0.14 0.01
47.5 0.21 0.03
61.6 0.25 0.01
63.1 0.25 0.02
63.2 0.24 0.02
53.3 0.19 0.01
58.7 0.28 0.03
57.3 0.22 0.01
62.0 0.27 0.02
53.6 0.17 0.02
Percent
„ . Mean SE
Consuming
Broccoli
13.9 0.11 0.01
3.5 0.07 0.02
12.0 0.25 0.03
10.7 0.18 0.01
11.0 0.14 0.02
8.3 0.06 0.01
14.7 0.10 0.01
17.3 0.11 0.01
14.6 0.12 0.01
13.5 0.11 0.02
13.7 0.11 0.01
13.7 0.10 0.01
25.7 0.23 0.06
9.1 0.11 0.07
13.2 0.14 0.02
8.2 0.09 0.02
14.0 0.10 0.01
13.0 0.09 0.01
15.3 0.13 0.01
13.1 0.11 0.01
14.6 0.12 0.02
15.1 0.13 0.01
14.9 0.12 0.01
9.7 0.06 0.01
Percent
„ . Mean SE
Consuming
Bulb Vegetables
95.3 0.20 0.00
33.4 0.07 0.01
93.3 0.30 0.01
95.8 0.27 0.01
97.3 0.21 0.01
97.7 0.19 0.01
97.4 0.21 0.01
93.4 0.17 0.00
95.8 0.21 0.01
95.4 0.20 0.01
94.3 0.19 0.01
95.5 0.21 0.01
95.0 0.38 0.03
99.3 0.25 0.04
92.9 0.16 0.01
95.0 0.31 0.02
95.6 0.19 0.00
96.2 0.19 0.01
94.5 0.19 0.01
94.4 0.18 0.01
96.3 0.25 0.01
95.0 0.21 0.01
95.7 0.20 0.01
94.7 0.19 0.01
Q
•*•
a-
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3
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!
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§
s
a
A,
Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Cabbage
15.5 0.08 0.01
1.0 0.01 0.00
8.0 0.06 0.01
8.9 0.07 0.01
9.5 0.06 0.01
9.0 0.04 0.01
16.0 0.07 0.01
22.8 0.12 0.01
16.2 0.07 0.01
15.1 0.08 0.01
14.5 0.08 0.01
16.3 0.08 0.01
33.9 0.24 0.04
15.8 0.05 0.04
15.9 0.14 0.03
9.5 0.02 0.01
15.2 0.07 0.00
15.5 0.08 0.01
13.4 0.08 0.01
16.8 0.09 0.01
15.5 0.06 0.01
16.4 0.09 0.01
16.0 0.07 0.00
13.4 0.06 0.01
Percent
„ . Mean SE
Consuming
Carrots
49.8 0.17 0.00
12.3 0.17 0.03
46.8 0.41 0.02
46.2 0.34 0.02
44.4 0.22 0.01
40.3 0.11 0.01
50.2 0.14 0.01
58.1 0.17 0.01
53.9 0.19 0.01
46.5 0.17 0.01
44.3 0.14 0.01
54.5 0.18 0.01
59.4 0.28 0.04
47.3 0.12 0.02
36.6 0.10 0.01
46.2 0.21 0.02
51.9 0.18 0.01
50.9 0.17 0.01
53.8 0.18 0.01
44.9 0.14 0.01
52.8 0.21 0.01
48.8 0.16 0.01
52.3 0.19 0.01
45.7 0.15 0.01
Percent
„ . Mean SE
Consuming
Citrus Fruits
19.3 0.19 0.01
2.5 0.07 0.02
15.5 0.47 0.05
18.2 0.50 0.03
16.0 0.26 0.02
12.3 0.11 0.02
18.1 0.12 0.01
27.1 0.23 0.01
16.6 0.16 0.01
20.3 0.20 0.01
15.8 0.08 0.01
24.6 0.33 0.02
23.4 0.35 0.07
20.4 0.33 0.13
13.0 0.15 0.02
22.4 0.37 0.06
20.0 0.18 0.01
18.9 0.16 0.01
22.4 0.21 0.02
15.1 0.14 0.01
23.7 0.28 0.02
19.8 0.20 0.01
20.0 0.19 0.01
17.0 0.17 0.01
Percent
„ . Mean SE
Consuming
Corn
94.6 0.44 0.01
46.0 0.48 0.03
96.5 1.13 0.05
98.7 1.24 0.03
98.9 0.87 0.03
95.7 0.43 0.02
94.7 0.32 0.01
94.2 0.26 0.01
94.2 0.42 0.01
94.5 0.44 0.02
95.1 0.50 0.02
94.8 0.41 0.02
85.6 0.32 0.04
93.6 0.51 0.06
93.7 0.49 0.02
92.6 0.70 0.05
95.3 0.42 0.01
96.6 0.46 0.02
93.3 0.40 0.01
94.4 0.44 0.01
94.1 0.47 0.02
93.8 0.44 0.01
94.8 0.45 0.01
95.5 0.43 0.02
Q
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I
a
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-------
Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Cucumbers
40.1 0.10 0.01
1.7 0.00 0.00
20.5 0.11 0.01
29.3 0.16 0.02
32.6 0.14 0.02
41.3 0.11 0.03
44.8 0.09 0.01
41.0 0.08 0.01
36.7 0.08 0.01
43.3 0.10 0.01
43.2 0.14 0.02
37.2 0.07 0.01
34.9 0.24 0.16
41.0 0.09 0.03
39.1 0.06 0.01
33.4 0.10 0.01
40.9 0.10 0.01
42.1 0.10 0.01
39.4 0.10 0.01
39.7 0.09 0.01
39.3 0.11 0.03
39.7 0.09 0.00
40.6 0.11 0.01
39.7 0.10 0.01
Percent
„ . Mean SE
Consuming
Cucurbits
48.9 0.40 0.02
14.0 0.45 0.04
31.3 0.72 0.06
38.7 0.83 0.07
39.9 0.54 0.06
46.7 0.32 0.08
52.8 0.29 0.01
52.8 0.43 0.03
45.4 0.21 0.01
51.8 0.48 0.04
55.6 0.73 0.06
43.0 0.16 0.01
46.9 0.90 0.39
51.3 0.53 0.13
43.4 0.27 0.04
46.1 0.53 0.09
50.1 0.39 0.02
49.6 0.37 0.03
50.7 0.43 0.05
46.7 0.33 0.03
50.1 0.50 0.06
48.3 0.34 0.02
49.9 0.44 0.04
47.8 0.37 0.03
Percent
„ . Mean SE
Consuming
Fruiting Vegetables
93.8 0.82 0.01
25.5 0.32 0.04
92.1 1.56 0.06
95.4 1.46 0.03
95.9 1.05 0.03
96.1 0.79 0.03
96.0 0.75 0.02
92.0 0.66 0.02
92.6 0.81 0.03
94.3 0.77 0.02
94.5 0.88 0.02
93.7 0.80 0.02
88.4 0.86 0.06
98.2 0.91 0.08
91.9 0.69 0.04
93.6 1.25 0.05
94.3 0.80 0.01
94.8 0.81 0.02
92.3 0.82 0.02
93.3 0.76 0.03
94.9 0.91 0.03
93.9 0.84 0.03
93.5 0.81 0.01
94.3 0.80 0.04
Percent
„ . Mean SE
Consuming
Leafy Vegetables
90.1 0.59 0.01
44.2 0.29 0.05
82.1 0.71 0.04
86.9 0.67 0.02
89.5 0.55 0.03
90.3 0.43 0.02
92.2 0.58 0.02
90.7 0.66 0.02
89.7 0.59 0.02
90.9 0.60 0.02
90.1 0.56 0.02
89.6 0.59 0.02
92.8 1.13 0.12
89.3 0.52 0.17
89.5 0.65 0.04
85.3 0.50 0.03
90.4 0.56 0.01
92.1 0.55 0.03
87.4 0.62 0.03
90.1 0.55 0.02
90.3 0.64 0.03
89.2 0.64 0.02
90.5 0.60 0.02
90.5 0.46 0.03
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Legumes
95.5 0.43 0.01
51.7 1.21 0.06
96.9 1.30 0.08
98.3 0.85 0.06
98.1 0.48 0.03
94.9 0.27 0.02
95.7 0.34 0.01
96.2 0.40 0.01
96.0 0.44 0.02
95.3 0.40 0.02
95.2 0.43 0.02
95.5 0.44 0.02
96.1 0.76 0.09
97.5 0.42 0.07
95.6 0.50 0.04
93.5 0.55 0.04
95.6 0.40 0.01
96.9 0.40 0.02
93.4 0.38 0.02
96.1 0.47 0.02
95.0 0.44 0.02
95.1 0.47 0.02
95.4 0.41 0.01
96.2 0.41 0.02
Percent
„ . Mean SE
Consuming
Lettuce
52.2 0.24 0.01
1.1 0.00 0.00
23.3 0.14 0.01
33.4 0.21 0.01
41.7 0.22 0.01
55.2 0.22 0.02
60.1 0.27 0.01
51.4 0.23 0.01
50.6 0.23 0.01
54.5 0.25 0.01
51.7 0.23 0.01
52.1 0.24 0.01
48.1 0.28 0.05
61.3 0.21 0.04
42.7 0.15 0.01
52.1 0.25 0.02
53.8 0.25 0.01
53.3 0.25 0.02
49.3 0.24 0.01
50.7 0.21 0.01
56.0 0.27 0.01
51.3 0.24 0.01
53.0 0.26 0.01
51.6 0.20 0.01
Percent
„ . Mean SE
Consuming
Okra
1.4 0.01 0.00
0.2 0.00 0.00
1.3 0.01 0.00
0.8 0.01 0.00
1.3 0.01 0.00
0.8 0.00 0.00
1.3 0.01 0.00
2.1 0.01 0.00
1.7 0.01 0.00
1.1 0.01 0.00
1.7 0.01 0.00
1.0 0.01 0.00
4.8 0.01 0.01
0.6 0.00 0.00
2.4 0.01 0.00
0.6 0.00 0.00
1.2 0.01 0.00
0.4 0.00 0.00
0.8 0.00 0.00
2.6 0.01 0.00
1.2 0.00 0.00
1.8 0.01 0.00
1.0 0.01 0.00
1.7 0.01 0.00
Percent
„ . Mean SE
Consuming
Onions
94.9 0.19 0.00
32.8 0.07 0.01
93.0 0.29 0.01
95.6 0.26 0.01
96.8 0.20 0.01
97.3 0.18 0.01
97.1 0.20 0.01
93.2 0.16 0.00
95.5 0.20 0.01
95.0 0.19 0.01
94.0 0.18 0.00
95.3 0.20 0.01
94.9 0.37 0.03
99.3 0.25 0.04
92.6 0.16 0.01
95.0 0.30 0.02
95.3 0.18 0.00
96.0 0.18 0.01
94.0 0.18 0.01
94.1 0.18 0.01
96.1 0.24 0.01
94.8 0.20 0.01
95.3 0.19 0.01
94.3 0.19 0.01
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Peaches
40.8 0.11 0.00
24.4 0.85 0.08
50.7 0.47 0.04
55.4 0.26 0.02
54.7 0.14 0.02
39.1 0.06 0.01
34.5 0.05 0.00
44.1 0.10 0.01
35.9 0.07 0.01
42.9 0.10 0.01
46.6 0.17 0.01
37.9 0.09 0.01
32.2 0.07 0.02
38.0 0.20 0.06
39.4 0.10 0.01
35.2 0.13 0.02
41.8 0.11 0.01
45.3 0.11 0.01
44.0 0.10 0.01
35.8 0.11 0.01
41.1 0.11 0.01
39.9 0.11 0.01
43.1 0.11 0.01
37.1 0.10 0.00
Percent
„ . Mean SE
Consuming
Pears
8.2 0.09 0.00
15.9 0.73 0.07
17.2 0.40 0.04
16.6 0.26 0.03
17.5 0.14 0.01
5.9 0.03 0.01
4.4 0.04 0.00
9.0 0.07 0.01
9.6 0.11 0.01
7.7 0.07 0.00
6.8 0.07 0.01
8.7 0.10 0.01
9.2 0.13 0.03
11.2 0.15 0.06
5.6 0.06 0.01
8.3 0.11 0.02
8.6 0.09 0.00
9.1 0.09 0.01
9.4 0.10 0.01
6.5 0.07 0.01
8.9 0.10 0.01
8.1 0.09 0.01
8.8 0.10 0.01
7.2 0.06 0.01
Percent
„ . Mean SE
Consuming
Peas
22.3 0.11 0.01
29.5 0.47 0.04
28.3 0.34 0.03
20.5 0.21 0.02
17.2 0.12 0.01
14.0 0.07 0.01
21.3 0.08 0.01
28.4 0.10 0.01
24.1 0.10 0.01
20.2 0.10 0.01
19.8 0.10 0.01
24.9 0.13 0.01
41.0 0.15 0.02
22.5 0.13 0.03
20.9 0.13 0.02
19.8 0.07 0.01
21.9 0.10 0.01
22.1 0.10 0.01
24.7 0.13 0.02
19.9 0.10 0.01
24.0 0.10 0.01
24.0 0.12 0.01
22.3 0.11 0.01
19.6 0.09 0.01
Percent
„ . Mean SE
Consuming
Peppers
83.0 0.06 0.00
15.6 0.01 0.00
77.5 0.05 0.01
84.6 0.05 0.00
85.1 0.05 0.00
84.8 0.04 0.00
86.9 0.08 0.01
78.9 0.06 0.01
81.3 0.07 0.01
84.8 0.06 0.00
83.1 0.06 0.00
83.0 0.06 0.00
70.9 0.08 0.01
89.3 0.08 0.02
82.8 0.04 0.01
81.7 0.12 0.01
83.6 0.06 0.00
85.6 0.06 0.01
79.0 0.07 0.01
82.1 0.05 0.00
85.4 0.08 0.01
83.4 0.07 0.01
82.2 0.06 0.00
84.4 0.06 0.01
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Pome Fruit
34.7 0.54 0.01
40.0 3.04 0.17
52.0 2.19 0.10
51.7 1.90 0.06
47.9 0.97 0.06
26.5 0.23 0.02
27.9 0.25 0.01
39.0 0.39 0.02
39.5 0.66 0.04
33.6 0.52 0.03
29.1 0.41 0.02
36.7 0.56 0.03
36.5 0.66 0.08
39.5 0.75 0.14
24.8 0.42 0.03
32.7 0.67 0.06
36.4 0.54 0.01
38.9 0.55 0.03
37.3 0.57 0.02
28.9 0.43 0.02
37.2 0.65 0.03
33.2 0.51 0.02
37.6 0.59 0.02
30.7 0.45 0.03
Percent
„ . Mean SE
Consuming
Pumpkins
1.8 0.01 0.00
0.3 0.00 0.00
0.7 0.01 0.00
0.9 0.01 0.00
1.8 0.01 0.00
1.3 0.01 0.00
1.7 0.00 0.00
2.3 0.01 0.00
4.9 0.01 0.00
0.4 0.00 0.00
0.7 0.00 0.00
1.0 0.00 0.00
1.0 0.00 0.00
1.2 0.00 0.00
0.5 0.00 0.00
3.5 0.01 0.00
1.9 0.01 0.00
2.4 0.01 0.00
2.0 0.01 0.00
1.1 0.00 0.00
1.9 0.01 0.00
1.5 0.00 0.00
1.8 0.00 0.00
2.0 0.01 0.00
Percent
„ . Mean SE
Consuming
Root Tuber Vegetables
99.2 1.42 0.02
61.7 2.60 0.15
99.6 3.38 0.09
100.0 2.96 0.07
100.0 2.09 0.07
99.9 1.36 0.06
99.7 1.12 0.02
99.7 1.13 0.02
99.4 1.49 0.04
99.3 1.41 0.03
99.2 1.34 0.03
99.0 1.45 0.04
97.3 1.31 0.10
99.7 1.71 0.30
99.0 1.31 0.09
98.0 1.47 0.05
99.4 1.44 0.02
99.5 1.57 0.05
99.4 1.33 0.05
99.2 1.40 0.04
98.8 1.38 0.05
99.0 1.34 0.04
99.3 1.44 0.03
99.4 1.52 0.06
Percent
„ . Mean SE
Consuming
Stalk, Stem Vegetables
19.4 0.05 0.00
1.9 0.01 0.00
13.2 0.06 0.01
10.9 0.04 0.00
10.7 0.03 0.01
16.6 0.03 0.01
24.5 0.05 0.00
18.3 0.05 0.00
18.5 0.04 0.00
20.1 0.05 0.00
17.0 0.03 0.00
21.8 0.06 0.01
36.5 0.11 0.01
21.6 0.05 0.02
8.1 0.01 0.00
14.5 0.03 0.00
20.9 0.05 0.00
22.1 0.05 0.00
17.2 0.05 0.01
16.4 0.04 0.00
23.1 0.06 0.00
19.6 0.05 0.00
20.0 0.05 0.00
17.8 0.04 0.00
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Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
Population Group N
Whole Population 20,607
Age Group
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
20 to 49 years 4,677
>50 years 4,646
Season
Fall 4'687
Spring 5,308
Summer 5,890
Winter 4,722
Race
Asian, Pacific Islander 557
American Indian, Alaskan Native 177
Black 2=740
Other/NA 1,638
White 15,495
Region
Midwest 4,822
Northeast 3,692
South 7,208
West 4,885
Urbanization
rrt r< t 6,164
S&burlSr? 9^98
Non-metropolitan 4,845
Percent
„ . Mean SE
Consuming
Strawberries
32.4 0.06 0.00
6.8 0.02 0.00
33.5 0.19 0.03
37.1 0.14 0.01
37.3 0.10 0.01
26.8 0.05 0.01
29.8 0.05 0.00
37.7 0.06 0.00
26.8 0.03 0.00
36.8 0.11 0.01
36.1 0.06 0.01
29.9 0.05 0.01
23.9 0.07 0.03
28.2 0.03 0.02
21.1 0.02 0.00
22.3 0.05 0.01
35.3 0.07 0.00
34.9 0.07 0.01
37.1 0.06 0.01
27.2 0.05 0.00
33.9 0.08 0.01
29.7 0.05 0.01
36.2 0.08 0.00
28.1 0.05 0.01
Percent
„ . Mean SE
Consuming
Stone Fruit
44.5 0.17 0.01
29.2 1.15 0.10
53.6 0.60 0.04
57.5 0.38 0.02
56.8 0.23 0.02
41.1 0.09 0.01
38.1 0.09 0.01
49.4 0.17 0.01
39.3 0.11 0.01
46.8 0.17 0.01
50.3 0.28 0.02
41.6 0.12 0.01
36.5 0.16 0.04
39.2 0.24 0.07
40.7 0.14 0.02
38.2 0.19 0.03
45.9 0.17 0.01
49.9 0.18 0.01
47.5 0.15 0.01
38.9 0.15 0.01
44.8 0.20 0.01
43.5 0.17 0.01
46.9 0.18 0.01
40.6 0.15 0.01
Percent
„ . Mean SE
Consuming
Tomatoes
84.4 0.74 0.01
21.5 0.30 0.03
80.7 1.50 0.05
85.7 1.40 0.03
86.9 1.00 0.03
90.2 0.74 0.03
87.1 0.66 0.01
80.1 0.57 0.01
83.5 0.73 0.03
84.3 0.69 0.02
85.1 0.80 0.02
84.5 0.72 0.02
74.1 0.73 0.06
89.2 0.82 0.07
78.1 0.63 0.03
89.6 1.11 0.05
85.4 0.73 0.01
85.5 0.74 0.02
83.4 0.73 0.02
82.7 0.69 0.02
86.6 0.81 0.02
84.1 0.75 0.02
84.5 0.73 0.01
84.4 0.73 0.03
Percent
„ . Mean SE
Consuming
Tropical Fruits
58.3 0.43 0.01
42.2 1.31 0.07
70.1 1.97 0.10
69.7 1.10 0.04
67.0 0.50 0.04
54.5 0.19 0.02
52.8 0.27 0.01
63.1 0.41 0.01
56.5 0.42 0.02
59.4 0.43 0.02
58.2 0.41 0.02
58.9 0.45 0.02
55.4 0.61 0.07
54.1 0.43 0.05
53.6 0.36 0.03
60.9 0.77 0.09
59.0 0.41 0.01
60.1 0.40 0.03
62.4 0.47 0.02
53.1 0.36 0.02
60.8 0.53 0.03
58.8 0.46 0.02
60.2 0.44 0.01
53.0 0.34 0.03
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Table 9-16. Per Capita
Population Group
Intake of Individual
N
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
>50 years
Season
Fall
f\ •
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N = Sample size.
SE = Standard error.
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
557
177
2,740
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
Percent
Consuming
Fruits
Mean
and Vegetables Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
(continued)
SE
White Potatoes
91.3
39.9
91.2
95.1
93.9
92.6
91.5
91.7
91.5
91.3
91.3
91.1
82.3
92.7
88.5
86.5
92.4
94.5
88.6
91.8
89.6
89.5
91.2
94.2
0.89
0.64
1.95
1.75
1.21
0.93
0.74
0.72
0.91
0.87
0.86
0.90
0.72
1.29
0.81
0.86
0.90
1.00
0.79
0.90
0.82
0.81
0.87
1.02
0.02
0.07
0.08
0.06
0.06
0.05
0.02
0.02
0.04
0.03
0.03
0.03
0.09
0.32
0.07
0.07
0.02
0.03
0.04
0.04
0.06
0.04
0.02
0.06
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables with higher
percentages consuming
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
Q
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Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Apples
7,193 1.47 0.03
496 6.71 0.31
947 4.00 0.15
1,978 3.68 0.08
792 2.17 0.12
271 0.90 0.06
1,171 0.82 0.03
1,538 0.92 0.04
1,841 1.57 0.06
1,818 1.52 0.07
1,801 1.32 0.06
1,733 1.44 0.05
182 1.59 0.12
58 1.93 0.27
762 1.62 0.12
536 2.00 0.13
5,655 1.42 0.03
1,792 1.35 0.06
1,385 1.46 0.05
2,201 1.44 0.05
1,815 1.67 0.06
2,091 1.46 0.05
3,647 1.49 0.05
1,455 1.45 0.03
JV Mean SE
Asparagus
233 0.85 0.04
3 2.59 1.16
19 1.99 0.54
23 1.37 0.32
13 1.77 0.43
4 0.56 0.08
58 0.79 0.08
113 0.77 0.07
44 0.80 0.13
91 0.90 0.07
36 0.66 0.12
62 0.94 0.10
5 0.62 0.15
2 0.81
8 1.01 0.64
5 0.31 0.09
213 0.86 0.05
63 0.91 0.08
43 0.72 0.10
64 1.07 0.09
63 0.69 0.04
81 0.85 0.07
97 0.78 0.07
55 0.98 0.11
N Mean SE
Bananas
10,734 0.73 0.02
605 3.04 0.12
1,328 2.82 0.12
2,746 1.54 0.06
1,214 0.66 0.05
511 0.30 0.04
1,887 0.50 0.01
2,443 0.65 0.02
2,292 0.79 0.04
2,856 0.70 0.03
3,124 0.66 0.03
2,462 0.80 0.03
265 0.95 0.10
88 0.87 0.15
1,288 0.59 0.05
865 1.21 0.11
8,228 0.71 0.02
2,589 0.68 0.04
2,122 0.68 0.02
3,356 0.70 0.04
2,667 0.89 0.03
3,182 0.75 0.03
5,303 0.75 0.02
2,249 0.67 0.04
N Mean SE
Beans
9,086 0.60 0.01
313 2.00 0.16
996 1.63 0.08
1,909 1.22 0.04
833 0.82 0.05
472 0.49 0.03
2,153 0.48 0.01
2,410 0.52 0.02
2,122 0.60 0.02
2,311 0.59 0.02
2,539 0.65 0.02
2,114 0.57 0.02
265 0.48 0.05
74 0.70 0.12
1,205 0.71 0.04
911 0.71 0.04
6,631 0.58 0.01
2,071 0.59 0.02
1,342 0.56 0.02
3,465 0.68 0.02
2,208 0.52 0.03
2,840 0.62 0.02
3,957 0.58 0.01
2,289 0.61 0.01
N Mean SE
Beets
374 0.35 0
6 1.42 0.9
13 0.98 0.3
36 0.9 0.2
16 0.66 0.3
9 0.2 0.1
93 0.23 0
201 0.38 0
90 0.25 0
92 0.45 0.1
104 0.34 0.1
88 0.33 0.1
16 0.04 0
1 0.02
18 0.29 0.1
16 0.39 0.2
323 0.36 0
90 0.35 0.1
78 0.42 0.1
99 0.29 0
107 0.33 0.1
110 0.28 0
171 0.39 0.1
93 0.35 0
Q
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a
A,
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Berries and Small Fruits
12,206 0.40 0.01
229 0.81 0.07
1,396 1.38 0.06
3,166 0.99 0.04
1,523 0.54 0.04
679 0.27 0.03
2,393 0.27 0.02
2,820 0.31 0.01
2,706 0.31 0.02
3,202 0.45 0.03
3,558 0.48 0.02
2,740 0.35 0.02
252 0.66 0.13
85 0.26 0.04
1,430 0.27 0.02
782 0.45 0.06
9,657 0.41 0.01
3,042 0.40 0.03
2,383 0.37 0.03
3,896 0.35 0.02
2,885 0.48 0.03
3,525 0.38 0.02
6,039 0.44 0.02
2,642 0.31 0.03
JV Mean SE
Broccoli
2,474 0.80 0.03
49 2.09 0.33
242 2.11 0.16
475 1.67 0.09
213 1.29 0.16
102 0.69 0.07
640 0.68 0.04
753 0.63 0.03
582 0.81 0.05
651 0.82 0.07
660 0.79 0.05
581 0.76 0.07
118 0.89 0.12
16 1.18 0.43
286 1.06 0.12
131 1.09 0.10
1,923 0.73 0.03
533 0.66 0.03
511 0.84 0.07
810 0.83 0.04
620 0.83 0.08
741 0.83 0.06
1,283 0.81 0.03
450 0.64 0.05
N Mean SE
N Mean SE
Bulb Vegetables Cabbage
18,738 0.21 0.00
489 0.22 0.02
1,957 0.32 0.01
4,207 0.28 0.01
2,040 0.22 0.01
1,194 0.20 0.01
4,546 0.22 0.01
4,305 0.18 0.00
4,310 0.22 0.01
4,835 0.21 0.01
5,280 0.20 0.01
4,313 0.22 0.01
481 0.40 0.03
169 0.25 0.04
2,438 0.18 0.01
1,484 0.33 0.02
14,166 0.20 0.00
4,457 0.20 0.01
3,324 0.20 0.01
6,497 0.19 0.01
4,460 0.26 0.01
5,547 0.22 0.01
8,768 0.21 0.01
4,423 0.20 0.01
2,633 0.50 0.03
15 0.61 0.41
160 0.73 0.11
369 0.78 0.07
190 0.63 0.11
106 0.40 0.06
746 0.45 0.03
1,047 0.52 0.02
623 0.44 0.03
684 0.52 0.03
676 0.56 0.07
650 0.48 0.04
152 0.69 0.09
18 0.34 0.13
359 0.87 0.11
144 0.24 0.05
1,960 0.43 0.02
629 0.49 0.04
413 0.56 0.06
978 0.52 0.06
613 0.41 0.03
794 0.58 0.07
1,251 0.45 0.02
588 0.48 0.04
N Mean SE
Carrots
9,513 0.34 0.01
179 1.39 0.20
999 0.87 0.05
2,048 0.74 0.03
904 0.50 0.03
482 0.27 0.02
2,289 0.28 0.01
2,612 0.29 0.01
2,338 0.35 0.02
2,345 0.36 0.02
2,440 0.33 0.01
2,390 0.34 0.01
329 0.47 0.05
82 0.26 0.03
958 0.28 0.02
749 0.45 0.03
7,395 0.34 0.01
2,313 0.34 0.02
1,843 0.34 0.01
2,981 0.31 0.01
2,376 0.40 0.01
2,759 0.34 0.01
4,690 0.36 0.01
2,064 0.32 0.01
Q
I
a
I
ft
-a,
I
a
a,
I
-------
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Citrus Fruits
3,656 0.99 0.03
37 2.79 0.53
336 3.06 0.20
751 2.75 0.15
324 1.60 0.12
157 0.90 0.15
841 0.68 0.04
1,210 0.84 0.03
761 0.93 0.06
1,002 0.97 0.05
815 0.53 0.04
1,078 1.32 0.06
117 1.50 0.19
41 1.61 0.17
369 1.15 0.08
347 1.66 0.16
2,782 0.89 0.03
842 0.84 0.06
754 0.94 0.06
998 0.94 0.04
1,062 1.20 0.07
1,146 1.01 0.04
1,738 0.97 0.04
772 0.99 0.07
JV Mean SE
Corn
19,059 0.47 0.01
671 1.05 0.07
2,027 1.17 0.05
4,334 1.26 0.03
2,064 0.88 0.03
1,176 0.45 0.01
4,415 0.34 0.01
4,372 0.28 0.01
4,342 0.44 0.01
4,909 0.47 0.02
5,423 0.52 0.02
4,385 0.44 0.02
454 0.37 0.05
165 0.55 0.06
2,502 0.52 0.02
1,475 0.76 0.05
14,463 0.44 0.01
4,562 0.48 0.02
3,377 0.43 0.01
6,648 0.46 0.01
4,472 0.49 0.02
5,641 0.47 0.01
8,886 0.47 0.01
4,532 0.45 0.02
N Mean SE
Cucumbers
6,779 0.24 0.02
25 0.28 0.11
439 0.52 0.05
1,266 0.56 0.05
667 0.43 0.06
500 0.26 0.06
2,033 0.20 0.01
1,849 0.21 0.01
1,374 0.22 0.02
1,906 0.23 0.01
2,070 0.32 0.05
1,429 0.20 0.02
134 0.68 0.43
60 0.23 0.06
858 0.17 0.01
413 0.30 0.03
5,314 0.24 0.01
1,693 0.23 0.02
1,191 0.25 0.02
2,356 0.22 0.02
1,539 0.29 0.07
1,965 0.22 0.01
3,151 0.26 0.03
1,663 0.25 0.03
N Mean SE
Cucurbits
8,763 0.81 0.04
213 3.19 0.29
682 2.29 0.17
1,694 2.15 0.17
833 1.34 0.15
563 0.69 0.16
2,400 0.55 0.03
2,378 0.81 0.05
1,778 0.46 0.03
2,408 0.94 0.07
2,855 1.32 0.10
1,722 0.36 0.03
217 1.92 0.79
75 1.04 0.32
987 0.62 0.08
633 1.14 0.19
6,851 0.77 0.03
2,091 0.75 0.05
1,614 0.85 0.08
2,905 0.70 0.06
2,153 0.99 0.12
2,570 0.71 0.05
4,119 0.89 0.07
2,074 0.78 0.06
N Mean SE
Fruiting Vegetables
18,407 0.87 0.01
371 1.24 0.11
1,927 1.70 0.06
4,180 1.53 0.03
2,014 1.10 0.03
1,176 0.82 0.03
4,489 0.78 0.02
4,250 0.71 0.02
4,186 0.87 0.03
4,755 0.82 0.02
5,262 0.93 0.02
4,204 0.85 0.03
439 0.98 0.06
162 0.93 0.08
2,398 0.75 0.04
1,447 1.34 0.05
13,961 0.85 0.01
4,379 0.85 0.02
3,254 0.88 0.02
6,416 0.81 0.03
4,358 0.96 0.03
5,477 0.89 0.03
8,563 0.86 0.01
4,367 0.85 0.04
Q
•*•
a-
QTQ
I
-------
a
A,
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3io 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Leafy Vegetables
17,637 0.65 0.01
639 0.65 0.11
1,729 0.87 0.05
3,815 0.77 0.03
1,860 0.62 0.03
1,101 0.47 0.02
4,308 0.63 0.02
4,185 0.72 0.02
4,046 0.66 0.03
4,579 0.66 0.02
4,964 0.62 0.02
4,048 0.66 0.02
469 1.22 0.12
151 0.59 0.19
2,367 0.73 0.04
1,329 0.59 0.04
13,321 0.62 0.01
4,226 0.60 0.03
3,081 0.71 0.03
6,174 0.61 0.02
4,156 0.71 0.04
5,232 0.72 0.03
8,220 0.67 0.02
4,185 0.51 0.03
N Mean SE
Legumes
19,258 0.45 0.01
754 2.34 0.11
2,037 1.34 0.08
4,308 0.86 0.06
2,045 0.49 0.03
1,168 0.29 0.02
4,477 0.36 0.01
4,469 0.41 0.01
4,412 0.46 0.02
4,952 0.42 0.02
5,476 0.45 0.02
4,418 0.46 0.02
503 0.79 0.09
170 0.44 0.08
2,563 0.52 0.04
1,478 0.58 0.05
14,544 0.42 0.01
4,577 0.41 0.02
3,421 0.40 0.02
6,771 0.49 0.02
4,489 0.47 0.03
5,735 0.50 0.02
8,950 0.43 0.02
4,573 0.43 0.02
JV Mean SE
Lettuce
8,430 0.46 0.01
15 0.17 0.02
481 0.58 0.04
1,415 0.62 0.03
858 0.53 0.02
669 0.40 0.03
2,693 0.45 0.01
2,299 0.45 0.01
1,894 0.46 0.02
2,279 0.46 0.02
2,325 0.45 0.01
1,932 0.46 0.02
191 0.58 0.09
88 0.34 0.04
884 0.35 0.02
643 0.49 0.04
6,624 0.47 0.01
2,035 0.47 0.03
1,396 0.49 0.02
2,830 0.41 0.02
2,169 0.49 0.03
2,414 0.46 0.02
3,999 0.49 0.01
2,017 0.39 0.02
N Mean SE
Okra
272 0.51 0.04
4 1.50 0.54
29 0.64 0.19
34 1.16 0.32
21 0.62 0.15
12 0.43 0.13
62 0.44 0.06
110 0.50 0.05
58 0.39 0.04
66 0.47 0.09
106 0.65 0.08
42 0.53 0.13
15 0.20 0.06
2 0.40
67 0.63 0.08
15 0.70 0.25
173 0.51 0.05
24 0.42 0.20
22 0.50 0.18
178 0.58 0.05
48 0.30 0.07
96 0.49 0.07
102 0.59 0.07
74 0.42 0.04
N Mean SE
Onions
18,678 0.20 0.00
481 0.22 0.02
1,948 0.31 0.01
4,200 0.27 0.01
2,030 0.21 0.01
1,190 0.19 0.01
4,533 0.21 0.01
4,296 0.17 0.00
4,300 0.21 0.01
4,815 0.20 0.01
5,265 0.19 0.01
4,298 0.21 0.01
480 0.39 0.03
169 0.25 0.04
2,431 0.17 0.01
1,484 0.32 0.02
14,114 0.19 0.00
4,448 0.19 0.01
3,308 0.19 0.01
6,479 0.19 0.01
4,443 0.25 0.01
5,531 0.21 0.01
8,739 0.20 0.01
4,408 0.20 0.01
Q
I
a
I
(%
-a,
I
a
a,
I
-------
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Peaches
9,069 0.26 0.01
344 3.47 0.28
1,067 0.93 0.08
2,461 0.48 0.03
1,150 0.26 0.03
480 0.15 0.03
1;544 0.14 0.01
2,023 0.22 0.01
1,841 0.20 0.02
2,439 0.23 0.02
2,815 0.37 0.02
1,974 0.22 0.02
200 0.23 0.04
68 0.54 0.17
1,146 0.25 0.03
590 0.38 0.07
7,065 0.26 0.01
2,283 0.25 0.02
1,778 0.22 0.02
2,849 0.30 0.02
2,159 0.26 0.02
2,640 0.27 0.02
4,457 0.26 0.01
1,972 0.27 0.01
N Mean SE
Pears
2,355 1.06 0.04
217 4.55 0.28
354 2.33 0.16
711 1.59 0.12
382 0.81 0.07
72 0.45 0.09
205 0.80 0.05
414 0.81 0.04
596 1.15 0.08
590 0.86 0.05
585 1.05 0.06
584 1.14 0.09
56 1.43 0.21
23 1.31 0.60
244 1.09 0.15
171 1.39 0.22
1,861 1.02 0.04
625 0.96 0.06
470 1.04 0.06
648 1.08 0.10
612 1.17 0.08
686 1.06 0.06
1,205 1.12 0.06
464 0.89 0.05
JV Mean SE
Peas
4,661 0.48 0.02
417 1.60 0.09
609 1.21 0.06
888 1.02 0.07
346 0.68 0.06
168 0.48 0.06
959 0.37 0.02
1,274 0.37 0.02
1,172 0.43 0.02
1,120 0.51 0.03
1,213 0.48 0.02
1,156 0.52 0.04
192 0.35 0.04
51 0.59 0.10
612 0.64 0.05
323 0.38 0.04
3,483 0.48 0.02
1,108 0.46 0.02
923 0.52 0.05
1,526 0.51 0.03
1,104 0.43 0.04
1,480 0.50 0.03
2,179 0.48 0.03
1,002 0.45 0.04
N Mean SE
Peppers
16,093 0.08 0.00
224 0.05 0.01
1,627 0.06 0.01
3,706 0.06 0.00
1,784 0.05 0.01
1,041 0.05 0.00
4,068 0.09 0.01
3,643 0.08 0.01
3,643 0.08 0.01
4,212 0.07 0.01
4,568 0.08 0.01
3,670 0.07 0.01
344 0.11 0.01
144 0.09 0.03
2,150 0.05 0.01
1,233 0.15 0.01
12,222 0.07 0.00
3,920 0.07 0.01
2,711 0.08 0.01
5,579 0.06 0.01
3,883 0.10 0.01
4,780 0.09 0.01
7,436 0.07 0.00
3,877 0.07 0.01
N Mean SE
Pome Fruit
8,316 1.55 0.03
572 7.60 0.34
1,097 4.21 0.13
2,291 3.68 0.08
1,012 2.03 0.10
320 0.87 0.06
1,274 0.88 0.03
1,750 1.00 0.03
2,102 1.67 0.07
2,102 1.54 0.06
2,092 1.40 0.06
2,020 1.53 0.06
209 1.82 0.14
73 1.89 0.29
878 1.68 0.12
624 2.05 0.14
6,532 1.48 0.03
2,094 1.42 0.07
1,598 1.54 0.05
2,535 1.50 0.05
2,089 1.74 0.07
2,408 1.54 0.05
4,224 1.58 0.06
1,684 1.48 0.03
Q
•*•
a-
QTQ
I
-------
§
s
a
A,
Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Pumpkins
299 0.30 0.02
3 1.06 0.71
15 1.08 0.51
36 0.56 0.10
37 0.52 0.11
14 0.42 0.16
89 0.24 0.02
105 0.22 0.01
193 0.29 0.02
22 0.65 0.18
40 0.22 0.06
44 0.25 0.04
4 0.33 0.07
3 0.11 0.01
12 0.34 0.05
43 0.21 0.08
237 0.31 0.02
87 0.31 0.01
62 0.30 0.09
70 0.28 0.03
80 0.30 0.05
76 0.31 0.05
137 0.26 0.02
86 0.36 0.04
N Mean SE
Root Tuber Vegetables
19,997 1.44 0.02
916 4.21 0.19
2,087 3.40 0.09
4,388 2.96 0.07
2,089 2.09 0.07
1,221 1.36 0.06
4,664 1.12 0.02
4,632 1.14 0.02
4,565 1.50 0.04
5,151 1.43 0.03
5,690 1.35 0.03
4,591 1.46 0.03
518 1.35 0.10
174 1.71 0.30
2,642 1.32 0.09
1,561 1.50 0.05
15,102 1.45 0.02
4,709 1.58 0.05
3,598 1.34 0.05
6,998 1.41 0.04
4,692 1.40 0.05
5,961 1.36 0.04
9,315 1.45 0.03
4,721 1.53 0.07
JV Mean SE
Stalk, Stem Vegetables
3,095 0.24 0.01
24 0.56 0.22
272 0.48 0.05
502 0.38 0.03
218 0.32 0.04
190 0.20 0.03
1,079 0.20 0.01
810 0.27 0.02
720 0.22 0.02
825 0.25 0.01
796 0.20 0.01
754 0.26 0.02
158 0.29 0.03
32 0.25 0.05
188 0.18 0.03
172 0.21 0.02
2,545 0.24 0.01
883 0.22 0.02
467 0.26 0.03
908 0.24 0.02
837 0.24 0.02
891 0.25 0.02
1,492 0.23 0.01
712 0.24 0.02
N Mean SE
Strawberries
6,675 0.20 0.01
96 0.26 0.06
729 0.57 0.08
1,710 0.38 0.03
783 0.28 0.02
326 0.18 0.03
1,330 0.15 0.02
1,701 0.15 0.01
1,250 0.13 0.01
1,911 0.30 0.03
2,060 0.17 0.02
1,454 0.16 0.02
149 0.29 0.11
50 0.11 0.04
550 0.11 0.02
367 0.22 0.06
5,559 0.20 0.01
1,668 0.20 0.01
1,381 0.16 0.02
1,952 0.18 0.02
1,674 0.23 0.03
1,772 0.18 0.02
3,517 0.22 0.01
1,386 0.17 0.03
N Mean SE
Stone Fruit
9,786 0.38 0.01
418 3.95 0.25
1,130 1.13 0.08
2,556 0.66 0.03
1,194 0.41 0.03
508 0.21 0.03
1,715 0.23 0.01
2,265 0.34 0.02
1,987 0.27 0.02
2,627 0.35 0.02
3,029 0.56 0.03
2,143 0.29 0.02
218 0.44 0.08
73 0.60 0.18
1,184 0.34 0.04
649 0.50 0.08
7,662 0.38 0.01
2,469 0.36 0.02
1,912 0.32 0.02
3,060 0.39 0.02
2,345 0.45 0.03
2,845 0.38 0.02
4,808 0.38 0.02
2,133 0.36 0.01
Q
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Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994-1996, 1998 CSF1I (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
> 50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
American Indian, Alaskan Native
Black
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
City Center
Suburban
Non-metropolitan
N Mean SE
Tomatoes
16,403 0.87 0.01
315 1.42 0.13
1,684 1.86 0.06
3,764 1.63 0.03
1,832 1.15 0.03
1,098 0.82 0.03
4,053 0.75 0.02
3,657 0.72 0.01
3,732 0.87 0.03
4,173 0.82 0.02
4,731 0.94 0.02
3,767 0.86 0.03
373 0.99 0.08
146 0.92 0.08
2,017 0.80 0.04
1,369 1.24 0.05
12,498 0.85 0.01
3,915 0.87 0.02
2,906 0.88 0.02
5,629 0.83 0.02
3,953 0.93 0.02
4,867 0.89 0.02
7,647 0.87 0.01
3,889 0.86 0.03
N Mean SE
Tropical Fruits
12,539 0.73 0.02
630 3.09 0.12
1,476 2.81 0.12
3,106 1.57 0.05
1,407 0.75 0.05
652 0.35 0.04
2,428 0.51 0.02
2,840 0.64 0.02
2,748 0.75 0.03
3,291 0.72 0.03
3,595 0.70 0.02
2,905 0.77 0.03
314 1.10 0.13
103 0.79 0.12
1,541 0.67 0.05
1,034 1.26 0.10
9,547 0.69 0.02
2,989 0.67 0.04
2,412 0.75 0.02
4,016 0.67 0.03
3,122 0.87 0.03
3,750 0.79 0.03
6,092 0.73 0.02
2,697 0.64 0.05
N Mean SE
White Potatoes
18,261 0.97 0.02
577 1.60 0.15
1,918 2.14 0.09
4,147 1.84 0.06
1,963 1.29 0.06
4,271 0.81 0.02
2,664 0.75 0.02
4,254 0.78 0.02
4,205 1.00 0.04
4,703 0.96 0.03
5,190 0.94 0.03
4,163 0.99 0.03
428 0.88 0.09
162 1.40 0.33
2,365 0.92 0.08
1,353 1.00 0.06
13,953 0.98 0.02
4,436 1.06 0.04
3,199 0.90 0.03
6,415 0.98 0.04
4,211 0.92 0.06
5,337 0.91 0.04
8,488 0.96 0.02
4,436 1.08 0.06
N = Sample size.
SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables
with higher percentages consuming.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
Q
•*•
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I
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-------
oo
QTQ
§
s
a
A,
Table 9-18. Per Capita Intake of Exposed Fruits Based
Population
Group
Whole Population
Age Group
0 to 5 months
6 to 12 months
<1 years
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-
Suburban
Race
Asian
Black
Native American
Other/NA
White
Region
Midwest
Northeast
South
West
Percent
on 1994-1996 CSFII (g/kg-day, as-consumed)
Percentile
consuming Mean
39.9
32.8
79.9
54.9
69.2
59.8
50
32.7
29.6
40
51.6
40.7
40.4
39.7
38.6
39.6
33.6
42.9
41.6
29
33.2
38.2
41.7
42.2
45.3
33.3
42.9
1.5
6.4
14.1
10.0
10.9
5.6
2.2
0.87
0.58
0.69
0.97
1.6
1.5
1.5
1.5
1.6
1.1
1.6
1.7
1.3
1.2
1.9
1.5
1.5
1.8
1.3
1.6
SE
0.06
1.6
1.2
1.0
0.47
0.28
0.14
0.09
0.05
0.03
0.06
0.11
0.10
0.11
0.12
0.11
0.10
0.08
0.35
0.17
0.57
0.29
0.06
0.11
0.13
0.10
0.12
1st
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10m
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25m
0
0
4.5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50m
0
0
11.8
4.5
5.7
2.7
0
0
0
0
0.11
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
75m
1.3
6.9
19.3
16.5
15.7
8.1
3.1
1.1
0.60
0.94
1.3
1.4
1.3
1.3
1.2
1.4
0.8
1.4
1.8
0.67
0.99
1.4
1.3
1.4
1.5
0.86
1.6
90th
3.8
23.7
32.7
30.1
29.4
15.8
6.3
2.9
2.0
2.2
2.8
4.0
3.8
3.7
3.4
4.3
2.8
3.9
5.0
3.3
3.8
4.3
3.7
3.7
4.5
3.2
4.2
95m
7.0
40.2
37.1
38.8
39.0
22.2
8.8
4.9
3.1
3.3
4.1
7.0
7.1
6.9
7.1
7.3
5.4
7.5
6.4
6.3
6.4
8.8
7.1
6.7
7.5
6.4
7.5
99th Max
22.6 101.3
48.5 63.4
63.7 69.6
58.5 69.6
65.8 101.3
35.0 77.1
17.6 32.2
8.8 14.9
6.2 16.0
6.3 18.6
7.5 18.6
22.5 101.3
20.9 77.1
23.7 81.1
21.2 83.6
23.6 83.6
16.5 65.8
23.7 101.3
22.1 61.9
22.4 101.3
14.0 40.8
28.4 69.6
21.6 83.6
21.0 101.3
24.6 81.1
20.4 81.3
22.1 83.6
SE = Standard error.
Source: U.S. EPA analysis of the
1994-1 996 CSFII.
Q
I
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a
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Table 9-19. Per Capita Intake of Protected Fruits Based
Population Percent
Group consuming
Whole Population 53
Age Group
0 to 5 months 10.8
6 to 12 months 49
<1 years 28.7
1 to 2 years 61.8
3 to 5 years 56.2
6 to 11 years 50.7
12 to 19 years 47.3
20 to 39 years 48
40 to 69 years 56.5
>70 years 68.7
Season
Fall 50.8
Spring 53.5
Summer 52.4
Winter 55.4
Urbanization
Central City 55.5
Non-metropolitan 45.6
Suburban 54.6
Race
Asian 62.3
Black 48.1
Native American 44 . 1
Other/NA 60.3
White 53
Region
Midwest 5 1
Northeast 62.5
South 47.6
West 55.3
SE = Standard error.
Source: U.S. EPA analysis of the
on 1994-1996 CSFII (g/kg-day, as-consumed)
Percentile
Mean
1.9
0.5
3.1
1.7
6.5
4.4
2.7
1.8
1.4
1.4
1.8
1.8
2.0
2.0
1.9
2.1
1.5
2.0
3.0
1.8
2.0
2.8
1.8
1.8
2.4
1.6
2.0
1994-1996
SE
0.04
0.34
0.58
0.39
0.31
0.22
0.17
0.12
0.07
0.04
0.07
0.08
0.08
0.08
0.07
0.07
0.08
0.06
0.30
0.11
0.65
0.21
0.04
0.08
0.09
0.06
0.09
CSFII.
1st
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25m
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50th
0.38
0
0
0
3.6
2.1
0.17
0
0
0.61
1.3
0.06
0.46
0.29
0.61
0.67
0
0.59
1.5
0
0
0.98
0.37
0.08
1.1
0
0.61
75m
2.6
0
4.4
2.0
9.2
6.7
3.8
2.6
1.9
2.2
2.8
2.3
2.6
2.7
2.6
2.8
1.9
2.7
4.1
2.2
2.5
3.9
2.5
2.4
3.2
2.1
2.8
90th
5.4
1.3
8.3
6.0
17.8
12.1
8.1
5.4
4.3
4.1
4.7
5.0
5.4
5.5
5.5
5.8
4.4
5.5
8.1
5.4
6.8
7.5
5.1
5.3
6.2
4.7
5.8
95m
8.1
4.3
11.2
8.3
24.2
17.2
11.4
8.4
6.3
5.5
5.9
7.3
8.8
8.4
8.0
8.5
7.0
8.3
11.7
8.1
7.9
10.8
7.7
7.8
9.5
7.1
8.4
99th
16.3
7.7
26.8
16.6
39.0
27.9
19.8
15.4
11.8
9.7
9.2
16.1
18.7
15.9
15.1
17.2
14.9
16.6
18.7
16.6
17.0
22.4
15.7
16.5
19.5
14.9
15.3
Max
113.4
12.5
30.3
30.3
113.4
66.5
31.7
27.0
39.3
45.8
27.6
75.7
47.4
113.4
52.0
66.5
61.9
113.4
64.0
50.1
61.9
113.4
75.7
75.7
66.5
65.7
113.4
Q
•*•
a-
QTQ
I
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a
A,
Table 9-20. Per Capita Intake of Exposed Vegetables
Population Percent
Group consuming
Whole Population 79.2
Age Group
0 to 5 months 6
6 to 12 months 40.8
<1 years 22.3
1 to 2 years 63.3
3 to 5 years 67.8
6 to 11 years 70.8
12 to 19 years 77.4
20 to 39 years 82.6
40 to 69 years 84
>70 years 83.2
Season
Fall 79.6
Spring 78.8
Summer 81.2
Winter 77.4
Urbanization
Central City 79.5
Non-metropolitan 78
Suburban 79.6
Race
Asian 82.2
Black 76.3
Native American 70.7
Other/NA 73.8
White 80.1
Region
Midwest 80.2
Northeast 79.4
South 79.6
West 77.5
SE = Standard error.
Source: U.S. EPA analysis of the
(g/kg-day, as-consumed)
Percentile
Mean
1.3
0.48
2.0
1.2
2.0
1.6
1.2
0.97
1.3
1.4
1.5
1.3
1.3
1.5
1.2
1.4
1.2
1.4
2.1
1.2
1.3
1.3
1.3
1.3
1.4
1.3
1.3
1994-1996
SE
0.02
0.62
0.49
0.37
0.11
0.08
0.06
0.04
0.03
0.02
0.05
0.03
0.03
0.03
0.03
0.03
0.03
0.02
0.15
0.04
0.40
0.08
0.02
0.03
0.04
0.03
0.04
CSFII.
1st
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25th
0.11
0
0
0
0
0
0
0.06
0.15
0.28
0.31
0.12
0.09
0.16
0.08
0.12
0.08
0.12
0.34
0.04
0
0
0.13
0.12
0.12
0.12
0.08
50th
0.80
0
0
0
0.59
0.67
0.60
0.53
0.81
0.97
1.09
0.79
0.79
0.92
0.74
0.83
0.69
0.85
1.39
0.66
0.45
0.73
0.82
0.81
0.91
0.78
0.78
75th
1.9
0
3.1
0
2.7
2.2
1.6
1.3
1.8
2.0
2.1
1.9
1.8
2.1
1.7
2.0
1.6
1.9
3.0
1.7
1.5
1.8
1.9
1.8
2.1
1.8
1.8
90th
3.4
0
5.8
5.0
5.8
4.4
3.4
2.5
3.2
3.3
3.6
3.4
3.3
3.5
3.2
3.5
2.9
3.4
4.9
3.3
2.0
3.3
3.3
3.3
3.5
3.2
3.4
95th
4.4
4.6
10.3
7.4
8.6
6.4
4.8
3.6
4.1
4.3
4.4
4.4
4.3
4.8
4.2
4.5
4.1
4.5
7.1
4.1
4.5
4.7
4.4
4.4
4.6
4.2
4.6
99th
7.6
11.8
14.7
14.7
14.9
12.8
8.1
5.8
6.9
6.4
7.2
7.3
7.9
8.6
7.0
8.1
6.9
7.8
13.0
7.2
9.5
10.4
7.2
7.1
7.9
7.1
8.9
Max
45.0
12.5
19.0
19.0
45.0
25.1
19.6
13.0
18.4
16.4
20.1
45.0
25.1
25.1
20.9
25.1
45.0
25.1
20.1
20.9
45.0
24.8
25.1
24.8
25.1
25.1
45.0
Q
I
a
I
(%
-a,
I
a
a,
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Table 9-21. Per Capita Intake of Protected Vegetables Based on 1994-1996 CSFH (g/kg-day, as-consumed)
Population Percent
Group consuming
Whole Population 38.0
Age Group
0 to 5 months 10.3
6 to 12 months 34.8
<1 years 21.8
1 to 2 years 40.8
3 to 5 years 38.2
6 to 11 years 38.8
12 to 19 years 30.4
20 to 39 years 36.7
40 to 69 years 41.2
>70 years 42.2
Season
Fall 37.9
Spring 37.8
Summer 39.3
Winter 37.1
Urbanization
Central City 38.9
Non-metropolitan 39.7
Suburban 36.6
Race
Asian 45.4
Black 36.2
Native American 32.0
Other/NA 50.4
White 37.2
Region
Midwest 36.3
Northeast 37.5
South 38.5
West 39.5
SE = Standard error.
Source: U.S. EPA analysis of the
Percentile
Mean
0.63
0.49
2.2
1.3
1.5
1.1
0.78
0.46
0.53
0.56
0.65
0.62
0.62
0.67
0.61
0.70
0.62
0.59
0.85
0.72
0.34
1.1
0.57
0.57
0.61
0.66
0.67
1994-1996
SE
0.02
0.41
0.55
0.37
0.13
0.09
0.07
0.06
0.04
0.03
0.05
0.04
0.04
0.04
0.04
0.04
0.04
0.03
0.14
0.07
0.13
0.10
0.02
0.04
0.05
0.03
0.04
CSFII.
1st
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.04
0
0
0
0
0
75th
0.73
0
4.4
0
1.9
1.4
1.0
0.44
0.61
0.73
0.86
0.71
0.67
0.85
0.71
0.78
0.75
0.68
1.1
0.77
0.13
1.5
0.68
0.62
0.75
0.78
0.75
90th
2.0
1.4
7.3
5.4
4.4
3.5
2.6
1.5
1.7
1.7
2.0
2.1
1.8
1.9
1.9
2.1
1.9
1.9
2.7
2.2
1.6
3.4
1.8
1.8
1.8
2.1
2.1
95th
3.1
3.9
9.6
7.8
7.0
5.4
3.9
2.4
2.7
2.6
3.1
3.2
2.9
3.1
3.0
3.4
3.1
2.9
4.1
3.5
2.0
5.2
2.8
2.9
2.9
3.1
3.3
99th
6.6
9.2
19.5
11.9
14.2
10.3
7.5
5.8
5.5
4.8
5.7
5.9
7.6
6.3
6.9
7.3
6.0
5.9
7.8
7.9
3.5
10.0
5.9
5.6
6.3
6.3
7.8
Max
45.8
11.0
23.1
23.1
27.8
18.0
26.5
21.6
23.6
45.8
21.5
21.6
23.6
45.8
27.8
45.8
25.8
27.8
23.3
45.8
5.3
26.5
27.8
21.5
27.8
45.8
23.1
Q
•*•
a-
QTQ
I
-------
8$
a
A,
Table 9-22. Per Capita Intake of Root Vegetables Based on 1994-1996 CSF1I (g/kg-day, as-consumed)
Population Percent
Group consuming
Whole Population 75.4
Age Group
0 to 5 months 12
6 to 12 months 56.9
<1 years 33
1 to 2 years 67.5
3 to 5 years 71.9
6 to 11 years 73.8
12 to 19 years 76.4
20 to 39 years 77.5
40 to 69 years 77.2
>70 years 73.2
Season
Fall 77-3
Spring 75.9
Summer 74
Winter 74.4
Urbanization
Central City 71.9
Non-metropolitan 78.5
Suburban 76.4
Race
Asian 64.2
Black 68.9
Native American 71.1
Other/NA 67
White 77.5
Region
Midwest 79.4
Northeast 72.3
South 77
West 71.3
SE = Standard error.
Source: U.S. EPA analysis of the
Percentile
Mean
1.2
0.96
2.8
1.8
2.6
2.2
1.6
1.3
1.1
0.99
1.1
1.3
1.2
1.2
1.2
1.2
1.4
1.2
0.97
1.1
1.4
1.1
1.3
1.4
1.1
1.3
1.1
1994-1996
SE
0.02
0.61
0.45
0.36
0.13
0.09
0.06
0.05
0.03
0.02
0.04
0.04
0.03
0.03
0.03
0.03
0.04
0.02
0.10
0.05
0.27
0.10
0.02
0.04
0.03
0.03
0.03
CSFII.
1st
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10th
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25th
0.03
0
0
0
0
0
0
0.09
0.10
0.08
0
0.09
0.05
0
0
0
0.14
0.07
0
0
0
0
0.09
0.16
0
0.09
0
50th
0.75
0
0.80
0
1.5
1.4
1.0
0.82
0.73
0.68
0.70
0.83
0.73
0.73
0.74
0.66
0.89
0.77
0.37
0.62
1.0
0.50
0.81
0.90
0.64
0.81
0.61
75th
1.7
0
4.6
2.3
3.6
3.2
2.3
1.8
1.6
1.5
1.6
1.8
1.7
1.6
1.7
1.6
1.9
1.7
1.3
1.4
1.9
1.4
1.8
2.0
1.5
1.8
1.5
90th
3.0
3.9
8.0
6.9
6.8
5.5
4.2
3.0
2.7
2.5
2.7
3.1
3.1
2.9
3.0
2.9
3.2
3.0
2.8
2.9
2.8
2.8
3.1
3.4
2.9
3.0
2.8
95th
4.1
8.3
10.4
9.6
8.3
7.1
5.3
4.0
3.5
3.2
3.4
4.2
4.3
3.9
4.1
4.2
4.5
4.0
4.0
4.2
3.0
3.7
4.2
4.6
3.8
4.1
3.7
99th
7.6
11.9
16.6
15.6
16.8
14.1
9.5
7.7
6.0
4.8
5.3
8.1
7.7
7.4
7.4
7.3
9.5
7.2
7.1
7.6
11.2
9.6
7.5
8.6
7.1
7.6
6.9
Max
83.3
21.9
32.9
32.9
83.3
32.1
20.6
22.5
16.6
15.1
9.8
83.3
30.0
25.8
34.3
83.3
34.3
26.1
17.3
32.9
34.3
83.3
32.1
26.1
20.7
83.3
34.3
Q
I
a
I
(%
-a,
I
a
a,
I
-------
Table 9-23. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and the Percentage of Individuals Consuming
These Foods in Two Days
Food category
Raw vegetables
Cucumbers
Lettuce
Mixed lettuce-based salad
Carrots
Tomatoes
Coleslaw
Onions
Cooked vegetables
Broccoli
Carrots
Total tomato sauce
String beans
Peas
Com
French-fried potatoes
Home-fried and hash-browned potatoes
Baked potatoes
Boiled potatoes
Mashed potatoes
Dried beans and peas
Baked beans
Fruits
Raw oranges
Orange juice
Raw apples
Applesauce and cooked apples
Apple juice
Raw bananas
Pprrpnt
jr ciuciii
Consuming3
10.8
53.3
2.2
14.1
32.0
5.0
14.4
7.3
5.8
54.3
13.2
6.1
15.1
25.5
8.9
12.4
5.3
15.0
8.0
4.7
7.9
27.2
15.6
4.6
7.0
20.8
Quantity consumed per
Consumers-only Quantity consumed per eating occasion
eating occasion (gram)
Average
48
41
97
33
53
102
23
119
72
34
90
86
101
83
135
120
157
188
133
171
132
268
135
134
271
111
SE
3
1
6
1
1
3
1
4
2
1
2
3
2
1
3
2
5
3
3
6
2
4
2
4
7
1
5
7
7
11
5
15
18
3
23
13
1
17
11
20
28
36
48
34
46
22
24
42
124
46
31
117
55
10
14
8
18
7
20
32
7
35
19
2
31
21
33
35
47
61
52
61
33
47
64
124
68
59
120
58
at specified percentiles (gram)
25
16
13
55
14
27
55
10
61
36
7
52
40
55
57
70
92
91
105
64
84
95
187
105
85
182
100
50
29
27
74
27
40
91
15
92
65
17
68
80
82
70
105
106
123
156
101
126
127
249
134
121
242
117
75
54
55
123
40
61
134
28
156
78
40
125
120
123
112
192
143
197
207
173
235
131
311
137
142
307
118
90
100
91
167
61
93
179
41
232
146
80
136
167
171
125
284
184
308
397
259
314
183
447
209
249
481
135
95
157
110
229
100
123
183
60
275
156
124
202
170
228
140
308
217
368
413
345
385
253
498
211
254
525
136
a = Percent consuming at least once in two days.
SE = Standard error of the mean.
Source: Smiciklas- Wright et al. , 2002
(based on 1994-1996 CSFII data).
Q
•*•
a-
QTQ
I
-------
a
A,
Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and
Consuming These Foods in Two Days, by Food
Percentage of Individuals
Quantity consumed per eating occasion (grams)
2 to 5 years
Food category
Carrots
Cucumbers
Lettuce
Onions
Tomatoes
Beans (string)
Broccoli
Carrots
Corn
Peas
Potatoes French-fried)
Potatoes home-fried and hash-browned)
Potatoes baked)
Potatoes moiled)
Potatoes (mashed)
Male and Female
(AT =2,109)
PC
10.4
6.4
34.0
3.9
14.8
16.8
7.2
6.0
18.9
8.4
32.7
9.3
7.6
4.8
14.8
Mean
27
32
17
9
31
50
61
48
68
48
52
85
70
81
118
SE
2
4
1
2
2
2
3
4
3
3
1
5
4
9
6
6 to 1 1 years
Male and Female
(AT =1,432)
PC
17.8
6.6
40.8
4.5
14.0
12.1
5.6
3.8
22.2
6.8
33.7
10.1
8.2
2.7
13.3
Mean
32
39
26
17
42
71
102
46
79
72
67
93
95
103a
162
SE
Raw\
2
6
1
2
4
Cooked
6
16
5
4
9
2
6
6^
12
12 to 19 years
Male
(W=696)
PC
fegetables
9.2
6.1
56.0
11.1
25.7
Vegetables
8.3
3.9
2.8
12.8
3.6
41.7
10.1
8.6
2.0
14.6
Mean
35
71a
32
28
49
85
127a
81a
125
115a
97
145
152
250a
245
SE
6
22a
3
4
5
9
17a
16a
9
15a
3
13
15
40a
16
PC
11.9
6.8
52.3
7.9
23.9
7.6
5.7
2.1
12.3
2.4
38.1
6.1
8.8
3.2
11.9
Female
(AT =702)
Mean
32
48
34
23
44
78
109a
75a
100
93a
81
138
115
144a
170
SE
4
11
2
4
3
5
14a
17a
6
17a
4
13
10
16a
17
Apples (raw)
Apples (cooked and applesauce)
Apple juice
Bananas (raw)
Oranges (raw)
Orange juice
26.8
10.1
26.3
25.0
11.1
34.4
106
118
207
95
103
190
2
5
5
2
5
4
21.9
9.0
12.2
16.5
10.5
30.9
123
130
223
105
114
224
3
7
10
3
5
6
11.7
2.3
7.8
10.3
4.3
30.8
149
153a
346
122
187a
354
9
19a
22
6
38a
16
12.4
2.6
8.5
8.4
5.4
29.5
129
200a
360
119
109a
305
5
47a
44
5
8a
11
Q
I
a
I
(%
-a,
I
a
a,
I
I
8
I
s»
I
&
a
1=
a
£.
-------
Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed Per Eating Occasion and Percentage of Individuals
Consuming These Foods in Two Days, by Food (continued)
Food category
Quantity
20 to <40 years
Male
(AT =1,543)
PC Mean SE
Female
(JV= 1,449)
PC
Mean SE
consumed per eating occasion (grams)
40 to <60 years
Male Female
(N= 1,663) (AT =1,694)
PC
Mean SE PC
Mean
SE
>60
Male
(AT =1,545)
PC Mean
SE
years
Female
(AT =1,429)
PC Mean
SE
Raw Vegetables
Carrots
Cucumbers
Lettuce
Onions
Tomatoes
12.3 35 4
10.5 62 12
63.4 40 2
17.9 27 2
33.1 57 2
15.4
10.4
57.6
14.7
32.3
38 4
45 4
44 2
22 1
49 2
14.4
12.5
55.5
19.6
38.1
35 2 18.1
47 4 15.7
48 2 59.1
26 1 18.3
60 2 42.4
31
41
48
19
53
2
3
1
1
1
13.6 29
14.2 51
48.1 47
19.0 19
40.0 62
2
4
2
1
3
12.7 27
13.2 45
46.1 42
15.6 19
41.0 52
1
3
2
1
2
Cooked Vegetables
Beans (string)
Broccoli
Carrots
Corn
Peas
Potatoes (French-fried)
Potatoes (home-fried/hash-browned)
Potatoes (baked)
Potatoes (boiled)
Potatoes (mashed)
10.6 111 5
7.6 152 13
5.0 79 7
12.7 122 5
4.4 109 10
35.3 107 2
9.5 160 10
11.4 154 7
3.9 185 16
14.7 269 12
12.5
6.7
5.3
15.3
4.9
23.9
8.8
11.1
2.9
13.5
89 6
129 13
69 6
98 5
82 9
79 3
129 7
126 5
162 15
167 5
13.7
7.8
6.7
17.1
7.4
20.6
11.
13.0
6.3
16.0
114 6 13.4
127 7 7.6
83 7 6.4
133 6 13.5
113 7 6.3
89 2 16.8
174 10 6.4
133 3 16.5
209 12 7.0
225 11 14.3
93
114
66
90
79
72
119
112
142
156
4
7
4
3
7
3
7
3
9
7
18.3 99
8.5 117
9.6 78
14.2 109
8.4 88
11.2 76
10.4 152
17.9 115
11.0 166
19.7 173
4
7
4
4
7
3
8
3
6
6
19.7 78
10.9 107
9.0 75
13.0 83
9.4 73
8.1 58
7.1 110
18.1 100
10.2 131
18.1 140
3
6
4
5
5
3
9
4
5
5
Fruits
Apples (raw)
Apples (cooked and applesauce)
Apple juice
Bananas (raw)
Oranges (raw)
Orange juice
6.6 153 8
24.3 373 20
12.1 161 6
1.3 153a 31a
4.2 345 20
14.4 126 2
6.3
23.2
12.9
2.4
4.7
18.5
126 6
289 12
134 3
155a 21a
302 19
112 2
7.4
24.1
14.1
3.1
4.7
21.9
148 8 8.3
285 10 25.2
145 3 16.2
142 12 3.9
358 33 3.2
125 3 24.4
132
231
136
125
259
111
5
6
4
10
21
2
8.9 133
30.2 213
17.6 145
8.1 135
4.8 233
36.5 105
5
5
8
10
11
2
11.2 129
31.7 196
16.1 128
9.2 121
5.0 225
34.0 96
4
5
3
7
13
2
a Indicates a statistic that is potentially unreliable because of a small sample size and a large SE.
PC = Percent consuming at least once in two days.
SE = Standard error of the mean.
N = Sample size.
Source: Smiciklas-Wright et al, 2002 (based on 1994-1996 CSFII data).
Q
•*•
a-
QTQ
I
-------
Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-25. Consumption of Major Food Groups: Median Servings (and Ranges) by
Demographic and Health Characteristics, for Older Adults
Subject Characteristic
Sex
Female
Male
Ethnicitya
African American
European American
Native American
Age
70 to 74 years
75 to 79 years
80 to 84 years
> 85 years
Marital Status
Married
Not Married
Education
8th grade or less
9th to 12th grades
> High School
Dentures
Yes
No
Chronic Diseases
0
1
2
3
4+
Weightb
130 pounds
131 to 150 pounds
151 to 170 pounds
171 to 190 pounds
191 pounds
'" p<0.05.
b Two missing values.
jV = Number of individuals.
Source: Vitolins et al, 2002.
N
80
50
44
47
39
42
36
36
16
49
81
37
47
46
83
47
7
31
56
26
10
18
32
27
22
29
Fruits and Vegetables
(servings per day)
5.7(1.5-8.1)
4.5 (0.8-8.8)
4.5 (0.8-8.0)
6.0(1.5-8.0)
4.5(1.6-8.8)
4.5(1.6-8.1)
5.6(0.8-8.0)
5.6(1.5-8.8)
5.4(1.8-8.0)
4.5(1.6-8.0)
5.6(0.8-8.8)
5.0(1.5-8.1)
4.5 (0.8-8.0)
6.0(1.5-8.8)
5.4(1.5-8.8)
4.7(0.8-8.0)
7.0(5.2-8.8)
5.4(1.5-8.0)
5.4(1.6-8.1)
4.5 (2.0-8.0)
5.5 (0.8-8.0)
6.0(1.8-8.0)
5.5(1.5-8.0)
5.7(1.7-8.1)
5.6(1.8-8.8)
4.5 (0.8-8.0)
Page
9-66
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-26. Characteristics
Sex
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing data
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition
Source: Devaney et al., 2004.
of the Feeding Infants and Toddlers Study
Sample Size
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
3,022
Program for Women, Infants, and Children.
(FITS) Sample Population
Percentage of Sample
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
100.0
Exposure Factors Handbook
September 2011
Page
9-67
-------
Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-27. Percentage
of Infants and Toddlers Consuming Different Types
of Vegetables
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
4to6 7to8 9 to 11
months months months
39.9
35.7
5.2
0.5
66.5
54.5
17.4
1.6
72.6
34.4
45.9
5.5
12 to 14
months
76.5
12.7
66.3
7.9
15 to 18 19 to 24
months months
79.2
3.0
72.9
14.3
81.6
1.6
75.6
18.6
Types of Vegetables8
Dark Green Vegetables'1
Deep Yellow Vegetables'
White Potatoes
French Fries and Other Fried Potatoes
Other Starchy Vegetables'1
Other Vegetables
0.1
26.5
3.6
0.7
6.5
11.2
2.9
39.3
12.4
2.9
10.9
25.9
4.2
29.0
24.1
8.6
16.9
35.1
5.0
24.0
33.2
12.9
17.3
39.1
10.4
13.6
42.0
19.8
20.8
45.6
a Totals include commercial baby food, cooked vegetables, and raw vegetables.
b Reported dark green vegetables include broccoli, spinach and other greens, and romaine lettuce.
' Reported deep yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
d Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava,
Source: Fox etal., 2004.
7.8
13.4
40.6
25.5
24.2
43.3
and rutabaga.
Page
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September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-28. Top Five Vegetables Consumed
Top Vegetables by Age Group8
by Infants and Toddlers
Percentage Consuming at Least Once in a Day
4 to 6 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Peas
9.6
9.1
8.1
7.2
5.0
7 to 8 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Mixed/Garden Vegetables
14.2
12.9
12.9
11.2
10.1
9 to 1 1 months
Cooked Green Beans
Mashed/Whipped Potatoes
French Fries/Other Fried Potatoes
Baby Food Mixed/Garden Vegetables
Cooked Carrots
9.7
9.0
8.6
8.4
8.0
12 to 14 months
Cooked Green Beans
French Fries/Other Fried Potatoes
Cooked Carrots
Mashed/Whipped Potatoes
Cooked Peas
18.2
12.9
11.5
10.3
8.4
15 to 18 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Peas
Cooked Tomatoes/Tomato Sauce
Mashed/Whipped Potatoes
19.8
16.7
13.9
13.7
12.4
19 to 24 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Corn
Cooked Peas
Cooked Tomatoes/Tomato Sauce
25.5
16.8
15.2
11.4
9.4
a Baby food vegetables include single vegetables (majority of vegetables reported) as well as mixtures with the named
vegetables the predominant vegetable, e.g., broccoli and cauliflower or broccoli and carrots.
Source: Fox etal., 2004.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-29. Percentage of Infants and Toddlers Consuming Different Types of Fruits
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Fruit
Baby Food Fruit
Non-Baby Food Fruit
4 to 6 months 7 to 8 months 9 to
41.9
39.1
5.3
75.5
67.9
14.3
1 1 months
75.8
44.8
44.2
12 to 14
months
77.2
16.2
67.1
15 to 18
months
71.8
4.2
69.4
19 to 24
months
67.3
1.8
66.8
Types of Non-Baby Food Fruit
Canned Fruit
Packed in Syrup
Packed in Juice or Water
Unknown Pack
Fresh Fruit
Dried Fruit
1.4
0.7
0.7
0.0
4.4
0.0
5.8
0.7
4.5
0.7
9.5
0.4
21.6
8.1
13.5
1.5
29.5
2.1
31.9
14.9
18.5
1.2
52.1
3.5
25.1
12.7
11.3
3.1
55.0
7.1
20.2
8.1
11.4
1.2
54.6
9.4
Types of Fruit8
Apples
Bananas
Berries
Citrus Fruits
Melons
a Totals include all baby
Source: Fox etal., 2004.
18.6
16.0
0.1
0.2
0.6
food and non-baby
33.1
30.6
0.6
0.4
1.0
food fruits.
31.6
34.5
5.3
1.6
4.4
27.5
37.8
6.6
4.9
7.3
19.8
32.4
11.3
7.3
7.2
22.4
30.0
7.7
5.1
9.6
Page
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Exposure Factors Handbook
Chapter 9 — Intake of Fruits and
Vegetables
Table 9-30. Top Five Fruits Consumed by Infants and Toddlers
Top Fruits by Age Group8
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
Fresh Banana
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Canned Applesauce
Fresh Banana
Canned Applesauce
Fresh Grapes
Fresh Apple
Canned Peaches
Canned Fruit Cocktail
Fresh Banana
Fresh Grapes
Fresh Apple
Fresh Strawberries
Canned Peaches
Fresh Banana
Fresh Apple
Fresh Grapes
Raisins
Fresh Strawberries
Percentage Consuming at Least Once in a Day
4 to 6 months
17.5
13.0
7.5
7.4
0.3
7 to 8 months
29.0
25.2
18.2
13.1
6.6
9 to 1 1 months
19.0
17.7
16.8
12.4
11.1
12 to 14 months
33.0
15.2
9.0
8.8
7.2
7.2
15 to 18 months
30.5
13.2
11.2
10.6
8.9
19 to 24 months
29.6
15.0
11.2
9.0
7.6
a Baby food fruits include single fruits (majority of fruits reported) as well as mixtures with the named fruit as the
predominant fruit, e.g., pears and raspberries or prunes with pears. Baby food fruits with tapioca and other baby food
dessert fruits were counted as desserts.
Source: Fox et al., 2004.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-31. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants"
(Percentages)
Infants 4 to 6 months
Infants 7 to 11 months
Toddlers 12 to 24 months
WIC
Participant
Non-Participant
WIC
Participant
Non-Participant
WIC
Participant
Non-Participant
Sex
Male 55
Female 45
Child's Ethnicity
Hispanic or Latino 20
Non-Hispanic or Latino 80
Child's Race
White 63
Black 15
Other 22
Child In Daycare
Yes 39
No 61
Age of Mother
14 to 19 years 18
20 to 24 years 33
25 to 29 years 29
30 to 34 years 9
>35 years 9
Missing 2
Mother's Education
11th Grade or Less 23
Completed High School 35
Some Postsecondary 33
Completed College 7
Missing 2
Parent's Marital Status
Married 49
Not Married 50
Missing 1
Mother or Female Guardian Works
Yes 46
No 53
Missing 1
Urbanicity
Urban 34
Suburban 36
Rural 28
Missing 2
Sample Size (Unweighted) 265
54
46
11
89
84
4
11
38
62
1
13
29
33
23
2
2
19
26
53
1
93
7
1
51
48
1
55
31
13
1
597
55
45
24
76
63
17
20
34
66
13
38
23
15
11
1
15
42
32
9
2
57
42
1
45
54
1
37
31
30
2
351
51
49
92
46
54
1
11
30
36
21
1
2
20
27
51
0
93
7
0
60
40
0
50
34
15
1
808
57
43
22
78
67
13
20
43
57
9
33
29
18
11
0
17
42
31
9
1
58
41
1
55
45
0
35
35
28
2
205
52
48
10
84
5
11
53
47
1
14
26
34
26
1
3
19
28
48
2
11
1
61
38
1
48
35
16
2
791
WIC
X2 tests were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of the %2 tests are listed next to the variable under the column labeled non-participants
for each of the three age groups.
p < 0.01 non-participants significantly different from WIC participants on the variable.
p < 0.05 non-participants significantly different from WIC participants on the variable.
= Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
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Exposure Factors Handbook
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-32. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
Participation Status
Infants 4 to 6 months
WIC
Participant
Non-
Infants 7 to 1 1 months
WIC
Participant Participant
Non-
Participant
Toddlers 12 to 24 months
WIC
Participant
Non-
Participant
Vegetables
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
Dark Green Vegetables
Deep Yellow Vegetables
Other Starchy Vegetables
Potatoes
40.2
32.9
8.0
1.4
0.4
23.2
6.5
6.0
39.8
37.0
3.9a
O.lb
0.0
28.1
6.4
2.4a
68.2
38.2
33.8
3.6
2.9
30.1
12.9
20.7
70.7
45.0
33.8
4.1
4.0
34.8
15.2
18.2
77.5
4.8
73.1
11.8
6.3
12.5
21.1
43.1
80.2
4.7
72.3
15.4
8.4
16.9
21.5
38.3
Fruits
Any Fruit
Baby Food Fruits
Non-Baby Food Fruit
Fresh Fruit
Canned Fruit
Sample Size (unweighted)
47.8
43.8
8.1
5.4
3.4
265
39.2a
36.9
4.0
3.8
0.5b
597
64.7
48.4
22.9
14.3
10.3
351
81. Ob
57.4a
35.9b
24.3b
17.3b
808
58.5
3.8
56.4
43.6
22.3
205
74.6b
6.5
70. 9b
57.0b
25.3
791
" =p <0.05 non-participants significantly different from WIC participants.
b =p <0.01 non-participants significantly
different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women,
Source: Ponza et al., 2004.
Infants, and Children.
Exposure Factors Handbook
September 2011
Page
9-73
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-33. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Infants from
the 2002 Feeding Infants and Toddlers
4 to 5 months
Food group
Reference
unit
(A? =624)
Study
6 to 8 months
(A? =708)
Mean ± SE
9 to 1 1 months
(A? = 687)
Fruits and Juices
All fruits
Baby food fruit
Baby food peaches
Baby food pears
Baby food bananas
Baby food applesauce
Canned fruit
Fresh fruit
100% juice
Apple/apple blends
Grape
Pear
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
fluid ounce
fluid ounce
fluid ounce
fluid ounce
3.6 ±0.19
3.3 ±0.16
3.6 ±0.37
3. 5 ±0.46
3.4 ±0.23
3.7 ±0.29
-
-
2.5 ±0.17
2.7 ±0.22
-
-
4.7 ±0.11
4.6 ±0.11
4.4 ±0.26
4.5 ±0.21
5.0 ±0.21
4.6 ±0.17
4.5 ±0.59
5.3 ±0.52
2.8±0.11
2.9 ±0.13
2.6 ±0.19
2.6 ±0.29
5.8 ±0.17
5.6 ±0.17
5.3 ±0.36
6.0 ±0.40
5.9 ±0.35
5.6 ±0.25
4.8 ±0.25
6.4 ±0.37
3.1 ±0.09
3.2±0.11
3.1 ±0.21
3.1 ±0.28
Vegetables
All vegetables
Baby food vegetables
Baby food green beans
Baby food squash
Baby food sweet
Baby food carrots
Cooked vegetables, excluding French fries
Deep yellow vegetables
Mashed potatoes
Green beans
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
3. 8 ±0.20
4.0 ±0.20
3. 5 ±0.33
4.3 ± 0.47
4.3 ±0.31
3. 5 ±0.33
-
-
-
-
5.8 ±0.16
5.9 ±0.16
5.1 ±0.28
5.6 ±0.30
6.1 ±0.34
5.6 ±0.27
4.2 ±0.47
3.2 ±0.59
4.1 ±0.67
3.2 ±0.62
5.6 ±0.20
6.6 ±0.21
6.1 ±0.50
6.9 ±0.41
7.2 ±0.69
6.7 ±0.48
3.8 ±0.31
3.2 ±0.39
2.8 ±0.37
5.0 ±0.61
= Cell size was too small to generate a reliable estimate.
N = Number of respondents.
SE = Standard error.
Source: Fox et al., 2006.
Page
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Exposure Factors Handbook
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-34. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study
Food group
Reference
unit
12 to 14 months
(JV = 371)
15 to 18 months
(JV=312)
Mean ± SE
19 to 24 months
(A? = 320)
Fruits and Juices
All fruits
Canned fruit
Fresh fruit
Fresh apple
Fresh banana
Fresh grapes
100% juice
Orange/orange blends
Apple/apple blends
Grape
All vegetables
Cooked vegetables,
excluding French fries
Deep yellow vegetables
Corn
Peas
Green beans
Mashed potatoes
Baked/boiled potatoes
French fries
cup
cup
cup
cup, slice
1 medium
cup, slice
1 medium
cup
fluid ounce
fluid ounce
fluid ounce
fluid ounce
Vej
cup
cup
cup
cup
cup
cup
cup
cup
cup
0.4 ±0.02
0.3 ±0.02
0.4 ±0.02
0.4 ±0.05
0.3 ±0.04
0.4 ±0.02
0.6 ±0.03
0.2 ±0.01
3.7±0.15
3.3 ±0.38
3.6 ±0.21
3.6 ±0.38
jetables
0.4 ±0.02
0.3 ±0.03
0.2 ±0.03
0.2 ±0.03
0.2 ±0.02
0.4 ±0.05
0.3 ±0.05
0.3 ±0.05
0.4 ±0.05
0.5 ±0.03
0.4 ±0.03
0.5 ±0.03
0.6 ±0.07
0.5 ±0.06
0.5 ±0.03
0.7 ±0.03
0.3 ± 0.03
5.0 ±0.20
4.5 ±0.33
4.5 ± 0.29
5.6 ±0.43
0.4 ±0.03
0.3 ± 0.03
0.3 ±0.05
0.2 ±0.03
0.2 ±0.02
0.4 ±0.05
0.4 ±0.05
0.4 ±0.06
0.6 ±0.05
0.6 ±0.03
0.4 ±0.04
0.6 ±0.03
0.8 ±0.14
0.6 ±0.11
0.5 ±0.03
0.7 ±0.04
0.3 ±0.02
5.1±0.18
5.2 ±0.35
4.9 ±0.27
4.7 ±0.31
0.4 ±0.02
0.3 ±0.02
0.3 ±0.05
0.2 ±0.03
0.2 ±0.02
0.3 ±0.03
0.3 ±0.05
-
0.6 ±0.05
Cell size too small to generate reliable estimate.
N = Number of respondents.
SE = Standard error of the mean.
Source: Fox et al., 2006.
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 9 — Intake of Fruits and Vegetables
Table 9-35. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types
of Fruits and Vegetables on a Given Day
Age 4 to 5 months Age 6 to 1 1 months Age 12 to 24 months
Hispanic Non-Hispanic Hispanic Non-Hispanic Hispanic
(AT =84) (A?=538) (AT =163) (AT =1,228) (N= 124)
Non-Hispanic
(A? =871)
Fruits
Any Fruit or 100% Fruit Juice 45.0 35.9 86.2 86.8 84.6
Any Fruit8 39.4 28.8 68.1 76.0 67.6
100% Fruit Juice 19.3 15.3 57.8 47.7 64.1
Fruit Preparation
Baby Food Fruit 32.6 28.4 42.9b 58.1 5.6C
Non-Baby Food Fruit 9.1C 1.3° 35.8 27.4 64.2
Canned Fruit 2.3<= - 8.8 13.7 12.111
Fresh Fruit 9.1b,c . 30.011 17.7 59.3
87.2
71.5
58.9
6.3
68.0
26.2
53.1
Vegetables
Any Vegetable or 100% Vegetable Juicee 30.0 27.3 66.2 70.3 76.0
Type of Preparation
Baby Food Vegetables 25.7 25.4 34. 4b 47.6 4.1=
Cooked Vegetables 4.2C 2.4C 33.2 29.4 71.4
Raw Vegetables 2.3° - 8.3C 2.6 25.0
Types of Vegetables'
Dark Green Vegetables' - - 3.3C 3.1 11. 4C
Deep Yellow Vegetables8 21.0 18.2 32.2 25.9 20.0
Starchy Vegetable:
White Potatoes 1.40 2.3C 20.7 17.4 43.5
French Fries/Fried Potatoes - - 570 5.3 23.4
Baked/Mashed . - 1440 10.7 19.8
Other Starchy Vegetables'1 5 o<= 4.0 6.711 15-1 16.6
Other Non-Starchy Vegetables1 g jc 8.0 28.5 29-° 42.0
a Total includes all baby food and non-baby food fruits and excludes 100% fruit juices and juice drinks.
b = Significantly different from non-Hispanic at the p < 0.05.
c = Statistic is potentially unreliable because of a high coefficient of variation.
d = Significantly different from non-Hispanic at the p < 0.01.
e Total includes commercial baby food, cooked vegetables, raw vegetables, and 100% vegetable juices.
f Reported dark green vegetables include broccoli, spinach, romaine lettuce, and other greens such as kale.
8 Reported yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
h Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava,
Corn is also shown as a subcategory of other starchy vegetables.
1 Reported non-starchy vegetables include asparagus, cauliflower, cabbage, onions, green beans, mixed vegetables,
tomatoes.
= Less than 1% of the group consumed this food on a given day.
N = Sample size.
Source: Mennella et al., 2006.
80.5
4.9
72.9
13.1
7.5
15.4
39.0
20.3
17.7
22.2
43.4
and rutabaga.
peppers, and
Page
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Chapter 9—Intake of Fruits and Vegetables
Table 9-36. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants and
Toddlers Per Age Group"
Age (month) N
4 to 5
6 to 11
12 to 24
4to5
6 to 11
12 to 24
N
Source:
84 Hispanic
538 non-Hispanic
136 Hispanic
1,228 non-Hispanic
124 Hispanic
871 non-Hispanic
84 Hispanic
538 non-Hispanic
136 Hispanic
1,228 non-Hispanic
124 Hispanic
871 non-Hispanic
Hispanic
Bananas (16.3%)
Apples (14.7%)
Peaches (10.9%)
Melons (3.5%)
Pears (2.5%)
Bananas (35.9%)
Apples (29.7%)
Pears (15.2%)
Peaches (11.7%)
Melons (4.7%)
Bananas (41.5%)
Apples (25.7%)
Berries (8.5%)
Melons (7.6%)
Pears (7.3%)
Top Vegetables By A;
Carrots (9.9%)
Sweet Potatoes (6.8%)
Green Beans (5.8%)
Peas (5.0%)
Squash (4.3%)
Potatoes (20.7%)
Carrots (19.0%)
Mixed Vegetables (11. 1%)
Green Beans (11.0%)
Sweet Potatoes (8.7%)
Potatoes (43. 5%)
Tomatoes (23. 1%)
Carrots (18. 6%)
Onions (11. 8%)
Corn (10.2%)
Ethnicity
Non-Hispanic
Top Fruits By Age Group
Apples (12.5%)
Bananas (10.0%)
Pears (5.9%)
Peaches (5. 8%)
Prunes (1.6%)
Apples (32.9%)
Bananas (31.5%)
Pears (17.5%)
Peaches (13.9%)
Apricots (3.7%)
Bananas (30.9%)
Apples (22.0%)
Grapes (12.3%)
Peaches (9.6%)
Berries (8.7%)
je Group
Sweet Potatoes (7.5%)
Carrots (6.6%)
Green Beans (5.9%)
Squash (5.4%)
Peas (3.8%)
Carrots (17.5%)
Potatoes (16.4%)
Green Beans (15.9%)
Squash (11. 8%)
Sweet Potatoes (11. 4%)
Potatoes (39.0%)
Green Beans (19.6%)
Peas (12.8%)
Carrots (12.3%)
Tomatoes (11.9%)
Percentage consuming at least one in a day is in parentheses.
= Sample size.
Mennella et al., 2006.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions
Food
Moisture Content
Raw
Cooked
— Comments
Fruits
Apples — dried
Apples
Apples — juice
Applesauce
Apricots
Apricots — dried
Bananas
Blackberries
Blueberries
Boysenberries
Cantaloupes
Casabas
Cherries — sweet
Crabapples
Cranberries
Cranberries — juice cocktail
Currants (red and white)
Elderberries
Grapefruit (pink, red and white)
Grapefruit — juice
Grapefruit — unspecified
Grapes — fresh
Grapes — juice
Grapes — raisins
Honeydew melons
Kiwi fruit
Kumquats
Lemons — juice
Lemons — peel
Lemons — pulp
Limes
Limes — juice
Loganberries
Mulberries
Nectarines
Oranges — unspecified
Peaches
Pears — dried
Pears — fresh
Pineapple
Pineapple — juice
Plums — dried (prunes)
Plums
Quinces
Raspberries
Strawberries
Tangerine — juice
Tangerines
Watermelon
31.76
85.56*
86.67**
-
-
86.35
30.09
74.91
88.15
84.21
85.90
90.15
91.85
82.25
78.94
87.13
85.00
83.95
79.80
90.89
90.00
90.89
81.30
84.12
15.43
89.82
83.07
80.85
90.73
81.60
88.98
88.26
90.79
84.61*
87.68
87.59
86.75
88.87
26.69
83.71
86.00
-
30.92
87.23
83.80
85.75
90.95
88.90
85.17
91.45
84.13*
-
-
87.93
88.35*
86.62*
75.56*
-
-
86.59*
-
-
-
84.95*
-
-
-
-
-
-
90.10*
-
-
-
-
-
-
-
92.46*
-
-
-
92.52*
-
-
-
-
87.49*
64.44*
86.47*
83.51*
86.37
-
84.02*
-
-
89.97*
87.00*
89.51*
-
sulfured; * without added sugar
*with skin
** without skin
canned or bottled
*unsweetened
* canned juice pack with skin
sulfured; *without added sugar
*frozen unsweetened
frozen unsweetened
* canned, juice pack
Bottled
* canned unsweetened
pink, red, white
American type (slip skin)
canned or bottled
Seedless
* canned or bottled
* canned or bottled
*frozen
all varieties
* canned juice pack
sulfured; *without added sugar
* canned juice pack
* canned juice pack
Canned
* canned juice pack
*frozen unsweetened
* canned sweetened
* canned juice pack
Page
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Chapter 9—Intake of Fruits and Vegetables
Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions (continued)
Food
Moisture Content
Raw
Cooked
Vegetables
Alfalfa seeds — sprouted
Artichokes — globe and French
Artichokes — Jerusalem
Asparagus
Bamboo shoots
Beans — dry — blackeyed peas (cowpeas)
Beans — dry — hyacinth (mature seeds)
Beans — dry — navy (mature seeds)
Beans — dry — pinto (mature seeds)
Beans — lima
Beans — snap — green — yellow
Beets
Beets — tops (greens)
Broccoli
Brussel sprouts
Cabbage — Chinese (pak-choi)
Cabbage — red
Cabbage — savoy
Carrots
Cassava (yucca blanca)
Cauliflower
Celeriac
Celery
Chives
Cole slaw
Collards
Corn — sweet
Cress — garden
Cucumbers — peeled
Dandelion — greens
Eggplant
Endive
Garlic
Kale
Kohlrabi
Lambsquarter
Leeks — bulb and lower leaf-portion
Lentils — sprouted
Lettuce — iceberg
Lettuce — cos or romaine
Mung beans — mature seeds (sprouted)
Mushrooms — unspecified
Mushrooms — oyster
Mushrooms — Maitake
Mushrooms — portabella
Mustard greens
Okra
Onions
Onions — dehydrated or dried
Parsley
Parsnips
Peas — edible-podded
Peppers — sweet — green
Peppers — hot chili-green
92.82
84.94
78.01
93.22
91.00
77.20
87.87
79.15
81.30
70.24
90.27
87.58
91.02
90.69
86.00
95.32
90.39
91.00
88.29
59.68
91.91
88.00
95.43
90.65
81.50
90.55
75.96
89.40
96.73
85.60
92.41
93.79
58.58
84.46
91.00
84.30
83.00
67.34
95.64
94.61
90.40
-
88.80
90.53
91.20
90.80
90.17
89.11
3.93
87.71
79.53
88.89
93.89
87.74
84.08
-
92.63
95.92
75.48
86.90
76.02
93.39
67.17
89.22
87.06
89.13
89.25
88.90
95.55
90.84
92.00
90.17
-
93.00
92.30
94.11
-
-
91.86
69.57
92.50
-
89.80
89.67
-
-
91.20
90.30
88.90
90.80
68.70
-
-
93.39
91.08
-
-
-
94.46
92.57
87.86
-
-
80.24
88.91
91.87
92.50*
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
stir-fried
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
* canned solids and liquid
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 9—Intake of Fruits and Vegetables
Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions (continued)
Food
Potatoes (white)
Pumpkin
Radishes
Rutabagas — unspecified
Salsify (vegetable oyster)
Shallots
Soybeans — mature seeds — sprouted
Spinach
Squash — summer
S quash — winter
Sweet potatoes
Swiss chard
Taro — leaves
Taro
Tomatoes — juice
Tomatoes — paste
Tomatoes — puree
Tomatoes
Towel gourd
Turnips
Turnips — greens
Water chestnuts — Chinese
Yambean — tuber
Moisture Content
Raw
81.58
91.60
95.27
89.66
77.00
79.80
69.05
91.40
94.64
89.76
77.28
92.66
85.66
70.64
-
-
-
93.95
93.85
91.87
89.67
73.46
90.07
Indicates data are not available for the fruit or veg
* Number without added sugar.
Source: USDA, 2007.
Cooked
75.43
93.69
-
88.88
81.00
-
79.45
91.21
93.70
89.02
75.78
92.65
92.15
63.80
93.90
73.50
87.88
-
84.29
93.60
93.20
86.42*
90.07
— Comments
Baked
boiled, drained
boiled, drained
boiled, drained
Steamed
boiled, drained
all varieties; boiled, drained
all varieties; baked
baked in skin
boiled, drained
Steamed
Canned
Canned
Canned
boiled, drained
boiled, drained
boiled, drained
* canned solids and liquids
boiled, drained
etable under those conditions.
Page
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Chapter 10—Intake of Fish and Shellfish
TABLE OF CONTENTS
LIST OF TABLES 10-iii
LIST OF FIGURES 10-vi
10. INTAKE OF FISH AND SHELLFISH 10-1
10.1. INTRODUCTION 10-1
10.2. RECOMMENDATIONS 10-4
10.2.1. Recommendations—General Population 10-4
10.2.2. Recommendations—Recreational Marine Anglers 10-5
10.2.3. Recommendations—Recreational Freshwater Anglers 10-5
10.2.4. Recommendations—Native American Populations 10-6
10.3. GENERAL POPULATION STUDIES 10-15
10.3.1. Key General Population Study 10-15
10.3.1.1. U.S. EPA Analysis of Consumption Data from 2003-2006 NHANES 10-15
10.3.2. Relevant General Population Studies 10-16
10.3.2.1. Javitz (1980) 10-16
10.3.2.2.Paoetal. (1982) 10-17
10.3.2.3.USDA(1992a) 10-17
10.3.2.4.U.S. EPA (1996) 10-18
10.3.2.5.Stern etal. (1996) 10-18
10.3.2.6.U.S. EPA (2002) 10-19
10.3.2.7. Westat (2006) 10-20
10.3.2.8.Moyaetal. (2008) 10-21
10.3.2.9.Mahaffey etal. (2009) 10-21
10.4. MARINE RECREATIONAL STUDIES 10-21
10.4.1. Key Marine Recreational Study 10-21
10.4.1.1.National Marine Fisheries Service (1986a,b,c, 1993) 10-21
10.4.2. Relevant Marine Recreational Studies 10-23
10.4.2.1.Pierce etal. (1981) 10-23
10.4.2.2. Puffer etal. (1981) 10-24
10.4.2.3.Burger and Gochfeld (1991) 10-25
10.4.2.4. Burger etal. (1992) 10-26
10.4.2.5.Moya and Phillips (2001) 10-26
10.4.2.6.KCA Research Division (1994) 10-27
10.4.2.7. Santa Monica Bay Restoration Project (SMBRP) (1994) 10-27
10.4.2.8.U.S. DHHS (1995) 10-28
10.4.2.9. Alcoa (1998) 10-29
10.4.2.10. Burger etal. (1998) 10-30
10.4.2.11. Chiang (1998) 10-30
10.4.2.12. San Francisco Estuary Institute (SFEI) (2000) 10-31
10.4.2.13. Burger (2002a) 10-31
10.4.2.14. Mayfield et al. (2007) 10-32
10.5. FRESHWATER RECREATIONAL STUDIES 10-32
10.5.1. Fioreetal. (1989) 10-32
10.5.2. West etal. (1989) 10-33
10.5.3. Chemrisk (1992) 10-35
10.5.4. Connelly etal. (1992) 10-37
10.5.5. Hudson River Sloop Clearwater, Inc. (1993) 10-37
10.5.6. West etal. (1993) 10-38
10.5.7. Alabama Dept. of Environmental Management (ADEM) (1994) 10-39
10.5.8. Connelly etal. (1996) 10-39
10.5.9. Balcometal. (1999) 10-40
10.5.10. Burger etal. (1999) 10-41
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September 2011 10-i
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Chapter 10—Intake of Fish and Shellfish
TABLE OF CONTENTS (continued)
10.5.11. Williams etal. (1999) 10-42
10.5.12. Burger (2000) 10-42
10.5.13. Williams et al. (2000) 10-43
10.5.14. Benson etal. (2001) 10-43
10.5.15. Moya and Phillips (2001) 10-44
10.5.16. Campbell et al. (2002) 10-44
10.5.17. Burger (2002b) 10-45
10.5.18. Mayfield et al. (2007) 10-45
10.6. NATIVE AMERICAN STUDIES 10-46
10.6.1. Wolfe and Walker (1987) 10-46
10.6.2. Columbia River Inter-Tribal Fish Commission (CRITFC) (1994) 10-47
10.6.3. Peterson etal. (1994) 10-48
10.6.4. Fitzgerald etal. (1995) 10-49
10.6.5. Fortietal. (1995) 10-50
10.6.6. Toy etal. (1996) 10-51
10.6.7. Duncan (2000) 10-52
10.6.8. Westat(2006) 10-53
10.6.9. Polissar et al. (2006) 10-53
10.7. OTHER POPULATION STUDIES 10-54
10.7.1. U.S. EPA (1999) 10-54
10.8. SERVING SIZE STUDIES 10-55
10.8.1. Pao etal. (1982) 10-55
10.8.2. Smiciklas-Wright et al. (2002) 10-56
10.9. OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION 10-56
10.9.1. Conversion between Wet and Dry Weight 10-56
10.9.2. Conversion Between Wet-Weight and Lipid-Weight Intake Rates 10-57
10.10. REFERENCES FOR CHAPTER 10 10-57
APPENDIX 10A: RESOURCE UTILIZATION DISTRIBUTION 10A-1
APPENDIX 10B: FISH PREPARATION AND COOKING METHODS 10B-1
Page Exposure Factors Handbook
10-ii September 2011
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Chapter 10—Intake of Fish and Shellfish
LIST OF TABLES
Table 10-1. Recommended Per Capita and Consumer-Only Values for Fish Intake (g/kg-day),
Uncooked Fish Weight, by Age 10-7
Table 10-2. Confidence in Recommendations for General Population Fish Intake 10-8
Table 10-3. Recommended Values for Recreational Marine Fish Intake 10-9
Table 10-4. Confidence in Recommendations for Recreational Marine Fish Intake 10-10
Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake 10-11
Table 10-6. Summary of Relevant Studies on Native American Fish Intake 10-13
Table 10-7. Per Capita Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-62
Table 10-8. Consumer-Only Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-63
Table 10-9. Per Capita Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-64
Table 10-10. Consumers-Only Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 10-65
Table 10-11. Per Capita Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion,
Uncooked Fish Weight 10-66
Table 10-12. Consumer-Only Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible
Portion, Uncooked Fish Weight 10-67
Table 10-13. Total Fish Consumption, Consumers Only, by Demographic Variables 10-68
Table 10-14. Percent Distribution of Total Fish Consumption for Females and Males by Age 10-70
Table 10-15. Mean Total Fish Consumption by Species 10-71
Table 10-16. Best Fits of Lognormal Distributions Using the Non-Linear Optimization Method 10-72
Table 10-17. Mean Fish Intake inaDay, by Sex and Age 10-72
Table 10-18. Percent of Respondents That Responded Yes, No, or Don't Know to Eating Seafood in 1
Month (including shellfish, eels, or squid) 10-73
Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of
Seafood in 1 Month 10-75
Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was
Purchased or Caught by Someone They Knew 10-77
Table 10-21. Distribution of Fish Meals Reported by NJ Consumers During the Recall Period 10-78
Table 10-22. Selected Species Among All Reported Meals by NJ Consumers During the Recall Period 10-79
Table 10-23. Cumulative Probability Distribution of Average Daily Fish Consumption (g/day) 10-79
Table 10-24. Distribution of the Usual Frequency of Fish Consumption 10-79
Table 10-25. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
Population, as Prepared 10-80
Table 10-26. Daily Average Per Capita Estimates of Fish Consumption: U.S. Population—Mean
Consumption by Species Within Habitat, as Prepared 10-81
Table 10-27. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U. S.
Population, Uncooked Fish Weight 10-82
Table 10-28. Daily Average Per Capita Estimates of Fish Consumption U.S. Population—Mean
Consumption by Species Within Habitat, Uncooked Fish Weight 10-83
Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepared 10-84
Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared 10-86
Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish
Weight 10-88
Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
Weight 10-90
Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepared 10-92
Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as
Prepared 10-94
Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked
Fish Weight 10-96
Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day),
Uncooked Fish Weight 10-98
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Chapter 10—Intake of Fish and Shellfish
LIST OF TABLES (continued)
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics (g/kg-day, as-consumed) 10-100
Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics (g/kg-day, as-consumed) 10-104
Table 10-39. Fish Consumption per kg Body Weight, all Respondents by State, Acquisition Method,
(g/kg-day, as-consumed) 10-108
Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method
(g/kg-day, as-consumed) 10-111
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day) 10-114
Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics, Uncooked (g/kg-day) 10-118
Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition Method,
Uncooked (g/kg-day) 10-122
Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,
Uncooked (g/kg-day) 10-125
Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and
Sex (g/kg-day, as-consumed) 10-128
Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex 10-130
Table 10-47. Fish Consumption Among General Population in Four States, Consumers Only (g/kg-
day, as-consumed) 10-133
Table 10-48. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion... 10-135
Table 10-49. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational
Fishermen, by Wave and Subregion 10-136
Table 10-50. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status 10-137
Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B l)a by Marine Recreational
Fishermen, by Species Group and Subregion 10-138
Table 10-52. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement
Bay, Washington 10-139
Table 10-53. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler
Populations Based on the Re-Analysis of the Puffer et al. (1981) and Pierce et al. (1981)
Data 10-139
Table 10-54. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their
Family/Living Group 10-140
Table 10-55. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport
Fishermen in the Metropolitan Los Angeles Area 10-140
Table 10-56. Catch Information for Primary Fish Species Kept by Sport Fishermen (N = 1,059) 10-141
Table 10-57. Fishing and Crabbing Behavior of Fishermen at Humacao, Puerto Rico 10-141
Table 10-58. Fish Consumption of Delaware Recreational Fishermen and Their Households 10-142
Table 10-59. Seafood Consumption Rates of All Fish by Ethnic and Income Groups of Santa Monica
Bay 10-143
Table 10-60. Means and Standard Deviations of Selected Characteristics by Population Groups in
Everglades, Florida 10-143
Table 10-61. Grams per Day of Self-Caught Fish Consumed by Recreational Anglers—Alcoa/Lavaca
Bay 10-144
Table 10-62. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational
Anglers Lavaca Bay, Texas 10-145
Table 10-63. Consumption Patterns of People Fishing and Crabbing in Barnegat Bay, New Jersey 10-146
Table 10-64. Fish Intake Rates of Members of the Laotian Community of West Contra Costa County,
California 10-146
Table 10-65. Consumption Rates (g/day) Among Recent Consumers3 by Demographic Factor 10-147
Page
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Chapter 10—Intake of Fish and Shellfish
LIST OF TABLES (continued)
Table 10-66. Mean + SD Consumption Rates for Individuals Who Fish or Crab in the Newark Bay
Area 10-148
Table 10-67. Consumption Rates (g/day) for Marine Recreational Anglers in King County, WA 10-148
Table 10-68. Percentile and Mean Intake Rates for Wisconsin Sport Anglers (all respondents) 10-149
Table 10-69. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households with
Recreational Fish Consumption 10-149
Table 10-70. Comparison of 7-Day Recall and Estimated Seasonal Frequency for Fish Consumption 10-150
Table 10-71. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and
Consumed Recreationally Caught Fish 10-150
Table 10-72. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989-
1990 Ice Fishing or 1990 Open-Water Seasons 10-151
Table 10-73. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day) 10-152
Table 10-74. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the
1990 Season 10-152
Table 10-75. Socio-Demographic Characteristics of Respondents 10-153
Table 10-76. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish
Consumption Study, 1991-1992 10-154
Table 10-77. Mean Per Capita Freshwater Fish Intake of Alabama Anglers 10-155
Table 10-78. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) for
1992 Lake Ontario Anglers 10-155
Table 10-79. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by Socio-
Demographic Characteristics 10-156
Table 10-80. Seafood Consumption Rates of Nine Connecticut Population Groups 10-156
Table 10-81. Fishing Patterns and Consumption Rates of People Fishing Along the Savannah River
(Mean±SE) 10-157
Table 10-82. Fish Consumption Rates for Indiana Anglers—Mail Survey (g/day) 10-158
Table 10-83. Fish Consumption Rates for Indiana Anglers—On-Site Survey (g/day) 10-158
Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North Dakota
Residents (g/day) 10-159
Table 10-85. Fishing Patterns and Consumption Rates of Anglers Along the Clinch River Arm of
Watts Bar Reservoir (Mean ± SE) 10-161
Table 10-86. Daily Consumption of Wild-Caught Fish, Consumers Only (g/kg-day, as-consumed) 10-161
Table 10-87. Consumption Rates (g/day) for Freshwater Recreational Anglers in King County, WA 10-162
Table 10-88. Number of Grams per Day of Fish Consumed by All Adult Respondents (consumers and
non-consumers combined)—Throughout the Year 10-162
Table 10-89. Fishlntake Throughout the Year by Sex, Age, and Location by All Adult Respondents 10-163
Table 10-90. Fish Consumption Rates Among Native American Children (Age 5 Years and Under) 10-163
Table 10-91. Number of Fish Meal Eaten per Month and Fish Intake Among Native American
Children Who Consume Particular Species 10-164
Table 10-92. Socio-Demographic Factors and Recent Fish Consumption 10-164
Table 10-93. Number of Local Fish Meals Consumed per Year by Time Period for All Respondents 10-165
Table 10-94. Mean Number of Local Fish Meals Consumed per Year by Time Period for All
Respondents and Consumers Only 10-165
Table 10-95. Mean Number of Local Fish Meals Consumed per Year by Time Period and Selected
Characteristics for All Respondents (Mohawk, N = 97; Control, N = 154) 10-166
Table 10-96. Fish Consumption Rates for Mohawk Native Americans (g/day) 10-166
Table 10-97. Percentiles and Mean of Adult Tribal Member Consumption Rates (g/kg-day) 10-167
Table 10-98. Median and Mean Consumption Rates by Sex (g/kg-day) within Each Tribe 10-168
Table 10-99. Median Consumption Rate for Total Fish by Sex and Tribe (g/day) 10-168
Table 10-100. Percentiles of Adult Consumption Rates by Age (g/kg-day) 10-169
Table 10-101. Median Consumption Rates by Income (g/kg-day) within Each Tribe 10-170
Exposure Factors Handbook
September 2011
Page
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Chapter 10—Intake of Fish and Shellfish
LIST OF TABLES (continued)
Table 10-102. Mean, 50th, and 90th Percentiles of Consumption Rates for Children Age Birth to 5 Years
(g/kg-day) 10-171
Table 10-103. Adult Consumption Rate (g/kg-day): Individual Finfish and Shellfish and Fish Groups 10-172
Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only 10-173
Table 10-105. Adult Consumption Rate (g/kg-day) by Sex 10-176
Table 10-106. Adult Consumption Rate (g/kg-day) by Age 10-177
Table 10-107. Consumption Rates for Native American Children (g/kg-day), All Children (including
non-consumers): Individual Finfish and Shellfish and Fish Groups 10-179
Table 10-108. Consumption Rates for Native American Children (g/kg-day), Consumers Only:
Individual Finfish and Shellfish and Fish Groups 10-180
Table 10-109. Percentiles and Mean of Consumption Rates for Adult Consumers Only (g/kg-day) 10-181
Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only (g/kg-
day) 10-182
Table 10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only—
Squaxin Island Tribe (g/kg-day) 10-184
Table 10-112. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only—Tulalip
Tribe (g/kg-day) 10-186
Table 10-113. Percentiles and Mean of Consumption Rates for Child Consumers Only (g/kg-day) 10-187
Table 10-114. Percentiles and Mean of Consumption Rates by Sex for Child Consumers Only (g/kg-
day) 10-188
Table 10-115. Consumption Rates of API Community Members 10-189
Table 10-116. Demographic Characteristics of "Higher" and "Lower" Seafood Consumers 10-190
Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community
(g/kg-day) 10-191
Table 10-118. Consumption Rates by Sex for All Asian and Pacific Islander Community 10-195
Table 10-119. Types of Seafood Consumed/Respondents Who Consumed (%) 10-196
Table 10-120. Mean, Median and 95th Percentile Fish Intake Rates for Different Groups (g/day) 10-198
Table 10-121. Distribution of Quantity of Fish Consumed (in grams) per Eating Occasion, by Age and
Sex 10-199
Table 10-122. Distribution of Quantity of Canned Tuna Consumed (grams) per Eating Occasion, by Age
and Sex 10-200
Table 10-123. Distribution of Quantity of Other Finfish Consumed (grams) per Eating Occasion, by Age
and Sex 10-201
Table 10-124. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies 10-202
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species 10-203
LIST OF FIGURES
Figure 10-1. Locations of Freshwater Fish Consumption Surveys in the United States 10-12
Figure 10-2. Species and Frequency of Meals Consumed by Geographic Residence 10-208
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
10. INTAKE OF FISH AND SHELLFISH
10.1. INTRODUCTION
Contaminated finfish and shellfish are potential
sources of human exposure to toxic chemicals.
Pollutants are carried in the surface waters but also
may be stored and accumulated in the sediments as a
result of complex physical and chemical processes.
Finfish and shellfish are exposed to these pollutants
and may become sources of contaminated food if the
contaminants bioconcentrate in fish tissue or
bioaccumulate through the food chain. Some
chemicals (e.g., polychlorinated biphenyls and
dioxins) are stored in fatty tissues, while others (e.g.,
mercury and arsenic) are typically found in the
non-lipid components.
Accurately estimating exposure to toxic
chemicals in fish requires information about the
nature of the exposed population (i.e., general
population, recreational fishermen, subsistence
fishers) and their intake rates. For example, general
population intake rates may be appropriate for
assessing contaminants that are widely distributed in
commercially caught fish. However, these data may
not be suitable to estimate exposure to contaminants
in a particular water source among recreational or
subsistence fishers. Because the catch of recreational
and subsistence fishermen is not "diluted" by fish
from other water bodies, these individuals and their
families represent the population that is most
vulnerable to exposure by intake of contaminated fish
from a specific location. Subsistence fishermen are
those individuals who consume fresh caught fish as a
major source of food. Their intake rates are generally
higher than those of the general population. It should
be noted that, depending on the study, the data
presented in this chapter for Native American
populations may or may not reflect subsistence
fishing. Harper and Harris (2007), and Donatuto and
Harper (2008) describe some difficulties associated
with evaluating fish intake rates among Native
American subsistence populations. For example,
Donatuto and Harper (2008) suggest that
contemporary Native American subsistence intake
rates may be lower (i.e., suppressed) compared to
heritage rates. Also, the intake rates among certain
subsets of the Native American populations may be
higher than the rate for the average Native American
(Harper and Harris, 2007; Donatuto and Harper,
2008).
This chapter focuses on intake rates of fish. Note
that in this section the term fish refers to both finfish
and shellfish, unless otherwise noted. Intake rates for
the general population, and recreational and Native
American fishing populations are addressed, and data
are presented for intake rates for both marine and
freshwater fish, when available. The general
population studies in this chapter use the term
consumer-only intake when referring to the quantity
of fish and shellfish consumed by individuals during
the survey period. These data are generated by
averaging intake across only the individuals in the
survey who consumed fish and shellfish. Per capita
intake rates are generated by averaging
consumer-only intakes over the entire survey
population (including those individuals that reported
no intake). In general, per capita intake rates are
appropriate for use in exposure assessments for
which average dose estimates are of interest because
they represent both individuals who ate the foods
during the survey period and individuals who may eat
fish at some time but did not consume it during the
survey period. Per capita intake, therefore, represents
an average across the entire population of interest but
does so at the expense of underestimating
consumption for the population of fish consumers.
Similarly, the discussions regarding recreationally
caught fish consumption use the terms "all
respondents" and "consuming anglers." "All
respondents" represents both survey
individuals/anglers who ate recreationally caught fish
during the survey period and those that did not but
may eat recreationally caught fish during other
periods. "Consuming anglers" refers only to the
individuals who ate fish during the survey period.
The determination to use consumers-only or per
capita estimates of fish consumption in exposure
assessments depends on the purpose of the
assessment and on the source of the data. Both
approaches can be a source of valuable insights on
analyses of exposure and risk related to consumption
of fish. This is because in the overall population, fish
is not a frequently consumed item, and quantities
may be relatively small, while in some populations,
fish is consumed frequently and in large quantities.
Nationwide surveys of food intake such as the
Continuing Survey of Food Intake by Individuals
(CSFII) or the National Health and Nutrition
Examination Survey (NHANES) provide objective
measures of food consumption that by design include
overall, population-based estimates of fish
consumption. The data from the CSFII or NHANES
can be analyzed in terms of overall per-capita
consumption or consumers only. Although the CSFII
and NHANES data are collected over short time
periods, the large scale nature and design of such
studies offer substantial advantages. In exposure
analysis and risk assessment applications where fish
intake is a concern, usually consumers-only data are
of greater interest because of the relative infrequency
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of fish consumption. Both approaches are a source of
valuable insights and help to provide context for the
results from specialized surveys that typically focus
on fish consumption. Specialized surveys are done
for a variety of reasons using different methodologies
that typically focus on relatively small, high-fish
consuming groups. It may be important to know how
results based on small, high consuming groups
compare to overall estimates of consumption based
on per capita data and consumers-only data. The data
presented in this chapter come from a variety of
sources and were collected using various
methodologies. Some data come from creel surveys
where fishermen are usually asked, among other
things, how much they have caught and the number
of family members with which they will share their
catch. These data will not represent usual behavior
because one cannot assume that the angler will have
the same luck over time. In all likelihood, there will
be variation in the amounts caught and consumed by
anglers that should be considered. Other data come
from mail surveys or personal or phone interviews
where participants are asked to recall how much fish
each family member eats over a certain period of
time. In some cases, data are recorded by survey
participants in a food diary. Some surveys may ask
about frequency of consumption, but not the amount.
Frequency of consumption data can be combined
with information on amount consumed per eating
occasion to estimate consumption. The recall period
determines if the survey characterizes long-term (i.e.,
usual intake) or short-term consumption. Exposure
assessors are generally interested in estimates of
long-term behaviors, but longer recall periods are
associated with generally higher reporting error that
should be considered. If the data come from a survey
where long-term or usual intake is characterized (i.e.,
how often does someone eat fish in a year?), then
consumers-only estimates may capture day-to-day
variability in consumption. On the other hand, if the
survey instrument used to collect the data
characterizes short-term consumption (e.g., how
much was eaten in a week, how much was consumed
on a particular day), then a per capita estimate may
account for the fact that individuals who are not
consumers during the survey period may consume
fish at some point over a longer time period. Using
consumers-only data from short-term surveys may
tend to overestimate consumption over the long term,
especially at the high end, because it would not
include days where respondents do not consume fish.
Overestimates of consumption could, however, be
considered conservative with regard to intake of
contaminants and, thus, provide the basis for
measures protective of human health.
The U.S. Environmental Protection Agency (EPA)
has prepared a review of and an evaluation of five
different survey methods used for obtaining fish
consumption data. They are
• Recall-Telephone Survey,
• Recall-Mail Survey,
• Recall-Personal Interview,
• Diary, and
• Creel Census.
Refer to U.S. EPA (1998) Guidance for
Conducting Fish and Wildlife Consumption Surveys
for more detail on these survey methods and their
advantages and limitations. The type of survey used,
its design, and any weighting factors used in
estimating consumption should be considered when
interpreting survey data for exposure assessment
purposes. For surveys used in this handbook,
respondents are typically adults who have reported on
fish intake for themselves and for children living in
their households.
Generally, surveys are either "creel" studies in
which fishermen are interviewed while fishing, or
broader population surveys using either mailed
questionnaires or phone interviews. Both types of
data can be useful for exposure assessment purposes,
but somewhat different applications and
interpretations are needed. In fact, results from creel
studies have often been misinterpreted, due to
inadequate knowledge of survey principles. Below,
some basic facts about survey design are presented,
followed by an analysis of the differences between
creel and population-based studies.
Typical surveys seek to draw inferences about a
larger population from a smaller sample of that
population. This larger population, from which the
survey sample is taken and to which the results of the
survey are generalized, is denoted the target
population of the survey. In order to generalize from
the sample to the target population, the probability of
being sampled must be known for each member of
the target population. This probability is reflected in
weights assigned to survey respondents, with weights
being inversely proportional to sampling probability.
When all members of the target population have the
same probability of being sampled, all weights can be
set to one and essentially ignored. For example, in a
mail or phone study of licensed anglers, the target
population is generally all licensed anglers in a
particular area, and in the studies presented, the
sampling probability is essentially equal for all target
population members.
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In a creel study (i.e., a study in which fishermen
are interviewed while fishing), the target population
is anyone who fishes at the locations being studied.
Generally, in a creel study, the probability of being
sampled is not the same for all members of the target
population. For instance, if the survey is conducted
for 1 day at a site, then it will include all persons who
fish there daily, but only about 1/7 of the people who
fish there weekly, 1/30 of the people who fish there
monthly, etc. In this example, the probability of being
sampled (or inverse weight) is seen to be proportional
to the frequency of fishing. However, if the survey
involves interviewers revisiting the same site on
multiple days, and persons are only interviewed once
for the survey, then the probability of being in the
survey is not proportional to frequency; in fact, it
increases less than proportionally with frequency. At
the extreme of surveying the same site every day over
the survey period with no re-interviewing, all
members of the target population would have the
same probability of being sampled regardless of
fishing frequency, implying that the survey weights
should all equal one. On the other hand, if the survey
protocol calls for individuals to be interviewed each
time an interviewer encounters them (i.e., without
regard to whether they were previously interviewed),
then the inverse weights will again be proportional to
fishing frequency, no matter how many times
interviewers revisit the same site. Note that when
individuals can be interviewed multiple times, the
results of each interview are included as separate
records in the database and the survey weights should
be inversely proportional to the expected number of
times that an individual's interviews are included in
the database.
In the published analyses of most creel studies,
there is no mention of sampling weights; by default,
all weights are set to one, implying equal probability
of sampling. However, because the sampling
probabilities in a creel study, even with repeated
interviewing at a site, are highly dependent on fishing
frequency, the fish intake distributions reported for
these surveys are not reflective of the corresponding
target populations. Instead, those individuals with
high fishing frequencies are given too big a weight,
and the distribution is skewed to the right, i.e., it
overestimates the target population distribution.
Price et al. (1994) explained this problem and set
out to rectify it by adding weights to creel survey
data; the authors used data from two creel studies
(Puffer et al., 1981; Pierce et al., 1981) as examples.
Price et al. (1994) used inverse fishing frequency as
survey weights and produced revised estimates of
median and 95th percentile intake for the above
two studies. These revised estimates were
dramatically lower than the original estimates. The
approach of Price et al. (1994) is discussed in more
detail in Section 10.4 where the Puffer et al. (1981)
and Pierce et al. (1981) studies are summarized.
When the correct weights are applied to survey
data, the resulting percentiles reflect, on average, the
distribution in the target population; thus, for
example, an estimated 90% of the target population
will have intake levels below the 90th percentile of the
survey fish intake distribution. There is another way,
however, of characterizing distributions in addition to
the standard percentile approach; this approach is
reflected in statements of the form "50% of the
income is received by, for example, the top 10% of
the population, which consists of individuals making
more than $100,000." Note that the 50th percentile
(median) of the income distribution is well below
$100,000. Here the $100,000 level can be thought of
as, not the 50th percentile of the population income
distribution, but as the 50th percentile of the "resource
utilization distribution" (see Appendix 10A for
technical discussion of this distribution). Other
percentiles of the resource utilization distribution
have similar interpretations; e.g., the 90th percentile
of the resource utilization distribution (for income)
would be that level of income such that 90% of total
income is received by individuals with incomes
below this level and 10% by individuals with income
above this level. This alternative approach to
characterizing distributions is of particular interest
when a relatively small fraction of individuals
consumes a relatively large fraction of a resource,
which is the case with regards to recreational fish
consumption. In the studies of recreational anglers,
this alternative approach, based on resource
utilization, will be presented, where possible, in
addition to the primary approach of presenting the
standard percentiles of the fish intake distribution.
The recommendations for fish and shellfish
ingestion rates are provided in the next section, along
with summaries of the confidence ratings for these
recommendations. The recommended values for the
general population and for other subsets of the
population are based on the key studies identified by
U.S. EPA for this factor. Following the
recommendations, the studies on fish ingestion
among the general population (see Section 10.3),
marine recreational angler populations (see
Section 10.4), freshwater recreational populations
(see Section 10.5), and Native American populations
(see Section 10.6) are summarized. Information is
provided on the key studies that form the basis for the
fish and shellfish intake rate recommendations.
Relevant data on ingestion of fish and shellfish are
also provided. These studies are presented to provide
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the reader with added perspective on the current
state-of-knowledge pertaining to ingestion of fish and
shellfish among children and adults. Information on
other population studies (see Section 10.7), serving
size (see Section 10.8), and other factors to consider
(see Section 10.9) are also presented.
10.2. RECOMMENDATIONS
Considerable variation exists in the mean and
upper percentile fish consumption rates obtained
from the studies presented in this chapter. This can be
attributed largely to the type of water body (i.e.,
marine, estuarine, freshwater) and the characteristics
of the survey population (i.e., general population,
recreational, Native American), but other factors such
as study design, method of data collection, and
geographic location also play a role. Based on these
study variations, fish consumption studies were
classified into the following categories:
General Population (finfish, shellfish, and
total fish and shellfish combined);
Recreational Marine Intake;
Recreational Freshwater Intake; and
Native American Populations
For exposure assessment purposes, the selection
of intake rates for the appropriate category (or
categories) will depend on the exposure scenario
being evaluated.
10.2.1. Recommendations—General Population
Fish consumption rates are recommended for the
general population, based on the key study presented
in Section 10.3.1. The key study for estimating mean
fish intake among the general population is the
U.S. EPA analysis of data from the Centers for
Disease Control and Prevention (CDC) NHANES
2003-2006.
Table 10-1 presents a summary of the
recommended values for per capita and
consumer-only intake of finfish, shellfish, and total
finfish and shellfish combined. Table 10-2 provides
confidence ratings for the fish intake
recommendations for the general population. The
U.S. EPA analysis of 2003-2006 NHANES data was
conducted using childhood age groups that differed
slightly from U.S. EPA's Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used
in the analysis.
Note that the fish intake values presented in
Table 10-1 are reported as uncooked fish weights.
Recipe files were used to convert, for each fish-
containing food, the as-eaten fish weight consumed
into an uncooked equivalent weight of fish. This is
important because the concentrations of the
contaminants in fish are generally measured in the
uncooked samples. Assuming that cooking results in
some reductions in weight (e.g., loss of moisture),
and the mass of the contaminant in the fish tissue
remains constant, then the contaminant concentration
in the cooked fish tissue will increase.
In terms of calculating the dose (i.e.,
concentration times weight), actual consumption may
be overestimated when intake is expressed on an
uncooked basis, but the actual concentration may be
underestimated when it is based on the uncooked
sample. The net effect on the dose would depend on
the magnitude of the opposing effects on these
two exposure factors. On the other hand, if the
"as-prepared" (i.e., as-consumed) intake rate and the
uncooked concentration are used in the dose
equation, dose may be underestimated because the
concentration in the cooked fish is likely to be higher,
if the mass of the contaminant remains constant after
cooking. Reported weights are also more likely to
reflect uncooked weight, and interpretation of
advisories are likely to be in terms of uncooked
weights. Although it is generally more conservative
and appropriate to use uncooked fish intake rates, one
should also be sure to use like measures. That is to
say, avoid using raw fish concentrations and cooked
weights to estimate the dose. For more information
on cooking losses and conversions necessary to
account for such losses, refer to Chapter 13 of this
handbook.
If concentration data can be adjusted to account
for changes after cooking, then the "as-prepared"
(i.e., as-consumed) intake rates are appropriate.
However, data on the effects of cooking on
contaminant concentrations are limited, and assessors
generally make the conservative assumption that
cooking has no effect on the contaminant mass. The
key study on fish ingestion provides intake data
based on uncooked fish weights. However, relevant
data on both "as-prepared" (i.e., as-consumed) and
uncooked general population fish intake are also
presented in this handbook. The assessor should
choose the intake data that best matches the
concentration data that are being used.
The NHANES data on which the general
population recommendations are based, are
short-term survey data and could not be used to
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estimate the distribution over the long term. Also, it is
important to note that a limitation associated with
these data is that the total amount of fish reported by
respondents included fish from all sources (e.g.,
fresh, frozen, canned, domestic, international origin).
The analysis of NHANES survey data used to
develop the recommended intake rates in this
handbook did not consider the source of the fish
consumed. This type of information may be relevant
for some assessments.
Recommended values should be selected that are
relevant to the assessment, choosing the appropriate
age groups and type offish (i.e., finfish, shellfish, or
total finfish, and shellfish). In some cases, a different
study or studies may be particularly relevant to the
needs of an assessment, in which case, results from
that specific study or studies may be used instead of
the recommended values provided here. For example,
it may be advantageous to use estimates that target a
particular region or geographical area, if relevant data
are available. In addition, seasonal, sex, and fish
species variations should be considered when
appropriate, if data are available. Also, relevant data
on general population fish intake in this chapter may
be used if appropriate to the scenarios being assessed.
For example, older data from the U.S. EPA's analysis
of data from the 1994-1996 and 1998 CSFII provide
intake rates for freshwater/estuarine fish and
shellfish, marine fish and shellfish, and total fish and
shellfish that are not available from the more recent
NHANES analysis.
10.2.2. Recommendations—Recreational Marine
Anglers
Table 10-3 presents the recommended values for
recreational marine anglers. These values are based
on the surveys of the National Marine Fisheries
Service (NMFS, 1993). The values from NMFS
(1993) are assumed to represent intake of marine fish
among adult recreational fishers. Values represent
both individuals who ate recreational fish during the
survey period and those that did not, but may eat
recreationally caught fish during other periods.
Age-specific values were not available from this
source. However, recommendations for children were
estimated based on the ratios of marine fish intake for
general population children to that of adults using
data from U.S. EPA's analysis of CSFII data from
1994-1996 and 1998 (U.S. EPA, 2002) (see
Section 10.3.2.6), multiplied by the adult recreational
marine fish intake rates for the Atlantic, Gulf, and
Pacific regions, using data from NMFS (1993) (see
Section 10.4.1.1). The ratios of each age group to
adults >18 years were calculated separately for the
means and 95th percentiles. Much of the other
relevant data on recreational marine fish intake in this
chapter are limited to certain geographic areas and
cannot be generalized to the U.S. population as a
whole. However, assessors may use the data from the
relevant studies provided in this chapter if
appropriate to the scenarios being assessed.
Table 10-4 presents the confidence ratings for
recommended recreational marine fish intake rates.
10.2.3. Recommendations—Recreational
Freshwater Anglers
Recommended values are not provided for
recreational freshwater fish intake because the
available data are limited to certain geographic areas
and cannot be readily generalized to the U.S.
population of freshwater recreational anglers as a
whole (see Figure 10-1). For example, factors
associated with water body, climate, fishing
regulations, availability of alternate fishable water
bodies, and water body productivity may affect
recreational fish intake rates. However, data from
several relevant recreational freshwater studies are
provided in this chapter. Table 10-5 summarizes data
from these studies. Assessors may use these data, if
appropriate to the scenarios and locations being
assessed. Although recommendations are not
provided, some general observations can be made.
Most of the studies in Table 10-5 represent state-wide
surveys of recreational anglers. These include
Alabama, Connecticut, Indiana, Maine, Michigan,
Minnesota, North Dakota, and Wisconsin.
Consumption data from these states would include
freshwater fish from rivers, lakes, and ponds. The
average range of consumption for all respondents
from these states varies from 5 g/day to 51 g/day.
Another two studies represent consumption of fish
from specific rivers. These included Savannah River
in Georgia and The Clinch River in Tennessee. The
consumption rates for all respondents from these
two rivers ranged from 20 g/day to 70 g/day. One of
the studies in Table 10-5 represents the consumption
of fish from three lakes in Washington, and another
represents consumption of fish from Lake Ontario.
The average consumption rate for all responding
adults was 10 g/day for the three Washington lakes. It
can also be noted that a large percentage of
recreational anglers consumed fish and shellfish
during the survey period. Thus, values for all
respondents and consuming anglers are fairly similar.
For Lake Ontario, the average consumption rate for
adults was 5 g/day.
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10.2.4. Recommendations—Native American
Populations
Recommended values are also not provided for
Native American fish intake because the available
data are limited to certain geographic areas and/or
tribes and cannot be readily generalized to Native
American tribes as a whole. However, data from
several Native American studies are provided in this
chapter and are summarized in Table 10-6. Assessors
may use these data, if appropriate to the scenarios
and populations being assessed. These studies were
performed at various study locations among various
tribes.
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Table 10-1. Recommended Per Capita and Consumer-Only Values for Fish Intake (g/kg-day), Uncooked Fish
Weight, by Age
Per Capita
Consumer Only
Age
% 95m
Consuming Mean percentile
Mean
95s
percentile
Source
Finfisha
All
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
Females 13 to 49 years
50+ years
16,783
865
1,052
1,052
978
2,256
3,450
3,450
4,289
4,103
3,893
23
2.6
14
14
15
15
15
15
23
22
29
0.16
0.03
0.22
0.22
0.19
0.16
0.10
0.10
0.15
0.14
0.20
1.1
0.0b
1.2b
1.2b
1.4
1.1
0.7
0.7
1.0
0.9
1.2
3,204
22
143
143
156
333
501
501
961
793
1,088
0.73
1.3
1.6
1.6
1.3
1.1
0.66
0.66
0.65
0.62
0.68
2.2
2.9b
4.9b
4.9b
3.6b
2.9b
1.7
1.7
2.1
1.8
2.0
U.S. EPA
Analysis
of
NHANES
2003-
2006 data
Shellfish*
All
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
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Table 10-2. Confidence in Recommendations for General Population Fish Intake
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodology and the analysis of the
survey data were adequate. Primary data were
collected and used in a secondary analysis of the data.
The sample size was large.
The response rate was adequate. The survey data were
based on recent recall. Data were collected over a
short duration (i.e., 2 days).
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key study focused on the exposure factor of
interest.
The survey was conducted nationwide and was
representative of the general U.S. population.
Data were derived from 2003-2006 NHANES.
Data were collected for 2 non-consecutive days.
High
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The primary data are accessible through CDC.
The methodology was clearly presented; enough
information was available to allow for reproduction of
the results.
Quality assurance of NHANES data was good; quality
control of secondary analysis was good.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were provided by the key study.
The survey was not designed to capture long-term
intake and was based on recall.
Medium to high for
averages; low for
long-term upper
percentiles
Evaluation and Review
Peer Review
Medium
The National Center for Health Statistics (NCHS)
NHANES survey received a high level of peer review.
The U.S. EPA analysis of these data has not been peer
reviewed outside the Agency, but the methodology
used has been peer reviewed in analysis of previous
data.
Number and Agreement of Studies The number of studies is one.
Overall Rating
Medium to High
(mean)
Medium
(long-term upper
percentiles)
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Table 10-3. Recommended Values for Recreational Marine Fish Intake
Age Group
Intake Rate3
Mean g/day
Atlantic
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
Gulf
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
Pacific
3 to <6 years
6 to <11 years
11 to <16 years
16 to <18 years
>18 years
2.5
2.5
3.4
2.8
5.6
3.2
3.3
4.4
3.5
7.2
0.9
0.9
1.2
1.0
2.0
8.6
13
6.6
18
13
12
18
9.5
26
3.3
3.2
4.8
2.5
6.8
Represents intake for the recreational fishing population only. Data from U.S. EPA analysis of NMFS
(1993) assumed to represent adults >18 years. Values represent both survey anglers who ate recreational
fish during the survey period and those that did not, but may eat recreationally caught fish during other
periods.
Recommendations for children were estimated based on the ratios of marine fish intake for general
population children to that of adults using data from U.S. EPA's analysis of CSFII data (see Table 10-31),
multiplied by the adult recreational marine fish intake rates for the Atlantic, Gulf, and Pacific regions,
using data from NMFS (1993) (see Table 10-50).The ratios of each age group to adults >18 years were
calculated separately for the means and 95th percentiles.
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Table 10-4. Confidence in Recommendations for Recreational Marine Fish Intake
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Medium
The survey methodology and the analysis of the survey data
were adequate. Primary data were collected and used in a
secondary analysis of the data. The sample size was large.
The response rate was adequate. The survey data were
based on recent recall.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Low to Medium
The key study was not designed to estimate individual
consumption offish. U.S. EPA obtained the raw data and
estimated intake distributions by employing assumptions
derived from other data sources.
The survey was conducted in coastal states in the Atlantic,
Pacific, and Gulf regions and was representative of fishing
populations in these regions of the United States.
The data are from a survey conducted in 1993.
Data were collected in telephone interviews and direct
interviews of fishermen in the field over a short time frame.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The primary data are from NMFS.
The methodology was clearly presented; enough
information was available to allow for reproduction of the
results.
Quality assurance of the primary data was not described.
Quality assurance of the secondary analysis was good.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Mean and 95th percentile values were provided.
The survey was specifically designed to estimate individual
intake rates. U.S. EPA estimated intake based on an analysis
of the raw data, using assumptions about the number of
individuals consuming fish meals from the fish caught.
Estimates for children are based on additional assumptions
regarding the proportion of intake relative to the amount
eaten by adults.
Low
Evaluation and Review
Peer Review
Number and Agreement of Studies
Data from NMFS (1993) were reviewed by NMFS and
U.S. EPA. U.S. EPA's analysis was not peer reviewed
outside of EPA.
The number of studies is one.
Medium
Overall Rating
Low to Medium
(adults)
Low (children)
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Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake
Location
Alabama
Connecticut
Georgia
(Savannah
River)
Indiana
Maine
Michigan
Minnesota
New York
(Lake Ontario)
North Dakota
Tennessee
(Clinch River)
Washington
Wisconsin
Summary (mean
ranges)
Population Group
All Respondents (Adults)
Consuming Anglers
All Respondents
Consuming Anglers
All Respondents (Adult
Whites)
All Respondents (Adult
Blacks)
All Respondents
Consuming Anglers
All Respondents
Consuming Anglers
Consuming Anglers
1 to 5 years
6 to 10 years
11 to 20 years
21 to 80 years
All ages
All Respondents
0 to 14 years
> 14 years (male)
15 to 44 (female)
>44 (female)
Consuming Anglers
All Respondents (Adults)
Consuming Anglers
All Respondents
0 to 14 years
>14 years (male)
15 to 44 (female)
>44 (female)
Consuming Anglers
All Respondents
Consuming Anglers
All Respondents (Adults)
Children of Respondents
Consuming Anglers
(Adults)
All Respondents (Adults)
Consuming Anglers
Statewide SurveysJ
Riversk
Lakes1
Mean
g/day
44a
53b
51C
53c,d
38e
70e
16
20
5.0
6.4
5.6
7.9
7.3
16f
14
1.2 (50th percentile)
4.5 (50th percentile)
2. 1(50* percentile)
3. 6 (50th percentile)
14
4.9f
5.8g
1.7 (50th percentile)
2.3 (50th percentile)
4.3 (50th percentile)
4.2 (50th percentile)
12
20e'h
38e'h
10
7
151
11
12
95th Percentile
g/day
-
-
-
-
-
-
61
61
21
26
-
-
.
-
39
14
40
25
37
37
18
-
22
25
30
33
43
-
-
42
29
-
37
37
5-51 g/day
20-70 g/day
5-10 g/day
Source
ADEM, 1994
Balcometal., 1999
Burger etal., 1999
Williams etal, 1999
Chemrisk, 1992;
Ebertetal., 1993
West etal., 1989,
1993
Benson etal., 2001
Connelly etal., 1996
Benson etal., 2001
Campbell et al., 2002
Mayfield etal., 2007
Fioreetal., 1989
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Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake (continued)
a Based on the average of two methods.
b Value represents anglers who consumed recreationally caught fish during the survey period, calculated by
dividing all respondents by the percent consuming of 83%.
0 Values included consumption of both freshwater and saltwater fish.
d Value calculated by dividing all respondents by the percent consuming of 97%.
e Calculated as amount eaten per year divided by 365 days per year.
f Based on average of multiple adult age groups.
8 Value calculated by dividing all respondents by the percent consuming of 84%.
h Values included consumption of both serf-caught and store-bought fish.
1 Value calculated by dividing all respondents by the percent consuming of 66%.
J Represents the range from the following states: Alabama, Connecticut, Indiana, Maine, Michigan,
Minnesota, North Dakota, and Wisconsin.
k Represents the range from the following rivers: Savannah River in GA and The Clinch River in TN.
1 Represents the range from three lakes in Washington and Lake Ontario.
Estimate not available.
Note All respondents represent both survey anglers who ate recreational fish during the survey period and those
that did not, but may eat recreationally caught fish during other periods.
Figure 10-1. Locations of Freshwater Fish Consumption Surveys in the United States.
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Table 10-6. Summary of Relevant Studies on Native American Fish Intake
Location/Tribe
94 Alaska
Communities
Chippewa Indians
(Wisconsin)
4 Columbia River
Tribes
(Oregon)
Florida
Minnesota
Mohawk Tribe
(New York and
Canada)
Mohawk Tribe
(New York and
Canada)
North Dakota
Tulalip Tribe
(Washington)
Squaxin Island Tribe
(Washington)
Tulalip Tribe
(Washington)
Squaxin Island Tribe
(Washington)
Suquamish Tribe
(Washington)
Population Group
All Respondents
Lowest of 94
Median of 94
Highest of 94
All Respondents
Adults
All Respondents
Adults
Children <5 years
Consumers
Adults
All Respondents
Consumers'1
All Respondents
Consumers'1
All Respondents
Women
Consuming Women
All Respondentsf
Adults
Children 2 yearsf
Consumers
Adultsf
Children 2 yearsf
All Respondents
Consumers'3
All Respondents
Adult
Children birth <5 years
All Respondents
Adults
Children
Consumers
Adults
Children birth <5 years
Consumers
Adults
Children birth <5 years
All Respondents
Adults
Children <6 years
Consumers
Adults
Children <6 years
Mean3
16 g/day
81 g/day
770 g/day
39 g/dayb
59 g/day
11 g/day (50th percentile)
63 g/dayc
0.8 g/kg-day
1.5 g/kg-day
2.8 g/kg-day
2.8 g/kg-day
13 g/daye
16 g/daye
25 g/day
10 g/day
29 g/day
13 g/day
0.4 g/kg-day
0.4 g/kg-day
0.9 g/kg-day
0.2 g/kg-day
0.9 g/kg-day
0.8 g/kg-day
1.0 g/kg-day
0.4 g/kg-day
1.0 g/kg-day
2.9 g/kg-day
2.7 g/kg-day
1.5 g/kg-day
2.7 g/kg-day
1.5 g/kg-day
95th Percentile3
-
-
170 g/day
98 g/day
183C
4.5 g/kg-day
5.7 g/kg-day
-
-
131 g/day
54 g/day
135 g/day
58 g/day
0.9s
0.8s
2.9 g/kg-day
0.7 g/kg-dayg
3.0 g/kg-day
2.1 g/kg-day8
2.6 g/kg-day
0.8 g/kg-day8
3.4 g/kg-day
7.7 g/kg-day
10 g/kg-day
7.3 g/kg-day
10 g/kg-day
7.3 g/kg-day
Source
Wolfe and Walker,
1987
Peterson et al.,
1994
CRITFC, 1994
Westat, 2006
Westat, 2006
Fitzgerald et al.,
1995
Fortietal., 1995
Westat, 2006
Toy et al., 1996
Polissar et al.,
2006
Duncan, 2000
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Table 10-6. Summary of Relevant Studies on Native American Fish Intake (continued)
Results are reported in g/day or g/kg-day, depending on which was provided in the source material.
All respondents consumed fish caught in Northern Wisconsin lakes.
Value calculated by dividing all respondents by the percent consuming of 93%.
Based on uncooked fish weight.
Value represents consumption by Mohawk women >1 year before pregnancy. Value estimated by
multiplying number of fish meals/year by the 90th percentile meal size of 209 g/meal for general population
females 20-39 years old from Smiciklas-Wright et al. (2002).
Based on 90th percentile general population meal size, based on Pao et al. (1982).
Value represents the 90th percentile.
Estimate not available.
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10.3. GENERAL POPULATION STUDIES
10.3.1. Key General Population Study
10.3.1.1. U.S. EPA Analysis of Consumption Data
from 2003-2006 NHANES
The key source of recent information on
consumption rates of fish and shellfish is the U.S.
CDC's NCHS' NHANES. Data from NHANES
2003-2006 have been used by the U.S. EPA, Office
of Pesticide Programs (OPP) to generate per capita
and consumer-only intake rates for finfish, shellfish,
and total fish and shellfish combined.
NHANES is designed to assess the health and
nutritional status of adults and children in the United
States. In 1999, the survey became a continuous
program that interviews a nationally representative
sample of approximately 7,000 persons each year and
examines a nationally representative sample of about
5,000 persons each year, located in counties across
the country, 15 of which are visited each year. Data
are released on a 2-year basis, thus, for example, the
2003 data are combined with the 2004 data to
produce NHANES 2003-2004.
The dietary interview component of NHANES is
called What We Eat in America and is conducted by
the U.S. Department of Agriculture (USDA) and the
U.S. Department of Health and Human Services
(DHHS). DHHS' NCHS is responsible for the sample
design and data collection, and USDAs Food
Surveys Research Group is responsible for the dietary
data collection methodology, maintenance of the
databases used to code and process the data, and data
review and processing. Beginning in 2003,
2 non-consecutive days of 24-hour intake data were
collected. The first day is collected in-person, and the
second day is collected by telephone 3 to 10 days
later. These data are collected using USDAs dietary
data collection instrument, the Automated Multiple
Pass Method. This method provides an efficient and
accurate means of collecting intakes for large-scale
national surveys. It is fully computerized and uses a
five-step interview. Details can be found at USDAs
Agriculture Research Service
(http ://www. ars.usda. gov/ba/bhnrc/fsrg).
For NHANES 2003-2004, there were
12,761 persons selected; of these, 9,643 were
considered respondents to the mobile examination
center (MEC) for examination and data collection.
However, only 9,034 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,354 provided complete dietary intakes for Day 2.
For NHANES 2005-2006, there were 12,862 persons
selected; of these, 9,950 were considered respondents
to the MEC examination and data collection.
However, only 9,349 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,429 provided complete dietary intakes for Day 2.
The 2003-2006 NHANES surveys are stratified,
multistage probability samples of the civilian
non-institutionalized U.S. population. The sampling
frame was organized using 2000 U.S. population
census estimates. NHANES oversamples low-income
persons, adolescents 12-19 years, persons 60 years
and older, African Americans, and Mexican
Americans. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all 4 years of the
surveys can be combined. Additional information on
NHANES can be obtained at
http://www.cdc.gov/nchs/nhanes.htm.
In 2010, U.S. EPAs OPP used NHANES 2003-
2006 data to update the Food Commodity Intake
Database (FCID) that was developed in earlier
analyses of data from the U.S. Department of
Agriculture's (USDAs) CSFII (USDA, 2000;
U.S. EPA, 2002). NHANES data on the foods people
reported eating were converted to the quantities of
agricultural commodities eaten. "Agricultural
commodity" is a term used by U.S. EPA to mean
plant (or animal) parts consumed by humans as food;
when such items are raw or unprocessed, they are
referred to as "raw agricultural commodities." For
example, clam chowder may contain the commodities
clams, vegetables, and spices. FCID contains
approximately 553 unique commodity names and
eight-digit codes. The FCID commodity names and
codes were selected and defined by U.S. EPA and
were based on the U.S. EPA Food Commodity
Vocabulary
(http ://www. epa. gov/pesticides/foodfeed/).
Intake rates were generated for finfish, shellfish,
and finfish and shellfish combined. These intake rates
represent intake of all forms of the food (e.g., both
serf-caught and commercially caught) for individuals
who provided data for 2 days of the survey.
Individuals who did not provide information on body
weight or for whom identifying information was
unavailable were excluded from the analysis. Two-
day average intake rates were calculated for all
individuals in the database for each of the food
items/groups. Note that if the person reported
consuming fish on only one day of the survey, their
2-day average would be half the amount reported for
the one day of consumption. These average daily
intake rates were divided by each individual's
reported body weight to generate intake rates in units
of grams per kilogram of body weight per day (g/kg-
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Chapter 10—Intake of Fish and Shellfish
day). The data were weighted according to the 4-year,
2-day sample weights provided in NHANES 2003-
2006 to adjust the data for the sample population to
reflect the national population.
Summary statistics were generated on a
consumer-only and on a per capita basis. Summary
statistics, including number of observations,
percentage of the population consuming fish, mean
intake rate, and standard error of the mean intake rate
were calculated for finfish, shellfish, and finfish and
shellfish combined, for both the entire population and
consumers only (see Tables 10-7 to 10-12). Data were
provided for the following age groups: birth to
<1 year, 1 to 2 years, 3 to 5 years, 6 to 12 years, 13 to
19 years, 20 to 49 years, and >50 years. Because
these data were developed for use in U.S. EPA's
pesticide registration program, the childhood age
groups used are slightly different than those
recommended in U.S. EPA's Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005).
The results are presented in units of g/kg-day
(same as the CSFII data). Thus, use of these data in
calculating potential dose does not require the
body-weight factor to be included in the denominator
of the average daily dose equation. It should be noted
that converting these intake rates into units of g/day
by multiplying by a single average body weight is
inappropriate because individual intake rates were
indexed to the reported body weights of the survey
respondents. Also, it should be noted that the
distribution of average daily intake rates generated
using short-term data (e.g., 2-day) does not
necessarily reflect the long-term distribution of
average daily intake rates. The distributions
generated from short-term and long-term data will
differ to the extent that each individual's intake varies
from day to day; the distributions will be similar to
the extent that individuals' intakes are constant from
day to day. Because of the increased variability of the
short-term distribution, the short-term upper
percentiles shown here may overestimate the
corresponding percentiles of the long-term
distribution.
The advantages of using the U.S. EPA's analysis
of NHANES data are that it provides distributions of
intake rates for various age groups of children and
adults, normalized by body weight. The data set was
designed to be representative of the U.S. population,
and includes 4 years of intake data combined.
Another advantage is the currency of the data. The
NHANES data are from 2003-2006. However,
short-term consumption data may not accurately
reflect long-term eating patterns and may
under-represent infrequent consumers of a given fish
species. This is particularly true for the tails
(extremes) of the distribution of food intake. Because
these are 2-day averages, consumption estimates at
the upper end of the intake distribution may be
underestimated if these consumption values are used
to assess acute (i.e., short-term) exposures. Also, the
analysis was conducted using slightly different
childhood age groups than those recommended in
U.S. EPA's Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, given the similarities in the age groups
used, the data should provide suitable intake
estimates for the age groups of interest.
10.3.2. Relevant General Population Studies
10.3.2.1. Javitz (1980)—Seafood Consumption
Study
Javitz (1980) utilized data that were originally
collected in a study funded by the Tuna Research
Foundation (TRF) to estimate fish intake rates. The
TRF study of fish consumption was performed by the
National Purchase Diary during the period of
September, 1973 to August, 1974. The data tapes
from this survey were obtained by the NMFS, which
later, along with the Food and Drug Administration,
USDA and TRF, conducted an intensive effort to
identify and correct errors in the database. Javitz
(1980) summarized the TRF survey methodology and
used the corrected tape to generate fish intake
distributions for various population groups.
The TRF survey sample included 9,590 families,
of which 7,662 (25,162 individuals) completed the
questionnaire, a response rate of 80%. The survey
was weighted to represent the U.S. population.
The population of fish consumers represented
94% of the U.S. population. For this population of
"fish consumers," Javitz (1980) calculated means and
percentiles of fish consumption by demographic
variables (age, sex, race, census region, and
community type) and overall (see Table 10-13). The
overall mean fish intake rate among fish consumers
was calculated at 14.3 g/day and the 95th percentile at
41.7 g/day.
Table 10-14 presents the distribution of fish
consumption for females and males, by age; this table
give the percentages of females/males in a given age
bracket with intake rates within various ranges.
Table 10-15 presents mean total fish consumption by
fish species.
The TRF survey data were also utilized by Rupp
et al. (1980) to generate fish intake distributions for
three age groups (1 to 11, 12 to 18, and 18 to
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Chapter 10—Intake of Fish and Shellfish
98 years) within each of the 9 census regions and for
the entire United States. Separate distributions were
derived for freshwater finfish, saltwater finfish, and
shellfish. Ruffle et al. (1994) used the percentiles data
of Rupp et al. (1980) to estimate the best-fitting
lognormal parameters for each distribution.
Table 10-16 presents the optimal lognormal
parameters, the mean (u) and standard deviation (o).
These parameters can be used to determine
percentiles of the corresponding distribution of
average daily fish consumption rates through the
relation (p) = exp[n + Z(P)G] where DCR(/?) is the p&
percentile of the distribution of average daily fish
consumption rates and z(p) is the z-score associated
with the p& percentile (e.g., z(50) = 0). The mean
average daily fish consumption rate is given by exp
[u + 0.5o2].
The advantages of the TRF data survey are that it
was a large, nationally representative survey with a
high response rate (80%) and was conducted over an
entire year. In addition, consumption was recorded in
a daily diary over a 1-month period; this format
should be more reliable than one based on 1-month
recall. The upper percentiles presented are derived
from 1 month of data and are likely to overestimate
the corresponding upper percentiles of the long-term
(i.e., 1 year or more) average daily fish intake
distribution. Similarly, the standard deviation of the
fitted lognormal distribution probably overestimates
the standard deviation of the long-term distribution.
However, the period of this survey (1 month) is
considerably longer than those of many other
consumption studies, including the USDA National
Food Consumption Surveys, CSFII, and NHANES,
which report consumption over a 2-day to 1-week
period. Another obvious limitation of this database is
that it is now over 30 years out of date. Ruffle et al.
(1994) considered this shortcoming and suggested
that one may wish to shift the distribution upward to
account for the recent increase in fish consumption,
though CSFII has shown little change in g/day fish
consumption from 1978 to 1996. Adding
ln(l+x/100) to the log mean n will shift the
distribution upward by x% (e.g., adding
0.22 = ln(1.25) increases the distribution by 25%).
Although the TRF survey distinguished between
recreationally and commercially caught fish, Javitz
(1980), Rupp et al. (1980), and Ruffle et al. (1994)
(which was based on Rupp et al., 1980) did not
present analyses by this variable.
10.3.2.2. Poo et al (1982)—Foods Commonly
Eaten by Individuals: Amount per Day
and per Eating Occasion
The USDA 1977-1978 Nationwide Food
Consumption Survey (NFCS) consisted of a
household and individual component. For the
individual component, all members of surveyed
households were asked to provide three consecutive
days of dietary data. For the first day's data,
participants supplied dietary recall information to an
in-home interviewer. Second and 3rd day dietary
intakes were recorded by participants. A total of
15,000 households were included in the 1977-1978
NFCS, and about 38,000 individuals completed the
3-day diet records. Fish intake was estimated based
on consumption of fish products identified in the
NFCS database according to NFCS-defined food
codes. These products included fresh, breaded,
floured, canned, raw, and dried fish, but not fish
mixtures or frozen plate meals.
Pao et al. (1982) used the data from this survey
set to calculate per capita fish intake rates. However,
because these data are now almost 30 years out of
date, this analysis is not considered key with respect
to assessing per capita intake (the average quantity of
fish consumed per fish meal should be less subject to
change over time than is per capita intake). In
addition, fish mixtures and frozen plate meals were
not included in the calculation of fish intake. The per
capita fish intake rate reported by Pao et al. (1982)
was 11.8 g/day. The 1977-1978 NFCS was a large
and well-designed survey, and the data are
representative of the U.S. population.
10.3.2.3. USDA (1992a)—Food and Nutrient
Intakes by Individuals in the United
States, 1 Day, 1987-1988: Nationwide
Food Consumption Survey 1987-1988
The USDA 1987-1988 (NFCS) also consisted of
a household and individual component. For the
individual component, each member of a surveyed
household was interviewed (in person) and asked to
recall all foods eaten the previous day; the
information from this interview made up the "1-day
data" for the survey. In addition, members were
instructed to fill out a detailed dietary record for the
day of the interview and the following day. The data
for this entire 3-day period made up the "3-day diet
records." A statistical sampling design was used to
ensure that all seasons, geographic regions of the
United States, and demographic and socioeconomic
groups were represented. Sampling weights were
used to match the population distribution of
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Chapter 10—Intake of Fish and Shellfish
13 demographic characteristics related to food intake
(USDA, 1992b).
Total fish intake was estimated based on
consumption of fish products identified in the NFCS
database according to NFCS-defined food codes.
These products included fresh, breaded, floured,
canned, raw, and dried fish but not fish mixtures or
frozen plate meals.
A total of 4,500 households participated in the
1987-1988 survey; the household response rate was
38%. One-day data were obtained for 10,172 (81%)
of the 12,522 individuals in participating households;
8,468 (68%) individuals completed 3-day diet
records.
USDA (1992b) used the 1-day data to derive per
capita fish intake rate and intake rates for consumers
of total fish. Table 10-17 shows these rates,
calculated by sex and age group. Intake rates for
consumers only were calculated by dividing the per
capita intake rates by the fractions of the population
consuming fish in 1 day.
An advantage of analyses based on the 1987-1988
USDA NFCS is that the data set is a large,
geographically and seasonally balanced survey of a
representative sample of the U.S. population. The
survey response rate, however, was low, and an
expert panel concluded that it was not possible to
establish the presence or absence of non-response
bias (USDA, 1992b). In addition, the data from this
survey have been superseded by more recent surveys.
10.3.2.4. U.S. EPA (1996)—Descriptive Statistics
from a Detailed Analysis of the National
Human Activity Pattern Survey (NHAPS)
Responses
The U.S. EPA collected information for the
general population on the duration and frequency of
time spent in selected activities and time spent in
selected microenvironments via 24-hour diaries (U.S.
EPA, 1996). Over 9,000 individuals from 48
contiguous states participated in NHAPS.
Approximately 4,700 participants also provided
information on seafood consumption. The survey was
conducted between October 1992 and September
1994. Data were collected on (1) the number of
people that ate seafood in the last month, (2) the
number of servings of seafood consumed, and
(3) whether the seafood consumed was caught or
purchased (U.S. EPA, 1996). The participant
responses were weighted according to selected
demographics such as age, sex, and race to ensure
that results were representative of the U.S.
population. Of those 4,700 respondents,
2,980 (59.6%) ate seafood (including shellfish, eels,
or squid) in the last month (see Table 10-18). The
number of servings per month was categorized in
ranges of 1-2, 3-5, 6-10, 11-19, and 20+ servings
per month (see Table 10-19). The highest percentage
(35%) of the respondent population had an intake of
3-5 servings per month. Most (92%) of the
respondents purchased the seafood they ate (see
Table 10-20).
Intake data were not provided in the survey.
However, intake of fish can be estimated using the
information on the number of servings of fish eaten
from this study and serving size data from other
studies. Smiciklas-Wright et al. (2002) estimated that
the mean value for fish serving size for all age groups
combined is 114 g/serving based on the 1994-1996
CSFII survey (see Section 10.8). The CSFII serving
size data are based on all finfish, except canned,
dried, and raw, whether reported separately or as part
of a sandwich or other mixed food. Using this mean
value for serving size and assuming that the average
individual eats 3-5 servings per month, the amount of
seafood eaten per month would range from 340 to
570 g/month or 11.3 to 19.0 g/day for the highest
percentage of the population. These values are within
the range of per capita mean intake values for total
fish (16.9 g/day, uncooked equivalent weight)
calculated by U.S. EPA (2002) analysis of the USDA
CSFII data. It should be noted that an all inclusive
description for seafood was not presented in U.S.
EPA (1996). It is not known if they included
processed or canned seafood and seafood mixtures in
the seafood category.
The advantages of NHAPS are that the data were
collected for a large number of individuals and are
representative of the U.S. general population.
However, evaluation of seafood intake was not the
primary purpose of the study, and the data do not
reflect the actual amount of seafood that was eaten.
However, using the assumption described above, the
estimated seafood intake from this study is
comparable to that observed in the U.S. EPA CSFII
analysis.
10.3.2.5. Stern et al. (1996)—Estimation of Fish
Consumption and Methylmercury Intake
in the New Jersey Population
Stern et al. (1996) reported on a 7-day fish
consumption recall survey that was conducted in
1993 as part of the New Jersey Household Fish
Consumption Study. Households were contacted by
telephone using the random-digit dialing technique,
and the survey completion rate was 72% of
households contacted. Respondents included 1 adult
(i.e., >18 years) resident per household, for a total of
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1,000 residents. The sample was "stratified to provide
equal numbers of men and women and proportional
representation by county" (Stern etal., 1996). Survey
respondents provided data on consumption of all
seafood consumed within the previous 7 days,
including the number of fish meals, fish type, amount
eaten at each meal, frequency of consumption, and
whether the consumption patterns during the recall
period were typical of their intake throughout the
year.
Stern et al. (1996) reported that "of the
1,000 respondents, 933 reported that they normally
consume fish at least a few times per year and
686 reported that they consumed fish during the
recall period" (Stern et al., 1996). Table 10-21
presents the distribution of the number of meals for
the 7-day recall period. The average portion size was
168 grams. Approximately "4-5% of all fish meals
consisted of fish obtained non-commercially, and
only about 13% of these consisted of freshwater fish"
(Stern et al., 1996). Tuna was consumed most
frequently, followed by shrimp and flounder/fluke
(see Table 10-22).
Table 10-23 provides the average daily
consumption rates (g/day) for all fish for all adults
and for women of childbearing age (i.e., 18-
40 years). The mean fish intake rate for all adult
consumers was 50 g/day, and the 90th percentile was
107 g/day. For women of childbearing age, the mean
fish intake rate was 41 g/day, and the 90th percentile
was 88 g/day. Table 10-24 provides information on
the frequency of fish consumption.
The advantages of this study are that it is based
on a 7-day recall period and that data were collected
for the frequency of eating fish. However, the data
are based on fish consumers in New Jersey and may
not be representative of the general population of the
United States.
10.3.2.6. U.S. EPA (2002)—Estimated Per Capita
Fish Consumption in the United States
U.S. EPA's Office of Water used data from the
1994-1996 CSFII and its 1998 Children's
Supplement (referred to collectively as CSFII 1994-
1996, 1998) to generate fish intake estimates
(U.S. EPA, 2002). Participants in the CSFII 1994-
1996, 1998 provided 2 non-consecutive days of
dietary data. The Day 2 interview occurred 3 to
10 days after the Day 1 interview but not on the same
day of the week. Data collection for the CSFII started
in April of the given year and was completed in
March of the following year. Respondents estimated
the weight of each food that they consumed.
Information on the consumption of food was
classified using 11,345 different food codes and
stored in a database in units of grams consumed per
day. A total of 831 of these food codes related to fish
or shellfish; survey respondents reported
consumption across 665 of these codes. The fish
component (by weight) of the various foods was
calculated using data from the recipe file for release
seven of USDA's Nutrient Data Base for Individual
Food Intake Surveys.
The amount of fish consumed by each individual
was then calculated by summing, over all fish
containing foods, the product of the weight of food
consumed and the fish component (i.e., the
percentage fish by weight) of the food. The recipe file
also contains cooking loss factors associated with
each food. These were used to convert, for each
fish-containing food, the as-eaten fish weight
consumed into an uncooked equivalent weight of
fish. Analyses of fish intake were performed on both
an "as-prepared" (i.e., as-consumed) and uncooked
basis.
Each fish-related food code was assigned, by
U.S. EPA, to a habitat category. The habitat
categories included freshwater/estuarine, or marine.
Food codes were also designated as finfish or
shellfish. Average daily individual consumption
(g/day) was calculated, for a given fish
type-by-habitat category (e.g., marine finfish), by
summing the amount of fish consumed by the
individual across the 2 reporting days for all
fish-related food codes in the given fish-by-habitat
category and then dividing by 2. Individual daily fish
consumption (g/day) was calculated similarly except
that total fish consumption was divided by the
specific number of survey days the individual
reported consuming fish; this was calculated for fish
consumers only (i.e., those consuming fish on at least
1 of the 2 survey days). The reported body weight of
the individual was used to convert consumption in
g/day to consumption in g/kg-day.
There were a total of 20,607 respondents in the
combined data set that had 2-day dietary intake data.
Survey weights were assigned to this data set to make
it representative of the U.S. population with respect
to various demographic characteristics related to food
intake. Survey weights were also adjusted for
non-response.
U.S. EPA (2002) reported means, medians, and
estimates of the 90th, 95A, and 99th percentiles of fish
intake. The 90% interval estimates are
non-parametric estimates from bootstrap techniques.
The bootstrap estimates result from the percentile
method, which calculates the lower and upper bounds
for the interval estimate by the lOOa percentile and
100 (1-a) percentile estimates from the
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non-parametric distribution of the given point
estimate (U.S. EPA, 2002).
Analyses of fish intake were performed on an
as-prepared as well as on an uncooked equivalent
basis and on a g/day and mg/kg-day basis.
Table 10-25 gives the mean and various percentiles
of the distribution of per capita finfish and shellfish
intake rates (g/day), as prepared, by habitat and fish
type, for the general population. Table 10-26
provides a list of the fish species categorized within
each habitat. Table 10-26 also shows per capita
consumption estimates by species. Table 10-27
displays the mean and various percentiles of the
distribution of per capita finfish and shellfish intake
rates (g/day) by habitat and fish type, on an uncooked
equivalent basis. Table 10-28 shows per capita
consumption estimates by species on an uncooked
equivalent basis.
Tables 10-29 through 10-36 present data for daily
average fish consumption. These data are presented
by selected age groupings (14 and under, 15-44, 45
and older, all ages, children ages 3 to 17, and ages
18 and older) and sex. It should be noted the analysis
predated the age groups recommended by U.S. EPA
Guidelines on Selecting Age Groups for Monitoring
and Assessing Childhood Exposure to Environmental
Contaminants (U.S. EPA, 2005). Tables 10-29
through 10-32 present fish intake data (g/day and
mg/kg-day; as prepared and uncooked) on a per
capita basis, and Tables 10-33 through 10-36 provide
data for consumers only.
The advantages of this study are its large size and
its representativeness. The survey was also designed
and conducted to support unbiased estimation of food
consumption across the population. In addition,
through use of the USDA recipe files, the analysis
identified all fish-related food codes and estimated
the percent fish content of each of these codes. By
contrast, some analyses of the USDA NFCSs, which
reported per capita fish intake rates (e.g., Pao et al.,
1982; USDA, 1992a), excluded certain fish-
containing foods (e.g., fish mixtures, frozen plate
meals) in their calculations.
10.3.2.7. Westat (2006)—Fish Consumption in
Connecticut, Florida, Minnesota, and
North Dakota
Westat (2006) analyzed the raw data from
three fish consumption studies to derive fish
consumption rates for various age, sex, and ethnic
groups, and according to the source of fish consumed
(i.e., bought or caught) and habitat (i.e., freshwater,
estuarine, or marine). The studies represented data
from four states: Connecticut, Florida, Minnesota,
and North Dakota.
The Connecticut data were collected in 1996/1997
by the University of Connecticut to obtain estimates
of fish consumption for the general population, sport
fishing households, commercial fishing households,
minority and limited income households, women of
child-bearing years, and children. Data were obtained
from 810 households, representing 2,080 individuals,
using a combination of a mail questionnaire that
included a 10-day diary, and personal interviews. The
response rate for this survey was low (i.e., 6% for the
general population and 10% for anglers) but was
considered to be adequate by the study authors
(Balcometal., 1999).
The Florida data were collected by telephone and
in-person interviews by the University of Florida and
represented a random sample of 8,000 households
(telephone interviews) and 500 food stamp recipients
(in-person interviews). The purpose of the survey was
to obtain information on the quantity of fish and
shellfish eaten, as well as the cooking method used.
Additional information of the Florida survey can be
found in Degner et al. (1994).
The Minnesota and North Dakota data were
collected by the University of North Dakota in 2000
and represented 1,572 households and
4,273 individuals. Data on purchased and caught fish
were collected for the general population, anglers,
new mothers, and Native American tribes. The survey
also collected information on the species of fish
eaten. Additional information on this study can be
found in Benson et al. (2001).
The primary difference in survey procedures
among the three studies was the manner in which the
fish consumption data were collected. In Connecticut,
the survey requested information on how often each
type of seafood was eaten, without a recall period
specified. In Minnesota and North Dakota, the survey
requested information on the rate of fish or shellfish
consumption during the previous 12 months. In
Florida, the survey requested information on fish
consumption during the last 7 days prior to the
telephone interview. In addition, for the Florida
survey, information on away-from-home fish
consumption was collected from a randomly selected
adult from each participating household. Because this
information was not collected from all household
members, the study may tend to underestimate
away-from-home consumption. The study notes that
estimates of fish consumption using a shorter recall
period will decrease the proportion of respondents
that report eating fish or shellfish. This trend was
observed in the Florida study (in which
approximately half of respondents reported eating
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fish/shellfish), compared with Connecticut,
Minnesota, and North Dakota (in which
approximately 90% of respondents reported eating
fish or shellfish).
Tables 10-37 through 10-46 present key findings
of the Westat (2006) consumption study. The tables
show the fish and shellfish consumption rates for
various groups classified by demographic
characteristics and by the source of the fish and
shellfish consumed (i.e., freshwater versus marine,
and bought versus serf-caught). Consumption rates
are presented in grams per kilogram of body weight
per day for the entire population (i.e., consumption
per capita) and for just those that reported consuming
fish and shellfish (consumption for consumers only).
An advantage of this study is that it focused on
individuals within the general population that may
consume more fish and shellfish and, thus, may be at
higher risk from exposure to contaminants in fish
than other members of the population. Also, it
provides distributions of fish consumption for
different age cohorts, ethnic groups, socioeconomic
status, types of fish (i.e., freshwater, marine,
estuarine), and sources of fish (i.e., store-bought
versus self-caught). However, the data were collected
in four states and may not be representative of the
U.S. population as a whole.
10.3.2.8. Moya et al. (2008)—Estimates of Fish
Consumption Rates for Consumers of
Bought and Self-Caught Fish in
Connecticut, Florida, Minnesota, and
North Dakota
Moya et al. (2008) summarized the analysis
conducted by Westat (2006) described in Section
10.3.2.7. Moya et al. (2008) utilized the data to
generate intake rates for 3 age groups of children
(i.e., 1 to <6 years, 6 to <11 years, and 11 to
< 16 years) and 3 age groups of adults (16 to
<30 years, 30 to <50 years, and >50 years), which are
also listed by sex. These data represented the general
population and angler population in the four states.
Recreational fish intake rates were not provided for
children, and data were not provided for children
according to the source of intake (i.e., bought or
caught) or habitat (i.e., freshwater, estuarine, or
marine). Table 10-47 presents the intake rates for the
general population who consumed fish and shellfish
in g/kg-day, as-consumed. Table 10-47 also provides
information on the fish intake among the sample
populations from the four states, based on the source
of the fish (i.e., caught or bought) and provides
estimated fish intake rates among the general
populations and angler populations from Connecticut,
Minnesota, and North Dakota.
This analysis is based on the data from Westat
(2006). Therefore, the advantages and limitations are
the same as those of the Westat (2006) study. Also,
while data were provided for individuals who ate
serf-caught fish, it is not possible from this analysis
to determine the proportion of serf-caught fish
represented by marine or freshwater habitats.
10.3.2.9. Mahaffey et al. (2009)—Adult Women's
Blood Mercury Concentrations Vary
Regionally in the United States:
Association with Patterns of Fish
Consumption (NHANES1999-2004)
Mahaffey et al. (2009) used NHANES 1999-2004
data to evaluate relationships between fish intake and
blood mercury levels. Mercury intake via fish
ingestion was evaluated for four coastal populations
(i.e., Atlantic, Pacific, Gulf of Mexico, and Great
Lakes), and four non-coastal populations defined by
U.S. census regions (i.e., Northeast, South, Midwest,
and West) (Mahaffey et al., 2009). Serving size data,
based on 24-hour dietary recall, were used with
30-day food frequency data to estimate mercury
intake from consumption of fish over a 30-day
period. The frequency data used in the study
indicated that people living on the Atlantic coast
consumed fish most frequently (averaging
6 meals/month), followed closely by those of the
Gulf and Pacific coasts. People living in non-coastal
areas or on the coasts of the Great Lakes consumed
fish least often (averaging <4 meals/month).
Figure 10-2 illustrates these regional differences.
The advantage of this study is that it is based on
relatively recent NHANES data (i.e., 1999-2004), it
uses data from the 30-day food frequency
questionnaire, and it provides regional data that are
not available elsewhere. However, because the study
focused on mercury exposure, it did not provide
non-chemical specific fish intake data (in g/day or
g/kg-day) that can be used to support risk
assessments for other chemicals (i.e., only frequency
data were provided). It does, however, provide useful
information on the relative differences in frequency
offish intake for regional populations.
10.4. MARINE RECREATIONAL STUDIES
10.4.1. Key Marine Recreational Study
10.4.1.1. National Marine Fisheries Service (1986a,
b, c, 1993)
The NMFS conducts systematic surveys, on a
continuing basis, of marine recreational fishing.
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These surveys are designed to estimate the size of the
recreational marine finfish catch by location, species,
and fishing mode. In addition, the surveys provide
estimates for the total number of participants in
marine recreational finfishing and the total number of
fishing trips.
The NMFS surveys involve two components:
telephone surveys and direct interviewing of
fishermen in the field. The telephone survey
randomly samples residents of coastal regions,
defined generally as counties within 25 miles of the
nearest seacoast, and inquires about participation in
marine recreational fishing in the resident's home
state in the past year, and more specifically, in the
past 2 months. This component of the survey is used
to estimate, for each coastal state, the total number of
coastal region residents who participate in marine
recreational fishing (for finfish) within the state, as
well as the total number of (within state) fishing trips
these residents take. To estimate the total number of
participants and fishing trips in the state, by coastal
residents and others, a ratio approach, based on the
field interview data, was used. Thus, if the field
survey data found that there was a 4:1 ratio of fishing
trips taken by coastal residents as compared to trips
taken by non-coastal and out-of-state residents, then
an additional 25% would be added to the number of
trips taken by coastal residents to generate an
estimate of the total number of within-state trips.
The surveys are not designed to estimate
individual consumption of fish from marine
recreational sources, primarily because they do not
attempt to estimate the number of individuals
consuming the recreational catch. Intake rates for
marine recreational anglers can be estimated,
however, by employing assumptions derived from
other data sources about the number of consumers.
The field intercept survey is essentially a creel
type survey. The survey utilizes a national site
register that details marine fishing locations in each
state. Sites for field interviews are chosen in
proportion to fishing frequency at the site. Anglers
fishing on shore, private boat, and charter/party boat
modes who had completed their fishing were
interviewed. The field survey included questions
about frequency of fishing, area of fishing, age, and
place of residence. The fish catch was classified by
the interviewer as either type A, type Bl, or type B2
catch. The type A catch denoted fish that were taken
whole from the fishing site and were available for
inspection. The type Bl and B2 catch were not
available for inspection; the former consisted of fish
used as bait, filleted, or discarded dead, while the
latter was fish released alive. The type A catch was
identified by species and weighed, with the weight
reflecting total fish weight, including inedible parts.
The type Bl catch was not weighed, but weights
were estimated using the average weight derived
from the type A catch for the given species, state,
fishing mode, and season of the year. For both the
type A and Bl catch, the intended disposition of the
catch (e.g., plan to eat, plan to throw away, etc.) was
ascertained.
U.S. EPA obtained the raw data tapes from NMFS
in order to generate intake distributions and other
specialized analyses. Fish intake distributions were
generated using the field survey tapes. Weights
proportional to the inverse of the angler's reported
fishing frequency were employed to correct for the
unequal probabilities of sampling; this was the same
approach used by NMFS in deriving their estimates.
Note that in the field survey, anglers were
interviewed regardless of past interviewing
experience; thus, the use of inverse fishing frequency
as weights was justified (see Section 10.1).
For each angler interviewed in the field survey,
the yearly amount of fish caught that was intended to
be eaten by the angler and his/her family or friends
was estimated by U.S. EPA as follows:
7 = f(wt of A catch) *IA
[Fishing frequency]
(wt ofBl catch) x IB] x
(Eqn. 10-1)
where IA (IB) are indicator variables equal to one if
the type A (Bl) catch was intended to be eaten, and
equal to 0 otherwise. To convert 7 to a daily fish
intake rate by the angler, it was necessary to convert
amount of fish caught to edible amount of fish, divide
by the number of intended consumers, and convert
from yearly to daily rate.
Although theoretically possible, U.S. EPA chose
not to use species-specific edible fractions to convert
overall weight to edible fish weight because edible
fraction estimates were not readily available for many
marine species. Instead, an average value of 0.5 was
employed. For the number of intended consumers,
U.S. EPA used an average value of 2.5, which was an
average derived from the results of several studies of
recreational fish consumption (Chemrisk, 1992;
Puffer et al., 1981; West et al., 1989). Thus, the
average daily intake rate (ADI) for each angler was
calculated as
ADI = 7 x (0.5)/[2.5 x 365] (Eqn. 10-2)
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Note that ADI will be 0 for those anglers who
either did not intend to eat their catch or who did not
catch any fish. The distribution of ADI among
anglers was calculated by region and coastal status
(i.e., coastal versus non-coastal counties).
The results presented in Tables 10-48 and 10-49
are based on the results of the 1993 survey. Sample
sizes were 200,000 for the telephone survey and
120,000 for the field surveys. All coastal states in the
continental United States were included in the survey
except Texas and Washington.
Table 10-48 presents the estimated number of
coastal, non-coastal, and out-of-state fishing
participants by state and region of fishing. Florida
had the greatest number of both Atlantic and Gulf
participants. The total number of coastal residents
who participated in marine finfishing in their home
state was eight million; an additional
750,000 non-coastal residents participated in marine
finfishing in their home state.
Table 10-49 presents the estimated total weight of
the type A and B1 catch by region and time of year.
For each region, the greatest catches were during the
6-month period from May through October. This
period accounted for about 90% of the North and
Mid-Atlantic catch, about 80% of the Northern
California and Oregon catch, about 70% of the
Southern Atlantic and Southern California catch, and
62% of the Gulf catch. Note that in the North and
Mid-Atlantic regions, field surveys were not done in
January and February due to very low fishing
activity. For all regions, over half the catch occurred
within 3 miles of the shore or in inland waterways.
Table 10-50 presents the mean and 95th percentile
of average daily intake (ADI) of recreationally caught
marine finfish among anglers by region. The mean
ADI values among all anglers were 5.6, 7.2, and 2.0
g/day for the Atlantic, Gulf, and Pacific regions,
respectively. Table 10-51 gives the distribution of
catch, by species, for the Atlantic, Gulf, and Pacific
regions.
The NMFS surveys provide a large,
geographically representative sample of marine
angler activity in the United States. The major
limitation of this database in terms of estimating fish
intake is the lack of information regarding the
intended number of consumers of each angler's catch.
In this analysis, it was assumed that every angler's
catch was consumed by the same number (2.5) of
people; this number was derived from averaging the
results of other studies. This assumption introduces a
relatively low level of uncertainty in the estimated
mean intake rates among anglers, but a somewhat
higher level of uncertainty in the estimated intake
distributions.
Under the above assumption, the distributions
shown here pertain not only to the population of
anglers, but also to the entire population of
recreational fish consumers, which is 2.5 times the
number of anglers. If the number of consumers was
changed, to, for instance, 2.0, then the distribution
would be increased by a factor of 1.25 (2.5/2.0), but
the estimated population of recreational fish
consumers to which the distribution would apply,
would decrease by a factor of 0.8 (2.0/2.5).
Another uncertainty involves the use of 0.5 as an
(average) edible fraction. This figure is assumed to be
somewhat conservative (i.e., the true average edible
fraction is probably lower); thus, the intake rates
calculated here may be biased upward somewhat.
The recreational fish intake distributions given
refer only to marine finfish. In addition, the intake
rates calculated are based only on the catch of anglers
in their home state. Marine fishing performed
out-of-state would not be included in these
distributions. Therefore, these distributions give an
estimate of consumption of locally caught marine
fish. These data are approximately 2 decades old and
may not be entirely representative of current intake
rates. Also, data were not available for children.
10.4.2. Relevant Marine Recreational Studies
10.4.2.1. Pierce et al (1981)—Commencement Bay
Seafood Consumption Study
Pierce et al. (1981) performed a local creel survey
to examine seafood consumption patterns and
demographics of sport fishermen in Commencement
Bay, WA. The objectives of this survey included
determining (1) the seafood consumption habits and
demographics of non-commercial anglers catching
seafood; (2) the extent to which resident fish were
used as food; and (3) the method of preparation of the
fish to be consumed. Salmon were excluded from the
survey because it was believed that they had little
potential for contamination. The first half of this
survey was conducted from early July to
mid-September, 1980 and the second half from
mid-September through most of November. During
the summer months, interviewers visited each of four
sub-areas of Commencement Bay on five mornings
and five evenings; in the fall, the areas were sampled
on four complete survey days. Interviews were
conducted only with persons who had caught fish.
The anglers were interviewed only once during the
survey period. Data were recorded for species, wet
weight, size of the living group (family), place of
residence, fishing frequency, planned uses of the fish,
age, sex, and race (Pierce et al., 1981). The analysis
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of Pierce et al. (1981) did not employ explicit
sampling weights (i.e., all weights were set to one).
There were 304 interviews in the summer and 204
in the fall. About 60% of anglers were White,
20% Black, and 19% Asian, and the rest were
Hispanic or Native American. Table 10-52 gives the
distribution of fishing frequency calculated by Pierce
et al. (1981); for both the summer and fall, more than
half of the fishermen caught and consumed fish
weekly. The dominant (by weight) species caught
were Pacific hake and walleye pollock. Pierce et al.
(1981) did not present a distribution of fish intake or
a mean fish intake rate.
Price et al. (1994) obtained the raw data from this
survey and performed a re-analysis using sampling
weights proportional to inverse fishing frequency.
The rationale for these weights is explained in
Section 10.1 and in the discussion of the Puffer et al.
(1981) study (see Section 10.4.2.2). In the
re-analysis, Price et al. (1994) calculated a median
intake rate of 1.0 g/day and a 90th percentile rate of
13 g/day. The distribution of fishing frequency
generated by Pierce et al. (1981) is shown in
Table 10-52. Note that when equal weights were
used, Price et al. (1994) found a median rate of
19 g/day (Table 10-53).
The same limitations apply to interpreting the
results presented here to those presented in the
discussion of Puffer et al. (1981) (see Section
10.4.2.2). As with the Puffer et al. (1981) data
described in the following section, these values (1.0
g/day and 19 g/day) are both probably underestimates
because the sampling probabilities are less than
proportional to fishing frequency; thus, the true target
population median is probably somewhat above 1.0
g/day, and the true 50th percentile of the resource
utilization distribution is probably somewhat higher
than 19 g/day. The data from this survey provide an
indication of consumption patterns for the time
period around 1980 in the Commencement Bay area.
However, the data may not reflect current
consumption patterns because fishing advisories were
instituted due to local contamination. Another
limitation of these data is that fish consumption rates
were estimated indirectly from a series of
assumptions.
10.4.2.2. Puffer etal. (1981)—Intake Rates of
Potentially Hazardous Marine Fish
Caught in the Metropolitan Los Angeles
Area
Puffer et al. (1981) conducted a creel survey with
sport fishermen in the Los Angeles area in 1980. The
survey was conducted at 12 sites in the harbor and
coastal areas to evaluate intake rates of potentially
hazardous marine fish and shellfish by local,
non-professional fishermen. It was conducted for the
full 1980 calendar year, although inclement weather
in January, February, and March limited the interview
days. Each site was surveyed an average of three
times per month, on different days, and at a different
time of the day. The survey questionnaire was
designed to collect information on demographic
characteristics, fishing patterns, species, number of
fish caught, and fish consumption patterns. Scales
were used to obtain fish weights. Interviews were
conducted only with anglers who had caught fish, and
the anglers were interviewed only once during the
entire survey period.
Puffer et al. (1981) estimated daily consumption
rates (g/day) for each angler using the following
equation:
where:
K x N x W x F)/[E x 3657 (Eqn. 10-3)
K= edible fraction of fish (0.25 to 0.5
depending on species),
N = number of fish in catch,
W= average weight of (grams) fish in
catch,
F = frequency of fishing/year, and
E = number of fish eaters in family/living
group.
No explicit survey weights were used in
analyzing this survey; thus, each respondent's data
were given equal weight.
A total of 1,059 anglers were interviewed for the
survey. Table 10-54 shows the ethnic and age
distribution of respondents; 88% of respondents were
male. The median intake rate was higher for
Asian/Samoan anglers (median 70.6 g/day) than for
other ethnic groups and higher for those ages over
65 years (median 113.0 g/day) than for other age
groups. Puffer et al. (1981) found similar median
intake rates for seasons: 36.3 g/day for November
through March and 37.7 g/day for April through
October. Puffer et al. (1981) also evaluated fish
preparation methods; Appendix 10B presents these
data. Table 10-55 presents the cumulative distribution
of recreational fish (finfish and shellfish)
consumption by survey respondents; this distribution
was calculated only for those fishermen who
indicated they eat the fish they catch. The median fish
consumption rate was 37 g/day, and the
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90th percentile rate was 225 g/day (Puffer etal.,
1981). Table 10-56 presents a description of catch
patterns for primary fish species kept.
As mentioned in the introduction to this chapter,
intake distributions derived from analyses of creel
surveys that did not employ weights reflective of
sampling probabilities will overestimate the target
population intake distribution and will, in fact, be
more reflective of the "resource utilization
distribution." Therefore, the reported median level of
37.3 g/day does not reflect the fact that 50% of the
target population has intake above this level; instead,
50% of recreational fish consumption is by
individuals consuming at or above 37 g/day. In order
to generate an intake distribution reflective of that in
the target population, weights inversely proportional
to sampling probability need to be employed. Price
et al. (1994) made this attempt with the Puffer et al.
(1981) survey data, using inverse fishing frequencies
as the sampling weights. Price et al. (1994) was
unable to get the raw data for this survey, but through
the use of frequency tables and the average level of
fish consumption per fishing trip provided in Puffer
et al. (1981), generated an approximate revised intake
distribution. This distribution was dramatically lower
than that obtained by Puffer et al. (1981); the median
was estimated at 2.9 g/day (compared with 37 from
Puffer et al. [1981]) and the 90th percentile at
35 g/day (compared to 225 g/day from Puffer etal.
[1981]).
There are several limitations to the interpretation
of the percentiles presented by both Puffer etal.
(1981) and Price et al. (1994). As described in
Appendix 10A, the interpretation of percentiles
reported from creel surveys in terms of percentiles of
the "resource utilization distribution" is approximate
and depends on several assumptions. One of these
assumptions is that sampling probability is
proportional to inverse fishing frequency. In this
survey, where interviewers revisited sites numerous
times and anglers were not interviewed more than
once, this assumption is not valid, though it is likely
that the sampling probability is still highly dependent
on fishing frequency, so that the assumption does
hold in an approximate sense. The validity of this
assumption also impacts the interpretation of
percentiles reported by Price et al. (1994) because
inverse frequency was used as sampling weights. It is
likely that the value (2.9 g/day) of Price et al. (1994)
underestimates somewhat the median intake in the
target population but is much closer to the actual
value than the Puffer et al. (1981) estimate of
37.3 g/day. Similar statements would apply about the
90th percentile. Similarly, the 37.3-g/day median
value, if interpreted as the 50th percentile of the
"resource utilization distribution," is also somewhat
of an underestimate.
The fish intake distribution generated by Puffer et
al. (1981) (and by Price et al. [1994]) was based only
on fishermen who caught fish and ate the fish they
caught. If all anglers were included, intake estimates
would be somewhat lower. In contrast, the survey
assumed that the number of fish caught at the time of
the interview was all that would be caught that day. If
it were possible to interview fishermen at the
conclusion of their fishing day, intake estimates could
be potentially higher. An additional factor potentially
affecting intake rates is that fishing quarantines were
imposed in early spring due to heavy sewage
overflow (Puffer et al., 1981). These data are also
over 20 years old and may not reflect current
behaviors.
10.4.2.3. Burger and Gochfeld (1991)—Fishing a
Superfund Site: Dissonance and Risk
Perception of Environmental Hazards by
Fishermen in Puerto Rico
Burger and Gochfeld (1991) examined fishing
behavior, consumption patterns, and risk perceptions
of fishermen and crabbers engaged in recreational
and subsistence fishing in the Humacao Lagoons
located in eastern Puerto Rico. For a 20-day period in
February and March 1988, all persons encountered
fishing and crabbing at the Humacao lagoons and at
control sites were interviewed on fishing patterns,
consumption patterns, cooking patterns, fishing and
crabbing techniques, and consumption warnings. The
control interviews were conducted at sites that were
ecologically similar to the Humacao lagoons and
contained the same species of fish and crabs. A total
of 45 groups of people (3 to 4 people per group)
fishing at the Humacao Lagoons and 17 control
groups (3 to 4 people per group) were interviewed.
Most people fished in the late afternoon or
evenings, and on weekends. Eighty percent of the
fishing groups from the lagoons were male. The
breakdown according to age is as follows: 27% were
younger than 20 years, 49% were 21-40 years old,
24% were 41-60 years old, and 2% were over 60.
The age groups for fishing were generally lower than
the groups for crabbing. Caught fish were primarily
tilapia and some tarpon. All crabs caught were blue
crabs.
On average, people at Humacao ate about 7 fish
(TV =25) or 13 crabs (TV =20) each week, while
people fishing at the control site ate about 2 fish
(TV =9) and 14 crabs (TV =9) a week (see
Table 10-57). All of the crabbers (100%) and 96% of
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the fisherman at the lagoons had heard of a
contamination problem.
All the interviewees that knew of a contamination
problem knew that the contaminant was mercury.
Most fisherman and crabbers believed that the water
was clean and the catch was safe (fisherman—96%
and crabbers—100%), and all fisherman and crabbers
ate their catch. Seventy-two percent of the fisherman
and crabbers from the lagoons lived within 3 km,
18% lived 17-30 km away, and 1 group came from
66 km away. Because many of the people interviewed
had cars, researchers concluded that they were not
impoverished and did not need the fish as a protein
substitute.
Burger and Gochfeld (1991) noted that fisherman
and crabbers did not know of anyone who had gotten
sick from eating catches from the lagoons, and the
potential of chronic health effects did not enter into
their consideration. The study concluded that
fisherman and crabbers experienced an
incompatibility between their own experiences, and
the risk driven by media reports of pollution and the
lack of governmental prohibition of fishing.
One limitation of the study is that consumption
rates were based on groups not individuals. In
addition, rates were given in terms of fish per week
and not mass consumed per time or body weight.
10.4.2.4. Burger et al. (1992)—Exposure
Assessment for Heavy Metal Ingestion
from Sport Fish in Puerto Rico:
Estimating Risk for Local Fishermen
Burger et al. (1992) conducted another study in
conjunction with the Burger and Gochfeld (1991)
study. The study interviewed 45 groups of fishermen
at Humacao and 14 groups at Boqueron in Puerto
Rico. The respondents were 80% male, 50% were 21
to 40 years old, most fished with pole or cast, and
most fished for 1.5 hours. In Humacao, 96% claimed
that they ate the entire fish besides the head. The fish
were either fried or boiled in stews or soups.
In February and March, 64% of the group caught
only tilapia, but respondents stated that in June they
caught mostly robalo and tarpon. Generally, the
fisherman stated that they ate 2.1 fish (maximum of
11 fish) from Boqueron and 6.8 fish (maximum of
23) from Humacao per week. The study reported that
adults ate 374 grams of fish per day, while children
ate 127 grams per day. In order to calculate the daily
mass intake of fish, the study assumed that an adult
ate 4.4 robalos, each weighing 595 grams over a
7-day period, and a child ate 1.5 robalos, each
weighing 595 grams over a 7-day period. The study
used a maximum consumption value of 200 g/day for
fishermen to create various hazard indices.
One limitation of this study is that the
consumption rates were based on groups not
individuals. In addition, consumption rates were
calculated using the average fish weight and the
number of meals per week reported by the
respondents.
10.4.2.5. Moya and Phillips (2001)—Analysis of
Consumption of Home-Produced Foods
The 1987-1988 NFCS was also utilized to
estimate consumption of home-produced (i.e.,
self-caught) fish (as well as home-produced fruits,
vegetables, meats, and dairy products) in the general
U.S. population. The methodology for estimating
home-produced intake rates was rather complex and
involved combining the household and individual
components of the NFCS; the methodology, as well
as the estimated intake rates, are described in detail in
Chapter 13. Some of the data on fish consumption
from households who consumed self-caught fish are
also provided in Moya and Phillips (2001). A total of
2.1% of the total survey population reported
self-caught fish consumption during the survey week.
Among consumers, the mean intake rate was
2.07 g/kg-day, and the 95th percentile was
7.83 g/kg-day; the mean per capita intake rate was
0.04 g/kg-day. Note that intake rates for
home-produced foods were indexed to the weight of
the survey respondent and reported in g/kg-day.
The NFCS household component contains the
question "Does anyone in your household fish?" For
the population answering yes to this question (21% of
households), the NFCS data show that 9% consumed
home-produced fish in the week of the survey; the
mean intake rate for fish consumers from fishing
households was 2.2 g/kg-day (all ages combined, see
Table 13-20) for the fishing population. Note that
92% of individuals reporting home-produced fish
consumption for the week of the survey indicated that
a household member fishes; the overall mean intake
rate among home-produced fish consumers,
regardless of fishing status, was the above reported
2.07 g/kg-day). The mean per capita intake rate
among all those living in fishing household is then
calculated as 0.2 g/kg-day (2.2 x 0.09). Using the
estimated average weight of survey participants of
59 kg, this translates into an average national per
capita self-caught fish consumption rate of 11.8 g/day
among the population of individuals who fish.
However, this intake rate represents intake of both
freshwater and saltwater fish combined. According to
the data in Chapter 13 (see Table 13-68),
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home-produced fish consumption accounted for
32.5% of total fish consumption among households
who fish.
As discussed in Chapter 13 of this handbook,
intake rates for home-produced foods, including fish,
are based on the results of the household survey, and
as such, reflect the weight of fish taken into the
household. In most of the recreational fish surveys
discussed later in this section, the weight of the fish
catch (which generally corresponds to the weight
taken into the household) is multiplied by an edible
fraction to convert to an uncooked equivalent of the
amount consumed. This fraction may be species
specific, but some studies used an average value;
these average values ranged from 0.3 to 0.5. Using a
factor of 0.5 would convert the above 11.8 g/day rate
to 5.9 g/day.
The advantage of this study is that it provides a
national perspective on the consumption of
serf-caught fish. A limitation of this study is that
these values include both freshwater and saltwater
fish. The proportion of freshwater to saltwater is
unknown and will vary depending on geographical
location. Intake data cannot be presented for various
age groups due to sample size limitations. The
unweighted number of households, who responded
positively to the survey question "do you fish"? was
also low (i.e., 220 households).
10.4.2.6. KCA Research Division (1994)—Fish
Consumption of Delaware Recreational
Fishermen and Their Households
In support of the Delaware Estuary Program, the
State of Delaware's Department of Natural Resources
and Environmental Control conducted a survey of
marine recreational fishermen along the coastal areas
of Delaware between July 1992 and June 1993 (KCA
Research Division, 1994). There were
two components of the study: (1) a field survey of
fishermen as they returned from their fishing trips,
and (2) a telephone follow-up call.
The purpose of the first component was to obtain
information on their fishing trips and on their
household composition. This information included
the method and location of fishing, number of fish
caught and kept by species, and weight of each fish
kept. Household information included race, age, sex,
and number of persons in the household. Information
was also recorded as to the location of the angler
intercept (i.e., where the angler was interviewed) and
the location of the household.
The purpose of the second component was to
obtain information on the amount of fish caught and
kept from the fishing trip and then eaten by the
household. The methods used for preparing and
cooking the fish were also documented.
The field portion of the study was designed to
interview 2,000 anglers. Data were obtained from
1,901 anglers, representing 6,204 household
members (KCA Research Division, 1994). While the
primary goal of the study was to collect data on
marine recreational fishing practices, the survey
included some freshwater fishing and crabbing sites.
Follow-up phone interviews typically occurred
2 weeks after the field interview and were used to
gather information about consumption. Interviewers
aided respondents in their estimation of fish intake by
describing the weight of ordinary products, for the
purpose of comparison to the quantity of fish eaten.
Information on the number of fishing trips a
respondent had taken during the month was used to
estimate average annual consumption rates.
For all respondents, the average consumption was
17.5 g/day. Males were found to have consumed
more fish than women, and Caucasians consumed
more fish per day than the other races surveyed (see
Table 10-58). More than half of the study respondents
reported that they skinned the fish that they ate (i.e.,
450 out of 807 who reported whether they skinned
their catch); the majority ate filleted fish (i.e., 617 out
of 794 who reported the preparation method used),
and over half fried their fish (i.e., 506 out of 875 who
reported the cooking method). Information on
consumption relative to preparation method indicated
a higher consumption level for skinned fish (0.627
oz/day) than for un-skinned fish (0.517 oz/day).
Although most respondents fried their catch (0.553
oz/day), baking and broiling were also common
(0.484 and 0.541 oz/day, respectively).
One limitation of this study is that information on
fish consumption is based on anglers' recall of
amount of fish eaten. While this study provides
information on fish consumption of various ethnic
groups, another limitation of this study is that the
sample size for ethnic groups was very small. Also,
the study was limited to one geographic area and may
not be representative of the U.S. population.
10.4.2.7. Santa Monica Bay Restoration Project
(SMBRP) (1994)—Seafood Consumption
Habits of Recreational Anglers in Santa
Monica Bay, Los Angeles, CA
The Santa Monica Bay Restoration Project
(SMBRP) conducted a study on the seafood
consumption habits of recreational anglers in Santa
Monica Bay, CA. The study was conducted between
September 1991 and August 1992. Surveys were
conducted at 11 piers and jetties, three private boat
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launches and hoists, 11 beach and intertidal sites, and
five party boat landings. Information requested in the
survey included fishing history, types of fish eaten,
consumption habits, methods of preparing fish, and
demographics. Consumption rates were calculated
based on the anglers' estimates of meal size relative
to a model fish fillet that represented a 150-gram
meal. Interviewers identified 67 species of fish,
2 species of crustaceans, 2 species of mollusks, and
1 species of echinoderms that had been caught from
the study area by recreational anglers during the
study period. The most abundant species caught were
chub mackerel, barred sand bass, kelp bass, white
croaker, Pacific barracuda, and Pacific bonito.
A total of 2,376 anglers were censused during
113 separate surveys. Of those anglers, 1,243 were
successfully interviewed, and 554 provided sufficient
information for calculation of consumption rates. The
socio-demographics of the sample population were as
follows: most anglers were male (93%), 21 to
40 years old (54%), White (43%), and had an annual
household income of $25,000 to $50,000 (39%).
The results of the survey showed that the mean
consumption rate was 50 g/day, while the
90th percentile was over two times higher at
107 g/day (see Table 10-59). Of the identified ethnic
groups, Asians had the highest mean consumption
rate (51 g/day) and the highest 90th percentile value
for consumption rate (116 g/day). Anglers with
annual household incomes greater than $50,000 had
the highest mean consumption rate (59 g/day) and the
highest 90th percentile consumption rate (129 g/day).
Species of fish that were consumed in larger amounts
than other species included barred sand bass, Pacific
barracuda, kelp bass, rockfish species, Pacific bonito,
and California halibut.
About 77% of all anglers were aware of health
warnings about consumption of fish from Santa
Monica Bay. Of these anglers, 50% had altered their
seafood consumption habits as a result of the
warnings (46% stopped consuming some species,
25% ate less of all species, 19% stopped consuming
all fish, and 10% ate less of some species). Most
anglers in the ethnic groups surveyed were aware of
the health-risk warnings, but Asian and White anglers
were more likely to alter their consumption behavior
based on these warnings.
One limitation of this study is the low numbers of
anglers younger than 21 years of age. In this study, if
several anglers from the same household were
fishing, only the head of the household was
interviewed. Hence, young individuals were
frequently not interviewed and, therefore, are under-
represented in this study.
It should also be noted that this study was not
adjusted for avidity bias, but the California Office of
Environmental Health Hazard Assessment has
adjusted the distribution of fish consumption for
avidity bias and other factors in the Air Toxics Hot
Spots Program Risk Assessment Guidelines Part IV:
Exposure Assessment and Stochastic Analysis
Technical Support (see http://www.oehha.ca.gov/
air/hot_spots/finalStoc. html).
10.4.2.8. U.S. DHHS (1995)—Health Study to
Assess the Human Health Effects of
Mercury Exposure to Fish Consumed
from the Everglades
A health study was conducted in two phases in the
Everglades, Florida for the U.S. Department of
Health and Human Services (U.S. DHHS, 1995). The
objectives of the first phase were to (a) describe the
human populations at risk for mercury exposure
through their consumption of fish and other
contaminated animals from the Everglades and
(b) evaluate the extent of mercury exposure in those
persons consuming contaminated food and their
compliance with the voluntary health advisory. The
second phase of the study involved neurologic testing
of all study participants who had total mercury levels
in hair greater than 7.5 ug/g.
Study participants were identified by using
special targeted screenings, mailings to residents,
postings and multi-media advertisements of the study
throughout the Everglades region, and direct
discussions with people fishing along the canals and
waterways in the contaminated areas. The
contaminated areas were identified by the
interviewers and long-term Everglade residents. Of a
total of 1,794 individuals sampled, 405 individuals
were eligible to participate in the study because they
had consumed fish or wildlife from the Everglades at
least once per month in the last 3 months of the study
period. The majority of the eligible participants
(>93%) were either subsistence fishermen, Everglade
residents, or both. Subsistence fishermen were
defined in the survey as "people who rely on fish and
the wildlife of the Everglades as a source of dietary
protein for themselves and their families." Of the
total eligible participants, 55 individuals refused to
participate in the survey. Useable data were obtained
from 330 respondents ranging in age from 10-81
years of age (mean age 39 years ± 18.8) (U.S. DHHS,
1995). Respondents were administered a three-page
questionnaire from which demographic information,
fishing and eating habits, and other variables were
obtained (U.S. DHHS, 1995).
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Table 10-60 shows the ranges, means, and
standard deviations of selected characteristics by
various groups of the survey population. Sixty-
two percent of the respondents were male with a
slight preponderance of Black individuals (43%
White, 46% Black non-Hispanic, and 11% Hispanic).
Most of the respondents reported earning an annual
income of $15,000 or less per family before taxes
(U.S. DHHS, 1995). The mean number of years
fished along the canals by the respondents was
15.8 years with a standard deviation of 15.8. The
mean number of times per week fish consumers
reported eating fish over the last 6 months and last
month of the survey period were 1.8 and 1.5 per
week with standard deviations of 2.5 and 1.4,
respectively. Table 10-60 also indicates that 71% of
the respondents reported knowing about the mercury
health advisories. Of those who were aware, 26%
reported that they had lowered their consumption of
fish caught in the Everglades, while the rest (74%)
reported no change in consumption patterns (U.S.
DHHS, 1995).
A limitation of this study is that fish intake rates
(g/day) were not reported. Another limitation is that
the survey was site limited and, therefore, not
representative of the U.S. population. An advantage
of this study is that it is one of the few studies
targeting populations expected to have higher
consumption rates.
10.4.2.9. Alcoa (1998)—Draft Report for the
Finfish/Shellfish Consumption Study—
Alcoa (Point Comfort)/Lavaca Bay
Superfund Site
The Texas Saltwater Angler Survey was
conducted in 1996/1997 to evaluate the quantity and
species of finfish and shellfish consumed by
individuals who fish at Lavaca Bay (Alcoa, 1998).
The target population for this study was residents of
three Texas counties: Calhoun, Victoria, and Jackson
(over 70% of the anglers who fish Lavaca Bay are
from these three counties). The random sample
design specified that the population percentages for
the counties should be as follows: 50% from
Calhoun, 30% from Victoria, and 20% from Jackson.
Each individual in the sample population was sent
an introductory note describing the study and then
was contacted by telephone. People who agreed to
participate and had taken fewer than six fishing trips
to Lavaca Bay were interviewed by telephone.
Persons who agreed to participate and had taken
more than five fishing trips to Lavaca Bay were sent
a mail survey with the same questions. A total of
1,979 anglers participated in this survey, representing
a response rate greater than 68%. Data were collected
from the households for men, women, and children.
The information collected as part of the survey
included recreational fishing trip information for
November 1996 (i.e., fishing site, site facilities,
distance traveled, number and species caught),
serf-caught fish consumption (by the respondent,
spouse and child, if applicable), opinions on different
types of fishing experiences, and
socio-demographics. Portion size for shellfish was
determined by utilizing the number of shrimp, crabs,
oysters, etc. that an individual consumed during a
meal and the assumed tissue weight of the particular
species of shellfish.
Table 10-61 presents the results of the study.
Adult men consumed 25 grams of self-caught finfish
per day while women consumed an average of
18 grams daily. Women of childbearing age
consumed 19 grams per day, on average. Small
children were found to consume 11 g/day, and youths
consumed 16 g/day, on average. Less shellfish was
consumed by all individuals than finfish. Men
consumed an average of 2 g/day, women and youths
an average of 1 g/day, and small children consumed
less than 1 g/day of shellfish.
The study results also showed the number of
average meals and portion sizes for the respondents,
(see Table 10-62). On average, members of each
cohort consumed slightly more than 3 meals per
month of finfish, although small children and youths
consumed slightly less than 3 meals per month of
finfish and less than 1 meal per month of shellfish.
For finfish, adult men consumed an average, per
meal, portion size of 8 ounces, while women and
youths consumed 7 ounces, and small children
consumed less than 5 ounces per meal. The average
number of shellfish meals consumed per month for
all cohorts was less than one. Adult men consumed
an average shellfish portion size of 4 ounces, women
and youth 3 ounces, and small children consumed
2 ounces per meal.
The study also discussed the species composition
of self-caught fish consumed by source.
Four different sources of fish were included: fish
consumed from the closure area, fish consumed from
Lavaca Bay, fish consumed from all waters, and all
serf-caught finfish and shellfish consumed, including
preserved (i.e., frozen or smoked) fish where the
location of the catch is not known. Red drum
comprised the bulk of total finfish grams consumed
from any area, while black drum represented the
smallest amount of finfish grams consumed. Overall,
almost 40% of all self-caught finfish consumed were
red drum, followed by speckled sea trout, flounder,
all other finfish (all species were not specifically
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examined in this study), and black dram. Out of all
self-caught shellfish, oysters accounted for 37%, blue
crabs for 35%, and shrimp for 29% of the total.
The study authors noted that because the survey
relied on the anglers' recall of meal frequency and
portion, fish consumption may have been
overestimated. There was evidence of overestimation
when the data were validated, and approximately
10% of anglers reported consuming more fish than
what they caught and kept. Also, the study was
conducted at one geographic location and may not be
representative of the U.S. population.
10.4.2.10. Burger et al. (1998)—Fishing,
Consumption, and Risk Perception in
Fisherfolk along an East Coast Estuary
Burger et al. (1998) examined fishing behavior,
consumption patterns, and risk perceptions of
515 people that were fishing and crabbing in
Barnegat Bay, NJ. This research also tested the null
hypotheses that there are no sex differences in fishing
behavior and consumption patterns and no sex
differences in the perception offish and crab safety.
The researchers interviewed 515 people who were
fishing or crabbing on Barnegat Bay and Great Bay.
Interviews were conducted from June 22 until
September 27, 1996. Fifteen percent of the fishermen
approached refused to be interviewed, usually
because they did not have the time to participate. The
questionnaire that researchers used to conduct the
interviews contained questions about fishing
behavior, consumption patterns, cooking patterns,
warnings, and safety associated with the seafood,
environmental problems, and changes in the Bay, and
personal demographics.
Eighty-four percent of those who were
interviewed were men, 95% were White, and the rest
were evenly divided between African American,
Hispanic, and Asian. The age of interviewees ranged
from 13 to 92 years. The subjects fished an average
of seven times per month and crabbed three times per
month (see Table 10-63). Bluefish (Pomatomus
saltatrix), fluke or summer flounder (Paralichthys
dentatus), and weakfish (Cynoscion regalis) were the
most frequently caught fish. The researchers found
that the average consumption rate for people fishing
along the Barnegat Bay was 5 fish meals per month
(eating just under 10 ounces per meal) for an
approximate total of 1,450 grams of fish per month
(48.3 g/day). Most of the subjects (80%) ate the fish
they caught.
The study found that there were significant
differences in fishing behavior and consumption as a
function of sex. Women had more children with them
when fishing, and more women fished on foot along
the Bay. The consumption by women included a
significantly lower proportion of self-caught fish than
men. Men ate significantly larger portions of fish per
meal than did women, and men ate the whole fish
more often. The study results showed that there were
no sex differences with regard to the average number
of fish caught or in fish size. Nearly 90% of the
subjects believed the fish and crabs from Barnegat
Bay were safe to eat, although approximately 40% of
the subjects had heard warnings about their safety.
The subjects generally did not have a clear
understanding of the relationships between
contaminants and fish size or trophic level. The
researchers suggested that reducing the risk from
contaminants does not necessarily involve a decrease
in consumption rates but rather a change in the fish
species and sizes consumed.
While the study provides some useful information
on sex difference in fishing behavior and
consumption, the study is limited in that the majority
of the people surveyed were White males. There were
low numbers for women and ethnic groups.
10.4.2.11. Chiang (1998)—A Seafood Consumption
Survey of the Laotian Community of West
Contra Costa County, CA
A survey of members of the Laotian community
of West Contra Costa, CA, was conducted to obtain
data on the fishing and fish consumption activities of
this community. A questionnaire was developed and
translated by the survey staff into the many ethnic
languages spoken by the members of the Laotian
community. The survey questions covered the
following topics: demographics, fishing and fish
consumption habits back home, current fishing and
fish consumption habits, fish preparation methods,
fish species commonly caught, fishing locations, and
awareness of the health advisory for this area. A total
of 229 people were surveyed.
Most respondents reported eating fish a few times
per month, and the most common portion size was
about 3 ounces. The mean amount of fish eaten per
day was reported as 18.3 g/day, with a maximum of
182.3 g/day (see Table 10-64). "Fish consumers"
were considered to be people who ate fish at least
once a month, and this group made up 86.9% of the
people surveyed. The mean fish consumption rate for
this group ("fish consumers") averaged 21.4 g/day.
Catfish was most often mentioned when respondents
were asked to name the fish they caught, but striped
bass was the species reported caught most often by
respondents. Soups/stews were reported as the most
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common preparation method of fish (86.4%)
followed by frying (78.4%), and baking (63.6%).
Of all survey respondents, 48.5% reported having
heard of the health advisory about eating fish and
shellfish from San Francisco Bay. Of those that had
heard the advisory, 59.5% reported recalling its
contents, and 60.3% said that it had influenced their
fishing and fish consumption patterns.
Some sectors of the Laotian community were not
included in the survey such as the Lue, Hmong, and
Lahu groups. However, it was noted that the groups
excluded from the survey do not differ greatly from
the sample population in terms of seafood
consumption and fishing practices. The study authors
also indicated that participants may have
under-reported fishing and fish consumption
practices due to recent publicity about contamination
of the Bay, fear of losing disability benefits, and fear
that the survey was linked to law enforcement actions
about fishing from the Bay. Another limitation of the
study involved the use of a 3-ounce fish fillet model
to estimate portion size of fish consumed. The use of
this small model may have biased respondents to
choose a smaller portion size than what they actually
eat. In addition, the study authors noted that the fillet
model may not have been appropriate for estimating
fish portions eaten by those respondents who eat
"family style" meals.
10.4.2.12. San Francisco Estuary Institute (SFEI)
(2000)—Technical Report: San Francisco
Bay Seafood Consumption Report
A comprehensive study of 1,331 anglers was
conducted by the California Department of Health
Services between July 1998 and June 1999 at various
recreational fishing locations in the San Francisco
Bay area (SFEI, 2000). The catching and
consumption of 13 finned fish species and 3 shellfish
species were investigated to determine the number of
meals eaten from recreational and other sources such
as restaurants and grocery stores. The method of fish
preparation, including the parts of the fish eaten, was
also documented. Information was gathered on the
amount of fish consumed per meal, as well as
respondents' ethnicity, age, income level, education,
and the mode of fishing (e.g., pier, boat, and beach).
Questions were also asked to ascertain the anglers'
knowledge and response to local fish advisories.
Respondents were asked to recall their
fishing/consumption experiences within the previous
4 weeks. Anglers were not asked about the
consumption habits of other members of their
families.
About 15% of the anglers reported that they do
not eat San Francisco Bay fish (whether serf-caught
or commercial). Of those who did consume Bay fish,
80% consumed about 1 fish meal per month or less;
10% ate about 2 fish meals per month; and 10% ate
more than 2 fish meals per month, which is above the
advisory level for fish. (The advisory level was
16 grams per day, or about two 8-ounce meals per
4 weeks.) Two-thirds of those consuming fish at
levels above the advisory limit consumed more than
twice the advisory limit. Difference in income,
education, or fishing mode did not markedly change
anglers' likelihood of eating in excess of the advisory
limit. African Americans and Filipino anglers
reported higher consumption levels than Caucasians
(see Table 10-65). The overall mean consumption
rate was 23 g/day.
More than 50% of the finfish caught by anglers
were striped bass, and about 25% were halibut.
Approximately 15% of the anglers caught each of the
following fish: jacksmelt, sturgeon, and white
croaker. All other species were caught by less than
10% of the anglers. For white croaker fish
consumption: (1) lower income anglers consumed
statistically more fish than mid- and upper-level
income anglers, (2) anglers who did not have a high
school education consumed more than those anglers
with higher education levels, and (3) anglers of Asian
descent consumed significantly more than anglers of
other ethnic backgrounds. Asian anglers were more
likely to eat fish skin, cooking juices, and raw fish
than other anglers. These portions of the fish are
believed to be more likely to contain higher levels of
contamination. Likewise, skin consumption was
higher for lower income and shore-based anglers.
Anglers who had eaten Bay fish in the previous
4 weeks indicated, in general, that they were likely to
have eaten 1 fish meal from another source in the
same time period.
More than 60% of the anglers interviewed
reported having knowledge of the health advisories.
Of that 60%, only about one-third reported changing
their fish-consumption behavior.
A limitation of this study is that the sample size
for ethnic groups was very small. Data are also
specific to the San Francisco Bay area and may not
be representative of anglers in other locations.
10.4.2.13. Burger (2002a)—Consumption Patterns
and Why People Eat Fish
Burger (2002a) evaluated fishing behavior and
consumption patterns among 267 anglers who were
interviewed at locations around Newark Bay and the
New York-New Jersey Harbor estuary in 1999.
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Among the 267 study respondents, 13% were Asian,
21% were Hispanic, 23% were Black, and 43% were
White. Survey participants provided demographic
information as well as information on their fish and
crab consumption, knowledge of fishing advisories,
and reasons for angling. Individual monthly fish
consumption was estimated by multiplying the
reported number of fish meals eaten per month by an
average portion size, based on comparisons to a
three-dimensional model of an 8-ounce fish fillet.
Individual monthly crab consumption was estimated
by multiplying the reported number of crabs eaten
per month by the edible portion of crab, which was
assumed to weigh 70 grams. Yearly fish and crab
consumption was estimated by multiplying the
monthly consumption rates by the number of months
in a year over which the survey respondents reported
eating serf-caught fish or crabs. Intake rates were
provided separately for those who fished only (44%),
for those who crabbed only (44%), and for
respondents who reported both fishing and crabbing
(12%) (Burger, 2002a). Burger (2002a) also reported
that more than 30% of the respondents reported that
they did not eat the fish or crabs that they caught.
Table 10-66 provides the average daily intake rates of
fish and crab. U.S. EPA calculated these average
daily intake rates by dividing the yearly intake rates
provided by Burger (2002a) by 365 days/year.
Burger (2002a) also evaluated potential
differences in consumption based on age, income,
and race/ethnicity. Consumption was found to be
negatively correlated with mean income and
positively correlated with age for fish, but not crabs.
An evaluation of differences based on ethnicity
indicated that Whites were the least likely to eat their
catch than other groups; 49% of Whites, 40% of
Hispanics, 24% of Asians, and 22% of Blacks
reported that they did not eat the fish or crabs that
they caught. Among all ethnicities most people
indicated that they fished (63%) or crabbed (68%) for
recreational purposes, and very few (4%) reported
that they angled to obtain food.
The advantages of this study are that it provides
information for both fish and crab intake, and that it
provides data on intake over a longer period of time
than many of the other studies summarized in this
chapter. However, the data are for individuals living
in the Newark Bay area and may not be
representative of the U.S. population as a whole.
Also, there may be uncertainties in long-term intake
estimates that are based on recall.
10.4.2.14. Mayfield et al. (2007)—Survey of Fish
Consumption Patterns of King County
(Washington) Recreational Anglers
Mayfield et al. (2007) conducted a series of fish
consumption surveys among recreational anglers at
marine and freshwater sites in King County, WA. The
marine surveys were conducted between 1997 and
2002 at public parks and boat launches throughout
Elliot Bay and the Duwamish River, and at North
King County marine locations. The numbers of
individuals interviewed at these three locations were
807, 152, and 228, respectively. The majority of
participants were male, 15 years and older, and were
either Caucasian or Asian and Pacific Islander. Data
were collected on fishing location preferences,
fishing frequency, consumption amounts, species
preferences, cooking methods, and whether family
members would also consume the catch. Respondent
demographic data were also collected. Consumption
rates were estimated using information on fishing
frequency, weight of the catch, a cleaning factor, and
the number of individuals consuming the catch. Mean
recreational marine fish and shellfish consumption
rates were 53 g/day and 25 g/day, respectively (see
Table 10-67). Mayfield et al. (2007) also reported
differences in intake according to ethnicity. Mean
marine fish intake rates were 73, 60, 50, 43, and
35 g/day for Native American, Caucasian, Asian and
Pacific Islander, African American, and
Hispanic/Latino respondents, respectively.
The advantages of this study are that it provides
additional perspective on recreational marine fish
intake. However, the data are limited to a specific
area of the United States and may not be
representative of anglers in other locations.
10.5. FRESHWATER RECREATIONAL
STUDIES
10.5.1. Fiore et al. (1989)—Sport Fish
Consumption and Body Burden Levels of
Chlorinated Hydrocarbons: A Study of
Wisconsin Anglers
This survey, reported by Fiore et al. (1989), was
conducted to assess socio-demographic factors and
sport-fishing habits of anglers, to evaluate anglers'
comprehension of and compliance with the
Wisconsin Fish Consumption Advisory, to measure
body burden levels of polychlorinated biphenyls
(PCBs) and Dichlorodiphenyldichloroethylene
(DDE) through analysis of blood serum samples, and
to examine the relationship between body burden
levels and consumption of sport-caught fish. The
survey targeted all Wisconsin residents who had
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purchased fishing or sporting licenses in 1984 in any
of 10 pre-selected study counties. These counties
were chosen in part based on their proximity to water
bodies identified in Wisconsin fish advisories. A total
of 1,600 anglers were sent survey questionnaires
during the summer of 1985.
The survey questionnaire included questions
about fishing history, locations fished, species
targeted, kilograms caught for consumption, overall
fish consumption (including commercially caught),
and knowledge of fish advisories. The recall period
was 1 year.
A total of 801 surveys were returned
(50% response rate). Of these, 601 (75%) were from
males and 200 from females; the mean age was
37 years. Fiore et al. (1989) reported that the mean
number of fish meals for 1984 for all respondents
was 18 for sport-caught meals and 24 for
non-sport-caught meals. Fiore et al. (1989) assumed
that each fish meal consisted of 8 ounces (227 grams)
of fish to generate means and percentiles of fish
intake. The reported mean and 95th percentile intake
rate of sport-caught fish for all respondents were
11.2 g/day and 37.3 g/day, respectively. Among
consumers, who comprised 91% of all respondents,
the mean sport-caught fish intake rate was 12.3 g/day,
and the 95th percentile was 37.3 g/day. The mean
daily fish intake from all sources (both sport-caught
and commercial) was 26.1 g/day, with a 95th
percentile of 63.4 g/day. The 95th percentile of 37.3
g/day of sport caught fish represents 60 fish meals
per year; the 95th percentile of 63.4 g/day of total fish
intake represents 102 fish meals per year.
U.S. EPA obtained the raw data from this study
and calculated the distribution of the number of
sport-caught fish meals and the distribution of fish
intake rates using the same meal size (227 g/meal)
used by Fiore et al. (1989). This meal size is higher
than the mean meal size of 114 g/meal, but similar to
the 90th percentile meal size for general population
adults (age 20-39 years) reported in a study by
Smiciklas-Wright et al. (2002). However, because
data for the general population may underestimate
meal size for anglers, use of an upper percentile
general population value may reflect higher intake
among anglers. This is supported by data from other
studies in the literature that have shown that the
average meal size for sport fishing populations is
higher than those of the general population. For
example, Balcom et al. (1999) reported an average
meal size for sport-caught fish for the angler
population of 7.3 ounces (i.e., 207 grams), while the
average meal size for the general population was
5 ounces (142 grams). Other studies reported similar
meal sizes for sport-caught fish. West et al. (1989)
stated that the meal size most often reported in their
survey was 8 ounces (i.e., 227 grams), and Connelly
et al. (1996) estimated an average meal size of
216 grams. Another study reported an average meal
size of 376 grams (Burger et al., 1999). Therefore, the
meal size used by Fiore et al. (1989) was deemed
reasonable to represent a mean value for the
population of sport anglers. Table 10-68 presents
distributions of fish consumption using a meal size of
227 grams.
This study is limited in its ability to accurately
estimate intake rates because of the absence of data
on weight of fish consumed. Another limitation of
this study is that the results are based on 1-year
recall, which may tend to over-estimate the number
of fishing trips (Ebert et al., 1993). In addition, the
response rate was rather low (50%).
10.5.2. West et al. (1989)—Michigan Sport
Anglers Fish Consumption Survey
The Michigan Sport Anglers Fish Consumption
Survey (West et al., 1989) surveyed a stratified
random sample of Michigan residents with fishing
licenses. The sample was divided into 18 cohorts,
with one cohort receiving a mail questionnaire each
week between January and May 1989. The survey
included both a short-term recall component, and a
usual frequency component. For the short-term recall
component, respondents were asked to identify all
household members and list all fish meals consumed
by each household member during the past 7 days.
Information on the source of the fish for each meal
was also requested (serf-caught, gift, market, or
restaurant). Respondents were asked to categorize
serving size by comparison with pictures of 8-ounce
fish portions; serving sizes could be designated as
either "about the same size," "less," or "more" than
the size pictured. Data on fish species, locations of
serf-caught fish, and methods of preparation and
cooking were also obtained.
The usual frequency component of the survey
asked about the frequency of fish meals during each
of the four seasons and requested respondents give
the overall percentage of household fish meals that
came from recreational sources. A sample of
2,600 individuals was selected from state records to
receive survey questionnaires. A total of 2,334 survey
questionnaires were deliverable, and 1,104 were
completed and returned, giving a response rate of
47.3%.
In the analysis of the survey data by West et al.
(1989), the authors did not attempt to generate the
distribution of recreationally caught fish intake in the
survey population. U.S. EPA obtained the raw data of
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this survey for the purpose of generating fish intake
distributions and other specialized analyses.
As described elsewhere in this handbook,
percentiles of the distribution of average daily intake
reflective of long-term consumption patterns cannot,
in general, be estimated using short-term (e.g.,
1 week) data. Such data can be used to adequately
estimate mean average daily intake rates (reflective
of short- or long-term consumption); in addition,
short-term data can serve to validate estimates of
usual intake based on longer recall.
U.S. EPA first analyzed the short-term data with
the intent of estimating mean fish intake rates. In
order to compare these results with those based on
usual intake, only respondents with information on
both short-term and usual intake were included in this
analysis. For the analysis of the short-term data,
U.S. EPA modified the serving size weights used by
West et al. (1989), which were 5, 8, and 10-ounces,
respectively, for portions that were less, about the
same, and more than the 8-ounce picture. U.S. EPA
examined the percentiles of the distribution of fish
meal sizes reported in Pao et al. (1982) derived from
the 1977-1978 USD A National Food Consumption
Survey and observed that a lognormal distribution
provided a good visual fit to the percentile data.
Using this lognormal distribution, the mean values
for serving sizes greater than 8 ounces and for
serving sizes at least 10% greater than 8 ounces were
determined. In both cases, a serving size of 12 ounces
was consistent with the Pao et al. (1982) distribution.
The weights used in the U.S. EPA analysis then were
5, 8, and 12 ounces for fish meals described as less,
about the same, and more than the 8-ounces picture,
respectively. The mean serving size from Pao et al.
(1982) was about 5 ounces, well below the value of
8 ounces most commonly reported by respondents in
the West et al. (1989) survey.
Table 10-69 displays the mean number of total
and recreational fish meals for each household
member based on the 7-day recall data. Also shown
are mean fish intake rates derived by applying the
weights described above to each fish meal. Intake
was calculated on both g/day and g/kg body weight-
day bases. This analysis was restricted to individuals
who eat fish and who reside in households reporting
some recreational fish consumption during the
previous year. About 75% of survey respondents (i.e.,
licensed anglers) and about 84% of respondents who
fished in the prior year reported some household
recreational fish consumption.
The U.S. EPA analysis next attempted to use the
short-term data to validate the usual intake data. West
et al. (1989) asked the main respondent in each
household to provide estimates of their usual
frequency of fishing and eating fish, by season,
during the previous year. The survey provides a series
of frequency categories for each season, and the
respondent was asked to check the appropriate range.
The ranges used for all questions were almost daily,
2-4 times a week, once a week, 2-3 times a month,
once a month, less often, none, and don't know. For
quantitative analysis of the data, it is necessary to
convert this categorical information into numerical
frequency values. As some of the ranges are
relatively broad, the choice of conversion values can
have some effect on intake estimates. In order to
obtain optimal values, the usual fish eating frequency
reported by respondents for the season during which
the questionnaire was completed was compared to the
number of fish meals reportedly consumed by
respondents over the 7-day short-term recall period.
The results of these comparisons are displayed in
Table 10-70; it shows that, on average, there is
general agreement between estimates made using
1-year recall and estimates based on 7-day recall. The
average number of meals (1.96/week) was at the
bottom of the range for the most frequent
consumption group with data (l-\ meals/week). In
contrast, for the lower usual frequency categories, the
average number of meals was at the top, or exceeded
the top of category range. This suggests some
tendency for relatively infrequent fish eaters to
underestimate their usual frequency of fish
consumption. The last column of the table shows the
estimated fish eating frequency per week that was
selected for use in making quantitative estimates of
usual fish intake. These values were guided by the
values in the second column, except that frequency
values that were inconsistent with the ranges
provided to respondents in the survey were avoided.
Using the four seasonal fish-eating frequencies
provided by respondents and the above conversions
for reported intake frequency, U.S. EPA estimated the
average number of fish meals per week for each
respondent. This estimate, as well as the analysis
above, pertains to the total number of fish meals
eaten (in Michigan) regardless of the source of the
fish. Respondents were not asked to provide a
seasonal breakdown for eating frequency of
recreationally caught fish; rather, they provided an
overall estimate for the past year of the percent of
fish they ate that was obtained from different sources.
U.S. EPA estimated the annual frequency of
recreationally caught fish meals by multiplying the
estimated total number of fish meals by the reported
percent of fish meals obtained from recreational
sources; recreational sources were defined as either
serf-caught or a gift from family or friends.
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The usual intake component of the survey did not
include questions about the usual portion size for fish
meals. In order to estimate usual fish intake, a portion
size of 8 ounces was applied (the majority of
respondents reported this meal size in the 7-day recall
data). Individual body-weight data were used to
estimate intake on a g/kg-day basis. Table 10-71
displays the fish intake distribution estimated by U.S.
EPA.
The distribution shown in Table 10-71 is based on
respondents who consumed recreational caught fish.
As mentioned above, these represent 75% of all
respondents and 84% of respondents who reported
having fished in the prior year. Among this latter
population, the mean recreational fish intake rate is
14.4 x 0.84 = 12.1 g/day; the value of 38.7 g/day
(95th percentile among consumers) corresponds to the
95.8th percentile of the fish intake distribution in this
(fishing) population.
The advantages of this data set and analysis are
that the survey was relatively large and contained
both short-term and usual intake data. The presence
of short-term data allowed validation of the usual
intake data, which were based on long-term recall;
thus, some of the problems associated with surveys
relying on long-term recall are mitigated here.
The response rate of this survey, 47%, was
relatively low. In addition, the usual fish intake
distribution generated here employed a constant fish
meal size, 8 ounces. Although use of this value as an
average meal size was validated by the short-term
recall results, the use of a constant meal size, even if
correct on average, may seriously reduce the
variation in the estimated fish intake distribution.
This study was conducted in the winter and spring
months of 1988. This period does not include the
summer months, when peak fishing activity can be
anticipated, leading to the possibility that intake
results based on the 7-day recall data may understate
individuals' usual (annual average) fish consumption.
A second survey by West et al. (1993) gathered diary
data on fish intake for respondents spaced over a full
year. However, this later survey did not include
questions about usual fish intake and has not been re-
analyzed here. The mean recreational fish intake rates
derived from the short-term and usual components
were quite similar, however, 14.0 versus 14.4 g/day.
10.5.3. Chemrisk (1992)—Consumption of
Freshwater Fish by Maine Anglers
Chemrisk conducted a study to characterize the
rates of freshwater fish consumption among Maine
residents (Chemrisk, 1992; Ebert et al., 1993).
Because the only dietary source of local freshwater
fish is recreational fish, the anglers in Maine were
chosen as the survey population. The survey was
designed to gather information on the consumption of
fish caught by anglers from flowing (rivers and
streams) and standing (lakes and ponds) water
bodies. Respondents were asked to recall the
frequency of fishing trips during the 1989-1990
ice-fishing season, and the 1990 open water season,
the number of fish species caught during both
seasons, and to estimate the number of fish consumed
from 15 fish species. The respondents were also
asked to describe the number, species, and average
length of each sport-caught fish consumed that had
been gifts from other members of their households or
other households. The weight of fish consumed by
anglers was calculated by first multiplying the
estimated weight of the fish by the edible fraction and
then dividing this product by the number of intended
consumers. Species-specific regression equations
were utilized to estimate weight from the reported
fish length. The edible fractions used were 0.4 for
salmon, 0.78 for Atlantic smelt, and 0.3 for all other
species (Ebert et al., 1993).
A total of 2,500 prospective survey participants
were randomly selected from a list of anglers
licensed in Maine. The surveys were mailed in during
October 1990. Because this was before the end of the
open fishing season, respondents were also asked to
predict how many more open water fishing trips they
would undertake in 1990.
Chemrisk (1992) and Ebert et al. (1993)
calculated distributions of freshwater fish intake for
two populations, "all anglers" and "consuming
anglers." All anglers were defined as licensed anglers
who fished during either the 1989-1990 ice-fishing
season or the 1990 open-water season (consumers
and non-consumers) and licensed anglers who did not
fish but consumed freshwater fish caught in Maine
during these seasons. "Consuming anglers" were
defined as those anglers who consumed freshwater
fish obtained from Maine sources during the
1989-1990 ice fishing or 1990 open water fishing
season. In addition, the distribution of fish intake
from rivers and streams was also calculated for
two populations, those fishing on rivers and streams
("river anglers"), and those consuming fish from
rivers and streams ("consuming river anglers").
A total of 1,612 surveys were returned, giving a
response rate of 64%; 1,369 (85%) of the
1,612 respondents were included in the "all angler"
population, and 1,053 (65%) were included in the
"consuming angler" population. Table 10-72 presents
freshwater fish intake distributions. The mean and
95th percentile were 5.0 g/day and 21.0 g/day,
respectively, for "all anglers," and 6.4 g/day and
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26.0 g/day, respectively, for "consuming anglers."
Table 10-72 also presents intake distributions for fish
caught from rivers and streams. Among "river
anglers," the mean and 95th percentile were 1.9 g/day
and 6.2 g/day, respectively, while among "consuming
river anglers," the mean and the 95th percentile were
3.7 g/day and 12.0 g/day, respectively. Table 10-73
presents fish intake distributions by ethnic group for
consuming anglers. The highest mean intake rates
reported are for Native Americans (10 g/day) and
French Canadians (7.4 g/day). Because there was a
low number of respondents for Hispanics,
Asian/Pacific Islanders, and African Americans,
intake rates within these groups were not calculated
(Chemrisk, 1992).
Table 10-74 presents the consumption, by species,
of freshwater fish caught. The largest species
consumption was salmon from ice fishing
(-292,000 grams); white perch (380,000 grams) for
lakes and ponds; and Brook trout (420,000 grams) for
rivers and streams (Chemrisk, 1992).
U.S. EPA obtained the raw data tapes from the
marine anglers survey and performed some
specialized analyses. One analysis involved
examining the percentiles of the "resource utilization
distribution" (this distribution was defined in
Section 10.1). The 50th, or more generally, the /7th
percentile of the resource utilization distribution, is
defined as the consumption level such that p percent
of the resource is consumed by individuals with
consumptions below this level and 100-p percent by
individuals with consumptions above this level.
U.S. EPA found that 90% of recreational fish
consumption was by individuals with intake rates
above 3.1 g/day, and 50% was by individuals with
intakes above 20 g/day. Those above 3.1 g/day make
up about 30% of the "all angler" population, and
those above 20 g/day make up about 5% of this
population; thus, the top 5% of the angler population
consumed 50% of the recreational fish catch.
U.S. EPA also performed an analysis of fish
consumption among anglers and their families. This
analysis was possible because the survey included
questions on the number, sex, and age of each
individual in the household and whether the
individual consumed recreationally caught fish. The
total population of licensed anglers in this survey and
their household members was 4,872; the average
household size for the 1,612 anglers in the survey
was thus 3.0 persons. Fifty-six percent of the
population was male, and 30% was 18 or under.
A total of 55% of this population was reported to
consume freshwater recreationally caught fish in the
year of the survey. The sex and ethnic distribution of
the consumers was similar to that of the overall
population. The distribution of fish intake among the
overall household population, or among consumers in
the household, can be calculated under the
assumption that recreationally caught fish was shared
equally among all members of the household
reporting consumption of such fish (note this
assumption was used above to calculate intake rates
for anglers). With this assumption, the mean intake
rate among consumers was 5.9 g/day, with a median
of 1.8 g/day, and a 95th percentile of 23.1 g/day; for
the overall population, the mean was 3.2 g/day and
the 95th percentile was 14.1 g/day.
The results of this survey can be put into the
context of the overall Maine population. The
1,612 anglers surveyed represent about 0.7% of the
estimated 225,000 licensed anglers in Maine. It is
reasonable to assume that licensed anglers and their
families will have the highest exposure to
recreationally caught freshwater fish. Thus, to
estimate the number of persons in Maine with
recreationally caught freshwater fish intake above,
for instance, 6.5 g/day (the 80th percentile among
household consumers in this survey), one can assume
that virtually all persons came from the population of
licensed anglers and their families. The number of
persons above 6.5 g/day in the household survey
population is calculated by taking 20% (i.e., 100-
80%) of the consuming population in the survey; this
number then is 0.2 x (0.55 x 4,872) = 536. Dividing
this number by the sampling fraction of 0.007 (0.7%),
gives about 77,000 persons above 6.5 g/day of
recreational freshwater fish consumption statewide.
The 1990 census showed the population of Maine to
be 1.2 million people; thus, the 77,000 persons above
6.5 g/day represent about 6% of the state's
population.
Chemrisk (1992) reported that the fish
consumption estimates were based upon the
following assumptions: a 40% estimate as the edible
portion of landlocked and Atlantic salmon; inclusion
of the intended number of future fishing trips and an
assumption that the average success and consumption
rates for the individual angler during the trips already
taken would continue through future trips. The data
collected for this study were based on recall and
serf-reporting, which may have resulted in a biased
estimate. The social desirability of the sport and
frequency of fishing are also bias-contributing
factors; successful anglers are among the highest
consumers of freshwater fish (Chemrisk, 1992).
Additionally, fish advisories are in place in these
areas and may affect the rate of fish consumption
among anglers. The survey results showed that in
1990, 23% of all anglers consumed no freshwater
fish, and 55% of the river anglers ate no freshwater
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fish. An advantage of this study is that the sample
size is rather large.
10.5.4. Connelly et al. (1992)—Effects of Health
Advisory and Advisory Changes on
Fishing Habits and Fish Consumption in
New York Sport Fisheries
Connelly et al. (1992) conducted a study to assess
the awareness and knowledge of New York anglers
about fishing advisories and contaminants found in
fish and their fishing and fish consuming behaviors.
The survey sample consisted of 2,000 anglers with
New York State fishing licenses for the year
beginning October 1, 1990, through
September 30, 1991. A questionnaire was mailed to
the survey sample in January 1992. The questionnaire
was designed to measure catch and consumption of
fish, as well as methods of fish preparation and
knowledge of and attitudes towards health advisories
(Connelly et al., 1992). The survey-adjusted response
rate was 52.8% (1,030 questionnaires were
completed, and 51 were not deliverable).
The average and median number of fishing days
per year were 27 and 15 days, respectively (Connelly
et al., 1992). The mean number of sport-caught fish
meals was 11 meals/year. The maximum number of
meals consumed was 757 meals/year. About 25% of
anglers reported that they did not consume sport-
caught fish.
Connelly et al. (1992) found that 80% of anglers
statewide did not eat listed species or ate them within
advisory limits and followed the 1 sport-caught fish
meal per week recommended maximum. The other
20% of anglers exceeded the advisory
recommendations in some way; 15% ate listed
species above the limit, and 5% ate more than
one sport-caught meal per week.
Connelly et al. (1992) found that respondents
eating more than 1 sport-caught meal per week were
just as likely as those eating less than one meal per
week to know the recommended level of sport-caught
fish consumption, although less than 1/3 in each
group knew the level. An estimated 85% of anglers
were aware of the health advisory. Over 50% of
respondents said that they made changes in their
fishing or fish consumption behaviors in response to
health advisories.
The advisory included a section on methods that
can be used to reduce contaminant exposure.
Respondents were asked what methods they used for
fish cleaning and cooking.
A limitation of this study with respect to
estimating fish intake rates is that only the number of
sport-caught meals was ascertained, not the weight of
fish consumed. The fish meal data can be converted
to a mean intake rate (g/day) by assuming a meal size
of 227 g/meal (i.e., 8 ounces). This value
corresponds to the adult general population 90th
percentile meal size derived from Smiciklas-Wright
et al. (2002). The resulting mean intake rate among
the angler population would be 6.8 g/day. However,
about 25% of this population reported no
sport-caught fish consumption. Therefore, the mean
consumption rate among consuming anglers would
be 27.4 g/day (i.e., 6.8 g/day divided by 0.25).
The major focus of this study was not on
consumption, per se, but on the knowledge of and
impact of fish health advisories; Connelly etal.
(1992) provides important information on these
issues.
10.5.5. Hudson River Sloop Clearwater, Inc.
(1993)—Hudson River Angler Survey
Hudson River Sloop Clearwater, Inc. (1993)
conducted a survey of adherence to fish consumption
health advisories among Hudson River anglers. All
fishing has been banned on the upper Hudson River
where high levels of PCB contamination are well
documented; while voluntary recreational fish
consumption advisories have been issued for areas
south of the Troy Dam (Hudson River Sloop
Clearwater, Inc., 1993).
The survey consisted of direct interviews with
336 shore-based anglers between the months of June
and November 1991, and April and July 1992.
Table 10-75 presents socio-demographic
characteristics of the respondents. The survey sites
were selected based on observations of use by
anglers, and legal accessibility. The selected sites
included upper-, mid-, and lower- Hudson River sites
located in both rural and urban settings. The
interviews were conducted on weekends and
weekdays during morning, midday, and evening
periods. The anglers were asked specific questions
concerning: fishing and fish consumption habits;
perceptions of presence of contaminants in fish;
perceptions of risks associated with consumption of
recreationally caught fish; and awareness of, attitude
toward, and response to fish consumption advisories
or fishing bans.
Approximately 92% of the survey respondents
were male. The following statistics were provided by
Hudson River Sloop Clearwater, Inc. (1993). The
most common reason given for fishing was for
recreation or enjoyment. Over 58% of those surveyed
indicated that they eat their catch. Of those anglers
who eat their catch, 48% reported being aware of
advisories. Approximately 24% of those who said
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they currently do not eat their catch have done so in
the past. Anglers were more likely to eat their catch
from the lower Hudson areas where health advisories,
rather than fishing bans, have been issued.
Approximately 94% of Hispanic Americans were
likely to eat their catch, while 77% of African
Americans and 47% of Caucasian Americans
intended to eat their catch. Of those who eat their
catch, 87% were likely to share their meal with others
(including women of childbearing age, and children
under the age of 15).
For subsistence anglers, more low-income than
upper-income anglers eat their catch (Hudson River
Sloop Clearwater, Inc., 1993). Approximately 10% of
the respondents stated that food was their primary
reason for fishing; this group is more likely to be in
the lowest per capita income group (Hudson River
Sloop Clearwater, Inc., 1993).
The average frequency of fish consumption
reported was just under 1 (0.9) meal over the
previous week, and 3 meals over the previous month.
Approximately 35% of all anglers who eat their catch
exceeded the amounts recommended by the New
York State health advisories. Less than half (48%) of
all the anglers interviewed were aware of the State
health advisories or fishing bans. Only 42% of those
anglers aware of the advisories have changed their
fishing habits as a result.
The advantages of this study include in-person
interviews with 95% of all anglers approached;
field-tested questions designed to minimize
interviewer bias; and candid responses concerning
consumption of fish from contaminated waters. The
limitations of this study are that specific intake
amounts are not indicated, and that only shore-based
anglers were interviewed.
10.5.6. West et al. (1993)—Michigan Sport
Anglers Fish Consumption Study, 1991—
1992
West et al. (1993) conducted a survey financed by
the Michigan Great Lakes Protection Fund, as a
follow-up to the earlier 1989 Michigan survey
described previously. The major purpose of 1991-
1992 survey was to provide short-term recall data of
recreational fish consumption over a full year period;
the 1989 survey, in contrast, was conducted over only
a half year period (West et al., 1993).
This survey was similar in design to the 1989
Michigan survey. A sample of 7,000 persons with
Michigan fishing licenses was drawn, and surveys
were mailed in 2-week cohorts over the period
January 1991 to January 1992. Respondents were
asked to report detailed fish consumption patterns
during the preceding 7 days, as well as demographic
information; they were also asked if they currently
eat fish. Enclosed with the survey were pictures of
about a half pound of fish. Respondents were asked
to indicate whether reported consumption at each
meal was more, less, or about the same as the picture.
Based on responses to this question, respondents
were assumed to have consumed ten, 5- or 8-ounce
portions offish, respectively.
A total of 2,681 surveys were returned. West et al.
(1993) calculated a response rate for the survey of
46.8%; this was derived by removing from the
sample those respondents who could not be located
or who did not reside in Michigan for at least
6 months.
Of these 2,681 respondents, 2,475 (93%) reported
that they currently eat fish; all subsequent analyses
were restricted to the current fish eaters. The mean
fish consumption rates were found to be 16.7 g/day
for sport fish and 26.5 g/day for total fish (West et al.,
1993). Table 10-76 shows mean sport-fish
consumption rates by demographic categories. Rates
were higher among minorities, people with low
income, and people residing in smaller communities.
Consumption rates in g/day were also higher in males
than in females; however, this difference would likely
disappear if rates were computed on a g/kg-day basis.
West et al. (1993) estimated the 80th percentile of
the survey fish consumption distribution. More
extensive percentile calculations were performed by
U.S. EPA (1995) using the raw data from the West
etal. (1993) survey. However, because this survey
only measured fish consumption over a short
(1 week) interval, the resulting distribution will not
be indicative of the long-term fish consumption
distribution, and the upper percentiles reported from
the U.S. EPA analysis will likely considerably
overestimate the corresponding long-term percentiles.
The overall 95th percentile calculated by U.S. EPA
(1995) was 77.9; this is about double the
95th percentile estimated using yearlong consumption
data from the 1989 Michigan survey.
The limitations of this survey are the relatively
low response rate and the fact that only
three categories were used to assign fish portion size.
The main study strengths were its relatively large size
and its reliance on short-term recall.
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10.5.7. Alabama Dept. of Environmental
Management (ADEM) (1994)—
Estimation of Daily Per Capita
Freshwater Fish Consumption of
Alabama Anglers
The Alabama Department of Environmental
Management (1994) conducted a fish consumption
survey of sport-fishing Alabama anglers during the
time period from August 1992 to August 1993. The
target population included all anglers who were
Alabama residents. The survey design consisted of
personal interviews given to sport fishermen at the
end of their fishing trips at 23 sampling sites. Each
sampling site was surveyed once during each season
(summer, fall, winter, and spring). The survey was
conducted for 2 consecutive days, either a Friday and
Saturday or a Sunday and Monday. This approach
minimized single-day-type bias and maximized
surveying the largest number of anglers because a
large amount of fishing occurs on weekends. Anglers
were asked about consumption of fish caught at the
sampling site as well as consumption of fish caught
from other lakes and rivers in Alabama.
A total of 1,586 anglers were interviewed during
the entire study period, of which, 83% reported
eating fish they caught from the sampling sites
(1,313 anglers). The number of anglers interviewed
during each season was as follows: 488 during the
summer, 363 during the fall, 224 during the winter,
and 511 during the spring. Fish consumption rates
were estimated using two methods: the 4-ounce
Serving Method and the Harvest Method. The
4-ounce Serving Method estimated consumption
based on a typical 4-ounce serving size. The Harvest
Method used the actual harvest of fish and dressing
method reported. All of the 1,313 anglers were used
in the mean estimates of daily consumption based on
the 4-ounce Serving Method, while only 563 anglers
were utilized in the calculations of mean estimates of
daily consumption, based on the Harvest Method.
Table 10-77 shows the results of the survey.
Adults consumed an annual average of 32.6 g/day
using the Harvest Method, calculated from study
sites, and an annual average of 43.1 g/day using the
Harvest Method, calculated from study sites plus
other Alabama lakes and rivers. The survey also
showed that adults consumed an annual average of
30.3 g/day using the 4-ounce Serving Method,
calculated from study sites, and an annual average of
45.8 g/day using the 4-ounce Serving Method,
calculated from study sites plus other Alabama lakes
and rivers. When the entire sample was pooled, and a
mean was taken over all respondents for the 4-ounce
Serving Method, the average annual consumption
was 44.8 g/day.
The study also examined fish consumption in
conjunction with socio-demographic factors. It was
noted that fish consumption tended to increase with
age. Anglers below the age of 20 years were not well
represented in this study. However, based on
estimates of consumption rates using the 4-ounce
Serving Method, the study found that anglers
between 20 and 30 years of age consumed an average
of 16 g/day, anglers between 30 and 50 years old
consumed 39 g/day, and anglers over 50 years old
consumed 76 g/day. Trends also emerged when ethnic
groups and income levels were examined together.
Using the 4-ounce Serving Method, estimates of fish
consumption for Blacks dropped from 60 g/day for
poverty-level families to 15 g/day for upper-income
families. For Whites, fish consumption rates dropped
slightly from 41 g/day for poverty-level families to
35 g/day for upper-income families. Similar trends
were observed with the Harvest Method estimates.
Averaging the results from the two estimation
methods, there was a tendency for upper-income
White anglers to eat roughly 30% less fish than
poverty-level White anglers, while upper-income
Black anglers ate about 80% less fish as poverty-
level Black anglers. The analysis of seasonal intake
showed that the highest consumption rates were
consistently found to occur in the summer (see
Table 10-77). It was also found the lowest fish
consumption rate occurred in the spring.
The advantages of this study are that it compares
estimates of intake using two different methods and
provides some perspective on seasonal differences in
intake. Data are not provided for children, and the
number of observations for some race/ethnic groups
is very small.
10.5.8. Connelly et al. (1996)—Sportfish
Consumption Patterns of Lake Ontario
Anglers and the Relationship to Health
Advisories, 1992
The objectives of the Connelly et al. (1996) study
were to provide accurate estimates of fish
consumption (overall and sport caught) among Lake
Ontario anglers and to evaluate the effect of Lake
Ontario health advisory recommendations (Connelly
et al., 1996). To target Lake Ontario anglers, a sample
of 2,500 names was randomly drawn from 1990-
1991 New York fishing license records for licenses
purchased in six counties bordering Lake Ontario.
Participation in the study was solicited by mail with
potential participants encouraged to enroll in the
study even if they fished infrequently or consumed
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little or no sport-caught fish. The survey design
involved three survey techniques including a mail
questionnaire asking for 12-month recall of 1991
fishing trips and fish consumption, serf-recording
information in a diary for 1992 fishing trips and fish
consumption, periodic telephone interviews to gather
information recorded in the diary, and a final
telephone interview to determine awareness of health
advisories (Connelly et al., 1996).
Participants were instructed to record in the diary
the species of fish eaten, meal size, method by which
fish was acquired (sport-caught or other), fish
preparation and cooking techniques used, and the
number of household members eating the meal. Fish
meals were defined as finfish only. Meal size was
estimated by participants by comparing their meal
size to pictures of 8-ounce fish steaks and fillets on
dinner plates. An 8-ounce size was assumed unless
participants noted their meal size was smaller than
8 ounces, in which case, a 4-ounce size was assumed,
or they noted it was larger than 8 ounces, in which
case, a 12-ounce size was assumed. Participants were
also asked to record information on fishing trips to
Lake Ontario and species and length of any fish
caught.
From the initial sample of 2,500 license buyers,
1,993 (80%) were reachable by phone or mail, and
1,410 of these were eligible for the study, in that they
intended to fish Lake Ontario in 1992. A total of
1,202 of these 1,410, or 85%, agreed to participate in
the study. Of the 1,202 participants, 853 either
returned the diary or provided diary information by
telephone. Due to changes in health advisories for
Lake Ontario, which resulted in less Lake Ontario
fishing in 1992, only 43%, or 366 of these
853 persons indicated that they fished Lake Ontario
during 1992. The study analyses summarized below
concerning fish consumption and Lake Ontario
fishing participation are based on these 366 persons.
Anglers who fished Lake Ontario reported an
average of 30.3 (standard error = 2.3) fish meals per
person from all sources in 1992; of these meals, 28%
were sport caught (Connelly et al., 1996). Less than
1% ate no fish for the year, and 16% ate no sport-
caught fish. The mean fish intake rate from all
sources was 17.9 g/day, and from sport-caught
sources was 4.9 g/day. Table 10-78 gives the
distribution of fish intake rates from all sources and
from sport-caught fish. The median rates were
14.1 g/day for all sources and 2.2 g/day for sport
caught; the 95th percentiles were 42.3 g/day and
17.9 g/day for all sources and sport caught,
respectively. As seen in Table 10-79, statistically
significant differences in intake rates were seen
across age and residence groups, with residents of
large cities and younger people having lower intake
rates, on average.
The main advantage of this study is the diary
format. This format provides more accurate
information on fishing participation and fish
consumption, than studies based on 1-year recall
(Ebert et al., 1993). However, a considerable portion
of diary respondents participated in the study for only
a portion of the year, and some errors may have been
generated in extrapolating these respondents' results
to the entire year (Connelly et al., 1996). In addition,
the response rate for this study was relatively low—
853 of 1,410 eligible respondents, or 60%—which
may have engendered some non-response bias.
The presence of health advisories should be taken
into account when evaluating the intake rates
observed in this study. Nearly all respondents (>95%)
were aware of the Lake Ontario health advisory. This
advisory counseled to eat none of nine fish species
from Lake Ontario and to eat no more than one meal
per month of another four species. In addition, New
York State issues a general advisory to eat no more
than 52 sport-caught fish meals per year. Among
participants who fished Lake Ontario in 1992, 32%
said they would eat more fish if health advisories did
not exist. A significant fraction of respondents did not
totally adhere to the fish advisory; however, 36% of
respondents, and 72% of respondents reporting Lake
Ontario fish consumption, ate at least one species of
fish over the advisory limit. Interestingly, 90% of
those violating the advisory reported that they
believed they were eating within advisory limits.
10.5.9. Balcom et al. (1999)—Quantification of
Seafood Consumption Rates for
Connecticut
Balcom et al. (1999) conducted a seafood
consumption study in Connecticut, utilizing a food
frequency questionnaire along with portion size
models. Follow-up telephone calls were made to
encourage participation 7-10 days after mailing the
questionnaires to improve response rates. Information
requested in the survey included frequency of fish
consumption, types of fish/seafood eaten, portion
size, parts eaten, and the source of the fish/seafood
eaten. A diary was also given to the sample
populations to record fish and seafood consumption
over a 10-day period, and to document where the
fish/seafood was obtained and how it was prepared.
The sample population size for this study was
2,354 individuals (1,048 households). The study
authors divided this overall population into various
population groups including the general population
(460 individuals/216 households), commercial
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fishing population (178 individuals/73 households),
sport fishing and cultural/subsistence fishing
population (514 individuals/348 households),
minority population
(860 individuals/245 households), Southeast Asian
(329 individuals/89 households), non-Southeast
Asian (531 individuals/156 households), limited
income population (937 individuals/276 households),
women of childbearing age population
(493 individuals/420 households), and children
population (559 individuals/305 households).
It is important to note that the nine population
groups used in this study are not mutually exclusive.
Many individuals were included in more than one
population. For this reason, the authors did not
attempt to make any statistical comparisons between
the population groups.
The survey showed that over 33% of the
respondents ate 1-2 meals of fish or seafood per
week, including 39% of the general population,
3 5% of the sport fishing population, 38% of the
commercial and minority populations, and 39% of
the limited income population. A total of 36% of the
Southeast Asian population consumed 2-3 meals per
week with 2.1% consuming 5 or more meals per
week, while 43% of non-Southeast Asians consumed
1-2 meals of seafood per week. The general
population consumed, on average, 4.2 ounces of fish
per meal of purchased fish and 5.0 ounces per meal
of caught fish. Individuals in the sport fishing
population showed a marked difference, consuming
4.7 ounces per meal of bought fish and 7.3 ounces
per meal of caught fish. Southeast Asians consumed
smaller portions of fish per meal, and children
consumed the smallest portions offish per meal.
On average, the general population consumed
27.7 g/day offish and seafood while the sport fishing
population consumed 51.1 g/day (see Table 10-80).
The consumption of sport fish among consuming
anglers can be estimated by dividing the consumption
for all respondents by the percentage of consuming
anglers reported by Balcom et al. (1999) of 97% to
yield 52.7 g/day. The commercial fishing population
had an average consumption rate of 47.4 g/day, while
the limited income population's rate was 43.1 g/day.
The overall minority population consumption rate
was 50.3 g/day, with Southeast Asians consuming an
average of 59.2 g/day (the highest overall rate) and
non-Southeast Asians consuming an average of
45.0 g/day. Child-bearing age women consumed an
average of 45.0 g/day, and children consumed an
average of 18.3 g/day.
The study also examined fish preparations and
cooking practices for each population group. It was
found that the sport fishing population was most
likely to perform risk-reducing preparation methods
compared to the other populations, while the minority
population was least likely to use the same
risk-reducing methods. Cooking information by
specie was only available for the Southeast Asian
population, but the most common cooking methods
were boiling, poaching-boiling-steaming, saute/stir
fry, and deep frying.
The authors noted that there were some
limitations to this study. First, there was some
association among household members in terms of
the tendency to eat fish and seafood, but there was no
dependence between households. Second, the study
had a very low percent return rate for the general
population mail survey, and it is questionable whether
or not the responses accurately reflect the total
population's behavior. In addition, the proportion of
intake that can be attributed to freshwater fish is not
known.
10.5.10. Burger et al. (1999)—Factors in Exposure
Assessment: Ethnic and Socioeconomic
Differences in Fishing and Consumption
of Fish Caught along the Savannah River
Burger et al. (1999) examined the differences in
fishing rates and fish consumption of people fishing
along the Savannah River as a function of age,
education, ethnicity, employment history, and
income. A total of 258 people who were fishing on
the Savannah River were interviewed. The interviews
were conducted both on land and by boat from April
to November 1997. Anglers were asked about fishing
behavior, consumption patterns, cooking patterns,
knowledge of warnings and safety of fish, and
personal demographics. The authors used multiple
regression procedures to examine the relative
contribution of ethnicity, income, age, and education
to parameters such as years fished, serving size,
meals/month, and total ounces of fish consumed per
year.
Eighty-nine percent of people interviewed were
men, 70% were White, 28% were African American,
and 2% were of other ethnicity not specified in the
study. The age of the interviewees ranged from 16 to
82 years (mean = 43 ± 1 years). The study authors
reported that the average fish intake for all survey
respondents was 1.46 kg of fish per month
(48.7 g/day). Although most of the respondents were
men, they indicated that their wives and children
consumed fish as often as they did, and children
began to eat fish at 3 to 5 years of age.
There were significant differences in fishing
behavior and consumption as a function of ethnicity
(see Table 10-81). African Americans fished more
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often, consumed fish more frequently, and ate larger
portions of fish than did Whites. Given the higher
level of consumption by African Americans
compared to consumption by Whites, the study
authors suggested that the potential for exposure is
higher for African Americans than for Whites,
although the risks depend on the levels of
contaminants in the fish. Income and education also
contributed to variations in fishing and consumption
behavior. Anglers with low incomes (less than or
equal to $20,000) ate fish more often that those with
higher incomes. Anglers who had not graduated from
high school consumed fish more frequently, ate more
fish per month and per year, and deep fried fish more
often than anglers with more education. At all levels
of education, African Americans consumed more fish
than Whites.
The authors acknowledged that there may have
been sampling bias in the study because they only
interviewed people who were fishing on the river and
were, therefore, limited to those people they found.
To reduce the bias, the authors conducted the survey
at all times of the day, on all days of the week, and
along different sections of the river. Another
limitation noted by the study authors is that the
survey asked questions about consumption of fish
from two general sources: serf-caught and bought.
The study authors indicated that it would have been
useful to distinguish between fish obtained directly
from the wild by the anglers, their friends or family,
and store-bought or restaurant fish.
10.5.11. Williams et al. (1999)—Consumption of
Indiana Sport-Caught Fish: Mail Survey
of Resident License Holders
In 1997, sport-caught fish consumption among
licensed Indiana anglers was assessed using a mail
survey (Williams et al., 1999). Anglers were asked
about their consumption patterns during a 3-month
recall, their fishing rates, species of fish consumed,
awareness of advisory warnings, and associated
behaviors.
Average meal size among respondents was
9.3 ounces per meal. Consumers indicated that, on
average, they ate between 1 and 2 meals per month.
The survey population was divided into active
consumers (those who actively engage in consuming
sport fish meals) and potential consumers (those who
eat fish during other times of the year). The average
consumption rate for active consumers was reported
as 19.8 g/day. For both active and potential
consumers, the rate was 16.4 g/day (see Table 10-82).
The statewide mail survey of licensed Indiana
anglers did not specifically address lower-income and
minority anglers. The respondents to the mail survey
were predominately White (94.5%). The recall period
for this survey extended from the summer through
the end of fall and early winter. No information was
collected on consumption during spring or winter.
Another limitation of the study was that only
sport-caught fish consumption was measured among
anglers.
10.5.12. Burger (2000)—Sex Differences in Meal
Patterns: Role of Self-Caught Fish and
Wild Game in Meat and Fish Diets
Burger (2000) used the hypothesis that there are
sex differences in consumption patterns of
serf-caught fish and wild game in a meat and fish
diet. A total of 457 people were randomly selected
and interviewed while attending the Palmetto
Sportsmen's Classic in Columbia, SC in March 1998.
The mean age of the respondents was 40 years and
ranged from 15 to 74. The questionnaire requested
information on two different categories:
socio-demographics and number of meals consumed
that included several types of fish and wild game.
The demographics section contained questions
dealing with ethnicity, sex, age, location of residence,
occupation, and income. The section on consumption
of wild game and fish included specific questions
about the number of meals eaten and the source (i.e.,
serf-caught fish, store-bought fish, and restaurant
fish).
The results of this study indicated that there were
no sex differences in the percentage of people who
ate commercial protein sources, but there were
significant sex differences for the consumption of
most wild-caught game and fish. A higher proportion
of men (81.5%) ate wild-caught species than women
(73.2%). There were also sex differences in mean
monthly meals and mean serving sizes for
wild-caught fish. Men ate more meals of wild-caught
fish than woman, and men also ate larger portions
than women. The mean number of wild-caught fish
meals eaten per month was 2.24 for men and 1.52 for
women. The mean serving size was 373 grams for
men and 232 for women. The study authors also
found that individuals who consumed a large number
of fish meals per month consumed a higher
percentage of wild-caught fish meals than individuals
who consumed a small number of fish meals per
month.
This study provides information on sex
differences with regard to consumption of
wild-caught fish. Information on the number of
monthly meals and meal size is provided. However,
the study did not distinguish between marine and
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freshwater fish. In addition, all subjects interviewed
were White.
10.5.13. Williams et al. (2000)—An Examination
of Fish Consumption by Indiana
Recreational Anglers: An Onsite Survey
An on-site survey of Indiana anglers was
conducted in the summer of 1998 (Williams etal.,
2000). A total of 946 surveys were completed.
Minority anglers accounted for 31.8% of those
surveyed, with African American anglers accounting
for the majority of this group (25.1% of all
respondents). Respondents reporting household
incomes below $25,000 comprised 30.9% of the
respondents. Anglers were asked to report their
Indiana sport-caught fish consumption frequency for
a 3-month recall period. Using the meal frequency
and portion size reported by the anglers, the amount
of fish consumed was calculated into a daily amount
called grams per day consumption. Consumption
rates were weighted to correct for participation bias.
Consumption was reported as 27.2 g/day among
minority consumers and 20.0 g/day among White
consumers (see Table 10-83). Of the anglers
surveyed, 75.4% of White active consumers reported
being aware of the fish consumption advisory, while
70.0% of the minority consumers reported awareness.
The study authors also examined angler consumption
rate based on the level of awareness of Indiana fish
consumption advisories reported by the anglers. The
consumption rate for those consumers who were very
aware of the advisory was 35.2 g/day. For those with
a general awareness of the advisory, the consumption
rate was 14.1 g/day, and for those who were not
aware of the advisory, the consumption rate was
21.3 g/day. In terms of income, the study authors
found that there was a significant difference in grams
of Indiana sport-caught fish consumed per day.
Anglers reporting a household income below $25,000
had an average consumption rate of 18.9 g/day.
Anglers with incomes between $25,000 and $34,999
averaged 18.8 g/day, and anglers with incomes
between $35,000 and $49,999 averaged 15.2 g/day.
The highest income—those reporting an income
$50,000 or above—consumed an average of
48.9 g/day.
The advantages of this study are that it was
designed to determine the consumption rates of
Indiana anglers, particularly those in minority and
low-income groups, during a portion of the year.
However, information was not collected for the
period of September through January, so calculation
of year-round consumption was not possible.
10.5.14. Benson et al. (2001)—Fish Consumption
Survey: Minnesota and North Dakota
Benson et al. (2001) conducted a fish
consumption survey among Minnesota and North
Dakota residents. The target population included the
general population, licensed anglers, and members of
Native American tribes. The survey focused on
obtaining the most recent year's fish intake from all
sources, including locally caught fish. Survey
questionnaires were mailed to potential respondent
households. Groups of interest were selected and
allotted a portion of the total number of surveys to be
distributed to each group as follows: a group
categorized as the general population and anglers
received 37.5% of the surveys, and new mothers and
Native Americans each received 12.5% of the total
surveys distributed. The survey distribution was split
60/40 between Minnesota and North Dakota. For the
entire survey population, a total of 1,565 surveys
were returned completed (out of 7,835 that were
mailed out), resulting in a total of 4,273 respondents.
A target of 100 completed telephone interviews of
non-respondents was set in order to characterize the
non-respondent population. However, this target was
not met.
The Minnesota survey showed median total fish
and sport fish consumption rates for the general
population (2,312 respondents) of 12.3 and 2.8 g/day,
respectively (see Table 10-84). The total number of
Minnesota Bois Forte Tribe respondents was 232, and
median total fish and sport fish consumption rates in
g/day were 9.3 and 2.8, respectively. For Minnesota
residents with fishing licenses (2,020 respondents),
median total fish and sport fish consumption rates in
g/day were 13.2 and 3.9, respectively. For Minnesota
respondents without fishing licenses, median total
fish and sport fish consumption rates in g/day were
7.5 and 0, respectively. Table 10-84 also shows
median intake rates for purchased fish, upper
percentile intake rates for total fish, sport fish and
purchased fish for various age groups.
The North Dakota survey showed median total
fish and sport fish consumption rates for the general
population (1,406 respondents) of 12.6 and 3.0 g/day,
respectively (see Table 10-84). The total number of
North Dakota Spirit Lake Nation and Three Affiliated
Tribes respondents was 105, and the median total fish
and sport fish consumption rates in g/day were 1.4
and 0, respectively. For North Dakota residents with
fishing licenses (1,101 respondents), median total
fish and sport fish consumption rates in g/day were
14.0 and 4.5, respectively. For North Dakota
respondents without fishing licenses, median total
fish and sport fish consumption rates in g/day were
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7.2 and 0, respectively. Table 10-84 also shows
median intake rates for purchased fish, upper
percentile intake rates for total fish, sport fish and
purchased fish for various age groups.
Westat (2006) analyzed the raw data from Benson
et al. (2001) to derive fish consumption rates for
various age, sex, and ethnic groups, and according to
the source of fish consumed (i.e., bought or caught)
and habitat (i.e., freshwater, estuarine, or marine).
Westat (2006) calculated consumption rates of
freshwater fish for consuming anglers. For Minnesota
and North Dakota, these values are identical to the
consumption rates estimated by Westat (2006) for
consuming anglers of all self-caught fish (i.e.,
freshwater and saltwater). From this observation, it
can be concluded that all the consumption of self-
caught fish comes from freshwater. The mean and
95th percentile consumption rate for consuming
anglers of freshwater fish reported by Westat (2006)
are 14 g/day and 37 g/day, respectively, for
Minnesota and 12 g/day and 43 g/day, respectively,
for North Dakota.
The authors noted that 80% of respondents in
Minnesota and 72% of respondents in North Dakota
lived in a household that included a licensed angler.
They stated that this was a result of a direct intent to
oversample the angling population in both states by
sending 37.5% of surveys distributed to persons who
purchased a fishing license in either Minnesota or
North Dakota. The data were adjusted to incorporate
overall licensed angler rates in both states (47.3% of
households in Minnesota and 40.0% of households in
North Dakota).
An advantage of this study is its large overall
sample size. A limitation of the study is the low
numbers of Native Americans surveyed; thus, the
survey may not be representative of overall Native
American populations in Minnesota. In addition, the
study did not include Asian Immigrants, African
Americans, African immigrants, or Latino
populations, and was limited to two states. Therefore,
the results may not be representative of the U.S.
population as a whole.
10.5.15. Moya and Phillips (2001)—Analysis of
Consumption of Home-Produced Foods
As discussed in Section 10.4.2.5, some data on
fish consumption from households who fish are
provided in Chapter 13 and in Moya and Phillips
(2001). This information is based on an analysis of
data from the household component of the USDA's
1987-1988 NFCS. This analysis shows a mean
consumer-only fish consumption of 2.2 g/kg-day (all
ages combined, see Table 13-20) for the fishing
population. This value can be converted to a per
capita value by multiplying by the number of
consumers and dividing by the total number of
positive responses to the survey question "do you
fish?" Assuming an average body weight of 59 kg for
the survey population results in an average national
per capita self-caught fish consumption rate of
12 g/day among the population of individuals who
fish. However, this mean intake rate represents intake
of both freshwater and saltwater fish combined.
Converting this number into the edible portion by
multiplying by 0.5 as described in Section 10.4.2.5,
the mean national per capita serf-caught fish
consumption rate is about 6 g/day.
The advantage of this study is that it provides a
national perspective on the consumption of
serf-caught fish. A limitation of this study is that
these values include both freshwater and saltwater
fish. The proportion of freshwater to saltwater is
unknown and will vary depending on geographical
location. Intake data cannot be presented for various
age groups due to sample size limitations. The
unweighted number of households, who responded
positively to the survey question "do you fish?" was
also low (i.e., 220 households).
10.5.16. Campbell et al. (2002)—Fishing along the
Clinch River Arm of Watts Bar Reservoir
Adjacent to the Oak Ridge Reservation,
Tennessee: Behavior, Knowledge, and
Risk Perception
Campbell et al. (2002) examined consumption
habits of anglers fishing along the Clinch River arm
of Watts Bar Reservoir, adjacent to the U.S.
Department of Energy's Oak Ridge Reservation in
East Tennessee. A total of 202 anglers were
interviewed on 65 sampling days, which included
48 weekdays and 17 weekend days. Eighty-
six percent of fishermen interviewed were fishing
from the shore, while 14% were fishing from a boat.
The questionnaire utilized in the study included
questions on demographics, fishing behavior,
perceptions, cooking patterns, consumption patterns,
and consumption warnings. Interviews were
conducted by two people who were local to the area
in order to promote participation in the study.
Out of all anglers interviewed, approximately
35% did not eat fish. Of the 65% who ate fish, only
38% ate fish from the study area. This 38%
(77 people) was considered useful to the study and,
thus, were the main focus of the data analysis. These
anglers averaged 2 meals of fish per month, with an
average consumption rate of 37 grams per day or
13.7 kilograms per year (see Table 10-85). They
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caught almost 90% of the fish they ate, had a mean
age of 42 years, and a mean income of $28,800. The
species of fish most often mentioned by anglers who
caught and ate fish from the study area were crappie,
striped bass, white bass, sauger, and catfish.
A limitation of this study is that the small size of
the population does not allow for statistically
significant analysis of the data.
10.5.17. Burger (2002b)—Daily Consumption of
Wild Fish and Game: Exposure of
High-End Recreationists
Burger (2002b) determined consumption patterns
for a range of wild-caught fish and game in South
Carolina. The population selected for dietary surveys
were attendees at the Palmetto Sportsman's Classic in
Columbia, South Carolina. Individual dietary
surveys were conducted at the show in March, 1998,
on 458 participants who were randomly selected from
an attending population of approximately 60,000
people. Of the survey participants, 15% were Black,
85% were White, and 33% were women. The age
composition was similar for black and white
respondents; however, Black participants had
significantly lower mean incomes than White
participants.
The dietary survey took about 20 minutes to
complete and was divided into three parts: a section
on demographics; one on the number of meals
consumed of different types of fish and meat for each
of the past 12 months, and a section collecting
information on serving size and cooking methods.
The types of fish and meat inquired about included
wild-caught fish, store-bought fish, restaurant fish,
deer, wild-caught quail, restaurant quail, dove, duck,
rabbit, squirrel, raccoon, wild turkey, beef, chicken,
pork, and any wild game not listed in the
questionnaire. Respondents were asked to provide
information regarding serving/portion size and what
percent of their meals they consumed as meat as
opposed to stews. The average number of meals eaten
as meat and stew were separately determined for each
of the 12 months, then multiplied by the average
serving size. Yearly consumption rates were then
determined by summing across months for each type
of fish or meat. Means and percentiles were
computed using SAS.
Mean daily consumption of wild-caught fish
ranged from 32.6 g/kg-day for respondents less than
32 years of age to 171.0 g/kg-day for Black
respondents (see Table 10-86). The disparity in mean
consumption was the greatest for ethnicity and
income level, with black and low income respondents
eating more than twice as much wild-caught fish as
Whites or higher income respondents. Male fish
consumption (mean of 55.2 g/kg-day) was higher
than that of females (mean of 39.1 g/kg-day), while
by age, fish consumption was highest among the
33-45 year olds (mean intake of 71.3 g/kg-day). The
author suggested that although the high consumption
of wild-caught fish for this age group may reflect a
more active lifestyle, it may also reflect exposure of
women of child-bearing age. As shown in
Table 10-86, the differences between mean
consumption rates and 99th percentile values were
very large. For some population groups at the higher
end of the distribution, fish consumption was
ten times greater than that of the mean.
This study provides useful comparisons on
wild-caught fish intake among populations with
differing ethnicity, sex, age, and income level. Data
on fish consumption at the higher end of the
distribution were also provided. A limitation of the
study includes the fact that the study was based on
dietary recall which is less reliable over time and may
have recall bias. In addition, although the
methodology indicated that information was collected
and/or calculated for serving/portion size, the percent
of meals consumed as meat versus stews, and yearly
consumption rates, no data were provided for these
parameters in the study.
10.5.18. Mayfield et al. (2007)—Survey of Fish
Consumption Patterns of King County
(Washington) Recreational Anglers
Mayfield et al. (2007) conducted a series of fish
consumption surveys among recreational anglers at
marine and freshwater sites in King County, WA. The
freshwater surveys were conducted between 2002
and 2003 at "freshwater locations around Lake
Sammamish, Lake Washington, and Lake Union"
(Mayfield et al., 2007). A total of 212 individuals
were interviewed at these locations. The majority of
participants were male, 18 years and older, and were
either Caucasian or Asian and Pacific Islander. Data
were collected on fishing location preferences,
fishing frequency, consumption amounts, species
preferences, cooking methods, and whether family
members would also consume the catch. Respondent
demographic data were also collected. Consumption
rates were estimated using information on fish meal
frequency and meal size. The mean recreational
freshwater fish consumption rates were 10 g/day for
all respondents and 7 g/day for the children of survey
respondents (see Table 10-87). Mayfield et al. (2007)
also reported differences in intake according to
ethnicity. Mean freshwater fish intake rates were 40,
38, 20, 19, and 2 g/day for Native American, African
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American, Asian and Pacific Islander, Caucasian, and
Hispanic/Latino respondents, respectively.
The advantage of this study is that it provides
additional perspective on recreational freshwater fish
intake. However, the data are limited to a specific
area of the United States and may not be
representative of anglers in other locations.
10.6. NATIVE AMERICAN STUDIES
10.6.1. Wolfe and Walker (1987)—Subsistence
Economies in Alaska: Productivity,
Geography, and Development Impacts
Wolfe and Walker (1987) analyzed a data set from
98 communities for harvests of fish, land mammals,
marine mammals, and other wild resources. The
analysis was performed to evaluate the distribution
and productivity of subsistence harvests in Alaska
during the 1980s. Harvest levels were used as a
measure of productivity. Wolfe and Walker (1987)
defined harvest to represent a single year's production
from a complete seasonal round. The harvest levels
were derived primarily from a compilation of data
from subsistence studies conducted between 1980
and 1985 by various researchers in the Alaska
Department of Fish and Game, Division of
Subsistence.
Of the 98 communities studied, four were large
urban population centers, and 94 were small
communities. The harvests for these latter
94 communities were documented through detailed
retrospective interviews with harvesters from a
sample of households (Wolfe and Walker, 1987).
Harvesters were asked to estimate the quantities of a
particular species that were harvested and used by
members of that household during the previous
12-month period. Wolfe and Walker (1987) converted
harvests to a common unit for comparison, pounds
dressed weight per capita per year, by multiplying the
harvests of households within each community by
standard factors, converting total pounds to dressed
weight, summing across households, and then
dividing by the total number of household members
in the household sample. Note average consumption
by household member can be misleading because
households include both children and adults whose
intake rates may be very different. Dressed weight
varied by species and community but, in general, was
70% to 75% of total fish weight; dressed weight for
fish represents that portion brought into the kitchen
for use (Wolfe and Walker, 1987).
Harvests for the four urban populations were
developed from a statewide data set gathered by the
Alaska Department of Fish and Game Divisions of
Game and Sports Fish. Urban sport-fish harvest
estimates were derived from a survey that was mailed
to a randomly selected statewide sample of anglers
(Wolfe and Walker, 1987). Sport-fish harvests were
disaggregated by urban residency, and the data set
was analyzed by converting the harvests into pounds
and dividing by the 1983 urban population.
For the overall analysis, each of the
98 communities was treated as a single unit of
analysis, and the entire group of communities was
assumed to be a sample of all communities in Alaska
(Wolfe and Walker, 1987). Each community was
given equal weight, regardless of population size.
Annual per capita harvests were calculated for each
community. For the four urban centers, fish harvests
ranged from 5 to 21 pounds per capita per year
(6.2 g/day to 26.2 g/day).
The range for the 94 small communities was 25 to
1,23 9 pounds per capita per year (31 g/day to
1,541 g/day). For these 94 communities, the median
per capita fish harvest was 130 pounds per year
(162 g/day). In most (68%) of the 98 communities
analyzed, resource harvests for fish were greater than
the harvests of the other wildlife categories (land
mammal, marine mammal, and other) combined.
The communities in this study were not made up
entirely of Alaska Natives. For roughly half the
communities, Alaska Natives comprised 80% or more
of the population, but for about 40% of the
communities, they comprised less than 50% of the
population. Wolfe and Walker (1987) performed a
regression analysis, which showed that the per capita
harvest of a community tended to increase as a
function of the percentage of Alaska Natives in the
community. Although this analysis was done for total
harvest (i.e., fish, land mammal, marine mammal,
and others), the same result should hold for fish
harvest because it is highly correlated with total
harvest.
A limitation of this report is that it presents per
capita harvest rates as opposed to individual intake
rates. Wolfe and Walker (1987) compared the per
capita harvest rates reported to the results for the
household component of the 1977-1978 USD A
NFCS. The NFCS showed that about 222 pounds of
meat, fish, and poultry were purchased and brought
into the household kitchen for each person each year
in the western region of the United States. This
contrasts with a median total resource harvest of
260 Ibs/year in the 94 communities studied. This
comparison, and the fact that Wolfe and Walker
(1987) state that "harvests represent that portion
brought into the kitchen for use," suggest that the
same factors used to convert household consumption
rates in the NFCS to individual intake rates can be
used to convert per capita harvest rates to individual
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intake rates. In Section 10.3, a factor of 0.5 was used
to convert fish consumption from household to
individual intake rates. Applying this factor, the
median per capita individual fish intake in the
94 communities would be 81 g/day and the range
15.5 to 770 g/day.
A limitation of this study is that the data were
based on 1-year recall from a mailed survey. An
advantage of the study is that it is one of the few
studies that present fish harvest patterns for
subsistence populations.
10.6.2. Columbia River Inter-Tribal Fish
Commission (CRITFC) (1994)—A Fish
Consumption Survey of the Umatilla, Nez
Perce, Yakama, and Warm Springs
Tribes of the Columbia River Basin
The Columbia River Inter-Tribal Fish
Commission (CRITFC) (1994) conducted a fish
consumption survey among four Columbia River
Basin Native American tribes during the fall and
winter of 1991-1992. The target population included
all adult tribal members who lived on or near the
Yakama, Warm Springs, Umatilla, or Nez Perce
reservations. The survey was based on a stratified
random sampling design where respondents were
selected from patient registration files at the Indian
Health Service. Interviews were performed in person
at a central location on the member's reservation.
The overall response rate was 69%, yielding a
sample size of 513 tribal members, 18 years old and
above. Of these, 58% were female, and 59% were
under 40 years old. Each participating adult was
asked if there were any children 5 years old or
younger in his or her household. Those responding
affirmatively were asked a set of survey questions
about the fish consumption patterns of the youngest
child in the household (CRITFC, 1994). Information
for 204 children, 5 years old and younger, was
provided by participating adult respondents.
Consumption data were available for 194 of these
children.
Participants were asked to describe and quantify
all food and drink consumed during the previous day.
They were then asked to identify the months in which
they ate the most and the least fish, and the number
of fish meals consumed per week during each of
those periods and an average value for the whole
year. The typical portion size (in ounces) was
determined with the aid of food models provided by
the questioner. The next set of questions identified
specific species of fish and addressed the number of
times per month each was eaten, as well as what parts
(e.g., fillet, skin, head, eggs, bones, other) were eaten.
Respondents were then asked to identify the
frequency with which they used various preparation
methods, expressed as a percentage. Respondents
sharing a household with a child, aged 5 years or less,
were asked to repeat the serving size, eating
frequency, and species questions for the child's
consumption behavior. All respondents were asked
about the geographic origin of any fish they
personally caught and consumed, and to identify the
major sources of fish in their diet (e.g., serf-caught,
grocery store, tribe, etc.). Fish intake rates were
calculated by multiplying the annual frequency of
fish meals by the average serving size per fish meal.
The population sizes of the four tribes were
highly unequal, ranging from 818 to
3,872 individuals (CRITFC, 1994). Nearly equal
sample sizes were collected from each tribe.
Weighting factors were applied to the pooled data (in
proportion to tribal population size) so that the survey
results would be representative of the overall
population of the four tribes for adults only. Because
the sample size for children was considered small,
only an unweighted analysis was performed for this
population. Based on a desired sample size of
approximately 500 and an expected response rate of
70%, 744 individuals were selected at random from
lists of eligible patients; the numbers from each tribe
were approximately equal.
The results of the survey showed that adults
consumed an average of 1.71 fish meals/week and
had an average intake of 58.7 g/day (CRITFC, 1994).
Table 10-88 shows the adult fish intake distribution;
the median was between 29 and 32 g/day, and the
95th percentile about 170 g/day. A small percentage
(7%) of respondents indicated that they were not fish
consumers. Table 10-89 shows that mean intake was
slightly higher in males than females (63 g/day
versus 56 g/day) and was higher in the over 60 years
age group (74.4 g/day) than in the 18-39 years
(57.6 g/day) or 40-59 years (55.8 g/day) age groups.
Intake also tended to be higher among those living on
the reservation. The mean intake for nursing
mothers—59.1 g/day—was similar to the overall
mean intake. Intake rates were calculated for children
for which both the number of fish meals per week
and serving size information were available.
Appendix 10B presents the weighted percentage of
adults consuming specific fish parts.
A total of 49% of respondents of the total survey
population reported that they caught fish from the
Columbia River basin and its tributaries for personal
use or for tribal ceremonies and distributions to other
tribe members, and 88% reported that they obtained
fish from either self-harvesting, family, or friends; at
tribal ceremonies; or from tribal distributions. Of all
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fish consumed, 41% came from self- or family
harvesting, 11% from the harvest of friends, 35%
from tribal ceremonies or distribution, 9% from
stores, and 4% from other sources (CRITFC, 1994).
Of the 204 children, the total number of
respondents used in the analysis varied from 167 to
202, depending on the topic (amount and species
consumed, fish meals consumed/week, age
consumption began, serving size, consumption of fish
parts) of the analysis. The unweighted mean for the
age when children begin eating fish was 13.1 months
of age (N = 167). The unweighted mean number of
fish meals consumed per week by children was
1.2 meals per week (N = 195), and the unweighted
mean serving size of fish for children aged 5 years
old and less was 95 grams (i.e., 3.36 ounces)
(N= 201). The unweighted percent of fish consumed
by children by species was 82.7% for salmon,
followed by 46.5% (N = 202) for trout.
The analysis of seasonal intake showed that May
and June tended to be high-consumption months and
December and January, low consumption months.
The mean adult intake rate for May and June was
108 g/day, while the mean intake rate for December
and January was 30.7 g/day. Salmon was the species
eaten by the highest number of respondents (92%)
followed by trout (70%), lamprey (54%), and smelt
(52%). Table 10-90 gives the fish intake distribution
for children under 5 years of age. The mean intake
rate was 19.6 g/day, and the 95th percentile was
approximately 70 g/day. These mean intake rates
include both consumers and non-consumers. These
values are based on survey questions involving
estimated behavior throughout the year, which survey
participants answered in terms of meals per week or
per month and typical serving size per meal.
Table 10-91 presents consumption rates for children,
who were reported to consume particular species of
fish.
The authors noted that some non-response bias
may have occurred in the survey because respondents
were more likely to be female and live near the
reservation than non-respondents. In addition, they
hypothesized that non-consumers may have been
more likely to be non-respondents than fish
consumers because non-consumers may have thought
their contribution to the survey would be
meaningless. If such were the case, this study would
overestimate the mean per capita intake rate. It was
also noted that the timing of the survey, which was
conducted during low fish consumption months, may
have led to underestimation of actual fish
consumption. The authors conjectured that an
individual may have reported higher annual
consumption if interviewed during a relatively high
consumption month and lower annual consumption if
interviewed during a relatively low consumption
month. Finally, with respect to children's intake, it
was observed that some of the respondents provided
the same information for their children as for
themselves; thereby, the reliability of some of these
data is questioned (CRITFC, 1994). The combination
of four different tribes' survey responses into a single
pooled data set is somewhat problematic. The data
presented are unweighted and, therefore, contain a
bias toward the smaller tribes, who were oversampled
compared to the larger tribes.
The limitations of this study, particularly with
regard to the estimates of children's consumption,
result in a high degree of uncertainty in the estimated
rates of consumption. Although the authors have
noted these limitations, this study does present
information on fish consumption patterns and habits
for a Native American population.
10.6.3. Peterson et al. (1994)—Fish Consumption
Patterns and Blood Mercury Levels in
Wisconsin Chippewa Indians
Peterson et al. (1994) investigated the extent of
exposure to methylmercury by Chippewa Indians
living on a Northern Wisconsin reservation who
consume fish caught in Northern Wisconsin lakes.
Chippewa have a reputation for high fish
consumption (Peterson et al., 1994). The Chippewa
Indians fish by the traditional method of spearfishing.
Spearfishing (for walleye) occurs for about 2 weeks
each spring after the ice breaks, and although only a
small number of tribal members participate in it, the
spearfishing harvest is distributed widely within the
tribe by an informal distribution network of family
and friends and through traditional tribal feasts
(Peterson etal., 1994).
Potential survey participants, 465 adults, 18 years
of age and older, were randomly selected from the
tribal registries (Peterson et al., 1994). Participants
were asked to complete a questionnaire describing
their routine fish consumption and, more extensively,
their fish consumption during the 2 previous months.
The survey was carried out in May 1990. A follow-up
survey was conducted for a random sample of
75 non-respondents (80% were reachable), and their
demographic and fish consumption patterns were
obtained. Peterson et al. (1994) reported that the
non-respondents' socioeconomic information and fish
consumption were similar to the respondents.
A total of 175 of the original random sample
(38%) participated in the study. In addition,
152 non-randomly selected participants were
surveyed and included in the data analysis; these
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participants were reported by Peterson et al. (1994) to
have fish consumption rates similar to those of the
randomly selected participants. Results from the
survey showed that fish consumption varied
seasonally, with 50% of the respondents reporting
April and May (spearfishing season) as the highest
fish consumption months (Peterson et al., 1994).
Table 10-92 shows the number of fish meals
consumed per week during the last 2 months (recent
consumption) before the survey was conducted and
during the respondents' peak consumption months
grouped by sex, age, education, and employment
level. During peak consumption months, males
consumed more fish (1.9 meals per week) than
females (1.5 meals per week), respondents under
3 5 years of age consumed more fish (1.8 meals per
week) than respondents 35 years of age and over
(1.6 meals per week), and the unemployed consumed
more fish (1.9 meals per week) than the employed
(1.6 meals per week). During the highest fish
consumption season (April and May), 50% of
respondents reported eating 1 or less fish meals per
week, and only 2% reported daily fish consumption.
A total of 72% of respondents reported Walleye
consumption in the previous 2 months. Peterson et al.
(1994) also reported that the mean number of fish
meals usually consumed per week by the respondents
was 1.2.
The mean fish consumption rate reported (1.2 fish
meals per week, or 62.4 meals per year) in this
survey was compared with the rate reported in a
previous survey of Wisconsin anglers (Fiore et al.,
1989) of 42 fish meals per year. These results indicate
that the Chippewa Indians do not consume much
more fish than the general Wisconsin angler
population (Peterson et al., 1994). The differences in
the two values may be attributed to differences in
study methodology (Peterson et al., 1994). Note that
this number (1.2 fish meals per week) includes fish
from all sources. Peterson et al. (1994) noted that
subsistence fishing, defined as fishing as a major
food source, appears rare among the Chippewa.
Using a meal size of 227 g/meal, the rate reported
here of 1.2 fish meals per week translates into a mean
fish intake rate of 39 g/day in this population. This
meal size is similar to an adult general population
90th percentile meal size derived from Smiciklas-
Wright et al. (2002) (see Section 10.8.2).
The advantages of this study are that it targeted a
specific Native American population and provides
some perspective on peak consumption and species
of fish consumed. However, the data are more than
2 decades old and may not be entirely representative
of current intake patterns.
10.6.4. Fitzgerald et al. (1995)—Fish PCB
Concentrations and Consumption
Patterns Among Mohawk Women at
Akwesasne
Akwesasne is a Native American community of
10,000 plus persons located along the St. Lawrence
River (Fitzgerald et al., 1995). Fitzgerald et al. (1995)
conducted a recall study from 1986 to 1992 to
determine the fish consumption patterns among
nursing Mohawk women residing near
three industrial sites. The study sample consisted of
97 Mohawk women living on the Akwesasne
Reservation and 154 nursing Caucasian controls
living in Warren and Schoharie counties, which are
primary rural like the Akwesasne. The Mohawk
mothers were significantly younger (mean age: 24.9)
than the controls (mean age: 26.4) and had
significantly more years of education (mean: 13.1 for
Mohawks versus 12.4 for controls). A total of 97 out
of 119 Mohawk nursing women responded, a
response rate of 78%; 154 out of 287 control nursing
Caucasian women responded, a response rate of 54%.
Statistical analysis focused upon socio-demographic,
physical, reproductive, lifestyle, and dietary and
consumption differences between the Mohawk and
control women.
Potential participants were identified prior to, or
shortly after, delivery. The interviews were conducted
at home within 1 month postpartum and were
structured to collect information for socio-
demographics, vital statistics, use of medications,
occupational and residential histories, behavioral
patterns (cigarette smoking and alcohol
consumption), drinking water source, diet, and fish
preparation methods (Fitzgerald et al., 1995). The
dietary data collected were based on recall for food
intake during the index pregnancy, the year before the
pregnancy, and more than 1 year before the
pregnancy.
The dietary assessment involved the report by
each participant on the consumption of various foods
with emphasis on local species of fish and game
(Fitzgerald et al., 1995). This method combined food
frequency and dietary histories to estimate usual
intake. Food frequency was evaluated with a
checklist of foods for indicating the amount of
consumption of a participant per week, month, or
year. Information gathered for the dietary history
included duration of consumption, changes in the
diet, and food preparation method.
Table 10-93 presents the number of local fish
meals per year for both the Mohawk and control
participants. The highest percentage of participants
reported consuming between 1 and 9 local fish meals
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per year. Table 10-93 indicates that Mohawk
respondents consumed statistically significantly more
local fish than did control respondents during the
two time periods prior to pregnancy; for the time
period during pregnancy, there was no significant
difference in fish consumption between the
two groups. Table 10-94 presents the mean number of
local fish meals consumed per year by time period for
all respondents and for those ever consuming
(consumers only). A total of 82 (85%) Mohawk
mothers and 72 (47%) control mothers reported ever
consuming local fish. The mean number of local fish
meals consumed per year by Mohawk respondents
declined over time, from 23.4 (over 1 year before
pregnancy) to 9.2 (less than 1 year before pregnancy)
to 3.9 (during pregnancy); a similar decline was seen
among consuming Mohawks only. There was also a
decreasing trend over time in consumption among
controls, though it was much less pronounced.
Table 10-95 presents the mean number of fish
meals consumed per year for all participants by time
period and selected characteristics (age, education,
cigarette smoking, and alcohol consumption).
Pairwise contrasts indicated that control participants
over 34 years of age had the highest fish consumption
of local fish meals (22.1) (see Table 10-95).
However, neither the overall nor pairwise differences
by age among the Mohawk women over 34 years old
were statistically significant, which may be due to the
small sample size (N = 6) (Fitzgerald et al., 1995).
The most common fish consumed by Mohawk
mothers was yellow perch; for controls, the most
common fish consumed was trout.
An advantage of this study is that it presents data
for fish consumption patterns for Native Americans
as compared to a demographically similar group of
Caucasians. Although the data are based on nursing
mothers as participants, the study also captures
consumption patterns prior to pregnancy (up to 1 year
before and more than 1 year before). Fitzgerald et al.
(1995) noted that dietary recall for a period more than
1 year before pregnancy may be inaccurate, but these
data were the best available measure of the more
distant past. They also noted that the observed
decrease in fish consumption among Mohawks from
1 year before pregnancy to the period of pregnancy is
due to a secular trend of declining fish consumption
over time in Mohawks. This decrease, which was
more pronounced than that seen in controls, may be
due to health advisories promulgated by tribal, as
well as state, officials. The authors noted that this
decreasing secular trend in Mohawks is consistent
with a survey from 1979-1980 that found an overall
mean of 40 fish meals per year among male and
female Mohawk adults.
The data are presented as number of fish meals
per year; the authors did not assign an average weight
to fish meals. If assessors wanted to estimate the
weight of fish consumed, some value of weight per
fish meal would have to be assumed.
Smiciklas-Wright et al. (2002) reported 209 grams as
the 90th percentile weight of fish consumed per eating
occasion for general population females 20-39 years
old. Using this value, the rate reported of 27.6 fish
meals per year for consumers only (over 1 year
before pregnancy) translates into a mean fish intake
rate of 15.8 g/day.
A limitation of this study is that information on
meal size was not available. It is not known whether
the 90th percentile meal size from the general
population is representative of the population of
Mohawk women.
10.6.5. Forti et al. (1995)—Health Risk
Assessment for the Akwesasne Mohawk
Population from Exposure to Chemical
Contaminants in Fish and Wildlife
Forti et al. (1995) estimated the potential
exposure of residents of the Mohawk Nation at
Akwesasne to PCBs through the ingestion of locally
caught fish and wildlife, and human milk. The study
was part of a remedial investigation/feasibility study
(RI/FS) for a National Priorities List site near
Massena, NY and the St. Lawrence River. Forti et al.
(1995) used data collected in 1979-1980 on the
source (store bought or locally caught), species, and
frequency of fish consumption among 1,092 adult
Mohawk Native Americans. The information on
frequency of fish consumption was combined with an
assumed meal size of 227 grams to estimate intake
among the adult population. This meal size represents
the 90th percentile meal size for fish consumers in the
U.S. population as reported by Pao et al. (1982).
Children were assumed to eat fish at the same
frequency as adults but were assumed to have a meal
size of 93 grams.
Table 10-96 presents the mean and 95th percentile
fish intake estimates for the Mohawk population, as
reported by Forti et al. (1995). Mean intake of local
fish was estimated to be 25 g/day for all adult fish
consumers and 29 g/day for adult consumers only;
95th percentile rates for these groups were 131 and
135 g/day, respectively. Mean intake of local fish was
estimated to be 10 g/day among all Mohawk children
and 13 g/day among children consumers only;
95th percentile estimates for these groups were 54 and
58 g/day, respectively.
The advantage of this study is that it provides
additional perspective on intake among Native
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American populations, especially those in the St.
Lawrence River area. However, the fish intake survey
data used in this analysis were collected more than
3 decades ago and may not represent current intake
patterns for this population. Also, the Forti etal.
(1995) report provides limited details about the
survey methodology and data used to estimate intake.
It should also be noted that fish intake rates were
estimated using a 90th percentile meal size. It is not
known whether the 90th percentile meal size from the
general population is representative of this population
of Native Americans.
10.6.6. Toy et al. (1996)—A Fish Consumption
Survey of the Tulalip and Squaxin Island
Tribes of the Puget Sound Region
Toy et al. (1996) conducted a study to determine
fish and shellfish consumption rates of the Tulalip
and Squaxin Island tribes living in the Puget Sound
region. These two Indian tribes were selected on the
basis of judgment that they would be representative
of the expected range of fishing and fish consumption
activities of the 14 tribes in the region. Commercial
fishing is a major source of income for members of
both tribes; some members of the Squaxin Island
tribe also participate in commercial shellfishing. Both
tribes participate in subsistence fishing and
shellfishing.
A survey was conducted to describe fish
consumption for Puget Sound tribal members over
the age of 18 years, and their dependents, aged
5 years and under, in terms of their consumption rate
of anadromous, pelagic, bottom fish, and shellfish in
grams per kilogram of body weight per day. The
survey focused on the frequency of fish and shellfish
consumption (number of fish meals eaten per day, per
week, per month, or per year) over a 1-year period,
and the portion size of each meal. Data were also
collected on fish parts consumed, preparation
methods, patterns of acquisition for all fish and
shellfish consumption (including seasonal variations
in consumption), and children's consumption rates.
Interviews were conducted between February 25 and
May 15, 1994. A total of 190 tribal members, aged
18 years old and older, and 69 children between birth
and 5 years old, were surveyed on consumption of
52 species. The response rate was 77% for the
Squaxin Island tribe and 76% for the Tulalip tribes.
The appropriate sample size was calculated based
on the enrolled population of each tribe and a desired
confidence interval of ±20% from the mean, with an
additional 25% added to the total to allow for
non-response or unusable data. The target population,
derived from lists of enrolled tribal members
provided by the tribes, consisted of enrolled tribal
members aged 18 years and older and children aged
5 years and younger living in the same household as
an enrolled member. Only members living on or
within 50 miles of the reservation were considered
for the survey. Each eligible enrolled tribal member
was assigned a number, and computer-generated
random numbers were used to identify the survey
participants. Children were not sampled directly but
through adult members of their household; if one
adult had more than one eligible child in his or her
household, one of the children was selected at
random. This indirect sampling method was
necessitated by the available tribal records but may
have introduced sampling bias to the process of
selecting children for the study. A total of 190 adult
tribal members (ages 18 years old and older) and
69 children between birth and 5 years old (i.e., 0 to
<6 years) were surveyed about their consumption of
52 fish species in six categories: anadromous,
pelagic, bottom, shellfish, canned tuna, and
miscellaneous.
Respondents described their consumption
behavior for the past year in terms of frequency of
fish meals eaten per week or per month, including
seasonal variations in consumption rates. Portion
sizes (in ounces) were estimated with the aid of
model portions provided by the questioner. Data were
also collected on fish parts consumed, preparation
methods, patterns of acquisition for all fish and
shellfish consumption, and children's consumption
rates.
The adult mean and median consumption rates for
all forms of fish combined were 0.89 and
0.55 g/kg-day for the Tulalip tribes, and 0.89 and
0.52 g/kg-day for the Squaxin Island tribe,
respectively (see Table 10-97). As shown in
Table 10-98, consumption per body weight varied by
sex (males consumed more as indicated by mean and
median consumption). The median rates for the
Tulalip Tribes were 53 g/day for males and 34 g/day
for females, while the rates were 66 g/day for males
and 25 g/day for females for the Squaxin Island tribe
(see Table 10-99). Among adults, consumption
generally followed a curvilinear pattern, with greater
median consumption in the age range of 35 to
64 years old, and lower consumption in the age range
of 18 to 34 years old and 65 years old and over (see
Table 10-100). No consistent pattern of consumption
by income was found for either tribe (see
Table 10-101).
The mean and median consumption rates for
children 5 years and younger for both tribes
combined, were 0.53 and 0.17 g/kg-day, respectively.
These values were significantly lower than those of
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adults, even when the consumption rate was adjusted
for body weight (see Table 10-102). Squaxin Island
children tended to consume more fish than Tulalip
children (mean: 0.825 g/kg-day vs. 0.239 g/kg-day).
The data were insufficient to allow re-analysis to fit
the data to the standard U.S. EPA age categories used
elsewhere in this handbook. A minority of consumers
ate fish parts that are considered to have a higher
concentration of toxins: skin, head, bones, eggs, and
organs, and for the majority of consumers, fish were
prepared (baking, boiling, broiling, roasting, and
poaching) and eaten in a manner that tends to reduce
intake of contaminants. Most anadromous fish and
shellfish were obtained by harvesting in the Puget
Sound area rather than by purchasing, though sources
of harvesting varied between the tribes.
The advantage of this study is that the data
can be used to improve how exposure assessments
are conducted for populations that include high
consumers of fish and shellfish and to identify
cultural characteristics that may place tribal members
at disproportionate risk to chemical contamination.
One limitation associated with this study is that
although data from the Tulalip and Squaxin Island
tribes may be representative of consumption rates of
these specific tribes, fish consumption rates, habits,
and patterns can vary among tribes and other
population groups. As a result, the consumption rates
of these two tribes may not be useful as a surrogate
for consumption rates of other Native American
tribes. There might also be a possible bias due to the
time the survey was conducted; many species in the
survey are seasonal, and although the survey was
designed to solicit annual consumption rates,
respondents may have weighted their responses
toward the interview period. For example, because of
the timing of the survey, respondents may have
overestimated their annual consumption of shellfish
and underestimated their annual consumption of
salmon. Furthermore, there were differences in
consumption patterns between the two tribes included
in this study; the study provided data for each tribe
and for the pooled data from both tribes, but the latter
may not be a statistically valid measure for tribes in
the region.
10.6.7. Duncan (2000)—Fish Consumption
Survey of the Suquamish Indian Tribe of
the Port Madison Indian Reservation,
Puget Sound Region
The Suquamish Tribal Council conducted a study
of the Suquamish tribal members living on and near
the Port Madison Indian Reservation in the Puget
Sound region (Duncan, 2000). The study was funded
by the Agency for Toxic Substances and Disease
Registry (ATSDR) through a grant to the Washington
State Department of Health. The purpose of the study
was to determine seafood consumption rates,
patterns, and habits of the members of the Suquamish
Tribe. The second objective was to identify cultural
practices and attributes that affect consumption rates,
patterns, and habits of members of the Suquamish
Tribe.
Adults, 16 years and older, were selected
randomly from a Tribal enrollment roster. The study
had a participation rate of 64.8%, which was
calculated on the basis of 92 respondents out of a
total of 142 potentially eligible adults on the list of
those selected into the sample. Consumption data for
children under 6 years of age were gathered through
adult respondents who had children in this age group
living in the household at the time of the survey. Data
were collected for 31 children under 6 years old.
A survey questionnaire was administered by
personal interview. The survey included four parts:
(1) 24-hour dietary recall; (2) identification, portions,
frequency of consumption, preparation, harvest
location of fish; (3) shellfish consumption,
preparation, harvest location; and (4) changes in
consumption over time, cultural information, physical
information, and socioeconomic information. A
display booklet was used to assist respondents in
providing consumption data and identifying harvest
locations of seafood consumed. Physical models of
finfish and shellfish were constructed to assist
respondents in determining typical food portions.
Finfish and shellfish were grouped into categories
based on similarities in life history as well as
practices of Tribal members who fish for subsistence,
ceremonial, and commercial purposes.
Adult respondents reported a mean consumption
rate of all finfish and all shellfish of 2.71 g/kg-day
(see Table 10-103). Tables 10-104, 10-105, and
10-106 provide consumption rates for adults by
species, sex, and age, respectively. For children under
6 years of age, the mean consumption rate of all
finfish and shellfish was 1.48 g/kg-day (see
Tables 10-107 and 10-108). The Suquamish Tribe's
seafood consumption rates for adults and children
under 6 years of age were higher than seafood
consumption rates reported in studies conducted
among the CRITFC, Tulalip Tribes, Squaxin Island
Tribe, and the Asian Pacific Island population of
King County (Duncan, 2000). This disparity
illustrates the high degree of variability found
between tribes even within a small geographic region
(Puget Sound) and indicates that exposure and risk
assessors should exercise care when imputing fish
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consumption rates to a population of interest using
data from tribal studies.
An important attribute of this survey is that it
provides consumption rates by individual type of fish
and shellfish. It is important to note that the report
indicates that increased levels of development as well
as pollutants from residential, industrial, and
commercial uses have resulted in degraded habitats
and harvesting restrictions. Despite degraded water
quality and habitat, tribal members continue to rely
on fish and shellfish as a significant part of their diet.
A limitation of this study is that the sample size for
children was fairly small (31 children).
10.6.8. Westat (2006)—Fish Consumption in
Connecticut, Florida, Minnesota, and
North Dakota
As discussed in Section 10.3.2.7, Westat (2006)
analyzed the raw data from three fish consumption
studies to derive fish consumption rates for various
age, sex, and ethnic groups, and according to the
source of fish consumed (i.e., bought or caught) and
habitat (i.e., freshwater, estuarine, or marine). The
studies represented data from four states:
Connecticut, Florida, Minnesota, and North Dakota.
Consumption rates for individuals of Native
American heritage were available for the states of
Florida, Minnesota, and North Dakota. Fish intake
distributions for these populations are presented in
Table 10-41 for all respondents and 10-42 for
consuming individuals. The mean and 95th percentile
for all Native American respondents were
0.8 g/kg-day and 4.5 g/kg-day for Florida,
respectively. The mean fish intake rate for all Native
American respondents for Minnesota was
2.8 g/kg-day. The mean and 90th percentile fish intake
rate for all Native American respondents for North
Dakota were 0.4 g/kg-day and 0.9 g/kg-day,
respectively. The mean and 95th percentile intake rate
for Native American consumers only for Florida were
1.5 g/kg-day and 5.7 g/kg-day, respectively. The
mean fish intake rate for Native American consumers
only for Minnesota was 2.8 g/kg-day. The mean and
90th percentile fish intake rate for Native American
consumers only for North Dakota were 0.4 g/kg-day
and 0.8 g/kg-day, respectively (Westat, 2006).
A limitation of this study is that sample sizes for
these populations were small. Intake rates represent
consumption offish from all sources. Also, the study
did not specifically target Native Americans, and it is
not known whether the Native Americans included in
the survey lived on reservations.
10.6.9. Polissar et al. (2006)—A Fish
Consumption Survey of the Tulalip and
Squaxin Island Tribes of the Puget Sound
Region—Consumption Rates for
Fish-Consumers Only
Using fish consumption data from the Toy et al.
(1996) survey of the Tulalip and Squaxin Island
tribes of Puget Sound, Polissar et al. (2006)
calculated consumption rates for various fish species
groups, considering only the consumers of fish within
each group. Weight-adjusted consumption rates were
calculated by tribe, age, sex, and species groups.
Species groups (anadromous, bottom, pelagic, and
shellfish) were defined by life history and distribution
in the water column. Data were available for
69 children, birth to <6 years of age; 18 of these
children had no reported fish consumption and were
excluded from the analysis. Thus, estimated fish
consumption rates are based on data for 51 children;
15 from the Tulalip tribe and 36 from the Squaxin
Island tribe. Both median and mean fish consumption
rates for adults and children within each tribe were
calculated in terms of grams per kilogram of body
weight per day (g/kg-day). Anadromous fish and
shellfish were the groups of fish most frequently
consumed by both tribes and sexes. Consumption per
body weight varied by sex (males consumed more)
and age (those 35 to 64 years old consumed more
than those younger and older). The consumption rates
for groups of fish differed between the tribes. The
distribution of consumption rates was skewed toward
large values. In the Tulalip tribes, the estimated adult
mean consumption rate for all forms of fish
combined was 1.0 g/kg-day, and in the Squaxin
Island tribe, the estimated mean rate was also
1.0 g/kg-day (see Table 10-109). Table 10-110
presents consumption rates for adults by species and
sex. Tables 10-111 and 10-112 show consumption
rates for adults by species and age for the Squaxin
Island and Tulalip tribes, respectively. The mean
consumption rate for the Tulalip children was
0.45 g/kg-day, and 2.9 g/kg-day for the Squaxin
Island children (see Table 10-113). Table 10-114
presents consumption rates for children by species
and sex.
Because this study used the data originally
generated by Toy et al. (1996), the advantages and
limitations associated with the Toy et al. (1996)
study, as described in Section 10.6.6, also apply to
this study. However, an advantage of this study is that
the consumption rates are based only on individuals
who consumed fish within the selected categories.
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10.7. OTHER POPULATION STUDIES
10.7.1. U.S. EPA (1999)—Asian and Pacific
Islander Seafood Consumption Study in
King County, WA
This study was conducted to obtain seafood
consumption rates, species, and seafood parts
consumed, and cooking methods used by the Asian
and Pacific Islander (API) community. Participants
were seafood consumers who were first or
second generation members of the API ethnic group,
18 years of age or older, and lived in King County,
WA. APIs represent one of the most diverse and
rapidly growing immigrant populations in the United
States. In 1997, APIs (166,000) accounted for 10% of
King County's population, an increase from 8% in
1990. Between 1990 and 1997, the total population of
King Country increased by 9%, while the population
of APIs increased by 43% (U.S. EPA, 1999).
This study was conducted in three phases. Phase I
focused on identifying target ethnic groups and
developing appropriate questionnaires in the
language required for each ethnic group. Phase II
focused on characterizing seafood consumption
patterns for 10 API ethnic groups (Cambodian,
Chinese, Filipino, Hmong, Japanese, Korean,
Laotian, Mien, Samoan, and Vietnamese) within the
study area. Phase III focused on developing culturally
appropriate health messages on risks related to
seafood consumption and disseminating this
information for the API community. The majority of
the 202 respondents (89%) were first generation (i.e.,
born outside the United States). There were slightly
more women (53%) than men (47%), and 35% lived
under the 1997 Federal Poverty Level (FPL).
In general, it was found that API members
consumed seafood at a very high rate. As shown in
Table 10-115, the mean overall consumption rate for
all seafood combined was 1.9 g/kg body weight-day
(g/kg-day), with a median consumption rate of
1.4g/kg-day. The predominant seafood consumed
was shellfish (46% of all seafood). The API
community consumed more shellfish (average
consumption rate of 0.87 g/kg-day) than all finfish
combined (an average consumption rate of
0.82 g/kg-day). Within the category of finfish,
pelagic fish were consumed most by the API
members, mean consumption rate of 0.38 g/kg-day
(median: 0.22 g/kg-day), followed by anadromous
fish with a mean consumption rate of 0.20 g/kg-day
(median: 0.09 g/kg-day). The mean consumption for
freshwater fish was 0.11 g/kg-day (median:
0.04 g/kg-day), and bottom fish was 0.13 g/kg-day
(median: 0.05 g/kg-day). Individuals in the lowest
income level (under the FPL) consumed more
seafood than those in higher income levels (1-2, 2-3,
and >3 times the FPL), but the difference was not
statistically significant.
In an effort to capture the participants consuming
large quantities of seafood, the survey participants
were classified as higher (N= 44) or lower (N= 158)
consumers of shellfish or finfish based on their
consumption rates being >75* (higher) or
<75* (lower) percentile. Table 10-116 shows that
people in the >55-years-old-category had the greatest
percentage for high consumers of finfish; they had
approximately the same percentage as other age
groups for shellfish. The Japanese had a greater
percentage (52%) for higher finfish consumers, and
Vietnamese (50%) were in the higher shellfish
consumer category.
Table 10-117 presents seafood consumption rates
by ethnicity. In general, members of the Vietnamese
and Japanese communities had the highest overall
consumption rate, averaging 2.6 g/kg-day (median
2.4 g/kg-day) and 2.2 g/kg-day (median
1.8 g/kg day), respectively.
Table 10-118 presents consumption rates by sex.
The mean consumption rate for all seafood for
women was 1.8 g/kg-day (median: 1.4 g/kg-day) and
1.7 g/kg-day (median: 1.3 g/kg-day) for men.
Salmon and tuna were the most frequently
consumed finfish. More than 75% of the respondents
consumed shrimp, crab, and squid. Table 10-119
presents these data. For all survey participants, the
head, bones, eggs, and other organs were consumed
20% of the time. Fillet without skin was consumed
45% of the time, and fillet with skin, 55% of the
time. Consumption patterns of shellfish parts varied
depending on the type of shellfish.
Preparation methods were also surveyed in the
API community. The survey covered two categories
of preparation methods: (1) baked, broiled, roasted,
or poached and (2) canned, fried, raw, smoked, or
dried. The respondents most frequently prepared their
finfish and shellfish using the baked, boiled, broiled,
roasted, or poached method, averaging 65% and
78%, respectively.
The benefit of this research is that it can be used
to improve API-specific risk assessments. API
community members consume greater amounts of
seafood than the general population, and these
consumption patterns may pose a health risk if the
consumed seafood is contaminated with toxic
chemicals. Because the survey was based on recall,
the authors selected 20 respondents for a follow-up
re-interview. Its purpose was to assess the reliability
of the responses. The results of the re-interview
suggest that, based on the difference in means
between the original and re-interview responses, the
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estimated consumption rates from this study are
reliable. One limitation associated with this study is
that it is based on a relatively small number of
respondents within each ethnic group. Caution should
be used to avoid extrapolation of data to other ethnic
groups that have potentially significant cultural
differences. Further study of the consumption
patterns and preparation methods for the Hmong,
Laotian, Mien, and Vietnamese communities is also
needed because of potential health risks from
contaminated seafood.
10.7.2 Shilling et al. (2010)—Contaminated Fish
Consumption in California's Central
Valley Delta
Shilling et al. (2010) conducted a survey of
373 anglers and 137 community members between
September 2005 and June 2008, in a region of the
Sacramento-San Joaquin River Delta where
subsistence fishing rates are high. This area was also
chosen as an area where mercury concentrations in
fish tissues were likely to be high. Anglers were
selected for interviews as they were encountered in
order to reduce bias, however, approximately 5% of
the anglers approached did not speak English and
were unable to be interviewed. Community members
were chosen for interviews based on knowledge that
an extended family member fished in this area. The
interviews were conducted primarily in the early
morning and late afternoon, and all days of the week
were represented. Subjects were told at the beginning
of the interview that the study was about fishing
activity along the river, but not that it was related to
fish contamination. Anglers and community members
were grouped according to ethnicity, and fish
consumption rates were calculated based on each
individual's 30-day recall of how much and how
often types of fish were eaten. Mean, median and
95th percentile fish consumption rates were calculated
for study participants according to ethnicity, age, and
sex. In addition, fish intake was determined for
households containing women of child-bearing age,
children, and for respondents whose awareness of
warnings about fish contamination in the area ranged
from no awareness to high awareness.
Regardless of ethnicity, the fish species that were
primarily targeted by anglers in this study were
striped bass, salmon, shad, and catfish, similar to
those identified in creel survey data for this region
from the California Department of Fish and Game.
Consumption rates for locally caught and
commercially obtained fish are shown in
Table 10-120. Mean intake of locally caught fish
among all ethnic groups ranged from 6.5 g/day for
Native American anglers to 57.6 g/day for Southeast
Asian/Lao anglers. For all anglers, the mean and
median consumption rates of locally caught fish were
27.4 and 19.7 g/day, respectively. These values
increased to 40.6 g/day (mean) and 26.1 g/day
(median) when commercially obtained fish were
included. The 95th percentile intake rates for all
anglers were 126.6 g/day for local fish consumption
and 147.3 g/day for total fish consumption. Fish
consumption rates were not significantly different
among age groups, but were higher for anglers from
households with either children or women of
child-bearing age.
No significant trend (p = 0.78) was observed
across the 3-year study period for the consumption of
locally caught fish. Peak consumption rates occurred
during the fall, when striped bass and salmon return
to the area to spawn and fishing activity is the
highest. Fish consumption rates were significantly
different for anglers and community members, with
the exception of Southeast Asians. No significant
difference was observed between the day of the week
when surveying was conducted and ethnic group or
fish consumption rates, or between anglers with
higher or lower awareness of warnings about fish
contamination in the area.
The advantages of this study are that the sample
size was fairly large and that a number of ethnic
groups were included. Limitations of the study
include the fact that information on fish consumption
was based on 30-day recall data and that the study
was limited to one geographic area and may not be
representative of the U.S. general population.
10.8. SERVING SIZE STUDIES
10.8.1. Pao et al. (1982)—Foods Commonly
Eaten in the United States: Amount per
Day and per Eating Occasion
Pao et al. (1982) used the 1977-1978 NFCS to
examine the quantity of fish consumed per eating
occasion. For each individual consuming fish in the
3-day survey period, the quantity of fish consumed
per eating occasion was derived by dividing the total
reported fish intake over the 3-day period by the
number of occasions the individual reported eating
fish. Table 10-121 displays the distributions, by age
and sex, for the quantity of fish consumed per eating
occasion (Pao et al., 1982). For the general
population, the average quantity of fish consumed per
fish meal was 117 grams, with a 95th percentile of
284 grams. Males in the age groups 19-34, 35-64,
and 65-74 years had the highest average and
95th percentile quantities among the age-sex groups
presented. It should be noted that the serving size
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data from this analysis has been superseded by the
analysis of the 1994-1996 USDA CSFII data
conducted by Smiciklas-Wright et al. (2002).
10.8.2. Smiciklas-Wright et al. (2002)—Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating
Occasion and in a Day, 1994-1996
Using data gathered in the 1994-1996 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of canned tuna and
other finfish consumed per eating occasion by
members of the U.S. population (i.e., serving sizes),
over a 2-day period. The estimates of serving size are
based on data obtained from 14,262 respondents,
ages 2 years and above, who provided 2 days of
dietary intake information. Only dietary intake data
from users of the specified food were used in the
analysis (i.e., consumers-only data).
Table 10-122 and Table 10-123 present serving
size data for canned tuna and other finfish,
respectively. These data are presented on an
as-consumed basis (grams) and represent the quantity
of fish consumed per eating occasion. These
estimates may be useful for assessing acute exposures
to contaminants in specific foods, or other
assessments where the amount consumed per eating
occasion is necessary. The average meal size for
finfish (other than tuna) for adults 20 years and older
was 114 g/meal (see Table 10-122). It should be
noted that this value represents fish eaten in any form
(e.g., as an ingredient in a meal) and not just fish
eaten as a meal (e.g., fish fillet).
The advantages of using these data are that they
were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002)
accounted for individual foods consumed as
ingredients of mixed foods. Mixed foods were
disaggregated via recipe files so that the individual
ingredients could be grouped together with similar
foods that were reported separately. Thus, weights of
foods consumed as ingredients were combined with
weights of foods reported separately to provide a
more thorough representation of consumption.
However, it should be noted that because the recipes
for the mixed foods consumed by respondents were
not provided by the respondents, standard recipes
were used. As a result, the estimates of the quantity
of some food types are based on assumptions about
the types and quantities of ingredients consumed as
part of mixed foods.
10.9. OTHER FACTORS TO CONSIDER FOR
FISH CONSUMPTION
Other factors to consider when using the available
survey data include location, climate, season, and
ethnicity of the angler or consumer population, as
well as the parts of fish consumed and the methods of
preparation. Some contaminants (for example,
persistent, bioaccumulative, and toxic contaminants
such as dioxins and polychlorinated biphenyls) have
the affinity to accumulate more in certain tissues,
such as the fatty tissue, as well as in certain internal
organs. The effects of cooking methods for various
food products on the levels of dioxin-like compounds
have been addressed by evaluating a number of
studies in U.S. EPA (2003). These studies showed
various results for contamination losses based on the
methodology of the study and the method of food
preparation. Refer to U.S. EPA (2003) for a detailed
review of these studies.
In addition, some studies suggest that there is a
significant decrease of contaminants in cooked fish
when compared with raw fish (San Diego County,
1990). Several studies cited in this section have
addressed fish preparation methods and parts of fish
consumed. Table 10-124 provides summary results
from these studies on fish preparation methods;
Appendix 10B presents further details on preparation
methods, as well as results from some studies on
parts of fish consumed.
Users of the data presented in this chapter should
ensure that consistent units are used for intake rate
and concentration of contaminants in fish. The
following sections provide information on converting
between wet weight and dry weight, and between wet
weight and lipid weight.
10.9.1. Conversion between Wet and Dry Weight
The intake data presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
uncooked weight of fish consumed per day or per
eating occasion). However, data on the concentration
of contaminants in fish may be reported in units of
either wet or dry weight (e.g., milligram of
contaminant per gram-dry-weight of fish). It is
essential that exposure assessors be aware of this
difference so that they may ensure consistency
between the units used for intake rates and those used
for concentration data (i.e., if the contaminant
concentration is measured in dry weight of fish, then
the dry-weight units should be used for fish intake
values).
If necessary, wet-weight (e.g., as-consumed)
intake rates may be converted to dry-weight intake
rates using the moisture content percentages
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presented in Table 10-125 and the following
equation:
rates using the fat content percentages presented in
Table 10-125 and the following equation:
100- W
100
(Eqn. 10-4)
L
100
(Eqn. 10-6)
where:
IRdv = dry-weight intake rate,
IRWV = wet-weight intake rate, and
W = percent water content.
Alternately, dry-weight residue levels in fish may
be converted to wet-weight residue levels for use
with wet-weight (e.g., as-consumed) intake rates, as
follows:
where:
IRh, = lipid-weight intake rate,
IRVW = wet-weight intake rate, and
L = percent lipid (fat) content.
Alternately, wet-weight residue levels in fish may
be estimated by multiplying the levels based on fat by
the fraction of fat per product as follows:
CL, = C*
where:
100- W
100
(Eqn. 10-5)
Cww = wet-weight concentration,
C&, = dry-weight concentration, and
W = percent water content.
c =
^-"tV\V
where:
Ch, I .A.
100
(Eqn. 10-7)
= wet-weight concentration,
= lipid-weight concentration, and
= percent lipid (fat) content.
The moisture content data presented in
Table 10-125 are for selected fish taken from USDA
(2007). The moisture content is based on the percent
of water present.
10.9.2. Conversion Between Wet-Weight and
Lipid-Weight Intake Rates
In some cases, the residue levels of contaminants
in fish are reported as the concentration of
contaminant per gram of fat. This may be particularly
true for lipophilic compounds. When using these
residue levels, the assessor should ensure consistency
in the exposure-assessment calculations by using
consumption rates that are based on the amount of fat
consumed for the fish product of interest.
The total fat content (percent) measured and/or
calculated in various fish forms (i.e., raw, cooked,
smoked, etc.) for selected fish species is presented in
Table 10-125, based on data from USDA (2007). The
total percent fat content is based on the sum of
saturated, monounsaturated, and polyunsaturated fat.
If necessary, wet-weight (e.g., as-consumed)
intake rates may be converted to lipid-weight intake
The resulting residue levels may then be used in
conjunction with wet-weight (e.g., as-consumed)
consumption rates. The total fat content data
presented in Table 10-125 are for selected fish taken
from USDA (2007).
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Resources for the Michigan Department of
Natural Resources, Ann Arbor, MI.
Technical Report No. 6, May.
Westat. (2006) Fish consumption in Connecticut,
Florida, Minnesota, and North Dakota: Draft
final report. July 16, 2006. Submitted by
Westat, Rockville, MD to EPA/ORD,
Washington, DC.
Williams, R; O'Leary, J; Sheaffer, A; Mason, D.
(1999) Consumption of Indiana sport caught
fish: Mail survey of resident license holders.
Technical Report 99-D-HDFW-l. Dept. of
Forestry and Natural Resources, West
Lafayette, IN.
Williams, R; O'Leary, J; Sheaffer, A; Mason, D.
(2000) An examination of fish consumption
by Indiana recreational anglers: An onsite
survey. Technical Report 99-D-HDFW-2.
Dept. of Forestry and Natural Resources,
Purdue University, West Lafayette, IN.
Wolfe, RJ; Walker, RJ. (1987) Subsistence economics
in Alaska: productivity, geography, and
development impacts. Arctic Anthropology
24(2): 56-81.
Exposure Factors Handbook
September 2011
Page
10-61
-------
Table 10-7. Per Capita Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight
Percentiles
%
Population Group „ Consuming Mean
Whole Population 16,783
Age Group (years)
0 to 1 865
Ito2 1,052
3 to 5 978
6 to 12 2,256
13 to 19 3,450
20 to 49 4,289
Females 13 to 49 4,103
50+ 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 552
Other a 749
a Other: Other Race - including
b Estimates are less statistically
23 0.16
2.6 0.03
14 0.22
15 0.19
15 0.16
15 0.10
23 0.15
22 0.14
29 0.20
16 0.15
24 0.18
22 0.15
22 0.18
33 0.31
Multiple Races.
reliable based on
Lower
SE 95% CL
0.01
0.01
0.05
0.03
0.04
0.01
0.01
0.01
0.02
0.02
0.02
0.01
0.03
0.05
0.14
0.01
0.12
0.13
0.08
0.08
0.13
0.11
0.16
0.11
0.15
0.13
0.11
0.20
guidance published
Upper
95%CL Min
0.18 0.0"
0.06 0.0b
0.32 0.0b
0.25 0.0b
0.24 0.0b
0.11 0.0b
0.17 0.0b
0.16 0.0b
0.23 0.0b
0.18 0.0b
0.22 0.0b
0.17 0.0b
0.24 0.0b
0.42 0.0b
in the Joint Policy
and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max = Maximum value.
1st
0.0
o.ob
o.ob
o.ob
o.ob
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.ob
o.ob
5th
0.0
10
o.ob
o.ob
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50th 75th
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.1
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.2
90th 95th
0.6 1.1
0.0 0.0b
0.5 1.2b
0.7 1.4
0.5 1.1
0.3 0.7
0.5 1.0
0.5 0.9
0.7 1.2
0.5 1.1
0.6 1.1
0.5 1.0
0.5 1.0
1.1 2.0
on Variance Estimation and Statistical Reporting Standards
, 1993).
99th Max
2.3 13.4"
1.5b 3.7b
4.3b 13.4b
2.7b 7.0b
2.6b 6.7b
1.7 6.9b
2.2 8.5b
1.8 8.5b
2.4 6.1b
2.6 8.5b
2.4 8.8b
2.0 13.4b
2.7b 7.3b
4.0b 6.5b
on NHANES III
Source: U.S. EPA analysis of NHANES 2003-2006.
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Table 10-8. Consumer-Only Intake of Finfish (g/kg-day),
Lower
Upper
Population Group N M SE 95%CL 95% CL
Whole Population 3,204 C^73 0.03
Age Group (years)
Otol 22 1.31 0.31
Ito2 143 1.61 0.27
3 to 5 156 1.28 0.13
6 to 12 333 1.05 0.12
13 to 19 501 0.66 0.03
20 to 49 961 0.65 0.02
Females 13 to 49 793 0.04
50+ 1,088 0.68 0.04
Race 0.62
Mexican American 534 0.93 0.04
Non-Hispanic Black 906 0.77 0.05
Non-Hispanic White 1,405 0.67 0.03
Other Hispanic \Q\ 0.82 0.10
Other3 208 0.96 0.14
a Other: Other Race - including Multiple Races.
0.67
0.68
1.06
1.01
0.81
0.59
0.60
0.54
0.61
0.84
0.66
0.62
0.61
0.68
0.78
1.94
2.16
1.55
1.29
0.73
0.70
0.69
0.76
1.03
0.88
0.72
1.03
1.23
Edible Portion,
Uncooked Fish Weight
Percentiles
Min
0.0*
O.lb
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
o.ob
b Estimates are less statistically reliable based on guidance published in the Joint Policy on
1st
0.0
O.lb
o.ob
o.ob
o.ob
o.ob
o.ob
0.0
o.ob
o.ob
0.0
o.ob
o.ob
o.ob
5th
0.0
10
0.2b
O.lb
0.0b
0.0b
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.ob
o.ob
til ^cth
0.0 0.2
0.2b 0.4b
0.2b 0.5b
0.2b 0.5
O.lb 0.3
0.0 0.2
0.0 0.2
0.0 0.1
0.0 0.2
0.0 0.3
0.1 0.2
0.0 0.2
O.lb 0.3
0.0 0.2
50th
0.5
0.8b
0.8b
1.0
0.7
0.5
0.4
0.4
0.5
0.7
0.5
0.5
0.5
0.5
75th
1.0
2.0b
1.7b
1.7
1.4
0.9
0.9
0.9
0.9
1.3
1.0
0.9
1.0
1.3
90th
1.6
2.8b
3.6b
2.7b
2.1b
1.4
1.5
1.4
1.5
1.9
1.7
1.5
2.0b
2.2
95th
2.2
2.9b
4.9b
3.6b
2.9b
1.7
2.1
1.8
2.0
2.8
2.1
1.9
2.7b
3.6b
99th Max
4.0 13.4"
3.7b 3.7b
13.4b 13.4b
5.6b 7.0b
6.5b 6.7b
2.6b 6.9b
3.9b 8.5b
2.9 8.5b
3.2b 6.1b
4.7b 8.5b
4.9 8.8b
3.2b 13.4b
4.9b 7.3b
5.3b 6.5b
Variance Estimation and Statistical Reporting Standards on
NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max = Maximum value.
Source: U.S. EPA analysis of NHANES 2003-2006.
1993).
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Table 10-9. Per Capita Intake of Shellfish (g/kg-day),
%
Population Group N Consuming Mean SE
Whole Population 16,783 11 0.06 0.01
Age Group (years)
Otol 865 0.66 0.00 0.00
Ito2 1,052 4.4 0.04 0.01
3 to 5 978 4.6 0.05 0.01
6 to 12 2,256 7.0 0.05 0.01
13 to 19 3,450 5.1 0.03 0.01
20 to 49 4,289 13 0.08 0.01
Females 13 to 49 4,103 11 0.06 0.01
50+ 3,893 13 0.05 0.01
Race
Mexican American 4,450 9.5 0.08 0.01
Non-Hispanic Black 4,265 12 0.06 0.01
Non-Hispanic White 6,757 10 0.05 0.01
Other Hispanic 552 0.09 0.02
Othera 749 20 0.13 0.02
a Other: Other Race - including Multiple Races.
Lower
95% CL
0.05
0.00
0.02
0.02
0.02
0.02
0.06
0.04
0.04
0.05
0.04
0.04
0.05
0.10
Upper
95% CL
0.07
0.01
0.06
0.08
0.08
0.04
0.10
0.07
0.07
0.11
0.07
0.07
0.14
0.17
Edible Portion, Uncooked
Min
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
o.ob
ist th
0.0 0.0
o.ob o.ob
o.ob o.ob
0.0b 0.0
0.0b 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0b 0.0
0.0b 0.0
10th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Fish Weight
Percentiles
25* 50th
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
75th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
90th
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.0
0.4
0.4
95th 99th
0.4 1.4
o.ob o.ob
0.0b 1.0b
0.0 1.4b
0.2 1.4b
0.0 1.1
0.5 1.9
0.3 1.3
0.4 1.0
0.5 1.8
0.3 1.1
0.3 1.2
0.7 2.1b
0.9 2.6b
Max
6.6"
2.3b
6.6b
4.0b
4.9b
4.5b
5.4b
5.3b
5.2b
6.6b
4.9b
5.4b
2.6b
4.5b
b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III and
CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max =Maximum value.
Source: U.S. EPA analysis of NHANES 2003-2006.
(NCHS, 1993).
^fc
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Table 10-10. Consumers-Only Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight
Lower
Population Group N Mean SE 95%CL
Whole Population 1,563 0.57 0.03 0.50
Age Group (years)
Otol 11 0.42 0.21 0.00
Ito2 53 0.94 0.18 0.56
3 to 5 56 1.00 0.18 0.63
6 to 12 158 0.72 0.12 0.47
13 to 19 245 0.61 0.06 0.49
20 to 49 605 0.63 0.06 0.52
Females 13 to 49 474 0.06 0.40
50+ 435 0.41 0.02 0.36
Race 0.53
Mexican American 331 0.83 0.10 0.62
Non-Hispanic Black 449 0.48 0.03 0.41
Non-Hispanic White 617 0.53 0.05 0.44
Other Hispanic 49 0.07 0.49
Other3 117 0.67 0.06 0.55
a Other: Other Race - incflufittng Multiple Races.
Upper
95% CL
0.63
0.85
1.31
1.36
0.97
0.74
0.75
0.66
0.46
1.04
0.54
0.63
0.79
0.80
Percentiles
Min
0.0"
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
0.0b
1st
0.0"
5
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
o.ob
ttl
0.0
o.ob
o.ob
o.ob
O.lb
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.ob
O.lb
10th
0.0
o.ob
O.lb
O.lb
O.lb
0.0
0.0
0.0
0.0
0.1
0.0
0.0
O.lb
O.lb
25m
0.1
o.ob
0.2b
0.4b
0.2
0.1
0.1
0.1
0.1
0.2
0.1
0.1
0.3b
0.2
50m
0.3
0.2b
0.6b
0.7b
0.5
0.4
0.4
0.3
0.3
0.5
0.3
0.3
0.4
0.4
75m 90m
0.7 1.3
0.2b 1.3b
1.0b 1.6b
1.4b 2.9b
1.1 1.7b
0.9 1.5
0.8 1.8
0.6 1.2
0.5 0.9
1.1 1.9
0.6 1.1
0.6 1.2
0.9b 1.3b
0.9 1.4b
95m
1.9
2.3b
3.5b
2.9b
2.0b
1.9
2.2
1.8
1.2
2.8
1.7
1.9
2.1b
2.6b
99m
3.0"
2.3b
6.6b
4.0b
4.5b
2.7b
4.3b
4.5b
1.8b
4.3b
2.5b
3.0b
2.6b
2.6b
Max
6.6"
2.3b
6.6b
4.0b
4.9b
4.5b
5.4b
5.3b
5.2b
6.6b
4.9b
5.4b
2.6b
4.5b
b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III
and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS,
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max = Maximum value.
Source: U.S. EPA analysis of NHANES 2003-2006.
1993).
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-------
Table 10-11. Per Capita Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion, Uncooked Fish Weight
Percentiles
% Lower Upper
Population Group N Consuming Mean
Whole Population 16,783
Age Group (years)
0 to 1 865
1 to 2 1,052
3 to 5 978
6 to 12 2,256
13 to 19 3,450
20 to 49 4,289
Females 13 to 49 4,103
50+ 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 552
Other a 749
a Other: Other Race - including
b Estimates are less statistically
29 0.22
3.1 0.04
17 0.26
18 0.24
22 0.21
18 0.13
31 0.23
28 0.19
36 0.25
22 0.23
32 0.24
28 0.20
32 0.27
43 0.45
Multiple Races.
SE
0.014
0.01
0.06
0.03
0.05
0.01
0.02
0.02
0.02
0.03
0.02
0.01
0.05
0.06
95%CL 95% CL Min
0.20
0.02
0.15
0.17
0.12
0.10
0.20
0.16
0.21
0.17
0.20
0.17
0.17
0.32
0.25 0.0b
0.06 0.0b
0.38 0.0b
0.31 0.0b
0.31 0.0b
0.15 0.0b
0.27 0.0b
0.22 0.0b
0.29 0.0b
0.28 0.0b
0.28 0.0b
0.23 0.0b
0.37 0.0b
0.58 0.0b
reliable based on guidance published in the Joint Policy on
ist th
o.o5 o.o
o.ob o.ob
o.ob o.ob
0.0b 0.0
0.0b 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0b 0.0
0.0b 0.0
10th 25th
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
50th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75th
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.3
0.0
0.2
0.1
0.2
0.4
90th
0.8
0.0
0.7
0.9
0.8
0.4
0.8
0.7
0.9
0.9
0.8
0.7
0.9
1.5
95th
1.39
0.0b
1.6b
1.6
1.4
1.0
1.3
1.2
1.4
1.4
1.3
1.2
1.7
2.5
* Max
2.7 13.4b
1.5b 5.1b
4.7b 13.4b
3.4b 7.0b
2.7b 6.7b
1.7 6.9b
2.7 8.6b
2.4 8.6b
2.6 6.1b
3.5 8.6b
2.7 8.9b
2.4 13.4b
3.1b 7.3b
4.1b 6.5b
Variance Estimation and Statistical Reporting Standards on NHANES III
and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max = Maximum value.
Source: U.S. EPA analysis of NHANES 2003-2006.
I
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-------
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1=
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Table 10-12. Consumer-Only Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion
Lower Unner
Population Group
Whole Population
Age Group (years)
Otol
Ito2
3 to 5
6 to 12
13 to 19
20 to 49
Females 13 to 49
50+
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other a
a Other: Other Race - including
b Estimates are less statistically
N
4,206
30
183
196
461
685
1,332
1,109
1,319
831
1,212
1,753
136
274
Mean SE 95%CL 95% CL
0.78 0.03
1.18 0.29
1.54 0.25
1.31 0.14
0.99 0.08
0.69 0.03
0.76 0.04
0.68 0.04
0.71 0.03
1.01 0.06
0.76 0.04
0.73 0.03
0.86 0.11
1.03 0.13
0.73
0.59
1.04
1.04
0.82
0.63
0.68
0.60
0.64
0.88
0.67
0.67
0.63
0.77
0.83
1.76
2.04
1.59
1.15
0.76
0.83
0.76
0.77
1.14
0.85
0.78
1.09
1.29
Min 1st
0.0" 0.0
0.0b ^
0.0b 0.0b
0.0b 0.0b
0.0b 0.0b
0.0b 0.0b
0.0b 0.0
o.ob o.ob
0.0b 0.0
o.ob o.ob
o.ob
o.ob o.ob
0.0b 0.0
o.ob o.ob
o.ob o.ob
o.ob o.ob
th
0.0
o.ob
O.lb
O.lb
O.lb
0.0
0.0
0.0
0.0
0.0
0.0
0.0
o.ob
o.ob
, Uncooked Fish Weight
Percentiles
10th 25th
0.1 0.2
O.lb 0.2b
0.2b 0.4b
0.2b 0.5
0.1 0.3
0.0 0.2
0.0 0.2
0.0 0.2
0.1 0.2
0.1 0.3
0.1 0.2
0.0 0.2
O.lb 0.3
0.1 0.2
50th
0.5
0.7b
0.8
1.0
0.7
0.5
0.5
0.4
0.5
0.8
0.5
0.5
0.5
0.6
75th
1.1
1.6b
1.7b
1.7
1.4
1.0
1.0
0.9
1.0
1.3
1.0
1.0
1.2
1.4
90th 95th
1.8 2.4
2.8b 2.9b
3.5b 5.9b
2.9b 3.6b
2.0 2.7b
1.5 1.8
1.8 2.5
1.5 1.9
1.6 2.1
2.1 3.2
1.8 2.2
1.6 2.1
2.0b 2.6b
2.5 2.9b
99th Max
4.2 13.4"
5.1b 5.1b
13.4b 13.4b
6.2b 7.0b
5.2b 6.7b
3.0 6.9b
4.2b 8.6b
4.0 8.6b
3.3b 6.1b
5.6b 8.6b
4.9 8.9b
3.4b 13.4b
5.2b 7.3b
6.1b 6.5b
Multiple Races.
reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III and
CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations
N = Sample size.
SE = Standard error.
CL = Confidence limit.
Min = Minimum value.
Max = Maximum value.
(NCHS,
1993).
Source: U.S. EPA analysis of NHANES 2003-2006.
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a
&
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-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-13. Total Fish
Demographic Category
Overall (all fish consumers)
Race
Caucasian
Black
Asian
Other
Sex
Female
Male
Age (years)
Oto9
10 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
>70
Sex and Age (years)
Female
Oto9
10 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
>70
Male
Oto9
10 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
>70
Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
Consumption, Consumers Only, by
Mean
14.3
14.2
16.0
21.0
13.2
13.2
15.6
6.2
10.1
14.5
15.8
17.4
20.9
21.7
13.3
6.1
9.0
13.4
14.9
16.7
19.5
19.0
10.7
6.3
11.2
16.1
17.0
18.2
22.8
24.4
15.8
16.3
16.2
12.9
12.0
15.2
13.0
14.4
12.1
14.2
Demographic Variables"
Intake (g/person-day)
95th Percentile
41.7
41.2
45.2
67.3
29.4
38.4
44.8
16.5
26.8
38.3
42.9
48.1
53.4
55.4
39.8
17.3
25.0
34.5
41.8
49.6
50.1
46.3
31.7
15.8
29.1
43.7
45.6
47.7
57.5
61.1
45.7
46.5
47.8
36.9
35.2
44.1
38.4
43.6
32.1
39.6
Page
10-68
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-13. Total Fish Consumption, Consumers Only,
by Demographic Variables
a (continued)
Intake (g/person-day)
Demographic Category
Community Type
Rural, non-SMSA
Central city, 2M or more
Outside central city, 2M or more
Central city, 1M-2M
Outside central city, 1M-2M
Central city, 500K-1M
Outside central city, 500K-1M
Outside central city, 250K-500K
Central city, 250K-500K
Central city, 50K-250K
Outside central city, 50K-250K
Other urban
Mean 9^
13.0
19.0
15.9
15.4
14.5
14.2
14.0
12.2
14.1
13.8
11.3
13.5
a The calculations in this table are based on respondents who consumed fish during the
These respondents are estimated to represent 94% of the
SMSA = Standard metropolitan statistical area.
Source: Javitz, 1980.
U.S. population.
^^Percentile
38.3
55.6
47.3
41.7
41.5
41.0
39.7
32.1
40.5
43.4
31.7
39.2
survey month.
Exposure Factors Handbook
September 2011
Page
10-69
-------
a*
I
»r
Table
10-14. Percent Distribution of Total
Fish Consumption for Females and Males by Age"
Consumption Category (g/day)
0.0-5.0
5.1-10.0
10.1-15.0 15.1-20.0
20.1-25.0 25.1-30.0 30.1-37.5 37.6-47.5 47.
6-60.0 60.1-122.5 over 122.5
Age
(years)
Females
0 to 9 55.5
10 to 19 17.8
20 to 29 28.1
30 to 39 22.4
40 to 49 17.5
50 to 59 17.0
60 to 69 11.5
>70 41.9
r^ 11 28.9
Overall
Males
Oto9 52.1
10 to 19 27.8
20 to 29 16.7
30 to 39 16.6
40 to 49 11.9
50 to 59 9.9
60 to 69 7.4
>70 24.5
Ovcnil 22.6
^/VLidll
The percentage
based upon the
population.
Source: Javitz, 1980.
26.8
31.4
26.1
23.6
21.9
17.4
16.9
22.1
24.0
30.1
29.3
22.9
21.2
22.3
15.2
15.0
21.7
23.1
of females
11.0
15.4
20.4
18.0
20.7
16.8
20.6
12.3
16.8
11.9
19.0
19.6
19.2
18.6
15.4
15.6
15.7
17.0
in an age
3.7
6.9
11.8
12.7
13.2
15.5
15.9
9.7
10.7
3.1
10.4
14.5
13.2
14.7
14.4
12.8
9.9
11.3
1.0
3.5
6.7
8.3
9.3
10.5
9.1
5.2
6.4
1.2
6.0
8.8
9.5
8.4
10.4
11.4
9.8
7.7
bracket whose average daily
respondents who consumed fish during
1.1
2.4
3.5
4.8
4.5
8.5
9.2
2.9
4.3
0.6
3.2
6.2
7.3
8.5
9.7
8.5
5.3
5.7
fish consumption
0.7
1.2
4.4
3.8
4.6
6.8
6.0
2.6
3.5
0.7
1.7
4.4
5.2
5.3
8.7
9.9
5.4
4.6
is within the
0.3
0.7
2.2
2.8
2.8
5.2
6.1
1.2
2.4
0.1
1.7
3.1
3.2
5.2
7.6
8.3
3.1
3.6
specified range.
the month of the survey. These respondents are estimated
0.0
0.2
0.9
1.9
3.4
4.2
2.4
0.8
1.6
0.2
0.4
1.9
1.3
3.3
4.3
5.5
1.7
2.2
The
0.0
0.4
0.9
1.7
2.1
2.0
2.1
1.2
1.2
0.1
0.5
1.9
2.2
1.7
4.1
5.5
2.8
2.1
0.0
0.0
0.0
0.1
0.2
0.2
0.2
0.1
0.1
0.0
0.0
0.1
0.0
0.1
0.2
0.1
0.1
0.1
calculations in this table are
to represent 94% of the U
s.
Q
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-15. Mean Total Fish Consumption by Species"
Mean consumption
Species
Not reported
Abalone
Anchovies
Bassb
Bluefish
Bluegillsb
Bonitob
Buffalofish
Butterfish
Carpb
Catfish (Freshwater)13
Catfish (Marine)13
Clamsb
Cod
Crab, King
Crab, other than Kingb
Crappieb
Croakerb
Dolphinb
Drums
Flounders'3
Groupers
Haddock
Hake
Halibutb
Herring
Kingfish
Lobster (Northern)13
Lobster (Spiny)
Mackerel, Jack
Mackerel, other than Jack
a The calculations in this table
(g/day)
1.173
0.014
0.010
0.258
0.070
0.089
0.035
0.022
0.010
0.016
0.292
0.014
0.442
0.407
0.030
0.254
0.076
0.028
0.012
0.019
1.179
0.026
0.399
0.117
0.170
0.224
0.009
0.162
0.074
0.002
0.172
Species
Mullet13
Oysters'3
Perch (Freshwater)13
Perch (Marine)
Pike (Marine)13
Pollock
Pompano
Rockfish
Sablefish
Salmon13
Scallops'3
Scupb
Sharks
Shrimp13
Smeltb
Snapper
Snookb
Spotb
Squid and Octopi
Sunfish
Swordfish
Tilefish
Trout (Freshwater)13
Trout (Marine)13
Tuna, light
Tuna, White Albacore
Whitefishb
Other finfishb
Other shellfish13
are based upon respondents who consumed fish during
survey. These respondents are estimated to
represent 94% of the U.S. population.
Mean consumption
(g/day)
0.029
0.291
0.062
0.773
0.154
0.266
0.004
0.027
0.002
0.533
0.127
0.014
0.001
1.464
0.057
0.146
0.005
0.046
0.016
0.020
0.012
0.003
0.294
0.070
3.491
0.008
0.141
0.403
0.013
the month of the
b Designated as freshwater or estuarine species.
Source: Javitz, 1980.
Exposure Factors Handbook
September 2011
Page
10-71
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-16. Best Fits of Lognormal Distributions Using the Non-Linear Optimization Method
Adults Teenagers Children
Shellfish
H 1.370 -0.183 0.854
a 0.858 1.092 0.730
Finfish (freshwater)
H 0.334 0.578 -0.559
a 1.183 0.822 1.141
Finfish (saltwater) 2.311 1.691 0.881
. 0.72 0.830 0.970
The following equations may be used with the appropriate n and a values to obtain an average Daily
Consumption Rate (DCR), in grams, and percentiles of the DCR distribution.
DCR50 = exp (u)
DCR90 = exp [\i + z(0.90) x a]
DCR99 = exp [n + z(0.99) x a]
DCRavg = exp [u + 0.5 x o2]
Source: Ruffle etal., 1994.
Table 10-17. Mean Fish Intake
in a Day, by Sex and Agea
Sex Per capita intake Percent of population Mean intake (g/day) for
Age (years) (g/day) consuming fish in 1 day consumers onlyb
Males or Females
5 and under
Males
6 to 11
12 to 19
20 and over
Females
6 to 11
12 to 19
20 and over
All individuals
4
o
J
o
J
15
7
9
12
11
6.0
3.7
2.2
10.9
7.1
9.0
10.9
9.4
Based on USDA Nationwide Food Consumption Survey 1987-1988 data for 1 day.
b Intake for users only was calculated by dividing the per capita consumption rate by
population consuming fish in 1 day.
Source: USDA, 1992b.
67
79
136
138
99
100
110
117
the fraction of the
Page Exposure Factors Handbook
10-72 September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-18. Percent of Respondents That Responded Yes, No, or Don't Know to Eating Seafood
(including shellfish, eels, or squid)
No
Population Group
Overall
Sex
*
Male
Female
Age (years)
*
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
*
White
Black
Asian
Some Others
Hispanic
Hispanic
*
No
Yes
DK
Employment
*
Full Time
Part Time
Not Employed
Education
*
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-18. Percent of Respondents That Responded Yes, No, or Don't Know to Eating Seafood
(including shellfish, eels, or squid) (continued)
No
Population Group
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No
Yes
DK
* = Missing data.
DK = Don't know.
% = Row percentage.
N = Sample size.
Source: U.S. EPA, 1996.
Total jV
1,048
1,036
1,601
978
3,156
1,507
1,264
1,181
1,275
943
4,287
341
35
4,500
125
38
4,424
203
36
N
370
449
590
402
1,254
557
462
469
506
374
1,674
131
6
1,750
56
50
1,726
80
5
%
35.3
43.3
36.9
41.1
39.7
37.0
36.6
39.7
39.7
39.7
39.0
38.4
17.7
38.9
44.8
13.2
9.0
39.4
13.9
Response
Yes
N
655
575
989
561
1,848
932
780
691
745
564
2,563
207
10
2,698
68
14
2,648
121
11
%
62.5
55.5
61.8
57.4
58.6
61.8
61.7
58.5
58.4
59.8
59.8
60.7
28.6
60.0
54.4
36.8
59.6
59.6
30.6
N
23
12
22
15
54
18
22
21
24
5
50
3
19
52
1
19
50
2
20
in 1 Month
DK
%
2.2
1.2
1.4
1.5
1.7
1.2
1.7
1.8
1.9
0.5
1.2
0.9
54.3
1.2
0.8
50.0
1.1
1.0
55.6
Page
10-74
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of Seafood
in 1 Month
Number of Servings in a Month
Population Group
Overall
Sex
*
Male
Female
Age (years)
*
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
*
White
Black
Asian
Some Others
Hispanic
Hispanic
*
No
Yes
DK
Employment
*
Full Time
Part Time
Not Employed
Refused
Education
*
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of
Seafood in 1 Month (continued)
Number of Servings in a Month
Population Group Total TV
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No
Yes
DK
* = Missing data.
DK = Don't know.
% = Row percentage.
N = Sample size.
Refused = Respondent refused to
Source: U.S. EPA, 1996.
1,848
932
780
691
745
564
2,563
207
10
2,698
68
14
2,648
121
11
answer.
1-2
602
316
262
240
220
196
846
69
3
896
19
3
877
37
4
3-5
661
329
284
244
249
213
917
71
2
960
27
3
940
47
3
6-10
346
173
131
123
160
105
475
42
2
509
8
2
495
23
1
11-19
129
62
60
45
59
27
180
11
*
183
7
1
185
6
*
20+
70
28
28
25
31
14
88
9
1
95
1
2
91
6
1
DK
40
24
15
14
26
9
57
5
2
55
6
3
60
2
2
Page
10-76
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or
Caught by Someone They Knew
Population Group
Overall
Sex
*
Male
Female
Age (years)
*
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
*
White
Black
Asian
Some Others
Hispanic
Hispanic
*
No
Yes
DK
Employment
*
Full Time
Part Time
Not Employed
Refused
Education
*
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or
Caught by Someone They Knew (continued)
Population Group
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No
Yes
DK
* = Missing data.
DK = Don't know.
N = Sample size.
Refused = Respondent refused to
Source: U.S. EPA, 1996.
TotalA^
1,848
932
780
691
745
564
2,563
207
10
2,698
68
14
2,648
121
11
answer.
Mostly
* Purchased
2 1,724
1 860
* 741
* 655
2 674
1 514
2 2,384
1 190
* 10
3 2,507
* 63
* 14
3 2,457
* 116
* 11
Mostly Caught
100
54
35
27
54
38
142
12
*
151
3
*
149
5
*
DK
22
17
4
9
15
11
35
4
*
37
2
*
39
*
*
Meals
1
2
3
4
5
6
7
>7
Total
N
Source
Table 10-21. Distribution of Fish Meals
N
288
204
118
34
16
13
7
6
686
= Number of respondents.
Stern etal., 1996.
Reported by
% of Total
41.9
29.7
17.2
5.0
2.3
1.9
1.0
0.9
99.9
NJ Consumers During the
Recall Period
Cumulative %
41.9
71.7
88.9
93.9
96.2
98.1
99.1
100.0
~
Page
10-78
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-22. Selected Species Among All Reported Meals by NJ Consumers During
the Recall Period
a
b
N
Species
Tuna3
Shrimp
Founder/fluke
Shellfish/clams, etc.b
Finfish (unidentified)
Salmon
Swordfish
Shark
Total
Includes fresh and canned tuna,
Includes soups and stews.
= Number of meals.
% of total reported meals (N= 1,447)
19.2
13.5
11.9
8.2
7.5
5.3
1.5
0.3
67.4
as fillets, sandwiches, and salads.
Source: Stern etal., 1996.
Table 10-23. Cumulative
Percentile
Arithmetic mean
Geometric mean
Percentiles
5th
10th
25th
40th
50th
60th
75th
90th
95th
99th
Probability Distribution of Average
All Adult Fish Consumers
(> 18 years)
50.2
36.6
9.1
12.2
24.3
28.4
32.4
42.6
62.1
107.4
137.7
210.6
Daily Fish Consumption (g/day)
Fish Consuming Women
(18 to 40 years)
41.0
30.8
7.0
10.3
20.3
24.3
28.0
33.4
48.6
88.1
106.8
142.3
Source: Stern etal., 1996.
Table 10-24. Distribution of the Usual Frequency of Fish Consumption"
Usual frequency
>2 times/week
1 to 2 times/week
2 times/month
1 time/month
Few times/year
a Based on survey
N = Sample size.
Source: Stern etal., 1996
All fish
consumers
jV=933
63
365
173
206
126
respondents
% of total Consumers
during recall
period
jV=686
6.8
39.1
18.5
22.0
13.5
and household members.
59
335
136
121
35
% of total
8.6
48.8
19.8
17.6
5.1
Exposure Factors Handbook
September 2011
Page
10-79
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-25. Per Capita Distribution of Fish Intake (g/day) by
for the U.S. Population, as Prepared
Habitat Statistic
Fresh/Estuarine Mean
50th percentile
90th percentile
95th percentile
99th percentile
Marine
All Fish
Note:
Source:
Mean
50th percentile
90th percentile
95th percentile
99th percentile
Mean
50th percentile
90th percentile
95th percentile
99th percentile
Estimate (90%
Finfish
2.6 (2.3-2.8)
0.0 (0.0-0.0)
0.0 (0.0-0.0)
6.7 (5.3-9.3)
67.2 (63.5-75.5)
6.6(6.1-7.0)
0.0 (0.0-0.0)
26.3 (24.3-27.4)
46.1(43.1-47.5)
94.7 (89.8-100.4)
9.1 (8.6-9.7)
0.0 (0.0-0.0)
34.8(31.4-36.6)
59.8 (57.5-61.6)
126.3 (120.6-130.1)
Habitat and Fish Type
Interval)
Shellfish
2.0 (1.8-2.3)
0.0 (0.0-0.0)
0.0 (0.0-0.2)
9.6 (7.9-10.6)
59.3 (51.5-64.0)
1.7(1.3-2.0)
0.0 (0.0-0.0)
0.0 (0.0-0.0)
0.0 (0.0-0.0)
67.9(51.6-84.5)
3.7 (3.2-4.2)
0.0 (0.0-0.0)
0.0 (0.0-0.0)
22.6 (17.2-26.3)
90.6 (82.9-95.7)
Percentile confidence intervals estimated using the bootstrap method with 1,000
replications. Estimates are projected from a sample of 20,607 individuals to the
U.S. population of 261,897,236 using 4-year combined survey weights.
U.S. EPA, 2002.
Page
10-80
Exposure Factors Handbook
September 2011
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OoCfQ
Table 10-26. Daily Average
Habitat
Estuarine
Freshwater
Marine
Notes:
Species
Shrimp
Flounder
Catfish (Estuarine)
Flatfish (Estuarine)
Crab (Estuarine)
Perch (Estuarine)
Oyster
Herring
Croaker
Trout, mixed sp.
Salmon (Estuarine)
Rockfish
Anchovy
Clam (Estuarine)
Mullet
Smelts (Estuarine)
Eel
Scallop (Estuarine)
Smelts, Rainbow
Sturgeon (Estuarine)
Catfish (Freshwater)
Trout
Perch (Freshwater)
Carp
Trout, mixed sp.
Pike
Whitefish (Freshwater)
Crayfish
Snails (Freshwater)
Cisco
Salmon (Freshwater)
Smelts, Rainbow
Sturgeon (Freshwater)
Tuna
Cod
Salmon (Marine)
Clam (Marine)
Pollock
Porgy
Haddock
Crab (Marine)
Whiting
Per Capita Estimates of Fish Consumption: U.S.
Estimated Mean TT , •
, , Habitat
g/ Person/Day
1.63012 Marine (Cont)
0.45769
0.34065
0.27860
0.17971
0.12882
0.11615
0.09409
0.08798
0.08582
0.05059
0.03437
0.02976
0.02692
0.02483
0.00415
0.00255
0.00100
0.00037
0.00013
Unknown
0.34065
0.15832
0.12882 All Species
0.09584
0.08582
0.02958
0.00988
0.00575
0.00198
0.00160
0.00053
0.00037
0.00013
2.62988
1.12504
1.01842
1.00458
0.27685
0.27346
0.25358
0.20404
0.20120
Estimates are projected from a sample of 20,607 individuals to the U.S
Prepared
Species
Lobster
Scallop (Marine)
Squid
Ocean Perch
Sea Bass
Mackerel
Swordfish
Sardine
Pompano
Flatfish (Marine)
Mussels
Octopus
Halibut
Snapper
Whitefish (Marine)
Smelts (Marine)
Shark
Snails (Marine)
Conch
Roe
Fish
Seafood
Tuna
Shrimp
Cod
Salmon (Marine)
Clam (Marine)
Flounder
Catfish (Estuarine)
Catfish (Freshwater)
Flatfish (Estuarine)
Pollock
Porgy
Haddock
Fish
Crab (Marine)
Whiting
Crab (Estuarine)
Trout
Lobster
Scallop (Marine)
Perch (Estuarine)
Population — Mean Consumption by Species Within Habitat, as
Estimated Mean TT , •
m i-n Habitat
g/Person/Day
0.15725 All Species
0.14813 (Cont)
0.12121
0.11135
0.09766
0.08780
0.07790
0.07642
0.07134
0.05216
0.05177
0.04978
0.02649
0.02405
0.00988
0.00415
0.00335
0.00198
0.00155
0.00081
0.23047
0.00203
2.62988
1.63012
1.12504
1.01842
1.00458
0.45769
0.34065
0.34065
0.27860
0.27685
0.27346
0.25358
0.23047
0.20404
0.20120
0.17971
0.15832
0.15725
0.14813
0.12882
population of 261,897,236 using 4-year combined survey weights.
Species
Perch (Freshwater)
Squid
Oyster
Ocean Perch
Sea Bass
Carp
Herring
Croaker
Mackerel
Trout (Estuarine)
Trout (Freshwater)
Swordfish
Sardine
Pompano
Flatfish (Marine)
Mussels
Salmon (Estuarine)
Octopus
Rockfish
Anchovy
Pike
Clam (Estuarine)
Halibut
Mullet
Snapper
Whitefish (Freshwater)
Whitefish (Marine)
Crayfish
Smelts (Estuarine)
Smelts (Marine)
Shark
Eel
Seafood
Snails (Freshwater)
Snails (Marine)
Cisco
Conch
Scallop (Estuarine)
Roe
Salmon (Freshwater)
Smelts, Rainbow (Estuarine)
Smelts, Rainbow
Sturgeon (Estuarine)
Sturgeon (Freshwater)
Source of individual consumption data
Estimated Mean
g/Pers on/Day
0.12882
0.12121
0.11615
0.11135
0.09766
0.09584
0.09409
0.08798
0.08780
0.08582
0.08582
0.07790
0.07642
0.07134
0.05216
0.05177
0.05059
0.04978
0.03437
0.02976
0.02958
0.02692
0.02649
0.02483
0.02405
0.00988
0.00988
0.00575
0.00415
0.00415
0.00335
0.00255
0.00203
0.00198
0.00198
0.00160
0.00155
0.00100
0.00081
0.00053
0.00037
0.00037
0.00013
0.00013
USDA Combined
1994-1996, 1998 CSFII. The fish component of foods containing fish was calculated using data from the recipe file of the USDA's Nutrient Data Base for Individual Food Intake Surveys.
Source:
U.S. EPA, 2002.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-27. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type
for the U.S. Population, Uncooked Fish Weight
Estimate (90% Interval)
Habitat Statistic Finfish Shellfish
Fresh/Estuarine Mean 3.6(3.2^.0) 2.7(2.4-3.1)
SO^percentile 0.0 (0.0-0.0) 0.0 (0.0-0.0)
QO^percentile 0.0(0.00-0.7) 0.0(0.0-0.0)
QS^percentile 14.1(10.0-16.8) 12.8(10.5-13.8)
Qg^percentile 95.3(80.7-100.8) 77.0(69.7-84.1)
Marine Mean 9.0(8.4-9.6) 1.6(1.2-2.0)
SO^percentile 0.0(0.0-0.0) 0.0(0.0-0.0)
gO^percentile 37.5(35.7-37.6) 0.0(0.0-0.0)
gS^percentile 62.9(61.3-65.5) 0.0(0.0-0.0)
gg^percentile 128.4(119.3-135.8) 54.8(33.1-80.6)
All Fish Mean 12.6(11.9-13.3) 4.3(3.7-4.9)
SO^percentile 0.0(0.0-0.0) 0.0(0.0-0.0)
gO^percentile 48.7(45.3-50.4) 0.0(0.0-0.0)
gS^percentile 81.8(79.5-85.0) 23.2(18.3-28.3)
gg^percentile 173.6(168.0-183.4) 110.5(93.1-112.9)
Note:
Source:
Percentile confidence intervals estimated using the bootstrap method with 1,000
replications. Estimates are projected from a sample of 20,607 individuals to the
U.S. population of 261,897,236 using 4-year combined survey weights.
U.S. EPA, 2002.
Page
10-82
Exposure Factors Handbook
September 2011
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II
fi
._
I
Table
Habitat
10-28. Daily Average Per Capita Estimates
Species
Estuarine Shrimp
Flounder
Catfish (Estuarine)
Flatfish (Estuarine)
Crab (Estuarine)
Perch (Estuarine)
Oyster
Croaker
Herring
Trout, mixed sp.
Salmon (Estuarine)
Rockfish
Anchovy
Mullet
Clam (Estuarine)
Smelts (Estuarine)
Eel
Scallop (Estuarine)
Smelts, Rainbow
Sturgeon (Estuarine)
Freshwater Catfish (Freshwater)
Trout
Perch (Freshwater)
Carp
Trout, mixed sp.
Pike
Whitefish (Freshwater)
Crayfish
Snails (Freshwater)
Cisco
Salmon (Freshwater)
Smelts, Rainbow
Sturgeon (Freshwater)
Marine Tuna
Cod
Salmon (Marine)
Clam (Marine)
Porgy
Pollock
Haddock
Crab (Marine)
Whiting
Notes:
Source:
Estimated Mean
g/Pers on/Day
2.20926
0.58273
0.48928
0.33365
0.25382
0.18148
0.13963
0.13730
0.13298
0.11908
0.06898
0.04448
0.04334
0.03617
0.01799
0.00611
0.00324
0.00128
0.00052
0.00013
0.48928
0.19917
0.18148
0.13406
0.11908
0.03260
0.00995
0.00746
0.00249
0.00234
0.00073
0.00052
0.00013
3.61778
1.47734
1.38873
0.67135
0.40148
0.32878
0.32461
0.28818
0.25725
of Fish Consumption U.S. Population — Mean Consumption
Habitat Species
Marine (Cont.) Lobster
Scallop (Marine)
Squid
Ocean Perch
Sea Bass
Mackerel
Sardine
Swordfish
Pompano
Mussels
Octopus
Flatfish (Marine)
Halibut
Snapper
Whitefish (Marine)
Smelts (Marine)
Shark
Snails (Marine)
Conch
Roe
Unknown
Fish
Seafood
All Species
Tuna
Shrimp
Cod
Salmon (Marine)
Clam (Marine)
Flounder
Catfish (Estuarine)
Catfish (Freshwater)
Porgy
Flatfish (Estuarine)
Pollock
Haddock
Fish
Crab (Marine)
Whiting
Crab (Estuarine)
Trout
Lobster
Scallop (Marine)
Perch (Estuarine)
Estimated Mean
g/Person/Day
0.21290
0.18951
0.15438
0.14074
0.12907
0.11468
0.10565
0.10193
0.09905
0.07432
0.06430
0.06247
0.03226
0.02739
0.00995
0.00611
0.00424
0.00249
0.00207
0.00102
0.60608
0.00326
3.61778
2.20926
1.47734
1.38873
0.67135
0.60608
0.58273
0.48928
0.48928
0.40148
0.33365
0.32878
0.32461
0.28818
0.25725
0.25382
0.21290
0.19917
0.18951
0.18148
by Species Within Habitat, Uncooked Fish Weight
TT , .. . _ . Estimated Mean
Habitat Species _, _
r g/Pers on/Day
All Perch (Freshwater) 0.18148
Species Squid 0.15438
(Cont.) Ocean Perch 0.14074
Oyster 0.13963
Croaker 0.13730
Carp 0.13406
Herring 0.13298
Sea Bass 0.12907
Trout (Estuarine) 0. 11908
Trout (Freshwater) 0. 11908
Mackerel 0.11468
Sardine 0.10565
Swordfish 0.10193
Pompano 0.09905
Mussels 0.07432
Salmon (Estuarine) 0.06898
Octopus 0.06430
Flatfish (Marine) 0.06247
Rockfish 0.04448
Anchovy 0.04334
Mullet 0.03617
Pike 0.03260
Halibut 0.03226
Snapper 0.02739
Clam (Estuarine) 0.01799
Whitefish (Freshwater) 0.00995
Whitefish (Marine) 0.00995
Crayfish 0.00746
Smelts (Estuarine) 0.00611
Smelts (Marine) 0.00611
Shark 0.00424
Seafood 0.00326
Eel 0.00324
Snails (Freshwater) 0.00249
Snails (Marine) 0.00249
Cisco 0.00234
Conch 0.00207
Scallop (Estuarine) 0.00128
Roe 0.00102
Salmon (Freshwater) 0.00073
Smelts, Rainbow (Estuarine) 0.00052
Smelts, Rainbow 0.00052
Sturgeon (Estuarine) 0.00013
Sturgeon (Freshwater) 0.00013
Estimates are projected from a sample of 20,607 individuals to the U.S. population of 261,897,236 using 4-year combined survey weights. Source of individual consumption data: USDA Combined
1994-1996, 1998 CSFII. Amount of consumed fish recorded by survey respondents was converted to uncooked fish quantities using data from the recipe file of USDA's Nutrient Data Base for
Individual Food Intake Survey. Fish component of foods containing fish was calculated using data from the recipe file of the USDA's Nutrient Data Base for Individual Food Intake Surveys.
U.S. EPA, 2002.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepared3
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182
2,332
2,654
10,168
5,277
2,382
2,780
10,439
4,391
1,670
1,005
363
9,596
10,459
4,714
5,434
20,607
1.6(1.2-1.9)
4.3 (3.4-5.1)
4.8 (4.0-5.6)
3.9 (3.3-4.4)
2.1 (1.6-2.6)
5.7 (4.8-6.6)
7.4 (6.3-8.5)
5.3 (4.7-6.0)
1.5(1.2-1.8)
2.1 (1.4-2.9)
3.0 (2.2-3.8)
3.4(1.6-5.3)
5.5 (4.9-6.0)
1.8(1.5-2.1)
5.0 (4.4-5.6)
6.0 (5.2-6.7)
4.6 (4.2-5.0)
0.0 (0.0-0.5)
5.1 (2.8-7.9)
11.8 (5.7-16.8)
4.9 (2.6-6.3)
0.0 (0.0-0.6)
10.4 (9.2-12.4)
23.6(19.7-28.1)
9.3 (7.1-10.9)
0.1 (0.00-1.0)
0.0 (0.0-0.6)
1.4 (0.5-5.5)
0.0 (0.0-1.5)
11.7 (9.9-14.7)
0.0 (0.0-0.0)
8.6 (5.3-10.4)
17.4(13.9-22.1)
6.6 (5.3-8.5)
5.8 (4.4-10.2)
23.9 (21.8-28.6)
32.7(26.7-40.1)
23.8(22.1-27.5)
6.6 (4.4-10.4)
38.6 (33.7-49.0)
56.6 (52.3-57.2)
37.1 (32.1-40.3)
5.1 (4.1-6.2)
5.9 (3.2-12.7)
18.2(14.8-21.1)
3 1.1* (5.2-29.2)
38.0 (34.7-43.0)
6.0 (5.5-9.5)
31.7(28.6-36.8)
42.7(37.1-52.8)
29.7(28.1-31.6)
40.0 (33.7-52.0)
82.9 (75.2-111.2)
79.4 (74.2-87.0)
77.1(74.3-85.2)
60.8 (42.7-74.2)
112.7(91.5-125.1)
112.3 (107.5-130.1)
107.1(97.1-125.1)
38.7 (32.9-43.6)
60.9* (51.0-86.0)
69.5* (56.0-75.1)
81.2* (42.0-117.0)
105.1 (91.5-113.5)
51.7(39.4-61.2)
98.9(85.5-125.1)
104.2(91.0-112.0)
91.0(82.6-100.1)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182
2,332
2,654
10,168
5,277
2,382
2,780
10,439
4,391
1,670
1,005
363
9,596
10,459
4,714
5,434
20,607
3.6 (3.0-4.2)
7.0(6.1-7.9)
10.9(9.6-12.1)
7.6 (6.9-8.3)
4.3 (3.6-5.1)
9.4 (8.2-10.6)
11.9(10.5-13.2)
8.9(8.1-9.8)
3.7 (3.2-4.3)
4.2 (3.5-4.9)
5.5 (4.2-6.7)
4.7 (2.9-6.4)
9.8 (9.0-10.6)
4.0 (3.5-4.5)
8.2(7.4-9.1)
11.3(10.3-12.3)
8.3 (7.6-8.9)
10.8(8.1-13.5)
27.9 (24.3-28.2)
42.0 (38.4-42.5)
28.1(27.9-29.2)
11.8 (8.4-14.0)
36.6(28.0-43.1)
47.1(42.2-54.5)
34.2 (28.2-38.5)
11.1 (10.4-12.6)
13.1 (9.7-17.0)
13.9 (9.8-20.6)
0.0 (0.0-6.9)
38.6 (36.6-41.5)
10.8(10.1-13.5)
28.2 (27.9-34.3)
42.7 (42.0-45.7)
29.2(28.2-32.1)
28.1(24.3-31.0)
48.1 (42.6-53.7)
63.3 (57.8-66.3)
49.6 (46.6-52.4)
29.1(26.7-31.4)
72.8 (58.8-82.8)
71.4 (64.4-81.3)
63.3 (59.0-73.2)
27.9(24.4-29.1)
28.7 (27.6-33.8)
38.5 (30.8-50.3)
24.2* (7.8-71.5)
63.8 (58.8-68.8)
28.2 (27.9-29.8)
56.6 (54.5-68.9)
65.1 (63.9-68.0)
55.8 (54.7-56.9)
61.3 (51.2-70.5)
97.0 (86.6-137.6)
128.5 (120.5-138.3)
106.6(95.2-119.2)
84.4 (77.0-113.3)
127.4(116.3-153.6)
140.1 (114.9-149.6)
122.8 (109.4-139.6)
59.8 (52.4-71.3)
78.6* (49.2-84.4)
102.3* (84.4-113.6)
107.8* (68.4-118.9)
126.3 (117.3-140.1)
79.0 (63.0-98.8)
115.7(98.5-143.8)
136.9 (125.6-140.3)
114.6 (108.9-120.8)
Page
10-84
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepared" (continued)
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182 5.2 (4.4-5.9)
2,332 11.3 (10.0-12.7)
2,654 15.6 (14.0-17.3)
10,168 11.4(10.5-12.4)
5,277 6.4 (5.5-7.3)
2,382 15.1(13.6-16.6)
2,780 19.2 (17.6-20.9)
10,439 14.3 (13.4-15.2)
4,391 5.2 (4.6-5.8)
1,670 6.3 (5.3-7.3)
1,005 8.5 (6.9-10.0)
363 8.1 (5.4-10.8)
9,596 15.3 (14.3-16.2)
10,459 5.8 (5.2-6.5)
4,714 13.2(12.2-14.2)
5,434 17.3 (16.0-18.6)
20,607 12.8(12.1-13.6)
18.9(15.3-21.1)
41.2 (36.6-46.2)
56.2 (52.7-60.6)
42.2 (39.0-45.7)
21.1(15.7-24.9)
58.4(51.0-70.3)
67.7 (65.0-72.2)
55.9(51.0-59.4)
18.9(15.3-21.3)
23.9(21.1-27.0)
28.1(24.9-31.4)
18.6 (7.0-40.9)
56.2 (55.4-58.3)
19.4 (17.2-21.2)
50.0 (45.3-56.2)
61.1(56.6-64.2)
48.2 (46.2-49.9)
37.5 (30.0-41.7)
66.3 (61.0-73.0)
82.9 (75.6-88.0)
66.8 (63.2-71.4)
42.2 (34.0-52.5)
89.1 (85.6-97.5)
98.6(92.7-105.1)
86.1 (84.3-89.7)
35.3(31.1-39.5)
39.6(34.3-51.5)
60.3 (53.4-74.2)
73.8* (29.2-89.8)
86.1 (84.3-87.5)
38.2(36.6-42.1)
82.9(76.2-86.1)
90.5 (86.5-93.2)
79.0 (74.6-83.3)
80.2 (72.6-83.0)
143.4 (128.0-148.4)
158.9 (141.6-170.6)
140.8 (128.5-148.4)
114.3 (98.4-130.6)
177.2 (163.0-185.3)
167.5 (157.0-193.3)
162.6 (155.8-178.7)
72.2 (66.7-81.4)
107.8* (91.6-130.6)
122.2* (106.8-131.9)
142.3* (107.9-200.4)
162.6 (155.8-171.0)
96.5 (83.0-114.3)
162.6 (147.2-176.2)
162.7 (158.4-170.6)
153.2 (145.9-160.9)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights.
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval (BI); percentile intervals were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the "Third Report on
Nutrition Monitoring in the United States" (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-85
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared"
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,127
4,112
1,553
975
360
9,432
9,873
4,644
5,333
19,850
56 (46-66)
67 (53-81)
72 (58-85)
66 (58-75)
65 (52-78)
72 (60-83)
88 (75-101)
75 (67-84)
82.9(67-99)
59.3 (39-79)
53.3 (42-64)
49.5(23-76)
74 (67-82)
61 (52-70)
69 (61-78)
79 (69-90)
71 (65-77)
0.0 (0.0-3.4)
75 (40-107)
184 (75-247)
80 (44-104)
0.0 (0.0-17)
131(101-170)
272 (212-321)
131(107-181)
0.0 (0.0-56)
0.0 (0.0-5.3)
0.0 (0.0-78)
0.0 (0.0-33)
158 (125-198)
0.0 (0.0-0.0)
104 (72-139)
236 (188-284)
106 (87-128)
208 (162-268)
380 (306-435)
491 (369.3-606.2)
398 (364-435)
279 (179-384)
481 (425-574)
666 (540-712)
504 (455-560)
284 (240-353)
178 (88-402)
312(253-390)
213* (106-390)
502 (452-567)
230 (187-283)
431(390-476)
557 (493.7-666)
451 (424-484)
,516(1,305-1,801)
,329 (1,238-2,021)
,339(1,133-1,462)
,352 (1,222-1,528)
,767 (1,470-1,888)
,350 (1,228-1,729)
,378 (1,260-1,508)
,470 (1,378-1,568)
2,317(1,736-2,463)
1,662* (1,433-2,335)
1,237* (950-1,521)
1,186* (600-2,096)
1,353 (1,238-1,511)
1,689 (1,470-1,805)
1,335 (1,238-1,684)
1,351 (1,260-1,462)
1,432(1,325-1,521)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,127
4,112
1,553
975
360
9,432
9,873
4,644
5,333
19,850
147 (125-168)
114 (98-129)
166 (147-185)
139 (127-150)
154 (132-176)
118(104-132)
149 (133-166)
136 (125-147)
209 (181-237)
150 (123-177)
109 (84-133)
75 (46-103)
137 (126-147)
150 (134-167)
116 (104-128)
158 (144-173)
137 (128-147)
381 (324-506)
423 (365-485)
620 (567-658)
501 (465-534)
426 (357-494)
444 (368-547)
568 (504-673)
494 (445-543)
614 (525-696)
416 (326-546)
338 (179-413)
0.0 (0.0-124)
527 (501-575)
413 (366-476)
440 (389-488)
601 (562-642)
497(480-517)
1,028(908-1,149)
768 (650-881)
950 (900-1,042)
892 (847-923)
1,081 (975-1,293)
880 (760-954)
889(831-990)
908 (868-954)
1,537 (1,340-1,670)
1,055 (969-1,275)
821 (629-1,034)
381* (132-951)
881 (840-945)
1,037(1,002-1,163)
830 (750-920)
921 (882-977)
903 (869-938)
2,819 (2,481-2,908)
1,648 (1,428-2,177)
2,022 (1,899-2,683)
2,151 (1,858-2,484)
2,678 (2,383-3,073)
1,643 (1,454-1,819)
1,859 (1,725-2,011)
1,965 (1,817-2,247)
3,447 (3,274-3,716)
2,800* (2,021-3,298)
1,902* (1,537-2,366)
1,785* (1,226-2,342)
1,798 (1,708-1,971)
2,692 (2,481-2,823)
1,651.83 (1,487-1,793)
1,975.67 (1,785-2,118)
2,014.52 (1,947-2,158)
Page
10-86
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared"
(continued)
Age (years)
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,12
7
4,112
1,553
975
360
18 and older 9,432
14 and under
15 to 44
45 and older
All ages
9,873
4,644
5,333
19,85
0
203 (178-227)
181 (158-204)
238 (212-263)
205 (188-221)
219 (252-356)
190 (219-263)
237 (225-277)
211 (240-279)
292 (260-326)
209 (176-242)
162 (133-191)
124 (83-165)
211 (197-225)
211 (191-231)
185 (170-200)
238 (219-256)
208 (196-220)
693 (929-1,408)
641 (641-879)
812 (797-956)
731 (797-912)
745 (583-881)
756 (689-851)
849 (812-920)
792 (727-884)
1,057(931-1,232)
780 (644-842)
570 (476-664)
261 (110-600)
779 (743-816)
713 (652-780)
714 (645-803)
836 (767-883)
762 (737-790)
1,344 (1,224-1,489)
1,040 (910-1,226)
,265 (1,165-1,353)
,211 (1,128-1,256)
,470 (1,282-1,775)
,165 (1,060-1,239)
,253 (1,183-1,282)
,239 (1,201-1,282)
1,988 (1,813-2,147)
1,357(1,173-1,451)
1,051 (991-1,313)
1,029* (390-1,239)
1,198(1,165-1,238)
1,429 (1,344-1,499)
1,139(1,014-1,228)
1,261(1,185-1,314)
1,227(1,198-1,251)
3,297 (2,823-3,680)
2,292 (2,096-2,494)
2,696 (2,247-2,974)
2,651 (2,358-2,823)
3,392 (2,893-3,954)
2,238 (2,045-2,492)
2,310(2,079-2,438)
2,537 (2,324-2,679)
4,089 (3,733-4,508)
3,350* (2,725-4,408)
2,305* (1,908-2,767)
2,359* (2,096-2,676)
2,327 (2,198-2,438)
3,354 (3,224-3,458)
2,290 (2,082-2,476)
2,386 (2,158-2,672)
2,539 (2,476-2,679)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights.
TV = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on
Nutrition Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-87
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish Weight3
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182
2,332
2,654
10,168
5,277
2,382
2,780
10,439
4,391
1,670
1,005
363
9,596
10,459
4,714
5,434
20,607
2.3 (1.8-2.8)
5.8 (4.6-6.9)
6.4 (5.3-7.4)
5.2 (4.5-5.9)
3.0 (2.3-3.7)
7.9(6.7-9.1)
10.2 (8.6-11.7)
7.4 (6.6-8.3)
2.2 (1.8-2.6)
3.0(1.9-4.1)
4.3 (3.2-5.4)
4.6 (2.2-6.9)
7.5 (6.8-8.3)
2.6(2.2-3.1)
6.8 (6.0-7.6)
8.1 (7.1-9.2)
6.3 (5.7-6.9)
0.0 (0.0-0.2)
6.3 (4.7-11.4)
17.7 (8.9-23.6)
7.3 (3.8-11.9)
0.0 (0.0-0.2)
15.6(13.2-19.8)
32.5 (27.3-37.2)
14.6 (12.6-17.7)
0.1 (0.0-1.5)
0.0 (0.0-0.5)
2.3 (0.1-7.7)
0.0 (0.0-1.9)
17.4(14.3-21.6)
0.0 (0.0-0.0)
13.0 (8.6-15.6)
24.8 (18.8-28.6)
11.7 (8.4-13.7)
13.1 (9.9-16.4)
32.4 (27.7-38.0)
44.9 (37.4-55.4)
31.9(28.3-37.4)
13.5 (10.2-17.0)
49.7 (45.7-66.4)
73.5(66.2-77.1)
49.3 (45.6-53.2)
12.2(10.3-14.1)
13.1 (4.8-20.1)
25.8 (21.0-28.9)
19.3* (13.3-36.8)
49.6 (46.9-55.4)
13.1 (11.9-14.8)
43.6 (37.8-17.4)
56.5 (48.9-69.7)
41.1(37.9-13.7)
58.8 (45.8-86.4)
109.8 (100.4-154.5)
108.8 (95.4-123.9)
102.1(95.5-114.0)
79.0 (55.2-97.9)
151.2(126.4-183.4)
165.9 (147.7-190.7)
147.8 (132.3-183.4)
52.5 (45.6-61.5)
78.5* (63.8-110.5)
94.8* (83. 1-109.5)
109.2* (57.7-154.5)
143.4 (125.3-156.8)
73.7(51.5-86.4)
135.9 (121.0-167.0)
144.3 (121.7-156.8)
123.9(114.0-138.8)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182
2,332
2,654
10,168
5,277
2,382
2,780
10,439
4,391
1,670
1,005
363
9,596
10,459
4,714
5,434
20,607
5.2 (4.5-6.0)
9.0(7.8-10.1)
13.7(12.0-15.4)
9.8 (8.9-10.6)
6.0 (4.9-7.0)
12.0(10.5-13.5)
15.0(13.3-16.7)
11.5(10.4-12.5)
5.5 (4.8-6.2)
5.6 (4.6-6.5)
7.6 (5.9-9.4)
6.1 (3.7-8.4)
12.4(11.5-13.4)
5.59 (4.9-6.3)
10.5 (9.4-11.6)
14.3 (13.0-15.6)
10.6 (9.8-11.4)
18.8(13.5-21.9)
37.5(31.0-37.9)
51.4(49.0-55.4)
37.8 (37.3-10.2)
17.0(13.0-21.4)
41.7 (37.8-56.3)
58.0(53.5-68.3)
41.3 (37.8-19.7)
19.8(16.6-23.1)
18.9 (14.2-24.3)
25.3 (16.4-34.5)
0.0 (0.0-9.3)
48.9(47.1-51.2)
18.7(16.1-19.7)
37.9(37.5-11.3)
55.7(53.1-57.9)
38.4 (37.8-10.6)
40.1(37.9-17.7)
61.7(55.8-71.2)
80.4 (76.9-82.6)
64.7 (59.2-67.7)
39.7(35.9-11.1)
90.2 (75.7-106.7)
90.7 (85.4-97.3)
82.9 (75.7-96.8)
39.4 (37.7-11.4)
38.4(37.9-11.6)
56.5(45.3-67.1)
29.5* (11.6-90.7)
80.7 (77.8-83.5)
40.2 (39.6-10.4)
75.3 (67.3-83.5)
83.4 (80.7-85.8)
74.9 (69.9-75.6)
81.3 (67.0-98.4)
120.6(116.5-132.5)
155.6 (148.7-179.2)
128.5(119.4-142.9)
113.3 (106.3-140.3)
151.5 (134.9-192.5)
168.8(157.1-186.9)
152.3 (136.6-166.9)
82.3 (73.0-95.4)
99.8* (62.8-111.4)
131.8* (110.3-148.7)
135.6* (92.0-177.1)
150.8 (139.7-164.3)
103.4 (82.6-123.5)
137.1 (122.0-151.0)
166.0 (155.5-178.0)
139.2(131.3-148.3)
Page
10-88
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish Weight"
(continued)
Age (years)
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
5,182 7.5 (6.5-8.5)
2,332 14.7(13.0-16.5)
2,654 20.1 (17.9-22.2)
10,168 15.0(13.7-16.2)
5,277 9.0 (7.6-10.3)
2,382 19.9 (18.0-21.7)
2,780 25.2 (23.0-27.3)
10,439 18.9(17.7-20.1)
4,391 7.7 (6.9-8.6)
1,670 8.5(7.1-10.0)
1,005 12.0 (9.7-14.2)
363 10.6 (7.0-14.2)
9,596 19.9(18.7-21.1)
10,459 8.2 (7.3-9.2)
4,714 17.3 (15.9-18.7)
5,434 22.4(20.7-24.1)
20,607 16.9 (15.9-17.9)
28.5 (25.4-34.0)
53.6 (46.6-58.8)
73.4 (67.7-77.3)
56.2(51.0-59.2)
31.5(24.6-37.5)
77.0 (65.8-88.8)
89.7 (86.5-94.2)
73.5 (66.6-80.5)
32.6 (27.6-34.0)
32.6 (27.0-37.9)
43.4 (36.7-50.8)
29.3 (9.4-48.7)
74.8 (71.7-75.7)
29.0 (27.6-32.6)
64.6 (57.0-73.5)
80.6 (75.0-85.3)
63.5 (59.5-66.2)
55.2 (49.0-59.2)
85.2 (77.3-94.6)
104.0(96.7-112.1)
86.3 (81.2-93.2)
56.5 (49.0-69.9)
118.6(110.7-127.1)
130.7(125.8-135.5)
113.4(110.7-118.6)
51.0(46.3-56.7)
56.4 (49.6-69.8)
87.4 (69.6-102.6)
83.5* (42.3-114.5)
111.4(110.0-114.0)
56.3 (52.2-56.7)
107.7 (99.2-113.6)
115.3 (111.7-122.2)
102.3 (97.9-107.6)
103.9(95.1-126.2)
189.9(165.1-197.1)
213.7(190.1-221.6)
185.7 (162.6-187.2)
165.2(141.6-177.4)
242.7 (224.3-254.9)
226.5 (207.3-278.3)
219.3 (204.8-236.5)
100.5(89.1-111.4)
144.4* (117.4-183.4)
170.7* (147.9-176.8)
192.5* (120.5-266.0)
215.7(197.1-228.5)
127.2(118.2-149.5)
211.3 (197.1-242.3)
215.7 (208.3-227.6)
198.2 (190.7-208.8)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights.
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on
Nutrition Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-89
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-32. Per Capita Distribution of Fish (fmfish and shellfish) Intake (mg/kg-day), Uncooked Fish Weight3
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,127
4,112
1,553
975
360
9,432
9,873
4,644
5,333
19,850
83 (69-96)
91 (71-110)
96 (78-113)
91 (79-103)
95 (76-113)
99 (84-115)
121 (102-140)
106 (94-117)
124 (102-146)
84 (55-112)
77 (60-94)
65 (30-100)
102 (92-112)
89 (76-101)
95 (83-107)
108 (94-122)
98 (90-107)
0.0 (0.0-1.6)
107 (57-145)
250 (123-322)
117(63-165)
0.0 (0.0-1.7)
201 (151-254)
378(317-429)
208 (165-272)
0.0 (0.0-83)
0.0 (0.0-1.4)
20(0.0-116)
0.0 (0.0-23)
236 (183-277)
0.0 (0.0-0.0)
150(115-195)
322 (250-379)
159(131-198)
443 (269-572)
482 (403-538)
655 (485-776)
535 (485-613)
534 (371-605)
623 (558-810)
891 (754-974)
697 (629-782)
712 (599-784)
354 (116-685)
477 (411-618)
285* (167-491)
669 (597-749)
485 (411-557)
558 (506-623)
751 (653.97-870)
631(590-675)
2,179 (1,866-2,345)
1,818 (1,633-2,767)
1,822(1,515-1,909)
1,871 (1,629-2,025)
2,351 (1,920-2,501)
1,910 (1,760-2,221)
1,963(1,731-2,132)
2,034 (1,856-2,221)
3,091 (2,495-3,475)
2,322* (1,856-2,994)
1,610* (1,358-2,203)
1,542* (760-2,767)
1,886 (1,700-2,049)
2,246 (1,987-2,495)
1,893 (1,683-2,221)
1,868 (1,709-1,941)
1,943 (1,816-2,086)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,127
4,112
1,553
975
360
9,432
9,873
4,644
5,333
19,850
212 (183-242)
146 (126-166)
209 (185-233)
181 (167-196)
214 (183-244)
150 (132-168)
187 (167-208)
175 (161-189)
309 (270-348)
198 (161-235)
153 (117-189)
98 (58-137)
173 (160-186)
213 (190-237)
148 (132-163)
199(181-217)
178 (167-190)
592 (508-785)
557 (463-632)
802 (757-844)
657 (601-718)
609 (480-808)
576 (461-675)
713 (658-851)
649 (575-711)
1,108 (984-1,332)
600 (474-733)
481 (361-609)
0.0 (0.0-177)
672(651-732)
606(517-688)
568 (502-630)
767 (718-828)
651 (620-675)
1,532(1,418-1,703)
995 (874-1,078)
1,184(1,132-1,281)
1,158(1,094-1,216)
1,542 (1,380-1,887)
1,113 (963-1,226)
1,138(1,103-1,213)
1,205 (1,127-1,233)
2,314(2,097-2,481)
1,481(1,310-1,549)
1,251 (808-1,390)
460* (197-1,079)
1,115 (1,078-1,182)
1,543 (1,491-1,670)
1,052(973-1,184)
1,156(1,115-1,214)
1,178(1,134-1,226)
3,708 (3,276-4,295)
2,056 (1,848-2,330)
2,464 (2,282-2,820)
2,716(2,382-3,051)
3,603(3,212-4,131)
1,990(1,782-2,317)
2,275 (1,993-2,495)
2,545(2,314-2,705)
4,608 (4,301-5,354)
3,684* (2,458-4,353)
2,381* (2,162-3,207)
2,148* (1,648-3,901)
2,157 (2,024-2,412)
3,694(3,318-4,065)
2,023 (1,925-2,197)
2,389 (2,273-2,546)
2,587 (2,454-2,705)
Page
10-90
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
Weight" (continued)
Age (years)
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
4,879
2,275
2,569
9,723
4,994
2,369
2,764
10,127
4,112
1,553
975
360
9,432
9,873
4,644
5,333
19,850
295 (261-330)
237 (206-267)
305 (272-338)
272(251-294)
308 (273-344)
249 (226-272)
309 (282-335)
281 (264-297)
433 (385-482)
282 (235-328)
231(186-275)
163 (107-219)
275 (258-292)
302 (274-330)
243 (223-262)
307(283-331)
276 (261-292)
1,046 (885-1,262)
834.58 (771-981)
1,065.15(98-1,200)
970.64 (906-1,040)
1,122(774-1,310)
982(908-1,154)
1,128 (1,078-1,206)
1,058 (962-1,201)
1,842 (1,555-1,957)
1,045 (744.58-1,219)
824 (657-952)
406 (145-756)
1,017 (975-1,065)
1,072 (961-1,162)
938 (878-1,019)
1,112(1,002-1,168)
1,013 (976-1,052)
2,03,8 (1,853-2,251)
1,362(1,181-1,556)
1,568 (1,472-1,671)
1,566(1,511-1,633)
2,136 (1,856-2,371)
1,533 (1,407-1,619)
1,605(1,534-1,731)
1,644(1,559-1,731)
2,964(2,790-3,194)
1,854(1,638-2,175)
1,531(1,362-1,850)
1,272* (558-1,500)
1,549(1,481-1,591)
2,089 (1,987-2,207)
1,451 (1,342-1,602)
1,591 (1,517-1,685)
1,613 (1,561-1,651)
4,548 (4,117-4,977)
3,113 (2,767-3,361)
3,071 (2,716-3,941)
3,566 (3,270-3,782)
4,518(4,055-5,465)
3,011 (2,820-3,349)
2,821 (2,587-3,204)
3,369 (3,204-3,680)
5,604(5,231-6,135)
4,371* (3,433-5,814)
3,651* (2,745-3,795)
3,544* (2,767-3,946)
3,060 (2,771-3,204)
4,539(4,391-5,108)
3,094 (2,788-3,349)
3,014 (2,714-3,226)
3,457 (3,349-3,680)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights.
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on
Nutrition Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-91
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepared"
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
445
325
449
1,219
442
361
553
1,356
442
147
107
28
1,633
887
686
1,002
2,575
32.7 (26.8-36.6)
55.4 (45.9-64.8)
49.0 (44.3-53.6)
49.4 (44.5-54.3)
41.7 (34.9-48.4)
66.6 (59.7-73.6)
65.8 (59.0-72.6)
62.9 (57.8-67.9)
27.1(23.2-31.1)
43.5(31.8-55.2)
49.0 (39.4-58.5)
75.8* (58.9-92.7)
59.2 (54.9-63.4)
36.8(32.5-41.1)
61.3 (56.4-66.2)
57.3 (51.9-62.7)
56.3 (52.5-60.0)
79.9(77.1-103.9)
125.9(117.0-157.8)
122.8(118.7-128.0)
122.7(117.0-126.6)
121.5 (85.3-148.4)
165.0 (158.8-171.0)
154.3 (148.1-174.0)
158.2(148.4-165.8)
72.6 (65.0-79.0)
121.6* (82.5-187.3)
126.6* (103.9-148.4)
158.5* (151. 1-171.0)
150.2 (141.8-154.2)
103.1(75.5-120.7)
157.8 (150.3-163.5)
141.1 (127.6-151.0)
145.3 (138.6-151.3)
111.0(103.0-163.5)
189.4 (154.2-259.9)
158.3 (151.3-165.8)
163.2(151.5-193.8)
161.9 (138.6-229.2)
226.3 (194.2-250.2)
214.4 (200.2-222.3)
215.4 (202.4-226.5)
95.6 (87.2-109.6)
186.7* (114.8-260.2)
149.9* (134.6-192.7)
167.8* (158.8-484.4)
201.0(181.9-216.6)
146.8(114.8-167.4)
217.1(181.8-253.2)
182.5(170.5-200.1)
188.8(178.5-211.9)
185.4(163.5-384.3)
341.4 (260.2-853.4)
284.7 (241.2-308.5)
320.6 (260.2-345.2)
260.8 (260.2-292.5)
336.9 (327.0-402.9)
400.2 (300.8-571.0)
335.9(316.5-437.1)
159.0* (136.1-260.2)
260.4* (172.1-261. 3)
307.1* (192.7-384.3)
371.6* (171.0-484.4)
338.2 (308.5-345.2)
260.0 (250.2-292.5)
342.6(321.1-484.4)
306.9 (261.8-345.5)
332.9(308.5-361.3)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
670
412
588
1,670
677
412
623
1,712
682
217
122
37
1.978
1,347
824
1,211
3,382
48.7 (43.7-53.7)
71.0 (66.2-75.7)
82.3 (75.9-88.6)
72.2 (68.6-75.8)
59.5(51.3-67.7)
99.1 (91.3-106.9)
90.0(84.9-95.1)
88.7 (83.7-93.7)
44.5 (40.6-48.5)
59.4(52.6-66.1)
72.4 (59.9-84.9)
96.9* (65.3-128.5)
85.1(81.3-88.9)
54.1(48.4-59.9)
85.0 (79.5-90.4)
85.8 (81.5-90.2)
80.2 (76.6-83.8)
98.1 (93.3-112.6)
158.5 (128.0-170.8)
153.3 (140.1-166.1)
146.3 (140.3-158.7)
144.6(113.3-168.7)
186.1 (174.7-199.5)
179.8(167.3-200.1)
178.2 (170.0-181.2)
90.6 (84.3-104.8)
128.7(111.6-158.4)
165.3* (157.6-202.8)
218.9* (179.6-237.8)
168.9 (168.9-174.6)
119.1(112.3-144.8)
172.0 (168.8-179.6)
168.4(158.7-181.2)
168.9 (165.6-169.0)
135.9(112.6-162.2)
181.5 (167.4-202.8)
203.5 (181.2-252.5)
181.6 (169.0-201.6)
168.8 (167.0-227.2)
232.5 (214.0-254.4)
224.4(207.2-280.1)
226.1(214.4-232.7)
119.1(102.0-142.8)
159.2* (134.9-219.05)
203.6* (168.8-227.2)
237.5* (179.6-292.5)
214.1(195.9-227.2)
162.3 (141.9-168.7)
213.7 (194.3-229.7)
218.7 (207.3-229.8)
207.6 (197.0-214.4)
196.2 (162.2-238.4)
286.7 (234.6-293.2)
362.3 (275.4-485.4)
286.6 (269.5-293.2)
265.1 (170.0-291.6)
403.8 (321.5-407.2)
306.3 (292.5-380.9)
354.2(315.3-403.6)
227.6* (168.7-292.5)
242.5* (219.0-291.6)
245.6* (213.6-268.6)
365.3* (229.8-428.0)
337.2 (306.4-380.9)
238.2 (219.0-269.4)
343.7 (304.9-404.2)
320.1 (299.2-485.4)
310.2(299.2-383.5)
Page
10-92
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepared"
(continued)
Age (years)
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
836 54.2 (49.3-59.0)
554 82.5 (74.8-90.2)
751 90.5(85.3-95.7)
2,141 81.5(77.3-85.7)
836 69.1 (61.9-76.3)
565 111.9(106.0-117.9)
849 106.5(101.5-111.5)
2,250 102.9 (99.0-106.8)
834 50.2 (46.3-54.0)
270 70.6 (63.8-77.4)
172 79.6 (70.4-88.7)
52 104.1* (75.0-133.1)
2,634 97.56 (93.7-101.4)
1,672 61.7 (56.6-66.8)
1,119 97.2(92.1-102.4)
1,600 98.1(93.6-102.6)
4,391 92.0 (88.5-95.5)
112.5(97.2-136.9)
170.8(151.0-184.7)
170.5 (158.7-181.7)
163.6(151.3-171.0)
157.0(136.1-168.8)
210.6 (195.0-242.5)
210.3 (193.3-229.8)
206.0 (192.7-219.0)
103.1 (94.5-124.9)
154.7(130.0-183.2)
167.1* (154.0-192.7)
200.5* (167.4-242.5)
191.8(184.7-197.9)
138.4(125.1-150.1)
195.1(183.2-206.0)
187.0(184.1-198.0)
184.5 (179.6-195.0)
155.4 (128.5-162.2)
221.7 (197.9-260.2)
219.8 (197.0-242.5)
208.2 (193.8-238.4)
227.5 (168.7-260.2)
296.1(249.7-316.5)
271.1 (241.4-292.5)
262.0(251.3-285.8)
133.9(120.7-151.8)
218.2* (197.9-261.3)
208.8* (205.9-257.0
241.9* (215.7-484.4)
253.2 (243.6-261.8)
168.7 (162.4-232.8)
256.0 (240.2-283.9)
248.5 (238.00-260.2)
249.3 (234.3-259.8)
237.5 (197.9-285.6)
336.5 (294.3-345.2)
326.0 (308.5-612.9)
327.0 (285.6-359.6)
276.0 (269.4-292.5)
427.9 (403.6-465.6)
392.5 (330.6-535.5)
404.1 (380.9-428.4)
260.0* (195.3-293.3)
280.9* (260.2-291.6)
285.2* (263.8-327.0)
451.0* (292.5-484.4)
399.5(359.1-407.2)
271.4 (260.2-291.6)
404.0 (352.4-450.4)
381.4 (300.6-413.0)
379.0 (340.2-413.0)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights;
consumers only are those individuals who consumed fish at least once during the 2-day reporting period.
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on
Nutrition Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-93
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-34. Consumer-Only Distributions of Fish (finfish and
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
shellfish) Intake (mg/kg-day), as Prepared"
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
410
315
432
1,157
419
358
548
1,325
416
132
101
28
1,599
829
673
980
2,482
1,198 (1,029-1,367)
872(7,13-1,032)
736 (658-813)
859 (776-943)
1,299 (1,106-1,492)
841(751-931)
782 (701-862)
882 (814-950)
1,532 (1,320-1,743)
1,296 (1,004-1,588)
869 (724.60-1,013)
1,063* (781-1,346)
805 (748-861)
1,251 (1,135-1,367)
855 (778-933)
759 (694-824)
871 (816-926)
3,167(2,626-3,601)
2,702 (1,777-2,484)
1,943 (1,803-2,128)
2,151 (1,941-2,476)
3,556 (3,068-3,830)
2,182(2,057-2,318)
1,804 (1,696-1,903)
2,148(2,045-2,318)
4,307 (3,472-4,624)
3,453* (2,626^,671)
2,030* (1,628-2, 104)
2,293* (2,096-2,577)
2,025 (1,888-2,072)
3,456(3,136-3,597)
2,136(2,057-2,371)
1,896 (1,739-1,983)
2,152(2,063-2,295)
4,921 (3,601-6,563)
3,153 (2,484-4,067)
2,487 (2,249-2,706)
3,004 (2,602-3,368)
4,495 (3,830-4,982)
2,819 (2,539-3,241)
2,511 (2,175-2,652)
3,021 (2,867-3,241)
5,257 (4,926-5,746)
4,675* (3,459-8,816)
3,162* (2,104-3,601)
2,505* (2,096-6,466)
2,679 (2,539-2,947)
4,681 (4,084-5,247)
3,071 (2,675-3,478)
2,512 (2,262-2,706)
3,019 (2,924-3,101)
9,106(6,875-10,967)
5,738 (4,584-15,930)
3,169 (3,027-7,078)
6,102 (5,475-7,078)
8,714 (6,266-11,276)
4,379(4,057-4,931)
4,812 (4,036-6,987)
5,333 (4,548-6,775)
10,644* (9,083-12,735)
8,3 14* (4,684-9,172)
4,665* (3,597-7,361)
5,067* (2,295-6,466)
4,930 (4,285-5,849)
8,792 (7,361-10,967)
5,795 (4,066-6,096)
4,261 (3,117-6,419)
5,839 (4,926-7,078)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
629
403
568
1,600
643
409
621
1,673
640
203
120
37
1,944
1,272
812
1,189
3,273
1,988(1,827-2,148)
1,147(1,061-1,234)
1,259(1,159-1,360)
1,323 (1,260-1,385)
2,084 (1,842-2,326)
1,242(1,151-1,333)
1,129(1,063-1,195)
1,337 (1,267-1,408)
2,492 (2,275-2,709)
2,120 (1,880-2,361)
1,427(1,203-1,651)
1,534* (1,063-2,004)
1,187(1,137-1,238)
2,037(1,880-2,195)
1,195 (1,127-1,263)
1,198(1,135-1,261)
1,330 (1,278-1,382)
4,378 (3,927-4,962)
2,404 (2,014-2,660)
2,430 (2,258-2,627)
2,680 (2,477-2,977)
4,734 (3,911-5,307)
2,448 (2,349-2,773)
2,294(2,106-2,452)
2,745 (2,513-2,858)
5,303 (4,873-5,930)
4,950 (4,043-5,384)
2,971* (2,858-3,741)
3,602* (2,974^,649)
2,386 (2,265-2,450)
4,646 (4,213-4,892)
2,442 (2,349-2,660)
2,394 (2,205-2,534)
2,710 (2,618-2,870)
5,767(5,041-6,519)
3,151 (2,621-3,325)
3,274 (2,699-4,029)
3,644 (3,381-4,305)
5,490 (4,944-6,628)
2,985 (2,870-3,265)
2,942 (2,809-3,526)
3,636 (3,450-3,922)
6,762 (6,097-7,168)
5,817* (5,333-6,596)
4,278* (3,026-4,766)
4,475* (3,068-4,685)
2,998 (2,907-3,191)
5,664 (5,384-6,093)
3,046 (2,856-3,309)
3,100(2,933-3,500)
3,637 (3,544-3,927)
8,185 (6,907-8,842)
4,774 (4,523-5,510)
5,798 (5,365-9,297)
5,895 (5,750-6,956)
9,004 (7,432-10,962)
4,674 (3,637-5,926)
4,622 (4,094-4,936)
5,908 (5,359-6,366)
11,457* (7,432-14,391)
8,092* (6,146-9,184)
5,214* (4,647-5,646)
4,982* (3,467-5,238)
4,961 (4,523-5,510)
8,611 (7,755-9,184)
4,817 (3,932-5,238)
5,436 (4,655-7,504)
5,910(5,646-6,711)
Page
10-94
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared"
(continued)
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
779 2,183 (2,021-2,344)
541 1,317(1,184-1,451)
725 1,380(1,299-1,460)
2,045 1,469(1,400-1,539)
788 2,355 (2,164-2,545)
561 1,409(1,339-1,478)
842 1,311 (1,250-1,373
2,191 1,518(1,461-1,575)
779 2,828 (2,608-3,049)
250 2,375 (2,199-2,551)
164 1,533 (1,384-1,682)
52 1,578*(1,187-1,969)
2,585 1,349(1,297-1,401)
1,567 2,271 (2,130-2,412)
1,102 1,363 (1,292-1,435)
1,567 1,347(1,288-1,406)
4,236 1,494(1,440-1,548)
4,786(4,422-5,138)
2,636(2,385-3,051)
2,639 (2,406-2,950)
3,008 (2,752-3,169)
5,097 (4,680-5,535)
2,770(2,570-3,241)
2,564(2,501-2,801)
3,043(2,867-3,159)
5,734 (5,268-6,706)
5,135 (4,684-5,816)
3,207* (2,945-3,485)
3,468* (2,676^1,752)
2,641 (2,539-2,773)
4,959 (4,647-5,450)
2,728 (2,570-2,974)
2,619(2,546-2,752)
3,021 (2,941-3,082)
6,218 (5,766-6,738)
3,611(3,225^1,584)
3,560 (3,008-3,967)
4,088 (3,649^1,544)
6,712 (6,146-7,432)
3,490 (3,092-3,725)
3,133 (3,050-3,584)
4,029 (3,779^1,477)
7,422 (6,907-8,393)
6,561* (5,404-8,816)
3,924.64* (3,485^1,764)
4,504.25* (3,709-6,466)
3,493 (3,258-3,628)
6,531 (5,887-6,929)
3,583 (3,275-3,999)
3,265(3,115-3,569)
4,055 (3,816^1,218)
10,395 (8,680-10,967)
5,712 (4,952-5,849)
5,929 (5,452-9,905)
7,074(6,519-8,761)
9,182(8,816-11,276)
5,612 (5,163-5,926)
4,935 (4,548-6,987)
6,736(6,096-7,117)
13,829* (11,349-14,391)
9,179* (8,130-10,485)
5,624* (4,764-6,929)
5,738* (4,752-6,466)
5,708 (5,085-5,926)
10,389 (8,982-10,967)
5,694 (4,987-5,849)
5,807 (5,073-6,987)
6,920 (6,466-7,527)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights; consumers
only are those individuals who consumed fish at least once during the 2-day reporting period..
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 1,000
bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-95
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-35.
Age (years)
Consumer-Only Distributions
N
Mean (90% CI)
of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish
Weight3
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
445
325
449
1,219
442
361
553
1,356
442
147
107
28
1,633
887
686
1,002
2,575
47 (40-54)
75 (62-88)
66 (59-72)
67 (60-74)
60 (50-70)
93 (82.33-103)
91 (81.11-100)
87 (80-95)
40 (35-46)
61 (44-79)
71 (58-83)
100* (80-121)
81 (75-87)
53 (47-59)
84 (77-91)
78 (70-86)
78 (72-83)
117 (104-142)
173 (155-204)
163 (153-168)
163 (154-170)
158(110-196)
236 (226-246)
221 (204-236)
220 (200-232)
95 (86-102)
157* (117-250)
173* (166-196)
203* (197-248)
200 (190-206)
144 (101-173)
205 (197-226)
191 (170-202)
196 (189-202)
172 (150-204)
274(204-331)
204 (192-226)
219 (199-267)
199 (189-296)
305 (272-367)
295 (264-332)
296 (289-333)
129 (120-142)
248* (150-381)
199* (173-296)
242* (206-643)
279 (253-301)
196 (173-220)
295 (253-345)
245 (230-264)
258 (243-289)
243 (220-514)
503 (381-1,144)
394(303-431)
461 (381-508)
381 (381-401)
495 (444-643)
562 (402-764)
490 (444-595)
205* (200-381)
386* (221-401)
392* (296-514)
501* (241-643)
506 (444-508)
381 (367-401)
504 (438-818)
413 (382-505)
468(431-531)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
670
412
588
1,670
677
412
623
1,712
682
217
122
37
1,978
1,347
824
1,211
3,382
71 (65-77)
91 (85-96)
104 (94-113)
93 (88-98)
81 (69-93)
127 (116-137)
113 (107-120)
114 (107-120)
66 (60-71)
78 (67-89)
102 (85-118)
126* (80-171)
108(103-113)
76 (68-85)
109(101-116)
108(102-114)
103 (98-108)
134 (124-155)
188 (163-210)
189 (170-213)
183 (174-192)
198 (162-227)
240 (227-258)
223 (205-252)
227 (223-236)
125(114-150)
150 (129-201)
220* (205-265)
281* (241-354)
217 (213-223)
161 (149-201)
225 (213-233)
206 (195-224)
215 (207-217)
183 (151-205)
241 (227-265)
239 (222-283)
232 (227-250)
231 (225-307)
279 (271-370)
285 (250-324)
277 (270-297)
165 (139-190)
202* (165-3 17)
262* (227-307)
353* (241-390)
270 (251-283)
220 (183-227)
270 (247-279)
272 (250-293)
258 (247-270)
240 (209-379)
376 (347-391)
441 (359-647)
385 (354-397)
353 (244-392)
568 (488-647)
384 (359-480)
483 (390-501)
3 16* (227-390)
350* (223-392)
320* (277-379)
530* (291-650)
464 (391-487)
335 (307-379)
483 (390-634)
407 (374-647)
395 (390-487)
Page
10-96
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish
Weight" (continued)
Age (years)
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
836
554
751
2,141
836
565
849
2,250
834
270
172
52
2,634
1,672
1,119
1,600
4,391
79 (73-85)
108 (97-118)
117(109-124)
107(101-113)
96 (85-107)
148 (139-156)
139 (132-146)
136 (130-142)
74 (69-79)
95 (85-106)
113 (99-127)
136*(97-174)
127 (122-133)
88 (80-95)
128(121-135)
127 (120-134)
121 (116-126)
158(142-198)
221 (197-236)
215 (200-228)
207 (196-227)
225 (195-254)
272 (253-334)
274 (285-304)
266 (248-289)
149 (136-165)
200 (177-235)
227* (205-296)
242* (206-358)
248 (236-264)
191 (173-201)
255 (241-271)
244 (230-258)
241 (233-255)
205 (180-218)
315(246-378)
270 (236-286)
275 (246-300)
336 (286-353)
381(323-431)
348 (320-374)
354(315-379)
184 (172-223)
313* (254-381)
308* (271-348)
357* (266-643)
334 (321-349)
249 (214-330)
358 (330-381)
317(304-330)
329(314-343)
372 (254-381)
495 (394-508)
444 (428-817)
453 (394-508)
390 (381-401)
636 (595-647)
505 (439-693)
595 (505-643)
363* (310-391)
387* (381-101)
380* (353-109)
645* (390-650)
519(508-634)
381 (367-392)
609 (508-647)
476 (439-593)
507 (486-593)
a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights;
consumers only are those individuals who consumed fish at least once during the 2-day reporting period..
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with
1,000 bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on
Nutrition Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-97
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-36.
Age (years)
Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
Weight3
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
Freshwater and Estuarine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
1 8 and older
14 and under
15 to 44
45 and older
All ages
410
315
432
1,157
419
358
548
1,325
416
132
101
28
1,599
829
673
980
2,482
1,776(1,543-2,009)
1,185 (962-1,408)
986 (880-1,093)
1,185 (1,071-1,299)
1,895 (1,618-2,172)
1,167 (1,034-1,299)
1,076 (963-1,190)
1,238(1,140-1,336)
2,292 (2,012-2,572)
1,830 (1,416-2,245)
1,273 (1,082-1,464)
1,401* (10,588-1,744)
1,102(1,023-1,181)
1,834 (1,680-1,987)
1,175 (1,067-1,282)
1,032(941-1,123)
1,213 (1,136-1,291)
4,397 (3,635-4,535)
2,922(2,294-3,314)
2,655(2,313-2,875)
2,875 (2,654-3,266)
4,707 (3,992-4,990)
2,998 (2,724-3,349)
2,467 (2,378-2,597)
3,052 (2,735-3,221)
5,852 (4,703-6,068)
4,688* (3,673-5,987)
2,777* (2,091-3,026)
2,971* (2,743-3,692)
2,693 (2,507-2,820)
4,512 (4,045-4,780)
2,978 (2,739-3,221)
2,508 (2,383-2,797)
2,947(2,808-3,118)
6,855 (4,881-9,166)
4,260 (3,266-5,973)
3,263 (2,944-3,716)
4,033 (3,516-4,406)
5,905 (5,522-6,103)
4,015 (3,712-4,635)
3,447 (3,093-3,849)
4,257 (4,039-4,473)
7,160 (6,950-7,442)
6,207* (4,767-12,926)
4,419* (3,026-5,522)
3,279* (2,767-8,577)
3,744 (3,520-4,037)
5,986(5,531-6,867)
4,125 (3,815-4,841)
3,319(3,034-3,716)
4,135 (4,037-4,287)
11,544(9,166-16,108)
8,154 (6,721-20,620)
4,630 (4,037-9,900)
8,608 (7,087-9,900)
12,628(8,111-15,495)
6,534(5,511-8,577)
6,574 (5,557-9,351)
7,998 (6,539-9,351)
15,600* (11,877-18,670)
12,365* (6,763-12,926)
5,717* (5,457-9,852)
6,819* (3,221-8,577)
7,140 (6,388-8,604)
12,389.(9,852-15,495)
8,580(5,973-9,477)
6,122 (4,422-8,254)
8,587 (6,950-9,900)
Marine
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
1 8 and older
14 and under
15 to 44
45 and older
All ages
629
403
568
1,600
643
409
621
640
203
120
37
1,944
1,272
812
1,189
2,893 (2,679-3,107)
1,475 (1,366-1,584)
1,579 (1,439-1,719)
1,732 (1,649-1,815)
2,885 (2,540-3,230)
1,579 (1,458-1,701)
1,412 (1,328-1,496)
3,689 (3,395-3,982)
2,787 (2,417-3,157)
2,020 (1,741-2,327)
2,007* (1,302-2,712)
1,501 (1,440-1,562)
2,892(2,674-3,111)
1,527(1,441-1,614)
1,501 (1,416-1,586)
6,279 (5,286-6,554)
3,102 (2,580-3,378)
3,028 (2,676-3,239)
3,558 (3,335-3,880)
6,244(5,390-6,931)
3,063 (2,855-3,481)
2,812 (2,589-3,072)
7,253 (6,777-8,504)
5,910 (4,813-7,365)
4,224* (3,744-4,781)
4,468* (3,880-7,802)
2,971 (2,740-3,098)
6,290 (5,748-6,448)
3,093 (2,855-3,318)
2,948 (2,664-3,232)
7,899 (7,033-8,478)
3,927 (3,440-4,929)
3,917 (3,584-4,560)
4,878 (4,560-5,640)
8,068 (6,577-8,707)
3,736 (3,554-4,048)
3,724 (3,386-3,987)
9,270 (8,415-9,991)
8,001* (6,375-8,707)
5,195* (3,859-6,448)
6,537* (3,991-7,802)
3,749 (3,579-3,962)
8,047 (7,365-8,564)
3,872(3,564-4,131)
3,889 (3,494-4,030)
10,514(9,322-11,981)
6,491 (5,931-7,802)
7,416 (6,021-12,395)
8,618 (7,802-9,322)
11,871 (10,365-14,194)
7,103 (4,634-7,701)
5,504 (5,134-6,321)
16,100* (11,980-17,989)
10,754* (8,707-12,055)
6,839* (6,076-8,970)
7,886* (4,661-7,958)
6,345 (5,653-7,224)
11,507(10,124-12,054)
6,898 (5,287-7,701)
6,229 (5,409-9,759)
Page
10-98
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
Weight" (continued)
Age (years)
N
Mean (90% CI)
90th Percentile
(90% BI)
95th Percentile
(90% BI)
99th Percentile
(90% BI)
All Fish
Females
14 and under
15 to 44
45 and older
All ages
Males
14 and under
15 to 44
45 and older
All ages
Both Sexes
3 to 5
6 to 10
11 to 15
16 to 17
18 and older
14 and under
15 to 44
45 and older
All ages
779 3,202(2,983-3,421)
541 1,728(1,547-1,909)
725 1,774(1,657-1,890)
2,045 1,962(1,864-2,061)
788 3,314(3,022-3,607)
561 1,851 (1,754-1,947)
842 1,703 (1,616-1,791)
779 4,198(3,894^1,502)
250 3,188(2,923-3,452)
164 2,199(1,950-2,449)
52 2,066* (1,529-2,603)
2,585 1,758(1,687-1,829)
1,567 3,260(3,062-3,457)
1,102 1,790(1,696-1,884)
1,567 1,740(1,650-1,830)
6,854 (6,596-7,365)
3,437 (3,153-3,925)
3,422 (3,098-3,767)
4,005(3,831-4,278)
7,402 (6,241-7,626)
3,599 (3,232-4,197)
3,395(3,118-3,638)
8,061 (7,366-9,223)
6,544 (6,013-8,707)
4,387* (3,785-5,522)
3,902* (3,536-7,892)
3,438 (3,303-3,584)
7,120 (6,533-7,859)
3,549(3,318-3,833)
3,416 (3,227-3,572)
8,808(8,451-9,408)
5,045 (4,221-6,122)
4,098 (3,870-4,853)
5,792 (5,097-6,059)
8,720 (8,323-10,591)
4,461 (3,991-5,063)
4,253 (3,912-4,685)
10,444 (9,475-12,261)
8,654* (7,086-11,756)
6,234* (4,420-7,589)
6,594* (4,661-8,577)
4,492 (4,271-4,810)
8,758 (8,487-9,362)
4,806 (4,214-5,422)
4,261 (4,017-4,497)
13,907(11,461-16,108)
8,011(6,721-8,604)
7,996(6,121-15,117)
9,878 (8,970-12,235)
13,025 (12,278-16,803)
7,621 (7,361-8,473)
6,376(5,514-9,351)
17,874* (15,290-18,670)
12,785* (10,930-13,979)
8,345* (6,076-8,970)
8,210* (7,892-8,577)
7,510(6,679-8,604)
13,955 (12,926-15,495)
7,839 (7,361-8,604)
6,704(6,195-9,351)
Estimates were projected from sample size to the U.S. population using 4-year combined survey weights;
consumers only are those individuals who consumed fish at least once during the 2-day reporting period..
N = Sample size.
CI = Confidence interval.
BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 1,000
bootstrap replications.
* The sample size does not meet minimum reporting requirements as described in the Third Report on Nutrition
Monitoring in the United States (LSRO, 1995).
Source: U.S. EPA, 2002.
Exposure Factors Handbook
September 2011
Page
10-99
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics (g/kg-day, as-consumed)
Percentiles
State
Connecticut
All
Sex
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Florida
All
Sexes
Demographic
Characteristic
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian
Unknown
0 to 1 1 years
High School
Some College
College Grad
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Unknown
Sample
Size
420
201
219
26
26
21
17
85
77
14
80
63
11
370
9
20
19
2
13
87
62
258
40
150
214
16
15,367
7,911
7,426
30
Arithmetic
Mean
0.41
0.39
0.43
0.32
0.51
0.27
0.67
0.46
0.43
0.16
0.47
0.35
0.09
0.41
0.05
0.48
0.61
0.01
0.33
0.38
0.41
0.43
0.39
0.47
0.38
0.32
0.47
0.44
0.50
0.41
Percent
Eating
Fish
85.1
86.2
84.0
51.7
86.7
85.6
79.9
86.7
90.6
70.5
92.8
90.5
76.1
88.7
33.5
70.9
59.2
43.4
100.0
85.3
88.7
83.4
86.4
87.4
84.1
73.4
50.5
49.2
51.9
48.0
10*
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.03
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.25
0.24
0.28
0.05
0.35
0.19
0.31
0.28
0.33
0.14
0.29
0.22
0.02
0.27
0.00
0.21
0.14
0.00
0.15
0.22
0.30
0.25
0.26
0.28
0.24
0.30
0.06
0.00
0.10
0.00
90th
1.00
1.05
0.95
0.95
1.13
0.52
1.06
1.00
0.96
0.41
1.13
0.86
0.37
0.98
0.17
1.53
1.33
*
1.04
1.00
0.80
1.03
0.96
1.04
0.99
0.75
1.27
1.22
1.32
1.41
95th
1.32
1.34
1.30
1.47
1.29
0.89
4.02
1.36
1.33
0.53
1.44
1.11
0.45
1.27
*
2.29
3.80
*
1.39
1.14
1.41
1.32
1.45
1.43
1.27
1.00
1.91
1.84
1.98
2.38
Page
10-100
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics (g/kg-day, as-consumed) (continued)
Percentiles
State
Florida (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Minnesota
All
Sexes
Age (years)-Sex
Category
Demographic
Characteristic
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Sample
Size
1,102
938
864
1,537
2,264
2,080
1,638
2,540
2,206
198
11,607
1,603
1,556
223
104
274
1,481
4,992
4,791
4,012
91
3,314
6,678
3,136
2,239
837
419
418
47
46
68
47
132
Arithmetic
Mean
0.89
0.44
0.37
0.44
0.53
0.41
0.44
0.43
0.38
0.35
0.46
0.54
0.46
0.58
0.63
0.43
0.40
0.46
0.49
0.47
0.46
0.47
0.48
0.51
0.35
0.31
0.26
0.36
0.57
0.33
0.22
0.67
0.24
Percent
Eating Fish
37.8
39.4
42.9
49.1
56.6
56.5
46.1
53.0
54.5
54.7
51.6
48.3
45.9
49.5
53.4
45.9
41.5
48.5
52.3
54.2
41.2
45.9
50.4
57.5
47.6
94.4
95.3
93.4
97.4
88.4
92.8
96.0
95.0
10*
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.02
0.02
0.05
0.00
0.02
0.02
0.02
50*
0.00
0.00
0.00
0.00
0.20
0.20
0.00
0.11
0.15
0.20
0.09
0.00
0.00
0.00
0.15
0.00
0.00
0.00
0.11
0.15
0.00
0.00
0.06
0.21
0.00
0.18
0.16
0.21
0.45
0.21
0.19
0.15
0.22
90th
2.75
.37
.02
.10
.38
.14
.11
.17
0.98
0.88
.24
.49
.20
.33
.95
.17
.16
.26
.30
.30
.57
1.21
1.28
1.38
1.09
0.62
0.58
0.65
1.09
0.82
0.54
0.61
0.50
95th
3.97
2.03
1.44
1.75
1.98
1.62
1.72
1.77
1.46
1.22
1.84
2.24
1.96
1.78
3.61
1.71
1.69
1.96
1.98
1.85
2.61
2.11
1.92
1.99
1.57
1.07
1.06
1.10
1.74
1.34
0.59
4.48
0.58
Exposure Factors Handbook
September 2011
Page
10-101
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics (g/kg-day, as-consumed) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating Fish
10*
50*
90th
95th
Minnesota (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
North Dakota
All
Sexes
Age (years)-Sex
Category
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
162
55
120
155
5
775
1
3
7
12
39
46
234
259
255
43
87
326
327
97
575
276
299
30
44
55
42
95
99
36
90
81
3
0.34
0.10
0.24
0.24
0.00
0.27
0.00
0.65
0.53
2.08
0.32
0.34
0.29
0.41
0.26
0.24
0.40
0.34
0.29
0.24
0.32
0.32
0.32
0.67
0.51
0.40
0.18
0.28
0.38
0.22
0.22
0.29
0.11
94.9
92.3
96.0
99.8
1.6
93.8
*
100.0
100.0
100.0
100.0
86.2
92.9
95.3
95.0
99.7
91.0
91.3
97.9
92.9
95.2
96.2
94.2
94.4
92.0
97.1
89.9
98.3
93.4
100.0
97.8
94.0
31.5
0.03
0.01
0.04
0.05
0.00
0.02
*
*
0.13
0.09
0.10
0.00
0.02
0.03
0.02
0.09
0.03
0.01
0.03
0.03
0.03
0.04
0.03
0.04
0.07
0.06
0.00
0.04
0.02
0.04
0.04
0.01
0.00
0.21
0.07
0.16
0.19
0.00
0.17
*
0.27
0.47
0.16
0.24
0.19
0.17
0.20
0.17
0.23
0.20
0.17
0.18
0.21
0.18
0.19
0.17
0.22
0.29
0.21
0.11
0.18
0.16
0.13
0.18
0.18
0.00
0.90
0.26
0.42
0.53
0.00
0.59
*
*
*
*
0.79
1.23
0.65
0.65
0.57
0.41
1.20
0.62
0.62
0.56
0.71
0.68
0.73
1.56
1.14
1.01
0.39
0.55
0.99
0.45
0.45
0.67
*
1.35
0.33
0.64
0.68
0.00
0.90
*
*
*
*
1.02
1.56
1.11
0.95
1.05
0.51
1.61
0.90
1.09
0.68
1.18
1.20
1.16
3.83
1.49
1.24
0.63
0.86
1.47
0.56
0.54
1.16
*
Page
10-102
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected
Characteristics (g/kg-day, as-consumed) (continued)
Demographic
Percentiles
State
North
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating Fish
10th
50th
90th
95th
Dakota (continued)
Race/Ethnicity
White, Non-Hispanic
Black, Non-Hispanic
Asian
American Indian
Unknown
528
2
4
9
32
0.33
0.25
0.20
0.30
0.30
95.1
100.0
100.0
100.0
93.5
0
0
0
03
*
*
08
05
0
0
0
0
0
18
25
18
25
13
0.72
*
*
0.69
0.71
1.21
*
*
*
0.94
Respondent
Education
0 to 1 1 years
High School
Some College
College Grad
Unknown
29
138
183
188
37
0.23
0.42
0.28
0.31
0.35
86.6
97.3
95.2
96.7
87.2
0
0
0
0
0
00
04
03
04
00
0
0
0
0
0
11
20
18
18
10
0.65
0.89
0.63
0.69
0.73
0.86
1.56
0.99
1.26
1.32
Household Income
($)
*
Notes:
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Percentiles cannot be estimated due
FL consumption is based on a 7-day
consumption
51
235
233
56
0.52
0.27
0.31
0.42
93.7
94.2
97.1
92.7
0
0
0
0
02
02
05
04
0
0
0
0
17
14
22
18
1.79
0.70
0.63
0.79
2.55
1.13
1.02
1.21
to small sample size.
recall; CT
, MN, and ND consumptions
FL consumption excludes away-from-home consumption by
Source
Statistics are
weighted to represent the general
children <1 8.
are based on rate of
population in the states.
: Westat, 2006.
Exposure Factors Handbook
September 2011
Page
10-103
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected
Demographic Characteristics (g/kg-day, as-consumed)
Percentiles
State
Connecticut
All
Sex
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household
Income ($)
Florida
All
Sexes
Demographic
Characteristic
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
Unknown
0 to 11 years
High School
Some College
College Grad
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Unknown
Sample
Size
362
175
187
14
22
18
14
74
70
10
74
57
9
331
3
15
12
1
13
76
56
217
35
133
182
12
7,757
3,880
3,861
16
Arithmetic
Mean
0.48
0.45
0.52
0.61
0.59
0.32
0.84
0.53
0.48
0.23
0.51
0.38
0.12
0.46
0.15
0.68
1.03
0.01
0.32
0.44
0.46
0.51
0.45
0.54
0.45
0.44
0.93
0.90
0.95
0.85
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
10th
0.07
0.08
0.05
0.16
0.14
0.07
0.11
0.05
0.05
0.08
0.11
0.10
0.01
0.07
*
0.12
0.09
*
0.05
0.05
0.10
0.08
0.08
0.07
0.07
0.10
0.19
0.18
0.19
0.12
50th
0.32
0.29
0.34
0.55
0.47
0.19
0.35
0.34
0.37
0.21
0.35
0.26
0.04
0.32
0.15
0.30
0.48
*
0.15
0.27
0.34
0.33
0.32
0.33
0.30
0.41
0.58
0.55
0.62
0.69
90th
1.09
1.11
1.03
1.42
1.15
0.52
1.12
1.12
1.03
0.47
1.15
0.93
0.39
1.05
*
1.86
1.95
*
0.97
1.04
0.85
1.12
1.13
1.12
1.06
0.84
1.89
1.85
1.94
2.37
95th
1.37
1.40
1.35
1.56
1.30
0.84
3.10
1.48
1.36
0.56
1.46
1.12
*
1.31
*
2.47
4.78
*
1.37
1.15
1.43
1.39
1.47
1.45
1.31
1.03
2.73
2.65
2.78
2.61
Page
10-104
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected
Demographic Characteristics (g/kg-day, as-consumed) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
10th
50th
90th
95th
Florida (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household
Income ($)
Minnesota
All
Sexes
Age (years)-Sex
Category
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 11 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
420
375
365
753
1,287
1,171
754
1,334
1,192
106
5,957
785
721
110
57
127
613
2,405
2,511
2,190
38
1,534
3,370
1,806
1,047
793
401
392
46
42
63
2.34
1.10
0.85
0.89
0.94
0.73
0.96
0.81
0.70
0.64
0.88
1.11
1.01
1.16
1.17
0.94
0.96
0.96
0.93
0.87
1.13
1.03
0.95
0.89
0.74
0.33
0.28
0.38
0.58
0.38
0.24
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
0.50
0.28
0.20
0.16
0.18
0.19
0.16
0.17
0.17
0.21
0.18
0.23
0.17
0.27
0.21
0.19
0.22
0.18
0.18
0.19
0.25
0.19
0.19
0.17
0.17
0.04
0.04
0.05
0.07
0.05
0.03
1.74
0.81
0.63
0.55
0.63
0.52
0.52
0.53
0.50
0.49
0.56
0.73
0.60
0.67
0.69
0.67
0.60
0.58
0.58
0.57
0.85
0.61
0.60
0.56
0.51
0.2
0.17
0.22
0.46
0.25
0.21
4.67
2.23
1.62
1.77
1.86
1.52
1.77
1.69
1.41
1.15
1.82
2.27
2.08
1.78
3.13
1.73
1.86
1.98
1.91
1.79
2.69
2.22
1.91
1.87
1.61
0.65
0.62
0.7
1.1
1.01
0.55
6.80
2.97
2.16
2.42
2.68
2.05
2.65
2.44
1.93
1.55
2.61
3.21
2.81
3.29
4.70
2.43
2.81
2.83
2.70
2.47
2.74
2.99
2.78
2.73
2.09
1.08
1.07
1.22
1.75
1.36
0.59
Exposure Factors Handbook
September 2011
Page
10-105
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected
Demographic Characteristics (g/kg-day, as-consumed) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
10th
50th
90th
95th
Minnesota (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household
Income ($)
North Dakota
All
Sexes
Age (years)-Sex
Category
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
44
127
150
52
115
153
1
732
*
o
J
7
12
39
41
219
249
242
42
77
301
321
94
546
265
281
28
41
53
38
93
92
36
0.69
0.25
0.36
0.11
0.25
0.24
0.18
0.29
*
0.65
0.53
2.08
0.32
0.39
0.31
0.43
0.27
0.24
0.44
0.37
0.29
0.26
0.34
0.33
0.34
0.70
0.56
0.41
0.20
0.29
0.40
0.22
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
0.02
0.04
0.05
0.02
0.07
0.05
*
0.04
*
*
0.13
0.09
0.10
0.07
0.04
0.04
0.04
0.09
0.09
0.05
0.03
0.05
0.05
0.04
0.05
0.05
0.11
0.06
0.04
0.05
0.06
0.04
0.16
0.23
0.22
0.08
0.17
0.19
*
0.19
*
0.27
0.46
0.15
0.24
0.20
0.18
0.22
0.19
0.23
0.20
0.18
0.19
0.23
0.19
0.20
0.18
0.23
0.30
0.22
0.15
0.18
0.17
0.13
0.66
0.51
0.93
0.27
0.42
0.53
*
0.60
*
*
*
*
0.79
1.37
0.68
0.65
0.58
0.41
1.30
0.65
0.62
0.57
0.74
0.74
0.74
1.58
1.17
1.04
0.41
0.56
1.14
0.45
2.95
0.58
1.37
0.33
0.64
0.68
*
0.98
*
*
*
*
1.01
1.56
1.13
0.98
1.05
0.50
1.63
0.96
1.10
0.69
1.21
1.22
1.20
3.82
1.51
1.26
0.67
0.87
1.52
0.56
Page
10-106
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-38. Fish Consumption per kg
Body Weight, Consumers Only,
Demographic Characteristics (g/kg-day, as-consumed)
by Selected
(continued)
Percentiles
State Demographic
Characteristic
North Dakota (continued)
Age (years)-Sex
Category
Male 30 to 49
Male 50+
Unknown
Race/Ethnicity
White, Non-
Hispanic
Black, Non-
Hispanic
Asian
American Indian
Unknown
Respondent
Education
0 to 11 years
High School
Some College
College Grad
Unknown
Household
Income ($)
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Sample
Size
88
76
1
501
2
4
9
30
25
134
174
181
32
48
221
225
52
Arithmetic
Mean
0.22
0.31
0.34
0.34
0.25
0.20
0.30
0.32
0.26
0.43
0.29
0.32
0.40
0.55
0.29
0.32
0.45
* Percentiles cannot be estimated due to small sample
Notes : FL consumption is based on a
rate of consumption.
7-day recall; CT, MN,
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
size.
10th
0.05
0.04
*
0.05
*
*
0.08
0.05
0.07
0.05
0.05
0.05
0.04
0.07
0.04
0.06
0.05
50th
0
18
0.19
0
*
19
90th
0
0
0
0.25
0.14
0.25
0.16
0.12
0
20
0.20
0
19
0.13
0
0
19
15
0.23
0
and ND consumptions
20
are
0
0
0
0
0
0
0
1
0
0
0
45
74
*
74
*
*
61
73
73
98
65
72
84
80
73
64
82
based
95*
0
1
54
20
*
1.23
0
0
*
*
*
95
90
1.62
1
1
1
02
30
43
2.62
1
1
1
on
17
04
28
FL consumption excludes away-from-home consumption by children <18.
Statistics are weighted to represent the
Source: Westat, 2006.
general population in the
states.
Exposure Factors Handbook
September 2011
Page
10-107
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-39. Fish Consumption per kg Body Weight, all Respondents by State, Acquisition Method,
(g/kg-day, as-consumed)
State Category
Connecticut
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
Florida
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
Sample
Size
420
420
420
Group
40
150
214
16
40
150
214
16
420
420
420
420
420
15,367
15,367
15,367
Group
3,314
6,678
3,136
2,239
3,314
6,678
3,136
2,239
15,367
15,367
15,367
15,367
15,367
Arithmetic
Mean
0.41
0.40
0.01
0.38
0.46
0.38
0.32
0.01
0.01
0.01
0.00
0.01
0.10
0.29
0.13
0.27
0.47
0.41
0.06
0.41
0.41
0.45
0.32
0.06
0.07
0.06
0.03
0.04
0.10
0.33
0.07
0.39
Percent
Eating
Fish
85.1
84.8
16.3
86.4
86.6
84.1
73.4
11.0
18.1
16.8
6.2
36.4
76.0
84.8
74.6
82.7
50.5
47.5
7.4
42.5
47.4
54.2
45.3
6.7
7.8
8.4
5.5
9.1
26.5
40.3
21.1
41.9
Percentiles
10th
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.25
0.25
0.00
0.26
0.27
0.24
0.30
0.00
0.00
0.00
0.00
0.00
0.04
0.17
0.06
0.14
0.06
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
90th
1.00
0.96
0.01
0.96
0.93
0.99
0.75
0.00
0.02
0.01
0.00
0.03
0.23
0.67
0.30
0.69
1.27
1.12
0.00
1.10
1.11
1.27
0.99
0.00
0.00
0.00
0.00
0.00
0.32
0.90
0.22
1.10
95th
1.32
1.30
0.03
1.45
1.42
1.27
1.00
0.05
0.06
0.02
0.01
0.07
0.43
0.97
0.55
0.95
1.91
1.70
0.34
1.84
1.68
1.79
1.45
0.32
0.38
0.42
0.16
0.26
0.54
1.43
0.43
1.67
Page
10-108
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-39. Fish Consumption per kg Body Weight, all Respondents by
(g/kg-day, as-consumed) (continued)
State Category
Minnesota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
North Dakota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Sample
Size
837
837
837
Group
87
326
327
97
87
326
327
97
837
837
837
837
837
575
575
575
Group
51
235
233
56
51
235
233
56
575
575
575
Arithmetic
Mean
0.31
0.20
0.11
0.26
0.18
0.20
0.21
0.14
0.15
0.09
0.04
0.11
0.02
0.18
0.04
0.27
0.32
0.23
0.09
0.41
0.21
0.19
0.30
0.10
0.07
0.12
0.11
0.09
0.02
0.21
Percent
Eating
Fish
94.4
89.9
60.6
90.7
84.4
93.9
91.3
70.4
66.0
55.5
56.7
60.6
67.5
89.9
67.5
94.0
95.2
89.9
68.3
88.0
90.6
90.7
85.5
53.9
59.4
76.2
85.7
68.3
71.3
89.9
State, Acquisition Method,
Percentiles
10*
0.02
0.00
0.00
0.02
0.00
0.02
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.03
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.18
0.10
0.03
0.12
0.10
0.10
0.18
0.03
0.04
0.02
0.02
0.03
0.01
0.09
0.01
0.15
0.18
0.10
0.04
0.12
0.09
0.10
0.10
0.01
0.02
0.06
0.05
0.04
0.01
0.09
90th
0.62
0.51
0.22
0.61
0.45
0.55
0.54
0.28
0.25
0.24
0.12
0.22
0.05
0.46
0.10
0.57
0.71
0.52
0.24
1.34
0.48
0.48
0.66
0.23
0.18
0.34
0.22
0.24
0.05
0.45
95*
1.07
0.76
0.37
1.06
0.58
0.86
0.65
1.00
0.36
0.39
0.14
0.37
0.09
0.68
0.18
0.83
1.18
0.93
0.40
2.03
1.01
0.77
0.91
0.45
0.30
0.46
0.23
0.40
0.08
0.80
Exposure Factors Handbook
September 2011
Page
10-109
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-39. Fish Consumption per kg Body Weight, all Respondents by State, Acquisition
Method,g/kg-day, as-consumed) (continued)
State Category
North Dakota (continued)
Fish/Shellfish Type
Shellfish
Finfish
Sample Arithmetic
Size Mean
575 0.04
575 0.28
Percentiles
Percent 10th 50th 90th
Eating
Fish
71.3 0.00 0.02 0.09
94.3 0.02 0.14 0.63
95th
0.15
1.01
Notes: FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of
consumption.
FL consumption excludes away-from-home consumption by children <18.
Statistics are weighted to represent the general population in the states.
A respondent can be represented in more than one row.
Source: Westat, 2006.
Page Exposure Factors Handbook
10-110 September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State
day, as-consumed)
, Acquisition Method (g/kg-
Percentiles
State Category
Connecticut
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Acquisition Method of Fish/Shellfish Eaten
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Habitat
Freshwater
Estuarine
Marine
Eats Freshwater/Estuarine Caught Fish
Sometimes
Never
Fish/Shellfish Type
Shellfish
Finfish
Florida
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Sample
Size
362
361
71
Group
35
132
182
12
4
30
36
1
1
70
291
157
327
361
50
312
320
353
7,757
7,246
1,212
Group
1,418
3,141
1,695
992
246
563
274
129
Arithmetic
Mean
0.48
0.47
0.05
0.44
0.53
0.45
0.44
0.05
0.08
0.03
0.01
0.01
0.49
0.48
0.04
0.14
0.34
0.46
0.49
0.18
0.32
0.93
0.86
0.83
0.97
0.87
0.83
0.71
0.89
0.90
0.76
0.58
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
10*
0.07
0.07
0.00
0.08
0.07
0.06
0.10
*
0.00
0.00
*
*
0.10
0.06
0.00
0.01
0.04
0.09
0.07
0.02
0.02
0.19
0.17
0.15
0.19
0.18
0.16
0.16
0.19
0.15
0.11
0.16
50th
0.32
0.31
0.02
0.30
0.32
0.30
0.41
0.01
0.02
0.02
*
*
0.34
0.32
0.02
0.06
0.23
0.29
0.32
0.09
0.20
0.58
0.54
0.52
0.58
0.56
0.53
0.48
0.60
0.53
0.49
0.41
90th
1.09
1.05
0.13
1.13
1.03
1.04
0.84
*
0.23
0.08
*
*
1.10
1.06
0.07
0.30
0.78
1.10
1.06
0.37
0.77
1.89
1.77
1.74
2.10
1.74
1.75
1.55
1.94
1.79
1.63
1.07
95*
1.37
1.38
0.18
1.47
1.46
1.29
1.03
*
0.46
0.11
*
*
1.33
1.39
0.15
0.51
1.09
1.25
1.41
0.68
1.08
2.73
2.55
2.36
2.78
2.50
2.54
2.06
2.77
2.38
2.42
1.52
Exposure Factors Handbook
September 2011
Page
10-111
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-40.
State
Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,(g/kg-
day, as-consumed) (continued)
Category
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
Percentiles
10*
50*
90*
95*
Florida (continued)
Acquisition Method of Fish/Shellfish Eaten
Habitat
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Freshwater
Estuarine
Marine
511
701
6,545
1,426
4,124
6,124
0.76
1.81
0.85
0.47
0.37
0.81
100
100
100
100
100
100
0.15
0.50
0.18
0.07
0.07
0.15
0.50
1.15
0.54
0.30
0.23
0.50
1.67
3.35
1.75
1.09
0.80
1.64
2.34
5.09
2.49
1.51
1.14
2.40
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
235
458
7,064
0.71
1.73
0.88
100
100
100
0.10
0.43
0.18
0.42
1.10
0.56
1.60
3.44
1.81
2.16
4.96
2.60
Fish/Shellfish Type
Minnesota
All
Shellfish
Finfish
3,260
6,428
793
0.35
0.94
0.33
100
100
100
0.07
0.24
0.04
0.21
0.60
0.20
0.74
1.85
0.65
1.02
2.72
1.08
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
755
593
Group
76
284
312
83
56
232
235
70
0.22
0.18
0.29
0.22
0.21
0.23
0.19
0.23
0.16
0.07
100
100
100
100
100
100
100
100
100
100
0.03
0.02
0.04
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.12
0.07
0.13
0.13
0.11
0.2
0.05
0.08
0.08
0.03
0.55
0.30
0.64
0.47
0.57
0.54
0.49
0.30
0.37
0.14
0.83
0.57
1.08
0.74
0.97
0.65
1.09
0.46
0.65
0.16
Acquisition Method of Fish/Shellfish Eaten
Habitat
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Freshwater
Estuarine
Marine
38
555
200
593
559
755
0.16
0.40
0.23
0.18
0.03
0.20
100
100
100
100
100
100
0.02
0.08
0.02
0.02
0.00
0.02
0.08
0.23
0.14
0.07
0.01
0.10
0.37
0.70
0.56
0.30
0.07
0.50
0.51
1.32
0.91
0.57
0.12
0.73
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
38
555
200
0.16
0.40
0.23
100
100
100
0.02
0.08
0.02
10*
0.08
0.23
0.14
50*
0.37
0.70
0.56
90*
0.51
1.32
0.91
95*
Page
10-112
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,(g/kg-
day, as-consumed) (continued)
Category
State
Minnesota (continued)
Fish/Shellfish Type
Shellfish
Finfish
North Dakota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Acquisition Method of Fish/Shellfish Eaten
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Habitat
Freshwater
Estuarine
Marine
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
Fish/Shellfish Type
Shellfish
Finfish
Sample Arithmetic Percent
Size
559
791
546
516
389
Group
45
213
210
48
27
142
173
47
30
359
157
389
407
516
30
359
157
407
541
Notes: FL consumption is based on a 7-day recall; CT
consumption.
Mean
0.06
0.28
0.34
0.25
0.14
0.47
0.23
0.21
0.35
0.19
0.11
0.15
0.13
0.21
0.39
0.25
0.14
0.03
0.23
0.21
0.39
0.25
0.05
0.30
, MN, and ND
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
consumptions
10*
0.01
0.03
0.05
0.03
0.02
0.05
0.03
0.03
0.03
0.01
0.02
0.02
0.03
0.05
0.07
0.03
0.02
0.00
0.02
0.05
0.07
0.03
0.01
0.04
Percentiles
50*
0.02
0.16
0.19
0.12
0.07
0.14
0.11
0.11
0.14
0.08
0.05
0.08
0.06
0.14
0.23
0.10
0.07
0.01
0.10
0.14
0.23
0.10
0.02
0.16
90th
0.14
0.57
0.74
0.61
0.34
1.54
0.52
0.48
0.70
0.42
0.25
0.38
0.23
0.33
0.82
0.53
0.34
0.06
0.54
0.33
0.82
0.53
0.13
0.67
95*
0.24
0.86
1.21
1.02
0.46
2.22
1.03
0.79
1.08
0.64
0.40
0.53
0.24
0.51
1.25
0.97
0.46
0.10
0.86
0.51
1.25
0.97
0.21
1.08
are based on rate of
FL consumption excludes away-from-home consumption by children <18.
Statistics are weighted to represent
the general
population in the states.
A respondent can be represented in more than one row.
Source: Westat, 2006.
Exposure Factors Handbook
September 2011
Page
10-113
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day)
Percentiles
State
Connecticut
All
Sex
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Florida
All
Sexes
Demographic
Characteristic
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
Unknown
0 to 1 1 years
High School
Some College
College Grad
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Unknown
Sample
Size
420
201
219
26
26
21
17
85
77
14
80
63
11
370
9
20
19
2
13
87
62
258
40
150
214
16
15,367
7,911
7,426
30
Arithmetic
Mean
0.56
0.53
0.59
0.43
0.71
0.37
0.88
0.64
0.59
0.23
0.64
0.47
0.12
0.56
0.07
0.67
0.81
0.01
0.43
0.51
0.56
0.58
0.52
0.64
0.52
0.45
0.59
0.55
0.62
0.51
Percent
Eating
Fish
85.1
86.2
84.0
51.7
86.7
85.6
79.9
86.7
90.6
70.5
92.8
90.5
76.1
88.7
33.5
70.9
59.2
43.4
100.0
85.3
88.7
83.4
86.4
87.4
84.1
73.4
50.5
49.2
51.9
48.0
10th
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.04
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.35
0.34
0.39
0.07
0.48
0.25
0.43
0.39
0.45
0.21
0.43
0.36
0.03
0.38
0.00
0.29
0.18
0.00
0.20
0.30
0.41
0.36
0.34
0.39
0.34
0.42
0.08
0.00
0.14
0.00
90th
1.37
1.48
1.29
1.25
1.55
0.71
1.41
1.39
1.28
0.55
1.56
1.15
0.52
1.32
0.23
2.14
1.74
*
1.34
1.40
1.09
1.40
1.28
1.40
1.37
1.02
1.59
1.51
1.66
1.73
95th
1.76
1.78
1.73
.95
.74
.20
5.25
.80
.74
0.74
1.97
1.55
0.62
1.69
*
3.43
4.96
*
1.74
1.55
1.87
1.78
1.86
1.93
1.69
1.36
2.39
2.32
2.48
2.90
Page
10-114
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Florida (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Minnesota
All
Sexes
Demographic
Characteristic
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Sample
Size
1,102
938
864
1,537
2,264
2,080
1,638
2,540
2,206
198
11,607
1,603
1,556
223
104
274
1,481
4,992
4,791
4,012
91
3,314
6,678
3,136
2,239
837
419
418
Arithmetic
Mean
1.10
0.54
0.46
0.55
0.67
0.52
0.55
0.54
0.49
0.45
0.57
0.67
0.57
0.72
0.78
0.53
0.50
0.58
0.61
0.60
0.58
0.59
0.61
0.65
0.45
0.41
0.35
0.48
Percent
Eating
Fish
37.8
39.4
42.9
49.1
56.6
56.5
46.1
53.0
54.5
54.7
51.6
48.3
45.9
49.5
53.4
45.9
41.5
48.5
52.3
54.2
41.2
45.9
50.4
57.5
47.6
94.4
95.3
93.4
10th
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.03
0.02
50th
0.00
0.00
0.00
0.00
0.27
0.27
0.00
0.16
0.20
0.27
0.12
0.00
0.00
0.00
0.20
0.00
0.00
0.00
0.15
0.20
0.00
0.00
0.08
0.27
0.00
0.24
0.22
0.27
90th
3.41
.69
.27
.42
.73
.44
.41
.49
.24
.07
1.56
1.87
1.52
1.65
2.46
1.45
1.45
1.59
1.59
1.64
2.04
1.55
1.61
1.77
1.36
0.83
0.77
0.87
95th
4.85
2.55
1.92
2.20
2.56
2.04
2.20
2.21
1.86
1.53
2.33
2.77
2.46
2.34
4.52
2.14
2.16
2.45
2.47
2.34
3.05
2.61
2.42
2.53
1.99
1.43
1.41
1.46
Exposure Factors Handbook
September 2011
Page
10-115
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
10th
50th
90th
95th
Minnesota (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
North Dakota
All
Sexes
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
47
46
68
47
132
162
55
120
155
5
775
1
3
7
12
39
46
234
259
255
43
87
326
327
97
575
276
299
0.76
0.44
0.29
0.89
0.32
0.46
0.13
0.32
0.32
0.00
0.36
0.00
0.86
0.71
2.77
0.43
0.45
0.39
0.54
0.34
0.32
0.53
0.45
0.38
0.33
0.43
0.43
0.43
97.4
88.4
92.8
96.0
95.0
94.9
92.3
96.0
99.8
1.6
93.8
*
100
100
100
100
86.2
92.9
95.3
95.0
99.7
91.0
91.3
97.9
92.9
95.2
96.2
94.2
0.06
0.00
0.02
0.03
0.03
0.04
0.01
0.06
0.06
0.00
0.02
*
*
0.18
0.12
0.14
0.00
0.02
0.04
0.03
0.12
0.04
0.02
0.04
0.04
0.05
0.05
0.04
0.60
0.28
0.25
0.20
0.29
0.28
0.09
0.22
0.25
0.00
0.23
*
0.36
0.63
0.21
0.31
0.25
0.22
0.27
0.23
0.30
0.27
0.23
0.24
0.29
0.24
0.25
0.23
1.46
1.09
0.72
0.81
0.67
1.19
0.35
0.56
0.70
0.00
0.79
*
*
*
*
1.05
1.64
0.86
0.86
0.76
0.55
1.60
0.83
0.82
0.74
0.95
0.91
0.97
2.32
1.79
0.78
5.97
0.77
1.80
0.44
0.85
0.91
0.00
1.19
*
*
*
*
1.36
2.08
1.48
1.27
1.40
0.68
2.14
1.20
1.46
0.91
1.58
1.60
1.55
Page
10-116
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
10th
50th
90th
95th
North Dakota (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
* Percentiles cannot be estimated due
Notes: FL consumption is based on a 7-day
30
44
55
42
95
99
36
90
81
3
528
2
4
9
32
29
138
183
188
37
51
235
233
56
to small
0.89
0.68
0.53
0.24
0.38
0.50
0.29
0.29
0.38
0.14
0.43
0.33
0.26
0.40
0.40
0.30
0.56
0.37
0.41
0.46
0.69
0.36
0.41
0.55
sample size.
94.4
92.0
97.1
89.9
98.3
93.4
100.0
97.8
94.0
31.5
95.1
100.0
100.0
100.0
93.5
86.6
97.3
95.2
96.7
87.2
93.7
94.2
97.1
92.7
0.05
0.09
0.07
0.00
0.05
0.03
0.05
0.05
0.02
0.00
0.04
*
*
0.11
0.06
0.00
0.06
0.04
0.05
0.00
0.03
0.03
0.06
0.05
0.30
0.39
0.28
0.15
0.24
0.21
0.17
0.23
0.23
0.00
0.24
0.33
0.24
0.33
0.18
0.15
0.26
0.25
0.25
0.13
0.23
0.18
0.30
0.24
2.08
1.52
1.35
0.52
0.74
1.32
0.61
0.59
0.90
*
0.96
*
*
0.92
0.95
0.86
1.19
0.84
0.92
0.98
2.39
0.93
0.84
1.05
recall; CT, MN, and ND consumptions are based on rate
5.10
1.99
1.65
0.84
1.14
1.95
0.75
0.71
1.54
*
1.62
*
*
*
1.25
1.15
2.08
1.32
1.69
1.76
3.40
1.51
1.36
1.62
of
consumption.
FL consumption excludes away-from-home
Statistics are
Source: Westat, 2006
consumption by
children <
weighted to represent the general population in the states.
Exposure Factors Handbook
September 2011
Page
10-117
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-42. Fish Consumption per kg Body Weight, Consumers Only,
Characteristics, Uncooked (g/kg-day)
State
Connecticut
All
Sex
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Florida
All
Sexes
Demographic
Characteristic
Male
Female
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
Unknown
0 to 1 1 years
High School
Some College
College Grad
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Unknown
Sample
Size
362
175
187
14
22
18
14
74
70
10
74
57
9
331
3
15
12
1
13
76
56
217
35
133
182
12
7,757
3,880
3,861
16
Arithmetic
Mean
0.66
0.61
0.70
0.83
0.81
0.43
1.10
0.73
0.65
0.32
0.69
0.52
0.16
0.63
0.20
0.95
1.36
0.03
0.43
0.60
0.63
0.70
0.60
0.73
0.62
0.61
1.16
1.12
1.20
1.05
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
by Selected Demographic
10th
0.10
0.11
0.09
0.21
0.21
0.12
0.15
0.08
0.07
0.11
0.15
0.14
0.01
0.10
*
0.16
0.12
*
0.07
0.06
0.16
0.11
0.10
0.12
0.09
0.13
0.24
0.23
0.25
0.15
Percentiles
50th 90th
0.43
0.41
0.47
0.74
0.74
0.30
0.47
0.47
0.50
0.30
0.48
0.38
0.05
0.43
0.20
0.39
0.69
*
0.20
0.37
0.46
0.45
0.43
0.46
0.41
0.57
0.73
0.69
0.77
0.91
1.51
1.54
1.40
1.88
1.57
0.72
1.50
1.60
1.39
0.63
1.58
1.25
0.54
1.41
*
2.95
2.57
*
1.27
1.47
1.16
1.53
1.53
1.55
1.49
1.14
2.39
2.33
2.42
2.90
95th
1.80
1.85
1.77
2.07
1.76
1.14
4.07
1.97
1.76
0.78
1.98
1.55
*
1.75
*
3.52
6.24
*
1.72
1.56
1.89
1.85
1.90
1.98
1.75
1.41
3.37
3.32
3.48
3.19
Page
10-118
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Florida (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
Minnesota
All
Sexes
Demographic
Characteristic
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
Sample
Size
420
375
365
753
1,287
1,171
754
1,334
1,192
106
5,957
785
721
110
57
127
613
2,405
2,511
2,190
38
1,534
3,370
1,806
1,047
793
401
392
Arithmetic
Mean
2.92
1.37
1.06
1.12
1.18
0.91
1.19
1.02
0.89
0.81
1.11
1.39
1.25
1.46
1.45
1.16
1.20
1.20
1.16
1.10
1.40
1.28
1.20
1.13
0.93
0.44
0.37
0.51
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
10th
0.63
0.38
0.28
0.23
0.24
0.24
0.22
0.22
0.22
0.27
0.24
0.30
0.23
0.35
0.28
0.24
0.27
0.23
0.24
0.24
0.32
0.25
0.25
0.22
0.23
0.06
0.05
0.06
50th
2.16
1.01
0.79
0.71
0.78
0.66
0.66
0.67
0.62
0.61
0.71
0.91
0.75
0.84
0.90
0.81
0.74
0.73
0.72
0.73
1.06
0.77
0.75
0.71
0.64
0.26
0.23
0.29
90th
5.73
2.72
2.02
2.22
2.39
1.92
2.26
2.18
1.75
1.50
2.30
2.81
2.53
2.34
4.02
2.23
2.38
2.49
2.39
2.25
3.08
2.77
2.41
2.39
2.06
0.86
0.82
0.93
95th
8.37
3.45
2.78
3.10
3.31
2.53
3.30
3.05
2.51
2.02
3.28
3.92
3.57
4.08
5.73
3.10
3.53
3.58
3.39
3.17
3.17
3.66
3.45
3.37
2.52
1.44
1.43
1.62
Exposure Factors Handbook
September 2011
Page
10-119
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Demographic
Characteristic
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
10th
50th
90th
95th
Minnesota (continued)
Age (years)-Sex
Category
Race/Ethnicity
Respondent
Education
Household Income
($)
North Dakota
All
Sexes
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
White, Non-
Hispanic
Black, Non-
Hispanic
Hispanic
Asian
American Indian
Unknown
0 to 1 1 years
High School
Some College
College Grad
Unknown
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Male
Female
46
42
63
44
127
150
52
115
153
1
732
*
3
7
12
39
41
219
249
242
42
77
301
321
94
546
265
281
0.78
0.50
0.32
0.92
0.34
0.48
0.14
0.33
0.33
0.24
0.38
*
0.86
0.71
2.77
0.43
0.53
0.42
0.57
0.36
0.32
0.59
0.49
0.39
0.35
0.45
0.44
0.46
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
0.09
0.06
0.04
0.03
0.05
0.07
0.02
0.09
0.06
*
0.05
*
*
0.18
0.12
0.14
0.10
0.06
0.05
0.05
0.12
0.12
0.07
0.04
0.07
0.07
0.06
0.07
0.62
0.33
0.28
0.21
0.30
0.29
0.11
0.23
0.25
*
0.25
*
0.36
0.62
0.21
0.31
0.26
0.24
0.29
0.25
0.31
0.27
0.24
0.25
0.30
0.25
0.27
0.24
1.47
1.35
0.73
0.88
0.68
1.24
0.36
0.56
0.70
*
0.81
*
*
*
*
1.05
1.83
0.90
0.86
0.78
0.55
1.73
0.86
0.83
0.76
0.99
0.99
0.99
2.33
1.81
0.78
3.93
0.78
1.82
0.44
0.86
0.91
*
1.31
*
*
*
*
1.34
2.08
1.51
1.31
1.41
0.67
2.17
1.28
1.46
0.92
1.62
1.62
1.60
Page
10-120
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
Characteristics, Uncooked (g/kg-day) (continued)
Percentiles
State
Demographic Sample
Characteristic Size
Arithmetic Percent 10th
Mean Eating
Fish
50th
90th
95th
North Dakota (continued)
Age (years)-Sex
Category
Child 1 to 5
Child 6 to 10
Child 11 to 15
Female 16 to 29
Female 30 to 49
Female 50+
Male 16 to 29
Male 30 to 49
Male 50+
Unknown
28
41
53
38
93
92
36
88
76
1
0.94
0
0
74
54
0.27
0
38
0.54
0
29
0.29
0
41
0.45
100
100
100
100
100
100
100
100
100
100
0
0
0
0
0
0
0
0
0
07
14
08
05
06
08
05
06
05
*
0
0
0
0
0
0
0
0
0
31
40
29
19
24
23
17
25
25
*
2.11
1.56
1.39
0.54
0.75
1.53
0.60
0.60
0.99
*
5.09
2.02
1.68
0.89
1.16
2.02
0.75
0.72
1.60
*
Race/Ethnicity
White, Non-
Hispanic
Black, Non-
Hispanic
Asian
American Indian
Unknown
501
2
4
9
30
0
0
45
33
0.26
0
0
40
42
100
100
100
100
100
0
0
0
06
*
*
11
07
0
0
0
0
0
25
33
18
33
21
0.99
*
*
0.82
0.98
1.64
*
*
*
1.27
Respondent
Education
0 to 1 1 years
High School
Some College
College Grad
Unknown
25
134
174
181
32
0.35
0
57
0.38
0
43
0.53
100
100
100
100
100
0
0
0
0
0
09
07
06
07
05
0
0
0
0
0
16
27
26
25
17
0.97
1.30
0.87
0.95
1.12
1.20
2.16
1.36
1.73
1.91
Household Income
($)
*
Notes:
0 to 20,000
20,000 to 50,000
>50,000
Unknown
Percentiles cannot be estimated due
FL consumption is based on a 7-day
of consumption.
48
221
225
52
to small
0
74
0.39
0.42
0
60
100
100
100
100
0
0
0
0
09
05
08
06
0
0
0
0
25
20
31
27
2.40
0.97
0.85
1.10
3.49
1.55
1.39
1.71
sample size.
recall; CT, MN, and ND consumptions
FL consumption excludes away-from-home
consumption by
are based on rate
children < 18.
Statistics are weighted to represent the general population in the
Source:
Westat, 2006.
states.
Exposure Factors Handbook
September 2011
Page
10-121
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition Method,
Uncooked (g/kg-day)
State Characteristic
Connecticut
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
Florida
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
Sample
Size
420
420
420
($) Group
40
150
214
16
40
150
214
16
420
420
420
420
420
15,367
15,367
15,367
($) Group
3,314
6,678
3,136
2,239
3,314
6,678
3,136
2,239
15,367
15,367
15,367
15,367
15,367
Arithmetic
Mean
0.56
0.55
0.01
0.51
0.62
0.52
0.45
0.01
0.02
0.01
0.00
0.02
0.15
0.40
0.19
0.36
0.59
0.51
0.08
0.51
0.52
0.57
0.40
0.08
0.09
0.08
0.04
0.05
0.13
0.40
0.11
0.48
Percent
Eating Fish
85.1
84.8
16.3
86.4
86.6
84.1
73.4
11.0
18.1
16.8
6.2
36.4
76.0
84.8
74.6
82.7
50.5
47.5
7.40
42.5
47.4
54.2
45.3
6.7
7.8
8.4
5.5
9.1
26.5
40.3
21.1
41.9
Percentiles
10th
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.35
0.34
0.00
0.34
0.37
0.33
0.42
0.00
0.00
0.00
0.00
0.00
0.06
0.23
0.09
0.19
0.08
0.00
0.00
0.00
0.00
0.19
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
90th
1.37
1.30
0.02
1.28
1.22
1.34
1.02
0.00
0.03
0.01
0.00
0.05
0.36
0.90
0.43
0.94
1.59
1.41
0.00
1.34
1.40
1.58
1.21
0.00
0.00
0.00
0.00
0.00
0.43
1.11
0.32
1.35
95th
1.76
1.76
0.04
1.86
1.93
1.64
1.36
0.06
0.08
0.03
0.01
0.09
0.59
1.29
0.76
1.28
2.39
2.16
0.45
2.32
2.12
2.27
1.82
0.42
0.48
0.53
0.21
0.33
0.73
1.76
0.61
2.08
Page
10-122
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition
MethodUncooked (g/kg-day) (continued)
Percentiles
State Characteristic
Minnesota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Fish/Shellfish Type
Shellfish
Finfish
North Dakota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Habitat
Freshwater
Estuarine
Marine
Sample
Size
837
837
837
($) Group
87
326
327
97
87
326
327
97
837
837
837
837
837
575
575
575
($) Group
51
235
233
56
51
235
233
56
575
575
575
Arithmetic
Mean
0.41
0.27
0.15
0.35
0.25
0.27
0.28
0.18
0.20
0.12
0.05
0.15
0.03
0.24
0.06
0.36
0.43
0.30
0.13
0.55
0.28
0.26
0.41
0.14
0.09
0.15
0.15
0.13
0.03
0.28
Percent
Eating Fish
94.4
89.9
60.6
90.7
84.4
93.9
91.3
70.4
66.0
55.5
56.7
60.6
67.5
89.9
67.5
94.0
95.2
89.9
68.3
88.0
90.6
90.7
85.5
53.9
59.4
76.2
85.7
68.3
71.3
89.9
10th
0.03
0.00
0.00
0.02
0.00
0.02
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.05
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50th
0.24
0.14
0.03
0.15
0.13
0.14
0.23
0.04
0.06
0.03
0.02
0.03
0.01
0.12
0.02
0.19
0.24
0.13
0.05
0.15
0.13
0.13
0.14
0.01
0.03
0.08
0.07
0.05
0.01
0.11
90th
0.83
0.68
0.30
0.82
0.60
0.74
0.72
0.38
0.33
0.31
0.16
0.30
0.06
0.61
0.13
0.76
0.95
0.69
0.31
1.79
0.65
0.64
0.88
0.31
0.23
0.45
0.29
0.31
0.06
0.60
95*
1.43
1.01
0.49
1.42
0.77
1.15
0.86
1.33
0.48
0.53
0.19
0.49
0.12
0.91
0.24
1.11
1.58
1.24
0.53
2.71
1.35
1.02
1.21
0.61
0.40
0.61
0.31
0.53
0.10
1.07
Exposure Factors Handbook
September 2011
Page
10-123
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition
MethodUncooked (g/kg-day) (continued)
Percentiles
State Characteristic Sample Arithmetic Percent
Size Mean Eating Fish
North Dakota (continued)
Fish/Shellfish Type
Shellfish 575 0.05 71.3
Finfish 575 0.38 94.3
Notes: FL consumption is based on a 7-day recall; CT, MN, and ND consumptions
consumption.
FL consumption excludes away-from-home consumption by children <18.
Statistics are weighted to represent the general population in the states.
A respondent can be represented in more than one row.
Source: Westat, 2006.
10th 50th 90th
0.00 0.02 0.12
0.03 0.19 0.84
are based on rate of
95*
0.20
1.35
Page Exposure Factors Handbook
10-124 September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State,
Uncooked (g/kg-day)
State
Category
Sample
Size
Arithmetic
Mean
Percent
Eating
Fish
Acquisition Method,
Percentiles
10th
50th
90th
95th
Connecticut
All
362
0
66
100
0
10
0.43
1.51
1
.80
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
361
71
Group
35
132
182
12
4
30
36
1
0
0
0
0
0
0
0
0
0
0
65
07
59
71
62
61
07
11
04
01
100
100
100
100
100
100
100
100
100
100
0
0
0
0
0
0
0
0
10
00
10
11
08
13
*
01
00
*
0.43
0.02
0.41
0.45
0.41
0.57
0.02
0.03
0.02
*
1.43
0.17
1.53
1.40
1.45
1.14
*
0.30
0.11
*
1
0
1
1
1
1
0
o
3
.80
.23
.90
.98
.75
.41
*
.62
.15
*
Acquisition Method of Fish/Shellfish Eaten
Habitat
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Freshwater
Estuarine
Marine
1
70
291
157
327
361
0
0
0
0
0
0
03
67
66
05
19
47
100
100
100
100
100
100
0
0
0
0
0
*
13
09
00
01
06
*
0.46
0.43
0.03
0.09
0.31
*
1.54
1.50
0.10
0.40
1.03
i
i
0
0
1
*
.71
.82
.21
.69
.45
Eats Freshwater/Estuarine Caught Fish
Sometimes
Never
50
312
0
0
64
66
100
100
0
0
12
10
0.39
0.44
1.53
1.50
1
.68
1.83
Fish/Shellfish Type
Florida
All
Shellfish
Finfish
320
353
7,757
0
0
1
26
43
16
100
100
100
0
0
0
03
03
24
0.14
0.26
0.73
0.56
1.03
2.39
0
1
3
.91
.45
.37
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
7,246
1,212
Group
1,418
3,141
1,695
992
246
563
274
129
1
1
1
1
1
0
1
1
0
0
07
05
20
09
05
89
14
14
95
74
100
100
100
100
100
100
100
100
100
100
0
0
0
0
0
0
0
0
0
0
23
20
24
24
22
22
26
20
16
22
0.68
0.64
0.72
0.70
0.67
0.60
0.76
0.67
0.61
0.54
2.22
2.18
2.54
2.18
2.18
1.96
2.40
2.31
2.09
1.36
o
J
3
3
o
J
3
2
3
3
o
6
i
.18
.03
.44
.21
.17
.50
.72
.13
.06
.03
Exposure Factors Handbook
September 2011
Page
10-125
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-44. Fish Consumption per kg Body Weight, Consumers Only,
Uncooked (g/kg-day) (continued)
State Category Sample
Size
Florida (continued)
Acquisition Method of Fish/Shellfish Eaten
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Habitat
Freshwater
Estuarine
Marine
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
Fish/Shellfish Type
Shellfish
Finfish
Minnesota
All
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
Acquisition Method of Fish/Shellfish Eaten
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Habitat
Freshwater
Estuarine
Marine
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
511
701
6,545
1,426
4,124
6,124
235
458
7,064
3,260
6,428
793
755
593
Group
76
284
312
83
56
232
235
70
38
555
200
593
559
755
38
555
200
Arithmetic
Mean
0.97
2.28
1.06
0.59
0.50
0.99
0.91
2.21
1.11
0.50
1.15
0.44
0.30
0.24
0.39
0.29
0.28
0.30
0.26
0.31
0.21
0.09
0.21
0.53
0.31
0.24
0.04
0.26
0.21
0.53
0.31
Percent
Eating
Fish
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
by State, Acquisition Method,
10th
0.20
0.65
0.23
0.09
0.10
0.20
0.13
0.56
0.24
0.10
0.29
0.06
0.04
0.02
0.05
0.04
0.03
0.03
0.02
0.03
0.03
0.02
0.02
0.11
0.03
0.02
0.00
0.03
0.02
0.11
0.03
Percentiles
50th 90th
0.64
1.48
0.68
0.37
0.31
0.62
0.56
1.40
0.71
0.30
0.73
0.26
0.16
0.09
0.18
0.17
0.15
0.26
0.07
0.10
0.11
0.04
0.11
0.31
0.18
0.09
0.02
0.14
0.11
0.31
0.18
2.14
4.38
2.20
1.36
1.05
2.01
2.14
4.54
2.27
1.07
2.28
0.86
0.73
0.40
0.85
0.63
0.76
0.73
0.65
0.41
0.5
0.19
0.49
0.93
0.75
0.4
0.09
0.67
0.49
0.93
0.75
95th
2.89
6.37
3.08
1.89
1.46
2.94
2.7
6.17
3.24
1.42
3.32
1.44
1.10
0.76
1.44
0.99
1.30
0.87
1.45
0.61
0.86
0.21
0.68
1.76
1.21
0.76
0.16
0.97
0.68
1.76
1.21
Page
10-126
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table
State
10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,
Uncooked (g/kg-day) (continued)
Category Sample
Size
Arithmetic Percent
Mean Eating
Fish
10th
Percentiles
50th 90th
95th
Minnesota (continued)
Fish/Shellfish Type
Shellfish
Finfish
559
791
0.08
0
38
100
100
0.01
0.04
0
0
03
21
0
0
19
77
0.32
1.15
North Dakota
All
546
0.45
100
0.07
0
25
0
99
1.62
Acquisition Method
Bought
Caught
Acquisition Method-Household Income ($)
Bought; 0 to 20,000
Bought; 20,000 to 50,000
Bought; >50,000
Bought; Unknown
Caught; 0 to 20,000
Caught; 20,000 to 50,000
Caught; >50,000
Caught; Unknown
516
389
Group
45
213
210
48
27
142
173
47
0.34
0
18
0.63
0
30
0.28
0
47
0.25
0
15
0.20
0.17
100
100
100
100
100
100
100
100
100
100
0.04
0.02
0.06
0.04
0.04
0.04
0.02
0.02
0.03
0.04
0
0
0
0
0
0
0
0
0
0
15
09
19
15
15
19
10
07
11
08
0
0
2
0
0
0
0
0
0
0
81
46
06
69
64
93
56
33
51
30
1.36
0.61
2.97
1.37
1.05
1.44
0.86
0.54
0.71
0.32
Acquisition Method of Fish/Shellfish Eaten
Habitat
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Freshwater
Estuarine
Marine
30
359
157
389
407
516
0.28
0
52
0.33
0
18
0.04
0
31
100
100
100
100
100
100
0.07
0.10
0.03
0.02
0.01
0.03
0
0
0
0
0
0
18
31
13
09
01
13
0
1
0
0
0
0
43
10
71
46
08
72
0.68
1.66
1.29
0.61
0.14
1.15
Eats Freshwater/Estuarine Caught Fish
Exclusively
Sometimes
Never
30
359
157
0
28
0.52
0
33
100
100
100
0.07
0.10
0.03
0
0
0
18
31
13
0
1
0
43
10
71
0.68
1.66
1.29
Fish/Shellfish Type
Shellfish
Finfish
407
541
* Percentiles cannot be estimated due to small
Notes:
0.07
0
40
100
100
0.01
0.05
0
0
03
21
0
0
17
89
0.27
1.44
sample size.
FL consumption is based on a 7-day recall; CT, MN, and ND consumptions
consumption.
FL consumption excludes away-from-home
Statistics are weighted to represent
consumption by
are based on
rate
of
children < 18.
the general population in the states.
A respondent can be represented in more than one
Source:
Westat, 2006.
row.
Exposure Factors Handbook
September 2011
Page
10-127
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and Sex
(g/kg-day, as-consumed)
Percentiles
State Category
Connecticut
Population for Sample Selection
Anglers
Aquaculture Students
Asians
Commercial Fishermen
EFNEP Participants
General
WIC Participants
Population for Sample Selection and Sex Group
Angler; Males
Angler; Females
Aquaculture Students; Males
Aquaculture Students; Females
Asians; Males
Asians; Females
Commercial Fishermen; Males
Commercial Fishermen; Females
EFNEP Participants; Males
EFNEP Participants; Females
General; Males
General; Females
WIC Participants; Males
WIC Participants; Females
Florida
Population for Sample Selection
General
Population for Sample Selection and Sex Group
General; Males
General; Females
Unknown
Minnesota
Population for Sample Selection
American Indians
Anglers
General
New Mothers
Sample
Size
250
25
396
173
67
420
699
197
53
10
15
188
208
94
79
25
42
201
219
312
387
15,367
7,911
7,426
30
216
1,152
837
401
Arithmetic
Mean
0.64
0.22
1.15
0.65
1.00
0.41
0.80
0.68
0.49
0.21
0.24
1.06
1.24
0.67
0.63
1.05
0.96
0.39
0.43
0.94
0.69
0.47
0.44
0.50
0.41
0.21
0.31
0.31
0.33
Percent
Eating
Fish
97.6
76.0
99.2
96.0
86.6
85.1
79.1
97.5
98.1
90.0
66.7
99.5
99.0
92.6
100
88.0
85.7
86.2
84.0
79.2
79.1
50.5
49.2
51.9
48.0
88.9
96.3
94.4
85.0
10th
0.08
0.00
0.30
0.05
0.00
0.00
0.00
0.08
0.10
0.00
0.00
0.27
0.36
0.05
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.02
0.00
50th
0.40
0.07
0.91
0.44
0.31
0.25
0.42
0.41
0.30
0.09
0.03
0.88
0.92
0.46
0.42
0.33
0.26
0.24
0.28
0.45
0.40
0.06
0.00
0.10
0.00
0.13
0.17
0.18
0.15
90th
1.51
0.65
2.28
1.51
2.46
1.00
1.93
1.68
1.06
0.75
0.62
1.99
2.85
1.54
1.40
2.83
2.02
1.05
0.95
2.30
1.64
1.27
1.22
1.32
1.41
0.52
0.66
0.62
0.80
95th
2.07
0.89
3.15
1.63
3.50
1.32
3.02
2.16
1.45
0.85
0.91
2.44
3.33
1.62
1.93
3.80
3.95
1.34
1.30
3.52
2.43
1.91
1.84
1.98
2.38
0.64
0.97
1.07
1.21
Page
10-128
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and Sex
(g/kg-day, as-consumed) (continued)
Percentiles
State
Category
Sample Arithmetic
Size Mean
Percent
Eating
Fish
10th
50th
90th
95th
Minnesota (continued)
Population for Sample Selection and Sex
North
American Indians; Males
American Indians; Females
Anglers; Males
Anglers; Females
General; Males
General; Females
New Mothers; Males
New Mothers; Females
Dakota
Group
108
108
606
546
419
418
205
196
0
0
0
0
0
0
0
0
19
23
30
31
26
36
27
39
89.8
88.0
96.9
95.6
95.3
93.4
86.3
83.7
0.00
0.00
0.04
0.04
0.02
0.02
0.00
0.00
0
0
0
0
0
0
0
0
14
12
18
17
16
21
15
14
0
0
0
0
0
0
0
0
46
57
63
70
58
65
67
95
0.55
0.93
0.93
1.04
1.06
1.10
0.93
1.42
Population for Sample Selection
American Indians
Anglers
General
Population for Sample Selection and Sex
Notes:
American Indians; Males
American Indians; Females
Anglers; Males
Anglers; Females
General; Males
General; Females
106
854
575
Group
50
56
467
387
276
299
FL consumption is based on a 7-day recall; CT, MN,
consumption.
0
0
0
0
0
0
0
0
0
35
32
32
35
36
32
33
32
32
60.4
94.6
95.2
58.0
62.5
95.3
93.8
96.2
94.2
and ND consumptions
0.00
0.04
0.03
0.00
0.00
0.04
0.03
0.04
0.03
0
0
0
0
0
0
0
0
0
04
19
18
04
05
19
19
19
17
are based on
1
0
0
0
1
0
0
0
0
10
77
71
76
34
77
77
68
73
2.27
1.14
1.18
1.39
2.32
1.14
1.18
1.20
1.16
rate of
FL consumption excludes away-from-home consumption by children <18.
Statistics are weighted to represent the general population in the
unweighted.
EFNEP = Expanded Food and Nutrition
WIC
Source
= USDA's Women, Infants, and
: Westat, 2006.
Education Program.
Children Program.
states. Subpopulations statistics are
Exposure Factors Handbook
September 2011
Page
10-129
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex
(g/kg-day, as-consumed)
Percentiles
State Category
Connecticut
Population for Sample Selection
Angler
Aquaculture Students
Asians
Commercial Fisherman
EFNEP Participants
General
WIC Participants
Population for Sample Selection and Sex Group
Angler; Male
Angler; Female
Aquaculture Students; Male
Aquaculture Students; Female
Asians; Male
Asians; Female
Commercial Fishermen; Male
Commercial Fishermen; Female
EFNEP Participants; Male
EFNEP Participants; Female
General; Male
General; Female
WIC Participants; Male
WIC Participants; Female
Sample Arithmetic Percent
Size Mean Eating
Fish
244
19
393
166
58
362
553
192
52
9
10
187
206
87
79
22
36
175
187
247
306
Population for Sample Selection and Eats Freshwater/Estuarine
Angler; Exclusively
Angler; Sometimes
Angler; Never
Aquaculture Students; Sometimes
Aquaculture Students; Never
Asians; Sometimes
Asians; Never
Commercial Fishermen; Sometimes
Commercial Fishermen; Never
EFNEP Participants; Sometimes
EFNEP Participants; Never
General; Sometimes
General; Never
WIC Participants; Sometimes
WIC Participants; Never
1
190
53
2
17
199
194
120
46
8
50
50
312
67
486
0.66
0.30
1.16
0.68
1.15
0.48
1.01
0.70
0.50
0.23
0.36
1.06
1.25
0.72
0.63
1.20
1.12
0.45
0.52
1.18
0.87
Caught
0.04
0.74
0.38
0.34
0.29
1.23
1.09
0.78
0.41
0.25
1.29
0.46
0.49
1.49
0.95
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Fish Group
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
10th
0.10
0.02
0.31
0.09
0.11
0.07
0.12
0.10
0.11
0.01
0.03
0.28
0.37
0.12
0.06
0.14
0.07
0.08
0.05
0.12
0.12
*
0.14
0.05
*
0.02
0.30
0.34
0.18
0.03
0.14
0.09
0.09
0.07
0.28
0.10
50th
0.40
0.14
0.91
0.46
0.39
0.32
0.61
0.42
0.33
0.11
0.31
0.88
0.93
0.54
0.42
0.42
0.39
0.29
0.34
0.69
0.59
*
0.44
0.27
0.21
0.14
0.93
0.87
0.54
0.30
0.22
0.52
0.29
0.32
0.91
0.60
90th
1.55
0.75
2.28
1.53
2.69
1.09
2.30
1.69
1.07
0.74
0.75
1.99
2.86
1.57
1.40
2.89
2.38
1.11
1.03
2.89
1.87
*
1.69
0.89
*
0.80
2.94
2.03
1.58
0.89
0.40
2.82
1.10
1.06
3.43
2.02
95th
2.07
0.91
3.16
1.65
4.51
1.37
3.39
2.17
1.45
*
1.00
2.44
3.34
1.63
1.91
3.75
4.50
1.40
1.35
3.78
2.73
*
2.18
1.00
*
0.93
3.50
2.39
1.98
1.36
*
6.09
1.25
1.41
5.12
3.12
Page
10-130
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-46. Fish Consumption per kg, Consumers
(g/kg-day, as-consumed)
Only, by State, Subpopulation, and Sex
(continued)
Percentiles
State Category
Florida
Population for Sample Selection
General
Population for Sample Selection and Sex Group
General; Male
General; Female
Unknown
Sample Arithmetic
Size Mean
7,757
3,880
3,861
16
Population for Sample Selection and Eats Freshwater/Estuarine
General; Exclusively
General; Sometimes
General; Never
Minnesota
Population for Sample Selection
American Indian
Anglers
General
New Mothers
Population for Sample Selection and Sex Group
American Indians; Male
American Indians; Female
Anglers; Male
Anglers; Female
General; Male
General; Female
New Mothers; Male
New Mothers; Female
235
458
7,064
192
1,109
793
341
97
95
587
522
401
392
177
164
Population for Sample Selection and Eats Freshwater/Estuarine
American Indians; Exclusively
American Indians; Sometimes
American Indians; Never
Anglers; Exclusively
Anglers; Sometimes
Anglers; Never
General; Exclusively
General; Sometimes
General; Never
New Mothers; Exclusively
New Mothers; Sometimes
New Mothers; Never
31
136
25
57
879
173
38
555
200
17
189
135
0.93
0.90
0.95
0.85
Caught
0.71
1.73
0.88
0.24
0.32
0.33
0.38
0.21
0.26
0.31
0.33
0.28
0.38
0.31
0.46
Caught
0.18
0.28
0.05
0.35
0.34
0.20
0.16
0.40
0.23
0.06
0.47
0.30
Percent
Eating
Fish
100
100
100
100
Fish Group
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Fish Group
100
100
100
100
100
100
100
100
100
100
100
100
10th
0.19
0.18
0.19
0.12
0.10
0.43
0.18
0.02
0.05
0.04
0.04
0.03
0.02
0.05
0.05
0.04
0.05
0.04
0.05
0.01
0.05
0.01
0.02
0.07
0.03
0.02
0.08
0.02
0.02
0.07
0.03
50th
0.58
0.55
0.62
0.69
0.42
1.10
0.56
0.15
0.18
0.20
0.20
0.15
0.16
0.18
0.18
0.17
0.22
0.19
0.21
0.07
0.18
0.04
0.16
0.20
0.10
0.08
0.23
0.14
0.09
0.27
0.12
90th
1.89
1.85
1.94
2.37
1.60
3.44
1.81
0.53
0.67
0.65
0.89
0.49
0.59
0.63
0.72
0.62
0.70
0.75
1.04
0.42
0.57
0.12
0.89
0.71
0.46
0.37
0.70
0.56
0.20
1.00
0.74
95th
2.73
2.65
2.78
2.61
2.16
4.96
2.60
0.70
0.99
1.08
1.30
0.55
0.95
0.93
.05
.07
.22
.06
.83
0.55
0.92
0.15
1.93
1.05
0.66
0.51
1.32
0.91
0.25
1.32
1.35
Exposure Factors Handbook Page
September 2011 10-131
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-46. Fish Consumption per kg, Consumers
(g/kg-day, as-consumed)
Only, by State, Subpopulation
(continued)
, and Sex
Percentiles
State
Category
Sample Arithmetic Percent
Size Mean Eating
Fish
10th
50th
90th
95th
North Dakota
Population for Sample Selection
American Indians
Anglers
General
64
808
546
0.58
0
34
0.34
100
100
100
0.03
0.05
0.05
0
0
0
19
20
19
1
0
0
.75
.81
.74
2.65
1.17
1.21
Population for Sample Selection and Sex Group
American Indians; Male
American Indians; Female
Anglers; Male
Anglers; Female
General; Male
General; Female
29
35
445
363
265
281
0.60
0
0
57
33
0.35
0
33
0.34
Population for Sample Selection and Eats Freshwater/Estuarine
American Indians; Exclusively
American Indians; Sometimes
American Indians; Never
Anglers; Exclusively
Anglers; Sometimes
Anglers; Never
General; Exclusively
General; Sometimes
General; Never
* Percentiles cannot be estimated due to small
Notes:
4
30
30
47
660
101
30
359
157
sample
100
100
100
100
100
100
0.03
0.02
0.05
0.05
0.04
0.05
0
0
0
0
0
0
18
19
20
21
20
18
1
2
.31
.25
0.78
0.83
0
0
.74
.74
3.67
2.55
1.14
1.29
1.22
1.20
Caught Fish Group
0.05
1
0
08
16
0.19
0
38
0.18
0
0
0
size.
21
39
25
100
100
100
100
100
100
100
100
100
FL consumption is based on a 7-day recall; CT, MN, and ND consumptions
* 0.05 * *
0.13
0.02
0.01
0.07
0.02
0.05
0.07
0.03
0
0
60
07
0.07
0
0
0
0
0
23
10
14
23
10
are based on
2
0
.65
.36
0.61
0
0
0
0
0
rate
.84
.41
.33
.82
.53
of
3.62
0.66
1.02
1.29
0.53
0.51
1.25
0.97
consumption.
FL consumption excludes away-from-home consumption by
Source:
Statistics are weighted to represent the
unweighted.
Westat, 2006.
general
population in
children < 18.
the states. Subpopulations statistics are
Page Exposure Factors Handbook
10-132 September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-47. Fish Consumption Among General Population in Four States,
(g/kg-day, as-consumed)
N
1\
IVTpiiTi
IVlCcul
Consumers Only
Percentiles
10th
25th
50th
75th
90th
95*
IVTn vi vni i in
IVldAllllUlll
Connecticut
1 to <6 years
6 to <11 years
11 to < 16 years
16 to <30 years
Females
Males
30 to <50 years
Females
Males
>50 years
Females
Males
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Anglers
General Population
14
22
18
14
10
74
74
70
57
1
70
291
244
362
0.61
0.59
0.32
0.84
0.23
0.53
0.51
0.48
0.38
0.01
0.49
0.48
0.66
0.48
0.42-0
81
0.040-0.77
0.17-0
0.10-1
46
58
0.14-0.32
0.37-0
0.40-0
0.37-0
0.30-0
-
0.36-0
0.40-0
-
-
70
61
59
46
61
57
0.16
0.14
0.07
0.11
0.08
0.05
0.11
0.05
0.10
-
0.10
0.06
0.10
0.07
0.26
0.23
0.14
0.30
0.13
0.15
0.18
0.13
0.17
-
0.17
0.16
0.20
0.16
0.55
0.47
0.19
0.35
0.21
0.34
0.35
0.37
0.26
-
0.34
0.32
0.40
0.32
0.83
0.96
0.38
0.87
0.25
0.67
0.70
0.72
0.50
-
0.75
0.61
0.80
0.63
1.4
1.2
0.52
1.1
0.47
1.1
1.2
1.0
0.93
-
1.1
1.1
1.6
1.1
1.6
1.3
0.84
3.1
0.56
1.5
1.5
1.4
1.1
-
1.3
1.4
2.1
1.4
1.6
1.5
1.3
7.0
0.58
4.5
2.2
2.7
1.4
0.01
2.2
7.0
3.5
2.4
Florida
1 to <6 years
6 to <11 years
11 to <16 years
16 to <30 years
Females
Males
30 to <50 years
Females
Males
>50 years
Females
Males
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
420
375
365
753
754
1,287
1,334
1,171
1,192
511
701
6,545
2.3
1.1
0.85
0.89
0.96
0.94
0.81
0.73
0.70
0.76
1.8
0.85
2.05-2
0.98-1
0.73-0
0.74-1
0.80-1
0.87-1
0.74-0
0.69-0
0.66-0
0.66-0
1.6-2
0.81-0
63
22
98
04
12
00
88
77
75
86
1
89
0.5
0.28
0.20
0.16
0.16
0.18
0.17
0.19
0.17
0.15
0.50
0.18
1.0
0.52
0.36
0.31
0.28
0.33
0.28
0.31
0.27
0.30
0.76
0.30
1.7
0.81
0.63
0.55
0.52
0.63
0.53
0.52
0.50
0.50
1.2
0.54
2.8
1.4
0.99
0.95
0.99
1.0
0.95
0.94
0.84
0.90
2.0
0.98
4.7
2.2
1.6
1.8
1.8
1.9
1.7
1.5
1.4
1.7
3.4
1.8
6.8
3.0
2.2
2.4
2.7
2.7
2.4
2.1
1.9
2.3
5.1
2.5
14.6
9.4
11.0
25
34
20
23
7.4
14
7.4
34
24
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-47. Fish Consumption Among General Population Children in Four States, Consumers
(g/kg-day, as-consumed) (continued)
Af
1\
JVlCclIl
Percentiles
10th
25th
50th
75th
90th
95*
Only
Maximum
Minnesota
1 to <6 years
6 to <11 years
11 to < 16 years
16 to <30 years
Females
Males
30 to <50 years
Females
Males
>50 years
Females
Males
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Anglers
General Population
46
42
63
44
52
127
115
150
153
38
555
200
1,109
793
0.58
0.38
0.24
0.69
0.11
0.25
0.25
0.36
0.24
0.16
0.40
0.23
0.32
0.33
0.32-0
0.21-0
0.16-0
-0.21-1
0.07-0
0.21-0
0.17-0
0.26-0
0.20-0
0.05-0
0.27-0
0.18-0
-
-
85
54
31
.59
15
30
32
46
29
26
52
28
0.07
0.05
0.03
0.02
0.02
0.04
0.07
0.05
0.05
0.02
0.08
0.02
0.05
0.04
0.15
0.07
0.06
0.08
0.02
0.10
0.11
0.11
0.11
0.03
0.11
0.05
0.10
0.10
0.46
0.25
0.21
0.16
0.08
0.23
0.17
0.22
0.19
0.08
0.23
0.14
0.18
0.20
0.73
0.47
0.32
0.29
0.14
0.32
0.30
0.38
0.28
0.25
0.49
0.26
0.34
0.34
1.1
1.0
0.55
0.66
0.27
0.51
0.42
0.93
0.53
0.37
0.70
0.56
0.67
0.65
1.8
1.4
0.59
3.0
0.33
0.58
0.64
1.4
0.68
0.51
1.3
0.91
0.99
1.1
8.0
5.3
1.4
9.2
0.74
1.3
1.9
1.9
1.3
0.57
9.2
8.0
2.2
1.8
North Dakota
1 to <6 years
6 to <11 years
11 to <16 years
16 to <30 years
Females
Males
30 to <50 years
Females
Males
>50 years
Females
Males
Eats Caught Only
Eats Caught and Bought
Eats Bought Only
Anglers
General Population
N = Sample size.
28
41
53
38
36
93
88
92
76
30
359
157
808
546
0.70
0.56
0.41
0.20
0.22
0.29
0.22
0.40
0.31
0.21
0.39
0.25
0.34
0.34
0.24-1
0.31-0
0.23-0
0.14-0
0.13-0
0.22-0
0.17-0
0.27-0
0.20-0
0.09-0
0.29-0
0.13-0
-
-
17
81
59
26
31
36
27
54
41
32
49
36
0.05
0.11
0.06
0.04
0.04
0.05
0.05
0.06
0.04
0.05
0.07
0.03
0.05
0.05
0.12
0.21
0.12
0.06
0.07
0.10
0.08
0.10
0.08
0.09
0.13
0.05
0.10
0.09
0.23
0.30
0.22
0.15
0.13
0.18
0.18
0.17
0.19
0.14
0.23
0.10
0.20
0.19
0.68
0.66
0.54
0.26
0.23
0.36
0.26
0.52
0.33
0.22
0.43
0.24
0.39
0.35
1.6
1.2
1.0
0.41
0.45
0.56
0.45
1.1
0.74
0.33
0.82
0.53
0.81
0.74
3.8
1.5
1.3
0.67
0.56
0.87
0.54
1.5
1.2
0.51
1.3
0.97
1.2
1.2
6.8
4.3
2.3
0.80
1.9
2.6
1.3
4.2
1.8
1.8
4.3
6.8
2.0
2.2
CI = Confidence interval.
Source: Moya et al., 2008.
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Chapter 10—Intake of Fish and Shellfish
Table 10-48.
Estimated Number of Participants in Marine Recreational Fishing by State and Subregion
Coastal Non-Coastal
Subregion
Pacific
North Atlantic
Mid-Atlantic
South Atlantic
Gulf of Mexico
State
Southern California
Northern California
Oregon
TOTAL
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
TOTAL
Delaware
Maryland
New Jersey
New York
Virginia
TOTAL
Florida
Georgia
North Carolina
South Carolina
TOTAL
Alabama
Florida
Louisiana
Mississippi
TOTAL
GRAND TOTAL
Participants Participants
902
534
265
1,701
186
93
377
34
97
787
90
540
583
539
294
1,046
1,201
89
398
131
1,819
95
1,053
394
157
1,699
8,053
a Not additive across states. One person can be counted as
b An asterisk (*) denotes no non-coastal counties in state.
Source: NMFS,
1993.
8
99
19
126
#b
9
69
10
*
88
*
32
9
13
29
83
*
61
224
77
362
9
*
48
42
99
760
"OUT OF
Total
Out of State3 Participants3
159
63
78
47
100
273
32
157
159
268
433
70
131
741
29
745
304
101
1,349
63
51
STATE" for more than one
910
633
284
186
102
446
44
97
90
572
592
552
323
1,201
150
622
208
104
1,053
442
200
state.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-49. Estimated Weight of Fish Caught (Catch Type A and Bl) by Marine Recreational Fishermen,
by Wave and Subregion
Jan/Feb
Mar/Apr
May/Jun
Jul/Aug
Sep/Oct
Nov/Dec
Source: NMFS,
Atlantic
Region
South Atlantic
Gulf
TOTAL
North Atlantic
Mid-Atlantic
South Atlantic
Gulf
TOTAL
North Atlantic
Mid-Atlantic
South Atlantic
Gulf
TOTAL
North Atlantic
Mid-Atlantic
South Atlantic
Gulf
TOTAL
North Atlantic
Mid-Atlantic
South Atlantic
Gulf
TOTAL
North Atlantic
Mid-Atlantic
South Atlantic
Gulf
TOTAL
GRAND TOTAL
1993.
and Gulf
Weight (1,000 kg)
1,060
3,683
4,743
310
1,030
1,913
3,703
6,956
3,272
4,815
4,234
5,936
18,257
4,003
9,693
4,032
5,964
23,692
2,980
7,798
3,296
7,516
21,590
456
1,649
2,404
4,278
8,787
84,025
Pacific
Region Weij
So. California
N. California
Oregon
TOTAL
So. California
N. California
Oregon
TOTAL
So. California
N. California
Oregon
TOTAL
So. California
N. California
Oregon
TOTAL
So. California
N. California
Oregon
TOTAL
So. California
N. California
Oregon
TOTAL
GRAND TOTAL
?ht (1,000 kg)
418
101
165
684
590
346
144
1,080
1,195
563
581
2,339
1,566
1,101
39
2,706
859
1,032
724
2,615
447
417
65
929
10,353
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-50. Average Daily Intake (g/day)
of Marine Finfish, by Region and Coastal Status
Intake Among Anglers
Region3
North Atlantic
Mid-Atlantic
South Atlantic
All Atlantic
Gulf
Southern California
Northern California
Oregon
All Pacific
North Atlantic— ME, NH, MA
NC, SC, GA, and FL (Atlantic
Source: NMFS, 1993.
Mean
6.2
6.3
4.7
5.6
7.2
2.0
2.0
2.2
2.0
, RI, and CT;
95th Percentile
20.1
18.9
15.9
18.0
26.1
5.5
5.7
8.9
6.8
Mid- Atlantic— NY, NJ, MD, DE, and VA; South Atlantic—
Coast); Gulf— AL, MS, LA, and FL (Gulf Coast).
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Chapter 10—Intake of Fish and Shellfish
Table 10-51. Estimated Weight of Fish Caught (Catch Type A and Bl)a by Marine Recreational Fishermen, by Species
Group and Subregion
Cartilaginous Fishes
Eels
Herrings
Catfishes
Toadfishes
Cods and Hakes
Searobins
Sculpins
Temperate Basses
Sea Basses
Bluefish
Jacks
Dolphins
Snappers
Grunts
Porgies
Drums
Mullets
Barracudas
Wrasses
Mackerels and Tunas
Flounders
Triggerfishes/Filefishes
Puffers
Other fishes
Species Group
Cartilaginous fish
Sturgeons
Herrings
Anchovies
Smelts
Cods and Hakes
Silversides
Striped Bass
Sea Basses
Jacks
Croakers
Sea Chubs
Surfperches
Pacific Barracuda
Wrasses
Tunas and Mackerels
Rockfishes
California Scorpionfish
Sablefishes
Greenlings
Sculpins
Flatfishes
Other fishes
North Atlantic
(1,000 kg)
66
14
118
0
0
2,404
2
1
837
22
4,177
0
65
0
0
132
3
1
0
783
878
512
0
*
105
Southern California
(1,000kg)
35
Ob
10
*c
0
0
58
0
1,319
469
141
53
74
866
73
1,260
409
86
0
22
6
106
89
Mid-Atlantic
(1,000 kg)
1,673
9
69
306
7
988
68
*
2,166
2,166
3,962
138
809
*
9
417
2,458
43
*
1,953
3,348
4,259
48
16
72
Northern California
(1,000 kg)
162
89
15
7
71
0
148
51
17
17
136
1
221
10
5
36
1,713
0
0
492
81
251
36
South Atlantic
(1,000 kg)
162
*b
1
138
0
4
*
0
22
644
1,065
760
2,435
508
239
1,082
2,953
382
356
46
4,738
532
109
56
709
Oregon
(1,000 kg)
1
13
40
0
0
0
0
0
0
1
0
0
47
0
0
1
890
0
5
363
44
5
307
Gulf
(1,000 kg)
318
Oc
89
535
*
0
*
0
4
2,477
158
2,477
1,599
3,219
816
2,629
9,866
658
244
113
4,036
377
544
4
915
All Atlantic and Gulf
(1,000 kg)
2,219
23
177
979
7
1,396
70
1
2,229
5,309
5,362
3,375
4,908
3,727
1,064
4,160
15,280
1,084
600
2,895
13,000
5,680
701
76
1,801
All Pacific
198
102
65
7
71
0
206
51
1,336
487
277
54
342
876
78
1,297
3,012
86
5
877
131
362
432
a For Catch Type A and Bl, the fish were not thrown back.
b An asterisk (*) denotes data not reported.
Zero (0) = < 1,000 kg.
Source: NMFS, 1993
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Chapter 10—Intake of Fish and Shellfish
Table 10-52. Percent of Fishing
Fishing Frequency
Daily
Weekly
Monthly
Bimonthly
Biyearly
Yearly
Frequency During the Summer and Fall Seasons in
Washington
Frequency Percent Frequency Percent
in the Summer3 in the Fallb
10.4 8.3
50.3 52.3
20.1 15.9
6.7 3.8
4.4 6.1
8.1 13.6
Commencement Bay,
Frequency Percent
in the Fair
5.8
51.0
21.1
4.2
6.3
11.6
3 Summer — July through September, includes 5 survey days and 4 survey areas (i.e., Areas #1, #2, #3, and
#4)
b Fall — September through November, includes 4 survey days and 4 survey areas (i.e., Areas #1, #2, #3, and
#4)
0 Fall — September through November, includes 4 survey days described in footnote b plus an additional
survey area (5 survey areas) (i.e., Areas #1, #2, #3, #4, and #5)
Source: Pierce etal., 1981.
Table 10-53. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler Populations
Based on the Re-Analysis of the Puffer et al. (1981) and Pierce et al. (1981) Data
Survey Population
Puffer etal. (1981)
Pierce etal. (1981)
Average
Total Angler Population
Puffer etal. (1981)
Pierce etal. (1981)
Average
3 Estimated based on the averag
b Estimated based on the averag
Source: Price etal., 1994.
50th Percentile
37
19
28
2.93
1.0
2.0
s intake for the 0-90* percentile anglers.
s intake for the 91st-96th percentile anglers.
90th Percentile
225
155
190
35b
13
24
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-54. Median Intake Rates
Ethnic Group
Caucasian
Black
Mexican American
Asian/Samoan
Other
Age (years)
<17
18 to 40
41 to 65
>65
a Not reported.
Source: Puffer etal, 1981.
Based on Demographic Data of Sport
Group
Percent of total interviewed
42
24
16
13
5
11
52
28
9
Fishermen and Their Family/Living
Median intake rates
(g/person-day)
46.0
24.2
33.0
70.6
a
27.2
32.5
39.0
113.0
Table
10-55. Cumulative
Distribution of Total Fish/Shellfish Consumption by Surveyed Sport Fishermen
in the Metropolitan Los Angeles Area
Percentile Intake rate (g/person-day)
Source:
5
10
20
30
40
50
60
70
80
90
95
Puffer etal., 1981.
2.3
4.0
8.3
15.5
23.9
36.9
53.2
79.8
120.8
224.8
338.8
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10-140 September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-56.
Species
White Croaker
Pacific Mackerel
Pacific Bonito
Queenfish
Jacksmelt
Walleye Perch
Shiner Perch
Opaleye
Black Perch
Kelp Bass
California Halibut
Shellfish3
Catch Information for Primary Fish
by Sport Fishermen (N= 1,059)
Species Kept
Average Weight Percent of Fishermen
(Grams) who Caught
153
334
717
143
223
115
54
307
196
440
1,752
421
34
25
18
17
13
10
7
6
5
5
4
3
a Crab, mussels, lobster, abalone.
Source: Modified from Puffer et al., 1981.
Table 10-57. Fishing and Crabbing Behavior of Fishermen at Humacao,
Puerto Rico
Mean ± Standard Error
Crabbing
Number of interviews
Number of people in group
Number of adults (>21 years)
Visits to site/month
No. crabs caught per season
Crabs/hour
Crabs eaten/week
Range in no. eaten/week
Fishing
Number of interviews
Number of people in group
Number of adults (>21 years)
Visits to site/month
No. fish caught per season
Fish/hour
Fish eaten/week
Range in no. eaten/week
20
3.5 ±0.4
2.3 ±0.3
3.8 ±0.7
21.4 ±4.7
21.6 ±4.9
13.3 ±2.3
0-25
25
2.9 ±0.3
2.3 ±0.2
2.8 ±0.4
16.9 ±3.5
11.3 ±2.5
6.8 ±0.7
3-30
Source: Burger and Gochfeld, 1991.
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-58. Fish Consumption
All respondents
Sex
Males
Females
Age (years)
Oto9
10 to 19
20 to 29
30 to 39
40 to 49
50 to 59
60 to 69
70 to 79
80 to 89
Race
African American
Asian
Hispanic
Caucasian
TV = Sample size.
SE = Standard error.
of Delaware Recreational Fishermen and
N
867
496
369
73
102
95
148
144
149
124
28
4
81
12
12
748
Mean consumption
(g/day)
17.5
18.6
15.9
6.0
11.4
11.7
18.1
12.6
28.6
23.0
21.8
53.9
14.9
5.6
3.0
18.2
Their Households
SE (%)
5.3
6.6
8.7
13.4
16.8
10.9
13.9
8.5
11.1
12.4
33.4
68.3
27.1
31.2
35.2
5.3
Source: KCA Research Division, 1994.
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Chapter 10—Intake of Fish and Shellfish
Table 10-59. Seafood Consumption Rates of All Fish by Ethnic and Income Groups of Santa
Monica Bay
Consumption (g/day)
Category
All respondents
Ethnicity
White
Hispanic
Black
Asian
Other
Income
<$5,000
$5,000 to $10,000
$10,000 to $25,000
$25,000 to $50,000
>$50,000
N
555
217
137
57
122
14
20
27
90
149
130
Mean
49.6
58.1
28.2
48.6
51.1
137.3
42.1
40.5
40.4
46.9
58.9
95% CI
9.3
19.1
5.9
18.9
18.7
92.2
18.0
29.1
9.3
10.5
20.6
50*
21.4
21.4
16.1
24.1
21.4
85.7
32.1
21.4
21.4
21.4
21.4
90th
107.1
112.5
64.3
85.7
115.7
173.6
64.3
48.2
80.4
113.0
128.6
N = Sample size.
CI = Confidence interval.
Source: Santa Monica Bay
Restoration Project,
1994.
Table 10-60. Means and Standard Deviations of Selected Characteristics by Population Groups in
Everglades, Florida
Variables
(Na = 330)
Age (years)
Sex
Female
Male
Race/ethnicity
Black
White
Hispanic
Number of Years Fished
Number Per Week Fished in Past 6 Months of Survey Period
Number Per Week Fished in Last Month of Survey Period
Aware of Health Advisories
a N= Number of respondents who reported consuming fish.
b SD = Standard deviation.
Source: U.S. DHHS, 1995.
Mean±SDb
38.6 ±18.8
38%
62%
46%
43%
11%
15.8 ±15.8
1.8 ±2.5
1.5 ±1.4
71%
Range
2 to 81
-
-
-
-
-
0-70
0-20
0-12
-
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Chapter 10—Intake of Fish and Shellfish
Table 10-61. Grams per Day of Self-Caught
Cohort
Mean
Fish Consumed by Recreational Anglers — Alcoa/Lavaca
Bay
95% Upper Confidence
Limit on Mean
90th or 95th Percentile of
Distribution3
Finfish
Adult men
Adult women
Women of childbearing age
Small children
Youths
24.8
17.9
18.8
11.4
15.6
27.7
19.7
22.1
14.2
17.8
68.1
47.8
45.4
30.3
45.4
Shellfish
Adult men
Adult women
Women of childbearing age
Small children
Youths
1.2
0.8
0.9
0.4
0.7
a For shellfish, the 95th percentile value
consumed shellfish, resulting in a 90th
Source: Alcoa, 1998.
1.6
1.1
1.2
0.6
1.0
5.1
2.4
4.0
2.0
4.5
is provided because less than 90% of the individuals
percentile of zero.
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Chapter 10—Intake of Fish and Shellfish
Table 10-62. Number of Meals
and Portion
Sizes of Self-Caught Fish
Lavaca Bay, Texas
Consumed
Number of Meals
Age Group
95% Upper
Mean Confidence
Limit on Mean
Mean
by Recreational Anglers
Portion Size
(ounces)3
95% Upper
Confidence Limit
on Mean
Finfish
Adult Men
Adult Women
Women of Childbearing Age
Small children (<6 years)
Youths (6 to 19 years)
3.2
2.6
2.8
2.6
2.4
3.5
3.0
3.2
3.1
2.7
8.0
6.8
6.8
4.5
6.6
8.2
7.1
7.3
4.7
6.9
Shellfish
Adult Men
Adult Women
Women of Childbearing Age
Small children (<6 years)
Youths (6 to 19 years)
a Converted from ounces;
Source: Alcoa, 1998.
0.3
0.3
0.3
0.3
0.3
1 ounce = 28
0.4
0.4
0.5
0.5
0.4
.35 grams.
3.7
2.9
3.3
2.0
2.5
4.3
3.4
4.3
2.4
2.9
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-63. Consumption Patterns of People
N
% Eat fish
% Give away fish
% Eat crabs
% Give away crabs
Number of times fish eaten/month
% Eaten that are self-caught
Number of times crabs eaten/month
Average serving size (ounces)
Average consumption (males and females)
(g/day)
N = Sample size.
Source: Burger etal, 1998.
Fishing and Crabbing in
Males
434
84.1
55.0
87.9
48.2
5.21 ±0.33
48.7 ±2.15
2.14 ±0.32
10.12 ±0.32
48.3
Barnegat Bay, New Jersey
Females
81
78.05
41.2
94.7
53.1
5.21 ±0.33
48.7 ±2.15
2.14 ±0.32
10.12 ±0.32
Table 10-64. Fish Intake Rates of Members of the Laotian
California
Group
All respondents
Fish consumers3
a "Fish consumers"
Max = Maximum.
Min = Minimum.
Source: Chiang, 1998.
Sample Size
229
199
were those who
Mear
18.3
21.4
reported
Community of West Contra Costa
Consumption (g/day)
Percentile
1 a n n 1V1C1A.
50th 90th 95th
9.1
9.1
42.5 85.1 182.3
42.5 85.1
County,
Min
1.5
consumption offish at least once a month.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-65. Consumption Rates (g/day) Among Recent Consumers" by Demographic Factor
Percentiles
Overall
Sex
Male
Female
Age (years)
18 to 45
46 to 65
65 and older
Ethnicity
African American
Asian-Chinese
Asian-Filipino
Asian-Other
Asian-Pacific Islander
Asian- Vietnamese
Hispanic
Caucasian
Education
<12* Grade
HS/GED
Some college
>4 years college
Annual income
<$20,000
$20,000 to $45,000
>$45,000
Season
Winter
Spring
Summer
Fall
N
465
410
35
256
148
43
41
26
70
31
12
51
52
158
73
142
126
94
101
119
180
70
76
189
130
Mean
23.0
22.7
22.3
24.2
21.0
21.8
26.7
27.8
32.7
22.0
38.0
21.8
22.0
18.9
24.2
21.5
nn
25.0
21.9
21.7
25.3
19.4
22.1
23.9
24.4
SD
32.1
32.3
26.8
32.2
32.9
24.4
38.3
34.8
48.8
27.6
44.2
20.7
29.5
27.0
28.7
28.0
29.0
42.1
27.8
32.9
35.3
28.2
37.6
30.6
32.1
10*
4
4
6
5
4
4
8
4
5
4
4
4
4
4
4
4
5
4
4
4
5
4
4
7
5
0
0
0
-,
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
9
4
50*
16.0
16.0
16.0
12.0
16.0
16.0
16.0
12.0
16.0
8.0
24.0
16.0
16.0
10.7
16.0
12.0
16.0
12.0
8.0
8.0
8.0
8.0
8.0
16.0
16.0
90
48
48
53
48
32
64
48
80
72
72
96
48
48
36
48
48
45
53
48
40
56
48
40
48
64
th
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
95*
80.0
72.0
84.0
84.0
64.0
72.0
6.04
128.0
176.0
72.0
184.0
72.0
84.0
56.0
64.0
72.0
84.0
96.0
72.0
56.0
108.0
80.0
144.0
72.0
96.0
a Recent consumers are defined in the study as anglers who report consuming fish caught from San
Francisco Bay in the 4 weeks prior to the date they were interviewed. Recent consumers are a
subset of the overall consumer group.
N = Sample size.
SD = Standard deviation.
HS/GED= High school/general education development.
Source: SFEI, 2000.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-66. Mean + SD Consumption Rates for Individuals Who Fish or Crab in the Newark Bay Area
Sample size
Number of times per month consuming
Serving size
Number of crabs
Fish or crabs (grams) (crabs assumed to weigh
70 grams each)
Monthly consumption (g/month)
Number of months per year fishing and/or
crabbing
Yearly consumption (g/year)
Average daily consumption (g/day)a
a Estimated by U.S. EPA by dividing yearly
SD = Standard deviation.
Note: Sample size is slightly different from that
Source: Burger, 2002a.
People that
crab
110
3.39 + 0.42
6.15 + 0.85
439 + 61.2
1,980 + 561
3.31+0.13
5,760 + 1,360
15.8 + 3.7
consumption rate
People that People that both crab and fish
fish Crab values
111
4.06 + 0.76
-
331+42.1
1,410 + 266
4.92 + 0.33
8,120+2,040 6
22.2 + 5.6
by 365 days/year.
33
2.96+0.45
7.27+0.91
509 + 63.8
1,620 + 330
3.5 + 0.37
,230 + 1,790
17.1+4.9
Fish values
33
3.56 + 0.66
-
428 + 57.6
1,630 + 358
7.24 + 0.74
13,600 + 3,480
37.3 + 9.5
reported in the text of Burger (2002a).
Table 10-67. Consumption Rates (g/day) for Marine Recreational
King County, WA
Location
Marine Fish Consumption
Duwamish River3
Elliott Bay
North King County
All Locations
Shellfish Consumption
Duwamish River3
Elliott Bay
North King County
All Locations
Sample , ,
„. r Mean
Size
50
377
67
494
16
49
31
96
a The Duwamish River is tidally
species; therefore, data
SD = Standard deviation.
SE = Standard error.
Source: Mayfield et al., 2007.
8
63
32
53
20
28
22
25
influenced by
SD
13
91
40
83
33
33
33
33
Elliott Bay,
SE
2
5
5
4
8
5
6
3
and anglers
Anglers in
Percentiles
50th
2
31
17
21
4
14
12
11
caught
90th
23
145
85
121
77
74
62
60
marine
95*
42
221
102
181
123
119
132
119
for these locations were considered to represent marine locations.
Page
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-68. Percentile and Mean Intake Rates for Wisconsin Sport Anglers (all respondents)
Percentile
25th
50th
75th
90th
95*
98th
100th
Mean
Source: Raw data
Annual Number of Sport-Caught Meals
4
10
25
50
60
100
365
18
on sport-caught meals from Fiore et al., 1989. U.S.
Intake Rate of Sport-Caught Meals (g/day)
2.6
6.2
15.5
31.3
37.2
62.1
227
11.2
EPA calculated distributions of intake rates
using a value of 227 grams per fish meal.
Table 10-69. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households with
Recreational Fish Consumption
Group
All household members
Respondents (i.e., licensed
anglers)
Age groups (years)
Ito5
6 to 10
11 to 20
21 to 40
41 to 60
61 to 70
71 to 80
80+
N = Sample size.
Source: U.S. EPA analysis
All Fish
meals/week
0.686
0.873
0.463
0.49
0.407
0.651
0.923
0.856
1.0
0.8
using data from
Recreational
Fish
meals/week N
0.332
0.398
0.223
0.278
0.229
0.291
0.42
0.431
0.622
0.6
West et al.,
2,196
748
121
151
349
793
547
160
45
10
1989.
Total Total
Fish Recreational Fish
g/day Fish g/day g/kg-day
21.9
29.4
11.4
13.6
12.3
22
29.3
28.2
32.3
26.5
11.0
14.0
5.63
7.94
7.27
10.2
14.2
14.5
20.1
20
0.356
0.364
0.737
0.481
0.219
0.306
0.387
0.377
0.441
0.437
Recreational
Fish
g/kg-day
0.178
0.168
0.369
0.276
0.123
0.139
0.186
0.193
0.271
0.345
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September 2011
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Chapter 10—Intake of Fish and Shellfish
Table 10-70. Comparison
Usual Fish Consumption
Frequency Category
Almost daily
2 to 4 times a week
Once a week
2 to 3 times a month
Once a month
Less often
of 7-Day Recall and Estimated Seasonal
Mean Fish Meals/Week
7-day Recall Data
no data
1.96
1.19
0.840 (3.6 times/month)
0.459 (1.9 times/month)
0.306 (1.3 times/month)
Frequency for Fish Consumption
Usual Frequency Value Selected
for Data Analysis (times/week)
4 (if needed)
2
1.2
0.7 (3 times/month)
0.4 (1.7 times/month)
0.2 (0.9 times/month)
Source: U.S. EPA analysis using data from West et al., 1989.
Table 10-71. Distribution
of Usual Fish Intake Among Survey Main Respondents Who Fished and
Consumed Recreationally Caught Fish
Recreational
All Fish
Fish
Meals/Week Meals/Week
N
Mean
10%
25%
50%
75%
90%
95%
N
Source:
738
0.859
0.300
0.475
0.750
1.200
1.400
1.800
= Sample size.
U.S. EPA analysis usinj
738
0.447
0.040
0.125
0.338
0.672
1.050
1.200
All Fish Intake
g/day
738
27.74
9.69
15.34
24.21
38.74
45.20
58.11
Recreational
Fish Intake
g/day
738
14.42
1.29
4.04
10.90
21.71
33.90
38.74
All Fish Intake
g/kg-day
726
0.353
0.119
0.187
0.315
0.478
0.634
0.747
Recreational
Fish Intake
g/kg-day
726
0.1806
0.0159
0.0504
0.1357
0.2676
0.4146
0.4920
; data from West et al., 1989.
Page
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-72. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989-1990 Ice
Fishing or 1990 Open-Water Seasons"
Intake Rates (g/day)
All Waters Rivers and Streams
All Anglers0 Consuming Anglersd River Anglers6 Consuming Anglersd
Percentile Rankings (N= 1,369) (N= 1,053) (AT =741) (N=464)
50th (median)
66th
75th
90th
95th
Arithmetic Meanf
1.1
2.6
4.2
11.0
21.0
5.0 [79]
2.0
4.0
5.8
13.0
26.0
6.4 [77]
0.19
0.71
1.3
3.7
6.2
1.9 [82]
0.99
1.8
2.5
6.1
12.0
3.7 [81]
a Estimates are based on rank except for those of arithmetic mean.
b All waters based on fish obtained from all lakes, ponds, streams, and rivers in Maine, from other
household sources, and from other non-household sources.
0 Licensed anglers who fished during the seasons studied and did or did not consume freshwater fish, and
licensed anglers who did not fish but ate freshwater fish caught in Maine during those seasons.
d Licensed anglers who consumed freshwater fish caught in Maine during the seasons studied.
e Those of the "all anglers" who fished on rivers or streams (consumers and nonconsumers).
f Values in brackets [ ] are percentiles at the mean consumption rates.
Source: Chemrisk, 1992; Ebert et al., 1993.
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Chapter 10—Intake of Fish and Shellfish
Table 10-73. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day)a
Consuming Anglers
French
Canadian
Heritage
Irish
Heritage
Italian
Heritage
Native
American
Heritage
Other White
Non-Hispanic
Heritage
Scandinavian
Heritage
TV of Cases
Median (50th percentile)c'd
ee^percentile0'"1
75thpercentilec'd
Arithmetic mean0
Percentile at the meand
90thpercentilec'd
gs^percentile0'"1
Percentile at 6.5 g/day4"
201
2.3
4.1
6.2
7.4
80
15
27
77
138
2.4
4.4
6.0
5.2
70
12
20
75
27
1.8
2.6
5.0
4.5
74
12
21
81
96
2.3
4.7
6.2
10
83
16
51
77
533
1.9
3.8
5.7
6.0
76
13
24
77
37
1.3
2.6
4.9
5.3
78
9.4
25
84
a "All Waters" based on fish obtained from all lakes, ponds, streams, and rivers in Maine, from other
household sources, and from other non-household sources.
b "Consuming Anglers" refers to only those anglers who consumed freshwater fish obtained from Maine
sources during the 1989-1990 ice fishing or 1990 open water fishing seasons.
0 The average consumption per day by freshwater fish consumers in the household.
d Calculated by rank without any assumption of statistical distribution.
e Fish consumption rate recommended by U.S. EPA (1984) for use in establishing ambient water quality
standards.
Source: Chemrisk, 1992.
Table 10-74. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the 1990
Season
Ice Fishing
Species
Landlocked salmon
Atlantic salmon
Togue (lake trout)
Brook trout
Brown trout
Yellow perch
White perch
Bass (smallmouth and largemouth)
Pickerel
Lake whitefish
Hompout (catfish and bullheads)
Bottom fish (suckers, carp, and sturgeon)
Chub
Smelt
Other
TOTALS
Quantity
Consumed
(#)
832
3
483
1,309
275
235
2,544
474
1,091
111
47
50
0
7,808
201
15,463
Grams
(xlO3)
Consumed
290
1.1
200
100
54
9.1
160
120
180
20
8.2
81
0
150
210
1,583.4
Lakes and Ponds
Quantity
Consumed
(#)
928
33
459
3,294
375
1,649
6,540
73
553
558
1,291
62
252
428
90
16,587
Grams
(xlO3)
Consumed
340
9.9
160
210
56
52
380
5.9
91
13
100
22
35
4.9
110
1,590
Rivers and Streams
Quantity
Consumed
(#)
305
17
33
10,185
338
188
3,013
787
303
55
180
100
219
4,269
54
20,046
Grams
(xlO3)
Consumed
120
11
2.7
420
23
7.4
180
130
45
2.7
7.8
6.7
130
37
45
1,168
Source: Chemrisk, 1992.
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Chapter 10—Intake of Fish and Shellfish
Table 10-75. Socio-Demographic Characteristics of Respondents
Category
Geographic Distribution
Age Distribution (years)
Annual Household Income
Ethnic Background
Subcategory
Upper Hudson
Mid Hudson
Lower Hudson
<14
15 to 29
30 to 44
45 to 59
>60
<$10,000
$10,000 to 29,999
$30,000 to 49,999
$50,000 to 69,999
$70,000 to 89,999
>$90,000
Caucasian American
African American
Hispanic American
Asian American
Native American
Percent of Total3
18%
35%
48%
3%
26%
35%
23%
12%
16%
41%
29%
10%
2%
3%
67%
21%
10%
1%
1%
a A total of 336 shore-based anglers were interviewed.
Source: Hudson River Sloop Clearwater, Inc.,
1993.
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Chapter 10—Intake of Fish and Shellfish
Table 10-76. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish
Income3
<$15,000
$15,000 to $24,999
$25,000 to $39,999
>$40,000
Education
Some High School
High School Degree
Some College-College Degree
Post-Graduate
Residence Sizeb
Large City/Suburb (>100,000)
Small City (20,000 to 100,000)
Town (2,000 to 20,000)
Small Town (100 to 2,000)
Rural, Non-Farm
Farm
Age (years)
16 to 29
30 to 39
40 to 49
50 to 59
60+
Sexa
Male
Female
Race/Ethnicityb
Minority
White
p< 0.01, F test.
b p < 0.05, F test.
N = Sample size.
CI = Confidence interval.
Source: Westetal., 1993.
Consumption Study,
N
290
369
662
871
299
1,074
825
231
487
464
475
272
598
140
266
583
556
419
596
299
1,074
160
2,289
1991-1992
Mean (g/day)
21.0
20.6
17.5
14.7
16.5
17.0
17.6
14.5
14.6
12.9
19.4
22.8
17.7
15.1
18.9
16.6
16.5
16.5
16.2
17.5
13.7
23.2
16.3
95% CI
16.3-25.8
15.5-25.7
15.0-20.1
12.8-16.7
12.9-20.1
14.9-19.1
14.9-20.2
10.5-18.6
11.8-17.3
10.7-15.0
15.5-23.3
16.8-28.8
15.1-20.3
10.3-20.0
13.9-23.9
13.5-19.7
13.4-19.6
13.6-19.4
13.8-18.6
15.8-19.1
11.2-16.3
13.4-33.1
14.9-17.6
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Chapter 10—Intake of Fish and Shellfish
Table 10-77.
Mean Per Capita Freshwater Fish Intake of Alabama Anglers
Mean Consumption (g/day)
Harvest Method3
All respondents
All respondents; all
meals; 4-ounce
serving method
Age (years)
20 to 30
31 to 50
5 1 and over
Race/Ethnicity
African American
Native American
Asian
Hispanic
Caucasian
Seasons
Fall
Winter
Spring
Summer
a The Harvest Method
N
563
-
-
113
0
2
2
413
130
56
185
192
used the
Site meals All meals
32.6 43.1
-
-
35.4 49.6
0 0
74.7 74.7
0 0
33.9 48.6
29.7 43.4
26.2 34.2
21.5 29.3
46.7 57.0
actual harvest offish and dressing
4-ounce Serving Methodb
N
1,303
-
-
232
2
3
2
925
303
177
414
417
method
Site Meals All Meals
30.3
-
-
33.4
22.7
44.1
0
29.4
32.0
30.8
20.5
36.4
reported to calculate
45.8
44.8
16
39
76
50.7
22.7
44.1
0
49.7
49.4
43.9
33.6C
53.0C
consumption rates.
b The 4-ounce Serving Method estimated consumption based on a typical 4-ounce serving size.
Statistical difference at/? < 0.05.
N = Number of respondents.
Source : Alabama Department of Environmental Management (ADEM),
1994.
Table
10-78. Distribution of Fish
Percentile of Lake Ontario Anglers
Source.
25%
50%
75%
90%
95%
99%
Connelly etal., 1996.
Intake Rates (from all sources and from
Lake Ontario Anglers
Fish from All Sources (g/day)
8.8
14.1
23.2
34.2
42.3
56.6
sport-caught sources) for 1992
Sport-Caught Fish (g/day)
0.6
2.2
6.6
13.2
17.9
39.8
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Chapter 10—Intake of Fish and Shellfish
Table 10-79. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers,
Demographic Characteristics
Demographic Group
Overall
Residence
Rural
Small City
City (25 to 100,000)
City (>100,000)
Income
<$20,000
$21,000 to 34,000
$35,000 to 50,000
>$50,000
Age (years)
<30
30 to 39
40 to 49
50+
Education
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-81. Fishing Patterns and Consumption Rates of People Fishing Along the Savannah River
(Mean ± SE)
Ethnicity
White
Black
Income
<$20,000
>$20,000
Education
Not high school graduate
High school graduate
College or technical
training
N
180
72
138
99
45
154
59
Age
(years)
42
±1
47 ±2
43
42
49
43
41
±1
±1
±2
±1
±2
Years
fished
31 ±1
34 ±2
32±2
30±1
36 ±2
31 ±1
28 ±2
Years
fished
Savannah
River
24 ±1
24 ±2
24 ±2
22 ±2
23 ±3
26 ±1
17 ±2
Distance
traveled
(km)
42
15
31
32
±9
±1
±4
±9
24 ±4
36 ±9
54 ±24
How
often eat
fish/month
2.88 ±0.30
5. 37 ±0.57
3.39 ±0.52
3. 97 ±0.36
5. 93 ±0.85
3.02 ±0.27
3. 36 ±0.67
Serving size
(grams)
370 i
387 i
379 i
375 i
383 i
366 i
398 i
6.60
10.2
7.27
8.10
13.3
6.81
11.8
Overall mean (all respondents)
N = Sample size.
SE = Standard error.
Source: Burger et al, 1 999
Fish/month Fish/year
(kg) (kg)
1.17±0.14 14.0 i 1.70
2. 13 ±0.24 25.6 ±2. 92
1.44 ±0.24 17.3 ±2.82
1.58±0.16 18. 9± 1.88
2.61 ±0.44 31. 3 ±5.26
U5iO.ll 13.8il.36
1.52 ±0.31 18.2 ±3.66
48.7 g/day
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-82. Fish Consumption Rates for Indiana Anglers — Mail Survey (g/day)
Active Consumers
Potential and Active Consumers
Percentile
N Mean 50th 80th 90th 95th
1,045 19.8 9.5 28.4 37.8 60.5
1,261 16.4 7.6 23.6 37.8 60.5
N = Sample size.
Source: Williams etal., 1999.
Table 10-83. Fish Consumption Rates for Indiana Anglers — On-Site Survey (g/day)
Percentile
Active Consumers
White
Minority
Income
<$25,000
$25,000 to $34,999
$35,000 to $49,999
>$50,000
Potential and Active Consumers
White
Minority
Income
<$25,000
$25,000 to $34,999
$35,000 to $49,999
>$50,000
TV = Sample size.
Source: Williams et al., 2000.
N
177
143
101
62
55
60
361
217
180
117
91
126
Mean
20.0
27.2
18.9
18.8
15.2
48.9
6.8
15.3
10.2
7.4
6.8
13.6
50th
7.6
7.6
7.5
7.6
5.7
11.3
0
3.8
3.8
0
0
0
80th
23.6
30.2
18.9
23.6
23.6
113.4
5.7
13.2
9.5
7.6
5.7
7.6
90th
37.8
90.7
37.8
60.5
23.6
181.4
15.1
37.8
23.6
15.1
22.7
37.8
95th
113.4
136.1
136.1
90.7
45.4
181.4
37.8
90.7
37.8
37.8
23.6
113.4
Page
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North
Dakota Residents (g/day)
Percentile
N
50th
75th
90th
95th
99th
Minnesota
Sport-caught fish only
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Bois Forte Tribe
With fishing license
Without fishing license
582
996
505
460
2,312
232
2,020
490
1.2
4.5
2.1
3.6
2.8
2.8
3.9
0.0
4.2
10.6
5.8
8.2
7.9
6.6
9.2
2.0
9.0
23.7
14.0
20.8
17.3
12.0
18.9
4.5
13.7
39.8
24.9
37.2
28.9
19.6
30.4
7.0
26.7
113.9
75.9
101.3
78.0
120.6
94.5
51.1
Purchased Fish Only
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Bois Forte Tribe
With fishing license
Without fishing license
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Bois Forte Tribe
With fishing license
Without fishing license
582
996
505
460
2,312
232
2,020
490
582
996
505
460
2,312
232
2,020
490
3.6
7.4
6.1
7.1
6.6
3.4
6.4
5.6
Total
6.9
15.1
10.1
13.8
12.3
9.3
13.2
7.5
9.3
15.4
14.0
14.6
14.4
9.0
14.0
12.7
14.0
27.2
19.1
22.8
22.6
14.5
23.1
15.2
18.0
30.3
29.2
25.3
27.7
14.4
25.9
29.6
25.6
50.3
39.5
45.2
42.8
26.0
42.3
30.4
31.3
47.5
50.3
42.5
43.2
24.1
39.7
55.4
38.1
72.3
69.2
64.1
64.5
38.4
64.5
58.7
61.2
91.6
103.7
89.4
91.3
71.9
88.7
98.7
78.2
155.6
147.7
139.3
128.7
123.0
133.5
110.0
North Dakota
Sport-Caught Fish Only
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Spirit Lake Nation Tribes
With fishing license
Without fishing license
343
579
311
278
1,406
105
1,101
391
1.7
2.3
4.3
4.2
3.0
0.0
4.5
0.0
6.0
6.8
10.7
11.5
9.2
2.9
11.2
1.5
13.3
15.1
23.8
21.8
16.4
20.3
21.2
4.8
21.6
24.6
30.1
32.5
27.4
36.3
30.8
7.9
44.3
79.8
89.8
87.5
80.9
97.6
87.2
23.1
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-84. Consumption of Sport-Caught
Dakota Residents
N
and Purchased Fish by Minnesota and North
(g/day) (continued)
50th
Purchased Fish
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Spirit Lake Nation Tribes
With fishing license
Without fishing license
Age in years (sex)
Otol4
14 and over (males)
15 to 44 (females)
44 and over (females)
General population
Spirit Lake Nation Tribes
With fishing license
Without fishing license
TV = Sample size.
Source: Benson et al., 2001.
343
579
311
278
1,406
105
1,101
391
343
579
311
278
1,406
105
1,101
391
4.7
7.4
7.1
6.1
6.4
1.2
6.8
5.7
Total
9.2
7.4
14.1
13.5
12.6
1.4
14.0
7.2
Percentile
75*
Only
14.3
15.4
16.1
15.4
15.4
16.5
15.9
15.1
20.4
15.4
27.3
25.4
24.1
21.2
25.3
15.9
90th
23.1
30.3
33.5
30.3
29.1
30.0
29.5
30.2
35.7
30.3
49.8
49.3
46.7
50.7
49.2
33.5
95*
32.9
47.5
50.6
47.0
47.8
40.7
47.0
52.8
57.1
47.5
80.5
78.8
71.4
80.8
76.2
54.1
99th
90.7
91.6
90.9
90.7
95.6
143.5
95.6
112.2
97.4
91.6
137.5
144.5
126.3
179.8
131.4
116.1
Page
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-85. Fishing Patterns
All anglers
Anglers who catch and eat fish
from study area
Ethnicity
White
Black
Income
<$20,000
$20,000 to $29,000
$30,000 to $39,000
>$40,000
Education
Not high school graduate
High school graduate
Some college, associates,
trade school
College, at least a bachelors
degree
jV = Sample size.
Source: Campbell et al, 2002.
N
202
77
71
6
22
19
18
15
18
28
20
10
and Consumption Rates of Anglers Along the Clinch River Arm of Watts Bar
Reservoir (Mean ± SE)
Age
(years)
39.2± 1
41.8±2
42 ±2
43 ±6
42 ±3
35 ±3
43 ±3
47 ±4
44 ±4
40 ±3
40 ±3
42 ±5
Years
fished
31 ±1
34 ±2
34 ±2
33 ±7
33 ±4
29 ±4
37 ±4
38 ±4
35 ±4
32 ±3
35 ±4
36 ±5
Years
fished,
Clinch
River
11±1
12 ±2
12 ±2
20 ±5
16±3
8.8 ±3
8.9 ±3
13.9 ±3
13 ±3
14 ±3
9.0 ±3
10 ±4
Distance
traveled
(km)
61 ±5
57 ±6
59 ±6
44 ±20
49 ±10
37 ±12
69±11
81 ±12
57 ±12
55 ±10
61 ±11
59 ±16
How
often eat
fish/month
1
2
2
0
1
1
2
3
1
2
2
2
28 ±0.12
06 ± 0.22
14 ±0.23
94 ± 0.78
.37 ±0.40
84 ± 0.44
13 ±0.45
01 ±0.49
67 ±0.46
12 ±0.37
05 ± 0.44
33 ±0.62
Serving
size
(grams)
283 ± 20
486 ± 32
501 ±33
9
7
6
307 ±116
392 ±41
548 ± 44
482 ± 46
452 ± 50
439 ± 67
551 ±54
486 ± 64
414 ±90
7
9
1
5
7
2
2
8
Fish/month
(kg)
0.62 ±0.08
1.14±0.19
1.21 ±0.20
0.34 ±0.68
0.52 ±0.29
1.19±0.32
1.11 ±0.33
1.56 ±0.36
0.83 ±0.39
1.45 ±0.32
1.11 ±0.38
0.92 ±0.53
Fish/year
(kg)
7.40 ±1.01
13.7±2.17
14. 5 ±2. 36
4.14±8.11
6.29 ±3. 58
14.3 ±3.85
13.3 ±3.95
18.8±4.33
9.99 ±4.77
17.4 ±3. 82
13.4 ±4.52
11.0 ±6.39
Table 10-86. Daily Consumption of Wild-Caught Fish, Consumers Only (g/kg-day, as-consumed)
g/person/day
Population
Ethnicity
Black
White
All
Sex
Female
Male
All
Age (years)
<32
33 to 45
>45
Income
$0 to <20K
$20 to 30K
>$30K
jV Consumers (%) Mean
39
415
458
149
308
458
145
159
150
98
95
172
79
78
78
72
80
73
77
77
78
82
82
76
171
38
.0
8
50.2
39
55
50
32
71
44
104
32
40
1
2
2
6
3
0
.0
7
9
Range
1.88-590
0.35-902
0.35-902
0.35^12
0.63-902
0.35-902
0.63^12
7.52-902
0.35-538
31.9-590
0.35^60
0.47-902
0
0
0
0
0
0
0
0
0
0
0
0
Median
137.0
15.3
17.6
11.6
21.3
17.6
14.2
18.8
20.0
31.9
15.0
19.4
75th
240.0
37.6
47.8
32.8
56.4
47.8
37.6
67.6
44.4
151.0
37.2
45.8
90th
446.0
93.0
123.0
123.0
127.0
123.0
66.5
177.0
100.0
285.0
93.0
87.9
95m
557.0
129.0
216.0
172.0
235.0
216.0
123.0
354.0
164.0
429.0
120.0
127.0
99th
590.0
286.0
538.0
373.0
557.0
538.0
216.0
590.0
286.0
590.0
460.0
216.0
N = Sample size.
Source: Burger,
2002b.
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-87. Consumption Rates (g/day) for Freshwater Recreational Anglers in King County, WA
Location
Freshwater Fish Consumption
King County Lakes (all respondents)
King County Lakes (children of
respondents)
SD = Standard deviation.
SE = Standard error.
Source: Mayfield et al., 2007.
Sample „ or Percentiles
Size JVKan kjU "L 50* 90* 95*
128 10 24 2 0 23 42
81 7 20 2 0 17 29
Table 10-88. Number of Grams per Day of Fish Consumed by All Adult Respondents (consumers and
non-consumers combined) — Throughout the Year
Number of g/day
0.00
1.6
3.2
4.0
4.9
6.5
7.3
8.1
9.7
12.2
13.0
16.2
19.4
20.2
24.3
29.2
32.4
38.9
40.5
48.6
Cumulative Percent
8.9%
9.0%
10.4%
10.8%
10.9%
12.8%
12.9%
13.7%
14.4%
14.9%
16.3%
22.8%
24.0%
24.1%
27.9%
28.1%
52.5%
52.9%
56.5%
67.6%
Number of g/Day
64.8
72.9
77.0
81.0
97.2
130
146
162
170
194
243
259
292
324
340
389
486
648
778
972
Cumulative Percent
80.6%
81.2%
81.4%
83.3%
89.3%
92.2%
93.7%
94.4%
94.8%
97.2%
97.3%
97.4%
97.6%
98.3%
98.7%
99.0%
99.6%
99.7%
99.9%
100%
TV = 500; N = sample size.
Weighted Mean = 58.7 g/day.
Weighted SE = 3.64; SE = standard error.
90th Percentile 97.2 g/day < (90th) < 130 g/day.
95th Percentile = 170 g/day.
99th Percentile =389 g/day.
Source: CRITFC, 1994.
Page
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-89.
Sex
Female
Male
Total
Age (years)
18 to 39
40 to 59
60 and Older
Total
Location
On Reservation
Off Reservation
Total
Source: CRITFC,
Fish Intake Throughout the Year by Sex, Age, and
N
278
222
500
287
155
58
500
440
60
500
1994.
Location by All Adult
Weighted Mean
(g/day)
55.8
62.6
58.7
57.6
55.8
74.4
58.7
60.2
47.9
58.7
Respondents
Weighted SE
4.78
5.60
3.64
4.87
4.88
15.3
3.64
3.98
8.25
3.64
Table 10-90. Fish Consumption Rates Among
g/day
0.0
0.4
0.8
1.6
2.4
3.2
4.1
4.9
6.5
8.1
9.7
12.2
13.0
16.2
19.4
20.3
24.3
32.4
48.6
64.8
72.9
81.0
97.2
162.0
Native American Children (Age 5 Years and Under)3
Unweighted Cumulative Percent
21.1
21.6
22.2
24.7
25.3
28.4
32.0
33.5
35.6
47.4
48.5
51.0
51.5
72.7
73.2
74.2
76.3
87.1
91.2
94.3
96.4
97.4
98.5
100
a Sample size = 194; unweighted mean = 19.6 g/day; unweighted standard error = 1.94.
Note: Data are compiled from the Umatilla, Nez Perce, Yakama, and Warm Springs tribes of the Columbia
River Basin.
Source: CRITFC, 1994.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-91. Number of Fish Meal Eaten per Month and Fish Intake Among Native American Children Who
Consume Particular Species
Species
Salmon
Lamprey
Trout
Smelt
Whitefish
Sturgeon
Walleye
Squawfish
Sucker
Shad
Not applicable.
SE = Standard error.
Source: CRITFC, 1994.
N
164
37
89
39
21
21
5
2
4
3
Fish Meals/Month
Unweighted Mean
2.3
0.89
0.96
0.40
3.5
0.43
0.22
0.00
0.35
0.10
Unweighted SE
0.16
0.27
0.12
0.09
2.83
0.12
0.20
0.22
0.06
Intake (g/day)
Unweighted Mean
19
8.1
8.8
3.8
21
4.0
2.0
0.0
2.6
1.1
Unweighted SE
1.5
2.8
1.4
0.99
16
1.3
1.5
1.7
0.57
Table 10-92. Socio-Demographic Factors and Recent Fish Consumption
Peak Consumption3
All participants
(#=323)
Sex
Male(# = 148)
Female (N= 175)
Age (years)
<35 (N= 150)
>35 (N= 173)
High School Graduate
No (AT =105)
¥65(^=218)
Unemployed
Yes (#=78)
No (#=245)
Average
meals/week0
1.7
1.9
1.5
1.8
1.6
1.6
1.7
1.9
1.6
Recent
Consumption13
>3 meals/weekd
(%)
20
26
15
23
17
18
21
27
18
Walleye
4.2
5.1
3.4
5.3a
3.2
3.6
4.4
4.8
4.0
N.Pike
0.3
0.5a
0.2
0.3
0.4
0.2
0.4
0.6
0.3
Muskellunge
0.3
0.5
0.1
0.2
0.3
0.4
0.2
0.6
0.2
Bass
0.5
0.7a
0.3
0.7
0.3
0.7
0.4
1.1
0.3
a Highest number of fish meals consumed/week.
b Number of meals of each species
0 Average peak
fish consumption.
in the previous 2
months.
d Percentage of population reporting peak fish consumption of >3
Source: Peterson etal
, 1994.
fish meals/week.
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Chapter 10—Intake of Fish and Shellfish
Table 10-93. Number of Local Fish Meals Consumed per Year by Time Period for All Respondents
Time Period
During Pregnancy
Number ot , , , .
T i T-- i A , i Mohawk
Local Fish Meals
Consumed Per Year N %
None
Ito9
10 to 19
20 to 29
30 to 39
40 to 49
50+
Total
63 64.9
24 24.7
5 5.2
1 1.0
0 0.0
0 0.0
4 4.1
97 100.0
Control
N
109
24
7
5
2
1
6
154
%
70.8
15.6
4.5
3.3
1.3
0.6
3.9
100.0
<1 Year Before Pregnancy3
Mohawk
N
42
40
4
3
0
1
7
97
%
43.3
41.2
4.1
3.1
0.0
1.0
7.2
100.0
Control
N
99
31
6
3
3
1
11
154
%
64.3
20.1
3.9
1.9
1.9
0.6
7.1
100.0
>1 Year Before Pregnancyb
Mohawk
N
20
42
6
9
1
1
18
97
%
20.6
43.3
6.2
9.3
1.0
1.0
18.6
100.0
Control
N
93
35
8
5
1
1
11
154
%
60.4
22.7
5.2
3.3
0.6
0.6
7.1
100.0
p < 0.05 for Mohawk vs. Control.
b
N
Source:
p < 0.001 for Mohawk vs. Control.
= Number of respondents.
Fitzgerald etal., 1995.
Table 10-94. Mean Number of Local Fish Meals Consumed per Year by Time Period for All Respondents
and Consumers Only
All Respondents
(N= 97 Mohawks and 154 Controls)
Consumers Only
(N= 82 Mohawks and 72 Controls)
During <1 Year Before >1 Year Before During <1 Year Before >1 Year Before
Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy
Mohawk
Control
3.9(1.2)
7.3 (2.1)
9.2 (2.3)
10.7 (2.6)
23.4 (4.3)a
10.9 (2.7)
4.6(1.3)
15.5 (4.2)a
10.9 (2.7)
23.0 (5.l)b
27.6 (4.9)
23.0(5.5)
a p < 0.001 for Mohawk vs. Controls.
b p< 0.05 for Mohawk vs. Controls.
() = Standard error.
Test for linear trend:
p < 0.001 for Mohawk (All participants and consumers only);
p = 0.07 for Controls (All participants and consumers only).
Source: Fitzgerald etal., 1995.
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-95. Mean Number of Local Fish Meals Consumed per Year by Time Period and Selected
Characteristics for All Respondents (Mohawk, TV = 97; Control, TV = 154)
Time Period
During Pregnancy <1 Year Before
Variable
Age (years)
<20
20 to 24
25 to 29
30 to 34
>34
Education (Years)
12
13 to 15
>15
Cigarette Smoking
Yes
No
Alcohol Consumption
Yes
No
Mohawk
7.7
1.3
3.9
12.0
1.8
6.3
7.3
1.7
0.9
3.8
3.9
4.2
3.8
Control
0.8
5.9
9.9
7.6
11.2
7.9
5.4
10.1
6.8
8.8
6.4
9.9
6.3b
Mohawk
13.5
5.7
15.5
9.5
1.8
14.8
8.1
8.0
10.7
10.4
8.4
6.8
12.1
Pregnancy
Control
13.9
14.5
6.2
2.9
26.2
12.4
8.4
15.4
0.8
13.0
8.3
13.8
4.7C
>1 Year Before
Mohawk
27.4
20.4
25.1
12.0
52.3
24.7
15.3
29.2
18.7
31.6
18.1
18.0
29.8
Pregnancy
Control
10.4
15.9
5.4
5.6
22.1a
8.6
11.4
13.3
2.1
10.9
10.8
14.8
2.9d
F (4, 149) = 2.66, p = 0.035 for Age Among Controls.
b F (1,152) = 3.77,^ = 0.054 for Alcohol Among Controls.
F (1, 152) = 5.20, p = 0.024 for Alcohol Among Controls.
d F (1,152) = 6A2,p = 0.012 for Alcohol Among Controls.
Note: F (rl, r2) = F statistic with rl and r2 degrees of freedom.
Source: Fitzgerald etal.,
1995.
Table 10-96. Fish Consumption Rates for Mohawk Native Americans (g/day)
Population Group
Adults— all3
All fish
Local fish
Adults — consumers only3
All fish
Local fish
Children— allb
Local fish
Children — consumers onlyb
Local fish
Sample Size
1,092
1,092
983
972
..
—
3 Value based on assumption that 1 fish meal = 227
[1982]).
b Value for 2-year old child,
Fish Intake Rate
Mean
28
25
31
29
10
13
grams (1/2
based on assumption that children
95th Percentile
132
131
142
135
54
58
pound) (based on data
/o Consuming
90%
90%
90%
90%
..
—
fromPao etal.,
consume fish at the same frequency as adults
but have a smaller meal size (93 grams).
Source: Forti etal., 1995.
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Chapter 10—Intake of Fish and Shellfish
Table 10-97. Percentiles and Mean of Adult Tribal Member Consumption
5%
50%
90% 95%
SE
Rates (g/kg-day)
Mean
95% CI
Tulalip Tribes (N = 73)
Anadromous fish
Pelagic fish
Bottom fish3
Shellfish3
Total finfish
Other fishb
Total fish
0.006
0.000
0.000
0.000
0.010
0.000
0.046
0.190
0.004
0.008
0.153
0.284
0.000
0.552
1.429 2.114
0.156 0.234
0.111 0.186
1.241 1.5296
1.779 2.149
0.113 0.264
2.466 2.876
0.068
0.008
0.007
0.059
0.072
0.008
0.111
0.426
0.036
0.033
0.362
0.495
0.031
0.889
(0.297, 0.555)
(0.021,0.051)
(0.020, 0.046)
(0.250, 0.474)
(0.359,0.631)
(0.016,0.046)
(0.679, 1.099)
Squaxin Island Tribe (N= 117)
Anadromous fish
Pelagic fish
Bottom fish3
Shellfish3
Total finfish
Other fishb
Total fish
0.016
0.000
0.000
0.000
0.027
0.000
0.045
0.308
0.003
0.026
0.065
0.383
0.000
0.524
1.639 2.182
0.106 0.248
0.176 0.345
0.579 0.849
1.828 2.538
0.037 0.123
2.348 3.016
0.069
0.009
0.010
0.027
0.075
0.003
0.088
0.590
0.043
0.063
0.181
0.697
0.014
0.891
(0.485, 0.695)
(0.029, 0.057)
(0.048, 0.078)
(0.140,0.222)
(0.583,0.811)
(0.009, 0.019)
(0.757, 1.025)
Both Tribes Combined (weighted)
Anadromous fish
Pelagic fish
Bottom fish**
Shellfish**
Total finfish
Other fish*
Total fish
0.010
0.000
0.000
0.000
0.017
0.000
0.047
3 p< 0.01 comparing two
0.239
0.004
0.015
0.115
0.317
0.000
0.531
1.433 2.085
0.112 0.226
0.118 0.118
0.840 1.308
1.751 2.188
0.049 0.145
2.312 2.936
0.042
0.005
0.005
0.030
0.045
0.004
0.064
0.508
0.040
0.048
0.272
0.596
0.023
0.890
(0.425,0.591)
(0.029, 0.050)
(0.038, 0.058)
(0.212,0.331)
(0.507, 0.685)
(0.015,0.030)
(0.765, 1.015)
tribes (Wilcoxon-Mann- Whitney test).
N = Sample size.
SE = Standard error.
CI = Confidence interval.
Source: Toy et al., 1996.
Exposure Factors Handbook
September 2011
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Chapter 10—Intake of Fish and Shellfish
Table 10-98. Median and Mean Consumption Rates by Sex (g/kg-day) within Each Tribe
Shellfish
Male
Female
N
42
31
Tulalip Tribe
Median Mean
0.158 0.370
0.153 0.353
Squaxin Island Tribe
95% CI N Median Mean
(0.215,
0.525) 65 0.100 0.202
(0.192, 52 0.038 0.155
0.514)
95% CI
(0.149,
0.255)
(0.093,
0.217)
Total finfish
Male
Female
42
31
0.414 0.559
0.236 0.409
(0.370,
0.748) 65 0.500 0.707
(0.218, 52 0.272 0.684
0.600)
(0.576,
0.838)
(0.486,
0.882)
Total fish3
Male
Female
42
31
0.623 0.959
0.472 0.794
(0.666, 0.775b
1.252) 65 0.926
(0.499, 52 0.353 0.847
1.089)
a Total fish includes anadromous, pelagic, bottom shellfish, finfish, and other fish.
b p< 0.05 for difference in consumption rate by sex within a tribe (Wilcoxon-Mann- Whitney
N = Sample size.
CI = Confidence interval.
Source:
Toyetal., 1996.
(0.771,
1.081)
(0.614,
1.080)
test).
Male
Female
Source:
Table 10-99. Median Consumption
Tulalip Tribe
53
34
Toyetal., 1996.
Rate for Total Fish by Sex and Tribe (g/day)
Squaxin Island Tribe
66
25
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-100. Percentiles of Adult Consumption Rates by Age (g/kg-day)
Tulalip Tribes
Ages (years)
Shellfish
18 to 34
35 to 49
50 to 64
65+
Total finfish
18 to 34
35 to 49
50 to 64
65+
Total fish3
18 to 34
35 to 49
50 to 64
65+
Total fish
Source: Toy etal.,
5%
0.00
0.00
0.00
0.00
0.013
0.002
0.156
0.006
0.044
0.006
0.190
0.050
includes
1996.
50%
0.181
0.161
0.173
0.034
0.156
0.533
0.301
0.176
0.571
0.968
0.476
0.195
anadromous,
90%
1.163
1.827
0.549
0.088
1.129
2.188
1.211
0.531
2.034
3.666
11.586
0.623
pelagic, bottom,
95%
1.676
1.836
0.549
0.088
1.956
2.388
1.211
0.531
2.615
4.204
1.586
0.623
shellfish,
Squaxin Island Tribe
50%
0.073
0.073
0.000
0.035
0.289
0.383
0.909
0.601
0.500
0.483
1.106
0.775
finfish, and other fish.
90%
0.690
0.547
0.671
0.188
1.618
2.052
3.439
2.049
2.385
2.577
3.589
2.153
95%
1.141
1.094
0.671
0.188
2.963
2.495
3.439
2.049
3.147
3.053
3.589
2.153
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September 2011
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Chapter 10—Intake of Fish and Shellfish
Table 10-101. Median
Income
Shellfish
< $10,000
$10,001 to $15,000
$15001 to $20 000
$20,001 to $25,000
$25,001 to $35,000
$35,001+
Total finfish
< $10,000
$10,001 to $15,000
$15,001 to $20,000
$20,001 to $25,000
$25,001 to $35,000
$35,001+
Total fish
<$ 10,000
$10,001 to $15,000
$15,001 to $20,000
$20,001 to $25,000
$25,001 to $35,000
$35,001+
Consumption Rates by Income
Tulalip Tribes
0.143
0.071
0 144
0.202
0.416
0.175
0.235
0.095
0.490
0.421
0.236
0.286
0.521
0.266
0.640
0.921
0.930
0.607
(g/kg-day) within Each Tribe
Squaxin Island Tribe
0.078
0.121
0072
0.000
0.030
0.090
0.272
0.254
0.915
0.196
0.387
0.785
0.476
0.432
0.961
0.233
0.426
1.085
Source: Toyetal., 1996.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-102. Mean, 50th, and 90th Percentiles of Consumption Rates for Children Age Birth to
5 Years (g/kg-day)
Shellfish
Total finfish
Total, all fish
Shellfish
Total finfish
Total, all fish
Shellfish
Total finfish
Total, all fish
TV = Sample size.
SE = Standard error.
CI = Confidence interval
Source: Toyetal., 1996.
Mean (SE) 95% CI
Tulalip Tribes (N= 21)
0.125(0.056) (0.014,0.236)
0.114(0.030) (0.056,0.173)
0.239 (0.077) (0.088, 0.390)
Squaxin Island Tribe (N = 48)
0.228(0.053) (0.126,0.374)
0.250(0.063) (0.126,0.374)
0.825(0.143) (0.546,1.105)
Both Tribes Combined (weighted)
0.177(0.039) (0.101,0.253)
0.182(0.035) (0.104,0.251)
0.532 (0.081) (0.373, 0.691)
50%
0.000
0.060
0.078
0.045
0.061
0.508
0.012
0.064
0.173
90%
0.597
0.290
0.738
0.574
0.826
2.056
0.574
0.615
1.357
Exposure Factors Handbook Page
September 2011 10-171
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*
I
Table 10-103. Adult Consumption Rate
(g/kg-day): Individual Finfish
and Shellfish and Fish Groups
All Adult Respondents (Including Non-Consumers)
Species/Group
v v N Mean SE
Group G
Abalone 92 0.001 0.001
Lobster 92 0.022. 0.007
Octopus 92 0.019 0.006
Limpets 92 0.010 0.009
Miscellaneous 92 0.0003 0.0003
Group A 92 0.618 0.074.
Group B 92 0.051 0.016
Group C 92 0.136 0.025
Group D 92 0.097 0.021
Group E 92 1.629 0.262
Group F 92 0.124 0.016
Group G 92 0.052 0.017
AllFinfish 92 1.026 0.113
All Shellfish 92 1.680 0.269
All Seafood 92 2.707 0.336
N = Sample size.
SE = Standard error.
LCL = Lower confidence limit.
UCL = Upper confidence limit.
GM = Geometric mean.
MSB = Multiplicative standard error.
Note: The minimum consumption for all
rate for "Group A" was 0.005, for
Source: Duncan, 2000.
95%
LCL
0.000
0.008
0.008
0.000
0.000
0.473
0.019
0.087
0.056
1.115
0.092
0.019
1.153
2.049
0.000
species
95%
UCL
0.002
0.036
0.030
. 0.027
0.001
0.763
0.082
0.185
0.138
2.143
0.156
0.084
2.208
3.364
0.000
Percentiles
5*
0.000
0.000
0.000
0.000
0.000
0.021
0.000
0.000
0.000
0.063
0.000
0.000
0.087
0.063
0.236
50th
0.000
0.000
0.000
0.000
0.000
0.350
0.003
0.055
0.029
0.740
0.068
0.000
0.639
0.796
1.672
and groups was zero, except
'All Finfish" was 0
75th 90th
0.000 0.000
0.000 0.085
0.015 0.069
0.000 0.000
0.000 0.000
1.002 1.680
0.019 0.128
0.141 0.369
0.076 0.206
1.688 4.555
0.144 0.352
0.038 0.128
1.499 2.526
1.825 4.590
3.598 6.190
for "Group A,
.018, and for "All Seafood" was
95th
0.000
0.139
0.128
.0.000
0.000
2.177
0.270
0.526
0.613
7.749
0.533
0.262
3.412
7.754
10.087
Max
0.063
0.549
0.407
0.795
0.023
3.469
1.149
1.716
1.069
15.886
0.778
1.344
5.516
15.976
18.400
1 "All Finfish," and
0.080.
N
3
22
25
2
1
92
49
87
76
91
85
42
92
91
92
Consumers Only
%
3
24
27
2
1
100
53
95
.83
99
92
46
100
99
100
"All Seafood".
GM
0.007
0.052
0.042
0.261
0.023
0.274
0.025
0.064
0.045
0.703
0.070
0.043
0.590
0.727
1.530
MSB
3.139
1.266
1.231
3.047
1.167
1.262
1.147
1.168
1.160
1.139
1.240
1.128
1.160
1.123
The minimum
Q
I
^
t
Si
&
a,
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only
Consumers Only
Group
Group A
Group B
Group C
Group D
Group E
Species
King
Sockeye
Coho
Chum
Pink
Other or Unspecified
Salmon
Steelhead
Salmon (gatherings)
Smelt
Herring
Cod
Perch
Pollock
Sturgeon
Sable Fish
Spiny Dogfish
Greenling
Bull Cod
Halibut
Sole/Flounder
Rock Fish
Manila/Littleneck
Clams
Horse Clams
Butter Clams
Geoduck
Cockles
Oysters
Mussels
Moon Snails
Shrimp
Dungeness Crab
N
63
59
50
42
17
32
26
85
49
14
78
2
40
8
5
1
2
1
74
20
12
84
52
72
83
61
60
25
0
86
81
Mean
0.200
0.169
0.191
0.242
0.035
0.159
0.102
0.074
0.078
0.059
0.126
0.012
0.054
0.041
0.018
0.004
0.013
0.016
0.080
0.052
0.169
0.481
0.073
0.263
0.184
0.233
0.164
0.059
—
0.174
0.164
SE
0.031
0.026
0.033
0.046
0.007
0.070
0.035
.0.012
0.024
0.020
0.024
0.002
0.020
0.021
0.009
—
0.002
—
0.018
0.015
0.072
0.154
0.016
0.062
0.039
0.055
0.034
0.020
—
0.027
0.028
Median
0.092
0.070
0.084
0.147
0.034
0.043
0.027
0.031
0.016
0.034
0.051
0.012
0.013
0.021
0.014
—
0.013
—
0.029
0.022
0.066
0.088
0.025
0.123
0.052
0.099
0.068
0.015
—
0.088
0.071
75th
Percentile
0.322
0.293
0.247
0.280
0.057
0.172
0.103
0.079
0.078
0.093
0.140
—
0.060
0.053
0.034
—
—
—
0.069
0.067
0.231
0.284
0.070
0.184
0.167
0.202
0.184
0.085
—
0.196
0.185
90th
Percentile
0.581
0.493
0.584
0.768
0.077
0.261
0.398
0.205
0.247
0.197
0.319
—
0.139
—
—
—
—
—
0.213
0.201
0.728
1.190
0.261
0.599
0.441
0.530
0.567
0.155
—
0.549
0.425
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September 2011
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Chapter 10—Intake of Fish and Shellfish
Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only (continued)
Consumers Only
Group
Group E
(cont'd)
Group F
Group G
Species
Red Rock Crab
Scallops
Squid
Sea Urchin
Sea Cucumber
Oyster (gatherings)
Clams (gatherings)
Crab (gatherings)
Clams (razor,
unspecified)
Crab (king/snow)
Cabazon
Blue Back (sockeye)
Trout/Cutthroat
Tuna (fresh/canned)
Groupers
Sardine
Grunter
Mackerel
Shark
Abalone
Lobster
Octopus
Limpets
Miscellaneous
Group A
Group B
Group C
Group D
Group E
Group F
Group G
All Finfish
N
19
54
23
6
5
40
61
43
35
1
1
2
o
3
83
1
1
4
1
1
3
22
25
2
1
92
49
87
76
91
85
42
92
Mean
0.037
0.037
0.041
0.025
0.056
0.061
0.071
0.056
0.124
0.017
0.080
0.006
0.112
0.129
0.025
0.049
0.056
0.008
0.002
0.022
0.092
0.071
0.440
0.023
0.618
0.095
0.144
0.118
I Ml
0.134
0.113
1.026
SE
0.010
0.009
0.017
0.008
0.031
0.014
0.016
0.019
0.036
—
—
0.004
0.035
0.017
—
—
0.026
—
—
0.020
0.025
0.017
0.355
—
0.074
0.029
0.026
0.025
0.265
0.017
0.034
0.113
Median
0.012
0.011
0.009
0.019
0.008
0.031
0.029
0.027
0.062
—
—
0.006
0.129
0.071
—
—
0.047
—
—
0.003
0.057
0.044
0.440
—
0.350
0.017
0.068
0.042
0.750
0.076
0.042
0.639
75th
Percentile
0.057
0.040
0:032
0.048
0.130
0.088
0.064
0.042
0.138
—
—
—
—
0.145
—
—
0.110
—
—
—
0.130
0.123
—
—
1.002
0.098
0.141
0.091
1.691
0.163
0.118
1.499
90th
Percentile
0.117
0.110
0.188
—
—
0.152
0.165
0.100
0.284
—
—
—
—
0.346
—
—
—
—
—
—
0.172
0.149
—
—
1.680
0.261
0.403
0.392
4.577
0.372
0.270
2.526
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Chapter 10—Intake of Fish and Shellfish
Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only (continued)
Group
N
SE
Source:
Species
All Shellfish
All Seafood
= Sample size.
= Standard error.
Duncan, 2000.
Consumers Only
75th 90th
TV Mean SE Median „ ... „ ...
Percentile Percentile
91 1.699 0.271 0.819 1.837 4.600
92 2.707 0.336 1.672 3.598 6.190
Exposure Factors Handbook Page
September 2011 10-175
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I
»r
Table
10-105. Adult Consumption Rate (g/kg-day) by Sex
All Adult Respondents (Including Non-Consumers)
c,-,/-, N Mean
Species/Group
Group A (p- 0.02)
Male 46 0.817
Female 46 0.419
Group B (p = 0.04)
Male 46 0.089
Female 46 0.013
Group C (p = 0.03)
Male 46 0.170
Female 46 0.102
Group D (p = 0.08)
Male 46 0.135
Female 46 0.060
Group E (p = 0.03)
Male 46 1.865
Female 46 1.392
Group F (p = 0.6)
Male 46 0.141
Female 46 0.107
Group G (p = 0.2)
Male 46 0.081
Female 46 0.023
All Finfish (p = 0.007)
5Male 46 1.351
Female 46 0.701
All Shellfish (p = 0.03)
Male 46 1.946
Female 46 1.415
All Seafood (p = 0.008)
Male 46 3.297
Female 46 2.116
A' = Sample size.
SE = Standard error.
LCL = Lower confidence interval.
UCL = Upper confidence interval.
GM = Geometric mean.
SE
0.120
0.077
0.031
0.004
0.043
0.025
0.037
0.018
0.316
0.419
0.026
0.020
0.032
0.007
0.193
0.100
0.335
0.421
0.458
0.480
MSB = Multiplicative standard error.
Note p- value is 2-sided and based upon Mann-Whitney
than 20 respondents.
Source: Duncan, 2000.
95%
LCL
0.582
0.268
0.028
0.005
0.086
0.053
0.062
0.025
1.246
0.571
0.090
0.068
0.018
0.009
0.973
0.505
1.289
0.590
2.399
1.175
95%
UCL
1.052
0.570
0.150
0.021
0.254
0.151
0.208
0.095
2.484
2.213
0.192
0.146
0.144
0.037
1.729
0.897
2.603
2.240
4.195
3.057
th
0.021
0.018
0.000
0.000
0.007
0.000
0.000
0.000
0.068
0.029
0.000
0.005
0.000
0.000
0.115
0.083
0.068
0.029
0.232
0.236
test. The 95% CL is based on
50m
0.459
0.294
0.008
0.000
0.078
0.047
0.045
0.026
1.101
0.644
0.072
0.052
0.001
0.000
0.905
0.465
1.121
0.678
2.473
0.965
the normal
Dercentiles
75th
1.463
0.521
0.076
0.013
0.148
0.102
0.133
0.056
2.608
0.936
0.195
0.126
0.070
0.016
1.871
0.943
2.628
1.007
4.518
2.219
distribution
90th
2.033
1.028
0.269
0.044
0.432
0.277
0.546
0.105
4.980
2.462
0.413
0.322
0.261
0.093
3.341
1.751
5.146
2.462
8.563
4.898
The 5th
95tB
2.236
1.813
0.623
0.099
0.847
0.496
0.948
0.453
7.453
9.184
0.597
0.451
0.476
0.162
4.540
2.508
7.453
9.231
10.008
10.400
N
46
46
27
22
46
41
39
37
46
45
40
45
23
19
46
46
46
45
46
46
and 95th percentile are not
Consumers Only
%
100
100
59
48
100
89
85
80
100
98
87
98
50
41
100
100
100
98
100
100
reported
GMa MSEb
0.385 1.245
0.195 1.232
0.046 1.378
0.012 1.309
0.075 1.210
0.053 1.215
0.057 1.274
0.035 1.204
0.879 1.238
0.559 1.224
0.089 1.199
0.056 1.198
0.057 1.395
0.031 1.272
0.800 1.191
0.434 1.169
0.909 1.240
0.579 1.221
1.971 1.188
1.188 1.158
for groups with less
Q
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I
Table 10-106. Adult Consumption Rate (g/kg-day) by Age
All Adult Respondents (Including Non-Consumers)
Species/Age Group
Group A (p — 0.04)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group B(p = 0.001)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group C (p = 0.6)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group D (p = 0.2)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group E(p = 0.1)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group F (p = 0.5)
16 to 42 Years
43 to 54 Years
55 Years and Over
Group G (p = 0.6)
16 to 42 Years
43 to 54 Years
55 Years and Over
All Finfish (p = 0.03)
16 to 42 Years
43 to 54 Years
55 Years and Over
All Shellfish (p = 0.1)
16 to 42 Years
43 to 54 Years
55 Years and Over
N
58
15
19
58
15
19
58
15
19
58
15
19
58
15
19
58
15
19
58
15
19
58
15
19
58
15
19
Mean
0.512
1.021
0.623
0.042
0.097
0.041
0.122
0.117
0.193
0.079
0.164
0.102
1.537
2.241
1.425
0.119
0.154
0.115
0.052
0.088
0.023
0.874
1.554
1.074
1.589
2.330
1.447
SE
0.083
0.233
0.159
0.022
0.047
0.017
0.026
0.029
0.091
0.023
0.079
0.038
0.289
0.571
0.811
0.021
0.050
0.029
0.024
0.043
0.011
0.136
0.304
0.247
0.301
0.586
0.815
95%
LCL
0.349
0.564
0.311
0.000
0.005
0.008
0.071
0.060
0.015
0.034
0.009
0.028
0.971
1.122
0.000
0.078
0.056
0.058
0.005
0.004
0.001
0.607
0.958
0.590
3.626
1.181
0.000
95%
UCL
0.675
1.478
0.935
0.085
0.189
0.074
0.173
0.174
0.371
0.124
0.319
0.176
2.103
3.360
3.015
0.160
0.252
0.172
0.099
0.172
0.045
1.141
2.150
1.558
2.179
3.479
3.044
Percentiles
5m 50th
0.015 0.294/5
1.020
0.394
0.000 0.000
0.019
0.010
0.000 0.055
0.078
0.050
0.000 0.026
0.049
0.033
0.059 0.740
1.679
0.678
0.000 0.044
0.109
0.072
0.000 0.006
0.000
0.000
0.087 0.536
1.422
0.861
0.059 0.799
1.724
0.688
th
0.660
1.596
0.868
0.009
0.124
0.054
0.134
0.146
0.141
0.072
0.094
0.088
1.715
4.403
1.159
0.123
0.217
0.145
0.035
0.116
0.018
1.062
2.005
1.525
1.834
4.519
1.160
90th 95th
1.544 2.105
2.468
2.170
0.098 0.295
0.421
0.182
0.301 0.578
0.339
0.503
0.164 0.610
0.862
0.513
3.513 8.259
6.115
1.662
0.387 0.563
0.472
0.302
0.126 0.241
0.420
0.091
2.471 2.754
3.578
2.424
3.626 8.305
6.447
1.837
N
58
15
19
22
12
15
54
15
18
44
15
17
57
15
19
53
14
18
30
5
7
58
15
19
57
15
19
Consumers Only
%
100
100
100
38
80
79
93
100
95
76
100
89
98
100
100
91
93
95
52
33
37
100
100
100
98
100
100
GMa
0.215
0.645
0.294
0.023
0.049
0.017
0.061
0.072
0.066
0.043
0.056
0.041
0.707
1.188
0.456
0.065
0.098 j
0.066
0.037
0.207
0.028
0.489
1.146
0.619
0.736
1.225
0.464
MSEb
1.219
1.337
1.402
1.447
1.503
1.503
1.186
1.335
1.429
1.218
1.435
1.434
1.199
1.419
1.415
.180
1.339
1.350
1.259
1.447
1.875
1.163
1.249
1.329
1.197
1.426
I All
Q
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5
3
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1=
a
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Table 10-106. Adult Consumption Rate (g/kg-day) by Age (continued)
All Adult Respondents (Including Non-Consumers)
Species/Age Group
All Seafood (p = 0.09)
16 to 42 Years 58 2.463
43 to 54 Years 15 3.884
55 Years and 19 2.522
Over
N = Sample size.
SB = Standard error.
LCL = Lower confidence interval.
UCL = Upper confidence interval.
GM = Geometric mean.
MSB = Multiplicative standard error.
95%
LCL
0.387 1.704
0.781 2.353
0.927 0.705
95%
UCL 5th
3.222 0.247
5.415
4.339
50m
1.270
3.869
1.393
Percentiles
75th 90th
3.410 6.206
4.942 9.725
2.574 5.220
Note />-value is 2-sided and based upon Kruskul-Wallis test. The 95% CL is based on the normal distribution. The 5
less than 20 respondents.
Source: Duncan, 2000.
Consumers Only
g.th JV /O U1V1 IVlOii
9.954 58 100 1.384 1.156
15 100 2.665 1.295
19 100 1.340 1.293
and 95 percentiles are not reported for groups with
Q
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Table 10-107. Consumption Rates for Native American Children (g/kg-day), All Children (including non-consumers): Individual Finfish and Shellfish
and Fish
Groups
Group Species N Mean SE 95% LCL
Group E
Manila/Littleneck clams 31 0.095 0.051 0.000
Horse clams 31 0.022 0.013 0.000
Butter clams 31 0.021 0.014 0.000
Geoduck 31 0.112 0.041 0.033
Cockles 31 0.117 0.079 0.000
Oysters 31 0.019 0.012 0.000
31 0.001 0.001 0.000
Moon snails 3 1 0.000
31 0.093 0.038 0.019
Dungeness crab 31 0.300 0.126 0.053
Mussels Red rock crab 31 0.007 0.003 0.001
Scallops 31 0.011 0.006 0.000
ShnmP 31 0.002 0.002 0.000
Sea urchin 31 0.000
Sea cucumber 31 0.000
g(jQ«pAa 31 0.271 0.117 0.043
Group Bb 31 0.004 0.002 0.000
Group Cc 31 0.131 0.040 0.052
Group Dd 31 0.030 0.011 0.008
Group Fe 31 0.240 0.075 0.094
All Finfish 31 0.677 0.168 0.346
All Shellfish 31 0.801 0.274 0.265
All Seafood 31 1.477 0.346 0.799
a Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead.
Group B is finfish, including smelt and herring.
95% UCL
0.195
0.048
0.048
0.191
0.271
0.043
0.002
-
0.168
0.547
0.014
0.022
0.005
-
-
0.499
0.008
0.210
0.053
0.387
1.007
1.337
2.155
P5
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.026
0.000
0.042
Median
0.031
0.000
0.000
0.027
0.000
0.000
0.000
0.000
0.004
0.047
0.000
0.000
0.000
0.000
0.000
0.063
0.000
0.036
0.010
0.092
0.306
0.287
0.724
P75
0.063
0.006
0.000
0.116
0.054
0.056
0.000
0.000
0.059
0.166
0.000
0.005
0.000
0.000
0.000
0.216
0.000
0.205
0.037
0.254
0.740
0.799
1.983
p90
0.181
0.048
0.041
0.252
0.240
0.058
0.000
0.000
0.394
1.251
0.046
0.031
0.000
0.000
0.000
0.532
0.015
0.339
0.081
0.684
2.110
2.319
3.374
p95
0.763
0.269
0.247
0.841
1.217
0.205
0.011
0.000
0.712
2.689
0.064
0.089
0.000
0.000
0.000
2.064
0.038
0.838
0.191
1.571
3.549
4.994
7.272
Maximum
1.597
0.348
0.422
1.075
2.433
0.362
0.026
0.000
0.982
2.833
0.082
0.174
0.411
0.000
0.000
3.559
0.069
1.014
0.342
1.901
4.101
7.948
9.063
c Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish, and greenling.
Group D is finfish, including halibut, sole, flounder, and rockfish.
Group F includes tuna, other finfish, and all others not included in Groups A, B
= Not applicable.
A' = Sample size.
SE = Standard error
LCL = Lower confidence limit
UCL = Upper confidence limit
p5 . . .p95 = Percentile value.
Note: The minimum consumption for all species and groups was zero, except for "All
Seafood" was 0.035.
Source: Duncan, 2000.
C, and D.
Finfish" and "All Seafood.'
' The minimum
rate for "All
Finfish"
was 0.023, and
for "All
Q
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ft
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-108. Consumption Rates for Native American Children (g/kg-day), Consumers Only: Individual
Finfish and Shellfish and Fish Groups
Group Species
Group E Manila/Littleneck clams
Horse clams
Butter clams
Geoduck
Cockles
Oysters
Mussels
Moon snails
Shrimp
Dungeness crab
Red rock crab
Scallops
Squid
Sea urchin
Sea cucumber
Group Aa
Group Bb
Group Cc
Group Dd
Group Fe (tuna/other finfish)
All finfish
All shellfish
All seafood
jV Mean SE Median
23 0.128 0.068 0.043
12 0.058 0.032 0.009
6 0.106 0.066 0.032
22 0.158 0.054 0.053
10 0.361 0.233 0.078
10 0.060 0.035 0.015
1 0.026
0 - - -
17 0.170 0.064 0.035
21 0.443 0.179 0.082
5 0.046 0.011 0.051
8 0.042 0.019 0.027
2 0.033 0.008 0.033
0 - - -
0 - - -
28 0.300 0.128 0.112
5 0.023 0.012 0.017
25 0.163 0.048 0.048
17 0.055 0.019 0.033
24 0.311 0.092 0.177
31 0.677 0.168 0.306
28 0.886 0.299 0.363
31 1.477 0.346 0.724
Percentiles
75th
0.066
0.046
0.203
0.230
0.291
0.074
-
0.299
0.305
0.067
0.032
-
0.246
0.043
0.236
0.064
0.336
0.740
0.847
1.983
90th
0.200
0.308
-
0.554
2.230
0.336
-
0.621
2.348
-
-
0.599
0.493
0.140
1.035
2.110
2.466
3.374
a Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead.
b Group B is finfish, including smelt and herring.
0 Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish, and greenling.
d Group D is finfish, including halibut, sole, flounder, and rockfish.
e Group F includes tuna, other finfish, and all others not included in Groups A, B, C, and D.
TV = Sample size.
SE = Standard error.
= No data.
Source: Duncan, 2000.
Page
10-180
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-109. Percentiles and Mean
of Consumption Rates for Adult
Consumers Only (g/kg-day)
Percentiles
Species TV
Anadromous
fish 117
Pelagic fish 62
Bottom fish 94
Shellfish 86
Other fish 39
Allfinfish 117
All fish 117
Mean
0.672
0.099
0.093
0.282
0.046
0.799
1.021
SD
1.174
0.203
0.180
0.511
0.066
1.263
1.407
95% CI
Squaxin
5th
10*
25th
50*
75th
90th
95th
Island Tribe
(0.522-1.034)
(0.064-0
(0.065-0
(0.208-0
(0.031-0
.181)
.140)
.500)
.073)
(0.615-1.136
(0.826-1
.368)
0.016
0.004
0.006
0.006
0.002
0.031
0.050
0.028
0.007
0.007
0.015
0.005
0.056
0.097
0.093
0.014
0.016
0.051
0.006
0.139
0.233
0.308
0.035
0.037
0.126
0.019
0.383
0.543
0.802
0.086
0.079
0.291
0.046
1.004
1.151
1.563
0.226
0.223
0.659
0.129
1.826
2.510
2.086
0.349
0.370
1.020
0.161
2.537
3.417
Tulalip Tribe
Anadromous
fish 72
Pelagic fish 38
Bottom fish 44
Shellfish 61
Other fish 36
All finfish 72
All fish 73
0.451
0.077
0.062
0.559
0.075
0.530
1.026
0.671
0.100
0.092
1.087
0.119
0.707
1.563
(0.321-0
(0.051-0
(0.043-0
(0.382-1
(0.044-0
(0.391-0
(0.772-1
.648)
.118)
.107)
.037)
.130)
.724)
.635)
0.010
0.005
0.006
0.037
0.004
0.017
0.049
0.020
0.011
0.007
0.047
0.004
0.026
0.074
0.065
0.015
0.011
0.104
0.011
0.119
0.238
0.194
0.030
0.030
0.196
0.022
0.286
0.560
0.529
0.088
0.077
0.570
0.054
0.603
1.134
1.372
0.216
0.142
1.315
0.239
1.642
2.363
1.990
0.266
0.207
1.824
0.372
2.132
2.641
N = Sample size.
SD = Standard deviation.
CI = Confidence interval.
Source: Polissaretal.,
2006.
Exposure Factors Handbook
September 2011
Page
10-181
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I
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Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only (g/kg-day)
Percentiles
Species
Sex
N
Mean
SD
95% CI
5*
10th
25th
50th
75th
90th
95th
Squaxin Island Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
65
52
39
23
55
39
52
34
27
12
65
52
65
52
0.596
0.766
0.104
0.091
0.091
0.096
0.305
0.245
0.047
0.045
0.735
0.878
0.999
1.049
0.629
1.618
0.235
0.136
0.185
0.175
0.586
0.372
0.066
0.068
0.784
1.686
0.991
1.808
(0.465-0.770)
(0.463-1.458)
(0.055-0.219)
(0.050-0.160)
(0.060-0.185)
(0.058-0.177)
(0.215-0.645)
(0.149-0.407)
(0.029-0.085)
(0.016-0.100)
(0.586-0.980)
(0.546-1.652)
(0.794-1.291)
(0.712-1.793)
0.026
0.016
0.003
0.005
0.005
0.006
0.006
0.007
0.003
-
0.044
0.026
0.082
0.041
0.039
0.023
0.008
0.007
0.007
0.007
0.014
0.018
0.005
0.004
0.079
0.039
0.157
0.061
0.163
0.068
0.013
0.017
0.017
0.014
0.052
0.047
0.006
0.008
0.226
0.115
0.335
0.183
0.388
0.184
0.037
0.030
0.041
0.034
0.136
0.119
0.020
0.015
0.500
0.272
0.775
0.353
0.816
0.656
0.074
0.096
0.077
0.089
0.337
0.250
0.061
0.037
1.045
0.840
1.196
1.083
1.313
1.736
0.181
0.322
0.180
0.226
0.662
0.563
0.124
0.144
1.552
1.908
2.036
2.918
1.957
3.321
0.299
0.349
0.365
0.330
0.782
1.163
0.139
-
2.181
3.687
2.994
4.410
Tulalip Tribe
Anadromous fish
Pelagic fish
Bottom fish
Male
Female
Male
Female
Male
Female
41
31
24
14
24
20
0.546
0.327
0.066
0.096
0.061
0.063
0.754
0.528
0.099
0.103
0.106
0.073
(0.373-0.856)
(0.189-0.578)
(0.037-0.119)
(0.046-0.153)
(0.035-0.147)
(0.039-0.103)
0.011
0.014
0.013
-
0.006
0.007
0.020
0.028
0.014
0.005
0.006
0.008
0.066
0.066
0.016
0.016
0.009
0.014
0.408
0.134
0.030
0.053
0.030
0.029
0.570
0.290
0.064
0.156
0.070
0.093
1.433
0.625
0.175
0.227
0.097
0.179
2.085
1.543
0.223
-
0.142
0.214
Q
I
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I
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&
a,
I,
-------
§ §
ft ft
s?
I
C
ft
Table 10-110. Percentiles and Mean of Consumption Rates by Sex
for Adult Consumers Only (g/kg-day) (continued)
Percentiles
Species
Shellfish
Other fish
All finfish
All fish
N
SD
CI
Sex
Male
Female
Male
Female
Male
Female
Male
Female
N
35
26
24
12
41
31
42
31
Mean
0.599
0.505
0.064
0.097
0.620
0.411
1.140
0.872
SD
1.261
0.818
0.114
0.131
0.795
0.561
1.805
1.168
95% CI
(0.343-1.499)
(0.292-1.018)
(0.029-0.134)
(0.041-0.190)
(0.438-0.966)
(0.265-0.678)
(0.785-2.047)
(0.615-1.453)
5th
0.036
0.043
0.004
-
0.017
0.025
0.049
0.066
10*
0.048
0.047
0.004
0.011
0.020
0.036
0.068
0.144
25th
0.098
0.117
0.007
0.015
0.098
0.126
0.208
0.305
50*
0.183
0.215
0.026
0.022
0.421
0.236
0.623
0.510
75th
0.505
0.582
0.043
0.142
0.706
0.404
1.142
0.963
90th
1.329
1.074
0.174
0.254
1.995
0.924
2.496
1.938
95th
1.826
1.357
0.334
-
2.185
1.769
2.638
2.317
Sample size.
Standard deviation.
Confidence interval.
No data.
Source: Polissar et al., 2006.
Q
I
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t
Si
&
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I
»r
Table 10-111.
Species
Anadromous
fish
Pelagic fish
Bottom fish
Shellfish
Other fish
Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only — Squaxin Island Tribe (g/kg-day)
Age
Group
(years)
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
Percentiles
N
54
41
11
11
22
30
4
6
41
35
9
9
44
27
5
10
20
10
2
7
Mean
0.664
0.563
1.126
0.662
0.067
0.128
0.154
0.036
0.063
0.126
0.159
0.035
0.335
0.264
0.321
0.076
0.079
0.014
0.007
0.010
SD
1.392
0.820
1.511
0.681
0.086
0.269
0.239
0.023
0.102
0.225
0.302
0.031
0.657
0.321
0.275
0.079
0.079
0.008
0.003
0.007
95% CI
(0.430-1.438)
(0.376-0.914)
(0.595-2.791)
(0.321-1.097)
(0.040-0.114)
(0.063-0.272)
(0.027-0.396)
(0.020-0.053)
(0.043-0.120)
(0.076-0.276)
(0.029-0.460)
(0.020-0.065)
(0.211-0.729)
(0.171-0.422)
(0.137-0.589)
(0.033-0.124)
(0.053-0.122)
(0.009-0.019)
(0.005-0.009)
(0.006-0.015)
5th 10th
0.019 °-°26
0.023 0.031
0.212
0.015
0.006 0.007
0.003 0.005
-
-
0.004 0.006
0.010 0.013
0.009
0.006
0.014 0.019
0.016 0.054
-
0.005
0.004 0.005
0.005
-
-
25th
0.078
0.073
0.278
0.107
0.014
0.014
0.033
0.017
0.012
0.023
0.014
0.018
0.041
0.082
0.100
0.007
0.025
0.007
-
0.006
50*
0.233
0.292
0.771
0.522
0.035
0.029
0.045
0.038
0.034
0.051
0.029
0.034
0.127
0.146
0.335
0.042
0.046
0.015
0.007
0.008
75*
0.863
0.590
0.948
0.924
0.081
0.101
0.166
0.047
0.069
0.111
0.067
0.043
0.327
0.277
0.364
0.155
0.124
0.020
-
0.014
90th
1.236
1.354
2.160
1.636
0.186
0.248
-
-
0.115
0.273
0.451
0.060
0.698
0.582
-
0.180
0.161
0.022
-
-
95th
1.969
2.062
-
-
0.228
0.626
-
-
0.221
0.446
-
-
1.046
0.984
-
-
0.218
-
-
-
Q
I
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Si
&
a,
-------
§ §
ft ft
s?
I
Oo
ft
Table
Species
10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only — Squaxin Island Tribe (g/kg-day)
(continued)
Age
Group
(years)
Allfinfish 18 to 34
All fish
N
SD
CI
Source:
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
= Sample size.
= Standard deviation.
= Confidence interval.
= No data.
Polissar et al., 2006.
Percentiles
N
54
41
11
11
54
41
11
11
Mean
0.739
0.764
1.312
0.711
1.041
0.941
1.459
0.786
SD
1.417
1.001
1.744
0.699
1.570
1.217
1.773
0.727
95% CI
(0.508-1.372)
(0.527-1.173)
(0.690-3.219)
(0.386-1.259)
(0.729-1.741)
(0.652-1.453)
(0.770-3.258)
(0.446-1.242)
5th 10th
0.025 0.039
0.046 0.082
0.212
0.027
0.052 0.107
0.051 0.136
0.317
0.058
25th
0.105
0.226
0.297
0.119
0.217
0.248
0.327
0.122
50*
0.289
0.383
0.909
0.601
0.500
0.483
1.106
0.775
75*
0.887
0.816
1.119
0.986
1.117
0.975
1.301
1.091
90th
1.466
1.859
2.188
1.637
2.669
2.227
2.936
1.687
95th
2.296
2.423
-
-
3.557
3.009
-
-
Q
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-112. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only — Tulalip Tribe
(g/kg-day)
Species
Anadromous
fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
= No
Age
Group
(years)
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
18 to 34
35 to 49
50 to 64
>65
data.
Source: Polissar et al.,
Percentiles
N
27
23
16
6
12
15
8
3
14
16
11
o
6
23
19
14
5
15
13
6
2
27
23
16
6
27
24
16
6
2006.
Mean
0.298
0.725
0.393
0.251
0.092
0.077
0.077
0.008
0.075
0.066
0.051
0.015
0.440
1.065
0.245
0.062
0.097
0.057
0.075
0.024
0.378
0.821
0.467
0.263
0.806
1.661
0.710
0.322
SD
0.456
0.928
0.550
0.283
0.099
0.118
0.085
0.009
0.138
0.069
0.056
0.005
0.487
1.784
0.216
0.064
0.146
0.085
0.138
0.015
0.548
0.951
0.535
0.293
0.747
2.466
0.591
0.344
95% CI
(0.169-0.524)
(0.436-1.202)
(0.225-0.854)
(0.065-0.475)
(0.051-0.173)
(0.039-0.206)
(0.037-0.160)
(0.002-0.014)
(0.033-0.205)
(0.041-0.112)
(0.026-0.098)
(0.008-0.018)
(0.289-0.702)
(0.536-2.461)
(0.158-0.406)
(0.027-0.135)
(0.043-0.197)
(0.022-0.123)
(0.015-0.215)
(0.014-0.024)
(0.222-0.680)
(0.532-1.315)
(0.311-0.925)
(0.091-0.518)
(0.575-1.182)
(0.974-3.179)
(0.513-1.144)
(0.107-0.642)
5th 10th
0.011 0.016
0.010 0.032
0.059
-
0.016
0.013
-
-
0.007
0.007
0.007
-
0.049 0.053
0.049 0.074
0.048
-
0.010
0.004
-
-
0.018 0.022
0.020 0.047
0.186
-
0.071 0.136
0.017 0.069
0.278
-
25th
0.061
0.078
0.164
0.022
0.021
0.015
0.027
0.003
0.010
0.023
0.011
0.013
0.131
0.123
0.117
0.023
0.017
0.006
0.012
-
0.080
0.116
0.227
0.030
0.231
0.177
0.370
0.062
50th
0.120
0.431
0.228
0.164
0.054
0.021
0.034
0.004
0.020
0.053
0.036
0.017
0.196
0.250
0.224
0.046
0.033
0.014
0.018
0.024
0.156
0.602
0.301
0.176
0.617
0.968
0.495
0.195
75th
0.315
0.719
0.420
0.425
0.124
0.087
0.090
0.011
0.078
0.077
0.069
0.018
0.582
1.222
0.282
0.060
0.102
0.049
0.038
-
0.438
0.898
0.503
0.430
1.126
2.005
0.944
0.475
90th
0.713
2.001
0.599
-
0.218
0.189
-
-
0.142
0.152
0.119
-
1.076
2.265
0.417
-
0.319
0.187
-
-
0.840
2.035
0.615
-
1.960
3.147
1.070
-
95*
1.281
2.171
-
-
-
-
-
-
-
-
-
-
1.410
4.351
-
-
-
-
-
-
1.677
2.268
-
-
2.457
5.707
-
-
Page
10-186
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-113. Percentiles
and Mean of Consumption Rates for Child Consumers Only (g/kg-day)
Percentiles
Species
N
Mean
SD
5th 10*
25*
50*
75*
90*
95*
Squaxin Island Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
33
21
18
31
30
35
36
0
0
0
2
0
0
2
392
157
167
311
577
538
890
1.295
0.245
0.362
8.605
0.584
1.340
8.433
0.005 0
0.010 0
0
0.006 0
0.012 0
0.005 0
006
014
006
025
051
007
0.012 0.019
0.030
0.019
0.014
0.050
0.111
0.046
0.244
0.049
0.044
0.026
0.262
0.400
0.062
0.704
0.130
0.107
0.050
0.404
0.566
0.216
1.495
0.686
0.547
0.482
0.769
1.620
1.698
2.831
0.786
0.712
-
4.479
1.628
2.334
7.668
Tulalip Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
14
7
2
11
1
15
15
0
0
0
0
0
0
0
148
152
044
311
115
310
449
0.229
0.178
0.005
0.392
0.115
0.332
0.529
0
-
-
0
-
0
0
012
-
-
012
-
027
066
0.026
0.027
-
0.034
-
0.082
0.088
0.045
0.053
0.041
0.036
-
0.133
0.215
0.136
0.165
-
0.518
-
0.431
0.601
0.334
-
-
0.803
-
0.734
0.884
-
-
-
-
-
-
-
N = Sample size.
SD = Standard deviation.
= No data.
Source: Polissar et al.,
2006.
Exposure Factors Handbook
September 2011
Page
10-187
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-114.
Percentiles and Mean of Consumption Rates by Sex
for Child Consumers Only (g/kg-day)
Percentiles
Species
Sex
N
Mean
SD 5th 10th
25th
50th
75th 90th 95th
Squaxin Island Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All fmfish
All fish
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
15
18
8
13
6
12
13
18
13
17
15
20
15
21
0.702
0.155
0.102
0.179
0.038
0.244
0.275
3.799
0.836
0.400
0.787
0.372
1.700
3.655
1.937 - 0.009
0.253 - 0.005
0.138
0.280 - 0.015
0.057
0.442 - 0.005
0.244 - 0.036
11.212 - 0.008
0.663 - 0.106
0.463 - 0.013
1.940 - 0.009
0.719 0.005 0.005
1.965 - 0.061
10.738 0.008 0.014
0.026
0.025
0.015
0.020
0.016
0.010
0.047
0.050
0.232
0.096
0.038
0.037
0.476
0.160
0.062
0.046
0.058
0.040
0.020
0.028
0.241
0.229
0.448
0.311
0.062
0.071
1.184
0.599
0.331 1.082
0.090 0.600
0.099
0.109 0.681
0.026
0.105 0.736
0.353 0.462
0.490 1.333
1.530 1.625
0.486 0.610
0.521 1.500
0.179 1.408 2.119
1.937 2.444
0.916 2.764 16.374
Tulalip Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All fmfish
All fish
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
7
7
5
2
0
2
5
6
0
1
8
7
8
7
0.061
0.237
0.106
0.265
-
0.044
0.141
0.431
-
0.115
0.208
0.433
0.202
0.745
0.052
0.306
0.081
0.350
.
0.005
0.221
0.459
.
0.115
0.176
0.440
0.169
0.670
0.023
0.032
0.044
-
-
-
0.012
0.034
-
-
0.087
0.045
0.071
0.155
0.034
0.080
0.053
0.017
-
0.041
0.027
0.219
-
-
0.133
0.165
0.122
0.488
0.067
0.198
0.128
-
.
.
0.110
0.651
.
.
0.322
0.652
0.233
0.835
N = Sample size.
SD = Standard deviation.
= No data
Source: Polissar et al., 2006.
Page
10-188
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-115. Consumption Rates of API Community Members
Median Mean
Category N (g/kg-day) (g/kg-day)
Anadromous 202 0.093 0.201
Fish
Pelagic Fish 202 0.215 0.382
Freshwater Fish 202 00.43 0.110
Bottom Fish 202 0.047 0.125
Shellfish Fish 202 0.498 0.867
Seaweed/Kelp 202 0.014 0.084
Miscellaneous 202 0.056 0.121
Seafood
AllFinfish 202 0.515 0.818
All Fish 202 1.363 1.807
All Seafood 202 1.439 1.891
a Percentage of consumption = the percent
fish eaten was anadromous fish).
N = Sample size.
SE = Standard error.
LCI = 95% lower confidence interval.
Percentage of
Consumption3
10.6%
20.2%
5.8%
6.6%
45.9%
4.4%
6.4%
43.3%
95.6%
100.0%
of each category
SE
0.008
0.013
0.005
0.006
0.023
0.005
0.004
0.023
0.042
0.043
95% LCI 95% UCI
(g/kg-day) (g/kg-day)
0.187
0.357
0.101
0.113
0.821
0.075
0.112
0.774
1.724
1.805
that makes up the total
0.216
0.407
0.119
0.137
0.913
0.093
0.130
0.863
1.889
1.976
(i.e., 10
90th
Percentile
(g/kg-day)
0.509
0.829
0.271
0.272
1.727
0.294
0.296
1.638
3.909
3.928
6% of total
UCI = 95% upper confidence interval.
Note: Confidence intervals were computed based on the Student's t-distribution. Rates were weighted across
ethnic groups.
Source: U.S. EPA, 1999.
Exposure Factors Handbook Page
September 2011 10-189
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-116. Demographic Characteristics of "Higher" and "Lower" Seafood Consumers
N
Female 107
Male 95
18 to 29 years 78
30 to 54 years 85
55+ 39
Cambodian 20
Chinese 30
Filipino 30
Japanese 29
Korean 22
Laotian 20
Mien 10
Hmong 5
Samoan 10
Vietnamese 26
Non-fishermen 136
Fishermen 66
a Higher Consumer:
b Higher Consumer:
TV = Sample size.
Source: U.S. EPA, 1999.
All
Lower
Consumers (%)
76
81
85
79
64
90
83
80
48
91
75
90
100
100
69
82
71
>75 percentile =
>75 percentile =
Finfish
Higher
Consumers3 (%)
24
19
15
21
36
10
17
20
52
9
25
10
0
0
31
18
29
1.144 g/kg-day.
1.072g/kg-day.
Lower
Consumers
71
79
73
78
72
70
70
87
79
68
75
90
100
100
50
76
73
Shellfish
Higher
(%) Consumers'3 (%)
29
21
27
22
28
30
30
13
21
32
25
10
0
0
50
24
27
Page
10-190
Exposure Factors Handbook
September 2011
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II
§
a
I
Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community
Category
Anadromous fish
(p< 0.001)
.
Filipino
Pelagic Fish
(p< 0.001)
T"1'! '
r ilipmo
Freshwater Fish
(a< 0.001)
len
.
Filipino
Ethnicity
Cambodian
Chinese
Japanese
Korean
Laotian
Mien
Hmong
Samoan
Vietnamese
All Ethnicity (1)
Cambodian
Chinese
Japanese
Korean
Laotian
Hmong
Samoan
Vietnamese
All Ethnicity (1)
Cambodian
Chinese
Japanese
Korean
Laotian
Mien
Hmong
Samoan
Vietnamese
All Ethnicity (1)
N
20
30
30
29
22
20
10
5
10
26
202
20
30
30
29
22
20
10
5
10
26
202
20
30
30
29
22
20
10
5
10
26
202
Mean
0.118
0.193
0.152
0.374
0.091
0.187
0.018
0.059
0.067
0.124
0.201
0.088
0.325
0.317
0.576
0.313
0.412
0.107
0.093
0.499
0.377
0.382
0.139
0.084
0.132
0.021
0.032
0.282
0.097
0.133
0.026
0.341
0.110
SE
0.050
0.052
0.027
0.056
0.026
0.064
0.008
0.013
0.017
0.026
0.008
0.021
0.068
0.081
0.079
0.056
0.138
0.076
0.028
0.060
0.086
0.013
0.045
0.023
0.034
0.006
0.015
0.077
0.039
0.051
0.007
0.064
0.005
10
Percentile
0.000
0.012
0.025
0.086
0.007
0.002
0.000
n/a
0.012
0.017
0.016
0.000
0.022
0.051
0.132
0.073
0.005
0.000
n/a
0.128
0.059
0.046
0.000
0.000
0.018
0.000
0.000
0.002
0.007
n/a
0.000
0.068
0.000
Median
0.030
0.066
0.100
0.251
0.048
0.069
0.011
0.071
0.054
0.072
0.093
0.061
0.171
0.132
0.429
0.186
0.115
0.09
0.090
0.535
0.208
0.215
0.045
0.015
0.086
0.007
0.008
0.099
0.070
0.081
0.025
0.191
0.043
90
Percentile
0.453
0.587
0.384
0.921
0.248
0.603
0.080
n/a
0.185
0.349
0.509
0.293
0.824
0.729
1.072
0.843
1.061
0.716
n/a
0.792
0.956
0.829
0.565
0.327
0.273
0.071
0.160
1.006
0.407
n/a
0.061
1.036
0.271
% with
Non-Zero
Consumption
18
30
29
29
22
18
7
5
10
26
194
17
30
30
29
22
20
7
5
10
26
196
18
24
30
20
13
18
10
5
9
26
173
(g/kg-day)a
Consumers
90
100
96.7
100
100
90
70
100
100
100
96
85
100
100
100
100
100
70
100
100
100
97
90
80
100
69
59.1
90
100
100
90
100
85.6
95%
LCI
0.014
0.086
0.098
0.261
0.037
0.054
0.000
0.026
0.030
0.071
0.187
0.044
0.187
0.151
0.415
0.196
0.124
-0.064
0.021
0.365
0.201
0.357
0.045
0.037
0.062
0.010
0.002
0.122
0.010
0.002
0.011
0.209
0.101
95%
UCI
0.223
0.300
0.206
0.488
0.146
0.321
0.036
0.091
0.104
0.176
0.216
0.131
0.463
0.482
0.737
0.429
0.700
0.277
0.164
0.633
0.553
0.407
0.232
0.131
0.202
0.032
0.062
0.442
0.184
0.263
0.041
0.472
0.119
Q
I
^
t
Si
&
a,
QTQ
-------
I
»r
Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)a (continued)
Category
Bottom Fish
(p< 0.001)
Filipino
Laotian,
Shelmsn Fish
(p^b.OOl)
Filipino
Seaweed/Kelp
(p< 0.001)
Filipino
Ethnicity
Cambodian
Chinese
Japanese
Korean
Hmong
Samoan
Vietnamese
All Ethnicity (1)
Cambodian
Chinese
Japanese
Korean
Mien
Hmong
Samoan
Vietnamese
All Ethnicity (1)
Cambodian
Chinese
Japanese
Korean
Laotian
Hmong
Samoan
Vietnamese
All Ethnicity (1)
N
20
30
30
29
22
20
10
5
10
26
202
20
30
30
29
22
20
10
5
10
26
202
20
30
30
29
22
20
10
5
10
26
202
Mean
0.045
0.082
0.165
0.173
0.119
0.066
0.006
0.036
0.029
0.102
0.125
0.919
0.985
0.613
0.602
1.045
0.898
0.338
0.248
0.154
1.577
0.867
0.002
0.062
0.009
0.190
0.200
0.004
0.000
0.002
0.000
0.017
0.084
SE
0.025
0.026
0.043
0.044
0.026
0.031
0.003
0.021
0.005
0.044
0.006
0.216
0.168
0.067
0.089
0.251
0.259
0.113
0.014
0.024
0.260
0.023
0.001
0.022
0.004
0.043
0.050
0.003
0.000
0.001
0.000
0.012
0.005
10
Percentile
0.000
0.004
0.001
0.023
0.000
0.000
0.000
n/a
0.008
0.000
0.000
0.085
0.176
0.188
0.116
0.251
0.041
0.015
n/a
0.086
0.247
0.168
0.000
0.001
0.000
0.019
0.011
0.000
0.000
n/a
0.000
0.000
0.000
Median
0.003
0.033
0.103
0.098
0.062
0.006
0.00
0.024
0.026
0.030
0.047
0.695
0.569
0.505
0.401
0.466
0.424
0.201
0.252
0.138
1.196
0.498
0.000
0.017
0.000
0.082
0.087
0.000
0.000
0.001
0.000
0.000
0.014
90
Percentile
0.114
0.212
0.560
0.554
0.270
0.173
0.026
n/a
0.058
0.388
0.272
2.003
2.804
1.206
1.428
2.808
2.990
1.058
n/a
0.336
4.029
1.727
0.008
0.314
0.025
0.752
0.686
0.013
0.000
n/a
0.000
0.050
0.294
% with
Non-Zero
Consumption
10
28
27
28
19
13
4
3
10
21
163
20
30
30
29
22
19
10
5
10
26
201
7
29
15
29
21
6
0
3
0
6
116
Consumers
50
93.3
90
96.6
86.4
65
40
60
100
80.8
80.7
100
100
100
100
100
95
100
100
100
100
99.5
35
96.7
50
100
95.5
30
0
60
0
23.1
57.4
95%
LCI
-0.006
0.028
0.078
0.083
0.064
0.000
-0.001
-0.017
0.018
0.013
0.113
0.467
0.643
0.477
0.419
0.524
0.357
0.086
0.212
0.100
1.044
0.821
0.000
0.016
0.002
0.101
0.096
-0.001
0.000
0.000
0.000
-0.008
0.075
95%
UCI
0.097
0.135
0.253
0.263
0.173
0.131
0.013
0.088
0.040
0.192
0.137
1.370
1.327
0.750
0.784
1.566
1.439
0.590
0.283
0.208
2.110
0.913
0.004
0.107
0.016
0.279
0.304
0.009
0.000
0.004
0.000
0.043
0.093
Q
I
^
t
Si
&
a,
Mien
-------
II
fi
._
I
Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)a (continued)
Category
Miscellaneous
Fish
(p< 0.001)
... .
Filipino
Laptjan,.
AllFinfish
(p< 0.001)
T7'1 '
r ilipino
T nntirm
Ethnicity
Cambodian
Chinese
Japanese
Korean
Mien
Hmong
Samoan
Vietnamese
All Ethnicity (1)
Cambodian
Chinese
Japanese
Korean
Hmong
Samoan
Vietnamese
All Ethnicity (1)
N
20
30
30
29
22
20
10
5
10
26
202
20
30
30
29
22
20
10
5
10
26
202
Mean
0.113
0.081
0.083
0.246
0.092
0.074
0.015
0.019
0.076
0.089
0.121
0.390
0.683
0.766
1.144
0.555
0.947
0.228
0.319
0.621
0.944
0.818
SE
0.026
0.021
0.025
0.036
0.031
0.021
0.008
0.014
0.028
0.013
0.004
0.098
0.133
0.148
0.124
0.079
0.204
0.117
0.073
0.059
0.171
0.023
10
Percentile
0.000
0.003
0.016
0.032
0.004
0.000
0.000
n/a
0.003
0.013
0.005
0.061
0.114
0.268
0.194
0.180
0.117
0.034
n/a
0.225
0.188
0.166
Median
0.087
0.030
0.043
0.206
0.047
0.025
0.002
0.008
0.045
0.087
0.056
0.223
0.338
0.452
1.151
0.392
0.722
0.097
0.268
0.682
0.543
0.515
90
Percentile
0.345
0.201
0.182
0.620
0.307
0.225
0.063
n/a
0.276
0.184
0.296
1.379
2.024
1.348
2.170
1.204
2.646
1.160
n/a
0.842
2.568
1.638
% with
Non-Zero
Consumption
18
30
30
29
21
15
7
4
10
25
189
20
30
30
29
22
20
10
5
10
26
202
Consumers
(%)
90
100
100
100
95.5
75
70
80
100
96.2
93.6
100
100
100
100
100
100
100
100
100
100
100
95%
LCI
0.058
0.038
0.032
0.173
0.028
0.029
0.003
0.018
0.014
0.062
0.112
0.185
0.412
0.464
0.890
0.391
0.523
-0.032
0.131
0.490
0.593
0.774
95%
UCI
0.168
0.123
0.134
0.139
0.156
0.118
0.033
0.055
0.138
0.115
0.130
0.594
0.954
1.067
1.398
0.719
1.372
0.488
0.507
0.751
1.296
0.863
Q
I
M
t
Si
&
a,
g
&
s
i
3
sT
&
1=
a
£.
Mien
ft
-------
I
»i
Table 10-117. Seafood
Category Ethnicity
All Fish
Cambodian
(p< 0.001) Chinese
... .
Filipino
AllSeaf
Japanese
Korean
Mien
Hmong
Samoan
Vietnamese
All Ethnicity (1)
ood Cambodian
(/?
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-118. Consumption Rates by Sex
for All Asian and Pacific Islander Community
Female
Category
Anadromous Fish (p = 0.8)
Pelagic Fish (p = 0.4)
Freshwater Fish (p= 1.0)
Bottom Fish (p = 0. 6)
Shellfish (p = 0.8)
Seaweed/Kelp (p = 0.5)
Miscellaneous Seafood (p = 0
AllFinfish(^ = 0.8)
All Fish (p = 0.5)
All Seafood (p = 0.4)
TV = Sample size.
SE = Standard error.
TV
107
107
107
107
107
107
5) 107
107
107
107
Mean
(g/kg-day)
0.165
0.349
0.131
0.115
0.864
0.079
0.105
0.759
1.728
1.807
SE
0.022
0.037
0.021
0.019
0.086
0.018
0.013
0.071
0.135
0.139
Median
(g/kg-day)
0.076
0.215
0.054
0.040
0.432
0.005
0.061
0.512
1.328
1.417
TV
95
95
95
95
95
95
95
95
95
95
Male
Mean
(g/kg-day)
0.169
0.334
0.137
0.087
0.836
0.044
0.104
0.726
1.666
1.710
SE
0.02
4
0.04
0.02
0.01
n
0.10
A
0.01
n
0.01
0.07
0.14
Q
0.15
Median
(g/kg-day)
0.080
0.148
0.054
0.034
0.490
0.002
0.055
0.458
1.202
1.257
Note: />-values are based on Mann- Whitney test.
Source: U.S. EPA, 1999.
Exposure Factors Handbook Page
September 2011 10-195
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-119. Types of Seafood
Consumed/Respondents Who Consumed (%)
Type of Seafood (%)
Anadromous Fish
Salmon
Trout
Smelt
Salmon Eggs
Pelagic Fish
Tuna
Cod
Mackerel
Snapper
Rockfish
Herring
Dogfish
Snowfish
Freshwater Fish
Catfish
Tilapia
Perch
Bass
Carp
Crappie
Bottom Fish
Halibut
Sole/Flounder
Sturgeon
Suckers
Shellfish
Shrimp
Crab
Squid
Oysters
Manila/Littleneck Clams
Lobster
Mussel
Scallops
93
61
45
27
86
66
62
50
34
21
7
6
58
45
39
28
22
17
65
42
13
4
98
96
82
71
72
65
62
57
Page
10-196
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-119. Types of Seafood
Consumed/Respondents Who Consumed (%)
(continued)
Type of Seafood (%)
Butter Clams
Geoduck
Cockles
Abalone
Razor Clams
Sea Cucumber
Sea Urchin
Horse Clams
Macoma Clams
Moon snail
Seaweed/Kelp
Seaweed
Kelp
39
34
21
15
16
15
14
13
9
4
57
29
Source: U.S. EPA, 1999.
Exposure Factors Handbook
September 2011
Page
10-197
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-120. Mean, Median
Sample Group „. ^
Ethnicity
African American 32
Southeast Asian 152
Hmong 67
Lao 30
Vietnamese 33
Asian/Pacific Islander 38
Hispanic 45
Native American 6
White 57
Russian 17
All Anglers 373
Southeast Asiand 286
Hmongd 130
Laod 54
Age
18 to 34 143
35 to 49 130
>49 87
Sex
Female 35
Male 336
Household Contains
Women 18 to 49 years 217
Children 174
Awareness6
0 172
1 44
2 115
3 35
4 7
and 95th Percentile Fish Intake
Local Fish Intake3
Mean Median 95th
31.2 21.3 242.3
32.3 17.0 129.4
17.8 14.9 89.6
57.6 21.3 310.4
27.1 21.7 152.4
23.8 15.6 148.3
25.8 19.1 155.9
6.5 NDC ND
23.6 21.3 138.9
23.7 17.7 ND
27.4 19.7 126.6
40.8 17.0 128.5
21.3 14.9 102.1
47.2 17.0 265.8
32.0 24.6 138.9
22.7 14.2 120.5
30.6 17.0 207.0
38.2 22.5 226.8
26.4 19.5 129.3
33.0 21.2 142.2
35.1 22.2 142.8
24.7 18.2 121.6
42.8 28.0 361.1
28.4 21.3 139.6
12.2 13.8 62.4
57.1 36.1 ND
Rates for Different Groups (g/day)
Mean
48.3
42.8
22.3
65.2
55.4
46.1
36.3
69.9
34.7
36.1
40.6
50.3
26.5
54.4
44.9
36.8
44.3
53.9
39.3
46.6
49.2
35.5
52.9
45.8
28.1
65.0
Total Fish Intakeb
Median
21.3
24.1
19.1
24.1
36.1
35.0
14.2
108.4
28.4
35.5
26.1
25.5
17.0
28.4
25.5
24.0
24.1
24.6
26.1
25.5
27.1
23.0
28.5
28.0
20.8
39.0
95th
252.0
180.2
89.6
317.5
249.3
156.4
169.5
ND
139.2
ND
147.3
144.5
119.7
267.0
151.5
143.9
217.2
263.1
146.6
158.1
171.9
143.5
361.1
151.7
95.6
ND
a Locally caught fish.
b Locally caught and commercially obtained fish.
0 Not determined because of insufficient data.
d All data shown are for angler surveying, except for these groups which are rates from combined
angler and community surveys.
e Respondent responses when asked about their awareness of warnings about fish contamination
ranged from 0 = no awareness to 4 = high awareness.
Source: Shilling etal., 2010.
Page
10-198
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-121. Distribution of Quantity of Fish Consumed (in grams) per Eating Occasion,
by Age and Sex
Percentiles
Age (years)-Sex Group
1 to 2 Male-Female
3 to 5 Male-Female
6 to 8 Male-Female
9 to 14 Male
9 to 14 Female
15 to 18 Male
15 to 18 Female
19 to 34 Male
19 to 34 Female
35 to 64 Male
35 to 64 Female
65 to 74 Male
65 to 74 Female
>75 Male
>75 Female
Overall
Mean
52
70
81
101
86
117
111
149
104
147
119
145
123
124
112
117
SD
38
51
58
78
62
115
102
125
74
116
98
109
87
68
69
98
5*
8
12
19
28
19
20
24
28
20
28
20
35
24
36
20
20
25th
28
36
40
56
45
57
56
64
57
80
57
75
61
80
61
57
50th
43
57
72
84
79
85
85
113
85
113
85
113
103
106
112
85
75th
58
85
112
113
112
142
130
196
135
180
152
180
168
170
151
152
90th
112
113
160
170
168
200
225
284
184
258
111
270
111
111
196
111
95*
125
170
170
255
206
252
270
362
111
360
280
392
304
111
225
284
99th
168
240
288
425
288
454
568
643
394
577
480
480
448
336
360
456
Source: Paoetal., 1982.
Exposure Factors Handbook
September 2011
Page
10-199
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-122. Distribution of Quantity of Canned Tuna Consumed (grams) per Eating Occasion, by Age and
Sex
Age (years)-Sex Group
2 to 5
Male-Female
6 to 11
Male-Female
12 to 19
Male
Female
20 to 39
Male
Female
40 to 59
Male
Female
60 and older
Male
Female
Mean SE
37
58
98*
64
84
61
72
60
64
67
3
8
16*
6
7
5
4
4
5
4
Percentiles
5*
5*
14*
14*
15*
14*
14*
13*
12*
12*
10th 25th
8 14
20* 28
18* 49*
18* 28*
27* 49
14* 34
27 37
15 28
17* 37
23 42
SE = Standard error.
* Indicates a statistic that is potentially unreliable because of small sample
variation.
Indicates a percentage that could not be estimated.
Source: Smiciklas-Wright
et al.,
2002 (based on
1994-1996
CSFII data).
50th 75th 90th 95th
29 56 73 85*
49 60 99* 157*
84 162* 170* 186*
56 77* 105* 156*
57 113 160* 168*
56 74 110* 142*
57 96 127 168*
56 74 112 144
56 81 114* 150*
57 85 112 153*
size or large coefficient of
Page Exposure Factors Handbook
10-200 September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-123. Distribution of Quantity of Other Finfish Consumed (grams) per Eating Occasion, by Age and
Sex
Age (years)-Sex Group
2 to 5
Male-Female
6 to 11
Male-Female
12 to 19
Male
Female
20 to 39
Male
Female
40 to 59
Male
Female
60 and older
Male
Female
Mean SE
64
93
4
8
119* 11*
89* 13*
117
111
130
107
111
108
SE = Standard error.
* Indicates a statistic that
variation.
Source: Smiciklas-Wright
et al.,
8
10
7
9
6
6
is potentially
2002 (based
Percentiles
5*
8*
17*
40*
20*
37*
26*
29*
29*
37*
33*
unreliable
10th 25th
16 33
31* 50
50* 64*
26* 47*
47 68
36* 50
47 75
42 51
45 57
42 57
because of small sample
50th 75th 90th 95th
58 77 124 128*
77 119 171* 232*
89 170* 185* 249*
67 124* 164* 199*
100 138 205 256*
85 129 209* 289*
110 153 243 287*
85 123 174 244*
90 133 220 261*
90 130 200 229*
size or large coefficient of
on 1994-1996 CSFII data).
Exposure Factors Handbook Page
September 2011 10-201
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-124. Percentage of Individuals Using Various Cooking Methods
Use
Study Frequency Bake
Connelly etal, 1992 Always 24a
Ever 75a
Connelly etal., 1996 Always 13
Ever 84
CRITFC, 1994 At Least 79
Monthly
Ever 98
Fitzgerald etal., 1995 Not
Specified
Puffer etal., 1981 As Primary 16.3
Method
Pan
Fry
51
88
4
72
51
80
94e'f
52.5
Deep Broil or
Fry Grill Poach
13 24a
59 75a
4
42
14 27 11
25 39 17
71e,g
12
at Specified Frequencies
Boil Smoke Raw Other
46 31 1 34b
29C
49d
73 66 3 67b71c
75d
0.25 19h
24 and 75 listed as bake, BBQ, or poach.
b Dried.
Roasted.
d Canned.
e Not specified whether deep or pan fried.
f Mohawk women.
8 Control population.
h Boil, stew, soup, or steam.
Page
10-202
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-125.
Species
Mean Percent Moisture
Moisture Content
(%)
and Total Fat
Total Fat Content
(%)
Content for Selected Species
Comments
FINFISH
Anchovy, European
Bass, Freshwater
Bass, Striped
Bluefish
Burbot
Butterfish
Carp
Catfish, Channel, Farmed
Catfish, Channel, Wild
Caviar, Black and Red
Cisco
Cod, Atlantic
Cod, Pacific
Croaker, Atlantic
Cusk
Dolphinfish
Drum, Freshwater
Eel
Flatfish, Flounder, and Sole
Grouper
Haddock
Halibut, Atlantic and Pacific
73.37
50.30
75.66
68.79
79.22
73.36
70.86
62.64
79.26
73.41
74.13
66.83
76.31
69.63
75.38
71.58
80.36
77.67
47.50
78.93
1.91
81.22
75.61
75.92
16.14
81.28
76.00
78.03
59.76
76.35
69,68
77.55
71.22
77.33
70.94
69.26
59.31
79.06
73.16
79.22
73.36
79.92
74.25
71.48
77.92
71.69
4.84
9.71
3.69
4,73
2.33
2.99
4.24
5.44
0.81
1.04
8.02
10.28
5.60
7.17
7.59
8.02
2.82
2.85
17.90
69.80
11.90
0.67
0.86
0.86
2.37
0.63
0.81
3.17
12.67
0.69
0.88
0.70
0.90
4.93
6.32
11.66
14.95
1.19
1.53
1.02
1.30
0.72
0.93
0.96
2.29
2.94
Raw
Canned in oil, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
--
Raw
Smoked
Raw
Canned, solids and liquids
Cooked, dry heat
Dried and salted
Raw
Cooked, dry heat
Raw
Cooked, breaded and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw, mixed species
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Exposure Factors Handbook
September 2011
Page
10-203
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Halibut, Greenland
Herring, Atlantic
Herring, Pacific
Ling
Lingcod
Mackerel, Atlantic
Mackerel, Jack
Mackerel, King
Mackerel, Pacific and Jack
Mackerel, Spanish
Milkfish
Monkfish
Mullet, Striped
Ocean Perch, Atlantic
Perch
Pike, Northern
Pike, Walleye
Pollock, Atlantic
Pollock, Walleye
Pompano, Florida
Pout, Ocean
Rockfish, Pacific
Roe
Roughy, Orange
Moisture Content
(%)
70.27
61.88
72.05
64.16
59.70
55.22
71.52
63.49
79.63
73,88
81.03
75.68
63.55
53.27
69.17
75.85
69.04
70.15
61.73
71.67
68.46
70.85
62.63
83.24
78.51
77.01
70.52
78.70
72.69
79.13
73.25
78.92
72.97
79.31
73.47
78.18
72.03
81.56
74.06
71.12
62.97
81.36
76.10
79.26
73.41
67.73
58.63
75.67
66.97
Total Fat Content
(%)
13.84
17.74
9.04
11.59
12.37
18.00
13.88
17.79
0.64
0.82
1.06
1.36
13.89
17.81
6.30
2.00
2.56
7.89
10.12
6.30
6.32
6.73
8.63
1.52
1.95
3.79
4.86
1.63
2.09
0.92
1.18
0.69
0.88
1.22
1.56
0.98
1.26
0.80
1.12
9.47
12.14
0.91
1.17
1.57
2.01
6.42
8.23
0.70
0.90
Comments
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Kippered
Pickled
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Page
10-204
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September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Sablefish
Salmon, Atlantic, Farmed
Salmon, Atlantic, Wild
Salmon, Chinook
Salmon, Chum
Salmon, Coho, Farmed
Salmon, Coho, Wild
Salmon, Pink
Salmon, Sockeye
Sardine, Atlantic
Sardine, Pacific
Scup
Sea Bass
Seatrout
Shad, American
Shark, mixed species
Sheepshead
Smelt, Rainbow
Snapper
Spot
Sturgeon
Sucker, white
Sunfish, Pumpkinseed
Moisture Content
(%)
71.02
62.85
60.14
68.90
64.75
68.50
59.62
71.64
65.60
72.00
75.38
68.44
70.77
70.47
67.00
72.66
71.50
65.39
76.35
69.68
68.81
70.24
61.84
67.51
59.61
66.65
75.37
68.42
78.27
72.14
78.09
71.91
68.19
59.22
73.58
60.09
77.97
69.04
78.77
72.79
76.87
70.35
75.95
69.17
76.55
69.94
62.50
79.71
73.99
79.50
Total Fat Content
(%)
15.30
19.62
20.14
10.85
12.35
6.34
8.13
10.43
13.38
4.32
3.77
4.83
5.50
7.67
8.23
5.93
4.30
7.50
3.45
4.42
6.05
8.56
10.97
7.31
11.45
10.46
2.73
3.50
2.00
2.56
3.61
4.63
13.77
17.65
4.51
13.82
2.41
1.63
2.42
3.10
1.34
1.72
4.90
6.28
4.04
5.18
4.40
2.32
2.97
0.70
Comments
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Cooked, moist heat
Raw
Cooked, dry heat
Canned, solids with bone and liquid
Raw
Cooked, dry heat
Canned, drained solids with bone
Canned in oil, drained solids with bone
Canned in tomato sauce, drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, batter-dipped and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Exposure Factors Handbook
September 2011
Page
10-205
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Surimi
Swordfish
Tilapia
Tilefish
Trout, Mixed Species
Trout, Rainbow, Farmed
Trout, Rainbow, Wild
Tuna, Fresh, Bluefm
Tuna, Fresh, Skipjack
Tuna, Fresh, Yellowfm
Tuna, Light
Tuna, White
Turbot, European
Whitefish, mixed species
Whiting, mixed species
Wolffish, Atlantic
Yellowtail, mixed species
Moisture Content
(%)
73.72
76.34
75.62
68.75
78.08
71.59
78.90
70.24
71.42
63.36
72.73
67.53
71.87
70.50
68.09
59.09
70.58
62.28
70.99
62.81
59.83
74.51
64.02
73.19
76.95
70.45
72.77
65.09
70.83
80.27
74.71
79.90
74.23
74.52
67.33
Total Fat Content
(%)
0.90
0.90
4.01
5.14
1.70
2.65
2.31
4.69
6.61
8.47
5.40
7.20
3.46
5.82
4.90
6.28
1.01
1.29
0.95
1.22
8.21
0.82
8.08
2.97
2.95
3.78
5.86
7.51
0.93
1.31
1.69
2.39
3.06
5.24
6.72
Comments
Cooked, dry heat
-
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned in oil, drained solids
Canned in water, drained solids
Canned in oil, drained solids
Canned in water, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
SHELLFISH
Abalone
Clam
Crab, Alaska King
Crab, Blue
74.56
60.10
81.82
63.64
97.70
61.55
63.64
79.57
77.55
74.66
79.02
79.16
77.43
71.00
0.76
6.78
0.97
1.95
0.02
11.15
1.95
0.60
1.54
0.46
1.08
1.23
1.77
7.52
Raw
Cooked, fried
Raw
Canned, drained solids
Canned, liquid
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, moist heat
Imitation, made from surimi
Raw
Canned
Cooked, moist heat
Crab cakes
Page
10-206
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Crab, Dungeness
Crab, Queen
Crayfish, Farmed
Crayfish, Wild
Cuttlefish
Lobster, Northern
Lobster, Spiny
Mussel, Blue
Octopus
Oyster, Eastern
Oyster, Pacific
Scallop, mixed species
Shrimp
Squid
Moisture Content
(%)
79.18
73.31
80.58
75.10
84.05
80.80
82.24
79.37
80.56
61.12
76.76
76.03
74.07
66.76
80.58
61.15
80.25
60.50
86.20
85.16
85.14
64.72
81.95
83.30
70.32
82.06
64.12
78.57
58.44
73.10
75.86
75.85
52.86
77.28
78.55
64.54
Total Fat Content
(%)
0.97
1.24
1.18
1.51
0.97
1.30
0.95
1.20
0.70
1.40
0.90
0.59
1.51
1.94
2.24
4.48
1.04
2.08
1.55
2.46
2.47
12.58
2.12
1.90
4.91
2.30
4.60
0.76
10.94
1.40
1.73
1.36
12.28
1.08
1.38
7.48
Comments
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw, farmed
Raw, wild
Canned
Cooked, breaded and fried
Cooked, farmed, dry heat
Cooked, wild, dry heat
Cooked, wild, moist heat
Raw
Cooked, moist heat
Raw
Cooked, breaded and fried
Steamed
Raw
Canned
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, fried
Source: USDA, 2007.
Exposure Factors Handbook
September 2011
Page
10-207
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Great Lakes
Inland Midwest
Inland Northeast
Inland West
Inland South
Pacific
Gulf of Mexico
Atlantic
I Tuna, canned and freslVfro/en
I Shrimp
I Salmon
I Other shellfish
|Otherfinfish[Hcj]" 0.2ug/g
|Otherfinfish[Hg]>0,2ug/g
01 23456
Mean reported frequency of consumption in 30-days
Figure 10-2. Species and Frequency of Meals Consumed by Geographic Residence.
Source: Mahaffey et al, 2009.
Page
10-208
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
APPENDIX 10A:
RESOURCE UTILIZATION DISTRIBUTION
Exposure Factors Handbook Page
September 2011 10A-1
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
10A.1. RESOURCE UTILIZATION
DISTRIBUTION
The percentiles of the resource utilization
distribution of Y are to be distinguished from the
percentiles of the (standard) distribution of Y. The
latter percentiles show what percentage of
individuals in the population are consuming below a
given level. Thus, the 50th percentile of the
distribution of Y is that level such that 50% of
individuals consume below it; on the other hand, the
50th percentile of the resource utilization distribution
is that level such that 50% of the overall
consumption in the population is done by individuals
consuming below it.
The percentiles of the resource utilization
distribution of Y will always be greater than or equal
to the corresponding percentiles of the (standard)
distribution of 7, and, in the case of recreational fish
consumption, usually considerably exceed the
standard percentiles.
To generate the resource utilization
distribution, one simply weights each observation in
the data set by the Y level for that observation and
performs a standard percentile analysis of weighted
data. If the data already have weights, then one
multiplies the original weights by the Y level for that
observation, and then performs the percentile
analysis.
Under certain assumptions, the resource
utilization percentiles of fish consumption may be
related (approximately) to the (standard) percentiles
of fish consumption derived from the analysis of
creel studies. In this instance, it is assumed that the
creel survey data analysis did not employ sampling
weights (i.e., weights were implicitly set to one); this
is the case for many of the published analyses of
creel survey data. In creel studies, the fish
consumption rate for the /* individual is usually
derived by multiplying the amount of fish
consumption per fishing trip (say C,) by the
frequency of fishing (say fy. If it is assumed that the
probability of sampling an angler is proportional to
fishing frequency, then sampling weights of inverse
fishing frequency (1//J) should be employed in the
analysis of the survey data. Above it was stated that
for data that are already weighted, the resource
utilization distribution is generated by multiplying
the original weights by the individual's fish
consumption level to create new weights. Thus, to
generate the resource utilization distribution from the
data with weights of (1//J), one multiplies (1//J) by the
fish consumption level offt Ct to get new weights of
C,.
Now if Ct (amount of consumption per fishing
trip) is constant over the population, then these new
weights are constant and can be taken to be one. But
weights of one is what (it is assumed) were used in
the original creel survey data analysis. Hence, the
resource utilization distribution is exactly the same
as the original (standard) distribution derived from
the creel survey using constant weights.
The accuracy of this approximation of the
resource utilization distribution of fish by the
(standard) distribution of fish consumption derived
from an unweighted analysis of creel survey data
depends then on two factors, how approximately
constant the C,'s are in the population and how
approximately proportional the relationship between
sampling probability and fishing frequency is.
Sampling probability will be roughly proportional to
frequency if repeated sampling at the same site is
limited or if re-interviewing is performed
independent of past interviewing status.
Note: For any quantity Y that is
consumed by individuals in a population, the
percentiles of the "resource utilization distribution"
of Y can be formally defined as follows: Yp (R) is the
pth percentile of the resource utilization distribution
if p percent of the overall consumption of Y in the
population is done by individuals with consumption
below Yp (R) and WO-p percent is done by
individuals with consumption above YP(K).
Page
10A-2
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
APPENDIX 10B:
FISH PREPARATION AND COOKING METHODS
Exposure Factors Handbook Page
September 2011 10B-1
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Size"
Large
Residence Size City/Suburb Small City Town
Small Town Rural
Non-Farm
Farm
Total Fish
Cooking Method
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (AO
32.7
19.6
6.0
23.6
12.4
2.5
31.0
24.0
3.0
20.8
12.4
6.0
3.2 2.8
0.0000 0.0000
393
317
36.0
23.3
3.4
13.8
10.0
8.3
5.2
0.0000
388
32.4
24.7
3.7
21.4
10.3
5.0
1.9
0.5
256
38.6
26.2
3.4
13.7
12.7
2.3
2.9
0.2
483
51.6
15.7
3.5
13.1
6.4
7.0
1.8
94
Sport Fish
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (smoked, etc.)
Don't Know
Total (AO
a Large City = over
100-2,000.
45.8
12.2
2.8
20.2
11.8
2.7
4.5
0
205
100,000; Small
45.7
14.5
2.3
17.6
8.8
8.5
2.7
0
171
City =
47.6
17.5
2.9
10.6
6.3
10.4
4.9
0
257
20,000-100,000;
41.4
15.2
0.5
25.3
8.7
6.7
1.5
0.7
176
Town = 2,000-20,000
51.2
21.9
3.6
8.2
9.7
1.9
3.5
0
314
; Small Town =
63.3
7.3
0
10.4
6.9
9.3
2.8
0
62
N = Total number of respondents.
Source: Westetal., 1993.
Page Exposure Factors Handbook
10B-2 September 2011
-------
Exposure Factors Handbook
Chapter 10 — Intake of Fish and Shellfish
Table 10B-2. Percent of Fish
Age (years)
Cooking Method
Pan Fried
Deep Fried
Boiled
Grilled or Boiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (AO
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (A7)
17-30
45.9
23.0
0.0000
15.6
10.8
3.1
1.6
0.0000
246
57.6
18.2
0.0000
15.0
3.6
3.8
1.7
0.0000
174
Meals Prepared Using Various Cooking Methods by Age
31-40
Total
31.7
24.7
6.0
15.2
13.0
5.2
4.2
0.0000
448
Sport
42.6
21.0
4.4
10.1
10.4
7.2
4.3
0.0000
287
41-50
Fish
30.5
26.9
3.6
24.3
8.7
2.2
3.5
0.3
417
Fish
43.4
17.3
0.8
25.9
6.4
3.0
3.2
0.0000
246
51-64
33.9
23.7
3.9
16.1
12.8
6.5
2.7
0.4
502
46.6
14.8
3.2
12.2
11.7
7.5
3.5
0.4
294
>64
40.7
14.0
4.3
18.8
11.5
6.8
4.0
0.0000
287
54.1
7.7
3.1
12.2
9.9
8.2
4.8
0.0000
163
Overall
35.3
23.5
3.9
17.8
11.4
4.7
3.2
0.2
1,946
47.9
16.5
2.4
14.8
8.9
5.9
3.5
0.1
1,187
TV = Total number of respondents.
Source: Westet al., 1993.
Exposure Factors Handbook
September 2011
Page
10B-3
-------
Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10B-3. Percent of Fish Meals Prepared Using Various Cooking Methods by Ethnicity
Ethnicity
Black
Native
American
Hispanic
White
Other
Total Fish
Cooking Method
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (AO
40.5
27.0
0
19.4
1.9
9.5
1.6
0
52
37.5
22.0
1.1
9.8
16.3
6.2
4.2
0
84
16.1
83.9
0
0
0
0
3.5
0.3
12
35.8
22.7
4.3
17.7
11.7
4.5
2.7
0.4
1,744
18.5
18.4
0
57.6
5.4
0
4.0
0
33
Sport Fish
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Total (AO
44.9
36.2
0
0
5.3
13.6
0
19
47.9
20.2
0
1.5
18.2
8.6
3.6
60
52.1
47.9
0
0
0
0
0
4
48.8
15.7
2.7
14.7
8.6
5.6
3.7
39
22.0
9.6
0
61.9
6.4
0
0
0
A" = Total number of respondents.
Source: Westetal., 1993.
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Chapter 10—Intake of Fish and Shellfish
Table 10B-4.
Ethnicity
Percent of Fish Meals Prepared Using Various
Through Some H.S.
H.S. Degree
Cooking Methods
College Degree
by Education
Post-Graduate
Education
Total Fish
Cooking Method
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (N)
44.7
23.6
2.2
8.9
8.1
10.0
2.1
0.5
236
41.8
23.6
2.8
10.9
12.1
5.1
3.4
0.3
775
28.8
23.8
5.1
23.8
11.6
3.0
4.0
0
704
22.9
19.4
5.8
34.1
12.8
3.8
1.3
0
211
Sport Fish
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Total (A7)
56.1
13.6
2.8
6.3
7.4
10.1
2.8
0.8
146
52.4
15.8
2.4
9.4
10.6
6.3
3.3
0
524
41.8
18.6
3.0
21.7
6.1
3.9
4.6
0
421
36.3
12.9
0
28.3
14.9
6.5
1.0
0
91
N = Total number of respondents.
Source: Westetal., 1993.
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Exposure Factors Handbook
Chapter 10—Intake of Fish and Shellfish
Table 10B-5. Percent
Ethnicity
of Fish Meals
0-$24,999
Prepared Using Various Cooking Methods by
$25,000-$39,999 $40,
Income
000-or more
Total Fish
Cooking Method
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Don't Know
Total (N)
44.8
21.7
2.1
11.3
9.1
8.7
2.4
0
544
39.1
22.2
3.5
15.8
12.3
2.9
4.0
0.2
518
26.5
23.4
5.6
25.0
13.3
2.5
3.5
0.3
714
Sport Fish
Pan Fried
Deep Fried
Boiled
Grilled/Broiled
Baked
Combination
Other (Smoked, etc.)
Total (N)
51.5
15.8
1.8
12.0
7.2
9.1
2.7
0
387
51.4
15.8
2.1
12.2
10.0
3.8
4.6
0
344
42.0
17.2
3.7
19.4
10.0
3.5
3.8
0.3
369
N = Total number of respondents.
Source: Westetal., 1993.
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Chapter 10—Intake of Fish and Shellfish
Table 10B-6. Percent of Fish
Meals Where
Total
Population Trimmed Fat (%)
Fat was Trimmed
Variables
Fish
Skin Off (%)
or Skin was Removed, by Demographic
Trimmed Fat
Sport Fish
(%) Skin Off (%)
Total Fish
Residence Size
Large City/Suburb
Small City
Town
Small Town
Rural Non-Farm
Farm
Age (years)
17-30
31-40
41-50
51-65
Over 65
Ethnicity
Black
Native American
Hispanic
White
Other
Education
Some High School
High School Degree
College Degree
Post-Graduate
Income
<$25,000
$25,000-$39,999
$40,000 or more
Overall
Source: Modified from West et al
51.7
56.9
50.3
52.6
42.4
37.3
50.6
49.7
53.0
48.1
41.6
25.8
50.0
59.5
49.3
77.1
50.8
47.2
51.9
47.6
50.5
47.8
50.2
49.0
, 1993.
31.6
34.1
33.4
45.2
32.4
38.1
36.5
29.7
32.2
35.6
43.1
37.1
41.4
7.1
34.0
61.6
43.9
37.1
31.9
26.6
43.8
34.0
28.6
34.7
56.7
59.3
51.7
55.8
46.2
39.4
53.9
51.6
58.8
48.8
43.0
16.0
56.3
50.0
51.8
75.7
49.7
49.5
55.9
53.4
50.6
54.9
51.7
52.1
28.9
36.2
33.7
51.3
34.6
42.1
39.3
29.9
37.0
37.2
42.9
40.1
36.7
23.0
35.6
65.5
47.1
37.6
33.8
38.7
47.3
34.6
27.7
36.5
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Chapter 10—Intake of Fish and Shellfish
Table
Species
White Croaker
Pacific Mackerel
Pacific Bonito
Queenfish
Jacksmelt
Walleye Perch
Shiner Perch
Opaleye
Black Perch
Kelp Bass
California Halibut
Shellfish3
10B-7. Method of Cooking of Most
Percent of
Anglers Catching
Species
34
25
18
17
13
10
7
6
5
5
4
3
Common
Species Kept by Sportfishermen
Use as Primary Cooking Method (%)
Deep Fried
19
10
5
15
17
12
11
16
18
12
13
0
Pan Fry
64
41
33
70
57
69
72
56
53
55
60
0
Bake and Charcoal
Broil
12
28
43
6
19
6
8
14
14
21
24
0
Raw
0
0
2
1
0
0
0
0
0
0
0
0
Otherb
5
21
17
8
7
13
11
14
15
12
3
100
3 Crab, mussels, lobster, abalone.
b Boil, soup, steam, stew.
N = 1,059.
Source: Modified from Puffer et al., 1981.
Species
Salmon
Lamprey
Trout
Smelt
Whitefish
Sturgeon
Walleye
Squawfish
Sucker
Shad
Number
Consuming
473
249
365
209
125
121
46
15
42
16
Table 10B-8.
Adult Consumption of Fish Parts
Weighted Percent Consuming Specific Parts
Fillet
95.1
86.4
89.4
78.8
93.8
94.6
100
89.7
89.3
93.5
Skin
55.8
89.3
68.5
88.9
53.8
18.2
20.7
34.1
50.0
15.7
Head
42.7
18.1
13.7
37.4
15.4
6.2
6.2
8.1
19.4
0.0
Eggs
42.8
4.6
8.7
46.4
20.6
11.9
9.8
11.1
30.4
0.0
Bones
12.1
5.2
7.1
28.4
6.0
2.6
2.4
5.9
9.8
3.3
Organs
3.7
3.2
2.3
27.9
0.0
0.3
0.9
0.0
2.1
0.0
Source: CRITFC, 1994.
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Chapter 11—Intake of Meats, Dairy Products, and Fats
TABLE OF CONTENTS
LIST OF TABLES 11-ii
11. INTAKE OF MEATS, DAIRY PRODUCTS, AND FATS 11-1
11.1. INTRODUCTION 11-1
11.2. RECOMMENDATIONS 11-1
11.3. INTAKE OF MEAT AND DAIRY PRODUCTS 11-6
11.3.1. Key Meat and Dairy Intake Studies 11-6
11.3.1.1.U.S. EPAAnalysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 11-6
11.3.2. Relevant Meat and Dairy Intake Studies 11-7
11.3.2.1.USDA (1980, 1992, 1996a,b) 11-7
11.3.2.2.USDA(1999a) 11-8
11.3.2.3. U.S. EPA Analysis of CSFII1994-1996, 1998 Based on USD A (2000)
and U.S. EPA (2000) 11-8
11.3.2.4. Smiciklas-Wright et al. (2002) 11-9
11.3.2.5. Vitolinsetal. (2002) 11-10
11.3.2.6.Fox etal. (2004) 11-10
11.3.2.7.Ponzaetal. (2004) 11-11
11.3.2.8.Mennellaetal. (2006) 11-11
11.3.2.9. Fox etal. (2006) 11-11
11.4. INTAKE OF FAT 11-12
11.4.1. Key Fat Intake Study 11-12
11.4.1.1.U.S. EPA (2007) 11-12
11.4.2. Relevant Fat Intake Studies 11-13
11.4.2.1.Cresantaetal. (1988)/Nicklasetal. (1993 )/and Frank etal. (1986) 11-13
11.5. CONVERSION BETWEEN WET-AND DRY-WEIGHT INTAKE RATES 11-13
11.6. CONVERSION BETWEEN WET-WEIGHT AND LIPID-WEIGHT INTAKE RATES 11-13
11.7. REFERENCES FOR CHAPTER 11 11-14
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Chapter 11—Intake of Meats, Dairy Products, and Fats
LIST OF TABLES
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion,
Uncooked 11-3
Table 11-2. Confidence in Recommendations for Intake of Meats, Dairy Products, and Fats 11-5
Table 11-3. Per Capita Intake of Total Meat and Total Dairy Products Based on 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 11-16
Table 11-4. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 2003-2006
NHANES (g/kg-day, edible portion, uncooked weight) 11-17
Table 11-5. Per Capita Intake of Individual Meats and Dairy Products Based on 2003-2006
NHANES (g/kg-day, edible portion, uncooked weight) 11-18
Table 11-6. Consumer-Only Intake of Individual Meats and Dairy Products Based on 2003-2006
NHANES (g/kg-day, edible portion, uncooked weight) 11-19
Table 11-7. Mean Meat Intakes per Individual in a Day, by Sex and Age (g/day, as-consumed) for
1977-1978 11-20
Table 11-8. Mean Meat Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed) for
1987-1988 11-21
Table 11-9. Mean Meat Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed) for 1994
and 1995 11-22
Table 11-10. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)
for 1977-1978 11-23
Table 11-11. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)
for 1987-1988 11-24
Table 11-12. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)
for 1994 and 1995 11-24
Table 11-13. Mean Quantities of Meat and Eggs Consumed Daily by Sex and Age, Per Capita (g/day,
as-consumed) 11-25
Table 11-14. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%) 11-26
Table 11-15. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day,
as-consumed) 11-27
Table 11-16. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) 11-28
Table 11-17 Per Capita Intake of Total Meat and Total Dairy Products (g/kg-day, edible portion,
uncooked weight) 11-29
Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 1994-1996,
1998 CSFII (g/kg-day, edible portion, uncooked weight) 11-31
Table 11-19. Per Capita Intake of Individual Meats and Dairy Products Based on 1994-1996, 1998
CSFII (g/kg-day, edible portion, uncooked weight) 11-33
Table 11-20. Consumer-Only Intake of Individual Meats and Dairy Products Based on 1994-1996,
1998 CSFII (g/kg-day, edible portion, uncooked weight) 11-34
Table 11-21. Quantity (as-consumed) of Meat and Dairy Products Consumed per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days 11-35
Table 11-22. Consumption of Milk, Yogurt, and Cheese: Median Daily Servings (and ranges) by
Demographic and Health Characteristics 11-37
Table 11-23. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 11-38
Table 11-24. Percentage of Infants and Toddlers Consuming Milk, Meat, or Other Protein Sources 11-39
Table 11-25. Characteristics of WIC Participants and Non-Participants (percentages) 11-40
Table 11-26. Food Choices for Infants and Toddlers by WIC Participation Status 11-41
Table 11-27. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Milk, Meats, or Other Protein Sources ona GivenDay 11-41
Table 11-28. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 11-42
Table 11-29. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 11-42
Table 11-30. Per Capita Total Fat Intake (g/day) 11-43
Table 11-31. Per Capita Total Fat Intake (g/kg-day) 11-45
Page
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Chapter 11—Intake of Meats, Dairy Products, and Fats
LIST OF TABLES (continued)
Table 11-32. Consumers-Only Total Fat Intake (g/day) 11-47
Table 11-33. Consumers-Only Total Fat Intake (g/kg-day) 11-49
Table 11-34. Consumers-Only Total Fat Intake—Top 10% of Animal Fat Consumers (g/day) 11-51
Table 11-35. Consumers-Only Total Fat Intake—Top 10% of Animal Fat Consumers (g/kg-day) 11-53
Table 11-36. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982
(g/day) 11-55
Table 11-37. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982
(g/kg-day) 11-56
Table 11-38. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products 11-57
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Chapter 11—Intake of Meats, Dairy Products, and Fats
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Chapter 11—Intake of Meats, Dairy Products, and Fats
11. INTAKE OF MEATS, DAIRY
PRODUCTS, AND FATS
11.1. INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, meats, dairy products, and fats may
become contaminated with toxic chemicals by
several pathways. These foods sources can become
contaminated if animals are exposed to contaminated
media (i.e., soil, water, or feed crops). To assess
exposure through this pathway, information on meat,
dairy, and fat ingestion rates are needed.
A variety of terms may be used to define intake of
meats, dairy products, and fats (e.g., consumer-only
intake, per capita intake, total meat, dairy product, or
fat intake, as-consumed intake, uncooked edible
portion intake, dry-weight intake). As described in
Chapter 9, Intake of Fruits and Vegetables,
consumer-only intake is defined as the quantity of
meats, dairy products, or fats consumed by
individuals during the survey period averaged across
only the individuals who consumed these food items
during the survey period. Per capita intake rates are
generated by averaging consumer-only intakes over
the entire population In general, per capita intake
rates are appropriate for use in exposure assessment
for which average dose estimates are of interest
because they represent both individuals who ate the
foods during the survey period and individuals who
may eat the food items at some time, but did not
consume them during the survey period. Per capita
intake, therefore, represents an average across the
entire population of interest, but does so at the
expense of underestimating consumption for the
subset of the population that consumes the food in
question. Total intake refers to the sum of all meats,
dairy products, or fats consumed in a day.
Intake rates may be expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the
as-consumed weight. Some of the food ingestion
values provided in this chapter are expressed as
as-consumed intake rates because this is the fashion
in which data were reported by survey respondents.
Others are provided as uncooked weights based on
analyses of survey data that account for weight
changes that occur during cooking. This is of
importance because concentration data to be used in
the dose equation are often measured in uncooked
food samples. It should be recognized that cooking
can either increase or decrease food weight.
Similarly, cooking can increase the mass of
contaminant in food (due to formation reactions, or
absorption from cooking oils or water) or decrease
the mass of contaminant in food (due to vaporization,
fat loss, or leaching). The combined effects of
changes in weight and changes in contaminant mass
can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. It is important
for the assessor to be aware of these issues and
choose intake rate data that best match the
concentration data that are being used. For more
information on cooking losses and conversions
necessary to account for such losses, refer to
Chapter 13 of this handbook.
Sometimes contaminant concentrations in food
are reported on a dry-weight basis. When these data
are used in an exposure assessment, it is
recommended that dry-weight intake rates also be
used. Dry-weight food concentrations and intake
rates are based on the weight of the food consumed
after the moisture content has been removed.
Similarly, when contaminant concentrations in food
are reported on a lipid-weight basis, lipid-weight
intake rates should be used. For information on
converting the intake rates presented in this chapter
to dry-weight or lipid-weight intake rates, refer to
Sections 11.5 and 11.6 of this chapter.
The purpose of this chapter is to provide intake
data for meats, dairy products, and fats. The
recommendations for ingestion rates of meats, dairy
products, and fats are provided in the next section,
along with a summary of the confidence ratings for
these recommendations. The recommended values
are based on the key study identified by
U.S. Environmental Protection Agency (EPA) for this
factor. Following the recommendations, the key study
on ingestion of meats, dairy products, and fats are
summarized. Relevant data on ingestion of meats,
dairy products, and fats are also provided. These
studies are presented to provide the reader with added
perspective on the current state-of-knowledge
pertaining to ingestion of meats, dairy products, and
fats.
11.2. RECOMMENDATIONS
Table 11-1 presents a summary of the
recommended values for per capita and
consumer-only intake of meats, dairy products, and
fats. Table 11-2 provides confidence ratings for these
recommendations.
Exposure Factors Handbook
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Chapter 11—Intake of Meats, Dairy Products, and Fats
U.S. EPA analyses of data from the 2003-2006
National Health and Nutrition Examination Survey
(NHANES) were used in selecting recommended
intake rates for intake of meats and dairy products by
the general population. The U.S. EPA analysis of
meat and dairy products was conducted using
childhood age groups that differed slightly from
U.S. EPA's Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, for the purposes of the recommendations
for children presented here, data were placed in the
standardized age categories closest to those used in
the analysis. The U.S. EPA analysis of fat intake data
from the U.S. Department of Agriculture's (USDAs)
Continuing Survey of Food Intake by Individuals
(CSFII, U.S. EPA, 2007) were used in selecting
recommended intake rates for fats. This study used
the childhood age groups recommended by U.S. EPA
(2005).
The NHANES data on which the
recommendations for meats and dairy products are
based, and the CSFII data on which the
recommendations for fats are based are short-term
survey data and may not necessarily reflect the
long-term distribution of average daily intake rates.
However, since these broad categories of food (i.e.,
total meats and dairy products), are eaten on a daily
basis throughout the year with minimal seasonality,
the short term distribution may be a reasonable
approximation of the long-term distribution, although
it will display somewhat increased variability. This
implies that the upper percentiles shown here will
tend to overestimate the corresponding percentiles of
the true long-term distribution. In general, the
recommended values based on U.S. EPA's analyses of
NHANES data and CSFII data represent the
uncooked weight of the edible portion of meat, dairy,
and fats. It should be noted that because the
recommendations for fat intake are based on
1994-1996 and 1998 CSFII data, they may not
reflect the most recent changes that may have
occurred in consumption patterns.
Page
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Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion,
Uncooked
Age Group
(years)
Per Capita
Mean
g/kg-day
Consumers Only
95th Percentile Mean
g/kg-day
g/kg-day
95* Percentile "f f
Percentiles
g/kg-day
Source
Total Meat"
Birth to 1
1 to<2
2to<3
3to<6
6to50
1.2
4.0
4.0
3.9
2.8
2.0
2.0
1.8
1.4
5.4b
10.0b
10.0b
8.5
6.4
4.7
4.7
4.1
3.1
2.7
4.1
4.1
3.9
2.8
2.0
2.0
1.8
1.4
8.1b
10.1b
10.1b
8.6
, . See Tables
n 4
11-3 and 11-4
4.7
4.7
4.1
3.1
U.S. EPA
Analysis of
NHANES
2003-2006.
Total Dairy Products3
Birth to 1
1 to<2
2to<3
3to<6
6to50
10.1
43.2
43.2
24.0
12.9
5.5
5.5
3.5
3.3
43. 2b
94.7b
94.7b
51.1
31.8
16.4
16.4
10.3
9.6
11.7
43.2
43.2
24.0
12.9
5.5
5.5
3.5
3.3
44.7b
94.7b
94.7b
51.1
, , „ See Tables
11-3 and 11-4
16.4
16.4
10.3
9.6
U.S. EPA
Analysis of
NHANES
2003-2006.
Individual Meat and Dairy Products — See Tables 11-5 and 11-6
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Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion,
Uncooked (continued)
Per Capita Consumers Only
Age Group Mean 95th Percentile Mean 95th Percentile MultlPle
0 r Percentiles
g/kg-day g/kg-day g/kg-day g/kg-day
Source
Total Fat
Birth to <1 month 5.2 16 7.8 16
1 to <3 months 4.5 12 6.0 12
3 to <6 months 4.1 8.2 4.4 8.3
6 to <12 months 3.7 7.0 3.7 7.0
1 to <2 years 4.0 7.1 4.0 7.1
2 to <3 years 3.6 6.4 3.6 6.4
3 to <6 years 3.4 5.8 3.4 5.8
6to81 years 0.9 1.5 0.9 1.5
U.S. EPA
(2007)
a Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on
Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants
(U.S. EPA., 2005). Data were placed in the standardized age categories closest to those used in the analysis.
b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation
and Statistical Reporting Standards on NHANES IN and CSFII Reports: NHIS/NCHS Analytical Working Group
Recommendations (NCHS, 1993).
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Table 11-2. Confidence in Recommendations for Intake of Meats, Dairy Products, and Fats
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodology and data analysis were adequate.
The surveys sampled approximately 16,000 for meats and
dairy products and 20,000 individuals for fats. Analyses of
primary data were conducted.
No physical measurements were taken. The method relied
on recent recall of meats and dairy products eaten.
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key studies were directly relevant to meat, dairy, and
fat intake.
The data were demographically representative of the U.S.
population (based on stratified random sample).
Data were collected between 2003 and 2006 for meat and
dairy products and between 1994 and 1998 for fats.
Data were collected for two non-consecutive days.
High for meats and dairy products;
medium for fats
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The NHANES and CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
NHANES and CSFII follow strict QA/QC procedures.
U.S. EPA analysis of NHANES data has only been
reviewed internally.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were provided for total meats, total dairy
products, and total fats. Means were provided for
individual meats and dairy products.
Data collection was based on recall of consumption for a
2-day period; the accuracy of using these data to estimate
long-term intake (especially at the upper percentiles) is
uncertain. However, use of short-term data to estimate
chronic ingestion can be assumed for broad categories of
foods such as total meats, total dairy products, and total
fats. Uncertainty is likely to be greater for individual
meats and dairy products.
Medium to high for averages, low
for long-term upper percentiles;
low for individual foods
Evaluation and Review
Peer Review
Medium
Number and Agreement of
Studies
Both the NCHS NHANES and the USDA CSFII survey
received high levels of peer review. The U.S. EPA
analysis of the NHANES data has not been peer reviewed
outside the Agency, but methodology has been used in
analysis of previous data.
There was one key study for intake of meat and dairy
products (2003-2006 NHANES) and 1 key study for fat
intake (U.S. EPA, 2007, based on 1994-1996, 1998
CSFII).
Overall Rating
Medium to high confidence in the
averages; Low confidence in the
long-term upper percentiles
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11.3. INTAKE OF MEAT AND DAIRY
PRODUCTS
11.3.1. Key Meat and Dairy Intake Studies
11.3.1.1. U.S. EPA Analysis of Consumption Data
from 2003-2006 National Health and
Nutrition Examination Survey
(NHANES)
The key source of recent information on
consumption rates of meat and dairy products is the
U.S. Centers for Disease Control and Prevention's
(CDC) National Center for Health Statistics' (NCHS)
NHANES. Data from NHANES have been used by
the U.S. EPA, Office of Pesticide Programs (OPP) to
generate per capita and consumer-only intake rates
for both individual meat and dairy products and total
meat and dairy products.
NHANES is designed to assess the health and
nutritional status of adults and children in the United
States. In 1999, the survey became a continuous
program that interviews a nationally representative
sample of approximately 7,000 persons each year and
examines a nationally representative sample of about
5,000 persons each year, located in counties across
the country, 15 of which are visited each year. Data
are released on a 2 year basis, thus, for example, the
2003 data are combined with the 2004 data to
produce NHANES 2003-2004.
The dietary interview component of NHANES is
called What We Eat in America and is conducted by
the U.S. Department of Agriculture (USDA) and the
U.S. Department of Health and Human Services
(DHHS). DHHS' NCHS is responsible for the sample
design and data collection and USD As Food Surveys
Research Group is responsible for the dietary data
collection methodology, maintenance of the databases
used to code and process the data, and data review
and processing. Beginning in 2003,
2 non-consecutive days of 24-hour intake data were
collected. The first day is collected in-person, and the
second day is collected by telephone 3 to 10 days
later. These data are collected using USDA's dietary
data collection instrument, the Automated Multiple
Pass Method. This method provides an efficient and
accurate means of collecting intakes for large-scale
national surveys. It is fully computerized and uses a
5-step interview. Details can be found at USDA's
Agriculture Research Service
(http://www.ars.usda.gov/ba/bhnrc/fsrg).
For NHANES 2003-2004, there were
12,761 persons selected; of these, 9,643 were
considered respondents to the mobile examination
center (MEC) examination and data collection.
However, only 9,034 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,354 provided complete dietary intakes for Day 2.
For NHANES 2005-2006, there were 12,862 persons
selected; of these 9,950 were considered respondents
to the MEC examination and data collection.
However, only 9,349 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,429 provided complete dietary intakes for Day 2.
The 2003-2006 NHANES surveys are stratified,
multistage probability samples of the civilian non-
institutionalized U.S. population. The sampling frame
was organized using 2000 U.S. population census
estimates. NHANES oversamples low income
persons, adolescents 12 to 19 years, persons 60 years
and older, African Americans, and Mexican
Americans. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all 4 years of the
surveys can be combined. Additional information on
NHANES can be obtained at
http://www.cdc.gov/nchs/nhanes.htm.
In 2010, OPP used NHANES 2003-2006 data to
update the Food Commodity Intake Database (FCID)
that was developed in earlier analyses of data from
the U.S. Department of Agriculture's (USDA's)
CSFII (USDA, 2000; U.S. EPA, 2000) (see
Section 11.3.2.3), NHANES data on the foods people
reported eating were converted to the quantities of
agricultural commodities eaten. "Agricultural
commodity" is a term used by U.S. EPA to mean
plant (or animal) parts consumed by humans as food;
when such items are raw or unprocessed, they are
referred to as "raw agricultural commodities." For
example, beef stew may contain the commodities
beef, potatoes, carrots, and other vegetables. FCID
contains approximately 558 unique commodity
names and 8-digit codes. The FCID commodity
names and codes were selected and defined by
U.S. EPA and were based on the U.S. EPA Food
Commodity Vocabulary
(http ://www. epa. gov/pesticides/foodfeed/).
Intake rates were generated for a variety of food
items/groups based on the agricultural commodities
included in the FCID. These intake rates represent
intake of all forms of the product (e.g., both home
produced and commercially produced) for individuals
who provided data for 2 days of the survey. Note that
if the person reported consuming food for only one
day, their 2-day average would be half the amount
reported for the one day of consumption. Individuals
who did not provide information on body weight or
for whom identifying information was unavailable
were excluded from the analysis. Two-day average
intake rates were calculated for all individuals in the
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database for each of the food items/groups. These
average daily intake rates were divided by each
individual's reported body weight to generate intake
rates in units of grams per kilogram of body weight
per day (g/kg-day). The data were weighted
according to the 4-year, 2-day sample weights
provided in NHANES 2003-2006 to adjust the data
for the sample population to reflect the national
population. Summary statistics were generated on a
consumer-only and on a per capita basis. Summary
statistics, including number of observations,
percentage of the population consuming the meats
and dairy products being analyzed, mean intake rate,
and standard error of the mean intake rate were
calculated for total meats, total dairy products, and
selected individual meats and dairy products.
Percentiles of the intake rate distribution (i.e., 1st, 5th,
10th, 25th, 50th, 75th, 90th, 95th, 99th, and the maximum
value) were also provided for total meats and dairy
products. Data were provided for the following age
groups: birth to 1 year, 1 to 2 years, 3 to 5 years, 6 to
12 years, 13 to 19 years, 20 to 49 years, and
>50 years. Data on females 13 to 49 years were also
provided. Because these data were developed for use
in U.S. EPA's pesticide registration program, the
childhood age groups used are slightly different than
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005).
Table 11-3 presents per capita intake data for total
meats and dairy products in g/kg-day; Table 11-4
provides consumer-only intake data for total meats
and total dairy products in g/kg-day. Table 11-5
provides per capita intake data for individual meats
and dairy products, and Table 11-6 provides
consumer-only intake data for individual meats and
dairy products. In general, these data represent intake
of the edible portions of uncooked foods.
The results are presented in units of g/kg-day.
Thus, the use of these data in calculating potential
dose does not require the body-weight factor to be
included in the denominator of the average daily dose
(ADD) equation. It should be noted that converting
these intake rates into units of g/day by multiplying
by a single average body weight is inappropriate
because individual intake rates were indexed to the
reported body weights of the survey respondents.
Also, it should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the
long-term distribution of average daily intake rates.
The distributions generated from short-term and
long-term data will differ to the extent that each
individual's intake varies from day to day; the
distributions will be similar to the extent that
individuals' intakes are constant from day to day.
However, for broad categories of foods (e.g., total
meats and total dairy) that are eaten on a daily basis
throughout the year, the short-term distribution may
be a reasonable approximation of the true long-term
distribution, although it will show somewhat more
variability. In this chapter, distributions are provided
only for broad categories of meats and dairy (i.e.,
total meats and total dairy). Because of the increased
variability of the short-term distribution, the
short-term upper percentiles shown here may
overestimate the corresponding percentiles of the
long-term distribution. For individual foods, only the
mean, standard error, and percent consuming are
provided.
An advantage of using the U.S. EPA's analysis of
NHANES data is that it provides distributions of
intake rates for various age groups of children and
adults, normalized by body weight. The data set was
designed to be representative of the U.S. population
and includes 4 years of intake data combined.
Another advantage is the currency of the data; the
NHANES data are from 2003-2006. However,
short-term dietary data may not accurately reflect
long-term eating patterns and may under-represent
infrequent consumers of a given food. This is
particularly true for the tails (extremes) of the
distribution of food intake. Because these are 2-day
averages, consumption estimates at the upper end of
the intake distribution may be underestimated if these
consumption values are used to assess acute (i.e.,
short-term) exposures. Also, the analysis was
conducted using slightly different childhood age
groups than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, given the similarities in the age groups
used, the data should provide suitable intake
estimates for the age groups of interest.
11.3.2. Relevant Meat and Dairy Intake Studies
11.3.2.1. USDA (1980,1992,1996a, b)—Food and
Nutrient Intakes of Individuals in 1 Day
in the U.S.
USDA calculated mean per capita intake rates for
meat and dairy products using Nationwide Food
Consumption Survey (NFCS) data from 1977-1978
and 1987-1988 (USDA, 1980, 1992) and CSFII data
from 1994 and 1995 (USDA, 1996a, b). The mean
per capita intake rates for meat are presented in
Tables 11-7 through 11-9 based on intake data for
1 day from the 1977-1978 (see Table 11-7) and
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1987-1988 NFCSs (see Table 11-8), and 1994 and
1995 CSFII (see Table 11-9). Tables 11-10 through
11-12 present similar data for dairy products. Note
that the age classifications used in the later surveys
were slightly different than those used in the
1977-1978 NFCS.
The advantages of using these data are that they
provide mean intake estimates for all meat, poultry,
and dairy products. The consumption estimates are
based on short-term (i.e., 1-day) dietary data, which
may not reflect long-term consumption. These data
are based on older surveys and may not be entirely
representative of current eating patterns.
11.3.2.2. USDA (1999a)—Food and Nutrient
Intakes by Children 1994-1996,1998,
Table Set 17
USDA (1999a) calculated national probability
estimates of food and nutrient intake by children
based on 4 years of the CSFII (1994-1996 and 1998)
for children age 9 years and under and on CSFII
1994-1996 only for individuals age 10 years and
over. The CSFII was a series of surveys designed to
measure the kinds and amounts of foods eaten by
Americans. Intake data, based on 24-hour dietary
recall, were collected through in-person interviews on
2 non-consecutive days. Section 11.3.2.3 provides
additional information on these surveys.
USDA (1999a) used sample weights to adjust for
non-response, to match the sample to the U.S.
population in terms of demographic characteristics,
and to equalize intakes over the 4 quarters of the year
and the 7 days of the week. A total of 503 breast-fed
children were excluded from the estimates, but both
consumers and non-consumers were included in the
analysis.
USDA (1999a) provided data on the mean per
capita quantities (grams) of various food
products/groups consumed per individual for 1 day,
and the percent of individuals consuming those foods
in 1 day of the survey. Tables 11-13 and 11-14
present data on the mean quantities (grams) of meat
and eggs consumed per individual for 1 day, and the
percentage of survey individuals consuming meats
and eggs on that survey day. Tables 11-15 and 11-16
present similar data for dairy products. Data on mean
intakes or mean percentages are based on
respondents'Day-1 intakes.
The advantage of the USDA (1999a) study is that
it uses the 1994-1996, 1998 CSFII data set, which
includes 4 years of intake data, combined, and
includes the supplemental data on children. These
data are expected to be generally representative of the
U.S. population, and they include data on a wide
variety of meats and dairy products. The data set is
one of a series of USDA data sets that are publicly
available. One limitation of this data set is that it is
based on 1 day, and short-term dietary data may not
accurately reflect long-term eating patterns. Other
limitations of this study are that it only provides
mean values of food intake rates, consumption is not
normalized by body weight, and presentation of
results is not consistent with U.S. EPA's
recommended age groups. These data are based on
older surveys and may not be entirely representative
of current eating patterns.
11.3.2.3. U.S. EPA Analysis of CSFII 1994-1996,
1998 Based on USDA (2000) and
U.S. EPA (2000)
U.S. EPA/OPP, in cooperation with USDA's
Agricultural Research Service, used data from the
1994-1996, 1998 CSFII to develop the FCID
(U.S. EPA, 2000; USDA, 2000), as described in
Section 11.3.1.1. The CSFII 1994-1996 was
conducted between January 1994 and January 1997
with a target population of non-institutionalized
individuals in all 50 states and Washington, DC. In
each of the 3 survey years, data were collected for a
nationally representative sample of individuals of all
ages. The CSFII 1998 was conducted between
December 1997 and December 1998 and surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-1996 and was
intended to be merged with CSFII 1994-1996 to
increase the sample size for children. The merged
surveys are designated as CSFII 1994-1996, 1998
(USDA, 2000). Additional information on the CSFII
can be obtained at
http://www.ars.usda.gov/Services/docs.htm?docid=14
531.
The CSFII 1994-1996, 1998 collected dietary
intake data through in-person interviews on
2 non-consecutive days. The data were based on
24-hour recall. A total of 21,662 individuals provided
data for the first day; of those individuals, 20,607
provided data for a second day. The 2-day response
rate for the 1994-1996 CSFII was approximately
76%. The 2-day response rate for CSFII 1998 was
82%. The CSFII 1994-1996, 1998 surveys were
based on a complex multistage area probability
sample design. The sampling frame was organized
using 1990 U.S. population census estimates, and the
stratification plan took into account geographic
location, degree of urbanization, and socioeconomic
characteristics. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all 4 years of the
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surveys can be combined. USDA recommends that
all 4 years be combined in order to provide an
adequate sample size for children.
The meats and dairy items/groups selected for the
U.S. EPA analysis included total meats and total dairy
products, and individual meats and dairy such as
beef, pork, poultry, and eggs. CSFII data on the foods
people reported eating were converted to the
quantities of agricultural commodities eaten. Intake
rates for these food items/groups were calculated, and
summary statistics were generated on both a per
capita and a consumer-only basis using the same
general methodology as in the U.S. EPA analysis of
2003-2006 NHANES data, as described in
Section 11.3.1.1. Because these data were developed
for use in U.S. EPA's pesticide registration program,
the childhood age groups used are slightly different
than those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005).
Table 11-17 presents per capita intake data for
total meat and total dairy products in g/kg-day; Table
11-18 provides consumer-only intake data for total
meat and total dairy products in g/kg-day.
Table 11-19 provides per capita intake data for
certain individual meats and dairy products, and
Table 11-20 provides consumer-only intake data for
these individual meats and dairy products. In general,
these data represent intake of the edible portions of
uncooked foods.
The results are presented in units of g/kg-day.
Thus, use of these data in calculating potential dose
does not require the body-weight factor to be
included in the denominator of the average daily dose
equation. The cautions concerning converting these
intake rates into units of g/day by multiplying by a
single average body weight and the discussion of the
use of short term data in the NHANES description in
Section 11.3.1.1 apply to the CSFII estimates as well.
A strength of U.S. EPA's analysis is that it
provides distributions of intake rates for various age
groups, normalized by body weight. The analysis
uses the 1994-1996, 1998 CSFII data set, which was
designed to be representative of the U.S. population.
The data set includes 4 years of intake data combined
and is based on a 2-day survey period. As discussed
above, short-term dietary data may not accurately
reflect long-term eating patterns and may
under-represent infrequent consumers of a given
food. This is particularly true for the tails (extremes)
of the distribution of food intake. Although the
analysis as conducted used slightly different age
groups than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005),
given the similarities in the age groups used, the data
should provide suitable intake estimates for the
childhood age groups of interest While the CSFII
data are older than the NHANES data, they provide
relevant information on consumption by season,
region of the United States, and urbanization, cohorts
that are not available in the publicly released
NHANES data.
11.3.2.4. Smiciklas- Wright et al (2002)—Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating
Occasion and in a Day, 1994-1996
Using data gathered in the 1994-1996 USDA
CSFII, Smiciklas-Wright etal. (2002) calculated
distributions for the quantities of meat, poultry, and
dairy products consumed per eating occasion by
members of the U.S. population (i.e., serving sizes).
The estimates of serving size are based on data
obtained from 14,262 respondents, ages two years
and above, who provided 2 days of dietary intake
information. Only dietary intake data from users of
the specified food were used in the analysis (i.e.,
consumer-only data).
Table 11-21 presents serving size data for meats
and dairy products. These data are presented on an
as-consumed basis (grams) and represent the quantity
of meats and dairy products consumed per eating
occasion. These estimates may be useful for assessing
acute exposures to contaminants in specific foods, or
other assessments where the amount consumed per
eating occasion is necessary. Only the mean and
standard deviation serving size data and percent of
the population consuming the food during the 2-day
survey period are presented in this handbook.
Percentiles of serving sizes of the foods consumed by
these age groups of the U.S. population can be found
in Smiciklas-Wright et al. (2002).
The advantages of using these data are that they
were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright etal. (2002)
accounted for individual foods consumed as
ingredients of mixed foods. Mixed foods were
disaggregated via recipe files so that the individual
ingredients could be grouped together with similar
foods that were reported separately. Thus, weights of
foods consumed as ingredients were combined with
weights of foods reported separately to provide a
more thorough representation of consumption.
However, it should be noted that since the recipes for
the mixed foods consumed were not provided by the
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respondents, standard recipes were used. As a result,
the estimates of quantity consumed for some food
types are based on assumptions about the types and
quantities of ingredients consumed as part of mixed
foods. This study used data from the 1994-1996
CSFII; data from the 1998 children's supplement
were not included.
11.3.2.5. Vitolins et al. (2002)—Quality of Diets
Consumed by Older Rural Adults
Vitolins etal. (2002) conducted a survey to
evaluate the dietary intake, by food groups, of older
(>70 years) rural adults. The sample consisted of
130 community dwelling residents from two rural
counties in North Carolina. Data on dietary intake
over the preceding year were obtained in face-to-face
interviews conducted in participants' homes, or in a
few cases, a senior center. The food frequency
questionnaire used in the survey was a modified
version of the National Cancer Institute Health Habits
and History Questionnaire; this modified version
included an expanded food list containing a greater
number of ethnic foods than the original food
frequency form. Demographic and personal data
collected included sex, ethnicity, age, education,
denture use, marital status, chronic disease, and
weight.
Food items reported in the survey were grouped
into food groups similar to the USDA Food Guide
Pyramid and the National Cancer Institute's 5 A Day
for Better Health program. These groups are: (1)
fruits and vegetables; (2) bread, cereal, rice, and
pasta; (3) milk, yogurt, and cheese; (4) meat, fish,
poultry, beans, and eggs; and (5) fats, oils, sweets,
and snacks. Medians, ranges, frequencies, and
percentages were used to summarize intake of each
food group, broken down by demographic and health
characteristics. In addition, multiple regression
models were used to determine which demographic
and health factors were jointly predictive of intake of
each of the five food groups.
Thirty-four percent of the survey participants
were African American, 36% were European
American, and 30% were Native American.
Sixty-two percent were female, 62% were not
married at the time of the interview, and 65% had
some high school education or were high school
graduates. Almost all of the participants (95%) had
one or more chronic diseases. Sixty percent of the
respondents were between 70 and 79 years of age; the
median age was 78 years old. Table 11-22 presents
the median servings of milk, yogurt, and cheese
broken down by demographic and health
characteristics. None of the demographic
characteristics were significantly associated with
milk intake, and only ethnicity was found to be
borderline (p = 0.13). In addition, none of the
demographic characteristics were jointly predictive of
milk, yogurt, and cheese consumption.
One limitation of the study, as noted by the study
authors, is that the study did not collect information
on the length of time the participants had been
practicing the dietary behaviors reported in the
survey. The questionnaire asked participants to report
the frequency of food consumption during the past
year. The study authors noted that, currently, there are
no dietary assessment tools that allow the collection
of comprehensive dietary data over years of food
consumption. Another limitation of the study is the
small sample size used, which makes associations by
sex and ethnicity difficult.
11.3.2.6. Fox et al. (2004)—Feeding Infants and
Toddlers Study: What Foods Are Infants
and Toddlers Eating
Fox etal. (2004) used data from the Feeding
Infants and Toddlers study (FITS) to assess food
consumption patterns in infants and toddlers. The
FITS was sponsored by Gerber Products Company
and was conducted to obtain current information on
food and nutrient intakes of children, ages 4 to
24 months old, in the 50 states and the District of
Columbia. The FITS is described in detail in
Devaney et al. (2004). FITS was based on a random
sample of 3,022 infants and toddlers for which
dietary intake data were collected by telephone from
their parents or caregivers between March and July
2002. An initial recruitment and household interview
was conducted, followed by an interview to obtain
information on intake based on 24-hour recall. The
interview also addressed growth, development, and
feeding patterns. A second dietary recall interview
was conducted for a subset of 703 randomly selected
respondents. The study over-sampled children in the
4 to 6 and 9 to 11-months age groups; sample weights
were adjusted for non-response, over-sampling, and
under-coverage of some subgroups. The response rate
for the FITS was 73% for the recruitment interview.
Of the recruited households, there was a response rate
of 94% for the dietary recall interviews (Devaney
etal., 2004). Table 11-23 shows the characteristics of
the FITS study population.
Fox et al. (2004) analyzed the first set of 24-hour
recall data collected from all study participants. For
this analysis, children were grouped into six age
categories: 4 to 6 months, 7 to 8 months, 9 to
11 months, 12 to 14 months, 15 to 18 months, and 19
to 24 months. Table 11-24 provides the percentage of
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infants and toddlers consuming milk, meats, or other
protein sources at least once in a day. The percentage
of children consuming any type of meat or protein
source ranged from 14.2% for 4 to 6-month olds to
97.2% for 19 to 24 month olds (see Table 11-24).
The advantages of this study are that the study
population represented the U.S. population and the
sample size was large. One limitation of the analysis
done by Fox etal. (2004) was that only frequency
data were provided; no information on actual intake
rates was included. In addition, Devaney et al. (2004)
noted several limitations associated with the FITS
data. For the FITS, a commercial list of infants and
toddlers was used to obtain the sample used in the
study. Since many of the households could not be
located and did not have children in the target
population, a lower response rate than would have
occurred in a true national sample was obtained
(Devaney etal., 2004). In addition, the sample was
likely from a higher socioeconomic status when
compared with all U.S. infants in this age group (4 to
24 months old), and the use of a telephone survey
may have omitted lower-income households without
telephones (Devaney et al., 2004).
11.3.2.7. Ponza et al. (2004)—Nutrient Food
Intakes and Food Choices of Infants and
Toddlers Participating in WIC
Ponza etal. (2004) conducted a study using
selected data from FITS to assess feeding patterns,
food choices, and nutrient intake of infants and
toddlers participating in the Special Supplemental
Nutrition Program for Women, Infants, and Children
(WIC). Ponza et al. (2004) evaluated FITS data for
the following age groups: 4 to 6 months (N = 862),
7 to 11 months (N = 1,159), and 12 to 24 months
(jV=996). Table 11-25 shows the total sample size
described by WIC participants and non-participants.
The foods consumed were analyzed by tabulating
the percentage of infants who consumed specific
foods/food groups per day (Ponza etal., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza etal., 2004). Table 11-25 presents
the demographic data for WIC participants and
non-participants. Table 11-26 provides the food
choices for infants and toddlers. In general, there was
little difference in food choices among WIC
participants and non-participants, except for
consumption of yogurt by infants 7 to 11 months of
age and toddlers 12 to 24 months of age (see
Table 11-26). Non-participants, 7 to 24 months of
age, were more likely to eat yogurt than WIC
participants (Ponza et al., 2004).
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
were not provided. Other limitations are associated
with the FITS data and are described previously in
Section 11.3.2.6.
11.3.2.8. Mennella et al. (2006)—Feeding Infants
and Toddlers Study: The Types of Foods
Fed to Hispanic Infants and Toddlers
Mennella etal. (2006) investigated the types of
food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic
infants and toddlers in the United States. The FITS
2002 data for children between 4 and 24 months old
were used for the study. The data represent a random
sample of 371 Hispanic and 2,367 non-Hispanic
infants and toddlers (Menella et al., 2006). Menella
etal. (2006) grouped the infants as follows: 4 to
5 months (N = 84 Hispanic; 538 non-Hispanic), 6 to
11 months (N = 163 Hispanic; 1,228 non-Hispanic),
and 12 to 24 months (N = 124 Hispanic;
871 non-Hispanic) of age.
Table 11-27 provides the percentages of Hispanic
and non-Hispanic infants and toddlers consuming
milk, meats, or other protein sources on a given day.
In most instances, the percentages consuming the
different types of meats and protein sources were
similar (Mennella et al., 2006).
The advantage of the study is that it provides
information on food preferences for Hispanic and
non-Hispanic infants and toddlers. A limitation is that
the study did not provide food intake data, but
provided frequency of use data instead. Other
limitations are those noted previously in
Section 11.3.2.6 for the FITS data.
11.3.2.9. Fox et al. (2006)—Average Portion of
Foods Commonly Eaten by Infants and
Toddlers in the United States
Fox et al. (2006) estimated average portion sizes
consumed per eating occasion by children 4 to
24 months of age who participated in the FITS. The
FITS is a cross-sectional study designed to collect
and analyze data on feeding practices, food
consumption, and usual nutrient intake of U.S.
infants and toddlers and is described in
Section 11.3.2.6 of this chapter. It included a
stratified random sample of 3,022 children between 4
and 24 months of age.
Using the 24-hour recall data, Fox et al. (2006)
derived average portion sizes for six major food
groups, including meats and other protein sources.
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Chapter 11—Intake of Meats, Dairy Products, and Fats
Average portion sizes for select individual foods
within these major groups were also estimated. For
this analysis, children were grouped into six age
categories: 4 to 5 months, 6 to 8 months, 9 to
11 months, 12 to 14 months, 15 to 18 months, and 19
to 24 months. Tables 11-28 and 11-29 present the
average portion sizes of meats and dairy products for
infants and toddlers, respectively.
11.4. INTAKE OF FAT
11.4.1. Key Fat Intake Study
11.4.1.1. U.S. EPA (2007)—Analysis of Fat Intake
Based on the U.S. Department of
Agriculture's 1994-1996,1998
Continuing Survey of Food Intakes by
Individuals (CSFII)
U.S. EPA conducted an analysis to evaluate the
dietary intake of fats by individuals in the United
States using data from the USDA's 1994-1996, 1998
CSFII (USDA, 2000). Intakes of CSFII foods were
converted to U.S. EPA food commodity codes using
data provided in U.S. EPA's FCID (U.S. EPA, 2000).
The FCID contains a "translation file" that was used
to break down the USDA CSFII food codes into
548 U.S. EPA commodity codes. The method used to
translate USD A food codes into U.S. EPA commodity
codes is discussed in detail in U.S. EPA (2000).
Each of the 548 U.S. EPA commodity codes was
assigned a value between zero and one that indicated
the mass fraction of fat in that food item. For many
sources of fat, a commodity code existed solely for
the nutrient fat portion of the food. For example, beef
is represented in the FCID database by 10 different
commodity codes; several of these codes specifically
exclude fat, and one code is described as "nutrient fat
only." In these cases, the fat fraction could be
expressed as 0 or 1, as appropriate. Most animal food
products and food oils were broken down in this way.
The fat contents of other foods in the U.S. EPA
commodity code list were determined using the
USDA Nutrient Database for Standard Reference,
Release 13 (USDA, 1999b). For each food item in the
U.S. EPA code list, the best available match in the
USDA Nutrient Database was used. If multiple
values were available for different varieties of the
same food item (e.g., green, white, and red grapes), a
mean value was calculated. If multiple values were
available for different cooking methods (i.e., fried vs.
dry cooked), the method least likely to introduce
other substances, such as oil or butter, was preferred.
In some cases, not all of the items that fall under a
given food commodity code could be assigned a fat
content. For example, the food commodity code list
identified "turkey, meat byproducts" as including
gizzard, heart, neck, and tail. Fat contents could be
determined only for the gizzard and heart. Because
the relative amounts of the different items in the food
commodity code were unknown, the mean fat content
of these two items was assumed to be the best
approximation of the fat content for the food code as
a whole.
The analysis was based on respondents who had
provided body weights and who had completed both
days of the 2-day survey process. These individuals
were grouped according to various age categories.
The mean, standard error, and a range of percentiles
of fat intake were calculated for 12 food categories
(i.e., all fats, animal fats, meat and meat products,
beef, pork, poultry, organ meats, milk and dairy
products, fish, oils, nuts/seeds^eans/legumes/tubers,
and others) and 98 demographic cohorts. Fat intake
was calculated as a 2-day average consumption
across both survey days in units of grams per day and
grams per kilogram of body weight per day for the
whole survey population and for consumers only.
A secondary objective of the study was to
evaluate fat consumption patterns of individuals who
consume high levels of animal fats. The entire data
analysis was repeated for a subset of individuals who
were identified as high consumers of animal fats. The
selection of the high-consumption group was done
for each age category individually, rather than on the
whole population, because fat intake on a per-body-
weight basis is heavily skewed towards young
children, and an analysis across the entire American
population was desired. For infants, the "less-than-1-
year-old" group was used instead of the smaller
infant groups (<1 month, 1 to <3 months, etc.).
Within each of the age categories, individuals that
ranked at or above the 90th percentile of consumption
of all animal fats on a per-unit body-weight basis
were identified. Because of the sample weighting
factors, the high consumer group was not necessarily
10% of each age group. The selected individuals
made up a survey population of 2,134 individuals.
Fat intake of individuals in this group was calculated
in g/day and g/kg-day for the whole population (i.e.,
per capita) and for consumers only.
The analysis presented in U.S. EPA (2007) was
conducted before U.S. EPA published the guidance
entitled Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Therefore, the age groups used for children in
U.S. EPA (2007) were not entirely consistent with the
age groups recommended in the 2005 guidance. A
re-analysis of the some of the data was conducted to
conform with U.S. EPA's recommended age groups
for children. The results of this re-analysis are
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11-12
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Chapter 11—Intake of Meats, Dairy Products, and Fats
included in Tables 11-30 through 11-35 for all
individuals. Only intake rates of all fats are provided
in these tables; refer to U.S. EPA (2007) for fat intake
rates from individual food sources. Tables 11-30 and
11-31 present intake rates of all fats for the whole
population (i.e., per capita) in g/day and g/kg-day,
respectively. Tables 11-32 and 11-33 present intake
rates of all fats for consumers only in g/day and
g/kg-day, respectively. Fat intake rates of all fats for
the top decile of animal fat consumers from the
consumers only group are presented in Table 11-34 in
g/day and in Table 11-35 in g/kg-day (per capita total
fat intake rates for the top decile of animal fat
consumers are not provided because they are the
same as those for consumers only).
11.4.2. Relevant Fat Intake Studies
11.4.2.1. Cresanta et al (1988)/Nicklas et al.
(1993)/Frank et al (1986)—Bogalusa
Heart Study
Cresanta etal. (1988), Nicklas etal. (1993), and
Frank et al. (1986) analyzed dietary fat intake data as
part of the Bogalusa heart study. The Bogalusa study,
an epidemiologic investigation of cardiovascular
risk-factor variables and environmental determinants,
collected dietary data on subjects residing in
Bogalusa, LA, beginning in 1973. Among other
research, the study collected fat intake data for
children, adolescents, and young adults. Researchers
examined various cohorts of subjects, including (1)
six cohorts of 10-year olds, (2) two cohorts of
13-year olds, (3) one cohort of subjects from
6 months to 4 years of age, and (4) one cohort of
subjects from 10 to 17 years of age (Nicklas, 1995).
To collect the data, interviewers used the 24-hour
dietary recall method. According to Nicklas (1995),
"the diets of children in the Bogalusa study are
similar to those reported in national studies of
children." Thus, these data are useful in evaluating
the variability of fat intake among the general
population. Tables 11-36 and 11-37 present data for
6-month-old to 17-year-old individuals collected
during 1973 to 1982 (Frank etal., 1986). Data are
presented for total fats, animal fats, vegetable fats,
and fish fats in units of g/day (see Table 11-36) and
g/kg-day (see Table 11-37).
11.5. CONVERSION BETWEEN WET- AND
DRY-WEIGHT INTAKE RATES
The intake rates presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
uncooked weight of meats and dairy products
consumed per day or per eating occasion). However,
data on the concentration of contaminants in meats
and dairy products may be reported in units of either
wet or dry weight (e.g., mg contaminant per gram
dry-weight of meats and dairy products). It is
essential that exposure assessors be aware of this
difference so that they may ensure consistency
between the units used for intake rates and those used
for concentration data (i.e., if the contaminant
concentration is measured in dry weight of meats and
dairy products, then the dry-weight units should be
used for their intake values).
If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to dry-weight intake
rates using the moisture content percentages
presented in Table 11-38 and the following equation:
IRdw=IRn
WO-W
100
(Eqn. 11-1)
where:
IRdw = dry-weight intake rate,
IRWW = wet-weight intake rate, and
W = percent water content.
Alternatively, dry-weight residue levels in meat
and dairy products may be converted to wet-weight
residue levels for use with wet-weight (e.g.,
as-consumed) intake rates as follows:
C =
^ww
100-E
100
(Eqn. 11-2)
where:
W
wet-weight concentration,
dry-weight concentration, and
percent water content.
The moisture content data presented in
Table 11-38 are for selected meats and dairy products
taken from USDA (2007).
11.6. CONVERSION BETWEEN
WET-WEIGHT AND LIPID-WEIGHT
INTAKE RATES
In some cases, the residue levels of contaminants
in meat and dairy products may be reported as the
concentration of contaminant per gram of fat. This
may be particularly true for lipophilic compounds.
When using these residue levels, the assessor should
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
ensure consistency in the exposure assessment
calculations by using consumption rates that are
based on the amount of lipids consumed for the meat
or dairy product of interest.
If necessary, wet-weight (e.g., as-consumed)
intake rates may be converted to lipid-weight intake
rates using the fat content percentages presented in
Table 11-38 and the following equation:
100
(Eqn. 11-3)
where:
IRww
L
lipid-weight intake rate,
wet-weight intake rate, and
percent lipid (fat) content.
Alternately, wet-weight residue levels in meat and
dairy products may be estimated by multiplying the
levels based on fat by the fraction of fat per product
as follows:
*-"WW ^hv -
100
(Eqn. 11-4)
where:
c
^ww
Clw
L
wet-weight concentration,
lipid-weight concentration, and
percent lipid (fat) content.
The resulting residue levels may then be used in
conjunction with wet-weight (e.g., as-consumed)
consumption rates. Table 11-38 presents the total fat
content data for selected meat and dairy products
taken from USDA (2007).
11.7. REFERENCES FOR CHAPTER 11
Cresanta, JL; Farris, RP; Croft, JB; Webber, LS;
Frank, GC; Berenson,GS. (1988) Trends in
fatty acid intakes of 10-year-old children,
1973-1982. J Am Diet Assoc
88(2):178-184.
Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T;
Clusen, N; Ziegler, P. (2004) Feeding infants
and toddlers study: overview of the study
design. J Am Diet Assoc 104(Suppl
1):S8-S13.
Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004)
Feeding Infants and Toddlers Study: what
foods are infants and toddlers eating? J Am
Diet Assoc 104:822-830.
Fox, MK; Reidy, K; Karwe, V; Ziegler, P. (2006)
Average portions of foods commonly eaten
by infants and toddlers in the United States.
J Am Diet Assoc 106 (Suppl 1):S66-S76.
Frank, GC; Webber, LS; Farris, RP; Berenson, GS.
(1986) Dietary databook: quantifying
dietary intakes of infants, children, and
adolescents, the Bogalusa heart study,
1973-1983. National Research and
Demonstration Center - Arteriosclerosis,
Louisiana State University Medical Center,
New Orleans, Louisiana.
Mennella, J; Ziegler, P; Briefel, R; Novak, T. (2006)
Feeding Infants and Toddlers Study: the
types of foods fed to Hispanic infants and
toddlers. J Am Diet Assoc 106 (Suppl 1):
S96-S106.
National Center for Health Statistics (NCHS) (1993).
Joint Policy on Variance Estimation and
Statistical Reporting Standards on NHANES
III and CSFII Reports: HNIS/NCHS
Analytic Working Group Recommendations.
Human Nutrition Information Service
(HNIS)/Analytic Working Group. Available
from: Agricultural Research Service, Survey
Systems/Food Consumption Laboratory,
4700 River Road, Unit 83, Riverdale, MD
20737.
Nicklas, TA. (1995) Dietary studies of children: The
Bogalusa Heart Study experience. J Am
Diet Assoc 95:1127-1133.
Nicklas, TA; Webber, LS; Srinivasan, SR; Berenson,
GS. (1993) Secular trends in dietary intakes
and cardiovascular risk factors in 10-y-old
children: the Bogalusa heart study
(1973-1988). Am J Clin Nutr 57:930-937.
Ponza, M; Devaney, B; Ziegler, P; Reidy, K;
Squatrito, C. (2004) Nutrient intakes and
food choices of infants and toddlers
participating in WIC. J Am Diet Assoc 104
(Suppl): S71-S79.
Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ;
Cook, AJ. (2002) Foods commonly eaten in
the United States: Quantities consumed per
eating occasion and in a day, 1994-1996.
U.S. Department of Agriculture NFS Report
No. 96-5, pre-publication version, 252 pp.
Page
11-14
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September 2011
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
USDA (Department of Agriculture). (1980) Food and
nutrient intakes of individuals in one day in
the United States, Spring 1977. Nationwide
Food Consumption Survey 1977-1978.
Preliminary Report No. 2. Human Nutrition
Information Service, Beltsville, MD.
USDA (Department of Agriculture). (1992) Food and
nutrient intakes by individuals in the United
States, 1 day, 1987-88. Nationwide Food
Consumption Survey Report No. 87. Human
Nutrition Information Service, Beltsville,
MD.
USDA (Department of Agriculture). (1996a) Data
tables: results from USDA's 1994
Continuing Survey of Food Intakes by
Individuals and 1994 Diet and Health
Knowledge Survey. Agricultural Research
Service, Riverdale, MD.
USDA (Department of Agriculture). (1996b) Data
tables: results from USDA's 1995
Continuing Survey of Food Intakes by
Individuals and 1995 Diet and Health
Knowledge Survey. Agricultural Research
Service, Riverdale, MD.
USDA (Department of Agriculture). (1999a) Food
and nutrient intakes by children 1994-96,
1998: table set 17. Food Surveys Research
Group, Human Nutrition Research Center,
Agricultural Research Service, Beltsville,
MD. Available online at
http://www.ars.usda.gov/SP2UserFiles/Place
/12355000/pdf/scs_all.pdf.
USDA (Department of Agriculture). (1999b) USDA
nutrient database for standard reference,
Release 13. Agricultural Research Service,
Nutrient Data Laboratory, Riverdale, MD.
Available online at
http ://www. nal.usda. gov/fnic/foodcomp.
USDA (Department of Agriculture). (2000) 1994-96,
1998 continuing survey of food intakes by
individuals (CSFII). CD-ROM. Agricultural
Research Service, Human Nutrition
Research Center, Beltsville, MD. Available
from the National Technical Information
Service, Springfield, VA; PB-2000-500027.
USDA (Department of Agriculture). (2007) USDA
national nutrient database for standard
reference, release 20. Agricultural Research
Service Nutrient Data Laboratory Home
Page. Available online at
http://www.ars.usda.gov/ba/bhnrc/ndl.
U.S. EPA (Environmental Protection Agency). (2000)
Food commodity intake database [FCID raw
data file]. Office of Pesticide Programs,
Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Risk Assessment Forum, Washington, DC;
EPA/630/P-03/003F. Available online at
http ://www. epa. gov/raf/publications/pdfs/A
GEGROUPS.PDF
U.S. EPA (Environmental Protection Agency). (2007)
Analysis of fat intake based on USDA's
1994-96, 1998 continuing survey of food
intakes by individuals (CSFII). National
Center for Environmental Assessment,
Washington, DC; EPA/600/R-05/021F.
Available from the National Technical
Information Service, Springfield, VA, and
online at www.epa.gov/ncea.
Vitolins, M; Quandt, S; Bell, R; Arcury, T; Case, LD.
(2002) Quality of diets consumed by older
rural adults. J Rural Health 18 (l):49-56.
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Table 11-3. Per Capita Intake of Total Meat and Total Dairy Products Based on
(g/kg-day, edible portion, uncooked weight)
2003-2006 NHANES
% Percentiles
Population Group
N
Consuming
Mean SE 1st m
10th
25th
50th
75th
90'"
95m
99"1
Max
Total Meat
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 o 12 years
13 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
16,783
865
1,052
978
2,256
3,450
4,289
4,103
3,893
4,450
4,265
6,757
562
lAn
98
44
98
99
99
99
99
99
99
98
99
98
97
98
2.0 0.02 0.0J 0.2
1.2 0.12 0.0* 0.0*
4.0 0.12 0.0* 0.4*
3.9 0.13 0.0* 0.7
2.8 0.06 0.1* 0.5
2.0 0.04 0.0 0.3
1.8 0.03 0.0 0.3
1.6 0.04 0.0 0.2
1.4 0.02 0.0 0.2
2.2 0.05 0.0 0.2
2.2 0.05 0.0 0.3
1.8 0.02 0.0 0.2
2.2 0.08 0.0* 0.2
2.3 0.12 0.0* 0.1
0.5
0.0
0.8
1.4
0.9
0.6
0.5
0.4
0.4
0.5
0.6
0.5
0.5
0.5
0.9
0.0
2.0
2.1
1.5
1.0
1.0
0.8
0.8
1.0
1.0
0.9
1.1
1.0
1.6
0.0
3.4
3.3
2.5
1.7
1.6
1.3
1.3
1.8
1.7
1.5
1.9
1.9
2.5
1.7
5.5
5.0
3.8
2.7
2.4
2.1
1.9
3.0
2.9
2.4
2.8
2.9
3.8
3.6
8.0
7.6
5.2
3.8
3.4
3.0
2.6
4.2
4.5
3.5
4.0
4.5
4.8
5.4*
10.0*
8.5
6.4
4.7
4.1
3.6
3.1
5.4
5.8
4.4
6.0
6.4
7.8
9.3*
14.0*
12.4*
8.9*
6.8
5.7
5.1
4.4
8.3
9.0
6.9
10.1*
9.6*
23.4*
18.7*
23.4*
19.5*
13.6*
13.5*
12.0*
12.2*
8.6*
18.9*
23.4*
18.7*
19.5*
15.1*
Total Dairy Product
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race —Including Multiple
N = Sample size.
SE = Standard error.
Max = Maximum value.
* Estimates are less statistically
16,783
865
1,052
978
2,256
3,450
4,289
4,103
3,893
4,450
4,265
6,757
562
749
99.7
86
100
100
100
100
99.8
99.6
100
99.6
99.5
99.8
99
99.6
6.6 0.16 0.0 0.2
10.1 0.76 0.0* *0.0
43.2 1.80 1.0* *5.7
24.0 0.76 0.9* 4.5
12.9 0.42 0.5* 1.5
5.5 0.25 0.1 0.4
3.5 0.14 0.0 0.2
3.8 0.16 0.0 0.2
3.3 0.09 0.0 0.2
8.5 0.36 0.0 0.2
5.0 0.19 0.0 0.1
6.6 0.19 0.1 0.3
8.1 0.88 0.0* 0.1
6.7 0.50 0.0* 0.0
0.5
0.0
10.7
8.3
2.6
0.6
0.4
0.5
0.4
0.7
0.2
0.6
0.4
0.3
1.3
1.2
20.3
13.6
5.6
1.6
1.0
1.1
1.0
1.4
0.7
1.4
1.2
0.9
3.2
6.4
39.1
20.7
10.8
4.0
2.4
2.5
2.3
3.7
1.8
3.3
3.1
3.3
7.1
11.5
59.4
32.0
17.8
7.6
4.7
5.2
4.5
9.4
4.6
7.1
7.0
7.9
15.4
19.6
84.1
41.9
26.0
12.3
8.1
8.5
7.3
21.8
12.6
14.8
20.5
15.3
25.0
43.2*
94.7*
51.1
31.8
16.4
10.3
11.3
9.6
34.4
20.1
24.5
39.2
23.1
56.8
83.1*
141.22*
68.2*
42.9*
24.9
17.1
18.9
15.2
67.2
50.6
54.1
69.2*
54.4*
185.3*
163.9*
185.3*
154.5*
57.7*
45.0*
52.7*
52.7*
28.8*
156.4*
175.2*
185.3*
141.2*
112.2*
reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on
NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of 2003-2006 NHANES data.
Q
I
a
I
ft
I
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Table 11-4. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 2003-2006 NHANES (g/kg-day, edible
portion, uncooked weight)
Percentiles
Population Group
Mean SE
10tf
25"
50"
75"
90"
95"
99"
Total Meat
Whole Population 16,147
Age Group
Birth to 1 year 385
1 to 2 years 1,030
3 to 5 years 968
6 to 12 years 2,250
13 to 19 years 3,422
20 to 49 years 4,248
Females 13 to 49 years 4,054
50 years and older 3,844
Race
Mexican American 4,229
Non-Hispanic Black 4,154
Non-Hispanic White 6,520
Other Hispanic 535
Other Race—Including Multiple .?,-,„
2.0 0.02 0.05
2.7
4.1
3.9
2.8
2.0
1.8
1.6
1.4
2.3
2.2
1.9
2.3
2.3
0.20
0.10
0.13
0.06
0.04
0.03
0.04
0.02
0.05
0.05
0.02
0.08
0.12
0.0*
0.1*
0.0*
0.1*
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.1*
0.0*
0.3
0.1*
0.5*
0.9
0.5
0.4
0.3
0.3
0.3
0.3
0.4
0.3
0.4
0.3
0.5
0.2*
1.0
1.4
0.9
0.6
0.5
0.4
05
0.6
0.6
0.5
0.7
0.6
1.0
1.0
2.2
2.1
1.5
1.1
1.0
0.8
0.8
1.1
1.1
0.9
1.2
1.1
1.6
1.9
3.5
3.3
2.5
1.7
1.6
1.3
1.3
1.9
1.7
1.6
1.9
1.9
2.6
3.4
5.6
5.0
3.8
2.7
2.4
2.1
1.9
3.0
2.9
2.4
2.8
2.9
6.0*
8.0
7.7
5.2
3.8
3.4
3.0
2.6
4.2
4.5
3.5
4.1
4.5
4.8
8.1*
10.1*
8.6
6.4
4.7
4.1
3.6
3.1
5.5
5.8
4.5
6.0
6.7
7.8
16.6*
14.0*
12.4*
8.9*
6.9
5.8
5.1
4.4
8.3
9.0
7.0
10.1*
9.6*
Total Dairy Product
Max
23.4*
18.7*
23.4*
19.5*
13.6*
13.5*
12.0*
12.2*
8.6*
18.9*
23.4*
18.7*
19.5*
15.1*
Whole Population 16,657 6.6 0.16 0.0 0.3 0.5 1.3 3.2 7.1 15.5 25.0 56.8 185.3*
Age Group
Birthtolyear 753 11.7 0.88 0.0* 0.1* 0.8* 3.1 7.8 12.3 22.1* 44.7* 86.4* 163.9*
Ito2years 1,052 43.2 1.79 1.0* 5.7* 10.6 20.3 39.1 59.4 84.0 94.7* 141.2* 185.3*
3 to 5 years 978 24.0 0.77 0.9* 4.7 8.3 13.7 20.7 32.0 41.9 51.1 68.2* 154.5*
6 to 12 years 2,256 12.9 0.42 0.5* 1.6 2.6 5.6 10.8 17.8 26.0 31.8 42.9* 57.7*
13tol9years 3,449 5.5 0.25 0.1 0.4 0.6 1.6 4.0 7.6 12.3 16.4 24.9 45.0*
20to49years 4,280 3.5 0.14 0.0 0.2 0.4 1.0 2.4 4.7 8.1 10.3 17.1 52.7*
Females 13 to 49 years 4,095 3.8 0.16 0.0 0.2 0.5 1.1 2.5 5.3 8.5 11.3 18.9 52.7*
50 years and older 3,889 3.3 0.09 0.0 0.2 0.4 1.0 2.3 4.5 7.3 9.6 15.2 28.8*
Race
Mexican American 4,406 8.6 0.36 0.0 0.3 0.5 1.4 3.8 9.5 21.8 34.4 67.1 156.4*
Non-Hispanic Black 4,246 5.0 0.19 0.0 0.1 0.2 0.7 1.8 4.7 12.7 20.3 50.6 175.2*
Non-Hispanic White 6,708 6.6 0.19 0.1 0.4 0.6 1.4 3.3 7.1 14.9 24.5 54.1 185.3*
Other Hispanic 553 8.1 0.87 0.0* 0.2 0.5 1.2 3.2 7.1 20.6 40.1 72.7* 141.2*
Other Race—Including Multiple 742 6.7 0.51 0.0* 0.0 0.3 0.9 3.3 7.9 15.3 23.1 54.4* 112.2*
N = Sample size;
SE = Standard error;
Max = Maximum value.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on
NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of 2003-2006 NHANES data.
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Table 11-5. Per Capita Intake of Individual Meats and Dairy Products Based on 2003-2006 NHANES (g/kg-day, edible
portion, uncooked weight)
Population Group N Consuming Mean SE Consuming Mean SE Consuming Mean SE
Whole Population 16,783
Age Group
Birth to 1 year 865
1 to 2 years 1,052
3 to 5 years 97$
6 to 12 years 2,256
13 to 19 years 3,450
20 to 49 years 4,289
Females 13 to 49 years 4,103
50 years and older 3,893
Race
Mexican American 4,450
Non-Hispanic Black 4,265
Non-Hispanic White 6,757
Other Hispanic 552
Other Race — Including Multiple 749
Beef
88 0.77 0.01
27 0.34 0.07
84 1.38 0.08
91 1.42 0.08
92 1.11 0.04
91 0.83 0.03
88 0.73 0.02
86 0.60 0.02
87 0.58 0.01
86 0.94 0.04
88 0.79 0.03
88 0.74 0.01
80 0.89 0.07
84 0.84 0.06
Pork
80 0.39 0.01
19 0.17 0.04
73 0.75 0.06
79 0.79 0.06
84 0.52 0.02
79 0.36 0.02
81 0.36 0.02
79 0.28 0.01
82 0.33 0.01
86 0.43 0.02
79 0.40 0.03
81 0.38 0.01
73 0.36 0.03
78 0.41 0.03
Poultry
75 0.77 0.02
37 0.69 0.09
81 1.87 0.07
82 1.65 0.07
77 1.18 0.06
74 0.80 0.02
77 0.71 0.02
77 0.66 0.02
71 0.50 0.02
78 0.82 0.02
84 1.01 0.03
72 0.70 0.02
79 0.97 0.06
80 1.00 0.10
N = Sample size.
SE = Standard error.
Source: U.S. EPA analysis of 2003-2006 NHANES data.
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Table 11-6. Consumer-Only Intake of Individual Meats and Dairy Products Based on 2003-2006 NHANES (g/kg-day,
edible portion, uncooked weight)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
Females 13 to 49 years old
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
N Mean SE
Beef
14,328 0.88 0.01
233 1.28 0.20
893 1.65 0.08
879 1.56 0.08
2,102 1.20 0.04
3,140 0.91 0.03
3,767 0.84 0.02
3,585 0.70 0.02
3,314 0.66 0.01
3,679 1.09 0.03
3,751 0.90 0.03
5,843 0.84 0.02
450 1.11 0.06
605 1.00 0.06
N Mean SE
Pork
13,180 0.49 0.01
172 0.93 0.17
781 1.03 0.08
784 1.00 0.07
1,922 0.62 0.02
2,770 0.46 0.02
3,539 0.44 0.01
3,283 0.36 0.01
3,212 0.40 0.01
3,595 0.50 0.02
3,312 0.51 0.03
5,304 0.48 0.01
397 0.50 0.05
572 0.53 0.04
N Mean SE
Poultry
12,660 1.03 0.02
315 1.89 0.16
880 2.32 0.07
800 2.02 0.08
1,813 1.54 0.08
2,652 1.07 0.03
3,360 0.92 0.02
3,224 0.86 0.03
2,840 0.70 0.02
3,371 1.05 0.03
3,522 1.21 0.03
4,769 0.97 0.02
434 1.23 0.07
564 1.26 0.10
N = Sample size.
SE = Standard error.
Source: U.S. EPA analysis of 2003-2006 NHANES data.
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Table 11-7. Mean Meat Intakes per Individual in a Day, by
Total Meat,
Group Age (years) Poultry and
Fish
Male and
Female
1 and Under 72
Ito2
3 to 5
6 to 8
Male
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
91
121
149
188
218
272
310
285
295
274
231
75 and Over 196
Female
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
162
176
180
184
183
187
187
159
75 and Over 134
Male and
All Ages
a
b
c
Female
207
Based on USDA Nationwide
Beef
9
18
23
33
41
53
82
90
86
75
70
54
41
38
47
46
52
48
49
52
34
31
54
Sex and Age (g/day, as-consumed)3 for 1977-1978
Frankfurters,
p , Lamb, Veal, Sausages,
Game Luncheon
Meats, Spreads
4
6
8
15
22
18
24
21
27
28
32
25
39
17
19
14
19
17
19
19
21
17
20
Food Consumption Survey
Includes mixtures containing meat, poultry,
3
C
C
1
3
C
1
2
1
1
1
2
7
1
1
2
1
1
2
2
4
2
2
2
15
15
17
19
25
25
33
30
26
29
22
19
20
18
16
18
16
14
12
12
9
20
Total
Poultry
4
16
19
20
24
27
37
45
31
31
31
29
28
27
23
28
26
24
24
26
30
19
27
Chicken
Only
1
13
19
19
21
24
32
43
29
28
29
26
25
23
22
27
24
22
21
24
25
16
24
Meat
Mixtures'3
51
32
49
55
71
87
93
112
94
113
86
72
54
55
61
61
61
66
63
60
47
49
72
1977-1978 data for 1 day.
or fish as a main in|
jredient.
Less than 0.5 g/day, but more than 0.
Indicates data are not available.
Source:
USDA, 1980.
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Table 11-8. Mean Meat Intakes
Total Meat,
Group Age (years) Poultry, and Beef
Fish
Male and Female
5 and Under
Male
6 to 11
12 to 19
20 and over
Female
6 to 11
12 to 19
20 and over
All individuals
92 10
156 22
252 38
250 44
151 26
169 31
170 29
193 32
per Capita in a Day, by Sex and Age (g/day, as-consumed)3 for 1987-1988
Pork
9
14
17
19
9
10
12
14
a Based on USDA Nationwide Food Consumption
b Includes mixtures containing meat,
Source: USDA, 1992.
Frankfurters,
Lamb, Veal, Sausages,
Game Luncheon
Meats
0.5
O.5
1
23
1
O.5
1
1
Survey 1987-1988 data
11
13
20
2
11
18
13
17
for 1 day.
Total
Poultry
14
27
27
31
20
17
24
26
Chicken
Only
12
24
20
25
17
13
18
20
Meat
Mixtures'3
39
74
142
108
74
80
73
86
poultry, or fish as a main ingredient.
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Table 11-9. Mean Meat Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)3 for 1994 and 1995
Group Age (years)
Male and Female
5 and Under
Male
6 to 11
12 to 19
20 and over
Female
6 to 11
12 to 19
20 and over
All individuals
Total Meat,
Poultry, and Beef Pork
Fish
1994 1995 1994 1995 1994
94 87 10 8 6
131 161 19 18 9
238 256 31 29 11
266 283 35 41 17
117 136 18 16 5
164 158 23 22 5
168 167 18 21 9
195 202 24 27 11
Lamb, Veal,
Game
Frankfurters,
Sausages,
Luncheon
Total
Poultry
Chicken Only
Meat
Mixtures'3
Meats
1995
4
7
11
14
5
7
11
10
1994 1995
C C
0
1 1
2 1
C C
0
1 1
1 1
1994
17
22
21
29
18
16
16
21
1995
18
27
27
27
20
10
15
21
1994
16
19
40
39
19
20
25
29
1995
15
25
26
31
17
19
22
24
1994
14
16
29
30
15
15
20
23
1995
14
22
23
27
14
18
19
21
1994
41
51
119
124
51
94
87
98
1995
39
68
150
149
69
82
83
104
Based on USDA CSFII 1994 and 1995 data for 1 day.
b Includes mixtures containing meat, poultry, or fish as
0 Less than 0
5 grams/day, but more than 0.
amain
ingredient.
Source: USDA, 1996a, b.
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-10. Mean Dairy
Group Age (years)
Male and Female
1 and Under
I to 2
3 to 5
6 to 8
Male
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
75 and Over
Female
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
75 and Over
Product Intakes Per Capita in a Day, by Sex
as-consumed)3 for 1977-1978
Total Milk Fluid Milk
618 361
404 397
353 330
433 401
432 402
504 461
519 467
388 353
243 213
203 192
180 173
217 204
193 184
402 371
387 343
316 279
224 205
182 158
130 117
139 128
166 156
214 205
a Based on USDA Nationwide Food Consumption Survey
Source: USDA, 1980.
Cheese
1
8
9
10
8
9
13
15
21
18
17
14
18
7
11
11
18
19
18
19
14
20
and Age (g/day,
Eggs
5
20
22
18
26
28
31
32
38
41
36
36
41
14
19
21
26
26
23
24
22
19
1977-1978 data for 1 day.
Exposure Factors Handbook
September 2011
Page
11-23
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-11. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)3 for
Group Age (years)
Male and Female
5 and under
Male
6 to 11
12 to 19
20 and over
Female
6 to 11
12 to 19
20 and over
All individuals
1987-1988
Total Fluid Milk Whole Milk
347
439
392
202
310
260
148
224
Based on USDA Nationwide Food
Source: USDA, 1992.
177
224
183
88
135
124
55
99
Consumption Survey
Lowfat/Skim
Milk
129
159
168
94
135
114
81
102
1987-1988 data for
Cheese
7
10
12
17
9
12
15
14
Iday.
Eggs
11
17
17
27
14
18
17
20
Table 11-12. Mean Dairy Product Intakes Per Capita in a Day, by Sex and Age (g/day, as-consumed)3 for 1994
and 1995
Group Age (years)
Male and Female
5 and under
Male
6 to 11
12 to 19
20 and over
Female
6 to 11
12 to 19
20 and over
All individuals
Total Fluid Milk
1994
424
407
346
195
340
239
157
229
Based on USDA CSFII 1 994
Source: USDA, 1996a, b.
1995
441
400
396
206
330
235
158
236
and 1995
Whole
1994
169
107
105
50
101
75
37
65
data for
Milk
1995
165
128
105
57
93
71
32
66
Iday.
Lowfat Milk
1994
130
188
160
83
136
88
56
89
1995
129
164
176
88
146
107
57
92
Cheese
1994
12
11
19
19
17
14
16
17
1995
9
12
20
16
13
13
15
15
Eggs
1994
11
13
18
23
12
13
15
17
1995
13
15
24
23
15
17
16
19
Page
11-24
Exposure Factors Handbook
September 2011
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ft
s
Table 11-13. Mean Quantities of Meat and Eggs Consumed Daily by Sex and Age, Per Capita
Age Group „. Total Beef
Pork
Lamb, „ Frankfun
, Organ
veal, sausage
meats 1 *
game luncheon i
(g/day, as-consumed)3
Poultry
tcrs,
;S' . Total Chicken
neats
Mixtures,
mainly
ggS meat/poultry/
fish
Male and Female
Under 1 1,126 24 lb
1 1,016 80 5
2 1,102 94 7
Ito2 2,118 87 6
3 1,831 101 8
4 1,859 115 10
5 884 121 14
3 to 5 4,574 112 11
5 and under 7,818 93 8
b,c
2
6
4
6
6
6
6
5
b,c b,c
b,c b,c
b,c b,c
b,c b,c
b,c b,c
b,c b,c
b,c b,c
c b,c
c b,c
2
13
18
15
19
22
22
21
17
3
12
17
15
19
20
22
21
16
2
12
16
14
18
19
19
19
15
3
13
18
16
13
13
13
13
13
16
43
41
42
43
49
51
47
42
Male
6 to 9 787 151 18
6 to 11 1,031 154 19
12 to 19 737 250 30
7
7
12
b,c b,c
b,c b,c
lb 0
24
24
28
23
22
31
21
20
26
11
12
22
71
72
134
Female
6 to 9 704 121 17
6 to 11 969 130 18
12 to 19 732 158 21
4
5
5
b,c b,c
b,c b,c
b,c b,c
18
19
15
19
20
21
16
17
19
10
11
13
55
60
85
Male and Female
9 and under 9,309 110 12
19 and under 11,287 152 18
5
7
Based on data from 1994-1996, 1998 CSFII.
b Estimate is not statistically reliable due to small
0 Value less than 0.5, but greater than 0.
Note: Consumption amounts shown are representative
Source: USD A, 1999a.
c b,c
b,c b,c
19
20
sample size reporting intake.
of the 1st day of each participant's
18
22
survey response.
17
19
12
14
50
76
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Table 11-14. Percentage of Individuals Consuming Meats
Age Group (years)
Under 1
1
2
I to 2
o
J
4
5
3 to 5
5 and under
Sample
Size
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
Total
26.0
77.4
85.2
81.4
86.2
86.2
87.1
86.5
77.5
Beef Pork
2.1
11.9
16.2
14.1
13.8
16.1
18.2
16.0
13.7
l.lb
7.3
14.9
11.2
13.3
13.8
13.2
13.4
11.2
Lamb,
veal,
game
Male
0.2b
0.8b
0.8b
0.8b
0.5b
0.5b
0.6b
0.5
0.6
and Eggs, by Sex and
_. Frankfurters,
Organ
sausages,
meats , , '
luncheon meats
and Female
0.2b
0.2b
0.2b
0.2b
_b,c
0.2b
0.2b
0.2b
0.2b
6.1
26.3
33.2
29.9
36.4
37.0
35.1
36.1
30.4
Age (%)a
Poultry
Total
6.3
24.0
27.6
25.8
28.3
27.4
27.7
27.8
24.5
Chicken
5.0
23.1
25.6
24.4
26.0
25.1
24.8
25.3
22.6
Mixtures,
mainly
ggS meat/poultry/
fish
6.7
22.8
27.3
25.1
19.8
16.9
16.4
17.7
18.9
13.7
32.2
31.4
31.8
29.2
30.5
30.8
30.2
28.8
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
87.4
87.8
86.8
20.1
22.0
24.2
11.9
12.2
15.8
0.4b
0.4b
0.6b
O.lb
0.2b
0.0
37.4
36.2
31.8
24.8
22.9
20.6
22.3
20.5
17.6
15.1
15.6
17.0
36.2
35.7
38.3
Female
6 to 9
6 to 11
12 to 19
9 and under
19 and under
704
969
732
9,309
11,287
84.6
86.5
80.1
80.9
82.8
19.4
20.2
22.0
16.1
19.6
9.2
10.0
11.2
10.9
12.1
0.4b
0.4b
O.lb
Male
0.5
0.4
0.2b
O.lb
O.lb
and Female
0.2b
O.lb
33.5
33.1
24.6
24.3
22.7
23.1
22.9
21.6
24.3
22.7
20.2
19.8
18.9
22.0
20.1
13.4
13.3
15.0
17.1
16.4
32.4
32.8
34.0
31.0
33.3
Based on data from 1994-1996, 1998 CSFII.
b Estimate is not statistically reliable due to small sample size reporting intake.
0 Value less than 0.5, but greater than 0.
Note: Percentages shown are representative of the 1st day of each participant's survey response.
Source: USD A, 1999a.
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Table 11-15. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day, as-consumed)3
. „ , , Sample
Age Group (year) „. r
Total Milk
and Milk
Products
Milk, Milk Drinks, Yogurt
Total
Fluid Milk
Total
Male and
Under 1 1,126
1 1,016
2 1,102
Ito2 2,118
3 1,831
4 1,859
5 884
3 to 5 4,574
5 and under 7,818
762
546
405
474
419
407
417
414
477
757
526
377
450
384
369
376
376
447
61
475
344
408
347
328
330
335
327
^
Whole Lowfat Skim
Female
49
347
181
262
166
147
137
150
177
11
115
141
128
150
149
159
153
127
b,c
17
11
26
27
25
26
18
'bgurt E
4
14
10
12
10
10
9
10
10
Milk
Jesserts
3
11
16
14
22
23
25
23
18
Cheese
1
9
11
10
12
14
14
13
11
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
450
450
409
405
402
358
343
335
303
127
121
99
176
172
158
29
33
40
6
6
3b
31
35
29
13
12
19
Female
6 to 9
6 to 11
12 to 19
704
969
732
380
382
269
337
336
220
288
283
190
Male and
9 and under 9,309
19 and under 11,287
a
b
c
Note:
Source:
453
405
417
362
Based on data from 1994-1996, 1998 CSFII.
Estimate is not statistically reliable due to small
Value less than 0.5, but greater than 0.
Consumption amounts shown are representative
USD A, 1999a.
323
291
105
108
66
Female
153
121
146
136
92
141
135
sample size reporting intake.
of the 1st day of each participant
26
29
30
22
29
's survey
4
4
4b
8
6
response.
29
30
29
23
27
13
14
14
12
14
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Table 11-16. Percentage of Individuals Consuming Dairy
Age Group (year)
Sample
Total Milk and
Milk Products
Products, by
Sex and Age (%)a
Milk, Milk Drinks, Yogurt
Total
Fluid Milk
Total Whole
Lowfat
Skim
- Yogurt
Milk
Desserts
Cheese
Male and Female
Under 1
1
2
Ito2
3
4
5
3 to 5
5 and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
85.4
95.3
91.6
93.4
94.3
93.2
93.1
93.5
92.5
84.6
92.7
87.3
90.0
88.3
87.8
86.4
87.5
88.0
11.1
87.7
84.3
86.0
84.6
85.0
81.2
83.6
75.7
8.3
61.7
44.8
53.0
42.5
41.3
38.1
40.6
41.0
2.4
26.5
36.3
31.5
39.5
40.4
41.7
40.6
32.9
0.2b
1.5b
5.2
3.4
6.8
7.7
6.5
7.0
4.9
3.1
10.0
6.8
8.4
7.3
5.8
5.5
6.2
6.6
4.5
13.9
17.5
15.8
21.4
21.7
21.4
21.5
17.5
6.0
29.7
32.6
31.2
37.0
36.9
34.9
36.3
30.9
Male
6 to 9
6 to 11
12 to 19
787
1,031
737
93.2
92.3
81.3
85.5
84.6
65.8
80.7
79.0
59.6
32.4
30.8
22.6
44.3
43.1
30.7
8.6
9.5
7.0
3.8
3.7
1.7b
24.0
25.0
13.6
34.6
32.3
37.1
Female
6 to 9
6 to 11
12 to 19
704
969
732
90.2
90.2
75.4
82.5
81.5
54.0
77.5
76.0
49.7
31.5
33.2
17.5
40.8
37.8
23.9
8.1
8.4
9.5
2.9
3.0
2.2b
24.1
22.4
17.1
30.9
31.9
36.1
Male and Female
9 and under
19 and under
9,309
11,287
92.2
86.7
86.4
75.6
77.1
68.1
37.4
30.1
36.8
33.1
6.3
7.5
5.3
3.8
20.1
18.6
31.7
33.5
Based on data from 1994-1996, 1998 CSFII.
b Estimate is not
statistically reliable due to small sample size reporting intake.
Note: Percentages shown are
Source: USD A, 1999a
representative of the
1st day
of each participant
's survey
response.
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Table 11-17 Per Capita Intake of Total Meat and Total Dairy Products (g/kg-day, edible portion, uncooked weight)
Population Group
, , Percent
N
Consuming
Mean
SE
Percentiles
1st
ttl
10m
25m
50m
75m
90m
95m
99m
Max
Total Meat
Whole Population
Age Group
Birth to 1 year
1 to 2 years
it -
j to 3 years
6 to 12 years
13 to 19 years
20 to 49 years
50+ years
Season
Fall
Spring
Summer
Winter
Race
American Indian, Alaska Native
Asian, Pacific Islander
Black
Other
White
Region
Midwest
Northeast
South
Midwest
West
Urbanization
MSA, Central City
MSA, Outside Central City
Non-MSA
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
177
557
2,740
1,638
15,495
4,822
3,692
7,208
4,822
4,885
6,164
9,598
4,845
97.5
40.0
97.3
98.8
98.7
98.8
98.2
98.2
96.8
97.6
97.4
98.0
98.4
96.8
97.9
96.5
97.5
97.9
96.3
97.7
97.9
97.6
97.3
97.3
98.1
2.1
1.2
4.1
4.1
2.9
2.1
1.9
1.5
2.1
2.1
2.1
2.0
2.4
2.5
2.6
2.5
1.9
2.2
2.1
2.0
2.2
2.0
2.1
2.0
2.1
0.02
0.1
0.1
0.05
0.05
0.05
0.04
0.02
0.06
0.04
0.03
0.04
0.25
0.17
0.10
0.08
0.02
0.04
0.07
0.03
0.04
0.06
0.04
0.04
0.03
O.O5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.2
0.6
0.4
0.2
0.2
0.2
0.1
0.2
0.1
0.2
0.3
0.1
0.3
0.2
0.2
0.3
0.0
0.2
0.3
0.2
0.1
0.2
0.3
0.5
0.0
0.8
1.2
0.8
0.5
0.5
0.4
0.5
0.5
0.5
0.5
0.5
0.3
0.6
0.5
0.5
0.6
0.4
0.5
0.6
0.4
0.5
0.5
0.6
1.0
0.0
1.9
2.2
1.5
1.0
1.0
0.8
1.0
1.0
0.9
1.0
1.0
1.1
1.2
1.1
0.9
1.1
0.9
0.9
1.1
0.9
0.9
1.0
1.0
1.7
0.0
3.6
3.6
2.5
1.9
1.6
1.3
1.7
1.7
1.6
1.6
2.0
2.1
2.0
2.0
1.6
1.8
1.6
1.7
1.8
1.6
1.7
1.6
1.7
2.7
1.6
5.7
5.4
3.8
2.7
2.5
1.9
2.8
2.7
2.7
2.6
3.3
3.5
3.3
3.1
2.5
2.8
2.7
2.6
2.8
2.7
2.7
2.6
2.7
4.0
4.2
8.0
7.7
5.4
3.8
3.5
2.7
4.2
4.0
4.0
3.8
4.3
4.5
5.4
4.9
3.7
4.1
4.1
3.9
4.1
4.0
4.2
3.9
4.1
5.3
6.7
9.8
9.4
6.5
4.8
4.2
3.3
5.4
5.2
5.4
5.0
6.3
6.0
7.1
6.5
4.8
5.3
5.4
5.2
5.3
5.2
5.6
5.1
5.1
8.7
10.7
14.1
12.7
9.6
7.1
6.9
4.8
8.7
8.7
8.6
7.9
9.0
9.6
10.4
10.8
7.7
9.1
8.7
8.3
9.1
8.1
8.9
8.0
8.6
30.3
29.6
20.6
23.4
18.0
30.3
13.4
9.7
21.2
23.6
30.3
29.6
12.4
13.0
23.6
29.6
30.3
30.3
20.5
23.4
30.3
29.6
23.6
29.6
30.3
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Table 11-17. Per Capita Intake of Total Meat and Total Dairy Products Based on 1994-1996, 1998 CSFII
uncooked weight) (continued)
Population Group
Whole population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
50+ years
Season
Fall
Spring
Summer
Winter
Race
American Indian, Alaska
Native
Asian, Pacific Islander
Black
Other
White
Region
Midwest
Northeast
South
West
Urbanization
MSA, Central City
MSA, Outside Central City
Non-MSA
N = Sample size.
SE = Standard error.
N
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
177
557
2,740
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
Percent
Consuming
99.5
79.5
99.8
100.0
100.0
99.8
99.8
99.8
99.7
99.5
99.6
99.4
99.8
97.0
99.6
99.1
99.6
99.7
99.6
99.6
99.2
99.6
99.4
99.7
Mean
6.7
12.6
36.7
23.3
13.6
5.6
3.3
3.2
7.0
6.6
6.4
6.7
8.0
6.4
5.6
9.5
6.6
7.0
6.7
6.0
7.4
6.5
7.0
6.3
°T7
Sii ist
Total Dairy
0.1 0.01
0.9 0.0
0.7 0.4
0.3 1.1
0.4 0.3
0.2 0.01
0.1 0.01
0.1 0.02
0.2 0.0
0.2 0.0
0.2 0.0
0.1 0.0
1.1 0.0
0.4 0.0
0.2 0.0
0.6 0.0
0.1 0.0
0.3 0.0
0.2 0.0
0.1 0.0
0.4 0.0
0.2 0.0
0.1 0.0
0.3 0.0
(g/kg-day, edible portion,
Percentiles
5m
Product
0.2
0.0
3.9
4.2
1.8
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.0
0.0
0.1
0.1
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
10m
0.4
0.0
7.7
7.0
3.5
0.5
0.3
0.4
0.4
0.4
0.4
0.5
0.1
0.0
0.2
0.4
0.5
0.5
0.6
0.3
0.4
0.4
0.5
0.4
25m
1.2
1.0
17.4
13.0
6.7
1.5
0.9
1.0
1.3
1.3
1.2
1.3
0.8
0.6
0.6
1.3
1.4
1.4
1.5
1.0
1.4
1.1
1.4
1.1
50m
3.2
8.0
31.3
20.8
11.7
4.2
2.2
2.4
3.4
3.1
3.1
3.4
3.1
3.0
2.1
4.2
3.4
3.5
3.4
2.8
3.7
3.2
3.4
3.0
75m
7.3
14.1
49.8
30.9
18.5
8.1
4.6
4.5
8.0
7.3
6.8
7.3
11.0
7.4
6.5
11.5
7.2
7.7
7.3
6.3
8.5
7.1
7.7
6.8
90th
16.1
24.1
72.1
42.0
26.0
12.5
7.6
6.9
16.9
16.2
15.2
16.4
21.2
14.9
14.7
25.4
15.6
16.9
15.9
14.5
17.5
15.8
16.9
15.0
95m
25.4
48.7
88.3
49.4
31.5
15.5
9.9
8.9
26.9
25.0
24.7
25.0
30.2
28.1
23.3
36.3
24.7
25.8
25.7
23.7
27.6
25.1
26.3
23.9
99th
52.1
127
126
67.7
42.7
25.4
14.9
14.1
55.3
52.0
52.8
49.1
68.9
51.7
45.4
69.3
51.2
52.7
54.2
48.6
54.5
49.8
54.3
51.4
Max
223
186
223
198
80.6
32.7
36.4
42.5
156.8
185.6
164.8
223.2
146.2
164.8
185.6
185.2
223.2
198.4
185.6
223.2
185.2
198.4
223.2
180.7
MSA = Metropolitan statistical area.
Source: U.S. EPA analysis of
1994-1996,
1998 CSFII.
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Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on
uncooked weight)
Population Group
N
Mean
SE
1994-1996, 1998 CSFII (g/kg-day, edible portion,
Percentiles
1st
th
10th
25*
50th
75th
90th
95th
99th
Max
Total Meat
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
\3to 19 years
20 to 49 years
50+ years
Whole population
Season
Fall
Spring
Summer
Winter
Race
American Indian, Alaska Native
Asian, Pacific Islander
Black
Other
White
Region
Midwest
Northeast
South
West
Urbanization
MSA, Central City
MSA, Outside Central City
Non-MSA
575
2,044
4,334
2,065
1,208
4,593
4,565
19,384
4,423
4,995
5,510
4,456
171
503
2,588
1,508
14,614
4,573
3,448
6,798
4,565
5,783
9,004
4,597
3.0
4.2
4.2
2.9
2.1
1.9
1.5
2.1
96.8
97.6
97.4
98.0
98.4
96.8
97.9
96.5
97.5
97.9
96.3
97.7
97.6
97.3
97.3
98.1
0.2
0.1
0.1
0.1
0.05
0.04
0.02
0.02
2.2
2.1
2.1
2.0
2.5
2.6
2.6
2.6
2.0
2.2
2.1
2.1
2.1
2.2
2.1
2.2
5
0.01
0.04
0.04
0.1
0.02
0.04
0.03
0.04
0.06
0.04
0.03
0.04
0.27
0.18
0.10
0.09
0.02
0.04
0.07
0.03
0.06
0.04
0.04
0.02
0.1
0.6
0.8
0.5
0.3
0.4
0.3
0.4
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.3
1.0
1.2
0.9
0.6
0.6
0.5
0.6
0.4
0.3
0.3
0.4
0.4
0.3
0.5
0.4
0.3
0.4
0.4
0.3
0.3
0.3
0.3
0.4
1.0
2.1
2.2
1.5
1.1
1.0
0.8
1.0
0.6
0.6
0.5
0.6
0.5
0.6
0.7
0.7
0.5
0.7
0.5
0.5
0.5
0.5
0.6
0.6
2.2
3.6
3.6
2.5
1.9
1.6
1.3
1.7
1.0
1.0
1.0
1.0
1.1
1.2
1.2
1.2
1.0
1.1
1.0
1.0
1.0
1.0
1.0
1.1
4.2
5.7
5.5
3.9
2.8
2.5
2.0
2.7
1.7
1.7
1.7
1.7
2.1
2.3
2.0
2.0
1.6
1.8
1.7
1.7
1.6
1.7
1.7
1.7
7.4
8.1
7.7
5.4
3.8
3.5
2.7
4.0
2.8
2.7
2.7
2.6
3.3
3.5
3.3
3.2
2.5
2.8
2.7
2.7
2.7
2.8
2.6
2.8
9.2
9.8
9.4
6.5
4.8
4.2
3.3
5.3
4.2
4.1
4.0
3.9
4.3
4.5
5.4
5.0
3.7
4.1
4.2
3.9
4.0
4.2
3.9
4.1
12.9
14.1
12.7
9.6
7.1
6.9
4.8
8.7
5.5
5.2
5.5
5.0
6.3
6.0
7.2
6.6
4.8
5.3
5.5
5.2
5.2
5.6
5.2
5.1
29.6
20.6
23.4
18.0
30.3
13.4
9.7
30.3
8.7
8.8
8.7
7.9
9.0
9.6
10.5
10.9
7.7
9.2
8.7
8.3
8.1
9.1
8.0
8.6
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Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion,
uncooked weight) (continued)
Population Group
N
Mean
SE
Percentiles
1st
5m
10th
25m
50m
75m
90th
95th 99th
Max
Total Dairy Product
Whole population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
50+ years
Season
Fall
Spring
Summer
Winter
Race
American Indian, Alaskan Native
Asian, Pacific Islander
Black
Other
White
Region
Midwest
Northeast
South
West
Urbanization
MSA, Central City
MSA, Outside Central City
Non-MSA
N = Sample size.
SE = Standard error.
MSA = Metropolitan statistical area.
20,287
1,192
2,093
4,390
2,089
1,221
4,666
4,636
4,630
5,210
5,801
4,646
176
537
2,708
1,607
15,259
4,765
3,638
7,104
4,780
6,072
9,440
4,775
6.7
15.9
36.8
23.3
13.6
5.6
3.3
3.2
99.7
99.5
99.6
99.4
99.8
97.0
99.6
99.1
99.6
99.7
99.6
99.6
99.2
99.6
99.4
99.7
0.1
1.0
0.7
0.3
0.4
0.2
0.1
0.1
7.1
6.6
6.4
6.7
8.0
6.6
5.7
9.6
6.7
7.1
6.8
6.0
7.4
6.5
7.0
6.3
0.02
0.03
0.4
1.1
0.3
0.01
0.01
0.02
0.2
0.2
0.2
0.1
1.1
0.4
0.2
0.7
0.1
0.3
0.2
0.1
0.4
0.2
0.1
0.3
0.2
0.8
4.2
4.2
1.8
0.3
0.2
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.4
1.9
7.8
7.0
3.5
0.5
0.3
0.4
0.2
0.2
0.2
0.2
0.0
0.0
0.1
0.2
0.3
0.3
0.3
0.2
0.2
0.2
0.3
0.2
1.3
5.8
17.4
13.0
6.7
1.5
0.9
1.1
0.5
0.4
0.4
0.5
0.1
0.1
0.2
0.4
0.6
0.6
0.6
0.3
0.5
0.4
0.5
0.4
3.3
10.2
31.3
20.8
11.7
4.2
2.3
2.4
1.3
1.3
1.2
1.3
0.8
0.6
0.6
1.3
1.4
1.4
1.5
1.0
1.5
1.2
1.4
1.1
7.4
16.0
49.8
30.9
18.5
8.1
4.6
4.5
3.4
3.2
3.1
3.4
3.1
3.1
2.1
4.3
3.4
3.5
3.4
2.8
3.8
3.2
3.5
3.0
16.2
27.7
72.1
42.0
26.0
12.5
7.6
6.9
8.0
7.3
6.8
7.3
11.1
7.6
6.6
11.6
7.2
7.8
7.3
6.3
8.5
7.2
7.8
6.8
25.5 52.2
57.5 141.8
88.3 126.2
49.4 67.7
31.5 42.7
15.5 25.4
9.9 14.9
8.9 14.1
16.9 26.9
16.3 25.1
15.2 24.7
16.5 25.1
21.2 30.2
15.6 28.1
14.8 23.4
25.5 36.5
15.7 24.7
16.9 25.8
16.0 25.8
14.6 23.8
17.8 27.7
15.9 25.2
17.0 26.4
15.0 23.9
223.2
185.6
223.2
198.4
80.6
32.7
36.4
42.5
55.4
52.1
53.0
49.2
68.9
51.7
45.4
69.3
51.3
52.7
54.3
48.6
54.6
49.8
54.3
51.5
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
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s
Table 11-19. Per Capita Intake of Individual Meats and Dairy Products Based on 1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked
weight)
Percent
„ . ,. „ 1T _ . Mean SE
Population Group N Consuming
Beef
Whole population 20,607 85.9 0.9 0.02
Age Group
Birth to 1 year 1,486 25.3 0.4 0.04
1 to 2 years 2,096 85.5 1.7 0.06
3 to 5 years 4,391 90.8 1.8 0.04
6 to 12 years 2,089 92.7 1.3 0.04
13 to 19 years 1,222 91.1 1.0 0.05
20 to 49 years 4,677 86.1 0.8 0.03
50+ years 4,646 83.5 0.6 0.02
Season
F ,, 4,687 85.0 0.9 0.05
Ipring 5,308 86.4 0.9 0.03
Summer 5,890 85.7 0.9 0.03
Winter 4,722 86.7 0.9 0.02
Race
American Indian, Alaskan Native 177 87.9 1.3 0.21
Asian, Pacific Islander 557 78.6 0.9 0.08
Black 2,740 85.3 1.1 0.10
Other 1,638 85.0 1.1 0.05
White 15,495 86.4 0.9 0.02
Region
Midwest 4,822 89.8 1.0 0.02
Northeast 3,692 82.0 0.8 0.08
South 7,208 86.1 0.9 0.02
West 4,885 85.1 0.9 0.04
Urbanization
MSA, Central City 6,164 84.0 0.9 0.04
MSA, Outside Central City 9,598 85.9 0.9 0.02
Non-MSA 4,845 88.9 1.0 0.04
Percent
„ . Mean SE
Consuming
Pork
78.5 0.42 0.01
17.7 0.15 0.02
69.7 0.72 0.03
79.8 0.84 0.02
82.4 0.59 0.03
81.5 0.40 0.03
78.9 0.37 0.01
79.3 0.34 0.01
78.5 0.41 0.02
78.1 0.44 0.02
78.1 0.42 0.02
79.1 0.40 0.02
85.2 0.49 0.06
71.5 0.63 0.11
82.1 0.53 0.04
79.4 0.48 0.03
78.0 0.39 0.01
83.1 0.47 0.02
72.1 0.41 0.02
79.8 0.42 0.02
77.0 0.36 0.03
77.1 0.41 0.02
77.2 0.39 0.01
83.3 0.49 0.02
Percent
„ . Mean SE
Consuming
Poultry
67.6 0.71 0.01
30.1 0.66 0.05
73.7 1.7 0.05
73.0 1.5 0.03
67.1 0.93 0.03
65.5 0.68 0.03
69.0 0.64 0.02
66.5 0.52 0.02
69.7 0.76 0.03
66.8 0.70 0.02
65.4 0.69 0.02
68.6 0.70 0.02
78.1 0.62 0.07
78.1 0.90 0.09
73.3 0.93 0.05
68.7 0.83 0.06
66.1 0.66 0.01
66.9 0.69 0.03
68.3 0.78 0.04
67.2 0.70 0.02
68.4 0.70 0.03
70.6 0.78 0.02
68.5 0.72 0.02
61.1 0.60 0.03
Percent
„ . Mean SE
Consuming
Eggs
93.4 0.40 0.01
27.9 0.30 0.04
92.3 1.3 0.04
95.1 0.91 0.03
95.8 0.51 0.02
95.4 0.33 0.02
94.1 0.31 0.01
94.0 0.33 0.01
93.1 0.39 0.02
93.5 0.41 0.02
93.3 0.39 0.01
93.8 0.39 0.02
94.5 0.49 0.06
84.7 0.46 0.05
93.9 0.48 0.01
89.9 0.62 0.05
93.9 0.36 0.01
95.1 0.38 0.01
91.2 0.36 0.02
94.2 0.39 0.01
92.5 0.44 0.02
92.8 0.41 0.01
93.4 0.39 0.01
94.5 0.39 0.01
jV = Sample size.
SE = Standard error.
MSA = Metropolitan statistical area.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
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Table 11-20. Consumer-Only Intake of Individual Meats and Dairy Products Based on 1994-1996, 1998 CSFII (g/kg-day, edible
portion, uncooked weight)
T, ! 4- ,-, N Mean SE
P opulation Group ^ ~
Whole population 17,116 1.1 0.02
Age Group
Birth to 1 year 361 1.6 0.2
1 to 2 years 1,795 2.0 0.06
3 to 5 years 3,964 1.9 0.04
6 to 12 years 1,932 1.4 0.04
13 to 19 years 1,118 1.1 0.05
20 to 49 years 4,058 1.0 0.04
50+ years 3,888 0.7Pork 0.02
Season
T-, „ 3,894 1.1 0.06
Fall
Spring 4,429 1.0 0.03
Summer 4,855 1.1 0.03
Winter 3,938 1.0 0.02
Race
American Indian, Alaskan Native 157 1.5 0.15
Asian, Pacific Islander 413 1.2 0.08
Black 2,280 1.3 0.11
Other 1=296 1.3 0.06
White 12,970 1.0 0.02
Region
Midwest 4,179 1.1 0.02
Northeast 2,936 1.0 0.08
South 6,029 1.0 0.02
West 3,972 1.1 0.04
Urbanization
MSA, Central City 4,992 1.1 0.05
MSA, Outside Central City 7,937 1.0 0.02
Non-MSA 4,187 1.1 0.03
N Mean SE
15,431 0.53 0.01
248 0.83 0.08
1,488 1.0 0.04
3,491 1.1 0.03
1,731 0.72 0.03
1,002 0.50 0.03
3,732 0.47 0.01
3,739 0.43 0.01
3,547 0.5 0.02
3,979 0.6 0.02
4,354 0.5 0.02
3,551 0.5 0.02
144 0.6 0.05
359 0.9 0.14
2,122 0.6 0.04
1,152 0.6 0.04
11,654 0.5 0.01
3,856 0.6 0.01
2,502 0.6 0.02
5,517 0.5 0.02
3,556 0.5 0.03
4,516 0.5 0.02
7,028 0.5 0.02
3,887 0.6 0.02
N Mean SE
Poultry
13,702 1.1 0.01
434 2.2 0.1
1,552 2.2 0.06
3,210 2.0 0.04
1,421 1.4 0.04
808 1.0 0.04
3,221 0.9 0.02
3,056 0.8 0.02
3,217 1.1 0.03
3,491 1.1 0.02
3,810 1.1 0.03
3,184 1.0 0.03
116 0.8 0.08
410 1.2 0.11
2,025 1.3 0.05
1,125 1.2 0.07
10,026 1.0 0.02
3,115 1.0 0.03
2,522 1.1 0.03
4,770 1.0 0.02
3,295 1.0 0.03
4,275 1.1 0.02
6,461 1.0 0.02
2,966 1.0 0.03
N Mean SE
Eggs
18,450 0.42 0.01
402 1.1 0.1
1,936 1.4 0.04
4,171 0.96 0.03
2,001 0.53 0.02
1,167 0.34 0.02
4,399 0.33 0.01
4,374 0.35 0.01
4,211 0.4 0.02
4,751 0.4 0.02
5,245 0.4 0.01
4,243 0.4 0.02
159 0.5 0.07
434 0.5 0.06
2,462 0.5 0.02
1,404 0.7 0.05
13,991 0.4 0.01
4,398 0.4 0.01
3,236 0.4 0.02
6,510 0.4 0.01
4,306 0.5 0.02
5,475 0.4 0.01
8,565 0.4 0.01
4,410 0.4 0.01
N = Sample size.
SE = Standard error.
MSA = Metropolitan statistical area.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
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Table 11-21. Quantity (as-consumed) of Meat and
Dairy Products Consumed per Eating
Foods in Two Days
Occasion
and Percentage of Individuals Using These
Quantity consumed per eating occasion (g)
2 to 5 years old
Male and Female
Food category
PC
(N= 2,109)
Mean
6 to 1 1 years old
Male and Female
(N =1,432)
SE
PC
Mean
SE
PC
Male
(jV=696)
Mean
12 to 19 years old
SE
PC
Female
(jV=702)
Mean
SE
Meat
Beef steaks
Beef roasts
Ground beef
Ham
Pork chops
Bacon
Pork breakfast sausage
Frankfurters and luncheon meats
Total chicken and turkey
Chicken
Turkey
Fluid milk (all)
Fluid milk consumed with cereal
Whole milk
Whole milk consumed with cereal
Lowfat milk
Lowfat milk consumed with cereal
Skim milk
Skim milk consumed with cereal
Cheese, other than cream or cottage
Ice cream and ice milk
Boiled, poached, and baked eggs
Fried eggs
Scrambled eggs
11.1
5.2
59.5
6.9
11.0
10.4
5.3
51.7
63.8
44.6
5.1
92.5
68.1
50.0
33.8
47.5
3\.5
7.8
4.9
53.2
18.4
8.0
\7.3
10.4
58
49
3\
35
48
15
33
49
46
52
63
196
149
202
161
189
\36
171
\3\
24
92
36
48
59
4
5
1
4
3
1
2
1
1
1
7
3
4
3
5
3
4
9
11
1
3
3
1
4
11.3
4.8
63.7
8.5
10.1
9.7
6.0
50.9
53.8
36.0
5.7
Dairy
89.2
64.7
39.5
26.2
52.8
32.7
11.1
7.5
50.4
21.1
8.2
14.0
7.1
87
67
41
40
62
19
32
57
62
70
66
Product
241
202
244
212
238
198
225
188
29
\35
34
58
72
9
7
1
4
4
2
3
2
2
3
5
4
5
7
11
4
4
9
14
1
4
3
2
5
9.5
5.1
73.4
11.6
11.6
14.9
6.3
46.7
58.4
34.3
8.2
72.3
44.4
30.0
14.8
39.6
24.3
9.7
6.5
61.1
14.2
5.0
14.9
7.1
168
233*
66
68
100
25
40a
76
100
117
117
337
276
333
265
326
277
375
285a
38
221
44a
83
72 o
14
149a
3
7
8
2
a
3
4
5
14
8
10
\3
18
8
12
38
2T
2
12
a
5
5
9.4
5.5
61.5
9.9
8.5
11.1
3.3
38.5
54.1
36.\
5.8
64.4
42.7
22.4
14.1
32.4
21.1
\3.5
8.3
53.9
15.2
7.7
13.5
8.9
112
97a
52
40
72
18
40a
57
71
80 5
60a
262
222 9
258
235
262
227
255
181
27
187
45
59
\03
10
16a
3
5
7
1
a
3
2
3
a
8
8
7
\3
\3
12
14
\3
1
14
7
3
9
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Table 11-21. Quantity (as-consumed) of Meat and
Dairy Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods
in Two Days (continued)
Quantity consumed per eating occasion (g)
20 to 39 years old
Food category PC
Male
(N= 1,543)
Mean
Female
(N
SE PC
= 1,449)
Mean
(N
SE PC
40 to 59 years old
Male
= 1,663)
Mean
Female
(N
SE PC
= 1,694 )
Mean
(N
SE PC
60 years and older
Male
= 1,545)
Mean
Female
(N
SE PC
= 1,429)
Mean SE
Meat
Beefsteaks 17.1
Beefroasts 6.9
Ground beef 65.3
Ham 10.8
Pork chops 12.8
Bacon 14.1
Pork breakfast sausage 6.6
Frankfurters and luncheon meats 46.2
Total chicken and turkey 57.3
Chicken 37.1
Turkey 6.8
202
132
80
78
117
26
57
88
112
122
131
20 11.8
14 5.8
4 51.5
7 9.7
8 12.5
1 12.4
4 5.1
6 35.6
4 57.8
3 35.5
21 5.6
121
85
52
47
71
18
37
61
78
92
76
8 18.3
8 9.9
2 50.0
4 13.5
4 14.3
1 17.5
3 6.6
2 44.9
2 56.8
3 34.5
6 8.5
159
119
82
68
108
22
48
79
111
124
115
7 10.7
8 9.6
3 44.6
5 12.2
6 13.0
1 14.8
4 5.8
2 34.3
4 58.7
4 36.0
12 8.8
117
74
57
50
67
18
38
59
80
87
81
6 13.4
5 11.7
2 40.7
4 15.2
4 16.4
1 20.6
4 10.7
2 41.6
2 53.8
2 32.1
8 7.7
129
102
73
56
89
19
48
62
87
99
80
7 9.5
6 8.8
3 36.2
3 14.4
3 13.1
1 17.4
4 5.5
2 33.9
3 57.8
3 34.0
7 7.2
95 6
80 4
62 3
45 3
62 3
16 1
34 3
51 2
71 2
79 2
77 7
Dairy Product
Fluid milk (all) 58.0
Fluid milk consumed with cereal 26.9
Whole milk 22.9
Whole milk consumed with cereal 7.9
Lowfat milk 29.4
Lowfat milk consumed with cereal 14.0
Skim milk 9.3
Skim milk consumed with cereal 5.6
Cheese, other than cream or cottage 63.8
Ice cream and ice milk 14.7
Boiled, poached, and baked eggs 9.4
Fried eggs 15.2
Scrambled eggs 10.7
291
275
278
111
298
284
318
260
39
200
50
86
89
9 61.3
12 32.4
11 22.4
16 8.7
15 29.4
22 15.2
13 15.5
12 9.3
2 52.6
2 13.6
4 10.4
2 14.6
4 7.8
209
198
202
216
198
181
235
207
30
136
39
61
74
6 60.5
5 30.1
10 20.3
14 6.2
7 31.2
5 16.1
11 15.1
10 8.7
1 48.3
6 18.0
3 12.0
3 20.9
3 11.1
238
211
223
216
242
212
244
197
36
173
45
83
83
6 60.2
7 30.2
15 19.0
16 6.1
7 27.7
10 13.1
12 19.2
11 11.8
1 46.3
6 14.2
3 14.2
2 17.5
3 8.0
169
166
142
183
159
151
193
173
29
141
38
60
66
5 73.9
5 48.1
7 22.3
10 10.1
5 40.2
7 26.5
7 17.7
7 12.4
1 40.9
8 22.7
2 15.7
2 24.6
3 12.0
189
170
188
177
189
165
186
174
33
138
45
70
73
5 71.6
5 46.6
9 19.7
10 9.9
5 37.8
5 24.4
9 21.6
9 14.2
2 35.4
5 18.9
3 16.1
2 18.3
4 9.3
154 4
140 6
137 8
156 13
161 6
134 5
154 9
135 9
26 1
107 4
39 2
56 2
64 5
a Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation.
jV = Sample size.
PC = Percent consuming at least once in 2 days.
SE = Standard error of the mean.
Source: Smiciklas-Wright et al. (2002, based on
1994-1996 CSFII data).
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-22. Consumption
ranges) by
Subject Characteristic
Sex
Female
Male
Ethnicity
African American
European American
Native American
Age
70 to 74 years
75 to 79 years
80 to 84 years
85+ years
Marital Status
Married
Not Married
Education
8th grade or less
9th to 12th grades
> High School
Denture
Yes
No
Chronic Disease
0
1
2
3
4+
Weight3
<130 pounds
131 to 150 pounds
151 to 170 pounds
171 to 190 pounds
>191 pounds
a = Two missing values.
TV = Number of subjects.
Source: Vitolins et al., 2002.
of Milk, Yogurt, a
Demographic and
N
80
50
44
47
39
42
36
36
16
49
81
37
47
46
83
47
7
31
56
26
10
18
32
27
22
29
id Cheese: Median Daily Servings (and
Health Characteristics
Milk, Yogurt, and Cheese
1.6 (0.2-5.6)
1.5 (0.3-7.4)
1.9 (0.2-4.5)
1.6 (0.2-5.6)
1.3 (0.5-7.4)
.8 (0.3-7.4)
.6 (0.2-5.6)
.4 (0.2-4.5)
.6 (0.2-3.8)
.5 (0.2-7.4)
.7 (0.2-5.4)
1.8 (0.2-5.4)
1.6 (0.2-5.6)
1.4 (0.3-7.4)
1.5 (0.2-7.4)
1.6 (0.3-5.6)
2.0 (0.8-4.5)
1.8 (0.3-5.6)
1.6 (0.2-7.4)
1.2 (0.2-4.8)
1.5 (0.5-4.5)
1.3 (0.3-5.4)
1.6 (0.5-5.6)
1.8 (0.2-4.5)
1.6 (0.2-3.7)
1.5 (0.2-7.4)
Exposure Factors Handbook
September 2011
Page
11-37
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-23. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population
Sample Size
Percentage of Sample
Sex
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 11 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
Sample Size (Unweighted)
3,022
100.0
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Devaney et al, 2004.
Page
11-38
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-24. Percentage of Infants and Toddlers Consuming Milk, Meat, or Other Protein Sources
Food Group/Food
Cow's Milk
Whole
Reduced- fat or Non-fat
Unflavored
Flavored
Soy Milk
Any Meat or Protein Source
Baby Food Meat
Non-baby Food Meat
Other Protein Sources
Dried Beans and Peas, Vegetarian Meat Substitutes
Eggs
Peanut Butter, Nuts, and Seeds
Cheese
Yogurt
Protein Sources in Mixed Dishes
Baby Food Dinners
Beans and Rice, Chili, Other Bean Mixtures
Mixtures with Vegetables and/or Rice/Pasta
Soupa
Types of Meatb
Beef
Chicken or Turkey
Fish and Shellfish
Hotdogs, Sausages, and Cold cuts
Pork/Ham
Other
Percentage of Infants and Toddlers Consuming at Least Once in a
Day
4 to 6
months
0.8
0.5
0.3
0.8
0.0
0.0
14.2
1.7
1.5
2.7
0.6
0.7
0.0
0.4
1.2
11.0
9.5
0.0
0.9
0.9
0.9
2.0
0.0
0.0
0.3
0.3
7 to 8 9 to 11
months months
2.9
2.4
0.5
2.9
0.0
0.5
54.9
4.0
8.4
9.7
1.3
2.9
0.5
2.1
4.1
43.3
39.8
0.0
1.2
3.4
2.6
7.3
0.5
2.1
1.7
0.6
a The amount of protein actually provided by soups varies. Soups could not be
groups because all soups were assigned the same 2-digit food code and many
major soup ingredients.
b Includes baby food and non-baby food sources.
Source: Fox etal., 2004.
20.3
15.1
5.3
19.5
0.9
1.7
79.2
3.1
33.7
36.1
3.3
7.3
1.9
18.5
15.7
46.2
33.5
0.9
4.7
10.1
7.7
22.4
1.9
7.1
4.0
2.5
12tol4
months
84.8
68.8
17.7
84.0
1.8
1.5
91.3
1.1
60.3
59.2
7.0
17.0
8.8
34.0
14.9
30.1
10.2
1.2
8.2
12.5
16.1
33.0
5.5
16.4
9.7
2.8
15tol8
months
88.3
71.1
20.7
87.0
4.4
3.9
92.7
0.0
76.3
66.8
6.6
25.0
11.6
39.1
20.2
25.5
2.4
2.1
9.0
13.8
16.3
46.9
8.7
20.1
11.2
2.1
19 to 24
months
87.7
58.8
38.1
86.5
5.6
3.8
97.2
0.0
83.7
68.9
9.9
25.2
10.4
41.1
15.3
20.5
1.3
2.0
7.8
11.5
19.3
47.3
7.1
27.0
13.9
3.9
sorted reliably into different food
food descriptions lacked detail about
Exposure Factors Handbook
September 2011
Page
11-39
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-25. Characteristics of WIC Participants and Non-Participants" (percentages)
Infants 4 to 6 months
Infants 7 to 11 months
Toddlers 12 to 24 months
WIC
Participant
Non-
Participant
WIC
Participant
Non-
Participant
WIC
Participant
Non-
Participant
Sex
Male 55
Female 45
Child's Ethnicity
Hispanic or Latino 20
Non-Hispanic or Latino 80
Child's Race
White 69
Black 15
Other 22
Child In Daycare
Yes 39
No 61
Age of Mother
14 to 19 years 18
20 to 24 years 33
25 to 29 years 29
30 to 34 years 9
35 years or Older 9
Missing 2
Mother's Education
11th Grade or Less 23
Completed High School 35
Some Postsecondary 33
Completed College 7
Missing 2
Parent's Marital Status
Married 49
Not Married 50
Missing 1
Mother or Female Guardian Work
Yes 46
No 53
Missing 1
Urbanicity
Urban 34
Suburban 36
Rural 28
Missing 2
Sample Size (Unweighted) 265
54
46
11
89
84
4
11
38
62
1
13
29
33
23
2
2
19
26
53
1
93
7
1
51
48
1
55
31
13
1
597
55
45
24
76
63
17
20
34
66
13
38
23
15
11
1
15
42
32
9
2
57
42
1
45
54
1
37
31
30
2
351
51
49
92
86
5
9
46
54
1
11
30
36
21
1
2
20
27
51
0
93
7
0
60
40
0
50
34
15
1
808
57
43
22
78
67
13
20
43
57
9
33
29
18
11
0
17
42
31
9
1
58
41
1
55
45
0
35
35
28
2
205
52
48
10
84
5
11
53
47
1
14
26
34
26
1
3
19
28
48
2
11
1
61
38
1
48
35
16
2
791
WIC
X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within each
age group for each variable. The results of y? test are listed next to the variable under the column labeled non-participants for each of
the three age groups.
= p >0.01; non-participants significantly different from WIC participants on the variable.
= p <0.05; non-participants significantly different from WIC participants on the variable.
= Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Page
11-40
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-26. Food Choices for Infants and Toddlers by WIC Participation Status
Cow's Milk
Meat or Other Protein Source
Baby Food Meat
Non-baby Meat
Eggs
Peanut Butter, Nuts, Seeds
Cheese
Yogurt
Sample Size (unweighted)
Infants 4 to 6 months Infants 7 to
WIC Non- WIC
Participant Participant Participant
1.0 0.6 11.4
0.9 2.0 3.3
3.7 0.5b 25.0
0.9 0.6 8.5
0.0 0.0 1.4
0.0 0.6 9.0
0.8 1.4 5.5
265 597 351
11 months
Non-
Participant
13.2
3.6
22.0
4.2b
1.3
12.5
13.3b
808
Toddlers
WIC
Participant
92.3
0.0
77.7
24.1
12.9
38.5
9.3
205
12 to 24 months
Non-
Participant
85. 8a
0.3
75.1
23.0
9.8
38.8
18.9b
791
8 =p <0.05; non-participants significantly different from WIC participants.
b =p <0.01; non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Table 11-27. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
Milk, Meats, or Other Protein Sources on a Given Day
Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic
(JV=84)
Non-Hispanic
(A? =538)
Hispanic
(N= 163)
Non-Hispanic
(N= 1,228)
Hispanic
(N= 124)
Non-Hispanic
(A? =871)
Milk
Fed Any Cow's or Goat Milk
Fed Cow's Milk
Whole
Reduced Fat or Non-fat
Meat or Other Protein Source
Any Meat or Protein Source8
Non-baby Food Meat
Other Protein Sources
Beans and Peas
Eggs
Cheese
Yogurt
Protein Sources in Mixed Dishes
Baby Food dinners
Soupb
Types of Meat8
9.7|
5.3
7.5|
4.4
3.9
7.5|
5.6|
2.2|
71.6
22.5
26.5
5.8|
9.5
11.2
7.7
44.8
24. T
16.3d
11.3
8.3
3.0
62.0
19.2
21.2
1.8
4.2
9.4
9.8
41.6
35.3
5.1
85.6
61.7
29.0
90.3
72.3
70.1
19.1C
26.4
29.3
15.7
33.3
3.5|
23.4C
87.7
66.3
27.0
94.7
76.0
65.3
6.5
22.5
40.2
17.0
22.7
3.9
10.7
Beef
Chicken and Turkey
Hotdogs, Sausages, and Cold Cuts
Pork/Ham
5.0|
11.2
7.2|
3.8|
4.6
11.9
3.4
1.7
25.2
46.5
14.8
11.7
16.0
43.6
23.3
12.1
Includes baby food and non-baby food sources.
The amount of protein actually provided by soups varies. Soups could not be sorted reliably into different food groups because many
food descriptions lacked detail about major soup ingredients.
= Significantly different from non-Hispanic atp <0.05.
= Significantly different from non-Hispanic atp >0.01.
= Less than 1% of the group consumed this food on a given day.
= Statistic is potentially unreliable because of a high coefficient of variation.
= Sample size.
Source: Mennella et al., 2006.
Exposure Factors Handbook
September 2011
Page
11-41
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-28. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly
by Infants from the 2002 Feeding Infants and Toddlers Study
Food Group
Non-baby food meats
Cheese
Scrambled eggs
Yogurt
Baby food dinners
4 to 5 months
Reference Unit (A? =624)
ounce
ounce
cup
ounce
ounce 2.9 ± 0.24
Consumed
6 to 8 months 9 to 1 1 months
(A? =708) (A? =687)
Mean ± SE
0.9 ±0.16
3.3 ±0.09
0.8 ±0.05
0.7 ±0.05
0.2 ±0.02
3.1 ±0.20
3.8±0.11
= Cell size was too small to generate a reliable estimate.
N = Number of respondents.
SE = Standard error of the mean.
Source: Fox et al., 2006.
Table 11-29. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly Consumed
by Toddlers from the 2002 Feeding Infants and Toddlers Study
Food Group
Milk
Milk
Milk, as a beverage
Milk, on cereal
Meats and other protein source
All meats
Beef
Chicken or turkey, plain
Hot dogs, luncheon meats, sausages
Chicken, breaded"
Scrambled eggs
Peanut butter
Yogurt
Cheese
Reference Unit
fluid ounce
fluid ounce
fluid ounce
ounce
ounce
ounce
ounce
ounce
nugget
cup
tablespoon
ounce
ounce
12 to 14 months
(A? =371)
5.6 ±0.14
5.7±0.14
3.4 ±0.37
1.2 ±0.06
0.8 ±0.08
1.3±0.10
1.3±0.13
1.5 ±0.14
2.4 ±0.22
0.2 ±0.02
0.7 ±0.08
3.4±0.19
0.8 ±0.05
15 to 18 months
(A? =3 12)
Mean ± SE
5.9 ±0.14
6.1±0.14
2.7 ±0.26
1.3 ±0.08
1.2±0.15
1.3±0.16
1.5±0.13
1.5±0.13
2.4 ±0.21
0.3 ±0.03
0.7 ±0.09
3. 8 ±0.26
0.8 ±0.05
19 to 24 months
(A? =320)
6.2 ±0.17
6.4 ±0.17
3.6 ±0.29
1.3 ±0.07
1.2 ±0.14
1.3 ±0.10
1.5±0.12
1.8±0.12
2.8 ±0.19
0.3 ±0.02
0.9 ±0.13
3. 8 ±0.28
0.7 ±0.04
a Not included in total for all meats because weight includes breading.
N = Number of respondents.
SE = Standard error of the mean.
Source: Fox et al., 2006.
Page
11-42
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-30. Per Capita Total Fat Intake (g/day)
Age Group"
Birth to <1 year
All
Female
Male
N
1,422
728
694
Mean
29
28
30
SE
18
17
18
Percentiles
10th
0
0
0
25th
19
18
20
50th
31
30
32
75th
40
39
40
95th
59
57
61
Max
107
92
107
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
All
Female
Male
<3 months
All
Female
Male
<6 months
All
Female
Male
<12 months
All
Female
Male
<2 years
All
Female
Male
<3 years
All
Female
Male
88
50
38
245
110
135
411
223
188
678
345
333
1,002
499
503
994
494
500
17
19
15
22
20
23
28
27
30
33
32
34
46
45
46
51
49
52
16
15
18
18
16
19
17
17
18
17
17
16
19
18
20
21
20
21
0
0
0
0
0
0
0.1
0
0.2
8.5
5.1
11
24
25
23
27
24
29
0
0
0
0
0
0
20
16
22
25
24
25
33
33
32
37
35
39
19
18
19
27
24
28
31
29
31
34
33
34
43
43
44
48
46
50
32
29
31
34
33
34
39
38
39
43
43
44
55
54
56
60
59
61
52
39
43
47
45
55
52
51
50
62
62
62
79
77
80
87
83
89
64
52
64
75
50
75
107
74
107
100
92
100
159
116
159
197
127
197
3 to <6 years
6 to
11 to
All
Female
Male
<11 years
All
Female
Male
<16 years
All
Female
Male
4,112
2,018
2,094
1,553
742
811
975
493
482
59
56
61
68
64
72
80
69
91
22
21
23
24
22
25
38
29
42
34
33
35
41
38
43
42
37
50
44
43
45
50
48
55
56
49
64
56
54
59
66
61
70
74
65
84
70
68
72
81
77
86
97
82
111
99
96
103
111
101
115
145
123
163
218
194
218
179
156
179
342
259
342
Exposure Factors Handbook
September 2011
Page
11-43
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Age Group"
16to<21
21to<31
31to<41
41to<51
51to<61
61 to <71
71to<81
81+ years
N
SE
Source:
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
All
Female
Male
Table
N
743
372
371
1,412
682
730
1,628
781
847
1644
816
828
1,578
768
810
1,507
719
788
888
421
467
392
190
202
Age groups are based on U.S.
Environmental Contaminants.
= Sample size.
= Standard error.
U.S. EPA, 2007.
11-30. Per Capita
Mean
85
79
92
84
65
103
83
64
101
78
63
93
73
58
88
66
53
78
60
51
68
57
49
64
SE
47
39
53
45
31
48
43
31
45
39
29
42
37
26
40
33
24
35
27
22
29
29
23
32
Total Fat Intake (g/day) (continued)
Percentiles
10th
37
35
41
36
30
50
36
29
49
36
31
46
31
27
39
29
26
37
28
27
34
24
22
31
EPA (2005) Guidance on Selecting
25th
54
49
57
53
43
68
52
42
69
50
43
63
46
39
57
42
36
53
41
37
48
36
32
43
Age Groups for
50th
76
75
77
76
59
93
74
58
96
70
59
87
66
56
82
60
49
73
55
49
67
54
48
61
Monitoring
75th
108
96
114
104
81
125
106
79
127
99
78
119
90
73
110
80
68
98
72
62
86
69
64
82
95th
168
154
186
164
126
181
162
121
190
153
114
166
137
104
156
123
96
138
104
86
114
102
84
106
Max
463
317
463
445
201
445
376
228
376
267
208
267
306
165
306
235
184
235
201
158
201
227
132
227
and Assessing Childhood Exposures to
Page
11-44
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-31. Per Capita Total
Age Group8
Birth to <1 year
All
Female
Male
N
1,422
728
694
Mean
4.0
4.1
4.0
SE
2.8
2.8
2.8
Fat Intake (g/kg-day)
Percentiles
10th
0
0
0
25th
2.3
2.4
2.3
50th
4.1
4.3
4.0
75th
5.6
5.8
5.5
95th
8.9
8.7
9.2
Max
20
18
20
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
11 to
All
Female
Male
<3 months
All
Female
Male
<6 months
All
Female
Male
<12 months
All
Female
Male
<2 years
All
Female
Male
<3 years
All
Female
Male
<6 years
All
Female
Male
<11 years
All
Female
Male
<16 years
All
Female
Male
88
50
38
245
110
135
411
223
188
678
345
333
1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
975
493
482
5.2
5.9
4.3
4.5
4.3
4.7
4.1
4.2
4.1
3.7
3.7
3.6
4.0
4.1
3.9
3.6
3.7
3.6
3.4
3.4
3.5
2.6
2.4
2.7
1.6
1.4
1.8
4.9
4.6
5.3
3.8
3.6
3.9
2.7
2.8
2.5
1.8
1.9
1.7
1.7
1.6
1.7
1.5
1.6
1.5
1.3
1.3
1.4
1.1
1.0
1.1
0.8
0.7
0.9
0
0
0
0
0
0
0
0
0
1.0
0.7
1.3
2.1
2.2
1.9
1.9
1.8
2.0
1.9
1.8
1.9
1.3
1.3
1.4
0.8
0.7
0.9
0
0
0
0
0
0
2.4
2.3
2.6
2.7
2.8
2.6
2.8
3.0
2.6
2.6
2.4
2.6
2.4
2.4
2.4
1.7
1.6
1.8
1.1
0.9
1.2
5.7
6.2
4.7
4.9
4.8
4.9
4.3
4.5
4.1
3.8
3.8
3.7
3.7
3.7
3.6
3.4
3.4
3.4
3.2
3.1
3.2
2.3
2.2
2.4
1.4
1.3
1.6
9.1
8.4
9.7
6.8
6.5
7.0
5.7
6.0
5.5
4.8
5.0
4.6
4.7
5.0
4.5
4.4
4.4
4.3
4.0
4.0
4.1
3.0
2.8
3.1
2.0
1.7
2.1
16
13
18
12
11
10
8.2
8.2
8.2
7.0
7.0
6.8
7.1
6.9
7.2
6.4
6.6
6.1
5.8
5.8
5.8
4.2
4.0
4.4
3.0
2.6
3.3
20
16
20
18
14
18
18
18
16
11
9.8
11
12
9.7
12
12
10
12
11
11
11
9.9
7.7
9.9
5.7
5.0
5.7
Exposure Factors Handbook
September 2011
Page
11-45
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-31. Per Capita Total Fat Intake (g/kg-day) (continued)
Age Group8
16to<21
21to<31
31to<41
41to<51
51to<61
61 to <71
71to<81
81+ years
a
N
SE
Source:
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
All
Female
Male
N
743
372
371
1,412
682
730
1,628
781
847
1,644
816
828
1,578
768
810
1,507
719
788
888
421
467
392
190
202
Age groups are based on U.S.
Environmental Contaminants.
= Sample size.
= Standard error.
U.S. EPA, 2007.
Mean
1.3
1.1
1.4
1.2
1.0
1.3
1.1
1.0
1.2
1.0
0.9
1.1
0.9
0.8
1.0
0.9
0.8
1.0
0.8
0.8
0.9
0.9
0.8
0.9
SE
0.66
0.56
0.73
0.61
0.52
0.66
0.55
0.52
0.54
0.49
0.43
0.53
0.46
0.38
0.50
0.43
0.39
0.45
0.37
0.37
0.37
0.43
0.39
0.47
Percentiles
10th
0.54
0.48
0.63
0.53
0.44
0.63
0.49
0.45
0.59
0.48
0.43
0.53
0.42
0.39
0.47
0.40
0.36
0.46
0.40
0.39
0.42
0.37
0.35
0.39
25th
0.81
0.75
0.85
0.72
0.65
0.85
0.69
0.61
0.85
0.66
0.61
0.72
0.61
0.56
0.65
0.55
0.50
0.61
0.56
0.53
0.61
0.56
0.54
0.56
EPA (2005) Guidance on Selecting Age Groups for
50th
1.2
1.1
1.2
1.1
0.9
1.2
1.0
0.9
1.2
0.9
0.9
1.0
0.86
0.79
0.95
0.79
0.74
0.87
0.78
0.72
0.82
0.82
0.82
0.82
75th
1.6
1.4
1.7
1.5
1.3
1.6
1.4
1.3
1.5
1.3
1.2
1.4
1.2
1.1
1.3
1.1
1.0
1.2
1.0
1.0
1.1
1.1
1.1
1.1
95th
2.7
2.1
2.9
2.3
2.0
2.4
2.1
1.9
2.3
1.9
1.7
2.0
1.7
1.5
1.9
1.7
1.5
1.8
1.5
1.4
1.5
1.5
1.5
1.6
Max
6.0
4.4
6.0
7.3
3.7
7.3
4.7
4.7
4.3
4.4
2.9
4.4
3.8
2.4
3.8
3.2
3.2
3.1
3.2
3.2
2.6
3.7
2.1
3.7
Monitoring and Assessing Childhood Exposures to
Page
11-46
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-32. Consumers-Only
Age Group8
Birth to <1 year
All
Female
Male
N
1,301
664
637
Mean
31
30
32
SE
16
16
16
Total Fat Intake (g/day)
Percentiles
10th
7.0
5.1
9.0
25th
24
24
25
50th
32
32
33
75th
41
40
41
95th
61
58
62
Max
107
92
107
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
All
Female
Male
<3 months
All
Female
Male
<6 months
All
Female
Male
<12 months
All
Female
Male
<2 year
All
Female
Male
<3 years
All
Female
Male
<6 years
All
Female
Male
<11 years
All
Female
Male
59
37
22
182
79
103
384
205
179
676
343
333
1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
26
26
25
29
28
31
30
29
31
33
32
34
46
45
46
51
49
52
59
56
61
68
64
72
13
11
17
14
12
16
16
16
17
16
17
16
19
18
20
21
20
21
22
21
23
24
22
25
6.7
7.8
-
5.8
4.3
8.5
2.5
1.2
4.6
8.9
6.2
11
24
25
23
27
24
29
34
33
35
41
38
43
17
17
-
24
21
27
24
24
25
25
24
25
33
33
32
37
35
39
44
43
45
50
48
55
27
25
-
31
30
31
32
31
33
34
34
34
43
43
44
48
46
50
56
54
59
66
61
70
32
32
-
35
35
38
40
39
39
43
43
44
55
54
56
60
59
61
70
68
72
81
77
86
52
39
-
53
46
59
54
52
53
62
62
62
79
77
80
87
83
89
99
96
103
111
101
115
64
52
64
75
50
75
107
72
107
100
92
100
159
116
159
197
127
197
218
194
218
179
156
179
11 to <16 years
All
Female
Male
975
493
482
80
69
91
38
29
42
42
37
50
56
49
64
74
65
84
97
82
111
145
123
163
342
259
342
Exposure Factors Handbook
September 2011
Page
11-47
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-32. Consumers-Only Total Fat Intake (g/day) (continued)
Age Group8
16to<21
21to<31
31to<41
41to<51
51to<61
61to<71
71to<81
81+ years
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
All
Female
Male
N Mean
743
372
371
1,412
682
730
1,628
781
847
1,644
816
828
1,578
768
810
1,507
719
788
888
421
467
392
190
202
85
79
92
84
65
103
83
64
101
78
63
93
73
58
88
66
53
78
60
51
68
57
49
64
SE
47
39
53
45
31
48
43
31
45
39
29
42
37
26
40
33
24
35
27
22
29
29
23
32
Percentiles
10th
37
35
41
36
30
50
36
29
49
36
31
46
31
27
39
29
26
37
28
27
34
24
22
31
25th
54
49
57
53
43
68
52
42
69
50
43
63
46
39
57
42
36
53
41
37
48
36
32
43
a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
to Environmental Contaminants.
N
SE
Source:
50th
76
75
77
76
59
93
74
58
96
70
59
87
66
56
82
60
49
73
55
49
67
54
48
61
75th
108
96
114
104
81
125
106
79
127
99
78
119
90
73
110
80
68
98
72
62
86
69
64
82
95th
168
154
186
164
126
181
162
121
190
153
114
166
137
104
156
123
96
138
104
86
114
102
84
106
Max
463
317
463
445
201
445
376
228
376
267
208
267
306
165
306
235
184
235
201
158
201
227
132
227
Monitoring and Assessing Childhood Exposures
= Percentiles were not calculated for sample sizes less than 30.
= Sample size.
= Standard error.
U.S. EPA, 2007.
Page
11-48
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-33.
Age Group8
Birth to <1 year
All
Female
Male
N
1,301
664
637
Mean
4.4
4.5
4.3
Consumers-Only Total Fat Intake (g/kg-day)
SE
2.6
2.6
2.6
Percentiles
10th
0.94
0.67
1.2
25th
2.9
3.1
2.8
50th
4.3
4.5
4.1
75th
5.8
6.0
5.6
95th
9.2
8.9
9.3
Max
20
18
20
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
All
Female
Male
<3 months
All
Female
Male
<6 months
All
Female
Male
<12 months
All
Female
Male
<2 years
All
Female
Male
<3 years
All
Female
Male
59
37
22
182
79
103
384
205
179
676
343
333
1,002
499
503
994
494
500
7.8
8.0
7.4
6.0
5.9
6.1
4.4
4.5
4.3
3.7
3.7
3.6
4.0
4.1
3.9
3.6
3.7
3.6
4.1
3.5
4.9
3.1
2.9
3.3
2.5
2.6
2.4
1.8
1.9
1.7
1.7
1.6
1.7
1.5
1.6
1.5
1.4
2.0
-
1.0
0.80
1.8
0.35
0.14
0.57
1.0
0.75
1.3
2.1
2.2
1.9
1.9
1.8
2.0
5.4
5.3
-
4.1
4.3
4.1
3.1
3.1
3.1
2.7
2.8
2.6
2.8
3.0
2.6
2.6
2.4
2.6
8.0
7.7
-
6.0
6.0
6.0
4.5
4.7
4.2
3.8
3.8
3.7
3.7
3.7
3.6
3.4
3.4
3.4
9.7
9.1
-
7.8
7.7
7.8
5.8
6.1
5.6
4.8
5.0
4.6
4.7
5.0
4.5
4.4
4.4
4.3
16
13
-
12
12
12
8.3
8.2
8.8
7.0
7.0
6.8
7.1
6.9
7.2
6.4
6.6
6.1
20
16
20
18
14
18
18
18
16
11
9.8
11
12
9.7
12
12
10
12
3 to <6 years
6 to
All
Female
Male
<11 years
All
Female
Male
4,112
2,018
2,094
1,553
742
811
3.4
3.4
3.5
2.6
2.4
2.7
1.3
1.3
1.4
1.1
1.0
1.1
1.9
1.8
1.9
1.3
1.3
1.4
2.4
2.4
2.4
1.7
1.6
1.8
3.2
3.1
3.2
2.3
2.2
2.4
4.0
4.0
4.1
3.0
2.8
3.1
5.8
5.8
5.8
4.2
4.0
4.4
11
11
11
9.9
7.7
9.9
11 to <16 years
All
Female
Male
975
493
482
1.6
1.4
1.8
0.80
0.69
0.86
0.77
0.67
0.88
1.1
0.91
1.2
1.4
1.3
1.6
2.0
1.7
2.1
3.0
2.6
3.3
5.7
5.0
5.7
Exposure Factors Handbook
September 2011
Page
11-49
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-33 Consumers-Only Total Fat Intake (g/kg-day) (continued)
Age Group8
16to<21
21to<31
31to<41
41to<51
51to<61
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
years
All
Female
Male
N
743
372
371
1,412
682
730
1,628
781
847
1,644
816
828
1,578
768
810
Mean
1.3
1.1
1.4
1.2
1.0
1.3
1.1
0.98
1.2
1.0
0.92
1.1
0.94
0.83
1.0
SE
0.66
0.56
0.73
0.61
0.52
0.66
0.55
0.52
0.54
0.49
0.43
0.53
0.46
0.38
0.50
Percentiles
10th
0.54
0.48
0.63
0.53
0.44
0.63
0.49
0.45
0.59
0.48
0.43
0.53
0.42
0.39
0.47
25th
0.81
0.75
0.85
0.72
0.65
0.85
0.69
0.61
0.85
0.66
0.61
0.72
0.61
0.56
0.65
50th
1.2
1.1
1.2
1.1
0.93
1.2
1.0
0.91
1.2
0.94
0.86
1.0
0.86
0.79
0.95
75th
1.6
1.4
1.7
1.5
1.3
1.6
1.4
1.3
1.5
1.3
1.2
1.4
1.2
1.1
1.3
95th
2.7
2.1
2.9
2.3
2.0
2.4
2.1
1.9
2.3
1.9
1.7
2.0
1.7
1.5
1.9
Max
6.0
4.4
6.0
7.3
3.7
7.3
4.7
4.7
4.3
4.4
2.9
4.4
3.8
2.4
3.8
61 to <71 years
71to<81
81+ years
a
N
SE
Source:
All
Female
Male
years
All
Female
Male
All
Female
Male
1,507
719
788
888
421
467
392
190
202
Age groups are based on U.S.
Environmental Contaminants
0.88
0.79
0.95
0.82
0.77
0.87
0.86
0.83
0.89
0.43
0.39
0.45
0.37
0.37
0.37
0.43
0.39
0.47
0.40
0.36
0.46
0.40
0.39
0.42
0.37
0.35
0.39
0.55
0.50
0.61
0.56
0.53
0.61
0.56
0.54
0.56
EPA (2005) Guidance on Selecting Age Groups for
= Percentiles were not calculated for sample
= Sample size.
= Standard error.
U.S. EPA, 2007.
sizes
less than 30.
0.79
0.74
0.87
0.78
0.72
0.82
0.82
0.82
0.82
1.1
0.99
1.2
1.0
0.95
1.1
1.1
1.1
1.1
1.7
1.5
1.8
1.5
1.4
1.5
1.5
1.5
1.6
3.2
3.2
3.1
3.2
3.2
2.6
3.7
2.1
3.7
Monitoring and Assessing Childhood Exposures to
Page
11-50
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-34. Consumers-Only Total Fat Intake— Top 10% of Animal Fat Consumers (g/day)
Age Group8
Birth to <1 year
All
1 to<
2to<
Female
Male
2 years
All
Female
Male
3 years
All
Female
Male
3 to <6 years
All
6to<
11 to
16 to
11 to
21 to
31 to
41 to
Female
Male
11 years
All
Female
Male
<16 years
All
<21 years
All
<21 years
All
Female
Male
<31 years
All
Female
Male
<41 years
All
Female
Male
<51 years
All
Female
Male
N
140
70
70
109
54
55
103
58
45
461
217
244
198
71
127
96
68
165
53
112
150
44
106
148
48
100
166
49
117
Mean
45
45
45
75
68
81
79
77
81
88
84
92
94
88
97
133
167
146
117
160
151
115
166
147
120
160
137
110
148
SE
16
15
17
20
16
22
20
16
24
25
24
25
25
21
27
53
64
60
30
65
55
31
56
51
33
53
42
30
41
Percentiles
10th
28
26
28
52
52
54
55
55
52
62
59
66
66
58
69
85
98
90
81
94
97
80
107
93
79
110
88
72
106
25th
35
35
34
61
57
67
64
65
61
72
68
76
77
70
78
95
122
105
92
117
113
97
128
110
93
125
110
86
119
50th
45
45
44
74
70
78
74
74
73
84
80
90
88
86
91
121
154
139
111
151
139
108
161
135
106
149
136
103
142
75th
54
54
53
85
78
90
85
79
90
102
95
103
105
100
112
154
189
168
140
191
173
131
177
172
132
201
156
130
166
95th
77
69
79
108
89
125
116
109
121
135
130
136
140
123
168
223
278
254
162
276
236
160
254
352
160
352
208
150
218
Max
100
92
100
159
114
159
133
116
133
218
194
218
178
156
178
342
463
463
195
463
445
201
445
376
228
376
267
208
267
Exposure Factors Handbook
September 2011
Page
11-51
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table
11-34. Consumers-Only Total Fat Intake — Top 10% of Animal Fat Consumers (g/day) (continued)
Age Group8
51to<61
61to<71
71 to <81
81+ years
71+ years
years
All
Female
Male
years
All
Female
Male
years
All
All
All
Female
Male
N Mean
183
39
144
168
47
121
104
40
144
50
94
127
96
135
114
91
123
98
97
98
83
105
SE
41
27
41
35
24
35
28
37
30
25
30
Percentiles
10th
80
63
96
74
68
87
65
60
62
54
76
25th
98
74
112
88
74
102
76
67
72
63
88
a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
to Environmental Contaminants.
N
SE
Source:
50th
118
86
122
108
87
117
92
86
91
72
97
75th
144
106
151
133
103
140
109
104
107
95
115
95th
206
126
214
183
120
197
144
137
144
123
165
Max
306
165
306
235
184
235
201
227
227
147
227
Monitoring and Assessing Childhood Exposures
= Sample size.
= Standard error.
U.S. EPA, 2007
Page Exposure Factors Handbook
11-52 September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-35. Consumers-Only
Age Group"
N
Mean
Total Fat Intake— Top 10% of Animal Fat Consumers (g/kg-day)
SE
Percentiles
10th
25th
50th
75th
95th
Max
Birth to <1 year
1 to<
2to<
All
Female
Male
:2 years
All
Female
Male
3 years
All
Female
Male
3 to <6 years
All
6to<
11 to
16 to
llto
21 to
31 to
Female
Male
:ll years
All
Female
Male
<16 years
All
<21 years
All
<21 years
All
Female
Male
<3 1 years
All
Female
Male
<41 years
All
Female
Male
140
70
70
109
54
55
103
58
45
461
217
244
198
71
127
96
68
165
53
112
150
44
106
148
48
100
4.7
4.8
4.6
6.9
6.6
7.1
6.1
6.2
6.1
5.6
5.5
5.7
4.2
4.2
4.2
3.0
2.5
2.8
2.6
2.9
2.2
2.0
2.2
2.1
2.1
2.1
1.7
1.6
1.7
1.5
1.2
1.6
1.3
1.2
1.3
1.3
1.3
1.3
1.1
1.1
1.1
0.85
0.74
0.84
0.65
0.90
0.73
0.54
0.79
0.59
0.62
0.58
2.8
2.7
2.8
5.1
5.1
5.1
4.6
4.6
4.5
4.2
4.2
4.2
3.0
2.9
3.0
2.0
1.7
1.9
1.7
1.9
1.5
1.5
1.6
1.5
1.5
1.5
3.7
3.7
3.6
5.7
5.7
5.8
5.2
5.2
5.2
4.7
4.5
4.8
3.4
3.3
3.4
2.4
2.0
2.1
2.0
2.3
1.7
1.8
1.7
1.7
1.7
1.6
4.6
4.7
4.4
6.8
6.7
6.9
5.8
5.9
5.6
5.3
5.3
5.3
3.8
3.8
3.8
2.8
2.4
2.7
2.3
2.8
2.1
1.9
2.1
1.9
1.9
2.0
6.0
6.0
5.8
7.7
7.4
8.0
6.7
6.8
6.6
6.2
6.0
6.2
4.6
4.8
4.5
3.3
2.9
3.1
2.7
3.1
2.4
2.3
2.4
2.4
2.2
2.6
7.7
7.7
7.5
9.5
9.3
9.4
8.3
7.9
8.4
8.3
7.8
8.4
6.0
5.8
6.3
4.6
3.7
4.4
3.4
4.5
3.2
3.1
3.2
3.9
2.8
3.9
11
9.5
11
12
9.7
12
9.5
9.5
9.5
11
11
11
9.9
7.7
9.9
5.7
6.0
6.0
4.6
6.0
7.3
3.7
7.3
4.7
4.7
4.3
41 to <51 years
All
Female
Male
166
49
117
1.8
1.8
1.9
0.49
0.45
0.50
1.3
1.3
1.4
1.5
1.4
1.6
1.8
1.8
1.8
2.1
2.1
2.0
2.8
2.6
2.8
4.0
2.9
4.0
Exposure Factors Handbook
September 2011
Page
11-53
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-35. Consumers-Only
„
Age CjTOiip 7V JVlCciri
51to<61
61to<71
71to<81
81+ years
71+ years
years
All
Female
Male
years
All
Female
Male
years
All
All
All
Female
Male
183
39
144
168
47
121
104
40
144
50
94
a Age groups are based on U
1.7
1.5
1.7
1.6
1.6
1.6
1.4
1.6
1.4
1.4
1.5
Total Fat Intake— Top 10% of Animal Fat Consumers (g/kg-day)
(continued)
CT7
or!/
0.46
0.34
0.48
0.42
0.42
0.43
0.37
0.48
0.41
0.41
0.41
Percentiles
10th
1.2
1.1
1.2
1.2
1.1
1.2
1.0
1.1
1.0
0.96
1.1
25th
1.3
1.3
1.4
1.3
1.3
1.3
1.1
1.2
1.1
1.1
1.2
S. EPA (2005) Guidance on Selecting Age Groups for
50th
1.6
1.4
1.6
1.5
1.5
1.5
1.3
1.4
1.3
1.4
1.3
75th
1.9
1.7
1.9
1.8
1.7
1.8
1.5
1.7
1.6
1.6
1.5
95th
2.5
2.0
2.6
2.5
2.3
2.5
2.0
2.0
2.0
1.8
2.1
Max
3
2
3
3
3
3
3
3
3
3
3
8
4
8
2
2
1
2
7
7
2
7
Monitoring and Assessing Childhood Exposures
to Environmental Contaminants.
N
SE
Source:
= Sample size
= Standard error.
U.S. EPA, 2007
Page Exposure Factors Handbook
11-54 September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-36. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day)
Age
N Mean
SD
10th
25th
Percentiles
50th
75th
90th
Minimum
Maximum
Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
37.1
59.1
86.7
91.6
98.6
93.2
107.0
97.7
107.8
17.5
26.0
41.3
38.8
56.1
50.8
53.9
48.7
64.3
18.7
29.1
39.9
50.2
46.0
45.7
53.0
46.1
41.4
25.6
40.4
55.5
63.6
66.8
60.5
69.8
65.2
59.7
33.9
56.1
79.2
82.6
87.0
81.4
90.8
85.8
97.3
46.3
71.4
110.5
114.6
114.6
111.3
130.7
124.0
140.2
60.8
94.4
141.1
153.0
163.3
154.5
184.1
165.2
195.1
3.4
21.6
26.5
32.6
29.3
14.6
9.8
10.0
8.5
107.6
152.7
236.4
232.5
584.6
529.5
282.2
251.3
327.4
Total Animal Fat
6 months
lyear
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
18.4
36.5
49.5
50.1
50.8
54.1
56.2
53.8
64.4
16.0
20.0
28.3
29.4
31.7
39.6
39.8
35.1
48.5
0.7
15.2
20.1
21.3
21.4
20.3
19.8
15.9
15.2
4.2
23.1
28.9
29.1
28.1
30.6
28.5
28.3
30.7
13.9
33.0
42.1
42.9
42.6
45.0
44.8
44.7
51.6
28.4
45.9
66.0
64.4
66.4
64.6
72.8
67.9
86.6
42.5
65.3
81.4
88.9
92.6
97.5
109.4
105.8
128.8
0.0
0.0
10.0
14.1
5.9
0.0
4.7
0.6
2.6
61.1
127.1
153.4
182.6
242.2
412.3
209.6
182.1
230.3
Total Vegetable Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
9.2
15.4
19.3
21.1
24.5
23.7
34.3
27.3
25.7
12.8
14.3
16.3
15.5
18.6
21.6
27.4
22.8
21.3
0.6
3.7
3.8
3.9
5.7
4.3
8.4
5.1
4.2
1.2
6.1
7.9
8.6
10.4
9.5
17.9
11.9
11.7
2.8
11.3
14.8
18.7
21.8
18.3
31.2
22.6
20.8
11.6
18.1
26.6
26.6
33.3
30.6
44.6
38.1
32.9
29.4
38.0
42.9
45.2
48.5
49.0
57.5
54.4
47.6
0.0
0.2
0.7
1.0
0.9
0.6
0.0
0.7
0.0
53.2
70.2
96.6
70.4
109.0
203.7
238.3
132.2
141.5
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
N
SD
125
99
135
106
219
871
148
108
159
0.05
0.05
0.04
0.1
2.3
0.3
0.3
0.4
0.5
0.1
0.2
0.2
0.6
31.1
1.5
2.2
1.5
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
1.9
1.9
4.5
459.2
19.2
25.4
9.5
15.3
Sample size.
Standard deviation.
Source: Frank et al., 1986.
Exposure Factors Handbook
September 2011
Page
11-55
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-37. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
Age
N
Mean
SD
Percentiles
10th
25th 50th
75th
90th
1973-1982 (g/kg-day)
Minimum
Maximum
Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
1 3 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
4.9
6.1
7.0
6.4
6.1
2.7
2.3
1.7
1.8
2.3
2.8
3.3
2.7
3.7
1.5
1.3
0.8
1.0
2.4
3.0
3.4
3.6
2.9
1.2
1.0
0.8
0.7
3.3
4.1
4.5
4.6
4.0
1.7
1.5
1.2
0.9
4.7
5.7
6.2
5.5
5.2
2.4
2.0
1.5
1.6
6.2
7.5
8.6
8.2
7.0
3.3
2.8
2.1
2.2
8.0
9.5
11.9
9.9
10.0
4.5
3.8
3.1
3.1
0.4
2.3
2.1
2.2
2.0
0.3
0.2
0.2
0.2
13.2
16.4
18.7
16.7
38.2
13.9
10.2
4.7
6.2
Total Animal Fat
6 months
1 year
2 years
3 years
4 years
10 years
1 3 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
2.4
3.8
4.0
3.5
3.1
16
1.2
1.0
1.0
2.1
2.1
2.3
2.0
2.1
1.2
0.9
0.6
0.8
0.08
1.7
1.7
1.6
1.3
0.6
0.4
0.3
0.3
0.6
2.4
2.3
2.1
1.7
0.8
0.6
0.5
0.5
2.0
3.4
3.4
3.1
2.6
1.3
0.9
0.8
0.8
3.7
4.9
5.2
4.2
4.0
1.9
1.6
1.3
1.4
5.5
6.5
6.7
6.1
5.4
2.8
2.3
1.9
2.0
0.0
0.0
0.7
0.9
0.4
0.00
0.08
0.01
0.05
9.0
13.6
13.4
13.1
15.4
10.8
5.2
3.1
4.2
Total Vegetable Fat Intake
6 months
lyear
2 years
3 years
4 years
10 years
1 3 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
1.2
1.6
1.6
1.5
1.5
0.7
0.8
0.5
0.4
1.8
1.6
1.4
1.1
1.2
0.6
0.8
0.4
0.4
0.08
0.4
0.3
0.3
0.4
0.1
0.2
0.09
0.07
0.2
0.6
0.7
0.6
0.6
0.3
0.4
0.2
0.2
0.4
1.2
1.1
1.4
1.2
0.5
0.6
0.4
0.4
1.6
1.9
2.0
2.0
2.1
0.9
0.9
0.7
0.6
4.1
3.8
3.5
3.0
2.8
1.4
1.3
0.9
0.9
0.0
0.02
0.06
0.08
0.06
0.02
0.0
0.01
0.0
8.2
7.6
8.5
5.1
7.3
4.2
8.6
2.2
2.1
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
1 3 years
1 5 years
17 years
N
SD
125
99
132
106
218
861
147
105
149
0.01
0.01
0.003
0.01
0.2
0.01
0.01
0.01
0.01
0.02
0.03
0.02
0.04
2.0
0.05
0.04
0.03
0.03
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.02
0.0
0.0
0.0
0.0
0.0
0.0
0.04
0.008
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.2
0.3
30.0
0.6
0.4
0.2
0.2
Sample size.
Standard deviation.
Source: Frank et al., 1986.
Page
11-56
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-38. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products"
Product
Moisture
Content
Total Fat
Content
Comment
Meat
Beef (composite of trimmed retail cuts; all grades)
Pork (composite of trimmed retail cuts)
Cured ham
Cured bacon
Lamb (composite of trimmed retail cuts)
Veal (composite of trimmed retail cuts)
Rabbit (domesticated)
Chicken (broilers or fryers)
Duck (domesticated)
Turkey (all classes)
70.62
59.25
60.44
51.43
72.34
60.31
65.11
54.55
63.46
55.93
40.20
12.52
12.32
12.12
16.49
73.42
61.96
60.70
53.72
75.91
60.16
72.84
57.08
72.82
60.61
58.82
75.46
66.81
63.79
57.53
65.99
63.93
59.45
52.41
73.77
64.22
48.50
51.84
74.16
64.88
70.40
61.70
71.97
59.42
6.16
9.91
19.24
21.54
5.88
9.66
14.95
17.18
12.90
8.32
45.04
43.27
41.78
40.30
37.27
5.25
9.52
21.59
20.94
2.87
6.58
6.77
11.39
5.55
8.05
8.41
3.08
6.71
7.41
9.12
15.06
12.56
13.60
14.92
5.95
11.20
39.34
28.35
2.86
4.97
8.02
9.73
8.26
13.15
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in fat trim
Cooked; lean and fat, 1/4 in fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat
Cooked; lean and fat
Center slice, unheated; lean and fat
Raw, center slice, country style; lean only
Raw
Cooked, baked
Cooked, broiled
Cooked, pan-fried
Cooked, microwaved
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in fat trim
Cooked; lean and fat, 1/4 in fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in fat trim
Cooked; lean and fat, 1/4 in fat trim
Raw
Cooked, roasted
Cooked, stewed
Raw; meat only
Cooked, stewed; meat only
Cooked, roasted; meat only
Cooked, fried; meat only
Raw; meat and skin
Cooked, stewed; meat and skin
Cooked, roasted; meat and skin
Cooked, fried, flour; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; ground
Cooked; ground
Exposure Factors Handbook
September 2011
Page
11-57
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Exposure Factors Handbook
Chapter 11—Intake of Meats, Dairy Products, and Fats
Table 11-38. Mean Percent Moisture
Product
and Total Fat
Moisture
Content
Content of Selected Meat and Dairy Products" (continued)
Total Fat
Content
Comment
Dairy
Milk
Cream
Butter
Cheese
Yogurt
Egg
a
Whole
Human
Lowfat (1%)
Reduced fat (2%)
Skim or fat free
Half and half
Light (coffee cream or table cream)
Heavy-whipping
Sour
Sour, reduced fat
American
Cheddar
Swiss
Cream
Parmesan
Cottage, lowfat
Colby
Blue
Provolone
Mozzarella
Based on the water and lipid content
88.32
87.50
89.81
88.86
90.38
80.57
73.75
57.71
70.95
80.14
15.87
39.16
36.75
37.12
53.75
29. 16; 20.84
82.48; 79.31
38.20
42.41
40.95
50.01; 53.78
85.07; 87.90
75.84
3.25
4.38
0.97
1.92
0.25
11.50
19.31
37.00
20.96
12.00
81.11
31.25
33.14
27.80
34.87
25.83; 28.61
1.02; 1.93
32.11
28.74
26.62
22.35; 15.92
1.55; 3.25
9.94
3.25%milkfat
Whole, mature, fluid
Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A
Fluid
Fluid
Fluid
Cultured
Cultured
Salted
Pasteurized
Hard; grated
l%fat; 2% fat
Whole milk; Skim milk
Plain, lowfat; Plain, with fat
Chicken, whole raw, fresh
in 100 grams, edible portion. Total Fat Content = saturated, monosaturated,
and
polyunsaturated. For additional information, consult the USDA nutrient database.
Source:
USDA, 2007.
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TABLE OF CONTENTS
LIST OF TABLES 12-ii
12. INTAKE OF GRAIN PRODUCTS 12-1
12.1. INTRODUCTION 12-1
12.2. RECOMMENDATIONS 12-1
12.3. INTAKE STUDIES 12-4
12.3.1. Key Grain Intake Study 12-4
12.3.1.1. U.S. EPA Analysis of Consumption Data from 2003-2006 National
Health and Nutrition Examination Survey (NHANES) 12-4
12.3.2. Relevant Grain Intake Studies 12-5
12.3.2.1. USDA(1980, 1992, 1996a, b) 12-5
12.3.2.2. USDA(1999a) 12-6
12.3.2.3. USDA(1999b) 12-6
12.3.2.4. U.S. EPA Analysis of Continuing Survey of Food Intake by
Individuals (CSFII) 1994-1996, 1998 12-7
12.3.2.5. Smiciklas-Wright et al. (2002) 12-8
12.3.2.6. Vitolins et al. (2002) 12-8
12.3.2.7. Fox et al. (2004) 12-9
12.3.2.8. Ponza et al. (2004) 12-9
12.3.2.9. Fox et al. (2006) 12-10
12.3.2.10. Mennella et al. (2006) 12-10
12.4. CONVERSION BETWEEN WET-AND DRY-WEIGHT INTAKE RATES 12-10
12.5. REFERENCES FOR CHAPTER 12 12-11
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LIST OF TABLES
Table 12-1. Recommended Values for Intake of Grains, Edible Portion, Uncooked 12-2
Table 12-2. Confidence in Recommendations for Intake of Grain Products 12-3
Table 12-3. Per Capita Intake of Total Grains Based 2003-2006 NHANES (g/kg-day, edible portion,
uncooked weight) 12-13
Table 12-4. Consumer-Only Intake of Total Grains Based 2003-2006 NHANES (g/kg-day, edible
portion, uncooked weight) 12-14
Table 12-5. Per Capita Intake of Individual Grain Products Based 2003-2006 NHANES (g/kg-day,
edible portion, uncooked weight) 12-15
Table 12-6. Consumer-Only Intake of Individual Grain Products Based 2003-2006 NHANES
(g/kg-day, edible portion, uncooked weight) 12-16
Table 12-7. Mean Grain Intake per Individual in a Day by Sex and Age (g/day as-consumed) for
1977-1978 12-17
Table 12-8. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed) for
1987-1988 12-18
Table 12-9. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed) for
1994-1995 12-18
Table 12-10. Per Capita Consumption of Flour and Cereal Products in 1997 12-19
Table 12-11. Mean Quantities of Grain Products Consumed by Children Under 20 Years of Age, by
Sex and Age, Per Capita (g/day, as-consumed) 12-20
Table 12-12. Percentage of Individuals Under 20 Years of Age Consuming Grain Products, by Sex and
Age(%) 12-21
Table 12-13. Per Capita Intake of Total Grains Based on 1994-1996, 1998 CSFII (g/kg-day, edible
portion, uncooked weight) 12-22
Table 12-14. Consumer-Only Intake of Total Grains Based on 1994-1996, 1998 CSFII (g/kg-day,
edible portion, uncooked weight) 12-23
Table 12-15. Per Capita Intake of Individual Grain Products Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 12-24
Table 12-16. Consumer-Only Intake of Individual Grain Products Based on 1994-1996, 1998 CSFII
(g/kg-day, edible portion, uncooked weight) 12-25
Table 12-17. Per Capita Intake of Breads Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-26
Table 12-18. Per Capita Intake of Sweets Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-27
Table 12-19. Per Capita Intake of Snacks Containing Grains Based on 1994-1996, 1998 CSFII
(g/kg-day, as-consumed) 12-28
Table 12-20. Per Capita Intake of Breakfast Foods Based on 1994-1996, 1998 CSFII (g/kg-day,
as-consumed) 12-29
Table 12-21. Per Capita Intake of Pasta Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed) 12-30
Table 12-22. Per Capita Intake of Cooked Cereals Based on 1994-1996, 1998 CSFII (g/kg-day,
as-consumed) 12-31
Table 12-23. Per Capita Intake of Ready-to-Eat Cereals Based on 1994-1996, 1998 CSFII (g/kg-day,
as-consumed) 12-32
Table 12-24. Per Capita Intake of Baby Cereals Based on 1994-1996, 1998 CSFII (g/kg-day,
as-consumed) 12-33
Table 12-25. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and the
Percentage of Individuals Using These Foods in 2 Days 12-34
Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and
Percentage of Individuals Using These Foods in 2 Days, by Sex and Age 12-35
Table 12-27. Consumption of Major Food Groups by Older Adults: Median Daily Servings (and
Ranges) by Demographic and Health Characteristics 12-37
Table 12-28. Characteristics of the Feeding Infant and Toddlers Study (FITS) Sample Population 12-38
Table 12-29. Percentage of Infants and Toddlers Consuming Different Types of Grain Products 12-39
Table 12-30. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants
(percentages) 12-40
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LIST OF TABLES (continued)
Table 12-31. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
Participation Status 12-41
Table 12-32. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study 12-42
Table 12-33. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study 12-42
Table 12-34. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Grain Products on a Given Day 12-43
Table 12-35. Mean Moisture Content of Selected Grain Products Expressed as Percentages of Edible
Portions (grams per 100 grams of edible portion) 12-44
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12. INTAKE OF GRAIN PRODUCTS
12.1. INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, grain products may become
contaminated with toxic chemicals by several
different pathways. Ambient air pollutants may be
deposited on or absorbed by the plants, or dissolved
in rainfall or irrigation waters that contact the plants.
Pollutants may also be absorbed through plant roots
from contaminated soil and ground water. The
addition of pesticides, soil additives, and fertilizers
may also result in contamination of grain products.
To assess exposure through this pathway, information
on ingestion rates of grain products is needed.
A variety of terms may be used to define intake of
grain products (e.g., consumer-only intake, per capita
intake, total grain intake, as-consumed intake,
uncooked edible intake, dry-weight intake). As
described in Chapter 9 (Intake of Fruits and
Vegetables), consumer-only intake is defined as the
quantity of grain products consumed by individuals
during the survey period. These data are generated by
averaging intake across only the individuals in the
survey who consumed these food items. Per capita
intake rates are generated by averaging
consumer-only intakes over the entire population
(including those that reported no intake). In general,
per capita intake rates are appropriate for use in
exposure assessments for which average dose
estimates for individuals are of interest because they
represent both individuals who ate the foods during
the survey period and those who may eat the food
items at some time but did not consume them during
the survey period. Per capita intake, therefore,
represents an average across the entire population of
interest, but does so at the expense of
underestimating consumption for the subset of the
population that consumed the food in question. Total
grain intake refers to the sum of all grain products
consumed in a day.
Intake rates may be expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the
as-consumed weight. Some of the food ingestion
values provided in this chapter are expressed as
as-consumed intake rates because this is the fashion
in which data were reported by survey respondents.
Others are provided as uncooked weights based on
analyses of survey data that account for weight
changes that occur during cooking. This is of
importance because concentration data to be used in
the dose equation are often measured in uncooked
food samples. It should be recognized that cooking
can either increase or decrease food weight.
Similarly, cooking can increase the mass of
contaminant in food (due to formation reactions, or
absorption from cooking oils or water) or decrease
the mass of contaminant in food (due to vaporization,
fat loss, or leaching). The combined effects of
changes in weight and changes in contaminant mass
can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. It is important
for the assessor to be aware of these issues and
choose intake rate data that best match the
concentration data that are being used. For more
information on cooking losses and conversions
necessary to account for such losses, refer to
Chapter 13 of this handbook.
Sometimes contaminant concentrations in food
are reported on a dry-weight basis. When these data
are used in an exposure assessment, it is
recommended that dry-weight intake rates also be
used. Dry-weight food concentrations and intake
rates are based on the weight of the food consumed
after the moisture content has been removed. For
information on converting the intake rates presented
in this chapter to dry-weight intake rates, refer to
Section 12.4.
The purpose of this chapter is to provide intake
data for grain products for the general population.
The recommendations for ingestion rates of grain
products are provided in the next section, along with
a summary of the confidence ratings for these
recommendations. The recommended values are
based on the key study identified by
U.S. Environmental Protection Agency (EPA) for this
factor. Following the recommendations, the key study
on ingestion of grain products is summarized.
Relevant data on ingestion of grain products are also
provided. These data are presented to provide the
reader with added perspective on the current state-of-
knowledge pertaining to ingestion of grain products
among children.
12.2. RECOMMENDATIONS
Table 12-1 presents a summary of the
recommended values for per capita and
consumer-only intake of grain products. Table 12-2
provides confidence ratings for the grain intake
recommendations for the general population.
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The U.S. EPA analysis of data from the
2003-2006 National Health and Nutrition
Examination Survey (NHANES) was used in
selecting recommended intake rates. The U.S. EPA
analysis was conducted using childhood age groups
that differed slightly from U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005). However, for the
purposes of the recommendations presented here,
data were placed in the standardized age categories
closest to those used in the analysis.
The NHANES data on which the
recommendations are based are short-term survey
data and may not necessarily reflect the long-term
distribution of average daily intake rates. However,
because broad categories of food (i.e., total grains),
are eaten on a daily basis throughout the year with
minimal seasonality, the short-term distribution may
be a reasonable approximation of the long-term
distribution, although it will display somewhat
increased variability. This implies that the upper
percentiles shown here will tend to overestimate the
corresponding percentiles of the true long-term
distribution. In general, the recommended values
based on U.S. EPA's analysis of NHANES data
represent the uncooked weight of the edible portion
of grain products.
Table 12-1. Recommended Values for Intake of Grains, Edible Portion, Uncooked"
Age Group
(years)
Per Capita
Consumers Only
Mean
95th Percentile
Mean
95m
Percentile
Multiple
Percentiles
Source
g/kg-day
g/kg-day
g/kg-day
g/kg-day
Total Grains
Birth to 1
lto<2
2to<3
3to<6
6to50
3.1
6.4
6.4
6.2
4.4
2.4
2.4
2.2
1.7
9.5b
12.4b
12.4b
11.1
8.2
5.0
5.0
4.6
3.5
4.1
6.4
6.4
6.2
4.4
2.4
2.4
2.2
1.7
10.3b
12.4b
12.4b
11.1
8.2
5.0
5.0
4.6
3.5
See Tables
12-3 and
12-4
U.S. EPA
Analysis of
NHANES
2003-2006
Individual Grain Products—See Tables 12-5 and 12-6
Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on
Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). Data were placed in the standardized age categories closest to those used in the analysis.
Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and
Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group
Recommendations (NCHS, 1993).
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Table 12-2. Confidence in Recommendations for Intake of Grain Products
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
The survey methodology and data analysis were
adequate. The survey sampled more than 16,000
individuals. An analysis of primary data was conducted.
No physical measurements were taken. The method
relied on recent recall of grain products eaten.
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key study was directly relevant to grain intake.
The data were demographically representative of the
U.S. population (based on stratified random sample).
Data were collected between 2003 and 2006.
Data were collected for two non-consecutive days.
High
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The NHANES data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
NHANES follows strict QA/QC procedures. The
U.S. EPA analysis has only been reviewed internally, but
the methodology has been used in an analysis of
previous data.
High
Variability and Uncertainty
Variability in Population
Minimal Uncertainty
Full distributions were provided for total grains. Means
were provided for individual grain products.
Data collection was based on recall for a two-day period;
the accuracy of using these data to estimate long-term
intake (especially at the upper percentiles) is uncertain.
However, use of short-term data to estimate chronic
ingestion can be assumed for broad categories of foods
such as total grains. Uncertainty is greater for individual
grain products.
Medium to high for
averages, low for long-
term upper percentiles;
low for individual foods
Evaluation and Review
Peer Review
Medium
Number and Agreement of Studies
The NCHS NHANES survey received a high level of
peer review. The U.S. EPA analysis of these data has not
been peer reviewed outside the Agency, but the
methodology has been used in an analysis of previous
data.
There was one key study.
Overall Rating
Medium to High
confidence in the
averages;
Low confidence in the
long-term upper
percentiles
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12.3. INTAKE STUDIES
12.3.1. Key Grain Intake Study
12.3.1.1. U.S. EPA Analysis of Consumption Data
from 2003-2006 National Health and
Nutrition Examination Survey
(NHANES)
The key source of recent information on
consumption rates of grain products is the U.S.
Centers for Disease Control and Prevention's
National Center for Health Statistics' (NCHS)
NHANES. Data from NHANES 2003-2006 have
been used by the U.S. EPA, Office of Pesticide
Programs (OPP) to generate per capita and
consumer-only intake rates for both individual grain
products and total grain products.
NHANES is designed to assess the health and
nutritional status of adults and children in the United
States. In 1999, the survey became a continuous
program that interviews a nationally representative
sample of approximately 7,000 persons each year and
examines a nationally representative sample of about
5,000 persons each year, located in counties across
the country, 15 of which are visited each year. Data
are released on a 2-year basis; thus, for example, the
2003 data are combined with the 2004 data to
produce NHANES 2003-2004.
The dietary interview component of NHANES is
called What We Eat in America and is conducted by
the U.S. Department of Agriculture (USDA) and the
U.S. Department of Health and Human Services
(DHHS). DHHS' NCHS is responsible for the sample
design and data collection, and USDA's Food
Surveys Research Group is responsible for the dietary
data collection methodology, maintenance of the
databases used to code and process the data, and data
review and processing. Beginning in 2003,
2 non-consecutive days of 24-hour intake data were
collected. The first day was collected in-person, and
the second day was collected by telephone, 3 to
10 days later. These data were collected using
USDA's dietary data collection instrument, the
Automated Multiple Pass Method. This method
provides an efficient and accurate means of collecting
intakes for large-scale national surveys. It is fully
computerized and uses a five-step interview. Details
can be found at USDA's Agriculture Research
Service (http://www.ars.usda.gov/ba/bhnrc/fsrg).
For NHANES 2003-2004, there were
12,761 persons selected; of these, 9,643 were
considered respondents to the mobile examination
center (MEC) examination and data collection.
However, only 9,034 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,354 provided complete dietary intakes for Day 2.
For NHANES 2005-2006, there were 12,862 persons
selected; of these, 9,950 were considered respondents
to the MEC examination and data collection.
However, only 9,349 of the MEC respondents
provided complete dietary intakes for Day 1.
Furthermore, of those providing the Day 1 data, only
8,429 provided complete dietary intakes for Day 2.
The 2003-2006 NHANES surveys are stratified,
multistage probability samples of the civilian
non-institutionalized U.S. population. The sampling
frame was organized using 2000 U.S. population
census estimates. NHANES oversamples low income
persons, adolescents 12 to 19 years, persons 60 years
and older, African Americans, and Mexican
Americans. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all 4 years of the
surveys can be combined. Additional information on
NHANES can be obtained at
http://www.cdc.gov/nchs/nhanes.htm.
In 2010, U.S. EPA, OPP used NHANES
2003-2006 data to update the Food Commodity
Intake Database (FCID) that was developed in earlier
analyses of data from the USDA's Continuing Survey
of Food Intake by Individuals (CSFII) (USDA, 2000;
U.S. EPA, 2000) (see Section 12.3.2.4), NHANES
data on the foods people reported eating were
converted to the quantities of agricultural
commodities eaten. "Agricultural commodity" is a
term used by U.S. EPA to mean plant (or animal)
parts consumed by humans as food; when such items
are raw or unprocessed, they are referred to as "raw
agricultural commodities." For example, an apple pie
may contain the commodities apples, flour, fat, sugar,
and spices. FCID contains approximately 558 unique
commodity names and 8-digit codes. The FCID
commodity names and codes were selected and
defined by U.S. EPA and were based on the U.S. EPA
Food Commodity Vocabulary
(http ://www. epa. gov/pesticides/foodfeed/).
Intake rates were generated for a variety of food
items/groups based on the agricultural commodities
included in the FCID. These intake rates represent
intake of all forms of the product (e.g., both home
produced and commercially produced) for individuals
who provided data for two days of the survey. Note
that if the person reported consuming food for only
one day, their two-day average would be half the
amount reported for the one day of consumption.
Individuals who did not provide information on body
weight or for whom identifying information was
unavailable were excluded from the analysis.
Two-day average intake rates were calculated for all
individuals in the database for each of the food
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items/groups. These average daily intake rates were
divided by each individual's reported body weight to
generate intake rates in units of grams per kilogram
of body weight per day (g/kg-day). The data were
weighted according to the 4-year, 2-day sample
weights provided in NHANES 2003-2006 to adjust
the data for the sample population to reflect the
national population.
Summary statistics were generated on a
consumer-only and on a per capita basis. Summary
statistics, including number of observations,
percentage of the population consuming the grains
being analyzed, mean intake rate, and standard error
of the mean intake rate were calculated for total
grains and selected individual grains. Percentiles of
the intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th,
75th, 90th, 95th, 99th, and the maximum value) were
also provided for total grains. Data were provided for
the following age groups: birth to 1 year, 1 to 2 years,
3 to 5 years, 6 to 12 years, 13 to 19 years, 20 to
49 years, and >50 years. Data on females 13 to 49
years were also provided. Because these data were
developed for use in U.S. EPA's pesticide registration
program, the childhood age groups used are slightly
different than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Table 12-3 presents per capita intake data for total
grains in g/kg-day; Table 12-4 provides
consumer-only intake data for total grains in
g/kg-day. Table 12-5 provides per capita intake data
for individual grains in g/kg-day, and Table 12-6
provides consumer-only intake data for individual
grains in g/kg-day. In general, these data represent
intake of the edible portions of i.e., uncooked foods.
The results are presented in units of g/kg-day.
Thus, use of these data in calculating potential dose
does not require the body-weight factor to be
included in the denominator of the average daily dose
(ADD) equation. It should be noted that converting
these intake rates into units of g/day by multiplying
by a single average body weight is inappropriate,
because individual intake rates were indexed to the
reported body weights of the survey respondents.
Also, it should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) does not necessarily reflect the
long-term distribution of average daily intake rates.
The distributions generated from short-term and
long-term data will differ to the extent that each
individual's intake varies from day to day; the
distributions will be similar to the extent that
individuals' intakes are constant from day to day.
Day-to-day variation in intake among individuals will
be high for grains that are not typically eaten every
day. For these grains, the intake distribution
generated from short-term data will not be a good
reflection of the long-term distribution. On the other
hand, for broad categories of foods (e.g., total grains)
that are eaten on a daily basis throughout the year, the
short-term distribution may be a reasonable
approximation of the true long-term distribution,
although it will show somewhat more variability. In
this chapter, distributions are provided for broad
categories of grains (e.g., total grains). Because of the
increased variability of the short-term distribution,
the short-term upper percentiles shown here may
overestimate the corresponding percentiles of the
long-term distribution. For individual foods, only the
mean, standard error, and percent consuming are
provided. An advantage of using the U.S. EPA's
analysis of NHANES data is that it provides
distributions of intake rates for various age groups of
children and adults, normalized by body weight. The
data set was designed to be representative of the U.S.
population and includes 4 years of intake data
combined. Another advantage is the currency of the
data; the NHANES data are from 2003-2006.
However, short-term dietary data may not accurately
reflect long-term eating patterns and may
under-represent infrequent consumers of a given
food. This is particularly true for the tails (extremes)
of the distribution of food intake. Because these are
2-day averages, consumption estimates at the upper
end of the intake distribution may be underestimated
if these consumption values are used to assess acute
(i.e., short-term) exposures. Also, the analysis was
conducted using slightly different childhood age
groups than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, given the similarities in the age groups
used, the data should provide suitable intake
estimates for the age groups of interest.
12.3.2. Relevant Grain Intake Studies
12.3.2.1. USDA (1980,1992,1996a, b)—Food and
Nutrient Intakes of Individuals in 1 Day
in the United States
USDA calculated mean per capita intake rates for
total and individual grain products using Nationwide
Food Consumption Survey (NFCS) data from
1977-1978 and 1987-1988 (USDA, 1980, 1992) and
CSFII data from 1994 and 1995 (USDA, 1996a, b).
The mean per capita intake rates for grain products
are presented in Tables 12-7 and 12-8 for the
two NFCS survey years, respectively. Table 12-9
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presents similar data from the 1994 and 1995 CSFII
for grain products.
The advantages of using these data are that they
provide mean intake estimates for various grain
products. The consumption estimates are based on
short-term (i.e., 1-day) dietary data, which may not
reflect long-term consumption. These data are based
on older surveys and may not be entirely
representative of current eating patterns.
12.3.2.2. USDA (1999a)—Food Consumption,
Prices, and Expenditures, 1970-1997
The USDA's Economic Research Service
calculates the amount of food available for human
consumption in the United States annually. Supply
and utilization balance sheets are generated. These
are based on the flow of food items from production
to end uses. Total available supply is estimated as the
sum of production (i.e., some products are measured
at the farm level or during processing), starting
inventories, and imports (USDA, 1999a). The
availability of food for human use commonly termed
as "food disappearance" is determined by subtracting
exported foods, products used in industries, farm
inputs (seed and feed), and end-of-the-year
inventories from the total available supply (USDA,
1999a). USDA (1999a) calculates the per capita food
consumption by dividing the total food disappearance
by the total U.S. population.
USDA (1999a) estimated per capita consumption
data for grain products from 1970-1997. In this
section, the 1997 values, which are the most recent
final data, are presented. Table 12-10 presents per
capita consumption in 1997 for grains.
An advantage of this study is that it provides per
capita consumption rates for grains that are
representative of long-term intake because
disappearance data are generated annually. Daily per
capita intake rates are generated by dividing annual
consumption by 365 days/year. One of the limitations
of this study is that disappearance data do not account
for losses from the food supply from waste, spoilage,
or foods fed to pets. Thus, intake rates based on these
data may overestimate daily consumption because
they are based on the total quantity of marketable
commodity utilized. Therefore, these data may be
useful for estimating bounding exposure estimates. It
should also be noted that per capita estimates based
on food disappearance are not a direct measure of
actual consumption or quantity ingested, instead the
data are used as indicators of changes in usage over
time (USDA, 1999a). These data are based on older
surveys and may not be entirely representative of
current consumption patterns.
12.3.2.3. USDA (1999b)—Food and Nutrient
Intakes by Children 1994-1996,1998,
Table Set 17
USDA (1999b) calculated national probability
estimates of food and nutrient intake by children
based on 4 years of the CSFII (1994-1996 and 1998)
for children age 9 years and under, and on CSFII
1994-1996 only for individuals age 10 years and
over. The CSFII was a series of surveys designed to
measure the kinds and amounts of foods eaten by
Americans. Intake data, based on 24-hour dietary
recall, were collected through in-person interviews on
2 non-consecutive days. Section 12.3.2.4 provides
additional information on these surveys.
USDA used sample weights to adjust for
non-response, to match the sample to the U.S.
population in terms of demographic characteristics,
and to equalize intakes over the four quarters of the
year and the 7 days of the week. A total of
503 breast-fed children were excluded from the
estimates, but both consumers and non-consumers
were included in the analysis.
USDA (1999b) provided data on the mean per
capita quantities (grams) of various food
products/groups consumed per individual for 1 day,
and the percent of individuals consuming those foods
in 1 day of the survey. Tables 12-11 and 12-12
present data on the mean quantities (grams) of grain
products consumed per individual for 1 day, and the
percentage of survey individuals consuming grain
products that survey day. Data on mean intakes or
mean percentages are based on respondents' Day-1
intakes.
The advantage of the USDA (1999b) study is that
it uses the 1994-1996, 1998 CSFII data set, which
includes 4 years of intake data, combined, and
includes the supplemental data on children. These
data are expected to be generally representative of the
U.S. population, and they include data on a wide
variety of grain products. The data set is one of a
series of USDA data sets that are publicly available.
One limitation of this data set is that it is based on
1-day, and short-term dietary data may not accurately
reflect long-term eating patterns. Other limitations of
this study are that it only provides mean values of
food intake rates, consumption is not normalized by
body weight, and presentation of results is not
consistent with U.S. EPA's recommended age groups.
These data are based on older surveys and may not be
entirely representative of current eating patterns.
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12.3.2.4. U.S. EPA Analysis of Continuing Survey
of Food Intake by Individuals (CSFII)
1994-1996,1998
U.S. EPA/OPP, in cooperation with USDA's
Agricultural Research Service, used data from the
1994-1996, 1998 CSFII to develop the FCID
(U.S. EPA, 2000; USDA, 2000), as described in
Section 12.3.1.1. The CSFII 1994-1996 was
conducted between January 1994 and January 1997
with a target population of non-institutionalized
individuals in all 50 states and Washington, DC. In
each of the three survey years, data were collected for
a nationally representative sample of individuals of
all ages. The CSFII 1998 was conducted between
December 1997 and December 1998 and surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-1996 and was
intended to be merged with CSFII 1994-1996 to
increase the sample size for children. The merged
surveys are designated as CSFII 1994-1996, 1998
(USDA, 2000). Additional information on the CSFII
can be obtained at http://www.ars.usda.gov/
Services/docs.htm?docid= 14531.
The CSFII 1994-1996, 1998 collected dietary
intake data through in-person interviews on
two non-consecutive days. The data were based on
24-hour recall. A total of 21,662 individuals provided
data for the first day; of those individuals, 20,607
provided data for a second day. The 2-day response
rate for the 1994-1996 CSFII was approximately
76%. The 2-day response rate for CSFII 1998 was
82%. The CSFII 1994-1996, 1998 surveys were
based on a complex multistage area probability
sample design. The sampling frame was organized
using 1990 U.S. population census estimates, and the
stratification plan took into account geographic
location, degree of urbanization, and socioeconomic
characteristics. Several sets of sampling weights are
available for use with the intake data. By using
appropriate weights, data for all 4 years of the
surveys can be combined. USDA recommends that
all four years be combined in order to provide an
adequate sample size for children.
The grain items/groups selected for the U.S. EPA
analysis included total grains, and individual grain
products such as cereal and rice. U.S. EPA
(2003) presents the food codes and definitions used
to determine the various grain products used in the
analysis. CSFII data on the foods people reported
eating were converted to the quantities of agricultural
commodities eaten. Intake rates for these food
items/groups and summary statistics were generated
on both a per capita and a consumer-only basis using
the same general methodology as in the U.S. EPA
analysis of 2003-2006 NHANES data, as described
in Section 12.3.1.1. Because these data were
developed for use in U.S. EPA's pesticide registration
program, the childhood age groups used are slightly
different than those recommended in U.S. EPA's
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Table 12-13 presents per capita intake data for
total grains in g/kg-day; Table 12-14 provides
consumer-only intake data for total grains in
g/kg-day. Table 12-15 provides per capita intake data
for individual grain products, and Table 12-16
provides consumer-only intake data for individual
grain products. In general, these data represent intake
of the edible portions of unprepared (i.e., uncooked)
foods. Tables 12-17 through 12-24 present per capita
intake data for individual grain products. The data
come from CSFII 1994-1996 only. The results are
presented in units of g/kg-day. These data represent
as-consumed intake rates.
The results are presented in units of g/kg-day.
Thus, use of these data in calculating potential dose
does not require the body-weight factor to be
included in the denominator of the ADD equation.
The cautions concerning converting these intake rates
into units of g/day by multiplying by a single average
body weight and the discussion of the use of short
term data in the NHANES description in
Section 12.3.1.1, apply to the CSFII estimates as
well.
A strength of U.S. EPA's analysis is that it
provides distributions of intake rates for various age
groups of individuals, normalized by body weight.
The analysis uses the 1994-1996, 1998 CSFII data
set, which was designed to be representative of the
U.S. population. Also, the data set includes 4 years of
intake data combined and is based on a 2-day survey
period. However, as discussed above, short-term
dietary data may not accurately reflect long-term
eating patterns and may under-represent infrequent
consumers of a given food. This is particularly true
for the tails (extremes) of the distribution of food
intake. Also, the analysis was conducted using
slightly different childhood age groups than those
recommended in U.S. EPA's Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the childhood age groups used, the data should
provide suitable intake estimates for the age groups
of interest. While the CSFII data are older than the
NHANES data, they provide relevant information on
consumption by season, region of the United States,
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and urbanization, breakdowns that are not available
in the publically released NHANES data.
12.3.2.5. Smiciklas-Wright et al (2002)—Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating
Occasion and in a Day, 1994-1996
Using data gathered in the 1994-1996 USDA
CSFII, Smiciklas-Wright etal. (2002) calculated
distributions for the quantities of grain products
consumed per eating occasion by members of the
U.S. population (i.e., serving sizes). The estimates of
serving size are based on data obtained from
14,262 respondents, ages two and above, who
provided two days of dietary intake information.
Only dietary intake data from users of the specified
food were used in the analysis (i.e., consumer-only
data). Table 12-25 presents, as-consumed, the
quantity of grain products consumed per eating
occasion and the percentage of individuals using
these foods in a 2-day period for a selected variety of
grain products. Table 12-26 presents the same data by
sex and age.
These data are presented on an as-consumed basis
(grams) and represent the quantity of grain products
consumed per eating occasion. These estimates may
be useful for assessing acute exposures to
contaminants in specific foods, or other assessments
where the amount consumed per eating occasion is
necessary. Only the mean and standard deviation
serving size data and percent of the population
consuming the food during the 2-day survey period
are presented in this handbook. Percentiles of serving
sizes of the foods consumed by these age groups of
the U.S. population can be found in Smiciklas-Wright
et al. (2002).
The advantages of using these data are that they
were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright etal. (2002)
accounted for individual foods consumed as
ingredients of mixed foods. Mixed foods were
disaggregated via recipe files so that the individual
ingredients could be grouped together with similar
foods that were reported separately. Thus, weights of
foods consumed as ingredients were combined with
weights of foods reported separately to provide a
more thorough representation of consumption.
However, it should be noted that since the recipes for
the mixed foods consumed were not provided by the
respondents, standard recipes were used. As a result,
the estimates of quantity consumed for some food
types are based on assumptions about the types and
quantities of ingredients consumed as part of mixed
foods. This study used data from the 1994 to 1996
CSFII; data from the 1998 children's supplement
were not included.
12.3.2.6. Vitolins et al. (2002)—Quality of Diets
Consumed by Older Rural Adults
Vitolins etal. (2002) conducted a survey to
evaluate the dietary intake, by food groups, of older
(>70 years) rural adults. The sample consisted of
130 community dwelling residents from two rural
counties in North Carolina. Data on dietary intake
over the preceding year were obtained in face-to-face
interviews conducted in participants' homes, or in a
few cases, a senior center. The food frequency
questionnaire used in the survey was a modified
version of the National Cancer Institute Health Habits
and History Questionnaire; this modified version
included an expanded food list containing a greater
number of ethnic foods than the original food
frequency form. Demographic and personal data
collected included sex, ethnicity, age, education,
denture use, marital status, chronic disease, and
weight.
Food items reported in the survey were grouped
into food groups similar to the USDA Food Guide
Pyramid and the National Cancer Institute's 5 A Day
for Better Health program. These groups are
(1) fruits, and vegetables; (2) bread, cereal, rice, and
pasta; (3) milk, yogurt, and cheese; (4) meat, fish,
poultry, beans, and eggs; and (5) fats, oils, sweets,
and snacks. Medians, ranges, frequencies, and
percentages were used to summarize intake of each
food group, broken down by demographic and health
characteristics. In addition, multiple regression
models were used to determine which demographic
and health factors were jointly predictive of intake of
each of the five food groups.
Thirty-four percent of the survey participants
were African American, 36% were European
American, and 30% were Native American.
Sixty-two percent were female, 62% were not
married at the time of the interview, and 65% had
some high school education or were high school
graduates. Almost all of the participants (95%) had
one or more chronic diseases. Sixty percent of the
respondents were between 70 and 79 years of age; the
median age was 78 years old. Table 12-27 presents
the median servings of bread, cereal, rice, and pasta
broken down by demographic and health
characteristic. Only sex was statistically predictive of
bread, cereal, rice, and pasta intake (/?<0.01), with
males consuming approximately an extra serving per
day compared to women. Also, the multiple
regression model indicated that sex was predictive of
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breads, cereal, rice, and pasta intake after controlling
for other demographic variables.
One limitation of the study, as noted by the study
authors, is that the study did not collect information
on the length of time the participants had been
practicing the dietary behaviors reported in the
survey. The questionnaire asked participants to report
the frequency of food consumption during the past
year. The study authors noted that, currently, there are
no dietary assessment tools that allow the collection
of comprehensive dietary data over years of food
consumption. Another limitation of the study is that
the small sample size used makes associations by sex
and ethnicity difficult.
12.3.2.7. Fox et al (2004)—Feeding Infants and
Toddlers Study: What Foods Are Infants
and Toddlers Eating
Fox etal. (2004) used data from the Feeding
Infants and Toddlers study (FITS) to assess food
consumption patterns in infants and toddlers. The
FITS was sponsored by Gerber Products Company
and was conducted to obtain current information on
food and nutrient intakes of children, ages 4 to
24 months old, in the 50 states and the District of
Columbia. The FITS is described in detail in
Devaney et al. (2004). FITS was based on a random
sample of 3,022 infants and toddlers for which
dietary intake data were collected by telephone from
their parents or caregivers between March and July
2002. An initial recruitment and household interview
was conducted, followed by an interview to obtain
information on intake based on 24-hour recall. The
interview also addressed growth, development, and
feeding patterns. A second dietary recall interview
was conducted for a subset of 703 randomly selected
respondents. The study over-sampled children in the
4 to 6 and 9 to 11 months age groups; sample weights
were adjusted for non-response, over sampling, and
under coverage of some subgroups. The response rate
for the FITS was 73% for the recruitment interview.
Of the recruited households, there was a response rate
of 94% for the dietary recall interviews (Devaney
et al., 2004). Table 12-28 shows the characteristics of
the FITS population.
Fox et al. (2004) analyzed the first set of 24-hour
recall data collected from all study participants. For
this analysis, children were grouped into six age
categories: 4 to 6 months, 7 to 8 months, 9 to
11 months, 12 to 14 months, 15 to 18 months, and 19
to 24 months. Table 12-29 provides the percentage of
infants and toddlers consuming different types of
grains or grain products at least once a day. The
percentages of children eating any type of grain or
grain product ranged from 65.8% for 4 to 6 month-
olds to 99.2% for 19- to 24-month-olds.
The advantages of this study is that it represents
the U.S. population, and the sample size was large.
One limitation of the analysis done by Fox etal.
(2004) is that only frequency data were provided; no
information on actual intake rates was included. In
addition, Devaney etal. (2004) noted several
limitations associated with the FITS data. For the
FITS, a commercial list of infants and toddlers was
used to obtain the sample used in the study. Since
many of the households could not be located and did
not have children in the target population, a lower
response rate than would have occurred in a true
national sample was obtained (Devaney et al., 2004).
In addition, the sample was likely from a higher
socioeconomic status when compared with all U.S.
infants in this age group (4 to 24 months old), and the
use of a telephone survey may have omitted
lower-income households without telephones
(Devaney et al., 2004).
12.3.2.8. Ponza et al. (2004)—Nutrient Food
Intakes and Food Choices of Infants and
Toddlers Participating in WIC
Ponza etal. (2004) conducted a study using
selected data from the FITS to assess feeding
patterns, food choices, and nutrient intake of infants
and toddlers participating in the Special
Supplemental Nutrition Program for Women, Infants,
and Children (WIC). Ponza etal. (2004) evaluated
FITS data for the following age groups: 4 to
6 months (N= 862), 7 to 11 months (N= 1,159), and
12 to 24 months (N=996). Table 12-30 shows the
total sample size described by WIC participants and
non-participants.
The foods consumed were analyzed by tabulating
the percentage of infants who consumed specific
foods/food groups per day (Ponza etal., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza et al., 2004). Table 12-30 presents
the demographic data for WIC participants and
non-participants. Table 12-31 provides information
on the food choices for the infants and toddlers
studied. In general, there was little difference in grain
product choices among WIC participants and
non-participants, except for the 7 to 11 months age
category (see Table 12-31). Non-participants, ages 7
to 11 months, were more likely to eat non-infant
cereals than WIC participants.
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
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were not provided. Other limitations are those
associated with the FITS data, as described
previously in Section 12.3.2.7.
12.3.2.9. Fox et al. (2006)—Average Portion of
Foods Commonly Eaten by Infants and
Toddlers in the United States
Fox et al. (2006) estimated average portion sizes
consumed per eating occasion by children 4 to
24 months of age who participated in the FITS. The
FITS is a cross-sectional study designed to collect
and analyze data on feeding practices, food
consumption, and usual nutrient intake of U.S.
infants and toddlers and is described in Section
12.3.2.7 of this chapter. It included a stratified
random sample of 3,022 children between 4 and
24 months of age.
Using the 24-hour recall data, Fox et al. (2006)
derived average portion sizes for six major food
groups, including breads and grains. Average portion
sizes for select individual foods within these major
groups were also estimated. For this analysis,
children were grouped into six age categories: 4 to
5 months, 6 to 8 months, 9 to 11 months, 12 to
14 months, 15 to 18 months, and 19 to 24 months.
Tables 12-32 and 12-33 present the average portion
sizes for grain products for infants and toddlers,
respectively.
12.3.2.10. Mennella etal. (2006)—Feeding Infants
and Toddlers Study: The Types of Foods
Fed to Hispanic Infants and Toddlers
Menella etal. (2006) investigated the types of
food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic
infants and toddlers in the United States. The FITS
2002 data for children between 4 and 24 months of
age were used for the study. The data represent a
random sample of 371 Hispanic and
2,367 non-Hispanic infants and toddlers (Menella
etal., 2006). Menella etal. (2006) grouped the
infants as follows: 4 to 5 months (N = 84 Hispanic;
538 non-Hispanic), 6 to 11 months
(N= 163 Hispanic; 1,228 non-Hispanic), and 12 to
24 months (N= 124 Hispanic; 871 non-Hispanic) of
age.
Table 12-34 provides the percentage of Hispanic
and non-Hispanic infants and toddlers consuming
grain products. In most instances, the percentages
consuming the different types are similar. However, 6
to 11 month old Hispanic children were more likely
to eat rice and pasta than non-Hispanic children in
this age groups.
The advantage of the study is that it provides
information on food preferences for Hispanic and
non-Hispanic infants and toddlers. A limitation is that
the study did not provide food intake data but
provided frequency of use data instead. Other
limitations are those noted previously in
Section 12.3.2.7 for the FITS data.
12.4. CONVERSION BETWEEN WET- AND
DRY-WEIGHT INTAKE RATES
The intake data presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
uncooked weight of grain products consumed per day
or per eating occasion). However, data on the
concentration of contaminants in grain products may
be reported in units of either wet or dry weight (e.g.,
mg contaminant per gram dry weight of grain
products). It is essential that exposure assessors be
aware of this difference, so that they may ensure
consistency between the units used for intake rates
and those used for concentration data (i.e., if the
contaminant concentration is measured in dry weight
of grain products, then the dry-weight units should be
used for their intake values).
If necessary, wet-weight (e.g., as-consumed)
intake rates may be converted to dry-weight intake
rates using the moisture content percentages
presented in Table 12-35 and the following equation:
100-FF
100
(Eqn. 12-1)
where:
IRW
dry -weight intake rate,
wet-weight intake rate, and
percent water content.
Alternatively, dry-weight residue levels in grain
products may be converted to wet-weight residue
levels for use with wet-weight (e.g., as-consumed)
intake rates as follows:
r =
"^-rww
100-E
100
(Eqn. 12-2)
where:
= wet concentration rate,
= dry-weight concentration, and
= percent water content.
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The moisture data presented in Table 12-35 are
for selected grain products taken from USD A (2007).
12.5. REFERENCES FOR CHAPTER 12
Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T;
Clusen, N; Ziegler, P. (2004) Feeding
infants and toddlers study: overview of the
study design. J Am Diet Assoc 104(Suppl
1):S8-S13.
Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004)
Feeding infants and toddlers study: what
foods are infants and toddlers eating? J Am
Diet Assoc 104(Suppl):S22-S30.
Fox, MK; Reidy, K; Karwe, V; Zeigler, P. (2006)
Average portions of foods commonly eaten
by infants and toddlers in the United States.
J Am Diet Assoc 106 (Suppl 1):S66-S76.
Mennella, JA; Ziegler, P; Briefel, R; Novak, T.
(2006) Feeding infants and toddlers study:
the types of foods fed to Hispanic infants
and toddlers. J Am Diet Assoc 106(Suppl
1): S96-S106.
National Center for Health Statistics (NCHS) (1993).
Joint Policy on Variance Estimation and
Statistical Reporting Standards on NHANES
III and CSFII Reports: HNIS/NCHS
Analytic Working Group Recommendations.
Human Nutrition Information Service
(HNIS)/Analytic Working Group. Available
from: Agricultural Research Service, Survey
Systems/Food Consumption Laboratory,
4700 River Road, Unit 83, Riverdale, MD
20737.
Ponza, M; Devaney, B; Ziegler, P; Squatrito, C.
(2004) Nutrient intakes and food choices of
infants and toddlers participating in WIC. J
Am Diet Assoc 104(Suppl): S71-S79.
Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ;
Cook, AJ; Goldman, JD. (2002) Foods
commonly eaten in the United States:
quantities consumed per eating occasion and
in a day, 1994-1996. U.S. Department of
Agriculture NFS Report No. 96-5, pre-
publication version, 252 pp.
USDA (Department of Agriculture). (1980) Food and
nutrient intakes of individuals in 1 day in the
United States, Spring 1977. Nationwide
Food Consumption Survey 1977-1978.
Preliminary Report No. 2. Human Nutrition
Information Service, Beltsville, MD.
USDA (Department of Agriculture). (1992) Food and
nutrient intakes by individuals in the United
States, 1 day, 1987-1988. Nationwide Food
Consumption Survey Report No. 87. Human
Nutrition Information Service, Beltsville,
MD.
USDA (Department of Agriculture). (1996a) Data
tables: results from USDA's 1994 continuing
survey of food intakes by individuals and
1994 diet and health knowledge survey.
Agricultural Research Service, Riverdale,
MD.
USDA (Department of Agriculture). (1996b) Data
tables: results from USD A's 1995 continuing
survey of food intakes by individuals and
1995 diet and health knowledge survey.
Agricultural Research Service, Riverdale,
MD.
USDA (Department of Agriculture). (1999a) Food
consumption prices and expenditures
(1970-1997) Statistical Bulletin, No. 965.
Economic Research Service, Washington,
DC. Available online at
http://www.ars.usda.gov/SP2UserFiles/Place
/12355000/pdf/scs_all.pdf.
USDA (Department of Agriculture). (1999b) Food
and nutrient intakes by children 1994-1996,
1998: table set 17. Food Surveys Research
Group, Human Nutrition Research Center,
Agricultural Research Service, Beltsville,
MD.
USDA (Department of Agriculture). (2000) 1994-
1996, 1998 continuing survey of food
intakes by individuals (CSFII). CD-ROM.
Agricultural Research Service, Beltsville
Human Nutrition Research Center,
Beltsville, MD. Available from the National
Technical Information Service, Springfield,
VA; PB-2000-500027.
USDA (Department of Agriculture). (2007) USDA
national nutrient database for standard
reference, release 20. Available online at
http://www.ars.usda.gov/ba/bhnrc/ndl.
U.S. EPA (Environmental Protection Agency). (2000)
Food commodity intake database [FCID raw
data file]. Office of Pesticide Programs,
Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
Exposure Factors Handbook
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U.S. EPA. (Environmental Protection Agency) (2003)
CSFII analysis of food intake distributions.
National Center for Environmental
Assessment, Washington, DC;
EPA/600/R-03/029.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Risk Assessment Forum, Washington, DC;
EPA/630/P-03/003F. Available online at
http ://www. epa. gov/raf/publications/pdfs/A
GEGROUPS.PDF
Vitolins, M; Quandt, S; Bell, R; Arcury, TA; Case,
LD. (2002) Quality of diets consumed by
older rural adults. J Rural Health 18
(l):49-56.
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Table 12-3. Per Capita
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple
Races
N = Sample size.
SE = Standard error.
Max = Maximum value.
* Estimates are less statistically
Intake of Total Grains
%
Based 2003-2006 NHANES
N Consuming Mean SE
16,783 100
865 76
1,052 100
978 100
2,256 100
3,450 100
4,289 100
4,103 100
3,893 100
4,450 99
4,265 100
6,757 100
562 99
749 100
2.6 0.04
3.1 0.20
6.4 0.17
6.2 0.13
4.4 0.09
2.4 0.05
2.2 0.04
1.9 0.04
1.7 0.03
3.0 0.05
2.4 0.04
2.5 0.05
2.7 0.13
3.0 0.11
i st th
0.2C 0.6
5
0.0* 0.0*
1.5* 2.3*
2.0* 2.4
0.6* 1.4
0.4 0.7
0.3 0.6
0.2 0.5
0.3 0.5
0.1 0.8
0.2 0.5
0.3 0.6
0.2* 0.7
0.3* 0.6
(g/kg-day, edible portion, uncooked weight)
10m
0.8
0.0
3.0
3.3
1.8
1.0
0.8
0.8
0.7
1.0
0.7
0.8
1.0
0.9
Percentiles
25m 50m 75m
1.3 2.0 3.2
0.1 2.3 5.0
4.2 5.8 8.4
4.4 5.9 7.6
2.8 4.1 5.5
1.5 2.1 3.2
1.2 1.9 2.8
1.1 1.7 2.5
1.0 1.5 2.1
1.6 2.4 3.9
1.1 1.8 2.9
1.3 1.9 3.1
1.5 2.1 3.3
1.5 2.5 3.9
90m
5.1
7.5
10.5
9.6
7.4
4.2
3.9
3.4
2.9
5.8
5.0
4.9
5.3
6.0
95m
6.7
9.5*
12.4*
11.1
8.2
5.0
4.6
3.9
3.5
7.2
6.8
6.5
7.0
7.5
99m
9.9
12.5*
15.9*
13.2*
11.1*
7.5
7.1
5.5
5.2
10.6
10.2
9.6
9.8*
11.1*
Max
34.8*
34.9*
21.1*
15.6*
14.5*
14.3*
15.0*
9.8*
9.4*
17.8*
21.1*
34.8*
15.3*
17.5*
reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on
NHANES III and CSFII Reports: NHISWCHS Analytical Working Group Recommendations (NCHS, 1993).
Source: Based on U.S. EPA analysis of 2003-2006 NHANES.
n
S«
»s.
5
fc
KH
51.
1
4
2
S'
5
5
1-
ri
*>
&
*
S
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ft
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ri
^
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-------
Table 12-4. Consumer-Only Intake of Total Grains Based 2003-2006 NHANES (g/kg-day, edible portion, uncooked weight)
Percentiles
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple Races
N = Sample size.
SE = Standard error.
Max = Maximum value.
N Mean SE
16,556 2.6 0.04
644 4.1 0.18
1,050 6.4 0.16
977 6.2 0.13
2,256 4.4 0.09
3,450 2.4 0.05
4,288 2.2 0.04
4,102 1.9 0.03
3,891 1.7 0.03
4,341 3.0 0.05
4,236 2.4 0.04
6,694 2.5 0.05
548 2.8 0.14
737 3.1 0.11
1st
0.35
0.1*
1.6*
2.0*
0.6*
0.4
0.3
0.2
0.3
0.4
0.2
0.3
0.4*
0.3*
ttl
0.6
0.4*
2.4*
2.4
1.4
0.7
0.6
0.5
0.5
0.8
0.5
0.6
0.7
0.7
10m
0.8
0.8*
3.0
3.3
1.8
1.0
0.8
0.8
0.7
1.1
0.7
0.8
1.0
0.9
25th
1.3
1.8
4.2
4.4
2.8
1.5
1.2
1.1
1.0
1.6
1.1
1.3
1.5
1.5
50m
2.0
3.5
5.8
5.9
4.1
2.1
1.9
1.7
1.5
2.4
1.8
2.0
2.1
2.5
75m
3.2
5.9
8.4
7.6
5.5
3.2
2.8
2.5
2.1
3.9
2.9
3.1
3.4
3.9
90m
5.1
8.1*
10.5
9.6
7.4
4.2
3.9
3.4
2.9
5.9
5.0
4.9
5.4
6.0
95th
6.7
10.3*
12.4*
11.1
8.2
5.0
4.6
3.9
3.5
7.2
6.9
6.5
7.1
7.5
99m
9.9
13.9*
15.9*
13.2*
11.1*
7.5
7.1
5.5
5.2
10.6
10.3
9.6
9.8*
11.1*
Max
34.9*
34.9*
21.1*
15.6*
14.5*
14.3*
15.0*
9.8*
9.4*
17.8*
21.1*
34.9*
15.3*
17.5*
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting
Standards on NHANES III and CSFII Reports: NHISMCHS Analytical Working Group Recommendations (NCHS, 1 993).
Source: Based on U.S. EPA analysis of 2003-2006 NHANES.
Q
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-5. Per Capita Intake of Individual Grain Products Based 2003-2006 NHANES (g/kg-day, edible
portion, uncooked weight)
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including
Races
N = Sample size.
N
16,783
865
1,052
978
2,256
3,450
4,289
4,103
3,893
4,450
4,265
6,757
562
Multiple
749
Consuming
100
81
100
100
100
100
100
100
100
100
100
100
99
100
Mean
Cereal
3.7
5.1
8.7
8.6
6.3
3.9
3.2
2.9
2.2
4.3
3.6
3.6
3.9
4.1
SE
0.04
0.30
0.18
0.17
0.10
0.08
0.04
0.04
0.04
0.07
0.06
0.05
0.20
0.12
Consuming
88
69
87
91
89
85
89
86
89
87
86
88
92
90
Mean
Rice
0.2
1.1
0.6
0.5
0.3
0.2
0.3
0.2
0.1
0.3
0.3
0.2
0.6
0.8
SE
0.01
0.08
0.06
0.06
0.03
0.01
0.01
0.01
0.01
0.02
0.02
0.01
0.05
0.08
SE = Standard error.
Source: Based on U.S.
EPA analysis of 2003-2006 NHANES.
Exposure Factors Handbook
September 2011
Page
12-15
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-6. Consumer-Only Intake of Individual Grain Products Based 2003-2006 NHANES (g/kg-day,
edible portion, uncooked
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
Females 13 to 49 years
50 years and older
Race
Mexican American
Non-Hispanic Black
Non-Hispanic White
Other Hispanic
Other Race — Including Multiple Races
jV = Sample size.
SE = Standard error.
N
16,613
696
1,051
978
2,256
3,450
4,289
4,103
3,893
4,372
4,244
6,707
550
740
Mean
Cereal
3.7
6.3
8.7
8.6
6.3
3.9
3.2
2.9
2.2
4.3
3.6
3.6
3.9
4.1
weight)
SE
0.04
0.31
0.18
0.17
0.10
0.08
0.04
0.04
0.04
0.07
0.06
0.05
0.20
0.13
N
14,447
552
928
875
2,000
2,898
3,812
3,511
3,382
3,757
3,645
5,887
491
667
Mean
Rice
0.3
1.5
0.7
0.5
0.3
0.2
0.3
0.2
0.2
0.3
0.3
0.2
0.6
0.8
SE
0.01
0.10
0.07
0.06
0.03
0.02
0.02
0.02
0.01
0.02
0.02
0.01
0.05
0.08
Source: Based on U.S. EPA analysis of 2003-2006 NHANES.
Page
12-16
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-7. Mean Grain Intake per Individual in a Day by Sex
Group Age (years) Total Grains
Breads, Rolls,
Biscuits
and Age (g/day as-consumed)
Other Baked „ . „ ,
„ , Cereals, Pasta
Goods
a for 1977-1978
Mixtures, Mainly
Grainb
Males and Females
<1
Ito2
3 to 5
6 to 8
Males
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
Females
9 to 11
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
>75
42
158
181
206
238
288
303
253
256
234
229
235
196
214
235
196
161
163
161
155
175
178
Males and Females — All Ages 204
a
b
Source:
4
27
46
53
67
76
91
84
82
82
78
71
70
58
57
57
44
49
49
52
57
54
62
5
24
37
56
56
80
77
53
60
58
57
60
50
59
61
43
36
38
37
40
42
44
49
30
44
54
60
51
57
53
64
40
44
48
69
58
44
45
41
33
32
32
36
47
58
44
3
63
45
38
64
74
82
52
74
50
46
35
19
53
72
55
48
44
43
27
29
22
49
Based on USDA Nationwide Food Consumption Survey 1977-1978 data for 1 day.
Includes mixtures containing grain as the main ingredient.
USDA, 1980.
Exposure Factors Handbook Page
September 2011 12-17
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-8. Mean Grain Intakes per Individual in a Day
1987-1988
. , P . Total Grains
Age (years)
Males and
Females <5
Males
6 to 11
12 to 19
>20
Females
6 to 11
12 to 19
>20
All Individuals
167
268
304
272
231
239
208
237
Yeast Breads and
Rolls
30
51
65
65
43
45
45
52
Quick Breads,
Pancakes,
French Toast
8
16
28
20
19
13
14
16
by Sex and Age (g/day
Cakes, Crackers,
Cookies, Popcorn,
Pastries, Pretzels,
Pies Com Chips
22
37
45
37
30
29
28
32
a Based on USDA Nationwide Food Consumption Survey 1 987-1 988 data for 1
b Includes mixtures containing grain as the main ingredient.
Source: USDA, 1992.
4
8
10
8
6
7
6
7
day.
as-consumed)3 for
Cereals and
Pastas
52
74
72
58
66
52
53
57
Mixtures,
Mostly
Grainb
51
83
82
83
68
91
62
72
Table 12-9. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed)3 for
1994-1995
Group
Age (years) —
Females <5
Males
6 to 11
12 to 19
>20
Females
6 to 11
12 to 19
>20
All
Individuals
„ , . „ . Yeast Breads
Total Grains ,„ ,,
and Rolls
1994 1995 1994 1995
213 210 26 28
285 341 51 45
417 364 53 54
357 365 64 61
260 286 43 46
317 296 40 37
254 257 44 45
300 303 50 49
Based on USDA CSFII 1 994 and 1 995
Quick Breads,
Pancakes,
French Toast
1994
11
15
30
22
16
16
16
18
1995
11
21
21
24
21
14
15
19
Cakes,
Cookies,
Pastries, Pies
1994
22
42
54
43
37
39
33
38
1995
23
46
43
46
51
35
34
39
Crackers,
Popcorn,
Pretzels, Com
Chips
1994
8
12
17
13
11
17
9
12
1995
7
18
22
15
14
16
10
13
Cereals and
Pastas
1994
58
66
82
86
57
63
59
70
1995
57
97
84
91
54
52
69
76
Mixtures,
Mostly
Grainb
1994
89
101
180
128
94
142
92
112
1995
84
115
138
128
100
143
83
107
data for 1 day.
b Includes mixtures containing grain as the main
Source: USDA,
1996a,b.
ingredient.
Page
12-18
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-10. Per Capita Consumption of Flour and Cereal Products in 1997
Per Capita Consumption
Food Item (g/day)a
Total Wheat Flourb 186
Rye Flour 0.7
Ricec 24
Total Com Products'1 29
Oat Products6 8
Barley Productsf 0.9
Total Flour and Cereal Products8 249
Original data were presented in Ibs/year; data were converted to g/day by multiplying by a factor of 454 g/lb and
dividing by 365 day/year. Consumption of most items at the processing level. Excludes quantities used in alcoholic
beverages and fuel.
Includes white, whole wheat, and durum flour.
Milled basis.
Includes corn flour and meal, hominy and grits, and corn starch.
Includes rolled oats, ready-to-eat oat cereals, oat flour, and oat bran.
Includes barley flour, pearl barley, and malt and malt extract used in food processing.
Excludes wheat not ground into flour.
Source: USDA, 1999a.
Exposure Factors Handbook Page
September 2011 12-19
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I
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Table 12-11. Mean Quantities of Grain Products Consumed by Children Under 20 Years of Age, by Sex and Age, Per Capita (g/day, as-consumed)3
Age Group Sample „ ,b
(years) Size
<1
1
2
I to 2
o
J
4
5
3 to 5
<5
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
56
192
219
206
242
264
284
264
219
Yeast,
Cereals and Pasta
Breads, „ , „
, „ , Ready -to-eat _.
and Total „ J , Rice
Rolls Cereals
2
16
26
21
30
36
41
36
27
29
57
62
59
64
67
76
69
61
Males
1
11
16
13
19
22
24
22
16
and Females
2
9
15
12
13
15
17
15
13
Pasta
ld
9
12
11
12
11
11
11
10
- Quick Breads,
Pancakes,
French Toast
1
9
12
11
16
17
15
16
12
Cakes,
Cookies
Pastries
Pies
o
3
16
22
19
23
30
33
29
22
Crackers, , ,. ,
_ Mixtures,
Popcorn, , , . ,
„ . , Mainly
Pretzels, „ . i
„ ™. Grain
Corn Chips
1
7
9
8
11
13
13
12
9
20
87
87
87
98
102
107
102
87
Males
6 to 9
6 to 11
12 to 19
787
1,031
737
310
318
406
45
46
54
77
80
82
28
31
29
18
16
27
15
18
17
23
23
26
39
40
49
16
15
19
109
115
175
Females
6 to 9
6 to 11
12 to 19
<9
<19
a
b
704
969
732
9,309
11,287
284
280
306
250
298
Based on data from 1994-1996,
43
43
40
34
40
1998 CSFII.
61
62
67
64
69
Includes yeast breads, rolls, cereals, pastas, quick breads,
chips, and mixtures having a grain product as
item and tabulated under another food group;
c
d
Note:
Source:
Includes mixtures having a grain product as a
mixtures; frozen meals
21
20
17
Males
20
22
pancakes
12
14
19
and Females
14
17
15
15
22
12
15
18
19
15
16
18
, French toast, cakes, cookies, pastries, pies
a main ingredient. Excludes grain products that were ingredients
for example
, noodles
in tuna-noodle casserole
main ingredient, such as burritos, tacos, pizza
in which the main course is a grain mixture
, noodle and rice
42
42
37
30
36
, crackers
13
14
15
12
14
popcorn, pretzels,
in food mixtures coded as a
107
101
132
96
120
corn
single
are tabulated under Meat, Poultry, and Fish.
egg rolls, quiche,
spaghetti
soups; and baby -food macaroni and
with sauce, rice and pasta
spaghetti mixtures
Estimate is not statistically reliable due to small sample size reporting intake.
Consumption amounts
USDA, 1999b.
shown are representative of the first day of each participant'
s survey
response.
Q
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§
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Table 12-12. Percentage of Individuals Under 20 Years of Age Consuming Grain Products, by Sex and Age (%)a
Yeast, Cereals and Pasta Quick Cakes, Crackers, ,,.
A p / -. Sample „ ,b Breads , Breads, Cookies, Popcorn, "^Ui]a'
Size and Total ^ _/ , Rice Pasta Pancakes, Pastries, Pretzels, „ . c
r, „ eat Cereals „ , ^ ' „. ^ ™. Gram
Rolls French Toast Pies Corn Chips
Males and Females
<1 1,126 70.6 10.9 62.8 9.1 3.4 2.1 4.4 16.5 10.3 15.0
1 1,016 98.2d 48.4 70.6 45.3 11.3 9.4 23.0 47.0 39.0 47.8
2 1,102 99.0d 58.7 71.1 51.9 14.4 9.4 27.5 46.6 37.9 45.3
Ito2 2,118 98.7 53.7 70.9 48.7 12.9 9.4 25.3 46.8 38.4 46.5
3 1,831 99.4d 64.1 69.7 53.3 11.1 8.6 28.8 46.1 38.5 49.0
4 1,859 99.5d 67.0 69.1 54.8 11.4 7.1 28.6 52.3 39.4 46.2
5 884 99.9d 69.2 70.4 54.9 11.4 6.8 25.2 52.4 32.1 47.4
3 to 5 4,574 99.6d 66.8 69.7 54.3 11.3 7.5 27.5 50.3 36.7 47.5
<5 7,818 95.8 55.5 69.3 46.9 10.9 7.5 24.0 45.0 34.1 43.3
Males
6 to 9 787 98.9d 69.8 62.6 50.8 10.5 7.4 28.1 52.5 36.0 44.5
6 to 11 1,031 99.0d 69.1 64.0 52.4 9.7 8.1 27.1 52.3 33.8 45.3
12 to 19 737 98.2d 62.7 44.6 33.2 10.0 5.9 24.4 41.3 27.2 46.2
Females
6 to 9 704 99.7d 71.5 61.2 47.6 9.0 7.9 26.3 57.1 38.3 48.0
6 to 11 969 99.3d 71.0 59.3 45.6 9.4 7.1 27.1 55.0 37.1 45.7
12 to 19 732 97.6d 60.9 45.9 30.3 8.6 9.3 19.8 40.6 30.9 46.1
Males and Females
<9 9,309 97.2 61.6 66.4 47.9 10.5 7.6 25.3 48.9 35.3 44.4
<19 11,287 97.6 62.4 57.6 41.7 9.9 7.6 24.2 46.1 32.5 45.1
Based on data from 1994-1996, 1998 CSFII.
b Includes yeast breads, rolls, cereals, pastas, quick breads, pancakes, French toast, cakes, cookies, pastries, pies, crackers, popcorn,
pretzels, corn chips, and mixtures having a grain product as a main ingredient. Excludes grain products that were ingredients in food
mixtures coded as a single item and tabulated under another food group; for example, noodles in tuna-noodle casserole are tabulated
under Meat, Poultry, and Fish.
0 Includes mixtures having a grain product as a main ingredient, such as burritos, tacos, pizza, egg rolls, quiche, spaghetti with sauce, rice
and pasta mixtures; frozen meals in which the main course is a grain mixture; noodle and rice soups; and baby-food macaroni and
spaghetti mixtures.
d Estimate is not statistically reliable due to small sample size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999b.
Exposure Factors Handbook
Chapter 12 — Intake of Grain Products
-------
I
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Table 12-13. Per Capita Intake of Total Grains
Population Group
Whole Population
Age group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
Black
American Indian, Alaskan Native
Other/NA
White
Region
.
Midwest
Northeast
^IniitTi
OiiU.Ul
Urbanization
Central City
Suburban
Non-metropolitan
N = Sample size.
SE = Standard error.
N
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
557
2,740
177
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
Source: U.S. EPA analysis of 1994-1996, 1998
Percent
Consuming
99.5
70.5
99.8
100.0
100.0
100.0
99.9
100.0
99.5
99.6
99.5
99.5
98.5
99.4
99.7
98.8
99.6
99.7
99.6
99.5
99.4
99.5
99.5
99.6
CSFII.
Based on
Mean
2.7
2.5
6.4
6.3
4.3
2.5
2.2
1.7
2.6
2.7
2.6
2.7
3.6
2.6
2.9
3.1
2.6
2.7
2.8
2.5
2.8
2.7
2.7
2.4
1994-1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight)
SE
0.0
0.1
0.1
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.2
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
Percentiles
1st
0.2
5
0.0
1.1
1.8
0.9
0.4
0.3
0.3
0.2
0.2
0.3
0.2
0.0
0.1
0.3
0.0
0.3
0.3
0.3
0.2
0.2
0.1
0.3
0.3
Hi
0.6
0.0
2.1
2.6
1.7
0.8
0.6
0.6
0.6
0.6
0.7
0.6
1.1
0.5
0.5
0.7
0.7
0.7
0.7
0.6
0.7
0.6
0.7
0.6
10th
0.9
0.0
2.8
3.2
2.0
1.1
0.8
0.7
0.9
0.8
0.9
0.9
1.5
0.7
0.8
0.9
0.9
0.9
1.0
0.8
0.9
0.9
0.9
0.8
25th
1.3
0.0
4.2
4.3
2.8
1.5
1.3
1.1
1.3
1.3
1.3
1.4
2.3
1.1
1.3
1.5
1.3
1.4
1.4
1.2
1.4
1.3
1.4
1.2
50th
2.1
1.6
5.9
5.9
4.0
2.3
1.9
1.5
2.1
2.1
2.1
2.1
3.2
1.9
2.2
2.4
2.0
2.1
2.2
1.9
2.2
2.1
2.1
1.9
75th
3.3
3.8
7.9
7.8
5.4
3.1
2.8
2.1
3.3
3.4
3.3
3.3
4.7
3.3
4.2
4.1
3.2
3.4
3.5
3.0
3.5
3.5
3.4
2.9
90th
5.2
6.2
10.4
9.9
7.0
4.4
3.9
2.8
5.0
5.5
5.1
5.2
6.2
5.4
6.3
6.1
5.0
5.3
5.3
5.0
5.4
5.4
5.3
4.8
95th
6.8
8.6
12.1
11.5
8.2
5.1
4.7
3.5
6.6
7.0
6.8
6.8
7.3
7.3
7.5
7.7
6.6
7.0
6.8
6.6
7.0
7.0
6.9
6.3
99th
10.3
12.7
16.8
15.6
11.1
7.9
7.1
4.9
10.0
10.5
10.5
10.1
11.2
11.5
12.0
11.7
9.8
10.4
11.0
9.7
10.3
10.7
10.0
10.4
Max
31.6
26.3
31.6
27.0
17.2
12.4
16.1
11.2
26.3
29.4
28.2
31.6
24.6
29.4
16.8
27.0
31.6
23.8
31.6
28.2
20.8
29.4
31.6
23.8
Q
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5
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Table 12-14. Consumer-Only Intake of Total Grains Based on
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
\3to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
Black
American Indian, Alaskan Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non -m etropol i tan
N = Sample size.
SE = Standard error.
Source: U.S. EPA analysis of 1994-1996,
N
20,157
1,048
2,092
4,389
2,089
1,222
4,673
4,644
4,587
5,190
5,751
4,629
527
2,675
175
1,570
15,210
4,743
3,628
7,053
4,733
6,023
9,378
4,756
1998CSFII.
Mean
2.7
3.6
6.4
6.3
4.3
2.5
2.2
1.7
2.6
2.7
2.7
2.7
3.7
2.6
3.0
3.2
2.6
2.7
2.8
2.5
2.8
2.8
2.7
2.4
SE
0.0
0.1
0.1
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.2
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
1994-1996, 1998 CSFH
(g/kg-day, edible portion, uncooked weight)
Percentiles
1st
0.3
5
0.1
1.2
1.8
0.9
0.4
0.3
0.3
0.3
0.3
0.4
0.3
0.8
0.2
0.3
0.5
0.4
0.4
0.4
0.3
0.4
0.3
0.4
0.3
th
0.7
0.3
2.1
2.6
1.7
0.8
0.6
0.6
0.7
0.7
0.7
0.7
1.2
0.5
0.5
0.7
0.7
0.7
0.8
0.6
0.7
0.7
0.7
0.6
10th
0.9
0.6
2.8
3.2
2.0
1.1
0.8
0.7
0.9
0.9
0.9
0.9
1.6
0.7
0.8
1.0
0.9
0.9
1.0
0.8
0.9
0.9
0.9
0.8
25th
1.3
1.4
4.2
4.3
2.8
1.5
1.3
1.1
1.3
1.3
1.4
1.4
2.3
1.1
1.3
1.5
1.3
1.4
1.4
1.2
1.4
1.3
1.4
1.2
50th
2.1
2.8
5.9
5.9
4.0
2.3
1.9
1.5
2.1
2.1
2.1
2.1
3.2
1.9
2.2
2.4
2.0
2.1
2.2
1.9
2.2
2.1
2.1
1.9
75th
3.3
4.8
7.9
7.8
5.4
3.1
2.8
2.1
3.3
3.4
3.3
3.3
4.7
3.3
4.2
4.1
3.2
3.4
3.5
3.0
3.5
3.5
3.4
2.9
90th
5.2
7.4
10.4
9.9
7.0
4.4
3.9
2.8
5.0
5.5
5.2
5.2
6.2
5.4
6.3
6.2
5.1
5.3
5.3
5.0
5.4
5.4
5.3
4.8
95th
6.8
9.2
12.1
11.5
8.2
5.1
4.7
3.5
6.6
7.0
6.8
6.8
7.3
7.3
7.5
7.7
6.6
7.0
6.8
6.6
7.0
7.0
6.9
6.4
99th
10.3
13.4
16.8
15.6
11.1
7.9
7.1
4.9
10.0
10.6
10.5
10.1
11.2
11.5
12.0
11.7
9.8
10.4
11.0
9.8
10.3
10.7
10.0
10.4
Max
31.6
26.3
31.6
27.0
17.2
12.4
16.1
11.2
26.3
29.4
28.2
31.6
24.6
29.4
16.8
27.0
31.6
23.8
31.6
28.2
20.8
29.4
31.6
23.8
Q
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-15. Per Capita Intake of Individual Grain Products Based
edible portion, uncooked weight)
on 1994-1996,
Cereal
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
Black
American Indian, Alaskan Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
N = Sample size.
SE = Standard error.
N
20,607
1,486
2,096
4,391
2,089
1,222
4,677
4,646
4,687
5,308
5,890
4,722
557
2,740
177
1,638
15,495
4,822
3,692
7,208
4,885
6,164
9,598
4,845
Percent
Consuming
99.6
74.6
99.8
100.0
100.0
100.0
99.9
100.0
99.6
99.6
99.5
99.6
98.5
99.5
99.7
98.9
99.7
99.7
99.7
99.6
99.4
99.6
99.5
99.7
Mean
3.7
4.0
8.4
8.7
6.2
4.1
3.1
2.2
3.7
3.8
3.8
3.7
4.4
3.8
4.2
4.3
3.7
3.9
3.7
3.6
3.8
3.8
3.8
3.5
SE
0.03
0.14
0.08
0.07
0.06
0.06
0.04
0.02
0.06
0.07
0.06
0.05
0.20
0.12
0.15
0.12
0.04
0.09
0.06
0.04
0.09
0.06
0.05
0.06
Percent
Consuming
86.5
60.2
86.4
87.9
88.0
85.8
88.3
84.5
85.1
87.1
86.9
87.1
96.6
86.3
92.6
85.9
86.2
88.2
87.2
85.0
86.7
87.2
86.6
85.6
1998 CSFH (g/kg-day,
Rice
Mean
0.3
0.7
0.6
0.5
0.4
0.3
0.3
0.2
0.3
0.3
0.3
0.3
1.7
0.3
0.3
0.6
0.2
0.2
0.3
0.2
0.4
0.4
0.3
0.2
SE
0.01
0.04
0.03
0.03
0.02
0.02
0.01
0.01
0.02
0.02
0.02
0.02
0.19
0.02
0.10
0.08
0.01
0.02
0.03
0.01
0.03
0.02
0.02
0.01
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
Page
12-24
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-16. Consumer-Only Intake of Individual Grain Products Based on 1994-1996, 1998 CSFII (g/kg-
day, edible portion, uncooked weight )
Population Group
Whole Population
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
1 3 to 19 years
20 to 49 years
>50 years
Season
Fall
Spring
Summer
Winter
Race
Asian, Pacific Islander
Black
American Indian, Alaskan Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
N = Sample size.
SE = Standard error.
Source: U.S. EPA analysis of 1994-1996,
N
20,227
1,116
2,092
4,389
2,089
1,222
4,674
4,645
4,598
5,213
5,768
4,648
529
2,683
175
1,579
15,261
4,759
3,639
7,081
4,748
6,039
9,410
4,778
1998 CSFII.
Cereal
Mean
3.8
5.4
8.4
8.7
6.2
4.1
3.1
2.2
3.7
3.8
3.8
3.7
4.5
3.8
4.3
4.4
3.7
3.9
3.7
3.6
3.9
3.8
3.8
3.6
SE
0.03
0.16
0.08
0.07
0.06
0.06
0.04
0.02
0.06
0.07
0.06
0.06
0.20
0.12
0.15
0.13
0.04
0.09
0.06
0.04
0.09
0.06
0.05
0.06
N
17,481
900
1,819
3,869
1,847
1,038
4,102
3,906
3,957
4,530
4,989
4,005
513
2,346
151
1,375
13,096
4,186
3,152
6,029
4,114
5,303
8,105
4,073
Rice
Mean
0.3
1.2
0.7
0.6
0.4
0.3
0.3
0.2
0.3
0.3
0.3
0.3
1.8
0.4
0.3
0.7
0.2
0.2
0.4
0.3
0.5
0.5
0.3
0.2
SE
0.01
0.07
0.04
0.03
0.02
0.03
0.01
0.01
0.02
0.02
0.02
0.02
0.19
0.02
0.10
0.08
0.01
0.02
0.04
0.01
0.03
0.03
0.02
0.02
Exposure Factors Handbook
September 2011
Page
12-25
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I
§
s
a3
Ru
Table 12-17. Per Capita Intake of Breads3 Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed)
Population Group
Whole Population
Age Group
^5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
1 Includes breads, rolls, muffins,
SE = Standard error.
Percent
Consuming
87.2
0.9
30.2
14.6
77.2
86.5
87.1
86.2
88.1
90.0
91.6
87.4
87.1
87.3
86.9
69.1
83.1
82.2
80.4
89.0
89.1
88.3
87.5
83.7
85.6
87.7
88.5
Perc entile
Mean
1.1
0.0
0.5
0.3
2.0
2.3
1.7
1.1
0.9
0.9
0.9
1.1
1.1
1.1
1.1
0.8
1.1
1.4
1.2
1.1
1.2
1.1
1.1
1.1
1.1
1.1
1.1
SE
0.01
0.08
0.16
0.11
0.06
0.05
0.04
0.03
0.02
0.01
0.02
0.02
0.02
0.02
0.02
0.06
0.03
0.18
0.04
0.01
0.02
0.02
0.02
0.02
0.02
0.01
0.02
1st
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25th
0.4
0.0
0.0
0.0
0.4
0.9
0.7
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.0
0.3
0.3
0.3
0.4
0.4
0.4
0.4
0.3
0.4
0.4
0.4
50th
0.9
0.0
0.0
0.0
1.4
2.0
1.4
0.9
0.8
0.8
0.8
0.9
0.9
0.9
0.8
0.4
0.7
0.9
0.9
0.9
0.9
0.9
0.9
0.8
0.8
0.9
0.9
75th
1.5
0.0
0.5
0.0
2.9
3.3
2.4
1.5
1.3
1.3
1.3
1.5
1.5
1.5
1.4
1.2
1.4
1.7
1.6
1.5
1.5
1.5
1.5
1.4
1.4
1.5
1.5
90th
2.3
0.0
1.8
0.8
4.4
4.7
3.5
2.3
2.0
1.9
1.9
2.4
2.3
2.4
2.3
1.9
2.3
3.6
2.7
2.3
2.5
2.3
2.3
2.4
2.3
2.4
2.3
95th
3.1
0.0
3.0
1.7
6.0
5.8
4.3
2.8
2.5
2.3
2.3
3.1
3.1
3.1
3.1
2.9
3.3
4.1
3.4
3.0
3.3
2.9
3.1
3.2
3.1
3.1
3.1
99th
5.1
0.0
4.8
4.6
8.5
8.7
6.7
4.0
3.9
3.5
2.9
4.9
5.1
5.2
5.1
4.5
6.3
6.2
5.6
4.9
5.7
4.5
4.9
5.1
5.1
5.0
5.0
Max
20.0
1.8
7.3
7.3
20.0
13.2
11.3
7.5
6.2
8.4
4.3
14.6
11.6
17.1
20.0
14.6
11.6
20.0
7.5
17.1
12.0
9.8
17.1
20.0
13.2
14.6
20.0
bagels, biscuits, combread, and tortillas.
Source: U.S. EPA analysis of the 1994-1996 CSFII.
Q
I
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I
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5
1=
Table 12-18. Per Capita
Population Group
Whole Population
Age Group
<^_5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
Percent
Intake of Sweets3 Based on 1994-1996,
1998 CSFH (g/kg-day, as-consumed)
Percentile
Consuming Mean
52.6
2.5
23.0
12.1
53.2
62.1
64.2
54.3
47.2
52.9
58.6
53.7
52.2
50.0
54.5
40.2
41.4
35.3
35.0
56.3
60.1
55.4
49.1
47.7
51.2
54.6
50.5
a Includes breakfast foods made with
SE = Standard error.
Source: U.S. EPA analysis of the
0.6
0.0
0.3
0.2
1.2
1.3
1.2
0.6
0.4
0.5
0.5
0.6
0.6
0.5
0.6
0.4
0.5
0.4
0.4
0.6
0.7
0.6
0.6
0.5
0.6
0.6
0.6
SE
0.01
0.04
0.14
0.10
0.07
0.06
0.06
0.03
0.02
0.02
0.03
0.03
0.02
0.02
0.03
0.08
0.04
0.11
0.05
0.01
0.03
0.03
0.02
0.02
0.02
0.02
0.03
i st th
0.0 0.0
5
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50th
0.1
0.0
0.0
0.0
0.3
0.8
0.6
0.2
0.0
0.1
0.2
0.2
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.2
0.3
0.2
0.0
0.0
0.1
0.2
0.1
75th
0.8
0.0
0.0
0.0
1.7
1.9
1.7
1.0
0.6
0.7
0.8
0.9
0.8
0.7
0.9
0.6
0.6
0.3
0.5
0.9
1.0
0.9
0.8
0.7
0.8
0.9
0.8
90th 95th
1.8 2.5
0.0 0.0
1.1 2.0
0.4 1.0
3.5 4.8
3.6 4.6
3.2 3.9
1.8 2.4
1.4 1.9
1.3 1.9
1.6 2.1
1.8 2.5
1.8 2.6
1.6 2.3
1.9 2.6
1.4 2.0
\.5 2.3
1.7 2.1
1.3 1.9
1.8 2.5
2.0 2.9
1.7 2.5
1.7 2.3
1.6 2.3
1.6 2.3
1.8 2.6
1.8 2.5
99th
4.6
0.4
3.6
3.6
7.2
8.8
6.7
3.7
3.2
3.2
3.6
4.7
4.7
4.1
4.8
3.1
4.7
2.8
4.1
4.7
5.3
4.8
4.4
3.8
4.6
4.5
5.\
Max
22.0
0.6
6.4
6.4
19.3
22.0
20.9
10.7
11.1
7.3
5.7
20.9
22.0
18.2
12.3
15.7
19.3
2.9
7.0
22.0
22.0
12.7
20.9
\5.7
20.9
12.7
22.0
grains such as pancakes, waffles, and French toast.
1994-1996 CSFII.
Q
I
-a,
a
I
ft
I
§
I
I
ft
-------
I
§
s
a3
Ru
Table 12-19. Per Capita Intake of Snacks Containing Grains" Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed)
Population Group
Whole Population
Age Group
<^5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
Percent
Consuming
43.1
1.0
29.0
14.1
58.1
56.7
51.3
45.0
41.1
41.1
37.7
42.3
43.6
40.6
45.8
24.1
29.5
38.3
28.4
47.1
49.2
41.9
41.1
40.7
40.1
44.6
44.1
1 Includes grain snacks such as crackers, salty
SE = Standard error.
Source: U.S. EPA analysis of the
1994-1 996 CSFII.
Percentile
Mean
0.2
0.0
0.3
0.1
0.7
0.7
0.5
0.3
0.2
0.1
0.1
0.2
0.3
0.2
0.3
0.1
0.2
0.2
0.2
0.3
0.3
0.2
0.2
0.2
0.2
0.3
0.2
snacks,
SE
0.01
0.11
0.08
0.06
0.04
0.04
0.03
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.02
0.04
0.02
0.08
0.03
0.01
0.01
0.02
0.01
0.02
0.01
0.01
0.01
popcorn,
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
and pretzels.
th i r\th
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
25m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50m
0.0
0.0
0.0
0.0
0.4
0.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75m
0.3
0.0
0.2
0.0
1.1
0.9
0.6
0.4
0.2
0.2
0.1
0.3
0.3
0.2
0.3
0.0
0.1
0.2
0.1
0.3
0.3
0.2
0.2
0.2
0.2
0.3
0.3
90th
0.7
0.0
0.9
0.6
2.0
1.8
1.3
0.9
0.6
0.5
0.3
0.7
0.8
0.7
0.8
0.4
0.5
0.6
0.5
0.8
0.8
0.7
0.7
0.7
0.7
0.7
0.7
95m
1.2
0.0
2.2
0.9
2.8
3.2
1.9
1.4
0.9
0.7
0.5
1.0
1.3
1.0
1.3
1.0
0.9
1.1
0.8
1.2
1.2
1.2
1.1
1.2
1.1
1.2
1.1
99th
2.6
0.1
2.5
2.2
5.0
5.9
4.6
2.4
1.8
1.4
0.8
2.3
2.9
2.3
2.9
2.3
2.1
3.2
2.4
2.7
2.7
2.7
2.4
2.6
2.6
2.7
2.3
Max
9.1
3.7
2.8
3.7
8.9
9.1
7.3
5.1
5.5
5.6
1.8
8.0
8.9
7.1
9.1
4.4
7.4
4.9
8.7
9.1
8.9
9.1
8.0
8.7
7.8
9.1
8.1
Q
I
I
•s,
I
a'
I
ri
s-
-------
5
1=
Table 12-20. Per Capita Intake of Breakfast Foods3 Based on 1994-1996, 1998 CSFH (g/kg-day, as-consumed)
Population Group
Whole Population
Age Group
<^5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
Percent
Consuming
11.8
0.0
4.2
2.0
20.4
20.8
23.7
13.0
8.9
9.5
10.4
11.6
11.6
12.8
11.3
5.9
12.7
8.8
10.2
12.0
12.1
12.7
10.7
12.4
12.0
12.2
10.7
1 Includes breakfast food made with grains
SE = Standard error.
Source: U.S. EPA analysis of the
Percentile
Mean
0.1
0.0
0.1
0.1
0.4
0.4.
0.4
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.2
0.1
0.1
0.1
SE
0.01
0.00
0.24
0.16
0.07
0.06
0.05
0.03
0.02
0.01
0.02
0.02
0.02
0.02
0.02
0.07
0.03
0.08
0.05
0.01
0.02
0.03
0.02
0.02
0.02
0.02
0.02
such as pancakes,
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
waffles,
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75th 90th
0.0 0.4
0.0 0.0
0.0 0.0
0.0 0.0
0.0 1.9
0.0 1.6
0.0 1.5
0.0 0.5
0.0 0.0
0.0 0.0
0.0 0.1
0.0 0.4
0.0 0.4
0.0 0.5
0.0 0.3
0.0 0.0
0.0 0.4
0.0 0.0
0.0 0.0
0.0 0.4
0.0 0.4
0.0 0.5
0.0 0.2
0.0 0.5
0.0 0.4
0.0 0.5
0.0 0.3
95m
1.0
0.0
0.0
0.0
2.7
2.5
2.2
0.9
0.6
0.6
0.7
1.0
1.0
1.0
0.9
0.6
1.2
0.3
0.9
1.0
1.1
1.2
0.8
1.0
1.0
1.0
0.9
99th Max
2.4 13.6
0.0 0.0
4.1 4.1
2.7 4.1
4.8 13.6
4.5 8.0
3.4 6.5
2.3 3.9
1.5 3.0
1.4 3.8
1.2 3.5
2.3 13.6
2.3 6.4
2.4 6.0
2.6 8.0
2.0 2.8
2.1 6.7
1.2 1.2
2.6 8.0
2.4 13.6
2.6 6.7
2.3 8.0
2.2 7.8
2.6 13.6
2.5 13.6
2.4 7.8
2.2 6.4
and French toast.
1994-1 996 CSFII.
Q
I
-a,
a
I
ft
I
§
I
I
ft
-------
I
§
s
a3
Ru
Table 12-21.
Population Group
Whole Population
Age Group
<5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
SE = Standard error.
Source: U.S. EPA analysis of the
Per Capita Intake of Pasta Based on 1994-1996, 1998
Percent
Consuming
13.0
0.0
7.5
3.5
16.0
12.8
13.4
11.7
13.9
13.7
9.0
13.6
13.2
12.6
12.6
19.4
7.0
1.8
9.6
14.1
12.1
20.1
9.5
13.2
13.4
14.0
10.3
1994-1996 CSFII.
CSFn (g/kg-day, as-consumed)
Percentile
Mean
0.3
0.0
0.1
0.1
0.8
0.6
0.5
0.3
0.3
0.2
0.2
0.3
0.3
0.3
0.3
0.5
0.2
0.1
0.2
0.3
0.3
0.5
0.2
0.3
0.3
0.3
0.2
SE
0.02
0.00
0.22
0.15
0.15
0.13
0.12
0.09
0.04
0.03
0.06
0.05
0.05
0.05
0.06
0.17
0.10
0.23
0.09
0.03
0.05
0.05
0.05
0.05
0.05
0.03
0.05
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
90th
1.0
0.0
0.0
0.0
3.4
2.1
2.0
0.8
1.1
1.0
0.0
1.2
1.1
0.9
0.8
2.0
0.0
0.0
0.0
1.1
0.8
1.9
0.0
0.9
1.2
1.2
0.1
95th
2.2
0.0
1.0
0.0
6.2
4.4
3.8
2.1
2.2
1.9
1.3
2.4
2.3
2.1
2.1
3.3
1.7
0.0
2.0
2.3
2.1
2.8
1.8
2.2
2.5
2.2
1.5
99th
5.1
0.0
3.3
2.3
10.6
8.4
7.5
4.2
4.1
3.6
2.9
4.7
5.8
5.2
5.1
6.6
3.6
2.4
3.5
5.3
5.2
5.9
4.4
5.7
5.3
5.3
4.2
Max
29.1
0.0
6.7
6.7
16.7
14.3
11.9
29.1
11.2
11.8
7.7
16.7
14.7
15.4
29.1
11.2
29.1
3.6
15.4
16.7
16.7
15.4
29.1
14.1
29.1
16.7
14.1
Q
I
I
•s,
I
a'
I
ri
s-
-------
5
1=
Table 12-22. Per
Population Group
Whole Population
Age Group
<5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
SE = Standard error.
Source: U.S. EPA analysis of the
Capita Intake of Cooked Cereals Based on 1994-1996,
Percent
Consuming
10.4
0.9
16.6
8.3
18.4
16.0
8.7
5.6
6.2
11.6
24.5
12.0
9.1
9.3
11.1
4.4
20.1
7.6
7.6
9.3
9.6
9.0
12.4
9.4
11.6
9.9
9.7
1994-1 996 CSFII
1998 CSFH (g/kg-day,
as-consumed)
Percentile
Mean
0.4
0.1
1.9
0.9
1.6
\.3
0.5
0.2
0.1
0.3
0.6
0.4
0.3
0.3
0.4
0.2
0.7
0.3
0.4
0.3
0.3
0.3
0.4
0.4
0.4
0.3
0.3
SE
0.04
0.54
1.18
0.82
0.29
0.28
0.17
0.09
0.05
0.03
0.07
0.08
0.06
0.08
0.08
0.20
0.10
0.32
0.30
0.04
0.07
0.10
0.06
0.09
0.08
0.05
0.07
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
90th
0.6
0.0
9.4
0.0
6.9
5.3
0.0
0.0
0.0
0.9
2.2
1.1
0.0
0.0
0.9
0.0
2.2
0.0
0.0
0.0
0.0
0.0
1.1
0.0
0.9
0.0
0.0
95th
2.3
0.0
16.1
5.7
10.7
7.9
4.0
1.0
1.1
1.9
3.4
2.6
2.0
2.1
2.5
0.0
4.4
2.1
2.0
2.0
2.1
2.2
2.6
2.3
2.6
2.1
2.3
99th
7.2
0.0
22.8
22.8
20.6
16.1
9.4
4.3
3.3
4.4
5.6
8.1
6.4
6.9
7.4
5.3
10.9
5.8
10.6
6.1
5.7
5.9
7.9
8.0
8.1
6.9
5.7
Max
72.5
5.6
22.8
22.8
33.9
72.5
24.1
10.6
9.2
8.7
10.6
45.9
20.9
72.5
44.5
16.1
33.9
\2.3
72.5
45.9
45.9
72.5
3\7
39.5
72.5
45.9
26.9
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Table 12-23. Per Capita Intake of Ready-to-Eat
T-, i •• /-, Percent
Population Group „ . —
r r Consuming
Whole Population 39.7
Age
<5 months 0.0
6 to 12 months 19.9
<1 year 9.3
1 to 2 years 64.9
3 to 5 years 69.8
6 to 11 years 64.0
12 to 19 years 45.7
20 to 39 years 30.5
40 to 69 years 31.8
>70 years 47.9
Season
Fall 39.1
Spring 40.1
Summer 39.6
Winter 39.9
Race
Asian 25.4
Black 34.0
American Indian/Alaska Native 33.1
Other/NA 33.3
White 41.7
Region
Midwest 42.2
Northeast 42-3
South 37-4
West 38.4
Urbanization
Central City 40.0
Suburban 41.2
Non-metropolitan 35.8
Cereals" Based on 1994-1996, 1998 CSFII (g/kg-day, as-consumed)
Percentile
Mean
0.3
0.0
0.1
0.1
1.0
1.1
0.8
0.4
0.2
0.2
0.2
0.3
0.3
0.3
0.3
0.2
0.3
0.3
0.3
0.3
0.4
0.4
0.3
0.3
0.3
0.4
0.3
SE
0.01
0.00
0.07
0.05
0.04
0.04
0.03
0.02
0.01
0.01
0.01
0.02
0.02
0.02
0.02
0.05
0.02
0.09
0.04
0.01
0.02
0.02
0.01
0.02
0.01
0.01
0.01
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50m
0.0
0.0
0.0
0.0
0.7
0.9
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75m
0.4
0.0
0.0
0.0
1.5
1.7
1.2
0.6
0.3
0.2
0.4
0.4
0.4
0.4
0.5
0.1
0.4
0.4
0.3
0.5
0.5
0.5
0.4
0.4
0.5
0.5
0.4
90th 95th
1.0 1.5
0.0 0.0
0.3 1.0
0.0 0.3
2.5 3.3
2.6 3.3
2.0 2.5
1.1 1.5
0.7 1.0
0.6 0.9
0.7 0.9
1.1 1.6
1.0 1.5
1.1 1.6
1.0 1.4
0.8 1.2
1.0 1.5
0.8 1.4
1.1 1.7
1.1 1.5
1.1 1.6
1.1 1.6
1.0 1.3
1.1 1.6
1.1 1.5
1.1 1.6
0.8 1.2
99th
2.9
0.0
1.8
1.7
4.9
4.8
4.0
2.2
1.7
1.4
1.5
2.9
2.9
3.0
2.7
2.7
3.2
2.6
3.0
2.8
2.9
2.9
2.8
3.1
2.8
3.1
2.6
Max
10.1
0.0
2.6
2.6
8.8
10.1
8.0
6.4
5.3
5.2
2.7
8.8
7.7
7.8
10.1
4.9
10.1
4.4
6.6
8.8
8.0
8.0
10.1
8.8
10.1
8.0
8.8
1 Includes dry ready-to-eat com, rice, wheat, and bran cereals in the form of flakes, puffs, etc.
SE = Standard error.
Source: U.S. EPA analysis of the 1994-1996 CSFII.
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Table 12-24. Per Capita Intake of Baby Cereals Based on
Population Group
Whole Population
Age
<5 months
6 to 12 months
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
Season
Fall
Spring
Summer
Winter
Race
Asian
Black
American Indian/Alaska Native
Other/NA
White
Region
Midwest
Northeast
South
West
Urbanization
Central City
Suburban
Non-metropolitan
SE = Standard error.
Source: U.S. EPA analysis of the
Percent
Consuming
1.0
40.8
67.8
53.4
6.2
0.3
0.1
0.0
0.0
0.1
0.0
0.9
1.2
0.8
1.1
0.7
1.0
0.6
1.7
1.0
1.1
1.2
0.9
0.9
1.1
1.1
0.8
1994-1996, 1998
CSFn (g/kg-day, as-consumed)
Percentile
Mean
0.0
0.8
2.5
1.6
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
SE
0.03
0.24
OA5
0.27
0.10
0.06
0.00
0.00
0.00
0.00
0.00
0.07
0.05
0.06
0.06
0.04
0.12
0.04
0.20
0.03
0.08
0.04
0.05
0.06
0.06
0.04
0.06
1st
0.0
5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10m
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25th
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50th
0.0
0.0
0.8
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
75th
0.0
1.0
2.8
1.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
90th
0.0
2.4
6.9
4.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
95th
0.0
3.1
n.3
7.3
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
99th
0.1
8.8
21.1
19.7
5.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.3
0.0
0.0
0.0
1.2
0.0
0.3
0.5
0.0
0.0
0.3
0.1
0.0
Max
37.6
26.6
37.6
37.6
\2.5
3.8
0.1
0.0
0.0
0.3
0.0
21.1
26.6
26.0
37.6
2.1
37.6
0.9
26.6
26.0
21.1
12.5
37.6
26.6
37.6
21.1
26.0
1994-1 996 CSFII.
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a3
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Table 12-25. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and the Percentage of Individuals
These Foods in 2 Days
Food category
White bread
Whole grain and wheat bread
Rolls
Biscuits
Tortillas
Quick breads and muffins
Doughnuts and sweet rolls
Crackers
Cookies
Cake
Pie
Pancakes and waffles
Cooked cereal
Oatmeal
Ready-to-eat cereal
Com flakes
Toasted oat rings
Rice
Pasta
Macaroni and cheese
Spaghetti with tomato sauce
Pizza
SE = Standard error.
Source: Smiciklas- Wright et al
% Indiv.
using food
at least
once in 2
days
59.6
28.1
48.0
10.9
15.5
12.5
12.4
17.4
30.7
16.2
8.5
10.3
10.3
6.1
40.6
8.1
6.8
28.0
36.0
8.5
8.0
19.9
, 2002, (based on
Quantity consumed per
eating occasion
(grams)
Average
50
50
58
61
60
82
77
26
40
92
150
85
248
264
54
46
42
150
162
244
436
169
1994-1996 CSFII
SE
1
1
1
1
1
2
1
1
1
3
3
3
6
6
1
1
1
3
3
9
15
5
data).
Quantity
5th
21
24
27
19
14
21
26
6
9
22
52
21
81
116
18
17
14
27
26
53
122
36
Using
Consumers Onlv
consumed per eating occasion at specified percentiles (grams)
10th
24
25
33
19
21
28
36
9
12
28
72
35
117
117
24
22
16
40
43
81
124
52
25th
33
37
43
35
32
52
47
12
20
41
102
42
157
176
30
25
27
76
73
121
246
78
50th
46
50
48
57
48
60
65
18
31
77
143
75
233
232
46
37
38
131
133
191
371
140
75th
52
56
70
76
79
94
93
30
50
116
168
109
291
333
67
56
54
192
210
324
494
214
90th
78
72
89
104
107
142
133
47
75
181
246
158
455
454
93
75
65
312
318
477
740
338
95th
104
92
110
139
135
187
164
62
96
217
300
205
484
473
113
100
83
334
420
556
983
422
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Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods
in 2 Days, by Sex and Age
2 to 5 years
Food Category
White bread
Whole grain and wheat bread
Rolls
Biscuits
Tortillas
Quick breads and muffins
Doughnuts and sweet rolls
Crackers
Cookies
Cake
Pie
Pancakes and waffles
Cooked cereal
Oatmeal
Ready -to-eat cereal
Corn flakes
Toasted oat rings
Rice
Pasta
Macaroni and cheese
Spaghetti with tomato sauce
Pizza
Corn chips
Popcorn
Male and Female
(AT =2, 109)
PC
66.9
24.3
40.0
S3
14.6
9.6
11.3
25.4
51.0
14.6
2.9
19.1
16.8
10.4
72.9
11.2
20.6
29.6
49.4
17.8
16.8
23.1
19.6
11.6
Mean
34
37
39
38
32
55
59
17
28
70
76
49
211
221
33
33
30
84
90
159
242
86
29
20
SE
a
1
1
2
2
4
2
1
1
3
8
1
10
9
1
2
1
3
o
J
8
11
o
J
2
1
Quantity
consumed
per eating occasion (grams)
6 to 1 1 years
Male and Female
(N= 1,432)
PC
67.1
20.5
53.5
9.7
16.4
9.6
13.4
17.2
46.7
19.7
5.6
21.5
9.0
5.1
67.3
13.1
12.5
24.6
41.4
13.2
11.5
32.8
25.6
12.7
Mean
42
44
48
48
47
67
69
26
37
79
116
77
245
256
47
42
45
124
130
217
322
108
33
31
SE
1
1
1
o
J
2
5
2
2
2
4
8
3
14
19
1
2
2
6
5
13
18
6
2
2
PC
61.3
14.5
61.9
12.2
22.9
11.0
17.3
10.6
29.0
15.1
6.6
13.5
5.2
2.4
45.6
10.4
7.3
24.2
33.4
1.5
10.1
39.6
26.9
7.8
12 to 19 years
Male
(N=696)
Mean
56
60
69
72
76
125
102
39
53
99
188
96
310b
348b
72
62
62
203
203
408
583
205
58
54
SE
1
2
2
4
5
12
12
5
3
9
15
6
29b
45b
3
4
5
10
9
46
46
13
5
5
Female
(AT =702)
PC
57.9
17.6
48.8
10.3
20.1
11.0
13.8
14.2
31.8
15.5
4.8
8.2
6.0
2.3
46.3
8.7
8.1
28.8
37.8
10.7
8.5
30.5
25.1
10.5
Mean
47
53
51
55
56
79
78
26
42
85
138b
74
256b
321b
52
49
42
157
155
260
479
143
44
37
SE
1
2
1
4
3
10
5
3
2
8
12b
5
31b
40b
2
4
3
10
9
30
51
8
3
4
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Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods
Food category
White bread
Whole grain and wheat bread
Rolls
Biscuits
Tortillas
Quick breads and muffins
Doughnuts and sweet rolls
Crackers
Cookies
Cake
Pie
Pancakes and waffles
Cooked cereal
Oatmeal
Ready -to-eat cereal
Corn flakes
Toasted oat rings
Rice
Pasta
Macaroni and cheese
Spaghetti with tomato sauce
Pizza
Corn chips
Popcorn
in 2 Days, by Sex and Age (continued)
Quantity consumed per eating occasion (g)
20 to <40 years 40 to <60 years >60 years
Male Female Male Female Male Female
(N= 1,543) (N= 1,449) (AT = 1,663) (AT = 1,694) (N= 1,545) (AT = 1,429)
PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE
63.0 63 2 54.9 47 1 59.7 59 2 55.3 46 1 59.3 51 1 54.8 41 1
25.3 63 1 25.2 48 1 32.8 57 1 32.3 46 2 39.8 48 1 43.1 41 1
62.0 73 4 46.4 53 1 47.9 65 1 43.4 52 1 37.8 54 1 30.6 43 1
11.5 73 3 9.4 55 2 13.4 80 3 11.2 56 2 13.0 58 3 9.8 48 3
20.6 79 4 20.1 53 2 13.4 67 3 12.7 52 2 4.2 47 4 5.4 41 2
8.0 93 7 11.3 79 5 15.7 93 7 14.9 72 4 17.4 86 5 18.3 72 4
13.3 94 5 11.2 68 2 13.4 88 4 11.0 72 4 11.4 65 2 10.4 56 2
11.9 36 3 15.6 28 2 16.6 30 1 17.5 24 1 25.6 23 1 25.9 17 1
20.8 56 4 26.5 39 2 27.6 47 2 29.0 36 1 29.7 40 2 32.2 30 1
13.5 113 6 14.9 94 7 16.5 108 6 16.8 83 4 19.2 85 4 18.3 87 7
5.8 161 7 7.2 150 9 11.8 162 6 9.9 151 8 16.4 154 7 13.3 137 5
8.0 126 15 7.4 80 6 7.5 117 8 8.0 74 5 10.8 99 5 8.2 68 4
5.2 313 30 7.3 219 11 9.7 300 16 10.3 243 11 20.9 255 8 20.2 216 8
2.7 360a 42a 3.7 258 17 6.0 332 16 6.2 242 10 13.6 257 10 12.9 224 10
26.9 77 3 34.7 55 1 29.8 68 2 29.7 51 1 44.6 53 1 44.0 41 1
6.5 73 6 5.3 43 2 5.9 49 3 5.2 40 3 12.4 37 2 10.4 30 1
4.2 62 4 5.4 42 2 4.8 46 2 4.1 35 2 4.3 36 3 4.9 27 2
30.8 199 9 32.1 139 6 29.4 167 5 28.8 130 4 23.1 147 6 21.4 118 5
37.1 214 8 37.1 155 6 34.3 208 7 34.7 140 5 27.9 167 7 27.9 132 5
7.8 301 19 7.8 235 19 6.1 302 31 6.0 210 12 7.1 230 13 6.5 215 18
8.6 630 48 7.8 385 22 5.5 543 59 5.4 386 18 5.0 450 22 4.5 379 33
23.7 253 12 20.2 150 6 13.0 220 13 14.5 147 8 5.3 187 18 4.7 109 8
16.2 61 5 17.9 35 2 12.8 47 4 12.0 33 2 4.8 30 3 5.3 21 2
8.1 63 6 9.7 35 2 9.6 50 4 10.9 39 3 6.1 52 4 7.6 34 3
a Indicates a SE value that is greater than 0 but less than 0.5.
b Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation.
N = Sample size.
PC = Percent consuming at
least once in 2 days.
SE = Standard error of the mean.
Source: Smiciklas-Wright et al.,
2002, (based on 1994-1996 CSFII data).
Q
I
I
•s,
I
a'
I
ri
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-27. Consumption of Major Food Groups by Older Adults: Median Daily Servings (and Ranges) by
Subject Characteristic
Sex
Female
Male
Ethnicity
African American
European American
Native American
Age
70 to 74 years
75 to 79 years
80 to 84 years
>85 years
Marital Status
Married
Not Married
Education
8th grade or less
9th to 12th grades
>High School
Dentures
Yes
No
Chronic Diseases
0
1
2
3
>4
Weight"
<130 pounds
131 to 150 pounds
151 to 170 pounds
171 to 190 pounds
>191 pounds
p<0.05.
b 2 missing values.
N = Number of subjects.
Source: Vitolins et al, 2002.
Demographic and
N
80
50
44
47
39
42
36
36
16
49
81
37
47
46
83
47
7
31
56
26
10
18
32
27
22
29
Health Characteristics
Bread, Cereal, Rice and Pasta (servings/day)
a
2.7(0.9-6.5)
3.6(1.4-7.3)
3.3(1.4-6.4)
3.2 (0.9-6.8)
2.9(1.1-7.3)
3.3(1.1-6.3)
3.0 (0.9-6.8)
3.2(1.5-6.4)
3.6(1.6-7.3)
3.3(1.1-5.8)
3.0 (0.9-7.3)
3.1(1.1-7.3)
3.3(1.1-6.8)
3.2 (0.9-6.5)
3.3(1.1-6.4)
3.1(0.9-7.3)
4.1(2.2-6.4)
3.3 (0.9-7.3)
3.1(1.1-5.8)
3.7(1.1-5.8)
2.9(1.4-5.3)
3.1(1.1-5.4)
3.3 (0.9-5.2)
3.1(1.4-7.3)
3.6(1.4-6.2)
3.0(1.1-6.8)
Exposure Factors Handbook Page
September 2011 12-37
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-28. Characteristics
Sex
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
1 5 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
of the Feeding Infant and Toddlers Study
Sample Size
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
3,022
(FITS) Sample Population
Percentage of Sample
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
100.0
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Devaney et al, 2004.
Page
12-38
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-29. Percentage of Infants and Toddlers Consuming Different Types of Grain Products
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Grain or Grain Product
Infant Cereals
Non-infant Cereals*
Not Pre-sweetened
Pre-sweetenedb
Breads and Rolls0
Crackers, Pretzels, Rice Cakes
Cereal or Granola Bars
Pancakes, Waffles, French Toast
Rice and Pastad
Other
Grains in Mixed Dishes
Sandwiches
Burrito, Taco, Enchilada, Nachos
Macaroni and Cheese
Pizza
Pot Pie/Hot Pocket
Spaghetti, Ravioli, Lasagna
4 to 6
Months
65.8
64.8
0.6
0.5
0.0
0.6
3.0
0.0
0.1
2.3
0.2
0.4
0.0
0.0
0.2
0.1
0.0
0.1
7 to 8
Months
91.5
81.2
18.3
17.0
1.8
9.9
16.2
1.1
0.8
4.5
0.1
5.3
1.1
0.0
1.6
0.7
0.9
1.8
a Includes both ready-to-eat and cooked cereals.
b Defined as cereals with more than 21.1 grams sugar per
0 Does not include bread in sandwiches. Sandwiches are
d Does not include rice or pasta in mixed dishes.
Source: Fox et al, 2004.
9 to 11
Months
97.5
63.8
44.3
37.0
9.0
24.5
33.4
3.4
7.5
18.2
2.7
24.1
8.6
1.0
4.9
2.2
0.5
9.9
12 to 14
Months
97.8
23.9
58.9
44.5
17.7
47.3
45.2
9.8
15.1
26.2
2.8
48.3
21.5
4.5
14.6
6.8
2.0
15.3
15 to 18
Months
98.6
9.2
60.5
40.6
26.4
52.7
46.4
10.0
16.1
39.0
2.5
52.0
25.8
2.8
15.0
9.0
1.0
12.1
19 to 24
Months
99.2
3.1
51.9
31.9
22.7
53.1
44.7
9.7
15.4
35.9
4.5
55.1
25.8
2.1
15.0
9.4
1.8
8.8
100 grams.
included in mixed dishes.
Exposure Factors Handbook
September 2011
Page
12-39
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-30. Characteristics of Women, Infants, and Children
(percentages)
Sex
Male
Female
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Child's Race
White
Black
Other
Child in Daycare
Yes
No
Age of Mother
14 to 19 years
20 to 24 years
25 to 29 years
30 to 34 years
>35 years
Missing
Mother's Education
11th Grade or Less
Completed High School
Some Postsecondary
Completed College
Missing
Parent's Marital Status
Married
Not Married
Missing
Infants 4
WIC
Participant
55
45
20
80
69
15
22
39
61
18
33
29
9
9
2
23
35
33
7
2
49
50
1
to 6 month
Non-Participant
54
46
b
11
89
b
84
4
11
38
62
b
1
13
29
33
23
2
b
2
19
26
53
1
b
93
7
1
(WIC) Participants and Non-Participants"
Infants 7 to 1 1 month
WIC
Participant
55
45
24
76
63
17
20
34
66
13
38
23
15
11
1
15
42
32
9
2
57
42
1
Mother or Female Guardian Works
Yes
No
Missing
46
53
1
51
48
1
45
54
1
Non-Participant
51
49
b
8
92
b
86
5
9
b
46
54
b
1
11
30
36
21
1
b
2
20
27
51
0
b
93
7
0
b
60
40
0
Toddlers
WIC
Participant
57
43
22
78
67
13
20
43
57
9
33
29
18
11
0
17
42
31
9
1
58
41
1
55
45
0
12 to 24 month
Non-Participant
52
48
b
10
89
b
84
5
11
C
53
47
b
1
14
26
34
26
1
b
3
19
28
48
2
b
88
11
1
C
61
38
1
Page
12-40
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-30. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants"
(Percentages) (continued)
Infants 4 to 6 months
Infants 7 to 11 months
Toddlers 12 to 24 months
WIC WIC WIC
Participant Non-Participant Participant Non-Participant Participant Non-Participant
Urbanicity
Urban
Suburban
Rural
Missing
Sample Size (Unweighted)
34
36
28
2
265
55
31
13
1
597
37
31
30
2
351
50
34
15
1
808
35
35
28
2
205
48
35
16
2
791
X1 tests were conducted to test for statistical significance in the differences between WIC participants and non-
participants within each age group for each variable. The results of/ tests are listed next to the variable under the
column labeled non-participants for each of the three age groups.
= p < 0.05 non-participants significantly different from WIC participants on the variable.
= p < 0.01 non-participants significantly different from WIC participants on the variable.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al, 2004.
Table 12-31. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC) Participation
Status
Infant Cereals
Non-infant Cereals, Total
Not Pre-sweetened
Pre- sweetened
Grains in Combination Foods
Sample Size (unweighted)
Infants 4 to
WIC
Participant
69.7
0.9
0.5
0.0
0.9
265
6 months
Non-
Participant
62.5
0.5
0.5
0.0
0.1
597
Infants 7 to
WIC
Participant
74.7
21.7
18.7
4.0
18.8
351
11 months
Non-
Participant
69.7
38.5a
32.9a
6.9
14.7
808
Toddlers 12
WIC
Participant
13.5
58.1
43.7
17.7
50.3
205
to 24 months
Non-
Participant
9.2
56.0
36.3
24.1
52.9
791
a =P< 0.01 non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza etal., 2004.
Exposure Factors Handbook
September 2011
Page
12-41
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-32. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study
Food group
Infant cereal, dry
Infant cereal, jarred
Ready-to-eat cereal
Crackers
Crackers
Bread
= Cell size was too small to g
jV = Number of respondents.
SE = Standard error of the mean
Source: Fox etal., 2006.
4 to 5 months
Reference =
unit v '
tablespoon 3.1 ±0.1 4
tablespoon
tablespoon
ounce
saltine
slice
enerate a reliable estimate.
6 to 8 months
(^=708)
Mean ± SE
4. 5 ±0.14
5.6 ±0.26
2. 3 ±0.34
0.2 ± 0.02
2.2 ±0.14
0.5 ±0.10
9 to 1 1 months
(Af=687)
5.2±0.18
7.4 ±0.34
3.4 ±0.21
0.3 ±0.01
2.7 ±0.12
0.8 ±0.06
Table 12-33. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study
Food Group
Bread
Rolls
Ready-to-eat cereal
Hot cereal, prepared
Crackers
Crackers
Pasta
Rice
Pancakes and waffles
Reference Unit
slice
ounce
cup
cup
ounce
saltine
cup
cup
1 (4-inch diameter)
12 to 14 months
(tf=371)
0.8 ±0.04
0.9±0.11
0.3 ± 0.02
0.6 ±0.05
0.3 ±0.02
3. 3 ±0.22
0.4 ± 0.04
0.3 ±0.04
1.0 ±0.08
15 to 18 months
(N= 312)
Mean ± SE
0.9 ±0.05
1.0±0.10
0.5 ±0.03
0.6 ±0.05
0.4 ±0.02
3. 5 ±0.22
0.4 ±0.04
0.4 ±0.05
1.4 ±0.21
19 to 24 months
(jV=320)
0.9 ±0.05
0.9±0.15
0.6 ±0.04
0.7 ±0.05
0.4 ±0.02
3.7 ±0.22
0.5 ±0.05
0.4 ±0.05
1.4±0.17
jV = Number of respondents.
SE = Standard error of the mean.
Source: Fox etal., 2006.
Page
12-42
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-34. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
Grain Products on a Given Day
Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic Non-Hispanic Hispanic Non-Hispanic Hispanic Non-Hispanic
(AT =84) (AT =538) (AT =163) (AT = 1,228) (N= 124) (AT =871)
Any Grain or Grain Product
Infant Cereal
Non-infant Cereal
Breadsb
Tortillas
Crackers, Pretzels, Rice Cakes
Pancakes, Waffles, French Toast
Rice and Pastad
Rice
Grains in Mixed Dishes
Sandwiches
Burrito, Taco, Enchilada, Nachos
Macaroni and Cheese
Pizza
Spaghetti, Ravioli, Lasagna
56.5
55.2
1.4°
1.4C
1.3C
-
_
_
.
.
_
_
-
95.0
56.9 74.1
56.5 18.5a
18.2
4.0C
27.8
1.4C
20. r
15. 9e
ISO
1 J . y
4.0C
'. 1.3C
3.0C
_
8.3C
93.5
73.6
29.2
15.1
-
22.5
4.3
10.3
4.7
13.0
4.6
3.1
1.4
4.6
97.1
15.9
45.3
44.0
35.6
13.0
44.3
26.9a'°
oo oa
JO.O
24.2
2.1C
10.1
1.0c'e
9.3C
98.9
9.3
57.8
52.9
0.6C
46.9
16.0
32.9
13.0
54.4
24.9
3.0
15.5
9.7
12.1
a = Significantly different from non-Hispanic atp < 0.05.
b Does not include bread in sandwiches. Sandwiches are included in mixed dishes. Includes tortillas, also shown
separately.
0 = Statistic is potentially unreliable because of a high coefficient of variation.
d Does not include rice or pasta in mixed dishes. Includes rice (e.g., white, brown, wild, and Spanish rice without meat)
and pasta (e.g., spaghetti, macaroni, and egg noodles). Rice is also shown separately.
e = Significantly different from non-Hispanic atp < 0.01.
= Less than 1% of the group consumed this food on a given day.
N = Sample size.
Source: Mennella et al, 2006.
Exposure Factors Handbook
September 2011
Page
12-43
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Exposure Factors Handbook
Chapter 12—Intake of Grain Products
Table 12-35. Mean Moisture Content of Selected Grain Products Expressed as Percentages of Edible
Portions (grams per 100 grams of edible portion)
Food
Barley — pearled
Corn — grain — endosperm
Corn — grain — bran
Millet
Oats
Rice — white — long-grained
Rye
Rye — flour — medium
Sorghum
Wheat — hard white
Wheat — germ
Wheat — bran
Wheat — flour — whole grain
Moisture Content
Raw Cooked
10.09 68.80
10.37
4.71 - crude
8.67 71.41
8.22
11.62 68.44
10.95
9.85
9.20
9.57
11.12 - crude
9.89 - crude
10.27
Indicates that the grain product was not assessed for water content under these conditions.
Source: USDA, 2007.
Page Exposure Factors Handbook
12-44 September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
TABLE OF CONTENTS
LIST OF TABLES 13-ii
13. INTAKE OF HOME-PRODUCED FOODS 13-1
13.1. INTRODUCTION 13-1
13.2. RECOMMENDATIONS 13-1
13.3. KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS 13-5
13.3.1. U.S. EPA Analysis of NFCS 1987-1988; Moya and Phillips (2001) Analysis of
Consumption of Home-Produced Foods 13-5
13.3.2. Phillips and Moya (2011) 13-9
13.4. RELEVANT STUDY FOR INTAKE OF HOME-PRODUCED FOODS 13-10
13.4.1. National Gardening Association (2009) 13-10
13.5. REFERENCES FOR CHAPTER 13 13-10
APPENDIX 13A FOOD CODES AND DEFINITIONS OF MAJOR FOOD GROUPS USED IN THE
ANALYSIS 13A-1
APPENDIX 13B 1987-1988 NFCS FOOD CODES AND DEFINITIONS OF INDIVIDUAL FOOD
ITEMS USED IN ESTIMATING THE FRACTION OF HOUSEHOLD FOOD
INTAKE THAT IS HOME-PRODUCED 13B-1
Exposure Factors Handbook Page
September 2011 13-i
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
LIST OF TABLES
Table 13-1. Summary of Recommended Values for Intake of Home-Produced Foods 13-2
Table 13-2. Confidence in Recommendations for Intake of Home-Produced Foods 13-4
Table 13-3. Subcategory Codes, Definitions, and Descriptions 13-12
Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in
Analysis of Food Intake 13-13
Table 13-5. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—All Regions Combined 13-14
Table 13-6. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Northeast 13-15
Table 13-7. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Midwest 13-16
Table 13-8. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—South 13-17
Table 13-9. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—West 13-18
Table 13-10. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—All Regions
Combined 13-19
Table 13-11. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Northeast 13-20
Table 13-12. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Midwest 13-21
Table 13-13. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—South 13-22
Table 13-14. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—West 13-23
Table 13-15. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—All Regions Combined 13-24
Table 13-16. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Northeast 13-25
Table 13-17. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Midwest 13-26
Table 13-18. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—South 13-27
Table 13-19. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—West 13-28
Table 13-20. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—All Regions Combined 13-29
Table 13-21. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Northeast 13-30
Table 13-22. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Midwest 13-31
Table 13-23. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—South 13-32
Table 13-24. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—West 13-33
Table 13-25. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—All Regions 13-34
Table 13-26. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Northeast 13-35
Table 13-27. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Midwest 13-36
Table 13-28. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—South 13-37
Table 13-29. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—West 13-38
Table 13-30. Seasonally Adjusted Consumer-Only Home-Produced Intake (g/kg-day) 13-39
Table 13-31. Consumer-Only Intake of Home-Produced Apples (g/kg-day) 13-40
Table 13-32. Consumer-Only Intake of Home-Produced Asparagus (g/kg-day) 13-41
Table 13-33. Consumer-Only Intake of Home-Produced Beef (g/kg-day) 13-42
Table 13-34. Consumer-Only Intake of Home-Produced Beets (g/kg-day) 13-43
Table 13-35. Consumer-Only Intake of Home-Produced Broccoli (g/kg-day) 13-44
Table 13-36. Consumer-Only Intake of Home-Produced Cabbage (g/kg-day) 13-45
Table 13-37. Consumer-Only Intake of Home-Produced Carrots (g/kg-day) 13-46
Table 13-38. Consumer-Only Intake of Home-Produced Corn (g/kg-day) 13-47
Table 13-39. Consumer-Only Intake of Home-Produced Cucumbers (g/kg-day) 13-48
Table 13-40. Consumer-Only Intake of Home-Produced Eggs (g/kg-day) 13-49
Table 13-41. Consumer-Only Intake of Home-Produced Game (g/kg-day) 13-50
Table 13-42. Consumer-Only Intake of Home-Produced Lettuce (g/kg-day) 13-51
Table 13-43. Consumer-Only Intake of Home-Produced Lima Beans (g/kg-day) 13-52
Table 13-44. Consumer-Only Intake of Home-Produced Okra (g/kg-day) 13-53
Table 13-45. Consumer-Only Intake of Home-Produced Onions (g/kg-day) 13-54
Table 13-46. Consumer-Only Intake of Home-Produced Other Berries (g/kg-day) 13-55
Table 13-47. Consumer-Only Intake of Home-Produced Peaches (g/kg-day) 13-56
Table 13-48. Consumer-Only Intake of Home-Produced Pears (g/kg-day) 13-57
Table 13-49. Consumer-Only Intake of Home-Produced Peas (g/kg-day) 13-58
Table 13-50. Consumer-Only Intake of Home-Produced Peppers (g/kg-day) 13-59
Table 13-51. Consumer-Only Intake of Home-Produced Pork (g/kg-day) 13-60
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Chapter 13—Intake of Home-Produced Foods
LIST OF TABLES (continued)
Table 13-52. Consumer-Only Intake of Home-Produced Poultry (g/kg-day) 13-61
Table 13-53. Consumer-Only Intake of Home-Produced Pumpkins (g/kg-day) 13-62
Table 13-54. Consumer-Only Intake of Home-Produced Snap Beans (g/kg-day) 13-63
Table 13-55. Consumer-Only Intake of Home-Produced Strawberries (g/kg-day) 13-64
Table 13-56. Consumer-Only Intake of Home-Produced Tomatoes (g/kg-day) 13-65
Table 13-57. Consumer-Only Intake of Home-Produced White Potatoes (g/kg-day) 13-66
Table 13-58. Consumer-Only Intake of Home-Produced Exposed Fruit (g/kg-day) 13-67
Table 13-59. Consumer-Only Intake of Home-Produced Protected Fruits (g/kg-day) 13-68
Table 13-60. Consumer-Only Intake of Home-Produced Exposed Vegetables (g/kg-day) 13-69
Table 13-61. Consumer-Only Intake of Home-Produced Protected Vegetables (g/kg-day) 13-70
Table 13-62. Consumer-Only Intake of Home-Produced Root Vegetables (g/kg-day) 13-71
Table 13-63. Consumer-Only Intake of Home-Produced Dark Green Vegetables (g/kg-day) 13-72
Table 13-64. Consumer-Only Intake of Home-Produced Deep Yellow Vegetables (g/kg-day) 13-73
Table 13-65. Consumer-Only Intake of Home-Produced Other Vegetables (g/kg-day) 13 -74
Table 13-66. Consumer-Only Intake of Home-Produced Citrus (g/kg-day) 13-75
Table 13-67. Consumer-Only Intake of Home-Produced Other Fruit (g/kg-day) 13-76
Table 13-68. Fraction of Food Intake That Is Home-Produced 13-77
Table 13-69. Percent Weight Losses from Food Preparation 13-81
Table 13-70. Estimated Age-Specific Per Capita Home-Produced Intake (adjusted; g/kg-day) 13-82
Table 13-71. 2008 Food Gardening by Demographic Factors 13-83
Table 13-72. Percentage of Gardening Households Growing Different Vegetables in 2008 13-84
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13. INTAKE OF HOME-PRODUCED
FOODS
13.1. INTRODUCTION
Ingestion of home-produced foods can be a
pathway for exposure to environmental contaminants.
Home-produced foods can become contaminated in
various ways. Ambient pollutants in the air may be
deposited on plants, adsorbed onto or absorbed by the
plants, or dissolved in rainfall or irrigation waters that
contact the plants. Pollutants also may be adsorbed
onto plant roots from contaminated soil and water.
Finally, the addition of pesticides, soil additives, and
fertilizers to crops or gardens may result in
contamination of food products. Meat and dairy
products can become contaminated if animals
consume contaminated soil, water, or feed crops.
Farmers, as well as rural and urban residents who
consume home-produced foods, may be potentially
exposed if these foods become contaminated.
Exposure via the consumption of home-produced
foods may be a significant route of exposure for these
populations (U.S. Environmental Protection Agency
[EPA], 1989, 1996). For example, consumption of
home-produced fruits, vegetables, game, and fish has
been shown to have an effect on blood lead levels in
areas where soil lead contamination exists (U.S. EPA,
1994). At Superfund sites where soil contamination is
found, ingestion of home-produced foods has been
considered a potential route of exposure (U.S. EPA,
1991, 1993). Assessing exposures to individuals who
consume home-produced foods requires knowledge
of intake rates of such foods.
Data from the 1987-1988 Nationwide Food
Consumption Survey (NFCS) were used to generate
intake rates for home-produced foods. The methods
used to analyze the 1987-1988 NFCS data are
presented in Section 13.3.
13.2. RECOMMENDATIONS
The data presented in this section may be used to
assess exposure to contaminants in foods grown,
raised, or caught at a specific site. Table 13-1 presents
the recommended values for mean and upper
percentile (i.e., 95th percentile) intake rates among
consumers of the various home-produced food
groups. The consumer-only data presented represent
average daily intake rates of food items/groups over
the 7-day survey period and do not account for
variations in eating habits during the rest of the year.
Thus, the recommended upper- percentile values, as
well as the percentiles of the distributions presented
in Section 13.3.1 may not necessarily reflect the
long-term distribution of average daily intake of
home-produced foods. Table 13-1 also provides
mean and 95th percentile per capita intake rates for
populations that garden, farm, or raise animals. Table
13-2 presents the confidence ratings for home-
produced food intake.
Because the consumer-only home-produced food
intake rates presented in this chapter (See Section
13.3.1) are based on foods as brought into the
household and not in the form in which they are
consumed, preparation loss factors should be applied
as appropriate. These factors are necessary to convert
intake rates to those that are representative of foods
"as consumed." The per capita data presented in this
chapter (See Section 13.3.2) account for preparation
and post-cooking losses. Additional conversions may
be necessary for both consumer-only and per capita
data to ensure that the form of the food used to
estimate intake (e.g., wet or dry weight) is consistent
with the form used to measure contaminant
concentration (see Section 13.3).
The NFCS data used to generate intake rates of
home-produced foods are more than 20 years old and
may not be reflective of current eating patterns
among consumers of home-produced foods. Although
the U.S. Department of Agriculture (USDA) and
others have conducted other food consumption
studies since the release of the 1987-1988 NFCS,
these studies do not include information on
home-produced foods.
Because the consumer-only analysis was
conducted prior to the issuance of EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005), the age groups used
are not entirely consistent with recent guidelines.
Also, recommended home-produced food intake rates
are not provided for children less than 1 year of age
because the methodology used is based on the
apportionment of home-produced foods used by a
household among the members of that household
who consume those foods. It was assumed that the
diets of children under 1 year of age differ markedly
from that of other household members; thus, they
were not assumed to consume any portion of the
home-produced food brought into the home.
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Chapter 13—Intake of Home-Produced Foods
Table 13-1.
Age Groupa
Summary of Recommended Values for Intake of Home-Produced Foods
Mean
gS^Percentile Multiple
g/kg-day Percentiles
Source
Home-Produced Fruits
Consumers Only, Unadjusted15
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
8.7
4.1
3.6
1.9
2.0
2.7
2.3
60.6
8.9
15.8
8.3 See Table 13-5
6.8
13.0
8.7
U.S. EPA Analysis of
1987-1 988 NFCS
Per Capita for Populations that Garden or (Farm), Adjusted0
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <50 years
50+ years
1.0 (1.4)
1.0 (1.4)
0.78(1.0)
0.40 (0.52)
0.13(0.17)
0.13(0.17)
0.15(0.20)
0.24(0.31)
4.8(9.1)
4.8(9.1)
3.6(6.8)
1.9(3.5)
0.62(1.2)
0.62(1.2)
0.70(1.3)
1.1(2.1)
Phillips and Moy a, 20 11
Home-Produced Vegetables
Consumers Only, Unadjusted15
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
5.2
2.5
2.0
1.5
1.5
2.1
2.5
19.6
7.7
6.2
6.0 See Table 13-10
4.9
6.9
8.2
U.S. EPA Analysis of
1987-1 988 NFCS
Per Capita for Populations that Garden or (Farm), Adjusted0
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
21 to <50 years
50+ years
1.3(2.7)
1.3(2.7)
1.1(2.3)
0.80(1.6)
0.56(1.1)
0.56(1.1)
0.56(1.1)
0.60(1.2)
7.1 (14)
7.1 (14)
6.1(12)
4.2(8.1)
3.0 (5.7) iNA
3.0 (5.7)
3.0 (5.7)
3.2(6.1)
Phillips and Moy a, 2011
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Table 13-1. Summary of Recommended Values for Intake of Home-Produced Foods (continued)
Age Group8
Mean 95th Percentile Multiple
g/kg-day Percentiles
Home-Produced Meats
Consumers Only, Unadjusted1"
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
20 to 39 years
40 to 69 years
>70 years
3.7 10.0
3.6 9.1
,' ., c TUI n ic U.S. EPA Analysis of
.7 4.3 See Table 13-15 1987_1988 ^
l.o D.2
1.7 5.2
1.4 3.5
Per Capita for Populations that Farm or (Raise Animals), Adjusted0
1 to <2 years
2 to <3 years
3 to <6 years
6 to70 years
d
28 71
,'- ,'_ „ ^ , , ,, ~n U.S. EPA Analysis of
1.5 4.7 See Table 13-20 1987_1988^cs
1.8 4.4
1.2 3.7
a Analysis was conducted prior to Agency's issuance of Guidance on Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005).
b Not adjusted to account for preparation or post-cooking losses.
0 Adjusted for preparation and post-cooking losses.
d Data not presented for age groups/food groups where less than 20 observations were available.
NA = Not available.
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Table 13-2. Confidence in Recommendations for Intake of Home-Produced Foods
General Assessment Factors
Rationale
Ratine
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The NFCS survey methodology and the approach to
data analysis were adequate, but individual intakes
were inferred from household consumption data.
The sample size was large (approximately 10,000
individuals).
Non-response bias cannot be ruled out due to low
response rate. Also, some biases may have occurred
from using household data to estimate individual
intake.
Medium (Means)
Low (Distributions)
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The U.S. EPA analysis of the NFCS data
specifically addressed home-produced intake.
Data from a nationwide survey, representative of
the general U.S. population was used.
The data were collected in 1987-1988.
Household data were collected over 1 week.
Low (Means and short-term
distributions)
Low (Long-term distributions)
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The methods used to analyze the data are described
in detail in this handbook; the primary data are
accessible through USDA.
Sufficient details on the methods used to analyze
the data are presented to allow the results to be
reproduced.
Quality assurance of NFCS data was good; quality
control of the secondary data was sufficient.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Low to Medium
Full distributions of home-produced intake rates
were provided in the NFCS analysis. Phillips and
Moya (2011) presented mean and 95th percentile
values.
Sources of uncertainty include: individuals'
estimates of food weights, allocation of household
food to family members, and potential changes in
eating patterns since these data were collected.
Evaluation and Review
Peer Review
Medium
The study was reviewed by USDA and EPA.
Number and Agreement of Studies There was one key study that described the primary
analysis of NFCS data and 1 key study that
described a secondary analysis of the NFCS home-
produced data.
Overall Rating
Low to Medium (Means and short-
term distributions)
Low (Long-term distributions)
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13.3. KEY STUDY FOR INTAKE OF HOME-
PRODUCED FOODS
13.3.1. U.S. EPA Analysis of NFCS 1987-1988;
Moya and Phillips (2001) Analysis of
Consumption of Home-Produced Foods
U.S. EPA's National Center for Environmental
Assessment (NCEA) analyzed USDA's 1987-1988
NFCS data to generate intake rates for
home-produced foods. In addition, Moya and Phillips
(2001) present a summary of these analyses. For the
purposes of this study, home-produced foods were
defined as home-produced fruits and vegetables, meat
and dairy products derived from consumer-raised
livestock or game meat, and home-caught fish.
Until 1988, USD A conducted the NFCS every
10 years to analyze the food consumption behavior
and dietary status of Americans (USDA, 1992).
While more recent food consumption surveys have
been conducted to estimate food intake among the
general population (e.g., USDA's Continuing Survey
of Food Intake by Individuals [CSFII] and the
National Health and Nutrition Examination Survey
[NHANES]), these surveys have not collected data
that can be used to estimate consumption of
home-produced foods. Thus, the 1987-1988 NFCS
data set is currently the best available source of
information for this factor.
The 1987-1988 NFCS was conducted between
April 1987 and August 1988. The survey used a
statistical sampling technique designed to ensure that
all seasons, geographic regions of the
48 conterminous states in the United States, and
socioeconomic and demographic groups were
represented (USDA, 1994). There were two
components of the NFCS. The household component
collected information over a 7-day period on the
socioeconomic and demographic characteristics of
households, as well as the types, amount, value, and
sources of foods consumed by the household (USDA,
1994). Meanwhile, the individual intake component
collected information on food intakes of individuals
within each household over a 3-day period (USDA,
1993). The sample size for the 1987-1988 survey
was approximately 4,300 households (more
than 10,000 individuals; approximately
3,000 children). This was a decrease from the
previous survey conducted in 1977-1978, which
sampled approximately 15,000 households (more
than 36,000 individuals) (USDA, 1994). The sample
size was lower in the 1987-1988 survey as a result of
budgetary constraints and low response rate (38% for
the household survey and 31% for the individual
survey; USDA, 1993).
The USDA data were adjusted by applying
sample weights calculated by USDA to the data set
prior to analysis. The USDA sample weights were
designed to "adjust for survey non-response and other
vagaries of the sample selection process" (USDA,
1987-1988). Also, the USDA weights are calculated
"so that the weighted sample total equals the known
population total, in thousands, for several
characteristics thought to be correlated with eating
behavior" (USDA, 1987-1988).
The food groups selected for analysis of
home-produced food intake included major food
groups (i.e., total fruits, total vegetables, total meats,
total dairy, total fish and shellfish) and individual
food items for which greater than 30 households
reported eating the home-produced form of the item;
fruits and vegetables categorized as exposed,
protected, and roots; and various USDA fruit and
vegetable subcategories (e.g., dark green vegetables,
citrus fruits). These food groups were identified in
the NFCS data base according to NFCS-defined food
codes. Appendix 13A presents the codes and
definitions used to determine the major food groups.
Foods with these codes, for which the source was
identified as home-produced, were included in the
analysis. The codes and definitions for individual
items in these food groups, as well as other
subcategories (e.g., exposed, protected, dark green,
citrus) considered to be home-produced are in
Appendix 13B.
Although the individual intake component of the
NFCS gives the best measure of the amount of each
food group eaten by each individual in the household,
it could not be used directly to measure consumption
of home-produced food because the individual
component does not identify the source of the food
item (i.e., as home-produced or not). Therefore, an
analytical method that incorporated data from both
the household and individual survey components was
developed to estimate individual home-produced
food intake.
The household data were used to determine
(1) the amount of each home-produced food items
used during a week by household members, and
(2) the number of meals eaten in the household by
each household member during a week. Note that the
household survey reports the total amount of each
food item used in the household (whether by guests
or household members); the amount used by
household members was derived by multiplying the
total amount used in the household by the proportion
of all meals served in the household (during the
survey week) that were consumed by household
members. The individual survey data were used to
generate average sex- and age-specific serving sizes
for each food item. The age categories used in the
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Chapter 13—Intake of Home-Produced Foods
analysis were as follows: 1 to 2 years, 3 to 5 years,
6 to 11 years, 12 to 19 years, 20 to 39 years, 40 to
69 years, and 70 years and older (intake rates were
not calculated for children under 1 year of age; the
rationale for this is discussed after equation 13-1).
The serving sizes were used during subsequent
analyses to generate home-produced food intake rates
for individual household members. Assuming that the
proportion of the household quantity of each
home-produced food item/group was a function of
the number of meals and the mean sex- and age-
specific serving size for each family member,
individual intakes of home-produced food were
calculated for all members of the survey population
using the following general equation:
W- = W:
(Eqn. 13-1)
where:
w, = Home-produced amount of food
item/group attributed to member
/ during the week (g/week),
Wf = Total quantity of home-produced
food item/group used by the family
members (g/week),
mt = Number of meals of household
food consumed by member / during
the week (meals/week), and
qt = Serving size for an individual
within the age and sex category of
the member (g/meal).
Daily intake of a home-produced food group was
determined by dividing the weekly value (w,) by 7.
Intake rates were indexed to the self-reported body
weight of the survey respondent and reported in units
of g/kg-day. Intake rates were not calculated for
children less than 1 year of age because their diet
differs markedly from that of other household
members, and, thus, the assumption that all members
share all foods would be invalid for this age group.
For the major food groups (i.e., fruits, vegetables,
meats, dairy, and fish) and individual foods
consumed by at least 30 households, distributions of
home-produced intake among consumers were
generated for the entire data set and for the following
subcategories: age groups, urbanization categories,
seasons, racial classifications, regions, and responses
to a questionnaire.
Consumers were defined as members of survey
households who reported consumption of the food
item/group of interest during the 1-week survey
period.
In addition, for the major food groups,
distributions were generated for each region by
season, urbanization, and responses to the
questionnaire. Table 13-3 presents the codes,
definitions, and a description of the data included in
each of the subcategories. Intake rates were not
calculated for food items/groups for which less than
30 households reported home-produced usage
because the number of observations may be
inadequate for generating distributions that would be
representative of that segment of consumers. Fruits
and vegetables were also classified as exposed,
protected, or roots, as shown in Appendix 13B.
Exposed foods are those that are grown above ground
and are likely to be contaminated by pollutants
deposited on surfaces of the foods that are eaten.
Protected products are those that have outer
protective coatings that are typically removed before
consumption.
Distributions of intake were tabulated for these
food classes for the same subcategories listed
previously. Distributions were also tabulated for the
following USD A food classifications: dark green
vegetables, deep yellow vegetables, other vegetables,
citrus fruits, and other fruits. Finally, the percentages
of total intake of the food items/groups consumed
within survey households that can be attributed to
home production were tabulated. The percentage of
intake that was home-produced was calculated as the
ratio of total intake of the home-produced food
item/group by the survey population to the total
intake of all forms of the food by the survey
population.
Percentiles of average daily intake derived from
short-time intervals (e.g., 7 days) will not, in general,
be reflective of long-term patterns. This is especially
true in regards to consumption of many
home-produced products (e.g., fruits, vegetables),
where a strong seasonal component often is
associated with their use. For the major food
categories, to try to derive the long-term distribution
of average daily intake rates from the short-term data
available here, an approach was developed that
attempted to account for seasonal variability in
consumption. This approach used regional
"seasonally adjusted distributions" to approximate
regional long-term distributions and then combined
these regional adjusted distributions (in proportion to
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Chapter 13—Intake of Home-Produced Foods
the weights for each region) to obtain a U.S. adjusted
distribution that approximated the U.S. long-term
distribution. See Moya and Phillips (2001) for details.
The percentiles of the seasonally adjusted
distribution for a given region were generated by
averaging the corresponding percentiles of each of
the four seasonal distributions of the region. More
formally, the seasonally adjusted distribution for each
region is such that its inverse cumulative distribution
function is the average of the inverse cumulative
distribution functions of each of the seasonal
distributions of that region. The use of regional
seasonally adjusted distributions to approximate
regional long-term distributions is based on the
assumption that each individual consumes the same
regional percentile levels for each season and
consumes at a constant weekly rate throughout a
given season. For instance, if the 60th percentile
weekly intake level in the South is 14.0 grams in the
summer and 7.0 grams in each of the three other
seasons, then the individual in the South with an
average weekly intake of 14.0 grams during the
summer is assumed to have an intake of 14.0 grams
for each week of the summer and an intake of
7.0 grams for each week of the other seasons.
Note that the seasonally adjusted distributions
were generated using the overall distributions (i.e.,
both consumers and non-consumers). However,
because all the other distributions presented in this
section are based on consumers only, the percentiles
for the adjusted distributions have been revised to
reflect the percentiles among consumers only. Given
the assumption about how each individual consumes,
the percentage consuming for the seasonally adjusted
distributions gives an estimate of the percentage of
the population consuming the specified food category
at any time during the year.
The intake data presented in this chapter for
consumers of home-produced foods and the total
number of individuals surveyed may be used to
calculate the mean and the percentiles of the
distribution of home-produced food consumption in
the overall population (consumers and
non-consumers) as follows:
Assuming that IRP is the home-produced intake
rate of the food group at the p^ percentile and Nc is
the weighted number of individuals consuming the
home-produced food item, and NT is the weighted
total number of individuals surveyed, then NT - Nc is
the weighted number of individuals who reported
zero consumption of the food item. In addition, there
are (p /100 x Nc) individuals below the />*percentile.
Therefore, the percentile that corresponds to a
particular intake rate (IRJ for the overall distribution
of home-produced food consumption (including
consumers and non-consumers) can be obtained by:
-t—xN + (NT-N)
PL* = 100x^1™ L (Eqn. 13-2)
For example, the percentile of the overall
population that is equivalent to the 50th percentile
consumer-only intake rate for home-produced fruits
would be calculated as follows:
From Table 13-5, the 50th percentile
home-produced fruit intake rate (IRsd) is
1.07 g/kg-day. The weighted number of
individuals consuming fruits (Nc) is 14,744,000.
From Table 13-4, the weighted total number of
individuals surveyed (NT) is 188,019,000. The
number of individuals consuming fruits below the
50th percentile is
p/100xNc = (0.5) x (14,744,000)
= 7,372,000
The number of individuals that did not consume
fruit during the survey period is
NT - Nc = 188, 019, 000 - 14, 744, 000
= 173,275,000
The total number of individuals with
home-produced intake rates at or below
1.07 g/kg-day is
/ 100
J = 7,372,000
+ 173,275,000
= 180,647,000
The percentile of the overall population that is
represented by this intake rate is
Pth overall 100 x (180,647,000/188,019,000)
96th percentile
Therefore, an intake rate of 1.07 g/kg-day of
home-produced fruit corresponds to the 96th
percentile of the overall population.
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Chapter 13—Intake of Home-Produced Foods
Following this same procedure, 5.97 g/kg-day,
which is the 90th percentile of the consumers-only
population, corresponds to the 99th percentile of the
overall population. Likewise, 0.063 g/kg-day, which
is the 1st percentile of the consumers-only population,
corresponds to the 92nd percentile of the overall
population. Note that the consumers-only distribution
corresponds to the tail of the distribution for the
overall population. Consumption rates below the 92nd
percentile are very close to zero. The mean intake
rate for the overall population can be calculated by
multiplying the mean intake rate among consumers
by the proportion of individuals consuming the
home-produced food item Nc /NT.
Table 13-4 displays the weighted numbers NT and
the unweighted total survey sample sizes for each
subcategory and overall. Note that the total
unweighted number of observations in Table 13-4
(9,852) is somewhat lower than the number of
observations reported by USD A; this study only used
observations for family members for which age and
body weight were specified.
The intake rate distributions (among consumers)
for total home-produced fruits, vegetables, meats,
fish, and dairy products are shown, respectively, in
Tables 13-5 through 13-29. These tables also show
the proportion of respondents consuming the item
during the (1-week) survey period. Home-produced
vegetables were the most commonly consumed of the
major food groups (18.3%), followed by fruit (7.8%),
meat (4.9%), fish (2.1%), and dairy products (0.7%).
The intake rates for the major food groups varied
according to region, age, urbanization code, race, and
responses to survey questions. In general, intake rates
of home-produced foods were higher among
populations in non-metropolitan and suburban areas
and lowest in central city areas. Results of the
regional analyses indicate that intake of
home-produced fruits, vegetables, meat, and dairy
products was generally highest for individuals in the
Midwest and South regions and lowest for those in
the Northeast region. Intake rates of home-caught
fish were generally highest among consumers in the
South. Home-produced intake was generally higher
among individuals who indicated that they operate a
farm, grow their own vegetables, raise animals, and
catch their own fish. The results of the seasonal
analyses for all regions combined indicate that, in
general, home-produced fruits and vegetables were
eaten at a higher rate in summer and home-caught
fish was consumed at a higher rate in spring;
however, seasonal intake varied based on individual
regions. Table 13-30 presents seasonally adjusted
intake rate distributions for the major food groups.
Tables 13-31 through 13-57 show distributions of
intake for individual home-produced food items for
households that reported consuming the
home-produced form of the food during the survey
period. Intake rate distributions among consumers for
home-produced foods categorized as exposed fruits
and vegetables, protected fruits and vegetables, and
root vegetables are presented in Tables 13-58 through
13-62; the intake distributions for various USDA
classifications (e.g., dark green vegetables) are
presented in Tables 13-63 through 13-67. The results
are presented in units of g/kg-day. Table 13-68
presents the fraction of household intake attributed to
home-produced forms of the food items/groups
evaluated. Thus, use of these data in calculating
potential dose does not require the body-weight
factor to be included in the denominator of the
average daily dose in equation 1-2 in Chapter 1. Note
that converting these intake rates into units of g/day
by multiplying by a single average body weight is
inappropriate, because individual intake rates were
indexed to the reported body weights of the survey
respondents.
As mentioned previously, the intake rates derived
in this section are based on the amount of household
food consumption. As measured by the NFCS, the
amount of food consumed by the household is a
measure of consumption in an economic sense (i.e., a
measure of the weight of food brought into the
household that has been consumed [used up] in some
manner). In addition to food being consumed by
persons, food may be used up by spoiling, by being
discarded (e.g., inedible parts), through cooking
processes, and other methods.
USDA estimated preparation losses for various
foods (USDA, 1975). For meats, a net cooking loss,
which includes dripping and volatile losses, and a net
post-cooking loss, which involves losses from
cutting, bones, excess fat, scraps and juices, were
derived for a variety of cuts and cooking methods.
For each meat type, U.S. EPA has averaged these
losses across all cuts and cooking methods to obtain a
mean net cooking loss and a mean net post-cooking
loss. Table 13-69 provides mean percentage values
for all meats and fish. For individual fruits and
vegetables, USDA (1975) also gave cooking and
post-cooking losses. These data, averaged across all
types of fruits and vegetables to give mean net
cooking and post-cooking losses, also are provided in
Table 13-69.
The formula presented in equation 13-3 can be
used to convert the home-produced intake rates
tabulated here to rates reflecting actual consumption:
I = I x (l - L ) x (l - L ) (Eqn. 13-3)
Page
13-8
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September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
where:
I A = the adjusted intake rate,
/ = the tabulated intake rate,
LI = the cooking or preparation loss, and
L2 = the post-cooking loss.
Corrections based on post-cooking losses only apply
to fruits that are eaten in cooked forms. For raw
forms of the fruits, paring or preparation loss data
should be used to correct for losses from the removal
of skin, peel, core, caps, pits, stems, and defects, or
from the draining of liquids from canned or frozen
forms. To obtain preparation losses for food
categories, the preparation losses of the individual
foods making up the category can be averaged.
In calculating ingestion exposure, assessors
should use consistent forms (e.g., as consumed or dry
weight) in combining intake rates with contaminant
concentrations (see Chapter 9).
The USDA NFCS data set is the largest publicly
available source of information on home-produced
food consumption habits in the United States. The
advantages of using this data set are that it is
expected to be representative of the U.S. population
and that it provides information on a wide variety of
food groups. However, the data collected by the
USDA NFCS are based on short-term dietary recall,
and the intake distributions generated from this data
set may not accurately reflect long-term intake
patterns, particularly with the tails (extremes) of the
distributions. Also, the two survey components (i.e.,
household and individual) do not define food
items/groups in a consistent manner; as a result, some
errors may be introduced into these analyses because
the two survey components are linked. The results
presented in this chapter also may be biased by
assumptions that are inherent in the analytical method
utilized. The analytical method may not capture all
high-end consumers within households because
average serving sizes are used in calculating the
proportion of home-produced food consumed by each
household member. Thus, for instance, in a
two-person household in which one member had high
intake and another had low intake, the method used
would assume that both members had an equal and
moderate level of intake. In addition, the analyses
assume that all family members consume a portion of
the home-produced food used within the household.
However, not all family members may consume each
home-produced food item, and serving sizes allocated
in this instance may not be entirely representative of
the portion of household foods consumed by each
family member. As was mentioned earlier, no
analyses were performed for children under 1 year of
age.
The preparation loss factors discussed previously
are intended to convert intake rates based on
"household consumption" to rates reflective of what
individuals actually consume. However, these factors
do not include losses to spoilage, feeding to pets,
food thrown away, and other methods. It also should
be noted that because this analysis is based on the
1987-1988 NFCS, it may not reflect recent changes
in food consumption patterns. The low response rate
associated with the 1987-1988 NFCS also
contributes to the uncertainty of the home-produced
intake rates generated using these data.
13.3.2. Phillips and Moya (2011)—Estimation of
Age-Specific Per Capita Home-Produced
Food Intake Among Populations That
Garden, Farm, or Raise Animals
Phillips and Moya (2011) used the consumer
intake data for home-produced fruits, vegetables,
meats, and dairy products from the analysis described
in Section 13.3.1 to estimate per capita intake rates
for the populations that garden, farm, or raise
animals. The consumer-only intake values in
Section 13.3.1 are based on short-term dietary survey
data and may be appropriate for estimating short-term
intake, but may over-estimate exposure over longer
time periods. Also, the intake rates in Section 13.3.1
represent intake of foods brought into the household
and have not been adjusted to account for preparation
losses and post-cooking losses. Phillips and Moya
(2011) converted the distribution of consumer-only
intake rates for populations that garden, farm, and
raise animals to the distribution of per capita rates
using equation 13-2 and adjusted these data to
account for preparation losses and post-cooking
losses using equation 13-3. Data for households that
garden, farm, or raise animals were used because
they were assumed to represent both households who
ate home-produced foods during the survey period as
well as those who did not eat home-produced foods
during the survey period, but may eat these foods at
some other time during the year. Also, the data in
Section 13.3.1 for the populations that garden, farm,
or raise animals are not provided by age group, but
represent data for all ages of the survey population
combined. Phillips and Moya (2011) calculated age-
specific intake rates using ratios of age-specific
dietary intake to total population intake rates, based
on survey data for intake of total fruits, vegetables,
meats, and dairy from all sources (i.e., both home-
produced and commercial sources) from the 1994-
1996, 1998 CSFII, as described in Chapters 9 and 11.
Exposure Factors Handbook
September 2011
Page
13-9
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
The age groups used are those recommended in U.S.
EPA (2005). Age-specific intake mean and 95th
percentile intake rates were estimated as: age-
specific ratio x mean (or 95th percentile) per capita
intake for the total population, where the age-specific
ratio = age-specific mean per capita total intake
(g/kg-day)/ total population mean per capita total
intake (g/kg-day). Table 13-70 provides the both the
adjusted and unadjusted estimated mean and 95th per-
capita intake rates for the total populations that
garden, farm, and raise animals. Table 13-70 also
provides age-specific per capita intake rates based on
data that have been adjusted to account for
preparation and post-cooking losses.
The advantages of this analysis are that it
provides data for populations that may be of
particular interest because they may represent the
high-end of the per capita home-produced food intake
distribution (Phillips and Moya, 2011), and that age-
specific intake rates are provided for the age groups
recommended by U.S. EPA (2005). However, it
should be noted that these estimates are based on data
that are more than 20 years old and may not reflect
recent changes in consumption patterns. Also, the
data for children less than 1 year of age are
considered to be less certain than for other age groups
because the diets of children in this age range would
be expected to be highly variable (Phillips and Moya,
2011). Other limitations associated with this analysis
are the same as those described in Section 13.3.1 for
the analysis of the NFCS data.
13.4. RELEVANT STUDY FOR INTAKE OF
HOME-PRODUCED FOODS
13.4.1. National Gardening Association (2009)
According to a survey by the National Gardening
Association (2009), an estimated 36 million (or 31%)
of U.S. households participated in food gardening in
2008. Food gardening includes growing vegetables,
berries, fruit, and herbs. Of the estimated 36 million
food-gardening households, 23% participated in
vegetable gardening, 12% participated in herb
gardening, 10% participated in growing fruit trees,
and 6% grew berries. Table 13-71 contains
demographic data on food gardening in 2008 by sex,
age, education, household income, and household
size. Table 13-72 contains information on the types of
vegetables grown by home gardeners in 2008.
Tomatoes, cucumbers, peppers, beans, carrots,
summer squash, onions, lettuce, peas, and corn are
among the vegetables grown by the largest
percentage of gardeners.
13.5. REFERENCES FOR CHAPTER 13
Moya, J; Phillips, L. (2001) Analysis of consumption
of home-produced foods. J Anal Environ
Epidemiol 11(5):398-406.
NGA (National Gardening Association). (2009) The
impact of home and community gardening
in America. South Burlington, VT: The
National Gardening Association.
Phillips, L.; Moya, J. (2011) Estimation of
age-specific per capita home-produced food
intake among populations that garden, farm,
or raise animals. J Expo Anal Environ
Epidemiol advance online publication:
27 April 2011:1-8.
USDA (U.S. Department of Agriculture). (1975)
Food yields summarized by different stages
of preparation. Agricultural Handbook No.
102. U.S. Department of Agriculture,
Agriculture Research Service, Washington,
DC.
USDA (U.S. Department of Agriculture).
(1987-1988) Dataset: Nationwide food
consumption survey 1987/88 household
food use. 1987/88 NFCS Database. U.S.
Department of Agriculture, Washington, DC.
USDA (U.S. Department of Agriculture). (1992)
Changes in food consumption and
expenditures in American households during
the 1980s. Statistical Bulletin No. 849. U.S.
Department of Agriculture, Washington, DC.
USDA (U.S. Department of Agriculture). (1993)
Food and nutrient intakes by individuals in
the United States, 1 Day, 1987-1988.
Nationwide Food Consumption Survey
1987-1988. NFCS Report No. 87-1-1. U.S.
Department of Agriculture, Washington, DC.
USDA (U.S. Department of Agriculture). (1994)
Food consumption and dietary levels of
households in the United States, 1987-1988.
Report No. 87-H-l. U.S. Department of
Agriculture, Agricultural Research Service,
Washington, DC.
U.S. EPA (Environmental Protection Agency). (1989)
Risk assessment guidance for superfund
(RAGS): Volume I, Human health
evaluation manual, Part A. Office of Solid
Waste and Emergency Response,
Washington, DC; EPA/540/1-89/002.
Available online at http://www.epa.gov/
oswer/riskassessment/ragsa/index.htm.
U.S. EPA (Environmental Protection Agency). (1991)
Record of decision. Environmental
Protection Agency, Washington, DC;
EPA/ROD/R10-91-029.
Page
13-10
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
U.S. EPA (Environmental Protection Agency). (1993)
Record of decision. Environmental
Protection Agency, Washington, DC;
EPA/ROD/R04-93 -166.
U.S. EPA (Environmental Protection Agency).
(1994) Validation strategy for the integrated
exposure uptake biokinetic model for lead in
children. Office of Solid Waste and
Emergency Response, Washington, DC;
EPA/540/R-94-039. Available online at
http ://www. epa. gov/superfund/lead/products
/valstratpdf.
U.S. EPA (Environmental Protection Agency). (1996)
Soil screening fact sheet guidance. Office of
Superfund, Washington, DC;
EPA/540/F-95/041. Available online at
http: //www. epa. gov/superfund/health/conme
dia/soil/index.htm.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
National Center for Environmental
Assessment, Washington, DC;
EPA/630/P-03/003F. Available online at
http ://epa. gov/ncea.
Exposure Factors Handbook Page
September 2011 13-11
-------
I
a1
^5 5.
IS
IS
* 1
Table 13-3. Subcategory Codes, Definitions, and Descriptions
Code
Definition
Description
Region"
1
2
3
4
Northeast
Midwest
South
West
Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island,
and Vermont.
Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South
Dakota, and Wisconsin.
Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland,
Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.
Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington,
Wyoming.
and
Urbanization
1
2
3
Central City
Suburban
Non-metropolitan
Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area (MSA).
An area that is generally within the boundaries of an MSA but is not within the legal limit of the central city
An area that is not within an MSA.
Race
1
2
3
4
5,8,9
—
—
—
—
Other/NA
White (Caucasian)
Black
Asian and Pacific Islander
Native American, Aleuts, and Eskimos
Don't know, no answer, some other race
Responses to Survey Questions
Grow
Raise Animals
Fish/Hunt
Farm
Question 75
Question 76
Question 77
Question 79
Did anyone in the household grow any vegetables or fruit for use in the household?
Did anyone in the household produce any animal products such as milk, eggs, meat, or poultry for home use in your
household?
Did anyone in the household catch any fish or shoot game for home use?
Did anyone in the household operate a farm or ranch?
Season
Spring
Summer
Fall
Winter
-
-
-
-
April, May, June
July, August, September
October, November, December
January, February, March
a Alaska and Hawaii were not included.
Source: USDA,
1987-1988.
Q
a
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^ >^
.0 ^
HJ S
^ "**
55* ^^
w *j
TJ ri
I I
ri
S,
I
I
1=
-------
I!
l
(% ft
i!
I
Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in Analysis of Food
All Regions
Total
Age (years)
70
Season
Fall .
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
Asian
Black
Native American
Other/NA
White
Response to Questionnaire
Do you garden?
Do you raise animals?
Do you hunt?
Do you fish?
Do you farm?
wgtd
188,019,000
2,814,000
5,699,000
8,103,000
16,711,000
20,488,000
61,606,000
56,718,000
15,880,000
47,667,000
46,155,000
45,485,000
48,712,000
56,352,000
45,023,000
86,584,000
2,413,000
21,746,000
1,482,000
4,787,000
157,531,000
6,8152,000
10,097,000
20,216,000
39,733,000
7,329,000
Source: Based on EPA's analyses of the
unwgtd
9,852
156
321
461
937
1,084
3,058
3,039
796
1,577
3,954
1,423
2,898
2,217
3,001
4,632
114
1,116
91
235
8,294
3,744
631
1,148
2,194
435
Northeast
wgtd
41,167,000
545,000
1,070,000
1,490,000
3,589,000
4,445,000
12,699,000
13,500,000
3,829,000
9,386,000
10,538,000
9,460,000
11,783,000
9,668,000
5,521,000
25,978,000
333,000
3,542,000
38,000
1,084,000
36,170,000
12,501,000
1,178,000
3,418,000
5,950,000
830,000
unwgtd
2,018
29
56
92
185
210
600
670
176
277
803
275
663
332
369
1,317
13
132
4
51
1,818
667
70
194
321
42
Midwest
wgtd
46,395,000
812,000
1,757,000
2,251,000
4,263,000
5,490,000
15,627,000
13,006,000
3,189,000
14,399,000
10,657,000
10,227,000
11,112,000
17,397,000
14,296,000
14,702,000
849,000
2,794,000
116,000
966,000
41,670,000
22,348,000
3,742,000
6,948,000
12,621,000
2,681,000
unwgtd
2,592
44
101
133
263
310
823
740
178
496
1,026
338
732
681
1,053
858
37
126
6
37
2,386
1,272
247
411
725
173
South
wgtd
64,331,000
889,000
1,792,000
2,543,000
5,217,000
6,720,000
21,786,000
19,635,000
5,749,000
13,186,000
16,802,000
17,752,000
16,591,000
17,245,000
19,100,000
27,986,000
654,000
13,701,000
162,000
1,545,000
48,269,000
20,518,000
2,603,000
6,610,000
13,595,000
2,232,000
unwgtd
3,399
51
105
140
284
369
1,070
1,080
300
439
1,437
562
961
715
1,197
1,487
32
772
8
86
2,501
1,136
162
366
756
130
Intake
West
wgtd
36,066,000
568,000
1,080,000
1,789,000
3,612,000
3,833,000
11,494,000
10,577,000
3,113,000
10,696,000
8,158,000
7,986,000
9,226,000
12,042,000
6,106,000
17,918,000
577,000
1,709,000
1,166,000
1,192,000
31,422,000
12,725,000
2,574,000
3,240,000
7,567,000
1,586,000
unwgtd
1,841
32
59
95
204
195
565
549
142
365
688
246
542
489
382
970
32
86
73
61
1,589
667
152
177
392
90
1987-1988 NFCS.
Q
I
ft
ft
I-
ri
a.
I
I
§
s
ri
1=
I
ft
-------
I
II
Is
5 I
Table 13-5. Consumer-Only Intake of Home-Produced Fruits (g/kg-day) — All Regions Combined
Population Nc Nc
%
Group wgtd Unwgtd Consuming
Total 14,744,000 817
Age (years)
Ito2 360'000 23
550,000 34
3 to 5
1,044,000 75
6 to 11
1,189,000 67
12 to 19
3,163,000 164
20 to 39
5,633,000 309
40 to 69
> 70 2,620,000 134
Season
3,137,000 108
Fall
Spring 2,963,000 301
Summer 4,356,000 145
Winter 4,288,000 263
Urbanization
Central City 3,668,000 143
Non-metropolitan 4,118,000 278
Suburban 6,898,000 394
Race
450,000 20
Black
White 14,185,000 793
Response to Questionnaire
Households who garden 12,742,000 709
1,917,000 112
Hguseholds whgttard error
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
7.84
6.32
6.79
6.25
5.80
5.13
9.93
16.50
6.58
6.42
9.58
8.80
6.51
9.15
7.97
2.07
9.00
18.70
26.16
Source: Moya and Phillips, 2001. (Based on EPA's analyses of the
Mean
2.68
8.74
4.07
3.59
1.94
1.95
2.66
2.25
1.57
1.58
3.86
3.08
2.31
2.41
3.07
1.87
2.73
2.79
2.58
SE pi
0.19 0.06
3.10 0.96
1.48 0.01
0.68 0.01
0.37 0.09
0.33 0.08
0.30 0.06
0.23 0.04
0.16 0.26
0.14 0.09
0.64 0.01
0.34 0.04
0.26 0.04
0.31 0.06
0.32 0.13
0.85 0.13
0.19 0.07
0.21 0.06
0.26 0.07
p5
0.17
1.09
0.01
0.19
0.13
0.13
0.19
0.22
0.30
0.20
0.09
0.17
0.18
0.13
0.23
0.28
0.18
0.18
0.28
plO
0.28
1.30
0.36
0.40
0.27
0.20
0.29
0.38
0.39
0.25
0.16
0.27
0.33
0.23
0.30
0.46
0.28
0.29
0.41
P25
0.50
1.64
0.98
0.70
0.44
0.37
0.47
0.61
0.57
0.42
0.45
0.56
0.57
0.45
0.49
0.61
0.51
0.53
0.75
p50
1.07
3.48
1.92
1.31
0.66
0.70
1.03
1.18
1.04
0.86
1.26
1.15
1.08
1.15
0.99
1.13
1.07
1.12
1.61
P75
2.37
7.98
2.73
3.08
2.35
1.77
2.33
2.35
1.92
1.70
3.31
2.61
2.46
2.42
2.33
1.53
2.46
2.50
3.62
p90
5.97
19.30
6.02
11.80
6.76
4.17
5.81
5.21
3.48
4.07
10.90
8.04
5.34
4.46
7.268
2.29
6.10
6.10
5.97
p95
11.10
60.60
8.91
15.80
8.34
6.84
13.00
8.69
4.97
5.10
14.60
15.30
10.50
3415.20
2.29
11.70
11.80
7.82
p99
24.00
60.60
48.30
32.20
18.50
16.10
23.80
11.70
10.60
8.12
53.30
24.90
14.30
24.00
37.00
19.30
24.00
24.90
15.80
MAX
60.60
60.60
48.30
32.20
18.50
37.00
53.30
15.30
10.60
31.70
60.60
48.30
19.30
53.30
60.60
19.30
60.60
60.60
15.80
1987-1988 NFCS.)
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Table
Population Nc
13-6.
Nc
Group wgtd unwgtd
Total 1,279,000
Season
Fall 260,000
Spring 352,000
Summer 271,000
Winter 396,000
Urbanization
Central City 50,000
Non-metropolitan 176,000
Suburban 1,053,000
Response to Questionnaire
Households who garden 983,000
Hou"ohold" who farm 132,000
72
8
31
9
24
3
10
59
59
4
Consumer-Only Intake of Home-Produced Fruits (g/kg-day) — Northeast
%
Consuming Mean SE pi p5 pW p25 p50 p75
3.11 0.93 0.22 0.08 0.08 0.16 0.31 0.49 0.78
2.77 ,,,,,,,,
3.34 0.88 0.23 0.09 0.16 0.17 0.29 0.49 0.88
2.86 ,,,,,,,,
3.36 0.71 0.11 0.18 0.21 0.23 0.29 0.54 0.88
0.52 ,,,,,,,,
3.19 ,,,,,,,,
4.05 1.05 0.26 0.18 0.23 0.29 0.44 0.54 0.81
7.86 1.04 0.26 0.09 0.18 0.21 0.38 0.54 0.88
15.90 ,,,,,,,,
p90 p95 p99 MAX
1.29 2.16 11.70 11.70
* * * *
1.83 2.16 7.13 7.13
* * * *
1.38 1.79 2.75 2.75
* * * *
,
1.29 2.75 11.70 11.70
1.38 2.75 11.70 11.70
*
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the
1987-1988 NFCS.
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Table 13-7.
Population Nc Nc
Group wgtd unwgtd
Total 4,683,000 302
Season
Fall 1,138,000 43
Spring 1,154,000 133
Summer 1,299,000 44
Winter 1,092,000 82
Urbanization
Central City 1,058,000 42
Non-metropolitan 1,920,000 147
Suburban 1,705,000 113
Response to Questionnaire
Households who garden 4,060,000 267
TT i u i f 694,000 57
Household" who farm •,""" ->
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Consumer-Only Intake of Home-Produced Fruits (g/kg-day) — Midwest
%
Consuming
10.09
7.90
10.83
12.70
9.83
6.08
13.43
11.60
18.17
25.89
Mean
3.01
1.54
1.69
7.03
1.18
1.84
2.52
4.29
3.27
2.59
SE
0.41
0.19
0.28
1.85
0.18
0.39
0.54
0.87
0.47
0.30
pi
0.04
0.26
0.09
0.06
0.03
0.04
0.06
0.09
0.04
0.06
p5
0.13
0.30
0.21
0.09
0.06
0.10
0.11
0.20
0.10
0.19
pW
0.24
0.47
0.26
0.13
0.15
0.26
0.15
0.31
0.20
0.41
p25
0.47
0.61
0.42
0.43
0.36
0.52
0.40
0.48
0.45
1.26
p50
1.03
1.07
0.92
1.55
0.61
1.07
1.03
0.76
1.07
1.63
p75
2.31
1.92
1.72
8.34
1.42
1.90
2.07
3.01
2.37
3.89
p90
6.76
3.48
2.89
16.10
2.61
2.82
4.43
13.90
6.84
7.15
6.76
p95 p99
13.90 53.30
4.34 5.33
4.47 16.00
37.00 60.60
3.73 10.90
9.74 10.90
53.30
18.00 60.60
14.60 53.30
8.34 11.10
MAX
60.60
5.33
31.70
60.60
10.90
10.90
53.30
60.60
60.60
11.10
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-8. Consumer-Only Intake of Home-Produced Fruits
Population Nc Nc
Group wgtd unwgtd
Total 4,148,000 208
Season
Fall 896,000 29
Spring 620,000 59
Summer 1,328,000 46
Winter 1,304,000 74
Urbanization
Central City 1,066,000 39
Non-metropolitan 1,548,000 89
Suburban 1,534,000 80
Response to Questionnaire
Households who garden 3,469,000 174
296,000 16
%
Consuming
6.45
6.80
3.69
7.48
7.86
6.18
8.10
5.48
16.91
13.26
Households who farm
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Mean
2.97
1.99
2.05
2.84
4.21
3.33
2.56
3.14
2.82
*
SE
0.30
0.44
0.26
0.65
0.65
0.54
0.39
0.60
0.29
*
pi
0.11
0.39
0.16
0.08
0.11
0.24
0.08
0.11
0.16
*
p5 pW
0.24 0.36
0.43 0.45
0.28 0.31
0.16 0.27
0.24 0.38
0.39 0.46
0.27 0.34
0.16 0.28
0.28 0.38
*
(g/kg-day) — South
P25
0.60
0.65
0.45
0.44
0.89
0.83
0.61
0.51
0.65
*
p50 p75
1.35 3.01
1.13 1.96
1.06 4.09
1.31 2.83
1.88 3.71
2.55 4.77
1.40 2.83
1.10 2.29
1.39 2.94
*
p90
8.18
4.97
5.01
6.10
14.10
8.18
5.97
11.80
6.10
*
p95
14.10
8.18
6.58
14.30
19.70
10.60
10.40
p99
23.80
10.60
7.05
24.00
23.80
14.30
15.5024.o?j3.80
14.10
*
21.10
*
MAX
24.00
10.60
7.05
24.00
23.80
14.30
24.00
23.80
24.00
*
less than 20 observations.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-9. Consumer-Only Intake of Home-Produced Fruits (g/kg-day) — West
Population Nc Nc
Group wgtd unwgtd
Total 4,574,000 233
Season
843,000 28
Spring 837,000 78
Summer 1,398,000 44
Winter 1,496,000 83
Urbanization
Central City 1,494,000 59
Non-metropolitan 474,000 32
Suburban 2,606,000 142
Response to Questionnaire
Households who garden 4,170,000 207
795,000 35
Households who farm
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey
%
Consuming
12.68
7.88
10.26
17.51
16.22
12.41
7.76
14.54
32.77
50.13
Mean
2.62
1.47
1.37
2.47
4.10
1.99
2.24
3.04
2.76
1.85
SE
0.31
0.25
0.16
0.47
0.79
0.42
0.53
0.46
0.34
0.26
pi
0.15
0.29
0.17
0.19
0.07
0.07
0.18
0.18
0.10
0.28
p5
0.28
0.29
0.20
0.28
0.30
0.24
0.28
0.28
0.28
0.28
pW
0.33
0.30
0.25
0.40
0.33
0.34
0.42
0.31
0.31
0.60
p25
0.62
0.48
0.51
0.62
0.77
0.53
0.63
0.71
0.63
0.71
p50
1.20
1.04
0.98
1.28
1.51
0.86
0.77
1.39
1.20
1.26
p75
2.42
2.15
1.61
3.14
3.74
2.04
2.64
3.14
2.54
2.50
p90
5.39
2.99
2.95
7.26
11.10
4.63
4.25
5.81
5.81
4.63
p95
10.90
4.65
5.29
10.90
18.50
9.52
10.90
10.30
10.90
5.00
p99
24.90
5.39
6.68
13.00
48.30
19.30
10.90
32.20
24.90
6.81
MAX
48.30
5.39
7.02
13.00
48.30
19.30
10.90
48.30
48.30
6.81
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-10. Consumer-Only Intake of Home-Produced
Population Nc
Group wgtd
Total 34,392,000
Age
951,000
1 to 2
1,235,000
3 to 5
3,024,000
6 to 11
3,293,000
12 to 19
8,593,000
20 to 39
12,828,000
>170 4,002,000
Season
11,026,000
Fall
Spring 6,540,000
Summer 11,081,000
Winter 5,745,000
Urbanization
Central City 6,183,000
Non-metropolitan 13,808,000
Suburban 14,341,000
Race
1,872,000
BW&te 31,917,000
Response to Questionnaire
Households who garden 30,217,000
4,319,000
Households wh§tfan|nrd enm
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc
unwgtd
1,855
53
76
171
183
437
700
211
394
661
375
425
228
878
747
111
1,714
1,643
262
%
Consuming
18.29
16.69
15.24
18.10
16.07
13.95
22.62
25.20
23.13
14.17
24.36
11.79
10.97
30.67
16.56
8.61
20.26
44.34
58.93
Mean
2.08
5.20
2.46
2.02
1.48
1.47
2.07
2.51
1.88
1.36
2.86
1.79
1.40
2.68
1.82
1.78
2.10
2.17
3.29
SE
0.07
0.85
0.28
0.25
0.14
0.10
0.10
0.19
0.13
0.07
0.19
0.11
0.12
0.12
0.09
0.23
0.07
0.07
0.25
Vegetables
pi p5
0.00 0.11
0.02 0.25
0.00 0.05
0.01 0.10
0.00 0.06
0.02 0.08
0.01 0.12
0.01 0.15
0.05 0.11
0.00 0.04
0.07 0.16
0.00 0.04
0.01 0.07
0.02 0.16
0.00 0.11
0.00 0.08
0.01 0.11
0.01 0.11
0.00 0.16
(g/kg-day) — All Regions Combined
plO
0.18
0.38
0.39
0.16
0.15
0.16
0.21
0.24
0.18
0.14
0.22
0.16
0.15
0.26
0.16
0.14
0.18
0.19
0.29
p25
0.45
1.23
0.71
0.40
0.32
0.27
0.53
0.58
0.41
0.32
0.71
0.47
0.30
0.60
0.39
0.44
0.45
0.48
0.85
p50
1.11
3.27
1.25
0.89
0.81
0.76
1.18
1.37
0.98
0.70
1.62
1.05
0.75
1.45
0.96
0.93
1.12
1.18
1.67
p75
2.47
5.83
3.91
2.21
1.83
1.91
2.47
3.69
2.11
1.63
3.44
2.27
1.67
3.27
2.18
2.06
2.48
2.68
3.61
p90
5.20
13.10
6.35
4.64
3.71
3.44
5.12
6.35
4.88
3.37
6.99
3.85
3.83
6.35
4.32
4.68
5.18
5.35
8.88
p95
7.54
19.60
7.74
6.16
6.03
4.92
6.94
8.20
6.94
5.21
9.75
6.01
4.67
9.33
6.78
5.70
7.68
7.72
11.80
p99 MAX
15.50 27.00
27.00 27.00
10.60 12.80
17.60 23.60
7.71 9.04
10.50 20.60
14.90 22.90
12.50 15.50
12.50 18.90
8.35 23.60
18.70 27.00
10.60 20.60
9.96 16.60
17.50 27.00
12.50 20.60
8.20 18.90
15.50 27.00
15.50 23.60
17.60 23.60
Nc unwgtd = Unweighted number of consumers in survey.
Source: Moya and Phillips, 2001. (Based on EPA's analyses of the 1987-1988 NCFS.)
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Page Exposure Factors Handbook
13-20 September 2011
Table 13-11. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day) — Northeast
Population Nc Nc %
Group wgtd unwgtd Consuming Mean SE pi p5 plO p25 p50 p75 p90 p95 p99 MAX
Total 4,883,000 236 11.86 1.78 0.17 0.00 0.08 0.14 0.28 0.75 1.89 6.03 7.82 12.70 14.90
Season
Fall 1,396,000 41 14.87 1.49 0.41 0.08 0.13 0.17 0.27 0.58 1.17 6.64 9.97 10.20 10.20
Spring 1,204,000 102 11.43 0.82 0.11 0.00 0.00 0.04 0.17 0.46 0.95 2.26 3.11 6.52 6.78
Summer 1,544,000 48 16.32 2.83 0.47 0.11 0.15 0.16 0.74 1.29 3.63 7.82 9.75 14.90 14.90
Winter 739,000 45 6.27 1.67 0.27 0.00 0.00 0.09 0.26 1.25 2.77 3.63 6.10 8.44 8.44
Urbanization
Central City 380,000 14 3.93 ,,,,,,,,
Non-metropolitan 787,000 48 14.25 3.05 0.54 0.00 0.05 0.11 0.20 2.18 4.61 9.04 14.90 14.90
Suburban 3,716,000 174 14.30 1.59 0.17 0.00 0.08 0.14 0.28 0.72 1.64 4.82 6.80 10.20 10.20
Response to Questionnaire 12.70
Households who garden 4,381,000 211 35.05 1.92 0.18 0.00 0.08 0.14 0.31 0.88 2.18 6.16 7.82 12.70 14.90
352,000 19 42.41 ,,,,,,,,
HouseholdSm^te/Ma not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Exposure Factors Handbook
Chapter 13 — Intake of Home-Produced Foods
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Table 13-12. Consumer-Only Intake of Home-Produced
Population Nc
Group wgtd
Total 12,160,000
Season
4,914,000
Spring 2,048,000
Summer 3,319,000
Winter 1,879,000
Urbanization
Central City 3,177,000
Non-metropolitan 5,344,000
Suburban 3,639,000
Response to Questionnaire
Households who garden 10,927,000
1,401,000
Hguseholds whg^fggrd error
Nc
unwgtd
699
180
246
115
158
113
379
207
632
104
%
Consuming
26.21
34.13
19.22
32.45
16.91
18.26
37.38
24.75
48.89
52.26
Mean
2.26
1.84
1.65
3.38
2.05
1.36
2.73
2.35
2.33
3.97
SE
0.12
0.18
0.15
0.39
0.26
0.19
0.19
0.22
0.13
0.43
pi
0.02
0.01
0.06
0.11
0.00
0.00
0.02
0.03
0.02
0.14
Vegetables (g/kg-day) — Midwest
p5
0.08
0.07
0.15
0.16
0.02
0.06
0.11
0.15
0.10
0.34
pW
0.18
0.16
0.22
0.30
0.07
0.11
0.26
0.22
0.18
0.55
p25
0.49
0.42
0.46
0.85
0.36
0.25
0.60
0.64
0.50
0.87
p50 p75
1.15 2.58
1.03 2.10
0.91 1.72
2.07 3.94
0.88 2.13
0.71 1.67
1.31 3.15
1.39 2.75
1.18 2.74
2.18 5.24
p90
5.64
5.27
4.49
7.72
5.32
3.94
7.19
p95
7.74
6.88
5.83
14.00
7.83
5.50
4.87io.6G7.18
5.81
10.60
7.75
14.40
p99 MAX
17.50 23.60
13.10 13.10
12.80 23.60
19.60 22.90
16.70 20.60
9.96 16.60
17.50 23.60
19.60 20.60
16.70 23.60
17.50 23.60
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-13. Consumer-Only Intake of Home-Produced Vegetables
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 11,254,000 618 17.49
Season
Fall 2,875,000 101 21.80
Spring 2,096,000 214 12.47
Summer 4,273,000 151 24.07
Winter 2,010,000 152 12.12
Urbanization
Central City 1,144,000 45 6.63
Non-metropolitan 6,565,000 386 34.37
Suburban 3,545,000 187 12.67
Response to Questionnaire
Households who garden 9,447,000 522 46.04
H^o^Ms «*„ farm 1,609,000 91 72.09
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Mean
2.19
2.07
1.55
2.73
1.88
1.10
2.78
1.44
2.27
3.34
SE
0.12
0.28
0.11
0.32
0.14
0.16
0.18
0.11
0.12
0.46
pi
0.03
0.10
0.01
0.11
0.00
0.01
0.05
0.00
0.03
0.00
p5
0.16
0.11
0.09
0.17
0.16
0.10
0.22
0.11
0.16
0.13
pW
0.24
0.19
0.26
0.25
0.35
0.15
0.35
0.20
0.26
0.23
p25
0.56
0.52
0.53
0.62
0.64
0.26
0.71
0.40
0.61
1.03
(g/kg-day)— South
p50
1.24
1.14
0.94
1.54
1.37
0.62
1.66
0.93
1.37
1.72
p75
2.69
2.69
2.07
3.15
2.69
1.37
3.31
1.72
3.02
3.15
p90
4.92
4.48
3.58
5.99
3.79
2.79
5.99
3.61g
5.18
9.56
p95
7.43
6.02
4.81
9.70
5.35
3.70
.,5.26
7.43
11.80
p99
17.00
15.50
8.35
23.60
7.47
4.21
18.90
8.20
15.50
23.60
MAX
27.00
18.90
10.30
27.00
8.36
4.58
27.00
8.20
23.60
23.60
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Table 13-14. Consumer-Only Intake of Home-Produced Vegetables
Population Nc Nc
Group wgtd unwgtd
Total 6,035,000 300
Season
,, „ 1,841,000 72
Fall
Spring 1,192,000 99
Summer 1,885,000 59
Winter 1,117,000 70
Urbanization
Central City 1,482,000 56
Non-metropolitan 1,112,000 65
Suburban 3,441,000 179
Response to Questionnaire
Households who garden 5,402,000 276
HniisptmMs whn ftrm 957,000 48
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
%
Consuming
16.73
17.21
14.61
23.6
12.11
12.31
18.21
19.20
42.45
60.34
Mean
1.81
2.01
1.06
2.39
1.28
1.80
1.52
1.90
1.91
2.73
SE
0.14
0.29
0.17
0.37
0.17
0.28
0.22
0.20
0.00
0.00
pi
0.01
0.10
0.00
0.07
0.01
0.03
0.00
0.01
0.01
0.12
p5
0.10
0.15
0.01
0.10
0.15
0.07
0.01
0.10
0.10
0.41
pW
0.17
0.20
0.05
0.25
0.20
0.16
0.20
0.15
0.17
0.47
p25
0.38
0.48
0.20
0.55
0.48
0.48
0.27
0.39
0.43
0.77
(g/kg-day) — West
P50
0.90
1.21
0.36
1.37
0.77
1.10
0.68
0.93
1.07
1.42
p75
2.21
2.21
0.91
3.23
1.43
2.95
2.13
2.20
2.37
3.27
p90
4.64
4.85
3.37
4.67
2.81
4.64
4.13
4.63
4.67
6.94
p95
6.21
7.72
5.54
8.36
5.12
4.85
5.12
7.988
6.21
10.90
p99 MAX
11.40 15.50
12.50 12.50
8.60 8.60
15.50 15.50
7.57 7.98
11.40 11.40
8.16
Ig12.50 15.50
12.50 15.50
15.50 15.50
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-15. Consumer-Only Intake of Home-Produced Meats (g/kg-day) — All Regions Combined
Population Nc Nc
Group wgtd unwgtd
Total 9,257,000 569
Age
276,000 22
1 to 2
396,000 26
3 to 5
6 to 11 1,064,000 65
1,272,000 78
12 to 19
2,732,000 158
20 to 39
2,872,000 179
40 to 69
> 70 441,000 28
Season
2,852,000 107
Fall
Spring 1,726,000 197
Summer 2,368,000 89
Winter 2,311,000 176
Urbanization
Central City 736,000 28
Non-metropolitan 4,932,000 315
Suburban 3,589,000 226
Race
128,000 6
B1Wliite 8,995,000 556
Response to Questionnaire
Households who raise animals 5,256,000 343
%
Consuming
4.92
4.84
4.89
6.37
6.21
4.43
5.06
2.78
5.98
3.74
5.21
4.74
1.31
10.95
4.15
0.59
5.71
52.06
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Mean
2.21
3.65
3.61
3.65
1.70
1.82
1.72
1.39
1.57
2.37
3.10
1.98
1.15
2.70
1.77
*
2.26
2.80
SE
0.11
0.61
0.51
0.45
0.17
0.15
0.11
0.23
0.14
0.15
0.38
0.17
0.18
0.18
0.10
0.11
0.15
pi
0.12
0.39
0.80
0.37
0.19
0.12
0.02
0.09
0.12
0.24
0.02
0.14
0.18
0.12
0.03
*
0.09
0.21
p5
0.24
0.95
0.80
0.65
0.32
0.19
0.21
0.09
0.21
0.32
0.19
0.24
0.19
0.26
0.29
*
0.26
0.39
plO
0.37
0.95
1.51
0.72
0.47
0.30
0.34
0.13
0.35
0.45
0.41
0.37
0.21
0.41
0.37
*
0.39
0.62
p25
0.66
1.19
2.17
1.28
0.62
0.53
0.58
0.55
0.52
0.78
0.85
0.65
0.44
0.75
0.68
*
0.68
1.03
p50
1.39
2.66
2.82
2.09
1.23
1.11
1.17
1.01
1.11
1.69
1.77
1.33
0.72
1.63
1.33
1.41
1.94
p75
2.89
4.72
3.72
4.71
2.35
2.65
2.38
1.81
2.27
3.48
4.34
2.43
1.58
3.41
2.49
*
2.91
3.49
p90
4.89
8.68
7.84
8.00
3.66
4.52
3.67
2.82
3.19
5.00
7.01
3.96
2.69
6.06
3.66
*
5.00
5.90
p95
6.78
10.00
9.13
14.00
4.34
6.23
5.16
3.48
4.41
6.67
10.50
6.40
3.40
84?4.71
*
7.01
7.84
p99 MAX
14.00 23.20
11.50 11.50
13.00 13.00
15.30 15.30
6.78 7.51
9.17 10.90
5.90 7.46
7.41 7.41
6.78 7.84
10.10 13.00
22.30 22.30
10.90 23.20
3.64 3.64
15.30 23.20
7.20 10.10
* *
14.00 23.20
14.00 23.20
less than 20 observations.
Source: Moya and Phillips, 2001. (Based on EPA's analyses of the 1987-1988 NFCS.)
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Table 13-16. Consumer-Only Intake of Home-Produced Meats (g/kg-day) — Northeast
Population
Group
Total 1
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Response to Questionnaire
Households who raise animals
Houccholdc vho farm
Nc Nc %
wgtd unwgtd Consuming Mean SE pi p5 pW p25 p50 p75 p90
,113,000 52 2.70 1.46 0.21 0.29 0.34 0.35 0.64 0.89 1.87 2.68
569,000 18 6.06 ,,,,,, ,
66,000 8 0.63 ,,,,,, ,
176,000 6 1.86 * *
302,000 20 2.56 2.02 0.56 0.29 0.31 0.43 0.62 1.11 2.38 2.93
,
0 0 0.00 .......
391,000 17 7.08 ,,,,,, ,
722,000 35 2.78 1.49 0.15 0.29 0.35 0.43 0.68 1.39 2.34 2.68
,
509,000 25 43.21 2.03 0.39 0.62 0.65 0.65 0.88 1.62 2.38 2.93
373,000 15 44.94 ,,,,,, ,
p95 p99 MAX
2.89 10.90 10.90
,
* * *
7.46 10.90 10.90
* * *
2.89 3.61 3.61
7.46 10.90 10.90
* * *
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available. «
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-17. Consumer-Only
Population Nc Nc
Group wgtd unwgtd
Total 3,974,000 266
Season
,, „ 1,261,000 49
Fall
Spring 940,000 116
Summer 930,000 38
Winter 843,000 63
Urbanization
Central City 460,000 18
Non-metropolitan 2,477,000 175
Suburban 1,037,000 73
Response to Questionnaire
Households who raise animals 2,165,000 165
1,483,000 108
Houccholdc vho farm
* Intake data not provided for subpopulations for whi
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
%
Consuming
8.57
8.76
8.82
9.09
7.59
2.64
17.33
7.05
57.86
55.32
ch there were
Intake of Home-Produced Meats (g/kg-day) — Midwest
Mean
2.55
1.76
2.58
4.10
2.00
*
3.15
1.75
3.20
3.32
less than
SE
0.18
0.23
0.22
0.75
0.24
*
0.26
0.20
0.22
0.29
pi
0.13
0.21
0.24
0.09
0.12
*
0.09
0.29
0.26
0.37
p5 pW
0.26 0.39
0.26 0.37
0.31 0.41
0.13 0.58
0.24 0.33
* *
0.30 0.43
0.37 0.41
0.39 0.58
0.54 0.59
p25 p50
0.66 1.40
0.50 1.19
0.73 1.98
0.89 2.87
0.65 1.36
*
0.82 2.38
0.66 1.11
1.07 2.56
1.07 2.75
p75
3.39
2.66
3.67
5.42
2.69
*
4.34
2.03
4.42
4.71
p90
5.75
3.49
5.14
8.93
4.11
*
6.15
4.169
6.06
6.78
p95
7.20
6.06
7.79
15.30
5.30
*
17 5'39
9.13
9.17
p99
15.30
6.78
11.50
22.30
8.10
*
15.30
7.20
15.30
15.30
MAX
22.30
6.78
13.00
22.30
12.20
*
22.30
10.10
15.30
15.30
20 observations.
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Table 13-18. Consumer-Only Intake of Home-Produced Meats (g/kg-day) — South
Population Nc Nc
Group wgtd unwgtd
Total 2,355,000 146
Season
Fall 758,000 28
Spring 511,000 53
Summer 522,000 18
Winter 564,000 47
Urbanization
Central City 40,000 1
Non-metropolitan 1,687,000 97
Suburban 628,000 48
Response to Questionnaire
Households who raise animals 1,222,000 74
1,228,000 72
%
Consuming
3.66
5.75
3.04
2.94
3.40
0.23
8.83
2.24
46.95
55.02
Mean
2.24
1.81
2.33
,
1.80
*
2.45
1.79
3.16
2.85
SE
0.19
0.29
0.27
,
0.25
*
0.26
0.23
0.32
0.32
pi p5
0.02 0.16
0.12 0.16
0.19 0.30
,
0.04 0.20
* *
0.12 0.19
0.02 0.03
0.26 0.67
0.20 0.50
pW
0.30
0.19
0.50
,
0.25
*
0.40
0.04
0.84
0.60
p25
0.72
0.82
0.75
,
0.72
*
0.78
0.63
1.34
1.01
p50
1.53
1.53
1.80
,
1.40
,
*
1.61
1.40
2.11
1.93
p75
3.07
2.38
2.82
2.17
3.19
2.31
3.79
3.48
p90 p95
5.07 6.71
3.19 4.41
5.16 6.71
,
3.55 4.58
* *
6.09
4.567844.61
6.67 8.47
6.23 8.47
p99
14.00
7.84
7.51
,
8.47
*
14.00
6.40
14.00
14.00
MAX
14.00
7.84
7.51
,
8.47
*
14.00
6.40
14.00
14.00
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-19. Consumer-Only Intake of Home-Produced Meats (g/kg-day) — West
Population Nc Nc
Group wgtd unwgtd
Total 1,815,000 105
Season
,, „ 264,000 12
Fall
Spring 209,000 20
Summer 740,000 27
Winter 602,000 46
Urbanization
Central City 236,000 9
Non-metropolitan 377,000 26
Suburban 1,202,000 70
Response to Questionnaire
Households who raise animals 1,360,000 79
„ ,,,,,- 758,000 48
Hniisphnlns who farm
%
Consuming
5.03
2.47
2.56
9.27
6.53
1.96
6.17
6.71
52.84
47.79
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Mean
1.89
*
1.86
2.20
2.11
*
2.10
1.95
2.12
2.41
SE
0.21
*
0.23
0.32
0.46
*
0.70
0.20
0.27
0.43
pi
0.15
*
0.30
0.19
0.14
*
0.33
0.15
0.15
0.14
p5
0.23
*
0.43
0.41
0.36
*
0.33
0.23
0.23
0.33
pW
0.39
*
0.87
0.54
0.43
*
0.41
0.37
0.39
0.47
p25
0.66
*
1.22
1.07
0.67
*
0.67
0.78
0.82
0.79
p50
1.42
*
1.56
1.69
1.19
*
1.19
1.52
1.56
1.55
p75
2.49
2.43
3.27
2.35
1.77
2.71
2.71
2.91
p90 p95
3.66 4.71
* *
3.48 4.20
4.44 4.71
3.64 7.02
* *
3.72
4.204.971.71
4.20 4.97
4.71 7.02
p99 MAX
8.00 23.20
* *
4.20 4.20
8.00 8.00
23.20 23.20
* *
23.20 23.20
8.00 8.00
8.00 23.20
23.20 23.20
less than 20 observations.
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Table 13-20. Consumer-Only Intake of Home-Caught Fish (g/kg-day) — All Regions Combined
Population Nc Nc %
Total
Age
Ito2
3£\o 11
12 to 19
20 to 39
40>tp,(69
Season
Fall .
Spring
Summer
Winter
Group wgtd unwgtd
3,914,000 239
82,000 6
142,000 11
382,000 29
346,000 21
962,000 59
1,524,000 86
450,000 24
1,220,000 45
1,112,000 114
911,000 29
671,000 51
Consuming Mean
2.08
1.44
1.75
2.29
1.69
1.56
2.69
2.83
2.56
2.41
2.00
1.38
2.07
*
2.78
1.52
1.91
1.79
1.22
1.31
3.08
1.88
2.05
SE pi
0.24 0.08
* *
0.84 0.16
0.41 0.20
0.33 0.08
0.26 0.09
0.23 0.10
0.22 0.18
0.56 0.10
0.42 0.08
0.37 0.09
p5 plO
0.09 0.20
* *
0.16 0.18
0.20 0.20
0.08 0.09
0.09 0.21
0.10 0.23
0.18 0.20
0.12 0.31
0.08 0.09
0.09 0.11
p25 p50
0.23 0.43
* *
0.23 0.55
0.20 0.31
0.12 0.44
0.28 0.35
0.23 0.57
0.21 0.32
0.34 0.56
0.20 0.30
0.16 0.51
p75
1.00
*
i.o3
0.9§
1.06
0.99
0.76
0.92
1.27
0.76
1.06
p90
2.17
3.67
1.79
2.18
1.99
1.56
1.79
2.64
3.19
2.09
p95
4.68
*
7.05
4.68
4.46
4.43
3.73
2.64
6.68
4.43
5.89
p99
7.83
*
7.85
6.67
9.57
6.56
3.73
3.73
10.80
5.65
7.85
MAX
15.50
*
25.30
8.44
13.00
10.80
5.12
6.56
37.30
9.57
13.10
Urbanization
Central City 999,000 46
Non-metropolitan 1,174,000 94
Suburban
Race
B1$rnte
1,741,000 99
593,000 41
3,228,000 188
1.77
2.61
2.01
2.73
2.05
1.79
3.15
1.50
1.81
2.07
0.34 0.09
0.57 0.10
0.23 0.08
0.37 0.18
0.28 0.08
0.09 0.16
0.12 0.31
0.08 0.18
0.18 0.20
0.08 0.16
0.28 0.61
0.36 0.57
0.20 0.29
0.29 0.32
0.23 0.39
1.07
1.88
0.59
0.98
1.00
1.85
3.86
1.38
2.17
2.16
3.73
6.52
4.37
4.68
4.99
9.57
7.83
7.05
9.57
6.68
9.57
37.30
10.80
9.57
16.10
Response to Questionnaire
H-..~ -i, -i j~
*
SE
P
Nc wgtd
Nc unwgtd
Source:
3,553,000 220
8.94
2.22
Intake data not provided for subpopulations for which there were
= Standard error.
= Percentile of the distribution.
= Weighted number of consumers.
0.26 0.08
0.08 0.18
0.23 0.47
1.09
2.23
5.61
7.85
16.10
less than 20 observations.
= Unweighted number of consumers in survey.
Moya and Phillips, 2001. (Based on EPA's analyses of the
1987-1988 NFCS.)
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Table 13-21. Consumer-Only Intake of Home-Caught Fish (g/kg-day) — Northeast
Population Nc Nc
Group wgtd unwgtd
Total 334,000 12
Season
135,000 4
Spring 14,000 2
Summer 132,000 3
Winter 53,000 3
Urbanization
Central City 0
Non-metropolitan 42,000 4
Suburban 292,000 8
Response to Questionnaire
Houccholdc-hofich 334'000 12
%
Consuming Mean SE pi
0.81
1.44
0.13
1.40
0.45
0.00
0.76
1.12
5.61
p5 plO p25 p50 p75 p90 p95 p99 MAX
*********
*
,
,
*********
,
fc********
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-22. Consumer-Only Intake of Home-Caught Fish (g/kg-day) — Midwest
Population Nc Nc
Group wgtd unwgtd
Total 1,113,000 71
Season
,, „ 362,000 13
Fall
Spring 224,000 27
Summer 264,000 8
Winter 263,000 23
Urbanization
Central City 190,000 9
Non-metropolitan 501,000 40
Suburban 422,000 22
Response to Questionnaire
956,000 60
Houccholdc vho fich
%
Consuming
2.40
2.51
2.10
2.58
2.37
1.09
3.50
2.87
7.57
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS
Mean SE pi p5 plO p25 p50
2.13 0.42 0.08 0.08 0.20 0.23 0.47
******
3.45 1.22 0.12 0.12 0.12 0.31 0.49
******„
2.38 0.53 0.51 0.51 0.51 0.55 1.03
.
* * * * *
3.42 0.72 0.12 0.12 0.33 0.47 0.53
0.91 0.18 0.08 0.08 0.08 0.20 0.30
2.35 0.49 0.08 0.08 0.12 0.23 0.47
less than 20 observations.
p75 p90 p95 p99 MAX
1.03 1.95 6.10 6.56 16.10
*****
0.82 1.67 15.50 16.10 25.30
*****
1.56 2.13 5.89 6.10 13.10
*****
1.88 5.65 13.10 25.30
0.55 1.286.562.09 2.78 3.73
1.12 2.16 6.52 6.56 25.30
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Table 13-23
Population
Group
Total
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Response to Questionnaire
Houccholdc vho fich
Nc
wgtd
1,440,000
274,000
538,000
376,000
252,000
281,000
550,000
609,000
1,280,000
Consumer-Only Intake of Home-Caught Fish (g/kg-day) — South
Nc
unwgtd
101
11
58
14
18
16
41
44
95
%
Consuming Mean SE pi p5 plO p25 p50 p75
2.24 2.74 0.48 0.09 0.09 0.20 0.29 0.51 1.48
2.08 ,,,,,,,
3.20 4.00 0.94 0.31 0.31 0.39 0.45 0.87 1.94
2.12 ,,,,,,,'
1.52 ,,,,,,,
1.63
2.88 3.33 1.06 0.29 0.29 0.34 0.51 1.12 1.94
2.18 2.73 0.50 0.20 0.20 0.28 0.29 0.43 1.08
9.42 3.00 0.51 0.09 0.09 0.20 0.28 0.71 1.93
p90 p95 p99 MAX
3.37 5.61 8.44 37.30
* * * *
3.71 8.33 13.00 45.20
,
w * * *
w * * *
3.19 45.20
4.374 438.336 67L0.40 13.00
3.67 6.68 8.44 37.30
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-24. Consumer-Only Intake of Home-Caught Fish (g/kg-day)— West
Population
Group
Total 1
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Response to Questionnaire
Houccholdc vho fich
Nc Nc %
wgtd unwgtd Consuming Mean SE pi p5 plO p25 p50 p75 p90 p95
,027,000 55 2.85 1.57 0.27 0.10 0.16 0.20 0.24 0.44 0.84 1.79 3.73
449,000 17 4.20 *
336,000 27 4.12 1.35 0.29 0.10 0.10 0.24 0.33 0.44 0.61 1.68 4.68
139,000 4 1.74 *
103,000 7 1.12 * t
528,000 21 4.38 2.03 0.53 0.33 0.33 0.43 0.53 0.71 1.45 1.85 3.73
81,000 9 1.33 *
418,000 25 2.33 1.09 0.25 0.18 0.18 0.20 0.21 0.31 0.59 1.21 2.90
983,000 53 12.99 1.63 0.28 0.10 0.16 0.20 0.22 0.55 0.96 1.79 3.73
p99 MAX
5.67 9.57
* *
5.61 5.67
,
* *
9.57 9.57
468 5.61
5.67 9.57
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of
consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
ft
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Table 13-25. Consumer-Only Intake of Home-Produced Dairy (g/kg-day) — All Regions
Population Nc Nc
Group wgtd unwgtd
Total 1,409,000 89
Age
79,000 6
1 to 2
57,000 5
3 to 5
6 to 11 264,000 16
84,000 5
12 to 19
612,000 36
20 to 39
216,000 16
40 to 69
> 70 77,000 3
Season
211,000 7
Spring 253,000 27
Summer 549,000 22
Winter 396,000 33
Urbanization
Central City 115,000 7
Non-metropolitan 988,000 59
Suburban 306,000 23
Race
0 0
B1Wliite 1,382,000 86
Response to Questionnaire
Households who raise animals 1,228,000 80
Households who farm W20'000 63
%
Consuming
0.75
1.39
0.70
1.58
0.41
0.99
0.38
0.48
0.44
0.55
1.21
0.81
0.20
2.19
0.35
0.00
0.88
12.16
13.92
* Intake data not provided for subpopulations for which there were
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Mean SE pi p5 plO
14.00 1.62 0.18 0.45 0.51
*****
7.41 1.02 0.21 0.40 0.45
*****
*****
17.80 4.27 0.63 0.65 0.67
15.30 2.73 0.45 0.45 0.51
8.08 1.99 0.18 0.21 0.28
*****
16.80 2.10 0.48 0.96 1.89
9.86 2.38 0.40 0.40 0.45
14.30 1.65 0.18 0.45 0.51
15.90 1.73 0.18 0.40 1.89
17.10 1.99 0.40 0.74 3.18
less than 20 observations.
p25 p50 p75 p90 p95 p99 MAX
3.18 10.20 19.50 34.20 44.00 72.60 111.00
* *****
*
**
1.89 6.46 12.10 15.40 19.50 23.00 23.00
*
* *****
,
** *****
5.06 12.20 19.50 50.90 80.10 111.00 111.00
5.3-6 10.60 25.10 34.90 36.70 46.80 46.80
0.74 5.47 11.50 19.80 20.40 72.60 72.60
* *****
6.74 10.80 20.40 34.90 111.00
0.57 5.36 13.10 28.1044.§§.9()80.J@.90 50.90
3.82 10.30 19.50 34.20 44.00 80.10 111.00
6.13 10.80 19.60 34.90 44.00 80.10 111.00
9.06 12.10 20.40 34.90 44.00 80.10 111.00
Source: Moya and Phillips, 2001. (Based on EPA's analyses of the 1987-1988 NFCS.)
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Table 13-26.
Population
Group
Total
Season
Fall
Spring
Summer
Winter w
Urbanization
Central City
Non-metropolitan
Suburban
Response to Questionnaire
Households who raise animals
Houceholdc "'ho farm
Consumer-Only Intake of Home-Produced Dairy (g/kg-day) — Northeast
Nc Nc %
gtd unwgtd Consuming Mean SE pi p5 pW p25 p50 p75 p90
312,000
48,000
36,000
116,000
112,000
0
240,000
72,000
312,000
312,000
16
2
4
4
6
0
10
6
16
16
0.76 ,,,,,,
0.51 ,,,,,,
0.34 ,,,,,,
1.23 ,,,,,,
0.95 ,,,,,,
o.oo ......
4.35 ,,,,,,
0.28 ,,,,,,
26.49 ,,,,,,
37.59 ,,,,,,
p95 p99 MAX
,
,
* * *
* * *
* * *
* * *
* * *
,
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses
of the 1987-1988 NFCS.
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Table 13-27. Consumer-Only Intake of Home-Produced Dairy
Population Nc Nc %
Group wgtd unwgtd Consuming Mean SE pi p5 plO
Total 594,000 36 1.28 18.60 3.15 0.45 0.45 1.97
Season
,, „ 163,000 5 1.13 *
Fall
Spring 94,000 12 0.88
Summer 252,000 11 2.46 *
Winter 85,000 8 0.76 *
Urbanization
Central City 43,000 1 0.25 *
Non-metropolitan 463,000 31 3.24 23.30 3.40 4.25 8.27 9.06
Suburban 88,000 4 0.60 *
Response to Questionnaire
Households who raise animals 490,000 32 13.09 22.30 3.33 4.25 5.36 8.27
490,000 32 18.28 22.30 3.33 4.25 5.36 8.27
Houccholdc vho farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
'g/kg-day) — Midwest
p25 p50 p75 p90 p95 p99 MAX
8.27 12.40 23.00 44.00 46.80 111.00 111.00
* * * * * *
,
* * * * * *
* * * * * *
12.10 16.00 31.40 44.00 46.80 111.00 111.00
,
10.80 15.40 31.40 44.00 46.80 111.00 111.00
10.80 15.40 31.40 44.00 46.80 111.00 111.00
Q
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Table 13-28. Consumer-Only Intake of Home-Produced Dairy (g/kg-day) — South
Population Nc Nc
Group wgtd unwgtd
Total 242,000 17
Season
0 0
Spring 27,000 3
Summer 131,000 5
Winter 84,000 9
Urbanization
Central City 27,000 3
Non-metropolitan 215,000 14
Suburban 0 0
Response to Questionnaire
Households who raise animals 215,000 14
148,000 8
%
Consuming Mean SE pi p5 plO p25
0.38 *
0.00 -----
0.16
0.74
0.51
0.16
1.13
0.00 -----
8.26
6.63
p50 p75 p90 p95 p99 MAX
***** *
*
* * * * * *
* * * * * *
* * * * * *
,
,
* * * * * *
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Q
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-------
oo
Table 13-29. Consumer-Only Intake of Home-Produced Dairy (g/kg-day) — West
Population
Group
Total
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Response to Questionnaire
Households who raise animals
Houccholdc vho farm
Nc Nc %
wgtd unwgtd Consuming Mean SE pi p5 pW p25
261,000 20
0 0
96,000 8
50,000 2
115,000 10
45,000 3
70,000 4
146,000 13
211,000 18
70,000 7
072 10.00 2.75 0.18 0.18 0.21 0.51
0.00 • -----
1.18 * *
0.63 * *
1.25 * *
0.37 * *
1.15 * *
0.81 * *
8.20 * *
4.41 * *
p50 p75 p90 p95 p99 MAX
6.10 13.30 28.10 28.90 50.90 50.90
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Q
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Table 13-30. Seasonally Adjusted Consumer-Only Home-Produced Intake (g/kg-day)
Population Group
Total Vegetable
Northeast
Midwest
S(West
All Regions
Total Fruit
Northeast
Midwest
South
West
All Regions
Total Meat
Northeast
Midwest
South
West
All Regions
Percent
Consuming
16.50
33.25
24.00
23.75
24.60
3.50
12.75
8.00
17.75
10.10
6.25
9.25
5.75
9.50
7.40
Source : Moya and Phillips, 200 1
pi
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.00
(Based on U.S.
p5
0.02
0.04
0.03
0.02
0.03
0.02
0.01
0.03
0.06
0.02
0.03
0.04
0.03
0.03
0.04
plO
0.04
0.08
0.06
0.04
0.06
0.05
0.01
0.11
0.09
0.06
0.08
0.22
0.05
0.10
0.09
EPA's analyses of the
p25
0.20
0.29
0.21
0.11
0.22
0.17
0.14
0.38
0.29
0.25
0.13
0.05
0.19
0.24
0.22
1987-1988 NFCS.)
p50
0.46
0.81
0.61
0.49
0.64
0.36
0.79
0.95
0.69
0.75
0.21
1.61
0.53
0.56
0.66
p75
1.37
1.96
1.86
1.46
1.80
0.66
2.98
2.10
1.81
2.35
0.70
3.41
1.84
1.30
1.96
p90
3.32
4.40
3.95
2.99
4.00
1.48
5.79
6.70
4.75
5.61
1.56
5.25
3.78
2.29
4.05
p95
5.70
7.41
5.63
5.04
6.08
3.00
9.52
10.20
8.54
9.12
1.91
7.45
4.95
3.38
5.17
p99
8.78
1.31
12.00
8.91
11.70
5.10
22.20
14.90
14.50
17.60
4.09
11.90
8.45
7.20
9.40
MAX
10.10
20.10
16.20
11.20
20.10
5.63
27.10
16.40
18.40
27.10
4.80
13.60
9.45
9.10
13.60
ft
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Table 13-31. Consumer-Only Intake of Home-Produced Apples (g/kg-day)
Population
Group
Total
Age
Ito2
3t^(69
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
Bl$rnte
Region
Midwest
Northeast
S
-------
§
(^ (^
il
I
Table 13-32. Consumer-Only Intake of Home-Produced Asparagus (g/kg-day)
Population Nc Nc
%
Group wgtd unwgtd Consuming Mean SE
Total 763,000 66
Age
8,000 1
1 to 2 25,000 3
3tft§ll 31,000 3
70,000 5
121019 144,000 11
20 to39 430,000 38
^tyc69 55,000 5
Season
62,000 2
Spring 608,000 59
Summer 0 0
Winter 93,000 5
Urbanization
Central City 190,000 9
Non-metropolitan 215,000 27
Suburban 358,000 30
Race
0 0
BWSte 763,000 66
Region
Midwest 368,000 33
Northeast 270,000 20
95,000 9
S
-------
I
II
Is
s I
Table 13-33. Consumer-Only
Population Nc Nc
%
Group wgtd Unwgtd Consuming
Total 4,958,000 304
Age
110,000 8
1 1° 2 234,000 13
3
-------
II
il
._
I
I
ft
Table 13-34. Consumer-Only Intake
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 2,214,000 125 1.18
Age
27,000 2 0.47
ll°2 51,000 4 0.63
35°toll 167,000 10 1.00
227,000 13 1.11
12 1°19 383,000 22 0.62
20 1°39 951,000 51 1.68
^^O69 408,000 23 2.57
Season
Fall 562,000 21 1.18
Spring 558,000 55 1.21
Summer 676,000 22 1.49
Winter 418,000 27 0.86
Urbanization
Central City 651,000 27 1.16
Non-metropolitan 758,000 51 1.68
Suburban 805,000 47 0.93
Race
Black 00 0.00
White 2,186,000 124 1.39
Region
Midwest 885,000 53 1.91
Northeast 230,000 13 0.56
545,000 31 0.85
S(West 554,000 28 1.54
Response to Questionnaire
Households who garden 2,107,000 120 3.09
229,000 11 3.12
Mean SE
0.51 0.05
* *
* *
* *
* *
0.38 0.06
0.43 0.04
0.58 0.09
0.55 0.09
0.47 0.09
0.39 0.05
0.73 0.15
0.52 0.12
0.58 0.09
0.45 0.06
-
0.52 0.05
0.63 0.08
* *
0.45 0.12
0.40 0.08
0.53 0.05
* *
of Home-Produced
pi
0.03
*
*
*
*
0.08
0.05
0.03
0.03
0.07
0.08
0.07
0.11
0.05
0.03
-
0.03
0.05
*
0.07
0.03
0.03
*
p5
0.07
*
*
*
*
0.08
0.07
0.03
0.05
0.08
0.12
0.07
0.14
0.07
0.05
-
0.07
0.11
*
0.08
0.05
0.07
*
plO
0.11
*
*
*
*
0.12
0.07
0.05
0.05
0.11
0.12
0.07
0.18
0.07
0.08
-
0.11
0.18
*
0.08
0.07
0.10
*
Beets
P25
0.19
*
*
*
*
0.14
0.21
0.27
0.26
0.14
0.18
0.28
0.26
0.18
0.14
-
0.21
0.32
*
0.18
0.12
0.21
*
(g/kg-day)
p50
0.40
*
*
*
*
0.29
0.40
0.45
0.36
0.27
0.40
0.52
0.40
0.39
0.40
-
0.40
0.45
*
0.26
0.29
0.40
*
p75
0.59
*
*
*
*
0.56
0.55
0.91
0.95
0.45
0.55
0.83
0.55
0.66
0.56
-
0.59
0.91
*
0.48
0.55
0.61
*
p90
1.03
*
*
*
*
1.00
0.93
1.36
1.36
0.87
0.62
1.13
0.91
1.36
0.93
-
1.03
1.15
*
0.66
0.62
1.03
*
p95
1.36
*
*
*
*
1.00
1.15
1.36
1.36
1.59
0.91
2.32
1.12
40LO°4.08
-
1.36
1.36
*
0.94
0.70
1.36
*
p99
3.69
*
*
*
*
1.12
1.40
1.59
1.40
4.08
0.91
3.69
3.69
2.32
-
3.69
3.69
*
4.08
2.32
3.69
*
MAX
4.08
*
*
*
*
1.12
1.40
1.59
1.40
4.08
0.91
3.69
3.69
4.08
2.32
-
4.08
3.69
*
4.08
2.32
4.08
*
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Q
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Table 13-35. Consumer-Only Intake of Home-Produced Broccoli (g/kg-day)
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 1,745,000 80 0.93
Age
Ito2 00 0.00
13,000 1 0.16
35°toll 187,000 9 1.12
102,000 4 0.50
12 1°19 486,000 19 0.79
20 to 39
761,000 37 1.34
^^O69 196,000 10 1.23
Season
Fall 624,000 20 1.31
Spring 258,000 27 0.56
Summer 682,000 22 1.50
Winter 181,000 11 0.37
Urbanization
Central City 165,000 5 0.29
Non-metropolitan 647,000 34 1.44
Suburban 933,000 41 1.08
Race
Black 0 0 0.00
White 1,719,000 79 1.09
Region
Midwest 792,000 38 1.71
Northeast 427,000 19 1.04
373,000 16 0.58
S(Wehst 153,000 7 0.42
Response to Questionnaire
Households who garden 1,729,000 78 2.54
599,000 29 8.17
Mean
0.42
-
*
*
*
*
0.41
*
0.29
0.54
0.51
*
*
0.42
0.43
-
0.42
0.26
*
*
*
0.42
0.47
* Intake data not provided for subpopulations for which there were
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
SE pi
0.05 0.08
-
* *
* *
* *
* *
0.07 0.08
* *
0.04 0.08
0.12 0.05
0.11 0.08
* *
* *
0.04 0.05
0.08 0.08
-
0.05 0.08
0.06 0.08
* *
* *
* *
0.05 0.08
0.08 0.05
p5
0.08
-
*
*
*
*
0.11
*
0.08
0.15
0.13
*
*
0.13
0.08
-
0.08
0.08
*
*
*
0.08
0.08
plO
0.16
-
*
*
*
*
0.16
*
0.08
0.17
0.18
*
*
0.17
0.14
-
0.16
0.08
*
*
*
0.16
0.15
p25
0.20
-
*
*
*
*
0.22
*
0.18
0.27
0.22
*
*
0.22
0.21
-
0.20
0.18
*
*
*
0.20
0.20
p50
0.29
-
*
*
*
*
0.35
*
0.23
0.33
0.40
*
*
0.37
0.24
-
0.29
0.21
*
*
*
0.29
0.31
p75
0.46
-
*
*
*
*
0.46
*
0.38
0.59
0.66
*
*
0.59
0.44
-
0.46
0.28
*
*
*
0.46
0.66
p90
0.82
-
*
*
*
*
0.61
*
0.45
1.25
0.89
*
*
0.75
p95
0.97
-
*
*
*
*
0.82
*
0.53
2.37
0.97
*
*
p99
2.48
-
*
*
*
*
3.02
*
0.82
3.02
2.48
*
*
0.680 392. 370 972.48
-
0.82
0.34
*
*
*
0.82
0.89
-
0.97
0.40
*
*
*
0.97
0.97
-
2.48
3.02
*
*
*
2.48
3.02
MAX
3.02
-
*
*
*
*
3.02
*
0.82
3.02
2.48
*
*
0.97
3.02
-
3.02
3.02
*
*
*
3.02
3.02
less than 20 observations.
Q
I
a
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^ >^
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I
ri
8.
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I
i
Table 13-36. Consumer-Only Intake of Home-Produced Cabbage (g/kg-day)
Population Nc Nc %
Group wgtd unwgtd Consuming Mean
Total
Age
Ito2
3 to 5 ,,
6 to 11
12 to 19
20 to 39
40>t^(69
Season
Fall
Spring
Summer
Winter
Urbanization
2,019,000 89
14,000 2
29,000 1
61,000 3
203,000 9
391,000 16
966,000 44
326,000 13
570,000 21
126,000 15
1,142,000 39
181,000 14
Central City 157,000 5
Non-metropolitan 1,079,000 48
Suburban
Race
B1$rnte
Region
Midwest
Northeast
S
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5 I
Table 13-37. Consumer-Only Intake of Home-Produced Carrots (g/kg-day)
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 4,322,000 193 2.30
Age
51,000 4 0.89
lto2 53,000 3 0.65
3£tSll 299,000 14 1.79
389,000 17 1.90
12 to19 1,043,000 46 1.69
20 to39 1,848,000 82 3.26
^tyf69 574,000 24 3.61
Season
F ,, 1,810,000 66 3.80
Spring 267,000 28 0.58
Summer 1,544,000 49 3.39
Winter 701,000 50 1.44
Urbanization
Central City 963,000 29 1.71
Non-metropolitan 1,675,000 94 3.72
Suburban 1,684,000 70 1.94
Race
107,000 7 0.49
BWSte 3,970,000 178 2.52
Region
Midwest 2,001,000 97 4.31
Northeast 735,000 29 1.79
378,000 20 0.59
S
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Table 13-38. Consumer-Only Intake of Home-Produced
Population Nc Nc
Group wgtd unwgtd
Total 6,891,000 421
Age
205,000 13
lto2 313,000 24
3i?to'll 689,000 43
530,000 32
12 to19 1,913,000 108
20 to39 2,265,000 142
^f69 871,000 53
Season
F ,, 2,458,000 89
Spring 1,380,000 160
Summer 1,777,000 62
Winter 1,276,000 110
Urbanization
Central City 748,000 27
Non-metropolitan 4,122,000 268
Suburban 2,021,000 126
Race
Black 188,000 9
White 6,703,000 412
Region
Midwest 2,557,000 188
Northeast 586,000 33
South 2,745,000 153
West 1,003,000 47
Response to Questionnaire
Households who garden 6233000 387
1739000 114
Households \
*
SE
P
Nc wgtd
Nc unwgtd
Source:
%
Consuming
3.67
3.60
3.86
4.12
2.59
3.11
3.99
5.48
5.16
2.99
3.91
2.62
1.33
9.16
2.33
0.86
4.26
5.51
1.42
4.27
2.78
9.15
23.73
Mean
0 89
*
1 25
093
0 59
060
0 86
094
0 54
064
1 82
0 55
074
0.96
0.80
*
0 89
093
061
0 87
1 00
0 88
1.20
SE pi
0 06 0 05
* *
0 26 0 33
0 17 Oil
0 10 0 10
0 06 0 07
Oil Oil
0 26 0 04
0 08 0 04
006 014
0 26 0 07
0 05 Oil
0 14 0 04
0.08 0.07
0.13 0.11
* *
007 005
0 10 0 04
0 08 0 10
0 10 0 07
028 Oil
0 06 0 05
0.18 0.04
p5 plO
0 12 0 17
* *
0 33 0 40
0 12 0 19
Oil 0 14
0 14 0 15
015 0 17
0 05 Oil
Oil 0 14
0 17 0 19
018 034
0 12 015
0 04 0 05
0.12 0.17
0.15 0.17
* *
0 12 0 16
0 12 0 17
0 17 0 19
0 12 0 17
015 015
0 14 0 17
0.11 0.17
Corn (g/kg-day)
p25 p50
0 24 0 48
* *
0 60 1 00
025 051
021 034
021 037
0 26 0 52
019 036
019 032
0 26 0 45
0 64 0 94
022 041
018 0 55
0.25 0.53
0.24 0.40
* *
0 24 0 48
0 25 0 46
0 24 0 38
028 056
018 040
0 24 0 50
0.23 0.38
p75
091
*
1 21
1 08
071
071
0 88
076
0 55
077
2 13
061
093
1.00
0.65
*
0 88
093
0 88
094
075
091
0.97
p90
100
*
1 67
3.13
1 55
1 53
1 42
1 34
1.27
1 21
452
1 16
204
p95
3 37
*
5 35
3.37
1 88
204
3 22
649
1.42
1.57
6 84
1 47
7.7.3
p99
744
*
5 35
4.52
1.88
3 70
744
923
5.35
5.15
923
204
3 04
2.13
L343.3g-.7l7.43.23
* * *
1 88 3 22 7 44
2.28
1 34
1 55
223
1 82
3.37
3.22
1.71
3 37
649
3 13
6.49
6.84
1.71
5 69
923
6 84
9.23
MAX
9.23
*
5 35
4.52
1.88
3.70
744
923
5.69
6.68
9.23
3 94
3 04
8.97
9.23
*
923
7.44
1.71
8.97
923
923
9.23
Intake data not provided for subpopulations for which there were less than 20 observations.
= Standard error.
= Percentile of the distribution.
= Weighted number of consumers.
= Unweighted number of consumers in survey.
Based on EPA's analyses of the 1987-1988 NFCS.
Q
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§
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1=
I
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a.
I
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I
tl
- 3
S
§
Table 13-39. Consumer-Only Intake of Home-Produced Cucumbers (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 3,994,000 141
Age
132,000 5
1 to 2 107,000 4
3£tSll 356,000 12
254,000 10
12 to 19 864,000 29
20 to39 1,882,000 68
40^(69 399,000 13
Season
F ,, 370,000 12
Spring 197,000 15
Summer 3,427,000 114
Winter 0 0
Urbanization
Central City 640,000 18
Non-metropolitan 1,530,000 64
Suburban 1,824,000 59
Race
86,000 2
BWSte 3,724,000 132
Region
Midwest 969,000 31
Northeast 689,000 22
1,317,000 54
S
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._
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ft
Table 13-40. Consumer-Only Intake of Home-Produced
Eggs (g/kg-day)
Population Nc Nc %
Total
Age
Ito2
3fPt5 11
12 to 19
20 to 39
40^7(69
Season
Fall
Spring
Summer
Winter
Urbanization
Group wgtd unwgtd
2,075,000 124
21,000 3
20,000 2
170,000 12
163,000 14
474,000 30
718,000 43
489,000 18
542,000 18
460,000 54
723,000 26
350,000 26
Central City 251,000 9
Non-metropolitan 1,076,000 65
Suburban
Race
BWSte
Region
Midwest
Northeast
S(wfet
748,000 50
63,000 9
2,012,000 115
665,000 37
87,000 7
823,000 44
500,000 36
Consuming
1.10
0.37
0.25
1.02
0.80
0.77
1.27
3.08
1.14
1.00
1.59
0.72
0.45
2.39
0.86
0.29
1.28
1.43
0.21
1.28
1.39
Mean
0.73
*
*
*
*
0.63
0.59
*
*
1.31
0.50
0.86
*
0.73
0.85
*
0.74
0.79
*
0.54
0.92
SE pi
0.10 0.07
* *
* *
* *
* *
0.09 0.07
0.06 0.14
* *
* *
0.29 0.16
0.08 0.07
0.10 0.17
* *
0.12 0.07
0.20 0.14
* *
0.11 0.07
0.20 0.07
* *
0.06 0.15
0.28 0.17
p5 pW
0.15 0.18
* *
* *
* *
* *
0.07 0.22
0.14 0.15
* *
* *
0.33 0.39
0.14 0.14
0.18 0.22
* *
0.14 0.17
0.15 0.21
* *
0.15 0.18
0.14 0.14
* *
0.18 0.20
0.21 0.21
p25 p50
0.27 0.47
* *
* *
* *
* *
0.30 0.42
0.32 0.51
* *
* *
0.50 0.67
0.26 0.33
0.40 0.75
* *
0.26 0.47
0.38 0.59
* *
0.27 0.48
0.22 0.34
* *
0.26 0.36
0.46 0.67
p75
0.90
*
*
*
*
0.81
0.84
*
*
1.31
0.54
1.17
*
0.92
1.17
*
0.90
1.08
*
0.60
1.05
p90
1.36
*
*
*
*
1.32
1.30
*
*
2.10
1.36
1.62
*
1.34
1.36j
*
1.36
1.51
*
1.18
1.36
p95
1.69
*
*
*
*
1.93
1.36
*
*
3.26
1.51
1.93
*
651.85
*
1.69
2.10
*
1.62
1.36
p99
6.58
*
*
*
*
2.50
1.38
*
*
13.50
1.65
1.93
*
6.58
13.509
*
6.58
9.16
*
1.93
13.50
MAX
13.50
*
*
*
*
2.50
1.38
*
*
13.50
1.65
1.93
*
1(13.50
*
13.50
9.16
*
1.93
13.50
Response to Questionnaire
Households who raise animals 1,824,000 113
741,000 44
18.06
10.11
0.75
0.90
0.11 0.07
0.17 0.15
0.15 0.17
0.17 0.18
0.26 0.48
0.27 0.67
0.90
1.19
1.36
1.65
1.85
1.85
6.58
6.58
13.50
9.16
Households wno lanii
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE
P
Nc wgtd
Nc unwgtd
Source:
= Standard error.
= Percentile of the distribution.
= Weighted number of consumers.
= Unweighted number of consumers in survey.
Based on EPA's analyses of the 1987-1988 NFCS.
Q
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Table 13-41.
Population Nc
Group wgtd
Total 2,707,000
Age
89,000
1 to 2 94,000
3^t5ll 362,000
462,000
12 to 19 844j000
20 to 39 694000
^tyc69 74,000
Season
Fall 876,000
Spring 554,000
Summer 273,000
Winter 1,004,000
Urbanization
Central City 506,000
Non-metropolitan 1,259,000
Suburban 942,000
Race
Black 0
White 2,605,000
Region
Midwest 1,321,000
Northeast 394,000
South 609,000
West 383,000
Response to Questionnaire
2,357,000
Consumer-Only
Intake of Home-Produced Game (g/kg-day)
Nc %
unwgtd Consuming Mean
185
8
8
28
27
59
41
7
31
68
9
77
20
101
64
0
182
97
20
47
21
158
1.44
1.56
1.16
2.17
2.25
1.37
1.22
0.47
1.84
1.20
0.60
2.06
0.90
2.80
1.09
0.00
1.65
2.85
0.96
0.95
1.06
11.66
0.97
*
*
1 09
1.04
0.82
096
*
1 00
0.91
*
1 07
069
0.95
1.15
098
0 88
1 13
1.26
0.63
1.04
SE pi
0.06 0.00
* *
* *
0 14 0 12
0.14 0.21
0.11 0.10
0 14 0 12
* *
0 16 0 12
0.09 0.00
* *
Oil 000
013 000
0.09 0.00
0.10 0.00
0 06 0 00
0 08 0 00
0 22 0 29
0.13 0.00
0.07 0.12
0.07 0.00
p5
0.12
*
*
023
0.21
0.12
0 17
*
0 15
0.10
*
000
000
0.12
0.26
0 12
008
029
0.12
0.15
0.14
pW p25
0.21 0.40
* *
* *
0 43 0 63
0.29 0.63
0.19 0.30
0 29 0 34
* *
0 22 0 43
0.17 0.44
* *
017 039
019 028
0.17 0.32
0.40 0.52
020 038
0 22 0 34
0 32 0 43
0.15 0.63
0.19 0.40
0.28 0.44
p50
0.71
*
*
076
0.85
0.63
0 51
*
063
0.75
*
0 82
063
0.66
0.82
073
061
077
1.09
0.63
0.75
p75
1.22
*
*
1 48
1.22
1.09
1 41
*
1 19
1.22
*
1 52
077
1.19
1.52
1 38
1 10
1 41
1.93
0.77
1.44
p90 p95
2.27 2.67
* *
* *
2 67 2 85
1.99 3.13
1.57 2.50
2.51 3.19
* *
2 50 3 13
1.75 2.52
* *
2.20 2.67
1 48 1 99
2.27
2.513.0?.854
2 34 2 85
1 99 251
3 13 3 13
2.38 3.19
1.12 1.22
2.38 2.90
p99
3.61
*
*
290
3.13
4.59
3.61
*
3 19
3.61
*
4.59
234
59-13
361
459
3 61
3.19
1.52
3.61
MAX
4.59
*
*
290
3.13
4.59
3.61
*
3 19
3.61
*
4.59
234
4.59
3.61
459
459
3 61
3.19
1.52
4.59
Households who hunL
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Q
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Table 13-42. Consumer-Only Intake of Home-Produced Lettuce (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 1,520,000 80
Age
54,000 4
1 to 2 25,000 2
3£tSll 173,000 7
71,000 3
12 to19 379,000 17
20 to 39 485,000 26
40^(69 317,000 20
Season
F n 214,000 8
Spring 352,000 35
Summer 856,000 30
Winter 98,000 7
Urbanization
Central City 268,000 8
Non-metropolitan 566,000 36
Suburban 686,000 36
Race
51,000 3
BWSte 1,434,000 75
Region
Midwest 630,000 33
Northeast 336,000 16
305,000 20
S
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5 I
Table 13-43. Consumer-Only Intake of Home-Produced Lima Beans (g/kg-day)
Population Nc Nc
Group Wgtd unwgtd
Total 1,917,000 109
Age
62,000 3
1 to 2 35,000 2
3£tSll 95,000 7
108,000 6
12 to 19 464,000 20
20 to 39 757,000 44
^yf69 361,000 25
Season
Fall 375,000 14
Spring 316,000 39
Summer 883,000 29
Winter 343,000 27
Urbanization
Central City 204,000 8
Non-metropolitan 1,075,000 69
Suburban 638,000 32
Race
Black 213,000 9
White 1,704,000 100
Region
Midwest 588,000 36
Northeast 68,000 6
South 1,261,000 67
West 0 0
Response to Questionnaire
Households who garden 1,610,000 97
62,000 6
%
Consuming
1.02
1.09
0.43
0.57
0.53
0.75
1.33
2.27
0.79
0.68
1.94
0.70
0.36
2.39
0.74
0.98
1.08
1.27
0.17
1.96
0.00
2.36
0.85
Mean SE
0.45 0.04
* *
* *
* *
* *
0.38 0.07
0.45 0.06
0.52 0.11
* *
0.42 0.06
0.50 0.10
0.53 0.06
* *
0.30 0.03
0.75 0.10
* *
0.38 0.03
0.43 0.06
* *
0.47 0.06
-
0.45 0.04
* *
pi
0.00
*
*
*
*
0.03
0.09
0.08
*
0.08
0.00
0.00
*
0.03
0.00
*
0.00
0.00
*
0.03
-
0.03
*
p5
0.09
*
*
*
*
0.11
0.11
0.19
*
0.09
0.09
0.03
*
0.09
0.08
*
0.09
0.00
*
0.10
-
0.09
*
pW
0.12
*
*
*
*
0.13
0.12
0.19
*
0.13
0.12
0.11
*
0.12
0.09
*
0.11
0.11
*
0.13
-
0.12
*
p25
0.19
*
*
*
*
0.18
0.20
0.23
*
0.23
0.17
0.31
*
0.17
0.32
*
0.18
0.25
*
0.18
-
0.18
*
p50
0.29
*
*
*
*
0.23
0.29
0.29
*
0.31
0.29
0.54
*
0.21
0.68
*
0.25
0.31
*
0.25
-
0.29
*
p75
0.55
*
*
*
*
0.49
0.56
0.64
*
0.55
0.49
0.76
*
0.32
0.99
*
0.49
0.42
*
0.63
-
0.53
*
p90
0.99
*
*
*
*
0.94
0.87
1.86
*
0.75
1.53
0.86
*
0.49
1.71
0.77
*
0.86
0.99
*
1.10
-
0.94
*
p95
1.69
*
*
*
*
1.10
1.71
1.86
*
1.31
1.71
0.87
*
1.86
*
0.99
1.53
*
1.71
-
1.71
*
p99 MAX
1.86 1.91
* *
* *
* *
* *
1.10 1.10
1.91 1.91
1.86 1.86
* *
1.91 1.91
1.86 1.86
1.69 1.69
* *
1.69 1.91
1.86 1.86
* *
1.53 1.91
1.69 1.69
* *
1.86 1.91
-
1.86 1.91
* *
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
Q
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8.
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1=
-------
ft
§
ft ft
s?
I
ft
Table 13-44. Consumer-Only Intake of Home-Produced Okra (g/kg-day)
Population Nc Nc
Group Wgtd unwgtd
Total 1,696,000 82
Age
53,000 2
1 to 2 68,000 3
3£tSll 218,000 11
194,000 9
121019 417,000 18
20 to39 587,000 32
40^(69 130,000 6
Season
F ,, 228,000 9
Spring 236,000 24
Summer 1,144,000 41
Winter 88,000 8
Urbanization
Central City 204,000 6
Non-metropolitan 1,043,000 55
Suburban 449,000 21
Race
236,000 13
BWSte 1,419,000 68
Region
Midwest 113,000 7
Northeast
„ , 1,443,000 70
West 140,000 5
Response to Questionnaire
Households who garden 1,564,000 77
233,000 14
%
Consuming
0.90
0.93
0.84
1.30
0.95
0.68
1.03
0.82
0.48
0.51
2.52
0.18
0.36
2.32
0.52
1.09
0.90
0.24
2.24
0.39
2.29
3.18
Mean
0.39
*
*
*
*
*
0.40
*
*
0.39
0.39
*
*
0.37
0.51
*
0.43
*
0.37
*
0.38
*
SE pi
0.04 0.00
* *
* *
* *
* *
* *
0.05 0.07
* *
* *
0.06 0.03
0.06 0.00
* *
* *
0.05 0.00
0.07 0.07
* *
0.04 0.00
* *
0.04 0.00
* *
0.04 0.00
* *
p5
0.05
*
*
*
*
*
0.11
*
*
0.05
0.05
*
*
0.03
0.10
*
0.07
*
0.05
*
0.05
*
pW p25
0.10 0.15
* *
* *
* *
* *
* *
0.14 0.25
* *
* *
0.07 0.11
0.10 0.14
* *
* *
0.08 0.15
0.11 0.31
* *
0.10 0.18
* *
0.08 0.14
* *
0.10 0.15
* *
p50
0.30
*
*
*
*
*
0.31
*
*
0.41
0.30
*
*
0.26
0.46
*
0.33
*
0.26
*
0.30
*
p75
0.46
*
*
*
*
*
0.46
*
*
0.60
0.44
*
*
0.44
0.60
*
0.52
*
0.44
*
0.45
*
p90
0.78
*
*
*
*
*
0.78
*
*
0.78
1.15
*
*
0.78
1.14
1
*
1.14
*
0.75
*
1.07
*
p95
1.21
*
*
*
*
*
1.14
*
*
1.00
1.53
*
*
1.15
53 1
*
1.21
*
1.21
*
1.21
*
p99
1.53
*
*
*
*
*
1.14
*
*
1.07
1.53
*
*
1.15
53 1
*
1.53
*
1.53
*
1.53
*
MAX
1.53
*
*
*
*
*
1.14
*
*
1.07
1.53
*
*
1.15
53
*
1.53
*
1.53
*
1.53
*
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-45. Consumer-Only Intake of Home-Produced
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 6,718,000 370 3.57
Age
291,000 17 5.11
lto2 178,000 9 2.20
3^t5ll 530,000 31 3.17
652,000 37 3.18
12 to19 1,566,000 78 2.54
20 to39 2,402,000 143 4.23
^Yf69 1,038,000 52 6.54
Season
Fall 1,557,000 59 3.27
Spring 1,434,000 147 3.11
Summer 2,891,000 101 6.36
Winter 836,000 63 1.72
Urbanization
Central City 890,000 37 1.58
Non-metropolitan 2,944,000 177 6.54
Suburban 2,884,000 156 3.33
Race
Black 253,000 16 1.16
White 6,266,000 345 3.98
Region
Midwest 2,487,000 143 5.36
Northeast 876,000 52 2.13
South 1,919,000 107 2.98
West 1,436,000 68 3.98
Response to Questionnaire
Households who garden 6,441,000 356 9.45
1,390,000 81 18.97
Mean
0.30
*
*
0.30
0.21
0.29
0.25
0.43
0.38
0.20
0.31
0.29
0.22
0.32
0.29
*
0.31
0.27
0.23
0.33
0.33
0.30
0.38
Households who farm
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
SE pi
0.02 0.00
* *
* *
0.06 0.01
0.04 0.01
0.03 0.01
0.02 0.00
0.09 0.00
0.07 0.00
0.02 0.00
0.03 0.01
0.04 0.00
0.03 0.00
0.02 0.01
0.04 0.00
* *
0.02 0.00
0.02 0.00
0.04 0.00
0.03 0.00
0.07 0.00
0.02 0.00
0.04 0.03
p5
0.01
*
*
0.01
0.01
0.04
0.00
0.01
0.03
0.01
0.02
0.00
0.01
0.03
0.01
*
0.01
0.04
0.00
0.03
0.01
0.01
0.04
plO
0.03
*
*
0.03
0.01
0.06
0.01
0.03
0.06
0.03
0.04
0.01
0.03
0.07
0.01
*
0.03
0.06
0.01
0.04
0.02
0.03
0.05
Onions (g/kg-day)
p25
0.09
*
*
0.11
0.06
0.09
0.08
0.14
0.12
0.06
0.11
0.03
0.07
0.14
0.06
*
0.09
0.10
0.01
0.15
0.06
0.09
0.11
p50
0.21
*
*
0.23
0.14
0.19
0.17
0.29
0.26
0.11
0.23
0.20
0.19
0.26
0.13
*
0.22
0.22
0.11
0.25
0.15
0.21
0.28
p75
0.38
*
*
0.38
0.26
0.30
0.36
0.46
0.44
0.26
0.38
0.46
0.30
0.43
0.36
*
0.39
0.34
0.35
0.39
0.39
0.38
0.52
p90
0.61
*
*
0.61
0.57
0.64
0.55
0.56
0.60
0.43
0.69
0.64
0.52
0.63
p95
0.91
*
*
1.36
0.76
0.94
0.69
2.68
0.78
0.52
0.97
0.92
0.56
0.64Q910.97
*
0.62
0.56
0.64
0.69
0.55
0.61
0.94
*
0.94
0.72
1.05
1.08
0.97
0.92
1.11
p99
1.49
*
*
1.36
0.91
1.49
1.11
3.11
3.11
1.41
1.49
1.36
0.56
1.49
3.11
*
1.77
1.34
1.36
1.49
3.11
1.77
1.49
MAX
3.11
*
*
1.36
0.91
1.49
1.41
3.11
3.11
1.77
1.49
1.36
0.56
1.77
3.11
*
3.11
1.34
1.41
1.77
3.11
3.11
1.49
less than 20 observations.
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Table 13-46. Consumer-Only Intake of Home-Produced Other Berries (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 1,626,000 99
Age
41,000 2
1 to 2 53,000 3
3£tSll 106,000 10
79,000 5
12 to19 309,000 20
20 to39 871,000 51
40^(69 159,000 7
Season
F ,, 379,000 13
Spring 287,000 29
Summer 502,000 18
Winter 458,000 39
Urbanization
Central City 378,000 15
Non-metropolitan 466,000 37
Suburban 722,000 45
Race
76,000 4
BWSte 1,490,000 93
Region
Midwest 736,000 56
Northeast 211,000 11
204,000 12
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Table 13-47.
Population Nc Nc
Group Wgtd unwgtd
Total 2,941,000 193
Age
103,000 8
1 to 2 65,000 6
3£tSll 329,000 26
177,000 13
12 to19 573,000 35
20 to39 1,076,000 70
40^(69 598,000 33
Season
F ,, 485,000 19
Spring 756,000 91
Summer 1,081,000 35
Winter 619,000 48
Urbanization
Central City 429,000 12
Non-metropolitan 1,110,000 99
Suburban 1,402,000 82
Race
39,000 1
BWSte 2,861,000 191
Region
Midwest 824,000 75
Northeast 75,000 5
852,000 51
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Table 13-48. Consumer-Only
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 1,513,000 94 0.80
Age
24,000 3 0.42
lto2 45,000 3 0.56
3^t5ll 145,000 10 0.87
121,000 7 0.59
12 to19 365,000 23 0.59
20 to39 557,000 33 0.98
^Yf69 256,000 15 1.61
Season
F ,, 308,000 11 0.65
Spring 355,000 39 0.77
Summer 474,000 16 1.04
Winter 376,000 28 0.77
Urbanization
Central City 222,000 11 0.39
Non-metropolitan 634,000 44 1.41
Suburban 657,000 39 0.76
Race
51,000 3 0.23
BWSte 1,462,000 91 0.93
Region
Midwest 688,000 57 1.48
Northeast 18,000 2 0.04
377,000 13 0.59
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Table 13-49. Consumer-Only Intake of Home-Produced Peas
Population Nc Nc %
Group Wgtd unwgtd Consuming
Total 4,252,000 226 2.26
Age
163,000 9 2.86
lto2 140,000 7 1.73
3£tSll 515,000 26 3.08
377,000 22 1.84
12 to19 1,121,000 52 1.82
20 to39 1,366,000 80 2.41
40^(69 458,000 26 2.88
Season
Fall 1,239,000 41 2.60
Spring 765,000 78 1.66
Summer 1,516,000 51 3.33
Winter 732,000 56 1.50
Urbanization
Central City 558,000 19 0.99
Non-metropolitan 2,028,000 126 4.50
Suburban 1,666,000 81 1.92
Race
Black 355,000 19 1.63
White 3,784,000 203 2.40
Region
Midwest 1,004,000 55 2.16
Northeast 241,000 14 0.59
South 2,449,000 132 3.81
West 558,000 25 1.55
Response to Questionnaire
Households who garden 3,980,000 214 5.84
884,000 55 12.06
Households who farm
Mean SE
0.51 0.03
* *
* *
0.61 0.09
0.41 0.04
0.41 0.06
0.46 0.05
0.33 0.06
0.30 0.03
0.44 0.04
0.59 0.07
0.75 0.09
* *
0.48 0.04
0.51 0.05
* *
0.50 0.03
0.40 0.07
* *
0.57 0.04
0.38 0.06
0.51 0.03
0.46 0.06
pi
0.05
*
*
0.15
0.06
0.10
0.07
0.03
0.03
0.06
0.07
0.12
*
0.08
0.07
*
0.03
0.03
*
0.13
0.07
0.03
0.03
p5
0.10
*
*
0.15
0.13
0.12
0.10
0.03
0.05
0.11
0.13
0.18
*
0.14
0.12
*
0.10
0.05
*
0.17
0.07
0.10
0.05
pW
0.14
*
*
0.22
0.16
0.14
0.12
0.05
0.12
0.12
0.17
0.21
*
0.17
0.13
*
0.13
0.10
*
0.20
0.10
0.14
0.09
p25
0.23
*
*
0.30
0.24
0.18
0.23
0.18
0.21
0.19
0.22
0.27
*
0.25
0.23
*
0.22
0.14
*
0.26
0.22
0.23
0.21
(g/kg-day)
p50
0.32
*
*
0.39
0.36
0.25
0.30
0.27
0.26
0.33
0.39
0.54
*
0.35
0.39
*
0.33
0.25
*
0.37
0.27
0.32
0.35
p75
0.62
*
*
0.90
0.50
0.41
0.61
0.37
0.35
0.52
0.82
0.95
*
0.58
0.68
*
0.60
0.35
*
0.68
0.48
0.63
0.52
p90
1.04
*
*
1.35
0.71
0.85
1.00
1.00
0.60
0.92
1.35
1.54
*
1.04
1.00
1
*
1.00
0.88
*
1.24
0.90
1.04
0.90
p95
1.46
*
*
1.40
0.82
1.36
1.30
1.00
0.71
1.40
1.60
2.36
*
1.30
36
*
1.40
1.54
*
1.60
0.94
1.54
1.40
p99
2.66
*
*
2.06
0.82
2.71
2.36
1.46
1.00
2.06
2.66
2.89
*
1.89
2.28
*
2.66
2.71
*
2.66
1.40
2.66
1.60
MAX
2.89
*
*
2.06
0.82
2.71
2.36
1.46
1.00
2.06
2.66
2.89
*
2.89
2.36
*
2.89
2.89
*
2.66
1.40
2.89
2.89
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-50. Consumer-Only Intake of Home-Produced
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 5,153,000 208 2.74
Age
163,000 6 2.86
lto2 108,000 5 1.33
3£tSll 578,000 26 3.46
342,000 16 1.67
12 to19 1,048,000 40 1.70
20 to39 2,221,000 88 3.92
^tyf69 646,000 25 4.07
Season
F ,, 1,726,000 53 3.62
Spring 255,000 28 0.55
Summer 2,672,000 94 5.87
Winter 500,000 33 1.03
Urbanization
Central City 865,000 30 1.53
Non-metropolitan 1,982,000 89 4.40
Suburban 2,246,000 87 2.59
Race
127,000 6 0.58
BWSte 4,892,000 198 3.11
Region
Midwest 1,790,000 74 3.86
Northeast 786,000 31 1.91
South i'739'000 72 2'70
West 778,000 29 2.16
Response to Questionnaire
Households who garden 4,898,000 199 7.19
867,000 35 11.83
Households who farm
Mean
*
*
0.23
*
0.22
0.25
0.26
0.20
0.30
0.25
0.24
0.25
*
0.25
0.23
0.23
0.21
0.24
0.30
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
SE pi
* *
* *
0.04 0.00
* *
0.06 0.02
0.03 0.01
0.06 0.02
0.03 0.00
0.07 0.00
0.04 0.04
0.04 0.01
0.03 0.00
* *
0.02 0.02
0.04 0.01
0.03 0.03
0.05 0.02
0.02 0.00
0.08 0.00
p5
*
*
0.00
*
0.03
0.03
0.02
0.03
0.02
0.06
0.02
0.03
*
0.03
0.02
0.07
0.02
0.02
0.03
pW
*
*
0.03
*
0.06
0.05
0.02
0.04
0.04
0.07
0.03
0.04
*
0.04
0.03
0.08
0.03
0.03
0.03
Peppers (g/kg-day)
p25
*
*
0.09
*
0.09
0.08
0.07
0.09
0.07
0.11
0.07
0.09
*
0.09
0.06
0.11
0.04
0.08
0.07
p50
*
*
0.16
*
0.12
0.17
0.14
0.17
0.15
0.18
0.12
0.16
*
0.15
0.15
0.17
0.09
0.15
0.17
p75
*
*
0.30
*
0.22
0.32
0.24
0.24
0.32
0.27
0.27
0.29
*
0.29
0.26
0.27
0.25
0.29
0.36
p90
*
*
0.43
*
0.40
0.48
0.92
0.35
1.09
0.36
0.54
0.49
0.77
*
0.49
0.39
0.43
0.54
0.48
0.60
p95
*
*
0.77
*
0.62
0.74
0.94
0.40
1.20
0.94
0.97
*
0.92
0.85
0.53
0.92
0.85
0.85
p99
*
*
0.85
*
2.48
1.50
1.07
1.07
1.53
1.10
2.48
1.50
*
1.81
2.48
1.81
1.07
1.50
2.48
MAX
*
*
0.85
*
2.48
1.50
1.07
1.07
1.53
1.10
2.48
1.53
*
2.48
2.48
1.81
1.07
2.48
2.48
less than 20 observations.
ft
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Table 13-51. Consumer-Only Intake of Home-Produced Pork (g/kg-day)
Population Nc
Total
Age
Ito2
3!Pto' 11
12 to 19
20 to 39
40,17(69
Season
Fall
Spring
Summer
Winter
Urbanization
Group Wgtd
1,732,000
38,000
26,000
129,000
291,000
511,000
557,000
180,000
362,000
547,000
379,000
444,000
Central City 90,000
Non-metropolitan 1,178,000
Suburban
Race
Black
White
Region
Midwest
Northeast
^*wlfet
464,000
0
1,732,000
844,000
97,000
554,000
237,000
Nc
%
unwgtd Consuming Mean SE
121
5
3
11
20
32
38
12
13
59
15
34
2
77
42
0
121
64
5
32
20
0.92
0.67
0.32
0.77
1.42
0.83
0.98
1.13
0.76
1.19
0.83
0.91
0.16
2.62
0.54
0.00
1.10
1.82
0.24
0.86
0.66
1.23 0.10
* *
* *
* *
1.28 0.24
1.21 0.18
1.02 0.12
* *
* *
1.13 0.13
* *
1.40 0.24
* *
1.39 0.13
0.88 0.12
-
1.23 0.10
1.06 0.12
* *
1.35 0.15
1.15 0.31
pi p5
0.09 0.14
* *
* *
* *
0.31 0.32
0.11 0.28
0.12 0.18
* *
* *
0.11 0.14
* *
0.13 0.26
* *
0.09 0.22
0.11 0.12
-
0.09 0.14
0.09 0.12
* *
0.18 0.26
0.13 0.32
plO p25
0.31 0.54
* *
* *
* *
0.34 0.52
0.41 0.55
0.22 0.41
* *
* *
0.22 0.35
* *
0.38 0.50
* *
0.41 0.62
0.18 0.33
-
0.31 0.54
0.21 0.50
* *
0.34 0.81
0.38 0.44
p50
0.90
*
*
*
0.89
0.79
0.81
*
*
0.90
*
0.88
*
0.97
0.59
-
0.90
0.67
*
1.26
0.73
p75
1.71
*
*
*
1.75
1.43
1.71
*
*
1.50
*
2.21
*
1.75
1.10
-
1.71
1.20
*
1.75
1.10
p90
2.73
*
*
*
3.69
2.90
1.78
*
*
2.68
*
3.08
*
3.16
2.28
3.69
-
2.73
2.68
*
2.44
1.75
p95
3.37
*
*
*
3.69
3.08
2.28
*
*
3.68
*
4.93
*
2.73
-
3.37
3.37
*
3.08
2.73
p99
4.93
*
*
*
4.29
4.93
3.16
*
*
4.29
*
7.41
*
4.93
2.90
-
4.93
3.69
*
4.29
7.41
MAX
7.41
*
*
*
4.29
4.93
3.16
*
*
4.29
*
7.41
*
7.41
2.90
-
7.41
3.73
*
4.29
7.41
Response to Questionnaire
Households who raise animals 1,428,000
Households \
*
-
SE
P
Nc wgtd
Nc unwgtd
Source:
1,218,000
vho farm
100
82
14.14
16.62
Intake data not provided for subpopulations for which there were
Indicates data are not available.
= Standard error.
= Percentile of the distribution.
= Weighted number of consumers.
1.34 0.10
1.30 0.11
0.14 0.32
0.22 0.34
0.41 0.59
0.41 0.59
0.97
0.92
1.75
1.71
2.90
3.08
3.37
3.69
4.29
4.93
4.93
4.93
less than 20 observations.
= Unweighted number of consumers in survey.
Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-52. Consumer-Only Intake of Home-Produced Poultry (g/kg-day)
Population Nc Nc
Group Wgtd unwgtd
Total 1,816,000 105
Age
91,000 8
1 to 2 70,000 5
3£tSll 205,000 12
194,000 12
121019 574,000 33
20 to 39 568,000 30
40^(69 80,000 3
Season
F ,, 562,000 23
Spring 374,000 34
Summer 312,000 11
Winter 568,000 37
Urbanization
Central City 230,000 8
Non-metropolitan 997,000 56
Suburban 589,000 41
Race
44,000 2
BWSte 1,772,000 103
Region
Midwest 765,000 41
Northeast 64,000 4
654,000 38
S
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1 3
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I,
Table 13-53. Consumer-Only Intake of Home-Produced Pumpkins (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 2,041,000 87
Age
73,000 4
lto2 18,000 2
3^t5ll 229,000 9
244,000 10
121019 657,000 26
201039 415,000 20
40>17$9 373,000 15
Season
F ,, 1,345,000 49
Spring 48,000 6
Summer 405,000 13
Winter 243,000 19
Urbanization
Central City 565,000 20
Non-metropolitan 863,000 44
Suburban 613,000 23
Race
22,000 1
BWSte 2,019,000 86
Region
Midwest 1,370,000 54
Northeast 15,000 1
179,000 10
S
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Table 13-54. Consumer-Only Intake of Home-Produced Snap Beans (g/kg-day)
Population Nc Nc
Group wgtd Unwgtd
Total 12,308,000 739
Age
246,000 17
1 to 2 455,000 32
3^t5ll 862,000 62
1,151,000 69
12 to19 2,677,000 160
20 to 39 4,987,000 292
40^(69 1,801,000 100
Season
F ,, 3,813,000 137
Spring 2,706,000 288
Summer 2,946,000 98
Winter 2,843,000 216
Urbanization
Central City 2,205,000 78
Non-metropolitan 5,696,000 404
Suburban 4,347,000 255
Race
634,000 36
BWSte 11,519,000 694
Region
Midwest 4,651,000 307
Northeast 990,000 52
4,755,000 286
S(Wfet 1,852,000 92
Response to Questionnaire
Households who garden 11,843,000 700
2,591,000 157
%
Consuming
6.55
4.32
5.62
5.16
5.62
4.35
8.79
11.34
8.00
5.86
6.48
5.84
3.91
12.65
5.02
2.92
7.31
10.02
2.40
7.39
5.14
17.38
35.35
Mean SE
0.80 0.03
* *
1.49 0.24
0.90 0.12
0.64 0.06
0.61 0.04
0.72 0.03
0.92 0.12
0.81 0.08
0.90 0.05
0.63 0.05
0.86 0.05
0.60 0.06
0.96 0.05
0.70 0.04
0.76 0.14
0.81 0.03
0.86 0.06
0.57 0.07
0.88 0.04
0.59 0.04
0.79 0.03
0.80 0.05
pi
0.06
*
0.00
0.00
0.00
0.07
0.10
0.06
0.06
0.03
0.00
0.11
0.06
0.09
0.10
0.25
0.07
0.07
0.00
0.13
0.07
0.06
0.06
p5
0.15
*
0.00
0.20
0.16
0.13
0.16
0.07
0.15
0.15
0.12
0.18
0.07
0.18
0.14
0.25
0.15
0.15
0.10
0.21
0.14
0.15
0.13
plO
0.19
*
0.35
0.22
0.22
0.16
0.23
0.15
0.18
0.22
0.16
0.24
0.16
0.23
0.19
0.28
0.19
0.19
0.11
0.25
0.18
0.19
0.19
p25
0.34
*
0.90
0.32
0.32
0.26
0.36
0.37
0.27
0.37
0.33
0.42
0.26
0.37
0.34
0.30
0.35
0.34
0.18
0.40
0.27
0.33
0.41
p50
0.57
*
1.16
0.64
0.50
0.50
0.56
0.64
0.54
0.59
0.50
0.62
0.51
0.68
0.52
0.48
0.57
0.55
0.49
0.68
0.51
0.56
0.66
p75
1.04
*
1.66
1.21
0.81
0.79
0.86
1.22
1.18
1.11
0.85
1.12
0.71
1.19
0.93
1.04
1.06
0.99
0.82
1.22
0.74
1.02
1.12
p90
1.58
*
3.20
1.79
1.34
1.24
1.45
1.70
1.52
1.72
1.30
1.72
1.23
1.89
1.36
2.70
1.30
1.63
1.70
1.28
1.72
1.20
1.60
1.54
p95 p99
2.01 3.90
* *
4.88 6.90
2.75 4.81
1.79 2.72
1.64 2.05
1.77 2.70
2.01 9.96
2.01 4.82
2.85 5.66
1.70 2.05
2.02 3.85
1.54 1.93
4.88
1.77 2.98
1.34 5.98
2.01 3.90
2.47 4.88
1.36 1.97
2.01 3.23
1.52 2.19
2.01 3.85
1.98 2.96
MAX
9.96
*
6.90
5.66
2.72
4.26
4.23
9.96
9.96
6.90
2.63
7.88
3.35
9.96
6.08
5.98
9.96
9.96
3.09
5.98
2.19
9.96
4.23
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-55. Consumer-Only Intake of Home-Produced Strawberries (g/kg-day)
Population Nc Nc %
Group wgtd unwgtd Consuming
Total 2,057,000 139 1.09
Age
30,000 2 0.53
lto2 66,000 6 0.81
3^t5ll 153,000 15 0.92
201,000 11 0.98
12 to19 316,000 22 0.51
20 to39 833,000 55 1.47
40^(69 449,000 27 2.83
Season
Fall 250,000 8 0.52
Spring 598,000 66 1.30
Summer 388,000 11 0.85
Winter 821,000 54 1.69
Urbanization
Central City 505,000 23 0.90
Non-metropolitan 664,000 52 1.47
Suburban 888,000 64 1.03
Race
Black 00 0.00
White 2,057,000 139 1.31
Region
Midwest 1,123,000 76 2.42
Northeast 382,000 25 0.93
South 333,000 23 0.52
West 219,000 15 0.61
Response to Questionnaire
Households who garden 1,843,000 123 2.70
87,000 9 1.19
Households who farm
Mean SE
0.65 0.05
* *
* *
* *
* *
0.32 0.06
0.64 0.06
0.64 0.11
* *
0.83 0.10
* *
0.51 0.06
0.75 0.12
0.62 0.11
0.62 0.06
-
0.65 0.05
0.69 0.08
0.64 0.10
0.67 0.08
* *
0.64 0.05
* *
pi
0.04
*
*
*
*
0.08
0.02
0.04
*
0.08
*
0.02
0.04
0.02
0.08
0.04
0.02
0.09
0.13
*
0.04
*
p5
0.08
*
*
*
*
0.08
0.07
0.04
*
0.09
*
0.04
0.04
0.07
0.18
0.08
0.07
0.16
0.21
*
0.08
*
plO
0.12
*
*
*
*
0.11
0.18
0.09
*
0.18
*
0.11
0.09
0.08
0.22
0.12
0.08
0.18
0.38
*
0.12
*
p25
0.26
*
*
*
*
0.12
0.36
0.26
*
0.28
*
0.21
0.38
0.13
0.35
0.26
0.18
0.26
0.52
*
0.23
*
p50
0.47
*
*
*
*
0.21
0.58
0.47
*
0.47
*
0.39
0.49
0.39
0.53
0.47
0.42
0.47
0.62
*
0.45
*
p75
0.82
*
*
*
*
0.46
0.94
0.70
*
0.97
*
0.60
1.33
0.81
0.70
0.82
1.00
0.87
0.70
*
0.82
*
p90
1.47
*
*
*
*
0.82
1.42
1.66
*
1.93
*
1.27
1.47
1.66
1.27
2.16
1.47
1.66
1.46
1.00
*
1.46
*
p95
1.77
*
*
*
*
0.97
1.47
1.89
*
2.54
*
1.46
1.69
1.56
1.77
1.93
1.83
1.00
*
1.77
*
p99
2.72
*
*
*
*
1.56
2.37
2.72
*
4.83
*
2.37
2.37
4.83
2.97
2.72
2.97
2.16
2.72
*
2.54
*
MAX
4.83
*
*
*
*
1.56
2.37
2.72
*
4.83
*
2.37
2.37
4.83
2.97
4.83
4.83
2.16
2.72
*
4.83
*
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Sandard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-56. Consumer-Only Intake of Home-Produced Tomatoes (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 16,737,000 743
Age
572,000 26
lto2 516,000 26
3£tSll 1,093,000 51
1,411,000 61
12 to19 4,169,000 175
20 to 39 6,758,000 305
40^(69 1,989,000 89
Season
F n 5,516,000 201
Spring 1,264,000 127
Summer 8,122,000 279
Winter 1,835,000 136
Urbanization
Central City 2,680,000 90
Non-metropolitan 7,389,000 378
Suburban 6,668,000 275
Race
743,000 28
BWSte 15,658,000 703
Region
Midwest 6,747,000 322
Northeast 2,480,000 87
4,358,000 202
S
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Table 13-57. Consumer-Only Intake of Home-Produced White Potatoes (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 5,895,000 281
Age
147,000 10
lto2 119,000 6
3^t5ll 431,000 24
751,000 31
12 to19 1,501,000 66
201039 1,855,000 95
^tyf69 1,021,000 45
Season
Fall 2,267,000 86
Spring 527,000 58
Summer 2,403,000 81
Winter 698,000 56
Urbanization
Central City 679,000 25
Non-metropolitan 3,046,000 159
Suburban 2,110,000 95
Race
Black 140,000 5
White 5,550,000 269
Region
Midwest 2,587,000 133
Northeast 656,000 31
South 1,796,000 84
West 796,000 31
Response to Questionnaire
Households who garden 5,291,000 250
1,082,000 62
%
Consuming
3.14
2.58
1.47
2.58
3.67
2.44
3.27
6.43
4.76
1.14
5.28
1.43
1.20
6.77
2.44
0.64
3.52
5.58
1.59
2.79
2.21
7.76
14.76
Mean
1.66
*
*
2.19
1.26
1.24
1.86
1.27
1.63
1.23
1.63
2.17
0.96
1.96
1.49
*
1.67
1.77
1.28
2.08
0.76
1.65
1.83
Households who farm
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
SE pi
0.11 0.00
* *
* *
0.39 0.00
0.19 0.07
0.12 0.16
0.23 0.13
0.12 0.21
0.22 0.16
0.13 0.07
0.18 0.00
0.20 0.14
0.15 0.16
0.16 0.18
0.17 0.11
* *
0.11 0.14
0.15 0.18
0.20 0.07
0.24 0.16
0.11 0.16
0.11 0.00
0.18 0.07
p5
0.19
*
*
0.00
0.19
0.16
0.26
0.22
0.22
0.11
0.19
0.40
0.16
0.27
0.19
*
0.21
0.24
0.13
0.35
0.22
0.21
0.21
pW
0.31
*
*
0.41
0.26
0.20
0.35
0.36
0.27
0.20
0.32
0.50
0.18
0.37
0.32
*
0.31
0.34
0.17
0.46
0.26
0.31
0.58
p25
0.55
*
*
0.72
0.38
0.48
0.70
0.55
0.46
0.41
0.62
0.86
0.38
0.77
0.54
*
0.55
0.64
0.35
0.92
0.41
0.56
0.92
p50
1.27
*
*
1.76
1.22
1.00
1.31
1.21
1.13
0.86
1.32
2.02
0.56
1.50
0.93
*
1.28
1.35
0.86
1.56
0.54
1.28
1.46
p75
2.07
*
*
3.10
1.80
1.62
2.04
1.69
1.79
1.91
2.09
2.95
1.52
2.38
1.68
*
2.09
2.15
1.97
2.40
0.96
2.09
2.31
p90
3.11
*
*
5.94
2.95
2.54
3.43
2.35
3.43
2.86
3.08
4.26
2.07
3.55
3.11
*
3.11
3.77
2.95
3.44
1.40
3.10
3.80
p95
4.76
*
*
6.52
3.11
3.08
5.29
2.88
4.14
3.08
5.29
5.40
2.25
5.64
4.76
*
4.76
5.29
3.80
5.64
1.95
4.28
5.09
p99 MAX
9.52 12.80
* *
* *
6.52 6.52
4.14 4.14
4.29 5.09
12.80 12.80
3.92 3.92
12.80 12.80
4.28 4.28
9.43 9.43
6.00 6.00
2.54 2.54
12.80 12.80
9.43 9.43
* *
9.52 12.80
9.43 9.43
5.09 5.09
12.80 12.80
3.11 3.11
9.52 12.80
6.52 6.52
less than 20 observations.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-58. Consumer-Only Intake of Home-Produced Exposed Fruit (g/kg-day)
Population Nc Nc
%
Group Wgtd unwgtd Consuming Mean
Total 11,770,000 679
Age
306,000 19
1 to 2 470,000 30
3^t5ll 915,000 68
896,000 50
12 to19 2,521,000 139
20 to 39 4,272,000 247
^tyf69 2,285,000 118
Season
F ,, 2,877,000 100
Spring 2,466,000 265
Summer 3,588,000 122
Winter 2,839,000 192
Urbanization
Central City 2,552,000 99
Non-metropolitan 3,891,000 269
Suburban 5,267,000 309
Race
250,000 12
BWSte 11,411,000 663
Region
Midwest 4,429,000 293
Northeast 1,219,000 69
2,532,000 141
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Table 13-59. Consumer-Only Intake of Home-Produced Protected
Population Nc Nc %
Group Wgtd unwgtd Consuming
Total 3,855,000 173 2.05
Age
Ito2 79,000 5 1.39
3 to 5 80,000 4 0.99
6 to 11 181,000 9 1.08
377,000 20 1.84
12 to19 755,000 29 1.23
20 to39 1,702,000 77 3.00
^tyf69 601,000 26 3.78
Season
Fall 394,000 12 0.83
Spring 497,000 36 1.08
Summer 1,425,000 47 3.13
Winter 1,539,000 78 3.16
Urbanization
Central City 1,312,000 50 2.33
Non-metropolitan 506,000 19 1.12
Suburban 2,037,000 104 2.35
Race
Black 200,000 8 0.92
White 3,655,000 165 2.32
Region
Midwest 657,000 24 1.42
Northeast 105,000 5 0.26
1,805,000 74 2.81
S(Wfet 1,288,000 70 3.57
Response to Questionnaire
Households who garden 3,360,000 146 4.93
Houccholdc vho farm 357'000 14 4'87
Mean
5.74
*
*
*
2.96
4.51
5.65
4.44
*
2.08
7.39
6.24
3.94
*
6.83
*
5.91
10.70
*
4.77
4.85
5.90
*
* Intake data not provided for subpopulations for which there were
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
SE
0.63
*
*
*
0.99
1.08
0.87
0.69
*
0.35
1.45
0.91
0.58
*
0.94
*
0.65
2.60
*
0.65
0.93
0.70
*
pi
0.15
*
*
*
0.12
0.18
0.11
0.26
*
0.16
0.11
0.15
0.15
*
0.11
*
0.12
0.25
*
0.16
0.11
0.12
*
p5
0.27
*
*
*
0.16
0.36
0.24
0.26
*
0.18
0.27
0.30
0.26
*
0.25
*
0.26
0.26
*
0.36
0.18
0.27
*
plO
0.34
*
*
*
0.28
0.49
0.29
0.29
*
0.26
0.39
0.38
0.33
*
0.29
*
0.33
0.29
*
0.45
0.27
0.34
*
P25
0.93
*
*
*
0.39
1.22
0.67
1.95
*
0.38
1.25
1.39
0.83
*
0.59
*
1.06
1.18
*
1.23
0.49
1.16
*
Fruits (g/kg-day)
p50
2.34
*
*
*
1.23
1.88
2.22
3.29
*
1.22
3.06
2.65
3.01
*
2.01
*
2.44
7.44
*
2.54
1.84
2.42
*
P75
7.45
*
*
*
2.84
4.47
9.36
7.06
*
4.08
10.30
8.23
5.01
*
10.30
*
7.46
14.60
*
5.10
5.34
7.46
*
p90
16.00
*
*
*
7.44
14.60
15.50
8.97
*
5.10
16.60
17.80
9.23
*
17.90
*
16.00
24.10
*
15.20
12.30
16.00
*
p95
19.70
*
*
*
11.40
16.10
21.20
9.97
*
6.57
24.10
21.20
9.97
*
23.80
*
21.20
41.30
*
16.60
18.80
19.10
*
p99 MAX
47.30 53.60
* *
* *
* *
19.10 19.10
24.10 24.10
41.30 41.30
15.20 15.20
* *
6.79 6.79
53.60 53.60
47.30 47.30
18.80 18.80
* *
53.60 53.60
* *
47.30 53.60
53.60 53.60
* *
23.80 24.00
47.30 47.30
47.30 53.60
* *
less than 20 observations.
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Table 13-60. Consumer-Only Intake of Home-Produced Exposed Vegetables
Population Nc Nc
Group wgtd unwgtd
Total 28,762,000 1,511
Age
815,000 43
1 to 2 1,069,000 62
3^t5ll 2,454,000 134
2,611,000 143
12 to19 6,969,000 348
20 to 39 10,993,000 579
^tyf69 3,517,000 185
Season
F u 8,865,000 314
Ipring 4,863,000 487
Summer 10,151,000 348
Winter 4,883,000 362
Urbanization
Central City 4,859,000 173
Non-metropolitan 11,577,000 711
Suburban 12,266,000 625
Race
1,713,000 100
BWSte 26,551,000 1,386
Region
Midwest 10,402,000 570
Northeast 4,050,000 191
9,238,000 503
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Table 13-61
Population Nc
Group Wgtd
Total 11,428,000
Age
1 to 2 348,000
3 to 5 440,000
6 to 11 1,052,000
12 to 19 910,000
20 to 39 3,227,000
40 1 69 3,818,000
>70 1,442,000
Season
Fall 3,907,000
Spring 2,086,000
Summer 3,559,000
Winter 1,876,000
Urbanization
Central City 1,342,000
Non-metropolitan 5,934,000
Suburban 4,152,000
Race
Black 479,000
White 10,836,000
Region
Midwest 4,359,000
Northeast 807,000
South 4,449,000
West 1,813,000
Response to Questionnaire
Households who garden 10,286,000
Houcoholdc vho farm 2,325,000
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
. Consumer-Only Intake of Home-Produced
Nc
%
unwgtd Consuming
656
21
32
63
51
164
226
89
143
236
118
159
49
391
216
27
625
273
48
253
82
602
142
6.08
6.11
5.43
6.30
4.44
5.24
6.73
9.08
8.20
4.52
7.82
3.85
2.38
13.18
4.80
2.20
6.88
9.40
1.96
6.92
5.03
15.09
31.72
Mean
1.01
2.46
1.30
1.10
0.78
0.76
0.93
1.05
0.85
0.70
1.40
0.93
1.00
1.07
0.93
1.50
0.99
1.01
0.70
1.08
0.96
1.01
1.30
SE
0.05
0.49
0.21
0.13
0.09
0.06
0.07
0.16
0.07
0.04
0.16
0.08
0.15
0.06
0.08
0.23
0.05
0.07
0.09
0.07
0.16
0.05
0.15
pi
0.10
0.32
0.23
0.19
0.06
0.11
0.07
0.12
0.12
0.06
0.10
0.12
0.12
0.11
0.07
0.16
0.10
0.11
0.06
0.13
0.07
0.10
0.09
p5
0.15
0.32
0.23
0.21
0.16
0.15
0.14
0.21
0.16
0.14
0.18
0.14
0.15
0.17
0.15
0.26
0.15
0.17
0.15
0.17
0.12
0.15
0.17
Protected Vegetables
plO
0.19
0.54
0.32
0.32
0.24
0.17
0.17
0.24
0.20
0.17
0.23
0.18
0.17
0.21
0.19
0.33
0.19
0.23
0.17
0.21
0.15
0.19
0.21
p25
0.32
1.36
0.48
0.39
0.35
0.24
0.32
0.36
0.32
0.27
0.38
0.31
0.32
0.35
0.29
0.87
0.32
0.33
0.27
0.38
0.21
0.34
0.34
p50
0.63
1.94
1.04
0.79
0.58
0.51
0.60
0.57
0.57
0.49
0.78
0.60
0.72
0.65
0.56
0.94
0.61
0.57
0.51
0.71
0.48
0.64
0.60
(g/kg-day)
p75
1.20
2.96
1.48
1.31
0.82
0.97
1.11
1.21
1.10
0.91
1.69
1.20
1.18
1.30
1.15
2.20
1.20
1.08
0.99
1.38
1.01
1.21
1.40
p90
2.24
3.88
2.51
2.14
1.85
1.73
1.87
1.86
1.73
1.44
3.05
2.32
2.36
2.51
1.85
3.05
2.17
2.45
1.71
2.32
1.86
2.32
3.55
p95
3.05
9.42
5.10
3.12
2.20
2.51
3.04
3.05
2.51
1.86
5.40
3.06
2.83
3.55
2.67
3.23
3.04
3.68
2.33
3.05
3.12
3.05
5.40
p99 MAX
6.49 9.42
9.42 9.42
5.31 5.31
5.40 5.40
2.69 2.69
3.63 4.76
6.84 7.44
9.23 9.23
4.78 5.31
3.74 5.73
9.23 9.42
4.76 6.39
4.78 4.78
6.84 9.42
6.49 9.23
4.95 4.95
6.49 9.42
6.84 7.44
2.77 2.77
5.40 9.42
9.23 9.23
6.49 9.23
9.23 9.23
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-62.
Population Nc Nc
Group Wgtd unwgtd
Total 13,750,000 743
Age
371,000 22
1 to 2 390,000 23
3^t5ll 1,106,000 67
1,465,000 76
12 to19 3,252,000 164
20 to 39 4,903,000 276
^tyf69 2,096,000 107
Season
F ,, 4,026,000 153
Spring 2,552,000 260
Summer 5,011,000 169
Winter 2,161,000 161
Urbanization
Central City 2,385,000 96
Non-metropolitan 6,094,000 366
Suburban 5,211,000 279
Race
521,000 31
BWSte 12,861,000 697
Region
Midwest 5,572,000 314
Northeast 1,721,000 92
3,842,000 205
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Table 13-63. Consumer-Only Intake of Home-Produced Dark Green Vegetables (g/kg-day)
Population Nc Nc %
Group Wgtd unwgtd Consuming
Total 8,855,000 428 4.71
Age
180,000 8 3.16
lto2 226,000 12 2.79
3^t5ll 826,000 39 4.94
628,000 32 3.07
12 to19 1,976,000 87 3.21
20 to39 3,710,000 184 6.54
^tyf69 1,253,000 63 7.89
Season
Fall 2,683,000 88 5.63
Spring 1,251,000 127 2.71
Summer 3,580,000 124 7.87
Winter 1,341,000 89 2.75
Urbanization
Central City 1,298,000 48 2.30
Non-metropolitan 3,218,000 167 7.15
Suburban 4,279,000 211 4.94
Race
724,000 49 3.33
BWSte 7,963,000 373 5.05
Region
Midwest 2,668,000 121 5.75
Northeast 1,554,000 76 3.77
South 2,945,000 148 4.58
West 1,628,000 81 4.51
Response to Questionnaire
Households who garden 8,521,000 412 12.50
1,450,000 66 19.78
Mean
0.39
*
*
0.31
0.42
0.34
0.40
0.41
0.44
0.56
0.34
0.27
0.27
0.33
0.48
1.04
0.32
0.28
0.51
0.48
0.32
0.40
0.38
SE
0.03
*
*
0.05
0.15
0.06
0.04
0.07
0.07
0.08
0.04
0.04
0.04
0.04
0.05
0.18
0.02
0.04
0.09
0.05
0.07
0.03
0.06
pi
0.00
*
*
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
p5
0.00
*
*
0.01
0.01
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.01
0.10
0.00
0.00
0.00
0.07
0.00
0.00
0.00
pW
0.01
*
*
0.02
0.01
0.01
0.03
0.01
0.09
0.01
0.01
0.01
0.01
0.02
0.02
0.11
0.01
0.01
0.00
0.09
0.01
0.01
0.01
p25 p50
0.09 0.21
* *
* *
0.09 0.18
0.06 0.20
0.09 0.18
0.08 0.23
0.11 0.23
0.15 0.24
0.10 0.31
0.06 0.15
0.02 0.15
0.11 0.21
0.07 0.17
0.09 0.23
0.22 0.55
0.08 0.20
0.06 0.21
0.06 0.20
0.15 0.29
0.04 0.11
0.09 0.21
0.07 0.23
p75
0.44
*
*
0.39
0.37
0.38
0.48
0.47
0.46
0.54
0.41
0.37
0.32
0.45
0.46
1.17
0.38
0.36
0.49
0.64
0.31
0.45
0.48
p90
0.92
*
*
0.95
0.92
0.67
0.98
0.93
0.79
1.28
0.98
0.66
0.63
0.75
1.15
3.29
0.78
0.50
1.25
0.92
0.66
0.92
0.95
p95
1.25
*
*
1.04
1.64
0.92
1.25
1.08
1.08
2.81
1.15
1.17
0.92
1.00
2'182.48
3.86
1.07
0.98
1.93
1.28
0.93
1.25
1.25
p99
3.53
*
*
1.28
4.86
2.94
3.29
3.45
3.86
4.86
2.48
2.04
1.07
3.86
4.86
2.37
2.48
3.53
3.86
4.86
3.53
2.48
MAX
5.82
*
*
1.28
4.86
4.29
5.82
3.45
4.29
5.82
2.48
2.18
1.07
5.82
4.86
4.86
5.82
3.02
5.82
4.29
4.86
5.82
3.02
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-64. Consumer-Only Intake of Home-Produced Deep Yellow Vegetables (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 5,467,000 245
Age
124,000 8
lto2 61,000 4
3^t5ll 382,000 17
493,000 21
12 to19 1,475,000 63
20 to 39 2,074,000 96
^tyf69 761,000 32
Season
Fall 2,664,000 97
Spring 315,000 34
Summer 1,619,000 52
Winter 869,000 62
Urbanization
Central City 1,308,000 43
Non-metropolitan 2,100,000 118
Suburban 2,059,000 84
Race
Black 129,000 8
White 5,093,000 229
Region
Midwest 2,792,000 128
Northeast 735,000 29
South 557,000 30
West 1,383,000 58
Response to Questionnaire
Households who garden 5,177,000 233
1,088,000 51
%
Consuming
2.91
2.18
0.75
2.29
2.41
2.39
3.66
4.79
5.59
0.68
3.56
1.78
2.32
4.66
2.38
0.59
3.23
6.02
1.79
0.87
3.83
7.60
14.85
Mean
0.64
*
*
*
0.47
0.53
0.54
0.78
0.74
0.56
0.51
0.63
0.51
0.67
0.71
*
0.65
0.75
0.40
0.54
0.60
0.62
0.61
SE pi
0.04 0.04
* *
* *
* *
0.09 0.06
0.08 0.05
0.05 0.04
0.09 0.08
0.08 0.09
0.08 0.14
0.06 0.04
0.09 0.04
0.07 0.04
0.08 0.04
0.07 0.06
* *
0.04 0.05
0.06 0.04
0.08 0.04
0.21 0.05
0.07 0.06
0.04 0.04
0.09 0.09
p5
0.07
*
*
*
0.06
0.06
0.09
0.20
0.12
0.15
0.05
0.04
0.06
0.06
0.09
*
0.09
0.13
0.06
0.05
0.13
0.09
0.09
pW p25
0.13 0.22
* *
* *
* *
0.06 0.09
0.12 0.17
0.14 0.22
0.28 0.37
0.14 0.26
0.20 0.25
0.06 0.23
0.06 0.17
0.14 0.21
0.09 0.22
0.13 0.26
* *
0.14 0.24
0.19 0.28
0.06 0.09
0.08 0.22
0.14 0.22
0.13 0.23
0.12 0.19
p50
0.42
*
*
*
0.36
0.31
0.40
0.57
0.45
0.45
0.41
0.35
0.39
0.37
0.43
*
0.43
0.51
0.15
0.31
0.41
0.42
0.34
p75
0.77
*
*
*
0.78
0.51
0.65
1.24
0.97
0.64
0.64
0.80
0.59
0.87
0.97
*
0.80
0.96
0.64
0.44
0.64
0.75
0.94
p90
1.44
*
*
*
1.13
1.22
1.09
1.61
1.73
1.01
0.96
1.54
0.96
1.39
1.67
*
1.50
1.73
1.09
0.77
1.44
1.42
1.28
p95
2.03
*
*
*
1.44
2.03
1.33
1.99
2.23
1.42
1.67
2.23
1.41
2.12
2.034
*
2.03
2.23
1.37
1.22
1.89
1.99
1.73
p99
2.67
*
*
*
1.58
2.67
3.02
1.99
3.02
2.41
2.31
4.37
2.24
372'67
*
2.67
3.02
2.21
6.63
2.31
2.67
3.02
MAX
6.63
*
*
*
1.58
2.67
3.02
1.99
6.63
2.41
2.31
4.37
2.24
6.63
2.67
*
4.37
4.37
2.21
6.63
2.31
4.37
3.02
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
ft
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Table 13-65. Consumer-Only Intake of Home-Produced Other Vegetables (g/kg-day)
Population Nc Nc
Group Wgtd unwgtd
Total 25,221,000 1,437
Age
613,000 38
1 to 2 887,000 59
3^t5ll 2,149,000 134
2,379,000 141
12 to19 6,020,000 328
20 to 39 9,649,000 547
^f69 3,226,000 174
Season
Fall 6,934,000 253
Spring 5,407,000 567
Summer 8,454,000 283
Winter 4,426,000 334
Urbanization
Central City 4,148,000 161
Non-metropolitan 10,721,000 710
Suburban 10,292,000 564
Race
Black 1,347,000 84
White 23,367,000 1,327
Region
Midwest 8,296,000 522
Northeast 2,914,000 162
9,218,000 518
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Table 13-66. Consumer-Only Intake of Home-Produced
Population Nc Nc
Group wgtd unwgtd
Total 2,530,000 125
Age
54,000 4
lto2 51,000 3
3^t5ll 181,000 9
194,000 14
12 to19 402,000 18
201039 1,183,000 55
^YC69 457,000 21
Season
Fall 280,000 8
Spring 437,000 33
Summer 334,000 11
Winter 1,479,000 73
Urbanization
Central City 1,053,000 43
Non-metropolitan 0 0
Suburban 1,477,000 82
Race
Black 200,000 8
White 2,330,000 117
Region
Midwest 64,000 4
Northeast 0 0
1,240,000 55
S(WBst 1,226,000 66
Response to Questionnaire
Households who garden 2,151,000 102
130,000 5
%
Consuming
1.35
0.95
0.63
1.08
0.95
0.65
2.09
2.88
0.59
0.95
0.73
3.04
1.87
0.00
1.71
0.92
1.48
0.14
0.00
1.93
3.40
3.16
1.77
Mean
4.76
*
*
*
*
*
4.54
4.43
*
2.31
*
6.47
3.57
-
5.61
*
4.93
*
-
5.18
4.56
4.55
*
SE pi
0.61 0.08
* *
* *
* *
* *
* *
0.81 0.08
0.76 0.08
* *
0.38 0.16
* *
0.95 0.15
0.52 0.15
-
0.91 0.08
* *
0.63 0.08
* *
-
0.74 0.16
0.98 0.08
0.66 0.08
* *
p5
0.16
*
*
*
*
*
0.15
0.08
*
0.18
*
0.33
0.33
-
0.11
*
0.15
*
-
0.38
0.11
0.15
*
pl()
0.29
*
*
*
*
*
0.25
0.49
*
0.24
*
0.49
0.45
-
0.25
*
0.28
*
-
0.64
0.24
0.28
*
Citrus
p25
0.76
*
*
*
*
*
0.52
1.95
*
0.37
*
1.64
1.13
-
0.52
*
0.78
*
-
1.60
0.37
0.76
*
(g/kg-day)
p50
1.99
*
*
*
*
*
1.74
3.53
*
1.36
*
2.93
3.01
-
1.81
*
2.34
*
-
3.42
1.42
1.99
*
p75
5.10
*
*
*
*
*
5.24
6.94
*
4.15
*
8.59
4.97
-
8.12
*
5.34
*
-
6.50
4.53
4.99
*
p90
14.10
*
*
*
*
*
15.20
8.97
*
5.10
*
19.10
7.46
-
17.90
*
14.10
*
-
14.10
12.40
12.40
*
p95
19.70
*
*
*
*
*
19.70
8.97
*
6.50
*
23.80
8.97
-
23.80
*
19.70
*
-
19.70
20.00
17.90
*
p99 MAX
32.20 47.90
* *
* *
* *
* *
* *
23.80 23.80
15.70 15.70
* *
7.52 7.52
* *
47.90 47.90
20.00 20.00
-
47.90 47.90
* *
32.20 47.90
* *
-
23.80 23.80
47.90 47.90
32.20 47.90
* *
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
Indicates data are not available.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-67. Consumer-Only Intake of Home-Produced Other Fruit (g/kg-day)
Population Nc Nc
Group wgtd unwgtd
Total 12,615,000 706
Age
306,000 19
lto2 499,000 31
3^t5ll 915,000 68
1,021,000 54
12 to19 2,761,000 146
20 to39 4,610,000 259
^yf69 2,326,000 119
Season
Fall 2,923,000 102
Spring 2,526,000 268
Summer 4,327,000 144
Winter 2,839,000 192
Urbanization
Central City 2,681,000 102
Non-metropolitan 4,118,000 278
Suburban 5,756,000 324
Race
Black 250,000 12
White 12,256,000 690
Region
Midwest 4,619,000 298
Northeast 1,279,000 72
3,004,000 157
S(WBst 3,653,000 177
Response to Questionnaire
Households who garden 10,926,000 619
1,917,000 112
%
Consuming
6.71
5.37
6.16
5.48
4.98
4.48
8.13
14.65
6.13
5.47
9.51
5.83
4.76
9.15
6.65
Mean SE
2.20 0.19
* *
2.66 0.76
2.60 0.44
1.62 0.28
1.85 0.37
2.09 0.31
1.66 0.18
1.39 0.11
1.47 0.15
1.29 0.11
1.79 0.29
2.43 0.31
2.25 0.31
pi
0.05
*
0.00
0.00
0.08
0.08
0.07
0.04
0.26
0.09
0.04
0.04
0.07
0.13
p5
0.15
*
0.00
0.18
0.12
0.13
0.15
0.21
0.30
0.20
0.10
0.17
0.12
0.20
pW
0.26
*
0.38
0.39
0.26
0.18
0.25
0.36
0.38
0.25
0.23
0.29
0.24
0.28
p25
0.46
*
1.02
0.64
0.39
0.31
0.44
0.57
0.57
0.43
0.45
0.52
0.45
0.45
p50
0.91
*
1.87
1.14
0.61
0.62
0.77
1.07
1.07
0.83
0.83
0.89
1.13
0.76
p75
1.91
*
2.71
2.99
2.36
1.39
1.77
1.65
1.88
1.65
1.55
1.60
2.43
1.81
p90
4.59
*
5.54
7.13
3.92
3.70
3.17
4.06
2.89
2.89
2.70
2.61
4.60
4.72
p95
8.12
*
6.30
12.10
6.81
6.64
9.77
5.21
4.06
4.59
4.79
10.40
8.12
7.61
p99 MAX
18.40 62.60
* *
33.20 33.20
16.20 16.50
8.12 8.12
37.00 37.00
18.40 53.30
11.70 11.70
5.39 5.54
8.26 33.20
8.06 11.30
15.40 15.40
53.30
18.40 62.60
24.00
1.15
7.78
9.96
3.11
4.67
10.13
16.03
26.16
* *
2.24 0.19
3.07 0.43
0.93 0.22
1.99 0.26
1.76 0.16
2.38 0.21
2.57 0.27
*
0.07
0.04
0.08
0.08
0.10
0.04
0.07
*
0.15
0.13
0.09
0.24
0.22
0.16
0.28
*
0.26
0.24
0.16
0.30
0.29
0.26
0.36
*
0.47
0.45
0.31
0.55
0.54
0.47
0.73
*
0.92
1.04
0.48
1.10
0.97
0.99
1.55
*
1.94
2.35
0.81
1.82
2.04
1.96
3.62
*
4.65
6.73
1.29
4.06
4.35
4.94
5.80
*
8.26
14.20
2.16
6.30
5.75
10.40
8.06
* *
18.40 62.60
53.30 62.60
11.70 11.70
16.20 24.00
13.00 13.00
18.40 62.60
16.20 16.20
Households who farm
* Intake data not provided for subpopulations for which there were less than 20 observations.
SE = Standard error.
p = Percentile of the distribution.
Nc wgtd = Weighted number of consumers.
Nc unwgtd = Unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Table 13-68. Fraction of Food Intake That Is Home-Produced
Total
Season
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
BWrite
Region
Northeast
Midwest
South
West
Response to Questionnaire
Households who garden
Households who raise animals
Households who farm
HniifiahnlHr, whn fir.h
Total
Fruits
0.040
0.021
0.021
0.058
0.059
0.027
0.052
0.047
0.007
0.049
0.005
0.059
0.042
0.062
0.101
0.161
Total
Vegetables
0.068
0.081
0.037
0.116
0.041
0.027
0.144
0.058
0.027
0.081
0.038
0.112
0.069
0.057
0.173
0.308
Total
Meats
0.024
0.020
0.020
0.034
0.022
0.003
0.064
0.018
0.001
0.031
0.009
0.046
0.017
0.023
0.306
0.319
Total
Dairy
0.012
0.008
0.011
0.022
0.008
0.000
0.043
0.004
0.000
0.014
0.010
0.024
0.006
0.007
0.207
0.254
Total
Fish
0.094
0.076
0.160
0.079
0.063
0.053
0.219
0.075
0.063
0.110
0.008
0.133
0.126
0.108
-
0.325
Exposed
Vegetables
0.095
0.106
0.050
0.164
0.052
0.037
0.207
0.079
0.037
0.109
0.062
0.148
0.091
0.079
0.233
0.420
Protected
Vegetables
0.069
0.073
0.039
0.101
0.048
0.027
0.134
0.054
0.029
0.081
0.016
0.109
0.077
0.060
0.178
0.394
Root
Vegetables
0.043
0.060
0.020
0.066
0.026
0.016
0.088
0.035
0.012
0.050
0.018
0.077
0.042
0.029
0.106
0.173
Exposed
Fruits
0.050
0.039
0.047
0.068
0.044
0.030
0.100
0.043
0.008
0.059
0.010
0.078
0.040
0.075
0.116
0.328
Protected
Fruits
0.037
0.008
0.008
0.054
0.068
0.026
0.025
0.050
0.007
0.045
0.002
0.048
0.044
0.054
0.094
0.030
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Table 13-68.
Total
Season
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
BWfite
Region
Northeast
Midwest
W
Response to Questionnaire
Households who garden
Dark Green
Vegetables
0.044
0.059
0.037
0.063
0.018
0.012
0.090
0.054
0.053
0.043
0.039
0.054
0.049
0.034
0.120
0.220
Deep Yellow
Vegetables
0.065
0.099
0.017
0.080
0.041
0.038
0.122
0.058
0.056
0.071
0.019
0.174
0.022
0.063
0.140
0.328
Fraction of Food Intake That Is Home-Produced (continued)
Other
Vegetables
0.069
0.069
0.051
0.114
0.044
0.026
0.154
0.053
0.026
0.082
0.034
0.102
0.077
0.055
0.180
0.368
Citrus
Fruits
0.038
0.114
0.014
0.010
0.091
0.035
0.000
0.056
0.012
0.045
0.000
0.001
0.060
0.103
0.087
0.005
Other
Fruits
0.042
0.027
0.025
0.070
0.030
0.022
0.077
0.042
0.004
0.051
0.008
0.083
0.031
0.046
0.107
0.227
Apples
0.030
0.032
0.013
0.053
0.024
0.017
0.066
0.024
0.007
0.035
0.004
0.052
0.024
0.043
0.070
0.292
Peaches
0.147
0.090
0.206
0.133
0.183
0.087
0.272
0.121
0.018
0.164
0.027
0.164
0.143
0.238
0.316
0.461
Pears
0.067
0.038
0.075
0.066
0.111
0.038
0.155
0.068
0.004
0.089
0.002
0.112
0.080
0.093
0.169
0.606
Strawberries
0.111
0.408
0.064
0.088
0.217
0.107
0.133
0.101
0.000
0.125
0.085
0.209
0.072
0.044
0.232
0.057
Other Berries
0.217
0.163
0.155
0.232
0.308
0.228
0.282
0.175
0.470
0.214
0.205
0.231
0.177
0.233
0.306
0.548
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Total
Season
^spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
BWSte
Region
Northeast
Midwest
South
West
Response to Questionnaire
Households who garden
Table
Asparagus
0.063
0.024
0.103
0
0.019
0.058
0.145
0.040
0.000
0.071
0.091
0.194
0.015
0.015
0.125
0.432
13-68. Fraction of Food Intake That
Beets
0.203
0.199
0.191
0.209
0.215
0.212
0.377
0.127
0.000
0.224
0.074
0.432
0.145
0.202
0.420
0.316
Broccoli
0.015
0.013
0.011
0.034
0.006
0.004
0.040
0.016
0.000
0.018
0.020
0.025
0.013
0.006
0.043
0.159
Cabbage
0.038
0.054
0.011
0.080
0.008
0.004
0.082
0.045
0.001
0.056
0.047
0.053
0.029
0.029
0.099
0.219
Carrots
0.043
0.066
0.015
0.063
0.025
0.018
0.091
0.039
0.068
0.042
0.025
0.101
0.020
0.039
0.103
0.185
Is Home-Produced (continued)
Corn
0.078
0.076
0.048
0.118
0.043
0.025
0.173
0.047
0.019
0.093
0.020
0.124
0.088
0.069
0.220
0.524
Cucumbers
0.148
0.055
0.040
0.320
0
0.029
0.377
0.088
0.060
0.155
0.147
0.193
0.140
0.119
0.349
0.524
Lettuce
0.010
0.013
0.010
0.017
0.002
0.009
0.017
0.009
0.007
0.011
0.009
0.020
0.006
0.009
0.031
0.063
Lima Beans
0.121
0.070
0.082
0.176
0.129
0.037
0.132
0.165
0.103
0.135
0.026
0.149
0.140
0.000
0.258
0.103
Okra
0.270
0.299
0.211
0.304
0.123
0.068
0.411
0.299
0.069
0.373
0.000
0.224
0.291
0.333
0.618
0.821
Onions
0.056
0.066
0.033
0.091
0.029
0.017
0.127
0.050
0.009
0.068
0.022
0.098
0.047
0.083
0.148
0.361
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Total
Season
Spring
Summer
Winter
Urbanization
Central City
Non-metropolitan
Suburban
Race
BWSte
Region
Northeast
Midwest
South
West
Response to Questionnaire
Households who garden
HfK5rfMolfdFw!i6afa%)e animals
Houceholdc "'ho hunt
Indicates data are not
Table
0.069
0.046
0.048
0.126
0.065
0.033
0.123
0.064
0.047
0.076
0.021
0.058
0.106
0.051
0.193
0.308
-
-
available.
13-68. Fraction of Food Intake That Is Home-Produced (continued)
Peppers
0.107
0.138
0.031
0.194
0.03
0.067
0.228
0.086
0.039
0.121
0.067
0.188
0.113
0.082
0.246
0.564
-
-
Pumpkin
0.155
0.161
0.046
0.19
0.154
0.130
0.250
0.127
0.022
0.187
0.002
0.357
0.044
0.181
0.230
0.824
-
-
Snap
Beans
0.155
0.199
0.152
0.123
0.147
0.066
0.307
0.118
0.046
0.186
0.052
0.243
0.161
0.108
0.384
0.623
-
-
Tomatoes
0.184
0.215
0.045
0.318
0.103
0.100
0.313
0.156
0.060
0.202
0.117
0.291
0.149
0.182
0.398
0.616
-
-
White
Potatoes
0.038
0.058
0.010
0.060
0.022
0.009
0.080
0.029
0.007
0.044
0.016
0.065
0.042
0.013
0.090
0.134
-
-
Beef
0.038
0.028
0.027
0.072
0.022
0.001
0.107
0.026
0.000
0.048
0.014
0.076
0.022
0.041
0.485
0.478
-
Game
0.276
0.336
0.265
0.100
0.330
0.146
0.323
0.316
0.000
0.359
0.202
0.513
0.199
0.207
-
-
0.729
Pork
0.013
0.012
0.015
0.010
0.014
0.001
0.040
0.006
0.000
0.017
0.006
0.021
0.012
0.011
0.242
0.239
-
Poultry
0.011
0.011
0.012
0.007
0.014
0.002
0.026
0.011
0.001
0.014
0.002
0.021
0.012
0.008
0.156
0.151
-
Eggs
0.014
0.009
0.022
0.013
0.011
0.002
0.029
0.014
0.002
0.017
0.004
0.019
0.012
0.021
0.146
0.214
-
Source: Based on EPA's analyses of the 1987-1988 NFCS.
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13-69. Percent Weight Losses from Food Preparation
Food Group Mean Net Preparation/Cooking Loss (%) Mean Net Post Cooking (%)
Meats3
Fish and shellfish"1
Fruits
Vegetables8
29.7b
31. 5b
25.4e
12.4h
29.T
10.5C
30.5f
221
a Averaged over various cuts and preparation methods for various meats including beef, pork,
chicken, turkey, lamb, and veal.
b Includes dripping and volatile losses during cooking.
0 Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices.
d Averaged over a variety of fish and shellfish to include bass, bluefish, butterfish, cod, flounder,
haddock, halibut, lake trout, mackerel, perch, porgy, red snapper, rockfish, salmon, sea trout, shad,
smelt, sole, spot, squid, swordfish steak, trout, whitefish, clams, crab, crayfish, lobster, oysters, and
shrimp and shrimp dishes.
e Based on preparation losses. Averaged over apples, pears, peaches, strawberries, and oranges.
Includes losses from removal of skin or peel, core or pit, stems or caps, seeds, and defects. Also
includes losses from removal of drained liquids from canned or frozen forms.
f Averaged over apples and peaches. Include losses from draining cooked forms.
8 Averaged over various vegetables to include asparagus, beets, broccoli, cabbage, carrots, corn,
cucumbers, lettuce, lima beans, okra, onions, green peas, peppers, pumpkins, snap beans, tomatoes,
and potatoes.
h Includes losses due to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling,
slicing, husking, chopping, and dicing and gains from the addition of water, fat, or other
ingredients. Averaged over various preparation methods.
1 Includes losses from draining or removal of skin. Based on potatoes only.
Source: U.S. EPA, 1997. (Derived from USD A, 1975.)
Exposure Factors Handbook Page
September 2010 13-81
-------
I
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Table 13-70. Estimated Age-Specific Per Capita Home-Produced Intake (adjusted; g/kg-day)a
Home-Produced
Fruits
Gardening Farming
Population Population
Mean 95th Mean 95th
Home-Produced
Vegetables
Gardening
Population
Mean
95th
Farming
Population
Mean
95th
Home-Produced
Meats
Population that
Raises Animals
Mean 95th
Farming
Population
Mean
95th
Home-Produced
Dairy
Population that
Raises Animals
Mean
Farming
Population
95th Mean
95th
Unadjusted (g/kg-day)b
Total
population 0.52 2.4 0.67 4.5
0.96
5.1
1.9
9.8
1.5 6.1
1.5
6.3
1.9
14
2.4
17
Adjusted (g/kg-day)°
Total
population 0.27 1.2 0.35 2.4
Birth to 1 yeard 1.0 4.4 1.2 8.4
1 to <2 years 1.0 4.8 1.4 9.1
2 to <3 years 1.0 4.8 1.4 9.1
3 to <6 years 0.78 3.6 1.0 6.8
6to^
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13-71. 2008
Demographic
Factor
Total
(~36 million)
Sex
Female
Male
Age
18-34
35-44
45-54
55 and over
Education
College graduate
Some college
High school
Household income
$75,000 and over
$50-$74,999
$35-$49,999
Under $35,000
Undesignated
Household size
One person
Two person
Three to four person
Five or more persons
Food Gardening by Demographic Factors
Percentage of total households that
have gardens (%)
31
54
46
21
11
24
44
43
36
21
22
16
24
21
17
20
40
32
9
Source: National Gardening Association, 2009.
Exposure Factors Handbook
September 2011
Page
13-83
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13-72. Percentage of Gardening Households Growing
Different Vegetables in 2008
Vegetable
Tomatoes
Cucumbers
Sweet peppers
Beans
Carrots
Summer squash
Onions
Hot peppers
Lettuce
Peas
Sweet Corn
Radish
Potatoes
Salad greens
Pumpkins
Watermelon
Spinach
Broccoli
Melon
Cabbage
Beets
Winter squash
Asparagus
Collards
Cauliflower
Celery
Brussels sprouts
Leeks
Kale
Parsnips
Chinese cabbage
Rutabaga
Source: National
Percent (%)
86
47
46
39
34
32
32
31
28
24
23
20
18
17
17
16
15
15
15
14
11
10
9
9
7
5
5
3
3
2
2
1
Gardening Association, 2009.
Page
13-84
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
APPENDIX 13A
FOOD CODES AND DEFINITIONS OF MAJOR FOOD GROUPS USED IN THE ANALYSIS
OF THE 1987-1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE RATES
Exposure Factors Handbook Page
September 2011 13A-1
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13A-1. Food Codes and Definitions of Major Food Groups Used in Analysis of the 1987-1988
USDA NFCS Data to Estimate Intake of Home-Produced Foods
Food Product
Household Code/Definition8
Individual Code
MAJOR FOOD GROUPS
Total Fruits
50- Fresh Fruits
citrus
other vitamin-C rich
other fruits
512- Commercially Canned Fruits
522- Commercially Frozen Fruits
533- Canned Fruit Juice
534- Frozen Fruit Juice
535- Aseptically Packed Fruit Juice
536- Fresh Fruit Juice
542- Dried Fruits
(includes baby foods)
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
(includes baby foods)
Total Vegetables
48- Potatoes, Sweet Potatoes
49- Fresh Vegetables
dark green
deep yellow
tomatoes
light green
other
511 - Commercially Canned Vegetables
521- Commercially Frozen Vegetables
531- Canned Vegetable Juice
532- Frozen Vegetable Juice
537- Fresh Vegetable Juice
538- Aseptically Packed Vegetable Juice
541- Dried Vegetables
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures/dinners)
7- Vegetables (all forms)
white potatoes & Puerto Rican starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
veg. and mixtures/baby food
veg. with meat mixtures
(includes baby foods; mixtures, mostly vegetables)
Total Meats
44- Meat
beef
pork
veal
lamb
mutton
goat
game
lunch meat
mixtures
451- Poultry
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures)
20- Meat, type not specified
21- Beef
22- Pork
23- Lamb, veal, game, carcass meat
24- Poultry
25- Organ meats, sausages, lunchmeats, meat
spreads
(excludes meat, poultry, and fish with non-meat items;
frozen plate meals; soups and gravies with meat,
poultry and fish base; and gelatin-based drinks;
includes baby foods)
Total Dairy
40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
1- Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
(includes regular fluid milk, human milk, imitation
milk products, yogurt, milk-based meal replacements,
and infant formulas)
Total Fish
452- Fish, Shellfish
various species
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
26- Fish, Shellfish
various species and forms
(excludes meat, poultry, and fish with non-meat items;
frozen plate meals; soups and gravies with meat,
poultry and fish base; and gelatin-based drinks)
Food items within these categories that were identified by the household as being home-produced or home-caught (i.e., source
code pertaining to home-produced foods) were included in the analysis.
Page
13A-2
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
APPENDIX 13B
1987-1988 NFCS FOOD CODES AND DEFINITIONS OF INDIVIDUAL FOOD ITEMS USED IN
ESTIMATING THE FRACTION OF HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED
Exposure Factors Handbook Page
September 2011 13B-1
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced
Food Product
Household Code/Definition
Individual Code
INDIVIDUAL FOODS
White Potatoes
4811- White Potatoes, fresh
4821- White Potatoes, commercially canned
4831- White Potatoes, commercially frozen
4841- White Potatoes, dehydrated
4851- White Potatoes, chips, sticks, salad
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners)
71- White Potatoes and Puerto Rican Starchy Veg.
baked, boiled, chips, sticks, creamed, scalloped,
au gratin, fried, mashed, stuffed, puffs, salad,
recipes, soups, Puerto Rican starchy vegetables
(does not include vegetables soups; vegetable
mixtures; or vegetable with meat mixtures)
Peppers
4913- Green/Red Peppers, fresh
5111201 Sweet Green Peppers, commercially canned
5111202 Hot Chili Peppers, commercially canned
5211301 Sweet Green Peppers, commercially frozen
5211302 Green Chili Peppers, commercially frozen
5211303 Red Chili Peppers, commercially frozen
5413112 Sweet Green Peppers, dry
5413113 Red Chili Peppers, dry
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners)
7512100 Pepper, hot chili, raw
7512200 Pepper, raw
7512210 Pepper, sweet green, raw
7512220 Pepper, sweet red, raw
7522600 Pepper, green, cooked, NS as to fat added
7522601 Pepper, green, cooked, fat not added
7522602 Pepper, green, cooked, fat added
7522604 Pepper, red, cooked, NS as to fat added
7522605 Pepper, red, cooked, fat not added
7522606 Pepper, red, cooked, fat added
7522609 Pepper, hot, cooked, NS as to fat added
7522610 Pepper, hot, cooked, fat not added
7522611 Pepper, hot, cooked, fat added
7551101 Peppers, hot, sauce
7551102 Peppers, pickled
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Onions
4953-
Onions, Garlic, fresh
onions
chives
garlic
leeks
5114908 Garlic Pulp, raw
5114915 Onions, commercially canned
5213722 Onions, commercially frozen
5213723 Onions with Sauce, commercially frozen
5413103 Chives, dried
5413105 Garlic Flakes, dried
5413110 Onion Flakes, dried
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners)
7510950 Chives, raw
7511150 Garlic, raw
7511250 Leek, raw
7511701 Onions, young green, raw
7511702 Onions, mature
7521550 Chives, dried
7521740 Garlic, cooked
7522100 Onions, mature cooked, NS as to fat added
7522101 Onions, mature cooked, fat not added
7522102 Onions, mature cooked, fat added
7522103 Onions, pearl cooked
7522104 Onions, young green cooked, NS as to fat
7522105 Onions, young green cooked, fat not added
7522106 Onions, young green cooked, fat added
7522110 Onion, dehydrated
7541501 Onions, creamed
7541502 Onion rings
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Page
13B-2
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Corn
4956- Corn, fresh
5114601 Yellow Corn, commercially canned
5114602 White Corn, commercially canned
5114603 Yellow Creamed Corn, commercially canned
5114604 White Creamed Corn, commercially canned
5114605 Corn on Cob, commercially canned
5114607 Hominy, canned
5115306 Low Sodium Corn, commercially canned
5115307 Low Sodium Cr. Corn, commercially canned
5213501 Yellow Corn on Cob, commercially frozen
5213502 Yellow Corn off Cob, commercially frozen
5213503 Yell. Corn with Sauce, commercially frozen
5213504 Corn with other Veg., commercially frozen
5213505 White Corn on Cob, commercially frozen
5213506 White Corn off Cob, commercially frozen
5213507 Wh. Corn with Sauce, commercially frozen
5413104 Corn, dried
5413106 Hominy, dry
5413603 Corn, instant baby food
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby food)
7510960 Corn, raw
7521600 Com, cooked, NS as to color/fat added
7521601 Corn, cooked, NS as to color/fat not added
7521602 Corn, cooked, NS as to color/fat added
7521605 Corn, cooked, NS as to color/cream style
7521607 Corn, cooked, dried
7521610 Corn, cooked, yellow/NS as to fat added
7521611 Corn, cooked, yellow/fat not added
7521612 Corn, cooked, yellow/fat added
7521615 Corn, yellow, cream style
7521616 Corn, cooked, yell. & wh./NS as to fat
7521617 Corn, cooked, yell. & wh./fat not added
7521618 Corn, cooked, yell. & wh./fat added
7521619 Corn, yellow, cream style, fat added
7521620 Corn, cooked, white/NS as to fat added
7521621 Corn, cooked, white/fat not added
7521622 Corn, cooked, white/fat added
7521625 Corn, white, cream style
7521630 Corn, yellow, canned, low sodium, NS fat
7521631 Corn, yell., canned, low sod., fat not add
7521632 Corn, yell., canned, low sod., fat added
7521749 Hominy, cooked
752175- Hominy, cooked
7541101 Corn scalloped or pudding
7541102 Corn fritter
7541103 Corn with cream sauce
7550101 Corn relish
76405- Corn, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby food)
Apples
Apples, fresh
Applesauce with sugar, commercially canned
Applesauce without sugar, comm. canned
Apple Pie Filling, commercially canned
Apples, Applesauce, baby/jr., comm. canned
Apple Pie Filling, Low Cal., comm. canned
Apple Slices, commercially frozen
Apple Juice, canned
Apple Juice, baby, Comm. canned
Apple Juice, comm. frozen
Apple Juice, home frozen
Apple Juice, aseptically packed
Apple Juice, fresh
Apples, dried
5031-
5122101
5122102
5122103
5122104
5122106
5223101
5332101
5332102
5342201
5342202
5352101
5362101
5423101
(includes baby food; except mixtures)
6210110 Apples, dried, uncooked
6210115 Apples, dried, uncooked, low sodium
6210120 Apples, dried, cooked, NS as to sweetener
6210122 Apples, dried, cooked, unsweetened
6210123 Apples, dried, cooked, with sugar
6310100 Apples, raw
6310111 Applesauce, NS as to sweetener
6310112 Applesauce, unsweetened
6310113 Applesauce with sugar
6310114 Applesauce with low calorie sweetener
6310121 Apples, cooked or canned with syrup
6310131 Apple, baked NS as to sweetener
6310132 Apple, baked, unsweetened
6310133 Apple, baked with sugar
6310141 Apple rings, fried
6310142 Apple, pickled
6310150 Apple, fried
6340101 Apple, salad
6340106 Apple, candied
6410101 Apple cider
6410401 Apple juice
6410405 Apple juice with vitamin C
6710200 Applesauce baby fd., NS as to str. or jr.
6710201 Applesauce baby food, strained
6710202 Applesauce baby food, junior
6720200 Apple juice, baby food
(includes baby food; except mixtures)
Exposure Factors Handbook
September 2011
Page
13B-3
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Tomatoes
4931- Tomatoes, fresh
5113- Tomatoes, commercially canned
5115201 Tomatoes, low sodium, commercially canned
5115202 Tomato Sauce, low sodium, comm. canned
5115203 Tomato Paste, low sodium, comm. canned
5115204 Tomato Puree, low sodium, comm. canned
5311- Canned Tomato Juice and Tomato Mixtures
5321- Frozen Tomato Juice
5371- Fresh Tomato Juice
5381102 Tomato Juice, aseptically packed
5413115 Tomatoes, dry
5614- Tomato Soup
5624- Condensed Tomato Soup
5654- Dry Tomato Soup
(does not include mixtures, and ready-to-eat dinners)
74- Tomatoes and Tomato Mixtures
raw, cooked, juices, sauces, mixtures, soups,
sandwiches
Snap Beans
4943- Snap or Wax Beans, fresh
5114401 Green or Snap Beans, commercially canned
5114402 Wax or Yellow Beans, commercially canned
5114403 Beans, baby/jr, commercially canned
5115302 Green Beans, low sodium, comm. canned
5115303 Yell, or Wax Beans, low sod., comm. canned
5213301 Snap or Green Beans, comm. frozen
5213302 Snap or Green w/sauce, comm. frozen
5213303 Snap or Green Beans w/other veg., comm. fr.
5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr.
5213305 Wax or Yell. Beans, comm. frozen
(does not include soups, mixtures, and ready-to-eat
dinners; includes baby foods)
7510180 Beans, string, green, raw
7520498 Beans, string, cooked, NS color/fat added
7520499 Beans, string, cooked, NS color/no fat
7520500 Beans, string, cooked, NS color & fat
7520501 Beans, string, cooked, green/NS fat
7520502 Beans, string, cooked, green/no fat
7520503 Beans, string, cooked, green/fat
7520511 Beans, str, canned, low sod., green/NS fat
7520512 Beans, str, canned, low sod., green/no fat
7520513 Beans, str., canned, low sod., green/fat
7520600 Beans, string, cooked, yellow/NS fat
7520601 Beans, string, cooked, yellow/no fat
7520602 Beans, string, cooked, yellow/fat
7540301 Beans, string, green, creamed
7540302 Beans, string, green, w/mushroom sauce
7540401 Beans, string, yellow, creamed
7550011 Beans, string, green, pickled
7640100 Beans, green, string, baby
7640101 Beans, green, string, baby, str.
7640102 Beans, green, string, baby, junior
7640103 Beans, green, string, baby, creamed
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby foods)
Beef
441- Beef
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
21- Beef
beef, nfs
beef steak
beef oxtails, neck bones, ribs
roasts, stew meat, corned, brisket, sandwich
steaks
ground beef, patties, meatballs
other beef items
beef baby food
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry, and fish
base; and gelatin-based drinks; includes baby food)
Page
13B-4
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Pork
442- Pork
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
22- Pork
pork, nfs; ground dehydrated
chops
steaks, cutlets
ham
roasts
Canadian bacon
bacon, salt pork
other pork items
pork baby food
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry and fish
base; and gelatin-based drinks; includes baby food)
Game
445- Variety Meat, Game
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
233- Game
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry, and fish
base; and gelatin-based drinks)
Poultry
451- Poultry
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
24- Poultry
chicken
turkey
duck
other poultry
poultry baby food
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry, and fish
base; and gelatin-based drinks; includes baby food)
46- Eggs (fresh equivalent)
fresh
processed eggs, substitutes
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
3- Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
(includes baby foods)
Broccoli
4912- Fresh Broccoli (and home canned/froz.)
5111203 Broccoli, comm. canned
52112- Comm. Frozen Broccoli
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
722- Broccoli (all forms)
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Carrots
4921- Fresh Carrots (and home canned/froz.)
51121- Comm. Canned Carrots
5115101 Carrots, Low Sodium, Comm. Canned
52121- Comm. Frozen Carrots
5312103 Comm. Canned Carrot Juice
5372102 Carrot Juice Fresh
5413502 Carrots, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7310- Carrots (all forms)
7311140 Carrots in Sauce
7311200 Carrot Chips
76201- Carrots, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby foods except
mixtures)
Pumpkin
4922-
51122-
52122-
5413504
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
Fresh Pumpkin, Winter Squash (and home
canned/froz.)
Pumpkin/Squash, Baby or Junior, Comm.
Canned
Winter Squash, Comm. Frozen
Squash, Dried Baby Food
732- Pumpkin (all forms)
733- Winter squash (all forms)
76205- Squash, baby
(does not include vegetable soups; vegetables mixtures; or
vegetable with meat mixtures; includes baby foods)
Exposure Factors Handbook
September 2011
Page
13B-5
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Asparagus
4941- Fresh Asparagus (and home canned/froz.)
5114101 Comm. Canned Asparagus
5115301 Asparagus, Low Sodium, Comm. Canned
52131- Comm. Frozen Asparagus
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7510080 Asparagus, raw
75202- Asparagus, cooked
7540101 Asparagus, creamed or with cheese
(does not include vegetable soups; vegetables mixtures, or
vegetable with meat mixtures)
Lima Beans
4942- Fresh Lima and Fava Beans (and home
canned/froz.)
5114204 Comm. Canned Mature Lima Beans
5114301 Comm. Canned Green Lima Beans
5115304 Comm. Canned Low Sodium Lima Beans
52132- Comm. Frozen Lima Beans
54111- Dried Lima Beans
5411306 Dried Fava Beans
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures; does not include succotash)
7510200 Lima Beans, raw
752040- Lima Beans, cooked
752041- Lima Beans, canned
75402- Lima Beans with sauce
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; does not include succotash)
Cabbage
4944-
4958601
5114801
5114904
5114905
5115501
5312102
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
Fresh Cabbage (and home canned/froz.)
Sauerkraut, home canned or pkgd
Sauerkraut, comm. canned
Comm. Canned Cabbage
Comm. Canned Cabbage (no sauce; incl.
baby)
Sauerkraut, low sodium., comm. canned
Sauerkraut Juice, comm. canned
7510300 Cabbage, raw
7510400 Cabbage, Chinese, raw
7510500 Cabbage, red, raw
7514100 Cabbage salad or coleslaw
7514130 Cabbage, Chinese, salad
75210- Chinese Cabbage, cooked
75211- Green Cabbage, cooked
75212- Red Cabbage, cooked
752130- Savoy Cabbage, cooked
75230- Sauerkraut, cooked
7540701 Cabbage, creamed
755025- Cabbage, pickled or in relish
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Lettuce
4945- Fresh Lettuce, French Endive (and home
canned/froz.)
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
75113- Lettuce, raw
75143- Lettuce salad with other veg.
7514410 Lettuce, wilted, with bacon dressing
7522005 Lettuce, cooked
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Okra
4946- Fresh Okra (and home canned/froz.)
5114914 Comm. Canned Okra
5213720 Comm. Frozen Okra
5213721 Comm. Frozen Okra with Oth. Veg. & Sauce
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7522000 Okra, cooked, NS as to fat
7522001 Okra, cooked, fat not added
7522002 Okra, cooked, fat added
7522010 Lufta, cooked (Chinese Okra)
7541450 Okra, fried
7550700 Okra, pickled
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Page
13B-6
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Peas
4947-
51147-
5115310
5115314
5114205
52134-
5412-
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
Fresh Peas (and home canned/froz.)
Comm Canned Peas (incl. baby)
Low Sodium Green or English Peas (canned)
Low Sod. Blackeyed, Gr. or Imm. Peas
(canned)
Blackeyed Peas, comm. canned
Comm. Frozen Peas
Dried Peas and Lentils
7512000 Peas, green, raw
7512775 Snowpeas, raw
75223- Peas, cowpeas, field or blackeyed, cooked
75224- Peas, green, cooked
75225- Peas, pigeon, cooked
75231- Snowpeas, cooked
7541650 Pea salad
7541660 Pea salad with cheese
75417- Peas, with sauce or creamed
76409- Peas, baby
76411- Peas, creamed, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby foods except
mixtures)
Cucumbers
4952- Fresh Cucumbers (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7511100 Cucumbers, raw
75142- Cucumber salads
752167- Cucumbers, cooked
7550301 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweet
7550305 Cucumber pickles, fresh
7550307 Cucumber, Kim Chee
7550311 Cucumber pickles, dill, reduced salt
7550314 Cucumber pickles, sweet, reduced salt
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Beets
4954- Fresh Beets (and home canned/froz.)
51145- Comm. Canned Beets (incl. baby)
5115305 Low Sodium Beets (canned)
5213714 Comm. Frozen Beets
5312104 Beet Juice
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7510250 Beets, raw
752080- Beets, cooked
752081- Beets, canned
7540501 Beets, harvard
7550021 Beets, pickled
76403- Beets, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby foods except
mixtures)
Strawberries
5022- Fresh Strawberries
5122801 Comm. Canned Strawberries with sugar
5122802 Comm. Canned Strawberries without sugar
5122803 Canned Strawberry Pie Filling
5222- Comm. Frozen Strawberries
(does not include ready-to-eat dinners; includes baby
foods except mixtures)
6322- Strawberries
6413250 Strawberry Juice
(includes baby food; except mixtures)
Exposure Factors Handbook
September 2011
Page
13B-7
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Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Other Berries
Peaches
Pears
Household Code/Definition
5033- Fresh Berries Other than Strawberries
5 122804 Comm. Canned Blackberries with sugar
5122805 Comm. Canned Blackberries without sugar
5122806 Comm. Canned Blueberries with sugar
5122807 Comm. Canned Blueberries without sugar
5 122808 Canned Blueberry Pie Filling
5122809 Comm. Canned Gooseberries with sugar
5122810 Comm. Canned Gooseberries without sugar
5 12281 1 Comm. Canned Raspberries with sugar
5 122812 Comm. Canned Raspberries without sugar
5122813 Comm. Canned Cranberry Sauce
5122815 Comm. Canned Cranberry-Orange Relish
52233- Comm. Frozen Berries (not strawberries)
5332404 Blackberry Juice (home and comm. canned)
5423114 Dried Berries (not strawberries)
(does not include ready-to-eat dinners; includes baby
foods except mixtures)
5036- Fresh Peaches
51224- Comm. Canned Peaches (incl. baby)
5223601 Comm. Frozen Peaches
5332405 Home Canned Peach Juice
5423 105 Dried Peaches (baby)
5423106 Dried Peaches
(does not include ready-to-eat dinners; includes baby
foods except mixtures)
5037- Fresh Pears
51225- Comm. Canned Pears (incl. baby)
5332403 Comm. Canned Pear Juice, baby
5362204 Fresh Pear Juice
5423107 Dried Pears
(does not include ready-to-eat dinners; includes baby
foods except mixtures)
Individual Code
6320- Other Berries
6321- Other Berries
6341101 Cranberry salad
6410460 Blackberry Juice
64105- Cranberry Juice
(includes baby food; except mixtures)
62116- Dried Peaches
63135- Peaches
6412203 Peach Juice
6420501 Peach Nectar
67108- Peaches, baby
6711450 Peaches, dry, baby
(includes baby food; except mixtures)
62119- Dried Pears
63137- Pears
6341201 Pear salad
6421501 Pear Nectar
67109- Pears, baby
6711455 Pears, dry, baby
(includes baby food; except mixtures)
Page
13B-8
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
EXPOSED/PROTECTED FRUITS/VEGETABLES, ROOT VEGETABLES
Exposed Fruits 5022-
5023101
5023401
5031-
5033-
5034-
5036-
5037-
50381-
5038305
50384-
50386-
50387-
5038805
5038901
51221-
51222-
51223-
51224-
51225-
51228-
5122903
5122904
5122905
5122906
5122907
5122911
5122912
5122913
5122914
5222-
52231-
52233-
52234-
52236-
52239-
53321-
53322-
Strawberries, fresh
Acerola, fresh
Currants, fresh
Apples/ Applesauce, fresh
Berries other than Strawberries, fresh
Cherries, fresh
Peaches, fresh
Pears, fresh
Apricots, Nectarines, Loquats, fresh
Dates, fresh
Grapes, fresh
Plums, fresh
Rhubarb, fresh
Persimmons, fresh
Sapote, fresh
Apples/ Applesauce, canned
Apricots, canned
Cherries, canned
Peaches, canned
Pears, canned
Berries, canned
Grapes with sugar, canned
Grapes without sugar, canned
Plums with sugar, canned
Plums without sugar, canned
Plums, canned, baby
Prunes, canned, baby
Prunes, with sugar, canned
Prunes, without sugar, canned
Raisin Pie Filling
Frozen Strawberries
Apples Slices, frozen
Berries, frozen
Cherries, frozen
Peaches, frozen
Rhubarb, frozen
Canned Apple Juice
Canned Grape Juice
62101- Apple, dried
62104- Apricot, dried
62108- Currants, dried
62110- Date, dried
62116- Peaches, dried
62119- Pears, dried
62121- Plum, dried
62122- Prune, dried
62125- Raisins
63101- Apples/applesauce
63102- Wi-apple
63103- Apricots
63111- Cherries, maraschino
63112- Acerola
63113- Cherries, sour
63115- Cherries, sweet
63117- Currants, raw
63123- Grapes
6312601 Juneberry
63131- Nectarine
63135- Peach
63137- Pear
63139- Persimmons
63143- Plum
63146- Quince
63147- Rhubarb/Sapodillo
632- Berries
64101- Apple Cider
64104- Apple Juice
64105- Cranberry Juice
64116- Grape Juice
64122- Peach Juice
64132- Prune/Strawberry Juice
6420 1 0 1 Apricot Nectar
64205- Peach Nectar
64215- Pear Nectar
67102- Applesauce, baby
67108- Peaches, baby
Exposure Factors Handbook
September 2011
Page
13B-9
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced
Food Product
Exposed Fruits
(continued)
Protected Fruits
Household Code/Definition
5332402 Canned Prune Juice
5332403 Canned Pear Juice
5332404 Canned Blackberry Juice
5332405 Canned Peach Juice
53421- Frozen Grape Juice
5342201 Frozen Apple Juice, comm. fr.
5342202 Frozen Apple Juice, home fr.
5352101 Apple Juice, asep. packed
5352201 Grape Juice, asep. packed
5362101 Apple Juice, fresh
5362202 Apricot Juice, fresh
5362203 Grape Juice, fresh
5362204 Pear Juice, fresh
5362205 Prune Juice, fresh
5421- Dried Prunes
5422- Raisins, Currants, dried
5423101 Dry Apples
5423102 Dry Apricots
5423 103 Dates without pits
5423 104 Dates with pits
5423 105 Peaches, dry, baby
5423106 Peaches, dry
5423107 Pears, dry
5423114 Berries, dry
5423115 Cherries, dry
(includes baby foods)
501- Citrus Fruits, fresh
5021- Cantaloupe, fresh
5023201 Mangoes, fresh
5023301 Guava, fresh
5023601 Kiwi, fresh
5023701 Papayas, fresh
5023801 Passion Fruit, fresh
5032- Bananas, Plantains, fresh
5035- Melons other than Cantaloupe, fresh
50382- Avocados, fresh
5038301 Figs, fresh
5038302 Figs, cooked
5038303 Figs, home canned
5038304 Figs, home frozen
50385- Pineapple, fresh
5038801 Pomegranates, fresh
5038902 Cherimoya, fresh
5038903 Jackfruit, fresh
5038904 Breadfruit, fresh
5038905 Tamarind, fresh
5038906 Carambola, fresh
5038907 Longan, fresh
5121- Citrus, canned
51226- Pineapple, canned
5 12290 1 Figs with sugar, canned
5122902 Figs without sugar, canned
5122909 Bananas, canned, baby
5122910 Bananas and Pineapple, canned, baby
5122915 Litchis, canned
1987-1988
(continued)
Individual Code
67109- Pears, baby
6711450 Peaches, baby, dry
6711455 Pears, baby, dry
67202- Apple Juice, baby
6720380 White Grape Juice, baby
67212- Pear Juice, baby
(includes baby foods/juices except mixtures; excludes
fruit mixtures)
61- Citrus Fr, Juices (incl. cit. juice mixtures)
62107- Bananas, dried
62113- Figs, dried
62114- Lychees/Papayas, dried
62120- Pineapple, dried
62126- Tamarind, dried
63105- Avocado, raw
63107- Bananas
63109- Cantaloupe, Carambola
63110- Cassaba Melon
63119- Figs
63121- Genip
63125- Guava/Jackfruit, raw
6312650 Kiwi
6312651 Lychee, raw
6312660 Lychee, cooked
63127- Honey dew
63129- Mango
63133- Papaya
63134- Passion Fruit
63141- Pineapple
63145- Pomegranate
63148- Sweetsop, Soursop, Tamarind
63149- Watermelon
64120- Papaya Juice
64121- Passion Fruit Juice
64124- Pineapple Juice
64133- Watermelon Juice
6420 1 50 Banana Nectar
Page
13B-10
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Protected Fruits
(continued)
5122916 Mangos with sugar, canned
5122917 Mangos without sugar, canned
5122918 Mangos, canned, baby
5122920 Guava with sugar, canned
5122921 Guava without sugar, canned
5122923 Papaya with sugar, canned
5122924 Papaya without sugar, canned
52232- Bananas, frozen
52235- Melon, frozen
52237- Pineapple, frozen
5331- Canned Citrus Juices
53323- Canned Pineapple Juice
5332408 Canned Papaya Juice
5332410 Canned Mango Juice
5332501 Canned Papaya Concentrate
5341- Frozen Citrus Juice
5342203 Frozen Pineapple Juice
5351- Citrus and Citrus Blend Juices, asep. packed
5352302 Pineapple Juice, asep. packed
5361- Fresh Citrus and Citrus Blend Juices
5362206 Papaya Juice, fresh
5362207 Pineapple-Coconut Juice, fresh
5362208 Mango Juice, fresh
5362209 Pineapple Juice, fresh
5423108 Pineapple, dry
5423109 Papaya, dry
5423110 Bananas, dry
5423111 Mangos, dry
5423117 Litchis, dry
5423118 Tamarind, dry
5423119 Plantain, dry
(includes baby foods)
64202- Cantaloupe Nectar
64203- Guava Nectar
64204- Mango Nectar
64210- Papaya Nectar
64213- Passion Fruit Nectar
64221- Soursop Nectar
6710503 Bananas, baby
6711500 Bananas, baby, dry
6720500 Orange Juice, baby
6721300 Pineapple Juice, baby
(includes baby foods/juices except mixtures; excludes fruit
mixtures)
Exposure Factors Handbook
September 2011
Page
13B-11
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Exposed Veg.
Household Code/Definition
491-
493-
4941-
4943-
4944-
4945-
4946-
49481-
49483-
4951-
4952-
4955-
4958103
4958111
4958112
4958113
4958114
4958118
4958119
4958120
4958200
4958201
4958202
4958203
4958402
4958403
4958504
4958506
4958508
4958601
5111-
5113-
5114101
51144-
5114704
5114801
5114901
5114902
5114903
5114904
5114905
5114906
5114907
5114913
5114914
5114918
5114920
Fresh Dark Green Vegetables
Fresh Tomatoes
Fresh Asparagus
Fresh Beans, Snap or Wax
Fresh Cabbage
Fresh Lettuce
Fresh Okra
Fresh Artichokes
Fresh Brussel Sprouts
Fresh Celery
Fresh Cucumbers
Fresh Cauliflower
Fresh Kohlrabi
Fresh Jerusalem Artichokes
Fresh Mushrooms
Mushrooms, home canned
Mushrooms, home frozen
Fresh Eggplant
Eggplant, cooked
Eggplant, home frozen
Fresh Summer Squash
Summer Squash, cooked
Summer Squash, home canned
Summer Squash, home frozen
Fresh Bean Sprouts
Fresh Alfalfa Sprouts
Bamboo Shoots
Seaweed
Tree Fern, fresh
Sauerkraut
Dark Green Vegetables (all are exposed)
Tomatoes
Asparagus, comm. canned
Beans, green, snap, yellow, comm. canned
Snow Peas, comm. canned
Sauerkraut, comm. canned
Artichokes, comm. canned
Bamboo Shoots, comm. canned
Bean Sprouts, comm. canned
Cabbage, comm. canned
Cabbage, comm. canned, no sauce
Cauliflower, comm. canned, no sauce
Eggplant, comm. canned, no sauce
Mushrooms, comm. canned
Okra, comm. canned
Seaweeds, comm. canned
Summer Squash, comm. canned
Individual Code
721-
722-
74-
7510050
7510075
7510080
75101-
7510275
7510280
7510300
7510400
7510500
7510700
7510900
7510950
7511100
7511120
7511200
75113-
7511500
7511900
7512100
75122-
7512750
7512775
75128-
7513210
7514100
7514130
7514150
75142-
75143-
7514410
7514600
7514700
7520600
75201-
75202-
75203-
752049-
75205-
75206-
75207-
752085-
752090-
75210-
75211-
Dark Green Leafy Veg.
Dark Green Non-Leafy Veg.
Tomatoes and Tomato Mixtures
Alfalfa Sprouts
Artichoke, Jerusalem, raw
Asparagus, raw
Beans, sprouts and green, raw
Brussel Sprouts, raw
Buckwheat Sprouts, raw
Cabbage, raw
Cabbage, Chinese, raw
Cabbage, Red, raw
Cauliflower, raw
Celery, raw
Chives, raw
Cucumber, raw
Eggplant, raw
Kohlrabi, raw
Lettuce, raw
Mushrooms, raw
Parsley
Pepper, hot chili
Peppers, raw
Seaweed, raw
Snowpeas, raw
Summer Squash, raw
Celery Juice
Cabbage or Cole Slaw
Chinese Cabbage Salad
Celery with cheese
Cucumber salads
Lettuce salads
Lettuce, wilted with bacon dressing
Greek salad
Spinach salad
Algae, dried
Artichoke, cooked
Asparagus, cooked
Bamboo Shoots, cooked
Beans, string, cooked
Beans, green, cooked/canned
Beans, yellow, cooked/canned
Bean Sprouts, cooked
Breadfruit
Brussel Sprouts, cooked
Cabbage, Chinese, cooked
Cabbage, green, cooked
Page
13B-12
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Exposed Veg.
(cont.)
5114923 Chinese or Celery Cabbage, comm. canned
51152- Tomatoes, canned, low sod.
5115301 Asparagus, canned, low sod.
5115302 Beans, Green, canned, low sod.
5115303 Beans, Yellow, canned, low sod.
5115309 Mushrooms, canned, low sod.
51154- Greens, canned, low sod.
5115501 Sauerkraut, low sodium
5211- Dark Gr. Veg., comm. frozen (all exp.)
52131- Asparagus, comm. froz.
52133- Beans, snap, green, yellow, comm. froz.
5213407 Peapods, comm. froz.
5213408 Peapods, with sauce, comm. froz.
5213409 Peapods, with other veg., comm. froz.
5213701 Brussel Sprouts, comm. froz.
5213702 Brussel Sprouts, comm. froz. with cheese
5213703 Brussel Sprouts, comm. froz. with other veg.
5213705 Cauliflower, comm. froz.
5213706 Cauliflower, comm. froz. with sauce
5213707 Cauliflower, comm. froz. with other veg.
5213708 Caul., comm. froz. with other veg. & sauce
5213709 Summer Squash, comm. froz.
5213710 Summer Squash, comm. froz. with other veg.
5213716 Eggplant, comm. froz.
5213718 Mushrooms with sauce, comm. froz.
5213719 Mushrooms, comm. froz.
5213720 Okra, comm. froz.
5213721 Okra, comm. froz., with sauce
5311- Canned Tomato Juice and Tomato Mixtures
5312102 Canned Sauerkraut Juice
5321- Frozen Tomato Juice
5371- Fresh Tomato Juice
5381102 Aseptically Packed Tomato Juice
5413101 Dry Algae
5413102 Dry Celery
5413103 Dry Chives
5413109 Dry Mushrooms
5413111 Dry Parsley
5413112 Dry Green Peppers
5413113 Dry Red Peppers
5413114 Dry Seaweed
5413115 Dry Tomatoes
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
75212- Cabbage, red, cooked
752130- Cabbage, savoy, cooked
75214- Cauliflower
75215- Celery, Chives, Christophine (chayote)
752167- Cucumber, cooked
752170- Eggplant, cooked
752171- Fern shoots
752172- Fern shoots
752173- Flowers of sesbania, squash or lily
7521801 Kohlrabi, cooked
75219- Mushrooms, cooked
75220- Okra/lettuce, cooked
7522116 Palm Hearts, cooked
7522121 Parsley, cooked
75226- Peppers, pimento, cooked
75230- Sauerkraut, cooked/canned
75231- Snowpeas, cooked
75232- Seaweed
75233- Summer Squash
7540050 Artichokes, stuffed
7540101 Asparagus, creamed or with cheese
75403- Beans, green with sauce
75404- Beans, yellow with sauce
7540601 Brussel Sprouts, creamed
7540701 Cabbage, creamed
75409- Cauliflower, creamed
75410- Celery/Chiles, creamed
75412- Eggplant, fried, with sauce, etc.
75413- Kohlrabi, creamed
75414- Mushrooms, Okra, fried, stuffed, creamed
754180- Squash, baked, fried, creamed, etc.
7541822 Christophine, creamed
7550011 Beans, pickled
7550051 Celery, pickled
7550201 Cauliflower, pickled
755025- Cabbage, pickled
7550301 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweet
7550305 Cucumber pickles, fresh
7550307 Cucumber, Kim Chee
7550308 Eggplant, pickled
7550311 Cucumber pickles, dill, reduced salt
7550314 Cucumber pickles, sweet, reduced salt
7550500 Mushrooms, pickled
7550700 Okra, pickled
75510- Olives
7551101 Peppers, hot
7551102 Peppers, pickled
7551301 Seaweed, pickled
7553500 Zucchini, pickled
76102- Dark Green Veg., baby
76401- Beans, baby (excl. most soups & mixtures)
Exposure Factors Handbook
September 2011
Page
13B-13
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Protected Veg.
4922- Fresh Pumpkin, Winter Squash
4942- Fresh Lima Beans
4947- Fresh Peas
49482- Fresh Soy Beans
4956- Fresh Corn
4958303 Succotash, home canned
4958304 Succotash, home frozen
495 8401 Fresh Cactus (prickly pear)
4958503 Burdock
4958505 Bitter Melon
4958507 Horseradish Tree Pods
51122- Comm. Canned Pumpkin and Squash (baby)
51142- Beans, comm. canned
51143- Beans, lima and soy, comm. canned
51146- Corn, comm. canned
5114701 Peas, green, comm. canned
5114702 Peas, baby, comm. canned
5114703 Peas, blackeyed, comm. canned
5114705 Pigeon Peas, comm. canned
5114919 Succotash, comm. canned
5115304 Lima Beans, canned, low sod.
5115306 Corn, canned, low sod.
5115307 Creamed Corn, canned, low sod.
511531- Peas and Beans, canned, low sod.
52122- Winter Squash, comm. froz.
52132- Lima Beans, comm. froz.
5213401 Peas, gr., comm. froz.
5213402 Peas, gr., with sauce, comm. froz.
5213403 Peas, gr., with other veg., comm. froz.
5213404 Peas, gr., with other veg., comm. froz.
5213405 Peas, blackeyed, comm. froz.
5213406 Peas, blackeyed, with sauce, comm. froz.
52135- Corn, comm. froz.
5213712 Artichoke Hearts, comm. froz.
5213713 Baked Beans, comm. froz.
5213717 Kidney Beans, comm. froz.
5213724 Succotash, comm. froz.
5411- Dried Beans
5412- Dried Peas and Lentils
5413104 Dry Corn
5413106 Dry Hominy
5413504 Dry Squash, baby
5413603 Dry Creamed Corn, baby
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
732- Pumpkin
733- Winter Squash
7510200 Lima Beans, raw
7510550 Cactus, raw
7510960 Corn, raw
7512000 Peas, raw
7520070 Aloe vera juice
752040- Lima Beans, cooked
752041- Lima Beans, canned
7520829 Bitter Melon
752083- Bitter Melon, cooked
7520950 Burdock
752131- Cactus
752160- Corn, cooked
752161- Corn, yellow, cooked
752162- Corn, white, cooked
752163- Corn, canned
7521749 Hominy
752175- Hominy
75223- Peas, cowpeas, field or blackeyed, cooked
75224- Peas, green, cooked
75225- Peas, pigeon, cooked
75301- Succotash
75402- Lima Beans with sauce
75411- Corn, scalloped, fritter, with cream
7541650 Pea salad
7541660 Pea salad with cheese
75417- Peas, with sauce or creamed
7550101 Corn relish
76205- Squash, yellow, baby
76405- Corn, baby
76409- Peas, baby
76411- Peas, creamed, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Page
13B-14
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Root Vegetables
Household Code/Definition
48- Potatoes, Sweetpotatoes
4921- Fresh Carrots
4953- Fresh Onions, Garlic
4954- Fresh Beets
4957- Fresh Turnips
4958101 Fresh Celeriac
4958102 Fresh Horseradish
4958104 Fresh Radishes, no greens
4958105 Radishes, home canned
4958106 Radishes, home frozen
4958107 Fresh Radishes, with greens
4958108 Fresh Salsify
4958109 Fresh Rutabagas
49581 10 Rutabagas, home frozen
4958115 Fresh Parsnips
4958116 Parsnips, home canned
4958117 Parsnips, home frozen
4958502 Fresh Lotus Root
4958509 Ginger Root
4958510 Jicama, including yambean
51121- Carrots, comm. canned
51145- Beets, comm. canned
5114908 Garlic Pulp, comm. canned
5114910 Horseradish, comm. prep.
5114915 Onions, comm. canned
5114916 Rutabagas, comm. canned
5114917 Salsify, comm. canned
5114921 Turnips, comm. canned
5114922 Water Chestnuts, comm. canned
51151- Carrots, canned, low sod.
5115305 Beets, canned, low sod.
5115502 Turnips, low sod.
52121- Carrots, comm. froz.
5213714 Beets, comm. froz.
5213722 Onions, comm. froz.
5213723 Onions, comm. froz., with sauce
5213725 Turnips, comm. froz.
5312103 Canned Carrot Juice
5312104 Canned Beet Juice
5372102 Fresh Carrot Juice
5413105 Dry Garlic
5413110 Dry Onion
5413502 Dry Carrots, baby
5413503 Dry Sweet Potatoes, baby
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
Individual Code
71- White Potatoes and Puerto Rican St. Veg.
7310- Carrots
73 1 1 1 40 Carrots in sauce
7311200 Carrot chips
734- Sweetpotatoes
7510250 Beets, raw
7511150 Garlic, raw
7511180 Jicama (yambean), raw
7511250 Leeks, raw
75117- Onions, raw
7512500 Radish, raw
7512700 Rutabaga, raw
7512900 Turnip, raw
752080- Beets, cooked
752081- Beets, canned
7521362 Cassava
7521740 Garlic, cooked
7521771 Horseradish
7521850 Lotus root
752210- Onions, cooked
7522110 Onions, dehydrated
752220- Parsnips, cooked
75227- Radishes, cooked
75228- Rutabaga, cooked
75229- Salsify, cooked
75234- Turnip, cooked
75235- Water Chestnut
7540501 Beets, harvard
75415- Onions, creamed, fried
7541601 Parsnips, creamed
7541810 Turnips, creamed
7550021 Beets, pickled
7550309 Horseradish
7551201 Radishes, pickled
7553403 Turnip, pickled
76201- Carrots, baby
76209- Sweetpotatoes, baby
76403- Beets, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
USDA SUBCATEGORIES
Dark Green
Vegetables
49 1 - Fresh Dark Green Vegetables
5111- Comm. Canned Dark Green Veg.
51154- Low Sodium Dark Green Veg.
5211- Comm. Frozen Dark Green Veg.
5413111 Dry Parsley
5413112 Dry Green Peppers
5413113 Dry Red Peppers
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures/dinners; excludes vegetable juices and dried
vegetables)
72- Dark Green Vegetables
all forms
leafy, nonleafy, dk. gr. veg. soups
Exposure Factors Handbook
September 2011
Page
13B-15
-------
Exposure Factors Handbook
Chapter 13—Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987-1988
USDANFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued)
Food Product
Household Code/Definition
Individual Code
Deep Yellow
Vegetables
492- Fresh Deep Yellow Vegetables
5112- Comm. Canned Deep Yellow Veg.
51151 - Low Sodium Carrots
5212- Comm. Frozen Deep Yellow Veg.
5312103 Carrot Juice
54135- Dry Carrots, Squash, Sw. Potatoes
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures/dinners; excludes vegetable juices and dried
vegetables)
73- Deep Yellow Vegetables
all forms
carrots, pumpkin, squash, sweet potatoes, dp. yell. veg.
soups
Other
Vegetables
Fresh Light Green Vegetables
Fresh Other Vegetables
Comm. Canned Other Veg.
Low Sodium Other Veg.
Low Sodium Other Veg.
Comm. Frozen Other Veg.
Sauerkraut Juice
Beet Juice
Dried Beans
Dried Peas, Lentils
Dried Other Veg.
Dry Seaweed
Dry Cr. Corn, baby
494-
495-
5114-
51153-
51155-
5213-
5312102
5312104
5411-
5412-
541310-
5413114
5413603
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures/dinners; excludes vegetable juices and dried
vegetables)
75- Other Vegetables
all forms
Citrus Fruits
501- Fresh Citrus Fruits
5121 - Comm. Canned Citrus Fruits
5331- Canned Citrus and Citrus Blend Juice
5341- Frozen Citrus and Citrus Blend Juice
5351- Aseptically Packed Citrus and Citr. Blend
Juice
5361- Fresh Citrus and Citrus Blend Juice
(includes baby foods; excludes dried fruits)
61- Citrus Fruits and Juices
6720500 Orange Juice, baby food
6720600 Orange-Apricot Juice, baby food
6720700 Orange-Pineapple Juice, baby food
6721100 Orange-Apple-Banana Juice, baby food
(excludes dried fruits)
Other Fruits
502- Fresh Other Vitamin C-Rich Fruits
503- Fresh Other Fruits
5122- Comm. Canned Fruits Other than Citrus
5222- Frozen Strawberries
5223- Frozen Other than Citr. or Vitamin C-Rich Fr.
5332- Canned Fruit Juice Other than Citrus
5342- Frozen Juices Other than Citrus
5352- Aseptically Packed Fruit Juice Other than
Citr.
5362- Fresh Fruit Juice Other than Citrus
542- Dry Fruits
(includes baby foods; excludes dried fruits)
62- Dried Fruits
63- Other Fruits
64- Fruit Juices and Nectars Excluding Citrus
671- Fruits, baby
67202- Apple Juice, baby
67203- Baby Juices
67204- Baby Juices
67212- Baby Juices
67213- Baby Juices
673- Baby Fruits
674- Baby Fruits
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Chapter 14—Total Food Intake
TABLE OF CONTENTS
LIST OF TABLES 14-ii
14. TOTAL FOOD INTAKE 14-1
14.1. INTRODUCTION 14-1
14.2. RECOMMENDATIONS 14-1
14.3. STUDIES OF TOTAL FOOD INTAKE 14-4
14.3.1. U.S. EPA Re-Analysis of 1994-1996, 1998 Continuing Survey of Food Intake
by Individuals (CSFII), Based on U.S. EPA (2007) 14-4
14.3.2. U.S. EPAAnalysis of National Health and Nutrition Examination Survey
(NHANES) 2003-2006 Data 14-5
14.4. REFERENCES FOR CHAPTER 14 14-6
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LIST OF TABLES
Table 14-1. Recommended Values for Per Capita Total Food Intake, Edible Portion, Uncooked
Weight 14-2
Table 14-2. Confidence in Recommendations for Total Food Intake 14-3
Table 14-3. Per Capita Total Food Intake, Edible Portion, Uncooked 14-7
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion,
uncooked) 14-8
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible
portion, uncooked) 14-12
Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Food Intake 14-16
Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Meat Intake 14-20
Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Meat and Dairy
Intake 14-24
Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Fish Intake 14-28
Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Fruit and
Vegetable Intake 14-33
Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Intake for Individuals with Low-End, Mid-Range, and High-End Total Dairy Intake 14-37
Table 14-12. Intake of Total Food (g/kg-day), Edible Portion, Uncooked Weight 14-41
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Chapter 14—Total Food Intake
14. TOTAL FOOD INTAKE
14.1. INTRODUCTION
The U.S. food supply is generally considered to
be one of the safest in the world. Nevertheless,
contamination of foods may occur as a result of
environmental pollution of the air, water, or soil, or
the intentional use of chemicals such as pesticides or
other agrochemicals. Ingestion of contaminated foods
is a potential pathway of exposure to such
contaminants. To assess chemical exposure through
this pathway, information on food ingestion rates is
needed. Chapters 9 through 13 of this handbook
report per capita and consumer-only data on food
consumption rates for various food items and food
categories. These intake rates were estimated by the
U.S. Environmental Protection Agency (EPA) using
databases developed by the U.S. Department of
Agriculture (USDA). U.S. EPA (2007) expanded the
analysis of food intake in order to examine
individuals' food consumption habits in greater
detail. Using data from the USDA's Continuing
Survey of Food Intake by Individuals (CSFII)
conducted in 1994-1996 and 1998, U.S. EPA (2007)
derived distributions to characterize (1) the total food
intake among various groups in the U.S. population,
subdivided by age, race, geographic region, and
urbanization; (2) the contribution of various food
categories (e.g., meats, grains, vegetables, etc.) to
total food intake among these populations; and
(3) the contribution of various food categories to total
food intake among individuals exhibiting low- or
high-end consumption patterns of a specific food
category (e.g., individuals below the 10th percentile
or above the 90th percentile for fish consumption).
These data may be useful for assessing exposure
among populations exhibiting lower or higher than
usual intake of certain types of foods (e.g., people
who eat little or no meat, or people who eat large
quantities of fish). Recently, U.S. EPA's Office of
Pesticide Programs (OPP) used data from the 2003 to
2006 National Health and Nutrition Examination
Survey (NHANES) to estimate intake of various
foods, including total foods.
The recommendations for total food intake rates
are provided in the next section, along with a
summary of the confidence ratings for these
recommendations. Following the recommendations,
the studies on total food intake are summarized.
14.2. RECOMMENDATIONS
Table 14-1 presents a summary of recommended
values for total food intake. Table 14-2 presents the
confidence ratings for these recommendations. The
recommended total food intake rates are based on
data from the U.S. EPA/OPP's recent analysis of
NHANES data from 2003 to 2006. For information
about the proportion of total intake represented by the
major food groups, it is recommended that the data
based on a re-analysis of the data from U.S. EPA
(2007) be used. Section 14.3.1 describes this re-
analysis, and Tables 14-3 to 14-11 provide the data.
However, it should be noted that, because the
U.S. EPA (2007) data are based on 1994-1996 and
1998 CSFII data, they may not reflect recent changes
that may have occurred in consumption patterns.
Both of the studies of total dietary intake
presented in this chapter are based on data collected
over a 2-day period and may not necessarily reflect
the long-term distribution of average daily intake
rates. However, because the broad categories of foods
used in this analysis (e.g., total foods, total fruits,
total vegetables, etc.) are typically eaten on a daily
basis throughout the year with minimal seasonality,
the short-term distribution may be a reasonable
approximation of the long-term distribution, although
it will display somewhat increased variability. This
implies that the upper percentiles shown here will
tend to overestimate the corresponding percentiles of
the true long-term distribution.
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Chapter 14—Total Food Intake
Table 14-1. Recommended Values for Per Capita Total Food Intake, Edible Portion, Uncooked Weight
Mean 95th
Age Gioup (yeais)
g/kg-day
Children
Birth to <1 91
lto<3 113
3 to <6 79
6to50 29
Multiple c
„ ^., oource
Percentiles
208C
185C
137
92 U.S. EPA/OPP analysis
See Table 14-12 of NHANES
2003-2006
56
63
59
a Based on data for ages 6 to <13 years.
b Based on data for ages 13 to <20 years.
0 Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance
Estimation and Statistical Reporting Standards on NHANES III and CSFll Reports: NHIS/NCHS
Analytical Working Group Recommendations (NCHS, 1993).
Note: Total food intake was defined as intake of the sum of all foods, beverages, and water ingested.
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Chapter 14—Total Food Intake
Table 14-2. Confidence in Recommendations for Total Food Intake
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodologies were adequate and the analytical approaches
were competently executed. The study sizes were very large; sample
sizes varied with age. The response rates were good. The studies
analyzed primary data on recall of ingestion.
No direct measurements were taken. The studies relied on survey data.
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The analyses were specifically designed to address food intake.
The populations studied were representative of the U.S. population.
The data used were the most current data publicly available at the time
the analysis was conducted for the handbook. However, the data used in
the re-analysis of the U.S. EPAstudy are now 11-15 years old. The
national trends in bodyweight,(increasing obesity prevalence) may in
part be due to changes in food intake patterns.
Ingestion rates were estimated based on short-term data collected in the
CSFII 1994-1996, 1998 andNHANES 2003-2006.
Medium
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The NHANES and CSFII data are publicly available. The U.S. EPA
(2007) report is available online.
The methodology was clearly presented; enough information was
included to reproduce results.
NHANES and CSFII follow strict QA/QC procedures. U.S. EPA's
analysis of NHANES data has only been reviewed internally, but the
methodology has been used in an analysis of previous data.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Short term distributions of total intake were provided. The survey was
not designed to capture long-term day-to-day variability.
The survey data were based on recall over a 2-day period. The
U.S. EPA/OPP analysis of NHANES data included all foods, beverages,
and water ingested. Beverages, sugar, candy, and sweets, and nuts and
nut products were not included in the re-analysis of the U.S. EPA (2007)
data. There is also some uncertainty associated with the translation of
mixed foods (i.e., recipes) to food commodity ingredients in both
studies.
Medium
Evaluation and Review
Peer Review
Number and Agreement of Studies
The USDA CSFII survey received a high level of peer review. The
U.S. EPA (2007) analysis was also peer reviewed; however, the
re-analysis of these data using the new age categories for children was
not peer reviewed outside the Agency. The methodology used in the
NHANES 2003-2006 analysis is the same as used in previous peer-
reviewed analysis conducted by U.S. EPA/OPP.
Two studies were available for this factor.
Medium
Overall Rating
Medium
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Chapter 14—Total Food Intake
14.3. STUDIES OF TOTAL FOOD INTAKE
14.3.1. U.S. EPA Re-Analysis of 1994-1996,
1998 Continuing Survey of Food Intake
by Individuals (CSFII), Based on
U.S. EPA (2007)—Analysis of Total Food
Intake and Composition of Individual's
Diet Based on U.S. Department of
Agriculture's (USDA's) 1994-1996,1998
CSFII
U.S. EPA's National Center for Environmental
Assessment (NCEA) conducted an analysis to
evaluate the total food intake of individuals in the
United States using data from the USDA's
1994-1996, 1998 CSFII (USDA, 2000) and
U.S. EPA's Food Commodity Intake Database
(FCID) (U.S. EPA, 2000). The 1994-1996 CSFII and
its 1998 Supplemental Children's Survey were
designed to obtain data from a statistically
representative sample of non-institutionalized
persons living in the United States. Survey
participants were selected using a multistage process.
The respondents were interviewed twice to collect
information on food consumption during
2 non-consecutive days. For both survey days, data
were collected by an in-home interviewer. The Day 2
interview was conducted 3 to 10 days later and on a
different day of the week. Of the more than
20,000 individuals surveyed, approximately 10,000
were under 21 years of age, and approximately 9,000
were under the age of 11. The 1994-1996 survey and
1998 supplement are referred to collectively as CSFII
1994-1996, 1998. Each individual in the survey was
assigned a sample weight based on his or her
demographic data; these weights were taken into
account when calculating mean and percentile values
of food consumption for the various demographic
categories that were analyzed in the study. The
sample weighting process used in the CSFII
1994-1996, 1998 is discussed in detail in USDA
(2000).
For the analysis of total food intake, food
commodity codes provided in U.S. EPA's FCID
(U.S. EPA, 2000) were used to translate as-eaten
foods (e.g., beef stew) identified by USDA food
codes in the CSFII data set into food commodities
(e.g., beef, potatoes, carrots, etc.). The method used
to translate USDA food codes into U.S. EPA
commodity codes is discussed in detail in USDA
(2000). The U.S. EPA commodity codes were
assigned to broad food categories (e.g., total meats,
total vegetables, etc.) for use in the analysis. Total
food intake was defined as intake of the sum of all
foods in the following major food categories: dairy,
meats, fish, eggs, grains, vegetables, fruits, and fats.
Beverages, sugar, candy, and sweets, and nuts (and
nut products) were not included because they could
not be categorized into the major food groups. Also,
human milk intake was not included. Percent
consuming, mean, standard error, and a range of
percentile values were calculated on the basis of
grams of food per kilogram of body weight per day
(g/kg-day) and on the basis of grams per day (g/day).
In addition to total food intake, intake of the various
major food groups for the various age groups in units
of g/day and g/kg-day were also estimated for
comparison to total intake.
To evaluate variability in the contributions of the
major food groups to total food intake, individuals
were ranked from lowest to highest, based on total
food intake. Three subsets of individuals were
defined, as follows: a group at the low end of the
distribution of total intake (below the 10th percentile
of total intake), a mid-range or central group (the 45th
to 55th percentile of total intake), and a group at the
high end of the distribution of total intake (above the
90th percentile of total intake). Mean total food intake
(in g/day and g/kg-day), mean intake of each of the
major food groups (in g/day and g/kg-day), and the
percent of total food intake that each of these food
groups represents were calculated for each of the
three populations (i.e., individuals with low-end,
central, and high-end total food intake). A similar
analysis was conducted to estimate the contribution
of the major food groups to total food intake for
individuals at the low-end, central, and high-end of
the distribution of total meat intake, total dairy
intake, total meat and dairy intake, total fish intake,
and total fruit and vegetable intake. For example, to
evaluate the variability in the diets of individuals at
the low-end, mid-range, and high-end of the
distribution of total meat intake, survey individuals
were ranked according to their reported total meat
intake. Three subsets of individuals were formed as
described above. Mean total food intake, intake of the
major food groups, and the percent of total food
intake represented by each of the major food groups
were tabulated. U.S. EPA (2007) presented the
results of the analysis for the following age groups:
<1 year, 1 to 2 years, 3 to 5 years, 6 to 11 years, 12 to
19 years, 20 to 39 years, 40 to 69 years, and 70 years
and older. The data were tabulated in units of
g/kg-day and g/day.
The analysis presented in U.S. EPA (2007) was
conducted before U.S. EPA published the guidance
entitled Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005). As a result, the age
groups used for children in U.S. EPA (2007) were not
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Chapter 14—Total Food Intake
entirely consistent with the age groups recommended
in the 2005 guidance. In order to conform to the
standard age categories for children recommended in
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005), each
of the tables from U.S. EPA (2007) was modified by
re-analyzing the source data and applying the new
childhood age categories (i.e., <1 month, 1 to
<3 months, 3 to <6 months, 6 to <12 months, 1 to
<2 years, 2 to <3 years, 3 to <6 years, 6 to <11 years,
11 to <16 years, and 16 to <21 years). Table 14-3
presents distributions of total food intake in units of
g/day and g/kg-day. Tables 14-4 and 14-5 compare
total food intake to intake of the various major food
groups for the various age groups in units of g/day
and g/kg-day, respectively. It should be noted that
some U.S. EPA commodity codes are listed under
more than one food category. For this reason, in the
tables, the intake rates for the individual food
categories do not necessarily add up to the figure
given for total food intake (U.S. EPA, 2007). Also,
data are not reported for food groups for which there
were less than 20 consumers in a particular age
group. Tables 14-6 through 14-11 present the
contributions of the major food groups to total food
intake for individuals (in the various age groups) at
the low-end, central, and high-end of the distribution
of total food intake (see Table 14-6), total meat
intake (see Table 14-7), total meat and dairy intake
(see Table 14-8), total fish intake (see Table 14-9),
total fruit and vegetable intake (see Table 14-10), and
total dairy intake (see Table 14-11) in units of g/day
and g/kg-day. For each of the three classes of
consumers, consumption of nine different food
categories is presented (i.e., total foods, dairy, meats,
fish, eggs, grains, vegetables, fruits, and fats). For
example, in Table 14-9 one will find the mean
consumption of meats, eggs, vegetables, etc. for
individuals with an unusually high (or low or
average) consumption offish.
As discussed in previous chapters, the
1994-1996, 1998 CSFII data have both advantages
and limitations with regard to estimating food intake
rates. The large sample size (more than
20,000 persons) is sufficient to allow categorization
within narrowly defined age categories. In addition,
the survey was designed to obtain a statistically valid
sample of the entire U.S. population that included
children and low income groups. However, the
survey design is of limited utility for assessing small
and potentially at-risk populations based on ethnicity,
medical status, geography, or other factors (such as
activity level). Another limitation is that data are
based on a 2-day survey period and, as such, may not
accurately reflect long-term eating patterns. This is
particularly true for the extremes of the distribution
of food intake.
14.3.2. U.S. EPA Analysis of National Health and
Nutrition Examination Survey
(NHANES) 2003-2006 Data
U.S. EPA/OPP used data from the 2003 to 2006
NHANES to estimate intake of various individual
foods, major food groups, and total foods. This
chapter presents the data for total foods (Chapter 9
provides data on the intake of fruits and vegetables;
Chapter 11 provides data on intake of meat, dairy
products, and fats, and Chapter 12 provides data on
intake of grain and grain products). The total intake
rates presented here represent intake of all forms of
foods eaten (e.g., both home produced and
commercially produced). Individuals who provided
data for 2 days of the survey were included in the
intake estimates. Individuals who did not provide
information on body weight or for whom identifying
information was unavailable were excluded from the
analysis. The U.S. EPA/OPP analysis of 2003-2006
NHANES data included all foods, beverages, and
water ingested. Two-day average intake rates were
calculated for all individuals in the database for each
of the food items/groups. These average daily intake
rates were divided by each individual's reported body
weight to generate intake rates in units of grams per
kilogram of body weight per day (g/kg-day). The data
were weighted according to the 4-year, 2-day sample
weights provided in the 2003-2006 NHANES to
adjust the data for the sample population to reflect the
national population.
Intake data from the NHANES were based on
uncooked forms of the edible portion of the food
items/groups. Summary statistics, including: number
of individuals represented in the estimates, mean
intake rate, and standard error of the mean intake rate
were calculated for total foods. Percentiles of the
intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th,
75th, 90th, 95th, 99th, and the maximum value) were
also provided. The data represent per capita data.
However, the intake rates are the same as those for
consumers only because all survey respondents ate
some type of food during the survey period. Data
were provided for the following age groups: <1 year,
1 to <3 years, 3 to <6 years, 6 to <13 years, 13 to
<20 years, 20 to <50 years, >50 years, females
only—13 to 49 years, and all ages combined. Data
were also generated for various racial/ethnic groups
(i.e., Mexican American, non-Hispanic Black,
non-Hispanic White, other Hispanic, and other race).
Table 14-12 presents intake data for total foods in
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Chapter 14—Total Food Intake
g/kg-day from the 2003-2006 NHANES analysis for
these age groups and racial/ethnic groups.
The strength of U.S. EPA's analysis is that it
provides distributions of total food intake for various
age groups of children and adults, normalized by
body weight. The analysis uses the 2003-2006
NHANES data set, which was designed to be
representative of the U.S. population. The data set
includes 4 years of intake data combined, and is
based on a 2-day survey period. Because these data
were developed for use in U.S. EPA's pesticide
registration program, the childhood age groups used
are slightly different than those recommended in
U.S. EPA's Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
However, given the similarities in the age groups
used, the data should provide suitable intake
estimates for the age groups of interest. The data for
infants <12 months could not be separated out into
the recommended age groups due to sample size
limitations. This analysis generated data for total
foods only. Analyses to estimate the proportion of
total food intake represented by the various food
groups were not conducted for this data set.
14.4. REFERENCES FOR CHAPTER 14
NCHS (National Center for Health Statistics). (1993)
Joint policy on variance estimation and
statistical reporting standards on NHANES
III and CSFII reports: HNIS/NCHS analytic
working group recommendations. Human
Nutrition Information Service
(HNIS)/Analytic Working Group. Available
from: Agricultural Research Service, Survey
Systems/Food Consumption Laboratory,
4700 River Road, Unit 83, Riverdale, MD.
USD A (Department of Agriculture). (2000) 1994-96,
1998 continuing survey of food intakes by
individuals (CSFII). CD-ROM. Agricultural
Research Service, Beltsville Human
Nutrition Research Center, Beltsville, MD.
Available from the National Technical
Information Service, Springfield, VA; PB-
2000-500027.
U.S. EPA (Environmental Protection Agency). (2000)
Food commodity intake database [FCID raw
data file]. Office of Pesticide Programs,
Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
U.S. Environmental Protection Agency,
Washington, DC; EPA/630/P-03/003F.
U.S. EPA (Environmental Protection Agency) (2007)
Analysis of total food intake and
composition of individual's diet based on
USDA's 1994-96, 1998 continuing survey
of food intakes by individuals (CSFII).
National Center for Environmental
Assessment, Washington, DC; EPA/600/R-
05/062F. Available from the National
Technical Information Service, Springfield,
VA, and online at http://www.epa.gov/ncea.
Page
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s
1=
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
21 to <40 years
40 to <70 years
70 years and older
Table 14-3. Per Capita Total Food Intake, Edible Portion, Uncooked"
Q
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
20 to <40 years
40 to <70 years
70 years and older
T- * ic
Total
PC
(%)
Mean
SE
Percentile
10
25
50
75
90
95
Total Food Intake (g/day)
59
183
385
676
1,002
994
4,112
1,553
975
743
2,950
4,818
1,393
88
245
411
678
1,002
994
4,112
1,553
975
743
2,950
4,818
1,393
67.0
74.7
93.7
99.7
100
100
100
100
100
100
100
100
100
67
80
197
507
1,039
1,024
1,066
1,118
1,209
1,184
1,100
1,100
1,000
59
70
150
344
407
377
380
372
499
634
518
468
430
0
0
0
34
216
312
416
438
343
308
0
0
0
141
414
491
548
586
536
467
493
472
449
0
0
12
191
570
575
629
680
657
556
579
567
549
0
0
100
283
770
752
805
846
851
750
778
766
741
67
94
167
413
998
994
1,020
1,052
1,124
1,061
1,040
1,030
982
108
120
286
600
1,244
1,257
1,276
1,344
1,491
1,447
1,390
1,350
1,280
142
168
385
925
1,556
1,517
1,548
1,642
1,860
1,883
1,780
1,710
1,560
221
188
476
1,220
1,756
1,649
1,746
1,825
2,179
2,283
2,110
1,930
1,820
Total Food Intake (g/kg-day)
59
183
385
676
1,002
994
4,112
1,553
975
743
2,950
4,818
1,393
88
245
411
678
1,002
994
4,112
1,553
975
743
2,950
4,818
1,393
67.0
74.7
93.7
99.7
100
100
100
100
100
100
100
100
100
20
16
28
56
90
74
61
40
24
18
16
14
15
18
14
21
36
37
29
24
17
11
9
7
6
6
0
0
0
3
17
23
21
10
5
5
0
0
0
17
38
34
30
17
9
6
6
6
6
0
0
2
22
48
39
34
21
11
8
8
7
8
0
0
15
33
65
52
44
28
16
12
11
10
10
19
18
24
47
85
72
57
38
22
16
15
14
14
33
25
38
66
109
92
73
49
30
22
20
18
19
43
36
53
99
137
113
91
61
38
30
25
23
24
61
40
65
134
161
126
102
70
45
35
30
26
27
99
222
273
705
1,823
2,215
2,071
2,168
2,218
2,668
3,281
3,120
2,480
2,260
69
55
107
211
207
146
132
88
55
47
38
34
35
Max
222
404
1,151
2,465
3,605
2,737
4,886
3,602
4,548
8,840
5,640
4,320
3,090
69
76
169
233
265
194
239
122
82
115
70
75
47
PC
SE
Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages, sugar, candy,
and sweets, and nuts (and nut products) were not included because they could not be categorized into the major food groups.
Number of consumers. The number of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human milk was not
included in the total food intake estimates presented here.
Sample size.
= Percent consuming.
= Standard error.
= Value not available.
8
£
S
I,
£
&
r
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
-------
^S3
* *Q
I
§
s
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked)
Food Group
jV
consa
jV
totalb
PC
(%)
Mean
SE
Percentile
1
5
10
25
50
75
90
95
99
Max
Age Group: Birth to <1 month
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
59
51
0
0
0
5
27
2
58
183
147
1
0
0
44
88
23
176
385
308
44
28
1
284
263
218
357
88
88
88
88
88
88
88
88
88
245
245
245
245
245
245
245
245
245
411
411
411
411
411
411
411
411
411
67.0
58.0
0.0
0.0
0.0
5.7
30.7
2.3
65.9
74.7
60.0
0.4
0.0
0.0
18.0
35.9
9.4
71.8
93.7
74.9
10.7
6.8
0.2
69.1
64.0
53.0
86.9
67
41
-
-
-
-
5
-
19
80
37
-
-
-
1
15
4
21
197
56
2
0.23
-
8
34
68
28
59
38
-
-
-
-
23
-
16
Age Group:
70
40
-
-
-
5
33
21
17
Age Group:
150
56
7
3
-
11
46
102
17
0
0
-
-
-
-
0
-
0
Ito
0
0
-
-
-
0
0
0
0
3 to
0
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
<3 months
0
0
-
-
-
0
0
0
0
<6 months
0
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
0
0
-
-
-
0
0
0
0
12
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
0
0
-
-
-
0
0
0
0
100
0
0
0
-
0
0
0
20
67
40
-
-
-
-
0
-
20
94
19
-
-
-
0
0
0
27
167
60
0
0
-
4
13
15
30
108
72
-
-
-
-
0.29
-
32
120
72
-
-
-
0
0.92
0
34
286
85
0
0
-
11
58
99
38
142
81
-
-
-
-
16
-
38
168
89
-
-
-
3
74
0
42
385
109
1
0
-
21
102
196
45
221
156
-
-
-
-
32
-
64
188
103
-
-
-
9
94
31
49
476
124
13
0.49
-
27
120
282
53
222
156
-
-
-
-
108
-
64
273
129
-
-
-
20
119
114
65
705
260
29
4
-
44
184
522
81
222
156
-
-
-
-
125
-
64
404
155
-
-
-
45
211
171
72
1,151
496
92
50
-
68
226
750
106
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) (continued)
Food Group
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
N
cons.a
676
628
500
352
34
653
662
639
661
1,002
999
965
906
188
997
1,000
986
1,002
994
994
981
943
190
993
994
970
994
N
total"
678
678
678
678
678
678
678
678
678
1,002
1,002
1,002
1,002
1,002
1,002
1,002
1,002
1,002
994
994
994
994
994
994
994
994
994
PC
(%)
99.7
92.6
73.7
51.9
5.0
96.3
97.6
94.2
97.5
100
99.7
96.3
90.4
18.8
99.5
99.8
98.4
100
100
100
98.7
94.9
19.1
99.9
100
97.6
100
Mean
507
151
22
6
0.62
33
91
169
3\
1,039
489
47
14
3
66
120
254
39
1,024
383
60
18
4
81
145
279
42
CT7
Age Group: 6
344
246
27
\3
3
28
67
142
16
Age Group:
407
332
37
21
10
34
75
204
17
Age Group:
377
243
41
24
12
35
89
230
18
Percentile
1
to<12
34
0
0
0
0
0
0
0
0
lto<2
216
1
0
0
0
8
9
0
8
2to<3
3\2
6
0
0
0
16
18
0
11
5
months
141
0
0
0
0
0.83
2
0
2
years
414
38
0
0
0
19
25
4
15
years
491
54
8
0
0
32
45
2
17
10
191
1.0
0
0
0
6
14
17
7
570
94
6
0
0
27
37
30
20
575
104
14
0
0
41
57
25
22
25
283
26
0
0
0
14
41
70
23
770
241
20
1
0
42
68
99
28
752
201
31
1
0
58
86
117
30
50
413
71
14
0
0
28
81
147
31
998
451
39
4
0
60
107
209
37
994
346
51
7
0
78
128
231
40
75
600
124
32
2
0
45
127
232
40
1,244
681
66
23
0
83
155
349
48
1,257
510
80
27
0
99
178
382
51
90
925
401
59
22
0
66
180
335
51
1,556
917
100
45
11
111
220
532
62
1,517
709
115
50
13
126
249
594
65
95
1,220
722
78
42
0
84
231
425
58
1,756
1,090
120
57
21
126
255
664
69
1,649
838
139
60
26
147
302
750
73
99
1,823
1,297
117
73
21
125
285
670
81
2,215
1,474
181
86
45
172
402
828
87
2,071
1,079
199
93
53
195
431
992
101
Max
2,465
1,873
269
103
42
260
452
1,254
90
3,605
2,935
221
212
135
209
739
1,762
146
2,737
1,378
280
169
127
263
846
2,042
129
Q
I,
-------
I
§
s
ft1
s
Table 14-4. Per Capita Intake of Total Food and
Food Group
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
N
cons.a
4,112
4,112
4,062
3,910
801
4,111
4,111
4,021
4,112
N
totalb
4,112
4,112
4,112
4,112
4,112
4,112
4,112
4,112
4,112
PC
(%)
100
100
98.8
95.1
19.5
100
100
97.8
100
Mean
1,066
392
73
16
5
101
170
243
50
Intake of Major Food Groups (g/day, edible portion, uncooked) (continued)
°T7
SE j
Age Group: 3 to
380 416
249 14
49 0
23 0
16 0
41 29
89 30
220 0
19 14
Percentile
5
<6 years
548
68
11
0
0
44
56
2
23
10
629
121
20
0
0
54
75
16
27
25
805
224
38
1
0
72
109
85
36
50
1,020
356
65
6
0
95
156
196
47
75
1,276
522
97
24
0
122
213
344
60
90
1,548
706
133
47
19
155
280
516
74
95
1,746
805
163
59
36
175
329
642
85
99
2,168
1,151
230
99
71
230
454
1,000
113
Max
4,886
3,978
433
290
192
410
915
2,252
167
Age Group: 6 to <1 1 years
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
1,553
1,553
1,533
1,490
258
1,553
1,553
1,515
1,553
975
975
970
930
167
975
975
923
975
743
742
730
703
143
743
743
671
743
1,553
1,553
1,553
1,553
1,553
1,553
1,553
1,553
1,553
975
975
975
975
975
975
975
975
975
743
743
743
743
743
743
743
743
743
100
100
98.7
95.9
16.6
100
100
97.6
100
100
100
99.5
95.4
17.1
100
100
94.7
100
100
99.9
98.3
94.6
19.2
100
100
90.3
100
1,118
408
87
16
6
119
210
193
58
1,209
368
114
19
9
136
280
195
69
1,184
283
139
21
10
150
325
168
74
372 438
243 10
56 0
22 0
17 0
48 31
103 42
184 0
22 16
Age Group: 11 to
499 343
291 1
75 1
27 0
24 0
63 33
146 65
202 0
33 18
Age Group: 16 to
634 308
279 0
127 0
30 0
33 0
93 13
204 43
237 0
42 13
586
63
12
0
0
54
76
1
27
<16 years
536
25
18
0
0
56
105
0
28
<21 years
467
8
12
0
0
48
86
0
22
680
126
24
0
0
67
96
8
33
657
43
32
0
0
70
124
0.68
34
556
19
28
0
58
128
0
30
846
229
48
2
0
87
136
60
42
851
152
63
2
0
93
176
31
47
750
63
64
1
0
88
194
3
46
1,052
371
79
6
0
114
193
141
56
1,124
307
101
7
0
127
246
135
64
1,061
196
116
7
0
132
280
74
67
1,344
557
116
22
0
143
264
280
70
1,491
507
154
25
0
168
352
273
83
1,447
410
185
29
0
190
400
242
94
1,642
741
156
46
23
179
342
440
86
1,860
740
208
53
30
212
472
483
110
1,883
649
266
59
34
256
562
432
129
1,825
837
195
58
38
201
410
545
95
2,179
948
244
72
62
249
552
635
131
2,283
934
310
89
76
307
683
665
148
2,218
1,130
268
107
102
262
560
880
121
2,668
1,401
355
123
125
333
713
930
176
3,281
1,235
458
126
146
543
1,160
1,023
213
3,602
2,680
435
163
169
513
896
1,406
168
4,548
1,972
578
244
227
645
1,333
1,535
321
8,840
1,866
2,343
223
399
730
2,495
2,270
391
s
I
i
I,
I
ft
-------
3
1=
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) (continued)
„ , „ W N PC ^ Percentile
Food Group
cons.
total"
Mean
SE
1
10
25
50
75
90
95
99
Max
Age Group: 20 years and older
Total Food Intake0 9,161 9,161 100 1,110 481
Total Dairy Intake 9,161 9,143 99.8 221 228
Total Meat Intake 9,161 9,005 98.3 130 90
Total Egg Intake 9,161 8,621 94.1 24 32
Total Fish Intake 9,161 2,648 28.9 15 36
Total Grain Intake 9,161 9,152 99.9 136 84
Total Vegetable Intake 9,161 9,161 100 309 171
Total Fruit Intake 9,161 8,566 93.5 191 224
Total Fat Intake 9,161 9,161 100 64 34
477
9
15
0
0
42
91
0
20
570
20
35
0.13
0
53
124
0
26
769 1,030 1,360 1,730 2,010 2,650 5,640
60
65
2
0
79
191
18
39
153
111
10
0
116
281
125
57
312
171
36
12
167
394
280
81
509
246
63
56
238
525
473
109
643
299
87
86
297
626
625
127
1,020
457
129
162
462
850
996
178
3,720
1,010
445
434
1,110
1,810
2,690
359
PC
SE
Number of consumers. The number of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human milk
was not included in the total food intake estimates presented here.
Sample size.
Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages,
sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
= Percent consuming.
= Standard error.
= Value not available or data not reported where the number of consumers was less than 20.
Q
I,
I
§
s
3
s
ri
!
I
I
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
-------
I
§
s
Table 14-5. Per Capita Intake of Total Food
Food Group
N
cons3
N
totalb
PC
(%)
Mean
and Intake of Major Food
SE -
Groups (g/kg-day, edible portion, uncooked)
Percentile
1
5
10
25
50
75
90
95
99
Max
Age Group: Birth to <1 month
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
59
51
0
0
0
5
27
2
58
183
147
1
0
0
44
88
23
176
385
308
44
28
1
284
263
218
357
88
88
88
88
88
88
88
88
88
245
245
245
245
245
245
245
245
245
411
411
411
411
411
411
411
411
411
67.0
58.0
0.0
0.0
0.0
5.7
30.7
2.3
65.9
74.7
60.0
0.4
0.0
0.0
18.0
35.9
9.4
71.8
93.7
74.9
10.7
6.8
0.2
69.1
64.0
53.0
86.9
20
12
-
-
-
_
2
-
6
16
8
-
-
-
0
3
1
4
28
8
0
0
-
1
5
9
4
18
12
-
-
-
_
6
-
5
Age Group:
14
9
-
-
-
1
6
5
4
Age Group:
21
8
1
0
-
2
7
15
3
0
0
-
-
-
_
0
-
0
Ito
0
0
-
-
-
0
0
0
0
3 to
0
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
<3 months
0
0
-
-
-
0
0
0
0
<6 months
0
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
0
0
-
-
-
0
0
0
0
2
0
0
0
-
0
0
0
0
0
0
-
-
-
-
0
-
0
0
0
-
-
-
0
0
0
0
15
0
0
0
-
0
0
0
2
19
13
-
-
-
_
0
-
6
18
4
-
-
-
0
0
0
5
24
8
0
0
-
1
2
2
4
33
21
-
-
-
_
0
-
9
25
15
-
-
-
0
0
0
7
38
12
0
0
-
1
8
13
6
43
25
-
-
-
_
4
-
11
36
20
-
-
-
1
13
0
9
53
16
0
0
-
3
14
29
7
61
43
-
-
-
_
12
-
18
40
26
-
-
-
2
17
7
11
65
20
1
0
-
4
18
37
8
69
49
-
-
-
_
30
-
20
55
34
-
-
-
3
26
19
14
107
38
4
1
-
6
25
72
12
69
49
-
-
-
_
35
-
20
76
43
-
-
-
9
34
43
18
169
73
13
4
-
10
52
110
17
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible portion,
Food Group
N
consa
N
totalb
PC
(%)
Mean
SE
uncooked) (continued)
Percentile
1
5
10
25
50
75
90
95
99 Max
Age Group: 6 to <12 months
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
676
628
500
352
34
653
662
639
661
678
678
678
678
678
678
678
678
678
99.7
92.6
73.7
51.9
5.0
96.3
97.6
94.2
97.5
56
16
2
1
0
4
10
19
3
36
26
3
I
0
3
8
16
2
3
0
0
0
0
0
0
0
0
Age Group: 1 to
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
1,002
999
965
906
188
997
1,000
986
1,002
1,002
1,002
1,002
1,002
1,002
1,002
1,002
1,002
1,002
100
99.7
96.3
90.4
18.8
99.5
99.8
98.4
100
90
43
4
1
0
6
10
22
3
37
30
3
2
1
3
7
18
2
17
0
0
0
0
1
1
0
0.73
Age Group: 2 to
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
994
994
981
943
190
993
994
970
994
994
994
994
994
994
994
994
994
994
100
100
98.7
94.9
19.1
99.9
100
97.6
100
74
28
4
1
0
6
10
20
3
29
18
3
2
1
3
6
17
1
23
0
0
0
0
1
1
0
1
17
0
0
0
0
0
0
0
0
<2 years
38
3
0
0
0
2
2
0
1
<3 years
34
4
1
0
0
2
3
0
1
22
0
0
0
0
1
2
2
1
48
8
1
0
0
2
3
3
2
39
7
1
0
0
3
4
2
1
33
3
0
0
0
2
5
8
2
65
20
2
0
0
4
6
9
2
52
14
2
0
0
4
6
8
2
47
8
1
0
0
3
9
16
3
85
38
3
0
0
5
9
18
3
72
24
4
0
0
5
9
16
3
66
14
4
0
0
5
14
26
4
109
59
6
2
0
7
14
31
4
92
37
6
2
0
7
\3
27
4
99
38
6
2
0
7
20
36
6
137
83
8
4
1
9
19
44
5
\\3
52
8
4
1
9
18
44
5
134
72
8
4
0
9
25
46
7
161
100
10
5
2
11
22
58
6
126
63
9
4
2
10
22
56
5
211 233
165 180
12 30
7 11
2 4
14 26
34 67
84 \38
8 10
207 265
\37 216
14 21
7 15
3 12
15 19
33 61
81 144
8 11
146 194
84 108
14 20
6 \3
4 11
14 28
34 64
71 114
7 9
Q
I,
Ore
-------
I
§
s
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible portion,
Food Group
N
consa
N
totalb
PC
Mean
CT7
1
Age Group: 3
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
4,112
4,112
4,062
3,910
801
4,111
4,111
4,021
4,112
4,112
4,112
4,112
4,112
4,112
4,112
4,112
4,112
4,112
100
100
98.8
95.1
19.5
100
100
97.8
100
61
22
4
1
0
6
10
14
3
24 21
15
3
1
1
3
5
13
1
1
0
0
0
2
2
0
1
5
to <6 years
30
4
1
0
0
2
3
0
1
10
34
7
1
0
0
3
4
1
2
25
44
12
2
0
0
4
6
5
2
Perceri
50
57
20
4
0
0
5
9
11
3
75
73
30
5
1
0
7
12
20
3
uncooked) (continued)
90
91
41
8
3
1
9
16
30
4
95
102
48
9
3
2
10
19
39
5
99 Max
132 239
66 195
13 23
5 13
4 12
14 27
26 60
57 124
6 10
Age Group: 6 to <1 1 years
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
Total Food Intake0
Total Dairy Intake
Total Meat Intake
Total Egg Intake
Total Fish Intake
Total Grain Intake
Total Vegetable Intake
Total Fruit Intake
Total Fat Intake
1,553
1,553
1,533
1,490
258
1,553
1,553
1,515
1,553
975
975
970
930
167
975
975
923
975
1,553
1,553
1,553
1,553
1,553
1,553
1,553
1,553
1,553
975
975
975
975
975
975
975
975
975
100
100
98.7
95.9
16.6
100
100
97.6
100
100
100
99.5
95.4
17.1
100
100
94.7
100
40
15
3
1
0
4
7
7
2
24
7
2
0
0
3
5
4
1
17
10
2
1
1
2
4
7
1
Age Group
11
6
1
1
0
1
3
4
1
10
0
0
0
0
1
1
0
1
11
5
0
0
0
0
1
1
0
0
17
2
0
0
0
2
2
0
1
to <1 6 years
9
0
0
0
0
1
2
0
0
21
4
1
0
0
2
3
0
1
11
1
1
0
0
1
2
0
1
28
7
2
0
0
3
5
2
1
16
3
1
0
0
2
3
1
1
38
13
3
0
0
4
7
5
2
22
6
2
0
0
2
5
3
1
49
20
4
1
0
5
9
10
3
30
10
3
0
0
3
7
6
2
61
27
6
2
1
7
12
16
3
38
15
4
1
1
5
9
10
2
70
33
7
2
1
8
15
21
4
45
20
5
1
1
5
11
14
3
88 122
42 79
10 18
4 8
3 7
11 16
20 50
32 55
5 9
55 82
29 38
7 10
3 7
2 7
7 9
14 31
18 32
4 5
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Total Food Intake0 743 743 100 18 9 5 6 8 12 16 22 30 35 47 115
Total Dairy Intake 742 743 99.9 4400 0 1 3 6 10 12 19 25
Total Meat Intake 730 743 98.3 2200 0 123457 30
Total Egg Intake 703 743 94.6 0000 0 0001123
Total Fish Intake 143 743 19.2 0100 0 0001127
Total Grain Intake 743 743 100 2 1 01 1 1 2 3 4 5 7 12
Total Vegetable Intake 743 743 100 5 3 1 1 2 3 4 6 8 10 15 32
Total Fruit Intake 671 743 90.3 3400 0 0 1 4 7 10 16 29
Total Fat Intake 743 743 100 1 1 0 0 0 1112235
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible portion, uncooked) (continued)
Food Group
cons
, , ib
total
/n/\
(%)
Mean
SE
1
1
1/A
10
,._
25
50
75
90
95
Age Group: 16 to <21 years
Age Group: 20 years and older
Total Food Intake0 9,161 9,161 100 15 7
Total Dairy Intake 9,161 9,143 99.8 3 3
Total Meat Intake 9,161 9,005 98.3 2 1
Total Egg Intake 9,161 8,621 94.1 0 0
Total Fish Intake 9,161 2,648 28.9 0 0
Total Grain Intake 9,161 9,152 100 2 1
Total Vegetable Intake 9,161 9,161 100 4 2
Total Fruit Intake 9,161 8,566 93.5 3 3
Total Fat Intake 9,161 9,161 100 1 0
10
1
1
0
0
1
3
0
1
14
2
2
0
0
2
4
2
1
19
4
2
0
0
2
5
4
1
24
7
3
1
1
3
7
7
1
28
9
4
1
1
4
9
9
2
99
37
14
6
2
2
6
12
15
2
Max
75
41
13
8
8
16
28
52
4
PC
SE
Number of consumers. The number of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human
milk was not included in the total food intake estimates presented here.
Sample size.
Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages,
sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
= Percent consuming.
= Standard error.
= Data not reported where the number of consumers was less than 20.
Q
I,
Source: U.S. EPAanalysis of 1994-1996, 1998 CSFII.
Ore
ft
-------
I
§
s
Table 14-6.
Per Capita Intake
of Total Foods and
Major Food Groups, and Percent
Mid-Range,
Food.
CjTOUp
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Low-End
Consumer
Intake %
Age Group: Birth
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
Mid-Range
Consumer
Intake %
to <1 month (g/day)
64 100.0
39 61.2
0 0.0
0 0.0
0 0.0
0 0.0
5 7.4
0 0.0
19 29.4
and High-End Total Food
High-End
Consumer
Intake
196
109
0
0
0
4
24
8
52
%
100.0
55.4
0.0
0.0
0.0
2.1
12.1
4.1
26.2
Age Group: 1 to <3 months (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
0 0.0
94 100.0
53 56.9
0 0.0
0 0.0
0 0.0
1 1.1
11 12.0
0 0.0
27 28.4
206
63
0
0
0
3
58
27
49
100.0
30.8
0.0
0.0
0.0
1.3
28.4
13.0
23.6
Age Group: 3 to <6 months (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
1 100.0
0 3.0
0 0.0
0 0.0
0 0.0
1 74.5
0 10.9
0 9.9
0 1.3
166 100.0
69 41.9
0 0.2
0 0.0
1 0.3
8 4.9
27 16.3
24 14.6
34 20.4
507
90
4
0
1
14
73
284
36
100.0
17.8
0.8
0.1
0.1
2.8
14.4
56.0
7.2
Food
Group
of Total Food
Intake
Intake for Individuals with
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake
Low-End,
High-End
Consumer
% Intake %
Age Group: Birth to <1 month (g/kg-day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
0
0
0
0
0
0
0
0
0
Age Group
0
0
0
0
0
0
0
0
0
Age Group
0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
lto<3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3to<6
100.0
0.5
0.0
0.0
0.0
85.0
7.4
6.7
0.2
20
14
0
0
0
0
0
0
6
100.0
70.5
0.0
0.0
0.0
0.0
0.1
0.0
29.4
58
35
0
0
0
1
6
0
16
100.0
60.1
0.0
0.0
0.0
2.1
10.0
0.0
27.8
months (g/kg-day)
18
9
0
0
0
0
3
0
5
100.0
51.9
0.0
0.0
0.0
1.1
18.9
0.0
111
44
20
0
0
0
0
7
5
11
100.0
45.4
0.0
0.0
0.0
0.5
16.4
12.3
24.4
months (g/kg-day)
24
9
0
0
0
1
5
4
5
100.0
37.3
0.5
0.0
0.0
4.0
20.8
15.0
21.3
73
13
1
0
0
2
11
40
5
100.0
17.9
0.8
0.1
0.0
3.4
14.5
55.0
7.5
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-6.
Per Capita Intake of Total Foods and
Major Food Groups, and Percent
Mid-Range, and
Food
Group
Low-End
Consumer
Intake %
Mid-Range
Consumer
Intake %
of Total Food
Intake for Individuals with
Low-End,
High-End Total Food Intake (continued)
High-End
Consumer
Intake
%
Age Group: 6 to <12 months (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
124 100.0
33 26.4
3 2.4
0 0.2
1 0.5
11 9.1
30 24.2
30 24.4
14 11.6
Age Group: 1
407 100.0
113 27.8
28 6.9
1 0.3
9 2.2
44 10.8
82 20.1
100 24.6
24 5.8
Age Group: 2
448 100.0
118 26.3
50 11.1
1 0.3
12 2.7
62 13.7
98 21.9
70 15.6
31 6.8
414 100.0
72 17.5
19 4.6
1 0.3
7 1.6
37 8.9
90 21.9
151 36.5
35 8.4
to <2 years (g/day)
998 100.0
487 48.8
46 4.6
3 0.3
16 1.6
63 6.3
101 10.2
238 23.8
38 3.8
to <3 years (g/day)
989 100.0
370 37.4
60 6.1
4 0.4
14 1.4
86 8.7
145 14.6
255 25.8
44 4.4
1,358
770
47
0
8
50
121
314
44
1,859
1,008
66
4
22
81
165
446
61
1,760
698
72
7
24
98
185
609
56
100.0
56.7
3.5
0.0
0.6
3.7
8.9
23.1
3.2
100.0
54.2
3.5
0.2
1.2
4.3
8.9
24.0
3.3
100.0
39.7
4.1
0.4
1.4
5.6
10.5
34.6
3.2
Food.
Cjroup
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Low-End
Consumer
Intake
Age Group:
15
4
0
0
0
2
3
4
2
Mid-Range Hi§
Consumer
;h-End
Consumer
% Intake % Intake %
6 to <12
100.0
25.4
2.3
0.2
0.9
10.7
21.9
25.9
11.4
Age Group: 1 to <2
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
35
10
3
0
1
4
7
8
2
100.0
29.5
7.5
0.4
2.1
10.9
18.6
23.0
6.4
Age Group: 2 to <3
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
32
8
4
0
1
4
7
5
2
100.0
24.8
11.2
0.4
3.6
13.8
22.0
16.2
7.1
months (g/kg-day)
47
6
2
0
1
4
10
19
4
years
85
41
4
1
1
5
10
19
3
years
72
26
4
0
1
6
10
21
3
100.0
13.8
4.9
0.2
1.5
9.1
22.4
40.0
7.5
(g/kg-day)
100.0
48.1
4.7
0.5
1.4
6.0
11.9
22.8
3.8
(g/kg-day)
100.0
36.3
5.3
0.2
1.7
8.0
13.3
29.8
3.9
144
77
5
0
1
5
14
37
5
167
94
5
0
2
7
13
40
5
129
54
5
0
2
7
13
42
4
100.0
53.1
3.4
0.0
0.8
3.6
9.8
25.8
3.2
100.0
56.1
3.2
0.2
0.9
4.3
7.8
24.0
3.2
100.0
42.2
3.8
0.3
1.3
5.6
10.0
32.9
3.2
Q
I,
X)
-------
oo
I
§
s
Table 14-6.
Per Capita Intake of Total
Foods and
Major Food Groups, and Percent
Mid-Range, and
Food
CjTOUp
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Low-End
Consumer
Intake %
Age Group: 3
527 100.0
144 27.3
53 10.0
3 0.6
11 2.0
76 14.4
117 22.3
76 14.4
34 6.5
Age Group: 6
565 100.0
147 26.1
65 11.4
2 0.3
10 1.7
89 15.8
136 24.1
66 11.6
39 6.8
Age Group: 1 1
513 100.0
92 17.9
71 13.9
4 0.8
10 1.9
84 16.3
162 31.6
42 8.2
40 7.8
Mid-Range
Consumer
Intake
%
of Total Food
Intake for Individuals with
Low-End,
High-End Total Food Intake (continued)
High-End
Consumer
Intake
%
to <6 years (g/day)
1,020
378
72
5
15
103
163
216
50
100.0
37.0
7.0
0.5
1.5
10.1
16.0
21.2
4.9
1,817
728
94
9
24
132
233
509
68
100.0
40.1
5.2
0.5
1.3
7.3
12.8
28.0
3.7
to
-------
5
1=
Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Food Intake (continued)
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
High-End
Consumer
Intake
%
Age Group: 16 to <21 years (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
438
56
61
7
8
67
Total Vegetables 148
Total Fruits 48
Total Fatsb 33
100.0
12.8
14.0
1.5
1.9
15.2
33.8
11.0
7.6
1,060 100.0
219 20.7
141 13.3
11 1.1
17 1.6
138 13.0
312 29.4
138 13.1
72 6.8
2,590
759
272
14
29
241
620
487
136
100.0
29.3
10.5
0.5
1.1
9.3
23.9
18.8
5.3
Age Group: 20 years and older (g/day)
Total Foodsa
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
451
55
74
7
15
69
Total Vegetables 147
Total Fruits 40
Total Fatsb 34
100.0
12.1
16.5
1.6
3.2
15.3
32.6
8.9
7.6
1,030 100.0
188 18.3
128 12.5
13 1.2
23 2.3
130 12.7
291 28.4
174 17.0
60 5.9
2,140
520
210
25
34
230
516
466
105
100.0
24.3
9.8
1.2
1.6
10.8
24.2
21.8
4.9
Food
Group
Low-End Mid-Range
Consumer Consumer
Intake
% Intake %
High-End
Consumer
Intake
%
Age Group: 16 to <21 years (g/kg-day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foodsa
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
6
1
1
0
0
1
2
1
1
Age Group:
6
1
1
0
0
1
2
0
0
100.0 16
12.2 4
15.6 2
1.7 0
1.8 0
14.8 2
34.0 5
10.2 2
8.1 1
100.0
23.8
11.5
1.0
1.6
13.1
30.0
10.9
7.1
38
10
4
0
0
4
10
8
2
100.0
27.4
10.0
0.5
1.1
9.9
25.3
19.7
5.0
20 years and older (g/kg-day)
100.0 14
12.5 3
17.3 2
1.6 0
3.5 0
15.6 2
32.1 4
7.9 2
7.7 1
100.0
19.4
12.2
1.4
2.3
13.1
28.9
14.9
6.1
30
7
2
0
0
3
7
7
1
100.0
24.9
8.2
0.9
1.5
10.1
23.5
23.6
4.6
a Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: U.S.
EPA analysis of 1994-1996
, 1998CSFII.
Q
I,
Ore
-------
*l
I
§
s
Table 14-7.
Food
Group
Per Capita Intake of Total
Low-End
Consumer
Intake %
Foods" and Major Food Groups, and Percent
Mid-Range, and High-End Total Meat
Mid-Range
Consumer
Intake
%
High-End
Consumer
Intake %
Age Group: Birth to <1 month (g/day)°
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
67 100.0
41 61.5
0 0.0
0 0.0
0 0.0
0 0.7
5 7.7
1 1.3
19 28.3
Age Group: 1 to <3
79 100.0
37 46.4
0 0.0
0 0.0
0 0.0
1 1.5
15 18.6
4 5.2
21 26.4
Age Group: 3 to <6
181 100.0
55 30.1
0 0.0
0 0.0
0 0.1
7 3.7
31 17.0
59 32.9
28 15.3
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
months (g/day)d
_
-
-
-
-
-
_
-
-
-
-
-
149 100.0
103 68.9
1 0.7
0 0.0
0 0.0
0 0.1
3 2.1
0 0.0
42 28.2
months (g/day)e
-
-
-
-
-
-
-
-
-
-
316 100.0
62 19.7
16 4.9
0 0.1
1 0.5
16 5.0
56 17.9
133 42.3
28 8.9
Food
Group
of Total Food Intake for Individuals with
Intake
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake
Low-End,
High-End
Consumer
% Intake %
Age Group: Birth to <1 month (g/kg-day)°
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
20
12
0
0
0
0
2
0
6
Age Group:
16
8
0
0
0
0
3
1
4
Age Group:
26
8
0
0
0
1
4
8
4
100.0
61.6
0.0
0.0
0.0
0.7
7.7
1.1
28.4
lto<3
100.0
47.9
0.0
0.0
0.0
1.4
16.8
5.6
26.5
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
months (g/kg-day)d
_
-
-
-
-
-
_
-
-
-
-
-
47
32
0
0
0
0
1
0
13
100.0
68.9
0.7
0.0
0.0
0.1
2.1
0.0
28.2
3 to <6 months (g/kg-day)e
100.0
30.6
0.0
0.0
0.0
3.7
16.9
32.2
15.6
-
-
-
-
-
-
-
-
-
-
41
8
2
0
0
2
7
17
4
100.0
20.5
4.9
0.1
0.3
4.8
17.6
41.7
9.2
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-7.
Per Capita
Intake of Total Foods and
Major Food Groups, and Percent
of Total Food Intake
for Individuals with
Low-End,
Mid-Range, and High-End Total Meat Intake (continued)
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
High-End
Consumer
Intake %
Age Group: 6 to <12 months (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
347
80
0
0
2
24
69
143
27
100.0
23.0
0.0
0.0
0.5
6.8
19.8
41.3
7.7
Age Group: 1 to
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
921
464
2
3
8
56
97
250
30
100.0
50.4
0.2
0.3
0.9
6.1
10.5
27.2
3.3
Age Group: 2 to
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
950
426
7
4
12
73
104
279
29
100.0
44.9
0.7
0.5
1.3
7.7
10.9
29.4
3.0
466 100.0
108 23.2
14 2.9
0 0.1
3 0.6
29 6.2
116 24.8
162 34.8
31 6.7
<2 years (g/day)
992 100.0
483 48.7
39 4.0
2 0.2
14 1.5
64 6.5
113 11.3
228 23.0
38 3.8
<3 years (g/day)
947 100.0
373 39.3
52 5.4
4 0.5
18 1.9
76 8.1
146 15.4
226 23.8
40 4.2
922 100.0
384 41.6
85 9.3
0 0.0
11 1.2
51 5.6
135 14.7
216 23.4
43 4.6
1,229 100.0
460 37.4
128 10.4
6 0.5
24 1.9
78 6.4
189 15.4
290 23.6
57 4.6
1,131 100.0
374 33.0
148 13.1
2 0.2
21 1.9
90 8.0
202 17.9
232 20.5
62 5.5
Food.
(jToup
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Low-End
Consumer
Intake
Age Group:
40
9
0
0
0
3
8
17
2
%
6 to <12
100.0
22.6
0.0
0.0
0.5
6.6
19.7
41.9
7.8
Age Group: 1 to <2
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
82
41
0
0
1
5
9
22
3
100.0
49.9
0.2
0.3
0.8
6.1
11.1
27.3
3.3
Age Group: 2 to <3
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
71
31
1
0
1
6
8
21
2
100.0
44.2
0.7
0.5
1.3
7.8
11.1
29.6
3.1
Mid-Range
Consumer
Intake
High-End
Consumer
% Intake %
months (g/kg-day)
48
11
1
0
0
3
10
17
3
years (§
90
46
3
0
1
6
10
21
3
100.0
23.9
3.0
0.1
1.0
6.0
21.9
36.5
7.1
;/kg-day)
100.0
50.5
3.8
0.3
1.4
6.1
10.8
22.7
3.8
99
41
9
0
1
6
15
23
5
108
43
11
0
2
7
16
22
5
100.0
41.1
9.3
0.0
0.9
5.8
15.4
23.1
4.6
100.0
40.1
10.0
0.5
1.9
6.9
15.1
20.8
4.7
years (g/kg-day)
68
26
4
0
1
6
10
18
3
100.0
37.7
5.5
0.3
1.3
8.3
15.1
26.7
4.0
83
27
10
0
2
7
14
19
4
100.0
32.3
12.4
0.2
1.8
8.1
16.8
23.1
5.2
Q
I,
I
§
a
3
S
ri
!
I
I
-------
^S3
> *Q
I
§
s
Table 14-7.
Food
Group
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Per Capita Intake of Total
Low-End
Consumer
Intake %
Age Group: 3 to
991 100.0
419 42.3
10 1.0
7 0.7
10 1.0
98 9.9
128 13.0
257 25.9
35 3.6
Age Group: 6 to
1,028 100.0
424 41.3
11 1.1
6 0.6
13 1.3
121 11.8
164 16.0
214 20.8
40 3.9
Age Group: 11 to
1,043 100.0
342 32.8
17 1.6
13 1.3
17 1.6
116 11.1
227 21.7
238 22.8
44 4.2
Foods and Major Food Groups, and Percent of Total Food Intake
Mid-Range, and High-End Total Meat Intake (continued)
Mid-Range
Consumer
Intake
%
High-End
Consumer
Intake
%
<6 years (g/day)
1,037
376
65
6
16
101
170
238
48
100.0
36.3
6.3
0.5
1.5
9.8
16.4
22.9
4.7
1,246
389
176
4
24
117
217
243
73
100.0
31.2
14.1
0.3
1.9
9.4
17.4
19.5
5.9
<11 years (g/day)
1,087
386
79
5
15
117
212
191
59
100.0
35.5
7.3
0.5
1.4
10.7
19.5
17.6
5.4
1.300
382
206
4
17
136
270
198
81
100.0
29.4
15.8
0.3
1.3
10.4
20.7
15.2
6.2
<16 years (g/day)
1,194
377
101
7
13
144
260
202
67
100.0
31.6
8.5
0.6
1.1
12.1
21.8
16.9
5.6
1,606
435
268
7
21
159
404
204
106
100.0
27.1
16.7
0.4
1.3
9.9
25.2
12.7
6.6
Food
Group
Low-End
Consumer
Intake %
for Individuals with
Mid-Range
Consumer
Intake
Age Group: 3 to <6 years (^
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
57 100.0
24 42.1
1 1.0
0 0.6
1 1.0
6 9.9
7 13.0
15 26.1
2 3.6
Age Group: 6 to
-------
3
1=
Table 14-1. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Meat Intake (continued)
-p , Low-End Mid-Range High-End
„ Consumer Consumer Consumer
Up Intake % Intake % Intake %
Age Group: 16 to <21 years (g/day)
Total Foods3 922 100.0 1,084 100.0 1,957 100.0
Total Dairy 307 33.3 280 25.8 403 20.6
Total Meats 12 1.3 115 10.6 385 19.7
Total Fish 20 2.1 9 0.9 12 0.6
Total Eggs 14 1.5 15 1.4 31 1.6
Total Grains 131 14.2 147 13.6 231 11.8
Total Vegetables 215 23.3 287 26.5 532 27.2
Total Fruits 151 16.4 147 13.5 226 11.6
Total Fatsb 42 4.5 73 6.7 139 7.1
Age Group: 20 years and older (g/day)
Total Foods3 943 100.0 1,030 100.0 1,560 100.0
Total Dairy 213 22.6 211 20.4 254 16.3
Total Meats 15 1.6 111 10.8 338 21.7
Total Fish 25 2.6 12 1.2 13 0.8
Total Eggs 17 1.8 21 2.0 33 2.1
Total Grains 113 12.0 124 12.0 196 12.5
Total Vegetables 259 27.4 282 27.2 446 28.5
Total Fruits 234 24.9 192 18.6 165 10.5
Total Fatsb 38 4.1 59 5.7 115 7.4
Food
Low-End Mid-Range High-End
Consumer Consumer Consumer
Intake % Intake % Intake %
Age Group: 16 to <21 years (g/kg-day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
15 100.0 18 100.0 28 100.0
4 30.3 4 24.0 5 18.1
0 1.3 2 9.6 5 19.8
0 2.2 0 1.0 0 0.4
0 1.4 0 1.9 0 1.6
2 14.5 2 12.8 3 12.3
4 24.6 5 27.5 8 28.9
3 17.8 3 15.7 3 12.4
1 4.6 1 6.2 2 6.5
Age Group: 20 years and older (g/kg-day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
14 100.0 15 100.0 21 100.0
3 22.6 3 20.7 3 15.9
0 1.6 2 10.3 4 21.3
0 2.6 0 1.3 0 0.9
0 1.8 0 2.1 0 2.0
2 11.9 2 12.2 3 12.2
4 27.3 4 27.6 6 28.2
3 25.3 3 18.2 3 12.3
1 4.0 1 5.5 1 7.0
a Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
0 All individuals in this sample group consumed 0 g/day of meat. Therefore, results are reported in the low-end decile.
d Only one individual in this sample group consumed more than 0 g/day of meat. This result is reported in the high-end decile. All other samples are reported in
the low-end decile.
e All individuals in this sample group below the 89th percentile consumed 0 g/day of meat. Therefore, only high-end and low-end consumer groups are reported.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
Q
I,
I
§
s
3
s
ri
!
I
I
-------
*l
I
§
s
Table 14-8.
Per Capita
Intake
of Total Foods and
Major Food Groups, and Percent of Total Food
Mid-Range, and
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
Hi
High-End Total Meat and
gh-End
Consumer
Intake
%
Age Group: Birth to <1 month (g/day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
12
0
0
0
0
0
8
0
3
100.0
0.0
0.0
0.0
0.0
0.3
66.1
0.0
27.1
Age Group: 1 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
36
0
0
0
0
0
21
2
10
100.0
0.0
0.0
0.0
0.0
0.9
58.8
4.3
26.7
Age Group: 3 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
121
0
0
0
0
5
44
52
15
100.0
0.0
0.0
0.0
0.0
4.5
36.4
42.9
12.3
60 100.0
40 67.3
0 0.0
0 0.0
0 0.0
0 0.0
2 3.4
0 0.0
18 29.2
<3 months (g/day)
84 100.0
19 22.4
0 0.0
0 0.0
0 0.0
1 1.2
42 50.7
0 0.0
21 25.4
<6 months (g/day)
204 100.0
60 29.7
0 0.3
0 0.0
0 0.1
7 3.2
29 14.5
80 39.0
27 13.2
185
127
0
0
0
4
1
0
52
166
109
0
0
0
1
4
6
45
334
159
5
0
1
12
27
74
54
100.0
69.0
0.0
0.0
0.0
2.2
0.4
0.0
28.4
100.0
65.6
0.0
0.0
0.0
0.8
2.7
3.7
27.2
100.0
47.7
1.4
0.1
0.2
3.7
8.0
22.3
16.3
Food
Group
Dairy Intake
Intake for Individuals with
Low-End Mid-Range
Consumer Consumer
Intake
% Intake
Low-End,
High-End
Consumer
% Intake %
Age Group: Birth to <1 month (g/kg-day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
4
0
0
0
0
0
2
0
1
Age Group
7
0
0
0
0
0
4
0
2
Age Group
17
0
0
0
0
1
6
7
2
100.0 18
0.0 12
0.0 0
0.0 0
0.0 0
0.2 0
64.4 1
0.0 0
27.5 5
100.0
67.1
0.0
0.0
0.0
0.0
3.7
0.0
29.2
56
39
0
0
0
1
0
0
16
100.0
69.0
0.0
0.0
0.0
2.1
0.5
0.0
28.4
1 to <3 months (g/kg-day)
100.0 14
0.0 3
0.0 0
0.0 0
0.0 0
0.8 0
57.8 7
5.4 0
26.4 4
100.0
24.0
0.0
0.0
0.0
2.0
48.7
0.0
25.0
41
26
0
0
0
0
0
3
11
100.0
64.1
0.0
0.0
0.0
0.6
1.1
7.7
26.5
3 to <6 months (g/kg-day)
100.0 30
0.0 8
0.0 0
0.0 0
0.0 0
4.5 1
37.1 3
41.7 14
12.6 3
100.0
26.5
0.6
0.0
0.3
3.7
11.2
46.0
11.4
45
24
1
0
0
2
2
8
8
100.0
53.4
1.3
0.1
0.1
3.6
5.3
17.3
18.7
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-8.
Per Capita Intake of Total Foods
and Major Food Groups, and Percent
Mid-Range, and High-End Total Meat and Dairy
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
ffij
'h-End
Consumer
Intake
%
Age Group: 6 to <12 months (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
253
1
1
0
3
22
95
110
17
100.0
0.5
0.3
0.0
1.0
8.5
37.7
43.4
6.7
Age Group: 1
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
569
46
30
2
12
54
128
264
25
100.0
8.0
5.2
0.4
2.0
9.5
22.5
46.4
4.5
Age Group: 2
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
641
57
45
4
21
75
155
240
32
100.0
9.0
6.9
0.6
3.2
11.8
24.1
37.5
5.0
403 100.0
71 17.6
17 4.1
1 0.4
3 0.7
32 8.0
82 20.3
166 41.1
32 8.0
to <2 years (g/day)
1,014 100.0
456 45.0
43 4.2
2 0.2
13 1.3
64 6.3
114 11.3
278 27.4
36 3.6
to <3 years (g/day)
981 100.0
348 35.5
59 6.0
3 0.3
18 1.9
86 8.7
148 15.1
264 26.9
42 4.3
1,284
827
45
0
7
45
108
209
41
1,687
1,165
52
3
19
65
111
209
59
1,546
883
60
4
20
86
143
286
55
100.0
64.5
3.5
0.0
0.5
3.5
8.4
16.3
3.2
100.0
69.0
3.1
0.2
1.1
3.8
6.6
12.4
3.5
100.0
57.1
3.9
0.3
1.3
5.6
9.2
18.5
3.6
Food
Group
of Total
Food Intake for Individuals with Low-End,
Intake (continued)
Low-End
Consumer
Intake
%
Age Group: 6 to <12
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
29
0
0
0
0
2
11
13
2
100.0
0.4
0.3
0.0
1.1
8.0
38.2
43.4
6.7
Age Group: 1 to <2
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
51
4
3
0
1
5
11
24
2
100.0
7.7
5.5
0.2
2.1
9.5
22.2
46.6
4.5
Age Group: 2 to <3
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
46
4
3
0
1
5
11
18
2
100.0
8.2
7.4
0.4
3.2
11.6
23.6
38.7
5.2
Mid-Range
Consumer
Intake %
months (g/kg-day)
43 100.0
8 18.0
2 4.7
0 0.3
0 0.9
3 7.1
9 20.0
17 40.4
4 8.3
years (g/kg-day)
82 100.0
38 45.6
4 5.3
0 0.3
1 1.6
6 7.2
11 13.0
19 22.7
3 3.8
years (g/kg-day)
73 100.0
24 32.6
5 6.5
0 0.3
1 1.6
6 8.7
11 14.9
22 29.9
3 4.3
High-End
Consumer
Intake
135
87
5
0
1
5
12
22
4
155
106
4
0
1
6
11
21
5
114
67
4
0
2
7
11
19
4
%
100.0
64.2
3.3
0.0
0.5
3.5
8.6
16.6
3.2
100.0
68.2
2.8
0.1
0.9
3.7
6.9
13.7
3.4
100.0
58.3
3.8
0.2
1.3
5.7
9.5
16.6
3.7
Q
I,
ft
-------
^S3
> *Q
I
§
s
ft1
s
Table 14-8.
Food
Group
Per Capita Intake of Total Foods and Major Food Groups, and Percent
Mid-Range, and High-End Total Meat and Dairy
Low-End
Consumer
Intake
%
Age Group: 3
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
702
75
52
5
15
85
159
258
35
100.0
10.7
7.5
0.7
2.2
12.0
22.6
36.7
5.0
Age Group: 6
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
725
76
66
6
16
101
202
198
43
100.0
10.5
9.2
0.8
2.3
13.9
27.9
27.3
6.0
Age Group: 11
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
727
38
58
10
16
103
234
213
42
100.0
5.2
8.0
1.4
2.2
14.2
32.2
29.3
5.8
Mid-Range
Consumer
Intake %
to <6 years (g/day)
1,043 100.0
352 33.8
79 7.6
5 0.5
16 1.5
107 10.2
167 16.0
251 24.1
51 4.9
to <11 years (g/day)
1,061 100.0
366 34.5
91 8.6
7 0.7
17 1.6
116 10.9
205 19.4
178 16.7
56 5.3
to <16 years (g/day)
1,111 100.0
299 26.9
118 10.6
11 1.0
22 2.0
137 12.4
265 23.9
176 15.8
66 6.0
High-End
Consumer
Intake
1,646
878
88
5
19
121
191
259
67
1,727
883
105
6
18
151
245
221
73
2,045
1,004
161
12
26
181
332
204
104
%
100.0
53.3
5.4
0.3
1.2
7.3
11.6
15.8
4.1
100.0
51.1
6.1
0.3
1.1
8.7
14.2
12.8
4.2
100.0
49.1
7.9
0.6
1.3
8.9
16.2
10.0
5.1
Food
Group
of Total Food Intake
Intake (continued)
Low-End
Consumer
for Individuals with Low-End,
Mid-Range
Consumer
Intake % Intake
Age Group: 3 to <6 years (g
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
39 100.0
4 10.8
3 7.6
0 0.8
1 2.2
5 12.0
9 22.7
14 36.1
2 5.1
Age Group: 6 to
-------
5
1=
Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Meat and Dairy Intake (continued)
„ , Low-End
Food „
^ Consumer
Mid-Range
Consumer
Gr°Up Intake % Intake
High-End
Consumer
% Intake %
Age Group: 16 to <21 years (g/day)
Total Foods3 610
Total Dairy 22
Total Meats 42
Total Fish 12
Total Eggs 13
Total Grains 87
Total Vegetables 202
Total Fruits 177
Total Fatsb 34
100.0
3.5
6.8
1.9
2.2
14.3
33.1
29.1
5.6
Age Group: 20 years
Total Foods3 679
Total Dairy 28
Total Meats 45
Total Fish 21
Total Eggs 19
Total Grains 99
Total Vegetables 236
Total Fruits 179
Total Fatsb 34
100.0
4.1
6.6
3.1
2.8
14.6
34.7
26.3
5.0
1,017
204
128
12
19
140
305
133
68
100.0
20.1
12.6
1.2
1.8
13.8
29.9
13.1
6.6
2,379
923
256
8
28
233
492
282
127
100.0
38.8
10.8
0.3
1.2
9.8
20.7
11.9
5.3
and older (g/day)
1,050
157
136
14
22
131
319
190
65
100.0
14.9
12.9
1.3
2.1
12.5
30.3
18.1
6.1
1,860
696
208
17
29
185
385
215
100
100.0
37.5
11.2
0.9
1.5
10.0
20.7
11.6
5.4
Food
Group —
Low-End Mid-Range
Consumer Consumer
Intake
% Intake
High-End
Consumer
% Intake %
Age Group: 16 to <21 years (g/kg-day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
9
0
1
0
0
1
3
3
1
Age Group:
9
0
1
0
0
1
3
2
0
100.0 15
3.8 3
6.8 2
1.8 0
2.0 0
14.6 2
34.0 5
28.1 2
5.5 1
20 years and older (£
100.0 14
3.9 2
6.8 2
3.1 0
2.8 0
14.5 2
35.0 4
26.1 3
5.1 1
100.0
19.1
13.4
0.9
1.8
14.3
30.4
12.2
6.8
5/kg-day)
100.0
15.2
12.7
1.4
2.1
12.9
29.9
18.1
6.0
34
13
4
0
0
3
7
4
2
26
10
3
0
0
3
5
3
1
100.0
39.1
10.8
0.3
1.1
10.1
20.8
11.2
5.4
100.0
37.6
10.4
1.0
1.5
9.8
20.3
13.1
5.1
3 Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
Q
I,
X)
-------
-------
5
1=
Table 14-9.
Per Capita
Intake of Total Foods and
Major
Food Groups, and Percent of Total Food Intake for Individuals
with Low-End,
Mid-Range, and High-End Total Fish Intake (continued)
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
Hig
h-End
Consumer
Intake
%
Age Group: 6 to <12 months (g/day)e
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
799
334
38
0
11
47
101
227
37
100.0
41.8
4.7
0.0
1.4
5.9
12.6
28.4
4.7
Age Group: 1 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
1,032
496
46
0
14
65
118
247
39
100.0
48.1
4.5
0.0
1.4
6.3
11.4
24.0
3.8
Age Group: 2 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
1,015
381
62
0
18
81
144
276
42
100.0
37.6
6.1
0.0
1.8
7.9
14.2
27.2
4.2
-
-
-
-
-
-
-
-
-
<2 years (g/day)e
_
-
-
-
-
-
-
-
-
<3 years (g/day)e
-
-
-
-
-
-
-
-
-
770
287
46
7
14
66
117
194
36
1,139
461
56
26
19
76
151
300
43
1,107
424
53
31
17
84
142
304
43
100.0
37.3
6.0
0.9
1.9
8.6
15.3
25.2
4.7
100.0
40.5
4.9
2.3
1.7
6.7
13.2
26.3
3.8
100.0
38.3
4.8
2.8
1.6
7.6
12.8
27.4
3.9
Food
Cjroup
Low-End
Consumer
Intake
%
Age Group: 6 to <12
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
81
34
4
0
1
5
10
23
4
Age Group
90
43
4
0
1
6
10
22
3
Age Group
73
28
4
0
1
6
10
20
3
100.0
41.8
4.7
0.0
1.4
5.9
12.6
28.4
4.7
: 1 to <2
100.0
48.2
4.4
0.0
1.3
6.2
11.4
24.0
3.8
: 2 to <3
100.0
37.9
6.0
0.0
1.7
7.9
14.1
27.0
4.2
Mid-Range
Consumer
Intake %
months (g/kg-day)
-
-
-
-
-
-
-
-
-
years (g/kg-day )e
_
-
-
-
-
-
-
-
-
years (g/kg-day )e
-
-
-
-
-
-
-
-
-
Hi{
Jh-End
Consumer
Intake
e
74
27
4
1
1
6
12
19
3
98
41
5
2
2
7
12
25
4
82
31
4
2
1
6
10
23
3
%
100.0
37.1
6.0
0.9
2.0
8.4
15.6
25.2
4.7
100.0
42.4
4.8
2.2
1.6
6.7
12.3
25.5
3.8
100.0
37.6
4.6
2.9
1.5
7.5
12.7
28.5
3.9
Q
I,
I
§
a
3
S
ri
!
I
I
-------
I
§
s
Table 14-9.
Food
Group
Per Capita
Intake of Total Foods and Major Food Groups, and Percent of Total Food
Mid-Range, and High-End Total Fish Intake (continued)
Low-End Mid-Range
Consumer Consumer
Intake
% Intake %
High-End
Consumer
Intake %
Age Group: 3 to <6 years (g/day)e
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsc
1,053
390
76
0
16
101
168
237
50
100.0
37.1
7.2
0.0
1.5
9.6
15.9
22.5
4.8
1,156 100.0
399 34.5
62 5.3
43 3.7
17 1.4
103 8.9
193 16.7
273 23.6
50 4.3
Age Group: 6 to <11 years (g/day)e
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsc
1,109
408
89
0
15
119
208
190
58
100.0
36.8
8.0
0.0
1.3
10.7
18.8
17.1
5.2
1,23 100.0
4
430 34.8
76 6.2
51 4.1
22 1.8
126 10.2
233 18.9
218 17.7
61 4.9
Food
Group
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsc
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsc
Intake for Individuals
Low-End Mid-Range
Consumer Consumer
Intake
Age Group
% Intake %
3 to <6 years (g/kg-day)e
60 100.0
22
4
0
1
6
9
14
3
Age Group:
40
15
3
0
1
4
7
7
2
37.1
7.1
0.0
1.5
9.5
15.8
22.7
4.7
6 to <11 years (g/kg-day)e
100.0
37.0
7.9
0.0
1.3
10.7
18.5
17.3
5.2
with Low-End,
High-End
Consumer
Intake
66
22
3
2
1
6
11
16
3
44
16
3
2
1
4
8
8
2
%
100.0
33.9
5.3
3.7
1.6
9.0
16.9
23.8
4.3
100.0
35.6
6.1
4.1
1.6
10.1
18.4
17.5
4.9
s
I
i
ft1
s
I,
I
ft
-------
5
1=
Table 14-9.
Food
Group
Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food
Mid-Range, and High-End Total Fish Intake (continued)
Low-End Mid-Range
Consumer Consumer
Intake % Intake %
High-End
Consumer
Intake
%
Age Group: 11 to <16 years (g/day)e
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
1,197 100.0
372 31.1
117 9.8
0 0.0 -
17 1.4
135 11.3
277 23.1
190 15.8
69 5.8
1,378
397
104
72
28
146
310
226
76
100.0
28.8
7.5
5.2
2.0
10.6
22.5
16.4
5.5
Age Group: 16 to <21 years (g/day)e
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
1,171 100.0
288 24.6
143 12.2
0 0.0 -
20 1.7
146 12.5
325 27.8
160 13.7
75 6.4
1,339
261
139
86
21
162
357
219
80
100.0
19.5
10.4
6.5
1.6
12.1
26.6
16.3
6.0
Food
Group
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Intake for Individuals
Low-End Mid-Range
Consumer Consumer
Intake
Age Group:
% Intake %
11 to <16 years (g/kg-day)e
24 100.0
7
2
0
0
3
5
4
1
Age Group:
18
4
2
0
0
2
5
2
1
31.1
9.7
0.0
1.4
11.3
22.9
16.2
5.7
16 to <21 years (g/kg-day)e
100.0
24.5
11.9
0.0
1.7
12.5
27.9
13.9
6.4
with Low-End,
High-End
Consumer
Intake
28
9
2
1
1
3
6
5
1
19
4
2
1
0
2
5
3
1
%
100.0
30.9
6.9
4.9
1.9
10.5
21.1
17.1
5.2
100.0
20.3
9.4
6.7
1.6
12.0
26.0
16.9
5.9
Q
I,
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§
a
3
S
ri
!
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Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Fish Intake (continued)
-p , Low-End Mid-Range High-End
„ Consumer Consumer Consumer
Up Intake % Intake % Intake %
Age Group: 20 years and older (g/day)
Total Foods" 1,040 100.0 1,060 100.0 1,340 100.0
Total Dairy 207 20.0 205 19.3 250 18.7
Total Meats 126 12.1 143 13.4 121 9.1
Total Fish 0 0.0 0 0.0 102 7.7
Total Eggs 22 2.1 24 2.2 27 2.0
Total Grains 134 12.9 133 12.5 152 11.4
Total Vegetables 303 29.2 300 28.3 348 26.0
Total Fruits 165 15.9 180 16.9 238 17.8
Total Fatsc 62 6.0 64 6.0 74 5.5
-p , Low-End Mid-Range High-End
„ Consumer Consumer Consumer
Up Intake % Intake % Intake %
Age Group: 20 years and older (g/kg-day)
Total Foods" 14 100.0 15 100.0 19 100.0
Total Dairy 3 20.2 3 19.1 4 19.0
Total Meats 2 11.9 2 12.7 2 8.5
Total Fish 0 0.0 0 0.0 1 7.6
Total Eggs 0 2.0 0 2.0 0 1.9
Total Grains 2 13.0 2 12.3 2 11.2
Total Vegetables 4 29.1 4 28.3 5 26.0
Total Fruits 2 16.1 3 18.2 4 18.7
Total Fatsc 1 5.9 1 5.8 1 5.2
a All individuals in this sample group consumed 0 g/day of fish. Therefore, only low-end consumers are reported.
b Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
0 Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
d Only one individual in this sample group consumed more than 0 g/day of fish. Therefore, this sample is reported in the high-end consumer group and all other
samples are placed in the low-end consumer group.
e All individuals in this sample group below the 80 percentile consumed 0 g/day of fish. Therefore, only high-end and low-end consumer groups are reported.
Source: U.S. EPA analysis of 1994-1996, 1998 CSFII.
I
§
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5
1=
Table 14-10.
Food
Group
Per Capita Intake of Total Foods and
Mid-Range,
Low-End
Consumer
Intake %
Mid-Range
Consumer
Intake
%
Major Food Groups, and Percent of Total Food Intake for Individuals with
and High-End Total Fruit and Vegetable Intake
High-End
Consumer
Intake
%
Age Group: Birth to <1 month (g/day)a
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
49 100.0
34 69.7
0 0.0
0 0.0
0 0.0
1 1.2
0 0.0
0 0.0
14 29.1
Age Group: 1 to
49 100.0
34 69.2
0 0.0
0 0.0
0 0.0
1 1.9
0 0.0
0 0.0
14 28.9
Age Group: 3 to
69 100.0
47 68.0
0 0.0
0 0.0
0 0.0
2 3.3
0 0.0
0 0.0
20 28.4
-
-
-
-
-
-
-
-
-
-
-
-
101
21
0
0
0
0.21
44
8
25
100.0
21.1
0.0
0.0
0.0
0.2
43.3
7.6
24.8
<3 months (g/day)a
_
-
_
-
-
-
-
_
-
_
-
-
-
-
171
16
0
0
0
2
89
18
40
100.0
9.5
0.0
0.0
0.0
1.0
52.0
10.2
23.4
<6 months (g/day)
144
51
2
0
1
10
24
29
25
100.0
35.6
1.3
0.3
0.4
6.7
16.6
19.9
17.7
495
49
4
0
0
12
88
311
27
100.0
9.9
0.8
0.0
0.0
2.4
17.7
62.8
5.4
Food
Group
Low-End Mid-Range
Consumer Consumer
Intake
% Intake
Low-End,
High-End
Consumer
% Intake %
Age Group: Birth to <1 month (g/kg-day)a
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
14
10
0
0
0
0
0
0
4
Age Group:
11
7
0
0
0
0
0
0
3
Age Group
11
7
0
0
0
0
0
0
3
100.0
69.6
0.0
0.0
0.0
1.3
0.0
0.0
29.1
-
-
-
-
-
-
29
6
0
0
0
0
13
2
7
100.0
19.4
0.0
0.0
0.0
0.2
44.8
6.4
25.4
1 to <3 months (g/kg-day)a
100.0
69.4
0.0
0.0
0.0
1.7
0.0
0.0
29.0
_
-
_
-
-
-
-
35
4
0
0
0
0
16
5
8
100.0
11.5
0.0
0.0
0.0
1.1
46.8
13.9
111
3 to <6 months (g/kg-day)
100.0 21
68.1 8
0.0 0
0.0 0
0.0 0
3.2 1
0.0 3
0.0 4
28.5 4
100.0
37.2
1.5
0.3
0.5
6.6
15.1
20.8
16.9
70
7
1
0
0
2
12
44
4
100.0
10.1
0.7
0.0
0.0
2.6
17.7
62.4
5.5
Q
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a
3
S
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!
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§
s
Table 14-10.
Food
Group
Per Capita
Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals
Low-End
Consumer
Intake
%
Mid-Range, and
Mid-Range
Consumer
Intake %
High-End
Total Fruit and Vegetable
High-End
Consumer
Intake
%
Age Group: 6 to <12 months (g/day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsc
189
91
8
1
4
23
18
15
31
100.0
48.3
4.0
0.4
1.9
12.1
9.4
7.7
16.3
Age Group: 1 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
796
578
35
1
8
49
56
26
36
100.0
72.7
4.5
0.1
1.0
6.2
7.1
3.2
4.6
Age Group: 2 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
601
308
53
2
14
72
81
24
38
100.0
51.2
8.8
0.3
2.3
12.0
13.4
4.0
6.3
461 100.0
129 28.0
17 3.6
1 0.2
9 1.9
31 6.8
83 18.1
158 34.3
31 6.8
<2 years (g/day)
1,048 100.0
535 51.0
46 4.4
3 0.3
16 1.5
65 6.2
123 11.7
210 20.1
41 3.9
<3 years (g/day)
942 100.0
352 37.4
59 6.3
4 0.5
18 2.0
80 8.5
141 15.0
237 25.1
40 4.2
951
207
37
0
8
41
160
459
35
1,499
425
62
5
17
77
179
687
39
1,589
384
64
5
20
91
202
765
46
100.0
21.8
3.9
0.0
0.8
4.3
16.8
48.2
3.6
100.0
28.4
4.2
0.4
1.1
5.1
11.9
45.8
2.6
100.0
24.1
4.0
0.3
1.3
5.7
12.7
48.1
2.9
Food
Group
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Intake (continued)
Low-End
Consumer
Intake %
Age Group: 6 to <12
21 100.0
10 48.1
1 3.6
0 0.4
0 1.7
2 11.4
2 9.3
2 8.4
3 16.8
Age Group: 1 to <2
68 100.0
49 71.8
3 4.7
0 0.2
1 1.1
4 6.2
5 7.1
2 3.4
3 4.7
Age Group: 2 to <3
43 100.0
22 51.3
4 8.8
0 0.3
1 2.3
5 12.0
6 13.8
2 3.7
3 6.3
Mid-Range
Consumer
Intake %
with Low-End,
Hi
gh-End
Consumer
Intake
%
months (g/kg-day)
57
19
2
0
1
4
10
18
4
years
88
44
4
0
1
6
11
18
3
years
69
27
4
0
1
6
10
17
3
100.0
33.2
4.3
0.1
1.0
6.5
16.9
30.8
6.6
(g/kg-day)
100.0
49.6
4.5
0.3
1.2
6.9
12.6
20.5
3.7
(g/kg-day)
100.0
39.3
6.0
0.4
1.9
8.6
14.0
24.6
4.1
100
18
4
0
1
5
19
50
4
133
39
5
0
2
7
15
60
4
114
27
4
0
2
7
14
56
3
100.0
17.9
3.8
0.0
0.7
4.6
19.0
49.5
3.9
100.0
29.5
3.6
0.2
1.2
5.2
11.6
45.4
2.7
100.0
23.6
3.8
0.4
1.4
5.7
12.4
49.1
2.9
s
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i
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ft
-------
5
1=
Table 14-10.
Food
Group
Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals
Mid-Range, and
Low-End Mid-Range
Consumer Consumer
Intake % Intake %
High-End Total Fruit and Vegetable
High-End
Consumer
Intake %
Age Group: 3 to <6 years (g/day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
731 100.0 1,014 100.0
388 53.\ 385 38.0
60 8.2 74 7.3
4 0.5 7 0.7
\3 1.7 14 1.4
92 12.5 96 9.4
92 12.5 174 17.1
27 3.6 199 19.6
45 6.1 49 4.9
1,594 100.0
401 25.1
81 5.1
9 0.6
21 \.3
U3 7.1
23\ 14.5
668 41.9
53 3.3
Age Group: 6 to <11 years (g/day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
784 100.0 1,068 100.0
385 49.2 406 38.0
76 9.7 88 8.3
5 0.6 6 0.6
16 2.1 16 1.5
105 13.3 117 11.0
103 13.2 213 19.9
26 3A 144 13.5
48 6.2 59 5.5
1,664 100.0
448 26.9
98 5.9
8 0.5
17 10.
127 7.6
313 18.8
559 33.6
64 3.9
Age Group: 11 to <16 years (g/day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
709 100.0 1,149 100.0
301 42.4 362 31.5
91 12.8 112 9.7
3 0.4 10 0.8
13 1.8 20 1.7
106 15.0 136 11.8
125 17.7 286 24.9
13 1.9 136 11.8
49 6.9 66 5.8
1,911 100.0
395 20.7
146 7.7
14 0.7
24 1.3
165 8.6
458 24.0
597 31.2
87 4.5
Food
Group
Intake (continued)
Low-End Mid-Range
Consumer Consumer
Intake % Intake %
with Low-End,
Hi
gh-End
Consumer
Intake
%
Age Group: 3 to <6 years (g/kg-day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
40 100.0 58 100.0
21 52.7 22 38.2
3 8.6 4 7.0
0 0.4 0 0.6
1 1.6 1 1.4
5 12.4 6 \0.3
5 \3.0 10 16.5
1 3.4 11 19.5
2 6.1 3 4.9
95
25
5
0
1
7
\3
41
3
100.0
25.8
4.8
0.5
1.1
6.8
\3.9
42.5
3.3
Age Group: 6 to <11 years (g/kg-day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
23 100.0 38 100.0
11 47.0 14 37.6
2 10.1 3 8.9
0 0.8 0 0.4
1 2.3 I 1.5
3 13.8 5 11.8
3 13.8 7 19.1
1 3.6 5 13.3
I 6.4 2 5.4
64
18
4
0
1
5
11
22
3
100.0
27.5
5.7
0.5
1.2
8.1
17.7
33.6
3.9
Age Group: 11 to <16 years (g/kg-day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
12 100.0 23 100.0
5 42.0 8 33.1
I 12.4 2 9.8
0 0.5 0 0.5
0 1.9 0 1.7
2 14.8 3 12.1
2 18.2 5 23.0
0 2.2 3 12.3
I 7.0 I 5.9
39
9
3
0
I
3
9
13
2
100.0
22.3
6.4
0.5
1.5
8.8
22.4
32.3
4.2
Q
I,
ft
-------
I
§
s
Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Fruit and Vegetable Intake (continued)
Food
Group
Low-End Mid-Range
Consumer Consumer
Intake
% Intake
%
High-End
Consumer
Intake %
Age Group: 16 to <21 years (g/day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
624
238
76
8
21
100
109
18
46
100.0 970
38.1 203
12.2 112
1.2 15
3.3 16
16.1 138
17.5 283
2.9 121
7.3 66
100.0
21.0
11.5
1.6
1.6
14.2
29.2
12.5
6.8
2,353 100.0
449 19.1
245 10.4
17 0.7
30 1.3
211 9.0
615 26.1
644 27.4
116 4.9
Age Group: 20 years and older (g/day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
602
178
99
11
21
105
115
16
45
100.0 1,040
29.6 215
16.4 129
1.8 15
3.5 23
17.5 131
19.1 306
2.6 138
7.5 64
100.0
20.6
12.4
1.4
2.2
12.6
29.4
13.3
6.2
1,920 100.0
282 14.7
168 8.7
23 1.2
28 1.5
177 9.2
527 27.4
610 31.7
83 4.3
Food
Group
Low-End
Consumer
Intake
Mid-Range
Consumer
% Intake %
High-End
Consumer
Intake %
Age Group: 16 to <21 years (g/kg-day)
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
Total Foodsb
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fats0
9
4
1
0
0
1
2
0
1
Age Group:
8
2
1
0
0
1
2
0
1
100.0
39.0
11.7
1.4
3.4
16.2
17.9
1.8
7.2
16
3
2
0
0
2
5
1
1
100.0
21.0
12.7
0.8
2.5
14.6
30.7
9.1
7.5
34
6
3
0
0
3
9
10
2
100.0
17.8
9.6
0.6
1.0
10.0
25.8
30.0
4.4
20 years and older (g/kg-day)
100.0
28.6
16.9
1.8
3.4
17.8
19.6
2.5
7.7
14
3
2
0
0
2
4
2
1
100.0
20.3
13.0
1.2
2.1
13.2
29.7
12.5
6.3
27
4
2
0
0
2
7
9
1
100.0
14.7
7.5
1.3
1.3
9.0
27.2
33.9
3.8
a All individuals in this sample group below the 75 percentile consumed 0 g/day of fruits and vegetables. Therefore, only high-end and low-end consumer
groups are reported.
b Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
0 Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: U.S. EPA analysis of 1994-1996, 1998
CSFII.
s
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ft
-------
5
1=
Table 14-11.
Per Capita
Intake of Total Foods and
Major Food Groups, and Percent of Total Food Intake for Individuals with
Mid-Range, and High-End Total Dairy
Food
Group
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake %
High-End
Consumer
Intake
%
Age Group: Birth to <1 month (g/day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
12
0
0
0
0
0
8
0
3
100.0
0.0
0.0
0.0
0.0
0.3
66.1
0.0
27.1
Age Group: 1 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
36
0
0
0
0
0
21
2
10
100.0
0.0
0.0
0.0
0.0
0.9
58.8
4.3
26.7
Age Group: 3 to
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
132
0
1
0
0
6
46
58
16
100.0
0.0
0.4
0.0
0.0
4.5
34.9
44.1
11.9
60 100.0
40 67.3
0 0.0
0 0.0
0 0.0
0 0.0
2 3.4
0 0.0
18 29.2
<3 months (g/day)
84 100.0
19 22.4
0 0.0
0 0.0
0 0.0
1 1.2
42 50.7
0 0.0
21 25.4
<6 months (g/day)
217 100.0
59 27.0
2 1.0
0 0.0
0 0.2
8 3.8
37 17.0
84 38.8
26 12.1
185
127
0
0
0
4
1
0
52
166
109
0
0
0
0
4
6
45
346
160
4
0
1
12
26
87
55
100.0
69.0
0.0
0.0
0.0
2.2
0.4
0.0
28.4
100.0
65.6
0.0
0.0
0.0
0.8
2.7
3.7
27.2
100.0
46.3
1.1
0.1
0.2
3.4
7.6
25.1
15.8
Food
Group
Intake
Low-End Mid-Range
Consumer Consumer
Intake
% Intake
Low-End,
High-End
Consumer
% Intake %
Age Group: Birth to <1 month (g/kg-day)
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
4
0
0
0
0
0
2
0
1
Age Group
7
0
0
0
0
0
4
0
2
Age Group
19
0
0
0
0
1
7
8
2
100.0 18
0.0 12
0.0 0
0.0 0
0.0 0
0.2 0
64.4 1
0.0 0
27.5 5
100.0
67.1
0.0
0.0
0.0
0.0
3.7
0.0
29.2
56
39
0
0
0
1
0
0
16
100.0
69.0
0.0
0.0
0.0
2.1
0.5
0.0
28.4
1 to <3 months (g/kg-day)
100.0 14
0.0 3
0.0 0
0.0 0
0.0 0
0.8 0
57.8 7
5.4 0
26.4 4
100.0
24.0
0.0
0.0
0.0
2.0
48.7
0.0
25.0
41
26
0
0
0
0
0
3
11
100.0
64.1
0.0
0.0
0.0
0.6
1.1
7.7
26.5
3 to <6 months (g/kg-day)
100.0 32
0.0 8
0.5 0
0.0 0
0.0 0
4.5 1
35.6 4
43.0 14
12.2 3
100.0
24.8
0.7
0.0
0.3
3.8
13.7
45.8
10.7
44
24
0
0
0
2
2
7
8
100.0
54.9
1.0
0.1
0.1
3.4
5.0
15.9
19.2
Q
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I
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s
Table 14-11.
Food
Group
Per Capita Intake of Total Foods and
Low-End
Consumer
Intake %
Mid-Range,
Mid-Range
Consumer
Intake
%
Major Food Groups, and Percent
of Total Food Intake for Individuals with Low-End,
and High-End Total Dairy Intake (continued)
ffij
'h-End
Consumer
Intake
%
Age Group: 6 to <12 months (g/day)
Total Foodsa
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
317 100.0
0 0.0
11 3.4
0 0.0
3 0.9
27 8.6
114 35.9
137 43.3
20 6.4
Age Group: 1 to
601 100.0
40 6.7
43 7.1
3 0.5
14 2.3
57 9.5
139 23.1
268 44.7
29 4.8
Age Group: 2 to
661 100.0
48 7.3
61 9.3
2 0.3
25 3.8
78 11.9
163 24.7
237 35.8
37 5.5
368
71
16
1
5
23
75
147
30
100.0
19.2
4.4
0.3
1.4
6.3
20.4
39.9
8.2
1,285
833
41
0
6
46
106
211
40
100.0
64.8
3.2
0.0
0.5
3.6
8.2
16.4
3.1
<2 years (g/day)
989
451
51
4
15
65
120
240
38
100.0
45.6
5.2
0.4
1.5
6.5
12.1
24.3
3.8
1,700
1,170
45
3
18
63
112
226
58
100.0
68.8
2.6
0.2
1.1
3.7
6.6
13.3
3.4
<3 years (g/day)
996
348
63
6
20
82
144
279
41
100.0
34.9
6.3
0.6
2.1
8.2
14.5
28.0
4.1
1,528
885
55
5
19
86
137
277
55
100.0
57.9
3.6
0.3
1.3
5.6
9.0
18.1
3.6
Food
Group
Low-End
Consumer
Intake
%
Age Group: 6 to <12
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods"
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Foods"
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
36
0
1
0
0
3
13
16
2
Age Group
55
3
4
0
1
5
12
25
3
Age Group
47
3
4
0
2
5
12
17
3
100.0
0.0
3.5
0.0
1.0
7.9
35.3
44.6
6.3
: 1 to <2
100.0
6.1
7.2
0.5
2.3
9.5
21.8
46.3
4.7
: 2 to <3
100.0
7.2
9.4
0.3
3.7
11.6
24.6
36.4
5.5
Mid-Range
Consumer
Intake %
months (g/kg-day)
43 100.0
8 18.2
2 4.8
0 0.3
1 2.1
3 7.7
8 17.9
18 40.7
4 8.1
years (g/kg-day)
86 100.0
38 44.0
4 4.8
1 0.6
2 1.8
6 6.9
11 13.0
21 24.5
3 3.7
years (g/kg-day)
72 100.0
24 33.7
4 6.2
0 0.4
1 1.5
6 8.5
10 14.0
22 30.2
3 4.2
High-End
Consumer
Intake
135
87
4
0
1
5
11
22
4
154
106
4
0
1
6
10
21
5
114
67
4
0
1
6
11
20
4
%
100.0
64.8
3.0
0.0
0.5
3.5
8.2
16.6
3.1
100.0
68.5
2.6
0.1
0.8
3.7
6.7
13.8
3.4
100.0
58.4
3.6
0.2
1.3
5.7
9.3
17.3
3.6
s
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s
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ft
-------
5
1=
Table 14-11.
Food
Group
Per Capita
Intake of Total Foods and
Mid-Range,
Low-End
Consumer
Intake
%
Mid-Range
Consumer
Intake
%
Major Food Groups, and Percent of Total Food Intake for Individuals with
and High-End Total Dairy Intake (continued)
High-End
Consumer
Intake
%
Age Group: 3 to <6 years (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
725
64
75
4
19
87
168
253
40
Age
766
63
99
6
17
105
221
194
49
100.0
8.9
10.4
0.6
2.6
12.1
23.2
34.9
5.6
Group:
100.0
8.2
12.9
0.8
2.2
13.7
28.9
25.3
6.4
Age Group:
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
747
22
102
8
20
104
239
197
47
100.0
3.0
13.6
1.1
2.7
13.9
32.0
26.4
6.2
1,047
355
72
6
15
104
173
257
49
100.0
33.9
6.9
0.5
1.4
9.9
16.
24.5
4.7
1,612
886
70
6
18
116
183
251
63
100.0
55.0
4.3
0.4
1.1
7.2
11.3
15.6
3.9
6 to <11 years (g/day)
1,053
372
80
5
14
113
214
175
56
llto<16
1,094
307
101
9
18
133
265
180
62
100.0
35.4
7.6
0.5
1.3
10.7
20.3
16.6
5.3
years (g/day)
100.0
28.0
9.2
0.8
1.6
12.2
24.2
16.4
5.6
1,722
892
87
6
17
152
242
227
70
2,020
1,017
134
12
25
181
322
204
100
100.0
51.8
5.1
0.4
1.0
8.8
14.0
13.2
4.1
100.0
50.3
6.7
0.6
1.2
9.0
16.0
10.1
5.0
Food
Group
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Low-End
Consumer
Intake %
Age Group: 3
41 100.0
4 8.8
4 10.6
0 0.5
1 2.6
5 12.1
10 23.8
14 34.0
2 5.7
Age Group: 6
25 100.0
2 8.1
3 13.2
0 0.8
1 2.3
3 13.6
7 29.5
6 24.4
2 6.6
Age Group: 11
13 100.0
0 2.9
2 13.8
0 1.0
0 2.6
2 13.7
4 33.0
3 25.7
1 6.2
Mid-Range
Consumer
Low-End,
High-End
Consumer
Intake % Intake %
to <6 years (g/kg-day)
58 100.0
20 34.2
4 6.6
0 0.5
1 1.5
6 9.9
9 16.3
14 24.7
3 4.7
to <11 years (g/kg-day)
38 100.0
13 34.2
2 8.0
0 0.5
1 1.8
4 10.7
8 19.7
7 17.8
2 5.2
to <16 years (g/kg-day)
22 100.0
6 27.3
2 9.6
0 0.6
0 1.7
3 12.2
5 23.3
4 17.8
1 5.9
97
52
4
0
1
7
11
16
4
67
35
3
0
1
6
9
9
3
42
21
3
0
1
4
6
5
2
100.0
54.0
4.4
0.3
1.0
7.2
11.6
16.5
4.0
100.0
51.9
4.9
0.4
0.9
9.0
13.7
13.5
4.2
100.0
49.4
6.4
0.8
1.2
9.1
15.1
11.9
4.8
Q
I,
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^S3
^
I
Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals with Low-End,
Mid-Range, and High-End Total Dairy Intake (continued)
Food
Group
Low-End
Consumer
Mid-Range
Consumer
Intake % Intake %
Age Group: 16to<21
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
647 100.0 1
8 1.2
101 15.7
8 1.2
12 1.8
90 13.9
228 35.2
152 23.5
37 5.8
,095
197
125
16
28
162
324
154
73
years (g/day)
100.0
18.0
11.4
1.5
2.5
14.8
29.6
14.1
6.7
High-End
Consumer
[ntake
2,233
950
197
8
27
217
438
249
114
%
100.0
42.5
8.8
0.4
1.2
9.7
19.6
11.2
5.1
Age Group: 20 years and older (g/day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
741 100.0 1
9 1.2
117 15.8
16 2.2
20 2.7
113 15.2
258 34.8
159 21.4
42 5.6
,030
155
129
16
23
130
304
189
62
100.0
15.1
12.6
1.6
2.3
12.6
29.6
18.4
6.0
1,810
725
156
19
26
176
361
226
89
100.0
40.1
8.6
1.1
1.4
9.7
20.0
12.5
4.9
Food
Group
Low-End
Consumer
Intake
%
Mid-Range High-End
Consumer Consumer
Intake
% Intake %
Age Group: 16 to <21 years (g/kg-day)
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
Total Foods3
Total Dairy
Total Meats
Total Fish
Total Eggs
Total Grains
Total Vegetables
Total Fruits
Total Fatsb
10
0
2
0
0
1
4
2
1
Age
10
0
2
0
0
2
4
2
1
100.0
1.2
15.1
1.1
1.7
14.1
35.8
23.9
5.6
Group: 20
100.0
1.2
15.8
2.1
2.7
15.0
34.5
21.9
5.5
17
3
2
0
0
2
5
3
1
100.0 33
16.6 14
13.6 3
0.9 0
2.2 0
14.0 3
28.6 7
16.1 3
6.5 2
100.0
42.8
8.9
0.3
1.2
9.6
20.0
10.6
5.1
years and older (g/kg-day)
14
2
2
0
0
2
4
3
1
100.0 25
14.8 10
12.3 2
1.6 0
2.3 0
12.5 2
29.5 5
19.4 3
5.9 1
100.0
41.0
7.3
1.0
1.4
9.5
19.4
14.2
4.5
3 Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and
fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups.
b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: U.S. EPA analysis of 1994-1996, 1998
CSFII.
S
I
i
ft1
S
I,
I-.*
>—
I
ft
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3
1=
Table 14-12. Intake of Total Food3 (g/kg-day), Edible Portion, Uncooked Weight
Age or Race/Ethnic Group N Mean SEb
50 years 3,893 29.1 0.55
All Ages 16,783 36.1 0.56
Female 13 to 49 years 4,103 28.8 0.85
Mexican American 4,450 40.2 0.86
Non-Hispanic Black 4,265 30.7 0.85
Non-Hispanic White 6,757 36.0 0.72
Other Hispanic 562 39.5 2.01
Other 749 40.3 1.94
LCLC UCLd
Age 98.1
108.0 118.1
76.0 81.2
44.7 49.4
26.0 28.9
27.9 30.9
28.0 30.3
35.0 37.2
27.1 30.5
38.4 42.0
29.0 32.4
34.6 37.5
35.4 43.7
36.3 44.3
Percentiles
Mine st m
0*
0*
0*
0*
0*
0*
0*
0*
0*
0*
0*
0*
0*
0*
0* 0*
38.3* 54.0*
28.3* 41.3
7.1* 16.1
5.0 9.4
4.1 9.4
0 10.0
3.4 10.0
3.1 9.0
4.8 11.1
0 7.1
5.4 10.5
0* 12.1
0* 11.2
10th
3.8
65.2
45.9
21.3
11.7
12.1
13.0
13.0
11.5
14.0
9.6
13.5
14.1
14.1
25th
32.0
84.5
55.5
30.1
17.1
17.8
18.6
19.4
17.1
19.7
14.6
20.2
20.8
21.9
50m
90.0
106.6
73.0
42.2
24.5
25.9
26.2
28.8
24.9
29.5
22.3
29.5
27.9
31.9
75m
134.2
137.8
96.5
59.3
34.8
37.6
36.3
43.1
36.7
48.7
36.8
43.1
42.9
50.1
90m
179.9
164.3
119.0
76.8
46.6
52.3
49.5
66.7
52.7
82.6
60.8
64.9
83.1
76.6
95m
207.7*
184.9*
136.5
92.3
56.3
62.8
58.5
89.4
62.9
108.4
83.4
84.1
115.2
99.0
99m
277.8*
244.2*
167.4*
128.1*
75.2
82.1
80.8
148.0
84.1
163.5
147.4
141.9
170.7*
157.1*
Max1
355.2*
346.0*
254.0*
167.3*
122.0*
211.2*
119.6*
355.2*
211.2*
278.1*
304.1*
355.2*
346.0*
315.6*
a Total food includes all foods, beverages, and water ingested.
b SE = Standard error of the mean.
0 LCL = Lower confidence limit of the mean.
d UCL = Upper confidence limit of the mean.
e Min = Minimum value.
f Max = Maximum value.
* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards
on NHANES III
and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
Source: U.S. EPA analysis of NHANES 2003-2006 data.
Q
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s
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
TABLE OF CONTENTS
LIST OF TABLES 15-ii
15. HUMAN MILK INTAKE 15-1
15.1. INTRODUCTION 15-1
15.2. RECOMMENDATIONS 15-1
15.2.1. Human Milk Intake 15-2
15.2.2. Lipid Content and Lipid Intake 15-2
15.3. KEY STUDIES ON HUMAN MILK INTAKE 15-9
15.3.1. Paoetal. (1980) 15-9
15.3.2. Dewey and Lonnerdal (1983) 15-9
15.3.3. Butteetal. (1984) 15-9
15.3.4. Neville etal. (1988) 15-10
15.3.5. Dewey etal. (1991a,b) 15-10
15.3.6. Butte et al. (2000) 15-11
15.3.7. Arcus-Arth et al. (2005) 15-11
15.4. KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK 15-12
15.4.1. Butte et al. (1984) 15-12
15.4.2. Mitoulas et al. (2002) 15-13
15.4.3. Mitoulas et al. (2003) 15-13
15.4.4. Arcus-Arth et al. (2005) 15-14
15.4.5. Kent et al. (2006) 15-14
15.5. RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK 15-14
15.5.1. Maxwell and Burmaster (1993) 15-14
15.6. OTHER FACTORS 15-15
15.6.1. Population of Nursing Infants 15-15
15.6.2. Intake Rates Based on Nutritional Status 15-17
15.6.3. Frequency and Duration of Feeding 15-18
15.7. REFERENCES FOR CHAPTER 15 15-18
Exposure Factors Handbook Page
September 2011 15-i
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
LIST OF TABLES
Table 15-1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively
Breast-Fed Infants 15-3
Table 15-2. Confidence in Recommendations for Human Milk Intake 15-4
Table 15-3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/day) 15-5
Table 15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/kg-day) 15-6
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/day) 15-7
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants (mL/kg-
day) 15-8
Table 15-7. Daily Intakes of Human Milk 15-21
Table 15-8. Human Milk Intakes for Infants Aged 1-6 Months 15-21
Table 15-9. Human Milk Intake Among Exclusively Breast-Fed Infants During the First 4 Months of
Life 15-21
Table 15-10. Human Milk Intake During a 24-Hour Period 15-22
Table 15-11. Human Milk Intake Estimated by the Darling Study 15-23
Table 15-12. Mean Breast-Fed Infants Characteristics 15-23
Table 15-13. Mean Human Milk Intake of Breast-Fed Infants (mL/day) 15-23
Table 15-14. Feeding Practices by Percent of Infants 15-24
Table 15-15. Body Weight of Breast-Fed Infants 15-24
Table 15-16. AAP Data Set Milk Intake Rates at Different Ages 15-25
Table 15-17. Average Daily Human Milk Intake (mL/kg-day) 15-25
Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-Fed
Infants 15-26
Table 15-19. Human Milk Production and Composition During the First 12 Months of Lactation 15-26
Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content During the First Year
of Lactation 15-27
Table 15-21. Changes in Fatty Acid Composition of Human Milk During the First Year of Lactation
(g/100 g total fatty acids) 15-27
Table 15-22. Comparison Daily Lipid Intake Based on Lipid Content Assumptions (mL/kg-day) 15-28
Table 15-23. Distribution of Average Daily Lipid Intake (mL/kg-day) Assuming 4% Milk Lipid
Content 15-28
Table 15-24. Predicted Lipid Intakes for Breast-Fed Infants Under 12 Months of Age 15-28
Table 15-25. Socioeconomic Characteristics of Exclusively Breast-Fed Infants Born in 2004 15-29
Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children Born in 2006 15-30
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6
Months Old 15-32
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12
Months Old 15-33
Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
During the Previous 24 Hours 15-34
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, NHANES III
(1988-1994) 15-35
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk
at 6 Months (NHANES III, 1988-1994) 15-37
Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at
4 Months (NHANES III, 1991-1994) 15-39
Table 15-33. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants at 5
or 6 Months of Age in the United States in 1989 and 1995, by Ethnic Background and
Selected Demographic Variables 15-41
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Chapter 15—Human Milk Intake
LIST OF TABLES (continued)
Table 15-34. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants at 6
and 12 Months of Age in the United States in 2003, by Ethnic Background and Selected
Demographic Variables 15-42
Table 15-35. Number of Meals Per Day 15-43
Table 15-36. Comparison of Breast-Feeding Patterns Between Age and Groups (Mean± SD) 15-43
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Chapter 15—Human Milk Intake
15. HUMAN MILK INTAKE
15.1. INTRODUCTION
Human lactation is known to impart a wide range
of benefits to nursing infants, including protection
against infection, increases in cognitive development,
and avoidance of allergies due to intolerance to cow's
milk (AAP, 2005). Ingestion of human milk also has
been associated with a reduction in risk of
postneonatal death in the United States. (Chen and
Rogan, 2004). The American Academy of Pediatrics
(AAP) recommends exclusive breast-feeding for
approximately the first 6 months and supports the
continuation of breast-feeding for the first year and
beyond if desired by the mother and child (AAP,
2005). However, contaminants may find their way
into human milk of lactating mothers because
mothers are themselves exposed, thus making human
milk a potential source of exposure to toxic
substances for nursing infants. Lipid-soluble
chemical compounds accumulate in body fat and may
be transferred to breast-fed infants in the lipid portion
of human milk. Water soluble chemicals also may
partition into the aqueous phase and be excreted via
human milk. Because nursing infants obtain most—if
not all—of their dietary intake from human milk,
they are especially vulnerable to exposures to these
compounds. Estimating the magnitude of the
potential dose to infants from human milk requires
information on the milk intake rate (quantity of
human milk consumed per day) and the duration
(months) over which breast-feeding occurs.
Information on the fat content of human milk also is
needed for estimating dose from human milk residue
concentrations that have been indexed to lipid
content.
Several studies have generated data on human
milk intake. Typically, human milk intake has been
measured over a 24-hour period by weighing the
infant before and after each feeding without changing
its clothing (test weighing). The sum of the difference
between the measured weights over the 24-hour
period is assumed to be equivalent to the amount of
human milk consumed daily. Intakes measured using
this procedure often are corrected for evaporative
water losses (insensible water losses) between infant
weighings (NAS, 1991). Neville et al. (1988)
evaluated the validity of the test weight approach
among bottle-fed infants by comparing the weights of
milk taken from bottles with the differences between
the infants' weights before and after feeding. When
test weight data were corrected for insensible weight
loss, they were not significantly different from bottle
weights. Conversions between weight and volume of
human milk consumed are made using the density of
human milk (approximately 1.03 g/mL) (NAS, 1991).
Techniques for measuring human milk intake using
stable isotopes such as deuterium have been
developed. The advantages of these techniques over
test weighing procedures are that they are less
burdensome for the mother and do not interfere with
normal behavior (Albernaz et al., 2003). However,
few data based on this technique were found in the
literature.
Among infants born in 2004, 73.8% were breast-
fed postpartum, 41.5% at 6 months, and 20.9% at 12
months. Studies of nursing mothers in industrialized
countries have shown that average intakes among
infants ranged from approximately 500 to 800
mL/day, with the highest intake reported for infants 3
to <6 months old (see Table 15-1).
The recommendations for human milk intake
rates and lipid intake rates are provided in the next
section along with a summary of the confidence
ratings for these recommendations. The
recommended values are based on key studies
identified by U.S. Environmental Protection Agency
(EPA) for this factor. Following the
recommendations, key studies on human milk intake
are summarized. Relevant data on lipid content and
fat intake, breast-feeding duration, and the estimated
percentage of the U.S. population that breast-feeds
also are presented.
A number of other studies exist in the literature,
but they focus on other aspects of lactation such as
growth patterns of nursing infants, supplementary
food and energy intake, and nutrition of lactating
mothers (Dewey et al., 1992; Drewett et al., 1993;
Gonzalez-Cossio et al., 1998). These studies are not
included in this chapter because they do not focus on
the exposure factor of interest. Other studies in the
literature focus on formula intake. Because some
baby formula is prepared by adding water, these data
are presented in Chapter 3-Ingestion of Water and
Other Select Liquids.
15.2. RECOMMENDATIONS
The studies described in Section 15.3 were used
in selecting recommended values for human milk
intake and lipid intake. Although different survey
designs, testing periods, and populations were used
by the studies to estimate intake, the mean and
standard deviation estimates reported in these studies
are relatively consistent. There are, however,
limitations with the data. With the exception of Butte
et al. (1984) and Arcus-Arth et al. (2005), data were
not presented on a body weight basis. This is
particularly important because intake rates may be
higher on a body weight basis for younger infants
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Chapter 15—Human Milk Intake
than older infants. Also, the data used to derive the
recommendations are more than 15 years old and the
sample size of the studies was small. Other
populations of concern—such as mothers highly
committed to breast-feeding, sometimes for periods
longer than 1 year—may not be captured by the
studies presented in this chapter. Note that data for
infants 12 months old are not included in the
recommendation table because the U.S. EPA's
standard age group for children, as described in
chapter 1 of this handbook, is 6 to <12 months and it
may not be appropriate to use this value to represent
the next age group of 1 to <2 years old.
15.2.1. Human Milk Intake
Table 15-1 presents a summary of recommended
values for human milk and lipid intake rates, and
Table 15-2 presents the confidence ratings for these
recommendations. The human milk intake rates for
nursing infants that have been reported in the studies
described in this section are summarized in
Table 15-3 in units of mL/day and in Table 15-4 in
units of mL/kg-day (i.e., indexed to body weight). It
should be noted that the decrease in human milk with
age is likely a result of complementary foods being
introduced as the child grows and not necessarily a
decrease in total energy intake. To conform to the
new standardized age groupings used in this
handbook (see Chapter 1), data from Pao et al.
(1980), Dewey and Lonnerdal (1983), Butte et al.
(1984), Neville et al. (1988), Dewey et al. (1991a),
Dewey et al. (1991b), Butte et al. (2000), and
Arcus-Arth et al. (2005) were compiled for each
month of the first year of life. Recommendations
were converted to mL/day by using a density of
human milk of 1.03 g/mL, and rounded to two
significant figures. Only two studies (i.e., Butte et al.,
1984, and Arcus-Arth et al., 2005) provided data on a
body weight basis. For some months, multiple studies
were available; for others only one study was
available. Weighted means were calculated for each
age in months. When upper percentiles were not
available from a study, they were estimated by adding
two standard deviations to the mean value. When
multiple studies were available, recommendations for
upper percentiles were calculated as the midpoint of
the range of upper percentile values of the studies
available for each age in months. These
month-by-month intakes were composited to yield
intake rates for the standardized age groups by
calculating a weighted average. Recommendations
are provided for the population of exclusively breast-
fed infants because this population may have higher
exposures than partially breast-fed infants.
Exclusively breast-fed in this chapter refers to infants
whose sole source of milk comes from human milk,
with no other milk substitutes. Partially breast-fed
refers to infants whose source of milk comes from
both human milk and other milk substitutes (i.e.,
formula). Note that some studies define partially
breast-fed as infants whose dietary intake comes from
not only human milk and formula, but also from
other solid foods (e.g., strained fruits, vegetables,
meats).
15.2.2. Lipid Content and Lipid Intake
Table 15-5 presents recommended lipid intake
rates in units of mL/day. The table parallels the
human milk intake tables (see Table 15-3). With the
exception of the data from Butte et al. (1984), the
rates were calculated assuming a lipid content of 4%
(Butte et al., 1984; NAS, 1991; Mitoulas et al., 2002,
2003; Arcus-Arth et al., 2005; Kent et al., 2006). In
the case of the Butte et al. (1984) study, lipid intake
rates were provided and were used in place of the
estimated lipid intakes. Table 15-6 presents lipid
intake rates on a body weight basis (mL/kg-day).
These were calculated from the values presented in
Table 15-4 multiplied by 4% lipid content.
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Chapter 15—Human Milk Intake
Table 15-1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breast-
Fed Infants
Mean
Age Group mL/day
Upper Percentile3
mL/kg-day mL/day mL/kg-day
Source
Human Milk Intake
Birth to <1 month 510
1 to <3 months 690
3 to <6 months 770
6 to < 12 months 620
150
140
110
83
950
980
1,000
1,000
220
190
150
130
b,c
b, c, d, e, f
b, c, d, e, f, g, h
b, c, d, f, g, h
Lipid Intake1
Birth to <1 month 20
1 to <3 months 27
3 to <6 months 30
6 to < 12 months 25
a Upper percentile is reported as
b Neville etal., 1988.
Arcus-Arth etal., 2005.
d Pao etal., 1980.
Butte etal., 1984.
f Dewey and Lonnerdal, 1983.
g Butte etal., 2000.
h Dewey et al., 1991b.
6.0
5.5
4.2
3.3
mean plus 2 standard
38
40
42
42
deviations.
1 The recommended value for the lipid content of human milk is 4.0 %.
8.7
8.0
6.1
5.2
See Section
b,c
b, c, d, e, f
b, c, d, e, f, g, h
b, c, d, f, g, h
15.4.
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September 2011 15-3
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Chapter 15—Human Milk Intake
Table 15-2. Confidence in Recommendations for Human Milk Intake
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
Methodology uses changes in body weight as a surrogate for total
ingestion. More sophisticated techniques measuring stable isotopes
have been developed, but data with this technique were not
available. Sample sizes from individual studies were relatively
small (7-108). Mothers selected for the studies were volunteers.
The studies analyzed primary data.
Mothers were instructed in the use of infant scales to minimize
measurement errors. Three out of the eight studies indicated
correcting data for insensible water loss. Some biases may be
introduced by including partially breast-fed infants.
The studies focused on estimating human milk intake.
Most studies focused on the U.S. population, but were not national
samples. Populations studied were mainly from high socioeconomic
status. One study included populations from Sweden and Finland.
However, this may not affect the amount of intake, but, rather, the
prevalence and initiation of lactation.
Studies were conducted between 1980 and 2000. However, this may
not affect the amount of intake but rather the prevalence and
initiation of lactation.
Infants were not studied long enough to fully characterize day-to-
day variability.
All key studies are available from the peer-reviewed literature.
The methodology was clearly presented, but some studies did not
discuss adjustments due to insensible weight loss.
Some steps were taken to ensure data quality. For example, mothers
were trained to use the scales. However, this element could not be
fully evaluated from the information presented in the published
studies.
Variability was not very well-characterized. Mothers committed to
breast-feeding more than 1 year were not captured.
Not correcting for insensible water loss may underestimate intake.
The studies appeared in peer-review journals.
There are eight key studies. The results of studies from different
researchers are in agreement.
Rating
Medium
Medium
Medium
Low
High
Medium
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Chapter 15—Human Milk Intake
Table 15-3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/day)
, , Upper
A ^T i f Mean _ ^.,
Age Number of Percentile
(months) Children . T , , . Consumption
(mL/day) *\a
(mL/day)
0<1 6 to 13 511 951
11 600 918
37 729 981
10 to 12 67911 889
16 673 1,057
10 to 12 679d 889
2 19 756 1,096
40 704 958
2 833
37 702 924
10 713 935
16 782 1,126
73 788 1,047
40 728 988
12 690 888
4 13 810 1,094
41 718 996
12 814 1,074
11 805 1,039
1 682
13 744 978
6 11 896 1,140
60 747 1,079
30 637 1,050
7 12 700 1,000
8 9 604 1,012
12 600 1,028
50 627 1,049
10 11 535 989
11 8 538 1,004
8 391 877
12 42 435 922
13 403 931
Weighted Mean Intake and Upper Percentile
Consumption (across all key studies)
(mL/day)
Individual Age Composite Age Groups
Meanb Upper' Meanb Upper0
Neville et al., 1988 511 951 511 951
Pao et al., 1980
Butteetal.,1984
Neville et al., 1988
Dewey and Lonnerdal, 1983 ^^ 983
Neville et al., 1988
Dewey and Lonnerdal, 1983 713 992
Butte et al., 1984
Pao et al., 1980
Butte et al., 1984
Neville et al., 1988 ?58 ^ Q25
Dewey and Lonnerdal, 1983 '
Dewey et al., 1991b
Butte et al., 2000
76Q 1 (P4
Neville et al., 1988
Dewey and Lonnerdal, 1983 739 991
Butte et al., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983 '
Pao et al., 1980
Neville et al., 1988
Dewey and Lonnerdal, 1983 741 1,059
Dewey etal., 1991b
Butte et al., 2000
Neville et al., 1988 700 1,000
622 1,024
Neville et al., 1988 604 1,012
Neville et al., 1988
T^ .1 i ,™,i 614 1,039
Dewey etal., 1991b
Neville et al., 1988 535 989
Neville et al., 1988 538 1,004
Neville et al., 1988
Dewey et al., 1991a,b 410 904 410 904
Butte et al., 2000
a Upper percentile is reported as mean plus 2 standard deviations.
b Calculated as the mean of the means.
c Middle of the range of upper percentiles.
d Calculated for infants 1 to <2 months old.
e Standard deviations and upper percentiles not calculated for small sample sizes.
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Chapter 15—Human Milk Intake
Table 15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants
(mL/kg-day)
,, , Mean
. Number T , .
Age ,, Intake
(months) „. ... (mL/kg
v ' Children v , °
-day)
0<1
1
2
3
4
5
6
7
9
12
a
b
c
9 to 25
37
25
40
25
37
108
41
57
26
39
8
57
42
150
154
150
125
144
114
127
108
112
100
101
75
72
47
Upper
Percentile
Consumption
(mL/kg-day )a
217
200
198
161
188
152
163
142
148
140
141
125
118
101
Source
Arcus-Arth
Butte et al.,
Arcus-Arth
Butte et al.,
Arcus-Arth
Butte et al.,
Arcus-Arth
Butte et al.,
Arcus-Arth
Arcus-Arth
Arcus-Arth
Arcus-Arth
Arcus-Arth
Arcus-Arth
etal.,
1984
etal.,
1984
etal.,
1984
etal.,
1984
etal.,
etal.,
etal.,
etal.,
etal.,
etal.,
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
Weighted Mean Intake and Upper Percentile
Consumption (cross all key studies)
(mL/kg-day)
T ,. . , . . Composite Age
Individual Age £ &
fe Groups
Mean"
150
152
135
121
110
100
101
75
72
47
Upper0 Mean Upper0
217
199
175
158
145
140
141
125
118
101
150 217
144 187
110 149
83 130
47 101
Upper percentile is reported as mean plus two standard deviations.
Calculated as the mean of the means.
Middle of the range of upper percentiles.
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15-6
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Chapter 15—Human Milk Intake
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants (mL/day)a
, . , , ,, Mean Upper Percentil
Age Number of T , \f
. ° . _, ., , Intake Consumption
(months) Children . , , , r b
v ' (mL/day) (mL/day)
0<1 6 to 13
11
1 10 to 12
16
10 to 12
2 19
40
2
37
3 10
J 16
73
40
12
4 13
41
S
1
13
6 11
60
30
7 12
8 9
9 12
50
10 11
11 9
9
12 42
13
20
24
27
27
27
27
30
24
33
23
29
31
32
29
28
32
25
33
32
27
30
36
30
25
28
24
24
25
21
22
16
17
16
38
37
43
36
42
36
44
38
e
37
37
45
42
40
36
44
41
43
42
e
39
46
43
42
40
40
41
42
40
40
35
37
37
Weighted Mean Intake and Upper Percentile
Consumption (across all key studies)
* (mL/day)
Individual Age Composite Age Groups
Mean0 Upper"1 Mean0 Upper"1
Neville etal., 1988 20 38
Paoetal., 1980
Butte et al., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Neville etal., 1988
Dewey and Lonnerdal, 1983 27 40
Butte et al., 1984
Paoetal., 1980
Butte et al., 1984
Neville etal., 1988 3Q ^
Dewey and Lonnerdal, 1983
Dewey etal., 1991b
Butte et al., 2000
Neville etal., 1988
Dewey and Lonnerdal, 1983 28 40
Butte et al., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Paoetal., 1980
Neville etal., 1988
Dewey and Lonnerdal, 1983 30 40
Dewey etal., 1991b
Butte et al., 2000
Neville etal., 1988 28 40
Neville etal., 1988 24 40
Neville etal., 1988
Dewey et al., 1991b
Neville etal., 1988 21 40
Neville etal., 1988 22 40
Neville etal., 1988
Dewey etal., 199 la, b 16 36
Butte et al., 2000
20 38
27 40
30 42
25 42
16 36
" Except for Butte et al. (1984), values were calculated from Table 15-3 using 4% lipid content.
b Upper percentile is reported as mean plus 2 standard deviations.
0 Calculated as the mean of the means.
11 Middle of the range of upper percentiles.
e Standard deviations and upper percentiles not calculated for small sample sizes.
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Chapter 15—Human Milk Intake
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-Fed Infants (mL/kg-day)a
XT , Mean Upper
. Number T . , _ t..
Age - Intake Percentile
(months) p^-ij (mL/kg- Consumption
day) (mL/kg-day)b
Source
Weighted Mean Intake and Upper
Percentile Consumption13 (across all
key studies)
(mL/kg-day)
Individual Age Composite Age
Groups
Mean0
0 <1 9 to 25
1 3?
25
2 4°
25
3 3?
108
* £
5 26
6 39
7 8
9 57
12 42
6.0
5.7
6.0
4.3
5.8
3.7
5.1
3.7
4.5
4.0
4.0
3.0
2.9
1.9
8.7
9.1
8.7
6.7
7.5
6.1
6.5
6.3
5.9
5.6
5.6
5.0
4.7
4.0
Arcus-Arth et al.,
Butte etal., 1984
Arcus-Arth et al.,
Butte etal., 1984
Arcus-Arth etal.,
Butte etal., 1984
Arcus-Arth etal.,
Butte etal., 1984
Arcus-Arth etal.,
Arcus-Arth etal.,
Arcus-Arth etal.,
Arcus-Arth etal.,
Arcus-Arth etal.,
Arcus-Arth etal.,
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
a Except for Butte et al. (1984), values were calculated from Table 15-4
b Upper percentile is reported as mean plus two standard deviations.
0 Calculated as the mean of the means.
d Middle of the range of upper percentiles .
6.0
5.9
5.1
4.4
4.1
4.0
4.0
3.0
2.9
1.9
using
Upperd Mean6 Upperd
8
8
7
6
6
5
5
5
4
4
7
9
1
3
1
8
6
0
7
0
6.0 8.7
5.5 8.0
4.2 6.1
3.3 5.2
1.9 4.0
4% lipid content.
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Chapter 15—Human Milk Intake
15.3. KEY STUDIES ON HUMAN MILK
INTAKE
15.3.1. Pao et al. (1980)—Milk Intakes and
Feeding Patterns of Breast-Fed Infants
Pao et al. (1980) conducted a study of 22 healthy
nursing infants to estimate human milk intake rates.
Infants were categorized as completely breast-fed or
partially breast-fed. Breast-feeding mothers were
recruited through La Leche League groups. Except
for one Black infant, all other infants were from
White middle-class families in southwestern Ohio.
The goal of the study was to enroll infants as close to
1 month of age as possible and to obtain records near
1, 3, 6, and 9 months of age (Pao et al., 1980).
However, not all mother-infant pairs participated at
each time interval. Data were collected for these 22
infants using the test weighing method. Records were
collected for three consecutive 24-hour periods at
each test interval. The weight of human milk was
converted to volume by assuming a density of
1.03 g/mL. Daily intake rates were calculated for
each infant based on the mean of the three 24-hour
periods. Table 15-7 presents mean daily human milk
intake rates for the infants surveyed at each time
interval. These data are presented as they are reported
in Pao et al. (1980). For completely breast-fed
infants, the mean intake rates were 600 mL/day at 1
month of age, 833 mL/day at 3 months of age, and
682 mL/day at 6 months of age. Partially breast-fed
infants had mean intake rates of 485 mL/day, 467
mL/day, 395 mL/day, and <554 mL/day at 1, 3, 6,
and 9 months of age, respectively. Pao etal. (1980)
also noted that intake rates for boys in both groups
were slightly higher than for girls.
The advantage of this study is that data for both
exclusively and partially breast-fed infants were
collected for multiple time periods. Also, data for
individual infants were collected over 3 consecutive
days, which would account for some individual
variability. However, the number of infants in the
study was relatively small. In addition, this study did
not account for insensible weight loss, which may
underestimate the amount of human milk ingested.
15.3.2. Dewey and Lonnerdal (1983)—Milk and
Nutrient Intake of Breast-Fed Infants
from 1 to 6 Months: Relation to Growth
and Fatness
Dewey and Lonnerdal (1983) monitored the
dietary intake of 20 nursing infants between age
1 and 6 months. The number of study participants
dropped to 13 by the end of the 6th month. Most of
the infants in the study were exclusively breast-fed.
One infant's intake was supplemented by formula
during the first and second month of life. During the
3rd, 4th, and 5th months, three, four, and five infants,
respectively, were given some formula to supplement
their intake. Two infants were given only formula (no
human milk) during the 6th month. According to
Dewey and Lonnerdal (1983), the mothers were all
well-educated and recruited through Lamaze
childbirth classes in the Davis area of California.
Human milk intake volume was estimated based on
two 24-hour test weighings per month. Table 15-8
presents human milk intake rates for the various age
groups. Human milk intake averaged 673, 782, and
896 mL/day at 1, 3, and 6 months of age,
respectively.
The advantage of this study is that it evaluated
nursing infants for a period of 6 months based on two
24-hour observations per infant per month. However,
corrections for insensible weight loss apparently were
not made. Also, the number of infants in the study
was relatively small, and the study participants were
not representative of the general population. During
the study period, some infants were given some
formula (i.e., up to five infants during the 5th month).
Without the raw data, these subjects could not be
excluded from the study results. Thus, these subjects
may affect the results when deriving
recommendations for exclusively breast-fed infants.
15.3.3. Butte et al. (1984)—Human Milk Intake
and Growth in Exclusively Breast-Fed
Infants
Human milk intake was studied in exclusively
breast-fed infants during the first 4 months of life
(Butte et al., 1984). Nursing mothers were recruited
through the Baylor Milk Bank Program in Texas.
Forty-five mother-infant pairs participated in the
study. However, data for some time periods (i.e., 1, 2,
3, or 4 months) were missing for some mothers as a
result of illness or other factors. The mothers were
from the middle-to-upper socioeconomic stratum and
had a mean age of 28.0 ±3.1 years. A total of 41
mothers were White, 2 were Hispanic, 1 was Asian,
and 1 was West Indian. Infant growth progressed
satisfactorily during the course of the study.
The amount of milk ingested over a 24-hour
period was determined by weighing the infant before
and after feeding. The study did not indicate whether
the data were corrected for insensible water or weight
loss. The study evaluated the accuracy of the test
weighing procedure using a bottle-fed infant. Test
weighing occurred over a 24-hour period for most
study participants, but intake among several infants
was studied over longer periods (48 to 96 hours) to
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assess individual variation in intake. Eight of the
infants received some food supplementation during
the study period. Six of them received less than 60
kcal/day of formula, oatmeal, glucose water, or rice
water for 1 or 2 days. One infant received an
additional 90 kcal/day of infant formula and rice
water for 6 days during the 4th month because of
inadequate milk production. When converting values
reported as g/day to mL/day, using a conversion
factor of 1.03 g/mL, mean human milk intake ranged
from 702 mL/day at 3 months to 729 mL/day at 1
month, with an overall mean of 712 mL/day for the
entire study period (see Table 15-9). Intakes also
were calculated on the basis of body weight (see
Table 15-9).
The advantage of this study is that data for a
larger number of exclusively breast-fed infants were
collected than in previous studies. However, data
were collected for infants up to 4 months and
day-to-day variability was not characterized for all
infants. Eighteen percent (i.e., 8 out of 45) of the
infants received some formula supplementation
during the study period. Without the raw data, these
subjects could not be excluded from the study results.
Therefore, values derived from this study for
exclusively breast-fed infants may be somewhat
underestimated.
15.3.4. Neville et al. (1988)—Studies in Human
Lactation: Milk Volumes in Lactating
Women During the Onset of Lactation
and Full Lactation
Neville et al. (1988) studied human milk intake
among 13 infants during the 1st year of life. The
mothers were all multiparous, non-smoking, White
women of middle- to upper-socioeconomic status
living in Denver, CO. All women in the study
practiced exclusive breast-feeding for at least
5 months. Solid foods were introduced at mean age
of 7 months. Daily milk intake was estimated by the
test weighing method with corrections for insensible
weight loss. Data were collected daily from birth to
14 days, weekly from weeks 3 through 8, and
monthly until the study period ended at 1 year after
inception. One infant was weaned at 8 months, while
all others were weaned on or after the 12 months.
Formula was used occasionally (< 240 mL/week)
after 4 months in three infants. Table 15-10 lists the
estimated human milk intakes for this study.
Converting values reported as g/day to mL/day, using
a conversion factor of 1.03 g/mL, mean human milk
intakes were 748 mL/day, 713 mL/day, 744 mL/day,
and 391 mL/day at 1, 3, 6, and 12 months of age,
respectively.
In comparison to the previously described studies,
Neville et al. (1988) collected data on numerous days
over a relatively long time period (12 months) and
they were corrected for insensible weight loss.
However, the intake rates presented in Table 15-10
are estimated based on intake only during a 24-hour
period. Consequently, these intake rates are based on
short-term data that do not account for day-to-day
variability among individual infants. Also, a smaller
number of subjects was included than in the previous
studies. Three infants were given some formula after
4 months. Without the raw data, these subjects could
not be excluded from the study results. Thus, data
presented for infants between 5 and 12 months may
underestimate the intake of exclusively breast-fed
infants.
15.3.5. Dewey et al. (1991a, b)—(a) Maternal
Versus Infant Factors Related to Human
Milk Intake and Residual Volume: The
DARLING Study; (b) Adequacy of
Energy Intake among Breast-Fed Infants
in the DARLING Study: Relationships to
Growth, Velocity, Morbidity, and Activity
Levels
The Davis Area Research on Lactation, Infant
Nutrition and Growth (DARLING) study was
conducted in 1986 to evaluate growth patterns,
nutrient intake, morbidity, and activity levels in
infants who were breast-fed for at least their first
12 months of life (Dewey et al., 1991a, b). Subjects
were non-randomly selected through letters to new
parents using birth listings. One of the criteria used
for selection was that mothers did not plan to feed
their infants more than 120 mL/day of other milk or
formula for the first 12 months of life. Seventy-three
infants aged 3 months were included in the study. At
subsequent time intervals, the number of infants
included in the study was somewhat lower as a result
of attrition. All infants in the study were healthy and
of normal gestational age and weight at birth, and
they did not consume solid foods until after they were
4 months old. The mothers were highly educated and
of "relatively high socioeconomic status."
Human milk intake was estimated by weighing
the infants before and after each feeding and
correcting for insensible water loss. Test weighings
were conducted over a 4-day period every 3 months.
The results of the study indicate that human milk
intake declines over the first 12 months of life. This
decline is associated with the intake of solid food.
When converting values reported as g/day to mL/day,
using a conversion factor of 1.03 g/mL, mean human
milk intake was estimated to be 788 mL/day, 747
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mL/day, 627 mL/day, and 435 mL/day at 3, 6, 9, and
12 months, respectively (see Table 15-11). Based on
the estimated intakes at 3 months of age, variability
between individuals (coefficient of variation ([CV] =
16.3%) was higher than the average day-to-day
variability ([CV] = 8.9 ± 5.4%)) for the infants in the
study (Dewey et al., 1991a).
The advantages of this study are that data were
collected over a relatively long-time (4 days) period
at each test interval, which would account for some
day-to-day infant variability, and corrections for
insensible water loss were made. Data from this study
are assumed to represent exclusively breast-fed
infants because mothers were specifically recruited
for that purpose. It is, however, unclear from the
Dewey et al. (1991a) study if this criterion was met
throughout the length of the study period.
15.3.6. Butte et al. (2000)—Infant Feeding Mode
Affects Early Growth and Body
Composition
Butte et al. (2000) conducted a study to assess the
effect of infant feeding mode on growth and body
composition during the first 2 years of life. The study
was conducted in the Houston, TX, area, recruited
through the Children's Nutrition Research Center
(CNRC) referral system. The study was approved by
the Baylor Affiliates Review Boards for Human
Subject Research. The overall sample was 76 healthy
term infants at 0.5, 3, 6, 9, 12, 18, and 24 months of
age. The sample size varied between 71 to 76 infants
for each age group. Repeated measurements for body
composition and anthropometric were performed.
The mothers agreed to either exclusively breast-feed
or formula feed the infants for the first 4 months of
life.
At 3-month or 6-month study intervals, the
feeding history was taken. The mothers or caretakers
were questioned about breast-feeding frequency, and
the use of formula, milk, juice, solids, water, and
vitamin or mineral supplements. Also, infant food
intake was quantified at 3, 6, 12, and 24 months with
a 3-day weighted intake record completed by the
mother or caretaker (Butte et al., 2000). The intake of
human milk was assessed by test weighing; the infant
weights were calculated before and after each
feeding. Using a pre-weighing and post-weighing
method, the intake of formula and other foods and
beverages was measured for 3 days by the mothers
using a digital scale and recorded on predetermined
forms.
The average duration of breast-feeding was
11.4 months (standard deviation [SD] = 5.8). Butte et
al. (2000) reported that infants were exclusively
breast-fed for at least the first 4 months—except for
one who was weaned at 109 days, another who
received formula at 102 days, and another who was
given cereal at 106 days. Table 15-12 shows the
infant feeding characteristics. Table 15-13 shows the
intakes of human milk for the infants. When
converting values reported as g/day to mL/day, using
a conversion factor of 1.03 g/mL, mean human milk
intake was estimated to be 728 mL/day at 3 months
(weighted average of boys and girls), 637 mL/day at
6 months (weighted average of boys and girls), and
403 mL/day at 12 months (weighted average of boys
and girls) (see Table 15-13). Table 15-14 shows
feeding practices by percentage for infants.
Table 15-15 provides the mean body weights of
breast-fed infants.
Advantages of this study are that it provides
intake data for breast-fed infants for their first
4 months. The study also provides the mean weights
for the infants by feeding type and by sex. The
limitations of the study are that the sample size is
small and limited to one geographical location. The
authors did not indicate if results were corrected for
insensible weight loss. Because mothers could
introduce formula after 4 months, only the data for
the 3-month old infants can be considered exclusively
breast-fed.
15.3.7. Arcus-Arth et al. (2005)—Human Milk
and Lipid Intake Distributions for
Assessing Cumulative Exposure and Risk
Arcus-Arth et al. (2005) derived population
distributions for average daily milk and lipid intakes
in g/kg-day for infants age 0-6 months and 0-
12 months for infants fed according to the AAP
recommendations. The AAP recommends exclusively
breast-feeding for the first 6 months of life, with
human milk as the only source of milk until age
1 year and the introduction of solid foods after
6 months. The distributions were derived based on
data in the peer-reviewed literature and data sets
supplied by the publication authors for infants 7 days
and older (Arcus-Arth et al., 2005). As cited in
Arcus-Arth et al. (2005), data sources included
Dewey et al. (1991a, b), HofVander et al. (1982),
Neubauer et al. (1993), Ferris et al. (1993),
Salmenpera et al. (1985), and Stuff and Nichols
(1989). The authors also evaluated intake rates for
infants breast-fed exclusively over the 1st year and
provided a regression line of intake versus age for
estimating short-term exposures. Arcus-Arth et al.
(2005) derived human milk intake rates for the entire
infant population (nursing and non-nursing) from
U.S. data on consumption, prevalence and duration.
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Arcus-Arthet al. (2005) defined exclusive breast-
feeding (EBF) as "breast milk is the sole source of
calories, with no or insignificant calories from other
liquid or solid food sources," and predominant
breast-feeding as "breast milk is the sole milk source
with significant calories from other foods." The data
that were consistent with AAP advice were used to
construct the AAP data set (Arcus-Arth et al., 2005).
The 0-12 months EBF data set was created using 0-
6 month AAP data and data from the EBF infants
older than 6 months of age. Because there are no data
in the AAP data set for any individual infant followed
at regular, frequent intervals during the 12-month
period, population distributions were derived with
assumptions regarding individual intake variability
over time (Arcus-Arth et al., 2005). Two methods
were used. In Method 1, the average population daily
intake at each age was described by a regression line,
assuming normality. Arcus-Arth et al. (2005) noted
that age specific intake data were consistent with the
assumption of normality. In Method 2, intake over
time was simulated for 2,500 hypothetical infants and
the distribution intakes derived from 2,500 individual
intakes (Arcus-Arth et al., 2005). The population
intake distribution was derived following Method 1.
Table 15-16 presents the means and standard
deviations for intake data at different ages; the
variability was greatest for the two youngest and
three oldest age groups. The values in Table 15-16
using Method 1 were used to derive the
recommendations presented in Table 15-1 because it
provides data for the fine age categories. When
converting values reported as g/day to mL/day, using
a conversion factor of 1.03 g/mL, mean human milk
intake was estimated to be 150 mL/kg-day at
1 month, 127 mL/kg-day at 3 months,
101 mL/kg-day at 6 months, and 47 mL/kg-day at
12 months (see Table 15-16). Time weighted average
intakes for larger age groups (i.e., 0-6 months, 0-
12 months) are presented in Table 15-17.
An advantage of this study is that it was designed
to represent the infant population whose mothers
follow the AAP recommendations. Intake was
calculated on a body weight basis. In addition, the
data used to derive the distributions were from peer-
reviewed literature and data sets supplied by the
publication authors. The distributions were derived
from data for infants fed in accordance to AAP
recommendations, and they most likely represent
daily average milk intake for a significant portion of
breast-fed infants today (Arcus-Arth et al., 2005).
The limitations of the study are that the data used
were from mothers who were predominantly White,
well-nourished, and from middle or high
socioeconomic status. Arcus-Arth et al. (2005) also
included data from Sweden and Finland. However,
human milk volume in mL/day is similar among all
women except for severely malnourished women
(Arcus-Arth et al., 2005). According to Arcus-Arth et
al. (2005): "Although few infants are exclusively
breast-fed for 12 months, the EBF distributions may
represent a more highly exposed subpopulation of
infants exclusively breast-fed in excess of 6 months."
15.4. KEY STUDIES ON LIPID CONTENT
AND LIPID INTAKE FROM HUMAN
MILK
Human milk contains more than 200 constituents,
including lipids, various proteins, carbohydrates,
vitamins, minerals, and trace elements as well as
enzymes and hormones. The lipid content of human
milk varies according to the length of time that an
infant nurses, and it increases from the beginning to
the end of a single nursing session (NAS, 1991). The
lipid portion accounts for approximately 4% of
human milk (3.9% ± 0.4%) (NAS, 1991). This value
is supported by various studies that evaluated lipid
content from human milk (Butte et al., 1984;
Mitoulas et al., 2002, 2003; Arcus-Arth et al., 2005;
Kent et al., 2006). Several studies also estimated the
quantity of lipid consumed by breast-feeding infants.
These values are appropriate for performing exposure
assessments for nursing infants when the
contaminant(s) have residue concentrations that are
indexed to the fat portion of human milk.
15.4.1. Butte et al. (1984)—Human Milk Intake
and Growth in Exclusively Breast-Fed
Infants
Butte et al. (1984) analyzed the lipid content of
human milk samples taken from women who
participated in a study of human milk intake among
exclusively breast-fed infants. The study was
conducted with more than 40 women during a
4-month period. Table 15-18 presents the mean lipid
content of human milk at various infants' ages. The
overall lipid content for the 4-month study period
was 3.43 ± 0.69% (3.4%). Butte et al. (1984) also
calculated lipid intakes from 24-hour human milk
intakes and the lipid content of the human milk
samples. Lipid intake was estimated to range from
22.9 mL/day (3.7 mL/kg-day) to 27.2 mL/day
(5.7 mL/kg-day).
The number of women included in this study was
small, and these women were selected primarily from
middle to high socioeconomic classes. Thus, data on
human milk lipid content from this study may not be
entirely representative of human milk lipid content
among the U.S. population. Also, these estimates are
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based on short-term data, and day-to-day variability
was not characterized.
15.4.2. Mitoulas et al. (2002)—Variation in Fat,
Lactose, and Protein in Human Milk
Over 24 h and Throughout the First Year
of Lactation
Mitoulas et al. (2002) conducted a study of
healthy nursing women to determine the volume and
composition of human milk during the 1st year of
lactation. Nursing mothers were recruited through the
Nursing Mothers' Association of Australia. All
infants were completely breast-fed on demand for at
least 4 months. Complementary solid food was
introduced between 4 and 6 months of age. Mothers
consumed their own ad libitum diets throughout the
study. Seventeen mothers initially provided data for
milk production and fat content, whereas lactose,
protein, and energy were initially obtained from nine
mothers. The number of mothers participating in the
study decreased at 6 months because of the cessation
of sample collection from 11 mothers, the maximum
period of exclusive breast-feeding.
Milk samples were collected before and after each
feed from each breast over a 24-28 hour period. Milk
yield was determined by weighing the mother before
and after each feed from each breast. Insensible water
loss was accounted for by weighing the mother
20 minutes after the end of each feeding. The rate of
water loss during this 20-minute period was used to
calculate insensible water loss during the feeding.
Samples of milk produced at the beginning of the
feeding (foremilk) and at the end of the feeding
(hindmilk) were averaged to provide the fat, protein,
lactose, and energy content for each feed. In all cases
the left and right breasts were treated separately;
therefore, TV represents the number of individual
breasts sampled.
Table 15-19 presents mean human milk
production and composition at each age interval. The
mean fat, lactose, and protein contents (g/L) were
37.4 (standard error [SE] = 0.6), 61.4 (SE = 0.6), and
9.2 (SE = 0.2), respectively. Composition did not
vary between left and right breasts or preferred and
non-preferred breasts. Milk production was constant
for the first 6 months and thereafter steadily declined.
Mitoulas et al. (2002) reported a mean 24-hour milk
production from both breasts was 798 (SD = 232)
mL. The fat content of milk decreased between 1 and
4 months before increasing to 12 months of lactation.
The concentration of protein decreased to 6 months
and then remained steady. Lactose remained constant
throughout the 12 months of lactation. The decrease
of energy at 2 months and subsequent increase by
9 months can be attributed to changes in fat content.
Assuming a density of human milk of 1.03 g/mL, the
overall fat content in human milk was 3.6%. Milk
production, as well as concentrations of fat, lactose,
protein, and energy, differed significantly between
women.
The focus of this study was on human milk
composition and production, not on infant's human
milk intake. The advantage of this study is that it
evaluated nursing mothers for a period of 12 months.
However, the number of mother-infant pairs in the
study was small (17 mothers with infants) and may
not be entirely representative of the U.S. population.
This study accounted for insensible water loss, which
increases the accuracy of the amount of human milk
produced.
15.4.3. Mitoulas et al. (2003)—Infant Intake of
Fatty Acids from Human Milk Over the
First Year of Lactation
Mitoulas et al. (2003) conducted a study of five
healthy nursing women to determine the content of
fat in human milk and fat intake by infants during the
1st year of lactation. Thirty nursing mothers were
recruited through the Australian Breast-feeding
Association or from private healthcare facilities. All
infants were completely breast-fed on demand for at
least 4 months. Complementary solid food was
introduced between 4 and 6 months of age. Mothers
consumed their own ad libitum diets throughout the
study.
Milk samples were collected before and after each
feed from each breast over a 24-28 hour period.
Fore- and hind-milk samples were averaged to
provide the fat content for each feed. Milk yield was
determined by weighing the mother before and after
each feed from each breast. Insensible water loss was
accounted for by weighing the mother 20 minutes
after the end of each feeding. The rate of water loss
during those 20 minutes was used to calculate
insensible water loss during the feeding.
Table 15-20 presents changes in volume of human
milk produced and milk fat content over the 1st year
of lactation. The mean volumes of milk produced for
both breasts combined were 813, 791, 912, 810, 677,
and 505 mL/day at 1, 2, 4, 6, 9, and 12 months,
respectively. The average daily production over the
12 months was 751 mL/day with a mean fat content
of 35.5 g/L. Assuming a density of human milk of
1.03 g/mL, the fat content in human milk was 3.4%
over the 12 month period. There was a significant
difference in the proportional composition of fatty
acids during the course of lactation. Table 15-21
provides average fatty acid composition during the
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first 12 months of lactation. Additionally, fatty acid
composition varied during the course of the day.
The focus of this study was on human milk
composition and production—not on infant's human
milk intake. The advantage of this study is that it
evaluated the human milk composition for a period of
12 months. However, the number of mother-infant
pairs in the study was small (five mothers with
infants) and may not be entirely representative of the
entire U.S. population. This study accounted for
insensible water loss, which increases the accuracy of
the amount of human milk produced.
15.4.4. Arcus-Arth et al. (2005)—Human Milk
and Lipid Intake Distributions for
Assessing Cumulative Exposure and Risk
Arcus-Arth et al. (2005) derived population
distributions for average daily milk and lipid intakes
in g/kg a day for infants 0-6 months and 0-
12 months of age for infants fed according to the
AAP recommendations. Lipid intakes were calculated
from lipid content and milk intakes measured on the
same infant (Arcus-Arth et al., 2005). Table 15-22
provides lipid intakes based on data from Dewey et
al. (1991a) and Table 15-23 provides lipid intakes
calculated assuming 4% lipid content and milk intake
in the AAP data set. The mean measured lipid content
ranged from 3.67%-4.16%, with a mean of 3.9%
over the 12 month period. Arcus-Arth et al. (2005)
noted that the distributions presented are intended to
represent the U.S. infant population.
An advantage of this study is that it was designed
to represent the population of infants who are breast-
fed according to the AAP recommendations. In
addition, the data used to derive the distributions
were from peer-review literature and data sets
supplied by the publication authors. The limitation of
the study are that the data used were from mothers
that were predominantly white, well-nourished, and
from mid- or upper-socioeconomic status; however,
human milk volume in mL/day is similar among all
women except for severely malnourished women
(Arcus-Arth et al., 2005). The authors noted that
"although few infants are exclusively breast-fed for
12 months, the exclusively breast-fed distributions
may represent a more highly exposed subpopulation
of infants exclusively breast-fed in excess of
6 months." The distributions were derived from data
for infants fed in accordance to AAP
recommendations, and they most likely represent
daily average milk intake for a significant portion of
breast-fed infants today (Arcus-Arth et al., 2005).
15.4.5. Kent et al. (2006)—Volume and
Frequency of Breast-Feeding and Fat
Content of Breast Milk Throughout the
Day
Kent et al. (2006) collected data from
71 Australian mothers who were exclusively nursing
their 1-6 month-old infants. The study focused on
examining the variation of milk consumed from each
breast, the degree of fullness of each breast before
and after feeding, and the fat content of milk
consumed from each breast during daytime and
nighttime feedings. The volume of milk was
measured using test-weighing procedures with no
correction for infant insensible water loss. On
average, infants had 11 ± 3 breast-feedings per day
(range = 6-18). The interval between feedings was
2 hours and 18 minutes ± 43 minutes (range =
4 minutes to 10 hours, 58 minutes). The 24-hour
average human milk intake was 765 ± 164 mL/day
(range = 464-1,317 mL/day). The fat content of milk
ranged from 22.3 g/L to 61.6 g/L (2.2%-6.0%) with
an average of 41.1 g/L (4.0%).
This study examined breast-feeding practices of
volunteer mothers in Australia. Although amounts of
milk consumed by Australian infants may be similar
to infants in the U.S. population, results could not be
broken out by smaller age groups to examine
variability with age. The study provides estimates of
fat content from a large number of samples.
15.5. RELEVANT STUDY ON LIPID INTAKE
FROM HUMAN MILK
15.5.1. Maxwell and Burmaster (1993)—A
Simulation Model to Estimate a
Distribution of Lipid Intake from Human
Milk During the First Year of Life
Maxwell and Burmaster (1993) used a
hypothetical population of 5,000 infants between
birth and 1 year of age to simulate a distribution of
daily lipid intake from human milk. The hypothetical
population represented both bottle-fed and breast-fed
infants aged 1-365 days. A distribution of daily lipid
intake was developed based on data in Dewey et al.
(1991b) on human milk intake for infants at 3, 6, 9,
and 12 months and human milk lipid content, and
survey data in Ryan et al. (1991) on the percentage of
breast-fed infants under 12 months (i.e.,
approximately 22%). A model was used to simulate
intake among 1,113 of the 5,000 infants expected to
be breast-fed. The results indicated that lipid intake
among nursing infants under 12 months can be
characterized by a normal distribution with a mean of
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26.0 mL/day and a standard deviation of 7.2 mL/day
(see Table 15-24). The model assumes that nursing
infants are completely breast-fed and does not
account for infants who are breast-fed longer than 1
year. Based on data collected by Dewey et al.
(1991b), Maxwell and Burmaster (1993) estimated
the lipid content of human milk to be 36.7 g/L at 3
months (35.6 mg/g or 3.6%), 39.2 g/L at 6 months
(38.1 mg/g or 3.8%), 41.6 g/L at 9 months (40.4 mg/g
or 4.0%), and 40.2 g/L at 12 months (39.0 mg/g or
3.9%).
The limitation of this study is that it provides a
snapshot of daily lipid intake from human milk for
breast-fed infants. These results also are based on a
simulation model and there are uncertainties
associated with the assumptions made. Another
limitation is that lipid intake was not derived for the
U.S. EPA recommended age categories. The
estimated mean lipid intake rate represents the
average daily intake for nursing infants under
12 months. The study also did not generate new data.
A reanalysis of previously reported data on human
milk intake and human milk lipid intake were
provided.
15.6. OTHER FACTORS
Many factors influence the initiation,
continuation, and amount of human milk intake.
These factors are complex and may include
considerations such as maternal nutritional status,
parity, parental involvement, support from lactation
consultants, mother's working status, infant's age,
weight, sex, food supplementation, the frequency of
breast-feeding sessions each day, the duration of
breast-feeding for each event, the duration of breast-
feeding during childhood, ethnicity, geographic area,
and other socioeconomic factors. For example, a
study conducted in the United Kingdom found that
social and educational factors most influenced the
initiation and continuation of lactation (Wright et al.,
2006). Prenatal and postnatal lactation consultant
intervention was found to be effective in increasing
lactation duration and intensity (Bonuck et al., 2005).
15.6.1. Population of Nursing Infants
Breast-feeding rates in the United States have
consistently increased since 1993. McDowell et al.
(2008) reported that the percentage of infants who
were ever breast-fed increased from 60% in 1993-
1994 to 77% among infants born in 2005-2006
according to the data from the National Health and
Nutrition Examination Surveys (NHANES). This
exceeded the goal of 75% set in the Healthy People
2010 McDowell et al. (2008). Rates among non-
Hispanic black women increased significantly from
36% in 1993-1994 to 65% in 2005-2006. Income
and age had a significant impact on breast-feeding
rates. Breast-feeding rates among higher income
women were 74% compared to 57% among lower
income women (McDowell et al., 2008).
In another study to monitor progress toward
achieving the Centers for Disease Control and
Prevention (CDC) Healthy People 2010 breast-
feeding objectives (initiation and duration), Scanlon
et al. (2007) analyzed data from the National
Immunization Survey (NIS). NIS uses random-digit
dialing to survey households to survey age-eligible
children, followed by a mail survey to eligible
children's vaccination providers to validate the
vaccination information. NIS is conducted annually
by the CDC to obtain national, state, and selected
urban area estimation on vaccinations rates among
U.S. children ages 19-35 months. The interview
response rate for years 2001-2006 ranged between
64.5% and 76.1%. Questions regarding breast-
feeding were added to the NIS survey in 2001. The
sample population was infants born during 2000-
2004. Scanlon et al. (2007) noted that because data in
their analysis are for children ages 19-35 months at
the time of the NIS interview, each cross-sectional
survey includes children from birth cohorts that span
3 calendar years; the breast-feeding data were
analyzed by year-of-birth during 2000-2004 (birth
year cohort instead if survey year).
Among infants born in 2000, breast-feeding rates
were 70.9% (CI = 69.0-72.8) for the postpartum
period (in hospital before discharge), 34.2%
(CI = 32.2-36.2) at 6 months, and 15.7 (CI = 14.2-
17.2) at 12 months. For infants born in 2004, these
rates had increased to 73.8% (CI = 72.8-74.8) for the
postpartum period, 41.5% (CI = 40.4-42.6) at 6
months, and 20.9 (CI = 20.0-21.8) at 12 months.
Rates of breast-feeding through 3 months were
lowest among black infants (19.8%), infants whose
mothers were <20 years of age (16.8%), those whose
mothers had a high school education or less (22.9%
and 23.9%), those whose mothers were unmarried
(18.8%), those who resided in rural areas (23.9%),
and those whose families had an income-to-poverty
ratio of <100% (23.9%). Table 15-25 shows data for
exclusive breast-feeding through 3 and 6 months by
socioeconomic characteristics for infants born in
2004.
Scanlon et al. (2007) noted the following
limitations could affect the utility of these data:
(1) breast-feeding behavior was based on
retrospective serf-report by mothers or other
caregivers, whose responses might be subject to
recall bias; (2) the NIS question defining early
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postpartum breast-feeding or initiation—"Was
[child's name] ever breast-fed or fed breast milk?"—
collects information that might differ from the
HP2010 objective for initiation; and (3) although
survey data were weighted to make them
representative of all U.S. children ages 19-
35 months, some bias might remain. The advantage
of the study is that is representative of the U.S. infant
population.
In 2007, CDC released the CDC Breast-feeding
Report Card, which has been updated every year
since. The CDC National Immunization Program in
partnership with the CDC National Center for Health
Statistics conducts the NIS within all 50 states, the
District of Columbia, and selected geographic areas
within the states. Five breast-feeding goals are in the
Healthy People 2010 report. The Breast-feeding
Report Card presents data for each state for the
following categories of infants: ever breast-fed,
breast-fed at 6 months, breast-fed at 12 months,
exclusive breast-feeding through 3 months, and
exclusive breast-feeding through 6 months (CDC,
2009). These indicators are used to measure a state's
ability to promote, protect, and support breast-
feeding. Table 15-26 presents these data for the
estimated percentage of infants born in 2006. The
advantage of this report is that it provides data for
each state and is representative of the U.S. infant
population.
Analysis of breast-feeding practices in other
developing countries also was found in the literature.
Marriott et al. (2007) researched feeding practices in
developing countries in the first year of life, based on
24-hour recall data. Marriott et al. (2007) used
secondary data from the Demographic and Health
Surveys (DHS) for more than 35,000 infants in
20 countries. This survey has been conducted since
1986 and was expanded to provide a standardized
survey instrument that can be used by developing
countries to collect data on maternal-infant health and
intake and household variables, as well as to build
national health statistics (Marriott et al., 2007). The
analysis was based on the responses of the survey
mothers for questions on whether they were currently
breast-feeding and had fed other liquids and solid
foods to their infants in the previous 24 hours. The
data incorporated were from between 1999 and 2003.
Marriott et al. (2007) selected the youngest infant
(i.e., less than 1 year old) in each of the families;
multiples were included such as twins or triplets.
Separate analyses were conducted for infants less
than 6 months old and infants 6 months and older, but
less than 12 months old. Food and liquid variables
other than water and infant formulas were collapsed
into broader food categories for cross-country
comparisons (Marriott et al., 2007). Tinned,
powdered, and any other specified animal milks were
collapsed. In addition, all other liquids such as herbal
teas, fruit juices, and sugar water (excluding unique
country-specific liquids) were collapsed into other
liquids and the 10 types of solid food groups into an
any-solid-foods category (Marriott et al., 2007). Data
were pooled from the 20 countries to provide a large
sample size and increase statistical power. Tables 15-
27 and 15-28 present the percentage of mothers who
were currently breast-feeding and separately had fed
their infants other liquids or solid food by age groups.
Table 15-29 presents the pooled data summary for the
study period. The current breast-feeding was
consistent across countries for both age groups; the
countries that reported the highest percentages of
current breast-feeding for the 0- to 6-month-old
infants also reported the highest percentages in the 6-
to 12-month-old infants. Pooled data show that
96.6% of the 0- to 6-month-old infants and 87.9% of
the 6- to 12-month-old infants were breast-feeding.
Feeding of other fluids was lowest in the 0- to 6-
month-old infants, with the percentage feeding water
the highest of this category. The percentage of
mothers feeding commercial infant formulas was the
lowest in most countries.
There are other older studies that analyze ethnic
and racial differences in breast-feeding practices. Li
and Grummer-Strawn (2002) investigated ethnic and
racial disparities in lactation in the United States
using data from the NHANES III that was conducted
between 1988 and 1994. NHANES II participants
were ages 2 months and older. The data were
collected during a home interview from a parent or a
proxy respondent for the child (Li and Grummer-
Strawn, 2002). The sample population consisted of
children 12-71 months of age at time of interview.
The NHANES III response rate for children
participating was approximately 94% (Li and
Grummer-Strawn, 2002). Data for a total of 2,863
exclusively breast-fed, 6,140 ever breast-fed, and
6,123 continued breast-fed children were included in
the analysis (Li and Grummer-Strawn, 2002). The
percentage of children ever breast-fed was 60%
among non-Hispanic Whites, 26% among
non-Hispanic Blacks, and 54% among Mexican
Americans. This percentage decreased to 27%, 9%,
and 23% respectively by 6 months. The percentage of
children fed exclusively human milk at 4 months also
was significantly lower for Blacks at 8.5%, compared
to 22.6% for Whites and 14.1% for Mexican
Americans. The racial and ethnic differences in
proportion of children ever breast-fed is presented in
Table 15-30, the proportion of children who received
any breast milk at 6 months are presented in
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Chapter 15—Human Milk Intake
Table 15-31, and the proportion of children
exclusively breast-fed at 4 months is presented in
Table 15-32.
Li and Grummer-Strawn (2002) noted that there
may have been some lag time between birth and the
time of the interview. This may have caused
misclassification if the predicator variables changed
considerably between birth and the time of interview.
Also, NHANES III did not collect information on
maternal education. Instead, the educational level of
the household head was used as a proxy. The
advantage of this study is that it is representative of
the U.S. children's population.
Data from some older studies provide historical
information on breast-feeding practices in the United
States. These data are provided in this chapter to
show trends in the U.S. population. In 1991, the
National Academy of Sciences (NAS) reported that
the percentage of breast-feeding women has changed
dramatically over the years (NAS, 1991). The Ross
Products Division of Abbott Laboratories conducted
a large national mail survey in 1995 to determine
patterns of breast-feeding during the first 6 months of
life. The Ross Laboratory Mothers' Survey was first
developed in 1955 and has been expanded to include
many more infants. Before 1991, the survey was
conducted on a quarterly basis, and approximately
40,000 to 50,000 questionnaires were mailed each
quarter (Ryan, 1997). Beginning in 1991, the survey
was conducted monthly; 35,000 questionnaires were
mailed each month. Over time, the response rate has
been consistently in the range of 50 ± 5%. In 1989
and 1995, 196,000 and 720,000 questionnaires were
mailed, respectively. Ryan (1997) reported rates of
breast-feeding through 1995 and compared them with
those in 1989.
The survey demonstrates increases in both the
initiation of breast-feeding and continued breast-
feeding at 6 months of age between 1989 and 1991.
Table 15-33 presents the percentage of breast-feeding
in hospitals and at 6 months of age by selected
demographic characteristics. In 1995, the incidence
of breast-feeding at birth and at 6 months for all
infants was approximately 59.7% and 21.6%,
respectively. The largest increases in the initiation of
breast-feeding between 1989 and 1995 occurred
among women who were black, were less than
20 years of age, earned less than $10,000 per year,
had no more than a grade school education, were
living in the South Atlantic region of the United
States, had infants of low birth weight, were
employed full time outside the home at the time they
received the survey, and participated in the Women,
Infants, and Children program (WIC). In 1995, as in
1989, the initiation of breast-feeding was highest
among women who were more than 35 years of age,
earned more than $25,000 per year, were
college-educated, did not participate in the WIC
program, and were living in the Mountain and Pacific
regions of the United States.
Data on the actual length of time that infants
continue to breast-feed beyond 5 or 6 months were
limited (NAS, 1991). However, Maxwell and
Burmaster (1993) estimated that approximately 22%
of infants under 1 year are breast-fed. This estimate
was based on a reanalysis by Ryan et al. (1991) of
survey data collected by Ross Laboratories (Maxwell
and Burmaster, 1993). Studies also have indicated
that breast-feeding practices may differ among ethnic
and socioeconomic groups and among regions of the
United States. More recently, the Ross Products
Division of Abbott Laboratories reported the results
of their ongoing Ross Mothers Survey in 2003
(Abbott Laboratories, 2003). Table 15-34 presents
the percentages of mothers who breast-feed, based on
ethnic background and demographic variables. These
data update the values presented in the NAS 1991
report.
15.6.2. Intake Rates Based on Nutritional Status
Information on differences in the quality and
quantity of human milk on the basis of ethnic or
socioeconomic characteristics of the population is
limited. Lonnerdal et al. (1976) studied human milk
volume and composition (nitrogen, lactose, proteins)
among underprivileged and privileged Ethiopian
mothers. No significant differences were observed
between the data for these two groups. Similar data
were observed for well-nourished Swedish mothers.
Lonnerdal et al. (1976) stated that these results
indicate that human milk quality and quantity are not
affected by maternal malnutrition. However, Brown
et al. (1986a, b) noted that the lactational capacity
and energy concentration of marginally nourished
women in Bangladesh were "modestly less than in
better nourished mothers." Human milk intake rates
for infants of marginally nourished women in this
study were 690 ± 122 g/day at 3 months,
722 ± 105 g/day at 6 months, and 719 ± 119 g/day at
9 months (Brown et al., 1986a). Brown et al. (1986a)
observed that human milk from women with larger
measurements of arm circumference and triceps
skinfold thickness had higher concentrations of fat
and energy than mothers with less body fat. Positive
correlations between maternal weight and milk fat
concentrations also were observed. These results
suggest that milk composition may be affected by
maternal nutritional status.
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Chapter 15—Human Milk Intake
15.6.3. Frequency and Duration of Feeding
HofVander et al. (1982) reported on the frequency
of feeding among 25 bottle-fed and 25 breast-fed
infants at ages 1, 2, and 3 months. The mean number
of meals for these age groups was approximately five
meals a day (see Table 15-35). Neville et al. (1988)
reported slightly higher mean feeding frequencies.
The mean number of meals per day for exclusively
breast-fed infants was 7.3 at ages 2-5 months and
8.2 at ages 2 weeks to 1 month. Neville et al. (1988)
reported that, for infants between the ages of 1 week
and 5 months, the average duration of a breast-
feeding session is 16-18 minutes.
Buckley (2001) studied the breast-feeding
patterns, dietary intake, and growth measurement of
children who continued to breast-feed beyond 1 year
of age. The sample was 38 mother-child pairs living
in the Washington, DC, area. The criteria for
inclusion in the study were that infants or their
mothers had no hospitalization of either subject
3 months prior to the study and that the mother was
currently breast-feeding a 1-year-old or older child
(Buckley, 2001). The participants were recruited
through local medical consultants and the La Leche
League members. The children selected as the final
study subjects consisted of 22 boys and 16 girls with
ages ranging from 12 to 43 months old. The data
were collected using a 7-day breast-feeding diary.
The frequency and length of breast-feeding varied
with the age of the child (Buckley, 2001). The author
noted a statistically significant difference in the mean
number of breast-feeding episodes each day and the
average total minutes of breast-feeding between the
1-, 2-, and 3-year-old groups. Table 15-36 provides
the comparison of breast-feeding patterns between
age groups. An advantage of this study is that the
frequency and duration data are based primarily on a
7-day diary and some dietary recall. Limitations of
the study are the small sample size and that it is
limited to one geographical area.
15.7. REFERENCES FOR CHAPTER 15
AAP (American Academy of Pediatrics). (2005)
Breast feeding and the use of human milk.
Policy statement. Pediatrics
115(2):496-506.
Abbott Laboratories. (2003) Breastfeeding trends -
2003. In: Ross Mothers Survey. Columbus,
OH: Ross Products Division.
Albernaz, E; Victora, CG; Haisma, H; Wright, A;
Coward, WA. (2003) Lactation counseling
increases breast-feeding duration but not
breastmilk intake as measured by isotopic
methods. JNutr 133:205-210.
Arcus-Arth, A; Krowech, G; Zeise, L. (2005) Human
milk and lipid intake distributions for
assessing cumulative exposure and risk. J
Expos Anal Environ Epidemiol 15:357-365.
Bonuck, KA; Trombley, M; Freeman, K; McKee, D.
(2005) Randomized, controlled trial of a
prenatal and postnatal lactation consultant
intervention on duration and intensity of
breastfeeding up to 12 months. Pediatrics
116(6):1413-1426.
Brown, KH; Akhtar, NA; Robertson, AD; Ahmed,
MG. (1986a) Lactational capacity of
marginally nourished mothers: relationships
between maternal nutritional status and
quantity and proximate composition of milk.
Pediatrics 78(5):909-919.
Brown, KH; Robertson, AD; Akhtar, NA. (1986b)
Lactational capacity of marginally nourished
mothers: infants' milk nutrient consumption
and patterns of growth. Pediatrics
78:920-927.
Buckley, K. (2001) Long-term breastfeeding:
nourishment or nurtance. J Hum Lactat
17(4):304-311.
Butte, NF; Garza, C; Smith, EO; Nichols, BL. (1984)
Human milk intake and growth in
exclusively breast-fed infants. J Pediatr
104(2): 187-195.
Butte, N; Wong, W; Hopkinson, J; Smith, EO; Ellis,
KJ. (2000) Infant feeding mode affects early
growth and body composition. Pediatrics
106(6): 1355-1366.
CDC (Centers for Disease Control and Prevention).
(2009) Breastfeeding report card 2008.
Breastfeeding practices-results from the
National Immunization Survey. Available at
http://www.cdc.gov/breastfeeding/pdf/2009
BreastfeedingReportCard.pdf.
Chen, A; Rogan, WJ. (2004) Breastfeeding and the
risk of postneonatal death in the United
States. Pediatrics 113:435-439.
Dewey, KG; Lonnerdal, B. (1983) Milk and nutrient
intake of breast-fed infants from 1 to
6 months: Relation to growth and fatness. J
Pediatr Gastroenterol Nutr 2:497-506.
Dewey, KG; Heinig, J; Nommsen, LA; Lonnerdal, B.
(1991a) Maternal versus infant factors
related to human milk intake and residual
volume: the DARLING study. Pediatrics
87(6):829-837.
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Chapter 15—Human Milk Intake
Dewey, KG; Heinig, J; Nommsen, L; Lonnerdal, B.
(1991b) Adequacy of energy intake among
breast-fed infants in the DARLING study:
relationships to growth, velocity, morbidity,
and activity levels. J Pediatr
119(4):538-547.
Dewey, KG; Peerson, JM; Heinig, MJ; Nommsen,
LA; Lonnerdal, B; Lopez de Romana, G; de
Kanashiro, HC; Black, RE; Brown, KH.
(1992) Growth patterns of breast-fed infants
in affluent (United States) and poor (Peru)
communities: implications for timing of
complementary feeding. Am J Clin Nutr
56(6): 1012-1018.
Drewett, R; Amatayakul, K; Wongsawasdii, L;
Mangkiabruks, A; Ruckpaopunt, S;
Ruangyuttikarn, C; Baum, D; Imong, S;
Jackson, D; Woolridge, M. (1993) Nursing
frequency and the energy intake from breast
milk and supplementary food in a rural Thai
population: a longitudinal study. Eur J Clin
Nutr47(12):880-891.
Ferris, AM; Neubauer, SH; Bendel, RB; Green, KW;
Ingardia, CJ; Reece, EA. (1993) Perinatal
lactation protocol and outcome in mothers
with and without insulin-dependent diabetes
mellitus. Am J Clin Nutr 58:43^8.
Gonzalez-Cossio, T; Habicht, JP; Rasmussen, KM;
Delgado, HL. (1998) Impact of food
supplementation during lactation on infant
breast-milk intake and on the proportion of
infants exclusively breast-fed. J Nutr
128(10):1692-1702.
HofVander, Y; Hagman, U; Hillervik, C; Sjolin,S.
(1982) The amount of milk consumed by
1-3 months old breast or bottled-fed
infants. Acta Paediatrica Scand
71(6):953-958.
Kent, JC; Mitoulas, LR; Cregan, MD; Ramsay, DT;
Doherty,DA; Hartmann, PE. (2006) Volume
and frequency of breastfeeding and fat
content of breast milk throughout the day.
Pediatrics 117(3):387-395.
Li, R; Grummer-Strawn, L. (2002) Racial and ethnic
disparities in breastfeeding among Unites
States infants: third national health and
nutrition examination survey, 1988 - 1994.
Birth 29(4):251-257.
Lonnerdal, B; Forsum, E; Gebre-Medhim, M;
Hambraeus, L. (1976) Breast milk
composition in Ethiopian and Swedish
mothers. II. Lactose, nitrogen, and protein
contents. Am J Clin Nutr
29(10):1134-1141.
Marriott, M; Campbell, L; Hirsch, E; Wilson, D.
(2007) Preliminary data from demographic
and health surveys on infant feeding in 20
developing countries. J Nutr
137(2):518S-523S.
Maxwell, NI; Burmaster, DE. (1993) A simulation
model to estimate a distribution of lipid
intake from human milk during the first year
of life. J Expo Anal Environ Epidemiol
3:383-406.
McDowell, M; Wang, C; Kennedy-Stephenson, J.
(2008) Breastfeeding in the United States:
Findings from the National Health and
Nutrition Examination Surveys, 1999-2006.
NCHS Data Brief, No. 5.
Mitoulas, L; Kent, J; Cox, D; Owens, RA; Sheriff,
JL; Hartmann, PE. (2002) Variation in fat,
lactose, and protein in human milk over 24 h
and throughout the first year of lactation. Br
J Nutr 88:29-37.
Mitoulas, L; Gurrin, L; Doherty, D; Sherriff, JL;
Hartmann, PE. (2003) Infant intake of fatty
acids from human milk over the first year of
lactation. Br JNutr 90(5):979-986.
NAS (National Academy of Sciences). (1991)
Nutrition during lactation. Washington, DC:
National Academies Press.
Neubauer, SH; Ferris, AM; Chase, CG; Fanelli, J;
Thompson, CA; Lammi-Keefe, CJ; Clark,
RM; Jensen, RG; Bendel, RB; Green, KW.
(1993) Delayed lactogenesis in women with
insulin-dependent diabetes mellitus. Am J
Clin Nutr 58:54-60.
Neville, MC; Keller, R; Seacat, J; Lutes, V; Neifert,
M; Casey, C; Allen, J; Archer, P. (1988)
Studies in human lactation: Milk volumes in
lactating women during the onset of
lactation and full lactation. Am J Clin Nutr
48(6): 1375-1386.
Pao, EM; Hines, JM; Roche, AF. (1980) Milk intakes
and feeding patterns of breast-fed infants. J
Am Diet Assoc 77:540-545.
Ryan, AS. (1997) The resurgence of breastfeeding in
the United States. Pediatrics 99(4):el2.
http://pediatrics.aappublications.org/cgi/cont
ent/full/99/4/e!2.
Ryan, AS; Rush, D; Krieger, FW; Lewandowski, GE.
(1991) Recent declines in breast-feeding in
the United States, 1984 through!989.
Pediatrics 88(4):719-727.
Salmenpera, L; Perheentupa, J; Siimes, MA. (1985)
Exclusively breast-fed healthy infants grow
slower than reference infants. Pediatr Res
19:307-312.
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Scanlon, KS; Grummer-Strawn, L; Shealy, KR;
Jefferds, ME; Chen, J. (2007) Breastfeeding
trends and updated national health
objectives for exclusive breastfeeding -
United States, birth years 2000-2004.
MMWR 56(30):760-763.
Stuff, JE; Nichols, BL. (1989) Nutrient intake and
growth performance of older infants fed
human milk. JPediatr 115:959-968.
Wright, CM; Parkinson, K; Scott, J. (2006) Breast-
feeding in a UK urban context: Who breast-
feeds, for how long and does it matter?
Public Health Nutr 9(6):686-691.
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Age
Completely Breast-fed
1 month
3 months
6 months
Partially Breast-fed
1 month
3 months
6 months
9 months
a Data expressed as mean ±
Source: Pao etal., 1980.
Table 15-7. Daily
Number of Infants
11
2
1
4
11
6
3
standard deviation.
Intakes of Human Milk
Intake
Mean ± SD (mL/day) a
600 ±159
833
682
485 ± 79
467 ±100
395 ±175
<554
Intake Range (mL/day)
426-989
645-1,000
616-786
398-655
242-698
147-684
451-732
Table 15-8. Human Milk Intakes for Infants Aged 1-6 Months
Age
1 month
2 months
3 months
4 months
5 months
6 months
Number of Infants
16
19
16
13
11
11
Intake
Mean ± SD (mL/day)
673 ±192
756 ±170
782 ±172
810 ±142
805 ±117
896 ± 122
Intake Range (mL/day)
341-1,003
449-1,055
492-1,053
593-1,045
554-1,045
675-1,096
Source: Dewey and Lonnerdal, 1983.
Table 15-9. Human Milk Intake Among Exclusively Breast-Fed Infants During the First 4
a
b
SD
Age Number of Infants
1 month 37
2 months 40
3 months 37
4 months 41
Intake (mL/day )a
Mean ± SD
729 ± 126
704 ± 127
702 ±111
718 ±124
Values reported by the author in units of g/day and
dividing by 1.03 g/mL (density of human milk).
Calculated by dividing human milk intake (g/day) by
= Standard deviation.
Intake (mL/kg-day)a „ ,. „
r GGQ1HS S/L)£
Mean ± SD fe
154±23 8. 3 ±1.9
125 ±18 7.2 ±1.9
114±19 6.8±1.9
108 ±17 6.7 ±1.8
g/kg-day were converted to units of mL/day
human milk intake (g/kg-day).
Months of Life
Body Weightb
4.7
5.6
6.2
6.7
and mL/kg-day by
Source: Butteetal, 1984.
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Table 15-10. Human Milk Intake During a 24-Hour Period
, , . Number
(days)
a
b
c
SD
Source
1
2
3
4
5
6
7
8
9
10
11
14
21
28
35
42
49
56
90
120
150
180
210
240
270
300
330
360
of Infants
6
9
10
10
11
9
7
8
9
9
8
9
10
13
12
12
10
12
10
12
12
13
12
9
12
11
8
8
Intake (mL/day)a
Mean ± SD
43 ±68
177 ± 83
360 ±149
438 ±171
483 ± 125
493 ± 162
556 ±162
564 ±154
563 ± 74
569 ±128
597 ±163
634 ±150
632 ± 82
748 ± 174
649 ±114
690 ± 108
688 ±112
674 ± 95
713 ±111
690 ± 97
814 ±130
744 ±117
700 ± 150
604 ± 204
600 ±214
535 ±227
538 ±233
391 ±243
Range
-30-145C
43-345
203-668
159-674
314-715
306-836
394-817
398-896
456-699
355-841
386-907
404-895
538-763
481-1,111
451-903
538-870
543-895
540-834
595-915
553-822
668-1,139
493-909
472-935
280-973
217-846
125-868
117-835
63-748
Intake by Age
Category
(mL/day)3' b
511 ±220
679 ± 105
713 ±111
690 ± 97
814 ±130
744 ±117
700 ± 150
604 ± 204
600 ±214
535 ± 227
538 ±233
391 ±243
Values reported by the author in units of g/day were converted to units of mL/day by dividing by
1.03 g/mL (density of human milk).
Multiple data sets were combined by producing simulated data sets fitting the known mean and SD for
each age, compositing the data sets to correspond to age groups of 0 to <1 month and 1 to <2 months, and
calculating new means and SD's on the composited data.
Negative value due to insensible weight loss correction.
= Standard deviation.
: Neville etal., 1988
Page
15-22
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
a
SD
Source
Table 15-11. Human Milk Intake Estimated by
Age Number of Infants
3 months 73
6 months 60
9 months 50
12 months 42
Values reported by the author in units of g/day were
dividing by 1.03 g/mL (density of human milk).
= Standard deviation.
Deweyetal., 1991b.
the Darling Study
Intake (mL/day)a
Mean ± SD
788 ±129
747 ± 166
627 ±211
435 ± 244
converted to units of mL/day by
Table 15-12. Mean
Ethnicity (White, Black, Hispanic, Asian) (N)
Duration of Breast-feeding (days)
Duration of Formula Feeding (days)
Age at Introduction of Formula (months)
Age at Introduction of Solids (months)
Age at Introduction of Cow's Milk (months)
a Mean ± standard deviation.
N = Number of infants.
Source: Butte etal., 2000.
Breast-Fed Infants Characteristics"
Boys (N= 14)
10/1/2/1
315 ±152
184 ±153
6.2 ±2.9
5.0 ±1.5
13.1±3.1
Girls (N= 26)
21/1/3/1
362 ±190
105 ±121
5.2 ±2.3
5.0 ±0.09
12.5 ±3.8
Table 15-13. Mean Human Milk Intake of Breast-Fed Infants (mL/day)a
Age Group Boys Girls
3 months 790 ± 172 (N = 14) 694 ± 108 (N = 26)
6 months 576 ± 266 (N = 12) 678 ± 250 (N = 18)
12 months 586 ± 286 (N= 2) 370 ± 260 (N= 11)
24 months
a 3-day average; values reported by the author in units of g/day were converted to units of mL/day by
dividing by 1.03 g/mL (density of human milk); mean ± standard deviation.
TV = Number of infants.
= Not quantitated.
Source: Butte et al., 2000.
Exposure Factors Handbook Page
September 2011 15-23
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-14. Feeding Practices by Percent of Infants
Age
Infants 3
months
6 9
months months
12
months
18
months
24
months
Percentage
Infants Still Breast-fed 100
Breast-fed Infants Given Formula 0
Formula-Fed Infants Given Breast Milk 100
Use of Cow's Milk for Breast-fed Infants
Use of Cow's Milk for Formula-Fed Infants
80 58
40 48
100 94
8
28
38
30
47
65
67
25
10
6
82
89
5
2
0
88
92
Source: Butte et al., 2000.
Table 15-15.
Body Weight of Breast-Fed
Infants3
Weight (kg)
Age
0.5 months
3 months
6 months
9 months
12 months
18 months
24 months
Boys
3.9±0.4(w =
6.4 ± 0.6 (n =
8.1±0.8(w =
9.3±1.0(w =
10.1 ± !.!(« =
11.6 ± 1.2 (n =
12.7 ± 1.3 (« =
14)
14)
14)
14)
14)
14)
12)
Girls
3.7±0.5(w =
6.0 ± 0.6 (n =
7.5 ± 0.6 (n =
8.4 ± 0.6 (n =
9.2 ± 0.7 (n =
10.7 ± 1.0 (n =
11.8 ± 1.1 (H =
19)
19)
18)
19)
19)
19)
19)
a Mean ± standard deviation.
n = Number of infants.
Source: Butte etal., 2000.
Page
15-24
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-16. AAP Data Set Milk Intake Rates at Different Ages
Mean SD
ge (mL/kg-day)a (mL/kg-day)a
a
b
SD
CV
N
7 days
14 days
30 days
60 days
90 days
120 days
150 days
180 days
210 days
270 days
360 days
143
156
150
144
127
112
100
101
75
72
47
37
40
24
22
18
18
21
20
25
23
27
CV
0.26
0.26
0.16
0.15
0.14
0.16
0.21
0.20
0.33
0.32
0.57
Skewness
Statistic15
0.598
-1.39
0.905
0.433
-0.168
0.696
-1.077
-1.860
-0.844
-0.184
0.874
Values reported by the author in units of g/kg-day were converted to units
dividing by 1.03 g/mL (density of human milk).
Statistic/SE: -2 < Statistic/SE < +2 suggests a normal distribution.
= Standard deviation.
N
10
9
25
25
108
57
26
39
8
57
42
of mL/kg-day by
= Coefficient of variation.
= Number of infants.
Source: Arcus-Arth et al
,2005.
Table
Averaging Period IV
AAP 0 to 6 months
Method 1
Method 2
AAP 0 to 12 months
Method 1
Method 2
EBF 0 to 12 months
General Pop.
0 to 6 months
0 to 12 months
15-17. Average Daily Human Milk Intake (mL/kg-day)a
Trnn f^Fi^
126(21)
Population Percentile
5
92
123(7) 112
98 (22)
99(5)
110(21)
79
51
61
90
75
0
0
a Values reported by the author in units
1.03 g/mL (density of human milk).
AAP = American Academy of Pediatrics.
EBF = Exclusively breast-fed.
10
99
114
69
92
83
0
0
of g/kg-day
25
112
118
83
95
95
24
12
were
50
126
123
98
99
110
92
49
converted to
75
140
127
113
102
124
123
85
units
90
152
131
127
105
137
141
108
of mL/kg-day
95
160
133
135
107
144
152
119
99
174
138
150
110
159
170
138
by dividing by
Source: Arcus-Arth et al., 2005.
Exposure Factors Handbook
September 2011
Page
15-25
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-Fed
Infants
Age
(months)
1
2
o
J
4
Number
of
Observations
37
40
37
41
Lipid Content
(mg/g)
Mean ± SD
36.2 ±7.5
34.4 ±6.8
32.2 ±7.8
34.8 ± 10.8
Lipid
Content %a
3.6
3.4
3.2
3.5
a Percents calculated from lipid content reported in mg/g.
b Values reported by the author in units of g/day and g/kg-day were
day by dividing by 1.03 g/mL (density of human milk).
Source: Butte et al, 1984.
Lipid
Intake
(mL/day)b
Mean ± SD
27 ±8
24 ±7
23 ±7
25 ±8
converted to units
Lipid
Intake
(mL/kg-day)b
Mean ± SD
5.7 ±1.7
4.3 ±1.2
3.7 ±1.2
3.7 ±1.3
of mL/day and mL/kg-
Table 15-19. Human Milk Production
and Composition During
Volume, per Fat
Age Group Breast (mL/24 (g/L)
(months) hours)
1
2
4
6
9
12
Ito
a
SE
N
Source
Mean SE TV Mean
416 24 34 39.9
408 23 34 35.2
421 20 34 35.4
413 25 30 37.3
354 47 12 40.7
252 51 10 40.9
12 399 11 154 37.4
SE
1.4
1.4
1.4
1.4
1.7
3.3
0.6
Infants were completely breast-fed to
and 6 months.
= Standard error.
= Number of individual breasts.
Mitoulas et al., 2002.
N
34
34
32
28
12
10
150
Lactose
(g/L)
Mean
59.7
60.4
62.6
62.5
62.8
61.4
61.4
4 months and
SE
0.8
1.1
1.3
1.7
1.5
2.9
0.6
N
18
18
16
16
12
10
90
the First 12 Months of Lactation"
Protein
(g/L)
Mean
10.5
9.6
9.3
8.0
8.3
8.3
9.2
SE
0.4
0.4
0.4
0.4
0.5
0.6
0.2
complementary solid food
N
18
18
18
16
12
10
92
was
Energy
(kJ/mL)
Mean
2.7
2.5
2.6
2.6
2.8
2.8
2.7
SE
0.06
0.06
0.09
0.09
0.09
0.14
0.04
N
18
18
16
16
12
10
90
introduced between 4
Page
15-26
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table
15-20. Changes in Volume of Human Milk Produced and Milk Fat Content During the
of Lactation"
Age Grnup
(months)
1
1
2
4
6
9
12
to 12
Volume, Left
Breast (mL/day)
TV Mean
5
5
5
5
5
5
30
Statistical
338
364
430
373
312
203
337
NS
SE
52
52
51
75
65
69
26
Volume, Right Breast
(mL/day)
Mean
475
427
482
437
365
302
414
NS
SE
69
42
58
56
94
85
28
First Year
Fat, Left Breast Fat, Right Breast
(g/L) (g/L)
Mean
38
31
32
33
43
40
36
0.004
SE
1
2
3
2
2
4
1
5
2
3
5
2
8
4
Mean
38
30
29
33
38
42
35
0.008
SE
2.6
2.9
2.6
2.5
3.3
5.0
1.5
significance: P
a
Infants were
completely breast-fed to
4 months,
and complementary
solid
food was
introduced
between 4 and 6 months.
N
SE
NS
P
Source
= Number of mothers.
= Standard error.
= No statistical difference.
= Probability
: Mitoulasetal., 2003.
Table 15-21. Changes in Fatty Acid Composition of Human Milk During the First Year of Lactation (g/100 g
total fatty acids)
Fatty Acid
Medium-Chain
Saturated
Odd-Chain
Saturated
Long-Chain
Saturated
Mono-
Unsaturated
Trans
Poly-
Unsaturated
1 month 2 months 4 months 6 months
Mean
14.2
0.9
34.1
37.5
2.0
12.7
SE Mean SE Mean SE Mean SE
0.4 13.9 0.6 12.0 0.5 11.5 0.2
0.01 0.9 0.02 0.8 0.02 0.8 0.03
0.3 33.7 0.3 32.8 0.3 31.8 0.6
0.2 33.7 0.4 38.6 0.5 37.5 0.5
0.08 2.2 0.1 2.2 0.09 4.6 0.02
0.2 9.5 0.2 11.8 0.4 13.4 0.6
9 months 12 months
Mean SE Mean SE
14.1 0.3 17.0 0.4
0.8 0.02 0.8 0.02
31.4 0.6 33.9 0.6
37.3 0.5 33.0 0.5
1.7 0.2 1.8 0.09
8.0 0.1 6.7 0.03
SE = Standard error.
Source: Mitoulas
etal.,
2003.
Exposure Factors Handbook
September 2011
Page
15-27
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-22. Comparison Daily Lipid Intake Based on Lipid Content Assumptions (mL/kg-day)a'b
Lipid Content Used in . . Population Percentile
Mean
Calculation 5 10 25 50 75 90 95 99
Measured Lipid Content0 3.6 2.0 2.3 2.9 3.6 4.3 4.9 5.2 5.9
4% Lipid Contentd 3.9 2.5 2.8 3.3 3.8 4.4 4.9 5.2 5.8
a Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by dividing
by 1.03 g/mL (density of human milk).
b Estimates based on data from Dewey et al. (1991a).
0 Lipid intake derived from lipid content and milk intake measurements.
d Lipid intake derived using 4% lipid content value and milk intake.
Source: Arcus-Arth et al., 2005.
Table
15-23. Distribution of Average Daily
Mean —
AAP Infants 0-12 months 3.9
a
AAP
Source
Values reported by the author in units
1.03 g/mL (density of human milk).
= American Academy of Pediatrics.
: Arcus-Arth et al., 2005.
Lipid
Intake
(mL/kg-day) Assuming 4%
Milk Lipid
Content
a
Population Percentile
5
2.4
10
2.8
25
3.3
50
3.9
of g/kg-day were converted to
75
4.5
90
5.1
units of mL/kg-day
95
5.4
99
6
by dividing
0
;by
Table 15-24. Predicted Lipid Intakes for Breast-Fed Infants Under 12 Months of Age
Statistic
Number of Observations in Simulation
Minimum Lipid Intake
Maximum Lipid Intake
Arithmetic Mean Lipid Intake
Standard Deviation Lipid Intake
a Values reported by the author in units
(density of human milk).
Source: Maxwell and Burmaster, 1993.
Value
1,113
1.0 mL/daya
51.0mL/daya
26.0 mL/daya
7.2 mL/daya
of g/day were converted to units of mL/day by dividing by 1.03 g/mL
Page Exposure Factors Handbook
15-28 September 2011
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-25. Socioeconomic Characteristics of Exclusively Breast-Fed Infants Born in
2004
Percent of Exclusive Breast-Feeding
Characteristic
U.S. Overall (N= 17,654)
%
30.5
3 months
95% CI
29.4-31.6
Infants Through 3 and 6 Months
%
11.3
6 months
95% CI
10.5-12.1
Infant Sex
Male
Female8
30.7
30.3
29.1-32.3
28.7-31.9
10.8
11.7
9.8-11.8
10.5-12.9
Race/Ethnicity (child)
Hispanic
White, non-Hispanica
Black, non-Hispanic
Asian, non-Hispanic
Other
30.8
33.0
19. 8b
30.6
29.3
28.3-33.3
31.6-34.4
17.0-22.6
25.0-36.2
24.9-33.7
11.5
11.8
7.3b
14.5
12.2
9.7-13.3
10.9-12.7
5.5-9.1
10.0-19.0
9.2-15.2
Maternal Age (years)
<20
20 to 29
>30a
16.8b
26.2b
34.6
10.3-23.3
24.4-28.0
33.2-36.0
6.1b
8.4b
13.8
1.5-10.7
7.3-9.5
12.7-14.9
Household Head Education
350a
23.9b
26.6b
33.2b
37.7
a Referent group.
b p< 0.05 by chi-square test, compared
N = Number of infants.
MSA = Metropolitan statistical area.
Source: Scanlon et al., 2007.
21.6-26.2
23.8-29.4
30.9-35.5
35.7-39.7
with referent group.
8.3b
8.9b
11. 8b
14.0
6.9-9.7
7.2-10.6
10.3-13.3
12.6-15.4
Exposure Factors Handbook
September 2011
Page
15-29
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children Born in
2006a
State
U.S. National
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Ever
Breast-Fed
73.9
58.8
88.5
76.5
61.5
84.7
82.5
74.9
66.7
69.6
75.7
62.5
88.2
79.8
69.5
71.1
68.1
78.1
53.6
49.1
75.0
76.4
78.2
64.8
79.9
48.3
65.3
82.7
Breast-Fed
at 6 Months
43.4
26.6
48.9
45.3
26.9
53.0
59.5
41.9
32.8
45.6
37.2
36.4
56.3
55.1
38.7
37.2
33.2
43.8
28.9
20.7
45.7
43.3
44.7
31.2
51.6
20.1
33.1
56.8
Breast-Fed Exclusive Breast-
at 12 Feeding Through
Months 3 Months
22.7
11.4
26.2
22.3
10.6
31.1
30.5
23.3
15.4
20.2
18.2
18.1
35.0
25.3
15.9
18.9
15.8
23.6
15.8
9.9
26.0
25.4
24.5
14.4
24.7
8.7
14.9
30.6
33.1
24.2
45.5
29.7
23.6
42.4
49.2
35.1
28.1
31.3
30.7
28.0
44.9
46.7
28.5
28.9
32.3
36.0
27.2
17.8
38.7
28.5
39.0
23.5
39.8
16.8
24.8
40.8
Exclusive Breast-
Feeding Through
6 Months
13.6
6.3
16.9
11.9
6.3
18.6
22.6
14.4
7.5
13.3
11.9
14.8
22.4
17.7
11.9
10.6
10.6
16.8
9.4
5.0
18.1
10.1
13.5
10.7
15.0
4.6
8.5
20.5
Page
15-30
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children Born in
2006a (continued)
Ever
State Breast-Fed
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
76.8
79.3
78.4
81.4
72.6
76.4
66.9
71.1
58.5
65.6
91.4
67.6
75.4
61.3
76.8
58.8
78.2
92.8
80.1
79.7
86.4
58.8
75.3
84.2
a Exclusive breast-feeding
as ONLY breast milk: no
Source: CDC, 2009.
Breast-Fed Exclusive Breast- Exclusive Breast-
Breast-Fed at 12 Feeding Through Feeding Through
at 6 Months Months 3 Months 6 Months
46.2
45.3
55.1
53.0
42.2
49.4
36.7
37.6
29.7
27.4
63.0
35.8
40.4
30.4
47.5
37.9
48.7
69.5
59.5
48.3
58.0
27.2
48.6
50.8
information is from
solids, no water, no
22.6
22.5
30.5
27.4
25.7
28.9
18.9
20.6
12.0
12.4
37.0
19.4
19.8
13.9
22.1
14.8
25.3
33.9
38.4
25.8
35.0
12.6
25.9
26.7
the 2006 NIS
other liquids.
31.7
31.8
42.6
29.7
33.2
24.9
30.2
33.7
22.4
30.6
56.6
29.3
31.8
25.5
36.5
28.2
34.2
50.8
49.2
38.7
48.8
21.3
45.2
46.2
survey data only
11.9
9.7
20.6
13.2
14.0
9.6
13.1
11.1
9.1
8.4
20.8
10.1
8.7
9.6
17.6
12.8
14.2
24.0
23.5
18.8
25.3
8.4
16.8
16.8
and is defined
Exposure Factors Handbook
September 2011
Page
15-31
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6 Months
Old3
Country
Armenia
Bangladesh
Cambodia
Egypt
Ethiopia
Ghana
India
Indonesia
Jordan
Kazakhstan
Kenya
Malarwi
Nambia
Nepal
Nigeria
Philippines
Uganda
Vietnam
Zamibia
Zimbabwe
Pooled
Breast-Feeding
86.1
99.6
98.9
95.5
98.8
99.6
98.1
92.8
92.4
94.4
99.7
100
95.3
100
99.1
80.5
98.7
98.7
99.6
100
96.6
Water
62.7
30.2
87.9
22.9
26.3
41.9
40.2
37
58.5
53.7
60
46
65.4
23.3
78.2
53.4
15.1
45.9
52.6
63.9
45.9
a Percentage of mothers who stated that they
categories of liquid or solid food in the past
Milk
22.9
13.6
2.1
11.1
19
6.7
21.2
0.7
3
21.4
35.1
1.4
0
12.3
9.2
4.4
20.3
16.9
2.1
1.6
11.9
Formula
13.1
5.3
3.3
4.3
0
3.5
0
24.2
25.1
8.2
4.8
1.7
0
0
12.7
30
1.5
0.8
2.7
3.2
9
Other Liquids
48.1
19.7
6.7
27.6
10.8
4.3
7.1
8.7
13.8
37.4
35.9
5.2
17.9
2.8
17.9
12.4
10.3
8.9
6.7
9
15.1
Solid Foods
23.9
20.3
16.6
13.2
5.3
15.6
6.5
43
20.2
15.4
46.3
42.3
33.4
9.3
18.5
16.8
11.4
18.7
31.2
43.7
21.9
currently breast-feed and separately had fed their infants four
24 hours by country for infants age 0 to 6 months old.
Source: Marriott etal., 2007.
Page Exposure Factors Handbook
15-32 September 2011
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12 Months
Old3
Country
Armenia
Bangladesh
Cambodia
Egypt
Ethiopia
Ghana
India
Indonesia
Jordan
Kazakhstan
Kenya
Malarwi
Nambia
Nepal
Nigeria
Philippines
Uganda
Vietnam
Zamibia
Zimbabwe
Pooled
Breast-Feeding
53.4
96.2
94.4
89.1
99.4
99.3
94.9
84.8
65.7
81.2
96.5
99.4
78.7
98.8
97.8
64.4
97.4
93.2
99.5
96.7
87.9
Water
91.1
87.7
97.5
85.9
69.2
88.8
81.4
85.4
99.3
74.3
77.7
93.5
91.9
84.3
91.6
95.1
65.9
95
91.7
92.5
87.4
a Percentage of mothers who stated that they
categories of liquid or solid food in the past
Source: Marriott
et al., 2007.
Milk
56.9
29.8
3.7
36.8
37.6
14.6
45
4.9
24.3
85.4
58.7
5.9
0
32
14.4
12.2
32.1
36.1
8.2
8.7
29.6
Formula
11.6
10.1
6.7
16.7
0
9.6
0
38.8
28.8
11.4
6
3.2
0
0
13.4
47.1
1.6
5.3
5
2.4
15.1
Other Liquids
85.3
21.9
29
48.5
23.9
23.9
25.2
35.4
57.7
91.8
56.4
31.2
42.7
15.8
27.4
31
56.2
37.9
25.9
49.9
41.6
Solid Foods
88.1
65.2
81
75.7
54.7
71.1
44.1
87.9
94.9
85.9
89.6
94.9
79.5
71.5
70.4
88
82.1
85.8
90.2
94.8
80.1
currently breast-feed and separately had fed their infants four
24 hours by country for infants age 6 to 12 months old.
Exposure Factors Handbook Page
September 2011 15-33
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
During the Previous 24 Hours
Feeding Practices
Infant Age
0-6 months
6-12 months
Percentage (weighted N)
Current Breast-Feeding
96.6 (22,781)
87.9 (18,944)
Gave Infant:
Water
Tinned, Powdered, or Other Milk
Commercial Formula
Other Liquids
Any Solid Food
45.9 (10,767)
11.9 (2,769)
9.0(1,261)
15.1(3,531)
21.9(5,131)
87.4 (18,663)
29.6 (6,283)
15.1(1,911)
41.6 (8,902)
80.1(17,119)
TV = Number of infants.
Source: Marriott et al., 2007.
Page
15-34
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, NHANES III
(1988-1994)
Absolute Difference (%, SE)a
Non-Hispanic White
Characteristic N
All Infants 1,869
%
60.3
(SE)
2.0
Non-Hispanic Black
N
1,845
%
25.5
(SE)
1.4
Mexican American
N
2,118
%
54.4
(SE)
1.9
White vs. Black
%
34.8
(SE)
(2.0)b
White vs.
Mexican
American
%
6.0
(SE)
(2.3)a
Infant Sex
Male 901
Female 968
60.4
60.3
2.6
2.3
913
932
24.4
26.7
1.6
1.9
1,033
1,085
53.8
54.9
1.8
2.9
35.9
33.7
(2.9)b
(2.6)b
6.6
5.4
(2.8)a
(3.4)c
Infant Birth Weight (g)
<2,500 118
>2,500 1,738
40.1
62.1
5.3
2.1
221
1,584
14.9
26.8
2.6
1.6
165
1,838
34.1
55.7
3.9
2.0
25.1
35.3
(5.8)b
(2.1)b
5.9
6.4
(6.4)c
(2.5)a
Maternal Age (years)
<20 175
20-24 464
25-29 651
>30 575
33.7
48.3
65.4
71.9
4.4
3.0
2.2
2.7
380
559
504
391
13.1
22.0
30.6
36.1
2.1
2.0
2.5
2.3
381
649
624
454
43.7
54.8
56.9
59.6
3.0
2.6
3.3
2.8
20.6
26.4
34.8
35.8
(4.8)b
(3.7)b
(3.4)b
-10
-6.4
8.6
12.3
(4.2)c
(4.0)a
(3.4)b
Household Head Education
30 204
64.9
50.9
48.6
2.0
3.4
4.8
872
484
415
26.8
24.1
24.3
2.0
3.2
2.7
961
534
359
54.1
57.8
47.1
2.5
2.1
4.4
38.0
26.8
24.3
(2.5)b
(4.5)b
(5.3)b
10.8
-6.8
1.5
(2.7)b
(6.1)°
Residence
Metropolitan 762
Rural 1,107
67.2
54.9
3.0
3.1
943
902
32.0
18.3
1.9
1.9
1,384
734
56.1
51.3
2.0
3.1
35.3
36.6
(2.6)b
(2.7)b
11.2
3.6
(2.9)b
(4.0)c
Region
Northeast 317
Midwest 556
South 748
West 248
51.6
61.7
52.7
82.4
4.6
2.3
2.7
3.9
258
346
1,074
167
34.2
26.5
19.4
45.1
4.4
2.4
2.0
5.1
12
170
694
1,242
74.1
51.5
42.7
59.1
10.4
3.7
3.5
2.2
17.3
35.2
33.3
37.3
(3.6)b
(3.3)b
(2.7)b
-22.5
10.2
10
23.4
(14.5)c
(5.0)a
(4.6)a
(3.3)b
Exposure Factors Handbook
September 2011
Page
15-35
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, NHANES III
(1988-1994) (continued)
Absolute Difference (%, SE)a
Non-Hispanic White Non-Hispanic Black Mexican American White vs.
White vs. Black Mexican
American
Poverty Income N % (SE) N % (SE) N
Ratio (%)
<100 257 38.5 4.2 905 18.2 1.9 986
100to<185 388 55.7 2.6 391 26.8 2.1 490
185to<350 672 61.9 2.5 294 32.0 3.0 288
>350 444 77.0 2.5 105 58.1 5.1 74
Unknown 108 44.7 7.1 150 25.5 3.9 280
p<0.05.
b p<0.0l.
c No statistical difference.
jV = Number of infants.
SE = Standard error.
Source: Li and Grummer-Strawn, 2002.
% (SE) % (SE) % (SE)
48.2 2.8 20.3 (4.4)b -9.6 (4.7)a
54.1 3.4 28.9 (3.5)b 1.5 (4.2)c
64.7 4.7 30.0 (3.7)b 2.8 (5.3)c
71.9 9.0 19.0 (5.6)b 5.2 (9.0)c
59.5 2.8 19.2 (7.9)a -14.8 (7.9)c
Page
15-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human
6 Months (NHANES III, 1988-1994)
Milk at
Absolute Difference (%, SE)
Non-Hispanic White
Characteristic N
All Infants 1,863
%
26.8
(SE)
1.6
Non-Hispanic Black
No.
1,842
%
8.5
(SE)
0.9
Mexi
N
2,112
can American
%
23.1
(SE)
1.4
White vs. Black
%
18.3
(SE)
(1.7)a
White vs. Mexican
American
%
3.7
(SE)
(2.1)b
Infant Sex
Male 900
Female 963
27.6
26.1
2.3
1.8
912
930
8.5
8.6
1.1
1.1
1,029
1,083
22.3
24.0
1.6
2.0
19.1
17.5
(2.6)a
(2.1)°
5.2
2.1
(2.6)c
(2.7)b
Infant Birth Weight (g)
<2,500 118
>2,500 1,733
10.9
28.3
3.1
1.8
221
1,581
4.2
9.0
1.8
0.9
165
1,832
15.2
23.1
4.7
1.7
6.7
19.3
(3.3)c
-4.3
5.2
(5.7)b
(2.3)c
Maternal Age (years)
<20 174
20-24 461
25-29 651
>30 573
10.2
13.4
29.3
39.0
2.9
2.4
2.6
2.6
380
559
503
389
4.7
7.5
10.9
10.7
1.4
1.1
2.0
1.7
380
646
624
452
11.6
23.8
24.6
30.0
1.7
2.4
2.6
2.8
5.5
5.9
18.4
28.4
(3.0)b
(2.5)c
(3.5)a
(3.3)a
-1.3
-10.4
4.8
9.0
(3.8)b
(3.3)a
(3.6)b
(3.6)c
Household Head Education
30 204
29.6
19.0
20.4
1.8
2.4
4.1
871
482
415
8.9
8.2
7.3
1.2
1.9
1.6
959
534
357
21.9
26.4
17.2
2.1
1.9
3.0
20.7
10.8
13.1
(3.2)a
(4.4)a
7.8
7.4
3.3
(2.7)a
(3.0)c
(5.2)b
Residence
Metropolitan 760
Rural 1,103
29.7
24.6
2.5
2.4
941
901
11.8
4.9
1.3
0.9
1,378
734
23.5
22.5
1.7
2.8
17.9
19.7
(2.4)a
(2.2)a
6.1
2.2
(3.4)b
Region
Northeast 316
Midwest 553
South 746
West 248
21.0
28.8
20.1
42.7
2.2
2.1
2.8
4.7
258
344
1,073
167
9.7
9.8
5.9
19.3
1.8
2.4
1.0
3.3
12
170
693
1,237
43.6
18.2
17.2
25.9
16.0
4.7
2.8
1.4
11.3
19.0
14.3
23.4
(3.7)a
(2.8)a
(5.3)a
-22.6
10.6
2.9
16.8
(16.5)"
(6.2)b
(4.2)b
Exposure Factors Handbook
September 2011
Page
15-37
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any
6 Months (NHANES III, 1988-1994) (continued)
Human Milk at
Absolute Difference (%,SE)
Non-Hispanic White Non-Hispanic Black Mexican American
White vs. Black
Poverty Income N %
Ratio (%)
100to<185 387 23.5
185to<350 670 30.4
>350 443 33.0
Unknown 108 13.3
b No statistical difference.
p<0.05.
N = Number of individuals.
SE = Standard error.
Source: Li and Grummer-Strawn,
(SE) No. %
2.9 390 9.9
2.7 293 10.0
3.0 105 15.2
3.8 149 6.4
2002.
(SE) N % (SE) % (SE)
1.8 486 23.4 2.7 13.6 (3.9)a
2.4 287 27.6 4.4 20.4 (4.0)a
2.8 74 32.3 9.0 17.8 (4.2)a
2.9 280 26.7 4.5 7.0 (5.3)b
White vs. Mexican
American
% (SE)
0 (4.1)b
2.9 (4.8)b
0.7 (9.5)b
-13.4 (6.6)c
Page
15-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at 4 Months
(NHANES III, 1991-1994)
Absolute Difference (%,SE)
Non-Hispanic White
Characteristic N
All Infants 824
%
22.6
(SE)
1.7
Non-Hispanic
N
906
%
8.5
Black
(SE)
1.5
Mexican American
N
957
%
20.4
(SE)
1.4
White vs. Black
%
14.1
(SE)
(2.2)a
White vs.
Mexican
American
%
2.3
(SE)
(1.6)b
Infant Sex
Male 394
Female 430
22.3
23.0
1.9
2.2
454
452
7.0
10.0
1.6
2.2
498
459
20.7
20.0
1.5
1.8
15.3
12.9
(2.6)'
(3.0)a
1.5
3.0
(2P
Infant Birth Weight (g)
<2,500 50
>2,500 774
15.2
23.1
7.1
1.8
118
786
7.0
8.8
2.3
1.6
66
880
5.6
21.6
1.8
1.4
8.2
14.4
(2.2)a
9.5
1.5
(6.9)b
Maternal Age (years)
<20 76
20-24 205
25-29 271
>30 270
6.6
11.4
21.6
34.8
3.2
2.2
2.3
2.7
172
273
254
201
6.4
7.4
8.6
11.9
2.1
2.4
2.5
2.6
170
319
256
210
12.1
21.0
22.1
23.6
2.5
2.3
2.5
3.1
0.2
4.0
13.0
22.9
(3.7)b
(2.7)b
(3.2)a
(4.2)a
-5.6
-9.6
-0.5
11.1
(3.8)b
(3.2)a
(3.2)b
(3.7)a
Household Head Education
30 91
24.8
19.7
15.4
2.1
4.3
3.8
407
230
230
8.0
8.6
9.0
1.9
1.9
2.9
417
261
184
19.4
23.1
15.9
1.9
3.4
2.3
16.8
11.1
6.4
(3.0)a
(4.6)c
(5.2)b
5.4
-3.4
-0.5
(4.9)b
(4.6)b
Residence
Metropolitan 312
Rural 512
24.4
21.3
3
1.8
535
371
11.0
4.2
2.0
1.3
608
349
19.6
22.3
1.6
3.3
13.4
17.1
(3.5)a
4.8
-1.1
(2.8)b
(3.0)b
Region
Northeast 138
Midwest 23 1
South 378
West 77
20.0
26.5
14.1
34.7
1.4
3.2
2.8
2.7
131
143
574
58
11.1
12.6
5.9
12.5
2.9
5.6
1.4
5.0
10
98
383
466
9.4
19.2
15.9
23.0
9.5
4.1
3.1
1.3
8.8
13.9
8.2
22.2
(2.2)a
(7.6)b
(5.4)a
10.6
7.4
-1.8
11.7
(8.7)b
(3.7)b
(3.7)b
(2.5)
Exposure Factors Handbook
September 2011
Page
15-39
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at 4 Months
(NHANES III, 1991-1994) (continued)
Absolute Difference (%, SE)
Non-Hispanic White Non-Hispanic Black Mexican American
White vs. Black
Poverty Income
Ratio (%)
<100
100to<185
185to<350
>350
Unknown
p<0.05.
N % (SE) N % (SE) N
116 13.1 3.3 448 5.7 1.6 471
166 18.9 3.2 197 10.6 2.8 234
274 25.1 3.2 145 12.9 4.3 132
235 27.4 4.1 57 12.8 3.5 37
33 16.5 7.6 59 7.3 3.7 83
% (SE) % (SE)
18.4 1.8 7.4 (3.5)c
21.9 4.1 8.3 (3.3)c
26.4 4.2 12.2 (5.0)c
17.0 5.0 14.6 (5.0)a
16.1 5.1 9.2 (8.6)b
White vs.
Mexican
American
% (SE)
-5.3 (3.1)b
-3 (6.1)b
-1.3 (4.1)b
10.4 (5.2)b
0.4 (9.5)b
c No statistical difference.
N = Number of individuals.
SE = Standard error.
Source: Li and Grummer-Strawn, 2002.
Page
15-40
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-33. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants at 5 or 6
Months of Age in the United States in 1989 and 1995, by Ethnic Background and Selected Demographic
Variables
Percentage of Mothers Breast-Feeding
Characteristic
All Infants
White
Black
Hispanic
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Total Family Income
<$10,000
$10,000 to $14,999
$15,000 to $24,999
>25,000
Maternal Education
Grade School
High School
College
Maternal Employment
Employed Full Time
Employed Part Time
Not Employed
Birth Weight
Low (<2,500 g)
Normal
Parity
Primiparous
Multiparous
WIC Participation0
Participant
Non-participant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
In Hospital
1989 1995
52.2 59.7
58.5 64.3
23.0 37.0
48.4 61.0
30.2 42.8
45.2 52.6
58.8 63.1
65.5 68.1
66.5 70.0
31.8 41.8
47.1 51.7
54.7 58.8
66.3 70.7
31.7 43.8
42.5 49.7
70.7 74.4
50.8 60.7
59.4 63.5
51.0 58.0
36.2 47.7
53.5 60.5
52.6 61.6
51.7 57.8
34.2 46.6
62.9 71.0
52.2 61.2
47.4 53.8
47.6 54.6
55.9 61.9
43.8 54.8
37.9 44.1
46.0 54.4
70.2 75.1
70.3 75.1
a The percent change was calculated using the following formula
At 6 Months
Change"
14.4
9.9
60.9
26.0
41.7
16.4
7.3
4.0
5.3
31.4
9.8
7.5
6.6
38.2
16.9
5.2
19.5
6.9
13.7
31.8
13.1
17.1
11.8
36.3
12.9
17.2
13.5
14.7
10.7
25.1
16.4
18.3
7.0
6.8
1989
18.1
21.0
6.4
13.9
5.6
11.5
21.1
29.3
34.0
8.2
13.9
18.9
25.5
11.5
12.4
28.8
8.9
21.1
21.6
9.8
18.8
15.1
21.1
8.4
23.8
18.6
16.8
16.7
18.4
13.7
11.5
13.6
28.3
26.6
% breast-fed in 1984 - % breast-fed
b Figures in parentheses indicate a decrease in the rate of breast-feeding from 1989 to
c WIC indicates Women,
Source: Ryan, 1997.
1995.
1995
21.6
24.1
11.2
19.6
9.1
14.6
22.9
29.0
33.8
11.4
15.4
19.8
28.5
17.1
15.0
31.2
14.3
23.4
25.0
12.6
22.3
19.5
23.6
12.7
29.2
22.2
19.6
18.9
21.4
18.6
13.0
17.0
30.3
30.9
in 1989 ^
Change8
19.3
14.8
75.0
41.0
62.5
27.0
8.5
(1.0)"
(0.6)b
39.0
10.8
4.8
11.8
48.7
21.0
8.3
60.7
10.9
15.7
28.6
18.6
29.1
11.8
51.2
22.7
19.4
16.7
13.2
16.3
35.8
13.0
25.0
7.1
16.2
% breast-fed in 1984.
Infants, and Children supplemental food program.
Exposure Factors Handbook
September 2011
Page
15-41
-------
Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-34. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital and Infants
at 6 and 12 Months of Age
in the United States in 2003, by
Demographic Variables
Ethnic Background
and Selected
Percentage of Mothers Breast-Feeding
In Hospital At 6 Months At
All Infants
White
Black
Hispanic
Asian
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Maternal Education
Any Grade School
Any High School
No College
College
Maternal Employment
Employed Full Time
Employed Part Time
Total Employed
Not Employed
Low Birth Weight <5 Ibs 9oz
Parity
Primiparous
Multiparous
WIC Participation3
Participant
Non-participant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
44
53
26
33
39
28
40
48
50
47
26
35
35
55
44
49
45
43
27
48
43
32
55
52
36
44
55
42
37
37
53
50
18
20
10
15
23
9
13
20
23
23
13
12
12
24
11
19
14
21
10
17
19
11
25
22
17
17
18
16
11
15
23
24
12 Months
10
12
5
12
12
4
8
10
14
14
17
8
8
14
6
11
8
13
6
10
11
7
14
11
9
9
9
10
7
8
16
15
a WIC indicates Women, Infants, and Children supplemental food program.
Source: Abbott Laboratories, 2003.
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Exposure Factors Handbook
Chapter 15—Human Milk Intake
Table 15-35. Number of Meals Per Day
A£
a
Source
;e (months)
1
2
3
Data expressed as
HofVanderetal.,
Bottle-Fed Infants
(meals/day)a
5.4 (4-7)
4.8 (4-6)
4.7 (3-6)
mean with range in parentheses.
1982.
Breast-Fed
(meals/day)a
5.8 (5-7)
5.3 (5-7)
5.1(4-8)
Table 15-36. Comparison of Breast-Feeding Patterns Between Age and Groups (Mean ± SD)
Breast-Feeding Episodes per Day 5.8 ±2.6 6.8 ±2.4 2.5 ± 2.0
Total Time Breast-Feeding (minute/day) 65.2 ±44.0 102.2 ±51.4 31.2 ±24.6
Length of Breast-Feeding (minute/episode) 10.8 ±6.1 14.2 ±6.1 11.6 ± 5.6
SD = Standard deviation.
Source: Buckley, 2001.
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Exposure Factors Handbook
Chapter 16—Activity Factors
TABLE OF CONTENTS
LIST OF TABLES 16-ii
16. ACTIVITY FACTORS 16-1
16.1. INTRODUCTION 16-1
16.2. RECOMMENDATIONS 16-1
16.2.1. Activity Patterns 16-1
16.2.2. Occupational Mobility 16-2
16.2.3. Population Mobility 16-2
16.3. ACTIVITY PATTERNS 16-11
16.3.1. Key Activity Pattern Studies 16-11
16.3.1.1. Wiley etal. (1991) 16-11
16.3.1.2. U.S. EPA (1996) 16-12
16.3.2. Relevant Activity Pattern Studies 16-13
16.3.2.1. Hill (1985) 16-13
16.3.2.2. Timmeretal. (1985) 16-14
16.3.2.3. Robinson and Thomas (1991) 16-15
16.3.2.4. Funk etal. (1998) 16-15
16.3.2.5. CohenHubaletal. (2000) 16-16
16.3.2.6. Wong et al. (2000) 16-17
16.3.2.7. Graham and McCurdy (2004) 16-18
16.3.2.8. Juster et al. (2004) 16-18
16.3.2.9. Vandewater et al. (2004) 16-19
16.3.2.10. U.S. Department of Labor (2007) 16-19
16.3.2.11. Nader et al. (2008) 16-20
16.4. OCCUPATIONAL MOBILITY 16-20
16.4.1. Key Occupational Mobility Studies 16-20
16.4.1.1. Carey (1988) 16-20
16.4.1.2. Carey (1990) 16-21
16.5. POPULATION MOBILITY 16-21
16.5.1. Key Population Mobility Studies 16-21
16.5.1.1. Johnson and Capel (1992) 16-21
16.5.1.2. U.S. Census Bureau (2008a) 16-22
16.5.2. Relevant Population Mobility Studies 16-22
16.5.2.1. Israeli and Nelson (1992) 16-22
16.5.2.2. National Association of Realtors (NAR) (1993) 16-23
16.5.2.3. U.S. Census Bureau (2008b) 16-23
16.6. REFERENCES FOR CHAPTER 16 16-23
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September 2011 16-i
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Exposure Factors Handbook
Chapter 16—Activity Factors
LIST OF TABLES
Table 16-1. Recommended Values for Activity Patterns 16-3
Table 16-2. Confidence in Recommendations for Activity Patterns 16-6
Table 16-3. Recommended Values for Occupational Mobility 16-7
Table 16-4. Confidence in Recommendations for Occupational Mobility 16-8
Table 16-5. Recommended Values for Population Mobility 16-9
Table 16-6. Confidence in Recommendations for Population Mobility 16-10
Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, for All Respondents and Doers 16-26
Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, by Age and Sex 16-27
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, Grouped by Seasons and Regions 16-28
Table 16-10. Time (minutes/day) Children Under 12 Years of Age Spent in 6 Major Location
Categories, for All Respondents and Doers 16-28
Table 16-11. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 6 Location
Categories, Grouped by Age and Sex 16-29
Table 16-12. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 6 Location
Categories, Grouped by Season and Region 16-30
Table 16-13. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Proximity to 2
Potential Sources of Exposure, Grouped by All Respondents, Age, and Sex 16-30
Table 16-14. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
Grouped by Age and Sex 16-31
Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only, Children <21 years 16-32
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined,
Doers Only 16-35
Table 16-17. Time Spent (minutes/day) at Selected Indoor Locations Whole Population and Doers
Only, Children <21 years 16-43
Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only 16-44
Table 16-19. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population and Doers
Only, Children <21 years 16-51
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only 16-52
Table 16-21. Mean Time Spent (minutes/day) Inside and Outside, by Age Category, Children <21
years 16-58
Table 16-22. Mean Time Spent (minutes/day) Outside and Inside, Adults 18 Years and Older, Doers
Only 16-58
Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined Whole
Population and Doers Only, Children <21 Years 16-59
Table 16-24. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined, Doers Only 16-61
Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only,
Children <21 Years 16-65
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only 16-68
Table 16-27. Number of Showers Taken per Day, by Children <21 Years 16-79
Table 16-28. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately After Bathing
and Showering, Children <21 Years 16-80
Table 16-29. Mean Time Spent (minutes/day) and Bathing/Showering, Adults 18 Years and Older,
Doers Only 16-81
Table 16-30. Number of Times Respondent Took Shower or Bathed, Doers Only 16-82
Table 16-31. Time Spent (minutes/day) Bathing and Showering, Doers Only 16-84
Table 16-32. Number of Times Washing the Hands at Specified Daily Frequencies, Children <21 Years 16-85
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Chapter 16—Activity Factors
LIST OF TABLES (continued)
Table 16-33. Number of Times Washing the Hands at Specified Daily Frequencies, Doers Only 16-86
Table 16-34. Number of Times Swimming in a Month in Freshwater Swimming Pool, Children <21
Years 16-87
Table 16-35. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool, Children <21
Years 16-87
Table 16-36. Number of Times Swimming in a Month in Freshwater Swimming Pool, Doers Only 16-88
Table 16-37. Time Spent (minutes/month) inFreshwater Swimming Pool, Doers Only 16-90
Table 16-38. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population and
Doers only, Children <21 Years 16-91
Table 16-39. Number of Minutes Spent Playing on Selected Outdoor Surfaces (minutes/day), Doers
Only 16-92
Table 16-40. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Children
<21 Years 16-95
Table 16-41. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Doers Only 16-96
Table 16-42. Time Spent (minutes/day) with Smokers Present, Children <21 Years 16-97
Table 16-43. Time Spent (minutes/day) with Smokers Present, Doers Only 16-98
Table 16-44. Mean Time Spent (hours/week)3 in Ten Major Activity Categories Grouped by Regions 16-99
Table 16-45. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Type
of Day 16-99
Table 16-46. Mean Time Spent (minutes/day) in Ten Major Activity Categories During 4 Waves of
Interviews3 16-100
Table 16-47. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Sex 16-100
Table 16-48. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of
Day 16-101
Table 16-49. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for 5 Different Age
Groups 16-102
Table 16-50. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week 16-103
Table 16-51. Mean Time Spent (minutes/day) in Various Microenvironments by Age Group (years) for
the National and California Surveys 16-104
Table 16-52. Mean Time Spent in Ten Major Activity Categories Grouped by Total Sample and Sex for
the CARB and National Studies (age 18-64 years) 16-105
Table 16-53. Total Mean Time Spent at 3 Major Locations Grouped by Total Sample and Sex for the
CARB and National Study (age 18-64 years) 16-105
Table 16-54. Mean Time Spent at 3 Locations for both CARB and National Studies (ages 12 years and
older) 16-106
Table 16-55. Sample Sizes for Sex and Age Groups 16-106
Table 16-56. Assignment of At Home Activities to Inhalation Rate Levels for All Individuals 16-107
Table 16-57. Aggregate Time Spent (minutes/day) At Home in Activity Groups 16-108
Table 16-58. Comparison of Mean Time Spent (minutes/day) At Home, by Sex 16-108
Table 16-59. Comparison of Mean Time Spent (minutes/day) At Home, by Sex and Age for Children 16-109
Table 16-60. Number of Person-Day s/Individualsa for Children Less than 12 Years in CHAD Database.... 16-109
Table 16-61. Time Spent (hours/day) in Various Microenvironments, by Age 16-110
Table 16-62. Mean Time Children Spent (hours/day) Doing Various Macroactivities While Indoors at
Home 16-110
Table 16-63. Time Children Spent (hours/day) in Various Microenvironments, by Age Recast into New
Standard Age Categories 16-111
Table 16-64. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
Recast Into New Standard Age Categories 16-111
Table 16-65. Number and Percentage of Respondents with Children and Those Reporting Outdoor
Play3 Activities in Both Warm and Cold Weather 16-112
Table 16-66. Play Frequency and Duration for All Child Players (from SCS-II data) 16-112
Table 16-67. Hand Washing and Bathing Frequency for all Child Players (from SCS-II data) 16-112
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Chapter 16—Activity Factors
LIST OF TABLES (continued)
Table 16-68. NHAPS and SCS-II Play Duration Comparison (Children Only) 16-113
Table 16-69. NHAPS and SCS-II Hand Wash Frequency Comparison (Children only) 16-113
Table 16-70. Time Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only) 16-114
Table 16-71. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Sex and Age
Cohort (Doers Only) 16-115
Table 16-72. Time Spent (minutes/day) Indoors Based on CHAD Data (Doers Only) 16-116
Table 16-73. Time Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only) 16-117
Table 16-74. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday
(Children Only) 16-118
Table 16-75. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day
(Children Only) 16-119
Table 16-76. Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to
17 Years 16-120
Table 16-77. Time Spent (minutes/2-day period) in Various Activities by Children Participating in the
Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement (CDS) 16-121
Table 16-78. Annual Average Time Spent (hours/day) on Various Activities According to Age, Race,
Ethnicity, Marital Status, and Educational Level (Ages 15 Years and Over) 16-122
Table 16-79. Annual Average Time Use by the U.S. Civilian Population, Ages 15 Years and Older 16-123
Table 16-80. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years 16-124
Table 16-81. Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity (Children
Only) 16-125
Table 16-82. Occupational Tenure of Employed Individuals by Age and Sex 16-125
Table 16-83. Occupational Tenure for Employed Individuals3 Grouped by Sex and Race 16-126
Table 16-84. Occupational Tenure for Employed Individuals3 Grouped by Sex and Employment Status.... 16-126
Table 16-85. Occupational Tenure of Employed Individuals3 Grouped by Major Occupational Groups
and Age 16-126
Table 16-86. Voluntary Occupational Mobility Rates for Workers Age 16 Years and Older 16-127
Table 16-87. Descriptive Statistics for Residential Occupancy Period (years) 16-128
Table 16-88. Descriptive Statistics for Both Sexes by CurrentAge 16-129
Table 16-89. Residence Time of Owner/Renter Occupied Units 16-130
Table 16-90. Percent of Householders Living in Houses for Specified Ranges of Time, and Statistics
for Years Lived in Current Home 16-130
Table 16-91. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in
Survey 16-131
Table 16-92. Total Residence Time, T (years), Corresponding to Selected Values of R(t) by Housing
Category 16-131
Table 16-93. Summary of Residence Time of Recent Home Buyers (1993) 16-132
Table 16-94. Tenure in Previous Home (percentage distribution) 16-132
Table 16-95. Number of Miles Moved (percentage distribution) 16-132
Table 16-96. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational
Attainment, Marital Status, Nativity, Tenure, and Poverty Level: 2006 to 2007 (numbers
in thousands) 16-133
Table 16-97. Distance of Intercounty Move, by Sex, Age, Race and Hispanic Origin, Educational
Attainment, Marital Status, Nativity, Tenure, Poverty Status, Reason for Move, and State
of Residence 1 Year Ago: 2006 to 2007 16-135
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Chapter 16—Activity Factors
16. ACTIVITY FACTORS
16.1. INTRODUCTION
Individual or group activities are important
determinants of potential exposure. Toxic chemicals
introduced into the environment may not cause harm
to an individual until an activity is performed that
brings the individual into contact with those
contaminants. An activity or time spent in a given
activity will vary among individuals depending on
culture, ethnicity, hobbies, location, sex, age,
socioeconomic characteristics, and personal
preferences. However, limited information is
available regarding ethnic, cultural, and
socioeconomic differences in individuals' choice of
activities or time spent in a given activity. Children
are of special concern because certain activities and
behaviors specific to children place them at a higher
risk of exposure to certain environmental agents and
expose them to higher levels of many chemicals
(Chance and Harmsen, 1998). Trends associated
with activity patterns include increases in the
proportion of the population engaging in sedentary
activities and decreases in physical activity in the
home and related to work, including walking to work,
as there has been a strong trend toward Americans
living in the suburbs (Brownson, 2005). Recent
trends in occupational mobility include the facts that
average tenure increases directly with age, and that a
large proportion of American workers show
substantial job stability (U.S. Census Bureau, 2010).
For population mobility, the U.S. Census Bureau
reported that the national residential move rate
increased to 12.5% in 2009 following a record low of
11.9% in 2008 (U.S. Census Bureau, 2010).
In calculating exposure, a person's average daily
dose is determined from a combination of variables
including the pollutant concentration, exposure
duration, and frequency of exposure (see Chapter 1).
These variables can be dependent on human activity
patterns and time spent at each activity and/or
location.
Time activity data are generally obtained using
recall questionnaires and diaries to record the
person's activities and microenvironments. Other
methods include the use of videotaping and global
positioning system technology to provide information
on individuals' locations (Phillips et al., 2001;
Elgethun et al., 2003).
Obtaining accurate information on time and
activities can be challenging. This is especially true
for children (Cohen Hubal et al., 2000). Children
engage in more contact activities than adults;
therefore, a much wider distribution of activities need
to be considered when assessing children's exposure
(Cohen Hubal et al., 2000). Mouthing behavior,
which includes all activities in which objects,
including fingers, are touched by the mouth or put
into the mouth are provided in Chapter 4. Chapter 7
provides frequency and duration data for dermal
(hand) contact.
This chapter summarizes data on how much time
individuals spend participating in various activities in
various microenvironments and on the frequency of
performing various activities. Information is also
provided on occupational mobility and population
mobility. The data in this chapter cover a wide range
of activities and populations, arranged by age group
when such data are available. One of the objectives
of this handbook is to provide recommended
exposure factor values using a consistent set of age
groups. In this chapter, several studies are used as
sources for activity pattern data. In some cases, the
source data could be retrieved and analyzed using the
standard age groupings recommended in Guidance
for Monitoring and Assessing Childhood Exposures
to Environmental Contaminants (U.S. EPA, 2005). In
other cases, the original source data were not
available, and the study results are presented here
using the same age groups as the original study,
whether or not they conform to the standard age
groupings.
The recommendations for activity factors are
provided in the next section, along with a summary
of the confidence ratings for these recommendations.
The recommended values are based on key studies
identified by U.S. Environmental Protection Agency
(U.S. EPA) for this factor. Following the
recommendations, key studies on activity patterns are
summarized. Relevant data on activity patterns are
also presented to provide the reader with added
perspective on the current state-of-knowledge
pertaining to activity patterns in adults and children.
Additional information on microactivity patterns (i.e.,
hand-to-mouth, object-to-mouth, and dermal [hand]
contact with surfaces and objects) is provided in
Chapters 4 and 7.
16.2. RECOMMENDATIONS
16.2.1. Activity Patterns
Assessors are commonly interested in
quantitative information describing several types of
time use data for adults and children including the
following: time spent indoors and outdoors; time
spent bathing, showering, and swimming; and time
spent playing on various types of surfaces.
Table 16-1 summarizes the recommended values for
these factors. Note that, except for swimming, all
activity factors are reported in units of minutes/day.
Exposure Factors Handbook
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Chapter 16—Activity Factors
Time spent swimming is reported in units of
minutes/month. These data are based on 2 key studies
presented in this chapter: a study of children's
activity patterns in California (Wiley et al., 1991) and
the National Human Activity Pattern Survey
(NHAPS) (U.S. EPA, 1996). Both mean and
95th percentile recommended values are provided.
However, because these recommendations are based
on short-term survey data, 95th percentile values may
be misleading for estimating chronic (i.e., long-term)
exposures and should be used with caution. Also, the
upper percentile values for some activities are
truncated as a result of the maximum response
included in the survey (e.g., durations of more than
120 minutes/day were reported as 121 minutes/day),
and could not be further refined). Table 16-2 presents
the confidence ratings for the recommendations.
The recommendations for total time spent
indoors and the total time spent outdoors are based on
the U.S. EPA re-analysis of the source data from
Wiley et al. (1991) for children <1 year of age and
U.S. EPA (1996) for childhood age groups >1 year of
age. Although Wiley et al. (1991) is a study of
California children and the sample size was very
small for infants, it provides data for children's
activities for the younger age groups. Data from
U.S. EPA (1996) are representative of the U.S.
general population. In some cases, however, the time
spent indoors or outdoors would be better addressed
on a site-specific basis since the times are likely to
vary depending on the climate, residential setting
(i.e., rural versus urban), personal traits (e.g., health
status), and personal habits. For children >1 year of
age, the recommended values for time spent indoors
at a residence, duration of showering and bathing,
time spent swimming, and time spent playing on
sand, gravel, grass or dirt are based on a U.S. EPA
re-analysis of the source data from U.S. EPA (1996).
For adults 18 years and older, the recommended
values are taken directly from the source document
(U.S. EPA, 1996).
16.2.2. Occupational Mobility
Occupational mobility may be an important
factor in determining exposure. For example, the
duration of exposure to occupationally-related
contaminants, such as the chemicals used in an
industrial or laboratory setting, will be directly
associated with the period of time an individual
spends in the occupation.
The median occupational tenure of the working
population (109.1 million people) ages 16 years of
age and older in January 1987 was 7.9 years for men
and 5.4 years for women (Carey, 1988). Since the
occupational tenure varies significantly according to
age and sex, the recommended values are given by 5-
year age groups separately for males and females in
Table 16-3. Section 16.4 provides occupational
tenure for males and females combined. Part-time
employment, race and the position held are important
to consider in determining occupational tenure. These
data are also presented in Section 16.4. Table 16-3
also presents recommendations for occupational
mobility rate, by age. This rate is the percentage of
persons employed in an occupation who had
voluntarily entered it from another occupation. The
overall percent was 5.3 (Carey, 1990). The ratings
indicating confidence in the occupational mobility
recommendations are presented in Table 16-4. It
should be noted that the recommended values are not
for use in evaluating job tenure. These data can be
used for determining time spent in an occupation and
not for time spent at a specific job site.
16.2.3. Population Mobility
An assessment of population mobility can assist
in determining the length of time a household is
exposed in a particular location. For example, the
duration of exposure to site-specific contamination,
such as a polluted stream from which a family fishes
or contaminated soil on which children play or
vegetables are grown, will be directly related to the
period of time residents live near the contaminated
site.
There are two key studies from which the
population mobility recommendations were derived:
the U.S. Census Bureau American Housing Survey,
(U.S. Census Bureau, 2008a) and Johnson and Capel
(1992). The U.S. Bureau of Census (2008a) provides
data on current residence time and Johnson and Capel
(1992) provide data on residential occupancy period.
Table 16-5 presents the recommendations for
population mobility. Table 16-6 presents the
confidence ratings for these recommendations.
The 50th and 90th percentiles for current
residence time from the U.S. Census Bureau (2008a)
are 8 years and 32 years, respectively. The mean and
90th percentile for residential occupancy period from
Johnson and Capel (1992) are 12 years and 26 years,
respectively.
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Chapter 16—Activity Factors
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
18 to<65 years
>65 years
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to65 years
Birth to 65 years
Birth to 18 years (U.S. EPA, 1996). Total minutes/24 hours
(1,440) minus time outdoors, doersb only. See Table 16-22.
-
Time Outdoors (total)
minutes/day
U. S. EPA analysis of source data from Wiley et al. ( 1 99 1 )
for age groups from birth to <12 months. Average for boys
and girls, whole population. See Table 16-14.
U.S. EPA re-analysis of source data from U.S. EPA (1996)
for age groups from 1 to <21 years, whole population. See
Table 16-21.
Adults, >18 years (U.S. EPA, 1996). Sum of minutes spent
outdoors away from the residence and minutes spent
outdoors at the residence. Doersb only. See Table 16-22.
Time Indoors (at residence)
minutes/day
1,440
1,440
1,296 Children, Birth to <21 years: U.S. EPA re-analysis of source
1,355 data from U.S. EPA (1996). Doersb only. See Table 16-15.
1,275
1,315 Adults >18 years (U.S. EPA, 1996). Doersb only. See Table
1,288 16-16.
1,428
1,440
Showering
minutes/day
_
-
44
, . U. S. EPA re-analysis of source data from
U.S. EPA (1996). Doersb only. See Table 16-28.
40
45
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Chapter 16—Activity Factors
Table 16-1. Recommended Values for Activity Patterns (continued)
Age Group
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
18 to <65 years
>65 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to65 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to65 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
18 to <65 years
>65 years
Mean
19
23
23
24
24
25
33
17
17
96
105
116
137
151
139
145
45C
40C
18
43
53
60
67
67
83
Oc
Oc
52
68
62
79
73
75
60
60C
121C
95th Percentile Source
Bathing
minutes/day
30
32
45
„ U.S. EPA re-analysis of source data from
46 U.S. EPA (1996). Doersb only. See Table 16-28.
43
60
Bathing/Showering
minutes/day
U.S. EPA (1996). Doersb only. See Table 16-29.
Swimming
minutes/month
_
_
181 Children, Birth to <21 years: U.S. EPA re-analysis of source
181 data from U.S. EPA (1996). Doersb only. See Table 16-35.
181
181 Adults, >18 years (U.S. EPA, 1996). Doersb only. See Table
181 16-37.
181
181
Playing on Sand/Gravel
minutes/day
-
121
121 Children, <21 years: U.S. EPA re-analysis of source data
121 from U.S. EPA (1996). Doersb only. See Table 16-38.
121
121 Adults, >18 years (U.S. EPA, 1996). Doersb only. See Table
16-39.
121
-
Playing on Grass
minutes/day
_
121
121 Children, <21 years: U.S. EPA re-analysis of source data
121 from U.S. EPA (1996). Doersb only. See Table 16-38.
121
121 Adults, >18 years (U.S. EPA, 1996). Doersb only. See Tables
16-39.
121
-
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Chapter 16—Activity Factors
Table 16-1. Recommended Values for Activity Patterns (continued)
Age Group
Mean
95th Percentile
Source
Playing on Dirt
minutes/day
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
18 to <65 years
>65 years
33
56
47
63
63
49
30
Oc
Oc
_
121
121
121
121
120
-
120
-
Children, <21 years: U.S. EPA re-analysis of source data
from U.S. EPA (1996). Doersb only. See Table 16-38.
Adults, >18 years (U.S. EPA, 1996). Doersb only. See Table
16-39.
Note:
Percentiles were not calculated for sample sizes less than 10 or in cases where the mean was calculated by summing
the means from multiple locations or activities.
These activities are averaged over seasons.
Doers are those respondents who engaged or participated in the activity.
Median value, mean not available in U.S. EPA, 1996.
All activities are reported in units of minutes/day, except swimming, which is reported in units of minutes/month.
There are 1,440 minutes in a day. Time indoors and outdoors may not add up to 1,440 minutes due to activities that
could not be classified as either indoors or outdoors.
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Table 16-2. Confidence in Recommendations for Activity Patterns
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodologies and data analyses were adequate. For the
reanalysis of U.S. EPA (1996) study data, responses were weighted;
however, adult data were not reanalyzed. The California children's
activity pattern survey design (Wiley et al., 1991) and NHAPS
(U.S. EPA, 1996) consisted of large overall sample sizes that varied
with age. Data were collected via questionnaires and interviews.
Measurement or recording error may have occurred since the diaries
were based on 24 hour recall. The sample sizes for some age groups
were small for some activity factors. The upper ends of the
distributions were truncated for some factors. The data were based
on short-term data.
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key studies focused on activities of children and adults.
U.S. EPA (1996) was a nationally representative survey of the U.S.
population and the reanalysis was weighted; the Wiley et al. (1991)
survey was conducted in California and it was not representative of
the U.S. population.
The Wiley et al. (1991) study was conducted between April 1989
and February 1990; the U.S. EPA (1996) study was conducted
between October 1992 and September 1994.
Data were collected for a 24-hour period.
Medium
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The original studies are widely available to the public; U.S. EPA
analysis of the original raw data from U.S. EPA (1996) is available
upon request.
The methodologies were clearly presented; enough information was
included to reproduce the results.
Quality assurance methods were not well described in study reports.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Variability was characterized across various age categories of
children and adults.
The studies were based on short term recall data, and the upper ends
of the distributions were truncated.
Medium
Evaluation and Review
Peer Review
Number and Agreement of Studies
The original studies received a high level of peer review. The
re-analysis of the U.S. EPA (1996) data to conform to the
standardized age categories was not peer-reviewed.
There were 2 key studies.
Medium
Overall Rating
Medium for
the mean; low
for upper
percentile
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Table 16-3. Recommended Values for Occupational Mobility
Age Group
Median Tenure
(years)
Men
Median Tenure
(years)
Women
Source
All ages, >16 years 7.9
16 to 24 years 2.0
25 to 29 years 4.6
30 to 34 years 7.6
35 to 39 years 10.4
40 to 44 years 13.8
45 to 49 years 17.5
50 to 54 years 20.0
55 to 59 years 21.9
60 to 64 years 23.9
65 to 69 years 26.9
>70 years 30.5
5.4
1.9
4.1
6.0
7.0
8.0
10.0
10.8
12.4
14.5
15.6
18.8
(Carey, 1988). See Table 16-82
Age Group
Occupational Mobility Ratea
(percent)
Source
16 to 24 years
25 to 34 years
35 to 44 years
45 to 54 years
55 to 64 years
>64 years
Total, >16 years
12.7
6.6
4.0
1.9
1.0
0.3
5.3
(Carey, 1990). See Table 16-8
Occupational mobility rate = percentage of persons employed in an occupation who had voluntarily entered it from another
occupation.
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Table 16-4. Confidence in Recommendations for Occupational Mobility
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Both studies are based on the U.S. Census Bureau's Current
Population Survey which uses valid methodologies and
approaches and is representative of the U.S. population with
sample sizes of approximately 50,000 a month. Both studies
are secondary analyses based on supplemental data to the
January, 1987, Current Population Survey (a U.S. Census
publication).
Much of the original study data is not available. Only median
values are reported. There is minimal concern about sampling
and non-sampling error and non-response bias as in all
surveys based on statistical samples.
Medium
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Occupational tenure was the focus of both key studies.
The data are statistically representative of the U.S.
population.
The data were collected over 20 years ago in 1986 and 1987.
It is questionable whether the results would be the same if
current data were analyzed based on changes in the economy
that have occurred since the study was conducted.
Data were collected in 1986-1987.
Medium
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The studies are widely available to the public. The Current
Population Survey January, 1987: Occupational Mobility and
Job Tenure data are available from the U.S. Census Bureau.
Results can be reproduced and methodology can be followed
and evaluated.
Quality assurance methods were not well described.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
The study provided averages according to sex, race, and
education; age averages and percentiles were provided.
The studies are based on recall data.
High
Evaluation and Review
Peer Review
Number and Agreement of Studies
The studies received a high level of peer review.
There are 2 key studies based on the same data source.
Medium
Overall Rating
Medium
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Table 16-5. Recommended Values for Population Mobility
Mean
95m
Percentile
Source
Residential Occupancy Period 12 years 33 years
Current Residence Time 13 years 46 years
(Johnson and Capel, 1992).
See Table 16-87.
(U.S. Census Bureau, 2008a). See
Table 16-90.
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Table 16-6. Confidence in Recommendations for Population Mobility
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
Both key studies are based on U.S. Census Bureau studies
which used valid data collection methodologies and
approaches and are representative of the U.S. population.
Data do not account for each member of the household;
values are more realistic estimates for the individual's total
residence time than the average time a household has been
living at its current residence. The moving process was
modeled in Johnson and Capel (1992). For the mean and
percentile calculations of U.S. Census Bureau (2008a) data,
an even distribution was assumed within different ranges
which may bias the statistics.
The Census data provided length of time at current residence.
The other study used modeling to estimate total time.
The sample surveyed was statistically representative of the
U.S. population.
The data were collected in 2007 and 1985-1987, and reported
in 2008 and 1992, respectively.
Data were collected throughout the calendar year.
The studies are widely available to the public.
Results can be reproduced or methodology can be followed
and evaluated.
Quality assurance is discussed in the documentation on the
U.S. Census Bureau studies.
The study provided data by age and sex. Variability across
several geographic regions was noted. Type of ownership was
also addressed.
The U.S. Census Bureau data was truncated at 65 years.
The studies received high levels of peer review and appear in
publications.
The 2 studies produced similar results.
Rating
Medium
Medium
High
Medium
High
Medium
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Chapter 16—Activity Factors
16.3. ACTIVITY PATTERNS
16.3.1. Key Activity Pattern Studies
16.3.1.1. Wiley et al (1991)—Study of Children's
Activity Patterns
The California Study of Children's Activity
Patterns survey (Wiley et al., 1991) provided
estimates of the time children spent in various
activities and locations (microenvironments) on a
typical day. The sample population consisted of
1,200 children, under 12 years of age, selected from
English-speaking households using Random Digit
Dial (ROD) methods. This represented a survey
response rate of 77.9%. One child was selected from
each household. If the selected child was less than
9 years old, the adult in the household who spent the
most time with the child responded. However, if the
selected child was between 9 and 11 years old, that
child responded. The population was also stratified to
provide representative estimates for major regions of
the state. The survey questionnaire included a time
diary which provided information on the children's
activity and location patterns based on a 24-hour
recall period. In addition, the survey questionnaire
included questions about potential exposure to
sources of indoor air pollution (e.g., presence of
smokers) on the diary day, and the socio-demographic
characteristics of children and adult respondents. The
questionnaires and the time diaries were administered
via a computer-assisted telephone interviewing
(CATI) technology (Wiley etal., 1991). The
telephone interviews were conducted during April
1989 to February 1990 over 4 seasons: spring (April
to June 1989), summer (July to September 1989), fall
(October to December 1989), and winter (January to
February 1990).
The data obtained from the survey interviews
resulted in 10 major activity categories, 113 detailed
activity codes, 6 major categories of locations, and
63 detailed location codes. The time respondents
under 12 years of age spent in the 10 activity
categories (plus a "don't know" or non-coded activity
category) are presented in Table 6-7. For each of the
10 activity categories, this table presents the mean
duration for all survey participants, the percentage of
respondents who reported participating in the activity
(i.e., percent doers), and the mean, median, and
maximum duration for only those survey respondents
who engaged in the activity (i.e., doers). It also
includes the detailed activity with the highest mean
duration of time for each activity category. The
activity category with the highest time expenditure
was personal needs and care, with a mean of
794 minutes/day (13.2 hours/day). Night sleep was
the detailed activity that had the highest mean
duration in that activity category. The activity
category "don't know" had a mean duration of about
2 minutes/day and only 4% of the respondents
reported missing activity time.
Table 16-8 presents the mean time spent in the
10 activity categories by age and sex. Because the
original source data were available, U.S. EPA
re-analyzed the data according to the standardized
age categories used in this handbook. Differences
between activity patterns in boys and girls tended to
be small. Table 16-9 presents the mean time spent in
the 10 activity categories grouped by season and
geographic region in the state of California. There
were seasonal differences for 5 activity categories:
personal needs and care, education,
entertainment/social, recreation, and
communication/passive leisure. Time expenditure
differences in various regions of the state were
minimal for childcare, work-related, goods/services,
personal needs and care, education,
entertainment/social, and recreation.
Table 16-10 presents the distribution of time
across 6 location categories. The mean duration for
all survey participants, the percent of respondents
engaging in the activity (i.e., percent doers); the
mean, median, and maximum duration for doers
only; and the detailed locations with the highest
average time expenditure are shown. For all survey
respondents, the largest mean amount of time spent
was at home (1,078 minutes/day); 99% of
respondents spent time at home (mean of
1,086 minutes/day for these individuals only).
Tables 16-11 and 16-12 show the average time spent
in the 6 locations grouped by age and sex, and
season and region, respectively. Again, because the
original source data were available, the age
categories used by Wiley et al. (1991) have been
replaced in Table 16-11 by the standardized age
categories used in this handbook. There were
relatively large differences among the age groups in
time expenditure for educational settings (see
Table 16-11). There were small differences in time
expenditure at the 6 locations by region, but time
spent in school decreased in the summer months
compared with other seasons (see Table 16-12).
Table 16-13 shows the average time children
spent in proximity to gasoline fumes and gas oven
fumes. In general, the sampled children spent more
time closer to gasoline fumes than to gas oven
fumes. The age categories in Table 16-13 have been
modified to conform to the standardized categories
used in this handbook.
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The U.S. EPA estimated the total time indoors
and outdoors using the data from the Wiley et al.
(1991) study. Activities performed indoors were
assumed to include household work, child care,
personal needs and care, education, and
communication/passive leisure. The average times
spent in these indoor activities and half the time spent
in each activity which could have occurred either
indoors or outdoors (i.e., work-related,
goods/services, organizational activities,
entertainment/social, don't know/not coded) were
summed. Table 16-14 summarizes the results of this
analysis using the standard age groups.
A limitation of this study is that the sampling
population was restricted to only English-speaking
households; therefore, the data obtained do not
represent the diverse population group present in
California. Another limitation is that time use values
obtained from this survey were based on short-term
recall (24-hour) data; therefore, the data set obtained
may be biased. Other limitations are as follows: the
survey was conducted in California and is not
representative of the national population, and the
significance of the observed differences in the data
obtained (i.e., sex, age, seasons, and regions) were not
tested statistically. An advantage of this study is that
time expenditure in various activities and locations
were presented for children grouped by age, sex, and
season. Also, potential exposures of respondents to
pollutants were explored in the survey. Another
advantage is the use of the CATI program in
obtaining time diaries, which allows automatic coding
of activities and locations onto a computer tape, and
allows activities forgotten by respondents to be
inserted into their appropriate position during
interviewing.
16.3.1.2. U.S. EPA (1996)—Descriptive Statistics
Tables from a Detailed Analysis of the
National Human Activity Pattern Survey
(NHAPS) Data
U.S. EPA (1996) analyzed data collected by the
National Human Activity Pattern Survey. This survey
was conducted by U.S. EPA and is the largest and
most current human activity pattern survey available
(U.S. EPA, 1996). Data for 9,386 respondents in the
48 contiguous United States were collected via
minute-by-minute 24-hour diaries. NHAPS was
conducted from October 1992 through September
1994 by the University of Maryland's Survey
Research Center using CATI technology to collect
24-hour retrospective diaries and answers to a number
of personal and exposure related questions from each
respondent. Detailed data were collected for a
maximum of 82 different possible locations, and a
maximum of 91 different activities. Participants were
selected using a ROD method. The response rate was
63% overall. If the chosen respondent was a child
less than 10 years of age, an adult in the household
gave a proxy interview. Each participant was asked
to recount their entire daily routine from midnight to
midnight immediately previous to the day that they
were interviewed. The survey collected information
on duration and frequency of selected activities and
of the time spent in selected microenvironments. In
addition, demographic information was collected for
each respondent to allow for statistical summaries to
be generated according to specific groups of the U.S.
population (i.e., by sex, age, race, employment
status, census region, season, etc.). Saturdays and
Sundays were over sampled to ensure an adequate
weekend sample.
For children, the source data from U.S. EPA
have been reviewed and re-analyzed by U.S. EPA to
conform to the age categories recommended in
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
This analysis was weighted according to geographic,
socioeconomic, time/season, and other demographic
factors to ensure that results were representative of
the U.S. population. The weighted sample matched
the 1990 U.S. census population for each sex, age
group, census region, and the day-of-week and
seasonal responses were equally distributed.
Tables 16-15 through 16-44 provide data from
the NHAPS study. Because no data were available
on subjects' age in months, age groups less than
1 year old were consolidated into a single group.
These tables provide statistics for 24-hour
cumulative time spent (mean, minimum, percentiles,
and maximum) in selected locations or engaging in
selected activities. The original analysis generated
statistics for the subset of the survey population that
reported being in the location or doing the activity in
question (i.e., doers only). For the reanalysis,
statistics were calculated for the entire survey
population (i.e., whole population) and for doers
only. When the sample size was 10 persons or fewer,
percentile values were not calculated.
Data are presented for the time children, aged
birth to less than 21 years, spent in various locations
and doing various activities. Each children only table
is followed by a table for the whole population
which presents data for specific populations (i.e., by
sex, age, race, ethnicity, employment, education,
Census region, day of the week, season, asthma
status, and bronchitis/emphysema status) and
includes the time adults, aged 18 years and older,
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Chapter 16—Activity Factors
spent in various locations and doing various activities.
Tables 16-15 and 16-16 present data for time spent in
rooms of the house (e.g., kitchen, bathroom, bedroom,
and garage), and all rooms combined, for children and
by demographic characteristics (including adulthood)
respectively. Tables 16-17 and 16-18 present data for
time spent in other indoor locations (e.g., restaurants,
indoors at school, and grocery/convenience stores).
Tables 16-19 and 16-20 present data for the time
survey participants spent outdoors on school
grounds/playgrounds, parks or golf courses, or pool
rivers, or lakes.
Table 16-21 provides data on time spent in indoor
and outdoor environments for children birth to
<21 years of age. The U.S. EPA estimated the time
spent indoors by adding the average times spent
indoors at the respondents' home (kitchen, living
room, bathroom, etc.), at other houses, and inside
other locations such as school, restaurants, etc. Time
outdoors was estimated by adding the average time
spent outdoors at the respondents' pool and yard,
others' pool and yard, and outside other locations
such as sidewalk, street, neighborhood, parking lot,
service station/gas station, school grounds, park/golf
course, pool, river, lake, farm, etc. Table 16-22
provides data on time spent in outdoor and indoor
environments for adults aged 18 years and older. The
average time spent outdoors was estimated by
summing the average time spent outdoors away from
the residence and the average time spent outdoors at
the residence. Note that these averages are for doers
only and thus over-estimate the total time spent in the
environments for the population.
Tables 16-23 and 16-24 present data for the time
spent in various types of vehicles (i.e., car, truck/van,
bus), and in all vehicles combined. Tables 16-25 and
16-26 present data for the time children and adults
spent in various major activity categories (i.e.,
sleeping, napping, eating, attending school, outdoor
recreation, active sports, exercise, and walking).
Tables 16-27 through 16-31 provide data related
to showering and bathing. Data on handwashing
activities are in Tables 16-32 and 16-33. Tables 16-34
and 16-35 provide data for children on monthly
swimming (in a freshwater pool) frequency and
swimming duration, respectively. Tables 16-36 and
16-37 provide data by demographic characteristics
(including adulthood) on monthly swimming (in a
freshwater pool) frequency and swimming duration,
respectively. Table 16-38 provides data on the time
children spent playing on dirt, sand/gravel, or grass,
and Table 16-39 displays these data by demographic
characteristics (including adulthood). Tables 16-40
and 16-41 provide data on the number of minutes
spent near excessive dust. Tables 16-42 and 16-43
provide information on time spent in the presence of
smokers. For this data set, the authors' original age
categories for children were used because the
methodology used to generate these data could not
be reproduced.
The advantages of the NHAPS data set are that
it is representative of the U.S. population. The
reanalysis done by U.S. EPA to get estimates for
childhood age groups that correspond to the
Guidance on Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005) was
weighted and thus the results presented are balanced
geographically, seasonally, and for day/time. Also,
the NHAPS is inclusive of all ages, sexes, and races.
A disadvantage of the study is that for the standard
age categories, the number of respondents is small
for the "doers" of many activities. In addition, the
durations exceeding 60, 120, and 181 minutes were
not collected for some activities. Therefore, the
actual time spent at the high end of the distribution
for these activities could not be accurately estimated.
In addition, some of the activities were not
necessarily mutually exclusive (e.g., time spent in
active sports likely overlaps with exercise time).
16.3.2. Relevant Activity Pattern Studies
16.3.2.1. Hill (1985)—Patterns of Time Use
Hill (1985) investigated the total amount of time
American adults spend in 1 year performing various
activities and the variation in time use across
3 different dimensions: demographic characteristics,
geographical location, and seasonal characteristics.
In this study, time estimates were based on data
collected from time diaries in 4 waves (I/season) of
a survey conducted in the fall of 1975 through the
fall of 1976 for the 1975-1976 Time Allocation
Study. The sampling periods included 2 weekdays,
1 Saturday and 1 Sunday. The information gathered
was in response to the survey question "What were
you doing?" The survey also provided information
on secondary activities (i.e., respondents performing
more than 1 activity at the same time). Hill (1985)
analyzed time estimates from 971 individuals for
10 broad categories of activities based on data
collected from 87 activities. These estimates
included seasonal variation in time use patterns and
comparisons of time use patterns for different days
of the week.
Analysis of the 1975-1976 survey data revealed
very small regional differences in time use among
the broad activity patterns (Hill, 1985). The weighted
mean hours/week spent performing the 10 major
activity categories presented by region are shown in
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Table 16-44. Table 16-45 presents the time spent per
day, by the day of the week for the 10 major activity
categories. Adult time use was dominated in
descending order by personal care (including sleep),
market work, passive leisure, and housework.
Collectively, these activities represent about 80% of
available time (Hill, 1985).
According to Hill (1985), sleep (included in
personal care) was the single most dominant activity
averaging about 56.3 hours/week. Television
watching (included in passive leisure) averaged about
21.8 hours/week, and housework activities averaged
about 14.7 hours/week. Weekdays were
predominantly market-work oriented. Weekends
(Saturday and Sunday) were predominantly devoted
to household tasks ("sleeping in," socializing, and
active leisure) (Hill, 1985). Table 16-46 presents the
mean time spent performing these 10 groups of
activities during each wave of interview (fall, winter,
spring, and summer). Adjustments were made to the
data to assure equal distributions of weekdays,
Saturdays, and Sundays (Hill, 1985). The data
indicate that the time periods adults spent performing
market work, child care, shopping, organizational
activities, and active leisure were fairly constant
throughout the year (Hill, 1985). The mean hours
spent per week in performing the 10 major activity
patterns are presented by sex in Table 16-47. These
data indicate that time use patterns determined by data
collected for the mid-1970's survey show sex
differences. Men spent more time on activities related
to labor market work and education, and women spent
more time on household work activities.
A limitation associated with this study is that the
time use data were obtained from an old survey
conducted in the mid-1970s. Because of fairly rapid
changes in American society, applying these data to
current exposure assessments may result in some
biases. Another limitation is that time use data were
not presented for children. An advantage of this study
is that time diaries were kept and data were not based
on recall. The former approach may result in a more
accurate data set. Another advantage of this study is
that the survey is seasonally balanced since it was
conducted throughout the year and the data are from a
large survey sample.
16.3.2.2. Timmer et al (1985)—How Children Use
Time
Timmer et al. (1985) conducted a study using the
data obtained on children's time use from a 1981-
1982 panel study. Data were obtained for 389 children
between 3 and 17 years of age. Data were collected
using a time diary and a standardized interview. The
time diary involved children reporting their activities
beginning at 12:00 a.m. the previous night, the
duration and location of each activity, the presence
of another individual, and whether they were
performing other activities at the same time. The
standardized interview was administered to the
children to gather information about their
psychological, intellectual (using reading
comprehension tests), and emotional well-being;
their hopes and goals; their family environment; and
their attitudes and beliefs.
For preschool children, parents provided
information about the child's previous day's
activities. Children in first through third grades
completed the time diary with their parents'
assistance and, in addition, completed reading tests.
Children in 4th grade and above provided their own
diary information and participated in the interview.
Parents were asked to assess their children's
socioemotional and intellectual development, and a
survey form was sent to a teacher of each school-age
child to evaluate their socioemotional and
intellectual development. The activity descriptor
codes used in this study were developed by Juster
etal. (1983).
The mean time spent performing major activities
on weekdays and weekends by age, sex, and type of
day is presented in Table 16-48. On weekdays,
children spend about 40% of their time sleeping,
20% in school, and 10% eating, and performing
personal care activities (Timmer et al., 1985). The
data in Table 16-48 indicate that girls spent more
time than boys performing household work and
personal care activities and less time playing sports.
Also, the children spent most of their free time
watching television.
Table 16-49 presents the mean time children
spent during weekdays and weekends performing
major activities by 5 different age groups. The
significant effects of each variable (i.e., age and sex)
are also shown. Older children spent more time
performing household and market work, studying,
and watching television and less time eating,
sleeping, and playing. The authors estimated that, on
average, boys spent 19.4 hours a week and girls
spent 17.8 hours/week watching television.
U.S. EPA estimated the total time indoors and
outdoors using the Timmer et al. (1985) data.
Activities performed indoors were assumed to
include household work, personal care, eating,
sleeping, attending school, studying, attending
church, watching television, and engaging in
household conversations. The average times spent in
these indoor activities and half the time spent in each
activity which could have occurred indoors or
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outdoors (e.g., market work, sports, hobbies, art
activities, playing, reading, and other passive leisure)
were summed. Table 16-50 summarizes the results of
this analysis by age group and day of the week.
A limitation associated with this study is that it
was conducted in 1981. It is likely that activity
patterns of children have changed from 1981 to the
present. Thus, the application of these data to current
exposure assessments may bias their results. Another
limitation is that the data do not provide overall
annual estimates of children's time use since data
were collected only during the time of the year when
children attended school and not during school
vacations. An advantage of this survey is that diary
recordings of activity patterns were kept and the data
obtained were not based entirely on recall. Another
advantage is that parents assisted younger children
with keeping their diaries and with interviews,
minimizing any bias that may have been created by
having younger children record their own data.
16.3.2.3. Robinson and Thomas (1991)—Time
Spent in Activities, Locations, and
Microenvironments: A California-
National Comparison
Robinson and Thomas (1991) reviewed and
compared data from the 1987-1988 California Air
Resources Board (CARD) time-activity study for
California residents and from a similar 1985 national
study, Americans' Use of Time, conducted at the
University of Maryland. Both studies used the diary
approach to collect data. Time-use patterns were
collected for individuals aged 12 years and older.
Telephone interviews based on the ROD procedure
were conducted for 1,762 and 2,762 respondents for
the CARD study and the national study, respectively.
Robinson and Thomas (1991) defined a set of
16 microenvironments based on the activity and
location codes employed in the 2 studies. The mean
durations of time spent in the 16 microenvironments
by age, are presented in Table 16-51. In both studies,
children and adults spent the majority of their time
sleeping, and engaging in leisure and work/study-
related activities.
Table 16-52 shows the mean time spent in the
10 major activities by sex and for all respondents
between the ages of 18-64 years. Table 16-53 presents
the mean time spent at 3 major locations for the
CARD and national study grouped by total sample
and sex, ages 18-64 years. The mean duration of time
spent in locations for total sample population,
12 years and older, across 3 types of locations is
presented in Table 16-54 for both studies.
The limitations associated with the Robinson
and Thomas (1991) study are that the CARB survey
was performed in California only and may not be
representative of the U.S. population as a whole, and
the studies were conducted in the 1980s and activity
patterns may have changed over time. Another
limitation is that the data are based on short-term
studies. Finally, the available data could not be
re-analyzed to conform to the standardized age
categories used in this handbook.
16.3.2.4. Funk et al. (1998)—Quantifying the
Distribution of Inhalation Exposure in
Human Populations: Distribution of
Time Spent by Adults, Adolescents, and
Children at Home, at Work, and at
School
Funk et al. (1998) used the data from the CARB
study to determine distributions of exposure time by
tracking the time spent participating in daily
activities for male and female children, adolescents,
and adults. CARB performed 2 studies from 1987 to
1990; the first was focused on adults (18 years and
older) and adolescents (12 to 17 years old), and the
second focused on children (6 to 11 years old). The
targeted groups were non-institutionalized English
speaking Californians with telephones in their
residences. Individuals were contacted by telephone
and asked to account for every minute within the
previous 24 hours, including the amount of time
spent on an activity and the location of the activity.
The surveys were conducted on different days of the
week as well as different seasons of the year.
Using the location descriptors provided in the
CARB study, Funk et al. (1998) categorized the
activities into 2 groups, "at home" (any activity at
principal residence) and "away." Each activity was
assigned to 1 of 3 inhalation rate levels (low,
moderate, or high) based on the level of exertion
expected from the activity. Ambiguous activities
were assigned to moderate inhalation rate levels.
Among the adolescents and children studied, means
were determined for the aggregate age groups.
Sample sizes are shown in Table 16-55.
Funk et al. (1998) used several statistical
methods, such as Chi-square, Kolmogorov-Smirnov,
and Anderson-Darling, to determine whether the
time spent in an activity group had a known
distribution. Most of the activities performed by all
individuals were assigned a low or moderate
inhalation rate (see Table 16-56).
The aggregate time periods spent at home in
each activity are shown in Table 16-57. Aggregate
time spent at home performing different activities
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was compared between sexes. There were no
significant differences between adolescent males and
females in any of the activity groups (see
Table 16-58). There were significant differences
between males and females among adults in all
activity groups except for the low activity group (see
Table 16-58). In children, ages 6 to 11 years,
differences between sex and age were observed at the
low inhalation rate levels. There were significant
differences (p < 0.05) between 2 age groups (6 to
8 years, and 9 to 11 years) and sex at the moderate
inhalation rate level (see Table 16-59).
A limitation of this study was that large
proportions of the respondents in the study did not
participate in high-inhalation rate-level activities. The
Funk et al. (1998) study was based on data from
1 geographic location, collected more than a decade
ago. Thus, it may not be representative of current
activities among the general population of the United
States.
16.3.2.5. Cohen Hubal et al. (2000)—Children's
Exposure Assessment: A Review of
Factors Influencing Children's Exposure
and the Date Available to Characterize
and Assess That Exposure
Cohen Hubal et al. (2000) reviewed available
data from the Consolidated Human Activity Database
(CHAD, U.S. EPA, 2000), including activity pattern
data, to characterize and assess environmental
exposures to children. Data from the 2 key studies in
this chapter (Wiley et al., 1991; U.S. EPA, 1996) are
included in CHAD. CHAD was developed by the
U.S. EPA's National Exposure Research Laboratory
to provide access to existing human activity pattern
data for use in exposure and risk assessment efforts. It
is available online at http://www.epa.gov/chadnetl/.
Data from twelve activity pattern studies conducted at
the city, state, and national levels are included in
CHAD. CHAD contains both the original raw data
from each study and data modified based on
predefined format requirements. Modifications made
to data included: receding of variables to fit into them
a common activity/location code system, and
standardization of time diaries to an exact 24-hour
length. Detailed information on the coding system and
the studies included in CHAD is available in the
CHAD User Manual, available at
http://oaspub.epa.gov/chad/
CHAD_Datafiles$.startup#Manual, and in McCurdy
et al. (2000).
A total of 144 activity codes and 115 location
codes were used in CHAD (McCurdy et al., 2000).
Although some participants in a study conducted
multiple activities, many activities were only
conducted within a few studies. The same is true for
activity locations. The selection of exposure
estimates for a particular activity or particular
location should be based on study parameters that
closely relate to the exposure scenario being
assessed. The maximum amount of time, on average,
within a majority of the studies was sleeping or
taking a nap, while the maximum amount of time
spent at a particular location was at home or at work,
depending on the study.
Many of the limitations of CHAD data arise
from the incorporation of multiple studies into the
time diary functions specified in CHAD. Activities
and locations were coded similarly to the NHAPS
study; studies with differing coding systems were
modified to fit the NHAPS codes. In some cases start
times and end times from a study had to be adjusted
to fit a 24-hour period. Respondents were not
randomly distributed in CHAD. For example, some
cities or states were over sampled because entire
studies were carried out in those places. Other
studies excluded large groups of people such as
smokers, or non-English speakers, or people without
telephones. Many surveys were age restricted, or
they preferentially sampled certain target groups. As
a result, users are cautioned against using random
individuals in CHAD to represent the U.S.
population as a whole (Stallings et al., 2000).
CHAD contains 3,009 person-days of
macroactivity data for 2,640 children less than
12 years of age (Cohen Hubal et al., 2000) (see
Table 16-60). The number of hours these children
spent in various microenvironments are shown in
Table 16-61 and the time they spent in various
activities indoors at home is shown in Table 16-62.
Cohen Hubal et al. (2000) noted that CHAD
contains approximately "140 activity codes and
110 location codes, but the data generally are not
available for all activity locations for any single
respondent. In fact, not all of the codes were used for
most of the studies. Even though many codes are
used in macroactivity studies, many of the activity
codes do not adequately capture the richness of what
children actually do. They are much too broadly
defined and ignore many child-oriented behaviors.
Thus, there is a need for more and better-focused
research into children's activities."
U.S. EPA updated the analysis performed by
Cohen Hubal et al. (2000) using CHAD data
downloaded in 2000, sorted according to the age
groups recommended in Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants
(U.S. EPA, 2005). Tables 16-63 and 16-64 show the
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results. In this analysis, individual study participants
within CHAD whose behavior patterns were
measured over multiple days were treated as multiple
1-day activity patterns. This is a potential source of
error or bias in the results because a single individual
may contribute multiple data sets to the aggregate
population being studied.
Advantages of the CHAD database are that it
includes data from 12 activity pattern studies and is a
fairly comprehensive tool for cohort development and
for simulating individuals within exposure
assessments. However, because the database is
comprised of separate studies, issues such as quality
assurance and consistency between the studies are
difficult to assess. In addition, current human activity
pattern surveys do not collect data on microactivities
that are important to understanding exposures,
especially for children, nor do they discriminate
sufficiently among activities important to developing
energy expenditure estimates.
16.3.2.6. Wongetal. (2000)—Adult Proxy
Responses to a Survey of Children's
Dermal Soil Contact Activities
Wong et al. (2000) conducted telephone surveys
to gather information on children's activity patterns as
related to dermal contact with soil during outdoor
play on bare dirt or mixed grass and dirt surfaces.
This study, the second Soil Contact Survey (SCS-II),
was a follow-up to the initial Soil Contact Survey
(SCS-I), conducted in 1996, that primarily focused on
assessing adult behavior related to dermal contact
with soil and dust (Garlock et al., 1999). As part of
SCS-I, information was gathered on the behavior of
children under the age of 18 years, however, the
questions were limited to clothing choices and the
length of time between soil contact and hand washing.
Questions were posed for SCS-II to further define
children's outdoor activities and hand washing and
bathing frequency. For both soil contact surveys
households were randomly phoned in order to obtain
nationally representative results. The adult
respondents were questioned as surrogates for
1 randomly chosen child under the age of 18 residing
within the household.
In the SCS-II, of 680 total adult respondents with
a child in their household, 500 (73.5%) reported that
their child played outdoors on bare dirt or mixed grass
and dirt surfaces (identified as "players"). Those
children that reportedly did not play outdoors
("non-players") were typically very young (<1 year)
or relatively older (>14 years). Of the 500 children
that played outdoors, 497 played outdoors in warm
weather months (April through October) and 390
were reported to play outdoors during cold weather
months (November through March). These results
are presented in Table 16-65. The frequency
(days/week), duration (hours/day), and total
hours/week spent playing outdoors was determined
for those children identified as "players" (see
Table 16-66). The responses indicated that children
spent a relatively high percentage of time outdoors
during the warmer months, and a lesser amount of
time outdoors in cold weather. The median play
frequency reported was 7 days/week in warm
weather and 3 days/week in cold weather. Median
play duration was 3 hours/day in warm weather and
1 hour/day during cold weather months.
Adult respondents were then questioned as to
how many times per day their child washed his/her
hands and how many times the child bathed or
showered per week, during both warm and cold
weather months. This information provided an
estimate of the time between skin contact with soil
and removal of soil by washing (i.e., exposure time).
Hand washing and bathing frequencies for child
players are reported in Table 16-67. Based on these
results, hand washing occurred a median of 4 times
per day during both warm and cold weather months.
The median frequency for baths and showers was
estimated to be 7 times per week for both warm and
cold weather.
Based on reported household incomes, the
respondents sampled in SCS-II tended to have higher
incomes than that of the general population. This
may be explained by the fact that phone surveys
cannot sample households without telephones.
Additional uncertainty or error in the study results
may have occurred as a result of the use of surrogate
respondents. Adult respondents were questioned
regarding child activities that may have occurred in
prior seasons, introducing the chance of recall error.
In some instances, a respondent did not know the
answer to a question or refused to answer.
Table 16-68 compares mean play duration data from
SCS-II to similar activities identified in NHAPS
(U.S. EPA, 1996). Table 16-69 compares the number
of times per day a child washed his or her hands,
based on data from SCS-II and NHAPS. As
indicated in Tables 16-68 and 16-69, where
comparison is possible, NHAPS and SCS-II results
showed similarities in observed behaviors.
An advantage of this study includes the fact that
a random household survey was conducted to obtain
nationally representative results. A limitation of the
study is that questions were limited to clothing
choices and the length of time between soil contact
and hand washing. In addition, the participants were
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questioned about events from prior seasons, which
may have introduced recall error.
16.3.2.7. Graham andMcCurdy (2004)—
Developing Meaningful Cohorts for
Human Exposure Models
Graham and McCurdy (2004) used a statistical
model (general linear model and analysis of variance
[GLM/ANOVA]) to assess the significance of various
factors in explaining variation in time spent outdoors,
indoors and in motor vehicles. These factors, which
are commonly used in developing cohorts for
exposure modeling, included age, sex, weather,
ethnicity, day type, and precipitation. Activity pattern
data from CHAD, containing 30 or more records per
day, were used in the analysis (Graham and McCurdy,
2004). Data from the 2 key studies in this chapter
(Wiley et al., 1991; U.S. EPA, 1996) are included in
CHAD.
Table 16-70 presents data on time spent outdoors
for people who spent >0 time outdoors (i.e., doers).
Graham and McCurdy (2004) found that all the
factors evaluated were significant (p < 0.001) in
explaining differences in time spent outdoors
(Graham and McCurdy, 2004). An evaluation of sex
differences in time spent outdoors by age cohorts was
also conducted. Table 16-71 presents descriptive
statistics and the results of the 2-sample Kolmogorov-
Smirnov (K-S) test for this evaluation. As shown in
Table 16-71, there were statistically significant sex
differences in time spent outdoors starting with the 6
to 10 year old age category and continuing through all
age groups, up to and including >64 years of age. In
addition, Graham and McCurdy (2004) evaluated the
effect of physical activity and concluded that this was
the most important factor in explaining time spent
outdoors. For time spent indoors (see Table 16-72),
there were statistically significant effects for all the
factors evaluated, with sex, weather, and day type
being the most important variables. Regarding time
spent in motor vehicles (see Table 16-73),
precipitation was the only factor found to have no
significant effects (Graham and McCurdy, 2004).
Based on the results of these analyses, Graham
and McCurdy (2004) noted that "besides age and sex,
other important attributes for defining cohorts are the
physical activity level of individuals, weather factors
such as daily maximum temperature in combination
with months of the year, and combined
weekday/weekend with employment status." The
authors also noted that even though the factors
evaluated were found to be statistically significant in
explaining differences in time spent outdoors,
indoors, and in motor vehicles, "parameters such as
lifestyle and life stages that are absent from CHAD
might have reduced the amount of unexplained
variance." The authors recommended that, in
defining cohorts for exposure modeling, age and sex
should be used as "first-order" attributes, followed
by physical activity level, daily maximum
temperature, and day type (weekend/weekday or
day-of-the-week/working status) (Graham and
McCurdy, 2004).
The CHAD database is a fairly comprehensive
tool for cohort development and for simulating
individuals within exposure assessments. However,
the database is comprised of 12 separate studies, and
because of this, issues such as quality assurance and
consistency between the studies are difficult to
assess. In addition, current human activity pattern
surveys do not collect data on microactivities that are
important to understanding exposures, especially for
children, nor do they discriminate sufficiently among
activities important to developing energy
expenditure estimates. Other limitations of the
CHAD database are described earlier in this chapter
by Cohen Hubal et al. (2000) in Section 16.3.2.5.
16.3.2.8. Juster et al (2004)—Changing Times of
American Youth: 1983-2003
Juster et al. (2004) evaluated changes in time
use patterns of children by comparing data collected
in a 1981-1982 pilot study of children ages 6 to 17
to data from the 2002-2003 Child Development
Supplement (CDS) to the Panel Study of Income
Dynamics (PSID). The 1981-1982 pilot study is the
same study described in Timmer et al. (1985). The
2002-2003 CDS gathered 24-hour time diary data on
2,908 children ages 6 to 17; as was done in the 1997
CDS, information was collected on 1 randomly
selected weekday and 1 randomly selected weekend
day (Juster etal., 2004).
Tables 16-74 and 16-75 present the mean time
children spent (in minutes/day) performing major
activities on weekdays and weekend days,
respectively, for the years 1981-1982 and
2002-2003. Table 16-76 shows the weekly time
spent in these activities for the years 1981-1982 and
2002-2003. Juster et al. (2004) noted that the time
spent in school and studying increased while time
spent in active sports and outdoors activities
decreased during the period studied.
An advantage of this survey is that diary
recordings of activity patterns were kept and the data
obtained were not based entirely on recall. Another
advantage is that because parents assisted younger
children with keeping their diaries and with
interviews, minimizing any bias that may have been
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created by having younger children record their own
data. A limitation associated with this study is that the
data from the Timmer et al. (1985) study were
collected in 1981 and it is likely that the activity
patterns of children have changed from 1981 to the
present. Another limitation is that the data from the
CDS study do not provide overall annual estimates of
children's time use since data were collected only
during the time of the year when children attended
school and not during school vacations.
16.3.2.9. Vandewater et al. (2004)—Linking Obesity
and Activity Level with Children's
Television and Video Game Use
Vandewater et al. (2004) evaluated children's
media use and participation in active and sedentary
activities using 24-hour time-use diaries collected in
1997, as part of the Child Development Supplement
to the Panel Study of Income Dynamics. The PSID is
an ongoing, longitudinal study of U.S. individuals and
their families conducted by the Survey Research
Center of the University of Michigan. In 1997, PSID
families with children younger than 12 years of age
completed the CDS and reported all activities
performed by the children on 1 randomly selected
weekday and 1 randomly selected weekend day. Since
minorities, low-income families, and less educated
individuals were oversampled in the PSID, sample
weights were applied to the data (Vandewater et al.,
2004). More information on the CDS can be found
on-line at http://psidonline.isr.umich.edu/CDS/.
Using time use diary data from 2,831 children
participating in the CDS, Vandewater et al. (2004)
estimated the time in minutes over the 2-day study
period (i.e., sum of time spent on 1 weekday and
1 weekend day) that children spent watching
television, playing games on video games consoles or
computers, reading, and using computers for other
purposes besides playing games. In addition, the time
spent participating in highly active (i.e., playing
sports), moderately active (i.e., fishing, boating,
camping, taking music lessons, and singing), and
sedentary (i.e., using the phone, doing puzzles,
playing board games, and relaxing) activities was
determined. Table 16-77 presents the means and
standard deviations for the time spent in the selected
activities by age and sex.
A limitation of this study is that the survey was
not designed for exposure assessment purposes.
Therefore, the time use data set may be biased.
However, the survey provides a database of current
information on various human activities. This
information can be used to assess various exposure
pathways and scenarios associated with these
activities.
16.3.2.10. U.S. Department of Labor (2007)—
American Time Use Survey, 2006
Results
The American Time Use Study has been
conducted annually since 2003 by the U.S.
Department of Labor's (DOL) Bureau of Labor
Statistics (DOL, 2007). The purpose of the study is
to collect "data on what activities people do during
the day and how much time they spend doing them."
In 2006, the survey focused on "the time Americans
worked, did household activities, cared for
household children, participated in educational
activities, and engaged in leisure and sports
activities." Approximately 13,000 individuals,
15 years of age and older, were interviewed during
2006. Participants were randomly selected and
interviewed using the CATI method and were asked
to recall their activities on the day before the
interview. The survey response rate was 55.1%
(DOL, 2007). Data were collected for all days of the
week, including weekends (i.e., 10% of the
individuals were interviewed about their activities on
1 of the 5 weekdays, and 25% of the individuals
were interviewed about their activities on 1 of the
2 weekend days). Demographic information,
including age, sex, race/ethnicity, marital status, and
educational level were also collected, and sample
weights were applied to records to "reduce bias in
the estimates due to differences in sampling and
response rates across populations and days of the
week." Data were collected for 17 major activities,
which were subsequently combined into
12 categories for publication of the results.
Table 16-78 provides information on the average
amount of time spent in the 12 major time use
categories by sex, age, race/ethnicity, marital status,
and educational level (DOL, 2007). Estimates of
time use in sub-categories of the 12 major categories
are presented in Table 16-79. The majority of time
was spent engaging in personal care activities
(9.41 hours/day) which included sleeping
(8.63 hours/day), followed by leisure and sports
activities (5.09 hours/day), and work activities
(3.75 hours/day). Note that because these data are
averaged over both weekdays and weekends for the
entire year, the amount of time spent daily on
work-related activities does not reflect that of a
typical work day.
Table 16-80 provides estimates of time use for
all children ages 15 to 19 years by sex. It also
provides a more detailed breakdown of the Leisure
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and Sports category for all children, ages 15 to
19 years old.
The limitation of this study is that it did not
account for all activities during the day and therefore
estimates about total time indoors and outdoors could
not be calculated. The advantages are the large sample
size, the representativeness of the sample, and the
currency of the data.
16.3.2.11. Nader et al (2008)—Moderate-to-
Vigorous Physical Activity from Ages 9 to
15 years
Nader et al. (2008) conducted a longitudinal
study of 1,032 children from ages 9 to 15 years. The
purpose of the study was to determine the amount of
time children 9 to 15 years of age engaged in
moderate-to-vigorous physical activities (MVPA) and
compare results with the recommendations issued by
the U.S. Department of Health and Human Services
and the U.S. Department of Agriculture (U.S.
DHHS/DOA, 2005) of a minimum of 60 minutes/day.
Participants were recruited from university-based
community hospitals located in Arkansas, California,
Kansas, Massachusetts, Pennsylvania, Virginia,
Washington, North Carolina, and Wisconsin.
Children's activity levels were recorded for 4 to 7
days using an accelerometer, set so that it recorded
minute-by-minute movement counts. The study
participants included 517 boys and 515 girls.
The study found that at age nine years, children
engaged in 3 hours of MVP A/day. By age 15 years,
the amount of time engaged in MVP A was dropped to
49 minutes/day on weekdays and 35 minutes/day on
weekends. Boys spent 18 more minutes/day of MVP A
than girls on weekdays and 13 more minutes/day on
weekends. Estimates of the mean time spent in
MVPA by various age groups are presented in Table
16-81.
Advantages of this study include the fact that
both weekdays and weekends were included in the
study and the use of an accelerometer to measure
physical activity. A limitation of the study is the fact
that the sample of children was not nationally
representative of the U.S. population. In addition, the
study did not provide information about the amount of
time spent at specific activities.
16.4. OCCUPATIONAL MOBILITY
16.4.1. Key Occupational Mobility Studies
16.4.1.1. Carey (1988)—Occupational Tenure in
1987: Many Workers Have Remained in
Their Fields
Carey (1988) presented median occupational and
employer tenure for different age groups, sex,
earnings, ethnicity, and educational attainment.
Occupational tenure was defined as "the cumulative
number of years a person worked in his or her
current occupation, regardless of number of
employers, interruptions in employment, or time
spent in other occupations" (Carey, 1988). The
information presented was obtained from
supplemental data to the January 1987 Current
Population Study, a U.S. Census Bureau publication.
Carey (1988) did not present information on the
survey design.
The median occupational tenure by age and sex,
race, and employment status are presented in Tables
16-82, 16-83, and 16-84, respectively. The median
occupational tenure of the working population (109.1
million people) 16 years of age and older in January
of 1987 was 6.6 years (see Table 16-82). Table 16-
82 also shows that median occupational tenure
increased from 1.9 years for workers 16 to 24 years
old to 21.9 years for workers 70 years and older. The
median occupational tenure for men 16 years and
older was higher (7.9 years) than for women of the
same age group (5.4 years). Table 16-83 indicates
that Whites had longer occupational tenure (6.7
years) than Blacks (5.8 years), and Hispanics (4.5
years). Full-time workers had more occupational
tenure than part-time workers 7.2 years and 3.1
years, respectively (see Table 16-84).
Table 16-85 presents the median occupational
tenure among major occupational groups. The
median tenure ranged from 4.1 years for service
workers to 10.4 years for people employed in
farming, forestry, and fishing.
The strength of an individual's attachment to a
specific occupation has been attributed to the
individual's investment in education (Carey, 1988).
Carey (1988) reported the median occupational
tenure for the surveyed working population by age
and educational level. Workers with 5 or more years
of college had the highest median occupational
tenure of 10.1 years. Workers that were 65 years and
older with 5 or more years of college had the highest
occupational tenure level of 33.8 years. The median
occupational tenure was 10.6 years for self-
employed workers and 6.2 years for wage and salary
workers (Carey, 1988).
A limitation associated with this study is that the
survey design employed in the data collection was
not presented, though it can be found on the U.S.
Census Bureau's website. Therefore, the validity and
accuracy of the data set cannot be determined.
Another limitation is that only median values were
reported in the study. An advantage of this study is
that occupational tenure (years spent in a specific
occupation) was obtained for various age groups by
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Chapter 16—Activity Factors
sex, ethnicity, employment status, and educational
level. Another advantage of this study is that the data
were based on a survey population which appears to
represent the general U.S. population.
16.4.1.2. Carey (1990)—Occupational Tenure,
Employer Tenure, and Occupational
Mobility
Carey (1990) conducted another study that was
similar in scope to the study of Carey (1988). The
January 1987 Current Population Study was used.
This study provided data on occupational mobility
and employer tenure in addition to occupational
tenure. Occupational tenure was defined in Carey
(1988) as the "the cumulative number of years a
person worked in his or her current occupation,
regardless of number of employees, interruptions in
employment, or time spent in other locations."
Employer tenure was defined as "the length of time a
worker has been with the same employer," while
occupational mobility was defined as "the number of
workers who change from 1 occupation to another"
(Carey, 1990). Occupational mobility was measured
by asking individuals who were employed in both
January 1986 and January 1987 if they were doing the
same kind of work in each of these months (Carey,
1990). Carey (1990) further analyzed the occupational
mobility data and obtained information on entry and
exit rates for occupations. These rates were defined as
"the percentage of persons employed in an occupation
who had voluntarily entered it from another
occupation" and an exit rate was defined as "the
percentage of persons employed in an occupation who
had voluntarily left for a new occupation" (Carey,
1990).
Table 16-86 shows the voluntary occupational
mobility rates in January 1987 for workers 16 years
and older. For all workers, the overall voluntary
occupational mobility rate during that year was 5.3%.
These data also show that younger workers left
occupations at a higher rate than older workers. Carey
(1990) reported that 10 million of the 100.1 million
individuals employed in January 1986 and in January
1987 had changed occupations during that period,
resulting in an overall mobility rate of 9.9%.
Executive, administrative, and managerial
occupations had the highest entry rate of 5.3%,
followed by administrative support (including
clerical) at 4.9%. Sales had the highest exit rate of
5.3% and service had the 2nd highest exit rate of 4.8%
(Carey, 1990). In January 1987, the median employer
tenure for all workers was 4.2 years. The median
employee tenure was 12.4 years for those workers that
were 65 years of age and older (Carey, 1990).
Because the study was conducted by Carey
(1990) in a manner similar to that of the previous
study (Carey, 1988), the same advantages and
disadvantages associated with Carey (1988) also
apply to this data set.
16.5. POPULATION MOBILITY
16.5.1. Key Population Mobility Studies
16.5.1.1. Johnson and Capel (1992)—A Monte
Carlo Approach to Simulating
Residential Occupancy Periods and It's
Application to the General U.S.
Population
Johnson and Capel developed a methodology to
estimate the distribution of the residential occupancy
period (ROP) in the national population. ROP
denotes the time (years) between a person moving
into a residence and the time the person moves out or
dies. The methodology used a Monte Carlo approach
to simulate a distribution of ROP for
500,000 persons using data on population, mobility,
and mortality.
The methodology consisted of 6 steps. The 1st
step defined the population of interest and
categorized them by location, sex, age, sex, and race.
Next the demographic groups were selected and the
fraction of the specified population that fell into each
group was developed using U.S. Census Bureau
data. A mobility table was developed based on
census data, which provided the probability that a
person with specified demographics did not move
during the previous year. The fifth step used data on
vital statistics published by the National Center for
Health Statistics and developed a mortality table
which provided the probability that individuals with
specific demographic characteristics would die
during the upcoming year. As a final step, a
computer based algorithm was used to apply a
Monte Carlo approach to a series of persons selected
at random from the population being analyzed.
Table 16-87 presents the results for residential
occupancy periods for the total population, by sex.
The estimated mean ROP for the total population
was 11.7 years. The distribution was skewed
(Johnson and Capel, 1992): the 25th, 50th, and 75th
percentiles were 3, 9, and 16 years, respectively. The
90th, 95th, and 99th percentiles were 26, 33, and 47
years, respectively. The mean ROP was 11.1 years
for males and 12.3 years for females, and the median
value was 8 years for males and 9 years for females.
Descriptive statistics for groups defined by
current ages were also calculated. These data,
presented by sex, are shown in Table 16-88. The
mean ROP increases from age 3 to age 12 years and
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there is a noticeable decrease at age 24 years.
However, there is a steady increase from age 24
through age 81 years.
There are a few biases within this methodology
that have been noted by the authors. The probability
of not moving is estimated as a function only of sex
and age. The Monte Carlo process assumes that this
probability is independent of (1) the calendar year to
which it is applied, and (2) the past history of the
person being simulated. These assumptions, according
to Johnson and Capel (1992), are not entirely correct.
They believe that extreme values are a function of
sample size and will, for the most part, increase as the
number of simulated persons increases.
16.5.1.2. U.S. Census Bureau (2008a)—American
Housing Survey for the United States in
2007
This survey is a national sample of
55,000 interviews in which data were collected from
present owners, renters, Black householders, and
Hispanic householders. The data reflect the number of
years a unit has been occupied and represent all
occupied housing units that the residents' rented or
owned at the time of the survey.
The results of the survey pertaining to residence
time of owner/renter occupied units in the United
States are presented in Table 16-89. Using the data in
Table 16-89, the percentages of householders living in
houses for specified time ranges were determined and
are presented in Table 16-90. Based on the U.S.
Census Bureau data in Table 16-90, the 50th percentile
and the 90th percentile values were calculated for the
number of years lived in the householder's current
house. These values were calculated by apportioning
the total sample size (110,692 households) to the
indicated percentile associated with the applicable
range of years lived in the current home. Assuming an
even distribution within the appropriate range, the 50th
and 90th percentile values for years living in the
current home were determined to be 8.0 and 32.0
years, respectively. Based on the above data, 8 and
32 years are assumed to best represent a central
tendency estimate of length of residence and upper
percentile estimate of residence time, respectively.
A limitation associated with the above analysis is
the assumption that there is an even distribution
within the different ranges. As a result, the 50th and
90th percentile values may be biased.
16.5.2. Relevant Population Mobility Studies
16.5.2.1. Israeli and Nelson (1992)—Distribution
and Expected Time of Residence for U.S.
Households
In risk assessments, the average current
residence time (time since moving into current
residence) has often been used as a substitute for the
average total residence time (time between moving
into and out of a residence) (Israeli and Nelson,
1992). Israeli and Nelson (1992) have estimated
distributions of expected time of residence for U.S.
households. Distributions and averages for both
current and total residence times were calculated for
several housing categories using the 1985 and 1987
U.S. Census Bureau housing survey data. The total
residence time distribution was estimated from
current residence time data by modeling the moving
process (Israeli and Nelson, 1992). Israeli and
Nelson (1992) estimated the average total residence
time for a household to be approximately 4.6 years
or 1/6 of the expected life span (see Table 16-91).
The maximal total residence time that a given
fraction of households will live in the same residence
is presented in Table 16-92. For example, only 5% of
the individuals in the "All Households" category will
live in the same residence for 23 years and 95% will
move in less than 23 years.
The authors note that the data presented are for
the expected time a household will stay in the same
residence. The data do not predict the expected
residence time for each member of the household,
which is generally expected to be smaller (Israeli and
Nelson, 1992). These values are more realistic
estimates for the individual total residence time, than
the average time a household has been living at its
current residence. The expected total residence time
for a household is consistently less than the average
current residence time. This is the result of greater
weighting of short residence time when calculating
the average total residence time than when
calculating the average current residence time
(Israeli and Nelson, 1992). When averaging total
residence over a time interval, frequent movers may
appear several times, but when averaging current
residence times, each household appears only once
(Israeli and Nelson, 1992). According to Israeli and
Nelson (1992), the residence time distribution
developed by the model is skewed and the median
values are considerably less than the means, which
are less than the average current residence times.
Advantages of this study are the large sample
size and its representativeness to the U.S. population,
since it was based on U.S. Census Bureau housing
survey data. Several limitations of the study have
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been noted by Israeli and Nelson (1992) above. An
additional limitation is the age of the study and the
fact that the U.S. Census Bureau housing survey is
based on recall data.
16.5.2.2. National Association of Realtors (NAR)
(1993)—The Home Buying and Selling
Process
The NAR survey was conducted by mailing a
questionnaire to 15,000 home buyers throughout the
United States who purchased homes during the
second half of 1993. The survey was conducted in
December 1993 and 1,763 usable responses were
received, equaling a response rate of 12% (NAR,
1993). Of the respondents, 41% were first time
buyers. Home buyer names and addresses were
obtained from Dataman Information Services (DIS).
DIS compiles information on residential real estate
transactions from more than 600 counties throughout
the United States using courthouse deed records. Most
of the 250 Metropolitan Statistical Areas are also
covered in the DIS data compilation.
The home buyers were questioned on the length
of time they owned their previous home. The typical
homebuyer (40%) was found to have lived in their
previous home between 4 and 7 years (see
Table 16-93). The survey results indicate that the
average tenure of home buyers is 7.1 years based on
an overall residence history of the respondents (NAR,
1993). In addition, the median length of residence in
respondents' previous homes was found to be 6 years
(see Table 16-94).
The distances the respondents moved to their new
homes were typically short distances. Data presented
in Table 16-95 indicate that the mean distances range
from 230 miles for new home buyers and 270 miles
for repeat buyers to 110 miles for first time buyers
and 190 for existing home buyers. Seventeen percent
(17%) of respondents purchased homes over
100 miles from their previous homes and
49% purchased homes less than 10 miles away.
Advantages of this study are the large sample size
and its representativeness to the U.S. population,
since it was based on 15,000 home buyers throughout
the United States. A limitation of the study is the fact
that the data are over 17 years old.
16.5.2.3. U.S. Census Bureau (2008b)—Current
Population Survey 2007, Annual Social
and Economic Supplement
The Current Population Survey is conducted
monthly by the U.S. Census Bureau. The sample is
selected to be statistically representative of the
civilian non-institutionalized U.S. population. The
data presented in Tables 16-96 and 16-97 are yearly
averages for the year 2006-2007. Approximately
50,000 people are surveyed each month.
Table 16-96 presents data on general mobility
by demographic factors (i.e., sex, age, education,
marital status, nativity, tenure, and poverty status).
"Movers" are respondents who did not report living
at the same residence 1 year earlier than the date of
interview. Of the total number of respondents, 13%
had moved residences. Of those, 65% moved within
the same county. Table 16-97 presents data on these
intercounty moves and shows that of these
intercounty moves, over 60% moved less than
200 miles.
Advantages of this study are the large sample
size, the currency of the data set, and its
representativeness to the U.S. population.
Limitations are that the study is based on recall data
and that due to the Current Population Survey
design, data for states are not as reliable as
nationwide estimates.
16.6. REFERENCES FOR CHAPTER 16
Brownson, RC; Boehmer, TK; Luke, DA. (2005)
Declining rates of physical activity in the
United States: What are the contributors?
Ann Rev Pub Health 26:421-443.
Carey, M. (1988) Occupational tenure in 1987: many
workers have remained in their fields.
Monthly Labor Rev 111:3-12.
Carey, M. (1990) Occupational tenure, employer
tenure, and occupational mobility.
Occupational Outlook Quarterly. Summer
1990:55-60.
Chance, WG; Harmsen, E. (1998) Children are
different: environmental contaminants and
children's health. Can J Public Health
89(Suppl 1):S9-S13.
Cohen Hubal, EA; Sheldon, LS; Burke, JM;
McCurdy, TR; Berry, MR; Rigas, ML;
Zartarian, VG; Freeman, NG. (2000)
Children's exposure assessment: a review of
factors influencing children's exposure and
the data available to characterize and assess
that exposure. Environ Health Persp
108(6):475^86.
Elgethun, K; Fenske, RA; Yost, MG; Palcisko, GJ.
(2003) Time-location analysis for exposure
assessment studies of children using a novel
global positioning system instrument.
EnvironHealth Persp 111(1):115-122.
Funk, L; Sedman, R; Beals, JAJ; Fountain, R. (1998)
Quantifying the distribution of inhalation
exposure in human populations:
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1. Distributions of time spent by adults,
adolescents, and children at home, at work,
and at school. Risk Anal 18(l):47-56.
Garlock, TJ; Shirai, JH; Kissel, JC. (1999) Adult
responses to a survey of soil contact related
behaviors. J Expo Anal Environ Epidemiol
9(2):134-142.
Graham, SE; McCurdy, T. (2004) Developing
meaningful cohorts for human exposure
models. J Expo Anal Environ Epidemiol
14:23-43.
Hill, MS. (1985) Patterns of time use. In: Juster, F.T.;
Stafford, P.P., eds. Time, goods, and
well-being. Ann Arbor, MI: University of
Michigan, Survey Research Center, Institute
for Social Research, pp. 133-176.
Israeli, M; Nelson, CB. (1992) Distribution and
expected time of residence for U.S.
households. Risk Anal 12(l):65-72.
Johnson, T. (1989) Human activity patterns in
Cincinnati, Ohio. Palo Alto, CA: Electric
Power Research Institute.
Johnson, T; Capel, J. (1992) A Monte Carlo approach
to simulating residential occupancy periods
and its application to the general U.S.
population. U.S. Environmental Protection
Agency, Office of Air Quality and Standards,
Research Triangle Park, NC. Available
online at http://nepis.epa.gov/Exe
/ZyPURL.cgi?Dockey=2000MU7N.txt.
Juster, FT; Hill, MS; Stafford, FP; Eccles Parsons, J.
(1983). Time use longitudinal panel study,
1975-1981. University of Michigan, Survey
Research Center, Institute for Social
Research, Ann Arbor, MI. Available online
at
http://www.icpsr.umich.edu/icpsrweb/ICPSR
/studies/09054.
Juster, T; Ono, H; Stafford, F (2004) Changing times
of American youth: 1981-2003. Institute for
Social Research, University of Michigan,
Ann Arbor, Michigan. Available on-line at
http://www.umich.edu/news/Releases/2004/
Nov04/teen_time_report.pdf.
McCurdy, T; Glen, G; Smith, L; Lakkadi, Y. (2000)
The National Exposure Research
Laboratory's consolidated human database. J
Expo Anal Environ Epidemiol 10(6 pt
l):566-578.
Nader, PR; Bradley, RH; Houts, RM; McRitchie, SL;
O'Brien, M. (2008) Moderate-to-vigorous
physical activity from ages 9 to 15 years.
JAMA300(3):295-305.
NAR (National Association of Realtors). (1993) The
homebuying and selling process: 1993. The
Real Estate Business Series. Washington,
DC: NAR.
Phillips, ML; Hall, TA; Esmen, NA; Lynch, R;
Johnson, DL. (2001) Use of global
positioning system technology to track
subject's location during environmental
exposure sampling, J Expo Anal Environ
Epidemiol 11(3):207-215.
Robinson, JP; Thomas, J. (1991) Time spent in
activities, locations, and
microenvironments: a California-National
Comparison Project report.
U.S. Environmental Protection Agency,
Environmental Monitoring Systems
Laboratory, Las Vegas, NV.
Stallings, C; Tippett, J; Glen, G; Smith, L. (2000)
CHAD'S user guide: Extracting human
activity information from CHAD on the PC.
Prepared for the U.S. EPA National
Exposure Research Laboratory by ManTech
Environmental Technology, Inc. Available
online at http://www.epa.gov/chadnetl/
reports/CHAD_Manual.pdf.
Timmer, SG; Eccles, J; O'Brien, K. (1985) How
children use time. In: Juster, FT; Stafford,
FP; eds. Time, goods, and well-being. Ann
Arbor, MI: University of Michigan, Survey
Research Center, Institute for Social
Research, pp. 353-380.
U.S. DHHS/DOA (Department of Health and Human
Services/Department of Agriculture). (2005)
Dietary guidelines for Americans, 2005.
6th edition. Government Printing Office,
Washington, DC. Available online at
http://www.health.gov/dietaryguidelines/dg
a2005/document/pdf/DGA2005 .pdf.
U.S. Census Bureau. (2008a) American housing
survey for the United States in 2007. U.S.
Government Printing Office, Washington,
DC. Available online at
http://www.census.gov/prod/2008pubs/hl50
-07.pdf.
U.S. Census Bureau. (2008b) Current population
survey, 2007 annual social and economic
supplement. Table 1. Internet Release.
Available online at
http://www.census.gov/apsd/techdoc/cps/cp
smar07.pdf.
U.S. Census Bureau. (2010) Current population
survey, annual social and economic
supplement. Washington, DC: U.S.
Government Printing Office. Available
online at
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http://www.census.gov/apsd/techdoc/cps/cps
mar09.pdf.
U.S. DOL (Department of Labor). (2007) American
time use survey - 2006. Results. News
release, June 28, 2007. Bureau of Labor
Statistics, Washington, DC. Available online
at at http://www.bls.gov/news.release/
archives/atus_06032008.pdf.
U.S. EPA (Environmental Protection Agency). (1996)
Descriptive statistics tables from a detailed
analysis of the National Human Activity
Pattern Survey (NHAPS) data. Office of
Research and Development, Washington,
DC. EPA/600/R-96/148. Available online at
http://exposurescience.org/pub/reports/NHA
PS_RPT2_DescStat.pdf.
U.S. EPA (Environmental Protection Agency). (2000)
Consolidated Human Activity Database
(CHAD). National Exposure Research
Laboratory, Washington, DC. Available
online at http://www.epa.gov/chadnetl/.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Risk Assessment Forum, Washington, DC;
EPA/630/P-03/003F. Available online at
http ://www. epa. gov/raf/publications/pdfs/AG
EGROUPS.PDF.
Vandewater, EA; Shim, M; Caplovitz, AG. (2004)
Linking obesity and activity level with
children's television and video game use. J
Adolesc 27:71-85.
Wiley, JA; Robinson, JP; Cheng, Y; Piazza, T; Stork,
L; Plasden, K. (1991) Study of children's
activity patterns. California Environmental
Protection Agency, Air Resources Board
Research Division. Sacramento, CA.
Available online at http://www.arb.ca.gov/
research/apr/past/a733-149a.pdf.
Wong, EY; Shirai, JH; Garlock, TJ; Kissel, JC. (2000)
Adult proxy responses to a survey of
children's dermal soil contact activities. J
Expo Anal Environ Epidemiol
10(6):509-517.
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Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, for All Respondents and Doers
Activity Category
Work-related11
Household0
Childcared
Good/Service'
Personal Needs and Caref
Education8
Organizational Activities'1
Entertain/Social1
RecreationJ
Mean
Duration
(All)
10
53
<1
21
794
110
4
15
239
Doers8
25
86
<1
26
100
35
4
17
92
Mean
Duration
(Doers)8
39
61
83
81
794
316
111
87
260
Median
Duration
(Doers)8
30
40
30
60
770
335
105
60
240
Maximum
Duration
(Doers)8
405
602
290
450
1,440
790
435
490
835
Detailed Activity with
Highest Average Minutes
Eating at Work/School/Daycare
Travel to Household
Other Child Care
Errands
Night Sleep
School Classes
Attend Meetings
Visiting with Others
Games
Communication/Passive
Leisure k
Don't know/Not coded
All Activities
192
2
1,440
93
4
-
205
41
-
180
15
-
898
600
-
TV Use
-
-
Doers indicate the respondents who reported participating in each activity category.
Includes: travel to and during work/school; children's paid work; eating at work/school/daycare; and accompanying or watching adult
at work.
Includes: food preparation; meal cleanup; cleaning; clothes care; car and home repair/painting; building a fire; plant and pet care; and
traveling to household.
Includes: baby and child care; helping/teaching children; talking and reading; playing while caring for children; medical care; travel
related to child care; and other care.
Includes: shopping; medical appointments; obtaining personal care services (e.g., haircuts), government and financial services, and
repairs; travel related to goods and services; and errands.
Includes: bathing, showering, and going to bathroom; medical care; help and care; meals; night sleep and daytime naps, dressing and
grooming; and travel for personal care.
Includes: student and other classes; daycare; homework; library; and travel for education.
Includes: attending meetings and associated travel.
Includes: sports events; eating and amusements; movies and theater; visiting museums, zoos, art galleries, etc.; visiting others; parties
and other social events; and travel to social activities.
Includes: active sports; leisure; hobbies; crafts; art; music/drama/dance; games; playing; and travel to leisure activities.
Includes: radio and television use; reading; conversation; paperwork; other passive leisure; and travel to passive leisure activities.
Source: Wiley et al., 1991.
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Chapter 16—Activity Factors
Table 16-8. Mean Time (minutes/day) Children
Ten Major Activity Categories,
Activity
Category8
Work-related
Household
Childcare
Goods/Services
Personal Needs and Care
Education
Organizational Activities
Entertainment/Social
Recreation
Communication/Passive
Leisure
Sample Sizes
(Unweighted)
Category8
Work-related
Household
Childcare
Goods/Services
Personal Needs and Care
Education
Organizational Activities
Entertainment/Social
Recreation
Communication/Passive
Leisure
Sample Sizes
(Unweighted)
Birth to
1 Month
0
12
0
0
910
180C
0
0
0
338
3
Birth to 1
Month
0
28
0
0
1,123
0
0
0
0
290
4
lto<3
Months
0
30
0
16
1,143
0
0
0
0
250
7
lto<3
Months
0
29
0
18
1,115
0
0
0
0
278
10
3to<6
Months
0
49
0
14
937
75
0
0
26
339
15
3to<6
Months
5
23
0
14
971
110
0
0
10
308
11
6to<12
Months
1
28
0
28
919
70
0
0
104
292
31
6to<12
Months
1
25
0
24
922
94
0
1
147
226
23
lto<2
Years
8
35
0
27
903
33
7
8
314
106
54
lto<2
Years
3
45
0
24
894
25
0
13
256
179
43
Under 12 Years of Age Spent in
by Age and Sex
Boys
2to<3
Years
9
44
0
14
889
69
0
6
304
103
62
Girls
2to<3
Years
22
65
0
34
858
40
2
6
305
107
50
3to<6
Years
10
44
0
28
802
67
5
15
294
175
151
3to<6
Years
9
49
0
31
820
81
3
16
270
161
151
8 See Table 16-3 for a description of what is included in each activity category.
b The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to
c The data for this age group and category are 2 values of 0 and 1 of 540.
Note: Column totals may not sum to 1,440 due to rounding.
6to
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent
Ten Major Activity Categories, Grouped by Seasons and Regions
Activity Category8
Work-related
Household
Childcare
Goods/Services
Personal Needs and
Care
Education
Organizational
Activities
Entertainment/Social
Recreation
Communication/
Passive Leisure
Don't know/Not coded
All Activities'1
Sample Sizes
(Unweighted)
Winter
(Jan-Mar)
10
47
<1
19
799
124
3
14
221
203
<1
1,442
318
Season
in
Region of California
Spring Summer Fall All
(Apr-June) (July-Sept) (Oct-Dec) Seasons
10
58
1
17
774
137
5
12
243
180
2
1,439
204
8 See Table 16-3 for a description of what
b The column totals may not be equal to 1
Source: Wiley et al.,
1991.
6
53
<1
26
815
49
5
12
282
189
3
1,441
407
13
52
<1
23
789
131
3
22
211
195
<1
1,441
271
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
Southern
Coast
10
45
<1
20
799
109
2
17
230
206
1
1,440
224
Bay
Area
10
62
<1
21
785
115
6
10
241
190
1
1,442
263
Rest of
State
8
55
1
23
794
109
6
16
249
175
3
1,439
713
All
Regions
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
is included in each activity category.
,440 due to rounding.
Table 16-10. Time (minutes/day) Children Under 12 Years of Age Spent in
6 Major Location Categories, for All Respondents and Doers
Location Category
Mean Mean
Duration % Doers8 Duration
(All) (Doers)8
Median Maximum
Duration Duration
(Doers)8 (Doers)8
Detailed Location with
Highest Average Time
Home 1,078 99 1,086 1,110 1,440
School/Childcare 109 33 330 325 1,260
Friend's/Other's House 80 32 251 144 1,440
Stores, Restaurants,
Shopping Places 24 35 69 50 475
In-transit 69 83 83 60 1,111
Other Locations 79 57 139 105 1,440
Don't Know/Not Coded <1 1 37 30 90
All Locations 1,440 ...
Home - Bedroom
School or Daycare Facility
Friend's/Other's House - Bedroom
Shopping Mall
Traveling in Car
Park, Playground
8 Doers indicate the respondents who reported participating in each activity category.
Source: Wiley et al., 1991.
Page
16-28
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-11. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
6 Location Categories, Grouped by Age and Sex
Boys
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
Sample Sizes
(Unweighted)
Birth to
1 Month
938
0
418
0
77
7
0
3
lto<3
Months
1,295
1
40
14
51
40
0
7
3to<6
Months
1,164
26
127
21
69
33
0
15
6to<12
Months
1,189
53
63
36
63
36
0
31
lto<2
Years
1,177
73
54
29
56
52
0
54
2to<3
Years
1,161
86
69
22
61
41
0
62
3to<6
Years
1,102
79
89
24
67
78
0
151
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-12. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
6 Location Categories, Grouped by Season and Region
Location Category
Home
School/Childcare
Friend's/Other's
House
Stores, Restaurants,
Shopping Places
In transit
Other Locations
Don't Know/Not
Coded
All Locations"
Sample Sizes
(Unweighted JVs)
Winter
(Jan-Mar)
1,091
119
69
22
75
63
<1
1,439
318
Spring
(Apr-June)
1,042
141
75
21
75
85
<1
1,439
204
Season
Summer
(July-Sept)
1,097
52
108
30
60
93
<1
1,440
407
Region of California
Fall
(Oct-Dec)
1,081
124
69
24
65
76
<1
1,439
271
All
Seasons
1,078
109
80
24
69
79
<1
1,439
1,200
Southern
Coast
1,078
113
73
26
71
79
<1
1,439
224
Bay
Area
1,078
103
86
23
73
76
<1
1,440
263
Rest of
State
1,078
108
86
23
63
81
<1
1,440
713
All
Regions
1,078
109
80
24
69
79
<1
1,439
1,200
a The column totals may not sum to 1,440 due to rounding.
Source: Wiley et al.,
1991.
Table 16-13. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Proximity to 2 Potential Sources of Exposure, Grouped by All Respondents, Age, and Sex
Potential
Exposures
Gasoline Fume
Gas Oven Fume
Sample Size
(Unweighted N)
Potential Exposure
Gasoline Fume
Gas Oven Fume
Sample Size
(Unweighted JV)
Birth to 1
Month
3
0
3
Birth to 1
Month
0
0
4
" The source data end at
lto<3
Months
9
0
7
lto<3
Months
3
0
10
1 1 years of aj
3to<6
Months
0
2
15
3to<6
Months
0
0
11
;e, so the
6to<12
Months
2
2
31
6to<12
Months
3
0
23
11 to <16 year
lto<2
Years
1
1
54
lto<2
Years
1
0
43
Boys
2to<3
Years
4
3
62
Girls
2to<3
Years
2
3
50
3to<6
Years
2
0
151
3to<6
Years
1
2
151
category is truncated and the 16 to
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-14. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
Grouped by Age and Sex
Boys
Girls
Age Group
N
Indoor8
Outdoor"
N
Indoor8
Outdoor"
Birth to <1 Month
1 to <3 Months
3 to <6 Months
6 to <12 Months
1 to <2 Years
2 to <3 Years
3 to <6 Years
6 to <11 Years
11 Years'
All Ages
3
7
15
31
54
62
151
239
62
624
1,440
1,432
1,407
1,322
1,101
1,121
1,117
1,145
1,166
1,181
33
118
339
319
323
295
274
258
4
10
11
23
43
50
151
225
59
576
1,440
1,431
1,421
1,280
1,164
1,102
1,140
1,183
1,215
1,181
0
9
19
160
276
338
300
255
225
258
N
Note:
Time indoors was estimating by adding the average times spent performing indoor activities (household work, child care, personal
needs and care, education, and communication/passive leisure) and half the time spent in each activity which could have occurred
either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social, don't know/not coded).
Time outdoors was estimated by adding the average time spent in recreation activities and half the time spent in each activity which
could have occurred either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social,
don't know/not coded).
The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to <21 year category is not included.
= Sample size.
Indoor and outdoor minutes/day may not sum to 1,440 minutes/day due to rounding.
Source: U.S. EPA analysis of source data used by Wiley etal., 1991.
Exposure Factors Handbook
September 2011
Page
16-31
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole
Population and Doers Only, Children <21 years
Percentiles
1
2
5 10 25 50
75
90
95
98
99
Kitchen — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-15. Time
Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole
Population and Doers Only, Children <21 years (continued)
Percentiles
1
2
5 10 25 50
75
90
95
98
99
Bathroom — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole
Population and Doers Only, Children <21 years (continued)
Birth to <
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day)
in Various Rooms
at Home and in All Rooms Combined, Doers Only
Kitchen
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
7,063
2,988
4,072
3
144
335
477
396
4,531
1,180
5,827
641
113
119
266
97
6,458
497
32
76
1,200
2,965
608
2,239
51
1,346
678
2,043
1,348
933
715
1,645
1,601
2,383
1,434
4,849
2,214
1,938
1,780
1,890
1,455
6,510
503
50
6,798
207
58
6,671
338
54
Mean
92.6
75.0
105.6
40.0
102.7
73.7
60.5
55.0
90.3
131.4
95.1
79.4
89.4
69.1
84.2
90.3
93.4
83.9
82.3
88.4
62.3
77.7
97.7
126.9
106.4
63.9
108.1
107.2
94.4
91.9
88.2
99.6
96.1
86.3
91.4
90.1
98.3
96.6
89.0
89.3
96.2
92.4
94.0
104.4
91.6
122.5
105.9
91.8
104.8
117.9
SD
94.2
80.8
101.0
31.2
110.8
54.4
53.0
58.1
90.9
119.6
95.2
92.0
95.5
60.8
77.3
113.6
94.8
82.9
71.9
118.6
55.4
77.5
94.0
115.8
168.5
62.3
102.9
102.3
101.2
92.1
87.7
99.7
93.6
87.1
99.1
92.2
98.2
100.3
90.2
91.0
94.5
93.6
96.0
143.7
93.0
111.4
138.4
92.6
113.4
142.4
SE
1.1
1.5
1.6
18.0
9.2
3.0
2.4
2.9
1.4
3.5
1.2
3.6
9.0
5.6
4.7
11.5
1.2
3.7
12.7
13.6
1.6
1.4
3.8
2.4
23.6
1.7
4.0
2.3
2.8
3.0
3.3
2.5
2.3
1.8
2.6
1.3
2.1
2.3
2.1
2.1
2.5
1.2
4.3
20.3
1.1
7.7
18.2
1.1
6.2
19.4
Mm
1
1
1
15
5
5
1
1
1
3
1
2
5
2
1
5
1
1
5
5
1
1
1
1
-)
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
7
1
4
0
1
1
9
Max
1,320
840
1,320
75
840
392
690
450
1,320
825
840
1,320
690
315
585
880
1,320
675
300
880
690
840
755
1,320
880
880
775
840
1,320
840
770
840
833
880
1,320
1,320
840
1,320
840
880
770
1,320
785
880
1,320
657
880
1,320
825
880
5
10
10
10
15
15
15
10
5
10
15
10
10
10
7
10
7
10
10
10
7
10
10
10
12
5
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
25
30
30
35
15
30
30
30
15
30
49
30
30
30
30
30
30
30
30
35
30
30
30
30
45
30
30
34
35
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
45
30
30
30
30
50
60
55
75
30
70
60
50
36
60
100
65
60
75
55
60
60
60
60
60
60
50
60
70
95
48
50
80
75
60
60
60
70
65
60
60
60
66
65
60
60
65
60
60
60
60
100
60
60
71
76
75
120
90
145
75
130
100
75
65
120
172
120
100
115
90
110
90
120
110
113
90
85
100
134
175
130
85
150
150
120
120
113
130
125
115
119
119
135
120
120
120
125
120
120
120
120
155
135
120
135
160
90
205
155
230
75
215
140
120
125
200
275
210
175
150
150
190
190
210
180
185
190
125
165
213
270
210
130
230
235
210
200
190
210
213
190
195
195
220
210
195
195
210
205
210
195
200
255
240
200
225
240
95
270
215
295
75
260
180
150
155
260
360
273
230
220
195
240
275
270
240
240
240
153
225
270
342
250
165
295
300
280
261
260
300
270
245
255
255
280
285
255
255
275
270
270
240
265
360
240
265
300
275
98
365
300
395
75
485
225
180
240
345
490
380
275
265
210
305
480
370
315
300
480
213
300
405
470
840
235
405
415
380
330
380
390
355
330
380
360
390
390
350
362
375
365
345
713
360
415
545
360
480
545
99
460
392
475
75
540
240
235
340
420
620
465
380
650
315
360
880
460
415
300
880
260
376
445
545
880
285
545
500
450
410
405
465
450
420
480
450
480
485
420
430
470
450
450
880
450
620
880
445
657
880
Exposure Factors Handbook
September 2011
Page
16-35
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day)
in Various Rooms at Home and in All
(continued)
Rooms Combined, Doers Only
Bathroom
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
6,661
3,006
3,653
0
122
328
490
445
4,486
790
5,338
711
117
134
283
78
6,067
498
33
63
1,240
3,130
583
1,661
47
1,386
522
1,857
1,305
913
678
1,497
1,465
2,340
1,359
4,613
2,048
1,853
1,747
1,772
1,289
6,132
493
36
6,473
145
43
6,327
296
38
Mean
35.0
32.7
36.9
27.5
43.9
35.9
31.0
29.1
34.5
42.2
34.3
36.9
33.6
47.3
38.6
34.6
34.5
39.2
44.4
44.1
32.0
33.4
35.5
40.2
34.7
32.2
40.9
35.8
36.1
35.0
32.1
34.3
35.8
35.1
34.9
33.9
37.5
37.0
36.6
32.8
33.0
34.9
35.2
49.5
34.6
51.9
44.9
34.8
36.8
54.6
SD
48.8
50.4
47.4
3.5
67.0
46.5
38.6
32.9
46.1
69.4
48.6
39.6
41.4
69.6
61.5
49.2
45.9
68.6
72.3
95.2
39.7
44.8
43.9
61.6
54.8
42.8
64.5
50.2
44.1
54.1
42.8
51.2
54.5
42.0
50.4
46.7
53.2
50.7
50.5
44.5
49.1
48.8
38.2
121.1
46.8
88.3
111.2
48.1
47.5
122.7
SE Mm
0.6 1
0.9 1
0.8 1
2.5 25
6.1 2
2.6 1
1.7 1
1.6 1
0.7 1
2.5 1
0.7 1
1.5 1
3.8 5
6.0 1
3.7 1
5.6 3
0.6 1
3.1 1
12.6 5
12.0 3
1.1 1
0.8 1
1.8 1
1.5 1
8.0 3
1.1 1
2.8 1
1.2 1
1.2 1
1.8 1
1.6 1
1.3 1
1.4 1
0.9 1
1.4 1
0.7 1
1.2 1
1.2 1
1.2 1
1.1 1
1.4 1
0.6 1
1.7 1
20.2 3
0.6 1
7.3 3
17.0 3
0.6 1
2.8 1
19.9 3
Max 5
870 5
870 5
665 5
30 25
530 5
600 10
535 5
547 5
665 5
870 5
870 5
460 5
375 5
535 5
546 5
360 5
705 5
870 5
422 10
665 5
600 5
595 5
430 5
870 5
360 5
665 5
870 5
600 5
540 5
705 5
460 5
600 5
870 5
510 5
705 5
870 5
600 5
665 5
870 5
570 5
540 5
870 5
410 5
665 5
870 5
600 7
665 5
870 5
600 5
665 5
25
15
15
15
25
15
15
15
15
15
15
15
15
15
15
15
10
15
15
15
10
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
11
15
15
10
15
20
10
15
15
10
50
25
20.5
30
27.5
30
30
27
20
25
30
25
30
25
30
24
20
5
5
0
0
0
5
9
0
5
5
30
25
25
20
22
25
25
30
25
25
30
30
30
25
20
25
30
17.5
25
30
15
25
30
17.5
75
40
35
45
30
45
40
35
35
40
45
40
45
40
45
45
35
40
45
45
35
35
40
45
45
30
35
45
40
45
40
40
40
40
40
40
40
45
42
45
38
35
40
45
30
40
45
30
40
43.5
30
90
60
60
70
30
85
60
52.5
60
60
75
60
70
60
95
60
60
60
60
60
60
60
60
60
75
55
60
70
63
70
60
60
60
60
60
60
60
65
65
60
60
60
60
65
60
60
75
50
60
60
110
95
90
75
90
30
120
75
60
65
90
120
85
98
90
120
80
135
90
90
120
150
70
80
90
110
75
70
100
90
95
90
75
80
90
90
90
85
90
90
90
80
90
90
90
360
90
185
110
90
90
360
98
137
150
135
30
300
125
100
90
135
240
135
135
110
315
270
165
135
270
422
360
100
123
140
210
360
110
240
135
150
150
110
140
145
135
140
135
150
150
135
135
140
135
140
665
135
546
665
135
180
665
99
255
300
240
30
360
270
200
100
250
360
255
186
210
422
425
360
240
425
422
665
180
240
270
340
360
200
350
270
225
340
300
335
315
214
250
240
300
270
240
210
303
255
220
665
240
570
665
255
250
665
Page
16-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day)
in Various Rooms at Home and in All Rooms Combined, Doers Only
(continued)
Bedroom
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
1 to 4
5 to 11
12tol7
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
9,151
4,157
4,990
4
184
488
689
577
5,891
1,322
7,403
923
153
174
378
120
8,326
684
43
98
1,736
3,992
777
2,578
68
1,925
807
2,549
1,740
1,223
907
2,037
2,045
3,156
1,913
6,169
2,982
2,475
2,365
2,461
1,850
8,420
671
60
8,836
244
71
8,660
423
68
Mean
563.1
549.6
574.3
648.8
525.1
742.0
669.1
636.2
532.7
550.8
553.4
612.3
612.3
590.7
602.6
555.8
560.9
597.4
542.3
523.4
679.5
513.5
551.6
566.4
514.0
668.3
554.8
534.1
539.1
526.0
525.2
561.5
552.4
570.0
564.9
552.6
584.9
576.0
559.0
566.1
547.2
560.8
593.8
543.1
564.2
535.5
522.1
563.1
570.1
524.8
SD
184.6
183.0
185.3
122.8
193.5
167.1
162.9
210.9
173.0
172.0
175.9
219.9
187.4
200.2
214.4
198.6
182.6
206.3
169.9
180.2
185.5
157.6
169.4
191.2
209.6
188.8
180.6
176.2
176.1
164.9
160.6
185.3
179.2
186.4
186.4
174.5
202.4
183.8
176.7
195.2
179.9
182.8
201.5
218.4
183.9
203.9
193.9
184.2
192.0
186.7
SE
1.9
2.8
2.6
61.4
14.3
7.6
6.2
8.8
2.3
4.7
2.0
7.2
15.2
15.2
11.0
18.1
2.0
7.9
25.9
18.2
4.5
2.5
6.1
3.8
25.4
4.3
6.4
3.5
4.2
4.7
5.3
4.1
4.0
3.3
4.3
2 2
3.7
3.7
3.6
3.9
4.2
2.0
7.8
28.2
2.0
13.1
23.0
2.0
9.3
22.6
Mm
3
3
5
540
15
30
35
15
3
15
3
15
25
15
25
30
3
15
135
30
15
3
15
5
30
15
5
3
5
15
3
5
3
10
5
3
3
5
15
3
3
3
30
30
3
20
30
3
15
30
Max
1,440
1,440
1,440
785
1,440
1,440
1,440
1,375
1,440
1,440
1,440
1,440
1,285
1,405
1,440
1,405
1,440
1,440
1,002
1,295
1,440
1,440
1,335
1,440
1,440
1,440
1,440
1,440
1,440
1,404
1,355
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,295
1,440
1,440
1,295
1,440
1,440
1,295
5
300
285
312
540
195
489
435
165
295
315
300
300
345
300
265
285
300
300
300
255
390
283
330
300
210
360
300
285
282
300
315
300
280
300
305
325
223
305
315
285
270
300
300
223
300
215
180
300
294
240
25
460
450
470
545
420
635
600
542
440
475
455
480
510
464
480
440
460
480
420
415
590
435
455
478
420
575
450
447
450
445
445
457
450
465
460
450
480
475
455
455
450
460
475
423
460
450
420
460
450
420
50
540
540
555
635
513
740
665
645
520
540
540
597
600
580
588
534
540
585
555
515
675
510
540
540
498
663
540
520
530
515
510
540
540
552
540
539
570
555
540
545
538
540
580
540
540
523
540
540
555
540
75
660
640
660
753
600
840
740
750
610
610
640
725
705
700
720
630
650
713
660
600
785
585
630
650
585
780
630
607
615
600
600
655
643
660
660
635
690
660
655
660
630
655
690
605
660
613
600
660
660
600
90
780
780
790
785
720
930
840
875
723
735
760
895
830
830
865
763
780
840
756
735
892
680
750
780
725
885
775
720
735
713
690
781
765
790
793
760
825
805
770
810
750
780
835
760
785
770
690
780
795
700
95
880
860
900
785
860
990
915
970
820
840
850
990
950
960
958
875
870
958
830
795
960
765
835
905
795
960
860
835
825
785
780
885
860
900
875
855
920
900
855
900
850
870
946
983
880
840
820
880
900
820
98
1,005
980
1,030
785
950
1,095
1,065
1,040
975
1,000
975
1,160
1,005
1,050
1,095
1,290
1,000
1,095
1,002
930
1,065
890
1,005
1,095
1,200
1,060
1,015
975
1,005
965
950
1,020
965
1,055
995
975
1,055
1,035
960
1,030
960
1,000
1,060
1,275
1,005
1,135
990
1,005
1,055
930
99
1,141
1,095
1,185
785
1,295
1,200
1,140
1,210
1,110
1,140
1,105
1 323
1,245
1,152
1 213
1,295
1,140
1,200
1,002
1,295
1,170
1,000
1,100
1,223
1,440
1,170
1,160
1,151
1,135
1,070
1,095
1,139
1,035
1,155
1,152
1,130
1,170
1,148
1,095
1,190
1,100
1,140
1,327
1,295
1,140
1,230
1,295
1,141
1,110
1,295
Exposure Factors Handbook
September 2011
Page
16-37
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only
(continued)
Garage
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
Refused
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
Yes
No
Yes
N
193
120
73
1
4
6
12
130
40
165
12
1
6
8
1
174
17
2
21
85
17
70
22
14
63
48
25
21
23
42
60
68
116
77
51
59
51
32
184
9
187
6
185
8
Mean
117.8
144.1
74.6
20.0
83.5
63.3
80.8
134.5
88.6
109.5
205.0
5.0
186.3
120.0
120.0
116.6
128.6
127.5
79.7
145.3
50.1
112.3
76.5
188.9
127.3
121.6
118.2
75.9
137.2
131.4
103.7
115.3
128.7
101.4
115.6
136.8
101.1
112.9
118.6
101.1
118.2
104.2
114.1
201.9
SD
144.5
162.6
94.3
47.5
63.4
78.4
165.1
84.1
127.5
219.5
308.4
164.9
138.5
207.3
10.6
67.5
175.2
52.0
127.4
67.6
195.0
159.3
147.8
145.8
88.1
159.5
166.4
128.6
139.7
159.0
118.4
161.8
163.3
121.3
110.2
146.3
102.6
146.2
78.6
142.9
163.6
SE
10.4
14.8
11.0
23.7
25.9
22.6
14.5
13.3
9.9
63.4
125.9
58.3
10.5
50.3
7.5
14.7
19.0
12.6
15.2
14.4
52.1
20.1
21.3
29.2
19.2
33.2
25.7
16.6
16.9
14.8
13.5
22.7
21.3
17.0
19.5
10.8
34.2
10.7
32.1
10.5
57.9
Min
1
2
1
20
15
10
10
1
5
1
5
5
10
15
120
1
5
120
10
1
5
5
10
5
9
5
5
1
5
10
2
1
1
2
2
5
1
5
1
5
1
10
1
15
Max
790
790
530
20
120
165
240
790
300
690
570
5
790
510
120
690
790
135
240
790
194
690
240
675
690
790
480
300
510
690
570
790
790
675
690
790
530
480
790
270
790
220
790
450
5
5
10
5
20
15
10
10
5
8
5
5
5
10
15
120
5
5
120
15
5
5
5
10
5
5
10
5
9
15
20
5
5
5
10
5
10
5
10
5
5
5
10
5
15
25
20
30
15
20
52
25
20
20
25
20
38
5
18
23
120
20
20
120
25
20
15
30
20
30
25
30
20
10
30
40
13
20
25
20
15
30
20
25
25
15
20
25
20
60
50
60
94
30
20
100
30
51
68
60
60
90
5
30
60
120
60
60
128
51
65
30
75
51
120
60
60
60
30
60
88
53
73
60
60
50
90
60
85
60
60
60
110
60
178
75
150
183
120
20
115
120
148
180
143
135
405
5
240
135
120
155
110
135
120
180
60
135
120
235
165
140
120
120
195
120
128
153
165
120
150
165
120
158
150
180
150
150
135
338
90
296
315
180
20
120
165
185
360
228
240
530
5
790
510
120
296
510
135
165
405
135
255
165
510
300
296
405
195
460
260
283
300
315
240
240
315
260
240
300
270
300
220
260
450
95
480
518
240
20
120
165
240
526
270
315
570
5
790
510
120
460
790
135
185
530
194
450
185
675
530
450
460
260
510
665
428
315
510
300
526
570
450
315
480
270
480
220
480
450
98
665
675
450
20
120
165
240
675
300
526
570
5
790
510
120
570
790
135
240
675
194
480
240
675
665
790
480
300
510
690
480
530
665
526
665
675
460
480
665
270
665
220
665
450
99
690
690
530
20
120
165
240
690
300
675
570
5
790
510
120
675
790
135
240
790
194
690
240
675
690
790
480
300
510
690
570
790
690
675
690
790
530
480
690
270
690
220
690
450
Page
16-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
(continued)
, Doers Only
Basement
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
274
132
141
1
3
8
25
26
170
42
248
15
2
3
1
5
263
6
1
4
57
107
22
85
3
65
15
78
48
39
29
90
123
35
26
178
96
80
65
79
50
253
20
1
269
3
2
265
8
1
Mean
142.2
160.4
125.7
60.0
171.7
94.8
135.4
97.5
151.3
143.8
133.8
183.8
135.0
468.7
30.0
263.2
139.0
185.0
185.0
271.3
115.6
149.1
115.0
158.0
151.7
129.5
169.9
159.4
160.6
146.7
73.1
115.6
129.0
188.0
234.4
135.3
154.8
144.5
174.2
142.4
96.4
143.1
124.7
245.0
141.4
201.7
152.5
139.0
233.8
245.0
SD
162.9
180.7
143.3
-
122.7
55.7
145.9
113.1
172.7
173.5
154.1
165.5
106.1
455.7
173.1
161.7
197.3
198.8
124.2
178.6
114.8
176.3
110.3
133.4
203.5
188.7
184.2
150.8
66.3
118.7
146.9
205.8
247.7
159.4
169.3
147.0
196.8
180.7
83.1
164.2
151.0
163.7
122.1
130.8
161.0
214.2
SE
9.8
15.7
12.1
-
70.8
19.7
29.2
22.2
13.2
26.8
9.8
42.7
75.0
263.1
77.4
10.0
80.6
99.4
16.5
17.3
24.5
19.1
63.7
16.6
52.5
21.4
26.6
24.1
12.3
12.5
13.2
34.8
48.6
11.9
17.3
16.4
24.4
20.3
11.7
10.3
33.8
10.0
70.5
92.5
9.9
75.7
Mm
1
1
2
60
30
28
15
1
1
5
1
12
60
20
30
60
1
15
185
60
1
1
10
5
30
1
5
5
2
10
1
5
2
10
1
1
5
5
1
1
5
1
1
245
1
65
60
1
20
245
Max
931
931
810
60
245
180
705
515
810
931
810
515
210
931
30
540
931
555
185
540
705
810
535
931
245
705
605
810
931
555
245
555
765
931
810
810
931
630
931
765
332
931
510
245
931
300
245
931
605
245
5
10
10
10
60
30
28
15
10
5
10
10
12
60
20
30
60
10
15
185
60
12
5
25
10
30
15
5
5
10
10
10
10
10
28
1
10
10
14
5
5
10
10
6
245
10
65
60
10
20
245
25
30
40
30
60
30
48
60
30
30
40
30
40
60
20
30
231
30
30
185
150
40
30
60
35
30
45
30
40
25
30
30
40
30
45
30
30
50
30
60
30
30
35
16
245
30
65
60
30
68
245
50
90
90
75
60
240
90
105
60
90
90
90
150
135
455
30
240
90
150
185
243
90
75
78
120
180
90
90
90
120
70
60
73
90
110
165
83
98
90
105
85
60
90
73
245
90
240
153
90
180
245
75
180
203
175
60
245
138
140
150
210
170
168
270
210
931
30
245
180
210
185
393
150
210
150
210
245
160
255
195
203
210
100
150
180
255
325
180
190
221
210
150
145
180
178
245
180
300
245
180
375
245
90
330
490
265
60
245
180
270
240
410
330
315
450
210
931
30
540
330
555
185
540
240
450
185
330
245
270
565
420
400
450
210
250
270
450
705
315
450
315
490
455
240
330
383
245
330
300
245
330
605
245
95
535
565
420
60
245
180
420
275
555
455
510
515
210
931
30
540
510
555
185
540
420
540
290
600
245
420
605
720
600
510
210
400
510
720
720
535
540
480
555
605
255
540
510
245
535
300
245
515
605
245
98
705
720
705
60
245
180
705
515
720
931
705
515
210
931
30
540
705
555
185
540
515
720
535
720
245
535
605
765
931
555
245
540
605
931
810
720
600
610
810
720
301
705
510
245
705
300
245
705
605
245
99
765
765
720
60
245
180
705
515
765
931
720
515
210
931
30
540
765
555
185
540
705
765
535
931
245
705
605
810
931
555
245
555
630
931
810
765
931
630
931
765
332
765
510
245
765
300
245
765
605
245
Exposure Factors Handbook
September 2011
Page
16-39
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home
(continued)
and in All Rooms Combined, Doers Only
Utility /Laundry Room
Percentiles
Group Name
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/emphysema
Bronchitis/emphysema
Group Code
Male
Female
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
Yes
DK
No
Yes
N
458
70
388
6
3
3
8
362
76
400
35
4
6
10
3
435
20
1
2
12
206
51
187
2
17
51
163
107
60
60
105
116
151
86
322
136
145
89
132
92
432
26
440
16
2
428
30
Mean
73.2
78.4
72.3
65.8
75.0
105.7
55.5
73.6
72.6
69.2
100.5
82.5
86.7
95.9
170.0
72.1
81.7
55.0
247.5
76.8
69.2
72.2
77.7
76.0
72.0
71.8
71.6
77.2
74.0
71.3
80.9
64.9
72.7
75.9
68.6
84.1
75.2
81.9
69.3
67.3
73.8
64.2
72.1
103.1
72.5
73.3
72.4
SD
71.9
95.7
66.8
34.4
116.9
168.4
77.1
73.9
58.1
65.8
103.2
37.7
27.9
78.8
264.2
69.9
63.0
-
321.7
107.8
78.4
62.5
63.8
104.7
90.9
49.4
71.6
71.7
77.3
79.9
84.6
63.3
69.5
69.9
66.7
82.1
81.0
83.0
60.8
58.6
73.2
44.8
70.2
109.9
17.7
73.5
43.5
SE
3.4
11.4
3.4
14.0
67.5
97.2
27.3
3.9
6.7
3.3
17.5
18.9
11.4
24.9
152.5
3.4
14.1
-
227.5
31.1
5 5
8.8
4.7
74.0
22.0
6.9
5.6
6.9
10.0
10.3
8.3
5.9
5.7
7.5
3.7
7.0
6.7
8.8
5.3
6.1
3.5
8.8
3.3
27.5
12.5
3.6
7.9
Min
1
1
2
25
5
2
1
2
2
2
1
30
60
4
15
1
4
55
20
1
2
2
5
2
1
15
2
2
5
5
2
2
1
4
1
5
1
5
2
3
1
10
1
5
60
1
10
Max
510
510
510
120
210
300
240
510
345
510
510
120
120
225
475
510
225
55
475
300
510
225
475
150
300
245
510
475
510
360
510
475
510
405
510
510
510
510
360
345
510
200
510
360
85
510
200
5
5
5
5
25
5
0
1
5
10
5
5
30
60
4
15
5
5
55
20
1
5
5
10
2
1
20
6
5
10
5
5
5
10
5
5
10
5
10
5
10
5
10
5
5
60
5
15
25
25
20
28
40
5
2
17
20
30
25
20
60
65
20
15
25
40
55
20
4
20
15
30
2
10
30
30
20
27
18
25
15
30
30
23
30
17
30
25
22
25
25
25
30
60
24
45
50
60
60
60
60
10
15
33
60
60
60
60
90
78
105
20
60
60
55
248
23
60
55
60
76
35
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
73
60
60
75
100
90
105
90
210
300
53
105
90
90
135
105
120
120
475
90
120
55
475
135
90
120
115
150
90
90
90
120
98
90
120
90
90
115
90
120
90
100
120
90
105
90
100
138
85
105
90
90
150
168
150
120
210
300
240
150
150
150
240
120
120
218
475
150
183
55
475
240
135
150
150
150
240
120
140
155
154
155
180
135
150
150
140
180
165
180
135
125
150
120
150
345
85
150
125
95
200
345
190
120
210
300
240
195
180
180
300
120
120
225
475
190
218
55
475
300
203
180
180
150
300
180
180
200
190
263
225
155
210
180
180
240
215
240
155
180
200
130
185
360
85
200
150
98
300
360
240
120
210
300
240
325
245
258
510
120
120
225
475
300
225
55
475
300
360
225
245
150
300
195
325
225
203
360
345
215
245
360
240
360
360
405
240
245
325
200
270
360
85
325
200
99
360
510
330
120
210
300
240
405
345
353
510
120
120
225
475
360
225
55
475
300
405
225
345
150
300
245
405
240
510
360
360
240
330
405
345
405
475
510
325
345
360
200
360
360
85
360
200
Page
16-40
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms
(continued)
Combined, Doers Only
Indoors in a Residence (all rooms)
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
9,343
4,269
5,070
4
187
498
700
588
6,022
1,348
7,556
941
157
181
382
126
8,498
696
46
103
1,768
4,068
797
2,639
71
1,963
829
2,602
1,788
1,240
921
2,068
2,087
3,230
1,958
6,286
3,057
2,513
2,424
2,522
1,884
8,591
689
63
9,019
249
75
8,840
432
71
Mean
1,001.4
945.9
1,048.1
1,060.0
1,001.1
1,211.6
1,005.1
969.5
947.9
1,174.6
999.4
1,016.0
983.5
996.1
1,009.4
1,019.7
1,000.4
1,009.8
1,097.9
984.1
1,053.3
881.0
982.4
1,158.0
995.1
1,044.5
1,093.4
1,008.1
974.3
939.5
943.7
1,003.4
1,001.7
999.0
1,002.8
965.7
1,074.8
1,034.9
977.9
980.5
1,014.8
999.1
1,027.4
1,025.7
997.8
1,125.5
1,024.1
997.7
1,070.5
1,045.5
SD
275.1
273.5
267.9
135.6
279.9
218.7
222.3
241.8
273.0
229.3
275.7
272.5
254.7
268.3
281.8
276.6
275.4
270.8
286.7
269.5
248.5
259.2
243.1
233.8
268.1
251.9
278.6
279.3
272.6
275.0
274.3
278.4
280.6
270.2
274.0
272.6
265.7
278.2
267.2
274.0
277.5
274.4
284.4
264.3
274.1
281.4
285.1
274.8
273.8
273.0
SE
2.8
4.2
3.8
67.8
20.5
9.8
8.4
10.0
3.5
6.2
3.2
8.9
20.3
19.9
14.4
24.6
3.0
10.3
42.3
26.6
5.9
4.1
8.6
4.6
31.8
5.7
9.7
5.5
6.4
7.8
9.0
6.1
6.1
4.8
6.2
3.4
4.8
5.6
5.4
5 5
6.4
3.0
10.8
33.3
2.9
17.8
32.9
2.9
13.2
32.4
Min
8
8
30
900
265
270
190
95
8
60
8
190
30
10
55
270
8
55
401
270
95
8
255
60
445
95
150
30
10
30
8
30
8
10
30
30
8
30
10
8
30
8
190
445
8
180
150
8
205
445
Max
1,440
1,440
1,440
1,200
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
I ,,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
5
575
540
620
900
565
795
686
585
540
760
570
600
600
604
555
575
575
585
645
565
675
515
600
735
575
660
630
565
570
528
540
570
565
585
575
567
615
590
580
555
589
576
555
630
575
660
560
575
585
565
25
795
750
840
950
799
1,065
845
812
750
1,030
795
815
810
805
810
840
795
810
835
810
870
715
820
1,015
810
855
870
803
775
745
750
795
790
800
800
770
895
825
780
785
805
795
825
840
795
925
840
795
868
845
50
985
900
1,050
1,070
955
1,260
975
950
900
1,210
980
1,000
930
975
1,005
975
980
1,000
1,173
950
1,030
835
970
1,190
940
1,020
1,130
995
930
885
900
980
989
970
1,000
911
1,105
1,015
955
960
997
980
1,025
960
975
1,185
975
975
1,110
975
75
1,235
1,160
1,280
1,170
1,230
1,410
1,165
1,155
1,165
1,375
1,235
1,245
1,180
1,198
1,250
1,255
1,235
1,230
1,355
1,200
1,255
1,046
1,170
1,350
1,255
1,254
1,345
1,245
1,205
1,165
1,155
1,245
1,250
1,228
1,230
1,190
1,290
1,285
1,185
1,201
1,260
1,230
1,260
1,315
1,230
1,380
1,305
1,230
1,293
1,320
90
1,395
1,350
1,420
1,200
1,440
1,440
1,334
1,310
1,350
1,440
1,395
1,410
1,355
1,380
1,410
1,440
1,395
1,405
1,440
1,375
1,413
1,290
1,320
1,440
1,440
1,410
1,440
1,400
1,371
1,335
1,350
1,405
1,390
1,400
1,390
1,380
1,420
1,432
1,370
1,365
1,405
1,393
1,430
1,410
1,391
1,440
1,425
1,395
1,440
1,440
95
1,440
1,430
1,440
1,200
1,440
1,440
1,412.5
1,405
1,428
1,440
1,440
1,440
1,420
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,385
1,380
1,440
1,440
1,440
1,440
1,440
1,436
1,428
1,410
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,435
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
98
1,440
1,440
1,440
1,200
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
99
1,440
1,440
1,440
1,200
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
Exposure Factors Handbook
September 2011
Page
16-41
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only
(continued)
= Indicates missing data.
DK = The respondent replied "don't know".
Refused = Refused data.
N = Doer sample size.
Mean = Mean 24-hour cumulative number of minutes for doers.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
Page Exposure Factors Handbook
16-42 September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-17. Time Spent (minutes/day) at Selected Indoor Locations Whole Population and Doers Only, Children <21 years
Age (years) N Mean
Percentiles
1 2 5 10 25
50
75
90
95
98
99
Max
Restaurants — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only
Restaurant
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
2,059
986
1,073
30
61
84
122
1,503
259
1,747
148
37
30
78
19
1,911
129
5
14
263
1,063
208
515
10
299
132
590
431
359
248
409
504
680
466
1,291
768
524
559
556
420
1,903
150
6
1,998
50
11
1,945
104
10
Mean
94.5
87.5
101.0
126.1
62.7
56.7
69.8
101.2
83.6
91.7
102.8
81.3
145.2
123.0
123.8
92.9
116.7
76.0
114.5
62.3
105.5
122.6
76.3
135.0
72.2
134.8
99.4
94.9
89.5
95.0
94.4
96.9
92.7
94.9
97.3
89.8
97.7
91.6
95.1
93.6
94.1
96.3
196.3
94.9
69.0
140.3
93.7
96.1
232.8
SD
119.9
114.2
124.7
138.2
47.7
38.1
78.4
131.2
83.5
114.7
141.3
78.9
194.8
156.8
127.6
117.6
148.0
134.3
134.7
57.9
142.4
144.8
61.4
133.5
79.6
171.8
136.3
114.9
104.1
109.4
113.6
120.9
125.1
116.9
128.8
103.2
125.7
109.7
123.0
121.7
117.4
143.6
220.9
120.7
53.6
171.3
117.7
130.1
288.2
SE
2.6
3.6
3.8
25.2
6.1
4.2
7.1
3.4
5.2
2.7
11.6
13.0
35.6
17.8
29.3
2.7
13.0
60.1
36.0
3.6
4.4
10.0
2.7
42.2
4.6
15.0
5.6
5.5
5.5
6.9
5.6
5.4
4.8
5.4
3.6
3.7
5 5
4.6
5.2
5.9
2.7
11.7
90.2
2.7
7.6
51.6
2.7
12.8
91.1
Mm
1
1
1
15
4
5
2
1
3
1
3
15
5
10
20
1
1
5
30
2
1
1
3
30
1
5
3
1
1
3
2
1
2
1
1
1
3
2
1
1
1
4
30
1
3
30
1
5
10
Max
925
900
925
495
330
180
455
925
750
925
805
480
765
700
480
925
765
315
480
455
925
805
490
425
548
925
910
770
765
765
765
805
910
925
925
770
875
925
910
900
910
925
480
925
340
480
910
925
875
5
10
10
10
30
10
10
10
10
19
10
5
18
10
15
20
10
15
5
30
10
10
5
15
30
10
10
10
10
10
15
15
10
10
10
10
10
15
10
10
10
10
10
30
10
15
30
10
15
10
25
30
30
40
45
35
30
30
30
45
30
30
30
45
40
30
30
40
10
30
30
35
33
40
60
30
30
35
35
35
40
35
30
30
30
30
36
35
35
30
30
35
30
30
30
45
30
30
30
30
50
60
60
60
60
55
45
45
60
60
60
60
60
83
60
70
60
60
10
60
45
60
65
60
83
50
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
46
79
60
60
70
60
60
79
75
95
90
105
150
85
85
65
105
90
95
95
90
120
110
210
95
115
40
90
80
105
123
90
135
85
152
90
105
100
115
100
105
90
110
93
105
105
95
94
95
100
90
480
100
90
120
97
90
480
90
185
160
230
398
115
120
165
211
150
175
295
135
433
375
330
180
360
315
330
120
235
320
145
378
130
375
203
180
165
180
210
190
195
175
210
155
178
180
210
185
180
238
480
190
105
480
180
235
678
95
351
305
380
490
120
120
250
400
215
320
430
200
750
585
480
330
435
315
480
140
485
441
195
425
250
535
435
340
295
260
330
340
365
375
377
280
351
360
360
325
330
485
480
355
120
480
335
360
875
98
548
550
540
495
130
140
325
570
315
535
555
480
765
660
480
542
660
315
480
273
630
595
260
425
360
700
645
550
490
560
507
560
550
535
555
510
595
505
555
540
545
590
480
550
286
480
548
500
875
99
660
660
670
495
330
180
360
675
520
640
735
480
765
700
480
645
700
315
480
330
735
660
315
425
480
750
680
640
570
675
585
675
650
640
700
620
685
555
675
653
653
670
480
660
340
480
653
620
875
Page
16-44
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued)
Indoors at Bar/Nightclub/Bowling Alley
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
5 to 11
12tol7
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
352
213
139
4
4
8
313
23
297
25
8
7
10
5
327
20
2
3
12
223
43
70
4
13
28
117
95
55
44
83
88
91
90
192
160
93
83
99
77
331
18
3
345
5
0
333
17
2
Mean
175.8
174.3
178.1
158.8
98.8
151.3
180.2
141.2
173.6
205.4
169.9
197.3
121.3
246.6
177.1
144.9
142.5
261.0
133.8
182.4
201.2
146.3
176.3
146.5
218.0
177.8
205.3
141.8
131.4
179.3
169.8
175.7
178.5
167.5
185.9
182.7
186.1
160.3
176.4
176.3
169.4
160.0
177.0
82.0
210.0
177.3
148.6
165.0
SD
132.2
133.2
131.2
98.0
57.5
77.7
136.7
85.2
132.6
126.6
153.3
187.6
52.3
127.2
134.5
85.1
31.8
171.9
73.6
138.3
155.5
97.4
115.1
84.2
170.2
130.1
152.8
92.8
90.2
137.0
126.2
132.0
135.5
133.5
130.4
131.7
147.6
130.7
117.2
133.7
109.0
124.9
132.8
47.2
127.3
133.3
108.5
190.9
SE
7.0
9.1
11.1
49.0
28.8
27.5
7.7
17.8
7.7
25.3
54.2
70.9
16.5
56.9
7.4
19.0
22.5
99.2
21.2
9.3
23.7
11.6
57.6
23.3
32.2
12.0
15.7
12.5
13.6
15.0
13.5
13.8
14.3
9.6
10.3
13.7
16.2
13.1
13.4
7.4
25.7
72.1
7.1
21.1
90.0
7.3
26.3
135.0
Min
3
5
3
75
45
50
3
5
3
50
5
70
5
73
3
5
120
73
45
5
5
3
45
45
60
3
5
10
30
5
5
3
5
5
3
5
5
3
15
3
60
60
3
5
120
3
50
30
Max
870
870
630
300
170
270
870
328
870
540
479
615
198
410
870
440
165
410
270
870
615
479
300
300
870
630
650
417
400
650
615
870
605
650
870
650
870
630
615
870
530
300
870
120
300
870
530
300
5
30
30
30
75
45
50
30
30
30
60
5
70
5
73
30
38
120
73
45
30
45
30
45
45
75
25
30
20
30
45
30
35
30
30
45
40
30
30
30
30
60
60
30
5
120
30
50
30
25
90
90
95
98
53
80
90
75
90
120
38
110
105
180
90
110
120
73
60
90
90
73
83
60
120
90
105
75
60
89
90
90
85
80
108
87
90
75
100
90
105
60
90
75
120
90
110
30
50
150
140
150
130
90
160
150
135
140
180
175
135
118
270
150
120
143
300
135
150
150
123
180
150
175
150
180
120
110
140
148
148
153
120
165
150
140
120
165
150
135
120
150
90
210
150
120
165
75
223
220
225
220
145
205
225
180
220
240
225
185
160
300
225
160
165
410
178
228
270
180
270
185
235
225
240
205
178
240
212
225
225
210
228
240
230
189
220
225
210
300
225
120
300
225
175
300
90
328
340
300
300
170
270
370
240
328
417
479
615
179
410
340
222
165
410
225
340
455
255
300
270
420
360
462
265
265
328
299
270
407
340
322
410
380
285
299
340
270
300
340
120
300
340
210
300
95
487
479
530
300
170
270
498
325
487
498
479
615
198
410
489
343
165
410
270
525
520
328
300
300
568
489
590
340
290
489
487
462
479
520
475
455
498
530
410
487
530
300
487
120
300
487
530
300
98
570
568
600
300
170
270
590
328
590
540
479
615
198
410
590
440
165
410
270
600
615
462
300
300
870
540
615
410
400
630
568
570
590
590
568
560
570
605
600
590
530
300
590
120
300
590
530
300
99
615
615
605
300
170
270
615
328
630
540
479
615
198
410
615
440
165
410
270
630
615
479
300
300
870
570
650
417
400
650
615
870
605
605
630
650
870
630
615
615
530
300
615
120
300
615
530
300
Exposure Factors Handbook
September 2011
Page
16-45
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day)
at Selected Indoor Locations, Doers Only (continued)
Indoors at School
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,224
581
643
18
43
302
287
550
24
928
131
39
36
76
14
1,082
127
5
10
616
275
138
190
5
679
24
114
173
93
141
261
290
427
246
1,179
45
392
353
207
272
1,095
124
5
1,209
9
6
1,175
42
7
Mean
343.4
358.6
329.6
314.1
288.5
396.3
402.6
295.4
187.7
348.5
339.8
332.4
363.6
294.0
279.7
344.9
333.0
293.0
329.5
390.3
331.3
280.9
258.7
166.0
388.9
233.3
186.6
281.4
300.4
373.5
345.7
334.4
354.0
332.8
346.8
252.0
369.3
355.1
316.8
311.0
342.8
350.7
287.0
344.6
205.8
292.2
344.8
306.7
315.4
SD
179.1
167.7
187.9
230.9
217.6
109.2
125.5
207.3
187.0
180.5
169.3
179.9
155.6
175.7
221.3
179.6
173.8
244.7
180.1
130.2
222.0
174.8
199.5
179.1
132.8
179.6
193.6
209.9
208.7
193.4
181.5
176.7
178.5
180.3
177.5
198.5
164.4
165.5
196.4
195.3
179.2
178.8
190.7
178.9
169.5
178.9
178.8
188.2
163.7
SE
5.1
7.0
7.4
54.4
33.2
6.3
7.4
8.8
38.2
5.9
14.8
28.8
25.9
20.2
59.1
5 5
15.4
109.4
56.9
5.2
13.4
14.9
14.5
80.1
5.1
36.7
18.1
16.0
21.6
16.3
11.2
10.4
8.6
11.5
5.2
29.6
8.3
8.8
13.6
11.8
5.4
16.1
85.3
5.1
56.5
73.0
5.2
29.0
61.9
Mm
1
1
1
5
5
5
15
1
-)
1
9
5
10
2
5
1
2
3
5
5
1
1
1
5
5
1
1
1
1
1
1
1
1
1
1
20
1
1
2
1
1
1
5
1
15
5
1
3
5
Max
995
995
855
713
665
665
855
995
585
995
855
840
820
565
681
995
820
562
625
855
995
800
855
440
855
540
785
995
755
683
995
730
855
820
995
820
855
855
995
855
995
855
445
995
510
480
995
632
440
5
10
30
5
5
10
170
120
5
3
10
15
20
105
10
5
10
15
3
5
115
5
10
5
5
100
2
4
5
5
15
11
10
10
15
10
40
20
12
10
5
10
10
5
10
15
5
10
10
5
25
210
255
180
165
60
365
383
104
45
213
230
190
273
143
60
210
200
65
200
365
115
160
60
5
360
30
20
120
115
250
210
180
235
195
222
105
285
250
125
120
200
250
180
210
90
180
212
120
180
50
395
400
390
248
269
403
420
300
120
400
390
365
366
363
260
395
390
415
350
410
405
285
263
180
410
298
108
255
320
442
385
390
415
378
395
180
405
400
365
365
390
402
365
395
180
324
395
378
378
75
454
450
455
520
500
445
450
460
328
458
445
450
458
432
440
455
445
420
445
450
510
412
410
200
450
374
295
425
470
510
455
440
462
440
455
360
457
455
445
445
455
445
440
455
275
440
455
444
440
90
540
540
540
625
580
535
500
553
480
545
510
560
502
495
625
540
500
562
538
525
575
480
528
440
525
460
480
550
540
575
535
530
540
555
540
555
545
535
557
540
540
535
445
540
510
480
540
465
440
95
585
600
582
713
595
565
565
612
510
600
580
580
598
525
681
598
565
562
625
570
625
537
572
440
580
465
580
640
580
615
620
585
575
595
585
632
600
575
585
595
585
605
445
595
510
480
595
580
440
98
660
690
640
713
665
625
710
683
585
665
624
840
820
540
681
665
600
562
625
640
690
660
778
440
640
540
645
820
730
655
710
645
640
681
655
820
680
636
640
660
660
645
445
660
510
480
660
632
440
99
723
778
683
713
665
640
778
785
585
723
645
840
820
565
681
730
630
562
625
665
755
683
840
440
710
540
690
855
755
680
855
683
755
713
723
820
710
713
723
778
723
800
445
723
510
480
730
632
440
Page
16-46
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day)
at Selected Indoor Locations,
Doers Only (continued)
Office or Factory
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12tol7
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,975
1,012
963
49
12
14
19
1,749
132
1,612
191
42
28
74
28
1,805
138
7
25
43
1,535
164
213
20
80
104
631
462
415
283
465
439
666
405
1,759
216
531
470
550
424
1,845
114
16
1,931
26
18
1,873
86
16
Mean
394.0
410.8
376.3
438.9
31.6
100.9
145.4
419.0
145.8
387.6
413.9
428.0
480.9
394.5
482.9
393.5
393.6
262.6
470.0
121.3
455.6
293.0
77.6
449.2
225.1
329.5
396.9
393.1
437.2
396.9
399.1
389.3
408.6
369.1
406.8
289.6
390.7
385.2
393.5
408.4
395.0
371.7
437.0
395.7
265.5
392.3
395.6
356.4
403.9
SD
230.8
233.5
226.7
232.6
25.6
155.1
181.1
218.4
194.0
232.0
218.0
216.8
200.9
237.8
246.1
229.6
238.6
242.1
258.8
178.0
200.3
197.0
123.0
184.8
248.5
264.4
228.1
228.8
205.2
232.2
226.2
229.1
228.2
240.4
225.2
249.1
231.7
240.7
224.5
226.6
230.4
231.3
272.1
229.7
246.8
282.6
230.0
236.1
289.5
SE
5.2
7.3
7.3
33.2
7.4
41.5
41.6
5.2
16.9
5.8
15.8
33.4
38.0
27.6
46.5
5.4
20.3
91.5
51.8
27.1
5.1
15.4
8.4
41.3
27.8
25.9
9.1
10.6
10.1
13.8
10.5
10.9
8.8
11.9
5.4
16.9
10.1
11.1
9.6
11.0
5.4
21.7
68.0
5.2
48.4
66.6
5.3
25.5
72.4
Mm
1
1
1
10
5
2
1
1
1
1
1
10
40
1
30
1
1
1
17
1
1
1
1
30
1
2
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
3
5
1
5
5
i
5
5
Max
1,440
1,440
855
900
90
580
625
1,440
705
1,440
1,037
780
795
840
997
1,440
840
610
860
685
1,440
750
705
675
860
930
997
1,440
900
860
930
997
1,440
900
997
1,440
997
1,440
1,037
840
1,440
840
860
1,440
650
860
1,440
800
860
5
9
10
5
20
5
2
1
10
3
6
10
30
75
5
30
10
5
1
30
2
15
10
3
60
3
5
10
5
10
5
10
8
10
5
10
3
10
5
9
10
8
10
5
10
9
5
8
10
5
25
180
225
120
299
13
10
10
273
10
150
268
285
348
230
373
180
180
12
311
10
400
95
10
334
15
51
210
210
325
175
215
180
225
95
237
30
180
120
200
239
185
120
233
195
15
30
195
75
30
50
485
495
480
500
25
33
50
500
40
480
485
492
540
493
533
483
498
245
525
40
510
343
30
523
105
389
492
480
510
480
485
480
498
470
495
283
480
480
483
500
490
463
520
490
175
490
490
428
490
75
550
565
540
555
45
178
240
555
205
550
540
553
583
560
608
550
560
540
615
178
570
480
90
550
470
553
550
540
570
565
550
550
555
550
555
495
550
553
540
567
550
540
588
550
490
550
550
540
583
90
630
645
600
675
60
195
510
630
495
628
635
660
715
645
818
630
644
610
810
307
644
525
215
645
608
640
615
615
640
640
625
630
630
630
630
600
625
630
614
640
630
630
780
630
630
780
630
620
780
95
675
710
645
780
90
580
625
680
540
675
720
745
780
720
860
675
675
610
818
580
700
555
305
675
675
705
675
660
690
675
675
670
675
675
675
670
675
695
675
675
675
675
860
675
645
860
675
660
860
98
765
780
710
900
90
580
625
765
640
750
803
780
795
765
997
755
765
610
860
685
775
585
570
675
780
765
760
770
750
780
765
750
760
760
755
800
755
775
753
750
760
800
860
760
650
860
760
720
860
99
818
855
750
900
90
580
625
818
675
800
900
780
795
840
997
810
795
610
860
685
837
615
640
675
860
855
800
820
800
818
840
800
840
800
810
900
835
837
810
770
810
837
860
811
650
860
818
800
860
Exposure Factors Handbook
September 2011
Page
16-47
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day) at Selected
Indoor Locations, Doers
Only
(continued)
Schools, Churches, Hospitals, and Public Buildings
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12tol7
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
2,932
1,234
1,698
50
98
391
355
1,653
385
2,310
332
61
57
141
31
2,654
240
13
25
821
1,029
293
775
14
917
166
617
520
351
361
645
686
1,036
565
2,091
841
847
805
667
613
2,689
229
14
2,836
78
18
2,794
121
17
Mean
274.3
285.1
266.5
269.0
233.0
351.2
366.3
267.7
151.1
268.2
303.5
295.0
314.7
283.9
257.8
271.3
306.4
279.4
286.6
343.5
300.3
251.3
176.4
212.9
340.3
172.6
207.3
247.5
261.6
319.1
272.7
275.4
278.4
267.4
309.8
186.0
296.6
276.8
254.1
262.4
273.2
288.0
270.0
277.1
176.4
258.3
277.0
212.6
275.8
SD
205.9
206.7
205.1
221.0
235.8
149.6
161.2
221.2
128.6
204.3
207.1
199.4
203.5
229.8
192.5
203.6
230.8
230.7
175.4
171.1
239.8
199.3
148.4
147.7
172.6
138.0
199.0
213.6
214.3
236.2
211.6
207.2
201.0
207.2
212.6
156.9
201.2
204.6
209.7
207.3
207.3
191.6
171.2
206.4
172.8
165.6
207.3
166.3
163.4
SE
3.8
5.9
5.0
31.3
23.8
7.6
8.6
5.4
6.6
4.3
11.4
25.5
27.0
19.4
34.6
4.0
14.9
64.0
35.1
6.0
7.5
11.6
5.3
39.5
5.7
10.7
8.0
9.4
11.4
12.4
8.3
7.9
6.2
8.7
4.6
5.4
6.9
7.2
8.1
8.4
4.0
12.7
45.8
3.9
19.6
39.0
3.9
15.1
39.6
Min Max
1 1,440
1 1,440
1 1,440
5 1,030
1 1,440
5 665
1 935
1 1,440
5 710
1 1,440
1 1,440
5 900
10 967
2 1,440
5 681
1 1,440
1 1,440
35 760
5 625
1 1 440
1 1,440
1 1,030
1 855
5 440
1 1,440
1 735
1 1,440
1 1,000
1 1,005
1 1,440
1 1,440
1 1,440
1 1,440
1 1,440
1 1,440
1 1,440
1 1,440
1 1,440
1 1,015
1 1,005
1 1,440
1 855
5 565
1 1,440
5 890
3 565
1 1,440
10 662
5 565
5
20
30
20
30
5
70
60
15
21
20
35
30
30
11
5
20
20
35
55
55
15
20
15
5
45
27
15
15
15
30
25
30
20
15
15
40
30
30
20
14
20
25
5
20
28
3
20
30
5
25
95
110
90
100
60
245
260
87
60
90
135
135
135
100
120
94
110
65
145
190
90
85
60
120
190
70
60
85
85
110
90
88
110
100
115
85
120
110
80
75
94
120
145
100
60
145
95
90
145
50
221
255
200
193
150
389
415
190
115
210
285
240
360
237
240
215
288
235
255
393
215
200
121
190
390
124
135
165
180
290
215
239
230
200
340
140
285
220
180
210
217
275
280
230
120
270
228
145
305
75
430
425
430
400
390
440
446
450
195
429
440
425
455
430
430
425
445
420
440
441
510
387
250
305
440
235
295
420
450
510
420
425
440
420
460
230
444
420
420
425
430
435
430
430
195
378
430
375
415
90
540
540
540
590
545
535
502
570
340
540
540
535
525
525
495
540
568
562
495
520
610
525
400
430
525
375
510
553
560
615
545
540
535
555
565
385
545
535
550
540
540
533
445
540
480
480
540
445
440
95
615
620
610
625
595
562
605
655
435
612
630
565
598
630
625
612
695
760
565
570
685
610
475
440
580
465
585
640
625
683
630
615
600
620
632
525
615
600
630
615
615
605
565
615
575
565
615
490
565
98
725
745
713
872
900
625
710
760
525
705
775
840
820
840
681
712
840
760
625
645
775
800
570
440
645
525
690
760
750
765
735
745
690
712
750
640
710
725
738
712
725
645
565
725
625
565
726
605
565
99
805
840
800
1,030
1,440
645
805
855
615
765
1,000
900
967
940
681
800
940
760
625
713
900
880
641
440
713
640
785
855
800
900
855
850
778
820
855
735
770
840
890
778
820
800
565
805
890
565
840
630
565
Page
16-48
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day)
at Selected Indoor Locations, Doers Only (continued)
Malls, Grocery Stores, or Other Stores
Percentiles
Group Name
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Group Code
Male
Female
-
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
2,697
1,020
1,677
50
110
129
140
1,871
397
2,234
237
37
52
110
27
2,476
188
12
21
372
1,170
285
854
16
420
206
792
583
411
285
622
601
871
603
1,721
976
683
679
759
576
2,480
208
9
2,607
74
16
2,553
130
14
Mean
115.0
120.2
111.8
139.4
90.0
77.7
88.7
125.9
88.6
111.6
123.0
158.9
150.2
133.1
124.7
114.4
126.1
49.4
122.4
86.9
136.8
134.1
91.2
98.9
88.3
128.9
126.3
129.8
117.9
78.2
110.2
108.2
127.9
107.9
117.5
110.6
111.7
115.8
113.1
120.2
116.2
101.1
85.1
116.0
90.8
62.7
115.7
104.8
71.1
SD
141.0
157.1
130.1
137.6
77.9
68.0
101.4
156.8
88.5
139.4
152.3
151.7
146.7
138.3
131.1
141.8
133.2
37.7
138.5
86.3
176.7
147.7
87.2
110.0
91.9
155.7
158.9
149.5
144.1
95.7
134.9
133.1
155.8
130.7
148.9
125.7
134.0
142.2
147.5
138.9
142.4
125.0
79.6
142.1
103.9
68.1
141.7
131.3
66.9
SE
2.7
4.9
3.2
19.5
7.4
6.0
8.6
3.6
4.4
3.0
9.9
24.9
20.3
13.2
25.2
2.9
9.7
10.9
30.2
4.5
5.2
8.8
3.0
27.5
4.5
10.8
5.6
6.2
7.1
5.7
5.4
5.4
5.3
5.3
3.6
4.0
5.1
5.5
5.4
5.8
2.9
8.7
26.5
2.8
12.1
17.0
2.8
11.5
17.9
Mm
1
1
1
15
5
3
1
1
1
1
2
2
5
1
10
1
1
0
10
1
1
-)
1
10
1
0
1
1
1
1
1
2
1
1
1
1
2
1
1
1
1
1
33
1
0
0
1
5
20
Max
1,080
840
1,080
660
420
320
530
1,080
655
1,080
800
600
660
720
515
1,080
720
122
515
660
1,080
540
585
357
660
1,080
960
800
720
630
755
840
1,080
840
1,080
840
840
720
1,080
840
1,080
600
290
1,080
630
290
1,080
613
290
5
10
5
10
20
10
5
5
10
10
10
10
14
14
10
10
10
10
2
20
5
10
6
10
10
5
10
5
10
10
10
5
10
10
10
10
5
10
10
5
10
10
5
33
10
15
2
10
10
20
25
30
30
30
45
40
30
20
30
30
30
25
50
65
35
30
30
30
18
33
30
30
30
30
32
29
30
30
30
30
25
30
30
30
30
30
30
30
30
30
30
30
30
55
30
37
30
30
25
35
50
60
60
60
93
65
60
45
60
60
60
60
105
103
90
60
60
90
48
60
60
60
65
60
53
60
75
60
70
60
50
60
60
60
60
60
65
60
60
60
60
60
60
58
60
64
55
60
60
57
75
135
130
135
180
105
110
124
150
120
130
135
220
180
195
207
132
173
70
180
120
150
186
120
115
120
150
150
165
135
90
130
130
155
120
135
135
135
130
125
160
135
120
60
135
105
60
135
135
70
90
285
375
255
339
210
180
223
360
180
265
370
410
280
310
300
285
270
105
290
206
480
400
195
290
210
330
365
345
290
160
280
250
320
255
320
255
255
300
300
295
288
245
290
290
150
110
285
193
110
95
482
530
400
420
250
225
318
525
255
495
480
480
588
450
380
495
450
122
380
255
562
480
255
357
263
500
524
510
515
250
465
440
520
430
510
380
420
500
510
480
495
420
290
495
190
290
481
505
290
98
570
609
550
565
359
255
384
600
400
570
600
600
600
535
515
570
540
122
515
360
640
520
360
357
384
570
600
563
600
450
563
560
600
550
586
560
568
588
570
550
575
545
290
570
510
290
570
575
290
99
640
658
600
660
360
280
413
658
470
640
613
600
660
540
515
640
610
122
515
384
690
540
420
357
420
605
660
651
640
555
600
645
660
600
650
608
660
645
610
640
640
550
290
640
630
290
640
609
290
Exposure Factors Handbook
September 2011
Page
16-49
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-18. Time Spent (minutes/day)
at Selected Indoor Locations,
Doers Only (continued)
Indoors at a Gym/Health Club
Percentiles
Category Population Group
All
Sex Male
Sex Female
Age (years)
Age (years) 1 to 4
Age (years) 5 to 1 1
Age (years) 12 to 17
Age (years) 1 8 to 64
Age (years) >64
Race White
Race Black
Race Asian
Race Some Others
Race Hispanic
Race Refused
Hispanic No
Hispanic Yes
Hispanic Refused
Employment
Employment Full Time
Employment Part Time
Employment Not Employed
Employment Refused
Education
Education < High School
Education High School Graduate
Education < College
Education College Graduate
Education Post Graduate
Census Region Northeast
Census Region Midwest
Census Region South
Census Region West
Day Of Week Weekday
Day Of Week Weekend
Season Winter
Season Spring
Season Summer
Season Fall
Asthma No
Asthma Yes
Asthma DK
Angina No
Angina Yes
Angina DK
Bronchitis/Emphysema No
Bronchitis/Emphysema Yes
Bronchitis/Emphysema DK
= Indicates missing data.
DK = The respondent replied "don't know".
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
N
364
176
188
6
5
28
39
254
32
307
30
10
11
4
2
345
17
2
72
176
40
75
1
81
9
61
71
81
61
83
62
118
101
281
83
127
85
81
71
333
28
3
357
4
3
352
10
2
Mean
129.7
147.2
113.2
202.5
156.0
105.3
165.4
123.1
141.4
134.3
117.7
75.2
112.9
83.8
57.5
132.0
90.1
57.5
139.6
131.2
129.3
117.9
40.0
136.9
110.6
128.5
145.6
122.0
115.6
140.5
127.0
125.7
127.0
121.3
158.1
139.8
141.5
109.9
119.9
132.4
100.1
101.7
130.5
90.0
81.7
130.7
97.3
107.5
SD
104.3
115.6
89.9
227.9
29.9
69.5
122.1
98.8
114.2
109.4
75.4
36.5
69.1
42.7
3.5
105.9
58.8
3.5
103.3
112.5
92.8
91.3
99.7
97.7
110.0
129.1
99.5
76.9
107.2
88.7
107.0
108.5
96.6
123.7
108.3
115.2
87.4
99.0
106.8
69.4
55.8
105.0
47.6
65.3
104.8
92.8
67.2
SE
5.5
8.7
6.6
93.0
13.4
13.1
19.5
6.2
20.2
6.2
13.8
11.5
20.8
21.3
2.5
5.7
14.3
2.5
12.2
8.5
14.7
10.5
11.1
32.6
14.1
15.3
11.1
9.8
11.8
11.3
9.9
10.8
5.8
13.6
9.6
12.5
9.7
11.7
5.9
13.1
32.2
5.6
23.8
37.7
5.6
29.4
47.5
Min
5
5
5
30
105
5
15
5
10
5
5
30
25
40
55
5
5
55
5
5
25
5
40
5
10
5
5
15
10
20
5
5
5
5
5
5
10
5
20
5
5
60
5
60
30
5
10
60
Max
686
686
660
560
180
325
660
686
533
686
320
145
270
140
60
686
255
60
660
686
420
533
40
660
300
660
600
686
415
660
440
660
686
686
660
686
600
525
660
686
330
165
686
160
155
686
330
155
5
30
30
30
30
105
30
30
30
30
30
10
30
25
40
55
30
5
55
30
30
35
25
40
30
10
25
35
30
40
40
25
15
50
30
30
25
30
30
30
30
25
60
30
60
30
30
10
60
25
60
78
60
55
160
58
90
60
60
65
60
54
65
53
55
65
60
55
76
60
60
60
40
75
30
75
65
60
60
70
60
60
60
60
77
75
65
60
56
62
60
60
62
60
30
61
45
60
50
110
120
93
75
160
83
138
100
103
110
115
60
90
78
58
110
90
58
120
110
95
90
40
120
80
105
110
98
90
120
113
105
92
98
120
120
102
90
98
110
86
80
110
70
60
110
77
108
75
155
175
135
420
175
141
206
150
173
164
145
95
153
115
60
160
115
60
165
150
168
145
40
164
165
145
170
135
145
170
170
150
135
145
180
177
164
130
150
160
118
165
155
120
155
158
120
155
90
240
285
200
560
180
165
330
210
292
255
235
133
179
140
60
240
140
60
265
240
285
230
40
215
300
210
285
220
225
240
285
240
225
210
285
240
285
160
215
255
210
165
240
160
155
240
245
155
95
320
360
279
560
180
270
440
295
340
330
285
145
270
140
60
325
255
60
330
330
325
285
40
325
300
310
533
285
265
330
300
330
292
295
415
330
340
310
295
325
230
165
325
160
155
320
330
155
98
525
533
420
560
180
325
660
475
533
533
320
145
270
140
60
533
255
60
440
560
420
475
40
440
300
525
560
420
320
600
340
533
525
475
600
533
560
440
420
533
330
165
525
160
155
525
330
155
99
600
660
560
560
180
325
660
600
533
600
320
145
270
140
60
600
255
60
660
660
420
533
40
660
300
660
600
686
415
660
440
540
560
560
660
660
600
525
660
600
330
165
600
160
155
600
330
155
Page
16-50
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-19. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population and Doers Only,
Children <21 years
Age (years) A^ Mean
A fiii
Mill
1
2
5 10
Percentiles
25 50 75
90
95
98
99
Max
School Grounds/Playground — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in Selected
Outdoor Locations,
Doers Only
Outdoors on School Grounds/Playground
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12tol7
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
DK
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
Yes
No
Yes
DK
N
259
0.136
123
2
9
64
76
101
7
208
23
6
7
15
225
32
2
143
48
24
42
2
162
11
33
19
19
15
66
53
82
58
205
54
53
88
65
53
237
22
254
5
248
10
1
Mean
98.4
118.0
76.7
275.0
85.0
88.0
78.7
119.8
65.0
98.2
128.4
59.0
70.0
83.7
102.6
71.2
57.5
80.2
130.3
129.7
95.4
322.5
86.6
124.8
113.6
129.8
122.1
102.9
106.0
86.1
85.5
119.3
87.0
141.5
72.2
108.6
116.4
85.5
100.9
70.9
99.1
61.2
100.6
52.7
15.0
SD
110.1
126.4
83.9
374.8
61.1
95.6
88.2
127.6
47.3
106.5
157.5
66.1
59.7
103.0
113.7
79.9
31.8
88.0
127.2
158.9
94.8
307.6
94.6
171.9
110.7
147.4
149.9
98.1
115.2
109.2
92.4
125.6
105.5
117.1
102.0
96.5
137.9
96.2
113.2
62.0
110.8
53.4
111.6
45.4
0.0
SE
6.8
10.8
7.6
265.0
20.4
12.0
10.1
12.7
17.9
7.4
32.9
27.0
22.6
26.6
7.6
14.1
22.5
7.4
18.4
32.4
14.6
217.5
7.4
51.8
19.3
33.8
34.4
25.3
14.2
15.0
10.2
16.5
7.4
15.9
14.0
10.3
17.1
13.2
7.4
13.2
7.0
23.9
7.1
14.4
0.0
Min
1
1
1
10
10
5
3
1
5
1
5
10
10
1
3
1
35
3
1
3
1
105
3
1
3
5
5
1
5
3
1
1
1
10
1
5
5
5
1
5
1
1
1
9
15
Max
690
690
570
540
175
625
570
690
150
690
570
179
180
370
690
370
80
625
555
690
440
540
625
540
555
510
690
360
690
540
570
625
625
690
555
540
690
540
690
179
690
130
690
160
15
5
5
10
5
10
10
10
5
5
5
9
5
10
10
1
9
1
35
9
10
10
5
105
10
1
5
5
5
1
10
5
5
10
5
25
3
10
10
5
5
10
5
1
5
9
15
25
30
35
20
10
30
30
25
30
30
30
25
10
10
10
30
13
35
25
40
35
30
105
27
5
30
33
50
30
30
20
30
30
25
67
20
45
30
20
30
15
30
15
30
22
15
50
70
85
51
275
65
60
55
85
60
70
67
35
60
30
70
33
58
55
85
85
80
323
60
45
90
70
85
75
85
50
60
85
55
113
35
85
75
55
70
45
69
70
71
44
15
75
120
149
120
540
140
120
105
165
95
125
170
85
105
120
125
110
80
115
180
144
120
540
120
180
160
210
125
125
150
115
115
160
115
180
85
148
135
120
120
145
120
90
125
60
15
90
208
255
180
540
175
170
165
240
150
190
300
179
180
228
210
150
80
160
300
228
180
540
170
345
240
440
235
235
190
190
180
235
180
290
130
215
270
180
215
160
208
130
210
125
15
95
300
370
225
540
175
220
225
360
150
281
540
179
180
370
300
228
80
215
360
510
235
540
220
540
290
510
690
360
281
290
255
440
240
345
315
255
360
235
315
165
300
130
300
160
15
98
540
555
270
540
175
315
370
540
150
510
570
179
180
370
540
370
80
315
555
690
440
540
370
540
555
510
690
360
540
510
360
555
540
440
440
510
625
345
540
179
540
130
540
160
15
99
570
625
440
540
175
625
570
555
150
555
570
179
180
370
570
370
80
570
555
690
440
540
570
540
555
510
690
360
690
540
570
625
555
690
555
540
690
540
570
179
570
130
570
160
15
Page
16-52
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued)
Outdoors at a Park/ Go If Course
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers
Only
(continued)
Outdoors at a Pool/River/Lake
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
Refused
-
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
283
152
131
6
14
29
22
187
25
246
12
4
5
12
4
259
20
4
66
119
26
69
3
73
18
69
62
37
24
61
41
111
70
165
118
30
77
151
25
262
17
4
272
8
3
266
14
3
Mean
209.6
229.8
186.0
175.0
250.6
175.4
128.3
224.5
194.2
201.6
380.6
265.0
237.0
161.0
243.8
208.9
210.9
243.8
176.9
210.7
217.0
238.9
141.7
172.9
267.6
213.2
233.3
230.9
172.7
220.7
219.2
182.2
237.6
188.8
238.6
173.2
206.5
219.7
201.4
209.0
238.8
121.3
205.9
359.4
141.7
211.0
197.1
141.7
SD
185.7
202.7
161.3
157.0
177.5
117.9
94.4
203.8
161.8
182.3
231.9
247.1
129.9
131.7
208.6
187.8
160.1
208.6
131.3
176.1
199.9
236.2
52.5
130.0
159.4
224.1
192.4
187.3
197.0
172.4
257.2
161.3
181.8
179.9
190.4
181.7
163.6
196.8
189.7
188.2
162.0
59.2
185.2
178.8
52.5
189.1
131.5
52.5
SE
11.0
16.4
14.1
64.1
47.4
21.9
20.1
14.9
32.4
11.6
66.9
123.5
58.1
38.0
104.3
11.7
35.8
104.3
16.2
16.1
39.2
28.4
30.3
15.2
37.6
27.0
24.4
30.8
40.2
22.1
40.2
15.3
21.7
14.0
17.5
33.2
18.6
16.0
37.9
11.6
39.3
29.6
11.2
63.2
30.3
11.6
35.2
30.3
Min
5
10
5
60
90
25
40
5
20
5
20
30
70
20
90
5
20
90
25
10
20
5
90
20
40
10
5
14
20
30
10
5
25
10
5
20
15
5
20
5
15
60
5
60
90
5
15
90
Max
1,440
1,440
645
480
630
390
420
1,440
525
1,440
690
505
435
390
550
1,440
540
550
630
900
670
1,440
195
630
600
1,440
690
645
900
900
1,440
670
690
1,440
900
630
690
1,440
670
1,440
570
195
1,440
690
195
1,440
440
195
5
25
30
20
60
90
30
58
20
30
25
20
30
70
20
90
25
29
90
40
20
30
20
90
30
40
20
30
20
25
30
20
20
40
30
20
20
30
26
45
25
15
60
25
60
90
25
15
90
25
60
83
60
85
130
60
60
60
60
60
178
53
220
53
115
60
88
115
70
65
60
65
90
70
145
60
65
70
45
60
60
60
90
60
75
40
80
65
70
60
105
75
60
288
90
60
90
90
50
150
174
135
115
168
145
83
150
115
145
450
263
225
113
168
150
155
168
143
150
120
145
140
140
248
145
150
173
113
180
120
118
180
125
188
103
180
155
105
150
225
115
145
340
140
150
173
140
75
296
305
280
195
370
293
210
320
277
285
563
478
235
265
373
295
338
373
235
298
320
370
195
225
375
285
360
400
240
325
280
280
300
255
350
270
288
300
310
295
350
168
291
435
195
296
300
195
90
480
510
440
480
560
365
225
511
480
440
615
505
435
375
550
480
451
550
370
510
570
510
195
370
525
511
550
505
370
390
480
420
548
420
555
493
480
445
510
480
525
195
480
690
195
480
370
195
95
570
600
550
480
630
375
235
615
510
560
690
505
435
390
550
585
526
550
420
600
580
630
195
420
600
670
580
630
480
510
600
525
615
511
630
585
555
580
510
580
570
195
570
690
195
580
440
195
98
670
690
630
480
630
390
420
690
525
670
690
505
435
390
550
670
540
550
560
645
670
690
195
560
600
690
615
645
900
670
1,440
630
690
615
690
630
670
630
670
670
570
195
645
690
195
670
440
195
99
690
900
630
480
630
390
420
900
525
690
690
505
435
390
550
690
540
550
630
670
670
1,440
195
630
600
1,440
690
645
900
900
1,440
645
690
670
690
630
690
900
670
690
570
195
690
690
195
690
440
195
Page
16-54
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in
Selected Outdoor Locations,
Outdoors on a Sidewalk, Street
Doers Only (continued)
or in the Neighborhood
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
896
409
487
15
30
75
74
580
122
727
87
11
18
42
11
807
79
1
9
176
384
74
255
7
198
56
223
172
138
109
202
193
298
203
642
254
210
242
276
168
832
57
7
857
33
6
855
34
7
Mean
85.8
108.8
66.5
72.5
54.8
110.8
52.6
94.3
59.4
85.7
89.2
88.7
80.6
71.4
122.9
87.5
67.8
2.0
100.8
79.2
102.2
74.4
70.0
45.1
74.9
131.2
100.2
77.2
76.3
78.2
89.1
87.9
79.9
89.1
86.7
83.5
73.5
97.9
84.0
86.6
86.1
85.6
48.9
86.2
81.7
52.0
84.8
117.7
46.3
SD
133.8
168.1
91.9
69.4
52.7
116.8
74.8
153.9
61.5
136.5
132.7
114.0
106.0
110.8
117.7
136.1
110.3
-
115.9
96.3
169.5
113.9
94.0
36.6
92.3
247.3
146.9
128.8
106.6
121.3
132.3
153.3
125.5
127.9
143.9
104.2
144.3
137.2
123.1
131.9
129.5
193.1
28.0
134.9
117.4
29.3
132.3
176.4
27.5
SE
4.5
8.3
4.2
17.9
9.6
13.5
8.7
6.4
5.6
5.1
14.2
34.4
25.0
17.1
35.5
4.8
12.4
-
38.6
7.3
8.7
13.2
5.9
13.8
6.6
33.0
9.8
9.8
9.1
11.6
9.3
11.0
7.3
9.0
5.7
6.5
10.0
8.8
7.4
10.2
4.5
25.6
10.6
4.6
20.4
11.9
4.5
30.3
10.4
Mm
1
1
1
1
1
1
1
1
1
1
1
2
10
1
2
1
1
2
2
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
2
1
3
2
Max
1,440
1,440
580
290
235
540
435
1,440
380
1,440
565
405
420
525
310
1,440
615
2
310
540
1,440
795
615
90
540
1,440
795
675
600
710
735
1,440
710
795
1,440
565
1,440
795
690
710
795
1,440
90
1,440
465
90
1,440
735
90
5
2
3
1
1
2
5
2
2
2
2
2
2
10
1
2
2
1
2
2
2
3
1
1
2
2
1
5
i
3
5
3
2
2
1
2
2
1
4
4
2
2
1
2
2
1
2
2
8
2
25
15
20
15
40
10
20
15
15
20
15
10
30
20
20
40
15
15
2
40
15
15
15
15
4
15
15
20
10
20
20
15
15
15
20
15
25
15
25
15
15
15
15
30
15
17
40
15
30
32
50
40
45
35
55
43
65
30
40
40
41
35
45
40
40
60
45
30
2
60
45
41
43
40
40
41
40
45
30
45
45
45
30
35
45
40
45
33
45
45
40
40
35
60
40
45
60
40
45
40
75
90
120
75
90
78
178
60
83
75
90
120
120
75
75
290
90
62
2
90
110
75
86
85
90
90
118
95
75
70
60
90
85
75
105
80
90
60
120
90
90
90
90
60
90
60
60
85
120
60
90
223
330
152
120
125
240
125
278
120
215
324
149
240
135
300
225
140
2
310
200
330
180
152
90
185
465
275
180
205
200
235
240
185
210
223
220
160
240
200
240
225
180
90
223
250
90
225
215
90
95
405
525
255
290
158
410
200
480
190
405
426
405
420
290
310
410
300
2
310
260
525
255
270
90
240
710
480
435
310
330
410
333
420
300
426
310
270
435
420
405
418
235
90
410
380
90
405
690
90
98
565
615
435
290
235
465
338
600
235
570
540
405
420
525
310
565
525
2
310
435
600
390
380
90
435
735
600
570
485
560
530
565
532
570
585
440
560
570
525
600
565
260
90
565
465
90
560
735
90
99
615
710
465
290
235
540
435
690
270
675
565
405
420
525
310
600
615
2
310
465
710
795
485
90
465
1,440
680
600
565
570
570
600
680
615
680
480
710
675
580
615
600
1,440
90
615
465
90
600
735
90
Exposure Factors Handbook
September 2011
Page
16-55
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued)
At Home in the Yard or Other Areas
Outside the House
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
2,308
1,198
1,107
3
27
151
271
157
1,301
401
1,966
173
21
37
83
28
2,122
153
10
23
581
807
166
739
15
615
236
618
381
251
207
473
456
832
547
1,453
855
399
787
796
326
2,129
166
13
2,228
63
17
2,191
105
12
Mean
137.6
158.4
114.9
183.3
167.4
135.3
150.6
113.2
136.4
141.1
139.0
128.4
101.2
183.5
106.1
152.3
137.7
125.0
213.8
176.7
137.5
131.1
126.1
146.1
198.0
136.3
161.0
144.7
128.8
123.0
127.1
137.7
138.9
136.5
138.2
126.9
155.7
112.2
149.7
143.7
124.5
137.7
131.6
188.5
136.5
158.7
199.1
138.8
104.4
207.5
SD
144.1
160.0
120.9
60.3
164.5
111.5
135.1
117.7
147.9
155.2
145.5
144.6
88.5
161.9
96.8
151.0
144.3
134.3
192.2
156.6
125.6
150.7
134.1
149.7
239.0
125.7
186.5
144.9
141.2
135.8
150.0
132.8
155.7
146.7
139.9
131.6
161.7
136.0
139.2
155.9
130.5
144.4
136.0
192.1
141.1
216.3
191.3
145.0
111.3
192.2
SE
3.0
4.6
3.6
34.8
31.7
9.1
8.2
9.4
4.1
7.8
3.3
11.0
19.3
26.6
10.6
28.5
3.1
10.9
60.8
32.6
5.2
5.3
10.4
5.5
61.7
5.1
12.1
5.8
7.2
8.6
10.4
6.1
7.3
5.1
6.0
3.5
5 5
6.8
5.0
5 5
7.2
3.1
10.6
53.3
3.0
27.3
46.4
3.1
10.9
55.5
Min Max
1 1,290
1 1,290
1 1,065
120 240
2 600
5 630
2 1,250
2 660
1 1,080
1 1,290
1 1,290
1 1,250
12 360
2 750
2 610
5 600
1 1,290
1 750
3 585
5 600
2 1,250
1 1,080
1 1,080
1 1,290
5 660
2 1,250
2 1,290
1 840
1 1,080
1 750
1 1,065
1 750
2 1,290
1 1,080
1 750
1 1,250
1 1,290
1 1,080
1 915
1 1,290
1 720
1 1,290
1 670
5 600
1 1,290
2 1,080
5 600
1 1,290
1 553
5 600
5
10
10
5
120
5
25
20
5
5
10
10
5
15
3
5
5
10
5
3
5
15
5
10
10
5
15
10
5
5
10
5
10
10
10
5
5
10
5
10
10
10
10
10
5
10
5
5
10
5
5
25
40
60
30
120
60
60
60
30
30
45
40
30
35
84
35
60
40
30
60
60
60
30
30
45
30
60
45
40
35
30
30
45
45
35
36
35
45
30
60
45
35
40
30
60
41
30
35
45
30
60
50
90
120
75
190
120
90
120
80
90
90
90
95
90
120
75
98
90
85
145
160
110
80
78
100
120
105
105
100
85
75
78
90
90
90
90
90
110
60
120
99
88
90
90
90
90
75
120
90
60
140
75
180
198
150
240
230
180
190
150
180
180
180
180
125
270
145
210
180
150
380
240
180
175
180
185
465
180
195
195
175
160
150
185
180
180
180
165
210
140
195
180
160
180
165
300
180
180
325
180
145
330
90
320
360
285
240
395
305
310
240
330
302
330
270
210
380
240
360
320
270
503
360
300
307
300
360
600
300
390
360
300
300
320
317
300
310
330
300
360
300
338
330
300
315
345
480
315
420
480
320
270
480
95
420
500
360
240
600
345
405
405
435
465
435
390
240
553
270
510
420
435
585
510
370
450
360
465
660
370
510
479
400
390
435
420
440
420
460
395
475
380
430
450
380
420
450
600
420
485
600
430
360
600
98
570
627
450
240
600
450
553
462
570
598
570
462
360
750
330
600
570
575
585
600
480
600
450
585
660
480
765
555
585
575
570
532
575
570
570
553
630
540
555
610
510
570
553
600
570
1,065
600
570
415
600
99
660
730
560
240
600
480
570
610
715
660
670
745
360
750
610
600
670
630
585
600
570
745
485
655
660
570
915
660
720
690
630
600
690
730
630
610
745
690
660
715
655
690
610
600
660
1,080
600
690
475
600
Page
16-56
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers
Only
(continued)
Cumulative Outdoors (outside the residence)
Percentiles
Group Name Group Code
All
Sex Male
Sex Female
Sex Refused
Age (years)
Age (years) 1 to 4
Age (years) 5 to 1 1
Age (years) 1 2 to 1 7
Age (years) 1 8 to 64
Age (years) >64
Race White
Race Black
Race Asian
Race Some Others
Race Hispanic
Race Refused
Hispanic No
Hispanic Yes
Hispanic DK
Hispanic Refused
Employment
Employment Full Time
Employment Part Time
Employment Not Employed
Employment Refused
Education
Education < High School
Education High School Graduate
Education < College
Education College Graduate
Education Post Graduate
Census Region Northeast
Census Region Midwest
Census Region South
Census Region West
Day Of Week Weekday
Day Of Week Weekend
Season Winter
Season Spring
Season Summer
Season Fall
Asthma No
Asthma Yes
Asthma DK
Angina No
Angina Yes
Angina DK
Bronchitis/Emphysema No
Bronchitis/Emphysema Yes
Bronchitis/Emphysema DK
= Indicates missing data.
DK = The respondent replied "don't know
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
N
3,124
1,533
1,588
3
40
201
353
219
1,809
502
2,622
255
34
53
125
35
2,857
222
15
30
774
1,110
240
978
22
825
306
837
527
355
274
635
639
1,120
730
1,933
1,191
548
1,034
1,098
444
2,869
236
19
3,023
76
25
2,968
139
17
Mean
154.0
174.9
133.5
340.0
164.0
195.7
187.6
135.3
144.2
156.4
156.8
141.6
115.8
167.0
117.3
187.1
153.8
146.4
191.5
212.5
175.8
141.3
134.7
156.1
152.7
174.1
171.9
153.6
143.4
126.9
130.5
148.0
156.0
158.6
150.6
141.2
174.9
114.0
171.9
168.3
126.5
154.5
145.8
182.4
153.2
172.9
195.0
154.9
129.4
206.8
SD
158.3
173.7
138.8
140.0
179.6
163.7
158.6
137.0
155.1
168.3
160.2
153.2
135.6
149.0
128.9
163.8
158.4
154.1
178.3
165.3
156.1
159.9
140.8
159.2
209.8
156.2
188.4
154.8
157.1
142.6
151.0
143.7
169.2
165.2
149.6
149.0
170.4
138.1
159.4
168.2
140.7
159.2
145.5
181.0
156.3
222.3
170.4
158.8
142.5
179.8
SE
2.8
4.4
3.5
80.8
28.4
11.5
8.4
9.3
3.6
7.5
3.1
9.6
23.2
20.5
11.5
21.1
3.0
10.3
46.0
30.2
5.6
4.8
9.1
5.1
44.7
5.4
10.8
5.4
6.8
7.6
9.1
5.7
6.7
4.9
5 5
3.4
4.9
5.9
5.0
5.1
6.7
3.0
9.5
41.5
2.8
25.5
34.1
2.9
12.1
43.6
Mm
1
1
1
240
2
3
4
1
1
1
1
1
1
3
1
5
1
1
15
5
1
1
1
1
5
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
5
1
1
5
Max
1,290
1,290
1,065
500
720
715
1,250
720
1,080
1,290
1,290
1,250
480
750
720
600
1,290
750
585
600
1,250
1,080
1,080
1,290
660
1,250
1,290
840
1,080
750
1,065
750
1,290
1,080
855
1,250
1,290
1,080
990
1,290
960
1,290
885
600
1,290
1,080
600
1,290
855
600
5
5
10
5
240
4
30
20
5
5
5
5
5
5
5
5
5
5
5
15
5
15
5
5
5
5
15
7
5
5
5
5
5
5
5
5
5
10
5
10
5
5
5
5
1
5
5
5
5
5
5
25
40
60
30
240
40
75
80
35
30
36
45
30
20
60
30
60
40
30
40
60
60
30
30
40
15
60
45
35
30
30
30
35
45
40
36
31
50
25
60
50
30
40
45
60
40
30
60
40
30
60
50
105
120
90
280
108
135
150
100
90
110
105
95
60
130
70
170
105
113
140
180
125
85
90
115
60
125
120
105
90
80
75
105
102
110
105
90
120
60
120
120
75
105
105
120
105
69
150
105
75
170
75
210
240
190
500
213
270
265
190
199
210
215
195
150
238
150
240
210
200
380
345
245
195
183
220
125
240
240
215
195
170
180
215
210
210
213
190
260
150
240
235
163
210
190
300
210
253
300
210
175
300
90
362
420
325
500
430
430
365
300
360
375
375
330
360
320
270
450
362
345
420
458
380
359
333
375
555
380
405
380
360
300
325
345
360
390
360
345
400
280
390
400
313
365
360
480
360
465
465
367
327
480
95
480
540
415
500
600
535
479
452
470
485
485
420
450
475
355
510
480
480
585
510
480
490
423
480
600
480
510
480
465
415
465
450
500
495
465
452
500
380
495
510
420
480
450
600
479
660
480
480
415
600
98
610
680
525
500
720
625
600
545
600
645
625
535
480
553
590
600
610
640
585
600
610
660
485
610
660
610
765
598
615
615
570
575
655
640
575
598
660
540
645
630
575
615
575
600
610
1,065
600
615
553
600
99
715
745
610
500
720
699
720
610
715
735
720
645
480
750
610
600
720
690
585
600
705
745
525
701
660
699
855
701
720
690
660
610
750
745
660
698
745
690
730
715
655
720
610
600
707
1,080
600
715
735
600
Exposure Factors Handbook
September 2011
Page
16-57
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-21. Mean Time Spent (minutes/day) Inside and Outside, by Age Category, Children <21 years
Age (years) N Average Indoor Minutes3 Average Outdoor Minutes* Avera§
Birth to <1 25 1,353 44
lto<2 90 1,353 36
2to<3 131 1,316 76
3to<6 360 1,278 107
6to64 156.5 485 141.1 465
Total Time Outdoors15
95th
Mean Percentile
281
298
Time Indoors
Age
(years) Total Minutes/24 hours Total Time Outdoors
Mean
18 to 64 1,440 281
>64 1,440 298
Total Time Indoors0
Mean
1,159
1,142
a For additional statistics see Table 16-26.
b Total Time Outdoors was calculated by summing the time spent outdoors away from the
residence and the time outdoors at the residence.
Source: U.S. EPA, 1996.
Page
16-58
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles
Doers Only, Children <21 Years
Age (years)
N
Combined Whole Population and
Percentiles
1
2
5 10 25 50
75
90
95
98
99
Max
Car — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined Whole Population and
Doers Only, Children <21 Years (continued)
2
5 10
Percentiles
25
50
75
90
95
98
99
All Vehicles — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-24. Time Spent (minutes/day) in
Selected Vehicles and All Vehicles Combined, Doers Only
Car
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
Ito 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
6,560
2,852
3,706
-)
120
297
449
393
4,489
812
5,337
640
117
121
265
80
5,987
477
29
67
1,124
3,134
632
1,629
41
1,260
434
1,805
1,335
992
734
1,412
1,492
2,251
1,405
4,427
2,133
1,703
1,735
1,767
1,355
6,063
463
34
6,368
154
38
6,224
300
36
Mean
87.4
90.7
84.9
30.0
94.0
63.0
64.6
64.8
93.8
83.5
87.6
86.8
78.8
87.7
90.1
82.4
87.5
88.5
63.9
86.1
64.2
93.6
90.1
90.4
97.2
66.5
86.0
91.8
93.2
95.7
91.5
85.8
89.1
88.3
85.9
83.9
94.7
83.5
88.6
88.0
90.1
87.4
88.2
78.4
87.5
82.2
89.6
87.6
85.6
81.1
SD
88.2
97.3
80.4
14.1
90.2
56.8
81.1
71.0
92.3
79.4
89.7
74.3
66.3
84.5
101.5
73.3
87.6
97.2
73.1
78.4
72.3
92.2
82.0
90.2
84.0
72.3
82.1
91.1
94.3
95.5
82.0
83.8
86.6
89.3
92.2
85.0
94.0
82.1
91.5
86.5
93.2
88.0
92.1
57.4
88.7
68.6
72.9
88.9
76.2
63.1
SE
1.1
1.8
1.3
10.0
8.2
3.3
3.8
3.6
1.4
2.8
1.2
2.9
6.1
7.7
6.2
8.2
1.1
4.5
13.6
9.6
2 2
1.6
3.3
2 2
13.1
2.0
3.9
2.1
2.6
3.0
3.0
2.2
2 2
1.9
2.5
1.3
2.0
2.0
2.2
2.1
2.5
1.1
4.3
9.8
1.1
5 5
11.8
1.1
4.4
10.5
Mm
1
1
1
20
7
2
1
1
1
4
1
1
5
3
2
5
i
2
5
5
i
2
2
1
10
1
5
1
2
4
4
1
4
1
2
1
1
1
1
1
1
1
4
10
1
8
10
1
1
5
Max
1,280
1,280
878
40
593
390
900
630
1,280
780
1,280
690
360
540
825
420
1,280
825
325
420
900
1,280
878
780
330
900
620
870
1,280
840
905
780
825
900
1,280
905
1,280
870
905
900
1,280
1,280
870
239
1,280
365
360
1,280
505
239
5
10
10
10
20
10
10
5
9
13
10
10
10
20
10
15
12
10
10
6
14
5
15
10
10
15
6
10
10
10
14
20
10
10
10
10
10
10
10
10
10
10
10
15
10
10
10
10
10
10
10
25
34
30
35
20
38
25
20
20
40
30
31
35
35
30
35
30
35
30
20
30
20
40
40
35
30
21
35
38
36
40
40
33
35
34
30
30
35
30
30
35
35
34
34
30
34
30
35
34
35
30
50
63
63
64
30
72
45
40
41
70
60
64
65
60
60
65
60
65
60
40
60
45
70
70
60
75
45
60
65
70
73
75
60
65
65
60
60
70
60
60
65
70
63
64
71
64
60
74
62
69
71
75
110
115
110
40
120
80
85
80
120
110
110
115
95
120
100
120
110
103
60
120
81
120
117
115
120
85
115
115
120
120
115
110
113
115
110
105
120
105
110
115
115
110
110
100
110
115
120
110
109
120
90
175
185
165
40
180
135
145
136
184
165
175
180
135
180
165
168
175
180
187
180
136
180
175
195
220
145
165
190
180
185
175
170
180
175
175
165
190
165
180
170
170
175
165
160
175
162
180
175
185
175
95
240
254
220
40
223
180
175
185
250
225
240
240
225
250
235
230
240
240
200
239
180
242
230
250
290
187
210
255
250
250
235
240
250
235
235
225
265
230
250
235
240
240
245
220
240
214
239
240
238
220
98
345
360
335
40
435
235
310
300
360
315
360
305
320
330
465
315
345
388
325
315
270
360
330
365
330
270
360
385
380
370
330
330
360
338
345
330
360
350
380
330
335
350
345
239
350
285
360
350
305
239
99
450
526
420
40
450
270
345
380
495
405
460
330
330
345
620
420
440
595
325
420
345
490
384
465
330
350
455
465
460
580
380
410
465
490
435
440
455
425
480
450
545
450
505
239
450
320
360
450
435
239
Exposure Factors Handbook
September 2011
Page
16-61
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-24. Time Spent (minutes/day)
in Selected Vehicles and All Vehicles Combined, Doers Only (continued)
Truck (Pick-up/Van)
Percentiles
Group Name
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Group Code
Male
Female
-
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,172
760
412
13
41
89
80
859
90
1,022
68
3
20
48
11
1,069
87
5
11
205
642
97
217
11
230
119
392
238
127
66
170
268
491
243
796
376
322
300
323
227
1,092
72
8
1,142
20
10
1,128
35
9
Mean
85.3
91.1
74.6
110.8
80.8
47.6
66.8
91.4
79.0
84.7
91.3
138.3
67.2
92.8
88.2
85.1
89.1
58.0
85.9
60.2
93.3
89.4
83.0
96.4
64.0
90.5
87.6
92.0
85.2
112.4
85.4
91.2
87.3
74.7
80.1
96.3
78.5
92.5
86.1
84.2
85.3
83.6
101.9
84.9
93.4
118.5
85.5
77.8
93.3
SD
95.9
105.4
74.2
129.2
154.3
44.2
71.1
98.0
82.4
96.2
98.5
63.3
48.5
99.3
110.8
95.6
100.8
36.2
111.6
86.4
101.4
89.0
85.8
114.3
86.9
81.7
94.7
111.8
74.6
118.0
104.2
94.4
100.1
81.3
90.6
105.5
91.6
100.2
99.3
90.9
93.5
125.3
129.7
95.2
116.0
128.6
96.6
60.5
123.9
SE
2.8
3.8
3.7
35.8
24.1
4.7
7.9
3.3
8.7
3.0
11.9
36.6
10.8
14.3
33.4
2.9
10.8
16.2
33.7
6.0
4.0
9.0
5.8
34.5
5.7
7.5
4.8
7.2
6.6
14.5
8.0
5.8
4.5
5.2
3.2
5.4
5.1
5.8
5.5
6.0
2.8
14.8
45.8
2.8
25.9
40.7
2.9
10.2
41.3
Mm
1
1
1
10
1
1
5
2
10
1
6
90
5
5
10
1
5
20
10
1
4
2
5
10
1
5
2
4
5
10
2
1
4
5
1
2
1
1
2
5
i
5
10
i
5
10
i
5
10
Max
955
955
510
450
955
240
352
750
453
955
453
210
165
440
390
955
630
97
390
955
750
460
655
390
955
453
675
750
370
650
695
750
955
478
750
955
955
695
750
675
750
955
390
955
555
390
955
240
390
5
10
10
10
10
10
7
6
10
12
10
14
90
8
10
10
10
5
20
10
7
10
6
10
10
7
14
10
10
15
10
10
10
10
10
10
12
10
10
10
10
10
10
10
10
8
10
10
5
10
25
30
30
25
35
15
15
15
30
30
30
28
90
25
28
30
30
29
20
30
15
30
30
30
30
15
35
30
30
30
35
20
30
30
23
30
30
29
30
30
30
30
20
20
30
38
30
30
30
20
50
60
60
55
60
35
30
37
60
49
60
63
115
63
60
60
60
60
68
35
30
60
60
60
35
35
60
60
60
60
80
50
60
60
52
55
61
51
60
60
60
60
46
60
60
70
60
60
60
60
75
110
115
95
90
70
65
94
115
105
110
106
210
103
120
65
110
115
85
65
75
120
120
110
170
85
120
115
110
110
135
110
119
111
90
101
120
95
120
110
105
110
115
128
110
103
190
110
120
65
90
180
190
165
300
206
110
180
189
185
180
220
210
137
224
190
180
210
97
190
146
192
190
180
190
160
195
185
190
180
220
186
205
180
160
170
192
170
208
180
165
184
170
390
180
141
340
180
165
390
95
240
265
220
450
210
130
223
260
265
235
295
210
155
330
390
240
230
97
390
185
270
270
235
390
206
280
255
290
230
412
260
245
235
235
230
280
220
268
233
265
240
235
390
235
351
390
240
220
390
98
395
450
300
450
955
180
265
440
390
390
450
210
165
440
390
390
440
97
390
240
450
450
300
390
245
295
450
555
345
445
445
390
445
395
375
430
355
443
430
395
412
395
390
395
555
390
412
240
390
99
478
620
355
450
955
240
352
555
453
510
453
210
165
440
390
478
630
97
390
265
555
460
355
390
352
450
510
655
355
650
630
460
595
440
510
460
445
549
595
465
478
955
390
475
555
390
478
240
390
Page
16-62
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-24. Time Spent (minutes/day) in Selected Vehicles and
(continued)
All Vehicles Combined, Doers Only
Bus
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
469
219
250
14
5
133
143
147
27
311
101
15
14
24
4
415
46
9
6
274
95
34
61
5
295
25
57
38
30
24
145
102
142
80
426
43
158
140
94
77
413
50
6
459
4
6
442
19
8
Mean
74.6
77.3
72.4
145.0
56.0
48.4
59.4
96.6
132.0
70.1
85.2
58.0
107.1
65.5
168.0
72.8
83.9
47.5
137.8
54.0
122.6
83.3
80.3
167.4
55.3
120.4
111.6
108.8
84.6
110.5
77.1
69.7
71.7
81.8
70.6
114.7
78.3
61.6
86.6
76.2
76.4
55.4
111.5
73.4
168.8
109.5
74.8
58.2
104.6
SD
93.5
104.1
83.3
167.2
40.2
29.4
46.3
128.4
144.6
89.5
92.4
58.5
176.5
71.5
196.2
86.1
138.9
10.6
159.6
39.4
168.8
79.3
69.2
169.9
45.0
124.3
116.7
133.4
128.1
199.2
75.4
103.3
82.8
124.3
84.6
152.2
98.1
53.5
116.7
107.5
96.8
39.3
161.5
91.3
182.7
162.4
94.3
39.9
137.9
SE
4.3
7.0
5.3
44.7
18.0
2.6
3.9
10.6
27.8
5.1
9.2
15.1
47.2
14.6
98.1
4.2
20.5
7.5
65.2
2.4
17.3
13.6
8.9
76.0
2.6
24.9
15.5
21.6
23.4
40.7
6.3
10.2
7.0
13.9
4.1
23.2
7.8
4.5
12.0
12.3
4.8
5.6
65.9
4.3
91.3
66.3
4.5
9.1
48.8
Mm
-)
5
-)
10
15
5
7
2
10
2
5
5
20
15
10
2
7
40
10
5
5
2
5
10
5
10
10
10
2
5
7
2
5
5
2
10
5
2
5
5
2
5
10
0
20
10
-)
10
10
Max
945
945
640
605
120
140
370
945
570
945
570
175
690
370
435
945
690
55
435
370
945
468
460
435
435
570
501
640
690
945
435
945
570
690
690
945
690
460
945
640
945
195
435
945
435
435
945
155
435
5
10
10
15
10
15
10
10
10
20
10
15
5
20
20
10
10
15
40
10
10
10
10
10
10
10
30
20
20
5
10
15
10
10
13
10
20
10
10
10
10
10
10
10
10
20
10
10
10
10
25
30
30
30
60
30
25
30
30
45
30
35
20
30
30
21
30
30
40
32
29
30
40
30
32
29
45
45
40
30
29
30
30
30
30
30
45
0
0
0
0
0
0
2
0
60
30
30
30
29
50
55
55
55
100
55
43
54
60
73
54
60
20
43
43
114
55
38
48
78
50
60
60
65
165
49
90
73
75
60
60
60
55
50
42
50
90
58
50
60
50
55
48
46
55
110
41
55
55
68
75
90
90
90
140
60
67
75
110
130
80
110
120
100
87
315
90
85
55
195
70
120
100
120
195
70
135
120
120
90
102
95
85
80
90
85
120
90
75
95
80
90
71
100
90
278
100
90
65
100
90
125
135
120
435
120
90
110
180
435
120
140
155
225
90
435
125
145
55
435
100
405
135
135
435
100
195
225
195
130
125
135
120
135
128
120
180
125
120
155
125
125
115
435
125
435
435
125
125
435
95
180
180
175
605
120
110
135
405
460
147
185
175
690
120
435
165
370
55
435
120
570
185
165
435
120
405
435
605
300
460
180
125
180
298
165
300
180
138
225
175
180
135
435
179
435
435
180
155
435
98
435
460
420
605
120
120
179
640
570
405
460
175
690
370
435
420
690
55
435
150
690
468
205
435
155
570
468
640
690
945
435
175
460
640
435
945
435
205
435
570
435
165
435
420
435
435
435
155
435
99
570
570
501
605
120
122
225
690
570
501
468
175
690
370
435
468
690
55
435
179
945
468
460
435
225
570
501
640
690
945
435
468
501
690
501
945
605
225
945
640
570
195
435
570
435
435
570
155
435
Exposure Factors Handbook
September 2011
Page
16-63
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-24. Time Spent (minutes/day) in Selected Vehicles and All
(continued)
Vehicles Combined, Doers Only
All Vehicles Combined
Percentiles
Category Population Group
All
Sex Male
Sex Female
Sex Refused
Age (years)
Age (years) 1 to 4
Age (years) 5 to 1 1
Age (years) 12 to 17
Age (years) 1 8 to 64
Age (years) >64
Race White
Race Black
Race Asian
Race Some Others
Race Hispanic
Race Refused
Hispanic No
Hispanic Yes
Hispanic DK
Hispanic Refused
Employment
Employment Full Time
Employment Part Time
Employment Not Employed
Employment Refused
Education
Education < High School
Education High School Graduate
Education < College
Education College Graduate
Education Post Graduate
Census Region Northeast
Census Region Midwest
Census Region South
Census Region West
Day Of Week Weekday
Day Of Week Weekend
Season Winter
Season Spring
Season Summer
Season Fall
Asthma No
Asthma Yes
Asthma DK
Angina No
Angina Yes
Angina DK
Bronchitis/Emphysema No
Bronchitis/Emphysema Yes
Bronchitis/Emphysema DK
= Indicates missing data.
DK = The respondent replied "don't know'
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
N
7,743
3,603
4,138
2
144
335
571
500
5,286
907
6,288
766
133
144
319
93
7,050
578
34
81
1,388
3,732
720
1,849
54
1,550
561
2,166
1,556
1,108
802
1,662
1,759
2,704
1,618
5,289
2,454
2,037
2,032
2,090
1,584
7,152
544
47
7,516
172
55
7,349
342
52
Mean
97.3
103.7
91.7
30.0
117.0
68.1
71.0
81.5
104.0
90.9
97.2
98.7
83.4
96.2
101.7
93.6
97.1
100.0
73.0
98.9
73.6
105.8
98.8
96.6
120.3
76.4
100.8
101.6
103.2
104.5
101.9
98.6
101.2
96.1
93.7
94.4
103.4
94.3
99.6
97.8
97.4
97.3
97.2
100.0
97.3
93.1
108.9
97.6
91.0
98.9
SD
104.9
119.7
89.8
14.1
129.1
75.5
77.6
79.8
111.1
93.9
107.2
91.3
74.9
94.0
110.4
90.1
104.8
109.0
68.3
95.3
77.8
116.2
95.0
99.5
108.6
78.9
120.2
107.6
110.1
109.5
108.7
106.6
114.6
97.7
103.7
101.4
111.9
101.4
110.5
103.8
103.7
104.6
110.8
95.2
105.2
93.1
99.7
106.1
79.3
93.8
SE
1.2
2.0
1.4
10.0
10.8
4.1
3.2
3.6
1.5
3.1
1.4
3.3
6.5
7.8
6.2
9.3
1.2
4.5
11.7
10.6
2.1
1.9
3.5
2.3
14.8
2.0
5.1
2.3
2.8
3.3
3.8
2.6
2.7
1.9
2.6
1.4
2.3
2.2
2.5
2.3
2.6
1.2
4.8
13.9
1.2
7.1
13.4
1.2
4.3
13.0
Min
1
1
1
20
5
1
1
1
1
4
1
2
5
3
2
10
1
2
5
10
i
4
2
1
10
1
5
1
2
4
4
1
1
1
2
1
1
1
1
1
1
1
4
10
1
8
10
1
2
5
Max
1,440
1,440
995
40
810
955
900
790
1,440
900
1,440
810
540
690
825
480
1,440
825
325
480
955
1,440
960
995
480
955
1,440
1,210
1,280
1,215
1,357
1,215
1,440
955
1,280
1,215
1,440
1,080
1,440
1,357
1,280
1,440
955
480
1,440
615
480
1,440
505
480
5
12
10
12
20
20
10
10
10
15
10
10
15
20
10
20
15
10
15
6
15
10
16
10
10
20
10
15
12
15
15
20
15
10
13
10
10
13
10
12
10
14
10
17
10
11
15
20
10
15
10
25
40
40
40
20
40
30
25
30
43
35
40
45
35
40
41
30
40
40
25
30
30
45
45
37
35
30
40
40
40
45
45
40
40
40
35
40
40
35
40
40
40
40
40
30
40
30
35
40
40
30
50
70
70
70
30
80
47
51
60
75
60
70
75
70
70
70
65
70
70
60
65
55
75
75
65
88
60
70
70
75
75
76
70
70
70
65
66
75
65
70
70
70
70
65
75
70
65
75
70
70
74
75
120
120
115
40
143
85
90
100
120
120
120
120
105
128
120
120
120
120
97
130
90
124
120
120
190
95
120
120
120
125
120
120
120
120
115
115
125
116
120
120
120
120
117
120
120
120
150
120
115
145
90
190
205
180
40
210
150
140
166
200
190
190
195
150
180
190
205
190
190
175
220
150
198
195
200
290
155
180
210
195
200
195
190
205
190
180
180
205
190
200
190
180
190
180
220
190
185
235
190
195
195
95
270
295
240
40
435
200
171
233
285
258
270
265
210
250
335
255
270
285
200
255
195
290
260
275
330
201
265
286
285
280
270
275
290
250
260
260
280
270
275
260
265
270
255
239
270
280
360
270
240
239
98
425
478
385
40
593
245
275
345
450
400
425
390
330
345
465
420
420
480
325
420
275
475
380
420
390
303
460
445
460
450
365
425
435
420
420
435
420
425
440
415
420
425
460
480
425
420
390
425
325
390
99
570
655
465
40
660
270
360
405
620
460
595
485
360
540
620
480
566
630
325
480
382
660
470
526
480
385
620
570
630
675
480
570
595
558
540
575
540
544
546
558
620
570
705
480
570
540
480
580
460
480
Page
16-64
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only, Children
<21 Years
1
Percentiles
2 5 10 25 50
75
90
95
98
99
Sleeping/Napping — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only
<21 Years (continued)
Age (years)
, Children
Percentiles
1
2 5 10
25 50
75
90
95
98
99
Outdoor Recreation — Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table
16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only, Children
<21 Years (continued)
Percentiles
1
2
5 10
Walking— Whole
Birth to <
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in
Selected Activities, Doers
Only
Sleeping/Napping
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
9,362
4,283
5,075
4
185
499
702
588
6,041
1,347
7,576
940
156
181
383
126
8,514
700
45
103
1,771
4,085
798
2,638
70
1,966
832
2,604
1,791
1,245
924
2,068
2,096
3,234
1,964
6,303
3,059
2,514
2,431
2,533
1,884
8,608
692
62
9,039
249
74
8,860
432
70
Mean
526.3
523.3
528.7
645.0
502.3
732.4
625.1
563.7
496.9
517.1
523.6
541.3
537.1
528.8
538.0
523.4
525.2
540.1
527.5
521.6
636.6
487.2
502.8
520.3
513.7
625.6
515.4
505.4
496.6
492.5
486.7
523.1
520.8
529.0
530.9
511.1
557.5
534.9
526.8
527.7
512.2
525.1
540.1
544.2
526.8
513.7
511.4
526.5
521.7
521.2
SD
134.4
135.2
133.7
123.7
125.4
124.3
100.7
110.8
123.0
117.5
129.5
162.7
118.1
142.3
148.9
143.7
133.2
147.1
139.3
138.9
128.5
118.9
117.4
125.5
136.5
134.0
135.7
123.0
119.9
117.6
110.4
133.7
127.6
135.7
140.0
131.8
134.4
134.7
130.5
139.5
131.1
133.6
143.6
141.0
134.2
137.7
146.3
134.3
138.5
131.9
SE
1.4
2.1
1.8
61.8
9.2
5.6
3.8
4.6
1.6
3 2
1.5
5.3
9.5
10.6
7.6
12.8
1.4
5.6
20.8
13.7
3.1
1.9
4.2
2.4
16.3
3.0
4.7
2.4
2.8
3.3
3.6
2.9
2.8
2.4
3 2
1.7
2.4
2.7
2.6
2.8
3.0
1.4
5.5
17.9
1.4
8.7
17.0
1.4
6.7
15.8
Mm
30
30
30
540
195
270
120
150
30
30
30
60
300
60
60
180
30
60
195
240
120
30
60
30
210
120
30
30
60
75
105
55
30
30
60
30
30
55
30
30
60
30
30
300
30
60
30
30
80
210
Max
1,430
1,295
1,430
780
908
1,320
1,110
1,015
1,420
1,430
1,430
1,415
920
905
1,125
1,140
1,430
1,125
842
930
1,320
1,420
1,005
1,430
930
1,420
1,317
1,430
1,350
1,404
1,295
1,420
1,215
1,430
1,404
1,430
1,420
1,404
1,175
1,430
1,420
1,430
1,404
1,035
1,420
1,430
930
1,430
1,110
930
5
345
330
350
540
330
540
480
395
330
345
350
315
345
300
315
330
345
320
345
330
440
325
330
345
320
420
300
330
315
330
345
345
330
345
345
330
360
355
345
330
330
345
330
330
345
300
300
345
300
300
25
445
435
450
540
420
655
570
484
420
450
445
424
468
420
450
420
445
450
420
420
555
420
435
450
420
540
435
420
420
420
420
435
440
450
450
420
480
450
445
435
430
445
450
465
445
445
420
445
420
450
50
510
510
510
630
480
720
630
550
480
510
510
530
540
525
540
510
510
540
515
510
630
480
495
510
490
628
510
495
480
480
480
510
510
510
510
495
540
520
510
510
505
510
538
535
510
510
510
510
510
510
75
600
600
600
750
555
810
680
630
555
570
600
630
600
630
630
600
600
630
659
590
705
540
570
590
570
699
585
570
565
540
540
600
598
600
600
570
630
600
600
600
570
600
618
600
600
595
600
600
600
600
90
690
690
690
780
655
900
725
705
630
660
690
738
690
720
720
720
690
720
690
720
802
628
645
660
697
790
670
659
630
629
615
690
690
699
690
670
720
700
690
699
660
690
715
720
690
660
720
690
705
690
95
760
765
750
780
745
930
780
750
705
720
750
823
735
769
765
780
750
778
710
780
860
685
720
720
780
855
750
720
690
690
660
760
745
765
769
745
780
780
750
765
735
750
780
780
760
735
780
760
765
745
98
850
860
840
780
865
1,005
840
810
780
780
840
940
840
810
870
870
855
843
842
865
930
770
780
800
900
926
860
780
779
775
725
860
840
855
862
840
870
870
840
840
840
840
900
930
855
795
840
850
840
840
99
925
925
925
780
900
1,110
875
900
868
860
900
1,020
870
842
930
930
925
915
842
870
975
840
860
885
930
975
900
840
845
900
800
930
870
925
940
920
925
930
900
930
900
915
945
1,035
925
845
930
924
930
930
Page
16-68
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only
(continued)
Eating or Drinking
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
8,627
3,979
4,644
4
157
492
680
538
5,464
1,296
7,049
808
148
168
345
109
7,861
639
41
86
1,695
3,684
715
2,472
61
1,867
758
2,363
1,612
1,160
867
1,916
1,928
2,960
1,823
5,813
2,814
2,332
2,222
2,352
1,721
7,937
635
55
8,318
243
66
8,169
397
61
Mean
74.9
75.8
74.1
60.0
75.3
93.5
68.5
55.9
71.9
91.7
77.0
59.9
80.4
66.0
68.7
74.2
75.6
68.3
60.4
68.9
72.2
70.6
72.2
83.9
71.0
70.9
72.3
74.9
73.9
78.5
82.8
78.3
75.8
71.4
76.0
71.2
82.5
76.1
76.3
73.5
73.3
75.2
71.4
69.3
74.6
85.0
75.7
74.7
80.7
67.0
SD
54.8
56.2
53.6
21.2
50.1
52.9
39.0
35.0
55.1
62.7
55.7
46.6
47.8
52.1
51.9
60.8
55.2
50.2
37.1
55.5
44.9
55.1
55.4
59.1
61.0
45.4
57.4
57.1
56.5
55.4
59.7
59.2
51.4
55.1
53.0
52.0
59.5
56.4
55.2
53.3
54.3
54.8
55.0
56.6
54.4
63.5
67.3
54.3
65.2
47.7
SE
0.6
0.9
0.8
10.6
4.0
2.4
1.5
1.5
0.7
1.7
0.7
1.6
3.9
4.0
2.8
5.8
0.6
2.0
5.8
6.0
1.1
0.9
2.1
1.2
7.8
1.1
2.1
1.2
1.4
1.6
2.0
1.4
1.2
1.0
1.2
0.7
1.1
1.2
1.2
1.1
1.3
0.6
2.2
7.6
0.6
4.1
8.3
0.6
3.3
6.1
Mm
1
1
2
30
10
2
5
2
1
5
1
2
2
7
2
8
1
2
5
8
2
1
2
2
8
2
2
1
2
1
2
1
1
2
2
1
2
2
1
1
2
1
2
8
1
2
5
1
2
8
Max
900
900
640
75
315
345
255
210
900
750
900
505
305
525
435
410
900
435
150
410
345
900
509
750
385
375
460
900
525
640
750
750
435
900
500
900
630
640
630
750
900
900
460
335
900
500
435
900
460
230
5
15
15
15
30
15
20
15
10
15
20
15
15
15
15
12
20
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
25
35
39
34
45
30
60
40
30
30
50
40
30
45
30
30
30
35
30
30
30
40
30
30
45
30
38
30
35
30
40
40
37
40
30
35
33
40
39
35
35
30
35
30
30
35
45
30
35
30
30
50
60
60
60
68
65
90
65
50
60
80
64
50
73
60
60
60
60
60
55
60
65
60
60
75
55
60
60
60
60
65
70
65
64
60
60
60
70
65
60
60
60
60
60
60
60
75
60
60
60
60
75
96
96
98
75
100
120
90
75
90
120
100
75
107
83
90
90
100
90
90
90
90
90
90
110
90
90
90
96
90
105
110
103
100
90
100
90
110
96
100
95
95
100
90
90
95
115
90
95
110
90
90
140
140
140
75
145
160
120
105
135
165
145
119
150
120
125
130
140
120
120
115
133
135
135
150
120
130
135
140
145
145
150
145
140
135
150
130
150
140
145
135
140
140
133
120
140
160
150
140
150
120
95
175
180
170
75
150
190
143
125
170
200
180
140
160
135
165
180
175
155
130
155
150
165
170
185
145
150
180
175
175
180
185
180
175
165
180
165
190
175
178
170
175
175
170
210
175
180
195
170
180
155
98
215
210
225
75
195
225
165
150
220
270
225
200
200
190
195
290
220
195
150
210
195
225
230
235
235
190
230
220
230
220
240
240
210
210
210
210
240
240
220
210
210
215
225
215
210
285
215
210
285
215
99
270
270
270
75
285
270
195
170
270
295
270
225
200
200
225
315
270
225
150
410
210
270
260
285
385
210
315
270
275
265
270
285
255
270
240
250
297
275
275
260
232
270
285
335
265
330
435
260
360
230
Exposure Factors Handbook
September 2011
Page
16-69
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued)
Working in a Main Job
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
3,259
1,733
1,526
80
3
10
38
2,993
135
2,630
343
57
56
125
48
2,980
221
12
46
47
2,679
395
112
26
108
217
1,045
795
627
467
721
755
1,142
641
2,788
471
864
791
910
694
3,042
195
22
3,192
44
23
3,120
116
23
Mean
475.9
492.3
457.3
472.4
16.7
150.4
293.2
484.8
366.1
477.5
466.6
464.1
477.4
465.9
492.1
475.4
481.5
529.6
468.5
257.9
504.4
364.6
270.9
513.6
343.0
473.5
482.0
475.6
484.5
483.0
476.0
477.0
478.2
470.4
487.9
405.2
475.8
473.0
477.2
477.7
477.0
453.4
523.2
475.7
472.1
507.4
476.5
447.0
535.2
SD
179.1
187.0
167.7
183.3
11.5
185.8
180.7
173.1
208.7
179.0
176.0
177.3
181.7
185.3
191.6
179.2
174.3
146.2
201.3
202.8
164.8
159.4
216.0
155.5
211.9
216.7
180.6
174.0
159.8
169.6
180.8
182.2
176.7
177.8
166.2
229.5
172.8
195.4
179.9
166.0
177.0
204.2
217.0
178.4
200.7
230.3
178.2
189.4
226.3
SE
3.1
4.5
4.3
20.5
6.7
58.8
29.3
3 2
18.0
3.5
9.5
23.5
24.3
16.6
277
3.3
11.7
42.2
29.7
29.6
3 2
8.0
20.4
30.5
20.4
14.7
5.6
6.2
6.4
7.8
6.7
6.6
5.2
7.0
3.1
10.6
5.9
6.9
6.0
6.3
3 2
14.6
46.3
3 2
30.3
48.0
3 2
17.6
47.2
Mm
1
1
2
5
10
2
5
1
5
1
5
5
45
2
50
1
2
295
10
2
1
5
4
170
2
4
1
2
5
1
1
2
1
5
i
2
5
i
i
2
1
5
170
1
10
80
1
5
170
Max
1,440
1,440
1,440
940
30
550
840
1,440
990
1,440
1,037
870
855
840
957
1,440
1,106
757
860
840
1,440
945
990
840
860
1,440
1,440
1,440
1,005
945
1,440
1,440
1,440
1,080
1,440
1,440
1,440
1,440
1,215
1,005
1,440
1,440
1,215
1,440
990
1,215
1,440
985
1,215
5
120
120
120
118
10
2
15
140
30
120
105
45
75
95
120
120
150
295
115
5
180
80
9
225
10
85
120
140
120
125
120
120
105
120
155
30
150
75
120
130
120
45
225
120
60
170
120
30
225
25
395
417
390
378
10
10
185
420
185
400
390
390
415
360
410
395
405
425
350
65
450
250
83
440
177
360
405
409
424
400
405
395
405
390
425
245
390
390
400
405
400
345
430
395
386
430
400
368
430
50
500
510
485
483
10
68
269
505
395
500
490
493
510
485
508
500
505
554
498
245
510
365
245
510
343
485
500
495
510
510
495
495
505
500
505
415
495
495
500
510
500
480
500
500
500
500
500
480
500
75
570
595
543
560
30
264
390
570
500
570
550
553
570
580
575
570
580
610
585
390
582
480
378
570
510
568
565
563
570
590
570
570
570
570
570
555
570
570
565
570
570
550
565
570
573
565
570
558
600
90
660
690
620
673
30
448
510
660
600
660
655
660
680
720
810
660
670
710
780
540
675
540
600
778
610
710
670
648
645
660
669
660
660
657
660
670
660
670
670
645
660
668
780
660
679
780
660
644
860
95
740
770
690
850
30
550
675
745
660
735
735
750
765
750
840
740
740
757
818
625
750
600
675
790
675
795
765
750
720
730
740
750
735
730
740
770
735
765
750
720
740
793
860
740
730
860
740
720
875
98
840
890
785
900
30
550
840
840
840
845
880
780
780
825
957
850
825
757
860
840
855
675
795
840
840
940
890
825
765
810
890
825
840
850
840
870
835
850
890
780
840
855
1,215
840
990
1,215
840
800
1,215
99
930
955
850
940
30
550
840
930
940
933
990
870
855
840
957
940
840
757
860
840
950
795
870
840
840
1,080
979
905
815
860
950
940
900
880
930
960
900
915
979
840
930
979
1,215
930
990
1,215
930
855
1,215
Page
16-70
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in
Selected Activities, Doers Only (continued)
Attending Full Time School
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
Whrte
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Trme
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Wrnter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
884
468
416
7
56
297
271
247
6
665
92
33
29
58
7
771
103
4
6
608
49
89
135
3
666
14
54
100
24
26
186
200
322
176
858
26
302
287
125
170
784
96
4
875
4
5
851
27
6
Mean
358.5
369.3
346.4
232.1
365.0
387.8
392.3
292 2
203.3
362.9
351.8
346.3
337.8
345.3
285.0
359.6
353.1
315.5
348.3
386.5
206.6
304.7
325.3
270.0
385.0
267.1
238.5
303.4
238.4
302.8
351.6
358.1
373.9
338.3
363.7
189.5
375.1
353.4
332.4
357.0
358.0
363.0
363.8
358.6
382.5
333.6
359.1
340.1
357.2
SD
130.3
123.2
137.1
148.1
199.2
98.0
85.0
154.6
147.4
128.5
129.6
156.0
148.1
124.0
157.0
130.8
126.4
167.8
140.6
107.3
133.6
134.8
161.0
147.2
107.9
129.3
141.1
170.6
145.9
144.1
127.0
123.9
139.7
120.5
126.0
158.4
118.5
133.7
142.1
132.8
130.7
127.9
162.6
130.5
87.7
140.5
130.4
132.7
121.5
SE
4.4
5.7
6.7
56.0
26.6
5.7
5.2
9.8
60.2
5.0
13.5
24.2
27.5
16.3
59.4
4.7
12.5
83.9
57.4
4.4
19.1
14.3
13.9
85.0
4.2
34.6
19.2
17.1
29.8
28.3
9.3
8.8
7.8
9.1
4.3
31.1
6.8
7.9
12.7
10.2
4.7
13.1
81.3
4.4
43.9
62.8
4.5
25.5
49.6
Mm
1
20
1
10
20
60
10
1
75
1
40
90
58
30
60
1
30
65
150
10
5
25
1
185
10
5
58
1
25
10
60
5
10
1
1
15
5
10
40
1
1
20
120
1
255
120
1
30
120
Max
840
840
710
495
710
645
605
840
480
825
710
840
553
565
440
840
630
416
445
710
502
695
840
440
710
415
785
840
565
535
825
645
840
630
840
465
695
840
630
785
840
695
450
840
455
460
840
605
440
5
95
120
75
10
30
170
200
60
75
107
70
120
70
85
60
100
85
65
150
165
15
90
60
185
160
5
60
60
30
95
120
88
60
120
120
20
150
90
70
120
95
95
120
95
255
120
95
60
120
25
300
320
263
180
173
360
375
180
120
310
287
225
212
260
150
300
269
221
185
361
115
210
215
185
360
175
125
185
135
210
268
308
330
263
310
60
330
290
217
285
295
334
280
300
330
270
300
305
350
50
390
390
385
210
428
390
405
289
153
392
388
365
360
378
290
390
385
391
435
400
180
295
340
440
400
310
212
273
200
300
375
393
405
375
390
120
395
390
375
380
390
390
443
390
410
378
390
365
397
75
435
435
430
320
530
435
435
400
240
435
433
435
445
430
440
435
425
410
440
440
305
395
420
440
440
357
330
415
360
461
420
425
450
410
435
300
440
430
425
430
435
428
448
435
435
440
435
435
440
90
483
485
480
495
595
485
460
480
480
485
465
500
502
480
440
483
483
415
445
485
430
480
500
440
485
385
400
526
430
500
483
470
500
465
485
460
495
475
470
510
485
475
450
483
455
460
485
450
440
95
550
555
535
495
628
555
485
535
480
550
526
565
540
510
440
550
510
415
445
550
461
500
605
440
550
415
480
614
460
502
520
528
565
540
550
465
550
500
550
565
550
540
450
550
455
460
550
460
440
98
600
595
600
495
665
600
510
645
480
600
645
840
553
510
440
600
595
415
445
595
502
585
785
440
595
415
480
760
565
535
600
578
625
555
600
465
612
570
600
605
595
645
450
600
455
460
600
605
440
99
640
645
628
495
710
630
555
785
480
630
710
840
553
565
440
645
600
415
445
625
502
695
825
440
625
415
785
833
565
535
785
602
645
600
640
465
640
710
600
645
630
695
450
640
455
460
640
605
440
Exposure Factors Handbook
September 2011
Page
16-71
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day)
in Selected Activities,
Doers Only (continued)
Outdoor Recreation
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
253
140
112
1
2
13
21
27
158
32
225
16
3
2
4
3
238
12
3
60
104
19
68
2
64
22
59
54
31
23
52
54
84
63
129
124
31
75
102
45
232
19
2
245
6
2
238
13
2
Mean
211.2
231.8
183.7
420.0
337.5
166.5
206.1
155.1
223.6
211.1
209.8
233.9
203.3
327.5
77.5
308.3
211.8
175.5
308.3
177.1
210.7
205.3
244.4
187.5
176.7
259.4
238.2
218.1
224.7
157.6
189.6
212.1
217.3
220.3
197.2
225.8
196.6
198.9
228.2
203.5
208.2
250.2
187.5
206.8
399.2
187.5
212.2
196.3
187.5
SD
185.5
207.4
150.2
201.5
177.1
156.2
128.3
193.0
206.6
182.7
231.3
262.2
130.8
53.9
209.4
187.1
149.1
209.4
150.0
153.4
204.0
245.0
10.6
145.3
178.0
229.0
172.2
193.1
178.2
160.9
228.4
175.3
179.7
195.3
174.3
165.5
161.7
204.2
193.8
187.7
166.6
10.6
184.9
151.2
10.6
189.2
122.2
10.6
SE
11.7
17.5
14.2
142.5
49.1
34.1
24.7
15.4
36.5
12.2
57.8
151.4
92.5
27.0
120.9
12.1
43.0
120.9
19.4
15.0
46.8
29.7
7.5
18.2
37.9
29.8
23.4
34.7
37.2
22.3
31.1
19.1
22.6
17.2
15.6
29.7
18.7
20.2
28.9
12.3
38.2
7.5
11.8
61.7
7.5
12.3
33.9
7.5
Mm
5
5
5
420
195
15
30
5
5
5
5
5
30
235
20
180
5
15
180
5
5
30
5
180
5
5
15
5
20
5
5
5
5
10
5
5
5
5
5
5
5
15
180
5
285
180
5
5
180
Max
1,440
1,440
645
420
480
630
585
465
1,440
735
1,440
690
505
420
150
550
1,440
511
550
630
670
690
1,440
195
630
600
1,440
690
690
735
690
1,440
645
690
1,440
690
585
690
1,440
735
1,440
570
195
1,440
690
195
1,440
370
195
5
20
18
20
420
195
15
60
5
30
5
20
5
30
235
20
180
20
15
180
13
30
30
15
180
15
30
20
25
30
10
30
20
15
30
15
20
5
25
30
20
20
15
180
20
285
180
20
5
180
25
60
68
60
420
195
30
90
60
80
30
60
43
30
235
43
180
60
70
180
60
83
60
60
180
60
105
90
65
60
50
60
60
63
75
60
85
60
75
75
60
60
80
180
60
310
180
60
117
180
50
165
177
150
420
338
130
165
135
173
171
165
150
75
328
70
195
165
150
195
148
180
150
180
1 88
153
248
175
173
150
80
163
178
150
165
150
180
165
180
180
120
159
255
188
160
345
1 88
165
160
1 88
75
300
330
255
420
480
180
245
225
310
375
300
450
505
420
113
550
300
255
550
230
294
180
375
195
225
380
310
345
325
200
232
280
348
280
275
310
280
270
325
330
294
350
195
288
420
195
300
310
195
90
480
503
380
420
480
370
360
420
505
495
460
585
505
420
150
550
480
340
550
395
419
570
525
195
370
525
511
460
505
370
370
419
495
545
465
480
440
465
459
505
480
525
195
480
690
195
495
340
195
95
574
600
525
420
480
630
574
420
585
600
570
690
505
420
150
550
585
511
550
520
511
690
690
195
465
600
670
550
645
480
574
600
525
585
525
600
550
545
585
574
585
570
195
570
690
195
585
370
195
98
670
690
585
420
480
630
585
465
690
735
670
690
505
420
150
550
690
511
550
585
600
690
735
195
585
600
690
570
690
735
670
735
600
690
670
690
585
670
690
735
690
570
195
670
690
195
690
370
195
99
690
735
630
420
480
630
585
465
690
735
690
690
505
420
150
550
690
511
550
630
645
690
1,440
195
630
600
1,440
690
690
735
690
1,440
645
690
735
690
585
690
690
735
690
570
195
690
690
195
690
370
195
Page
16-72
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities,
Doers Only (continued)
Active Sport
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
-
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,384
753
629
-)
23
105
247
215
642
152
1,139
109
30
35
59
12
1,250
120
4
10
561
375
87
352
9
610
86
233
178
165
112
333
254
479
318
902
482
316
423
425
220
1,266
105
13
1,343
33
8
1,331
43
10
Mean
124.0
136.8
108.6
142.5
108.7
115.8
148.9
137.5
120.3
88.0
126.0
113.4
89.9
135.4
116.3
120.0
124.5
121.2
113.8
102.0
137.1
117.6
116.2
112.5
99.4
137.7
101.0
116.8
115.8
116.2
106.4
132.0
116.9
119.5
128.1
115.5
139.9
115.6
130.8
129.5
112.3
122.5
144.8
105.0
125.5
72.1
86.9
124.1
130.0
84.0
SD
112.8
120.8
100.6
38.9
78.6
98.9
126.6
124.5
110.4
80.2
116.2
96.8
79.2
112.2
91.3
86.6
113.5
110.8
57.5
72.1
120.8
107.3
87.6
110.0
77.2
121.2
99.7
116.8
100.3
97.9
97.9
129.1
101.9
108.7
108.8
97.8
135.2
115.2
105.0
115.1
118.3
109.6
145.8
110.4
113.6
74.0
41.1
113.2
112.7
39.8
SE
3.0
4.4
4.0
27.5
16.4
9.6
8.1
8.5
4.4
6.5
3.4
9.3
14.5
19.0
11.9
25.0
3.2
10.1
28.8
22.8
5.1
5.5
9.4
5.9
25.7
4.9
10.8
7.7
7.5
7.6
9.2
7.1
6.4
5.0
6.1
3.3
6.2
6.5
5.1
5.6
8.0
3.1
14.2
30.6
3.1
12.9
14.5
3.1
17.2
12.6
Mm
1
1
1
115
5
10
2
5
i
i
i
5
5
15
i
40
1
1
60
40
2
5
1
1
30
2
10
1
1
1
5
i
5
1
1
1
1
1
5
i
i
i
i
30
1
5
40
1
10
40
Max
1,130
1,130
1,065
170
290
630
975
1,065
1,130
380
1,130
440
310
553
520
300
1,130
630
185
290
1,065
1,130
450
600
280
1,065
570
1,130
525
600
375
1,130
570
975
625
650
1,130
1,065
650
625
1,130
1,130
1,065
450
1,130
330
155
1,130
553
155
5
15
20
15
115
30
30
20
15
15
15
15
10
10
20
15
40
15
15
60
40
20
20
15
10
30
20
15
20
15
15
10
15
18
15
25
15
20
15
30
15
15
15
15
30
15
5
40
15
30
40
25
50
60
38
115
40
45
60
60
45
30
50
45
30
60
45
60
45
50
68
60
60
45
60
30
45
60
30
45
45
50
40
60
45
45
55
45
59
45
60
45
43
45
60
60
50
30
60
50
45
60
50
90
105
75
143
90
90
120
110
90
60
90
86
60
105
115
95
90
90
105
83
110
90
95
70
90
110
60
85
90
90
60
100
90
90
93
90
100
85
105
95
78
90
110
60
90
50
75
90
110
75
75
165
180
150
170
155
159
188
180
160
120
165
150
145
195
145
130
165
148
160
105
180
155
160
150
120
180
135
150
160
150
143
170
150
160
175
150
180
155
175
178
144
162
180
90
165
60
115
165
165
105
90
267
285
240
170
220
250
320
265
250
220
270
240
215
270
240
290
270
240
185
215
285
240
235
270
280
285
225
240
270
250
270
275
255
265
295
240
300
240
270
290
240
266
300
165
270
180
155
267
270
148
95
330
375
300
170
225
330
390
375
330
285
340
332
235
330
305
300
330
335
185
290
370
305
285
330
280
370
270
300
340
310
330
345
315
330
330
300
380
305
330
375
290
330
390
450
332
275
155
330
340
155
98
435
500
370
170
290
345
510
470
450
315
452
430
310
553
345
300
435
520
185
290
452
380
355
475
280
470
510
420
418
380
360
485
430
410
500
395
500
370
435
462
460
430
553
450
440
330
155
435
553
155
99
525
558
435
170
290
390
558
520
525
330
530
435
310
553
520
300
515
553
185
290
558
525
450
520
280
558
570
530
475
450
375
558
440
462
525
485
565
475
515
530
565
515
565
450
525
330
155
520
553
155
Exposure Factors Handbook
September 2011
Page
16-73
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers
Only
(continued)
Exercise
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
564
262
302
10
11
26
35
407
75
480
34
10
14
19
7
516
38
3
7
72
300
50
139
3
83
21
124
104
110
122
130
101
177
156
426
138
150
140
192
82
523
37
4
553
7
4
542
17
5
Mean
77.4
84.7
71.1
76.5
127.3
132.5
67.8
77.6
54.9
78.0
74.7
46.3
80.2
63.0
128.6
76.9
76.6
65.0
128.6
99.0
72.7
86.0
72.7
113.3
102.0
58.2
81.0
80.9
73.6
60.9
88.4
63.6
75.3
79.6
73.1
90.8
67.4
74.9
93.2
63.3
76.6
78.2
175.0
77.3
27.3
188.8
77.1
64.6
157.0
SD
70.4
75.8
64.9
74.0
187.2
126.3
41.6
63.6
44.5
71.5
44.7
25.0
73.9
60.7
130.5
70.1
59.5
69.5
130.5
111.6
55.6
83.6
63.4
135.8
111.0
66.1
63.0
70.2
62.5
38.4
77.6
44.3
71.6
75.3
63.9
86.6
49.9
55.4
91.3
63.3
70.2
51.5
167.0
69.4
19.6
150.4
69.5
60.6
149.6
SE
3.0
4.7
3.7
23.4
56.4
24.8
7.0
3.2
5.1
3.3
7.7
7.9
19.8
13.9
49.3
3.1
9.7
40.1
49.3
13.2
3.2
11.8
5.4
78.4
12.2
14.4
5.7
6.9
6.0
3.5
6.8
4.4
5.4
6.0
3.1
7.4
4.1
4.7
6.6
7.0
3.1
8.5
83.5
2.9
7.4
75.2
3.0
14.7
66.9
Mm
4
5
4
15
15
15
15
4
6
4
15
15
30
15
30
4
15
20
30
15
5
10
4
30
15
10
4
15
5
5
10
10
5
4
4
6
8
10
5
4
4
20
10
4
6
60
4
10
15
Max
670
670
525
270
670
525
180
480
195
670
250
95
275
265
360
670
265
145
360
670
460
420
480
270
670
300
298
480
460
240
450
300
525
670
670
525
285
360
670
460
670
275
360
670
60
360
670
275
360
5
15
20
15
15
15
25
20
20
10
15
15
15
30
15
30
15
20
20
30
20
20
20
10
30
25
10
15
20
20
15
15
15
15
20
15
15
15
18
20
15
15
20
10
15
6
60
15
10
15
25
30
30
30
30
30
60
30
30
25
0
5
0
0
0
55
30
30
20
55
30
30
0
0
0
0
8
0
30
30
30
30
30
30
0
0
0
0
0
0
30
30
45
35
30
10
63
30
30
60
50
60
60
60
60
60
90
60
60
40
60
60
42
48
45
60
60
60
30
60
60
60
60
60
40
60
30
60
60
60
60
60
60
60
60
60
60
60
60
63
45
60
65
165
60
25
168
60
50
80
75
100
117
90
90
150
180
100
100
70
100
105
60
90
60
270
99
110
145
270
120
90
92
90
270
120
60
115
113
98
80
120
89
90
104
90
120
90
90
120
75
100
100
315
100
45
315
100
63
270
90
150
165
125
188
160
275
120
145
120
150
120
83
179
160
360
145
160
145
360
180
130
168
135
270
205
90
179
150
130
110
200
115
150
130
130
200
128
148
180
120
150
120
360
145
60
360
145
120
360
95
195
205
175
270
670
450
150
185
150
194
130
95
275
265
360
193
250
145
360
275
180
300
195
270
275
165
205
170
180
127
240
120
185
183
180
265
175
181
250
135
185
200
360
193
60
360
185
275
360
98
275
285
265
270
670
525
180
265
193
285
250
95
275
265
360
275
265
145
360
525
240
390
240
270
525
300
250
240
285
165
297
170
298
270
240
420
213
220
450
300
265
275
360
265
60
360
265
275
360
99
420
450
360
270
670
525
180
300
195
450
250
95
275
265
360
420
265
145
360
670
291
420
265
270
670
300
265
420
297
185
420
215
480
460
298
460
240
298
525
460
420
275
360
420
60
360
420
275
360
Page
16-74
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in
Selected Activities, Doers Only (continued)
Walking
Percentiles
Category
All
Sex
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
Refused
-
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,639
755
883
1
38
58
155
223
944
221
1,289
175
36
30
88
21
1,467
144
10
18
431
561
153
482
12
472
138
366
288
210
165
507
321
423
388
1,182
457
412
459
475
293
1,504
120
15
1,578
44
17
1,553
67
19
Mean
29.7
32.5
27.3
20.0
29.5
24.3
18.2
25.8
31.8
33.8
29.6
34.8
26.6
23.8
23.1
33.2
29.9
26.8
30.2
35.7
22.8
31.0
26.9
35.5
18.4
22.7
42.7
29.3
32.5
29.8
34.6
34.9
29.3
25.0
28.2
29.3
30.7
32.3
28.9
26.6
32.2
29.6
29.7
36.2
29.5
29.0
46.6
29.7
27.0
35.4
SD
41.6
48.3
34.8
23.7
26.3
21.0
32.4
45.0
49.3
43.7
39.7
24.7
21.2
21.1
33.0
41.0
48.7
28.8
34.8
28.0
43.8
37.1
49.4
13.5
27.6
71.9
41.6
39.3
38.8
44.6
45.3
46.9
37.7
35.0
39.2
47.4
47.7
41.5
31.3
46.7
42.0
38.3
27.8
41.5
36.1
63.1
42.1
31.9
31.4
SE Mm
1.0 1
1.8 1
1.2 1
20
3.9 1
3.5 1
1.7 1
2.2 1
1.5 1
3.3 1
1.2 1
3.0 1
4.1 1
3.9 1
2.2 1
7.2 4
1.1 1
4.1 1
9.1 2
8.2 8
1.3 1
1.8 1
3.0 1
2.3 1
3.9 5
1.3 1
6.1 1
2.2 1
2.3 1
2.7 1
3.5 1
2.0 1
2.6 1
1.8 1
1.8 1
1.1 1
2.2 1
2.4 1
1.9 1
1.4 1
2.7 1
1.1 1
3.5 1
7.2 5
1.0 1
5.4 2
15.3 5
1.1 1
3.9 1
7.2 3
Max
540
540
360
20
100
160
170
190
410
540
540
250
100
60
100
150
410
540
80
150
190
365
295
540
55
190
540
410
295
300
360
365
540
410
285
540
410
365
540
270
410
540
250
90
540
150
270
540
165
110
5 25
2 6
2 7
2 6
20 20
2 10
2 10
1 5
2 6
2 6
2 10
2 6
2 10
1 10
1 6
2 6
8 15
2 6
2 6
2 10
8 15
2 5
2 7
2 5
2 10
5 10
2 5
3 7
2 5
2 10
2 8
2 10
2 10
2 6
2 5
2 8
2 7
2 5
2 6
2 6
2 6
2 8
2 6
2 5
5 10
2 6
4 6
5 10
2 6
2 5
3 10
50
16
20
15
20
25
15
10
15
19
20
15
20
20
17
15
20
16
15
18
25
13
16
15
20
17
13
20
18
20
19
20
20
15
10
15
18
15
20
16
15
20
16
15
30
16
15
30
16
16
30
75
39
40
35
20
40
35
25
30
40
45
35
50
30
43
37
40
40
35
55
55
30
40
35
50
20
30
50
35
45
40
45
45
31
30
40
40
35
39
35
35
45
36
40
60
38
36
60
38
40
60
90
65
70
60
20
60
60
40
60
70
73
65
75
60
60
50
65
65
60
78
65
55
70
60
75
30
55
115
65
75
60
80
75
60
60
60
65
60
75
60
60
61
65
70
75
65
60
90
65
60
90
95
95
100
94
20
80
60
60
100
110
95
100
125
78
60
60
65
100
70
80
150
65
100
92
120
55
65
145
100
100
90
95
107
105
80
90
92
120
120
90
85
105
95
118
90
95
115
270
95
90
110
98
151
170
140
20
100
70
65
135
171
155
160
160
100
60
92
150
155
100
80
150
131
180
135
150
55
130
360
150
160
140
180
170
160
135
140
145
171
180
146
123
155
152
135
90
151
150
270
151
130
110
99
190
270
171
20
100
160
100
151
250
180
225
194
100
60
100
150
194
135
80
150
151
250
165
250
55
151
365
240
180
225
200
250
180
171
180
180
200
250
180
160
295
190
150
90
190
150
270
194
165
110
Exposure Factors Handbook
September 2011
Page
16-75
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only
(continued)
Housekeeping3
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
18 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,943
370
1,573
47
11
54
72
1,316
443
1,649
137
32
26
71
28
1,771
134
15
23
138
673
193
925
14
171
246
677
433
245
171
464
413
648
418
1,316
627
470
451
563
459
1,789
140
14
1,853
75
15
1,816
107
20
Mean
118.8
109.4
121.0
146.0
74.1
42.9
78.1
120.4
128.2
119.1
116.6
98.8
82.4
112.6
189.3
117.4
121.7
146.9
191.1
65.6
106.6
124.7
132.7
236.8
82.2
140.7
125.1
112.9
107.3
130.8
119.2
117.9
119.9
117.7
113.2
130.6
111.4
122.6
111.8
131.3
118.5
115.7
189.3
117.7
122.9
234.7
118.1
118.7
188.5
SD
113.4
116.5
112.5
121.3
69.4
34.1
75.5
113.7
118.9
112.2
109.4
100.5
56.4
129.3
176.2
110.6
129.6
127.9
180.3
68.8
102.4
117.5
119.4
208.2
96.9
125.4
120.5
100.1
102.2
118.0
116.4
112.6
116.2
106.6
111.9
115.6
100.6
114.0
114.5
122.4
112.1
115.8
208.6
112.3
103.8
204.0
112.9
102.9
176.4
SE
2.6
6.1
2.8
17.7
20.9
4.6
8.9
3.1
5.7
2.8
9.3
17.8
11.1
15.3
33.3
2.6
11.2
33.0
37.6
5.9
3.9
8.5
3.9
55.6
7.4
8.0
4.6
4.8
6.5
9.0
5.4
5.5
4.6
5.2
3.1
4.6
4.6
5.4
4.8
5.7
2.6
9.8
55.7
2.6
12.0
52.7
2.7
10.0
39.5
Mm
1
1
1
10
10
1
1
1
3
1
1
15
5
5
10
1
5
10
10
1
1
1
3
10
1
3
2
1
1
5
2
1
1
5
i
i
i
3
1
1
1
5
10
1
5
10
1
5
5
Max
810
810
790
480
270
180
300
810
790
790
490
425
210
660
810
790
660
510
810
375
655
660
790
810
810
715
790
570
585
655
790
715
810
720
790
810
810
720
690
790
790
690
810
790
394
810
790
480
810
5
10
10
15
10
10
5
5
15
10
10
5
15
15
8
20
10
10
10
20
5
10
15
15
10
5
10
15
10
15
15
10
10
10
15
10
15
10
15
10
15
10
10
10
13
5
10
10
10
8
25
40
30
45
45
40
20
28
40
55
40
30
30
40
30
53
40
35
30
45
25
30
45
55
120
30
60
45
40
30
60
35
34
40
40
30
55
45
40
30
45
40
37
45
40
30
120
40
30
85
50
90
60
90
115
60
30
60
90
90
90
90
60
60
60
148
90
85
120
150
45
70
90
105
183
45
120
90
90
60
90
90
88
90
90
75
90
85
90
75
90
90
67
123
90
90
240
90
90
155
75
165
150
165
240
90
53
105
165
180
165
150
128
115
135
248
165
135
210
255
80
145
180
180
300
105
180
175
150
150
180
165
165
165
165
150
180
160
180
135
180
165
150
255
160
210
300
160
180
240
90
270
270
270
300
90
80
210
270
270
265
300
265
185
270
420
265
270
240
390
180
240
270
295
430
220
300
270
240
240
280
245
255
285
255
255
290
240
270
255
300
270
278
340
265
270
480
270
255
320
95
345
360
345
375
270
120
240
360
345
340
358
345
190
465
465
335
470
510
420
240
325
390
370
810
270
400
375
320
328
390
330
345
370
340
330
370
290
360
365
390
345
378
810
345
320
810
355
290
575
98
465
425
465
480
270
150
285
465
540
465
480
425
210
518
810
425
540
510
810
285
413
480
484
810
300
540
490
420
405
495
480
480
435
420
470
435
390
465
465
480
465
470
810
465
370
810
465
465
810
99
540
560
540
480
270
180
300
525
570
540
484
425
210
660
810
525
658
510
810
300
490
540
600
810
375
660
610
470
465
540
655
525
540
470
550
525
480
540
610
560
540
480
810
540
394
810
540
470
810
Page
16-76
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers
Only
(continued)
Yardwork/Maintenanceb
Percentiles
Category
All
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Race
Hispanic
Hispanic
Hispanic
Hispanic
Employment
Employment
Employment
Employment
Employment
Education
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day Of Week
Day Of Week
Season
Season
Season
Season
Asthma
Asthma
Asthma
Angina
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
Refused
No
Yes
DK
Refused
Full Time
Part Time
Not Employed
Refused
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
DK
No
Yes
DK
No
Yes
DK
N
1,414
804
610
20
12
26
54
1,015
287
1,249
77
13
26
37
12
1,331
65
8
10
92
664
121
526
11
105
160
465
305
211
168
291
314
438
371
878
536
289
438
458
229
1,311
98
5
1,360
42
12
1,352
57
5
Mean
147.7
174.8
111.9
181.9
93.2
96.2
116.0
150.2
149.3
151.5
114.5
140.0
117.2
102.1
177.1
148.7
106.2
248.8
203.5
106.8
146.7
134.5
157.8
211.6
113.5
158.5
151.4
152.8
145.4
142.2
140.5
145.1
152.7
149.6
140.9
158.9
139.4
162.2
137.9
150.0
147.0
149.3
312.0
145.3
192.6
257.1
148.5
114.7
312.0
SD
148.2
160.2
122.0
170.3
80.8
85.5
116.8
154.5
133.8
150.2
127.1
150.1
110.6
113.5
190.8
148.0
127.4
206.5
200.1
101.8
155.5
130.8
147.0
198.7
113.9
164.8
147.0
157.0
138.8
147.8
139.6
143.2
156.4
149.3
140.8
159.2
151.7
150.5
140.3
153.4
147.1
155.8
230.0
145.1
203.4
216.7
148.5
121.4
230.0
SE
3.9
5.6
4.9
38.1
23.3
16.8
15.9
4.8
7.9
4.3
14.5
41.6
21.7
18.7
55.1
4.1
15.8
73.0
63.3
10.6
6.0
11.9
6.4
59.9
11.1
13.0
6.8
9.0
9.6
11.4
8.2
8.1
7.5
7.8
4.8
6.9
8.9
7.2
6.6
10.1
4.1
15.7
102.9
3.9
31.4
62.6
4.0
16.1
102.9
Mm
1
2
1
5
5
5
3
1
2
1
2
5
5
5
30
1
5
5
60
3
1
2
2
2
2
2
3
2
1
2
3
0
2
1
1
2
1
3
2
2
1
5
60
1
5
5
1
5
60
Max
1,080
1,080
900
600
285
330
505
1,080
810
1,080
750
425
380
565
600
1,080
575
585
600
505
1,080
554
810
600
600
900
840
1,080
625
690
840
780
1,080
750
810
1,080
690
900
1,080
720
1,080
670
600
900
1,080
600
1,080
460
600
5
5
10
5
10
5
5
5
5
10
5
5
5
5
5
30
5
5
5
60
5
5
5
10
2
5
8
5
5
5
5
5
10
5
5
5
5
5
10
5
5
5
5
60
5
15
5
5
5
60
25
45
60
30
60
30
39
30
35
60
45
20
15
30
20
60
45
20
90
60
32
35
30
60
60
33
45
50
45
40
30
40
55
45
40
40
50
30
60
40
40
45
30
120
45
60
53
45
30
120
50
100
120
75
116
83
60
90
100
120
105
65
85
88
60
98
105
60
190
120
77
90
90
120
120
79
111
110
95
105
90
90
95
111
104
93
117
75
120
90
97
100
90
300
100
143
233
105
60
300
75
205
250
145
240
133
120
150
210
205
210
165
210
178
120
215
209
120
420
300
148
203
200
220
375
150
210
210
210
225
180
200
195
205
210
190
225
195
220
180
210
200
210
480
200
255
473
205
135
480
90
360
415
278
468
178
210
285
360
330
360
285
360
290
255
510
360
255
585
555
240
360
317
370
465
285
413
345
360
330
340
330
360
375
350
345
380
360
360
310
390
355
445
600
355
465
510
360
340
600
95
470
510
360
570
285
300
385
480
420
480
355
425
360
300
600
465
300
585
600
330
490
390
480
600
360
493
460
473
465
470
450
445
480
480
460
510
480
480
440
480
465
480
600
465
485
600
470
375
600
98
570
600
465
600
285
330
450
585
525
575
405
425
380
565
600
570
565
585
600
450
575
490
595
600
450
595
575
600
525
570
525
560
585
575
560
600
565
570
555
600
570
670
600
570
1,080
600
570
405
600
99
655
670
510
600
285
330
505
670
630
660
750
425
380
565
600
660
575
585
600
505
690
495
655
600
505
810
690
630
533
630
600
655
635
690
625
690
600
700
630
655
635
670
600
655
1,080
600
660
460
600
Exposure Factors Handbook
September 2011
Page
16-77
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued)
= Indicates missing data.
DK = The respondent replied "don't know".
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Includes cleaning house, other repairs, and household work.
Includes car repair services, other repairs services, outdoor cleaning, car repair maintenance, other repairs, plant care, other household work, domestic
crafts, domestic arts.
Source: U.S. EPA, 1996.
Page Exposure Factors Handbook
16-78 September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-27. Number of Showers Taken per Day, by Children
Birth to <
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-28. Time Spent (minutes)
Age (years)
N
Mean Mm
1
Bathing, Showering, and in Bathroom Immediately After Bathing
Showering, Children <21 Years
Percentiles
2 5
10 25 50
75 90
95
98
99
and
Max
Duration of Bath (minutes)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table
16-28. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately
Showering, Children <21 Years (continued)
1 2 5 10
After Bathing and
Percentiles
25
50
75
90
95
98
99
Sum of Shower Duration and Time Spent in Shower Room Immediately Following Shower (minutes)
Birth to <
lto<
2to<
3to<
6to<
11 to
16 to
N
Min
Max
=2
=3
i.6
64
Mean No. Baths/Showers
per Daya
1.27
1.14
Median Time Spent in
Shower/Bathb
(minutes/bath)
13.5
15.0
Time Spent in
Shower/Bathc
(minutes/day)
17.1
17.1
For additional statistics see Table 16-30. Calculated by averaging the reported number of
baths/showers taken per day (truncated at 11), by the number of respondents. Respondents
responding Missing and Don't Know were excluded (N = 5).
For additional statistics see Table 16-31.
Calculated by multiplying the mean number of showers/baths per day by the median time
spent in shower/bath.
Source: U.S. EPA, 1996.
Exposure Factors Handbook
September 2011
Page
16-81
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-30. Number of Times Respondent Took Shower or Bathed, Doers Only
Group Name
All
Sex
Male
Female
Refused
Age (years)
-
1 to 4
5 to 11
12tol7
1 8 to 64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-
Full Time
Part Time
Not Employed
Refused
Education
-
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day Of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
N
3,594
1,720
1,872
2
64
41
140
270
2,650
429
2,911
349
64
65
162
43
3,269
111
17
31
439
1,838
328
967
22
515
297
1,042
772
576
392
828
756
1,246
764
2,481
1,113
941
889
1,003
761
3,312
261
21
3,481
261
22
2
-
2
-
-
-
-
-
1
1
2
-
-
-
-
-
2
-
-
-
-
1
1
-
-
-
-
1
1
-
-
-
-
1
1
-
2
-
-
-
2
2
-
-
1
-
-
1
2,747
1,259
1,486
2
46
30
112
199
1,983
377
2,323
199
49
40
103
33
2,521
190
13
23
330
1,361
261
780
15
382
240
789
589
434
313
622
621
893
611
1,889
858
732
674
735
606
2,543
189
15
2,653
189
17
2
802
436
366
-
17
9
26
65
636
49
562
140
14
23
56
7
711
81
4
6
99
454
65
177
7
121
54
243
176
133
75
196
131
334
141
563
239
198
205
254
145
730
67
5
730
67
4
3
30
21
9
-
-
1
1
6
21
1
17
7
1
2
2
1
24
5
-
1
8
17
-
5
-
9
2
5
4
7
3
7
3
14
6
17
13
9
7
10
4
25
5
-
25
5
-
4 5 8 10 11+
11114
1 ... 1
1113
.
.
.
.
.
3
1
1 - - 4
1 - 1 - -
.
.
1
.
111-4
1
.
.
.
1 2
1 ...
1-1-2
.
.
1
11-1
1
1 ... 1
1
.
.
1 - - - 3
1111
11114
.
1
1
1 - - - 2
11-1
11114
.
.
11114
.
.
DK
5
2
3
-
1
1
1
-
2
-
2
1
-
-
-
2
4
-
-
1
2
2
-
1
-
3
-
1
1
-
-
3
1
-
1
4
1
1
2
1
1
4
-
1
4
-
1
Page
16-82
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-30. Number of Times Respondent Took Shower or Bathed, Doers Only
(tontmued)
Group Name N
Bronchitis
No
Yes
DK
DK
Refused
N
SD
SE
Mm
Max
Source:
Emphysema
3,419 2 2,620 758
154 - 112 39
21 - 15 5
= Indicates missing data.
= The respondent replied "don't know".
= Refused data.
= Doer sample size.
= Standard deviation.
= Standard error.
= Minimum number of minutes.
= Maximum number of minutes.
U.S. EPA, 1996.
3 4 5 8 10 11+ DK
27 1 1 1 1 4 4
3
1
Exposure Factors Handbook
September 2011
Page
16-83
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-31. Time Spent (minutes/day) Bathing and Showering, Doers Only a
Percentiles
Group Name Group Code
All
Sex Male
Sex Female
Sex Refused
Age (years)
Age (years) 1 to 4
Age (years) 5 to 1 1
Age (years) 12 to 17
Age (years) 1 8 to 64
Age (years) >64
Race White
Race Black
Race Asian
Race Some Others
Race Hispanic
Race Refused
Hispanic No
Hispanic Yes
Hispanic DK
Hispanic Refused
Employment
Employment Full Time
Employment Part Time
Employment Not Employed
Employment Refused
Education
Education < High School
Education High School Graduate
Education < College
Education College Graduate
Education Post Graduate
Census Region Northeast
Census Region Midwest
Census Region South
Census Region West
Day Of Week Weekday
Day Of Week Weekend
Season Winter
Season Spring
Season Summer
Season Fall
Asthma No
Asthma Yes
Asthma DK
Angina No
Angina Yes
Angina DK
Bronchitis/Emphysema No
Bronchitis/Emphysema Yes
Bronchitis/Emphysema DK
= Indicates missing data.
DK = The respondent replied "don't know
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
a Includes baby and child care, persona]
Source: U.S. EPA, 1996.
N
6,416
2,930
3,484
2
114
330
438
444
4,383
707
5,117
707
112
122
280
78
5,835
486
33
62
1,189
3,095
558
1,528
46
1,330
474
1,758
1,288
897
669
1,444
1,402
2,266
1,304
4,427
1,989
1,796
1,645
1,744
1,231
5,912
468
36
6,243
131
42
6,112
268
36
Mean
26.1
24.2
27.6
20.0
29.0
30.0
25.8
23.1
25.4
29.9
25.0
31.5
28.2
30.2
28.8
27.6
25.9
28.8
25.8
24.3
26.1
24.1
24.8
30.3
30.4
25.7
33.3
25.8
26.4
25.4
22.8
25.0
24.6
27.4
26.5
25.3
27.9
26.9
28.6
23.9
24.7
26.1
26.5
23.1
26.0
31.1
22 2
26.1
27.2
22.5
SD
29.7
31.0
28.4
14.1
39.0
19.4
35.3
18.7
27.2
44.5
28.5
31.6
29.8
27.3
39.3
40.3
28.5
40.6
16.8
37.2
26.4
25.1
23.2
39.9
45.2
26.4
53.0
23.6
27.0
34.8
23.1
24.3
30.3
26.1
38.8
30.3
28.2
26.9
41.1
20.7
25.6
30.0
23.0
44.1
29.0
49.5
40.9
29.9
22 2
44.1
SE Mm Max
0.4
0.6
0.5
10.0
3.7
1.1
1.7
0.9
0.4
1.7
0.4
1.2
2.8
2.5
2.3
4.6
0.4
1.8
2.9
4.7
0.8
0.5
1.0
1.0
6.7
0.7
2.4
0.6
0.8
1.2
0.9
0.6
0.8
0.5
1.1
0.5
0.6
0.6
1.0
0.5
0.7
0.4
1.1
7.3
0.4
4.3
6.3
0.4
1.4
7.3
care services, washing and personal hyg
1 705
1 705
1 555
10 30
2 300
1 170
1 690
1 210
1 555
1 705
1 705
1 295
5 270
1 240
2 546
3 275
1 705
2 570
5 65
3 275
1 690
1 555
1 295
1 705
3 275
1 690
1 570
1 270
1 255
1 705
1 257
1 360
1 570
1 300
1 705
1 705
1 555
1 546
1 705
1 270
1 340
1 705
1 210
3 275
1 705
5 546
3 275
1 705
1 150
3 275
ene (bathing,
5
5
5
5
10
5
10
5
5
5
5
5
5
5
8
5
5
5
5
10
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
showering
25
10
10
10
10
10
15
15
10
10
10
10
15
15
15
15
10
10
15
15
10
15
10
10
10
10
15
15
10
10
10
10
10
10
15
10
10
15
11
15
10
10
10
15
10
10
15
10
10
13
10
, etc.).
50 75
20 30
20 30
20 30
20 30
20 30
30 31
20 30
18 30
20 30
20 30
20 30
22 40
20 30
28 35
20 32
15 30
20 30
20 30
20 30
15 25
20 30
15 30
20 30
20 30
15 30
20 30
21 33
20 30
20 30
15 30
15 30
20 30
15 30
20 30
20 30
20 30
20 30
20 30
20 30
20 30
17 30
20 30
20 30
15 25
20 30
25 30
15 25
20 30
20 30
15 23
90
50
45
60
30
60
55
45
45
50
60
45
60
60
50
55
60
50
50
55
30
45
45
46
60
55
45
60
50
55
50
45
50
45
55
48
45
60
50
60
45
50
50
46
30
50
50
30
50
60
30
95
60
60
75
30
60
60
60
60
60
85
60
80
75
60
63
100
60
60
65
60
60
60
60
85
105
60
85
60
75
65
60
60
60
65
60
60
68
60
70
60
60
60
60
30
60
60
30
60
60
30
98 99
90 120
75 100
105 135
30 30
105 275
85 90
60 75
65 90
90 120
120 150
90 115
120 170
90 90
100 150
90 155
195 275
90 120
90 140
65 65
105 275
75 90
85 110
90 110
120 155
275 275
75 90
110 300
90 120
105 150
105 135
85 100
90 105
85 115
100 135
90 133
90 115
100 130
90 110
115 150
80 100
95 120
90 120
100 120
275 275
90 120
105 131
275 275
90 120
95 131
275 275
Page
16-84
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table
Age(y
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-33. Number of Times Washing the Hands at Specified Daily Frequencies, Doers Only
Number of Times/Day
Overall
Sex
Male
Female
Refused
Age (years)
_
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
_
Full Time
Part Time
Not Employed
Refused
Education
_
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No
Yes
DK
= Indicates missing data.
DK = The respondent replied
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
N
4,663
2,163
2,498
2
84
263
348
326
2,972
670
3,774
463
77
96
193
60
4,244
347
26
46
926
2,017
379
1,309
32
1,021
399
1,253
895
650
445
1,048
1,036
1,601
978
3,156
1,507
1,264
1,181
1,275
943
4,287
341
35
4,500
125
38
4,424
203
36
'don't know"
-
38
16
22
-
8
-
1
3
18
8
21
6
1
_
1
9
27
2
-
9
4
12
-
18
4
13
2
12
2
6
3
9
5
14
10
34
4
6
13
15
4
28
1
9
28
2
8
27
3
8
0-0
34
19
15
-
_
15
5
6
7
1
28
2
_
1
3
-
29
5
-
-
26
4
-
4
-
26
-
4
3
_
1
6
7
11
10
22
12
10
9
9
6
32
2
-
34
-
-
33
1
-
1-2
311
218
92
1
1
62
61
46
131
10
251
30
5
10
14
1
276
33
1
1
165
96
13
36
1
174
8
56
28
23
22
68
68
108
67
199
112
91
78
78
64
283
26
2
306
3
2
302
7
2
3-5
1,692
975
716
1
25
125
191
159
1,029
163
1,377
149
29
39
78
20
1,536
130
12
14
471
707
142
365
7
507
120
391
284
238
152
404
373
559
356
1,103
589
507
406
443
336
1,562
126
4
1,652
32
8
1,627
57
8
6-9
1,106
487
619
-
15
35
48
64
760
184
902
120
19
16
42
7
1,022
76
4
4
145
525
101
327
8
158
96
318
246
174
114
243
251
379
233
764
342
286
283
315
222
1,024
77
5
1,069
34
3
1,040
61
5
10-19
892
286
606
-
11
11
21
30
640
179
740
85
12
15
31
9
823
57
5
7
61
406
86
334
5
74
88
298
197
139
96
195
212
299
186
599
293
223
238
232
199
819
69
4
851
36
5
835
55
2
20-29
223
59
164
-
4
2
4
7
168
38
181
19
4
8
10
1
205
17
1
-
13
116
10
83
1
13
26
70
59
28
27
55
41
79
48
155
68
55
60
65
43
207
16
-
218
5
-
213
10
-
30+
178
49
129
-
5
3
2
2
143
23
140
23
1
5
5
4
164
10
1
3
7
103
15
52
1
12
24
47
48
27
20
38
38
66
36
147
31
51
44
48
35
165
10
3
171
3
4
172
3
3
DK
189
54
135
-
15
10
15
9
76
64
134
29
6
2
9
9
162
17
2
8
34
48
12
90
5
44
35
57
28
15
10
30
41
86
32
133
56
35
50
70
34
167
14
8
171
10
8
175
6
8
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
Page
16-86
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-34. Number of Times Swimming in a Month in Freshwater Swimming Pool, Children <21 Years
Age N
(year)
Birth to <1 10
Ito <2 8
2to<3 18
3 to <6 45
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-36. Number of Times Swimming in a
Month in Freshwater Swimming Pool, Doers Only
Times/Month
Overall
Sex
Male
Female
Refused
Age (years)
_
Ito4
5 to 11
12 to 17
18 to 64
>64
Race
White
Black
Asian
Some Others
Hispanic
T? f^fiic^H
Hispanic
No
Yes
DK
Refused
Employment
_
Full Time
Part Time
Not Employed
Refused
Education
_
< High School
High School Graduate
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-36. Number of Times Swimming in a Month in Freshwater Swimming Pool, Doers Only (continued)
Times/Month
18
Overall 2
Sex
Male
Female 2
TJ a-pnc f> A
Age (years)
Ito4
5 to 11
12 to 17 1
18 to 64
>64 1
Race
White 2
Black
A '
S Otli
Hispanic
Refused
Hispanic
No 2
Yes
DK
Refused
Employment
1
Full Time
Part Time
Not Employed 1
Education
1
< High School
High School Graduate
< College
College Graduate
Post Graduate 1
Census Region
Northeast
Midwest
South 2
West
Day of Week
Weekday 1
Weekend 1
Season
Winter 1
Spring
Summer 1
Fall
Asthma
No 2
Yes
DK
Angina
No 2
Yes
DK
Bronchitis/Emphysema
No 2
Yes
DK
= Indicates missing data.
DK = The respondent replied
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
20 23
25 1
10
15 1
2
3
4
15 1
1
19 1
3
1
1
1
23 1
1
1
9
8
-
7 1
1
11
1
6
3 1
2
2
7
4
7 1
7
18 1
7
3
8
10 1
4
21 1
3
1
24 1
1
22 1
2
1
don't know".
24 25
1 9
4
1 5
_
1 2
-
7
-
1 9
-
_
-
1 9
_
1 2
5
1
1
1 2
-
1
4
2
-
2
1
1 4
2
1 7
2
_
2
1 7
-
1 9
_
-
1 9
1 9
-
-
26
2
2
-
_
-
1
1
-
2
-
_
-
2
_
1
_
-
1
2
-
-
-
-
-
1
-
-
1
1
1
1
-
1
-
1
1
-
2
2
-
-
28 29 30 31
1 1 26 2
1 - 10 2
1 16
1 2
5
2
1 - 15 2
2
1 1 19 2
3
3
1
1 1 20 2
6
1 9
1 - 10 2
1
6
1 9
1
4
4
3 2
1 - 5 -
2 1
4
1191
11
1 - 19
1 7 2
1 - - 1
3
1 21 1
2
1 1 23 2
2
1
1 1 26 2
1 1 23 2
3
.
32 40 42
1 2 2
1 1 1
1 1
1
.
.
2 1
1
1 2 2
.
_
.
1 2 2
_
1
2 1
.
1
1
.
1
.
2 1
.
1 1
1
1
1
1 1
1 2
1
1
1 2
.
1 2 2
_
.
1 2 1
1
1 2 2
.
.
45 50 60
1 1 2
.
1 1 2
_
1
1
1
1
2
.
1
1
.
1 2
1
1 1
1
.
1
1 1
.
1
1
.
.
.
.
1 1
1 - 1
1 1 2
.
.
1 1
1 - 1
.
1 - 2
1
.
1 1 2
1 1 2
.
.
DK
5
4
1
_
-
1
3
1
5
-
-
-
4
1
1
2
-
1
I
1
-
1
2
1
-
1
-
4
-
4
1
-
2
3
-
5
_
-
5
4
1
-
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
Exposure Factors Handbook
September 2011
Page
16-89
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-37. Time Spent (minutes/month) in Freshwater Swimming Pool, Doers Only
Percentiles
Category
Overall
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Employment
Employment
Employment
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day of Week
Day of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
Yes
No
Yes
N = Doer sample size.
Note : A Value of 1 8 1 for number of minutes sij
Source: U.S. EPA, 1996
N
640
295
345
60
95
83
357
38
548
27
13
12
34
580
54
237
43
121
16
111
102
92
71
134
127
227
152
434
206
60
171
356
53
578
55
626
8
608
26
1
2
3
2
3
2
4
2
5
2
10
4
2
3
2
3
3
2
2
1
3
3
2
5
4
5
2
2
2
4
2
2
3
2
2
2
2
15
3
2
2
3
4
3
3
3
5
3
5
3
10
4
2
3
3
5
4
2
2
1
5
3
3
10
8
5
3
3
3
5
3
4
3
10
3
3
3
15
3
2
jnifies that more than
5
10
8
10
7.5
20
15
5
8
10
15
4
2
5
10
5
5
5
8
1
8
5
10
10
10
10
5
5
8
10
5
5
10
10
10
4
10
15
10
5
10
15
10
15
15
30
20
10
10
15
30
20
15
10
15
15
10
15
10
2
10
10
15
10
15
15
15
10
10
15
12.5
10
15
10
15
10
15
15
15
5
25
30
30
30
20
45
40
20
30
30
60
30
25
20
30
30
20
20
20
12.5
30
20
22.5
20
30
30
30
20
30
30
30
20
30
20
30
30
30
25
30
15
50 75
60 90
45 90
60 90
42.5 120
60 120
60 120
45 60
40 60
45 90
60 150
60 60
60 150
60 120
60 90
52.5 120
45 60
30 90
45 60
30 60.5
60 90
30 60
42.5 60.5
30 60
45 120
45 90
60 120
45 61
60 90
60 90
52.5 90
40 60
60 120
45 70
55 90
60 120
60 90
42.5 75
60 90
42.5 60
90 95
180 181
180 181
180 181
180 181
180 181
180 181
120 181
120 120
180 181
181 181
120 181
181 181
180 181
180 181
180 181
150 181
120 181
120 180
181 181
180 181
120 120
150 181
70 120
180 181
150 180
180 181
120 180
180 181
180 181
120 180.5
120 180
180 181
180 181
180 181
180 181
180 181
120 120
180 181
181 181
98
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
181
180
181
180
181
181
181
181
181
181
181
181
181
181
181
181
181
120
181
181
99 100
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
181 181
120 120
181 181
181 181
180 minutes were spent.
Page
16-90
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-38. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population and Doers
only, Children <21 Years
Age (years) N Mean
Mi
1
Percentiles
2 5 10 25 50
75
90
95
98
99
Max
Playing on Dirt — Whole Population
Birth to <
lto<2
2to<3
3to<6
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-39. Number of Minutes Spent Playing on Selected Outdoor Surfaces (minutes/day), Doers Only
Dirt
Percentiles
Category
Overall
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Employment
Employment
Employment
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day of Week
Day of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
No
Yes
N
647
326
320
205
185
38
214
2
528
60
5
16
36
574
69
138
25
52
17
67
62
51
18
118
116
250
163
406
241
93
230
245
79
590
56
646
627
20
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50
0
0
0
0
0
0.5
0
0
0
0
30
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
10
0
0
0
75
30
30
30
30
30
30
15
0
30
30
30
20
60
30
30
15
10
10
60
10
15
15
0
30
20
30
60
30
30
45
30
30
10
30
60
30
30
37.5
90
100
120
60
120
120
60
60
0
120
74
121
40
120
90
120
60
60
60
121
60
60
30
60
60
60
90
121
88
120
121
105
90
60
110
60
100
120
60
95
121
121
121
121
121
120
120
0
121
120
121
60
121
121
121
120
60
60
121
88
60
60
120
121
120
121
121
121
121
121
121
121
120
121
121
121
121
90.5
98
121
121
121
121
121
120
121
0
121
121
121
60
121
121
121
121
121
121
121
120
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
99
121
121
121
121
121
120
121
0
121
121
121
60
121
121
121
121
121
121
121
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
100
121
121
121
121
121
120
121
0
121
121
121
60
121
121
121
121
121
121
121
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
Page
16-92
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-39. Number of Minutes Spent Playing on Selected Outdoor Surfaces (minutes/day), Doers Only
(continued)
Sand or Gravel
Percentiles
Category
Overall
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Employment
Employment
Employment
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day of Week
Day of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Bronchitis/emphysema
Bronchitis/emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
No
Yes
N
659
334
324
203
193
40
219
2
534
64
5
15
39
583
72
140
27
53
17
69
64
50
20
116
122
256
165
410
249
97
232
250
80
600
58
659
638
21
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50
0
0
1
0
3
0
0
0
0
0
30
0
15
0
1.5
0
10
0
0
0
0
0
15
0
0
0
0
0
0
5
1
0
0
0
3
0
0
30
75
45
45
60
30
60
45
45
0
50
15
60
60
60
45
60
45
60
30
60
30
37.5
30
60
60
30
45
60
40
60
45
52.5
60
30
45
60
45
45
60
90
120
120
120
120
121
120
120
0
120
120
121
121
121
120
120
105
121
120
121
121
120
60
120
120
60
120
121
120
121
120
120
120
105
120
120
120
120
121
95
121
121
121
121
121
121
121
0
121
121
121
121
121
121
121
121
121
121
121
121
121
60
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
98
121
121
121
121
121
121
121
0
121
121
121
121
121
121
121
121
121
121
121
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
99
121
121
121
121
121
121
121
0
121
121
121
121
121
121
121
121
121
121
121
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
100
121
121
121
121
121
121
121
0
121
121
121
121
121
121
121
121
121
121
121
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
Exposure Factors Handbook
September 2011
Page
16-93
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-39. Number of Minutes Spent Playing on Selected Outdoor Surfaces (minutes/day),
(continued)
Doers Only
Grass
Percentiles
Category
Overall
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Employment
Employment
Employment
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day of Week
Day of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
No
Yes
N
657
327
329
206
185
39
221
3
532
65
5
16
37
581
72
141
27
55
20
69
64
51
19
119
120
252
166
412
245
95
231
250
81
600
56
656
636
21
1
0
0
0
0
0
0
0
30
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
30
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
30
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
30
0
3
10
0
0
0
0
0
0
5
5
0
0
1
0
0
7.5
1
0
0
1
0
1
1.5
0
0
0
0
0
0
25 50
20 60
20 60
15 60
15 60
30 60
30 60
20 60
30 121
20 60
20 58
30 30
10 60
30 60
20 60
10 35
20 60
15 60
23 60
30 60
15 60
17.5 46.5
30 60
25 60
30 60
30 60
20 60
10 45
15 60
30 60
4 30
30 60
30 60
10 35
20 60
22.5 60
20 60
20 60
30 60
75
120
121
120
120
121
120
120
121
121
90
30
120
110
121
100
121
120
121
120.5
121
60
121
121
121
121
120
120
120
121
120
121
121
120
120
120.5
120
120
121
90 95
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
98
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
99 100
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
N = Doer sample size.
NOTE: Avalueof"121"
Source: U.S. EPA, 1996.
for number of minutes signifies that more than 120 minutes were spent.
Page
16-94
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-40. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Children <21 Years
1 2 5 10
Birth to <1 2 63 5
lto<2 5 44 0
2to<3 1 121 121
3to<6 15 63 0 0 1 1 2
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-41. Time Spent (minutes/day) Working or Being Near Excessive Dust in
the Air, Doers Only
Percentiles
Category
Overall
Sex
Sex
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Race
Race
Race
Race
Race
Hispanic
Hispanic
Employment
Employment
Employment
Education
Education
Education
Education
Education
Census Region
Census Region
Census Region
Census Region
Day of Week
Day of Week
Season
Season
Season
Season
Asthma
Asthma
Angina
Angina
Bronchitis/Emphysema
Bronchitis/Emphysema
Population Group
Male
Female
1 to 4
5 to 11
12 to 17
1 8 to 64
>64
White
Black
Asian
Some Others
Hispanic
No
Yes
Full Time
Part Time
Not Employed
< High School
High School Graduate
< College
College Graduate
Post Graduate
Northeast
Midwest
South
West
Weekday
Weekend
Winter
Spring
Summer
Fall
No
Yes
No
Yes
No
Yes
N
679
341
338
22
50
52
513
38
556
66
7
15
29
611
57
368
66
122
52
199
140
82
76
138
145
227
169
471
208
154
193
193
139
606
73
662
15
637
41
1
0
1
0
0
0 0
0
2
2
0
1
2
2
2
2
0
5
1
5
2
2
3
20 20
5
3
0
0
2
0
0
2
0
5
1
3
0
2
1
0
0
2
0
0
2
3
0
0
0
3
0
0
N = Doer sample size.
Note: A value of "121" for number of minutes signifies that more than
5
3
2
3
5
2
2
5
0
5
2
5
0
2
2
3
1
2
0
1
2
5
2
3
2
3
2
0
5
5
5
5
0
2
2
5
2
5
5
20
5
5
5
3
7
5
5
5
5
10
5
5
5
5
5
5
5
5
5
3
5
5
5
5
5
3
5
5
10
7
8
5
2
4
5
10
5
8
5
20
10
7
5
10
15
5
8
7
10
20
15
10
5
10
5
10
7
5
5
5
10
10
5
10
7
30
7
5
25
30
30
30
5
15
5
30
50 75
121 121
121 121
121 121
75 121
75 121
20 120
121 121
35 105.5 121
30
20
60
60
20
30
30
37.5
20
30
35
30
60
30
37.5
20
30
30
30
30
30
30
20
30
30
30
30
30
60
30
30
121 121
121 121
90 121
120 121
121 121
121 121
121 121
121 121
120 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
120 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
90
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
95 98
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
99 100
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
121 121
120 minutes were spent.
Source: U.S. EPA, 1996.
Page
16-96
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-42. Time Spent (minutes/day) with Smokers Present, Children <21 Years
Age
(year)
Ito4
5 to 11
12 to 17
N
SD
SE
Min
Max
Source:
N Mean SD SE
155 367 325 26
224 318 314 21
256 246 244 15
= Doer sample size.
= Standard deviation.
= Standard error.
= Minimum.
= Maximum.
U.S. EPA, 1996.
Percentiles
5 25 50 75 90 95 98 99
5 30 90 273 570 825 1,010 1,140 1,305 1,440
1 25 105 190 475 775 1,050 1,210 1,250 1,440
1 10 60 165 360 595 774 864 1,020 1,260
Exposure Factors Handbook Page
September 2011 16-97
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-43. Time Spent (minutes/day) with Smokers Present
, Doers Only
Percentiles
Category Population Group
All
Sex Male
Sex Female
Sex Refused
Age (years)
Age (years) 1 to 4
Age (years) 5 to 1 1
Age (years) 12 to 17
Age (years) 1 8 to 64
Age (years) >64
Race White
Race Black
Race Asian
Race Some Others
Race Hispanic
Race Refused
Hispanic No
Hispanic Yes
Hispanic DK
Hispanic Refused
Employment
Employment Full Time
Employment Part Time
Employment Not Employed
Employment Refused
Education
Education < High School
Education High School Graduate
Education < College
Education College Graduate
Education Post Graduate
Census Region Northeast
Census Region Midwest
Census Region South
Census Region West
Day Of Week Weekday
Day Of Week Weekend
Season Winter
Season Spring
Season Summer
Season Fall
Asthma No
Asthma Yes
Asthma DK
Angina No
Angina Yes
Angina DK
Bronchitis/Emphysema No
Bronchitis/Emphysema Yes
Bronchitis/Emphysema DK
= Indicates missing data.
DK = The respondent replied "don't know
Refused = Refused data.
N = Doer sample size.
SD = Standard deviation.
SE = Standard error.
Min = Minimum number of minutes.
Max = Maximum number of minutes.
Source: U.S. EPA, 1996.
N
4,005
1,967
2,035
3
54
155
224
256
2,976
340
3,279
395
48
79
165
39
3,666
288
18
33
624
2,042
381
935
23
704
377
1,315
829
473
307
932
938
1,409
726
2,661
1,344
1,046
1,034
1,059
866
3,687
298
20
3,892
87
26
3,749
236
20
Mean
381.5
411.4
352.8
283.3
386.3
366.6
318.1
245.8
403.1
342.7
389.2
360.0
262.1
420.7
292.6
393.5
384.9
336.2
369.8
403.4
301.7
405.9
378.0
383.8
342.0
308.6
497.7
425.7
388.8
325.9
282.5
369.5
384.1
404.0
349.9
374.7
394.9
374.2
384.8
385.1
382.0
378.8
416.9
350.0
380.9
404.3
390.6
378.7
431.2
326.3
SD
300.5
313.0
285.1
188.2
305.4
324.5
314.0
243.6
299.4
292 2
303.0
288.0
209.9
339.2
250.2
325.3
301.2
280.9
371.5
322.8
295.5
296.3
291.1
308.7
254.2
292.8
317.8
301.7
295.8
272.7
257.1
287.7
304.8
308.5
292.0
296.2
308.5
304.2
301.6
300.4
295.1
298.4
324.0
304.3
299.5
345.1
300.4
298.6
326.8
291.1
SE
4.7
7.1
6.3
108.6
41.6
26.1
21.0
15.2
5 5
15.8
5.3
14.5
30.3
38.2
19.5
52.1
5.0
16.6
87.6
56.2
11.8
6.6
14.9
10.1
53.0
11.0
16.4
8.3
10.3
12.5
14.7
9.4
10.0
8.2
10.8
5.7
8.4
9.4
9.4
9.2
10.0
4.9
18.8
68.0
4.8
37.0
58.9
4.9
21.3
65.1
Min
1
1
1
105
5
5
1
1
2
5
1
2
5
10
5
25
1
1
15
25
1
2
5
3
25
1
2
3
5
2
3
2
2
1
1
1
1
1
2
2
2
1
5
25
1
2
25
1
5
10
Max
1,440
1,440
1,440
480
1,440
1,440
1,440
1,260
1,440
1,440
1,440
1,440
800
1,328
1,095
1,110
1,440
1,440
1,440
1,110
1,440
1,440
1,440
1,440
925
1,440
1,440
1,440
1,435
1,140
1,205
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
995
1,440
1,380
995
1,440
1,380
995
5
30
30
29
105
25
30
25
10
30
30
30
22
10
30
15
30
30
20
15
30
15
30
30
30
30
15
40
30
30
30
20
30
29
30
30
30
30
25
30
30
30
30
20
28
30
30
30
30
30
18
25
120
135
105
105
105
90
105
60
135
100
120
118
64
135
75
115
120
115
90
120
75
135
135
120
120
88
225
155
135
90
60
120
120
130
110
120
120
115
120
120
120
120
135
60
120
120
115
120
150
85
50
319
355
285
265
370
273
190
165
355
240
330
300
213
310
220
290
324
252
220
325
190
365
325
310
325
205
465
390
330
240
200
314
320
345
274
315
322
295
320
330
324
315
343
290
320
270
343
315
363
223
75
595
638
545
480
555
570
475
360
625
540
610
538
413
655
475
655
600
512
600
655
450
625
585
600
450
465
775
650
600
499
430
565
600
630
541
578
625
590
610
591
590
591
652
540
595
703
670
590
680
540
90
815
855
780
480
780
825
775
595
830
798
825
775
560
885
660
865
822
760
760
840
735
835
805
825
715
741
905
840
810
735
665
800
825
840
800
810
833
815
810
840
810
810
870
795
815
910
780
810
892
755
95
925
965
870
480
995
1,010
1,050
774
930
880
930
905
630
1,140
800
1,040
930
850
1,440
1,040
900
925
915
930
885
900
990
928
930
860
810
892
930
943
900
915
940
925
900
940
915
915
1,015
902.5
920
1,015
790
915
980
888
98
1,060
1,105
995
480
995
1,140
1,210
864
1,047
1,015
1,060
1,080
800
1,305
845
1,110
1,060
1,010
1,440
1,110
1,140
1,005
1,080
1,110
925
1,095
1,120
1,060
1,050
990
900
990
1,080
1,090
1,045
1,045
1,110
1,080
1,105
1,040
1,030
1,050
1,202
995
1,060
1,320
995
1,060
1,205
995
99
1,170
1,217
1,110
480
1,440
1,305
1,250
1,020
1,150
1,205
1,190
1,160
800
1,328
945
1,110
1,170
1,260
1,440
1,110
1,230
1,110
1,245
1,290
925
1,217
1,369
1,202
1,155
1,035
983
1,095
1,140
1,205
1,180
1,150
1,260
1,170
1,215
1,130
1,150
1,170
1,335
995
1,170
1,380
995
1,170
1,260
995
Page
16-98
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-44. Mean Time Spent
(hours/week)3 in Ten Major Activity Categories Grouped by Regions
Totalb
A? = 975
Activity
Activity Category
Market Work
House/yard work
Child care
Services/shop
Personal care
Education
Organizations
Social
entertainment
Active leisure
Passive leisure
Total Time
West
A? = 200
23.44
14.64
2.50
5.22
79.23
2.94
3.42
8.26
5.94
22.47
168.00
North Central Northeast
A? =304
29.02
14.17
2.82
5.64
76.62
1.43
2.97
8.42
5.28
21.71
168.00
a Weighted for day of week, panel loss (not defined
to rounding.
b N = surveyed population.
c SD = standard deviation.
Source: Hill, 1985.
N= 185
27.34
14.29
2.32
4.92
78.11
0.95
2.45
8.98
4.77
23.94
168.00
South
A? = 286
24.21
15.44
2.66
4.72
79.38
1.45
2.68
8.22
5.86
23.47
168.00
in report), and correspondence to Census.
Mean
26.15
14.66
2.62
5.15
78.24
1.65
2.88
8.43
5.49
22.80
168.00
SDC
23.83
12.09
5.14
5.40
12.70
6.34
5.40
8.17
7.81
13.35
0.09
Data may not add to totals shown due
Table 16-45. Total Mean Time
Spent (minutes/day) in Ten Major Activity Categories
Day
Grouped by Type of
Time Duration (minutes/day)
Activity Category
Market Work
House/Yardwork
Child Care
Services/Shopping
Personal Care
Education
Organizations
Social Entertainment
Active Leisure
Passive Leisure
Total Time
Weekday
[A/8 = 831]
288.0 (257. 7)b
126.3(119.3)
26.6 (50.9)
48.7(58.7)
639.2(114.8)
16.4 (64.4)
21.1 (49.7)
54.9 (69.2)
37.9(71.11)
181.1 (121.9)
1,440
Saturday
[A? =831]
97.9(211.9)
160.5 (157.2)
19.4(51.5)
64.4(92.5)
706.8(169.8)
5.4(38.1)
18.4(75.2)
1,114.1 (156.0)
61.4(126.5)
191.8(161.6)
1,440
Sunday
[A? =831]
58.0(164.8)
124.5(133.3)
24.8(61.9)
21.6(49.9)
734.3 (156.5)
7.3 (48.0)
58.5(104.5)
110.0(151.2)
64.5 (120.6)
236.5(167.1)
1,440
* N = Number of respondents.
b ( ) = Numbers in parentheses are standard deviations.
Source: Hill, 1985.
Exposure Factors Handbook
September 2011
Page
16-99
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-46. Mean Time Spent (minutes/day) in Ten Major Activity Categories During 4 Waves of
Interviews"
Fall Spring
(Nov. 1, 1975)b (June 1, 1976)b
A?=861 A?=861
Activity Category
Market work
House/yard work
Child care
Services/shop
Personal care
Education
Organizations
Social
entertainment
Active leisure
Passive leisure
Total Time
Wavel
222.94
133.16
25.50
48.98
652.95
22.79
25.30
63.87
42.71
210.75
1,440.00
Wave 2
226.53
135.58
22.44
44.09
678.14
12.57
22.55
67.11
47.46
183.48
1,440.00
a Weighted for day of week, panel loss (not defined in report), and
b Dates by which 50% of the interviews for each wave were taken
Source: Hill, 1985.
Spring Summer
(June 1, 1976)b (Sept. 21, 1976)b
W=861 A?=861
Wave 3
210.44
143.10
25.51
44.61
688.27
2.87
23.21
83.90
46.19
171.85
1,440.00
correspondence to Census.
Wave 4
230.92
119.95
21.07
47.75
674.85
10.76
29.91
72.24
42.30
190.19
1,440.00
Range of Standard
Deviations
272-287
129-156
49-58
76-79
143-181
32-93
68-87
102-127
96-105
144-162
-
Table 16-47. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Sexa
Time Duration (hours/week)
Men
N= 140
Women
N=56l
Men and Women
N=97l
Activity Category
Market work
House/yard
Child care
Services/shop
Personal care
Education
Organizations
Social entertainment
Active leisure
Passive leisure
Total time
35.8
8.5
1.2
3.9
77.3
2.3
2.5
7.9
5.9
22.8
168.1
(23.6)b
(9.0)
(2.5)
(4.5)
(13.0)
(7.7)
(5.5)
(8.3)
(8.2)
(14.1)
a Detailed components of activities (87) are presented in Table
b
17.9
20.0
3.9
6.3
79.0
1.1
3.2
8.9
5.2
22.7
168.1
1A-4 of the original
(20.7)
(11.9)
(6.4)
(5.9)
(12.4)
(4.8)
(5.3)
(8.0)
(7.4)
(12.7)
study.
26.2
14.7
2.6
5.2
78.2
1.7
2.9
8.4
5.5
22.8
168.1
(23.8)
(12.1)
(5.2)
(5.4)
(12.7)
(6.4)
(5.4)
(8.2)
(7.8)
(13.3)
( ) = Numbers in parentheses are standard deviations.
Source: Hill, 1985.
Page
16-100
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-48. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of Day
Age (3 to
Activity
Market Work
Household Work
Personal Care
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoors
Hobbies
Art Activities
Playing
TV
Reading
Household Conversations
Other Passive Leisure
Unknown
Percent of Time Accounted for
by Activities Above
N = Sample size.
= No data
Source: Timmer et al., 1985.
Weekday
Boy
(TV=118) (TV
16
17
43
81
584
252
14
7
16
25
10
3
4
137
117
9
10
9
22
94
Girl
= 111)
0
21
44
78
590
259
19
4
9
12
7
1
4
115
128
7
11
14
25
92
11 years)
Weekend
Boy
(TV=118) (TV
7
32
42
78
625
-
4
53
23
33
30
3
4
177
181
12
14
16
20
93
Age (12 to 17 years)
Girl
= 111)
4
43
50
84
619
-
9
61
37
23
23
4
4
166
122
10
9
17
29
89
Weekday
Boy
(TV =77) (A
23
16
48
73
504
314
29
3
17
52
10
7
12
37
143
10
21
21
14
93
Girl
r=83)
21
40
71
65
478
342
37
7
25
37
10
4
6
13
108
13
30
14
17
92
Weekend
Boy
(TV =77) (A
58
46
35
58
550
-
25
40
46
65
36
4
11
35
187
12
24
43
10
88
Girl
r=83)
25
89
76
75
612
-
25
36
53
26
19
7
9
24
140
19
30
33
4
89
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-49. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for 5 Different Age Groups
Activity
Weekday
Weekend
Age (years)
Age (years)
Significant
Effect8
3-5
6-8
9-11 12-14
15-17
3-5
6-8 9-11
12-14
15-17
Market Work - 14 8 14 28
Personal Care 41 49 40 56 60
Household Work 14 15 18 27 34
Eating 82 81 73 69 67
Sleeping 630 595 548 473 499
School 137 292 315 344 314
Studying 2 8 29 33 33
Church 4999 3
Visiting 14 15 10 21 20
Sports 5 24 21 40 46
Outdoor Activities 49 8 7 11
Hobbies 0224 6
Art Activities 5433 12
Other Passive Leisure 9126 4
Playing 218 111 65 31 14
TV 111 99 146 142 108
Reading 5 5 9 10 12
Being Read to 2200 0
Unknown 30 14 23 25 7
4 10
47 45 44
17 27 51
81 80 78
634 641 596
1
55
10
3
8
1
4
6
267
122
4
3
52
2
56
8
30
23
5
4
10
180
136
9
2
7
12
53
13
42
39
3
4
7
92
185
10
0
14
29
60
72
68
604
15
32
22
51
25
8
7
10
35
169
10
0
4
48
51 A, S, AxS(F>M)
60 A, S, AxS (F > M)
65 A
562 A
30
37
56
37
26
3
10
18
21
157
18
0
9
A
A
A (Weekend Only)
A, S (M > F)
A
A, S (M > F)
A, S, AxS (M > F)
A
A
A
a Effects are significant for weekdays and weekends,
weekend activities; S = sex effect/) < 0.05, F > M,
interaction, p < 0.05.
= No data.
Source: Timmer et al., 1985.
, unless otherwise specified. A = age effect, p < 0.05, for both weekdays and
M > F = females spend more time than males, or vice versa; and AxS = age by sex
Page
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-50. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week
Indoors8 Outdoors
Age Group —
Weekday Weekend Weekday Weekend
3 to 5 years
6 to 8 years
9 to 1 1 years
12 to 14 years
15 to 17 years
19.4
20.7
20.8
20.7
19.9
18.9
18.6
18.6
18.5
17.9
2.5
1.8
1.3
1.6
1.4
3.1
2.5
2.3
1.9
2.3
Time indoors was estimated by adding the average times spent performing indoor activities (household work, personal care, eating,
sleeping, attending school, studying, attending church, watching television, and engaging in conversation) and half the time spent in
each activity which could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing,
reading, and other passive leisure).
Time outdoors was estimated by adding the average time spent in outdoor activities and half the time spent in each activity which
could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing, reading, and other passive
leisure).
Source: Adapted from Timmer et al., 1985.
Exposure Factors Handbook Page
September 2011 16-103
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-51. Mean Time Spent (minutes/day) in Various Microenvironments by Age Group (years) for the
National and California Surveys
National Data
Mean Duration (Standard Errorl
Microenvironment
Autoplaces
Restaurant/bar
In-vehicle/internal combustion
In-vehicle/other
Physical/outdoors
Physical/indoors
Work/study-residence
Work/study-other
Cooking
Other activities/kitchen
Chores/child
Shop/errands
Other/outdoors
Social/ cultural
Leisure-eat/indoors
Sleep/indoors
Age 12-1 7
AT =340"
2(11
9(21
79(71
0(01
32(81
15(31
22(41
159(14)
11(3)
53(4)
91 (7)
26(4)
70(13)
87(10)
237(16)
548 (31)
Doerb
73
60
88
12
130
87
82
354
40
64
92
68
129
120
242
551
Age 18-24
AT =340
7(21
28(31
103 (81
KD
17(4)
8(2)
19(6)
207 (20)
18(2)
42(3)
124(9)
31(4)
34(4)
100(12)
181 (11)
511 (26)
Doer
137
70
109
160
110
76
185
391
39
55
125
65
84
141
189
512
Age 24-44
AT =340
2(11
25(31
94(41
1 (0)
19(41
7(1)
16(2)
220(11)
38(2)
70(4)
133 (6)
33(2)
48(6)
56(3)
200 (8)
479 (14)
Doer
43
86
101
80
164
71
181
422
57
86
134
66
105
94
208
480
Age 45-64
AT =340
4(11
19(21
82(51
KD
7(1)
7(2)
9(2)
180(13)
43(3)
90(6)
121 (6)
33(3)
60(7)
73(6)
238(11)
472(15)
Doer
73
67
91
198
79
77
169
429
64
101
122
67
118
116
244
472
Age 65+
AT =340
4(21
20(5)
62(5)
KD
15(4)
7(1)
5(3)
35(6)
50(5)
108 (9)
119(7)
35(5)
82(13)
85(8)
303 (20)
507 (26)
Doer
57
74
80
277
81
51
297
341
65
119
121
69
140
122
312
509
GARB Data
Mean Duration (Standard Error)
Microenvironment
Autoplaces
Restaurant/bar
In-vehicle/internal combustion
In-vehicle/other
Physical/outdoors
Physical/indoors
Work/study-residence
Work/study-other
Cooking
Other activities/kitchen
Chores/child
Shop/errands
Other/outdoors
Social/ cultural
Leisure-eat/indoors
Sleep/indoors
Age 12-17
AT =340"
16(8)
16(4)
78(11)
1 (0)
32(7)
20(4)
25(5)
196(30)
3(1)
31(4)
72(11)
14(3)
58(8)
63 (14)
260 (27)
557 (44)
Doer
124
44
89
19
110
65
76
339
19
51
77
50
78
109
270
560
Age 18-24
AT =340
16(4)
40(8)
111 (13)
3(1)
13(3)
5(2)
30(11)
201 (24)
14(2)
31(5)
79(8)
35(7)
80(15)
65 (10)
211 (19)
506 (30)
Doer
71
98
122
60
88
77
161
344
40
55
85
71
130
110
234
510
Age 24^14
AT =340
25(9)
44(5)
98(5)
5(2)
17(3)
6(1)
7(2)
215(14)
32(2)
43(3)
110(6)
33(4)
68(8)
50(5)
202 (9)
487(17)
Doer
114
116
111
143
128
61
137
410
59
65
119
71
127
122
215
491
Age 45-64
AT =340
20(5)
31(4)
100(11)
2(1)
14(3)
5(1)
10(3)
173(20)
31(3)
62(6)
99(8)
32(3)
76(12)
50(5)
248(15)
485 (23)
Doer
94
82
117
56
123
77
139
429
68
91
109
77
134
107
261
491
Age 65+
AT =340
9(2)
25(7)
63(8)
2(1)
15(4)
3(1)
5(3)
30(11)
41 (7)
97(14)
123(15)
35(5)
55(7)
49(7)
386 (34)
502(31)
Doer
53
99
89
53
104
48
195
336
69
119
141
76
101
114
394
502
" All Ws are weighted number.
b Doer = Respondents who reported part
Source: Robinson and Thomas,
1991.
cipating in
each activity
location spent in microenv
ironments.
Page
16-104
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-52. Mean Time Spent in Ten Major Activity Categories Grouped by Total Sample
and Sex for the CARB and National Studies (age 18-64 years)
Time Duration (minutes/day)
Activity Category
Paid Work
Household Work
Child Care
Obtaining Goods and Services
Personal Needs and Care
Education and Training
Organizational Activities
Entertainment/Social Activities
Recreation
Communication
a jV = total diary days.
Source: Robinson and Thomas, 1991.
CARB
National
(1987-1988) (1985)
Total
N°= 1,359
273
102
23
61
642
22
12
60
43
202
Sample
N= 1,980
252
118
25
55
642
19
17
62
50
196
CARB
(1987-1988)
Men
A? =639
346
68
12
48
630
25
11
57
53
192
National
Women
A? =720
200
137
36
73
655
20
13
55
31
214
Men
N=92l
323
79
11
44
636
21
12
64
69
197
(1985)
Women
N= 1,059
190
155
43
62
645
16
20
62
43
194
Table 16-53. Total Mean Time Spent at 3 Major Locations Grouped by Total Sample and Sex
for the CARB and National Study (age 18-64 years)
Location8 CARB
(1987-1988)
National CARB National
(1985) (1987-1988) (1985)
Total Sample Men Women Men Women
JV = 1,359
At Home 892
Away From Home 430
Travel 116
Not Ascertained 2
Total Time 1,440
" N = total diary days.
Source: Robinson and Thomas, 1991.
JV= 1,980 N=39 N=720 N=92l N= 1,059
954 822 963 886 1,022
384 487 371 445 324
94 130 102 101 87
81487
1,440 1,440 1,440 1,440 1,440
Exposure Factors Handbook
September 2011
Page
16-105
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-54. Mean Time Spent at 3 Locations for both CARB and National Studies
(ages 12 years and older)
Mean Duration (minutes/day)
Location Category CARB National
(N = 1,762)' SE^ (N = 2,762)' SE
Indoor 1,255C 28 1,279C 21
Outdoor 86d 5 74d 4
In-Vehicle 98d 4 87d 2
Total Time Spent 1,440 1,440
' N = Weighted Number - National sample population was weighted to obtain a ratio of 46.5 males and 53.5 females, in equal
proportion for each day of the week, and for each quarter of the year.
b SE = Standard error of mean.
c Difference between the mean values for the CARB and national studies is not statistically significant.
d Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level.
Source: Robinson and Thomas, 1991.
Table 16-55. Sample Sizes for Sex
Age Group Group
Adults Men
Women
Adolescents Male
Female
Children* Young male
Young female
Old male
Old female
and Age Groups
Sample Size
724
855
98
85
145
124
156
160
a Children under the age of 6 are excluded for the present study (too few responses
Source: Funk etal., 1998.
Age Range
>1 8 years
>1 8 years
12-1 7 years
12-1 7 years
6-8 years
6-8 years
9-11 years
9-11 years
in CARB study).
Page Exposure Factors Handbook
16-106 September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-56. Assignment of At Home Activities to Inhalation Rate Levels for All Individuals
Children
Low
Watching child care
Night sleep
Watch personal care
Homework
Radio use
TV use
Records/tapes
Reading books
Reading magazines
Reading newspapers
Letters/writing
Other leisure
Homework/watch TV
Reading/TV
Reading/listen music
Paperwork
Moderate
Outdoor cleaning
Food Preparation
Metal clean-up
Cleaning house
Clothes care
Car/boat repair
Home repair
Plant care
Other household
Pet care
Baby care
Child care
Helping/teaching
Talking/reading
Indoor playing
Outdoor playing
Medical child care
Washing, hygiene
Medical care
Help and care
Meals at home
Dressing
Visiting at home
Hobbies
Domestic crafts
Art
Music/dance/drama
Indoor dance
Conservations
Painting room/home
Building fire
Washing/dressing
Outdoor play
Playing/eating
Playing/talking
Playing/watch TV
TV/eating
TV/something else
Reading book/eating
Read magazine/eat
Read newspaper/eat
Adolescent and Adult
Low
Night sleep
Naps/resting
Doing homework
Radio use
TV use
Records/tapes
Read books
Read magazines
Writing/paperwork
Other passive leisure
Moderate
Food preparation
Food clean-up
Cleaning house
Clothes care
Car care
Household repairs
Plant care
Animal care
Other household
Baby care
Child care
Helping/teaching
Talking/reading
Indoor playing
Outdoor playing
Medical child care
Washing
Medical care
Help and care
Meals at home
Dressing/grooming
Not ascertained
Visiting at home
Hobbies
Domestic crafts
Art
Music/drama/dance
Games
Computer use
Conversations
High
Outdoor cleaning
Source: Funketal., 1998.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-57. Aggregate Time Spent (minutes/day) At Home in Activity Groups"
Adult
Mean SD
Low 702 214
Moderate 257 183
High 9 38
Highpartlclpmtsc 92 83
Adolescent
Mean
789
197
1
43
a Time spent engaging in all activities embodied by inhalation rate category
b Significantly different from adolescents (p < 0.05).
0 Participants in high inhalation rate level activities (i.e., doers).
SD = Standard deviation.
Source: Funket al., 1998.
SD
230
131
11
72
(minutes/day).
Children
Mean SD
823 153
241b 136
3 17
58 47
Table 16-58. Comparison of Mean Time Spent (minutes/day) At Home, by Sexa
Activity Group
Adults
Low
Moderate
High
-tll§ftparticipants
Adolescents
Low
Moderate
High
Male
Mean
691
190
14
109
775
181
2
a Time spent engaging in all activities embodied by
b Significantly different from male (p < 0.05).
0 Participants in high inhalation rate activities (i.e.,
SD = Standard deviation.
Source: Funket al., 1998.
Female
SD
226
150
50
97
206
126
16
inhalation rate category
doers).
Mean
714
323b
4b
59b
804
241
0
(minutes/day).
SD
200
189
18
40
253
134
0
Page
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-59. Comparison of Mean Time Spent (minutes/day) At Home, by Sex and Age for Children"
Activity
Group
Low
Moderate
High
6 to 8
Mean
806
259
3
77
Years
SD
134
135
17
59
Male
9 to 11
Mean
860
198
7
70
a Time spent engaging in all activities embodied by
b Participants in high inhalation rate activities (i.e.,
SD = Standard deviation.
Source: Funk etal., 1998.
Years
SD
157
111
27
54
Female
6 to 8 Years 9 to
Mean
828
256
1
68
inhalation rate category
doers).
SD Mean
155 803
141 247
9 2
11 30
(minutes/day).
11 Years
SD
162
146
10
23
Table 16-60. Number of Person-Days/Individualsa for Children Less than 12 Years in CHAD Database
Age Group
All Studies
California"
Cincinnati0
NHAPS-Air
NHAPS-Water
0 Years
0 to 6 Months
6 to 12 Months
1 Year
12 to 18 Months
18 to 24 Months
2 Years
3 Years
4 Years
5 Years
6 Years
7 Years
8 Years
9 Years
10 Years
11 Years
Total
223/199
259/238
317/264
278/242
259/232
254/227
237/199
243/213
259/226
229/195
224/199
227/206
3,009/2,640
104
50
54
97
57
40
112
113
91
98
81
85
103
90
105
121
1,200
36/12
15/5
21/7
31/11
81/28
54/18
41/14
40/14
57/19
45/15
49/17
51/17
38/13
32/11
556/187
39
64
57
51
64
52
59
57
51
42
39
44
619
44
67
67
60
63
64
40
56
55
46
42
30
634
a The number of person-days of data are the same as the number of individuals for all studies except for the Cincinnati
study. Since up to 3 days of activity pattern data were obtained from each participant in this study, the number of
person-days of data is approximately 3 times the number of individuals.
b The California study referred to in this table is the Wiley et al. (1991) study.
0 The Cincinnati study referred to in this table is the Johnson (1989) study.
= No data.
Source: Cohen Hubal et al., 2000.
Exposure Factors Handbook
September 2011
Page
16-109
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-61. Time Spent (hours/day)
Age (years)
0
1
2
3
4
5
6
7
8
9
10
11
in Various Microenvironments, by Age
Average Time ± Standard Deviation (Percent > 0 Hours)
Indoors at Home
19. 6 ±4.3 (99)
19. 5 ±4.1 (99)
17.8 ±4.3 (100)
18.0 ±4.2 (100)
17.3 ±4.3 (100)
16.3 ±4.0 (99)
16.0 ±4.2 (98)
15. 5 ±3. 9 (99)
15. 6 ±4.1 (99)
15.2 ±4.3 (99)
16.0 ±4.4 (96)
14.9 ±4.6 (98)
Outdoors at Home
1.4 ±1.5 (20)
1.6 ±1.3 (35)
2.0 ±1.7 (46)
2.1 ±1.8 (48)
2.4 ±1.8 (42)
2. 5 ±2. 1(52)
2.6 ±2.2 (48)
2.6 ±2.0 (48)
2.1 ±2.5 (44)
2.3 ±2.8 (49)
1.7 ±1.9 (40)
1.9 ±2.3 (45)
Indoors at School
3. 5 ±3. 7 (2)
3.4 ±3. 8 (5)
6.2 ±3. 3 (9)
5.7 ±2.8 (14)
4.9 ±3.2 (16)
5.4 ±2. 5 (39)
5.8 ±2.2 (34)
6. 3 ±1.3 (40)
6.2 ±1.1 (41)
6.0 ±1.5 (39)
5. 9 ±1.5 (39)
5. 9 ±1.5 (41)
Outdoors at Park
1.6 ±1.5 (9)
1.9±2.7(10)
2.0 ±1.7 (17)
1.5 ±0.9 (17)
2.3 ±1.9 (20)
1.6 ±1.5 (28)
2.1 ±2.4 (32)
1.5 ±1.0 (28)
2.2 ±2.4 (37)
1.7 ±1.5 (34)
2.2 ±2.3 (40)
2.0 ±1.7 (44)
In Vehicle
1.2 ±1.0 (65)
1.1 ±0.9 (66)
1.2 ±1.5 (76)
1.4 ±1.9 (73)
1.1 ±0.8 (78)
1.3 ±1.8 (80)
1.1 ±0.8 (79)
1.1 ±1.1 (77)
1.3 ±2.1 (82)
1.2 ±1.2 (76)
1.1 ±1.1 (82)
1.6 ±1.9 (74)
Source: Cohen Hubaletal., 2000.
Table 16-62. Mean Time Children Spent (hours/day) Doing Various Macroactivities While Indoors at Home
Age
(years)
0
1
2
3
4
5
6
7
8
9
10
11
Source:
Mean Time (Percent > 0 Hours)
Eat
1.9(96)
1.5(97)
1.3(92)
1.2(95)
1.1(93)
1.1(95)
1.1(94)
1.0(93)
0.9(91)
0.9 (90)
1.0(86)
0.9(89)
Cohen Hubal
Sleep or Nap
12.6(99)
12.1(99)
11.5(100)
11.3(99)
10.9(100)
10.5(98)
10.4(98)
9.9 (99)
10.0(96)
9.7 (96)
9.6 (94)
9.3 (94)
etal.,2000.
Shower or
Bath
0.4 (44)
0.5 (56)
0.5(53)
0.4(53)
0.5 (52)
0.5 (54)
0.4 (49)
0.4 (56)
0.4(51)
0.5 (43)
0.4 (43)
0.4 (45)
Play Games
4.3 (29)
3.9(68)
2.5(59)
2.6(59)
2.6 (54)
2.0 (49)
1.9(35)
2.1 (38)
2.0(35)
1.7(28)
1.7(38)
1.9(27)
Watch TV or
Listen to Radio
1.1(9)
1.8(41)
2.1 (69)
2.6(81)
2.5 (82)
2.3(85)
2.3 (82)
2.5 (84)
2.7(83)
3.1(83)
3.5 (79)
3.1 (85)
Read, Write,
Homework
0.4 (4)
0.6(19)
0.6 (27)
0.8 (27)
0.7(31)
0.8(31)
0.9(38)
0.9 (40)
1.0(45)
1.0(44)
1.5(47)
1.1(47)
Think, Relax,
Passive
3.3 (62)
2.3 (20)
1.4(18)
1.0(19)
1.1(17)
1.2(19)
1.1(14)
0.6(10)
0.7(7)
0.9(17)
0.6(10)
0.6(10)
Page
16-110
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-63. Time Children
Spent (hours/day) in Various Microenvironments, by Age Recast into
Standard Age Categories
Indoors at Home Outdoors at Home
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
JV = Sample
JV
123
33
120
287
728
765
2,110
3,283
2,031
1,005
size.
Mean
Time
19.6
20.9
19.6
19.1
19.2
18.2
17.3
15.7
15.5
14.6
Doing
98
100
100
99
99
99
100
99
97
98
Source: Based on data source (CHAD) used by Cohen
Mean
Time
1.7
1.8
0.8
1.1
1.4
1.8
1.9
1.9
1.7
1.4
Hubal et al
Doing
21
9
8
15
34
38
43
40
30
20
., 2000.
Indoors at School
Mean
Time
4.3
0.2
7.8
7.6
6.4
6.8
5.9
6.5
6.6
5.7
Doing
3
3
7
8
9
12
26
44
45
33
Outdoors at Park
Mean
Time
1.3
1.6
1.3
1.8
1.5
2.1
1.6
2.1
2.6
3.1
Doing
3
9
6
5
5
7
10
17
15
10
New
In Vehicle
Mean
Time
1.3
1.3
1.1
1.3
1.1
1.3
1.3
1.1
1.3
1.7
Doing
63
27
14
14
27
28
29
29
42
90
Table 16-64. Time Children Spent (hours/day) in Various Macroactivities While Indoors at
New Standard Age Categories
Eat
Age Group JV
Mean
Time
Birth to <1 month 123 2.2
1 to <3 months 33 2.4
3 to <6 months 120 2.0
6 to <12 months 287 1.8
1 to <2 years 728 1.7
2 to <3 years 765 1.5
3 to <6 years 2,110 1.4
6to
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-65. Number and Percentage of Respondents with Children and Those Reporting
Outdoor Play" Activities in Both Warm and Cold Weather
Source
Respondents
with Children
Child Player"
Child
Non-Player
Warm Cold
Weather Weather
Playerb Player
Player in Both Seasons
SCS-II base
SCS-II over sample
Total
197
483
680
128
372
500
65.0
77.0
73.5
69
111
180
35.0
23.0
26.5
127
370
497
100
290
390
50.8
60.0
57.4
a "Play" and "player" refer specifically to participation in outdoor play on bare dirt or mixed grass and dirt.
b Does not include three "Don't know/refused" responses regarding warm weather play.
N = Sample size.
Source: Wong et al, 2000.
Table 16-66. Play
Statistic
N
5th Percentile
50th Percentile
95th Percentile
Frequency
(days/week)
372
1
3
7
Frequency and
Cold Weather
Duration
(hours/day)
374
1
1
4
Duration for all
Total
(hours/week)
373
1
5
20
Child Players (from SCS-II data)
Frequency
(days/week)
488
2
7
7
Warm Weather
Duration
(hours/day)
479
1
3
8
Total
(hours/week)
480
4
20
50
N = Sample size.
Source: Wong et al
, 2000.
Table 16-67. Hand Washing and Bathing Frequency for all Child Players (from
Cold Weather
Statistic
N
5th Percentile
50th Percentile
95th Percentile
jV = Sample size.
Source: Wong et al., 2000.
Hand Washing
(times/day)
329
2
4
10
Bathing
(times/week)
388
2
7
10
SCS-II data)
Warm Weather
Hand Washing
(times/day)
433
2
4
12
Bathing
(times/week)
494
3
7
14
Page
16-112
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-68. NHAPS and
Data Source
NHAPS
SCS-II
a
b
Source:
Cold Weather
114
102
SCS-II Play Duration3
Mean Play Duration
(minutes/day)
Warm Weather
109
206
Comparison (Children Only)
Total
223
308
/testb
p< 0.0001
Selected previous day activities in NHAPS; average day outdoor play on bare dirt or mixed grass and dirt in SCS-II.
2x2 Chi-square test for contingency between NHAPS and SCS-II.
Wong etal, 2000.
Table 16-69. NHAPS and SCS-II Hand Wash Frequency3
Dat
Sour
NHAPS
SCS-II
NHAPS
SCS-II
a
b
c
Source:
Season
ce
Cold
Cold
Warm
Warm
Comparison (Children only)
Percent* Reporting Frequency (times/day) of:
0
3
1
3
0
1-2
18
16
18
12
3-5
51
50
51
46
6-9
17
11
15
16
10-19
7
7
7
10
20-29
1
1
2
1
30+
1
0
1
0
Selected previous day activities in NHAPS; average day outdoor play on bare dirt or mixed
Results are reported as percentage of total for clarity. Incidence data were used in statistical
2x2 Chi-square test for contingency between NHAPS and SCS-II.
Wong etal., 2000.
"Don't
Know"
3
15
4
13
grass and dirt
tests.
r test0
p = 0.06
^ = 0.001
in SCS-II.
Exposure Factors Handbook Page
September 2011 16-113
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-70. Time Spent (minutes/day) Outdoors
Based on CHAD Data (Doers Only)3
Age Group
Time Spent Outdoors
Minimum
Median
Maximum
Mean
SD
COV(%) Participation' (%)
<1 month
1 to 2 months
3 to 5 months
6 to 11 months
1 year
2 years
3 to 5 years
6 to 10 years
11 to 15 years
16 to 17 years
18 to 20 years
21 to 44 years
45 to 64 years
>64 years
57
5
27
91
389
448
1,336
2,216
1,423
356
351
3,660
1,914
1,002
2
4
10
5
1
1
1
1
1
1
1
1
1
1
60
60
90
60
75
100
120
120
110
85
70
61
69
65
700
225
510
450
1,035
550
972
1,440
1,440
1,083
788
1,305
1,015
840
99
102
114
91
102
134
146
162
154
129
132
131
135
118
124
90
98
76
99
108
117
144
163
145
155
165
162
130
125
89
86
84
97
80
80
89
106
112
118
126
120
110
47
36
23
33
58
64
68
71
73
81
72
62
62
57
" Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis.
b Participation rates or percent of sample days in the study spending some time (>0 minutes per day) outdoors. The mean time spent
outdoors for the age group may be obtained by multiplying the participation rate by the mean time shown above.
SD = Standard deviation.
COV = Coefficient of variation (SD/mean x 100).
Source: Graham and McCurdy, 2004.
Page
16-114
Exposure Factors Handbook
September 2011
-------
s
I
ft
Table 16-71. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Sex and Age Cohort (Doers Only)3
Time Spent Outdoors in Minutes
Age Group Sex
<1 month Male
1 to 2 months Male
Minimum Median
35
22
4
7
2
4
1 225
3 to 5 months Male
6 to 1 1 months Male
Inflate Male
f<3ifiSte Male
f&naigears Male
f&hlftyears Male
f tmrfe5 years Male
Female
f 6rttalfe7 years Male
f §rtiaBP years Male
Slrtoft4 years Male
45 to 64 years Male
Piasters Male
20
7
53
38
184
205
232
216
723
612
1,228
987
779
640
168
188
184
167
1,702
1,956
839
1,075
396
605
10
50
10
5
1
4
1
2
1
2
1
2
1
1
2
1
2
1
1
1
1
1
2
1
69
58
58
225
86
140
60
68
80
70
105
90
120
120
132
115
125
90
113
68
95
50
82
55
91
58
118
60
Maximum
700
333
165
225
210
510
450
270
1,035
511
550
525
972
701
1,440
1,380
1,440
1,371
810
1,083
788
606
1,005
1,305
1,015
930
840
630
Mean
116
73
71
225
89
187
95
86
110
95
136
131
146
144
173
148
171
134
151
109
162
99
164
103
178
102
164
88
Female Only data for individuals that spent >0 time outdoors and had 30 or more records are
b The 2-sample Kolmogoroz-Smirnov
Female at a = 0.050.
Data not available.
BBnale = Standard deviation.
COV = Coefficient of variation (SD/mean
Female
(K-S) test H
x 100).
o is that
the distribution
of variable
SD
144
78
68
-
56
153
83
67
114
82
105
111
119
113
148
138
169
153
147
141
176
119
191
133
193
124
156
98
included
COV (%)
125
106
95
0
63
81
87
77
104
86
77
84
81
78
86
93
99
114
97
127
109
120
117
129
109
121
96
111
in the analysis.
1 is the same as variable 2,
Dn
0.24
K-S Test"
/
0.90X
C^ztrrnr
P
0.3964
t T>-ct
Reject
Ho
No
0.42
0.07
0.07
0.09
0.04
0.09
0.17
0.19
0.20
0.14
0.18
0.25
using Dn
0.96
1.00
0.71
1.00
0.74
2.05
3.12
1.80
1.84
4.23
3.90
3.81
0.3158
0.3200
0.6896
0.2705
0.6465
0.0004
0.0001
0.0030
0.0023
O.0001
O.0001
0.0001
(test statistic) and a % test
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
statistic
Source: Graham and McCurdy, 2004.
ft
».
4'
ft
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-72. Time Spent (minutes/day) Indoors
Based on CHAD Data (Doers Only)3
Age Group
Time Spent Indoors
Minimum
Median
Maximum
Mean
SD
COV (%) Participation11 (%)
<1 month
1 to 2 months
3 to 5 months
6 to 11 months
1 year
2 years
3 to 5 years
6 to 10 years
11 to 15 years
16 to 17 years
18 to 20 years
21 to 44 years
45 to 64 years
>64 years
121
14
115
278
668
700
1,977
3,118
1,939
438
485
5,872
3,073
1,758
490
1,125
840
840
315
290
23
7
69
161
512
60
23
600
1,380
1,380
1,385
1,370
1,350
1,319
1,307
1,292
1,300
1,296
1,310
1,317
1,320
1,350
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,440
1,336
1,348
1,359
1,353
1,324
1,286
1,276
1,256
1,255
1,251
1,242
1,259
1,262
1,310
137
105
93
81
107
138
136
153
160
171
180
176
172
141
10
8
7
6
8
11
11
12
13
14
15
14
14
11
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
99.8
100.0
100.0
100.0
100.0
100.0
a Only data for individuals that spent >0 time indoors and had 30 or more records are included in the analysis.
b Participation rates or percent of sample days in the study spending some time (>0 minutes/day) indoors. The mean time spent indoors
for the age group may be obtained by multiplying the participation rate (as a decimal) by the mean time shown above.
N = Sample size.
SD = Standard deviation.
COV = Coefficient of variation (SD/mean x 100).
Source: Graham and McCurdy, 2004.
Page
16-116
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-73. Time Spent (minutes/day) in Motor Vehicles
Based on CHAD Data (Doers Only)3
Age Group
Time Spent in Motor Vehicle
Minimum
Median
Maximum
Mean
SD
COV (%) Participation' (%)
<1 month
1 to 2 months
3 to 5 months
6 to 11 months
1 year
2 years
3 to 5 years
6 to 10 years
11 to 15 years
16 to 17 years
18 to 20 years
21 to 44 years
45 to 64 years
>64 years
80
9
75
226
515
581
1,702
2,766
1,685
400
449
5,429
2,739
1,259
2
20
13
4
1
2
1
1
1
4
4
1
1
4
68
83
60
51
52
54
55
58
60
73
76
80
75
60
350
105
335
425
300
955
1,389
1,214
825
1,007
852
1,440
1,357
798
86
67
71
62
67
73
70
71
76
92
109
105
102
86
32
49
47
50
76
70
68
74
90
106
100
105
85
79
48
69
76
76
104
99
95
97
98
98
96
103
99
66
64
65
81
77
83
86
89
87
91
93
92
89
72
N
SD
COV
Only data for individuals that spent >0 time in motor vehicles and had 30 or more records are included in the analysis.
Participation rates or percent of sample days in the study spending some time (>0 minutes/day) in motor vehicles. The mean time
spent in motor vehicles for the age group may be obtained by multiplying the participation rate (as a decimal) by the mean time
shown above.
= Sample size.
= Standard deviation.
= Coefficient of variation (SD/mean x 100).
Source: Graham and McCurdy, 2004.
Exposure Factors Handbook
September 2011
Page
16-117
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-74. Mean Time Spent (minutes/day) in Various Activity Categories, by Age — Weekday
(children only)
2002-2003
Activity Category
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
Data not provided.
Source: Juster et al, 2004.
6 to 8
years
0
25
68
60
607
406
29
4
16
10
6
1
8
94
9
74
11
2
6
4
9 to 11
years
0
32
66
57
583
398
39
5
25
17
6
1
7
106
10
56
12
1
10
8
12 to 14
years
1
38
68
54
542
395
49
5
25
33
4
1
7
111
24
45
11
0
25
4
15 to 17
years
22
39
73
49
515
352
50
3
53
33
6
2
4
115
39
35
7
0
38
6
1981-1982
6 to 8
years
-
15
49
81
595
292
8
9
-
24
9
2
4
99
-
Ill
5
-
-
-
9 to 11
years
-
18
40
73
548
315
29
9
-
21
8
2
3
146
-
65
9
-
-
-
12 to 14
years
-
27
56
69
473
344
33
9
-
40
7
4
3
142
-
31
10
-
-
-
15 to 17
years
28
34
60
67
499
314
33
3
-
46
11
6
12
108
-
14
12
-
-
-
Page
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-75. Mean
Time Spent (minutes/day) in Various Activity Categories, by Age — Weekend Day
(children only)
2002-2003
Activity Category
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
Data not provided.
Source: Juster et al, 2004.
6 to 8
years
0
81
78
89
666
3
5
41
61
23
12
2
11
155
14
163
14
1
12
9
9 to 11
years
0
91
72
80
644
6
9
37
66
40
12
1
7
184
15
134
15
1
19
8
12 to 14
years
9
100
73
69
633
7
20
36
58
40
12
4
9
181
40
148
13
0
39
9
15 to 17
years
39
79
77
64
629
7
24
30
91
27
11
5
6
162
54
59
7
0
58
11
1981-1982
6 to 8
years
-
27
45
80
641
-
2
56
-
30
23
5
4
136
-
180
9
-
-
-
9 to 11
years
-
51
44
78
596
-
12
53
-
42
39
3
4
185
-
92
10
-
-
-
12 to 14
years
-
72
60
68
604
-
15
32
-
51
25
8
7
169
-
35
10
-
-
-
15 to 17
years
48
60
51
65
562
-
30
37
-
37
26
3
10
157
-
21
18
-
-
-
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-76. Mean Time Spent (minutes/week) in
Various Activity Categories for Children, Ages 6 to 17 Years
Activity Category
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
2002-2003
53
343
493
426
4,092
1,947
238
94
287
179
50
12
48
876
166
485
77
5
165
45
1981-1982
126
223
356
508
3,758
1,581
158
125
132
244
100
27
40
944
39
440
69
3
0
1,206
Source: Juster et al., 2004.
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-77. Time Spent (minutes/2-day period)3 in Various Activities by Children Participating in
the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement (CDS)
Age Group
Television Use
1 to 5 years
6 to 8 years
9 to 12 years
Electronic Game Use
1 to 5 years
6 to 8 years
9 to 12 years
Computer Use
1 to 5 years
6 to 8 years
9 to 12 years
Print Useb
1 to 5 years
6 to 8 years
9 to 12 years
Highly Active Activities'
1 to 5 years
6 to 8 years
9 to 12 years
Moderately Active Activities'1
1 to 5 years
6 to 8 years
9 to 12 years
Sedentary Activities'
1 to 5 years
6 to 8 years
9 to 12 years
Boys (A? = 1,444)
Mean8
197
263
251
8
44
57
7
13
27
21
20
19
42
107
137
55
31
40
55
75
110
Girls (N
Standard Deviation Mean8
168
165
185
38
113
102
28
43
71
32
37
47
74
123
149
81
65
73
71
77
109
184
239
266
5
14
18
7
8
15
23
20
29
34
62
63
59
37
46
54
80
122
= 1,387)
Standard Deviation
163
159
194
40
39
47
35
28
43
34
32
56
78
92
88
92
69
89
71
84
111
a Means represent minutes spent in each activity over a 2-day period (1 weekday and 1 weekend day).
b Print use represents time spent using print media including reading and being read to.
' Includes all sport activities such as basketball, soccer, swimming, running or bicycling.
d Includes activities such as singing, camping, taking music lessons, fishing, and boating.
' Includes activities such as playing board games, doing puzzles, talking on the phone, and relaxing.
jV = Sample size.
Source: Vanderwater et al., 2004.
Exposure Factors Handbook
September 2011
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Page Exposure Factors Handbook
16-122 June 2011
Table 16-78. Annual Average Time Spent (hours/day) On Various Activities According to Age, Race, Ethnicity, Marital Status, and Educational
Level (ages 15 years and over)
Characteristic Personal Eating and Household Purchasing Caring for Caring for and Working on Educational Organizational Leisure Telephone Other
care3 Drinkingb Activity0 Goods and and Helping Helping WorkRrelated Activity11 Civic and and Call, Mail, Activity not
Services'1 Household Non-Household Activity8 Religious Sportf and E-mailk Elsewhere
Member6 Memberf Activity1 Classified1
15+ 9.41 1.23 1.79 0.81 0.53 0.21 3.75 0.49 0.30 5.09 0.19 0.21
15 to 19 10.30 1.07 0.76 0.56 0.15 0.21 1.39 3.29 0.34 5.40 0.33 0.22
20to24 9.64 1.21 1.05 0.67 0.51 0.20 4.23 0.80 0.21 5.03 0.19 0.24
25to34 9.31 1.19 1.55 0.81 1.07 0.12 4.77 0.39 0.16 4.30 0.14 0.17
35to44 9.12 1.18 1.87 0.87 0.98 0.19 4.96 0.15 0.30 4.09 0.13 0.16
45 to 54 9.10 1.17 1.97 0.82 0.36 0.24 5.06 0.09 0.29 4.52 0.17 0.20
55 to 64 9.19 1.31 2.11 0.91 0.16 0.28 3.80 0.04 0.39 5.41 0.18 0.20
65 to 74 9.68 1.44 2.64 0.93 0.13 0.30 0.94 0.05 0.38 6.97 0.24 0.29
75+ 9.83 1.50 2.32 0.80 0.12 0.21 0.34 0.06 0.43 7.82 0.30 0.27
Sex
Male 9.21 1.25 1.33 0.64 0.33 0.18 4.53 0.45 0.29 5.47 0.12 0.20
Female 9.59 1.22 2.23 0.96 0.71 0.24 3.02 0.53 0.31 4.72 0.26 0.22
Race/Ethnicity
White 9.30 1.28 1.85 0.81 0.53 0.21 3.76 0.47 0.29 5.09 0.18 0.21
Black 10.08 0.87 1.38 0.75 0.46 0.20 3.54 0.43 0.37 5.49 0.25 0.18
Hispanic/Latino 9.67 1.18 1.85 0.77 0.60 0.15 3.92 0.69 0.23 4.63 0.13 0.18
Marital Status
Married 9.12 1.28 2.09 0.88 0.75 0.21 4.08 0.11 0.33 4.79 0.14 0.21
Other 9.75 1.18 1.43 0.72 0.25 0.22 3.34 0.94 0.27 5.45 0.25 0.20
Education
< High School grad 9.86 1.10 2.38 0.80 0.50 0.20 2.57 0.04 0.25 6.01 0.10 0.17
HS grad, no college 9.42 1.19 2.05 0.76 0.46 0.25 3.58 0.07 0.28 5.57 0.15 0.21
Some college 9.21 1.24 1.94 0.92 0.58 0.23 4.25 0.22 0.29 4.76 0.19 0.18
BS or higher 8.94 1.41 1.77 0.91 0.71 0.18 4.72 0.22 0.37 4.33 0.22 0.23
a Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities.
b Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent purchasing meals, snacks, or beverages.
c Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and renovation.
d Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair salons, barbershops, day spas, tanning salons), household services (e.g.,
housecleaning, lawn care and landscaping, pet care, dry cleaning, vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses, or paying fines).
e Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to child or adult, attending to health care needs, dropping off, picking up, or
waiting for children).
f Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with children, reading to child or adult, attending to health care needs, dropping off,
picking up or waiting for children). Does not include activities done through a volunteer organization.
8 Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related activities.
11 Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, except sports.
1 Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through participating in religious or spiritual activities (e.g., church choir, youth
groups, praying).
1 Includes sports, exercise, and recreation. This category is broken down into subcategories for the 1 5 to 19 years old age category.
k Includes telephone use, mail, and e-mail. Does not include communications related to purchase of goods and services or those related to work or volunteering.
1 Includes residual activities that could not be coded or where information was missing.
Source: DDL, 2007.
Chapter 16 — Activity Factors
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-79. Annual Average Time Use by the U.S. Civilian Population, Ages 15 Years and Older
hours/day
Activity
Total Male Female Weekday Weekend and Holiday
Personal Care8 9.41 9.21 9.59 9.12
sleeping 8.63 8.56 8.69 8.33
Eating and Drinking6 1.23 1.25 1.22 1.18
Household Activities' 1.79 1.33 2.23 1.66
housework 0.61 0.25 0.95 0.57
food preparation/cleanup 0.53 0.29 0.75 0.51
lawn and garden care 0.20 0.26 0.14 0.16
household management 0.13 0.11 0.14 0.12
Purchasing Goods and Services'1 0.81 0.64 0.96 0.76
consumer goods purchase 0.40 0.29 0.51 0.34
professional/personal goods purchase 0.09 0.06 0.11 0.10
Caring for and Helping Household Members' 0.53 0.33 0.71 0.56
caring for household children 0.41 0.24 0.57 0.43
Caring for and Helping Non-Household Members' 0.21 0.18 0.24 0.19
caring for non-household adults 0.07 0.07 0.08 0.06
Working on Work-related Activities8 3.75 4.53 3.02 4.77
Working 3.40 4.10 2.74 4.33
Educational Activities'1 0.49 0.45 0.53 0.63
attending classes 0.30 0.29 0.32 0.42
homework and research 0.15 0.12 0.17 0.16
Organizational Civic and Religious Activities' 0.30 0.29 0.31 0.20
religious and spiritual activities 0.12 0.11 0.13 0.04
volunteering (organizational and civic activities) 0.13 0.13 0.13 0.13
Leisure and Sportsj 5.09 5.47 4.72 4.54
socializing and communicating 0.76 0.71 0.80 0.60
watching TV 2.58 2.80 2.36 2.35
sports, exercise, recreation 0.28 0.38 0.18 0.26
Telephone Calls, Mail, and E-mailk 0.19 0.12 0.26 0.20
Other Activities not Elsewhere Classified1 0.21 0.20 0.22 0.20
10.08
9.32
1.37
2.11
0.70
0.57
0.27
0.15
0.93
0.53
0.04
0.45
0.37
0.26
0.11
1.36
1.23
0.16
0.04
0.10
0.53
0.30
0.15
6.37
1.11
3.10
0.33
0.17
0.22
Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities.
Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent
purchasing meals, snacks, or beverages.
Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and
renovation.
Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair
salons, barbershops, day spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry
cleaning, vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses
or paying fines).
Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading
to child or adult, attending to health care needs, dropping off, picking up or waiting for children).
Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with
children, reading to child or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include
activities done through a volunteer organization.
Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related
activities.
Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities,
except sports.
Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through
participating in religious or spiritual activities (e.g., church choir, youth groups, praying).
Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category.
Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related
to work or volunteering.
Includes residual activities that could not be coded or where information was missing.
Source: POL, 2007.
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-80. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years
Activity
hours/day
Male
Female
All
Personal Care8
Eating and Drinking1"
Household Activities'
Purchasing Goods and Services'1
Caring for and Helping Household Members'
Caring for and Helping Non-Household Members'
Working on Work-related Activities8
Educational Activities'1
Organizational Civic and Religious Activities'
Leisure and SportsJ
total leisure and sports - weekdays
total leisure and sports - weekends
sports, exercise, recreation - weekdays
sports, exercise, recreation - weekends/holidays
socializing and communicating - weekdays
socializing and communicating, - weekends/holidays
watching TV - weekdays
watching TV - weekends/holidays
reading - weekdays
reading - weekends/holidays
relaxing, thinking - weekdays
relaxing, thinking - weekends/holidays
playing games, computer use for leisure - weekdays
playing games, computer use for leisure - weekends/holidays
other sports/leisure including travel - weekdays
other sports/leisure including travel - weekends/holidays
Telephone Calls, Mail, and E-mailk
Other Activities not Elsewhere Classified1
10.26
1.02
0.61
0.38
0.10
0.20
1.53
3.08
0.34
6.02
10.34
1.11
0.92
0.74
0.19
0.23
1.24
3.51
0.33
4.75
0.24
0.23
0.42
0.21
10.30
1.07
0.76
0.56
0.15
0.21
1.39
3.29
0.34
5.40
4.85
6.68
0.58
0.69
0.76
1.32
1.96
2.45
0.11
0.11
0.15
0.13
0.69
1.00
0.61
0.98
0.33
0.22
Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities.
Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent
purchasing meals, snacks, or beverages.
Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and
renovation.
Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair
salons, barbershops, day spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry
cleaning, vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses or
paying fines).
Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to
child or adult, attending to health care needs, dropping off, picking up or waiting for children).
Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with
children, reading to child or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include
activities done through a volunteer organization.
Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related
activities.
Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities,
except sports.
Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through
participating in religious or spiritual activities (e.g., church choir, youth groups, praying).
Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category.
Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related to
work or volunteering.
Includes residual activities that could not be coded or where information was missing.
Source: DOL, 2007.
Page
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September 2011
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-81.
Age
(years)
9
11
12
15
SD
Source:
Mean
Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity
(children only)
Number of Participants
Boys
555
544
532
503
Girls
543
540
532
506
Weekday
Mean (SD)
Boys
190.8(53.2)
133.0(42.9)
105.3(40.2)
58.2(31.8)
Girls
173.3(46.6)
115.6(36.3)
86.0(32.5)
38.7(23.6)
Both
181.8(50.6)
124.1(40.6)
95.6(37.8)
49.2(29.9)
Weekend
Mean (SD)
Boys
184.3(68.6)
127.1(59.5)
93.4(55.3)
43.2(38.0)
Girls
173.3(64.3)
112.6(53.2)
73.9(45.8)
25.5(23.3)
Both
178.6(66.6)
119.7(56.8)
83.6(51.7)
35.1(33.3)
= Standard deviation.
Nader etal., 2008.
Table 16-82. Occupational Tenure of Employed Individuals"
Age Group
(years) jV
16 to 24 19,090
25 to 29 16,326
30 to 34 15,833
35 to 39 14,674
40 to 44 11,871
45 to 49 9,350
50 to 54 7,684
55 to 59 6,914
60 to 64 4,500
65 to 69 1,692
70 and older 1,146
Total 109,090
a Working population =109
jV = Number of individuals.
Source: Carey, 1988.
by Age and Sex
Median Tenure (years)
All Workers
1.9
4.4
6.9
9.0
10.7
13.3
15.2
17.7
19.4
20.1
21.9
6.6
1 million persons.
N
9,520
8,974
8,971
8,109
6,463
5,208
4,341
4,006
2,673
1,000
678
60,242
Men
2.0
4.6
7.6
10.4
13.8
17.5
20.0
21.9
23.9
26.9
30.5
7.9
N
9,270
7,353
6,863
6,565
5,408
4,152
3,343
2,908
1,827
692
467
41,949
Women
1.9
4.1
6.0
7.0
8.0
10.0
10.8
12.4
14.5
15.6
18.8
5.4
Exposure Factors Handbook
September 2011
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Chapter 16—Activity Factors
Table 16-83. Occupational Tenure for Employed Individuals" Grouped by Sex and Race
Median Tenure (years)
Race N
White 95,044
Black 10,851
Hispanic 7,198
a Working population =109
jV = Number of individuals.
Source: Carey, 1988.
All
Individuals jV
6.7 53,096
5.8 5,447
4.5 4,408
1 million persons.
Men jV Women
8.3 41,949 5.4
5.8 5,404 5.8
5.1 2,790 3.7
Table 16-84. Occupational Tenure for Employed Individuals3 Grouped by Sex and Employment Status
Median Tenure (years)
Employment
Status W
Full-Time 93,665
Part-Time 15,425
a Working population =109
N = Number of individuals.
Source: Carey, 1988.
All
Individuals N
7.2 55,464
3.1 4,778
1 million persons.
Men N Women
8.4 38,201 5.9
2.4 10,647 3.6
Table 16-85. Occupational Tenure of Employed Individuals3 Grouped by Major Occupational Groups and Age
Median Tenure (years)
Age Group (years)
Occupational Group
Executive, Administrative, and Managerial
Professional Specialty
Technicians and Related Support
Sales Occupations
Administrative Support, including Clerical
Service Occupations
Precision Production, Craft, and Repair
Operators, Fabricators, and Laborers
Farming, Forestry, and Fishing
Totalb
8.4
9.6
6.9
5.1
5.4
4.1
9.3
5.5
10.4
16-24
2.4
2.0
2.2
1.7
2.1
1.7
2.6
1.7
2.9
25-34
5.6
5.7
5.7
4.7
5.0
4.4
7.1
4.6
7.9
35^14
10.1
12.0
10.9
7.7
7.6
6.9
13.5
9.1
13.5
45-54
15.1
18.2
17.7
10.5
10.9
9.0
19.9
13.7
20.7
55-64
17.9
25.6
20.8
15.5
14.6
10.6
25.7
18.1
30.5
65+
26.3
36.2
22.2
21.6
15.4
10.4
30.1
14.7
39.8
a Working population = 109.1 million persons.
b Includes all workers 16 years and older.
Source: Carey, 1988.
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-86. Voluntary
Age Group (years)
16 to 24
25 to 34
35 to 44
45 to 54
55 to 64
64 and older
Total, age 16 and older
a Working population =100
b Occupational mobility rate
another occupation.
Source: Carey, 1990.
Occupational Mobility Rates for Workers" Age 16 Years and Older
Occupational Mobility Rateb
(Percent)
12.7
6.6
4.0
1.9
1.0
0.3
5.3
1 million persons.
= percentage of persons employed in an occupation who had voluntarily entered it from
Exposure Factors Handbook Page
September 2011 16-12 7
-------
oo
§
ri
I!
Table 16-87. Descriptive Statistics for Residential Occupancy Period (years)
N Mean 5th
Both sexes 500,000 11.7 2
Male only 244,274 11.1 2
Female only 255,726 12.3 2
= Number of simulated persons.
Source: Johnson and Capel, 1992.
Percentiles
10th 25th 50th 75th 90th 95th 98th 99th 99.5th 99.8th
2 3 9 16 26 33 41 47 51 55
2 4 8 15 24 31 39 44 48 53
2 5 9 17 28 35 43 49 53 58
99.9th
59
56
61
^nd
Largest
Value
75
73
75
Max.
87
73
87
s
I
*
I
ri
ri
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Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-88.
Descriptive Statistics
for Both Sexes by Current Age
Residential Ooccupancy
Current
age, years
3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
63
66
69
72
75
78
81
84
87
90
All ages
Source: Johnson and Capel,
Mean
6.5
8.0
8.9
9.3
9.1
8.2
6.0
5.2
6.0
7.3
8.7
10.4
12.0
13.5
15.3
16.6
17.4
18.3
19.1
19.7
20.2
20.7
21.2
21.6
21.5
21.4
21.2
20.3
20.6
18.9
11.7
1992.
25
3
4
5
5
5
4
2
2
3
3
4
5
5
6
7
8
9
9
10
11
11
12
12
13
13
12
11
11
10
8
4
50
5
7
8
9
8
7
4
4
5
6
7
8
9
11
13
14
15
16
17
18
19
20
20
20
20
19
20
19
18
15
9
Period (years)
Percentiles
75 90
8 13
10 15
12 16
13 16
12 16
11 16
8 13
6 11
8 12
9 14
11 17
13 21
15 24
18 27
20 31
22 32
24 33
25 34
26 35
27 35
27 36
28 36
29 37
29 37
29 38
29 38
29 39
28 37
29 39
27 40
16 26
95
17
18
18
18
18
19
17
15
16
19
23
28
31
35
38
39
39
40
41
40
41
41
42
43
43
44
45
44
46
47
33
99
22
22
22
23
23
23
23
25
27
32
39
47
48
49
52
52
50
50
51
51
51
50
50
53
53
53
55
56
57
56
47
Exposure Factors Handbook
September 2011
Page
16-129
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-89. Residence Time of Owner/Renter Occupied Units
Year Household Moved into Unit
2005-2009
2000-2004
1995-1999
1990-1994
1985-1989
1980-1984
1975-1979
1970 - 1974
1960 -1969
1950-1959
1940-1949
1939 or earlier
Total Occupied Units (number in thousands)
33,543
28,695
15,120
9,631
6,459
3,703
4,412
2,979
3,661
1,892
460
137
Total 110,692
Source: U.S. Census Bureau, 2008a.
Table 16-90. Percent of Householders Living in Houses for Specified Ranges of Time, and Statistics for
Years Lived in Current Home
Years Lived in Current Home
Percent of Total Households
CM
5-9
10-14
15-19
20-24
25-29
30-34
3 5^4
45-54
55-64
65-74
>75
30.3
25.9
13.7
8.7
5.8
3.3
4.0
2.7
3.3
1.7
0.4
0.1
Total" 99.9
Statistics for Years Lived in Current Home
N
110,692
Mean"
13
SO'Percentile1'
90th Percentileb
32
95th Percentileb
46
99th Percentileb
62
a Total does not equal 100 due to rounding errors.
b The mean, 50th and 90th percentiles were calculated for the number of years lived in current house by apportioning
the total sample size (110,692 households) to the indicated percentile associated with the applicable range of years
lived in the current home, assuming an even distribution.
Source: Adapted from U.S. Census Bureau, 2008a.
Page
16-130
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-91. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in
Survey3
Households
All households
Renters
Owners
Farms
Urban
Rural
Northeast region
Midwest region
South region
West region
Average Total Residence
Time
T (years)
4.55 ±0.60
2.35 ±0.14
11. 36 ±3. 87
17.31 ±13. 81
4.19±0.53
7.80 ±1.17
7.37 ±0.88
5.11 ±0.68
3.96 ±0.47
3.49 ±0.57
a Values of the average current residence time,
Source: Israeli and Nelson,
1992.
SD
ST
8.68
4.02
13.72
18.69
8.17
11.28
11.48
9.37
8.03
6.84
TCR, are
Average Current
Residence
TCR (years)
10.56 ±0.10
4.62 ±0.08
13. 96 ±0.12
18.75 ±0.38
10.07±0.10
12.06 ±0.23
12.64 ±0.12
11.15±0.10
10.12 ±0.08
8.44 ±0.11
given for comparison.
Households (percent)
1985
100.0
36.5
63.5
2.1
74.9
25.1
21.2
25.0
34.0
19.8
1987
100.0
36.0
64.0
1.9
74.5
25.5
20.9
24.5
34.4
20.2
Table 16-92. Total Residence Time, T (years), Corresponding to Selected Values of R(t)a by Housing
Category
R(t) =
All households
Renters
Owners
Farms
Urban
Rural
Northeast region
Midwest region
South region
West region
0.05
23.1
8.0
41.4
58.4
21.7
32.3
34.4
25.7
20.7
17.1
a R(t) = fraction of households living
Source: Israeli and Nelson,
1992.
0.1
12.9
5.2
32.0
48.3
10.9
21.7
22.3
15.0
10.8
8.9
in the same residence
0.25
3.7
2.6
17.1
26.7
3.4
9.1
7.5
4.3
3.0
2.9
for T years or more.
0.5
1.4
1.2
5.2
10.0
1.4
3.3
2.8
1.6
1.2
1.2
0.75
0.5
0.5
1.4
2.4
0.5
1.2
1.0
0.6
0.4
0.4
Exposure Factors Handbook Page
September 2011 16-131
-------
Exposure Factors Handbook
Chapter 16—Activity Factors
Table 16-93. Summary of Residence
Number of Years Lived in Previous House
1 year or less
2-3
4-7
8-9
10 years or more
Time of Recent Home Buyers (1993)
Percent of Respondents
2
16
40
10
32
Source: NAR, 1993.
1 year or less
2-3 Years
4-7 Years
8-9 Years
10 or More Years
Total
Median
Table 16-94. Tenure in Previous
1987
5
25
36
10
24
100
6
Home (Percentage
1989
Percent
8
15
22
11
34
100
Years
6
Distribution)
1991
4
21
37
9
29
100
6
1993
2
16
40
10
32
100
6
Source: NAR, 1993.
Table 16-95. Number of Miles Moved (Percentage Distribution)
Mile
Less than 5 miles
5-9 miles
10-1 9 miles
20-34 miles
35-50 miles
5 1-1 00 miles
Over 100 miles
Total
Median
Mean
All Buyers
29
20
18
9
2
5
17
100
9
200
First- Time
Buyer
33
25
20
11
2
2
6
100
8
110
Repeat Buyer
Percent
27
16
17
8
2
6
24
100
Miles
11
270
New Home
Buyer
23
18
20
12
2
6
19
100
11
230
Existing Home
Buyer
31
20
17
9
3
4
16
100
8
190
Source: NAR, 1993.
Page
16-132
Exposure Factors Handbook
September 2011
-------
II
il
I
Table 16-96. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational Attainment, Marital Status, Nativity, Tenure,
and Poverty Level: 2006 to 2007 (numbers in thousands)
Population
Total 1+ years
Sex
Male
Female
Age (years)
1 to 4 years
5 to 9 years
10 to 14years
15 to 17 years
1 8 to 1 9 years
20 to 24 years
25 to 29 years
30 to 34 years
35 to 39 years
40 to 44 years
45 to 49 years
50 to 54 years
55 to 59 years
60to61years
62 to 64 years
65 to 69 years
70 to 74 years
75 to 79 years
80 to 84 years
85+ years
Educational Attainment
Not a high school
graduate
High school graduate
Some college or AA
degree
Bachelor's degree
Prof or graduate degree
Persons age 1 to 24
Total
N
292,74
9
143,58
9
149,16
0
16,455
19,830
20,444
13,297
7,873
20,532
20,666
19,202
20,907
21,856
22,643
20,819
18,221
6,093
7,877
10,629
8,369
7,567
5,513
3,958
27,742
61,490
49,243
36,658
19,184
98,431
Mover
N
38,681
19,457
19,224
3,217
3,161
2,517
1,465
1,330
5,516
5,316
3,767
2,962
2,456
1,963
1,612
1,171
381
386
496
357
233
219
159
3,458
6,435
5,534
4,062
1,985
17,205
To
(of
total)
13%
14%
13%
20%
16%
12%
11%
17%
27%
26%
20%
14%
11%
9%
8%
6%
6%
5%
5%
4%
3%
4%
4%
12%
10%
11%
11%
10%
17%
Same County
N
25,192
12,579
12,613
2,188
2,092
1,735
1,057
898
3,623
3,335
2,374
1,877
1,567
1,362
1,119
706
212
201
286
179
153
121
108
2,431
4,398
3,475
2,290
1,004
11,593
70
(of
movers)
65%
65%
66%
68%
66%
69%
72%
68%
66%
63%
63%
63%
64%
69%
69%
60%
56%
52%
58%
50%
66%
55%
68%
70%
68%
63%
56%
51%
67%
Different County,
Same State
N
7,436
3,693
3,743
577
614
441
224
252
1,069
1,061
789
587
480
304
292
258
82
98
110
79
41
53
24
575
1,207
1,167
910
399
3,177
/O
(of
movers)
19%
19%
19%
18%
19%
18%
15%
19%
19%
20%
21%
20%
20%
15%
18%
22%
22%
25%
22%
22%
18%
94.0/
15%
17%
19%
21%
22%
20%
18%
Different State,
Same Division
N
1,446
771
675
117
121
92
50
40
168
219
140
104
102
74
55
57
30
19
16
24
4
10
2
103
221
206
231
97
589
/O
(of
movers)
4%
4%
4%
4%
4%
4%
3 TO
3%
3 TO
4%
4%
4%
4%
4%
3%
5%
8%
5%
3%
7%
2%
5%
1%
3 TO
3%
4%
6%
5%
3%
Different
Division,
Same Region
N
968
505
463
81
73
62
22
25
157
136
106
84
60
42
42
37
9
1
5
17
6
4
-
33
145
145
124
102
419
70
(of
movers)
3%
3%
2%
3 TO
2%
907
2%
2%
3%
3%
3 /o
3%
907
2%
3%
3%
90/
0%
1%
5%
3 /o
907
-
1%
907
3 70
3%
5%
7°/
Different
Region
N
2,448
1,220
1,228
184
179
139
75
68
320
339
221
187
178
131
76
86
39
49
63
43
21
26
22
137
353
411
336
246
965
70
(of
movers)
6%
6%
6%
6%
6%
6%
5%
5%
6%
6%
6%
6%
7%
7%
5%
7%
10%
13%
13%
12%
9%
12%
14%
4%
5%
7%
8%
12%
6%
Abroad
N
1,191
689
502
72
81
47
37
47
179
226
137
121
68
49
27
27
10
18
16
15
7
5
3
178
112
130
172
137
462
70
(of
movers)
3%
4%
3%
2%
3%
2%
3 /o
4%
3%
4%
4%
4%
3%
2%
7°/
2%
3%
5%
3%
4%
3%
2%
2%
5%
2%
2%
4%
7%
3%
Q
j
I
I
ri
-------
§
s
Table 16-96. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational Attainment, Marital Status, Nativity, Tenure,
and Poverty Level: 2006 to 2007 (numbers in thousands) (continued)
Different County,
Total
Population N
Marital Status
121,39
Married, spouse present 0
Married, spouse absent 3,472
Widowed 13,920
Divorced 22,867
Separated 5,047
Never married 69,324
Persons age 1 to 14 56,730
Nativity
255,50
Native 1
Foreign born 37,248
Naturalized US citizen 14,525
Not a US citizen 22,723
Tenure
Owner-occupied housing 207,77
unit 4
Renter-occupied housing
unit 81,351
No cash renter-occupied
housing unit 3,624
Poverty Status
Below 100% of poverty 35,924
100% to 149% of
poverty 26,183
150% of poverty and 230,64
above 2
Represents 0 or rounds to 0.
N = Number of respondents.
Source: U.S. Census Bureau, 2008b.
Mover
N
10,671
805
802
3,483
1,246
12,779
8,895
33,023
5,658
1,161
4,497
13,760
24,228
694
8,777
4,705
25,199
/O
(of
total)
9%
23%
6%
15%
25%
18%
16%
13%
15%
8%
20%
7%
30%
19%
24%
18%
11%
Same County
N
6,434
501
533
2,369
911
8,429
6,015
21,603
3,589
768
2,821
8,467
16,353
372
6,041
3,312
15,839
/O
(of
movers)
60%
62%
66%
68%
73%
66%
68%
65%
63%
66%
63%
62%
67%
54%
69%
70%
63%
Same State
N
2,220
90
136
702
213
2 442
1,632
6,671
765
212
553
2,881
4,374
181
1,484
832
5,120
/O
(of
movers)
21%
11%
17%
20%
17%
19%
18%
20%
14%
18%
12%
21%
18%
26%
17%
18%
20%
Different State,
Same Division
N
502
31
34
93
29
427
330
1,279
167
41
126
595
806
45
270
128
1,048
/O
(of
movers)
5%
4%
4%
3%
2%
3%
4%
4%
3%
4%
3%
4%
3 /o
6%
3 /o
3%
4%
Different
Division, Different
Same Region Region
N
338
11
8
69
16
310
216
904
64
31
33
408
547
13
166
84
718
/O
(of
movers) N
3% 808
1% 73
1% 68
2% 200
1% 57
2% 739
2% 502
3% 2,180
1% 268
3% 76
1% 192
3% 1,027
2% 1,371
2% 49
2% 392
2% 215
3% 1,841
/O
(of
movers)
8%
9%
8%
6%
5%
6%
6%
7%
5%
7%
4%
7%
6%
7%
4%
5%
7%
Abroad
N
369
98
22
50
19
433
200
387
804
31
772
381
776
33
423
136
632
/O
(of
movers)
3%
12%
3%
1%
2%
3%
2%
1%
14%
3%
17%
3%
3%
5%
5%
3%
3%
s
I
*
I
ri
ri
-------
II
§
s
I
Table 16-97. Distance of Intercounty Move", by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007
(numbers in thousands)
Population
Intercounty Movers 1+ years
Sex
Male
Female
Age
Under 16 years
16 to 19 years
20 to 24 years
25 to 29 years
30 to 44 years
45 to 64 years
65 to 74 years
75+ years
Race and Hispanic Origin
White alone
Black or African American alone
Asian alone
All remaining single races and all race
combinations11
White alone, not Hispanic or Latino
Hispanic or Latino0
White alone or in combination with 1 or more other
races
Black or African American alone or in combination
with 1 or more other races
Asian alone or in combination with 1 or more other
races
Total
N
12,299
6,190
6,109
2,809
629
1,714
1,755
3,040
1,782
357
213
9,730
1,626
515
427
8,290
1,575
9,986
1,733
573
Less than 50 miles
N
5,149
2,554
2,595
1,230
279
720
792
1,295
633
128
71
4,049
729
205
166
3,527
578
4,161
111
223
%
42%
41%
42%
44%
44%
42%
45%
43%
36%
36%
33%
42%
45%
40%
39%
43%
37%
42%
45%
39%
50 to 199 miles
N
2,582
1,324
1,258
520
148
436
347
618
408
68
37
2,064
285
120
113
1,697
401
2,130
312
146
%
21%
21%
21%
19%
24%
25%
20%
20%
23%
19%
17%
21%
18%
23%
26%
20%
25%
21%
18%
25%
200 to 499 miles
N
1,802
894
909
455
82
185
215
458
312
66
30
1,382
320
51
49
1,156
232
1,405
329
59
%
15%
14%
15%
16%
13%
11%
12%
15%
18%
18%
14%
14%
20%
10%
11%
14%
15%
14%
19%
10%
500 miles or more
N
2,765
1,418
1,347
603
120
373
400
669
429
95
76
2,234
293
138
99
1,910
364
2,290
315
144
%
22%
23%
22%
21%
19%
22%
23%
22%
24%
27%
36%
23%
18%
27%
23%
23%
23%
23%
18%
25%
Q
j
I
I
ri
ft
-------
§
s
a
A,
Table 16-97. Distance of Intercounty Move", by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007 (continued)
(numbers in thousands)
Population
Educational Attainment
Not a high school graduate
High school graduate
Some college or AA degree
Bachelor's degree
Prof, or graduate degree
Persons age 1 to 24
Marital Status
Married, spouse present
Married, spouse absent
Widowed
Divorced
Separated
Never married
Persons age 1 to 14
Nativity
Native
Foreign bom
Naturalized U.S. citizen
Not a US citizen
Tenure
Owner-occupied housing unit
Renter-occupied housing unit
No cash renter-occupied housing unit
Poverty Status
Below 100% of poverty
100% to 149% of poverty
150% of poverty and above
Total
N
848
1,926
1,929
1,601
844
5,151
3,868
206
246
1,065
316
3,917
2,680
11,034
1,265
361
904
4,912
7,099
288
2,313
1,258
8,728
Less than 50 miles
N
390
776
836
651
268
2,229
1,500
57
78
493
146
1,691
1,184
4,627
523
156
367
2,083
2,962
104
967
625
3,558
%
46%
40%
43%
41%
32%
43%
39%
28%
32%
46%
46%
43%
44%
42%
41%
43%
41%
42%
42%
36%
42%
50%
41%
50 to 199 miles
N
197
414
376
340
151
1,104
834
44
60
221
57
867
500
2,299
283
63
220
950
1,554
78
576
245
1,761
%
23%
21%
19%
21%
18%
21%
22%
21%
24%
21%
18%
22%
19%
21%
22%
17%
24%
19%
22%
27%
25%
19%
20%
200 to 499 miles
N
126
351
254
210
140
721
560
31
45
158
66
517
426
1,646
156
45
111
742
1,019
41
353
176
1,274
%
15%
18%
13%
13%
17%
14%
14%
15%
18%
15%
21%
13%
16%
15%
12%
12%
12%
15%
14%
14%
15%
14%
15%
500 miles or more
N
135
385
463
400
286
1,096
975
74
63
193
47
843
570
2,462
303
96
206
1,137
1,564
64
417
212
2,136
%
16%
20%
24%
25%
34%
21%
25%
36%
26%
18%
15%
22%
21%
22%
24%
27%
23%
23%
22%
22%
18%
17%
24%
s
I
*
I
ri
ri
-------
II
§
s
I
Table 16-97. Distance of Intercounty Move", by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007 (continued)
(numbers in thousands)
Total Less than 50 miles 50 to 199 miles 200 to 499 miles 500 miles or more
Population
N
N
N
N
N
N
State of Residence 1 Year Ago
Same state
Different state
7,436
4,862
4,741
408
64%
8%
2,059
524
28%
11%
627
1,175
8%
24%
9 0%
2,756 57%
a The estimated distance in miles of an intercounty move is measured from the county of previous residence's geographic population centroid
to the county of current residence's geographic population centroid.
b Includes American Indian and Alaska Native alone, Native Hawaiian and Other Pacific Islander alone, and 2 or More Races.
0 Hispanics or Latinos may be of any race.
Source: U.S. Census Bureau, 2008b.
Q
j
I
I
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TABLE OF CONTENTS
LIST OF TABLES 17-ii
17. CONSUMER PRODUCTS 17-1
17.1. INTRODUCTION 17-1
17.1.1. Background 17-1
17.1.2. Additional Sources of Information 17-1
17.2. RECOMMENDATIONS 17-2
17.3. CONSUMER PRODUCTS USE STUDIES 17-2
17.3.1. CTFA(1983) 17-2
17.3.2. Westat (1987a) 17-2
17.3.3. Westat (1987b) 17-3
17.3.4. Westat (1987c) 17-4
17.3.5. Abt(1992) 17-4
17.3.6. U.S. EPA (1996) 17-5
17.3.7. Bass etal. (2001) 17-6
17.3.8. Weegels and van Veen (2001) 17-6
17.3.9. Loretz et al. (2005) 17-6
17.3.10. Loretz et al. (2006) 17-7
17.3.11. Hall et al. (2007) 17-7
17.3.12. Loretz et al. (2008) 17-8
17.3.13. Sathyanarayana et al. (2008) 17-8
17.4. REFERENCES FOR CHAPTER 17 17-8
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LIST OF TABLES
Table 17-1. Consumer Products Commonly Found in Some U.S. Households3 17-10
Table 17-2. List of Product Categories in the Simmons Study of Media and Markets 17-12
Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products 17-13
Table 17-4. Frequency of Use for Household Solvent Products (users only) 17-16
Table 17-5. Exposure Time of Use for Household Solvent Products (users only) 17-17
Table 17-6. Amount of Products Used for Household Solvent Products (users only) 17-18
Table 17-7. Time Exposed After Duration of Use for Household Solvent Products (users only) 17-19
Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household Cleaning
Products 17-20
Table 17-9. Percentile Rankings for Total Exposure Time in Performing Household Tasks 17-22
Table 17-10. Mean Percentile Rankings for Frequency of Performing Household Tasks 17-23
Table 17-11. Mean and Percentile Rankings for Exposure Time per Event of Performing Household Tasks 17-24
Table 17-12. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning3 17-24
Table 17-13. Total Exposure Time of Painting Activity of Interior Painters (hours) 17-25
Table 17-14. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions Spent
Painting per Year 17-25
Table 17-15. Amount of Paint Used by Interior Painters 17-25
Table 17-16. Frequency of Use and Amount of Product Used for Adhesive Removers 17-26
Table 17-17. Adhesive Remover Usage by Sex 17-26
Table 17-18. Frequency of Use and Amount of Product Used for Spray Paint 17-27
Table 17-19. Spray Paint Usage by Sex 17-27
Table 17-20. Frequency of Use and Amount of Product Used for Paint Removers/Strippers 17-28
Table 17-21. Paint Stripper Usage by Sex 17-28
Table 17-22. Number of Minutes Spent Using Any Microwave Oven (minutes/day) 17-29
Table 17-23. Number of Minutes Spent in Activities Working With or Near Freshly Applied Paints
(minutes/day) 17-29
Table 17-24. Number of Minutes Spent in Activities Working With or Near Household Cleaning Agents Such
as Scouring Powders or Ammonia (minutes/day) 17-29
Table 17-25. Number of Minutes Spent in Activities (at home or elsewhere) Working with or Near Floorwax,
Furniture Wax, or Shoe Polish (minutes/day) 17-30
Table 17-26. Number of Minutes Spent in Activities Working with or Near Glue (minutes/day) 17-30
Table 17-27. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes, or Strong Smelling
Chemicals (minutes/day) 17-30
Table 17-28. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers
(minutes/day) 17-31
Table 17-29. Number of Minutes Spent in Activities Working with or Near Gasoline or Diesel-Powered
Equipment, Besides Automobiles (minutes/day) 17-31
Table 17-30. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug Sprays
or Bug Strips (minutes/day) 17-31
Table 17-31. Number of Respondents Using Cologne, Perfume, Aftershave, or Other Fragrances at Specified
Daily Frequencies 17-32
Table 17-32. Number of Respondents Using Any Aerosol Spray Product or Personal Care Item Such as
Deodorant or Hair Spray at Specified Daily Frequencies 17-32
Table 17-33. Number of Respondents Using a Humidifier at Home 17-32
Table 17-34. Number of Respondents Indicating Pesticides Were Applied by a Professional at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-33
Table 17-35. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to Eradicate
Insects, Rodents, or Other Pests at Specified Frequencies 17-33
Table 17-36. Household Demographics and Pesticide Types, Characteristics, and Frequency of Pesticide Use . 17-34
Table 17-37. Amount and Frequency of Use of Household Products 17-35
Table 17-38. Frequency of Use of Cosmetic Products 17-36
Table 17-39. Amount of Test Product Used (grams) for Lipstick, Body Lotion, and Face Cream 17-37
Table 17-40. Frequency of Use of Personal Care Products 17-39
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LIST OF TABLES (continued)
Table 17-41. Average Amount of Product Applied per Application3 (grams) 17-40
Table 17-42. Average Amount of Product Applied per Use Day3 (grams) 17-41
Table 17-43. Body Lotion Exposure for Consumers Only (male and female) 17-42
Table 17-44. Deodorant/Antiperspirant Spray Exposure for Consumers Only (male and female)—Under Arms
Only 17-43
Table 17-45. Deodorant/Antiperspirant Spray Exposure for Consumers Only (male and female) Using Product
Over Torso and Under Arms 17-44
Table 17-46. Deodorant/Antiperspirant Non-Spray for Consumers Only (male and female) 17-45
Table 17-47. Lipstick Exposure for Consumers Only (female) 17-46
Table 17-48. Facial Moisturizer Exposure for Consumers Only (male and female) 17-47
Table 17-49. Shampoo Exposure for Consumers Only (male and female) 17-48
Table 17-50. Toothpaste Exposure for Consumers Only (male and female) 17-49
Table 17-51. Average Number of Applications per Use Day3 17-50
Table 17-52. Average Amount of Product Applied per Use Day (grams)3 17-51
Table 17-53. Average Amount of Product Applied per Application (grams)3 17-52
Table 17-54. Characteristics of the Study Population and the Percentage Using Selected Baby Care Products.. 17-53
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17. CONSUMER PRODUCTS
17.1. INTRODUCTION
17.1.1. Background
Consumer products may contain toxic or
potentially toxic chemical constituents to which
people may be exposed as a result of their use. For
example, household cleaners can contain ammonia,
alcohols, acids, and/or organic solvents that may pose
health concerns. Potential routes of exposure to
consumer products or chemicals released from
consumer products during use include ingestion,
inhalation, and dermal contact. These household
consumer products include cleaners, solvents, and
paints. Non-users, including children, can be
passively exposed to chemicals in these products.
Because people spend a large amount of time
indoors, the use of household chemicals in the indoor
environment can be a principal source of exposure
(Franklin, 2008).
Very little information is available about the exact
way the different kinds of products are used by
consumers, including the many ways in which these
products are handled, the frequency and duration of
contact, and the measures consumers may take to
minimize exposure or risk (Steenbekkers, 2001). In
addition, the factors that influence these behaviors
are not well studied, but some studies have shown
that a large variation exists in behavior between
persons (Steenbekkers, 2001).
This chapter presents information on the amount
of product used, the frequency of use, and the
duration of use for various consumer products
typically found in consumer households. All tables
that present information for these consumer products
are located at the end of this chapter.
Note that this chapter does not provide an
exhaustive treatment of all consumer products, but
rather, it provides some background and data that can
be used in an exposure assessment. Also, the data
presented may not capture the information needed to
assess the highly exposed population (i.e., consumers
who use commercial and industrial strength products
at home). The studies presented in the following
sections represent readily available surveys for which
data were collected on the frequency and duration of
use and the amount of use of cleaning products,
painting products, household solvent products,
cosmetic and other personal care products, household
equipment, pesticides, and tobacco. Also note that
some of the data in this chapter comes from
corporate, consortia, or trade organizations.
17.1.2. Additional Sources of Information
There are several sources of information on data
relevant to consumer products.
Table 17-1 provides a list of household consumer
products found in some U.S. households (U.S. EPA,
1987). It should be noted, however, that this list was
compiled by the U.S. Environmental Protection
Agency (EPA) in 1987, and consumer use of some
products listed may have changed (e.g., aerosol
product use has declined). Therefore, refer to the
Household Product Database of the National Library
of Medicine database as a source of more current
information on the types of products used. This
database contains over 7,000 consumer brands
including auto products; products used inside the
home; pesticides; landscape and yard; personal care;
home maintenance, arts, and crafts; pet care; and
home office. The information includes chemical
ingredients, specific brands that contain those
ingredients, and acute and chronic health effects
associated with specific ingredients. The database
does not contain any information on frequency or
amount of product used.
The Soaps and Detergent Association (SDA)
developed a peer-reviewed document that presents
methodologies and specific exposure information that
can be used for screening-level risk assessments from
exposures to high production volume chemicals. The
document addresses the use of consumer products,
including laundry, cleaning, and personal care
products. It includes data for daily frequency of use
and the amount of product used. The data used were
compiled from a number of sources including
cosmetic associations and data from the SDA. The
document Exposure and Risk Screening Methods for
Consumer Product Ingredients can be found on the
SDA Web site at http://www.cleaningl01.com/files/
Exposure_and_Risk_Screening_Methods_for_Consu
mer_Product_Ingredients .pdf.
Another document has been developed by the
U.S. EPA Office of Toxic Substances (1986):
Standard Scenarios for Estimating Exposure to
Chemical Substances During Use of Consumer
Products - Volumes I and II. This document presents
data and supporting information required to assess
consumer exposure to constituents in household
cleaners and components of adhesives. Its
information includes a description of standard
scenarios selected to represent upper bound
exposures for each product. Values also are presented
for parameters needed to estimate exposure for
defined exposure routes and pathways assumed for
each scenario.
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An additional reference is the Simmons Market
Research Bureau's (SMRB's) Simmons Study of
Media and Markets. This document provides an
example of available marketing data that may be
useful in assessing exposure to selected products. The
report is published biannually. Data are collected on
the buying habits of the U.S. population during the
previous 12 months for more than 1,000 consumer
products. Data are presented on frequency of use,
total number of buyers in each use category, and
selected demographics. The consumer product data
are presented according to the buyer and not
necessarily according to the user (i.e., actively
exposed person). Therefore, it may be necessary to
adjust the data to reflect potential uses. The reports
are available for purchase from the SMRB.
Table 17-2 presents a list of product categories in the
Simmons Study of Media and Markets for which
information is available.
17.2. RECOMMENDATIONS
Because of the large range and variation among
consumer products and their exposure pathways, it is
not feasible to recommend specific exposure values
as has been done in other chapters of this handbook.
Refer to the information provided by the references
of this chapter to derive appropriate exposure factors.
The following sections of this chapter provide
summaries of data from surveys involving the use of
consumer products.
17.3. CONSUMER PRODUCTS USE STUDIES
17.3.1. CTFA (1983)—Cosmetic, Toiletry, and
Fragrance Association, Inc.—Summary
of Results of Surveys of the Amount and
Frequency of Use of Cosmetic Products
by Women
The Cosmetic, Toiletry, and Fragrance
Association, Inc. (CTFA, 1983), a major
manufacturer and a market research bureau,
published three surveys that collected data on the
frequency of use of various cosmetic products and
selected baby products. In the first survey, CTFA
(1983) conducted a 1-week prospective survey of
47 female employees and relatives of employees
between ages 13 and 61 years. In the second survey, a
cosmetic manufacturer conducted a retrospective
survey of 1,129 of its customers. In the third survey, a
market research bureau sampled 19,035 female
consumers nationwide over a 91/2-month period. Of
the 19,035 females interviewed, responses from only
9,684 females were tabulated (CTFA, 1983). The
respondents in all three surveys were asked to record
the number of times they used the various products in
a given time period (i.e., a week, a day, a month, or a
year). The third survey also was designed to reflect
the socio-demographic (e.g., age, income)
characteristics of the entire U.S. population.
To obtain the average frequency of use for each
cosmetic product, responses were averaged for each
product in each survey. Averages were calculated by
adding the reported number of uses per given time
period for each product, dividing by the total number
of respondents in the survey, and then dividing again
by the number of days in the given time period
(CTFA, 1983). The average frequency of use of
cosmetic products was determined for both users and
non-users. The frequency of use of baby products
was determined among users only. The upper
90th percentile frequency of use values were
determined by eliminating the top 10% most extreme
frequencies of use. Therefore, the highest remaining
frequency of use was recorded as the upper
90th percentile value. Table 17-3 presents the amount
of product used per application (grams) and the
average and 90th percentile frequency of use per day
for various cosmetic products for all the surveys.
Note that Table 17-3 reports values provided by
cosmetic companies, associations, or market research
firms.
An advantage of the frequency data obtained from
the third survey (by the market research bureau) is
that the sample population was more likely to be
representative of the U.S. population. Another
advantage of the third data set is that the survey was
conducted over a longer period of time when
compared with the other two frequency datasets.
Also, the study provided empirical data that may be
useful in generating more accurate estimates of
consumer exposure to cosmetic products. In contrast
to the large market research bureau survey, the CTFA
employee survey is very small, and both that survey
and the cosmetic company survey are likely to be
biased toward high-end users. Therefore, data from
these two surveys should be used with caution. The
limitations of these surveys are that data were not
tabulated by age, are more than 20 years old, and are
only representative of products used by babies and
female consumers. Another limitation is that these
data may not be representative of long-term use
patterns.
17.3.2. Westat (1987a)—Household Solvent
Products: A National Usage Survey
Westat (1987a) conducted a nationwide survey to
determine consumer exposure to common household
products believed to contain methylene chloride or its
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substitutes (i.e., carbon tetrachloride, trichloroethane,
trichloroethylene, perchloroethylene, and 1,1,1,2,2,2 -
trichlorotrifluoroethane). The survey methodology
was comprised of two phases. In the first phase, the
sample population was generated by using a random
digit dialing (RDD) procedure, in which telephone
numbers of households nationwide were randomly
selected by using an unbiased, equal probability of
selection method, known as the Waksberg Method
(Westat, 1987a). After the respondents in the selected
households (18 years and older) agreed to participate
in the survey, questionnaires and product pictures
were mailed to each respondent. Finally, telephone
follow-up calls were made to those respondents who
did not respond to the mailed questionnaire within a
4-week period to administer the same questionnaire.
Of the 6,700 individuals contacted for the survey,
4,920 individuals either responded to the mailed
questionnaire or to a telephone interview (a response
rate of 73%). Survey questions included how often
the products were used in the last 12 months, when
they were last used, how much time was spent using
a product (per occasion or year), how long the
respondent remained in the room after use, how much
of a product was used per occasion or year, and what
protective measures were used (Westat, 1987a).
Thirty-two categories of common household
products were included in the survey and are
presented in Table 17-4. Tables 17-4, 17-5, 17-6, and
17-7 provide means, medians, and percentile
rankings for the following variables: frequency of
use, exposure time, amount of use, and time exposed
after use.
An advantage of this study is that the RDD
procedure (i.e., Waksberg Method) to identify
participants enabled a diverse selection of a
representative, unbiased sample of the U.S.
population (Westat, 1987a). Also, empirical data on
consumer household product use are provided.
However, a limitation associated with this study is
that the data generated were based on recall behavior.
Another limitation is that extrapolation of these data
to long-term use patterns may be difficult; the data
are more than 20 years old and cannot be broken out
by age groups.
17.3.3. Westat (1987b)—National Usage Survey
of Household Cleaning Products
Westat (1987b) collected usage data from a
nationwide survey to assess the magnitude of
exposure of consumers to various products used
when performing certain household cleaning tasks.
The survey was conducted from the middle of
November 1985 to the middle of January 1986.
Telephone interviews were conducted with
193 households. According to Westat (1987b), the
resulting response rate for this survey was 78%. The
Waksberg Method discussed in the Westat (1987a)
study also was used in randomly selecting telephone
numbers employed in this survey. The survey was
designed to obtain information on cleaning activities
performed in the interior of the home during the
previous year. The person who did the majority of the
cleaning in the kitchen and bathroom areas of each
household was interviewed. Of those respondents, the
primary cleaner was female in 160 households (83%)
and male in 30 households (16%); the sex of the
respondents in the three remaining households was
not ascertained (Westat, 1987b). Data obtained from
the survey included the frequency of performing
14 different cleaning tasks, the amount of time
(duration) spent at each task, the cleaning product
most frequently used, the type of product (i.e., liquid,
powder, aerosol, or spray pump) used, and the
protective measures taken during cleaning, such as
wearing rubber gloves or having a window open or
an exhaust fan on (Westat, 1987b).
Tables 17-8 through 7-12 present the survey data.
Table 17-8 presents the mean and median total
exposure time of use for each cleaning task and the
product type preferred for each task. Table 17-9
presents the percentile rankings for the total time
exposed to the products used for 14 cleaning tasks.
Table 17-10 presents the mean and percentile
rankings of the frequency in performing each task.
Table 17-11 shows the mean and percentile rankings
for exposure time per event of performing household
tasks. Table 17-12 presents the mean and percentile
rankings for total number of hours spent per year
using the top 10 product groups.
Westat (1987b) randomly selected a subset of
30 respondents from the original survey and re-
interviewed them during the first 2 weeks of March
1986 as a reliability check on the recall data from the
original phone survey. Frequency and duration data
for 3 of the original 14 cleaning tasks were obtained
from the re-interviews. In a second effort to validate
the phone survey, 50 respondents of the original
phone survey participated in a 4-week diary study
(between February and March 1986) of 8 of the
14 cleaning tasks originally studied. The diary
approach assessed the validity of using a 1-time
telephone survey to determine usual cleaning
behavior (Westat, 1987b). The data (i.e., frequency
and duration) obtained from the re-interviews and the
diary approach were lower than the data from the
original telephone survey, but were more consistent
with one other. Westat (1987b) attributed the
significant differences in the data obtained from these
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surveys to seasonal changes rather than
methodological problems.
A limitation of this survey is evident from the
reliability and validity check of the data collected by
Westat (1987b). The data obtained from the telephone
survey may reflect heavier seasonal cleaning because
the survey was conducted during the holidays
(November through January). Therefore, usage data
obtained in this study may be biased and may
represent upper bound estimates. Other limitations of
this study include the small size of the sample
population, the age of the data set, and that the data
cannot be broken out by age groups. An advantage of
this survey is that the RDD procedure (Waksberg
Method) used provides unbiased results of sample
selection and reduces the number of unproductive
calls. Another advantage of this study is that it
provides empirical data on frequency and duration of
consumer use.
17.3.4. Westat (1987c)—National Household
Survey of Interior Painters
Westat (1987c) conducted a nationwide study
between November 1985 and January 1986 to obtain
usage information that estimates the magnitude of
exposure of consumers to different types of painting
and painting-related products used while painting the
interior of the home. The study sampled
777 households to determine whether any household
member had painted the interior of the home during
the 12 months prior to the survey date. Of the
sampled households, 208 households (27%) had a
household member who had painted during the past
12 months. Based on the households with primary
painters, the response rate was 90% (Westat, 1987c).
The person in each household who did most of the
interior painting during the past 12 months was
interviewed over the telephone. The RDD procedure
(Waksberg Method) previously described in Westat
(1987a) was used to generate sample blocks of
telephone numbers in this survey. Questions were
asked about the frequency and time spent for interior
painting activities, the amount of paint used, and the
protective measures used (i.e., wearing gloves, hats,
and masks or keeping a window open) (Westat,
1987c). Fifty-three percent of the primary painters in
the households interviewed were male, 46% were
female, and the sex of the remaining 1% was not
ascertained. Three types of painting products were
used in this study: latex paint, oil-based paint, and
wood stains and varnishes. Of the respondents,
94.7% used latex paint, 16.8% used oil-based paint,
and 20.2% used wood stains and varnishes.
Tables 17-13, 17-14, and 17-15 summarize data
generated from this survey. Table 17-13 presents the
mean, standard deviation, and percentile rankings for
the total exposure time for painting activity by paint
type. Table 17-14 presents the mean and median
exposure times for each painting activity per occasion
for each paint type. A painting occasion is defined as
a time period from start to cleanup (Westat, 1987c).
Table 17-14 also presents the frequency and
percentile rankings of painting occasions per year.
Table 17-15 presents the total amount of paint used
by interior painters.
In addition, 30 respondents from the original
survey were re-interviewed in April 1986 as a
reliability check on the recall data. There were no
significant differences between the data obtained
from the re-interviews and the original painting
survey (Westat, 1987c).
An advantage of this survey, based on the
reliability check conducted by Westat (1987c), is the
stability in the painting data obtained. Another
advantage of this survey is that the response rate was
high (90%), thus minimizing non-response bias. Also,
the Waksberg Method employed provides an
unbiased equal probability method of RDD. The
limitations of the survey are that the data are based
on 12-month recall and may not accurately reflect
long-term use patterns and the age of the data set.
17.3.5. Abt (1992)—Methylene Chloride
Consumer Use Study Survey Findings
As part of a plan to assess the effectiveness of
labeling of consumer products containing methylene
chloride, Abt (1992) conducted a nationwide
telephone survey of nearly 5,000 households. The
survey was conducted in April and May of 1991.
Three classes of products were included: (1) paint
strippers, (2) non-automotive spray paint, and (3)
adhesive removers. The survey paralleled a
1986 consumer use survey conducted by Abt for the
U.S. EPA.
The survey was conducted to estimate the
percentage of the U.S. adult population using paint
remover, adhesive remover, and non-automotive
spray paint. In addition, an estimate of the population
using these products containing methylene chloride
was determined. A survey questionnaire was
developed to collect product usage data and
demographic data. The survey sample was generated
using a RDD technique.
A total of 4,997 product screener interviews were
conducted for the product interview sections. The
number of respondents was 381 for paint strippers,
58 for adhesive removers, and 791 for
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non-automotive spray paint. Survey responses were
weighted to allow estimation at the level of the total
U.S. population (Abt, 1992). A follow-up mail survey
also was conducted by using a short questionnaire.
Respondents who had used the product in the past
year or had purchased the product in the past 2 years
and still had the container were asked to respond to
the questionnaire (Abt, 1992). Of the 527 mailed
questionnaires, 259 were returned. The questionnaire
responses included 67 on paint strippers, 6 on
adhesive removers, and 186 on non-automotive spray
paint. Tables 17-16 through 17-21 (TVs are
unweighted) present the results of the survey. Data
are presented for recent users, who were defined as
persons who have used the product within the last
year of the survey or who have purchased the product
in the past 2 years.
Abt (1992) found the following results when
comparing the new data to the 1986 findings:
A significantly smaller proportion of
current survey respondents used a paint
stripper, spray paint, or adhesive remover.
The proportion of the population who used
the three products recently (within the past
year) decreased substantially.
Those who used the products reported a
significantly longer time since their last
use. For all three products, the reported
amount used per year was significantly
higher in the current survey.
An advantage of this survey is that the survey
population was large, and the survey responses were
weighted to represent the U.S. population. In
addition, the survey was designed to collect data for
frequency of product use and amount of product used
by sex. Limitations of the survey are that the
information may be dated, and that the data were
generated based on recall behavior. Extrapolation of
these data to accurately reflect long-term use patterns
may be difficult.
17.3.6. U.S. EPA (1996)—National Human
Activity Pattern Survey (NHAPS)
U.S. EPA (1996) collected data on the duration
and frequency of selected activities and the time
spent in selected microenvironments via 24-hour
diaries as part of the National Human Activity Pattern
Survey (NHAPS). More than 9,000 individuals from
various age groups in 48 contiguous states
participated in NHAPS, including 2,000 children.
The survey was conducted between October 1992
and September 1994. Individuals were interviewed to
categorize their 24-hour routines (diaries) and/or to
answer follow-up questions that were related to
exposure events. Demographic, including
socioeconomic (e.g., sex, age, race, education),
geographic (e.g., census region, state), and temporal
(i.e., day of week, month, season) data were included
in the study. Data were collected for a maximum of
82 possible microenvironments and 91 different
activities.
As part of the survey, data also were collected on
duration and frequency of use of selected consumer
products. Tables 17-22 through 17-30 present data on
the number of minutes that survey respondents spent
in activities working with or being near certain
consumer products, including microwave ovens;
freshly applied paints; household cleaning agents
such as scouring powders or ammonia; floor wax,
furniture wax, or shoe polish; glue; solvents, fumes,
or strong-smelling chemicals; stain or spot removers;
gasoline, diesel-powered equipment, or automobiles;
and pesticides, bug sprays, or bug strips.
Tables 17-31 through 17-35 present data on the
number of respondents in these age categories that
used fragrances, aerosol sprays, humidifiers, and
pesticides (professionally-applied and consumer-
applied). Because the age categories used by the
study authors did not coincide with the standardized
age categories recommended in U.S. EPA (2005) and
used elsewhere in this handbook, the source data
from NHAPS on pesticide use (professionally applied
and consumer-applied) were reanalyzed by U.S. EPA
to generate data for the standardized age categories.
Data for subsets of the 1st year of life (e.g., 1 to
2 months, 3 to 5 months, etc.) were not available.
As discussed in previous chapters that used
NHAPS as a data source, the primary advantage is
that the data were collected for a large number of
individuals, and the survey was designed to be
representative of the U.S. general population.
However, due to the wording of questions in the
survey, precise data were not available for consumers
who spent more than 60 or 120 minutes (depending
on the activity) using some consumer products. This
prevents accurate characterization of the high end of
the distribution and also may introduce error into the
calculation of the mean. Another limitation is that the
adult data were not broken down into finer age
categories. These data are also based on 24-hour
diaries and may not be representative of long-term
use patterns.
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17.3.7. Bass et al. (2001)—What's Being Used at
Home: A Household Pesticide Survey
Bass et al. (2001) conducted a survey to
assess the use of pesticide products in homes with
children in March 1999. The study obtained
information on what pesticides were used, where they
were used, and how frequently they were used. A
total of 107 households in Arizona that had a least
one child less than 10 years old in the household and
had used a pesticide within the last 6 months were
surveyed (Bass et al., 2001). The survey population
was composed predominantly of Hispanic females
and represented a survey response rate of
approximately 74%. Study participants were selected
by systematic random sampling. Pesticide use was
assessed by a one-on-one interview in the home.
Survey questions pertained to household pesticides
used inside the house for insect control and outside
the house for controlling weeds in the garden and
repelling animals from the garden. As part of the
interview, information was gathered on the
pesticides' frequency of use.
Table 17-36 presents information on the type,
characteristics, and frequency of pesticide use, as
well as information on the demographics of the
survey population. A total of 148 pesticide products
were used in the 107 households surveyed.
Respondents had used pesticides in the kitchen,
bathroom, floors, baseboards, and cabinets with
dishes or cookware. The frequency of use data
showed the following: about 32% of the households
used pesticides once per week or more; about 44%
used the products once per month or once in
3 months; and about 19% used the products once in
6 months or once peryear (Bass et al., 2001).
Although this study was limited to a selected area
in Arizona, it provides useful information on the
frequency of use of pesticides among households
with children. This may be useful for populations in
similar geographical locations where site-specific
data are not available. However, these data are the
result of a community-based survey and are not
representative of the U.S. general population.
17.3.8. Weegels and van Veen (2001)—Variation
of Consumer Contact with Household
Products: A Preliminary Investigation
Weegels and van Veen (2001) conducted a survey
to determine consumer exposure to common
household products used once a day or every other
day. Thirty households participated in the study,
including 10 families with children, 10 couples,
9 individuals, and 1 household of 6 adults from the
city of Delft in The Netherlands. Households were
recruited through the Usability Panel of the School of
Industrial Design and through public notices and
pamphlets.
Three types of products were studied:
dishwashing detergent, all-purpose cleaners, and hair-
styling products. Three activities in which these
products are commonly used were studied in more
detail: dishwashing, toilet cleaning, and styling hair.
In-home observations, diaries, and measurement of
the amount of product utilized were used to collect
data. Subjects were visited in their homes and
videotaped performing the activities. After 3 weeks,
subjects were again visited in their homes and
videotaped performing activities, diaries were
collected, and the amount of product used was
measured.
Table 17-37 presents the survey data. During
toilet cleaning, 22 of 29 subjects observed used at
least two different products (e.g., toilet cleaner, all-
purpose cleaner, and/or abrasive cleaner). The large
variation in duration of toilet cleaning was due to the
diverse ways in which toilet cleaner was used: some
subjects left the toilet cleaner to soak overnight, some
left it in the bowl while cleaning the remainder of the
toilet, others flushed the toilet immediately after
cleaning. The authors noted that the findings of the
study suggest that "...individuals have a consistent
way of using a product for a particular activity, but
there is a large variety in product usage among
consumers, with relations among frequency,
durations and amount. If this conclusion is confirmed
by future research, it suggests that there will be
people who exhibit high-end use of products and will,
most likely follow their own routine, which may have
consequences for the definition of worst-case use of
consumer products."
An advantage of this study is that the empirical
data generated provide more accurate calculations of
exposure than studies relying on recall data.
Limitations of the study are the small study
population (30 households) and that The Netherlands
may not be representative of U.S. population
behaviors. Another limitation is that the short
duration (3 weeks) may not accurately reflect long-
term or seasonal usage patterns.
17.3.9. Loretz et al. (2005)—Exposure Data for
Cosmetic Products: Lipstick, Body
Lotion, and Face Cream
Loretz et al. (2005) conducted a nationwide
survey to estimate the usage (i.e., frequency of
application and amount used per application) of
lipstick, body lotion, and face cream. The study was
conducted in 2000 and included 360 study subjects
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recruited in 10 U.S. cities (i.e., Atlanta, GA; Boston,
MA; Chicago, IL; Denver, CO; Houston, TX;
Minneapolis, MN; St. Louis, MO; San Bernardino,
CA; Tampa Bay, FL; and Seattle, WA). The survey
participants were women, ages 19 to 65 years, who
regularly used the products of interest. Typical
cosmetic formulations of the three product types were
weighed and provided to the women for use over a
2-week period. Subjects recorded information on
product usage (e.g., whether the product was used,
number of applications, time of applications) on a
daily basis in a diary provided to them. At the end of
the 2-week period, unused portions of product were
returned and weighed. The amount of product used
was estimated as the difference between the weight of
product at the beginning and end of the survey
period. Of the 360 subjects, 86.4%, 83.3%, and
85.6% completed the study and returned the diaries
for lipstick, body lotion, and face cream, respectively
(Loretz et al., 2005).
Tables 17-38 and 17-39 present the survey data.
Table 17-38 provides the mean, median, and standard
deviations for the frequency of use. Table 17-39
provides distribution data for the total amount
applied, the average amount applied per use day, and
the average amount applied per application.
An advantage of this study is that the survey
population covered a diverse geographical area of the
United States and that it was not based on recall data.
A limitation of the study is that the short duration
(2 weeks) may not accurately reflect long-term usage
patterns. Another limitation is that the study only
included women who already used the products;
therefore, the usage patterns are not representative of
the entire female population. Also, the data are not
presented by age group.
17.3.10. Loretz et al. (2006)—Exposure Data for
Personal Care Products: Hairspray,
Spray Perfume, Liquid Foundation,
Shampoo, Body Wash, and Solid
Antiperspirant
Loretz et al. (2006) conducted a nationwide
survey to determine the usage (i.e., frequency of use
and amount used) of hairspray, spray perfume, liquid
foundation, shampoo, body wash, and solid
antiperspirant. The survey was similar to that
described by Loretz et al. (2005). This study was
conducted in 2000 and 2001. A total of 360 women
were recruited from 10 U.S. cities (Atlanta, GA;
Boston, MA; Chicago, IL; Denver, CO; Houston, TX;
Minneapolis, MN; St. Louis, MO; San Bernardino,
CA; Tampa Bay, FL; and Seattle, WA). The survey
participants were women, ages 19 to 65 years old,
who regularly used the test products. Subjects kept
daily records on product usage (e.g., whether the
product was used, number of applications, time of
applications) in a diary. For spray perfume, liquid
foundation, and body wash, subjects recorded the
body areas where these products were applied. For
shampoo, subjects recorded information on their hair
type (i.e., length, thickness, oiliness, straight or curly,
and color treated or not). At the end of the 2-week
period, unused portions of products were returned
and weighed. Of the 360 subjects recruited per
product, the study was completed by 91% of
participants for hairspray, 91% for spray perfume,
94% for liquid foundation, and 94% for shampoo,
body wash, and solid antiperspirant.
Tables 17-40 through 17-42 present the survey
data. Table 17-40 provides the minimum, maximum,
mean, and standard deviations for the frequency of
use. Table 17-41 provides percentile values for the
amount of product applied per application.
Table 17-42 provides distribution data for the amount
applied per use day.
An advantage of this study is that the survey
population covered a diverse geographical range of
the United States and that it did not rely on recall
data. A limitation of the study is that the short
duration (2 weeks) may not accurately reflect long-
term usage patterns. Another limitation is that the
study only included women who already used these
products; therefore, the usage patterns are not entirely
representative of the entire female population. Also,
the data are not presented by age group.
17.3.11. Hall et al. (2007)—European Consumer
Exposure to Cosmetic Products, a
Framework for Conducting Population
Exposure Assessments
European cosmetic manufacturers constructed a
probabilistic European population model of exposure
for six cosmetic products: body lotion,
deodorant/antiperspirant, lipstick, facial moisturizer,
shampoo, and toothpaste (Hall et al., 2007). Data
were collected by using both market information
databases and a controlled product use study from
44,100 households and 18,057 individual consumers,
creating a sample of the 249 million inhabitants of
the 15 countries in the European Union. Tables 17-43
through 17-50 show the amount used in g/day and
mg/kg-day. The study found an inverse correlation
between frequency of product use and quantity used
per application for body lotion, facial moisturizer,
toothpaste, and shampoo, and so the authors
cautioned against calculating daily exposure to these
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products by multiplying the maximum frequency
value by the maximum quantity per event value.
The advantage of this study is that it included a
large sample size. However, behaviors and activities
in the European population may not be representative
of the U.S. population, and results were not broken
out by age groups.
17.3.12. Loretz et al. (2008)—Exposure Data for
Cosmetic Products: Facial Cleanser, Hair
Conditioner, and Eye Shadow
Loretz et al. (2008) used the data from a study
conducted in 2005 to estimate frequency of use and
usage amount for facial cleanser, hair conditioner,
and eye shadow. The study was conducted in a
similar manner as Loretz et al. (2005, 2006). A total
of 360 women, ages 18 to 69 years, were recruited by
telephone to provide diary records of product use
during a 2-week period. The study subjects were
representative of four U.S. Census regions (i.e.,
Northeast, Midwest, South, and West). A total of 295,
297, and 299 women completed the study for facial
cleanser, hair conditioner, and eye shadow,
respectively.
The participants recorded daily in a diary whether
the product was used that day, the number of
applications, and the time of applications during a
2-week period. Products were weighed at the start
and completion of the study to determine the amount
used. A statistical analysis of the data was conducted
to provide summary distributions of use patterns,
including number of applications, amount used per
day, and amount of product used per application for
each product. Table 17-51 provides data on the
number of applications per use day. Table 17-52
shows the average amounts of product applied per
use day, while Table 17-53 shows the average
amounts of product applied per application.
The advantages of this study are that it is
representative of the U.S. female population for users
of the products studied, it provides data for frequency
of use and amount used, and it provides distribution
data. A limitation of the study is that the data were
not provided by age group. In addition, the
participants were regular users of the product, so the
amount applied and the frequency of use may be
higher than for other individuals who may use the
products. According to Loretz et al. (2008),
"...variability in amount used by the different
subjects is high, but consistent with the data from
other cosmetic and personal care studies." The
authors also noted that it was not clear if the high-end
users of products represented true usage. Data were
also collected over a 2-week period and may not be
representative of long-term usage patterns.
17.3.13. Sathyanarayana et al. (2008)—Baby Care
Products; Possible Sources of Infant
Phthalate Exposure
Sathyanarayana et al. (2008) investigated dermal
exposure to phthalates via the dermal application of
personal care products. The study was conducted on
163 infants born between 2000 and 2005. The
products studied were baby lotion, baby powder,
baby shampoo, diaper cream, and baby wipes. Infants
were recruited through Future Families, a multicenter
pregnancy cohort study, at prenatal clinics in Los
Angeles, CA; Minneapolis, MN; and Columbia, MO.
Although the study was designed to assess exposure
to phthalates, the authors collected information on the
percentage of the total participants who used the baby
products. Data were collected from questionnaire
responses of the mothers and at study visits.
Table 17-54 shows the characteristics and the
percentage of the population using the studied baby
products. Of the 163 infants studied, 94% of the
participants used baby wipes, and 54% used infant
shampoo.
The advantages of this study are that it
specifically targeted consumer products used by
children, it captured the percentage of the study
population using these products, and it collected the
data from a diverse ethnic population. The limitation
is that these data may not be entirely representative of
the U.S. population because the study population was
from only three states and the sample size was small.
Also, this study did not contain any information on
amount or frequency of product use.
17.4. REFERENCES FOR CHAPTER 17
Abt. (1992) Methylene chloride consumer products
use survey findings. Prepared by Abt
Associates, Inc., for the U.S. Consumer
Product Safety Commission, Bethesda, MD.
Bass, J; Ortega, L; Resales, C; Petersen, N; Philen, R.
(2001) What's being used at home: a
household pesticide survey. Pub Health
9(3):138-144.
Cosmetic, Toiletry, and Fragrance Association
(CTFA). (1983) Summary of the results of
surveys of the amount and frequency of use
of cosmetic products by women. Prepared
by Environ Corporation for CTFA, Inc.,
Washington, DC.
Franklin, P. (2008) Household chemicals: Good
housekeeping or occupational hazard. Eur
Respir 131:489-491.
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Hall, B., Tozer, S., Safford, B., Coroama, M,
Steiling, W., Leneveu-Duchemin, MC.,
McNamara, C., and Gibney M. (2007)
European consumer exposure to cosmetic
products, a framework for conducting
population exposure assessments. Food
Chem Toxicol 45(11):2097-2108.
Loretz, L; Api, A; Barraj, L; Burdick, J; Dressier, W;
Gettings, S; Hsu, H; Pan, Y; Re, T;
Renskers, K; Rothenstein, A; Scrafford, C;
Sewall, C. (2005) Exposure data for
cosmetic products: lipstick, body lotion, and
face cream. Food Chem Toxicol
43:279-291.
Loretz, L; Api, A; Barraj, L; Burdick, J; Davis, D;
Dressier, W; Gilberti, E; Jarrett, G; Mann, S;
Pan, Y; Re, T; Renskers, K; Scrafford, C;
Vater, S. (2006) Exposure data for personal
care products: Hairspray, spray perfume,
liquid foundation, shampoo, body wash, and
solid antiperspirant. Food Chem Toxicol
44:2008-2018.
Loretz, L; Api, A; Babcock, L; Barraj, L; Burdick, J;
Cater, K; Jarrett, G; Mann, S; Pan, Y; Re, T;
Renskers, K; Scrafford, C. (2008) Exposure
data for cosmetic products: Facial cleanser,
hair conditioner, and eye shadow. Food
Chem Toxicol 46:1516-1524.
Sathyanarayana, S; Karr, C; Lozano, P; Brown, E;
Calafat, M. (2008) Baby care products;
possible sources of infant phthalate
exposure. Pedriatrics 121:260-268.
Steenbekkers, LP (2001) Methods to study everyday
use of products un households: The
Wageningen mouthing study. Am Occup
Hyg45(1001):125-129.
U.S. EPA (Environmental Protection Agency). (1986)
Standard scenarios for estimating exposure
to chemical substances during use of
consumer products - volumes I and II.
Office of Toxic Substances Exposure
Evaluation Division, Washington, DC.
U.S. EPA (Environmental Protection Agency). (1987)
Methods for assessing exposure to chemical
substances - volume 7. (EPA/560/5-85/007).
Office of Toxic Substances. Washington,
DC.
U.S. EPA (Environmental Protection Agency). (1996)
Descriptive statistics tables from a detailed
analysis of the National Human Activity
Pattern Survey (NHAPS) data. Office of
Research and Development, Washington,
DC: EPA/600/R-96/148.
U.S. EPA (Environmental Protection Agency). (2005)
Guidance on selecting age groups for
monitoring and assessing childhood
exposures to environmental contaminants.
Washington, DC: EPA/630/P-03/003F.
Weegels, MF; van Veen, MP. (2001) Variation of
consumer contact with household products:
A preliminary investigation. Risk Anal
21(3):499-511.
Westat. (1987a) Household solvent products - A
national usage survey. Prepared for U.S.
Environmental Protection Agency,
Washington, DC. Available from the
National Technical Information Service,
Springfield, VA;.PB88-132881.
Westat. (1987b) National usage survey of household
cleaning products. Prepared for U.S.
Environmental Protection Agency, Office of
Toxic Substances and Office of Pesticides
and Toxic Substances, Washington, DC.
Westat. (1987c) National household survey of interior
painters. Prepared for U.S. Environmental
Protection Agency, Office of Toxic
Substances and Office of Pesticides and
Toxic Substances, Washington, DC.
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Table 17-1. Consumer Products Commonly Found in Some U.S. Households"
Consumer Product Category
Consumer Product
Cosmetics Hygiene Products
Adhesive bandages
Bath additives (liquid)
Bath additives (powder)
Cologne/perfume/aftershave
Contact lens solutions
Deodorant/antiperspirant (aerosol)
Deodorant/antiperspirant (wax and liquid)
Depilatories
Facial makeup
Fingernail cosmetics
Hair coloring/tinting products
Hair conditioning products
Hairsprays (aerosol)
Lip products
Mouthwash/breath freshener
Sanitary napkins and pads
Shampoo
Shaving creams (aerosols)
Skin creams (non-drug)
Skin oils (non-drug)
Soap (toilet bar)
Sunscreen/suntan products
Talc/body powder (non-drug)
Toothpaste
Waterless skin cleaners
Household Furnishings
Carpeting
Draperies/curtains
Rugs (area)
Shower curtains
Vinyl upholstery, furniture
Garment Conditioning Products
Anti-static spray (aerosol)
Leather treatment (liquid and wax)
Shoe polish
Spray starch (aerosol)
Suede cleaner/polish (liquid and
aerosol)
Textile water-proofing (aerosol)
Household Maintenance Products
Adhesive (general) (liquid)
Bleach (household) (liquid)
Bleach (see laundry)
Candles
Cat box litter
Charcoal briquettes
Charcoal lighter fluid
Drain cleaner (liquid and powder)
Dishwasher detergent (powder)
Dishwashing liquid
Fabric dye (DIY)b
Fabric rinse/softener (liquid)
Fabric rinse/softener (powder)
Fertilizer (garden) (liquid)
Fertilizer (garden) (powder)
Fire extinguishers (aerosol)
Floor polish/wax (liquid)
Food packaging and packaged food
Furniture polish (liquid)
Furniture polish (aerosol)
General cleaner/disinfectant (liquid)
General cleaner (powder)
General cleaner/disinfectant (aerosol
and pump)
General spot/stain remover (liquid)
General spot/stain remover (aerosol and
pump)
Herbicide (garden-patio) (liquid and aerosol)
Insecticide (home and garden) (powder)
Insecticide (home and garden)
(aerosol and pump)
Insect repellent (liquid and aerosol)
Laundry detergent/bleach (liquid)
Laundry detergent (powder)
Laundry prewash/soak (powder)
Laundry prewash/soak (liquid)
Laundry prewash/soak (aerosol
and pump)
Lubricant oil (liquid)
Lubricant (aerosol)
Matches
Metal polish
Oven cleaner (aerosol)
Pesticide (home) (solid)
Pesticide (pet dip) (liquid)
Pesticide (pet) (powder)
Pesticide (pet) (aerosol)
Pesticide (pet) (collar)
Petroleum fuels (home) (liquid and
aerosol)
Rug cleaner/shampoo (liquid and
aerosol)
Rug deodorizer/freshener (powder)
Room deodorizer (solid)
Room deodorizer (aerosol)
Scouring pad
Toilet bowl cleaner
Toiler bowl deodorant (solid)
Water-treating chemicals
(swimming pools)
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Table 17-1. Consumer Products Commonly Found in Some
U.S. Households" (continued)
Consumer Product Category Consumer Product
Home Building/Improvement • Adhesives, specialty (liquid)
Products (DIY)b • Ceiling tile
• Caulks/sealers/fillers
• Dry wall/wall board
• Flooring (vinyl)
• House paint (interior) (liquid)
• House paint and stain (exterior)
(liquid)
• Insulation (solid)
• Insulation (foam)
Automobile-Related Products • Antifreeze
• Car polish/wax
• Fuel/lubricant additives
• Gasoline/diesel fuel
• Interior upholstery /components,
synthetic
Personal Materials • Clothes/shoes
• Diapers/vinyl pants
• Jewelry
• Printed material (colorprint, newsprint,
photographs)
• Paint/varnish removers
• Paint thinner/brush cleaners
• Patching/ceiling plaster
• Roofing
• Refinishing products
(e.g., polyurethane, varnishes)
• Spray paints (home) (aerosol)
• Wall paneling
• Wall paper
• Wall paper glue
• Motor oil
• Radiator flush/cleaner
• Automotive touch-up paint
(aerosol)
• Windshield washer solvents
• Sheets/towels
• Toys (intended to be placed in
mouths)
a A subjective listing based on consumer use profiles.
b DIY= do it yourself.
Source: U.S. EPA, 1987.
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Table 17-2. List of Product Categories in the Simmons Study of Media and Markets
The volumes included in the Media series are as follows:
Ml Publications: Total Audiences
M2 Publications: Qualitative Measurements and In-Home Audiences
M3 Publications: Duplication of Audiences
M4 Multi-Media Audiences: Adults
M5 Multi-Media Audiences: Males
M6 Multi-Media Audiences: Females and Mothers
M7 Business to Business
M8 Multi-Media Reach and Frequency and Television Attentiveness and Special Events
The following volumes are included in the Product series:
PI Automobiles, Cycles, Trucks and Vans
P2 Automotive Products and Services
P3 Travel
P4 Banking, Investments, Insurance, Credit Cards and Contributions, Memberships and Public
Activities
P5 Games and Toys, Children's and Babies' Apparel and Specialty Products
P6 Computers, Books, Discs, Records, Tapes, Stereo, Telephones, TV and Video
P7 Appliances, Garden Care, Sewing and Photography
P8 Home Furnishings and Home Improvements
P9 Sports and Leisure
P10 Restaurants, Stores and Grocery Shopping
PI 1 Direct Mail and Other In-Home Shopping, Yellow Pages, Florist, Telegrams, Faxes and Greeting
Cards
P12 Jewelry, Watches, Luggage, Writing Tools and Men's Apparel
P13 Women's Apparel
P14 Distilled Spirits, Mixed Drinks, Malt Beverages, Wine and Tobacco Products
PI 5 Coffee, Tea, Cocoa, Milk, Soft Drinks, Juices and Bottled Water
PI 6 Dairy Products, Desserts, Baking and Bread Products
PI 7 Cereals and Spreads, Rice, Pasta, Pizza, Mexican Foods, Fruits and Vegetables
PI 8 Soup, Meat, Fish, Poultry, Condiments and Dressings
PI 9 Chewing Gum, Candy, Cookies and Snacks
P20 Soap, Laundry, Paper Products and Kitchen Wraps
P21 Household Cleaners, Room Deodorizers, Pest Controls and Pet Foods
P22 Health Care Products and Remedies
P23 Oral Hygiene Products, Skin Care, Deodorants and Drug Stores
P24 Hair Care, Shaving Products and Fragrances
P25 Women's Beauty Aids, Cosmetics and Personal Products
P26 Relative Volume of Consumption
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Table 17-3.
Product Type
Baby Lotion - baby use0
Baby Lotion - adult use
Baby Oil - baby use0
Baby Oil - adult use
Baby Powder - baby use0
Baby Powder - adult use
Baby Cream - baby use0
Baby Cream - adult use
Baby Shampoo - baby use0
Baby Shampoo - adult use
Bath Oils
Bath Tablets
Bath Salts
Bubble Baths
Bath Capsules
Bath Crystals
Eyebrow Pencil
Eyeliner
Eye Shadow
Eye Lotion
Eye Makeup Remover
Mascara
Under Eye Cover
Blusher and Rouge
Face Powders
Foundations
Leg and Body Paints
Lipstick and Lip Gloss
Makeup Bases
Amount and
Amount of
Product Per
Application3
(grams)
1.4
1.0
1.3
5.0
0.8
0.8
-
-
0.5
5.0
14.7
-
18.9
11.8
-
-
-
-
-
-
-
-
-
0.011
0.085
0.265
-
-
0.13
Frequency
of Use of Various Cosmetic
Average Frequency
(per day)
CTFA
0.38
0.22
0.14
0.06
5.36
0.13
0.43
0.07
0.14
0.02
0.08
0.003
0.006
0.088
0.018
0.006
0.27
0.42
0.69
0.094
0.29
0.79
0.79
1.18
0.35
0.46
0.003
1.73
0.24
Survey Type
Cosmetic
Co.
1.0
0.19
1.2
0.13
1.5
0.22
1.3
0.10
-
-
0.19
0.008
0.013
0.13
0.019
-
0.49
0.68
0.78
0.34
0.45
0.87
-
1.24
0.67
0.78
0.011
1.23
0.64
of Use
Market"
Research
Bureau
-
0.24d
-
-
0.35d
-
-
-
O.llf
-
0.22B
-
-
-
-
-
-
0.27
0.40
-
-
0.46
-
0.55
0.33
0.47
-
2.62
-
and Baby
Upper 90th
CTFA
0.57
0.86
0.14
0.29
8.43
0.57
0.43
0.14
0.14
0.86e
0.29
0.14e
0.14e
0.43
0.29e
0.29e
1.0
1.43
1.43
0.43
1.0
1.29
0.29
2.0
1.29
1.0
0.14e
4.0
0.86
Products
Percentile Frequency of
Use
(per day)
Survey Type
Cosmetic
Co.
2.0
1.0
3.0
0.57
3.0
1.0
3.0
0.1 4e
-
-
0.86
0.1 4e
0.1 4e
0.57
0.1 4e
0.1 4e
1.0
1.0
1.0
1.0
1.0
1.0
-
1.43
1.0
1.0
0.1 4e
2.86
1.0
Market
Research
Bureau
-
1.0d
-
-
1.0d
-
-
-
0.43f
-
1.0g
-
-
-
-
-
-
1.0
1.0
-
-
1.5
-
1.5
1.0
1.5
-
6.0
-
Exposure Factors Handbook
September 2011
Page
17-13
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-3. Amount and Frequency of Use
Product Type
Makeup Fixatives
Sunscreen
Colognes and Toilet Water
Perfumes
Powders
Sachets
Fragrance Lotion
Hair Conditioners
Hair Sprays
Hair Rinses
Shampoos
Tonics and Dressings
Wave Sets
Dentifrices
Mouthwashes
Breath Fresheners
Nail Basecoats
Cuticle Softeners
Nail Creams and Lotions
Nail Extenders
Nail Polish and Enamel
Nail Polish and Enamel
Remover
Nail Undercoats
Bath Soaps
Underarm Deodorants
Douches
Feminine Hygiene
Deodorants
Cleansing Products (cold
creams, cleansing lotions,
liquids, and pads)
Depilatories
Amount of
Product Per
Application3
(grams)
-
3.18
0.65
0.23
2.01
0.2
-
12.4
-
12.7
16.4
2.9
2.6
-
-
-
0.2
0.7
0.6
-
0.3
3.1
-
2.6
0.5
-
-
1.7
"
of Various Cosmetic and
Average Frequency of Use
(per day)
CTFA
0.052
0.003
0.68
0.29
0.18
0.0061
0.0061
0.4
0.25
0.064
0.82
0.073
0.00311
1.62
0.42
0.052
0.052
0.040
0.070
0.003
0.16
0.088
0.049
1.53
1.01
0.013
0.021
0.63
0.0061
Survey Type
Cosmetic
Co.
0.12
-
0.85
0.26
0.39
0.034
-
0.40
0.55
0.18
0.59
0.021
0.040
0.67
0.62
0.43
0.13
0.10
0.14
0.013
0.20
0.19
0.12
0.95
0.80
0.089
0.084
0.80
0.051
Marketb
Research
Bureau
-
0.002
0.56
0.38
-
-
-
0.27
0.32
-
0.48
-
-
2.12
0.58
0.46
-
-
-
-
0.07
-
-
-
1.10
0.085
0.05
0.54
0.009
Baby Products (continued)
Upper 90th Percentile Frequency of
Use
(per day)
CTFA
0.14
0.14e
1.71
0.86
1.0
0.14e
0.29e
1.0
1.0
0.29
1.0
0.29
h
2.6
1.86
0.14
0.29
0.14
0.29
0.14e
0.71
0.29
0.14
3.0
1.29
0.14e
1.0e
1.71
0.016
Survey Type
Cosmetic
Co.
1.0
-
1.43
1.0
1.0
0.1 4e
-
1.0
1.0
1.0
1.0
0.14d
0.14
2.0
1.14
1.0
0.29
0.29
0.43
0.14e
0.43
0.43
0.29
1.43
1.29
0.29
0.29
2.0
0.14
Market
Research
Bureau
-
0.005
1.5
1.5
-
-
-
0.86
1.0
-
1.0
-
-
4.0
1.5
0.57
-
-
-
-
1.0
-
-
-
2.0
0.29
0.14
1.5
0.033
Page
17-14
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued)
Product Type
Amount of
Product Per
Application3
Average Frequency of Use
(per day)
Upper 90th Percentile Frequency of
Use
(per day)
Survey Type
Survey Type
(grams)
CTFA
Cosmetic
Marketb
Research
Bureau
CTFA
Cosmetic
Market
Research
Bureau
Face, Body and Hand Preps 3.5 0.65
(excluding shaving preps)
Foot Powder and Sprays - 0.061
Hormones - 0.012
Moisturizers 0.5 0.98
Night Skin Care Products 1.3 0.18
Paste Masks (mud packs) 3.7 0.027
Skin Lighteners
Skin Fresheners and 2.0 0.33
Astringents
Wrinkle Smoothers 0.4 0.021
(removers)
Facial Cream 0.6 0.0061
Permanent Wave 101 0.003
Hair Straighteners 0.2 0.0007
Hair Dye - 0.001
Hair Lighteners - 0.0003
Hair Bleaches - 0.0005
Hair Tints - 0.0001
Hair Rinse (coloring) - 0.0004
Shampoo (coloring) - 0.0005
Hair Color Spray
Shave Cream 1.73
1.12
0.079
0.028
0.88
0.50
0.20
0.024
0.56
0.15
0.63
0.001
0.005
2.0
0.57e
0.57e
2.0
1.0
0.14
_e
i.o
i.od
0.0061
0.0082
0.005e
0.004e
0.005e
0.02e
0.005e
0.02e
0.02e
2.14
0.29
0.14e
1.71
1.0
0.43
0.14e
1.43
1.0
1.5
0.005
0.014
0.082
0.36
Values reported are the averages of the responses reported by the 20 companies interviewed.
The averages shown for the Market Research Bureau are not true averages - this is due to the fact that in many cases the class of most
frequent users is indicated by "1 or more"; also, ranges are used in many cases (i.e., "10-12"). The average, therefore, is
underestimated slightly. The "1 or more" designation also skews the 90th percentile figures in many instances. The 90th percentile
values may, in actuality, be somewhat higher for many products.
Average usage among users only for baby products.
Usage data reflects entire household use for both baby lotion and baby oil.
Fewer than 10% of individuals surveyed used these products. Value listed is lowest frequency among individuals reporting usage. In
the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during the
period of the study.
Usage data reflects entire household use.
Usage data reflects total bath product usage.
None of the individuals surveyed reported using this product.
indicate no data available.
Source: CTFA, 1983.
Exposure Factors Handbook
September 2011
Page
17-15
-------
I
5?
^5 5.
1M
is
* I
Table 17-4. Frequency of Use for Household Solvent Products (users only)
Products
Spray Shoe Polish
Water Repellents/Protectors
Spot Removers
Solvent- Type Cleaning Fluids or Degreasers
Wood Floor and Paneling Cleaners
Typewriter Correction Fluid
Adhesives
Adhesive Removers
Silicone Lubricants
Other Lubricants (excluding automotive)
Specialized Electronic Cleaners (e.g., for TVs)
Latex Paint
Oil Paint
Wood Stains, Varnishes, and Finishes
Paint Removers/Strippers
Paint Thinners
Aerosol Spray Paint
Primers and Special Primers
Aerosol Rust Removers
Outdoor Water Repellents (for wood or cement)
Glass Frostings, Window Tints, and Artificial
Snow
Engine Degreasers
Carburetor Cleaners
Aerosol Spray Paints for Cars
Auto Spray Primers
Spray Lubricant for Cars
Transmission Cleaners
Battery Terminal Protectors
Brake Quieters Cleaners
Gasket Remover
Tire/Hubcap Cleaners
Ignition and Wire Dryers
NA = Not available.
SD = Standard deviation.
Min/Max= Minimum/Maximum.
Source: Westat, 1987a.
Mean
(use/year)
10.28
3.50
15.59
16.46
8.48
40.00
8.89
4.22
10.32
10.66
13.41
3.93
5.66
4.21
3.68
6.78
4.22
3.43
6.17
2.07
2.78
4.18
3.77
4.50
6.42
10.31
2.28
3.95
3.00
2.50
11.18
3.01
Percentile Rankings for Frequency of Use/Year
20.10
11.70
43.34
44.12
20.89
74.78
26.20
12.30
25.44
25.46
38.16
20.81
23.10
12.19
9.10
22.10
15.59
8.76
9.82
3.71
21.96
13.72
7.10
9.71
33.89
30.71
3.55
24.33
6.06
4.39
18.67
5.71
Min
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.03
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.03
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
NA
1.00
NA
NA
1.00
1.00
5
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.10
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
10
1.00
1.00
1.00
1.00
1.00
2.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.23
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
25
2.00
1.00
2.00
2.00
NA
4.00
2.00
1.00
2.00
2.00
2.00
1.00
1.00
1.00
4.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
2.00
1.00
1.00
1.00
1.00
2.00
1.00
50
4.00
2.00
3.00
4.00
2.00
12.00
3.00
1.00
3.00
4.00
3.00
2.00
1.00
2.00
2.00
2.00
2.00
1.00
2.00
2.00
1.00
2.00
2.00
2.00
2.00
3.00
1.00
2.00
2.00
1.00
4.00
2.00
75
8.00
3.00
10.00
12.00
6.00
40.00
6.00
3.00
10.00
10.00
10.00
4.00
3.00
4.00
3.00
4.00
4.00
3.00
6.00
2.00
1.00
3.25
3.00
4.00
3.75
6.00
2.00
2.00
2.00
2.00
12.00
3.00
90
24.30
6.00
40.00
46.00
24.00
100.00
15.00
6.00
20.00
20.00
24.00
6.00
6.00
7.00
6.00
12.00
6.10
6.00
15.00
3.00
2.00
6.70
6.00
10.00
10.00
20.00
3.00
4.00
6.00
5.00
30.00
5.00
95
52.00
10.00
52.00
52.00
50.00
200.00
28.00
16.80
46.35
50.00
52.00
10.00
12.00
12.00
11.80
23.00
12.00
10.00
24.45
5.90
2.00
12.00
12.00
15.00
15.00
40.00
9.00
6.55
10.40
6.50
50.00
9.70
99
111.26
35.70
300.00
300.00
56.00
365.00
100.00
100.00
150.00
100.00
224.50
30.00
139.20
50.80
44.56
100.00
31.05
50.06
50.90
12.00
27.20
41.70
47.28
60.00
139.00
105.60
NA
41.30
NA
NA
77.00
44.52
Max
156.00
300.00
365.00
365.00
350.00
520.00
500.00
100.00
300.00
420.00
400.00
800.00
300.00
250.00
100.00
352.00
365.00
104.00
80.00
52.00
365.00
300.00
100.00
100.00
500.00
365.00
26.00
365.00
52.00
30.00
200.00
60.00
Q
I
I-
ri
-------
II
il
._
I
Table 17-5. Exposure Time of Use for Household Solvent Products (users only)
Products
Spray Shoe Polish
Water Repellents/Protectors
Spot Removers
Solvent-Type Cleaning Fluids or Degreasers
Wood Floor and Paneling Cleaners
Typewriter Correction Fluid
Adhesives
Adhesive Removers
Silicone Lubricants
Other Lubricants (excluding automotive)
Specialized Electronic Cleaners (e.g., for TVs)
Latex Paint
Oil Paint
Wood Stains, Varnishes, and Finishes
Paint Removers/Strippers
Paint Thinners
Aerosol Spray Paint
Primers and Special Primers
Aerosol Rust Removers
Outdoor Water Repellents (for wood or cement)
Glass Frostings, Window Tints, and Artificial Snow
Engine Degreasers
Carburetor Cleaners
Aerosol Spray Paints for Cars
Auto Spray Primers
Spray Lubricant for Cars
Transmission Cleaners
Battery Terminal Protectors
Brake Quieters/Cleaners
Gasket Remover
Tire/Hubcap Cleaners
Ignition and Wire Dryers
NA = Not available.
SD = Standard deviation.
Min/Max = Minimum/Maximum.
Source: Westat, 1987a.
Mean
(minutes)
7.49
14.46
10.68
29.48
74.04
7.62
15.58
121.20
10.42
8.12
9.47
295.08
194.12
117.17
125.27
39.43
39.54
91.29
18.57
104.94
29.45
29.29
13.57
42.77
51.45
9.90
27.90
9.61
23.38
23.57
22.66
7.24
Percentile Rankings for Duration of Use (minutes)
9.60
24.10
22.36
97.49
128.43
29.66
81.80
171.63
29.47
32.20
45.35
476.11
345.68
193.05
286.59
114.85
87.79
175.05
48.54
115.36
48.16
48.14
23.00
71.39
86.11
35.62
61.44
18.15
36.32
27.18
23.94
8.48
Min
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.05
0.02
0.02
0.03
0.02
0.02
0.03
0.05
0.02
0.17
0.03
0.07
0.33
0.08
0.02
1
0.03
0.08
0.03
0.03
1.00
0.02
0.03
0.03
0.03
0.03
0.03
1.00
0.51
0.74
0.38
0.08
0.17
0.24
0.05
0.05
0.14
0.95
0.08
0.19
0.22
0.03
NA
0.04
NA
NA
0.71
0.02
5
0.25
0.50
0.08
1.00
5.00
0.03
0.08
1.45
0.08
0.05
0.08
22.50
15.00
5.00
5.00
1.00
2.00
3.00
0.17
5.00
2.00
2.00
0.33
1.00
2.00
0.08
0.35
0.08
0.50
0.50
3.00
0.08
10
0.50
1.40
0.25
2.00
10.00
0.03
0.33
3.00
0.17
0.08
0.17
30.00
30.00
10.00
5.00
2.00
5.00
5.00
0.25
15.00
3.00
5.00
1.00
3.00
5.00
0.17
1.80
0.23
1.00
2.00
5.00
0.47
25
2.00
3.00
2.00
5.00
20.00
0.17
1.00
15.00
0.50
0.50
0.50
90.00
60.00
30.00
20.00
5.00
10.00
15.00
2.00
30.00
5.00
10.00
3.00
10.00
10.00
1.00
5.00
1.00
5.00
6.25
10.00
1.50
50
5.00
10.00
5.00
15.00
30.00
1.00
4.25
60.00
2.00
2.00
2.00
180.00
12.00
60.00
60.00
10.00
20.00
30.00
5.00
60.00
15.00
15.00
7.00
20.00
27.50
5.00
15.00
5.00
15.00
15.00
15.00
5.00
75
10.00
15.00
10.00
30.00
90.00
2.00
10.00
120.00
10.00
5.00
5.00
360.00
240.00
120.00
120.00
30.00
45.00
120.00
20.00
120.00
30.00
30.00
15.00
60.00
60.00
10.00
30.00
10.00
30.00
30.00
30.00
10.00
90
18.00
30.00
30.00
60.00
147.00
10.00
30.00
246.00
20.00
15.00
20.00
480.00
480.00
140.00
240.00
60.00
60.00
240.00
60.00
240.00
60.00
60.00
30.00
120.00
120.00
15.00
60.00
20.00
49.50
60.00
60.00
15.00
95
30.00
60.00
30.00
120.00
240.00
32.00
60.00
480.00
45.00
30.00
30.00
810.00
579.00
360.00
420.00
180.00
120.00
360.00
60.00
300.00
96.00
120.00
45.00
145.00
180.00
30.00
60.00
30.00
120.00
60.00
60.00
25.50
99
60.00
120.00
120.00
300.00
480.00
120.00
180.00
960.00
180.00
90.00
93.60
2,880.00
1,702.80
720.00
1,200.00
480.00
300.00
981.60
130.20
480.00
268.80
180.00
120.00
360.00
529.20
120.00
NA
120.00
NA
NA
120.00
48.60
Max
60.00
480.00
360.00
1,800.00
2,700.00
480.00
2,880.00
960.00
360.00
900.00
900.00
5,760.00
5,760.00
280.00
4,320.00
2,400.00
1,800.00
1,920.00
720.00
960.00
360.00
900.00
300.00
900.00
600.00
720.00
450.00
180.00
240.00
180.00
240.00
60.00
Q
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oo
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^5 5.
IS
IS
* 1
Table 17-6
Products
Spray Shoe Polish
Water Repellents/Protectors
Spot Removers
Solvent- Type Cleaning Fluids or Degreasers
Wood Floor and Paneling Cleaners
Typewriter Correction Fluid
Adhesives
Adhesive Removers
Silicone Lubricants
Other Lubricants (excluding automotive)
Specialized Electronic Cleaners (e.g., for TVs)
Latex Paint
Oil Paint
Wood Stains, Varnishes, and Finishes
Paint Removers/Strippers
Paint Thinners
Aerosol Spray Paint
Primers and Special Primers
Aerosol Rust Removers
Outdoor Water Repellents (for wood or cement)
Glass Frostings, Window Tints, and Artificial Snow
Engine Degreasers
Carburetor Cleaners
Aerosol Spray Paints for Cars
Auto Spray Primers
Spray Lubricant for Cars
Transmission Cleaners
Battery Terminal Protectors
Brake Quieters/Cleaners
Gasket Remover
Tire/Hubcap Cleaners
Ignition and Wire Dryers
NA = Not available.
SD = Standard deviation.
Min/Max = Minimum/Maximum.
Source: Westat, 1987a.
Amount of Products Used
Mean
(ounces/year)
9.90
11.38
26.32
58.30
28.41
4.14
7.49
34.46
12.50
9.93
9.48
371.27
168.92
65.06
63.73
69.45
30.75
68.39
18.21
148.71
13.82
46.95
22.00
44.95
70.37
18.63
35.71
16.49
11.72
13.25
31.58
9.02
SD
17.90
22.00
90.10
226.97
57.23
13.72
55.90
96.60
27.85
44.18
55.26
543.86
367.82
174.01
144.33
190.55
52.84
171.21
81.37
280.65
14.91
135.17
50.60
89.78
274.56
54.74
62.93
87.84
13.25
22.35
80.39
14.59
for Household Solvent Products (users only)
Percentile Rankings for Amount of Products Used (ounces/year)
Min.
0.04
0.04
0.01
0.04
0.03
0.01
0.01
0.25
0.02
0.01
0.01
0.03
0.02
0.12
0.64
0.03
0.02
0.01
0.09
0.01
1.00
0.04
0.10
0.04
0.12
0.08
2.00
0.12
0.50
0.50
0.12
0.13
i
0.20
0.47
0.24
0.50
0.80
0.02
0.02
0.29
0.20
0.18
0.05
4.00
0.33
1.09
1.50
0.45
0.75
0.09
0.25
0.37
1.40
1.56
0.50
0.14
0.77
0.40
NA
0.13
NA
NA
0.50
0.32
5
0.63
0.98
0.60
2.00
2.45
0.06
0.05
1.22
0.69
0.30
0.13
12.92
4.00
4.00
4.00
3.10
2.01
1.30
1.00
3.63
2.38
4.00
1.50
1.50
3.00
0.96
3.75
0.58
1.00
1.00
1.82
1.09
10
1.00
1.43
1.00
3.00
3.50
0.12
0.12
2.80
1.00
0.52
0.25
32.00
8.00
4.00
8.00
4.00
3.25
3.23
1.43
8.00
3.25
6.00
3.00
3.00
4.00
1.00
4.00
1.00
2.00
1.00
3.00
1.50
25
2.00
2.75
2.00
6.50
7.00
0.30
0.35
6.00
2.25
1.00
0.52
64.00
25.20
8.00
16.00
8.00
7.00
8.00
2.75
16.00
6.00
12.00
5.22
6.12
9.00
2.75
8.00
2.00
3.02
3.75
6.00
3.00
50
4.50
6.00
5.50
16.00
14.00
0.94
1.00
10.88
4.50
2.25
2.00
256.00
64.00
16.00
32.00
20.48
13.00
16.00
8.00
64.00
12.00
16.00
12.00
16.00
16.00
6.00
15.00
4.00
8.00
7.75
12.00
6.00
75
10.00
12.00
16.00
32.00
30.00
2.40
3.00
32.00
12.00
8.00
6.00
384.00
148.48
64.00
64.00
64.00
32.00
60.00
13.00
128.00
14.00
36.00
16.00
48.00
48.00
15.50
32.00
8.00
14.25
16.00
28.00
10.75
90
24.00
24.00
48.00
96.00
64.00
8.00
8.00
64.00
24.00
18.00
12.65
857.60
384.00
128.00
128.00
128.00
65.00
128.00
32.00
448.00
28.00
80.00
39.00
100.80
128.00
36.00
77.00
15.00
32.00
24.00
64.00
16.00
95
36.00
33.00
119.20
192.00
96.00
18.00
20.00
138.70
41.20
32.00
24.00
1,280.00
640.00
256.00
256.00
256.00
104.00
256.00
42.60
640.00
33.00
160.00
75.00
156.00
222.00
64.00
140.00
24.60
38.60
58.40
96.00
20.55
99
99.36
121.84
384.00
845.00
204.40
67.44
128.00
665.60
192.00
128.00
109.84
2,560.00
1,532.16
768.00
512.00
640.00
240.00
867.75
199.80
979.20
98.40
480.00
212.00
557.76
1,167.36
240.00
NA
627.00
NA
NA
443.52
113.04
Max
180.00
450.00
1,600.00
5,120.00
1,144.00
181.80
1,280.00
1,024.00
312.00
1,280.00
1,024.00
6,400.00
5,120.00
3,840.00
2,560.00
3,200.00
1,053.00
1,920.00
1,280.00
3,200.00
120.00
2,560.00
672.00
900.00
3840.00
864.00
360.00
1,050.00
78.00
160.00
960.00
120.00
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II
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Table 17-7.
Products
Spray Shoe Polish
Water Repellents/Protectors
Spot Removers
Solvent-Type Cleaning Fluids or Degreasers
Wood Floor and Paneling Cleaners
Typewriter Correction Fluid
Adhesives
Adhesive Removers
Silicone Lubricants
Other Lubricants (excluding automotive)
Specialized Electronic Cleaners (e.g., for TVs)
Latex Paint
Oil Paint
Wood Stains, Varnishes, and Finishes
Paint Removers/Strippers
Paint Thinners
Aerosol Spray Paint
Primers and Special Primers
Aerosol Rust Removers
Outdoor Water Repellents (for wood or cement)
Glass Frostings, Window Tints, and Artificial Snow
Engine Degreasers
Carburetor Cleaners
Aerosol Spray Paints for Cars
Auto Spray Primers
Spray Lubricant for Cars
Transmission Cleaners
Battery Terminal Protectors
Brake Quieters/Cleaners
Gasket Remover
Tire/Hubcap Cleaners
Ignition and Wire Dryers
NA = Not available.
SD = Standard deviation.
Min/Max = Minimum/Maximum.
Source: Westat, 1987a.
Time Exposed After Duration of Use for Household Solvent Products (users only)
Mean
(minutes)
31.40
37.95
43.65
33.29
96.75
124.70
68.88
94.12
30.77
47.45
117.24
91.38
44.56
48.33
31.38
32.86
12.70
22.28
15.06
8.33
137.87
4.52
7.51
10.71
11.37
4.54
5.29
3.25
10.27
27.56
1.51
6.39
SD
80.50
111.40
106.97
90.39
192.88
153.46
163.72
157.69
107.39
127.11
154.38
254.61
155.19
156.44
103.07
105.62
62.80
65.57
47.58
43.25
243.21
24.39
68.50
45.53
45.08
30.67
29.50
17.27
30.02
58.54
20.43
31.63
Percentile Rankings for Time Exposed After Duration of Use (minutes)
Min.
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
NA
NA
NA
NA
0.00
0.00
5
0.00
0.00
0.00
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
10
0.00
0.00
0.00
0.00
0.00
5.00
0.00
0.00
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
25
0.00
0.00
1.00
0.00
5.00
30.00
1.00
1.75
0.00
0.00
10.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
50
5.00
3.00
5.00
3.00
30.00
60.00
10.00
20.00
0.00
2.00
60.00
5.00
0.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
60.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
75
20.00
20.00
30.00
28.75
120.00
180.00
60.00
120.00
10.00
30.00
180.00
60.00
30.00
30.00
20.00
15.00
1.00
10.00
5.00
0.00
180.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
12.50
0.00
0.00
90
120.00
120.00
120.00
60.00
240.00
360.00
180.00
360.00
60.00
120.00
300.00
240.00
120.00
120.00
60.00
60.00
30.00
60.00
60.00
5.00
360.00
0.00
0.10
17.50
20.00
2.00
5.00
2.90
30.00
120.00
0.00
0.10
95
120.00
240.00
240.00
180.00
480.00
480.00
360.00
480.00
180.00
240.00
480.00
480.00
240.00
240.00
180.00
180.00
60.00
120.00
60.00
58.50
480.00
15.50
30.00
60.00
77.25
15.00
22.50
15.00
120.00
180.00
0.00
30.00
99
480.00
480.00
480.00
480.00
1,062.00
600.00
720.00
720.00
480.00
485.40
720.00
1,440.00
480.00
694.00
541.20
480.00
260.50
319.20
190.20
309.60
1,440.00
120.00
120.60
282.00
360.00
70.20
NA
120.00
NA
NA
30.00
216.60
Max
720.00
1,800.00
1,440.00
1,440.00
1,440.00
1,800.00
2,100.00
720.00
1,440.00
1,440.00
1,440.00
2,880.00
2,880.00
2,880.00
1,440.00
1,440.00
1,440.00
720.00
600.00
420.00
1,800.00
360.00
1,800.00
480.00
360.00
420.00
240.00
180.00
120.00
240.00
480.00
240.00
Q
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household
Cleaning Products
Tasks
Clean Bathroom Sinks and Tubs
Clean Kitchen Sinks
Clean Inside of Cabinets
(e.g., kitchen)
Clean Outside of Cabinets
Wipe Off Kitchen Counters
Thoroughly Clean Counters
Clean Bathroom Floors
Clean Kitchen Floors
Clean Bathroom or Other tilted or Ceramic Walls
Mean Median Product Type Percent of
(hours/year) (hours/year) Used Preference
44 26 Liquid
Powder
Aerosol
Spray pump
Other
41 18 Liquid
Powder
Aerosol
Spray pump
Other
12 5 Liquid
Powder
Aerosol
Spray pump
Other
21 6 Liquid
Powder
Aerosol
Spray pump
Other
92 55 Liquid
Powder
Aerosol
Spray pump
Other
24 13 Liquid
Powder
Aerosol
Spray pump
Other
20 9 Liquid
Powder
Aerosol
Spray pump
Other
31 14 Liquid
Powder
Aerosol
Spray pump
Other
16 9 Liquid
Powder
Aerosol
Spray pump
Other
29%
44%
16%
10%
1%
31%
61%
2%
4%
2%
68%
12%
2%
16%
2%
61%
8%
16%
13%
2%
67%
13%
2%
15%
3%
56%
21%
5%
17%
1%
70%
21%
2%
4%
3%
70%
27%
2%
1%
37%
18%
17%
25%
3%
Page
17-20
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household
Cleaning Products (continued)
-, , Mean
Tasks ,. , ,
(hours/year)
Clean Outside of Windows 1 3
C lean Inside of Windows 1 8
Clean Glass Surfaces Such as Mirrors and Tables 34
Clean Outside of Refrigerator and Other Appliances 27
Clean Spots or Dirt on Walls or Doors 1 9
Finishes
Indicates value is less than 1%.
Source: Westat, 1987b.
Median Product Type Percent of
(hours/year) Used Preference
6 Liquid
Powder
Aerosol
Spray pump
Other
6 Liquid
Powder
Aerosol
Spray pump
Other
1 3 Liquid
Powder
Aerosol
Spray pump
Other
1 3 Liquid
Powder
Aerosol
Spray pump
Other
8 Liquid
Powder
Aerosol
Spray pump
Other
27%
2%
6%
65%
24%
1%
8%
66%
2%
13%
1%
8%
76%
2%
48%
3%
7%
38%
4%
46%
15%
4%
30%
4%
Exposure Factors Handbook
September 2011
Page
17-21
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-9. Percentile Rankings for Total Exposure Time in Performing Household Tasks
Percentile Rankings for Total Exposure Time Performing Task
(hours/year)
Tasks
Clean Bathroom Sinks and Tubs
Clean Kitchen Sinks
Clean Inside of Kitchen Cabinets
Clean Outside of Cabinets
Wipe Off Kitchen Counters
Thoroughly Clean Counters
Clean Bathroom Floors
Clean Kitchen Floors
Clean Bathroom or Other Tilted or Ceramic
Walls
Clean Outside of Windows
Clean Inside of Windows
Clean Glass Surfaces Such as Mirrors and
Tables
Clean Outside Refrigerator and Other
Appliances
Clean Spots or Dirt on Walls or Doors
Min = Minimum.
Max = Maximum.
Source: Westat, 1987b.
Min 10th
0.4 5.2
0.3 3.5
0.2 1
0.1 1
1.2 12
0.2 1.8
0.1 2
0.5 4.3
0.2 1
0.1 1.5
0.2 1.2
0.2 1.7
0.1 1.8
0.1 0.6
25th
13
8.7
2
2
24.3
6
4.3
8.7
3
2
3
6
4.3
2
50th
26
18.3
4.8
6
54.8
13
8.7
14
8.7
6
6
13
13
8
75th
52
60.8
12
17.3
91.5
26
26
26
26
11.5
19.5
26
30.4
24
90th
91.3
97.6
32.5
36
231.2
52
36.8
52
36
24
36
60.8
91.3
52
95th
121.7
121.7
48
78.7
456.3
94.4
71.5
97
52
32.6
72
104
95.3
78
Max
365
547.5
208
780
912.5
547.5
365
730
208
468
273
1460
365
312
Page
17-22
Exposure Factors Handbook
September 2011
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I!
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Table 17-10. Mean Percentile Rankings for Frequency of Performing Household Tasks
Tasks
Clean Bathroom Sinks and Tubs
Clean Kitchen Sinks
Clean Inside of Cabinets Such as Those
in the Kitchen
Clean Outside of Cabinets
Wipe Off Counters Such as Those in the
Kitchen
Thoroughly Clean Counters
Clean Bathroom Floors
Clean Kitchen Floors
Clean Bathroom or Other Tiled or
Ceramic Walls
Clean Outside of Windows
Clean Inside of Windows
Clean Other Glass Surfaces such as
Mirrors and Tables
Clean Outside of Refrigerator and Other
Appliances
Clean Spots or Dirt on Walls or Doors
Min = Minimum.
Max = Maximum.
Source: Westat, 1987b.
Mean
3 x/week
7 x/week
9 x/year
3 x/month
2 x/day
8 x/month
6 x/month
6 x/month
4 x/month
5 x/year
10 x/year
7 x/month
10 x/month
6 x/month
Percentile Rankings
Min
0.2 x/week
0 x/week
1 x/year
0.1 x/month
0 x/day
0.1 x/month
0.2 x/month
0.1 x/month
0.1 x/month
1 x/year
1 x/year
0.1 x/month
0.2 x/month
0.1 x/month
10th
1 x/week
1 x/week
1 x/year
0.1 x/month
0.4 x/day
0.8 x/month
1 x/month
1 x/month
0.2 x/month
1 x/year
1 x/year
1 x/month
1 x/month
0.2 x/month
25*
1 x/week
2 x/weak
1 x/year
0.3 x/month
1 x/day
1 x/month
2 x/month
2 x/month
1 x/month
1 x/year
2 x/year
2 x/month
2 x/month
0.3 x/month
th
2 x/week
7 x/week
2 x/year
1 x/month
1 x/day
4 x/month
4 x/month
4 x/month
2 x/month
2 x/year
4 x/year
4 x/month
4 x/month
1 x/month
75th
3.5 x/week
7 x/week
12 x/year
4 x/month
3 x/day
4 x/month
4 x/month
4 x/month
4 x/month
4 x/year
12 x/year
4 x/month
13 x/month
4 x/month
90th
7 x/week
15 x/week
12 x/year
4 x/month
4 x/day
30 x/month
13 x/month
13 x/month
9 x/month
12 x/year
24 x/year
17 x/month
30 x/month
13 x/month
95th
7 x/week
21 x/week
52 x/year
22 x/month
6 x/day
30 x/month
30 x/month
30 x/month
13 x/month
12 x/year
52 x/year
30 x/month
30 x/month
30 x/month
Max
42 x/week
28 x/week
156 x/year
30 x/month
16 x/day
183 x/month
30 x/month
30 x/month
30 x/month
156 x/year
156 x/year
61 x/month
61 x/month
152 x/month
Q
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-11. Mean and Percentile Rankings for Exposure Time per Event of Performing Household
,,, . Mean
Tasks , . , .
(minutes/event
Clean Bathroom Sinks and Tubs
Clean Kitchen Sinks
Clean Inside of Cabinets Such as Those in the
Kitchen
Clean Outside of Cabinets
Wipe Off Counters Such as Those in the
Kitchen
Thoroughly Clean Counters
Clean Bathroom Floors
Clean Kitchen Floors
Clean Bathroom or Other Tiled or Ceramic
Walls
Clean Outside of Windows
Clean Inside of Windows
Clean Other Glass Surfaces Such as Mirrors
and Tables
Clean Outside of Refrigerator and Other
Appliances
Clean Spots or Dirt on Walls or Doors
Min = Minimum.
Max = Maximum.
Source: Westat, 1987b.
20
10
137
52
9
25
16
30
34
180
127
24
19
50
Tasks
Percentile Rankings (minutes/event)
) Min
1
1
5
1
1
1
1
2
1
4
4
1
1
1
10th
5
2
24
5
2
5
5
10
5
30
20
5
4
5
25th
10
3
44
15
3
10
10
15
15
60
45
10
5
10
50th
15
5
120
30
5
15
15
20
30
120
90
15
10
20
75th
30
10
180
60
10
30
20
30
45
240
158
30
20
60
90th
45
15
240
120
15
60
30
60
60
420
300
60
30
120
95th
60
20
360
180
30
90
38
60
120
480
381
60
45
216
Max
90
480
2,880
330
120
180
60
180
240
1,200
1,200
180
240
960
Table 17-12. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning"
Products
Dish Detergents
Glass Cleaners
Floor Cleaners
Furniture Polish
Bathroom Tile Cleaners
Liquid Cleansers
Scouring Powders
Laundry Detergents
Rug Cleaners/Shampoos
All Purpose Cleaners
Mean
(hours/year)
107
67
52
32
47
68
78
66
12
64
Percentile Rankings of Total Exposure Time
(hours/year)
Min 10th
0.2
0.4
0.7
0.1
0.5
0.2
0.3
0.6
0.3
0.3
6
3
4
0.3
2
2
9
8
0.3
4
25th
24
12
7
1
8
9
17
14
0.3
9
a The data in Table 17-12 reflect only the 14 tasks included in the
the table underestimate the hours of the use of the product group
not included.
Min = Minimum.
Max = Maximum.
Source: Westat, 1987b.
50th
56
29
22
12
17
22
35
48
9
26
75th
134
62
52
36
48
52
92
103
26
77
90th
274
139
102
101
115
122
165
174
26
174
95th
486
260
414
215
287
215
281
202
26
262
Max
941
1,508
449
243
369
2,381
747
202
26
677
survey. Therefore, many of the durations reported in
. For example, use of dish detergents to wash dishes is
Page
17-24
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-13. Total Exposure Time of Painting Activity of Interior Painters (hours)
T° ^-T-, • i Mean „„
Types of Paint ,. . SD
J r (hours)
Latex 12.2 11.3
Oil-Based 10.7 15.6
Wood Stains and Varnishes 8.6 10.9
SD = Standard deviation.
Min = Minimum.
Max = Maximum.
Source: Westat, 1987c.
Percentile Rankings for Duration of Painting Activity
(hours)
Min 10 25 50 75 90 95 Max
1 3 4 9 15 24 40 248
1 1.6 3 6 10 21.6 65.6 72
1 1 2 4 9.3 24 40 42
Table 17-14. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions
Spent Painting per Year
Duration of Frequency of
Painting/Occasion Occasions Spent
(hours) Painting/Year Percentile Rankings for Frequency of Occasions Spent Painting
Types of Paint Mean Median Mean SD Min 10 25 50 75
Latex 3.0 3 4.2 5.5 11234
Oil-Based 2.1 3 5.1 12.0 11124
Wood Stains and 2.2 2 4.0 4.9 11124
Varnishes
90 95 Max
9 10 62
8 26 72
9 20 20
SD = Standard deviation.
Min = Minimum.
Max = Maximum.
Source: Westat, 1987c.
Table 17-15. Amount of Paint Used by Interior Painters
~ f-n • . Median
Types ol Paint , „ .
J ^ (gallons)
Latex 3.0
Oil-Based 2.0
Wood Stains and 0.8
Varnishes
SD = Standard deviation.
Min = Minimum.
Max = Maximum.
Source: Westat, 1987c.
Percentile Rankings for Amount of Paint Used
TV/Tpnn / 11 \
iviean ^^ (gallons)
(gallons)
Min 10 25 50 75 90 95 Max
3.9 4.6 0.1 1 2 3 5 8 10 50
2.6 3.0 0.1 0.3 0.5 2 3 7 12 12
0.9 0.8 0.1 0.1 0.3 0.8 122 4.3
Exposure Factors Handbook
September 2011
Page
17-25
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-16. Frequency of Use
Mean
Standard Deviation
Minimum Value
lstPercentile
5th Percentile
10th Percentile
25th Percentile
Median Value
75th Percentile
90th Percentile
95th Percentile
99th Percentile
Maximum Value
No. of Times
Used Within the
Last 12 Months
jV = 58
1.66
1.67
1.00
1.00
1.00
1.00
1.00
1.00
2.00
3.00
5.00
12.00
12.00
Minutes
Using
N=52
172.87
304.50
5.00
5.00
10.00
15.00
29.50
120.00
240.00
480.00
1,440.00
1,440.00
1,440.00
and Amount of Product Used for Adhesive Removers
Minutes in Room
After Usinga
AT =51
13.79
67.40
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
120.00
420.00
420.00
Minutes in
Room After
Usingb
N=5
143.37
169.31
5.00
5.00
5.00
5.00
20.00
120.00
420.00
420.00
420.00
420.00
1,440.00
Amount Used in
Past Year (fluid oz.)
AT =51
96.95
213.20
13.00
13.00
13.00
16.00
16.00
32.00
96.00
128.00
384.00
1,280.00
1,280.00
Amount per
Use (fluid oz.)
AT =51
81.84
210.44
5.20
5.20
6.50
10.67
16.00
26.00
64.00
128.00
192.00
1,280.00
1,280.00
a Includes those who did not spend any time in the room after use.
b Includes only those who spent time in the room.
Source: Abt, 1992.
Table 17-17. Adhesive Remover Usage
by Sex
Sex
Mean number of months since last time adhesive remover was used - includes
all respondents (unweighted N = 240).
Mean number of uses of product in the past year.
Mean number of minutes spent with the product during last use.
Mean number of minutes spent in the room after last use of product. (Includes
all recent users.)
Mean number of minutes spent in the room after last use of product. (Includes
only those who did not leave immediately.)
Mean ounces of product used in the past year.
Mean ounces of product used per use in the past year.
Male
N = 25
35.33
1.94
127.95
19.76
143.37
70.48
48.70
Female
N=33
43.89
1.30
233.43
0
0
139.71
130.36
Source: Abt, 1992.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-18.
Frequency of Use and Amount of Product Used for Spray Paint
No. of Times
Used Within the Minutes
Last 12 Months Using
N = 775 N = 786
Mean
Standard Deviation
Minimum Value
lstPercentile
5th Percentile
10th Percentile
25th Percentile
Median Value
75th Percentile
90th Percentile
95th Percentile
99th Percentile
Maximum Value
8.23
31.98
1.00
1.00
1.00
1.00
1.00
2.00
4.00
11.00
20.00
104.00
365.00
40.87
71.71
1.00
1.00
3.00
5.00
10.00
20.00
45.00
90.00
120.00
360.00
960.00
Minutes in Room Minutes in Room
After Using" After Usingb
W = 791 jV = 35
3.55
22.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
120.00
300.00
65.06
70.02
1.00
1.00
1.00
10.00
15.00
30.00
60.00
120.00
120.00
300.00
300.00
Amount Used in
Past Year
(fluid oz.)
jV = 778
83.92
175.32
13.00
13.00
13.00
13.00
13.00
26.00
65.00
156.00
260.00
1,170.00
1,664.00
Amount per
Use (fluid oz.)
jV = 778
19.04
25.34
0.36
0.36
3.47
6.50
9.75
13.00
21.67
36.11
52.00
104.00
312.00
a Includes those who did not spend any time in the room after use.
b Includes only those who spent time in the room.
Source: Abt, 1992.
Table 17-19. Spray Paint Usage by Sex
Sex
Mean number of months since last time spray paint was used - includes all
respondents (unweighted N = 1724).
Mean number of uses of product in the past year.
Mean number of minutes spent with the product during last use.
Mean number of minutes spent in the room after last use of product. (Includes
all recent users.)
Mean number of minutes spent in the room after last use of product. (Includes
only those who did not leave immediately.)
Mean ounces of product used in the past year.
Mean ounces of product used per use in the past year.
Male
N = 405
17.39
10.45
40.87
5.49
67.76
103.07
18.50
Female
jV=386
26.46
4.63
40.88
0.40
34.69
59.99
19.92
Source: Abt, 1992.
Exposure Factors Handbook
September 2011
Page
17-27
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-20. Frequency of Use and Amount of Product Used for Paint Removers/Strippers
No. of Times
Used Within the Minutes Minutes in Room Minutes in Room
Last 12 Months Using After Using3 After Usingb
jV=316 jV=390 jV = 390 N = 39
Mean
Standard Deviation
Minimum Value
lstPercentile
5th Percentile
10th Percentile
25th Percentile
Median Value
75th Percentile
90th Percentile
95th Percentile
99th Percentile
Maximum Value
3.54 144.59
7.32 175.54
1.00 2.00
1.00 5.00
1.00 15.00
1.00 20.00
1.00 45.00
2.00 120.00
3.00 180.00
6.00 360.00
12.00 480.00
50.00 720.00
70.00 1,440.00
12.96
85.07
0.00
0.00
0.00
0.00
0.00
0.00
0.00
10.00
60.00
180.00
1,440.00
93.88
211.71
1.00
1.00
1.00
3.00
10.00
60.00
120.00
180.00
420.00
1,440.00
1,440.00
Amount Used in
Past Year
(fluid oz.)
jV=307
142.05
321.73
15.00
15.00
16.00
16.00
32.00
64.00
128.00
256.00
384.00
1,920.00
3,200.00
Amount per
Use (fluid oz.)
jV=307
64.84
157.50
0.35
2.67
8.00
10.67
16.00
32.00
64.00
128.00
192.00
320.00
2,560.00
a Includes those who did not spend any time in the room after use.
b Includes only those who spent time in the room.
Source: Abt, 1992.
Table 17-21. Paint Stripper Usage by
Sex
Sex
Mean number of months since last time paint stripper was used - includes all
respondents (unweighted N = 1724).
Mean number of uses of product in the past year.
Mean number of minutes spent with the product during last use.
Mean number of minutes spent in the room after last use of product. (Includes
all recent users.)
Mean number of minutes spent in the room after last use of product. (Includes
only those who did not leave immediately.)
Mean ounces of product used in the past year.
Mean ounces of product used per use in the past year.
Male
jV=156
32.07
3.88
136.70
15.07
101.42
160.27
74.32
Female
jV=162
47.63
3.01
156.85
9.80
80.15
114.05
50.29
Source: Abt, 1992.
Page
17-28
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-22.
Age Group
5 to 1 1 years
12 to 17
18 to 64
years
years
> 64 years
Note:
Source:
Number of Minutes Spent Using Any Microwave Oven (minutes/day)
N
62
141
1
0
0
1,686 0
375
A value of "121"
N = doer sample
of minutes.
U.S. EPA,
1996.
0
2
0
0
0
0
5
0
0
1
1
10 25
1 1
1 2
2 3
2 3
Percentiles
50 75
2 5
3 5
5 10
5 10
90 95
10 15
10 15
15 25
20 30
98
20
30
45
60
99
30
30
60
60
Max
30
60
121
70
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Table 17-23. Number of Minutes Spent in Activities Working With or Near Freshly
Applied Paints (minutes/day)
Age Group
Percentiles
10 25 50 75 90 95 98 99
Max
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
> 64 years
7
12
20
212
20
3
5
0
0
0
3
5
0
0
0
3
5
0.5
1
0
3
15
3
2
3
5
20
8
11
18
15
45
45
60
90
121
120
75
121
121
121
120
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
121
Note: A value of" 121" for number of minutes signifies that more than 120 minutes were spent;
jV = doer sample size; percentiles are the percentage of doers below or equal to a given number
of minutes.
Source: U.S. EPA, 1996.
Table 17-24. Number of Minutes Spent in Activities Working With or Near Household
Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
> 64 years
Percentiles
N 1
21 0
26 1
41 0
672 0
127 0
2
0
1
0
0
0
5
0
2
0
1
0
10
0
2
0
2
1
25
5
3
2
5
3
50
10
5
5
10
5
75
15
15
10
20
15
90 95
20 30
30 30
40 60
60 121
30 60
98
121
30
60
121
120
99
121
30
60
121
121
Max
121
30
60
121
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
N = doer sample size; percentiles are the percentage of doers below or equal to a given number
of minutes.
Source: U.S. EPA,
1996.
Exposure Factors Handbook
September 2011
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17-29
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-25. Number of Minutes Spent in Activities (at home or elsewhere) Working with
or Near Floorwax, Furniture Wax, or Shoe Polish (minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
> 64 years
Percentiles
N
13
21
15
238
34
Note: A value of "121"
N = doer sample
of minutes.
Source: U.S. EPA,
1996.
1
0
0
0
0
0
2
0
0
0
0
0
5
0
2
0
2
0
10
5
2
1
3
2
25
10
3
2
5
5
50
15
5
10
15
10
75 90
20 60
10 35
25 45
95 98
121 121
60 120
121 121
30 120 121 121
20 35
121 121
99
121
120
121
121
121
Max
121
120
121
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Table 17-26. Number of Minutes Spent in Activities Working with or Near Glue
(minutes/day)
1 to 4 years 6
5 to 11 years 36
12 to 17 years 34
18 to 64 years 207
> 64 years 10
Note: A value of "121'
N = doer sample
of minutes.
Source: U.S. EPA, 1996.
Percentiles
1 2
0 0
2 2
0 0
0 0
0 0
5
0
3
1
0
0
10
0
5
2
1
0
25
30
5
5
5
0
50
30
12.5
10
20
4
75
30
25
30
90
60
90
50
30
30
121
121
95
50
60
60
121
121
98
50
120
120
121
121
99
50
120
120
121
121
Max
50
120
120
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Table 17-27. Number of Minutes Spent in Activities Working with or Near Solvents,
Fumes, or Strong Smelling Chemicals (minutes/day)
1 to 4 years 7
5 to 11 years 16
12 to 17 years 38
18 to 64 years 407
> 64 years 21
Note: A value of "121"
jV = doer sample
of minutes.
Source: U.S. EPA, 1996.
Percentiles
1
0
0
0
0
0
2
0
0
0
0
0
5
0
0
0
1
0
10
0
2
0
2
0
25
1
5
5
5
2
50
5
5
10
30
5
75 90
60 121
17.5 45
60 121
121 121
15 121
95
121
70
121
121
121
98
121
70
121
121
121
99
121
70
121
121
121
Max
121
70
121
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Page
17-30
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-28. Number of Minutes Spent in Activities Working with or Near Stain or Spot
Removers (minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
> 64 years
Percentiles
N
3
3
7
87
9
Note: A value of "121"
N = doer sample
of minutes.
Source: U.S. EPA,
1996.
1
0
3
0
0
0
2 5 10
0 0
3 3
0 0
0 0
0 0
0
3
0
0
0
25
0
3
5
2
2
50
0
5
15
5
3
75 90
3 3
5 5
35 60
15 60
15 121
95
3
5
60
121
121
98
3
5
60
121
121
99
3
5
60
121
121
Max
3
5
60
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Table 17-29. Number of Minutes Spent in Activities Working with or Near Gasoline or
Diesel-Powered Equipment, Besides Automobiles (minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64
years
> 64 years
Note:
Source:
Percentiles
N
14
12
25
312
26
A value of "121"
N = doer sample
of minutes.
U.S. EPA,
1996.
1
0
1
2
0
2
2
0
1
2
0
2
5 10
0
1
5
1
2
1
3
5
3
3
25
5
7.5
13
15
10
50
22.5
25
35
60
25
75 90 95 98
120 121 121 121
50 60 60 60
120 121 121 121
121 121 121 121
90 121 121 121
99
121
60
121
121
121
Max
121
60
121
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Table 17-30. Number of Minutes Spent in Activities Working with or Near Pesticides,
Including Bug Sprays or Bug Strips (minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17
18 to 64
years
years
> 64 years
Note:
Source:
Percentiles
N
6
16
10
190
764
A value of "121"
jV = doer sample
of minutes.
U.S. EPA,
1996.
1 2
1 1
0 0
0 0
0 0
31 0
5
1
0
0
0
0
10
1
0
0
1
0
25
3
1.5
2
2
02
50
10
7.5
2.5
10
5
75 90
15 20
30 121
40 121
88 121
15 60
95 98
20 20
121 121
121 121
121 121
121 121
99
20
121
121
121
121
Max
20
121
121
121
121
for number of minutes signifies that more than 120 minutes were spent;
size; percentiles are the percentage of doers below or equal to a given number
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-31. Number of Respondents Using Cologne, Perfume, Aftershave, or Other Fragrances at
Specified Daily Frequencies
Number of Times Used in a Day
Age Group
5 to 1 1 years
12 to 17 years
18 to 64 years
> 64 years
Total N Ito2 3 to 5 6 to 9
26 24 2 *
144 133 9 *
1,735 1,635 93 3
285 277 8 0
10+ Do Not
Know
* *
1 1
1 3
0 0
* = Missing data.
jV = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-32. Number of Respondents Using Any Aerosol Spray Product or Personal Care Item Such as
Deodorant or Hair Spray at Specified Daily Frequencies
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
> 64 years
40
75
103
1,071
175
Number of Times Used in a Day
1
30
57
53
724
141
2
9
14
31
263
27
3
0
1
12
39
4
4
0
1
4
15
0
5
1
1
1
13
0
6
0
1
0
1
0
7
0
0
0
1
0
10
0
0
1
2
0
10+
0
0
1
8
1
Don't Know
0
0
0
5
2
N = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-33.
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
> 64 years
Number of Respondents Using a Humidifier at Home
Total N
111
88
83
629
120
Almost
Every
Day
33
18
21
183
42
3-5 Times a
Week
16
10
7
77
10
Frequency
1-2 Times a
Week
7
12
5
70
10
1-2 Times a
Month
53
46
49
287
53
Don't
Know
2
2
1
12
5
N = Number of respondents.
Source: U.S. EPA, 1996.
Page
17-32
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-34. Number of Respondents Indicating Pesticides Were Applied by a Professional
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
Total N
at Home to
Frequency
(number of times over a 6-month period that pesticides were applied by a
professional)
None
<1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
18 to 64 years
> 64 years
15
23
32
80
106
115
87
1,264
243
N = Number of respondents.
Source: U.S. EPA reanalysis of NHAPS (U.S
9
13
9
51
59
68
40
660
146
.EPA,
Ito2
4
5
15
22
22
35
36
387
55
1996) data.
3 to 5
1
3
5
5
7
4
2
89
15
6 to 9
1
1
3
2
17
6
5
97
19
10+
0
1
0
0
1
0
1
15
3
Don't Know
0
0
0
0
0
2
3
16
5
Table 17-35. Number of Respondents Reporting Pesticides Applied by the Consumer at
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
Home to
Frequency
Total N (number of times over a 6-month period that pesticides were applied by a resident)
None
<1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to<21 years
18 to 64 years
> 64 years
15
23
32
80
106
115
87
1,264
243
N = Number of respondents.
Source: U.S. EPA reanalysis of NHAPS (U.S
4
11
18
26
37
37
36
473
94
.EPA,
Ito2
8
10
9
35
49
50
33
477
85
1996) data.
3 to 5
2
1
2
18
14
18
9
192
31
6 to 9
0
0
2
1
1
4
4
48
15
10+
1
1
1
0
4
6
4
55
9
Don't Know
0
0
0
0
1
0
1
19
9
Exposure Factors Handbook Page
September 2011 17-33
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-36. Household Demographics
and Pesticide Types, Characteristics, and
Use
Frequency of Pesticide
Survey Population Demographics
Sex
Female
Male
Language of Interview
Spanish
English
Reading Skills
Able to read English
Able to read Spanish
Number in Household
2 to 3 people
4 to 5 people
6 to 8 people
Children under 10 years
1 child
2 children
3 to 5 children
Type of Home
Single family detached
Multi-family
Trailer/mobile home
Single-family attached
Apartment/other
Pets
Pets kept in household
Pesticides used on pets
Number8
90
17
72
35
71
95
25
59
23
37
45
25
75
9
9
8
4
55
22
Percent8
84.1
15.9
67.3
32.7
66.4
88.8
23.3
55.1
21.4
34.6
42.1
23.3
70.1
8.4
8.4
7.5
3.7
51.4
40.0
Pesticide Use
Type of Pesticide
Insecticide
Rodenticide
Herbicide
Storage of Pesticide
Kitchen
Garage/shed
Laundry/washroom
Other, inside home
Other, outside home
Bathroom
Basement
Closet
Storage Precautions
Child-resistant container
Pesticide locked away
Storage Risks
< 4 feet from ground
Kept near food
Kept near dishes/cookware
Disposal
Throw it away
Wrap in separate container, throw away
Other
Frequency of Use
More than once/week
Once/week
Once/month
Once every 3 months
Once every 6 months
Once/year
Time Stored in Home
< 6 months
6 to 12 months
12 to 24 months
> 24 months
a Totals may not add up to 107 participants or
to survey questions.
Source: Bass et al., 2001.
135
10
3
67
30
14
11
7
7
4
4
83
55
72
5
5
132
10
5
20
27
42
23
16
13
75
24
17
16
91.2
6.8
2.0
45.3
20.3
9.4
7.4
4.7
4.7
2.7
2.7
56.1
37.2
48.6
3.4
3.4
89.2
6.8
3.4
13.5
18.2
28.4
15.5
10.8
8.8
50.7
15.2
11.5
10.8
148 products, and percentages may not add up to 100 because of some non-responses
Page Exposure Factors Handbook
17-34 September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-37. Amount and Frequency of Use of Household Products
Product Type —
Dishwashing Liquid
Frequency of use per day
Duration of contact (minutes)
Amount used per contact
(grams)
All-Purpose Cleaner
Frequency of use per day
Duration of contact (minutes)
Amount used per contact
(grams)
Toilet Cleaner
Frequency of use per day
Duration of contact (minutes)
Amount used per contact
(grams)
Hair Spray
Frequency of use per day
Amount used per contact
(grams)
Duration of release (seconds)
Duration of contact with
nebula (seconds)
Duration of contact with
nebula x gram released
(seconds x grams)
Mean
0.63
11
5
0.35
20
27
0.28
74
-
0.76
-
11
23
48
SD
0.79
5
3
0.70
22
30
0.55
204
-
0.68
-
6
11
48
Overall
Min Max
0 5
1 60
1 16
0 4
1 135
1 123
0 2
1 1,209
-
0 3
-
5 25
5 41
5 150
Subjects Events
45 596
45 596
13 163
28 218
28 204
12 105
18 105
28 101
-
9 143
-
12
12
10
Per Subject
Min Max
0.05 2.29
2 35
2 10
0.050 1.82
5 60
2 74
0.05 1.67
T 24a
9 153
0.29 1.76
1.0 11.6
-
-
-
a Excludes durations over 30 minutes.
Indicates insufficient sample size to estimate
Source: Weegels and van Veen, 200 1
average use.
Exposure Factors Handbook
September 2011
Page
17-35
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-38.
Product Type
Lipstick
Body lotion, hands
Body lotion, arms
Body lotion, feet
Body lotion, legs
Body lotion, neck and throat
Body lotion, back
Body lotion, other
Face cream
N = Number of subjects (women, ages 1 9
SD = Standard deviation.
Source: Loretz et al., 2005.
Frequency
N
311
308
308
308
308
308
308
308
300
to 65 years).
of Use of Cosmetic Products
Mean
2.35
2.12
1.52
0.95
1.11
0.43
0.26
0.40
1.77
Number of Applications per Day
Median
2
2
1
1
1
0
0
0
2
SD
1.80
1.59
1.30
1.01
0.98
0.82
0.63
0.76
1.16
Page
17-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-39. Amount
Summary Statistics
of Test Product Used (grams)
Total Amount Applied
for Lipstick, Body Lotion,
Average* Amount Applied per
Use Day
and Face Cream
Average* Amount
Applied per Application
Lipstick
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
99th
Best Fit Distributions and
Parameters0
0.001
2.666
0.272
0.408
0.026
0.063
0.082
0.110
0.147
0.186
0.242
0.326
0.655
0.986
2.427
Lognormal Distribution
GM = 0.14
GSD=3.56
;?-value (Gof) =0.01
0.000
0.214
0.024
0.034
0.003
0.005
0.008
0.010
0.013
0.016
0.021
0.029
0.055
0.087
0.191
Lognormal Distribution
GM= 0.01
GSD=3.45
p- value (Gof) <0.01
0.000
0.214
0.010
0.018
0.001
0.003
0.004
0.004
0.005
0.006
0.009
0.011
0.024
0.037
0.089
Lognormal Distribution
GM=0.01
GSD = 3.29
;?-value (Gof) <0.01
Body Lotion
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
0.67
217.66
103.21
53.40
36.74
51.99
68.43
82.75
96.41
110.85
134.20
160.26
0.05
36.31
8.69
5.09
3.33
4.68
5.71
6.74
7.63
9.25
10.90
12.36
0.05
36.31
4.42
4.19
1.30
1.73
2.32
2.76
3.45
4.22
4.93
6.14
Exposure Factors Handbook
September 2011
Page
17-37
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-39. Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream (continued)
Summary Statistics
90th
95th
99th
Best Fit Distributions and
Parameters0
Total Amount Applied
182.67
190.13
208.50
Beta Distribution0
Alpha = 1.53
Beta =1.77
Scale = 222.01
/7-value (GoF) = 0.06
Average* Amount Applied per
Use Day
14.39
16.83
27.91
Gamma Distribution
Location = -0.86
Scale = 2.53
Shape = 3.77
;?-value (GoF) = 0.37
Average* Amount
Applied per Application
8.05
10.22
21.71
Lognormal Distribution
GM=3.26
GSD = 2.25
^-value (GoF) = 0.63
Face Cream
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
99th
Best Fit Distributions and
Parameters0
0.04
55.85
22.36
14.01
5.75
9.35
12.83
16.15
19.86
23.79
29.31
36.12
44.58
48.89
51.29
Triangle Distribution
Minimum = -1.09
Maximum = 58.71
Likeliest = 7.53
/7-value (GoF) = 0.27
0.00
42.01
2.05
2.90
0.47
0.70
1.03
1.26
1.53
1.88
2.23
2.90
3.50
3.99
12.54
Lognormal Distribution0
GM=1.39
GSD = 2. 58
^-value(GoF)<0.01
a Derived as the ratio of the total amount used to the number of use days.
b Derived as the ratio of the total amount used to the total number of applications during the
0 None of the tested distributions provided a good fit.
GM = Geometric mean.
0.00
21.01
1.22
1.76
0.28
0.40
0.53
0.67
0.84
1.04
1.22
1.55
2.11
2.97
10.44
Lognormal Distribution0
GM=0.80
GSD = 2.55
;?-value (GoF) = 0.02
survey.
GSD = Geometric standard deviation.
GoF = Goodness of fit.
Note: Data are for women
Source: Loretz et al., 2005.
, ages 19 to 65 years.
Page
17-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-40. Frequency of Use of Personal Care Products
Average Number of Applications per Use Day
PrnrHir.t Typs jV
Mean SD Min
Hairspray (aerosol) 165b 1.49 0.63 1.00
Hairspray (pump) 162 1.51 0.64 1.00
Liquid Foundation 326 1.24 0.32 1.00
Spray Perfume 326 1.67 1.10 1.00
Body Wash 340 1.37 0.58 1.00
Shampoo 340 1.11 0.24 1.00
Solid Antiperspirant 340 1.30 0.40 1.00
a
Max
5.36
4.22
2.00
11.64
6.36
2.14
4.00
a Derived as the ratio of the number of applications to the number of use days.
b Subjects who completed the study but did not report their number of applications were excluded.
N = Number of subjects (women, ages 1 8 to 65 years).
SD = Standard deviation.
Source: Loretz et al., 2006.
Exposure Factors Handbook
September 2011
Page
17-39
-------
I
IS
s I
Table 17-41. Average Amount of Product Applied per Application" (grams)
Summary Statistics
N
Mean
SD
Minimum
Maximum
Hairspray
(aerosol)
163b
2.58
2.26
0.05
14.08
Hairspray
(pump)
161b
3.64
3.50
0.00
21.44
Spray Perfume
310b
0.33
0.41
0.00
5.08
Liquid
Foundation
321b
0.54
0.52
0.00
2.65
Shampoo
340
11.76
8.77
0.39
67.89
Body Wash
340
11.3
6.9
1.1
58.2
Solid
Antiperspirant
340
0.61
0.56
0.00
5.55
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99thc
Best Fit Distributions
and Parameters
rj-value
(Kolmo^
a
b
c
'orov-Smimov)
Derived as the ratio
0.66
0.94
1.26
1.56
1.83
2.38
2.87
3.55
5.33
7.42
8.77
11.30
Lognormal
Distribution
GM=1.84
GSD = 2.40
0.06
0.70
1.01
1.59
2.14
2.66
3.43
3.84
5.16
7.81
10.95
14.68
15.52
Lognormal
Distribution
GM = 2.44
GSD = 2.67
0.07
of the total amount used to the total
0.06
0.10
0.13
0.18
0.23
0.28
0.36
0.49
0.68
0.94
1.25
1.73
Lognormal
Distribution
GM=0.21
GSD =3. 01
0.077
number of applications.
Subjects who completed the study, but did not report their number of applications,
0.08
0.14
0.19
0.26
0.36
0.48
0.63
0.86
1.23
1.70
2.07
2.36
Lognormal
Distribution
GM=0.33
GSD = 2. 99
0.041
3.90
5.50
6.78
8.27
9.56
11.32
13.29
16.07
22.59
27.95
35.65
51.12
Lognormal
GM=9.32
GSD = 2.02
0.1328
4.6
5.8
7.1
8.5
9.5
11.4
13.4
16.0
21.1
24.3
28.4
35.1
Gamma
Location = 0.51
Scale =3. 92
Shape = 2.76
0.486
0.14
0.22
0.30
0.37
0.45
0.55
0.69
0.89
1.25
1.67
2.15
2.52
Lognormal
Distribution
GM = 0.43
GSD = 2.37
0.339
or who did not return the unused portion of the product, were excluded.
Estimate does not meet the minimum sample size criteria (N = 800) as set by the National Center for Health Statistics.
minimum sample size (N) satisfies the
N
SD
GM
GSD
Source:
following rule: n
8/(l-p)]. http://www/cdc.j
For upper percentile (>75), the
Jov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf
= Number of subjects (women, ages 19 to 65 years).
= Standard deviation.
= Geometric mean.
= Geometric standard deviation.
Loretzetal.,2006.
Q
I
I-
ri
-------
£ S1
11
ft ft
*s ^
^ «
Kj S'
^
^
£.
1=
1
^
Si
Summary Statistics
N
Mean
SD
Minimum
Maximum
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
ggthc
Best fit distributions
and parameters
p- value
(Kolmogorov-Smimov)
a Derived as the ratio
Table
Hairspray
(aerosol)
163"
3.57
3.09
0.05
18.25
0.84
1.35
1.65
2.23
2.71
3.30
3.89
4.86
7.73
9.89
13.34
15.05
Lognormal
Distribution
GM = 2.57
GSD = 2.37
0.05
17-42. Average Amount of Product Applied per Use
Hairspray
(pump)
161"
5.18
4.83
0.00
24.12
0.91
1.48
2.33
2.66
3.74
4.71
5.67
7.38
12.22
15.62
19.41
23.98
Lognormal
Distribution
GM = 3.45
GSD = 2.70
0.05
Spray Perfume
310"
0.53
0.57
0.00
5.08
0.08
0.12
0.19
0.26
0.34
0.45
0.61
0.81
1.45
1.77
1.86
2.01
Lognormal
Distribution
GM = 0.30
GSD =3.36
0.075
Liquid
Foundation
321"
0.67
0.65
0.00
3.00
0.10
0.16
0.23
0.30
0.45
0.58
0.76
1.04
1.76
2.18
2.40
2.70
Lognormal
Distribution
Day" (grams)
Shampoo
340
12.80
9.11
0.55
67.89
4.12
5.80
7.32
9.09
10.75
12.82
14.73
17.61
23.63
29.08
36.46
51.12
Lognormal
GM = 0.40 Location = 0.38
GSD = 3. 10
0.047
Scale =5. 79
Shape = 2. 15
0.8208
Body Wash
340
14.5
8.5
1.3
63.4
5.7
7.6
9.3
10.9
12.9
14.8
17.4
20.7
25.5
29.1
35.6
43.5
Gamma
Location = 0.67
Scale = 4. 89
Shape = 2.84
0.760
Solid
Antiperspirant
340
0.79
0.78
0.00
5.55
0.17
0.29
0.38
0.46
0.59
0.70
0.86
1.08
1.70
2.32
3.33
4.42
Lognormal
Distribution
GM = 0.56
GSD = 2.41
0.293
of the total amount used to the total number of applications.
b Subjects who completed the study, but did not report their number of applications, or who did not return the unused portion of the product, were
excluded.
0 Estimate does not meet the minimum sample size criteria (N = 800) as set by
minimum sample size (N) satisfies the following rule:
N = Number of subjects (women, ages
19 to 65 years).
the National Center for Health Statistics. For upper percentile (>75), the
w[8/(l -/?)]. http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf
SD = Standard deviation.
GM = Geometric mean.
GSD = Geometric standard deviation.
Source: Loretz et al., 2006.
Q
I
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-43. Body Lotion Exposure for Consumers Only (male and
female)
Distribution
Parameter
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
P92
p94
P95
p96
p97.5
p98
p99
^99.5
p99.9
Source: Hall et al,
Amount
(g/day)
4.543
2.707
4.556
0.005
21.081
0.005
0.017
0.556
1.129
1.948
2.907
3.737
4.556
5.246
5.898
6.645
7.822
8.183
8.651
8.951
9.326
10.191
10.655
12.261
13.893
16.991
2007.
Parameter SD
0.012
0.013
0.023
0.000
1.264
0.000
0.000
0.008
0.006
0.018
0.024
0.027
0.023
0.023
0.021
0.024
0.033
0.038
0.042
0.047
0.054
0.081
0.096
0.155
0.221
0.413
Amount
(mg/kg-day)
67.869
43.866
64.265
0.043
401.371
0.079
0.250
8.066
15.055
27.535
40.763
53.072
64.265
75.114
86.751
101.024
123.227
130.177
139.085
144.797
151.892
167.036
174.414
198.018
222.667
282.959
Parameter SD
0.228
0.307
0.369
0.003
46.215
0.003
0.011
0.191
0.293
0.330
0.359
0.357
0.369
0.374
0.404
0.495
0.715
0.868
0.968
1.072
1.211
1.559
1.768
2.888
4.420
10.304
Page
17-42
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-44. Deodorant/Antiperspirant Spray Exposure for
Consumers Only (male and female) — Under Arms Only
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
p92
p94
p95
p96
P97.5
p9&
p99
p99.5
p99.9
Source: Halletal.,
Amount
(g/day)
3.478
2.051
3.153
0.045
23.663
0.228
0.373
0.598
1.135
1.951
2.425
2.796
3.153
3.548
4.049
4.804
6.095
6.477
6.955
7.262
7.645
8.537
9.005
10.451
11.628
13.843
2007.
Parameter SD
0.007
0.009
0.012
0.005
1.724
0.012
0.008
0.011
0.014
0.012
0.010
0.011
0.012
0.013
0.015
0.019
0.029
0.031
0.037
0.040
0.047
0.064
0.076
0.107
0.132
0.277
Amount
(mg/kg-day)
49.07
31.00
43.52
0.59
379.03
3.08
5.08
8.23
15.31
25.75
32.38
37.96
43.52
49.73
57.50
68.59
87.79
93.94
101.93
107.01
113.29
126.91
133.46
154.31
175.01
222.53
Parameter SD
0.13
0.22
0.19
0.10
63.23
0.13
0.12
0.16
0.20
0.17
0.17
0.17
0.19
0.22
0.27
0.32
0.49
0.58
0.71
0.81
0.91
1.24
1.40
1.98
2.80
7.29
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-45. Deodorant/Antiperspirant Spray Exposure for
Consumers Only (male and female) Using Product Over Torso and
Under Arms
Value
Mean
Standard
Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
p92
p94
p95
p96
P97.5
p9&
p99
p99.5
p99.9
Source: Hall et al.
Amount
(g/day)
3.732
2.213
3.383
0.044
24.662
0.239
0.384
0.639
1.214
2.078
2.580
2.986
3.383
3.819
4.364
5.156
6.543
6.969
7.505
7.839
8.263
9.213
9.711
11.263
12.544
14.898
2007.
Parameter SD
0.008
0.010
0.012
0.005
2.057
0.014
0.009
0.015
0.015
0.013
0.012
0.011
0.012
0.014
0.016
0.021
0.030
0.036
0.042
0.048
0.053
0.069
0.080
0.117
0.157
0.300
Amount
(mg/kg-day)
52.47
32.94
46.66
0.59
389.12
3.19
5.30
8.80
16.47
27.71
34.76
40.73
46.66
53.26
61.50
73.25
93.70
100.24
108.70
114.08
120.73
135.17
142.13
164.14
186.13
235.47
Parameter SD
0.14
0.23
0.20
0.10
66.91
0.14
0.15
0.18
0.23
0.18
0.17
0.18
0.20
0.21
0.27
0.35
0.53
0.60
0.73
0.81
0.92
1.24
1.42
2.31
3.14
7.01
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-46. Deodorant/Antiperspirant Non-Spray for Consumers
Only (male and female)
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pO\
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
p92
p94
p95
p96
P97.5
p9&
p99
p99.5
p99.9
Source: Hall et al,
Amount
(g/day)
0.898
0.494
0.820
0.000
4.528
0.064
0.123
0.221
0.363
0.509
0.617
0.718
0.820
0.934
1.068
1.238
1.509
1.598
1.722
1.806
1.912
2.134
2.233
2.515
2.771
3.426
2007.
Parameter SD
0.002
0.002
0.003
0.000
0.300
0.002
0.004
0.004
0.003
0.003
0.003
0.003
0.003
0.004
0.004
0.005
0.007
0.008
0.010
0.011
0.013
0.016
0.017
0.025
0.033
0.088
Amount
(mg/kg-day)
12.95
7.34
11.77
0.00
73.91
0.90
1.75
3.12
5.08
7.26
8.85
10.30
11.77
13.36
15.25
17.77
22.08
23.51
25.37
26.57
28.05
31.18
32.67
37.25
41.93
52.79
Parameter SD
0.04
0.05
0.05
0.00
7.48
0.04
0.05
0.06
0.05
0.05
0.05
0.05
0.05
0.05
0.07
0.08
0.12
0.14
0.17
0.19
0.21
0.28
0.32
0.48
0.72
1.63
Exposure Factors Handbook
September 2011
Page
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-47
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
P92
p94
P95
p96
p97.5
p98
p99
^99.5
^99.9
Source: Halletal.,
Lipstick Exposure for Consumers Only
Amount
(mg/day)
24.61
24.05
17.11
0.13
217.53
0.57
1.00
1.68
2.95
5.69
9.20
12.93
17.11
22.37
29.43
39.70
56.53
61.66
68.29
72.51
77.78
89.08
94.46
110.98
126.71
160.06
2007.
Parameter SD
0.17
0.25
0.18
0.04
26.01
0.04
0.07
0.07
0.07
0.11
0.14
0.15
0.18
0.24
0.33
0.47
0.66
0.72
0.86
0.95
1.08
1.34
1.52
2.06
2.93
6.33
Amount
(mg/kg-day)
0.39
0.40
0.26
0.00
3.88
0.01
0.02
0.03
0.04
0.09
0.14
0.20
0.26
0.34
0.46
0.62
0.90
0.98
1.10
1.17
1.26
1.46
1.55
1.84
2.13
2.78
(female)
Parameter SD
0.00
0.01
0.00
0.00
0.55
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.01
0.02
0.02
0.02
0.03
0.03
0.04
0.06
0.14
Page
17-46
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-48. Facial Moisturizer Exposure for Consumers Only (male
and female)
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plO
p&O
p90
P92
p94
p95
p96
P97.5
p9&
p99
p99.5
p99.9
Source: Halletal.,
Amount
(g/day)
0.906
0.533
0.851
0.001
4.751
0.055
0.079
0.138
0.261
0.472
0.603
0.721
0.851
0.990
1.131
1.289
1.536
1.617
1.727
1.801
1.897
2.129
2.251
2.653
3.040
3.714
2007.
Parameter
SD
0.003
0.004
0.004
0.000
0.380
0.002
0.004
0.001
0.004
0.004
0.003
0.003
0.004
0.004
0.004
0.005
0.007
0.008
0.010
0.012
0.014
0.022
0.027
0.043
0.057
0.108
Amount
(mg/kg-day)
13.62
8.63
12.42
0.02
92.75
0.73
1.13
1.89
3.67
6.63
8.66
10.51
12.42
14.47
16.78
19.65
24.14
25.57
27.46
28.68
30.23
33.73
35.52
41.63
48.23
63.35
Parameter SD
0.05
0.08
0.06
0.00
11.80
0.04
0.03
0.04
0.06
0.05
0.05
0.06
0.06
0.07
0.07
0.10
0.14
0.17
0.19
0.22
0.25
0.35
0.43
0.71
1.08
2.62
Exposure Factors Handbook
September 2011
Page
17-47
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-49.
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plQ
p80
p90
p92
p94
p95
p96
p97.5
p98
p99
p99.5
p99.9
Source: Halletal.,
Shampoo Exposure for Consumers Only
female)
Amount
(g/day)
6.034
3.296
5.503
0.344
29.607
1.071
1.268
1.482
2.178
3.236
3.843
4.777
5.503
6.416
7.390
8.597
10.456
11.013
11.721
12.181
12.705
13.765
14.194
15.637
16.992
20.397
2007.
Parameter SD
0.014
0.015
0.020
0.036
0.669
0.000
0.023
0.024
0.019
0.016
0.019
0.023
0.020
0.022
0.026
0.028
0.039
0.054
0.041
0.063
0.064
0.073
0.091
0.110
0.149
0.443
Amount
(mg/kg-day)
85.888
48.992
77.895
3.826
528.361
12.781
16.367
21.059
29.737
44.415
55.58
66.502
77.895
90.255
104.537
122.6
150.488
159.046
169.939
176.768
185.092
202.349
210.49
235.613
260.624
320.47
(male and
Parameter SD
0.223
0.278
0.294
0.461
65.887
0.148
0.181
0.182
0.269
0.242
0.253
0.27
0.294
0.332
0.373
0.461
0.642
0.73
0.846
0.922
1.08
1.396
1.551
2.142
3.009
6.689
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-50. Toothpaste Exposure for Consumers Only (male
and female)
Value
Mean
Standard Deviation
Median
Minimum
Maximum
Percentile
pOl
p02.5
p05
pW
p20
p30
p40
p50
p60
plQ
p80
p90
p92
p94
p95
p96
P97.5
p9&
p99
p99.5
p99.9
Source: Halletal.,
Amount
(g/day)
2.092
0.577
2.101
0.069
4.969
0.777
1.049
1.204
1.370
1.591
1.790
1.958
2.101
2.237
2.383
2.551
2.749
2.809
2.895
2.960
3.052
3.323
3.447
3.760
3.956
4.303
2007.
Parameter
SD
0.001
0.001
0.003
0.012
0.159
0.011
0.006
0.004
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.004
0.005
0.006
0.008
0.010
0.015
0.006
0.026
0.049
Amount
(mg/kg-
day)
29.85
10.34
28.67
0.93
98.77
10.14
13.34
15.47
17.96
21.29
23.94
26.32
28.67
31.15
34.00
37.62
43.29
45.03
47.23
48.61
50.27
53.70
55.28
60.12
64.77
74.84
Parameter
SD
0.04
0.05
0.06
0.18
8.19
0.14
0.08
0.06
0.06
0.05
0.05
0.06
0.06
0.06
0.07
0.08
0.12
0.14
0.16
0.17
0.20
0.25
0.26
0.39
0.52
1.10
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 1 7 — Consumer Products
Table 17-51. Average Number of Applications per Use Day"
Facial Cleanser „ .
Summary Statistics (lathering and non- „ .... Eye Shadow
J , ., • , Conditioner 3
lathenng)
N 295
Mean 1.6
SD 0.52
Minimum 1.0
Maximum 3.2
Percentiles
10th 1.0
20th 1.0
30th 1.2
40th 1.4
50th 1.7
60th 1.9
70th 2.0
80th 2.0
90th 2.2
95th 2.4
97.5th 2.9b
99thb 3 lb
297 299
1.1 1.2
0.19 0.33
1.0 1.0
2.4 2.7
1.0 1.0
1.0 1.0
1.0 1.0
1.0 1.1
1.0 1.1
1.0 1.1
1.0 1.2
1.1 1.4
1.2 1.7
1.4 2.0
1.8b 2.2b
2.1b 2.5b
a Derived as the ratio of the number of applications to the number of use
days.
b Estimate does not meet the minimum sample size criteria (n = 800) as set
by the National Center for Health Statistics. For upper percentile (>0.75),
the minimum sample size (n) satisfies the following rule: n [8/(l-p.]
Seehttp://www/cdc/gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf
jV = Number of subjects (women, ages 1 8 to 69 years).
SD = Standard deviation.
Source: Loretz et al., 2008.
Page
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Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-52. Average Amount of Product Applied per Use Day (grams)3
Facial Cleanser ... ...
„ „, , . , . ,. ,. , Facial Cleanser Facial Cleanser
Summary Statistics (lathering and ,. ,. . . , . ,. . .
. ,. . , (lathenng) (non-lathenng)
non-lathenng) \ BJ \ a;
N 295 174 121
Mean 4.06 4.07 4.05
SD 2.78 2.87 2.67
Minimum 0.33 0.33 0.83
Maximum 16.70 15.32 16.70
Percentiles
10th 1.41 1.23 1.50
20th 1.79 1.72 1.94
30th 2.18 2.15 2.22
40th 2.66 2.64 2.80
50th 3.25 3.19 3.33
60th 3.86 3.84 3.88
70th 4.62 4.71 4.59
80th 6.24 6.33 5.92
90th 8.28 8.24 8.40
95th 9.93 10.50 9.37b
97.5th 10.71b 11.47b 10.26b
99ftb 1244b 13Q7b 1529b
Best Fit Distributions Lognormal Lognormal Lognormal
and Parameters Distribution Distribution Distribution
GM=3.26 GM=3.21 GM=3.35
GSD=1.12 GSD = 2.03 GSD=1.86
/>-value
(chi-square test) 0.1251 0.4429 0.4064
Hair Conditioner
297
13.77
11.50
0.84
87.86
3.71
5.54
6.95
8.73
10.62
12.61
15.54
20.63
28.20
33.19
45.68b
60.20b
Lognormal
Distribution
GM= 10.28
GSD = 2.20
0.8595
Eye Shadow
299
0.04
0.11
0.001
0.74
0.003
0.005
0.007
0.009
0.010
0.013
0.017
0.025
0.052
0.096
0.525b
0.673b
Lognormal
Distribution
GM=0.01
GSD = 3.61
<0.0001
a Derived as the ratio of the total amount used to the number of use days.
b Estimate does not meet the minimum sample size criteria (w = 800) as set by the National Center for Health Statistics.
For upper percentile (>0. 75), the minimum sample size (w) satisfies the following rule: n [8/(l -/?)]. See
http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf
N = Number of subjects (women, ages 18 to 69 years).
SD = Standard deviation.
GM = Geometric mean.
GSD = Geometric standard deviation.
Source: Loretz et al, 2008.
Exposure Factors Handbook
September 2011
Page
17-51
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-53. Average Amount of Product Applied per Application (grams)3
Summary Statistics
N
Mean
SD
Minimum
Maximum
Facial Cleanser
(lathering and
non-lathering)
295
2.57
1.78
0.33
14.61
Facial Cleanser
(lathering)
174
2.56
1.78
0.33
10.67
Facial Cleanser ,, . „ ....
, . ,, . . Hair Conditioner
(non-lathering)
121
2.58
1.77
0.57
14.61
297
13.13
11.22
0.84
87.86
Eye Shadow
299
0.03
0.10
0.0004
0.69
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99*hb
Best Fit
Distributions and
Parameters
/>-value (chi-square
test)
a
b
N
SD
GM
GSD
Source:
0.92
1.32
1.57
1.85
2.11
2.50
2.94
3.47
4.81
5.89
7.16b
9.44b
Extreme Value
Mode =1.86
Scale = 1.12
0.0464
0.83
1.26
1.55
1.84
2.11
2.50
2.96
3.56
5.10
6.37
7.77b
9.61b
Gamma
Loc = 0.28
Scale = 1.29
0.6123
1.10
1.35
1.59
1.89
2.15
2.51
2.96
3.40
4.52
5.11b
6.29b
15.46b
Extreme Value
Mode =1.92
Scale = 1.03
0.5219
3.48
5.34
6.71
8.26
10.21
12.24
14.54
18.88
27.32
32.43
45.68b
60.20b
Lognormal
Distribution
GM = 9.78
GSD = 2.20
0.9501
0.003
0.004
0.006
0.007
0.009
0.011
0.015
0.022
0.041
0.096
0.488b
0.562b
Lognormal
Distribution
GM=0.01
GSD =3. 59
0.0001
Derived as the ratio of the total amount used to the total number of applications.
Estimate does not meet the minimum sample size criteria (n = 800) as set by the National Center for Health
Statistics. For upper percentile (>0.75), the minimum sample size (w) satisfies the following rule: n [8/(l-p)J.
http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf
= Number of subjects (women, ages 18 to 69 years).
= Standard deviation.
= Geometric
= Geometric
Loretz etal.,
mean.
standard deviation
2008.
Page
17-52
Exposure Factors Handbook
September 2011
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Exposure Factors Handbook
Chapter 17—Consumer Products
Table 17-54. Characteristics of the Study Population and the Percentage Using
Selected Baby Care Products
Characteristic
Number of Participants
Los Angeles, CA
Minneapolis, MN
Columbia, MO
Sex
Male
Female
Age (months)
2 to 8
9 to 16
17 to 24
24 to 28
Infant Weight (kg)
<10
>10
Race
White
Hispanic/Latino
Native American
Asian
Black
Product Use
Baby Lotion
Baby Shampoo
Baby Powder
Diaper Cream
Baby Wipes
Sample Number (%)
43 (26)
77(47)
43 (26)
84 (52)
79 (48)
42 (26)
82 (50)
30(18)
9(6)
84 (52)
79 (48)
131 (80)
17(10)
3(2)
8(5)
4(3)
% Using
36
54
14
33
94
Source: Sathyanarayanaet al., 2008.
Exposure Factors Handbook
September 2011
Page
17-53
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Exposure Factors Handbook
Chapter 18—Lifetime
TABLE OF CONTENTS
LIST OF TABLES 18-i
18. LIFETIME 18-1
18.1. INTRODUCTION 18-1
18.2. RECOMMENDATIONS 18-1
18.3. KEY LIFETIME STUDY 18-3
18.3.1. Xuetal. (2010) 18-3
18.4. RELEVANT LIFETIME STUDY 18-3
18.4.1. U.S. Census Bureau (2008) 18-3
18.5. REFERENCES FOR CHAPTER 18 18-3
LIST OF TABLES
Table 18-1. Recommended Values for Expectation of Life atBirth: 2007 18-1
Table 18-2. Confidence in Lifetime Expectancy Recommendations 18-2
Table 18-3. Expectation of Life atBirth, 1970 to 2007 (years) 18-4
Table 18-4. Expectation of Life by Race, Sex, andAge: 2007 18-5
Table 18-5. Projected Life Expectancy at Birth by Sex, Race, and Hispanic Origin for the United
States: 2010 to 2050 18-6
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Chapter 18—Lifetime
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18-ii September 2011
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Exposure Factors Handbook
Chapter 18—Lifetime
18. LIFETIME
18.1. INTRODUCTION
The length of an individual's life is an important
factor to consider when evaluating cancer risk
because the dose estimate is averaged over an
individual's lifetime. The recommendations for life
expectancy are provided in the next section, along
with a summary of the confidence rating for this
recommendation. Because the averaging time is
found in the denominator of the dose equation, a
shorter lifetime would result in a higher potential risk
estimate, and, conversely, a longer life expectancy
would produce a lower potential risk estimate.
The recommended values are based on one key
study identified by the U.S. Environmental Protection
Agency (EPA) for this factor. Following the
recommendations, the key study is summarized.
18.2. RECOMMENDATIONS
Current data suggest that 78 years would be an
appropriate value to reflect the average life
expectancy of the general population and is the
recommended value. If sex is a factor considered in
the assessment, note that the average life expectancy
value for females is higher than that for males. It is
recommended that the assessor use the appropriate
value of 75 years for males and 80 years for females,
based on life expectancy data from 2007 (Xu et al.,
2010). If race is a consideration in assessing exposure
for individuals, note that the life expectancy is longer
for Whites than for Blacks. Therefore, assessors are
encouraged to use values that most reflect the
exposed population. Tables 18-1 and 18-2 present the
recommendations and confidence ratings for life
expectancy, respectively.
This recommended value is different than the
70 years commonly assumed for the general
population in U.S. EPA risk assessments. The
Integrated Risk Information System does not use a
70-year lifetime assumption in the derivation of
reference concentration and reference dose, cancer
slope factors, or unit risks. Therefore, using a value
different than 70 years will not result in an
inconsistency with the toxicity data.
Table 18-1. Recommended Values for Expectation of Life at Birth: 2007
Population
Total
Males
Females
Life Expectancy
(years)
78
75
80
Source
Xuetal.,2010
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Exposure Factors Handbook
Chapter 18—Lifetime
Table 18-2. Confidence in Lifetime Expectancy Recommendations
Considerations
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
Recommendations are based on data from death certificates
filed in the 50 states in the United States and District of
Columbia.
There are no apparent biases.
Death certificate data were used to calculate life expectancy
for various population groups born between 1940 and 2007.
The data are representative of the U.S. population.
The study was published in 2010 based on data collected in
2007.
Data were collected in 2007.
The key study is widely available to the public.
Results can be reproduced by analyzing death certificate
data.
Information on ensuring data quality are available publicly.
Data were averaged by sex and race — but only for Blacks
and Whites; no other nationalities were represented within
the study.
Data were based on death certificates filed in the 50 states in
the United States and District of Columbia.
Data are published and have been peer reviewed.
Recommendations for expectation of life at birth were based
on only one study.
Rating
High
High
High
Medium
High
High
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18-2
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Exposure Factors Handbook
Chapter 18—Lifetime
18.3. KEY LIFETIME STUDY
18.3.1. Xu et al. (2010)—Deaths: Final Data for
2007
Xu et al. (2010) used information compiled from
death certificates filed in the 50 states of the United
States and District of Columbia and calculated life
expectancy for various population groups born
between 1940 and 2007. "Life expectancy at birth
represents the average number of years that a group
of infants would live if the group was to experience
throughout life the age-specific death rates present in
the year of birth" (Xu et al., 2010).
Table 18-3 shows life expectancy data by sex,
age, and race (i.e., Whites and Blacks). Although data
for other ethnic groups were collected, they were not
considered as reliable because of inconsistencies
between the race reported in the death certificates and
in the censuses and surveys. Data for 2007 show that
the life expectancy for an average person born in the
United States is 77.9 years (Xu et al., 2010). The
average life expectancy for males in 2007 was
75.4 years and 80.4 years for females. Whereas the
gap between males and females was about 7 years in
1970, it has now narrowed to about 5 years.
Table 18-3 also indicates that life expectancy for
White males and females is consistently longer than
for Black males and females. Table 18-4 presents data
for the expectation of life for persons at a specific age
in year 2007 (Xu et al., 2010). The advantages of this
study are that it is representative of the United States
and provides life expectancy data based on death
certificates and calculations of death rates. A
disadvantage is that the data were averaged by sex
and race—but only for Blacks and Whites. \
18.4. RELEVANT LIFETIME STUDY
18.4.1. U.S. Census Bureau (2008)—U.S.
Population Projections: Projected Life
Expectancy at Birth by Sex, Race, and
Hispanic Origin for the United States:
2010 to 2050
Statistical data on life expectancy are published
annually by the U.S. Department of Commerce in the
publication, Statistical Abstract of the United States.
Data are collected for the 50 states and the District of
Columbia. The Statistical Abstract of the United
States has been published by the U.S. Census Bureau
since 1878 (U.S. Census Bureau, 2010). The U.S.
Census Bureau (2008) computed life expectancy
projections for 2010 through 2050, by decade. This
analysis uses historical mortality trend data collected
by the National Center for Health Statistics and
applies forecast models to estimate projected life
expectancy at birth. These data are provided, by sex
and race in Table 18-5.
The advantage of this survey is that it is
representative of the United States, and it provides
projections by sex and race. A disadvantage is that
life expectancy estimates are based on future
projections.
18.5. REFERENCES FOR CHAPTER 18
U.S. Census Bureau. (2008) U.S. population
projections: projected life expectancy at
birth by sex, race, and Hispanic origin for
the United States: 2010 to 2050. Released
2008 (based on Census 2000). Available
online at http://www.census.gov/
population/www/projections/summary tables
.html.
U.S. Census Bureau. (2010) The 2010 statistical
abstract. Available online at
http://www.census.gov/compendia/statab/20
10/cats/population.html.
Xu, J; Kochanek, K; Murphy, S; Tejada-Vera, B.
(2010) Deaths: final data for 2007. Nat Vital
Stat Reports 58(19)1-135. Available online
at http://www.cdc.gov/nchs/data/nvsr/
nvsr58Aivsr58_19.pdf.
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Chapter 18—Lifetime
Table 18-3. Expectation of Life at Birth, 1970 to 2007 (years)3
Yearb
1970
1975
1980
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Total
70.8
72.6
73.7
74.5
74.6
74.7
74.7
74.7
74.9
74.9
75.1
75.4
75.5
75.8
75.5
75.7
75.8
76.1
76.5
76.7
76.7
76.8
76.9
76.9
77.1
77.5
77.4
111
77.9
Total
Male
67.1
68.8
70.0
70.8
71.0
71.1
71.1
71.2
71.4
71.4
71.7
71.8
72.0
72.3
72.2
72.4
72.5
73.1
73.6
73.8
73.9
74.1
74.2
74.3
74.5
74.9
74.9
75.1
75.4
White
Female
74.7
76.6
77.4
78.1
78.1
78.2
78.2
78.2
78.3
78.3
78.5
78.8
78.9
79.1
78.8
79.0
78.9
79.1
79.4
79.5
79.4
79.3
79.4
79.5
79.6
79.9
79.9
80.2
80.4
Total
71.7
73.4
74.4
75.1
75.2
75.3
75.3
75.4
75.6
75.6
75.9
76.1
76.3
76.5
76.3
76.5
76.5
76.8
77.2
77.3
77.3
77.3
77.4
77.4
77.6
77.9
77.9
78.2
78.4
Male
68.0
69.5
70.7
71.5
71.6
71.8
71.8
71.9
72.1
72.2
72.5
72.7
72.9
73.2
73.1
73.3
73.4
73.9
74.3
74.5
74.6
74.7
74.8
74.9
75.0
75.4
75.4
75.7
75.9
Female
75.6
77.3
78.1
78.7
78.7
78.7
78.7
78.8
78.9
78.9
79.2
79.4
79.6
79.8
79.5
79.6
79.6
79.7
79.9
80.0
79.9
79.9
79.9
79.9
80.0
80.4
80.4
80.6
80.8
Total
64.1
66.8
68.1
69.4
69.4
69.5
69.3
69.1
69.1
68.9
68.8
69.1
69.3
69.6
69.2
69.5
69.6
70.2
71.1
71.3
71.4
71.8
72.0
72.1
72.3
72.8
72.8
73.2
73.6
Black
Male
60.0
62.4
63.8
65.1
65.2
65.3
65.0
64.8
64.7
64.4
64.3
64.5
64.6
65.0
64.6
64.9
65.2
66.1
67.2
67.6
67.8
68.2
68.4
68.6
68.8
69.3
69.3
69.7
70.0
a Based on middle mortality assumptions; for details, source: U.S. Census Bureau (2008).
Life expectancies for 2000-2007 were calculated using a revised methodology and may
those previously published; see Xu et al. (2010).
Source: Xu et
al.,2010.
Female
68.3
71.3
72.5
73.6
73.5
73.6
73.4
73.4
73.4
73.2
73.3
73.6
73.8
73.9
73.7
73.9
73.9
74.2
74.7
74.8
74.7
75.1
75.2
75.4
75.6
76.0
76.1
76.5
76.8
differ from
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Chapter 18—Lifetime
Table 18-4. Expectation
Exact age in
years
0
1
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
a Includes
Source: Xuetal.
of Life by
All Races3
Both
sexes
77.9
77.5
73.6
68.6
63.7
58.8
54.1
49.4
44.6
39.9
35.4
30.9
26.7
22.5
18.6
15.0
11.7
8.8
6.5
4.6
3.2
2.3
Male
75.4
74.9
71.0
66.1
61.1
56.4
51.8
47.1
42.5
37.8
33.3
29.0
24.9
20.9
17.2
13.7
10.6
7.9
5.8
4.1
2.9
2.1
races other than White
,2010.
Female
80.4
79.9
76.0
71.0
66.1
61.2
56.3
51.5
46.7
41.9
37.2
32.7
28.2
23.9
19.9
16.0
12.5
9.4
6.8
4.8
3.3
2.3
and Black.
Both
sexes
78.4
77.8
73.9
68.9
64.0
59.2
54.4
49.7
44.9
40.2
35.6
31.1
26.8
22.6
18.7
15.0
11.7
8.8
6.4
4.6
3.2
2.2
Race, Sex, and Age: 2007
White
Male
75.9
75.4
71.4
66.5
61.6
56.8
52.2
47.5
42.8
38.1
33.6
29.2
25.1
21.0
17.3
13.8
10.6
7.9
5.7
4.1
2.9
2.0
Female
80.8
80.2
76.3
71.3
66.3
61.5
56.6
51.7
46.9
42.1
37.4
32.8
28.4
24.0
19.9
16.0
12.4
9.3
6.8
4.8
3.3
2.2
Both
sexes
73.6
73.6
69.7
64.7
59.8
55.1
50.4
45.8
41.2
36.7
32.3
28.1
24.2
20.6
17.2
14.1
11.2
8.7
6.7
5.1
3.8
2.8
Black
Male
70.0
70.1
66.2
61.3
56.3
51.7
47.2
42.7
38.2
33.8
29.5
25.4
21.7
18.3
15.2
12.4
9.9
7.7
6.0
4.6
3.5
2.6
Female
76.8
76.8
72.9
67.9
63.0
58.1
53.3
48.5
43.8
39.1
34.7
30.4
26.3
22.4
18.7
15.2
12.1
9.4
7.1
5.3
3.9
2.8
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Chapter 18—Lifetime
Table 18-5. Projected Life Expectancy at Birth by Sex, Race, and Hispanic Origin for
the United States: 2010 to 2050
Sex, Race, and Hispanic Origin
2010
Male and Female
Total Population
White
Black
American Indian and Alaskan
Native
Asian
Native Hawaii or Pacific Islander
Two or more races
Non-Hispanic White alone
Hispanic3
78.3
78.9
73.8
79.1
78.8
79.2
79.4
78.7
81.1
2020
Combined
79.5
80.0
76.1
80.2
80.0
80.2
80.5
79.8
81.8
2030
80.7
81.1
78.1
81.3
81.1
81.2
81.5
80.9
82.6
2040
81.9
82.2
80.0
82.3
82.2
82.4
82.4
82.0
83.3
2050
83.1
83.3
81.8
83.4
83.3
83.4
83.4
83.1
84.1
Males
Total Population
White
Black
American Indian and Alaskan
Native
Asian
Native Hawaii or Pacific Islander
Two or more races
Non-Hispanic White alone
Hispanic3
75.7
76.5
70.2
76.6
76.3
76.8
77.0
76.3
78.4
77.1
77.7
72.6
77.8
77.5
77.8
78.1
77.5
79.3
78.4
78.9
74.9
79.0
78.7
79.0
79.1
78.7
80.2
79.6
80.0
77.1
80.1
79.8
80.1
80.2
79.8
81.0
80.9
81.2
79.1
81.2
81.0
81.2
81.2
81.0
81.8
Females
Total Population
White
Black
American Indian and Alaskan
Native
Asian
Native Hawaii or Pacific Islander
Two or more races
Non-Hispanic White alone
Hispanic3
3 Hispanics may be of any race.
Source: U.S. Census Bureau, 2008.
80.8
81.3
77.2
81.5
81.1
81.6
81.7
81.1
83.7
81.9
82.4
79.2
82.5
82.2
82.6
82.7
82.1
84.4
83.1
83.4
81.0
83.6
83.2
83.5
83.6
83.2
85.0
84.2
84.5
82.7
84.5
84.2
84.5
84.6
84.2
85.6
85.3
85.5
84.3
85.5
85.3
85.5
85.5
85.2
86.3
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Exposure Factors Handbook
Chapter 19—Building Characteristics
TABLE OF CONTENTS
LIST OF TABLES
LIST OF FIGURES
19. BUILDING CHARACTERISTICS
19.1. INTRODUCTION
19.2. RECOMMENDATIONS
19.3. RESIDENTIAL BUILDING CHARACTERISTICS STUDIES
19.3.1. Key Study of Volumes of Residences
19.3.1.1. U.S. DOE (2008a)
19.3.2. Relevant Studies of Volumes of Residences
19.3.2.1. Versar(1990)
19.3.2.2. Murray (1996)
19.3.2.3. U.S. Census Bureau (2010)
19.3.3. Other Factors
19.3.3.1. Surface Area and Room Volumes
19.3.3.2. Products and Materials
19.3.3.3. Loading Ratios
19.3.3.4. Mechanical System Configurations
19.3.3.5. Type of Foundation
19.3.3.5.1. Lucas etal. (1992)
19.3.3.5.2. U.S. DOE (2008a)
19.4. NON-RESIDENTIAL BUILDING CHARACTERISTICS STUDIES
19.4.1. U.S. DOE(2008b)
19.5. TRANSPORT RATE STUDIES
19.5.1. Air Exchange Rates
19.5.1.1. Key Study of Residential Air Exchange Rates
19.5.1.1.1. Koontz and Rector (1995)
19.5.1.2. Relevant Studies of Residential Air Exchange Rates
19.5. .2.1. Nazaroff etal. (1988)
19.5. .2.2. Versar(1990)
19.5. .2.3. Murray and Burmaster( 1995)
19.5. .2.4. Diamond etal. (1996)
19.5. .2.5. Grahametal. (2004)
19.5. .2.6. Price et al. (2006)
19.5. .2.7. Yamamoto et al. (2010)
19.5.1.3. Key Study of Non-Residential Air Exchange Rates
19.5.1.3.1. Turk etal. (1987)
19.5.2. Indoor Air Models
19.5.3. Infiltration Models
19.5.4. Vapor Intrusion
19.5.5. Deposition and Filtration
19.5.5.1. Deposition
19.5.5.1.1. Thatcher and Layton( 1995)
19.5.5.1.2. Wallace (1996)
19.5.5.1.3. Thatcher et al. (2002)
19.5.5.1.4. He et al. (2005)
19.5.5.2. Filtration
19.5.6. Interzonal Airflows
19.5.7. House Dust and Soil Loadings
19.5.7.1. Roberts etal. (1991)
19.5.7.2. Thatcher and Layton( 1995)
19.6. CHARACTERIZING INDOOR SOURCES
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19-9
19-9
19-9
19-9
19-9
19-9
19-10
19-10
19-10
19-10
19-11
19-11
19-12
19-12
19-13
19-13
19-13
19-14
19-14
19-15
19-15
19-15
19-15
19-15
19-16
19-16
19-16
19-16
19-17
19-17
19-17
19-17
19-18
19-19
19-19
19-19
19-20
19-20
19-20
19-20
19-20
19-20
19-21
19-21
19-21
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Exposure Factors Handbook
Chapter 19—Building Characteristics
TABLE OF CONTENTS (continued)
19.6.1. Source Descriptions for Airborne Contaminants 19-22
19.6.2. Source Descriptions for Waterborne Contaminants 19-23
19.6.3. Soil and House Dust Sources 19-24
19.7. ADVANCED CONCEPTS 19-24
19.7.1. Uniform Mixing Assumption 19-24
19.7.2. Reversible Sinks 19-24
19.8. REFERENCES FOR CHAPTER 19 19-25
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Chapter 19—Building Characteristics
LIST OF TABLES
Table 19-1. Summary of Recommended Values for Residential Building Parameters 19-3
Table 19-2. Confidence in Residential Volume Recommendations 19-4
Table 19-3. Summary of Recommended Values for Non-Residential Building Parameters 19-5
Table 19-4. Confidence in Non-Residential Volume Recommendations 19-6
Table 19-5. Confidence in Air Exchange Rate Recommendations for Residential and Non-Residential
Buildings 19-7
Table 19-6. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership 19-31
Table 19-7. Residential Volumes in Relation to Year of Construction 19-31
Table 19-8. Summary of Residential Volume Distributions Based on U.S. DOE (2008a) 19-32
Table 19-9. Summary of Residential Volume Distributions Based on Versar (1990) 19-32
Table 19-10. Number of Residential Single Detached and Mobile Homes by Volume 19-33
Table 19-11. Dimensional Quantities for Residential Rooms 19-33
Table 19-12. Examples of Products and Materials Associated with Floor and Wall Surfaces in
Residences 19-34
Table 19-13. Residential Heating Characteristics by U.S. Census Region 19-35
Table 19-14. Residential Heating Characteristics by Urban/Rural Location 19-36
Table 19-15. Residential Air Conditioning Characteristics by U.S. Census Region 19-37
Table 19-16. Percent of Residences with Basement, by Census Region and U.S. EPARegion 19-37
Table 19-17. Percent of Residences with Basement, by Census Region 19-38
Table 19-18. States Associated with U.S. EPA Regions and Census Regions 19-39
Table 19-19. Percent of Residences with Certain Foundation Types by Census Region 19-40
Table 19-20. Average Estimated Volumes of U.S. Commercial Buildings, by Primary Activity 19-41
Table 19-21. Non-Residential Buildings: Hours Per Week Open and Number of Employees 19-42
Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings 19-43
Table 19-23. Non-Residential Air Conditioning Energy Sources for Non-Mall Buildings 19-45
Table 19-24. Summary Statistics for Residential Air Exchange Rates (in ACH), by Region 19-46
Table 19-25. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database 19-47
Table 19-26. Distributions of Residential Air Exchange Rates (in ACH) by Climate Region and Season 19-48
Table 19-27. Air Exchange Rates in Commercial Buildings by Building Type 19-48
Table 19-28. Statistics of Estimated Normalized Leakage Distribution Weighted for all Dwellings in
the United States 19-49
Table 19-29. Particle Deposition During Normal Activities 19-49
Table 19-30. Deposition Rates for Indoor Particles 19-49
Table 19-31. Measured Deposition Loss Rate Coefficients 19-50
Table 19-32. Total Dust Loading for Carpeted Areas 19-50
Table 19-33. Particle Deposition and Resuspension During Normal Activities 19-51
Table 19-34. Dust Mass Loading after 1 Week without Vacuum Cleaning 19-51
Table 19-35. Simplified Source Descriptions for Airborne Contaminants 19-52
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Exposure Factors Handbook
Chapter 19—Building Characteristics
LIST OF FIGURES
Figure 19-1. Elements of Residential Exposure 19-53
Figure 19-2. Configuration for Residential Forced-Air Systems 19-53
Figure 19-3. Idealized Patterns of Particle Deposition Indoors 19-54
Figure 19-4. Air Flows for Multiple-Zone Systems 19-55
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Exposure Factors Handbook
Chapter 19—Building Characteristics
19. BUILDING CHARACTERISTICS
19.1. INTRODUCTION
Unlike previous chapters in this handbook,
which focus on human behavior or characteristics
that affect exposure, this chapter focuses on building
characteristics. Assessment of exposure in indoor
settings requires information on the availability of the
chemical(s) of concern at the point of exposure,
characteristics of the structure and microenvironment
that affect exposure, and human presence within the
building. The purpose of this chapter is to provide
data that are available on building characteristics that
affect exposure in an indoor environment. This
chapter addresses residential and non-residential
building characteristics (volumes, surface areas,
mechanical systems, and types of foundations),
transport phenomena that affect chemical transport
within a building (airflow, chemical-specific
deposition and filtration, and soil tracking), and
information on various types of indoor
building-related sources associated with airborne
exposure and soil/house dust sources.
Source-receptor relationships in indoor exposure
scenarios can be complex due to interactions among
sources, and transport/transformation processes that
result from chemical-specific and building-specific
factors.
There are many factors that affect indoor air
exposures. Indoor air models generally require data
on several parameters. This chapter provides
recommendations on two parameters, volume and air
exchange rates. Other factors that affect indoor air
quality are furnishings, siting, weather, ventilation
and infiltration, environmental control systems,
material durability, operation and maintenance,
occupants and their activities, and building structure.
Available relevant information on some of these other
factors is provided in this chapter, but specific
recommendations are not provided, as site-specific
parameters are preferred.
Figure 19-1 illustrates the complex factors that
must be considered when conducting exposure
assessments in an indoor setting. In addition to
sources within the building, chemicals of concern
may enter the indoor environment from outdoor air,
soil, gas, water supply, tracked-in soil, and industrial
work clothes worn by the residents. Indoor
concentrations are affected by loss mechanisms, also
illustrated in Figure 19-1, involving chemical
reactions, deposition to and re-emission from
surfaces, and transport out of the building.
Particle-bound chemicals can enter indoor air through
resuspension. Indoor air concentrations of gas-phase
organic chemicals are affected by the presence of
reversible sinks formed by a wide range of indoor
materials. In addition, the activity of human receptors
greatly affects their exposure as they move from
room to room, entering and leaving the exposure
scene.
Inhalation exposure assessments in indoor
settings are modeled by considering the building as
an assemblage of one or more well-mixed zones. A
zone is defined as one room, a group of
interconnected rooms, or an entire building. At this
macroscopic level, well-mixed assumptions form the
basis for interpretation of measurement data as well
as simulation of hypothetical scenarios. Exposure
assessment models on a macroscopic level
incorporate important physical factors and processes.
These well-mixed, macroscopic models have been
used to perform indoor air quality simulations (Axley,
1989), as well as indoor air exposure assessments
(McKone, 1989; Ryan, 1991). Nazaroff and Cass
(1986) and Wilkes et al. (1992) have used computer
programs featuring finite difference or finite element
numerical techniques to model mass balance. A
simplified approach using desktop spreadsheet
programs has been used by Jennings et al. (1985).
U.S. Environmental Protection Agency (EPA) has
created two useful indoor air quality models: the
(I-BEAM) (http://www.epa.gov/iaq/largebldgs/
i-beam/index.html), which estimates indoor air
quality in commercial buildings and the
Multi-Chamber Concentration and Exposure Model
(MCCEM) (http://www.epa.gov/opptintr/exposure/
pubs/mccemhtm), which estimates average and peak
indoor air concentrations of chemicals released from
residences.
Major air transport pathways for airborne
substances in buildings include the following:
Air exchange—Air leakage through windows,
doorways, intakes and exhausts, and
"adventitious openings" (i.e., cracks and
seams) that combine to form the leakage
configuration of the building envelope plus
natural and mechanical ventilation;
Interzonal airflows—Transport through
doorways, ductwork, and service chaseways
that interconnect rooms or zones within a
building; and
Local circulation—Convective and advective
air circulation and mixing within a room or
within a zone.
The air exchange rate is generally expressed in
terms of air changes per hour (ACH), with units of
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(hour"). It is defined as the ratio of the airflow
(m3 hour"1) to the volume (m3). The distribution of
airflows across the building envelope that contributes
to air exchange and the interzonal airflows along
interior flowpaths is determined by the interior
pressure distribution. The forces causing the airflows
are temperature differences, the actions of wind, and
mechanical ventilation systems. Basic concepts on
distributions and airflows have been reviewed by the
American Society of Heating Refrigerating & Air
Conditioning Engineers (ASHRAE, 1993). Indoor-
outdoor and room-to-room temperature differences
create density differences that help determine basic
patterns of air motion. During the heating season,
warmer indoor air tends to rise to exit the building at
upper levels by stack action. Exiting air is replaced at
lower levels by an influx of colder outdoor air.
During the cooling season, this pattern is reversed:
stack forces during the cooling season are generally
not as strong as in the heating season because the
indoor-outdoor temperature differences are not as
pronounced.
The position of the neutral pressure level (i.e.,
the point where indoor-outdoor pressures are equal)
depends on the leakage configuration of the building
envelope. The stack effect arising from
indoor-outdoor temperature differences is also
influenced by the partitioning of the building interior.
When there is free communication between floors or
stories, the building behaves as a single volume
affected by a generally rising current during the
heating season and a generally falling current during
the cooling season. When vertical communication is
restricted, each level essentially becomes an
independent zone. As the wind flows past a building,
regions of positive and negative pressure (relative to
indoors) are created within the building; positive
pressures induce an influx of air, whereas negative
pressures induce an outflow. Wind effects and stack
effects combine to determine a net inflow or outflow.
The final element of indoor transport involves
the actions of mechanical ventilation systems that
circulate indoor air through the use of fans.
Mechanical ventilation systems may be connected to
heating/cooling systems that, depending on the type
of building, recirculate thermally treated indoor air or
a mixture of fresh air and recirculated air. Mechanical
systems also may be solely dedicated to exhausting
air from a designated area, as with some kitchen
range hoods and bath exhausts, or to recirculating air
in designated areas as with a room fan. Local air
circulation also is influenced by the movement of
people and the operation of local heat sources.
19.2. RECOMMENDATIONS
Table 19-1 presents the recommendations for
residential building volumes and air exchange rates.
Table 19-2 presents the confidence ratings for the
recommended residential building volumes. The
U.S. EPA 2010 analysis of the 2005 Residential
Energy Consumption Survey (RECS) data indicates a
492 m3 average living space (U.S. DOE, 2008a).
However, these values vary depending on the type of
housing (see Section 19.3.1.1). The recommended
lower end of housing volume is 154 m3. Other
percentiles are available in Section 19.3.1.1.
Residential air exchange rates vary by region of the
country. The recommended median air exchange rate
for all regions combined is 0.45 ACH. The arithmetic
mean is not preferred because it is influenced fairly
heavily by extreme values at the upper tail of the
distribution. This value was derived by Koontz and
Rector (1995) using the perflourocarbon tracer (PFT)
database. Section 19.5.1.1.1 presents distributions for
the various regions of the country. For a conservative
value, the 10th percentile for the PFT database
(0.18 ACH) is recommended (see Section 19.5.1.1.1).
Table 19-3 presents the recommended values for
non-residential building volumes and air exchange
rates. Volumes of non-residential buildings vary with
type of building (e.g., office space, malls). They
range from 1,889 m3 for food services to 287,978 m3
for enclosed malls. The mean for all buildings
combined is 5,575 m3. These data come from the
Commercial Buildings Energy Consumption Survey
(CBECS) (U.S. DOE, 2008b). The last CBECS for
which data are publicly available was conducted in
2003. Table 19-4 presents the confidence ratings for
the non-residential building volume
recommendations. The mean air exchange rate for all
non-residential buildings combined is 1.5 ACH. The
10th percentile air exchange rate for all buildings
combined is 0.60 ACH. These data come from Turk
etal. (1987).
Table 19-5 presents the confidence ratings for the
air exchange rate recommendations for both
residential and non-residential buildings. Air
exchange rate data presented in the studies are
extremely limited. Therefore, the recommended
values have been assigned a "low" overall confidence
rating, and these values should be used with caution.
Volume and air exchange rates can be used by
exposure assessors in modeling indoor-air
concentrations as one of the inputs to exposure
estimation. Other inputs to the modeling effort
include rates of indoor pollutant generation and
losses to (and, in some cases, re-emissions from)
indoor sinks. Other things being equal (i.e., holding
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constant the pollutant generation rate and effect of
indoor sinks), lower values for either the indoor
volume or the air exchange rate will result in higher
indoor-air concentrations. Thus, values near the lower
end of the distribution (e.g., 10th percentile) for either
parameter are appropriate in developing conservative
estimates of exposure.
There are some uncertainties in, or limitations
on, the distribution for volumes and air exchange
rates that are presented in this chapter. For example,
the RECS contains information on floor area rather
than total volume. The PFT database did not base its
measurements on a sample that was statistically
representative of the national housing stock. PFT has
been found to underpredict seasonal average air
exchange by 20 to 30% Sherman (1989). Using PFT
to determine air exchange can produce significant
errors when conditions during the measurements
greatly deviate from idealizations calling for
constant, well-mixed conditions. Principal concerns
focus on the effects of naturally varying air exchange
and the effects of temperature in the permeation
source. Some researchers have found that failing to
use a time-weighted average temperature can greatly
affect air exchange rate estimates (Leaderer etal.,
1985). A final difficulty in estimating air exchange
rates for any particular zone results from
interconnectedness of multi-zone models and the
effect of neighboring zones as demonstrated by
Sinden (1978) and Sandberg (1984).
Table 19-1. Summary of Recommended Values for Residential Building Parameters
Mean 10th Percentile
Volume of Residence3 492 m3 (central estimate)1" 154 m3 (lower percentile)0
Air Exchange Rate 0.45 ACH (central estimate)"1 0.18 ACH (lower percentile)6
Source
U.S. EPA 2010 analysis of U.S. DOE,
2008a
Koontz and Rector, 1995
ACH
Volumes vary with type of housing. For specific housing type volumes, see Table 19-6.
Mean value presented in Table 19-6 recommended for use as a central estimate for all single family homes, including
mobile homes and multifamily units.
10th percentile value from Table 19-8 recommended to be used as a lower percentile estimate.
Median value recommended to be used as a central estimate based across all U.S. census regions (see Table 19-24).
10th percentile value across all U.S. census regions recommended to be used as a lower percentile value (see
Table 19-24).
= Air changes per hour.
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Table 19-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Confidence in Residential Volume Recommendations
Rationale
The study was based on primary data. Volumes were
estimated assuming an 8-foot ceiling height. The effect of
this assumption has been tested by Murray (1996) and
found to be insignificant.
Selection of residences was random.
The focus of the studies was on estimating house volume
as well as other factors.
Residences in the United States were the focus of the
study. The sample size was fairly large and representative
of the entire United States. Samples were selected at
random.
The most recent RECS survey was conducted in 2005.
Data were collected in 2005.
The RECS database is publicly available.
Direct measurements were made.
Not applicable.
Distributions are presented by housing type and regions,
but some subcategory sample sizes were small.
Although residence volumes were estimated using the
assumption of 8-foot ceiling height, Murray (1996) found
this assumption to have minimal impact.
The RECS database is publicly available. Some data
analysis was conducted by U.S. EPA.
Only one study was used to derive recommendations.
Other relevant studies provide supporting evidence.
Rating
Medium
Medium
High
Medium
Medium
Medium
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Table 19-3. Summary of Recommended Values for
Meana
Volume of Building (m3)0
Vacant 4,789
Office 5,036
Laboratory 24,681
Non-refrigerated
warehouse '
Food sales 1,889
Public order and safety 5,253
Outpatient healthcare 3,537
Refrigerated warehouse 19,716
Religious worship 3,443
Public assembly 4,839
Education 8,694
Foodservice 1,889
Inpatient healthcare 82,034
Nursing 15,522
Lodging 11,559
Strip shopping mall 7,891
Enclosed mall 287,978
Retail other than mall 3,310
Service 2,213
Other 5,236
All Buildings'1 5,575
.. _ , _,e Mean (SD) 1.5 (0.87) ACH
Air Exchange Rate ^^ Q 3^ { ACH
Non-Residential Building Parameters
10thPercentileb Source
408
510
2,039
1,019
476
816
680
1,133
612
595 U.S. EPA analysis of
527 U.S. DOE, 2008b
442
17,330
1,546
527
1,359
35,679
510
459
425
527
0.60 ACH Turk etal., 1987
a Mean values are recommended as central estimates for non-residential buildings (see Table 1 9-20).
b lO^percentile values are recommended as lower estimates for non-residential buildings (see
Table 19-20).
0 Volumes were calculated assuming a ceiling height of 20 feet for warehouses and enclosed malls and
12 feet for other structures (see Table 1 9-20).
d Weighted average assuming a ceiling height of 20 feet for warehouses and enclosed malls and 12 feet
for other structures (see Table 1 9-20).
e Air exchange rates for commercial buildings (see Table 1 9-27).
SD = Standard deviation.
ACH = Air changes per hour.
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Table 19-4.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency, Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Confidence in Non-Residential Volume Recommendations
Rationale
All non-residential data were based on one study: CBECS
(U.S. DOE, 2008b). Volumes were estimated assuming a
20-foot ceiling height assumption for warehouses and a
12-foot height assumption for all other non-residential
buildings based on scant anecdotal information. Although
Murray (1996) found that the impact of an 8-foot ceiling
assumption was insignificant for residential structures, the
impact of these ceiling height assumptions for non-
residential buildings is unknown.
Selection of residences was random for CBECS.
CBECS (U.S. DOE, 2008b) contained ample building size
data, which were used as the basis provided for volume
estimates.
CBECS (U.S. DOE, 2008b) was a nationwide study that
generated weighted nationwide data based upon a large
random sample.
The data were collected in 2003.
The data are available online in both summary tables and
raw data.
http://www.eia.doe.gov/emeu/cbecs/contents.html
Direct measurements were made.
Not applicable.
Distributions are presented by building type, heating and
cooling system type, and employment, but a few
subcategory sample sizes were small.
Volumes were calculated using speculative assumptions
for building height. The impact of such assumptions may
or may not be significant.
There are no studies from the peer-reviewed literature.
All data are based upon one study: CBECS (U.S. DOE,
2008b).
Rating
Medium
High
High
Medium
Low
Medium
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Table 19-5. Confidence in
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Air Exchange Rate Recommendations for Residential and Non-Residential
Buildings
Rationale
The studies were based on primary data; however, most
approaches contained major limitations, such as assuming
uniform mixing, and residences were typically not selected
at random.
Bias may result because the selection of residences and
buildings was not random. The commercial building study
(Turk et al., 1987) was conducted only on buildings in the
northwest United States.
The focus of the studies was on estimating air exchange
rates as well as other factors.
Study residences were typically in the United States, but
only RECS (U.S. DOE, 2008a) selected residences
randomly. PFT residences were not representative of the
United States. Distributions are presented by housing type
and regions; although some of the sample sizes for the
subcategories were small. The commercial building study
(Turk et al., 1987) was conducted only on buildings in the
northwest United States.
Measurements in the PFT database were taken between
1982-1987. The Turk et al. (1987) study was conducted in
the mid-1 980s.
Only short-term data were collected; some residences were
measured during different seasons; however, long-term air
exchange rates are not well characterized. Individual
commercial buildings were measured during one season.
Papers are widely available from government reports and
peer-reviewed journals.
Precision across repeat analyses has been documented to
be acceptable.
Not applicable.
For the residential estimates, distributions are presented by
U.S. regions, seasons, and climatic regions, but some of
the sample sizes for the subcategories were small. The
commercial estimate comes from buildings in the
northwest U.S. representing two climate zones, and
measurements were taken in three seasons (spring,
summer, and winter).
Some measurement error may exist. Additionally, PFT has
been found to underpredict seasonal average air exchange
by 20-30% (Sherman, 1989). Turk et al. (1987) estimates
a 10-20% measurement error for the technique used to
measure ventilation in commercial buildings.
Rating
Low
Low
Medium
Medium
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Table 19-5. Confidence in Air Exchange Rate Recommendations for Residential and Non-Residential
Buildings (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The studies appear in peer-reviewed literature.
Three residential studies are based on the same PFT
database. The database contains results of 20 projects of
varying scope. The commercial building rate is based on
one study.
Rating
Low
Low
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19.3. RESIDENTIAL BUILDING
CHARACTERISTICS STUDIES
19.3.1. Key Study of Volumes of Residences
19.3.1.1. U.S. DOE (2008a)—Residential Energy
Consumption Survey (RECS)
Measurement surveys have not been conducted
to directly characterize the range and distribution of
volumes for a random sample of U.S. residences.
Related data, however, are regularly collected
through the U.S. Department of Energy's (DOE)
RECS. In addition to collecting information on
energy use, this triennial survey collects data on
housing characteristics including direct
measurements of total and heated floor space for
buildings visited by survey specialists. For the most
recent survey done in 2005, a multistage probability
sample of 4,381 residences was surveyed,
representing 111 million housing units nationwide.
The 2005 survey response rate was 77.1%. Volumes
were estimated from the RECS measurements by
multiplying the heated floor space area by an
assumed ceiling height of 8 feet. The data and data
tables were released to the public in 2008.
In 2010, the U.S. EPA conducted an analysis of
the RECS 2005 survey data. Tables 19-6 and 19-7
present results for residential volume distributions by
type of residence, ownership, and year of
construction from the 2005 RECS. Table 19-6
provides information on average estimated residential
volumes according to housing type and ownership.
The predominant housing type—single-family
detached homes—also had the largest average
volume. Multifamily units and mobile homes had
volumes averaging about half that of single-family
detached homes, with single-family attached homes
about halfway between these extremes. Within each
category of housing type, owner-occupied residences
averaged about 50% greater volume than rental units.
Data on the relationship of residential volume to year
of construction are provided in Table 19-7 and
indicate a slight decrease in residential volumes
between 1950 and 1979, followed by an increasing
trend. A ceiling height of 8 feet was assumed in
estimating the average volumes, whereas there may
have been some time-related trends in ceiling height.
Table 19-8 presents distributions of residential
volumes for all house types and all units. The average
house volume for all types of units for all years was
estimated to be 492 m3.
It is important to note that in 2005, the RECS
changed the way it calculated total square footage.
The total average square footage per housing unit for
the 2001 RECS was reported as 1,975 ft2. This figure
excluded unheated garages, and for most housing
units, living space in attics. The average total square
footage for housing units in the 2005 RECS was
2,171 ft2 (i.e., 492 m3 converted to ft3 and assuming
an 8-foot ceiling; see Table 19-7), which includes
attic living space for all housing units. The only
available figures that permit comparison of total
square footage for both survey years would exclude
all garage floorspace and attic floorspace in all
housing units—for 2001, the average total square
footage was 2,005, and for 2005, the average total
was 2,029 ft2.
The advantages of this study were that the
sample size was large, and it was representative of
houses in the United States. Also, it included various
housing types. A limitation of this analysis is that
volumes were estimated assuming a ceiling height of
8 feet. Volumes of individual rooms in the house
cannot be estimated.
19.3.2. Relevant Studies of Volumes of
Residences
19.3.2.1. Versar (1990)—Database on
Perfluorocarbon Tracer (PET)
Ventilation Measurements
Versar (1990) compiled a database of
time-averaged air exchange and interzonal airflow
measurements in more than 4,000 residences. These
data were collected between 1982 and 1987. The
residences that appear in this database are not a
random sample of U.S. homes. However, they
represent a compilation of homes visited in about
100 different field studies, some of which involved
random sampling. In each study, the house volumes
were directly measured or estimated. The collective
homes visited in these field projects are not
geographically balanced. A large fraction of these
homes are located in southern California. Statistical
weighting techniques were applied in developing
estimates of nationwide distributions to compensate
for the geographic imbalance. The Versar (1990) PFT
database found a mean value of 369 m3 (see
Table 19-9).
The advantage of this study is that it provides a
distribution of house volumes. However, more
up-to-date data are available from RECS 2005 (U.S.
DOE, 2008a).
19.3.2.2. Murray (1996)—Analysis of RECS and
PFT Databases
Using a database from the 1993 RECS and an
assumed ceiling height of 8 feet, Murray (1996)
estimated a mean residential volume of 382 m3 using
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RECS estimates of heated floor space. This estimate
is slightly different from the mean of 369 m3 given in
Table 19-9. Murray's (1996) sensitivity analysis
indicated that when a fixed ceiling height of 8 feet
was replaced with a randomly varying height with a
mean of 8 feet, there was little effect on the standard
deviation of the estimated distribution. From a
separate analysis of the PFT database, based on
1,751 individual household measurements, Murray
(1996) estimated an average volume of 369 m3, the
same as previously given in Table 19-9. In
performing this analysis, the author carefully
reviewed the PFT database in an effort to use each
residence only once, for those residences thought to
have multiple PFT measurements.
Murray (1996) analyzed the distribution of
selected residential zones (i.e., a series of connected
rooms) using the PFT database. The author analyzed
the "kitchen zone" and the "bedroom zone" for
houses in the Los Angeles area that were labeled in
this manner by field researchers, and "basement,"
"first floor," and "second floor" zones for houses
outside of Los Angeles for which the researchers
labeled individual floors as zones. The kitchen zone
contained the kitchen in addition to any of the
following associated spaces: utility room, dining
room, living room, and family room. The bedroom
zone contained all the bedrooms plus any bathrooms
and hallways associated with the bedrooms. The
following summary statistics (mean ± standard
deviation) were reported by Murray (1996) for the
volumes of the zones described above: 199 ± 115 m3
for the kitchen zone, 128 ± 67 m3 for the bedroom
zone, 205 ± 64 m3 for the basement, 233 ± 72 m3 for
the first floor, and 233 ± 111 m3 for the second floor.
The advantage of this study is that the data are
representative of homes in the United States.
However, more up-to-date data are available from the
RECS 2005 (U.S. DOE, 2008a).
19.3.2.3. U.S. Census Bureau (2010)—American
Housing Survey for the United States:
2009
The American Housing Survey (AHS) is
conducted by the Census Bureau for the Department
of Housing and Urban Development. It collects data
on the Nation's housing, including apartments,
single-family homes, mobile homes, vacant housing
units, household characteristics, housing quality,
foundation type, drinking water source, equipment
and fuels, and housing unit size. National data are
collected in odd-numbered years, and data for each of
47 selected Metropolitan Areas are collected about
every 6 years. The national sample includes about
55,000 housing units. Each metropolitan area
samples 4,100 or more housing units. The AHS
returns to the same housing units year after year to
gather data. The U.S. Census Bureau (2010) lists the
number of residential single detached and
manufactured/mobile homes in the United States
within various categories including seasonal, year-
round occupied, and new in the last 4 years, based on
the AHS (see Table 19-10). Assuming an 8-foot
ceiling, these units have a median size of 385 m3;
however, these values do not include multifamily
units. It should be mentioned that 8 feet is the most
common ceiling height, and Murray (1996) has
shown that the effect of the 8-foot ceiling height
assumption is not significant.
The advantage of this study is that it was a large
national sample and, therefore, representative of the
United States. The limitations of these data are that
distributions were not provided by the authors, and
the analysis did not include multifamily units.
19.3.3. Other Factors
19.3.3.1. Surf ace Area and Room Volumes
The surface areas of floors are commonly
considered in relation to the room or house volume,
and their relative loadings are expressed as a surface
area-to-volume, or loading ratio. Table 19-11
provides the basis for calculating loading ratios for
typical-sized rooms. Constant features in the
examples are a room width of 12 feet and a ceiling
height of 8 feet (typical for residential buildings), or a
ceiling height of 12 feet (typical for some types of
commercial buildings).
Volumes of individual rooms are dependent on
the building size and configuration, but summary
data are not readily available. The exposure assessor
is advised to define specific rooms, or assemblies of
rooms, that best fit the scenario of interest. Most
models for predicting indoor air concentrations
specify airflows in m3 per hour and, correspondingly,
express volumes in m3. A measurement in ft3 can be
converted to m3 by multiplying the value in ft3 by
0.0283 m3/ft3. For example, a bedroom that is 9 feet
wide by 12 feet long by 8 feet high has a volume of
864 ft3 or 24.5 m3. Similarly, a living room with
dimensions of 12 feet wide by 20 feet long by 8 feet
high has a volume of 1,920ft3 or 54.3 m3, and a
bathroom with dimensions of 5 feet by 12 feet by
8 feet has a volume of 480 ft3 or 13.6 m3.
19.3.3.2. Products and Materials
Table 19-12 presents examples of assumed
amounts of selected products and materials used in
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constructing or finishing residential surfaces (Tucker,
1991). Products used for floor surfaces include
adhesive, varnish, and wood stain; and materials used
for walls include paneling, painted gypsum board,
and wallpaper. Particleboard and chipboard are
commonly used for interior furnishings such as
shelves or cabinets but could also be used for decking
or underlayment. It should be noted that numbers
presented in the table for surface area are based on
typical values for residences, and they are presented
as examples. In contrast to the concept of loading
ratios presented above (as a surface area), the
numbers in the table also are not scaled to any
particular residential volume. In some cases, it may
be preferable for the exposure assessor to use
professional judgment in combination with the
loading ratios given above. For example, if the
exposure scenario involves residential carpeting,
either as an indoor source or as an indoor sink, then
the American Society for Testing and Materials
(ASTM) loading ratio of 0.43 m2nf3 for floor
materials could be multiplied by an assumed
residential volume and assumed fractional coverage
of carpeting to derive an estimate of the surface area.
More specifically, a residence with a volume of
300 m3, a loading ratio of 0.43 m2nT3, and coverage
of 80%, would have 103 m2 of carpeting. The
estimates discussed here relate to macroscopic
surfaces; the true surface area for carpeting, for
example, would be considerably larger because of the
nature of its fibrous material.
19.3.3.3. Loading Ratios
The loading ratios for the 8-foot ceiling height
range from 0.98 mm to 2.18 m m for wall areas
and from 0.36 m2nT3 to 0.44 m2nT3 for floor area. In
comparison, ASTM Standard E 1333 (ASTM, 1990),
for large-chamber testing of formaldehyde levels
from wood products, specifies the following loading
ratios: (1) 0.95 m2nT3 for testing plywood (assumes
plywood or paneling on all four walls of a typical
size room); and (2) 0.43 m2nT3 for testing
particleboard (assumes that particleboard decking or
underlayment would be used as a substrate for the
entire floor of a structure).
19.3.3.4. Mechanical System Configurations
Mechanical systems for air movement in
residences can affect the migration and mixing of
pollutants released indoors and the rate of pollutant
removal. Three types of mechanical systems are
(1) systems associated with heating, ventilating, and
air conditioning (HVAC); (2) systems whose primary
function is providing localized exhaust; and
(3) systems intended to increase the overall air
exchange rate of the residence.
Portable space heaters intended to serve a single
room, or a series of adjacent rooms, may or may not
be equipped with blowers that promote air movement
and mixing. Without a blower, these heaters still have
the ability to induce mixing through convective heat
transfer. If the heater is a source of combustion
pollutants, as with unvented gas or kerosene space
heaters, then the combination of convective heat
transfer and thermal buoyancy of combustion
products will result in fairly rapid dispersal of such
pollutants. The pollutants will disperse throughout
the floor where the heater is located and to floors
above the heater, but will not disperse to floors
below.
Central forced-air HVAC systems are common in
many residences. Such systems, through a network of
supply/return ducts and registers, can achieve fairly
complete mixing within 20 to 30 minutes (Koontz
etal., 1988). The air handler for such systems is
commonly equipped with a filter (see Figure 19-2)
that can remove particle-phase contaminants. Further
removal of particles, via deposition on various room
surfaces (see Section 19.5.5), is accomplished
through increased air movement when the air handler
is operating.
Figure 19-2 also distinguishes forced-air HVAC
systems by the return layout in relation to supply
registers. The return layout shown in the upper
portion of the figure is the type most commonly
found in residential settings. On any floor of the
residence, it is typical to find one or more supply
registers to individual rooms, with one or
two centralized return registers. With this layout,
supply/return imbalances can often occur in
individual rooms, particularly if the interior doors to
rooms are closed. In comparison, the supply/return
layout shown in the lower portion of the figure by
design tends to achieve a balance in individual rooms
or zones. Airflow imbalances can also be caused by
inadvertent duct leakage to unconditioned spaces
such as attics, basements, and crawl spaces. Such
imbalances usually depressurize the house, thereby
increasing the likelihood of contaminant entry via
soil-gas transport or through spillage of combustion
products from vented fossil-fuel appliances such as
fireplaces and gas/oil furnaces.
Mechanical devices such as kitchen fans,
bathroom fans, and clothes dryers are intended
primarily to provide localized removal of unwanted
heat, moisture, or odors. Operation of these devices
tends to increase the air exchange rate between the
indoors and outdoors. Because local exhaust devices
are designed to be near certain indoor sources, their
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effective removal rate for locally generated pollutants
is greater than would be expected from the dilution
effect of increased air exchange. Operation of these
devices also tends to depressurize the house, because
replacement air usually is not provided to balance the
exhausted air.
An alternative approach to pollutant removal is
one which relies on an increase in air exchange to
dilute pollutants generated indoors. This approach
can be accomplished using heat recovery ventilators
(HRVs) or energy recovery ventilators (ERVs). Both
types of ventilators are designed to provide balanced
supply and exhaust airflows and are intended to
recover most of the energy that normally is lost when
additional outdoor air is introduced. Although
ventilators can provide for more rapid dilution of
internally generated pollutants, they also increase the
rate at which outdoor pollutants are brought into the
house. A distinguishing feature of the two types is
that ERVs provide for recovery of latent heat
(moisture) in addition to sensible heat. Moreover,
ERVs typically recover latent heat using a
moisture-transfer device such as a desiccant wheel. It
has been observed in some studies that the transfer of
moisture between outbound and inbound air streams
can result in some re-entrainment of indoor pollutants
that otherwise would have been exhausted from the
house (Andersson et al., 1993). Inadvertent air
communication between the supply and exhaust air
streams can have a similar effect.
Studies quantifying the effect of mechanical
devices on air exchange using tracer-gas
measurements are uncommon and typically provide
only anecdotal data. The common approach is for the
expected increment in the air exchange rate to be
estimated from the rated airflow capacity of the
device(s). For example, if a device with a rated
capacity of 100 ft3 per minute, or 170 m3 per hour, is
operated continuously in a house with a volume of
400 m3, then the expected increment in the air
exchange rate of the house would be
170 m3 hour"17400 m3, or approximately 0.4 ACH.
U.S. DOE RECS contains data on residential
heating characteristics. The data show that most
homes in the United States have some kind of heating
and air conditioning system (U.S. DOE, 2008a). The
types of system vary regionally within the United
States. Table 19-13 shows the type of primary and
secondary heating systems found in U.S. residences.
The predominant primary heating system in the
Midwest is natural gas (used by 72% of homes there)
while most homes in the South (54%) primarily heat
with electricity. Nationwide, 31% of residences have
a secondary heating source, typically an electric
source.
Table 19-14 shows the type of heating systems
found in the United States by urban/rural location. It
is noteworthy that 56% of suburban residences use
central heating compared to 16% in rural areas.
Another difference is that only 25% of residences in
cities used a secondary heating system, which used
typically electric, compared to 48% in rural areas,
typically electric or wood.
Table 19-15 shows that 84% of U.S. residences
have some type of cooling system: 59% have central
air while 26% use window units. Like heating
systems, cooling system type varies regionally as
well. In the South, 97% of residences have either
central or room air conditioning units whereas only
57% of residences in the Western United States have
air conditioning. Frequency of use varies regionally
as well. About 61% of residences in the South use
their air conditioner all summer long, but only 15%
do so in the Northeast.
19.3.3.5. Type of Foundation
The type of foundation of a residence is of
interest in residential exposure assessment. It
provides some indication of the number of stories and
house configuration, as well as an indication of the
relative potential for soil-gas transport. For example,
such transport can occur readily in homes with
enclosed crawl spaces. Homes with basements
provide some resistance, but still have numerous
pathways for soil-gas entry. By comparison, homes
with crawl spaces open to the outside have significant
opportunities for dilution of soil gases prior to
transport into the house. Using data from the 2009
AHS, of total housing units in the United States, 33%
have a basement under the entire building, 10% have
a basement under part of the building, 23% have a
crawl space, and 32% are on a concrete slab (U.S.
Census Bureau, 2010).
19.3.3.5.1. Lucas et al. (1992)—National
Residential Radon Survey
The estimated percentage of homes with a full or
partial basement according to the National
Residential Radon Survey of 5,700 households
nationwide was 45% (see Table 19-16) (Lucas et al.,
1992). The National Residential Radon Survey
provides data for more refined geographical areas,
with a breakdown by the 10 U.S. EPA Regions. The
New England region (i.e., U.S. EPARegion 1), which
includes Connecticut, Maine, Massachusetts, New
Hampshire, Rhode Island, and Vermont, had the
highest prevalence of basements (93%). The lowest
prevalence (4%) was for the South Central region
(i.e., U.S. EPA Region 6), which includes Arkansas,
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Louisiana, New Mexico, Oklahoma, and Texas.
Section 19.3.3.5.2 presents the States associated with
each census region and U.S. EPA region.
19.3.3.5.2. U.S. DOE (2008a)—Residential
Energy Consumption Survey
(RECS)
The most recent RECS (described in
Section 19.3.1.1) was administered in 2005 to over
4,381 households (U.S. DOE, 2008a). The type of
information requested by the survey questionnaire
included the type of foundation for the residence (i.e.,
basement, enclosed crawl space, crawl space open to
outside, or concrete slab). This information was not
obtained for multifamily structures with five or more
dwelling units or for mobile homes. U.S. EPA
analyzed the RECS 2005 data (U.S. DOE, 2008a) to
estimate the percentage of residences with basements
and different foundation types by census region and
by U.S. EPA region. Table 19-17 presents these
estimates. Table 19-18 shows the states associated
with each U.S. EPA region and census region.
Table 19-19 presents estimates of the percentage of
residences with each foundation type, by census
region, and for the entire United States. The
percentages can add up to more than 100% because
some residences have more than one type of
foundation; for example, many split-level structures
have a partial basement combined with some
crawlspace that typically is enclosed. The data in
Table 19-19 indicate that 40.6% of residences
nationwide have a basement. It also shows that a
large fraction of homes have concrete slabs (46%).
There are also variations by census region. For
example, around 73% and 68% of the residences in
the Northeast and Midwest regions, respectively,
have basements. In the South and West regions, the
predominant foundation type is concrete slab.
The advantage of this study is that it had a large
sample size, and it was representative of houses in
the United States. Also, it included various housing
types. A limitation of this analysis is that homes have
multiple foundation types, and the analysis does not
provide estimates of square footage for each type of
foundation.
19.4. NON-RESIDENTIAL BUILDING
CHARACTERISTICS STUDIES
19.4.1. U.S. DOE (2008b)—Non-Residential
Building Characteristics—Commercial
Buildings Energy Consumption Survey
(CBECS)
The U.S. Department of Energy conducts the
CBECS to collect data on the characteristics and
energy use of commercial buildings. The survey is
conducted every 4 years. The latest survey for which
data are available (released in 2008) is the 2003
CBECS. CBECS defines "Commercial" buildings as
all buildings in which at least half of the floorspace is
used for a purpose that is not residential, industrial, or
agricultural, so they include building types that might
not traditionally be considered commercial, such as
schools, correctional institutions, and buildings used
for religious worship.
CBECS is a national survey of U.S. buildings
that DOE first conducted in 1979. The 2003 CBECS
provided nationwide estimates for the United States
based upon a weighted statistical sample of
5,215 buildings. DOE releases a data set about the
sample buildings for public use. The 2003 CBECS
Public Use Microdata set includes data for
4,820 non-mall commercial buildings (U.S. DOE,
2008b). A second data set available that includes
information on malls, lacks building characteristics
data. Building characteristics data provided by
CBECS includes floor area, number of floors, census
division, heating and cooling design, principal
building activity, number of employees, and
weighting factors. The 2003 CBECS data survey
provides the best statistical characterization of the
commercial sector available for the United States. A
2007 CBECS was conducted, but the data were not
publicly available at the time this handbook was
published.
In 2010, U.S. EPA conducted an analysis of the
U.S. DOE CBECS 2003 data, released in 2008.
Table 19-20 shows that non-residential buildings vary
greatly in volumes. The table shows average volume
for a numbers of structures including offices
(5,036m3), restaurants (food services) (1,889 m3),
schools (education) (8,694 m3), hotels (lodging)
(11,559 m3), and enclosed shopping malls (287,978
m3). Each of these structures varies considerably in
size as well. The large shopping malls are over
500,000 m3 (90th percentile). The most numerous of
the non-residential buildings are office buildings
(18%), non-food service buildings (13%), and
warehouses (13%).
Table 19-21 presents data on the number of
hours various types of non-residential buildings are
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open for business and the number of employees that
work in such buildings. In general, places of worship
have the most limited hours. The average place of
worship is open 32 hours per week. On the other
extreme are healthcare facilities, which are open
168 hours a week (24 hours per day, 7 days per
week). The average restaurant is open 86 hours per
week. Hours vary considerably by building type.
Some offices, labs, warehouses, restaurants, police
stations, and hotels are also open 24 hours per day,
7 days per week, as reflected by the 90th percentiles.
Table 19-21 also presents the number of employees
typically employed in such buildings during the main
shift. Overall, the average building houses
16 workers during its primary shift, but some
facilities employ many more. The average hospital
employs 471 workers during its main shift, although
those in the 10th percentile employ only 175, and
those in the 90th employ 2,250.
CBECS data on heating and cooling sources
were tabulated by the U.S. Energy Information
Administration of the U.S. DOE and released to the
public (along with the data) in 2008 (U.S. DOE,
2008b). Tables 19-22 and 19-23 present these data.
Table 19-22 indicates that electricity and natural gas
are the heating sources used by a majority of
non-residential buildings. Of those buildings heated
by fuel oil, most are older buildings.
Table 19-23 describes non-residential building
cooling characteristics. About 78% (i.e., 3,625/4,645)
of non-residential buildings have air conditioning, but
this varies regionally from 14% in the Northeast to
41% in the South. Nationwide, 77% (i.e.,
3,589/4,645) of non-residential buildings use
electricity for air conditioning. The remaining
fraction use natural gas or chilled water.
It should be noted, however, that there are many
critical exposure assessment elements not addressed
by CBECS. These include a number of elements
discussed in more detail in the Residential Building
Characteristics Studies section (i.e., Section 19.3).
Data to characterize the room volume, products and
materials, loading ratios, and foundation type for
non-residential buildings were not available in
CBECS.
Another characteristic of non-residential
buildings needed in ventilation and air exchange
calculations is ceiling height. In the residential
section of this chapter, ceiling height was assumed to
be 8 feet, a figure often assumed for residential
buildings. For non-residential buildings, U.S. EPA
has assumed a 20 foot ceiling height for warehouses
and enclosed shopping malls and a 12-foot average
ceiling height for other structures. These assumptions
are based on professional judgment. Murray (1996)
found that the impact of assuming an 8-foot ceiling
height for residences was insignificant, but
non-residential ceiling height varies more greatly and
may or may not have a significant impact on
calculations.
19.5. TRANSPORT RATE STUDIES
19.5.1. Air Exchange Rates
Air exchange is the balanced flow into and out of
a building and is composed of three processes:
(1) infiltration—air leakage through random cracks,
interstices, and other unintentional openings in the
building envelope; (2) natural ventilation—airflows
through open windows, doors, and other designed
openings in the building envelope; and (3) forced or
mechanical ventilation—controlled air movement
driven by fans. For nearly all indoor exposure
scenarios, air exchange is treated as the principal
means of diluting indoor concentrations. The air
exchange rate is generally expressed in terms of ACH
(with units of hours"1). It is defined as the ratio of
the airflow (m3 hours"1) to the volume (m3). Thus,
ACH and building size and volume are negatively
correlated.
No measurement surveys have been conducted to
directly evaluate the range and distribution of
building air exchange rates. Although a significant
number of air exchange measurements have been
carried out over the years, there has been a diversity
of protocols and study objectives. Since the early
1980s, however, an inexpensive PFT technique has
been used to measure time-averaged air exchange and
interzonal airflows in thousands of occupied
residences using essentially similar protocols (Dietz
et al., 1986). The PFT technique utilizes miniature
permeation tubes as tracer emitters and passive
samplers to collect the tracers. The passive samplers
are returned to the laboratory for analysis by gas
chromatography. These measurement results have
been compiled to allow various researchers to access
the data (Versar, 1990).
With regard to residential air exchange, an
attached garage can negatively impact indoor air
quality. In addition to automobile exhaust, people
often store gasoline, oil, paints, lacquers, and yard
and garden supplies in garages. Appliances such as
furnaces, heaters, hot water heaters, dryers,
gasoline-powered appliances, and wood stoves may
also impact indoor air quality. Garages can be a
source of volatile organic compounds (VOCs) such
as benzene, toluene, ethylbenzene, /w,/>-xylene, and
o-xylene. Emmerich et al. (2003) conducted a
literature review on indoor air quality and the
transport of pollutants from attached garages to
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residential living spaces. The authors found the body
of literature on the subject was limited and contained
little data with regard to airtightness and geometry of
the house-garage interface, and the impact of heating
and cooling equipment. They concluded, however,
that there is substantial evidence that the transport of
contaminants from garages has the potential to
negatively impact residences.
19.5.1.1. Key Study of Residential Air Exchange
Rates
19.5.1.1.1. Koontz and Rector (1995)—
Estimation of Distributions for
Residential Air Exchange Rates
In analyzing the composite data from various
projects (2,971 measurements), Koontz and Rector
(1995) assigned weights to the results from each state
to compensate for the geographic imbalance in
locations where PFT measurements were taken. The
results were weighted in such a way that the resultant
number of cases would represent each state in
proportion to its share of occupied housing units, as
determined from the 1990 U.S. Census of Population
and Housing.
Table 19-24 shows summary statistics from the
Koontz and Rector (1995) analysis, for the country as
a whole and by census regions. Based on the statistics
for all regions combined, the authors suggested that a
10th percentile value of 0.18 ACH would be
appropriate as a conservative estimator for air
exchange in residential settings, and that the
50th percentile value of 0.45 ACH would be
appropriate as a typical air exchange rate. In applying
conservative or typical values of air exchange rates, it
is important to realize the limitations of the
underlying database. Although the estimates are
based on thousands of measurements, the residences
represented in the database are not a random sample
of the U.S. housing stock. Also, the sample
population is not balanced in terms of geography or
time of year, although statistical techniques were
applied to compensate for some of these imbalances.
In addition, PFT measurements of air exchange rates
assume uniform mixing of the tracer within the
building. This is not always so easily achieved.
Furthermore, the degree of mixing can vary from day
to day and house to house because of the nature of
the factors controlling mixing (e.g., convective air
monitoring driven by weather, and type and operation
of the heating system). The relative placement of the
PFT source and the sampler can also cause variability
and uncertainty. It should be noted that sampling is
typically done in a single location in a house that may
not represent the average from that house. In
addition, very high and very low values of air
exchange rates based on PFT measurements have
greater uncertainties than those in the middle of the
distribution. Despite such limitations, the estimates in
Table 19-24 are believed to represent the best
available information on the distribution of air
exchange rates across U.S. residences throughout the
year.
19.5.1.2. Relevant Studies of Residential Air
Exchange Rates
19.5.1.2.1. Nazaroff et al. (1988)—Radon Entry
via Potable Water
Nazaroff et al. (1988) aggregated the data from
two studies conducted earlier using tracer-gas decay.
At the time these studies were conducted, they were
the largest U.S. studies to include air exchange
measurements. The first (Grot and Clark, 1981) was
conducted in 255 dwellings occupied by low-income
families in 14 different cities. The geometric
mean ± standard deviation for the air exchange
measurements in these homes, with a median house
age of 45 years, was 0.90 ± 2.13 ACH. The second
study (Grimsrud et al., 1983) involved 312 newer
residences, with a median age of less than 10 years.
Based on measurements taken during the heating
season, the geometric mean ± standard deviation for
these homes was 0.53 ± 1.71 ACH. Based on an
aggregation of the two distributions with proportional
weighting by the respective number of houses
studied, Nazaroff et al. (1988) developed an overall
distribution with a geometric mean of 0.68 ACH and
a geometric standard deviation of 2.01.
19.5.1.2.2. Versar (1990)—Database of PFT
Ventilation Measurements
The residences included in the PFT database do
not constitute a random sample across the United
States. They represent a compilation of homes visited
in the course of about 100 separate field-research
projects by various organizations, some of which
involved random sampling, and some of which
involved judgmental or fortuitous sampling.
Table 19-25 summarizes the larger projects in the
PFT database, in terms of the number of
measurements (samples), states where samples were
taken, months when samples were taken, and
summary statistics for their respective distributions of
measured air exchange rates. For selected projects
(Lawrence Berkeley Laboratory, Research Triangle
Institute, Southern California—SOCAL), multiple
measurements were taken for the same house, usually
during different seasons. A large majority of the
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measurements are from the SOCAL project that was
conducted in Southern California. The means of the
respective studies generally range from 0.2 to
LOACH, with the exception of two California
projects—RTI2 and SOCAL2. Both projects involved
measurements in Southern California during a time of
year (July) when windows would likely be opened by
many occupants.
The limitation of this study is that the PFT
database did not base its measurements on a sample
that was statistically representative of the national
housing stock. PFT has been found to underpredict
seasonal average air exchange by 20 to 30%
(Sherman, 1989). Using PFT to determine air
exchange can produce significant errors when
conditions in the measurement scene greatly deviate
from idealizations calling for constant, well-mixed
conditions.
19.5.1.2.3. Murray and Burmaster (1995)—
Residential Air Exchange Rates in
the United States: Empirical and
Estimated Parametric Distributions
by Season and Climatic Region
Murray and Burmaster (1995) analyzed the PFT
database using 2,844 measurements (essentially the
same cases as analyzed by Koontz and Rector (1995),
but without the compensating weights). These
authors summarized distributions for subsets of the
data defined by climate region and season. The
months of December, January, and February were
defined as winter; March, April, and May were
defined as spring; and so on. Table 19-26 summarizes
the results of Murray and Burmaster (1995)
Neglecting the summer results in the colder regions,
which have only a few observations, the results
indicate that the highest air exchange rates occur in
the warmest climate region during the summer. As
noted earlier, many of the measurements in the
warmer climate region were from field studies
conducted in Southern California during a time of
year (July) when windows would tend to be open in
that area. Data for this region in particular should be
used with caution because other areas within this
region tend to have very hot summers, and residences
use air conditioners, resulting in lower air exchange
rates. The lowest rates generally occur in the colder
regions during the fall.
19.5.1.2.4. Diamond et al. (1996)—Ventilation
and Infiltration in High-Rise
Apartment Buildings
Diamond et al. (1996) studied air flow in a
13-story apartment building and concluded that "the
ventilation to the individual units varies
considerably." With the ventilation system disabled,
units at the lower level of the building had adequate
ventilation only on days with high temperature
differences, while units on higher floors had no
ventilation at all. At times, units facing the windward
side were over-ventilated. With the mechanical
ventilation system operating, they found wide
variation in the air flows to individual apartments.
Diamond et al. (1996) also conducted a literature
review and concluded there were little published data
on air exchange in multifamily buildings, and that
there was a general problem measuring, modeling,
and designing ventilation systems for high-rise
multifamily buildings. Air flow was dependent upon
building type, occupation behavior, unit location, and
meteorological conditions.
19.5.1.2.5. Graham et al. (2004)—Contribution
of Vehicle Emissions from an
Attached Garage to Residential
Indoor Air Pollution Levels
There have been several studies of vehicle
emission seepage into homes from attached garages,
which examined a single home. Graham et al. (2004)
conducted a study of vehicle emission seepage of
16 homes with attached garages. On average, 11% of
total house leakage was attributed to the house/garage
interface (equivalent to an opening of 124 cm2), but
this varied from 0.6 to 29.6%. The amount of
in-house chemical concentrations attributed to
vehicle emissions from the garage varied widely
between homes from 9 to 85%. Greater leakage
tended to occur in houses where the garage attached
to the house on more than one side. The home's age
was not an important factor. Whether the engine was
warm or cold when it was started was important
because cold-start emissions are dominated by the
by-products of incomplete combustion. Cold-start tail
pipe emissions were 32 times greater for carbon
monoxide (CO), 10 times greater for nitrogen oxide
(NOx), and 18 times greater for total hydrocarbon
emissions than hot-start tailpipe emissions.
19.5.1.2.6. Price et al. (2006)—Indoor-Outdoor
Air Leakage of Apartments and
Commercial Buildings
Price et al. (2006) compiled air exchange rate
data from 14 different studies on apartment buildings
in the United States and Canada. The authors found
that indoor-outdoor air exchange rates seem to be
twice as high for apartments as for single-family
houses. The observed apartment air exchange rates
ranged from 0.5 to 2 ACH.
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19.5.1.2.7. Yamamoto et al. (2010)—Residential
Air Exchange Rates in Three U.S.
Metropolitan Areas: Results from
the Relationship Among Indoor,
Outdoor, and Personal Air Study
1999-2001
Between 1999 and 2001, Yamamoto et al. (2010)
conducted approximately 500 indoor-outdoor air
exchange rate (AER) calculations based on
residences in metropolitan Elizabeth, NJ; Houston,
TX; and Los Angeles, CA. The median AER across
these urban areas was 0.71 ACH; 0.87 in CA, 0.88 in
NJ, and 0.47 in TX. In Texas, the measured AERs
were lower in the summer cooling season
(median =0.37 ACH) than in the winter heating
season (median = 0.63 ACH), likely because of the
reported use of room air conditioners. The measured
AERs in California were higher in summer
(median =1.13 ACH) than in winter
(median = 0.61 ACH) because summers in Los
Angeles County are less humid than NJ or TX, and
residents are more likely to utilize natural ventilation
through open windows and screened doors. In New
Jersey, air exchange rates in the heating and cooling
seasons were similar.
19.5.1.3. Key Study of Non-Residential Air
Exchange Rates
19.5.1.3.1. Turk et al. (1987)—Commercial
Building Ventilation Rates and
Particle Concentrations
Few air exchange rates for commercial buildings
are provided in the literature. Turk et al. (1987)
conducted indoor air quality measurements, including
air exchange rates, in 38 commercial buildings. The
buildings ranged in age from 0.5 to 90 years old.
One test was conducted in 36 buildings, and two tests
were conducted in 2 buildings. Each building was
monitored for 10 working days over a 2-week period
yielding a minimum sampling time of 75 hours per
building. Researchers found an average ventilation
measurement of 1.5 ACH, which ranged from 0.3 to
4.1 ACH with a standard deviation of 0.87.
Table 19-27 presents the results by building type.
19.5.2. Indoor Air Models
Achieving adequate indoor air quality in a non-
residential building can be challenging. There are
many factors that affect indoor air quality in
buildings (e.g., building materials, outdoor
environment, ventilation systems, operation and
maintenance, occupants and their activities). Indoor
air models are typically used to study, identify, and
solve problems involving indoor air quality in
buildings, as well as to assess efficiency of energy
use. Indoor air quality models generally are not
software products that can be purchased as "off-the-
shelf items. Most existing software models are
research tools that have been developed for specific
purposes and are being continuously refined by
researchers. Leading examples of indoor air models
implemented as software products are as follows:
CONTAM 3.0—CONTAM was developed at
the National Institute of Standards and
Technology (NIST) with support from
U.S. EPA and the U.S. DOE. Version 3.0 was
sponsored by the Naval Surface Warfare
Center Dahlgren Division. (Axley, 1988;
Walton and Dols, 2010; Wang et al., 2010).
IAQX—The Indoor Air Quality and Inhalation
Exposure model is a Windows-based
simulation software package developed by
U.S. EPA (Quo, 2000).
CPIEM—The California Population Indoor
Exposure Model was developed for the
California Air Resources Board (Rosenbaum
etal.,2002).
TEM—The Total Exposure Model was
developed with support from U.S. EPA and
the U.S. Air Force (Wilkes, 1998; Wilkes and
Nuckols, 2000).
RISK—RISK was developed by the Indoor
Environment Management Branch of the
U.S. EPA National Risk Management
Research Laboratory (Sparks, 1997).
TRIM—The Total Risk Integrated
Methodology is an ongoing modeling project
of U.S. EPAs Office of Air Quality Planning
and Standards (Efroymson and Murphy, 2001;
Palma, 1999).
TOXLT/TOXST—The Toxic Modeling
System Long-Term was developed along with
the release of the new version of the
U.S. EPAs Industrial Source Complex
Dispersion Models (U.S. EPA, 1995).
MIAQ—The Multi-Chamber Indoor Air
Quality Model was developed for the
California Institute of Technology and
Lawrence Berkeley National Laboratory.
Documentation last updated in 2002.
(Nazaroff and Cass, 1986; Nazzaroff and
Cass, 1989a).
MCCEM—the Multi-Chamber Consumer
Exposure Model was developed for U.S.
EPA Office of Pollution Prevention and
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Toxics (EPA/OPPT) (GEOMET,
Koontz and Nagda, 1991).
1989;
Price (2001) is an evaluation of the use of many
of the above products (TOXLT/TOXST, MCCEM,
IAQX, CONTAM, CPIEM, TEM, TRIM, and RISK)
in a tiered approach to assessing exposures and risks
to children. The information provided is also
applicable to adults.
19.5.3. Infiltration Models
A variety of mathematical models exist for
prediction of air infiltration rates in individual
buildings. A number of these models have been
reviewed, for example, by Liddament and Allen
(1983), and by Persily and Linteris (1984). Basic
principles are concisely summarized in the ASHRAE
Handbook of Fundamentals (ASHRAE, 1993). These
models have a similar theoretical basis; all address
indoor-outdoor pressure differences that are
maintained by the actions of wind and stack
(temperature difference) effects. The models
generally incorporate a network of airflows where
nodes representing regions of different pressure are
interconnected by leakage paths. Individual models
differ in details such as the number of nodes they can
treat or the specifics of leakage paths (e.g., individual
components such as cracks around doors or windows
versus a combination of components such as an entire
section of a building). Such models are not easily
applied by exposure assessors, however, because the
required inputs (e.g., inferred leakage areas, crack
lengths) for the model are not easy to gather.
Another approach for estimating air infiltration
rates is developing empirical models. Such models
generally rely on the collection of infiltration
measurements in a specific building under a variety
of weather conditions. The relationship between the
infiltration rate and weather conditions can then be
estimated through regression analysis and is usually
stated in the following form:
bT-T
(Eqn. 19-1)
where:
A = air infiltration rate (hours :),
Tt = indoor temperature (°C),
T0 = outdoor temperature (°C),
U = windspeed (m/second),
n is an exponent with a value typically
between 1 and 2, and
a, b and c are parameters to be estimated.
Relatively good predictive accuracy usually can
be obtained for individual buildings through this
approach. However, exposure assessors often do not
have the information resources required to develop
parameter estimates for making such predictions.
A reasonable compromise between the
theoretical and empirical approaches has been
developed in the model specified by Dietz et al.
(1986). The model, drawn from correlation analysis
of environmental measurements and air infiltration
data, is formulated as follows:
—
(Eqn. 19-2)
where:
A = average ACH or infiltration rate,
hours"1,
L = generalized house leakiness factor
(KK5),
C = terrain sheltering factor (1< C < 10),
AT = indoor-outdoor temperature difference
(°C), and
U = windspeed (m/second).
The value of L is greater as house leakiness
increases, and the value of C is greater as terrain
sheltering (reflects shielding of nearby wind barrier)
increases. Although the above model has not been
extensively validated, it has intuitive appeal, and it is
possible for the user to develop reasonable estimates
for L and C with limited guidance. Historical data
from various U.S. airports are available for
estimation of the temperature and windspeed
parameters. As an example application, consider a
house that has central values of 3 and 5 for L and C,
respectively. Under conditions where the indoor
temperature is 20°C (68°F), the outdoor temperature
is 0°C (32°F), and the windspeed is 5 m/second, the
predicted infiltration rate for that house would be 3
(0.006 x 20 + 0.03/5 x 51.5), or 0.56 ACH. This
prediction applies under the condition that exterior
doors and windows are closed and does not include
the contributions, if any, from mechanical systems
(see Section 19.3.3.4). Occupant behavior, such as
opening windows, can, of course, overwhelm the
idealized effects of temperature and wind speed.
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Chan et al. (2005) analyzed the U.S. Residential
Air Leakage database at Lawrence Berkley National
Laboratory (LBNL) containing 73,000 air leakage
measurements from 30 states (predominantly Ohio,
Alaska, and Wisconsin). They present the following
equation for estimating ACH:
where:
H
ACH
H
NL
F
h
— M
HF1 J
(Eqn 19-3)
: air changes per hour,
: building height (meters),
: normalized leakage (unitless),
: scaling factor (unitless), and
: hours.
Chan et al. (2005) found that "older and smaller
homes are more likely to have higher normalized
leakage areas than newer and larger ones."
Table 19-28 summarizes the normalized leakage
distributions in the United States.
It should be noted that newer homes were
generally built tighter until about 1997 when the
construction trend leveled off. Sherman and Matson
(2002) also examined LBNL's U.S. Residential Air
Leakage database and found that average normalized
leakage for 22,000 houses already in the database
was 1.18 NL (total leakage cm2 normalized for
dwelling size m2), but leakage among the
8,700 newer homes averaged 0.30 NL.
19.5.4. Vapor Intrusion
In 1998, concerns about subsurface
contamination of soil or ground water impacting
indoor air quality led the U.S. EPA to develop a series
of models for estimating health risks from subsurface
vapor intrusion into buildings based on the analytical
solutions of Johnson and Ettinger (1991). Since that
time, the models have been revised, and new models
have been added. The 3-phase soil contamination
models theoretically partition the contamination into
three discrete phases: (1) in solution with water,
(2) sorbed to the soil organic carbon, and (3) in vapor
phase within the air-filled pores of the soil. Two new
models have been added, allowing the user to
estimate vapor intrusion into buildings from
measured soil gas data. When Non-Aqueous Phase
Liquid (NAPL) is present in soils, the contamination
includes a fourth or residual phase. In such cases, the
new NAPL models can be used to estimate the rate of
vapor intrusion into buildings and the associated
health risks. The new NAPL models use a numerical
approach for simultaneously solving the
time-averaged soil and building vapor concentration
for each of up to 10 soil contaminants. This involves
a series of iterative calculations for each contaminant.
These models are available online from U.S. EPA at
http://www.epa.gov/oswer/riskassessment/airmodel/
j ohnson_ettinger. htm.
19.5.5. Deposition and Filtration
Deposition refers to the removal of airborne
substances to available surfaces that occurs as a result
of gravitational settling and diffusion, as well as
electrophoresis and thermophoresis. Filtration is
driven by similar processes but is confined to
material through which air passes. Filtration is
usually a matter of design, whereas deposition is a
matter of fact.
19.5.5.1. Deposition
The deposition of paniculate matter and reactive
gas-phase pollutants to indoor surfaces is often stated
in terms of a characteristic deposition velocity
(mhouT1) allied to the surface-to-volume ratio
(m2 m"3) of the building or room interior, forming a
first order loss rate (hour"1) similar to that of air
exchange. Theoretical considerations specific to
indoor environments have been summarized in
comprehensive reviews by Nazaroff and Cass
(1989b) and Nazaroff etal. (1993).
For airborne particles, deposition rates depend on
aerosol properties (size, shape, density) as well as
room factors (thermal gradients, turbulence, surface
geometry). The motions of larger particles are
dominated by gravitational settling; the motions of
smaller particles are subject to convection and
diffusion. Consequently, larger particles tend to
accumulate more rapidly on floors and up-facing
surfaces while smaller particles may accumulate on
surfaces facing in any direction. Figure 19-3
illustrates the general trend for particle deposition
across the size range of general concern for
inhalation exposure (<10 um). The current thought is
that theoretical calculations of deposition rates are
likely to provide unsatisfactory results due to
knowledge gaps relating to near-surface air motions
and other sources of inhomogeneity (Nazaroff et al.,
1993).
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19.5.5.1.1. Thatcher and Layton (1995)—
Deposition, Re-suspension, and
Penetration of Particles within a
Residence
Thatcher and Layton (1995) evaluated removal
rates for indoor particles in four size ranges (1-5,
5-10, 10-25, and >25 um) in a study of one house
occupied by a family of four. Table 19-29 lists these
values. In a subsequent evaluation of data collected in
100 Dutch residences, Layton and Thatcher (1995)
estimated settling velocities of 2.7 m hour"1 for lead-
bearing particles captured in total suspended
paniculate matter samples.
19.5.5.1.2. Wallace (1996)—Indoor Particles: A
Review
In a major review of indoor particles, Wallace
(1996) cited overall particle deposition per hour
(hour"1) for respirable (PM25), inhalable (PM10), and
coarse (difference between PM10 and PM25) size
fractions determined from U.S. EPA's Particle Total
Exposure Assessment Methodological Study
(PTEAM) study. These values, listed in Table 19-30,
were derived from measurements conducted in nearly
200 residences.
19.5.5.1.3. Thatcher et al. (2002)—Effects of
Room Furnishings and Air Speed on
Particle Deposition Rates Indoors
Thatcher et al. (2002) measured deposition loss
rate coefficients for particles of different median
diameters (0.55 to 8.66 mm) with fans off and on at
various airspeeds in three types of experimental
rooms: (1) bare (unfurnished with metal floor),
(2) carpeted and unfurnished, and (3) fully furnished.
They concluded that large particles (over 25 um)
settle eight times faster than small particles (1-5 um).
Table 19-31 summarizes the results.
19.5.5.1.4. He et al. (2005)—Particle Deposition
Rates in Residential Houses
He et al. (2005) investigated particle deposition
rates for particles ranging in size from 0.015 to 6 um.
The lowest deposition rates were found for particles
between 0.2 and 0.3 um for both minimum (air
exchange rate: 0.61 ± 0.45 hour"1) and normal (air
exchange rate: 3.00 ± 1.23 hour"1) conditions. Thus,
air exchange rate was an important factor affecting
deposition rates for particles between 0.08 and
1.0 um, but not for particles smaller than 0.08 um or
larger than 1.0 um.
19.5.5.2. Filtration
A variety of air cleaning techniques have been
applied to residential settings. Basic principles related
to residential-scale air cleaning technologies have
been summarized in conjunction with reporting early
test results (Offerman et al., 1984). General
engineering principles are summarized in ASHRAE
(1988). In addition to fibrous filters integrated into
central heating and air conditioning systems,
extended surface filters and High Efficiency Particle
Arrest filters, as well as electrostatic systems, are
available to increase removal efficiency.
Free-standing air cleaners (portable and/or console)
are also being used. Product-by-product test results
reported by Hanley et al. (1994); Shaughnessy et al.
(1994); and Offerman et al. (1984) exhibit
considerable variability across systems, ranging from
ineffectual (<1% efficiency) to nearly complete
removal.
19.5.6. Interzonal Airflows
Residential structures consist of a number of
rooms that may be connected horizontally, vertically,
or both horizontally and vertically. Before
considering residential structures as a detailed
network of rooms, it is convenient to divide them into
one or more zones. At a minimum, each floor is
typically defined as a separate zone. For indoor air
exposure assessments, further divisions are
sometimes made within a floor, depending on
(1) locations of specific contaminant sources and
(2) the presumed degree of air communication among
areas with and without sources.
Defining the airflow balance for a multiple-zone
exposure scenario rapidly increases the information
requirements as rooms or zones are added. As shown
in Figure 19-4, a single-zone system (considering the
entire building as a single well-mixed volume)
requires only two airflows to define air exchange.
Further, because air exchange is balanced flow (air
does not "pile up" in the building, nor is a vacuum
formed), only one number (the air exchange rate) is
needed. With two zones, six airflows are needed to
accommodate interzonal airflows plus air exchange;
with three zones, 12 airflows are required. In some
cases, the complexity can be reduced using judicious
(if not convenient) assumptions. Interzonal airflows
connecting non-adjacent rooms can be set to zero, for
example, if flow pathways do not exist. Symmetry
also can be applied to the system by assuming that
each flow pair is balanced.
Examples of interzonal airflow models include
CONTAM (developed by NIST) and COMIS (Feustel
and Raynor-Hoosen, 1990).
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19.5.7. House Dust and Soil Loadings
House dust is a complex mixture of biologically
derived material (animal dander, fungal spores, etc.),
paniculate matter deposited from the indoor aerosol,
and soil particles brought in by foot traffic. House
dust may contain VOCs (Wolkoff and Wilkins, 1994;
Hirvonen et al., 1995), pesticides from imported soil
particles as well as from direct applications indoors
(Roberts et al., 1991), and trace metals derived from
outdoor sources (Layton and Thatcher, 1995). The
indoor abundance of house dust depends on the
interplay of deposition from the airborne state,
resuspension due to various activities, direct
accumulation, and infiltration.
In the absence of indoor sources, indoor
concentrations of paniculate matter are significantly
lower than outdoor levels. For some time, this
observation supported the idea that a significant
fraction of the outdoor aerosol is filtered out by the
building envelope. More recent data, however, have
shown that deposition (incompletely addressed in
earlier studies) accounts for the indoor-outdoor
contrast, and outdoor particles smaller than 10-um
aerodynamic diameter penetrate the building
envelope as completely as non-reactive gases
(Wallace, 1996).
It should be noted that carpet dust loadings may
be higher than previously believed. This is important
because embedded dust is a reservoir for organic
compounds. Fortune et al. (2000) compared the mass
of dust in carpets removed using conventional
vacuuming to that removed by vacuuming with a
beater-bar to remove deeply embedded dust. The
amount removed was 10 times that removed by
conventional vacuuming.
19.5.7.1. Roberts et al (1991)—Development and
Field Testing of a High-Volume Sampler
for Pesticides and Toxics in Dust
Dust loadings, reported by Roberts et al. (1991),
were measured in conjunction with the
Non-Occupational Pesticide Exposure Study
(NOPES). In this study, house dust was sampled from
a representative grid using a specially constructed
high-volume surface sampler. The surface sampler
collection efficiency was verified in conformance
with ASTM F608 (ASTM, 1989). Table 19-32
summarizes data collected from carpeted areas in
volunteer households in Florida encountered during
the course of NOPES. Seven of the nine sites were
single-family detached homes, and two were mobile
homes. The authors noted that the two houses
exhibiting the highest dust loadings were only those
homes where a vacuum cleaner was not used for
housekeeping.
19.5.7.2. Thatcher and Layton (1995)—
Deposition, Resuspension, and
Penetration of Particles within a
Residence
Relatively few studies have been conducted at
the level of detail needed to clarify the dynamics of
indoor aerosols. One intensive study of a California
residence (Thatcher and Layton, 1995), however,
provides instructive results. Using a model-based
analysis for data collected under controlled
circumstances, the investigators verified penetration
of the outdoor aerosol and estimated rates for particle
deposition and resuspension (see Table 19-33). The
investigators stressed that normal household activities
are a significant source of airborne particles larger
than 5 um. During the study, they observed that just
walking into and out of a room could momentarily
double the concentration. The airborne abundance of
submicrometer particles, on the other hand, was
unaffected by either cleaning or walking.
Mass loading of floor surfaces (see Table 19-34)
was measured in the study of Thatcher and Layton
(1995) by thoroughly cleaning the house and
sampling accumulated dust, after 1 week of normal
habitation and no vacuuming. The methodology,
validated under ASTM F608 (ASTM, 1989), showed
fine dust recovery efficiencies of 50% with new
carpet and 72% for linoleum. Tracked areas showed
consistently higher accumulations than untracked
areas, confirming the importance of tracked-in
material. Differences between tracked areas upstairs
and downstairs show that tracked-in material is not
readily transported upstairs. The consistency of
untracked carpeted areas throughout the house,
suggests that, in the absence of tracking, particle
transport processes are similar on both floors.
19.6. CHARACTERIZING INDOOR
SOURCES
Product- and chemical-specific mechanisms for
indoor sources can be described using simple
emission factors to represent instantaneous releases,
as well as constant releases over defined time
periods; more complex formulations may be required
for time-varying sources. Guidance documents for
characterizing indoor sources within the context of
the exposure assessment process are limited (see, for
example, Jennings et al., 1987; Wolkoff, 1995).
Fairly extensive guidance exists in the technical
literature, however, provided that the exposure
assessor has the means to define (or estimate) key
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mechanisms and chemical-specific parameters. Basic
concepts are summarized below for the broad source
categories that relate to airborne contaminants,
waterborne contaminants, and for soil/house dust
indoor sources.
19.6.1. Source Descriptions for Airborne
Contaminants
Table 19-35 summarizes simplified indoor
source descriptions for airborne chemicals for direct
emission sources (e.g., combustion, pressurized
propellant products), as well as emanation sources
(e.g., evaporation from "wet" films, diffusion from
porous media), and transport-related sources (e.g.,
infiltration of outdoor air contaminants, soil gas
entry).
Direct-emission sources can be approximated
using simple formulas that relate pollutant mass
released to characteristic process rates. Combustion
sources, for example, may be stated in terms of an
emission factor, fuel content (or heating value), and
fuel consumption (or carrier delivery) rate. Emission
factors for combustion products of general concern
(e.g., CO, NOX) have been measured for a number of
combustion appliances using room-sized chambers
(see, for example, Relwani et al., 1986). Other
direct-emission sources would include volatiles
released from water use and from pressurized
consumer products. Resuspension of house dust (see
Section 19.5.5.1) would take on a similar form by
combining an activity-specific rate constant with an
applicable dust mass.
Diffusion-limited sources (e.g., carpet backing,
furniture, flooring, dried paint) represent probably the
greatest challenge in source characterization for
indoor air quality. Vapor-phase organics dominate
this group, offering great complexity because
(1) there is a fairly long list of chemicals that could
be of concern, (2) ubiquitous consumer products,
building materials, coatings, and furnishings contain
varying amounts of different chemicals, (3) source
dynamics may include non-linear mechanisms, and
(4) for many of the chemicals, emitting as well as
non-emitting materials evident in realistic settings
may promote reversible and irreversible sink effects.
Very detailed descriptions for diffusion-limited
sources can be constructed to link specific properties
of the chemical, the source material, and the
receiving environment to calculate expected behavior
(see, for example, Schwope et al., 1992; Cussler,
1984). Validation to actual circumstances, however,
suffers practical shortfalls because many parameters
simply cannot be measured directly.
The exponential formulation listed in
Table 19-35 was derived based on a series of papers
generated during the development of chamber testing
methodology by U.S. EPA (Dunn, 1987; Dunn and
Tichenor, 1988; Dunn and Chen, 1993). This
framework represents an empirical alternative that
works best when the results of chamber tests are
available. Estimates for the initial emission rate (E0)
and decay factor (ks) can be developed for
hypothetical sources from information on pollutant
mass available for release (M) and supporting
assumptions.
Assuming that a critical time period (4)
coincides with reduction of the emission rate to a
critical level (Ec) or with the release of a critical
fraction of the total mass (Mc), the decay factor can
be estimated by solving either of these relationships:
where:
EC
En
Ec
E0
ks
tc
= e sc (Eqn. 19-4)
= emission rate to a critical level
(ughouT1),
= initial emission rate (ug hour"1),
= decay factor (ug hour"1), and
= critical time period (hours),
or
M
(Eqn. 19-5)
where:
Mc
M
critical mass (ug), and
total mass (ug).
The critical time period can be derived from
product-specific considerations (e.g., equating drying
time for paint to 90% emissions reduction). Given
such an estimate for ks, the initial emission rate can
be estimated by integrating the emission formula to
infinite time under the assumption that all chemical
mass is released:
M = JE0 e - kstdt = —- (Eqn. 19-6)
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The basis for the exponential source algorithm
has also been extended to the description of more
complex diffusion-limited sources. With these
sources, diffusive or evaporative transport at the
interface may be much more rapid than diffusive
transport from within the source material, so that the
abundance at the source/air interface becomes
depleted, limiting the transfer rate to the air. Such
effects can prevail with skin formation in "wet"
sources like stains and paints (see, for example,
Chang and Guo, 1992). Similar emission profiles
have been observed with the emanation of
formaldehyde from particleboard with "rapid" decline
as formaldehyde evaporates from surface sites of the
particleboard over the first few weeks. It is then
followed by a much slower decline over ensuing
years as formaldehyde diffuses from within the
matrix to reach the surface (see, for example, Zinn
etal., 1990).
Transport-based sources bring contaminated air
from other areas into the airspace of concern.
Examples include infiltration of outdoor
contaminants, and soil gas entry. Soil gas entry is a
particularly complex phenomenon and is frequently
treated as a separate modeling issue (Little et al.,
1992; Sextro, 1994). Room-to-room migration of
indoor contaminants would also fall under this
category, but this concept is best considered using
multi-zone models.
19.6.2. Source Descriptions for Waterborne
Contaminants
Residential water supplies may be a route for
exposure to chemicals through ingestion, dermal
contact, or inhalation. These chemicals may appear in
the form of contaminants (e.g., trichloroethylene) as
well as naturally occurring by-products of water
system history (e.g., chloroform, radon). Among
indoor water uses, showering, bathing, and hand-
washing of dishes or clothes provide the primary
opportunities for dermal exposure. The escape of
volatile chemicals to the gas phase associates water
use with inhalation exposure. The exposure potential
for a given chemical will depend on the source of
water, the types and extents of water uses, and the
extent of volatilization of specific chemicals. Primary
types of residential water use include
showering/bathing, toilet use, clothes washing,
dishwashing, and faucet use (e.g., for drinking,
cooking, general cleaning, or washing hands).
Upper-bounding estimates of chemical release
rates from water use can be formulated as simple
emission factors by combining the concentration in
the feed water (g nT3) with the flow rate for the water
use (m3 hour :), and assuming that the chemical
escapes to the gas phase. For some chemicals,
however, not all of the chemical escapes in realistic
situations due to diffusion-limited transport and
solubility factors. For inhalation exposure estimates,
this may not pose a problem because the bounding
estimate would overestimate emissions by no more
than approximately a factor of two. For multiple
exposure pathways, the chemical mass remaining in
the water may be of importance. Refined estimates of
volatile emissions are usually considered under
two-resistance theory to accommodate mass transport
aspects of the water-air system (see, for example,
U.S. EPA, 2000; Howard-Reed et al., 1999; Moya
etal., 1999; Little, 1992; Andelman, 1990; McKone,
1987). More detailed descriptions of models used to
estimate emissions from indoor water sources
including showers, bathtubs, dishwashers, and
washing machines are included in U.S. EPA, 2000.
Release rates (S) are formulated as
(Eqn. 19-7)
where:
Ca
H
= chemical release rate (g hour :),
= dimensionless mass-transfer
coefficient,
= water flow rate (m3 hour"1),
= concentration in feed water (g m"3),
= concentration in air (g m"3), and
= dimensionless Henry's Law
constant.
Because the emission rate is dependent on the air
concentration, recursive techniques are required. The
mass-transfer coefficient is a function of water use
characteristics (e.g., water droplet size spectrum, fall
distance, water film) and chemical properties
(diffusion in gas and liquid phases). Estimates of
practical value are based on empirical tests to
incorporate system characteristics into a single
parameter (see, for example, Giardino et al., 1990).
Once characteristics of one chemical-water use
system are known (reference chemical, subscript r),
the mass-transfer coefficient for another chemical
(index chemical, subscript /') delivered by the same
system can be estimated using formulations identified
in the review by Little (1992):
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i (D,
K(DT
KLr
1 1
where:
(Eqn. 19-8)
DL = liquid diffusivity (m2 second :),
DG = gas diffusivity (m2 second"1),
KL = liquid-phase mass-transfer
coefficient,
KG = gas-phase mass transfer coefficient,
and
H = dimensionless Henry's Law
constant.
19.6.3. Soil and House Dust Sources
The rate process descriptions compiled for soil
and house dust provide inputs for estimating indoor
emission rates:
Sd =MdRdAf
(Eqn. 19-9)
where:
Sd = dust emission (g hour :),
Md = dust mass loading (g m"2),
Rd = resuspension rates (hour"1), and
Af = floor area (m2).
Because house dust is a complex mixture,
transfer of particle-bound constituents to the gas
phase may be of concern for some exposure
assessments. For emission estimates, one would then
need to consider particle mass residing in each
reservoir (dust deposit, airborne).
19.7. ADVANCED CONCEPTS
19.7.1. Uniform Mixing Assumption
Many exposure measurements are predicated on
the assumption of uniform mixing within a room or
zone of a house. Mage and Ott (1994) offer an
extensive review of the history of use and misuse of
the concept. Experimental work by Baughman et al.
(1994) and Drescher et al. (1995) indicates that, for
an instantaneous release from a point source in a
room, fairly complete mixing is achieved within
10 minutes when convective flow is induced by solar
radiation. However, up to 100 minutes may be
required for complete mixing under quiescent (nearly
isothermal) conditions. While these experiments were
conducted at extremely low air exchange rates
(<0.1 ACH), based on the results, attention is focused
on mixing within a room.
The situation changes if a human invokes a point
source for a longer period and remains in the
immediate vicinity of that source. Personal exposure
in the near vicinity of a source can be much higher
than the well-mixed assumption would suggest. A
series of experiments conducted by GEOMET (1989)
for the U.S. EPA involved controlled point-source
releases of carbon monoxide tracer (CO), each for
30 minutes. Breathing-zone measurements located
within 0.4 m of the release point were 10 times
higher than for other locations in the room during
early stages of mixing and transport.
Similar investigations conducted by Furtaw et al.
(1995) involved a series of experiments in a
controlled-environment, room-sized chamber. Furtaw
et al. (1995) studied spatial concentration gradients
around a continuous point source simulated by sulfur
hexafluoride (SF6) tracer with a human moving about
the room. Average breathing-zone concentrations
when the subject was near the source exceeded those
several meters away by a factor that varied inversely
with the ventilation intensity in the room. At typical
room ventilation rates, the ratio of source-proximate
to slightly-removed concentration was on the order of
2:1.
19.7.2. Reversible Sinks
For some chemicals, the actions of reversible
sinks are of concern. For an initially "clean"
condition in the sink material, sorption effects can
greatly deplete indoor concentrations. However, once
enough of the chemical has been adsorbed, the
diffusion gradient will reverse, allowing the chemical
to escape. For persistent indoor sources, such effects
can serve to reduce indoor levels initially, but once
the system equilibrates, the net effect on the average
concentration of the reversible sink is negligible.
Over suitably short time frames, this can also affect
integrated exposure. For indoor sources whose
emission profile declines with time (or ends
abruptly), reversible sinks can serve to extend the
emissions period as the chemical desorbs long after
direct emissions are finished. Reversible sink effects
have been observed for a number of chemicals in the
presence of carpeting, wall coverings, and other
materials commonly found in residential
environments.
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Chapter 19—Building Characteristics
Interactive sinks (and models of the processes)
are of special importance; while sink effects can
greatly reduce indoor air concentrations, re-emission
at lower rates over longer time periods could greatly
extend the exposure period of concern. For
completely reversible sinks, the extended time could
bring the cumulative exposure to levels approaching
the sink-free case. Publications (Axley and
Lorenzetti, 1993; Tichenor et al., 1991) show that
first principles provide useful guidance in postulating
models and setting assumptions for reversible-
irreversible sink models. Sorption/desorption can be
described in terms of Langmuir (monolayer) as well
as Brunauer-Emmet-Teller (BET, multilayer)
adsorption.
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Table 19-6. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership
Ownership
Owner-Occupied
TT . Volume" %
Housing
Type (m3) of Total
Single-Family
(Detached) 637 57.7
Single-Family
(Attached) 544 3.8
Multifamily
363 1.7
(2-4 units)
Multifamily
253 2.1
(5+ Units)
Mobile Home 249 5.2
All Types 586 70.5
Rental8
Volume" %
(m ) of Total
449 7.2
313 3.1
211 5.3
189 13.0
196 1.1
269 29.7
All Units
Volume"
(m3)
616
440
247
197
240
492
%
of Total
64.9
6.8
7.0
15.1
6.3
100
a The classification "Occupied without payment of rent" is included in the estimates for rentals.
b Volumes calculated from floor areas assuming a ceiling height of 8 feet. Excludes floor space in unheated
garages.
Source: U.S. EPAAnalysis of U.S. DOE, 2008a.
Table 19-7.
Year of Construction
Before 1940
1940-1949
1950-1959
1960-1969
1970-1979
1980-1989
1990-1999
2000-2005
All Years
a Volumes calculated from
garages.
Residential Volumes in Relation to
Volume" (m3)
527
464
465
446
422
451
567
640
492
floor areas assuming a ceiling height of 8
Year of Construction
% of Total
13.2
6.7
11.3
11.2
17.0
16.7
15.6
8.3
100
feet. Excludes floor space in unheated
Source: U.S. EPAAnalysis of U.S. DOE, 2008a.
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Table 19-8. Summary of Residential Volume
Distributions Based on U.S. DOE (2008a)a
(m3)
Parameter
Arithmetic Mean
Standard Deviation
10thPercentile
25thPercentile
50thPercentile
75thPercentile
90thPercentile
a All housing types, all units
Source: U.S. EPA's Analysis of U.S
Volume
492
349
154
231
395
648
971
. DOE, 2008a.
Table 19-9. Summary of Residential Volume
Distributions Based on Versar (1990) (m3)
Parameter
Arithmetic Mean
Standard Deviation
10thPercentile
25thPercentile
50thPercentile
75thPercentile
90thPercentile
Source: Versar, 1990;
Volume
369
209
167
225
321
473
575
based on PFT database.
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-10. Number of Residential Single Detached and Mobile Homes by Volume" (m3)
and Median Volumes by Housing Type
Year-Round
Occupied
Housing Units
Total all housing units
Single detached and
manufactured/mobile homes
Volume (m )
Less than 113.3
113.3-169.7
169.9-226.3
226.5-339.6
339.8^152.8
453.1-566.1
566.3-679.4
679.6-905.9
906 or more
Not reported/Don't know
Median Volume (m3)
Total
housing
units
130,112
91,241
988
2,765
6,440
21,224
20,636
14,361
7,589
7,252
4,456
5,529
385.1
Seasonal
4,618
3,524
225
462
593
814
521
284
141
137
113
234
260.5
Total
125,494
87,717
764
2,303
5,847
20,410
20,115
14,077
7,448
7,115
4,343
5,295
393.3
Owner
76,428
68,742
383
1,085
3,519
14,978
16,284
12,057
6,622
6,391
3,787
3,638
407.8
Renter
35,378
11,176
220
686
1,495
3,441
2,235
1,134
429
301
243
992
294.5
Vacant
Total
Vacant
13,688
7,799
161
532
833
1,991
1,596
886
398
424
313
666
339.8
New
units in
last 4
years
5,955
4,291
10
19
68
557
827
813
535
751
469
241
521.0
Manuf./
mobile
homes
8,769
8,769
331
1,020
1,935
2,779
1,309
334
126
54
146
735
247.4
a Converted from ft2. Assumes 8-foot ceiling.
Source: U.S. Census Bureau, 2010.
Table 19-11. Dimensional Quantities for Residential Rooms
Nominal Dimensions
8-Foot Ceiling
12' x 15'
12' x 12'
10' x 12'
9'x 12'
6'x 12'
4'x 12'
12-Foot Ceiling
12' x 15'
12'xl2'
10' x 12'
9'x 12'
6'x 12'
4'x 12'
Length
(meters)
4.6
3.7
3.0
2.7
1.8
1.2
4.6
3.7
3.0
2.7
1.8
1.2
Width
(meters)
3.7
3.7
3.7
3.7
3.7
3.7
3.7
3.7
3.7
3.7
3.7
3.7
Height
(meters)
2.4
2.4
2.4
2.4
2.4
2.4
3.7
3.7
3.7
3.7
3.7
3.7
Volume
(m3)
41
33
27
24
16
11
61
49
41
37
24
16
Wall Area
(m2)
40
36
33
31
27
24
60
54
49
47
40
36
Floor Area
(m2)
17
13
11
10
7
4
17
13
11
10
7
4
Total Area
(m2)
74
62
55
51
40
32
94
80
71
67
54
44
Exposure Factors Handbook
September 2011
Page
19-33
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-12. Examples of Products and
Material Sources
Silicone caulk
Floor adhesive
Floor wax
Wood stain
Polyurethane wood finish
Floor varnish or lacquer
Plywood paneling
Chipboard
Gypsum board
Wallpaper
a Based on typical values for a residence
Source: Adapted from Tucker, 1991.
Materials Associated with Floor and Wall Surfaces in Residences
Assumed Amount of
Surface Covered8 (m2)
0.2
10.0
50.0
10.0
10.0
50.0
100.0
100.0
100.0
100.0
Page Exposure Factors Handbook
19-34 September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-13. Residential Heating Characteristics by U.S. Census Region
Space Heating Characteristics
Total
Do Not Have Space Heating Equipment
Have Main Space Heating Equipment
Main Heating Fuel and Equipment
Natural Gas
Central Warm-Air Furnace
Steam or Hot Water System
Floor, Wall or Pipeless Furnace
Room Heater
Other Equipment
Electricity
Built-in Electric Units
Central Warm-Air Furnace
Heat Pump
Portable Electric Heater
Other Equipment
Fuel Oil
Steam or Hot Water System
Central Warm-Air Furnace
Other Equipment
Wood
Propane/LPGa
Central Warm-Air Furnace
Room Heater
Other Equipment
Kerosene
Other Fuel
Secondary Heating Fuel and Equipment
No
Yes (More than One May Apply)
Natural Gas
Fireplace
Room Heater
Central Warm- Air Furnace
Other Equipment
Electricity
Portable Heater
Built-in Electric Units
Heat Pump
Other Equipment
Fuel Oil
Wood
Propane/LPG
Kerosene
Other Fuel
a Liquefied Petroleum Gas.
Q = Data withheld either because the Relative Standard
households were sampled.
N/R = No cases in reporting sample.
Source: U.S. DOE, 2008a.
Housing
Jnits (%)
100.0
1.1
98.8
52.4
40.2
7.4
2.1
1.8
0.8
30.3
4.5
14.4
8.3
1.4
1.7
6.9
4.2
2.5
0.3
2.6
5.4
3.7
0.8
0.9
0.6
0.5
68.6
31.4
4.5
2.4
0.5
1.0
0.7
17.7
14.4
2.0
0.5
1.2
0.4
8.0
2.1
0.8
0.2
U
S. Census Region
Northeast Midwest
100.0
Q
99.5
55.3
29.6
23.8
Q
Q
1.0
7.8
4.4
1.5
Q
Q
1.0
30.1
20.9
8.7
Q
2.4
1.9
1.0
Q
Q
1.0
Q
78.6
21.4
1.9
Q
Q
Q
Q
12.1
9.7
1.9
N/R
Q
1.0
4.4
1.5
1.0
Q
Error (RSE) was greater than
100.0
Q
100.0
71.9
63.3
6.3
1.2
Q
Q
13.7
4.3
5.5
3.1
Q
Q
2.7
Q
2.0
Q
2.7
7.4
6.6
Q
Q
Q
Q
63.3
36.7
5.9
3.1
Q
1.6
Q
20.7
16.8
2.3
Q
1.6
Q
8.6
2.7
1.2
Q
50% or
South
100.0
Q
99.0
33.4
27.0
2.5
0.5
2.2
1.0
54.3
3.7
27.0
17.7
2.2
3.4
1.2
Q
0.7
Q
2.2
6.6
3.7
1.7
1.0
1.0
Q
71.0
29.0
3.2
1.5
0.7
Q
Q
17.0
13.8
1.0
1.0
1.5
Q
7.6
2.7
1.0
Q
fewer than 10
West
100.0
2.9
96.7
60.7
47.1
2.5
6.6
3.3
1.2
26.9
6.6
14.0
4.1
2.1
Q
1.2
Q
Q
Q
3.3
4.1
2.5
Q
1.2
Q
Q
61.6
38.4
7.4
4.5
Q
1.7
1.2
21.1
16.9
2.9
Q
1.7
N/R
11.2
N/R
N/R
Q
Exposure Factors Handbook
September 2011
Page
19-35
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-14. Residential Heating Characteristics by Urban/Rural Location
Space Heating Characteristics
Total
Do Not Have Space Heating Equipment
Have Main Space Heating Equipment
Main Heating Fuel and Equipment
Natural Gas
Central Warm-Air Furnace
Steam or Hot Water System
Floor, Wall or Pipeless Furnace
Room Heater
Other Equipment
Electricity
Built-in Electric Units
Central Warm-Air Furnace
Heat Pump
Portable Electric Heater
Other Equipment
Fuel Oil
Steam or Hot Water System
Central Warm-Air Furnace
Other Equipment
Wood
Heating Stove
Other Equipment
Propane/LPGa
Central Warm-Air Furnace
Room Heater
Other Equipment
Kerosene
Other Fuel
Secondary Heating Fuel and Equipment
No
Yes (More than One May Apply)
Natural Gas
Fireplace
Room Heater
Central Warm- Air Furnace
Other Equipment
Electricity
Portable Heater
Built-in Electric Units
Heat Pump
Other Equipment
Fuel Oil
Wood
Propane/LPG
Kerosene
Other Fuel
a Liquefied Petroleum Gas.
Q = Data withheld either because Relative
N/R = No cases in reporting sample.
Source: U.S. DOE, 2008a.
Housing
Units (%)
100.0
1.1
98.8
52.4
40.2
7.4
2.1
1.8
0.8
30.3
4.5
14.4
8.3
1.4
1.7
6.9
4.2
2.5
0.3
2.6
1.8
0.8
5.4
3.7
0.8
0.9
0.6
0.5
68.6
31.4
4.5
2.4
0.5
1.0
0.7
17.7
14.4
2.0
0.5
1.2
0.4
8.0
2.1
0.8
0.2
Urban/Rural Location
City Town
100.0
1.5
98.3
57.3
42.0
9.3
2.5
2.3
0.8
33.8
5.3
16.8
7.2
1.7
2.5
5.1
3.8
1.3
Q
0.6
Q
Q
0.6
Q
Q
Q
Q
0.6
75.2
24.8
3.8
1.9
Q
0.8
0.8
15.9
13.2
1.7
Q
0.8
N/R
5.5
Q
Q
Q
Standard Error (RSE) was >50% or <10
100.0
Q
99.5
62.6
45.3
11.1
2.6
2.6
1.6
24.2
4.2
14.2
4.2
Q
Q
8.9
4.7
3.7
Q
Q
Q
Q
l.l
Q
Q
Q
Q
Q
73.2
26.8
3.7
1.6
Q
Q
Q
15.8
13.7
Q
Q
1.1
Q
6.3
Q
Q
Q
Suburbs
100.0
0.9
99.1
65.6
56.4
6.2
1.8
Q
Q
25.6
4.0
10.1
9.7
Q
Q
5.3
3.5
2.2
N/R
Q
Q
N/R
1.3
Q
Q
Q
Q
Q
67.4
32.2
7.5
4.8
Q
1.3
Q
17.6
14.5
2.2
Q
Q
Q
7.0
1.3
Q
Q
Rural
100.0
Q
99.1
19.3
16.1
1.3
Q
Q
Q
33.2
4.0
14.3
12.1
2.2
Q
10.8
5.4
4.5
Q
10.3
6.7
3.1
23.3
16.6
3.1
3.6
1.8
Q
52.0
48.4
3.1
1.8
Q
Q
Q
23.3
17.0
3.1
1.3
2.2
Q
15.2
8.1
2.2
Q
households were sampled.
Page
19-36
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-15. Residential Air Conditioning Characteristics by U.S. Census Region
. . „ .... . „. .... Housing
Air Conditioning Characteristics ,, . .0°.
Total
Do Not Have Cooling Equipment
Have Cooling Equipment
Air-Conditioning Equipment3' b
Central System
Window/Wall Units
Frequency of Central Air-Conditioner Use
Never
Only a Few Times When Needed
Quite a Bit
All Summer
Frequency Most-Used Unit Used
Never
Only a Few Times When Needed
Quite a Bit
All Summer
a In the 2005 RECS, 1 .5 million housing units reported having
100.0
16.0
84.0
59.3
26.0
1.3
10.3
11.3
36.5
0.5
10.9
6.8
7.7
U.S. Census Region
Northeast Midwest
100.0 100.0
19.4 8.2
80.1 91.8
29.1 67.6
51.9 25.8
Q Q
7.8 15.2
5.8 17.6
14.6 34.4
Q Q
23.8 12.1
14.6 6.3
12.6 7.0
South
100.0
3.4
96.6
78.9
19.7
1.0
6.1
11.1
60.9
Q
5.2
5.4
8.8
West
100.0
42.6
57.4
43.4
14.9
3.3
14.0
9.9
16.1
Q
8.3
2.9
2.9
both central and window/wall air conditioners.
b The number of housing units using air-conditioning includes a small
where the fuel for central air-conditioning was other than electricity;
as if the air-conditioning fuel was electricity.
, undetermined number of housing units
these housing units were treated
Q = Data withheld either because the Relative Standard Error (RSE) was greater than 50% or fewer than
10 households were sampled.
Source: U.S. DOE, 2008a.
Table 19-16. Percent of Residences with Basement, by
Census Region and U.S. EPA Region
Census Region
Northeast
Northeast
Midwest
Midwest
South
South
South
West
West
West
Source: Lucas et al,
U.S. EPA Regions
1
2
3
4
5
6
7
8
9
10
All Regions
1992.
% of Residences
with Basements
93.4
55.9
67.9
19.3
73.5
4.1
75.3
68.5
10.3
11.5
45.2
Exposure Factors Handbook
September 2011
Page
19-37
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-17. Percent of Residences with Basement, by Census Region
Census Region
Northeast
Northeast
Midwest
Midwest
South
South
South
West
West
Census Divisions
1 New England
2 Mid Atlantic
3 East North Central
4 West North Central
5 South Atlantic
6 East South Central
7 West South Central
8 Mountain
9 Pacific
All Divisions
% of Residences with Basements
83.2
69.1
68.7
65.3
27.0
23.7
2.8
29.9
10.9
40.6
Source: U.S. EPAAnalysis of U.S. DOE, 2008a.
Page
19-38
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-18. States Associated with U.S. EPA Regions and Census Regions
U.S. EPA Regions
Region 1
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
Region 2
New Jersey
New York
Region 3
Delaware
District of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
Northeast Region
Connecticut
Maine
Massachusetts
New Hampshire
New Jersey
New York
Pennsylvania
Rhode island
Vermont
Region 4
Alabama
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennessee
Region 5
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
U.S.
Midwest Region
Illinois
Indiana
Iowa
Kansas
Michigan
Minnesota
Missouri
Nebraska
North Dakota
Ohio
South Dakota
Wisconsin
Region 6
Arkansas
Louisiana
New Mexico
Oklahoma
Texas
Region 7
Iowa
Kansas
Missouri
Nebraska
Census Bureau Regions
South Region
Alabama
Arkansas
Delaware
District of Columbia
Florida
Georgia
Kentucky
Louisiana
Maryland
Mississippi
North Carolina
Oklahoma
South Carolina
Tennessee
Texas
Virginia
West Virginia
Region 8
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
Region 9
Arizona
California
Hawaii
Nevada
Region 10
Alaska
Idaho
Oregon
Washington
West Region
Alaska
Arizona
California
Colorado
Hawaii
Idaho
Montana
Nevada
New Mexico
Oregon
Utah
Washington
Wyoming
Source: U.S. DOE, 2008a.
Exposure Factors Handbook
September 2011
Page
19-39
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-19. Percent of Residences with Certain Foundation Types by
Census Region
Census
Region
With
Basement
Northeast 72.9
Midwest 67.7
South 19.1
West 17.0
All Regions 40.6
a
Source:
% of Residences8
With
Crawlspace
18.9
27.4
29.7
36.9
28.7
With
Concrete Slab
24.5
30.2
58.5
61.8
46.0
Percentage may add to more than 100 because more than one foundation
type may apply to a given residence.
U.S. EPA Analysis of U.S. DOE, 2008a.
Page
19-40
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-20. Average Estimated Volumes" of U.S. Commercial Buildings, by Primary
Activity
Primary
Building
Activity
Vacant
Office
Laboratory
Non-
refrigerated
warehouse
Food sales
Public order
and safety
Outpatient
healthcare
Refrigerated
warehouse
Religious
worship
Public
assembly
Education
Food
service
Inpatient
healthcare
Nursing
Lodging
Strip
shopping
mall
Enclosed
mall
Retail other
than mall
Service
Other
All
Buildings'3
Percentiles
N
134
976
43
473
125
85
144
20
311
279
649
242
217
73
260
349
46
355
370
64
5,215
Mean
4,789
5,036
24,681
9,298
1,889
5,253
3,537
19,716
3,443
4,839
8,694
1,889
82,034
15,522
11,559
7,891
287,978
3,310
2,213
5,236
5,575
SEof
Mean
581
397
1,114
992
106
482
251
3,377
186
394
513
112
5,541
559
1,257
610
14,780
218
182
984
256
10th
408
510
2,039
1,019
476
816
680
1,133
612
595
527
442
17,330
1,546
527
1,359
35,679
510
459
425
527
25th
612
714
5,437
1,812
680
1,019
1,019
1,699
917
1,019
867
680
25,485
5,097
1,376
2,277
35,679
680
629
544
816
a Volumes calculated from floor areas assuming a ceilinj
50*
1,257
1,359
10,534
2,945
951
1,699
2,039
3,398
2,039
2,277
2,379
1,189
36,019
10,534
4,078
4,078
113,268
1,631
934
1,427
1,699
75th
3,823
3,398
40,776
7,504
2,039
3,398
3,398
8,212
4,163
4,417
10,194
2,039
95,145
17,330
10,194
6,966
453,070
3,398
2,039
3,398
4,248
90th % of
y(J Total
11,213
8,155
61,164
16,990
3,398
8,495
6,966
38,511
8,325
7,136
23,786
3,568
203,881
38,737
27,184
19,709
849,505
6,116
4,587
9,175
10,194
3.7
17.0
0.2
12.0
4.6
1.5
2.5
0.3
7.6
5.7
7.9
6.1
0.2
0.4
2.5
4.3
0.1
9.1
12.8
1.4
100
I height of 12 feet for other structures
and 20 feet for warehouses.
b Wei{
^hted average calculated from floor areas assumin;
I a ceiling
height of
12 feet for all
buildings except warehouses and enclosed malls, which assumed 20-foot ceilings.
N = Number of observations.
SE = Standard error.
Source: U.S
EPA Analysis of U
S. DOE, 2008b.
Exposure Factors Handbook
September 2011
Page
19-41
-------
I
3
Table
19-21. Non-Residential
Buildings:
Hours per Week Open
and Number of Employees
Number of Hours/Week Open
Primary Building
Activity
Vacant
Office
Laboratory
Non-refrigerated warehouse
Food sales
Public order and safety
Outpatient healthcare
Refrigerated warehouse
Religious worship
Public assembly
Education
Food service
Inpatient healthcare
Nursing
Lodging
Retail other than mall
Service
Other
All Activities
N
134
976
43
473
125
85
144
20
311
279
649
242
217
73
260
355
370
64
4,820
%
2.8%
20.2%
0.9%
9.8%
2.6%
1.8%
3.0%
0.4%
6.5%
5.8%
13.5%
5.0%
4.5%
1.5%
5.4%
7.4%
7.7%
1.3%
100.0%
Mean
6.7
54.7
103.5
66.2
107.3
103.0
52.0
61.3
32.0
50.3
49.6
85.8
168.0
168.0
166.6
59.1
55.0
57.8
61.2
SEof
Mean
1.2
1.6
0.8
4.8
2.5
7.6
2.8
0.7
2.4
3.8
1.0
2.6
*
*
0.8
1.5
2.1
7.1
1.2
Perc entiles
10th 25th 50th 75th
0 000
40 45 54 65
50 58 98 168
20 40 55 80
60 80 109 127
10 40 168 168
40 45 54 70
44 53 102 126
5 13 40 60
12 40 63 96
38 42 54 70
40 66 84 105
168 168 168 168
168 168 168 168
168 168 168 168
42 50 62 80
40 40 50 68
12 40 51 90
30 45 60 98
90th Mean
40 0.35
168 34.2
168 105.6
168 7.0
168 6.3
168 19.1
168 21.5
168 18.2
79 4.6
125 8.7
85 32.4
130 10.5
168 471.0
168 44.8
168 12.3
105 7.8
105 5.9
168 12.3
168 15.7
Number of Employees During Main Shift
SEof
Mean
0.08
2.8
4.5
0.9
0.5
2.2
1.9
2.4
0.5
1.5
8.8
0.9
40.4
2.5
2.0
0.7
0.6
1.7
1.2
Percentiles
10th
0
4
20
0
1
1
5
4
1
0
3
2
175
15
1
2
1
1
1
25th 50th
0 0
11 57
55 156
1 8
2 4
4 15
8 40
8 38
1 3
2 5
14 38
4 8
315 785
25 50
3 10
3 6
2 4
2 10
3 14
75th
0
300
300
25
15
60
125
61
10
22
75
15
1,300
80
25
22
10
44
66
* All sampled inpatient healthcare and nursing buildings reported being open 24 hours a day, 7 days a week.
jV = Number of observations.
SE = Standard error.
Source: U.S. EPA Analysis of U
S. DOE,
2008b.
90th
0
886
435
64
50
200
200
165
19
80
133
33
2,250
170
80
72
35 f
150 j
300 5
h.
V
t
S
«•
*•
f
$
f
^
»
:
f*
P
N
z
f
*>
r
t
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings
Buildings
All
Buildings"
All Buildings"
Building Floorspace (ft )
1,001-5,000
5,001-10,000
10,001-25,000
25,001-50,000
50,001-100,000
100,001-200,000
200,001-500,000
Over 500,000
Principal Building Activity
Education
Food Sales
Food Service
Health Care
Lodging
Retail (Other Than Mall)
Office
Public Assembly
Public Order and Safety
Religious Worship
Service
Warehouse and Storage
Other
Vacant
Year Constructed
Before 1920
1920-1945
1946-1959
1960-1969
1970-1979
1980-1989
1990-1999
2000-2003
Census Region and
Division
Northeast
Midwest
South
West
Heating Equipment*
Heat Pumps
Furnaces
Individual Space Heaters
District Heat
Boilers
Packaged Heating Units
4,645
54.9%
19.1%
15.9%
5.2%
2.8%
1.4%
0.5%
0.2%
8.3%
4.9%
6.4%
2.8%
3.1%
9.5%
17.7%
6.0%
1.5%
8.0%
13.4%
12.9%
1.7%
3.9%
7.1%
11.3%
12.1%
12.5%
15.7%
15.2%
18.9%
7.2%
15.6%
27.3%
38.2%
18.9%
10.2%
40.1%
17.6%
1.4%
12.5%
20.5%
wim
Space
Heating Electricity
3,982
52.7%
19.6%
16.5%
5.7%
3.1%
1.6%
0.6%
0.2%
9.6%
4.7%
7.1%
3.1%
3.6%
10.2%
20.1%
6.5%
1.8%
9.0%
12.9%
7.9%
1.7%
1.7%
7.6%
11.1%
12.4%
13.2%
16.3%
15.5%
18.1%
5.9%
16.9%
27.9%
36.7%
18.5%
12.0%
46.8%
20.6%
1.6%
14.5%
23.9%
1,766
50.3%
19.8%
17.6%
6.5%
3.4%
1.6%
0.6%
0.2%
10.2%
5.5%
7.1%
3.5%
5.8%
9.6%
21.5%
4.7%
1.4%
8.6%
10.2%
8.5%
1.8%
1.5%
3.7%
8.0%
11.0%
12.0%
16.6%
19.9%
21.5%
7.1%
10.1%
20.2%
50.0%
19.7%
26.4%
31.4%
34.2%
0.3%
9.1%
32.4%
Space-Heating Energy Sources Usedb
Natural
Gas
2,165
46.8%
20.8%
18.9%
7.0%
3.9%
1.8%
0.7%
0.2%
8.6%
3.6%
7.9%
3.1%
2.6%
10.9%
21.5%
6.5%
1.4%
9.6%
12.3%
8.2%
1.9%
1.8%
8.5%
14.3%
12.9%
13.0%
16.6%
12.5%
17.2%
4.9%
16.0%
35.8%
29.1%
19.1%
5.7%
58.8%
18.4%
0.2%
18.3%
24.4%
Fuel
Oil
360
54.4%
23.9%
12.8%
3.1%
2.2%
2.5%
1.1%
0.3%
5.8%
Q
Q
Q
4.4%
9.7%
12.8%
10.3%
Q
10.0%
22.8%
7.8%
Q
Q
20.0%
13.3%
18.1%
13.6%
12.8%
10.0%
9.4%
Q
63.6%
16.4%
14.2%
6.1%
1.7%
52.2%
21.9%
Q
40.0%
4.7%
District
Heat
65
Q
Q
27.7%
13.8%
12.3%
13.8%
6.2%
3.1%
38.5%
N/R
Q
3.1%
Q
Q
24.6%
9.2%
Q
Q
Q
Q
Q
Q
Q
18.5%
20.0%
20.0%
9.2%
6.2%
12.3%
Q
26.2%
20.0%
30.8%
23.1%
3.1%
Q
6.2%
100.0%
Q
4.6%
Propane
372
65.3%
19.4%
10.2%
3.0%
Q
Q
Q
Q
9.7%
Q
8.3%
Q
Q
10.8%
9.7%
Q
Q
11.8%
20.2%
6.5%
Q
Q
Q
Q
11.0%
11.6%
12.9%
19.9%
19.4%
12.6%
6.5%
38.7%
36.6%
18.0%
7.5%
57.0%
32.8%
Q
8.1%
21.2%
Other0
113
63.7%
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
N/R
60.2%
Q
Q
Q
Q
Q
Q
Q
39.8%
Q
Q
Q
Q
31.9%
Q
Q
Q
57.5%
35.4%
N/R
15.9%
Q
Exposure Factors Handbook
September 2011
Page
19-43
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings (continued)
Other
a
b
c
Q
N/R
Source:
Buildings Space-Heating Energy Sources Usedb
with
All Space Natural Fuel District
Buildings3 Heating Electricity Gas Oil Heat Propane
4.4% 5.1% 6.6% 3.7% 10.0% Q 10.8%
Figures in this table do not include enclosed malls and strip malls.
More than one may apply.
"Other" includes wood, coal, solar, and all other energy sources.
= Data withheld because the Relative Standard Error (RSE) was >50%, or <20 buildings were sampled.
= No responding cases in sample.
U.S. DOE, 2008b.
Other0
41.6%
Page Exposure Factors Handbook
19-44 September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-23. Non-Residential Air Conditioning Energy Sources for Non-Mall Buildings
All Buildings3
Building Floorspace (ft2)
1,001-5,000
5,001-10,000
10,001-25,000
25,001-50,000
50,001-100,000
100,001-200,000
200,001-500,000
Over 500,000
Principal Building Activity
Education
Food Sales
Food Service
Health Care
Lodging
Retail (Other Than Mall)
Office
Public Assembly
Public Order and Safety
Religious Worship
Service
Warehouse and Storage
Other
Vacant
Year Constructed
Before 1920
1920-1945
1946-1959
1960-1969
1970-1979
1980-1989
1990-1999
2000-2003
Census Region and Division
Northeast
Midwest
South
West
Cooling Equipment1"
Central Air Conditioners
Heat Pumps
Individual Air Conditioners
District Chilled Water
Central Chillers
Packaged A/C Units
Swamp Coolers
Other
All
Buildings3
4,645
54.9%
19.1%
15.9%
5.2%
2.8%
1.4%
0.5%
0.2%
8.3%
4.9%
6.4%
2.8%
3.1%
9.5%
17.7%
6.0%
1.5%
8.0%
13.4%
12.9%
1.7%
3.9%
7.1%
11.3%
12.1%
12.5%
15.7%
15.2%
18.9%
7.2%
15.6%
27.3%
38.2%
18.9%
21.7%
10.6%
16.0%
0.7%
2.4%
34.7%
2.6%
0.9%
Buildings
with
Cooling
3,625
50.8%
20.2%
17.4%
6.0%
3.3%
1.7%
0.6%
0.2%
9.7%
5.8%
7.8%
3.6%
3.6%
11.2%
21.8%
5.9%
1.7%
8.5%
10.2%
7.3%
1.6%
1.4%
6.4%
10.5%
11.9%
12.9%
16.8%
15.9%
19.2%
6.5%
14.3%
26.4%
40.8%
18.5%
27.8%
13.6%
20.5%
0.9%
3.1%
44.5%
3.4%
1.1%
a Figures in this table do not include enclosed malls and
b More than one may
apply.
Cooling Energy Sources'5
Electricity
3,589
51.2%
20.3%
17.2%
5.9%
3.2%
1.5%
0.6%
0.1%
9.4%
5.8%
7.9%
3.6%
3.6%
11.3%
21.8%
5.9%
1.7%
8.6%
10.3%
7.3%
1.6%
1.4%
6.4%
10.6%
11.9%
12.8%
16.9%
15.9%
19.1%
6.5%
14.3%
26.5%
40.9%
18.4%
28.0%
13.7%
20.7%
0.3%
3.0%
44.9%
3.4%
0.8%
strip malls.
Natural
District
Gas Chilled Water
17
Q
Q
Q
Q
Q
Q
Q
Q
Q
N/R
Q
0.0%
Q
Q
Q
Q
Q
Q
Q
Q
Q
N/R
Q
Q
Q
Q
Q
Q
Q
Q
41.2%
Q
Q
Q
Q
47.1%
Q
Q
29.4%
23.5%
Q
Q
Q = Data withheld because the Relative Standard Error (RSE) was >50%, or <20 building
sampled.
33
Q
Q
Q
18.2%
15.2%
18.2%
6.1%
3.0%
42.4%
N/R
Q
3.0%
Q
Q
27.3%
9.1%
Q
Q
N/R
Q
Q
Q
Q
Q
12.1%
12.1%
15.2%
15.2%
24.2%
Q
18.2%
12.1%
42.4%
27.3%
Q
3.0%
6.1%
100.0%
Q
12.1%
Q
Q
'S were
N/R = No responding cases in sample.
Source: U.S. DOE, 2008b.
Exposure Factors Handbook
September 2011
Page
19-45
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-24. Summary
Arithmetic Mean
Arithmetic Standard Deviation
Geometric Mean
Geometric Standard Deviation
10thPercentile
50thPercentile
90thPercentile
Maximum
Statistics for Residential Air Exchange Rates (in ACH),a by Region
West
Region
0.66
0.87
0.47
2.11
0.20
0.43
1.25
23.32
Midwest
Region
0.57
0.63
0.39
2.36
0.16
0.35
1.49
4.52
Northeast
Region
0.71
0.60
0.54
2.14
0.23
0.49
1.33
5.49
South
Region
0.61
0.51
0.46
2.28
0.16
0.49
1.21
3.44
All
Regions
0.63
0.65
0.46
2.25
0.18
0.45
1.26
23.32
aACH = Air changes per hour.
Source: Koontz and Rector, 1995.
Page
19-46
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-25. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database
Project Code
ADM
BSG
GSS
FLEMING
GEOMET1
GEOMET2
GEOMET3
LAMBERT1
LAMBERT2
LAMBERT3
LAMBERT4
LBL1
LBL2
LBL3
LBL4
LBL5
LBL6
NAHB
NYSDH
PEI
PIERCE
RTI1
RTI2
RTD
SOCAL1
SOCAL2
SOCAL3
UMINN
UWISC
State
CA
CA
AZ
NY
FL 1
MD
TX
ID
MT
OR
WA
OR
WA
ID
WA
WA
ID
MN
NY
MD
CT
CA
CA
NY
CA
CA
CA
MN
WI
, , ., , ,„ Number of
Month(s)a
Measurements
5-7
1, 8-12
1-3, 8-9
1-6, 8-12
,6-8, 10-12
1-6
1-3
2-3, 10-11
1-3, 11
1-3, 10-12
1-3, 10-12
1-4, 10-12
1-4, 10-12
1-5, 11-12
1-4, 11-12
2-4
3-4
1-5, 9-12
1-2, 4, 12
3-4
1-3
2
7
1-4
3
7
1
1-4
2-5
29
40
25
56
18
23
42
36
51
83
114
126
71
23
29
21
19
28
74
140
25
45
41
397
551
408
330
35
57
Mean Air
Exchange Rate SDb
(ACH)
0.70
0.53
0.39
0.24
0.31
0.59
0.87
0.25
0.23
0.46
0.30
0.56
0.36
1.03
0.39
0.36
0.28
0.22
0.59
0.59
0.80
0.90
2.77
0.55
0.81
1.51
0.76
0.36
0.82
0.52
0.30
0.21
0.28
0.16
0.34
0.59
0.13
0.15
0.40
0.15
0.37
0.19
0.47
0.27
0.21
0.14
0.11
0.37
0.45
1.14
0.73
2 12
0.37
0.66
1.48
1.76
0.32
0.76
Percentiles
10th
0.29
0.21
0.16
0.05
0.15
0.12
0.33
0.10
0.10
0.19
0.14
0.28
0.18
0.37
0.14
0.13
0.11
0.11
0.28
0.15
0.20
0.38
0.79
0.26
0.29
0.35
0.26
0.17
0.22
25th
0.36
0.30
0.23
0.12
0.18
0.29
0.51
0.17
0.14
0.26
0.20
0.35
0.25
0.73
0.18
0.19
0.17
0.16
0.37
0.26
0.22
0.48
1.18
0.33
0.44
0.59
0.37
0.20
0.33
50th
0.48
0.40
0.33
0.22
0.25
0.65
0.71
0.23
0.19
0.38
0.30
0.45
0.32
0.99
0.36
0.30
0.26
0.20
0.50
0.49
0.38
0.78
2.31
0.44
0.66
1.08
0.48
0.28
0.55
75th
0.81
0.70
0.49
0.29
0.48
0.83
1.09
0.33
0.26
0.56
0.39
0.60
0.42
1.34
0.47
0.47
0.38
0.24
0.68
0.83
0.77
1.08
3.59
0.63
0.94
1.90
0.75
0.40
1.04
90th
1.75
0.90
0.77
0.37
0.60
0.92
1.58
0.49
0.38
0.80
0.50
1.02
0.52
1.76
0.63
0.62
0.55
0.38
1.07
1.20
2.35
1.52
5.89
0.94
1.43
3.11
1.11
0.56
1.87
a 1 = January, 2 = February, etc.
b SD = Standard deviation.
Source: Adapted from Versar, 1990.
Exposure Factors Handbook
September 2011
Page
19-47
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-26. Distributions of Residential Air Exchange Rates (in ACH)a by Climate Region and Season
Arithmetic Standard Percentiles
Mean
Climate
Regionb
Season Sample Size
Deviation
10'
,th
25th
50th
75th
90'
,th
Coldest
Winter
Spring
Summer
Fall
161
254
5
47
0.36
0.44
0.82
0.25
0.28
0.31
0.69
0.12
0.11
0.18
0.27
0.10
0.18
0.24
0.41
0.15
0.27
0.36
0.57
0.22
0.48
0.53
1.08
0.34
0.71
0.80
2.01
0.42
Colder
Winter
Spring
Summer
Fall
428
43
2
23
0.57
0.52
1.31
0.35
0.43
0.91
0.18
0.21
0.13
0.15
0.30
0.21
0.22
0.42
0.24
0.33
0.69
0.39
0.41
1.18
0.83
0.59
Warmer
Winter
Spring
Summer
Fall
96
165
34
37
0.47
0.59
0.68
0.51
0.40
0.43
0.50
0.25
0.19
0.18
0.27
0.30
0.26
0.28
0.36
0.30
0.39
0.48
0.51
0.44
0.58
0.82
0.83
0.60
0.78
1.11
1.30
0.82
Warmest
Winter
Spring
Summer
Fall
454
589
488
18
0.63
0.77
1.57
0.72
0.52
0.62
1.56
1.43
0.24
0.28
0.33
0.22
0.34
0.42
0.58
0.25
0.48
0.63
1.10
0.42
0.78
0.92
1.98
0.46
1.13
1.42
3.28
0.74
a ACH = air changes per hour.
b The coldest region was defined as having 7,000 or more heating degree days, the colder region as 5,500-6,999 degree
days, the warmer region as 2,500-5,499 degree days, and the warmest region as fewer than 2,500 degree days.
Few observations for summer results in colder regions. Data not available.
Source: Murray and Burmaster, 1995.
Table 19-27. Air Exchange
N
Building Type
Educational 7
Office (<100,000 ft2) 8
Office (>100,000 ft2) 14
Libraries 3
Multi-use 5
Naturally ventilated 3
Total (all commercial) 40
a ACH = air changes per hour.
Rates in Commercial Buildings by
.fnuax SD 10thPercentile
(AUH )
1.9
1.5
1.8
0.6
1.4
0.8
1.5 0.87 0.60b
Building Type
Range
(ACH)
0.8 to 3.0
0.3 to 4.1
0.7 to 3.6
0.3 to 1.0
0.6 to 1.9
0.6 to 0.9
0.3 to 4.1
b Calculated from data presented in Turk et al. (1987), Table I V.C.I.
jV = Number of observations.
SD = Standard deviation.
Source: Turketal, 1987.
Page
19-48
Exposure Factors Handbook
September 2011
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-28. Statistics of Estimated Normalized Leakage Distribution Weighted for all Dwellings in the
United States
5th
Low income 0.30
Conventional 0.17
Whole U.S. 0.17
Estimated normalized leakage percentiles Estimated
10th
0.39
0.21
0.22
25th 50th 75th 90th 95th GM
0.62 0.98 1.5 2.2 2.7 0.92
0.31 0.48 0.75 1.1 1.4 0.49
0.33 0.52 0.84 1.3 1.7 0.54
GSD
1.9
1.9
2.0
GM = Geometric mean.
GSD = Geometric standard deviation.
Source: Chan etal., 2005.
Table 19-29. Particle
Particle Size Range
1-5
5-10
10-25
>25
Deposition During Normal Activities
Particle Removal Rate
(hour"1)
0.5
1.4
2.4
4.1
Source: Adapted from Thatcher and Layton, 1995.
Table
Size Fraction
PM25
PM10
Coarse
19-30. Deposition Rates for Indoor Particles
Deposition Rate (hour1)
0.39
0.65
1.0
Source: Adapted from Wallace, 1996.
Exposure Factors Handbook Page
September 2011 19-49
-------
Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-31. Measured Deposition Loss Rate Coefficients (hour
Fans off
Median particle
diameter (^m)
0.55
0.65
0.81
1.00
1.24
1.54
1.91
2.37
2.94
3.65
4.53
5.62
6.98
8.66
Bare room
surfaces
1.10
0.10
0.10
0.13
0.20
0.32
0.49
0.78
1.24
1.81
2.83
4.41
5.33
6.79
1
II
0.12
0.12
0.11
0.12
0.18
0.28
0.44
0.70
1.02
1.37
2.13
2.92
3.97
4.92
1
0.20
0.20
0.19
0.21
0.29
0.42
0.61
0.93
1.30
1.93
2.64
3.43
4.12
5.45
Room core airspeed
5.4 cm/second
Bare room
surfaces
0.10
0.10
0.10
0.12
0.18
0.27
0.42
0.64
0.92
1.28
1.95
3.01
4.29
6.72
1
II
0.13
0.13
0.15
0.20
0.28
0.39
0.58
0.84
1.17
1.58
2.41
3.17
4.06
5.55
1
0.23
0.23
0.24
0.28
0.38
0.54
0.75
1.07
1.46
1.93
2.95
3.51
4.47
5.77
Room core
airspeed
Bare room
surfaces
0.09
0.10
0.11
0.15
0.25
0.39
0.61
0.92
1.45
2.54
3.79
4.88
6.48
8.84
ll
0.18
0.19
0.19
0.23
0.34
0.51
0.78
1.17
1.78
2.64
4.11
5.19
6.73
8.83
Fully
furnished
0.23
0.24
0.27
0.33
0.47
0.67
0.93
1.32
1.93
3.39
4.71
5.73
7.78
10.5
-1)
Room core airspeed
19.1 cm/second
Bare room
surfaces
0.14
0.14
0.15
0.20
0.33
0.51
0.80
1.27
2.12
3.28
4.55
6.65
10.6
12.6
Carpeted
room
0.16
0.17
0.19
0.25
0.38
0.59
0.89
1.45
2.27
3.13
4.60
5.79
8.33
11.6
•8
ti
0.27
0.28
0.30
0.38
0.53
0.77
1.11
1.60
2.89
3.88
5.46
6.59
8.89
11.6
Source: Thatcher et al. , 2002 .
Household
1
2
3
4
5
6
7
8
9
Table 19-32. Total Dust
Total Dust Load
(g/m2)
10.8
4.2
0.3
2.2; 0.8
1.4; 4.3
0.8
6.6
33.7
812.7
Loading for Carpeted Areas
Fine Dust (<150 \am) Load (g/m2)
6.6
3.0
0.1
1.2; 0.3
1.0; 1.1
0.3
4.7
23.3
168.9
Source: Adapted from Roberts etal, 1991.
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-33. Particle
Particle Size Range (um)
0.3-0.5
0.6-1
1-5
5-10
10-25
>25
Source: Adapted from Thatcher and Layton,
Deposition and Resuspension During
Particle Deposition Rate (hour"1)
1995.
(not measured)
(not measured)
0.5
1.4
2.4
4.1
Normal Activities
Particle Resuspension Rate (hour"1)
9.9 x 10~7
4.4 x 10~7
1.8 x 1Q-5
8.3 x 1Q-5
3.8 x 10"4
3.4 x 1Q-5
Table 19-34. Dust Mass Loading after 1
Location in Test House
Tracked area of downstairs carpet
Untracked area of downstairs carpet
Tracked area of linoleum
Untracked area of linoleum
Tracked area of upstairs carpet
Untracked area of upstairs carpet
Front doormat
Week without Vacuum Cleaning
Dust Loading
2.20
0.58
0.08
0.06
1.08
0.60
43.34
(g/m2)
Source: Adapted from Thatcher and Layton, 1995.
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Table 19-35. Simplified Source Descriptions for Airborne Contaminants
Description
Direct emission rate
Combustion emission rate
Volume emission rate
Mass emission rate
Diffusion limited emission rate
Exponential emission rate
Transport
Infiltration
Interzonal
Soil gas
EfHf\
Ef =
Hf =
Mf =
QpCp
Ql =
cp =
e =
Mpwe
Mp =
we =
e =
(DfS-
Df =
s-l =
cs =
d =
A, =
Components
4f
emission factor
fuel content
fuel consumption rate
e
volume delivery rate
concentration in carrier
transfer efficiency
e
mass delivery rate
weight fraction
transfer efficiency
XC,-C,>4,
diffusivity
boundary layer thickness
vapor pressure of surface
room concentration
area
AtE0€-kt
At =
E0 =
k =
t
QiiC\
Qn =
c, =
area
initial unit emission rate
emission decay factor
time
air flow from zone/
air concentration in zone/
Dimensions
g hour"1
g-T1
Jmol"1
mol hour"1
g hour"1
rr^hour"1
g m"3
gg-1
g hour"1
g hour"1
gg"1
& &
gg-1
g hour"1
n^hour"1
meters
gm"3
gm"3
2
m
g hour"1
m2
g hour"1 m"2
hour"1
hours
g hour"1
rr^hour"1
gm"3
Page
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Exposure Factors Handbook
Chapter 19—Building Characteristics
Air In
Water In
Soil In
Concentration, C |
Source
| Resuspension
1 ,9ecay
Exposure, E for Occupant(s)
Removal
Reversible
Sinks
Out
Figure 19-1. Elements of Residential Exposure.
ilC'N RETURN -A'-
"t-
'v.AMCEL SLPF1Y 3nd RETURN LAYOUT
Gijp^y
Figure 19-2. Configuration for Residential Forced-Air Systems.
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Exposure Factors Handbook
Chapter 19—Building Characteristics
001 01 1
Particle Diameter (|jm)
Figure 19-3. Idealized Patterns of Particle Deposition Indoors.
Source: Adapted from Nazaroff and Cass, 1989a.
10
Page
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Chapter 19—Building Characteristics
SSGLE IC«
m«.> ZONE
H-Kti-ZOM;
•J-7nrn Rystrn
Figure 19-4. Air Flows for Multiple-Zone Systems.
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GLOSSARY OF TERMS
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Exposure Factors Handbook
Glossary
Absorbed dose—The amount of an agent that enters
a target by crossing an exposure surface that acts as
an absorption barrier. See also Absorption barrier,
Dose, and Internal dose.
Absorption barrier—Any exposure surface that
may retard the rate of penetration of an agent into a
target. Examples include the skin, respiratory tract
lining, and gastrointestinal tract wall.
Activity pattern data—Information on human
activities used in exposure assessments. These may
include a description of the activity, frequency of
activity, duration spent performing the activity, and
the microenvironment in which the activity occurs.
Acute exposure—A single exposure to a toxic
substance which may result in severe biological harm
or death. Acute exposures are usually characterized
as lasting no longer than a day, as compared to
longer, continuing exposure over a period of time.
Adherence factor—The amount of a material (e.g.,
soil) that adheres to the skin per unit of surface area.
Activity pattern (time use) data—Information on
activities in which various individuals engage, length
of time spent performing various activities, locations
in which individuals spend time and length of time
spent by individuals within those various
environments.
Age dependent adjustment factor (ADAF)—In
cases where age-related differences in toxicity occur,
differences in both toxicity and exposure need to be
integrated across all relevant age intervals, by the use
of age dependent potency adjustment factors
(ADAFs). This is a departure from the way cancer
risks have historically been calculated based upon the
premise that risk is proportional to the daily average
of the long-term adult dose.
Agent—Refers to a chemical, biological, or physical
entity that contacts a target.
Aggregate exposure—The combined exposure of an
individual (or defined population) to a specific agent
or stressor via relevant routes, pathways, and sources.
Total exposure can include exposure through
multiple routes (e.g., dermal, inhalation, and
ingestion).
Agricultural commodity—Used by U.S. EPA to
mean plant (or animal) parts consumed by humans as
food. When such items are raw or unprocessed, they
are referred to as "raw agricultural commodities."
Air exchange rate—Rate of air leakage through
windows, doorways, intakes and exhausts, and
"adventitious openings" (i.e., cracks and seams) that
combine to form the leakage configuration of the
building envelope plus natural and mechanical
ventilation.
All water sources—Includes water from all supply
sources such as community water supply (i.e., tap
water), bottled water, etc.
Analytical uncertainty propagation—Examining
how uncertainty in individual parameters affects the
overall uncertainty of the exposure assessment.
Anthropometric—The study of human body
measurements for use in anthropological
classification and comparison.
As-consumed intake—Intake rate based on the
weight of the food in the form that it is consumed
(e.g., cooked or prepared).
Assessment—A determination or appraisal of
possible consequences resulting from an analysis of
data.
Average Daily Dose (ADD)—The mean amount of
an agent to which a person is exposed on a daily
basis, often averaged over a long period of time. U.S.
EPA is transitioning from average daily dose
methodologies to more refined aggregate and
cumulative approaches for estimating exposure
across each lifestage. See also Lifetime average daily
dose (LADD) and Time-averaged exposure.
Bayesian Analysis—Bayesian analysis is a method
of statistical inference in which the knowledge of
prior events is used to predict future events. Bayes'
Theorem is a means of quantifying uncertainty.
Benchmark Dose or Concentration—An exposure
due to a dose or concentration of a substance
associated with a specified low incidence of risk,
generally in the range of 1% to 10%, of a health
effect; or the dose or concentration associated with a
specified measure or change of a biological effect.
Best Tracer Method (BTM)—Method for
estimating soil ingestion that allows for the selection
of the most recoverable tracer for a particular subject
or group of subjects. Selection of the best tracer is
made on the basis of the food/soil (F/S) ratio.
Bioaccumulate—The increase in concentration in
living organisms as they take in contaminated air,
water, or food because the substances are very slowly
metabolized or excreted.
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Glossary
Bias—A systematic error inherent in a method or
caused by some feature of the measurement system.
Unavailability—The rate and extent to which an
agent can be absorbed by an organism and is
available for metabolism or interaction with
biologically significant receptors. Bioavailability
involves both release from a medium (if present) and
absorption by an organism.
Bioconcentrate—The accumulation of a chemical in
tissues of a fish or other organism to levels greater
than in the surrounding medium.
Biokinetic model comparison—A methodology that
compares direct measurements of a biomarker such
as blood or urine levels of a toxicant with predictions
from a biokinetic model.
Biological marker or biomarker—An indicator of
changes or events in biological systems. Biological
markers of exposure are cellular, biochemical,
analytical, or molecular measures that are obtained
from biological media such as tissues, cells, or fluids
and are indicative of exposure to an agent.
Biomarkers of effect are quantifiable changes,
indicating exposure to a compound, while biomarkers
of susceptibility are characteristics that make an
individual susceptible to the effects of an exposure.
Biomarker model comparison—A methodology
that compares results from a biokinetic exposure
model to biomarker measurements children blood.
The method is used to confirm assumptions about
ingested soil and dust quantities in this handbook.
Basal Metabolic Rate (BMR)—Minimum level of
energy required to maintain normal body functions.
Body Mass Index (BMI)—The ratio of weight and
height squared.
Bootstrap—A statistical method of resampling data
use to estimate variance and bias of an estimator and
provide confidence intervals for parameters.
Bounding estimate—An estimate of exposure, dose,
or risk that is higher or lower than that incurred by
the person with the highest or lowest exposure, dose,
or risk in the population being assessed. Bounding
estimates are useful in developing statements that
exposures, doses, or risks are "not greater than" or
"less than" the estimated value, because assumptions
are used which define the likely bounding conditions.
Central tendency exposure—A measure of the
middle or the center of an exposure distribution. The
mean is the most commonly used measure of central
tendency.
Chronic exposure—Repeated exposure by the oral,
dermal, or inhalation route for more than
approximately 10% of the life span in humans (more
than approximately 90 days to 2 years in typically
used laboratory animal species).
Chronic intake—The long term period over which a
substance crosses the outer boundary of an organism
without passing an absorption barrier.
Classical statistical methods—Estimating the
population exposure distribution directly, based on
measured values from a representative sample.
Coating—Method used to measure skin surface area,
in which either the whole body or specific body
regions are coated with a substance of known density
and thickness.
Community water—Includes tap water ingested
from community or municipal water supply.
Comparability—The ability to describe likenesses
and differences in the quality and relevance of two or
more data sets.
Concentration—Amount of a material or agent
dissolved or contained in unit quantity in a given
medium or system.
Confidence intervals—An estimated range of values
with a given probability of including the population
parameter of interest. The range of values is usually
based on the results of a sample that estimated the
mean and the sampling error or standard error.
Consumer-only intake rate—The average quantity
of food consumed per person in a population
composed only of individuals who ate the food item
of interest during a specified period.
Contact boundary—The surface on a target where
an agent is present. Examples of outer exposure
surfaces include the exterior of an eyeball, the skin
surface, and a conceptual surface over the nose and
open mouth. Examples of inner exposure surfaces
include the gastrointestinal tract, the respiratory tract,
and the urinary tract lining. As an exposure surface
gets smaller, the limit is an exposure point. It is also
referred to as an exposure surface.
Contaminant concentration—Contaminant
concentration is the concentration of the contaminant
in the medium (air, food, soil, etc.) contacting the
body and has units of mass/volume or mass/mass.
Creel study—A study in which fishermen are
interviewed while fishing.
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Glossary
Cumulative exposure—Exposure via mixtures of
contaminants both indoors and outdoors. Exposure
may also occur through more than one pathway. New
directions in risk assessments in U.S. EPA put more
emphasis on total exposures via multiple pathways.
Deposition—The removal of airborne substances to
available surfaces that occurs as a result of
gravitational settling and diffusion, as well as
electrophoresis and thermophoresis.
Dermal absorption—A route of exposure by which
substances can enter the body through the skin.
Dermal adherence—The loading of a substance
onto the outer surface of the skin.
Diary study—Survey in which individuals are asked
to record food intake, activities, or other factors in a
diary which is later used to evaluate exposure factors
associated with specific populations.
Direct water ingestion—Consumption of plain
water as a beverage. It does not include water used
for preparing beverages such as coffee or tea.
Distribution—A set of values derived from a
specific population or set of measurements that
represents the range and array of data for the factor
being studied.
Doers—Survey respondents who report participating
in a specified activity.
Dose—The amount of an agent that enters a target
after crossing an exposure surface. If the exposure
surface is an absorption barrier, the dose is an
absorbed dose. If the exposure surface is not an
absorption barrier, the dose is an intake dose.
Dose rate—Dose per unit time.
Dose-response assessment—Analysis of the
relationship between the total amount of an agent
administered to, taken up by, or absorbed by an
organism, system, or target population and the
changes developed in that organism, system, or target
population in reaction to that agent, and inferences
derived from such an analysis with respect to the
entire population. Dose-response assessment is the
second of four steps in risk assessment.
Dose-response curve—Graphical presentation of a
dose-response relationship.
Dose-response relationship—The resulting
biological responses in an organ or organism
expressed as a function of a series of doses.
Dressed weight—The portion of the harvest brought
into kitchens for use, including bones for particular
species.
Drinking water— All fluids consumed by
individuals to satisfy body needs for internal water.
Dry-weight intake rates—Intake rates that are based
on the weight of the food consumed after the
moisture content has been removed.
Dust Ingestion—Consumption of dust that results
from various behaviors including, but not limited to,
mouthing objects or hands, eating dropped food,
consuming dust directly, or inhaling dust that passes
from the respiratory system into the gastrointestinal
tract.
Effect—Change in the state or dynamics of an
organism, system, or (sub) population caused by
exposure to an agent.
Employer tenure—The length of time a worker has
been with the same employer.
Energy expenditures—The amount of
expended by an individual during activities.
energy
Exclusively breast fed—Infants whose sole source
of milk comes from human milk with no other milk
substitutes.
Exposed foods—Foods grown above ground.
Exposure—Contact between an agent and a target.
Exposure assessment—The process of estimating or
measuring the magnitude, frequency, and duration of
exposure to an agent, along with the number and
characteristics of the population exposed.
Exposure concentration—The concentration of a
chemical in its transport or carrier medium at the
point of contact.
Exposure duration—Length of time over which
contact with the contaminant lasts.
Exposure event—The occurrence of continuous
contact between an agent and a target.
Exposure factor—Factors related to human behavior
and characteristics that help determine an individual's
exposure to an agent.
Exposure frequency—The number of exposure
events in an exposure duration.
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Glossary
Exposure loading—The exposure mass divided by
the exposure surface area. For example, a dermal
exposure measurement based on a skin wipe sample,
expressed as a mass of residue per skin surface area,
is an exposure loading.
Exposure pathway—The physical course a chemical
takes from the source to the organism exposed.
Exposure route—The way a chemical pollutant
enters an organism after contact, e.g., by ingestion,
inhalation, or dermal absorption.
Exposure scenario—A set of facts, assumptions, and
interferences about how exposure takes place that
aids the exposure assessor in evaluating estimating,
or quantifying exposures.
Exposure surface—See contact boundary.
Fate—Pattern of distribution of an agent, its
derivatives, or metabolites in an organism, system,
compartment, or population of concern as a result of
transport, partitioning, transformation, or
degradation.
Foremilk—Milk produced at the beginning of
breastfeeding.
General population—The total of individuals
inhabiting an area or making up a whole group.
Geographic information system (GIS)—GIS is a
system of hardware and software that captures,
stores, analyzes, manages, and presents geographic
data.
Geometric mean—The n* root of the product of n
values.
Geophagy—A form of soil ingestion involving the
intentional ingestion of earths, usually associated
with cultural practices.
Hazard—Inherent property of an agent or situation
having the potential to cause adverse effects when an
organism, system, or population is exposed to that
agent.
Hazard assessment—A process designed to
determine the possible adverse effects of an agent or
situation to which an organism, system, or target
population could be exposed. The process typically
includes hazard identification, dose-response
evaluation and hazard characterization. The process
focuses on the hazard, in contrast to risk assessment,
where exposure assessment is a distinct additional
step.
High-end exposure—An estimate of individual
exposure or dose for those persons at the upper end
of an exposure or dose distribution, conceptually
above the 90th percentile, but not higher than the
individual in the population who has the highest
exposure or dose. See also Bounding estimate.
Hindmilk—Milk produced at the end of the
breastfeeding.
Home-produced foods—Fruits and vegetables
produced by home gardeners, meat and dairy
products derived form consumer-raised livestock,
game meat, and home caught fish.
Human Equivalent Concentration or Dose—The
human concentration (for inhalation exposure) or
dose (for other routes of exposure) of an agent that is
believed to induce the same magnitude of toxic effect
as the experimental animal species concentration or
dose. This adjustment may incorporate toxicokinetic
information on the particular agent, if available, or
use a default procedure, such as assuming that daily
oral doses experienced for a lifetime are proportional
to body weight raised to the 0.75 power.
Indirect water ingestion—Includes water added
during food preparation, but not water intrinsic to
purchased foods. Indirect water includes for example,
water used to prepare baby formulas, cake mix, and
concentrated orange juice.
Indoor settled dust—Particles in building interiors
that have settled onto objects, surfaces, floors, and
carpeting. These particles may include soil particles
that have been tracked into the indoor environment
from outdoors.
Infiltration—Air leakage through random cracks,
interstices, and other unintentional openings in the
building envelope.
Inhalation dosimetry—Process
estimating inhaled dose.
of measuring or
Inhalation unit risk—The upper-bound excess
lifetime cancer risk estimated to result from
continuous exposure to an agent at a concentration of
1 ug/m3 in air for a lifetime.
Inhaled dose—The amount of an inhaled substance
that is available for interaction with metabolic
processes or biologically significant receptors after
crossing the outer boundary of an organism.
Insensible water loss—Evaporative water losses that
occur during breastfeeding. Corrections are made to
account for insensible water loss when estimating
breast milk intake using the test weighing method.
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Glossary
Intake—The process by which a substance crosses
the outer boundary of an organism without passing an
absorption barrier (e.g., through ingestion or
inhalation).
Intake dose—The amount of an agent that enters a
target by crossing an exposure surface that does not
act as an absorption barrier. See also Absorption
barrier and Dose.
Intake rate—Rate of inhalation, ingestion, and
dermal contact depending on the route of exposure.
For ingestion, the intake rate is simply the amount of
food containing the contaminant of interest that an
individual ingests during some specific time period
(units of mass/time). For inhalation, the intake rate is
the rate at which contaminated air is inhaled. Factors
that affect dermal exposure are the amount of
material that comes into contact with the skin, and
the rate at which the contaminant is absorbed.
Inter-individual variability—Variations between
individuals in terms of human characteristics such as
age or body weight, or behaviors such as location,
activity patterns, and ingestion rates.
Internal dose—The amount of an agent that enters a
target by crossing an exposure surface that acts as an
absorption barrier. Synonymous with absorbed dose.
See also Absorption barrier and Dose.
Interzonal air flows—Transport of air through
doorways, ductwork, and service chaseways that
interconnect rooms or zones within a building.
Intra-individual variability—Fluctuations in an
individual's physiologic (e.g., body weight), or
behavioral characteristics (e.g., ingestion rates or
activity patterns).
Key study—A study that is the most up-to-date and
scientifically sound for deriving recommendations for
exposure factors. Alternatively, studies may be
classified as "relevant" and not "key" for one or more
of the following: (1) they provide supporting data
(e.g., older studies on food intake that may be useful
for trend analysis); (2) they provide information
related to the factor of interest (e.g., data on
prevalence of breast feeding); or (3) the study design
or approach makes the data less applicable for
exposure assessment purposes (e.g., studies with
small sample size, studies not conducted in the
United States). As new data or analyses are
published, "key" studies may be moved to the
"relevant" category because they are replaced by
more up-to-date data or an analysis of improved
quality.
Lead isotope ratio methodology—A method that
measures different lead isotopes in children's blood
and/or urine, food, water, and house dust and
compares the ratio of these isotopes to infer sources
of lead exposure that may include dust or other
environmental exposures.
Life expectancy—The length of an individual's life.
Lifestage—A distinguishable time frame in an
individual's life characterized by unique and
relatively stable behavioral and/or physiological
characteristics that are associated with development
and growth.
Lifetime Average Daily Dose (LADD)—Dose rate
averaged over a lifetime. The LADD is used for
compounds with carcinogenic or chronic effects. The
LADD is usually expressed in terms of mg/kg-day or
other mass/mass-time units. Often used in carcinogen
risk assessments that employ linear low-dose
extrapolation methods. See also Average daily dose
and Time-averaged exposure.
Limiting Tracer Method (LTM)—Method for
evaluating soil ingestion that assumes that the
maximum amount of soil ingested corresponds with
the lowest estimate from various tracer elements.
Local circulation—Convective and adjective air
circulation and mixing within a room or within a
zone.
Long-term exposure—Repeated exposure for more
than 30 days, up to approximately 10% of the life
span in humans (more than 30 days).
Lowest-Observed-Adverse-Effect Level
(LOAEL)—The lowest exposure level at which there
are biologically significant increases in frequency or
severity of adverse effects between the exposed
population and its appropriate control group.
Margin of safety—For some experts, margin of
safety has the same meaning as margin of exposure,
while for others, margin of safety means the margin
between the reference dose and the actual exposure.
Mass-balance/tracer techniques—Method for
evaluating soil intake that accounts for both inputs
and outputs of tracer elements. Tracers in soil, food,
medicine and other ingested items as well as in feces
and urine are accounted for.
Mean value—Simple or arithmetic average of a
range of values, computed by dividing the total of all
values by the number of values.
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Glossary
Measurement error—A systematic error arising
from inaccurate measurement (or classification) of
subjects on the study variables.
Measurement end-point—Measurable (ecological)
characteristic that is related to the valued
characteristic chosen as an assessment point.
Mechanical ventilation—Controlled air movement
driven by fans. Also referred to as forced ventilation.
Median value—The value in a measurement data set
such that half the measured values are greater and
half are less.
Metabolic Equivalent of Work (MET)—A
dimensionless energy expenditure metric used to
represent an activity level.
Microenvironment—Surroundings that can be
treated as homogeneous or well characterized in the
concentrations of an agent (e.g., home, office,
automobile, kitchen, store).
Mode of action—Defined as a sequence of key
events and processes, starting with interaction of an
agent with a cell, proceeding through operational and
anatomical changes, and resulting in cancer
formation.
Model uncertainty—Uncertainty regarding gaps in
scientific theory required to make predictions on the
basis of causal inferences.
Moisture content—The portion of foods made up by
water. The percent water is needed for converting
food intake rates and residue concentrations between
whole-weight and dry-weight values.
Monte Carlo technique—A repeated random
sampling from the distribution of values for each of
the parameters in a generic (exposure or dose)
equation to derive an estimate of the distribution of
(exposures or doses in) the population.
Mouthing behavior—Activities in which objects,
including fingers, are touched by the mouth or put
into the mouth except for eating and drinking, and
includes licking, sucking, chewing, and biting.
Natural ventilation—Airflow through open
windows, doors, and other designed openings in the
building envelope.
Non-dietary ingestion— Ingestion of non-food
substances, typically resulting from the mouthing of
hands and objects.
No-Observed-Adverse-Effect-Level (NOAEL)—
The highest exposure level at which there are no
biologically significant increases in the frequency or
severity of adverse effect between the exposed
population and its appropriate control; some effects
may be produced at this level, but they are not
considered adverse or precursors of adverse effects.
Occupational mobility—An indicator of the
frequency at which workers change from one
occupation to another.
Occupational tenure—The cumulative number of
years a person worked in his or her current
occupation, regardless of number of employers,
interruptions in employment, or time spent in other
occupations.
Outdoor settled dust—Particles that have settled
onto outdoor objects and surfaces due to either wet or
dry deposition.
Oxygen consumption (VO2)—The rate at which
oxygen is used by tissues.
Parameter uncertainty—Uncertainty regarding
some parameter.
Partially breast fed—Infants whose source of milk
comes from both human milk and other milk
substitutes.
Pathway—The physical course a chemical or
pollutant takes from the source to the organism
exposed.
Physiologically-based pharmacokinetic (PBPK)
modeling—PBPK modeling is an approach for
predicting the absorption, distribution, metabolism
and excretion of a compound in humans.
Per capita intake rate—The average quantity of
food consumed per person in a population composed
of both individuals who ate the food during a
specified time period and those that did not.
Pica—Pica behavior is the repeated eating of
non-nutritive substances, whereas soil-pica is a form
of soil ingestion that is characterized by the recurrent
ingestion of unusually high amounts of soil (i.e., on
the order of 1,000-5,000 milligrams per day or
more).
Plain tap water—Excludes tap water consumed in
the form of juices and other beverages containing tap
water.
Population mobility—An indicator of the frequency
at which individuals move from one residential
location to another.
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Glossary
Population risk descriptor—An assessment of the
extent of harm to the population being addressed. It
can be either an estimate of the number of cases of a
particular effect that might occur in a population (or
population segment), or a description of what fraction
of the population receives exposures, doses, or risks
greater than a specified value.
Potential dose—The amount of a chemical contained
in material ingested, air breathed, or bulk material
applied to the skin.
Poverty/income ratio—Ratio of reported family
income to federal poverty level.
Precision—A measure of the reproducibility of a
measured value under a given set of circumstances.
Preparation losses—Net cooking losses, which
include dripping and volatile losses, post cooking
losses, which involve losses from cutting, bones,
excess fat, scraps and juices, and other preparation
losses which include losses from paring or coring.
Primary data/analysis— Information gathered from
observations or measurements of a phenomena or the
surveying of respondents.
Probabilistic uncertainty analysis—Technique that
assigns a probability density function to each input
parameter, then randomly selects values from each of
the distributions and inserts them into the exposure
equation. Repeated calculations produce a
distribution of predicted values, reflecting the
combined impact of variability in each input to the
calculation. Monte Carlo is a common type of
probabilistic Uncertainty analysis.
Protected products—Foods that have an outer
protective coating that is typically removed before
consumption.
Questionnaire/survey response—A "question and
answer" data collection methodology conducted via
in-person interview, mailed questionnaire, or
questions administered in a test format in a school
setting.
Random samples—Samples selected from a
statistical population such that each sample has an
equal probability of being selected.
Range—The difference between the largest and
smallest values in a measurement data set.
Ready-to-feed—Infant and baby products (formula,
juices, beverages, baby food), and table foods that do
not need to have water added to them prior to
feeding.
Real-time hand recording—Method by which
trained observers manually record information on
children's behavior.
Reasonable maximum exposure—A
semiquantitative term referring to the lower portion
of the high end of the exposure, dose, or risk
distribution. As a semiquantitative term, it should
refer to a range that can conceptually be described as
above the 90th percentile in the distribution, but
below the 98th percentile.
Recreational/sport fishermen—Individuals who
catch fish as part of a sporting or recreational activity
and not for the purpose of providing a primary source
of food for themselves or for their families.
Reference Concentration (RfC)—An estimate (with
uncertainty spanning perhaps an order of magnitude)
of a continuous inhalation exposure to the human
population (including sensitive target groups) that is
likely to be without an appreciable risk of deleterious
effects during a lifetime. It can be derived from a
NOAEL, LOAEL, or benchmark concentration, with
uncertainty factors generally applied to reflect
limitations of the data used. Generally used in
U.S. EPA's noncancer health assessments. Durations
include acute, short-term, subchronic, and chronic.
Reference Dose (RfD)—An estimate (with
uncertainty spanning perhaps an order of magnitude)
of a daily oral exposure to the human population
(including sensitive target groups) that is likely to be
without an appreciable risk of deleterious noncancer
effects during a lifetime. It can be derived from a
NOAEL, LOAEL, or benchmark dose, with
uncertainty factors generally applied to reflect
limitations of the data used. Generally used in U.S.
EPA's noncancer health assessments. Durations
include acute, short-term, subchronic, and chronic.
Relevant study—Studies that are applicable or
pertinent, but not necessarily the most important to
derive exposure factors. See also Key study.
Representativeness—The degree to which a sample
is, or samples are, characteristic of the whole
medium, exposure, or dose for which the samples are
being used to make inferences.
Residential occupancy period—The time between a
person moving into a residence and the time the
person moves out or dies.
Residential volume—The volume (m3) of the
structure in which an individual resides and may be
exposed to airborne contaminants.
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Glossary
Risk—The probability of an adverse effect in an
organism, system, or population caused under
specified circumstances by exposure to an agent.
Risk assessment—A process intended to calculate or
estimate the risk to a given target organism, system,
or population, including the identification of
attendant uncertainties, following exposure to a
particular agent, taking into account the inherent
characteristics of the agent of concern as well as the
characteristics of the specific target system. The risk
assessment process includes four steps: hazard
identification, hazard characterization (related term:
Dose-response assessment), exposure assessment,
and risk characterization. It is the first component in
a risk analysis process.
Risk characterization—The qualitative and,
wherever possible, quantitative determination,
including attendant uncertainties, of the probability of
occurrence of known and potential adverse effects of
an agent in a given organism, system, or population,
under defined exposure conditions. Risk
characterization is the fourth step in the risk
assessment process.
Risk communication—Interactive exchange of
information about (health or environmental) risks
among risk assessors, managers, news media,
interested groups, and the general public.
Route—The way a chemical or pollutant enters an
organism after contact, e.g., by ingestion, inhalation,
or dermal absorption.
Sample—A small part of something designed to
show the nature or quality of the whole.
Exposure-related measurements are usually samples
of environmental or ambient media, exposures of a
small portion of a population for a short time, or
biological samples, all for the purpose of inferring the
nature and quality of parameters important to
evaluating exposure.
Scenario uncertainty—Uncertainty regarding
missing or incomplete information needed to fully
define exposure and dose.
Screening-level assessment—An exposure
assessment that examines exposures that would fall
on or beyond the high end of the expected exposure
distribution.
Secondary data/analysis—The reanalysis of data
collected by other individuals or group; an analysis of
data for purposes other than those for which the data
were originally collected.
Sensitivity analysis—Process of changing one
variable while leaving the others constant to
determine its effect on the output. This procedure
fixes each uncertain quantity at its credible lower and
upper bounds (holding all others at their nominal
values, such as medians) and computes the results of
each combination of values. The results help to
identify the variables that have the greatest effect on
exposure estimates and help focus further
information-gathering efforts.
Serving sizes—The quantities of individual foods
consumed per eating occasion. These estimates may
be useful for assessing acute exposures.
Short-term exposure—Repeated exposure for more
than 24 hours, up to 30 days.
Slope Factor—An upper bound, approximating a
95% confidence limit, on the increased cancer risk
from a lifetime exposure to an agent. This estimate,
usually expressed in units of proportion (of a
population) affected per mg/kg-day, is generally
reserved for use in the low-dose region of the dose-
response relationship, that is, for exposures
corresponding to risks less than 1 in 100.
Soil—Particles of unconsolidated mineral and/or
organic matter from the earth's surface that are
located outdoors, or are used indoors to support plant
growth.
Soil adherence—The quantity of soil that adheres to
the skin and from which chemical contaminants are
available for uptake at the skin surface.
Soil ingestion—The intentional or unintentional
consumption of soil, resulting from various behaviors
including, but not limited to, mouthing, contacting
dirty hands, eating dropped food, or consuming soil
directly. Soil-pica is a form of soil ingestion that is
characterized by the recurrent ingestion of unusually
high amounts of soil (i.e., on the order of 1,000-
5,000 milligrams per day or more). Geophagy is also
a form of soil ingestion defined as the intentional
ingestion of earths and is usually associated with
cultural practices.
Spatial variability—Variability across location,
whether long- or short-term.
Subchronic exposure—Repeated exposure by the
oral, dermal, or inhalation route for more than 30
days, up to approximately 10% of the life span in
humans (more than 30 days up to approximately 90
days in typically used laboratory animal species).
Subsistence fishermen—Individuals who consume
fresh caught fish as a major source of food.
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Toxicokinetics—The passage through the body of a
toxic agent or its metabolites, usually in an action
similar to that of pharmacokinetics.
Tracer-element studies—Soil ingestion studies that
use trace elements found in soil and poorly
metabolized in the human gut as indicators of soil
intake.
Triangulation—Method used to measure skin
surface area in which areas of the body are marked
into geometric figures, then their linear dimensions
are calculated.
Uncertainty—Uncertainty represents a lack of
knowledge about factors affecting exposure or risk
and can lead to inaccurate or biased estimates of
exposure. The types of uncertainty include: scenario,
parameter, and model.
Unit risk—The quantitative estimate in terms of
either risk per ug/L drinking water (water unit risk)
or risk per ug/m3 air breathed (air unit risk).
Upper percentile—Values in the upper tail (i.e.,
between 90th and 99.9th percentile) of the distribution
of values for a particular exposure factor. Values at
the upper end of the distribution of values for a
particular set of data.
Uptake—The process by which a substance crosses
an absorption barrier and is absorbed into the body.
Usual dietary intakes— Refers to the long-term
average daily intake by an individual.
Vapor intrusion—The migration of volatile
chemicals from contaminated groundwater or soil
into an overlying building.
Variability—Variability arises from true
heterogeneity across people, places or time and can
affect the precision of exposure estimates and the
degree to which they can be generalized. The types of
variability include: spatial, temporal, and
inter-individual.
Ventilation Rate (VR)—Alternative term for
inhalation rate or breathing rate. Usually measured as
minute volume, i.e., volume (liters) of air exhaled per
minute.
Video transcription—Method by which trained
videographers tape a child's activities and
subsequently extract data manually with computer
software.
Wet-weight intake rates—Intake rates that are
based on the wet (or whole) weight of the food
consumed. This in contrast to dry-weight intake rates.
Surface area—Coating, triangulation, and surface
integration are direct measurement techniques that
have been used to measure total body surface area
and the surface area of specific body parts.
Consideration has been given for differences due to
age, gender, and race. Surface integration is
performed by using a planimeter and adding the
areas.
Surface integration—Method used to measure skin
surface area in which a planimeter is used to measure
areas of the skin, and the areas of various surfaces are
summed.
Survey response methodology—Responses to
survey questions are analyzed. This methodology
includes questions asked of children directly, or their
care givers, about behaviors affecting exposures.
Target—refers to any physical, biological, or
ecological object exposed to an agent.
Tap water from food manufacturing—Water used
in industrial production of foods.
Temporal variability—Variability over time,
whether long- or short-term.
Threshold—Dose or exposure concentration of an
agent below which a stated effect is not observed or
expected to occur.
Time-averaged exposure—The time-integrated
exposure divided by the exposure duration. An
example is the daily average exposure of an
individual to carbon monoxide. (Also called
timeweighted average exposure.)
Total dietary intake—The sum of all foods in the
following food categories: dairy, meats, fish, eggs,
grains, vegetables, fruits, and fats. It does not include
beverages, sugar, candy, sweets, nuts and nut
products.
Total tap water—Water consumed directly from the
tap as a beverage or used in the preparation of foods
and beverages (i.e., coffee, tea, frozen juices, soups,
etc.).
Total fluid intake—Consumption of all types of
fluids including tapwater, milk, soft drinks, alcoholic
beverages, and water intrinsic to purchased foods.
Total water—Water from tap water and non tap
water sources including water contained in food.
Toxicodynamics—The physiological mechanisms by
which toxins are absorbed, distributed, metabolized
and excreted
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Glossary
Worst case scenario—The maximum possible
exposure, when everything that can plausibly happen
to maximize exposure happens. The worst case
represents a hypothetical individual and an extreme
set of conditions that usually will not be observed in
an actual population.
GLOSSARY ENTRIES ADAPTED FROM:
International Programme on Chemical Safety. (2004)
IPCS risk assessment terminology.
Available online at:
http://www.who.int/ipcs/methods/harmoniza
tion/areas/ipcsterminologypartsland2.pdf
U.S. EPA (Environmental Protection Agency).
(1992) Guidelines for exposure assessment.
Office of Research and Development, Office
of Health and Environmental Assessment,
Washington, DC; EPA/600/2-92/001.
U.S. EPA. (Environmental Protection Agency)
(1997) Exposure factors handbook revised.
Office of Research and Development,
Washington, DC; EPA/600/P-95/002F.
U.S. EPA (Environmental Protection Agency) (2005)
Guidelines for carcinogen risk assessment.
Risk Assessment Forum, Washington, DC;
EPA/630/P-03/001F. Available online at
http://cfpub.epa.gOv/ncea/cfm/recordisplay.c
fm?deid=l 16283.
Zartarian, VG, Ott, WR, Duan, N. (2007). Basic
concepts and definitions of exposure and
dose. In: Ott, W.R., Steinemann, A.C., and
Wallace, L.A. (Eds.). Exp Anal 33-63. Boca
Raton, FL: CRC Press, Taylor & Francis
Group.
Exposure Factors Handbook Page
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