EPA/600/8-89/043
March 1990
EXPOSURE FACTORS HANDBOOK
: Exposure Assessment Group
Office of Health and Environmental Assessment
U.S.. Environmental Protection Agency
Washington, DC 20460
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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.
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CONTENTS
Page No.
Tables ... vi i ~
Foreword . \ ... x
Preface ,.. xi
Abstract .. .. xi i
Authors, Contributors, and Reviewers xiii
PART I
1. INTRODUCTION 1-1
1.1 Background ... i-i
1.2 General Equation for Calculating Exposure ., . . 1-1
1.3 Organization .. 1-4
1.4 References . . 1-5
2. INGESTION ROUTE 2-1
2.1 Exposure Equation for Ingestion 2-1
2.2 Drinking Water Consumption . 2-1
2.3 Consumption of Homegrown Fruits and Vegetables 2-10
2.3.1 Background ...... 2-10
2.3.2 Methods 2-15
2.3.3 Results 2-16
2.3.4 Exposure Calculation 2-22
2.3.5 Conclusion , , 2-23
2.4 Consumption of Homegrown Beef and Dairy Products i 2-24
2.5 Consumption of Recreationally Caught Fish and Shellfish 2-28
2.5.1 Background .. 2-28
2.5.2 Methods 2-28
2.5.3 Conclusion , 2-39
2.6 Soil Ingestion and Pica 2-40
2.6.1 Background ; 2-40
2.6.2 Methods.. ...., ..... 2-44
2.6.3 Results 2-45
2.6.4 Conclusion . 2-57
2.7 References , .... 2-60
Appendix 2A. National Marine Fisheries Service Recreational
Fishing Data'...;....................... 2-69
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CONTENTS (continued)
Page No.
Appendix 2B. Method of Calculation: Weighted Means, and
Percentiles • • 2-81
Appendix 2C. Studies of Consumption of Recreationally Caught
Fish 2-83
Appendix 2D. Pica Data Sources ... ... 2-91
3. INHALATION ROUTE ...... 3-1
3.1 Exposure Equation for Inhalation 3-1
3.2 Pulmonary Ventilation ....... . 3-1
'.
3.2.1 Background 3-1.
3.2.2 Methods 3-2
3.2.3 Results 3-3
3.2.4 Application of Pulmonary Ventilation Data 3-5
3.2.5 Conclusion . .... ...... 3-6
3,3 References —... 3-9
Appendix 3A. Detailed Ventilation Rate Data 3-11
4. DERMAL ROUTE . ..... .............^., 4-1
4.1 Exposure Equation for Dermal . .... 4-1
4.2 Surface Area of the Human Body ... ... 4-2
4.2.1 Background 4-2
4.2.2 Measurement Techniques 4-2
4.2.3 Formulae for Total Body Surface Area ... . 4-4
4.2.4 Surface Area of Body Parts ... 4-4
4.2.5 Methods .: ... 4-6
4.2.6 Total Body Surface Area 4-6
4.2.7 Body Part Surface Area .. , 4-7
4.2.8 Results 4-8
4.2.9 Application of Body Surface Area Data ... 4-14
4.2.1Q Conclusion, 4-14
4.3 References . ..... ,., 4-17
Appendix 4A. Formulae for Total Body Surface Area . 4-19
Appendix 4B. PercentiTe Estimates; of Total Body Surface Area
and Surface Area o,f Body Parts for Adult Males,
Adult Females, Male Children, and Female
Children ................ ......... 4-27
IV
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CONTENTS (continued)
Page Mo.
5. OTHER FACTORS FOR EXPOSURE CALCULATIONS .. 5-1
5.1 Lifetime ....... 5-1
5.2 Body Weight [. 5.1
5.2.1 Background .. .. „. 5-1
5.2.2 Methods .. 5.3
5.2.3 Results ... ... 5-4
5.2.4 Application of Body Weight Data 5-4
5.2.5 Conclusion 5-7
5.3 Activity Patterns ..;....... 5-7
5.3.1 Background ...... 5-7
5.3.2 Estimations of Exposure Duration 5-9
5.3.3 Application of Time Use Data .'..'.. 5-24
5.3.4 Regional Variations 5-31
5.3.5 Population Mobility 5-31
5.3.6 Showering 5.34
5.4 References 5-37
Appendix 5A. Percentile Distribution of the Body Weights of
Adults and Children 5-41
Appendix 5B. Activity Codes and Descriptors Used for Adult
Time Diaries 5.47
Appendix 5C. Percentile Distributions of Weighted Mean Hours
Per Week for Men and Women >. 5-53
Appendix 5D. Mobility of Resident Population by State: 1980 5-67
PART II
1. STANDARD EXPOSURE SCENARIOS i-i
1.1 Approach 1_1
1.2 Ingestion of Drinking Water at Residence 1-5
1.3 Ingestion of Homegrown Fruits and Vegetables 1-8
1.4 Ingestion of Homegrown Meat and Dairy Products 1-11
1.5 Ingestion of Recreationally Caught Fish/Shellfish from
Large Water Bodies 1-14
1.6 Ingestion of Soil - Residential Setting - Children".'.'.'.. 1-17
1.7 Inhalation of Vapors Outside Residence 1-20
1.8 Inhalation of Vapors Inside Residence 1-23
1.9 Inhalation of Vapors While Showering at Residence 1-26
1.10 Inhalation of Particulates Outside Residence 1-29
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CONTENTS (continued)
Page No.
1.11 Inhalation of Participates Inside Residence 1-32
1.12 Dermal Contact With Water at Residence 1-35
1.13 Dermal Contact with Soil While Gardening 1-36
2. ANALYSIS OF UNCERTAINTIES 2-1
2.1 Qualitative Analysis 2-1
2.2 Quantitative Analysis 2-3
2.2.1 Sensitivity Analysis 2-3
2.2.2 Monte Carlo Simulation 2-4
2.3 Presentation of Uncertainty Analysis Results ;.... 2-7
2.4 Example Problems 2-7
2.5 References 2-14
VI
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TABLES
Page No.
PART I
2-1. Tap Water Consumption Rate by Sex, Age, and Geographic
Area 2-4
2-2. Frequency Distribution of Tap Water Consumption Rates 2-5
2-3. Average Daily Fluid Consumption Rate by Age Group from the
Total Diet Study . 2-6
2-4. Mean and Standard Error for the Daily Intake of Beverages
and Tap Water by Age 2-7
2-5. Measured Fluid Intakes (ml/day) 2-8
2-6. 1986 Vegetable Gardening by Demographic Factors 2-12
2-7. Weight Ratio of Homegrown to Total,Fruits and Vegetables
Consumed (Unitless) .... . 2-13
2-8. Seasonal Variations in Weekly Household Consumption of
Fruits and Vegetables 2-14
2-9. Percentage of Gardening Households Growing Different
Vegetables 2-18
2-10. Average Daily Consumption of Total Fruits and Vegetables,
from Three-Day Dietary Recall, at Specified Percentiles
(9/day) .... 2-19
2-11. Rates of Ingestion of Beef and Dairy Products ...... .. 2-26
2-12. Summary of National Surveys ..... 2-29
2-13. Summary of Local Recreational Surveys .... 2-30
2-14. Mean Total Fish Consumption by Species 2-32
2-15. Total Fish Consumption by Demographic Variables .......... 2-34
2-16. Distribution of Fish and Shellfish Consumption Rates of
Fish Eaters .,-. ; 2-36
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TABLES (continued)
Page No.
2-17. Cumulative Distribution of Total Fish/Shellfish
Consumption by Sport Fishermen in the Metropolitan
Los Angeles Area 2-37
2-18. Yearly and Daily Fish Consumption Data by Recreational
Fishing Frequencies in Commencement Bay, Washington 2-38
2-19. Definitions of Pica Used in the Research Literature 2-42
2-20. Incidence of Abnormal Ingestion Behavior in Selected
Reports 2-47
2-21. Soil Ingestion According to Age 2-51
2-22. Estimates of Soil Ingestion from Dermal Contact 2-52
2-23. Estimates of Soil Ingestion by Age and Degree of Ingestion 2-58
3-1. Summary of Human Inhalation Rates for Men, Women, and
Children by Activity Level (nr/hr) 3-4
3-2. Activity Pattern Data Aggregated for Three
Microenvironments by Activity Level 3-7
4-1. Surface Area by Body Part for Adults (m2) 4-10
4-2. Percentage of Total Body Surface Area by Part for Adults . 4-11
4-3. Percentage of Total -Body Surface Area by Part for Children 4-12
5-1. Expectation of Life at Birth: 1920 to 1985 5-2
5-2. Body Weights of Adults (kilograms) 5-5
5-3. Body Weights of Children (kilograms) 5-6
5-4. Major Time Use Activity Categories 5-11
5-5. Weighted Mean Hours Per Week by Sex: 87 Activities and
10 Subtotals 5-12
5-6. Weighted Mean Hours Per Week by Age: 87 Activities and
10 Subtotals - Respondents: Males 5-16
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TABLES (continued)
Page No.
5-7. Weighted Mean Hours Per Week by Age: 87 Activities and
10 Subtotals - Respondents: Females . '....- ... 5-20
5-8. Mean Hours Per Week Spent by Children in Primary
Activities by Age and Sex 5-25
5-9. Summary of Average Time-Activity Patterns for a 24-Hour
Period from Studies by Chapin (1974) and Szalai (1972) ... 5-29
5-10. Cumulative Frequency Distribution of Average Shower
Duration for 2,500 Households 5-36
PART II
2-1. Summary of Sensitivity Analysis Results for Example 1 .... 2-10
2-2. Summary of Probabilistic Analysis Results for Example 2 .. 2-12
2-3. Summary of Sensitivity Analysis Results for Example 2 2-13
ix
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FOREWORD
The Exposure Assessment Group (EAG) of EPA's Office of Research and
Development has three main functions: (1) to conduct exposure assess-
ments, (2) to review assessments and related documents, and (3) to develop
guidelines for exposure assessments. The activities under each of these
functions are supported by and respond to the needs of the various program
offices. In relation to the third function, EAG sponsors projects aimed
at developing or refining techniques used in exposure assessments.
The purpose of this document is to provide statistical data on the
various factors used in assessing exposure. Additionally, a number of
specific exposure scenarios are identified and recommendations are
provided for default parameter values to be used when appropriate site-
specific data are not available. The recommended values are based solely
on our interpretations of the available data.. In many situations differ-
ent values may be appropriate to use in consideration of policy, precedent
or other factors. The document is published in the three-ring binder for-
mat so that it can be easily updated as new information on these factors
becomes available.
Michael A. Callahan
Director
Exposure Assessment Group
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PREFACE
The Exposure Assessment Group (EAG) of the Office of Health and
Environmental Assessment (OHEA) has prepared this handbook to address
factors commonly used in exposure assessments. It was prepared in
response to requests from many EPA program and regional offices for
additional guidance on how to select values for exposure factors.
The purpose of this handbook is to provide a summary of the available
data on various factors used in assessing exposure. Additionally, a
number of specific exposure scenarios are identified with recommendations
for default values to use when site-specific data are not available. The
handbook will provide a common data base which all Agency programs can
use to derive values for exposure assessment factors. Thus, it should
help improve the consistency with which exposure assessments are
conducted across the Agency, but still allow different approaches as may
be appropriate in consideration of policy, precedent, or other factors.
The document is published in a 3-ring binder format to allow convenient
updates which we plan to make as new data become available.
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ABSTRACT
This document provides a summary of the available data on various
factors used in assessing human exposure including drinking water
consumption, consumption rates of broad classes of food including fruits,
vegetables, beef, dairy products, and fish; soil ingestion; inhalation
rate; skin area; lifetime; activity patterns; and body weight.
Additionally, a number of specific exposure scenarios are identified with
recommendations for default values to use when site-specific data are not
available. The basic equations using these parameters to calculate
exposure levels are also presented for each scenario. Default values are
presented as ranges from typical to reasonable worst case and as
frequency distributions where appropriate data were available. Finally,
procedures for assessing the uncertainties in exposure assessments are
also presented with illustrative examples. These procedures include
qualitative and quantitative methods such as Monte Carlo and sensitivity
analysis.
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
The Exposure Assessment Group (EAG) within EPA's Office of Health and
Environmental Assessment was responsible for the preparation of this
handbook. The document was prepared by Versar Inc. under EPA Contract
No. 68-02-4254, Work Assignment No. 189. John Schaum, of EAG, served as
the EPA task manager, providing overall direction and coordination of the
production effort as well as technical assistance and guidance.
AUTHORS
James J. Konz
Karen Li si
Elaine Friebele
Douglas A. Dixon
Exposure Assessment Division
Versar Inc.
Springfield, VA
Among the authors, Mr. James Konz was Task Manager responsible for the
overall technical content of the manual; development of the exposure meth-
odologies and exposure scenarios; summarization of the factors from the
previous publication dealing with body weight, pulmonary ventilation, and
surface area; preparation of sections on ingestion of soil and.homegrown
beef and dairy products; and preparation of the manual.
Ms. Karen Lisi researched and prepared sections on activity patterns
and drinking water consumption. Ms. Elaine Friebele was responsible for
the sections dealing with consumption of recreationally-caught fish and
shellfish and consumption of homegrown fruits and vegetables. Mr. Douglas
Dixon prepared the section on the analysis of uncertainties.
REVIEWERS
The following individuals within EPA reviewed an earlier draft of
this document and provided valuable comments:
XI 1 1
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Karen Blackburn
Environmental Criteria and Assessment Office
Office of Health and Environmental Assessment
Cincinnati, OH
Joseph Cotruvo
Office of Drinking Water
Lynn Del pi re
Office of Toxic Substances
Arnold Den
Region 9
Stephanie Irene
Office of Solid Waste and Emergency Response
Paul White
Exposure Assessment Group
Office of Health and Environmental Assessment
The following individuals outside of EPA also reviewed this document
and provided helpful comments and suggestions:
Mitchell Small
U.S. Army Biomedical and Research and Development Laboratory
Fort Dietrick, MD
Martha Workman
USDA Food Safety and Inspection Service
Washington, D.C.
Judith Douglas
USDA Food Safety and Inspection Service
Washington, D.C.
Thomas McLaughlin
Chemical Exposure Assessment, Inc.
Washington, D.C.
ACKNOWLEDGEMENTS
Technical editing support was provided by Ms. Barbara Malczak and
Ms. Martha Martin, word processing was provided by Ms. Lynn Maxfield and
Ms. Kammi Johannsen, and the drafting and graphics were prepared by
Ms. Kathy Bowles. T;,e dedicated assistance of these Versar Inc.
employees allowed the successful completion of this project and is
sincerely appreciated.
xiv
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1. INTRODUCTION
1.1 Background
The Exposure Factors Handbook is intended to serve as a support
document to EPA's Guidelines for Estimating Exposures (USEPA 1986), and
Proposed Guidelines for Exposure-Related Measurements (USEPA 1988) by
providing data on standard factors that may be needed to calculate human
exposure to toxic chemicals. The Guidelines were developed to promote
consistency among the various exposure assessment activities that are
carried out by the various EPA program offices. This handbook should
assist in this goal by providing a consistent framework to calculate
exposure.
The handbook is organized by grouping the factors into those needed
for each specific route of exposure (i.e., ingestion, inhalation, or
dermal) or those needed for more than one route. Standard exposure
scenarios using these factors are included to facilitate the use of the
data. Finally, procedures for analyzing uncertainty in exposure
assessments are presented.
The Exposure Factors Handbook is an extension of earlier efforts
towards standardizing the Agency's exposure assessment calculations
sponsored by the Exposure Assessment Group, Office of Health and
Environmental Assessment, Office of Research and Development. USEPA
(1985) covered body weight, body surface area, and respiration rate in
their report "Development of Statistical Distributions or Ranges of
Standard Factors Used in Exposure Assessments." The results of this
study are incorporated into this handbook.
1•2 General Equation for Calculating Exposure
The Guidelines define exposure as the contact with a chemical or
physical agent. The magnitude of the exposure is the amount of the agent
available at human exchange boundaries (skin, lungs, gut) during some
1-1
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specified time. Starting with a general integral equation for exposure
(USEPA 1988), several exposure equations can be derived depending upon
boundary assumptions. One of the more useful of these derived equations
used for dealing with lifetime exposures to agents with linear
non-threshold responses (i.e., our current assumptions about many
carcinogens) is the Lifetime Average Daily Exposure (LADE) discussed
below. Exposure assessments are usually done to support risk
assessments; only exposure calculations used to support cancer risk
assessments and repeated and prolonged (chronic) exposures to
noncarcinogens will be covered in this handbook. (See the Proposed
Guidelines for Exposure-Related Measurements (USEPA 1988) for an expanded
discussion of some of the other equations that can be used.)
For cancer risk assessments, exposure is averaged over the body
weight and lifetime:
Total Exposure
Body Weight x Lifetime
The total exposure can be expanded as follows:
Total Fxnosure - Contaminant Contact Exposure
IotaI txposure - Concentration * Rate x Duration
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.
The contact rate refers to the rates of inhalation, ingestion, and
dermal contact depending on the route of exposure. For ingestion, the
contact 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). Much of this handbook is devoted to standard rates
of ingestion for some broad classes of food.
The exposure duration is the length of time that contaminant
contact lasts. The time a person lives in an area, frequency of bathing,
time spent indoors vs. outdoors, etc. all affect the exposure duration.
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The Activity Patterns Section (Section 5.3) gives some examples of
population behavior patterns, which may be useful for exposure
calculations.
When the above parameter levels remain constant over time, they are
substituted directly into the exposure equation. When they change with
time, a summation approach is needed to calculate exposure. In either
case, the exposure duration is the length of time exposure occurs at the
concentration and contact rate specified by the other parameters in the
equation.
Exposure (sometimes called "administered dose") can be expressed as a
total amount (with units of mass, e.g., mg) or as an exposure 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 LADE is usually expressed in terms of mg/kg-day or
other mass/mass-time units.
In using the LADE, the upper-bound cancer risk is estimated by
adjusting the exposure to account for absorption into the body and
multiplying by the 95 percent upper confidence limit of the linear slope
factor of the dose-response function. Since the slope factor is derived
on the basis of administered dose, the exposure should be expressed on a
comparable basis. If the absorption from the medium used in the animal
studies is the same as that occurring in the human exposure scenario, no'
adjustment is needed.
The lifetime value used in the above equation is the period of time
over which the administered dose is averaged. For carcinogens, this
should represent the average life expectancy of the exposed population.
According to the 1985 edition of the U.S. Bureau of the Census
Statistical Abstract of the United States, the average life expectancy of
men and women is 74.6 years, and the figures have shown a steady increase
in life span through time. Therefore, an average figure of 75 years is
suggested for the lifetime of men and women. For exposure estimates to
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be used for assessments other than carcinogenic risk, different averaging
periods are frequently used. For acute exposures, the administered doses
are usually averaged over a day or single event. For chronic noncancer
effects, the time period used is the actual period of exposure. The
objective in selecting the averaging time is to express the exposure in a
way which makes it comparable to the dose-response relationship used in
conjunction with the exposure estimate to calculate risk.
The body weight used to calculate the total exposure in the above
equation should reflect the average weight of the exposed population
during the time when the exposure actually occurs. If the exposure
occurs continuously throughout an individual's life or only during the
adult ages, using an adult average weight of 70 kg should provide
sufficient accuracy. However, when the exposure.is limited to childhood,
the weight representing those ages should be used. Body weight is
covered in more detail in the section on other factors needed for
exposure calculations.
1.3 Organization
All factors are organized in a loose-leaf, tabbed format for easy
reference. Factors are grouped according to exposure route in Part I:
ingestion, inhalation and dermal contact. Standard exposure scenarios
using these factors are presented in Part II. This Part provides default
values and ranges to use for specific exposure scenarios. This Part will
be useful for screening assessments and for quick-response estimations.
Additional scenarios will be added as data become available.
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1.4 References
USEPA. 1985. U.S. Environmental Protection Agency. Development of
statistical distributions or ranges of standard factors used in exposure
assessments. Washington, DC: Office of Health and Environmental
Assessment. EPA No. 600/8-85-010. Available from: NTIS, Springfield,
VA. PB85-242667. ,
USEPA. 1986. U.S. Environmental Protection Agency. Guidelines for
estimating exposures. Federal Register 51:34042-34054.
USEPA. 1988. U.S. Environmental Protection Agency. Proposed guidelines
for exposure-related measurements. Federal Register 53:48830-48853.
1-5
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2. INGESTION ROUTE
This chapter discusses consumption rates of broad classes of food
including water, fruits and vegetables, beef, dairy products, and fish.
Consumption of the specific food groups has been the subject of a number
of studies, and the assessor should refer to other references to obtain
consumption rates. For example, Pennington (1983) developed representa-
tive diets using about 200 foods for eight age-sex groups. Also,-Sawders
and Petersen (1987) .describe the Tolerance Assessment System, which can be
used to estimate dietary exposure to a pesticide.
2.1 Exposure Equation for Inqestion
The contact rate for the ingestion route is the consumption rate. The
general LADE equation for ingestion exposure is:
Lifetime
Average Consumption Rate x Contaminant x Exposure
Ingestion = Concentration in Food Duration
Exposure Body Weight x Lifetime
Consumption rate is determined from site-specific data or (less desirably)
can be estimated from generic rates derived from relevant regional studies
or national consumption surveys. The contaminant concentration refers to
the concentration in food or whatever is being ingested. Exposure dura-
tion refers to the time an individual is exposed at a particular site of
concern.
2.2 Drinking Water Consumption
The USEPA presently uses the quantity of 2 L per day for adults and
1 L per day for infants (individuals of 10 kg body mass or less) as the
average amount of water consumed per person (USEPA 1980). This amount
includes drinking water consumed in the form of juices and other
beverages containing tap water (e.g., coffee). The volume of 2 L per day
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is a historical figure set by the U.S. Army in determining the amount of
•jf
water needed for each person in the field. Based on discussions with
USEPA officials, Patrizi* stated that the Agency believes that a water
consumption rate of 2 L per day is an overestimate for most people and is
used to represent a long-term average consumption rate.
The National Academy of Sciences (MAS 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
th«t some individuals in physically oriented occupations or living in
warmer regions may exceed this level of water intake on an average
basis. NAS (1977) estimated that most of those who consume more than 2 L
of water per day are still adequately protected, since the margin of
safety estimated for contaminants in drinking water is sufficient to
offset the excess consumption.
NAS (1977) calculated the average per capita water (liquid) consump-
tion 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 Schlegal
(1968), Randall (1973), NAS (1974), and Pike and Brown (1975). Although
the calculated intake and volume of 1.63 L per day may have more of a
scientific basis than the presently accepted figure of 2 L per day,
NAS (1977) adopted the larger volume (i.e., 2 L per day) to represent
the intake of the majority of water consumers.
Several other drinking water intake rates have been suggested. The
National Cancer Institute (NCI), in a population-based, case control
study investigating the possible relationship between bladder cancer and
drinking water, interviewed approximately 9,000 individuals using a
standardized questionnaire (Cantor et al. 1987). Based on responses from
K. Patrizi, Safe Drinking Water Hotline, U.S. Environmental
Protection Agency, Office of Drinking Water, personal communication
with K. Lisi (Versar) August 25, 1987.
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the interviews (2,982 cases and 5,782 controls), average consumption
rates for a "typical" week were compiled by sex, age group, and
geographic region. These rates are listed in Table 2-1. The overall
average tap water consumption rate was 1.39 L/day. Distribution data are
presented in Table 2-2. These data suggest a 50th percentile value of
approximately 1.3VL/day and a 90th percentile value of approximately 2.0
L/day.
Gillies and Paul in (1983) reported drinking water intake rates based
on a survey of 109 adults .in New Zealand. The mean intake rate was
1.256 (±0.39) L/day and the 90th percentile rate was 1.90 L/day. The
reported range was 0.26 to 2.80 L/day.
Based on data from the Food and Drug Administration's (FDA's) Total
Diet Study, Pennington (1983) reported the average daily fluid
consumption rates for different age/sex groups. Using these data, the
average fluid and water/water-based food consumption rates were
summarized for six age groups. These consumption rates are presented in
Table 2-3. Based on the consumption rates for water and water-based
foods for the two adult age groups, 1.07 and 1.30 L/day, the average
adult consumption rate is 1.2 L/day.
Using data collected by the U.S. Department of Agriculture (USDA) in
the 1977-78 Nationwide Food Consumption Survey, EPA (1984e) determined
daily beverage intake levels by age. Tap water was one of the identified
subcategories of the beverage category. Daily intake rates for beverages
and for tap water are presented in Table 2-4. As seen in the table,
daily beverage intake levels for adults ranged from 1.24 to 1.73 L.
Data on fluid intake levels have been summarized by the International
Commission on Radiological Protection (ICRP) in the Report of the Task
Group on Reference Man (ICRP 1981). These intake levels for adults and
children are summarized in Table 2-5. The amount of drinking water (tap
water and water-based drinks) consumed by adults ranged from about 400
mL/day to about 2,200 mL/day under "normal" conditions. The levels for
children ranged from 540 to 790 mL/day.
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Table 2-1. Tap Water Consumption Rate by
Sex, Age, and Geographic Area
Group/subgroup
Total group
Sex
Hales
Females
Age, years
21-44
45-64
65-84
Geographic area
Atlanta
Connecticut
Detroit
Iowa
New Jersey
New Mexico
New Orleans
Seattle
San Francisco
Utah
No. of
respondents
5,258
3,892
1,366
291
1,991
2,976
207
844
429
743
1,542
165
112
316
621
279
Average
Tap water
consumption,
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
1.44
1.36
1,35
Source: Cantor et al. (1987).
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Table 2-2. Frequency Distribution of Tap Water Consumption Rates3
Consumption rate (L/day) Cumulative frequency (%)
<0.80 • 19.2
0.81-1.12 39.6
1.13-1.44 59.7
1.45-1.95 , 79.9
>1.96 100.0
Represents consumption in a "typical" week.
Source: Cantor et al. (1987).
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Table 2-3. Average Daily Fluid Consumption Rate by
Age Group from the Total Diet Study
Total average daily consumption rate (L/dav)
Age group
6-11 months
2 years
14-16 years
25-30 years
60-65 years
Total
fluids3
0.689
0.930
1.470
1.750
1.645
Water and
water-based
foods'3
0.201
0.499
0.746
1 . 066
1.295
a Includes milk/formula/milk-based soup, carbonated soda, alcoholic
beverages, canned juices, water, coffee, tea, reconstituted
juices, and reconstituted soups.
Includes water, coffee, tea, reconstituted juices; and
reconstituted soups.
Source: Pennington (1983).
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Table 2-4. Mean and Standard Error for the Daily Intake
of Beverages3 and Tap Water by Age
Age
All ages
Under 1
1 to 4
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 39
40 to 59
60 and over
Beverage intake
(ml)
1434 ±13.7 -
307 ± 89.2
743 ± 43.5
861 ±36.5
1025 ±34.2
1241 ± 35.9
1484 ±46.9
1531 ± 48.0
1642 ±37.7
1732 ± 29.3
1547 ±32.8
Tap water intake
(nt)
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
a Includes tap water; water-based drinks such as coffee, tea,
soups, and other drinks such as soft drinks, fruitades, alcoholic
drinks.
Source: USEPA (1984e).
2-7
-------
Table 2-5. Measured Fluid Intakes (ml/day)
Subject
Adults ("normal" conditions)
Adults (high environmental
temperature to 32 "C)
Adults (moderately active)
Children (5-14 yr)
Total
fluids Milk
1000-2400 120-450
2840-3410
3256 ±
SO = 900
3700
1000-1200 330-500
1310-1670 540-650
Tap Water-based
water drinks3
45-730 320-1450
ca. 200 ca. 380
540-790
a Includes tea, coffee, soft drinks, beer, cider, wine, etc.
Source: 1CRP (1981).
2-8 *
-------
The drinking water consumption rates for adults, that have been
reported in the literature, can be summarized as follows:
90th
Range percentile
Average (L/dav) (L/day) (L/dav) Reference
1.63 (calculated) -- -- NAS 1977
1.39 • <0.80->1.96 2.0 (est.) Cantor et al. 1987
1.25 0.26-2.80 1.90 Gillies and
Paul in 1983
1.20 -- -- Pennington 1983
1.53 1.24-1.73 1.68 (est.) USEPA 1984
Average 1.4
These studies were selected as the basis for determining a recommended
consumption rate since they were based on large surveys and other
scientifically based data.
Based on the above data, the average adult drinking water consumption
rate is 1.4 L/day and the reasonable worst-case value is 2.0 L/day. This
average rate differs from the rate that is widely used as the average
drinking water consumption rate of 2.0 L/day. However, the 1.4 L/day
value is supported by the studies cited above and by the fact that
Pennington (1983) and Cantor et al. (1987) report total fluid intake
average rates of 1.7 L/day and 1.87 L/day in adults. Thus the average
drinking water consumption rate would be somewhat less than the 2.0 L/day
commonly used. Policy or precedent reasons may support the continued use
of the 2.0 L/day as the average adult drinking water consumption rate;
however, the data from the scientific literature suggest a rate of
1.4 L/day as the average.
Very little data are available upon which to recommend a reasonable
worst-case rate. The 90th percentile value reported by Gillies and
Paul in (1983), 1.90 L/day, suggests that a rate of 2.0 L/day may be a
reasonable approximation. In addition, the approximate 90th percentile
value suggested by Cantor et al. (1987) is 2.0 L/day. Based on these
2-9
-------
studies, a value of 2.0 L/day is recommended as the reasonable worst-case
drinking water consumption rate for adults. Since drinking water
consumption rates for sensitive subpopulations (e.g., manual laborers)
are not addressed by these studies, additional data for these groups are
required.
2.3 Consumption of Homegrown Fruits and Vegetables
2.3.1 Background
Homegrown fruits and vegetables may become contaminated with toxic
chemicals by several different pathways. Ambient pollutants in the air
may be deposited on or absorbed by the plants, or dissolved in rainfall
or irrigation waters which contact the plants. Pollutants may also be
absorbed through plant roots from contaminated soil and ground water.
Finally, the addition of pesticides, soil additives, and fertilizers to
gardens may result in food contamination (USEPA 1986).
This section provides information relevant to the assessment of expo-
sure resulting from the consumption of homegrown fruits and vegetables.
Its focus is on homegrown food crops since it is believed that any contam-
inated commercial foods would be widely distributed, thus reducing
individual exposure potential. (Note that population risks would not be
changed by this "dilution" effect. Thus, exposure assessors should also
consider population risks resulting from consumption of contaminated
commercial products.) The distinctions between fruits and vegetables are
those commonly used, not the botanical definitions. For example, in this
report, tomatoes are considered vegetables, although technically they are
fruits.
Estimation of toxic chemical exposures via ingestion of homegrown
fruits and vegetables requires information regarding the rates of their
ingestion. These consumption rates are influenced by several factors:
size of home gardening plots, yield, quality of produce, types of foods
grown, length of growing season, and climate. According to the latest
2-10
-------
survey by the National Gardening Association (1987), a total of
34 million, or 38 percent, of U.S. households participated in vegetable
gardening in 1986.
In recent years, the median size of the home vegetable garden has
decreased from 600 square feet in 1982 to 325 square feet in 1986 (Nation-
al Gardening Association 1987). The average yield from the home vegetable
garden is 0.9 pounds of produce per square foot.* Table 2-6 contains
demographic data on vegetable gardening in 1986. The largest numbers of
vegetable gardens are in the Midwest and South. A larger percentage of
rural households have gardens than do those in cities and suburbs.
Families with children have more gardens than single people or married
couples without children (National Gardening Association 1987).
Using information from the 1977-78 USDA Nationwide Food Consumption
Survey (1983), the homegrown fraction of total fruits and vegetables
consumed was calculated for rural, suburban, and city households (see
Table 2-7). Generally, homegrown fruits and vegetables make up a larger-
portion of the average person's fruit and vegetable diet in rural areas
than in cities or suburban areas. Consumption rates of some fruits and
vegetables show seasonal fluctuations, that follow the harvesting period
and storage characteristics of that crop. In Table 2-8, for example, the
difference between summer and winter consumption of melons is quite large,
but nearly equal quantities of lettuce are eaten throughout the year.
Seasonal fluctuations in consumption of homegrown fruits and vegetables
may be even more pronounced, since consumption is influenced by the length
of local growing seasons. On the other hand, preservation of homegrown
produce by canning or freezing allows consumption of the garden yield
throughout the year.
Rule-of-thumb average based on production rates of top 10 most
popular vegetables as determined from USDA studies.
Bruce Butterfield, Research Director, National Gardening
Association. Personal Communication with J. Konz (Versar) August
12, 1988.
2-11
-------
Table 2-6. 1986 Vegetable Gardening by Demographic Factors
Total
Region/section
East
New England
Mid-Atlantic
Midwest
East Central
West Central
South
Deep South
Rest of South
West
Rocky Mountain
Pacific
Percentage of
total households
that have gardens
38
33
37
32
50
50
50
33
44
29
37
53
32
Number
of households
(million)
34
7.3
1.9
5.4
11.0
6.6
4.5
9.0
3,1
5.9
6.2
2.3
4.2
Size of conmunitv
City 26 6.2
Suburb 33 10.2
Small town 32 3.4
Rural 61 14.0
Household size
Single + divorced, widowed 54 8.5
Married, no children 35 11.9
Married, with children 44 13.2
Source: National Gardening Association (1987).
2-12
-------
Table 2-7.' Weight Ratio of Homegrown to Total Fruits
and Vegetables Consumed (Unitless)
Fresh vegetables
Total fresh potatoes
White potatoes
Sweet potatoes
Total dark green
Spinach
Broccoli
Carrots
Tomatoes
Total other green
Lima beans
Snap, wax beans
Cabbage
Lettuce
Peas
Cucumbers
Mature onions
Corn
Fresh fruits
Citrus (all)
Total other fruit
Oranges
Cantaloupe
Strawberries
Apples
Melons except cantaloupe
Peaches
Pears
Grapes
Plums
All
0.124
0.119
0.176
0.333
0.200
0.067
0.159
0.487
0.226
0.750
0.658
0.162
0.042
0.727
0.395
0.100
0.448
0.113
0.154
0.093
0.141
0.333
0.165
0.181
0.297
0.286
0.118
0.200
Rural
0.225
0.220
0.333
0.500
0.333
0.200
0.268
0.623
0.336
0.857
0.857
0.271
0.058
0.800
0.590
0.195
0.667
0.126
0.233
0.120
0.250
0.417
0.239
0.305
0.400
0.421
0.154
0.375
City
0.031
0.030
0.095
0.133
0.000
0.059
0.073
0.317
0.096
0.500
0.346
0.065
.0.026
0.500
0.212
0.018
0.195
0.060
0.076
0.049
0.051
0.125
0.080
0.079
0.161
0.143
0.053
0.182
Suburban
0.072
0.065
0.154
0.233
0.167
0.053
0.143
0.466
0.173
0.667
0.576
0.105
. 0.044
0.625
0.390
0.080
0.344
0.148
0.150
0.236
0.108
0.267
0.158
0.170
0.300
0.217
0.053
0.250
Source: USDA (1983).
2-13
-------
Table 2-8. Seasonal Variations in Weekly Household
Consumption of Fruits and Vegetables
Hiqh
Carrots
Corn
Cucumbers
Dark green, leafy
Lettuce
Onions
Peas
Peppers
Potatoes
Pumpkin, winter
squash
Snap, wax beans
Tomatoes
Apples
Bananas
Cantaloupe
Grapefruit
Grapes
Melons except
cantaloupe
Oranges
Peaches
Pears
Plums
Strawberries
Season
Winter
Sunnier
Summer
Fall
Summer
Winter
Summer
Summer
Winter
Fall
Summer
Summer
Fall
Fall
Summer
Winter
Summer
Summer
Winter
Summer
Fall
Summer
Spring
Quantity
(Ib/wk)
0.50
1.47
0.78
0.38
1.30
0.57
0.18
0.26
3.69
0.36
0.54
2.04
2.39
1.30
1.80
1.21
0.33
2.82
1.65
1.01
0.29
0.29
0.32
Low
Season
Spring
Winter
Winter
Summer,
Winter
Fall
Spring
Winter
Spring,
Winter
Spring
Spring
Winter
Winter
Spring
Spring
Winter
Summer
Winter
Winter
Summer
Winter
Spring
Winter
Fall
Quantity
(Ib/wk)
0.38
0.17
0.17
0.25
1.08
0.39
0.07
0.14
3.11
0.06
0.29
0.75
1.14
1.21
0.03
0.23
0.06
0.02
0.62
0.07
0.11
0.01
0.04
Ratio:
high/low
1.3
8.6
4.6
1.5
1.2
1.5
2.6
1.9
1.2
6.0
1.9
2.7
2.1
1.1
60.0
5.3
5.5
141.0
2.7
14.4
2.6
29.0
8.0
Source: USDA (1983).
2-14
-------
2.3.2 Methods
Two information sources were used to determine consumption rates of
fruits and vegetables from household gardens: (1) Foods Commonly Eaten
by Individuals: Amount Per Dav and Per Eating Occasion ( Pap et al . 1-982 )
and (2) Food Consumption: Households in the United States. Seasons and
Year 1977-1978 (USDA 1983).
Using the data gathered in the 1977-78 USDA Nationwide Food Consump-
tion Survey, Pao et al . (1982) calculated percentiles of total fruit and
vegetable consumption of the U.S. population. The data were collected
during home interviews of 37,874 respondents, who were asked to recall
food intake for the day proceeding the interview, and record food intake
the day of the interview and the day after the interview. Therefore, if
the food was eaten at least once in 3 days, the quantity consumed was
recorded.
"All" and "bought" categories of consumption data for all foods are
provided by the USDA Food Consumption Survey. From these data, the aver-
age percentage of total fruits and vegetables consumed that are homegrown
is calculated by assuming that the difference between "all" and "bought"
is the amount "homegrown." The consumption rate of a homegrown fruit or
vegetable at a certain frequency, C , i~s approximated as follows:
Cp =
where
Ctp = the total (homegrown + bought) consumption rate of a
vegetable or frutt at a particular frequency, or percentile
(i.e., for people whose consumption of white potatoes falls into
the 95th percentile, Ctp is 202 g/day), and
P = the percentage of the quantity of the fruit or vegetable
consumed that is homegrown. The average percentage for all
types of households was used (rural, suburban, and metropolitan;
Table 2-7).
The necessary assumption in this method is that the consumption
behavior of home gardeners and their families follows the consumption
2-15
-------
rate frequencies of the U.S. population, which includes a majority of
nongardeners. This assumption could be a major source of error.
Although Pao et al. (1982) reported distributions from the data, it
was not felt that the data obtained from the 3-day diet records could be
used to derive a distribution of annual consumption rates. These data
actually represent the 3-day average intake of fruits and vegetables by
consumers. No distributions of consumption rates for broader food
categories--all vegetables or all fruits--are available. Obtaining a
frequency distribution for all vegetables by summing the distributions
for individual vegetables is not possible because the data represent the
national average intake of each vegetable on any 1 day in the year. The
sum of ingestion rates implies that the average individual's diet in 1 day
included the average amount of all vegetables. In addition, similarly
shaped distributions for each vegetable must be assumed. For example, the
person whose consumption rate for tomatoes falls in the 90th percent!le
is also assumed to have a 90th percentile consumption rate of broccoli.
While this assumption may be valid for consumption rates near the median;
it introduces a large degree of uncertainty at the extremes of the distri-
bution.
It is possible that people who consume large amounts of one vegetable
eat large quantities of all vegetables, or that people whose diet includes
a low vegetable intake, shun all vegetables equally. To avoid uncertain-
ty, however, intakes of different vegetables or fruits should be treated
as independent variables.
2.3.3
Results
The percentage of homegrown fruits and vegetables in the diet may
vary according to the difficulty involved in growing them, their cost and
availability at the market, the growing period, and the harvesting
frequency.
The data in Table 2-7 show that homegrown dark green vegetables make
up approximately one-third of the dark green vegetables consumed. This
category includes mustard greens, kale, kohlrabi, spinach, and broccoli.
2-16
-------
These greens may not always be available in the market and they are easy
to grow. Consumption of homegrown corn, cucumbers, green beans, and
tomatoes makes a significant contribution to the total consumption. The
data for green peas and lima beans are probably not representative because
they are based upon very small quantities. The proportion of homegrown
fruits consumed is highest for strawberries, peaches, and pears and lowest
for citrus fruits.
Table 2-9 contains information on the types of vegetables grown by
home gardeners in 1986. Tomatoes, peppers, onions, cucumbers, lettuce,
beans, carrots, and corn are among the vegetables grown by the largest
percentage of gardeners. Comparison of Tables 2-7 and 2-8 suggest that
the popularity of a vegetable with homegrowers does not necessarily lead
to high consumption rates.
Percentiles of consumption of total and homegrown fruits and vege-
tables are. presented in Table 2-10. However, any use of these data must
consider that these may not be representative values for annual consump-
tion rates since they were derived from 3-day consumption rates. Note
that lettuce, tomatoes, corn, and green beans were the items identified
most often in the 3-day diet recall. The homegrown vegetables consumed at
the highest rate are corn, lima beans, green beans, tomatoes, cabbage, and
cucumbers.
The average consumption rate of vegetables by individuals in 1 day,
based on the USDA Nationwide Food Consumption Survey, was 201 g/day (USDA
1980, as cited by USEPA 1986). Assuming a diet consists of a mix of all
listed vegetables, the average homegrown portion of all vegetables may be
determined from Table 2-10. Based on this table, the average homegrown
percentage of all vegetables is 25 percent. Thus, the total homegrown
vegetable consumption rate is 50 g/day.
The most frequently recalled fruits in the dietary intake survey were
orange juice and raw and cooked apples. The high proportion of homegrown
peaches, pears, and strawberries is reflected in their consumption rates:
15.1, 15.7, and 12.3_g/day, respectively. The consumption of juices
2-17
-------
Table 2-9. Percentage of Gardening Households
Growing Different Vegetables
Vegetable
Artichokes
Asparagus
Beans
Beets
Broccoli
Brussel sprouts
Cabbage
Carrots
Cauliflower
Celery
Chard
Corn
Cucumbers
Dried peas
Dry beans
Eggplant
Herbs
Kale
Kohlrabi
Leeks
Lettuce
Melons
Okra
Onions
Oriental vegetables
Parsnips
Peanuts
Peas
Peppers
Potatoes
Pumpkins
Radishes
Rhubarb
Spinach
Sunnier squash
Sunflowers
Sweet potatoes
• Tomato
Turnips
Winter squash
Percent
0.80
8.20
43.40
20.60
19.60
5.70
29.60
34.90
14,. 00
5.40
3.50
34.40
49.90
2.50
8.90
13.00
9.80
3.10
3.00
1,20
41.70
21.90
13.60
50.30
2.10
2.20
1.90
29.00
57.70
25.50
10.20
30.70
12.20
10.20
25.70
8.20
5.70
85.40
10.70
11.10
Source: National Gardening Association (1987).
2-18
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made from homegrown fruits is also large because beverage consumption
rates are higher per unit weight than food consumption rates. A source
of uncertainty in these data is the assumption that home gardeners prepare
juice from fruit that they grow, and that the "homegrown percentage" can
be applied to juices as well as whole fruits. Total average daily fruit
intake is 142 g/day per individual (USDA 1980, as cited by USEPA 1986).
Assuming a diet consists of a mix of all listed fruits, the average
homegrown portion of all fruits may be determined from Table 2-10.
Based on this table, the average homegrown percentage of fruits is 20 per-
cent. Thus, the total homegrown fruit consumption rate is 28 g/day.
The major source of uncertainty with these data is that they represent
the average intake of homegrown fruits and vegetables per person on any
1 day in the year. This average daily intake contrasts with the daily
intake, averaged over a year, of a person in the U.S. population, which
would be used in exposure calculations. The two values may, in fact, be
similar, although it is likely that intakes of people who eat fruits and
vegetables infrequently were underrepresented in the 3-day diet recall
study (Pao et al . 1982).
2.3.4 Exposure Calculation
The total dietary exposure, Et, that results from eating contami-
nated fruits and vegetables from the home garden is calculated as follows
(USEPA 1986):
Et - I (Cf)i'(Di
where
Cf = the concentration (mg/kg) of the pollutant in the
food at the time of consumption,
L = the amount (kg/day) of contaminated food consumed, and
subscript i - the number of different fruits and vegetables consumed.
2-22
-------
In order to perform this calculation, Cf, or the contaminant concen-
tration in the fruit or vegetable, i, must be known. L. is selected
from Table 2-10. If specific contaminated foods are not known, the
generic amounts of total homegrown fruits and vegetables can be used
(i.e., 50 g/day for. vegetables and 28 g/day for fruits). The median, or
50th percentile, value is used for a national exposure estimate. If the
exposure is limited to one region, different percentile values might be
used. Consideration should also be given to urban vs. suburban vs. rural
areas. The total exposure is then the sum of exposures from each home-
grown fruit or vegetable consumed.
The frequency of consumption also affects exposure. It is likely that
homegrown fruits and vegetables are not consumed by gardeners and their
families throughout the year. The length of time that homegrown vege-
tables and fruits are consumed varies with geographic location, climate,
and types of produce grown. As stated in the background section, preser-
vation of the garden yield by freezing and canning extends the period
during which homegrown fruits and vegetables are consumed. No information
on the length of time that homegrown fruits and vegetables are consumed
is available.
2.3.5 Conclusion
No data were available that presented the actual annual consumption
rates for homegrown fruits and vegetables by gardeners. Because of this,
it is recommended that the following four procedures be considered by
assessors in the order presented:
(1) Conduct local survey of residents in the area of concern and
determine actual annual consumption rates for homegrown fruits
and vegetables.
(2) Determine productivity levels for gardeners in the area, and
derive consumption rates by dividing the quantity of fruits and
vegetables produced by the number of consumers of the homegrown
crops.
2-23
-------
(3) Based on national survey data (USDA 1980), the average amounts
of total fruits and total vegetables consumed on any one day ihave
been estimated as 200 g/day for vegetables and 140 g/day for
fruits. It is not known how representative these estimates are
of the entire year; however, it was assumed that the esti-
mates represented long-term average daily consumption rates
rather than actual meal sizes. Consumption rates also vary by
region. These values assume that all the homegrown fruits and
vegetables consumed by exposed individuals are derived from the
contaminated source. From Table 2-10, the fraction of vegetables
homegrown ranges from 0.04 to 0.75 depending on type. The over-
all average homegrown fraction from this table is 0.25, repre-
senting the typical portion. It was judged that the reasonable
worst-case portion would be 0.40. Using these fractions, total
homegrown vegetable consumption is estimated as follows:
Typical homegrown vegetable consumption = (200 g/day) (0.25)
« 50 g/day
Reasonable worst case homegrown vegetable consumption =
(200 g/day) (0.40) = 80 g/day.
The fraction of fruits that are homegrown, from Table 2-10,
ranges from 0.09 to 0.33 depending on type. The overall average
homegrown fraction from this table is 0.20, representing the typ-
ical portion. It was judged that a reasonable worst-case portion
would be 0.30. Using these fractions, total homegrown fruit con-
sumption is estimated as follows:
Typical homegrown fruit consumption = (140 g/day) (0.20) =
28 g/day
Reasonable worst-case homegrown fruit consumption =
(140 g/day) (0.30) = 42 g/day.
2.4 Consumption of Homegrown Beef and Dairy Products
Consumption of homegrown beef and dairy products is a potential path-
way of exposure to toxic chemicals. These food sources are contaminated
as animals consume contaminated soil, water, or feed crops. This chapter
focuses on homegrown food products, since any contaminated commercial
products would be widely distributed, thus reducing individual exposure
potential. (Note that population risks would not be changed by this
"dilution" effect. Thus, exposure assessors should also consider popula-
tion risks resulting from consumption of contaminated commercial prod-
ucts.) Data for consumption of both whole beef and dairy products and
2-24
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fat portions are provided, since many contaminants concentrate in the fat
portion of these foods. Additional exposure scenarios could be developed
using these data. Other meat groups, such as poultry and pork, are
potentially of interest to exposure assessors and will be added to future
editions of this handbook.
Average consumption rates and fat content data for all (homegrown and
bought) beef and dairy products are presented in Table 2-11, which has
been adapted from USEPA (1984b) by the addition of information from USEPA
(1984c, 1984d) and Fries (1986). Much greater "resolution" actually is
available in USEPA (1984c, 1984d) than is found in Table 2-11, since both
(USEPA 1984c, 1984d) are based on a USDA Nationwide Food Consumption
Survey (NFCS) conducted in 1977-78. The NFCS covered intake of
3,735 possible food items by 30,770 individuals characterized by age,
sex, geographic locations, and season of the year. A further description
of the survey design is given in USEPA (1984e).
The average beef fat consumption noted in Table 2-11 ranges from 14.9
to 26.0 g/70 kg/person-day, with a single high consumption estimate of
30.6 g/70 kg/person-day. Since this is a per capita value, it is likely
that families of beef producers who home slaughter would have higher
consumption rates. Milk fat consumption from all dairy products ranges
from 24.1 to 43 g/70 kg/person-day, with the lower end of this range
appearing best supported at present. Considering fresh milk only, milk
fat consumption is reported to average 8.9 to 10.7 g/70 kg/person-day,
with a single high consumption estimate of 35 g/70 kg/person-day, perhaps
appropriate for dairy farm families. [Age range-specific information is
available in both USEPA (1984c) and USEPA (1984d).]
According to USDA studies, in farm households where beef is homegrown,
the average percent of annual consumption of beef that is homegrown is
44 percent. This is based on a survey of 900 rural farm households (USDA
1966). Since the total amount of beef consumed averages approximately
100 g/day (see Table 2-11), it can be estimated that 44 percent of this
amount, 44 g/day, represents the average consumption rato for homegrown
2-25
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Table 2-11. Rates of Ingestion of Beef and Dairy Products
Total consumption
rate ± std. error
(g/70 kg/person-day)
Percentage
of fat
Fat consumption
rate ± std. error
(g/70 kg/person-day)
Reference
124a
110.7 * 1.7b
87.6 ± 1.1°
96.3s
66.8f
137.1 (high)f
Dairy products
15
23
(23)
(23)
22
22
19
26.0 :
(20.1 ±
(22.1)
14.9
30.6
0.3
0.3)c
USEPA (1981)
USEPA (1984c)
USEPA (1984d)
Berglund (1984)
Fries (1986)c
Fries (1986)
550 7.8
308.6 ± 5.3C (7.8)
431.6 ± 5.6° (7.8)
Fresh milk (only)
43
(24.1 d
(33.7)
0.4)3
USEPA (1981)
USEPA (1984d)
USEPA (1984c)
253.5 ± 4.9
305 (average)
1000 (high)
(3.5)
3.5
3.5
(8.9)
10.7
35.0
USEPA (1984d)
Fries (1986)
Fries (1986)
Per capita ingestion rate for the United States from national statistics.
Average consumption rate for all beef subcategories included in EPA's
Tolerance Assessment System.
Mean per capita ingestion rates. The categories established in USEPA (1984d)
exclude beef in meat mixtures (e.g., meat loaf), meat by-products (e.g.,
wieners), and organ meats. The basic data set underlying both USEPA (1984c)
and USEPA (1984d) was the 1977-78 USDA Nationwide Food Consumption Survey. The
basis for the difference in total dairy products consumption rates noted for
USEPA (1984c) and USEPA (1984d) has not yet been resolved.
Beef fat consumption rates in parentheses are calculated using percentages of
fat derived from USEPA (1984c).
Estimate derived from National Cattleman's Association.
This and succeeding values from Fries (1986) are reportedly derived from
Breidenstein (1984). Values are per capita ingestion rates for "average" and
"high" beef consumption populations.
9 Dairy fat consumption rates are calculated using percentages of fat derived
from USEPA (1981).
2-26
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beef (in farm households). Because this value is applied to a per capita
rate, it is likely to underestimate actual consumption by families who
home slaughter.
Similarly, in farm households where dairy products are homegrown, the
average percent of annual consumption that is of homegrown dairy products
is 40 percent (USDA 1966). Since the total amount of dairy products
consumed averages approximately 400 g/day (see Table 2-11), it can be
estimated that 40 percent of this amount, or 160 g/day, represents the
average consumption rate for homegrown dairy products.
These consumption rates represent long-term averages and are not rep-
resentative of the amounts consumed for a meal. The duration of exposure
to be used in conjunction with these rates is thus not the number of days
on which an individual actually consumes beef and dairy products, but
rather the entire period of time from the first to the last meal that
included homegrown beef and dairy products.
No data were available that presented the actual annual consumption
rates for homegrown beef and dairy products. Because of this, it is
recommended that the following two steps be considered by assessors in the
order presented:
(1) Conduct a survey of farmers in the area of concern and determine
the actual annual consumption rates of homegrown beef and dairy
products.
(2) Based on data presented in this section, an estimate of annual
average consumption rates can be made using per capita data.
This results in an estimated annual average consumption rate of
44 g/day for beef and 160 g/day for dairy products for
individuals consuming homegrown blef and dairy products. No data
are available to represent the 90th percentile consumption rate.
It is suggested that a consumption rate of 75 g/day for beef and
300 g/day for dairy products be used as reasonable worst case
rates until better data are available. These rates were de-
rived from the assumption that the percentage of annual consump-
tion that is homegrown is 75 percent for the 90th percentile
consumer.
2-27
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2.5 Consumption of Recreationallv Caught Fish and Shellfish
2.5.1 Background
Currently, a consumption rate of 6.5 g/day is used to represent the
average per capita nonmarine fish consumption rate. This value is the
value established for setting Ambient Water Quality Criteria (LISEPA 1980;
PTI 1987). This value is based on one-year survey data collected during
1973 and 1974 by NPD Research, Inc. The overall fish consumption rate
estimated from this survey was 14.3 g/day. Both of these values were
estimated on a per capita basis and represent the average over the entire
population including fish-eaters and nonfish-eaters. Thus, they
underestimate actual consumption rates for recreational fisherman and are
not accurate values to use when assessing exposure to recreational
fishermen at a specific site.
Accurate estimation of toxic chemical exposures of people who consume
fish from polluted water bodies requires an additional estimation of con-
sumption rates for recreationally caught fish by fishermen and their fami-
lies. Commercially caught fish are marketed widely, making the prediction
of an individual's consumption from a particular commercial source diffi-
cult. Since the catch of sport fishermen is not "diluted" in this way,
these individuals represent the population that is most vulnerable to
exposure by consumption of contaminated fish from one location.
2.5.2 Methods
Three surveys are available that represent national fish consumption
rates. Two additional local recreational surveys are also available that
*•
represent consumption rates for recreational fishermen. These surveys are
discussed below and summarized in Tables 2-12 and 2-13.
National recreational catch data for coastal areas in 1985 was
obtained by the National Marine Fisheries Service (NMFS) by direct surveys
of fishermen in the field and an independent telephone survey of house-
2-28
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Table 2-12. Summary of National Surveys
Parameter
Area studied
No. of people
Survey time
Type of fish
Recreational/commercial
Catch/diet survey
Statistics generated
NMFS
Coastal
200,000
Entire year
Marine
Recreational
Catch
Catch size
Survey
NPD/Javitz
National
24.652
2/mo. for year3
Marine/fresh
Both
Diet
Consumption rate
Pao/USDA
National
37,874
3 days
Marine/fresh
Both
Diet
Consumption rate
This is twice per month for one year.
2-29
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Table 2-13. Summary of Local Recreational Surveys
Parameter
Area studied
No. of people
Survey time
Type of fish
Catch/diet survey
Statistics generated
Survev
Puffer (1981) Pierce et al
Los Angeles Conrnencement Bay
1059 608
3/month for year3 July-November
Marine/fresh Marine/fresh
Diet Diet
Consumption rate distribution Consumption rate
. (1981)
distribution
a This is three times per month for one year.
2-30
-------
holds. For the Atlantic and Gulf coasts, approximately 41,000 field
interviews and 58,000 telephone interviews were conducted. For the
Pacific coast, approximately 38,000 field interviews and 73,000 telephone
interviews were conducted. Estimates were derived for six 2-month periods
in 1985. The recreational marine catch represented an estimated 30 per-
cent of the finfish landing used for food in 1985 in the U.S. and totaled
717 million pounds (NMFS 1986a). Total catch size by marine species,
seasonal variations in catch, and number of sport fishermen in Atlantic,
Gulf, and Pacific Coast regions are presented in Appendix 2A.
Consumption rates were not derived from these surveys.
Data on total fish consumption were obtained by a 1-year survey con-
ducted during 1973 and 1974 by NPD Research, Inc. and funded by the Tuna
Research Institute. The sample of 6,980 families represented the U.S.
population, i.e., they were weighted on the basis of a number of
census-defined controls, which included census region, family size,
income, children, race, and age. The head of each household completed a
diary of fish purchases twice monthly for 12 months (i.e., summarizing
fish diet for previous 2 weeks). The families answered questionnaires
concerning the date of meals containing fish, type and quantity of fish,
the number of servings consumed by each family member and the amount of
fish not consumed during the meal, packaging of the fish, and whether
fresh fish was recreationally caught or purchased. Meals eaten away from
home were also included in the survey. The total number of fish consumers
was 24,652, representing, on a weighted basis, 94 percent of U.S.
residents.
Using the data obtained by NPD Research, Inc., Javitz (1980)
calculated means (see Table 2-14) and 95th percentiles of monthly fish
consumption for fish consumers in the United States (assumed to be 94
percent of the population). The calculation of means, percentiles, and
percentages, which was performed on a weighted basis, with each person
contributing to the mean in proportion to his/her assigned survey weight
is explained in Appendix 2B. The mean and 95th percentile consumption
2-31
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Table 2-14. Mean Total Fish Consumption by Species3
Species
Hot reported
Aba lone
Anchovies
1L
bBass
Bluefish
bBluegills
Bon i to
bBuffalofish
Butterfish
bCarp
bCatfish (Freshwater)
bCatfish (Marine)
bCla«s
Cod
Crab, King
Crab, other than King
Crappie
bCroaker
Dolphin
Drums
Flounders
Groupers
Haddock
Hake
Halibut
bBerring
Kingf ish
bLobster (Northern)
Lobster (Spiny)
Mackerel, Jack
Mackerel, other than Jack
Mean
consumption
(g/day)
1.173
0.014
0.010
0.258
0.070
0.089
Q. 035
0.023
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
t
Species
bMuTlet
Oysters
Perch (Freshwater)
Perch (Marine)
bPike (Marine)
Pollock
Pompano
bRockfish
Sablefish
Salmon
bScallops
bScup
Sharks
Shrimp
bSraelt
Snapper
bSnook
bSpot
Squid and Octopi
bSunfish
Swordf ish
Tilefish
Trout (Freshwater)
bTrout (Marine)
Tuna, light
Tuna, White Albacore
bWhitefish
bOther finfish
bOther shellfish
Mean
consumption
(9/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 calculations in this table are based on responses to a survey conducted by NPD
Research, Inc. in which respondents were asked to report the species and amount consumed
during the month in which the survey was conducted. NPD Research, Inc. estimates that
these respondents represent, on a weighted basis, 94.0 percent of the population of U.S.
residents.
Designated as freshwater or estuarine species by Stephan (1980).
Source: Javitz (1980).
2-32
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rates derived by Javitz (1980) were 14.3 g/day and 41.7 g/day,
respectively. Note that this is one of the few diet studies where the
percentile data can be appropriately applied to long-term exposures since
the data were collected over the entire year. Unfortunately, the
distinction between recreationally caught and purchased fish was not
maintained in the original compilation of data.
The weighted mean and 95th percentile total fish consumption rates for
the U.S. population calculated by Javitz (1980) are presented by demo-
graphic variables on Table 2-15. Consumption of fish by Asian-American
people is significantly higher than that of other groups, a fact that is
confirmed by regional sportfishing consumption studies, which are dis-
cussed later. Other obvious differences in consumption rates are those
between sexes and between age groups. While males eat slightly more fish
than females, and adults eat more fish than children, the corresponding
difference in body weight would compensate for the different consumption
rates in exposure calculations. There appear to be no large differences
in regional consumption rates, although higher rates occur in the coastal
states. From Table 2-13, the overall calculated (weighted) mean fish con-
sumption rate for fish eaters is 14.3 g/day, and the 95th percentile rate
.is 41.7 g/day. These data were based on both purchased fish and
recreationally caught fish. Therefore, these data were not used for sub-
sequent calculations of fish consumption rates for recreationally caught
fish.
Pao et al. (1982) used consumption information obtained in the
1977-78 USDA Nationwide Food Consumption Survey to obtain frequency
distributions for consumption rates of various foods. The data were
collected during home interviews in which the respondent was asked to
recall food intake for the day of the interview, the day preceding, and
the day after the interview. Therefore, if the food was eaten at least
once in 3 days, the quantity consumed was recorded. Of 37,874
individuals with 3-day diet records, 24.5 percent had eaten fish and
shellfish at least once in 3 days.
2-33
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Table 2-15. Total Fish Consumption by Demographic Variables3
Demographic
category
Race
Caucasian
Black
Oriental
Other
Sex
Female
Hale
Age (years)
0- 9
10-19
20-29
30-39
40-49
50-59
60-69
70+
Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mounta in
Pacific
Mean
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
16.3
16.2
12.9
12.0
15.2,
13.0
14.4
12.1
14.2
l
Consumption
(q/Derson/dav)
Upper 95th
percent i le
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
46.5
47.8
36.9
35.2
44.1
38.4
; 43.6
32.1
39.6
The calculations in this table are based on responses to a survey conducted by NPD
Research, Inc. in which respondents were asked to report the species and amount consumed
during the month in which the survey was conducted. NPD Research, Inc. estimates that
these respondents represent, on a weighted basis, 94.0 percent of the population of U.S.
residents.
2-34
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The distribution for total consumption of fish and shellfish calcu-
lated by Pao et al. (1982) from the 1977-78 USDA consumption survey is
presented in Table 2-16. The median and 95th percentile fish consumption
rates for persons who included fish in their 3-day dietary intake (37 and
128 g/day, respectively) are more than twice those calculated from the
NPD data.
Since many individuals eat fish at a frequency of less than once every
3 days, the data obtained from the 3-day diet records cannot be used to
derive distributions of annual consumption rates. However, they should
provide accurate estimates of mean per capita ingestion rates since a very
large population was surveyed. Because these studies present per capita
consumption rates, the data are not representative of recreational
fishermen who consume larger amounts of fish than the general population.
Puffer (1981) conducted 1059 interviews with sport fishermen in the
Los Angeles harbor area. (The study is described in detail in Appendix
2C.) Puffer (1981) also observed higher consumption of recreationally
caught fish by Asian-American people than people in other ethnic groups.
Sport fishermen kept 67 to 89 percent of the finfish and 97 percent of the
shellfish catch. The distribution of total fish and shellfish consumption
by sport fishermen in the Los Angeles area is presented in Table 2-17.
The median fish and shellfish consumption rate was reported to be
37 g/day and the 90th percentile consumption rate was 225 g/day.
Another survey of sport fishermen was performed in Commencement Bay at
Tacoma, Washington, by Pierce et al. in 1981. The sample size, 304 fish-
ermen, was smaller than in the Puffer study, and the sampling frequency
was lower. Consumption rates by species, ethnic makeup of sport fisher-
men, and a detailed description of the study are contained in Appendix 2C.
Pierce et al. found that over half of the fishermen caught and consumed
fish weekly (see Table 2-17). The fishing frequencies can be used with
the mean daily total sportsfish consumption to calculate the fish consump-
tion rates on a yearly and daily basis for people in different fishing
frequency categories in Table 2-18. The 50th percentile consumption rate
2-35
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Table 2-16. Distribution of Fish and Shellfish
Consumption Rates of Fish Eaters
Ct
Total fish
+ shellfish
consumption3
Source Percentile (g/person/day)
Pao et al, (1982)
5
25
50
75
90
95
99
.8.00
20.00
37.00
57.00
94.00
128.00
215.00
USOA (1976) Mean 18.8
a Consumers who ate fish once in 3 days.
2-36
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Table 2-17. Cumulative Distribution of Total Fish/
Shellfish Consumption by Sport Fishermen
in the Metropolitan Los Angeles Area
Consumption rate
Percentile (g/person/day)
5 2.3
10 4.0
20 8.3
30 15.5
40 23.9
50 36.9
60 53.2
70 79.8
80 120.8
90 224.8
95 338.8
Source: Puffer (1981).
2-37
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Table 2-18. Yearly and Daily Fish Consumption Data by Recreational
Fishing Frequencies in Commencement Bay, Washington
Fishing
frequency
Daily
Weekly
Monthly
Bimonthly
Biyearly
Yearly
Percentage
9,40
51.30
18.45
5.25
5.40
10.85
Fish
consumption3
(kg/person/yr)
139.14
19.82
4.57
2.29
0.76
0.38
Fish
consumption
(g/person/day)
381.19
54.31
12.53
6.27
2.09
1.04
Percent ile
100.65
91.25
39.95
21.50
16.25
10.85
3 Mean daily consumption of the recreational catch x number of fishing
days per year.
Source: Pierce et al. (1981). •
2-38
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for recreatTonally caught fish lies within the range of 12 to 54 g/day,
which is in fair agreement with Puffer's estimate for median consumption
rates of recreationally caught marine fish. Fish species that spend a
portion of their lives in .estuaries (and therefore fall into the fresh-
water category) probably constitute a portion of the total recreational
catch consumption obtained in these coastal studies.
2.5.3 Conclusion
The consumption rate data from the Puffer (1981) and Pierce et al.
(1981) studies are considered representative of actual annual consumption
rates for recreational fishermen. Although these studies were limited to
the west coast, it is recommended that these values be used to represent
consumption rates for recreational fishermen in any area where there is a
large water body present and widespread contamination is evident. The
values to use under these conditions are the average of the 50th and 90th
percentile values reported by Puffer (1981)^and Pierce et al. (1981):
50th percentile 90th percentile Reference
^
36.9 g/day 224.8 g/day Puffer (1981)
23.0 g/day (est) 54.0 g/day (est) Pierce et al. (1981)
Average 30 g/day 140 g/day
Additional factors to consider when using data derived from these studies
include location, climate, and ethnic makeup of the fishing population.
Due to a lack of data, no specific values are recommended for small
water bodies or for areas of localized contamination in large water
bodies. For contaminated sites located in these areas, the following four
procedures are recommended for consideration by assessors in the order
presented:
(1) Interview local recreational fishermen in the affected area and
obtain actual consumption rates. This would provide data compar-
able to the Puffer (1981) and Pierce et al. (1981) studies.
Since consumption rates are likely to vary by region, climate,
location, and the ethnic makeup of the population, local surveys
would provide the most accurate data for exposure assessment
purposes.
2-39
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(2) Obtain productivity data for the area under consideration and
divide this total catch data by the number of recreational fish-
ermen (and family members) in the area. This will provide an
average consumption rate assuming productivity data and popula-
tion estimates were adequate.
(3) Estimate what portion of fish consumed in the local area is
caught in the local area. This diet fraction could then be
applied to the 50th and 90th percentile consumption rates
recommended for large water bodies.
(4) Develop standard exposure scenarios assuming the number of fish
meals eaten from the area per year and applying a meal size in
the range of 100 to 200 g/meal.
2.6 Soil Ingestion and Pica
2.6.1 Background
All children mouth or ingest substances that are not considered food.
This is usually a temporary behavior and is considered to be a normal
phase of childhood development (Barltrop 1966, Bicknell 1974, Lourie et
al. 1963). When this behavior persists beyond the age of about 18 months,
the child is said to practice pica (Barltrop 1966, Robischon 1971, Ziai
1983). The extent to which a child practices pica is highly variable
depending upon many factors, including nutrition, quality of care, and
parental relationship (Behrman and Vaughan 1983, Bellinger et al. 1986,
Bicknell 1967, Danford 1982, Danford et al. 1982, Forfar and Arneil 1984,
Glickman et al. 1981). As stated by Danford (1987),* "No sharp
demarcation exists between pathological states and normality, nor between
the age at which some form of pica is considered normal." It is not felt
that children who engage in pica are different from those who do not in
•jf-fc
any consistently predictable way (Feldman 1987). According to
Chisolm (1987), severe pica (i.e., abnormal ingestion of nonfood
D. Danford. Nutrition Coordinator Office, National Institutes
of Health, Bethesda, MD. Personal communication with J. Konz
(Versar) August 27, 1987.
H.D. Feldman. Duke University Medical Center. Personal
***
communication with J. Konz (Versar) August 7, 1987.
J. Chisolm. Francis Scott Key Medical Center, Baltimore, MD.
Personal communication with J. Konz (Versar) July 27, 1987.
2-40
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substances) is representative of grossly disturbed or mentally retarded
children and will not be seen in the "normal" population.
As commonly used in the medical, behavioral, and psychological litera-
ture, however, pica refers to the ingestion of nonfood substances (see
Table 2-19). This ingestion may be deliberate or may occur through the
mouthing of objects or hands (Gallacher et al. 1984, Lepow et al. 1975,
McAlpine and Singh 1986, Walker and Roberts 1983).
The literature reports a wide variety of substances that have been
ingested including: soil, clay, sand, dust, grass, leaves, plaster, hair,
starch, paint chips, string, soap, polish, cloth, insects, feces, ashes,
cigarettes, matches, charcoal, plastic, crayons, wood, metal, powders,
chalk, and paper (Adams and Sutker 1984, Albin 1977, Bellinger et al.
1986, Illingworth 1983, Lourie et al. 1963, Mahaffey 1981, Ziai 1983).
The most common form of pica (in the study that differentiated among the
objects ingested)'was dirt eating, which occurred in 23 percent of the
children studied (Cooper 1957). The range of substances mouthed or
ingested decreases with increasing age (Barltrop 1966). Pica appears to
be more common in populations of low socioeconomic status (Behrman and
Vaughan 1983, Danford 1982, Glickman et al. 1981). Groups at high risk
include infants, young children, and blacks — especially those who are
brain-damaged, epileptic, or mentally retarded. Sources of information
on pica are presented in Appendix 2D.
In conclusion, pica is defined in many ways (see Table 2-19). For
purposes of this handbook, pica is defined as an abnormally high soil
ingestion rate. No quantitative ingestion rates are recommended since
children with known pica behavior have not been studied. The aim of this
section is to discuss factors relevant to normal soil ingestion that
occurs as a result of normal mouthing or unintentional hand-to-mouth
activity. "Abnormal" soil ingestion (i.e., pica) is believed to be uncom-
mon and may need to be addressed in cases involving sensitive population
considerations.
2-41
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Table 2-19. Definitions of Pica Used in the Research Literature
Reference
Pica definition
Adams and Sutker 1984
Albin 1977
Anonymous 1975
Barltrop 1966
Behrman and Vaughan 1983
Blcknell 1974
Bruhn and Pangborn 1971
Cooper 1957
Crosby 1976
Feldtean 1986
Forfar and Arneil 1984
Gallacher et al. 1984
Glickman et al. 1981
Illingsworth 1983
Kaplan and Sadock 1985
Keith et al. 1970
Lepow et al. 1975
Levine et al. 1983
Lourle et al. 1963
Hace and Knight 1986
Hayer 1970
McAlpine and Singh 1986
Persistent eating of nonnutritive substances
Ingest ion of nonnutritive substances
Eating of substances usually considered inedible
Persistent ingest ion of nonedible substances after the age of 18 months
Repeated and chronic ingestion of inedible substances
Eating objects not usually considered food
Ingestion of nonfood items
Habit of eating clay, plastics, ashes, charcoal, etc.
Compulsive eating of anything
Repeated eating of a nonnutritive substance for at least 1 month
Scavenging ... incessant eating
Ingestion of alien, nonfood substances
Habitual ingestion of nonfood substances
Dirt eating
Persistent ingestion of nonnutritive substances
Denotes perversion of the appetite, ingestion of unnatural substances
Ingestion or mouthing of nonfood items
Stubborn pursuit and ingestion of nonedible matters [sic]
Craving for ingestion of a particular substance
Ingestion of inedible objects
Persistent ingestion of substances commonly considered unfit as food
Persistent eating of nonnutritive or inedible substances
2-42
-------
Table 2-19. (continued)
Reference
Pica definition
Pueschel et al. 1978
Robischon 1971
Sayetta 1986
Vermeer and Frate 1979
Walker and Roberts 1983
Walter et al. 1980
Ziai 1983
Habitual intake of nonfood substances by young children beyond the oral
stage of development
Habitual ingest ion of nonedible substances
Persistent, compulsive ingestion of any substance
(Geophagia) the deliberate consumption of earth
Ingestion of inedible substances
Craving nonfood objects ;
Perversion of the appetite with persistent and purposeful ingestion of
unsuitable substances seemingly of no nutrient value
2-43
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2.6.2 Methods
Several studies have been conducted to characterize soil ingestion by
children. Most of the earlier studies attempted to estimate the amount
of soil ingested by measuring the amount of dirt present on children's
hands and making generalizations based on behavior. Lepow et al. (1975)
measured hand dirt by applying preweighed adhesive labels to the hands
and weighing the amount of dirt that was removed. These researchers also
observed "mouthing" behavior and reported that a child would put fingers
or other "dirty" objects into his mouth about 10 times a day. The authors
acknowledged, however, that the amount of hand dirt measured with this
technique was an underestimate, since dirt trapped in skin folds and
creases was not removed by the adhesive label.
Duggan and Williams (1977) estimated the amount of dust that would be
retained on the forefinger and thumb by removing a small amount of dust.
from a weighed amount, rubbing the forefinger and thumb together, and-
reweighing to determine the amount retained on the finger and thumb. They
then assumed that a child would suck his/her finger or thumb 10 times a
day.
Day et al. (1975) estimated the amount of soil that might be ingested
by measuring the amount of dirt that was transferred to a sticky sweet
during 30 minutes of play. They then assumed that a child might eat from
2 to 20 such sweets per day.
During the past 2 years, studies have been conducted using a new
methodology, that of measurement of trace elements in feces and soil which
are believed to be poorly absorbed in the gut. These include studies by
Binder et al. (1986) and Clausing et al. (1987). Similar studies are
currently being conducted by USEPA and by the University of Massachusetts.
Binder et al. (1986) studied the ingestion of soil among children 1
to 3 years of age who wear diapers. The children studied were 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
2-44
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65 children (42 males and 23 females), and composited samples of soil were
obtained from the children's yards. Both excreta and soil were analyzed
for aluminum, silicon, and titanium, elements thought to be poorly
absorbed in the gut and to have been present in the diet only in limited
quantities, making them reasonable to use as tracers in a mass-balance
calculation. Both soil and excreta measurements were obtained for
59 children. Using a standard assumed fecal dry weight of 15 g/day, soil
ingestion by each child was estimated using each of the three tracer
elements (assuming no absorption or nonsoil source of these elements).
All ingestion rates were corrected to account for fecal sample losses.
Clausing et al. (1987) conducted a soil ingestion study with Dutch
children using a tracer element methodology similar to that of Binder et
al. (1986). Aluminum, titanium, and acid-insoluble residue (AIR) contents
were determined for fecal samples from children, aged 2 to 4, attending a
nursery school, and for samples of playground dirt at that school. Fecal
samples were obtained daily over a 5-day period for the 18 children
examined. Using the average soil concentrations present at the school,
and assuming a standard fecal dry weight of 10 g/day, the authors
calculated mass-balance estimates of soil ingestion for each material.
In a second sample, Clausing et al. (1987) collected fecal samples for
six hospitalized, bedridden children. These children served as a control
group, representing children who had very limited access to soil.
2.6.3 Results
(1) Age of concern for soil inqestion. Based on observational data,
children are most likely to ingest soil from ages 1 to 6 (Walter et al.
1980, Cooper 1957, Charney et al. 1980, Sayre et al. 1974). Several
researchers have investigated the age of occurrence of soil .ingestion and
the duration of the behavior. Soil ingestion is usually established by
the 18th month and abnormal ingestion behavior may persist until age 6 or
7 (Walter et al. 1980, Cooper 1957, Charney et al. 1980, Sayre et al.
1974). Ingestion of nonfood .substances beyond age 6 or 7 is usually the
2-45
-------
result of inadvertent ingestion (e.g., from soil or dust present on fruits
and vegetables) or developmental problems (Lourie et al. 1963, Paustenbach
et al. 1986). As will be discussed subsequently,'Several investigators
have proposed different so.il ingestion rates for different age groups.
(2) Incidence of soil ingestion. All children will inadvertently in-
gest soil as part of a normal mouthing behavior. The incidence of abnor-
mal soil ingestion behavior is more difficult to generalize. Statistics
on the incidence of abnormal soil ingestion behavior are difficult to
interpret for several reasons. Most information about abnormal soil
ingestion behavior is derived from clinical data rather than research
data. Because of this, the data base is not conclusive for the general
population. For example, the occurrence of abnormal soil ingestion
behavior is usually not a part of a child's medical history unless lead
poisoning is suspected (Zamula 1986). Therefore, the actual incidence
rate of abnormal soil ingestion behavior among children cannot be derived
from the clinical data. The literature contains information based on
several surveys of abnormal ingestion behavior; however, the groups were
usually selected from a particular population (e.g., the group of children
coming to a particular clinic) and are not necessarily representative of
the general population. These surveys used different definitions of
abnormal ingestion behavior, which resulted in inconsistencies in the
evaluation of the results. There is also some evidence that the results
may be biased because the subjects or the subjects' parents were reluctant
to admit to abnormal ingestion behavior. The information obtained from
these surveys is summarized in Table 2-20. According to these studies,
the incidence rate for abnormal ingestion behavior in these selected
groups of children range's from 10 to 57 percent.
The incidence of abnormal ingestion behavior in children differs for
different subpopulations. The incidence rate appears to be higher for
black children than for white children. Approximately 30 percent of black
children aged 1 to 6 years are reported to have abnormal ingestion behav-
ior, compared with 10 to 18 percent of white children in the same age
2-46
-------
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group (Danford 1982). There does not appear to be any sex difference in
the incidence rates for males or females (Kaplan and Sadock 1985).
Abnormal soil ingestion behavior appears to be more common in rural areas
(Vermeer and Frate 1979); therefore, more children in these areas can be
expected to practice this behavior.
Mentally retarded children have been identified as being especially
prone to practice abnormal ingestion behavior. A child is considered
mentally retarded if intelligence is below an IQ of 70 and behavioral
development (e.g., eating, dressing, etc.) shows deficiencies (American
Psychiatric Association 1980). Based on national statistics on mental
retardation, approximately 9 percent of the 7 million mentally retarded
people in the United States (or approximately 630,000). are children aged
1 to 6 years (Bureau of the Census 1986, Bouthilet 1987).* Of these,
89 percent are considered mildly retarded,.6 percent are moderately
retarded, 3.5 percent are severely retarded, and 1.5 percent are
profoundly retarded. Less than 2 percent of these children are
institutionalized, predominantly those in the severely and profoundly
retarded groups. The others liVe with their families, or in residential
facilities within their communities (Bouthilet 1987).* Although it would
be useful to know how the severity of abnormal ingestion behavior is
distributed among the different classes of mentally retarded children
(i.e., whether the problem is worse in the severely and profoundly
retarded groups), these data have not been collected (Bouthilet 1987).*
Data from mentally retarded adults show a 10 percent incidence in mildly
retarded adults and a 33 percent incidence in severely retarded adults
(Feldman 1986). However, these rates may. not be relevant to children.
In general, it can be assumed that abnormal ingestion behavior is more
frequent and more severe in mentally retarded children than in children
G. Bouthilet, Research Coordinator, President's Committee on Mental
Retardation, Washington, DC. Personal communication with J. Konz
(Versar) August 17, 1987.
2-49
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in the general population (Behrman and Vaughan 1983, Danford 1982, Forfar
and Arneil 1984, Illingworth 1983, Sayetta 1986). However, the incidence
rate in this subpopulation has not been reported.
As previously discussed, the incidence rate data are primarily based
on abnormal ingestion behavior among selected (e.g., clinical, rural, low
income) groups and are not representative of the general population.
Based on the data from the four tracer studies (Binder et al. 1986,
Clausing et al. 1987, USEPA, and University of Massachusetts), only one
child out of the 240 involved in all of these studies ingested an amount
of soil significantly greater than the range for other children.
Although these studies did not include all populations and were
representative of short-term ingestions only, it will be assumed that the
incidence rate of abnormal soil ingestion behavior in the general
population is extremely low.
(3) Amount ingested. The normal amount of soil ingested by children
has been investigated by several researchers whose work has been summar-
ized by Paustenbach et al. (1986). These researchers have estimated dif-
ferent amounts ingested depending upon the age of the child. The environ-
mental setting is also an important variable; rural areas appear to be
associated with higher ingestion rates (Vermeer and Frate 1979). Esti-
mates of the amount of soil ingested are presented in Table 2-21. The
support of these estimates varies widely from judgment to experimental
evidence.
Hawley (1985), using existing literature, developed scenarios for
estimating exposure of young children, older children, and adults to
contaminated soil. His approach to estimating levels of ingestion is
presented here (see Table 2-22). Each year was divided into two activity
periods, Hay through October, when individuals were assumed to spend much
J. Schaum, USEPA. Personal communication with J. Konz (Versar)
March 31, 1988.
2-50
-------
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2-51
-------
Table 2-22, Estimates of Soil Ingestion from Dermal Contact
Scenarios
Exposure
(rag/day)
Days/year
activity
Annual
average
.(mg/day)
Young child (2.5 years old)
Outdoor activities (summer)
Indoor activities (summer)
Indoor activities (winter)
Older child (6 years old)
250
50
100
130
182
182
- ' '•'
90
25
50
; IBS
Outdoor activities (summer)
Indoor activities (year-round)
50
3
152
365
21
_3
24
Adult
Work in attic (year-round)
Living space (year-round)
Outdoor work (summer)
110
0.56
480
12
365
43
3.7
0.56
_57
61.26
Source: Hawley (1985).
2-52
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time outdoors, and November through April, when weather conditions were
assumed to eliminate outdoor exposure to soil. The following estimates
were made by Hawley (1985):
1. Young children (2.5 years old, 13.2 ka)
Outdoor activity, May through October, 5 days/week: 250 mg/day.
Estimate based on analysis of data from Lepow et al. (1974, 1975),
who hypothesized 250 mg ingestion after experiments showing that
dirt from a 21.5 cm* area of a child's hand typically had a
mass of 11 mg. Additionally, Roels et al. (1980) measured contam-
ination of children's hands by metal contaminants of soil while
the children were active on playgrounds. These data led to an
estimate of 40 to 180 mg dirt being present on the dominant hand
of an 11-year-old (said to be equivalent in area to both hands of
a 2.5-year-old).
Indoor activity, May through October: Child assumed to ingest
50 mg of household dust each day. Reference was made to the
previously cited experimental data.
Indoor activity, November through April: 100 mg/day ingestion
assumed because of the longer period of indoor activity.
2. Older child (6 years old. 20.8 kal
Outdoor activity, May through October: 50 mg/day. Using the
surface dust value cited from Lepow et al. (1974) of 0.51 mg/cm2
on skin, a child is assumed to ingest dirt from an area equal to
the area of the fingers on one hand.
Indoor activity, year-round: 3 mg/day. Indoors, the child is
assumed to have dermal dirt present at the reduced level of
0.056 mg/cmS which is the quantity of dirt estimated by the
authors to be present on surfaces within the home. Dirt from
inside surfaces of hands is assumed to be ingested.
3. Adult (70 kal
Work in attics or other uncleaned areas of a house, 12 days/year:
110 mg/day. Estimate based on ingestion of a 50-^m-thick dust
layer from the inside surfaces of the fingers and thumb of one
hand while eating food or handling cigarettes. Data from Wolfe
et al. (1974) are cited to support dust intake while smoking
cigarettes.
Living space activities: 0.56 mg/day. Adults' hands are assumed
to have dust contamination equal to that on indoor surfaces
(0.056 mg/cm*), and dust is ingested from a 10 cm2 area of
skin while eating or smoking.
2-53
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Outdoor activities, May through October: 480 mg/active day. The
adult is assumed to be engaged in yard work or other outdoor phys-
ical activity for 8 hours/day, 2 days/week. The estimate is based
on ingesting a 50 ^m-thick layer of soil from the inside sur-
faces of the fingers and thumb of one 'hand twice daily. These
estimates are summarized in Table 2-21.
The average quantity of soil ingested by the children in the Binder
et al. (1986) study was estimated at 181 nig/day (range 25 to 1,324)
(aluminum tracer); 184 mg/day (range 31 to 799) (silicon tracer); and
1,830 mg/day (range 4 to 17,000) (titanium). The overall soil ingestion
estimate based on the minimum of the three individual element ingestion
estimates for each child was 108 mg/day (range 4 to 708).
The authors were not able to explain the difference between the
results for titanium and for the other two elements, but speculated that
other dietary sources would account for the increased levels. The fre-
quency distribution graph of soil ingestion estimates based on titanium
shows that a group of 21 children had particularly high titanium values,
>1,000 mg/day; the remainder of the children showed titanium
ingestion estimates at lower levels, with a distribution more comparable
to that for the other elements.
The average quantity of soil (based on individual tracer elements)
ingested by children in the Clausing et al. (1987) study was as follows:
aluminum, average 230 mg/day (range 23 to 979); AIR, average 129 mg/day
(range 48 to 362); and titanium, average 1,430 mg/day (range 64 to
11,620). As in the Binder et al. (1986) study, a fraction of the
children (6/19) showed titanium values of well above 1,000 mg/day, with
most of the remaining children showing substantially lower values. Based
on the minimum of the three chemical measurements for each child, an
estimate of 105 mg/day, with a range of 23 to 362, was obtained.
A mass-balance calculation for the hospitalized children in the
Clausing et al. (1987) study yielded estimates of 56 mg/day based on
aluminum. For titanium, three of the children had estimates well in
excess of 1,000 mg/day, with the remaining three children in the range of
28 to 58 mg/day. The data on hospitalized children suggest a major
2-54
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nonsoil source of titanium for some children, and may suggest a
background nonsoil source of aluminum. However, conditions specific to
hospitalization, e.g., medications, need to be considered. AIR
measurements were not reported for the hospitalized children.
Speculation as to the source of titanium includes the white coloring in
(disposable) diapers and several other items, but this has not as yet
been investigated.
The amount of soil ingested by children with abnormal soil 'ingestion
.behavior has not been measured. Although no values have been reported in
the literature, some evidence suggests that a rate on the order of 5 to
10 g/day may not be unreasonable. The value of 5 g/day was used by USEPA
in the risk assessment for TCDD (USEPA 1984b). A value of 10 g/day was
used by the USDA in conducting exposure assessments in relation to the
use of sludge in gardens and soils. This value is not published but is
used as a general rule of thumb (Chaney 1987).*
In conducting its exposure assessment for TCDD, the Centers for
Disease Control also investigated the potential for exposure through the
soil ingestion route. In this study, a value of 10 g/day was suggested
as the amount of soil that a child with abnormal soil ingestion behavior
might ingest (Kimbrough et al. 1984).
Two additional studies may provide more recent information on the
subject of the amount of soil ingested by children. One study being
conducted at the University of Massachusetts involves the development of
a soil ingestion profile. The other is a study being carried out in
Thailand that investigates the amount of clay that is eaten by children
and adults who intentionally ingest the clay. The University of
Massachusetts study was completed in 1988 (Calabrese et al. 1989) but was
not available for review for this report. Results from the study in
Thailand should be available in 1989.
R.L. Chaney. U.S. Agricultural Research Service, Beltsville, MD.
Personal communication with J. Konz (Versar) August 17, 1987. •
2-55
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Another source of data on abnormal ingestion behavior is the second
National Health and Nutrition Examination Survey. This survey collected
data on the medical history of 6,839 people aged 6 months to 11 years.
The medical history contained information on abnormal ingestion behavior;
however, the data have not yet been published.
The data from the tracer element studies, Binder et al. (1986) and
Clausing et al. (1987), provide support for a preliminary estimate of
average soil ingestion by children on the order of 100 to 200 mg/day,
consistent with the "low" estimate reported by other researchers (see
Table 2-21). These estimates are based on findings with silicon or AIR
and aluminum. Estimates based on a titanium tracer are higher by a
factor of 5 to 10 and were not used to derive the average value. This
discrepancy has not been explained, but may be due to inadvertent sample
contamination or to dietary sources other than soil. Recent unpublished
data indicate that dietary contribution should be considered in calcula-
tions of soil ingestion using tracer elements (USEPA, University of
Massachusetts). Hawley (1985), who estimated quantities of soil likely
to be present on skin and subsequently ingested, also arrived at an esti-
mate in the above range. It should be noted that Hawley's approach would
not address children who deliberately ingest dirt or mouth soiled objects.
Binder et al. (1986) and Clausing et al. (1987) also provided some
limited information on the upper range of soil ingestion in children.
With the exception of the titanium data, the two studies provide evidence
of an upper range of soil ingestion in children on the order of
800 mg/day or more. It should be noted that both studies had limited
sample sizes and that neither specifically included children with
abnormal soil ingestion behavior. Again, estimates based on titanium
would be substantially higher, on the order of 20 g/day.
Calabrese et al. (1987) have recently summarized the data on soil
ingestion from available studies. Based on the data and the authors'
opinions, various levels of consumption have been suggested to represent
the range of soil ingestion rates experienced by different categories of
2-56
-------
children. Level 1 represents the child with the lowest tendency to inges-
tion soil, while Levels 2 and 3 are intermediate levels. Level 4 repre-
sents the child with abnormal soil ingestion behavior. These results are
presented in Table 2-23. As discussed by Calabrese et al. (1987), a high
level of uncertainty is associated with all values.
The EPA is sponsoring a study of soil ingestion by children, using
the tracer element methodology. Preliminary research has included a study
in miniature swine to assess the assumption that the tracer elements are
poorly absorbed, and to provide an experimental check on mass-balance
calculations.
The study in children includes a pre-pilot study to test field methods
and to address possible nonsoil sources of titanium. A randomly selected
sampling of 100 children was selected to provide a population-based esti-
mate of soil ingestion in one location (the Richland, Washington, area).
Dietary contributions to tracer element intake will be measured in this
study. The field work for this study is complete and the results will be
available in late 1989.
Inadvertent soil ingestion occurs among adults as well as children.
While actual measurements of adult soil ingestion have not been made,
Hawley (1985) estimated that soil ingestion could be 61 mg/day, based
largely on unsupported assumptions regarding activity patterns and
corresponding ingestion amounts. Calabrese et al. (1987) have suggested
a range from 1 to 100 mg/day. These ingestion rates are less than the
100 to 1,000 mg/day measured in children by Binder et al. (1986) and
Clausing et al. (1987). However, the longer exposure periods for adults
(ages 7 to 70) suggest that total adult soil ingestion quantities could
be of the same magnitude as those for children (ages 2 to 6) even if
ingestion rates are lower.
2.6.4 Conclusion
Based on this review of the limited data now available, the studies
of Binder et al. (1986) and Clausing et al. (1987) appeared to be the
2-57
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Table 2-23. Estimates of Soil Ingestion by
Age and Degree of Ingestion
Age
0-9 months
9-18 months
1.5-3.5 years
3.5-5.0 years
5-18 years
18 years
Soil inqestion
Level 1 Level 2
0 0
5 50
10 200
5 50
1 10
1 10
ranqe (ma/dav)
Level 3 Level 4
0 . 0
50 1,000
1,000 10,000
50 1,000
10 100
10 100
a Level 1 - Represents child with low tendency to ingest soil;
based in part on data from Rabinowitz and Bellinger
(1986).
Levels 2 - Represent child with intermediate tendency to ingest
and 3 soil; based in part on data from Binder et al. (1986)
and Clausing et al. (1987).
Level 4 - Based on CDC estimates (Kimbrough et al. 1984),
considered to be overestimates of normal soil ingestion
behavior. Hay be representative of child with a high
tendency to ingest soil.
Source: Caldbrese et al. (1987).
2-58
-------
most reliable. These studies suggest the following values for soil inges-
tion: average soil ingestion in the population of young children (under
the age of 7) is estimated at approximately 0.1 to 0.2 g/day. For cal-
culation purposes, an estimate of 0.2 g/day is suggested as an average
value. An upper-range ingestion estimate among children with a higher
tendency to ingest soil materials is 0.8 g/day. These estimates are
based on data using silicon, aluminum, and AIR as trace elements. The
reason for the higher estimates for titanium are likely to be due to non-
soil factors such as other dietary factors. The upper ends of the range
values for silicon, aluminum, and AIR were used for the upper bound esti-
mate because of the small sample size used in these studies (i.e., cannot
distinguish 90th percentile).
Soil ingestion rates for children who exhibit abnormal soil Ingestion
behavior and for people older than 6 cannot be recommended because of the
lack of data.
2-59
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2.7 References
Adams HE, Sutker PB. 1984. Comprehensive handbook of psychopathology.
New York: Plenum Press.
Albin JB. 1977. The treatment of pica (scavenging) behavior in the
retarded: A critical analysis of implications for research. Mental
Retardation: August:14-17.
American Psychiatric Association. 1980. Diagnostic and statistical
manual of mental disorders,- 3rd ed. Washington, DC: American
Psychiatric Association.
Anonymous. 1975. The problem of pica. The Medical Journal of
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2-67
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APPENDIX 2A
National Marine Fisheries Service
Recreational Fishing Data
2-69
-------
Appendix 2A
National Marine Fisheries Service
Recreational Fishing Data
The National Marine Fisheries Service (NMFS) estimated recreational
marine catch from intercept surveys of fishermen in the field and an
independent telephone survey of households. In 1985, the marine
recreational finfish catch in the United States, excluding fish caught in
Alaska and Hawaii and Pacific Coast salmon, was an estimated 425 million
fish weighing 717.3 million pounds (NMFS 1986a). The estimated number of
marine recreational fishermen, which has been relatively stable over the
last few years, is 17 million. The size of the population that consumes^
the national recreational marine catch has not been measured.
Recreational marine fish catch data from the Atlantic and Gulf Coasts
for 1985 is presented by species and region, in Table 2A-1 (NMFS 1986b).
Catch quantities include catch brought ashore in whole form and available
for identification during the interview; fish not available for identifi-
cation and those released alive, discarded dead, filleted, or used for
bait are excluded. Weights (including inedible portions) and lengths of
the identified fish were measured. Of the approximately 114 million kilo-
grams of fish caught on the Atlantic and Gulf Coasts, the smallest portion
of the total catch was made in the North Atlantic. Over one half of the
recreational marine catch occurred within 3 miles of the shore or in in-
land waterways. The data in Table 2A-2 demonstrate the effect of season
and local climate on the size of recreational catch. Total catch weight
for the Atlantic declines significantly from November throughout February,
but the Gulf Coast catch rate remains fairly stable throughout the year.
Estimated total numbers of sport fishermen by state and subregion are
given in Table 2A-3. These totals may include fishermen who participate
but take no fish home for consumption.
Similar data for the Pacific Coast are presented in Tables 2A4
through 2A6 (NMFS 1986c). Table 2A-4 shows that over 80 percent of the
12.7 million kg total Pacific Coast recreational catch (excluding Hawaii
2-70
-------
and Alaska occurs along the California coast. As in the Atlantic, the
majority of the recreational marine catch is taken within 3 miles of the
shore or from inland waterways. Table 2A-5 shows seasonal fluctuations
in the recreational catch; May through October are the peak recreational
fishing months for the Pacific Coast. The estimated total number of
participants is given according to regions in Table 2A-6.
2-71
-------
Table 2A-1. Estimated Weight of Fish Caught (Catch Type A)a by Marine
Recreational Fishermen by Species Group and Subregion
Species group
01.
02.
03.
04.
05.
06.
07.
08.
09.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30,
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
Sharks
Sharks, Dogfish
Skates/Rays
Eels
Herrings
Freshwater Catf ishes
Saltwater Catf ishes
Toadf ishes
Atlantic Cod
Atlantic Tomcod
Pollock
Silver Hake
Searobins
Sculpins
White Perch
Striped Bass
Black Sea Bass
Groupers
Sea Basses
Bluefish
Jack Crevalle
Blue Runner
Greater Amberjack
Florida Pompano
Jacks
Dolphins
Gray Snapper
Red Snapper
Lane Snapper
Vermilion Snapper
Yellowtail Snapper
Snappers
Pigfish
White Grunt
Grunts
Scup
Pinefish
Sheepshead
Red Porgy
Porgies
North
Atlantic
(1.000 kg)
*b
c
—
22
19
*
*
—
2,128
22
94
—
22
—
—
169
9
*
—
9,283
*
*
*
*
*
*
it
*
*
*
*
*
*
*
*
1.441
*
*
*
*
Mid-
Atlantic
(1,000 kg)
2,165
126
—
73
31
138
*
18
311
—
—
21
70
—
82
149
1,084
*
10,733
*
*
*
—
—
--
*
*
*
*
*
*
5
*
—
1,537
—
*
*
—
South
Atlantic
(1,000 kg)
1,521
—
*
--
,—
161
--
*
*
*
*
*
*
14
--
1,125
947
29
7,108
230
56
668
81
67
1,745
347
803
31
138
36
74
100
43
95
—
86
413
107
89
Gulf
(1,000 kg)
1,618
A
--
--
--
226
—
*
*
*
*
--
*
*
—
843
2,881
17
213
247
42
925
—
257
262
369
1,865
47
54
197
68
19
605
149
*
46
1,088
126
66
All
regions
(1,000 kg)
5,305
148
110
95
54
142
387
20
2,439
22
128
23
92
—
104
332
3,061
3,827
47
27,337
478
98
1,593
93
325
2,040
716
2,667
78
192
232
142
124
648
245
2,977
132
1,501
233
156
2-72
-------
Table 2A-1. (continued)
Species group
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
Spotted Seatrout
Weakfish
Sand Seatrout
Si Iver Perch
Spot
Kingf ishes
Atlantic Croaker
Black Drum
Red Drum
Drums
Mullets
Barracudas
Tautog
Gunner
Little Tunny /ATL Bon i to
Atlantic Mackerel
King Mackerel
Spanish Mackerel
Tunas/Mackerels
Summer Flounder
Gulf Flounder
Southern Flounder
Winter Flounder
Flounders
Triggerf ishes/Fi lef ishes
Puffers
Other Fishes
TOTALS
North
Atlantic
(1,000 kg)
*
—
*
*
*
*
it
*
*
*
*
if
355
11
—
479
*
*
--
202
*
*
2,380
—
*
-- .
108
18,045
Mid-
Atlantic
(1,000 kg)
„
1,969
*
*
1,248
17
527
.
*
__
7
*
1,758
—
208
988
--
*
2,328
3,966
*
—
5,837
21
—
30
282
36,074
South
Atlantic
(1,000 kg)
931
157
*
19
1,222
485
441
295
610
49
130
230
--
*
506
it
4,571
425
5,401
597
--
210
*
--
165
36
1.180
33,876
Gulf
(1,000 kg)
3,222
*
1.392
20
4
298
821
785
2,217
196
196
240
*
*
321
*
684
528
115
*
240
734
*
50
203
—
1,130
25,684
All
regions
(1,000 kg)
4,178
2,218
1.392
39
2,473
800
1,788
1,311
2,828
246
333
470
2,116
15
1,062
1,467
5,258
953
8,985
4,765
245
948
8,217
77
379
70
2.701
113,679
a Catch Type A is an estimate of part of the total catch based on fish brought ashore in whole
form, available for interviewer identification and enumeration, from which samples of lengths
and weights were obtained.
An asterisk (*) denotes none reported.
A dash denotes no information 'available.
2-73
-------
Table 2A-2. Estimated Weight of Fish Caught (Catch Type A)a by
Marine Recreational Fishermen by Wave and Subregion
January 1985 - December 1985
Wave
Subregion
Weight
Jan/Feb
Mar/Apr
Hay/Jun
Jul/Aug
Sep/Oct
Nov/Dec
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
Guld
TOTAL
North Atlantic
Mid Atlantic
South Atlantic
Gulf
TOTAL
2,345
4.355
6,700
1,348
' 8,063
9,884
2.315
21,609
3,818
9,339
6,325
5.096
24,577
4,928
6,221
4,002
5.403
20,554
7,516
10,259
8,731
4.720
31,227
436
2,193
2,588
3.795
9,012
GRAND TOTAL
113,679
Catch Type A is an estimate of part of the total catch based on fish
brought ashore in whole form, available for interviewer identification
and enumeration, from which samples of lengths and weights were
obtained.
2-74
-------
Table 2A-3. Estimated Number of Participants in Marine Recreational Fishing
by State and Subregion for the Atlantic and Gulf Coasts
January 1985 - December 1985
Subregion State
North Atlantic Connecticut
Std. Err.
Maine
Std. Err.
Massachusetts
Std. Err.
New Hampshire
Std. Err.
Rhode Island
Std. Err.
TOTALS
Std. Errs.
Mid Atlantic Delaware
Std. Err.
Maryland
Std. Err.
New Jersey
Std. Err.
New York
Std. Err.
Virginia
Std. Err.
TOTALS
Std. Errs.
Coastal
participants
(thousands)
284
203
125
94
760
620
18
11
188
116
1.37,4
669
38
' 29
366
248
625
542
612
458
528
347
2,168
828
Non-coastal
participants
(thousands)
*a
*
38
32
110
75
1
1
*
*
149
81
*
«
18
11
4
5
20
32
71
^48
114
58
Out of
state
(1)
(thousands)
78
42
115
88
710
333
22
12
362
149
91
56
213
109
1,170
747
72
75
310
163
Total
participants
in state
(1)
(thousands)
362
208
277
133
1,580
707
41
16
550
189
128
63
597
271
1,799
923
704
465 ,
909
387
*An asterisk denotes none reported.
(1) = not additive across states. One person can be counted as "out-of-state" for more than one
state.
2-75
-------
Table 2A-4. Estimated Weight of Fish Caught (Catch Type A)a by Marine
Recreational Fishermen by Species Group and Subregion
January 1985 to December 1985
Southern
California
Species group (1,000 kg)
01.
02.
03,
04.
05.
06.
07.
08.
09.
10.
11.
12.
13.
14.
15.
16.
17.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28,
29.
30.
31.
32.
33.
34.
35.
38.
37.
38.
39.
Spiny Dogfish
Sharks, Other
Sturgeons
Pacific Herring
Northern Anchovy
Surf Smelt
Smelts, Other
Pacific Cod
Pacific Tomcod
Walleye Pollock
Pacific Hake
Silvers ides
Jacksmelt
Striped Bass
Kelp Bass
Spotted Sand Bass
Barred Sand Bass
Yellowtall
White Croaker
California Corbina
Queenfish
Croakers, Other
Opal eye
Ha If moon
Shiner Perch
Striped Seaperch
Black Perch
Walleye Surf perch
Silver Surf perch
White Seaperch
Pile Perch
Redtatl Surf perch
Barred Surf.perch
Surf perches. Other
Pacific Barracuda
California Sheephead
Pacific Bon.ito
Chub Hackere-1
__fa
253
*
*
—
*
*
*
*
*
~
*
40
—
354
29
431
179
78
—
14
57
21
10
~
~
12
9
10
—
—
*
75.
IS
132-
132
267
684
Northern
California
(1,000 kg)
_._.
—
—
7
—
46
*
*
—
*
49
*
7
58
*
*
*
*
142
*
*
—
*
*
1
20
—
6
9
—
—
29
24
7
*'
*'
—
37
Oregon
(1,000 kg)
*c
*
—
—
—
•2
—
*
—
*
*
-_
*
—
*
*
*
*
*
*
*
*
*
*
'
27
*
—
~
__
21
34
*•
__
*
*
*
—
Washington
(1,000 kg)
7
*
—
Od
*
1
--
78
—
158
—
*
*
*
*
*
*
*
it
*
*
*
*
*
~
*
—
*
15
53
*
—
*
*
*
*
All
regions
(1,000 kg)
57
401
—
7
--
48
--
78
—
158
58
0
47 .
62
354
29
431
179
--
--
1-4
58
21
10
1
55
15.
20,
20;
Itt
60
1L6
99
22
132
132
268,
72-1
2-76
-------
Table 2A-4. (continued)
Species group
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
'56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
Tunas
Brown Rockfish
Copper Rockfish
Widow Rockfish
Yellowtail Rockfish
Chilipepper Rockfish
Quillfaack Rockfish
Black Rockfish
Blue Rockfish
Bocaccio
Canary Rockfish
Greensoptted Rockfish
Olive Rockfish
Gopher Rockfish
California Scorpionfish
Rockfishes, Other
Sablefish
Kelp Green ling
Lingcod
Green lings, Other
Cabezon
Sculpins, Other
Sanddabs
California Halibut
Rock Sole
Starry Flounder
Flatfishes, Other
Other Fish
TOTALS
Southern
California
(1,000 kg)
612
89
140
34
151
203
—
34
138
298
33
159
108
104
63
601
.--
—
128
*
29
—
11
227
—
—
—
184
6,248
Northern
California
(1,000 kg)
333
121
134
18
238
159
—
430
258
64
129
75
28
30
*
280
• ' —
28
760
—
39
—
39
—
—
—
. . -,
107
4,064
Oregon
(1,000 kg)
*
*
—
--
45
*
"
354
43
--
60
*
*
*
*
47
*
18
175
«
: " ' "• --
'
- -
*
*
—
—
179
1,069
Washington
(1,000 kg)
*
21 '
78
•
—
*
61
219
--
— •
—
*
*
*
. *
—
—
—
162 .
—
—
—
16
*
16
—
87
__
1,364
All
regions
(1,000 kg)
945
231
355
54
441
362
78
1,037
451
366
229
235
136
134
63
952
34
64
1,225
10
106
6
65
252
24
106 ;
479
12,745
Catch Type A is an estimate of part of the total catch based on fish brought ashore in
whole form, available for interviewer identification and enumeration, from which samples of
lengths and weights were obtained.
A dash denotes no information available.
An asterisk (*) deno*es none reported.
A zero (0) indicates less than one thousand. "'
2-77
-------
Table 2A-5. Estimated Weight of Fish Caught (Catch Type A)a by Marine
Recreational Fishermen by Wave and Subregion
January 1985 - December 1985
Wave
Jan/Feb
Mar/ Apr
May/Jun
Jul/Aug
Sep/Oct
Nov/Dec
Subregion
Southern California
Northern California
Oregon
Washington
TOTAL
Southern California
Northern California
Oregon
Washington
TOTAL
Southern California
Northern California
Oregon
Washington
TOTAL
Southern California
Northern California
Oregon
Washington
TOTAL
Southern California
Northern California
Oregon
Washington
TOTAL
Southern California
Northern California
Oregon
Washington
TOTAL
GRAND TOTAL
Weight
827
365
27
75
1,294
495
253
43
144
935
1,201
489
366
617
2,673
1,757
1,543
42
425
3,768
921
1,006
505
67
2,499
1,047
408
86
35
1,576
12,745
a Catch Type A is an estimate of part of the total catch based on fish
brought ashore in whole form, available for interviewer identification
and enumeration, from which samples of lengths and weights were
obtained.
2-78
-------
Table 2A-6. Estimated Number of Participants in Marine Recreational
Fishing by Subregion for the Pacific Coast
January 1985 - December 1986
Subregion
Southern California
Standard Error
Northern California
Standard Error
Oregon
Standard Error
Washington
Standard Error
GRAND TOTALS
Standard Errors
Coastal .
participants
(thousands)
994
1,427
624
783
188
234
252
_352
2,058
. 1,682
Non-coastal
participants
(thousands)
50
44
101
92
22
18 -
34
.32
208
108
Out of
state
(1)
(thousands)
344
193
62
52
35
35
46
43
Total
participants
in state
(1)
(thousands)
1,389
1,441
787
790
245
237
333
356
(1) = Not additive across states. One person can be counted as "out of state" for
more than one state.
2-79
-------
-------
APPENDIX 2B
Method of Calculation: Weighted Means
and Percentiles
2-81
-------
Appendix 2B
Method of Calculation: Weighted Means
and Percent!les
The weighted mean of N respondents from the survey having weights W,,
l^, Wn and monthly fish consumption Cp C2, ..., Cn is computed as
fol1ows:
N N
Mean consumption = £ wici/ Z W-j.
i=l i=l
The weight W^ is the number of fish consumers represented by the ith
survey respondent. The sum of all the weights represents the average
number of U.S. fish consumers during the survey year.
The 95th percentile of fish consumption was also computed on a
weighted basis; no assumptions about the data distribution were made.
Using the same parameters described above, the consumption rates of indi-
viduals in a subset can be ordered so the Cj < C2 < ... < C . The 95th
percentile of fish consumption for N respondents is defined as the con-
sumption of the jth individual such that:
j-1 N
E Hi < (0.95) E "I-
i=l i=l
The sum of the weights of the individuals in the subset with consumption
less than the jth person is less than 95 percent of the total weight of
the subset, or:
j N
E «1 > (0-95) £ Wj.
i=l i=l
The sum of the weights of individuals in the subset with consumption
equal to or less than the jth person's is 95 percent or more of the total
weight of the subset.
2-82
-------
APPENDIX 2C
Studies of Consumption of
Recreationally Caught Fish
2-83
-------
Appendix 2C
Studies of Consumption of
Recreationally Caught Fish
The primary data requirements for determining consumption rates of
fish and shellfish that are caught by sport fishermen are catch
quantities, the number of fishermen making the catch, and the total
number of people who consume the catch. The average number of people in
the family or living group of the fisherman is usually assumed to be the
number of people consuming the fish. For simplicity, it is assumed that
each person in the family eats equal portions of the catch. The practice
of giving away part or all of a catch to people outside of the family is
rarely measured and is therefore generally ignored.
The following factors must also be considered in estimating consump-
tion rates:
(1) The proportional quantity of the total catch that is taken home
for consumption. All or part of the catch may be released alive,
used for bait, or discarded dead.
(2) The portion of the total fish weight that is edible. This
fraction may vary with species, but usually one value is applied
to all species.
(3) Fishing frequency, which determines the level of consumption,
shows seasonal variations; however, for simplicity, the frequency
of consumption of recreationally caught fish is assumed to be
constant over the year.
(4) In some studies, an average fish weight for each species may be
used with the catch number to obtain the catch weight. The
resulting catch estimates are accurate if the catch weight for a
species follows a normal distribution. However, if, on the
whole, more small fish are caught than large ones, the total
catch weight may be overestimated by using an average species
weight.
Perhaps the most thorough recreational survey was conducted in the
Los Angeles area by Puffer (1981). The survey of 12 fishing locations in
the harbor and coastal areas was conducted for the full 1980 calendar
2-84
-------
year; each site was surveyed an average of three times per month on dif-
ferent days and at a different time of the day. A total of 1,059 inter-
views with fishermen were conducted. The sample number was extrapolated
to an estimated 91,606 total unique fishermen in the area. Including
family/living groups, the total population estimated to consume locally
caught fish was 342,606.
Puffer used the following formula to calculate the consumption of
sportfishing catch in the Los Angeles area:
Consumption = K x NW/E x F/365
where , .
K = edible proportion of fish,
F = frequency of fishing/year,
E = number of fish eaters in family/living group,
W = average weight of fish in catch, and
N = number of fish in catch.
Assumptions inherent in the calculations are the following:
(1) Amount of fish and average weight of fish per catch is constant.
(2) The frequency of fishing for each fisherman is constant through-
out the year.
(3) The number of family fish-eaters is constant (greater than zero),
and the catch is shared evenly among family members.
(4) All of the catch is eaten, and 25 to 50 percent of the weight of
the fish is edible.
Consumption rates were calculated only for those fishermen who indicated
that they eat the fish they catch.
The median consumption rate for total fish and shellfish is approxi-
mately 37 g/person/day. Consumption data in Table 2C-1, organized by
species, show that California halibut is consumed in the largest quanti-
ties. Table 2C-2 shows differences in the participation and consumption
rates of ethnic groups. Although Caucasians make up the largest percent
of fishermen interviewed, the fish consumption rate for Oriental/Samoan
fishermen and their families is considerably higher than for other groups.
2-85
-------
Table 2C-1, Description of Consumption Patterns for Primary
Fish Kept by Sport Fishermen (n = 1059)
Species
Percent of fishermen
who consume/give away
Median consumption
(g/person/day)
White Croaker
Pacific Mackerel
Pacific Bonito
Queenfish
Jacksmelt
Walleye Perch
Shiner Perch
Opal eye
Black Perch
Kelp Bass
California Halibut
Shellfish3
82%
74%
77%
79%
78%
83%
67%
87%
89%
78%
86%
97%
15%
15%
18%
13%
16%
7%
10%
7%
5%
2%
8%
0%
14.8
35.8
63.6
7.8
9.4
5.4
2.0
16.1
8.1
3.9
143.1
10.0
a Crab, mussels, lobster, aba lone.
Source: Puffer (1981).
2-86
-------
Table 2C-2. Demographic Data of Sport Fishermen
and Their Family/Living Group
Ethnic group
Caucasian
Black
Mexican-American
Oriental/Samoan
Other
Percent
of total
interviewed
42
24
16'
13
5
Median
consumption
(g/person/day)
46.0
24.2
33.0
70.6
Source: Puffer-(1981).
2-87
-------
Another local survey of sportfishing was performed in Commencement
Bay, Washington, by Pierce et al. (1981). This survey was conducted by
interviewing fishermen along Commencement Bay waterways in Tacoma,
Washington, for 5 consecutive days in the summer and 4 consecutive days
in the fall. The total number of interviews was 304 in the summer and
204 in the fall, and the total number of unique fishermen was calculated
at 3,391. The ethnic makeup of the fishermen surveyed is presented in
Table 2C-3.
Table 2C-4 contains catch data by species obtained from the survey.
The mean daily catch (kilograms/day) was calculated from the total summer
and fall catch quantities during the survey. Therefore, the mean value
may not be entirely representative because winter and spring fishing were
omitted.
The formula of Puffer (1981) can be used for the Commencement Bay
sport catch data because the following factors were measured:
(1) Interviews with fishermen suggested that, on the average, 98 per-
cent of the catch is eaten.
(2) The average number of fishermen per day is 53.
(3) The average size of the family or living group of the fishermen
was 3.74 persons.
(4) The edible portion of all fish caught was assumed to be 49 percent
of the total weight.
Thus,
mean daily fish consumption = [mean daily catch/(fishermen x family size)]
x 0.98 x 0.49.
Calculated mean daily consumption of recreationally caught fish is
listed by species in the fourth column in Table 2C-4. The largest propor-
tion' of the fishermen is composed of weekly fishermen. Fishing frequen-
cies obtained in the study can be used to obtain cumulative frequencies
and to calculate yearly fish consumption for each group (see Table 2-17 in
this handbook).
2-88
-------
Table 2C-3. Commencement Bay Ethnic Makeup of Fishermen Surveyed
Ethnic group Summer Fall
White 58.9% 60.8%
Black 22.7% 15.2%
Oriental 15.5% 23.5%
Mexican 2.6% 0.5%
Indian 0.3% 0%
Source: Pierce et al. (1981).
2-89
-------
Table 2C-4. Catch Quantities and Consumption Rates - Commencement Bay, Washington
Species
Pacific Hake
Walleye Poilock
Pile Perch
Pacific Cod
Pacific Torocod
Rock Sole
Striped Seaperch
Speckled Sandab
Brown Rockfish
Sand Sole
English Sole
Big Skate
Copper Rockfish
Quillback Rockfish
Black Rockfish
Solney Dogfish
Starry Flounder
White Spotted Green ling
Shiner Perch
Canary Rockfish
Red Irish Lord
Dover Sole
Boccaccia Rockfish
Flathead Sole
Pacific Sandab
Staghorn Sculpin
Petrale Sole
Butter Sole
Red Stripe Rockfish
TOTAL
Summer
catch wt
(kg/day)
30.08
30.52
11.74
9.65
7.56
2.67
2.64
2.53
2.06
1.96
1.60
1.36
0.07
0.69
0.68
0.68
0.57
0.48
0.40
0.40
0.28
0.26
0.23
0.18
0.14
0.12
0.10
0.06
Fall
catch wt
(kg/day)
34.34
108.35
1.95
10.59
5.92
1.36
0.39
4.65
1.58
0.77
0.41
1.08
1.53
1.38
5.88
0.72
0.92
0.08
2.47
1.21
0.46
0.36
0.05
0.00
1.19
0.45
0.14
0.00
0.60
Mean daily
catch3
(kg/day)
31.97
61.72
6.08
8,99
5.99
1.79
1.35
3.19
1.62
1,22
0.90
1.08
0.71
0.92
2,92
0.62
0,66
0.25
1.28
0.72
0,33
0.27
0.12
0.08
0.59
0^25
0.11
0.03
0.27
Mean fish
consumed
(g/person/day)
77.46
180.14
17.76
26.25
17.49
5.23
3.93
9.32
4.72
3.55
2.61
3.17
2.08
2.69
8.51
1.81
1.94
0.73
3.73
2.09
0.96
0.80
0.36
0.23
1.72
0.74
0.31
0.07
0.78
381.19
a Sunnier + Fall Catch/9 days
Assumptions:
98% of catch eaten.
Average fishermen/day - 53.
Average living group = 3.74/fishermen.
Portion of edible tissue « 0.49 percent.
Source: Derived from Pierce et al. (1981).
2-90
-------
APPENDIX 2D
Pica Data Sources
2-91
-------
Appendix 2D
Pica Data Sources
The data base used to assess pica consisted of textbooks, handbooks,
research literature, and personal contacts. Textbooks and handbooks
covered such fields as pediatric behavior, pediatric psychology, pediatric
psychiatry, and pediatric nutrition. Research literature was identified
from an online literature search on DIALOG. The DIALOG data bases
searched were Medline, Toxline, Embase, Eric, Agricola, Psychlnfo, Social
Scisearch, and NTIS. Personal contacts consisted of telephone inquiries
to the following organizations and researchers:
Organizations
American Academy of Pediatrics
American Psychiatric Association
National Association of Anorexia Nervosa and Associated Disorders
National Center for Health Statistics
National Institute of Child Health and Human Development
National Institute of Environmental Health Sciences
National Institute on Mental Health
National Research Council
North American Society for Pediatric Gastroenterology
Society for Pediatric Research
U.S. Public Health Service, Division of Maternal and Child Health
Researchers
David Bellinger, M.D. Children's Hospital (Boston)
Susan Binder, M.D. Centers for Disease Control
Rufus Chaney, Ph.D. Agriculture Research Service (USDA)
James Chisolm, M.D. Johns Hopkins University
William Crosby, M.D. George Washington University
Darla Danford, M.D. Nutrition Coordinator (NIH)
Marc Feldman, M.D. Duke University
James Smith, Ph.D. Vitamin and Mineral Research
Center (USDA)
Donald Vermeer, Ph.D. Louisiana State University
Mohsen Ziai, M.D. Georgetown University
2-92
-------
3. INHALATION ROUTE
Humans can be exposed to toxic chemicals from the inhalation route
from various sources. This chapter discusses factors associated with
exposure to both vapors and particulates.
3.1 Exposure Equation for Inhalation
The general equation for calculating inhalation exposure is given by:
Lifetime
Average Inhalation x Contaminant Concentration x Exposure
Inhalation = Rate in Air Duration
Exposure Body Weight x Lifetime
The inhalation rate varies according to the exertion.level and other
factors. Activity patterns that might indicate the exertion level for
various periods of time are given in the section on other factors needed
for exposure calculations (Section 5.3). Pulmonary ventilation is
discussed in detail in the following section.
3.2 Pulmonary Ventilation
3.2.1 Background
Pulmonary ventilation is the mass movement of gas in and out of the
lungs (Astrand 1970). This movement is generally represented by the
minute volume, the volume of gas expired in L per minute at normal body
temperature and ambient barometric pressure, saturated with water vapor.
Minute volume is the product of tidal volume, the volume of gas moved
during each respiratory cycle, and respiratory frequency (Astrand and
Rodahl 1977). It will vary with an individual's age, weight, sex,
activity level, and general physical condition.
Measurement of minute volumes is usually conducted through the use of
a spirometer and a collection system. The spirometer, through the use of
one-way valves, funnels the expired gas into a collection system (e.g., a
Douglas Bag). In this manner, the expired gas volume is recorded over
time. These types of spirometric measurements of minute volume have been
reported by various clinical studies since the early 1930s. Today, the
3-1
-------
accuracy of this instrumentation is still considered to be very good.
For this reason, experts in the field of pulmonary science regard the
results of these early studies to be valid determinations of lung volume
measurements.
Several formulae have been proposed in the literature to calculate
minute volumes of humans at rest from anthropometric data (USEPA 1985).
Most of these formulae are based upon measurements of relatively small
sample sizes; all of them are applicable only to the estimation of minute
ventilation at rest.
3.2.2 Methods
Review of the literature failed to identify equations .that would
enable the development of statistical distributions of minute ventilation
at all activity levels for male and female children and adults.
Therefore, ranges of measured values were compiled from the available
data and estimates of minute ventilation rates were derived (USEPA
1985). Many of these measurements are from early studies. In more
recent investigations, minute ventilation tends to be measured more as
background information than as a research objective itself, making more
current measurements difficult to locate in the literature. In addition,
those recent measurements that have been located are frequently of
specific subpopulations such as obese asthmatics or marathon runners.
Measurements of minute ventilation at various activity levels were
compiled for each age/sex group. The activity levels at which the
measurements were taken were categorized as light, moderate, or heavy
according to criteria developed by the Environmental Criteria and
Assessment Office of EPA for the air quality criteria document for
ozone. These criteria were developed for a reference male adult with a
body weight of 70 kg (USEPA 1984). Minute ventilation rates for adult
males based on these activity level categories are detailed in Appendix
3A. Activity level categories for the other age/sex groups were
extrapolated from the criteria for male adults on the basis of body
3-2
-------
weight (AIHA 1971). For exposure assessment purposes, minute volumes
(expressed as L per minute) were converted to an inhalation rate
expressed as cubic meters per hour.
3.2.3 Results
Table 3-1 presents the compilation of available inhalation rate data
by age, sex, and activity level. The data presented include inhalation
rates for adult males, adult females, and children during resting and
during light, moderate, and heavy exertion. Values of inhalation rates
presented in this table represent the mean of values reported for each
activity level in USEPA (1985). Additional detailed information that
would provide range data for these age/sex/activity level categories and
for individual ages from infants to 18 years of age is found in
Appendix 3A.
Each activity level is representative of various activities. Resting
is characterized by activities such as watching television, reading, or
sleeping. Light activity includes level walking, meal cleanup, care of
laundry and clothes, domestic work and other miscellaneous household
chores, attending to personal needs and care, photography, hobbies, and
conducting minor indoor repairs and home improvements. Moderate activity
includes climbing stairs, heavy indoor cleanup (e.g., scrubbing
surfaces), and performing major indoor repairs and alterations (e.g.,
remodeling). Heavy activity consists of vigorous physical exercise, such
as weight lifting, dancing, or riding an exercise bike.
Very few data are available for preschool-aged children. This is
because of the difficulty of conducting clinical studies with this age
group. For many of the children's age/sex groups, the sample numbers are
very small. In addition, for most groups, very few measurements at light
and moderate activity levels are available. Representative data have
been included for a 6-year-old child and a 10-year-old child. Additional
inhalation rate data for all aged children could be developed from the
data in Appendix 3A.
3-3
-------
Table 3-1. Summary of Human Inhalation Rates for Men, Women,
and Children by Activity Level (m3/hour)a
Adult male
Adult female
Average adult
Child, age 6
Child, age 10
Restingb
0.7
0.3
0.5
0.4
0.4
Light0
0.8
0.5
0.6
0.8
1.0
Moderated
2.5
1.6
2.1
2.0
3.2
Heavy6
4.8
2.9
3.9
2.4
4.2
Values of inhalation rates for males, females, and children presented in
this table represent the mean of values reported for each activity level in
USEPA (1985).
Includes watching television, reading, and sleeping.
c Includes most domestic work, attending to personal needs and care,
hobbies, and conducting minor indoor repairs and home improvements.
Includes heavy indoor cleanup, performance of major indoor repairs and
alterations, and climbing stairs.
e Includes vigorous physical exercise and climbing stairs carrying a load.
Derived by taking the mean of the adult male and adult female values for
each activity level.
3-4
-------
3.2.4 Application of Pulmonary Ventilation Data
Inhalation rate is a necessary component of an assessment of
inhalation exposure. The overall equation that is used to calculate
inhalation exposure is:
IHX = IR x ED x C
where
IHX = inhalation exposure (mg/year),
IR = inhalation rate (nr/hour),
ED = duration of exposure event (hours), and
C = average air concentration of a given constituent (mg/m3).
The selection of the inhalation rate to be used in the equation would
depend upon the age of the population exposed and the activity level of
the population during exposure. For example, if the exposed population
were adults conducting minor home improvements, a ventilation rate of
o
0.6 m /hour would be used. Judgment would have to be used to decide
upon the activity levels represented by various forms of activity.
Various inhalation:rates are commonly used to represent daily
inhalation rates. Based on 16 hours of activity at the light activity
level and 8 hours resting, the International Commission of Radiological
Protection (ICRP) reported 23 m3/day for adult males and 21 m3/ day
for adult females as representative inhalation rates (ICRP 1981). Using
o
these rates an average value for an adult would be 22 m /day. A value
of 20 m /day is used in the Ambient Water Quality Criteria documents
(USEPA 1980). J"his value is derived from earlier publications on
reference man values by ICRP.
For estimating inhalation rates for indoor and outdoor scenarios,
USEPA (1985) report the total amount of time spent indoors and outdoors
at 3 activity levels, low, medium, and high. Since these activity levels
do not correspond to the resting, light, moderate, and heavy activity
levels used in Table 3-1, the values cannot be used directly. However,
3-5
-------
if one assumes that the amount of time spent at the "low" activity level
can be equally divided between "resting" and "light" activity, estimates
of inhalation rates for indoor and outdoor activities may be made. These
data are presented in Table 3-2.
3.2.5 Conclusion
Inhalation rate varies depending upon the activity levels of the
exposed individual. The commonly used values, 20 to 23 m3/day are
based on data from ICRP (1981) for reference man. These values assume
16 hours of light activity and 8 hours of resting. Daily inhalation
rates for individuals performing activities at levels other than resting
or light are not presented. Thus, the values are not representative
inhalation rates for individuals at the moderate and/or heavy activity
levels.
Data presented in USEPA (1985) suggest lower inhalation rates for
light and resting activity levels. Using the same assumptions as used in
ICRP (1981), the daily inhalation rate would be approximately 14 m3
(See Table 3-1). In addition, USEPA (1985) report inhalation data for
moderate and heavy activity levels, making it possible to estimate total
daily inhalation rate for any combination of activity levels. The data
also suggest that the maximum inhalation rate is roughly twice the
reported mean rates for all activity levels.
Based on the above discussion, the following recommendations are made:
(1) For continuous exposure situations, or assessments in which
specific activity patterns are not known, use 20 nryday as the
average adult daily inhalation rate and 30 m3/day as the
reasonable worst-case inhalation rate. The 20 m3/day rate is
the value reported for reference man, rounded to one significant.
figure, and is widely used for exposure assessments. The 30
nryday rate was estimated based on the observation that
maximal inhalation rates reported in USEPA (1985) were roughly
twice the reported mean values. Based on this, it was judged
that a value 1.5 times the mean rate would represent a
reasonable worst-case rate.
3-6
-------
Table 3-2. Activity Pattern Data Aggregated for Three
Microenvironments by Activity Level
Micro-environment
Indoors
Outdoors
In
transportation
vehicle
Activity
level
Resting
Light
Moderate
Heavy
Total
Resting
Light
Moderate
Heavy
Total
Resting
Light
Moderate
Heavy
Total
Average hours in each
microenvironment
at each
activity level
9.82
9.82
0.71;
0.098
20.4
0.505
0.505
0.65
0.12
1 . 77
0.86
0.86
0.05
0.0012
1.77
Source: Adapted from USEPA (1985)
3-7
-------
(2) For exposure scenarios in which the distribution of activity
patterns is known, the values reported by USEPA (1985) in Table
3-1, should be used. These activity-specific rates allow a more
representative daily inhalation rate to be calculated.
In calculating an average inhalation rate for an individual performing
outdoor activities, data from Table 3-2 suggest that a typical activity
mix would consist of the following: 37 percent of the time at a moderate
activity level, 28 percent at both the resting and the light activity
levels, and 7 percent at a heavy activity level. For a reasonable
worst-case inhalation rate, it was assumed that an individual would spend
50 percent of the time at a heavy activity level and 50 percent of the
time at a moderate activity level. Using the values in Table 3-1, the
average hourly outdoor inhalation rate is 1.4 m3/hour and the
reasonable worst-case outdoor inhalation rate is 3.0 m3/hour.
For indoor activities, inhalation rates were based on a different mix
of activities. For an average case, it was assumed that an individual
would spend 48 percent of the time at both the resting activity level and
the light activity level, 3 percent of the time at a moderate activity
level, and 1 percent of the time at a heavy activity level. A reason-
able worst-case value is based on 25 percent of the time at a resting
activity level, 60 percent at a light activity level, 10 percent at a
moderate activity level, and 5 percent at a heavy activity level. Based
on the values in Table 3-1, the average indoor inhalation rate is
2
0.63 m /hour, and the reasonable worst-case indoor inhalation rate is
0.89 m3/hour.
If the assessment is applicable to children, a similar approach can
be taken using values for specific age groups at specified activity levels
as provided in Table 3-1. For assessments involving specific activities
(e.g., showering, painting), inhalation rates can be selected that are
judged to be representative of these activities.
3-8
-------
3.3 References
AIHA. 1971. American Industrial Hygiene Association. Ergonomics
Guides: Ergonomics guide to assessment of metabolic and cardiac costs of
physical work. American Industrial Hygiene Association J. 32(8):560-564.
Astrand I. 1970. Aerobic work capacity in men and women with special
reference'to age. Acta Physiologica Scandinavica Vol. 49, Supplement 169.
Astrand PO, Rodahl K. 1977. Textbook of work physiology. New York:
McGraw-Hill Book Company.
ICRP. 1981. International Commission on Radiological Protection.
Report of the task group on reference man. New York: Pergammon Press.
USEPA. 1980. U.S. Environmental Protection Agency. Water Quality
Criteria Documents; Availability. Federal Register 45(231): 79318-79379.
USEPA. 1985. U.S. Environmental Protection Agency. Development of
statistical distributions or ranges of standard factors used in exposure
assessments. Washington, DC: Office of Health and Environmental
Assessment. EPA No. 600/8-85-010. Available from: NTIS, Springfield,
VA. PB85-242667.
USEPA. 1986. U.S. Environmental Protection Agency. Air quality
criteria for ozone and other photochemical oxidants. Washington, DC:
Office of Health and Environmental Assessment. EPA 600/8-84-020AF-EF.
Available from: NTIS, Springfield, VA. PB87-142949.
Versar. 1987. Methods for assessing exposure to chemical substances in
the ambient environment. Washington, DC: U.S. Environmental Protection
Agency, Exposure Evaluation Division, Office of Toxic Substances.
3-9
-------
-------
APPENDIX 3A
Detailed Ventilation Rate Data
3-11
-------
Table 3A-1. Estimated Minute Ventilation Associated with
Activity Level for Average Male Adult
Level
of work
Light
Light
Light
L/min
13
19
25
Representative activities
Level walking at 2 mph; washing clothes
Level walking at 3 mph; bowling; scrubbing floors
Dancing; pushing wheelbarrow with 15-kg load
J
Moderate
30
simple construction; stacking firewood
Easy cycling; pushing wheelbarrow with 75-kg load;
using sledgehammer
Moderate
Moderate
Heavy
Heavy
Very heavy
Very heavy
Severe
35
40
55
63
72
85
100*
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 long distance
skiing
competitive cycling
running; cross-country
Source: Adapted from USEPA (1985).
3-12
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4. DERMAL ROUTE
4.1 Exposure Equation for Dermal
The equation for calculating dermal exposure is:
Contact x Contaminant Concentration x Exposure
Dermal _ Rate on Skin Duration
Exposure Body Weight x Lifetime
For this route, the contact rate is expressed differently for liquids arid
solids. For dermal exposure to liquids, the contact rate should be
expressed as a volumetric rate to keep the units consistent with the
concentration term which is typically expressed as mass per unit volume.
When exposure to solids is being assessed, the concentration of the
contaminant on the skin is usually expressed in mass per mass units;
thus, a contact rate consistent with these units should be used.
Dermal dose can be calculated in two ways:
Dose = (Mass Contact Rate/Density) x Contaminant x Exposure x Absorption
Concentration Duration Fraction
or
Dose = Permeability .x Contaminant x Exposure x Contact
Constant Concentration Duration Area
The first equation for dose is simply the numerator of the equation above
for dermal exposure adjusted for absorption and with the first term
changed from a volumetric contact rate to a mass contact rate divided by
density. The second equation for dos.e is derived from Fick's Law on
diffusion and requires data on permeability. Both the contact rate and
permeability constant are difficult to estimate. This lack of data makes
dermal exposure calculations more uncertain than calculations for the
other routes. The body surface area standard factors presented in the
next section will reduce the uncertainty associated with one of the terms
in the dose equation.
4-1
-------
4.2 Surface Area of the Human Body
4.2.1 Background
Dermal exposure to contaminants is a potentially important pathway
that warrants consideration in many exposure assessments. Subsequent
health effects depend on the chemical characteristics of the compound and
the duration and frequency of exposure. Upon determination that a
contaminant can gain access to the body through topical (skin) exposure,
the assessor may use estimations of total body surface area to help
calculate the contact rate for the contaminant. Mean values of total
surface area of body parts can be used for cases in which only a certain
area of the body is at risk of exposure. A literature search of the
historical development of models to estimate surface area of the human
body was conducted by USEPA (1985). A review of estimation techniques
and human body surface data generated by USEPA (1985) is presented below.
4.2.2 Measurement Techniques
Direct measurement techniques that have been used to measure total
body surface area include direct coating, triangulation, and surface
integration (Boyd 1935). The coating methods consist of coating either
the whole body or specific regions with a substance of known or measured
area. In some instances the pieces of coating were placed on
cross-section paper and the area was measured by counting the squares
covered. In others, the areas of the pieces of coating were calculated
by weighing the coating or weighing duplicates cut from a; substance of
uniform thickness (Boyd 1935). 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
running a planimeter over the body in parallel strips of equal width.
The surface area is calculated by adding the areas of all the strips
measured.
4-2
-------
Directly measuring body surface area by the methods described above
is a difficult, time-consuming task. Gehan and George (1970) cited only
three studies completed after 1935 that used methods of direct
measurement to determine the surface area of the human body.
Consequently, existing direct measurement data are limited and somewhat
old.
Surface area of the body can also be estimated using geometric
approximations by assuming that parts of the body resemble geometric
solids. Calculation of the surface area of a solid results in an
estimation of the surface area of the corresponding body part. Boyd
(1935) cited one example in which an estimation of surface area of the
trunk was performed by measuring the length from the groove of the neck
to the tip of the coccyx, and the circumferences just under the arms, at
the level of the umbilicus, and the level of the pubis. The surface
areas of cylindrical shapes corresponding to these measurements were
calculated.
A linear method has been proposed by DuBois and DuBois (1916) in
which estimates are made on the principle that the surface area of the
parts of the body are proportional, rather than equal, to the surface
area of the solids they resemble. Estimates of surface area made from
lengths and circumferences are corrected by constants obtained from
direct measurements of surface area. A table was developed with
definitions of linear dimensions and constants for each body part,
derived from direct measurement (Boyd 1935).
More recently, Popendorf and Leffinwell (1976) and Haycock et al.
(1978) used their own geometric methods for estimating body surface
area. Both methods made use of the assumption that body parts correspond
to geometric solids, such as the sphere and cylinder. Haycock et al.
(1978) calculated surface area of the body from 34 body measurements.
4-3
-------
4.2.3 Formulae for Total Body Surface Area
Several formulae have been proposed for estimating body surface area
from measurements of other major body dimensions. Generally, the
formulae are based on the principles that body density and shape are
roughly the same and that the relationship of surface area to any
dimension may be represented by the curve of central tendency of their
plotted values or by the algebraic expression for the curve (Boyd 1935).
A discussion and comparison of formulae to determine total body surface
area is presented in Appendix 4A. Analysis of the formulae reveal that
the model proposed by Gehan and George (1970) will produce the most
accurate estimations of total body surface area. Description and use of
the model will be discussed in the Methods section of this chapter.
4.2.4 Surface Area of Body Parts
Several investigators who have worked in determining body surface
area have reported their results in terms of surface areas of different
parts of the body as well as total surface area. The literature contains
surface area of body parts both as direct measurements and as estimates.
Data on surface area of body parts have been reported for both sexes, for
several ethnic groups, and for ages ranging from newborn to elderly.
Boyd (1935) summarized direct measurements of surface area made by
various investigators who reported results in varying degrees of detail.
Boyd measured a female child at three different ages and another female
child at five different ages over a period of 8 months. The result is a
record of the growth of the surface area of the body and the change in
the percentage of total body surface area associated with each part.
Another investigator (Lissauer 1903, as cited in USEPA 1985) reported the
body surface area of 12 infants ranging in age from 17 days to 15
months. Measurements of body parts recorded surface area in terms of
head, trunk, upper extremities, and lower extremities. DuBois and DuBois
(1916) reported the surface area of various body parts for four adult
males and one adult female. Another research team (Sawyer et al.
4.4
-------
no date, as cited in USEPA 1985) reported body part surface area for a
29-month-old female, a 12-year-old, 10-month-old male, an 18-year-old
male, a 21-year-old male or female, 6-month-old male, and a 26-year-old
female. Both research efforts measured surface area for head, trunk,
arms, hand, thighs, legs, and feet.
A study by Fujimoto and Watanabe (1969) presented the results of
direct measurements of 201 Japanese of both sexes ranging in age from
less than 1 year to 76 years. The subjects were prescreened by an
obesity index so that all individuals had a "standard Japanese physique
by sex and age," or were categorized as slender or obese after
adolescence. The authors reported the average percentage of total body
surface area for a large number of different body regions, including the
area covered by head hair, the forehead, face, ear, neck, upper front
trunk, lower front trunk, upper back trunk, lower back trunk, hip, upper
arm, lower arm, hand, thigh, leg, and foot. Upon analyzing the data
according to sex and age, the authors made the following generalizations:
• The percentage of total surface area of the head, face, and neck
decreases with increasing age;
• The percentage of total surface area of the lower extremities,
such as thighs, increases with age; and
• The differences in percentages of different body regions between
sexes become significant after adolescence, the thigh having a
higher percentage in the female.
While there are some physical differences between Japanese and Americans
that might limit the.applicability of the data from this study to the
U.S. population, it is possible that these generalizations may pertain to
all humans. This study represents the largest single group of direct
measurements made by any surface area investigator and presents a
balanced sample of individuals according to sex and age.
Two additional methods have been used extensively to estimate the
surface area of body parts: linear methods and geometric methods.
Linear methods are based on actual measurement data, and generally
4-5'
-------
involve multiplying a linear dimension of a body part (length,
circumference, etc.) by a constant derived from previous direct
measurements. Geometric methods divide the body into parts that are
assigned a simple geometric shape; e.g., a forearm is treated like a
cylinder, the head like a sphere, etc. The dimensions of the body parts
are measured; then the surface area is computed from the formula for the
particular geometric solid. " Both of these methods provide only a rough
estimation of the surface area of body parts.
4.2.5 Methods
Available direct measurement data were analyzed using the Statistical
Processing System (SPS) software package (Buhyoff et al . 1982) to
generate equations that calculate surface area as a function of height
and weight. These equations were then used to calculate surface area
distributions of the U.S. population using the National Health and
Nutrition Examination 'Survey (NHANES) II height and weight data and the
computer program QNTLS (Rochon and Kalsbeek 1983). A description of this
program is provided in Appendix B of the final report by USEPA (1985).
4.2.6 Total Body Surface Area
A review of the literature identified the equation proposed by Gehan
and George (1970) a's the best choice for estimating surface area.
However, their paper gave insufficient information to estimate the
standard error about the regression. Therefore, the 401 direct
measurements of children and adults used by the authors were reanalyzed
using the SPS to obtain the standard error. These data are presented in
Appendix B, Table B-l of USEPA (1985). Summary data are presented in
Appendix 4B of this chapter.
The model uses weight and height as independent variables to predict
total body surface area (SA), and can be written as:
H.
,
4-6
-------
or in logarithmic form:
In (SA)i = In aQ + ajln H.J+ a2ln Wi + In e.
where
SA = surface area in meters squared,
H = height in centimeters,
W = weight in kg,
a0, aj,
and a£ = parameters to be estimated, and
In e-j = a random error term with mean zero and constant variance.
For tests of hypotheses, it was assumed that In e. is normally
distributed. The random errors were assumed to be independent among
individuals.
Using the least squares procedure, the following parameter estimates
(and their standard errors) were obtained:
a0 = -3.73 (0.18), aj = 0.417 (0.054), a2 = 0.517 (0.022).
The model is then:
SA = 0.0239 H0-417 W0-517
or in logarithmic form:
In SA = -3.73 + 0.417 In H + 0.517 In W ~ '
with a standard error about the regression of 0.00374. This model
explains more than 99 percent of the total variation in surface area
among the observations, and is identical to two significant figures with
the model developed by Gehan and George (1970).
4.2.7 Body Part Surface Area
Because of the rapid changes in the proportions of body parts in
childhood, the surface area of body parts was analyzed separately for
children (<18 years) and adults (>18 years). Direct measurements of
surface area of various body parts provided by Boyd (1935) and Van Graan
(1969) are presented in Appendix B of USEPA (1985). Table B-2 of USEPA
(1985) tabulates measurements of adults and Table B-3 presents children's
4-7
-------
data. The data for adults were used to develop equations for estimating
body part surface area from height and weight. Insufficient data for
children, however, precluded the development of. equations to estimate
their body part surface area.
For adults, regression equations relating weight and height to the
surface area of the body part were developed using the SPS for the head,
trunk, upper extremities and lower extremities. Upper extremities
comprise arms and hands; arms are further divided into upper arms and
forearms. Lower extremities include legs and feet, with legs further
divided into thighs and lower legs. The trunk includes the neck. Only
data reflecting similar demarcation between parts were used in the
analyses.
The same model used to estimate total body surface area with the
independent variables height and weight was used for the surface area of
body parts (surface areaP):
a, a2
SAP = aQ H L W .
Three regressions were run on each body part for which data were
available: observations on females, observations on males, and the
pooled observations. For each body part an F-test was conducted to test
whether two different regression models (male and female) were
necessary. When indicated by the F-test, the null hypothesis that there
was no difference between the two regressions (i.e., that the data should
be pooled) was rejected and two equations were listed. The equations are
summarized in Table 3-5 of USEPA (1985). The data and statistical
summaries are presented in Appendix B of USEPA (1985).
4.2.8 Results
(1) Adults. Percentile estimates of total surface area and surface
area of body parts calculated with regression equations and NHANES II
height and weight data using QNTLS are presented in Appendix 4B for adult
4-8
-------
males and adult females. The calculated mean surface areas of body parts
for men and women are presented in Table 4-1. The standard deviation,
the minimum value, and the maximum value for each body part are
included. The median total body surface area for men and women and the
corresponding standard errors about the regressions are also given for
the 106 individuals upon which the data in Table 4-1 are based. It has
been assumed that errors associated with height and weight are
negligible. The data in Table 4-2 present the percentage of total body
surface by body part for men and women.
(2) Children. Available measurements of the surface area of
children's body parts are summarized as percentage of total surface area
in Table 4-3. Because of the small sample size (21 children), the data^
cannot be assumed to represent the average percentage of surface area by
body part for all children.
Percentile estimates of total surface area of children calculated
with the total surface area regression equation and NHANES II height and
weight data using QNTLS for males and females are presented in Appendix
4B (Tables 4B-3 and 4B-4). Estimates are not included for children
younger than 2 years old because there are no NHANES height data for this
age group. For children, the error associated with height and weight
cannot be assumed to be zero because of their relatively small sizes.
Therefore, the standard errors of the percent!le estimates cannot be
estimated, since it cannot be assumed that the errors associated with the
exogenous variables (height and weight) are independent of that
associated with the model; there are insufficient data to determine the
relationship between these errors. A summary of total body surface area
for male and female children from Appendix 4B is presented below.
Median Total Body Surface Area (m )
Age (year) Male Female
3<6 0.728 0.711
6<9 0.931 0.919
9<12 1.16 1.16
12<15 1.49 1.48
15<18 1.75 1.60
4-9
-------
o
Table 4-1. Surface Area by Body Part for Adults (m )
Body part
Head
Trunk
Upper extremities
Arms
Upper arms
Forearms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
TOTAL
Mean
0.118
0.569
0.319
0.228
0.143
0.114
0.084
0.636
0.505
0.198
0.207
0.112
1.94
(s.d.)
(0.0160)
(0.0140)
(0.0461)
(0.0374)
(0.0143)
(0.0127)
(0.0127)
(0.0994)
(0.0885)
(0.1470)
(0.0379)
(0.0177)
(0.00374)3
Hen
Hin.
0.090
0.306
0.169
0.109
0.122
0.0945
0.0596
0.283
0.221
0.128
0.093
0.0611
1.66
- Max.
- 0.161
- 0.893
- 0.429
- 0.292
- 0.156
- 0.136
- 0,113
- 0.868
- 0.656
- 0.403
- 0.296
- 0.156
- 2.28b
n
29
29
48
32
6
6
32
48
32
32
32
32
48
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
1.
Mean (s
.d.)
110 (0.00625)
542 (0.
276 (0.
210 (0.
-
-
0746 (0
J
626 (0.
488 (0.
258 (0.
194 (0.
0975 (0
0712)
0241)
0129)
.00510)
0675)
0515)
0333)
0240)
.00903)
69 (0.00374)a
Women
Min.
0.0953
0.437
0.215
0.193
0.0639
0.492
0.423
0.258
0.165
0.0834
1.45
- Max.
- 0.127
- 0.867
- 0.333
- 0.235
-
-
- 0.0824
- 0.809
- 0.585
- 0.360
- 0.229
- 0.115
- 2.09b
n
54
54
57
13
-
-
12
57
13
13
13
13
58
8 median (standard error).
b percent ties (5th - 95th).
s.d. « standard deviation.
s,e. » standard error for the 5th to 95th percent!le of each body part.
n * number of observations.
Source: Adapted from USEPA (1985),
4-10
-------
Table 4-2. Percentage of Total Body Surface Area by Part for Adults
Body part
Head
Trunk
Upper Extremities
Arms
Upper Arms
Forearms
Hands
Lower Extremities
Legs
Thighs
Lower Legs
Feet
Mean
7.8
35.9
18.8
14.1
7.4
5.9
5.2
37.5
31.2
18.4
12.8
7.0
(s.
(1,
(2,
(1,
(0,
(0,
(0,
(°-
(1.
(1.
(1.
(1.
(0.
• d.)
.0)
,1) '
.1)
.9)
•5)
.3)
,5)
.9)
6)
2)
.0)
5)
Men
Min. -
6.1-10
30.5-41
16.4-21
12.5-15
6.7- 8
5.4- 6
4.6- 7
33.3-41
26.1-33
15.2-20
11.0-15
6.0- 7
Women
Max.
.6
.4
.0
.5
.1
.3
.0
.2
.4
.2
.8
.9'
n
48
48
48
32
6
6
32
48
32
32
32
32
Mean (s.d.)
7.1
,34.8
17.9
14.0
-
-
5.1
40.3
32.4
19.5
12.8
6.5
(0.6)
(1.9)
(0.9)
(0.6)
(0.3)
(1.6)
(1-6)"
(1.1)
(1.0)
(0.3)
Min. -
5'. 6- 8
32.8-41
15.6-19
12.4-14,
-
-
4.4- 5,
36.0-43,
29.8-35.
18.0-21,
11.. 4-14.
6.0-7.
Max.
.1
.7
.9
.8
.4 .
.2
.3
.7
.9
.0
n
57
57
57
13
-
-
13
57
13
13
13
13
s.d. = standard deviation.
n = number of observations.
Source: USEPA (1985).
4-11
-------
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4-12
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4-13
-------
4.2.9 Application of Body Surface Area Data
For cases of dermal exposure to contaminants, the assessor may
estimate the median total body surface area of an adult male or female
from the data presented in Table 4-1. There is a greater likelihood that
only certain areas of the body, as opposed to the total body, are at risk
of exposure, and the assessor may also use the data in Table 4-1 to
estimate the surface area of a particular body part(s). For example, if
an individual is using a household cleaning product that contains a
contaminant of interest, the hands and arms have the greater risk of
exposure. The assessor may determine the mean surface area of these body
parts for men and women as follows:
2
Surface Area (m )
Men Women
Arms 0.228 0.210
Hands 0.0840 0.0746
Total area 0.312 0.285
Therefore, the total body part surface area that may be in contact with
2
the contaminant contained in the cleaning product is 0.312 m for men
n
and 0.285 m for women. For some cleaning products, only the hands may
be exposed. The assessor must determine all body parts that may come in
contact with a contaminant to estimate the total surface area of the body
dermally exposed to the contaminant.
4.2.10 Conclusion
For most dermal exposure scenarios, it is recommended that the body
surface areas presented in Table 4-1 be used following a determination of
.which body parts will be exposed. For most scenarios this will be a
straightforward determination; however, for some scenarios additional
considerations may need to be addressed. For example, the type of
clothing worn will have a significant effect on the surface area
exposed. An individual may wear gloves while contacting contaminated
4-14
-------
soil, which would reduce dermal exposure, or may wear shorts, short-
sleeve shirt, and no gloves, which would increase exposure potential.
Climatic conditions will also affect the type of clothing worn and, thus,
the skin surface area exposed.
For outdoor activities, the following "clothing" scenarios are
suggested:
Typical case: Individual will wear long-sleeve shirt,
pants, and shoes. Exposed areas will be head
. _ - and hands (0.20 mz).
Reasonable worst case: Individual will wear short-sleeve shirt,
shorts, and shoes. Exposed areas will be
head, hands, forearms, and lower legs (0.53 m2)
For these activities, the amount of clothing worn will differentiate
between typical and reasonable worst-case exposure conditions. Therefore,
mean values from Table 4-1 can be used to determine exposed surface area.
For activities in which the entire body is exposed (e.g., swimming,
bathing), the range of typical to reasonable worst-case exposure
conditions may be accounted for by using percentile data from Appendix
Table 4B-1. The 50th percentile would represent typical exposure
conditions (i.e., 1.94 m2 for adult males, 1.69 m2 for adult
females), and the 90th percentile would represent reasonable worst-case
exposure (i.e., 2.20 m2 for adult males, 1.98 m2 for adult females).
The body surface area data for children presented in Appendix 4B
(Tables 4B-3 and 4B-4) and Table 4-3 provide only rough estimations of
the surface area of body parts. We recommend that the data not be used
to represent all children within age groups presented unless the assessor
is particularly interested in the exposures of children and no other data
exist at that time.
4-15
-------
Typical scenarios involving dermal exposure will include dermal
contact with contaminated water and dermal contact with contaminated
soil. Since standard scenarios for dermal exposure have not yet been
developed, more detailed recommendations regarding selection of standard
dermal factors will be included in a later draft of this handbook.
4-16
-------
4.3 References
Boyd E. 1935. The growth of the surface area of the human body.
Minneapolis, Minnesota: University of Minnesota Press.
Buhyoff GJ, Rauscher HM, Hull RB, Killeeen K, Kirk RC. 1982. User's
manual for statistical processing system (version 3C.1). Southeast
Technical Associates, Inc.
DuBois D, DuBois EF. 1916. A formula to estimate the approximate
surface area if height and weight be known. Archives of Internal
Medicine 17:863-871.
Fujimoto S, Watanabe T. 1969. Studies on the body surface area of
Japanese. Acta Med. Nagasaki 13:1-13.
Gehan E, George GL. 1970. Estimation of human body surface area from
height and weight. Cancer Chemotherapy Reports 54(4):225-235.
Geigy Scientific Tables. 1981. Nomograms for determination of body
surface area from height and mass. Lentner, C. (ed.). CIBA-Geigy
Corporation, West Caldwell, N.J. pp. 226-227.
George SL. Gehan EA, Haycock GB, Schwartz GJ. 1979. Letters to the
Editor. The Journal of Pediatrics 94(2):342-342.
Haycock GB, Schwartz GJ, Wisotsky DH. 1978. Geometric method for
measuring body surface area: A height-weight formula validated in
infants, children, and adults. The Journal of Pediatrics 93(l):62-66.
Popendorf WJ, Leffinwell JT. 1976. Regulating OP pesticide residues for
farmworker protection. In: Residue Review 82. New York, NY:
Springer-Verlag New York, Inc., 1982. pp. 125-201.
Rochon J, Kalsbeek WD. 1983. Variance estimation from multi-stage
sample survey data: The Jackknife Repeated Replicate Approach.
Presented at 1983 SAS Users Group Conference, New Orleans, LA, January
1983.
Sendroy J, Cecchini LP. 1954. Determination of human body surface area
from height and weight. Journal of Applied Physiology 7(1):3-12.
USEPA. 1985. U.S. Environmental Protection Agency. Development of
statistical distributions or ranges of standard factors used in exposure
assessments. Washington, DC: Office of Health and Environmental
Assessment. EPA No. 600/8-85-010. Available from: NTIS, Springfield,
VA. PB85-242667.
Van Graan CH. 1969. The determination of body surface area. Supplement
to the South African Journal of Laboratory and Clinical Medicine 8-2-69.
4-17
-------
-------
APPENDIX 4A
Formulae for Total Body Surface Area
4-19
-------
APPENDIX 4A
Formulae for Total Body Surface Area
Most formulae for estimating surface area (SA) relate height to
weight. The first such equation can be expressed by:
SA = KW2/3
where
SA - surface area in square meters,
W « weight in kg, and
K is a constant (Gehan and George 1970).
While the above equation has been criticized because the specific gravity
of human bodies is not equal 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 has found wide acceptance and
use even to the1 present is that of DuBois and DuBois. Their model can be
written:
a,
,
SA = aQ H L W
where
SA « surface area in square meters,
H * height in centimeters, and
W - weight in kg.
The values of aQ (0.007182), aj (0.725), and a2 (0.425) were
estimated from a sample of only' nine individuals for which surface area
was directly measured. Boyd (1935) stated that the DuBois and DuBois
formula was used more extensively than any other for estimating 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. In addition, a computerized literature
search conducted for this report identified several articles written in
the last 10 years in which the DuBois and DuBois formula was used to
estimate body surface area.
4-20
-------
Boyd (1935) developed new constants for the DuBois and DuBois model
based on 231 direct measurements of body surface area she found in her
review of the literature. These data were limited to measurements of
surface area by coating methods (122 cases), surface integration
(93 cases), and triangulation (16 cases) made of 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 aQ = 0.01787, 3j = 0.500, and a2 = 0.4838.
Boyd also developed a formula based on weight alone, but this was
inferior to the DuBois and DuBois formula based on height and weight.
In 1970 Gehan and George 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). Included were data for some Japanese and
Chinese individuals, as well as for some individuals with unusual body
types. The methods used to measure these subjects were coating (163
cases), surface integration (222 cases), and triangulation (16 cases).
A least-squares method was used 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, rather than minimizing the sum of squared
absolute error, was used because the importance of an error of 0.1 square
meter depends on the surface area of the individual. Using the
least-squares.method on the 401 observations summarized in Boyd (1935),
Gehan and George (1970) obtained the following estimates of the
constants: aQ = 0.02350, aj = 0.42246, and a2 = 0.51456. Hence,
their equation for predicting surface area (SA) is:
SA = 0.02350 H°-42246 W°-51456
or in logarithmic form:
In SA= -3.75080 + 0.42246 In H + 0.51456 In W
4-21
-------
where
i
H = height in centimeters,
W - weight in kg, and
SA * surface area in square meters.
This prediction explains more than 99 percent of the variations in
surface area among the 401 individuals measured (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
individuals differed from the measured value by 25 percent or more.
Because each of the five individuals weighed less than 13 pounds, the
amount of difference was small. Eighteen estimates differed from
measurements by 15 to 24 percent. Of these, 12 weighed less than
15 pounds each, 1 was overweight (5 feet 7 inches, 172 pounds), 1 was
very thin (4 feet 11 inches, 78 pounds), and 4 were of average build.
Since the same observer measured surface area for these 4 individuals,
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. The different values for the
constants are presented below:
Estimated Parameter Values for Different Age Intervals
Age
group
All ages
<5 years old
>. 5 - <20 years old
>. 20 years old
Number
of persons
401
229
42
130
ao
0.02350
0.02667
0.03050
0.01545
al
0.42246
0.38217
0.35129
0.54468
a2
0.51456
0.53937
0.54375
0.46336
4-22
-------
The surface areas estimated by the values for all ages were compared
to surface areas estimated by the values for each age group for
individuals at the 3rd, 50th, and 97th percentiles of weight and height.
Nearly all differences in surface area estimates were less than 0.01
square meter, 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 aQ, 3j, and a2 by age interval.
Haycock et al. (1978) without knowledge of the work by Gehan and
George (1970), developed values for the parameters aQ, ap and a2
for the DuBois and DuBois model. Their interest in making the DuBois and
DuBois model more accurate arose 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 13.8 pounds at age
21 months. Haycock et al. (1978) used their own geometric method for
estimating surface area from 34 body measurements for 81 individuals.
Their study included newborn infants (10 cases), infants (12 cases),
children (40 cases), and adult members of the medical and secretarial
staffs of 2 hospitals (19 cases). The subjects all had grossly normal
body structure, but the sample included individuals of widely varying
physique ranging from thin to obese. Black, Hispanic, and white 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 coefficients: aQ = 0.024265, a, =
0.3964, and a2 = 0.5378. The result was the following equation for
estimating surface area:
SA = 0.024265 H°'3964 W°-5378
4-23
-------
expressed logarithmically as:
In SA = In 0.024265 + 0.3964 In H + 0.5378 In W.
The coefficients for this equation agree remarkably with those obtained
by Gehan and George (1970) for 401 measurements.
George et al. (1979) agree that a more complex model than the DuBois
and DuBois model 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 et al. (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:
In SA = In aQ + aj In H + a2 In W.
The values for aQ, ap and a2 obtained by the various authors
discussed in this section are presented below.
Summary of Surface Area Prediction Formulae
for the DuBois and DuBois Model
Author
(year)
DuBois and DuBois (1916)
Boyd (1935)
Gehan and George (1970)
Haycock et al . (1978)
Number
of persons
9
231
401
81
ao
0.007184
0.01787
0.02350
0.024265
al
0.725
0.500
0.42246
0.3964
a2
0.425
0.4838
0.51456
0.5378
The agreement between the model parameters estimated by Gehan and
George (1970) and Haycock et al. (1978) is remarkable in view of the fact
that Haycock et al. were unaware of the previous work. They used an
entirely different set of subjects, and they used geometric estimates of
4-24
-------
surface area rather than direct measurements. It has been determined
that the Gehen and George model is the formula of choice for estimating
total surface area of the body since it is based on the largest number of
direct measurements.
Nomoqrams
Sendroy and Ce.cchini (1954) proposed a graphical method whereby
surface area could be read from a diagram relating height and weight to
surface area. However, they do not give an explicit model for
calculating surface area. The graph was developed empirically bas.ed 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 formulae of other authors discussed above.
4-25
-------
-------
APPENDIX 4B
- , • */ -. -
Percentile Estimates of Total Body Surface Area and Surface Area
of Body Parts for Adult Males, Adult Females, Male Children,
and Female Children
4-27
-------
Table 4B 1. Surface Area of Adult Males in Square Meters
Percent i le
Body part
Total
Head
Trunk4
Upper extremities
Arms
Forearms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
5
1.66
0.119
0.591
0.321
0.241
0.106
0.085
0.653
0.539
0.318
0.218
0.114
10
1.72
0.121
0.622
0.332
0.252
0.111
0.088
0.676
0.561
0.331
0.226
0.118
15
1.76
0.123
0.643
0.340
0.259
0.115
0.090
0.692
0.576
0.341
0.232
0.120
25
1.82
0.124
0.674
0.350
0.270
0.121
0.093
0.715
0.597
0.354
0.240
0.124
50
1.94
0.130
0.739
0.372
0.291
0.131
0.099
0.761
0.640
0.382
0.256
0.131
2
0
0.
0
0
0
0
0
0
0
0
0
75
.07
.135
.807
.395
.314*
.144*,
.105
.810
.686*
.411*
.272
.138
85
2.14
0.138
0.851
0.408
0.328*
0.151*
0.109
0.838
0.714*
0.429*
0.282
0.142
90
2.20
0.140
0.883
0.418
0.339*
0.157*
0.112
0.858
0.734*
0.443*
0.288
0.145
95
2.28
0.143
0.935*
0.432*
0.354*
0.166*
0.117
0.888*
0.762*
0.463*
0.299*
0.149
s.e.
0.00374
0.0202
0.0118
0.00101
0.00387
0.0207
0.0187
0.00633
0.0130
0.0149
0.0149
0.0147
* Trunk includes neck.
"These percentile estimates exceed the maximum measured values upon which the equations are based.
s.e. » standard error for the 5-95 percentile of each body part.
4-28
-------
Table 4B-2. Surface Area of Adult Females in Square Meters
Percent ile
Body part
Total
Head
Trunk3
Upper extremities
Arms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
1.
0.
0.
0.
0,
0,
0.
0.
0.
0
0
5
,45
.106
.490
.260
.210
.0730
.564
.460
.271
.186
.100
10
1.49
0.107
0.507
0.265.
0.214
0.074.6.
0.582
0.477
0.281
0.192
0.103
15
1.53
0.108
0.518
0.269
0.217
0.0757
0.595
0.488
0.289
0.197
0.105
25
1.58
0.109
0.538
0.274
0.221
0.0777
0.615
0.507
0.300
0.204
0.108
50
1.69
0.111
0.579
0.287
0.230
0.0817
0.657
0.546
0.326
0.218
0.114
75
1.82
0.113
0.636
0.301
0.238*
0.868*
0.704
0.592
0.357
0.233
0.121
85
1.91
0.114
0.677
0.311
0.243*
0.0903*
0.736
0.623
0.379
0.243
0.126
90
1.98
0.115
0.704
0.318
0.247*
0.0927*
0.757
0.645
0.394
0.249
0.129
95
2.09
0.117
0.752
0.329
0.253*
0.0966*
0.796
0.683*
0.421*
0.261
0.134'
s.e.
0.00374
0.00678
0.00567
0.00833
0.00996
0.0172
0.00633
0.0130
0.0149
0.0149
0.0147
Trunk includes neck.
*These percentile estimates exceed the maximum measured values upon which the equations are based.
s.e. = standard error for the 5-95 percentile of each body part.
4-29
-------
Table 4B-3. Total Body Surface Area of Male Children in Square Meters
Percent He
Age
(yr)a
2 < 3
3 < 4
4 < 5
5 < 6
6 < 7
7 < 8
8 < 9
9 < 10
10 < 11
I1 < 12
12 < 13
13 < 14
14 < 15
15 < 16
16 < 17
17 < 18
3 < 6
6 < 9
9 < 12
12 < 15
15 < 18
5
0.527
0.585
0.633
0.692
0.757
0.794
0.836
0.932
1.01
1.00
1.11
1.20
1.33
1.45
1.55
1.54
0.616
0.787
0.972
1.19
1.50
10
0.544
0.606
0.658
0,721
0.788
0.832
0:397
0.966
1.04
1.06
1.13
1,24
1.39
1.49
1.59
1.56
0 . 636
0.814
1.00
1.24
1.55
15
0.552
0.620
0.673
0.732
0.809
0.848
0.914
0.988
1.06
1.12
1.20
1.27
1.45
1.52
1.61
1.62
0.649
0.834
1.02
1.27
1.59
25
0.569
0.636
0.689
0.746
0.821
0.877
0.932
1.00
1.10
1.16
1.25
1.30
1.51
1.60
1.66
1.69
0.673
0.866
1.07
1.32
1.65
50
0.603
0.664
0.731
0.793
0.866
0.936
1. 00
1.07
1.18
1.23
1.34
1.47
1.61
1.70
1.76
1.80
0.728
0.931
1.16
1.49
1.75
75
0.629
0.700
0.771
0.840
0.915
,0.993
1.06
1.13
1.28
1.40'
1.47
1.62
1.73
1.79
1.87
1.91
0.785
1.01
1.28
1.64
1.86
85
0.643
0.719
0.796
0.864
0.957
1.01
1.12
1.16
1.35
1.47
1.52
1.67
1.78
1.84
1.98
1.96
0.817
1.05
1.36
1.73
1.94
90
0.661
0.729
0.809
0.895
1.01
1.06
1.17
1.25
1.40
1.53
1.62
1.75
1.84
1.90
2.03
2.03
0.842
1.09
1.42
1.77
2.01
95
0.682
0.764
0.845
0.918
1.06
1.11
1.24
1.29
1.48
1.60
1.76
1.81
"1.91
2.02
2.16
2,09
0.876
1.14
1.52
1.85
2.11
a Lack of height measurements for children <2 years in NHANES II precluded calculation
of surface areas for this age group.
4-30
-------
Table 4B-4. Total Body Surface Area of Female Children in Square Meters
Percent ile
Age
(yr)a
2 < 3
3 < 4
4 < 5
5 < 6
6 < 7
7 < 8
8 < 9
9 < 10
10 < 11
11 < 12
12 < 13
13 < 14
14 < 15
15 < 16
16 < 17
17 < 18
3 < 6
6 < 9
9 < 12
12 < 15
15 < 18
5
0.516
0.555
0.627
0.675
0.723
0.792
0.863
0.897
0.981
1.06
1.13
1.21
1.31
1.38
1.40
1.42
0.585
0.754
0.957
1.21
1.40
10
0.532
0.570
0 . 639
0.700
0.748
0.808
0.886
0.948
1.01
1.09
1.19
1.28
1.34
1.42
1.46
1.49
0.610
0.790
0.990
1.27
1.44
15
. 0.544
0.589
0.649
0.714
0:770
0.819
0.913
0.969
1.05
1.12
1.24
1.32
1.39
1.43
1.48
1.51
0.630
0.804
1.03
1.30
1.47
25
0.557
0.607
0.666
0.735
0.791
0.854
0.932
1.01 ..-
1.10
1.16
1.27
1.38
1.45
1.47
1.53
1.56
0.654
0.845
1.06
1.37
1.51
50
0.579
0.649
0.706
0.779
0.843
0.917
1.00
1.06
1.17
1.30
1.40
1.48
1.55
1.57
1.60
1.63
0.711
0.919
1.16
1.48
1.60
75
0.610
0.688
0.758
0.830
0.914
0.977
1.05
1.14
1.29
1.40
1.51
1.59
1.66
1.67
1.69
1.73
0.770
1.00
1.31
1.61
1.70
85
0.623
0.707
0.777
0.870
0.961
1.02
1.08
1.22
1.34
1.50
1.62
1.67
1.74
1.72
1.79
1.80
0.808
1.04
1.38
1.68
1.76
90
0.637
0.721
0.794
0.902
0.989
1.06
1.11
1.31
1.37
1.56
1.64
1.75
1.76
1.76
1.84
1.84
0.831
1.07
1.43
1.74
1.82
95
0.653'
0.737
0.820
0.952
1.03
1.13
1.18
1.41
1.43
1.62
1.70
1.86
1.88
1.83
1.91
1.94
0.879
1.13
1.56
1.82
1.92
a Lack of height measurements for children <2 years in NHANES II precluded calculation
of surface areas for this age group.
4-31
-------
-------
5. OTHER FACTORS FOR EXPOSURE CALCULATIONS
5.1 Lifetime
Statistical data on life expectancy are published annually by the
U.S. Department of Commerce. The latest year for which statistics are
available is 1985. Preliminary data for 1985 show that life expectancy
for the total population is 74.7 years, for males 71.2 years, and for
females 78.2,years (Bureau of the Census 1986), Life expectancies for
various subpopulatioris from 1920 to 1950 are presented in Table 5-1.
Although 70 years has been widely used in the past, current data suggest
that 75 years would now be a more appropriate average value.
5.2 Body Weight
5.2.1 Background
Published percentile distributions for body weight for men and women
(Abraham et al. 1979) and male and female children (Hamill et al. 1979)
are based primarily on data gathered in the first National Health and
Nutrition Examination Survey conducted during 1970 to 1974. The source
of the data used in this study is the more recent, second National Health
and Nutrition Examination Survey, NHANES II.
NHANES II was conducted on a nationwide probability sample of approxi-
mately 28,000 persons, aged 6 months to 74 years, from the civilian, non-
institutionalized population of the United States. The survey began in
February 1976 and was completed in February 1980. The sample was selected
so that certain population groups thought to be at high risk of malnutri-
tion (persons with low incomes, preschool children, and the elderly) were
oversampled. Adjusted sampling weights were then computed for 76 age,
sex, and race categories in order to reflect the estimated civilian non-
institutionalized U.S. population aged 6 months to 74 years on March 1,
1978, the midpoint of the survey (National Center for Health Statistics
1983).
NHANES II provides information on 20,322 interviewed and examined
individuals. Selected sample persons for whom appointments could be made
were brought into examination centers. There, examinees changed from
5-1
-------
Table 5-1. Expectation of Life at Birth: 1920 to 1985
Year
1920
1930
1940
1950
1955
1960
1965
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985, prel
Total
54.1
59.7
62.9
68.2
69.6
69.7
70.2
70.8
71.1
71.2
71.4
72.0
72.6
72.9
73.3
73.5
73.9
73.7
74.2
74.5
74.6
74.7
74.7
Total
Male
53.6
58.1
60.8
65.6
66.7
66.6
66.8
67.1
67.4
67.4
67.6
68.2
68.8
69.1
69.5
69.6
70.0
70.0
70.4
70.9
71.0
71.2
71.2
Female
54.6
61,6
65. L'
71.1
72.8
73.1
73.7
74.7
75.0
75.1
75.3
75.9
76.6
76.8
77.2
77.3
77.8
77.4
77.8
78.1
78.1
78.2
78.2
Total
54.9
61.4
64.2
69.1
70.5
70.6
71.0
71.7
72.0
72.0
72.2
72.8
73.4
73.6
74.0
74.1
74.6
74.4
74.8
75.1
75.2
75.3
75.3
White
Male
54.4
59.7
62.1
66.5
67.4
67.4
67.6
68.0
68.3
68.3
68.5
69.0
69.5
69.9
70.2
70.4
70.8
70.7
71.1
71.5
71.7
71.8
71.8
Black and other
Female
55.6
63.5
66.6
72.2
73.7
74.1
74.7
75.6
75.8
75.9
76.1
76.7
77.3
77.5
77.9
78.0
78.4
78.1
78.4
78.7
78.7
78.8
78.7
Total
45.3
48.1
53.1
60.8
63.7
63.6
64.1
65.3
65.6
65.7
66.1
67.1
68.0
68.4
68.9
69.3
69.8
69.5
70.3
71.0
71.1
71.3
71.2
Male
45.5
47.3
51.5
59.1
61.4
61.1
61.1
61.3
61.6
61.5
62.0
62.9
63.7
64.2
64.7
65.0
65.4
65.3
66.1
66.8
67.2
67.3
67.2
Female
45.2
49.2
54.9
62.9
66.1
66.3
67.4
69,.4
69.8
70.1
70.3
71.3
72.4
72.7
73.2
73.5
74.1
73.6
74.4
75.0
74.9
75.2
75.2
Total
NA
NA
NA
NA
NA
NA
NA
64.1
64,6
64.7
65.0
66.0
66.8
67,2
67.7
68,1
68.5
68.1
68.9
69.4
69.6
69.7
69.5
BTack
Male
NA
NA
NA
NA
NA
NA
NA
60.0
60.5
60.4
60.9
61,7
62.4
62,9
63,4
63.7
64.0
63.8
64.5
65.1
65.4
65.5
65,3
Female
NA
NA
NA
NA
NA
NA
NA
68.3
68.9
69.1
69.3
70.3
71.3
71. IS
72.0
72.4
72.9
72.5
73.2
73.7
73.6
73.7
73.7
HA - not available.
Source: Bureau of the Census (1986).
5-2
-------
their street clothing into disposable paper examination uniforms and foam
rubber slippers designed to facilitate and standardize various elements
of the examination. Body measurements, including height and weight, were
made at various times of the day and in different seasons of the year;
thus, diurnal and seasonal variations in body measurements were not
standardized. This approach takes into account the fact that one's
weight may vary between winter and summer and may fluctuate with recency
of food and water intake and other daily activities (National Center for
Health Statistics 1983).
Weight was measured with a Toledo self-balancing scale that
mechanically prints weight to quarter-pound intervals directly onto the
permanent record. Direct printing was used to minimize observer and
recording errors. The scale was calibrated with a set of known weights,
and any necessary fine adjustments were made at each new examination
location (National Center for Health Statistics 1983).
5.2.2 Methods
NHANES II uses a multistage sample designed to represent the civilian
noninstitutionalized population of the United States, 6 months to 74 years
of age. Since the sample is not a simple random one, it is necessary to
incorporate the person's sample weight for proper analysis of the data.
The sample weight is a composite of the individual selection probability,
adjustments for nonresponse, and poststratification adjustments (National
Center for Health Statistics 1983).
The current methodologies appropriate for the analysis of data from
complex surveys such as NHANES II have not been made readily available in
the standard statistical software packages. In this study, percentiles
(and their standards errors) of the distribution of body weight have been
computed from the NHANES II data using the computer program QNTLS. QNTLS
is a SAS macro written in PROC MATRIX that performs variance estimation
of multistage sample survey data using the Jackknife Repeated Replicate
Approach (Rochon and Kalsbeek 1983). A more detailed discussion of this
program is presented in a paper by its authors found in Appendix A of the
5-3
-------
final report by USEPA (1985). Weighted mean body weights have been
determined from the NHANES II data using the SAS procedure UNIVARIATE
(SAS Institute, Inc. 1982).
5.2.3 Results
Mean body weights of adults, by age, and their'standard errors are
presented in Table 5-2 for men, women, and men and women combined. Mean
body weights of children, by age, and their standard errors are presented
in Table 5-3 for boys, girls, and boys and girls combined. Percent!Te
distributions of the body weights of adults and children are included in
Appendix 5A.
5.2.4 Application of Body Weight Data
A standard factor in exposure assessments is the average body weight
of individuals. The data in Table 5-2 present the mean body weights of
men and women, by age groups. The mean body weigjits for men and women
between the ages of 18 and 75 are also included. If the assessor has an
age and sex distribution of the exposed population, the mean body weight
values of the age groups can be used to better characterize body weights
within the population. If the number of individuals in the specific age
groups is not known, the average body weights for men and women (18 to
75) can be used as an estimation of body weights within the population.
The average body weights of adults, under the column headed "Men and
Women," were derived by adding the body weight values for men and the
body weight values for women, and dividing by two. The figures in this
column can be used if the assessor does not distinguish sex differences
within the population.
The data in Table 5-3 present the mean body weights of boys and girls,
by age group. The mean body weights for all children between the ages of
0 and 18 were not included by USEPA (1985), presumably because body
weights change relatively rapidly during these years. The assessor will
need an estimation of the age distribution within the exposed popula-
tion of children to determine the standard factor of body weight to be
used in exposure assessment. The average body weights of children, under
5-4
-------
Table 5-2. Body Weights of Adults (kilograms)
Mean
Age
18
25
35
45
55
65
< 25
< 35
< 45
< 55
< 65
< 75
73,
78.
80.
81.
78.
74.
.7
,7 '
.8
.0
.8
.8
Men
Std.
of
0.
0.
0.
0.
0.
0.
Women
error
mean
0035
0034
0040
0041
0041
0051
Mean
60.
64.
67.
67.
67.
66.
.6
2
,1
,9-
.9
.6
Std.
of
0.
0.
0.
0.
0.
0.
error
mean
0032
0037
0043
0044
0045
0048
Men and women
Mean Std. error
67.
71.
74.
74.
73.
70.
of mean
.2
.5
.0 ' — -
5
,4
,7
18 < 75 78.1 0.0016 65.4 0.0017 71.8
Source: Adapted from USEPA (1985).
5-5
-------
Table 5-3. Body Weights of Children (kilograms)
Mean
Age
<
3 <
6 <
9 <
12 <
15 <
3
6
9
12
15
18
11
17
25
35
50
64
.9
.6
.3
.7
.5
.9
Boys
Std
of
0
0
0
0
0
0
Girls
. error
mean
.0016
.0014
.0023
.0038
.0051
.0047
Mean
11
17
24
36
50
.2
.1 •
.6
.2
.7
57.4
Std.
of
0.
error
mean
0011
0.0015
0.
0.
0.
0.
0024
0043
0049
0042
Boys and qirls
Mean Std. error
11.
17.
25.
36.
50.
61.
of mean
6
4
0
0
6
2
Source: Adapted from USEPA (1985).
5-6
-------
the column headed "Boys and Girls," were derived by adding the body
weight values for boys and the body weight values for girls, and dividing
by two. The figures in this column can be used if the assessor does not;
distinguish between sexes of children.
5.2.5 Conclusion
Based on data from Table 5-2 for men and women combined, the value of
71.8 kg was rounded to 70 kg. Thus, 70 kg is recommended as the body
weight to use for adults. For younger ages, appropriate weights may be
selected from Table 5-3,
5.3 Activity Patterns
5.3.1 Background
Time use studies reveal human activity patterns within the population
and provide a means by which to estimate the duration of exposure to
contaminants in a particular setting or in a variety of settings over a
lifetime. A broad range of time use studies have^been conducted to
determine the amount of time spent in specific activities, such as
television viewing and commuting to and from work. On a larger scale,
four national studies of time use have been conducted to collect data on
how groups of people of different ages, sex, marital status, and
employment status use time, with one day (24 hours) as the sampling
unit. Different time use patterns depending on the day of the week
(i.e., weekdays, Saturdays, and Sundays) were also assessed to give
properly weighted weekly averages of time use.
The University of Michigan Institute for Social Research has compiled
information and created data bases for three of the national studies.
The earliest survey was conducted in 1965-66 as part of a multinational
study of daily activities in 12 countries (Szalai 1972). To meet the
study design criteria, the portion of the population sampled was limited
by age, occupation, and geographic location. The following groups of
people were excluded: (1) those over age 65, (2) those in farm-related
occupations, (3) those in households where no adult members were in the
5-7
-------
labor force for at least 10 hours per week, and (4) those who resided in
a town with a population of less than 30,000 (Robinson 1977). According
to Juster and Stafford (1985), these limitations eliminated approximately
40 percent of the 1965-66 U.S. population over 18 years of age.
The second study, conducted from fall 1975 to fall 1976, was complete-
ly nationally representative (Robinson 1977). The entire noninstitutional
population 18 years of age and older served as the sampling base, regard-
less of occupation. Excluded were individuals in college dormitories,
nursing homes, and other institutional settings. The Sampling Department
within the University of Michigan's Institute for Social Research main-
tains national lists of sampling units based on U.S. census information
about residential locations. A probability sample of households and
individuals was obtained from this information. The data for the 1975-76
study were collected from the sample of Americans who were first inter-
viewed in October through November of 1975 as part of the Institute's
1975 Fall Omnibus Study. The study covered time use plus a number of
other types of behavior that were of interest to other research programs
(Kalton 1985). The respondents in the 1975 general purpose survey were
chosen to form a representative sample of American adults living in the
continental United States. As part of the time use measurement effort,
spouses of respondents, when present, were also interviewed. The
original respondents and spouses were reinterviewed three times during
1976, in the months of February, May, and September. The result was an
annual representation of time use. Juster and Stafford (1985) discussed
the response rates and sample sizes in the four waves of the 1975-76
study. The first wave of the survey had 1,519 respondents, produced by a
response rate of 72 percent. The response rates for subsequent interviews
ranged from 75 percent in the first (February) reinterview to approximate-
ly 94 percent in the last (September) reinterview. The total number of
respondents who completed four time diaries with proper distribution
between weekdays and weekend days was 975.
5-8
-------
The third study, conducted in 1981-82, was a longitudinal panel
follow-up survey of respondents who participated in all four waves of the
1975-76 study. Since no new respondents were added to the sample, no
time diaries were obtained from individuals aged 18 to 24. The survey
had xa relatively low response rate and was not intended to be a
representative cross-section of the American population (Juster 1985a).
The fourth, and most recent, national study was conducted from
January through December of 1985 by Dr. John Robinson of the University of
Maryland Survey Research Center. Dr. Robinson was also a key figure in
the 1965-66 University of Michigan survey. The data from the 1985 study
have undergone preliminary analysis but are not currently available for
citation.
5.3.2 Estimations of Exposure Duration
Much of the following discussion of human time use patterns in the
United States and their subsequent use in estimating exposure durations
is based on the 1975-76 University of Michigan study. As previously
mentioned, the 1975-76 data were obtained through use of a time diary.
Respondents were asked to reconstruct the activities of the preceding
day, from midnight to midnight, in four separate interviews spaced
approximately 3 months apart. Time diary dates were selected to include
two weekdays, one Saturday, and one Sunday. Each time diary consisted of
a sequential list of activities and the time allotted to each activity,
with all minutes of the 24-hour period accounted for. The diaries were
then subjected to uniform coding procedures by a trained staff.
Data from each separate diary were weighted to adjust for the fact
that a week contains 5 weekdays, and all observations were weighted to
adjust for differential nonresponse (Hill 1985). In creating the weights,
researchers were attempting to produce a weighted sample with a sex and
age distribution close to the 1970 census distributions. Some groups of
respondents tended to have a lower response rate resulting in a higher
level of uncertainty. Reported values for these low response groups
required heavier weights to give an accurate representation of time use by
5-9
-------
these individuals. For example, single men between the ages of 18 and 25
may have a response rate of only 10 percent, whereas the response rate of
men in the age group 25 to 44 may be as high as 60 percent. Since respon-
dents should represent the entire male population within a particular age
group according to census information, the resulting values of time use
obtained from the time diaries of single men (18 to 25) must have propor-
tionately heavier weights. For a more detailed discussion of weighting
procedures, refer to Juster et al. (1983).
One inherent deficiency in the time diary method used for the 1975-76
study is the possible misrepresentation of time spent in activities that
take place rarely. Activities that take place every day or on a regular
basis for most individuals (e.g., sleeping, eating, and working) will be
sufficiently represented by the four diaries collected during the sampling
period. In contrast, a very large sample of days would be needed to give
an accurate representation of activities that take place rarely, such as
visiting museums, medical appointments, and attending sporting events.
Additionally, if an activity is frequent but highly variable in the amount
of time spent, small samples of days will have large sampling errors
(Juster 1985b).
Table 5-4 shows the ten major time use categories that formed the
basis of the aforementioned national studies. The data from all the
studies were coded in the same manner to allow comparisons of human
activity patterns through time. The categorization first divides activi-
ties into non-free activities (01-49), and free time activities (50-99).
Non-free activities are subdivided as follows: paid work codes (00-09),
family care (10-39), and personal care (40-49). The categories and
corresponding groups of activity codes are further broken down into the
87 activities presented in Table 5-5. A detailed explanation of the
coding scheme and activities is presented in Appendix 5B. The time use
data in Table 5-5 represent the activity patterns of all respondents of
the 1975-76 survey who completed acceptable time diaries for the four-
wave study. The data are given in units of mean hours per week spent in
5-10
-------
Table 5-4. Major Time Use Activity Categories
Activity code Activity
01-09
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Market work
House/yard work
Child care
Serv i ces/shopp ing
Personal care
Education
Organizations
Social entertainment
Active leisure
Passive leisure
5-11
-------
Table 5-5. Weighted Mean Hours Per Week by Sex:
87 Activities and 10 Subtotals
01
02
05
06
07
08
09
10
11
12
13
14
16
17
19
20
21
22
23
24
25
26
27
29
30
31
32
33
34
35
37
38
39
11
Activity
- Normal work
- Unemployment acts
- Second job
- Lunch at work
- Before/after work
- Coffee breaks
- Travel: to/from work
- Heal preparation
- Heal cleanup
- Indoor cleaning
- Outdoor cleaning
- Laundry
- Repairs/maintenance
- Gardening/pet care
- Other household
- Baby care
- Child care
- Helping/teaching
- Reading/talking
- Indoor playing
- Outdoor playing
- Medical care - child
- Babysitting/other
- Travel: child care
- Everyday shopping
- Durables/house shopping
- Personal care services
- Medical appointments
- Govt/f inancial services
•- Repair services
- Other services
- Errands
- Travel: goods/services
Men
N = 410
Mean
29
.78
0.14
0
1
0
0
2
1
0
0
1
0
2
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
.73
.08
.51
.57
.98
.57
.33
.85
.59
.13
.14
.94
.92
.24
.24
.07
.07
.13
.06
.01
.14
.23
.45
,19
.06
.15
.15
.11
.11
.04
1.60
Std. dev.
20.41
1.06
3.20
1.43
1.27
1.05
2.87
2.61
0.83
2.01
3.59
0.72
4.29
2.78
2.42
1.20
0.78
0.61
0.35
0.69
0.37
0.09
' 0.78
0.67
2.18
1.39
0.42
0.75
0.44
0.45
0.61
0.41
2.02
Women
N = 561
Mean
14
0
0
0
0
0
1
7
2
5
0
2
0
1
0
0
0
0
0
0
0
0
0
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.08
.17
,65
.23
.36
.45
.25
.30
.03
.56
.44
.68
.00
.72
.90
.99
.15
.30
.18
.12
.09
.64
0.50
2,78
0
0
0
.08
.35
.37
0.19
0
0
0
2
.1.7
.13
.06
.14
Std.
17.
0.
1.
1.
dev.
62
75
62
21
0.69
1.
2.
5.
2.
5.
1.
3.
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2.
1.
3.
2.
0.
0.
0.
0.
0.
2.
1.
3.
0.
1.
1.
0.
0.
0.
0.
2.
03
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04
19
05
59
34
43
1-9
84
04
11
76
86
82
72
67
58
21
25
51
14
63
61
,78
61
68
17
Men and women
N = 971
Mean
21.
0.
0.
0.
0.
0.
2.
4.
1.
3.
1.
1.
1.
0.
0.
0.
0.
0.
0.
0.
'0.
0.
0.
0.
2.
0.
0.
0.
0.
0.
0...
0.
1.
82
11
43
85
36
46
16
63
39
10
03
38
35
97.
81
60
64
11
19
16
09
05
41
38
17
13
22
27
17
14
12
05
89
Std. dev.
20.33
0,90
2.49
1.33
1.01
1.04
2.63
4.98
1.97
4.46
2.75
2.75
3.92
2.48
2. 13
2.40
1.68
0,70
0.68
0.76
0.58
0.50
1.98
1.00
2.89
1.01
0.90
1.31
0.54
0.65
0..61
0.57
2.12
5-12
-------
Table 5-5. (continued)
40 -
41 -
42 -
43 -
44 -
45 -
46 -
48 -
49 -
50 -
51 -
54 -
56 -
59 -
60 -
61 -
62 -
63 -
64 -
65 -
66 -
67 -
68 -
69 -
70 -
71 -
72 -
73 -
74 -
75 -
76 -
77 -
78 -
79 -
Activity
Washing/dressing
Medical care - adults
Help and care
Heals at home
Meals out
Night sleep
Naps/resting
N.A. activities
Travel: personal
Students' classes
Other classes
Homework
Other education
Travel: education
Professional/union
organizations
Identity organizations
Political/citizen
organizations
Volunteer/helping
organizations
Religious groups
Religious practice
Fraternal organizations
Child/family organizations
Other organizations
Travel: organizations
Sports events
Miscellaneous events
Movies
Theatre ,
Museums
Visiting with others
Parties
Bars/ lounges
.Other events
Travel: events/social
N
Mean
4.33
0.09
1.02
6.59
2.72
55.76
2.94
1.77
2.06
0.92
0.23
0.76
0.11
0.29
0.04
0.14
0.01
0.02
0.38 -
0.89
0.16
0.10
0.34
.0.43
0.30
0.07
0.31
0.13
0.04
4.24
0.64..:
0.71
0.12
1.40
Men
= 410
Std. dev.
2.39
0.67
2.84
3.87
3.48
8.43
5.18
6.12
2.59
4.00
1.68
3.48
0.86
1.07
0.46
0.97
0.08
0.32
1.82
2.05
1.17
0.88
2.40
1.04
1.31
0.52
1.25
0.93
0.37
5.72
2.05
2.21
0.72
1.82
Mean
5.43
0.18
1.30
6.32
2.24
56.74
3.19
1..99
1.61
0.38
0.15
0.38
0.02
0.16
0.04
0.18
0.02
0.14
0.41
1.31
0.05
0.21
0.32
0.52
0.26
0.08
0.26
0.06
0.03
5.84
0.44
0.46
0.18
1.26
Women
N = 561
Std. dev.
3.24
1.00
3.04
3.53
2.73
8.49
4.70 .
5.70
2.51
2.51
1.05
1.87
0.22
1.06
0.62
1.55
0.15
1.05
1.61
2.97
0.66
1.33
1.53
1.02
1.28
0.59
1.13
0.48
0.35
6.42
- . 1.65
2.09
1 . 18
1.67
Men
Mean
4.92
0.14
1.17
6.44
2.46
56.29
3.08
1.89
1.82
0.63
0.18
0.56
0.06
0.22
0.04
0.16
0.01
0.09
0.40
1.12
0.10
0.16
0.32
0.48
0.28
0.07
0.28
0.09
0.03
5.10
.0.53
0.57
0.15
1.32
and women
N - 971
Std. dev.
*
2.93
• 0.86
2i95
3.69
3.10
8.47
4.93
5.89
2.56
3.29
1.38
2.74
0.61
1.07
0.55
• 1.31
0.12
0.80
1.71
1.60
0.93
1.15
1.98
1.03
1.29
0.56
1.19
0.72
0.36
6.16
1.84
2.15
0.99
1.74
5-13
-------
Table 5-5. (continued)
Activity
80 - Active sports
81 - Outdoors
82 - Walking/biking
83 - Hobbies
84 - Domestic crafts
85 - Art/literature
86 - Music/drama/dance
87 - Games
88 - Classes/other
89 - Travel: active leisure
90 - Radio
91 - TV
92 - Records/tapes
93 - Reading books
94 - Reading magazines/N.A.
95 - Reading newspapers
95 - Conversations
97 - Letters
98 - Other passive leisure
99 - Travel: passive leisure
Totals by category:
Hr/wk market work
Hr/wk house/yard
Hr/wk child care
Hr/wk services/shop
Hr/wk personal care
Hr/wk education
Hr/wk organizations
Hr/wk social entertainment
Hr/wk active leisure
Hr/wk passive leisure
Total time
N
Mean
1.05 .
1.49
0.52
0.69
0.30
0.05
0.06
0.60
0.41
0.76
0.39
14.75
0.46
0.37
1.32
1.86
1.61
0.20
1.68
0.18
35.78
8.47
1.18
3.85
77. ?8
2.31
2.50
7.95
5.93
22.81
168.07
Hen
= 410
Std. dev.
2.62
4.59
1.31
3.88
1.59
0.45
0.49
2.00
1.75
1.91
1.40
12.14
2.35
1.52
2.81
2.72
2.19
1.06
3.53
0.49
23.63
9.03
2.52
4.48
13.02
7.73
5.47
. 8.34
8.23
14.11
0.11
N
Mean
0.50
0.48
0.23
0.06
2.00
0.13
0.07
0.99
0.28
0.43
0.39
13.95
0.33
0.56
1.97
1.47
2.18
0.31
1.41
0.13
17.94
19.99
3.86
6.28
79.00
1.10
3.20
8.86
5.15
22.71
168.08
Women
= 561
1!
Std. dev.
1.68
1.67
0.98
0.43
4.72
1.03
0.47
3.16
1.50
1.43
1.55
10.67
2.13
1.83
3.67
2.27
2.74
1.12
3.32
0.49
20.74
11.88
6.36
5.87
12.35
4.79
5.33
8.01
7.43
12.65
0.08
Men
N
Mean
0.76
0.94
0.36
0.35
1.21
0.09
0.07
0.81
0.34
0.58
0.39
14.32
0.39
0.47
1.67
1.65
1.91
0.26
1.53
0.15
26.18
14.67
2.62
5.16
78.21
1.66
2.88
8.44
5.51
22.75
168.08
and women
= 971
Std. dev.
2.18
3.39
1.16
2.67
3.93 .
0.81
0.48
2.69
1.62 .
1.68
1.49
11.38
2.23
1.70
3.32
2.49
2.52
1.10
3.42
0.49
23.83
12.11
5.15
5.41
12.68
6.35
5.40
8.17
7.81
13.34
0.09
Source: Hill (1985).
5-14
-------
each of the 87 activities by men, women, and men and women combined. The
standard deviation for each value is included. Tables 5-6 and 5-7 provide
additional time use data by age for men and women, respectively. The time
value shown for each activity in the column headed "Men" (Table 5-5) is
the weighted mean of the activity values for all four age groups shown in
Table 5-6. The time value shown for each activity in the column headed
"Women" (Table 5-5) is the weighted mean of the activity values for all
four age groups shown in Table 5-7. A percentile distribution (10th
through 90th percentile) and minimum and maximum time values for all
activities, men and women combined, are provided in Appendix 5C. However,
since these percentiles are based on only 4-day diaries of activities, it'
is uncertain how representative they are for long-term exposure assess-
ments. The reported mean values provide an appropriate estimate of long-
term behavior averaged over the population; however, the percentiles can
be appropriately applied to short term exposures (i.e., lengths comparable
to the length of the time-use study) such as acute exposure scenarios.
Tables 5-5, 5-6, and 5-7 allow varying degrees of specificity in the
application of time use data to the estimation of exposure duration. It
can be seen from these tables that mean hours per week spent in Market
(or paid) work activities (01-09) vary greatly by sex and age. Therefore,
the assessor may wish to estimate exposure duration based on time use in
these activities for all individuals (men and women, Table 5-5), men only
(Table 5-5), women only (Table 5-5), men of a specific age group
(Table 5-6), or women of a specific age group (Table 5-7). The amount of
time allotted to other groups of activities, such as Child care (20-29),
Personal care (40-49), and Education (50-59), show less pronounced differ-
ences between sexes but large variations by age. In order to estimate the
exposure duration of individuals or a population to a specific contami-
nant, all possible exposure pathways should be identified. An examination
of the 87 activities listed in Table 5-5 will enable the assessor to
identify human activities associated with the exposure pathways under
consideration.
5-15
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Time use data for children are extremely limited. As part of the
1981-82 panel follow-up of the 1975-76 study, time use diaries and ques-
tionnaires were administered to children of respondents. A total, of up to
three children between the ages of 3 and 17 were interviewed per house-
hold. Table 5-8 is a summary of children's time use data for 18 primary
activities obtained in the 1981-82 study. Data were collected from
children in two waves. Two time diaries were obtained from each child and
sample days were chosen to represent one school day and one nonschool day.
Therefore, the weekly averages of time use in Table 5-8 only represent
time when children are in school. Since vacation time is not accounted
for, the data do not provide an annual estimation of children's time use.
Other constraints of the 1981-82 study have been discussed. The values
for mean hours per week spent in the various activities in Table 5-8 are
the sum of five school days and two nonschool days. Standard deviations
and weighted means for boys and girls of all ages combined were not avail-
able in the data supplied by Timmer et al. (1985). Although there are
many deficiencies in the data, the time activity patterns representing
389 children in Table 5-8 provide the only estimate of children's time
use that is currently available.
5.3.3 Application of Time Use Data
The time use data from the 1975-76 study provide a data base of human
activity information. Once the exposure pathways of the contaminant of
concern are identified, an assessment of all activities associated with
the pathways can be performed. The total time allotted to the identified
activities can provide an estimate of exposure duration to the contami-
nant. The following examples illustrate how one can apply the data in
Tables 5-5, 5-6, and 5-7 to an estimation of time spent in three exposure
scenarios: (1) total time spent in the yard or outdoors at home; (2) time
at home vs. time away from home; and (3) and total time indoors vs. out-
doors. The data in Tables 5-6 and 5-7 have the same application as the
data in Table 5-5 and should be used for cases in which the assessor is
interested in determining exposure to a specific age group of men or
5-24
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Table 5-B. Mean Hours Per Week Spent by Children
In Primary Activities by Age and Sexa
Activity
Market work
Household work
Personal care
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoors
Hobbies
Art activities
Playing and games
TV
Reading
Household conversations
Other passive leisure
NA
Percent of time accounted
for by above activities
Boys 3-11
N = 118
1.56
2.49
4.98
9.35
69.50
21.00
1.30
3.52
2.10
3.18
1.83
0.35
0.46
17.32
15.78
1.15
1.30
1.28
2.50
94.3
Boys 12-17
N = 77
3.85
2.86
5.17
8.01
60.41
26.17
3.25
1.58
2.95
6.50
2.03
0.71
1.37
4.25
18.15
1.23
2.55
3.18
0.56
91.8
Girls 3-11
N = 111
0.13
3.18
5.34
9.30
69.80
21.58
1.88
2.36
1.98
1.77
1.35
0.21
0.46
15.11
14.73
0.91
1.21
1.74
3.05
91.1 .
Girls 12-17
N = 83
2.58
6.30
8.45
7.92
60.23
28.50
3.91
1.78
3.85
3.95
1.46
0.56
0.80
1.88 ,
13.67
1.71
3.50
1.33
1.55
90.7
This is applicable only for the time of year when children attend school.
Source: Adapted from Timmer et al. (1985).
5-25
-------
women. For simplicity, Table 5-5 will be the reference data set in the
following examples. Note that several activities are not specifically
defined in the tables and the assessor must use judgment and the descrip-
tive information included in Appendix 5B to determine the activities that
are associated with a particular exposure pathway or set of pathways. It
is assumed that there is no overlap or double-counting of time spent in
each of the 87 activities. As discussed in Section 5.3.2, all time
diaries were uniformly coded by a trained staff. Respondent diaries
contained a sequential list of primary activities throughout the 24-hour
sampling period. Refer to Appendix 5B for a listing of all activities
included under each activity code.
(1) Example 1. In the case of the presence of a contaminant in the
yards of households, the assessor may estimate the time spent in the yard
by identifying activities in Table 5-5 that take place outdoors at home.
Adding the mean time values for the identified activities results in a
figure that is an estimation of exposure duration to the contaminant
present in the yard. Activities that take place outdoors at home include:
13 - Outdoor cleaning;
16 - Outdoor repair/maintenance;
17 - Gardening/pet care;
19 - Other household;
25 - Outdoor playing; and
80 - Active sports.
Activities 16, 17, and 19 may include indoor and outdoor activities, while
Activity 80 may include time outdoors away from home as well as time
spent in the yard. Based on the characteristics of the pollutant and the
extent of contamination, the assessor may choose to include all or only a
percentage of the time given for Activities 16, 17, 19, and 80 in an esti-
mation of time spent in the yard. For example, adding the mean hours per
week spent in Activities 13 and 25, and assuming that 50 percent of the
time coded to Activities 16, 17, 19, and 80 is spent in the yard, the
results are as follows:
5-26
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Time Spent Outdoors at Home
(weighted mean hours per week)
Men 4.17
Women 2.13
Men and Women 3.07
(2) Example 2. A comparison of importance, in terms of exposure to
contaminants in and around the residence, is the amount of time spent at
home vs. away from home. A review of literature.relating to the coding
scheme for the 87 activities in Table 5-5 resulted in the following break-
down of activity codes by number (refer to Table 5-5 for activity
descriptions):
Activity Code Numbers
Time spent at home: 10-27, 40-43, 45-48, 54, 75-76 (50%),
. .. 83-85, 87 (50%), 90-98 (50%)
Time spent away from home: 01-09, 29-39, 44, 49-51, 56-74, 75-76
(50%), 77-82, 86, 87 (50%), 88-89, 90-98
(50%), 99.
Although many codes involve a mix of at-home and away-from-home activi-
ties, most codes were assigned to one category only. For codes where this
would obviously be incorrect, a 50-50 split was assumed. A more detailed
analysis was not considered necessary for this example.
Adding the mean time values for the activities in each of the above
two categorical breakdowns results in the following time use estimates:
Weighted Mean Hours Per Week
Men Women Men and Women
Time spent at home 97.80 115.98 107 59
Time spent away from home 70.27 52.10 6o!49
These figures indicate that, on average, men spend roughly 58 percent of
their time at home, women spend approximately 69 percent of their time at
home, and the average adult spends 64 percent of his/her time at home.
(3) Example 3. Another time use comparison that is useful in the
estimation of exposure duration to indoor and outdoor pollutants is the
5-27
-------
amount of time spent indoors vs. outdoors. A summary of earlier time use
studies by Chapin (1974) and Szalai (1972) is provided in Table 5-9. The
data from the Chapin (1974) study were collected from residents of
Washington, D.C. Time use data from urban and suburban populations in
12 countries, including the United States, were collected in the Szalai
(1972) study. The data in Table 5-9 indicate that adults spend approxi-
mately 93 percent of their time indoors, 2 percent outdoors, and 5 percent
in transit (e.g., car, train, bus).
In order to determine the amount of time spent indoors, outdoors, and
in transit from the time use data in Table 5-5, all outdoor and transit
activities were identified. The remaining activities take place indoors.
Refer to Table 5-5 for activity descriptions.
Activity Code Numbers
Time spent outdoors: 13, 16*, 17, 19* 25, 70*, 80*, 81, 82
Time spent in transit: 09, 29, 39, 49, 59, 69, 79, 89, 99.
*Assuming 50 percent of the time allotted to these activities is
spent outdoors.
Although some codes involve a mix of indoor and outdoor activities, most
codes were assigned to one category only. For codes where this would
obviously be incorrect, a 50-50 split was assumed. A more detailed
analysis was not considered necessary for this example.
Mean time values were added and percent of daily time in each location
was calculated for the amount of time spent outdoors and in transit. All
remaining time was assumed to be spent indoors. The results are as
fol1ows:
Time (weighted mean
hours per week) Percent of Daily Time
Men
Women
Hen and Women
Outdoors
5.28
2.77
3.91
In
transit
9.93
8.20
9.00
Indoors
152.87
157.11
155.17
Outdoors
3.1
1.6
2.3
In
transit
5.9
4.9
5.4
,
Indoors
91.0
93.5
92.4
5-28
-------
Table 5-9. Summary of Average Time-Activity Patterns for a 24-Hpur
Period from Studies by Chapin (1974) and Szalai (1972)a
Location
Hours in each location
Chapin (1974)
Szalai (1972)
: Indoors
Home
Work
Other
Subtotal
16.03
4.61
1.31
21.95
16.75
4.03
1.63
22.41
Outdoors
Home
Work
Other •
Subtotal
0.27
0.27
0.54
0.23
0.12
0.35
In transit
All modes
1.16
1.25
TOTAL
23.65U
24.01
Adapted from Sexton and Ryan (1987).
Shortfall, from 24 hours not explained by the author.
5-29
-------
The estimates of time spent indoors, outdoors, and in transit from the
time use data in Table 5-5 for men and women combined are virtually the
same as the estimates from the earlier studies (Table 5-9).
•Comparisons of the data in Table 5-9 to the previously calculated
values in Examples 1 and 2 were also performed. According to the studies
summarized in Table 5-9, the average adult spends 0.23 to 0.27 hour per
day, or 1.6 to 1.9 hours per week, outdoors at home. These figures are
slightly lower than the previous estimates of time spent outdoors at home
using the activity data in Table 5-5. By the method proposed in this
section it was determined that men, women, and men and women combined
spend 4.17, 2.13, and 3.07 mean hours per week outdoors at home, respec-
tively. One source of discrepancy lies in the fact that Table 5-9 reports
time-activity patterns for a 24-hour period. The time values in Table 5-5
are mean hours per week weighted to reflect time use on weekdays and week-
end days combined. Therefore, the additional time that respondents of the
1975-76 study spent outdoors on weekends (Hill 1985) is accounted for in
Table 5-5. This distinction is not necessarily reflected in the data from
studies by Chapin (1974) and Szalai (1972).
Table 5-9 also provides an estimation of time spent at home. The
studies indicate that adults spend an average of 68 to 71 percent of
their total daily time at home. These figures roughly correspond to the
time use estimates calculated in Example 2, where it was determined that
average adults spend 73 percent of their time at home.
These examples demonstrate the use of time-activity data in
determining the average amount of time a population spends in specific or
broad groups of activities. The amount of time allotted to an activity
represents the duration of exposure to a contaminant associated with the
activity. Exposure scenarios will vary among different contaminants and
judgment is required when identifying all activities related to exposure
pathways.
5-30
-------
5.3.4 Regional Variations
Other factors that may affect exposure duration are regional varia-
tions in time use patterns and mobility of the population. Analysis of
the 1975-76 survey data revealed very small regional differences in time
use. Hill (1985) discussed a few notable variations. In southern regions
respondents averaged somewhat larger amounts of time in outdoor activities
and recreation, such as gardening/pet care, fishing, boating, camping,
etc. Hill (1985) also rioted that the ratio of time spent playing outdoors
with children to time spent playing indoors with children was much higher
for adults in the South than for those in other parts of the country.
Adults in the West also averaged somewhat more time in outdoor activities
than did adults in the North Central or Northeast regions. These
variations in time use are presumably due to climatic differences between
regions. Other regional differences were present in the activity areas
of personal care and leisure. Adults in the South tended to spend larger
amounts of time sleeping and less time eating (meals out and at home plus
lunch at work) than adults in other areas. However, adults in the South
spent a larger proportion of their time eating at home. Respondents from
the South averaged more leisure time in domestic crafts than adults in
the'Northeast, and they spent more time watching television than adults
in the West or North Central regions. Overall, regional differences in
time use are relatively small. The trends discussed above may warrant
consideration in contamination problems in the South and West. A listing
of states that correspond to these geographic areas was not included in
the discussion.
5.3.5 Population Mobility
An assessment of population mobility can aid in determining the length
of exposure of a household 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. The Bureau of the
5-31
-------
Census provides information about population mobility; however, this
information is difficult to use to determine the average residence time of
a homeowner or apartment dweller. Census data provide representations of
a cross-section of the population at specific points in time, but the
surveys are not designed to follow individual families through time.
Appendix 5D summarizes the most current Bureau of the Census information
about population mobility.
Other organizations that use residence history information include
banks, insurance companies, and credit card companies. Several companies
and banks were contacted, and it was determined that residence history
information is not compiled statistically or the information is considered
confidential and is not available for release to the public. Several
real estate and housing associations throughout the country were also
contacted. Again, the majority of associations do not follow families or
individuals through time. The available information is provided below.
According to Oxford Development Corporation, a property management
firm, the average residence time for an apartment dweller has been
estimated to range from 18 to 24 months. A survey of recent home
buyers was conducted in 1986 by the National Association of Realtors.
The survey provides an overall residence history of 1,200 respondents.
The results of the survey were as follows:
Percent of respondents Years lived in previous house
5 1 year or less
25 2-3
36 4-7
10 8-9
24 10 years or more
J. Hendricks, Sales Department, Oxford Development Corporation,
personal communication with K. Lisi (Versar) September 10, 1987,
J. Beckord, Economist, National Association of Realtors,
Washington, D.C., personal communication with K. Lisi (Versar)
September 14, 1987.
5-32
-------
The average length of residence in respondents' previous house was 7 years
and the median length was 6 years. Note that the sample includes only
recent buyers of houses and not people living in their first house; there-
fore, the above figures are biased estimates. Because of uncertainty in
these estimates, the values were not used in exposure scenarios.
In a survey representing all occupied housing units, conducted in
1983 by the Bureau of the Census, it was determined that 93 percent of
householders moved into their present unit between 1950 and 1983 (Bureau
of Census 1983). The householders owned the unit they occupied at the
time of the survey. The information pertaining to residence time of
owner-occupied housing units is as follows:
Year householder Percent of total
moved into unit householders
1982-1983 7.5
1980-1983 24.4
1970-1983 64.6
1965-1983 75.6
1960-1983 83.5
1950-1983 93.0
Using these data, the percent of householders living in houses for
specified ranges of time can be determined as follows:
Years lived in Percent of total
current home householders
0-1 7.5
1-3 16.9
3-13 40.2
13 - 18 11.0
18 - 23 7.9
23-33 9.5
>33 7.0
Based on these statistics, 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
5-33
-------
sample size (18,825 households) to the indicated percentile associated
with the applicable range of years lived in current home. Assuming an
even distribution within the appropriate range, the 50th and 90th
percentile values for years living in current home were determined to be
9.37 and 29.84 years, respectively. These were then rounded to 9 and
30 years. The 50th percentile represents the average length of time a
typical homeowner will live in the same house, while the 90th percentile
is assumed to represent a reasonable worst case. Therefore, based on the
above surveys, the range of 9 to 30 years will be used in the final
section of this report to represent the average length of residence and
reasonable upper bound of residence time, respectively. Additional
aspects such as regional variability, as well as differences among rural,
suburban, and urban areas, will be investigated in future editions of this
handbook.
5.3.6 Showering
Another current concern is the possibility of exposure to contaminants
during the time individuals spend showering. Contaminants may include
tribalomethanes and a variety of other volatile organic compounds that can
be released to the air from heated water used in the shower. According
to Tarshis (1981), 90 percent of the American population takes some sort
of bath every day and 5 percent average more than one bath per day. Of
these, 75 percent of men and 50 percent of women use showering as a
primary means of bathing.
The amount of time spent showering may vary. No information could be
found that specifically referred to differences in the time men, women,
and children spend showering. Shower flow rates range from 5 to
15 gallons per minute. For a shower length of 5 minutes, the average
amount of water used is 40 gallons.*
C. Cameron, Customer Service Office, Washington Surburban Sanitary
Commission, personal communication with K. Lisi (Versar) August 26,
1987.
5-34
-------
A recent study conducted in Australia provided a distribution of the
amount of time spent showering (James and Knuiman 1987). This distribu-
tion was based on diary records of 2,500 households. Using these data, a
cumulative frequency distribution was derived and is presented in
Table 5-10. Based on these results, the median shower length is approxi-
mately 7 minutes and the 90th percentile is approximately 12 minutes.
In addition to inhalation of volatilized organics from showering,
Andelman et al. (1986) pointed out that volatilization from other indoor
water uses may also be significant. Andelman et al. (1986) suggest that
releases from other sources (e.g., dishwasher, cooking, washing machine)
also add to the overall indoor air levels of volatile organics. Releases
from showering and these other sources will disperse throughout the
house, leading to longer exposure times.
5-35
-------
Table 5-10. Cumulative Frequency Distribution of Average
Shower Duration for 2,500 Households
Shower durat ion
(minutes)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Cumulative frequency
(percentage) •
0.20
0.80
3.20
9.80
22.60
38.20
52.60
63.80
73.40
81.00
86.20
90.20
92.40
94.20
95.60 '
96.80
97.60
98.60
99.40
100.00
Source: James and Knuiman (1987).
5-36
-------
5.4 References •
Abraham S, Johnson CL, Najjar MF. 1979. National Center for Health
Statistics, weight and height of adults 18-74 years of age: United
States, 1971-74. Vital and Health Statistics. Series 11 - No. 211.
Public Health Service. Washington, DC: U.S. Government Printing Office.
DHEW Pub. No. (PHS) 79-1659.
Andelman JB, Meyers SM, Wilder LC. 1986. Volatilization of organic
chemicals from indoor uses of water. Chemicals in the environment.
Lester JN, Perry R, Sterritt RM, eds. London: Selper Ltd.
Bureau of the Census. 1983. Current Housing Reports, Series H-150-83.
Housing characteristics of recent movers for the United States and
Regions: 1983. Annual Housing Survey: 1983, Part D.Washington, DC:
U.S. Government Printing Office.
Bureau of the Census. 1984. Statistical abstract of the United States:
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Bureau of the Census. 1986. Statistical abstract of the United States:
1987. 107th ed. Washington, DC: U.S. Government Printing Office. '
Chapin S. 1974. Human activity patterns in the city: things people do
in time and in space. New York: Wiley Interscience.
Hamill PVV et al. 1979. Physical growth: National Center for Health
Statistics percentiles. American Journal of Clinical Nutrition
32:607-629.
Hill MS. 1985. Patterns of time use. in: Juster FT, Stafford FP,
eds. Time, goods, and well-being. Ann Arbor, MI: Survey Research
Center, Institute for Social Research. University of Michigan, pp.
133-166.
James IR, Knuiman MW. 1987. An application of Bayes methodology to the
analysis of diary records from a water use study. Journal of the
American Statistical Assoc. 82(399):705-711.
Juster FT. 1985a. A note on recent changes in time use. In:
Juster FT, Stafford FP, eds. Time, goods, and well-being. Ann Arbor, MI
Survey Research Center, Institute for Social Research. University of
Michigan, pp. 313-330.
Juster FT. 1985b. Conceptual and methodological issues involved in the
measurement of time use. In: Juster FT, Stafford FP, eds. Time, goods,
and well-being. Ann Arbor, MI: Survey Research Center. Institute for
Social Research. University of Michigan, pp. 19-31.
5-37
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Ouster FT, Stafford FP, eds. 1985. Time, goods, and well-being.
Ann Arbor, MI: Survey Research Center, Institute for Social Research.
University of Michigan.
Ouster FT, Hill MS, Stafford FP, Parsons OE. 1983. Study description.
1975-1981 time use longitudinal panel study. Ann Arbor, MI: Survey
Research Center, Institute for Social Research. The University of
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Kalton G. 1985. Sample design issues in time diary studies, in.:
Ouster FT, Stafford FP, eds. Time, goods, and well-being. Ann Arbor, MI
Survey Research Center, Institute for Social Research. University of
Michigan, pp. 93-108.
National Center for Health Statistics. 1983. Public use data tape
documentation, antropometric, National Health and Nutrition Examination
Survey, 1976-1980, Hyattsville, Maryland.
Robinson OP. 1977. Changes in Americans' use of time: 1965-1975.
progress report. Communication Research Center, Cleveland State
University.
A
Rochon 0, Kalsbeek WD. 1983. Variance estimation from multi-stage
sample survey data: The jackknife repeated replicate approach.
Presented at 1983 SAS Users Group International Conference, New Orleans,
LA, Oanuary 1983.
SAS Institute, Inc. 1982. SAS Users Guide: Basics. 1982 edition.
Cary, NC.
Sexton K, Ryan PB. 1987. Assessment of human exposure to air pollution:
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Sciences Press.
F i hi "' ii
Szalai A., ed. 1972. The use of time: daily activities of urban and
suburban populations in twelve countries. Paris: Mouton, The Hague.
Tarshis B. 1981. The "Average American" book.
American Library, p. 191.
New York, NY,: New
Timmer SG, Eccles 0, O'Brien K. 1985. How children use time. In:
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Survey Research Center, Institute for Social Research. University of
Michigan, pp. 353-380.
5-38
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University of Michigan. 1976. Ann Arbor, MI: Institute for Social
Research. Unpublished data.
USEPA. 1985. U.S. Environmental Protection Agency. Development of
statistical distributions or ranges of standard factors used in exposure
assessments. Washington, DC: Office of Health and Environmental
Assessment. EPA No. 600/8-85-010. Available from: NTIS, Springfield,
VA. PB85-242667.
5-39
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APPENDIX 5A
Percentile Distribution of the Body Weights
of Adults and Children
5-41
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APPENDIX 5B
Activity Codes and Descriptors Used
for Adult Time Diaries
5-47
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Appendix SB. Activity Codes and Descriptors Used for Adult Time Diaries
WORK AND OTHER INCOME-PRODUCING ACTIVITIES
Paid Work
01 - Normal work: activities at the main job including work brought home, travel that is
part of the job, and overtime; "working," "at work"
— Work, at home; work activities for pay done in the home when home is the main workplace
(include travel as above)
OH - Job search; looking for work, including visits to employment agencies, phone calls to
prospective employers, answering want ads
- Unemployment benefits; applying for or collecting unemployment compensation
- Welfare, food stamps; applying for or collecting welfare, food stamps
05 - Second job; paid work activities that are not part of the main job (use this code only
when R* clearly indicates a second job or "other" job); paid work for those not having
main job; garage sales, rental property
OS - Lunch at the workplace; lunch eaten at work, cafeteria, lunchroom when "where" = work
(lunch at a restaurant, code 44; lunch at home, code 43)
- Eating, smoking, drinking coffee as a secondary activity while working (at workplace)
07 - Before and/or after work at the workplace; activities at the workplace before starting
or after stopping work; include "conversations," other work. Do not code secondary
activities with this primary activity
- Other work-related
08 - Coffee breaks and other breaks at the workplace; unscheduled breaks and other nonwork
during work hours at the workplace; "took a break"; "had coffee" (as a primary
activity). Do not code secondary activities with this primary activity
09 - Travel; to and from the workplace when R's travel to and from work were both
interrupted by stops; waiting for related travel
- Travel to and from the workplace, including time spent awaiting transportation
HOUSEHOLD ACTIVITIES
Indoor
10 - Heal preparation: cooking, fixfng lunches
- Serving food, setting table, putting groceries away, unloading car after grocery
shopping
11 - Doing dishes, rinsing dishes, loading dishwasher
- Heal cleanup, clearing table, unloading dishwasher
5-48
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Appendix SB. (continued)
HOUSEHOLD ACTIVITIES (continued)
Indoor (continued)
12 - Miscellaneous, "worked around house," NA if indoor or outdoor
- Routine indoor cleaning and chores, picking up, dusting, making beds, washing windows,
vacuuming, "cleaning," "fall/spring cleaning," "housework"
14 - Laundry and clothes care - wash
- Laundry and clothes care - iron, fold, mending, putting away clothes ("Sewing" code 84)
16 - Repairs indoors; fixing, repairing appliances
- Repairs indoors; fixing, repairing furniture
- Repairs indoors; fixing, repairing furnace, plumbing, painting a room
17 - Care of houseplants
19 - Other indoor, NA whether cleaning or repair; "did things in house"
Outdoor ,
13 - Routine outdoor cleaning and chores; yard work, raking leaves, mowing grass, garbage
removal, snow shoveling, putting on storm windows, cleaning garage, cutting wood
16 - Repair, maintenance, exterior; fixing repairs outdoors, painting the house, fixing the
roof, repairing the driveway (patching)
- Home improvements: additions to and remodeling done to the house, garage; new roof
- Improvement to grounds around house; repaved driveway
17 - Gardening; flower or vegetable gardening; spading, weeding, composting, picking,
"worked in garden"
19 - Other outdoor; "worked outside," "puttering in garage"
MISCELLANEOUS HOUSEHOLD CHORES
16 - Car care; necessary repairs and routine care to cars; tune up
- Car maintenance; changed oil, changed tires, washed cars; "worked on car" except when
clearly as a hobby - (code 83)
17 - Pet care; care of household pets including activities with pets; playing with the dog;
walking the dog; (caring for pets of relatives, friends, code 42)
19 - Household paperwork; paying bills, balancing the checkbook, making lists, getting the
mail, working on the budget
- Other household chores; (no travel), picking up things at home, e.g., "picked up
deposit slips" (relate travel to purpose)
5-49
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Appendix SB. (continued)
CHILD CARE
Child Care for Children of Household
20 - Baby care; care to children aged 4 and under
21 - Child care; care to children aged 5-17
- Child care; mixed ages or NA ages of children
22 - Helping/teaching children learn, fix, make things; helping son bake cookies; helping
daughter fix bike
- Help with homework or supervising homework
23 - Giving children orders or instructions; asking them to help; telling them to behave
- Disciplining child; yelling at kids, spanking children; correcting children's behavior
- Reading to child
- Conversations with household children only; listening to children
24 - Indoor playing; other indoor activities with children (including games ("playing")
unless obviously outdoor games)
25 - Outdoor playing; outdoor activities with children including sports, walks, biking
with, other outdoor games
- Coaching/lead ing outdoor, nonorganizational activities
26 - Medical care at home or outside home; activities associated with children's health;
"took son to doctor," "gave daughter medicine"
Other Child Care
27 - Babysitting (unpaid) or child care outside R's home or for children not residing in HH
- Coordinating or facilitating child's social or instructional nonschool activities;
(travel related, code 29)
- Other child care, including phone conversations relating to child care other than
medical
29 - Travel related to child's social and instructional nonschool activities
- Other travel related to child care activities; waiting for related travel
OBTAINING GOODS AND SERVICES
Goods (include phone calls to obtain goods)
30 - Groceries; supermarket, shopping for food
- All other shopping for goods; including for clothing, small appliances; at drug
stores, hardware stores, department stores, "downtown" or "uptown," "shopping,"
"shopping center," buying gas, "window shopping"
5-50
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Appendix 58. (continued)
OBTAINING GOODS AND SERVICES (continued)
Goods (continued)
31 -. Durable household goods; shopping for large appliances, cars, furniture
- House, apartment; activities connected to buying, selling, renting, looking for house,
apartment, including phone calls; showing house, including traveling around looking at
real estate property (for own use) . . . - .
Services (include phone conversations to obtain services)
32 - Personal care; beauty, barber shop; hairdressers'
33 - Medical care for self; visits to doctor, dentist, optometrist, including making
appointments
34 - Financial services; activities related to taking care of financial business; going to
the bank, paying utility bills (not by mail), going to accountant, tax office, loan
agency, insurance office
- Other government services: post office, driver's license, sporting licenses, marriage
licenses, police station
35 - Auto services; repair and other auto services including waiting for such services
- Clothes repair and cleaning; cleaners, laundromat, tailor
- Appliance repair: including furnace, water heater, electric-or battery operated
appliances; including watching repair person
- Household repair services: including furniture; other repair services NA type;
including watching repairperson
37 - Other professional services; lawyer, counseling (therapy)
- Picking up food at a takeout place - no travel
- Other services, "going to the dump"
38 - Errands; "running errands," NA whether for goods or services; borrowing goods
39 - Related travel; travel related to obtaining goods and services and/or household
activities-except 31; waiting for related travel
PERSONAL NEEDS AND CARE '
Care to Self .
40 - Washing, showering, bathing
- Dressing; getting ready, packing and unpacking clothes, personal hygiene, going to the
bathroom
41 - Medical care at home to self
5-51
-------
Appendix 56. (continued)
PERSONAL HEEDS AND CARE (continued)
Care to Self (continued)
43 - Meals at home; including coffee, drinking, smoking, food from^a restaurant eaten at
home, "breakfast," "lunch"
44 - Heals away from home; eaten at a friend's home (including coffee, drinking, smoking)
- Heals away from home, except at workplace (06) or at friend's home (44); eating at
restaurants, out for coffee
45 - Night sleep; longest sleep for day; (may occur during day for night shift workers)
including "in bed," but not asleep
46 - Naps and resting; rest periods, "dozing," "laying down" (relaxing code 98)
48 - Sex, making out
- Personal, private; "none of your business"
- Affection between household members; giving and getting hugs, kisses, sitting on laps
Help and Care to Others
41 - Medical care to adults in household (HH)
" ,ii"
42 - Nonmedical care to adults in HH; routine nonmedical care to adults in household; "got
my wife up," "ran a bath for my husband"
- Help and care to relatives not living in HH; helping care for, providing for needs of
relatives; (except travel) helping move, bringing food, assisting in emergencies,
doing housework for relatives; visiting when sick
- Help and care to neighbors, friends
- Help and care to others, NA relationship to respondent
Other Personal and Helping
48 - Other personal; watching personal care activities
49 - Travel (helping); travel related to code 42, including travel that is the helping
activity; waiting for related travel
- Other personal travel; travel related to other personal care activities; waiting for
related travel; travel, NA purpose of trip - e.g., "went to Memphis" (no further
explanation given)
EDUCATION AND PROFESSIONAL TRAINING
50 - Student (full-time); attending classes, school if full-time student; includes daycare,
nursery school for children not in school
5-52
-------
Appendix 5B. (continued)
EDUCATION AND PROFESSIONAL TRAINING (continued)
51 - Other classes, courses, lectures, academic or professional; R not a full-time student
or NA whether a student; being tutored
54 - Homework, studying, research, reading, related to classes or profession, except for
current job (code 07); "went to the library"
56 - Other education
59 - Other school-related travel; travel related to education coded above; waiting for
related travel; travel to school not originating from home
ORGANIZATIONAL ACTIVITIES :
Volunteer. Helping Organizations: hospital volunteer group. United Fund, Red Cross, Big
Brother/Sister
63 - Attending meetings of volunteer, helping organizations
- Officer work; work as an officer of volunteer, helping organizations'; R must indicate
he/she is an officer to be coded here
- Fund raising activities as a member of volunteer helping organization, collecting
money, planning a collection drive
- Direct help to individuals or groups as a member of volunteer helping organizations;
visiting, bringing food, driving
- Other activities as a member of volunteer helping organizations, including social
events and meals
Religious Practice
65 - Attending services of a church or synagogue, including participating in the service;
ushering, singing in choir, leading youth group, going to church, funerals
- Individual practice; religious practice carried put as an individual or in a small
group; praying, meditating, Bible study"group (not a church), visiting graves
Religious Groups
64 - Meetings: religious helping groups; attending meetings of helping - oriented church
groups -ladies aid circle, missionary society, Knights of Columbus
- Other activities"; religious helping groups; other activities as a member of groups
listed above, including social activities and meals
- Meetings: other church groups; attending meetings of church group, not primarily
helping-oriented, or NA if helping-oriented
- Other activities, other church groups; other activities as a member of church groups
that are not helping-oriented or NA if helping, including social activities and meals;
choir practice; Bible class
5-53
-------
Appendix 5B. (continued)
ORGANIZATIONAL ACTIVITIES (continued)
Professional/Union Organizations: State Education Association; AFL-CIO; Teamsters
60 - Meetings; professional/union; attending meetings of professional or union groups
- Other activities, professional/union; other activities as a member of professional or
union group including social activities and meals
Child/Youth/Family Organizations: PTA, PTO; Boy/Girl Scouts; Little Leagues; YMCA/YWCA;
school volunteer
67 - Meetings, family organizations; attending meetings of child/youth/family-oriented
organizations
- Other activities, family organizations; other activities as a member of
chlld/youth/fami'ly-oriented organizations including social activities and meals
Fraternal Organizations: Moose, VFW, Kiwanis, Lions, Civitan, Chamber of Commerce, Shriners,
American Legion
66 - Meetings, fraternal organizations; attending meetings of fraternal organizations
- Other activities, fraternal organizations; other activities as a member of fraternal
organizations including social activities and helping activities and meals
Political Party and Civic Participation: Citizens' groups. Young Democrats, Young
Republicans, radical political groups, civic duties
62 - Meetings, political/citizen organizations; attending meetings of a political party or
citizen group, including city council
- Other activities, political/citizen organizations; other participation in political
party and citizens' groups, including social activities, voting, jury duty, helping
with elections, and meals
Special interest/Identity Organizations (including groups based on sex, race, national
origin); NOW; NAACP; Polish-American Society; neighborhood, block organizations; CR groups;
senior citizens; Weight Watchers
61 - Meetings: identify organizations; attending meetings of special interest, identity
organizations
- Other activities, identity organizations; other activities as a member of a special
interest, identity organization, including social activities and meals
Other Miscellaneous Organizations, do not fit above
68 - Other organizations; any activities as a member of an organization not fitting into
above categories; (meetings and other activities included here)
5-54
-------
Appendix SB. (continued)
ORGANIZATIONAL ACTIVITIES (continued)
Travel Related to Organizational Activities '
69 - Travel related to organizational activities as a member of a volunteer .(helping)
organization (code 63); including travel that is the helping activity, waiting for
related travel
- Travel (other organization-related); travel related to all other organization
activities; waiting for related travel
ENTERTAINMENT/SOCIAL ACTIVITIES
Attending Spectacles, Events
70 - Sports; attending sports events - football, basketball, hockey, etc.
71 - Miscellaneous spectacles, events: circus, fairs, rock concerts, accidents
72 - Movies; "went to the show"
73 - Theatre, opera, concert, ballet
74 - Museums, art galleries, exhibitions, zoos
Socializing
75 - Visiting with others; socializing with people other than R's own HH members either at
R's home or another home (visiting on the phone, code 96); talking/chatting in the
context of receiving a visit or paying a visit
76 - Party; reception, weddings
77 - At bar; cocktail lounge, nightclub; socializing or hoping to socialize at bar, lounge
- Dancing
78 - Other events; other events or socializing, do not fit above
79 - Related travel; waiting for related travel
SPORTS AND ACTIVE LEISURE
Active Sports
80 - Football, basketball, baseball, volleyball, hockey, soccer, field hockey
- Tennis, squash, racketball, paddleball
- Golf, miniature golf
5-55
-------
Appendix SB. (continued)
SPORTS AND ACTIVE LEISURE (continued)
Active Sports (continued)
80 - Swimming, waterskiing
- Skiing, ice skating, sledding, roller skating
- Bowling; pool, ping-pong, pinball
- Frisbee, catch
- Exercises, yoga (gymnastics - code 86)
- Judo, boxing, wrestling
Out of Doors
81 - Hunting
- Fishing
- Boating, sailing, canoeing
- Camping, at the beach
- Snowroobiling, dune-buggies
- Gliding, ballooning, flying
- Excursions, pleasure drives (no destination), rides with the family
- Picnicking
Walking. Biking
82 - Walking for pleasure
- Hiking
- Jogging, running
- Bicycling
- Motorcycling
- Horseback riding
Hobbies
83 - Photography
- Working on cars - not necessarily related to their running; customizing, painting
- Working on or repairing leisure time equipment (repairing the boat, "sorting out
fishing tackle")
- Collections, scrapbooks
- Carpentry and woodworking (as a hobby)
Domestic Crafts
84 - Preserving foodstuffs (canning, pickling)
- Knitting, needlework, weaving, crocheting (including classes), crewel, embroidery,
quilting, quilling, macrame
- Sewing
- Care of animals/livestock when R is not a farmer (pets, code 17; "farmer", code 01,
work)
5-56
-------
Appendix SB. (continued)
SPORTS AND ACTIVE LEISURE (continued)
Art and Literature
85 - Sculpture, painting, potting, drawing
- Literature, poetry, writing (not letters), writing a diary
HusIc/Theat re/Dance
86 - Playing a musical instrument (include practicing), whistling
- Singing
- Acting (rehearsal for play)
- Nonsocial dancing (ballet, modern dance, body movement)
- Gymnastics (lessons - code 88)
Games
87 - Playing card games (bridge, poker)
- Playing board games (Monopoly, Yahtzee, etc.), bingo, dominoes
- Playing social games (scavenger hunts), "played games" - NA kind
- Puzzles
*
Classes/Lessons for Active leisure Activity
88 - Lessons in sports activities: swimming, golf, tennis, skating, roller skating
- Lessons in gymnastics, dance, judo, body movement
- Lessons in music, singing, instruments
- Other lessons, not listed above
Travel
89 - Related travel; travel related to sports and active leisure; waiting for related
travel; vacation travel
PASSIVE LEISURE
90 - Radio
91 - TV
92 - Records, tapes, "listening to music," listening to others playing a musical instrument
93 - Reading books (current job related, code 07; professionally or class-related, code 54)
94 - Reading magazines, reviews, pamphlets
- Reading NA what; or other
5-57
-------
Appendix 56. (continued)
PASSIVE LEISURE (continued)
95 - Reading newspapers
96 - Phone conversations - not coded elsewhere, including all visiting by phone
- Other talking/conversations; face-to-face conversations, not coded elsewhere (if
children in HH only, code 23); visiting other than 75
- Conversations with HH members only - adults only or children and adults
- Arguing or fighting with people other than HH members only, household and nonhousehold
members, or NA
- Arguing or fighting with HH members only
97 - Letters (reading or writing); reading mail
98 - Relaxing
- Thinking, planning; reflecting
- "doing nothing," "sat"; just sat;
- Other passive leisure, smoking dope, pestering, teasing, joking around, messing
around; laughing
99 - Related travel: waiting for related travel
HISSING DATA CODES
- Activities of others reported - R's activity not specified
- NA activities; a time gap of greater than 10 minutes.
EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES
Other Work Related
07 - Foster parent activities
Other Household
19 - Typing
- Wrapping presents
- Checked refrigerator for shopping list
- Unpacked gifts from shower
- Packing/unpacking car
- "Settled in" after trip
- Hooked up boat to car
- Showed wife car (R was fixing)
- Packing to move
- Moved boxes
- Looking/searching for things at home (inside or out)
5-58
-------
Appendix 5B. (continued)
EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued)
Other Child Care
27 - Waited for son to get hair cut
- Picked up nephew at sister's house
- "Played with kids" (R's children from previous marriage not living with R)
- Called babysitter
Other Services
37 - Left clothing at Goodwill
- Unloaded furniture (just purchased)
- Returned books (at library)
- Brought clothes in from car (after laundromat)
- Delivered some stuff to a friend
- Waited for father to pick up meat
- Waited for stores to open
- Put away things from swap meet
- Sat in car waiting for rain to stop before shopping
- Waiting for others while they are shopping
- Showing mom what I bought
Other Personal
48 - Waiting to hear from daughter
- Stopped at home, NA what for
- Getting hystericaI
- Breaking up a fight (not child care related)
- Waited for wife to get up
- Waiting for dinner at brother's house
- Waiting for plane (meeting someone at airport)
- Laughing
- Crying
- Moaning - head hurt :
- Watching personal care activities ("watched dad shave")
Other Education
56 - Watched a film
- In discussion group
5-59
-------
Appendix 5B. (continued)
EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued)
Other Organization
68 - Attending "Club House coffee klatch"
- Waited for church activities to begin
- "Meeting" NA kind
- Cleanup after banquet
- Checked into swap meet - selling and looking
Other Social, Entertainment
78 - Waiting for movies, other events
- Opening presents (at a party)
- Looking at gifts
- Decorating for party
- Tour of a home (friends or otherwise)
- Waiting for date
- Preparing for a shower (baby shower)
- Unloaded uniforms (for parade)
Other Active leisure
88 - Fed birds, bird watching
- Astrology
- Swinging
- At park
- Showing slides
- Showing sketches
Other Active Leisure (continued)
- Recording music
- Hung around airport (NA reason)
- Picked up fishing gear
- Inspecting motorcycle
- Arranging flowers
- Work on model airplane
- Picked asparagus
- Picked up Softball equipment
- Registered to play golf
- Toured a village or lodge (coded 81)
5-60
-------
Appendix 58. (continued)
EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued)
• Other Passive Leisure
98 - Lying in sun
- Listening to birds
- Looking at slides
- Stopped at excavating place
- Looking at pictures
- Walked around outside
- Waiting for a call
- Watched plane leave
- Girl watching/boy watching
- Watching boats
- Wasted time
- In and out of house
- Home movies
* R = Respondent
HH = Household.
Source: Juster et al. (1983).
5-61
-------
-------
APPENDIX 5C
Percentile Distributions of Weighted Mean
Hours Per Week for Men and Women
5-63
-------
Appendix 5C. Percentile Distributions of Weighted Mean Hours Per Week
for Men and Women Combined: 87 Activities and 10 Subtotals
Percentile
Activity
01 -Normal work
02-Unemployment acts
05- Second job
06-Luneh at work
07-Before/after work
08-Coffee breaks
09-Travel: to/from work
10-Heal preparation
11 -Heal cleanup
12- Indoor cleaning
13-Outdoor cleaning
14 -Laundry
1 6-Repa i rs/ma i n tenance
17-Gardening/pet care
19-Other household
20-Baby care
21-Child care
22~Belping/teaching
23-Readfng/talking
24-lndoor playing
25-Outdoor playing
26-Hedical care-child
27-Babysitt ing/other
29«Travel: child care
30-Everyday shopping
31 -Durables/house shopping
32-Personal care services
33-Hedical appointments
34-Govt/f mancial services
35-Repair services
37-Other services
38-Errands
39-Travel: goods/services
40-Washlng/dressing
41-Medical care - adults
42-Kelp and care
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
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.73
0,00
0.00
20
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.40
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
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.22
2.57
0.00
0.00
30
0.34
0.00
0.00
0.00
0.00
0.00
0.25
0.99
0.13
0.22
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
0.35
0.00
0.00
0.00
0.00
0.00
o.oo'
0.00
0.58
3.27
0.00
0.00
40
8.31
0.00
0.00
0.14
0.00
0,03
0.49
1.72
0.34
0.46
0.04
0.11
0.03
0.07
0.04
0.00
0.00
0.00
0.00
0..00
0.00
0.00
0.00
0.00
0.72
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.95
3.91
0.00
0.07
50
20.22
0.01
0.03
0.30
0.11
0.16
1.35
2.98
0.62
1.21
0.18
0.27
0.16
0.21
0.18
0.07
0.19
0.03
0.06
0.04
0.02
0.01
0.05
0.12
1.20
0.02
0.04
0.05
0.07
0.04
0.03
0.01
1.32
4.52
0.03
0.22
60
32.08
0.11
0.13
0.46
0.23
0.29
2.22
4.41
1.12
2.38
0.31
0.42
0.3Q
0.35 .
0.32
0.18
0.24
0.13 .
0.17
0.14
0.12
o.n
0.16
0.24
1.81
0.12
0.15
0.16
0.18
0.15
0.14
0.11
1 .77
5.19
0.13
0.36
70
37.68
0.22
0.24
1.07
0.35
0.43
3.07
6.12
1.70
3.84
0.46
1.07
0.43
0.49
0.45
0.29
0.37
0.24
0.28
0.25
0.23
0.21
0.26
0.36
2.63
0.23
0.26
0.27
0.29
0.26
0.25
0.21
2.34
5.96
0.24
0.52
80
41.33
0.32
0.35
2.41
0.48
0.83
4.07
8.75
2. -58
5.85
1.27
2.40
1.32
1.35
1.09
0.41
0.49
0.34
0.39
0.36
0.33
0.32
0.39
0.48
3.73
0.33
0.37
0.37
0.41
0.37
0.36
0.32
3.23
6.98
0.34
1.43
90
46.88
0.42
0.45
3.16
1.23
1.74
5.47
12.30
4.31
8.93
3.56
4.96
4.40
3.30
2.68
1.03
2.60
0.45
0.58
0.46
0.44
0.42
0.50
1.39
5.92
0.43
0.48
0.48
0.69
0.48
0.47
0.42
4.69
8.48
0.45
3.49
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
107
13
29
9
11
12
18
27
14
32
29
21
58
35
21
30
12
11
8
9
11
12
27
10
23
6
9
19
11
10
8
15
21
29
14
22
5-64
-------
Appendix 5C. (continued)
Percent ile
Activity
43-Meals at home
44-Meals out
45-Night sleep
46-Naps/ rest ing
48-N.A. activities
49-Trave 1 : persona 1
5p-Students' classes
51-Other classes
54-Horoework
56-Other education
59-Travel: education
60-Prof ess iona I/union org.
61-Identity organizations
62-Political/citizen org.
63-Volunteer/helping org.
64-Religious groups
65-Religious practice
66-Fraternal organizations
67-Chi Id/family org.
68-Other organizations
69-Travel: organizations
70-Sports events
71-Miscellaneous events
72-Movies
73-Theatre
74-Museums
75-Visiting with others
76-Parties
77 -Bars/ lounges
78-Othef events
79-Travel: events/social
80-Active sports
81 -Outdoors
82-Wa Ik ing/biking
83 -Hobbies
84-Domestic crafts
85-Art/literature
10
2.28
0.00
46.23
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
o'.oo
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
20
3.43
0.11
50.11
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
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.32
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
30
4.22
0.42
52.24
0.17
0.00
0.33
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
1.10
0.00
0.00
0.00
0.22
0.00
0.00
0.00
0.00
0.00
0.00
40
5.01
0.92
54.01
0.39
0.14
0.65
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
0.00
0.04
o.oo-
0.00
0.00
0.00
0.00
2.26
0.00
0.00
o.do
0.46
0.00
0.00
0.00
0.00
0.01
0.00
50
5.85
1.50
56.10
0.98
0.30
1.04
0.03
0.01
0.05
0.01
0.04
0.01
0.01
0.01
0.01
0.06
0.29
0.01
0.01
0.03
0.18
0.03
0.01
0.04
0.01
0.01
3.39
0.08
0.07
0.02
0.82
0.10
0.11
0.08
0.04
0.13
0.01.
60
6.79
2.34
58.38
2.01
0.46
1.42
0.13
0.12
0.16
0.11
0.15
0.11
0.11
" 0.11
0.11
0.18
0.45
0.11
0.12
0.14
0.32
0.14
0.12
0.15
0.12
0.11
4.74
0.19
0.18
0.13
1.21
0.22
0.23
0.20
0.14
0.26
0.11
70
7.83
3.15
60.34
3.43
0.97
2.13
0.24
0.22
0.27
0.22
0.26
0.21
0.22
0.21
0.21
0.29
0.93
0.21
0.22
0.24
0.45
0.25
0.22
0.26
0.22
0.21
6.32
0.31
0.30
0.23
1.66
0.34
0.36
0.32
0.25
0.39
0.22
80
9.23
4.26
62.69
5.74
1.81
3.09
0.34
0.32
0.38
0.32
0.36
0,31
0.32
0.31
0.31
0.40
1.57
0.32
0.32
0.35
0.89
0.35
0.32
0.36
0,32
0.31
8.60
0.42
0.41
0.34
2.37
0.46
0.48
0.43
0.36
0.69 ,
0.32
90
11.69
6.43
66.63
9.13
4.31
4.97
0.45
0.42
0.49
0.42
0.47
0.41
0.42
0.41
0.42
0.76
3.36
0.42
0.43
0.45
1.48"
0.46
0.42
0.47
0.42
0.41
12.37
1.48
1.55
0.44
3.67
2.73
2.70
1.21
0.47
3.50
0.42
Min.
0
0
13
0
" 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
23
24
88
38
67
26
35
27
33
10
14
13
25
3
13
21
28
13
17
29
14
12
10
15
9
6
51
16
22
16
14
20
47
12
62
34
18
5-65
-------
Appendix 5C. (continued)
Percentile
Activity
86-Mus tc/drama/dance
87 -Games
88-C lasses/other
89-Travelr active leisure
90-Radio
91-Television
92 Records/tapes
93-Reading books
94-Reading roagazines/H,A.
95-Rcading newspapers
96-Conversations
97-Letters
98-Other passive leisure
99-Travel: passive leisure
Hr/wk - total work
Hr/wk - house/yard
Hr/wk - child care
Hr/wk - services/shop
Hr/wk - personal care
Hr/wk - education
Hr/wk - organizations
Hr/wk - social/entertainment
Hr/wk - active leisure
Hr/wk - passive leisure
10
0.00
0.00
0.00
0.00
0.00
1.99
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1,68
0.00
0,04
63.66
0.00
0.00
0.14
0.00
7.99
20
0.00
0.00
0.00
0.00
0.00
4.66
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.09
3.80
0.00
0.66
68.38
0.00
0.00
1.31
0.14
11.70
30
0.00
0.00
0.00
0.00
0.00
7.47
0.00
0.00
0.02
0.16
0.28
0.00
0.06
0.00
0.38
5.90
0.01
1.61
70.93
0.00
0.07
3.00
0.45
14.95
40
0.00
0.00
0.00
0.01
0.00
9.80
0.00
0.00
0.20
0.38
0.58
0.00
0.25
0.00
11.22
8.49
0.19
2.59
74.15
0.00
0.26
4.72
1.45
17.92
50
0.02
0.09
0.05
0.14
0.08
12.25
0.05
0.08
0.37
0.73
1.06
0.06 **
0.43
0.05
25.45
11.71
0.36
3.60
76.79
0.07
0.45
6.43
2.71
20.44
60
0.12
0.21
0.16
0.27
0.19
15.08
0.15
0.19
0.73
1.26
1.57
0.18
0.83
0.17
37.80
16.05
0.71
4.69
79.55
0.19
1.31,
8.54
4.42
23.76
70
0.22
0.33
0.27
0.39
0.31
18.45
0.26
0.31
1.58
2.02
2.48
0.29
1.35
0.28
.I,,
44.80
19.61
2.15
6.58
83.09
0.30
2.50
10.89
6.66
27.08
80
0.32
0.44
0.38
0.66
0.42
21.97
0.37
0.43
2.85
3.05
3.45
0.40
2.45
0.39
49.24
24.52
4.56
9.02
87.90
0.41
4.71
13.96
9.55
32.28
90
0.42
2.81
0.48
1.78
1.11
29.00
0.48
1.31
5.34
4.91
5.35
0.69
4.37
0.50
55,95
31.67
9.06
12.10
94.28
2.10
8.98
20^01
14.11
40.17
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
32
0
0
0
0
0
Max.
6
33
18
19
15
79
30
16
29
23
18
16
45
8
110
67
44
48
127
57
54
55
63
92
5-66
-------
APPENDIX 5D
Mobility of Resident Population by State: 1980
5-67
-------
Appendix 50. Mobility of the Resident Population by State: 1980
Percent distribution -
3
residence in 1975
Region, division.
and state
United States
Northeast
New England
Maine
New Hampshire
Vermont
Massachusetts
Rhode Island
Connecticut
Middle Atlantic
New York
Hew Jersey
Pennsylvania
Midwest
East North Central
Ohio
Indiana
Illinois
Michigan
Wisconsin
West North Central
Minnesota
Iowa
Missouri
North Dakota
South Dakota
Nebraska
Kansas
Persons
5 years
old, and
overb
1980
(1,000)
210,323
46,052
11,594
1,047
857
476
5,398
891
2,925
34,458
16,432
6,904
11,122
54,513
38,623
10,015
5.074
10,593
8,582
4,360
15,890
3r770
2,693
4,564
598
633
1,448
2,184
Same
house
in
1980
as
1975
53.6
61.7
59.1
56.9
51.6
54.4
61.0
60.5
59.0
62.6
61.5
61.5
65.0
55.4
56.0
56.7
54.8
55.5
56.4
56.2
53.9
55.6
55.6
54.0
51.7
52.9
53.1
50.2
Different
house ,
same
county
25,1
22.3
23.4
24.0
22.8
23.9
22.7
23.9
24.4
21.9
22.6
20.0
22.0
26.4
27.4
27.9
27.5
28.5
26.2
25.5
24.0
22.8
25.0
24.1
23.1
23.2
24.4
25.1
Different
county,
same
state
9.8
8.0
6.7
7.5
6.2
6.5
7.6
5.0
5.5
8.4
9.3
8.6
7.1
10.2
9.6
9.0
9.6
8.1
11.3
11.0
11.8
13.3
10.9
11.8
11.4
12.1
11.0
10.7
Different
county ,
different
state
9.7
6.1
9.2
10.8
18.5
14.3
7.0
8.7
9.3
5.0
3.8
7.8
5.2
7.0
6.0
5.7
7.6
6.1
5.1
6.7
9.4
7.3
7.9
9.4
12.7
11.1
'10.5
12.6
5-68
-------
Appendix 5D. (continued)
Percent distribution -
a
residence in 1975
Region, division,
and state
South
South Atlantic •
Delaware
Maryland
District of Columbia
Virginia
West Virginia
North Carolina
South Carolina
Georgia
Florida
East South Central
Kentucky
Tennessee
Alabama
Mississippi
West South Central
Arkansas
Louisiana
Oklahoma
Texas
West
Mountain
Montana
Idaho
Wyoming
Colorado
New Mexico
Arizona
Utah
Nevada
Persons
5 years
old, and
over
1980
(1,000)
69,880
34,498
555
3,947
603
4,991
1,806
5,476
2,884
5,052
9,183
13,556
3,379
4,269
• V3,601
2,307
21,826
2,113
3,847
2,793
13.074
39,879
10,386
722
852
425
2,676
1,188
2,506
1,272
745
Same
house
in
1980
as
1975
52.4
52.7
57.0
55.5
58.2
51.0
60.9
56.9
57.5
52.5
46.2
56.0
54.4
54.2
57.6
59.0
49.6
53.1
57.0
47.6
47.3
43.8
42.7
47.3
44.4
38.4
39.8
50.3
41.9
45.8
34.8
Different
house.
same
county
24.1
22.4
26.3
21.9
22.7
17.9
23.4
23.5
22.3
22.8
23.7
25.9
27.2
27.2
25.3
, 22.5
25.6
24.8
24.3
24.9
26.2
28.3
25.1
24.5
24.7
23.6
22.7
23.2
27.1
27.8
27.4
Different
county.
same
state
10.0
9.7
2.0
10.3
(x)
15.0
6.6
8.9
7.7
12.2
7.8
7.9
8.6
7.4
7.4
8.6
11.8
9.1
9.2
12.3
12.9
11.0
9.1
12.3
9.5
8.6
14.8
7.2
5.0
8.4
3.6
Different
county,
different
state
12.0
13.6
13.3
10.4
16.3
13.9
8.6
9.8
11.5
11.5
19.6
9.5
9.0
10.6
8.9
9.2
11.0
12.4
8.4
13.7
11.0
13.4
21.1
15.0
20.0
28.3
20.6
17.4
23.9
16.0
31.5
5-69
-------
Appendix 5D. (continued)
Percent distribution -
a
residence in 1975
Persons
5 years
Same
house
old, and in
overb 1980
Region, division,
and state
Pacific
Washington
Oregon
California
Alaska
Hawa i i
a Survey assessed changes
1980
(1,000)
29.493
3,825
2,437
21,980
363
888
in residence
as
1975
44.2
43.7
41.4
44.6
32.2
49.3
between 1975
n7c
Different
house,
same
county
29.4
27.7
26.6
30.2
27.6
25.2
and 1980.
Different
county.
same
state
11.6
10.1
13.4
12.1
8.7
2.8
Different
county.
different
state
1Q.7
16.2
16.9
8.5
29.1
16.9
x » not applicable.
Source: Bureau of the Census, Statistical Abstract (1984).
5-70
-------
PART II
1.
1.1
STANDARD EXPOSURE SCENARIOS
Approach
The purpose of this section is to demonstrate how to apply the
standard factor statistics summarized in the previous sections to specific
exposure scenarios. The following scenarios are currently included:
Standard Exposure Scenario Page
Ingestion of Drinking Water 1-5
Ingestion of Homegrown Fruits and Vegetables 1-8
Ingestion of Homegrown Meat and Dairy Products 1-11
Ingestion of Recreationally Caught Fish/Shellfish 1-14
Ingestion of Soil 1-17
Inhalation of Vapors Outside Residence i-20
Inhalation of Vapors Inside Residence 1-23
Inhalation of Vapors While Showering 1-26
Inhalation of Particulates Outside Residence 1-29
Inhalation of Particulates Inside Residence 1-32
Dermal Contact with Water - to be developed 1-35
Dermal Contact with Soil - to be developed 1-36
For each scenario, the following information is provided:
• The basic equation for estimating exposure. This equation
estimates exposure as the amount of contaminant an individual
contacts averaged over lifetime and body weight. Expressed as a
lifetime average, the exposure estimate is appropriate for
computing cancer risk. If sufficient data are available to
determine how the absorption of the chemical into the body differs
between the human exposure scenario and the animal experiment used
to derive the 95th percent upper confidence limit of the linear
slope factor of the dose-response function, the risk estimate can
be further refined on this basis. For noncancer effects, the
exposure levels are typically compared to Reference Doses (RfDs).
In such cases, the equation is modified slightly by substituting
exposure duration for lifetime. The EPA intends to add more
detailed information on absorption considerations and estimation
of noncancer chronic effects to this report in later editions.
• Recommended default values for each parameter in the exposure
equation. These values are defaults in the sense that they are
intended to be used only when site-specific data are not available
to make more accurate estimates. Prior sections of this report
1-1
-------
provide data and procedures for estimating parameter values and
should be used in lieu of these default values if feasible. These
default values are presented in three ways: averages, ranges, and
distributions. The recommended parameter values were derived
solely from our interpretation of the available data. In many
situations, different values may be appropriate to use in
consideration of policy, precedent, strategy, or other factors.
• Justifications for each-recommended parameter value. To the
extent possible, these values were derived directly from the
preceding sections. In many cases, however, no appropriate data
were available and the recommendations were based on the best
judgments of the authors in conjunction with EPA. Users are
encouraged to modify these assumptions based on site-specific
information.
The three types of default values and how they are used are described
below:
• The average values are intended to represent typical values and
should be used when time allows calculation of only one best
estimate. Mean values were used when available; median values
were used when means were not reported. Generally, users are
encouraged to estimate a range of exposure values to represent the
uncertainty.
• A range of values is also provided for each parameter. Where
possible these ranges were derived from distributions, basing the
lower end on the mean or 50th percentile and the upper end on the
90th or 95th percentile. These values were selected to help
create a range of scenarios from typical to reasonable worst-
case. Expressing exposures over this range provides an indication
of the uncertainty and provides more information to the risk
manager for making public health decisions. Typical scenarios
were constructed by combining all lower ends (i.e., mean or 50th
percentile) of the ranges for each parameter. The EPA does not
have an official position on how to define a reasonable worst-case
scenario, but we recommend using a combination of some lower
values and some upper values. While not producing any firm
percentile estimate, this procedure would provide an upper
estimate and reduce the possibility of creating an overly worst-
case scenario. It is difficult to prescribe a more precise
procedure since "reasonable" is a largely subjective term. The
best approach for deriving a 90th percentile (or other percentile
judged to represent reasonable worst-case) exposure level is by
using Monte Carlo techniques. Unfortunately this requires
reliable distribution data for each parameter, which is rarely
available. It is further recommended that assessors not limit
1-2
-------
their analysis to only these two scenarios. A variety of
parameter combinations can be evaluated as a sensitivity analysis
to identify the most influential parameter (see Chapter 2 in
Part II). Additionally, an absolute worst-case scenario (made up
of absolute upper bounds of each parameter) is useful for purposes
of demonstrating that the risk is not of concern.
• The most ideal exposure estimates can be obtained using
frequency distributions for the parameter values. Where these
distributions are available, the scenario descriptions provide
page references to the preceding sections. These parameter
distributions can be used in conjunction with Monte Carlo
techniques to obtain frequency distributions for exposure levels
(see Chapter 2 in Part II).
Some of the parameters used in estimating exposure (primarily concen-
trations) are exclusively site specific, and therefore default recommenda-
tions could not be made..
Note that only the average body weight value is recommended under the
set of values for the parameter ranges. Since the body weight appears in
the denominator of the exposure equation, a smaller value would lead to
larger exposures. This would make the combination of values used in the
reasonable worst-case scenario less likely, since the combination of low
body weight and high consumption (or inhalation) rates is not likely to
occur.
Similarly, only the average lifetime value is recommended under the
set of values for the parameter ranges. Use of a .short lifetime estimate
in the reasonable worst-case scenario could be unlikely in conjunction
with a long exposure duration assumption. Additionally, certain lifetime
assumptions are made in derivation of the cancer potency factor. Sorting
out how to maintain consistency between the exposure and potency values
while.adjusting lifetime over a relatively narrow range implies more
precision than is appropriate in risk assessment.
The linkage between the contact 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 contact rate:
1-3
-------
• The contact rate can be based on an individual event, such as
100 g of fish eaten per meal. The duration should be based on the
number of events or, in this case, meals.
• The contact rate can also 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 together
they give the appropriate estimate of mass of contaminant contacted.
This can be accomplished by basing the contact rate on either a long-term
average (chronic exposure) or an event (acute exposure) basis, as long as
the duration value is selected appropriately. Consider the case in which
a person eats a 100-g fish meal every 10 days (long-term average is
10 g/day) for 40 years:
(100 g/day) (36.5 days/year) (40 years) = 146,000 g
(10 g/day) (365 days/year) (40 years) = 146,000 g
Thus, a duration of either 36.5 days/year or 365 days/year could be used
as long as it is matched with the appropriate contact rate. As shown
later in this chapter, both approaches were used depending on the data
available.
Normally, exposure scenarios such as those presented in this chapter
are used to estimate individual risks. If the scenario is considered
representative of a population, then the population risk is estimated by
multiplying the individual risk by the population size. Note that
exposure durations less than an individual's lifetime were typically
recommended. In these cases, the population risk must be computed using
the total population exposed over a 70-year period. For example, if the
exposure duration is assumed to last 10 years for an individual, the
exposed population over 70 years could be 7 people since a different
person could be exposed during each 10-year period.
1-4
-------
1 . 2
Inqestion of Drinking Water at Residence
SCENARIO: An individual ingests tap water and beverages made from tap
water at his residence. All tap water consumed at the
residence is from one contaminated source.
Lifetime Average Daily Exposure = (CR) (C) (ED) (DF)
CR
C
ED
OF
BW
LT
1
(BW) (LT) (365 days/yr)
water consumption rate (L/day)
concentration of contaminant in water (mg/L)
exposure duration (day)
diet fraction
body weight (kg)
lifetime (yr)
Parameter
CR
DF
BW
LT
Average
1.4
1.4-2.0
Site specific
3,285 3,285-10,950
0.75 0.75-1.0
70 70
75 75
Distribution
p. 2-5
Not available
Not available
pp. 5-40 - 5-43
To be developed
1. Diet fraction refers to the proportion of drinking water an
individual consumes at home from one contaminated source.
2. Range represents the assumed typical value and the assumed reasonable
worst-case value.
3. Exposure duration refers to the actual number of days exposed at a
given residence.
1-5
-------
RATIONALE FOR RECOMMENDED VALUES FOR
CONSUMPTION OF DRINKING WATER AT RESIDENCE
Consumption Rate
The water consumption rate of 2 L/day is a historical figure set by
the U.S. Army and used extensively throughout the EPA and other
agencies. As discussed in Section 2.2, Part I, the scientific literature
suggests an average adult drinking water consumption rate of 1.4 L/day.
These data can be summarized as follows:
90th
Range percent!le
Average (L/dav) (L/dav) (L/dav) Reference
1.63 (calculated) -- -- NAS 1977
1.39 0.80-1.96 2.0 Cantor et al. 1987
1.25 0.26-2.80 1.90 Gillies and Paulin 1983
1.20 -- -- Pennington 1983
Average 1.4
For the reasonable worst-case value, the 90th percent!le rate
reported by Gillies and Paulin (1983), 1.90 L/day, suggests that a rate
of 2.0 L/day may be a reasonable approximation. The 90th percentile
value suggested by Cantor et al. (1987) is also approximately 2.0 L/day.
This value, 2.0 L/day, is recommended as the reasonable worst-case
consumption rate.
Exposure Duration
It is assumed that an individual is exposed every day at the same con-
sumption rate. Assuming that an individual spends an average of 9 years
at each residence, total exposure would be for 3,285 days. Using a
reasonable worst-case assumption of 30 years at any one residence, total
exposure would be 10,950 days. These 9- and 30-year values represent a
judgment of how long a person will live in one area (see Section 5.3.5).
1-6
-------
Diet Fraction
Based on survey data on time spent at home (see Section 5.3.3), the
average individual would consume 75 percent of the total amount of water
consumed per day at home and 25 percent would be consumed away from
home. For the reasonable worst-case value, it was assumed that the
individual would consume 100 percent of the total amount at home.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 U.S.
National Center for Health Statistics survey.
1-7
-------
1.3
Ingestion of Homegrown Fruits and Vegetables
SCENARIO: Individuals ingest fruits and vegetables grown in the
contaminated soil at their residence.
Lifetime Average Daily Exposure
(CR) fd (ED)
(BW) (LT) (365 days/yr)
CR - consumption rate (g/day)
C - concentration of contaminant in food (mg/g)
ED1 - exposure duration (day)
BW = body weight of average adult (kg)
LT = lifetime (yr)
Parameter Average Ranqe^ Distribution
pp. 2-19, 2-20
pp. 2-20, 2-21
Not available
pp. 5-40 - 5-43
To be developed
1. Exposure duration refers to the actual number of days in which
exposure occurs at a given residence.
2. Range values represent typical and reasonable worst-case values.
CR (vegetables)
CR (fruits)
C
ED
BW
LT
50
28
Site
650
70
75
50-80
28-42
specific
650-5,500
70
75
1-8
-------
RATIONALE FOR RECOMMENDED VALUES'FOR INGESTION OF
HOMEGROWN FRUITS AND VEGETABLES
Consumption Rate
Based on national survey data (USDA 1980), the average amounts of
total fruits and total vegetables consumed on any one day have been
estimated as 200 g/day for vegetables and 140 g/day for fruits (see
discussion in Section 2.3, Part I). These values assume that all the
homegrown fruits and vegetables consumed by exposed individuals are
derived from the contaminated source. From Table 2-10, the fraction of
vegetables homegrown ranges from 0.04 to 0.75, depending on type. The
overall average homegrown fraction from this table is 0.25, representing
the typical portion. It was judged that the reasonable worst-case
portion would be 0.40. Using these fractions, total homegrown vegetable
consumption is estimated as follows:
Typical vegetable consumption = (200 g/day) (0.25) = 50 g/day
Reasonable worst-case vegetable consumption = (200 g/day) (0.40)
=80 g/day.
The fraction of fruits that are homegrown, as shown on Table 2-10,
ranges from 0.09 to 0.33 depending on type. The overall average homegrown
fraction from this table is 0.20, representing the typical portion. It
was judged that a reasonable worst-case portion would be 0.30. Using
these fractions, total homegrown fruit consumption is estimated as
follows:
Typical fruit consumption = (140 g/day) (0.20) = 28.g/day
Reasonable worst-case fruit consumption = (140 g/day) (0.30)
= 42 g/day.
Exposure Duration
The number of days homegrown fruits and vegetables are consumed will
depend on the seasonal characteristics of the fruits and vegetables and
on factors such as whether they are canned, personal taste, etc.
1-9
-------
Additionally, the overall time contaminated food is obtained from a
particular source is limited by how long a person lives in an area. No
precise data are available on this issue. Thus, it was judged that
homegrown fruits and vegetables are eaten primarily during the late
summer and fall months when they are harvested, or about 20 percent of
the year. For the reasonable worst-case in areas that have longer
harvest periods or for people who preserve their food, this exposure
duration was judged to be 50 percent of the time. Assuming that an
individual spends an average 9 years at each residence, total residence
time would be for 3,285 days. Using a reasonable worst-case assumption
of 30 years at any one residence, total residence time would be 10,950
days. These 9- and 30-year values represent an estimate of how long a
person will live in one area (see Section 5.3.5). Combining residence
time and consumption time for homegrown fruits and vegetables results in
the following estimates:
Typical exposure duration = (3,285 days) (0.20) =657 days
Reasonable worst-case exposure duration = (10,950 days) (0.50)
« 5,475 days.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-10
-------
1.4 Inqestion of Homegrown Meat and Dairy Products
SCENARIO: Individuals ingest homegrown meat and dairy products that were
either grown on contaminated soil or obtained from animals fed
contaminated feed that was grown in contaminated soil.
Lifetime Average Daily Exposure = (CR) (C) (ED)
(BW) (LT) (365 days/yr)
CR = consumption rate (g/day)
C = concentration of contaminant in food (mg/g)
ED1 = exposure duration (day)
BW = body weight (kg)
LT = lifetime (yr)
Parameter Average Ranqe^ Distribution
CR (Beef) 44 44-75 Not available
CR (Dairy) 160 160-300 Not available
C Site specific
ED 7,300 7,300-14,600 Not available
BW 70 70 pp. 5-40-5-43
LT 75 75 To be developed
1. Exposure duration refers to the overall time period in which exposure
occurs at a given residence.
2. Range values represent typical and reasonable worst-case values for
rural farm households.
1-11
-------
, RATIONALE FOR RECOMMENDED VALUES FOR
CONSUMPTION OF HOMEGROWN MEAT AND DAIRY PRODUCTS
Consumption Rate
Consumption rates for the average amount of homegrown beef and dairy
products consumed were derived by averaging the following values from
Table 2-11:
' , " nL, ,
Beef (g/dav) Dairy Products (q/dav)
124 500
111 308
88 431
96 -400 avg. total
67 40 %
-100 avg. total 160 avg. homegrown
- 44 %
44 avg. homegrown
up' .' N .,' . ' j!ii i'
According to USDA studies (USDA 1966), homegrown beef consumption for
rural farm households is 44 percent of total beef consumption, and the
consumption of homegrown dairy products for rural farm households is
40 percent of the total consumed. For the average case, it can be assumed
that an individual will consume 44 g/day of homegrown beef and 160 g/day
!K • •'' „•!! :1 '!' " ,, '" ""! "':
of homegrown dairy products. For a reasonable worst-case, it was assumed
by judgment that 75 percent of an individual's daily intake would be
homegrown. This would amount to 75 g/day of homegrown beef and 300 g/day
of homegrown dairy products.
Exposure Duration
Since the consumption rate estimates are long-term averages rather
than the actual amount eaten peY day, the exposure duration value should
represent the overall time period in which exposure occurs instead of the
actual number of days that the food is consumed. Farm families are
likely to live at one residence longer than the general population, thus
the census data suggesting 9 to 30 years for the general population is
probably low for farmers. It was judged that a typical farm family would
i .
live in one location for 20 years and that 40 years would represent a
1-12
-------
reasonable worst case exposure duration. Using these values, exposure
for a typical case would be 7,300 days and for a reasonable worst-case
would be 14,600 days.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
concensus value of 70 kg traditionally used to exposure/risk assessments,
the value of 70 kg should be used to represent average body weight.
lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-13
-------
1.5 Inqestlon of Recreational1v Caught Fish/Shellfish from Large
, Water Bodies
SCENARIO: A recreational fisherman and his/her family consume
fish/shellfish derived from one contaminated large water body
while residing at one location.
Lifetime Average Daily Exposure = (CR) (C) (ED) (DF)
(BW) (LT) (365 days/yr)
CR
BW
LT
fish consumption rate (g/day)
concentration of contaminant in fish (mg/g)
exposure duration (day)
diet fraction
body weight (kg)
lifetime (yr)
Parameter Average Range3 Distribution
CR 30 30-140 pp. 2-37, 2-38
C Site-specific
ED 3,285 3,285-10,950 Not available
DF 0.2 0.2-0.75 Not available
BW 70 70 pp. 5-40 - 5-43
LT 75 75 To be developed
Exposure duration refers to the overall time period that an individual
is exposed at a given residence.
Diet fraction represents the portion of a person's fish diet derived
from the contaminated source.
Range represents typical (-50th percentile or mean) values for total
recreational fish catch to reasonable worst-case (~50th percentile)
values for populations with high fish consumption rates.
1-14
-------
RATIONALE FOR RECOMMENDED VALUES FOR CONSUMPTION OF
RECREATIONALLY CAUGHT FISH/SHELLFISH FROM LARGE WATER BODIES
Consumption Rate
The consumption rate data for recreationally caught fish/shellfish
from large water bodies can be summarized as follows:
Reasonable Worst Case:
50th oercentile 90th oercentile Reference
37 g/day 224.8 g/day Puffer 1981
23 g/day 54.0 g/day (est) Pierce et al. 1981
Average 30 g/day 140 g/day
Although these values were derived from local surveys on the west coast,
they are recommended as the consumption rates to be used to estimate fish/
shellfish ingestion by recreational fishermen in any area with large
water bodies. No consumption rate values are recommended for small water
body areas. Guidance for estimating site-specific consumption rates is
provided in Section 2.5.3, Part I.
Exposure Duration
The consumption rate estimates are based on long-term averages. Thus,
in order to estimate the total amount of fish ingested, these values must
be multiplied by an exposure duration equal to the total amount of time
spent in one location. Thus, the exposure duration was assumed to equal
9 years or 3,285 days on average, and 30 years or 10,950 days for reason-
able worst-case estimates, where 9 and 30 years, respectively, represent
judgments of how long a person will live in one area (see Section 5.3.5).
Diet Fraction
An individual is unlikely to obtain all of his/her recreationally
caught fish from the same source. The diet fraction term represents this
phenomenon. This fraction is best estimated on the basis of site-specific
data or" judgments. For example, the diet fraction is likely to be higher
1-15
-------
for large water bodies than for small water bodies. Lacking such
information, it was judged that a typical value for this parameter could
be 20 percent; for a reasonable worst-case, the value would be 75 percent.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
if "'
concensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-16
-------
!-6 Ingestioh of Soil - Residential Setting - Children
SCENARIO: A child inadvertently ingests contaminated soil/dust from
hands or food while playing in and around his/her residence.
Lifetime Average Daily Exposure = (CR) (C) (ED)
CR =
C 1 =
ED1 =
BW =
LT -..
soil consumption
concentration of
exposure duration
body weight (kg)
lifetime (yr)
Parameter Average
CR
C
ED
BW
LT
0.2
Site
800
16
75
(BW)
rate (g/day)
contaminant in
(day)
Range2
0.2-0.8
specific
800-2,200
16
75
(LT) (365 days/yr)
soil (mg/g)
-
Distribution
-
Not
pp.
To
available
5-40 - 5-43
be developed
1. Exposure duration refers to the actual number of days that exposure
occurs.
2. Range represents typical (-50th percentile or mean) to reasonable
worst-case (-90th percentile) values.
1-17
-------
RATIONALE FOR RECOMMENDED VALUES FOR
INGESTION OF SOIL
Consumption Rate
As explained in Section 2.6, Part I, the most reliable soil inges-
tion studies are the tracer studies done by Binder et al. (1986) and by
Clausing et al. (1987). The data from these studies can be summarized as
fol1ows:
Soil inqestion rate
Element Avg. fmq/dav) Range (mq/dav)
Binder et al. (1986) Al 181 25 - 1324
Si 184 31 - 799
Clausing et al. (1987) Al 230 21 - 878
AIR 127 48 - 362
Avg. 180 31 - 841
These studies suggest that soil ingestion among children varies from 0.2
to 0.8 g/day. This range was adopted for the consumption rate
estimates. The lower limit, or 0.2 g/days was assumed to represent
typical exposure, while the upper range value of 0.8 g/day was selected
as the reasonable worst-case value. The upper ends of the range values
were used for the reasonable worst-case value because of the small sample
size used in these studies (i.e., cannot distinguish 90th percentile).
These values should not be considered long-term average values. The
studies from which these values were derived were short-duration studies
conducted in warm weather. Because of this, the values are for an expo-
sure "event" rather than for a long-term daily average rate. The rate is
also for "warm" month exposure for both indoor (dust) and outdoor (dirt)
contact, and assumes equal contamination levels in dirt and dust during
"warm" weather months.
Exposure Duration
Since the soil consumption rate estimates represent the actual amount
consumed per day, exposure duration must be based on the actual number of
days that a child ingests soil. .For this scenario, the assumption is that
1-18
-------
a child only contacts contaminated soil at his/her residence. Time spent
in "nearby" uncontaminated areas would reduce exposure. The literature
(see Section 2.6.3) suggested that soil ingestion is most prevalent among
children aged 1 to 6. During this period, the actual number of days that
a child ingests soil will depend on climate and individual behavior
patterns. Ingestion may occur outside with direct soil contact or inside
from house dust derived from outside soil. Climatic factors, such as how
long the soil is frozen, can affect how often children play in the soil
and ingest it. It was judged that ingestion of contaminated soil could
occur typically 75 percent of the time over a 3-year period. In a
reasonable worst case, this would occur 100 percent of the time over a
6-year period. Thus, the range of values was derived as follows:
Typical case: (3 years)(365 days/year)(0.75) = 820 days
Reasonable worst case: (6 years)(365 days/year)(1.00) = 2,200 day
No data were available for deriving distributions.
Body Weight
The 50th percentile body weight of children aged 1 to 6 averages
16 kg. This weight was selected as the typical value. Distribution data
are presented in Tables 5A-3 through 5A-4.
Lifetime
According to the 1985 edition of the Bureau of the Census
Statistical Abstract of the United States, the average life expectancy of
men and women is 74.6 years, and the figures have shown a steady increase
in life span through time. Therefore, an average figure of 75 years was
used for the average lifetime of men and women. The source of the data is
a 1982 National Center for Health Statistics survey.
Even for exposures limited to childhood ages, the averaging "period
used in cancer risk assessments should represent the entire life of an
individual. Thus, an average of 75 years was assumed to apply.
1-19
-------
1.7 Inhalation of Vapors Outside Residence
SCENARIO: An individual is engaged in various activities outside his/her
residence and is inhaling contaminant vapors present in
ambient air.
Lifetime Average Daily Exposure = (IR) (C) (ED)
IR -
C , -
ED* -
BW »
LT -
(BW) (LT)
inhalation rate (m3/hr)
concentration of contaminant in air (/
exposure duration (hr)
body weight of average adult (kg)
lifetime (yr)
Parameter Average Range^
IR
C
ED
BW
LT
1.4 1.4-3.0
Site specific
1,440 1,440-4,800
70 70
75 75
(365 days/yr)
iQ/m )
Distribution
Not available
Not available
pp. 5-40 - 5-43
To be developed
1. Exposure duration refers to the actual number of hours an individual
is exposed outside a given residence.
2. Range values represent typical and reasonable worst-case values.
1-20
-------
RATIONALE FOR RECOMMENDED VALUES FOR
INHALATION OF VAPORS OUTSIDE RESIDENCE
Inhalation Rate
This parameter varies depending upon the activity levels of the
exposed individual. Because activities vary widely depending upon the
individual and the environmental setting, a generic mix of activity levels
was assumed. More accurate, site-specific activity level data should be
used when available. For the average case of an individual performing
activities outside the residence, data from Table 3-2 suggest that 37 per-
cent of the time would be spent at a moderate activity level, 28 percent
at both the resting and light activity levels, and 27 percent at a heavy
activity level. Using the values in Table 3-1, the average inhalation
rate for this mix of outdoor activities is 1.4 m3/hour. For a reason-
able worst-case exposure, it was judged that an individual would spend
50 percent of the time at a heavy activity level and 50 percent of the
time at a moderate activity level.. The reasonable worst-case inhalation
rate estimated using these assumptions is 3.0 m3/hour. The above esti-
mates are based on adults, but assessments applicable to children can be
done similarly, using values for specific age groups at specified activity
levels as provided in Table 3-1.
Exposure Duration
Exposure duration is determined by multiplying the number of hours
exposed per week, the number of weeks exposed per year, and the number of
years exposed at a residence. For this route, the number of hours exposed
per week must be determined for each specific scenario. A generic value
for the number of hours spent outside one's residence has been estimated
at 3.07 hours per week. Refer to Section 5.3.3 for an explanation of the
derivation of this generic value. This value may be used as a default
value for the time spent outside one's residence on a weekly basis. It
is also assumed that this value represents an annual average of the
amount of time adults spend outdoors at home. Time-use data were
1-21
-------
collected during the months of October, November, February, May, and
September, providing an annual representation of human activity patterns
(Hill 1985). It is assumed that an individual is exposed every week of
the year. The average number of years an individual lives in any given
residence is assumed to be 9. For a reasonable worst-case estimate, a
value of 30 years may be used. Thus, the number of hours an individual
is exposed outside a given residence is as follows:
Typical outdoor exposure = (9 yr)(5^r!i)(3.07 Jf) = -1,440 hr
CO \fjlf hy»
Reasonable worst-case outdoor exposure = (30 yr)( yr )(3.07 ^) = -4800 hr.
These values should only be used when site-specific considerations do not
allow estimation of more precise time values. For specific activities
that produce exposures of shorter duration, the lower activity-specific
values should be used.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
i '!•:. ' !" ' '"",
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-22
-------
1.8 Inhalation of Vapors Inside Residence
SCENARIO: An individual is engaged in various activities inside his/her
residence and is inhaling contaminant vapors present in indoor
air. :
Lifetime Average Daily Exposure = (IR) (C) (ED)
(BW) (LT) (365 days/yr)
IR = inhalation rate (rn^/hr)
C = concentration of contaminant in air (ng/m3)
ED1 = exposure duration (hr)
BW = body weight of average adult (kg)
LT = lifetime (yr)
Parameter Average Ranqe^ Distribution
IR 0.63 0.63-0.89 Not available
C Site specific
ED 54,000 54,000-180,000 . Not available
BW 70 70 pp. 5-40 - 5-43
LT 75 75 To be developed
1. Exposure duration refers to the actual number of hours an individual
is exposed inside a given residence.
2. Range values represent typical and reasonable worst-case values.
1-23
-------
RATIONALE FOR RECOMMENDED VALUES FOR
INHALATION OF VAPORS INSIDE RESIDENCE
Inhalation Rate
This parameter varies depending upon the activity levels of the
exposed individual. Since activity levels vary widely, a typical mix of
activity levels was assumed. More accurate, site-specific activity level
data should be used when available. An average inhalation rate for time
spent indoors at home was assumed to be 0.63 m /hour. This was calcu-
lated using the average inhalation rates in Table 3-1 and activity levels
from Table 3-2: approximately 48 percent of time at both the resting and
the light activity levels, 3 percent at the moderate activity level, and
1 percent at the heavy activity level. A reasonable worst-case value of
0.89 m3/hour may be used. This value was 25 percent of time at the
resting activity level, 60 percent at the light level, 10 percent at the
moderate activity level and 5 percent at the heavy activity level. If
the assessment is applicable to children, a similar approach can be taken
using values for specific age groups at specified activity levels as
provided in Table 3-1.
Exposure Duration
Exposure duration is determined by multiplying the number of hours
exposed per week, the number of weeks exposed per year, and the number of
years exposed at a residence. For this route, the number of hours exposed
per week must be determined for each specific scenario. As explained
below, a generic value for the number of hours spent inside one's resi-
dence has been estimated at 115 hours per week. In a determination of
the amount of time adults spend indoors at home, it was assumed, based on
activity descriptions in Appendix 5B, that 50 percent of the time allotted
to the following activities (Table 5-5) was spent inside the home: 02,
05, 16, 19, 27, 54, 75, 83, 85.
The remaining activity codes describe all other activities taking
place indoors at home: 10-12, 14, 20-24, 26, 40-43, 45-48, 84, 90-98.
1-24
-------
By adding the time values associated with the above activities, it is
estimated that the average adult spends approximately 115 hours per week
inside the home. This value may be used as a default value for the time
spent inside one's residence on a weekly basis. The average number of
years an individual lives in any given residence is assumed to be 9. For
a reasonable worst-case estimate, a value of 30 years may be used. Thus,
the average number of hours an individual is exposed inside a given
residence is 54,000. For the reasonable worst-case estimate, a total of
180,000 hours of exposure can be used. These values should only be used
when more precise time values are not available. For specific activities
that produce exposures of a shorter duration, the lower activity-specific
values should be used (see Section 5.3).
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk-
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-25
-------
1.9
Inhalation of Vapors While Showering at Residence1
SCENARIO: An individual showers at his/her residence daily and is
exposed to contaminants volatilizing from the water.
Lifetime Average Daily Exposure
(IR) It) (ED)
(BW) (LT) (365 days/yr)
IR - inhalation rate (m3/hr)
C s concentration of contaminant in air (p.g/mr)
ED^ s exposure duration (hr)
BW » body weight of average adult (kg)
LT = lifetime (yr)
Parameter Average
IR 0.6 0.6
C Site specific
ED 375 375-2,200
BW 70 70
LT 75 75
Distribution
Not available
p. 5-36
pp. 5-40 - 5-43
To be developed
1. The contaminants released during showering are likely to be found
throughout a house because of the exchange with the bathroom air and
releases from other sources within the house (i.e., dishwasher, cook-
ing, washing machine). Recent work by Andelman et al. (1986) suggests
that exposure while showering is less than exposure occurring through-
out the house because of the longer exposure time.
2. Exposure duration refers to the actual number of hours an individual
is exposed while showering at a given residence.
3. No range value is given for inhalation rate since it was felt that
0.6 nr/hr was representative of the entire exposed population.
1-26
-------
RATIONALE FOR RECOMMENDED VALUES FOR"
INHALATION OF VAPORS WHILE SHOWERING AT RESIDENCE
Inhalation Rate
The value recommended for this parameter assumes that showering
represents light activity. The recommended value for this activity is
3
0.6 m /hour (see Table 3-1). No reasonable worst-case value is recom-
mended since it is felt that the light activity level is representative of
showering for the entire exposed population.
Exposure Duration
Exposure duration is determined by multiplying the number of hours
exposed per week, the number of weeks exposed per year, and the number of
years exposed at a residence. The number of hours exposed per week is
0.8 (7 minutes/day) for the average case (see Section 5.3.6), and 1.4
(12 minutes/day) for the reasonable worst-case exposure (James and Knuiman
1987). It was assumed that individuals were exposed daily. The average
number of years an individual spends in one residence is assumed to be 9.
For a reasonable worst case estimate, a value of 30 years may be used.
«
Thus, the average number of hours an individual is exposed while showering
is 375. For the reasonable worst-case estimate, a total of 2,200 hours of
- ^w
exposure can be assumed.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
1-27
-------
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-28
-------
1-10 Inhalation of Participates Outside Residence
SCENARIO: An individual is engaged in various activities outside his/her
residence and is exposed to contaminated particulates present
in ambient air.
(IR) (PC) (RF) (C) (ED) (10-6 g/^g)
- (BW) (LT) (365 days/yr)
xDurP
txposure -
IR
PC
RF
C
ED1
BW
LT
inhalation rate (m3/hr)
particulate concentration in air
respirable fraction of particulates
concentration of contaminant on particulate
exposure duration (hr)
body weight of average adult (kg)
lifetime (yr)
Parameter
JR
PC
RF
C
Ll
Average
Range2
1-4 1.4-3.0
Site specific
Site specific
Site specific
1,440 1,440-4,800
70 70
/J> '5
Distribution
Not available
Not avail able
pp. 5-40 - 5-43
To be developed
1. Exposure duration refers to the actual number of hours an individual
is exposed outside a given residence.
2. Range values represent typical and reasonable worst-case values.
1-29
-------
RATIONALE FOR RECOMMENDED VALUES FOR
INHALATION OF PARTICULATES OUTSIDE RESIDENCE
Inhalation Rate
For exposure screening purposes, it can be assumed that the inhalation
of particulates takes place at a constant rate. This parameter varies
depending upon the activity levels of the exposed individual. Because
activities vary widely depending upon the individual and the environmental
setting, a generic mix of activity levels was assumed. More accurate,
site-specific activity data should be used when available. For the
average case of an individual performing activities outside the residence,
data from Table 3-2 suggest that 37 percent of the time would be spent at
a moderate activity level, 28 percent at both the resting and the light
activity levels, and 7 percent at a heavy activity level. The average
inhalation rate for this mix of outdoor activities is 1.4 m /hour. For
a reasonable worst-case exposure, it was assumed that an individual would
spend 50 percent of the time at a heavy activity level and 50 percent of
the time at a moderate activity level. The reasonable worst-case inhala-
o
tion rate estimated using these assumptions is 3.0 m /hour. The above
estimates are based on adults, but assessments applicable to children can
be done similarly using values for specific age groups at specified activ-
ity levels as provided in Table 3-1.
Exposure Duration
Exposure duration is determined by multiplying the number of hours
exposed per week, the number of weeks exposed per year, and the number of
years exposed at a residence. For this route, the number of hours exposed
per week must be determined for each specific scenario. A generic value
for the number of hours spent outside one's residence has been estimated
at 3.07 hours per week. Refer to Section 5.3.3 for an explanation of the
derivation of this generic value. This value may be used as a default
value for the time spent outside one's residence on a weekly basis. It
is also assumed that this value represents an annual average of the
1-30
-------
amount of time adults spend outdoors at home. Time use data were
collected for the months of October, November, February, May, and
September, providing an annual representation of human activity patterns
(Hill 1985). It is assumed that an individual is exposed every week of
the year. , The average number of years an individual lives in any given
residence is assumed to be 9. For a reasonable worst-case estimate, a
value of 30 years may be used. Thus, the number of hours an individual
is exposed outside a given residence is as follows:
Typical outdoor exposure = (9 yr)(^r)(3'°^khr) = -1,440 hr
Reasonable worst-case outdoor exposure = (30 yr)( wk)(3-07 nr) = -4,300 hr
jr i WK
These, values should only be used when site-specific considerations do not
allow estimation of more precise time Values. For specific activities
that produce exposures of shorter duration, the lower activity-specific
values should be used.
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the Uriited States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-31
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1.11
Inhalation of Particulates Inside Residence
SCENARIO: An individual is engaged in various activities inside his/her
residence and is inhaling contaminated particulates present in
indoor air. .
Lifetime Average
Daily Exposure =
(IR) (PC) (RF) (C) (ED) (10-6 g/Mg)
(BW) (LT) (365 days/yr)
IR « inhalation rate (m3/hr)
PC - particulate concentration in air (/*g/nr)
RF « respirable fraction of particulates
C ** concentration of contaminant on particulate
ED1 - exposure duration (hr)
BW - body weight of average adult (kg)
LT - lifetime (yr)
Parameter Average
IR 0.63 0.63-0.89
PC Site specific
RF Site specific
C Chemical specific
ED 54,000 54,000-180,000
BW 70 70
LT 75 75
Distribution
Not available
Not available
pp. 5-40 - 5-43
To be developed
1. Exposure duration refers to the actual number of hours an individual
is exposed at a given residence.
2. Range values represent typical and reasonable worst-case values.
1-32
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RATIONALE FOR RECOMMENDED VALUES FOR
INHALATION OR PARTICULATES INSIDE RESIDENCE
Inhalation Rate
For exposure screening purposes, it can be assumed that the inhalation
of particulates takes place at a constant rate. This parameter varies
depending upon the activity levels of the exposed individual. Since
activity levels vary widely, a typical mix of activity levels was assumed.
More accurate, site-specific activity data should be used when available.
The average inhalation rate for time spent indoors at home was assumed to
O
be 0.63 m /hour. This was calculated using the average adult inhalation
rates in Table 3-1 and activity levels from Table 3-2: approximately
48 percent of the time at both the resting and the light activity levels,
3 percent at the moderate activity level, and 1 percent at the heavy
activity level. A reasonable worst-case value of 0.89 m3/hour may be
used. This value was calculated assuming 25 percent of time at the
resting activity level, 60 percent at the light activity level,
10 percent at the moderate activity level, and 5 percent at the heavy
activity level. If the assessment is applicable to children, a similar
approach can be taken, using values for specific age groups at specified
activity levels as provided in Table 3-1.
Exposure Duration
Exposure duration is determined by multiplying the number of hours
exposed per week, the number of weeks exposed per year, and the number of
years exposed at a residence. For this route, the number of hours exposed
per week must be determined for each specific scenario. As explained
below, a generic value for the number of hours spent inside one's resi- •
dence has been estimated at 115 hours per week. In a determination of
the amount of time adults spend indoors at home, it was assumed, based on
activity descriptions in Appendix 5B, that 50 percent of the time allotted
to the following activities (Table 5-5) was spent inside the home: 02,
05, 16, 19, 27, 54, 75, 83, 85.
1-33
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The remaining activity codes describe all other activities taking
place indoors at home: 10-12, 14, 20-24, 26, 40-43, 45-48, 84, 90-98.
By adding the time values associated with the above activities, it is
estimated that the average adult spends approximately 115 hours per week
inside the home. This value may be used as a default value for the time
spent inside a house on a weekly basis. The average number of years an
individual lives in any given residence is assumed to be 9. For a
reasonable worst-case estimate, a value of 30 years may be used. Thus,
the average number of hours an individual is exposed inside a given
residence is 54,000. For the reasonable worst-case estimate, a total of
180,000 hours of exposure can be used. These values should only be used
when more precise time values are not available. For specific activities
that produce exposures of a shorter duration, the lower activity-specific
values should be used (see Section 5.3).
Body Weight
The average body weight for an adult (men and women combined) was
calculated to be 71.8 kg (USEPA 1985). Since this approximates the
consensus value of 70 kg traditionally used for exposure/risk
assessments, the value of 70 kg should be used to represent average body
weight.
Lifetime
According to the 1985 edition of the Bureau of the Census Statistical
Abstract of the United States, the average life expectancy of men and
women is 74.6 years, and the figures have shown a steady increase in life
span through time. Therefore, an average figure of 75 years was used for
the lifetime of men and women. The source of the data is a 1982 National
Center for Health Statistics survey.
1-34
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1.12 Dermal Contact with Water at Residence
(CMKolfA) fED)
Lifetime Average =
Daily Dose*
(BW) (LT) (365 days/yr)
C
Kp
A
ED
BW
LT
contaminant concentration in water (mg/cm^)
dermal permeability constant for contaminant (cm/hr)
skin surface area contacted (cnr)
exposure duration (hr)
body weight of average adult (kg)
lifetime (yr)
Parameter
C
Kp
A
ED
BW
LT
Average
Range
Site specific
Chemical specific
To be developed
To be developed
70 70
75 75
Distribution
pp. 5-40 - 5-43
To be developed
*This equation computes the absorbed dermal dose. Dose is presented here
instead of exposure (amount of contaminant in water contacting body)
because it is more useful in dermal risk assessments.
1-35
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1.13 Dermal Contact with Soil While Gardening
Lifetime Average = fC) (CR) (ED)
Daily Exposure (BW) (LT) (365 days/yr)
C - contaminant concentration in soil (mg/g)
CR - contact rate (g/day)
ED * exposure duration (day)
BW = body weight of average adult (kg)
LT = lifetime (yr)
Parameter Average Range ,- Distribution
C Site specific
CR To be developed —
ED To be developed
BW 70 70 pp. 5-40 - 5-43
LT 75 75 To be developed
1-36
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2. ANALYSIS OF UNCERTAINTIES
The previous section presented standard exposure scenarios, algorithms
for estimating exposure in each scenario, and the exposure factor values
recommended for use. The exposure factor values recommended can be used
to obtain average exposure estimates, reasonable worst-case estimates, and
estimates that realistically "bound" the range of possible exposures.
This section discusses methods that can be used to qualitatively and quan-
titatively evaluate and present the uncertainty associated with exposure
scenario estimates.
The goal of an analysis of uncertainties is to provide decision makers
with the complete spectrum of information concerning the quality of an
assessment, including the potential variability in the estimated exposures
(because of the inherent variability in the exposure scenario input
factors), the major data gaps, and the effect these data gaps have on the
accuracy or reasonableness of the exposure estimates developed. Analysis
and presentation of the uncertainties allow the user(s) or decision
maker(s) to better evaluate the assessment results in the context of other
factors being considered. This, in turn, leads to a more sound and open
decision-making process. The following subsections briefly describe
procedures for qualitatively and quantitatively analyzing and presenting
the uncertainties in exposure scenario estimates. Detailed information
on the analysis of uncertainties in exposure assessments is presented in
EPA's Guidelines for Estimating Exposures (USEPA 1986) and EPA (1985).
2.1 Qualitative Analysis
Qualitative analysis of uncertainties involves determination of the
general quality and reasonableness of exposure data and exposure assess-
ment results. Qualitative analysis should be performed on all exposure
assessments and exposure-related data. Qualitative analysis is paramount
to screening, preliminary, and intermediate level assessments. In
addition to a qualitative analysis, however, detailed assessments may
also require quantitative uncertainty analysis techniques.
2-1
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As part of the qualitative analysis, the cause of uncertainty is ini-
tially determined. The basic cause of uncertainty is a lack of knowledge
on the part of the analyst because of inadequate, or even nonexistent,
experimental and operational data on processes and parameters. Specific
causes of uncertainty include or can be categorized as follows:
• Measurement error - uncertainty in this case arises from random
and systematic error in the measurement technique.
• Sampling error - uncertainty arises from the representativeness
of the data of the actual population being sampled.
• Variability - the natural variability in environmental and
exposure-related parameters can frequently be a major cause of
uncertainty. For example, the exposure factors discussed in this
handbook are all subject to variability, which in turn causes
variability in the exposure estimates developed using them.
• Limitations in model form - how close to reality is the model
function and output (e.g., the water quality model for estimating
pollutant concentrations in the aquatic environment)?
* Application and quality of generic or indirect empirical data -
uncertainty arises from both the applicability of the indirect data
and the measurement or sampling error in the data.
• Professional judgment - frequently, data gaps must be filled
based on engineering or scientific assumptions, which have inherent
uncertainty.
Identification of the causes of uncertainty, therefore, is an outcome of
the determination of the extent, consistency, completeness, and quality
of the available exposure data.
Once the causes of the uncertainties are identified, the impact these
uncertainties have on the assessment results should be determined. Where
uncertainty exists, data or estimates of a range of plausible values
should be gathered. The effects of the range of assessment input values
on the assessment results (or output value) can be determined numerically
through the substitution of plausible alternative values for each input
parameter. This procedure is similar to a sensitivity analysis, which is
discussed in the next subsection. The variation in output attributable
to variations in input values or parameters can thus be evaluated. A
2-2
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table should be constructed to correspond to the parameters in the assess-
ment, including a listing of possible variations in each parameter that
would encompass a reasonable range of actual .expected exposure conditions.
The text or footnotes accompanying this table should explain the basis of
each assumption.
This review of uncertainties should include a qualitative evaluation
of the significance of pertinent assumptions in light of reasonable varia-
tions that could be encountered for actual exposure conditions. If possi-
ble, special emphasis should be placed on evaluating extremes in each
assumption. For example, have parameters been chosen to evaluate extreme
or average exposure conditions? Are the exposure estimates likely to be
overestimates or underestimates? Explicit presentation of the qualitative
analysis results will transmit the level of confidence in the results to
the future data user or decision maker and will aid in determining future
actions.
2.2 Quantitative Analysis
In detailed exposure assessments or when initial worst-case exposure
estimates indicate significant exposure or risk, uncertainty can be char-
acterized via (1) sensitivity analysis and/or (2) probability analysis
(e.g., Monte Carlo simulation) techniques. The technique selected depends
on the availability of input data statistics. Performance of sensitivity
testing requires data on the range of values for each exposure factor in
the scenario. Probabilistic analysis requires data on the range and
probability function (or distribution) of each exposure factor in the
scenario. Each of these procedures is subsequently discussed.
2.2.1 Sensitivity Analysis
Sensitivity analysis is a technique that tests the sensitivity of an
output variable to the possible variation in the input variables of a
given model. The purpose of the sensitivity analysis is to identify the
influential^ input variables and develop bounds on the model output. By
identifying the influential input variables, more resources can be direct-
ed to reduce their uncertainties and hence reduce the output uncertainty.
2-3
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The sensitivity of the output variable of a given mathematical model
depends on the nature of the mathematical relationship of the model (and
plausible values of its input variables). For. a given model, the sensi-
tivity of the output variable with respect to each input variable is
computed and the sensitivities of all input variables are compared. When
computing the sensitivity with respect to a given input variable, all
other input variables are held fixed at their nominal values.
The sensitivity analysis is to be performed when limited information
(data) is available about the input variables. This information can be
in the form of best estimates of the centralities of the input variable
(mean, median, mode) or estimates of the ranges (minimum and maximum) of
the input variables. Accordingly, two types of sensitivity analysis can
be classified: point sensitivity and range sensitivity.
Range sensitivity analysis estimates the range of output values that
would result as individual input variables are varied from their minimum
to their maximum possible value with other input variables held at fixed
values, e.g., their midranges. Point sensitivity is the sensitivity of
the output to the centrality variability (mean, median, mode) of a given ,
input variable at a given value of that input variable with the other
input variables held at best estimates of their centralities. Point
sensitivity analysis is applicable only to skewed models with distinct
values for the mean, median, and mode.
Once the most influential model input variables are identified, col-
lection of additional data for these variables would be warranted. Less
effort also might be directed toward collecting data on the less sensitive
input factors. It might be reasonable to treat the less sensitive factor
or factors as fixed at the estimate of their centralities. A demonstra-
tion of a sensitivity analysis on an example exposure scenario algorithm
is presented in Section 2.4.
2.2.2 Monte Carlo Simulation
The Monte Carlo simulation is a technique that can be used to provide
a probability function of estimated exposure using random values of
2-4
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exposure factors in an exposure scenario. The Monte Carlo simulation
involves assigning a joint probability distribution to the input variables
(i.e., exposure factors) of an exposure scenario. Next, a large number
of independent samples from the assigned joint distribution are taken and
the corresponding outputs calculated (i.e., >1,000 iterations). This
is accomplished by repeated computer runs through the problem using random
numbers to assign values to the exposure factors. The simulated output
represents a sample from the true output distribution. Methods of statis-
tical inference are used to estimate, from the exposure output sample,
some parameters of the exposure distribution, such as percentiles, mean,
variance, and confidence intervals. The Monte Carlo simulation can also
be used to test the effect a hypothesized probability distribution for an
input parameter has on the output distribution.
When a specific probability distribution is used to express uncertain-
ty in one or more input factors of an exposure model, a distribution of
exposure is generated. The exposure assessor may investigate the effects
of using different probability distributions for an input variable and/or
the effects of using different functional forms of the exposure model on
the type of exposure distribution output. The Monte Carlo simulation pro-
cedure yields an exposure distribution that is strictly a consequence of
the assumed distributions of the model inputs and the assumed functional
form of the model.
In general, the selection of a probability distribution to represent
an input factor in the exposure models should be based upon any gathered
information about that factor, theoretical arguments, and/or expert
opinions. A probability distribution can be ascertained from such infor-
mation as the following: general shape of the distribution, minimum,
maximum, mode, mean, median, midrange, and other percentiles. Available
data on the probability distributions for each of the exposure factors
discussed in this handbook have been presented in previous sections.
When distribution data are not available, distributions can be assigned
using professional judgment. The following considerations are relevant
to the process of selection:
2-5
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• A uniform distribution would be used to represent a factor when
nothing is known about the factor except its finite range. The use
of a uniform distribution assumes that all possible values within
the range are equally likely.
• If the range of the factor and its mode are known, then a triangu-
lar distribution would be used.
• If the factor has a finite range of possible values and a smooth
probability function is desired, a Beta distribution (scaled to the
desired range) may be most appropriate. The Beta distribution can
be fit from the mode and the range that defines a middle specific
percent (e.g., 95 percent) of the distribution.
• If the factor only assumes positive values, then a Gamma, Log-
normal, or Wei bull distribution may be an appropriate choice. The
Gamma distribution is probably the most flexible; its probability
function can assume a variety of shapes by varying its parameters
and it is mathematically tractable. These distributions also can be
fit from the knowledge of the mode and the percentiles that capture
the middle 95 percent of the distribution.
• If the factor has an unrestricted range of possible values and is
symmetrically distributed around its mode, then a normal distribu-
tion may be an appropriate distribution.
• Unless specific information on the relationships between exposure
parameters is available, assume values for the required input
parameters are independent.
Once the probability distributions of all exposure factors are
developed or assigned, the Monte Carlo simulation can be performed.
Normally, this simulation is time-consuming and requires the use of a
computer. Numerous commercial personal computer (PC) based programs are
available to perform the simulation. One in particular, designed specifi-
cally for use in exposure assessment, was recently developed (Versar.
1987). The program, called PC-MC, can simulate algorithms with up to nine
input and three output functions. A simulation can be performed in little
more than the time required to enter the algorithm, range, and probability
distribution of each input value. The output of the simulation is a fre-
quency distribution and cumulative frequency distribution from which the
mean, median, variance, and percentile exposure levels can be extracted.
(Note: percentile exposure levels reflect the real statistical distribu-
tion only if all input assumptions (i.e., variable distributions and their
2-6
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independence) are known to be correct). If the input distributions were
arrived at using judgment instead of actual data, the output of the simu-
lation is useful only in terms of discussing a likely range of exposure).
A demonstration of a probabilistic analysis on an example exposure
scenario problem using the PC-MC program is presented in Section 2.4.
2.3 Presentation of Uncertainty Analysis Results
Comprehensive qualitative analysis and rigorous quantitative analysis
are of little value if the analysis results are not clearly presented for
use in the decision-making process. The following procedures can be used
to present the results of the uncertainty analysis:
• Exposure estimates should clearly identify the input parameters to
which they are most sensitive, including a quantitative statement
of the magnitude of sensitivity (e.g., percent variability of the
output across the range of possible input values). Where Monte
Carlo simulations are performed, exposure estimates could be
presented as percentile intervals (or cumulative probability
percentile intervals). For each interval, the associated exposure
conditions should be described.
• Each exposure scenario should conclude with statements of qualita-
tive and quantitative uncertainties, including the major data gaps
or other causes of uncertainty. This information can be presented
in tabular format.
• Uncertainties for the overall exposure assessment could be
summarized and presented as a section that precedes all other
report sections or, alternatively, the results could be
incorporated into an Executive Summary.
2.4 Example Problems
Performance of sensitivity analysis and probabilistic analysis tech-
niques on exposure scenario problems is demonstrated in the following sub-
sections. Completion of the two example problems that follow was facili-
tated by the use of the PC-MC program previously described. Numerous
other programs are available or can be developed for specific exposure
assessment problems. The example problems presented use the .scenarios
and exposure factors previously presented in this handbook. As has been
discussed in all the scenarios presented, the concentration values used
are site or issue specific. For the following sample problems, the
2-7
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concentration values used were assumed for demonstration purposes only.
Furthermore, the values assumed are fixed values (i.e., a range and
probability function for the concentration factor was not developed).
This approach permits the evaluation of the significance of the other
exposure factors on the estimated exposure output.
Example 1: Analysis of the Sensitivity of Estimated Inhalation Exposure
to Exposure Factors Variability (Scenario presented in Section 1-9,
Part II)
Scenario: Estimate the range of lifetime inhalation exposure (mass/kg
body wt/day) to chemical X that volatilizes from water while
showering at residence. Calculate the range sensitivity of the
estimated exposure to variations in the range of values for
each input parameter.
Lifetime Average Daily Exposure = (IR) (C) (ED)
(BW) (LT) (365 days/yr)
IR = inhalation rate (m3/tir)
C - concentration of contaminant in air (/ig/nr)
ED1 - exposure duration (hr)
BW * body weight of average adult (kg)
LT - lifetime (yr)
Parameter Average Range2
IR 0.6 0,6-2.0
C Site specific*3
ED 220 220-1,520
BW 70 46.8-70
LT 75 75
Notes for Example 1:
* Exposure duration refers to the actual number of days an individual is
exposed at a given residence.
2 Except for body weight, the range of values listed is the average
value to the 95th percentile value. The ranges of body weight values
are the 5th to 50th percentile values for adult females and males.
(These values may differ from those used in Chapter 1, Part II because
a sensitively analysis requires the use of a range of values rather
than a single constant value.)
3 For purposes of this example problem, the concentration of chemical X
is assumed to have a mean value of 100 pg/nr3. For most exposure
estimates, a range of values should be available. For this example
problem, however, use of a fixed value for the concentration permits
evaluation of the sensitivity of the exposure estimate to variations of
the exposure factors.
2-8
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Summary of Results for Example 1:
Table 2-1 summarizes the estimated exposure range, as each parameter
value is varied from its minimum to maximum while all other parameters are
fixed at their nominal value. For this example problem, the estimated
inhalation exposure can range from 0.00689 Atg/kg/day (i.e., when
average or minimum input values are used) to 0.23729 /*g/kg/day (i.e.,
when 95th percentile or maximum input values are used). Examination of
the sensitivity analysis results indicates that the estimated exposure is
most sensitive to variation in the exposure duration (ED) values.
Variation in values for body weight (BW) have minimal impact on the
estimated exposure.
Example 2: Analysis of the Probability Distribution of Estimated
Ingestion Exposure (Scenario presented"in'Section 1.5, Part II)
Scenario: Estimate the average to 95th percentile probability distribu-
tion of lifetime ingestion exposure (mass/kg of body wt/day) to
chemical X from recreationally caught fish.
Exposure = (CR) fC) (ED) (DF)
(BW) (LT) (365 days/yr)
CR = fish consumption rate (g/day)
C = concentration of contaminant in fish (mg/g)
ED;* = exposure duration (day)
DF^ = diet fraction
BW = body weight (kg)
LT = lifetime (yr)
Parameter
CR
C
ED
DF
BW
LT
Average
30
10
3,285
0.2
70
75
30-140
10
3,285-10,950
0.2-0.75
46.8-70
75
Distribution^
Lognormal
(skewed right)
Fixed value^
Lognormal
Lognormal
Normal
Fixed value
2-9
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Table 2-1. Sumnary of Sensitivity Analysis Results
for Example 1
Input
parameter Input range
Estimated exposure
range -(ug/kg/day)
Range
difference
1R
C
ED
BW
LT
0.6 - 2.0
100
220 - 1520
46.8 - 70
75
0.00689 - 0.02236
* * * FIXED VALUE * * *
fi.00689 - 0.04760
0,00689 - 0-01031
* * * FIXED VALUE * * *
0.01607
0,. 04071
0.00341
2-10
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Notes for Example 2:
1 Exposure duration refers to the actual number of days an individual
is exposed.'
Diet fraction represents the portion of a person's fish diet derived
_ from the contaminated source.
Except for body weight, the range of values listed is the average
value to the 90th or 95th percentile value. The ranges of body weight
values are the 5th to.50th percentile values for both males and females
(These values may differ from those used in Chapter 1, Part II since a
probabilistic simulation requires the use of a distribution rather than
a single constant value.)
Distributions listed are assumed for demonstration purposes only
For purposes of this example problem, the concentration of chemical X
is assumed to have a mean value of 10 mg/g. For most exposure esti-
mates, a range of values should be available. For this example problem
however, use of a fixed value for the concentration permits evaluation
of the sensitivity of the exposure estimate to variations of the
exposure factors.
Summary of Results for Example 2:
Statistics .for the probability distribution of the estimated exposure
are provided in Table 2-2., Table 2-3 presents results of'a sensitivity
analysis. Based on the simulation results, the estimated mean exposure
is 0.604 mg/kg/day, with a median (50th percentile) value of 0.324
mg/kg/day. The 5th percentile value is 0.131 mg/kg/day, and the 95th
percentile value is 1.95 mg/kg/day. The sensitivity analysis results
indicate that each of the parameters has approximately equal significance
to variation in the estimated exposure. Performance of the probabilistic
analysis, as demonstrated, allows for the presentation of data that
provide a clearer characterization of the potential variability of an
output as opposed to single-value best estimates". The results are
further enhanced when a qualitative analysis is also performed,
describing the analyst's confidence in the algorithm input data (e.g.,
reasonableness of the scenario) and the overall estimated exposure.
2-11
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Table 2-2. Summary of Probabilistic Analysis Results
for Example 2
Statistic
Value (rag/kg/day)
Mean
Median
0.604
0.324
Minimum
Maximum
Range
0.104
10.149
10.045
Percent:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0.131
0.144
0.160
0.178
0.193
0.213
0.228
0.251
0.287
0.324
0.368
0.416
0.495
0.556
0.650
0.810
1.023
1.319
1.950
2-12
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Table 2-3. Summary of Sensitivity Analysis Results
for Example 2
Input
parameter Input range
Estimated exposure
range (mg/kg/day)
Range
difference
CR
C
ED
DF
BW
LT
3.0 - 140
10
3285 - 10950
0.2 - 0.75
46.8 - 70
75
0.1028 - 0.48 .
* * * FIXED VALUE * * *
0.1028 - 0.3427
0.1028 - 0.3855
0.1028 - 0.1538
* * * FIXED VALUE * * *
0.3772
0.2399
0.2827
0.0510
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2.5 References
USEPA. 1985. U.S. Environmental Protection Agency. Methodology for
characterization of uncertainty in exposure assessments. Washington,
DC: Office of Health and Environmental Assessment, Exposure Assessment
Group. EPA/600/8-85-009. Available from: NTIS, Springfield, VA.
PB85-240455.
USEPA. 1986. U.S. Environmental Protection Agency. Guidelines for
estimating exposures. Federal Register 51(I85):34042-34054.
Versar. 1987. PC-MC (Version 1.1) Monte Carlo simulation program.
Washington, DC: U.S. Environmental Protection Agency, Office of Toxic
Substances. EPA Contract No. 68-02-4254.
2-14
•&US. GOVERNMENT PRINTING OFFICE: 1991 - 548-I87/4M28
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