-------
Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
Table
3-26. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and Poverty Category
Plain Tap Water
(mL/kg-day)
Age
Sex
Region
Variable
<12 months
12-24 months
Male
Female
Northeast
Midwest
South
West
N
296
650
475
471
175
197
352
222
Mean
11
18
15
15
13
14
15
17
SE
1.0
0.8
1.0
0.8
1.4
1.0
1.3
1.1
Total Water
(mL/kg-day)
Mean
130
108
116
119
121
120
113
119
SE
4.6
1.7
4.1
3.2
6.3
3.1
3.7
4.6
Urbanicity
Poverty
Total
a
N
SE
Source:
Urban
Suburban
Rural
category3
0-1.30
1.31-3.50
>3.50
Poverty category represents
federal poverty level.
= Number of observations.
= Standard Error.
Heller etal, 2000.
305
446
195
289
424
233
946
family
16
13
15
19
14
12
15
s annual incomes of 0-1
1.5
0.9
1.2
1.5
1.0
1.3
0.6
30,1.31-3
123
117
109
128
117
109
118
50, and greater than 3
3.5
3.1
3.9
2.6
4.2
3.5
2.3
50 times the
Page
3-28
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
Table 3-27. Intake of
Water Intake from:
Water from Various Sources in 2-13-y-old Participants of the
DONALD Study 1985-1999
Boys and girls Boys and girls
2-3 years 4-8 years
N=858b N= 1,795"
Boys
9-13 years
N=541b
Girls
9-13 years
N = 542"
Mean
Water in Food (mL/day)3
Beverages (mL/day)3
Milk (mL/day)3
Mineral water (mL/day)3
Tap water (mL/day)3
Juice (mL/day)3
Soft drinks (mL/day)3
Coffee/tea (mL/day)3
Total water intake3-4 (mL/day)
Total water intake3-4 (mL/kg-day)
Total water intake3-4 (mL/kcal-
day)
365 (33)c
614(55)
191(17)
130(12)
45(4)
114(10)
57(5)
77(7)
1,114±289 1
78 ±22
1.1±0.3
3 Converted from g/day, g/kg-day, or g/kcal-day; 1 g =
b N = Number of records.
487 (36)
693(51)
177(13)
179(13)
36(3)
122 (0)
111(8)
69(5)
Mean±
,363 ±333
61 ±13
0.9 ±0.2
ImL.
673 (36)
969(51)
203(11)
282(15)
62(3)
133 (7)
203(11)
87(4)
SD
1,891 ±428
49±11
1.0 ±0.2
634 (38)
823 (49)
144 (9)
242(15)
56(3)
138(8)
155(9)
87(5)
1,676 ±386
43 ±10
1.0 ±0.2
c Percent of total water shown in parentheses.
4 Total water = water in food + beverages + oxidation.
SD = Standard deviation.
Source: Sichert-Hellert et al. , 200 1 .
Child-Specific Exposure Factors Handbook
September 2008
Page
3-29
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
Table 3-28. Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years,
NHANESm, 1988-94
Total fluid
Plain water
Milk
Carbonated drinks
Juice
N = Number of observations
Source: Sohnet al., 2001.
Total Sample
(N = 7,925)
84 ±1.0
27 ±0.8
18 ±0.3
6 ±0.2
12 ±0.3
Sample with
Temperature Information
(N = 3,869)
84 ±1.0
27 ±1.0
18 ±0.6
5 ±0.3
11±0.6
Sample without
Temperature Information
(N = 4,056)
85 ±1.4
26±1.1
18 ±0.4
6 ±0.3
12 ±0.4
Page
3-30
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
Table 3-29. Estimated Mean (± Standard Error) Amount of Total Fluid and Plain Water Intake
among Children3 Aged 1-10 Years: (NHANES HI, 1988-94)
Total Fluid
mL/day mL/kg-day
Age (years)
1 578 1,393 ±31 124 ±2. 9
2 579 1,446 ±31 107 ±2.3
3 502 1,548 ±75 100 ±4.6
4 511 1,601 ±41 91 ±2. 8
5 465 1,670 ±54 84 ±2. 3
6 255 1,855 ±125 81 ±4. 9
7 235 1,808 ±66 71 ±2.3
8 247 1,792 ±37 61 ± 1.8
9 254 2,113 ±78 65 ±2.1
10 243 2,051 ±97 58 ±2.4
Sex
Male 1,974 1,802 ±30 86 ±1.8
Female 1,895 1,664±24 81 ± 1.5
Race/ethnicity
White 736 1,653 ±26 79 ±1.8
African American 1,122 1,859 ±42 88 ±1.8
Mexican American 1,728 1,817 ±25 89 ±1.7
Other 283 1,813 ±47 90 ±4.2
Poverty income ratiob
Low 1,868 1,828 ±32 93 ±2. 6
Medium 1,204 1,690 ±31 80 ±1.6
High 379 1,668 ±54 76 ±2.5
Region04
Northeast 679 1,735 ±31 87 ±2. 3
Midwest 699 1,734 ±45 84 ±1.5
South 869 1,739 ±31 83 ±2.2
West 1,622 737 ±25 81 ± 1.7
Urban/rural11
Urban 3,358 1,736 ±18 84 ±1.0
Rural 511 1,737 ±19 84 ±4.3
Total 3,869 1,737 ±15 84 ±1.1
a Children for whom temperature data were obtained.
b Based on ratio of household income to federal poverty threshold. Low: <1 .300; medium: 1
Plain Water
mL/day mL/kg-day
298 ±19 26 ±1.8
430 ±26 32 ±1.9
482.±27 31 ±1.8
517±23 29±1.3
525 ±36 26 ±1.7
718±118 31 ±4.7
674 ±46 26 ±1.9
626 ±37 21 ±1.2
878 ±59 26 ±1.4
867 ±74 24 ± 2.0
636 ±32 29 ±1.3
579 ±26 26 ±1.0
552 ±34 24 ±1.3
795 ±36 36 ±1.5
633 ±23 29 ±1.1
565 ±39 26 ±1.7
662 ±27 32 ±1.3
604 ±35 26 ±1.4
533 ±41 22 ±1.7
568 ±52 26 ±2.1
640 ±54 29 ±1.8
613 ±24 28 ±1.3
624 ±44 27 ±1.9
609 ±29 27 ±1.1
608 ±20 28 ±1.2
609 ±24 27 ±1.0
301-3. 500; high >3. 501.
0 All variables except for Region and Urban/rural showed statistically significant differences for both total fluid and plain water
intake by Bonferroni multiple comparison method.
d Northeast = Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York,
Vermont;
Pennsylvania, Rhode Island,
Midwest = Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota,
Wisconsin;
South = Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky,
North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia;
Louisiana, Maryland, Mississippi,
West = Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington,
Wyoming.
N = Number of observations.
Source: Sohn et al., 2001.
Child-Specific Exposure Factors Handbook
September 2008
Page
3-3.
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
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September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
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Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
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Child-Specific Exposure Factors Handbook
September 2008
Page
3-35
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion
Table 3-34. Pool Water Ingestion by Swimmers
Study Group
Children <16 years old
Males <16 years old
Females <16 years old
Adults (> 18 Years)
Men
Women
a Converted from mL/45
Source: Dufour et al., 2006.
Number of Average Water Ingestion Rate
Participants (mL/45-minute interval)
41
20
21
12
4
8
minute interval.
37
45
30
16
22
12
Average Water Ingestion Rate
(mL/hour)a
49
60
43
21
29
16
Page Child-Specific Exposure Factors Handbook
3-36 September 2008
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
TABLE OF CONTENTS
NON-DIETARY INGESTION FACTORS
4.1
4.2
4.3
4.4
4.5
4.6
INTRODUCTION
RECOMMENDATIONS
NON-DIETARY INGESTION - MOUTHING FREQUENCY STUDIES
4.3.1 Key Studies of Mouthing Frequency
4.3. .1 Zartarian et al.,1997a/Zartarian et al, 1997b/Zartarian et al, 1998 . . .
4.3. .2 Reed et al., 1999
4.3. .3 Freeman et al., 2001
4.3. .4 Tulve et al., 2002
4.3. .5 Black et al., 2005
4.3. .6 Xue et al., 2007
4.3.2 Relevant Studies of Mouthing Frequency
4.3.2.1 Davis etal., 1995
4.3.2.2 Lew and Butterworth, 1997
4.3.2.3 Tudella et al., 2000
4.3.2.4 AuYeung et al., 2004
4.3.2.5 Ko et al., 2007
NON-DIETARY INGESTION - MOUTHING DURATION STUDIES
4.4. 1 Key Mouthing Duration Studies
4.4.1.1 Juberg et al., 2001
4.4.1.2 Greene, 2002
4.4.2 Relevant Mouthing Duration Studies
4.4.2.1 Barr et al., 1994
4.4.2.2 Zartarian et al., 1997a/Zartarian et al., 1997b/Zartarianet al., 1998 . .
4.4.2.3 Groot et al., 1998
4424 Smith and Norris 2003/Norris and Smith 2002
4425 Au Yeung et al 2004
MOUTHING PREVALENCE
451 Stanek et al 1998
452 Warren et al 2000
REFERENCES FOR CHAPTER 4
. ... 4-1
. ... 4-1
. ... 4-2
. ... 4-5
. ... 4-5
. ... 4-5
. ... 4-5
. ... 4-6
. ... 4-7
. ... 4-7
. ... 4-8
. ... 4-8
. ... 4-8
. ... 4-9
. . . 4-10
. . . 4-10
. . . 4-11
. . . 4-12
. . . 4-12
. . . 4-12
. . . 4-12
. . . 4-13
. . . 4-13
. . . 4-14
. . . 4-15
4-15
4-16
4-17
4-17
4-18
4-18
Child-Specific Exposure Factors Handbook Page
September 2008 4-i
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
LIST OF TABLES
Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration 4-3
Table 4-2. Confidence in Recommendations for Mouthing Frequency and Duration 4-4
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-transcription 4-21
Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age 4-21
Table 4-5. Video-transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
(contacts/hour) 4-21
Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour) 4-22
Table 4-7. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD) 4-23
Table 4-8. Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
Studies 4-23
Table 4-9. Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
Studies 4-23
Table 4-10. Survey Reported Mouthing Behaviors for 92 Washington State Children 4-24
Table 4-11. Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children
with >15 minutes in View Indoors 4-24
Table 4-12. Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children .... 4-25
Table 4-13. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
Other Objects 4-26
Table 4-14. Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category
and Child's Age 4-26
Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) 4-27
Table 4-16. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without
Pacifier, in Minutes per Day 4-29
Table 4-17. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys,
and Other Objects (hours:minutes:seconds) 4-30
Table 4-18. Outdoor Median Mouthing Duration (Seconds per contact), Video-transcription
of 38 Children 4-31
Table 4-19. Indoor Mouthing Duration (Minutes per hour), Video-transcription of 9 Children
with >15 minutes in View Indoors
Table 4-20. Outdoor Mouthing Duration (Minutes per hour), Video-transcription of 38 Children . .
Table 4-21. Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
Behaviors
4-31
4-32
4-33
Page
4-ii
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
4 NON-DIETARY INGESTION FACTORS
4.1 INTRODUCTION
Young children have the potential for
exposure to toxic substances through non-dietary
ingestion pathways other than soil and dust ingestion
(e.g., ingesting pesticide residues that have been
transferred from treated surfaces to the hands or
objects that are mouthed). Young children mouth
objects or their fingers as they explore their
environment. Mouthing behavior includes all
activities in which objects, including fingers, are
touched by the mouth or put into the mouth except for
eating and drinking, and includes licking, sucking,
chewing, and biting (Groot et al., 1998). Videotaped
observations of children's mouthing behavior
demonstrate the intermittent nature of hand to mouth
and object to mouth behaviors in terms of the number
of contacts recorded per unit of time (e.g., Ko et al.,
2007).
In a large non-random sample of children
born in Iowa, non-nutritive sucking behaviors were
reported by parents to be very common in infancy, and
to continue for a substantial proportion of children up
to the third and fourth birthdays (Warren et al., 2000).
Hand to mouth behavior has been observed in both pre-
term and full term infants (Rochat et al., 1988, Blass
et al., 1989, Takaya et al., 2003). Infants are born
with a sucking reflex for breast feeding, and within a
few months, they begin to use sucking or mouthing as
a means to explore their surroundings. Sucking also
becomes a means of comfort when a child is tired or
upset. In addition, teething normally causes
substantial mouthing behavior (i.e., sucking or
chewing) to alleviate discomfort in the gums (Groot et
al., 1998). Children's mouthing behavior can
potentially result in ingestion of toxic substances
(Lepow et al., 1975).
There are three general approaches to gather
data on children's mouthing behavior: real-time hand
recording, in which trained observers manually record
information (e.g., Davis et al., 1995); video-
transcription, in which trained videographers tape a
child's activities and subsequently extract the pertinent
data manually or with computer software (e.g., Black
et al., 2005); and questionnaire, or survey response,
techniques (e.g., Stanek et al., 1998). With real-time
hand recording, observations made by trained
professionals (rather than parents) may offer the
advantage of consistency in interpreting visible
behaviors and may be less subjective than observations
made by someone who maintains a care giving
relationship to the child. On the other hand, young
children's behavior may be influenced by the presence
of unfamiliar people (e.g., Davis et al., 1995). Groot
et al. (1998) indicated that parent observers perceived
that deviating from their usual care giving behavior by
observing and recording mouthing behavior appeared
to have influenced the children's behavior. With
video-transcription methodology, an assumption is
made that the presence of the videographer or camera
does not influence the child's behavior. This
assumption may result in minimal biases introduced
when filming newborns, or when the camera and
videographer are not visible to the child. However, if
the children being studied are older than newborns and
can see the camera or videographer, biases may be
introduced. Ferguson et al. (2006) described
apprehension caused by videotaping and described
situations where a child's awareness of the videotaping
crew caused "play-acting" to occur, or parents
indicated that the child was behaving differently
during the taping session. Another possible source of
measurement error may be introduced when children's
movements or positions cause their mouthing not to be
captured by the camera. Data transcription errors can
bias results in either the negative or positive direction.
Finally, measurement error can occur if situations arise
in which care givers are absent during videotaping and
researchers must stop videotaping and intervene to
prevent risky behaviors (Zartarian et al., 1995).
Survey response studies rely on responses to questions
about a child's mouthing behavior posed to parents or
care givers. Measurement errors from these studies
could occur for a number of different reasons,
including language/dialect differences between
interviewers and respondents, question wording
problems and lack of definitions for terms used in
questions, differences in respondents' interpretation of
questions, and recall/memory effects.
Some researchers express mouthing behavior
as the frequency of occurrence (e.g., contacts per hour
or contacts per minute). Others describe the duration
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of specific mouthing events, expressed in units of
seconds or minutes. This handbook does not address
issues related to contaminant transfer from thumbs,
fingers, or objects or surfaces, into the mouth, and
subsequent ingestion. The recommendations for
mouthing frequency and duration are provided in
Section 4.2, along with a summary of the confidence
ratings for these recommendations. The recommended
values are based on key studies identified by U. S. EPA
for this factor. Although some studies in sections 4.3.1
and 4.4.1 are classified as key, they were not directly
used to provide the recommendations. They are
included as key because they were used by Xue et al.,
2007 in a meta analysis, which is the primary source of
the recommendations provided in this chapter for
hand-to-mouth frequency. Following the
recommendations, key and relevant studies on
mouthing frequency (section 4.3) and duration (section
4.4) are summarized and the methodologies used in the
key and relevant studies are described. Information on
the prevalence of mouthing behavior is presented in
Section 4.5.
studies. Xue et al. 2007, provided data for the age
groups of interest to U. S. EPA and categorized the data
according to indoor and outdoor contacts. The
recommendations for frequency of object-to-mouth
contact are based on data from Reed et al., (1999),
Freeman et al., (2001), Tulve et al., (2002), AuYeung
et al., (2004), and Black et al., 2005.
Recommendations for duration of object-to-mouth are
based on data from Juberg et al., (2001) and Greene,
(2002). Recommendations for hand-to-mouth duration
are not provided since those estimates may not be
relevant to environmental exposures. Table 4-2
presents the confidence ratings for the recommended
values. The overall confidence rating is low for both
frequency and duration of hand-to-mouth and object-
to-mouth.
4.2 RECOMMENDATIONS
The key studies described in Section 4.3 and
Section 4.4 were used to develop recommended values
for mouthing frequency and duration, respectively,
among children. In several cases, key studies pre-
dated the recommendations on age groups in U.S.
EPA's Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants U.S. EPA, 2005), and
were performed on groups of children of varying ages.
For cases in which age groups of children in the key
studies did not correspond exactly to U.S. EPA's
recommended age groups, the closest age group was
used.
Table 4-1 shows recommended mouthing
frequencies, expressed in units of contacts per hour,
between either any part of the hand (including fingers
and thumbs) and the mouth, or between an object or
surface and the mouth. The recommended hand-to-
mouth frequencies are based on data from Xue et al.
(2007). Xue et al. (2007) conducted a secondary
analysis of data from several of the studies summarized
in this chapter, as well as data from unpublished
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Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration
Age Group
Hand-to-Mouth
Indoor Frequency (contacts/hour)
Outdoor Frequency (contacts/hour)
Source
Mean
95th Percentiile
Mean
95th Percentile
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
28
19
20
13
15
7
65
52
63
37
54
21
15
14
5
9
3
47
42
20
36
12
Xue et al., 2007
Object-to-mouth
Mean Frequency (contacts/hour)
95th Percentile Frequency (contacts/hour)
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
20"
20b
10°
10C
1"
Reed et al., 1999; Freeman et
al., 2001; Tulve etal., 2002;
AuYeung et al., 2004; and
Black etal., 2005.
Mean Duration (minutes/hour)
95th Percentile Duration (minutes/hour)
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
8
138
26f
26f
22
16s
Juberg etal., 2001 and
Greene, 2002.
Mean calculated from Black et al., 2005 (7 to 12 months).
Mean calculated from Tulve et al., 2002 (• 24 months), AuYeung et al., 2004 (• 24 months), and Black et al., 2005 (1 and 2 years).
Mean calculated from Reed et al., 1999 (2 to 6 years), Freeman et al., 2001 (3 to 4 years and 5 to 6 years), AuYeung et al., 2004 (2 to
6 years), and Black et al., 2005 (37 to 53 months).
Mean calculated from Freeman et al., 2001 (7 to 8 years and lOto 12years).
Mean calculated from Juberg et al., 2001 (0 to 18 months) and Greene, 2002 (3 to 12 months).
Calculated 95th percentile from Greene, 2002 (3 to 12 months).
Mean calculated from Juberg, et al., 2001 (19 to 36 months) and Greene, 2002 (24 to 36 months).
Calculated 95th percentile from Greene, 2002 (24 to 36 months).
= No data.
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\A
tZ^B Chapter 4 - Non-dietary Ingestion Factor.
Table 4-2. Confidence in Recommendations for Mouthing Frequency and Duration
General Assessment Factors Rationale Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertinty
Variability in Population
Description of Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of
Studies
Overall rating
Low
The approaches for data collection and analysis used were adequate to provide
estimates of children's mouthing frequencies and durations. Sample sizes were
very small relative to the population of interest. Almost all key studies
published primary data; in cases where secondary data were used, U. S. EPA
judged the secondary data to be of suitable utility for the purposes for
developing recommendations.
Bias in either direction likely exists in both frequency and duration estimates;
the magnitude of bias is unknown.
Low
Key studies for older children focused on mouthing behavior while the infant
studies were designed to research developmental issues.
Most key studies were of samples of U.S. children, but due to the small sample
sizes and small number of locations under study, the study subjects may not be
representative of the overall U.S. child population.
The studies were conducted over a wide range of dates. However, the currency
of the data are not expected to affect mouthing behavior recommendations.
Extremely short data collection periods may not represent behaviors over longer
time periods.
Low
The journal articles are in the public domain, but in many cases, primary data
were unavailable.
Data collection methodologies were capable of providing results that were
reproducible within a certain range, when compared with results obtained using
alternate data collection techniques (e.g., Smith and Norris, 2003).
Several of the key studies applied and documented quality assurance/quality
control measures.
Low
The key studies characterized inter- individual variability to a limited extent,
and did not characterize intra-individual variability over diurnal or longer term
time frames.
The study authors typically did not attempt to quantify uncertainties inherent in
data collection methodology (such as the influence of observers on behavior),
although some described these uncertainties qualitatively. The study authors
typically did attempt to quantify uncertainties in data analysis methodoloogies
(if video-transcription methods were used). Uncertainties arising from short
data collection periods typically were unaddressed either qualitatively or
quantitatively.
Medium
All key studies appear in peer review journals.
Several key studies were available for both frequency and duration, but data
were not available for all age groups. The results of studies from different
researchers are generally in agreement.
Low
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4.3 NON-DIETARY INGESTION
MOUTHING FREQUENCY STUDIES
4.3.1 Key Studies of Mouthing Frequency
4.3.1.1 Zartarian et al.,1997a - Quantifying
Videotaped Activity Patterns: Video
Translation Software and Training
Technologies/Zartarian et al., 1997b -
Quantified Dermal Activity Data From a
Four-Child Pilot Field Study/Zartarian et
al., 1998 - Quantified Mouthing Activity
Data From a Four-Child Pilot Field Study
Zartarian et al. (1991 a, 1997b, 1998)
conducted a pilot study of the video-transcription
methodology to investigate the applicability of using
videotaping for gathering information related to
children's activities, dermal exposures and mouthing
behaviors. The researchers had conducted studies
using the real-time hand recording methodology,
resulting in poor inter-observer reliability and observer
fatigue when attempted for long periods of time,
prompting the investigation into using videotaping
with transcription of the children's activities at a point
in time after the observations (videotaping) occurred.
Four Mexican-American farm worker
children in the Salinas Valley of California each were
videotaped with a hand-held videocamera during their
waking hours, excluding time spent in the bathroom,
over one day in September 1993. The boys were 2
years 10 months old and 3 years, 9 months old; the
girls were 2 years 5 months old and 4 years 2 months
old. Time of videotaping was 6.0 hours for the
younger girl, 6.6 hours for the older girl, 8.4 hours for
the younger boy and 10.1 hours for the older boy. The
videotaping gathered information on detailed micro-
activity patterns of children to be used to evaluate
software for videotaped activities and translation
training methods. The researchers reported measures
taken to assess inter-observer reliability and several
problems with the video-transcription process.
The hourly data showed that non-dietary
object mouthing occurred in 30 of the 31 hours of tape
time, with one child eating during the hour in which
no non-dietary object mouthing occurred. Average
object to mouth contacts for the four children were
reported to be 9 contacts per hour, with the average per
child ranging from 1 to 19 contacts per hour (Zartarian
et al., 1997a). Objects mouthed included
bedding/towels, clothes, dirt, grass/vegetation, hard
surfaces, hard toys, paper/card, plush toy, and skin
(Zartarian et al., 1997a). Average hand to mouth
contacts for the four children were reported to be 13
contacts per hour (averaging the sum of left hand and
right hand to mouth contacts and averaging across
children, from Zartarian et al., 1997b), with the
average per child ranging from 9 to 19 contacts per
hour.
This study's primary purpose was to develop
and evaluate the video-transcription methodology; a
secondary purpose was collection of mouthing
behavior data. The sample of children studied was
very small and not likely to be representative of the
national population. As with other video-transcription
studies, the presence of non-family-member
videographers and a video camera may have
influenced the children's behavior.
4.3.1.2 Reed et al., 1999 - Quantification of
Children's Hand and Mouthing Activities
Through a Videotaping Methodology
In this study, Reed et al. (1999) used a video-
transcription methodology to quantify the frequency
and type of children's hand and mouth contacts, as
well as a survey response methodology, and compared
the videotaped behaviors with parents' perceptions of
those behaviors. Twenty children ages 3 to 6 years old
selected randomly at a day care center in New
Brunswick, New Jersey, and ten children ages 2 to 5
years old at residences in Newark and Jersey City, New
Jersey who were not selected randomly, were studied
(gender not specified). For the video-transcription
methodology, inter-observer reliability tests were
performed during observer training and at four points
during the two years of the study. The researchers
compared the results of videotaping the ten children in
the residences with their parents' reports of the
children's daily activities. Mouthing behaviors studied
included hand to mouth and hand bringing object to
mouth.
The video-transcription mouthing contact
frequency results are presented in Table 4-3. The
authors analyzed parents' responses on frequencies of
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their children's mouthing behaviors and compared
those responses with the children's videotaped
behaviors, which revealed certain discrepancies.
Parents' reported hand to mouth contact of "almost
never" corresponded to overall somewhat lower
videotaped hand to mouth frequencies than those of
children whose parents reported "sometimes," but
there was little correspondence between parents'
reports of object to mouth frequency and videotaped
behavior.
The advantages of this study were that it
compared the results of video-transcription with the
survey response methodology results, and described
quality assurance steps taken to assure reliability of
transcribed videotape data. However, only a small
number of children were studied, some were not
selected for observation randomly, and the sample of
children studied may not be representative of either the
locations studied or the national population. Due to
the children's ages, the presence of unfamiliar persons
following the children with a video camera may
influence the video-transcription results. The parents'
survey responses may also be influenced by
recall/memory effects and other limitations of survey
methodologies.
4.3.1.3 Freeman et al., 2001 - Quantitative Analysis
of Children's Microactivity Patterns: The
Minnesota Children's Pesticide Exposure
Study
Freeman et al. (2001) conducted a survey
response and video-transcription study of some of the
respondents in a phased study of children's pesticide
exposures in the summer and early fall of 1997. A
probability-based sample of 168 families with children
ages 3 to < 14 years old in urban (Minneapolis/St. Paul)
and non-urban (Rice and Goodhue Counties) areas of
Minnesota answered questions about children's
mouthing of paint chips, food-eating without utensils,
eating of food dropped on the floor, mouthing of non-
food items, and mouthing of thumbs/fingers. For the
survey response portion of the study, parents provided
the responses for children ages 3 and 4 years, and
collaborated with or assisted older children with their
responses. Of the 168 families responding to the
survey, 102 were available, selected, and agreed to
measurements of pesticide exposure. Of these 102
families, 19 agreed to videotaping of the study
children's activities for a period of four consecutive
hours.
Based on the survey responses for 168
children, the 3 year olds had significantly more
positive responses for all reported behavior compared
to the other age groups. The authors stated that they
did not know whether parent reporting of 3 year olds'
behavior influenced the responses given. Table 4-4
shows the percent of children, grouped by age, who
were reported to exhibit non-food related mouthing
behaviors. Table 4-5 presents the mean and median
number of mouthing contacts by age for the 19
videotaped children. Among the four age categories of
these children, object to mouth activities were
significantly greater for the 3 and 4 year olds than any
other age group, with a median of 3 and a mean of 6
contacts per hour (P = 0.002, Kruskal Wallis test
comparison across four age groups). Hand to mouth
contacts had a median of 3.5 and mean of 4 contacts
per hour for the three 3 and 4 year olds observed,
median of 2.5 and mean of 8 contacts per hour for the
seven 5 and 6 year olds observed, median of 3 and
mean of 5 contacts per hour for the four 7 and 8 year
olds observed, and median of 2 and mean of 4 for the
five 10, 11 and 12 year olds observed. Gender
differences were observed for some of the activities,
with boys spending significantly more time outdoors
than girls. Hand to mouth and object to mouth
activities were less frequent outdoors than indoors for
both boys and girls.
For the 19 children in the video-transcription
portion of the study, inter-observer reliability checks
and quality control checks were performed on
randomly sampled tapes. For four children's tapes,
comparison of the manual video-transcription with a
computerized transcription method (Zartarian et al.,
1995) was also performed; no significant differences
were found in the frequency of events recorded using
the two techniques. The frequency of six behaviors
(hand to mouth, hand to object, object to mouth, hand
to smooth surface, hand to textured surface, and hand
to clothing) was recorded. The amount of time each
child spent indoors, outdoors, in contact with soil or
grass, and whether the child was barefoot was also
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recorded. For the four children whose tapes were
analyzed with the computerized transcription method,
which calculates event durations, the authors stated
that most hand to mouth and object to mouth activities
were observed during periods of lower physical
activity, such as television viewing.
An advantage to this study is that it included
results from two separate methodologies, and included
quality assurance steps taken to assure reliability of
transcribed videotape data. However, the children in
this study may not be representative of all children in
the U.S. Variation in who provided the survey
responses (sometimes parents only, sometimes children
with parents) may have influenced the responses given.
Children studied using the video-transcription
methodology were not chosen randomly from the
survey response group. The presence of unfamiliar
persons following the children with a video camera
may have influenced the video-transcription
methodology results.
4.3.1.4 Tulve et al., 2002 - Frequency of Mouthing
Behavior in Young Children
Tulve et al. (2002) coded the unpublished
Davis et al. (1995) data for location (indoor and
outdoor) and activity type (quiet or active) and
analyzed the subset of the data that consisted of indoor
mouthing behavior during quiet activity (72 children,
ranging in age from 11 to 60 months). A total of 186
15-minute observation periods were included in the
study, with the number of observation periods per child
ranging from 1 to 6.
Results of the data analyses indicated that
there was no association between mouthing frequency
and gender, but a clear association between mouthing
frequency and age was observed. The analysis
indicated that children • 24 months had the highest
frequency of mouthing behavior (81 events/hour) and
children >24 months had the lowest (42 events/hour)
(Table 4-6). Both groups of children were observed to
mouth toys and hands more frequently than household
surfaces or body parts other than hands.
An advantage of this study is that the
randomized design may mean that the children studied
were relatively representative of young children living
in the study area, although they may not be
representative of the U.S. population. Due to the ages
of the children studied, the observers' use of
headphones and manual recording of mouthing
behavior on observation sheets may have influenced
the children's behavior.
4.3.1.5 Black et al., 2005 - Children's Mouthing
and Food-Handling Behavior in an
Agricultural Community on the U.S./Mexico
Border
Black et al. (2005) studied mouthing behavior
of children in a Mexican-American community along
the Rio Grande River in Texas, in the spring and
summer of 2000, using a survey response and a video-
transcription methodology. A companion study of this
community (Shalat et al., 2003) identified 870
occupied households during the April 2000 U.S.
census and contacted 643 of these via in-person
interview to determine presence of children under the
age of 3 years. Of the 643 contacted, 91 had at least
one child under the age of 3 years (Shalat et al., 2003).
Of these 91 households, the mouthing and food-
handling behavior of 52 children (26 boys and 26
girls) from 29 homes was videotaped, and the
children's parents answered questions about children's
hygiene, mouthing and food-handling activities (Black
et al., 2005). The study was of children ages 7 to 53
months, grouped into four age categories: infants (7 to
12 months), 1 year olds (13 to 24 months), 2 year olds
(25 to 36 months), and preschoolers (37 to 53 months).
The survey asked questions about children's
ages, genders, reported hand-washing, mouthing and
food-handling behavior (N=52), and activities (N=49).
Parental reports of thumb/finger placement in the
mouth showed decreases with age. The researchers
attempted to videotape each child for four hours. The
children were followed by the videographers through
the house and yard, except for times when they were
napping or using the bathroom. Virtual Timing
Device™ software was used to analyze the videotapes.
Based on the results of videotaping, most
of the children (49 of 52) spent the majority of their
time indoors. Of the 39 children who spent time
both indoors and outdoors, all three behaviors (hand
to mouth, object to mouth and food handling) were more
frequent and longer while the child was indoors. Hand
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to mouth activity was recorded during videotaping for
all but one child, a 30 month old girl.
For the four age groups, the mean hourly
hand to mouth frequency ranged from 11.9 (2 year
olds) to 22.1 (preschoolers), and the mean hourly
object to mouth frequency ranged from 7.8 (2 year
olds) to 24.4 (infants). No significant linear trends
were seen with age or gender for hand to mouth hourly
frequency. A significant linear trend was observed for
hourly object to mouth frequency, which decreased as
age increased (adjusted R2 = 0.179; P = 0.003).
Results of this study are shown in Table 4-7.
One advantage of this study is that it
compared survey responses with videotaped
information on mouthing behavior. A limitation is
that the sample was fairly small and was from a
limited area (mid-Rio Grande Valley) and is not likely
to be representative of the national population. Due to
the children's ages, the presence of unfamiliar persons
following the children with a video camera may have
influenced the video-transcription methodology results.
4.3.1.6 Xue et al, 2007 - A Meta-analysis of
Children 'sHand-to-Mouth Frequency Data
for Estimating Nondietary Ingestion
Exposure
Xue et al. (2007) gathered hand-to-mouth
frequency data from 9 available studies representing
429 subjects and more than 2,000 hours of behavior
observation. The studies used in this analysis included
several of the studies summarized in this chapter
(Zartarian et al. ,1998; Reed et al., 1999; Freeman et
al., 2001; Greene, 2002; Tulve et al., 2002; and Black
et al., 2005), as well as several other sets of
unpublished data. These data were used to conduct a
meta-analysis to study differences in hand-to-mouth
behavior. The purpose of the analysis was to:
1) examine differences across studies by age
(using the new U.S. EPA recommended age
groupings (U.S. EPA, 2005)), gender, and
indoor/outdoor location;
2) fit variability distributions to the available
hand-to-mouth frequency data for use in one
dimensional Monte Carlo exposure
assessments;
3) fit uncertainty distributions to the available
hand-to-mouth frequency data for use in two
dimensional Monte Carlo exposure
assessments; and
4) assess hand-to-mouth frequency data needs
using the new U.S. EPA recommended age
groupings (U.S. EPA, 2005).
The data were sorted into age groupings.
Visual inspection of the data and statistical methods
(method of moments and maximum likelihood
estimation) were used, and goodness-of-fit tests were
applied to verify the selection among lognormal,
Weibull, and normal distributions (Xue et al., 2007).
Analyses to study inter- and intra- individual
variability of indoor and outdoor hand to mouth
frequency were conducted. There were 894 hours of
behavior observation data for the 429 children, ages
0.3 to 12 years, across all available studies. It was
found that age and location (indoor vs. outdoor) were
important factors contributing to hand to mouth
frequency, but study and gender were not (Xue et al.,
2007). Distributions of hand to mouth frequencies
were developed for both indoor and outdoor activities.
Distributions are presented in Table 4-8 for indoor
settings and Table 4-9 for outdoor settings. Hand to
mouth frequencies decreased for both indoor and
outdoor activity as age increased, and were higher
indoors than outdoors for all age groups (Xue et al.,
2007).
A strength of this study is that it is the first
effort to fit hand to mouth distributions using U.S.
EPA's recommended age groups using available data
on mouthing behavior from studies using different
methodologies, of children in different locations.
Limitations of the studies used in this meta-analysis
apply to the results from the meta-analysis as well; the
uncertainty analysis in this study does not account for
uncertainties arising out of differences in approaches
used in the various studies used in the meta-analysis.
4.3.2 Relevant Studies of Mouthing Frequency
4.3.2.1 Davis et al., 1995 - Soil Ingestion in
Children with Pica: Final Report
In 1992, under a Cooperative Agreement with
U.S. EPA, the Fred Hutchinson Cancer Research
Center conducted a survey response and real-time hand
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recording study of mouthing behavior data. The study
included 92 children (46 males, 46 females) ranging in
age from <12 months to 60 months, from Richland,
Kennewick, and Pasco, Washington. The children
were selected randomly based on date of birth through
a combination of birth certificate records and random
digit dialing of residential telephone numbers. For
each child, data were collected during a seven day
period in January to April, 1992. Eligibility included
residence within the city limits, residence duration >1
month, and at least one parent or guardian who spoke
English. Most of the adults who responded to the
survey reported their marital status as being married
(90 percent), their race as Caucasian (89 percent), their
household income in the >$30,000 range (56 percent)
or their housing status as single-family home
occupants (69 percent).
The survey asked questions about thumb-
sucking and frequency questions about pacifier use,
placing fingers, hands and feet in the mouth, and
mouthing of furniture, railings, window sills, floor,
dirt, sand, grass, rocks, mud, clothes, toys, crayons,
pens, and other items. Table 4-10 shows the survey
responses for the 92 study children. For most of the
children in the study, the mouthing behavior real-time
hand recording data were collected simultaneously by
parents and by trained observers who described and
quantified the mouthing behavior of the children in
their home environment. The observers recorded
mouth and tongue contacts with hands, other body
parts, natural objects, surfaces, and toys every 15
seconds during 15-minute observation periods spread
over 4 days. Parents and trained observers wore
headphones that indicated elapsed time (Davis et al.,
1995). If all attempted observation periods were
successful, each child would have a total of 16 15-
minute observation periods with 6015 -second intervals
per 15-minute observation period, or 960 15-second
intervals in all. The number of successful intervals of
observation ranged from 0 to 840 per child.
Comparisons of the inter-observer reliability between
the trained observers and parents showed "a high
degree of correlation between the overall degree of
both mouth and tongue activity recorded by parents
and observers. For total mouth activity, there was a
significant correlation between the rankings obtained
according to parents and observers, and parents were
able to identify the same individuals as observers as
being most and least oral in 60 percent of the cases."
One advantage of this study is the
simultaneous observations by both parents and trained
observers that allows comparisons to be made
regarding the consistency of the recorded observations.
The random nature in which the population was
selected may provide a representative population of the
study area, within certain limitations, but not of the
national population. Simultaneous collection of food,
medication, fecal, and urine samples that occurred as
part of the overall study (not described in this
summary) may have contributed a degree of deviation
from normal routines within the households during the
7 days of data collection and may have influenced
children's usual behaviors. Wearing of headphones by
parents and trained observers during mouthing
observations, presence of non-family-member
observers, and parents' roles as observers as well as
care givers may also have influenced the results; the
authors state "Having the child play naturally while
being observed was challenging. Usually the first day
of observation was the most difficult in this respect,
and by the third or fourth day of observation the child
generally paid little attention to the observers."
4.3.2.2 Lew and Butterworth, 1997 - The
Development of Hand-Mouth Coordination
In 2- to 5-Month-Old Infants: Similarities
With Reaching and Grasping
Lew and Butterworth (1997) studied 14
mostly first-born infants (10 males, 4 females) in
Stirling, United Kingdom, in 1990 using a video-
transcription methodology. Attempts were made to
study each infant within a week of the infant's 2-
month, 3-month, 4-month and 5-month birthdays.
After becoming accustomed to the testing laboratory,
and with their mothers present, infants were placed in
semi-reclining seats and filmed during an
experimental protocol in which researchers placed
various objects into the infants' hands. Infants were
observed for two baseline periods of 2 minutes each.
The researchers coded all contacts to the face and
mouth that occurred during baseline periods (prior to
and after the object handling period) as well as
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contacts occurring during the object handling period.
Hand to mouth contacts included contacts that landed
directly in or on the mouth as well as those in which
the hand landed on the face first and then moved to the
mouth. The researchers assessed inter-observer
agreement using a rater not involved with the study,
for a random proportion (approximately 10 percent) of
the movements documented during the object handling
period, and reported inter-observer agreement of 0.90
using Cohen's kappa (a measure of the agreement
between two raters) for the location of contacts. The
frequency of contacts ranged between 0 and 1 contacts
per minute.
The advantages of this study were that use of
video cameras could be expected to have minimal
impact on infant behavior for infants of these ages, and
the researchers performed tests of inter-observer
reliability. A disadvantage is that the study included
baseline observation periods of only 2 minutes'
duration, during which spontaneous hand to mouth
movements could be observed. The extent to which
these infants' behavior is representative of other
infants of these ages is unknown.
4.3.2.3 Tudella et al., 2000 - The Effect of Oral-
Gustatory, Tactile-Bucal, and Tactile-
Manual Stimulation on the Behavior of the
Hands in Newborns
Tudella et al. (2000) studied the frequency of
hand to mouth contact, as well as other behaviors, in
24 full-term Brazilian newborns (10 to 14 days old)
using a video-transcription methodology. Infants were
in an alert state, in their homes in silent and previously
heated rooms in a supine position and had been fed
between 1 and 1 1/2 hours before testing. Infants were
studied for a four minute baseline period without
stimuli before experimental stimuli were administered.
Results from the four minute baseline period, without
stimuli, indicated that the mean frequency of hand to
mouth contact (defined as right hand or left hand
touching the lips or entering the buccal cavity, either
with or without rhythmic jaw movements) was almost
3 right hand contacts and slightly more than 1.5 left
hand contacts, for a total hand to mouth contact
frequency of about 4 contacts in the four minute
period. The researchers performed inter-observer
reliability tests on the videotape data and reported an
inter-coder Index of Concordance of 93 percent.
The advantages of this study were that use of
video cameras could be expected to have virtually no
impact on newborns' behavior, and inter-observer
reliability tests were performed. However, the study
data may not represent newborn hand to mouth contact
during non-alert periods such as sleep. The extent to
which these infants' behavior is representative of other
full-term 10 to 14 day old infants' behavior is
unknown.
4.3.2.4 AuYeung et al, 2004 - Young Children's
Mouthing Behavior: An Observational
Study via Videotaping in a Primarily
Outdoor Residential Setting
AuYeung et al. (2004) used a video-
transcription methodology to study a group of 38
children (20 females and 18 males; ages 1 to 6 years),
37 of whom were selected randomly via a telephone
screening survey of a 300 to 400 square mile portion of
the San Francisco, California peninsula, along with
one child selected by convenience due to time
constraints. Families who lived in a residence with a
lawn and whose annual income was >$35,000 were
asked to participate. Videotaping took place between
August 1998 and May 1999 for approximately two
hours per child. Videotaping by one researcher was
supplemented with field notes taken by a second
researcher who was also present during taping. Most
of the videotaping took place during outdoor play,
however, data were included for several children (one
child <2 years old and 8 children >2 years old) who
had more than 15 minutes of indoor play during their
videotaping sessions.
The videotapes were translated into ASCII
computer files using VirtualTimingDevice™ software
described in Zartarian et al. (1997a). Both frequency
and duration (see Section 4.4.2.5 of this Chapter) were
analyzed. Between 5 and 10 percent of the data files
translated were randomly chosen for quality control
checks for inter-observer agreement. Ferguson et al.
(2006) described quality control aspects of the study in
detail.
For analysis, the mouthing contacts were
divided into indoor and outdoor locations, and 16
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object/surface categories. Mouthing frequency was
analyzed by age and gender separately, and in
combination. Mouthing contacts were defined as
contact with the lips, inside of the mouth, and/or the
tongue; dietary contacts were ignored. Mouthing
frequencies for indoor locations are shown in Table 4-
11. For the one child observed that was • 24 months of
age, the total mouthing frequency was 84.8
contacts/hour; for children >24 months, the median
indoor mouthing frequency was 19.5 contacts/hour.
Outdoor median mouthing frequencies (Table 4-12)
were very similar for children • 24 months of age (13.9
contacts/hour) and >24 months (14.6 contacts/hour).
Nonparametric tests, such as the Wilcoxon
rank sum test were used for the data analyses. Both age
and gender were found to be associated with
differences in mouthing behavior. Girls had
significantly higher frequencies of mouthing contacts
with the hands and non-dietary objects than boys (p =
0.01 and;? = 0.008, respectively).
This study provides distributions of outdoor
mouthing frequencies with a variety of objects and
surfaces. Although indoor mouthing data were also
included in this study, the results were based on a
small number of children (N=9) and a limited amount
of indoor play. The sample of children may be
representative of certain socioeconomic strata in the
study area, but is not likely to be representative of the
national population. Due to the children's ages, the
presence of unfamiliar persons following the children
with a video camera may have influenced the video-
transcription methodology results.
4.3.2.5 Ko et al, 2007 - Relationships of Video
Assessments of Touching and Mouthing
Behaviors During Outdoor Play in Urban
Residential Yards to Parental Perceptions of
Child Behaviors and Blood Lead Levels
Ko et al. (2007) compared parent survey
responses with results from a video-transcription study
of children's mouthing behavior in outdoor settings, as
part of a study of relationships between children's
mouthing behavior and other variables with blood lead
levels. A convenience sample of 37 children (51
percent males, 49 percent females) 14 to 69 months old
was recruited via an urban health center and direct
contacts in the surrounding area, apparently in
Chicago, Illinois. Participating children were
primarily Hispanic (89 percent). The mouth area was
defined as within 1 inch of the mouth, including the
lips. Items passing beyond the lips were defined as in
the mouth. Placement of an object or food item in the
mouth along with part of the hand was counted as both
hand and food or object in mouth. Mouthing behaviors
included hand-to-mouth area both with and not with
food, hand- in-mouth with or without food, and object-
in-mouth including food, drinks, toys or other objects.
Survey responses for the 37 children who
were also videotaped included parents reporting
children's inserting hand, toys or objects in mouth
when playing outside, and inserting dirt, stones or
sticks in mouth. Video-transcription results of outdoor
play for these 37 children indicated 0 to 27 hand-in-
mouth, and 3 to 69 object-in-mouth touches per hour
for the 13 children reported to frequently insert hand,
toys or objects in mouth when playing outside; 0 to 67
hand in mouth, and 7 to 40 object-in-mouth touches
per hour for the 10 children reported to "sometimes"
perform this behavior; 0 to 30 hand-in-mouth, and 0 to
125 object in mouth touches per hour for the 12
children reported to "hardly ever" perform this
behavior, and 1 to 8 hand-in-mouth, and 3 to 6 object-
in-mouth touches per hour for the 2 children reported
to "never" perform this behavior.
Videotaping was attempted for two hours per
child over two or more play sessions, with
videographers trying to avoid interacting with the
children. Children played with their usual toys and
partners, and no instructions were given to parents
regarding their supervision of the children's play. The
authors stated that during some portion of the
videotape time, children's hands and mouths were out
of camera view. Videotape transcription was
performed manually, according to a modified version
of the protocol used in the Reed et al. (1999) study.
Inter-observer reliability between three video-
transcribers was checked with seven 30 minute video
segments.
One strength of this study is its comparison of
survey responses with results from the video-
transcription methodology. A limitation is that the
non-randomly selected sample of children studied is
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unlikely to be representative of the national population.
Comparing results from this study with results from
other video-transcription studies may be problematic
due to inclusion of food handling with hand to mouth
and object to mouth frequency counts. Due to the
children's ages, their behavior may have differed from
normal patterns due to the presence of strangers who
videotaped them.
4.4 NON-DIETARY INGESTION
MOUTHING DURATION STUDIES
4.4.1 Key Mouthing Duration Studies
4.4.1.1 Juberg et al., 2001 - An Observational Study
of Object Mouthing Behavior by Young
Children
Juberg et al. (2001) studied 385 children ages
0 to 36 months in western New York state, with
parents collecting real-time hand-recording mouthing
behavior data, primarily in children's own home
environments. The study consisted of an initial pilot
study conducted in February 1998, a second phase
conducted in April 1998, and a third phase conducted
at an unspecified later time. The study's sample was
drawn from families identified in a child play research
center database or whose children attended a child care
facility in the same general area; some geographic
variation within the local area was obtained by
selecting families with different zip codes in the
different study phases. The pilot phase had 30
children who participated out of 150 surveys
distributed; the second phase had 187 children out of
approximately 300 surveys distributed, and the third
phase had 168 participants out of 300 surveys
distributed.
Parents were asked to observe their child's
mouthing of objects only; hand to mouth behavior was
not included. Data were collected on a single day
(pilot and second phases) or five days (third phase);
parents recorded the insertion of objects into the mouth
by noting the "time in" and "time out" and the
researchers summed the recorded data to tabulate total
times spent mouthing the various objects during the
day(s) of observation. Thus, the study data were
presented as minutes per day of object mouthing time.
Mouthed items were classified as pacifiers, teethers,
plastic toys, or other objects.
The results of the combined pilot and second
phase II data are shown in Table 4-13. For both age
groups, mouthing time for pacifiers greatly exceeded
mouthing time for non-pacifiers, with the difference
more acute for the older age group than for the
younger age group. Histograms of the observed data
show a peak in the low end of the distribution (0 to 100
minutes per day) and a rapid decline at longer
durations.
A third phase of the study focused on children
between the ages of 3 and 18 months and included
only non-pacifier objects. Subjects were observed for
5 non-consecutive days over a 2 month period. A total
of 168 participants returned surveys for at least one
day, providing a total of 793 person-days of data. The
data yielded a mean non-pacifier object mouthing
duration of 36 minutes per day; the mean was the same
when calculated on the basis of 793 person-days of
data as on the basis of 168 daily average mouthing
times.
One advantage of this study is the large
sample size (385 children); however, the children
apparently were not selected randomly, although some
effort was made to obtain local geographic variation
among study participants. There is no description of
the socioeconomic status or racial and ethnic identities
of the study participants. The authors do not describe
the methodology (such as stopwatches, analog or
digital clocks, or guesses) parents used to record
mouthing event durations. The authors stated that
using mouthing event duration units of minutes, rather
than seconds, may have yielded observations rounded
to the nearest minute.
4.4.1.2 Greene, 2002 - A Mouthing Observation
Study of Children Under Six Years of Age
The U.S. Consumer Product Safety
Commission (CPSC) conducted a survey response and
real-time hand recording study between December
1999 and February 2001 to quantify the cumulative
time per day that young children spend awake, not
eating, and mouthing objects. "Mouthing" was
defined as sucking, chewing, or otherwise putting an
object on his/her lips or into his/her mouth.
Participants were recruited via a random digit dialing
telephone survey in urban and nearby rural areas of
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Houston, Texas and Chicago, Illinois. Of the 115,289
households surveyed, 1,745 households had a child
under the age of 6 years and were willing to
participate. In the initial phase of the study,
491children ages 3 to 81 months participated. Parents
were instructed to use watches with second hands, or
count seconds to estimate mouthing event durations.
Parents also were to record mouthing frequency and
types of objects mouthed. Parents collected data in
four separate, non-consecutive 15- minute observation
periods. Initially, parents were called back by the
researchers and asked to provide their data over the
telephone. Of the 491 children, 43 children (8.8
percent) had at least one 15-minute observation period
with mouthing event durations recorded as exceeding
15 minutes. Due to this data quality problem, the
researchers excluded the parent observation data from
further analysis.
In a second phase, trained observers used
stopwatches to record the mouthing behaviors and
mouthing event durations of the subset of 109 of these
children ages 3 to 36 months, and an additional 60
children (total in second phase, 169), on two hours of
each of two days. The observations were done at
different times of the day at the child's home and/or
child care facility. Table 4-14 shows the prevalence of
observed mouthing among the 169 children in the
second phase. All children were observed to mouth
during the four hours of observation time; 99 percent
mouthed the category defined as "anatomy." Pacifiers
were mouthed by 27 percent in an age-declining
pattern ranging from 47 percent of children less than
12 months old to 10 percent of the 2 to <3 year olds.
Table 4-15 provides the average mouthing
time by object category and age in minutes per hour.
The average mouthing time for all objects ranged from
5.3 to 10.5 minutes per hour, with the highest
mouthing time corresponding to children <1 year of
age and the lowest to the 2 to <3 years of age category.
Among the objects mouthed, pacifiers represented
about one third of the total mouthing time, with 3.4
minutes per hour for the youngest children, 2.6
minutes per hour for the children between 1 and 2
years and 1.8 minutes per hour for children 2 to <3
years old. The next largest single item category was
anatomy. In this category, children under 1 year of
age spent 2.4 minutes per hour mouthing fingers and
thumbs; this behavior declined with age to 1.2 minutes
per hour for children 2 to <3 years old.
Of the 169 children in the second phase, there
were usable data on the time awake and not eating (or
"exposure time") for only 109; data for the remaining
60 children were missing. Thus, in order to develop
extrapolated estimates of daily mouthing time, from
the 2 hours of observation per day for two days, for the
109 children, the researchers developed a statistical
model that accounted for the children's demographic
characteristics, in order to estimate exposure times for
the 60 children for whom exposure time data were
missing, and then computed statistics for the
extrapolated daily mouthing times for all 169 children,
using a "bootstrap" procedure. Using this method, the
estimated mean daily mouthing time of objects other
than pacifiers ranged from 37 minutes/day to 70
minutes/day with the lowest number corresponding to
the 2 to <3 year old children and the largest number
corresponding to the 3 to < 12 month old children.
The 551 child participants were 55 percent
males, 45 percent females. The study's sample was
drawn in an attempt to duplicate the overall U.S.
demographic characteristics with respect to race,
ethnicity, socioeconomic status and
urban/suburban/rural settings. The sample families'
reported annual incomes were generally higher than
those of the overall U.S. population.
This study's strength was that it consisted of
a randomly selected sample of children from both
urban and non-urban areas in two different geographic
areas within the U.S. However, the observers'
presence and use of a stopwatch to time mouthing
durations may have affected the children's behavior.
4.4.2 Relevant Mouthing Duration Studies
4.4.2.1 Barr et al, 1994 - Effects of Intra-Oral
Sucrose on Crying, Mouthing and Hand-
Mouth Contact in Newborn and Six Week
Old Infants
Barr et al. (1994) studied hand to mouth
contact, as well as other behaviors, in 15 newborn (8
males, 7 females) and 15 five to seven week old (8
males, 7 females) full-term Canadian infants using a
video-transcription methodology. The newborns were
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2 to 3 days old, in a quiet, temperature-controlled room
at the hospital, in a supine position and had been fed
between 2 1/2 and 3 1/2 hours before testing. Barr et
al. (1994) analyzed a one minute baseline period, with
no experimental stimuli, immediately before a
sustained crying episode lasting 15 seconds. For the
newborns, reported durations of hand to mouth contact
during 10 second intervals of the one minute baseline
period were in the range of 0 to 2 percent. The five to
seven week old infants apparently were studied at
primary care pediatric facilities when they were in
bassinets inclined at an angle of 10 degrees. For these
slightly older infants, the baseline periods analyzed
were less than 20 seconds in length, but Barr et al.
(1994) reported similarly low mean percentages of the
10 second intervals (approximately 1 percent of the
time with hand to mouth contact). Hand to mouth
contact was defined as "any part of the hand touching
the lips and/or the inside of the mouth." The
researchers performed inter-observer reliability tests on
the videotape data and reported a mean inter-observer
reliability of 0.78 by Cohen's kappa (a measure of the
agreement between two raters).
The advantages of this study were that use of
video cameras could be expected to have virtually no
impact on newborns' or five to seven week old infants'
behavior, and inter-observer reliability tests were
performed. The study data did not represent newborn
or five to seven week old infant hand to mouth contact
during periods in which infants of these ages were in
a sleeping or other non-alert state, and may only
represent behavior immediately prior to a state of
distress (sustained crying episode). The extent to
which these infants' behavior is representative of other
full-term infants of these ages is unknown.
4.4.2.2 Zartarian et al., 1997a - Quantifying
Videotaped Activity Patterns: Video
Translation Software and Training
Technologies/Zartarian et al., 1997b -
Quantified Dermal Activity Data From a
Four-Child Pilot Field Study/Zartarian et
al., 1998 - Quantified Mouthing Activity
Data From a Four-Child Pilot Field Study
As described in Section 4.3.1.1, Zartarian et
al. (1997a, 1997b, 1998) conducted a pilot study of the
video-transcription methodology to investigate the
applicability of using videotaping for gathering
information related to children's activities, dermal
exposures and mouthing behaviors. The researchers
had conducted studies using the real-time hand
recording methodology, resulting in poor inter-
observer reliability and observer fatigue when
attempted for long periods of time, prompting the
investigation into using videotaping with transcription
of the children's activities at a point in time after the
observations (videotaping) occurred.
Four Mexican-American farm worker
children in the Salinas Valley of California each were
videotaped with a hand-held videocamera during their
waking hours, excluding time spent in the bathroom,
over one day in September 1993. The boys were 2
years 10 months old and 3 years, 9 months old; the
girls were 2 years 5 months old and 4 years 2 months
old. Time of videotaping was 6.0 hours for the
younger girl, 6.6 hours for the older girl, 8.4 hours for
the younger boy and 10.1 hours for the older boy. The
videotaping gathered information on detailed micro-
activity patterns of children to be used to evaluate
software for videotaped activities and translation
training methods.
The four children mouthed non-dietary
objects an average of 4.35 percent (range 1.41 to 7.67
percent) of the total observation time, excluding the
time during which the children were out of the
camera's view (Zartarian et al., 1997a). Objects
mouthed included bedding/towels, clothes, dirt,
grass/vegetation, hard surfaces, hard toys, paper/card,
plush toy, and skin (Zartarian et al., 1997a).
Frequency distributions for the four children's non-
dietary object contact durations were reported to be
similar in shape. Reported hand to mouth contact
presumably is a subset of the object to mouth contacts
described in Zartarian et al., 1997a, and is described in
Zartarian et al., 1997b. The four children mouthed
their hands an average of 2.35 percent (range 1.0 to
4.4 percent) of observation time. The researchers
reported measures taken to assess inter-observer
reliability and several problems with the video-
transcription process.
This study's primary purpose was to develop
and evaluate the video-transcription methodology; a
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secondary purpose was collection of mouthing
behavior data. The sample of children studied was
very small and not likely to be representative of the
national population. Thus, U.S. EPA did not judge it
to be suitable for consideration as a key study of
children's mouthing behavior. As with other video-
transcription studies, the presence of non-family-
member videographers and a video camera may have
influenced the children's behavior.
4.4.2.3 Groot et al, 1998 - Mouthing Behavior of
Young Children: An Observational Study
In this study, Groot etal. (1998) examined the
mouthing behavior of 42 Dutch children (21 boys and
21 girls) between the ages of 3 and 36 months in late
July and August 1998. Parent observations were made
of children in 36 families. Parents were asked to
observe their children ten times per day for 15 minute
intervals (i.e., 150 minutes total per day) for two days
and measure mouthing times with a stopwatch. In this
study, mouthing was defined as "all activities in which
objects are touched by mouth or put into the mouth
except for eating and drinking. This term includes
licking as well as sucking, chewing and biting."
For the study, a distinction was made between
toys meant for mouthing (e.g., pacifiers, teething
rings) and those not meant for mouthing. Inter-
observer and intra-observer reliability was measured by
trained observers who co-observed a portion of
observation periods in three families, and who co-
observed and repeatedly observed some video-
transcriptions made of one child. Another quality
assurance procedure performed for the extrapolated
total mouthing time data was to select 12 times per
hour randomly during the entire waking period of four
children during one day, in which the researchers
recorded activities and total mouthing times.
Although the sample size was relatively
small, the results provided estimates of mouthing
times, other than pacifier use, during a day. The
results were extrapolated to the entire day based on the
150 minutes of observation per day, and the mean
value for each child for the two days of observations
was interpreted as the estimate for that child.
Summary statistics are shown in Table 4-16. The
standard deviation in all four age categories except the
3 to 6 month old children exceeded the estimated
mean. The 3 to 6 month children (N=5) were
estimated to have mean non-pacifier mouthing
durations of 36.9 minutes per day, with toys as the
most frequently mouthed product category, and the 6
to 12 month children (N=14) 44 minutes per day
(fingers most frequently mouthed). The 12 to 18
month olds' (N=12) estimated mean non-pacifier
mouthing time was 16.4 minutes per day, with fingers
most frequently mouthed, and 18 to 36 month olds'
(N=ll) estimated mean non-pacifier mouthing time
was 9.3 minutes per day (fingers most frequently
mouthed).
One strength of this study is that the
researchers recognized that observing children's
behavior might affect the behavior, and emphasized to
the parents the importance of making observations
under conditions that were as normal as possible. In
spite of these efforts, many parents perceived that their
children's behavior was affected by being observed,
and observation interfered with care giving
responsibilities such as comforting children when they
were upset. Other limitations included a small sample
size that was not representative of the Dutch
population and that also may not be representative of
U.S. children. Technical problems with the
stopwatches affected at least 14 of 36 parents' data.
4.4.2.4 Smith and Norris, 2003 - Reducing the Risk
of Choking Hazards: Mouthing Behavior of
Children Aged 1 Month to 5 Years/Norris
and Smith, 2002 - Research Into the
Mouthing Behaviour of Children up to 5
Years Old
Smith and Norris (2003) conducted a real-
time hand recording study of mouthing behavior
among 236 children (111 males, 125 females) in the
United Kingdom (exact locations not specified) who
were from 1 month to 5 years old. Children were
observed at home by parents, who used stopwatches to
record the time that mouthing began, the type of
mouthing, the type of object being mouthed, and the
time that mouthing ceased. Children were observed for
a total of 5 hours over a two week period; the
observation time consisted of twenty 15 minute periods
spread over different times and days during the child's
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waking hours. Parents also recorded the times each
child was awake and not eating meals so that the
researchers could extrapolate estimates of total daily
mouthing time from the shorter observation periods.
Mouthing was defined as licking/lip touching,
sucking/trying to bite, biting or chewing, with a
description of each category, together with pictures,
given to parents as guidance for what to record.
The results of the study are shown in Table 4-
17. While no overall pattern could be found in the
different age groups tested, a Kruskal-Wallis test on
the data for all items mouthed indicated that there was
a significant difference between the age groups. Across
all age groups and types of items, licking and sucking
accounted for 64 percent of all mouthing behavior.
Pacifiers and fingers exhibited less variety on
mouthing behavior (principally sucking), while other
items had a higher frequency of licking, biting, or
other mouthing. The researchers selected
25of the 236 children randomly for a single 15 minute
observation of each child (total observation time across
all children: 375 minutes), in order to compare the
mouthing frequency and duration data obtained
according to the real-time hand recording and the
video-transcription methodologies, as well as the
reliability of parent observations versus those made by
trained professionals. For this group of 25 children,
the total number of mouthing behavior events recorded
by video (160) exceeded those recorded by parents
(114) and trained observers (110). Similarly, the total
duration recorded by video (24 minutes and 15
seconds) exceeded that recorded by observers (parents
and trained observers both recorded identical totals of
19 minutes and 44 seconds). The mean and standard
deviation of observed mouthing time were both lower
when recorded by video versus real-time hand
recording. The maximum observed mouthing time
was also lower (6 minutes and 7 seconds by video
versus 9 minutes and 43 seconds for both parents and
trained observers).
The strengths of this study were its
comparison of three types of observation (parents,
trained professional observers, and videotaping), and
its detailed reporting of mouthing behaviors by type,
object/item mouthed, and age group. However, the
children studied may not be representative of the study
population, and may not be representative of U.S.
children.
4.4.2.5 Au Yeung et al, 2004 - Young Children's
Mouthing Behavior: An Observational
Study via Videotaping in a Primarily
Outdoor Residential Setting
As described in Section 4.3.2.4, AuYeung et
al. (2004) used a video-transcription methodology to
study a group of 38 children (20 females and 18 males;
ages 1 to 6 years), 37 of whom were selected randomly
via a telephone screening survey of a 300 to 400 square
mile portion of the San Francisco, California
peninsula, along with one child selected by
convenience due to time constraints. Families who
lived in a residence with a lawn and whose annual
income was >$35,000 were asked to participate.
Videotaping took place between August 1998 and May
1999 for approximately two hours per child.
Videotaping by one researcher was supplemented with
field notes taken by a second researcher who was also
present during taping. Most of the videotaping took
place during outdoor play, however, data were
included for several children (one child <2 years old
and 8 children >2 years old) who had more than 15
minutes of indoor play during their videotaping
sessions.
The videotapes were translated into ASCII
computer files using VirtualTimingDevice™ software
described in Zartarian et al. (1997a). Both frequency
(see Section 4.3.2.4 of this Chapter) and duration were
analyzed. Between 5 and 10 percent of the data files
translated were randomly chosen for quality control
checks for inter-observer agreement. Ferguson et al.
(2006) described quality control aspects of the study in
detail.
For analysis, the mouthing contacts were
divided into indoor and outdoor locations, and 16
object/surface categories. Mouthing durations were
analyzed by age and gender separately, and in
combination. Mouthing contacts were defined as
contact with the lips, inside of the mouth, and/or the
tongue; dietary contacts were ignored. Mouthing
durations are shown in Table 4-18 (outdoor locations).
For the children in all age groups, the median duration
of each mouthing contact was 1 to 2 seconds,
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4-16
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Chapter 4 - Non-dietary Ingestion Factors
confirming the observations of other researchers that
children's mouthing contacts are of very short
duration. For the one child observed that was • 24
months, the total indoor mouthing duration was 11.1
minutes/hour; for children >24 months, the median
indoor mouthing duration was 0.9 minutes/hour (Table
4-19). For outdoor environments, median contact
durations for these age groups decreased to 0.8 and 0.6
minutes/hour, respectively (Table 4-20).
Nonparametric tests, such as the Wilcoxon
rank sum test were used for the data analyses. Both age
and gender were found to be associated with
differences in mouthing behavior. Girls' hand to
mouth contact durations were significantly shorter
than for boys (p = 0.04).
This study provides distributions of outdoor
mouthing durations with a variety of objects and
surfaces. Although indoor mouthing data were also
included in this study, the results were based on a
small number of children (N=9) and a limited amount
of indoor play. The sample of children may be
representative of certain socioeconomic strata in the
study area, but is not likely to be representative of the
national population. Due to the children's ages, the
presence of unfamiliar persons following the children
with a video camera may have influenced the video-
transcription methodology results.
4.5 MOUTHING PREVALENCE
4.5.1 Stanek et al., 1998 - Prevalence of Soil
Mouthing/Ingestion Among Healthy
Children Aged 1 to 6
Stanek et al. (1998) characterized the
prevalence of mouthing behavior among healthy
children based on a survey response study of parents or
guardians of 533 children (289 females, 244 males)
ages 1 to 6 years old. Study participants were
attendees at scheduled well-child visits at three clinics
in Western Massachusetts in August through October,
1992. Participants were questioned about the
frequency of 28 mouthing behaviors of the children
over the preceding month in addition to exposure time
(e.g., time outdoors, play in sand or dirt) and
children's characteristics (e.g., teething).
Table 4-21 presents the prevalence of reported
non-food ingestion/mouthing behaviors by child's age
as the percent of children whose parents reported the
behavior in the preceding month. The table includes
a column of data for the 3 to <6 year age category; this
column was calculated by U.S. EPA as a weighted
mean value of the individual data for 3, 4, and 5 year
olds in order to conform to the standardized age
categories used in this handbook. Among all the age
groups, 1 year olds had the highest reported daily
sucking of fingers/thumb; the proportion dropped for
two year olds, but rose slightly for three and four year
olds and declined again after age 4. A similar pattern
was reported for more than weekly finger/thumb
sucking, while more than monthly finger/thumb
sucking showed a very slight increase for 6 year olds.
Reported pacifier use was highest for one year olds and
declined with age for daily and more than weekly use;
for more than monthly use of a pacifier several six year
olds were reported to use pacifiers, which altered the
age-declining pattern for the daily and more than
weekly reported pacifier use. A pattern similar to
pacifier use existed with reported mouthing of teething
toys, with highest reported use for one year olds, a
decline with age until age 6 when reported use for
daily, more than weekly, and more than monthly use of
teething toys increased.
The authors developed an outdoor mouthing
rate for each child as the sum of rates for responses to
four questions on mouthing specific outdoor objects.
Survey responses were converted to mouthing rates per
week, using values of 0, 0.25,1, and 7 for responses of
never, monthly, weekly, and daily ingestion. Reported
outdoor soil mouthing behavior prevalence was found
to be higher than reported indoor dust mouthing
prevalence, but both behaviors had the highest reported
prevalence among 1 year old children and decreased
for children 2 years and older. The investigators
conducted principal component analyses on responses
to four questions relating to ingestion/mouthing of
outdoor objects in an attempt to characterize
variability. Outdoor ingestion/mouthing rates
constructed from the survey responses were that
children 1 year of age were reported to mouth or ingest
outdoor objects 4.73 times per week while 2 to 6 year
olds were reported to mouth or ingest outdoor objects
0.44 times per week. The authors developed
regression models to identify factors related to high
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Chapter 4 - Non-dietary Ingestion Factors
outdoor mouthing rates. The authors found that
children who were reported to play in sand or dirt had
higher outdoor object ingestion/mouthing rates.
A strength of this study is that it was a large
sample obtained in an area with urban and semi-urban
residents within various socioeconomic categories and
with varying racial/ethnic identities. However,
difficulties with parents' recall of past events may have
caused either over-estimates or under-estimates of the
behaviors studied.
4.5.2 Warren et al., 2000 - Non-nutritive
Sucking Behaviors in Preschool Children:
A Longitudinal Study
Warren et al. (2000) conducted a survey
response study of a non-random cohort of children
born in certain Iowa hospitals from early 1992 to early
1995, as part of a study of children's fluoride exposure.
For this longitudinal study of children's non-nutritive
sucking behaviors, 1,374 mothers were recruited at the
time of their newborns' birth, and over 600 were active
in the study until the children were at least 3 years old.
Survey questions on non-nutritive sucking behaviors
were administered to the mothers when the children
were 6 weeks, 3, 6, 9, 12, 16 and 24 months old, and
yearly after age 24 months. Questions were posed
regarding the child's sucking behavior over the
previous 3 to 12 months.
The authors reported that nearly all children
sucked non-nutritive items, including pacifiers, thumbs
or other fingers, and/or other objects, at some point in
their early years. The parent-reported sucking
behavior prevalence peaked at 91 percent for 3 month
old children. At 2 years of age, a majority (53 percent)
retained a sucking habit, while 29 percent retained the
habit at age 3 years and 21 percent at age 4 years.
Parent-reported pacifier use was 28% for 1 year olds,
25% for 2 year olds, and 10% for 3 year olds. The
authors cautioned against generalizing the results to
other children due to study design limitations.
Strengths of this study were its longitudinal
design and the large sample size. A limitation is that
the non-random selection of original study participants
and the self-selected nature of the cohort of survey
respondents who participated over time means that the
results may not be representative of other U. S. children
of these ages.
4.6 REFERENCES FOR CHAPTER 4
AuYeung, W.; Canales, R.; Beamer, P.; Ferguson,
A.C.; Leckie, J.O. (2004) Young children's
mouthing behavior: An observational study
via videotaping in a primarily outdoor
residential setting. J Children's Health 2(3-
4):271-295.
Barr, R.G.; Quek, V.S.H.; Cousineau, D.; Oberlander,
T.F.; Brian, J.A.; Young, S.N. (1994) Effects
of Intra-oral sucrose on crying, mouthing and
hand-mouth contact in newborn and six-
week-old infants. Dev Med Child Neurol
36:608-618.
Black, K.; Shalat, S.L.; Freeman, N.C.G.; Jimenez,
M; Donnelly, K.C.; Calvin, J.A. (2005)
Children's mouthing and food-handling
behavior in an agricultural community on the
US/Mexico border. J Expo Anal Environ
Epidemiol 15:244-251.
Blass, E.M.; Pillion, T.J.; Rochat, P.; Hoffmeyer, L.B.;
Metzger, M.A. (1989) Sensorimotor and
Motivational Determinants of Hand-Mouth
Coordination in 1 -3 -Day-Old Human Infants.
Dev Psych 25(6):963-975.
Davis, S.; Myers, P.A.; Kohler, E.; Wiggins, C.
(1995). Soil Ingestion in Children with Pica:
Final Report. U.S. EPA Cooperative
Agreement CR 816334-01. Seattle,
Washington: Fred Hutchinson Cancer
Research Center.
Ferguson, A.C.; Canales, R.A.; Beamer, P.; AuYeung,
W.; Key, M.; Munninghoff, A.; Lee, K. T.-
W.; Robertson, A., Leckie, J.O. (2006)
Video methods in the quantification of
children's exposures. J Expo Sci Environ
Epidemiol 16:287-298.
Freeman, C.G.; Jimenez, M.; Reed, K.J.; Gurunathan,
S.; Edwards, R.D.; Roy, A.; Adgate, J.L.;
Pellizzari, E.D.; Quackenboss, J.; Sexton, K.;
Lioy, P.J. (2001) Quantitative analysis of
children's microactivity patterns: The
Minnesota children's pesticide exposure
study. J Expo Anal Environ Epidemiol
11:501-509.
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4-18
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Chapter 4 - Non-dietary Ingestion Factors
Greene, M.A. (2002) Mouthing times for children
from the observational study. U.S. Consumer
Product Safety Commission, Bethesda, MD.
Groot, M. E.; Lekkerkerk, M. C.; Steenbekkers, L. P.
A. (1998) Mouthing Behavior of Young
Children: An observational Study.
Wageningen Agricultural University,
Wageningen, the Netherlands.
Juberg, D.R.; Alfano, K.; Coughlin, R.J.; Thompson,
K.M. (2001) An Observational Study of
Object Mouthing Behavior by Young
Children. Pediatrics 107(1)135-142.
Ko, S.; Schaefer, P.; Vicario, C.; Binns, H.J. (2007)
Relationships of video assessments of
touching and mouthing behaviors during
outdoor play in urban residential yards to
parental perceptions of child behaviors and
blood lead levels. J Expo Sci Environ
Epidemiol 17:47-47.
Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz,
S.; Robino, R.; Kapish, J. (1975)
Investigations into Sources of Lead in the
Environment of Urban Children. Environ
Res 10:415-26.
Lew, A.R.; Butterworth, G. (1997) The Development
of Hand-Mouth Coordination in 2- to 5-
Month-Old Infants: Similarities with
Reaching and Grasping. Infant Behav Dev
20(l):59-69.
Norris, B.; Smith, S. (2002) Research into the
mouthing behaviour of children up to 5 years
old. London: Consumer and Competition
Policy Directorate, Department of Trade and
Industry.
Reed, K.; Jimenez, M.; Freeman, N.; Lioy, P. (1999)
Quantification of children's hand and
mouthing activities through a videotaping
methodology. J Expo Anal Environ
Epidemiol 9:513-520.
Rochat, P.; Blass, E.M.; Hoffmeyer, L.B. (1988)
Oropharyngeal Control of Hand-Mouth
Coordination in Newborn Infants. Dev Psych
24(4):459-63.
Shalat, S.L.; Donnelly, K.C.; Freeman, N.C.G.;
Calvin, J. A.; Ramesh, S.; Jimenez, M.; Black,
K.; Coutinho, C.; Needham, L.L.; Barr, D.B.;
Ramirez, J. (2003) Nondietary ingestion of
pesticides by children in an agricultural
community on the U.S./Mexico border:
Preliminary Results. J Expos Anal Environ
Epidemiol 13:42-50.
Smith, S.A.; Norris, B. (2003). Reducing the risk of
choking hazards: mouthing behavior of
children aged 1 month to 5 years. Injury
Control and Safety Promotion 10(3): 145-154.
Stanek, E.J.; Calabrese, E.J.; Mundt, K.; Pekow, P.;
Yeatts, K.B. (1998) Prevalence of soil
mouthing/ingestion among healthy children
aged 1 to 6. J Soil Contam 7(2):227-242.
Takaya, R.; Yukuo, K.; Bos, A.F.; Einspieler, C.
(2003) Preterm to early postterm changes in
the development of hand-mouth contact and
other motor patterns. Early Hum Dev 75
Suppl. S193-S202.
Tudella, E.; Oishi, J.; Puglia Bermasco, N.H. (2000)
The Effect of Oral-Gustatory, Tactile-Bucal,
and Tactile-Manual Stimulation on the
Behavior of the Hands in Newborns. Dev
Psychobiol 37:82-89.
Tulve, N.S.; Suggs, J.C.; McCurdy, T.; Cohen Hubal,
E.A.; Moya, J. (2002) Frequency of
mouthing behavior in young children. J Expo
Anal Environ Epidemiol 12:259-264.
U.S. EPA. (2005) Guidance on selecting age groups
for monitoring and assessing childhood
exposures to environmental contaminants.
Washington, DC.: U.S. Environmental
Protection Agency, Office of Research and
Development. EPA/630/P-03/003F.
Warren, J.J.; Levy, S.M.; Nowak, A.J.; Tang. S. Non-
nutritive sucking behaviors in preschool
children: a longitudinal study. (2000) Pediatr
Dent 22(3): 187-91.
Xue, J.; Zartarian, V.; Moya, J.; Freeman, N.; Beamer,
P.; Black, K; Tulve, N.; Shalat, S. (2007) A
Meta-Analysis of Children's Hand-to-Mouth
Frequency Data for Estimating Nondietary
Ingestion Exposure. Risk Analysis
27(2):411-420.
Zartarian, V.G.; Streicker, J.; Rivera, A.; Cornejo,
C.S.; Molina, S.; Valadez, O.F.; Leckie, J.O.
(1995) A Pilot Study to Collect Micro-
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Activity Data of Two- to Four-Year-Old Farm
Labor Children in Salinas Valley, California.
J Expo Anal Environ Epidemiol 5(l):21-34.
Zartarian V.G.; Ferguson A.C.; Ong, C.G.; Leckie J.
(1997a) Quantifying Videotaped Activity
Patterns: Video Translation Software and
Training Methodologies. J Expo Anal
Environ Epidemiol 7(4):535-542.
Zartarian V.G.; Ferguson A.; Leckie J. (1997b)
Quantified dermal activity data from a four-
child pilot field study. J Expo Anal Environ
Epidemiol 7(4):543-553.
Zartarian, V.G.; Ferguson, A.C.; Leckie, J.O. (1998)
Quantified mouthing activity data from a four-
child pilot field study. J Expo Anal Environ
Epidemiol 8(4):543-553.
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Chapter 4 - Non-dietary Ingestion Factors
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-transcription
Category Minimum Mean
Hand to mouth 0.4 9.5
Object to mouth 0 16.3
Median 90th Percentile Maximum
8.5 20.1 25.7
3.6 77.1 86.2
Source: Reed etal., 1999.
Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age
Age Group Thumbs/fingers in Mouth Toes in Mouth Non-food Items in Mouth
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
1 1 years
12 years
-
Source:
71 29
63 0
33
30
28
33
43
38
33
33
= No data.
Freeman et al., 2001.
71
31
20
29
28
40
38
38
48
17
Table 4-5. Video-transcription Median (Mean) Observed Mouthing
Age Group N
3 to 4 years 3
5 to 6 years 7
7 to 8 years 4
10 to 12 years 5
Obj ect-to-mouth"
3(6)
0(1)
0(1)
0(1)
in 19 Minnesota Children (contacts/hour)
Hand-to-mouth
3.5 (4)
2.5 (8)
3(5)
2(4)
a Kruskal Wallis test comparison across four age groups, P=0.002.
N = Number of observations.
Source: Freeman et al., 2001.
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
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Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-7. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD)
Age
Infant
1 year
2 years
Preschool
N
SD
Source:
N
13
12
18
9
= Number of subjects.
= Standard deviation.
Black etal., 2005.
Hand to mouth
Frequency
(contacts/hour)
14(19.8±14.5)
13.3 (15. 8 ±8.7)
9.9 (11. 9 ±9.3)
19.4 (22.1 ±22.1)
Object to Mouth
Frequency
(contacts/hour)
18. 1(24.4 ±11. 6)
8.4 (9.8 ±6.3)
5. 5 (7.8 ±5. 8)
8.4(10.1± 12.4)
Table 4-8. Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various Studies
Age Group
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
N = Number of subjects.
SD = Standard deviation.
Source: Xue etal., 2007.
N
23
119
245
161
169
14
Mean
28.0
18.9
19.6
12.7
14.7
6.7
SD
21.7
17.4
19.6
14.2
18.4
5.5
Percentiles
5
3.0
1.0
0.1
0.1
0.1
1.7
25
8.0
6.6
6.0
2.9
3.7
2.4
50
23.0
14.0
14.0
9.0
9.0
5.7
75
48.0
26.4
27.0
17.0
20.0
10.2
95
65.0
52.0
63.0
37.0
54.0
20.6
Table 4-9. Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various Studies
5 25
6 to <12 months 10 14.5 12.3 2.4 7.6
1 to <2 years 32 13.9 13.6 1.1 4.2
2 to <3 years 46 5.3 8.1 0.1 0.1
3 to <6 years 55 8.5 10.7 0.1 0.1
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-10. Survey Reported Mouthing Behaviors for 92 Washington State Children
Never
N
Hand/Foot in Mouth 4
Pacifier 74
Mouth on Object 14
Non-Food in Mouth 5
Eat Dirt/Sand 37
N = Number of subjects.
Source: Davis et al. 1995.
%
4
81
15
5
40
Seldom
N
27
6
30
25
39
%
30
7
33
27
43
Occasionally
N
23
2
25
33
11
%
25
2
27
36
12
Frequently
N
31
9
19
24
4
%
34
10
21
26
4
Always
N
4
1
1
5
1
%
4
1
1
5
1
Unknown
N
3
0
3
0
0
%
3
0
3
0
0
Table 4-11. Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children with
Age Group N
13 to 84 months 9
• 24 months 1
>24 months 8
Statistic
Mean
Median
Range
-
Mean
Median
Range
a Object/surface categories mouthed indoors included: Clothes/towels, hands,
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
20.5
14.8
2.5 - 70.4
73.5
13.9
13.3
2.2-34.1
metal, paper/wrapper,
>15 minutes in View Indoors
Total non-dietary"
29.6
22.1
3.2-82.2
84.8
22.7
19.5
2.8-51.3
plastic, skin, toys, and wood.
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Table 4-12. Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
13 to 84 months 38 50th percentile
75th percentile
95th percentile
99th percentile
Mean
• 24 months 8 Median
Range
Mean
5th percentile
25th percentile
>24 months 30 50th percentile
75th percentile
95th percentile
99th percentile
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
11.7
0.4
4.4
8.4
14.8
31.5
47.6
13.0
7.0
1.3-47.7
11.3
0.2
4.7
8.6
14.8
27.7
39.5
hands, metal,
Total non-dietary"
18.3
0.8
9.2
14.5
22.4
51.7
56.6
20.4
13.9
6.2-56.4
17.7
0.6
7.6
14.6
22.4
43.8
53.0
non-dietary water, paper/wrapper,
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Table 4-13. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and Other Objects
Age 0 to 18 months
Age 19 to 36 months
Object Type
All Children
Only Children Who
Mouthed Objecta
All Children
Only Children Who
Mouthed Object"
Minutes
Minutes
Minutes
Minutes
Pacifier
Teether
Plastic Toy
Other Objects
108 (N = 107)
6 (N=107)
17 (N=107)
9 (N=107)
221 (N=52)
20 (N=34)
28 (N=66)
22 (N=46)
126(N=110)
0(N=110)
2(N=110)
2(N=110)
462 (N=52)
30 (N=l)
11 (N=21)
15 (N=18)
a Refers to means calculated for the subset of the sample children who mouthed the object stated (zeroes are eliminated from the
calculation of the mean).
N = Number of children.
Source: Juberg et al., 2001.
Table 4-14. Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category and Child's Age
Object Category
All Objects
Pacifiers
Non-pacifiers
Soft Plastic Food Content Items
Anatomy
Non-soft Plastic Toys, Teethers, and Rattles
Other Items
All ages
100
27
100
28
99
91
98
<1 year
100
43
100
13
100
94
98
1 to 2 years
100
27
100
30
97
91
97
2 to 3 years
100
10
100
41
100
86
98
Source: Greene, 2002.
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Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour)
Age Group
Mean (SD)
Median
95th Percentile
99th Percentile
All Items"
3 to < 12 months
12 to <24 months
24 to <36 months
10.5 (7.3)
7.3 (6.8)
5.3 (8.2)
9.6
5.5
2.4
26.2
22.0
15.6
39.8
28.8
47.8
Non Pacifiers'"
3 to < 12 months
12 to <24 months
24 to <36 months
7.1(3.6)
4.7(3.7)
3.5 (3.6)
6.9
3.6
2.3
13.1
12.8
12.8
14.4
18.9
15.6
All Soft Plastic Items
3 to < 12 months
12 to <24 months
24 to <36 months
0.5 (0.6)
0.4 (0.4)
0.4(0.6)
0.1
0.2
0.1
1.8
1.3
1.6
2.5
1.9
2.9
Soft Plastic Items Not Food Contact
3 to < 12 months
12 to <24 months
24 to <36 months
0.4(0.6)
0.3 (0.4)
0.2 (0.4)
0.1
0.1
0.0
1.8
1.1
1.3
2.0
1.5
1.8
Soft Plastic Toys, Teethers, and Rattles
3 to < 12 months
12 to <24 months
24 to <36 months
0.3 (0.5)
0.2 (0.3)
0.1 (0.2)
0.1
0.0
0.0
1.8
0.9
0.2
2.0
1.3
1.6
Soft Plastic Toys
3 to < 12 months
12 to <24 months
24 to <36 months
0.1 (0.3)
0.2 (0.3)
0.1 (0.2)
0.0
0.0
0.0
0.7
0.9
0.2
1.1
1.3
1.6
Soft Plastic Teethers and Rattles
3 to <12 months
12 to <24 months
24 to <36 months
0.2 (0.4)
0.0(0.1)
0.0(0.1)
0.0
0.0
0.0
1.0
0.1
0.0
2.0
0.6
1.0
Other Soft Plastic Items
3 to <12 months
12 to <24 months
24 to <36 months
0.1 (0.2)
0.1 (0.1)
0.1 (0.3)
0.0
0.0
0.0
0.8
0.4
0.5
1.0
0.6
1.4
Child-Specific Exposure Factors Handbook
September 2008
Page
4-27
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) (continued)
Age Group
Mean (SD)
Median
95th Percentile
99th Percentile
Soft Plastic Food Contact Items
3 to < 12 months
12 to <24 months
24 to <36 months
0.0 (0.2)
0.1 (0.2)
0.2 (0.4)
0.3
0.7
1.2
0.9
1.2
1.9
Anatomy
3 to < 12 months
12 to <24 months
24 to <36 months
2.4(2.8)
1.7(2.7)
1.2(2.3)
1.5
0.8
0.4
10.1
8.3
5.1
12.2
14.8
13.6
Non Soft Plastic Toys, Teethers, and Rattles
3 to < 12 months
12 to <24 months
24 to <36 months
1.8(1.8)
0.6 (0.8)
0.2 (0.4)
1.3
0.3
0.1
6.5
1.8
0.9
7.7
4.6
2.3
Other Items
3 to < 12 months
12 to <24 months
24 to <36 months
2.5(2.1)
2.1(2.0)
1.7(2.6)
2.1
1.4
0.7
7.8
6.6
7.1
8.1
9.0
14.3
Pacifiers
3 to < 12 months
12 to <24 months
24 to <36 months
3.4(6.9)
2.6(6.5)
1.8(7.9)
0.0
0.0
0.0
19.5
19.9
4.8
37.3
28.6
46.3
SD
Object category " all items" is subdivided into pacifiers and non-pacifiers.
Object category "non-pacifiers" is subdivided into all soft plastic items, anatomy (which includes hair, skin, fingers and hands), non-
soft plastic toys/teethers/rattles, and other items.
Object category " all soft plastic items" is subdivided into food contact items, nonfood contact items (toys, teethers and rattles) and other
soft plastic.
= Standard deviation.
Source: Greene, 2002.
Page
4-28
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-16. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without Pacifier, in Minutes per Day
Age Group
3 to 6 months
6 to 12 months
12 to 18 months
18 to 3 6 months
N
5
14
12
11
Note: The object most mouthed in all a;
N = Number of children.
SD = Standard deviation.
Source: Groot et al., 1998.
Mean
36.9
44
16.4
9.3
je groups was the fingers,
SD
19.1
44.7
18.2
9.8
except for the 6 to
Minimum
14.5
2.4
0
0
Maximum
67
171.5
53.2
30.9
12 month group which mostly mouthed toys.
Child-Specific Exposure Factors Handbook
September 2008
Page
4-29
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
£
O
nutes:sec
g
|
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t/3
s
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~i cc
- 2
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cc
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m
m
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II
£
o *sD m o oo t>
(N o *n o *n i— i
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o -^f o -— i o >n
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o *sD •— i ^ *n >n
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(N (N t> ^ -— i O>
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0 0 0 0 0 -H
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(N ON (N •— i (N ON
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(N ^ NO m m ON
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w~) v~) w~) (N "^ m
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o -^f o -^f -— i -:^-
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(N i> -^f -— i oo m
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(N| i— i i— i (N O •— i
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-H 0 0 0 0 -H
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m o o (N o -— i
-— i -^ m NO o >n
•rf .— i (N -— i o m
O O O O O -— i
^D ^t 0 0 0 -H
m >n i— i m o •— i
•^ NO ON -^f o «n
-— i -— i m (N o m
O O O O O -— i
in m o ON "^ •— i
^ O (N (N (N TI^
t> ON OO (N O t>
(N "^ (N •— i O w~)
0 0 0 0 0 -H
m (N -^f -^ oo o *n o •— i
0 0 0 0 0 -H
& 1 S ^
3 S & £ S S
Q E H O £ H
_OJ
g
S
.S m
1 1
4= 'fc
N = Number of c
Source: Smith and No
Page
4-30
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-18. Outdoor Median Mouthing Duration (seconds per contact), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
13 to 84 months 38 50th percentile
75th percentile
95th percentile
99th percentile
Mean
• 24 months 8 Median
Range
Mean
5th percentile
25th percentile
>24 months 30 50th percentile
75th percentile
95th percentile
99th percentile
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
3.5
0
1
1
2
12
41.6
9
3
0 to 136
3.5
0
1
1
2
12
41.6
hands, metal,
Total non-dietary*
3.4
0
1
1
3
11
40
2
1
Oto40
3.4
0
1
1
3
11
40
non-dietary water, paper/wrapper,
Table 4-19. Indoor Mouthing Duration (minutes per hour), Video-transcription of 9 Children with >
Age Group N
13 to 84 months 9
• 24 months 1
>24 months 8
Statistic
Mean
Median
Range
Observation
Mean
Median
Range
a Object/surface categories mouthed indoors included: Clothes/towels, hands,
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
1.8
0.7
0-10.7
10.7
0.7
0.7
0-1.9
metal, paper/wrapper,
15 minutes in View Indoors
Total non-dietary"
2.3
0.9
0-11.1
11.1
1.2
0.9
0-3.7
plastic, skin, toys, and wood.
Child-Specific Exposure Factors Handbook
September 2008
Page
4-31
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-20. Outdoor Mouthing Duration (minutes per hour), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
.,,„.,, ,„ 50th percentile
13 to 84 months 38 -,cth 4-i
75 percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25th percentile
„ 50th percentile
'24months 8 75th percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25th percentile
... ,„ Median
>24 months 30 „, ...
75 percentile
95th percentile
99th percentile
Range
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
0.9
0
0.1
0.2
0.6
2.6
11.2
0-15.5
2.7
0
0.2
0.4
1.5
11.5
14.7
0-15.5
0.4
0
0.1
0.2
0.4
1.2
2.2
0-2.4
hands, metal,
Total non-dietary*
1.2
0
0.2
0.6
1.2
2.9
11.5
0-15.8
3.1
0.2
0.2
0.8
3.1
11.7
15
0.2-15.8
0.7
0
0.2
0.6
1
2.1
2.5
0-2.6
non-dietary water, paper/wrapper,
Page
4-32
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 4 - Non-dietary Ingestion Factors
Table 4-21. Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion Behaviors
Object or substance
mouthed or ingested
Grass, leaves, flowers
Twigs, sticks, woodchips
Teething toys
Other toys
Blankets, cloth
Shoes, Footwear
Clothing
Crib, chairs, furniture
Paper, cardboard, tissues
Crayons, pencils, erasers
Toothpaste
Soap, detergent, shampoo
Plastic, plastic wrap
Cigarette butts, tobacco
Suck fingers/thumb
Suck feet or toes
Bite nails
Use pacifier
Percent of children reported to mouth/ingest daily
1 year
N=171
16
12
44
63
29
20
25
13
28
19
52
15
7
4
44
8
2
20
* Weighted mean of 3, 4, and 5 year-olds'
Handbook.
Source: Stanek et al. (1998).
2 years
N=70
0
0
6
27
11
1
7
3
9
17
87
14
4
0
21
1
7
6
data calculated by U.S
3 to <6 years"
N=265
1
0
2
12
10
0
9
1
5
5
89
2
1
1
24
0
10
2
6 years
N=22
0
0
9
5
5
0
14
0
5
18
82
0
0
0
14
0
14
0
All years
N=528
6
4
17
30
16
7
14
5
13
12
77
8
3
2
30
3
7
9
EPA to conform to standardized age categories used in this
Child-Specific Exposure Factors Handbook
September 2008
Page
4-33
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
TABLE OF CONTENTS
INHALATION RATES 6-1
6.1 INTRODUCTION 6-1
6.2 RECOMMENDATIONS 6-2
6.3 KEY INHALATION RATE STUDIES 6-6
6.3.1 Brochu et al., 2006 6-6
6.3.2 U.S. EPA, 2006 6-6
6.3.3 Arcus-Arth and Blaisdell, 2007 6-8
6.3.4 Stifelman, 2007 6-9
6.3.5 Key Studies Combined 6-9
6.4 RELEVANT INHALATION RATE STUDIES 6-9
6.4.1 International Commission on Radiological Protection (ICRP), 1981 6-9
6.4.2 U.S. EPA, 1985 6-10
6.4.3 Linn et al., 1992 6-10
6.4.4 Spier et al., 1992 6-11
6.4.5 Adams, 1993 6-11
6.4.6 Layton, 1993 6-12
6.4.7 Rusconi et al., 1994 6-14
6.4.8 Price et al., 2003 6-14
6.5 REFERENCES FOR CHAPTER 6 6-15
Child-Specific Exposure Factors Handbook Page
September 2008 6-i
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
LIST OF TABLES
Table 6-1. Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation
(Males and Females Combined) 6-3
Table 6-2. Recommended Short-Term Exposure (Less Than 30 Days) Values for Inhalation
(Males and Females Combined) 6-4
Table 6-3. Confidence in Recommendations for Inhalation Rates 6-5
Table 6-4. Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less 6-17
Table 6-5. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
Normal-weight Males and Females Aged 2.6 months to 23 years 6-18
Table 6-6. Mean and 95th Percentile Inhalation Rate Values (mVday) for Free-living Normal-weight
Males, Females, and Males and Females Combined 6-19
Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years 6-20
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight
(mVkg-day) for Free-living Normal-weight Males and Females Aged 2.6 months
to 23 years 6-21
Table 6-9. Distribution Percentiles of Physiological Daily Inhalation Rates (mVkg-day) for Free-living
Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years 6-22
Table 6-10. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category 6-23
Table 6-11. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category 6-24
Table 6-12. Mean and 95th Percentile Inhalation Rate Values (mVday) for Males, Females and
Males and Females Combined 6-25
Table 6-13. Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
Specified Activity Category, for Males by Age Category 6-26
Table 6-14. Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
Specified Activity Category, for Females by Age Category 6-28
Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
Within the Specified Activity Category, by Age and Gender Categories 6-30
Table 6-16. Nonnormalized Daily Inhalation Rates (mVday) Derived Using Layton's (1993)
Method and CSFII Energy Intake Data 6-32
Table 6-17. Mean and 95th Percentile Inhalation Rate Values (mVday) for Males and Females
Combined 6-33
Table 6-18. Summary of Institute of Medicine Energy Expenditure Recommendations
for Active and Very Active People with Equivalent Inhalation Rates 6-34
Table 6-19. Mean Inhalation Rate Values (mVday) for Males, Females, and Males and Females
Combined 6-35
Table 6-20. Mean Inhalation Rate Values (mVday) from Key Studies for Males and Females
Combined 6-36
Table 6-21. 95th Percentile Inhalation Rate Values (mVday) from Key Studies for Males and Females
Combined 6-37
Table 6-22. Daily Inhalation Rates Estimated From Daily Activities 6-38
Table 6-23. Selected Inhalation Rate Values During Different Activity Levels Obtained From Various
Literature Sources 6-39
Table 6-24. Summary of Human Inhalation Rates for Children by Activity Level (m3/hour) 6-40
Table 6-25. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for
All Age Groups 6-40
Page
6-ii
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
LIST OF TABLES (continued)
Table 6-26. Summary of Daily Inhalation Rates Grouped by Age and Activity Level 6-41
Table 6-27. Calibration and Field Protocols for Self-monitoring of Activities Grouped by
Subject Panels 6-42
Table 6-28. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated
Breathing Rates 6-42
Table 6-29. Distribution of Predicted Inhalation Rates by Location and Activity Levels for Elementary
and High School Students 6-43
Table 6-30. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and
High School Students 6-44
Table 6-31. Summary of Average Inhalation Rates (mVhour) by Age Group and Activity Levels for
Laboratory Protocols 6-45
Table 6-32. Summary of Average Inhalation Rates (mVhour) by Age Group And Activity Levels in Field
Protocols 6-46
Table 6-33. Mean Minute Inhalation Rate (mVminute) by Group and Activity for Laboratory Protocols . . 6-47
Table 6-34. Mean Minute Inhalation Rate (mVminute) by Group and Activity for Field Protocols 6-47
Table 6-35. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy
Intakes (EFD) for Individuals Sampled in the 1977-78 NFCS 6-48
Table 6-36. Daily Inhalation Rates Calculated from Food-energy Intakes 6-49
Table 6-37. Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR) 6-50
Table 6-38. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal
Metabolic Rate (BMR) 6-51
Table 6-39. Inhalation Rates for Short-term Exposures 6-52
Table 6-40. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 618
Infants and Children Grouped in Classes of Age 6-53
Child-Specific Exposure Factors Handbook
September 2008
Page
6-iii
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
LIST OF FIGURES
Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects .... 6-54
Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects .... 6-54
Page Child-Specific Exposure Factors Handbook
6-iv September 2008
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
6 INHALATION RATES
6.1 INTRODUCTION
Ambient and indoor air are potential sources
of children's exposure to toxic substances. Children
can be exposed to contaminated air during a variety of
activities in different environments. Children may be
exposed due to sources that contribute pollution to
ambient air. Children may also inhale chemicals from
the indoor use of various consumer products. Due to
their size, physiology, and activity level, the inhalation
rates of children differ from those of adults.
Infants and children have a higher resting
metabolic rate and oxygen consumption rate per unit of
body weight than adults, because of their rapid growth
and relatively larger lung surface area per unit of body
weight that requires cooling. For example, the oxygen
consumption rate for a resting infant between one week
and one year of age is 7 milliliters per kilogram of body
weight (mL/kg) per minute, while the rate for an adult
under the same conditions is 3-5 mL/kg per minute
(WHO, 1986). Thus, while greater amounts of air and
pollutants are inhaled by adults than children over
similar time periods on an absolute basis, the volume of
air passing through the lungs of a resting infant is up to
twice that of a resting adult on a body weight basis.
The Agency defines exposure as the chemical
concentration at the boundary of the body (U.S. EPA,
1992). In the case of inhalation, the situation is
complicated by the fact that oxygen exchange with
carbon dioxide takes place in the distal portion of the
lung. The anatomy and physiology of the respiratory
system as well as the characteristics of the inhaled agent
diminishes the pollutant concentration in inspired air
(potential dose) such that the amount of a pollutant that
actually enters the body through the lung (internal dose)
is less than that measured at the boundary of the body.
A detailed discussion of this concept can be found in
Guidelines for Exposure Assessment (U.S. EPA, 1992).
When constructing risk assessments that concern the
inhalation route of exposure, one must be aware of any
adjustments that have been employed in the estimation
of the pollutant concentration to account for this
reduction in potential dose.
Children's inhalation dosimetry and health
effects were topics of discussion at a U.S. EPA
workshop held in June 2006 (Foos and Sonawane,
2008). Age related differences in lung structure and
function, breathing patterns, and how these affect the
inhaled dose and the deposition of particles in the lung
are important factors in assessing risks from inhalation
exposures (Foos et al, 2008). Children may have a
lesser nasal contribution to breathing during rest and
while performing various activities. The uptake of
particles in the nasal airways is also less efficient in
children. Thus, the deposition of particles in the lower
respiratory tract may be greater (Foos et al., 2008).
Inclusion of this chapter in the Child-Specific
Exposure Factors Handbook does not imply that
assessors will always need to select and use inhalation
rates when evaluating exposure to air contaminants.
For example, it is unnecessary to calculate inhaled dose
when using dose-response factors from the Integrated
Risk Information System (IRIS) (U.S. EPA, 1994),
because the IRIS methodology accounts for inhalation
rates in the development of "dose-response"
relationships. Information in this chapter may be used
by toxicologists in their derivation of human equivalent
concentrations. When using IRIS for inhalation risk
assessments, "dose-response" relationships require only
an average air concentration to evaluate health
concerns:
For non-carcinogens, IRIS uses Reference
Concentrations (RfCs) which are expressed in
concentration units. Hazard is evaluated by
comparing the inspired air concentration to the
RfC.
For carcinogens, IRIS uses unit risk values
which are expressed in inverse concentration
units. Risk is evaluated by multiplying the
unit risk by the inspired air concentration.
Detailed descriptions of the IRIS methodology for
derivation of inhalation reference concentrations can be
found in two methods manuals produced by the Agency
(U.S. EPA, 1992; 1994).
The Superfund Program has also updated its
approach for determining inhalation risk, eliminating
the use of inhalation rates when evaluating exposure to
air contaminants (U.S. EPA, 2008). The current
methodology recommends that risk assessors use the
concentration of the chemical in air as the exposure
Child-Specific Exposure Factors Handbook
September 2008
Page
6-1
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
metric (e.g., mg/m3), instead of the intake of a
contaminant in air based on inhalation rate and body
weight (e.g., mg/kg-day).
Recommended inhalation rates (both long- and
short-term) are provided in the next section, along with
the confidence ratings for these recommendations.
These recommendations are based on four key studies
identified by U.S. EPA for this factor. Long-term
exposure is repeated exposure for more than 30 days,
up to approximately 10% of the life span in humans
(more than 30 days). Long-term inhalation rates for
children (including infants) are presented as daily rates
(mVday). Short-term exposure is repeated exposure for
more than 24 hours, up to 30 days. Short-term
inhalation rates are reported for children (including
infants) performing various activities in mVminute.
Following the recommendations, the available studies
(both key and relevant studies) on inhalation rates are
summarized.
6.2 RECOMMENDATIONS
The recommended inhalation rates for children
are based on four recent studies: Brochu et al, 2006;
U.S. EPA, 2006; Arcus-Arth and Blaisdell, 2007; and
Stifelman, 2007. These studies represent an
improvement upon those previously used for
recommended inhalation rates in this handbook,
because they use a large data set that is representative
of the United States as a whole and consider the
correlation between body weight and inhalation rate.
The selection of inhalation rates to be used for
exposure assessments depends on the age of the
exposed population and the specific activity levels of
this population during various exposure scenarios. The
recommended long-term values for children (including
infants) for use in various exposure scenarios are
presented in Table 6-1 for the standard U.S. EPA
childhood age groups used in this handbook. As
shown in Table 6-1, the daily average inhalation rates
for long-term exposures for male and female children
combined (unadjusted for body weight) range from 3.6
mVday for children from birth to <1 month to 16.5
mVday for children aged 16 to <21 years. These values
represent averages of the inhalation rate data from the
four key studies. The 95th percentile values range from
7.1 mVday to 27.6 mVday for the same age categories.
The 95th percentile values represent averages of the
inhalation rate data from the three key studies for which
95th percentile values were available for selected age
groups (Brochu et al., 2006; U.S. EPA, 2006; Arcus-
Arth and Blaisdell, 2007). It should be noted that there
may be a high degree of uncertainty associated with the
upper percentiles. These values equate to unusually
high estimates of caloric intake per day, and are
unlikely to be representative of the average child. For
example, using Layton's equation (Layton, 1993) for
estimating metabolically consistent inhalation rates to
calculate caloric equivalence (see Section 6.4.6), the
95th percentile value for 16 to <21 year old children is
4,840 kcal/day. All of the 95th percentile values listed
in Table 6-1 may represent unusually high inhalation
rates for long-term exposures, even for the upper end of
the distribution, but were included in this handbook to
provide exposure assessors a sense of the possible range
of inhalation rates for children. These values should be
used with caution when estimating long-term exposures.
For short-term exposures for children aged 21
years and under, for which activity patterns are known,
mean and 95thpercentile data are provided in Table 6-2
for males and females combined, in mVminute. These
values represent averages of the activity level data from
the one key study from which short-term inhalation rate
data were available (U.S. EPA, 2006).
The confidence ratings for the inhalation rate
recommendations are shown in Table 6-3. Multiple
percentiles for long- and short-term inhalation rates for
both males and females are provided in Tables 6-5
through 6-11 and Table 6-16.
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6-2
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Chapter 6 - Inhalation Rates
Table 6-1. Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation
(Males and Females Combined).
. „ Mean Sources Used 95th Percentile Sources Used , , ... , „ ...
Age Group ,,, ,, ,, ,,, „ „,„,,, ... Multiple Percentiles
0 ^ nr/day for Means nr/day for 95™ Percentiles r
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
1 Arcus-Arth and
b No data for this
3.6
_ b
4.1
5.4
8.0
9.5
10.9
12.4
15.1
16.5
a
a,c
a,c
a,c,d,e
a,d,e
a,d,e
a,d,e
a,d,e
a,d,e
7.1
6.1
8.1
12.8
15.9
16.2
18.7
23.5
27.6
a
a,c
a,c
See Tables 6-5
a'c'd through 6- 11 and 6- 16
a,d
a,d
a,d
a,d
a,d
Blaisdell, 2007.
age group.
Brochuetal.,2006.
d U.S. EPA, 2006
Stifelman, 2007
Note: Some 95th percentile values
may be unusually
high, and
may not be representative of the average child.
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Chapter 6 - Inhalation Rates
Table 6-2.
Activity Level
Sleep or Nap
Sedentary/
Passive
Light Intensity
Moderate Intensity
High Intensity
Source: U.S. EPA,
Recommended Short- Term Exposure (Less Than 30 Days) Values for Inhalation
(Males and Females Combined)
Age Group
years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16to<21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
2006.
Mean
mVminute
3.0E-03
4.5E-03
4.6E-03
4.3E-03
4.5E-03
5.0E-03
4.9E-03
3.1E-03
4.7E-03
4.8E-03
4.5E-03
4.8E-03
5.4E-03
5.3E-03
7.6E-03
1.2E-02
1.2E-02
1.1E-02
1.1E-02
1.3E-02
1.2E-02
1.4E-02
2.1E-02
2.1E-02
2.1E-02
2.2E-02
2.5E-02
2.6E-02
2.6E-02
3.8E-02
3.9E-02
3.7E-02
4.2E-02
4.9E-02
4.9E-02
95 Percentile ,, ... . „ ...
, , . , Multiple Percentiles
m /minute
4.6E-03
6.4E-03
6.4E-03
5.8E-03
6.3E-03
7.4E-03
7.1E-03
4.7E-03
6.5E-03
6.5E-03
5.8E-03
6.4E-03
7.5E-03
7.2E-03
1.1E-02 See Tables 6- 11 and 6- 12
1.6E-02
1.6E-02
1.4E-02
1.5E-02
1.7E-02
1.6E-02
2.2E-02
2.9E-02
2.9E-02
2.7E-02
2.9E-02
3.4E-02
3.7E-02
4.1E-02
5.2E-02
5.3E-02
4.8E-02
5.9E-02
7.0E-02
7.3E-02
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Chapter 6 - Inhalation Rates
Table 6-3. Confidence in Recommendations for Inhalation Rates
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The survey methodology and data analysis was adequate.
Measurements were made by indirect methods. The
studies analyzed existing primary data.
Potential bias within the studies was fairly well
documented.
The studies focused on inhalation rates and factors
influencing them.
The studies focused on the U.S. population. A wide
range of age groups were included.
The studies were published during 2006 and 2007 and
represent current exposure conditions.
The data collection period for the studies may not be
representative of long-term exposures.
All key studies are available from the peer reviewed
literature.
The methodologies were clearly presented; enough
information was included to reproduce most results.
Information on ensuring data quality in the key studies
was limited.
In general, the key studies addressed variability in
inhalation rates based on age and activity level.
However, other factors that may affect inhalation rates
(e.g., weight, body mass index [BMI], ethnicity) are not
discussed.
Multiple sources of uncertainty exist for these studies.
Assumptions associated with Energy Expenditure (EE)
based estimation procedures are a source of uncertainty
in inhalation rate estimates.
Three of the key studies appeared in peer reviewed
journals, and one key study is a U.S. EPA peer reviewed
report.
There are four key studies. The results of studies from
different researchers are in general agreement.
Rating
Medium
High
Medium
Medium
High
Medium
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Chapter 6 - Inhalation Rates
6.3 KEY INHALATION RATE STUDIES
6.3.1 Brochu et aL, 2006 - Physiological Daily
Inhalation Rates for Free-living Individuals
Aged 1 Month to 96 Years, Using Data
from Doubly Labeled Water
Measurements: A proposal for Air Quality
Criteria, Standard Calculations and Health
Risk Assessment
Brochu et al. (2006) calculated physiological
daily inhalation rates (PDIR) for 2,210 individuals aged
3 weeks to 96 years using the reported disappearance
rates of oral doses of doubly labeled water (DLW)
(2H20 and H2180) in urine, monitored by gas-isotope-
ratio mass spectrometry for an aggregate period of more
than 30,000 days. DLW data were complemented with
indirect calorimetry and nutritional balance
measurements.
In the DLW method, the disappearance of the
stable isotopes deuterium (2H) and heavy oxygen-18
(180) are monitored in urine, saliva, or blood samples
over a long period of time (from 7 to 21 days) after
subjects receive oral doses of 2H20 and H2180. The
disappearance rate of 2H reflects water output and that
of 180 represents water output plus carbon dioxide
(C02) production rates. The C02 production rate is
then calculated by difference between the two
disappearance rates. Total daily energy expenditures
(TDEEs) are determined from C02 production rates
using classic respirometry formulas, in which values for
the respiratory quotient (RQ = C02produced/02 consumed) are
derived from the composition of the diet during the
period of time of each study. The DLW method also
allows for measurement of the energy cost of growth
(ECG). TDEE and ECG measurements can be
converted into PDIR values using the following
equation developed by Layton (1993):
PDIR = (TDEE + ECG) x H x VQ 10'3 (Eqn. 6-1)
H =
where:
PDIR =
TDEE =
(kcal/day);
ECG =
physiological daily inhalation rates
(mVday);
total daily energy expenditure
stored daily energy cost for growth
(kcal/day);
VQ =
io-3 =
oxygen uptake factor, volume of
0.21 L of oxygen (at standard
temperature and pressure, dry air)
consumed to produce 1 kcal of
energy expended;
ventilatory equivalent ratio of the
minute volume (VE) at body
temperature pressure saturation) to
the oxygen uptake rate (V02 at
standard temperature and pressure,
dry air) VE/V02 = 27; and
conversion factor (L/m3).
Brochu et al. (2006) calculated daily inhalation
rates (expressed in mVday and m3/kg-day) for a variety
of age groups and physiological conditions. Published
data on BMI, body weight, basal metabolic rate (BMR),
ECG, and TDEE measurements (based on DLW
method and indirect calorimetry) for subjects aged 2.6
months to 96 years were used. Only the data for
children are presented in this handbook. Data for
underweight, healthy normal-weight, and
overweight/obese individuals were gathered and
defined according to BMI cutoffs. Data for newborns
were included regardless of BMI values, because they
were clinically evaluated as being healthy infants.
Mean inhalation rates for newborns are
presented in Table 6-4. Due to the insufficient number
of subj ects, no distributions were derived for this group.
The distribution of daily inhalation rates for normal-
weight and overweight/obese individuals by gender and
age groups are presented in Tables 6-5 to 6-9.
An advantage of this study is that data are
provided for age groups of less than one year. A
limitation of this study is that data for individuals with
pre-existing medical conditions was lacking.
6.3.2 U.S. EPA, 2006 - Metabolically-derived
Human Ventilation Rates: A Revised
Approach Based Upon Oxygen
Consumption Rates
U.S. EPA (2006) conducted a study to
ascertain inhalation rates for children and adults.
Specifically, U.S. EPA sought to improve upon the
methodology used by Layton (1993) and other studies
that relied upon the ventilatory equivalent (VQ) and a
linear relationship between oxygen consumption and
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Chapter 6 - Inhalation Rates
fitness rate. A revised approach, developed by U.S.
EPA's National Exposure Research Laboratory
(NERL), was used, in which an individual's inhalation
rate was derived from his or her assumed oxygen
consumption rate. U.S. EPA applied this revised
approach using body weight data from the 1999-2002
National Health and Nutrition Examination Survey
(NHANES) and metabolic equivalents (METS) data
from U.S. EPA's Consolidated Human Activity
Database (CHAD). In this database, metabolic cost is
given in units of "METS" or "metabolic equivalents of
work," an energy expenditure metric used by exercise
physiologists and clinical nutritionists to represent
activity levels. An activity's METS value represents a
dimensionless ratio of its metabolic rate (energy
expenditure) to a person's resting, or basal metabolic
rate (BMR).
NHANES provided age, gender, and body
weight data for 19,022 individuals from throughout the
United States. From these data, basal metabolic rate
(BMR) was estimated using an age-specific linear
equation used in the Exposure Factors Handbook (U. S.
EPA, 1997), and in several other studies and reference
works.
The CHAD database is a compilation of
several databases of human activity patterns. U.S. EPA
used one of these studies, the National Human Activity
Pattern Survey (NHAPS), as its source for METS
values because it was more representative of the entire
United States population than the other studies in the
database. The NHAPS data set included activity data
for 9,196 individuals, each of which provided 24 hours
of activity pattern data using a diary-based
questionnaire. While NHAPS was identified as the best
available data source for activity patterns, there were
some shortcomings in the quality of the data. Study
respondents did not provide body weights; instead,
body weights are simulated using statistical sampling.
Also, the NHAPS data extracted from CHAD could not
be corrected to account for non-random sampling of
study participants and survey days.
NHANES and NHAPS data were grouped into
age categories using the standardized age categories
presented elsewhere in this handbook, with the
exception that children under the age of one year were
placed into a single category to preserve an adequate
sample size within the category. For each NHANES
participant, a "simulated" 24-hour activity pattern was
generated by randomly sampling activity patterns from
the set of NHAPS participants with the same gender
and age category as the NHANES participant. Twenty
such patterns were selected at random for each
NHANES participant, resulting in 480 hours of
simulated activity data for each NHANES participant.
The data were then scaled down to a 24-hour time
frame to yield an average 24-hour activity pattern for
each of the 19,022 NHANES individuals.
Each activity was assigned a METS value
based on statistical sampling of the distribution
assigned by CHAD to each activity code. For most
codes, these distributions were not age-dependent, but
age was a factor for some activities for which intensity
level varies strongly with age. Using statistical
software, equations for METS based on normal,
lognormal, exponential, triangular, and uniform
distributions were generated as needed for the various
activity codes. The METS values were then translated
into energy expenditure (EE) by multiplying the METS
by the basal metabolic rate (BMR), which was
calculated as a linear function of body weight. The
oxygen consumption rate (V02) was calculated by
multiplying EE by H, the volume of oxygen consumed
per unit of energy. V02 was calculated both as volume
per time and as volume per time per unit body weight.
The inhalation rate for each activity within the
24-hour simulated activity pattern for each individual
was estimated as a function of V02, body weight, age,
and gender. Following this, the average inhalation rate
was calculated for each individual for the entire 24-hour
period, as well as for four separate classes of activities
based on METS value (sedentary/passive (METS less
than or equal to 1.5), light intensity (MET S greater than
1.5 and less than or equal to 3.0), moderate intensity
(METS greater than 3.0 and less than or equal to 6.0),
and high intensity (METS greater than 6.0). Data for
individuals were then used to generate summary tables
based on gender and age categories.
Data from this study are presented in Tables 6-
10 through 6-15. Tables 6-10 and 6-11 present, for
male and female subjects, respectively, summary
statistics for daily average inhalation rate by age
category on a volumetric (mVday) and body-weight
adjusted (m3/day-kg) basis. Table 6-12 presents the
mean and 95th percentile values for males, females, and
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Chapter 6 - Inhalation Rates
males and females combined. Tables 6-13 and 6-14
present, for male and female subjects, respectively,
mean ventilation rates by age category on a volumetric
(mVmin) and body-weight adjusted (mVmin-kg) basis
for the five different activity level ranges described
above. Table 6-15 presents the number of hours spent
per day at each activity level by males and females.
An advantage of this study is the large sample
size. In addition, the datasets used, NHAPS and
NHANES, are representative of the U.S. general
population. Limitations are that the NHAPS data are 10
years old, there is variability in the 24-hour activity, and
there is uncertainly in the METs randomization, all of
which were noted by the authors.
6.3.3 Arcus-Arth and Blaisdell, 2007 - Statistical
Distributions of Daily Breathing Rates for
Narrow Age Groups of Infants and
Children
Arcus-Arth and Blaisdell (2007) derived daily
breathing rates for narrow age ranges of children using
the metabolic conversion method of Layton (1993) and
energy intake data adjusted to represent the U.S.
population from the Continuing Survey of Food Intake
for Individuals (CSFII) 1994-1996,1998. Normalized
(mVkg-day) and nonnormalized (mVday) breathing
rates for children 0-18 years of age were derived using
the general equation developed by Layton (1993) to
calculate energy-dependent inhalation rates (see
Equation 6-2).
VE = H x VQ x EE (Eqn. 6-2)
where:
VE = volume of air breathed per day
(mVday);
H = volume of oxygen consumed to
produce 1 kcal of energy (m3/kcal);
VQ = ratio of the volume of air to the
volume of oxygen breathed per unit
time (unitless); and
EE = energy (kcal) expended per day.
Arcus-Arth and Blaisdell (2007) calculated H
values of 0.22 and 0.21 for infants and noninfant
children, respectively, using the 1977-1978 NFCS and
CSFII data sets. Ventilatory equivalent (VQ) data,
including those for infants, were obtained from 13
studies that reported VQ data for children aged 4-8
ears. Separate preadolescent (4-8 years) and adolescent
(9-18 years) VQ values were calculated in addition to
separate VQ values for adolescent boys and girls. Two-
day-averaged daily energy intake (El) values reported
in the CSFII data set were used a surrogate for EE.
CSFII records that did not report body weight and those
for children who consumed breast milk or were breast
fed were excluded from their analyses. The Els of
children 9 years of age and older were multiplied by
1.2, the value calculated by Layton (1993) to adjust for
potential bias related to underreporting of dietary
intakes by older children. For infants, El values were
adjusted by subtracting the amount of energy put into
storage by infants as estimated by Scrimshaw et al.
(1996). Self-reported body weights for each individual
from the CSFII data set were used to calculate
nonnormalized (mVday) and normalized (m3/kg-day)
breathing rates, which decreased the variability in the
resulting breathing rate data. Daily breathing rates were
grouped into three-month age groups for infants, one-
year age groups for children 1-18 years of age, and the
age groups recommended by U.S. EPA cancer
guidelines supplement (U.S. EPA, 2005) to receive
greater weighting for mutagenic carcinogens (0 to < 2
years of age, and 2 to < 16 years of age). Data were
also presented for adolescent boys and girls, aged 9-18
years (Table 6-16). For each age and age-gender group,
Arcus-Arth and Blaisdell (2007) calculated the
arithmetic mean, standard error of the mean, percentiles
(50th, 90th, and 95th), geometric mean, standard
deviation, and best-fit parametric models of the
breathing rate distributions. Overall, the C SFII-derived
nonnormalized breathing rates progressively increased
with age from infancy through 18 years of age, while
normalized breathing rates progressively decreased.
The data are presented in Table 6-16 in units of mVday.
There were statistical differences between boys and
girls 9-18 years of age, both for these years combined
(/KO.OO) and for each year of age separately (p<0.05).
The authors reasoned that since the fat-free mass
(basically muscle mass) of boys typically increases
during adolescence, and because fat-free mass is highly
correlated to basal metabolism which accounts for the
majority of EE, nonnormalized breathing rates for
adolescent boys may be expected to increase with
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Chapter 6 - Inhalation Rates
increasing age. Table 6-17 presents the mean and 95th
percentile values for males and females combined,
averaged to fit within the standard EPA age groups.
The CSFII-derived mean breathing rates
derived by Arcus-Arth and Blaisdell (2007) were
compared to the mean breathing rates estimated in
studies that utilized doubly labeled water (DLW)
technique EE data that had been coupled with the
Layton (1993) method. The infants' CSFII-derived
breathing rates were 15 to 27 percent greater than the
comparison DLW EE breathing rates while the
children'sCSFII rates ranged from 23 percent less to 14
percent greater than comparison rates. Thus, the CSFII
and comparison rates were quite similar across age
groups.
An advantage of this study is that it provides
breathing rates specific to narrow age ranges, which can
be useful for assessing inhalation dose during periods of
greatest susceptibility. However, the study is limited by
the potential for misreporting, underestimating, or
overestimating of food intake data in the CSFII. In
addition to underreporting of food intake by
adolescents, El values for younger children may be
under- or overestimated. Overweight children (or their
parents) may also underreport food intakes. In addition,
adolescents who misreport food intake may have also
misreported body weights.
6.3.4 Stifelman, 2007 - Using Doubly-labeled
Water Measurements of Human Energy
Expenditure to Estimate Inhalation Rates
Stifelman (2007) estimated inhalation rates
using DLW energy data. The DLW method administers
two forms of stable isotopically labeled water:
deuterium-labeled (2H20) and 18oxygen-labeled (H2180).
The difference in disappearance rates between the two
isotopes represents the energy expended over a period
of 1-3 half-lives of the labeled water (Stifelman, 2007).
The resulting duration of observation is typically 1-3
weeks, depending on the size and activity level.
The DLW database contains subjects from
areas around the world and represents diversity in
ethnicity, age, activity, body type, and fitness level.
DLW data have been compiled by the Institute of
Medicine (IOM) Panel on Macronutrients and the Food
and Agriculture Organization of the United Nations
(FAO). Stifelman (2007) used the equation of Layton
(1993) to convert the recommended energy levels of
IOM for the active-very active people to their
equivalent inhalation rates. The IOM reports
recommend energy expenditure levels organized by
gender, age and body size (Stifelman, 2007).
The equivalent inhalation rates are shown in
Table 6-18. Shown in Table 6-19 are the mean and 95th
percentile values for the IOM "active" energy level
category, averaged to fit within the standard EPA age
groups. Stifelman (2007) noted that the estimates based
on the DLW are consistent with previous findings of
Layton (1993) and the Exposure Factors Handbook
(U.S. EPA, 1997) and that inhalation rates based on the
IOM active classification are consistent with the mean
inhalation rate in the handbook.
The advantages of this study are that the
inhalation rates were estimated using the DLW data
from a large data set. Stifelman (2007) noted that DLW
methods are advantageous; the data are robust,
measurements are direct and avoid errors associated
with indirect measurements (heart rate), subjects are
free-living, and the period of observation is longer than
what is possible from staged activity measures.
Observations over a longer period of time reduce the
uncertainties associated with using short duration
studies to infer long-term inhalation rates. A limitation
with the study is that the inhalation rates that are
presented are for active/very active persons only.
6.3.5 Key Studies Combined
In order to provide the recommended long-
term inhalation rates shown in Table 6-1, data from the
four key studies were combined. The data from each
study were averaged by gender and grouped according
to the standard U. S. EPA childhood age groups used in
this handbook, when possible. Mean and 95thpercentile
inhalation rate values for the four key studies are shown
in Tables 6-20 and 6-21, respectively.
6.4 RELEVANT INHALATION RATE
STUDIES
6.4.1 International Commission on Radiological
Protection (ICRP), 1981 - Report of the
Task Group on Reference Man
The International Commission on Radiological
Protection (ICRP) (1981) estimated daily inhalation
rates for reference children (10 years old), infants (1
Child-Specific Exposure Factors Handbook
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Chapter 6 - Inhalation Rates
year old), and newborn babies by using a time-activity-
ventilation approach. This approach for estimating an
inhalation rate over a specified period of time was
based on calculating a time weighted average of
inhalation rates associated with physical activities of
varying durations (Table 6-22). ICRP( 1981) compiled
reference values (Table 6-23) of minute
volume/inhalation rates from various literature sources.
ICRP (1981) assumed that the daily activities of a
reference child (10 yrs) consisted of 8 hours of rest and
16 hours of light activities. It was assumed that a day
consisted of 14 hours resting and 10 hours light activity
for an infant (1 year). A newborn's daily activities
consisted of 23 hours resting and 1 hour light activity.
The estimated inhalation rates were 14.8 mVday for
children (age 10 years), 3.76 mVday for infants (age 1
year), and 0.78 mVday for newborns (Table 6-22).
A limitation associated with this study is that
the validity and accuracy of the inhalation rate data
used in the compilation of reference values were not
specified. This introduces some degree of uncertainty
in the results obtained. Also, the approach used
required that assumptions be made regarding the hours
spent by various age/gender cohorts in specific
activities. These assumptions may over/under-estimate
the inhalation rates obtained.
6.4.2 U.S. EPA, 1985 - Development of Statistical
Distributions or Ranges of Standard
Factors Used in Exposure Assessments
The U.S. EPA (1985) compiled measured
values of minute ventilation for various age/gender
cohorts from early studies. The data compiled by the
U.S. EPA (1985) for each age/gender cohorts were
obtained at various activity levels (Table 6-24). These
levels were categorized as light, moderate, or heavy
according to the criteria developed by the U.S. EPA
Office of Environmental Criteria and Assessment for
the Ozone Criteria Document. These criteria were
developed for a reference male adult with a body
weight of 70 kg (U.S. EPA, 1985).
Table 6-24 presents a summary of inhalation
rates by age and activity level. A description of
activities included in each activity level is also
presented in Table 6-24. Table 6-24 indicates that at
rest, the mean inhalation rate for children, ages 6 and 10
years, is 0.4 m3/hr. Table 6-25 presents activity pattern
data aggregated for three microenvironments by activity
level for all age groups. The total average hours spent
indoors was 20.4, outdoors was 1.77, and in a
transportation vehicle was 1.77. Based on the data
presented in Tables 6-24 and 6-25, a daily inhalation
rate was calculated for adults and children by using a
time-activity-ventilation approach. These data are
presented for children in Table 6-26. The average daily
inhalation rate for 6 and 10 years old children is 16.74
and 21.02 mVday, respectively.
Limitations associated with this study are its
age and that many of the values used in the data
compilation were from early studies. The accuracy
and/or validity of the values used and data collection
method were not presented in U.S. EPA (1985). This
introduces uncertainty in the results obtained. An
advantage of this study is that the data are actual
measurement data for a large number of children.
6.4.3 Linn et al., 1992 - Documentation of
Activity Patterns in "High-risk" Groups
Exposed to Ozone in the Los Angeles Area
Linn et al. (1992) conducted a study that
estimated the inhalation rates for "high-risk"
subpopulation groups exposed to ozone in their daily
activities in the Los Angeles area. The population
surveyed consisted of several panels of children. The
panels included Panel 2: 17 healthy elementary school
students (5 males and 12 females, ages 10-12 years);
Panel 3:19 healthy high school students (7 males and
12 females, ages 13-17 years); Panel 6: 13 young
asthmatics (7 males and 6 females, ages 11-16 years).
An initial calibration test was conducted,
followed by a training session. Finally, a field study
that involved the subjects collecting their own heart
rates and diary data was conducted. During the
calibration tests, ventilation rate (VR), breathing rate,
and heart rate (HR) were measured simultaneously at
each exercise level. From the calibration data an
equation was developed using linear regression analysis
to predict VR from measured HR.
In the field study, each subject recorded in
diaries their daily activities, change in locations
(indoors, outdoors, or in a vehicle), self-estimated
breathing rates during each activity/location, and time
spent at each activity/location. Healthy subjects
recorded their HR once every 60 seconds using a Heart
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Chapter 6 - Inhalation Rates
Watch, an automated system consisting of a transmitter
and receiver worn on the body. Asthmatic subjects
recorded their diary information once every hour.
Subjective breathing rates were defined as slow
(walking at their normal pace), medium (faster than
normal walking), and fast (running or similarly
strenuous exercise). Table 6-27 presents the calibration
and field protocols for self-monitoring of activities for
each subject panel.
Table 6-28 presents the mean, 99th percentile,
and mean VR at each subjective activity level (slow,
medium, fast). The mean and 99th percentile VR were
derived from all HR recordings that appeared to be
valid, without considering the diary data. Each of the
three activity levels was determined from both the
concurrent diary data and HR recordings by direct
calculation or regression. The authors reported that the
diary data showed that on a typical day, most
individuals spent most of their time indoors at slow
activity level. During slow activity, asthmatic subjects
had higher VRs than healthy subjects (Table 6-28). The
authors also reported that in every panel the predicted
VR correlated significantly with the subjective
estimates of activity levels.
A limitation of this study is that calibration
data may overestimate the predictive power of HR
during actual field monitoring. The wide variety of
exercises in everyday activities may result in greater
variation of the VR-HR relationship than was
calibrated. Another limitation is the small sample size
of each subpopulation surveyed. An advantage of this
study is that diary data can provide rough estimates of
ventilation patterns which are useful in exposure
assessments. Another advantage is that inhalation rates
were presented for both healthy and asthmatic children.
6.4.4 Spier et aL, 1992 - Activity Patterns in
Elementary and High School Students
Exposed to Oxidant Pollution
Spier et al. (1992) investigated the activity
patterns of 17 elementary school students (10-12 years
old) and 19 high school students (13-17 years old) in
suburban Los Angeles from late September to October
(oxidant pollution season). Calibration tests were
conducted in supervised outdoor exercise sessions. The
exercise sessions consisted of 5 minutes each of rest,
slow walking, jogging, and fast walking. HR and VR
were measured during the last 2 minutes of each
exercise. Individual VR and HR relationships for each
individual were determined by fitting a regression line
to HR values and log VR values. Each subj ect recorded
their daily activities, changes in location, and breathing
rates in diaries for 3 consecutive days. Self-estimated
breathing rates were recorded as slow (slow walking),
medium (walking faster than normal), and fast
(running). HR was recorded once per minute during the
3 days using a Heart Watch. VR values for each self-
estimated breathing rate and activity type were
estimated from the HR recordings by employing the VR
and HR equation obtained from the calibration tests.
The data presented in Table 6-29 represent HR
distribution patterns and corresponding predicted VR
for each age group during hours spent awake. At the
same self-reported activity levels for both age groups,
inhalation rates were higher for outdoor activities than
for indoor activities. The total number of hours spent
indoors was higher for high school students
(21.2 hours) than for elementary school students (19.6
hours). The converse was true for outdoor activities:
2.7 hours for high school students and 4.4 hours for
elementary school students (Table 6-30).
A limitation of this study is the small sample
size. The results may not be representative of all
children in these age groups. Another limitation is that
the accuracy of the self-estimated breathing rates
reported by younger age groups is uncertain. This may
affect the validity of the data set generated. An
advantage of this study is that inhalation rates were
determined for children and adolescents. These data
are useful in estimating exposure for the younger
population.
6.4.5 Adams, 1993 - Measurement of Breathing
Rate and Volume in Routinely Performed
Daily Activities, Final Report
Adams (1993) conducted research to
accomplish two main objectives: (1) identification of
mean and ranges of inhalation rates for various
age/gender cohorts and specific activities, and (2)
derivation of simple linear and multiple regression
equations that could be used to predict inhalation rates
through other measured variables: breathing frequency
and oxygen consumption. A total of 160 subjects
participated in the primary study. For children, there
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Chapter 6 - Inhalation Rates
were two age-dependent groups: children 6 to 12.9
years old and adolescents 13 to 18.9 years old. An
additional 40 children from 6 to 12.9 years old and
12 young children from 3 to 5.9 years old were
identified as subjects for pilot testing purposes.
Resting protocols conducted in the laboratory
for all age groups consisted of three phases (25 minutes
each) of lying, sitting, and standing. The phases were
categorized as resting and sedentary activities. Two
active protocols— moderate (walking) and heavy
(jogging/ running) phases— were performed on a
treadmill over a progressive continuum of intensity
levels made up of 6-minute intervals at three speeds
ranging from slow to moderately fast. All protocols
involved measuring VR, HR, fB (breathing frequency),
and V02 (oxygen consumption). Measurements were
taken in the last 5 minutes of each phase of the resting
protocol and the last 3 minutes of the 6-minute intervals
at each speed designated in the active protocols.
In the field, all children completed
spontaneous play protocols; most protocols were
conducted for 30 minutes. All the active field protocols
were conducted twice. Results are shown in Tables 6-
31 and 6-32.
During all activities in either the laboratory or
field protocols, VR for the children's group revealed no
significant gender differences. Therefore, VR data
presented in Tables 6-33 and 6-34 were categorized by
activity type (lying, sitting, standing, walking, and
running) for young children and children without regard
to gender. These categorized data from Tables 6-33
and 6-32 are summarized as inhalation rates in Tables
6-31 and 6-32. The laboratory protocols are shown in
Table 6-31. Table 6-32 presents the mean inhalation
rates by group and for moderate activity levels in field
protocols. Data were not provided for the light and
sedentary activities because the group did not perform
for this protocol or the number of subjects was too
small for appropriate comparisons. Accurate
predictions of inhalation rates across all population
groups and activity types were obtained by including
body surface area (S A), HR, and breathing frequency in
multiple regression analysis (Adams, 1993). Adams
(1993) calculated SA from measured height and body
weight using the equation:
SA = Height(0725) x Weight(0425) x 71.84 (Eqn. 6-3)
A limitation associated with this study is that
the population does not represent the general U.S.
population. Also, the classification of activity types
(i.e., laboratory and field protocols) into activity levels
may bias the inhalation rates obtained for various
age/gender cohorts. The estimated rates were based on
short-term data and may not reflect long-term patterns.
6.4.6 Layton, 1993 - Metabolically Consistent
Breathing Rates for Use in Dose
Assessments
Layton (1993) presented a method for
estimating metabolically consistent inhalation rates for
use in quantitative dose assessments of airborne
radionuclides. Generally, the approach for estimating
the breathing rate for a specified time frame was to
calculate a time-weighted-average of ventilation rates
associated with physical activities of varying durations.
However, in this study, breathing rates were calculated
on the basis of oxygen consumption associated with
energy expenditures for short (hours) and long (weeks
and months) periods of time, using the following
general equation to calculate energy-dependent
inhalation rates:
VE =ExHxVQ
(Eqn. 6-4)
where:
VE =
E =
H =
VQ =
ventilation rate (mVmin or
mVday);
energy expenditure rate;
[kilojoules/minute (KJ/min) or
megajoules/hour (MJ/hr)];
volume of oxygen (at standard
temperature and pressure, dry air
consumed in the production of 1
kilojoule (KJ) of energy expended
(L/KJ or m3/MJ)); and
ventilatory equivalent (ratio of minute
volume (mVmin) to oxygen uptake
(mVmin)) unitless.
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Layton (1993) used two alternative approaches
to estimate daily chronic (long term) inhalation rates for
different age/gender cohorts of the U.S. population
using this methodology.
First Approach
Inhalation rates were estimated by multiplying
average daily food energy intakes for different
age/gender cohorts, H, and VQ, as shown in the
equation above. The average food energy intake data
(Table 6-35) are based on approximately 30,000
individuals and were obtained from the 1977-78
USDA-NFCS. The food energy intakes were adjusted
upwards by a constant factor of 1.2 for all individuals
9 years and older. This factor compensated for a
consistent bias in USDA-NFCS that was attributed to
under-reporting of the foods consumed or the methods
used to ascertain dietary intakes. Layton (1993) used a
weighted average oxygen uptake of 0.05 L 02/KJ which
was determined from data reported in the 1977-78
USDA-NFCS and the second NHANES (NHANESII).
The survey sample for NHANES II was approximately
20,000 participants. A VQ of 27 used in the
calculations was calculated as the geometric mean of
VQ data that were obtained from several studies.
The inhalation rate estimation techniques are
shown in footnote (a) of Table 6-36. Table 6-37
presents the daily inhalation rate for each age/gender
cohort. The highest daily inhalation rates were 10
mVday for children between the ages of 6 and 8 years,
17 mVday for males between 15 and 18 years, and 13
mVday for females between 9 and 11 years. Inhalation
rates were also calculated for active and inactive
periods for the various age/gender cohorts.
The inhalation rate for inactive periods was
estimated by multiplying the BMR times H times VQ.
BMR was defined as "the minimum amount of energy
required to support basic cellular respiration while at
rest and not actively digesting food" (Layton, 1993).
The inhalation rate for active periods was calculated by
multiplying the inactive inhalation rate by the ratio of
the rate of energy expenditure during active hours to the
estimated BMR. This ratio is presented as F in Table 6-
36. These data for active and inactive inhalation rates
are also presented in Table 6-36. For children, inactive
and active inhalation rates ranged from 2.35 to 5.95
mVday and from 6.35 to 13.09 mVday, respectively.
Second Approach
Inhalation rates were calculated as the product
of the BMR of the population cohorts, the ratio of total
daily energy expenditure to daily BMR, H, and VQ.
The BMR data obtained from the literature were
statistically analyzed, and regression equations were
developed to predict BMR from body weights of
various age/gender cohorts. The statistical data used to
develop the regression equations are presented in Table
6-37. The data obtained from the second approach are
presented in Table 6-38. Inhalation rates for children
(6 months -10 years) ranged from 7.3 to 9.3 mVday for
male and 5.6 to 8.6 mVday for female children; for
older children (10 to 18 years), inhalation rates were 15
mVday for males and 12 mVday for females. These
rates are similar to the daily inhalation rates obtained
using the first approach. Also, the inactive inhalation
rates obtained from the first approach are lower than the
inhalation rates obtained using the second approach.
This may be attributed to the BMR multiplier employed
in the equation of the second approach to calculate
inhalation rates.
Inhalation rates were also obtained for short-
term exposures for various age/gender cohorts and five
energy-expenditure categories (rest, sedentary, light,
moderate, and heavy). BMRs were multiplied by the
product of the metabolic equivalent, H, and VQ. The
data obtained for short-term exposures are presented in
Table 6-39.
This study obtained similar results using two
different approaches. The maj or strengths of this study
are that it estimates inhalation rates in different age
groups and that the populations are large. Explanations
for differences in results due to metabolic
measurements, reported diet, or activity patterns are
supported by observations reported by other
investigators in other studies. Major limitations of this
study are (1) the estimated activity pattern levels are
somewhat subjective; (2) the explanation that activity
pattern differences are responsible for the lower level
obtained with the metabolic approach (25 %) compared
to the activity pattern approach is not well supported by
the data; and (3) different populations were used in
each approach, which may have introduced error.
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Chapter 6 - Inhalation Rates
6.4.7 Rusconi et al., 1994 - Reference Values for
Respiratory Rate in the First 3 Years of
Life
Rusconi et al. (1994) examined a large number
of infants and children in Milano, Italy in order to
determine the reference values for respiratory rate in
children aged 15 days to 3 years. A total of 618 infants
and children (336 males and 282 females) who did not
have respiratory infections or any severe disease were
included in the study. Of the 618, a total of 309 were in
good health and were observed in day care centers,
while the remaining 309 were seen in hospitals or as
outpatients.
Respiratory rates were recorded twice, 30 to
60 minutes apart, listening to breath sounds for 60
seconds with a stethoscope, when the child was awake
and calm and when the child was sleeping quietly (sleep
not associated with any spontaneous movement,
including eye movements or vocalizations) (Table 6-
40). The children were assessed for one year in order to
determine the repeatability of the recordings, to
compare respiratory rate counts obtained by stethoscope
and by observation, and to construct reference
percentile curves by age in a large number of subjects.
The authors plotted the differences between
respiratory rate counts determined by stethoscope at 30-
to 60-minute intervals against their mean count in
waking and sleeping subjects. The standard deviation
of the differences between the two counts was 2.5 and
1.7 breaths/minute, respectively, for waking and
sleeping children. This standard deviation yielded 95%
repeatability coefficients of 4.9 breaths/minute when the
infants and children were awake and 3.3 breaths/minute
when they were asleep.
In both waking and sleeping states, the
respiratory rate counts determined by stethoscope were
found to be higher than those obtained by observation.
The mean difference was 2.6 and 1.8 breaths per
minute, respectively, in waking and sleeping states. The
mean respiratory rate counts were significantly higher
in infants and children at all ages when awake and calm
than when asleep. A decrease in respiratory rate with
increasing age was seen in waking and sleeping infants
and children. A scatter diagram of respiratory rate
counts by age in waking and sleeping subjects showed
that the pattern of respiratory rate decline with age was
similar in both states, but it was much faster in the first
few months of life. The authors constructed centile
curves by first log-transforming the data and then
applying a second degree polynomial curve, which
allowed excellent fitting to observed data. Figures 6-1
and 6-2 show smoothed percentiles by age in waking
and sleeping subjects, respectively. The variability of
respiratory rate among subjects was higher in the first
few months of life, which may be attributable to
biological events that occur during these months, such
as maturation of the neurologic control of breathing and
changes in lung and chest wall compliance and lung
volumes.
An advantage of this study is that it provides
distribution data for respiratory rate for children from
infancy (less than 2 months) to 36 months old. These
data are not U.S. data; U.S. distributions were not
available. Although, there is no reason to believe that
the respiratory rates for Italian children would be
different from that of U.S. children, this study only
provided data for a narrow range of activities.
6.4.8 Price et al., 2003 - Modeling Interindividual
Variation in Physiological Factors Used in
PBPK Models of Humans
Price et al. (2003) developed a database of
values for physiological parameters often used in
physiologically-based pharmacokinetic models (PBPK).
The database consisted of approximately 31,000
records containing information on volumes and masses
of selected organs and tissues, blood flows for the organ
and tissues, and total resting cardiac output and average
inhalation rates. Records were created based on data
from the NHANES III survey.
The study authors note that the database
provides a source of data for human physiological
parameters were the parameter values for an individual
are correlated with one another and capture
interindividual variation in populations of a specific
gender, race, and age range. A computer program,
Physiological Parameters for PBPK Modeling (PPPM
or P3M), which is publicly available (The Lifeline
Group, 2007), was also developed to randomly retrieve
records from the database for groups of individuals of
specified age ranges, gender, and ethnicities. Price et
al. (2003) recommends that output sets be used as
inputs to Monte Carlo-based PBPK models of
interindividual variation in dose.
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Chapter 6 - Inhalation Rates
6.5
REFERENCES FOR CHAPTER 6
Adams, W.C. (1993) Measurement of breathing rate
and volume in routinely performed daily
activities, Final Report. California Air
Resources Board (CARB) Contract No.
A033-205June 1993. 185 pgs.
Arcus-Arth, A. and Blaisdell, R. J. (2007) Statistical
distributions of daily breathing rates for
narrow age groups of infants and children.
Risk Anal 27(1):97-110
Brochu, P.; Ducre-Robitaille, J.; Brodeur, J. (2006)
Physiological daily inhalation rates for free-
living individuals aged 1 month to 96 years,
using data from doubly labeled water
measurements: a proposal for air quality
criteria, standard calculations and health risk
assessment. Hum Ecol Risk Assess 12:675-
701.
FASEB/LSRO (Federation of American Societies for
Experimental Biology, Life Sciences Research
Office). (1995) Joint policy on variance
estimation and statistical standards on
NHANES III and CSFII reports (Appendix
III). In: Third Report on Nutrition
Monitoringin the United States. Prepared for
the Interagency Board for Nutrition
Monitoring and Related Research.
Washington, DC: U.S. Government Printing
Office.
Foos, B., Sonwane, B. (2008) Overview: workshop on
children's inhalation dosimetry and health
effects for risk assessment. JToxicol Environ
Health Part A 71(3): 147-148.
Foos, B.; Marty, M.; Schwartz, J.; Bennett, W.;
Moya, J.; Jarabek, A; Salmon, A. (2008)
Focusing on children's inhalation dosimetry
and health effects for risk assessment: an
introduction. J Toxicol Environ Health Part A
71(3):149-165.
International Commission on Radiological Protection.
(1981) Report of the task group on reference
man. New York: Pergammon Press.
Layton, D.W. (1993) Metabolically consistent
breathing rates for use in dose assessments.
Health Phys 64(l):23-36.
Linn, W.S.; Shamoo, D.A.; Hackney, J.D. (1992)
Documentation of activity patterns in "high-
risk" groups exposed to ozone in the Los
Angeles area. In: Proceedings of the
Second EPA/A WMA Conference on
Tropospheric Ozone, Atlanta, Nov. 1991.
pp. 701-712. Air and Waste Management
Assoc., Pittsburgh, PA.
Price, P.; Conolly, R.; Chaisson, C.; Gross, E.;
Young, J.; Mathis, E.; Tedder, D. (2003)
Modeling interindividual variation in
physiological factors used in PBPK models
of humans. Crit Rev Toxicol 33 (5):469-
503.
Rusconi, F.; Castagneto, M.; Garliardi, L.; Leo, G.;
Pellegatta, A.; Porta, N.; Razon, S.; Braga, M.
(1994) Reference values for respiratory rate in
the first 3 years of life. Pediatrics 94(3):350-
355.
Scrimshaw, N. S.; Waterlow, J. C.; Schurch, B. (Eds.).
(1996) Energy and Protein Requirements.
Proceedings of an International Dietary and
Energy Consultancy Group Workshop; 1994
Oct 31-Nov 4; London, UK: Stockton Press.
Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson, T.R.;
Linn, W.S.; Hackney, J.D. (1992) Activity
patterns in elementary and high school
students exposed to oxidant pollution. J Exp
Anal Environ Epidemiol 2(3):277-293.
Stifelman, M. (2007) Using doubly-labeled water
measurements of human energy expenditure to
estimate inhalation rates. Sci Total Environ
373:585-590.
The Lifeline Group. (2007) Physiological parameters
for PBPK modeling™ version 1.3 (P3M™).
Accessed May 2007. Available at:
http://www.thelifelinegroup.org/p3iii/
U.S. EPA. (1985) Development of statistical
distributions or ranges of standard factors used
in exposure assessments. Washington, DC:
Office of Health and Environmental
Assessment; EPA Report No.
EPA 600/8-85-010. Available from: NTIS,
Springfield, VA; PB85-242667.
U.S. EPA. (1992) Guidelines for exposure
assessment. Washington, DC: Office of
Child-Specific Exposure Factors Handbook
September 2008
Page
6-15
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Chapter 6 - Inhalation Rates
Research and Development, Office of Health
and Environmental Assessments.
U.S. EPA. (1994) Methods for derivation of inhalation
reference concentrations and application of
inhalation dosimetry. Washington, DC:
Office of Health and Environmental
Assessment. EPA/600/8-90/066F.
U.S. EPA. (1997) Exposure Factors Handbook.
Washington, DC: Office of Research and
Development, Office of Health and
Environmental Assessment.
U.S. EPA. (2005). Supplemental guidance for
assessing susceptibility from early-life
exposure to carcinogens. Washington, DC:
Risk Assessment Forum. EPA/630/R-
03/003F.
U.S. EPA. (2006) Metabolically-derived human
ventilation rates: A revised approach based
upon oxygen consumption rates. Washington,
DC: National Center for Environmental
Assessment. External Review Draft. Prepared
forUSEPA/ORD, ContractNo. EP-C-04-027.
U.S. EPA. (2008) Risk Assessment Guidance for
Superfund: Volume I: Human Health
Evaluation Manual (Part F, Supplemental
Guidance for Inhalation Risk Assessment).
Washington, DC: Office of Superfund
Remediation and Technology Innovation.
Peer Review Draft. Prepared for USEPA,
ContractNo. 68-W-01-05.
WHO. (1986) Principles for evaluating health risks
from chemicals during infancy and early
childhood: the need for a special approach.
Environmental Health Criteria 59, World
Health Organization, International Programme
on Chemical Safety.
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Chapter 6 - Inhalation Rates
Table 6-4. Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less
Physiological Daily Inhalation Rates6
Group N Body Weight (kg) Mean±SD
WOUp 1N MeaniSD
(mVday) (m3/kg-day)
21 days (3 weeks) IS3-' 1.2 ±0.2 0.85±0.17f 0.74±0.09f
32 days (~ 1 month) 10M 4.7 ± 0.7 2.45 ± 0.59s 0.53 ± 0.10s
33 days (~ 1 month) 10'-" 4.8 ± 0.3 2.99 ± 0.47s 0.62 ±0.09S
1 Formula-fed infants.
b Breast-fed infants.
c Healthy infants with very low birth weight.
d Infants evaluated as being clinically healthy and neither underweight or overweight.
e Physiological daily inhalation rates were calculated using the following equation: (TDEE +
ECG)*H*(VE/V02)*10-3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily
energy expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day).
f TDEEs based on nutritional balance measurements during 3-day periods.
8 TDEEs based on 2H2O and H218O disappearance rates from urine
N = Number of individuals.
SD = Standard deviation.
Source: Brochu et al., 2006.
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Chapter 6 - Inhalation Rates
Table 6-5. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living Normal-weight
Males and Females Aged 2.6 months to 23 years
Body Physiological Daily Inhalation Rates'" (mVday)
Age Group Weighf(kg) ...
, . v N f, Percentile0
±SD 5th 10th 25th 50th 75th 90th
95th
99th
Males
0.22to<0.5 32 6.7±1.0 3.38±0.72 2.19 2.46 2.89 3.38 3.87 4.30
0.5to
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Chapter 6 - Inhalation Rates
Table 6-6. Mean and 95th Percentile Inhalation Rate Values (mVday) for Free-living Normal-weight
Males, Females, and Males and Females Combined.
Age Group1
N
Mean
95th
Males
3 to <6 months'1
6 to <12 months
1 to <2 years
32
40
35
3.38
4.42
5.12
4.57
5.51
6.56
Females
3 to <6 months'1
6 to <12 months
1 to <2 years
53
63
66
3.26
3.96
4.78
4.36
5.14
6.36
Males and Females Combined
3 to <6 months'1
6 to <12 months
1 to <2 years
1 No other age groups from
b Age group from Brochu ei
N = Number of individuals.
Source: Brochu et al., 2006.
85
103
101
Table 6-5 (Brochu et al., 2006) fit into the
al. (2006) was 2.6 to <6 months.
3.32
4.09
4.95
U.S. EPA age groupings.
4.47
5.53
6.46
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Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living Normal-weight and Overweight/obese
Males and Females Aged 4 to 18 years
Age Group
(years)
BodyWeight'(kg)
Mean ± SD
Physiological Daily Inhalation Rates" (mVday)
Mean ± SD
Perc entile0
5th
10th
25th
50th
75th
90th
95th
99th
Males - Normal-weight
4to<5
5.1 to <
9.1 to <
77
52
36
19.0 ± 1.9
22.6 ±3.5
41.4 ± 12.1
7.90 ± 0.97
9.14 ± 1.44
13.69 ±3.95
6.31
6.77
7.19
6.66
7.29
8.63
7.25
8.17
11.02
7.90
9.14
13.69
8.56
10.11
16.35
9.15
10.99
18.75
9.50 10.16
11.51 12.49
20.19 22.88
Males - Overweight/obese
4to<5
5.1 to-
9.1 to-
54
40
33
26.5 ±4.9
32.5 ±9.2
55.8± 10.8
9.59 ± 1.26
10.88 ±2.49
14.52 ± 1.98
7.52
6.78
11.25
7.98
7.69
11.98
8.74
9.20
13.18
9.59
10.88
14.52
10.44
12.56
15.85
11.21
14.07
17.06
11.66
14.98
17.78
12.52
16.68
19.13
Females - Normal-weight
4to<5
5.1 to-
9.1 to-
82
151
124
18.7 ±2.0
25.5 ±4.1
42.7± 11.1
7.41 ±0.91
9.39 ± 1.62
12.04 ±2.86
5.92
6.72
7.34
6.25
7.31
8.38
6.80
8.30
10.11
7.41
9.39
12.04
8.02
10.48
13.97
8.57
11.47
15.70
8.90
12.05
16.74
9.52
13.16
18.68
Females - Overweight/obese
4to<5
5.1 to-
9.1 to <
56
26.1 ±5.5
34.6 ±9.9
59.2 ± 12.8
8.70 ± 1.13
10.55 ±2.23
14.27 ±2.70
6.84
6.88
9.83
7.26
7.69
10.81
7.94
9.05
12.45
8.70
10.55
14.27
9.47
12.06
16.09
10.15
13.41
17.73
10.56 11.33
14.22 15.75
18.71 20.55
N
SD
Measured body weight. Normal-weight and overweight/obese males defined according to the body mass index (BMI) cut-offs.
Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(VE/VO2)* 10"3, where H =
0.21 L of O2/Kcal, V/VO2= 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) and ECG = stored daily energy
cost for growth (kcal/day).
Percentiles based on a normal distribution assumption for age groups.
= Number of individuals.
= Standard deviation.
Source: Brochu et al.. 2006.
Page
6-20
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight (mVkg-day) for Free-living
Normal-weight Males and Females Aged 2.6 months to 23 years
Age(
(ye
ars) Mean ± S
Physiological Daily Inhalation Rates
(mVkg-day)
Percentileb
D
5th
10th
25th
50th
75th
90th
95th
99th
Males
0.22 to <0
0.5to
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-9.
Distribution Percentiles of Physiological Daily Inhalation Rates (m3/kg-day) for Free-living Normal-weight and
Overweight/obese Males and Females Aged 4 to 18 years
Physiological Daily Inhalation Rates"
(m3/k
g-day)
Age Group (years) Percentileb
Mean±SD 5th 1()th 25th 5Qto
75*
90*
95th
99th
Males - Normal-weight
4to<5.1
5.1to<9.1
9.1to<18.1
0.42 ±0.04 0.35 0.36 0.39 0.42
0.41 ±0.06 0.31 0.34 0.37 0.41
0.33 ±0.05 0.26 0.27 0.30 0.33
0.45
0.45
0.37
0.47
0.48
0.40
0.49
0.50
0.41
0
0
0
52
54
45
Males - Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
0.37 ±0.04 0.30 0.31 0.34 0.37
0.35 ±0.08 0.22 0.25 0.29 0.35
0.27 ±0.04 0.20 0.22 0.24 0.27
0.40
0.40
0.29
0.42
0.45
0.32
0.44
0.47
0.33
0
0
0
47
53
36
Females - Normal-weight
4to<5.1
5.1to<9.1
9.1to<18.1
0.40 ±0.05 0.32 0.34 0.37 0.40
0.37 ±0.06 0.27 0.29 0.33 0.37
0.29 ±0.06 0.20 0.22 0.25 0.29
0.43
0.41
0.33
0.46
0.45
0.36
0.48
0.47
0.38
0
0
0
51
52
42
Females - Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
0.34 ±0.04 0.27 0.28 0.31 0.34
0.32 ±0.07 0.21 0.23 0.27 0.32
0.25 ±0.05 0.17 0.18 0.21 0.25
0.37
0.36
0.28
0.40
0.40
0.31
0.41
0.43
0.33
0
0
0
44
47
36
" Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(VE/VO2)* 10"3,
where H = 0.21 L of O2/Kcal, V/VO2= 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) and ECG =
stored daily energy cost for growth (kcal/day).
b Percentiles based on a normal distribution assumption for age groups.
SD = Standard deviation.
Source: Brochu et al., 2006.
Page
6-22
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-10. Descriptive Statistics
for Daily Average Inhalation Rate in Males, by Age Category'
Daily Average Inhalation Rate, Unadjusted for Body Weight
(mVday)
Age Group
Birth to <1 year
lto<
2to<
2 years
3 years
3 to <6 years
6to<
11 to
16 to
1 1 years
<16 years
<21 years
Age Group
Birth to <1 year
1 to<
2to<
2 years
3 years
3 to <6 years
6to<
11 to
16 to
N
BW
11 years
<16 years
<21 years
N
419
308
261
540
940
1337
1241
N
419
308
261
540
940
1337
1241
Mean
8.76
13.49
13.23
12.65
13.42
15.32
17.22
Mean
1.09
1.19
0.95
0.70
0.44
0.29
0.23
5th
4.77
9.73
9.45
10.42
10.08
11.41
12.60
5th
0.91
0.96
0.78
0.52
0.32
0.21
0.17
10th
5.70
10.41
10.20
10.87
10.69
12.11
13.41
Daily Average
10th
0.94
1.02
0.82
0.56
0.34
0.22
0.18
25th
7.16
11.65
11.43
11.40
11.73
13.27
14.48
Percentiles
50th
8.70
13.11
13.19
12.58
13.09
14.79
16.63
75th
10.43
15.02
14.49
13.64
14.73
16.81
19.16
90th
11.93
17.03
16.27
14.63
16.56
19.54
21.94
95th
12.69
17.89
17.71
15.41
17.72
21.21
23.38
Maximum
17.05
24.24
28.17
19.52
24.97
28.54
39.21
Inhalation Rate, Adjusted for Body Weight
(m3/day-kg)
25th
1.00
1.09
0.87
0.61
0.38
0.25
0.20
Percentiles
50th
1.09
1.17
0.94
0.69
0.43
0.28
0.23
75th
1.16
1.26
1.01
0.78
0.50
0.32
0.25
90th
1.26
1.37
1.09
0.87
0.55
0.36
0.28
95th
1.29
1.48
1.13
0.92
0.58
0.38
0.30
Individual daily averages are weighted by their 4-year sampling weights as assigned within NHANES 1999-2002 when
the statistics in this table. Inhalation rate was estimated using a multiple linear regression model.
= Number of individuals.
Maximum
1.48
1.73
1.36
1.08
0.81
0.51
0.40
calculating
= Body weight.
Source: U.S. EPA,
2006.
Child-Specific Exposure Factors Handbook
September 2008
Page
6-23
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-11. Descriptive Statistics for Daily Average Inhalation Rate in Females, by A
je Category
»
Daily Average Inhalation Rate, Unadjusted for Body Weight
(mVday)
Age Group
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
N
415
245
255
543
894
1,451
1,182
Mean
8.53
13.31
12.74
12.16
12.41
13.44
13.59
5th
4.84
9.08
8.91
9.87
9.99
10.47
9.86
10th
5.48
10.12
10.07
10.38
10.35
11.11
10.61
25th
6.83
11.24
11.38
11.20
11.01
12.04
11.78
Percentiles
50th
8.41
13.03
12.60
12.02
11.95
13.08
13.20
75th
9.78
14.64
13.96
13.01
13.42
14.54
15.02
90th
11.65
17.45
15.58
14.03
15.13
16.25
17.12
95th
12.66
18.62
16.37
14.93
16.34
17.41
18.29
Maximum
26.26
24.77
23.01
19.74
20.82
26.58
30.11
Daily Average Inhalation Rate, Adjusted for Body Weight
(m3/day-kg)
Age Group
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
N
415
245
255
543
894
1,451
1,182
Mean
1.14
1.20
0.96
0.69
0.43
0.25
0.21
5th
0.91
0.98
0.82
0.48
0.28
0.19
0.16
10th
0.97
1.01
0.84
0.54
0.31
0.20
0.17
25th
1.04
1.10
0.89
0.60
0.36
0.22
0.19
a Individual daily averages are weighted by their 4-year sampling weights
the statistics in this table. Inhalation rate was estimated using a multiple
N = Number of individuals.
Source: U.S. EPA,
2006.
Percentiles
50th
1.13
1.18
0.96
0.68
0.43
0.25
0.21
75th
1.24
1.30
1.01
0.77
0.49
0.28
0.24
90th
1.33
1.41
1.07
0.88
0.55
0.31
0.27
95th
1.38
1.47
1.11
0.92
0.58
0.34
0.28
as assigned within NHANES 1999-2002 when
linear regression model.
Maximum
1.60
1.73
1.23
1.12
0.75
0.47
0.36
calculating
Page
6-24
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-12. Mean anc
Age Group"
95th Percentile Inhalation Rate Values (mVday) for Males, Females and
Males and Females Combined
N
Mean
95th
Males
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1,337
1,241
8.76
13.49
13.23
12.65
16.42
15.32
17.22
12.69
17.89
17.71
15.41
17.72
21.21
23.38
Females
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
415
245
255
543
894
1,451
1,182
8.53
13.31
12.74
12.16
12.41
13.44
13.59
12.66
18.62
16.37
14.93
16.34
17.41
18.29
Males and Females Combined
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
1 No other age groups from
N = Number of individuals.
Source: U.S. EPA, 2006.
834
553
516
1,083
1,834
2,788
2423
Tables 6-9 and 6-10 (U.S. EPA,
8.65
13.40
12.99
12.41
12.92
14.38
15.41
2006) fit into the EPA age
12.68
18.26
17.04
15.17
17.03
19.31
20.84
groupings.
Child-Specific Exposure Factors Handbook
September 2008
Page
6-25
-------
i
s
oo
Table 6-13. Descriptive Statistics for Average Ventilation Rate" While Performing Activities Within the Specified Activity Category, for
Males by Age Category
Age Group
Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
Percentiles
5th 10* 25th 50* 75th 90* 95th
Vlaximum
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
Mean
Percentiles
5th
10*
25th
50*
75th
90*
95*
Maximum
Sleep or nap (Activity ID = 14500)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
419 3.08E-03 1.66E-03 1.91E-03 2.45E-03 3.00E-03 3.68E-03 4.35E-03 4.77E-03
308 4.50E-03 3.11E-03 3.27E-03 3.78E-03 4.35E-03 4.95E-03 5.90E-03 6.44E-03
261 4.61E-03 3.01E-03 3.36E-03 3.94E-03 4.49E-03 5.21E-03 6.05E-03 6.73E-03
540 4.36E-03 3.06E-03 3.30E-03 3.76E-03 4.29E-03 4.86E-03 5.54E-03 5.92E-03
940 4.61E-03 3.14E-03 3.39E-03 3.83E-03 4.46E-03 5.21E-03 6.01E-03 6.54E-03
1,337 5.26E-03 3.53E-03 3.78E-03 4.34E-03 5.06E-03 5.91E-03 6.94E-03 7.81E-03
1,241 5.31E-03 3.55E-03 3.85E-03 4.35E-03 5.15E-03 6.09E-03 6.92E-03 7.60E-03
7.19E-03
l.OOE-02
8.96E-03
7.67E-03
9.94E-03
1.15E-02
1.28E-02
3.85E-04
3.95E-04
3.30E-04
2.43E-04
1.51E-04
9.80E-05
7.10E-05
2.81E-04
2.95E-04
2.48E-04
1.60E-04
1.02E-04
6.70E-05
4.70E-05
3.01E-04
3.13E-04
2.60E-04
1.74E-04
1.09E-04
720E-05
5.20E-05
3.37E-04
3.45E-04
2.89E-04
1.98E-04
1.25E-04
8.10E-05
6.10E-05
3.80E-04
3.84E-04
3.26E-04
2.37E-04
1.48E-04
9.40E-05
6.90E-05
4.27E-04
4.41E-04
3.62E-04
2.79E-04
1.74E-04
1.10E-04
8.00E-05
4.65E-04
4.91E-04
4.05E-04
3.14E-04
2.00E-04
1.29E-04
9.00E-05
5.03E-04
5.24E-04
4.42E-04
3.50E-04
2.15E-04
1.41E-04
9.80E-05
6.66E-04
6.26E-04
5.38E-04
4.84E-04
3.02E-04
2.08E-04
1.47E-04
Sedentary & Passive Activities (METS s 1.5 - Includes Sleep or Nap)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419 3.18E-03 1.74E-03 1.99E-03 2.50E-03 3.10E-03 3.80E-03 4.40E-03 4.88E-03
308 4.62E-03 3.17E-03 3.50E-03 3.91E-03 4.49E-03 5.03E-03 5.95E-03 6.44E-03
261 4.79E-03 3.25E-03 3.66E-03 4.10E-03 4.69E-03 5.35E-03 6.05E-03 6.71E-03
540 4.58E-03 3.47E-03 3.63E-03 4.07E-03 4.56E-03 5.03E-03 5.58E-03 5.82E-03
940 4.87E-03 3.55E-03 3.78E-03 4.18E-03 4.72E-03 5.40E-03 6.03E-03 6.58E-03
1,337 5.64E-03 4.03E-03 4.30E-03 4.79E-03 5.43E-03 6.26E-03 7.20E-03 787E-03
1,241 5.76E-03 4.17E-03 4.42E-03 4.93E-03 5.60E-03 6.43E-03 7.15E-03 776E-03
7.09E-03
9.91E-03
9.09E-03
7.60E-03
9.47E-03
1.11E-02
1.35E-02
3.97E-04
4.06E-04
3.43E-04
2.55E-04
1.60E-04
1.05E-04
7.70E-05
Light Intensity Activities (1.5 < METS
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419 7.94E-03 4.15E-03 5.06E-03 6.16E-03 7.95E-03 9.57E-03 1.08E-02 1.19E-0
308 1.16E-02 8.66E-03 8.99E-03 9.89E-03 1.14E-02 1.29E-02 1.44E-02 1.58E-0
261 1.17E-02 8.52E-03 9.14E-03 9.96E-03 1.14E-02 1.30E-02 1.47E-02 1.53E-0
540 1.14E-02 9.20E-03 9.55E-03 1.02E-02 1.11E-02 1.23E-02 1.34E-02 1.40E-0
940 1.16E-02 8.95E-03 9.33E-03 1.02E-02 1.13E-02 1.28E-02 1.46E-02 1.56E-0
1,337 1.32E-02 9.78E-03 1.03E-02 1.13E-02 1.28E-02 1.47E-02 1.64E-02 1.87E-0
1,241 1.34E-02 l.OOE-02 1.05E-02 1.15E-02 1.30E-02 1.50E-02 1.70E-02 1.80E-0
1.55E-02
2.11E-02
1.90E-02
1.97E-02
2.18E-02
2.69E-02
2.91E-02
9.88E-04
1.02E-03
8.37E-04
6.33E-04
3.84E-04
2.46E-04
1.79E-04
3.03E-04
3.21E-04
2.74E-04
1.78E-04
1.13E-04
7.70E-05
5.50E-05
<3.0)
786E-04
8.36E-04
6.83E-04
4.41E-04
2.67E-04
1.76E-04
1.37E-04
3.17E-04
3.31E-04
2.86E-04
1.93E-04
1.18E-04
8.00E-05
6.00E-05
8.30E-04
8.59E-04
7.16E-04
4.80E-04
2.86E-04
1.87E-04
1.44E-04
3.51E-04
3.63E-04
3.09E-04
2.15E-04
1.35E-04
8.80E-05
6.80E-05
8.97E-04
9.18E-04
7.61E-04
5.44E-04
3.24E-04
2.09E-04
1.56E-04
3.91E-04
3.97E-04
3.40E-04
2.50E-04
1.57E-04
1.01E-04
760E-05
9.72E-04
1.01E-03
8.26E-04
6.26E-04
3.77E-04
2.38E-04
1.78E-04
4.37E-04
4.48E-04
3.69E-04
2.88E-04
1.80E-04
1.18E-04
8.50E-05
1.07E-03
1.10E-03
8.87E-04
711E-04
4.37E-04
2.82E-04
1.99E-04
4.70E-04
4.88E-04
4.05E-04
3.27E-04
2.09E-04
1.35E-04
9.50E-05
1.17E-03
1.22E-03
9.95E-04
7.94E-04
4.93E-04
3.11E-04
2.18E-04
4.98E-04
5.25E-04
4.46E-04
3.46E-04
2.18E-04
1.42E-04
1.02E-04
1.20E-03
1.30E-03
1.03E-03
8.71E-04
5.29E-04
3.32E-04
2.30E-04
6.57E-04
6.19E-04
5.10E-04
4.54E-04
2.89E-04
1.95E-04
1.32E-04
1.44E-03
1.49E-03
1.18E-03
1.08E-03
709E-04
4.42E-04
3.32E-04
Q
ri
I
1
s
s
I
-------
"53
-• p
»•*
ft
I
&
a
a.
X| ft
Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
Age Uroup JN
5th
Percentiles
10th 25th 50th 75th 90th 95th
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
5th 1Qth
Percentiles
25th 50th 75th 90th
95^
Table 6-13. Descriptive Statistics for Average Ventilation Rate" While Performing Activities Within the Specified Activity Category, for
Males by Age Category (continued)
Moderate Intensity Activities (3.0 < METS f 6.0)
3irthto 6.0)
3irthto
-------
ft
i
s
oo
Table 6-14. Descriptive Statistics for Average Ventilation Rate' While Performing Activities Within the Specified Activity Category, for Females by Age Category
Age Group
Average Ventilation Rate (mVmin),
N Unadjusted for Body Weight
Mean Percentiles
5* 10* 25* 50* 75* 90*
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
95*
vlaximum Mean
Percentiles
5*
10*
25*
50*
75*
90*
95*
Vlaximum
Sleep or nap (Activity ID = 14500)
Jirthto <1 year
year
! years
i to <6 years
i to <11 years
1 to <16 years
6 to <2 1 years
415 2.92E-03 1.54E-03 1.72E-03 2.27E-03 2.88E-03 3.50E-03 4.04E-03
245 4.59E-03 3.02E-03 3.28E-03 3.76E-03 4.56E-03 5.32E-03 5.96E-03
255 4.56E-03 3.00E-03 3.30E-03 3.97E-03 4.52E-03 5.21E-03 5.76E-03
543 4.18E-03 2.90E-03 3.20E-03 3.62E-03 4.10E-03 4.71E-03 5.22E-03
894 4.36E-03 2.97E-03 3.17E-03 3.69E-03 4.24E-03 4.93E-03 5.67E-03
1,451 4.81E-03 3.34E-03 3.57E-03 3.99E-03 4.66E-03 5.39E-03 6.39E-03
1,182 4.40E-03 2.78E-03 2.96E-03 3.58E-03 4.26E-03 5.05E-03 5.89E-03
4.40E-03
6.37E-03
6.15E-03
5.73E-03
6.08E-03
6.99E-03
6.63E-03
8.69E-03
9.59E-03
9.48E-03
7.38E-03
8.42E-03
9.39E-03
1.23E-02
3.91E-04
4.14E-04
3.42E-04
2.38E-04
1.51E-04
9.00E-05
6.90E-05
2.80E-04
3.15E-04
2.58E-04
1.45E-04
8.90E-05
5.90E-05
4.40E-05
3.01E-04
3.29E-04
2.71E-04
1.63E-04
9.70E-05
6.50E-05
4.70E-05
3.35E-04
3.61E-04
2.93E-04
1.95E-04
1.20E-04
7.50E-05
5.70E-05
3.86E-04
4.05E-04
3.33E-04
2.33E-04
1.46E-04
8.70E-05
6.70E-05
4.34E-04
4.64E-04
3.91E-04
2.75E-04
1.76E-04
1.02E-04
8.00E-05
4.79E-04
5.21E-04
4.25E-04
3.20E-04
2.11E-04
1.18E-04
9.30E-05
5.17E-04
5.36E-04
4.53E-04
3.53E-04
2.29E-04
1.30E-04
1.02E-04
7.39E-04
6.61E-04
4.94E-04
5.19E-04
2.97E-04
1.76E-04
1.52E-04
Sedentary & Passive Activities (METS < 1.5 - Includes Sleep or Nap)
Jirthto <1 year
year
! years
i to <6 years
i to <11 years
1 to <16 years
6 to <2 1 years
415 3.00E-03 1.60E-03 1.80E-03 2.32E-03 2.97E-03 3.58E-03 4.11E-03
245 4.71E-03 3.26E-03 3.44E-03 3.98E-03 4.73E-03 5.30E-03 5.95E-03
255 4.73E-03 3.34E-03 3.53E-03 4.19E-03 4.67E-03 5.25E-03 5.75E-03
543 4.40E-03 3.31E-03 3.49E-03 3.95E-03 4.34E-03 4.84E-03 5.29E-03
894 4.64E-03 3.41E-03 3.67E-03 4.04E-03 4.51E-03 5.06E-03 5.88E-03
1,451 5.21E-03 3.90E-03 4.16E-03 4.53E-03 5.09E-03 5.68E-03 6.53E-03
1,182 4.76E-03 3.26E-03 3.56E-03 4.03E-03 4.69E-03 5.32E-03 6.05E-03
4.44E-03
6.63E-03
6.22E-03
5.73E-03
6.28E-03
7.06E-03
6.60E-03
9.59E-03
9.50E-03
9.42E-03
7.08E-03
8.31E-03
9.07E-03
1.18E-02
4.02E-04
4.25E-04
3.55E-04
2.51E-04
1.60E-04
9.70E-05
7.50E-05
Light Intensity Activities (1.5 < METS <
Jirthto <1 year
year
! years
S to <6 years
> to <11 years
1 to <16 years
6 to <2 1 years
415 7.32E-03 3.79E-03 4.63E-03 5.73E-03 7.19E-03 8.73E-03 9.82E-03
245 1.16E-02 8.59E-03 8.80E-03 l.OOE-02 1.12E-02 1.29E-02 1.52E-02
255 1.20E-02 8.74E-03 9.40E-03 1.03E-02 1.17E-02 1.32E-02 1.56E-02
543 1.09E-02 8.83E-03 9.04E-03 9.87E-03 1.07E-02 1.17E-02 1.29E-02
894 1.11E-02 8.51E-03 9.02E-03 9.79E-03 1.08E-02 1.20E-02 1.35E-02
1,451 1.20E-02 9.40E-03 9.73E-03 1.06E-02 1.18E-02 1.31E-02 1.47E-02
1,182 1.11E-02 8.31E-03 8.73E-03 9.64E-03 1.08E-02 1.23E-02 1.38E-02
1.08E-02
1.58E-02
1.63E-02
1.38E-02
1.47E-02
1.58E-02
1.49E-02
1.70E-02
2.02E-02
2.36E-02
1.64E-02
2.22E-02
2.21E-02
2.14E-02
9.78E-04
1.05E-03
8.97E-04
6.19E-04
3.82E-04
2.25E-04
1.74E-04
2.97E-04
3.35E-04
2.85E-04
1.64E-04
9.90E-05
7.10E-05
5.30E-05
3.0)
7.91E-04
8.45E-04
7.30E-04
4.48E-04
2.52E-04
1.63E-04
1.29E-04
3.16E-04
3.48E-04
2.96E-04
1.79E-04
1.10E-04
7.50E-05
5.70E-05
8.17E-04
8.68E-04
7.63E-04
4.84E-04
2.70E-04
1.74E-04
1.38E-04
3.52E-04
3.76E-04
3.20E-04
2.11E-04
1.31E-04
8.30E-05
6.30E-05
8.80E-04
9.49E-04
8.19E-04
5.37E-04
3.15E-04
1.96E-04
1.54E-04
3.96E-04
4.18E-04
3.48E-04
2.48E-04
1.57E-04
9.50E-05
7.40E-05
9.62E-04
1.04E-03
8.93E-04
5.99E-04
3.76E-04
2.17E-04
1.73E-04
4.46E-04
4.69E-04
3.91E-04
2.84E-04
1.85E-04
1.09E-04
8.50E-05
1.05E-03
1.14E-03
9.64E-04
6.98E-04
4.42E-04
2.49E-04
1.93E-04
4.82E-04
5.12E-04
4.20E-04
3.28E-04
2.12E-04
1.23E-04
9.60E-05
1.18E-03
1.25E-03
1.04E-03
7.83E-04
5.03E-04
2.84E-04
2.13E-04
5.19E-04
5.43E-04
4.42E-04
3.58E-04
2.34E-04
1.33E-04
1.04E-04
1.23E-03
1.27E-03
1.10E-03
8.28E-04
5.39E-04
3.05E-04
2.24E-04
7.19E-04
6.42E-04
4.85E-04
4.89E-04
2.93E-04
1.74E-04
1.41E-04
1.65E-03
1.64E-03
1.26E-03
1.02E-03
7.10E-04
3.96E-04
2.86E-04
Q
ri
I
1
s
s
I
-------
00
ri
1=
Table 6-14. Descriptive Statistics for Average Ventilation Rate* While Performing Activities Within the Specified Activity Category, for
Females by Age Category (continued)
N Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
AgeCjroup
Mean Percentiles
5* 10th 25th 50* 75th 90th 95* Maxlmum
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
Mean Percentiles
5«, 1Q«, 25t 50«, 75«, 90«, 95* Maximum
Moderate Intensity Activities (3.0 < METS s 6.0)
5irthto 6.0)
5irthto
I
».
s
I
ri
&
&
1=
-------
i
s
oo
Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category,
by Age and Gender Categories
Duration (hours/day) Spent at Activity - Males
AgeGroup
N
Mean
5* 10*
Percentiles
25th 50th
75th 90th
95* Maximum
N
Duration (hours/day) Spent at Activity - Females
Percentiles
Mean
5th
10th 25th
50th 75th
90th 95th
Vlaximum
Sleep or nap (Activity ID = 14500)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1337
1241
13.51
12.61
12.06
11.18
10.18
9.38
8.69
12.63 12.78
11.89 12.15
11.19 11.45
10.57 10.70
9.65 9.75
8.84 8.94
7.91 8.08
13.19 13.53
12.34 12.61
11.80 12.07
10.94 11.18
9.93 10.19
9.15 9.38
8.36 8.67
13.88 14.24
12.89 13.13
12.39 12.65
11.45 11.63
10.39 10.59
9.61 9.83
9.03 9.34
14.46
13.29
12.75
11.82
10.72
9.95
9.50
15.03
13.79
13.40
12.39
11.24
10.33
10.44
415
245
255
543
894
1451
1182
12.99
12.58
12.09
11.13
10.26
9.57
9.08
12.00
11.59
11.45
10.45
9.55
8.82
8.26
12.16 12.53
11.88 12.29
11.68 11.86
10.70 10.92
9.73 10.01
8.97 9.27
8.44 8.74
12.96 13.44
12.63 12.96
12.08 12.34
11.12 11.38
10.27 10.54
9.55 9.87
9.08 9.39
13.82 14.07
13.16 13.31
12.57 12.66
11.58 11.75
10.74 10.91
10.17 10.31
9.79 10.02
14.82
14.55
13.48
12.23
11.43
11.52
11.11
Sedentary & Passive Activities (METS < 1.5 - Includes Sleep or Nap)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1337
1241
14.95
14.27
14.62
14.12
13.51
13.85
13.21
13.82 14.03
13.22 13.33
13.52 13.67
13.01 13.18
12.19 12.45
12.39 12.65
11.39 11.72
14.49 14.88
13.76 14.25
14.11 14.54
13.54 14.03
12.86 13.30
13.06 13.61
12.32 13.08
15.44 15.90
14.74 15.08
15.11 15.60
14.53 15.26
13.85 14.82
14.30 15.41
13.97 14.83
16.12
15.38
15.77
15.62
15.94
16.76
15.44
17.48
16.45
17.28
17.29
19.21
18.79
18.70
415
245
255
543
894
1451
1182
Light Intensity Activities (1.5 < METS
Birth to <1 year
1 year
2 years
3 to <6 years
6to
-------
00
ri
1=
Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category,
by Age and Gender Categories" (continued)
Duration (hours/day) Spent at Activity - Males
Age Group N lvk-d" „,
Birth to <1 year 419 3.67 0.63
1 year 308 4.04 0.45
2 years 261 .83 0.59
3 to <6 years 540 .15 0.55
6to
Birth to <1 year 183 0.20 0.00
1 year 164 0.31 0.01
2 years 162 0.10 0.00
3 to <6 years 263 0.27 0.02
6to
I
».
§
I
ri
&
&
1=
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-16. Nonnormalized Daily Inhalation Rates (mVday) Derived Using Layton's (1993)
Method and CSFII Energy Intake Data
Age
Sample Size
(Non-weighted)
Mean
SEM
50th
Percentiles
90th
95th
SE of 95th
percentile
Infancy
0-2 months
3-5 months
6-8 months
9-11 months
0-11 months
182
294
261
283
1,020
3.63
4.92
6.09
7.41
5.70
0.14
0.14
0.15
0.20
0.10
3.30
4.56
5.67
6.96
5.32
5.44
6.86
8.38
10.21
8.74
7.10
7.72
9.76
11.77
9.95
0.64
0.48
0.86
-
0.55
Children
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
1 0 years
1 1 years
12 years
1 3 years
14 years
1 5 years
1 6 years
1 7 years
1 8 years
934
989
1,644
1,673
790
525
270
253
271
234
233
170
194
193
185
201
159
135
8.77
9.76
10.64
11.40
12.07
12.25
12.86
13.05
14.93
15.37
15.49
17.59
15.87
17.87
18.55
18.34
17.98
18.59
0.08
0.10
0.10
0.09
0.13
0.18
0.21
0.25
0.29
0.35
0.32
0.54
0.44
0.62
0.55
0.54
0.96
0.78
8.30
9.38
10.28
11.05
11.56
11.95
12.51
12.42
14.45
15.19
15.07
17.11
14.92
15.90
17.91
17.37
15.90
17.34
12.19
13.56
14.59
15.53
15.72
16.34
16.96
17.46
19.68
20.87
21.04
25.07"
22.81"
25.75"
28. II1
27.56
31.42"
28.80"
13.79
14.81
16.03
17.57
18.26
17.97
19.06
19.02
22.45"
22.90"
23.91"
29.17"
26.23"
29.45"
29.93"
31.01
36.69"
35.24"
0.25
0.35
0.27
0.23
0.47
0.87
1.27
1.08
1.35
1.02
1.62
1.61
1.11
4.38
1.79
2.07
-
4.24
Adolescent Boys
9- 18 years
983
19.27
0.28
17.96
28.78
32.82
1.39
Adolescent Girls
9- 18 years
0 through 1 year
2 through 1 5 years
992
U.S. EPA Cancer
1,954
7,624
14.27
0.22
Guidelines' Age Groups
7.50
14.09
0.08
0.12
13.99
21.17
23.30
0.61
with Greater Weighting
7.19
13.13
11.50
20.99
FASEB/LSRO (1995) convention, adopted by CSFII, denotes a value that might be
reliable than other estimates due
12.86
23.88
0.17
0.50
less statistically
to small cell size.
Denotes unable to calculate.
SEM = Standard
SE = Standard
Source: Arcus-Arth
error of the mean.
error.
and Blaisdell, 2007.
Page
6-32
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-17. Mean and 95th Percentile Inhalation Rate Values (mVday) for Males and Females Combined
Age Group1 Sample Size Mean
Birth to <1 monthb 182 3.63
3 to <6 months 294 4.92
6 to <12 months' 544 6.75
1 to <2 years 934 8.77
2 to <3 years 989 9.76
3 to <6 years" 4,107 11.37
6 to <1 1 years6 1,553 13.69
11 to <16 years5 975 17.07
16 to <21 years8 495 18.31
1 No other age groups from Table 6-14 (Arcus-Arth and Blaisdell, 2007) fit into the U.S. EPA age
b Age group from Arcus-Arth and Blaisdell (2007) was 0-2 months.
c Age groups of 6-8 months and 9-11 months from Arcus-Arth and Blaisdell (2007) were averagec
d Age groups of 3, 4 and 5 years from Arcus-Arth and Blaisdell (2007) were averaged.
e Age groups of 6, 7, 8, 9 and 10 years from Arcus-Arth and Blaisdell (2007) were averaged.
f Age groups of 1 1, 12, 13, 14 and 15 years from Arcus-Arth and Blaisdell (2007) were averaged.
8 Age groups of 16, 17 and 18 years from Arcus-Arth and Blaisdell (2007) were averaged.
Source: Arcus-Arth and Blaisdell, 2007.
95th
7.10
7.72
10.77
13.79
14.81
17.29
20.28
27.74
34.32
groupings.
Child-Specific Exposure Factors Handbook Page
September 2008 6-33
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-18. Summary of Institute of Medicine Energy Expenditure Recommendations
for Active and Very Active People with Equivalent Inhalation Rates
Age
Years
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19—30
31—50
51—70
Males
Energy Expenditure
(kcal/day)
607
869
1050
1,485—1,683
1,566—1,783
1,658—1,894
1,742—1,997
1,840—2,115
1,931—2,225
2,043—2,359
2,149—2,486
2,279—2,640
2,428—2,817
2,618—3,038
2,829—3,283
3,013—3,499
3,152—3,663
3,226—3,754
2,823—3,804
3,015—3,490
2,862—3,338
2,671—3,147
Inhalation Rate
(mVday)
3.4
4.9
5.9
8.4—9.5
8.8—10.1
9.4—10.7
9.8—11.3
10.4—11.9
10.9—12.6
11.5—13.3
12.1—14.0
12.9—14.9
13.7—15.9
14.8—17.2
16.0—18.5
17.0—19.8
17.8—20.7
18.2—21.2
18.4—21.5
17.0—19.7
16.2—18.9
15.1—17.8
Females
Energy Expenditure
(kcal/day)
607
869
977
1,395—1,649
1,475—1,750
1,557—1,854
1,642—1,961
1,719—2,058
1,810—2,173
1,890—2,273
1,972—2,376
2,071—2,500
2,183—2,640
2,281—2,762
2,334—2,831
2,362—2,870
2,368—2,883
2,353—2,871
2,336—2,858
2,373—2,683
2,263—2,573
2,124—2,435
Inhalation Rate
(mVday)
3.4
4.9
5.5
7.9—9.3
8.3—9.9
8.8—10.5
9.3—11.1
9.7—11.6
10.2—12.3
10.7—12.8
11.1—13.4
11.7—14.1
12.3—14.9
12.9—15.6
13.2—16.0
13.3—16.2
13.4—16.3
13.3—16.2
13.2—16.1
13.4—15.2
12.8—14.5
12.0—13.8
Source: Stifelman, 2007.
Page
6-34
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-19. Mean Inhalation Rate Values (mVday) for Males, Females, and Males and Females Combined.1
Age Groupb Males
Birth to <1 year 3.4
1 to <2 years 4.9
2 to <3 years 5.9
3 to <6 years' 9.2
6 to <1 1 years'1 10.9
11 to <16 years6 14.9
16 to <21 years5 18.2
b
d
e
f
Source
Females
3.4
4.9
5.5
8.3
10.2
12.7
13.3
Inhalation rates are for IOM Physical Activity Level (PAL) category "active"; the total
all PAL categories was 3007.
No other age groups from Table 6-15 (Stifelman, 2007) fit into the EPA age groupings
Age groups of 3, 4, and 5 years from Stifelman, 2007 were averaged.
Age groups of 6, 7, 8, 9 and 10 years from Stifelman, 2007 were averaged.
Age groups of 11, 12, 13, 14 and 15 years from Stifelman, 2007 were averaged.
Age groups of 16, 17 and 18 years from Stifelman, 2007 were averaged.
Stifelman, 2007.
Combined
3.4
4.9
5.7
8.8
10.6
13.8
15.8
number of subjects for
Child-Specific Exposure Factors Handbook Page
September 2008 6-35
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-20. Mean Inhalation Rate Values (mVday) from Key Studies for Males and Females Combined
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
TTC T-T>A ^nn^-. Brochuetal.
U.S. EPA (2006) (20Q6)
N"
_b
-
-
-
834
553
516
1,083
1,834
2,788
2,423
1 Number of individuals;
b No data from this study
Mean N Mean
-
-
85 3.32
103 4.09
8.65
13.40 101 4.95
12.99
12.41
12.92
14.38
15.41
the total number of subjects
for this age group.
Arcus-Arth and „,. „ . /o™-^
Blaisdell(2007) Stifelman (2007)
N
182
-
294
544
--
934
989
4,107
1,553
975
495
for Stifelman
Mean N Mean
3.63
-
4.92
6.75
3.40
8.77 - 4.90
9.76 - 5.70
11.37 - 8.77
13.69 - 10.57
17.07 - 13.78
18.31 - 15.75
(2007) was 3,007.
Combined Key
Studies
N
182
-
379
647
834
1,588
1,505
5,190
3,387
3,763
2,918
Mean
3.63
-
4.12
5.42
6.03
8.01
9.48
10.85
12.39
15.08
16.48
Page
6-36
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-21.
Age Group
Birth to <1 month
1
3
6
to
to
to
<3
<6
months
months
95th Percentile Inhalation Rate Values (mVday) from Key Studies for Males and Females Combined
U.S. EPA
Na
b
-
-
(2006)
95
-
-
-
th
<12 months
Birth to <1 year
1
2
3
6
to
to
to
to
<2
<3
<6
years
years
years
<1 1 years
11 to <16 years
16to<
a
b
21 years
Number
No data
834
553
516
1,083
1,834
2,788
2,423
12
18
17
15
17
19
20
68
26
04
17
03
31
84
of individuals; the tola
from this study for this
Brochuetal. Arcus-Arth and „,. „ , ,~.nnn^
(2006) Bla1sdell(2007) Stfelmn (2007)
N 95th N
182
-
85 4.47 294
103 5.33 544
-
101 6.46 934
989
4,107
1,553
975
495
95th N 95th
7.
7.
10
13
14
17
20
27
34
10
72
.77
.79
.81
.29
.28
.74
.32
Combined Key
Studies
N
182
-
379
647
834
1,588
1,505
5,190
3,387
3,763
2,918
95th
7.10
-
6.09
8.05
12.68
12.84
15.93
16.23
18.66
23.53
27.58
number of subjects for Stifelman (2007) was 3,007.
age group.
Child-Specific Exposure Factors Handbook Page
September 2008 6-37
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-22. Daily Inhalation Rates Estimated From Daily
„ , . , Inhalation Rate (mVhour)
Resting Light Activity
Child (10 years) 0.29 0.78
Infant (1 year) 0.09 0.25
Newborn 0.03 0.09
Activities1
Daily Inhalation Rate (DIR)b
(mVday)
14.8
3.76
0.78
1 Assumptions made were based on 8 hours resting and 16 hours light activity for adults and children (10 yrs); 14
b hours resting and 10 hours light activity for infants (1 yr); 23 hours resting and 1 hour light activity for newborns.
!•£
Dm=-Zmttl
i i=l
DIR = Daily Inhalation Rate
IR; = Corresponding inhalation rate at i"1 activity
t; = Hours spent during the i"1 activity
k = Number of activity periods
T = Total time of the exposure period (i.e., a day)
Source: ICRP, 1981.
Page Child-Specific Exposure Factors Handbook
6-38 September 2008
-------
00
ri
1=
53
Table
Subject
Adolescent
male, 14-16 y
male, 14-15 y
female, 14-16 y
6-23. Selected
W(kg)
59.4
Inhalation Rate Values During Different Activity Levels Obtained From
Resting Light Activity
f VT V* f VT V* f
16 330 5.2
15 300 4.5
female, 14-15y;164.9cmL 56
Children
10 y; 140 cm L
males, 10-11 y
males, 10-1 1 y; 140.6 cm L
females, 4-6 y
females, 4-6 y; 111. 6 cm L
Infant, 1 y
Newborn
20hrs-13wk
9.6 hrs
6.6 days
W = Body weights
* Calculated from
b Crying.
Source: ICRP, 1981.
36.5
32.5
20.8
18.4
2.5
2.5-5.3
3.6
3.7
16 300 4.8 24 600 14
30 48 1.4"
34 15 0.5
25 21 0.5
29 21 0.6
f = frequency (breaths/min); VT = tidal volume (ml); V* = minute volume (1/min); cm
V*=fxVT.
Various Literature Sources
Heavy Work Maximal Work During
VT V* f
53
52
58
61
70
66
68b
L = length/height; y = years
Exercise
VT
2520
1870
1330
1050
600
520
51"-b
of age; wk =
V*
113
88
71
61
40
34
3.5"
week.
* ^
* &
* 1
^ >
I
».
§
I
ri
&
&
1=
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-24. Summary of Human Inhalation Rates for Children by
Nb Resting' Nb Light11
Child, 6 years 8 0.4 16 0.8
Child, 10
a
b
c
d
e
f
Source:
years 10 0.4 40 1
Values of inhalation rates for children (male and female) presented
reported for each activity level in 1985.
Number of observations at each activity level.
Includes watching television, reading, and sleeping.
includes most domestic work, attending to personal needs and care
and home improvements.
Nb
4
29
Activity Level (m3
Moderate6
2
3.2
in this table represent the
hobbies, and conducting
/hour)"
Nb Heavy5
5 2.3
43 3.9
mean of values
minor indoor repairs
Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs.
Includes vigorous physical exercise and climbing stairs carrying a load.
Adapted from U.S. EPA, 1985.
Table 6-25. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level
for All Age Groups
Microenvironment
Indoors
Outdoors
In Transportation
Vehicle
Source: Adapted from U.S
Average Hours Per Day in Each
Activity Level Microenvironment at Each Activity Level
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
EPA, 1985.
9.82
9.82
0.71
0.10
20.4
0.51
0.51
0.65
0.12
1.77
0.86
0.86
0.05
0.0012
1.77
Page
6-40
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Child, 6 years
Child, 10 years
4.47
4.47
8.95
11.19
2.82
4.51
0.50
0.85
16.74
21.02
Table 6-26. Summary of Daily Inhalation Rates Grouped by
Age and Activity Level
Subject
Daily Inhalation Rate (rnVday)1
Resting
Light
Moderate
Heavy
IR,
t;
k
T
Total Daily IRb
(mVday)
Daily inhalation rate was calculated using the following equation:
= E IRA
= Inhalation rate at i activity (Table 6-13 and 6-14)
= Hours spent per day during i activity (Table 6-15)
= Number of activity periods
= Total time of the exposure period (e.g., a day)
Total daily inhalation rate was calculated by summing the specific activity (resting, light, moderate,
heavy) and dividing them by the total amount of time spent on all activities.
Source: Generated using the data from U.S. EPA (1985) as shown in Tables 6-24 and 6-25.
Child-Specific Exposure Factors Handbook
September 2008
Page
6-41
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-27. Calibration and Field Protocols for Self-monitoring of Activities Grouped by Subject Panels
Panel
Panel 2 - Healthy Elementary
School Students - 5 male,
12 female, ages 10-12
Panel 3 - Healthy High School
Students - 7 male, 12 female, ages
13-17
Panel 6 - Young Asthmatics - 7
male, 6 female, ages 11-16
Calibration Protocol
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and
fast walking
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and
fast walking
Laboratory exercise tests on bicycles
and treadmills
Field Protocol
Saturday, Sunday and Monday (school
day) in early autumn; heart rate recordings
and activity diary during waking hours and
during sleep.
Same as Panel 2, however, no heart rate
recordings during sleep for most subjects.
Summer monitoring for 2 successive
weeks, including 2 controlled exposure
studies with few or no observable
respiratory effects.
Source: Linn et al., 1992.
Table 6-28. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated Breathing Rates
Inhalation Rates (mVhour)
Panel Number
and Description
Mean VR
99th Percentile
VR
Mean VR at Activity Levels'1
Slow Medium Fast
Healthy
2 - Elementary School Students 17
3 - High School Students 19
Asthmatics
6 - Elementary and High School 13
Students
1.20
1.98
2.22
2.40
0.84
0.78
1.20
0.96
1.14
1.20
1.14
1.62
1.50
VR
Number of individuals in each survey panel.
Some subjects did not report medium and/or fast activity. Group means were calculated from individual means (i.e..
give equal weight to each individual who recorded any time at the indicated activity level).
= Ventilation rate.
Source: Linn et al., 1992.
Page
6-42
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-29. Distribution of Predicted Inhalation Rates by Location and Activity Levels
for Elementary and High School Students
Inhalation Rates (mVhour)
Age (years) Student Location Activity °/
Level
10-12 ELC Indoors slow
(Nd=17) medium
fast
Outdoors slow
medium
fast
13-17 HSC Indoors slow
(Nd=19) medium
fast
Outdoors slow
medium
fast
1 Recorded time averaged about 23 hr per elementary
hour periods.
'a Recorded
Time1
49.6
23.6
2.4
8.9
11.2
4.3
70.7
10.9
1.4
8.2
7.4
1.4
Mean ± SD
0.84 ±0.36
0.96 ±0.36
1.02 ±0.60
0.96 ±0.54
1.08 ±0.48
1.14±0.60
0.78 ±0.36
0.96 ±0.42
1.26 ±0.66
0.96 ±0.48
1.26 ±0.78
1.44 ±1.08
school student and 33 hours
b Geometric means closely approximated 50th percentiles; geometric
forVR.
c Elementary school student or high school student.
d Number of students that participated in survey.
e Highest single value.
SD = Standard deviation.
Source: Spier et al., 1992.
Percentile Rankings11
1st
0.18
0.24
0.24
0.36
0.24
0.48
0.30
0.42
0.54
0.42
0.48
0.48
50th
0.78
0.84
0.84
0.78
0.96
0.96
0.72
0.84
1.08
0.90
1.08
1.02
per high school student
standard deviations were
99.9th
2.34
2.58
3.42
4.32
3.36
3.60
3.24
4.02
6.84e
5.28
5.70
5.94
over 72-
1.2-1.3 for HR,1. 5-1. 8
Child-Specific Exposure Factors Handbook
September 2008
Page
6-43
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-30. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and High School Students
Students
Elementary school,
10-12 years
(N=17)
High school,
ages 13- 17 years
(N=19)
N = Number
Source: Spier et al
Slow
ages Indoors 16.3
Outdoors 2.2
Indoors 19.5
Outdoors 1 .2
of students that participated in survey.
, 1992.
Activity Level
Medium
2.9
1.7
1.5
1.3
Total Time Spent
(hours/day)
Fast
0.4 19.6
0.5 4.4
0.2 21.2
0.2 2.7
Page Child-Specific Exposure Factors Handbook
6-44 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-31. Summary of Average Inhalation Rates (mVhour) by
Age Group and Activity Levels for Laboratory Protocols
Activity Level
Age Group
Resting1 Sedentary Lighf Moderate Heavy6
Young Children 0.37 0.40 0.65 DNPf DNPf
(3-5.9 years)
Average inhalation rate (mVhour)
(N=12, gender not specified)
Children 0.45 0.47 0.95 1.74 2.23
(6-12.9 years)
Average inhalation rate (mVhour)
(N=40, 20 male and 20 female)
1 Resting defined as lying (see Table 6-33 for original data).
b Sedentary defined as sitting and standing (see Table 6-33 for original data).
c Light defined as walking at speed level 1.5 - 3.0 mph (see Table 6-33 for original data).
d Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Table 6-33 for original
data).
e Heavy defined as fast running (4.5 - 6.0 mph) (see Table 6-33 for original data).
f Group did not perform (DNP) this protocol or N was too small for appropriate mean comparisons. All young
children did not run.
Source: Adapted from Adams, 1993.
Child-Specific Exposure Factors Handbook Page
September 2008 6-45
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-32. Summary of Average Inhalation Rates (mVhour) by Age Group And Activity Levels in Field Protocols
Age Group Moderate Activity1
Young Children (3-5.9 years) 0.68
Average inhalation rate (mVhour)
(N=12, gender not specified)
Children (6-12.9 years) 1.07
Average inhalation rate (mVhour)
(N=40, 20 male and 20 female)
1 Moderate activity was defined as play.
N = Number of individuals.
Source: Adams, 1993.
Page Child-Specific Exposure Factors Handbook
6-46 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-33. Mean Minute Inhalation Rate (mVminute) by Group and Activity for Laboratory Protocols
Activity
Lying
Sitting
Standing
Walking
1.5 mph
1.875mph
2.0 mph
2.25 mph
2.5 mph
3.0 mph
3.3 mph
4.0 mph
Running
3.5 mph
4.0 mph
4.5 mph
5.0 mph
6.0 mph
* Young Children, male and female
b Group did not perform (DNP) this
Source: Adams , 1993.
Young Children"
6.19E-03
6.48E-03
6.76E-03
1.03E-02
1.05E-02
DNP
1.17E-02
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
3-5.9 years old; Children, male and female 6-12.9
protocol or N was too small for appropriate mean
Children1
7.51E-03
7.28E-03
8.49E-03
DNP»
DNP
1.41E-02
DNP
1.56E-02
1.78E-02
DNP
DNP
2.68E-02
3.12E-02
3.72E-02
DNP
DNP
years old.
comparisons.
Activity
Play
a
Source:
Table 6-34
Young children,
Adams, 1993.
Mean Minute Inhalation Rate (m3 /minute) by Group and Activity
Young Children"
1.13E-02
male and female 3-5.9 years old; children, male and female 6-12.9
for Field Protocols
Children1
1.89E-02
years old.
Child-Specific Exposure Factors Handbook
September 2008
Page
6-47
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-35.
Cohort/Age
(years)
Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy Intakes (EFD) for
Individuals Sampled in the 1977-78 NFCS
BodvWeisht
(kg)
MJ/day"
BMR1
Kcal/dayc
Energy
MJ/day
Intake (EFD)
Kcal/day
Ratio
EFDd/BMR
Males and Females
<1
Ito2
3 to 5
6 to 8
7.6
13
18
26
1.74
3.08
3.69
4.41
416
734
881
1053
3.32
5.07
6.14
7.43
793
1209
1466
1774
1.90
1.65
1.66
1.68
Males
9 to 11
12 to 14
15 to 18
36
50
66
5.42
6.45
7.64
1293
1540
1823
8.55
9.54
10.80
2040
2276
2568
1.58
1.48
1.41
Females
9 to 11
12 to 14
15 to 18
36
49
56
4.91
5.64
6.03
1173
1347
1440
7.75
7.72
7.32
1849
1842
1748
1.58
1.37
1.21
1 Calculated from the appropriate age and gender-based BMR equations given in Table 6-37.
b MJ/day - mega joules/day.
c Kcal/d - kilo calories/day.
d Food energy intake (Kcal/day) or (MJ/day).
Source: Layton
, 1993.
Page Child-Specific Exposure Factors Handbook
6-48 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-36. Daily Inhalation Rates Calculated from Food-energy Intakes
Cohort/Age
(years)
T b Daily Inhalation Ratec Sleep
(mVday) (hours)
MET Value
Inhalation Rates
Ad
Inactive5 Active5
(mVday) (mVday)
Males and Females
<1
Ito2
3 to 5
6 to 8
1
2
3
3
4.5
6.8
8.3
10
11
11
10
10
1.9
1.6
1.7
1.7
2.7
2.2
2.2
2.2
2.35
4.16
4.98
5.95
6.35
9.15
10.96
13.09
Males
9 to 11
12 to 14
15 to 18
3
3
4
14
15
17
9
9
8
1.9
1.8
1.7
2.5
2.2
2.1
7.32
8.71
10.31
18.3
19.16
21.65
Females
9 to 11
12 to 14
15 to 18
3
3
4
13
12
12
9
9
8
1.9
1.6
1.5
2.5
2.0
1.7
6.63
7.61
8.14
16.58
15.22
13.84
MET = Metabolic equivalent.
L = Number of years for each age cohort.
Daily inhalation rate was calculated by multiplying the EFD values (see Table 6-35) by H x VQ for subjects under 9
years of age and by 1.2 x H x VQ (for subjects 9 years of age and older (see text for explanation), where EFD =
Food energy intake (Kcal/day) or (MJ/day), H = Oxygen uptake = 0.05 LO2/KJ or 0.21 LO2/Kcal, and VQ =
Ventilation equivalent = 27 = geometric mean of VQs (unitless).
For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (Table
6-35) by the factor 1.2 (see text for explanation).
F = (24 x A - S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated
BMR (unitless), where S = Number of hours spent sleeping each day.
Inhalation rate for inactive periods was calculated as BMR x H x VQ, and for active periods by multiplying the
inactive inhalation rate by F (see footnote c); BMR values are from Table 6-35, where BMR = basal metabolic rate
(MJ/day) or (kg/hr).
Source: Layton, 1993.
Child-Specific Exposure Factors Handbook
September 2008
Page
6-49
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-37. Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR)
„ , BMR Body
Gender. . j
Age (years) MJd_! §D CV vv(jjlu N BMR Equation1
Males
Under 3 1.51 0.92 0.61 6.6 162 0.249 bw- 0.127
3 to < 10 4.14 0.50 0.12 21 338 0.095 bw + 2.110
10 to < 18 5.86 1.17 0.20 42 734 0.074 bw + 2.754
Females
Under 3 1.54 0.92 0.59 6.9 137 0.244 bw- 0.130
3 to < 10 3.85 0.49 0.13 21 413 0.085 bw + 2.033
10 to < 18 5.04 0.78 0.15 38 575 0.056 bw + 2.898
1 Body weight (bw) in kg.
SD = Standard deviation.
CV = Coefficient of variation (SD/mean).
N = Number of observations.
r = Coefficient of correlation.
Source: Layton, 1993.
r
0.95
0.83
0.93
0.96
0.81
0.8
Page
6-50
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-38. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR)
Gender/Age Body Weight1
(years) (kg)
Males
0.5 to <3
3 to <10
14
23
10to<18 53
Females
0.5 to <3
3 to <10
10to<18
a
b
c
11
23
50
Body weight was based
BMR"
(MJ/day) M
3.4 27 1.6
4.3 27 1.6
6.7 27 1.7
2.6 27 1.6
4.0 27 1.6
5.7 27 1.5
on the average weights for age/gender cohorts
H Inhalation Rate, VE
(m3O2/MJ) (mVday)"
0.05
0.05
0.05
0.05
0.05
0.05
in the U.S. population.
The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations
36).
The values of the BMR
(1989) study: Male = 1
multiplier (EFD/BMR) for those 18 years and
7.3
9.3
15
5.6
8.6
12
(see Table 6-
older were derived from the Basiotis et al.
.59, Female = 1.38. For males and females under 10 years old, the mean BMR
used was 1.6. For males and females aged 10 to < 18 years, the mean
cl
Source:
years and 15-18 years, a
ge brackets for males and females were used:
values for A given in Table 6-36
male =1.7 and female = 1.5.
multiplier
for 12-14
Inhalation rate = BMR x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake.
Layton, 1993.
Child-Specific Exposure Factors Handbook Page
September 2008 6-51
-------
Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-39. Inhalation Rates for Short-term Exposures
Activity Type
Gender/Age
(years)
Body
Weight
(kg)1
BMR"
(MJ/day)
Rest
Sedentary
Light
Moderate
Heavy
MET (BMR Multiplier)
1.2
4"
10e
Inhalation Rate (mVminute)5'8
Males
0.5 to <3
3 to <10
10to<18
Females
0.5 to <3
3 to <10
10to<18
14
23
53
11
23
50
3.40
4.30
6.70
2.60
4.00
5.70
3.2E-03
4.0E-03
6.3E-03
2.4E-03
3.8E-03
5.3E-03
3.8E-03
4.8E-03
7.5E-03
2.9E-03
4.5E-03
6.4E-03
6.4E-03
8.1E-03
1.3E-02
4.9E-03
7.5E-03
1.1E-02
1.3E-02
1.6E-02
2.5E-02
l.OE-02
1.5E-02
2.1E-02
6.3E-02
5.3E-02
Body weights were based on average weights for age/gender cohorts of the U.S. population
The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR
equations (Table 6-37).
Range = 1.5 -2.5.
Range = 3-5.
Range = >5 - 20.
The inhalation rate was calculated as IR = BMR (MJ/day) x H (0.05 L/KJ) x MET x VQ (27) x (day/1440 min)
Original data were presented in L/min. Conversion to mVmin was obtained as follows: x
5 v 1000L mm
The maximum possible MET sustainable for more than 5 minutes does not reach 10 for females and males until age
13 and 12, respectively. Therefore, a METs of 10 is not possible for this age category.
Source: Layton, 1993.
Page
6-52
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 6 - Inhalation Rates
Table 6-40. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in
618 Infants and Children Grouped in Classes of Age
Inhalation Rate (breaths/min)
Age (months) N Waking
<2
2to<6
6 to <12
12to<18
18to<24
24 to <30
30 to 36
SD
N
Source:
Mean ± SD Median
104 48.0 ±9.1 47
106 44.1 ±9.9 42
126 39.1 ±8. 5 38
77 34.5 ± 5.8 34
65 32.0 ±4. 8 32
79 30.0 ± 6.2 30
61 27.1 ±4.1 28
= Standard deviation.
= Number of individuals.
Rusconietal., 1994.
Sleeping
Mean ± SD Median
39. 8 ±8.7 39
33.4 ±7.0 32
29.6 ±7.0 28
27.2 ± 5.6 26
25.3 ±4.6 24
23.1 ±4.6 23
21. 5 ±3.7 21
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Chapter 6 - Inhalation Rates
70 T
3 6 9 12 15 18 21 24 27 30 33 36
Age (months)
Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects
(RR = respiratory rate). Source: Rusconi et al, 1994.
70 T
12 15 18 21 24 27 30 33 36
Age (months)
Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects
(RR = respiratory rate). Source: Rusconi et al., 1994.
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Chapter 7 - Dermal Exposure Factors
TABLE OF CONTENTS
7 DERMAL EXPOSURE FACTORS 7-1
7.1 INTRODUCTION 7-1
7.2 RECOMMENDATIONS 7-2
7.2.1 Body Surface Area 7-2
7.2.2 Adherence of Solids to Skin 7-2
7.3 SURFACE AREA 7-10
7.3.1 Key Body Surface Area Studies 7-10
7.3.1.1 U.S. EPA, 1985 7-10
7.3.1.2 U.S. EPA Analysis of NHANES 1999-2006 Data 7-10
7.3.2 Relevant Body Surface Area Studies 7-10
7.3.2.1 Phillips et al, 1993 7-10
7.3.2.2 Wong et al., 2000 7-11
7.4 ADHERENCE OF SOLIDS TO SKIN 7-11
7.4.1 Key Adherence of Solids to Skin Studies 7-11
7.4.1.1 Kissel et al., 1996a 7-11
7.4.1.2 Holmes et al., 1999 7-12
7.4.1.3 Shoafetal., 2005 7-12
7.4.2 Relevant Adherence of Solids to Skin Studies 7-13
7.4.2.1 Kissel et al., 1996b 7-13
7.4.2.2 Kissel et al., 1998 7-13
7.5 REFERENCES FOR CHAPTER 7 7-14
APPENDIX 7A 7A-1
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Chapter 7 - Dermal Exposure Factors
LIST OF TABLES
Table 7-1. Recommended Values for Total Body Surface Area, Males and
Females Combined 7-4
Table 7-2. Recommended Values for Surface Area of Body Parts 7-5
Table 7-3. Confidence in Recommendations for Body Surface Area 7-6
Table 7-4. Recommended Values for Mean Solids Adherence 7-8
Table 7-5. Confidence in Recommendations for Solids Adherence to Skin 7-9
Table 7-6. Percentage of Total Body Surface Area by Body Part For Children 7-16
Table 7-7. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
1999-2006 Males and Females Combined 7-17
Table 7-8. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
1999-2006 Males 7-17
Table 7-9. Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
1999-2006 Females 7-18
Table 7-10. Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (mVkg) 7-19
Table 7-11. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 7-20
Table 7-12. Summary of Field Studies 7-21
Table 7-13. Geometric Mean and Geometric Standard Deviations of Solids Adherence by
Activity and Body Region 7-22
Table 7-14. Summary of Controlled Greenhouse Trials - Children Playing 7-23
Table 7A-1. Estimated Parameter Values for Different Age Intervals 7A-4
Table 7A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model 7A-5
Page
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Chapter 7 - Dermal Exposure Factors
LIST OF FIGURES
Figure 7-1. Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing
in Wet Soils 7-24
Figure 7-2. Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils 7-24
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Chapter 7 - Dermal Exposure Factors
7 DERMAL EXPOSURE FACTORS
7.1 INTRODUCTION
Dermal exposure can occur during a variety of
activities in different environmental media and
microenvironments (U.S. EPA, 1992a; 1992b; 2004).
These include:
• Water (e.g., bathing, washing,
swimming);
• Soil (e.g., outdoor recreation, gardening,
construction);
• Sediment (e.g., wading, fishing);
• Liquids (e.g., use of commercial
products);
• Vapors/fumes (e.g., use of commercial
products); and
• Indoor dust (e.g., carpets, floors, counter
tops).
Children may be more highly exposed to
environmental toxicants through dermal routes than
adults. For instance, children may crawl, roll or sit on
surfaces treated with chemicals (i.e., carpets and floors)
and play with objects such as toys where residues may
settle. Children also are more likely to wear less
clothing than adults. As a result, children may have
higher dermal contact with contaminated media. In
addition, young children who wear diapers may be
exposed for long periods of time to chemical
components of lotions and other products used for
diapering. Children also have a higher surface area
relative to body weight compared to adults. The
surface-area-to-body weight ratio for newborn infants
is more than two times greater than that for adults
(Cohen-Hubal et al, 1999). Therefore, the dose
relative to body weight would be greater for a child
than for an adult with an equal amount of skin exposure
to a chemical.
This chapter focuses on measurements of body
surface area and dermal adherence of solids to the skin.
These are only two of a several parameters that
influence dermal absorption. Other factors include the
concentration of chemical in contact with the skin,
characteristics of the chemical (i.e., lipophilicity,
polarity, volatility, solubility), the site of application
(i.e., the thickness of the stratum corneum varies over
parts of the body), absorption of chemical through the
skin and factors that affect absorption (i.e, thickness,
age, condition), and the amount of chemical delivered
to the target organ. For guidance on how to use skin
surface area and dermal adherence factors, as well as
these other factors to assess dermal exposure, readers
are referred to Dermal Exposure Assessment:
Principles and Applications (U.S. EPA, 1992b) and
Risk Assessment Guidelines for Superfund (RAGs) Part
E (U.S. EPA, 2004). Frequency and duration of contact
also affect dermal exposure. Information on activity
factors is presented in Chapter 17 of this handbook.
Surface area of the skin can be determined
using measurement or estimation techniques. Coating,
triangulation, and surface integration are direct
measurement techniques that have been used to measure
total body surface area and the surface area of specific
body parts. The coating method consists of coating
either the whole body or specific body regions with a
substance of known density and thickness.
Triangulation consists of marking the area of the body
into geometric figures, then calculating the figure areas
from their linear dimensions. Surface integration is
performed by using a planimeter and adding the areas.
The results of studies conducted using these various
techniques have been summarized in Development of
Statistical Distributions or Ranges of Standard Factors
Used in Exposure Assessments (U.S. EPA, 1985).
Because of the difficulties associated with direct
measurements of body surface area, the existing direct
measurement data are limited and dated. However,
several researchers have developed methods for
estimating body surface area from measurements of
other body dimensions (DuBois and DuBois, 1916;
Boyd, 1935; Gehan and George, 1970). Generally,
these formulas are based on the observation that body
weight and height are correlated with surface area and
are derived using multiple regression techniques. U. S.
EPA (1985) evaluated the various formulas for
estimating total body surface area. A discussion and
comparison of formulas are presented in Appendix 7 A.
The key studies on body surface area that are presented
in Section 7.3 of this chapter are based on these
formulas, and weight and height data from the National
Health and Nutrition Examination Survey (NHANES).
Several field studies have been conducted to
estimate the adherence of solids to skin. These field
studies consider factors such as activity, gender, age,
field conditions, and clothing worn. These studies are
presented in Section 7.4 of this chapter.
The recommendations for skin surface area
and dermal adherence of solids to skin are provided in
the next section, along with a summary of the
confidence ratings for these recommendations. The
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Chapter 7 - Dermal Exposure Factors
recommended values are based on key studies identified
by U.S. EPA for these factors. Following the
recommendations, the two key studies on skin surface
area and the three key studies on dermal adherence of
solids to skin are summarized. Relevant data on these
factors are also presented to provide added perspective
on the state-of-knowledge pertaining to dermal
exposure factors.
7.2 RECOMMENDATIONS
7.2.1 Body Surface Area
The recommended mean and 95th percentile
total body surface area values for children are
summarized in Table 7-1. If gender-specific data or
data for percentiles other than the mean or 95th
percentile are needed, the reader is referred to Tables 7-
7 through 7-9 of this chapter. The recommendations for
total body surface area are based on the U.S. EPA
analysis of NHANES 1999-2006 data and are presented
for the standard age groupings recommended by U.S.
EPA (2005) for male and female children combined.
The U.S. EPA analysis of NHANES 1999-2006 data
uses correlations with body weight and height for
deriving skin surface area (see Section 7.3.1.2 and
Appendix 7A). NHANES 1999-2006 used a
statistically-based survey design which should ensure
that the data are reasonably representative of the
general population. The recommendations for the
percentage of total body surface area represented by
individual body parts are based on data from U. S. EPA
(1985), and are presented in Table 7-2 (See Section
7.3.1). Table 7-2 also provides age-specific body part
surface areas (m2) that were obtained by multiplying the
mean body part percentages by the total body surface
areas presented in Table 7-1. If gender-specific data or
data for percentiles other than the mean and 95th
percentile are needed, the body part percentages in
Table 7-2 may be applied to the total skin surface area
data in Tables 7-7 through 7-9. Table 7-3 presents the
confidence ratings for the recommendations for body
surface area.
For swimming and bathing scenarios, past
exposure assessments have assumed that 75 to 100
percent of the skin surface is exposed (U.S. EPA,
1992b). More recent guidance recommends assuming
100 percent exposure for these scenarios (U.S. EPA,
2004). For other exposure scenarios, it is reasonable to
assume that clothing reduces the contact area.
However, while it is generally assumed that adherence
of solids to skin occurs to only the areas of the body not
covered by clothing, it is important to understand that
soil and dust particles can get under clothing and be
deposited on skin to varying degrees depending on the
protective properties of the clothing. Likewise, liquids
may soak through clothing and contact covered areas of
the skin. Assessors should consider these possibilities
for the scenario of concern and select skin areas that are
judged appropriate.
7.2.2 Adherence of Solids to Skin
The adherence factor (AF) describes the
amount of material that adheres to the skin per unit of
surface area. Although most research in this area has
focused on soils, a variety of other solid residues can
accumulate on skin, including household dust,
sediments and commercial powders. Studies on soil
adherence have shown that: 1) soil properties influence
adherence; 2) soil adherence varies considerably across
different parts of the body; and 3) soil adherence varies
with activity (U. S. EPA, 2004). It is recommended that
exposure assessors use adherence data derived from
testing that matches the exposure scenario of concern in
terms of solid type, exposed body parts, and activities,
as closely as possible. Assessors should refer to the
activities described in Table 7-12 to select those that
best represent the exposure scenarios of concern and
use the corresponding adherence values from Table 7-
13. Table 7-12 lists the age ranges covered by each
study. This may be used as a general guide to the ages
covered by these data. Recommended mean AF values
are summarized in Table 7-4 according to common
activities involving children. Insufficient data were
available to develop distributions or probability
functions for these values. Also, the small number of
subjects in these studies prevented the development of
recommendations for the specific age groups
recommended by U.S. EPA (2005).
RAGS Part E (U.S. EPA, 2004) recommends
that scenario-specific adherence values be weighted
according to the body parts exposed. Weighted
adherence factors may be estimated according to the
following equation:
AFwtd= (AF.YSA.) + (AF.YSA.) + . . . . (AF.YSA)
SAj + SA2 + . . . SAj
(Eqn. 7-1)
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Chapter 7 - Dermal Exposure Factors
where:
AF^ = weighted adherence factor;
AF = adherence factor; and
SA = surface area.
For the purposes of this calculation, the surface area of
the face may be assumed to be 1/3 that of the head,
forearms may be assumed to represent 45 percent of the
arms and lower legs may be assumed to represent 40
percent of the legs (U.S. EPA, 2004).
The recommended dermal AFs represent the
amount of material on the skin at the time of
measurement. U.S. EPA (1992b) recommends
interpreting AFs as representative of contact events.
Assuming that the amount of solids measured on the
skin represents accumulation between washings, and
that people wash at least once per day, these adherence
values can be interpreted as daily contact rates (U.S.
EPA, 1992b). The rate of solids accumulation on skin
over time has not been well studied, but probably
occurs fairly quickly. Therefore, pro-rating the
adherence values for exposure time periods of less than
one day is not recommended.
The confidence ratings for these AF
recommendations are shown in Table 7-5. It should be
noted that while the recommendations are based on the
best available estimates of activity-specific adherence,
they are based on limited data from studies that have
focused primarily on soil. Therefore, they have a high
degree of uncertainty and considerable judgment must
be used when selecting them for an assessment. It
should also be noted that the skin adherence studies
have not considered the influence of skin moisture on
adherence. Skin moisture varies depending on a
number of factors, including activity level and ambient
temperature/humidity. It is uncertain how well this
variability has been captured in the dermal adherence
studies.
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Chapter 7 - Dermal Exposure Factors
Table 7-1. Recommended Values for Total Body Surface Area,
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Mean
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
Males and Females Combined
95th Percentile ,, ... ,
Multiple
m2 Percentiles
0.34
0.38
0.44
0.51
0.61 See Tables 7-7,
0.70 7-8, and 7-9
0.95
1.48
2.06
2.33
Source
U.S. EPA Analysis of
NHANES 1999-2006 data
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Chapter 7 - Dermal Exposure Factors
Table 7-2. Recommended Values for Surface Area of Body Parts
Birth
1 to<
3to<
6to<
1 to<
2to<
3to<
6to<
11 to
16 to
Birth
lto<
3to<
6to<
lto<
2to<
3to<
6to<
11 to
16 to
Birth
lto<
3to<
6to<
lto<
2to<
3to<
6to<
11 to
16 to
a
b
Note
Age Group
to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years
to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years
to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years
Head
Trunk Arms
Hands
Legs
Feet
Mean Percent of Total Surface Area
18.2
18.2
18.2
18.2
16.5
14.2
13.7
12.6
9.4
7.8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
053
060
069
082
087
087
104
136
149
144
062
069
080
093
101
099
130
186
194
182
35
35
35
35
35
38
31
34
33
32
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
95
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
Calculated as mean percentage
Calculated as mean percentage
Surface area values reported in
7
7
7
7
5
5
7
7
7
2
Mean
104
118
136
161
188
235
241
375
536
592
13.7
13.7
13.7
13.7
13.0
11.8
14.2
12.7
12.9
15.3
5.3
5.3
5.3
5.3
5.7
5.3
5.9
5.0
5.3
5.4
Surface Area by Body
m2
0.040
0.045
0.052
0.062
0.069
0.072
0.108
0.137
0.205
0.282
0.015
0.017
0.020
0.024
0.030
0.032
0.045
0.054
0.084
0.099
20.6
20.6
20.6
20.6
23.1
23.2
27.3
27.9
31.3
32.2
Part1
0.060
0.068
0.078
0.093
0.122
0.142
0.207
0.301
0.498
0.592
6.5
6.5
6.5
6.5
6.3
7.1
7.3
7.2
7.5
7.1
Source
U.S. EPA, 1985
0.019
0
0
0
0
0
0
0
0
0
021
025
029
033
043
055
078
119
131
U.S. EPA Analysis
ofNHANES 1999-
2006 data and U.S.
EPA, 1985
* Percentile Surface Area by Body Partb
m2
121
136
157
182
217
270
301
514
694
750
0.047
0.052
0.060
0.070
0.079
0.083
0.135
0.188
0.266
0.356
0.018
0.020
0.023
0.027
0.035
0.037
0.056
0.074
0.109
0.126
0.070
0.078
0.091
0.105
0.141
0.162
0.259
0.413
0.645
0.750
0
0
0
0
0
0
0
0
0
0
022
025
029
033
038
050
069
107
155
165
U.S. EPA Analysis
ofNHANES 1999-
2006 data and U.S.
EPA, 1985
of body part times mean total body surface area.
of body part times 95th percentile total body surface area.
m2 can be converted to cm2 by multiplying by 10,000 cmVm2.
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Chapter 7 - Dermal Exposure Factors
Table 7-3. Confidence in Recommendations for Body Surface Area
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Medium
Minimal (or Defined) Bias
Total surface area estimates were based on algorithms developed using
direct measurements and data from NHANES surveys. The methods
used for developing these algorithms were adequate. The NHANES
data and the secondary data analyses to estimate total surface areas
were appropriate. NHANES included a large sample sizes; sample size
varied with age. Body part percentages were based on direct
measurements from a limited number of subjects.
The data used to develop the algorithms for estimating surface area
from height and weight data were limited. NHANES collected
physical measurements of weight and height. Body part data were
based on direct measurements from a limited number of subjects.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Medium
Currency
Data Collection Period
The key studies were directly relevant to surface area estimates.
The direct measurement data used to develop the algorithms for
estimating total body surface area from weight and height may not be
representative of the U.S. population. However, NHANES height and
weight data were collected using a complex, stratified, multi-stage
probability cluster sampling design intended to be representative of the
U.S. population. The sample used to derive body part percentages of
total surface was not representative of U.S. population.
The U.S. EPA analysis used the most current data at the time both
studies were conducted. The data on body part percentages were
dated; however, the age of the data is not expected to affect its utility.
The U.S. EPA analysis was based on four NHANES data sets covering
1999-2006.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Medium
The U.S. EPA analysis of the NHANES data is unpublished, but
available upon request. U.S. EPA (1985) is a U.S. EPA-published
report.
The methodology was clearly presented; enough information was
included to reproduce the results.
Quality assurance of NHANES data was good; quality control of
secondary data analysis was not well described.
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Table 7-3. Confidence in Recommendations for Body Surface Area (continued)
General Assessment Factors
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The full distributions were given for total surface area.
A source of uncertainty in total surface areas resulted from
the limitations in data used to develop the algorithms for
estimating total surface from height and weight. Because of
the small sample size, there is uncertainty in the body part
percentage estimates.
The NHANES surveys received a high level of peer review.
The U.S. EPA analysis was not published in a peer-reviewed
journal.
There is one key study for total surface area and one key
study for the surface area of body parts.
Rating
Medium
Medium
Medium for Total
Surface Area and
Low for Surface
Area of Individual
Body Parts
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Table 7-4. Recommended Values for Mean Solids Adherence to Skin
Face
Arms Hands
Legs
Feet
Source
Residential (indoors)1
Daycare (indoors & outdoors)11
Outdoor sports'
Indoor sports'1
Activities with soil6
Playing in mudf
Playing in sediment8
0
0
0
-
-
012
-
054
-
040
0.0041
0.024
0.011
0.0019
0.046
11
0.17
0.011
0.099
0.11
0.0063
0.17
47
0.49
0.0035
0.020
0.031
0.0020
0.051
23
0.70
0.010
0.071
-
0.0022
0.20
15
21
Holmes et al
Holmes et al
Kissel et al.,
Kissel et al.,
Holmes et al
Kissel et al.,
Shoafetal.,
,1999
,1999
1996a
1996a
,1999
1996a
2005
Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to 13 years; N = 10)
playing indoors.
Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years; N
= 21) playing both indoors and outdoors.
Based on geometric mean soil loadings of 6 children (ages >8 years) and 1 adult engaging in Tae Kwon Do.
Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer.
Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years).
Based on weighted average of geometric mean solids loading of 2 groups of children (age 9 to 14 years; N= 12)
playing in mud.
Based on geometric mean solids loading of 9 children (ages 7 to 12 years) playing in tidal flats.
= No data.
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Table 7-5. Confidence in Recommendations for Solids Adherence to Skin
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The approach was adequate; the skin rinsing technique is
widely employed for purposes similar to this. Small
sample sizes (4 to 9 children) were used in the studies; the
key studies directly measured soil adherence to skin.
The studies attempted to measure soil adherence for
selected activities and conditions. The number of
activities and study participants was limited.
Medium
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The studies were relevant to the factor of interest; the goal
was to determine soil adherence to skin.
The soil/dust studies were limited to the State of
Washington and the sediment study was limited to Rhode
Island. The data may not be representative of other
locales.
The studies were published between 1996 and 2005
Short-term data were collected. Seasonal factors may be
important, but have not been studied adequately.
Low
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Articles were published in widely circulated
journals/reports.
The reports clearly describe the experimental methods,
and enough information was provided to allow for the
study to be reproduced.
Quality control was not well described.
Medium
Variability and Uncertainty
Variability in Population
Uncertainty
Variability in soil adherence is affected by many factors
including soil properties, activity and individual behavior
patterns. Not all age groups were represented in the
sample.
The estimates are highly uncertain; the soil adherence
values were derived from a small number of observations
for a limited set of activities.
Low
Evaluation and Review
Peer Review
Number and Agreement of Studies
The studies were reported in peer reviewed journal articles.
There are three key studies that evaluated different
activities in children.
Medium
Overall Rating
Low
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7.3 SURFACE AREA
7.3.1 Key Body Surface Area Studies
7.3.1.1 U.S. EPA, 1985 - Development of Statistical
Distributions or Ranges of Standard Factors
Used in Exposure Assessments
The U.S. EPA (1985) summarized the direct
measurements of the surface area of children's body
parts provided by Boyd (1935) and Van Graan (1969)
as a percentage of total surface area. A total of 21
children less than 18 years of age were included. These
percentages are presented in Table 7-6. Because of the
small sample size, it is unclear how accurately these
estimates represent averages for the age groups. Note
that the proportion of total body surface area
contributed by the head decreases from childhood to
adulthood, whereas the proportion contributed by the
leg increases.
7.3.1.2 U.S. EPA Analysis ofNHANES 1999-2006
Data
The U.S. EPA estimated total body surface
areas for children in U.S. EPA's standard age
categories, using the empirical relationship shown in
Appendix 7A and U.S. EPA (1985), and body weight
and height data from the 1999-2006 NHANES.
NHANES is conducted annually by the Center for
Disease Control (CDC), National Center of Health
Statistics (NCHS). The survey's target population is
the civilian, noninstitutionalized U.S. population. The
NHANES 1999-2006 survey was conducted on a
nationwide probability sample of approximately 40,000
persons for all ages, of which approximately 20,000
were children. The survey is designed to obtain
nationally representative information on the health and
nutritional status of the population of the United States
through interviews and direct physical examinations. A
number of anthropometrical measurements were taken
for each participant in the study, including body weight
and height. Unit nonresponse to the household
interview was 19 percent, and an additional 4 percent
did not participate in the physical examinations
(including body weight measurements).
The NHANES 1999-2006 survey includes
over-sampling of low-income persons, adolescents
12-19 years, persons 60+ years of age, African
Americans, and Mexican Americans. Sample data were
assigned weights to account both for the disparity in
sample sizes for these groups and for other
inadequacies in sampling, such as the presence of
non-respondents. Because the U.S. EPA utilized four
NHANES data sets in its analysis (NHANES 1999-
2000,2001-2002,2003-2004, and 2005-2006), sample
weights were developed for the combined data set in
accordance with CDC guidance from the NHANES'
web site (http://www.cdc.gov/nchs/about/major/
nhanes/nhanes2005-2006/faqs05_06.htm#question%2
012).
Table 7-7 presents the mean and percentile
estimates of body surface area by age category for male
and female children, combined. Tables 7-8 and 7-9
present mean and percentiles of body surface area by
age category for male and female children, respectively.
An advantage of using the NHANES datasets to derive
surface area estimates is that data are available for
infants from birth and older. In addition, the NHANES
data are nationally representative and remain the
principal source of body weight and height data
collected nationwide from a large number of subjects.
It should be noted that in the NHANES surveys height
measurements for children under 2 years of age were
based on recumbent length while standing height
information was collected for children aged 2 years and
older. Some studies have reported differences between
recumbent length and standing height measurements for
the same individual, ranging from 0.5 to 2 cm, with
recumbent length being the larger of the two
measurements (Buyken et al, 2005). The use of height
data obtained from two different types of height
measurements to estimate surface area of children may
potentially introduce errors into the estimates.
7.3.2 Relevant Body Surface Area Studies
7.3.2.1 Phillips et al, 1993 - Distributions of Total
Skin Surface Area to Body Weight Ratios
Phillips et al. (1993) observed a strong
correlation (0.986) between body surface area and body
weight and studied the effect of using these factors as
independent variables in the lifetime average daily dose
(LADD) equation (See Chapter 1). The authors
suggested that, because of the correlation between these
two variables, the use of body surface area to body
weight (SA/B W) ratios in human exposure assessments
may be more appropriate than treating these factors as
independent variables. Direct measurement data from
the scientific literature were used to calculate SA/BW
ratios for two age groups of children (infants aged 0 to
2 years and children aged 2.1 to 17.9 years). These
ratios were calculated by dividing body surface areas by
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Chapter 7 - Dermal Exposure Factors
corresponding body weights for the 401 individuals
analyzed by Gehan and George (1970) and summarized
by U.S. EPA (1985). Distributions of SA/BW ratios
were developed, and summary statistics were calculated
for the two age groups and the combined data set.
Summary statistics for the two children's age
groups are presented in Table 7-10. The shapes of
these SA/BW distributions were determined using
D'Agostino's test, as described in D'Agostino et al.
(1990). The results indicate that the SA/BW ratios for
infants are lognormally distributed. SA/BW ratios for
children were neither normally nor lognormally
distributed. According to Phillips etal. (1993), SA/BW
ratios may be used to calculate L ADDs by replacing the
body surface area factor in the numerator of the LADD
equation with the SA/BW ratio and eliminating the
body weight factor in the denominator of the LADD
equation.
The effect of gender and age on SA/BW
distribution was also analyzed by classifying the
401 observations by gender and age. Statistical
analyses indicated no significant differences between
SA/BW ratios for males and females. SA/BW ratios
were found to decrease with increasing age. The
advantage of this study is that it studied correlations
between surface area and body weight. However, data
could not be broken out by finer age categories.
7.3.2.2 Wong et al, 2000-Adult Proxy Responses to
a Survey of Children's Dermal Soil Contact
Activities
Wong et al. (2000) reported on two surveys
that gathered information on activity patterns related to
dermal contact with soil. The first of these national
phone surveys (also reported on by Garlock et al.,
1999) was conducted in 1996 using random digit
dialing. Information about children was gathered from
adults over the age of 18, and obtained information on
211 children. For older children (those between the
ages of 5 and 17 years), information was gathered on
their participation in "gardening and yardwork,"
"outdoor sports," and "outdoor play activities." For
children less than 5 years old, information was gathered
on "outdoor play activities," including whether the
activity occurred on a playground or yard with "bare
dirt or mixed grass and dirt" surfaces. Information on
the types of clothing worn while participating in these
play activities during warm weather months (April
though October) was obtained. The results of this
survey indicate that most children wore short pants, a
dress or skirt, short sleeve shirts, no socks, and leather
or canvas shoes during the outdoor play activities of
interest. Using the survey data on clothing and total
body surface area data from U.S. EPA (1985), estimates
were made of the skin area exposed (expressed as
percentages of total body surface area) associated with
various age ranges and activities. These estimates are
provided in Table 7-11.
7.4 ADHERENCE OF SOLIDS TO SKIN
7.4.1 Key Adherence of Solids to Skin Studies
7.4.1.1 Kissel et al., 1996a - Field Measurements of
Dermal Soil Loading Attributable to Various
Activities: Implications for Exposure
Assessment
Kissel et al. (1996a) collected direct
measurements of soil loading on the surface of the skin
of volunteers, before and after activities expected to
result in soil contact. Soil adherence associated with
the following indoor and outdoor activities were
estimated: greenhouse gardening, tae kwon do karate,
soccer, rugby, reed gathering, irrigation installation,
truck farming, and playing in mud. Skin surface areas
monitored included hands, forearms, lower legs, faces
and/or feet (Kissel et al., 1996a).
Several of the activities studied by Kissel et al.
(1996a) involved children, as shown in Table 7-12. A
group of young male soccer players (Soccer) was
monitored before and after 40 minutes of practice on a
field consisting of half grass and half bare earth. Six
children were monitored after 10 and 20 minutes of
playing in the mud at a lake with an exposed shoreline
(Kids-in-mud No. 1 and No. 2). For indoor activities,
soil loadings were estimated from six children and one
adult practicing tae kwon do (Tae Kwon Do); the
activity lasted 90 minutes including a 30-min warm up.
Information on activity duration, sample size and
clothing worn by participants is provided in Table 7-12.
The subjects' body surfaces (forearms, hands, lower
legs for all sample groups; faces and/or feet pairs in
some sample groups) were washed before and after the
monitored activities. Paired samples were pooled into
single ones. The mass recovered was converted to soil
loading using allometric models of surface area.
Geometric means for post-activity soil
adherence by activity and body region for the four
groups of volunteers evaluated are presented in Table
7-13. Children playing in the mud had the highest soil
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loadings among the groups evaluated. The results also
indicate that, in general, the amount of soil adherence to
the hands is higher than for other parts of the body
during the same activity.
An advantage of this study is that it provides
information on soil adherence to various body parts
resulting from unscripted activities. However, the study
authors noted that, because the activities were unstaged,
"control of variables such as specific behaviors within
each activity, clothing worn by participants, and
duration of activity was limited." In addition, soil
adherence values were estimated based on a small
number of observations and very young children and
indoor activities were under-represented in the study.
7.4.1.2 Holmes et aL, 1999 - Field Measurements of
Dermal Loadings in Occupational and
Recreational A ctivities
Holmes et al. (1999) collected pre- and post-
activity soil loadings on various body parts of
individuals within groups engaged in various
occupational and recreational activities. These groups
included: children at a daycare center (Daycare Kids),
children playing indoors in a residential setting (Indoor
Kids), individuals (aged 16 to 35) removing historical
artifacts from a site (Archeologists), and individuals
(aged 16 to 35) performing gardening work
(Gardeners). This study was conducted as a follow up
to previous field sampling of soil adherence on
individuals participating in various activities (Kissel et
al., 1996a). For this round of sampling, soil loading
data were collected utilizing the same methods used and
described in Kissel et al. (1996a). Information
regarding the groups studied and their observed
activities is presented in Table 7-12.
The daycare children studied were all at one
location, and measurements were taken on three
different days. The children freely played both indoors
in the house and outdoors in the backyard. The
backyard was described as having a grass lawn, shed,
sand box, and wood chip box. In this setting, the
children engaged in typical activities including: playing
with toys and each other, wrestling, sleeping, and
eating. The number of children within each day's group
and the clothing worn is described in Table 7-12. The
five children measured on the first day were washed
first thing in the morning to establish a preactivity level.
They were next washed at noon to determine the
postactivity soil loading for the morning (Daycare Kids
No. la). The same children were washed once again at
the close of the day for measurement of soil adherence
from the afternoon play activities (Daycare Kids No.
Ib). For the second observation day (Daycare Kids No.
2), postactivity data were collected for five children.
All the activities on this day occurred indoors. For the
third daycare group (Daycare Kids No. 3), four children
were studied.
On two separate days, children playing indoors
in a home environment were monitored. The first group
(Indoor Kids No. 1) had four children while the second
group (Indoor Kids No. 2) had six children. The play
area was described by the authors as being primarily
carpeted. The clothing worn by the children within
each day's group is described in Table 7-12.
Seven individuals (Archeologists), ages 16 to
35 years, were monitored while excavating, screening,
sorting, and cataloging historical artifacts from an
ancient Native American site during a single event.
Eight volunteers (Gardeners), ages 16 to 35 years, were
monitored while performing gardening activities (i.e.,
weeding, pruning, digging small irrigation trenches,
picking and cleaning fruit). The clothing worn by these
groups is described in Table 7-12.
The geometric means and standard deviations
of the postactivity soil adherence for each group of
individuals and for each body part are summarized in
Table 7-13. According to the authors, variations in the
soil loading data from the daycare participants reflect
differences in the weather and access to the outdoors.
An advantage of this study is that it provides
a supplement to soil loading data collected in a previous
round of studies (Kissel et al., 1996a). Also, the data
support the assumption that hand loading can be used as
a conservative estimate of soil loading on other body
surfaces for the same activity. The activities studied
represent normal child play both indoors and outdoors,
as well as different combinations of clothing. The small
number of participants is a disadvantage of this study.
Also, the children studied and the activity setting may
not be representative of the U.S. population.
7.4.1.3 Shoafet aL, 2005 - Child Dermal Sediment
Loads Following Play in a Tide Flat
The purpose of this study was to obtain
sediment adherence data for children playing in a tidal
flat (Shoreline Play). The study was conducted on one
day in late September 2003 at a tidal flat in Jamestown,
Rhode Island. Nine subjects (three females and six
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Chapter 7 - Dermal Exposure Factors
males) ages 7 to 12 years old participated in the study.
Information on activity duration, sample size and
clothing worn by participants is provided in Table 7-12.
Participants' parents completed questionnaires
regarding their child's typical activity patterns during
tidal flat play, exposure frequency and duration,
clothing choices, bathing practices and clothes
laundering.
This study reported direct measurements of
sediment loadings on five body parts (face, forearms,
hands, lower legs, and feet) after play in a tide flat.
Each of nine subjects participated in two timed sessions
and pre- and post-activity sediment loading data were
collected. Geometric mean (geometric standard
deviations) dermal loadings (mg/cm2) on the face,
forearm, hands, lower legs, and feet for the combined
sessions, as shown in Table 7-13, were 0.04 (2.9), 0.17
(3.1), 0.49 (8.2), 0.70 (3.6) and 21 (1.9), respectively.
The primary advantage of this study is that it
provides adherence data specific to children and
sediments which had previously been largely
unavailable. Results will be useful to risk assessors
considering exposure scenarios involving child
activities at a coastal shoreline or tidal flat. The limited
number of participants (9) and sampling during just one
day and at one location, make extrapolation to other
situations uncertain.
7.4.2 Relevant Adherence of Solids to Skin
Studies
7.4.2.1 Kissel et al, 1996b - Factors Affecting Soil
Adherence to Skin in Hand-press Trials:
Investigation of Soil Contact and Skin
Coverage
Kissel et al. (1996b) conducted soil adherence
experiments using five soil types obtained locally in the
Seattle, WA, area: sand, 2 types of loamy sand, sandy
loam, and silt loam. All soils were analyzed by
hydrometer (settling velocity) to determine
composition. Clay content ranged from 0.5 to 7.0
percent. Organic carbon content, determined by
combustion, ranged from 0.7 to 4.6 percent. Soils were
dry-sieved to obtain particle size ranges of <150, 150-
250, and >250 (im. For each soil type, the amount of
soil adhering to an adult female hand, using both sieved
and unsieved soils, was determined by measuring the
soil sample weight before and after the hand was
pressed into a pan containing the test soil. Loadings
were estimated by dividing the recovered soil mass by
total hand area, although loading occurred primarily on
only one side of the hand. Results showed that
generally, soil adherence to hands was directly
correlated with moisture content, inversely correlated
with particle size, and independent of clay content or
organic carbon content. The advantage of this study is
that it provides information on how soil type can affect
adherence to the skin. However, the soil adherence
data are for a single subject and the data are limited to
five soil samples.
7.4.2.2 Kissel et al, 1998 - Investigation of Dermal
Contact with Soil in Controlled Trials
Kissel et al. (1998) measured dermal exposure
to soil from staged activities conducted in a greenhouse.
A fluorescent marker was mixed in soil so that soil
contact for a particular skin surface area could be
identified. The subjects, which included a group of
children, were video-imaged under a long-wave
ultraviolet (UV) light before and after soil contact. In
this manner, soil contact on hands, forearms, lower legs,
and faces was assessed by presence of fluorescence. In
addition to fluorometric data, gravimetric measurements
for preactivity and postactivity were obtained from the
different body parts examined.
The studied group of children played for 20
minutes in a soil bed of varying moisture content
representing wet and dry soils. Three trials with
children were conducted, each representing a different
clothing/soil moisture scenario. For wet soils, both
combinations of long sleeves and long pants, and short
sleeves and short pants were tested. For dry soil, only
short sleeves and short pants were worn during play.
Clothing was laundered after each trial. The parameters
describing each of these trials are summarized in Table
7-14. Before each trial, each child was washed in order
to obtain a preactivity or background gravimetric
measurement.
For wet soil, postactivity fluorescence results
indicated that the hand had a much higher fractional
coverage than other body surfaces (see Figure 7-1). No
fluorescence was detected on the forearms or lower legs
of children dressed in long sleeves and pants. As
shown in Figure 7-2, postactivity gravimetric
measurements showed higher soil loading on hands and
much lower amounts on other body surfaces, as was
observed with fluorescence data. According to Kissel
et al. (1998), the relatively low loadings observed on
non-hand body parts may be a result of a more limited
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area of contact for the body part rather than lower
localized loadings. The highest soil loading observed
was a geometric mean dermal loading of 0.7 mg/cm2,
found on the children's hands following play in wet
soil. Mean loadings were lower on hands in the dry soil
trial and on lower legs, forearms, and faces in both the
wet and dry soil trials. Higher loadings were observed
for all body surfaces with the higher moisture content
soils.
This report is valuable in showing soil
loadings from soils of different moisture content and
providing evidence that dermal exposure to soil is not
uniform for various body surfaces. This study also
provides some evidence of the protective effect of
clothing. Disadvantages of the study include the small
number of study participants and a short activity
duration.
7.5 REFERENCES FOR CHAPTER 7
Boyd, E. (1935) The growth of the surface area of the
human body. Minneapolis, MN: University
of Minnesota Press.
Buyken, A.E.; Hahn, S.; Kroke, A. (2005) Differences
between recumbent length and stature
measurement in groups of 2- and 3-y-old
children and its relevance for the use of
European body mass index references. Int J
Obes 29:24-28.
Cohen-Hubal, E.A.; Sheldon, L.S.; Burke, J.M.;
McLundy, T.R.; Berry, M.R.; Rigas, M.L.;
Zartarian, V.G.; Freeman, N.C.G. (1999)
Children's exposure assessment: A review of
factors influencing children's exposure, and
the data available to characterize and assess
that exposure. Research Triangle Park, NC:
U.S. EPA, National Exposure Research
Laboratory.
D'Agostino, R.B.; Belanger, A.; D'Agostino, R.B. Jr. A
suggestion for using powerful and informative
tests of normality. The American Statistician
44(4);316-321.
Dubois, D.; Dubois, E.F. (1916) A formula to estimate
the approximate surface area if height and
weight be known. Arch Intern Med 17:863-
871.
Garlock, T.J.; Shirai, J.H.; Kissel, J.C. (1999) Adult
responses to a survey of soil contact related
behaviors. J Expo Anal Environ Epidemiol
9:134-142.
Gehan, E.; George, G.L. (1970) Estimation of human
body surface area from height and weight.
Cancer ChemotherRep 54(4):225-235.
George, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz,
G.J. (1979) Letters to the editor. J Pediatr
94(2):342.
Holmes, Jr., K.K.; Shirai, J.H.; Richter, K.Y.; Kissel,
J.C. (1999) Field measurement of dermal
loadings in occupational and recreational
activities. Environ Res Section A80:148-157.
Kissel, J.C.; Richter, K.; Fenske, R. (1996a) Field
measurements of dermal soil loading
attributable to various activities: Implications
for exposure assessment. Risk Anal
Kissel, J.C.; Richter, K.; Duff, R.; Fenske, R. (1996b)
Factors affecting soil adherence to skin in
hand-press trials. Bull Environ Contam
Toxicol 56:722-728.
Kissel, J.C.; Shirai, J.H.; Richter, K.Y.; Fenske, R.A.
(1998) Investigation of dermal contact with
soil in controlled trials. J Soil Contam 7(6):
737-752.
Phillips, L.J.; Fares, R.J.; Schweer, L.G. (1993)
Distributions of total skin surface area to body
weight ratios for use in dermal exposure
assessments. J Expo Anal Environ Epidemiol
3(3):331-338.
Shoaf, M.B.; Shirai, J.H.; Kedan, G.; Schaum, J.;
Kissel, J.C. (2005) Child dermal sediment
loads following play in a tide flat. J Expo
Anal Environ Epidemiol 15:407-412.
U.S. EPA (1985) Development of statistical
distributions or ranges of standard factors used
in exposure assessments. Washington, DC:
Office of Research and Development, Office
of Health and Environmental Assessment.
EPA 600/8-85-010. Available from: NTIS,
Springfield, VA. PB85-242667.
U.S. EPA (1992a) Guidelines for exposure assessment.
Federal Register. FR 57:104:22888-22938.
May 29, 1992.
U.S. EPA (1992b) Dermal exposure assessment:
principles and applications. Washington, DC :
Office of Research and Development, Office
of Health and Environmental
Assessment/OHEA. U.S. EPA/600/8-9-91.
U.S. EPA (2004) Risk assessment guidance for
Superfund (RAGS): Volume I, Human Health
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Chapter 7 - Dermal Exposure Factors
Evaluation Manual, Part E. Washington, DC.
EPA/540/R/99/005.
U.S. EPA (2005) Guidance on selecting age groups for
monitoring and assessing childhood exposures
to environmental contaminants. U.S.
Environmental Protection Agency,
Washington, DC. EPA/630/P-03/003F.
November 2005.
Van Graan, C.H. (1969) The determination of body
surface area. S AfrMed J 43(31):952-959.
Wong, E.Y.; Shirai, J.H.; Garlock, T.J.; Kissel, J.C.
(2000) Adult proxy responses to a survey of
children's dermal soil contact activities. J
Expo Anal Environ Epidemiol 10:509-517.
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Table 7-6. Percentage of Total Body Surface Area by Body Part For Children
Males and Females Combined
Age
(years)
<1
1 <2
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9< 10
11 <12
12<13
13<14
14<15
15<16
16<17
17 < 18
N
Min.
Max.
Source:
N Head
Mean Min-Max
2:0 18.2 18.2-18.3
1:1 16.5 16.5-16.5
1:0 14.2
0:5 13.6 13.3-14.0
1:3 13.8 12.1-15.3
1:0 13.1
0:2 12.0 11.6-12.5
1:0 8.7
1:0 10.0
1:0 8.0
1:0 7.6
= Number of subjects, (M:F =
= Minimum percent.
= Maximum percent.
U.S. EPA, 1985.
Trunk
Mean Min-Max
35.7 34.8-36.6
35.5 34.5-36.6
38.5
31.9 29.9-32.8
31.5 30.5-32.4
35.1
34.2 33.4-34.9
34.7
32.7
32.7
31.7
males:females).
Percent of Total
Arms Hands Legs Feet
Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max
13.7 12.4-15.1 5.3 5.2-5.4 20.6 18.2-22.9 6.5 6.5-6.6
13.0 12.8-13.1 5.7 5.6-5.8 23.1 22.1-24.0 6.3 5.8-6.7
11.8 5.3 23.2 7.1
14.4 14.2-14.7 6.1 5.8-6.3 26.8 26.0-28.6 7.2 6.8-7.9
14.0 13.0-15.5 5.7 5.2-6.6 27.8 26.0-29.3 7.3 6.9-8.1
13.1 4.7 27.1 6.9
12.3 11.7-12.8 5.3 5.2-5.4 28.7 28.5-28.8 7.6 7.4-7.8
13.7 5.4 30.5 7.0
12.1 5.1 32.0 8.0
13.1 5.7 33.6 6.9
17.5 5.1 30.8 7.3
s
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Chapter 7 - Dermal Exposure Factors
Table 7-7. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES 1999-2006
Males and Females Combined
Percentiles
N
154
281
488
923
1159
1122
2303
3590
5294
4843
Mean
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
5th
0.24
0.27
0.33
0.38
0.45
0.52
0.61
0.81
1.19
1.47
10th
0.25
0.29
0.34
0.39
0.46
0.54
0.64
0.85
1.25
1.53
15th
0.26
0.29
0.35
0.40
0.47
0.55
0.66
0.88
1.31
1.58
25th
0.27
0.31
0.36
0.42
0.49
0.57
0.68
0.93
1.4
1.65
50th
0.29
0.33
0.38
0.45
0.53
0.61
0.74
1.05
1.57
1.80
75th
0.31
0.35
0.40
0.48
0.56
0.64
0.81
1.21
1.75
1.99
85th
0.31
0.37
0.42
0.49
0.58
0.67
0.85
1.31
1.86
2.10
90th
0.33
0.37
0.43
0.50
0.59
0.68
0.89
1.36
1.94
2.21
95th
0.34
0.38
0.44
0.51
0.61
0.70
0.95
1.48
2.06
2.33
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Table 7-8. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <1 6 years
16 to <21 years
Skin Surface Area (m2) Derived from U
Males
S. EPA Analysis of NHANES 1999-2006
Percentiles
N
85
151
255
471
620
548
1150
1794
2593
2457
Mean
0.29
0.33
0.39
0.45
0.53
0.62
0.76
1.09
1.61
1.94
5th
0.24
0.28
0.34
0.39
0.46
0.54
0.61
0.82
1.17
1.61
10th
0.25
0.29
0.35
0.41
0.47
0.56
0.64
0.86
1.23
1.66
15th
0.26
0.30
0.36
0.42
0.48
0.56
0.66
0.89
1.28
1.7
25th
0.27
0.31
0.37
0.43
0.50
0.58
0.69
0.94
1.39
1.76
50th
0.29
0.34
0.39
0.46
0.53
0.62
0.75
1.06
1.60
1.91
75th
0.31
0.36
0.41
0.48
0.57
0.65
0.82
1.21
1.79
2.08
85th
0.33
0.37
0.42
0.49
0.58
0.67
0.86
1.29
1.90
2.22
90th
0.34
0.37
0.43
0.50
0.59
0.68
0.89
1.34
1.99
2.30
95th
0.36
0.38
0.44
0.51
0.62
0.70
0.95
1.46
2.12
2.42
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Child-Specific Exposure Factors Handbook
September 2008
Page
7-17
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Table 7-9. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Skin Surface Area (m2) Derived from U
Females
S. EPA Analysis of NHANES 1999-2006
Percentiles
N
69
130
233
452
539
574
1153
1796
2701
2386
Mean
0.28
0.32
0.38
0.44
0.52
0.60
0.75
1.08
1.57
1.73
5th
0.24
0.27
0.32
0.38
0.44
0.51
0.61
0.80
1.20
1.42
10th
0.25
0.28
0.33
0.39
0.46
0.53
0.64
0.85
1.28
1.47
15th
0.26
0.29
0.34
0.40
0.47
0.54
0.66
0.87
1.34
1.51
25th
0.27
0.30
0.35
0.41
0.48
0.56
0.68
0.92
1.42
1.57
50th
0.28
0.31
0.38
0.44
0.52
0.59
0.74
1.04
1.55
1.69
75th
0.30
0.35
0.40
0.47
0.56
0.63
0.80
1.21
1.69
1.85
85th
0.30
0.36
0.40
0.48
0.57
0.66
0.84
1.33
1.8
1.98
90th
0.31
0.37
0.41
0.49
0.58
0.67
0.88
1.39
1.88
2.06
95th
0.33
0.37
0.43
0.51
0.59
0.70
0.94
1.51
2.00
2.17
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Page
7-18
Child-Specific Exposure Factors Handbook
September 2008
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00
I
ri
1=
Table 7-10. Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (m2/kg)
Age
(years)
Oto2
2.1 to 17
SD
SE
Source:
Rannp
Mean ,,. // SD SE
Mm-Max ^ w
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Table 7-11. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities
Age (years)
N
Mean
Median
SD
N = Number of observations.
SD = Standard deviation.
Source: Wong et al., 2000.
Skin Area Exposed (% of total body
Play Gardening/yardwork
<5 5-17
41 437
38.0 33.8
36.5 33.0
6.0 8.3
surface area)
Organized Team Sport
5-17
65
29.0
30.0
10.5
Page Child-Specific Exposure Factors Handbook
7-20 September 2008
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I
ri
1=
1ab\el-\2. Summary of 7 ie\d Studies
Activity
Month Event1 (hrs)
N
M
F
Age (years)
Conditions
Clothing Study
Indoor
fae Kwon Do
Indoor Kids No. I
Indoor Kids No. 2
Daycare Kids No. la
Daycare Kids No. \b
Daycare Kids No. 2b
Daycare Kids No. 3
Feb. 1.5
Jan. 2
Feb. 2
Aug. 3.5
Aug. 4
Sept. 8
Nov. 8
7
4
6
6
6
5
4
6
3
4
5
5
4
3
1
1
2
1
1
1
1
8-42
6-13
3-13
1-6.5
1-6.5
1-4
1-4.5
Carpeted floor
Playing on carpeted floor
Playing on carpeted floor
Indoors: linoleum surface;
Outdoors: grass, bare earth,
barked area
Indoors: linoleum surface;
Outdoors: grass, bare earth,
barked area
Indoors: low napped
carpeting, linoleum surfaces
Indoors: linoleum surface,
Outside: grass, bare earth,
barked area
All in long sleeve-long pants martial Kissel et al.,
arts uniform, sleeves rolled back, 1996a
barefoot
3 of 4 short pants, 2 of 4 short Holmes et al.,
sleeves, socks, no shoes 1999
5 of 6 long pants, 5 of 6 long sleeves,
socks, no shoes
4 of 6 in long pants, 5 of 6 short
sleeves, socks, shoes
4 of 6 long pants, 5 of 6 short
sleeves, 3 of 6 barefoot all afternoon,
others barefoot half the afternoon
4 of 5 long pants, 3 of 5 long sleeves,
all barefoot for part of the day
All long pants, 3 of 4 long sleeves,
socks and shoes
Outdoor
Soccer
Kids-in-mud No. I
Kids-in-mud No. 2
Gardeners
Archeologists
Shoreline Play
* Event duration.
Nov. 0.67
Sept. 0.17
Sept. 0.33
Aug. 4
July 11.5
Sept. 0.33-1.0
8
6
6
8
7
9
8
5
5
1
3
6
0
1
1
7
4
3
13-15
9-14
9-14
16-35
16-35
7-12
Half grass- half bare earth
Lake shoreline
Lake shoreline
Weeding, pruning, digging a
trench
Digging with trowel,
screening dirt, sorting
Tidal flat
6 of 8 long sleeves, 4 of 8 long pants, Kissel et al.,
3 of 4 short pants and shin guards 1996a
All in short sleeve T-shirts, shorts,
barefoot
All in short sleeve T-shirts, shorts,
barefoot
6 of 8 long pants, 7 of 8 short Holmes et al.,
sleeves, 1 sleeveless, socks, shoes, 1999
intermittent use of gloves
6 of 7 short pants, all short sleeves, 3
no shoes or socks, 2 sandals
No shirt or short sleeve T-shirts, Shoaf et al.,
shorts, barefoot 2005
b Activities were confined to the house.
N = Number of subj ects
M = Male.
F = Female.
I
1
s
ri
Q
ri
&
&
1=
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Table
Activity
7-13. Geometric Mean and Geometric Standard Deviations of Solids Adherence by
Activity and Body Region1
Post-activity Dermal Solids Loadings (mg/cm2)
Hands
Arms
Legs
Faces Feet
Indoor
Tae Kwon Do
Indoor Kids No. 1
Indoor Kids No. 2
Day care Kids No. la
Day care Kids No. Ib
Day care Kids No. 2
Day care Kids No. 3
7
4
6
6
6
5
4
0.0063
1.9
0.0073
1.9
0.014
1.5
0.11
1.9
0.15
2.1
0.073
1.6
0.036
1.3
0.0019
4.1
0.0042
1.9
0.0041
2.0
0.026
1.9
0.031
1.8
0.023
1.4
0.012
1.2
0.0020
2.0
0.0041
2.3
0.0031
1.5
0.030
1.7
0.023
1.2
0.011
1.4
0.014
3.0
0.0022
2.1
0.012
1.4
0.0091
1.7
0.079
2.4
0.13
1.4
0.044
1.3
0.0053
5.1
Outdoor
Soccer
Kids-in-mud No. 1
Kids-in-mud No. 2
Gardeners
Archeologists
Shoreline Play
8
6
6
8
7
9
0.11
1.8
35
2.3
58
2.3
0.20
1.9
0.14
1.3
0.49
8.2
* Means are presented above the standard deviations
indicating high variability in the data.
N = Number of subj ects .
Sources: Kissel et al., 1996a; Holmes
0.011
2.0
11
6.1
11
3.8
0.050
2.1
0.041
1.9
0.17
3.1
0.031
3.8
36
2.0
9.5
2.3
0.072
-
0.028
4.1
0.70
3.6
0.012
1.5
24
3.6
6.7
12.4
0.058 0.17
1.6
0.050 0.24
1.8 1.4
0.04 21
2.9 1.9
. The standard deviations generally exceed the means by large amounts
etal., 1999; Shoafetal., 2005.
Page
7-22
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Table 7-14. Summary of Controlled Greenhouse Trials - Children Playing
a
N
Activity Ages Duration (min) Soil Moisture Clothing" N Male
(years) (%)
Playing 8 to 12 20 17-18 L 4 3
16-18 S 9 5
3-4 S 5 3
L, long sleeves and long pants; S, short sleeves and short pants.
= Number of subjects.
Female
1
4
2
Source: Kissel etal., 1998.
Child-Specific Exposure Factors Handbook Page
September 2008 7-23
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Hands
Lower legs/short pants
Forearms/short sleeves
-
0 20
1—r~
40
60
•—r~
80
'—I
100
Percent Fluorescing
Figure 7-1. Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing in Wet
Soils (bars are arithmetic means and corresponding 95% confidence intervals)
Source: Kissel etal, 1998.
10 -,
child, wet
"O
«s
o
']
0,1-
0.01-
0 00!
4
child, dry
I
T
"T
f t
1 ' <
i
> ,. I
T
- T? j
ff
Figure 7-2. Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils (symbols are
geomettric means and 95% confidence intervals)
Source: Kissel etal., 1998.
Page
7-24
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
APPENDIX 7A
FORMULAS FOR TOTAL BODY SURFACE AREA
Child-Specific Exposure Factors Handbook Page
September 2008 7A-1
-------
Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
APPENDIX 7A - FORMULAS FOR TOTAL
BODY SURFACE AREA
Most formulas for estimating surface area (S A)
relate height to weight to surface area. The following
formula was proposed by Gehan and George (1970):
SA = KW2/3
(Eqn. 7A-1)
where:
SA = surface area in square meters;
W = weight in kg; and
K = constant.
While the above equation has been criticized
because human bodies have different specific gravities
and because the surface area per unit volume differs for
individuals with different body builds, it gives a
reasonably good estimate of surface area.
A formula published in 1916 that still finds
wide acceptance and use is that of DuBois and DuBois
(1916). Their model can be written:
SA =
(Eqn. 7A-2)
where:
SA = surface area in square meters;
H = height in centimeters; and
W = weight in kg.
The values of a0 (0.007182), al (0.725), and a2
(0.425) were estimated from a sample of only nine
individuals for whom surface area was directly
measured. Boyd (1935) stated that the Dubois formula
was considered a reasonably adequate substitute for
measuring surface area. Nomograms for determining
surface area from height and mass presented in Volume
I of the Geigy Scientific Tables (1981) are based on the
DuBois and DuBois formula. 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.
Boyd (1935) developed new constants for the
DuBois and DuBois model based on 231 direct
measurements of body surface area found in the
literature. These data were limited to measurements of
surface area by coating methods (122 cases), surface
integration (93 cases), and triangulation (16 cases).
The subjects were Caucasians of normal body build for
whom data on weight, height, and age (except for exact
age of adults) were complete. Resulting values for the
constants in the DuBois and DuBois model were a0 =
0.01787, E! = 0.500, and a2 = 0.4838. Boyd also
developed a formula based exclusively on weight,
which was inferior to the DuBois and DuBois formula
based on height and weight.
Gehan and George (1970) proposed another
set of constants for the DuBois and DuBois model. The
constants were based on a total of 401 direct
measurements of surface area, height, and weight of all
postnatal subjects listed in Boyd (1935). The methods
used to measure these subjects were coating (163
cases), surface integration (222 cases), and triangulation
(16 cases).
Gehan and George (1970) used a least-squares
method to identify the values of the constants. The
values of the constants chosen are those that minimize
the sum of the squared percentage errors of the
predicted values of surface area. This approach was
used because the importance of an error of 0.1 square
meter depends on the surface area of the individual.
Gehan and George (1970) used the 401 observations
summarized in Boyd (1935) in the least-squares
method. The following estimates of the constants were
obtained: a0 = 0.02350, al = 0.42246, and a2 = 0.51456.
Hence, their equation for predicting SA is:
SA = 0.02350 H
-0.42246-1-170.51456
W°
(Eqn. 7A-3)
or in logarithmic form:
InSA = -3.75080 + 0.42246 InH + 0.51456 InW
(Eqn. 7A-4)
where:
SA = surface area in square meters;
H = height in centimeters; and
W = weight in kg.
This prediction explains more than 99 percent
of the variations in surface area among the 401
individuals measured (Gehan and George, 1970).
Page
7A-2
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
The equation proposed by Gehan and George
(1970) was determined by the U.S. EPA (1985) as the
best choice for estimating total body surface area.
However, the paper by Gehan and George gave
insufficient information to estimate the standard error
about the regression. Therefore, the 401 direct
measurements of children and adults (i.e., Boyd, 1935)
were reanalyzed in U. S. EPA (1985) using the formula
of Dubois and Dubois (1916) and the Statistical
Processing System (SPS) software package to obtain
the standard error.
The Dubois and Dubois (1916) formula uses
weight and height as independent variables to predict
total body surface area (SA), and can be written as:
SA. =a0Ha'W.a'e. (Eqn. 7A-5)
or in logarithmic form:
ln(SA), = Ina0 + aJnH, + a2lnW, + Ine, (Eqn. 7A-6)
where:
SAj = surface area of the i-th
individual (m2);
Hj = height of the i-th individual
(cm);
Wj = weight of the i-th individual
(kg);
a0, ab and a2 = parameters to be estimated;
and
e; = a random error term with
mean zero and constant
variance.
Using the least squares procedure for the 401
observations, the following parameter estimates and
their standard errors were obtained:
a0 = -3.73 (0.18), al = 0.417 (0.054), a2 = 0.517 (0.022)
The model is then:
SA = 0.0239 H°-417W°-517 (Eqn. 7A-7)
or in logarithmic form:
In SA = 3.73 + 0.417 InH + 0.517 InW (Eqn. 7A-8)
with a standard error about the regression of 0.00374.
This model explains more than 99 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).
When natural logarithms of the measured
surface areas are plotted against natural logarithms of
the surface predicted by the equation, the observed
surface areas are symmetrically distributed around a
line of perfect fit, with only a few large percentage
deviations. Only five subjects differed from the
measured value by 25 percent or more. Because each
of the five subjects weighed less than 13 pounds, the
amount of difference was small. Eighteen estimates
differed from measurements by 15 to 24 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 subjects, the possibility of
some bias in measured values cannot be discounted
(Gehan and George 1970).
Gehan and George (1970) also considered
separate constants for different age groups: less than
5 years old, 5 years old to less than 20 years old, and
greater than 20 years old. The different values for the
constants are presented in Table 7A-1.
The surface areas estimated using the parameter values
for all ages were compared to surface areas estimated
by the values for each age group for subjects at the
3rd, 50th, and 97th percentiles of weight and height.
Nearly all differences in surface area estimates were
less than 0.01 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 a0, ab and a2 by age interval.
Haycock et al. (1978) without knowledge of
the work by Gehan and George (1970), developed
values for the parameters a0, ab and a2 for the DuBois
and DuBois model. Their interest in making the
DuBois and DuBois model more accurate resulted
from their work in pediatrics and the fact that DuBois
and DuBois (1916) included only one child in their
study group, a severely undernourished girl who
weighed only 13.8 pounds at age 21 months. Haycock
et al. (1978) used their own geometric method for
estimating surface area from 34 body measurements
for 81 subjects. Their study included newborn infants
(10 cases), infants (12 cases), children (40 cases), and
Page
7A-3
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
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 subjects
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: a0 =
0.024265, E! = 0.3964, and a2 = 0.5378. The result was
the following equation for estimating surface area:
SA = 0.024265H°-3964W°-5378 (Eqn. 7A-9)
expressed logarithmically as:
In SA = In 0.024265 + 0.3964 In H
(Eqn. 7A-10)
-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 model more
complex than the model of DuBois and DuBois for
estimating surface area is unnecessary. Based on
samples of direct measurements by Boyd (1935) and
Gehan and George (1970), and samples of geometric
estimates by Haycock 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:
InSA = Ina0 + al InH + a2 InW
(Eqn. 7A-11)
The values for a0, ab and a2 obtained by the
various authors discussed in this section are presented
in Table 7A-2.
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. (1978) were unaware of the previous
work. Haycock et al. (1978) used an entirely different
set of subjects, and used geometric estimates of surface
area rather than direct measurements. It has been
determined that the Gehan and George model is the
formula of choice for estimating total surface area of
the body since it is based on the largest number of
direct measurements.
Sendroy and Cecchini (1954) proposed a
method of creating a nomogram, a diagram relating
height and weight to surface area. However, they do
not give an explicit model for calculating surface area.
The nomogram was developed empirically based on
252 cases, 127 of which were from the 401 direct
measurements reported by Boyd (1935). In the other
125 cases the surface area was estimated using the
linear method of DuBois and DuBois (1916). Because
the Sendroy and Cecchini method is graphical, it is
inherently less precise and less accurate than the
formulas of other authors discussed above.
REFERENCES FOR APPENDIX 7A
Boyd, E. (1935) The growth of the surface area of
the human body. Minneapolis, MN:
University of Minnesota Press.
Dubois, D.; Dubois, E.F. (1916) A formula to
estimate the approximate surface area if
height and weight be known. Arch Intern
Med 17:863-871.
Gehan, E.; George, G.L. (1970) Estimation of human
body surface area from height and weight.
Cancer Chemother Rep 54(4):225-235.
Geigy Scientific Tables (1981) Nomograms for
determination of body surface area from
height and mass. Lentner, C. (ed.). CIBA-
Geigy Corporation, West Caldwell, NJ. pp.
226-227.
Haycock, G.B.; Schwartz, G.J.; Wisotsky, D.H.
(1978) Geometric method for measuring
body surface area: A height-weight formula
validated in infants, children, and adults. J
Pediatr 93(l):62-66.
Sendroy, J.; Cecchini, L.P. (1954) Determination of
human body surface area from height and
weight. JApplPhysiol7(l):3-12.
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 7 - Dermal Exposure Factors
Table 7A-1 . Estimated Parameter Values for Different Age Intervals
Age
Group
All ages
<5 years old
>5to <20 years old
>20 years old
Number
of persons
401
229
42
30
a0
0.02350
0.02667
0.03050
0.01545
*i
0.42246
0.38217
0.35129
0.54468
a2
0.51456
0.53937
0.54375
0.46336
Table 7A-2.
Author
(year)
DuBois and DuBois (1916)
Boyd (1935)
Gehan and George (1970)
Haycock etal. (1978)
Summary of Surface Area
Number
of persons
9
231
401
81
Parameter Values
a0
0.007184
0.01787
0.02350
0.024265
for the Dubois and Dubois Model
*i
0.725
0.500
0.42246
0.3964
a2
0.425
0.4838
0.51456
0.5378
Child-Specific Exposure Factors Handbook
September 2008
Page
7A-5
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
TABLE OF CONTENTS
BODY WEIGHT STUDIES 8-1
8.1 INTRODUCTION 8-1
8.2 RECOMMENDATIONS 8-1
8.3 KEY BODY WEIGHT STUDY 8-4
8.3.1 U.S. EPA analysis of NHANES 1999-2006 data 8-4
8.4 RELEVANT BODY WEIGHT STUDIES 8-4
8.4.1 National Center for Health Statistics, 1987 8-4
8.4.2 Burmaster and Crouch, 1997 8-5
8.4.3 U.S. EPA, 2000 8-5
8.4.4 Kuczmarski et al, 2002 8-5
8.4.5 Ogden et al., 2004 8-6
8.4.6 Freedman et al., 2006 8-6
8.4.7 Martin et al., 2007 8-7
8.4.8 Portier et al., 2007 8-7
8.4.9 Kahn and Stralka, 2008 8-8
8.5 RELEVANT FETAL WEIGHT STUDIES 8-8
8.5.1 Brenner et al., 1976 8-8
8.5.2 Doubilet et al., 1997 8-8
8.6 REFERENCES FOR CHAPTER 8 8-9
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September 2008 8-i
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
LIST OF TABLES
Table 8-1. Recommended Values for Body Weight 8-2
Table 8-2. Confidence in Recommendations for Body Weight 8-3
Table 8-3. Mean and Percentile Body Weights (kilograms) Derived from NHANES 1999-2006, Males and
Females Combined 8-10
Table 8-4. Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES
1999-2006 8-11
Table 8-5. Mean and Percentile Body Weights (kilograms) for Females Derived from
NHANES 1999-2006 8-11
Table 8-6. Weight in Kilograms for Males 2 Months-19 Years of Age- Number Examined, Mean, and
Selected Percentiles, by Age Category: United States, 1976-1980 8-12
Table 8-7. Weight in Kilograms for Females 6 Months-19 Years of Age-Number Examined, Mean, and
Selected Percentiles, by Age Category: United States, 1976-1980 8-13
Table 8-8. Statistics for Probability Plot Regression Analyses:
Females Body Weights 6 Months to 20 Years of Age 8-14
Table 8-9. Statistics for Probability Plot Regression Analyses:
Males Body Weights 6 Months to 20 Years of Age 8-15
Table 8-10. Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From
NHANES III (1988-94 8-16
Table 8-11. Body Weight Estimates (in kilograms) by Age, U. S. Population Derived From
NHANES III (1988-94 8-17
Table 8-12. Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender
and Age: Birth to 36 Months 8-18
Table 8-13. Mean Body Weight (kilograms) by Age and Gender Across Multiple Surveys 8-25
Table 8-14. Mean Height (centimeters) by Age and Gender Across Multiple Surveys 8-26
Table 8-15. Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys 8-27
Table 8-16. Sample Sizes by Age, Sex, Race, and Examination 8-28
Table 8-17. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex .... 8-29
Table 8-18. Prevalence of Overweight and Obesity* Among Children 8-30
Table 8-19. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth
Weights, by Race and Hispanic Origin of Mother: United States, 2005 8-31
Table 8-20. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
NHANES II Data 8-32
Table 8-21. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
NHANES III Data 8-33
Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
NHANES IV Data 8-34
Table 8-23. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments . . 8-35
Table 8-24. Estimated Percentile Distribution of Body Weight by Fine Age Categories 8-35
Table 8-25. Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence
Interval 8-36
Table 8-26. Fetal Weight (grams) Percentiles Throughout Pregnancy 8-37
Table 8-27. Neonatal Weight by Gestational Age for Males and Females Combined 8-38
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Chapter 8 - Body Weight
LIST OF FIGURES
Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months 8-19
Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months 8-20
Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months 8-21
Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months 8-22
Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years 8-23
Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years 8-24
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
8 BODY WEIGHT STUDIES
8.1 INTRODUCTION
The average daily dose (ADD) is a dose that is
typically normalized to the average body weight of the
exposed population. If exposure occurs only during
childhood years, the average child body weight during
the exposure period should be used to estimate risk
(U.S. EPA, 1989).
The purpose of this section is to describe a key
published study on body weight for children in the
general U.S. population, as described in Section 1.5 of
this handbook. The recommendations for body weight
are provided in the next section, along with a summary
of the confidence ratings for these recommendations.
The recommended values are based on one key study
identified by U.S. EPA for this factor. Following the
recommendations, the key study on body weight is
summarized. Relevant data on body weight are also
provided. Since childhood obesity is a growing
concern and may increase the risk of chronic diseases
during adulthood, information on body mass index
(BMI) and height are also provided.
8.2 RECOMMENDATIONS
The recommended values for body weight are
summarized in Table 8-1. Table 8-2 presents the
confidence ratings for body weight recommendations.
The recommended values represent mean body weights
in kilograms for the age groups recommended by U. S.
EPA in Guidance for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). Use of upper percentile body weight
values are not routinely recommended for calculating
ADDs because inclusion of an upper percentile value in
the denominator of the ADD equation would be a non-
conservative approach. However, distributions of body
weight data are provided in section 8.3 of this chapter.
These distributions may be useful if probabilistic
methods are used to assess exposure. Also, if gender-
specific data are needed, or if data for finer age bins are
needed, the reader should refer to the tables in Section
8.3.
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Chapter 8 - Body Weight
Table 8-1.
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <11 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Recommended Values for Body Weight
Mean Multiple _
_ ;•, Source
^ Percentiles
4.8
5.6
7.4
9.2
11,1 r,, , , o ^ U.S. EPA analysis of
I l«< NHANES, 1999-2006
13.8 through 8-5 ^
18.6
31.8
56.8
71.6
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Chapter 8 - Body Weight
Table
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
8-2. Confidence in Recommendations for Body Weight
Rationale
The survey methodology and secondary data analysis
analysis was adequate. NHANES consisted of a large
sample size; sample size varied with age. Direct
measurements were taken during a physical examination.
No significant biases were apparent.
The key study is directly relevant to body weight.
NHANES was a nationally representative sample of the
U.S. population; participants are selected using a complex,
stratified, multi-stage probability cluster sampling design.
The U.S. EPA analysis used the most current NHANES
data.
The U.S. EPA analysis was based on 4 data sets of
NHANES data covering 1999-2006.
NHANES data are available from NCHS; the U.S. EPA
analysis of the NHANES data is available upon request.
The methods used were well-described; enough information
was provided to allow for reproduction of results.
Quality assurance of NHANES data was good; quality
control of secondary data analysis was not well described.
The full distributions were given in the key study.
No significant uncertainties were apparent in the NHANES
data, nor in the secondary analyses of the data.
NHANES received a high level of peer review. The
U.S. EPA analysis was not published in a peer-reviewed
journal.
The number of studies is 1.
Rating
High
High
High
High
Medium
High
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Chapter 8 - Body Weight
8.3 KEY BODY WEIGHT STUDY
8.3. 1 U.S. EPA analysis of NHANES 1999-2006
data
The U.S. EPA analyzed data from the 1999-
2006 National Health and Nutrition Examination
Survey (NHANES) to generate distributions of body
weight for various age ranges of children. NHANES
is conducted annually by the Center for Disease
Control (CDC), National Center of Health Statistics
(NCHS). The survey's target population is the
civilian, noninstitutionalized U.S. population. The
NHANES 1999-2006 survey was conducted on a
nationwide probability sample of approximately
40,000 persons for all ages, of which approximately
20,000 were children. The survey is designed to
obtain nationally representative information on the
health and nutritional status of the population of the
United States through interviews and direct physical
examinations. A number of anthropometric
measurements, including body weight, were taken for
each participant in the study. Unit non-response to the
household interview was 1 9 percent, and an additional
4 percent did not participate in the physical
examinations (including body weight measurements).
The NHANES 1999-2006 survey includes
over-sampling of low-income persons, adolescents
12-19 years, persons 60+ years of age, African
Americans and Mexican Americans. Sample data were
assigned weights to account both for the disparity in
sample sizes for these groups and for other
inadequacies in sampling, such as the presence of
non-respondents. Because the U. S. EPA utilized four
NHANES data sets in its analysis (NHANES 1999-
2000, 200 1 -2002, 2003-2004, and 2005-2006) sample
weights were developed for the combined data set in
accordance with CDC guidance from the NHANES'
website
(http ://www. cdc. gov/nchs/about/maj or/nhanes/nhane
s2005-2006/faqs05_06.htm#question%20 1 2).
Using the data and the weighting factors from
the four NHANES data sets, U.S. EPA calculated
body weight statistics for the standard age categories.
The mean value for a given group was calculated using
the following formula:
(Eqn.8-1)
where:
X = sample mean;
x,. = the i* observation;
w, = sample weight assigned to observation
Percentile values were generated by first
calculating the sum of the weights for all observations in
a given group and multiplying this sum by the percentile
of interest (e.g., multiplying by 0.25 to determine the 25th
percentile). The observations were then ordered from
least to greatest, and each observation was assigned a
cumulative weight, equal to its own weight plus all
weights listed before the observation. The first
observation listed with a cumulative weight greater than
the value calculated for the percentile of interest was
selected.
Table 8-3 presents the body weight means and
percentiles, by age category, for male and female
children, combined. Tables 8-4 and 8-5 present the body
weight means and percentiles for male and female
children, respectively.
The advantage of this study is that it provides
body weight distributions for children at ages ranging
from infancy to young adults. A limitation of the study
is that the data in Tables 8-3 to 8-5 may underestimate
current body weights due to an observed upward trend in
body weights (Ogden et al, 2004). However, the
NHANES data are nationally representative and remain
the principal source of body weight data collected
nationwide from a large number of subjects.
8.4 RELEVANT BODY WEIGHT STUDIES
8.4.1 National Center for Health Statistics, 1987 -
Anthropometric reference data and
prevalence of overweight, United States,
1976-80
This study used anthropometric measurement
data for body weight for the U.S. population that were
collected by NCHS as part of the second National Health
and Nutrition Examination Survey (NHANES II).
NHANES II began in February 1976 and was completed
in February 1980. The survey was conducted on a
nationwide probability sample of 27,801 persons aged 6
months to 74 years from the civilian, noninstitutionalized
population of the United States. A total of 20,322
individuals in the sample were interviewed and
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Chapter 8 - Body Weight
examined, resulting in a response rate of 73.1 percent.
The sample was selected so that certain subgroups
thought to be at high risk of malnutrition (persons with
low incomes, preschool children, and the elderly) were
over sampled. The estimates were weighted to reflect
national population estimates. The weighting was
accomplished by inflating examination results for each
subject by the reciprocal of selection probabilities,
adjusted to account for those who were not examined,
and-post stratifying by race, age, and sex.
NHANES II collected standard body
measurements of sample subjects, including height and
weight, that were made at various times of the day and
in different seasons of the year. This technique was
used because an individual's weight may vary between
winter and summer and may fluctuate with patterns of
food and water intake and other daily activities
(NCHS, 1987). NCHS (1987) provided descriptive
statistics of the body weight data. Means and
percentiles, by age category, are presented in Table 8-
6 for males, and in Table 8-7 for females.
The advantages of the study are that it is
nationally representative and provides data for various
age groups of children, beginning at 2 months of age.
The limitation of the study is the age of the data.
8.4.2 Burmaster and Crouch, 1997 - Lognormal
distributions for body weight as a function
of age for males and females in the United
States, 1976-1980
Burmaster and Crouch (1997) performed data
analysis to fit normal and lognormal distributions to
the body weights of females and males aged 9 months
to 70 years. The data used in this analysis were from
the second survey of the National Center for Health
Statistics, NHANES II, which was based on a national
probability sample of 27,801 persons 6 months to 74
years of age in the U. S. (Burmaster and Crouch 1997).
The NHANES II data had been statistically adjusted
for non-response and probability of selection, and
stratified by age, sex, and race to reflect the entire U.S.
population prior to reporting. Burmaster and Crouch
(1997) conducted exploratory and quantitative data
analyses and fit normal and lognormal distributions to
percentiles of body weights of children and teens, as a
function of age. Cumulative distribution functions
were plotted for female and male body weights on
both linear and logarithmic scales.
Burmaster and Crouch (1997) used "maximum
likelihood" estimation to fit lognormal distributions to
the data. Linear and quadratic regression lines were
fitted to the data. A number of goodness-of-fit measures
were conducted on the data generated. The investigators
found that lognormal distributions gave strong fits to the
data for each gender across all age groups. The statistics
for the lognormal probability plots for female and male
children aged 9 months to 20 years are presented in
Tables 8-8 and 8-9, respectively. These data can be used
for further analyses of body weight distribution (i.e.,
application of Monte Carlo analysis).
The advantage of this study is that NHANES
data were used for the analysis and the data are
representative nationally. It also provides statistics for
probability plot regression analyses for females and
males from 6 months to 20 years old. However, the
analysis is based on an older set of NHANES data.
8.4.3 U.S. EPA, 2000 - Body weight estimates on
NHANES III Data
U. S. EP A's Office of Water has estimated body
weights for children by age and gender using data from
NHANES III, which was conducted from 1988 to 1994.
NHANES III collected body weight data for
approximately 15,000 children between the ages of 2
months and 17 years. Table 8-10 presents the body
weight estimates in kilograms by age and gender. Table
8-11 shows the body weight estimates for infants under
the age of 3 months.
The limitations of this analysis are that data
were not available for infants under 2 months old, and
that the data are roughly 14 to 20 years old. With the
upward trends in body weight from NHANES II (1976-
1980) to NHANES III, which may still be valid, the data
in Tables 8-10 and 8-11 may underestimate current body
weights. However, the data are national in scope and
represent the general children's population.
8.4.4 Kuczmarski et al., 2002 - 2000 CDC growth
charts for the United States: methods and
development
NCHS published growth charts for infants, birth
to 36 months of age, and children and adolescents, 2 to
20 years of age (Kuczmarski et al., 2002). Growth charts
were developed with data from five national health
examination surveys: National Health Examination
Survey (NHES) II (1963-65) for ages 6-11 years, NHES
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Chapter 8 - Body Weight
III (1966-70) for ages 12-17 years, National Health
and Nutrition Examination Survey (NHANES) I
(1971 -74) for ages 1-17 years, NHANES II (1976-80)
beginning at 6 months of age, and NHANES III (1988-
94) beginning at 2 months of age. Data from these
national surveys were pooled because no single survey
had enough observations to develop these charts. For
the infant charts, a limited number of additional data
points were obtained from other sources where
national data were either not available or insufficient.
Birth weights <1,500 grams were excluded when
generating the charts for weights and lengths. Also,
the length-for-age charts exclude data from NHANES
III for ages <3.5 months. Supplemental birth
certificate data from the U. S. vital statistics were used
in the weight-for-age charts and supplemental birth
certificate data from Wisconsin and Missouri vital
statistics, CDC Pediatric Nutrition Surveillance
System data were used for ages 0.5, 1.5, 2.5, 3.5, and
4.5 months for the length-for-age charts. The Missouri
and Wisconsin birth certificate data were also used to
supplement the surveys for the weight-for-length
charts. Table 8-12 presents the percentiles of weight
by gender and age. Figures 8-1 and 8-2 present weight
by age percentiles for boys and girls, aged birth to 36
months, respectively. Figures 8-3 and 8-4 present
weight by length percentiles for boys and girls,
respectively. Figures 8-5 and 8-6 provide the Body
Mass Index (BMI) for boys and girls aged 2 to 20
years old.
A limitation of this analysis is that trends in
the weight data cannot be assessed because data from
various years were combined. The advantages of this
analysis are that it is based on a nationally
representative sample of the U.S. population and it
provides body weight on a month-by-month basis up
to 36 months of age, as well as BMI data for children
through age 20 years.
8.4.5 Ogden et aL, 2004 - Mean body weight,
height, and body mass index, United States
1960-2002
Ogden et al. (2004) analyzed trends in body
weight measured by the National Health Examination
Surveys II and III (NHES II and III), the National
Health and Nutrition Examination Surveys I, II, and III
(NHANES I, II, and III), and NHANES 1999-2002.
The surveys covered the period from 1960 to 2002.
Table 8-13 presents the measured body weights for
various age groups as measured in NHES and NHANES.
Tables 8-14 and 8-15 present the mean height and BMI
data for the same population, respectively. The BMI
data were calculated as weight in kilograms divided by
the square of height in meters. Population means were
calculated using sample weights to account for variation
in sampling for certain subsets of the U.S. population,
non-response, and non-coverage (Ogden et al., 2004).
The data indicate that mean body weight has increased
over the period analyzed.
There is some uncertainty inherent in such an
analysis, however, because of changes in sampling
methods during the 42 year time span covered by the
studies. Because this study is based on an analysis of
NHANES data, its limitations are the same as those for
that study. However, it serves to illustrate the
importance of the use of timely data when analyzing
body weight.
8.4.6 Freedman et al., 2006 - Racial and ethnic
differences in secular trends for childhood
BMI, weight, and height
Freedman et al. (2006) examined sex and
race/ethnicity differences in secular trends for childhood
BMI, overweight, weight, and height in the United States
using data from NHANES I (1971 to 1974), NHANES
II (1976- 1980), NHANES III (1988 to 1994) and
NHANES 1999-2002. The analyses included children 2
to 17 years olds. Persons with missing weight or height
information were excluded from the analyses (Freedman
et al., 2006). The authors categorized the data across the
four examinations and presented the data for non-
Hispanic White, non-Hispanic Black, or Mexican
American. Freedman et al. (2006) excluded other
categories of race/ethnicity such as other Hispanics,
because the sample sizes were small. Height and weight
data were obtained for each survey and BMI was
calculated as weight in kilograms divided by height in
meters square. Sex specific z-scores and percentiles of
weight-for-age, height-for-age, and BMI-for-age were
calculated. Childhood overweight was defined as BMI-
for-age >95th percentile and childhood obesity was
defined as children with a BMI-for-age > 99th percentile.
In the analyses, sample weights were used to
account for differential probabilities, non-selection, non
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Chapter 8 - Body Weight
response, and non-coverage. The sample sizes used in
the analyses by age, race and survey are presented in
Table 8-16. Mean BMI levels are provided in Table
8-17 and the prevalence of overweight and obesity is
shown in Table 8-18. Table 8-17 shows that in 1971 -
1974 survey total population, Mexican American
children had the highest mean BMI level (18.6 kg/m2).
However the greatest increase throughout the survey
occurred among Black children increasing from 17.8
to 20 kg/m2 (Freedman et al, 2006). Table 8-18
shows that 2 to 5 year old White children had slightly
larger increases in overweight, but among the older
children, the largest increases were among the Black
and Mexican American children (Freedman et al.,
2006). Overall, in most sex-age groups, Mexican
Americans experienced the greater increase in BMI
and overweight than what was experienced by Black
and White Children (Freedman et al., 2006). Black
children experienced larger secular increases in BMI,
weight, and height than did White children (Freedman
et al., 2006). According to Freedman et al. (2006)
racial/ethnicity differences were less marked in the 2
to 5 years old children.
The advantages of the study are that the
sample size is large and the analysis was designed to
represent the general population of the racial and
ethnic groups studied. The disadvantage is that some
ethnic population groups were excluded because of
small sample sizes.
8.4.7 Martin et al., 2007 - Births: final data for
2005
Martin et al.(2007) provided statistics on the
percentage of live births categorized as having low or
very low birth weights in the U.S. Low birth weight
was defined as <2,500 grams (<5 pounds 8 ounces)
and very low birth weight was defined as <1,500
grams (<3 pounds 4 ounces). The data used in the
analysis were from birth certificates registered in all
states and the District of Columbia for births occurring
in 2005. Data were presented for maternal
demographic characteristics including race ethnicity:
non-Hispanic White, non-Hispanic Black, and
Hispanic.
The numbers of live births within various
weight ranges, and the percentages of live births with
low or very low birth weights are presented in Table 8-
19. The percentage of live births with low birth
weights was 8.2, and the percentage of very low birth
weights was 1.5 in 2005. Non-Hispanic Blacks had the
highest percentage of low birth weights (14.0 percent)
and very low birth weights (3.3 percent). Martin et al.
(2007) also provided statistics on the numbers and
percentages of pre-term live births in the U.S. Of the
4,138,349 live births in the U.S. in 2005, 522,913 were
defined as pre-term (i.e., less than 37 weeks gestation).
A total of 43.3 percent of these pre-term infants had low
birth weights an 11.3 percent had very low birth weights.
The advantage of this data set is that it is nationally
representative and provides data for infants.
8.4.8 Portier et al., 2007 - Body weight
distributions for risk assessment
Portier et al. (2007) provided age-specific
distributions of body weight based on NHANES II, III,
and IV data. The number of observations in these
surveys was 20,322, 33,311, and 9,965, respectively.
Portier et al. (2007) computed the means and standard
deviations of body weight as back transformations of the
weighted means and standard deviations of natural
log-transformed body weights. Body weight
distributions were computed by gender and various age
brackets (Portier et al., 2007). The estimated mean body
weights are shown in Tables 8-20, 8-21, and 8-22 using
NHANES II, III, and IV data, respectively. The sample
size (N) shown in the tables is the observed number of
individuals and not the expected population size (sum of
the sample weights) in each age category (Portier et al.,
2007). The authors noted that the age groups are defined
as starting at the birth month and include the next eleven
months (i.e., age group 2 includes children 24-35 months
at the time of the health assessment). Table 8-23
provides estimates for age groups that are often
considered in risk assessments (Portier et al., 2007). The
authors concluded that the data show changes in the
average body weight over time and that the changes are
not constant for all ages. The reader is referred to Portier
et al. (2007) for equations suggested by the authors to be
used when performing risk assessments where shifts and
changes in body weight distributions need factoring in.
The advantages of this study are that it
represents the U.S. general population, it provides
distribution data, and can be used for trend analysis. In
addition, the data are provided for both genders and for
single-year age groups. The study results are also based
on a large sample size.
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8.4.9 Kahn and Stralka, 2008 - Estimated daily
average per capita water ingestion by
child and adult age categories based on
USDA's 1994-96 and 1998 Continuing
Survey of Food Intakes
As part of an analysis of water ingestion,
Kahn and Stralka (2008) provided body weight
distributions for children. The analysis was based on
self reported body weights from the 1994 -1996,1998
Continuing Survey of Food Intake Among Individuals
(CSFII). The average body weight across all
individuals was 65 kilograms. According to Kahn and
Stralka (2008), 10 kilograms, which is often used as
the default body weight for babies, is the 95th value of
the distribution of body weight for children in the 3 to
<6 months category. The median weight is 9
kilograms for the 6 to 12 month age category and 11
kilograms for the 1 to 2 year old category (Kahn and
Stralka, 2008). The body weight distributions are
presented in Table 8-24 and the intervals around the
mean and 90th and 95th percentiles are presented in
Table 8-25.
The advantages of the study are its large
sample size and that it is representative of the U.S.
population for the age groups presented. A limitation
of the study is that the data are based on self reporting
from the participants.
8.5 RELEVANT FETAL WEIGHT STUDIES
8.5.1 Brenner et al., 1976 - A Standard of Fetal
Growth for the United States of America
Brenner et al. (1976) determined fetal
weights for 430 fetuses aborted at 8 to 20 weeks of
gestation and for 30,772 liveborn infants delivered at
21 to 44 weeks of gestation. Gestational age for the
aborted fetuses was determined through a combination
of the physician's estimate of uterine size and the
patient's stated last normal menstrual period. Data
were not used when these two estimates differed by
more than 2 weeks. To determine fetal growth, the
fetuses were weighed and measured (crown-to-rump
and crown-to heel lengths). All abortions were legally
performed at Memorial Hospital, University of North
Carolina at Chapel Hill from 1972 to 1975. For the
liveborn infants, data were analyzed from single birth
deliveries with the infant living at the onset of labor,
among pregnancies not complicated by pre-eclampsia,
diabetes or other disorders. Infants were weighed on a
balance scale immediately after delivery. The liveborn
infants were delivered at MacDonald House, University
Hospitals of Cleveland, Ohio from 1962 to 1969.
Percentiles for fetal weight were calculated
from the data at each week of gestation and are shown in
Table 8-26. The resulting percentile curves were
smoothed with two-point weighted means. Variables
associated with significant differences in fetal weight in
the latter part of pregnancy (after 34-38 weeks of
gestation) included maternal parity and race, and fetal
gender.
The advantage of this study is the large sample
size. Limitations of the study are that the data were
collected more than 30 years ago in only two U.S. states.
In addition, a number of variables which may affect fetal
weight (i.e., maternal smoking, disease, nutrition, and
addictions) were not evaluated in this study.
8.5.2 Doubilet et al., 1997 - Improved Birth
Weight Table for Neonates Developed from
Gestations Dated by Early Ultrasonography
Doubilet et al. (1997) matched a database of
obstetrical ultrasonograms over a period of 5 years from
1988 to 1993 to birth records for 3,718 infants (1,857
males and 1,861 females). The study population
included 1,514 Whites, 770 Blacks, 1,256 Hispanics, and
178 who were either unclassified, or classified as
"other." Birth weights were obtained from hospital
records and a gestational age was assigned based on the
earliest first trimester sonogram. The database was
screened for possible outliers, defined as infants with
birth weights that exceeded 5000 grams. Labor and
delivery records and mother-infant medical records were
retrieved to correct any errors in data entry for infants
with birth weights exceeding 5000 grams. The mean
gestational age at initial sonogram was 9.5 ± 2.3 weeks.
Regression analysis techniques were used to derive
weight tables for neonates at each gestational age for 25
weeks of gestation onward. Weights for each gestational
age were found to conform to a natural logarithm
distribution. Polynomial equations were derived from the
regression analysis to estimate mean weight by
gestational age for males, females, and males and
females combined. Table 8-27 provides the distribution
of neonatal weights by gestational age from 25 weeks of
gestation onward.
Page
8-8
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
8.6
REFERENCES FOR CHAPTER 8
Brenner, W.E.; Edelman, D.A.; Hendricks, C.H.
(1976) A standard of fetal growth for the
United States of America. Am J Obstet
Gynecol l:126(5):555-64.
Burmaster, D.E.; Crouch, E.A.C. (1997) Lognormal
distributions for body weight as a function of
age for males and females in the United
States, 1976-1980. Risk Anal 17(4):499-
505.
Doubilet, P.M.; Benson, C.B.; Nadel, A.S.; Ringer,
S.A. (1997) Improved birth weight table for
neonates developed from gestations dated by
early ultrasonography. J Ultrasound Med
16:241-249.
Freedman, D.; Kettel, K.; Serdula, M; Ogden, C.;
Dietz, W. (2006) Racial and ethnic
differences in secular trends for childhood
BMI, weight, and height. Obesity
14(2):301:307.
Kahn, H.; Stralka, K. (2008) Estimated daily average
per capita water ingestion by child and adult
age categories based on USDA's 1994-96
and 1998 continuing survey of food intakes
(CSFII). J Expo Sci Environ Epidemiol
(2008) 1-9.
Kuczmarski, R.J.; Ogden, C.L.; Guo, S.S.; Grummer-
Strawn, L.; Flegal, K., et al. (2000) CDC
growth charts for the United States: methods
and development. National Center for Health
Statistics. Vital Health Stat. 11(246)2002.
LSRO (1995) Third report on nutrition monitoring in
the United States: Volume 1. Prepared by:
Federation of American Societies for
Experimental Biology, Life Sciences
Research Office for the Interagency Board
for Nutrition Monitoring and Related
Research. Washington, D.C.: U.S.
Government Printing Office.
Martin, J.;Hamilton,B.; Sutton,P.; Ventura, S.; Fay,
M.; et al. (2007) Births: final data for 2005.
CDC National Vital Statistics Report,
Volume 56. No. 6.
National Center for Health Statistics (NCHS). (1987)
Anthropometric reference data and
prevalence of overweight, United States,
1976-80. Data from the National Health and
Nutrition Examination Survey, Series 11,
No. 238. Hyattsville,MD: U. S. Department of
Health and Human Services, Public Health
Service, National Center for Health Statistics.
DHHS Publication No. (PHS) 87-1688.
Ogden, C.L.; Fryar, C.D.; Carroll, M.D.; Flegal, K. M.
(2004) Mean Body Weight, Height, and Body
Mass Index, United States 1960-2002. Advance
Data from Vital and Health Statistics, No. 347,
October 27, 2004. U.S. Department of Health
and Human Services, Centers for Disease
Control and Prevention, National Center for
Health Statistics.
Portier K.; Tolson, J.; Roberts, S. (2007) Body weight
distributions for risk assessment. Risk Anal
27(1)11-26.
U.S. EPA (1989) Risk assessment guidance for
Superfund, Volume I: Human health evaluation
manual. Washington,DC: U.S.Environmental
Protection Agency, Office of Emergency and
Remedial Response. EPA/540/1-89/002.
U.S. EPA (2000) Memorandum entitled: Body weight
estimates on NHANES III data, revised,
Contract 68-C-99-242, Work Assignment 0-1
from Bob Clickner, Westat Inc. to Helen
Jacobs, U.S. EPA dated March 3, 2000.
U.S. EPA (2005) Guidance on selecting age groups for
monitoring and assessing childhood exposures
to environmental contaminants (2005).
Washington, D.C.: U.S. Environmental
Protection Agency, EPA/630/P-03/003F.
Child-Specific Exposure Factors Handbook
September 2008
Page
8-9
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-3
Age Group N
Birth to <1 month 158
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Source: U.S.
284
489
927
1176
1144
2318
3593
5297
4851
Mean and Percentile Body Weights (kilograms) Derived from NHANES 1999-2006,
Males and Females Combined
Mean
4.8
5.9
7.4
9.2
11.4
13.8
18.6
31.8
56.8
71.6
EPA Analysis of NHANES
Percentiles
5th
3.6
4.5
5.7
7.1
8.9
10.9
13.5
19.7
34.0
48.2
10th
3.9
4.7
6.1
7.5
9.3
11.5
14.4
21.3
37.2
52.0
15th
4.1
4.9
6.3
7.9
9.7
11.9
14.9
22.3
40.6
54.5
25th
4.2
5.2
6.7
8.3
10.3
12.4
15.8
24.4
45.0
58.4
50th
4.8
5.9
7.3
9.1
11.3
13.6
17.8
29.3
54.2
67.6
75th
5.1
6.6
8.0
10.1
12.4
14.9
20.3
36.8
65.0
80.6
85th
5.5
6.9
8.4
10.5
13.0
15.8
22.0
42.1
73.0
90.8
90th
5.8
7.1
8.7
10.8
13.4
16.3
23.6
45.6
79.3
97.7
95th
6.2
7.3
9.1
11.3
14.0
17.1
26.2
52.5
88.8
108.0
1999-2006 data.
Page
8-10
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-4. Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES 1999-2006
Age Group JN
Birth to <1 month 88
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Source: U.S.
153
255
472
632
558
1158
1795
2593
2462
Mean
4.9
6.0
7.6
9.4
11.6
14.1
18.8
31.9
57.6
77.3
EPA Analysis of NHANES
Percentiles
5th
3.6
4.6
5.9
7.3
9.0
11.4
13.5
20.0
33.6
54.5
10th
3.6
5.0
6.4
7.9
9.7
12.0
14.4
21.8
36.3
57.6
15th
4.0
5.1
6.6
8.2
10.0
12.2
14.9
22.9
38.9
60.0
25th
4.4
5.4
6.9
8.5
10.5
12.8
15.9
24.8
44.2
63.9
50th
4.8
6.1
7.5
9.4
11.5
14.0
18.1
29.6
55.5
73.1
75th
5.5
6.8
8.2
10.3
12.6
15.2
20.8
36.4
66.5
86.0
85th
5.8
7.0
8.6
10.6
13.2
15.9
22.6
41.2
75.5
96.8
90th
6.2
7.2
8.8
10.8
13.5
16.4
23.8
45.2
81.2
104.0
95th
6.8
7.3
9.1
11.5
14.3
17.0
26.2
51.4
91.8
113.0
1999-2006 data.
Table 8-5. Mean and Percentile Body Weights (kilograms) for Females
Age Group N
Birth to <1 month 70
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Source: U.S.
131
234
455
544
586
1160
1798
2704
2389
Mean
4.6
5.7
7.2
9.0
11.1
13.5
18.3
31.7
55.9
65.9
EPA Analysis of NHANES
5th
3.6
4.3
5.5
7.1
8.7
10.5
13.5
19.3
34.9
46.2
1999-2006 data
10th
4.0
4.6
5.9
7.3
9.1
11.0
14.3
20.9
38.6
48.6
15th
4.1
4.74
6.2
7.6
9.4
11.5
14.7
22.0
41.6
51.1
25th
4.2
5.1
6.4
8.0
10.0
12.1
15.6
23.9
45.7
54.5
Derived from NHANES 1999-2006
Percentiles
50th
4.6
5.5
7.2
8.9
11.1
13.2
17.5
29.0
53.3
61.5
75th
4.9
6.4
7.9
9.8
12.2
14.6
19.7
37.3
62.8
73.3
85th
5.0
6.6
8.2
10.3
12.9
15.5
21.3
43.1
70.7
83.4
90th
5.2
6.9
8.4
10.6
13.2
16.2
23.2
46.7
76.5
89.9
95th
5.9
7.3
9.0
11.2
13.7
17.1
26.2
53.4
86.3
99.7
Child-Specific Exposure Factors Handbook
September 2008
Page
8-11
-------
I
If
I
Table 8-6. Weight in Kilograms for Males 2 Months-19 Years of Age- Number Examined, Mean, and Selected Percentiles,
by Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Number of
Persons
Examined
-
-
103
287
589
613
627
1556
1373
1037
890
Mean ~
(kg)
-
-
6.6
7.7
9.4
11.7
13.7
18.0
30.7
55.2
71.8
5th
-
-
5.3
6.3
7.5
9.4
11.4
13.7
19.5
34.0
54.1
10th 15th
-
-
5.5 5.7
6.6 6.7
7.9 8.1
9.8 10.1
11.8 12.2
14.6 14.9
21.1 22.1
36.5 38.7
56.6 58.3
25th
-
-
5.9
7.0
8.6
10.8
12.6
15.7
24.0
42.8
61.8
Percentiles
50th
-
-
6.8
7.7
9.4
11.7
13.6
17.5
28.5
53.0
68.7
75th
-
-
7.2
8.4
10.2
12.6
14.6
19.7
35.2
63.0
77.9
85th
-
-
7.6
8.9
10.6
13.1
15.2
21.0
40.5
69.4
84.3
90th
-
-
7.8
9.2
10.9
13.7
15.8
22.0
43.5
74.8
89.7
95th
-
-
8.4
9.6
11.4
14.5
16.5
24.0
48.7
84.3
101.0
" Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
No data available for infants less than two months old.
Source: National Center for Health Statistics, 1987.
oo
!
-------
00
1
s
1=
I
Table 8-7. Weight in Kilograms for Females 6 Months-19 Years of Age- Number Examined, Mean, and Selected Percentiles,
by Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Number of
Persons
Examined
-
-
131
269
574
617
597
1658
1321
1144
1001
Mean
(kg)
-
-
6.0
7.1
8.8
11.0
13.4
18.0
30.6
53.2
62.2
5th
-
-
4.7
5.8
7.2
9.1
10.8
13.3
19.0
34.1
46.7
" Includes clothing weight, estimated as ranging from 0
No data available for infants less than two months old
10th
-
-
5.1
5.9
7.5
9.4
11.2
14.0
20.5
37.2
48.2
09 to 0.28 kilogram
15th
-
-
5.2
6.1
7.7
9.6
11.6
14.5
21.3
40.4
49.7
25th
-
-
5.6
6.4
8.0
9.9
12.1
15.4
23.4
45.2
52.2
Percentiles
50th
-
-
6.0
7.1
8.7
10.9
13.2
17.2
28.9
51.6
58.9
75th
-
-
6.5
7.7
9.4
11.9
14.6
19.7
35.0
60.0
68.3
85th
-
-
7.1
7.9
10.1
12.6
15.4
21.1
39.6
67.2
74.7
90th
-
-
7.3
8.4
10.4
12.9
15.6
22.6
44.3
70.6
80.8
95th
-
-
7.8
8.7
10.8
13.4
16.3
25.1
50.2
78.2
92.6
Source: National Center for Health Statistics, 1987.
Ore
Q
I
oo
ri
1=
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-8. Statistics for Probability Plot Regression Analyses:
Females Body Weights 6 Months to 20 Years of Age
Age Midpoint (years)
Lognormal Probability Plots
Linear Curve
Hi'
0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
a U2, a2 - correspond to the mean
Source: Burmaster and Crouch, 1997.
2.16
2.38
2.56
2.69
2.83
2.98
3.10
3.19
3.31
3.46
3.57
3.71
3.82
3.92
3.99
4.00
4.05
4.08
4.07
4.10
0.145
0.129
0.112
0.136
0.134
0.164
0.174
0.174
0.156
0.214
0.199
0.226
0.213
0.215
0.187
0.156
0.167
0.165
0.147
0.149
and standard deviation, respectively, of the lognormal distribution of body weight (kg).
Page
8-14
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-9. Statistics for Probability Plot Regression Analyses:
Males Body Weights 6 Months to 20 Years of Age
Age Midpoint (years)
0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
* u2, a2 - correspond to the mean and
Source: Burmaster and Crouch, 1997.
Lognormal Probability Plots
Linear Curve
Hz"
2.23
2.46
2.60
2.75
2.87
2.98
3.13
3.21
3.33
3.43
3.59
3.69
3.78
3.88
4.02
4.09
4.20
4.19
4.25
4.26
standard deviation, respectively, of the lognormal
CT2°
0.132
0.119
0.120
0.114
0.133
0.138
0.145
0.151
0.181
0.165
0.195
0.252
0.224
0.215
0.181
0.159
0.168
0.167
0.159
0.154
distribution of body weight (kg).
Child-Specific Exposure Factors Handbook Page
September 2008 8-15
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-10. Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From
NHANES III (1988-94)
Age Group
2 to 6 months
7 to 12 months
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
1 1 years
12 years
13 years
14 years
15 years
16 years
17 years
1 and older
1 to 3 years
1 to 14 years
1 5 to 44 years
Source: U.S.
Sample Size
1,020
1,072
1,258
1,513
1,309
1,284
1,234
750
736
711
770
751
754
431
428
415
378
427
410
31,311
4,080
12,344
10,393
EPA, 2000.
Population
1,732,702
1,925,573
3,935,114
4,459,167
4,317,234
4,008,079
4,298,097
3,942,457
4,064,397
3,863,515
4,385,199
3,991,345
4,270,211
3,497,661
3,567,181
4,054,117
3,269,777
3,652,041
3,719,690
251,097,002
12,711,515
56,653,796
118,430,653
Male and
Median
7.4
9.4
11.3
13.2
15.3
17.2
19.6
21.3
25.0
27.4
31.8
35.2
40.6
47.2
53.0
56.9
59.6
63.2
65.1
66.5
13.2
24.9
70.8
Female
Mean
7.4
9.4
11.4
12.9
15.1
17.1
19.4
21.7
25.5
28.1
32.7
35.6
41.5
46.9
55.1
61.1
62.8
65.8
67.5
64.5
13.1
29.9
73.5
Male
Median
7.6
9.7
11.7
13.5
15.5
17.2
19.7
21.5
25.4
27.2
32.0
35.9
38.8
48.1
52.6
61.3
62.6
66.6
70.0
73.9
13.4
25.1
77.5
Mean
7.7
9.7
11.7
13.1
15.2
17.0
19.3
22.1
25.5
28.4
32.3
36.0
40.0
49.1
54.5
64.5
66.9
69.4
72.4
89.0
13.4
30.0
80.2
Female
Median
7.0
9.1
10.9
13.0
15.1
17.3
19.6
20.9
24.1
27.9
31.1
34.3
43.4
45.7
53.7
53.7
57.1
56.3
60.7
80.8
13.0
24.7
63.2
Mean
7.0
9.1
11.0
12.5
14.9
17.2
19.4
21.3
25.6
27.9
33.0
35.2
42.8
48.6
55.9
57.9
59.2
61.6
62.2
80.3
12.9
29.7
67.3
Page
8-16
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-11. Body Weight Estimates (in kilograms) by Age, U.S. Population Derived From
NHANES III (1988-94)
Age Group Sample Size Population
2 Months 243 408,837
3 Months 190 332,823
3 Months and Younger 433 741,660
CI = Confidence Interval.
Source: U.S. EPA, 2000.
Male and Female
Median Mean
6.3 6.3
7.0 6.9
6.6 6.6
95% CI
6.1-6.4
6.7-7.1
6.4-6.7
Child-Specific Exposure Factors Handbook Page
September 2008 8-17
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-12. Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender and Age: Birth to 36 Months
Age Group
Perc entile
01^
10th
25th
50th
75th
90th
95th
Rovs
Birth
0 < 1 months
1< 2 months
2 < 3 months
3 < 4 months
4 < 5 months
5 < 6 months
6 < 7 months
7 < 8 months
8 < 9 months
9 < 10 months
10 < 11 months
11 < 12 months
12 < 15 months
15 < 18 months
18<21 months
21 < 24 months
24 < 30 months
30 < 36 months
Birth
0 < 1 months
1< 2 months
2 < 3 months
3 < 4 months
4 < 5 months
5 < 6 months
6 < 7 months
7 < 8 months
8 < 9 months
9 < 10 months
10 < 11 months
11 < 12 months
12 < 15 months
15 < 18 months
18<21 months
21 < 24 months
24 < 30 months
30 < 36 months
3.4
-
-
6.5
7.0
7.2
7.9
8.4
8.6
9.3
9.3
9.5
10.0
10.6
11.4
12.1
12.4
13.1
14.0
3.3
-
-
5.4
6.3
6.7
7.3
7.7
8.0
8.3
8.9
9.0
9.3
9.8
10.4
11.1
11.8
12.5
13.6
0.6
-
-
0.8
0.9
0.8
0.9
1.1
1.1
1.1
0.9
1.1
1.0
1.2
1.9
1.5
1.3
1.7
1.5
0.5
-
-
0.5
0.7
0.9
0.9
0.8
1.4
0.9
0.9
1.1
1.0
1.1
1.1
1.4
1.3
1.5
1.7
2.7
-
-
5.6
5.9
6.3
6.7
7.3
7.1
7.9
8.2
8.3
8.7
9.2
9.9
10.4
10.9
11.3
12.0
2.6
-
-
4.8
5.6
5.8
6.3
6.6
6.7
7.3
7.8
7.8
7.9
8.5
9.1
9.6
10.1
10.8
11.8
3.1
-
-
5.8
6.5
6.7
7.5
7.6
7.8
8.6
8.6
8.7
9.5
9.8
10.5
11.0
11.6
12.1
13.0
Girls
3.0
-
-
5.0
5.8
6.1
6.7
7.1
7.4
7.8
8.1
8.4
8.6
9.1
9.7
10.2
10.9
11.5
12.5
3.4
-
-
6.7
7.0
7.2
7.8
8.4
8.6
9.2
9.3
9.3
10.0
10.6
11.3
11.9
12.4
12.9
13.8
3.3
-
-
5.6
6.3
6.6
7.1
7.6
7.8
8.3
8.7
9.0
9.2
9.8
10.3
11.0
11.8
12.4
13.4
3.8
-
-
6.9
7.5
7.7
8.6
9.0
9.5
10.1
10.0
10.1
10.6
11.3
12.0
12.7
13.1
14.1
14.7
3.6
-
-
5.9
6.8
7.4
7.7
8.1
8.6
8.9
9.4
9.5
10.1
10.4
11.2
11.9
12.8
13.3
14.52
4.1
-
-
7.4
8.2
8.0
9.4
10.2
10.1
10.5
10.8
11.3
11.1
12.1
12.8
13.9
14.4
15.1
16.0
3.9
-
-
6.0
7.4
8.0
8.5
8.9
9.4
9.4
10.1
10.4
10.6
11.3
11.8
12.8
13.5
14.5
15.7
4.3
-
-
7.5
8.5
8.4
9.6
10.7
10.4
11.0
10.9
11.5
11.6
12.4
13.5
15.5
14.7
15.9
16.6
4.1
-
-
-
7.8
8.3
8.8
9.0
9.8
9.8
10.5
10.9
10.9
11.6
12.0
13.5
13.9
15.1
16.4
No data available.
Source: Kuczmarski et
al. 2002.
Page
8-18
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts: United States
kg
kg
Weight-for-age percentiles:
Boys, birth to 36 months •
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Age (months)
Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months
Source: Kuczmarski et al, 2002.
-4 —
Ib
Child-Specific Exposure Factors Handbook
September 2008
Page
8-19
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts: United States
kg
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Source: Kuczmarski et al, 2002.
Page
8-20
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts: United States
kg-
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Length
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Kuczmarskietal.,2002.
Child-Specific Exposure Factors Handbook
September 2008
Page
8-21
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts; United States
22-
21
Weight-for-length pereentiles:
Girls, birth to 36 months
cm 45 50 55 60 65 70 75 BO 85 90 95 100
Length
Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months
Source: Kuczmarski et al, 2002.
-50-
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Page
8-22
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts: United States
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Source: Kuczmarski et al, 2002.
Child-Specific Exposure Factors Handbook
September 2008
Page
8-23
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
CDC Growth Charts: United States
kg/m2
Body mass index-for-age percentiles:
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Source: Kuczmarski et al, 2002.
Page
8-24
Child-Specific Exposure Factors Handbook
September 2008
-------
Table 8-13. Mean Body Weight (kilograms) by A
Gender
and
Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
N
SE
Source:
NHES II, 1 963-65 NHES III, 1 966-70
N Mean SE N Mean SE
_
_
575 22.0 0.1 -
632 24.7 0.2 -
618 27.8 0.2 -
603 31.2 0.4 -
576 33.7 0.3 -
595 38.2 0.3 -
643 42.9 0.4
626 50.0 0.5
618 56.7 0.6
613 61.6 0.4
556 64.8 0.6
458 68.1 0.4
_
_
_
536 21.5 0.2 -
609 24.2 0.2 -
613 27.5 0.2 -
581 31.4 0.4 -
584 35.2 0.4 -
525 39.8 0.4 -
547 46.6 0.4
582 50.5 0.5
586 54.2 0.4
503 56.5 0.5
536 58.1 0.7
442 57.6 0.6
_
Data not available.
= Number of individuals.
= Standard error.
Ogdenetal, 2004.
NHANES I, 1971-74
N
298
308
304
273
179
164
152
169
184
178
200
174
174
171
169
176
124
136
272
292
281
314
176
169
152
171
197
166
177
198
184
167
171
150
141
130
Mean
13.6
15.6
17.7
20.2
22.0
24.9
26.4
31.6
34.2
38.8
44.0
49.9
56.3
60.3
66.9
68.6
74.3
72.6
13.0
15.0
16.8
19.7
21.6
24.3
27.5
32.0
33.8
41.2
46.7
51.8
54.6
56.6
56.8
59.5
58.2
59.5
SE
0.2
0.1
0.1
0.2
0.3
0.4
0.3
0.8
0.6
0.8
0.8
1.0
0.9
1.2
1.3
1.1
1.3
1.3
0.1
0.2
0.2
0.3
0.3
0.4
0.5
0.6
0.6
0.8
1.0
1.0
1.0
0.9
1.1
1.6
1.1
1.4
ge and Gender Across Multiple Surveys
NHANES II, 1976-80
N
370
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150
330
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158
Mean
13.4
15.5
17.6
19.7
22.8
24.9
28.0
30.7
36.2
39.7
44.1
49.5
56.4
61.2
66.5
66.7
71.1
71.8
12.8
14.8
16.8
19.4
21.9
24.6
27.5
31.7
35.7
41.4
46.1
50.9
54.3
55.0
57.7
59.6
59.0
59.8
SE
0.1
0.1
0.1
0.1
0.4
0.4
0.6
0.6
0.7
0.9
1.0
1.2
0.9
1.0
1.2
0.8
1.2
0.8
0.1
0.1
0.2
0.3
0.4
0.5
0.4
0.7
0.6
0.9
0.9
1.2
1.0
0.8
0.9
1.0
1.0
1.0
NHANES III, 1988-94
N
644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168
624
587
537
554
272
274
248
280
258
275
236
220
218
191
208
201
175
177
Mean
13.6
15.8
17.6
20.1
23.2
26.3
30.2
34.4
37.3
42.5
49.1
54.0
64.1
66.9
68.7
72.9
71.3
73.0
13.2
15.4
17.9
20.2
22.6
26.4
29.9
34.4
37.9
44.1
49.0
55.8
58.5
58.1
61.3
62.4
61.2
63.2
SE
0.1
0.2
0.2
0.2
0.6
0.4
0.8
1.0
0.9
0.9
1.1
1.0
3.6
1.9
1.6
1.3
1.7
2.2
0.1
0.1
0.3
0.2
0.6
0.8
0.6
1.2
.2
.1
.2
.6
.4
.1
.4
.2
.9
.9
NHANES 1999-2002
N
262
216
179
147
182
185
214
174
187
182
299
298
266
283
306
313
284
270
248
178
191
186
171
196
184
183
164
194
316
321
324
266
273
256
243
225
Mean
13.7
15.9
18.5
21.3
23.5
27.2
32.7
36.0
38.6
43.7
50.4
53.9
63.9
68.3
74.4
75.6
75.6
78.2
13.3
15.2
17.9
20.6
22.4
25.9
31.9
35.4
40.0
47.9
52.0
57.7
59.9
61.1
63.0
61.7
65.2
67.9
SE
0.1
0.2
0.2
0.5
0.4
0.4
1.0
0.7
0.8
.1
.3
.9
.6
.1
.4
.4
.1
.3
0.1
0.2
0.3
0.6
0.5
0.5
1.2
0.7
.0
.3
.1
.4
.0
^7
2
.2
.5
.2
I
oo
i
I
ri
I
1=
a
I-
oo
K>QTQ
<•»! ft
-------
I
If
oo
Table 8-14. Mean Height (centimeters) by Age and Gender Across Multiple Surveys
Gender
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
N
SE
Source:
NHES II, 1963-65 NHES III, 1966-70
N Mean SE N Mean SE
_
575 118.9 0.2 -
632 124.5 0.3 -
618 130.0 0.3 -
603 135.5 0.4 -
576 140.2 0.3 -
595 145.5 0.3 -
643 152.3 0.4
626 159.8 0.4
618 166.7 0.5
613 171.4 0.3
556 174.3 0.4
458 175.6 0.4
_
_
_
536 117.8 0. - - -
609 123.5 0. - - -
613 129.4 0. - - -
581 135.5 0. - - -
584 140.9 0. - - -
525 147.3 0.3 -
547 46.6 0.3
582 50.5 0.3
586 54.2 0.3
503 56.5 0.5
536 58.1 0.3
442 57.6 0.3
_
Data not available.
= Number of individuals.
= Standard error.
Ogden et al., 2004.
NHANESI, 1971-74
N
298
308
304
273
179
164
152
169
184
178
200
174
174
171
169
176
124
136
272
292
281
314
176
169
152
171
197
166
177
198
184
167
171
150
141
130
Mean
91.1
98.5
106.0
112.8
118.1
125.0
129.0
135.1
140.0
146.3
152.8
159.3
166.7
170.8
175.0
176.9
176.6
176.5
90.1
97.7
104.2
112.2
118.2
124.6
129.2
135.9
140.1
148.2
154.6
158.9
160.8
163.6
161.7
162.1
164.7
163.1
SE
0.4
0.3
0.3
0.3
0.6
0.5
0.5
0.6
0.5
0.7
0.7
0.8
0.6
0.9
0.8
0.5
0.7
0.9
0.3
0.3
0.4
0.4
0.5
0.7
0.6
0.5
0.8
0.8
0.6
0.5
0.6
0.6
0.5
0.9
0.5
0.5
NHANESII, 1976-80
N
350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150
314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158
Mean
91.1
98.7
105.5
112.3
119.1
124.5
129.6
135.0
141.3
145.5
152.5
158.3
166.8
171.2
173.4
174.8
177.3
176.1
89.4
97.1
104.2
111.2
117.9
123.4
129.5
134.1
141.7
147.4
143.8
158.7
160.7
163.3
162.8
163.5
162.8
163.2
SE
0.2
0.3
0.4
0.3
0.5
0.5
0.7
0.6
0.6
0.6
0.7
0.8
0.6
0.7
0.5
0.5
0.6
0.5
0.3
0.2
0.4
0.4
0.6
0.7
0.5
0.5
0.6
0.7
0.6
0.5
0.7
0.5
0.5
0.6
0.5
0.4
NHANES III, 1988-94
N
589
513
551
497
283
270
269
280
297
285
207
190
191
188
197
196
176
169
564
590
535
557
274
275
247
282
262
275
239
225
224
195
214
201
175
178
Mean
90.9
98.8
105.2
112.3
118.9
125.9
131.3
137.7
142.0
147.4
155.5
161.6
169.0
172.8
175.0
176.5
177.3
175.5
89.7
98.2
105.1
112.2
117.9
124.3
131.1
136.6
142.7
150.2
155.5
159.9
161.2
162.8
163.0
163.6
163.2
163.4
SE
0.2
0.3
0.4
0.3
0.7
0.6
0.6
0.7
1.1
0.7
1.1
0.8
0.9
1.0
0.9
0.9
1.0
0.6
0.2
0.2
0.3
0.5
0.6
0.7
0.6
0.7
0.6
0.7
0.7
0.9
0.7
0.6
0.7
0.6
0.9
0.7
NHANES 1999-2002
N
254
222
183
156
188
187
217
177
188
187
301
298
267
287
310
317
289
275
233
187
195
190
172
200
184
189
164
194
318
324
326
271
275
258
249
231
Mean
91.2
98.6
106.5
113.0
119.2
126.2
1325.
138.1
141.4
148.7
154.8
160.1
168.5
173.8
175.3
175.3
176.4
176.7
90.1
97.6
105.9
112.4
117.1
124.4
130.9
136.9
143.3
151.4
156.0
159.1
161.8
162.0
161.9
163.2
163.0
163.1
SE
0.3
0.3
0.4
0.5
0.5
0.6
0.7
0.4
0.6
0.9
0.7
0.8
0.9
0.6
0.6
0.6
0.7
0.6
0.4
0.5
0.5
0.7
0.7
0.5
0.6
0.7
0.9
0.7
0.7
0.6
0.6
0.6
0.5
0.6
0.5
0.7
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Table 8-15. Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys
Gender
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
N
SE
Source:
NHES II, 1963-65 NHES III, 1966-70 NHANES I, 1971-74
N Mean SE N
_
_
575 15.6 0.
632 15.9 0.
618 16.3 0.
603 16.9 0.2
576 17.1 0.
595 17.9 0.
643
626
618
613
556
458
_
_
_
_
536 115.4 0.1
609 15.8 0.1
613 16.4 0.1
581 17.0 0.1
584 17.6 0.2
525 18.2 0.2
547
582
586
503
536
442
_
-
Data not available.
= Number of individuals.
= Standard error.
Ogden et al., 2004.
Mean SE N
298
308
304
273
179
164
152
169
184
178
18.4 0.1 200
19.4 0.1 174
20.2 0.2 174
20.9 0.1 171
21.3 0.1 169
22.1 0.1 176
124
136
272
292
281
314
176
169
152
171
197
166
19.2 0.1 177
19.9 0.1 198
20.8 0.1 184
21.4 0.2 167
21.9 0.2 171
21.7 0.2 150
141
130
Mean
16.3
16.0
15.7
15.6
15.7
15.8
15.8
17.1
17.3
18.0
18.7
19.6
20.2
20.5
21.8
21.9
23.7
23.3
15.9
15.7
15.5
15.5
15.4
15.6
16.4
17.2
17.1
18.6
19.5
20.4
21.1
21.1
21.7
22.6
21.5
22.5
SE
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.2
0.3
0.2
0.3
0.3
0.3
0.3
0.3
0.3
0.5
0.
0.
0.
0.
0.
0.2
0.2
0.2
0.2
0.3
0.4
0.3
0.3
0.3
0.3
0.5
0.3
0.6
NHANES II, 1976-80
N
350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150
314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158
Mean
16.2
15.9
15.8
15.6
16.0
16.0
16.5
16.8
18.0
18.6
18.8
19.5
20.2
20.8
22.0
21.8
22.6
23.1
16.1
15.6
15.5
15.6
15.6
16.1
16.3
17.5
17.7
18.9
19.3
20.1
21.0
20.6
21.8
22.3
22.3
22.4
SE
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.3
0.3
0.3
0.4
0.2
0.3
0.3
0.2
0.4
0.3
0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.3
0.3
0.3
0.4
0.3
0.3
0.3
0.4
0.4
0.3
NHANES III, 1988-94
N
588
512
547
495
282
269
266
279
297
280
203
187
188
187
194
196
176
168
562
582
533
554
272
274
247
280
258
275
236
220
218
191
208
201
175
177
Mean
16.5
16.1
15.9
15.9
16.3
16.5
17.3
18.0
18.4
19.4
20.1
20.5
22.3
22.3
22.3
23.4
22.6
23.7
16.5
15.9
16.0
15.9
16.1
16.9
17.3
18.2
18.4
19.4
20.2
21.8
22.4
21.9
23.0
23.3
22.9
23.7
SE
0.1
0.2
0.1
0.1
0.3
0.2
0.4
0.7
0.3
0.3
0.3
0.3
1.1
0.5
0.5
0.4
0.5
0.6
0.1
0.1
0.2
0.1
0.3
0.3
0.3
0.5
0.4
0.4
0.5
0.6
0.5
0.4
0.5
0.5
0.6
0.8
NHANES 1999-2002
N
225
209
178
147
182
185
214
174
187
182
299
298
266
283
306
313
284
269
214
173
190
186
170
196
184
183
163
194
315
321
324
266
273
255
243
225
Mean
16.6
16.2
16.3
16.5
16.4
17.0
18.4
18.7
19.1
19.6
20.7
20.7
22.3
22.5
24.1
24.5
24.2
24.9
16.4
16.0
15.9
16.1
16.2
16.6
18.3
18.7
19.3
20.7
21.2
22.6
22.9
23.2
24.0
23.1
24.4
25.5
SE
0.1
0.1
0.2
0.3
0.2
0.2
0.4
0.3
0.3
0.4
0.4
0.5
0.4
0.3
0.4
0.4
0.3
0.4
0.1
0.1
0.2
0.3
0.2
0.2
0.5
0.3
0.3
0.4
0.4
0.4
0.4
0.5
0.4
0.4
0.5
0.4
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Table 8-16. Sample
Age Group Sex Race"
Overall
2 to 5 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
6 to 11 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
12 to 17 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
1 Race was receded in the first two examinations (using
surveys.
b Mean ages are shown in parentheses.
Source: Freeman et al., 2006.
Sizes by Age, Sex,
1(1971-1974)
6431 (10.3)b
829 (3.9)
286 (3.9)
51 (3.8)
772 (4.0)
297 (4.0)
56(4.1)
711(9.1)
249 (9.0)
51 (9.0)
722(9.1)
268 (9.0)
45 (8.9)
764(14.9)
252(14.9)
42(15.0)
749(15.0)
251(14.8)
36(14.9)
Race, and Examination
NHANES
11(1976-1980)
6395(10.6)
1082(4.1)
273(4.1)
105 (4.2)
1028 (4.0)
234 (4.0)
102 (4.2)
667 (9.0)
137(9.0)
60 (9.2)
631(9.1)
155(9.0)
40 (9.3)
786(15.1)
155(15.1)
49(15.0)
695(15.1)
159(15.0)
37(15.2)
data concerning ancestry/national origin)
Examination
III (1988-1994)
9610 (9.9)
605 (4.0)
693 (3.9)
732 (4.0)
639 (4.0)
684 (3.9)
800 (3.9)
446 (8.9)
584 (9.0)
565 (9.0)
428(9.1)
538(9.0)
581 (8.9)
282(14.9)
412(15.0)
406(15.0)
344(15.0)
450(14.9)
421 (14.8)
to create comparable cate^
1999-2002
6710(10.1)
226 (3.9)
234 (4.0)
231 (3.9)
235(4.1)
222 (4.0)
238(4.1
298 (8.9)
371 (9.0)
384 (9.0)
293 (8.9)
363(9.1)
361 (9.0)
449(14.9)
543 (14.9)
648(15.0)
456(14.9)
528(14.8)
631 (14.9)
Dories in all
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Table 8-17. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity
Examination Year"
Overall
Sex
Boys
Girls
Age (years)
2 to 5
6 to 11
12 to 17
Race
White
Black
Mexican- American
White
Black
Mexican- American
White
Black
Mexican- American
White
Black
Mexican- American
White
Black
Mexican- American
White
Black
Mexican- American
1971-1974 1976-1980 1988-1994 1999-2002
18.0b
17.8
18.6
17.9
17.7
18.6
18.0
17.9
18.5
15.8
15.8
16.5
16.7
16.5
16.9
20.7
20.4
21.6
18.0
18.2
18.8
18.0
17.8
18.9
18.0
18.6
18.6
15.7
15.7
16.2
16.9
17.1
17.7
20.6
20.9
21.5
18.8
19.1
19.5
18.8
18.8
19.4
18.7
19.5
19.6
16.0
15.9
16.5
17.6
17.9
18.5
21.8
22.4
22.6
19.0
20.0
20.1
19.0
19.6
20.3
19.0
20.4
19.9
16.2
16.2
16.5
17.9
18.7
18.8
22.0
23.7
24.0
and Sex
Increase in Mean z-score
From 1971-1974to 1999-2002
BMI
+0.33
+0.61
+0.32
+0.37
+0.53
+0.38
+0.30
+0.71
+0.25
+0.21
+0.34
-0.02
+0.42
+0.67
+0.50
+0.32
+0.72
+0.37
Weight
+0.36
+0.63
+0.52
+0.42
+0.58
+0.67
+0.32
+0.69
+0.35
+0.22
+0.32
+0.29
+0.47
+0.69
+0.65
+0.35
+9,77
+0.55
a Secular trends for BMI, BMI-for-age, weight-for-age, and height-for-age were each statistically significant at the 0.00 1
BMI, BMI-for-age, and weight also differed (p <0.001) by race.
b Mean BMI levels have been adjusted for differences in age and sex across exams.
Height
+0.20
+0.31
+0.39
+0.25
+0.32
+0.57
+0.16
+0.30
+0.21
+0.13
+0.18
+0.43
+0.30
+0.36
+0.41
+0.15
+0.33
+0.34
level. Trends in
Source: Freedman et al., 2006.
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Table 8-18. Prevalence of Overweight and Obesity* Among Children
Examination year
Race
Overall White
Black
Mexican- American
Sex
Boys White
Black
Mexican- American
Girls White
Black
Mexican- American
Age (years)
2 to 5 White
Black
Mexican- American
6 to 11 White
Black
Mexican- American
12 to 17 White
Black
Mexican- American
1971-1974
5% (l)b
6% (1)
8% (1)
5% (1)
6% (2)
8% (1)
5% (1)
6% (1)
8% (2)
4% (1)
7% (3)
10% (5)
4% (0)
4% (0)
6% (0)
6% (1)
8% (1)
9% (0)
1976-1980
5% (1)
7% (2)
10% (1)
5% (1)
5% (1)
12% (1)
5% (1)
9% (2)
7% (0)
3% (1)
4% (0)
11% (3)
6% (1)
9% (3)
11% (0)
4% (0)
8% (1)
8% (1)
Increase in Prevalence From 1971-
1974to 1999-2002
1988-1994 1999-2002 Overweight
9% (2)
12% (3)
14% (4)
10% (2)
11% (3)
15% (4)
9% (2)
14% (3)
14% (3)
5% (1)
8% (3)
12% (5)
11% (3)
15% (3)
17% (4)
11% (2)
13% (3)
14% (2)
* Overweight is defined as a BMI > 95th percentile or > 30 kg/m2; obesity is defined as a BMI
b Values are percentage of overweight children (percentage of obese children).
Source: Freedman et al., 2006.
12% (3)
18% (5)
21% (5)
13% (4)
16% (5)
24% (4)
12% (2)
21% (6)
17% (4)
9% (3)
9% (4)
13% (5)
13% (4)
20% (5)
22% (5)
13% (2)
22% (6)
25% (5)
> 99th percentile or
+8
+12
+12
+8
+10
+16
+7
+14
+9
+5
+2
+3
+10
+15
+16
+7
+14
+15
> 40 kg/m2.
Obesity
+2
+4
+4
+3
+3
+6
+1
+5
+2
+2
+1
0
+3
+4
+5
+1
+5
+5
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-19. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth Weights,
by Race and Hispanic Origin of Mother: United States, 2005
Total Births
Weight (grams)
<500
500-999
1,000-1,499
1,500-1,999
2,000-2,499
2,500-2,999
3,000-3,499
3,500-3,999
4,000-4499
4,500-4999
>5,000
Not stated
All Races'
4,138,349
Non-Hispanic
Whiteb
2,279,768
Non-Hispanic
Blackb
583,759
Hispanic0
985,505
Number of Live Births
6,599
23,864
31,325
66,453
210,324
748,042
1,596,944
1,114,887
289,098
42,119
4,715
3,979
2,497
10,015
14,967
33,687
104,935
364,726
857,136
672,270
167,269
27,541
2,840
1,885
2,477
8,014
8,573
15,764
46,846
144,803
221,819
108,698
22,149
3,203
405
1,008
1,212
4,586
5,988
12,710
43,300
176,438
399,295
266,338
64,704
9,167
1,174
593
Percent of Total
Low Birth Weight11
Very Low Birth Weight'
8.2
1.5
7.3
1.2
14.0
3.3
6.9
1.2
* All Races includes White, Black, and races other than White and Black and origin not stated.
b Race categories are consistent with the 1977 Office of Management and Budget standards.
0 Hispanic includes all persons of Hispanic origin of any race.
d Low birth weight is birth weight less than 2,500 grams (5 Ib 8 oz).
' Very low birth weight is birth weight less than l,500grams (3 Ib 4 oz).
Source: Martin et al., 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
8-31
-------
Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-20. Estimated
Mean Body Weights of Males and Females by Single- Year Age Groups Using NHANES II Data
Males (kg)
Mean
0 to 1 year 9.4
1 to 2 years 11.8
2 to 3 years 13.6
3 to 4 years 15.6
4 to 5 years 17.8
5 to 6 years 19.8
6 to 7 years 23.0
7 to 8 years 25.1
8 to 9 years 28.2
9 to 10 years 31.1
10 to 11 years 36.4
11 to 12 years 40.2
12 to 13 years 44.2
13 to 14 years 49.8
14 to 15 years 57.1
15 to 16 years 61.0
16 to 17 years 67.1
17 to 18 years 66.7
18 to 19 years 71.0
19 to 20 years 71.7
20 to 21 years 71.6
SD
1.3
1.6
1.8
1.9
2.4
2.8
3.7
3.8
5.6
5.8
7.2
9.8
9.8
11.4
10.7
10.4
11.7
11.3
12.0
11.3
12.0
a Data were converted from ag
SD = Standard Deviation.
N
179
370
375
418
404
397
133
148
147
145
157
155
145
173
186
184
178
173
164
148
114
Mean
8.8
10.8
13.0
14.9
17.0
19.6
22.1
24.7
27.8
31.8
36.1
41.8
46.4
50.9
54.7
55.1
58.1
59.6
59.0
60.1
60.5
;es in months to ages in years.
Females (kg)
SD
1.3
1.4
1.5
2.1
2.3
3.2
3.9
4.6
4.8
7.3
7.7
10.1
10.1
11.2
10.7
9.0
9.6
10.4
10.2
10.1
10.7
For instance, age
Overall (kg)
N
177
336
336
366
396
364
135
157
123
149
136
140
147
162
178
145
170
134
170
158
162
Mean
9.1
11.3
13.3
15.2
17.4
19.7
22.5
24.8
28.1
31.4
36.2
41.0
45.4
50.4
55.9
58.0
62.4
63.3
64.6
65.3
65.2
1-2 years represents ages from
SD
1.2
1.5
1.6
1.8
2.4
2.8
3.6
3.8
5.6
5.9
7.1
9.9
10.0
11.5
10.5
9.9
10.9
10.7
10.9
10.3
10.9
12 to 23
N
356
706
711
784
800
761
268
305
270
294
293
295
292
335
364
329
348
307
334
306
276
months.
N = Number of individuals.
Source: Portier et al., 2007.
Page
8-32
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8
Age Group"
0 to 1 years
1 to 2 years
2 to 3 years
3 to 4 years
4 to 5 years
5 to 6 years
6 to 7 years
7 to 8 years
8 to 9 years
9 to 10 years
10 to 11 years
11 to 12 years
12 to 13 years
13 to 14 years
14 to 15 years
15 to 16 years
16 to 17 years
17 to 18 years
18 to 19 years
19 to 20 years
20 to 21 years
-21. Estimated
Mean
Males (k
Mean
8.5
11.6
13.6
15.8
17.6
20.1
23.2
26.3
30.1
34.4
37.3
42.5
49.1
54.0
63.7
66.8
68.6
72.7
71.2
73.0
72.5
SD
1.5
1.5
1.5
2.3
2.4
3.0
5.0
5.0
6.9
7.9
8.6
10.5
11.1
12.9
17.1
14.9
14.9
13.3
14.3
12.8
13.4
" Data were converted from a§
SD = Standard Deviation.
Body Weights of Males and Females by Sin
g)
N
902
660
644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168
149
es in months to a;
Mean
7.8
10.9
13.2
15.4
17.9
20.2
22.6
26.3
29.8
34.3
37.9
44.2
49.1
55.7
58.3
58.3
61.5
62.4
61.5
63.6
61.7
jes in years.
Females (kj
SD
1.6
1.4
1.8
2.2
3.2
3.5
4.7
6.2
6.7
9.0
9.5
10.5
11.6
13.2
11.8
10.1
12.8
11.9
14.2
14.5
12.9
For instance,
gle-Year Age Groups Using NHANES III Data
1) Overall (kg)
N
910
647
624
587
537
554
272
274
248
280
258
275
236
220
220
197
215
217
193
193
180
Mean
8.17
11.2
13.4
15.6
17.8
20.2
22.9
26.4
30.0
34.4
37.7
43.4
49.1
54.8
60.6
61.7
65.2
67.6
66.4
68.3
66.1
age 1-2 years represents ages from
SD
1.7
1.5
1.8
2.2
3.2
3.5
4.8
6.2
6.7
9.0
9.4
10.3
11.7
13.0
12.2
10.7
13.6
12.9
15.3
15.6
13.8
12 to 23
N
1,812
1,307
1,268
1,103
1,086
1,051
555
543
514
561
555
556
439
407
408
384
409
413
369
361
329
months.
N = Number of individuals.
Source: Portier et al., 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
8-33
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES IV Data
Age Group"
0 to 1 year
1 to 2 years
2 to 3 years
3 to 4 years
4 to 5 years
5 to 6 years
6 to 7 years
7to 8 years
8 to 9 years
9 to 10 years
10 to 11 years
11 to 12 years
12 to 13 years
13 to 14 years
14 to 15 years
15 to 16 years
16 to 17 years
17 to 18 years
18 to 19 years
19 to 20 years
20 to 21 years
a Data
Males (kg)
Mean
9.3
11.3
13.7
16.4
18.8
20.2
22.9
28.1
31.9
36.1
39.5
42.0
49.4
54.9
65.1
68.2
72.5
75.4
74.8
80.1
80.0
were converted
SD
1.8
1.4
2.0
2.3
2.6
3.3
4.3
5.6
8.6
7.5
9.0
10.2
12.7
16.2
19.9
15.7
18.6
17.9
15.9
17.2
15.5
N
116
144
130
105
95
65
94
100
100
76
92
84
158
161
137
142
153
146
131
129
37
from ages in months to ages
Mean
9.3
11.5
13.3
15.2
18.1
20.7
22.0
26.0
30.8
36.0
39.4
47.2
51.6
59.8
59.9
63.4
63.4
59.9
65.0
68.7
66.3
in years.
Females (kg)
SD
1.5
1.9
1.9
2.1
3.2
4.9
4.5
6.2
7.2
8.4
10.2
12.2
12.3
15.3
13.3
13.9
16.0
11.9
15.2
17.4
15.5
For instance, age
Overall (kg)
N
101
98
113
77
87
92
74
82
89
84
84
97
160
156
158
126
142
128
139
132
44
Mean
9.3
11.4
13.5
15.9
18.5
20.6
22.5
27.4
31.3
36.2
39.5
44.6
50.3
56.9
61.5
65.9
68.0
66.6
70.2
74.6
74.3
1-2 years represents ages from
SD
1.5
1.8
2.0
2.2
3.3
4.9
4.6
6.5
7.3
8.5
10.2
11.6
11.9
14.6
13.7
14.4
17.1
13.2
16.4
19.0
17.4
12 to 23
N
217
242
243
182
182
157
168
182
189
160
176
181
318
317
295
268
295
274
270
261
81
months.
SD = Standard Deviation.
N = Number of individuals.
Source: Portier et al, 2007.
Page
8-34
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-23. Estimated Body Weights of Typical Age Groups
Age Gro
lip NHANF.S
Males (kg)
Mean
II
1 to 6 years III
IV
II
7 to 16 years III
SD
N
Source:
IV
17.0
16.9
17.1
45.2
49.3
47.9
SD
4.6
4.7
4.9
17.6
20.9
20.1
N
2,097
3,149
633
1,618
2,549
1,203
of Interest in U.S. EPA Risk Assessments*
Females (kg)
Mean
16.3
16.5
17.5
43.9
46.8
47.9
SD
4.7 1
4.9 3
5.0
15.9 1
18.0 2
19.2 1
N
,933
,221
541
,507
,640
,178
Overall (kg)
Mean
16.7
16.8
17.3
44.8
47.8
47.7
SD
4.5
5.0
5.0
17.5
18.4
19.1
N
4,030
6,370
1,174
3,125
5,189
2,381
Estimates were weighted using the sample weights provided with each survey.
= Standard Deviation.
= Number of individuals.
Portier et al., 2007.
Table 8-24. Estimated Percentile Distribution of Body Weight by Fine Age Categories Derived From 1994-96,
1998 CSFII
Weight (kilograms)
A ^ Sample
Age Group ^
Birth to 1 month 88
1 to <3 months 245
3 to <6 months 411
6 to <12 months 678
1 to <2 years 1,002
2 to <3 years 994
3 to <6 years 4,112
6to
-------
I
I
I
Table 8-25. Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence Interval
Weight (Kilograms)
Age Group
Birth to 1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21 years
CI
BI
Sample
Size
88
245
411
678
1,002
994
4,112
1,553
975
360
383
Estimate
4
5
7
9
12
14
18
30
54
67
69
Mean
90%
Lower
Bound
3
5
7
9
12
14
18
29
53
66
68
CI
90th Percentile
90% BI
95th
Percentile
90% BI
Estimate Estimate
Upper Lower Upper Lower
Bound Bound Bound Bound
4
5
7
9
12
14
18
30
55
68
70
4"
6
9
11
14
18
23
41
72
86
89
4"
6
9
11
14
17
23
41
70
84
88
5"
7
9
11
15
18
23
43
75
95
95
5*
7"
10
12
15
19
25
45
82
100'
100"
5"
1
10
12
15
18
25
44
81
95"
95"
Sample size does meet minimum reporting requirements as described in the "Third Report on Nutrition Monitoring in the United States"(Vol.
Interval estimates may involve aggregation of variance estimation units when data are too sparse to support estimation of variance.
= Confidence interval.
= Percentile intervals estimated using percentile bootstrap method with 1,000 bootstrap replications.
Upper
Bound
5*
7
10
12
16
19
25
48
84
109"
104"
I).
Source: Kahn and Stralka, 2008.
s
I
oo
I
1
«?
I
s
I
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-26. Fetal Weight (grams) Percentiles Throughout Pregnancy
Gestational Age Number of
(weeks) Women
8
9
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
41
42
43
44
b
Source:
6
7
15
13
18
43
61
63
59
36
58
31
21
43
69
71
74
48
86
76
91
88
128
113
210
242
373
492
1,085
1,798
3,908
5,413
10,586
3,399
1,725
507
147
10th
-
-
-
-
-
-
-
-
-
-
-
280
320
370
420
490
570
660
770
890
1,030
1,180
1,310
1,480
1,670
1,870
2,190
2,310
2,510
2,680
2,750
2,800
2,830
2,840
2,790
Data not available.
Median fetal weights may be overestimated.
weeks' gestation.
Brenner et al., 1976.
25th
:
-
-
11
23
3,405
51
80
125
172
217
255
330
410
460
530
630
730
840
980
1,100
1,260
1,410
1,570
1,720
1,910
2,130
2,470
2,580
2,770
2,910
3,010
3,070
3,110
3,110
3,050
50th
6.1"
7.3b
8.1b
11.9b
21
35
51
77
117
166
220
283
325
410
480
550
640
740
860
990
1,150
1,310
1,460
1,630
1,810
2,010
2,220
2,430
2,650
2,870
3,030
3,170
3,280
3,360
3,410
3,420
3,390
75th
:
-
-
34
55
77
108
151
212
298
394
460
570
630
690
780
890
1,020
1,160
1,350
1,530
1,710
1,880
2,090
2,280
2,510
2,730
2,950
3,160
3,320
3,470
3,590
3,680
3,740
3,780
3,770
90th
:
-
-
-
-
-
-
-
-
-
-
-
860
920
990
1,080
1,180
1,320
1,470
1,660
1,890
2,100
2,290
2,500
2,690
2,880
3,090
3,290
3,470
3,610
3,750
3,870
3,980
4,060
4,100
4,110
They were derived from only a small proportion of the fetuses delivered at these
Child-Specific Exposure Factors Handbook
September 2008
Page
8-37
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Child-Specific Exposure Factors Handbook
Chapter 8 - Body Weight
Table 8-27. Neonatal Weight by Gestational Age for
Males and Females Combined
Gestational Age
(weeks)
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Source: Doubilet et al.,
5th
450
523
609
707
820
947
1,090
1,249
1,422
1,608
1,804
2,006
2,210
2,409
2,595
2,762
2,900
3,002
3,061
1997.
10th
490
568
660
765
884
1,020
1,171
1,338
1,519
1,714
1,919
2,129
2,340
2,544
2,735
2,904
3,042
3,142
3,195
25th
564
652
754
870
1,003
1,151
1,317
1,499
1,696
1,906
2,125
2,349
2,572
2,786
2,984
3,155
3,293
3,388
3,432
Weight (g)
50th
660
760
875
1,005
1,153
1,319
1,502
1,702
1,918
2,146
2,383
2,622
2,859
3,083
3,288
3,462
3,597
3,685
3,717
75th
772
885
1,015
1,162
1,327
1,511
1,713
1,933
2,169
2,416
2,671
2,927
3,177
3,412
3,622
3,798
3,930
4,008
4,026
90th
889
1,016
1,160
1,322
1,504
1,706
1,928
2,167
2,421
2,687
2,959
3,230
3,493
3,736
3,952
4,127
4,254
4,322
4,324
95th
968
1,103
1,257
1,430
1,623
1,836
2,070
2,321
2,587
2,865
3,148
3,428
3,698
3,947
4,164
4,340
4,462
4,523
4,515
Page
8-38
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
TABLE OF CONTENTS
9 INTAKE OF FRUITS AND VEGETABLES 9-1
9.1 INTRODUCTION 9-1
9.2 RECOMMENDATIONS 9-2
9.3 INTAKE STUDIES 9-6
9.3.1 Key Fruits and Vegetables Intake Study 9-6
9.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 9-6
9.3.2 Relevant Fruit and Vegetable Intake Studies 9-8
9.3.2.1 USDA, 1999 9-8
9.3.2.2 Smiciklas-Wright et al, 2003 9-8
9.3.2.3 Fox et al., 2004 9-9
9.3.2.4 Ponza et al., 2004 9-9
9.3.2.5 Menella et al., 2006 9-10
9.3.2.6 Fox et al., 2006 9-10
9.4 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES 9-10
9.5 REFERENCES FOR CHAPTER 9 9-11
APPENDIX 9A 9A-1
Child-Specific Exposure Factors Handbook Page
September 2008 9-i
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
LIST OF TABLES
Table 9-1. Recommended Values for Intake of Fruits and Vegetables, As Consumed 9-3
Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables 9-4
Table 9-3. Per Capita Intake of Fruits and Vegetables (g/kg-day as consumed) 9-12
Table 9-4. Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed) 9-13
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) 9-14
Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) 9-17
Table 9-7. Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day) 9-20
Table 9-8. Percentage of Individuals Consuming Vegetables, by Sex and Age (%) 9-21
Table 9-9. Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day) 9-22
Table 9-10. Percentage of Individuals Consuming, Fruits by Sex and Age (%) 9-23
Table 9-11. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days 9-24
Table 9-12. Characteristics of the FITS Sample Population 9-25
Table 9-13. Percentage of Infants and Toddlers Consuming Different Types of Vegetables 9-26
Table 9-14. Top Five Vegetables Consumed by Infants and Toddlers 9-27
Table 9-15. Percentage of Infants and Toddlers Consuming Different Types of Fruits 9-28
Table 9-16. Top Five Fruits Consumed by Infants and Toddlers 9-29
Table 9-17. Characteristics of WIC Participants and Non-participants (Percentages) 9-30
Table 9-18. Food Choices for Infants and Toddlers by WIC Participation Status 9-32
Table 9-19. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming
Different Types of Fruits and Vegetables on A Given Day 9-33
Table 9-20. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants
and Toddlers Per Age Group 9-34
Table 9-21. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 9-35
Table 9-22. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 9-36
Table 9-23. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible
Portions 9-37
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data .... 9A-2
Page
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
9 INTAKE OF FRUITS AND VEGETABLES
9.1 INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, fruits and vegetables may become
contaminated with toxic chemicals by several different
pathways. Ambient pollutants from the air may be
deposited on or absorbed by the plants, or dissolved in
rainfall or irrigation waters that contact the plants.
Pollutants may also be absorbed through plant roots
from contaminated soil and ground water. The addition
of pesticides, soil additives, and fertilizers may also
result in contamination of fruits and vegetables. To
assess exposure through this pathway, information on
fruit and vegetable ingestion rates is needed.
Children's exposure from contaminated fruits
and vegetables may differ from that of adults because of
differences in the types and amounts of food eaten.
Also, for many foods, the intake per unit body weight is
greater for children than for adults. Common fruits and
vegetables eaten by children include apple juice, fresh
apples, orange juice, fresh pears, fresh peaches, carrots,
fresh bananas, succulent garden peas, and succulent
garden beans (Goldman, 1995).
A variety of terms may be used to define intake
of fruits and vegetables (e.g., consumer-only intake, per
capita intake, total fruit intake, total vegetable intake,
as-consumed intake, dry weight intake). These terms
are defined below to assist the reader in interpreting and
using the intake rates that are appropriate for the
exposure scenario being assessed.
Consumer-only intake is defined as the quantity
of fruits and vegetables consumed by children during
the survey period. These data are generated by
averaging intake across only the children in the survey
who consumed these food items. Per capita intake rates
are generated by averaging consumer-only intakes over
the entire population of children (including those
children that reported no intake). In general, per capita
intake rates are appropriate for use in exposure
assessments for which average dose estimates for
children are of interest because they represent both
children who ate the foods during the survey period and
children who may eat the food items at some time, but
did not consume them during the survey period. Per
capita intake, therefore, represents an average across
the entire population of interest, but does so at the
expense of underestimating consumption for the subset
of the population that consumed the food in question.
Total fruit intake refers to the sum of all fruits
consumed in a day including canned, dried, frozen, and
fresh fruits. Likewise, total vegetable intake refers to
the sum of all vegetables consumed in a day including
canned, dried, frozen, and fresh vegetables.
Intake rates may be expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the as-
consumed weight. The food ingestion values provided
in this chapter are expressed as as-consumed intake
rates because this is the fashion in which data were
reported by survey respondents. This is of importance
because concentration data to be used in the dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease food weight. Similarly, cooking can
increase the mass of contaminant in food (due to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching). The combined
effects of changes in weight and changes in contaminant
mass can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. Ideally, after-
cooking food concentrations should be combined with
the as-consumed intake rates. In the absence of data, it
is reasonable to assume that no change in contaminant
concentration occurs after cooking. It is important for
the assessor to be aware of these issues and choose
intake rate data that best match the concentration data
that are being used. For more information on cooking
losses and conversions necessary to account for such
losses, the reader is referred to Chapter 13 of this
handbook.
Sometimes contaminant concentrations in food
are reported on a dry weight basis. When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used. Dry-weight food
concentrations and intake rates are based on the weight
Child-Specific Exposure Factors Handbook
September 2008
Page
9-1
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
of the food consumed after the moisture content has
been removed. For information on converting the
intake rates presented in this chapter to dry weight
intake rates, the reader is referred to Section 9.4.
The purpose of this chapter is to provide intake
data for fruits and vegetables among children. The
recommendations for fruit and vegetable ingestion rates
are provided in the next section, along with a summary
of the confidence ratings for these recommendations.
The recommended values are based on the key study
identified by U.S. EPA for this factor. Following the
recommendations, the key study on fruit and vegetable
ingestion is summarized. Relevant data on ingestion of
fruits and vegetables are also provided. These data are
presented to provide the reader with added perspective
on the current state-of-knowledge pertaining to
ingestion of fruits and vegetables.
9.2 RECOMMENDATIONS
Table 9-1 presents a summary of the
recommended values for per capita and consumers-only
intake of fruits and vegetables, on an as-consumed
basis. Confidence ratings for the fruit and vegetable
intake recommendations for general population children
are provided in Table 9-2.
The U.S. EPA analysis of data from the 1994-96
and 1998 Continuing Survey of Food Intake among
Individuals (CSFII) was used in selecting recommended
intake rates for general population children. The U.S.
EPA analysis was conducted using age groups that
differed slightly from U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis. Also, the CSFII data on which the
recommendations are based are short-term survey data
and may not necessarily reflect the long-term
distribution of average daily intake rates. However, for
broad categories of food (i.e., total fruits and total
vegetables), because they are eaten on a daily basis
throughout the year with minimal seasonality, the short
term distribution may be a reasonable approximation of
the long-term distribution, although it will display
somewhat increased variability. This implies that the
upper percentiles shown here may tend to overestimate
the corresponding percentiles of the true long-term
distribution. It should also be noted that because these
recommendations are based on 1994-96 and 1998
CSFII data, they may not reflect the most recent
changes that may have occurred in consumption
patterns. More current data from the National Health
and Nutrition Survey (NHANES) will be incorporated
as the data become available and are analyzed.
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Chapter 9 - Intake of Fruits and Vegetables
Table 9-1. Recommended Values for Intake of Fruits and Vegetables, As Consumed1
Age Group
Per Capita
Consumers Only
Mean
95th Percentile
Mean
95th Percentile
Multiple
Percentiles
g/kg-day
g/kg-day
g/kg-day
Source
Birth to 1 year
1 to <2 years
2 to < 3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Total Fruits
5.7
6.2
6.2
4.6
2.4
0.8
0.8
21
19
19
14
8.8
3.5
3.5
10
6.9
6.9
5.1
2.7
1.1
1.1
26
19
19
15
9.3
3.8
3.8
See Tables
9-3 and 9-4
U.S. EPA
Analysis of
CSFII,
1994-96 and
1998.
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Total Vegetables
4.5
6.9
6.9
5.9
4.1
2.9
2.9
15
17
17
15
9.9
6.9
6.9
6.2
6.9
6.9
5.9
4.1
2.9
2.9
16
17
17
15
9.9
6.9
6.9
See Tables
9-3 and 9-4
U.S. EPA
Analysis of
CSFII,
1994-96 and
1998.
Individual Fruits and Vegetables - See Tables 9-5 and 9-6
Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005). Data
were placed in the standardized age categories closest to those used in the analysis.
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Chapter 9 - Intake of Fruits and Vegetables
Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Rationale
The survey methodology and data analysis was
adequate. The survey sampled more than 1 1,000
individuals up to age 18 years. However, samples size
for some individual fruits and vegetables for some of
the age groups are small. An analysis of primary data
was conducted.
No physical measurements were taken. The method
relied on recent recall of fruits and vegetables eaten.
The key study was directly relevant to fruit and
vegetable intake.
The data were demographically representative of the
U.S. population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total fruits and total
vegetables. Means were provided for individuals fruits
and vegetables.
Data collection was based on recall of consumption for
a 2-day period; the accuracy of using these data to
estimate long-term intake (especially at the upper
percentiles) is uncertain. However, use of short-term
data to estimate chronic ingestion can be assumed for
broad categories of foods such as total fruits and total
vegetables. Uncertainty is likely to be greater for
individual fruits and vegetables.
Rating
High for total fruits and
vegetables, low for some
individual fruits and
vegetables with small
sample size
Medium
High
Medium
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Chapter 9 - Intake of Fruits an
rs Handbook ^S$^P
^\y*A
id Vegetables \g^^j
Table 9-2. Confidence
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
in Recommendations for Intake of Fruits and Vegetables (continued)
Rationale Rating
Medium
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not
been peer reviewed outside the Agency.
There was 1 key study.
High confidence in the
averages; Low for some
individual fruits and
vegetables with small
sample size
Low confidence in the
long-term upper
percentiles
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Chapter 9 - Intake of Fruits and Vegetables
9.3 INTAKE STUDIES
The primary source of recent information on
consumption rates of fruits and vegetables among
children is the U.S. Department of Agriculture's
(USDA) CSFII. Data from the 1994-96 CSFII and the
1998 Children's supplement to the 1994-96 CSFII have
been used in various studies to generate children's
consumer-only and per capita intake rates for both
individual fruits and vegetables and total fruits and
vegetables. The CSFII is a series of surveys designed
to measure the kinds and amounts of foods eaten by
Americans. The CSFII 1994-96 was conducted
between January 1994 and January 1997 with a target
population of non-institutionalized individuals in all 50
states and Washington, D.C. In each of the 3 survey
years, data were collected for a nationally
representative sample of individuals of all ages. The
CSFII 1998 was conducted between December 1997
and December 1998 and surveyed children 9 years of
age and younger. It used the same sample design as the
CSFII 1994-96 and was intended to be merged with
CSFII 1994-96 to increase the sample size for children.
The merged surveys are designated as CSFII 1994-96,
1998. Additional information on these surveys can be
obtained at
http://www.ars.usda. goy^'Services/docs. htm ?docid=14531.
The CSFII 1994-96, 1998 collected dietary
intake data through in-person interviews on 2 non-
consecutive days. The data were based on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day. Over 11,000 of the sample persons
represented children up to 18 years of age. The 2-day
response rate for the 1994-1996 CSFII was
approximately 76 percent. The 2-day response rate for
CSFII 1998 was 82 percent.
The CSFII 1994-96,98 surveys were based on
a complex multistage area probability sample design.
The sampling frame was organized using 1990 U.S.
population census estimates, and the stratification plan
took into account geographic location, degree of
urbanization, and socioeconomic characteristics.
Several sets of sampling weights are available for use
with the intake data. By using appropriate weights, data
for all fours years of the surveys can be combined.
USDA recommends that all 4 years be combined in
order to provide an adequate sample size for children.
9.3.1 Key Fruits and Vegetables Intake Study
9.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998
For many years, the U.S. EPA's Office of
Pesticide Programs (OPP) has used food consumption
data collected by the U.S. Department of Agriculture
(USDA) for its dietary risk assessments. Most recently,
OPP, in cooperation with USDA's Agricultural
Research Service (ARS), used data from the 1994-96,
1998 CSFII to develop the Food Commodity Intake
Database (FCID). CSFII data on the foods people
reported eating were converted to the quantities of
agricultural commodities eaten. "Agricultural
commodity" is a term used by U.S. EPA to mean plant
(or animal) parts consumed by humans as food; when
such items are raw or unprocessed, they are referred to
as "raw agricultural commodities." For example, an
apple pie may contain the commodities apples, flour,
fat, sugar and spices. FCID contains approximately 553
unique commodity names and 8-digit codes. The FCID
commodity names and codes were selected and defined
by U.S. EPA and were based on the U.S. EPA Food
Commodity Vocabulary
(http://www.epa.Kov/pesticides/foodfeed/).
The fruit and vegetable items/groups selected
for the U.S. EPA analysis included total fruits and total
vegetables, and individual fruits such as: apples,
bananas, peaches, pears, strawberries, citrus fruits,
pome fruit, stone fruit, and tropical fruits; and
individual vegetables such as: asparagus, beets,
broccoli, cabbage, carrots, corn, cucumbers, lettuce,
okra, onions, peas, peppers, pumpkin, beans, tomatoes,
white potatoes, bulb vegetables, fruiting vegetables,
leafy vegetables, legumes, and small stalk stem
vegetables. Appendix 9A presents the food codes and
definitions used to determine the various fruits and
vegetables used in the analysis. Intake rates for these
food items/groups represent intake of all forms of the
product (e.g., both home produced and commercially
produced). Children who provided data for two days of
the survey were included in the intake estimates.
Individuals who did not provide information on body
weight or for whom identifying information was
unavailable were excluded from the analysis. Two-day
average intake rates were calculated for all individuals
in the database for each of the food items/groups.
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Chapter 9 - Intake of Fruits and Vegetables
These average daily intake rates were divided by each
individual's reported body weight to generate intake
rates in units of grams per kilogram of body weight per
day (g/kg-day). The data were weighted according to
the four-year, two-day sample weights provided in the
1994-96, 1998 CSFII to adjust the data for the sample
population to reflect the national population.
Summary statistics were generated on both a
per capita and a consumer only basis. For per capita
intake, both users and non-users of the food item were
included in the analysis. Consumer only intake rates
were calculated using data for only those individuals
who ate the food item of interest during the survey
period. Intake data from the CSFII were based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the fruits or vegetables being analyzed, mean intake
rate, and standard error of the mean intake rate were
calculated for total fruits, total vegetables, and selected
individual fruits and vegetables. Percentiles of the
intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th,
75th, 90th, 95th, 99th, and 100th percentile were also
provided for total fruits and total vegetables. Data were
provided for the following age groups of children: birth
to <1 year, 1 to <2 years, 3 to <5 years, 6 to <12 years,
and 13 to <19 years. Because these data were
developed for use in U.S. EPA's pesticide registration
program, the age groups used are slightly different than
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).
Table 9-3 presents as-consumed per capita
intake data for total fruits and vegetables in g/kg-day;
as-consumed consumer only intake data for total fruits
and vegetables in g/kg-day are provided in Table 9-4.
Table 9-5 provides per capita intake data for individual
fruits and vegetables and Table 9-6 provides consumer
only intake data for individual fruits and vegetables.
It should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the long-
term distribution of average daily intake rates. The
distributions generated from short-term and long-term
data will differ to the extent that each individual's
intake varies from day to day; the distributions will be
similar to the extent that individuals' intakes are
constant from day to day. Day-to-day variation in
intake among individuals will be high for fruits and
vegetables that are highly seasonal and for fruits and
vegetables that are eaten year-round, but that are not
typically eaten every day. For these fruits and
vegetables, the intake distribution generated from short-
term data will not be a good reflection of the long-term
distribution. On the other hand, for broad categories of
foods (e.g., total fruits and total vegetables) that are
eaten on a daily basis throughout the year, the short-
term distribution may be a reasonable approximation of
the true long-term distribution, although it will show
somewhat more variability. In this chapter,
distributions are provided only for broad categories of
fruits and vegetables (i.e., total fruits and total
vegetables). Because of the increased variability of the
short-term distribution, the short-term upper percentiles
shown here may overestimate the corresponding
percentiles of the long-term distribution. For individual
foods, only the mean, standard error, and percent
consuming are provided.
The strengths of U.S. EPA's analysis are that
it provides distributions of intake rates for various age
groups of children, normalized by body weight. The
analysis uses the 1994-96, 1998 CSFII data set which
was designed to be representative of the U.S.
population. The data set includes four years of intake
data combined, and is based on a two-day survey
period. As discussed above, short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food. This is particularly true for the tails (extremes)
of the distribution of food intake. Also, the analysis
was conducted using slightly different age groups than
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the age groups used, the data should provide suitable
intake estimates for the age groups of interest.
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Chapter 9 - Intake of Fruits and Vegetables
9.3.2 Relevant Fruit and Vegetable Intake
Studies
9.3.2.1 USDA, 1999 - Food and Nutrient Intakes by
Children 1994-96,1998, Table Set 17
USDA (1999) calculated national probability
estimates of food and nutrient intake by children based
on all 4 years of the CSFII (1994-96 and 1998) for
children age 9 years and under, and on CSFII 1994-96
only for individuals age 10 years and over. Sample
weights were used to adjust for non-response, to match
the sample to the U.S. population in terms of
demographic characteristics, and to equalize intakes
over the 4 quarters of the year and the 7 days of the
week. A total of 503 breast-fed children were excluded
from the estimates, but both consumers and non-
consumers were included in the analysis.
USDA (1999) provided data on the mean per
capita quantities (grams) of various food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey. Tables 9-7 through 9-10 present
data on the mean quantities (grams) of fruits and
vegetables consumed per individual for one day, and
the percentage of survey individuals consuming fruits
and vegetables on that survey day. Data on mean
intakes or mean percentages are based on respondents'
day-1 intakes.
The advantage of the USDA (1999) study is
that it uses the 1994-96, 98 CSFII data set, which
includes four years of intake data, combined, and
includes the supplemental data on children. These data
are expected to be generally representative of the U.S.
population and they include data on a wide variety of
fruits and vegetables. The data set is one of a series of
USDA data sets that are publicly available. One
limitation of this data set is that it is based on a one-day,
and short-term dietary data may not accurately reflect
long-term eating patterns. Other limitations of this
study are that it only provides mean values of food
intake rates, consumption is not normalized by body
weight, and presentation of results is not consistent with
U.S. EPA's recommended age groups.
9.3.2.2 Smiciklas-Wright et al, 2002 - Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating Occasion
and in a Day, 1994-1996
Using data gathered in the 1994-96 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of fruits and vegetables
consumed per eating occasion by members of the U. S.
population (i.e., serving sizes). The estimates of
serving size were based on data obtained from 14,262
respondents, ages 2 years and above, who provided 2
days of dietary intake information. A total of 4,939 of
these respondents were children, ages 2 to 19 years of
age. Only dietary intake data from users of the
specified food were used in the analysis (i.e., consumers
only data).
Table 9-1 presents serving size data for
selected fruits and vegetables. These data are presented
on an as-consumed basis (grams) and represent the
quantity of fruits and vegetables consumed per eating
occasion. These estimates may be useful for assessing
acute exposures to contaminants in specific foods, or
other assessments where the amount consumed per
eating occasion is necessary. Only the mean and
standard deviation serving size data and percent of the
population consuming the food during the 2-day survey
period are presented in this handbook. Percentiles of
serving sizes of the foods consumed by these age
groups of the U.S. population can be found in
Smiciklas-Wright et al. (2002).
The advantages of using these data are that
they were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
for individual foods consumed as ingredients of mixed
foods. Mixed foods were disaggregated via recipe files
so that the individual ingredients could be grouped
together with similar foods that were reported
separately. Thus, weights of foods consumed as
ingredients were combined with weights of foods
reported separately to provide a more thorough
representation of consumption. However, it should be
noted that since the recipes for the mixed foods
consumed were not provided by the respondents,
standard recipes were used. As a result, the estimates
of quantity consumed for some food types are based on
assumptions about the types and quantities of
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ingredients consumed as part of mixed foods. This
study used data from the 1994 to 1996 CSFII; data from
the 1998 children's supplement were not included.
9.3.2.3 Fox et al, 2004 - Feeding Infants and
Toddlers study: What Foods Are Infants and
Toddlers Eating
Fox et al. (2004) used data from the Feeding
Infants and Toddlers study (FITS) to assess food
consumption patterns in infants and toddlers. The FITS
was sponsored by Gerber Products Company and was
conducted to obtain current information on food and
nutrient intakes of children, ages 4 to 24 months old, in
the 50 states and the District of Columbia. The FITS is
described in detail in Devaney et al. (2004). FITS was
based on a random sample of 3,022 infants and toddlers
for which dietary intake data were collected by
telephone from their parents or caregivers between
March and July 2002. An initial recruitment and
household interview was conducted, followed by an
interview to obtain information on intake based on 24-
hour recall. The interview also addressed growth,
development and feeding patterns. A second dietary
recall interview was conducted for a subset of 703
randomly selected respondents. The study over-
sampled children in the 4 to 6 and 9 to 11 months age
groups; sample weights were adjustedfornon-response,
over-sampling, andunder-coverage of some subgroups.
The response rate for the FITS was 73 percent for the
recruitment interview. Of the recruited households,
there was a response rate of 94 percent for the dietary
recall interviews (Devaney et al., 2004). The
characteristics of the FITS study population is shown in
Table 9-12.
Fox et al. (2004) analyzed the first set of 24-
hour recall data collected from all study participants.
For this analysis, children were grouped into six age
categories: 4 to 6 months, 7 to 8 months, 9 to 11
months, 12 to 14 months, 15 to 18 months, and 19 to 24
months. Table 9-13 provides the percentage of infants
and toddlers consuming different types of vegetables at
least once in a day. The percentages of children eating
any type of vegetable ranged from 39.9 percent for 4 to
6 month olds to 81.6 percent for 19 to 24 month olds.
Table 9-14 provides the top five vegetables consumed
by age group. Some of the highest percentages ranged
from baby food carrots (9.6 percent) in the 4 to 6 month
old group to french fries (25.5 percent) in the 19 to 24
month old group. Table 9-15 provides the percentage
of children consuming different types of fruit at least
once per day. The percentages of children eating any
type of fruit ranged from 41.9 percent to 4 to 6 month
olds to 77.2 percent for 12 to 14 month olds. Table 9-
16 provides information on the top five fruits eaten by
infants and toddlers at least once per day. The highest
percentages were for bananas among infants 9 to 24
months, and baby food applesauce among infants 4 to
8 months old.
The advantages of this study were that the
study population represented the U.S. population and
the sample size was large. One limitation of the
analysis done by Fox et al. (2004) was that only
frequency data were provided; no information on actual
intake rates was included. In addition, Devaney et al.
(2004) noted several limitations associated with the
FITS data. For the FITS, a commercial list of infants
and toddlers was used to obtain the sample used in the
study. Since many of the households could not be
located and did not have children in the target
population, a lower response rate than would have
occurred in a true national sample was obtained
(Devaney et al., 2004). In addition, the sample was
likely from a higher socioeconomic status when
compared with all U.S. infants in this age group (4 to 24
months old) and the use of a telephone survey may have
omitted lower-income households without telephones
(Devaney et al., 2004).
9.3.2.4 Ponza et al, 2004 - Nutrient Food Intakes
and Food Choices of Infants and Toddlers
Participating in WIC
Ponza et al. (2004) conducted a study using
selected data from the FITS to assess feeding patterns,
food choices and nutrient intake of infants and toddlers
participating in the Special Supplemental Nutrition
Program for Women, Infants, and Children (WIC).
Ponza et al. (2004) evaluated FITS data for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months (N = 1,159) and 12 to 24 months (N= 996).
The total sample size described by WIC participants
and non-participants is shown in Table 9-17.
The foods consumed were analyzed by
tabulating the percentage of infants who consumed
specific foods/food groups per day (Ponza et al., 2004).
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Weighted data were used in all of the analyses used in
the study (Ponza et al, 2004). Table 9-17 presents the
demographic data for WIC participants and non-
participants. Table 9-18 provides information on the
food choices for the infants and toddlers studied. There
was little difference in vegetable choices among WIC
participants and non-participants (Table 9-18).
However, there were some differences for fruits.
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
were not provided. Other limitations are those
associated with the FITS data, as described previously
in Section 9.3.2.3.
9.3.2.5 Menella et al., 2006 - Feeding Infants and
Toddlers Study: The Types of Foods Fed to
Hispanic Infants and Toddlers
Menella et al. (2006) investigated the types of
food and beverages consumed by Hispanic infants and
toddlers in comparison to the non-Hispanic infants and
toddlers in the United States. The FITS 2002 data for
children between 4 and 24 months of age were used for
the study. The data represent a random sample of 371
Hispanic and 2,367 non-Hispanic infants and toddlers
(Menella et al., 2006). Menella et al. (2006) grouped
the infants as follows: 4 to 5 months (N = 84 Hispanic;
538 non-Hispanic), 6 to 11 months (N = 163 Hispanic
and 1,228 non-Hispanic), and 12 to 24 months (N = 124
Hispanic and 871 non-Hispanic) of age.
Table 9-19 provides the percentages of
Hispanic and non-Hispanic infants and toddlers
consuming fruits and vegetables. In most instances the
percentages consuming the different types of fruits and
vegetables were similar. However, 4 to 5 month old
Hispanic infants were more likely to eat fruits than non-
Hispanic infants in this age group. Table 9-20
provides the top five fruits and vegetables consumed
and the percentage of children consuming these foods
at least once in a day. Apples and bananas were the
foods with the highest percent consuming for both the
Hispanic and non-Hispanic study groups. Potatoes and
carrots were the vegetables with the highest percentage
of infants and toddlers consuming in both study groups.
The advantage of the study is that it provides
information on food preferences for Hispanic and non-
Hispanic infants and toddlers. A limitation is that the
study did not provide food intake data, but provided
frequency of use data instead. Other limitations are
those noted previously in Section 9.3.2.3 for the FITS
data.
9.3.2.6 Fox et al, 2006 - Average Portion of Foods
Commonly Eaten by Infants and Toddlers in
the United States
Fox et al. (2006) estimated average portion
sizes consumed per eating occasion by children 4 to 24
months of age who participated in the Feeding Infant
and Toddlers Study (FITS). The FITS is a cross-
sectional study designed to collect and analyze data on
feeding practices, food consumption, and usual nutrient
intake of U.S. infants and toddlers and is described in
Section 9.3.2.3 of this chapter. It included a stratified
random sample of 3,022 children between 4 and 24
months of age.
Usingthe 24-hour recall data, Fox et al. (2006)
derived average portion sizes for major food groups,
including fruits and vegetables. Average portion sizes
for select individual foods within these major groups
were also estimated. For this analysis, children were
grouped into six age categories: 4 to 5 months, 6 to 8
months, 9 to 11 months, 12 to 14 months, 15 to 18
months, and 19 to 24 months. Tables 9-21 and 9-22
present the average portion sizes for fruits and
vegetables for infants and toddlers, respectively.
9.4 CONVERSION BETWEEN WET AND
DRY WEIGHT INTAKE RATES
The intake data presented in this chapter are
reported in units of wet weight (i.e., as-consumed fruits
and vegetables consumed per day or per eating
occasion). However, data on the concentration of
contaminants in fruits and vegetables may be reported
in units of either wet or dry weight.(e.g., mg
contaminant per gram-dry-weight of fruits and
vegetables.) It is essential that exposure assessors be
aware of this difference so that they may ensure
consistency between the units used for intake rates and
those used for concentration data (i.e., if the
contaminant concentration is measured in dry weight of
fruits and vegetables, then the dry weight units should
be used for their intake values).
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If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to dry weight intake rates
using the moisture content percentages presented in
Table 9-23 and the following equation:
IR, = IR
dw ww
100- W
100
(Eqn. 9-1)
where:
Mw
W
dry weight intake rate;
wet weight intake rate; and
percent water content
Alternatively, dry weight residue levels in fruits and
vegetables may be converted to wet weight residue
levels for use with wet weight (e.g., as-consumed)
intake rates as follows:
C = C
ww dw
100- W
100
(Eqn. 9-2)
where:
dw
w
wet weight intake rate;
dry weight intake rate; and
percent water content.
The moisture data presented in Table 9-23 are for
selected fruits and vegetables taken from USDA (2007).
9.5
REFERENCES FOR CHAPTER 9
Devaney, B.; Kalb, L.; Brief el, R.; Zavitsky-Novak, T.;
Clusen, N.; Ziegler, P. (2004) Feeding infants
and toddlers study: overview of the study
design. J Am Diet Assoc 104(Suppl 1): S8-
S13.
Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L.
(2004) Feeding Infants and Toddlers Study:
what foods are infants and toddlers eating. J
Am Diet Assoc 104 (Suppl):S22-S30.
Fox, M.K.; Reidy, K.; Karwe, V.; Ziegler, P. (2006)
Average portions of foods commonly eaten by
infants and toddlers in the United States. J
Am Diet Assoc 106 (Suppl 1):S66-S76.
Goldman, L. (1995) Children - unique and vulnerable.
Environmental risks facing children and
recommendations for response. Environ
Health Perspect 103(6): 13-17.
Mennella, J.;Ziegler,P.;Briefel,R.;Novak, T. (2006)
Feeding Infants and Toddlers Study: the types
of foods fed to Hispanic infants and toddlers.
J Am Diet Assoc 106 (Suppl 1): S96-S106.
Ponza, M; Devaney, B.; Ziegler, P.; Reidy, K.;
Squatrito, C. (2004) Nutrient intakes and food
choices of infants and toddlers participating in
WIC. J Am Diet Assoc 104 (Suppl): S71-
S79.
Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.;
Cook, A.J.; Goldman, J.D. (2002) Foods
commonly eaten in the United States:
Quantities consumed per eating occasion and
in a day, 1994-1996. U.S. Department of
Agriculture NFS Report No. 96-5, pre-
publication version, 252 pp.
USDA. (1999) Food and nutrient intakes by children
1994-96,1998: Table Set 17. Beltsville, MD:
Food Surveys Research Group, Beltsville
Human Nutrition Research Center,
Agricultural Research Service, U.S.
Department of Agriculture.
USDA (2007) USDA National Nutrient Database for
Standard Reference, Release 20. Agricultural
Research Service Nutrient Data Laboratory
Home Page,
http://www.ars.usda.TOv/ba/bhnrc/ndl
U.S. EPA. (2005) Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
U.S. Environmental Protection Agency,
Washington, D.C., EPA/630/P-03/003F.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-11
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Table 9-3. Per Capita Intake of Fruits and Ve
. „ ,, Percent
Age Group N „
0 r Consuming
Mean
SE
jetables (g/kg-day as consumed)
Percentiles
1st
5th
10th
25th
50th
75th
90th
95th
99th 100th
Fruits
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U
56.4
89.5
90.0
88.3
73.2
72.1
99.7
100.0
99.9
100.0
5.7
6.2
4.6
2.4
0.8
4.5
6.9
5.9
4.1
2.9
S. EPA analysis of 1994-96,
0.3
0.2
0.1
0.1
0.1
Veg
0.2
0.2
0.1
0.1
0.1
1998 CSFII
0.0
0.0
0.0
0.0
0.0
etables
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.8
0.6
0.4
0.0
0.0
0.0
0.0
0.0
0.0
1.5
1.4
1.0
0.7
0.0
0.5
0.2
0.1
0.0
0.0
3.2
2.8
1.8
1.4
1.5
4.7
3.2
1.3
0.1
2.7
5.6
4.7
3.2
2.4
9.6
9.4
7.0
3.3
1.1
7.4
9.3
7.7
5.3
3.8
17.1
14.6
11.4
6.4
2.4
12.2
13.9
11.7
7.8
5.5
21.3
18.5
14.4
8.8
3.5
14.8
17.1
14.7
9.9
6.9
32.2 73.8
26.4 44.0
22.3 45.5
14.3 25.0
6.9 12.8
25.3 56.8
26.5 58.2
23.4 50.9
17.4 53.7
11.4 29.5
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Table 9-4. Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed)
Age Group N
Mean
SE
Percentiles
p,
5th 10th
25th
50th
75th
90th
95th
99th
100th
Fruits
Birth to 1 year 830
1 to 2 years 1,878
3 to 5 years 3,957
6 to 12 years 1,846
13 to 19 vears 898
10.1
6.9
5.1
2.7
1.1
0.4
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.4 1.2
0.0 0.1
0.0 0.0
0.0 0.0
0.0 0.0
3.7
2.2
1.0
0.3
0.0
8.5
5.4
3.8
1.7
0.5
14.4
10.1
7.5
3.7
1.5
20.4
15.3
11.9
6.7
2.9
26.4
19.0
15.0
9.3
3.7
34.7
27.1
22.8
14.8
7.6
73.8
44.0
45.5
25.0
12.8
Vegetables
Birth to 1 year 1,062
1 to 2 years 2,090
3 to 5 years 4,389
6 to 12 years 2,087
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U
6.2
6.9
5.9
4.1
2.9
0.3
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.1
0.0
S. EPA analysis of 1994-96,
0.1 0.1
0.7 1.5
0.8 1.4
0.6 1.0
0.4 0.7
1998 CSFII.
2.0
3.2
2.8
1.8
1.4
4.9
5.6
4.7
3.2
2.4
9.4
9.3
7.7
5.3
3.8
13.4
13.9
11.7
7.8
5.5
16.1
17.1
14.7
9.9
6.9
26.4
26.5
23.4
17.4
11.4
56.8
58.2
50.9
53.7
29.5
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed)
Age Group N
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Percent
_ . Mean SE
Consuming
Apples
34.6 2.32 0.13
44.8 1.79 0.09
44.6 1.64 0.05
38.2 0.83 0.05
22.5 0.20 0.02
Beets
0.4 0.01 0.01
0.7 0.01 0.00
0.8 0.01 0.00
0.8 0.01 0.00
0.7 0.00 0.00
Cabbage
1.0 0.01 0.00
8.0 0.06 0.01
8.9 0.07 0.01
9.5 0.06 0.01
9.0 0.04 0.01
Percent
_ . Mean SE
Consuming
Asparagus
0.21 0.01 0.00
0.77 0.02 0.01
0.54 0.01 0.00
0.66 0.01 0.00
0.56 0.00 0.00
Berries and Small Fruit
16.5 0.13 0.02
66.2 0.91 0.05
72.7 0.72 0.03
73.4 0.40 0.03
97.7 0.19 0.01
Carrots
12.3 0.17 0.03
46.8 0.41 0.02
46.2 0.34 0.02
44.4 0.22 0.01
40.3 0.11 0.01
Percent
_ . Mean SE
Consuming
Bananas
40.68 1.24 0.06
62.76 1.77 0.09
60.74 0.93 0.04
57.69 0.38 0.03
42.09 0.13 0.02
Broccoli
3.5 0.07 0.02
12.0 0.25 0.03
10.7 0.18 0.01
11.0 0.14 0.02
8.3 0.06 0.01
Citrus Fruits
2.5 0.07 0.02
15.5 0.47 0.05
18.2 0.50 0.03
16.0 0.26 0.02
12.3 0.11 0.02
Percent
_ . Mean SE
Consuming
Beans
21.6 0.43 0.04
46.8 0.76 0.04
43.0 0.52 0.02
38.8 0.32 0.02
55.4 0.15 0.02
Bulb Vegetables
33.4 0.07 0.01
93.3 0.30 0.01
95.8 0.27 0.01
97.3 0.21 0.01
12.3 0.11 0.02
Corn
46.0 0.48 0.03
96.5 1.13 0.05
98.7 1.24 0.03
98.9 0.87 0.03
95.7 0.43 0.02
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group N
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1.222
Percent
_ . Mean SE
Consuming
Cucumbers
1.7 0.00 0.00
20.5 0.11 0.01
29.3 0.16 0.02
32.6 0.14 0.02
41.3 0.11 0.03
Legumes
51.7 1.21 0.06
96.9 1.30 0.08
98.3 0.85 0.06
98.1 0.48 0.03
94.9 0.27 0.02
Peaches
24.4 0.85 0.08
50.7 0.47 0.04
55.4 0.26 0.02
54.7 0.14 0.02
39.1 0.06 0.01
Percent
_ . Mean SE
Consuming
Cucurbits
14.0 0.45 0.04
31.3 0.72 0.06
38.7 0.83 0.07
39.9 0.54 0.06
46.7 0.32 0.08
Lettuce
1.1 0.00 0.00
23.3 0.14 0.01
33.4 0.21 0.01
41.7 0.22 0.01
55.2 0.22 0.02
Pears
15.9 0.73 0.07
17.2 0.40 0.04
16.6 0.26 0.03
17.5 0.14 0.01
5.9 0.03 0.01
Percent
_ . Mean SE
Consuming
Fruiting Vegetables
25.50 0.32 0.04
92.14 1.56 0.06
95.38 1.46 0.03
95.87 1.05 0.03
96.08 0.79 0.03
Okra
0.2 0.00 0.00
1.3 0.01 0.00
0.8 0.01 0.00
1.3 0.01 0.00
0.8 0.00 0.00
Peas
29.5 0.47 0.04
28.3 0.34 0.03
20.5 0.21 0.02
17.2 0.12 0.01
14.0 0.07 0.01
Percent
_ . Mean SE
Consuming
Leafy Vegetables
44.2 0.29 0.05
82.1 0.71 0.04
86.9 0.67 0.02
89.5 0.55 0.03
90.3 0.43 0.02
Onions
32.8 0.07 0.01
93.0 0.29 0.01
95.6 0.26 0.01
96.8 0.20 0.01
97.3 0.18 0.01
Peppers
15.6 0.01 0.00
77.5 0.05 0.01
84.6 0.05 0.00
85.1 0.05 0.00
84.8 0.04 0.00
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group N
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year !=486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1.222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Percent ...
_ . Mean SE
Consuming
Pome Fruit
40.0 3.04 0.17
52.0 2.19 0.10
51.7 1.90 0.06
47.9 0.97 0.06
26.5 0.23 0.02
Strawberries
6.8 0.02 0.00
33.5 0.19 0.03
37.1 0.14 0.01
37.3 0.10 0.01
26.8 0.05 0.01
White Potatoes
39.9 0.64 0.07
91.2 1.95 0.08
95.1 1.75 0.06
93.9 1.21 0.06
92.6 0.93 0.05
Percent ...
_ . Mean SE
Consuming
Pumpkins
0.3 0.00 0.00
0.7 0.01 0.00
0.9 0.01 0.00
1.8 0.01 0.00
1.3 0.01 0.00
Stone Fruit
29.20 1.15 0.10
53.62 0.60 0.04
57.45 0.38 0.02
56.83 0.23 0.02
41.08 0.09 0.01
Percent ...
_ . Mean SE
Consuming
Root Tuber Vegetables
61.7 2.60 0.15
99.6 3.38 0.09
100.0 2.96 0.07
100.0 2.09 0.07
99.9 1.36 0.06
Tomatoes
21.5 0.30 0.03
80.7 1.50 0.05
85.7 1.40 0.03
86.9 1.00 0.03
90.2 0.74 0.03
Percent ...
_ . Mean SE
Consuming
Stalk, Stem Vegetables
1.9 0.01 0.00
13.2 0.06 0.01
10.9 0.04 0.00
10.7 0.03 0.01
16.6 0.03 0.01
Tropical Fruits
42.2 1.31 0.07
70.1 1.97 0.10
69.7 1.10 0.04
67.0 0.50 0.04
54.5 0.19 0.02
SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and
vegetables with higher percentages consuming.
Source: Based on unpublished U.S. EPA analysis of 1994-96. 1998 CSFII.
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed)
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
N Mean SE
Apples
496 6.71 0.31
947 4.00 0.15
1,978 3.68 0.08
792 2.17 0.12
271 0.90 0.06
Beets
6 1.42 0.87
13 0.98 0.32
36 0.90 0.20
16 0.66 0.33
9 0.20 0.12
Cabbage
15 0.61 0.41
160 0.73 0.11
369 0.78 0.07
190 0.63 0.11
106 0.40 0.06
N Mean SE
Asparagus
3 2.59 1.16
19 1.99 0.54
23 1.37 0.32
13 1.77 0.43
4 0.56 0.08
Berries and Small Fruits
229 0.81 0.07
1,396 1.38 0.06
3,166 0.99 0.04
1,523 0.54 0.04
679 0.27 0.03
Carrots
179 1.39 0.20
999 0.87 0.05
2,048 0.74 0.03
904 0.50 0.03
482 0.27 0.02
N Mean SE
Bananas
605 3.04 0.12
1,328 2.82 0.12
2,746 1.54 0.06
1,214 0.66 0.05
511 0.30 0.04
Broccoli
49 2.09 0.33
242 2.11 0.16
475 1.67 0.09
213 1.29 0.16
102 0.69 0.07
Citrus Fruits
37 2.79 0.53
336 3.06 0.20
751 2.75 0.15
324 1.60 0.12
157 0.90 0.15
N Mean SE
Beans
313 2.00 0.16
996 1.63 0.08
1,909 1.22 0.04
833 0.82 0.05
472 0.49 0.03
Bulb Vegetables
489 0.22 0.02
1,957 0.32 0.01
4,207 0.28 0.01
2,040 0.22 0.01
1,194 0.20 0.01
Corn
671 1.05 0.07
2,027 1.17 0.05
4,334 1.26 0.03
2,064 0.88 0.03
1.176 0.45 0.01
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
N Mean SE
Cucumbers
25 0.28 0.11
439 0.52 0.05
1,266 0.56 0.05
667 0.43 0.06
500 0.26 0.06
Legumes
754 2.34 0.11
2,037 1.34 0.08
4,308 0.86 0.06
2,045 0.49 0.03
1.168 0.29 0.02
Peaches
344 3.47 0.28
1,067 0.93 0.08
2,461 0.48 0.03
1,150 0.26 0.03
480 0.15 0.03
N Mean SE
Cucurbits
213 3.19 0.29
682 2.29 0.17
1,694 2.15 0.17
833 1.34 0.15
563 0.69 0.16
Lettuce
15 0.17 0.02
481 0.58 0.04
1,415 0.62 0.03
858 0.53 0.02
669 0.40 0.03
Pears
217 4.55 0.28
354 2.33 0.16
711 1.59 0.12
382 0.81 0.07
72 0.45 0.09
N Mean SE
Fruiting Vegetables
371 1.24 0.11
1,927 1.70 0.06
4,180 1.53 0.03
2,014 1.10 0.03
1,176 0.82 0.03
Okra
4 1.50 0.54
29 0.64 0.19
34 1.16 0.32
21 0.62 0.15
12 0.43 0.13
Peas
417 1.60 0.09
609 1.21 0.06
888 1.02 0.07
346 0.68 0.06
168 0.48 0.06
N Mean SE
Leafv Vegetables
639 0.65 0.11
1,729 0.87 0.05
3,815 0.77 0.03
1,860 0.62 0.03
1,101 0.47 0.02
Onions
481 0.22 0.02
1,948 0.31 0.01
4,200 0.27 0.01
2,030 0.21 0.01
1.190 0.19 0.01
Peppers
224 0.05 0.01
1,627 0.06 0.01
3,706 0.06 0.00
1,784 0.05 0.01
1.041 0.05 0.00
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years
N Mean SE
Pome Fruit
572 7.60 0.34
1,097 4.21 0.13
2,291 3.68 0.08
1,012 2.03 0.10
320 0.87 0.06
Strawberries
96 0.26 0.06
729 0.57 0.08
1,710 0.38 0.03
783 0.28 0.02
326 0.18 0.03
White Potatoes
577 1.60 0.15
1,918 2.14 0.09
4,147 1.84 0.06
1,963 1.29 0.06
1.131 1.01 0.05
N Mean SE
Pumpkins
3 1.06 0.71
15 1.08 0.51
36 0.56 0.10
37 0.52 0.11
14 0.42 0.16
Stone Fruit
418 3.95 0.25
1,130 1.13 0.08
2,556 0.66 0.03
1,194 0.41 0.03
508 0.21 0.03
N Mean SE
Root Tuber Vegetables
916 4.21 0.19
2,087 3.40 0.09
4,388 2.96 0.07
2,089 2.09 0.07
1,221 1.36 0.06
Tomatoes
315 1.42 0.13
1,684 1.86 0.06
3,764 1.63 0.03
1,832 1.15 0.03
1,098 0.82 0.03
N Mean SE
Stalk, Stem Vegetables
24 0.56 0.22
272 0.48 0.05
502 0.38 0.03
218 0.32 0.04
190 0.20 0.03
Tropical Fruits
630 3.09 0.12
1,476 2.81 0.12
3,106 1.57 0.05
1,407 0.75 0.05
652 0.35 0.04
SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and
vegetables with higher percentages consuming.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
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Age Group
Sample
Size
Table
Total
9-7. Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day)
White Potatoes
DarkG
Total
Vegeta
Fried
Lettuce,
reen „ lettuce-
, , Yellow lomatoes , ,
bles ., , , based
Vegetables , ,
salads
Green
beans
Corn,
green
peas, lima
beans
Other
vegetables
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
57
79
87
83
91
97
103
97
88
9
26
32
29
34
37
44
38
31
1
11
17
14
17
19
22
20
16
2
5
4
5
5
6
4
5
4
19
9
5
7
5
5
6
5
7
r
7
11
9
13
11
12
12
10
a,b
1
2
1
2
3
3
3
2
6
8
7
7
5
5
6
5
6
5
9
10
9
11
12
12
11
10
16
16
17
17
16
18
17
17
17
Males
6 to 9 years
6 to 1 1 yers
12 to 19 years
787
1,031
737
110
115
176
47
50
85
26
27
44
4
5
6
5
5
6
16
16
28
5
5
12
5
5
3"
11
11
10
16
18
25
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
110
116
145
42
46
61
22
25
31
5
5
9
4
4
4
14
15
18
6
7
12
5
5
4
13
12
8
21
22
28
Males and Females
9 years and under
19 years and under
9,309
11,287
97
125
37
53
19
27
4
6
6
6
a Estimate is not statistically reliable due to small samples size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption amounts shown are representative of the first day of each participant
12
17
's survey response.
3
7
6
5
11
10
18
22
Source: USDA, 1999.
s
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Table 9-8. Percentage of Individuals Consuming Vegetables, by Sex and Age (%)
Age Group
Sample .
_. Total
Size
White Potatoes
Total
Fried
Dark
Green
Vegetabl
Deep
Yellow
es Vegetables
Tomatoes
Lettuce,
lettuce-
based
salads
Green
beans
Corn,
green
peas, lima
beans
Other
vegetables
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
47.2
73.3
78.4
75.9
80.5
80.7
83.0
81.4
75.4
12.3
40.4
46.7
43.6
46.7
47.3
50.7
48.2
42.3
4.3
25.2
34.5
29.9
34.7
34.8
38.3
35.9
30.1
2.3
6.4
7.6
7.0
7.0
7.2
4.6
6.3
6.1
20.5
13.3
10.5
11.8
10.7
12.0
13.3
12.0
13.0
1.8
18.0
30.8
24.6
34.1
33.0
36.5
34.5
27.2
0.2"
3.9
7.5
5.7
8.3
10.0
13.4
10.6
7.6
7.8
13.7
11.5
12.6
10.1
9.0
10.4
9.9
10.5
8.5
17.6
15.0
16.2
14.6
16.4
16.1
15.7
15.0
14.8
19.4
22.3
20.9
24.7
26.5
28.8
26.7
23.3
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
78.8
79.3
78.2
47.9
48.7
49.5
38.0
38.4
38.6
6.3
6.1
3.6
12.5
12.4
8.0
38.2
38.7
43.0
13.1
13.9
23.8
7.8
6.7
3.5
15.0
13.8
7.4
29.7
30.8
33.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
80.5
81.7
79.5
48.2
50.8
46.4
36.3
38.9
34.6
5.9
5.4
7.0
11.9
11.4
10.6
33.8
33.5
35.3
15.8
17.1
25.1
8.4
7.8
4.4
15.9
15.1
7.4
26.6
29.2
34.5
Males and Females
9 years and under
19 years and under
9,309
77.1
11,287 78.3
44.6
46.8
32.9
35.3
6.1
5.6
12.7
11.2
30.7
34.6
10.3
16.6
9.6
7.0
15.2
11.9
25.2
29.4
a Estimate is not statistically reliable due to small samples size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
1 f
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Table 9-9. Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day)
Citrus Fruits and
Juices
Age Group
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
Sample
Size
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
Total
Total
131
267
276
271
256
243
218
239
237
4
47
65
56
61
62
55
59
52
Juices
4
42
56
49
51
52
44
49
44
Dried
fruits
Males and
_a,b
2
2
2
1
1
_a,b
1
1
Total
Females
126
216
207
212
191
177
160
176
182
Other fruits, mixtures, and juices
Apples
14
22
27
24
27
31
31
30
26
Bananas
10
23
20
22
18
17
14
16
17
Melons
and
berries
I"
8
10
9
13
14
13
13
10
Other
fruits and
mixtures
(mainly
fruit)
39
29
20
24
24
22
24
23
26
Non-
citrus
juices and
nectars
61
134
130
132
110
92
78
93
103
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
194
183
174
58
67
102
51
60
94
_a,b
_a,b
1"
133
113
70
32
28
13
11
11
8
21
16
11"
20
19
10
50
40
29
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
9 years and under
19 years and under
704
969
732
9,309
11,287
180
169
157
217
191
63
64
72
55
70
54
54
67
47
62
1"
_a,b
_a,b
Males and
1
1
113
103
83
Females
159
118
* Estimate is not statistically reliable due to small samples size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption amounts shown are representative of the first day of each participant
Source: USDA, 1999
23
21
13
27
21
10
8
5
15
11
10
8
15
12
12
25
23
14
24
19
46
42
35
81
56
s survey response
s
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Table 9-10.
Age Group
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
Percentage of Individuals Consuming,
Citrus Fruits and
Juices
Sample
Size
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
Total
59.7
81.0
76.6
78.8
74.5
72.6
67.6
71.6
72.6
Total
3.6
23.6
30.6
27.2
27.9
28.0
26.9
27.6
24.6
Juices
2.7
19.0
23.4
21.3
21.4
21.8
19.5
20.9
18.8
Dried
fruits
Males
0.4"
5.9
5.3
5.6
4.1
3.0
1.3"
2.8
3.5
Total
and Females
59.0
73.0
64.7
68.8
64.2
62.1
56.9
61.0
63.5
Fruits by Sex and Age (%)
Other fruits, mixtures, and juices
Apples
15.7
23.4
24.0
23.7
22.4
23.7
21.9
22.7
22.2
Bananas
13.3
25.1
20.2
22.6
17.5
15.7
12.6
15.3
17.6
Melons
and
berries
1.8
6.9
8.5
7.7
7.8
7.6
7.4
7.6
6.9
Other
fruits and
mixtures
(mainly
fruit)
29.9
26.5
19.4
22.9
20.1
20.0
19.0
19.7
22.0
Non-
citrus
juices and
nectars
33.0
43.2
37.0
40.0
33.3
30.8
24.5
29.5
33.5
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
59.0
56.5
44.5
24.8
25.2
24.7
20.5
21.6
21.7
0.8"
1.1"
1.0"
49.1
44.2
27.1
20.3
18.2
8.2
8.7
8.0
6.0
7.3
6.6
4.1
16.8
15.4
7.1
15.5
12.7
8.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
9 years and under
19 years and under
704
969
732
9,309
11,287
64.9
62.1
45.6
68.3
57.8
27.9
27.7
22.4
25.2
24.8
22.3
21.5
18.1
19.8
20.1
1.5"
1.1"
1.1"
Males
2.5
1.8
50.4
47.2
30.2
and Females
58.0
44.4
17.3
16.2
8.2
20.9
15.2
8.8
7.3
4.4
14.0
9.7
7.4
7.4
6.0
7.1
6.2
20.4
19.0
11.3
20.6
15.5
17.3
14.9
9.7
26.7
17.9
* Estimate is not statistically reliable due to small samples size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
1 f
a^ f
I £
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I
Table 9-11. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (g
Food category
2 to 5 years
6 to 1 1 years
Male and Female Male and Female
(N = 2,109) (N= 1,432)
PC
Mean.
SEM PC
Mean
SEM
PC
rams)
12 to 19 years
Male
(N = 696)
Mean
SEM
Female
(N = 702)
PC
Mean
SEM
Raw Vegetables
Carrots
Cucumbers
Lettuce
Onions
Tomatoes
10.4
6.4
34.0
3.9
14.8
27
32
17
9
31
2 17.8
4 6.6
1 40.8
2 4.5
2 14.0
32
39
26
17
42
2
6
1
2
4
9.2
6.1
56.0
11.1
25.7
35
71a
32
28
49
6
22"
3
4
5
11.9
6.8
52.3
7.9
23.9
32
48
34
23
44
4
11
2
4
3
Cooked Vegetables
Beans (string) 16.8
Broccoli 7.2
Carrots 6.0
Corn 18.9
Peas 8.4
Potatoes (French-fried) 32.7
Potatoes (home-fried and hash-browned) 9.3
Potatoes (baked) 7.6
Potatoes (boiled) 4.8
Potatoes (mashed) 14.8
50
61
48
68
48
52
85
70
81
118
2 12.1
3 5.6
4 3.8
3 22.2
3 6.8
1 33.7
5 10.1
4 8.2
9 2.7
6 13.3
71
102
46
79
72
67
93
95
103"
162
6
16
5
4
9
2
6
6
IT
12
8.3
3.9
2.8
12.8
3.6
41.7
10.1
8.6
2.0
14.6
85
127"
81"
125
115"
97
145
152
250"
245
9
17"
16*
9
15"
3
13
15
40s
16
7.6
5.7
2.1
12.3
2.4
38.1
6.1
8.8
3.2
11.9
78
1091
75"
100
93s
81
138
115
144"
170
5
14"
IT
6
17"
4
13
10
16"
17
Fruits
Apples (raw^
Apples (cooked and applesauce)
Apple juice
Bananas (raw)
Oranges (raw)
Orange juice
26.8
10.1
26.3
25.0
11.1
34.4
106
118
207
95
103
190
2 21.9
5 9.0
5 12.2
2 16.5
5 10.5
4 30.9
123
130
223
105
114
224
1 Indicates a statistic that is potentially unreliable because of small sample size
PC = Percent consuming at least once in 2 days.
SEM = Standard error of the mean.
Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
3
7
10
3
5
6
or large
11.7
2.3
7.8
10.3
4.3
30.8
149
153"
346
122
187"
354
9
19s
22
6
38"
16
12.4
2.6
8.5
8.4
5.4
29.5
129
200"
360
119
109"
305
5
47>
44
5
8"
11
coefficient of variation
s
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-12.
Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition Program
Source: Devaney et al., 2004.
Characteristics of the FITS Sample Population
Sample Size
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
3,022
for Women, Infants, and Children.
Percentage of Sample
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
100.0
Child-Specific Exposure Factors Handbook
September 2008
Page
9-25
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-13. Percentage of Infants and Toddlers Consuming Different Types of Vegetables
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
4 to 6 7 to 8
months months
39.9 66.5
35.7 54.5
5.2 17.4
0.5 1.6
9 to 11
months
72.6
34.4
45.9
5.5
12 to 14
months
76.5
12.7
66.3
7.9
15 to 18
months
79.2
3.0
72.9
14.3
19 to 24
months
81.6
1.6
75.6
18.6
Types of Vegetables'
Dark Green Vegetables'"
Deep Yellow Vegetables0
White Potatoes
French Fries and Other Fried Potatoes
Other Starchy Vegetables'1
Other Vegetables
0.1 2.9
26.5 39.3
3.6 12.4
0.7 2.9
6.5 10.9
11.2 25.9
4.2
29.0
24.1
8.6
16.9
35.1
5.0
24.0
33.2
12.9
17.3
39.1
a Totals include commercial baby food, cooked vegetables, and raw vegetables.
b Reported dark green vegetables include broccoli, spinach and other greens, and romaine lettuce.
0 Reported deep yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
d Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried),
Source: Fox et al., 2004.
10.4
13.6
42.0
19.8
20.8
45.6
cassava,
7.8
13.4
40.6
25.5
24.2
43.3
and rutabaga.
Page
9-26
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
^^f&tC
Table 9-14. Top Five Vegetables Consumed by Infants and Toddlers
Top Vegetables by Age Group" Percentage Consuming at Least Once in a Day
4 to 6 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Peas
9.6
9.1
8.1
7.2
5.0
7 to 8 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Mixed/Garden Vegetables
14.2
12.9
12.9
11.2
10.1
9 to 1 1 months
Cooked Green Beans
Mashed/Whipped Potatoes
French Fries/Other Fried Potatoes
Baby Food Mixed/Garden Vegetables
Cooked Carrots
9.7
9.0
8.6
8.4
8.0
12 to 14 months
Cooked Green Beans
French Fries/Other Fried Potatoes
Cooked Carrots
Mashed/Whipped Potatoes
Cooked Peas
18.2
12.9
11.5
10.3
8.4
15 to 18 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Peas
Cooked Tomatoes/Tomato Sauce
Mashed/Whipped Potatoes
19.8
16.7
13.9
13.7
12.4
19 to 24 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Corn
Cooked Peas
Cooked Tomatoes/Tomato Sauce
25.5
16.8
15.2
11.4
9.4
" Baby food vegetables include single vegetables (majority of vegetables reported) as well as mixtures with the named
vegetables the predominant vegetable, e.g., broccoli and cauliflower or broccoli and carrots.
Source: Fox et al., 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-27
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-15. Percentage of Infants and Toddlers Consuming Different Types of Fruits
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Fruit
Baby Food Fruit
Non-baby Food Fruit
4 to 6 months
41.9
39.1
5.3
7 to 8 months
75.5
67.9
14.3
9 to 11
months
75.8
44.8
44.2
12 to 14
months
77.2
16.2
67.1
15 to 18
months
71.8
4.2
69.4
19 to 24
months
67.3
1.8
66.8
Types of Non-baby Food Fruit
Canned Fruit
Packed in Syrup
Packed in Juice or Water
Unknown Pack
Fresh Fruit
Dried Fruit
1.4
0.7
0.7
0.0
4.4
0.0
5.8
0.7
4.5
0.7
9.5
0.4
21.6
8.1
13.5
1.5
29.5
2.1
31.9
14.9
18.5
1.2
52.1
3.5
25.1
12.7
11.3
3.1
55.0
7.1
20.2
8.1
11.4
1.2
54.6
9.4
Types of Fruit*
Apples
Bananas
Berries
Citrus Fruits
Melons
a Totals include all baby
Source: Fox et al., 2004.
18.6
16.0
0.1
0.2
0.6
food and non-baby
33.1
30.6
0.6
0.4
1.0
food fruits.
31.6
34.5
5.3
1.6
4.4
27.5
37.8
6.6
4.9
7.3
19.8
32.4
11.3
7.3
7.2
22.4
30.0
7.7
5.1
9.6
Page
9-28
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
jflSf
W¥
*jy!j£j\^
Table 9-16. Top Five Fruits Consumed by Infants and Toddlers
Top Fruits by Age Group* Percentage Consuming at Least Once in a Day
4 to 6 months
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
17.5
13.0
7.5
7.4
0.3
7 to 8 months
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
29.0
25.2
18.2
13.1
6.6
9 to 1 1 months
Fresh Banana
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Canned Applesauce
19.0
17.7
16.8
12.4
11.1
12 to 14 months
Fresh Banana
Canned Applesauce
Fresh Grapes
Fresh Apple
Canned Peaches
Canned Fruit Cocktail
33.0
15.2
9.0
8.8
7.2
7.2
15 to 18 Months
Fresh Banana
Fresh Grapes
Fresh Apple
Fresh Strawberries
Canned peaches
30.5
13.2
11.2
10.6
8.9
19 to 24 months
Fresh Banana
Fresh Apple
Fresh Grapes
Raisins
Fresh Strawberries
29.6
15.0
11.2
9.0
7.6
* Baby food fruits include single fruits (majority of fruits reported) as well as mixtures with the named fruit as the
predominant fruit, e.g., pears and raspberries or prunes with pears. Baby food fruits with tapioca and other baby food
dessert fruits were counted as desserts.
Source: Fox et al., 2004.
Child-Specific Exposure Factors Handbook
September 2008
Pagt
9-2<,
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-17. Characteristics of WIC Participants and Non-participants* (Percentages)
Infants 4 to 6 months
Gender
Male
Female
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or
Latino
Child's Race
White
Black
Other
Child In Day Care
Yes
No
Age of Mother
14 to 19
20 to 24
25 to 29
30 to 34
35 or Older
Missing
Mother's Education
11 ""Grade or Less
Completed High School
Some Postsecondary
Completed College
Missing
Parent's Marital Status
Married
Not Married
Missing
WIC
Participant
55
45
20
80
63
15
22
39
61
18
33
29
9
9
2
23
35
33
7
2
49
50
1
Non-participant
54
46
**
11
89
**
84
4
11
38
62
**
1
13
29
33
23
2
**
2
19
26
53
1
**
93
7
1
Infants 7 to 1 1 months
WIC
Participant
55
45
24
76
63
17
20
34
66
13
38
23
15
11
15
42
32
9
2
57
42
1
Non-participant
51
49
**
8
92
**
86
5
9
**
46
54
**
1
11
30
36
21
**
2
20
27
51
0
**
93
7
0
Toddlers 12 to 24 months
WIC
Participant
57
43
22
78
67
13
20
43
57
9
33
29
18
11
o
17
42
31
9
1
58
41
1
Non-participant
52
48
**
10
89
**
84
5
11
*
53
47
**
1
14
26
34
26
**
3
19
28
48
2
**
88
11
1
Page
9-30
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
ri
gt
w
Table 9-17. Characteristics of WIC Participants
Infants 4 to 6 months
WIC
Participant Non-participant
Mother or Female Guardian Works
Yes 46 51
No 53 48
Missing 1 1
Urbanicity **
Urban 34 55
Suburban 36 31
Rural 28 13
Missing 2 1
Sample Size 265 597
(Unweighted)
and Non-participants"
(Percentaj
Infants 7 to 1 1 months
WIC
Participant Non-participant
45
54
1
37
31
30
2
351
**
60
40
0
**
50
34
15
1
808
;es) (continued)
Toddlers 12 to 24 months
WIC
Participant Non-participant
*
55 61
45 38
0
**
35 48
35 35
28 16
2 2
205 791
a X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants for
each of the three age groups. * P<0.05; ** P>0.01; non-participants significantly different from WIC participants on the variable.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-31
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-18. Food Choices for Infants and Toddlers by WIC
Infants 4 to 6 months
WIC
Participant
Non-
participant
Infants 7 to
WIC
Participant
Participation Status
1 1 months
Non-
participant
Toddlers 12 to 24 months
WIC
Participant
Non-
participant
Vegetables
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
Dark Green Vegetables
Deep Yellow Vegetables
Other Starchy Vegetables
Potatoes
40.2
32.9
8.0
1.4
0.4
23.2
6.5
6.0
39.8
37.0
3.9*
0.1**
0.0
28.1
6.4
2.4*
68.2
38.2
33.8
3.6
2.9
30.1
12.9
20.7
70.7
45.0
33.8
4.1
4.0
34.8
15.2
18.2
77.5
4.8
73.1
11.8
6.3
12.5
21.1
43.1
80.2
4.7
72.3
15.4
8.4
16.9
21.5
38.3
Fruits
Any Fruit
Baby Food Fruits
Non-Baby Food Fruit
Fresh Fruit
Canned Fruit
Sample Size (unweighted)
47.8
43.8
8.1
5.4
3.4
265
39.2*
36.9
4.0
3.8
0.5**
597
64.7
48.4
22.9
14.3
10.3
351
81.0**
57.4*
35.9**
24.3**
17.3**
808
58.5
3.8
56.4
43.6
22.3
205
74.6**
6.5
70.9**
57.0**
25.3
791
* = P<0.05 non-participants significantly different from WIC participants.
** = P<0.01 non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al. 2004.
Page
9-32
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-19. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming
Different Types of Fruits and Vegetables on A Given Day
Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic
(n=84)
Non-Hispanic
(n=538)
Hispanic
(n=163)
Non-Hispanic
(n=l,228)
Hispanic
(n=124)
Non-Hispanic
(n=871)
Fruits
Any Fruit or 100%
Any Fruit"
100% Fruit Juice
Fruit Juice
45.0
39.4
19.3
35
28
15
9
8
3
86.2
68.1
57.8
86.8
76.0
47.7
84.6
67.6
64.1
87.2
71.5
58.9
Fruit Preparation
Baby Food Fruit
Non-Baby Food Fruit
Canned Fruit
Fresh Fruit
32.6
9.1T
2.3T
9.1*t
28.4
1.3T
-
-
42.9*
35.8
8.8
30.0**
58.1
27.4
13.7
17.7
5.6T
64.2
12.1**
59.3
6.3
68.0
26.2
53.1
Vegetables
Any Vegetable or 100% Vegetable 30.0 27.3 66.2 70.3 76.0 80.5
Juiceb
Type of Preparation 25.7 25.4 34.4* 47.6 4. It 4.9
Baby Food Vegetables 4.2t 2.4t 33.2 29.4 71.4 72.9
Cooked Vegetables 2.3J - 8-3T 2.6 25.0 13.1
Raw Vegetables
Types of Vegetables'1 - - 3.3t 3.1 11.4t 7.5
Dark Green Vegetables' 21.0 18.2 32.2 25.9 20.0 15.4
Deep Yellow Vegetables'1
Starchy Vegetable: 1.4t 2.3t 20.7 17.4 43.5 39.0
White Potatoes - - 5.?t 5.3 23.4 20.3
French Fries/Fried Potatoes - - 14.4t 10.7 19.8 17.7
Baked/Mashed 5.0t 4.0 6.7** 15.1 16.6 22.2
Other Starchy Vegetables' 8. It 8.0 28.5 29.0 42.0 43.4
Other Non-starchy Vegetables1
* Total includes all baby food and non-baby food fruits and excludes 100% fruit juices and juice drinks.
b Total includes commercial baby food, cooked vegetables, raw vegetables, and 100% vegetable juices.
' Reported dark green vegetables include broccoli, spinach, romaine lettuce and other greens such as kale.
d Reported yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
' Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava, and
rutabaga. Corn is also shown as a subcategory of other starchy vegetables.
f Reported non-starchy vegetables include asparagus, cauliflower, cabbage, onions, green beans, mixed vegetables, peppers, and
tomatoes.
= Less than 1 percent of the group consumed this food on a given day.
* = Significantly different from non-Hispanic at the P<0.05.
** = Significantly different from non-Hispanic at the P>0.01.
t = Statistic is potentially unreliable because of a high coefficient of variation.
Source: Mennella et al., 2006.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-33
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-20. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants
and Toddlers Per Age Group *
Ethnicity
Hispanic
Non-Hispanic
Top Fruits By Age Group
4 to 5 months
6 to 1 1 months
12 to 24 months
Bananas (16.3%)
Apples (14.7%)
Peaches (10.9%)
Melons (3.5%)
Pears (2.5%)
Bananas (35.9%)
Apples (29.7%)
Pears (15.2%)
Peaches (11. 7%)
Melons (4.7%)
Bananas (41.5%)
Apples (25.7%)
Berries (8.5%)
Melons (7.6%)
Pears (7.3%)
Apples (12.5%)
Bananas (10.0%)
Pears (5.9%)
Peaches (5.8%)
Prunes (1.6%)
Apples (32.9%)
Bananas (31. 5%)
Pears (17.5%)
Peaches (13.9%)
Apricots (3.7%)
Bananas (30.9%)
Apples (22.0%)
Grapes (12.3%)
Peaches (9.6%)
Berries (8.7%)
Top Vegetables By Age Group
4 to 5 months
6 to 1 1 months
12 to 24 months
Carrots (9.9%)
Sweet Potatoes (6.8%)
Green Beans (5. 8%)
Peas (5.0%)
Squash (4.3%)
Potatoes (20.7%)
Carrots (19.0%)
Mixed Vegetables (11.1%)
Green Beans (11.0%)
Sweet Potatoes (8.7%)
Potatoes (43.5%)
Tomatoes (23.1%)
Carrots (18.6%)
Onions (11. 8%)
Corn (10.2%)
Sweet Potatoes (7. 5%)
Carrots (6.6%)
Green Beans (5.9%)
Squash (5.4%)
Peas (3.8%)
Carrots (17.5%)
Potatoes (16.4%)
Green Beans (15.9%)
Squash (11. 8%)
Sweet Potatoes (11. 4%)
Potatoes (39.0%)
Green Beans (19.6%)
Peas (12.8%)
Carrots (12.3%)
Tomatoes (11. 9%)
a Percentage consuming at least one in a day is in parentheses.
Source: Mennella, et al., 2006.
Page
9-34
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-21. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study
Food group
JVCICICIILC
4 to 5 months
(N=624)
6 to 8 months
(N=708)
Mean± SEM
9 to 1 1 months
(N=687)
Fruits and Juices
All fruits
Baby food fruit
Baby food peaches
Baby food pears
Baby food bananas
Baby food applesauce
Canned fruit
Fresh fruit
100% juice
Apple/apple blends
Grape
Pear
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
fluid ounce
fluid ounce
fluid ounce
fluid ounce
3.6±0.19
3.3±0.16
3.6±0.37
3.5±0.46
3.4±0.23
3.7±0.29
-
-
2.5±0.17
2.7±0.22
-
-
4.7±0.11
4.6±0.11
4.4±0.26
4.5±0.21
5.0±0.21
4.6±0.17
4.5±0.59
5.3±0.52
2.8±0.11
2.9±0.13
2.6±0.19
2.6±0.29
5.8±0.17
5.6±0.17
5.3±0.36
6.0±0.40
5.9±0.35
5.6±0.25
4.8±0.25
6.4±0.37
3.1±0.09
3.2±0.11
3.1±0.21
3.1±0.28
Vegetables
All vegetables
Baby food vegetables
Baby food green beans
Baby food squash
Baby food sweet
Baby food carrots
Cooked vegetables, excluding french fries
Deep yellow vegetables
Mashed potatoes
Green beans
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
3.8±0.20
4.0±0.20
3.5±0.33
4.3±0.47
4.3±0.31
3.5±0.33
-
-
-
-
5.8±0.16
5.9±0.16
5.1±0.28
5.6±0.30
6.1±0.34
5.6±0.27
4.2±0.47
3.2±0.59
4.1±0.67
3.2±0.62
5.6±0.20
6.6±0.21
6.1±0.50
6.9±0.41
7.2±0.69
6.7±0.48
3.8±0.31
3.2±0.39
2.8±0.37
5.0±0.61
= Cell size was too small to generate a reliable estimate.
N = Number of respondents.
SEM = Standard error.
Source: Fox et al., 2006.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-35
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-22. Average Portion
Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Toddlers from the 2002
Food group
unit
7eeding Infants and Toddlers Study
12 to 14 months
(N=371)
15 to 18 months
(N=312)
Mean± SEM
19 to 24 months
(N=320)
Fruits and Juices
All fruits
Canned fruit
Fresh fruit
Fresh apple
Fresh banana
Fresh grapes
100% juice
Orange/orange blends
Apple/apple blends
Grape
cup
cup
cup
cup, slice
1 medium
cup, slice
1 medium
cup
fluid ounce
fluid ounce
fluid ounce
fluid ounce
0.4±0.02
0.3±0.02
0.4±0.02
0.4±0.05
0.3±0.04
0.4+0.02
0.6±0.03
0.2±0.01
3.7±0.15
3.3+0.38
3.6+0.21
3.6+0.38
0.5+0.03
0.4+0.03
0.5+0.03
0.6+0.07
0.5+0.06
0.5+0.03
0.7+0.03
0.3+0.03
5.0+0.20
4.5+0.33
4.5+0.29
5.6+0.43
0.6+0.03
0.4+0.04
0.6+0.03
0.8+0.14
0.6+0.11
0.5+0.03
0.7+0.04
0.3+0.02
5.1+0.18
5.2+0.35
4.9+0.27
4.7+0.31
Vegetables
All vegetables
Cooked vegetables,
excluding french fries
Deep yellow vegetables
Corn
Peas
Green beans
Mashed potatoes
Baked, boiled potatoes
French fries
cup
cup
cup
cup
cup
cup
cup
cup
cup
0.4+0.02
0.3+0.03
0.2+0.03
0.2+0.03
0.2+0.02
0.4+0.05
0.3+0.05
0.3+0.05
0.4+0.05
0.4+0.03
0.3+0.03
0.3+0.05
0.2+0.03
0.2+0.02
0.4+0.05
0.4+0.05
0.4+0.06
0.6+0.05
0.4+0.02
0.3+0.02
0.3+0.05
0.2+0.03
0.2+0.02
0.3+0.03
0.3+0.05
-
0.6+0.05
Cell size too small to generate reliable estimate.
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.
Page
9-36
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean
Food
Moisture Content of Selected Food Groups
Moisture Content
Raw
Cookec
Expressed as Percentages of Edible Portions
Comments
Fruits
Apples - dried
Apples
Apples - juice
Applesauce
Apricots
Apricots - dried
Bananas
Blackberries
Blueberries
Boysenberries
Cantaloupes
Casabas
Cherries - sweet
Crabapples
Cranberries
Cranberries - juice cocktail
Currants (red and white)
Elderberries
Grapefruit (pink, red and white)
Grapefruit -juice
Grapefruit - unspecified
Grapes - fresh
Grapes -juice
Grapes - raisins
Honeydew melons
Kiwi fruit
Kumquats
Lemons - juice
Lemons - peel
Lemons - pulp
Limes
Limes - juice
Loganberries
Mulberries
Nectarines
Oranges - unspecified
Peaches
Pears - dried
Pears - fresh
Pineapple
Pineapple - juice
31.76
85.56*
86.67**
86.35
30.09
74.91
88.15
84.21
85.90
90.15
91.85
82.25
78.94
87.13
85.00
83.95
79.80
90.89
90.00
90.89
81.30
84.12
15.43
89.82
83.07
80.85
90.73
81.60
88.98
88.26
90.79
84.61*
87.68
87.59
86.75
88.87
26.69
83.71
86.00
84.13*
87.93
88.35*
86.62*
75.56*
86.59*
84.95*
90.10*
92.46*
92.52*
87.49*
64.44*
86.47*
83.51*
86.37
sulfured; * without added sugar
*with skin
** without skin
canned or bottled
*unsweetened
* canned juice pack with skin
sulfured; *without added sugar
*frozen unsweetened
frozen unsweetened
*canned, juice pack
bottled
* canned unsweetened
pink, red, white
American type (slip skin)
canned or bottled
seedless
* canned or bottled
* canned or bottled
*frozen
all varieties
* canned juice pack
sulfured; *without added sugar
* canned juice pack
* canned juice pack
canned
Child-Specific Exposure Factors Handbook
September 2008
Page
9-37
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean Moisture Content
Food
Plums - dried (prunes)
Plums
Quinces
Raspberries
Strawberries
Tangerine - juice
Tangerines
Watermelon
of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Moisture Content
Raw
30.92
87.23
83.80
85.75
90.95
88.90
85.17
91.45
Cooked
84.02*
89.97*
87.00*
89.51*
Comments
* canned juice pack
*frozen unsweetened
* canned sweetened
* canned juice pack
Vegetables
Alfalfa seeds - sprouted
Artichokes - globe & French
Artichokes - Jerusalem
Asparagus
Bamboo shoots
Beans - dry - blackeye peas (cowpeas)
Beans - dry - hyacinth (mature seeds)
Beans - dry - navy (mature seeds)
Beans - dry - pinto (mature seeds)
Beans - lima
Beans - snap - green - yellow
Beets
Beets - tops (greens)
Broccoli
Brussel sprouts
Cabbage - Chinese (pak-choi)
Cabbage - red
Cabbage - savoy
Carrots
Cassava (yucca blanca)
Cauliflower
Celeriac
Celery
Chives
Cole slaw
Collards
Corn - sweet
Cress - garden
Cucumbers - peeled
Dandelion - greens
Eggplant
Endive
Garlic
Kale
Kohlrabi
92.82
84.94
78.01
93.22
91.00
77.20
87.87
79.15
81.30
70.24
90.27
87.58
91.02
90.69
86.00
95.32
90.39
91.00
88.29
59.68
91.91
88.00
95.43
90.65
81.50
90.55
75.96
89.40
96.73
85.60
92.41
93.79
58.58
84.46
91.00
84.08
92.63
95.92
75.48
86.90
76.02
93.39
67.17
89.22
87.06
89.13
89.25
88.90
95.55
90.84
92.00
90.17
93.00
92.30
94.11
91.86
69.57
92.50
89.80
89.67
91.20
90.30
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
Page
9-38
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean Moisture Content
Food
Lambsquarter
Leeks - bulb and lower leaf-portion
Lentils - sprouted
Lettuce - iceberg
Lettuce - cos or romaine
Mung beans - mature seeds (sprouted)
Mushrooms - unspecified
Mushrooms - oyster
Mushrooms - Maitake
Mushrooms - portabella
Mustard greens
Okra
Onions
Onions - dehydrated or dried
Parsley
Parsnips
Peas - edible-podded
Peppers - sweet - green
Peppers - hot chili-green
Potatoes (white)
Pumpkin
Radishes
Rutabagas - unspecified
Salsify (vegetable oyster)
Shallots
Soybeans - mature seeds - sprouted
Spinach
Squash - summer
Squash - winter
Sweet Potatoes
Swiss chard
Taro - leaves
Taro
Tomatoes -juice
Tomatoes - paste
Tomatoes - puree
Tomatoes
Towelgourd
Turnips
Turnips - greens
Water chestnuts - Chinese
Yambean - tuber
of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Moisture Content
Raw
84.30
83.00
67.34
95.64
94.61
90.40
88.80
90.53
91.20
90.80
90.17
89.11
3.93
87.71
79.53
88.89
93.89
87.74
81.58
91.60
95.27
89.66
77.00
79.80
69.05
91.40
94.64
89.76
77.28
92.66
85.66
70.64
93.95
93.85
91.87
89.67
73.46
90.07
Cooked
88.90
90.80
68.70
93.39
91.08
94.46
92.57
87.86
80.24
88.91
91.87
92.50*
75.43
93.69
88.88
81.00
79.45
91.21
93.70
89.02
75.78
92.65
92.15
63.80
93.90
73.50
87.88
84.29
93.60
93.20
86.42*
90.07
Comments
boiled, drained
boiled, drained
stir-fried
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
* canned solids & liquid
baked
boiled, drained
boiled, drained
boiled, drained
steamed
boiled, drained
all varieties; boiled, drained
all varieties; baked
baked in skin
boiled, drained
steamed
canned
canned
canned
boiled, drained
boiled, drained
boiled, drained
* canned solids and liquids
boiled, drained
Source: USDA, 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
9-39
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
APPENDIX 9A
CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS FRUITS AND
VEGETABLES USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
Child-Specific Exposure Factors Handbook
September 2008
Page
9A-1
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data
Food Category
EPA Food Commodity Codes
TOTAL FRUITS AND VEGETABLES
Total Fruits 95000010 Acerola
1 1000090 Apple, dried
11000091 Apple, dried-babyfood
1 1000070 Apple, fruit with peel
1 1000080 Apple, peeled fruit
11000081 Apple, peeled fruit-babyfood
11000110 Apple, sauce
11000111 Apple, sauce-babyfood
12000120 Apricot
12000130 Apricot, dried
12000121 Apricot-babyfood
95000200 Avocado
95000230 Banana
95000240 Banana, dried
95000241 Banana, dried-babyfood
95000231 Banana-babyfood
13010550 Blackberry
13020570 Blueberry
13020571 Blueberry-babyfood
13010580 Boysenberry
95000600 Breadfruit
95000740 Canistel
95000890 Cherimoya
12000900 Cherry
12000901 Cherry-babyfood
10001060 Citrus citron
10001070 Citrus hybrids
95001120 Coconut, dried
95001110 Coconut, meat
9500 1 1 1 1 Coconut, meat-babyfood
95001130 Coconut, milk
11001290 Crabapple
95001300 Cranberry
95001310 Cranberry, dried
95001301 Cranberry-babyfood
13021360 Currant
13021370 Currant, dried
95001410 Date
13011420 Dewberry
08001480 Eggplant
13021490 Elderberry
95001510 Feijoa
95001530 Fig
95001540 Fig, dried
13021740 Gooseberry
95001750 Grape
95001780 Grape, raisin
10001800 Grapefruit
95001830 Guava
95001831 Guava-babyfood
13021910 Huckleberry
95001920 Jaboticaba
95001930 Jackfruit
95001950 Kiwifruit
10001970 Kumquat
10001990 Lemon
10002010 Lemon, peel
10002060 Lime
13012080 Loganberry
95002090 Longan
11002100 Loquat
95002110 Lychee
95002120 Lychee, dried
95002140 Mamey apple
95002150 Mango
95002160 Mango, dried
95002151 Mango-babyfood
95002270 Mulberry
12002300 Nectarine
10002400 Orange
10002420 Orange, peel
95002450 Papaya
95002460 Papaya, dried
95002451 Papaya-babyfood
95002520 Passionfruit
95002521 Passionfruit-babyfood
95002540 Pawpaw
12002600 Peach
12002610 Peach, dried
12002611 Peach, dried-babyfood
12002601 Peach-babyfood
11002660 Pear
11002670 Pear, dried
11002661 Pear-babyfood
95002770 Persimmon
95002790 Pineapple
95002800 Pineapple, dried
95002791 Pineapple-babyfood
95002830 Plantain
95002840 Plantain, dried
12002850 Plum
12002870 Plum, prune, dried
12002871 Plum, prune, dried-babyfood
12002860 Plum, prune, fresh
12002861 Plum, prune, fresh-babyfood
12002851 Plum-babyfood
95002890 Pomegranate
10003070 Pummelo
11003100 Quince
13013200 Raspberry
13013201 Raspberry-babyfood
95003330 Sapote, Mamey
95003460 Soursop
95003510 Spanish lime
Page
9A-2
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Total Fruits
(continued)
Total Vegetables
1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
95003580
95003590
95003591
18000020
04010050
01030150
01030151
95000160
01030170
04010180
95000190
09020210
95000220
19010290
19010291
19010280
19010281
06020330
06030360
06030380
06020370
06030390
06030400
06030410
06030420
06010430
06010431
01010500
01010501
02000510
95000540
05010610
05020630
05010620
05010611
05010640
05010690
05020700
05010720
05010710
95000730
09010750
04020760
01010780
01010781
09010800
01030820
01030821
05010830
01010840
04020850
04020851
04020870
Starfruit
Strawberry
Strawberry-babyfood
Alfalfa, seed
Amaranth, leafy
Arrowroot, flour
Arrowroot, flour-babyfood
Artichoke, globe
Artichoke, Jerusalem
Arugula
Asparagus
Balsam pear
Bamboo, shoots
Basil, dried leaves
Basil, dried leaves-babyfood
Basil, fresh leaves
Basil, fresh leaves-babyfood
Bean, cowpea, succulent
Bean, kidney, seed
Bean, lima, seed
Bean, lima, succulent
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Bean, snap, succulent
Bean, snap, succulent-babyfood
Beet, garden, roots
Beet, garden, roots-babyfood
Beet, garden, tops
Belgium endive
Broccoli
Broccoli raab
Broccoli, Chinese
Broccoli-babyfood
Brussels sprouts
Cabbage
Cabbage, Chinese, bok choy
Cabbage, Chinese, mustard
Cabbage, Chinese, napa
Cactus
Cantaloupe
Cardoon
Carrot
Carrot-babyfood
Casaba
Cassava
Cassava-babyfood
Cauliflower
Celeriac
Celery
Celery-babyfood
Celtuce
95003610
95003680
10003690
09020880
06030990
06030980
06030981
01011000
02001010
09021020
19011030
04011040
19021050
19021051
19011180
19011181
19021190
19021191
04011380
01031390
02001400
19011440
19021430
04021520
03001640
03001650
03001651
01031660
01031670
01031661
01011680
95001770
06031820
06031821
19011840
19011841
05021940
05011960
03001980
19012020
04012040
04012050
19012200
19012201
08002340
03002370
03002380
03002381
03002371
03002390
95002430
19012490
19012491
Sugar apple
Tamarind
Tangerine
Chayote, fruit
Chickpea, flour
Chickpea, seed
Chickpea, seed-babyfood
Chicory, roots
Chicory, tops
Chinese waxgourd
Chive
Chrysanthemum, garland
Cinnamon
Cinnamon-babyfood
Coriander, leaves
Coriander, leaves-babyfood
Coriander, seed
Coriander, seed-babyfood
Dandelion, leaves
Dasheen, conn
Dasheen, leaves
Dill
Dill, seed
Fennel, Florence
Garlic
Garlic, dried
Garlic, dried-babyfood
Ginger
Ginger, dried
Ginger-babyfood
Ginseng, dried
Grape, leaves
Guar, seed
Guar, seed-babyfood
Herbs, other
Herbs, other-babyfood
Kale
Kohlrabi
Leek
Lemongrass
Lettuce, head
Lettuce, leaf
Marjoram
Marj oram-babyfood
Okra
Onion, dry bulb
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, dry bulb-babyfood
Onion, green
Palm heart, leaves
Parsley, dried leaves
Parsley, dried leaves-babyfood
Child-Specific Exposure Factors Handbook
September 2008
Page
9A-3
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Total Vegetables
(continued)
1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
04012480
01012500
01012510
01012511
06032560
06032561
06012570
06032580
06022590
06022550
06022551
08002700
08002710
08002711
08002701
19022740
19022741
08002720
08002730
08002721
95002750
01032960
01032970
01032971
01032980
01032981
01033000
01033001
01032990
01032991
09023080
04013130
01013160
02003170
01013140
02003150
05023180
04023220
Parsley, leaves
Parsley, turnip rooted
Parsnip
Parsnip-babyfood
Pea, dry
Pea, dry-babyfood
Pea, edible podded, succulent
Pea, pigeon, seed
Pea, pigeon, succulent
Pea, succulent
Pea, succulent-babyfood
Pepper, bell
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, bell-babyfood
Pepper, black and white
Pepper, black and white-babyfood
Pepper, nonbell
Pepper, nonbell, dried
Pepper, nonbell-babyfood
Peppermint
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood
Pumpkin
Radicchio
Radish, Oriental, roots
Radish, Oriental, tops
Radish, roots
Radish, tops
Rape greens
Rhubarb
01013270
01013310
02003320
19013340
95003351
03003380
06003480
06003481
06003470
19023540
19023541
09023560
09023561
09023570
09023571
01033660
01033661
04023670
01033710
08003740
08003750
08003780
08003781
08003760
08003761
08003770
08003771
95003800
08003751
01033870
05023890
01013880
95003970
95003980
09013990
01034070
01034060
Rutabaga
Salsify, roots
Salsify, tops
Savory 95003350 Seaweed
Seaweed-babyfood
Shallot
Soybean, flour
Soybean, flour-babyfood
Soybean, seed
Spices, other
Spices, other-babyfood
Squash, summer
Squash, summer-babyfood
Squash, winter
Squash, winter-babyfood
Sweet potato
Sweet potato-babyfood
Swiss chard
Tanier, corm
Tomatillo
Tomato
Tomato, dried
Tomato, dried-babyfood
Tomato, paste
Tomato, paste-babyfood
Tomato, puree
Tomato, puree-babyfood
Tomato, Tree
Tomato-babyfood
Turmeric
Turnip, greens
Turnip, roots
Water chestnut
Watercress
Watermelon
Yam bean
Yam, true
INDIVIDUAL FRUIT CATEGORIES
Apples
Bananas
11000090
11000091
11000070
11000100
11000101
95000230
95000240
95000241
95000231
Apple, dried
Apple, dried-babyfood
Apple, fruit with peel
Apple, juice
Apple, juice-babyfood
Banana
Banana, dried
Banana, dried-babyfood
Banana-babyfood
11000080
11000081
11000110
11000111
95002830
95002840
Apple, peeled fruit
Apple, peeled fruit-babyfood
Apple, sauce
Apple, sauce-babyfood
Plantain
Plantain, dried
Page
9A-4
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued)
Food Category
Berries and Small
Fruits
Citrus Fruits
Peaches
Pears
Pome Fruits
Strawberries
Stone Fruits
EPA Food Commodity Codes
13010550
13010580
13011420
13012080
13013200
13013201
13020570
13020571
13021360
13021370
13021490
13021740
10001060
10001070
10001800
10001970
10001990
10002010
12002600
12002610
12002611
12002601
11002660
11002670
11002680
11002681
11002661
11000070
11000080
11000081
11000090
11000091
11000110
11000111
95003590
95003591
12000120
12000121
12000130
12000900
12000901
12002300
12002600
12002601
12002610
Blackberry
Boysenberry
Dewberry
Loganberry
Raspberry
Raspberry-babyfood
Blueberry
Blueberry-babyfood
Currant
Currant, dried
Elderberry
Gooseberry
Citrus citron
Citrus hybrids
Grapefruit
Kumquat
Lemon
Lemon, peel
Peach
Peach, dried
Peach, dried-babyfood
Peach-babyfood
Pear
Pear, dried
Pear, juice
Pear, juice-babyfood
Pear-babyfood
Apple, fruit with peel
Apple, peeled fruit
Apple, peeled fruit-babyfood
Apple, dried
Apple, dried-babyfood
Apple, sauce
Apple, sauce-babyfood
Strawberry
Strawberry-babyfood
Apricot
Apricot-babyfood
Apricot, dried
Cherry
Cherry-babyfood
Nectarine
Peach
Peach-babyfood
Peach, dried
13021910
95001300
95001301
95001310
95001750
95001770
95001780
95001950
95002270
95003590
95003591
10002060
10002400
10002420
10003070
10003690
11001290
11002100
11002660
11002661
11002670
11003100
12002611
12002850
12002851
12002860
12002861
12002870
12002871
Huckleberry
Cranberry
Cranberry-babyfood
Cranberry, dried
Grape
Grape, leaves
Grape, raisin
Kiwifruit
Mulberry
Strawberry
Strawberry-babyfood
Lime
Orange
Orange, peel
Pummelo
Tangerine
Crabapple
Loquat
Pear
Pear-babyfood
Pear, dried
Quince
Peach, dried-babyfood
Plum
Plum-babyfood
Plum, prune, fresh
Plum, prune, fresh-babyfood
Plum, prune, dried
Plum, prune, dried-babyfood
Child-Specific Exposure Factors Handbook
September 2008
Page
9A-5
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in
Food Category
Tropical Fruits
Analysis of the 1994-96, 1998 USDACSFII Data (continued)
EPA Food Commodity Codes
95000010
95000220
95000230
95000231
95000240
95000241
95000600
95000740
95000890
95001110
95001111
95001120
95001130
95001410
95001510
95001530
95001540
95001830
95001831
95001930
95002090
95002110
95002120
Acerola
Avocado
Banana
Banana-babyfood
Banana, dried
Banana, dried-babyfood
Breadfruit
Canistel
Cherimoya
Coconut, meat
Coconut, meat-babyfood
Coconut, dried
Coconut, milk
Date
Feijoa
Fig
Fig, dried
Guava
Guava-babyfood
Jackfruit
Longan
Lychee
Lychee, dried
95002140
95002150
95002151
95002160
95002450
95002451
95002460
95002520
95002521
95002540
95002790
95002791
95002800
95002830
95002840
95002890
95003330
95003460
95003510
95003580
95003610
95003680
Mamey apple
Mango
Mango-babyfood
Mango, dried
Papaya
Papaya-babyfood
Papaya, dried
Passionfruit
Passionfruit-babyfood
Pawpaw
Pineapple
Pineapple-babyfood
Pineapple, dried
Plantain
Plantain, dried
Pomegranate
Sapote, Mamey
Soursop
Spanish lime
Starfruit
Sugar apple
Tamarind
INDIVIDUAL VEGETABLE CATEGORIES
Asparagus
Beans
Beets
Broccoli
Bulb Vegetables
Cabbage
95000190
06030350
06030300
06030320
06020310
06030340
06020330
06030360
06030380
01010500
01010501
02000510
05010610
05010611
03001640
03001650
03001651
03001980
03002370
05010690
05010720
05010710
Asparagus
Bean, great northern, seed
Bean, black, seed
Bean, broad, seed
Bean, broad, succulent
Bean, cowpea, seed
Bean, cowpea, succulent
Bean, kidney, seed
Bean, lima, seed
Beet, garden, roots
06020370
06030390
06030400
06030410
06030420
06010430
06010431
Bean, lima, succulent
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Bean, snap, succulent
Bean, snap, succulent-babyfood
Beet, garden, roots-babyfood
Beet, garden, tops
Broccoli
Broccoli-babyfood
Garlic
Garlic, dried
Garlic, dried-babyfood
Leek
Onion, dry bulb
Cabbage
Cabbage, Chinese, mustard
Cabbage, Chinese, napa
03002371
03002380
03002381
03002390
03003380
Onion, dry bulb-babyfood
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, green
Shallot
Page
9A-6
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued)
Food Category
Carrots
Corn
Cucumbers
Cucurbit
Vegetables
Fruiting Vegetables
Leafy Vegetables
(Brassica and
Nonbrassica)
EPA Food Commodity Codes
01010780
15001220
15001200
15001201
15001210
15001211
15001230
09021350
09010750
09010800
09011870
09013990
09020210
09020880
09021020
08001480
08002340
08002700
08002701
08002710
08002711
08002720
08002721
08002730
08003740
02000510
02001010
02001400
02003150
02003170
02003320
04010050
04010180
04011040
04011330
04011340
04011380
04011500
04012040
04012050
04012480
04013130
04013550
04013551
04020760
04020850
04020851
04020870
Carrot
Corn, field, bran
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, starch
Cucumber
Cantaloupe
Casaba
Honeydew melon
Watermelon
Balsam pear
Chayote, fruit
Chinese waxgourd
Eggplant
Okra
Pepper, bell
Pepper, bell-babyfood
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, nonbell
Pepper, nonbell-babyfood
Pepper, nonbell, dried
Tomatillo
Beet, garden, tops
Chicory, tops
Dasheen, leaves
Radish, tops
Radish, Oriental, tops
Salsify, tops
Amaranth, leafy
Arugula
Chrysanthemum, garland
Cress, garden
Cress, upland
Dandelion, leaves
Endive
Lettuce, head
Lettuce, leaf
Parsley, leaves
Radicchio
Spinach
Spinach-babyfood
Cardoon
Celery
Celery-babyfood
Celtuce
15001231
15001260
15001270
15001271
09021350
09023080
09023090
09023560
09023561
09023570
09023571
08003750
08003751
08003760
08003761
08003770
08003771
08003780
08003781
04021520
04023220
04023670
05010610
05010611
05010620
05010640
05010690
05010710
05010720
05010830
05011960
05020630
05020700
05021170
05021940
05022290
05023180
05023890
95000540
95003350
95003351
95003980
Corn, field, starch-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood
Cucumber
Pumpkin
Pumpkin, seed
Squash, summer
Squash, summer-babyfood
Squash, winter
Squash, winter-babyfood
Tomato
Tomato-babyfood
Tomato, paste
Tomato, paste-babyfood
Tomato, puree
Tomato, puree-babyfood
Tomato, dried
Tomato, dried-babyfood
Fennel, Florence
Rhubarb
Swiss chard
Broccoli
Broccoli-babyfood
Broccoli, Chinese
Brussels sprouts
Cabbage
Cabbage, Chinese, napa
Cabbage, Chinese, mustard
Cauliflower
Kohlrabi
Broccoli raab
Cabbage, Chinese, bok choy
Collards
Kale
Mustard greens
Rape greens
Turnip, greens
Belgium endive
Seaweed
Seaweed - babyfood
Watercress
Child-Specific Exposure Factors Handbook
September 2008
Page
9A-7
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Legume Vegetables
Lettuce
Okra
Onions
Peas
Peppers
Pumpkin
1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
06003470
06003480
06003481
06003490
06003491
06010430
06010431
06012570
06020310
06020330
06020370
06022550
06022551
06022590
06030300
06030320
04012040
04012050
08002340
03002370
03002380
03002381
03002371
03002390
06032560
06032561
06012570
06032580
06022590
08002700
08002710
08002711
08002701
08002720
09023080
09023090
Soybean, seed
Soybean, flour
Soybean, flour-babyfood
Soybean, soy milk
Soybean, soy milk-babyfood or infant
formula
Bean, snap, succulent
Bean, snap, succulent-babyfood
Pea, edible podded, succulent
Bean, broad, succulent
Bean, cowpea, succulent
Bean, lima, succulent
Pea, succulent
Pea, succulent-babyfood
Pea, pigeon, succulent
Bean, black, seed
Bean, broad, seed
Lettuce, head
Lettuce, leaf
Okra
Onion, dry bulb
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, dry bulb-babyfood
Onion, green
Pea, dry
Pea, dry-babyfood
Pea, edible podded, succulent
Pea, pigeon, seed
Pea, pigeon, succulent
Pepper, bell
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, bell-babyfood
Pepper, nonbell
Pumpkin
Pumpkin, seed
06030340
06030350
06030360
06030380
06030390
06030400
06030410
06030420
06030980
06030981
06030990
06031820
06031821
06032030
06032560
06032561
06032580
06022550
06022551
08002730
08002721
Bean, cowpea, seed
Bean, great northern, seed
Bean, kidney, seed
Bean, lima, seed
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Chickpea, seed
Chickpea, seed-babyfood
Chickpea, flour
Guar, seed
Guar, seed-babyfood
Lentil, seed
Pea, dry
Pea, dry-babyfood
Pea, pigeon, seed
Pea, succulent
Pea, succulent-babyfood
Pepper, nonbell, dried
Pepper, nonbell-babyfood
Page
9A-8
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Root and Tuber
Vegetables
Stalk and Stem
Vegetable and
Edible Fungi
Tomatoes
White Potatoes
1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
01030150
01030151
01030170
01010500
01010501
02000510
01010520
01010521
01010670
01010780
01010781
01030820
01030821
01010840
01011000
01031390
01031660
01031670
01031661
01011680
01011900
01012500
95000160
95000190
95000220
95002280
95002430
08003750
08003780
08003781
08003760
08003761
01032960
01032970
01032971
01032980
01032981
Arrowroot, flour
Arrowroot, flour-babyfood
Artichoke, Jerusalem
Beet, garden, roots
Beet, garden, roots-babyfood
Beet, garden, tops
Beet, sugar
Beet, sugar-babyfood
Burdock
Carrot
Carrot-babyfood
Cassava
Cassava-babyfood
Celeriac
Chicory, roots
Dasheen, conn
Ginger
Ginger, dried
Ginger-babyfood
Ginseng, dried
Horseradish
Parsley, turnip rooted
Artichoke, globe
Asparagus
Bamboo, shoots
Mushroom
Palm heart, leaves
Tomato
Tomato, dried
Tomato, dried-babyfood
Tomato, paste
Tomato, paste-babyfood
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
01012510
01012511
01032960
01032970
01032971
01032980
01032981
01033000
01033001
01032990
01032991
01013160
01013140
01013270
01033660
01033661
01033710
01033870
01013880
95003970
01034070
01034060
08003770
08003771
08003751
01033000
01033001
01032990
01032991
Parsnip
Parsnip-babyfood
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood
Radish, Oriental, roots
Radish, roots
Rutabaga
Sweet potato
Sweet potato-babyfood
Tanier, corm
Turmeric
Turnip, roots
Water chestnut
Yam bean
Yam, true
Tomato, puree
Tomato, puree-babyfood
Tomato-babyfood
Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
TABLE OF CONTENTS
10 INTAKE OF FISH AND SHELLFISH 10-1
10.1 INTRODUCTION 10-1
10.2 RECOMMENDATIONS 10-2
10.3 GENERAL POPULATION STUDIES 10-6
10.3.1 Key General Population Study 10-6
10.3.1.1 U.S. EPA 2002 10-6
10.3.2 Relevant General Population Studies 10-6
10.3.2.1 U.S. EPA, 1996 10-6
10.3.2.2 Moya et al., 2008 10-7
10.4 MARINE RECREATIONAL STUDIES 10-8
10.4.1 Relevant Marine Recreational Studies 10-8
10.4.1.1 KCA Research Division, 1994 10-8
10.4.1.2 Alcoa, 1998 10-8
10.5 FRESHWATER RECREATIONAL STUDIES 10-9
10.5.1 Relevant Freshwater Recreational Studies 10-9
10.5.1.1 Westetal, 1989 10-9
10.5.1.2 Benson etal, 2001 10-10
10.6 NATIVE AMERICAN STUDIES 10-10
10.6.1 Relevant Native American Studies 10-10
10.6.1.1 Columbia River Inter-Tribal Fish Commission (CRITFC), 1994 10-10
10.6.1.2 Toy etal., 1996 10-12
10.6.1.3 Duncan, 2000 10-13
10.6.1.4 Polissar et al., 2006 10-13
10.7 SERVING SIZE STUDY 10-14
10.7.1 Smiciklas-Wright et al., 2002 10-14
10.8 OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION 10-14
10.8.1 Conversion Between Wet and Dry Weight 10-14
10.8.2 Conversion Between Wet Weight and Lipid Weight Intake Rates 10-15
10.9 REFERENCES FOR CHAPTER 10 10-15
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Chapter 10 - Intake of Fish and Shellfish
LIST OF TABLES
Table 10-1. Recommended Values for General Population Fish Intake 10-4
Table 10-2. Confidence in Recommendations for General Population Fish Intake 10-5
Table 10-3. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, As-Consumed 10-17
Table 10-4. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed 10-17
Table 10-5. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, As-Consumed 10-18
Table 10-6. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed 10-18
Table 10-7. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight 10-19
Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight 10-19
Table 10-9. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight 10-20
Table 10-10. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight 10-20
Table 10-11. Number of General Population Respondents Reporting Consumption of a
Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten 10-21
Table 10-12. Fish Consumption Among General Population Children in Four States,
Consumers Only, g/kg-day As-Consumed 10-22
Table 10-13. Fish Consumption Among General Population in Four States According to Caught or Bought
Status, g/kg-day As-Consumed 10-23
Table 10-14. Fish Consumption Among General Population and Anglers in Three States,
g/kg-day As-Consumed 10-24
Table 10-15. Recreational Fish Consumption in Delaware Consumers Only 10-24
Table 10-16. Consumption of Self-Caught Fish by Recreational Anglers
Lavaca Bay, Texas, g/day 10-25
Table 10-17. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational
Anglers Lavaca Bay, Texas 10-25
Table 10-18. Mean Fish Intake Among Individuals Who Eat Fish and
Reside in Households With Recreational Fish Consumption - Michigan 10-26
Table 10-19. Consumption of Sports-caught and Purchased Fish by Minnesota and North Dakota
Children, Ages 0 to 14 Years (g/day) 10-26
Table 10-20. Fish Consumption Rates among Native American Children (age 5 years and under) 10-27
Table 10-21. Number of Fish Meal Eaten per Month and Fish Intake Among Native American
Children who Consume Particular Species 10-28
Table 10-22. Consumption Rates for Native American Children, Age Birth to Five Years (g/kg-day) 10-29
Table 10-23. Consumption Rates for Native American Children (g/kg-day), All Children
(including non-consumers): Individual Finfish and Shellfish and Fish Groups 10-30
Table 10-24. Consumption Rates for Native American Children (g/kg-day),
Consumers Only: Individual Finfish and Shellfish and Fish Groups 10-31
Table 10-25. Fish Consumption Rates for Tulalip and Squaxin Island Children
Consumers Only (g/kg-day) 10-32
Table 10-26. Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children
Consumers Only (g/kg-day) 10-33
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Chapter 10 - Intake of Fish and Shellfish
Table 10-27. Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion,
by Age and Sex 10-34
Table 10-28. Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion,
by Age and Sex 10-34
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species 10-35
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
10 INTAKE OF FISH AND SHELLFISH
10.1 INTRODUCTION
Contaminated finfish and shellfish are potential
sources of human exposure to toxic chemicals. Pollutants
are carried in the surface waters, but also may be stored
and accumulated in the sediments as a result of complex
physical and chemical processes. Consequently, finfish
and shellfish are exposed to these pollutants and may
become sources of contaminated food. Exposure to some
contaminants may be of concern for children because they
may be less able to metabolize, detoxify, and excrete
these substances (Moya, 2004).
Accurately estimating exposure to a toxic
chemicals among a population that consumes fish from a
polluted water body requires an estimation of intake rates
of the caught fish by both fishermen and their families.
Commercially caught fish are marketed widely, making
the prediction of an individual's consumption from a
particular water body or contaminant source difficult.
Since the catch of recreational and subsistence fishermen
is not "diluted" by fish from other water bodies, these
individuals and their families represent the population that
is most vulnerable to exposure by intake of contaminated
fish from a specific location. This chapter focuses on
intake rates offish. Note that in this section the term fish
refers to both finfish and shellfish. Intake rates for the
general population, and recreational and Native American
fishing populations are addressed, and data are presented
for intake rates for both marine and freshwater fish, when
available.
Survey data on fish consumption have been
collected using a number of different approaches which
need to be considered when interpreting the results.
Typical surveys seek to draw inferences about a larger
population from a smaller sample of that population. This
larger population, from which the survey sample is taken
and to which the results of the survey are generalized, is
denoted the target population of the survey. In order to
generalize from the sample to the target population, the
probability of being sampled must be known for each
member of the target population. This probability is
reflected in weights assigned to survey respondents, with
weights being inversely proportional to sampling
probability. When all members of the target population
have the same probability of being sampled, all weights
can be set to one and essentially ignored. For example, in
a mail or phone study of licensed anglers, the target
population is generally all licensed anglers in a particular
area, and in the studies presented, the sampling
probability is essentially equal for all target population
members. In a creel study (i.e., a study in which
fishermen are interviewed while fishing), the target
population is anyone who fishes at the locations being
studied; generally, in a creel study, the probability of
being sampled is not the same for all members of the
target population. For instance, if the survey is conducted
for one day at a site, then it will include all persons who
fish there daily, but only about 1/7 of the people who fish
there weekly, 1/3 Oth of the people who fish there
monthly, etc. In this example, the probability of being
sampled (or inverse weight) is seen to be proportional to
the frequency of fishing. However, if the survey involves
interviewers revisiting the same site on multiple days, and
persons are only interviewed once for the survey, then the
probability of being in the survey is not proportional to
frequency; in fact, it increases less than proportionally
with frequency. At the extreme of surveying the same site
every day over the survey period with no re-interviewing,
all members of the target population would have the same
probability of being sampled regardless of fishing
frequency, implying that the survey weights should all
equal one. On the other hand, if the survey protocol calls
for individuals to be interviewed each time an interviewer
encounters them (i.e., without regard to whether they were
previously interviewed), then the inverse weights will
again be proportional to fishing frequency, no matter how
many times interviewers revisit the same site. Note that
when individuals can be interviewed multiple times, the
results of each interview are included as separate records
in the data base and the survey weights should be
inversely proportional to the expected number of times
that an individual's interviews are included in the data
base.
The U.S. EPA has prepared a review of and an
evaluation of five different survey methods used for
obtaining fish consumption data. They are:
• Recall-Telephone Survey;
• Recall-Mail Survey;
• Recall-Personal Interview;
• Diary; and
• Creel Census.
The reader is referred to U.S. EPA (1998) Guidance for
Conducting Fish and Wildlife Consumption Surveys for
more detail on these survey methods and their advantages
and limitations. The type of survey used, its design, and
any weighting factors used in estimating consumption
should be considered when interpreting survey data for
exposure assessment purposes. For surveys used in this
handbook, respondents are typically adults who have
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
reported on fish intake for children living in their
households.
The recommendations for fish and shellfish
ingestion rates are provided in the next section, along with
a summary of the confidence ratings for these
recommendations. The recommended values are based on
the key study identified by U.S. EPA for this factor.
Following the recommendations, the studies on fish
ingestion among the general population (Section 10.3),
marine recreational angler households (Section 10.4),
freshwater recreational households (Section 10.5), and
Native American populations (Section 10.6) are
summarized. Information is provided on the key study
that forms the basis for the fish and shellfish intake rate
recommendations. Relevant data on ingestion offish and
shellfish are also provided. These studies are presented to
provide the reader with added perspective on the current
state-of-knowledge pertaining to ingestion of fish and
shellfish among children. Information on serving size
(Section 10.7), and other factors (Section 10.8) are also
presented.
10.2 RECOMMENDATIONS
Considerable variation exists in the mean and
upper percentile fish consumption rates obtained from the
studies presented in this chapter. This can be attributed
largely to the type of water body (i.e., marine, estuarine,
freshwater) and the characteristics of the survey
population (i.e., general population, recreational, Native
American), but other factors such as study design, method
of data collection, and geographic location also play a
role. Based on these study variations, fish consumption
studies were classified into the following categories:
• General Population (total, marine,
freshwater/estuarine);
• • Recreational Marine Intake;
• Recreational Freshwater Intake; and
• Native American Populations
For exposure assessment purposes, the selection of intake
rates for the appropriate category (or categories) will
depend on the exposure scenario being evaluated.
Fish consumption rates are recommended for
various ages of children in the general population, based
on the key study presented in Section 10.3.1. The key
study for estimating mean fish intake among the general
population is the U.S. EPA (2002) analysis of data from
the U.S. Department of Agriculture (USDA) Continuing
Survey of Food Intake among Individuals (CSFII) 1994-
1996, 1998. Per capita and consumer-only values for
children ages 3 to < 6, 6 to <11, 11 to < 16, and 16 to <
18 years, by habitat (i.e., marine, freshwater/estuarine, or
total fish), are shown in Table 10-1. It should be noted,
however, that the key general population study presented
in this chapter pre-dated the age groups recommended by
U.S. EPA in Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005). Thus,
recommended values were not available for children less
than 3 years old or 18 to < 21. The confidence ratings for
the fish intake recommendations for the general
population are presented in Table 10-2. Note that the fish
intake values presented in Table 10-1 are reported as
uncooked fish weights. The CSFII 1994-1996, 1998
recipe files were used to convert, for each fish-containing
food, the as-eaten fish weight consumed into an uncooked
equivalent weight of fish. This is important because the
concentrations of the contaminants in fish are generally
measured in the uncooked samples. Assuming that
cooking results in some reductions in weight (e.g., loss of
moisture), and the mass of the contaminant in the fish
tissue remains constant, then the contaminant
concentration in the cooked fish tissue will increase. In
terms of calculating the dose, actual consumption may be
overestimated when intake is expressed on an uncooked
basis, but the actual concentration may be underestimated
when it is based on the uncooked sample. The net effect
on the dose would depend on the magnitude of the
opposing effects on these two exposure factors. On the
other hand, if the "as-prepared" (i.e., as-consumed) intake
rate and the uncooked concentration are used in the dose
equation, dose may be underestimated since the
concentration in the cooked fish is likely to be higher, if
the mass of the contaminant remains constant after
cooking. Therefore, it is more conservative and
appropriate to use uncooked fish intake rates. If
concentration data can be adjusted to account for changes
after cooking, then the "as-prepared" (i.e., as-consumed)
intake rates are appropriate. However, data on the effects
of cooking on contaminant concentrations are limited and
assessors generally make the conservative assumption that
cooking has no effect on the contaminant mass. Both "as-
prepared" (i.e., as-consumed) and uncooked general
population fish intake values are presented in this
handbook so that the assessor can choose the intake data
that best matches the concentration data that are being
used.
The CSFII data on which the general population
recommendations are based, are short-term survey data
and could not be used to estimate the distribution over the
long term. Also, it is important to note that a limitation
Page
10-2
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
associated with these data is that the total amount of fish
reported by respondents included fish from all sources
(e.g., fresh, frozen, canned, domestic, international
origin). The CSFII surveys did not identify the source of
the fish consumed. This type of information may be
relevant for some assessments. It should also be noted
that because these recommendations are based on 1994-
1996, 1998 CSFII data, they may not reflect any recent
changes that may have occurred in consumption patterns.
Recommended values should be selected that are
relevant to the assessment, choosing the appropriate age
groups and source of fish (i.e., freshwater/estuarine,
marine, and total fish). In some cases a different study or
studies may be particularly relevant to the needs of an
assessment, in which case results from that specific study
or studies may be used instead of the recommended
values provided here. For example, it may be
advantageous to use available regional or site-specific
estimates if the assessment targets a particular region or
site. In addition, seasonal, gender, and fish species
variations should be considered when appropriate, if data
are available.
Recommendations are not provided for recreational
marine fish intake, recreational freshwater fish intake, or
intake among Native American children because the
available data are limited to certain geographic areas
and/or tribes and cannot be readily generalized to the U.S.
population as a whole. However, data from two relevant
recreational marine studies (KCA, 1994 and Alcoa, 1998);
two relevant recreational freshwater studies (West et al,
1989 and Benson et al., 2001); and four Native American
studies (CRITFC, 1994; Toy et al., 1996; Duncan, 2000;
and Polissar et al., 2006) are provided in this chapter.
Assessors may use these data, if appropriate to the
scenarios being assessed. These studies were performed
at various study locations using various age groups of
children.
For recreational marine fish intake, the KCA
(1994) study was conducted in Delaware using the age
groups 0 to 9 years and 10 to 19 years and the Alcoa
(1998) study was conducted in Texas using the age groups
<6 years and 6 to 19 years. Mean recreational marine fish
intake values in the KCA (1994) study were 6 grams/day
and 11.4 grams/day for the 0 to 9 years (N = 73) and 10 to
19 years (N = 102), respectively. The Alcoa (1998) study
provided mean recreational marine intake values for
finfish at 11.4 grams/day for the children <6 years old (N
= 320) and 15.6 grams/day for children 6 to 19 years old
(N = 749). Mean shellfish values were 0.4 grams/day and
0.7 grams/day for the same age groups, respectively.
Readers are referred to the studies provided in Section
10.4 of this chapter to determine if the values presented
are applicable to their specific assessment.
For recreational freshwater fish intake, the West et
al. (1989) study was conducted in Michigan to estimate
intake based on 7-day recall and the frequency of fish
meals over each of the four seasons. Based on a U.S.
EPA analysis of the data, mean recreational freshwater
fish intake rates were 5.6, 7.9, and 7.3 grams/day for
children ages 1 to 5 years (N = 121), 6 to 10 years (N =
151), and 11 to 20 years (N = 349), respectively. Benson
et al. (2001) reported median freshwater sports-caught
fish intake rates of 1.2 and 1.7 grams/day for children,
ages 0 to 14 years, in Minnesota (N = 582) and North
Dakota (N = 343), respectively. Readers are referred to
the studies provided in Section 10.5 of this chapter to
determine if the values presented are applicable to their
specific assessment.
Fish consumption data for Native American
children are very limited, and fish consumption rates,
habits, and patterns can vary among tribes and other sub-
populations. Therefore, fish intake data for a particular
tribe may not be representative of other tribes. Available
data on fish consumption among this population is
presented in Section 10.6. These data should be used, as
appropriate.
Child-Specific Exposure Factors Handbook
September 2008
Page
10-3
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
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Chapter 10 - Intake of Fish and Shellfish
Table 10-2. Confidence in Recommendations for General Population Fish Intake
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (Or Defined) Bias
The survey methodology and the analysis of the survey
data were adequate. Primary data were collected and used
in a secondary analysis of the data. The sample size was
large.
The survey data were based on recent recall. Data were
collected over a short-duration (i.e., 2 days).
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The key study focused the exposure factor of interest.
The survey was conducted nationwide and was
representative of the general U.S. population.
The most current CSFII 1994-96; 98 data were used.
Data were collected for two non-consecutive days.
High
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The primary data are accessible through USDA.
The methodology was clearly presented; enough
information was available to allow for reproduction of the
results.
Quality assurance of CSFII data was good; quality control
of secondary analysis was good.
High
Variability and Uncertainty
Variability in Population
Uncertainty
Full distributions were provided by the key study.
The survey was not designed to capture long-term intake
and was based on recall. Otherwise, the sources of
uncertainty were minimal.
Medium
Evaluation and Review
Peer Review
Number and Agreement of Studies
The primary data were reviewed by USDA; U.S. EPA
review conducted a review of the secondary data analysis
for fish intake.
The number of studies is 1.
Medium
Overall Rating
High (mean)
Medium (upper
percentile)
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Chapter 10 - Intake of Fish and Shellfish
10.3 GENERAL POPULATION STUDIES
10.3.1 Key General Population Study
10.3.1.1 U.S. EPA 2002 - Estimated Per Capita Fish
Consumption in the United States
U.S. EPA's Office of Water used data from the
1994-96 CSFII and its 1998 Children's Supplement
(referred to collectively as CSFII 1994-96, 1998) to
generate fish intake estimates. Participants in the
CSFII 1994-96, 98 provided two non-consecutive days
of dietary data. Respondents estimated the weight of
each food that they consumed. Information on the
consumption of food was classified using 11,345
different food codes, and stored in a database in units of
grams consumed per day. A total of 831 of these food
codes related to fish or shellfish; survey respondents
reported consumption across 665 of these codes. The
fish component (by weight) of the various foods was
calculated using data from the recipe file for release 7
of USDA's Nutrient Data Base for Individual Food
Intake Surveys. The amount of fish consumed by each
individual was then calculated by summing, over all
fish containing foods, the product of the weight of food
consumed and the fish component (i.e., the percentage
fish by weight) of the food. The recipe file also
contains cooking loss factors associated with each food.
These were used to convert, for each fish-containing
food, the as-eaten fish weight consumed into an
uncooked equivalent weight of fish. Analyses of fish
intake were performed on both an "as-prepared" (i.e.,
as-consumed) and uncooked basis.
Each fish-related food code was assigned, by
U.S. EPA, to a habitat category. The habitat categories
included freshwater/estuarine, or marine. Food codes
were also designated as finfish or shellfish. Average
daily individual consumption (g/day) was calculated,
for a given fish type-by-habitat category (e.g., marine
finfish), by summing the amount of fish consumed by
the individual across the two reporting days for all fish-
related food codes in the given fish-by-habitat category
and then dividing by 2. Individual daily fish
consumption (g/day) was calculated similarly except
that total fish consumption was divided by the specific
number of survey days the individual reported
consuming fish; this was calculated for fish consumers
only (i.e., those consuming fish on at least one of the
two survey days). The reported body weight of the
individual was used to convert consumption in g/day to
consumption in g/kg-day.
There were a total of 20,607 respondents in the
combined data set who had two-day dietary intake data.
A total of 7,429 of these individuals were children
between the ages of 3 and 17 years. Data for these
children were used in estimating fish intake in g/day.
Slightly fewer children were used in the fish intake
rates estimated in units of g/kg-day because body
weights were not reported for some individuals. Survey
weights were assigned to this data set to make it
representative of the U.S. population with respect to
various demographic characteristics related to food
intake. These weights were used to project the
estimates for the 7,429 children in the data set to
58,923,560 children in the U.S. population.
U.S. EPA (2002) reported means and estimates
of the 90th, 95th, and 99th percentiles of fish intake.
Tables 10-3 through 10-10 present these statistics for
daily average fish consumption. These data are
presented for selected age groups: 3 to 5, 6 to 10, 11 to
15, and 16 to 17 years of age. Tables 10-3 and 10-4
present per capita fish consumption, on an as-consumed
basis, in g/day and in mg/kg-day, respectively. Tables
10-5 and 10-6 provide consumer-only fish intake data,
on an as-consumed basis, in units of g/day and mg/kg-
day, respectively. Tables 10-7 through 10-10 provide
per capita and consumer only fish intake data (g/day
and mg/kg-day) on an uncooked equivalent basis.
The advantages of this study are that the data
used were from the CSFII survey, which had a large
sample size and was representative of the U.S.
population. The CSFII survey was also designed to
give unbiased estimates of food consumption (U.S.
EPA, 2002). In addition, through use of the USDA
recipe files, the analysis included all fish eaten (i.e.,
both fish eaten alone and in mixtures).
10.3.2 Relevant General Population Studies
10.3.2.1 U.S. EPA, 1996 - National Human Activity
Pattern Survey (NHAPS)
The U. S. EPA (1996) collected information for
the general population on the duration and frequency of
time spent in selected activities and time spent in
selected microenvironments via 24-hour diaries as part
of the National Human Activity Pattern Survey
(NHAPS). Over 9,000 individuals from 48 contiguous
states participated in NHAPS. Approximately 4,700
participants also provided information on seafood
consumption, with 2,980 responding that they ate
seafood (including shellfish, eel, or squid) in the last
month. Over 900 of these participants were children
between the ages of 1 and 17 years. The survey was
conducted between October 1992 and September 1994.
Data were collected on the (1) number of people that
ate seafood in the last month, (2) the number of
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servings of seafood consumed, and (3) whether the
seafood consumed was caught or purchased. The
participant responses were weighted according to
selected demographics such as age, gender, and race to
ensure that results were representative of the U.S.
population. In order to conform to the standardized age
categories used in this handbook, U.S. EPA
subsequently accessed the source data from U.S. EPA
(1996) and recalculated the relevant statistics using the
age categories recommended in Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005). The results of U.S. EPA's analysis are shown in
Table 10-11.
Intake data were not provided in the survey.
However, intake of fish can be estimated using the
information on the number of servings of fish eaten
from this study and serving size data for each age group
from other studies (see Section 10.7.1). Using the
mean value for serving size and the number of servings
per month from Table 10-11, the age-specific amount
of seafood eaten per month can be estimated.
The advantages of NHAPS is that the data
were collected for a large number of individuals and are
representative of the U.S. general population.
However, evaluation of seafood intake was not the
primary purpose of the study and the data do not reflect
the actual amount of seafood that was eaten. However,
using the assumption described above, the estimated
seafood intakes from this study are comparable to those
observed in the U.S. EPA CSFII analysis. It should be
noted that an all inclusive description for seafood was
not presented in U.S. EPA (1996) or in the NHAPS
data. It is not known if processed or canned seafood
and seafood mixtures are included in the seafood
category.
10.3.2.2 Moya et al, 2008 - Estimates of Fish
Consumption Rates for Consumers of
Bought and Sel-caught fish in Connecticut,
Florida, Minnesota, and North Dakota
Moya et al. (2008) analyzed the raw data from
three fish consumption studies to derive fish
consumption rates for various age, gender, and ethnic
groups, and according to the source of fish consumed
(i.e., bought or caught) and habitat (i.e., freshwater,
estuarine, or marine). The studies represented data
from four states: Connecticut, Florida, Minnesota and
North Dakota.
The Connecticut data were collected in
1996/1997 by the University of Connecticut to obtain
estimates of fish consumption for the general
population, sports fishing households, commercial
fishing households, minority and limited income
households, women of child-bearing years, and
children. Data were obtained from 810 households,
representing 2,080 individuals, using a combination of
a mail questionnaire that included a 10-day diary, and
personal interviews. The response rate for this survey
was low (i.e., 6 percent for the general population and
10 percent for anglers), but was considered to be
adequate by the study authors (Balcom et al., 1999).
Data from this survey were available for 54 children,
ages 0 to 15 years.
The Florida data were collected by telephone
and in-person interviews by the University of Florida,
and represented a random sample of 8,000 households
(telephone interviews), and 500 food stamp recipients
(in-person interviews). Data from this survey were
available for 1,160 children, ages 0 to 15 years. The
purpose of the survey was to obtain information on the
quantity of fish and shellfish eaten, as well as the
cooking method used. Additional information of the
Florida survey can be found in Degner et al. (1994).
The Minnesota and North Dakota data were
collected by the University of North Dakota in 2000
and represented 1,572 households and 4,273
individuals. Data from this survey were available for
273 children, ages 0 to 15 years (151 in Minnesota and
122 in North Dakota). Data on purchased and caught
fish were collected for the general population, anglers,
new mothers, and Native American tribes. The survey
also collected information of the species of fish eaten.
Additional information on this study can be found in
Benson et al. (2001).
Moya et al. (2008) utilized the data from these
three studies to generate intake rates for three age
groups of children (i.e., 1 to <6 years, 6 to <11 years,
and 11 to <16 years). These data represented the
general population of children in the four states.
Recreational fish intake rates were not provided for
children, and data were not provided for children
according to the source of intake (i.e., bought or
caught) or habitat (i.e., freshwater, estuarine, or
marine). Tables 10-12 presents the intake rates for the
general population of children who consumed fish and
shellfish in g/kg-day, as-consumed. Table 10-13
provides information on the fish intake among the
sample populations from the four states, based on the
source of the fish (i.e., caught or bought). Table 10-14
provides estimated fish intake rates among the general
populations and angler populations from Connecticut,
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Minnesota, and North Dakota. While the data in Tables
10-13 and 10-14 do not pertain specifically to children,
they provide an indication of the proportion of fish
consumption that is either caught or bought among the
sample population, and similarities and/or differences
between fish intake among the general population and
anglers.
10.4 MARINE RECREATIONAL STUDIES
10.4.1 Relevant Marine Recreational Studies
10.4.1.1 KCA Research Division, 1994 - Fish
Consumption of Delaware Recreational
Fishermen and Their Households
In support of the Delaware Estuary Program,
the State of Delaware's Department of Natural
Resources and Environmental Control conducted a
survey of marine recreational fishermen along the
coastal areas of Delaware between July 1992 and June
1993 (KCA Research Division, 1994). There were two
components of the study. One was a field survey of
fishermen as they returned from their fishing trips and
the second part was a telephone follow-up call. The
purpose of the first component was to obtain
information on their fishing trips and on their household
composition. This information included the method
and location of fishing, number of fish caught and kept
by species, and weight of each fish kept. Household
information included race, age, gender, and number of
persons in the household. Information was also
recorded as to the location of the angler intercept (i.e.,
where the angler was interviewed) and the location of
the household. The purpose of the second component
was to obtain information on the amount of fish caught
and kept from the fishing trip and then eaten by the
household. The methods used for preparing and
cooking the fish were also documented.
The field portion of the study was designed to
interview 2,000 anglers. Data were obtained from
1,901 anglers, representing 6,204 household members
(KCA Research Division, 1994). A total of 1,717 of
these were children between the ages of 0 and 19 years
of age. While the primary goal of the study was to
collect data on marine recreational fishing practices, the
survey included some freshwater fishing and crabbing
sites. Followup phone interviews typically occurred
two weeks after the field interview and were used to
gather information about consumption. Interviewers
aided respondents in their estimation of fish intake by
describing the weight of ordinary products, for the
purpose of comparison to the quantity of fish eaten.
Information on the number of fishing trips a respondent
had taken during the month was used to estimate
average annual consumption rates.
Table 10-15 presents the results of the study
for children who consumed fish (i.e., consumers only).
Children, ages 0 to 9 years old, had a mean fish
consumption rate of 6.0 g/day (N = 73), while children,
ages 10 to 19 years old, had a mean fish consumption
rate of 11.4 g/day (N = 102). More than half of the
study respondents reported that they skinned the fish
that they ate (i.e., 450 out of 807 who reported whether
they skinned their catch); the majority ate filleted fish
(i.e., 617 out of 794 who reported the preparation
method used), and over half fried their fish (i.e., 506
out of 875 who reported the cooking method).
One limitation of this study is that information
on fish consumption by children is based on anglers'
recall of amount of fish eaten. Also, the study was
limited to one geographic area and may not be
representative of the U.S. population.
10.4.1.2 Alcoa, 1998 - Draft Report for the
Finfish/Shellfish Consumption Study Alcoa
(Point Comfort)/Lavaca Bay Superfund Site
The Texas Saltwater Angler Survey was
conducted in 1996/97 to evaluate the quantity and
species of finfish and shellfish consumed by individuals
who fish at Lavaca Bay. The target population for this
study was residents of three Texas counties: Calhoun,
Victoria, and Jackson (over 70 percent of the anglers
who fish Lavaca Bay are from these three counties).
The random sample design specified that the population
percentages for the counties should be as follows: 50
percent from Calhoun, 30 percent from Victoria, and 20
percent from Jackson.
Each individual in the sample population was
sent an introductory note describing the study and then
was contacted by telephone. People who agreed to
participate and had taken fewer than six fishing trips to
Lavaca Bay were interviewed by telephone. Persons
who agreed to participate and had taken more than five
fishing trips to Lavaca Bay were sent a mail survey
with the same questions. A total of 1,979 anglers
participated in this survey, representing a response rate
greater than 68 percent. Data were collected from the
households for men, women, and children. There were
4,489 records with valid information and of those
records, 320 were for small children (less than 6 years
old) and 749 records for youths (6 to 19 years old).
The information collected as part of the survey
included recreational fishing trip information for
November 1996 (i.e., fishing site, site facilities,
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distance traveled, number and species caught), self-
caught fish consumption (by the respondent, spouse and
child, if applicable), opinions on different types of
fishing experiences, and socio-demographics. Portion
size for shellfish was determined by utilizing the
number of shrimp, crabs, oysters, etc. that an individual
consumed during a meal and the assumed tissue weight
of the particular species of shellfish. Red drum was
the most commonly consumed self-caught fish,
followed by speckled sea trout, flounder, all other
finfish and black drum. For shellfish, the order from
highest to lowest amount consumed was oysters, blue
crab, and shrimp.
Table 10-16 presents the mean and upper-
percentile consumption rates of self-caught fish,
expressed as grams per day, for small children (<6
years of age) and youths (ages 6 to 19 years of age).
Small children consumed an average of 11.4 grams of
finfish per day while youths consumed an average of
15.6 grams daily. Small children consumed an average
of 0.4 g/day of shellfish, while youths consumed an
average of 0.7 g/day. Note that these data represent the
amount of self-caught fish that is consumed from all
locations (i.e., not just from Lavaca Bay). Table 10-17
shows the average number of meals consumed by each
age group of children and the average portion size in
grams (converted from ounces) for these meals. Small
children and youths consumed slightly less than three
meals per month of finfish and less than one meal per
month of shellfish. For finfish, youths consumed an
average, per meal, portion size of 187 grams, and small
children consumed less than 128 grams per meal.
Youths consumed an average shellfish portion size of
71 grams per meal, while small children consumed 57
grams per meal.
The study authors noted that since the survey
relied on the anglers' recall of meal frequency and
portion, fish consumption may have been
overestimated. Also, the study was conducted at one
geographic location and may not be representative of
the U.S. population.
10.5 FRESHWATER RECREATIONAL
STUDIES
10.5.1 Relevant Freshwater Recreational Studies
10.5.1.1 West et aL, 1989 - Michigan Sport Anglers
Fish Consumption Survey
The Michigan Sport Anglers Fish
Consumption Survey (West et al, 1989) surveyed a
stratified random sample of Michigan residents with
fishing licences. The sample was divided into 18
cohorts, with one cohort receiving a mail questionnaire
each week between January and May 1989. The survey
included both a short term recall component, and a
usual frequency component. For the short-term recall
component, respondents were asked to identify all
household members and list all fish meals consumed by
each household member during the past seven days.
Information on the source of the fish for each meal was
also requested (self-caught, gift, market, or restaurant).
Respondents were asked to categorize serving size by
comparison with pictures of 8 ounce fish portions;
serving sizes could be designated as either "about the
same size", "less", or "more" than the size pictured.
Data on fish species, locations of self-caught fish and
methods of preparation and cooking were also obtained.
The usual frequency component of the survey
asked about the frequency of fish meals during each of
the four seasons and requested respondents to give the
overall percentage of household fish meals that came
from recreational sources. A sample of 2,600
individuals were selected from state records to receive
survey questionnaires. A total of 2,334 survey
questionnaires were deliverable and 1,104 were
completed and returned, giving a response rate of 47.3
percent.. The responses represented a total of 621
children between the ages of 1 and 20 years.
U.S. EPA obtained the raw data from the West
et al. (1989) survey and analyzed it to estimate mean
fish intake rates for children. Only respondents with
information on both short term and usual intake were
included in this analysis. For the analysis, U.S. EPA
modified the serving size weights used by West et al.
(1989), which were 5, 8 and 10 ounces, respectively,
for portions that were described as less, about the same,
and more than the 8 ounce picture. U.S. EPA examined
the percentiles of the distributions of fish meal sizes
reported in Pao et al. (1982), derived from the 1977-
1978 USDA National Food Consumption Survey
(NCFS), and observed that a lognormal distribution
provided a good visual fit to the percentile data. Using
this lognormal distribution, the mean values for serving
sizes greater than 8 ounces and for serving sizes at least
10 percent greater than 8 ounces were determined. In
both cases, a serving size of 12 ounces was consistent
with the Pao et al. (1982) distribution. The weights
used in the U.S. EPA analysis then were therefore 5, 8,
and 12 ounces for fish meals described as less, about
the same, and more than the 8 ounce picture,
respectively. It should be noted that the mean serving
size from Pao et al. (1982) was about 5 ounces, well
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below the value of 8 ounces most commonly reported
by respondents in the West et al. (1989) survey.
Table 10-18 displays the mean number of total
and recreational fish meals for each household member
between age 1 and 20 years based on the seven day
recall data. Also shown are mean fish intake rates
derived by applying the weights described above to
each fish meal. Intake was calculated in units of both
grams/day and grams/kg body weight/day. This
analysis was restricted to individuals who eat fish and
who reside in households reporting some recreational
fish consumption during the previous year. About 75
percent of the survey respondents (i.e., licensed
anglers) and about 84 percent of the respondents who
fished in the prior year reported some household
recreational fish consumption.
The advantages of this data set and analysis
are that the survey was relatively large and contained
both short-term and usual intake data. The response
rate of this survey, 47 percent, was relatively low and
it was conducted in one geographic location. This
study was conducted in the winter and spring months of
1989. This period does not include the summer months
when peak fishing activity can be anticipated, leading
to the possibility that intake results based on the 7 day
recall data may understate individuals' usual (annual
average) fish consumption.
10.5.1.2 Benson et aL, 2001 - Fish Consumption
Survey: Minnesota and North Dakota
Benson et al (2001) conducted a fish
consumption survey among Minnesota and North
Dakota residents. The target population included the
general population, licensed anglers, and members of
Native American tribes. The survey focused on
obtaining the most recent year's fish intake from all
sources, including locally caught fish. Survey
questionnaires were mailed to potential respondent
households. For the entire population, approximately
1,570 surveys were returned completed (out of 7,835
that were mailed out). Information on fish consumption
by children was collected if they were a part of a
respondent household. Data were collected for a total
of 604 children (ages 0 to 14 years) in Minnesota and a
total of 375 children (ages 0 to 14 years) in North
Dakota. Among these respondents, data on sport-
caught fish intake were available for 582 Minnesota
children and 343 North Dakota children. Table 10-19
presents the recreational freshwater intake rates for
children (ages 0 to 14 years). Rates for both purchased
and sports-caught fish are provided. For Minnesota, the
50th percentile sports-caught fish consumption rate was
1.2 grams/day and the 95th percentile rate was 14.6
grams/day. For North Dakota, the 50th percentile
sports-caught fish consumption rate was 1.7 grams/day,
and the 95th percentile rate was 23.3 grams/day. Intake
rates of purchased fish were higher for both Minnesota
(3.6 grams/day 50th percentile; 30.9 grams/day 95th
percentile) and North Dakota (4.7 grams/day 50th
percentile; 42.8 grasm/day 95th percentile).
An advantage of this study is its large overall
sample size. A limitation of the study is the broad age
range of children used (i.e., 0 to 14 years). Also, the
study was limited to two states. Therefore, the results
may not be representative of the U.S. population as a
whole..
10.6 NATIVE AMERICAN STUDIES
10.6.1 Relevant Native American Studies
10.6.1.1 Columbia River Inter-Tribal Fish
Commission (CRITFC), 1994 - A Fish
Consumption Survey of the Umatilla, Nez
Perce, Yakama, and Warm Springs Tribes of
the Columbia River Basin
The Columbia River Inter-Tribal Fish
Commission (CRITFC) (1994) conducted a fish
consumption survey among four Columbia River Basin
Native American tribes during the fall and winter of
1991-1992. The target population included all adult
tribal members who lived on or near the Yakama,
Warm Springs, Umatilla or Nez Perce reservations.
The survey was based on a stratified random sampling
design where respondents were selected from patient
registration files at the Indian Health Service. The
overall response rate was 69 percent yielding a sample
size of 513 tribal members, 18 years old and above.
Interviews were performed in person at a central
location on the member's reservation. Each
participating adult was asked if there were any children
5 years old or younger in his or her household. Those
responding affirmatively were asked a set of survey
questions about the fish consumption patterns of the
youngest child in the household (CRITFC, 1994).
Information for 204 children, 5 years old and younger,
was provided by participating adult respondents.
Consumption data were available for 194 of these
children.
Participants were asked to describe and
quantify all food and drink consumed during the
previous day. They were then asked to identify the
months in which they ate the most and the least fish,
and the number of fish meals consumed per week
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during each of those periods and an average value for
the whole year. The typical portion size (in ounces)
was determined with the aid of food models provided
by the questioner. The next set of questions identified
specific species of fish and addressed the number of
times per month each was eaten, as well as what parts
(e.g., fillet, skin, head, eggs, bones, other) were eaten.
Respondents were then asked to identify the frequency
with which they used various preparation methods,
expressed as a percentage. Respondents sharing a
household with a child, aged 5 years or less, were asked
to repeat the serving size, eating frequency, and species
questions for the child's consumption behavior. All
respondents were asked about the geographic origin of
any fish they personally caught and consumed, and to
identify the major sources offish in their diet (e.g., self-
caught, grocery store, tribe, etc.). Fish intake rates
were calculated by multiplying the annual frequency of
fish meals by the average serving size per fish meal.
The population sizes of the four tribes were
highly unequal, ranging from 818 to 3,872 individuals
(CRITFC, 1994). In order to ensure an adequate
sample size from each tribe, the study was designed to
give nearly equal sample sizes for each tribe.
Weighting factors were applied to the pooled data (in
proportion to tribal population size) so that the survey
results would be representative of the overall
population of the four tribes for adults only. Because
the sample size for children was considered small, only
an unweighted analysis was performed for this
population. Based on a desired sample size of
approximately 500 and an expected response rate of 70
percent, 744 individuals were selected at random from
lists of eligible patients; the numbers from each tribe
were approximately equal.
Intake rates were calculated for children for
which both the number of fish meals per week and
serving size information were available. A total of 49
percent of respondents of the total survey population
reported that they caught fish from the Columbia River
basin and its tributaries for personal use or for tribal
ceremonies and distributions to other tribe members
and 88 percent reported that they obtained fish from
either self-harvesting, family or friends, at tribal
ceremonies or from tribal distributions. Of all fish
consumed, 41 percent came from self or family
harvesting, 11 percent from the harvest of friends, 35
percent from tribal ceremonies or distribution, 9 percent
from stores and 4 percent from other sources (CRITFC,
1994).
Of the 204 children, the total number of
respondents used in the analysis varied from 167 to
202, depending on the topic (amount and species
consumed, fish meals consumed /week, age
consumption began, serving size, consumption of fish
parts) of the analysis. The unweighted mean for the age
when children begin eating fish was 13.1 months of age
(N = 167). The unweighted mean number of fish meals
consumed per week by children was 1.2 meals per
week (N = 195) and the unweighted mean serving size
of fish for children aged five years old and less was 95
grams (i.e., 3.36 ounces) (N = 201). The unweighted
percent of fish consumed by children by species was
82.7 percent for salmon, followed by 46.5 percent (N =
202) for trout. The analysis of seasonal intake showed
that May and June tended to be high-consumption
months and December and January low consumption
months. Table 10-20 presents the fish intake
distribution for children under 5 years of age (N = 194).
The mean intake rate was 19.6 g/day (N = 194) and the
95th percentile was approximately 70 g/day. These
mean intake rates include both consumers and non-
consumers. These values are based on survey questions
involving estimated behavior throughout the year,
which survey participants answered in terms of meals
per week or per month and typical serving size per
meal. Table 10-21 presents consumption rates for
children who were reported to consume particular
species offish.
The authors noted that some non-response bias
may have occurred in the survey since respondents
were more likely to be female and live near the
reservation than non-respondents. In addition, they
hypothesized that non-consumers may have been more
likely to be non-respondents than fish consumers since
non-consumers may have thought their contribution to
the survey would be meaningless; if such were the case,
this study would overestimate the mean intake rate. It
was also noted that the timing of the survey, which was
conducted during low fish consumption months, may
have led to underestimation of actual fish consumption;
the authors conjectured that an individual may have
reported higher annual consumption if interviewed
during a relatively high consumption month and lower
annual consumption if interviewed during a relatively
low consumption month. Finally, with respect to
children's intake, it was observed that some of the
respondents provided the same information for their
children as for themselves; thereby, the reliability of
some of these data is questioned (CRITFC, 1994). The
combination of four different tribes' survey responses
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into a single pooled data set is somewhat problematic.
The data presented in Table 10-20 are unweighted and
therefore contain a bias toward the smaller tribes, who
were oversampled compared to the larger tribes.
The limitations of this study, particularly with
regard to the estimates of children's consumption, result
in a high degree of uncertainty in the estimated rates of
consumption. However, it is one of a relative few
studies aimed at the fish consumption patterns of
Native Americans. It should be noted that the selection
process for children may be biased because the 204
children included in the study were not selected
independently, but were identified through a parent's
patient registration file. This indicates that children
from larger households would be less likely to be
chosen to participate in the study than would be the
case if the children themselves, rather than the parents,
were randomly selected.
10.6.1.2 Toy et al, 1996 - A Fish Consumption
Survey of the Tulalip and Squaxin Island
Tribes of the Puget Sound Region
Toy et al. (1996) conducted a study to
determine fish and shellfish consumption rates of the
Tulalip and Squaxin Island tribes living in the Puget
Sound region. These two Indian tribes were selected on
the basis of judgment that they would be representative
of the expected range of fishing and fish consumption
activities of the fourteen tribes in the region.
Commercial fishing is a major source of income for
members of both tribes; some members the Squaxin
Island tribe also participate in commercial shellfishing.
Both tribes participate in subsistence fishing and
shellfishing.
Fish consumption patterns for the two tribes
were estimated using a survey in which sample sizes
were calculated separately for each tribe. This allowed
separate analyses to be conducted for each tribe. The
appropriate sample size was calculated based on the
enrolled population of each tribe and a desired
confidence interval of ±20 percent from the mean, with
an additional 25 percent added to the total to allow for
non-response or unusable data. The target population,
derived from lists of enrolled tribal members provided
by the tribes, consisted of enrolled tribal members aged
18 years and older and children aged five years and
younger living in the same household as an enrolled
member. Only members living on or within 50 miles of
the reservation were considered for the survey. Each
eligible enrolled tribal member was assigned a number,
and computer-generated random numbers were used to
identify the survey participants. Children were not
sampled directly, but through adult members of their
household; if one adult had more than one eligible child
in his or her household, one of the children was selected
at random. This indirect sampling method was
necessitated by the available tribal records, but may
have introduced sampling bias to the process of
selecting children for the study. A total of 190 adult
tribal members (ages 18 years old and older) and 69
children between ages birth and 5 years old (i.e., 0 to
<6 years) were surveyed about their consumption of 52
fish species in six categories: anadromous, pelagic,
bottom, shellfish, canned tuna, and miscellaneous.
Respondents described their consumption
behavior for the past year in terms of frequency of fish
meals eaten per week or per month, including seasonal
variations in consumption rates. Portion sizes (in
ounces) were estimated with the aid of model portions
provided by the questioner. Data were also collected
on fish parts consumed, preparation methods, patterns
of acquisition for all fish and shellfish consumption,
and children's consumption rates. Interviews were
conducted between February and May 1994. The
response rate for adults was 77 percent for the Squaxin
Island tribe and 76 percent for the Tulalip tribes.
The mean and median consumption rates for
children 5 years and younger for both tribes combined
were 0.53 and 0.17 g/kg-day, respectively (Table 10-
22). Squaxin Island children tended to consume more
fish than Tulalip children (mean 0.83 g/kg-day vs. 0.24
g/kg-day). The data were insufficient to allow re-
analysis to fit the data to the standard U.S. EPA age
categories used elsewhere in this handbook.
One limitation associated with this study is
that although data from the Tulalip and Squaxin Island
tribes may be representative of consumption rates of
children in these specific tribes, fish consumption rates,
habits, and patterns can vary among tribes and other
sub-populations; as a result, the consumption rates of
these two tribes may not be useful as a surrogate for
consumption rates of other Native American tribes.
Furthermore, there were differences in consumption
patterns between the two tribes included in this study;
the study provided data for each tribe and for the pooled
data from both tribes, but the latter may not be a
statistically valid measure for tribes in the region.
There might also be a possible bias due to the time the
survey was conducted; many species in the survey are
seasonal. For example, because of the timing of the
survey, respondents may have overestimated annual
consumption.
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Chapter 10 - Intake of Fish and Shellfish
10.6.1.3 Duncan, 2000 - Fish Consumption Survey of
the Squamish Indian Tribe of the Port
Madison Indian Reservation, Puget Sound
Region
The Squamish Tribal Council conducted a
study of the Squamish tribal members living on and
near the Port Madison Indian Reservation in the Puget
Sound region (Duncan, 2000). The study was funded
by the Agency for Toxic Substances and Disease
Registry (AT SDR) through a grant to the Washington
State Department of Health. The purpose of the study
was to determine seafood consumption rates, patterns,
and habits of the members of the Squamish Tribe. The
second objective was to identify cultural practices and
attributes that affect consumption rates, patterns and
habits of members of the Squamish Tribe.
A systematic random sample of adults, defined
as individuals age 16 years and older, were selected
from a sorted Tribal enrollment roster. The study had
a participation rate of 64.8 percent, which was
calculated on the basis of 92 respondents out of a total
of 142 potentially eligible adults on the list of those
selected into the sample. Consumption data for
children under six years of age were gathered through
adult respondents who had children in this age group
living in the household at the time of the survey. Data
were collected for 31 children under six years old.
A survey questionnaire was administered by
personal interview. The survey included four parts: (1)
24-hour dietary recall; (2) identification, portions,
frequency of consumption, preparation, harvest location
offish; (3) shellfish consumption, preparation, harvest
location; and (4) changes in consumption over time,
cultural information, physical information, and
socioeconomic information. A display booklet was
used to assist respondents in providing consumption
data and identifying harvest locations of seafood
consumed. Physical models of finfish and shellfish
were constructed to assist respondents in determining
typical food portions. Finfish and shellfish were
grouped into categories based on similarities in life
history as well as practices of Tribal members who fish
for subsistence, ceremonial, and commercial purposes.
Interviewers collected data for 31 children
under six years of age. Table 10-23 provides the
consumption rates for children in units of g/kg-day for
all respondents. Table 10-24 provides consumption
rates for consumers only. Because all of the children
involved in the study consumed some form of fish, the
consumption distribution of all fish is the same in both
tables. The mean, median, and 95th percentile
consumption rates of all fish were 1.5 g/kg-day, 0.72
g/kg-day, and 7.3 g/kg-day, respectively. These values
are significantly greater than those presented for the
Tulalip and Squaxin Island tribes (Toy et al, 1996; see
Section 10.6.1.2). This disparity illustrates the high
degree of variability found between tribes even within
a small geographic region (Puget Sound) and indicates
that exposure and risk assessors should exercise care
when imputing fish consumption rates to a population
of interest using data from tribal studies.
A limitation of this study is that the sample
size for children was fairly small (31 children). An
important attribute of this survey is that it provided
consumption rates by individual type of fish and
shellfish.
10.6.1.4 Polissar et aL, 2006 - A Fish Consumption
Survey of the Tulalip and Squaxin Island
Tribes of the Puget Sound
Region-Consumption Rates for
Fish-consumers Only
Using fish consumption data from the Toy et
al. (1996) survey of the Tulalip and Squaxin Island
tribes of Puget Sound, Polissar et al. (2006) calculated
consumption rates for various fish species groups,
considering only the consumers of fish within each
group. Weight-adjusted consumption rates were
calculated by tribe, age, gender, and species groups.
Species groups (anadromous, bottom, pelagic, and
shellfish) were defined by life history and distribution
in the water column. Data were available for 69
children, birth to <6 years of age; 18 of these children
had no reported fish consumption and were excluded
from the analysis. Thus, estimated fish consumption
rates are based on data for 51 children; 15 from the
Tulalip tribe and 36 from the Squaxin Island tribe.
Both median and mean fish consumption rates for
children within each tribe were calculated in terms of
grams per kilogram of body weight per day (g/kg-day).
Anadromous fish and shellfish were the groups of fish
most frequently consumed by both tribes and genders.
The consumption rates for groups of fish differed
between the tribes. The distribution of consumption
rates was skewed toward large values. The estimated
mean consumption rate of all fish was 0.45 g/kg-day for
the Tulalip children and 2.9 g/kg-day for the Squaxin
Island children (Table 10-25). Table 10-26 presents
consumption rates for children by species and gender.
Because this study used the data originally
generated by Toy et al. (1996) the advantages and
limitations associated with the Toy et al. (1996) study,
Child-Specific Exposure Factors Handbook
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Chapter 10 - Intake of Fish and Shellfish
as described in Section 10.6.1.2, also apply to this
study. However, an advantage of this study is that the
consumption rates are based only on individuals who
consumed fish within the selected categories.
10.7 SERVING SIZE STUDY
10.7.1 Smiciklas-Wright et al., 2002 - Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating Occasion
and in a Day,1994-1996
Using data gathered in the 1994-96 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of canned tuna and other
finfish consumed per eating occasion by members of
the U.S. population (i.e., serving sizes), over a 2-day
period. The estimates of serving size are based on data
obtained from 14,262 respondents, ages 2 years and
above, who provided 2 days of dietary intake
information. A total of 4,93 9 of these respondents were
children, ages 2 to 19 years of age. Only dietary intake
data from users of the specified food were used in the
analysis (i.e., consumers only data).
Table 10-27 and Table 10-28 present serving
size data for canned tuna and other finfish, respectively.
These data are presented on an as-consumed basis
(grams), and represent the quantity of fish consumed
per eating occasion. These estimates may be useful for
assessing acute exposures to contaminants in specific
foods, or other assessments where the amount
consumed per eating occasion is necessary.
The advantages of using these data are that
they were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
for individual foods consumed as ingredients of mixed
foods. Mixed foods were disaggregated via recipe files
so that the individual ingredients could be grouped
together with similar foods that were reported
separately. Thus, weights of foods consumed as
ingredients were combined with weights of foods
reported separately to provide a more thorough
representation of consumption. However, it should be
noted that since the recipes for the mixed foods
consumed by respondents were not provided by the
respondents, standard recipes were used. As a result,
the estimates of the quantity of some food types are
based on assumptions about the types and quantities of
ingredients consumed as part of mixed foods.
10.8 OTHER FACTORS TO CONSIDER FOR
FISH CONSUMPTION
Other factors to consider when using the
available survey data include location, climate, season,
and ethnicity of the angler or consumer population, as
well as the parts offish consumed and the methods of
preparation. Some contaminants (for example,
persistent, bioaccumulative, aand toxic contaminants
such as dioxins and poly chlorinated biphenyls) have the
affinity to accumulate more in certain tissues, such as
the fatty tissue, as well as in certain internal organs.
The effects of cooking methods for various food
products on the levels of dioxin-like compounds have
been addressed by evaluating a number of studies in
U.S. EPA (2003). These studies showed various results
for contamination losses based on the methodology of
the study and the method of food preparation. The
reader is referred to U.S. EPA (2003) for a detailed
review of these studies. Additionally, users of the data
presented in this chapter should ensure that consistent
units are used for intake rate and concentration of
contaminants in fish. The following sections provide
information on converting between wet weight and dry
weight, and between wet weight and lipid weight.
10.8.1 Conversion Between Wet and Dry Weight
The intake data presented in this chapter is
reported in units of wet weight (i.e., as-consumed or
uncooked weight of fish consumed per day or per
eating occasion). However, data on the concentration
of contaminants in fish may be reported in units of
either wet or dry weight.(e.g., mg contaminant per
gram-dry-weight of fish). It is essential that exposure
assessors be aware of this difference so that they may
ensure consistency between the units used for intake
rates and those used for concentration data (i.e., if the
contaminant concentration is measured in dry weight of
fish, then the dry weight units should be used for fish
intake values).
If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to dry weight intake rates
using the moisture content percentages presented in
Table 10-29 and the following equation:
IRdw ~ IR ww
WO-W
100
(Eqn. 10-1)
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Chapter 10 - Intake of Fish and Shellfish
where:
W
dry weight intake
rate;
wet weight intake
rate; and
percent water
content.
Alternately, dry weight residue levels in fish may be
converted to wet weight residue levels for use with wet
weight (e.g., as-consumed) intake rates, as follows:
9100?
._, _ ._, . 1\J\J .
ww ' dw £ 10Q ?
(Eqn. 10-2)
where:
W
wet weight intake
rate;
dry weight intake
rate; and
percent water
content.
The moisture content data presented in Table 10-29 are
for selected fish taken from USD A, 2007.
10.8.2 Conversion Between Wet Weight and Lipid
Weight Intake Rates
In some cases, the residue levels of
contaminants in fish are reported as the concentration
of contaminant per gram of fat. This may be
particularly true for lipophilic compounds. When using
these residue levels, the assessor should ensure
consistency in the exposure assessment calculations by
using consumption rates that are based on the amount
of fat consumed for the fish product of interest.
If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to lipid weight intake
rates using the fat content percentages presented in
Table 10-29 and the following equation:
IR
Iw
IR
? L ?
where:
IR,,
(Eqn. 10-3)
lipid weight intake
rate;
wet weight intake
rate; and
L = percent lipid (fat)
content.
Alternately, wet weight residue levels in fish may be
estimated by multiplying the levels based on fat by the
fraction of fat per product as follows:
WW
(Eqn. 10-4)
where:
C^ = wet weight intake
rate;
Clw = lipid weight intake
rate; and
L = percent lipid (fat)
content.
The resulting residue levels may then be used in
conjunction with wet weight (e.g., as-consumed)
consumption rates. The total fat content data presented
in Table 10-29 are for selected fish taken from USD A,
2007.
10.9
REFERENCES FOR CHAPTER 10
Alcoa (1998) Draft report for the finfish/shellfish
consumption study Alcoa (Point
Comfort)/Lavaca Bay Superfund Site, Volume
B7b: Bay System Investigation Phase 2. Point
Comfort, TX: Aluminum Company of
America.
Balcom, N.; Capacchione, C.; Hirsch D.W. (1999)
Quantification of seafood consumption rates
for Connecticut. Report prepared for the
Connecticut Department of Environmental
Protection, Office of Long Island Sound
Programs, Hartford, CT. Contract No. CWF-
332-R.
Benson, S.; Crocker, C.; Erjavec, J.; Jensen, R.R.;
Nyberg, C.M.; Wixo, C.Y.; Zola, J.M. (2001)
Fish consumption survey: Minnesota and
North Dakota. Report prepared for the U.S.
Department of Energy by the Energy and
Environmental Research Center, University of
North Dakota, Grand Forks, ND. DOE
Cooperative Agreement No, DE-FC26-
98FT40321.
Child-Specific Exposure Factors Handbook
September 2008
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10-15
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Chapter 10 - Intake of Fish and Shellfish
Columbia River Inter-Tribal Fish Commission
(CRITFC) (1994) A fish consumption survey
of the Umatilla, Nez Perce, Yakama and
Warm Springs tribes of the Columbia River
Basin. Technical Report 94-3. Portland, OR:
CRITFC.
Degner, R.L.; Adams, C.M.; Moss, S.D.; Mack, S.K.
(1994) Per capita fish and shellfish
consumption in Florida. Gainesville, FL:
University of Florida.
Duncan, M. (2000) Fish consumption survey of the
Squamish Indian Tribe of the Port Madison
Indian Reservation, Puget Sound Region.
Squamish, WA: The Squamish Tribe, Port
Madison Indian Reservation.
KCA Research Division (1994) Fish consumption of
Delaware recreational fishermen and their
households. Prepared for the State of
Delaware, Department of Natural Resources
and Environmental Control in support of the
Delaware Estuary Program, Dover, DE.
LSRO (1995) Life Sciences Research Office,
Federation of American Societies for
Experimental Biology Prepared for the
Interagency Board for Nutrition Monitoring
and Related Research. Third Report on
Nutrition Monitoring in the United States:
Volume 1. U.S. Government Printing Office,
Washington, DC.
Moya, J. (2004) Overview offish consumption rates in
the United States. Hum Eco Risk Assess
10:1195-1211.
Moya, J.; Itkm, C.; Selevan, S.G.; Rogers, J.W.;
Clickner, R.P. (2008) Estimates of fish
consumption rates for consumers of bought
and self-caught fish in Connecticut, Florida,
Minnesota, and North Dakota. Sci Tot
Environ (in press).
Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J.
(1982) Foods commonly eaten by individuals:
amount per day and per eating occasion. U.S.
Department of Agriculture. Home Economic
Report No. 44.
Polissar, N.L.; Neradilek, B.; Liao, S.; Toy, K.A.;
Mittelstaedt, G.D. (2006) A fish consumption
survey of the Tulalip and Squaxin Island tribes
of the Puget Sound region - Consumption
rates for fish-consumers only. Report
prepared by Mountain-Whisper-Light
Statistical Consulting, Seattle, WA.
Smiciklas-Wnght, H.; Mitchell, D.C.; Mickle, S.J.;
Cook, A.J.; Goldman, J.D. (2002) Foods
commonly eaten in the United States 1994-
1996: Quantities consumed per eating
occasion and in a day. U.S. Department of
Agriculture. Agricultural Research Center
NFS Report No. 96-5, 264 pp.
Toy, K.A.; Polissar, N.L.; Liao, S.; Mittelstaedt, G.D.
(1996) A fish consumption survey of the
Tulalip and Squaxin Island Tribes of the Puget
Sound Region. Marysville, WA: Tulalip
Tribes, Department of Environment.
USDA, Agricultural Research Service. (2007) USDA
National Nutrient Database for Standard
Reference, Release 20. Nutrient Data
Laboratory Home Page:
http://www.ars.usda. gov/ha/hhnrc/ndl.
U.S. EPA (1996) Descriptive statistics tables from a
detailed analysis of the National Human
Activity Pattern Survey (NHAPS) data.
Washington, DC: Office of Research and
Development. EPA/600/R-96/148.
U.S. EPA (1998) Guidance for conducting fish and
wildlife consumption surveys. Washington,
DC: Office of Water. EPA-823-B-98-007.
U.S. EPA (2002) Estimated Per Capita Fish
Consumption in the United States.
Washington, DC: Office of Water.
EPA/821/C-02/003.
U.S. EPA (2003) Exposure and human health
reassessment of 2,3,7,8-tetrachlorodibenzo-p-
dioxin (TCDD) and related compounds, Part
1: Estimating exposure to dioxin-like
compounds, Volume 2: Properties,
environmental levels, and background
exposures. (National Academy of Sciences
Review Draft). Washington, DC: Office of
Research and Development, National Center
for Environmental Assessment.
www. epa. eov/N CH A/dioxin.
U.S. EPA (2005) Guidance on selecting age groups for
monitoring and assessing childhood exposures
to environmental contaminants. Washington,
DC: U.S. Environmental Protection Agency.
EPA/630/P-03/003F.
West, P.C.; Fly, M.J.; Marans, R.; Larkm, F. (1989)
Michigan sport anglers fish consumption
survey. A report to the Michigan Toxic
Substance Control Commission. Michigan
Department of Management and Budget
Contract No. 87-20141.
Page
10-16
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Chapter 10 - Intake of Fish and Shellfish
Table 10-3. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, As-Consumed
Age (years')
Sample Size
Mean (90% CD
90th % (90% BIV
95th % (90% BIV
99th % (90% BIV
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
1.5(1.2-1.8)
2.1 (1.4-2.9)
3.0(2.2-3.8)
3.4(1.6-5.3)
0.1 (0.0-1.0)
0.0 (0.0-0.6)
1.4(0.5-5.5)
0.0(0.0-1.5)
5.1(4.1-6.2)
5.9(3.2-13)
18(15-21)
13* (5.2-29)
39 (33-44)
61* (51-86)
70* (56-75)
81* (42-117)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
3.7(3.2-4.3)
4.2(3.5-4.9)
5.5 (4.2-6.7)
4.7(2.9-6.4)
11 (10-13)
13 (9.7-17)
14(9.8-21)
0.0 (0.0-6.9)
28 (24-29)
29 (28-34)
39(31-50)
24* (7.8-71)
60 (52-71)
79* (49-84)
102* (84-114)
108* (68-1 19)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,391
1,670
1,005
363
5.2(4.6-5.8)
6.3 (5.3-7.3)
8.5 (6.9-10)
8.1 rs.4-in
19(15-21)
24 (21-27)
28(25-31)
19 r?.0-4n
35(31-40)
40(34-51)
60 (53-74)
74* (29-90)
72(67-81)
108* (92-131)
122* (107-132)
142* (-108-2001
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Table 10-4. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed
Age (years) Sample Size
Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,112
1,553
975
360
83 (67-99)
59 (39-79)
53 (42-64)
49 (23-76)
0 (0-55)
0 (0-5)
27 (0-78)
0 (0-33)
284(240-353)
178 (88-402)
312(253-390)
213* (106-390)
2,317(1,736-2,463)
1,662* (1,433-2,335)
1,237* (950-1,521)
1,186* (600-2,096)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,112
1,553
975
360
209(182-237)
150(123-177)
109(84-133)
75(46-103)
614(525-696)
416 (326-546)
338(179-413)
0(0-124)
1,537(1,340-1,670)
1,055(969-1,275)
821 (629-1,034)
381* (132-951)
3,447 (3,274-3,716)
2,800* (2,021-3,298)
1,902* (1,537-2,366)
1,785* (1,226-2,342)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,112
1,553
975
360
292 (259-326)
209 (176-242)
162(133-191)
124r83-1651
1,057(931-1,232)
780 (644-842)
570 (476-664)
261 n 10-6001
1,988(1,813-2,147)
1,357(1,173-1,452)
1,051 (991-1,313)
1.029* (390-1.239}
4,089 (3,733-4,508)
3,350* (2,725-4,408)
2,305* (1,908-2,767)
2.359* r2.096-2.6761
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Child-Specific Exposure Factors Handbook
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Chapter 10 - Intake of Fish and Shellfish
Table 10-5. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, As-Consumed
Age (years) Sample Size
Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
442
147
107
28
27(23-31)
43 (32-55)
49 (39-59)
76* (59-93)
73 (65-79)
122* (83-187)
127* (104-148)
159* (151-171)
96(87-110)
187* (115-260)
150* (135-193)
168* (159-484)
159* (136-260)
260* (172-261)
307* (193-384)
372* (171-484)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
682
217
122
37
45 (41-48)
59(53-66)
72 (60-85)
97* (65-129)
91 (84-105)
129(112-158)
165* (158-203)
219* (180-238)
119(102-143)
159* (135-219)
204* (169-227)
238* (180-293)
228* (169-293)
243* (219-292)
246* (214-269)
365* (230-428)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Aees 16 to 17
834
270
172
52
50 (46-54)
71 (64-77)
80 (70-89)
104* (75-1331
103(94.5-125)
155(130-183)
167* (154-193)
201* (167-2431
134(121-152)
218* (198-261)
209* (206-257)
242* (216-4841
260* (195-293)
281* (260-292)
285* (264-327)
451* (293-4841
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Table 10-6. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed
Age (vearsl Sample Size
Mean (90% CI1
90th % (90% BI1'
95th % (90% BI1'
99th % (90% BI1'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
416
132
101
28
1,532(1,320-1,743)
1,296(1,004-1,588)
869(725-1,013)
1,063* (781-1,346)
4,307 (3,472-4,624)
3,453* (2,626-4,671)
2,030* (1,628-2,104)
2,293* (2,096-2,577)
5,257(4,926-5,746)
4,675* (3,459-8,816)
3,162* (2,104-3,601)
2,505* (2,096-6,466)
10,644* (9,083-12,735)
8,314* (4,684-9,172)
4,665* (3,597-7,361)
5,067* (2,295-6,466)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
640
203
120
37
2,492 (2,275-2,709)
2,120(1,880-2,361)
1,427(1,203-1,651)
1,534* (1,063-2,004)
5,303 (4,873-5,930)
4,950 (4,043-5,384)
2,971* (2,858-3,741)
3,602* (2,974-4,685)
6,762(6,097-7,168)
5,817* (5,333-6,596)
4,278* (3,026-4,766)
4,475* (3,068-4,685)
11,457* (7,432-14,391)
8,092* (6,146-9,184)
5,214* (4,647-5,646)
4,982* (3,467-5,238)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
779
250
164
52
2,828 (2,608-3,049)
2,375(2,199-2,551)
1,533(1,384-1,682)
1.578* (1.187-1.9691
5,734(5,268-6,706)
5,135(4,684-5,816)
3,207* (2,945-3,485)
3.468* (2.676-4.7521
7,422 (6,907-8,393)
6,561* (5,404-8,816)
3,925* (3,485-4,764)
4.504* (3.709-6.4661
13,829* (11,349-14,391)
9,179* (8,130-10,485)
5,624* (4,764-6,929)
5.738* (4.752-6.4661
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Page
10-18
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-7. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight
Age (years)
Sample Size
Mean (90% CI)
90th (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
2.2(1.8-2.6)
3.0(1.9-4.1)
4.3 (3.2-5.4)
4.6(2.2-6.9)
0.1(0.0-1.5)
0.0(0.0-0.5)
2.3(0.1-7.7)
0.0(0.0-1.9)
12(10-14)
13 (4.8-20)
26 (21-29)
19* (13-37)
52 (46-62)
78* (64- 111)
95* (83-1 10)
109* (58-155)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,391
1,670
1,005
363
5.5 (4.8-6.2)
5.6 (4.6-6.5)
7.6 (5.9-9.4)
6.1(3.7-8.4)
20 (17-23)
19 (14-24)
25 (16-35)
0.0 (0.0-9.3)
39(38-41)
38 (38-42)
56 (45-67)
29* (12-91)
82 (73-95)
100* (63-111)
132* (110-149)
136* (92.0-177)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
4,391
1,670
1,005
363
7.7(6.9-8.6)
8.5(7.1-10)
12(9.7-14)
11 r?.0-141
33 (28-34)
33 (27-38)
43(37-51)
29 (9.4-49)
51 (46-57)
56 (50-70)
87(70-103)
84* (42-114)
101 (89.1-111)
144* (117-183)
171* (148-176.8)
193* (121-266)
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight
Age (years) Sample Size Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,112
1,553
975
360
124(103-146)
84(55-112)
77 (60-94)
65 (30-100)
0 (0-83)
0(0-1)
20(0-116)
0 (0-23)
712(599-784)
354(116-685)
477(411-618)
285* (167-491)
3,091 (2,495-3,475)
2,322* (1,856-2,994)
1,610* (1,358-2,203)
1,542* (760-2,767)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,112
1,553
975
360
309 (270-348)
198(161-235)
153(117-189)
98(58-137)
1,108(984-1,332)
600 (474-733)
481 (361-609)
0(0-177)
2,314(2,096-2,481)
1,481(1,310-1,549)
1,251 (808-1,390)
460* (197-1,079)
4,608(4,301-5,354)
3,684* (2,458-4,353)
2,381* (2,162-3,207)
2,148* (1,648-3,901)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,112
1,553
975
360
433 (385-482)
282(235-328)
231(186-275)
163(108-219}
1,841 (1,555-1,957)
1,045 (745-1,219)
824(657-952)
406 (-145-7561
2,964(2,790-3,194)
1,854(1,638-2,175)
1,531(1,362-1,850)
1.272* r558-1.5001
5,604(5,231-6,135)
4,371* (3,433-5,814)
3,651* (2,745-3,795)
3.544* r2.767-3.9461
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Child-Specific Exposure Factors Handbook
September 2008
Page
10-19
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-9. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight
Age (years)
Sample Size
Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
442
147
107
28
40 (35-46)
61 (44-79)
71 (58-83)
100* (80-121)
95 (86-102)
157* (117-250)
173* (166-196)
203* (197-248)
129(120-142)
248* (150-381)
199* (173-296)
242* (206-643)
205* (200-381)
386* (221-401)
392* (296-5 14)
501* (241-643)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
682
217
122
37
66 (60-71)
78 (67-89)
102(86-118)
126* (80-171)
125(114-150)
150(129-201)
220* (205-265)
281* (241-354)
165(139-190)
202* (165-317)
262. (227-307)
353* (241-390)
316* (227-390)
350* (223-392)
320* (277-379)
530* (291-650)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
834
270
172
52
74 (69-79)
95(85-106)
113.(99-127)
136* (97-174)
149(136-165)
200 (177-235)
227* (205-296)
242* f206-3581
184(172-223)
313* (254-381)
308* (271-348)
357* (266-6431
363* (310-391)
387* (381-401)
380* (353-409)
645* (390-6501
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Table 10-10. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight
Age (years)
Sample
Size
Mean (90%
CI)
90th
% (90%
BI)'
95th
% (90% BI)'
99
111 % (90%
BI)'
Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
416
132
101
28
2,292(2,012-2,572)
1,830(1,416-2,245)
1,273(1,082-1,464)
1,401* (1,058-1,744)
5,852 (4,703-6,068)
4,688* (3,673-5,987)
2,777* (2,091-3,026)
2,971* (2,743-3,692)
7,160(6,950-7,442)
6,207* (4,767-12,926)
4,419* (3,026-5,522)
3,279* (2,767-8,577)
15,600* (11,877-18,670)
12,365* (6,763-12,926)
5,717* (5,457-9,852)
6,819* (3,221-8,577)
Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
640
203
120
37
3,689(3,395-3,982)
2,787(2,417-3,157)
2,020(1,741-2,327)
2,007* (1,302-2,712)
7,253 (6,777-8,504)
5,910(4,813-7,365)
4,224* (3,744-4,781)
4,468* (3,880-7,802)
9,270(8,415-9,991)
8,001* (6,375-8,707)
5,195* (3,859-6,448)
6,537* (3,991-7,802)
16,100* (11,980-17,989)
10,754* (8,707-12,055)
6,839* (6,076-8,970)
7,886* (4,661-7,958)
All Fish
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Aees 16 to 17
779
250
164
52
4,198(3,894-4,502)
3,188(2,923-3,452)
2,199(1,950-2,449)
2.066* fl.529-2.6031
8,061 (7,366-9,223)
6,544(6,013-8,707)
4,387* (3,785-5,522)
3.902* f3.536-7.8921
10,444(9,475-12,261)
8,654* (7,086-11,756)
6,234* (4,420-7,589)
6.594* f4.661-8.5771
17,874* (15,290-18,670)
12,785* (10,930-13,979)
8,345* (6,076-8,970)
8.210* f7.892-8.5771
CI
BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
Source: U.S. EPA, 2002.
Page
10-20
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-11. Number of General Population Respondents Reporting Consumption of a
Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten
Age Group N
(years)
Oto
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
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September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
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Child-Specific Exposure Factors Handbook
September 2008
Page
10-23
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-14. Fish Consumption Among General Population and Anglers in Three States,
g/kg-day As-Consumed
Category
N
Mean
Percentiles
10th
25th
50th
75th
90th
95th
99th
Connecticut
Anglers
General
Population
244
362
0.66
0.48
0.10
0.07
0.20
0.16
0.40
0.32
0.80
0.63
1.6
1.1
2
1
.1
.4
3.5
2.4
Minnesota
Anglers
General Population
1,109
793
0.32
0.33
0.05
0.04
0.10
0.10
0.18
0.20
0.34
0.34
0.67
0.65
0
1
99
.1
2 2
1.8
North Dakota
Anglers
General
N
Source:
Population
808
546
0.34
0.34
0.05
0.05
0.10
0.09
0.20
0.19
0.39
0.35
0.81
0.74
1
1
.2
2
2.0
2 2
= Sample size.
Moyaetal., 2008.
Table 10-15.
Age Group
0 to 9 years
10 to 19 years
1 Converted from ounces/day; 1 ounce =
Source: KCA Research Division, 1994.
Recreational Fish Consumption in Delaware
Consumers Only
Mean consumption
(s/davr
73 6.0
102 11.4
28.35 grams.
Standard Error (%)
13.4
16.8
Page
10-24
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-16
Age Group
Consumption of Self-Caught Fish by Recreational Anglers
Lavaca Bay, Texas, g/day
N Mean
95% Upper Confidence 90th
Limit on Mean
or 95th Percentile of
Distribution1
Finfish
Small children (<6 years)
Youths (6 to 19 years)
320 11.4
749 15.6
14.2
17.8
30.3
45.4
Shellfish
Small children (<6 years)
Youths (6 to 19 years)
320 0.4
749 0.7
0.6
1.0
2.0
4.5
* The 90th percentile values are presented for finfish. For shellfish, the 95th percentile value is provided because
less than 90 percent of the individuals consumed shellfish, resulting in a 90th percentile of zero.
Source: Alcoa, 1998.
Table 10-17. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational Anglers
Lavaca Bay, Texas
Age Group
Number of Meals
95% Upper
Mean Confidence
Limit on Mean
Portion Size
(grams)1
95% Upper
Mean Confidence Limit on
Mean
Finfish
Small children (<6 years)
Youths (6 to 19 years)
2.6 3.1
2.4 2.7
128 133
187 196
Shellfish
Small children (<6 years)
Youths (6 to 19 years)
1 Converted from ounces;
Source: Alcoa, 1998.
0.3 0.5
0.3 0.4
1 ounce =28.35 grams.
57 68
71 82
Child-Specific Exposure Factors Handbook
September 2008
Page
10-25
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-18. Mean Fish Intake Among Individuals Who Eat Fish and
Reside in Households With Recreational Fish Consumption - Michigan
Age Group
N
1 to 5 years 121
6 to 10 years 151
1 1 to 20 years 349
N
Source: U
Meals/Week
All Fish Recreational Fish
0.46 0.22
0.49 0.28
0.41 0.23
Intake
g/day g/kg-day
Total Fish Recreational Fish Total Fish Recreational Fish
11.4 5.6 0.74 0.37
13.6 7.9 0.48 0.28
12.3 7.3 0.22 0.12
Sample size.
S. EPA analysis, using data from West et al., 1989.
Table 10-19. Consumption of Sports-caught and Purchased Fish by
Minnesota and North Dakota Children, Ages 0 to 14 Years (g/day)
Percentile
50th 75th 90th
95th
Minnesota
Sports-caught 1.2 3.3 8.3
Purchased 3.6 8.7 19.2
14.6
30.9
North Dakota
Sports-caught 1.7 5.1 13.1
Purchased 4.7 11.6 26.3
23.3
42.8
Source: Benson etal., 2001.
Page
10-26
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-20. Fish Consumption Rates among Native American Children (age 5 years and under)'
Grams/Day Unweighted Cumulative Percent
0.0 21.1
0.4 21.6
0.8 22.2
1.6 24.7
2.4 25.3
3.2 28.4
4.1 32.0
4.9 33.5
6.5 35.6
8.1 47.4
9.7 48.5
12.2 51.0
13.0 51.5
16.2 72.7
19.4 73.2
20.3 74.2
24.3 76.3
32.4 87.1
48.6 91.2
64.8 94.3
72.9 96.4
81.0 97.4
97.2 98.5
162.0 100
* Sample size = 194; unweighted mean = 19.6 grams/day; unweighted standard error = 1.94.
Note: Data are compiled from the Umatilla, Nez Perce, Yakama, and Warm Springs tribes of the Columbia River Basin.
Source: CRITFC, 1994.
Child-Specific Exposure Factors Handbook Page
September 2008 10-27
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Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-21. Number of Fish Meal Eaten per Month and Fish Intake Among Native American Children who Consume Particular Species
Species
Salmon
Lamprey
Trout
Smelt
Whitefish
Sturgeon
Walleye
Squawfish
Sucker
Shad
SE = Standard error.
Source: CRITFC, 1994.
N
164
37
89
39
21
21
5
2
4
3
Fish Meals/Month
Unweighted Mean
2.3
0.89
0.96
0.40
3.5
0.43
0.22
0.00
0.35
0.10
Unweighted SE
0.16
0.27
0.12
0.09
2.83
0.12
0.20
0.22
0.06
Intake (g/day)
Unweighted Mean Unweighted SE
19
8.1
8.8
3.8
21
4.0
2.0
0.0
2.6
1.1
1.5
2.8
1.4
0.99
16
1.3
1.5
1.7
0.57
Page Child-Specific Exposure Factors Handbook
10-28 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-22. Consumption Rates
Fish Category
Mean (SE)
for Native American Children, Age Birth to Five Years (g/kg-day)
95% CI
50th percentile
90th percentile
Tulalip Tribes (N = 21)
Shellfish
Total finfish
Total, all fish
0.13(0.056)
0.11(0.030)
0.24 (0.077)
(0.014,0.24)
(0.056,0.17)
(0.088,0.39)
0.0
0.060
0.078
0.60
0.29
0.74
Squaxin Island Tribe (N = 48)
Shellfish
Total finfish
Total, all fish
0.23 (0.053)
0.25 (0.063)
0.83(0.14)
(0.13,0.37)
(0.13,0.37)
(0.55,1.1)
0.045
0.061
0.51
0.57
0.83
2.1
Both Tribes Combined (weighted)
Shellfish
Total finfish
Total, all fish
SE = Standard error.
CI = Confidence interval.
N = Sample size.
Source: Toy etal., 1996.
0.18(0.039)
0.18(0.035)
0.53(0.081)
(0.10,0.25)
(0.10,0.25)
(0.37,0.69)
0.012
0.064
0.17
0.57
0.32
1.4
Child-Specific Exposure Factors Handbook
September 2008
Page
10-29
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
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Page
10-30
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-24. Consumption Rates for Native American Children (g/kg-day),
Consumers Only: Individual Finfish and Shellfish and Fish Groups
Group Species
Group E Manila/Littleneck clams
Horse clams
Butter clams
Geoduck
Cockles
Oysters
Mussels
Moon snails
Shrimp
Dungeness crab
Red rock crab
Scallops
Squid
Sea urchin
Sea cucumber
Group A"
Group Bb
Group Cc
Group Dd
Group Fe (tuna/other finfish)
All finfish
All shellfish
All seafood
N Mean
23 0.13
12 0.058
6 0.11
22 0.16
10 0.36
10 0.060
1 0.026
0
17 0.17
21 0.44
5 0.046
8 0.042
2 0.033
0
0
28 0.300
5 0.023
25 0.16
17 0.055
24 0.31
31 0.68
28 0.89
31 1.5
SE
0.068
0.032
0.066
0.054
0.23
0.035
-
-
0.064
0.18
0.011
0.019
0.008
-
0.13
0.012
0.048
0.019
0.092
0.17
0.30
0.35
Median
0.043
0.009
0.032
0.053
0.078
0.015
-
-
0.035
0.082
0.051
0.027
0.033
-
0.11
0.017
0.048
0.033
0.18
0.31
0.36
0.72
Percentiles
75th
0.066
0.046
0.20
0.23
0.29
0.074
-
-
0.30
0.305
0.067
0.032
-
0.25
0.043
0.24
0.064
0.34
0.74
0.85
2.0
90th
0.20
0.31
-
0.55
2 2
0.34
-
-
0.62
2.3
-
-
0.60
0.49
0.14
1.0
2.1
2.5
3.4
" Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead.
b Group B is finfish, including smelt and herring.
0 Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish and greenling.
11 Group D is finfish, including halibut, sole, flounder and rockfish.
" Group F includes tuna, other finfish, and all others not included in Groups A, B, C, and D.
N = Sample size.
SE = Standard error.
= No data.
Source: Duncan, 2000.
Child-Specific Exposure Factors Handbook
September 2008
Page
10-31
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-25. Fish Consumption Rates for Tulalip and Squaxin Island Children
Consumers Only (g/kg-day)
Species"
Percentilesb
N
Mean
SD
10th
25*
50th
75th
90th
95*
Squaxin Island Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
33
21
18
31
30
35
36
0.39
0.16
0.17
2.3
0.58
0.54
2.9
1.3
0.25
0.36
8.6
0.58
1.3
8.4
0.005
0.010
0.006
0.012
0.005
0.012
0.006
0.014
0.006
0.025
0.051
0.007
0.019
0.030
0.019
0.014
0.050
0.11
0.046
0.24
0.049
0.044
0.026
0.26
0.40
0.062
0.70
0.13
0.11
0.050
0.40
0.57
0.22
1.5
0.69
0.55
0.48
0.77
1.6
1.7
2.8
0.79
0.71
4.5
1.6
2.3
7.7
Tulalip Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
14
7
2
11
1
15
15
0.15
0.15
0.044
0.31
0.12
0.31
0.45
0.23
0.18
0.005
0.39
0.12
0.33
0.53
0.012 0.026 0.045
0.027 0.053
0.041
0.012 0.034 0.036
0.027
0.066
0.082
0.088
0.133
0.22
0.14
0.17
0.52
0.43
0.60
0.33
0.80
0.73
0.88
N
SD
Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish,
greenling, herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder,
sturgeon, skate, eel, and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails,
scallops, squid, sea urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus,
abalone, barnacles, and crayfish. Other included canned tuna and trout,
Due to the small sample size for some fish groups, some percentiles could not be computed. A percentile was
only calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a
species group.
= Sample size.
= Standard deviation.
= No data.
Source: Polissar et al.. 2006.
Page
10-32
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-26. Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children
Consumers Only (g/kg-day)
Percentiles
,b
Species1
Gender
N
Mean
SD
10th
25*
50th
75*
90th
95*
Squaxin Island Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
15
18
8
13
6
12
13
18
13
17
15
20
15
21
0.70
0.16
0.10
0.18
0.038
0.24
0.28
3.8
0.84
0.40
0.79
0.37
1.7
3.7
1.9
0.25
0.14
0.28
0.057
0.44
0.24
11.2
0.66
0.46
1.9
0.72
2.0
10.7
0.005
0.008
0.009
0.005
0.015
0.005
0.036
0.008
0.11
0.013
0.009
0.005
0.061
0.014
0.026
0.025
0.015
0.020
0.016
0.010
0.047
0.050
0.23
0.096
0.038
0.037
0.48
0.16
0.062
0.046
0.058
0.040
0.020
0.028
0.24
0.23
0.45
0.31
0.062
0.071
1.2
0.60
0.33
0.090
0.099
0.11
0.026
0.11
0.35
0.49
1.5
0.49
0.52
0.18
1.9
0.92
1.1
0.60
0.68
0.74
0.46
1.3
1.6
0.61
1.5
1.4
2.4
9 8
2.1
16.4
Tulalip Tribe
Anadromous fish
Pelagic fish
Bottom fish
Shellfish
Other fish
All finfish
All fish
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
7
0.061
0.24
0.11
0.27
0.044
0.14
0.43
0.12
0.21
0.43
0.20
0.75
0.052
0.31
0.081
0.35
0.005
0.22
0.46
0.12
0.18
0.44
0.17
0.67
0.023 0.034 0.067
0.032 0.080 0.20
0.044 0.053 0.13
0.017
0.041
0.012 0.027 0.11
0.034 0.22 0.65
0.087
0.045
0.071
0.16
0.13
0.17
0.12
0.49
0.32
0.65
0.23
0.84
N
SD
Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish, greenling,
herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder, sturgeon, skate, eel,
and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails, scallops, squid, sea
urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus, abalone, barnacles, and
crayfish. Other included canned tuna and trout,
Due to the small sample size for some fish groups, some percentiles could not be computed. A percentile was only
calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a species
group.
= Sample size.
= Standard deviation.
= No data.
Source: Polissar et al.. 2006.
Child-Specific Exposure Factors Handbook
September 2008
Page
10-33
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-27. Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion, by Age and Sex
Age (years)- Sex Group
Percentiles
Mean
SE
5th
10th
25th
50th
75th 90th
95th
2 to 5
Male- Female
6 to 11
Male- Female
12 to 19
Male
Female
38
57
84*
64
12*
6
7*
14* 20*
- 18*
14* 18*
15
26
49*
28*
29
49
74
56
55
97*
77*
73
59 99*
162*
105*
85*
157*
156*
SE = Standard error.
* Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation.
Indicates a percentage that could not be estimated.
Source: Smiciklas-Wright et al., 2002 (based on 1994- 1996 CSFII data).
Table 10-28. Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion, by Age and Sex
Age (years)- Sex Group
2 to 5
Male- Female
6 to 11
Male- Female
12 to 19
Male
Female
SE = Standard error.
* Indicates a statistic that
Source: Smiciklas-Wriaht et al.
Percentiles
5th 10th 25th 50th 75th 90th
64 4 8* 16 33 58 77 124
93 8 17* 31* 50 77 119 171*
119* 11* 40* 50* 64* 89 170* 185*
89* 13* 20* 26* 47* 67 124* 164*
is potentially unreliable because of small sample size or large coefficient of variation.
2002 Chased on 1994-1996 CSFII data).
95th
128*
232*
249*
199*
Page
10-34
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species
Species
Moisture Content
<•%•>
Total Fat Content
<•%•>
Comments
FINFISH
Anchovy, European
Bass, Freshwater
Bass, Striped
Bluefish
Burbot
Butterfish
Carp
Catfish, Channel, Farmed
Catfish, Channel, Wild
Cavier, Black and Red
Cisco
Cod, Atlantic
Cod, Pacific
Croaker, Atlantic
Cusk
Dolphinfish
Drum, Freshwater
Eel
Flatfish, Flounder, and Sole
Grouper
Haddock
Halibut, Atlantic and Pacific
Halibut, Greenland
Herring, Atlantic
Herring, Pacific
Ling
73.37
50.30
75.66
68.79
79.22
73.36
70.86
62.64
79.26
73.41
74.13
66.83
76.31
69.63
75.38
71.58
80.36
77.67
47.50
78.93
1.91
81.22
75.61
75.92
16.14
81.28
76.00
78.03
59.76
76.35
69,68
77.55
71.22
77.33
70.94
69.26
59.31
79.06
73.16
79.22
73.36
79.92
74.25
71.48
77.92
71.69
70.27
61.88
72.05
64.16
59.70
55.22
71.52
63.49
79.63
73.88
4.84
9.71
3.69
4,73
2.33
2.99
4.24
5.44
0.81
1.04
8.02
10.28
5.60
7.17
7.59
8.02
2.82
2.85
17.90
69.80
11.90
0.67
0.86
0.86
2.37
0.63
0.81
3.17
12.67
0.69
0.88
0.70
0.90
4.93
6.32
11.66
14.95
1.19
1.53
1.02
1.30
0.72
0.93
0.96
2.29
2.94
13.84
17.74
9.04
11.59
12.37
18.00
13.88
17.79
0.64
0.82
Raw
Canned in oil, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
—
Raw
Smoked
Raw
Canned, solids and liquids
Cooked, dry heat
Dried and salted
Raw
Cooked, dry heat
Raw
Cooked, breaded and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw, mixed species
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Kippered
Pickled
Raw
Cooked, dry heat
Raw
Cooked, drv heat
Child-Specific Exposure Factors Handbook
September 2008
Page
10-35
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Lingcod
Mackerel, Atlantic
Mackerel, Jack
Mackerel, King
Mackerel, Pacific and Jack
Mackerel, Spanish
Milkfish
Monkfish
Mullet, Striped
Ocean Perch, Atlantic
Perch
Pike, Northern
Pike, Walleye
Pollock, Atlantic
Pollock, Walleye
Pompano, Florida
Pout, Ocean
Rockfish, Pacific
Roe
Roughy, Orange
Sablefish
Salmon, Atlantic, Farmed
Salmon, Atlantic, Wild
Salmon, Chinook
Salmon, Chum
Salmon, Coho, Farmed
Salmon, Coho, Wild
Moisture Content
(%)
81.03
75.68
63.55
53.27
69.17
75.85
69.04
70.15
61.73
71.67
68.46
70.85
62.63
83.24
78.51
77.01
70.52
78.70
72.69
79.13
73.25
78.92
72.97
79.31
73.47
78.18
72.03
81.56
74.06
71.12
62.97
81.36
76.10
79.26
73.41
67.73
58.63
75.67
66.97
71.02
62.85
60.14
68.90
64.75
68.50
59.62
71.64
65.60
72.00
75.38
68.44
70.77
70.47
67.00
72.66
71.50
65.39
Total Fat Content
(%)
1.06
1.36
13.89
17.81
6.30
2.00
2.56
7.89
10.12
6.30
6.32
6.73
8.63
1.52
1.95
3.79
4.86
1.63
2.09
0.92
1.18
0.69
0.88
1.22
1.56
0.98
1.26
0.80
1.12
9.47
12.14
0.91
1.17
1.57
2.01
6.42
8.23
0.70
0.90
15.30
19.62
20.14
10.85
12.35
6.34
8.13
10.43
13.38
4.32
3.77
4.83
5.50
7.67
8.23
5.93
4.30
7.50
Comments
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Cooked, moist heat
Page
10-36
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Salmon, Pink
Salmon, Sockeye
Sardine, Atlantic
Sardine, Pacific
Scup
Sea Bass
Seatrout
Shad, American
Shark, mixed species
Sheepshead
Smelt, Rainbow
Snapper
Spot
Sturgeon
Sucker, white
Sunfish, Pumpkinseed
Surimi
Swordfish
Tilapia
Tilefish
Trout, Mixed Species
Trout, Rainbow, Farmed
Trout, Rainbow, Wild
Tuna, Fresh, Bluefin
Tuna, Fresh, Skipjack
Tuna, Fresh, Yellowfin
Tuna, Light
Tuna, White
Moisture Content
<•%•>
76.35
69.68
68.81
70.24
61.84
67.51
59.61
66.65
75.37
68.42
78.27
72.14
78.09
71.91
68.19
59.22
73.58
60.09
77.97
69.04
78.77
72.79
76.87
70.35
75.95
69.17
76.55
69.94
62.50
79.71
73.99
79.50
73.72
76.34
75.62
68.75
78.08
71.59
78.90
70.24
71.42
63.36
72.73
67.53
71.87
70.50
68.09
59.09
70.58
62.28
70.99
62.81
59.83
74.51
64.02
73.19
Total Fat Content
<•%•>
3.45
4.42
6.05
8.56
10.97
7.31
11.45
10.46
2.73
3.50
2.00
2.56
3.61
4.63
13.77
17.65
4.51
13.82
2.41
1.63
2.42
3.10
1.34
1.72
4.90
6.28
4.04
5.18
4.40
2.32
2.97
0.70
0.90
0.90
4.01
5.14
1.70
2.65
2.31
4.69
6.61
8.47
5.40
7.20
3.46
5.82
4.90
6.28
1.01
1.29
0.95
1.22
8.21
0.82
8.08
2.97
Comments
Raw
Cooked, dry heat
Canned, solids with bone and liquid
Raw
Cooked, dry heat
Canned, drained solids with bone
Canned in oil, drained solids with bone
Canned in tomato sauce, drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, batter-dipped and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
-
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned in oil, drained solids
Canned in water, drained solids
Canned in oil, drained solids
Canned in water drained solids
Child-Specific Exposure Factors Handbook
September 2008
Page
10-37
-------
Child-Specific Exposure Factors Handbook
Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Turbot, European
Whitefish, mixed species
Whiting, mixed species
Wolffish, Atlantic
Yellowtail, mixed species
Moisture Content
<•%•>
76.95
70.45
72.77
65.09
70.83
80.27
74.71
79.90
74.23
74.52
67.33
Total Fat Content
<•%•>
2.95
3.78
5.86
7.51
0.93
1.31
1.69
2.39
3.06
5.24
6.72
Comments
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
SHELLFISH
Ab alone
Clam
Crab, Alaska King
Crab, Blue
Crab, Dungeness
Crab, Queen
Crayfish, Farmed
Crayfish, Wild
Cuttlefish
Lobster, Northern
Lobster, Spiny
Mussel, Blue
Octopus
Oyster, Eastern
74.56
60.10
81.82
63.64
97.70
61.55
63.64
79.57
77.55
74.66
79.02
79.16
77.43
71.00
79.18
73.31
80.58
75.10
84.05
80.80
82.24
79.37
80.56
61.12
76.76
76.03
74.07
66.76
80.58
61.15
80.25
60.50
86.20
85.16
85.14
64.72
81.95
83.30
70.32
0.76
6.78
0.97
1.95
0.02
11.15
1.95
0.60
1.54
0.46
1.08
1.23
1.77
7.52
0.97
1.24
1.18
1.51
0.97
1.30
0.95
1.20
0.70
1.40
0.90
0.59
1.51
1.94
2.24
4.48
1.04
2.08
1.55
2.46
2.47
12.58
2.12
1.90
4.91
Raw
Coofed, fried
Raw
Canned, drained solids
Canned, liquid
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, moist heat
Imitation, made from surimi
Raw
Canned
Cooked, moist heat
Crab cakes
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw, farmed
Raw, wild
Canned
Cooked, breaded and fried
Cooked, farmed, dry heat
Cooked, wild, dry heat
Cooked, wild, moist heat
Page
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Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Oyster, Pacific
Scallop, mixed species
Shrimp
Squid
Moisture Content
<•%•>
82.06
64.12
78.57
58.44
73.10
75.86
75.85
52.86
77.28
78.55
64.54
Total Fat Content
<•%•>
2.30
4.60
0.76
10.94
1.40
1.73
1.36
12.28
1.08
1.38
7.48
Comments
Raw
Cooked, moist heat
Raw
Cooked, breaded and fried
Steamed
Raw
Canned
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, fried
Source: USDA. 2007.
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Chapter 11 - Intake of Meats, Dairy Products and Fats
TABLE OF CONTENTS
11 INTAKE OF MEATS, DAIRY PRODUCTS AND FATS 11-1
11.1 INTRODUCTION 11-1
11.2 RECOMMENDATIONS 11-2
11.3 INTAKE STUDIES 11-6
11.3.1 Key Meat and Diary Intake Study 11-6
11.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 11-6
11.3.2 Relevant Meat and Dairy Intake Studies 11-7
11.3.2.1 USDA, 1999a 11-7
11.3.2.2 Smiciklas-Wright et al, 2002 11-8
11.3.2.3 Fox et al., 2004 11-8
11.3.2.4 Ponzaetal.,2004 11-9
11.3.2.5 Mennella et al., 2006 11-9
11.3.2.6 Fox et al., 2006 11-10
11.4 FAT INTAKE 11-10
11.4.1 Key Fat Intake Study 11-10
11.4.1.1 U.S. EPA, 2007 11-10
11.4.2 Relevant Fat Intake Studies 11-11
11.4.2.1 Cresantaetal, 1988; Nicklas et al., 1993; and Frank et al., 1986 .... 11-11
11.4.2.2 CDC, 1994 11-11
11.5 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES 11-12
11.6 CONVERSION BETWEEN WET WEIGHT AND LIPID WEIGHT INTAKE RATES ...11-12
11.7 REFERENCES FOR CHAPTER 11 11-13
APPENDIX 11A 11 A-l
APPENDIX 1 IB 11B-1
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Chapter 11 - Intake of Meats, Dairy Products and Fats
LIST OF TABLES
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed 11-3
Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats 11-4
Table 11-3. Per Capita Intake of Total Meat and Dairy Products (g/kg-day as consumed) 11-14
Table 11-4. Consumer Only Intake of Total Meat and Dairy Products (g/(kg-day as consumed) 11-15
Table 11-5. Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed) 11-16
Table 11-6. Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed).... 11-16
Table 11-7. Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (g/day) ... 11-17
Table 11-8. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%) 11-18
Table 11-9. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day) ... 11-19
Table 11-10. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) 11-20
Table 11-11. Quantity (as consumed) of Meat and Dairy Products Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days 11-21
Table 11-12. Characteristics of FITS Sample Population 11-22
Table 11-13. Percentage of Infants and Toddlers Consuming Meat or Other Protein Sources 11-23
Table 11-14. Characteristics of WIC Participants and Non-participants (Percentages) 11-24
Table 11-15. Food Choices for Infants and Toddlers by WIC Participation Status 11-25
Table 11-16. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Milk, Meats or Other Protein Sources on A Given Day 11 -26
Table 11-17. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 11 -27
Table 11-18. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 11-28
Table 11-19. Total Fat Intake (Per capita; g/day) 11-29
Table 11-20. Total Fat Intake (Per capita; g/kg-day) 11-30
Table 11-21. Total Fat Intake (Consumers Only; g/day) 11-31
Table 11-22. Total Fat Intake (Consumers Only; g/kg-day) 11-32
Table 11-23. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day) 11-33
Table 11-24. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/kg-day) 11-34
Table 11 -25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/day) 11-35
Table 11 -26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/kg-day) 11-37
Table 11-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender 11-39
Table 11-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products 11-40
Table 11 A-l Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data ... 11A-2
Page
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Chapter 11 - Intake of Meats, Dairy Products and Fats
11 INTAKE OF MEATS, DAIRY PRODUCTS
AND FATS
11.1 INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, meats, dairy products, and fats may
become contaminated with toxic chemicals by several
pathways. These foods sources can become
contaminated if animals are exposed to contaminated
media (i.e., soil, water, or feed crops). To assess
exposure through this pathway, information on meat,
dairy, and fat ingestion rates are needed.
Children's exposure from contaminated meats,
dairy products, and fats may differ from that of adults
because of differences in the type and amounts of food
eaten. Also, for many foods, the intake per unit body
weight is greater for children than for adults. Common
meats, dairy products, and fats eaten by children
include non-fat milk solids, milk fat and solids, lean
beef, and milk sugar (lactose) (Goldman, 1995).
A variety of terms may be used to define intake
of meats, dairy products, and fats (e.g., consumer-only
intake, per capita intake, total meat, dairy product, or
fat intake, as-consumed intake, dry weight intake). As
described in Chapter 9, Intake of Fruits and Vegetables,
consumer-only intake is defined as the quantity of
meats, dairy products, or fats consumed by children
during the survey period averaged across only the
children who consumed these food items during the
survey period. Per capita intake rates are generated by
averaging consumer-only intakes over the entire
population of children. In general, per capita intake
rates are appropriate for use in exposure assessment for
which average dose estimates for children are of interest
because they represent both children who ate the foods
during the survey period and children who may eat the
food items at some time, but did not consume them
during the survey period. Per capita intake, therefore,
represents an average across the entire population of
interest, but does so at the expense of underestimating
consumption for the subset of the population that
consume the food in question. Total intake refers to the
sum of all meats, diary products, or fats consumed in a
day.
Intake rates may be expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the as-
consumed weight. The food ingestion values provided
in this chapter are expressed as as-consumed intake
rates because this is the fashion in which data were
reported by survey respondents. This is of importance
because concentration data to be used in the dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease food weight. Similarly, cooking can
increase the mass of contaminant in food (due to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching). The combined
effects of changes in weight and changes in contaminant
mass can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. Ideally, after-
cooking food concentrations should be combined with
the as-consumed intake rates. In the absence of data, it
is reasonable to assume that no change in contaminant
concentration occurs after cooking. It is important for
the assessor to be aware of these issues and choose
intake rate data that best match the concentration data
that are being used. For more information on cooking
losses and conversions necessary to account for such
losses, the reader is referred to Chapter 13 of this
handbook.
Sometimes contaminant concentrations in food
are reported on a dry weight basis. When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used. Dry-weight food
concentrations and intake rates are based on the weight
of the food consumed after the moisture content has
been removed. Similarly, when contaminant
concentrations in food are reported on a lipid weight
basis, lipid weight intake rates should be used. For
information on converting the intake rates presented in
this chapter to dry weight or lipid weight intake rates,
the reader is referred to Sections 11.5 and 11.6 of this
chapter.
The purpose of this chapter is to provide intake
data for meats, diary products, and fats among children.
The recommendations for ingestion rates of meats,
dairy products, and fats are provided in the next section,
along with a summary of the confidence ratings for
these recommendations. The recommended values are
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
based on the key studies identified by U. S. EPA for this
factor. Following the recommendations, the key studies
on ingestion of meats, dairy products, and fats are
summarized. Relevant data on ingestion of meats, dairy
products, and fats are also provided. These studies are
presented to provide the reader with added perspective
on the current state-of-knowledge pertaining to
ingestion of meats, dairy products, and fats among
children.
11.2 RECOMMENDATIONS
Tables 11-1 presents a summary of the
recommended values for per capita and consumers-only
intake of meats, diary products, and fats, on an as-
consumed basis. Confidence ratings for the meats,
dairy products, and fat intake recommendations for
general population children are provided in Table 11-2.
U. S. EPA analyses of data from the 1994-96 and
1998 Continuing Survey if Food Intake among
Individuals (CSFII) were used in selecting
recommended intake rates for general population
children. The U.S. EPA analysis of meat and dairy
products was conducted using age groups that differed
slightly from U.S. EPA's Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005). However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis. The U.S. EPA analysis of fat intake data
from the CSFII used the age groups recommended by
U.S. EPA (2005). The CSFII data on which the
recommendations for meats, dairy products, and fats are
based are short-term survey data and may not
necessarily reflect the long-term distribution of average
daily intake rates. However, for these broad categories
of food (i.e., total meats and diary products), because
they are eaten on a daily basis throughout the year with
minimal seasonality, the short term distribution may be
a reasonable approximation of the long-term
distribution, although it will display somewhat
increased variability. This implies that the upper
percentiles shown here will tend to overestimate the
corresponding percentiles of the true long-term
distribution. It should be noted that because these
recommendations are based on 1994-96 and 1998
CSFII data, they may not reflect the most recent
changes that may have occurred in consumption
patterns.
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Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed
Age Group
Per Capita
Consumers Only
Mean
95th Percentile
Mean
95th Percentile
Multiple
Percentiles
Source
g/kg-day
g/kg-day
g/kg-day
g/kg-day
Total Meats1
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
1.2
4.1
4.1
4.1
2.9
2.1
2.1
6.7
9.8
9.8
9.4
6.5
4.8
4.8
3.0
4.2
4.2
4.2
2.9
2.1
2.1
9.2
9.8
9.8
9.4
6.5
4.8
4.8
See Tables 11-3
and 11-4
U.S. EPA
Analysis of
CSFII, 1994-
96 and 1998.
Total Dairy Products1
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
13
37
37
23
14
5.6
5.6
49
49
32
16
16
16
37
37
23
14
5.6
5.6
58
49
32
16
16
See Tables 11-3
and 11-4
U.S. EPA
Analysis of
CSFII, 1994-
96 and 1998.
Individual Meat and Dairy Products - See Tables 11-5 and 11-6
Total Fats
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
5.2
4.5
4.1
3.7
4.0
3.6
3.4
2.6
1.6
1.3
16
11
8.2
7.0
7.1
6.4
5.8
4.2
3.0
2.7
7.8
6.0
4.4
3.7
4.0
3.6
3.4
2.6
1.6
1.3
16
12
8.3
7.0
7.1
6.4
5.8
4.2
3.0
2.7
See Tables 11-
20 and 11-24
U.S. EPA
Analysis of
CSFII, 1994-
96 and 1998.
Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005). Data
were placed in the standardized age categories closest to those used in the analysis.
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Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Rationale
The survey methodology and data analysis was adequate.
The survey sampled approximately 11,000 children. An
analysis of primary data was conducted.
No physical measurements were taken. The method relied
on recent recall of meats and diary products eaten.
The key studies were directly relevant to meat, dairy, and
fat intake.
The data were demographically representative of the U.S.
population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total meats, total diary
products, and total fats. Means were provided for
individuals meats and diary products.
Data collection was based on recall of consumption for a
2-day period; the accuracy of using these data to estimate
long-term intake (especially at the upper percentiles) is
uncertain. However, use of short-term data to estimate
chronic ingestion can be assumed for broad categories of
foods such as total meats, total diary products, and total
fats. Uncertainty is likely to be greater for individual
meats and diary products.
Rating
High
Medium
High
Medium
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Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not been
peer reviewed outside the Agency.
There was 1 key study for intake of meat and diary
products and 1 key for fat intake. Both were based on the
1994-96, 1998 CSFII.
Rating
Medium
High confidence in
the averages;
Low confidence in the
long-term upper
percentiles
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
11.3 INTAKE STUDIES
The primary source of recent information on
consumption rates of meat and diary products among
children is the U.S. Department of Agriculture's
(USDA) CSFII. Data from the 1994-96 CSFII and the
1998 Children's supplement to the 1994-96 CSFII have
been used in various studies to generate children's
consumer-only and per capita intake rates for both
individual meats and diary products and total meats and
diary products. The CSFII is a series of surveys
designed to measure the kinds and amounts of foods
eaten by Americans. The CSFII 1994-96 was
conducted between January 1994 and January 1997
with a target population of non-institutionalized
individuals in all 50 states and Washington, D.C. In
each of the 3 survey years, data were collected for a
nationally representative sample of individuals of all
ages. The CSFII 1998 was conducted between
December 1997 and December 1998 and surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-96 and was intended
to be merged with CSFII 1994-96 to increase the
sample size for children. The merged surveys are
designated as CSFII 1994-96, 1998. Additional
information on these surveys can be obtained at
http://www.ars.usda.gov/Scrviccs/docs.hlm?docid=14
531.
The CSFII 1994-96, 1998 collected dietary
intake data through in-person interviews on 2 non-
consecutive days. The data were based on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day. Over 11,000 of the sample persons
represented children up to 18 years of age. The 2-day
response rate for the 1994-1996 CSFII was
approximately 76 percent. The 2-day response rate for
CSFII 1998 was 82 percent.
The CSFII 1994-96, 98 surveys were based on a
complex multistage area probability sample design.
The sampling frame was organized using 1990 U.S.
population census estimates, and the stratification plan
took into account geographic location, degree of
urbanization, and socioeconomic characteristics.
Several sets of sampling weights are available for use
with the intake data. By using appropriate weights data
for all fours years of the surveys can be combined.
USDA recommends that all 4 years be combined in
order to provide an adequate sample size for children.
11.3.1 Key Meat and Diary Intake Study
11.3.1.1 U.S. EPA Analysis of CSFII 1994-96,
1998
For many years, the U.S. EPA' Office of
Pesticide Programs (OPP) has used food consumption
data collected by the U.S. Department of Agriculture
(USDA) for its dietary risk assessments. Most recently,
OPP, in cooperation with USDA's Agricultural
Research Service (ARS), used data from the 1994-96,
1998 CSFII to develop the Food Commodity Intake
Database (FCID). CSFII data on the foods people
reported eating were converted to the quantities of
agricultural commodities eaten. "Agricultural
commodity" is a term used by U. S. EPA to mean animal
(or plant) parts consumed by humans as food; when
such items are raw or unprocessed, they are referred to
as "raw agricultural commodities." For example, a beef
stew may contain the commodities beef, carrots, and
potatoes. FCID contains approximately 553 unique
commodity names and 8-digit codes. The FCID
commodity names and codes were selected and defined
by U.S. EPA and were based on the U.S. EPA Food
Commodity Vocabulary
(httgV/www.epa.gov/pesticides^oodfegd/).
The meats and diary items/groups selected
for the U.S. EPA analysis included total meats and total
diary products, and individual meats and diary such as
beef, pork, poultry, and eggs. Appendix 11A presents
the food codes and definitions used to determine the
various meats and dairy products used in the analysis.
Intake rates for these food items/groups represent intake
of all forms of the product (e.g., both home produced
and commercially produced). Children who provided
data for two days of the survey were included in the
intake estimates. Individuals who did not provide
information on body weight or for whom identifying
information was unavailable were excluded from the
analysis. Two-day average intake rates were calculated
for all individuals in the database for each of the food
items/groups. These average daily intake rates were
divided by each individual's reported body weight to
generate intake rates in units of grams per kilogram of
body weight per day (g/kg-day). The data were
weighted according to the four-year, two-day sample
weights provided in the 1994-96,1998 CSFII to adjust
the data for the sample population to reflect the national
population.
Summary statistics were generated on both
a per capita and a consumer only basis. For per capita
intake, both users and non-users of the food item were
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Chapter 11 - Intake of Meats, Dairy Products and Fats
included in the analysis. Consumer only intake rates
were calculated using data for only those individuals
who ate the food item of interest during the survey
period. Intake data from the CSFII are based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the meat or dairy products being analyzed, mean intake
rate, and standard error of the mean intake rate were
calculated for total meats, total dairy products, and
selected individual meats and dairy products.
Percentiles of the intake rate distribution (i.e., 1st, 5th,
10th, 25th, 50th, 75th, 90th, 95th, 99th, and 100th
percentile were also provided for total meats and dairy
products. Data were provided for the following age
groups of children: birth to <1 year, 1 to <2 years, 3 to
<5 years, 6 to <12 years, and 13 to <19 years. Because
these data were developed for use in U.S. EPA's
pesticide registration program, the age groups used are
slightly different than those recommended in U.S.
EPA's Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Tables 11 -3 presents as-consumed per capita
intake data for total meats and dairy products in g/kg-
day; as-consumed consumer-only intake data for total
meats and dairy products in g/kg-day are provided in
Table 11-4. Table 11 -5 provides per capita intake data
for certain individual meats and dairy products and
Table 11-6 provides consumer only intake data for
these individual meats and dairy products.
It should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the long-
term distribution of average daily intake rates. The
distributions generated from short-term and long-term
data will differ to the extent that each individual's
intake varies from day to day; the distributions will be
similar to the extent that individuals' intakes are
constant from day to day. However, for broad
categories of foods (e.g., total meats and dairy
products) that are eaten on a daily basis throughout the
year, the short-term distribution may be a reasonable
approximation of the true long-term distribution,
although it will show somewhat more variability. In
this chapter, distributions are provided only for broad
categories of meats and dairy products (i.e., total meats
and dairy products). Because of the increased
variability of the short-term distribution, the short-term
upper percentiles shown here may overestimate the
corresponding percentiles of the long-term distribution.
For individual foods, only the mean, standard error, and
percent consuming are provided.
The strengths of U.S. EPA's analysis are
that it provides distributions of intake rates for various
age groups of children, normalized by body weight.
The analysis uses the 1994-96, 1998 CSFII data set
which was designed to be representative of the U.S.
population. The data set includes four years of intake
data combined, and is based on a two-day survey
period. As discussed above, short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food. This is particularly true for the tails (extremes)
of the distribution of food intake. Also, the analysis
was conducted using slightly different age groups that
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the age groups used, the data should provide suitable
intake estimates for the age groups of interest.
11.3.2 Relevant Meat and Dairy Intake Studies
11.3.2.1 USDA, 1999a-Food and Nutrient Intakes
by Children 1994-96,1998, Table Set 17
USDA (1999a) calculated national
probability estimates of food and nutrient intake by
children based on all 4 years of the CSFII (1994-96 and
1998) for children age 9 years and under and on CSFII
1994-96 only for individuals age 10 years and over.
Sample weights were used to adjust for non-response,
to match the sample to the U. S. population in terms of
demographic characteristics, and to equalize intakes
over the 4 quarters of the year and the 7 days of the
week. A total of 503 breast-fed children were excluded
from the estimates, but both consumers and non-
consumers were included in the analysis.
USDA (1999a) provided data on the mean
per capita quantities (grams) of various food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey. Tables 11-7 and 11-8 present
data on the mean quantities (grams) of meat and eggs
consumed per individual for one day, and the
percentage of survey individuals consuming meats and
eggs on that survey day. Tables 11 -9 and 11-10 present
similar data for dairy products. Data on mean intakes
or mean percentages are based on respondents' day-1
intakes.
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The advantage of the USD A (1999a) study
is that it uses the 1994-96, 98 CSFII data set, which
includes four years of intake data, combined, and
includes the supplemental data on children. These data
are expected to be generally representative of the U.S.
population and they include data on a wide variety of
meats and diary products. The data set is one of a
series of USDA data sets that are publicly available.
One limitation of this data set is that it is based on one-
day, and short-term dietary data may not accurately
reflect long-term eating patterns. Other limitations of
this study are that it only provides mean values of food
intake rates, consumption is not normalized by body
weight, and presentation of results is not consistent with
U.S. EPA's recommended age groups.
11.3.2.2 Smiciklas-Wright et al, 2002 - Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating Occasion
and in a Day, 1994-1996
Using data gathered in the 1994-96 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of meat, poultry, and
dairy products consumed per eating occasion by
members of the U.S. population (i.e., serving sizes).
The estimates of serving size are based on data obtained
from 14,262 respondents, ages 2 and above, who
provided 2 days of dietary intake information. A total
of 4,939 of these respondents were children, ages 2 to
19 years of age. Only dietary intake data from users of
the specified food were used in the analysis (i.e.,
consumers only data).
Table 11-11 presents serving size data for
meats and dairy products. These data are presented on
an as-consumed basis (grams) and represent the
quantity of meats and dairy products consumed per
eating occasion. These estimates may be useful for
assessing acute exposures to contaminants in specific
foods, or other assessments where the amount
consumed per eating occasion is necessary. Only the
mean and standard deviation serving size data and
percent of the population consuming the food during
the 2-day survey period are presented in this handbook.
Percentiles of serving sizes of the foods consumed by
these age groups of the U.S. population can be found
in Smiciklas-Wright et al. (2002).
The advantages of using these data are that
they were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
for individual foods consumed as ingredients of mixed
foods. Mixed foods were disaggregated via recipe files
so that the individual ingredients could be grouped
together with similar foods that were reported
separately. Thus, weights of foods consumed as
ingredients were combined with weights of foods
reported separately to provide a more thorough
representation of consumption. However, it should be
noted that since the recipes for the mixed foods
consumed were not provided by the respondents,
standard recipes were used. As a result, the estimates
of quantity consumed for some food types are based on
assumptions about the types and quantities of
ingredients consumed as part of mixed foods. This
study used data from the 1994 to 1996 CSFII; data from
the 1998 children's supplement were not included.
11.3.2.3 Fox et al, 2004 - Feeding Infants and
Toddlers Study: What Foods Are Infants
and Toddlers Eating
Fox et al. (2004) used data from the Feeding
Infants and Toddlers study (FITS) to assess food
consumption patterns in infants and toddlers. The FITS
was sponsored by Gerber Products Company and was
conducted to obtain current information on food and
nutrient intakes of children, ages 4 to 24 months old, in
the 50 states and the District of Columbia. The FITS is
described in detail in Devaney et al. (2004). FITS was
based on a random sample of 3,022 infants and toddlers
for which dietary intake data were collected by
telephone from their parents or caregivers between
March and July 2002. An initial recruitment and
household interview was conducted, followed by an
interview to obtain information on intake based on 24-
hour recall. The interview also addressed growth,
development and feeding patterns. A second dietary
recall interview was conducted for a subset of 703
randomly selected respondents. The study over-
sampled children in the 4 to 6 and 9 to 11 months age
groups; sample weights were adjusted for non-response,
over-sampling, andunder-coverageof some subgroups.
The response rate for the FITS was 73 percent for the
recruitment interview. Of the recruited households,
there was a response rate of 94 percent for the dietary
recall interviews (Devaney et al., 2004). The
characteristics of the FITS study population is shown in
Table 11-12.
Fox et al. (2004) analyzed the first set of 24-
hour recall data collected from all study participants.
For this analysis, children were grouped into six age
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categories: 4 to 6 months, 7 to 8 months, 9 to 11
months, 12 to 14 months, 15 to 18 months, and 19 to 24
months. Table 11-13 provides the percentage of infants
and toddlers consuming milk, meats or other protein
sources at least once in a day. The percentage of
children consuming any type of meat or protein source
ranged from 14.2 percent for 4 to 6 month olds to 97.2
percent for 19 to 24 month olds (Table 11-13).
The advantages of this study were that the
study population represented the U.S. population and
the sample size was large. One limitation of the
analysis done by Fox et al. (2004) was that only
frequency data were provided; no information on actual
intake rates was included. In addition, Devaney et al.
(2004) noted several limitations associated with the
FITS data. For the FITS, a commercial list of infants
and toddlers was used to obtain the sample used in the
study. Since many of the households could not be
located and did not have children in the target
population, a lower response rate than would have
occurred in a true national sample was obtained
(Devaney et al., 2004). In addition, the sample was
likely from a higher socioeconomic status when
compared with all U.S. infants in this age group (4 to 24
months old) and the use of a telephone survey may have
omitted lower-income households without telephones
(Devaney et al., 2004).
11.3.2.4 Ponza et al, 2004 - Nutrient Food Intakes
and Food Choices of Infants and Toddlers
Participating in WIC
Ponza et al. (2004) conducted a study using
selected data from FIT S to assess feeding patterns, food
choices and nutrient intake of infants and toddlers
participating in the Special Supplemental Nutrition
Program for Women, Infants, and Children (WIC).
Ponza et al. (2004) evaluated FITS data for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months( N = 1159) and 12 to 24 months (N= 996). The
total sample size described by WIC participant and non-
participant is shown in Table 11-14.
The foods consumed were analyzed by
tabulating the percentage of infants who consumed
specific foods/food groups per day (Ponza et al., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza etal, 2004). Table 11-14 presents the
demographic data for WIC participants and non-
participants. Table 11-15 provides the food choices for
infants and toddlers. In general, there was little
difference in food choices among WIC participants and
non-participants, except for consumption of yogurt by
infants 7 to 11 months of age and toddlers 12 to 24
months of age (Table 11-15). Non-participants, 7 to 24
months of age, were more likely to eat yogurt than WIC
participants (Ponza et al., 2004).
An advantage of this study is that it had a
relatively the large sample size and was representative
of the U.S. general population of infants and children.
A limitation of the study is that intake values for foods
were not provided. Other limitations are one associated
with the FITS data and are described previously in
Section 11.3.2.3.
11.3.2.5 Mennella et al, 2006 - Feeding Infants
and Toddlers Study: The Types of Foods
Fed to Hispanic Infants and Toddlers
Mennella et al. (2006) investigated the types
of food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic infants
and toddlers in the United States. The FITS 2002 data
for children between 4 and 24 months old were used for
the study. The data represent a random sample of 371
Hispanic and 2,367 non-Hispanic infants and toddlers
(Menella et al., 2006). Menella et al. (2006) grouped
the infants as follows: 4 to 5 months (N = 84 Hispanic;
538 non-Hispanic), 6 to 11 months (N = 163 Hispanic
and 1,228 non-Hispanic), and 12 to 24 months (N = 124
Hispanic and 871 non-Hispanic) of age.
Table 11-16 provides the percentages of
Hispanic and non-Hispanic infants and toddlers
consuming milk, meats or other protein sources on a
given day. In most instances the percentages
consuming the different types of meats and protein
sources were similar (Mennella et al., 2006).
The advantage of the study is that it provides
information on food preferences for Hispanic and non-
Hispanic infants and toddlers. A limitation is that the
study did not provide food intake data, but provided
frequency of use data instead. Other limitations are
those noted previously in Section 11.3.2.3 for the FITS
data.
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11.3.2.6 Fox et al., 2006 - Average Portion of
Foods Commonly Eaten by Infants and
Toddlers in the United States
Fox et al. (2006) estimated average portion
sizes consumed per eating occasion by children 4 to 24
months of age who participated in the FITS. The FITS
is a cross-sectional study designed to collect and
analyze data on feeding practices, food consumption,
and usual nutrient intake of U.S. infants and toddlers
and is described in Section 11.3.2.3 this chapter. It
included a stratified random sample of 3,022 children
between 4 and 24 months of age.
Using the 24-hour recall data, Fox et al.
(2006) derived average portion sizes for six major food
groups, including meats and other protein sources.
Average portion sizes for select individual foods within
these major groups were also estimated. For this
analysis, children were grouped into six age categories:
4 to 5 months, 6 to 8 months, 9 to 11 months, 12 to 14
months, 15 to 18 months, and 19 to 24 months. Tables
11-17 and 11-18 present the average portion sizes of
meats and dairy products for infants and toddlers,
respectively.
11.4 FAT INTAKE
11.4.1 Key Fat Intake Study
11.4.1.1 U.S. EPA, 2007 - Analysis of Fat Intake
Based on the U.S. Department of
Agriculture's 1994-96, 1998 Continuing
Survey of Food Intakes by Individuals
(CSFII)
U. S. EPA conducted an analysis to evaluate
the dietary intake of fats by individuals in the United
States using data from the USDA's 1994-1996, 1998
CSFII (USDA, 2000). Intakes of CSFII foods were
converted to U.S. EPA food commodity codes using
data provided in U.S. EPA's FCID (U.S. EPA, 2000).
The FCID contains a "translation file" that was used to
break down the USDA CSFII food codes into 548 U.S.
EPA commodity codes. The method used to translate
USDA food codes into U.S. EPA commodity codes is
discussed in detail in U.S. EPA (2000).
Each of the 548 U.S. EPA commodity codes
was assigned a value between 0 and 1 that indicated the
mass fraction of fat in that food item. For many sources
of fat, a commodity code existed solely for the nutrient
fat portion of the food. For example, beef is
represented in the FCID database by ten different
commodity codes; several of these codes specifically
exclude fat, and one code is described as "nutrient fat
only." In these cases, the fat fraction could be
expressed as 0 or 1, as appropriate. Most animal food
products and food oils were broken down in this way.
The fat contents of other foods in the U.S. EPA
commodity code list were determined using the USDA
Nutrient Database for Standard Reference, Release 13
(USDA, 1999b). For each food item in the U.S. EPA
code list, the best available match in the USDA
Nutrient database was used. If multiple values were
available for different varieties of the same food item
(e.g., green, white and red grapes), a mean value was
calculated. If multiple values were available for
different cooking methods (i.e, fried vs. dry cooked),
the method least likely to introduce other substances,
such as oil or butter, was preferred. In some cases, not
all of the items that fall under a given food commodity
code could be assigned a fat content. For example, the
food commodity code list identified "turkey, meat
byproducts" as including gizzard, heart, neck and tail.
Fat contents could be determined only for the gizzard
and heart. Because the relative amounts of the different
items in the food commodity code was unknown, the
mean fat content of these two items was assumed to be
the best approximation of the fat content for the food
code as a whole.
The analysis was based on approximately
11,000 C SFII child respondents who had provided body
weights and who had completed both days of the two-
day survey process. These individuals were grouped
according to various age categories. The mean,
standard error, and a range of percentiles of fat intake
were calculated for 12 food categories (i.e., all fats,
animal fats, meat and meat products, beef, pork,
poultry, organ meats, milk and dairy products, fish, oils,
and nuts/seeds/beans/legumes/tubers) and 98
demographic cohorts. Fat intake was calculated as a
two-day average consumption across both survey days
in units of grams per day and grams per kilogram of
body weight per day for the whole survey population
and for consumers only. A secondary objective of the
study was to evaluate fat consumption patterns of
individuals who consume high levels of animal fats.
The entire data analysis was repeated for a subset of
individuals who were identified as high consumers of
animal fats. The selection of the high-consumption
group was done for each age category individually,
rather than on the whole population, because fat intake
on a per-body-weight basis is heavily skewed towards
young children, and an analysis across the entire
American population was desired. For infants, the "less
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than one year old" group was used instead of the
smaller infant groups (<1 month, 1 to <3 months, etc.).
Within each of the age categories, individuals that
ranked at or above the 90thpercentile of consumption of
all animal fats on a per-unit body weight basis were
identified. Because of the sample weighting factors, the
high consumer group was not necessarily 10 percent of
each age group. The selected individuals made up a
survey population of 1,175 children. Fat intake of
individuals in this group was calculated in g/day and
g/kg-day for the whole population (i.e., per capita) and
for consumers only.
The analysis presented in U.S. EPA (2007)
was conducted before U.S. EPA published the guidance
entitled Guidance on Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005).
Therefore, the age groups used for children in U.S.
EPA (2007) were not entirely consistent with the age
groups recommended in the 2005 guidance. A re-
analysis of the some of the data was conducted for this
chapter to conform with U. S. EPA's recommended age
groups for children. The results of this re-analysis are
presented in Tables 11-19 through 11 -26 for individuals
less than 21 years of age. Only intake rates of all fats
are provided in these tables; the reader is referred to
U.S. EPA (2007) for fat intake rates from individual
food sources. Tables 11-19 and 11-20 present intake
rates of all fats for the whole population (i.e., per
capita) in g/day and g/kg-day, respectively. Table 11 -
21 and 11-22 present intake rates of all fats for
consumers only in g/day and g/kg-day, respectively.
Fat intake rates of all fats for the top decile of animal
fat consumers from the consumers only group are
presented in Table 11 -23 in g/day and in Table 11 -24 in
g/kg-day (per capita total fat intake rates for the top
decile of animal fat consumers are not provided because
they are the same as those for consumers only).
11.4.2 Relevant Fat Intake Studies
11.4.2.1 Cresanta et al., 1988; Nicklas et al., 1993;
and Frank et al., 1986 - Bogalusa Heart
Study
Cresanta et al. (1988), Nicklas etal. (1993),
and Frank et al. (1986) analyzed dietary fat intake data
as part of the Bogalusa heart study. The Bogalusa
study, an epidemiologic investigation of cardiovascular
risk-factor variables and environmental determinants,
collected dietary data on subjects residing in Bogalusa,
LA, beginning in 1973. Among other research, the
study collected fat intake data for children, adolescents,
and young adults. Researchers examined various
cohorts of subj ects, including (1) six cohorts of 10-year
olds, (2) two cohorts of 13-year olds, (3) one cohort of
subjects from 6 months to 4 years of age, and (4) one
cohort of subjects from 10 to 17 years of age (Nicklas,
1995). To collect the data, interviewers used the 24-
hour dietary recall method. According to Nicklas
(1995), "the diets of children in the Bogalusa study are
similar to those reported in national studies of
children." Thus, these data are useful in evaluating the
variability of fat intake among the general population.
Data for 6-month old to 17-year old individuals
collected during 1973 to 1982 are presented in Tables
11-25 and 11-26 (Frank et al., 1986). Data are
presented for total fats, animal fats, vegetable fats, and
fish fats in units of g/day (Table 11-25) and g/kg/day
(Table 11-26).
11.4.2.2 CDC, 1994 - Dietary Fat and Total Food-
energy Intake: Third National Health and
Nutrition Examination Survey, Phase 1,
1988-91
The Centers for Disease Control and
Prevention (CDC, 1994) used data from NHANES III
to calculate daily total food energy intake (TFEI), total
dietary fat intake, and saturated fat intake for the U.S.
population during 1988 to 1991. The sample
population comprised 20,277 individuals ages 2 months
and above, of which 14,801 respondents (73 percent
response rate) provided dietary information based on a
24-hour recall. Of these, 6,870 were children between
the ages of 2 months and 19 years. TFEI was defined
as "all nutrients (i.e., protein, fat, carbohydrate, and
alcohol) derived from consumption of foods and
beverages (excluding plain drinking water) measured in
kilocalories (kcal)." Total dietary fat intake was
defined as "all fat (i.e., saturated and unsaturated)
derived from consumption of foods and beverages
measured in grams" (CDC, 1994).
The authors estimated and provided data on
the mean daily TFEI and the mean percentages of TFEI
from total dietary fat grouped by age and gender. The
overall mean daily TFEI for the total population was
2,095 kcal, of which 34 percent (712 kcal or 82 g) was
from total dietary fat. Based on this information, the
mean daily fat intake was calculated for the various age
groups and genders (see Appendix 11B for detailed
calculation). Table 11 -27 presents the grams of fat per
day obtained from the daily consumption of foods and
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beverages grouped by age and gender for the U.S.
population, based on this calculation.
11.5 CONVERSION BETWEEN WET AND
DRY WEIGHT INTAKE RATES
The intake rates presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
uncooked weight of meats and dairy products consumed
per day or per eating occasion). However, data on the
concentration of contaminants in meats and dairy
products may be reported in units of either wet or dry
weight.(e.g., mg contaminant per gram-dry-weight of
meats and dairy products.) It is essential that exposure
assessors be aware of this difference so that they may
ensure consistency between the units used for intake
rates and those used for concentration data (i.e., if the
contaminant concentration is measured in dry weight of
meats and dairy products, then the dry weight units
should be used for their intake values).
If necessary, wet weight (e.g., as consumed)
intake rates may be converted to dry weight intake rates
using the moisture content percentages presented in
Table 11-28 and the following equation:
IRdw= IRww
where:
100- W
100
(Eqn. 11-1)
w =
dry weight intake rate;
wet weight intake rate; and
percent water content
11.6 CONVERSIONBETWEENWETWEIGHT
AND LIPID WEIGHT INTAKE RATES
In some cases, the residue levels of
contaminants in meat and dairy products may be
reported as the concentration of contaminant per gram
of fat. This may be particularly true for lipophilic
compounds. When using these residue levels, the
assessor should ensure consistency in the exposure
assessment calculations by using consumption rates that
are based on the amount of lipids consumed for the
meat or dairy product of interest.
If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to lipid weight intake
rates using the fat content percentages presented in
Table 11-28 and the following equation:
IRlw =
where:
Irww
L
(Eqn. 11-3)
lipid weight intake rate;
wet weight intake rate; and
percent lipid (fat) content.
Alternately, wet weight residue levels in meat and dairy
products may be estimated by multiplying the levels
based on fat by the fraction of fat per product as
follows:
C = C
ww Iw
L
100
(Eqn. 11-4)
Alternatively, dry weight residue levels in meat and
diary products may be converted to wet weight residue
levels for use with wet weight (e.g., as-consumed)
intake rates as follows:
where:
L =
wet weight intake rate;
lipid weight intake rate; and
percent lipid (fat) content.
ww dw
where:
ww
Cdw =
W =
(Eqn. 11-2)
wet weight intake rate;
dry weight intake rate; and
percent water content.
The resulting residue levels may then be used in
conjunction with wet weight (e.g., as-consumed)
consumption rates. The total fat content data presented
in Table 11 -28 are for selected meat and dairy products
taken from USDA, 2007.
The moisture content data presented in Table 11 -28 are
for selected meats and dairy products taken from USDA
(2007).
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11.7 REFERENCES FOR CHAPTER 11
CDC. (1994) Dietary fat and total food-energy intake:
Third National Health and Nutrition
Examination Survey, Phase 1,1988-91. Center
for Disease Control. Morbidity and Mortality
Weekly Report, February 25,1994: 43(7)118-
125.
Cresanta, J.L.; Farris, R.P.; Croft, J.B.; Frank, G.C.;
Berenson, G.S. (1988) Trends in fatty acid
intakes of 10-year-old children, 1973-1982. J
AmDietAssoc 88: 178-184.
Devaney, B.; Kalb, L.; Brief el, R.; Zavitsky-Novak, T.;
Clusen, N; Ziegler, P. (2004) Feeding Infants
and Toddlers Study: overview of the study
design. J Am Diet Assoc 104(Suppl 1): S8-
S13.
Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004)
Feeding Infants and Toddlers Study: what
foods are infants and toddlers eating. J Am
Diet Assoc 104 (Suppl): S22-S30.
Fox, M.K.; Reidy, K.; Karwe, V.; Ziegler, P. (2006)
Average portions of foods commonly eaten by
infants and toddlers in the United States. J Am
Diet Assoc. 106 (Suppl 1): S66-S76.
Frank, G.C.; Webber,L.S.;Farris,R.P.;Berenson, G.S.
(1986) Dietary databook: quantifying dietary
intakes of infants, children, and adolescents, the
Bogalusa heart study, 1973-1983. National
Research and Demonstration Center -
Arteriosclerosis, Louisiana State University
Medical Center, New Orleans, Louisiana.
Goldman, L. (1995) Children - unique and vulnerable.
Environmental risks facing children and
recommendations for response. Environ Health
Perspect 103(6): 13-17.
Mennella, J.; Ziegler, P.;Briefel,R.; Novak, T. (2006)
Feeding Infants and Toddlers Study: the types
of foods fed to Hispanic infants and toddlers.
J Am Diet Assoc 106 (Suppl 1): S96-S106.
Nicklas, T.A. (1995) Dietary studies of children: The
Bogalusa Heart Study experience. J Am Diet
Assoc 95:1127-1133.
Nicklas, T.A.; Webber, L.S.; Srinivasan, S.R.;
Berenson, G.S. (1993) Secular trends in
dietary intakes and cardiovascular risk factors
in 10-y-old children: the Bogalusa heart study
(1973-1988). Am JClinNutr 57:930-937.
Ponza, M.; Devaney, B.; Ziegler, P.; Reidy, K.;
Squatrito, C. (2004) Nutrient intakes and food
choices of infants and toddlers participating in
WIC. JAmDietAssoc 104(Suppl): S71-S79.
Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.;
Cook, A.J.; Goldman, J.D. (2002) Foods
commonly eaten in the United States: quantities
consumed per eating occasion and in a day,
1994-1996. U.S. Department of Agriculture
NFS Report No. 96-5, pre-publication version,
252 pp.
USD A. (1999a) Food and nutrient intakes by children
1994-96, 1998: Table Set 17. Beltsville, MD:
Food Surveys Research Group, Beltsville
Human Nutrition Research Center, Agricultural
Research Service, U.S. Department of
Agriculture.
USD A. (1999b) USD A Nutrient Database for Standard
Reference, Release 13. Agricultural Research
Service, Nutrient Data Laboratory.
http://www.nal.usda.gov/fnic/foodcomp
USD A. (2000) 1994-96, 1998 Continuing Survey of
Food Intakes by Individuals (CSFII). CD-
ROM. Agricultural Research Service,
Beltsville Human Nutrition Research Center,
Beltsville, MD. Available from the National
Technical Information Service, Springfield,
VA; PB-2000-500027.
USDA. (2007) USDA National Nutrient Database for
Standard Reference, Release 20. Agricultural
Research Service, Nutrient Data Laboratory
Home Page,
http://www.ars.usda.gov/ba/bhnrc/ndl
U.S. EPA. (2000) Food commodity intake database
[FCID raw data file]. Office of Pesticide
Programs, Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
U.S. EPA. (2005) Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
U.S. Environmental Protection Agency,
Washington, D.C., EPA/630/P-03/003F.
U.S. EPA. (2007) Analysis of fat intake based on the
U.S. Department of Agriculture's 1994-96,
1998 Continuing Survey of Food Intakes by
Individuals (CSFII). National Center for
Environmental Assessment, Washington, DC;
EPA/600/R-05/021F. Available from the
National Technical Information Service,
Springfield, VA, and online at
http ://www. epa.gov/ncea.
Child-Specific Exposure Factors Handbook
September 2008
Page
11-13
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Table 11-3. Per Capita Intake of Total Meat and Dairy Products (g/kg-day as
. „ ,, Percent
Age Group N „
Consuming
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
40.0
97.3
98.8
98.7
98.8
79.5
99.8
100.0
100.0
99.8
Source: Based on unpublished U.S. EPA
Mean
1.2
4.1
4.1
2.9
2.1
12.6
36.7
23.3
13.6
5.6
analysis
SE
0.1
0.1
0.05
0.05
0.05
0.9
0.7
0.3
0.4
0.2
of 1994-96,
consumed)
Percentiles
1st
Total
0.0
0.0
0.0
0.0
0.0
Total
0.0
0.4
1.1
0.3
0.01
5th
Meat
0.0
0.2
0.6
0.4
0.2
Dairy
0.0
3.9
4.2
1.8
0.2
10th
0.0
0.8
1.2
0.8
0.5
0.0
7.7
7.0
3.5
0.5
25th
0.0
1.9
2.2
1.5
1.0
1.0
17.4
13.0
6.7
1.5
50th
0.0
3.6
3.6
2.5
1.9
8.0
31.3
20.8
11.7
4.2
75th
1.6
5.7
5.4
3.8
2.7
14.1
49.8
30.9
18.5
8.1
90th
4.2
8.0
7.7
5.4
3.8
24.1
72.1
42.0
26.0
12.5
95th
6.7
9.8
9.4
6.5
4.8
48.7
88.3
49.4
31.5
15.5
99th 100th
10.7 29.6
14.1 20.6
12.7 23.4
9.6 18.0
7.1 30.3
127 186
126 223
67.7 198
42.7 80.6
25.4 32.7
1998 CSFII.
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Table 11-4. Consumer Only Intake
Age Group N Mean
SE
of Total Meat and
Dairy Products (g
/(kg-day as consumed)
Percentiles
1st
5th
10th
25th
50th
75th
90th
95th
99th
100th
Total Meat
Birth to 1 year 575
1 to 2 years 2,044
3 to 5 years 4,334
6 to 12 years 2,065
13 to 19 years 1,208
3.0
4.2
4.2
2.9
2.1
0.2
0.1
0.1
0.1
0.1
0.01
0.04
0.04
0.1
0.02
0.1
0.6
0.8
0.5
0.3
0.3
1.0
1.2
0.9
0.6
1.0
2.1
2.2
1.5
1.1
2.2
3.6
3.6
2.5
1.9
4.2
5.7
5.5
3.9
2.8
7.4
8.1
7.7
5.4
3.8
9.2
9.8
9.4
6.5
4.8
12.9
14.1
12.7
9.6
7.1
29.6
20.6
23.4
18.0
30.3
Total Dairy
Birth to 1 year 1,192
1 to 2 years 2,093
3 to 5 years 4,390
6 to 12 years 2,089
13 to 19 years 1,221
N = Sample size.
SE = Standard error.
Source: Based on unpublished
15.9
36.8
23.3
13.6
5.6
U.S
1.0
0.7
0.3
0.4
0.2
0.03
0.4
1.1
0.3
0.01
EPA analysis of 1994-96,
0.8
4.2
4.2
1.8
0.3
1998
1.9
7.8
7.0
3.5
0.5
CSFII.
5.8
17.4
13.0
6.7
1.5
10.2
31.3
20.8
11.7
4.2
16.0
49.8
30.9
18.5
8.1
27.7
72.1
42.0
26.0
12.5
57.5
88.3
49.4
31.5
15.5
141.8
126.2
61.1
42.7
25.4
185.6
223.2
198.4
80.6
32.7
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Table 11-5. Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed)
Percent , , __
Mean SE
Age Group N Consuming
Beef
Birth to 1 year 1,486 253 0.41 0.04
1 to 2 years 2,096 85.5 1.7 0.06
3 to 5 years 4,391 90.8 1.8 0.04
6 to 12 years 2,089 92.1 1.3 0.04
13tol9years 1,222 91.1 1.0 0.05
Percent , , „„
Mean SE
Consuming
Pork
17.7 0.15 0.02
69.7 0.72 0.03
79.8 0.84 0.02
82.4 0.59 0.03
81.5 0.40 0.03
Percent , , „„
Mean SE
Consuming
Poultry
30.1 0.66 0.05
73.7 1.7 0.05
73.0 1.5 0.03
67.1 0.93 0.03
65.5 0.68 0.03
Percent , , „„
Mean SE
Consuming
Eggs
27.9 0.30 0.04
92.3 1.3 0.04
95.1 0.91 0.03
95.8 0.51 0.02
95.4 0.33 0.02
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
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Table 11-6. Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed)
Age Group N Mean SE
Beef
Birth to 1 year 361 1.6 0.2
1 to 2 years 1,795 2.0 0.06
3 to 5 years 3,964 1.9 0.04
6 to 12 years 1,932 1.4 0.04
13 to 19 years 1,118 1.1 0.05
N Mean SE
Pork
248 0.83 0.08
1,488 1.0 0.04
3,491 1.1 0.03
1,731 0.72 0.03
1,002 0.50 0.03
N Mean SE
Poultry
434 2.2 0.1
1,552 2.2 0.06
3,210 2.0 0.04
1,421 1.4 0.04
808 1.0 0.04
N Mean SE
Eggs
402 1.1 0.1
1,936 1.4 0.04
4,171 0.96 0.03
2,001 0.53 0.02
1,167 0.34 0.02
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
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Age Group
Table
Sample
Size
1 1-7. Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (
Total
Beef
Pork
Lamb, _
. Organ
veal,
meats
game
Frankfurters,
sausages,
luncheon
meats
g/day)
Poultry
Total
Chicken
Eggs
Mixtures,
mainly meat/
poultry/
fish
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
24
80
94
87
101
115
121
112
93
1"
5
7
6
8
10
14
11
8
_a,b
2
6
4
6
6
6
6
5
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_b _a,b
_b _a,b
2
13
18
15
19
22
22
21
17
3
12
17
15
19
20
22
21
16
2
12
16
14
18
19
19
19
15
3
13
18
16
13
13
13
13
13
16
43
41
42
43
49
51
47
42
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
151
154
250
18
19
30
7
7
12
_a,b _a,b
_a,b _a,b
1" 0
24
24
28
23
22
31
21
20
26
11
12
22
71
72
134
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
121
130
158
17
18
21
4
5
5
_a,b _a,b
_a,b _a,b
_a,b _a,b
18
19
15
19
20
21
16
17
19
10
11
13
55
60
85
Males and Females
9 years and under
19 years and under
9,309
11,287
110
152
12
18
5
7
_b _a,b
_a,b _a,b
19
20
18
22
17
19
12
14
50
76
* Estimate is not statistically reliable due to small sample size reporting intake.
b Value less than 0.5
but greater than 0.
Note: Consumption amounts shown
Source: USDA, 1999a.
are representative of the
first day
of each participant's survey response.
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Table 11-8. Percentage of Individuals Consuming
Age Group
Sample
Size
Total
Beef
Lamb,
Pork veal,
game
Meats and Eggs, by Sex and Age (%)
Frankfurters,
Organ sausages,
meats luncheon
meats
Poultry
Total
Chicken
Eggs
Mixtures,
mainly meat/
poultry/
fish
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
26.0
77.4
85.2
81.4
86.2
86.2
87.1
86.5
77.5
2.1
11.9
16.2
14.1
13.8
16.1
18.2
16.0
13.7
1.1 "
7.3
14.9
11.2
13.3
13.8
13.2
13.4
11.2
0.2"
0.8"
0.8"
0.8"
0.5"
0.5"
0.6"
0.5
0.6
0.2"
0.2"
0.2"
0.2"
a,b
0.2"
0.2"
0.2"
0.2"
6.1
26.3
33.2
29.9
36.4
37.0
35.1
36.1
30.4
6.3
24.0
27.6
25.8
28.3
27.4
27.7
27.8
24.5
5.0
23.1
25.6
24.4
26.0
25.1
24.8
25.3
22.6
6.7
22.8
27.3
25.1
19.8
16.9
16.4
17.7
18.9
13.7
32.2
31.4
31.8
29.2
30.5
30.8
30.2
28.8
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
87.4
87.8
86.8
20.1
22.0
24.2
11.9
12.2
15.8
0.4"
0.4"
0.6"
0.1"
0.2"
0.0
37.4
36.2
31.8
24.8
22.9
20.6
22.3
20.5
17.6
15.1
15.6
17.0
36.2
35.7
38.3
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
84.6
86.5
80.1
19.4
20.2
22.0
9.2
10.0
11.2
0.4"
0.4"
0.1 "
0.2"
0.1 "
0.1 "
33.5
33.1
24.6
23.1
22.9
21.6
20.2
19.8
18.9
13.4
13.3
15.0
32.4
32.8
34.0
Males and females
9 years and under
19 years and under
9,309
11,287
* Estimate is not statistically
Note: Percenta£
80.9
82.8
16.1
19.6
reliable due to small
10.9
12.1
sample size reportin
0.5
0.4
g intake.
0.2"
0.1 "
24.3
22.7
24.3
22.7
22.0
20.1
17.1
16.4
31.0
33.3
es shown are representative of the first day of each participant's survey response.
Source: USD A, 1999a.
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Table 1 1-9. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day)
Age Group
_ , lotalMUK
S*mple and Milk
Size ,
Products
Milk, Milk Drinks, Yogurt
Total
Fluid Milk
Total
Whole
Lowfat
Skim
Yogurt
Milk
Desserts
Cheese
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
762
546
405
474
419
407
417
414
477
757
526
377
450
384
369
376
376
447
61
475
344
408
347
328
330
335
327
49
347
181
262
166
147
137
150
177
11
115
141
128
150
149
159
153
127
a,b
5'
17
11
26
27
25
26
18
4
14
10
12
10
10
9
10
10
3
11
16
14
22
23
25
23
18
1
9
11
10
12
14
14
13
11
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
450
450
409
405
402
358
343
335
303
127
121
99
176
172
158
29
33
40
6
6
3"
31
35
29
13
12
19
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
380
382
269
337
336
220
288
283
190
105
108
66
146
136
92
26
29
30
4
4
4"
29
30
29
13
14
14
Males and Females
9 years and under
19 years and under
9,309
11,287
a Estimate is not statistically
453
405
reliable due to
417
362
small sample
323
291
153
121
141
135
22
29
8
6
23
27
12
14
size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption
Source: USD A, 1999a
amounts shown are representative of the first day of each participant's
survey response.
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Table 11-10. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%)
Total
^ Sample Milk and
Age Group
Size Milk
Products
Milk, milk drinks, yogurt
Total
Fluid Milk
Total Whole
Lowfat
Skim
Yogurt
Milk
Desserts
Cheese
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
85.4
95.3
91.6
93.4
94.3
93.2
93.1
93.5
92.5
84.6
92.7
87.3
90.0
88.3
87.8
86.4
87.5
88.0
11.1
87.7
84.3
86.0
84.6
85.0
81.2
83.6
75.7
8.3
61.7
44.8
53.0
42.5
41.3
38.1
40.6
41.0
2.4
26.5
36.3
31.5
39.5
40.4
41.7
40.6
32.9
0.2"
1.5"
5.2
3.4
6.8
7.7
6.5
7.0
4.9
3
1
10.0
6
8
8
4
7.3
5
5
6
6
8
5
2
6
4.5
13.9
17.5
15.8
21.4
21.7
21.4
21.5
17.5
6.0
29.7
32.6
31.2
37.0
36.9
34.9
36.3
30.9
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
93.2
92.3
81.3
85.5
84.6
65.8
80.7
79.0
59.6
32.4
30.8
22.6
44.3
43.1
30.7
8.6
9.5
7.0
3
3
1
8
7
7"
24.0
25.0
13.6
34.6
32.3
37.1
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
90.2
90.2
75.4
82.5
81.5
54.0
77.5
76.0
49.7
31.5
33.2
17.5
40.8
37.8
23.9
8.1
8.4
9.5
2
3
9
0
2.2'
24.1
22.4
17.1
30.9
31.9
36.1
Males and Females
9 years and under
19 years and under
9,309
11,287
a Estimate is not statistically
92.2
86.7
86.4
75.6
reliable due to small
Note: Percentages shown are representative of the firs!
Source: USDA, 1999a
77.1
68.1
37.4
30.1
36.8
33.1
6.3
7.5
5
3
3
8
20.1
18.6
31.7
33.5
sample size reporting intake.
day of each participant's survey response.
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Table 11-11. Quantity (as consumed) of Meat and Dairy
Products Consumed Per Eating Occasion and Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (grams)
2 to 5 years old
Male and Female
(N = 2,109)
Food category PC
Mean
SEM
6 to
1 1 years old
Male and Female
(N = 1,432)
PC
Mean
SEM
PC
Male
(N = 696)
Mean
12 to 19 years old
SEM
PC
Female
(N = 702)
Mean
SEM
Meats
Beefsteaks 11.1
Beefroasts 5.2
Ground beef 59.5
Ham 6.9
Pork chops 11.0
Bacon 10.4
Pork breakfast sausage 5.3
Frankfurters and luncheon meats 51.7
Total chicken and turkey 63.8
Chicken 44.6
Turkey 5.1
Fluid milk (all) 92.5
Fluid milk consumed with cereal 68.1
Whole milk 50.0
Whole milk consumed with cereal 33.8
Lowfatmilk 47.5
Lowfat milk consumed with cereal 31.5
Skim milk 7.8
Skim milk consumed with cereal 4.9
Cheese, other than cream or 53.2
cottage 18.4
Ice cream and ice milk 8.0
Boiled, poached, and baked eggs 17.3
Fried eggs 10.4
Scrambled eggs
a Indicates a statistic that is potentially
PC = Percent consuming at least once in
SEM = Standard error of the mean.
58
49
31
35
48
15
33
49
46
52
63
196
149
202
161
189
136
171
131
24
92
36
48
59
4
5
1
4
3
1
2
1
1
1
7
3
4
3
5
3
4
9
11
1
3
3
1
4
11.3
4.8
63.7
8.5
10.1
9.7
6.0
50.9
53.8
36.0
5.7
Dairy
89.2
64.7
39.5
26.2
52.8
32.7
11.1
7.5
50.4
21.1
8.2
14.0
7.1
87
67
41
40
62
19
32
57
62
70
66
Products
241
202
244
212
238
198
225
188
29
135
34
58
72
9
7
1
4
4
2
3
2
2
3
5
4
5
7
11
4
4
9
14
1
4
3
2
5
9.5
5.1
73.4
11.6
11.6
14.9
6.3
46.7
58.4
34.3
8.2
72.3
44.4
30.0
14.8
39.6
24.3
9.7
6.5
61.1
14.2
5.0
14.9
7.1
168
233"
66
68
100
25
40"
76
100
117
117
337
276
333
265
326
277
375
285"
38
221
44"
83
72
14
149"
3
7
8
2
4"
3
4
5
14
8
10
13
18
8
12
38
23"
2
12
9"
5
5
9.4
5.5
61.5
9.9
8.5
11.1
3.3
38.5
54.1
36.1
5.8
64.4
42.7
22.4
14.1
32.4
21.1
13.5
8.3
53.9
15.2
7.7
13.5
8.9
112
97"
52
40
72
18
40"
57
71
80
60"
262
222
258
235
262
227
255
181
27
187
45
59
103
10
16"
3
5
7
1
5"
3
2
3
9"
8
8
7
13
13
12
14
13
1
14
7
3
9
unreliable because of small sample size or large coefficient of variation.
2 days.
Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
Q
^
!
§»
I
I
&
ri
1=
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-12. Characteristics of the FITS Sample Population
Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition
Source: Devaney et al., 2004.
Sample Size
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
3,022
Program for Women, Infants, and Children.
Percentage of Sample
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
100.0
Page
11-22
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-13. Percentage of Infants
and Toddlers Consuming Meat or Other Protein Sources
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Cow's Milk
Whole
Reduce-fat or non-fat
Unflavored
Flavored
Soy Milk
Any Meat or Protein Source
Baby Food Meat
Non-baby Food Meat
Other Protein Soources
Dried Beans and Peas, Vegetarian Meat
Eggs
Peanut Butter, Nuts, and Seeds
Cheese
Yogurt
Protein Sources in Mixed Dishes
Baby Food Dinners
Beans and Rice, Chilli, Other Bean Mixtures
Mixtures with Vegetables and/or Rice/Pasta
Soup"
Types of Meat'
Beef
Chicken or Turkey
Fish and Shellfish
Hotdogs, Sausages, and Cold cuts
Pork/Ham
Other
4 to 6 7 to 8
months months
0.8
0.5
0.3
0.8
0.0
0.0
14.2
1.7
1.5
2.7
0.6
0.7
0.0
0.4
1.2
11.0
9.5
0.0
0.9
0.9
0.9
2.0
0.0
0.0
0.3
0.3
2.9
2.4
0.5
2.9
0.0
0.5
54.9
4.0
8.4
9.7
1.3
2.9
0.5
2.1
4.1
43.3
39.8
0.0
1.2
3.4
2.6
7.3
0.5
2.1
1.7
0.6
9 to 11
months
20.3
15.1
5.3
19.5
0.9
1.7
79.2
3.1
33.7
36.1
3.3
7.3
1.9
18.5
15.7
46.2
33.5
0.9
4.7
10.1
7.7
22.4
1.9
7.1
4.0
2.5
a The amount of protein actually provided by soups varies. Soups could not be sorted reliably
soups were assigned the same two-digit food code and many food descriptions lacked detail
b Includes baby food and non-baby food sources.
Source: Fox et al., 2004.
12tol4 15tol8 19 to 24
months months months
84.8
68.8
17.7
84.0
1.8
1.5
91.3
1.1
60.3
59.2
7.0
17.0
8.8
34.0
14.9
30.1
10.2
1.2
8.2
12.5
16.1
33.0
5.5
16.4
9.7
2.8
88.3
71.1
20.7
87.0
4.4
3.9
92.7
0.0
76.3
66.8
6.6
25.0
11.6
39.1
20.2
25.5
2.4
2.1
9.0
13.8
16.3
46.9
8.7
20.1
11.2
2.1
87.7
58.8
38.1
86.5
5.6
3.8
97.2
0.0
83.7
68.9
9.9
25.2
10.4
41.1
15.3
20.5
1.3
2.0
7.8
11.5
19.3
47.3
7.1
27.0
13.9
3.9
into different food groups because all
about major soup ingredients.
Child-Specific Exposure Factors Handbook
September 2008
Page
11-23
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-14. Characteristics of WIC Participants and Non-participants" (Percentages)
Infants 4 to 6 months
Infants 7 to 11 months
Toddlers 12 to 24 months
WIC
Participant
Non-
participant
WIC
Participant
Non-
participant
WIC
Participant
Non-
participant
Gender
Male 55
Female 45
Child's Ethnicity
Hispanic or Latino 20
Non-Hispanic or Latino 80
Child's Race
White 69
Black 15
Other 22
Child In Day Care
Yes 39
No 61
Age of Mother
14 to 19 years 18
20 to 24 years 33
25 to 29 years 29
30 to 34 years 9
35 years or Older 9
Missing 2
Mother's Education
11 ""Grade or Less 23
Completed High School 35
Some Postsecondary 33
Completed College 7
Missing 2
Parent's Marital Status
Married 49
Not Married 50
Missing 1
Mother or Female Guardian Works
Yes 46
No 53
Missing 1
Urbanicity
Urban 34
Suburban 36
Rural 28
Missing 2
Sample Size (Unweighted) 265
54
46
11
89
**
84
4
11
38
62
**
1
13
29
33
23
7
2
19
26
53
1
**
93
7
1
51
48
1
55
31
13
1
597
55
45
24
76
63
17
20
34
66
13
38
23
15
11
1
15
42
32
9
2
57
42
1
45
54
1
37
31
30
2
351
51
49
92
**
86
5
9
**
46
54
**
1
11
30
36
21
1
**
2
20
27
51
0
**
93
7
0
**
60
40
0
**
50
34
15
1
57
43
22
78
67
13
20
43
57
33
29
18
11
0
17
42
31
9
1
58
41
1
55
45
0
35
35
28
2
205
52
48
10
89
**
84
5
11
*
53
47
**
1
14
26
34
26
1
**
3
19
28
48
2
11
1
*
61
38
1
48
35
16
2
791
WIC
X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants for
each of the three age groups. * P<0.05; ** P>0.01; non-participants significantly different from WIC participants on the variable.
= Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Page
11-24
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-15. Food Choices for Infants and Toddlers by WIC
Cow's Milk
Meat or Other Protein Sources
Baby Food Meat
Non-Baby Meat
Eggs
Peanut Butter, Nuts, Seeds
Cheese
Yogurt
Sample Size (unweighted)
Infants 4 to 6 months Infants 7 to
WIC Non- WIC
Participant participant Participant
1.0 0.6 11.4
0.9 2.0 3.3
3.7 0.5** 25.0
0.9 0.6 8.5
0.0 0.0 1.4
0.0 0.6 9.0
0.8 1.4 5.5
265 597 351
Participation Status
11 months
Non-
participant
13.2
3.6
22.0
4.2**
1.3
12.5
13.3**
808
Toddlers 12
WIC
Participant
92.3
0.0
77.7
24.1
12.9
38.5
9.3
205
to 24 months
Non-
participant
85.8*
0.3
75.1
23.0
9.8
38.8
18.9**
791
* = P<0.05; non-participants significantly different from WIC participants.
** = P<0.01; non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponzaetal., 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
11-25
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-16. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
Milk, Meats or Other Protein Sources on A Given Day
Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic
(N=84)
Non-Hispanic
(N=538)
Hispanic
(N=163)
Non-Hispanic
(N=l,228)
Hispanic
(N=124)
Non-Hispanic
(N=871)
Milk
Fed Any Cow's or Goat Milk
Fed Cow's Milk
Whole
Reduced Fat or Non-fat
Meat or Other Protein Sources
Any Meat or Protein Source*
Non-Baby Food Meat
Other Protein Sources
Beans and Peas
Eggs
Cheese
Yogurt
Protein Sources in Mixed Dishes
Baby Food dinners
Soupb
Types of Meat*
9.7T
1.4T
1.4T
7.5T
6.9t
5.3
4.4
3.9
7.5T
5.6T
2.2t
71.6
22.5
26.5
5.8T
9.5
11.2
7.7
44.8
24.7*
16.3**
11.3
8.3
3.0
62.0
19.2
21.2
1.8
4.2
9.4
9.8
41.6
35.3
5.1
85.6
61.7
29.0
90.3
72.3
70.1
19.1*
26.4
29.3
15.7
33.3
3.5T
23.4*
87.7
66.3
27.0
94.7
76.0
65.3
6.5
22.5
40.2
17.0
22.7
3.9
10.7
Beef
Chicken and Turkey
Hotdogs, Sausages, and Cold Cuts
Pork/Ham
5.0T
11.2
7.2T
3.8T
4.6
11.9
3.4
1.7
25.2
46.5
14.8
11.7
16.0
43.6
23.3
12.1
Includes baby food and non-baby food sources.
The amount of protein actually provided by soups varies. Soups could not be sorted reliably into different food groups because
many food descriptions lacked detail about major soup ingredients.
= Less than 1 percent of the group consumed this food on a given day.
= Significantly different from non-Hispanic at the P<0.05.
= Significantly different from non-Hispanic at the P>0.01.
= Statistic is potentially unreliable because of a high coefficient of variation.
= Sample size.
Source: Mennella et al., 2006.
Page
11-26
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-17. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study
Food group
Non-baby food meats
Cheese
Scrambled eggs
Yogurt
Baby food dinners
= Cell size was too small to g
N = Number of respondents.
SEM = Standard error of the mean
Source: Fox et al., 2006.
Reference Unit
ounce
ounce
cup
ounce
ounce
enerate a reliable estimate.
4 to 5 months
(N=624)
2.9±0.24
6 to 8 months 9 to 1 1 months
(N=708) (N=687)
Mean± SEM
0.9±0.16
3.3±0.09
0.8±0.05
0.7±0.05
0.2±0.02
3.1±0.20
3.8±0.11
Child-Specific Exposure Factors Handbook
September 2008
Page
11-27
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-18. Average Portion
Sizes Per Eating Occasion of Meats and Dairy Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study
Food Group
Milk
Milk
Milk, as a beverage
Milk, on cereal
Meats and other protein sources
All meats
Beef
Chicken or turkey, plain
Hot dogs, luncheon meats, sausages
Chicken, breaded"
Scrambled eggs
Peanut butter
Yogurt
Cheese
Reference unit
fluid ounce
fluid ounce
fluid ounce
ounce
ounce
ounce
ounce
ounce
nugget
cup
tablespoon
ounce
ounce
12 to 14 months
(N=371)
5.6±0.14
5.7±0.14
3.4±0.37
1.2±0.06
0.8±0.08
1.3±0.10
1.3±0.13
1.5±0.14
2.4±0.22
0.2±0.02
0.7±0.08
3.4±0.19
0.8±0.05
15 to 18 months
(N=312)
Mean ± SEM
5.9±0.14
6.1±0.14
2.7±0.26
1.3±0.08
1.2±0.15
1.3±0.16
1.5±0.13
1.5±0.13
2.4±0.21
0.3±0.03
0.7±0.09
3.8±0.26
0.8±0.05
19 to 24 months
(N=320)
6.2±0.17
6.4±0.17
3.6±0.29
1.3±0.07
1.2±0.14
1.3±0.10
1.5±0.12
1.8±0.12
2.8±0.19
0.3±0.02
0.9±0.13
3.8±0.28
0.7±0.04
* Not included in total for all meats because weight includes breading.
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.
Page
11-28
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-19. Total Fat Intake (Per capita; g/day)
Age Group*
N
Mean
SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year
all
female
male
1,422
728
694
29
28
30
18
17
18
0.03
0.03
0.04
19
18
20
31
30
32
40
39
40
59
57
61
107
92
107
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all
female
male
16to<21 years
all
N
SE
female
male
88
50
38
245
110
135
411
223
188
678
345
333
1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
975
493
482
743
372
371
17
19
15
22
20
23
28
27
30
33
32
34
46
45
46
51
49
52
59
56
61
68
64
72
80
69
91
85
79
92
16
15
18
18
16
19
17
17
18
17
17
16
19
18
20
21
20
21
22
21
23
24
22
25
38
29
42
47
39
53
0
0
0
0
0
0
0.10
0.02
0.15
8.5
5.1
11
24
25
23
27
24
29
34
33
35
41
38
43
42
37
50
37
35
41
0
0
0
0
0
0
20
16
22
25
24
25
33
33
32
37
35
39
44
43
45
50
48
55
56
49
64
54
49
57
Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
Exposures to Environmental Contaminants.
= Sample size.
= Standard error.
Source: Based on U.S.
EPA, 2007.
19
18
19
27
24
28
31
29
31
34
33
34
43
43
44
48
46
50
56
54
59
66
61
70
74
65
84
76
75
77
32
29
31
34
33
34
39
38
39
43
43
44
55
54
56
60
59
61
70
68
72
81
77
86
97
82
111
108
96
114
52
39
43
47
45
55
52
51
50
62
62
62
79
77
80
87
83
89
99
96
103
111
101
115
145
123
163
168
154
186
64
52
64
75
50
75
107
74
107
100
92
100
159
116
159
197
127
197
218
194
218
179
156
179
342
259
342
463
317
463
Monitoring and Assessing Childhood
Child-Specific Exposure Factors Handbook
September 2008
Page
11-29
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-20. Total Fat Intake (Per capita; g/kg-day)
Age Group*
N
Mean
SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year
all
female
male
1,422
728
694
4.0
4.1
4.0
2.8
2.8
2.8
0.01
0.01
0.01
2.3
2.4
2.3
4.1
4.3
4.0
5.6
5.8
5.5
8.9
8.7
9.2
20
18
20
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
88
50
38
245
110
135
411
223
188
678
345
333
1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
5.2
5.9
4.3
4.5
4.3
4.7
4.1
4.2
4.1
3.7
3.7
3.6
4.0
4.1
3.9
3.6
3.7
3.6
3.4
3.4
3.5
2.6
2.4
2.7
4.9
4.6
5.3
3.8
3.6
3.9
2.7
2.8
2.5
1.8
1.9
1.7
1.7
1.6
1.7
1.5
1.6
1.5
1.3
1.3
1.4
1.1
1.0
1.1
0
0
0
0
0
0
0.01
0.00
0.02
1.0
0.66
1.3
2.1
2.2
1.9
1.9
1.8
2.0
1.9
1.8
1.9
1.3
1.3
1.4
0
0
0
0
0
0
2.4
2.3
2.6
2.7
2.8
2.6
2.8
3.0
2.6
2.6
2.4
2.6
2.4
2.4
2.4
1.7
1.6
1.8
5.7
6.2
4.7
4.9
4.8
4.9
4.3
4.5
4.1
3.8
3.8
3.7
3.7
3.7
3.6
3.4
3.4
3.4
3.2
3.1
3.2
2.3
2.2
2.4
9.1
8.4
9.7
6.8
6.5
7.0
5.7
6.0
5.5
4.8
5.0
4.6
4.7
5.0
4.5
4.4
4.4
4.3
4.0
4.0
4.1
3.0
2.8
3.1
16
13
18
11
11
10
8.2
8.2
8.2
7.0
7.0
6.8
7.1
6.9
7.2
6.4
6.6
6.1
5.8
5.8
5.8
4.2
4.0
4.4
20
16
20
18
14
18
18
18
16
11
9.8
11
12
9.7
12
12
10
12
11
11
11
9.9
7.7
9.9
11 to <16 years
all
female
male
16to<21 years
all
female
male
975
493
482
743
372
371
1.6
1.4
1.8
1.3
1.1
1.4
0.80
0.69
0.86
0.66
0.56
0.73
0.77
0.67
0.88
0.54
0.48
0.63
1.1
0.91
1.2
0.81
0.75
0.85
a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
to Environmental Contaminants.
N
SE
1.4
1.3
1.6
1.2
1.1
1.2
2.0
1.7
2.1
1.6
1.4
1.7
3.0
2.6
3.3
2.7
2.1
2.9
5.7
5.0
5.7
6.0
4.4
6.0
Monitoring and Assessing Childhood Exposures
= Sample size.
= Standard error.
Source: Based on U.S. EPA, 2007.
Page
11-30
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table
Age Group" N Mean
Birth to <1 year
all 1,301
female 664
male 637
Birth to <1 month
all 59
female 37
male 22
1 to <3 months
all 182
female 79
male 103
3 to <6 months
all 384
female 205
male 179
6 to <12 months
all 676
female 343
male 333
1 to <2 year
all 1,002
female 499
male 503
2 to <3 years
all 994
female 494
male 500
3 to <6 years
all 4,112
female 2,018
male 2,094
6 to <11 years
all 1,553
female 742
male 811
11 to <16 years
all 975
female 493
male 482
16 to <21 years
all 743
female 372
male 371
31
30
32
26
26
25
29
28
31
30
29
31
33
32
34
46
45
46
51
49
52
59
56
61
68
64
72
80
69
91
85
79
92
11-21. Total Fat Intake (Consumers Only; g/day)
SE
16
16
16
13
11
17
14
12
16
16
16
17
16
17
16
19
18
20
21
20
21
22
21
23
24
22
25
38
29
42
47
39
53
Percentiles
10th
7.0
5.1
9.0
6.7
7.8
-
5.8
4.3
8.5
2.5
1.2
4.6
8.9
6.2
11
24
25
23
27
24
29
34
33
35
41
38
43
42
37
50
37
35
41
25th
24
24
25
17
17
-
24
21
27
24
24
25
25
24
25
33
33
32
37
35
39
44
43
45
50
48
55
56
49
64
54
49
57
50th
32
32
33
27
25
-
31
30
31
32
31
33
34
34
34
43
43
44
48
46
50
56
54
59
66
61
70
74
65
84
76
75
77
" Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring
to Environmental Contaminants.
= Percentiles were not calculated for sample sizes
N = Sample size.
SE = Standard error.
Source: Based on U.S. EPA, 2007.
less than 30.
75th
41
40
41
32
32
-
35
35
38
40
39
39
43
43
44
55
54
56
60
59
61
70
68
72
81
77
86
97
82
111
108
96
114
95th
61
58
62
52
39
-
53
46
59
54
52
53
62
62
62
79
77
80
87
83
89
99
96
103
111
101
115
145
123
163
168
154
186
100th
107
92
107
64
52
64
75
50
75
107
72
107
100
92
100
159
116
159
197
127
197
218
194
218
179
156
179
342
259
342
463
317
463
and Assessing Childhood Exposures
Child-Specific Exposure Factors Handbook
September 2008
Page
11-31
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-22. Total Fat Intake (Consumers Only; g/kg-day)
Age Group"
Birth to <1 year
all
female
male
N
1,301
664
637
Vlean
4.4
4.5
4.3
SE
2.6
2.6
2.6
Percentiles
10th
0.94
0.67
1.2
25th
2.9
3.1
2.8
50th
4.3
4.5
4.1
75th
5.8
6.0
5.6
95th
9.2
8.9
9.3
100th
20
18
20
Birth to <1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all
female
male
59
37
22
182
79
103
384
205
179
676
343
333
1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
975
493
482
7.8
8.0
7.4
6.0
5.9
6.1
4.4
4.5
4.3
3.7
3.7
3.6
4.0
4.1
3.9
3.6
3.7
3.6
3.4
3.4
3.5
2.6
2.4
2.7
1.6
1.4
1.8
4.1
3.5
4.9
3.1
2.9
3.3
2.5
2.6
2.4
1.8
1.9
1.7
1.7
1.6
1.7
1.5
1.6
1.5
1.3
1.3
1.4
1.1
1.0
1.1
0.80
0.69
0.86
1.4
2.0
-
1.0
0.80
1.8
0.35
0.14
0.57
1.0
0.75
1.3
2.1
2.2
1.9
1.9
1.8
2.0
1.9
1.8
1.9
1.3
1.3
1.4
0.77
0.67
0.88
5.4
5.3
-
4.1
4.3
4.1
3.1
3.1
3.1
2.7
2.8
2.6
2.8
3.0
2.6
2.6
2.4
2.6
2.4
2.4
2.4
1.7
1.6
1.8
1.1
0.91
1.2
8.0
7.7
-
6.0
6.0
6.0
4.5
4.7
4.2
3.8
3.8
3.7
3.7
3.7
3.6
3.4
3.4
3.4
3.2
3.1
3.2
2.3
2.2
2.4
1.4
1.3
1.6
9.7
9.1
-
7.8
7.7
7.8
5.8
6.1
5.6
4.8
5.0
4.6
4.7
5.0
4.5
4.4
4.4
4.3
4.0
4.0
4.1
3.0
2.8
3.1
2.0
1.7
2.1
16
13
-
12
12
12
8.3
8.2
8.8
7.0
7.0
6.8
7.1
6.9
7.2
6.4
6.6
6.1
5.8
5.8
5.8
4.2
4.0
4.4
3.0
2.6
3.3
20
16
20
18
14
18
18
18
16
11
9.8
11
12
9.7
12
12
10
12
11
11
11
9.9
7.7
9.9
5.7
5.0
5.7
16 to <21 years
all
female
male
743
372
371
1.3
1.1
1.4
0.66
0.56
0.73
0.54
0.48
0.63
0.81
0.75
0.85
1.2
1.1
1.2
" Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring
to Environmental Contaminants.
N
SE
= Percentiles were not calculated for sample sizes
= Sample size.
= Standard error.
less than 30.
1.6
1.4
1.7
and Assessing
2.7
2.1
2.9
6.0
4.4
6.0
Childhood Exposures
Source: Based on U.S. EPA, 2007.
Page
11-32
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-23. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day)
Age Uroup"
N Mean
SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year
1 to<
all
female
male
2 years
all
female
male
140
70
70
109
54
55
45
45
45
75
68
81
16
15
17
20
16
22
28
26
28
52
52
54
35
35
34
61
57
67
45
45
44
74
70
78
54
54
53
85
78
90
77
69
79
108
89
125
100
92
100
159
114
159
2 to <3 years
3to<
6to<
11 to
16 to
all
female
male
6 years
all
female
male
11 years
all
female
male
<16 years
all
<21 years
all
103
58
45
461
217
244
198
71
127
96
68
79
77
81
88
84
92
94
88
97
133
167
20
16
24
25
24
25
25
21
27
53
64
55
55
52
62
59
66
66
58
69
85
98
64
65
61
72
68
76
77
70
78
95
122
74
74
73
84
80
90
88
86
91
121
154
85
79
90
102
95
103
105
100
112
154
189
116
109
121
135
130
136
140
123
168
223
278
133
116
133
218
194
218
178
156
178
342
463
11 -20 years
all
female
male
165
53
112
" Age groups are based on U.S
146
117
160
60
30
65
EPA (2005) Guidance on
90
81
94
105
92
117
139
111
151
168
140
191
254
162
276
463
195
463
Selecting Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
N
SE
= Sample size
= Standard error.
Source: Based on U.S.
EPA, 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
11-33
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-24. Total Fat Intake - Top 10% of Animal
Age Group"
N Mean
Fat Consumers (Consumers Only; g/kg-day)
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year
1 to
2 to
3 to
6 to
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all
16to<21 years
all
140
70
70
109
54
55
103
58
45
461
217
244
198
71
127
96
68
4.7
4.8
4.6
6.9
6.6
7.1
6.1
6.2
6.1
5.6
5.5
5.7
4.2
4.2
4.2
3.0
2.5
1.7
1.6
1.7
1.5
1.2
1.6
1.3
1.2
1.3
1.3
1.3
1.3
1.1
1.1
1.1
0.85
0.74
2.8
2.7
2.8
5.1
5.1
5.1
4.6
4.6
4.5
4.2
4.2
4.2
3.0
2.9
3.0
2.0
1.7
3.7
3.7
3.6
5.7
5.7
5.8
5.2
5.2
5.2
4.7
4.5
4.8
3.4
3.3
3.4
2.4
2.0
4.6
4.7
4.4
6.8
6.7
6.9
5.8
5.9
5.6
5.3
5.3
5.3
3.8
3.8
3.8
2.8
2.4
6.0
6.0
5.8
7.7
7.4
8.0
6.7
6.8
6.6
6.2
6.0
6.2
4.6
4.8
4.5
3.3
2.9
7.7
7.7
7.5
9.5
9.3
9.4
8.3
7.9
8.4
8.3
7.8
8.4
6.0
5.8
6.3
4.6
3.7
11
9.5
11
12
9.7
12
9.5
9.5
9.5
11
11
11
9.9
7.7
9.9
5.7
6.0
11 -20 years
N
SE
all
female
male
165
53
112
2.8
2.6
2.9
0.84
0.65
0.90
Age groups are based on U.S. EPA (2005) Guidance on
Exposures to Environmental Contaminants.
= Sample size.
= Standard error.
Source: Based on U.S.
EPA, 2007.
1.9
1.7
1.9
2.1
2.0
2.3
2.7
2.3
2.8
3.1
2.7
3.1
4.4
3.4
4.5
6.0
4.6
6.0
Selecting Age Groups for Monitoring and Assessing Childhood
Page
11-34
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day)
Age
N
Mean
SD
Percentiles
10th
25th
50th
75th
90th
Minimum
Maximum
Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
37.1
59.1
86.7
91.6
98.6
93.2
107.0
97.7
107.8
17.5
26.0
41.3
38.8
56.1
50.8
53.9
48.7
64.3
18.7
29.1
39.9
50.2
46.0
45.7
53.0
46.1
41.4
25.6
40.4
55.5
63.6
66.8
60.5
69.8
65.2
59.7
33.9
56.1
79.2
82.6
87.0
81.4
90.8
85.8
97.3
46.3
71.4
110.5
114.6
114.6
111.3
130.7
124.0
140.2
60.8
94.4
141.1
153.0
163.3
154.5
184.1
165.2
195.1
3.4
21.6
26.5
32.6
29.3
14.6
9.8
10.0
8.5
107.6
152.7
236.4
232.5
584.6
529.5
282.2
251.3
327.4
Total Animal Fat
6 months
lyear
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
18.4
36.5
49.5
50.1
50.8
54.1
56.2
53.8
64.4
16.0
20.0
28.3
29.4
31.7
39.6
39.8
35.1
48.5
0.7
15.2
20.1
21.3
21.4
20.3
19.8
15.9
15.2
4.2
23.1
28.9
29.1
28.1
30.6
28.5
28.3
30.7
13.9
33.0
42.1
42.9
42.6
45.0
44.8
44.7
51.6
28.4
45.9
66.0
64.4
66.4
64.6
72.8
67.9
86.6
42.5
65.3
81.4
88.9
92.6
97.5
109.4
105.8
128.8
0.0
0.0
10.0
14.1
5.9
0.0
4.7
0.6
2.6
61.1
127.1
153.4
182.6
242.2
412.3
209.6
182.1
230.3
Total Vegetable Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
9.2
15.4
19.3
21.1
24.5
23.7
34.3
27.3
25.7
12.8
14.3
16.3
15.5
18.6
21.6
27.4
22.8
21.3
0.6
3.7
3.8
3.9
5.7
4.3
8.4
5.1
4.2
1.2
6.1
7.9
8.6
10.4
9.5
17.9
11.9
11.7
2.8
11.3
14.8
18.7
21.8
18.3
31.2
22.6
20.8
11.6
18.1
26.6
26.6
33.3
30.6
44.6
38.1
32.9
29.4
38.0
42.9
45.2
48.5
49.0
57.5
54.4
47.6
0.0
0.2
0.7
1.0
0.9
0.6
0.0
0.7
0.0
53.2
70.2
96.6
70.4
109.0
203.7
238.3
132.2
141.5
Child-Specific Exposure Factors Handbook
September 2008
Page
11-35
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Age
Table 11-25. Fat
N
Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day) (continued)
Mean
SD
10th
25th
Perc entiles
50th
75th
90th
Minimum
Maximum
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
N
SD
Source:
125
99
135
106
219
871
148
108
159
0.05
0.05
0.04
0.1
2.3
0.3
0.3
0.4
0.5
0.1
0.2
0.2
0.6
31.1
1.5
2.2
1.5
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
1.9
1.9
4.5
459.2
19.2
25.4
9.5
15.3
= Sample size.
= Standard deviation.
Frank etal., 1986.
Page
11-36
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day)
Age
Percentiles
10th
25th
50th
75th
90th
Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
4.9
6.1
7.0
6.4
6.1
2.7
2.3
1.7
1.8
2.3
2.8
3.3
2.7
3.7
1.5
1.3
0.8
1.0
2.4
3.0
3.4
3.6
2.9
1.2
1.0
0.8
0.7
3.3
4.1
4.5
4.6
4.0
1.7
1.5
1.2
0.9
4.7
5.7
6.2
5.5
5.2
2.4
2.0
1.5
1.6
6.2
7.5
8.6
8.2
7.0
3.3
2.8
2.1
2.2
8.0
9.5
11.9
9.9
10.0
4.5
3.8
3.1
3.1
0.4
2.3
2.1
2.2
2.0
0.3
0.2
0.2
0.2
13.2
16.4
18.7
16.7
38.2
13.9
10.2
4.7
6.2
Total Animal Fat
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
2.4
3.8
4.0
3.5
3.1
16
1.2
1.0
1.0
2.1
2.1
2.3
2.0
2.1
1.2
0.9
0.6
0.8
0.08
1.7
1.7
1.6
1.3
0.6
0.4
0.3
0.3
0.6
2.4
2.3
2.1
1.7
0.8
0.6
0.5
0.5
2.0
3.4
3.4
3.1
2.6
1.3
0.9
0.8
0.8
3.7
4.9
5.2
4.2
4.0
1.9
1.6
1.3
1.4
5.5
6.5
6.7
6.1
5.4
2.8
2.3
1.9
2.0
0.0
0.0
0.7
0.9
0.4
0.00
0.08
0.01
0.05
9.0
13.6
13.4
13.1
15.4
10.8
5.2
3.1
4.2
Total Vegetable Fat Intake
6 months
lyear
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
1.2
1.6
1.6
1.5
1.5
0.7
0.8
0.5
0.4
1.8
1.6
1.4
1.1
1.2
0.6
0.8
0.4
0.4
0.08
0.4
0.3
0.3
0.4
0.1
0.2
0.09
0.07
0.2
0.6
0.7
0.6
0.6
0.3
0.4
0.2
0.2
0.4
1.2
1.1
1.4
1.2
0.5
0.6
0.4
0.4
1.6
1.9
2.0
2.0
2.1
0.9
0.9
0.7
0.6
4.1
3.8
3.5
3.0
2.8
1.4
1.3
0.9
0.9
0.0
0.02
0.06
0.08
0.06
0.02
0.0
0.01
0.0
8.2
7.6
8.5
5.1
7.3
4.2
8.6
2.2
2.1
Child-Specific Exposure Factors Handbook
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Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-26. Fat Intake Among Children
Age
N
Mean
SD
Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day) (continued)
10th
25th
Percentiles
50th
75th
90th
Minimum
Maximum
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
N
SD
Source:
125
99
132
106
218
861
147
105
149
0.01
0.01
0.003
0.01
0.2
0.01
0.01
0.01
0.01
0.02
0.03
0.02
0.04
2.0
0.05
0.04
0.03
0.03
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.02
0.0
0.0
0.0
0.0
0.0
0.0
0.04
0.008
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.2
0.3
30.0
0.6
0.4
0.2
0.2
= Sample size.
= Standard deviation.
Frank etal., 1986
Page
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender"
Total
Age Group N Mean Fat Intake N
(g/day)
2tollmonths 871
1 to 2 years 1,231
3 to 5 year 1,647
6 to 11 years 1,745
12 to 16 years 711
16 to 19 years 785
37.5
50.0
60.4
74.2
85.2
100.5
" Total dietary fat intake includes all fat (i.e
(excluding plain drinking water).
N = Sample size.
Source: Adapted from CDC, 1994.
439
601
744
868
338
308
Males
Mean Fat Intake
(g/day)
38.3
51.6
62.3
79.4
98.1
123.2
N
432
630
803
877
373
397
Females
Mean Fat Intake
(g/day)
36.8
48.4
57.7
69.0
71.3
77.5
, saturated and unsaturated) derived from consumption of foods and beverages
Child-Specific Exposure Factors Handbook
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Table 1 1-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products"
Product
Moisture
Content
(%)
Total Fat
Content
(%)
Comment
Meats
Beet (composite ot trimmed retail cuts; all grades)
Pork (composite of trimmed retail cuts)
Cured ham
Cured bacon
Lamb (composite of trimmed retail cuts)
Veal (composite of trimmed retail cuts)
Rabbit (domesticated)
Chicken (broilers or fryers)
Duck (domesticated)
Turkey (all classes)
70.62
59.25
60.44
51.43
72.34
60.31
65.11
54.55
63.46
55.93
73.42
61.96
60.70
53.72
75.91
60.16
72.84
57.08
72.82
60.61
75.46
63.79
65.99
59.45
73.77
64.22
48.50
51.84
74.16
64.88
70.40
61.70
71.97
59.42
6.16
9.91
19.24
21.54
5.88
9.66
14.95
17.18
12.90
8.32
45.04
43.27
41.78
40.30
37.27
5.25
9.52
21.59
20.94
2.87
6.58
6.77
11.39
5.55
8.05
8.41
3.08
6.71
7.41
9.12
15.06
12.56
13.60
14.92
5.95
11.20
39.34
28.35
2.86
4.97
8.02
9.73
8.26
13.15
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat
Cooked; lean and fat
Center slice, unheated; lean and fat
Raw, center slice, country style; lean only
Raw
Cooked, baked
Cooked, broiled
Cooked, pan-fried
Cooked, microwaved
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw
Cooked, roasted
Cooked, stewed
Raw; meat only
Cooked, stewed; meat only
Cooked, roasted; meat only
Cooked, fried; meat only
Raw; meat and skin
Cooked, stewed; meat and skin
Cooked, roasted; meat and skin
Cooked, fried, flour; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; ground
Cooked; ground
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products" (continued)
Product
Moisture
Content
Total Fat
Content
Comment
Dairy
Milk
Cream
Butter
Cheese
Yogurt
Eggs
Whole
Human
Lowfat (1%)
Reduced fat (2%)
Skim or fat free
Half and half
Light (coffee cream or table cream)
Heavy-whipping
Sour
Sour, reduced fat
American
Cheddar
Swiss
Cream
Parmesan
Cottage, lowfat
Colby
Blue
Provolone
Mozzarella
88.32
87.50
89.81
88.86
90.38
80.57
73.75
57.71
70.95
80.14
15.87
39.16
36.75
37.12
53.75
29. 16; 20.84
82.48; 79.31
38.20
42.41
40.95
50.01; 53.78
85.07; 87.90
75.84
" Based on the water and lipid content in 100 grams, edible portion.
For additional information, consult the USDA nutrient database.
Source:
USDA, 2007.
3.25
4.38
0.97
1.92
0.25
11.50
19.31
37.00
20.96
12.00
81.11
31.25
33.14
27.80
34.87
25. 83; 28.61
1.02; 1.93
32.11
28.74
26.62
22.35; 15.92
1.55; 3. 25
9.94
3.25% milkfat
Whole, mature, fluid
Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A
Fluid
Fluid
Fluid
Cultured
Cultured
Salted
Pasteurized
Hard; grated
l%fat; 2% fat
Whole milk; Skim milk
Plain, lowfat; Plain, with fat
Chicken, whole raw, fresh
Total Fat Content = saturated, monosaturated and
polyunsaturated.
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
APPENDIX 11A
CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS MEATS AND
DAIRY PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
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September 2008 11A-1
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11A-1
Food Category
Total Meats
Total Dairy
Food Codes and Definitions Used in Analysis of the 1994-96,
1998 USDACSFII Data
EPA Food Commodity Codes
21000440
21000441
21000450
21000460
21000461
21000470
21000471
23001730
24001890
25002900
25002901
25002910
25002920
25002921
25002930
25002931
25002940
25002950
26003390
26003391
26003400
26003410
26003411
26003420
26003430
28002210
29003120
40000930
40000931
40000940
27002220
27002221
27012230
27012231
27022240
Beef, meat
Beef, meat-babyfood
Beef, meat, dried
Beef, meat byproducts
Beef, meat byproducts-babyfood
Beef, fat
Beef, fat-babyfood
Goat, liver
Horse, meat
Pork, meat
Pork, meat-babyfood
Pork, skin
Pork, meat byproducts
Pork, meat byproducts-babyfood
Pork, fat
Pork, fat-babyfood
Pork, kidney
Pork, liver
Sheep, meat
Sheep, meat-babyfood
Sheep, meat byproducts
Sheep, fat
Sheep, fat-babyfood
Sheep, kidney
Sheep, liver
Meat, game
Rabbit, meat
Chicken, meat
Chicken, meat-babyfood
Chicken, liver
Milk, fat
Milk, fat - baby food/infant formula
Milk, non-fat solids
Milk, non-fat solids-baby food/infant
formula
Milk, water
21000480
21000490
21000491
23001690
23001700
23001710
23001720
40000950
40000951
40000960
40000961
40000970
40000971
50003820
50003821
50003830
50003831
50003840
50003841
50003850
50003851
50003860
50003861
60003010
60003020
60003030
60003040
60003050
27022241
27032251
Beef, kidney
Beef, liver
Beef, liver-babyfood
Goat, meat
Goat, meat byproducts
Goat, fat
Goat, kidney
Chicken, meat byproducts
Chicken, meat byproducts-babyfood
Chicken, fat
Chicken, fat-babyfood
Chicken, skin
Chicken, skin-babyfood
Turkey, meat
Turkey, meat-babyfood
Turkey, liver
Turkey, liver-babyfood
Turkey, meat byproducts
Turkey, meat byproducts-babyfood
Turkey, fat
Turkey, fat-babyfood
Turkey, skin
Turkey, skin-babyfood
Poultry, other, meat
Poultry, other, liver
Poultry, other, meat byproducts
Poultry, other, fat
Poultry, other, skin
Milk, water-babyfood/infant formula
Milk, sugar (lactose)-baby food
formula
infant
Page
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1A-1 Food Codes and Definitions Used in Analysis of the
Food Category
Beef
Eggs
Pork
Poultry
1994-96, 1998
USDA CSFII Data (continued)
EPA Food Commodity Codes
21000440
21000441
21000450
21000460
21000461
70001450
70001451
70001460
25002900
25002901
25002910
25002920
25002921
40000930
40000931
40000940
40000950
40000951
40000960
40000961
40000970
40000971
50003820
50003821
50003830
Beef, meat
Beef, meat-babyfood
Beef, meat, dried
Beef, meat byproducts
Beef, meat byproducts-babyfood
Egg, whole
Egg, whole-babyfood
Egg, white
Pork, meat
Pork, meat-babyfood
Pork, skin
Pork, meat byproducts
Pork, meat byproducts-babyfood
Chicken, meat
Chicken, meat-babyfood
Chicken, liver
Chicken, meat byproducts
Chicken, meat byproducts-babyfood
Chicken, fat
Chicken, fat-babyfood
Chicken, skin
Chicken, skin-babyfood
Turkey, meat
Turkey, meat-babyfood
Turkey, liver
21000470
21000471
21000480
21000490
21000491
70001461
70001470
70001471
25002930
25002931
25002940
25002950
50003831
50003840
50003841
50003850
50003851
50003860
50003861
60003010
60003020
60003030
60003040
60003050
Beef, fat
Beef, fat-babyfood
Beef, kidney
Beef, liver
Beef, liver-babyfood
Egg, white (solids)-babyfood
Egg, yolk
Egg, yolk-babyfood
Pork, fat
Pork, fat-babyfood
Pork, kidney
Pork, liver
Turkey, liver-babyfood
Turkey, meat byproducts
Turkey, meat byproducts-babyfood
Turkey, fat
Turkey, fat-babyfood
Turkey, skin
Turkey, skin-babyfood
Poultry, other, meat
Poultry, other, liver
Poultry, other, meat byproducts
Poultry, other, fat
Poultry, other, skin
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
APPENDIX 11B
SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED
ON CDC (1994) DATA
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September 2008 11B-1
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Child-Specific Exposure Factors Handbook
Chapter 11 - Intake of Meats, Dairy Products and Fats
Sample Calculation of Mean Daily Fat Intake Based on
CDC (1994) Data
CDC (1994) provided data on the mean daily
total food energy intake (TFEI) and the mean
percentages of TFEI from total dietary fat grouped by
age and gender. The overall mean daily TFEI was
2,095 kcal for the total population and 34 percent (or 82
g) of their TFEI was from total dietary fat (CDC, 1994).
Based on this information, the amount of fat per kcal
was calculated as shown in the following example.
where 0.34 is the fraction of fat intake, 2,095 is the total
food intake, and X is the conversion factor from
kcal/day to g-fat/day.
Using the conversion factor shown above
(i.e., 0.12 g-fat/kcal) and the information on the mean
daily TFEI and percentage of TFEI for the various
age/gender groups, the daily fat intake was calculated
for these groups. An example of obtaining the grams of
fat from the daily TFEI (1,591 kcal/day) for children
ages 3-5 years and their percent TFEI from total dietary
fat (33 percent) is as follows:
0.34 x 2,095
day
x X
day
= 82
day
1,591
kcal
day
x 0.33 x 0.12
kcal
= 63
day
X = 0.12
g-fat
kcal
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
TABLE OF CONTENTS
5 SOIL AND DUST INGESTION
5.1
5.2
5.3
5.4
INTRODUCTION
RECOMMENDATIONS
KEY AND RELEVANT STUDIES
5.3.1 Methodologies Used in Key Studies
5.3.1.1 Tracer Element Methodology
5.3.1.2 Biokinetic Model Comparison Methodology
5.3.1.3 Survey Response Methodology
5.3.2 Key Studies of Primary Analysis
5.3.2.1 Vermeer and Frate, 1979
5.3.2.2 Calabrese et al., 1989/Barnes, 1990/Calabrese et al., 1991
5.3.2.3 Van Wijnen et al., 1990
5.3.2.4 Davis et al., 1990
5.3.2.5 Calabrese et al., 1997a
5.3.2.6 Stanek et al. 1998/Calabrese et al., 1997b
5.3.2.7 Davis and Mirick, 2006
5.3.3 Key Studies of Secondary Analysis
5.3.3.1 Wong, 1988/Calabrese and Stanek, 1993
5.3.3.2 Hogan et al., 1998
5.3.4 Relevant Studies of Primary Analysis
5.3.4.1 Dickins and Ford, 1942
5.3.4.2 Cooper, 1957
5.3.4.3 Barltrop, 1966
5.3.4.4 Bruhn and Pangborn, 1971
5.3.4.5 Robischon, 1971
5.3.4.6 Binder et al., 1986
5.3.4.7 Clausing, et al., 1987
5.3.4.8 Smulian et al., 1995
5.3.5 Relevant Studies of Secondary Analysis
5.3.5.1 Stanek et al., 2001a
5.3.5.2 Calabrese and Stanek, 1995
5.3.5.3 Stanek and Calabrese, 1995a
5.3.5.4 Calabrese and Stanek, 1992b
5.3.5.5 Calabrese et al., 1996
5.3.5.6 Stanek et al., 1999
5.3.5.7 Stanek and Calabrese, 1995b
5.3.5.8 Stanek and Calabrese, 2000
5.3.5.9 Stanek et al., 2001b
5.3.5.10 von Lindern et al., 2003
LIMITATIONS OF KEY STUDY METHODOLOGIES
5.4.1 Tracer Element Methodology
5.4.2 Biokinetic Model Comparison Methodology
5.4.3 Survey Response Methodology
5.4.4 Key Studies: Representativeness of U.S. Population
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Chapter 5 - Ingestion of Soil and Dust
5.5 SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES 5-25
5.6 REFERENCES FOR CHAPTER 5 5-26
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
LIST OF TABLES
Table 5-1. Recommended Values for Soil, Dust, and Soil + Dust Ingestion 5-5
Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust 5-6
Table 5-3. Soil, Dust and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
Children 5-31
Table 5-4. Amherst, Massachusetts Soil-Pica Child's Daily Ingestion Estimates by Tracer and by
Week (mg/day) 5-32
Table 5-5. Amherst, Massachusetts Soil-Pica Child's Tracer Ratios 5-33
Table 5-6. Van W'ijnen et al., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for
Sample of Dutch Children 5-34
Table 5-7. Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children
Attending Daycare Centers According to Age, Weather Category, and Sampling
Period 5-35
Table 5-8. Estimated Soil Ingestion for Sample of Washington State Children 5-35
Table 5-9. Soil Ingestion Estimates for 64 Anaconda Children 5-36
Table 5-10. Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior
(mg/day) 5-36
Table 5-11. Soil Ingestion Estimates for Sample of 12 Washington State Children 5-37
Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children 5-38
Table 5-13. Estimated Daily Soil Ingestion for East Helena, Montana Children 5-39
Table 5-14. Estimated Soil Ingestion for Sample of Dutch Nursery School Children 5-39
Table 5-15. Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children 5-40
Table 5-16. Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
Study: Effect on Mean Soil Ingestion Estimate (mg/day) 5-40
Table 5-17. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64
Children (mg/day) 5-41
Table 5-18. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects
Projected over 365 Days 5-41
Table 5- 19. Summary of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from
Key Studies (mg/day) 5-42
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
5 SOIL AND DUST INGESTION
5.1 INTRODUCTION
The ingestion of soil and dust is a potential
route of exposure to environmental chemicals.
Children may ingest significant quantities of soil, due
to their tendency to play on the floor indoors and on the
ground outdoors and their tendency to mouth objects or
their hands. Children may also ingest soil and dust
through deliberate hand to mouth movements, or
unintentionally by eating food that has dropped on the
floor. Thus, understanding soil and dust ingestion
patterns is an important part of estimating children's
overall exposures to environmental chemicals.
At this point in time, knowledge of soil and
dust ingestion patterns within the United States is
somewhat limited. Only a few researchers have
attempted to quantify soil and dust ingestion patterns in
U.S. children. This chapter explains the concepts of
soil ingestion, soil pica, and geophagy, defines these
terms for the purpose of this handbook's exposure
factors, and presents available data from the literature
on the amount of soil and dust ingested.
The Centers for Disease Control and
Prevention's Agency for Toxic Substances and Disease
Registry (ATSDR) held a workshop in June 2000 in
which a panel of soil ingestion experts developed
definitions for soil ingestion, soil-pica, and geophagy,
to distinguish aspects of soil ingestion patterns that are
important from a research perspective (ATSDR, 2001).
This chapter uses the definitions that are based on those
developed by participants in that workshop:
Soil ingestion is the consumption of soil.
This may result from various behaviors
including, but not limited to, mouthing,
contacting dirty hands, eating dropped food,
or consuming soil directly.
Soil-pica is the recurrent ingestion of
unusually high amounts of soil (i.e., on the
order of 1,000 - 5,000 mg/day or more).
Geophagy is the intentional ingestion of
earths and is usually associated with cultural
practices.
Some studies are of a behavior known as
"pica," and the subset of "pica" that consists of
ingesting soil. A general definition of the concept of
pica is that of ingesting non-food substances, or
ingesting large quantities of certain particular foods.
Definitions of pica often include references to recurring
or repeated ingestion of these substances. Soil-pica is
pica that is specific to ingesting materials that are
defined as soil, such as clays, yard soil, and flower-pot
soil. Researchers in many different disciplines have
hypothesized motivations for human soil-pica or
geophagy behavior, including alleviating nutritional
deficiencies, a desire to remove toxins or self-medicate,
and other physiological or cultural influences (e.g.,
Danford, 1982). Bruhn and Pangborn (1971) and
Harris and Harper (1997) suggest a religious context for
certain geophagy or soil ingestion practices. Some
researchers have investigated subpopulations of
children who may be more likely than other children to
exhibit soil-pica behavior on a recurring basis. These
subpopulations might include children who practice
geophagy (Vermeer and Frate, 1979), institutionalized
children (Wong, 1988), and children with
developmental delays (Danford, 1983), autism (Kinnell,
1985), or celiac disease (Korman, 1990). However,
identifying specific soil-pica and geophagy
subpopulations remains difficult due to limited research
on this topic.
In this handbook, soil, indoor settled and
outdoor settled dust, and dust ingestion are defined
generally as:
Soil. Particles of unconsolidated mineral
and/or organic matter from the earth's surface
that are located outdoors, or are used indoors
to support plant growth. It includes particles
that have settled onto outdoor objects and
surfaces (outdoor settled dust).
Indoor Settled Dust. Particles in building
interiors that have settled onto objects,
surfaces, floors, and carpeting. These
particles may include soil particles that have
been tracked into the indoor environment from
outdoors as well as organic matter.
Outdoor Settled Dust. Particles that have
settled onto outdoor objects and surfaces due
to either wet or dry deposition. Note that it is
not possible to distinguish between soil and
outdoor settled dust, since outdoor settled dust
generally would be present on the uppermost
surface layer of soil.
For the purposes of this handbook, soil ingestion
includes both soil and outdoor settled dust, and dust
ingestion includes indoor settled dust only.
There are several methodologies represented
in the literature related to soil and dust ingestion by
children. Three methodologies combine biomarker
measurements with measurements of the biomarker
substance's presence in environmental media. A fourth
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methodology offers indirect evidence of soil/dust
ingestion behaviors from the responses of caregivers
and/or children to survey questions.
The first of the biomarker methodologies
measures quantities of specific elements present in
children's feces, urine, food and medications, yard soil,
house dust, and sometimes also community soil and
dust, and combines this information using certain
assumptions about the elements' behavior in the
gastrointestinal tract to produce estimates of soil and
dust quantities ingested (e.g., Davis et al., 1990). In
this chapter, this methodology is referred to as the
"tracer element" methodology. The second biomarker
methodology compares results from a biokinetic model
of lead exposure and uptake that predict children's
blood lead levels, with biomarker measurements of lead
in children's blood (e.g., von Lindern et al., 2003). The
model predictions are made using assumptions about
ingested soil and dust quantities that are based, in part,
on results from early versions of the first methodology.
Therefore, the comparison with actual measured blood
lead levels serves to confirm, to some extent, the
assumptions about ingested soil and dust quantities
used in the biokinetic model. In this chapter, this
methodology is referred to as the "biokinetic model
comparison" methodology. The third biomarker
methodology, the "lead isotope ratio" methodology,
involves measurements of different lead isotopes in
children's blood and/or urine, food, water, and house
dust and compares the ratio of different lead isotopes to
infer sources of lead exposure that may include dust or
other environmental exposures (e.g., Manton et al.,
2000). In the fourth, "survey response" methodology,
responses to survey questions regarding soil and dust
ingestion are analyzed. This methodology includes
questions asked of children directly, or their caregivers,
about soil and dust ingestion behaviors, frequency, and
sometimes quantity (e.g., Barltrop, 1966).
Although not directly evaluated in this chapter,
a fifth methodology uses assumptions regarding
ingested quantities of soil and dust that are based on
general knowledge of children's behavior, and
potentially supplemented or informed by data from
other methodologies (e.g., Hawley, 1985; Kissel et al.,
1998; Wong et al., 2000).
The recommendations for soil, dust, and soil
+ dust ingestion rates are provided in the next section,
along with a summary of the confidence ratings for
these recommendations. The recommended values are
based on key studies identified by U.S. EPA for this
factor. Following the recommendations, key studies on
soil and dust ingestion are summarized. Summaries of
the relevant studies, methodology descriptions and
methodological strengths and limitations are also
provided.
5.2 RECOMMENDATIONS
The key studies described in Section 5.3 were
used to recommend values for soil and dust ingestion
among children. The key studies pre-dated the age
groups recommended by U.S. EPA (2005) and were
performed on groups of children of varying ages. As a
result, central tendency recommendations can be used
for the life stage categories of 6 to <12 months, 1 to <2
years, 2 to <3 years, 3 to <6 years, and part of the 6 to
<11 years categories. Upper percentile
recommendations can be used for the life stage
categories of 1 to <2 years, 2 to <3 years, 3 to <6 years,
6 to <11 years, and part or all of the 11 to <16 years
category. Due to the current state of research on soil
and dust ingestion, the upper percentile
recommendations are called "soil-pica" or "geophagy"
recommendations that are likely to represent high soil
ingestion episodes or behaviors at an unknown point on
the high end of the distribution of soil ingestion.
The soil ingestion recommendations in Table
5-1 are intended to represent ingestion of a combination
of soil and outdoor settled dust, without distinguishing
between these two sources. The source of the soil in
these recommendations could be outdoor soil, indoor
containerized soil used to support growth of indoor
plants, or a combination of both outdoor soil and
containerized indoor soil. These recommendations are
called "soil." The dust ingestion recommendations in
Table 5-1 include soil tracked into the indoor setting,
indoor settled dust and air-suspended particulate matter
that is inhaled and swallowed. Central tendency "dust"
recommendations are provided, in the event that
assessors need recommendations for an indoor or inside
a transportation vehicle scenario in which dust, but not
outdoor soil, is the exposure medium of concern. The
soil + dust recommendations would include soil, either
from outdoor or containerized indoor sources, dust that
is a combination of outdoor settled dust, indoor settled
dust, and air-suspended particulate matter that is
inhaled, subsequently trapped in mucous and moved
from the respiratory system to the gastrointestinal tract,
and a soil-origin material located on indoor floor
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surfaces that was tracked indoors by building
occupants. Soil and dust recommendations exclude the
soil or dust's moisture content. In other words,
recommended values represent mass of ingested soil or
dust that is represented on a dry weight basis.
Table 5-1 shows the central tendency
recommendations for daily ingestion of soil, dust, or
soil + dust, in mg/day. It also shows the soil-pica or
geophagy recommendations for daily ingestion of soil,
in mg/day. No data are available on which to base
comparable upper percentile recommendations for
"dust" or "soil + dust." Published estimates from the
key studies have been rounded to one significant figure.
The recommended central tendency soil + dust
ingestion estimate for infants from 6 months up to their
first birthday is 60 mg/day. If an estimate is needed for
soil only, from outdoor or indoor sources, or both
outdoor and indoor sources, the recommendation is 30
mg/day. If an estimate for indoor dust only is needed,
that would include a certain quantity of tracked-in soil
from outside, the recommendation is 30 mg/day. The
confidence rating for this recommendation is low due to
the small numbers of study subjects in the study on
which the recommendation is based and the inferences
needed to develop a quantitative estimate. Examples of
these inferences include: an assumption that the relative
proportions of soil and dust ingested by 6 to 12 month
old children is the same as the central tendency
assumption for older children (45 percent soil, 55
percent dust, based on U.S. EPA (1994a)), and the
assumption that pre-natal or non-soil, non-dust sources
of lead exposure do not dominate these children's blood
lead levels.
When assessing risks for children who are not
expected to exhibit soil-pica or geophagy behavior, the
recommended central tendency soil + dust ingestion
estimate is 100 mg/day for children ages 1 to <6 years.
If an estimate for soil only is needed, for exposure to
soil such as manufactured topsoil or potted-plant soil
that could occur in either an indoor or outdoor setting,
or when the risk assessment is not considering
children's ingestion of indoor dust (in an indoor setting)
as well, the recommendation is 50 mg/day. If an
estimate for indoor dust only is needed, the
recommendation is 60 mg/day. Although these
quantities add up to 110 mg/day, the sum is rounded to
one significant figure. Although there were no tracer
element studies orbiokinetic model comparison studies
performed for children 6 to < 21 years, as a group, their
mean or central tendency soil ingestion would not be
zero. In the absence of data that can be used to develop
specific central tendency soil and dust ingestion
recommendations for children aged 6 to <11 years, 11
to <16 years and 16 to <21 years, U.S. EPA
recommends using the same central tendency soil and
dust ingestion rates that are recommended for children
in the 1 to < 6 year old age range.
When assessing risks for children who may
exhibit soil-pica behavior, or a group of children that
includes individual children who may exhibit soil-pica
behavior, the soil-pica ingestion estimate for children
up to age 14 ranges from 400 to 41,000 mg/day. Due to
the definition of soil-pica used in this chapter, that sets
a lower bound on the quantity referred to as "soil-pica"
at 1,000 mg/day, and due to the significant number of
observations in the U.S. tracer element studies that are
at or exceed that quantity, the recommended soil-pica
ingestion rate is 1,000 mg/day. Currently, no data are
available for upper percentile, soil-pica behavior for
children ages 16 to <21 years. Because pica behavior
may occur among some children ages ~1 to 21 years
old (Hyman et al., 1990), it is prudent to assume that,
for some children, soil-pica behavior may occur at any
age up to <21 years.
The recommended geophagy soil estimate is
50,000 mg/day (50 grams). Risk assessors should use
this value for soil ingestion in areas where residents are
known to exhibit geophagy behaviors.
These recommendations are not robust enough
for use in probabilistic risk assessments.
Table 5-2 shows the confidence ratings for
these recommendations. Section 5.4 gives a more
detailed explanation of the basis for the confidence
ratings.
An important factor to consider when using
these recommendations is that they are limited to
estimates of soil and dust quantities ingested. The
scope of this chapter is limited to quantities of soil and
dust taken into the gastrointestinal tract, and does not
extend to issues regarding bioavailability of
environmental contaminants present in that soil and
dust. Information from other sources is needed to
address bioavailability. In addition, as more
information becomes available regarding
gastrointestinal absorption of environmental
contaminants, adjustments to the soil and dust ingestion
exposure equations may need to be made, to better
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represent the direction of movement of those
contaminants within the gastrointestinal tract.
To place these recommendations into context,
it is useful to compare these soil ingestion rates to
common measurements. The bulk densities of surface
soils are often in the range of 1.3 to 1.7 g/cm3. U.S.
EPA (1996) recommends using 1.5 g/cm3 as a default
value for dry soil bulk density. The central tendency
recommendation of 50 mg/day, or 0.050 g/day, dry
weight basis, with a 1.5 g/cm3 bulk density would be
equivalent to approximately 0.03 cm3. A teaspoon is
approximately 5 cm3 in volume, so the 50 mg/day
quantity would be roughly equivalent to seven
thousandths of a teaspoon per day. The 50 g/day
ingestion rate recommended to represent geophagy
behavior would be roughly equivalent to 5 to 7
teaspoons per day in volume.
Indoor settled dust could be expected to have
a lower dry bulk density than the surface soil bulk
density cited above (for example, bulk densities of five
grain dusts are reported by Parnell et al. (1986) to be
0.15-0.31 g/cm3, "specific density" of Danish office
building dust is reported by M01have et al. (2000) to be
1.0 gm/cm3). Thus, volumes of indoor settled dust
could be expected to weigh less than comparable
volumes of surface soil. The central tendency "dust"
recommendation for children of 60 mg/day, or 0.060
g/day, dry weight basis, with a 1.0 g/cm3 bulk density
would be equivalent to approximately 0.06 cm3, or
roughly equivalent to twelve thousandths of a teaspoon
per day.
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Table 5-1 . Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion
6 to
1 to
6 to
Age Group
<12 months
< 6 years
<21 years
Soil" Dust"
Upper Percentile
(mg/day) Soil-Pica Geophagy (mg/day)
(mg/day) (mg/day)
30 - - 30
50 1,000 50,000 60
50 1,000 50,000 60
Soil + Dust
(mg/day)
60
100°
100°
No recommendation.
a Includes soil and outdoor settled dust.
b Includes indoor settled dust only.
c
Total
soil and dust ingestion rate is 1 10 mg/day; rounded to one significant figure it is 100 mg/day.
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Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust
General Assessment Factors Rationale Rating
Soundness Low
Adequacy of Approach The methodologies have significant limitations. The studies did not capture all of the
information needed (quantities ingested, frequency of high soil ingestion episodes,
prevalence of high soil ingestion). Four of the 9 studies were of census or randomized
design. Sample selection may have introduced some bias in the results (i.e., children near
smelter or Superfund sites, volunteers in nursery schools). The total number of children
in key studies was 1,203 (859 U.S. children, 292 Dutch, and 52 Jamaican children), while
the target population currently numbers more than 74 million (U.S. DOC, 2008). The
response rates for in-person interviews and telephone surveys were often not stated in
published articles. Primary data were collected for 381 U.S. children and 292 Dutch
children; secondary data for 478 U.S. children and 52 Jamaican children.
Numerous sources of measurement error exist in the tracer element studies. Biokinetic
Minimal (or defined) Bias model comparison study may contain less measurement error than tracer element studies.
Survey response study may contain measurement error.
Applicability and Utility Low
Exposure Factor of Interest 8 of the 9 key studies focused on the soil exposure factor, with no or less focus on the
dust exposure factor. Biokinetic model comparison study did not focus exclusively on
soil and dust exposure factors.
Representativeness The study samples may not be representative of the U.S. in terms of race, ethnicity,
socio-economics, and geographical location; studies focused on specific areas.
Currency Studies results are likely to represent current conditions.
Data Collection Period Tracer element studies' data collection periods may not represent long-term behaviors.
Biokinetic model comparison and survey response studies do represent longer term
behaviors.
Clarity and Completeness Low
Accessibility Observations for individual children are available for only 3 of the 9 key studies.
Reproducibility For the methodologies used by more than one research group, reproducible results were
obtained in some instances. Some methodologies have been used by only one research
group and have not been reproduced by others.
Quality Assurance For some studies, information on quality assurance/quality control was limited or absent.
Variability and Uncertainty Low
Variability in Population Tracer element studies characterized variability among study sample members; biokinetic
model comparison and survey response studies did not. Day-to-day and seasonal
variability was not very well characterized. Numerous factors that may influence
variability have not been explored in detail.
Minimal Uncertainty Estimates are highly uncertain. Tracer element studies' design appears to introduces
biases in the results.
Evaluation and Review Medium
Peer Review All key studies appeared in peer review journals.
Number and Agreement of 9 key studies. Researchers using similar methodologies obtained generally similar
Studies results; somewhat general agreement between researchers using different
methodologies.
Overall Rating Low
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5.3 KEY AND RELEVANT STUDIES
The key tracer element, biokinetic model
comparison, and survey response studies are
summarized in the following sections. Certain studies
were considered "key" and were used as a basis for
developing the recommendations, using judgment about
the study's design features, applicability, and utility of
the data to U.S. children's soil and dust ingestion rates,
clarity and completeness, and characterization of
uncertainty and variability in ingestion estimates.
Because the studies often were performed for reasons
unrelated to developing soil and dust ingestion
recommendations, their attributes that were
characterized as "limitations" in this chapter might not
be limitations when viewed in the context of the study's
original purpose. However, when studies are used for
developing a soil or dust ingestion recommendation,
U.S. EPA has categorized some studies' design or
implementation as preferable to other studies' design or
implementation. In general, U.S. EPA chose studies
designed either with a census, or randomized sample,
approach, over studies that used a convenience sample
or other, non-randomized, approach, as well as studies
that more clearly explained various factors in the
study's implementation that affect interpretation of the
results. However, in some cases, studies that used a
non-randomized design contain information that is
useful for developing expo sure factor recommendations
(for example, if they are the only studies of children in
a particular age category), and thus may have been
designated as "key" studies. Other studies were
considered "relevant" but not "key" because they
provide useful information for evaluating the
reasonableness of the data in the key studies, but in
U.S. EPA's judgment they did not meet the same level
of soundness, applicability and utility, clarity and
completeness, and characterization of uncertainty and
variability that the key studies did. In addition, studies
that did not contain information that can be used to
develop a specific recommendation formg/day soil and
dust ingestion were classified as relevant rather than
key.
Some studies are re-analyses of data
previously published. For this reason, the sections that
follow are organized into key and relevant studies of
primary analysis (that is, studies in which researchers
have developed primary data pertaining to soil and dust
ingestion) and key and relevant studies of secondary
analysis (that is, studies in which researchers have
interpreted previously published results, or data that
were originally collected for a different purpose).
5.3.1 Methodologies Used in Key Studies
5.3.1.1 Tracer Element Methodology
The tracer element methodology attempts to
quantify the amounts of soil ingested by analyzing
samples of soil and dust from children's residences
and/or play areas, and the children's feces, and
sometimes also urine. The soil, dust, fecal, and urine
samples are analyzed for the presence and quantity of
tracer elements - typically, aluminum, silicon, titanium,
and other elements. A key underlying assumption is
that these elements are not metabolized into other
substances in the body or absorbed from the
gastrointestinal tract in significant quantities, and thus
their presence in feces and urine can be used to estimate
the quantity of soil ingested by mouth. Although they
are sometimes called mass balance studies, none of the
studies attempt to quantify amounts excreted in
perspiration, tears, glandular secretions, or shed skin,
hair or finger- and toe-nails, nor do they account for
tracer element exposure via the dermal or inhalation
into the lung routes, and thus they are not a complete
"mass balance" methodology. Early studies using this
methodology did not always account for the
contribution of tracer elements from non-soil
substances (food, medications, and non-food sources
such as toothpaste) that children might swallow. U.S.
studies using this methodology in or after the mid to
late 1980s account for, or attempt to account for, tracer
element contributions from these non-soil sources.
Some study authors adjust their soil ingestion estimate
results to account for the potential contribution of tracer
elements found in household dust as well as soil.
The general algorithm that is used to calculate
the quantity of soil or dust estimated to have been
ingested by each child is as follows: the quantity of a
given tracer element, in milligrams, present in the
child's feces and urine, minus the quantity of that tracer
element, in milligrams, present in the child's food and
medicine, the result of which is divided by the tracer
element's soil concentration, in milligrams oftracerper
gram of soil, to yield an estimate of ingested soil, in
grams.
The U.S. tracer element researchers have all
assumed a certain offset, or lag time between ingestion
of food, medication and soil, and the resulting fecal and
urinary output. The lag times used are typically 24 or
28 hours; thus, these researchers subtract the previous
day's food and medication tracer element quantity
ingested from the current day's fecal and urinary tracer
element quantity that was excreted. When compositing
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food, medication, fecal and urine samples across the
entire study period, daily estimates can be obtained by
dividing the total estimated soil ingestion by the
number of days in which fecal and/or urine samples
were collected. A variation of the algorithm that
provides slightly higher estimates of soil ingestion is to
divide the total estimated soil ingestion by the number
of days on which feces were produced, which by
definition would be equal to or less than the total
number of days of the study period's fecal sample
collection.
Substituting tracer element dust concentrations
for tracer element soil concentrations yields a dust
ingestion estimate. Because the actual non-food, non-
medication quantity ingested is a combination of soil
and dust, the unknown true soil and dust ingestion is
likely to be somewhere between the estimates that are
based on soil concentrations and estimates that are
based on dust concentrations. Tracer element
researchers have described ingestion estimates for soil
that actually represent a combination of soil and dust,
but were calculated based on tracer element
concentrations in soil. Similarly, they have described
ingestion estimates for dust that are actually for a
combination of soil and dust but were calculated based
on tracer element concentrations in dust. Other
variations on these general soil and dust ingestion
algorithms have been published, in attempts to account
for time spent indoors, time spent away from the house,
etc. that could be expected to influence the relative
proportion of soil vs. dust.
Each child's soil and dust ingestion can be
represented as an unknown constant in a set of
simultaneous equations of soil or dust ingestion
represented by different tracer elements. To date, only
one of the U.S. research teams (Lasztity et al., 1989)
has published estimates calculated for pairs of tracer
elements using simultaneous equations.
The U.S. tracer element studies have been
performed for only short-duration study periods, and
only for 241 children (101 in Davis et al., 1990, 12 of
whom were studied again in Davis and Mirick, 2006;
64 in Calabrese et al., 1989/Barnes 1990; 64 in
Calabrese et al., 1997a; and 12 in Calabrese et al.,
1997b). They provide information on quantities of soil
and dust ingested for the studied groups of children for
short time periods, but provide limited information on
overall prevalence of soil ingestion by U.S. children,
and limited information on the frequency of higher soil
ingestion episodes.
The tracer element studies appear to contain
numerous sources of error that influence the estimates
upward and downward. Sometimes the error sources
cause individual children's soil or dust ingestion
estimates to be negative, which is not physically
possible. In some studies, for some of the tracers, so
many individual children's "mass balance" soil
ingestion estimates were negative that median or mean
estimates based on that tracer were negative. For soil
and dust ingestion estimates based on each particular
tracer, or averaged across tracers, the net impact of
these competing upward and downward sources of error
is unclear.
5.3.1.2 Siokinetic Model Comparison Methodology
The Biokinetic Model Comparison
methodology compares direct measurements of a
biomarker, such as blood or urine levels of a toxicant,
with predictions from a biokinetic model of oral, dermal
and inhalation exposure routes with air, food, water,
soil, and dust toxicant sources. An example is to
compare children's measured blood lead levels with
predictions from the Integrated Exposure and Uptake
Biokinetic (IEUBK) model. Where environmental
contamination of lead in soil, dust, and drinking water
has been measured and those measurements can be used
as model inputs for the children in a specific
community, the model's assumed soil and dust
ingestion values can be confirmed or refuted by
comparing the model's predictions of blood lead levels
with those children's measured blood lead levels. It
should be noted, however, that such confirmation of the
predicted blood lead levels would be confirmation of
the net impact of all model inputs, and not just soil and
dust ingestions. Under the assumption that the actual
measured blood lead levels of various groups of
children studied have minimal error, and those
measured blood lead levels roughly match the
biokinetic model predictions for those groups of
children, then the model's default assumptions may be
roughly accurate for the central tendency, or typical,
children in an assessed group of children. The model's
default assumptions likely are not as useful for
predicting outcomes for highly exposed children.
5.3.1.3 Survey Response Methodology
The survey response methodology includes
studies that survey children's caretakers, or children
themselves, via in-person or mailed surveys that ask
about mouthing behavior and ingestion of various non-
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food items. Sometimes, questions about amounts
ingested are included in the survey instrument. There
could be either false positive or false negative
responses to these questions, for various reasons.
5.3.2 Key Studies of Primary Analysis
5.3.2.1 Vermeer and Frate, 1979 - Geophagia in
rural Mississippi: environmental and
cultural con texts andnu trition al implications
Vermeer and Frate (1979) performed a survey
response study in Holmes County, Mississippi in the
1970s (date unspecified). Questions about geophagy
(defined as regular consumption of clay over a period
of weeks) were asked of household members (N=229 in
50 households; 140 were children or adolescents) of a
subset of a random sample of nutrition survey
respondents. Caregiver responses to questions about
115 children under 13 indicate that geophagy was likely
to be practiced by a minimum of 18 (16 percent) of
these children; however, 16 of these 18 children were
1 to 4 years old, and only 2 of the 18 were older than 4
years. There was no reported geophagy among 25
adolescent study subjects questioned. The average
daily amount of clay consumed was reported to be
about 50 grams, for the 32 adult and 18 under-age-13
years child respondents who acknowledged practicing
geophagy. Quantities were usually described as either
portions or multiples of the amount that could be held
in a single, cupped hand. Clays for consumption were
generally obtained from the B soil horizon, or subsoil
rather than an uppermost layer, at a depth of 50 to 130
centimeters.
5.3.2.2 Calabrese et al., 1989 - How Much Soil Do
Young Children Ingest: An Epidemiologic
Study/Barnes, 1990 - Childhood Soil
Ingestion: How Much Dirt Do Kids
Eat?/Calabrese et al., 1991 - Evidence of
Soil-Pica Behaviour and Quantification of
Soil Ingested
Calabrese et al. (1989) and Barnes (1990)
studied soil ingestion among children using eight tracer
elements—aluminum, barium, manganese, silicon,
titanium, vanadium, yttrium, and zirconium. A non-
random sample of 30 male and 34 female 1, 2 and 3
year-olds from the greater Amherst, Massachusetts area
were studied, presumably in 1987. The children were
predominantly from two-parent households where the
parents were highly educated. The study was
conducted over a period of eight days spread over two
weeks. During each week, duplicate samples of food,
beverages, medicines, and vitamins were collected on
Monday through Wednesday, while excreta were
collected for four 24-hour cycles running from
Monday/Tuesday through Thursday/Friday. Soil and
dust samples were also collected from the child's home
and play area. Study participants were supplied with
toothpaste, baby cornstarch, diaper rash cream, and
soap with low levels of most of the tracer elements.
Fecal and urine samples, excluding wipes and toilet
paper, were also collected and analyzed for tracer
elements.
Table 5-3 shows the published mean soil
ingestion estimates ranging from -294 mg/day based on
manganese to 459 mg/day based on vanadium, median
soil ingestion estimates ranging from -261 mg/day
based on manganese to 96 mg/day based on vanadium,
and 95th percentile estimates ranged from 106 mg/day
based on yttrium to 1,903 mg/day based on vanadium.
Maximum daily soil ingestion estimates ranged from
1,391 mg/day based on zirconium to 7,281 mg/day
based on manganese. Dust ingestions calculated using
tracer concentrations in dust were often, but not always,
higher than soil ingestions calculated using tracer
concentrations in soil.
Data for the uppermost 23 subject-weeks (the
highest soil ingestion estimates, averaged over the four
days of excreta collection during each of the two
weeks) were published in Calabrese et al. (1991). One
child's soil-pica behavior was estimated in Barnes
(1990) using both the subtraction/division algorithm
and the simultaneous equations method. On two
particular days during the second week of the study
period, the child's aluminum-based soil ingestion
estimates were 19 g/day (18,700 mg/day) and 36 g/day
(35,600 mg/day), silicon-based soil ingestion estimates
were 20 g/day (20,000 mg/day) and 24 g/day (24,000),
and simultaneous-equation soil ingestion estimates
were 20 g/day (20,100 mg/day) and 23 g/day (23,100
mg/day) (Barnes 1990). By tracer, averaged across the
entire week, this child's estimates ranged from
approximately 10 to 14 g/day during the second week
of observation (Calabrese et al., 1991, shown in Table
5-4), and averaged 6 g/day across the entire study
period. Additional information about this child's
apparent ingestion of soil vs. dust during the study
period, shown in Table 5-5, was published in Calabrese
and Stanek(1992a).
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5.3.2.3 Van W'ijnen et al., 1990 - Estimated Soil
Ingestion by Children
In a tracer element study by Van W'ijnen et al.
(1990), soil ingestion among Dutch children ranging in
age from 1 to 5 years was evaluated using a tracer
element methodology. Van W'ijnen et al. (1990)
measured three tracers (titanium, aluminum, and acid
insoluble residue (AIR)) in soil and feces. The authors
estimated soil ingestion based on an assumption called
the Limiting Tracer Method (LTM), which assumed
that soil ingestion could not be higher than the lowest
value of the three tracers. LTM values represented soil
ingestion estimates that were not corrected for dietary
intake.
An average daily feces dry weight of 15 g was
assumed. A total of 292 children attending daycare
centers were studied during the first of two sampling
periods and 187 children were studied in the second
sampling period; 162 of these children were studied
during both periods (i.e., at the beginning and near the
end of the summer of 1986). A total of 78 children
were studied at campgrounds. The authors reported
geometric mean LTM values because soil ingestion
rates were found to be skewed and the log transformed
data were approximately normally distributed.
Geometric mean LTM values were estimated to be 111
mg/day for children in daycare centers and 174 mg/day
for children vacationing at campgrounds (Table 5-6).
For the 162 daycare center children studied during both
sampling periods the arithmetic mean LTM was 162
mg/day, and the median was 114 mg/day.
Fifteen hospitalized children were studied and
used as a control group. These children's LTM soil
ingestion estimates were 74 (geometric mean), 93
(mean), and 110 (median) mg/day. The authors
assumed the hospitalized children's soil ingestion
estimates represented dietary intake of tracer elements,
and used rounded 95 percent confidence limits on the
arithmetic mean, 70 to 120 mg/day, to correct the day-
care and campground children's LTM estimates for
dietary intake of tracers. Corrected soil ingestion rates
were 69 mg/day (162 mg/day minus 93 mg/day) for
daycare children and 120 mg/day (213 mg/day minus
93 mg/day) for campers. Corrected geometric mean
soil ingestion was estimated to range from 0 to 90
mg/day, with a 90th percentile value of up to 190
mg/day for the various age categories within the
daycare group and 30 to 200 mg/day, with a 90th
percentile value of up to 300 mg/day for the various age
categories within the camping group.
AIR was the limiting tracer in about 80 percent
of the samples. Among children attending daycare
centers, soil ingestion was also found to be higher when
the weather was good (i.e., <2 days/week precipitation)
than when the weather was bad (i.e., >4 days/week
precipitation (Table 5-7).
5.3.2.4 Davis et al., 1990 - Quantitative Estimates of
Soil Ingestion in Normal Children between
the Ages of 2 and 7 Years: Population-based
Estimates Using Aluminum, Silicon, and
Titanium as Soil Tracer Elements
Davis et al. (1990) used a tracer element
technique to estimate soil ingestion among children. In
this study, 104 children between the ages of 2 and 7
years were randomly selected from a three-city area in
southeastern Washington State. Soil and dust ingestion
was evaluated by analyzing soil and house dust, feces,
urine, and duplicate food, dietary supplement,
medication and mouthwash samples for aluminum,
silicon, and titanium. Data were collected for 101 of
the 104 children during July, August or September,
1987. In each family, data were collected over a seven
day period, with four days of excreta sample collection.
Participants were supplied with toothpaste with known
tracer element content. In addition, information on
dietary habits and demographics was collected in an
attempt to identify behavioral and demographic
characteristics that influence soil ingestion rates among
children. The amount of soil ingested on a daily basis
was estimated using equation 5-1:
Sl=(((DWf+ DWP) x Ef) + 2EJ - (DWax EJ (Eq. 5-1)
E.M
where:
S:,
DWf
DW,
DWfd
Efd
"soil
soil ingested for child i based on
tracer e (g);
feces dry weight (g);
feces dry weight on toilet paper (g);
tracer concentration in feces (ug/g);
tracer amount in urine (ug);
food dry weight (g);
tracer concentration in food (ug/g);
and
tracer concentration in soil (ug/g).
The soil ingestion rates were corrected by adding the
amount of tracer in vitamins and medications to the
amount of tracer in food, and adjusting the food, fecal
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and urine sample weights to account for missing
samples. Food, fecal and urine samples were
composited over a 4-day period, and estimates for daily
soil ingestion were obtained by dividing the 4 day
composited tracer quantities by 4.
Soil ingestion rates were highly variable,
especially those based on titanium. Mean daily soil
ingestion estimates were 38.9 mg/day for aluminum,
82.4 mg/day for silicon and 245.5 mg/day for titanium
(Table 5-8). Median values were 25 mg/day for
aluminum, 59 mg/day for silicon, and 81 mg/day for
titanium. The investigators also evaluated the extent to
which differences in tracer concentrations in house dust
and yard soil impacted estimated soil ingestion rates.
The value used in the denominator of the soil ingestion
estimate equation was recalculated to represent a
weighted average of the tracer concentration in yard
soil and house dust based on the proportion of time the
child spent indoors and outdoors, using an assumption
that the likelihood of ingesting soil outdoors was the
same as that of ingesting dust indoors. The adjusted
mean soil/dust ingestion rates were 64.5 mg/day for
aluminum, 160.0 mg/day for silicon, and 268.4 mg/day
for titanium. Adjusted median soil/dust ingestion rates
were: 51.8 mg/day for aluminum, 112.4 mg/day for
silicon, and 116.6 mg/day for titanium. The authors
investigated whether nine behavioral and demographic
factors could be used to predict soil ingestion, and
found family income less than $15,000/year and
swallowing toothpaste to be significant predictors with
silicon-based estimates; residing in one of the three
cities to be a significant predictor with aluminum-based
estimates, and washing the face before eating
significant for titanium-based estimates.
5.3.2.5 Calabrese et al. 1997a - Soil Ingestion
Estimates for Children Residing on a
Super fund Site
Calabrese et al. (1997a) estimated soil
ingestion rates for children residing on a Superfund site
using a methodology in which eight tracer elements
were analyzed. The methodology used in this study is
similar to that employed in Calabrese et al. (1989),
except that rather than using barium, manganese, and
vanadium as three of the eight tracers, the researchers
replaced them with cerium, lanthanum and neodymium.
A total of 64 children ages 1-3 years (36 male, 28
female) were selected for this study of the Anaconda,
Montana area. The study was conducted for seven
consecutive days during September or September and
October, apparently in 1992, shortly after soil was
removed and replaced in some residential yards in the
area. Duplicate samples of meals, beverages, and
over-the-counter medicines and vitamins were collected
over the seven day period, along with fecal samples. In
addition, soil and dust samples were collected from the
children's home and play areas. Toothpaste containing
nondetectable levels of the tracer elements, with the
exception of silica, was provided to all of the children.
Infants were provided with baby cornstarch, diaper rash
cream, and soap which were found to contain low levels
of tracer elements.
Calabrese et al. (1997a) estimated soil
ingestion by each tracer element, as shown in Table 5-
9.
5.3.2.6 Stanek et al. 1998 - Prevalence of Soil
Mouthing/Ingestion among Healthy
Children Aged 1 to 6/Calabrese et al. 1997b -
Soil Ingestion Rates in Children Identified by
Parental Observation as Likely High Soil
Ingesters
Stanek et al. (1998) conducted a survey
response study using in-person interviews of parents of
children attending well visits at three western
Massachusetts medical clinics in August, September
and October of 1992. Of 528 children ages 1 to 7 with
completed interviews, parents reported daily mouthing
or ingestion of sand and stones in 6 percent, daily
mouthing or ingestion of soil and dirt in 4 percent, and
daily mouthing or ingestion of dust, lint and dustballs in
1 percent. Parents reported more than weekly mouthing
or ingestion of sand and stones in 16 percent, more than
weekly mouthing or ingestion of soil and dirt in 10
percent, and more than weekly mouthing or ingestion of
dust, lint and dustballs in 3 percent. Parents reported
more than monthly mouthing or ingestion of sand and
stones in 27 percent, more than monthly mouthing or
ingestion of soil and dirt in 18 percent, and more than
monthly mouthing or ingestion of dust, lint and
dustballs in 6 percent.
Calabrese and colleagues performed a follow-
up tracer element study (Calabrese et al. 1997b) for a
subset (n= 12) of the Stanek et al. (1998) children whose
caregivers had reported daily sand/soil ingestion
(n=17). The time frame of the follow-up tracer study
relative to the original survey response study was not
stated; the study duration was 7 days. Of the 12
children in Calabrese et al. 1997b, one exhibited
behavior that the authors believed was clearly soil pica;
Table 5-10 shows estimated soil ingestion rates for this
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Chapter 5 - Ingestion of Soil and Dust
child during the study period. Estimated average daily
soil ingestion estimates (calculated based on soil tracer
element concentrations only) ranged from -0.015 to
+ 1.783 g/day based on aluminum, -0.046 to +0.931
g/day based on silicon, and -0.047 to +3.581 g/day
based on titanium. Estimated average daily dust
ingestion estimates (calculated based on dust tracer
element concentrations only) ranged from -0.039 to
+2.652 g/day based on aluminum, -0.028 to +3.145
g/day based on silicon, and -0.098 to +3.632 g/day
based on titanium. Calabrese et al. (1997b) question
the validity of retrospective caregiver reports of soil
pica on the basis of the tracer element results.
5.3.2.7 Davis and Mirick, 2006 - Soil ingestion in
children and adults in the same family
Davis and Mirick (2006) calculated soil
ingestion for children and adults in the same family
using a tracer element approach. Data were collected
in 1988, one year after the Davis etal. (1990) study was
conducted. Samples were collected and prepared for
laboratory analysis and then stored for a 12 year period
prior to tracer element quantification with laboratory
analysis. The 20 families in this study were a
nonrandom subset of the 104 families who participated
in the soil ingestion study by Davis et al. (1990), and
were chosen based on high compliance with the
previous study protocol and expressed willingness to
participate in a future study. Data collection issues
resulted in sufficiently complete data for only 19 of the
20 families consisting of a child participant from the
Davis et al. (1990) study ages 3 to 7, inclusive, and a
female and male parent or guardian living in the same
house. Duplicate samples of all food and medication
items consumed, and all feces excreted, were collected
for 11 consecutive days. Urine samples were collected
twice daily for 9 of the 11 days; for the remaining 2
days, attempts were made to collect full 24-hour urine
specimens. Soil and house dust samples were also
collected. Only 12 children had sufficiently complete
data for use in the soil and dust ingestion estimates.
Tracer elements for this study included
aluminum, silicon and titanium. Toothpaste was
supplied for use by study participants. In addition,
parents completed a daily diary of activities for
themselves and the participant child for 4 consecutive
days during the study period.
Children's estimated soil ingestion rates are
shown in Table 5-11. The mean and median estimates
for children for all three tracers ranged from 36.7 to
206.9 mg/day and 26.4 to 46.7 mg/day, respectively,
calculated by setting negative estimates to zero. These
estimates fall within the range of those reported by
Davis et al., 1990. Similar to the previous Davis et al.
study, the soil ingestion estimates were the highest for
titanium.
Only two of a number of children's behaviors
examined for their relationship to soil ingestion were
found to be associated with increased soil ingestion in
this study:
• reported eating of dirt; and
• hand washing before meals (based on 2 of 12
children who were reported not to wash hands
before eating).
Several typical childhood behaviors, however,
including thumb-sucking, furniture licking, and
carrying around a blanket or toy were not associated
with increased soil ingestion for the participating
children. When investigating correlations within the
same family, a child's soil ingestion rate was not found
to be associated with either parent's soil ingestion rate.
5.3.3 Key Studies of Secondary Analysis
5.3.3.1 Wong, 1988 - The Role of Environmental
and Host Behavioural Factors in
Determining Exposure to Infection with
Ascaris lumbricoides and Trichuris
Trichiura/Calabrese andStanek, 1993 -Soil
Pica: Not a Rare Event
Calabrese and Stanek (1993) reviewed a tracer
element study that was conducted by Wong (1988) to
estimate the amount of soil ingested by two groups of
children. Wong (1988) studied a total of 52 children in
two government institutions in Jamaica. The younger
group included 24 children with an average age of 3.1
years (range of 0.3 to 7.5 years). The older group
included 28 children with an average age of 7.2 years
(range of 1.8 to 14 years). One fecal sample was
collected each month from each subject over the four-
month study period. The amount of silicon in dry feces
was measured to estimate soil ingestion.
An unspecified number of daily fecal samples
were collected from a hospital control group of 30
children with an average age of 4.8 years (range of 0.3
to 12 years). Dry feces were observed to contain 1.45
percent silicon, or 14.5 mg Si per gram of dry feces.
This quantity was used to correct measured fecal silicon
from dietary sources. Fecal silicon quantities greater
than 1.45 percent in the 52 studied children were
interpreted as originating from soil ingestion.
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For the 28 children in the older group, soil
ingestion was estimated to be 58 mg/day, based on the
mean minus one outlier, and 1,520 mg/day, based on
the mean of all the children. The outlier was a child
with an estimated average soil ingestion rate of 41
g/day over the 4 months.
Estimates of soil ingestion were higher in the
younger group of 24 children. The mean soil ingestion
of all the children was 470 ± 370 mg/day. Due to some
sample losses, of the 24 children studied, only 15 had
samples for each of the 4 months of the study. Over the
entire 4-month study period, 9 of 84 samples (or 10.5
percent) yielded soil ingestion estimates in excess of 1
g/day.
Of the 52 children studied, 6 had one-day
estimates of more than 1,000 mg/day. The estimated
soil ingestion for these six children is shown in Table 5-
12. The article describes 5 of 24 (or 20.8 percent) in
the younger group of children as having a >1,000
mg/day estimate on at least one of the four study days;
in the older group one child is described in this manner.
A high degree of daily variability in soil ingestion was
observed among these six children; three showed soil-
pica behavior on 2, 3, and 4 days, respectively, with the
most consistent (4 out of 4 days) soil-pica child having
the highest estimated soil ingestion, 3.8 to 60.7 g/day.
5.3.3.2 Hogan et al., 1998 - Integrated Exposure
Uptake Siokinetic Model for Lead in
Children: Empirical Comparisons with
Epidemiologic Data
Hogan et al. (1998) used the biokinetic model
comparison methodology to review the measured blood
lead levels of 478 children. These children were a
subset of the entire population of children living in
three historic lead smelting communities, whose
environmental lead exposures (soil and dust lead levels)
had been collected as part of public health evaluations
in these communities.
The Integrated Exposure and Uptake
Biokinetic (IEUBK) model is a biokinetic model for
predicting children's blood lead levels that uses
measurements of lead content in house dust, soil,
drinking water, food and air, and child-specific
estimates of intake for each exposure medium (dust,
soil, drinking water, food and air). Model users can
also use default assumptions for the lead contents and
intake rates for each exposure medium when they do
not have specific information for each child.
Hogan et al. (1998) compared children's
measured blood lead levels with biokinetic model
predictions (IEUBK version 0.9 9d) of blood lead levels,
using the children's measured drinking water, soil, and
dust lead contamination levels together with default
IEUBK model inputs for soil and dust ingestion,
relative proportions of soil and dust ingestion, lead
bioavailability from soil and dust, and other model
parameters. Thus, the default soil and dust ingestion
rates in the model, and other default assumptions in the
model, were tested by comparing measured blood lead
levels with the model's predictions for those children's
blood lead levels.
For Palmerton, Pennsylvania (n=34), the
community-wide geometric mean measured blood lead
levels (6.8 ug/dl) were slightly over-predicted by the
model (7.5 ug/dl); for southeastern
Kansas/southwestern Missouri (n=l 11), the blood lead
levels (5.2 ug/dl) were slightly under-predicted (4.6
ug/dl), and for Madison County, Illinois (n=333), the
geometric mean measured blood lead levels matched
the model predictions (5.9 ug/dl measured and
predicted), with very slight differences in the 95 percent
confidence interval. These results suggest that the
default soil and dust ingestion rates used in this version
of the IEUBK model (approximately 50 mg/day soil
and 60 mg/day dust for a total soil + dust ingestion of
110 mg/day, averaged over children ages 1 through 6)
may be roughly accurate in representing the central
tendency soil and dust ingestion rates of residence-
dwelling children in the three locations studied.
5.3.4 Relevant Studies of Primary Analysis
The following studies are classified as relevant
rather than key. The tracer element studies described in
this section are not designated as key because the
methodology to account for non-soil tracer exposures
was not as well-developed as the methodology in the
five U.S. tracer element studies. However, Clausing et
al. (1987) was used in developing the biokinetic model
default soil and dust ingestion rates (U.S. EPA 1994a)
used in the Hogan et al. (1998) study, which was
designated as key. In the survey response studies, in
most cases the studies were of a non-randomized
design, insufficient information was provided to
determine important details regarding study design, or
no data were provided to allow quantitative estimates of
soil and/or dust ingestion rates.
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5.3.4.1 Dickins and Ford, 1942 - Geophagy (Dirt
Eating) Among Mississippi Negro School
Children
Dickens and Ford conducted a survey response
study of rural black school children (4th grade and
above) in Oktibbeha County, Mississippi in September
1941. A total of 52 of 207 children (18 of 69 boys and
34 of 138 girls) studied gave positive responses to
questions administered in a test-taking format regarding
having eaten dirt in the previous 10 to 16 days. The
authors stated that the study sample likely was more
representative of the higher socioeconomic levels in the
community, because older children from lower
socioeconomic levels sometimes left school in order to
work, and because children in the lower grades, who
were more socioeconomically representative of the
overall community, were excluded from the study.
Clay was identified as the predominant type of soil
eaten.
5.3.4.2 Cooper, 1957 - Present Study
Cooper (1957) conducted a non-randomized
survey response study in the 1950s of children age 7
months or older referred to a Baltimore, Maryland
mental hygiene clinic. For 86 out of 784 children
studied, parents or caretakers gave positive responses to
the question "Does your child have a habit, or did he
ever have a habit, of eating dirt, plaster, ashes, etc.?"
and identified dirt, or dirt combined with other
substances, as the substance ingested. Cooper (1957)
described a pattern of pica behavior, including ingesting
substances otherthan soil, being most commonbetween
ages 2 and 4 or 5 years, with one of the 86 children
ingesting clay at age 10 years and 9 months.
5.3.4.3 Sarltrop, 1966 - The Prevalence of Pica
Barltrop (1966) conducted a randomized
survey response study of children born in Boston,
Massachusetts between 1958 and 1962, inclusive,
whose parents resided in Boston and who were neither
illegitimate nor adopted. A stratified random
subsample of 500 of these children were contacted for
in-person caregiver interviews, in which a total of 186
families (37 percent) participated. A separate stratified
subsample of 1,000 children was selected for a mailed
survey, in which 277 (28 percent) of the families
participated. Interview-obtained data regarding care-
giver reports of pica (in this study is defined as placing
nonfood items in the mouth and swallowing them)
behavior in all children ages 1 to 6 in the 186 families
(n=439) indicated 19 had ingested dirt (defined as yard
dirt, house dust, plant-pot soil, pebbles, ashes, cigarette
ash, glass fragments, lint, and hair combings) in the
preceding 14 days. It does not appear that these data
were corrected for unequal selection probability in the
stratified random sample, nor were they corrected for
non-response bias. Interviews were conducted in the
March/April time frame, presumably in 1964. Mail-
survey obtained data regarding caregiver reports of pica
in the preceding 14 days indicated that 39 of 277
children had ingested dirt, presumably using the same
definition as above. Barltrop (1966) mentions several
possible limitations of the study, including non-
participation bias and respondents' memory, or recall,
effects.
5.3.4.4 Bruhn and Pangborn, 1971 - Reported
Incidence of Pica among Migrant Families
Bruhn and Pangborn (1971) conducted a
survey among 91 low income families of migrant
agricultural workers in California in May through
August 1969. Families were of Mexican descent in
two labor camps (Madison camp, 10 miles west of
Woodland, and Davis camp, 10 miles east of Davis)
and were "Anglo" families at the Harney Lane camp 17
miles north of Stockton. Participation was 34 of 50
families at the Madison camp, 31 of 50 families at the
Davis camp, and 26 of 26 families at the Harney Lane
camp. Respondents for the studied families (primarily
wives) gave positive responses to open-ended questions
such as "Do you know of anyone who eats dirt or
laundry starch?" Bruhn and Pangborn (1971) apparently
asked a modified version of this question pertaining to
the respondents' own or relatives' families. They
reported 18 percent (12 of 65) of Mexican families'
respondents as giving positive responses for
consumption of "dirt" among children within the
Mexican respondents' own or relatives' families. They
reported 42 percent (11 of 26) of "Anglo" families'
respondents as giving positive responses for
consumption of "dirt" among children within the Anglo
respondents' own or relatives' families.
5.3.4.5 Robischon, 1971 - Pica Practice and Other
Hand-Mouth Behavior and Children's
Developmental Level
A survey response sample of 19- to 24-month
old children examined at an urban well-child clinic in
the late 1960s or 1970 in an unspecified location
indicated that 48 of the 130 children whose caregivers
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were interviewed, exhibited pica behavior (defined as
"ate nonedibles more than once a week"). The specific
substances eaten were reported for 30 of the 48
children. All except 2 of the 30 children habitually ate
more than one nonedible substance. The soil and dust-
like substances reported as eaten by these 30 children
were: ashes (17), "earth" (5), dust (3), fuzz from rugs
(2), clay (1), and pebbles/stones (1). Caregivers for
some of the study subjects (between 0 and 52 of the 130
subjects, exact number not specified) reported that the
children "ate nonedibles less than once a week."
5.3.4.6 Binder et al, 1986 - Estimating Soil
Ingestion: The Use of Tracer Elements in
Estimating the Amount of Soil Ingested by
Young Children
Binder et al. (1986) used a tracer technique
modified from a method previously used to measure
soil ingestion among grazing animals to study the
ingestion of soil among children 1 to 3 years of age
who wore diapers. The children were studied during
the summer of 1984 as part of a larger study of
residents living near a lead smelter in East Helena,
Montana. Soiled diapers were collected over a 3-day
period from 65 children (42 males and 23 females), and
composited samples of soil were obtained from the
children's yards. Both excreta and soil samples were
analyzed for aluminum, silicon, and titanium. These
elements were found in soil but were thought to be
poorly absorbed in the gut and to have been present in
the diet only in limited quantities. Excreta
measurements were obtained for 59 of the children.
Soil ingestion by each child was estimated on the basis
of each of the three tracer elements using a standard
assumed fecal dry weight of 15 g/day, and the
following equation (5-2):
where:
T,,e
f
(Eq. 5-2)
estimated soil ingestion for child i
based on element e (g/day);
concentration of element e in fecal
sample of child i (mg/g);
fecal dry weight (g/day); and
concentration of element e in child i's
yard soil (mg/g).
The analysis assumed that (1) the tracer elements were
neither lost nor introduced during sample processing;
(2) the soil ingested by children originates primarily
from their own yards; and (3) that absorption of the
tracer elements by children occurred in only small
amounts. The study did not distinguish between
ingestion of soil and house dust, nor did it account for
the presence of the tracer elements in ingested foods or
medicines.
The arithmetic mean quantity of soil ingested
by the children in the Binder et al. (1986) study was
estimated to be 181 mg/day (range 25 to 1,324) based
on the aluminum tracer; 184 mg/day (range 31 to 799)
based on the silicon tracer; and 1,834 mg/day (range 4
to 17,076) based on the titanium tracer (Table 5-13).
The overall mean soil ingestion estimate, based on the
minimum of the three individual tracer estimates for
each child, was 108 mg/day (range 4 to 708). The
median values were 121 mg/day, 136 mg/day, and 618
mg/day for aluminum, silicon, and titanium,
respectively. The 95th percentile values for aluminum,
silicon, and titanium were 584 mg/day, 578 mg/day,
and 9,590 mg/day, respectively. The 95th percentile
value based on the minimum of the three individual
tracer estimates for each child was 386 mg/day.
The authors were not able to explain the
difference between the results for titanium and for the
other two elements, but they speculated that
unrecognized sources of titanium in the diet or in the
laboratory processing of stool samples may have
accounted for the increased levels. The frequency
distribution graph of soil ingestion estimates based on
titanium shows that a group of 21 children had
particularly high titanium values (i.e., > 1,000 mg/day).
The remainder of the children showed titanium
ingestion estimates at lower levels, with a distribution
more comparable to that of the other elements.
5.3.4.7 Clausing, et al., 1987 - A method for
estimating soil ingestion by children
Clausing et al. (1987) conducted a soil
ingestion study with Dutch children using a tracer
element methodology. Clausing et al. (1987) measured
aluminum, titanium, and acid-insoluble residue contents
of fecal samples from children aged 2 to 4 years
attending a nursery school, and for samples of
playground dirt at that school. Over a 5-day period, 27
daily fecal samples were obtained for 18 children.
Using the average soil concentrations present at the
school, and assuming a standard fecal dry weight of 10
g/day, soil ingestion was estimated for each tracer. Six
hospitalized, bedridden children served as a control
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group, representing children who had very limited
access to soil; 8 daily fecal samples were collected from
the hospitalized children.
Without correcting for the tracer element
contribution from background sources, represented by
the hospitalized children's soil ingestion estimates, the
aluminum-based soil ingestion estimates for the school
children in this study ranged from 23 to 979 mg/day,
the AIR-based estimates ranged from 48 to 3 62 mg/day,
and the titanium-based estimates ranged from 64 to
11,620 mg/day. As in the Binder et al. (1986) study, a
fraction of the children (6/18) showed titanium values
above 1,000 mg/day, with most of the remaining
children showing substantially lower values.
Calculating an arithmetic mean quantity of soil ingested
based on each fecal sample yielded 230 mg/day for
aluminum; 129 mg/day for AIR, and 1,430 mg/day for
titanium (Table 5-14). Based on the Limiting Tracer
Method (LTM) and averaging across each fecal sample,
the arithmetic mean soil ingestion was estimated to be
105 mg/day with a population standard deviation of 67
mg/day (range 23 to 362 mg/day); geometric mean soil
ingestion was estimated to be 90 mg/day. Use of the
LTM assumed that "the maximum amount of soil
ingested corresponded with the lowest estimate from
the three tracers" (Clausing et al., 1987).
The hospitalized children's arithmetic mean
aluminum-based soil ingestion estimate was 56
mg/day; titanium-based estimates included estimates for
three of the six children that exceeded 1,000 mg/day,
with the remaining three children in the range of 28 to
58 mg/day (Table 5-15). AIR measurements were not
reported for the hospitalized children. Using the LTM
method, the mean soil ingestion rate was estimated to
be 49 mg/day with a population standard deviation of
22 mg/day (range 26 to 84 mg/day). The geometric
mean soil ingestion rate was 45 mg/day. The
hospitalized children's data suggested a major nonsoil
source of titanium for some children and a background
nonsoil source of aluminum. However, conditions
specific to hospitalization (e.g., medications) were not
considered.
Clausing et al. (1987) estimated that the
average soil ingestion of the nursery school children
was 56 mg/day, after subtracting the mean LTM soil
ingestion forthe hospitalized children (49 mg/day) from
the nursery school children's mean LTM soil ingestion
(105 mg/day), to account for background tracer intake
from dietary and other nonsoil sources.
5.3.4.8 Smulian et al., 1995 - Pica in a Rural
Obstetric Population
In 1992, Smulian et al. (1995) conducted a
survey response study of pica in a convenience sample
of 125 pregnant women in Muscogee County, Georgia,
who ranged in age from 12 to 37. Of the 18 women
who acknowledged practicing pica, 4 acknowledged
eating "white dirt" (common name for white clay) or
"red dirt." Of the 18 women, 9 stated the amount of
substances that they ingested (which included several
substances besides white or red dirt). Thus, of the 4
respondents who acknowledged ingesting white or red
dirt, an unknown number of them acknowledged
ingesting 0.5 to 1.0 pounds of dirt or clay per week
(roughly 200-500 g/week). Of the 9 women who stated
amounts of substances ingested, 6 stated that their
ingestion occurred daily and 3 stated that it occurred
three times per week. The authors found a prevalence
for the overall pica, by race/ethnicity, of 17.8 percent of
the black women, 10.6 percent of the white women, and
0 percent of the Asian and Hispanic women in the
sample, with no significant differences between pica
and nonpica groups with respect to age distribution or
race.
5.3.5 Relevant Studies of Secondary Analysis
The secondary analysis literature on soil and
dust ingestion rates gives important insights into
methodological strengths and limitations. The tracer
element studies described in this section are grouped to
some extent according to methodological issues
associated with the tracer element methodology. These
methodological issues include attempting to determine
the origins of apparent positive and negative bias in the
methodologies, including: food input/fecal output
misalignment; missed fecal samples; assumptions about
children's fecal weights; particle sizes of, and relative
contributions of soils and dusts to total soil and dust
ingestion; and attempts to identify a "best" tracer
element or combination of tracer elements. Potential
error from using short-term studies' estimates for long
term soil and dust ingestion behavior estimates is also
discussed.
5.3.5.1 Stanek et al., 2001a - Biasing Factors for
Simple Soil Ingestion Estimates in Mass
Balance Studies of Soil Ingestion
In order to identify and evaluate biasing
factors for soil ingestion estimates, the authors
developed a simulation model based on data from
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previous soil ingestion studies. The soil ingestion data
used in this model were taken from Calabrese et al.
(1989) (the Amherst study); Davis et al. (1990)
(southeastern Washington State); Calabrese et al.
(1997a) (the Anaconda study) and Calabrese et al.
(1997b) (soil-pica in Massachusetts), and relied only on
the aluminum and silicon trace element estimates
provided in these studies.
Of the biasing factors explored, the impact of
study duration was the most striking, with a positive
bias of more than 100 percent for 95th percentile
estimates in a 4-day tracer element study. A smaller
bias was observed for the impact of absorption of trace
elements from food. Although the trace elements
selected for use in these studies are believed to have
low absorption, whatever amount is not accounted for
will result in an underestimation of the soil ingestion
distribution. In these simulations, the absorption of
trace elements from food of up to 30 percent was shown
to negatively bias the estimated soil ingestion
distribution by less than 20 mg/day. No biasing effect
was found for misidentifying play areas for soil
sampling (i.e., ingested soil from a yard other than the
subject's yard).
5.3.5.2 Calabrese and Stanek, 1995 - Resolving
Intertracer Inconsistencies in Soil Ingestion
Estimation
Calabrese and Stanek (1995) explored sources
and magnitude of positive and negative errors in soil
ingestion estimates for children on a subject-week and
trace element basis. Calabrese and Stanek (1995)
identified possible sources of positive errors to be:
• Ingestion of high levels of tracers before the
start of the study and low ingestion during the
study period; and
• Ingestion of element tracers from a non-food
or non-soil source during the study period.
Possible sources of negative bias were identified as:
• Ingestion of tracers in food that are not
captured in the fecal sample either due to slow
lag time or not having a fecal sample available
on the final study day; and
• Sample measurement errors that result in
diminished detection of fecal tracers, but not
in soil tracer levels.
The authors developed an approach that attempted to
reduce the magnitude of error in the individual trace
element ingestion estimates. Results from a previous
study conducted by Calabrese et al. (1989) were used to
quantify these errors based on the following criteria:
(1) a lag period of 28 hours was assumed for the
passage of tracers ingested in food to the feces (this
value was applied to all subject-day estimates); (2) a
daily soil ingestion rate was estimated for each tracer
for each 24-hour day a fecal sample was obtained; (3)
the median tracer-based soil ingestion rate for each
subject-day was determined; and (4) negative errors due
to missing fecal samples at the end of the study period
were also determined. Also, upper- and lower-bound
estimates were determined based on criteria formed
using an assumption of the magnitude of the relative
standard deviation (RSD) presented in another study
conducted by Stanek and Calabrese (1995a). Daily soil
ingestion rates for tracers that fell beyond the upper and
lower ranges were excluded from subsequent
calculations, and the median soil ingestion rates of the
remaining tracer elements were considered the best
estimate for that particular day. The magnitude of
positive or negative error for a specific tracer per day
was derived by determining the difference between the
value for the tracer and the median value.
Table 5-16 presents the estimated magnitude
of positive and negative error for six tracer elements in
the children's study (conducted by Calabrese et al.,
1989). The original non-negative mean soil ingestion
rates (Table 5-3) ranged from alow of 21 mg/day based
on zirconium to a high of 459 mg/day based on
vanadium. The adjusted mean soil ingestion rate after
correcting for negative and positive errors ranged from
97 mg/day based on yttrium to 208 mg/day based on
titanium. Calabrese and Stanek (1995) concluded that
correcting for errors at the individual level for each
tracer element provides more reliable estimates of soil
ingestion.
5.3.5.3 Stanek and Calabrese, 1995a - Daily
Estimates of Soil Ingestion in Children
Stanek and Calabrese (1995a) presented a
methodology which links the physical passage of food
and fecal samples to construct daily soil ingestion
estimates from daily food and fecal trace-element
concentrations. Soil ingestion data for children
obtained from the Amherst study (Calabrese et al.,
1989) were reanalyzed by Stanek and Calabrese
(1995a). A lag period of 28 hours between food intake
and fecal output was assumed for all respondents. Day
1 for the food sample corresponded to the 24 hour
period from midnight on Sunday to midnight on
Monday of a study week; day 1 of the fecal sample
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corresponded to the 24 hour period from noon on
Monday to noon on Tuesday. Based on these
definitions, the food soil equivalent was subtracted
from the fecal soil equivalent to obtain an estimate of
soil ingestion for a trace element. A daily overall
ingestion estimate was constructed for each child as the
median of trace element values remaining after tracers
falling outside of a defined range around the overall
median were excluded.
Table 5-17 presents adjusted estimates,
modified according to the input/output misalignment
correction, of mean daily soil ingestion per child
(mg/day) for the 64 study participants. The approach
adopted in this paper led to changes in ingestion
estimates from those presented in Calabrese et al.
(1989).
Estimates of children's soil ingestion projected
over a period of 365 days were derived by fitting log-
normal distributions to the overall daily soil ingestion
estimates using estimates modified according to the
input/output misalignment correction (Table 5-18). The
estimated median value of the 64 respondents' daily soil
ingestion averaged over a year was 75 mg/day, while
the 95th percentile was 1,751 mg/day. In developing the
365-day soil ingestion estimates, data that were
obtained over a short period of time (as is the case with
all available soil ingestion studies) were extrapolated
over a year. The 2-week study period may not reflect
variability in tracer element ingestion over a year.
While Stanek and Calabrese (1995a) attempted to
address this through modeling of the long term
ingestion, new uncertainties were introduced through
the parametric modeling of the limited subject day data.
5.3.5.4 Calabrese and Stanek, 1992b - What
Proportion of Household Dust is Derived
from Outdoor Soil?
Calabrese and Stanek (1992b) estimated the
amount of outdoor soil in indoor dust using statistical
modeling. The model used soil and dust data from the
60 households that participated in the Calabrese et al.
(1989) study, by preparing scatter plots of each tracer's
concentration in soil versus dust. Correlation analysis
of the scatter plots was performed. The scatter plots
showed little evidence of a consistent relationship
between outdoor soil and indoor dust concentrations.
The model estimated the proportion of outdoor soil in
indoor dust using the simplifying assumption that the
following variables were constants in all houses: the
amount of dust produced every day from both indoor
and outdoor sources; the proportion of indoor dust due
to outdoor soil; and the concentration of the tracer
element in dust produced from indoor sources. Using
these assumptions, the model predicted that 31.3
percent by weight of indoor dust came from outdoor
soil. This model was then used to adjust the soil
ingestion estimates from Calabrese et al. (1989). Using
an assumption that 50 percent of excess fecal tracers
were from indoor origin and 50 percent were from
outdoor origin, and multiplying the 50 percent indoor-
origin excess fecal tracer by the model prediction that
31.3 percent of indoor dust came from outdoor soil,
results in an estimate that 15 percent of excess fecal
tracers were from soil materials that were present in
indoor dust. Adding this 15 percent to the 50 percent
assumed outdoor (soil) origin excess fecal tracer
quantity results in an estimate that approximately 65
percent of the total residual excess fecal tracer was of
soil origin (Calabrese and Stanek, 1992b).
5.3.5.5 Calabrese et al., 1996 - Methodology to
Estimate the Amount and Particle Size of
Soil Ingested by Children: Implications for
Exposure Assessment at Waste Sites
Calabrese etal., 1996 examined the hypothesis
that one cause of the variation between tracers seen in
soil ingestion studies could be related to differences in
soil tracer concentrations by particle size. This study,
published prior to the Calabrese et al. (1997a) primary
analysis study results, used laboratory analytical results
for the Anaconda, Montana soil's tracer concentration
after it had been sieved to a particle size of <250 um in
diameter (it was sieved to <2 mm soil particle size in
Calabrese etal. (1997a)). The smaller particle size was
examined based on the assumption that children
principally ingest soil of small particle size adhering to
fingertips and under fingernails. For five of the tracers
used in the original study (aluminum, silicon, titanium,
yttrium, and zirconium), soil concentration was not
changed by particle size. However, the soil
concentrations of three tracers (lanthanum, cerium, and
neodymium) were increased two- to fourfold at the
smaller soil particle size. Soil ingestion estimates for
these three tracers were decreased by approximately 60
percent at the 95th percentile compared to the Calabrese
et al. (1997a) results.
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5.3.5.6 Stanek et al, 1999 - Soil Ingestion Estimates
for Children in Anaconda Using Trace
Element Concentrations in Different Particle
Size Fractions
Stanek et al. (1999) extends the findings from
Calabrese et al. (1996) by quantifying trace element
concentrations in soil based on sieving to particle sizes
of 100 to 250 um and to particle sizes of 53 to < 100
um. This study used the data from soil concentrations
from the Anaconda, Montana site reported by Calabrese
et al. (1997a). Results of the study indicated that soil
concentrations of aluminum, silicon and titanium do not
increase at the two finer particle size ranges measured.
However, soil concentrations of cerium, lanthanum and
neodymium increased by a factor of 2.5 to 4.0 in the
100-250 um particle size range when compared with
the 0 to 2 um particle size range. There was not a
significant increase in concentration in the 53 to 100
um particle size range.
5.3.5.7 Stanek and Calabrese, 1995b - Soil Ingestion
Estimates for Use in Site Evaluations Based
on the Best Tracer Method
Stanek and Calabrese (1995b) recalculated
children's soil ingestion rates from two previous
studies, using data for 8 tracers from Calabrese et al.,
1989 and 3 tracers from Davis et al., 1990.
Recalculations were performed using the Best Tracer
Method (BTM). This method selected the
"best"tracer(s), by dividing the total amount of tracer in
a particular child's duplicate food sample by tracer
concentration in that child's soil sample to yield a
food/soil (F/S) ratio. The F/S ratio was small when the
tracer concentration in food was low compared to the
tracer concentration in soil. Small F/S ratios were
desirable because they lessened the impact of transit
time error (the error that occurs when fecal output does
not reflect food ingestion, due to fluctuation in
gastrointestinal transit time) in the soil ingestion
calculation.
The BTM used a ranking scheme of F/S ratios
to determine the best tracers for use in the ingestion rate
calculation. To reduce the impact of biases that may
occur as a result of sources of fecal tracers other than
food or soil, the median of soil ingestion estimates
based on the four lowest F/S ratios was used to
represent soil ingestion.
Using the lowest four F/S ratios for each
child, calculated on a per-week ("subject-week") basis,
the median of the soil ingestion estimates from the
Calabrese et al. (1989) study most often included
aluminum, silicon, titanium, yttrium, and zirconium.
Based on the median of soil ingestion estimates from
the best four tracers, the mean soil ingestion rate was
132 mg/day and the median was 33 mg/day. The 95th
percentile value was 154 mg/day. Forthe 101 children
in the Davis et al. (1990) study, the mean soil ingestion
rate was 69 mg/day and the median soil ingestion rate
was 44 mg/day. The 95th percentile estimate was 246
mg/day. These data are based on the three tracers (i.e.,
aluminum, silicon and titanium) from the Davis et al.
(1990) study. When the results for the 128 subject-
weeks in Calabrese et al. (1989) and 101 children in
Davis et al. (1990) were combined, soil ingestion for
children was estimated to be 104 mg/day (mean); 37
mg/day (median); and 217 mg/day (95th percentile),
using the BTM.
5.3.5.8 Stanek and Calabrese, 2000 - Daily Soil
Ingestion Estimates for Children at a
Superfund Site
Stanek and Calabrese (2000) reanalyzed the
soil ingestion data from the Anaconda study. The
authors assumed a lognormal distribution for the soil
ingestion estimates in the Anaconda study to predict
average soil ingestion for children over a longer time
period. Using "best linear unbiased predictors," the
authors predicted 95th percentile soil ingestion values
over time periods of 7 days, 30 days, 90 days, and 365
days. The 95th percentile soil ingestion values were
predicted to be 133 mg/day over 7 days, 112 mg/day
over 30 days, 108 mg/day over 90 days, and 106
mg/day over 365 days. Based on this analysis,
estimates of the distribution of longer term average soil
ingestion are expected to be narrower, with the 95th
percentile estimates being as much as 25 percent lower
(Stanek and Calabrese, 2000).
5.3.5.9 Stanek et al., 2001b - Soil Ingestion
Distributions for Monte Carlo Risk
Assessment in Children
Stanek et al. (200 Ib) developed "best linear
unbiased predictors" to reduce the biasing effect of
short-term soil ingestion estimates. This study
estimated the long-term average soil ingestion
distribution using daily soil ingestion estimates from
children who participated in the Anaconda, Montana
study. In this long-term (annual) distribution, the soil
ingestion estimates were: mean 31, median 24, 75th
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percentile 42, 90th percentile 75, and 95th percentile 91
mg/day.
5.3.5.10 von Lindern etal., 2003 -Assessing remedial
effectiveness through the blood lead:soil/dust
lead relationship at the Bunker Hill
Superfund Site in the Silver Valley of Idaho
Similar to Hogan et al. (1998), von Lindern et
al. (2003) used the IEUBK model to predict blood lead
levels in a non-random sample of several hundred
children ages 0-9 years in an area of northern Idaho
from 1989-1998 during community-wide soil
remediation. Von Lindern et al. (2003) used the
IEUBK default soil and dust ingestion rates together
with observed house dust/soil lead levels (and imputed
values based on community soil and dust lead levels,
when observations were missing). The authors
compared the predicted blood lead levels with observed
blood lead levels and found that the default IEUBK soil
and dust ingestion rates and lead bioavailability value
overpredicted blood lead levels, with the overprediction
decreasing as the community soil remediation
progressed. The authors stated that the overprediction
may have been caused either by a default soil and dust
ingestion that was too high, a default bioavailability
value for lead that was too high, or some combination
of the two. They also noted underpredictions for some
children, for whom follow up interviews revealed
exposures to lead sources not accounted for by the
model, and noted that the study sample included many
children with a short residence time within the
community.
Von Lindern et al. (2003) developed a
statistical model that apportioned the contributions of
community soils, yard soils of the residence, and house
dust to lead intake; the models' results suggested that
community soils contributed more (50 percent) than
neighborhood soils (28 percent) or yard soils (22
percent) to soil found in house dust of the studied
children.
5.4 LIMITATIONS OF KEY STUDY
METHODOLOGIES
The three types of information needed to
provide recommendations to exposure assessors on soil
and dust ingestion rates among U.S. children include
quantities of soil and dust ingested, frequency of high
soil and dust ingestion episodes, and prevalence of high
soil and dust ingesters. The methodologies provide
different types of information: the tracer element and
biokinetic model comparison methodologies provide
information on quantities of soil and dust ingested; the
tracer element methodology provides limited evidence
of the frequency of high soil ingestion episodes; the
survey response methodology can shed light on
prevalence of high soil ingesters and frequency of high
soil ingestion episodes. The methodologies used to
estimate soil and dust ingestion rates and prevalence of
soil and dust ingestion behaviors have certain
limitations, when used for the purpose of developing
recommended soil and dust ingestion rates. This
section describes some of the known limitations,
presents an evaluation of the current state of the science
for U.S. children's soil and dust ingestion rates, and
describes how the limitations affect the confidence
ratings given to the recommendations.
5.4.1 Tracer Element Methodology
This section describes some previously
identified limitations of the tracer element methodology
as it has been implemented by U.S. researchers, as well
as additional potential limitations that have not been
explored. Some of these same limitations would also
apply to the Dutch and Jamaican studies that used a
control group of hospitalized children to account for
dietary and pharmaceutical tracer intakes.
Binder et al. (1986) described some of the
major and obvious limitations of the early U.S. tracer
element methodology as follows:
[T]he algorithm assumes that children ingest
predominantly soil from their own yards and
that concentrations of elements in composite
soil samples from front and back yards are
representative of overall concentrations in the
yards....children probably eat a combination of
soil and dust; the algorithm used does not
distinguish between soil and dust
ingestion....fecal sample weights...were much
lower than expected...the assumption that
aluminum, silicon and titanium are not
absorbed is not entirely true....dietary intake of
aluminum, silicon and titanium is not
negligible when compared with the potential
intake of these elements from soil....Before
accepting these estimates as true values of soil
ingestion in toddlers, we need a better
understanding of the metabolisms of
aluminum, silicon and titanium in children,
and the validity of the assumptions we made
in our calculations should be explored further.
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The subsequent U.S. tracer element studies (Calabrese
et al. (1989)/Barnes (1990), Davis et al. (1990),
Calabrese et al. (1997a), and Davis and Mirick (2006))
made some progress in addressing some of the Binder
et al. (1986) study's stated limitations.
Regarding the issue of non-yard (community-
wide) soil as a source of ingested soil, one study
(Calabrese et al. 1989/Barnes 1990) addressed this
issue to some extent, by including samples of children's
day care center soil in the analysis. Calabrese et al.
(1997a) attempted to address the issue by excluding
children in day care from the study sample frame.
Homogeneity of community soils' tracer element
content would play a role in whether this issue is an
important biasing factor for the tracer element studies'
estimates. Davis et al. (1990) evaluated community
soils' aluminum, silicon and titanium content and found
little variation among 101 yards throughout the three-
city area. Stanek et al. (200la) conclude that there is
"minimal impact" on estimates of soil ingestion due to
mis-specifying a child's play area.
Regarding the issue of soil and dust both
contributing to measured tracer element quantities in
excreta samples, the five key U.S. tracer element
studies all attempt to address the issue by including
samples of household dust in the analysis, and in some
cases estimates are presented in the published articles
that adjust soil ingestion estimates on the basis of the
measured tracer elements found in the household dust.
The relationship between soil ingestion rates and indoor
settled dust ingestion rates has been evaluated in some
of the secondary studies (e.g., Calabrese and Stanek
(1992b)). An issue similar to the community-wide soil
exposures in the previous paragraph could also exist
with community-wide indoor dust exposures (such as
dust found in schools and community buildings
occupied by study subjects during or prior to the study
period). A portion of the community-wide indoor dust
exposures (that due to occupying day care facilities)
was addressed in the Calabrese et al. (1989)/Barnes
(1990) study, but not in the other three key tracer
element studies. In addition, if the key studies' vacuum
cleaner collection method for household and day care
indoor settled dust samples influenced tracer element
composition of indoor settled dust samples, the dust
sample collection method would be another area of
uncertainty with the key studies' indoor dust related
estimates. The survey response studies suggest that
some young children may prefer ingesting dust to
ingesting soil. The existing literature on soil versus
dust sources of children's lead exposure may provide
useful information that has not yet been compiled for
use in soil and dust ingestion recommendations.
Regarding the issue of fecal sample weights
and the related issue of missing fecal and urine samples,
the four key tracer element studies have varying
strengths and limitations. The Calabrese et al. (1989)
article stated that wipes and toilet paper were not
collected by the researchers, and thus underestimates of
fecal quantities may have occurred. Calabrese et al.
(1989) stated that cotton cloth diapers were supplied for
use during the study; commodes apparently were used
to collect both feces and urine for those children who
were not using diapers. Barnes (1990) described
cellulose and polyester disposable diapers with
significant variability in silicon and titanium content
and suggested that children's urine was not included in
the analysis. Thus, it is unclear to what extent complete
fecal and urine output was obtained, for each study
subject. The Calabrese et al. (1997a) study did not
describe missing fecal samples and did not state
whether urinary tracer element quantities were used in
the soil and dust ingestion estimates, but stated that
wipes and toilet paper were not collected. Missing
fecal samples may have resulted in negative bias in the
estimates from both of these studies. Davis et al.
(1990) and Davis and Mirick (2006) were limited to
children who no longer wore diapers. Missed fecal
sample adjustments might affect those studies'
estimates in either a positive or negative direction, due
to the assumptions the authors made regarding the
quantities of feces and urine in missed samples.
Adjustments for missing fecal and urine samples could
introduce errors sufficient to cause negative estimates
if missed samples were heavier than the collected
samples used in the soil and dust ingestion estimate
calculations.
Regarding the issue of dietary intake, the five
key U.S. tracer element studies have all addressed
dietary (and non-dietary, non-soil) intake by subtracting
quantitated estimates of these sources of tracer elements
from excreta tracer element quantities, or by providing
study subjects with personal hygiene products that were
low in tracer element content. Applying the food and
non-dietary, non-soil corrections required subtracting
the tracer element contributions from these non-soil
sources from the measured fecal/urine tracer element
quantities. To perform this correction required
assumptions to be made regarding the gastrointestinal
transit time, or the time lag between inputs (food, non-
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dietary non-soil, and soil) and outputs (fecal and urine).
The gastrointestinal transit time assumption introduced
a new potential source of bias that some authors (e.g.,
Stanek and Calabrese, 1995a) called input/output
misalignment or transit time error. This lag time may
also be a function of age. Davis et al. (1990) and Davis
and Mirick (2006) assumed a 24 hour lag time in
contrast to the 28 hour lag times used in Calabrese et al.
(1989)/Barnes (1990) and Calabrese et al. (1997a).
ICRP (2002) suggested a lag time of 37 hours for one
year old children and 5 to 15 year old children. Stanek
and Calabrese (1995a) describe a method designed to
reduce bias from this error source.
Regarding gastrointestinal absorption, the
authors of three of the studies appeared to agree that the
presence of silicon in urine represented evidence that
silicon was being absorbed from the gastrointestinal
tract (Davis et al., 1990; Calabrese et al., 1989/Barnes
(1990); Davis and Mirick, 2006). There was some
evidence of aluminum absorption in Calabrese et al.,
1989/Barnes (1990); Davis and Mirick (2006) stated
that aluminum and titanium did not appear to have been
absorbed, based on low urinary levels. Davis et al.
(1990) stated that silicon appears to have been absorbed
to a greater degree than aluminum and titanium, based
on urine concentrations.
Aside from the gastrointestinal absorption, lag
time and missed fecal sample issues, Davis and Mirick
(2006) offer another other possible explanation for the
negative soil and dust ingestion rates estimated for
some study participants. Because the weights of dried
food and liquid (input) samples were sufficiently great,
relative to the urine and fecal (output) samples,
overestimates in laboratory analytical values for the
input samples would not be compensated for by a
similar overestimate in the output samples.
Another limitation on accuracy of tracer
element-based estimates of soil and dust ingestion
relates to inaccuracies inherent in environmental
sampling and laboratory analytical techniques. The
"percent recovery" of different tracer elements varies
(according to validation of the study methodology
performed with adults who swallowed gelatin capsules
with known quantities of sterilized soil, as part of the
Calabrese et al., 1989 and 1997a studies). Estimates
based on a particular tracer element with a lower or
higher recovery than the expected 100 percent in any of
the study samples would be influenced in either a
positive or negative direction, depending on the
recoveries in the various samples and their degree of
deviation from 100 percent (e.g., Calabrese et al.,
1989).
Davis et al. (1990) offered an assessment of
the impact of swallowed toothpaste on the tracer-based
estimates by adjusting estimates for those children
whose caregivers reported that they had swallowed
toothpaste. Davis et al. (1990) had supplied study
children with toothpaste that had been pre-analyzed for
its tracer element content, but it is not known to what
extent the children actually used the supplied
toothpaste. Similarly, Calabrese etal, 1989 and 1997a
supplied children in the Amherst, Massachusetts and
Anaconda, Montana studies with toothpaste containing
low levels of most tracers, but it is unclear to what
extent those children used the supplied toothpaste.
Other research suggests additional possible
limitations that have not yet been explored. First,
lymph tissue structures in the gastrointestinal tract
might serve as reservoirs for titanium dioxide food
additives and soil particles, which could bias estimates
either upward or downward depending on tracers'
entrapment within, or release from, these reservoirs
during the study period (ICRP (2002); Shepherd et al.
(1987); Powell et al. (1996)). Second, gastrointestinal
uptake of silicon may have occurred, which could bias
those estimates downward. Evidence of silicon's role
in bone formation (e.g., Carlisle (1980)) supported by
newerresearch on dietary silicon uptake (Jugdaohsingh
et al. (2002); Van Dyck et al. (2000)) suggests a
possible negative bias in the silicon-based soil ingestion
estimates, depending on the quantities of silicon
absorbed by growing children. Third, regarding the
potential for swallowed toothpaste to bias soil ingestion
estimates upward, commercially available toothpaste
may contain quantities of titanium and perhaps silicon
and aluminum in the range that could be expected to
affect the soil and dust ingestion estimates. Fourth, for
those children who drank bottled or tap water during
the study period, and did not include those drinking
water samples in their duplicate food samples, slight
upward bias may exist in some of the estimates for
those children, since drinking water may contain small,
but relevant, quantities of silicon and potentially other
tracer elements. Fifth, the tracer element studies
conducted to date have not explored the impact of soil
properties' influence on toxicant uptake or excretion
within the gastrointestinal tract. Nutrition researchers
investigating influence of clay geophagy behavior on
human nutrition have begun using in vitro models of the
human digestion (e.g., Dominy et al., 2003; Hooda et
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al., 2004). A recent review (Wilson, 2003) covers a
wide range of geophagy research in humans and various
hypotheses proposed to explain soil ingestion
behaviors, with emphasis on the soil properties of
geophagy materials.
5.4.2 Biokinetic Model Comparison Methodology
It is possible that the IEUBK biokinetic model
comparison methodology contained sources of both
positive and negative bias, like the tracer element
studies, and that the net impact of the competing biases
was in either the positive or negative direction. U.S.
EPA's judgment about the major sources of bias in the
biokinetic model comparison studies is that there may
be three significant sources of bias. The first source of
potential bias was the possibility that the biokinetic
model failed to account for sources of lead exposure
that are important for certain children. For these
children, the model might either under-predict, or
accurately predict, blood lead levels compared to actual
measured lead levels. However, this result may
actually mean that the default assumed lead intake rates
via either soil and dust ingestion, or another lead source
that is accounted for by the model, are too high. The
second source of potential bias was use of the
biokinetic model for predicting blood lead levels in
children who have not spent a significant amount of
time in the areas characterized as the main sources of
environmental lead exposure for those children, which
could result in either upward or downward biases in
those children's predicted blood lead levels.
Comparing upward-biased predictions with actual
measured blood lead levels and finding a relatively
good match could lead to inferences that the model's
default soil and dust ingestion rates are accurate, when
in fact the children's soil and dust ingestion rates, or
some other lead source, were actually higher than the
default assumption. Comparing downward-biased
predictions with actual measured blood lead levels and
finding a relatively good match could lead to inferences
that the model's default soil and dust ingestion rates
were accurate, when in fact the children's soil and dust
ingestion rates, or some other lead source, were actually
lower than the default assumption. The third source of
potential bias was the assumption within the model
itself regarding the biokinetics of absorbed lead, which
could result in either positively or negatively biased
predictions and the same kinds of incorrect inferences
as the second source of potential bias.
5.4.3 Survey Response Methodology
Each data collection methodology (in-person
interview, mailed questionnaire, or questions
administered in "test" format in a school setting) may
have had specific limitations. In-person interviews
could result in either positive or negative response bias
due to distractions posed by young children, especially
when interview respondents simultaneously care for
young children and answer questions. Other limitations
include positive or negative response bias due to
respondents' perceptions of a "correct" answer,
question wording difficulties, lack of understanding of
definitions of terms used, language and dialect
differences between investigators and respondents,
respondents' desires to avoid negative emotions
associated with giving a particular type of answer, and
respondent memory problems ("recall" effects)
concerning past events. Mailed questionnaires have
many of the same limitations as in-person interviews,
but may allow respondents to respond when they are
not distracted by childcare duties. An in-school test
format is more problematic than either interviews or
mailed surveys, because respondent bias related to
teacher expectations could influence responses.
Unweighted survey responses from the
National Health and Nutrition Examination Survey
(NHANES) I and II regarding children's clay and dirt
ingestion are available (U.S. DHHS 1981a,U.S. DHHS
1981b, U.S. DHHS 1985a, U.S. DHHS 1985b) and
appear generally to corroborate the results of the survey
response studies summarized in this chapter, in that a
small proportion of respondents acknowledge eating
dirt or clay. U.S. EPA has undertaken an effort to
weight the survey responses among adult caregiver
respondents who acknowledged clay and dirt ingestion
by children under age 12 years and among child
respondents ages 12 up to 21 years who acknowledged
clay and dirt ingestion, to develop an estimate of
prevalence of the behavior among children.
One approach to evaluating the degree of bias
in survey response studies may be to make use of a
surrogate biomarker indicator providing suggestive
evidence of ingestion of significant quantities of soil
(although quantitative estimates would not be possible).
The biomarker technique measures the presence of
serum antibodies to Toxocara species, a parasitic
roundworm from cat and dog feces. Two U.S. studies
have found associations between reported soil ingestion
and positive serum antibody tests for Toxocara
infection (Marmor et al., 1987; Glickman et al., 1981);
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Chapter 5 - Ingestion of Soil and Dust
a third (Nelson et al., 1996) has not, but the authors
state that reliability of survey responses regarding soil
ingestion may have been an issue. Further refinement
of survey response methodologies, together with recent
NHANES data on U.S. prevalence of positive serum
antibody status regarding infection with Toxocara
species, may be useful.
5.4.4 Key Studies: Representativeness of U.S.
Population
The two key studies of Dutch and Jamaican
children may represent different conditions and
different study populations than those in the U.S.; thus,
it is unclear to what extent those children's soil
ingestion behaviors may differ from U.S. children's soil
ingestion behaviors.
Limitations regarding the key studies
performed in the U.S. for estimating soil and dust
ingestion rates in the entire population of U.S. children
ages 0 to < 21 years fall into the broad categories of
geographic range and demographics (age, gender,
race/ethnicity, socioeconomic status).
Regarding geographic range, the two most
obvious issues relate to soil types and climate. Soil
properties might influence the soil ingestion estimates
that are based on excreted tracer elements. The Davis
et al. (1990), Calabrese et al. (1989)/Barnes (1990),
Davis and Mirick (2006) and Calabrese et al. (1997a)
tracer element studies were in locations with soils that
had sand content ranging from 21-80 percent, silt
content ranging from 16-71 percent, and clay content
ranging from 3-20 percent by weight, based on data
from USDA (2008). The location of children in the
Calabrese et al. (1997b) study was not specified, but
due to the original survey response study's occurrence
in western Massachusetts, the soil types in the vicinity
of the Calabrese et al. (1997b) study are likely to be
similar to those in the Calabrese et al. (1989)/Barnes
(1990) study.
The Hogan et al. (1998) study included
locations in the central part of the U.S. (an area along
the Kansas/Missouri border, and an area in western
Illinois) and one in the eastern U.S. (Palmerton,
Pennsylvania). The only key study conducted in the
southern part of the U.S. was Vermeer and Frate
(1979).
Children might be outside and have access to
soil in a very wide range of weather conditions (Wong
et al., 2000). In the parts of the U.S. that experience
moderate temperatures year-round, soil ingestion rates
may be fairly evenly distributed throughout the year.
During conditions of deep snow cover, extreme cold, or
extreme heat, children could be expected to have
minimal contact with outside soil. All children,
regardless of location, could ingest soils located indoors
in plant containers, or outdoor soil tracked inside
buildings by human or animal building occupants.
Davis et al. (1990) did not find a clear or consistent
association between the number of hours spent indoors
per day and soil ingestion, but reported a consistent
association between spending a greater number of hours
outdoors and high (defined as the uppermost tertile) soil
ingestion levels across all three tracers used.
The five key tracer element studies all took
place in northern latitudes. The temperature and
precipitation patterns that occurred during these four
studies' data collection periods was difficult to discern
due to no mention of specific data collection dates in
the published articles. The Calabrese et al.
(1989)/Barnes (1990) study apparently took place in
mid- to late September 1987 in and near Amherst,
Massachusetts; Calabrese etal. (1997a) apparently took
place in late September and early October 1992, in
Anaconda, Montana; Davis et al. (1990) took place in
July, August and September 1987, in Richland,
Kennewick and Pasco, Washington; and Davis and
Mirick (2006) took place in the same Washington state
location in late July, August and very early September
1988 (raw data). Inferring exact data collection dates,
a wide range of temperatures may have occurred during
the four studies' data collection periods (daily lows
from 22-60 °F and 25-48 °F, and daily highs from 53-81
°F and 55-88 °F in Calabrese et al. (1989) and Calabrese
et al. (1997a), respectively, and daily lows from 51-72
°F and 51 - 67 °F, and daily highs from 69-103 °F and
80-102 °F in Davis et al. (1990) and Davis and Mirick
(2006), respectively) (National Climatic Data Center,
2008). Significant amounts of precipitation occurred
during Calabrese et al. (1989) (more than 0.1 inches per
24 hour period) on several days; somewhat less
precipitation was observed during Calabrese et al.
(1997a); precipitation in Kennewick and Richland
during the data collection periods of Davis etal. (1990)
was almost nonexistent; there was no recorded
precipitation in Kennewick or Richland during the data
collection period for Davis and Mirick (2006) (National
Climatic Data Center, 2008).
The key biokinetic model comparison study
(Hogan et al., 1998) targeted three locations in more
southerly latitudes (Pennsylvania, southern Illinois, and
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Chapter 5 - Ingestion of Soil and Dust
southern Kansas/Missouri) than the five tracer element
studies. The biokinetic model comparison methodology
had an advantage over the tracer element studies in that
the study represented long-term environmental
exposures over periods up to several years, that would
include a range of seasons and climate conditions.
A brief review of the representativeness of the
key studies' samples with respect to gender and age
suggested that males and females were represented
roughly equally in those studies for which study
subjects' gender was stated. Children up to age 8 years
were studied in seven of the nine studies, with an
emphasis on younger children. Wong (1988)/Calabrese
et al. (1993) and Vermeer and Frate (1979) are the only
studies with children 8 years or older.
A brief review of the representativeness of the
key studies' samples with respect to socioeconomic
status and racial/ethnic identity suggested that there
were some discrepancies between the study subjects
and the current U.S. population of children age 0 to <21
years. The single survey response study (Vermeer and
Frate (1979)) was specifically targeted toward a
predominantly rural black population in a particular
county in Mississippi. The tracer element studies are of
predominantly white populations, apparently with
limited representation from other racial and ethnic
groups. The Amherst, Massachusetts study (Calabrese
et al. 1989/Barnes 1990) did not publish the study
participants' socioeconomic status or racial and ethnic
identities. The socioeconomic level of the Davis et al.
(1990) studied children was reported to be primarily of
middle to high income. Self-reported race and ethnicity
of relatives of the children studied (in most cases, they
were the parents of the children studied) in Davis et al.
(1990) were White (86.5 percent), Asian (6.7 percent),
Hispanic (4.8 percent), Native American (1.0 percent),
and Other (1.0 percent), and the 91 married or living-
as-married respondents identified their spouses as
White (86.8 percent), Hispanic (7.7 percent), Asian (4.4
percent), and Other (1.1 percent). Davis and Mirick
(2006) did not state the race and ethnicity of the follow-
up study participants, who were a subset of the original
study participants from Davis et al. (1990). For the
Calabrese et al. (1997a) study in Anaconda, Montana,
population demographics were not presented in the
published article. The study sample appeared to have
been drawn from a door-to-door census of Anaconda
residents that identified 642 toilet trained children who
were less than 72 months of age. Of the 414 children
participating in a companion study (out of the 642
eligible children identified), 271 had complete study
data for that companion study, and of these 271, 97.4
percent were identified as white and the remaining 2.6
percent were identified as native American, black,
Asian and Hispanic (Hwang et al., 1997). The 64
children in the Calabrese et al. (1997a) study apparently
were a stratified random sample drawn from the 642
children identified in the door-to-door census.
Presumably these children identified as similar races
and ethnicities to the Hwang et al. (1997) study
children. The Calabrese et al. (1997b) study indicated
that 11 of the 12 children studied were white.
5.5 SUMMARY OF SOIL AND DUST
INGESTION ESTIMATES FROM KEY
STUDIES
Table 5-19 summarizes the soil and dust
ingestion estimates from the 9 key studies. Forthe U.S.
tracer element studies, in order to compare estimates
that were calculated in a similar manner, the summary
is limited to estimates that use the same basic algorithm
of ((fecal and urine tracer content) - (food and
medication tracer content))/(soil or dust tracer
concentration). Note that several of the published
reanalyses suggested different variations on these
algorithms, or suggest adjustments that should be made
for various reasons. However, because individual
observations were not available from the studies with
reanalyzed data, those reanalyzed estimates were not
included in the summary table. Other reanalyses
suggested that omitting some of the data according to
statistical criteria would be a worthwhile exercise. Due
to the current state of the science regarding soil and
dust ingestion estimates, U.S. EPA does not advise
omitting an individual child's soil or dust ingestion
estimate, based on statistical criteria, at this point in
time.
There is a wide range of estimated soil and
dust ingestion across key studies. Note that some of the
soil-pica ingestion estimates from the tracer element
studies were consistent with the estimated mean soil
ingestion from the survey response study of geophagy
behavior. Also note that the biokinetic model
comparison methodology's confirmation of central
tendency soil and dust ingestion default assumptions
corresponded roughly with some of the central
tendency tracer element study estimates.
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5.6
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Parnell, C.B.; Jones, D.D.; Rutherford, R.D.; Goforth,
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Powell, J.J.; Ainley, C.C.; Harvey, R.S.; Mason, I.M.;
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Stanek, E.J., and Calabrese, E.J. (1995a) Daily
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1:133-156.
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ingestion estimates for children at a Superfund
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Stanek, E.J.; Calabrese, E.J.; Mundt, K.; Pekow, P.;
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Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
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Page
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-3. Soil, Dust and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study Children
Tracer Element
Aluminum
soil
dust
soil/dust
combined
Barium
soil
dust
soil/dust
combined
Manganese
soil
dust
soil/dust
combined
Silicon
soil
dust
soil/dust
combined
Vanadium
soil
dust
soil/Must
combined
Yttrium
soil
dust
soil/dust
combined
Zirconium
soil
dust
soil/dust
combined
Titanium
soil
dust
soil/dust
combined
SD = Standard devi
Source: Calabrese et al.,
N
64
64
64
64
64
64
64
64
64
64
64
64
62
64
62
62
64
62
62
64
62
64
64
64
ation.
1989.
Ingestion (mg/day)
Mean
153
317
154
32
31
29
-294
-1,289
-496
154
964
483
459
453
456
85
62
65
21
27
23
218
163
170
Median
29
31
30
-37
-18
-19
-261
-340
-340
40
49
49
96
127
123
9
15
11
16
12
11
55
28
30
SD
852
1,272
629
1,002
860
868
1,266
9,087
1,974
693
6,848
3,105
1,037
1,005
1,013
890
687
717
209
133
138
1,150
659
691
95th Percentile
223
506
478
283
337
331
788
2,916
3,174
276
692
653
1,903
1,918
1,783
106
169
159
110
160
159
1,432
1,266
1,059
Maximum
6,837
8,462
4,929
6,773
5,480
5,626
7,281
20,575
4,189
5,549
54,870
24,900
5,676
6,782
6,736
6,736
5,096
5,269
1,391
789
838
6,707
3,354
3,597
Child-Specific Exposure Factors Handbook
September 2008
Page
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-4. Amherst,
Tracer
element
Al
Ba
Mn
Si
Ti
V
Y
Zr
Massachusetts Soil-Pica Child's Daily
Week
74
458
2,221
142
1,543
1,269
147
86
Ingestion Estimates by Tracer and by Week (mg/day)
Estimated Soil Ingestion (mg/day)
1 Week 2
13,600
12,088
12,341
10,955
11,870
10,071
13,325
2,695
Source: Calabrese et al., 1991.
Page Child-Specific Exposure Factors Handbook
5-32 September 2008
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-5. Amherst, Massachusetts Soil-Pica Child's Tracer Ratios
Tracer Pairs
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Source:
Mn/Ti
Ba/Ti
Si/Ti
V/Ti
Ai/Ti
Y/Ti
Mn/Y
Ba/Y
Si/Y
V/Y
Al/Y
Mn/Al
Ba/Al
Si/Al
V/A1
Si/V
Mn/Si
Ba/Si
Mn/Ba
Calabrese and St
Soil
208.368
187.448
148.117
14.603
18.410
8.577
24.293
21.854
17.268
1.702
2.146
11.318
10.182
8.045
0.793
10.143
1.407
1.266
1.112
mek, 1992.
Ratio
Fecal
215.241
206.191
136.662
10.261
21.087
9.621
22.373
21.432
14.205
1.067
2.192
10.207
9.778
6.481
0.487
13.318
1.575
1.509
1.044
Dust
260.126
115.837
7.490
17.887
13.326
5.669
45.882
20.432
1.321
3.155
2.351
19.520
8.692
0.562
1.342
0.419
34.732
15.466
2.246
Estimated Residual Fecal
Tracers of Soil Origin as
Predicted by Specific
Tracer Ratios (%)
87
100
92
100
100
100
100
71
81
100
88
100
73
81
100
100
99
83
100
Child-Specific Exposure Factors Handbook Page
September 2008 5-33
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-6. Van W'ijnen et al
., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for
Daycare Centers
Age (years) Sex
Birth to <1
1 to <2
2 to <3
3 to <4
4 to <5
All girls
All boys
Total
Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys
N
3
1
20
17
34
17
26
29
1
4
86
72
162"
" Age and/or sex not registered for 8 children
b
N
GM
LTM
GSD
NA
Source:
Age not registered for 7 ch
- Number of subjects.
- Geometric mean.
- Limiting tracer method.
GM LTM
(mg/day)
81
75
124
114
118
96
111
110
180
99
117
104
111
one untransformec
ildren; geometric mean LTM value -
GSD LTM
(mg/day)
1.09
-
1.87
1.47
1.74
1.53
1.57
1.32
_
1.62
1.70
1.46
1.60
value - 0.
140.
N
NA
NA
3
5
4
8
6
8
19
18
36
42
78"
Sample of Dutch Children
Campgrounds
GM LTM
(mg/day)
NA
NA
207
312
367
232
164
148
164
136
179
169
174
GSD LTM
(mg/day)
NA
NA
1.99
2.58
2.44
2.15
1.27
1.42
1.48
1.30
1.67
1.79
1.73
- Geometric standard deviation.
- Not available.
Adapted from Van W'ijnen
et al., 1990.
Page
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Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-7. Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period
Weather Category
Bad
(>4 days/week
precipitation)
Reasonable
(2-3 days/week
precipitation)
Good
(<2 days/week
precipitation)
Age (years)
<1
1 to <2
2 to <3
4 to <5
<1
1 to <2
2 to <3
3 to <4
4 to <5
<1
1 to <2
2 to <3
3 to <4
4 to <5
First Sampling Period
Estimated
Geometric Mean
N
LTM Value
(mg/day)
3 94
18 103
33 109
5 124
4 102
42 229
65 166
67 138
10 132
Second Sampling Period
Estimated
Geometric Mean
N
LTM Value
(mg/day)
3 67
33 80
48 91
6 109
1 61
10 96
13 99
19 94
1 61
N - Number of subjects.
LTM - Limiting tracer method.
Source: Van Wi'inen
etal., 1990.
Table 5-1
Mean
Element
(mg/day)
Aluminum
Silicon
Titanium
Minimum
Maximum
b
Source:
38.9
82.4
245.5
38.9
245.5
Excludes three children who
Negative values occurred as
published as 279.0 mg/day in
. Estimated Soil Ingestion for Sample of Washington State Children a
Standard Error of the
Median Range
(mg/day) (mg/day)b
(mg/day)
25.3 14.4 -279.0 to 904.5
59.4 12.2 -404.0 to 534.6
81.3 119.7 -5,820.8 to 6,182.2
25.3 12.2 -5,820.8
81.3 119.7 6,182.2
did not provide any samples (N=101).
i result of correction for non-soil sources of the tracer elements. For aluminum, lower end of range
article appears to be a typographical error that omitted the negative sign.
Adapted from Davis et al., 1990.
Child-Specific Exposure Factors Handbook
September 2008
Page
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Tracer
Al
Ce
La
Nd
Si
Ti
Y
Zr
P
SD
Note:
Source:
Table 5-9. Soil Ingestion Estimates for 64 Anaconda
Estimated Soil Ingestion (mg/da
PI P50 P75 P90 P95
-202.8 -3.3 17.7 66.6 94.3
-219.8 44.9 164.6 424.7 455.8
-10,673 84.5 247.9 460.8 639.0
-387.2 220.1 410.5 812.6 875.2
-128.8 -18.2 1.4 36.9 68.9
-15,736 11.9 398.2 1,237.9 1,377.8
-441.3 32.1 85.0 200.6 242.6
-298.3 -30.8 17.7 94.6 122.8
- Percentile.
- Standard deviation.
Negative values are a result of limitations in the methodology.
Calabrese et al., 1997a.
Children
y)
Max Mean SD
461.1 2.7 95.8
862.2 116.9 186.1
1,089.7 8.6 1,377.2
993.5 269.6 304.8
262.3 -16.5 57.3
4,066.6 -544.4 2,509.0
299.3 42.3 113.7
376.1 -19.6 92.5
Table 5-10. Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior (mg/day)
Study day
1
2
3
4
5
6
7
Al-based estimate
53
7,253
2,755
725
5
1,452
238
Si-based estimate
9
2,704
1,841
573
12
1,393
92
Ti-based estimate
153
5,437
2,007
801
21
794
84
Source: Calabrese et al., 1997b.
Page
5-36
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-11. Soil Ingestion Estimates for Sample of 12 Washington State Children a
Estimated Soil Ingestion b
T r-i » (mg/day)
Tracer Element
Mean Median SD Maximum
Aluminum
Silicon
Titanium
36.7
38.1
206.9
33.3
26.4
46.7
35.4
31.4
277.5
107.9
95.0
808.3
a For some study participants, estimated soil ingestion resulted in a negative value. These estimates have been set to zero mg/day for
tabulation and analysis.
b Results based on 12 children with complete food, excreta and soil data.
SD = Standard deviation.
Source: Davis and Mirick, 2006.
Child-Specific Exposure Factors Handbook Page
September 2008 5-37
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children
Child Month Estimated soil ingestion (mg/day)
11 1 55
2 1,447
3 22
4 40
12 1 0
2 0
3 7,924
4 192
14 1 1,016
2 464
3 2,690
4 898
18 1 30
2 10,343
3 4,222
4 1,404
22 1 0
2
3 5,341
4 0
27 1 48,314
2 60,692
3 51,422
4 3,782
- No data.
Source: Calabrese and Stanek, 1993.
Page Child-Specific Exposure Factors Handbook
5-38 September 2008
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Estimation
Method
Aluminum
Silicon
Titanium
Minimum
Source: Binder et al.
Table 5
Mean
(mg/day)
181
184
1,834
108
1986.
13. Estimated Daily
Median
(mg/day)
121
136
618
88
Soil Ingestion for East Helena, Montana Children
Standard
Deviation
(mg/day)
203
175
3,091
121
Range
(mg/day)
25-1,324
31-799
4-17,076
4-708
95th Percentile
(mg/day)
584
578
9,590
386
Geometric Mean
(mg/day)
128
130
401
65
Table 5-14. Estimated Soil Ingestion for Sample of Dutch Nursery
Child
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Arithmetic Mean
- No data.
Source: Adapted from
Sample
Number
L3
L14
L25
L5
L13
L27
L2
L17
L4
Lll
L8
L21
L12
L16
L18
L22
LI
L6
L7
L9
L10
L15
L19
L20
L23
L24
L26
Clausing et al., 1987.
Soil Ingestion as
Calculated from Ti
(mg/day)
103
154
130
131
184
142
124
670
246
2,990
293
313
1,110
176
11,620
11,320
3,060
624
600
133
354
2,400
124
269
1,130
64
184
1,431
Soil Ingestion as
Calculated from Al
(mg/day)
300
211
23
_
103
81
42
566
62
65
_
-
693
-
_
77
82
979
200
-
195
-
71
212
51
566
56
232
School Children
Soil Ingestion as
Calculated from
AIR
(mg/day)
107
172
-
71
82
84
84
174
145
139
108
152
362
145
120
-
96
111
124
95
106
48
93
274
84
-
-
129
Limiting Tracer
(mg/day)
103
154
23
71
82
81
42
174
62
65
108
152
362
145
120
77
82
111
124
95
106
48
71
212
51
64
56
105
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Child
1
2
3
4
5
6
Arithmetic Mean
Source: Adapted
Table 5-15. Estimated
Sample
G5
G6
Gl
G2
G8
G3
G4
G7
from Clausing et al., 1987.
Soil Ingestion for Sample of Dutch
Soil Ingestion as
Calculated from Ti
(mg/day)
3,290
4,790
28
6,570
2,480
28
1,100
58
2,293
Hospitalized, Bedridden Children
Soil Ingestion as
Calculated from Al
(mg/day)
57
71
26
94
57
77
30
38
56
Limiting Tracer
(mg/day)
57
71
26
84
57
28
30
38
49
Table 5-16. Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989) Study:
Effect on Mean Soil Ingestion Estimate (mg/day)a
Tracer
Aluminum
Silicon
Titanium
Vanadium
Yttrium
Zirconium
Lack of Fecal
Sample on .
Other Causes
Final Study
Day
14
15
82
66
8
6
11
6
187
55
26
91
Total
Negative
Error
25
21
269
121
34
97
Negative Error
Total Positive
Error
43
41
282
432
22
5
Net Error
+ 18
+20
+ 13
+311
-12
-92
a How to read table: for example, aluminum as a soil tracer displayed both negative and positive error
negative error is estimated to bias the mean estimate by 25 mg/day downward. However, aluminum
original mean upward by 43 mg/day. The net bias in the original mean was 1 8 mg/day positive bias
mg/day mean for aluminum should be corrected downward to 136 mg/day.
b Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
Source:
Calabrese and Stanek, 1995
Original
Mean
153
154
218
459
85
21
Adjusted
Mean
136
133
208
148
97
113
The cumulative total
has positive error biasing the
Thus, the original 156
Page
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
Table 5-17. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children (mg/day)
Type of Estimate
Overall
Al
Ba
Mn
Ti
V
Y
Zr
Number of Samples
64
64
33
19
63
56
61
62
Mean
25th Percentile
50th Percentile
75th Percentile
90th Percentile
95th Percentile
Maximum
179
10
45
88
186
208
7,703
122
10
19
73
131
254
655
28
65
260
470
518
17,991
1,053
35
121
319
478
17,374
17,374
139
5
32
94
206
224
4,975
271
8
31
93
154
279
12,055
112
8
47
177
340
398
845
165
0
15
47
105
144
8,976
23
0
15
41
87
117
208
a For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then evaluated for each
child. The values in the column "overall" correspond to percentiles of the distribution of these means over the 64 children. When
specific trace elements were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the
specific trace element were formed for 108 days for each subject. The mean soil ingestion estimate was again evaluated. The
distribution of these means for specific trace elements is shown.
Source: Stanek and Calabrese, 1995a.
Table 5-18. Estimated Distribution of Individual Mean Daily Soil Ingestion
Based on Data for 64 Subjects Projected over 365 Daysa
Range
50th Percentile (median)
90th Percentile
95th Percentile
1 - 2,268 mg/db
75 mg/d
1,190 mg/d
1,751 mg/d
a Based on fitting a log-normal distribution to model daily soil ingestion values.
b Subject with pica excluded.
Source: Stanek and Calabrese, 1995a.
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Chapter 5 - Ingestion of Soil and Dust
Table 5- 19. Summary of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from Key Studies (mg
Sample Age Ingestion Mean P25 P50 P75 P90 P95
Size (years) medium
292 0.1-<1 Soil Oto30" NR NR NR NR NR
1 - <5 Soil 0 to 200" NR NR NR <300 NR
101 2-<8 Soil 39 to 246 NR 25 to 81 NR NR NR
Soil and Dust 65 to 268 NR 52 to 117 NR NR NR
64 l-<4 Soil -294to+459 NR -261 to +96 NR 67 to 1,366 106 to 1,903
Dust -l,289to+964 NR -340 to +127 NR 91 to 1,700 160 to 2,916
SoilandDust -496to+483 NR -340 to +456 NR 89 to 1,701 159to3,174
12 3-<8 Soil 37 to 207 NR 26 to 47 NR NR NR
64 l-<4 Soil -544to+270 -582 - +65 -31to+220 Ito411 37 to 1,238 69 to 1,378
478 <1 - <7 SoilandDust 113 NR NR NR NR NR
140 1-13+ Soil 50,000" NR NR NR NR NR
52 0.3 - 14 Soil NR NR NR NR -1,267 -4,000
/day)
Reference
Van Wijnen et
al., 1990
Davis et al.,
1990
Calabrese et al.,
1989
Davis and
Mirick, 2006
Calabrese et al.,
1997a
Hogan et al.,
1998
Vermeer and
Frate, 1979
Wong
(1988)/Calabres
e and Stanek
(1993)
a Geometric mean.
b Average includes adults and children.
NR = Not reported.
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Chapter 12 - Intake of Grain Products
TABLE OF CONTENTS
12 INTAKE OF GRAIN PRODUCTS 12-1
12.1 INTRODUCTION 12-1
12.2 RECOMMENDATIONS 12-2
12.3 INTAKE STUDIES 12-6
12.3.1 Key Grain Intake Study 12-6
12.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 12-6
12.3.2 Relevant Grain Intake Studies 12-7
12.3.2.1 USDA, 1999 12-7
12.3.2.2 Smiciklas-Wright et al, 2002 12-8
12.3.2.3 Fox et al., 2004 12-8
12.3.2.4 Ponza et al., 2004 12-9
12.3.2.5 Mennella et al., 2006 12-9
12.3.2.6 Fox et al., 2006 12-10
12.4 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES 12-10
12.5 REFERENCES FOR CHAPTER 12 12-10
APPENDIX 12A 12A-1
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LIST OF TABLES
Table 12-1. Recommended Values for Intake of Grains, As Consumed 12-3
Table 12-2. Confidence in Recommendations for Intake of Grain Products 12-4
Table 12-3. Per Capita Intake of Total Grains (g/kg-day as consumed) 12-12
Table 12-4. Consumer Only Intake of Total Grains (g/kg-day as consumed) 12-12
Table 12-5. Per Capita Intake of Individual Grain Products (g/kg-day as consumed) 12-13
Table 12-6. Consumer Only Intake of Individual Grain Products (g/kg-day as consumed) 12-13
Table 12-7. Mean Quantities of Grain Products Consumed Daily by Sex and Age, Per Capita (g/day) ... 12-14
Table 12-8. Percentage of Individuals Consuming Grain Products, by Sex and Age (%) 12-15
Table 12-9. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days 12-16
Table 12-10. Characteristics of the FITS Sample Population 12-17
Table 12-11. Percentage of Infants and Toddlers Consuming Different Types of Grain Products 12-18
Table 12-12. Characteristics of WIC Participants and Nonparticipants (Percentages) 12-19
Table 12-13. Food Choices for Infants and Toddlers by WIC Participation Status 12-20
Table 12-14. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Grain Products on A Given Day 12-21
Table 12-15. Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
by Infants from the 2002 Feeding Infants and Toddlers Study 12-22
Table 12-16. Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
by Toddlers from the 2002 Feeding Infants and Toddlers Study 12-22
Table 12-17. Mean Moisture Content of Selected Grain Products Expressed as Percentages
of Edible Portions 12-23
Table 12A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data . . . 12A-2
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Chapter 12 - Intake of Grain Products
12 INTAKE OF GRAIN PRODUCTS
12.1 INTRODUCTION
The American food supply is generally
considered to be one of the safest in the world.
Nevertheless, grain products may become contaminated
with toxic chemicals by several different pathways.
Ambient air pollutants may be deposited on or absorbed
by the plants, or dissolved in rainfall or irrigation
waters that contact the plants. Pollutants may also be
absorbed through plant roots from contaminated soil
and ground water. The addition of pesticides, soil
additives, and fertilizers may also result in
contamination of grain products. To assess exposure
through this pathway, information on ingestion rates of
grain products are needed.
Children's exposure from contaminated foods
may differ from that of adults because of differences in
the type and amounts of food eaten. Also, for many
foods, the intake per unit body weight is greater for
children than for adults. Common grain products eaten
by children include milled rice, oats, and wheat flour
(Goldman, 1995).
A variety of terms may be used to define
intake of grain products (e.g., consumer-only intake, per
capita intake, total grain intake, as-consumed intake,
dry weight intake). As described in Chapter 9, Intake
of Fruits and Vegetables, consumer-only intake is
defined as the quantity of grain products consumed by
children during the survey period. These data are
generated by averaging intake across only the children
in the survey who consumed these food items. Per
capita intake rates are generated by averaging
consumer-only intakes over the entire population of
children (including those children that reported no
intake). In general, per capita intake rates are
appropriate for use in exposure assessment for which
average dose estimates for children are of interest
because they represent both children who ate the foods
during the survey period and children who may eat the
food items at some time, but did not consume them
during the survey period. Per capita intake, therefore,
represents an average across the entire population of
interest, but does so at the expense of underestimating
consumption for the subset of the population that
consumed the food in question. Total grain intake
refers to the sum of all grain products consumed in a
day.
Intake rates may be expressed on the basis of
the as-consumed weight (e.g., cooked or prepared) or
on the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it is consumed and should be used in
assessments where the basis for the contaminant
concentrations in foods is also indexed to the as-
consumed weight. The food ingestion values provided
in this chapter are expressed as as-consumed intake
rates because this is the fashion in which data were
reported by survey respondents. This is of importance
because concentration data to be used in the dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease food weight. Similarly, cooking can
increase the mass of contaminant in food (due to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching). The combined
effects of changes in weight and changes in contaminant
mass can result in either an increase or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated. Ideally, after-
cooking food concentrations should be combined with
the as-consumed intake rates. In the absence of data, it
is reasonable to assume that no change in contaminant
concentration occurs after cooking. It is important for
the assessor to be aware of these issues and choose
intake rate data that best match the concentration data
that are being used. For more information on cooking
losses and conversions necessary to account for such
losses, the reader is referred to Chapter 13 of this
handbook.
Sometimes contaminant concentrations in food
are reported on a dry weight basis. When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used. Dry-weight food
concentrations and intake rates are based on the weight
of the food consumed after the moisture content has
been removed. For information on converting the
intake rates presented in this chapter to dry weight
intake rates, the reader is referred to Section 12.4.
The purpose of this chapter is to
provide intake data for grain products among children.
The recommendations for ingestion rates of grain
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Chapter 12 - Intake of Grain Products
products are provided in the next section, along with a
summary of the confidence ratings for these
recommendations. The recommended values are based
on the key study identified by U. S. EPA for this factor.
Following the recommendations, the key study on
ingestion of grain products is summarized. Relevant
data on ingestion of grain products are also provided.
These data are presented to provide the reader with
added perspective on the current state-of-knowledge
pertaining to ingestion of grain products among
children.
12.2 RECOMMENDATIONS
Tables 12-1 presents a summary of the
recommended values for per capita and consumers-only
intake of grain products, on an as consumed basis.
Confidence ratings for the grain intake
recommendations for general population children are
provided in Table 12-2.
The U.S. EPA analysis of data from the 1994-
96 and 1998 Continuing Survey of Food Intake among
Individuals (CSFII) was used in selecting recommended
intake rates for general population children. The U. S.
EPA analysis was conducted using age groups that
differed slightly from U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis. Also, the CSFII data on which the
recommendations are based are short-term survey data
and may not necessarily reflect the long-term
distribution of average daily intake rates. However, for
broad categories of food (i.e., total grains), because
they are eaten on a daily basis throughout the year with
minimal seasonality, the short term distribution may be
a reasonable approximation of the long-term
distribution, although it will display somewhat
increased variability. This implies that the upper
percentiles shown here will tend to overestimate the
corresponding percentiles of the true long-term
distribution. It should also be noted that because these
recommendations are based on 1994-96 and 1998
CSFII data, they may not reflect the most recent
changes that may have occurred in consumption
patterns. More current data from the National Health
and Nutrition Survey (NHANES) will be incorporated
as the data become available and are analyzed.
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Chapter 12 - Intake of Grain Products
Table 12-1 . Recommended Values for Intake of Grains, As Consumed*
Per Capita Consumers Only
Age Group
Mean
g/kg-day
95th Percentile Mean
g/kg-day g/kg-day
95th Percentile percentiles
g/kg-day
Source
Total Grains
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
2.5
6.4
6.4
6.3
4.3
2.5
2.5
8.6 3.6
12 6.4
12 6.4
12 6.3
8.2 4.3
5.1 2.5
5.1 2.5
Individual Grain Products - See Tables
9.2
12
12
12 See Tables
„ 2 12-3 and
12-4
5.1
5.1
12-5 and 12-6
U.S. EPA
Analysis of
CSFII,
1994-96 and
1998.
1 Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005).
Data were placed in the standardized age categories closest to those used in the analysis.
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Chapter 12 - Intake of Grain Products
Table 12-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Minimal Uncertainty
Confidence in Recommendations for Intake of Grain Products
Rationale
The survey methodology and data analysis was
adequate. The survey sampled more than 1 1,000
individuals up to age 18 years. An analysis of primary
data was conducted.
No physical measurements were taken. The method
relied on recent recall of grain products eaten.
The key study was directly relevant to grain intake.
The data were demographically representative of the
U.S. population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total grains.
Means were provided for individual grain products.
Data collection was based on recall for a 2-day period;
the accuracy of using these data to estimate long-term
intake (especially at the upper percentiles) is uncertain.
However, use of short-term data to estimate chronic
ingestion can be assumed for broad categories of foods
such as total grains. Uncertainty is likely to be greater
for individual grain products.
Rating
High
Medium
High
Medium
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Chapter 12 - Intake of Grain Products
Table 12-2. Confidence in Recommendations for Intake of Grain Products (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not
been peer reviewed outside the Agency.
There was 1 key study.
Rating
Medium
High confidence in the
averages;
Low confidence in the
long-term upper
percentiles
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Chapter 12 - Intake of Grain Products
12.3 INTAKE STUDIES
The primary source of recent information on
consumption rates of grain products among children is
the U.S. Department of Agriculture's (USDA) CSFII.
Data from the 1994-96 CSFII and the 1998 Children's
supplement to the 1994-96 CSFII have been used in
various studies to generate children's consumer-only
and per capita intake rates for both individual grain
products and total grains. The CSFII is a series of
surveys designed to measure the kinds and amounts of
foods eaten by Americans. The CSFII 1994-96 was
conducted between January 1994 and January 1997
with a target population of non-institutionalized
individuals in all 50 states and Washington, D.C. In
each of the 3 survey years, data were collected for a
nationally representative sample of individuals of all
ages. The CSFII 1998 was conducted between
December 1997 and December 1998 and surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-96 and was intended
to be merged with CSFII 1994-96 to increase the
sample size for children. The merged surveys are
designated as CSFII 1994-96, 1998. Additional
information on these surveys can be obtained at
littp://w\\-\v.ars.usda.sov/Services/docs. htm ?docid=14531.
The CSFII 1994-96, 1998 collected dietary
intake data through in-person interviews on 2 non-
consecutive days. The data were based on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day. Over 11,000 of the sample persons
represented children up to 18 years of age. The 2-day
response rate for the 1994-1996 CSFII was
approximately 76 percent. The 2-day response rate for
CSFII 1998 was 82 percent.
The CSFII 1994-96,98 surveys were based on
a complex multistage area probability sample design.
The sampling frame was organized using 1990 U.S.
population census estimates, and the stratification plan
took into account geographic location, degree of
urbanization, and socioeconomic characteristics.
Several sets of sampling weights are available for use
with the intake data. By using appropriate weights, data
for all fours years of the surveys can be combined.
USDA recommends that all 4 years be combined in
order to provide an adequate sample size for children.
12.3.1 Key Grain Intake Study
12.3.1.1 U.S. EPA Analysis of CSFII 1994-96,
1998
For many years, the U.S. EPA's Office of
Pesticide Programs (OPP) has used food consumption
data collected by the U.S. Department of Agriculture
(USDA) for its dietary risk assessments. Most recently,
OPP, in cooperation with USDA's Agricultural
Research Service (ARS), used data from the 1994-96,
1998 CSFII to develop the Food Commodity Intake
Database (FCID). CSFII data on the foods people
reported eating were converted to the quantities of
agricultural commodities eaten. "Agricultural
commodity" is a term used by U. S. EPA to mean plant
(or animal) parts consumed by humans as food; when
such items are raw or unprocessed, they are referred to
as "raw agricultural commodities." For example, an
apple pie may contain the commodities apples, flour,
fat, sugar and spices. FCID contains approximately 553
unique commodity names and 8-digit codes. The FCID
commodity names and codes were selected and defined
by U.S. EPA and were based on the U.S. EPA Food
Commodity Vocabulary
(httgV/www^epa.gov/pesticides^oodfegd/).
The grain items/groups selected for the
U.S. EPA analysis included total grains, and individual
grain products such as cereal and rice. Appendix 12A
presents the food codes and definitions used to
determine the various grain products used in the
analysis. Intake rates for these food items/groups
represent intake of all forms of the product (e.g., both
home produced and commercially produced). Children
who provided data for two days of the survey were
included in the intake estimates. Individuals who did
not provide information on body weight or for whom
identifying information was unavailable were excluded
from the analysis. Two-day average intake rates were
calculated for all individuals in the database for each of
the food items/groups. These average daily intake rates
were divided by each individual's reported body weight
to generate intake rates in units of grams per kilogram
of body weight per day (g/kg-day). The data were
weighted according to the four-year, two-day sample
weights provided in the 1994-96,1998 CSFII to adjust
the data for the sample population to reflect the national
population.
Summary statistics were generated on both
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a per capita and a consumer only basis. For per capita
intake, both users and non-users of the food item were
included in the analysis. Consumer-only intake rates
were calculated using data for only those individuals
who ate the food item of interest during the survey
period. Intake data from the CSFII are based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the grain product being analyzed, mean intake rate, and
standard error of the mean intake rate were calculated
for total grains and selected individual grain products.
Percentiles of the intake rate distribution (i.e., 1st, 5th,
10th, 25th, 50th, 75th, 90th, 95th, 99th, and 100th
percentile were also provided for total grains. Data
were provided for the following age groups of children:
birth to <1 year, 1 to <2 years, 3 to <5 years, 6 to <12
years, and 13 to <19 years. Because these data were
developed for use in U.S. EPA's pesticide registration
program, the age groups used are slightly different than
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).
Tables 12-3 presents as-consumed per
capita intake data for total grains in g/kg-day; as-
consumed consumer only intake data for total grains in
g/kg-day are provided in Table 12-4. Table 12-5
provides per capita intake data for individual grain
products and Table 12-6 provides consumer only intake
data for individual grain products.
It should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the long-
term distribution of average daily intake rates. The
distributions generated from short-term and long-term
data will differ to the extent that each individual's
intake varies from day to day; the distributions will be
similar to the extent that individuals' intakes are
constant from day to day. However, for broad
categories of foods (e.g., total grains) that are eaten on
a daily basis throughout the year, the short-term
distribution may be a reasonable approximation of the
true long-term distribution, although it will show
somewhat more variability. In this chapter,
distributions are provided only for total grains.
Because of the increased variability of the short-term
distribution, the short-term upper percentiles shown
here may overestimate the corresponding percentiles of
the long-term distribution. For individual grains, only
the mean, standard error, and percent consuming are
provided.
The strengths of U.S. EPA's analysis are
that it provides distributions of intake rates for various
age groups of children, normalized by body weight.
The analysis uses the 1994-96, 1998 CSFII data set
which was designed to be representative of the U.S.
population. The data set includes four years of intake
data combined, and is based on a two-day survey
period. As discussed above, short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food. This is particularly true for the tails (extremes)
of the distribution of food intake. Also, the analysis
was conducted using slightly different age groups that
those recommended in U.S. EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the age groups used, the data should provide suitable
intake estimates for the age groups of interest.
12.3.2 Relevant Grain Intake Studies
12.3.2.1 USDA, 1999-Food and Nutrient Intakes
by Children 1994-96,1998, Table Set 17
USDA (1999) calculated national
probability estimates of food and nutrient intake by
children based on all 4 years of the CSFII (1994-96 and
1998) for children age 9 years and under, and on CSFII
1994-96 only for individuals age 10 years and over.
Sample weights were used to adjust for non-response,
to match the sample to the U.S. population in terms of
demographic characteristics, and to equalize intakes
over the 4 quarters of the year and the 7 days of the
week. A total of 503 breast-fed children were excluded
from the estimates, but both consumers and non-
consumers were included in the analysis.
USDA (1999) provided data on the mean
per capita quantities (grams) of various food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey. Tables 12-7 and 12-8 present
data on the mean quantities (grams) of grain products
consumed per individual for one day, and the
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percentage of survey individuals consuming grain
products that survey day. Data on mean intakes or
mean percentages are based on respondents' day-1
intakes.
The advantages of USD A (1999) study is
that it uses the 1994-96, 98 CSFII data set, which
includes four years of intake data, combined, and
includes the supplemental data on children. These data
are expected to be generally representative of the U.S.
population and they include data on a wide variety of
grain products. The data set is one of a series of USD A
data sets that are publicly available. One limitation of
this data set is that it is based on a one-day, and short-
term dietary data may not accurately reflect long-term
eating patterns. Other limitations of this study are that
it only provides mean values of food intake rates,
consumption is not normalized by body weight, and
presentation of results is not consistent with U.S. EPA's
recommended age groups.
12.3.2.2 Smiciklas-Wright et al, 2002 - Foods
Commonly Eaten in the United States:
Quantities Consumed per Eating
Occasion and in a Day, 1994-1996
Using data gathered in the 1994-96 USDA
CSFII, Smiciklas-Wright et al. (2002) calculated
distributions for the quantities of grain products
consumed per eating occasion by members of the U. S.
population (i.e., serving sizes). The estimates of
serving size are based on data obtained from 14,262
respondents, ages 2 and above, who provided 2 days of
dietary intake information. A total of 4,939 of these
respondents were children, ages 2 to 19 years of age.
Only dietary intake data from users of the specified
food were used in the analysis (i.e., consumers only
data).
Table 12-9 presents serving size data for
selected grain products. These data are presented on an
as-consumed basis (grams) and represent the quantity of
grain products consumed per eating occasion. These
estimates may be useful for assessing acute exposures
to contaminants in specific foods, or other assessments
where the amount consumed per eating occasion is
necessary. Only the mean and standard deviation
serving size data and percent of the population
consuming the food during the 2-day survey period are
presented in this handbook. Percentiles of serving sizes
of the foods consumed by these age groups of the U.S.
population can be found in Smiciklas-Wright et al.
(2002).
The advantages of using these data are that
they were derived from the USDA CSFII and are
representative of the U.S. population. The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
for individual foods consumed as ingredients of mixed
foods. Mixed foods were disaggregated via recipe files
so that the individual ingredients could be grouped
together with similar foods that were reported
separately. Thus, weights of foods consumed as
ingredients were combined with weights of foods
reported separately to provide a more thorough
representation of consumption. However, it should be
noted that since the recipes for the mixed foods
consumed were not provided by the respondents,
standard recipes were used. As a result, the estimates
of quantity consumed for some food types are based on
assumptions about the types and quantities of
ingredients consumed as part of mixed foods. This
study used data from the 1994 to 1996 CSFII; data from
the 1998 children's supplement were not included.
12.3.2.3 Fox et al., 2004 - Feeding Infants and
Toddlers study: What Foods Are Infants
and Toddlers Eating
Fox et al. (2004) used data from the
Feeding Infants and Toddlers study (FITS) to assess
food consumption patterns in infants and toddlers. The
FITS was sponsored by Gerber Products Company and
was conducted to obtain current information on food
and nutrient intakes of children, ages 4 to 24 months
old, in the 50 states and the District of Columbia. The
FITS is described in detail in Devaney et al. (2004).
FITS was based on a random sample of 3,022 infants
and toddlers for which dietary intake data were
collected by telephone from their parents or caregivers
between March and July 2002. An initial recruitment
and household interview was conducted, followed by an
interview to obtain information on intake based on 24-
hour recall. The interview also addressed growth,
development and feeding patterns. A second dietary
recall interview was conducted for a subset of 703
randomly selected respondents. The study over-
sampled children in the 4 to 6 and 9 tol 1 months age
groups; sample weights were adjustedfornon-response,
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12-8
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
over sampling, and under coverage of some subgroups.
The response rate for the FITS was 73 percent for the
recruitment interview. Of the recruited households,
there was a response rate of 94 percent for the dietary
recall interviews (Devaney et al, 2004). The
characteristics of the FITS study population is shown in
Table 12-10.
Fox et al. (2004) analyzed the first set of
24-hour recall data collected from all study participants.
For this analysis, children were grouped into six age
categories: 4 to 6 months, 7 to 8 months, 9 to 11
months, 12 to 14 months, 15 to 18 months, and 19 to 24
months. Table 12-11 provides the percentage of infants
and toddlers consuming different types of grains or
grain products at least once in a day. The percentages
of children eating any type of grain or grain product
ranged from 65.8 percent for 4 to 6 month olds to 99.2
percent for 19 to 24 month olds.
The advantages of this study were that the
study population represents the U.S. population and the
sample size was large. One limitation of the analysis
done by Fox et al. (2004) is that only frequency data
were provided; no information on actual intake rates
was included. In addition, Devaney et al (2004) noted
several limitations associated with the FITS data. For
the FITS, a commercial list of infants and toddlers was
used to obtain the sample used in the study. Since
many of the household could not be located and did not
have children in the target population, a lower response
rate than would have occurred in a true national sample
was obtained (Devaney et al., 2004). In addition, the
sample was likely from a higher socioeconomic status
when compared with all U.S. infants in this age group
(4 to 24 months old) and the use of a telephone survey
may have omitted lower-income households without
telephones (Devaney et al., 2004).
12.3.2.4 Ponza et al, 2004 - Nutrient Food
Intakes and Food Choices of Infants and
Toddlers Participating in WIC
Ponza et al. (2004) conducted a study using
selected data from the FITS to assess feeding patterns,
food choices and nutrient intake of infants and toddlers
participating in the Special Supplemental Nutrition
Program for Women, Infants, and Children (WIC).
Ponza et al. (2004) evaluated FITS data for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months (N = 1,159) and 12 to 24 months (N= 996).
The total sample size described by WIC participants
and non-participants is shown in Table 12-12.
The foods consumed were analyzed by
tabulating the percentage of infants who consumed
specific foods/food groups per day (Ponza et al., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza et al., 2004). Table 12-12 presents the
demographic data for WIC participants and non-
participants. Table 12-13 provides information on the
food choices for the infants and toddlers studied. In
general, there was little difference in grain product
choices among WIC participants and non-participants,
except for the 7 to 11 months age category (Table 12-
13). Nonparticipants, ages 7 to 11 months, were more
likely to eat non-infant cereals than WIC participants.
An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
were not provided. Other limitations are those
associated with the FITS data, as described previously
in Section 12.3.2.3.
12.3.2.5 Mennella et al., 2006 - Feeding Infants
and Toddlers Study: The Types of Foods
Fed to Hispanic Infants and Toddlers
Menella et al. (2006) investigated the types
of food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic infants
and toddlers in the United States. The FITS 2002 data
for children between 4 and 24 months of age were used
for the study. The data represent a random sample of
371 Hispanic and 2,367 non-Hispanic infants and
toddlers (Menella et al., 2006). Menella et al. (2006)
grouped the infants as follows: 4 to 5 months (N = 84
Hispanic; 538 non-Hispanic), 6 to 11 months (N = 163
Hispanic and 1,228 non-Hispanic), and 12 to 24 months
(N = 124 Hispanic and 871 non-Hispanic) of age.
Table 12-14 provides the percentage of
Hispanic and non-Hispanic infants and toddlers
consuming grain products. In most instances the
percentages consuming the different types are similar.
However, 6 to 11 month old Hispanic children were
more likely to eat rice and pasta than non-Hispanic
children in this age groups.
The advantage of the study is that it
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
provides information on food preferences for Hispanic
and non-Hispanic infants and toddlers. A limitation is
that the study did not provide food intake data, but
provided frequency of use data instead. Other
limitations are those noted previously in Section
12.3.2.3 for the FITS data.
12.3.2.6 Fox et al, 2006 - Average Portion of
Foods Commonly Eaten by Infants and
Toddlers in the United States
Fox et al. (2006) estimated average portion
sizes consumed per eating occasion by children 4 to 24
months of age who participated in the FITS. The FITS
is a cross-sectional study designed to collect and
analyze data on feeding practices, food consumption,
and usual nutrient intake of U.S. infants and toddlers
and is described in Section 12.3.2.3 of this chapter. It
included a stratified random sample of 3,022 children
between 4 and 24 months of age.
Using the 24-hour recall data, Fox et al.
(2006) derived average portion sizes for six major food
groups, including breads and grains. Average portion
sizes for select individual foods within these major
groups were also estimated. For this analysis, children
were grouped into six age categories: 4 to 5 months, 6
to 8 months, 9 to 11 months, 12 to 14 months, 15 to 18
months, and 19 to 24 months. Tables 12-15 and 12-16
present the average portion sizes for grain products for
infants and toddlers, respectively.
12.4 CONVERSION BETWEEN WET AND
DRY WEIGHT INTAKE RATES
The intake data presented in this chapter
are reported in units of wet weight (i.e., as-consumed or
uncooked weight of grain products consumed per day
or per eating occasion). However, data on the
concentration of contaminants in grain products may be
reported in units of either wet or dry weight.(e.g., mg
contaminant per gram dry-weight of grain products.)
It is essential that exposure assessors be aware of this
difference so that they may ensure consistency between
the units used for intake rates and those used for
concentration data (i.e., if the contaminant
concentration is measured in dry weight of grain
products, then the dry weight units should be used for
their intake values).
If necessary, wet weight (e.g., as
consumed) intake rates may be converted to dry weight
intake rates using the moisture content percentages
presented in Table 12-17 and the following equation:
IRdw ~ IR ww
where:
100 -W
100
(Eqn. 12-1)
IRw
W
dry weight intake rate;
wet weight intake rate; and
percent water content
Alternatively, dry weight residue levels in grain
products may be converted to wet weight residue levels
foruse with wet weight (e.g., as-consumed) intake rates
as follows:
ww
where:
= C
dw
100-W
100
(Eqn. 12-2)
Cww = wet weight intake rate;
Cdw = dry weight intake rate; and
W = percent water content.
The moisture data presented in Table 12-17 are for
selected grain products taken from USDA (2007).
12.5
REFERENCES FOR CHAPTER 12
Devaney, B.; Kalb, L.; Briefel, R.; Zavitsky-Novak, T.;
Clusen, N.; Ziegler, P. (2004) Feeding infants
and toddlers study: overview of the study
design. J Am Diet Assoc 104(Suppl 1): S8-
S13.
Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004)
Feeding Infants and Toddlers Study: what
foods are infants and toddlers eating. J Am
Diet Assoc 104 (Suppl): S22-S30.
Fox, M.K.; Reidy, K.; Karwe, V.; Ziegler, P. (2006)
Average portions of foods commonly eaten by
infants and toddlers in the United States. J
Am Diet Assoc 106 (Suppl 1): S66-S76.
Goldman, L. (1995) Children - unique and vulnerable.
Environmental risks facing children and
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Chapter 12 - Intake of Grain Products
recommendations for response. Environ
Health Prespect 103(6): 13-17.
Mennella, J.; Ziegler, P.; Brief el, R.; Novak, T. (2006)
Feeding Infants and Toddlers Study: the types
of foods fed to Hispanic infants and toddlers.
J Am Diet Assoc 106 (Suppl 1): S96.
Ponza, M; Devaney, B.; Ziegler, P.; Reidy, K.;
Squatrito, C. (2004) Nutrient intakes and food
choices of infants and toddlers participating in
WIC. J Am Diet Assoc 104 (Suppl): S71-
S79.
Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.;
Cook, A.J.; Goldman, J.D. (2002) Foods
commonly eaten in the United States:
Quantities consumed per eating occasion and
in a day, 1994-1996. U.S. Department of
Agriculture NFS Report No. 96-5, pre-
publication version, 252 pp.
USDA. (1999) Food and nutrient intakes by children
1994-96,1998: Table Set 17. Beltsville,MD:
Food Surveys Research Group, Beltsville
Human Nutrition Research Center,
Agricultural Research Service, U.S.
Department of Agriculture.
USDA. (2007) USDA National Nutrient Database for
Standard Reference, Release 20. Agricultural
Research Service, Nutrient Data Laboratory
Home Page,
http://www.ars.usda.gov/ba/bhnrc/ndl
U.S. EPA. (2005) Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
U.S. Environmental Protection Agency,
Washington, D.C., EPA/630/P-03/003F.
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Table 12-3.
Age Group N
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished
Percent
Consuming
70.5
99.8
100.0
100.0
100.0
Mean
2.5
6.4
6.3
4.3
2.5
Per Capita Intake of Total Grains (g/kg-day as consumed)
SE
0.1
0.1
0.1
0.1
0.05
Percentiles
p,
0.0
1.1
1.8
0.9
0.4
5th
0.0
2.1
2.6
1.7
0.8
10th
0.0
2.8
3.2
2.0
1.1
25th
0.0
4.2
4.3
2.8
1.5
50th
1.6
5.9
5.9
4.0
2.3
75th
3.8
7.9
7.8
5.4
3.1
90th
6.2
10.4
9.9
7.0
4.4
95th
8.6
12.1
11.5
8.2
5.1
99th
12.7
16.8
15.6
11.1
7.9
100th
26.3
31.6
27.0
17.2
12.4
U.S. EPA analysis of 1994-96. 1998 CSFII.
Table 12-4. Consumer Only Intake of Total Grains (g/kg-day as consumed)
Age Group N Mean
Birth to 1 year 1,048
1 to 2 years 2,092
3 to 5 years 4,389
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S
3.6
6.4
6.3
4.3
2.5
SE
0.1
0.1
0.1
0.1
0.05
r'
0.1
1.2
1.8
0.9
0.4
5th 10th
0.3 0.6
2.1 2.8
2.6 3.2
1.7 2.0
0.8 1.1
Percentiles
25th 50th 75th 90th 95th 99th
1.4 2.8 4.8 7.4 9.2 13.4
4.2 5.9 7.9 10.4 12.1 16.8
4.3 5.9 7.8 9.9 11.5 15.6
2.8 4.0 5.4 7.0 8.2 11.1
1.5 2.3 3.1 4.4 5.1 7.9
100th
26.3
31.6
27.0
17.2
12.4
EPA analysis of 1994-96. 1998 CSFII.
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Chapter 12 - Intake of Grain Products
Age Group
Table 12-5.
N
Birth to 1 year 1,486
1 to 2 years
3 to 5 years
6 to 12 years
2,096
4,391
2,089
13 to 19 years 1,222
N
SE
Sample size.
Standard error.
Source: Based on unpublished U. S
Der Capita Intake of Individual Grain Products (g/kg-day as consumed)
Percent
Consuming
74.6
99.8
100.0
100.0
100.0
Cereal
Mean
4.0
8.4
8.7
6.2
4.1
. EPA analysis of 1994-96,
SE
0.14
0.08
0.07
0.06
0.06
1998 CSFII .
Rice
Percent
Mean
Consuming
60.2 0.74
86.4 0.57
87.9 0.50
88.0 0.35
85.8 0.27
SE
0.04
0.03
0.03
0.02
0.02
Table 12-6. Consumer Only Intake of Individual Grain Products (g/kg-day as consumed)
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
N
1,116
2,092
4,389
2,089
1,222
Cereal
Mean
5.4
8.4
8.7
6.2
4.1
Rice
SE N Mean
0.16 900 1.23
0.08 1,819 0.67
0.07 3,869 0.57
0.06 1,847 0.40
0.06 1,038 0.31
SE
0.07
0.04
0.03
0.02
0.03
N = Sample size.
SE = Standard error.
Source: Based on
unpublished U.S.
EPA analysis of 1994-96, 1998 CSFII .
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Table 12-1.
Age Group
Sample
Size
Total
Mean Quantities of Grain Products Consumed Daily by Sex and Age
Yeast,
breads,
and rolls
Total
Cereals and
Ready-to-eat
cereals
Dasta
Rice
Pasta
Per Capita (g/day)
Quick
breads,
pancakes,
French
toast
Cakes,
cookies,
pastries,
pies
Crackers,
popcorn,
pretzels,
corn chips
Mixtures,
mainly
grain
Males and Females
Under lyear
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
56
192
219
206
242
264
284
264
219
2
16
26
21
30
36
41
36
27
2
16
26
21
30
36
41
36
27
1
11
16
13
19
22
24
22
16
2
9
15
12
13
15
17
15
13
1"
9
12
11
12
11
11
11
10
1
9
12
11
16
17
15
16
12
3
16
22
19
23
30
33
29
22
1
7
9
8
11
13
13
12
9
20
87
87
87
98
102
107
102
87
Males
6 to 9 years
6 to 1 1 years
2 to 19 years
787
1,031
737
310
318
406
45
46
54
77
80
82
28
31
29
18
16
27
15
18
17
23
23
26
39
40
49
16
15
19
109
115
175
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
284
280
306
43
43
40
61
62
67
21
20
17
12
14
19
15
15
22
18
19
15
42
42
37
13
14
15
107
101
132
Males and Females
9 years and under
19 years and under
9,309
11,287
250
298
34
40
64
69
20
22
14
17
12
15
16
18
30
36
12
14
96
120
a Estimate is not statistically reliable due to small sample size reporting intake.
Note: Consumption amounts shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
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Age Group
Sample
Size
Table 12-8.
Percentage of Individuals Consuming Grain Products, by Sex and Age (%)
Yeast
Total breads,
and rolls T0tal
Cereals and
Ready-to-
eat
cereals
Pasta
Rice Pasta
Quick
breads,
pancakes,
French
toast
Cakes,
cookies,
pastries,
pies
Crackers,
popcorn,
pretzels,
corn
chips
Mixtures,
mainly
grain
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
70.6
98.2'
99.0'
98.7
99.4'
99.5'
99.9'
99.6'
95.8
10.9
48.4
58.7
53.7
64.1
67.0
69.2
66.8
55.5
62.8
70.6
71.1
70.9
69.7
69.1
70.4
69.7
69.3
9.1
45.3
51.9
48.7
53.3
54.8
54.9
54.3
46.9
3.4
11.3
14.4
12.9
11.1
11.4
11.4
11.3
10.9
2.1
9.4
9.4
9.4
8.6
7.1
6.8
7.5
7.5
4.4
23.0
27.5
25.3
28.8
28.6
25.2
27.5
24.0
16.5
47.0
46.6
46.8
46.1
52.3
52.4
50.3
45.0
10.3
39.0
37.9
38.4
38.5
39.4
32.1
36.7
34.1
15.0
47.8
45.3
46.5
49.0
46.2
47.4
47.5
43.3
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
98.9'
99.0'
98.2'
69.8
69.1
62.7
62.6
64.0
44.6
50.8
52.4
33.2
10.5
9.7
10.0
7.4
8.1
5.9
28.1
27.1
24.4
52.5
52.3
41.3
36.0
33.8
27.2
44.5
45.3
46.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
99.7'
99.3'
97.6'
71.5
71.0
60.9
61.2
59.3
45.9
47.6
45.6
30.3
9.0
9.4
8.6
7.9
7.1
9.3
26.3
27.1
19.8
57.1
55.0
40.6
38.3
37.1
30.9
48.0
45.7
46.1
Males and Females
9 years and under
19 years and under
9,309
11,287
97.2
97.6
61.6
62.4
66.4
57.6
47.9
41.7
10.5
9.9
7.6
7.6
25.3
24.2
48.9
46.1
35.3
32.5
44.4
45.1
' Estimate is not statistically reliable due to small sample size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
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Table 12-9. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (grams)
2 to 5 years
Male and Female
Food category (N
PC
White bread 66.9
Whole grain and wheat bread 24.3
Rolls 40.0
Biscuits 8.3
Tortillas 14.6
Quickbreads and muffins 9.6
Doughnuts and sweet rolls 11.3
Crackers 25.4
Cookies 51.0
Cake 14.6
Pie 2.9
Pancake and waffles 19.1
Cooked cereal 16.8
Oatmeal 10.4
Ready-to-eat cereal 72.9
Corn Flakes 11.2
Toasted Oat Rings 20.6
Rice 29.6
Pasta 49.4
Macaroni and cheese 17.8
Spaghetti with tomato sauce 16.8
Pizza 23.7
Corn chips 19.6
Popcorn 11.6
= 2,109)
Mean
34
37
39
38
32
55
59
17
28
70
76
49
211
221
33
33
30
84
90
159
242
86
29
20
6
to 11 years
Male and Female
(N= 1,432)
SEM
a
1
1
2
2
4
2
1
1
3
8
1
10
9
1
2
1
3
3
8
11
3
2
1
* Indicates a SEM value that is greater than 0 but less than
b Indicates a statistic that is potentially
PC = Percent consuming at least once in
SEM = Standard error of the mean.
unreliable
2 days.
PC
67.1
20.5
53.5
9.7
16.4
9.6
13.4
17.2
46.7
19.7
5.6
21.5
9.0
5.7
67.3
13.1
12.5
24.6
41.4
13.2
11.5
32.8
25.6
12.7
0.5.
Mean
42
44
48
48
47
67
69
26
37
79
116
77
245
256
47
42
45
124
130
217
322
108
33
31
SEM
1
1
1
3
2
5
2
2
2
4
8
3
14
19
1
2
2
6
5
13
18
6
2
2
because of small sample size or large
PC
61.3
14.5
61.9
12.2
22.9
11.0
17.3
10.6
29.0
15.1
6.6
13.5
5.2
2.4
45.6
10.4
7.3
24.2
33.4
7.5
10.1
39.6
26.9
7.8
Male
(N = 696)
Mean
56
60
69
72
76
125
102
39
53
99
188
96
310"
348"
72
62
62
203
203
408
583
205
58
54
12 to 19 years
Female
(N = 702)
SEM
1
2
2
4
5
12
12
5
3
9
15
6
29b
45"
3
4
5
10
9
46
46
13
5
5
PC
57.9
17.6
48.8
10.3
20.1
11.0
13.8
14.2
31.8
15.5
4.8
8.2
6.0
2.3
46.3
8.7
8.1
28.8
37.8
10.7
8.5
30.5
25.1
10.5
Mean
47
53
51
55
56
79
78
26
42
85
138"
74
256"
321"
52
49
42
157
155
260
479
143
44
37
SEM
1
2
1
4
3
10
5
3
2
8
12"
5
31"
40"
2
4
3
10
9
30
51
8
3
4
coefficient of variation.
Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
s
I
I
1
«?
I
S
I
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-10. Characteristics of the FITS Sample Population
Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition
Source: Devaney et al., 2004.
Sample Size
1,549
1,473
862
483
679
374
308
316
367
2,641
14
2,417
225
380
1,389
1,014
577
42
48
48
221
359
723
588
311
272
452
821
2,196
5
3,022
Program for Women, Infants, and Children.
Percentage of Sample
51.3
48.7
28.5
16.0
22.5
12.4
10.2
10.4
12.1
87.4
0.5
80.0
7.4
12.6
46.0
33.6
19.1
1.3
1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9
27.2
72.6
0.2
100.0
Child-Specific Exposure Factors Handbook
September 2008
Page
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-11. Percenta§
e of Infants and Toddlers Consuming Different Types of Grain Products
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food 4 to 6 7 to 8
months months
Any Grain or Grain Product
Infant Cereals
Noninfant Cereals"
Not Pre-sweetened
Pre-sweetenedb
Breads and Rolls0
Crackers, Pretzels, Rice Cakes
Cereal or Granola Bars
Pancakes, Waffles, French Toast
Rice and Pastad
Other
Grains in Mixed Dishes
Sandwiches
Burrito, Taco, Enchilada, Nachos
Macaroni and Cheese
Pizza
Pot Pie/Hot Pocket
Spaghetti, Ravioli, Lasagna
" Includes both ready-to-eat and cooked
b Defined as cereals with more than 2 1 .
0 Does not include bread in sandwiches
65.8
64.8
0.6
0.5
0.0
0.6
3.0
0.0
0.1
2.3
0.2
0.4
0.0
0.0
0.2
0.1
0.0
0.1
cereals.
1 g sugar per 100
91.5
81.2
18.3
17.0
1.8
9.9
16.2
1.1
0.8
4.5
0.1
5.3
1.1
0.0
1.6
0.7
0.9
1.8
g.
9 to 11
months
97.5
63.8
44.3
37.0
9.0
24.5
33.4
3.4
7.5
18.2
2.7
24.1
8.6
1.0
4.9
2.2
0.5
9.9
12 to 14
months
97.8
23.9
58.9
44.5
17.7
47.3
45.2
9.8
15.1
26.2
2.8
48.3
21.5
4.5
14.6
6.8
2.0
15.3
15 to 18
months
98.6
9.2
60.5
40.6
26.4
52.7
46.4
10.0
16.1
39.0
2.5
52.0
25.8
2.8
15.0
9.0
1.0
12.1
19 to 24
months
99.2
3.1
51.9
31.9
22.7
53.1
44.7
9.7
15.4
35.9
4.5
55.1
25.8
2.1
15.0
9.4
1.8
8.8
Sandwiches are included in mixed dishes.
d Does not include rice or pasta in mixed dishes.
Source: Fox et al., 2004.
Page
12-18
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-12. Characteristics of WIC Participants and Nonparticipants" (Percentages)
Infants 4 to 6 months
Infants 7 to 11 months
Toddlers 12 to 24 months
WIC
Participant
Non-participant
WIC
Participant
Non-participant
WIC
Participant
Non-participant
Gender
Male 55
Female 45
Child's Ethnicity
Hispanic or Latino 20
Non-Hispanic or Latino 80
Child's Race
White 69
Black 15
Other 22
Child In Day Care
Yes 39
No 61
Age of Mother
14 to 19 18
20 to 24 33
25 to 29 29
30 to 34 9
3 5 or Older 9
Missing 2
Mother's Education
11 ""Grade or Less 23
Completed High School 35
Some Postsecondary 33
Completed College 7
Missing 2
Parent's Marital Status
Married 49
Not Married 50
Missing 1
Mother or Female Guardian Works
Yes
No
Missing
Urbanicity
Urban
Suburban
Rural
Missing
Sample Size
(Unweighted)
46
53
1
34
36
28
2
265
54
46
**
11
84
4
11
38
62
**
1
13
29
33
23
2
**
2
19
26
53
1
**
93
7
1
51
48
1
55
31
13
1
597
55
45
24
76
63
17
20
34
66
13
38
23
15
11
1
15
42
32
9
2
57
42
1
45
54
1
37
31
30
2
351
51
49
92
**
86
5
9
**
46
54
**
1
11
30
36
21
1
**
2
20
27
51
0
**
93
7
0
**
60
40
0
50
34
15
1
57
43
22
78
67
13
20
43
57
9
33
29
18
11
0
17
42
31
9
1
58
41
1
55
45
0
35
35
28
2
205
52
48
**
10
84
5
11
*
53
47
**
1
14
26
34
26
1
**
3
19
28
48
2
11
1
*
61
38
1
48
35
16
2
791
WIC
X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants
for each of the three age groups. *P<0.05; **P>0.01; non-participants significantly different from WIC participants on the
variable.
=Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-13. Food Choices for Infants and Toddlers by WIC Participation Status.
Infant Cereals
Noninfant Cereals, Total
Not Pre-sweetened
Pre-sweetened
Grains in Combination Foods
Sample Size (unweighted)
Infants 4 to 6 months
WIC Non-
Participant participant
69.7 62.5
0.9 0.5
0.5 0.5
0.0 0.0
0.9 0.1
265 597
Infants 7 to
WIC
Participant
74.7
21.7
18.7
4.0
18.8
351
1 1 months
Non-
participant
69.7
38.5*
32.9*
6.9
14.7
808
Toddlers
WIC
Participant
13.5
58.1
43.7
17.7
50.3
205
12 to 24 months
Non-
participant
9.2
56.0
36.3
24.1
52.9
791
* = P<0.01 non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.
Page
12-20
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-14. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
Types of Grain Products on A Given Day
Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic
(n=84)
Non-Hispanic
(n=538)
Hispanic
(n=163)
Non-Hispanic
(n=l,228)
Hispanic
(n=124)
Non-Hispanic
(n=871)
Any Grain or Grain Product
Infant Cereal
Noninfant Cereal
Breads'
Tortillas
Crackers, Pretzels, Rice Cakes
Pancakes, Waffles, French Toast
Rice and Pastab
Rice
Grains in Mixed Dishes
Sandwiches
Burrito, Taco, Enchilada, Nachos
Macaroni and Cheese
Pizza
Spaghetti, Ravioli, Lasagna
56.5
55.2
1.4T
1.4T
1.3T
56.9
56.5
95.0
74.1
18.5*
18.2
4.0t
27.8
1.4T
20.1*
15.9**
15.9
4.0t
1.3T
3.0t
8.3t
93.5
73.6
29.2
15.1
22.5
4.3
10.3
4.7
13.0
4.6
3.1
1.4
4.6
97.1
15.9
45.3
44.0
6.7t*
35.6
13.0
44.3
26.9t*
38.8*
24.2
2.1T
10.1
i.o**t
9.3t
98.9
9.3
57.8
52.9
0.6t
46.9
16.0
32.9
13.0
54.4
24.9
3.0
15.5
9.7
12.1
* Does not include bread in sandwiches. Sandwiches are included in mixed dishes. Includes tortillas, also shown separately.
b Does not include rice or pasta in mixed dishes. Includes rice (e.g. white, brown, wild, and Spanish rice without meat) and pasta
(e.g. spaghetti, macaroni, and egg noodles). Rice is also shown separately.
= Less than 1 percent of the group consumed this food on a given day.
* = Significantly different from non-Hispanic at the P<0.05.
** = Significantly different from non-Hispanic at the P>0.01.
•f = Statistic is potentially unreliable because of a high coefficient of variation.
Source: Mennella et al., 2006.
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-15. Average
Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
Infants from the 2002
Food group
Infant cereal, dry
Infant cereal, jarred
Ready-to-eat
Crackers
Bread
=
N
SEM
cereal
Cell size was too small to §
Number of respondents.
Standard error of the mean
Reference
unit
tablespoon
tablespoon
tablespoon
ounce
saltine
slice
Feeding Infants and Toddlers
4 to 5 months
(N=624)
3.1+0.14
-
-
-
-
-
Study
6 to 8 months
(N=708)
Mean± SEM
4.5+0.14
5.6+0.26
2.3+0.34
0.2+0.02
2.2+0.14
0.5+0.10
by
9 to 11 months
(N=687)
5.2+0.18
7.4+0.34
3.4+0.21
0.3+0.01
2.7+0.12
0.8+0.06
enerate a reliable estimate.
Source: Fox et al., 2006.
Table 12-16
Food Group
Bread
Rolls
Ready-to-eat cereal
Hot cereal, prepared
Crackers
Pasta
Rice
Pancakes and waffles
Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study
Reference Unit
slice
ounce
cup
cup
ounce
saltine
cup
cup
1 (4-inch diameter)
12 to 14 months
(N=371)
0.8±0.04
0.9±0.11
0.3+0.02
0.6±0.05
0.3+0.02
3.3+0.22
0.4+0.04
0.3+0.04
1.0+0.08
15 to 18 months
(N=312)
Mean± SEM
0.9+0.05
1.0+0.10
0.5+0.03
0.6+0.05
0.4+0.02
3.5+0.22
0.4+0.04
0.4+0.05
1.4+0.21
19 to 24 months
(N=320)
0.9+0.05
0.9+0.15
0.6+0.04
0.7+0.05
0.4+0.02
3.7+0.22
0.5+0.05
0.4+0.05
1.4+0.17
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.
Page
12-22
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12-17.
Food
Barley - pearled
Corn - grain - endosperm
Corn - grain - bran
Millet
Oats
Rice - white - long-grained
Rye
Rye - flour - medium
Sorghum
Wheat - hard white
Wheat - germ
Wheat - bran
Wheat - flour - whole grain
Mean Moisture Content of Selected Grain Products Expressed as
Percentages of Edible Portions
Moisture Content
Raw Cooked
10.09 68.80
10.37
4.71
8.67 71.41
8.22
11.62 68.44
10.95
9.85
9.20
9.57
11.12
9.89
10.27
Comments
crude
crude
crude
Source: USDA, 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
12-23
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
APPENDIX 12A
CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS GRAIN
PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
Child-Specific Exposure Factors Handbook Page
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Table 12A-1. Food
Total Grains
Cereal Grains
95000060
15000250
15000251
15000260
15000261
15000270
15000650
15000660
15001200
15001201
15001210
15001211
15001220
15001230
15001231
15001260
15001270
15001271
15002260
15002310
15002320
15002321
15002330
15000250
15000251
15000260
15000261
15000270
15000650
15000660
15001200
15001201
15001210
15001211
15001220
15001230
15001231
15001240
15001241
15001260
15001270
15001271
15002260
15002310
15002320
15002321
15002330
15002331
Codes and Definitions Used in Analysis
Amaranth, grain
Barley, pearled barley
Barley, pearled barley-babyfood
Barley, flour
Barley, flour-babyfood
Barley, bran
Buckwheat
Buckwheat, flour
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, bran
Corn, field, starch
Corn, field, starch-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood
Millet, grain
Oat, bran
Oat, flour
Oat, flour-babyfood
Oat, groats/rolled oats
Barley, pearled barley
Barley, pearled barley-babyfood
Barley, flour
Barley, flour-babyfood
Barley, bran
Buckwheat
Buckwheat, flour
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, bran
Corn, field, starch
Corn, field, starch-babyfood
Corn, field, syrup
Corn, field, syrup-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood
Millet, grain
Oat, bran
Oat, flour
Oat, flour-babyfood
Oat, groats/rolled oats
Oat, groats/rolled oats-babyfood
ofthe 1994-96,
15002331
95003060
95003110
15003230
15003231
15003240
15003241
15003250
15003251
15003260
15003261
15003280
15003290
15003440
15003810
15003811
15004010
15004011
15004020
15004021
15004030
15004040
15004050
15003230
15003231
15003240
15003241
15003250
15003251
15003260
15003261
15003280
15003290
15003440
15003450
15003810
15003811
15004010
15004011
15004020
15004021
15004030
15004040
15004050
95000060
95003060
95003110
1998 USDA CSFII Data
Oat, groats/rolled oats-babyfood
Psyllium, seed
Quinoa, grain
Rice, white
Rice, white-babyfood
Rice, brown
Rice, brown-babyfood
Rice, flour
Rice, flour-babyfood
Rice, bran
Rice, bran-babyfood
Rye, grain
Rye, flour
Sorghum, grain
Triticale, flour
Triticale, flour-babyfood
Wheat, grain
Wheat, grain-babyfood
Wheat, flour
Wheat, flour-babyfood
Wheat, germ
Wheat, bran
Wild rice
Rice, white
Rice, white-babyfood
Rice, brown
Rice, brown-babyfood
Rice, flour
Rice, flour-babyfood
Rice, bran
Rice, bran-babyfood
Rye, grain
Rye, flour
Sorghum, grain
Sorghum, syrup
Triticale, flour
Triticale, flour-babyfood
Wheat, grain
Wheat, grain-babyfood
Wheat, flour
Wheat, flour-babyfood
Wheat, germ
Wheat, bran
Wild rice
Amaranth, grain
Psyllium, seed
Quinoa, grain
Page
12A-2
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Child-Specific Exposure Factors Handbook
Chapter 12 - Intake of Grain Products
Rice
15003260
15003261
15003240
15003241
Rice, bran
Rice, bran-babyfood
Rice, brown
Rice, brown-babyfood
15003250
15003251
15003230
15003231
Rice, flour
Rice, flour-babyfood
Rice, white
Rice, white-babyfood
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
TABLE OF CONTENTS
13 INTAKE OF HOME-PRODUCED FOODS 13-1
13.1 INTRODUCTION 13-1
13.2 RECOMMENDATIONS 13-1
13.3 KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS 13-6
13.3.1 U.S. EPA Analysis of NFCS 1987-1988 13-6
13.4 REFERENCES FOR CHAPTER 13 13-8
APPENDIX 13A FOOD CODES AND DEFINITIONS USED IN CHILD-SPECIFIC ANALYSIS
OF THE 1987-1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE
RATES 13A-1
APPENDIX 13B 1987-1988 NFCS FOOD CODES AND DEFINITIONS USED IN ESTIMATING
FRACTION OF HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED 13B-1
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
LIST OF TABLES
Table 13-1. Summary of Recommended Values for Intake of Home-produced Foods (Consumers Only). . 13-3
Table 13-2. Confidence in Recommendations for Intake of Home-produced Foods 13-4
Table 13-3. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in
Child-specific Analysis of Food Intake 13-10
Table 13-4. Consumer Only Intake of Home-produced Foods (g/kg-day) 13-11
Table 13-5. Percent Weight Losses from Food Preparation 13-12
Table 13-6. Fraction of Food Intake that is Home-produced 13-13
Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDA
NFCS Data to Estimate Intake of Home-produced Foods 13 A-2
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household
Data to Estimate Fraction of Food Intake that is Home-produced 13B-2
Page Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
13
13.1
INTAKE OF HOME-PRODUCED
FOODS
INTRODUCTION
Ingestion of home-produced foods can be a
pathway for exposure to environmental contaminants.
Home-produced foods can become contaminated in a
variety of ways. Ambient pollutants in the air may be
deposited on plants, adsorbed onto or absorbed by the
plants, or dissolved in rainfall or irrigation waters that
contact the plants. Pollutants may also be adsorbed
onto plant roots from contaminated soil and water.
Finally, the addition of pesticides, soil additives, and
fertilizers to crops or gardens may result in
contamination of food products. Meat and dairy
products can become contaminated if animals consume
contaminated soil, water, or feed crops. Farmers, as
well as rural and urban residents who consume home-
produced foods, may be potentially exposed if these
foods become contaminated. Exposure via the
consumption of home-produced foods may be a
significant route of expo sure for these populations (U.S.
EPA, 1989; U.S. EPA, 1996). For example,
consumption of home-produced fruits, vegetables,
game, and fish has been shown to have an impact on
blood lead levels in areas where soil lead contamination
exists (U.S. EPA, 1994). At Superfund sites where soil
contamination is found, ingestion of home-produced
foods has been considered a potential route of exposure
(U.S. EPA, 1991; U.S. EPA, 1993). Assessing
exposures to individuals who consume home-produced
foods requires knowledge of intake rates of such foods.
Data from the 1987-1988 Nationwide Food
Consumption Survey (NFCS) were used to generate
intake rates for home-produced foods (U.S. EPA,
1997). Until 1988, USDA conducted the NFCS every
10 years to analyze the food consumption behavior and
dietary status of Americans (USDA, 1992). While more
recent food consumption surveys have been conducted
to estimate food intake among the general population
(e.g., USDA's Continuing Survey of Food Intake
among Individuals [CSFII] and the National Health and
Nutrition Examination Survey [NHANES]), these
surveys have not collected data that can be used to
estimate consumption of home-produced foods. Thus,
the 1987-1988 NFCS data set is currently the best
available source of information for this factor.
The 1987-1988 NFCS was conducted between
April 1987 and August 1988. The survey used a
statistical sampling technique designed to ensure that
all seasons, geographic regions of the 48 conterminous
states in the U.S., and socioeconomic and demographic
groups were represented (USDA, 1994). There were
two components of the NFCS. The household
component collected information over a seven-day
period on the socioeconomic and demographic
characteristics of households, and the types, amount,
value, and sources of foods consumed by the household
(USDA, 1994). The individual intake component
collected information on food intakes of individuals
within each household over a three-day period (USDA,
1993). The sample size for the 1987-1988 survey was
approximately 4,300 households (over 10,000
individuals; approximately 3,000 children). This was
a decrease over the previous survey conducted in 1977-
1978, which samp led approximately 15,000 households
(over 36,000 individuals) (USDA, 1994). The sample
size was lower in the 1987-1988 survey as a result of
budgetary constraints and low response rate (38 percent
for the household survey and Slpercent for the
individual survey) (USDA, 1993). The methods used
to analyze the 1987-1988 NFCS data and the results of
these analyses that pertain to children are presented in
Section 13.3.
13.2 RECOMMENDATIONS
The data presented in this section may be used
to assess exposure to contaminants in foods grown,
raised, or caught at a specific site. The recommended
values for mean and upper percentile (i.e., 95th
percentile) intake rates among consumers of the various
home-produced food groups are presented in Table 13-
1; these rates can be converted to per capita rates by
multiplying by the fraction of the population consuming
these food groups during the survey period (See Section
13.3). Table 13-2 presents the confidence ratings for
home-produced food intake. The data presented in this
chapter for consumers of home-produced foods
represent average daily intake rates of food
items/groups over the seven-day survey period and do
not account for variations in eating habits during the
rest of the year; thus the recommended upper percentile
values, as well as the percentiles of the distributions
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
presented in Section 13.3 may not necessarily reflect
the long-term distribution of average daily intake of
home produced foods.
Because the home-produced food intake rates
presented in this chapter are based on foods as brought
into the household and not in the form in which they are
consumed, preparation loss factors should be applied,
as appropriate. These factors are necessary to convert
to intake rates to those that are representative of foods
"as consumed". Additional conversions may be
necessary to ensure that the form of the food used to
estimate intake (e.g., wet or dry weight) is consistent
with the form used to measure contaminant
concentration (see Section 13.3).
The NFCS data used to generate intake rates
of home-produced foods are over 20 years old and may
not be reflective of current eating patterns among
consumers of home-produced foods. Although USDA
and others have conducted other food consumption
studies since the release of the 1987-1988 NFCS, these
studies do not include information on home-produced
foods.
Recommended home-produced food intake
rates are not provided for children under 1 year of age
because the methodology used is based on
apportionment of home-produced foods used by a
household among the members of that household that
consume those foods. It was assumed that the diets of
children under 1 year of age differ markedly from that
of other household members; thus, they were not
assumed to consume any portion of the home-produced
food brought into the home. Also, recommended
home-produced food intake rates are not provided for
individual food items for children because, in general,
the sample size was too small to provide reliable data
for individual age groups. However, if intake rates are
needed for age groups under 1 year of age or for food
items other than the major food groups presented here,
data in Section 13.3 on the fraction of household intake
that is home-produced may be used in conjunction with
age-specific intake rates presented elsewhere in this
handbook to estimate intake of home produced foods
(U.S. EPA, 1997).
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Chapter 13 - Intake of Home-Produced Foods
Table 13-1. Summary
Age Group3
of Recommended Values for Intake of Home-produced Foods
Mean 95th Percentile ,,,... ,
Multiple
/, , Percentiles
g/kg-day
(Consumers Only)
Source
Home-produced Fruits
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
8.7 60.6
*'\ f'90 See Table 13-4
3.O 15.5
1.9 8.3
U.S. EPA Analysis of
1987-1988 NFCS
Home-produced Vegetables
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
5.2 19.6
25 77
'n '•' See Table 13-4
2.0 O.2
1.5 6.0
U.S. EPA Analysis of
1987-1988 NFCS
Home-produced Meats
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
3.7 10.0
I* ^ See Table 13-4
1.7 4.3
U.S. EPA Analysis of
1987-1988 NFCS
Home Caught Fish
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
b
2.8 7.1 See Table 13-4
1.5 4.7
U.S. EPA Analysis of
1987- 1988 NFCS
a Analysis was conducted prior to Agency ' s issuance of Guidance on Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005).
b
Data not presented for age groups/food groups where less than 20 observations were available.
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Chapter 13 - Intake of Home-Produced Foods
Table 13-2. Confidence in Recommendations for Intake of Home-produced Foods
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodology and the
approach to data analysis were adequate,
but individual intakes were inferred from
household consumption data. The
sample size was large (approximately
3,000 children).
Non-response bias can not be ruled out
due to low response rate. Also, some
biases may have occurred from using
household data to estimate individual
intake.
Medium (Means)
Low (Distributions)
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
The analysis specifically addressed
home-produced intake.
Data from a nationwide survey,
representative of the general U.S.
population was used.
The data were collected in 1987-1988.
Household data were collected over 1
week.
Low (Means & Short-term distributions)
Low (Long-term distributions)
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
The methods used described to analyze
the data are described in detail in this
handbook; the primary data are
accessible through USDA.
Sufficient detail on the methods used to
analyze the data are presented to allow
for the results to be reproduced.
Quality assurance of NFCS data was
good; quality control of the secondary
data was sufficient.
High
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Chapter 13 - Intake of Home-Produced Foods
Table 13-2. Confidence
General Assessment Factors
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
in Recommendations for Intake of Home-produced Food (continued)
Rationale
Full distributions of home-produced
intake rates were provided.
Sources of uncertainty include:
individuals' estimates of food
weights, allocation of household food
to family members, and potential
changes in eating patterns since these
data were collected,
The study was reviewed by USDA
and U.S. EPA.
The number of studies is 1 .
Rating
Low to Medium
Medium
Low-Medium (means and short-term
distributions)
Low (long-term distributions)
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Chapter 13 - Intake of Home-Produced Foods
13.3 KEY STUDY FOR INTAKE OF HOME-
PRODUCED FOODS
13.3.1 U.S. EPA Analysis of NFCS 1987-1988
U.S. EPA'sNational Center for Environmental
Assessment (NCEA) analyzed USDA's 1987-1988
NFCS data to generate intake rates for home-produced
foods (U.S. EPA, 1997). Forthe purposes of this study,
home-produced foods were defined as homegrown
fruits and vegetables, meat and dairy products derived
from consumer-raised livestock or game meat, and
home caught fish. The food groups selected for
analysis of children's home-produced food intake
included major food groups such as total fruits, total
vegetables, total meats, total dairy, total fish and
shellfish. These food groups were identified in the
NFCS data base according to NFCS-defmed food
codes. Appendix 13A presents the codes and
definitions used to determine these major food groups.
Foods with these codes, for which the source was
identified as home-produced, were included in the
analysis. This chapter presents the intake rate data for
these major food groups, except total dairy, for various
age ranges of children. An insufficient number of
observations (i.e., less than 30 households) were
available to allow for estimates of home-produced dairy
products. Also, child-specific intake rates for
individual food items (e.g., carrots, citrus fruit) were
not estimated because, in general, the sample size was
too small to provide reliable data for the individual age
groups of interest.
The USD A data were adjusted by applying the
sample weights calculated by USDA to the data set
prior to analysis. The USDA sample weights were
designed to "adjust for survey non-response and other
vagaries of the sample selection process" (USDA,
1987-1988). Also, the USDA weights are calculated
"so that the weighted sample total equals the known
population total, in thousands, for several
characteristics thought to be correlated with eating
behavior" (USDA, 1987-1988). The unweighted
sample included approximately 3,000 children (ages <1
to 19 years), which was weighted to reflect nearly 54
million children.
Although the individual intake component of
the NFCS gives the best measure of the amount of each
food group eaten by each individual in the household,
it could not be used directly to measure consumption of
home-producedfoodbecause the individual component
does not identify the source of the food item (i.e., as
home-produced or not). Therefore, an analytical
method which incorporated data from both the
household and individual survey components was
developed to estimate individual home-produced food
intake. The USDA household data were used to
determine (1) the amount of each home-produced food
item used during a week by household members and (2)
the number of meals eaten in the household by each
household member during a week. As measured by the
NFCS, the amount of food "consumed" by the
household is a measure of consumption in an economic
sense, i.e., a measure of the weight of food brought into
the household that has been consumed (used up) in
some manner. In addition to food being consumed by
persons, food may be used up by spoiling, by being
discarded (e.g., inedible parts), through cooking
processes, etc. Note that the household survey reports
the total amount of each food item used in the
household (whether by guests or household members);
the amount used by household members was derived by
multiplying the total amount used in the household by
the proportion of all meals served in the household
(during the survey week) that were consumed by
household members.
The individual survey data were used to
generate average sex- and age-specific serving sizes for
each food item. These serving sizes were used during
subsequent analyses to generate home-produced food
intake rates for individual household members.
Assuming that the proportion of the household quantity
of each home-produced food item/group was a function
of the number of meals and the mean sex- and age-
specific serving size for each family member,
individual intakes of home-produced food were
calculated for all members of the survey population
using the following general equation:
(Eqn. 13-1)
where:
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Chapter 13 - Intake of Home-Produced Foods
W; = Home-produced amount of food
item/group attributed to member i
during the week (g/week);
wf = Total quantity of home-produced
food item/group used by the family
members (g/week);
nij = Number of meals of household food
consumed by member i during the
week (meals/week); and
q; = Serving size for an individual within
the age and sex category of the
member (g/meal).
number of individuals surveyed, then NT - Nc is the
weighted number of individuals who reported zero
consumption of the food item. In addition, there are
(p/100 x Nc) individuals below the p* percentile.
Therefore, the percentile that corresponds to a particular
intake rate (IRp) for the overall distribution of home-
produced food consumption (including consumers and
non-consumers) can be obtained by:
100
xNc +|NT-NC
(Eqn. 13-2)
Daily intake of a home-produced food group
was determined by dividing the weekly value (w;) by
seven. Intake rates were indexed to the self-reported
body weight of the survey respondent and reported in
units of g/kg-day. For the major food groups (fruits,
vegetables, meats, and fish), distributions of home-
produced intake among consumers were generated by
age group. Consumers were defined as members of
survey households who reported consumption of the
food group of interest during the one week survey
period.
The age categories used in the analysis were as
follows: 1 to 2 years; 3 to 5 years; 6 to 1 1 years; and 12
to 19 years Because this analysis was conducted prior
to issuance of U.S. EPA's Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005), the age groups used are not entirely consistent
with recent guidelines. Intake rates were not calculated
for children under 1 year because their diet differs
markedly from that of other household members, and
thus, the assumption that all household members share
all foods would be invalid for this age group.
The intake data presented here for consumers
of home-produced foods and the total number of
individuals surveyed may be used to calculate the mean
and the percentiles of the distribution of home-
produced food consumption in the overall population
(consumers and non-consumers) as follows:
Assuming that IRp is the home-produced
intake rate of the food group at the p* percentile and Nc
is the weighted number of individuals consuming the
home-produced food item, and NT is the weighted total
Table 13-3 displays the weighted numbers NT,
as well as the unweighted total survey sample sizes, for
each age category. Table 13-4 presents home-
produced intake rates for fruits, vegetables, meats, and
fish. These intake rates are based on the amount of
household food consumption as well as age-specific
serving size data.
USDA estimated preparation losses forvarious
foods (USDA, 1975). For meats, a net cooking loss,
which includes dripping and volatile losses, and a net
post-cooking loss, which involves losses from cutting,
bones, excess fat, scraps and juices, were derived for a
variety of cuts and cooking methods. For total meats,
U.S. EPA has averaged these losses across all meat
types, cuts and cooking methods to obtain a mean net
cooking loss and a mean net post-cooking loss. Mean
percentage values for all meats and fish are provided in
Table 13-5. For individual fruits and vegetables,
USDA (1975) also gave cooking and post-cooking
losses. These data, averaged across all types of fruits
and vegetables to give mean net cooking and post
cooking losses, are also provided in Table 13-5.
The following formula can be used to convert
the home-produced intake rates tabulated here to rates
reflecting actual consumption:
= Ix jl-L
II- L2 i
(Eqn. 13-3)
where:
IA = the adjusted intake rate;
I = the tabulated intake rate;
L! = the cooking or preparation loss; and
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Chapter 13 - Intake of Home-Produced Foods
L2 = the post-cooking loss.
For fruits, corrections based on post-cooking
losses only apply to fruits that are eaten in cooked
forms. For raw forms of the fruits, paring or
preparation loss data should be used to correct for
losses from removal of skin, peel, core, caps, pits,
stems, and defects, or draining of liquids from canned
or frozen forms.
In calculating ingestion exposure, assessors
should use consistent forms (e.g./'as-consumed" or dry
weight) in combining intake rates with contaminant
concentrations, as discussed in Chapter 9 of this
handbook.
The USDA 1987-1988 NFCS household data
were also used to estimate the fraction of household
intake that can be attributed to home-produced foods
(Table 13-6). The analysis was conducted forthe major
food groups (i.e., total meat, dairy, fruits, vegetables,
and fish), as well as for a variety of individual food
items (e.g., apples, tomatoes, beef, etc.). The fraction
of intake that was home-produced was calculated as the
ratio of total intake of the home-produced food
item/group by the survey population to the total intake
of all forms of the food by the survey population. The
food codes used in this analysis are presented in
Appendix 13-B.
The USDA NFCS data set is the largest
publicly available source of information on home-
produced food consumption habits in the United States.
The advantages of using this data set are that it is
expected to be representative of the U.S. population and
that it provides information on a wide variety of food
groups. However, the data collected by the USDA
NFCS are based on short-term dietary recall and the
intake distributions generated from this data set may not
accurately reflect long-term intake patterns, particularly
with respect to the tails (extremes) of the distributions.
Also, the two survey components (i.e., household and
individual) do not define food items/groups in a
consistent manner; as a result, some errors may be
introduced into these analyses because the two survey
components are linked. The results presented here may
also be biased by assumptions that are inherent in the
analytical method utilized. The analytical method may
not capture all high-end consumers within households
because average serving sizes are used in calculating
the proportion of home-produced food consumed by
each household member. Thus, for instance, in a two-
person household where one member had high intake
and one had low intake, the method used here would
assume that both members had an equal and moderate
level of intake. In addition, the analyses assume that all
family members consume a portion of the home-
produced food used within the household. However,
not all family members may consume each home-
produced food item and serving sizes allocated here
may not be entirely representative of the portion of
household foods consumed by each family member. As
was mentioned earlier, no analyses were performed for
children under 1 year age.
The preparation loss factors discussed above
are intended to convert intake rates based on
"household consumption" to rates reflective of what
individuals actually consume. However, these factors
do not include losses to spoilage, feeding to pets, food
thrown away, etc. It should also be noted that because
this analysis is based on the 1987-1988 NFCS, it may
not reflect recent changes in food consumption patterns.
The low response rate associated with the 1987-1988
NFCS also contributes to the uncertainty of the home-
produced intake rates generated using these data.
13.4 REFERENCES FOR CHAPTER 13
USDA (1975) Food yields summarized by different
stages of preparation. Agricultural Handbook
No. 102. Washington, DC. U.S. Department
of Agriculture, Agriculture Research Service.
USDA (1987-1988) Dataset: Nationwide Food
Consumption Survey 1987/88 Household
Food Use. Washington, DC. U.S.
Department of Agriculture. 1987/88 NFCS
Database.
USDA (1992) Changes in food consumption and
expenditures in American households during
the 1980's. Washington, DC. U.S.
Department of Agriculture. Statistical
Bulletin No. 849.
USDA (1993) Food and nutrient intakes by individuals
in the United States, 1 Day, 1987-1988.
Nationwide Food Consumption Survey 1987-
1988, NFCS Report No. 87-1-1.
Page
13-8
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
USDA (1 994) Food consumption and dietary levels of
households in the United States, 1987-1988.
U.S. Department of Agriculture, Agricultural
Research Service. Report No. 87-H-l.
U.S. EPA (1989) Risk Assessment Guidance for
Superfund (RAGS): Volume I, Human Health
Evaluation Manual, Part A. Office of Solid
Waste and Emergency Response, Washington,
DC. EPA/540/1-89/002. Available online at
http://www.epa.gov/oswer/riskassessment/ra
gsa/index.htm
U.S. EPA (1991) Record of Decision. ROD ID
EPA/ROD/R10-91-029.
U.S. EPA (1993) Record of Decision. ROD ID
EPA/ROD/R04-93-166.
U.S. EPA (1 994) Validation strategy for the Integrated
Exposure Uptake Biokinetic Model for Lead
in Children. Office of Solid Waste and
Emergency Response, Washington DC.
EPA/540/R-94-039. Available online at
http://www.epa.gov/snperfiind/lead/products
/valstrat.pdf
U.S. EPA (1996) Soil Screening Fact Sheet Guidance.
EPA/540/F-95/041. Available online at
http://www.epa.gov/superfund/health/conme
dj_a/_sgjl/jndexjitiii
U.S. EPA (1997) Exposure Factors Handbook. Office
of Research and Development, Washington,
DC. EPA/600/P-95/002F. Available online at
fm?deid= 12464
Child-Specific Exposure Factors Handbook
September 2008
Page
13-9
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
Age Group
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
Total
weighted -
unweighted -
Table 13-3. Weighted and Unweighted Number of Observations (Individuals)
Child-specific Analysis of Food Intake
Number of Observations
weighted
2,814,000
5,699,000
8,103,000
16,711,000
20,488,000
53,815,000
Weighted number of observations.
Unweighted number of observations.
for NFCS Data Used in
unweighted
156
321
461
937
1,084
2,959
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Chapter 13 - Intake of Home-Produced Foods
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Child-Specific Exposure Factors Handbook
September 2008
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13-11
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Chapter 13 - Intake of Home-Produced Foods
Table 13-5. Percent Weight Losses from Food Preparation
Food Group Mean Net Preparation/Cooking Loss (%) Mean Net Post Cooking (%)
Meats3 29.7" 29.T
Fish and shellfish" 31.5" 10.5°
Fruits 25.4° 30.5f
Vegetables8 12.4" 22'
a Averaged over various cuts and preparation methods for various meats including beef, pork, chicken, turkey,
lamb, and veal.
b Includes dripping and volatile losses during cooking.
0 Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices.
d Averaged over a variety offish and shellfish, to include: bass, bluefish, butterfish, cod, flounder, haddock,
halibut, lake trout, mackerel, perch, porgy, red snapper, rockfish, salmon, sea trout, shad, smelt, sole, spot,
squid, swordfish steak, trout, whitefish, clams, crab, crayfish, lobster, oysters, and shrimp and shrimp
dishes.
° Based on preparation losses. Averaged over apples, pears, peaches, strawberries, and oranges. Includes
losses from removal of skin or peel, core or pit, stems or caps, seeds, and defects. Also, includes losses from
removal of drained liquids from canned or frozen forms.
f Averaged over apples and peaches. Include losses from draining cooked forms.
8 Averaged over various vegetables, to include: asparagus, beets, broccoli, cabbage, carrots, corn, cucumbers,
lettuce, lima beans, okra, onions, green peas, peppers, pumpkins, snap beams, tomatoes, and potatoes.
h Includes losses due to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling, slicing,
husking, chopping, and dicing and gains from the addition of water, fat, or other ingredients. Averaged over
various preparation methods.
1 Includes losses from draining or removal of skin. Based on potatoes only.
Source: U.S. EPA, 1997 (Derived from USDA, 1975).
Page Child-Specific Exposure Factors Handbook
13-12 September 2008
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Chapter 13 - Intake of Home-Produced Foods
Total Fruits
Apples
Peaches
Pears
Strawberries
Other Berries
Citrus
Other
Total Vegetables
Asparagus
Beets
Broccoli
Cabbage
Carrots
Corn
Cucumbers
Lettuce
Lima Beans
Okra
Onions
Peas
Peppers
Pumpkin
Snap Beans
Tomatoes
White Potatoes
Total Meats
Beef
Game
Pork
Poultry
Total Dairy
Eggs
Total fish
= No data.
Table 13-6. Fraction of Food Intake
All Households
0.04
0.030
0.147
0.067
0.111
0.217
0.038
0.042
All Households
0.068
0.063
0.203
0.015
0.038
0.043
0.078
0.148
0.010
0.121
0.270
0.056
0.069
0.107
0.155
0.155
0.184
0.038
All Households
0.024
0.038
0.276
0.013
0.011
All Households
0.012
0.014
All Households
0.094
that is Home-produced
Households who
garden
0.101
0.070
0.316
0.169
0.232
0.306
0.087
0.107
Households who
garden
0.173
0.125
0.420
0.043
0.099
0.103
0.220
0.349
0.031
0.258
0.618
0.148
0.193
0.246
0.230
0.384
0.398
0.090
Households who
raise animals/hunt
0.306
0.485
0.729
0.242
0.156
Households who
raise animals
0.207
0.146
Households who
fish
0.325
Households who farm
0.161
0.292
0.461
0.606
0.057
0.548
0.005
0.227
Households who farm
0.308
0.432
0.316
0.159
0.219
0.185
0.524
0.524
0.063
0.103
0.821
0.361
0.308
0.564
0.824
0.623
0.616
0.134
Households who farm
0.319
0.478
-
0.239
0.151
Households who farm
0.254
0.214
-
-
Source: U.S. EPA Analysis of 1987-1988 NFCS.
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Chapter 13 - Intake of Home-Produced Foods
APPENDIX 13A
FOOD CODES AND DEFINITIONS USED IN CHILD-SPECIFIC ANALYSIS
OF THE 1987-1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE RATES
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Chapter 13 - Intake of Home-Produced Foods
Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDANFCS Data
to Estimate Intake of Home-produced Foods
Food Product
Household Code/Definition1
Individual Code
MAJOR FOOD GROUPS
Total Fruits
50- Fresh Fruits
citrus
other vitamin-C rich
other fruits
512- Commercially Canned Fruits
522- Commercially Frozen Fruits
533- Canned Fruit Juice
534- Frozen Fruit Juice
535- Aseptically Packed Fruit Juice
536- Fresh Fruit Juice
542- Dried Fruits
(includes baby foods)
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
(includes baby foods)
Total Vegetables
48- Potatoes, Sweet potatoes
49- Fresh Vegetables
dark green
deep yellow
tomatoes
light green
other
511- Commercially Canned Vegetables
521- Commercially Frozen Vegetables
531- Canned Vegetable Juice
532- Frozen Vegetable Juice
537- Fresh Vegetable Juice
538- Aseptically Packed Vegetable Juice
541- Dried Vegetables
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures/dinners)
7- Vegetables (all forms)
white potatoes & PR starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
veg. and mixtures/baby food
veg. with meat mixtures
(includes baby foods; mixtures, mostly vegetables)
Total Meats
44- Meat
beef
pork
veal
lamb
mutton
goat
game
lunch meat
mixtures
451- Poultry
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures)
20- Meat, type not specified
21- Beef
22- Pork
23- Lamb, veal, game, carcass meat
24- Poultry
25- Organ meats, sausages, lunchmeats, meat
spreads
(excludes meat, poultry, and fish with non-meat
items; frozen plate meals; soups and gravies with
meat, poultry and fish base; and gelatin-based drinks;
includes baby foods)
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Chapter 13 - Intake of Home-Produced Foods
Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDANFCS Data
to Estimate Intake of Home-produced Foods (continued)
Food Product
Total Dairy
Total Fish
Household Code/Definition1
MAJOR FOOD GROUPS
40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
452- Fish, Shellfish
various species
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
Individual Code
1- Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
(includes regular fluid milk, human milk, imitation
milk products, yogurt, milk-based meal
replacements, and infant formulas)
26- Fish, Shellfish
various species and forms
(excludes meat, poultry, and fish with non-meat
items; frozen plate meals; soups and gravies with
meat, poultry and fish base; and gelatin-based drinks)
1 Food items within these categories that were identified by the household as being home-produced or home-caught (i.e., source code pertaining to home
produced foods) were included in the analysis.
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
APPENDIX 13B
1987-1988 NFCS FOOD CODES AND DEFINITIONS USED IN ESTIMATING FRACTION OF
HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household Data to
Estimate Fraction of Food Intake that is Home-produced
Food Product
Household Code/Definition
INDIVIDUAL FOODS
White Potatoes
4811- White Potatoes, fresh
4821- White Potatoes, commercially canned
4831- White Potatoes, commercially frozen
4841- White Potatoes, dehydrated
4851- White Potatoes, chips, sticks, salad
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
Peppers
4913- Green/Red Peppers, fresh
5111201 Sweet Green Peppers, commercially canned
5111202 HotChili Peppers, commercially canned
5211301 Sweet Green Peppers, commercially frozen
5211302 Green Chili Peppers, commercially frozen
5211303 Red Chili Peppers, commercially frozen
5413112 Sweet Green Peppers, dry
5413113 Red Chili Peppers, dry
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
Onions
4953- Onions, Garlic, fresh
onions
chives
garlic
leeks
5114908 Garlic Pulp, raw
5114915 Onions, commercially canned
5213722 Onions, commercially frozen
5213723 Onions with Sauce, commercially frozen
5413103 Chives, dried
5413105 Garlic Flakes, dried
5413110 Onion Flakes, dried
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
Corn
4956- Corn, fresh
5114601 Yellow Corn, commercially canned
5114602 White Corn, commercially canned
5114603 Yellow Creamed Corn, commercially canned
5114604 White Creamed Corn, commercially canned
5114605 Corn on Cob, commercially canned
5114607 Hominy, canned
5115306 Low Sodium Corn, commercially canned
5115307 Low Sodium Cr. Corn, commercially canned
5213501 Yellow Corn on Cob, commercially frozen
5213502 Yellow Corn off Cob, commercially frozen
5213503 Yell. Corn with Sauce, commercially frozen
5213504 Corn with other Veg., commercially frozen
5213505 White Corn on Cob, commercially frozen
5213506 White Corn off Cob, commercially frozen
5213507 Wh. Corn with Sauce, commercially frozen
5413104 Corn, dried
5413106 Hominy, dry
5413603 Corn, instant baby food
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby food)e
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Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to
Estimate Fraction of Food Intake that is Home-produced (continued)
Food Product
Household Code/Definition
Apples
5031- Apples, fresh
5122101 Applesauce with sugar, commercially canned
5122102 Applesauce without sugar, comm. canned
5122103 Apple Pie Filling, commercially canned
5122104 Apples, Applesauce, baby/jr., comm. canned
5122106 Apple Pie Filling, Low Cal., comm. canned
5223101 Apple Slices, commercially frozen
5332101 Apple Juice, canned
5332102 Apple Juice, baby, Comm. canned
5342201 Apple Juice, comm. frozen
5342202 Apple Juice, home frozen
5352101 Apple Juice, aseptically packed
5362101 Apple Juice, fresh
5423101 Apples, dried
(includes baby food; except mixtures)
Tomatoes
4931- Tomatoes, fresh
5113- Tomatoes, commercially canned
5115201 Tomatoes, low sodium, commercially canned
5115202 Tomato Sauce, low sodium, comm. canned
5115203 Tomato Paste, low sodium, comm. canned
5115204 Tomato Puree, low sodium, comm. canned
5311- Canned Tomato Juice and Tomato Mixtures
5321- Frozen Tomato Juice
5371- Fresh Tomato Juice
5381102 Tomato Juice, aseptically packed
5413115 Tomatoes, dry
5614- Tomato Soup
5624- Condensed Tomato Soup
5654- Dry Tomato Soup
(does not include mixtures, and ready-to-eat dinners)
Snap Beans
4943- Snap or Wax Beans, fresh
5114401 Green or Snap Beans, commercially canned
5114402 Wax orYellow Beans, commercially canned
5114403 Beans, baby/jr., commercially canned
5115302 Green Beans, low sodium, comm. canned
5115303 Yell. orWax Beans, low sod., comm. canned
5213301 Snap or Green Beans, comm. frozen
5213302 Snap or Green w/sauce, comm. frozen
5213303 Snap or Green Beans w/other veg., comm. fr.
5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr.
5213305 Wax or Yell. Beans, comm. frozen
(does not include soups, mixtures, and ready-to-eat dinners; includes baby foods)
Beef
441-Beef
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
Pork
442- Pork
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
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Child-Specific Exposure Factors Handbook
Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to Estimate Fraction
of Food Intake that is Home-produced (continued)
Food Product
Game
Poultry
Eggs
Broccoli
Carrots
Pumpkin
Asparagus
Lima Beans
Household Code/Definition
445- Variety Meat, Game
(does not include soups., sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
451 -Poultry
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
46- Eggs (fresh equivalent)
fresh
processed eggs, substitutes
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4912- Fresh Broccoli (and home canned/froz.)
5111203 Broccoli, comm. canned
521 12- Comm. Frozen Broccoli
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4921- Fresh Carrots (and home canned/froz.)
51121- Comm. Canned Carrots
5115101 Carrots, Low Sodium, Comm. Canned
52121- Comm. Frozen Carrots
5312103 Comm. Canned Carrot Juice
5372102 Carrot Juice Fresh
5413502 Carrots, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4922- Fresh Pumpkin, Winter Squash (and home canned/froz.)
51122- Pumpkin/Squash, Baby or Junior, Comm. Canned
52122- Winter Squash, Comm. Frozen
5413504 Squash, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4941- Fresh Asparagus (and home canned/froz.)
5114101 Comm. Canned Asparagus
5115301 Asparagus, Low Sodium, Comm. Canned
52131- Comm. Frozen Asparagus
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4942- Fresh Lima and Fava Beans (and home canned/froz.)
51 14204 Comm. Canned Mature Lima Beans
51 14301 Comm. Canned Green Lima Beans
51 15304 Comm. Canned Low Sodium Lima Beans
52132- Comm. Frozen Lima Beans
541 1 1- Dried Lima Beans
541 1306 Dried Fava Beans
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures; does not include succotash)
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Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household Data to
Estimate Fraction of Food Intake that is Home-produced (continued)
Food Product
Cabbage
Lettuce
Okra
Peas
Cucumbers
Beets
Strawberries
Household Code/Definition
4944- Fresh Cabbage (and home canned/froz.)
4958601 Sauerkraut, home canned or pkgd
5114801 Sauerkraut, comm. canned
5114904 Comm. Canned Cabbage
5114905 Comm. Canned Cabbage (no sauce; incl. baby)
5115501 Sauerkraut, low sodium., comm. canned
5312102 Sauerkraut Juice, comm. canned
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4945- Fresh Lettuce, French Endive (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4946- Fresh Okra (and home canned/froz.)
5114914 Comm. Canned Okra
5213720 Comm. Frozen Okra
5213721 Comm. Frozen Okra with Oth. Veg. & Sauce
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4947- Fresh Peas (and home canned/froz.)
51147- Comm Canned Peas (incl. baby)
5115310 Low Sodium Green or English Peas (canned)
5115314 Low Sod. B lackey e, Gr. or Imm. Peas (canned)
51 14205 B lackeyed Peas, comm. canned
52134- Comm. Frozen Peas
5412- Dried Peas and Lentils
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4952- Fresh Cucumbers (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4954- Fresh Beets (and home canned/froz.)
51145- Comm. Canned Beets (incl. baby)
5115305 Low Sodium Beets (canned)
5213714 Comm. Frozen Beets
5312104 Beet Juice
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
5022- Fresh Strawberries
5122801 Comm. Canned Strawberries with sugar
5122802 Comm. Canned Strawberries without sugar
5122803 Canned Strawberry Pie Filling
5222- Comm. Frozen Strawberries
(does not include ready-to-eat dinners; includes baby foods except mixtures)
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Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to
Estimate Fraction of Food Intake that is Home-produced (continued)
Food Product
Household Code/Definition
Other Berries
5033- Fresh Berries Other than Strawberries
5122804 Comm. Canned Blackberries with sugar
5122805 Comm. Canned Blackberries without sugar
5122806 Comm. Canned Blueberries with sugar
5122807 Comm. Canned Blueberries without sugar
5122808 Canned Blueberry Pie Filling
5122809 Comm. Canned Gooseberries with sugar
5122810 Comm. Canned Gooseberries without sugar
5122811 Comm. Canned Raspberries with sugar
5122812 Comm. Canned Raspberries without sugar
5122813 Comm. Canned Cranberry Sauce
5122815 Comm. Canned Cranberry-Orange Relish
52233- Comm. Frozen Berries (not strawberries)
5332404 Blackberry Juice (home and comm. canned)
5423 114 Dried Berries (not strawberries)
(does not include ready-to-eat dinners; includes baby foods except mixtures)
Peaches
5036- Fresh Peaches
51224- Comm. Canned Peaches (incl. baby)
5223601 Comm. Frozen Peaches
5332405 Home Canned Peach Juice
5423105 Dried Peaches (baby)
5423106 Dried Peaches
(does not include ready-to-eat dinners; includes baby foods except mixtures)
Pears
5037- Fresh Pears
51225- Comm. Canned Pears (incl. baby)
5332403 Comm. Canned Pear Juice, baby
5362204 Fresh Pear Juice
5423107 Dried Pears
(does not include ready-to-eat dinners; includes baby foods except mixtures)
Citrus Fruits
501- Fresh Citrus Fruits
5121 Comm. Canned Citrus Fruits
5331 Canned Citrus and Citrus Blend Juice
5341 Frozen Citrus and Citrus Blend Juice
5351 Aseptically Packed Citrus and Citr. Blend Juice
5361 Fresh Citrus and Citrus Blend Juice
(includes baby foods; excludes dried fruits)
Other
Fruits
502- Fresh Other Vitamin C-Rich Fruits
503- Fresh Other Fruits
5122- Comm. Canned Fruits Other than Citrus
5222- Frozen Strawberries
5332- Frozen Other than Citr. or Vitamin C-Rich Fr.
5333- Canned Fruit Juice Other than Citrus
5352- Frozen Juices Other than Citrus
5362- Aseptically Packed Fruit Juice Other than Citr.
542- Fresh Fruit Juice Other than Citrus Dry Fruits
(includes baby foods; excludes dried fruits)
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Child-Specific Exposure Factors Handbook
Chapter 14 - Total Food Intake
TABLE OF CONTENTS
14 TOTAL DIETARY INTAKE 14-1
14.1 INTRODUCTION 14-1
14.2 RECOMMENDATIONS 14-1
14.3 KEY STUDY OF TOTAL FOOD INTAKE 14-4
14.3.1 U.S. EPA, 2007 14-4
14.4 REFERENCES FOR CHAPTER 14 14-5
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Chapter 14 - Total Food Intake
LIST OF TABLES
Table 14-1. Recommended Values for Per Capita Total Intake of Foods, As Consumed 14-2
Table 14-2. Confidence in Recommendations for Total Food Intake 14-3
Table 14-3. Per Capita Total Food Intake 14-6
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) . . 14-7
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed)14-ll
Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Food Intake 14-15
Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat Intake 14-19
Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat and Dairy Intake .... 14-23
Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Fish Intake 14-27
Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Fruit and Vegetable Intake . 14-31
Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Dairy Intake 14-35
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Chapter 14 - Total Food Intake
14 TOTAL FOOD INTAKE
14.1 INTRODUCTION
The U.S. food supply is generally considered to
be one of the safest in the world. Nevertheless,
contamination of foods may occur as a result of
environmental pollution of the air, water, or soil, or the
intentional use of chemicals such as pesticides or other
agrochemicals. Ingestion of contaminated foods is a
potential pathway of exposure to such contaminants
among children. To assess chemical exposure through
this pathway, information on food ingestion rates is
needed. Per capita and consumers only data on food
consumption rates for various food items and food
categories are reported in Chapters 9 through 13 of
this handbook. These intake rates were estimated by
U.S. EPA using databases developed by the U.S.
Department of Agriculture (USD A). U.S. EPA (2007)
expanded the analysis of food intake in order to
examine individuals' food consumption habits in
greater detail. Using data from the USDA's
Continuing Survey of Food Intake by Individuals
(CSFII) conducted in 1994-1996, 1998, U.S. EPA
(2007) derived distributions to characterize (1) total
food intake among various groups in the U.S.
population, subdivided by age, race, geographic region,
and urbanization; (2) the contribution of various food
categories (e.g., meats, grains, vegetables, etc.) to total
food intake among these populations; and (3) the
contribution of various food categories to total food
intake among individuals exhibiting low- or high-end
consumption patterns of a specific food category (e.g.,
individuals below the 10th percentile or above the 90th
percentile for fish consumption). These data may be
useful for assessing exposure among populations
exhibiting lower or higher than usual intake of certain
types of foods (e.g., people who eat little or no meat, or
people who eat large quantities offish).
The recommendations for total food intake rates
are provided in the next section, along with a summary
of the confidence ratings for these recommendations.
Following the recommendations, the key study on total
food intake is summarized.
recommended intake rates for children are based on
data from the U. S. EPA (2007) analysis of CSFII data.
However, the analysis presented in U.S. EPA (2007)
was conducted before U.S. EPA published the
guidance entitled Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005). As a result, the age
groups used for children in U.S. EPA (2007) were not
entirely consistent with the age groups recommended
in the 2005 guidance. Therefore, a re-analysis of the
data was conducted to conform with U.S. EPA's
recommended age groups for children.
Because these recommendations are based on
1994-96 and 1998 CSFII data, they may not reflect
recent changes that may have occurred in consumption
patterns. In addition, these distributions are based on
data collected over a 2-day period and may not
necessarily reflect the long-term distribution of average
daily intake rates. However, for the broad categories
of foods used in this analysis (e.g., total foods, total
fruits, total vegetables, etc.), because they are typically
eaten on a daily basis throughout the year with
minimal seasonality, the short- term distribution maybe
a reasonable approximation of the long-term
distribution, although it will display somewhat
increased variability. This implies that the upper
percentiles shown here will tend to overestimate the
corresponding percentiles of the true long-term
distribution.
14.2 RECOMMENDATIONS
A summary of recommended values for total
food intake, on an as-consumed basis, is presented in
Table 14-1. The confidence ratings for these
recommendations are presented in Table 14-2. The
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Chapter 14 - Total Food Intake
Table 14-1.
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Note: Total food intake was
dairy, meats, fish, eg
nuts and nut products
groups. Also, human
Recommended Values for Per Capita Total Food Intake, As Consumed
Mean
20
16
28
56
90
74
61
40
24
18
95<*Percentile ^M^
g/kg-day Percentiles
61
40
65
134
161
See Table 14-3
126
102
70
45
35
defined as intake of the sum of all foods in the following
gs, grains, vegetables, fruits, and fats. Beverages, sugar,
were not included because they could not be categorized
milk intake was not included.
Source
U.S. EPA re-analysis of
CSFII 1994-96, 98 data
(Based on U.S. EPA,
2007)
major food categories:
candy, and sweets, and
into the major food
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Chapter 14 - Total Food Intake
Table 14-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Confidence in Recommendations for Total Food Intake
Rationale
The survey methodology was adequate and the analytical
approach was competently executed. The study size was very
large; sample size varied with age. The response rate was
good. The key study analyzed primary data on recall of
ingestion.
No direct measurements were taken. The study relied on
survey data.
The analysis was specifically designed to address food intake.
The population studied was representative of the U.S.
population.
The data used were the most current data publicly available
at the time the analysis was conducted for the handbook.
Ingestion rates were estimated based on short-term data
collected in the CSFII 1994-96, 1998.
The CSFII data are publicly available. The U.S. EPA (2007)
report is available online.
The methodology was clearly presented; enough information
was included to reproduce results.
Quality assurance methods were not described in the study
report.
Short term distributions were provided. The survey was not
designed to capture long term day-to-day variability.
The survey data were based on recall over a 2-day period.
Other sources of uncertainty were minimal.
The USDA CSFII survey received a high level of peer review.
U.S. EPA (2007) analysis was also peer-reviewed; however,
the re-analysis of these data using the new age categories was
not peer reviewed outside the Agency.
Only one key study was available for this factor
Rating
High
Medium
Medium
Medium
Medium
Medium
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 14 - Total Food Intake
14.3 KEY STUDY OF TOTAL FOOD INTAKE
14.3.1 U.S. EPA Re-analysis of 1994-96, 1998
CSFII, Based on U.S. EPA (2007) - Analysis
of Total Food Intake and Composition of
Individual's Diet Based on USDA's 1994-96,
1998 Continuing Survey of Food Intakes by
Individuals (CSFII)
U.S. EPA's National Center for Environmental
Assessment (NCEA) conducted an analysis to evaluate
the total food intake of individuals in the United States
using data from the USDA's 1994-1996, 1998 CSFII
(USDA, 2000) and U.S. EPA's Food Commodity
Intake Database (FCID) (U.S. EPA, 2000). The
1994-96 CSFII and its 1998 Supplemental Children's
Survey were designed to obtain data from a statistically
representative sample of noninstitutionalized persons
living in the United States. Survey participants were
selected using a multistage process. The respondents
were interviewed twice to collect information on food
consumption during two non-consecutive days. For
both survey days, data were collected by an in-home
interviewer. The day two interview was conducted 3
to 10 days later and on a different day of the week. Of
the more than 20,000 individuals surveyed,
approximately 10,000 were under 21 years of age, and
approximately 9,000 were under the age of 11. The
1994-96 survey and 1998 supplement are referred to
collectively as CSFII 1994-96, 1998. Each individual
in the survey was assigned a sample weight based on
his or her demographic data; these weights were taken
into account when calculating mean and percentile
values of food consumption for the various
demographic categories that were analyzed in the
study. The sample weighting process used in the
CSFII 1994-96, 1998 are discussed in detail in USDA
(2000).
For the analysis of total food intake, food
commodity codes provided in U.S. EPA's Food
Commodity Intake Database (FCID) (U. S. EPA, 2000)
were used to translate as-eaten foods (e.g., beef stew)
identified by USDA food codes in the CSFII data set
into food commodities (e.g., beef, potatoes, carrots,
etc.). The method used to translate USDA food codes
into U.S. EPA commodity codes is discussed in detail
in USDA (2000). The U.S. EPA commodity codes
were assigned to broad food categories (e.g., total
meats, total vegetables, etc.) for use in the analysis.
Total food intake was defined as intake of the sum of
all foods in the following major food categories: dairy,
meats, fish, eggs, grains, vegetables, fruits, and fats.
Beverages, sugar, candy, and sweets, and nuts and nut
products were not included because they could not be
categorized into the major food groups. Also, human
milk intake was not included. Total food intake was
calculated for various age groups of children. Percent
consuming, mean, standard error, and a range of
percentile values were calculated on the basis of grams
of food per kilogram of body weight per day (g/kg-day)
and on the basis of grams per day (g/day). In addition
to total food intake, intake of the various major food
groups for the various age groups in units of g/day and
g/kg-day were also estimated for comparison to total
intake.
To evaluate variability in the contributions of
the major food groups to total food intake, individuals
were ranked from lowest to highest, based on total food
intake. Three subsets of individuals were defined, as
follows: a group at the low end of the distribution of
total intake (i.e., below the 10th percentile of total
intake), a central group (i.e., the 45th to 55th percentile
of total intake), and a group at the high end of the
distribution of total intake (i.e., above the 90th
percentile of total intake). Mean total food intake (in
g/day and g/kg-day), mean intake of each of the major
food groups (in g/day and g/kg-day), and the percent of
total food intake that each of these food groups
represents was calculated for each of the three
populations (i.e., individuals with low-end, central,
and high-end total food intake). A similar analysis
was conducted to estimate the contribution of the
major food groups to total food intake for individuals
at the low-end, central, and high-end of the
distribution of total meat intake, total dairy intake,
total meat and dairy intake, total fish intake, and total
fruit and vegetable intake. For example, to evaluate
the variability in the diets of individuals at the low-
end, central range, and high-end of the distribution of
total meat intake, survey individuals were ranked
according to their reported total meat intake. Three
subsets of individuals were formed as described above.
Mean total food intake, intake of the major food
groups, and the percent of total food intake represented
by each of the major food groups were tabulated. U.S.
EPA (2007) presented the results of the analysis for the
following age groups: <1 year, 1 to 2 years, 3 to 5
Page
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Child-Specific Exposure Factors Handbook
Chapter 14 - Total Food Intake
years, 6 to 11 years, and 12 to 19 years. The data were
tabulated in units of g/kg-day and g/day.
In order to conform to the standard age
categories recommended in Guidance on SelectingAge
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U. S. EPA,
2005) and used in this handbook, each of the tables
from U.S. EPA (2007) was modified by re-analyzing
the source data and applying the new age categories
(i.e., <1 month, 1 to <3 months, 3 to <6 months, 6 to
<12 months, 1 to <2 years, 2 to < 3 years, 3 to < 6
years, 6 to < 11 years, 11 to < 16 years, and 16 to < 21
years). The results of this re-analysis are presented in
Tables 14-3 through 14-11. Distributions of total food
intake are presented in Table 14-3 in units of g/day
and g/kg-day. Tables 14-4 and 14-5 compare total
food intake to intake of the various major food groups
for the various age groups in units of g/day and g/kg-
day, respectively. It should be noted that some U.S.
EPA commodity codes are listed under more than one
food category. For this reason, in the tables, the intake
rates for the individual food categories do not
necessarily add up to the figure given for total food
intake (U.S. EPA, 2007). Also, data are not reported
for food groups for which there were less than 20
consumers in a particular age group. Tables 14-6
through 14-11 present the contributions of the major
food groups to total food intake for individuals (in the
various age groups) at the low-end, central, and high-
end of the distribution of total food intake (Table 14-
6), total meat intake (Table 14-7), total meat and dairy
intake (Table 14-8), total fish intake (Table 14-9), total
fruit and vegetable intake (Table 14-10), and total
dairy intake (Table 14-11) in units of g/day and g/kg-
day. For each of the three classes of consumers,
consumption of nine different food categories is
presented (i.e., total foods, dairy, meats, fish, eggs,
grains, vegetables, fruits, and fats). For example, in
Table 14-9 one will find the mean consumption of
meats, eggs, vegetables, etc. for individuals with an
unusually high (or low or average) consumption of
fish.
As discussed in previous chapters, the 1994-96,
98 CSFII data set have both advantages and limitations
with regard to estimating food intake rates. The large
sample size (more than 20,000 persons; approximately
10,000 children) is sufficient to allow categorization
within narrowly defined age categories. In addition,
the survey was designed to obtain a statistically valid
sample of the entire United States population that
included children and low income groups. However,
the survey design is of limited utility for assessing
small and potentially at-risk subpopulations based on
ethnicity, medical status, geography, or other factors
such as activity level. Another limitation is that data
are based on a two-day survey period and, as such, may
not accurately reflect long-term eating patterns. This
is particularly true for the tails (extremes) of the
distribution of food intake.
14.4 REFERENCES FOR CHAPTER 14
USDA (2000) 1994-96, 1998 Continuing survey of
food intakes by individuals (CSFII). CD-ROM.
Agricultural Research Service, Beltsville
Human Nutrition Research Center, Beltsville,
MD. Available from the National Technical
Information Service, Springfield, VA; PB-2000-
500027.
U.S. EPA (2000) Food commodity intake database
[FCID raw data file]. Office of Pesticide
Programs, Washington, DC. Available from the
National Technical Information Service,
Springfield, VA; PB2000-5000101.
U.S. EPA (2005) Guidance on selecting age groups
for monitoring and assessing childhood
exposures to environmental contaminants. U.S.
Environmental Protection Agency, Washington,
D.C., EPA/630/P-03/003F. Available from the
National Technical Information Service,
Springfield, VA, and online at
www. epa. gov/ncea.
U.S. EPA (2007) Analysis of total food intake and
composition of individual's diet based on
USDA's 1994-96, 1998 continuing survey of
food intakes by individuals (CSFII). National
Center for Environmental Assessment,
Washington, DC; EPA/600/R-05/062F.
Available from the National Technical
Information Service, Springfield, VA, and
online at www.epa.gov/ncea.
Child-Specific Exposure Factors Handbook
September 2008
Page
14-5
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Child-Specific Exposure Factors Handbook
Chapter 14 - Total Food Intake
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Child-Specific Exposure Factors Handbook
Chapter 14 - Total Food Intake
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
TABLE OF CONTENTS
15 HUMAN MILK INTAKE 15-1
15.1 INTRODUCTION 15-1
15.2 RECOMMENDATIONS 15-1
15.2.1 Human Milk Intake 15-2
15.2.2 Lipid Content and Lipid Intake 15-2
15.3 KEY STUDIES ON HUMAN MILK INTAKE 15-10
15.3.1 Pao et al, 1980 15-10
15.3.2 Dewey and Lonnerdal, 1983 15-10
15.3.3 Butte et al., 1984 15-10
15.3.4 Neville et al., 1988 15-11
15.3.5 Dewey et al., 1991a, b 15-11
15.3.6 Butte, et al., 2000 15-12
15.3.7 Arcus-Arth et al., 2005 15-12
15.4 KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK 15-13
15.4.1 Butte et al., 1984 15-13
15.4.2 Mitoulas et al., 2002 15-14
15.4.3 Mitoulas et al., 2003 15-14
15.4.4 Arcus-Arth et al., 2005 15-15
15.4.5 Kent et al., 2006 15-15
15.5 RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK 15-16
15.5.1 Maxwell and Burmaster, 1993 15-16
15.6 OTHER FACTORS 15-16
15.6.1 Population of Nursing Infants 15-16
15.6.2 Intake Rates Based on Nutritional Status 15-19
15.6.3 Frequency and Duration of Feeding 15-19
15.7 REFERENCES FOR CHAPTER 15 15-19
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September 2008 15-i
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
LIST OF TABLES
Table 15-1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed
Infants
Table 15-2. Confidence in Recommendations for Human Milk Intake
Table 15-3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
(mL/day)
Table 15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
(mL/kg/day)
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day). . .
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
(mL/kg/day)
Table 15-7. Daily Intakes of Human Milk
Table 15-8. Human Milk Intakes for Infants Aged 1 to 6 Months
Table 15-9. Human Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months
of Life
Table 15-10. Human Milk Intake During a 24-hour Period
Table 15-11. Human Milk Intake Estimated by the Darling Study
Table 15-12. Mean Breastfed Infants Characteristics
Table 15-13. Mean Human Milk Intake of Breastfed Infants (mL/day)
Table 15-14. Feeding Practices by Percent of Infants
Table 15-15. Body Weight of Breastfed Infants
Table 15-16. AAP Dataset Milk Intake Rates at Different Ages
Table 15-17. Average Daily Human Milk Intake (mL/kg day)
Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed
Infants
Table 15-19. Human Milk Production and Composition Over the First 12 Months of Lactation
Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content Over the First Year of
Lactation
Table 15-21. Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation
(g/100 g total fatty acids)
Table 15-22. Comparison of Lipid Content Assumptions (mL/kg-day)
Table 15-23. Distribution of Average Daily Lipid Intake (mL/kg day) assuming 4% Milk Lipid Content. .
Table 15-24. Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age
Table 15-25. Socio-economic Characteristics of Exclusively Breast-fed Infants Born in 2004
Tablel5-26. Geographic-specific Breastfeeding Percent Rates Among Children Born in 2004
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6
Months Old
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12
Months Old
Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
During the Previous 24-hours
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III
(1988-1994)
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk
at 6 Months (NHANES III, 1988-1994)
. 15-3
. 15-4
. 15-6
. 15-7
. 15-8
. 15-9
15-22
15-22
15-23
15-24
15-25
15-25
15-26
15-26
15-27
15-28
15-29
15-29
15-30
15-31
15-32
15-32
15-33
15-33
15-34
15-35
15-36
15-37
15-38
15-39
15-40
Page
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Chapter 15 - Human Milk Intake
Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breastfed at 4
Months (NHANES III, 1991-1994) 15-41
Table 15-33. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6
Months of Age in the United States in 1989 and 1995, by Ethnic Background and Selected
Demographic Variables 15-42
Table 15-34. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 6 and
12 Months of Age in the United States in 2003, by Ethnic Background and Selected
Demographic Variables 15-43
Table 15-35. Number of Meals Per Day 15-44
Table 15-36. Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD) 15-44
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
15 HUMAN MILK INTAKE
15.1 INTRODUCTION
Human lactation is known to impart a wide
range of benefits to nursing infants, including
protection against infection, increases in cognitive
development, and avoidance of allergies due to
intolerance to cow's milk (AAP, 2005). Ingestion of
human milk has also been associated with a reduction
in risk of postneonatal death in the U.S. (Chen and
Rogan, 2004). The American Academy of Pediatrics
recommends exclusive breastfeeding for approximately
the first six months and supports the continuation of
breastfeeding for the first year and beyond if desired
by the mother and child (AAP, 2005). However,
contaminants may find their way into human milk of
lactating mothers because mothers are themselves
exposed. Thus, making human milk a potential source
of exposure to toxic substances for nursing infants.
Lipid soluble chemical compounds accumulate in body
fat and may be transferred to breast-fed infants in the
lipid portion of human milk. Water soluble chemicals
may also partition into the aqueous phase and be
excreted via human milk. Because nursing infants
obtain most (if not all) of their dietary intake from
human milk, they are especially vulnerable to
exposures to these compounds. Estimating the
magnitude of the potential dose to infants from human
milk requires information on the milk intake rate
(quantity of human milk consumed per day) and the
duration (months) over which breast-feeding occurs.
Information on the fat content of human milk is also
needed for estimating dose from human milk residue
concentrations that have been indexed to lipid content.
Several studies have generated data on human
milk intake. Typically, human milk intake has been
measured over a 24-hour period by weighing the infant
before and after each feeding without changing its
clothing (test weighing). The sum of the difference
between the measured weights overthe 24-hourperiod
is assumed to be equivalent to the amount of human
milk consumed daily. Intakes measured using this
procedure are often corrected for evaporative water
losses (insensible water losses) between infant
weighings (NAS, 1991). Neville et al. (1988)
evaluated the validity of the test weight approach
among bottle-fed infants by comparing the weights of
milk taken from bottles with the differences between
the infants' weights before and after feeding. When
test weight data were corrected for insensible weight
loss, they were not significantly different from bottle
weights. Conversions between weight and volume of
human milk consumed are made using the density of
human milk (approximately 1.03 g/mL) (NAS, 1991).
Techniques for measuring human milk intake using
stable isotopes such as deuterium have been developed.
The advantages of these techniques over test weighing
procedures are that they are less burdensome for the
mother and do not interfere with normal behavior
(Albernaz et al., 2002). However, few data based on
this technique were found in the literature.
Among infants born in 2004, 73.8% were
breastfed postpartum, 41.5.% at 6 months, and 20.9%
at 12 months. Studies among nursing mothers in
industrialized countries have shown that average
intakes among infants ranged from approximately 500
to 800 mL/day, with the highest intake reported for
infants 3 to < 6 months old (see Table 15-1) .
The recommendations for human milk intake
rates and lipid intake rates are provided in the next
section along with a summary of the confidence ratings
for these recommendations. The recommended values
are based on key studies identified by EPA for this
factor. Following the recommendations, key studies on
human milk intake are summarized. Relevant data on
lipid content and fat intake, breast-feeding duration, and
the estimated percentage of the U.S. population that
breast-feeds are also presented.
A number of other studies exist in the
literature, but they focus on other aspects of lactation
such as growth patterns of nursing infants,
supplementary food and energy intake, and nutrition of
lactating mothers (Dewey et al., 1992; Drewett et
al.,1993; Gonzalez-Cossio et al., 1998). These studies
are not included in this chapter because they do no
focus on the exposure factor of interest. Other studies
in the literature focus on formula intake. Since some
baby formula are prepared by adding water, these data
are presented in chapter 3 - Water Intake.
15.2 RECOMMENDATIONS
The studies described in Section 15.3 were
used in selecting recommended values for human milk
intake and lipid intake. Although different survey
designs, testing periods, and populations were utilized
by the studies to estimate intake, the mean and standard
deviation estimates reported in these studies are
relatively consistent. There are, however, limitations
with the data. With the exception of Butte et al. (1984)
and Arcus-Arth et al. (2005), data were not presented
on a body weight basis. This is particularly important
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
since intake rates may be higher on a body weight basis
for younger infants. Also, the data used to derive the
recommendations are over 15 years old and the sample
size of the studies was small. Other populations of
concern such as mothers highly committed to
breastfeeding, sometimes for periods longer than
1 year, may not be captured by the studies presented in
this chapter.
15.2.1 Human Milk Intake
A summary of recommended values forhuman
milk and lipid intake rates is presented in Table 15-1
and the confidence ratings for these recommendations
are presented in Table 15-2. The human milk intake
rates for nursing infants that have been reported in the
studies described in this section are summarized in
Table 15-3 in units of mL/day and in Table 15-4 in
units of mL/kg-day (i.e., indexed to body weight). It
should be noted that the decrease in human milk with
age is likely a result of complementary foods being
introduced as the child grows and not necessarily a
decrease in total energy intake. In order to conform to
the new standardized age groupings used in this
handbook (see Chapter 1), data from Pao et al. (1980),
Dewey and Lonnerdal (1983), Butte et al. (1984),
Neville et al. (1988), Dewey et al. (199la), Dewey et
al. (1991b), Butte et al. (2000) and Arcus-Arth et al.
(2005) were compiled for each month of the first year
of life. Recommendations were converted to mL/day
using a density of human milk of 1.03 g/mL rounded up
to two significant figures. Only two studies (i.e., Butte
et al., 1984 and Arcus-Arth et al., 2005) provided data
on a body weight basis. For some months multiple
studies were available; for others only one study was
available. Weighted means were calculated for each
age in months. When upper percentiles were not
available from a study, these were estimated by adding
two standard deviations to the mean value.
Recommendations for upper percentiles, when multiple
studies were available, were calculated as the midpoint
of the range of upper percentile values of the studies
available for each age in months. These month-by-
month intakes were composited to yield intake rates for
the standardized age groups by calculating a weighted
average. Recommendations are provided for the
population of exclusively breastfed infants since this
population may have higher exposures than partially
breastfed infants. Exclusively breastfed in this
chapter refers to infants whose sole source of milk
comes from human milk, with no other milk
substitutes. Partially breastfed refers to infants
whose source of milk comes from both human milk
and other milk substitutes (i.e., formula). Note that
some studies define partially breastfed as infants whose
dietary intake comes from not only human milk and
formula, but also from other solid foods (e.g., strained
fruits, vegetables, meats).
15.2.2 Lipid Content and Lipid Intake
Recommended lipid intake rates are presented
in Table 15-5. The table parallels the human milk
intake tables (Table 15- 3). With the exception of the
data from Butte et al. (1984), the rates were calculated
assuming a lipid content of 4% (Butte et al.,1984; NAS,
1991; Maxwell and Burmaster, 1993). In the case of
the Butte et al. (1984) study, lipid intake rates were
provided, and were used in place of the estimated lipid
intakes. Lipid intake rates on a body weight basis are
presented in Table 15-6. These were calculated from
the values presented in Table 15-4 multiplied by 4%
lipid content.
Page
15-2
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Chapter 15 - Human Milk Intake
Table 15-1. Recommended
Age Group
Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed Infants
Mean Upper Percentilea
Source
mL/day mL/kg-day mL/day mL/kg-day
Human Milk Intake
Birth to <1 month 510
1 to <3 months 690
3 to <6 months 770
6 to <12 months 620
150 950 220 b
140 980 190 b,c, d, e,f
110 1,000 150 b,c, d, e, f, g
83 1,000 130 b,c, e, g
Lipid Intake h
Birth to <1 month 20
1 to <3 months 27
3 to <6 months 30
6 to <12 months 25
6.0 38 8.7 i
5.5 40 8.0 d, i
4.2 42 6.0 d, i
3.3 42 5.2 i
Upper percentile is reported as mean plus 2 standard deviations.
Neville et al., 1988.
' Pao etal., 1980.
a Butteet al., 1984.
e Dewey and Lonnerdal, 1983.
f Butteet al., 2000.
' Dewey etal., 1991b.
h The recommended value for the
Arcus- Arth et al., 2005.
lipid content of human milk is 4.0 percent. See Section 15.5.
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Chapter 15 - Human Milk Intake
Table 15-2. Confidence in Recommendations for Human Milk Intake
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Medium
Methodology uses changes in body weight as a surrogate for total
ingestion. More sophisticated techniques measuring stable
isotopes have been developed, but data with this technique were
not available. Sample sizes were relatively small (7-108).
Mothers selected for the studies were volunteers. The studies
analyzed primary data.
Mothers were instructed in the use of infant scales to minimize
measurement errors. Three out of the 8 studies indicated
correcting data for insensible water loss. Some biases may be
introduced by including partially-breastfed infants.
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Medium
The studies focused on estimating human milk intake.
Most studies focused on the U.S. population, but were not
national samples. Population studied were mainly from high
socioeconomic status. One study included populations from
Sweden and Finland. However, this may not affect the amount of
intake, but rather the prevalence and initiation of lactation.
Studies were conducted between 1980-2000. However, this may
not affect the amount of intake, but rather the prevalence and
initiation of lactation.
Infants were not studied long enough to fully characterize day to
day variability.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Medium
All key studies are available from the peer reviewed literature.
The methodology was clearly presented, but some studies did not
discuss adjustments due to insensible weight loss.
Some steps were taken to ensure data quality. For example,
mothers were trained to use the scales. However, this element
could not be fully evaluated from the information presented in the
published studies.
Variability and Uncertainty
Variability in Population
Uncertainty
Low
Not very well characterized. Mothers committed to breastfeeding
over 1 year were not captured.
Not correcting for insensible water loss may underestimate intake.
Page
15-4
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-2. Confidence in Recommendations for Human Milk Intake (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The studies appeared in peer review journals.
There are 8 key studies. The results of studies from
different researchers are in agreement.
Rating
High
Medium
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September 2008 15-5
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-3.
Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/day)
Upper
Age Number of , Percentile
Intake
(months) Children , T , , ^ Consumption
(mL/day) , T ,, ,,
v " (mL/day)"
0<
1
2
3
4
5
6
7
8
9
10
11
12
1 6 to 13
11
37
12
16
10 to 12
19
40
2
37
10
16
73
40
12
13
41
12
11
1
13
11
60
30
12
9
12
50
11
8
8
42
13
511
600
729
679 a
673
679 a
756
704
833
702
713
782
788
728
690
810
740
814
805
682
744
896
747
637
700
604
600
627
535
538
391
435
403
951
918
981
889
1,057
889
1,096
958
924
935
1,126
1,047
988
888
1,094
996
1,074
1,039
-ed
978
1,140
1,079
1,050
1,000
1,012
1,028
1,049
989
1,004
877
922
931
Weighted Mean Intake
and Upper Percentile Consumption
(across all Key Studies)
(mL/day)
Composite Age
Individual Age ^
Groups
Meanb Upperc Mean Upperc
Neville etal., 1988 511 951
Pao etal., 1980
Butte et al., 1984
Neville etal., 1988 6?° %1
Dewey and Lonnerdal, 1983
Neville et al., 1988
Dewey and Lonnerdal, 1983 713 992
Butte et al., 1984
Pao etal., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey etal., 1991b
Butte et al., 2000
Neville et al., 1988
Dewey and Lonnerdal, 1983 739 991
Butte et al., 1984
Neville et al., 1988 j Q57
Dewey and Lonnerdal, 1983 '
Pao etal., 1980
Neville et al., 1988
Dewey and Lonnerdal, 1983 741 1,000
Dewey etal., 1991b
Butte et al., 2000
Neville etal., 1988 700 1,006
Neville etal., 1988 604 1,012
Neville etal., 1988
Dewey etal., 199 Ib
Neville etal., 1988 535 989
Neville etal., 1988 538 1,004
Neville et al., 1988
Dewey et al., 1991a; 1991b 410 904
Butte et al., 2000
511 951
692 977
769 1,024
622 1,024
410 904
Calculated as the mean of the means.
Upper percentile is reported as mean plus 2 standard deviations.
c Middle of the range of upper percentiles.
d Calculated for infants 1 to < 2 months old.
e Standard deviations and upper percentiles not calculated for small sample sizes.
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15-6
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Chapter 15 - Human Milk Intake
Table
15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/kg/day)
Mean Upper
Age Number
Intake Percentile
(months) of
(mL/kg- Consumption
Children
day) (mL/kg-day)
0 <
1
2
3
4
5
6
7
9
12
1 9 to 25 150
37
25
40
25
37
108
41
57
26
39
8
57
42
154
150
125
144
114
127
108
112
100
101
75
72
47
Calculated as the mean of the means.
b Upper percentile is reported as mean plus
c Middle of the range of upper percentiles.
217
200
198
161
188
152
163
142
148
140
141
125
118
101
Weighted Mean Intake
and Upper Percent! e Consumption
(across all Key Studies)
(mL/kg-day)
Individual Age Composite Age
Groups
Meanb Upperc Mean Upperc
Arcus-Arth et al, 2005 150 217
Butte etal., 1984 152 199
Arcus-Arth et al, 2005
Butte etal., 1984 135 175
Arcus-Arth et al, 2005
Butte etal., 1984 121 158
Arcus-Arth et al, 2005
Butte etal., 1984 110 145
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005 100 140
Arcus-Arth et al, 2005 101 141
Arcus-Arth et al, 2005 75 125
Arcus-Arth et al, 2005 72 118
Arcus-Arth et al, 2005 47 101
150 217
144 187
111 149
83 130
47 101
2 standard deviations.
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Chapter 15 - Human Milk Intake
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day)a
Age Number of
(months) Children
0<
1
2
3
4
5
6
7
8
9
10
11
12
b
d
1 6 to 1 3
11
37
10 to 12
16
1 0 to 12
19
40
37
10
16
73
40
12
13
41
12
11
1
13
11
60
30
12
9
12
50
11
9
9
42
13
Except for Butte et al. 1984
Upper percentile is reported
Calculated as the mean of th
Middle of the range of uppe
Standard deviations and upp
Mean
Intake
(mL/day)
20
24
27
27
27
27
30
24
33
23
29
31
32
29
28
32
25
33
32
27
30
36
30
25
28
24
24
25
21
22
17
17
16
Upper Percentile
Consumption
(mL/day)b
38
37
43
36
42
36
44
38
37
37
45
42
40
36
44
41
43
42
39
46
43
42
40
40
41
42
40
40
35
37
37
as mean plus 2 standard deviations.
e means.
r percentiles.
er percentiles not calculated for smal
Weighted Mean Intake
and Upper Percentile Consumption
(across all Key Studies)
(mL/day)
source
Composite Age
Individual Age
Groups
Meanc Upperd Meanc Upperd
Neville etal., 1988 20 38
Pao etal., 1980
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Neville etal., 1988
Dewey and Lonnerdal, 1983 27 40
Butte etal., 1984
Pao etal., 1980
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Dewey etal., 1991b
Butte et al. 2000
Neville etal., 1988
Dewey and Lonnerdal, 1983 28 40
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Pao etal., 1980
Neville etal., 1988
Dewey and Lonnerdal, 1983 30 40
Dewey etal., 1991b
Butte etal., 2000
Neville etal., 1988 28 40
Neville etal., 1988 24 41
Neville etal., 1988
Dewey etal., 1991b
Neville etal., 1988 21 40
Neville etal., 1988 22 40
Neville etal., 1988
Dewey etal., 1991a; 1991b 16 36
Butte etal., 2000
20 38
27 40
30 42
25 42
16 36
3 using 4% lipid content.
sample sizes.
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Chapter 15 - Human Milk Intake
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/kg/day)a
Age Number Mean Intake
(months) of (mL/kg-day)
Children
0 <
1
2
3
4
5
6
7
9
12
•
1 9 to 25 6.0
37
25
40
25
37
108
41
57
26
39
8
57
42
Except for Butte
content.
Upper percentile
Calculated as the
5.7
6.0
4.3
5.8
3.7
5.1
3.7
4.5
4.0
4.0
3.0
2.9
1.9
et al. 1984, values were
is reported as mean plus
mean of the means.
Upper
Percentile
Consumption
(mL/kg-day)b
8.7
9.1
8.7
6.7
7.5
6.1
6.5
6.3
5.9
5.6
5.6
5.0
4.7
4.0
calculated from t
Source
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
ible 15-4 using 4% lipid
Weighted Mean Intake
and Upper Percentile Consumption11
(across a211 Key Studies)
(mL/kg-day)
Individual Age Composite Ages
Groups
Mean6 Upperd Mean6 Upperd
6.2 8.7
5.9 8.9
5.1 7.1
4.4 6.3
4.1 6.1
4.0 5.8
4.0 5.6
3.0 5.0
2.9 4.7
1.9 4.0
6.0 8.7
5.5 8.0
4.2 6.0
3.3 5.2
1.9 4.1
2 standard deviations.
Middle of the ranae of urmer nercentiles.
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
15.3 KEY STUDIES ON HUMAN MILK
INTAKE
15.3.1 Pao et al., 1980 - Milk Intakes and Feeding
Patterns of Breast-fed Infants
Pao et al. (1980) conducted a study of 22
healthy nursing infants to estimate human milk intake
rates. Infants were categorized as completely breast-fed
or partially breast-fed. Breastfeeding mothers were
recruited through LaLeche League groups. Except for
one black infant, all other infants were from white
middle-class families in southwestern Ohio. The goal
of the study was to enroll infants as close to one month
of age as possible and to obtain records near one, three,
six, and nine months of age (Pao et al., 1980).
However, not all mother/infant pairs participated at
each time interval. Data were collected for these 22
infants using the test weighing method. Records were
collected for three consecutive 24-hour periods at each
test interval. The weight of human milk was converted
to volume by assuming a density of 1.03 g/mL. Daily
intake rates were calculated for each infant based on the
mean of the three 24-hour periods. Mean daily human
milk intake rates for the infants surveyed at each time
interval are presented in Table 15-7. These data (Table
15-7) are presented as they are reported in Pao et al.
(1980). For completely breast-fed infants, the mean
intake rates were 600 mL/day at 1 month of age,
833 mL/day at 3 months of age, and 682 mL/day at 6
months of age. Partially breast-fed infants had mean
intake rates of 485 mL/day, 467 mL/day, 395 mL/day,
and <554 mL/day at 1, 3, 6, and 9 months of age,
respectively. Pao et al. (1980) also noted that intake
rates for boys in both groups were slightly higher than
for girls.
The advantage of this study is that data for both
exclusively and partially breast-fed infants were
collected for multiple time periods. Also, data for
individual infants were collected over 3 consecutive
days which would account for some individual
variability. However, the number of infants in the
study was relatively small. In addition, this study did
not account for insensible weight loss which may
underestimate the amount of human milk ingested.
15.3.2 Dewey and Lonnerdal, 1983 - Milk and
Nutrient Intake of Breast-fed Infants from
1 to 6 Months: Relation to Growth and
Fatness
Dewey and Lonnerdal (1983) monitored the
dietary intake of 20 nursing infants between the ages of
1 and 6 months. The number of study participants
dropped to 13 by the end of the sixth month. Most of
the infants in the study were exclusively breast-fed.
One infant's intake was supplemented by formula
during the first and second month of life. During the
third, fourth, and fifth months, three, four, and five
infants, respectively, were given some formula to
supplement their intake. Two infants were given only
formula (no human milk) during the sixth month.
According to Dewey and Lonnerdal (1983), the mothers
were all well educated and recruited through Lamaze
childbirth classes in the Davis area of California.
Human milk intake volume was estimated based on two
24-hour test weighings per month. Human milk intake
rates for the various age groups are presented in Table
15-8. Human milk intake averaged 673, 782, and 896
mL/day at 1, 3, and 6 months of age, respectively.
The advantage of this study is that it evaluated
nursing infants for a period of 6 months based on two
24-hour observations per infant per month. However,
corrections for insensible weight loss apparently were
not made. Also, the number of infants in the study was
relatively small and the study participants were not
representative of the general population. Some infants
during the study period were given some formula (i.e.,
up to 5 infants during the fifth month). Without the raw
data, these subjects could not be excluded from the
study results. Thus, these subjects may affect the
results when deriving recommendations for exclusively
breastfed infants.
15.3.3 Butte et al., 1984 - Human Milk Intake and
Growth in Exclusively Breast-fed Infants
Human milk intake was studied in exclusively
breast-fed infants during the first 4 months of life
(Butte et al., 1984). Nursing mothers were recruited
through the Baylor Milk Bank Program in Texas.
Forty-five mother/infant pairs participated in the study.
However, data for some time periods (i.e., 1, 2, 3, or 4
months) were missing for some mothers as a result of
illness or other factors. The mothers were from the
middle- to upper-socioeconomic stratum and had a
mean age of 28.0 ± 3.1 years. A total of 41 mothers
were white, 2 were Hispanic, 1 was Asian, and 1 was
West Indian. Infant growth progressed satisfactorily
over the course of the study.
The amount of milk ingested over a 24-hour
period was determined by weighing the infant before
and after feeding. The study did not indicate whether
the data were corrected for insensible water or weight
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Chapter 15 - Human Milk Intake
loss. The mean and standard deviation milk intake
difference based on weighing the bottle before and after
nine successive feedings, was estimated to be 3.2 ±3.1
g. Test weighing occurred over a 24-hour period for
most study participants, but intake among several
infants was studied over longer periods (48 to 96 hours)
to assess individual variation in intake. It was reported
that eight of the infants received some food
supplementation during the study period. Six of them
received less than 60 kcal/day of formula, oatmeal,
glucose water, or rice water for 1 or 2 days. One infant
received an additional 90 kcal/day of infant formula and
rice water for 6 days during the fourth month because
of inadequate milk production. Converting values
reported as g/day to mL/day, using a conversion factor
of 1.03 g/mL, mean human milk intake ranged from
702 mL/day at 3 months to 729 mL/day at 1 month,
with an overall mean of 712 mL/day for the entire study
period (Table 15-9). Intakes were also calculated on
the basis of body weight (Table 15-9). Based on the
results of test weighings conducted over 48 to 96 hours,
the overall mean variation in individual daily intake
was estimated to be 7.9 ± 3.6 percent.
The advantage of this study is that data for a
larger number of exclusively breast-fed infants were
collected than in previous studies. However, data were
collected for infants up to 4 months and day-to-day
variability was not characterized for all infants. It was
reported that eighteen percent (i.e., 8 out of 45) of the
infants received some formula supplementation during
the study period. Without the raw data, these subjects
could not be excluded from the study results. Therefore,
values derived from this study for exclusively breastfed
infants may be somewhat underestimated.
15.3.4 Neville et al., 1988 - Studies in Human
Lactation: Milk Volumes in Lactating
Women During the Onset of Lactation and
Full Lactation
Neville et al. (1988) studied human milk
intake among 13 infants during the first year of life.
The mothers were all multiparous, nonsmoking,
Caucasian women of middle- to upper-socioeconomic
status living in Denver, CO. All women in the study
practiced exclusive breast-feeding for at least 5 months.
Solid foods were introduced at mean age of 7 months.
Daily milk intake was estimated by the test weighing
method with corrections for insensible weight loss.
Data were collected daily from birth to 14 days, weekly
from weeks 3 through 8, and monthly until the study
period ended at 1 year after inception. One infant was
weaned at 8 months, while all others were weaned on or
after the 12 months. Formula was used occasionally (<
240 mL/wk) after 4 months in three infants. The
estimated human milk intakes for this study are listed in
Table 15-10. Converting values reported as g/day to
mL/day, using a conversion factor of 1.03 g/mL, mean
human milk intakes were 748 mL/day, 713 mL/day,
744 mL/day, and 391 mL/day at 1, 3, 6, and 12 months
of age, respectively.
In comparison to the previously described
studies, Neville et al. (1988) collected data on
numerous days over a relatively long time period (12
months) and they were corrected for insensible weight
loss. However, the intake rates presented in Table 15-
10 are estimated based on intake during only a 24-hour
period. Consequently, these intake rates are based on
short-term data that do not account for day-to-day
variability among individual infants. Also, a smaller
number of subjects was included than in the previous
studies. Three infants were given some formula after 4
months. Without the raw data, these subjects could not
be excluded from the study results. Thus, data
presented for infants between 5 and 12 months may be
an underestimate for the intake of exclusively breastfed
infants.
15.3.5 Dewey et al., 1991a, b - (a) Maternal
Versus Infant Factors Related to Human
Milk Intake and Residual Volume: The
DARLING Study; (b) Adequacy of Energy
Intake Among Breast-fed Infants in the
DARLING Study: Relationships to
Growth, Velocity, Morbidity, and Activity
Levels
The Davis Area Research on Lactation, Infant
Nutrition and Growth (DARLING) study was
conducted in 1986 to evaluate growth patterns, nutrient
intake, morbidity, and activity levels in infants who
were breast-fed for at least the first 12 months of life
(Dewey et al., 1991a, b). Subjects were non-randomly
selected through letters to new parents using birth
listing. One of the criteria used for selection was that
mothers did not plan to feed their infants more than 120
mL/day of other milk or formula for the first 12 months
of life. Seventy-three infants aged 3 months were
included in the study. At subsequent time intervals, the
number of infants included in the study was somewhat
lower as a result of attrition. All infants in the study
were healthy and of normal gestational age and weight
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
at birth, and did not consume solid foods until after the
first 4 months of age. The mothers were highly
educated and of "relatively high socioeconomic status."
Human milk intake was estimated by weighing
the infants before and after each feeding and correcting
for insensible water loss. Test weighings were
conducted over a 4-day period every 3 months. The
results of the study indicate that human milk intake
declines over the first 12 months of life. This decline
is associated with the intake of solid food. Converting
values reported as g/day to mL/day, using a conversion
factor of 1.03 g/mL, mean human milk intake was
estimated to be 788 mL/day at 3 months and
435 mL/day at 12 months (Table 15-11). Based on the
estimated intakes at 3 months of age, variability
between individuals (coefficient of variation ([CV] =
16.3%) was higher than the average day-to-day
variability ([CV] = 8.9 ± 5.4%) for the infants in the
study (Dewey et al., 199la).
The advantages of this study are that data were
collected over a relatively long-time (4 days) period at
each test interval, which would account for some day-
to-day infant variability, and corrections for insensible
water loss were made. Data from this study are
assumed to represent exclusively breastfed infants,
since mothers were specifically recruited for that
purpose. It is, however, unclear from the Dewey et al.,
199 la if this criterion was met throughout the length of
the study period.
15.3.6 Butte, et al., 2000 - Infant Feeding Mode
Affects Early Growth and Body
Composition
Butte et al. (2000) conducted a study to assess
the impact of infant feeding mode on growth and body
composition during the first two years of life. The
study was conducted in the Houston, Texas area,
recruited through the Children's Nutrition Research
Center (CNRC) referral system. The study was
approved by the Baylor Affiliates Review Boards for
Human Subject Research. The overall sample was 76
healthy term infants at 0.5, 3, 6, 9, 12, 18, and 24
months of age. The sample size varied between 71 to
76 infants for each age group. Repeated measurements
for body composition and anthropometric were
performed. The mothers agreed to either exclusively
breast feed or formula feed the infants for the first 4
months of life.
At 3-month or 6-month study intervals, the
feeding history was taken. The mothers or caretakers
were questioned about breastfeeding frequency, and the
use of formula, milk, juice, solids, water and vitamin or
mineral supplements. Also, infant food intake was
quantified at 3, 6, 12, and 24 months with a 3-day
weighted intake record completed by the mother or
caretaker (Butte et al., 2000). The intake of human
milk was assessed by test weighing; the infant weights
were measured before and after each feeding. Using a
pre-weighing and post-weighing method, the intake of
formula and other foods and beverages was determined
for 3 days by the mothers using a digital scale and
recorded on predetermined forms.
The average duration of breastfeeding was
11.4 months (SD = 5.8). Butte et al.(2000) reported
that infants were exclusively breastfed for at least the
first four months except for the following: one was
weaned at 109 days, another received formula at 102
days and another given cereal at 106 days. The infant
feeding characteristics are shown in Table 15-12. The
intake of human milk for the infants are shown in Table
15-13. Converting values reported as g/day to mL/day,
using a conversion factor of 1.03 g/mL, mean human
milk intake was estimated to be 728 mL/day at 3
months (weighted average of boys and girls),
637 mL/day at 6 months (weighted average of boys and
girls), and 403 mL/day at 12 months (weighted average
of boys and girls) (Table 15-13). Feeding practices by
percent for infants are shown in Table 15-14. The
mean weights are provided in Table 15-15.
Advantages of this study are that it provides
intake data for breastfed infants for the first four
months of life. The study also provides the mean
weights for the infants by feeding type and by gender.
The limitations of the study are that the sample size is
small and it is limited to one geographical location.
The authors did not indicate if results were corrected
for insensible weight loss. Since mothers could
introduce formula after 4 months, only the data for the
3-month old infants can be considered exclusively
breastfed.
15.3.7 Arcus-Arth et al., 2005 - Human Milk and
Lipid Intake Distributions for Assessing
Cumulative Exposure and Risk
Arcus-Arth et al. (2005) derived population
distributions for average daily milk and lipid intakes in
g/kg day for infants 0-6 months and 0-12 months of age
for infants fed according to the American Academy of
Pediatrics (AAP) recommendations. The AAP
recommends exclusively breastfeeding for the first 6
months of life, human milk as the only source of milk
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Chapter 15 - Human Milk Intake
age 1 year, with the introduction of solid foods after 6
months. The distributions were derived based on data
in the peer reviewed literature and datasets supplied by
the publication authors for infants 7 days and older
(Arcus-Arth et al., 2005). As cited in Arcus-Arth et al.
(2005), data sources included Dewey et al. (1991a,
199b), Hofvander et al. (1982), Neubauer et al. (1993),
Ferris et al. (1993), Salmenpera et al. (1985), and Stuff
and Nichols (1989). The authors also evaluated intake
rates for infants breastfed exclusively over the first year
and provides a regression line of intake versus age for
estimating short-term exposures. Arcus-Arth derived
human milk intake rates for the entire infant population
(nursing and non-nursing) from U.S. data on
consumption, prevalence and duration. Arcus-Arth et
al. (2005) defined exclusive breastfeeding (EBF) as
"breast milk is the sole source of calories, with no or
insignificant calories form other liquid or solid food
sources." Predominant breastfeeding was described by
Arcus-Arth et al. (2005) as "breast milk is the sole milk
source with significant calories from other foods." The
data that were consistent with AAP advice were used to
construct the AAP dataset (Arcus-Arth et al., 2005).
The 0-12 months EBF dataset was created using 0-6
month AAP data and data from the EBF infants older
than 6 months of age. Because there are no data in the
AAP dataset for any individual infant followed at
regular, frequent intervals over the 12 month period,
population distributions were derived with assumptions
regarding individual intake variability over time
(Arcus-Arth et al., 2005). Two methods were used. In
Method 1, the average population daily intake at each
age is described by a regression line, assuming
normality. Arcus-Arth et al. (2005) noted that age
specific intake data were consistent with the assumption
of normality. In Method 2, intake over time is
simulated for 2500 hypothetical infants and the
distribution intakes derived from 2500 individual
intakes (Arcus-Arth et al., 2005). The population
intake distribution was derived following Method 1.
Table 15-16 presents the means, and standard
deviations for intake data at different ages; the
variability was greatest for the 2 youngest and 3 oldest
age groups. The values in Table 15-6 using Method 1
were used to derive recommendations presented in
Table 15-4 since it provides data for the fine age
categories. Converting values reported as g/day to
mL/day, using a conversion factor of 1.03 g/mL, mean
human milk intake was estimated to be 150 mL/kg-day
at 1 month, 127 mL/kg-day at 3 months, 101 mL/kg-
day at 6 months, and 47 mL/kg-day at 12 months
(Table 15-16). Time weighted average intakes for
larger age groups (i.e., 0-6 months, 0-12 months) are
presented in Table 15-17.
An advantage of this study is that it was
designed to represent the infant population whose
mothers follow the AAP recommendations. Intake was
calculated on a body weight basis. In addition, the data
used to derive the distributions were from peer
reviewed literature and datasets supplied by the
publication authors. The distributions were derived
from data for infants fed in accordance to AAP
recommendations, and they most likely represent daily
average milk intake for a significant portion of
breastfed infants today (Arcus-Arth et al., 2005). The
limitations of the study are that the data used were from
mothers that were predominantly white, well nourished
and from mid or high socioeconomic status. Arcus-
Arth et al. (2005) also included data from Sweden and
Finland. However human milk volume in mL/day is
similar among all women except for severely
malnourished women (Arcus-Arth et al., 2005).
According to Arcus-Arth et al. (2005), "Although few
infants are exclusively breastfed for 12 months, the
EBF distributions may represent a more highly exposed
subpopulation of infants exclusively breastfed in excess
of 6 months."
15.4 KEY STUDIES ON LIPID CONTENT
AND LIPID INTAKE FROM HUMAN
MILK
Human milk contains over 200 constituents
including lipids, various proteins, carbohydrates,
vitamins, minerals, and trace elements as well as
enzymes and hormones. The lipid content of human
milk varies according to the length of time that an
infant nurses, and increases from the beginning to the
end of a single nursing session (NAS, 1991). The lipid
portion accounts for approximately 4% of human milk
(3.9% ± 0.4%) (NAS, 1991). This value is supported
by various studies that evaluated lipid content from
human milk. Several studies also estimated the quantity
of lipid consumed by breast-feeding infants. These
values are appropriate for performing exposure
assessments for nursing infants when the
contaminant(s) have residue concentrations that are
indexed to the fat portion of human milk.
15.4.1 Butte et al., 1984 - Human Milk Intake and
Growth in Exclusively Breast-fed Infants
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Butte et al. (1984) analyzed the lipid content
of human milk samples taken from women who
participated in a study of human milk intake among
exclusively breast-fed infants. The study was
conducted with over 40 women during a 4-month
period. The mean lipid content of human milk at
various infants' ages is presented in Table 15-18. The
overall lipid content for the 4-month study period was
3.43 ± 0.69 % (3.4%). Butte et al. (1984) also
calculated lipid intakes from 24-hour human milk
intakes and the lipid content of the human milk
samples. Lipid intake was estimated to range from 22.9
mL/day (3.7 mL/kg-day) to 27.2 mL/day (5.7 mL/kg-
day).
The number of women included in this study
was small, and these women were selected primarily
from middle to upper socioeconomic classes. Thus,
data on human milk lipid content from this study may
not be entirely representative of human milk lipid
content among the U.S. population. Also, these
estimates are based on short-term data, and day-to-day
variability was not characterized.
15.4.2 Mitoulas et al., 2002 - Variation in Fat,
Lactose, and Protein in Human Milk Over
24 h and Throughout the First Year of
Lactation
Mitoulas et al. (2002) conducted a study of
healthy nursing women to determine the volume and
composition of human milk during the first year of
lactation. Nursing mothers were recruited through the
Nursing Mothers' Association of Australia. All infants
were completely breastfed on demand for at least 4
months. Complementary solid food was introduced
between 4-6 months of age. Mothers consumed their
own ad libitum diets throughout the study. Seventeen
mothers initially provided data for milk production and
fat content, whereas lactose, protein, and energy were
initially obtained from nine mothers. The number of
mothers participating in the study decreased at 6
months due to the cessation of sample collection from
11 mothers, the maximum period of exclusive breast-
feeding.
Milk samples were collected before and after
each feed from each breast over a 24-28 hour period.
Milk yield was determined by weighing the mother
before and after each feed from each breast. Insensible
water loss was accounted for by weighing the mother
20 minutes after the end of each feeding. The rate of
water loss during this 20 minutes was used to calculate
insensible water loss during the feeding. Samples of
milk produced at the beginning of the feeding
(foremilk) and at the end of the feeding (hindmilk) were
averaged to provide the fat, protein, lactose, and energy
content for each feed. In all cases the left and right
breasts were treated separately, therefore, n, represents
the number of individual breasts sampled.
Mean human milk production and composition
at each age interval are presented in Table The
mean 24 hour milk production from both breasts was
798 (SD= 232) mL. The mean fat, lactose, and protein
contents (g/L) were 37.4 (SE= 0.6), 61.4 (SE =0.6), and
9.16 (SE= 0.19), respectively. Composition did not
vary between left and right breasts or preferred and
non-preferred breasts. Milk production was constant
for the first 6 months and thereafter steadily declined.
The fat content of milk decreased between 1 and 4
months, before increasing to 12 months of lactation.
The concentration of protein decreased to 6 months and
then remained steady. Lactose remained constant
throughout the 12 months of lactation. The decrease of
energy at 2 months and subsequent increase by 9
months can be attributed to the changes in fat content.
Milk production, as well as concentrations of fat,
lactose, protein, and energy, differed significantly
between women.
The focus of this study was on human milk
composition and production, not on infant's human
milk intake. The advantage of this study is that it
evaluated nursing mothers for a period of 12 months.
However, the number of mother-infant pairs in the
study was small (17 mothers with infants) and may not
be entirely representative of the U.S. population. This
study accounted for insensible water loss which
increases the accuracy of the amount of human milk
produced.
15.4.3 Mitoulas et al., 2003 - Infant Intake of Fatty
Acids from Human Milk Over the First
Year of Lactation
Mitoulas et al. (2003) conducted a study of 5
healthy nursing women to determine the content of fat
in human milk and fat intake by infants during the first
year of lactation. Nursing mothers were recruited
through the Australian Breastfeeding Association or
from private healthcare facilities. All infants were
completely breastfed on demand for at least 4 months.
Complementary solid food was introduced between 4-6
months of age. Mothers consumed their own ad libitum
diets throughout the study.
Milk samples were collected before and after
each feed from each breast over a 24-28 hour period.
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Fore- and hind-milk samples were averaged to provide
the fat content for each feed. Milk yield was
determined by weighing the mother before and after
each feed from each breast. Insensible water loss was
accounted for by weighing the mother 20 minutes after
the end of each feeding. The rate of water loss during
this 20 minutes was used to calculate insensible water
loss during the feeding.
Changes in volume of human milk produced
and milk fat content over the first year of lactation is
presented in Table 15-20. The mean volumes of milk
produced for both breasts combined were 812.13,
790.34, 911.38, 810.20, 677.35, and 505.10 mL/day at
1, 2, 4, 6, 9,and 12 months, respectively. The average
daily intake over the 12 months was 751.09 mL/day
with a mean fat content of 35.52 g/L. Their was a
significant difference in the proportional composition of
fatty acids over the course of lactation. Table 15-21
provides average fatty acid composition over the first
12 months of lactation. Additionally, fatty acid
composition varied over the course of the day.
The focus of this study was on human milk
composition and production, not on infant's human
milk intake. The advantage of this study is that it
evaluated the human milk composition for a period of
12 months. However, the number of mother-infant
pairs in the study was small (5 mothers with infants)
and may not be entirely representative of the entire U.S.
population. This study accounted for insensible water
loss which increases the accuracy of the amount of
human milk produced.
15.4.4 Arcus-Arth et al., 2005 - Human Milk and
Lipid Intake Distributions for Assessing
Cumulative Exposure and Risk
Arcus-Arth et al. (2005) derived population
distributions for average daily milk and lipid intakes in
g/kg day for infants 0-6 months and 0-12 months of age
for infants fed according to the American Academy of
Pediatrics (AAP) recommendations. Lipid intakes were
calculated from lipid content and milk intakes were
measured on the same infant (Arcus-Arth et al., 2005).
Table 15-22 provides lipid intakes based on data from
Dewey et al. 1991a and Table 15-23 provides lipid
intakes calculated assuming 4% lipid content and milk
intake in the AAP dataset. Arcus-Arth et al. (2005)
noted that the distributions presented are intended to
represent the U.S. infant population.
An advantage of this study is that it was
designed to represent the population of infants who are
breastfed according to the AAP recommendations. In
addition, the data used to derive the distributions were
from peer review literature and datasets supplied by the
publication authors. The limitation of the study are that
the data used were from mothers that were
predominantly white, well nourished and from mid- or
upper-socioeconomic status, however human milk
volume in mL/day is similar among all women except
for severely malnourished women (Arcus-Arth et al.,
2005). The authors noted that "although few infants are
exclusively breastfed for 12 months, the exclusively
breastfed distributions may represent a more highly
exposed subpopulation of infants exclusively breastfed
in excess of 6 months." The distributions were derived
from data for infants fed in accordance to AAP
recommendations, and they most likely represent daily
average milk intake for a significant portion of
breastfed infants today (Arcus-Arth et al., 2005).
15.4.5 Kent et al., 2006 - Volume and Frequency
of Breastfeeding and Fat Content of Breast
Milk Throughout the Day
Kent et al. (2006) collected data from 71
Australian mothers who were exclusively nursing their
1 to 6 months old infants. The study focused on
examining the variation of milk consumed from each
breast, the degree of fullness of each breast before and
after feeding, and the fat content of milk consumed
from each breast during daytime and nighttime
feedings. The volume of milk was measured using test-
weighing procedures with no correction for infant
insensible water loss. On average, infants had 11 ± 3
breastfeedings per day (range= 6 to 18). The intervals
between feedings was 2 hours and 18 minutes ± 43
minutes (range = 4 minutes to 10 hours and 58
minutes). The 24-hour average human milk intake was
765 ± 164 mL/day (range = 464 to 1,317 mL/day). The
fat content of milk ranged from 22.3 g/L to 61.6 g/L
(2.2% - 6.0 %) with an average of 41.1 g/L (4.0%).
This study examined breastfeeding practices of
volunteer mothers in Australia. Although amounts of
milk consumed by Australian infants may be similar to
infants in the U.S. population, results could not be
broken out by smaller age groups to examine variability
with age. The study provides estimates of fat content
from a large number of samples.
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15.5 RELEVANT STUDY ON LIPID INTAKE
FROM HUMAN MILK
15.5.1 Maxwell and Burmaster, 1993 - A
Simulation Model to Estimate a
Distribution of Lipid Intake from Human
Milk During the First Year of Life
Maxwell and Burmaster (1993) used a
hypothetical population of 5000 infants between birth
and 1 year of age to simulate a distribution of daily
lipid intake from human milk. The hypothetical
population represented both bottle-fed and breast-fed
infants aged 1 to 365 days. A distribution of daily lipid
intake was developed, based on data in Dewey et al.
(1991b) on human milk intake for infants at 3, 6, 9, and
12 months and human milk lipid content, and survey
data in Ryan et al. (1991) on the percentage of
breast-fed infants under the age of 12 months (i.e.,
approximately 22%). A model was used to simulate
intake among 1113 of the 5000 infants that were
expected to be breast-fed. The results of the model
indicated that lipid intake among nursing infants under
12 months of age can be characterized by a normal
distribution with a mean of 26.0 mL/day and a standard
deviation of 7.2 mL/day (Table 15-24). The model
assumes that nursing infants are completely breast-fed
and does not account for infants who are breast-fed
longer than 1 year. Based on data collected by Dewey
et al. (1991b), Maxwell and Burmaster (1993)
estimated the lipid content of human milk to be 36.7
g/L at 3 months (35.6 mg/g or 3.6%), 39.2 g/L at 6
months (38.1 mg/g or 3.8%), 41.6 g/L at 9 months (40.4
mg/g or 4.0%), and 40.2 g/L at 12 months (39.0 mg/g
or 3.9%).
The limitation of this study is that it provides
a "snapshot" of daily lipid intake from human milk for
breast-fed infants. These results are also based on a
simulation model and there are uncertainties associated
with the assumptions made. Another limitation is that
lipid intake was not derived for the EPA recommended
age categories. The estimated mean lipid intake rate
represents the average daily intake for nursing infants
under 12 months of age. The study did not generate
"new" data. A reanalysis of previously reported data
on human milk intake and human milk lipid intake were
provided.
15.6 OTHER FACTORS
There are many factors that influence the
initiation, continuation, and amount of human milk
intake. These factors are complex and may include
considerations such as: maternal nutritional status,
parity, parental involvement, support from lactation
consultants, mother's working status, infant's age,
weight, gender, food supplementation, the frequency of
breast-feeding sessions per day, the duration of breast-
feeding per event, the duration of breast-feeding during
childhood, ethnicity, geographic area, and other
socioeconomic factors. For example, a study conducted
in the United Kingdom found that social and
educational factors most influenced the initiation and
continuation of lactation (Wright et al. 2006). Prenatal
and postnatal lactation consultant intervention was
found to be effective in increasing lactation duration
and intensity (Bonuck et al. 2005).
15.6.1 Population of Nursing Infants
To monitor progress towards achieving the
CDC Healthy People 2010 breastfeeding objectives
(initiation and duration), Scanlon et al. (2007) analyzed
data from the National Immunization Survey (NIS).
NIS uses random-digit dialing to survey households to
survey age eligible children, followed by a mail survey
to eligible children's vaccination providers to validate
the vaccination information. NIS is conduced annually
by the CDC to obtain national, state, and selected urban
area estimation on vaccinations rates among U.S.
children age 19-35 months. The interview response
rate for years 2001-2006 ranged between 64.5% and
76.1%. Questions regarding breastfeeding were added
to the NIS survey in 2001. The sample population was
infants born during 2000-2004. Scanlon et al. (2007),
noted that because data in their analysis are for children
aged 19-35 months at the time of the NIS interview,
each cross-sectional survey includes children from birth
cohorts that span 3 calendar years; the breastfeeding
data were analyzed by year of birth during 2000-2004
(birth year cohort instead if survey year).
Among infants born in 2000, breastfeeding
rates were 70.9% (CI= 69.0-72.8) for the postpartum
period (in hospital before discharge), 34.2% (CI= 32.2-
36.2) at 6 months, and 15.7 (CI= 14.2-17.2) at 12
months. For infants born in 2004, these rates had
increased to 73.8% (CI= 72.8-74.8) for the postpartum
period, 41.5% (CI= 40.4-42.6) at 6 months, and 20.9
(CI= 20.0-21.8) at 12 months. Rates of breastfeeding
through 3 months were lowest among black infants
(19.8%), infants whose mothers were <20 years of age
(16.8%), those whose mothers had a high school
education or less (22.9% and 23.9%), those whose
mothers were unmarried (18.8%), those who resided in
rural areas (23.9%), and those whose families had an
income-to-poverty ratio of <100% (23.9%). Table 15-
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25 provides data for exclusive breastfeeding through 3
and 6 months by socioeconomic characteristics for
infants born in 2004.
Scanlon et al. (2007) noted the following
limitations that could affect the utility of these data: (1)
breastfeeding behavior was based on retrospective self-
report by mothers or other caregivers, whose responses
might be subject to recall bias, (2) the NIS question that
defines early postpartum breastfeeding or initiation,
"Was [child's name] ever breastfed or fed breast milk?"
collects information that might differ from the HP2010
objective for initiation, and (3) although survey data
were weighted to make them representative of all U.S.
children aged 19-35 months, some bias might remain.
The advantage of the study is that is representative of
the U.S. infant population.
The rate of breastfeeding initiation in the
United States is near the national goal of 75%
established in Healthy People 2010 (Ruowei et al.
2005). Using the data obtained from the NIS survey
conducted throughout 2002 for children who were 19 to
35 months old, Ruowi et al. (2005) shows that overall,
71.4% of children surveyed had ever been breastfed.
The percentage of children who are breastfed drops to
35.1% at 6 months and to 16.1% at 12 months (Rouwei
et al. 2005). These data also revealed significant
differences in breastfeeding participation related to
race/ethnicity, day care and WIC participation, maternal
age, socioeconomic status, and geographical area.
Overall, 51.5% of mothers of non-Hispanic black
children reported to ever breastfed their infants
compared to 72.1% of mothers of non-Hispanic white
children. Non-Hispanic black infants were exclusively
breastfed at 6 months at a rate of 5.4% compared to
14.6% of non-Hispanic white infants and 13.8% of
Hispanic infants. Infants who attended day care and
infants whose mothers received WIC benefits were less
likely to have ever been breastfed. Mothers with higher
socioeconomic status and older mothers were more
likely to have ever breastfed their infants.
CDC (2007) developed the breastfeeding
report card. The CDC National Immunization Program
in partnership with the CDC National Center for Health
Statistics, conducts the NIS within all 50 states, District
of Columbia, and selected geographic areas within the
states. Five breastfeeding goals are in the Healthy
People 2010 report. The Breastfeeding Report Card
presents data for each state for the following categories
of infants: ever breastfed, breastfed at 6 months,
breastfed at 12 months, exclusive breastfeeding through
3 month, and exclusive breastfeeding through 6 months.
These indicators are used to measure a state's ability to
promote, protect, and support breastfeeding. These data
for the estimated percentage of infants born in 2004 are
presented in Table 15-26. The weighted sample
number is 17,654 for the U.S. population. The
advantage of this report is that it provides data for each
state and is representative of the U.S. infant population.
Analysis of breastfeeding practices in other
developing countries was also found in the literature.
Marriott et al. (2007) researched feeding practices in
developing countries in the first year of life, based on
24-hour recall data. Marriott et al. (2007), used
secondary data from the Demographic and Health
Surveys (DHS) for more than 35,000 infants in twenty
countries. This survey has conducted since 1986 and
was expanded to provide a standardized survey
instrument that can be used by developing countries to
collect data on maternal/infant health, intake and
household variables and to build national health
statistics (Marriott et al., 2007). The analysis was
based on the responses of the survey mothers for
questions on whether they were currently breasfeeding
and had fed other liquids and solid foods to their infants
in the previous 24 hours. The data incorporated were
from between 1999 and 2003. Marriott et al. (2007)
selected the youngest child less than 1 year old in each
of the families; multiples were included such as twins
or triplets. Separate analyses were conducted for
infants less than 6 months old and infants 6 months and
older, but less than 12 months old. Food and liquid
variables other than water and infant formulas were
collapsed into broader food categories for cross-country
comparisons (Marriott et al., 2007). Tinned, powdered,
and any other specified animal milks were collapsed. In
addition, all other liquids such as herbal teas, fruit
juices, and sugar water (excluding unique country-
specific liquids) were collapsed into other liquids and
the 10 types of solid food groups into an any-solid-
foods category (Marriott et al., 2007). Data were
pooled from the 20 countries to provide a large sample
size and increase statistical power. Tables 15-27 and
15-28 present the percentage of mothers that were
currently breastfeeding and separately had fed their
infants other liquids or solid food by age groups. Table
15-29 presents the pooled data summary for the study
period. The current breastfeeding was consistent across
countries for both age groups; the countries that
reported the highest percentages of current
breastfeeding for the 0 to 6 months old infants also
reported the highest percentages in the 6 to 12 month
old infants. Pooled data show that 96.6% of the 0 to 6
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months old infants and 87.9% of the 6 to 12 month old
infants were breastfeeding. Feeding of other fluids was
lowest in the 0 to 6 months infants, with the percentage
feeding water the highest of this category. The
percentage of mothers feeding commercial infant
formulas was the lowest in most countries.
There are other older studies that analyze
ethnic and racial differences in breastfeeding practices.
Li and Grummer-Strawn (2002) investigated ethnic and
racial disparities in lactation in the United States using
data from the Third National Health and Nutrition
Examinations Survey (NHANES III) that was
conducted between 1988-1994. NHANES II
participants were ages 2 months and older. The data
were collected during a home interview from a parent
or a proxy respondent for the child (Li and Grummer-
Strawn, 2002). The sample population consisted of
children 12 to 71 months of age at time of interview.
The NHANES III response rate for children
participating was approximately 94 percent (Li and
Grummer-Strawn, 2002). Data for a total of 2,863
exclusively breastfed, 6,140 ever breastfed, and 6,123
continued breastfed children were included in the
analysis (Li and Grummer-Strawn, 2002). The
proportion of children ever-breastfed was 60% among
non-Hispanic whites, 26% among non-Hispanic blacks,
and 54% among Mexican Americans. This number
decreased to 27, 9, and 23 respectively by 6 months.
Children fed exclusively human milk at 4 months was
also significantly lower for blacks at 8.5%, compared to
22.6% for whites and 14.1% for Mexican-Americans.
The racial and ethnic differences in proportion of
children ever breastfed is presented in Table 15-30, the
proportion of children who received any breast milk at
6 months are presented in Table 15-31, and the
proportion of children exclusively breastfed at 4 months
is presented in Table 15-32.
Li and Grummer-Strawn (2002) noted that
there may have been some lag time between birth and
the time of the interview. This may have caused
misclassification if the predicator variables changed
considerably between birth and the time of interview.
Also, NHANES III did not collect information on
maternal education. Instead, the educational level of
household head was used as a proxy. The advantages
of this study is that it is representative of the U.S.
children's population.
Data from some older studies provide
historical information on breastfeeding practices in the
U.S. These data are provided here to show trends in the
U.S. population. In 1991, the National Academy of
Sciences (NAS) reported that the percentage of
breast-feeding women has changed dramatically over
the years (NAS, 1991). The Ross Products Division of
Abbott Laboratories conducted a large national mail
survey in 1995 to determine patterns of breastfeeding
during the first 6 months of life. The Ross Laboratory
Mothers's Survey was first developed in 1955 and has
been expanded to include many more infants. Before
1991, the survey was conducted on a quarterly basis,
and approximately 40,000 to 50,000 questionnaires
were mailed each quarter (Ryan, 1997). Beginning in
1991, the survey was conducted monthly; 35,000
questionnaires were mailed each month. Over time, the
response rate has been consistently in the range of 50 ±
5%. In 1989 and 1995, 196,000 and 720,000
questionnaires were mailed, respectively. Ryan (1997)
reported rates of breast-feeding through 1995 and
compared them with those in 1989.
The survey demonstrates increases in both the
initiation of breast-feeding and continued breast-
feeding at 6 months of age between 1989 and 1991.
Table 15-33 presents the percent of breast-feeding in
hospitals and at 6 months of age by selected
demographic characteristics. In 1995, the incidence of
breast-feeding at birth and at 6 months for all infants
was approximately 59.7% and 21.6 %, respectively.
The largest increases in the initiation of breast-feeding
between 1989 and 1995 occurred among women who
were Black, were less than 20 years of age, earned less
than $10,000 per year, had no more than a grade school
education, were living in the South Atlantic region of
the U.S., had infants of low birth weight, were
employed full time outside the home at the time they
received the survey, and participated in the Women,
Infants, and Children program (WIC). In 1995, as in
1989, the initiation of breast-feeding was highest
among women who were greater than 35 years of age,
earned more than $25,000 per year, and were college
educated, did not participate in the WIC program, and
were living in the Mountain and Pacific regions of the
U.S.
Data on the actual length of time that infants
continue to breast-feed beyond 5 or 6 months were
limited (NAS, 1991). However, Maxwell and
Burmaster (1993) estimated that approximately 22
percent of infants under 1 year of age are breast-fed.
This estimate was based on a reanalysis of survey data
in Ryan et al. (1991) collected by Ross Laboratories
(Maxwell and Burmaster, 1993). Studies have also
indicated that breast-feeding practices may differ
among ethnic and socioeconomic groups and among
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regions of the United States. More recently, the Ross
Products Division of Abbott Laboratories reported the
results of their ongoing "Ross Mothers Survey" in 2003
(Abbott 2003). The percentages of mothers who breast
feed, based on ethnic background and demographic
variables, are presented in Table 15-34. These data
update the values presented in the NAS 1991 report.
15.6.2 Intake Rates Based on Nutritional Status
Information on differences in the quality and
quantity of human milk on the basis of ethnic or
socioeconomic characteristics of the population is
limited. Lonnerdal et al. (1976) studied human milk
volume and composition (nitrogen, lactose, proteins)
among underprivileged and privileged Ethiopian
mothers. No significant differences were observed
between the data for these two groups. Similar data
were observed for well-nourished Swedish mothers.
Lonnerdal et al. (1976) stated that these results indicate
that human milk quality and quantity are not affected by
maternal malnutrition. However, Brown et al. (1986a,
b) noted that the lactational capacity and energy
concentration of marginally-nourished women in
Bangladesh were "modestly less than in better
nourished mothers." Human milk intake rates for
infants of marginally-nourished women in this study
were 690 ± 122 g/day at 3 months, 722 ± 105 g/day at
6 months, and 719 ± 119 g/day at 9 months of age
(Brown et al., 1986a). Brown et al. (1986a) observed
that human milk from women with larger measurements
of arm circumference and triceps skinfold thickness had
higher concentrations of fat and energy than mothers
with less body fat. Positive correlations between
maternal weight and milk fat concentrations were also
observed. These results suggest that milk composition
may be affected by maternal nutritional status.
15.6.3 Frequency and Duration of Feeding
Hofvander et al. (1982) reported on the
frequency of feeding among 25 bottle-fed and 25
breast-fed infants at ages 1, 2, and 3 months. The mean
number of meals for these age groups was
approximately 5 meals/day (Table 15-35). Neville etal.
(1988) reported slightly higher mean feeding
frequencies. The mean number of meals per day for
exclusively breast-fed infants was 7.3 at ages 2 to 5
months and 8.2 at ages 2 weeks to 1 month. Neville et
al. (1988) reported that, for infants between the ages of
1 week and 5 months, the average duration of a
breastfeeding session is 16-18 minutes.
Buckley (2001) studied the breastfeeding
patterns, dietary intake, and growth measurement of
children who continued to breastfeed beyond 1 year of
age. The sample was 38 mother-child pairs living in
the Washington, DC area. The criteria for inclusion in
the study were that infants or their mothers had no
hospitalization of either subject 3 months prior to the
study and that the mother was currently breastfeeding
a 1-year old or older child (Buckley, 2001). The
participants were recruited through local medical
consultants and the La Leche League members. The
children selected as the final study subjects consisted of
22 boys and 16 girls with ages ranging from 12 to 43
month old. The data were collected using a 7-day
breastfeeding diary. The frequency and length of
breastfeeding varied with the age of the child (Buckley,
2001). The author noted a statistically significant
difference in the mean number of breastfeeding
episodes per day and the average total minutes of
breastfeeding between the 1, 2, and 3 year old groups.
Table 15-36 provides the comparison of breastfeeding
patterns between age groups. An advantage of this
study is that the frequency and duration data are based
primarily on a 7-day diary and some dietary recall.
Limitations of the study are the small sample size and
that it is limited to one geographical area.
15.7 REFERENCES FOR CHAPTER 15
AAP (2005) Breast feeding and the use of human
milk. Policy Statement. Pediatrics. 115(2):
496-506. available on line at
http://aappolicy.aappublications.org/cgi/cont
ent/full/pediatrics; 115/2/496
Abbott Laboratories (2003) Breastfeeding Trends -
2003. Ross Mothers Survey, Ross Products
Division,Columbus, OH.
Albernaz, E.;Victora, C.G.; Haisma, H.; Wright, A.;
Coward, W.A. (2003) Lactation counseling
increases breast-feeding duration but not
breastmilk intake as measured by isotopic
methods. J Nutr. 133: 205-210.
Arcus-Arth, A.; Krowech, G.; Zeise, L. (2005)
Human milk and Lipid Intake Distributions
for assessing Cumulative Exposure and
Risk. J Expos Anal Environ Epidemiol. 15:
357-365.
Bonuck, K.A.; Trombley, M.; Freeman, K.; Mckee,
D. (2005) Randomized, controlled trial of a
prenatal and postnatal lactation consultant
intervention on duration and intensity of
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
breastfeeding up to 12 months. Pediatrics.
116: 1413-1426.
Brown, K.H.; Akhtar, N.A.; Robertson, A.D.;
Ahmed, M.G. (1986a) Lactational capacity
of marginally nourished mothers:
relationships between maternal nutritional
status and quantity and proximate
composition of milk. Pediatrics. 78: 909-
919.
Brown, K.H.; Robertson, A.D.; Akhtar, N.A.
(1986b) Lactational capacity of marginally
nourished mothers: infants' milk nutrient
consumption and patterns of growth.
Pediatrics. 78: 920-927.
Butte, N.F.; Garza, C.; Smith, E.O.; Nichols, B.L.
(1984) Human milk intake and growth in
exclusively breast-fed infants. J Pediatr.
104:187-195.
Butte, N.; Wong, W.; Hopkinson, J.; Smith E.; Ellis,
J. (2000) Infant feeding mode affects early
growth and body composition. Pediatrics.
106; 1355-1366.
Buckley, K. (2001) Long-term breastfeeding:
nourishment or nurtance. J Hum Lactat.
17(4):304-311.
CDC. (2007) Breastfeeding report card 2007.
Breastfeeding practices-results from the
National Immunization Survey. Available
on line at
http://www.cdc.gov/breastfeeding/data
Chen, A.; Rogan, W.J. (2004) Breastfeeding and the
risk of postneonatal death in the United
States. Pediatrics. 113:435-439.
Dewey, K.G.; Lonnerdal, B. (1983) Milk and
nutrient intake of breast-fed infants from 1
to 6 months:relation to growth and fatness. J
Pediatr Gastroenterol Nutr. 2:497-506.
Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lonnerdal,
B. (199la) Maternal versus infant factors
related to human milk intake and residual
volume: the DARLING study. Pediatrics.
87:829-837.
Dewey, K.G.; Heinig, J.; Nommsen, L.; Lonnerdal,
B. (1991b) Adequacy of energy intake
among breast-fed infants in the DARLING
study: relationships to growth, velocity,
morbidity, and activity levels. J Pediatr.
119:538-547.
Dewey, K.G.; Peerson, J.M.; Heinig, M.J.;
Nommsen, L.A.; Lonnerdal, B. (1992)
Growth patterns of breast-fed infants in
affluent (United States) and poor (Peru)
communities: implications for timing of
complementary feeding. Am J Clin Nutr.
56: 1012-1018.
Drewett, R.; Amatayakul, K.; Wongsawasdii, L.;
Mangklabruks, A.; Ruckpaopunt, S.;
Ruangyuttikarn, C.; Baum, D., Imong, S.;
Jackson, D.; Woolridge, M. (1993) Nursing
frequency and the energy intake from breast
milk and supplementary food in a rural Thai
population: a longitudinal study. Eur J Clin
Nutr. 47: 880-891.
Ferris, A.M.; Neubauer, S.H.; Bendel, R.B.; Green,
K.W.; Ingardia, C.J.; Reece, E.A. (1993)
Perinatal lactation protocol and outcome in
mothers with and without insulin-dependent
diabetes mellitus. Am J Clin Nutr. 58:
43-48.
Gonzalez-Cossio,T.; Habicht, J.P.; Rasmussen, K.M.;
Delgado, H.L. (1998) Impact of food
supplementation during lactation on infant
breast-milk intake and on the proportion of
infants exclusively breast-fed. J Nutr.
128:1692-1702.
Hofvander, Y.; Hagman, U.; Hillervik, C.; Siolin, S.
(1982) The amount of milk consumed by 1-3
months old breast or bottled-fed infants.
Acta Paediatrica Scand. 71: 953-958.
Kent, J.C.; Mitoulas, L.R.; Cregan, M.D.; Ramsay,
D.T.; Doherty, D.A.; Hartmann, P.E. (2006)
Volume and frequency of breastfeeding and
fat content of breast milk throughout the
day. Pediatrics. 117:387-395.
Li, R.; Grummer-Strawn, L. (2002) Racial and
ethnic disparities in breastfeeding among
Unites States infants: third national health
and nutrition examination survey, 1988-
1994. Birth. 29(4):251-257.
Lonnerdal, B.; Forsum, E.; Gebre-Medhim, M.;
Hombraes, L. (1976) Human milk
composition in Ethiopian and Swedish
mothers: lactose, nitrogen, and protein
contents. Am J Clin Nutr. 29:1134-1141.
Marriott, M.; Campbell, L.; Hirsch, E.; and Wilson,
D. (2007) Preliminary data from
demographic and health surveys on infant
feeding in 20 developing countries. J. Nutr.
Vol 137: 518S-523S.
Maxwell, N.I.; Burmaster, D.E. (1993) A simulation
model to estimate a distribution of lipid
intake from human milk during the first year
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
of life. J Expo Anal Environ Epidemiol.
3:383-406.
Mitoulas, L.; Kent, J.; Cox, D.; Owens, R.; Sherriff,
J.; Hartman, P. (2002) Variation in fat,
lactose, and protein in human milk over 24 h
and throughout the first year of lactation. Br
JNutr. 88:29-37.
Mitoulas, L.; Gurrin, L.; Doherty, D.; Sherriff, J.;
Hartman, P. (2003) Infant intake of fatty
acids from human milk over the first year of
lactation. Br J Nutr. 90:979-986.
National Academy of Sciences (NAS). (1991)
Nutrition during lactation. Washington, DC.
National Academy Press.
Neubauer, S. H.; Ferris, A.M.; Chase, C.G.; Fanelli
J., Thompson, C.A.; Lammi-Keefe, C.J.;
Clark, R. M.; Jensen, R. G.; Bendel, R. B.;
Green, K. W. (1993) Delayed lactogenesis
in women with insulin-dependent diabetes
mellitus. Am J Clin Nutr. 1993: 58:54-60.
Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.;
Neifert, M.; et al. (1988) Studies in human
lactation: milk volumes in lactating women
during the onset of lactation and full
lactation. Am J Clin Nutr. 48:1375-1386.
Pao, E.M.; Hines, J.M.; Roche, A.F. (1980) Milk
intakes and feeding patterns of breast-fed
infants. J Am Diet Assoc. 77:540-545.
Ryan, A.S.; Rush, D.; Krieger, F.W.; Lewandowski,
G.E. (1991) Recent declines in
breastfeeding in the United States, 1984-
1989. Pediatrics. 88:719-727.
Ryan, A.S. (1997) The resurgence of breastfeeding
in the United States. Pediatrics. 99(4):el2.
http: //www .p ediatric s .org/c q i/c ontent/full/9 9
/4/el2.
Salmenpera, L.; Perheentupa, J.,; Siimes, M.A.
(1985) Exclusively breast-fed healthy infants
grow slower than reference infants. Pediatr
Res. 19: 307-312.
Scanlon, K.S.; Grummer-Strawn, L.; Shealy, K.R.;
Jefferds, M.E.; Chen, J.; Singleton, J.A..
(2007) Breastfeeding Trends and Updated
National Health Objectives for Exclusive
Breastfeeding - United States, Birth Years
2000-2004. MMWR56(30):760-763.
Stuff I.E.; Nichols B.L. (1989) Nutrient intake and
growth performance of older infants fed
human milk. J Pediatr. 1989: 115:959-968.
Wright, C.M.; Parkinson, K.; Scott, J. (2006) Breast-
feeding in a UK urban context: who breast-
feeds, for how long and does it matter?
Public Health Nutr. 9(6):686-691.
Child-Specific Exposure Factors Handbook
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Chapter 15 - Human Milk Intake
Table 15-7. Daily Intakes of Human Milk
Intake
Age
Completely Breast-fed
1 month
3 months
6 months
Partially Breast-fed
1 month
3 months
6 months
9 months
" Data expressed as mean
Source: Pao et al., 1980.
Number of Infants
11
2
1
4
11
6
3
± standard deviation.
Mean ± SD
(mL/day) *
600 ±159
833
682
485 ± 79
467 ± 100
395 ± 175
<554
Intake Range
(mL/day)
426 - 989
645 - 1,000
616-786
398 - 655
242 - 698
147 - 684
451 -732
Table 15-8. Human Milk Intakes for Infants Aged 1 to 6 Months
Intake
Age
1 month
2 months
3 months
4 months
5 months
6 months
Source: Dewey and Lonnerdal,
Number of Infants
16
19
16
13
11
11
1983.
Mean ± SD
(mL/day)
673 ± 192
756 ±170
782 ±172
810 ±142
805 ±117
896 ±122
Intake Range
(mL/day)
341-1,003
449-1,055
492-1,053
593-1,045
554-1,045
675-1,096
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Chapter 15 - Human Milk Intake
Table 15-9. Human Milk Intake Among Exclusively Breast-fed Infants During
1
2
3
4
Age
month
months
months
months
Number of
Infants
37
40
37
41
* Values reported by the
dividing by 1 .03 g/mL
SD
Intake (mL/day)a
Mean ± SD
729 ±126
704 ±127
702±111
718 ±124
Intake (mL/kg-day)a
Mean ± SD
154 ±23
125 ±18
114±19
108 ±17
author in units of g/day and g/kg-day were converted to
(density of human milk).
Calculated by dividing human milk intake (g/day) by
= Standard deviation.
Source: Butte et
al, 1984.
the First 4 Months
Feedings/Day
8.3 ±1.9
7.2 ±1.9
6.8 ±1.9
6.7 ±1.8
of Life
Body
Weight"
(kg)
4.7
5.6
6.2
6.7
units of mL/day and mL/kg-day by
human milk intake (g/kg-day).
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Age
(days)
1
2
3
4
5
6
7
8
9
10
11
14
21
28
35
42
49
56
90
120
150
180
210
240
270
300
330
360
b
SD
Source:
Table 15-10.
Human Milk Intake During a 24-hour Period
Intake ( mL/day )a
Number ol Infants
6
9
10
10
11
9
7
8
9
9
8
9
10
13
12
12
10
12
10
12
12
13
12
9
12
11
8
8
Mean ± SD
43 ±68
177 ± 83
360 ±149
438 ±171
483 ±125
493 ±162
556 ±162
564 ±154
563 ± 74
569 ±128
597 ±163
634 ±150
632 ± 82
748 ±174
649 ±114
690 ±108
688 ±112
674 ± 95
713±111
690 ± 97
814 ±130
744 ±117
700 ±150
604 ± 204
600 ±214
535 ±227
538 ±233
391 ±243
Range
-30-145 b
43-345
203-668
159-674
314-715
306-836
394-817
398-896
456-699
355-841
386-907
404-895
538-763
481-1,111
451-903
538-870
543-895
540-834
595-915
553-822
668-1,139
493-909
472-935
280-973
217-846
125-868
117-835
63-748
Intake by Age Category
(mL/day)a'°
511 ±220
679 ±105
713±111
690 ± 97
814 ±130
744 ±117
700 ±150
604 ± 204
600 ±214
535 ±227
538 ±233
391 ±243
Values reported by the author in units of g/day were converted to units of mL/day by dividing by 1 .03 g/mL
(density of human milk).
Negative value due to insensible weight loss correction.
Multiple data sets were combined by producing simulated data sets fitting the known mean and SD for each
age, compositing the data sets to correspond to age groups of 0 to <1 month and 1 to <2 months, and
calculating new means and SD's on the composited data.
= Standard deviation.
Neville et al, 1988.
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-11
Age
3 months
6 months
9 months
12 months
. Human Milk Intake Estimated by the Darling Study
Number of Infants
73
60
50
42
a Values reported by the author in units of g/day were converted to
1 .03 g/mL (density of human milk).
SD = Standard deviation.
Source: Dewey et al, 1991b.
Intake (mL/day)
Mean ± SD
788 ±129
747 ±166
627 ±211
435 ± 244
units of mL/day by dividing by
Table 15-12.
Ethnicity (White, Black, Hispanic, Asian) (N)
Duration of Breastfeeding (days)
Duration of Formula Feeding (days)
Age at Introduction of Formula (months)
Age at Introduction of Solids (months)
Age at Introduction of Cow's Milk (months)
" Mean ± standard deviation.
N = Number of infants.
Source: Butte et al., 2000.
Mean Breastfed Infants Characteristics a
Boys (N=14)
10/1/2/1
315 ±152
184 ±153
6.2 ±2.9
5.0 ±1.5
13.1 ±3.1
Girls (N=26)
21/1/3/1
362 ±190
105 ±121
5.2 ±2.3
5.0 ±0.09
12.5 ±3.8
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-13. Mean Human Milk Intake of Breastfed Infants (mL/day)a
Age Group
3 months
6 months
12 months
24 months
a 3 -day average; values reported by the author
1 .03 g/mL (density of human milk); mean ±
N = Number of infants.
Source: Butte et al., 2000.
Boys Girls
790 ± 172 (N=14) 694 ± 108 (N=26)
576±266(N=12) 678 ±250 (N=18)
586 ±286 (N=2) 370± 260 (N=l 1)
in units of g/day were converted to units of mL/day by dividing by
standard deviation.
Table 15-14. Feeding Practices by Percent of Infants
Age
Infants
369
months months months
12
months
18
months
24
months
Percentage
Infants Still Breastfed
Breastfed Infants Given Formula
Formula-fed Infants Given Breast Milk
Use of Cow's Milk for Breastfed Infants
Use of Cow's Milk for Formula-fed Infants
100 80 58
0 40 48
100 100 94
8
28
38
30
47
65
67
25
10
6
82
89
5
2
0
88
92
Source: Butte et al., 2000.
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-15. Body Weight of Breastfed Infants"
0.5 months
3 months
6 months
9 months
12 months
1 8 months
24 months
Weight (kg)
Boys
3.9±0.4(n=14)
6.4±0.6(n=14)
8.1±0.8(n=14)
9.3±1.0(n=14)
10.1 ±1.1 (n=14)
11.6±1.2(n=14)
12.7±1.3(n=12)
Girls
3.7±0.5(n=19)
6.0±0.6(n=19)
7.5±0.6(n=18)
8.4±0.6(n=19)
9.2 ± 0.7(n=19)
10.7 ± 1.0 (n=19)
11.8 ±1.1 (n=19)
* Mean ± standard deviation.
N = Number of infants.
Source: Butte et al, 2000.
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-16. AAP Dataset Milk Intake
Age
7 days
14 days
30 days
60 days
90 days
120 days
150 days
180 days
210 days
270 days
360 days
b
SD
cv
N
Source:
Mean
(mL/kg day)a
143
156
150
144
127
112
100
101
75
72
47
SD
(mL/kg day)a
37
40
24
22
18
18
21
20
25
23
27
Rates
CV
0.26
0.26
0.16
0.15
0.14
0.16
0.21
0.20
0.33
0.32
0.57
at Different Ages
Skewness
Statistic"
0.598
-1.39
0.905
0.433
-0.168
0.696
-1.077
-1.860
-0.844
-0.184
0.874
N
10
9
25
25
108
57
26
39
8
57
42
Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by
dividing by 1.03 g/mL (density of human milk).
Statistic/SE: -2 < Statistic/SE < +2 suggests a normal distribution
= Standard deviation.
= Coefficient of variation.
= Number of infants.
Arcus-ArthetaL, 2005.
Page
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-17. Average
Averaging Period
AAP 0 to 6 months
Method 1
Method 2
AAP 0 to 12 months
Method 1
Method 2
EBFOto 12 months
General Pop.
0 to 6 months
Oto 12 months
Mean (SD)
126(21)
123 (7)
98 (22)
99(5)
110(21)
79
51
5
92
112
61
90
75
0
0
Daily Human
10
99
114
69
92
83
0
0
Milk Intake (mL/kg day) a
25
112
118
83
95
95
24
12
Population
50
126
123
98
99
110
92
49
Values reported by the author in units of g/kg-day were converted to
1 .03 g/mt (density of human milk).
Percentile
75 90 95 99
140 152 160 174
127 131 133 138
113 127 135 150
102 105 107 110
124 137 144 159
123 141 152 170
85 108 119 138
units of mL/kg-day by dividing by
Source: Arcus-Arth et al., 2005.
Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed Infants
Age
(months)
1
2
3
4
Number Lipid Content
of (mg/g)
Observations Mean ± SD
37 36.2 ±7. 5
40 34.4 ±6. 8
37 32.2 ±7. 8
41 34.8 ±10.8
Lipid
Content % a
3.6
3.4
3.2
3.5
a Percents calculated from lipid content reported in mg/g.
b Values reported by the author in units of g/day and g/kg-day were converted to
dividing by 1 .03 g/mL (density of human milk).
Source: Butte et al., 1984.
Lipid
Intake
(mL/day)b
Mean ± SD
27 ±8
24 ±7
23 ±7
25 ±8
Lipid
Intake
(mL/kg-day)b
Mean ± SD
5.7 ±1.7
4.3 ±1.2
3.7 ±1.2
3.7 ±1.3
units of mL/day and mL/kg-day by
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-19. Human Milk Production and
Age Grc
(month
1
2
4
6
9
12
1 to 12
Volume, per Breast
rap (mL/24h)
s)
Mean SE N
416 24 34
408 23 34
421 20 34
413 25 30
354 47 12
252 51 10
399 11 154
Fat
(g/L)
Mean SE
39.9 1.4
35.2 1.4
35.4 1.4
37.3 1.4
40.7 1.7
40.9 3.3
37.4 0.6
a Infants were completely breast-fed to 4
months.
SE
N
Source:
= Standard error.
= Number of infants.
Mitoulas et al, 2002.
N
34
34
32
28
12
10
150
Composition Over the First 12
Lactose
(g/L)
Mean SE
59.7 0.8
60.4 1.1
62.6 1.3
62.5 1.7
62.8 1.5
61.4 2.9
61.4 0.6
Vlonths of Lactation a
Protein
(g/L)
N
18
18
16
16
12
10
90
months and complementary
Mean
10.5
9.6
9.3
8.0
8.3
8.3
9.2
SE
0.4
0.4
0.4
0.4
0.5
0.6
0.2
N
18
18
18
16
12
10
92
Energy
(kJ/mL)
Mean
2.7
2.5
2.6
2.6
2.8
2.8
2.7
SE
0.06
0.06
0.09
0.09
0.09
0.14
0.04
N
18
18
16
16
12
10
90
solid food was introduced between 4-6
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content Over
First Year of Lactation a
AgeG
(monl
1
2
4
6
9
12
Itol2
Statistical
roup
N
5
5
5
5
5
5
30
Volume, Left
Breast (mL/day)
Mean
338
364
430
373
312
203
337
NS
SE
52
52
51
75
65
69
26
Volume, Right Breast
(mL/day)
Mean
475
427
482
437
365
302
414
NS
SE
69
42
58
56
94
85
28
Fat, Left Breast
(g/L)
Mean
38
31
32
33
43
40
36
0.004
SE
1.5
2.2
3.3
2.5
2.2
4.8
1.4
the
Fat, Right Breast
(g/L)
Mean
38
30
29
33
38
42
35
0.008
SE
2.6
2.9
2.6
2.5
3.3
5.0
1.5
significance: P
a Infants were completely breast-fed to 4
months.
SE
NS
P
Source:
months, and complementary
solid food was introduced between 4-6
= Standard error.
= No statistical
= Probability.
Mitoulas et al.,
difference.
2003.
Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-21. Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation (g/100 g total fatty acids)
1 month
Fatty Acid Mean SE
Medium-chain
Saturated
Odd-chain
Saturated
Long-chain
Saturated
Mono-
unsaturated
Trans-
Poly-
unsaturated
SE = Standard
14.2 0.4
0.9 0.01
34.1 0.3
37.5 0.2
2.0 0.08
12.7 0.2
error.
2 months 4 months 6 months 9 months 12 months
Mean SE Mean SE Mean SE Mean SE Mean SE
13.9 0.6 12.0 0.5 11.5 0.2 14.1 0.3 17.0 0.4
0.9 0.02 0.8 0.02 0.8 0.03 0.8 0.02 0.8 0.02
33.7 0.3 32.8 0.3 31.8 0.6 31.4 0.6 33.9 0.6
33.7 0.4 38.6 0.5 37.5 0.5 37.3 0.5 33.0 0.5
2.2 0.1 2.2 0.09 4.6 0.02 1.7 0.2 1.8 0.09
9.5 0.2 11.8 0.4 13.4 0.6 8.0 0.1 6.7 0.03
Source: Mitoulas et al., 2003.
Table 15-22. Comparison of Lipid Content Assumptions (mL/kg-day)a
Lipid Content Used in Mean Population Percentile
Calculation
5 10 25 50 75 90
Measured Lipid Content" 3.6 2.0 2.3 2.9 3.6 4.3 4.9
4% Lipid Content0 3.9 2.5 2.8 3.3 3.8 4.4 4.9
* Values reported by the author in units of g/kg-day were converted to units of mL/kg-day
1 .03 g/mL (density of human milk).
b Lipid intake derived from lipid content and milk intake measurements.
° Lipid intake derived using 4% lipid content value and milk intake.
Source: Arcus-Arth et al., 2005.
95 99
5.2 5.9
5.2 5.8
by dividing by
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Chapter 15 - Human Milk Intake
Table 15-23. Distribution of Average
AAP Infants 0 to 12 months
Mean
3.9
Daily Lipid
5
2.4
a Values reported by the author in units of g/kg-day
g/mL (density of human milk).
Source: Arcus-Arth et al., 2005.
Intake (mL/kg day) assuming 4% Milk
10 25
2.8 3.3
Population
50
3.9
Percentile
75
4.5
were converted to units of mL/kg-day
Lipid Content
90
5.1
by
95
5.4
dividing by 1
99
6.0
03
Table 15-24. Predicted Lipid Intakes for
Statistic
Number of Observations in Simulation
Minimum Lipid Intake
Maximum Lipid Intake
Arithmetic Mean Lipid Intake
Standard Deviation Lipid Intake
a Values reported by the author in units of g/day were
(density of human milk).
Source: Maxwell and Burmaster, 1993.
Breast-fed Infants Under 12 Months of Age
Value
1,113
1 .0 mL/daya
51.0mL/daya
26.0 mL/daya
7.2 mL/daya
converted to units of mL/day by dividing by 1 .03 g/mL
Child-Specific Exposure Factors Handbook Page
September 2008 15-33
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-25 Socio-economic Characteristics of Exclusively Breastfed Infants Born in 2004
Percent of Exclusive Breastfeeding Infants Through 3 and 6 Months
Characteristic
U.S. Overall (N=17,654)
%
30.5
3 months
95% CI
29.4-31.6
%
11.3
6 months
95% CI
10.5-12.1
Infant Sex
Male
Female"
30.7
30.3
29.1-32.3
28.7-31.9
10.8
11.7
9.8-11.8
10.5-12.9
Race/Ethnicity (child)
Hispanic
White, non-Hispanic"
Black, non-Hispanic
Asian, non-Hispanic
Other
30.8
33.0
19.8 b
30.6
29.3
28.3-33.3
31.6-34.4
17.0-22.6
25.0-36.2
24.9-33.7
11.5
11.8
7.3"
14.5
12.2
9.7-13.3
10.9-12.7
5.5-9.1
10.0-19.0
9.2-15.2
Maternal Age (years)
<20
20 to 29
>30"
16.8 b
26.2"
34.6
10.3-23.3
24.4-28.0
33.2-36.0
6.1"
8.4"
13.8
1.5-10.7
7.3-9.5
12.7-14.9
Household Head Education
350"
23.9"
26.6"
33.2"
37.7
21.6-26.2
23.8-29.4
30.9-35.5
35.7-39.7
8.3"
8.9"
11.8"
14.0
6.9-9.7
7.2-10.6
10.3-13.3
12.6-15.4
" Referent group.
b p<0.05 by chi-square test, compared with referent group.
N = Number of infants .
MSA = Metropolitan statistical area.
Source: Scanlon et al, 2007.
Page
15-34
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Tablel5-26. Geographic-specific Breastfeeding Percent Rates
Ever
State N
Breastfed
U.S. National 17,654 73.8
Alabama 310 52.1
Alaska 217 84.8
Arizona 543 83.5
Arkansas 200 59.2
California 1,702 83.8
Colorado 249 85.9
Connecticut 249 79.5
Delaware 213 63.6
Dist of Columbia 292 68.0
Florida 955 77.9
Georgia 582 68.2
Hawaii 221 81
Idaho 183 85.9
Illinois 561 72.5
Indiana 472 64.7
Iowa 193 74.2
Kansas 480 74.4
Kentucky 245 59.1
Louisiana 429 50.7
Maine 203 76.3
Maryland 512 71.0
Massachusetts 469 72.4
Michigan 604 63.4
Minnesota 202 80.9
Mississippi 287 50.2
Missouri 327 67.3
Montana 232 87.7
Nebraska 228 79.3
Nevada 281 79.7
New Hampshire 228 73.7
New Jersey 631 69.8
New Mexico 420 80.7
New York 533 73.8
North Carolina 220 72.0
North Dakota 285 73.1
Ohio 617 59.6
Oklahoma 280 67.1
Oregon 191 88.3
Pennsylvania 757 66.6
Rhode Island 291 69.1
South Carolina 314 67.4
South Dakota 315 71.1
Tennessee 671 71.2
Texas 1,439 75.4
Utah 190 84.5
Vermont 190 85.2
Virginia 259 79.1
Washington 615 88.4
West Virginia 224 59.3
Wisconsin 478 72.1
Wyoming 246 80.5
a Exclusive breastfeeding information
solids, no water, no other liquids. SE
Breastfed at 6
Months
41.5
25.4
60.9
46.5
23.2
52.9
42
44.6
35.7
40.0
37.5
38.0
50.5
49.0
40.9
34.6
44.9
42.2
26.4
19.2
46.6
40.2
42.1
36.4
46.5
23.3
32.5
53.8
47.6
45.6
48.7
45.1
41.2
50.0
34.2
45.1
33.3
29.6
56.4
35.2
31.2
30.0
40.5
32.6
37.3
55.6
55.3
49.8
56.6
26.8
39.6
42.9
is from the 2006 NIS
mple sizes appearing
Breastfed at
Months
20.9
11.5
31.8
23.4
8.5
30.4
23.6
23.7
14.6
21.4
15.6
16.8
35.5
22.6
17.6
18.0
20.0
16.9
14.4
8.3
27.6
21.2
19.0
18.6
23.8
8.2
15.8
28.8
21.8
21.9
27.5
19.4
21.1
26.9
18.3
19.5
12.9
12.7
33.5
16.8
14.0
11.1
23.4
16.6
18.7
28.1
34.1
25.6
32.3
14.0
19.0
18.5
survey data
Among Children Born in 2004 a
12 Exclusive Breastfeeding
Breastfeeding
Through 6 Months
Through 3 Months
30.5
19.3
47.2
38.8
15.8
38.7
36.2
35.6
26.3
27.8
27.8
25.6
37.8
38.7
31.6
28.3
37.6
30.0
25.3
15.2
42.1
32.1
32.7
27.4
33.9
19.0
26.6
50.9
31.7
31.9
34.3
27.0
32.9
26.0
23.0
39.4
27.2
23.0
41.5
27.1
31.2
26.6
32.2
26.7
25.2
39.8
47.3
32.6
49.6
21.3
32.5
36.2
only and is defined as
11.3
4.9
24.3
14.3
6.2
17.4
10.8
10.1
11.4
9.8
9.1
11
15.8
10.3
10
10.4
11.6
9.2
7.5
2.8
15.9
8.6
11.9
8.3
16.1
8
7.4
18.3
9.8
10.3
13.6
11.8
14.3
11.4
6.9
15.4
9.8
10.6
19.9
8
9.5
5.4
12.2
11.9
7.1
10.2
15.9
13.4
22.5
5.2
13.4
11.4
ONLY breast milk- No
in the NIS breastfeeding tables are slightly smaller than the
numbers published in other NIS publications due to the fact that in the DNPA breastfeeding
limited to records with valid responses to the breastfeedin
N - Number of infants.
Source: CDC, 2007.
g questions.
analyses, the sample was
Child-Specific Exposure Factors Handbook Page
September 2008 15-35
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0 to 6 Months Old a
Country
Ethiopia
Ghana
Kenya
Malarwi
Nambia
Nigeria
Uganda
Zamibia
Zimbabwe
Armenia
Egypt
Jordan
Bangladesh
Cambodia
India
Indonesia
Nepal
Philippines
Vietnam
Kazakhstan
Pooled
Breastfeeding
98.8
99.6
99.7
100
95.3
99.1
98.7
99.6
100
86.1
95.5
92.4
99.6
98.9
98.1
92.8
100
80.5
98.7
94.4
96.6
Water
26.3
41.9
60
46
65.4
78.2
15.1
52.6
63.9
62.7
22.9
58.5
30.2
87.9
40.2
37
23.3
53.4
45.9
53.7
45.9
Milk
19
6.7
35.1
1.4
0
9.2
20.3
2.1
1.6
22.9
11.1
3
13.6
2.1
21.2
0.7
12.3
4.4
16.9
21.4
11.9
Formula
0
3.5
4.8
1.7
0
12.7
1.5
2.7
3.2
13.1
4.3
25.1
5.3
3.3
0
24.2
0
30
0.8
8.2
9
a Percentage of mothers who stated that they currently breast-feed and separately
liquid or solid food in the past 24 hours by country for infants age 0 to 6 months
Source: Marriott et
al, 2007.
Other Liquids
10.8
4.3
35.9
5.2
17.9
17.9
10.3
6.7
9
48.1
27.6
13.8
19.7
6.7
7.1
8.7
2.8
12.4
8.9
37.4
15.1
had fed their infants 4
old.
Solid Foods
5.3
15.6
46.3
42.3
33.4
18.5
11.4
31.2
43.7
23.9
13.2
20.2
20.3
16.6
6.5
43
9.3
16.8
18.7
15.4
21.9
categories of
Page
15-36
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6 to 12 Months Old"
Country
Ethiopia
Ghana
Kenya
Malarwi
Nambia
Nigeria
Uganda
Zamibia
Zimbabwe
Armenia
Egypt
Jordan
Bangladesh
Cambodia
India
Indonesia
Nepal
Philippines
Vietnam
Kazakhstan
Pooled
Breastfeeding Water
99.4
99.3
96.5
99.4
78.7
97.8
97.4
99.5
96.7
53.4
89.1
65.7
96.2
94.4
94.9
84.8
98.8
64.4
93.2
81.2
87.9
69.2
88.8
77.7
93.5
91.9
91.6
65.9
91.7
92.5
91.1
85.9
99.3
87.7
97.5
81.4
85.4
84.3
95.1
95
74.3
87.4
Milk
37.6
14.6
58.7
5.9
0
14.4
32.1
8.2
8.7
56.9
36.8
24.3
29.8
3.7
45
4.9
32
12.2
36.1
85.4
29.6
Formula Other Liquids Solid Foods
0
9.6
6
3.2
0
13.4
1.6
5
2.4
11.6
16.7
28.8
10.1
6.7
0
38.8
0
47.1
5.3
11.4
15.1
23.9
23.9
56.4
31.2
42.7
27.4
56.2
25.9
49.9
85.3
48.5
57.7
21.9
29
25.2
35.4
15.8
31
37.9
91.8
41.6
a Percentage of mothers who stated that they currently breast-feed and separately had fed their infants 4
liquid or solid food in the past 24 hours by country for infants age 6 to 12 months old.
Source: Marriott et
al, 2007.
54.7
71.1
89.6
94.9
79.5
70.4
82.1
90.2
94.8
88.1
75.7
94.9
65.2
81
44.1
87.9
71.5
88
85.8
85.9
80.1
categories of
Child-Specific Exposure Factors Handbook
September 2008
Page
15-37
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-29. Population Weighted Averages of Mothers Who Reported
Selected Feeding Practices During the Previous 24-hours
Feeding Practices
Infant Age
0 to 6 months 6 to 12 months
Percentage (weighted N)
Current Breast-feeding
Gave Infant:
Water
Tinned, Powdered, or Other Milk
Commercial Formula
Other Liquids
Any Solid Food
N = Number of infants .
Source: Marriott et al, 2007.
96.6 (22,781) 87.9 (18,944)
45.9(10,767) 87.4(18,6663)
11.9(2,769) 29.6(6,283)
9.0(1,261) 15.1(1,911)
15.1(3,531) 41.6(8,902)
21.9(5,131) 80.1(17,119)
Page Child-Specific Exposure Factors Handbook
15-38 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III (1988-1994)
Absolute Difference (%,SE)"
Non-Hispanic White Non-Hispanic Black Mexican American White vs Black White vs Mexican
American
Characteristic N % (SE) N % (SE) N % (SE) % (SE) % (SE)
All infants 1,869 60.3 2.0 1,845 25.5 1.4 2,118 54.4 1.9 34.8 (2.0)b 6.0 (2.3)"
Infant sex
Male 901 60.4 2.6 913 24.4 1.6 1,033 53.8 1.8 35.9 (2.9)b 6.6 (2.8)"
Female 968 60.3 2.3 932 26.7 1.9 1,085 54.9 2.9 33.7 (2.6)b 5.4 (3.4)°
Infant birth weight (g)
118 40.1 5.3 221 14.9 2.6 165 34.1 3.9 25.1 (5.8)b 5.9 (6.4)°
1,738 62.1 2.1 1,584 26.8 1.6 1,838 55.7 2.0 35.3 (2.1)b 6.4 (2.5)"
Maternal age (years)
<20 175 33.7 4.4 380 13.1 2.1 381 43.7 3.0 20.6 (4.8)b -10 (5.1)°
20 to 24 464 48.3 3.0 559 22.0 2.0 649 54.8 2.6 26.4 (3.7)b -6.4 (4.2)°
25 to 29 651 65.4 2.2 504 30.6 2.5 624 56.9 3.3 34.8 (3.1)b 8.6 (4.0)"
>30 575 71.9 2.7 391 36.1 2.3 454 59.6 2.8 35.8 (3.4)b 12.3 (3.4)b
Household head education
30 204 48.6 4.8 415 24.3 2.7 359 47.1 4.4 24.3 (5.3)b 1.5 (6.1)°
Residence
Metropolitan 762 67.2 3.0 943 32.0 1.9 1,384 56.1 2.0 35.3 (2.6)b 11.2 (2.9)b
Rural 1,107 54.9 3.1 902 18.3 1.9 734 51.3 3.1 36.6 (2.7)b 3.6 (4.0)°
Region
Northeast 317 51.6 4.6 258 34.2 4.4 12 74.1 10.4 17.3 (3.6)b -22.5 (14.5)c
Midwest 556 61.7 2.3 346 26.5 2.4 170 51.5 3.7 35.2 (3.3)b 10.2 (5.0)"
South 748 52.7 2.7 1,074 19.4 2.0 694 42.7 3.5 33.3 (2.7)b 10 (4.6)"
West 248 82.4 3.9 167 45.1 5.1 1,242 59.1 2.2 37.3 (7.1)b 23.4 (3.3)b
Poverty income ratio (%)
<100 257 38.5 4.2 905 18.2 1.9 986 48.2 2.8 20.3 (4.4)b -9.6 (4.7)"
100to<185 388 55.7 2.6 391 26.8 2.1 490 54.1 3.4 28.9 (3.5)b 1.5 (4.2)°
185to<350 672 61.9 2.5 294 32.0 3.0 288 64.7 4.7 30.0 (3.7)b 2.8 (5.3)=
>350 444 77.0 2.5 105 58.1 5.1 74 71.9 9.0 19.0 (5.6)b 5.2 (9.0)°
Unknown 108 44.7 7.1 150 25.5 3.9 280 59.5 2.8 19.2 (7.9)" -14.8 (7.9)°
p<0.05.
p<0.01.
No statistical difference.
N - Number of infants.
SE - Standard error.
Source: Li and Grummer-Strawn, 2002.
Child-Specific Exposure Factors Handbook Page
September 2008 15-39
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-31. Racial and Ethnic Differences in Proportion of Children Who
Received Any Human Milk at 6 Months (NHANES III, 1988-1994)
Absolute Difference (%,SE)
Non-Hispanic White
Non-Hispanic Black
Mexican American
White vs Black White vs Mexican
American
Characteristic
(SE)
No.
(SE)
(SE)
(SE)
(SE)
All infants
1863
26.8
1.6
'112
23.1
1.4
18.3
(1.7)"
3.7
Infant sex
Male
Female
900
963
27.6
26.1
2.3
1.8
912
930
8.5
8.6
1.1 1,029
1.1 1,083
22.3
24.0
1.6
2.0
19.1
17.5
(2.6)b
(2.1)'
5.2
2.1
(2.6)'
(2.7)=
Infant birth weight (g)
<2,500
> 2,500
118
1,733
10.9
28.3
3.1
1.8
221
1,581
4.2
9.0
1.8
0.9
165
1,832
15.2
23.1
4.7
1.7
6.7
19.3
(3.3)'
-4.3
5.2
(5.7)=
(2.3)'
Maternal age (years)
<20
20 to 24
25 to 29
>30
174 10.2
461 13.4
651 29.3
573 39.0
2.9
2.4
2.6
2.6
380
559
503
389
4.7
7.5
10.9
10.7
1.4
1.1
2.0
1.7
380 11.6
646 23.8
624 24.6
452 30.0
1.7 5.5 (3.0)°
2.4 5.9 (2.5)'
2.6 18.4 (3.5)b
2.8 28.4 (3.3)b
-1.3 (3.8)°
-10.4 (3.3)b
4.8 (3.6)°
9.0 (3.6)"
Household head education
350
Unknown
387 23.5
670 30.4
443 33.0
108 13.3
2.9
2.7
3.0
3.8
390
293
105
149
9.9
10.0
15.2
6.4
1.8
2.4
2.8
2.9
486 23.4
287 27.6
74 32.3
280 26.7
2.7
4.4
9.0
4.5
13.6 (3.9)b
20.4 (4.0)b
17.8 (4.2)b
7.0
(5.3)=
0 (4.1)=
2.9 (4.8)=
0.7 (9.5)=
-13.4 (6.6)'
p<0.05.
p<0.01.
N
SE
Source:
No statistical difference.
- Number of individuals.
- Standard error.
Li and Grummer-Strawn, 2002.
Page
15-40
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-32.
Racial and Ethnic Differences in Proportion of Children Exclusively
Breastfed at 4 Months (NHANES III, 1991-1994)
Non-Hispanic White
Characteristic N
All infants 824
%
22.6
(SE)
1.7
Non-Hispanic Black
N
906
%
8.5
(SE)
1.5
Mex
N
957
can Amer
%
20.4
Absolute Difference (%,SE)
lean White
(SE) %
1.4 14.1
vs Black
(SE)
(2.2)b
White vs Mexican
American
%
2.3
(SE)
(1.6)=
Infant sex
Male 394
Female 430
22.3
23.0
1.9
2.2
454
452
7.0
10.0
1.6
2.2
498
459
20.7
20.0
1.5 15.3
1.8 12.9
(2.6)b
(3.0)b
1.5
3.0
(1.8)=
(2.1)=
Infant birth weight (g)
<2500 50
>2500 774
15.2
23.1
7.1
1.8
118
786
7.0
8.8
2.3
1.6
66
880
5.6
21.6
1.8 8.2
1.4 14.4
(8.1)=
(2.2)b
9.5
1.5
(6.9)=
(1.6)=
Maternal age (years)
<20 76
20 to 24 205
25 to 29 271
>30 27°
6.6
11.4
21.6
34.8
3.2
2.2
2.3
2.7
172
273
254
201
6.4
7.4
8.6
11.9
2.1
2.4
2.5
2.6
170
319
256
210
12.1
21.0
22.1
23.6
2.5 0.2
2.3 4.0
2.5 13.0
3.1 22.9
(3.7)=
(2.7)=
(3.2)b
(4.2)b
-5.6
-9.6
-0.5
11.1
(3.8)=
(3.2)b
(3.2)=
(3.7)b
Household head education
30 91
24.8
19.7
15.4
2.1
4.3
3.8
407
230
230
8.0
8.6
9.0
1.9
1.9
2.9
417
261
184
19.4
23.1
15.9
1.9 16.8
3.4 11.1
2.3 6.4
(3.0)b
(4.6)"
(5.2)=
5.4
-3.4
-0.5
(2.3)"
(4.9)=
(4.6)=
Residence
Metropolitan 312
Rural 512
24.4
21.3
3
1.8
535
371
11.0
4.2
2.0
1.3
608
349
19.6
22.3
1.6 13.4
3.3 17.1
(3.5)b
4.8
-1.1
(2.8)=
(3.0)=
Region
Northeast 138
Midwest 231
South 378
West 77
20.0
26.5
14.1
34.7
1.4
3.2
2.8
2.7
131
143
574
58
11.1
12.6
5.9
12.5
2.9
5.6
1.4
5.0
10
98
383
466
9.4
19.2
15.9
23.0
9.5 8.8
4.1 13.9
3.1 8.2
1.3 22.2
(2.2)b
(7.6)=
(1.9)"
(5.4)b
10.6
7.4
-1.8
11.7
(8.7)=
(3.7)=
(3.7)=
(2.5)
Poverty income ratio (%)
<100 116
100to<185 166
185to<350 274
>350 235
Unknown 33
13.1
18.9
25.1
27.4
16.5
3.3
3.2
3.2
4.1
7.6
448
197
145
57
59
5.7
10.6
12.9
12.8
7.3
1.6
2.8
4.3
3.5
3.7
471
234
132
37
83
18.4
21.9
26.4
17.0
16.1
1.8 7.4
4.1 8.3
4.2 12.2
5.0 14.6
5.1 9.2
(3.5)"
(3.3)"
(5.0)"
(5.0)b
(8.6)=
-5.3
-3
-1.3
10.4
0.4
(3.1)=
(6.1)=
(4.1)=
(5.2)=
(9.5)=
p<0.05.
* p<0.01.
No statistical difference.
N - Number of individuals.
SE - Standard error.
Source: Li and Grummer-Strawn, 2002.
Child-Specific Exposure Factors Handbook
September 2008
Page
15-41
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-33. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6 Months of Age in
United States in 1989 and 1995, by Ethnic Background and Selected Demographic Variables
Characteristic
All Infants
White
Black
Hispanic
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Total Family Income
<$10,000
$10,000 to $14,999
$15,000 to $24,999
> 25,000
Maternal Education
Grade School
High School
College
Maternal Employment
Employed Full Time
Employed Part Time
Not Employed
Birth Weight
Low (< 2,500 g)
Normal
Parity
Primiparous
Multiparous
WIC Participation'
Participant
Nonparticipant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
the
Percentage of Mothers Breast-Feeding
In Hospital
1989
52.2
58.5
23.0
48.4
30.2
45.2
58.8
65.5
66.5
31.8
47.1
54.7
66.3
31.7
42.5
70.7
50.8
59.4
51.0
36.2
53.5
52.6
51.7
34.2
62.9
52.2
47.4
47.6
55.9
43.8
37.9
46.0
70.2
70.3
1995
59.7
64.3
37.0
61.0
42.8
52.6
63.1
68.1
70.0
41.8
51.7
58.8
70.7
43.8
49.7
74.4
60.7
63.5
58.0
47.7
60.5
61.6
57.8
46.6
71.0
61.2
53.8
54.6
61.9
54.8
44.1
54.4
75.1
75.1
Change"
14.4
9.9
60.9
26.0
41.7
16.4
7.3
4.0
5.3
31.4
9.8
7.5
6.6
38.2
16.9
5.2
19.5
6.9
13.7
31.8
13.1
17.1
11.8
36.3
12.9
17.2
13.5
14.7
10.7
25.1
16.4
18.3
7.0
6.8
The percent change was calculated using the following formula: % breastfed in 1984 - %
Figures in parentheses indicate a decrease in the rate of breastfeeding from 1989 to 1995.
0 WIC indicates Women
Source: Ryan, 1997.
1989
18.1
21.0
6.4
13.9
5.6
11.5
21.1
29.3
34.0
8.2
13.9
18.9
25.5
11.5
12.4
28.8
8.9
21.1
21.6
9.8
18.8
15.1
21.1
8.4
23.8
18.6
16.8
16.7
18.4
13.7
11.5
13.6
28.3
26.6
breastfed in
At 6 Months
1995
21.6
24.1
11.2
19.6
9.1
14.6
22.9
29.0
33.8
11.4
15.4
19.8
28.5
17.1
15.0
31.2
14.3
23.4
25.0
12.6
22.3
19.5
23.6
12.7
29.2
22.2
19.6
18.9
21.4
18.6
13.0
17.0
30.3
30.9
19897% breastfed in
Change"
19.3
14.8
75.0
41.0
62.5
27.0
8.5
(1.0)"
(0.6)b
39.0
10.8
4.8
11.8
48.7
21.0
8.3
60.7
10.9
15.7
28.6
18.6
29.1
11.8
51.2
22.7
19.4
16.7
13.2
16.3
35.8
13.0
25.0
7.1
16.2
1984.
, Infants, and Children supplemental food program.
Page Child-Specific Exposure Factors Handbook
15-42 September 2008
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-34. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 6 and 12
Months of Age in the United States in 2003, by Ethnic Background and Selected Demographic Variables
Characteristic
All Infants
White
Black
Hispanic
Asian
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Maternal Education
Any Grade School
Any High School
No College
College
Maternal Employment
Employed Full Time
Employed Part Time
Total Employed
Not Employed
Low Birth Weight <5 Ibs 9oz
Parity
Primiparous
Multiparous
WIC Participation"
Participant
Nonparticipant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
a WIC indicates Women, Infants,
Source: Abbott, 2003.
Percentage of Mothers Breast-Feeding
In Hospital At 6 Months
44
53
26
33
39
28
40
48
50
47
26
35
35
55
44
49
45
43
27
48
43
32
55
52
36
44
55
42
37
37
53
50
and Children supplemental
18
20
10
15
23
9
13
20
23
23
13
12
12
24
11
19
14
21
10
17
19
11
25
22
17
17
18
16
11
15
23
24
food program.
At 12 Months
10
12
5
12
12
4
8
10
14
14
17
8
8
14
6
11
8
13
6
10
11
7
14
11
9
9
9
10
7
8
16
15
Child-Specific Exposure Factors Handbook
September 2008
Page
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-35. Number of Meals Per Day
Age (months)
1
2
3
" Data expressed
Source: Hofvander et al
Bottle-fed Infants
(meals/day) "
5.4 (4-7)
4.8 (4-6)
4.7 (3-6)
as mean with range in parentheses.
, 1982.
Breast-fed
(meals/day) "
5.8 (5-7)
5.3 (5-7)
5.1 (4-8)
Table 15-36. Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD)
Breastfeeding Episodes per Day 5.8 ±2.6 6.8 ±2.4 2.5 ± 2.0
Total Time Breastfeeding (min/day) 65.2 ±44.0 102.2 ±51.4 31.2 ±24.6
Length of Breastfeeding (min/episode) 10.8 ±6.1 14.2 ±6.1 11.6±5.6
SD = Standard deviation
Source: Buckley, 2001.
Page Child-Specific Exposure Factors Handbook
15-44 September 2008
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
TABLE OF CONTENTS
16 ACTIVITY FACTORS 16-1
16.1 INTRODUCTION 16-1
16.2 RECOMMENDATIONS 16-1
16.3 ACTIVITY PATTERNS 16-7
16.3.1 KEY STUDIES 16-7
16.3.1.1 Wiley etal, 1991 16-7
16.3.1.2 U.S. EPA, 1996 16-8
16.3.2 RELEVANT STUDIES 16-9
16.3.2.1 Timmer et al., 1985 16-9
16.3.2.2 Robinson and Thomas, 1991 16-10
16.3.2.3 Funk etal., 1998 16-11
16.3.2.4 U.S. EPA, 2000 16-11
16.3.2.5 Hubal et al., 2000 16-12
16.3.2.6 Wong et al., 2000 16-12
16.3.2.7 Graham and McCurdy, 2004 16-13
16.3.2.8 Vandewater et al., 2004 16-14
16.3.2.9 Juster et al. (2004) 16-14
16.3.2.10 U.S. Department of Labor, 2007 16-14
16.3.2.11 Nader etal. 2008 16-15
16.4 REFERENCES FOR CHAPTER 16 16-15
Child-Specific Exposure Factors Handbook Page
September 2008 16-i
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
LIST OF TABLES
Table 16-1. Recommended Values for Activity Factors
Table 16-2. Confidence in Recommendations for Activity Factors
Table 16-3. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, for All Respondents and Doers
Table 16-4. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, by Age and Gender
Table 16-5. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
Categories, Grouped by Seasons and Regions
Table 16-6. Time (minutes/day) Children Under 12 Years of Age Spent in Six Major Location
Categories, for All Respondents and Doers
Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
Categories, Grouped by Age and Gender
Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
Categories, Grouped by Season and Region
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Proximity to Two Potential Sources of Exposure, Grouped by All Respondents,
Age, and Gender
Table 16-10. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
Grouped by Age and Gender
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only
Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations Whole Population
and Doers Only
Table 16-13. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population
and Doers Only
Table 16-14. Mean Time Spent (minutes/day) Inside and Outside, by Age Category
Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
Whole Population and Doers Only
Table 16-16. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only ....
Table 16-17. Number of Showers Taken per Day, by Number of Respondents
Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing
and Showering
Table 16-19. Range of Number of Times Washing the Hands at Specified Daily Frequencies by
the Number of Respondents
Table 16-20. Number of Times Swimming in a Month in Freshwater Swimming Pool by the
Number of Respondents
Table 16-21. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool
Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population
and Doers Only
Table 16-23. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air
Table 16-24. Time Spent (minutes/day) with Smokers Present
Table 16-25. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex
and Type of Day
. 16-3
. 16-6
16-17
16-18
16-19
16-20
16-21
16-22
16-23
16-24
16-25
16-29
16-31
16-33
16-34
16-36
16-40
16-41
16-43
16-44
16-45
16-46
16-48
16-48
16-49
Page
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
LIST OF TABLES (continued)
Table 16-26. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different
Age Groups 16-50
Table 16-27. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week 16-51
Table 16-28. Mean Time Spent (minutes/day) in Various Microenvironments, Children Ages 12 to
17 Years National and California Surveys 16-52
Table 16-29. Gender and Age Groups 16-53
Table 16-30. Assignment of At-Home Activities to Inhalation Rate Levels for Children 16-54
Table 16-31. Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents
and Children 16-55
Table 16-32. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents) 16-55
Table 16-33. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender and Age
for Children 16-56
Table 16-34. Number of Person-Days/Individuals for Children in CHAD Database 16-57
Table 16-35. Time Spent (hours/day) in Various Microenvironments, by Age 16-58
Table 16-36. Mean Time Children Spent (hours/day) Doing Various Macroactivities
While Indoors at Home 16-59
Table 16-37. Time Children Spent (hours/day) in Various Microenvironments, by Age
Recast into New Standard Age Categories 16-60
Table 16-38. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
Recast Into New Standard Age Categories 16-61
Table 16-39. Number and Percentage of Respondents with Children and Those Reporting
Outdoor Play Activities in both Warm and Cold Weather 16-62
Table 16-40. Play Frequency and Duration for all Child Players (from SCS-II data) 16-63
Table 16-41. Hand Washing and Bathing Frequency for all Child Players (from SCS-II data) 16-63
Table 16-42. NHAPS and SCS-II Play Duration Comparison 16-64
Table 16-43. NHAPS and SCS-II Hand Wash Frequency Comparison 16-64
Table 16-44. Time Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only) 16-65
Table 16-45. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Gender
and Age Cohort (Doers Only) 16-66
Table 16-46. Time Spent (minutes/day) Indoors Based on CHAD Data (Doers Only) 16-67
Table 16-47. Time Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only) 16-68
Table 16-48. Time Spent (minutes/two-day period) in Various Activities by Children Participating
in the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement
(CDS) 16-69
Table 16-49. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday 16-70
Table 16-50. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day . . 16-71
Table 16-51. Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to 1716-72
Table 16-52. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years 16-73
Table 16-53. Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity 16-74
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
16 ACTIVITY FACTORS
16.1 INTRODUCTION
As a consequence of a child's immaturity and
small stature, certain activities and behaviors specific
to children place them at higher risk to certain
environmental agents (Chance and Harmsen, 1998).
Individual or group activities are important
determinants of potential exposure, because toxic
chemicals introduced into the environment may not
cause harm to a child until an activity is performed
that subjects the child to contact with those
contaminants. An activity or time spent in a given
activity will vary among children on the basis of, for
example, culture, ethnicity, hobbies, location, gender,
age, socioeconomic characteristics, and personal
preferences. However, limited information is available
regarding ethnic, cultural and socioeconomic
differences in children's choice of activities or time
spent in a given activity.
It is difficult to accurately collect/record data for
a child's activity patterns (Hubal et al., 2000).
Children engage in more contact activities than adults;
therefore, a much wider distribution of activities need
to be considered when assessing children's exposure
(Hubal et al., 2000). Behavioral patterns, preferred
activities, and developmental stages result in different
exposures for children than for adults (Chance and
Harmsen, 1998). Other factors that may affect
children's activity patterns include: social status,
economics, and the cultural practices of their families.
This chapter summarizes data on how much
time children spend participating in various activities
in various microenvironments. Information on the
frequency of performing various activities is also
provided. The data in this chapter cover a wide range
of activities and populations, arranged by age group
when such data are available. One of the objectives of
this handbook is to provide recommended exposure
factor values using a consistent set of age groups. In
this chapter, several studies are used as sources for
activity pattern data. In some cases, the source data
could be retrieved and analyzed using the standard age
groupings recommended in Guidance for Monitoring
and Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005). In other cases, the
original source data were not available, and the study
results are presented here using the same age groups as
the original study, whether or not they conform to the
standard age groupings.
The recommendations for activity factors are
provided in the next section, along with a summary of
the confidence ratings for these recommendations.
The recommended values are based on key studies
identified by U.S. EPA for this factor. Following the
recommendations, key studies on activity patterns are
summarized. Relevant data on activity patterns are
also presented to provide the reader with added
perspective on the current state-of-knowledge
pertaining to activity patterns in children.
16.2 RECOMMENDATIONS
Assessors are commonly interested in
quantitative information describing several types of
time use data for children including: time spent
indoors and outdoors; time spent bathing, showering,
and swimming; and time spent playing on various
types of surfaces. The recommended values for these
factors are summarized in Table 16-1. Note that,
except for swimming, all activity factors are reported
in units of minutes/day. Time spent swimming is
reported in units of minutes/month. These data are
based on two key studies presented in this chapter: a
study of children's activity patterns in California
(Wiley et al., 1991) and the National Human Activity
Pattern Survey (NHAPS) (U.S. EPA, 1996). Both
mean and 95th percentile recommended values are
provided. However, because these recommendations
are based on short-term survey data, 95th percentile
values may be misleading for estimating chronic (i.e.,
long term) exposures and should be used with caution.
Also, the upper percentile values for some activities are
truncated as a result of the maximum response
included in the survey (e.g., durations of more than
120 minutes/day were reported as 121 minutes/day),
and could not be further refined). The confidence
ratings for the recommendations are presented in
Table 16-2.
The recommendations for total time spent
indoors and the total time spent outdoors are based on
U.S. EPA re-analysis of the source data from Wiley et
al. (1991) for children < 1 year of age and U.S. EPA
(1996) for age groups > 1 year of age. Although Wiley
Child-Specific Exposure Factors Handbook
September 2008
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16-1
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
et al. (1991) is a study of California children and the
sample size was very small for infants, it provides data
for children's activities for the younger age groups.
Data from U.S. EPA (1996) are representative of the
U.S. general population. In some cases, however, the
time spent indoors or outdoors would be better
addressed on a site-specific basis since the times are
likely to vary depending on the climate, residential
setting (i.e., rural versus urban), personal traits (e.g.,
health status) and personal habits. The recommended
values for time spent indoors at a residence, duration
of showering and bathing, and time spent swimming
are based on a U.S. EPA re-analysis of the source data
from U.S. EPA (1996). Likewise, the recommended
values for time spent playing on sand, gravel, grass or
dirt are based on a U.S. EPA re-analysis of the source
data from U.S. EPA (1996).
Page
16-2
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September 2008
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-1. Recommended Values for Activity Factors
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Age Group
Table 16-1
Mean
Recommended Values for Activity Factors (continued)
95th Percentile Source
Bathing
minutes/day
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-1. Recommended Values for Activity Factors (continued)
Age Group
Mean
95th Percentile
Source
Playing on Dirt
minutes/day
Birth to <1 year
1 to < 2 years
2 to <3 years
3 to <6 years
6 to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-2. Confidence in Recommendations for Activity Factors
General Assessment Factors
Rationale
Rating
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
The survey methodologies and data analyses were
adequate. In the U.S. EPA (1996) study, responses were
weighted according to this demographic data. The
California children's activity pattern survey design (Wiley
et al., 1991) andNHAPS (U.S. EPA, 1996) consisted of
large overall sample sizes that varied with age. Data were
collected via questionnaires and interviews.
Measurement or recording error may have occurred since
the diaries were based on 24 hour recall. The sample sizes
for some age groups were small for some activity factors.
The upper ends of the distributions were truncated for
some factors. The data were based on short-term data.
High
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Medium
The key studies focused on activities of children.
U.S. EPA (1996) was a nationally representative survey of
the U.S. population; the Wiley et al. (1991) survey was
conducted in California and it was not representative of the
U.S. population.
The Wiley et al. (1991) study was conducted between
April 1989 and February 1990; the U.S. EPA (1996) study
was conducted between October 1992 and September
1994.
Data were collected for a 24-hour period.
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Medium
The original studies are widely available to the public;
U.S. EPA analysis of the original raw data from U.S. EPA
(1996) is available upon request.
The methodologies were clearly presented; enough
information was included to reproduce the results.
Quality assurance methods were not well described in
study reports.
Variability and Uncertainty
Variability in Population
Uncertainty
Medium
Variability was characterized across various age categories
of children.
The studies were based on short term recall data, and the
upper ends of the distributions were truncated.
Evaluation and Review
Peer Review
Number and Agreement of Studies
Medium
The original studies received a high level of peer review.
The re-analysis of the U.S. EPA (1996) data to conform to
the standardized age categories was not peer-reviewed.
There were 2 key studies.
Page
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Chapter 16 - Activity Factors
Overall Rating
Medium for the
mean; low for
upper percentile
16.3 ACTIVITY PATTERNS
This section briefly describes published time-use
studies that provide information on time-activity
patterns of children in the U.S. For a detailed
description of the studies, the reader is referred to the
Exposure Factors Handbook (U.S. EPA, 1997).
16.3.1 KEY STUDIES
16.3.1.1 Wiley et al, 1991 - Study of Children's
Activity Patterns
The California Study of Children's Activity
Patterns survey (Wiley et al., 1991) provided estimates
of the time children spent in various activities and
locations (microenvironments) on a typical day. The
sample population consisted of 1,200 children, under
12 years of age, selected from English-speaking
households using Random Digit Dial (ROD) methods.
This represented a survey response rate of 77.9
percent. One child was selected from each household.
If the selected child was 8 years old or less, the adult in
the household who spent the most time with the child
responded. However, if the selected child was between
9 and 11 years old, that child responded. The
population was also stratified to provide representative
estimates for major regions of the state. The survey
questionnaire included a time diary which provided
information on the children's activity and location
patterns based on a 24-hour recall period. In addition,
the survey questionnaire included questions about
potential exposure to sources of indoor air pollution
(e.g., presence of smokers) on the diary day, and the
socio-demographic characteristics of children and
adult respondents. The questionnaires and the time
diaries were administered via a computer-assisted
telephone interviewing (CATI) technology (Wiley et
al., 1991). The telephone interviews were conducted
during April 1989 to February 1990 over four seasons:
spring (April to June 1989), summer (July to
September 1989), fall (October to December 1989),
and winter (January to February 1990).
The data obtained from the survey interviews
resulted in ten major activity categories, 113 detailed
activity codes, 6 major categories of locations, and 63
detailed location codes. The time respondents under
12 years of age spent in the 10 activity categories (plus
a "don't know" or non-coded activity category) are
presented in Table 6-3. For each of the 10 activity
categories, this table presents the mean duration for all
survey participants, the percentage of respondents who
reported participating in the activity (i.e., percent
doers), and the mean, median, and maximum duration
for only those survey respondents who engaged in the
activity (i.e., doers). It also includes the detailed
activity with the highest mean duration of time for
each activity category. The activity category with the
highest time expenditure was personal needs and care,
with a mean of 794 minutes/day (13.2 hours/day).
Night sleep was the detailed activity that had the
highest mean duration in that activity category. The
activity category "don't know" had a mean duration of
about 2 minutes/day and only 4 percent of the
respondents reported missing activity time.
Table 16-4 presents the mean time spent in
the 10 activity categories by age and gender. Because
the original source data were available, U.S. EPA re-
analyzed the data according to the standardized age
categories used in this handbook. Differences between
activity patterns in boys and girls tended to be small.
Table 16-5 presents the mean time spent in the 10
activity categories grouped by season and geographic
region in the state of California. There were seasonal
differences for 5 activity categories: personal needs and
care, education, entertainment/social, recreation, and
communication/passive leisure. Time expenditure
differences in various regions of the state were
minimal for childcare, work-related, goods/services,
personal needs and care, education,
entertainment/social, and recreation.
Table 16-6 presents the distribution of time
across six location categories. The mean duration for
all survey participants, the percent of respondents
engaging in the activity (i.e., percent doers); the mean,
median, and maximum duration for doers only; and
the detailed locations with the highest average time
expenditure are shown. For all survey respondents, the
largest mean amount of time spent was at home (1,078
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minutes/day); 99 percent of respondents spent time at
home (mean of 1,086 minutes/day for these individuals
only). Tables 16-7 and 16-8 show the average time
spent in the six locations grouped by age and gender,
and season and region, respectively. Again, because
the original source data were available, the age
categories used by Wiley et al. (1991) have been
replaced in Table 16-7 by the standardized age
categories used in this handbook. There were
relatively large differences among the age groups in
time expenditure for educational settings (Table 16-7).
There were small differences in time expenditure at the
six locations by region, but time spent in school
decreased in the summer months compared to other
seasons (Table 16-8).
Table 16-9 shows the average time children
spent in proximity to gasoline fumes and gas oven
fumes. In general, the sampled children spent more
time closer to gasoline fumes than to gas oven fumes.
The age categories in Table 16-9 have been modified
to conform to the standardized categories used in this
handbook.
The U.S. EPA estimated the total time
indoors and outdoors using the data from the Wiley et
al. (1991) study. Activities performed indoors were
assumed to include household work, child care,
personal needs and care, education, and
communication/passive leisure. The average times
spent in these indoor activities and half the time spent
in each activity which could have occurred either
indoors or outdoors (i.e., work-related, goods/services,
organizational activities, entertainment/social, don't
know/not coded) were summed. Table 16-10
summarizes the results of this analysis using the
standard age groups.
A limitation of this study is that the
sampling population was restricted to only English-
speaking households; therefore, the data obtained do
not represent the diverse population group present in
California. Another limitation is that time use values
obtained from this survey were based on short-term
recall (24-hr) data; therefore, the data set obtained may
be biased. Other limitations are: the survey was
conducted in California and is not representative of the
national population, and the significance of the
observed differences in the data obtained (i.e., gender,
age, seasons, and regions) were not tested statistically.
An advantage of this study is that time expenditure in
various activities and locations were presented for
children grouped by age, gender, and season. Also,
potential exposures of respondents to pollutants were
explored in the survey. Another advantage is the use
of the CATI program in obtaining time diaries, which
allows automatic coding of activities and locations
onto a computer tape, and allows activities forgotten by
respondents to be inserted into their appropriate
position during interviewing.
16.3.1.2 U.S. EPA, 1996-National Human Activity
Pattern Survey (NHAPS)
U.S. EPA (1996) analyzed data collected by
the National Human Activity Pattern Survey (NHAPS).
This survey was conducted by U.S. EPA and is the
largest and most current human activity pattern survey
available (U.S. EPA, 1996). Data for 9,386
respondents in the 48 contiguous United States were
collected via minute-by-minute 24-hour diaries.
NHAPS was conducted from October 1992 through
September 1994 by the University of Maryland's
Survey Research Center using CATI technology to
collect 24-hour retrospective diaries and answers to a
number of personal and exposure related questions
from each respondent. Detailed data were collected for
a maximum of 82 different possible locations, and a
maximum of 91 different activities. Participants were
selected using a ROD method. The response rate was
63 percent, overall. If the chosen respondent was a
child too young to interview, an adult in the household
gave a proxy interview. Each participant was asked to
recount their entire daily routine from midnight to
midnight immediately previous to the day that they
were interviewed. The survey collected information on
duration and frequency of selected activities and of the
time spent in selected microenvironments. In addition,
demographic information was collected for each
respondent to allow for statistical summaries to be
generated according to specific subgroups of the U.S.
population (i.e., by gender, age, race, employment
status, census region, season, etc.). The participants'
responses were weighted according to geographic,
socioeconomic, time/season, and other demographic
factors to ensure that results were representative of the
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U.S. population. The weighted sample matched the
1990 U.S. census population for each gender, age
group, census region, and the day-of-week and
seasonal responses were equally distributed. Saturdays
and Sundays were over sampled to ensure an adequate
weekend sample.
Tables 16-11 through 16-24 provide data
from the NHAPS study. In most cases, the source data
from U. S. EPA have been reviewed and re-analyzed by
U.S. EPA to conform to the age categories
recommended in Guidance for Monitoring and
Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005) and used in this
handbook. Because no data were available on subjects'
age in months, age groups less than 1 year old were
consolidated into a single group. These tables provide
statistics for 24-hour cumulative time spent (mean,
minimum, percentiles, and maximum) in or in selected
locations or engaging in selected activities. For each
location or activity, statistics were calculated for the
entire survey population (i.e., whole population) and
for the subset of the survey population that reported
being in the location or doing the activity in question
(i.e., doers only). When the sample size was 10
persons or fewer, percentile values were not calculated.
Also note that some of these activities were not
necessarily mutually exclusive (e.g. time spent in
active sports likely overlaps with exercise time).
Table 16-11 presents data for the time
children spent in various rooms of the house (i.e.,
kitchen, living room, dining room, bathroom,
bedroom, and garage), and all rooms combined. Table
16-12 presents data for time spent in other indoor
locations (i.e., restaurants, indoors at school, and
grocery/convenience stores). Table 16-13 presents
data for the time children spent outdoors on school
grounds/playgrounds, parks or golf courses, or pool
rivers, or lakes. Table 16-14 provides data on time
spent in indoor and outdoor environments. The U.S.
EPA estimated the time spent indoors by adding the
average times spent indoors at the respondents' home
(kitchen, living room, bathroom, etc.), at other houses,
and inside other locations such as school, restaurants,
etc. Time outdoors was estimated by adding the
average time spent outdoors at the respondents' pool
and yard, others' pool and yard, and outside other
locations such as sidewalk, street, neighborhood,
parking lot, service station/gas station, school grounds,
park/golf course, pool, river, lake, farm, etc. Table 16-
15 presents data for the time spent in various types of
vehicles (i.e., car, truck/van, bus), and in all vehicles
combined. Table 16-16 presents data for the time
children spent in various major activity categories (i.e.,
sleeping, napping, eating, attending school, outdoor
recreation, active sports, exercise, and walking).
Table 16-17 through 16-19 provide data
related to showering, bathing, and handwashing
activities. Tables 16-20 and 16-21 provide data on
monthly swimming (in a freshwater pool) frequency by
the number of respondents and swimming duration,
respectively. Table 16-22 provides data on the time
children spent playing on dirt, sand/gravel, or grass,
and Table 16-23 provides data on the number of
minutes spent near excessive dust. Table 16-24
provides information on time spent in the presence of
smokers. For this data set, the authors' original age
categories were used because the methodology used to
generate the data could not be reproduced.
The advantages of the NHAPS data set are
that it is representative of the U.S. population and it
has been adjusted to be balanced geographically,
seasonally, and for day/time. Also, it is inclusive of all
ages, genders, and races. A disadvantage of the study
is that for the standard age categories, the number of
respondents is small for the "doers" of many activities.
In addition, the durations exceeding 60, 120, and 181
minutes were not collected for some activities.
Therefore, the actual time spent at the high end of the
distribution for these activities could not be accurately
estimated.
16.3.2 RELEVANT STUDIES
16.3.2.1 Timmer et al, 1985 - How Children Use
Time
Timmer et al. (1985) conducted a study
using the data obtained on children's time use from a
1981-1982 panel study. Data were obtained for 389
children between the ages of 3 and 17 years of age.
Data were collected using a time diary and a
standardized interview. The time diary involved
children reporting their activities beginning at 12:00
a.m. the previous night, the duration and location of
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each activity, the presence of another individual, and
whether they were performing other activities at the
same time. The standardized interview was
administered to the children to gather information
about their psychological, intellectual (using reading
comprehension tests), and emotional well-being; their
hopes and goals; their family environment; and their
attitudes and beliefs.
For preschool children, parents provided
information about the child's previous day's activities.
Children in first through third grades completed the
time diary with their parents assistance and, in
addition, completed reading tests. Children in fourth
grade and above provided their own diary information
and participated in the interview. Parents were asked
to assess their children's socioemotional and
intellectual development, and a survey form was sent
to a teacher of each school-age child to evaluate their
socioemotional and intellectual development. The
activity descriptor codes used in this study were
developed by Juster et al. (1983).
The mean time spent performing major
activities on weekdays and weekends by age, sex, and
type of day is presented in Table 16-25. On weekdays,
children spend about 40 percent of their time sleeping,
20 percent in school, and 10 percent eating, and
performing personal care activities (Timmer et al.,
1985). The data in Table 16-25 indicate that girls
spent more time than boys performing household work
and personal care activities and less time playing
sports. Also, the children spent most of their free time
watching television.
Table 16-26 presents the mean time children
spent during weekdays and weekends performing
major activities by five different age groups. The
significant effects of each variable (i.e., age and sex)
are also shown. Older children spent more time
performing household and market work, studying, and
watching television and less time eating, sleeping, and
playing. The authors estimated that, on average, boys
spent 19.4 hours a week and girls spent 17.8 hours per
week watching television.
U.S. EPA estimated the total time indoors
and outdoors using the Timmer et al. (1985) data.
Activities performed indoors were assumed to include
household work, personal care, eating, sleeping,
attending school, studying, attending church, watching
television, and engaging in household conversations.
The average times spent in these indoor activities and
half the time spent in each activity which could have
occurred indoors or outdoors (e.g., market work,
sports, hobbies, art activities, playing, reading, and
other passive leisure) were summed. Table 16-27
summarizes the results of this analysis by age group
and time of the week.
A limitation associated with this study is that
it was conducted in 1981. It is likely that activity
patterns of children have changed from 1981 to the
present. Thus, the application of these data to current
exposure assessments may bias their results. Another
limitation is that the data do not provide overall annual
estimates of children's time use since data were
collected only during the time of the year when
children attended school and not during school
vacations. An advantage of this survey is that diary
recordings of activity patterns were kept and the data
obtained were not based entirely on recall. Another
advantage is that because parents assisted younger
children with keeping their diaries and with
interviews, any bias that may have been created by
having younger children record their data should have
been minimized.
16.3.2.2 Robinson and Thomas, 1991 - Time Spent
in Activities, Locations, and
Microenvironments: A California-National
Comparison
Robinson and Thomas (1991) reviewed and
compared data from the 1987-88 California Air
Resources Board (CARD) time-activity study for
California residents and from a similar 1985 national
study, Americans' Use of Time, conducted at the
University of Maryland. Both studies used the diary
approach to collect data. Time- use patterns were
collected for individuals aged 12 years and older.
Telephone interviews based on the ROD procedure
were conducted for 1,762 and 2,762 respondents for
the CARD study and the national study, respectively.
Of these respondents, 183 were children, ages 12 to!7
years in the CARD study and 340 were children, ages
12 to 17 years, in the national study. Robinson and
Thomas (1991) defined a set of 16 microenvironments
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based on the activity and location codes employed in
the two studies. The mean durations of time spent in
the 16 microenvironments by children, ages 12 to 17
years, are presented in Table 16-28. In both studies,
children spent the majority of their time sleeping, and
engaging in leisure and work/study-related activities.
The limitations associated with the Robinson
and Thomas (1991) study are that the CARD survey
was performed in California only and may not be
representative of the U.S. population as a whole. In
addition, the studies were conducted in the 1980s and
activity patterns may have changed over time.
Another limitation is that the data are based on short-
term studies. Finally, the available data could not be
re-analyzed to conform to the standardized age
categories used in this handbook.
16.3.2.3 Funk et al, 1998 - Quantifying the
Distribution of Inhalation Exposure in
Human Populations: Distribution of Time
Spent by Adults, Adolescents, and Children
at Home, at Work, and at School
Funk et al. (1998) used the data from the
CARD study to determine distributions of exposure
time by tracking the time spent participating in daily
at-home and at-school activities for male and female
children and adolescents. CARD performed two
studies from 1987 to 1990; the first was focused on
adults (18 years and older) and adolescents (12-17
years old), and the second focused on children (6-11
years old). The targeted groups were
noninstitutionalized English speaking Californians
with telephones in their residences. Individuals were
contacted by telephone and asked to account for every
minute within the previous 24 hours, including the
amount of time spent on an activity and the location of
the activity. The surveys were conducted on different
days of the week as well as different seasons of the
year.
Using the location descriptors provided in
the CARB study, Funk et al. (1998) categorized the
activities into two groups, "at home" (any activity at
principal residence) and "away." Each activity was
assigned to one of three inhalation rate levels (low,
moderate, or high) based on the level of exertion
expected from the activity. Ambiguous activities were
assigned to moderate inhalation rate levels. Among
the adolescents and children studied, means were
determined for the aggregate age groups, as shown in
Table 16-29.
Funk et al. (1998) used several statistical
methods, such as Chi-square, Kolmogorov-Smirnov,
and Anderson-Darling, to determine whether the time
spent in an activity group had a known distribution.
Most of the activities performed by children were
assigned a low or moderate inhalation rate rate (Table
16-30).
The aggregate time periods spent at home in
each activity are shown in Table 16-31. Aggregate
time spent at home performing different activities was
compared between genders. There were no significant
differences between adolescent males and females in
any of the activity groups (Table 16-32). In children,
ages 6-11 years, differences between gender and age
were observed at the low inhalation rate levels. There
were significant differences between two age groups
(6-8 years, and 9-11 years) and gender at the moderate
inhalation rate level (Table 16-33).
A limitation of this study was that large
proportions of the respondents in the study did not
participate in high-inhalation rate-level activities. The
Funk et al. (1998) study was based on data from one
geographic location, collected more that a decade ago.
Thus, it may not be representative of current activities
among the general population of the U.S.
16.3.2.4 U.S. EPA, 2000 - Consolidated Human
Activity Database (CHAD)
The Consolidated Human Activity Database
(CHAD), available online at
http://www.cpa. gov/chadnct 1 /, was developed by the
U.S. EPA's National Exposure Research Laboratory
(NERL) to provide access to existing human activity
data for use in exposure and risk assessment efforts.
Data from twelve activity pattern studies conducted at
the city, state, and national levels are included in
CHAD. CHAD contains both the original raw data
from each study and data modified based on predefined
format requirements. Modifications made to data
included: receding of variables to fit into them a
common activity/location code system, and
standardization of time diaries to an exact 24-hour
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length. Detailed information on the coding system and
the studies included in CHAD is available in the
CHAD User Manual, available at
htlp://oaspub.cpa.gov/chad/CHAD DaiafilcsS. start n
p#Manual and in McCurdy et al. (2000).
A total of 144 activity codes and 115 location
codes were used in CHAD (McCurdy et al., 2000).
Although some participants in a study conducted
multiple activities, many activities were only
conducted within a few studies. The same is true for
activity locations. The selection of exposure estimates
for a particular activity or particular location should be
based on study parameters that closely relate to the
exposure scenario being assessed. The maximum
amount of time, on average, within a majority of the
studies was sleeping or taking a nap, while the
maximum amount of time spent at a particular location
was at home or at work, depending on the study.
Many of the limitations of CHAD data arise
from the incorporation of multiple studies into the time
diary functions specified in CHAD. Activities and
locations were coded similarly to the NHAPS study;
studies with differing coding systems were modified to
fit the NHAPS codes. In some cases start times and
end times from a study had to be adjusted to fit a 24-
hour period. Respondents were not randomly
distributed in CHAD. For example, some cities or
states were over sampled because entire studies were
carried out in those places. Other studies excluded
large groups of people such as smokers, or
non-English speakers, or people without telephones.
Many surveys were age-restricted, or they
preferentially sampled certain target groups. As a
result, users are cautioned against using random
individuals in CHAD to represent the U.S. population
as a whole (Glenn et al., 2000).
16.3.2.5 Hubal et al., 2000 - Children's Exposure
Assessment: A Review of Factors
Influencing Children's Exposure and the
Date Available to Characterize and Assess
that Exposure
Hubal et al. (2000) reviewed available data
from CHAD, including activity pattern data, to
characterize and assess environmental exposures to
children. CHAD contains 3,009 person-days of
macroactivity data for 2,640 children less than 12
years of age (Hubal et al., 2000) (Table 16-34). The
number of hours these children spent in various
microenvironments are shown in Table 16-35 and the
time they spent in various activities indoors at home is
shown in Table 16-36.
Hubal et al. (2000) noted that CHAD
contains approximately "140 activity codes and 110
location codes, but the data generally are not available
for all activity locations for any single respondent. In
fact, not all of the codes were used for most of the
studies. Even though many codes are used in
macroactivity studies, many of the activity codes do not
adequately capture the richness of what children
actually do. They are much too broadly defined and
ignore many child-oriented behaviors. Thus, there is
a need for more and better-focused research into
children's activities."
U.S. EPA updated the analysis performed by
Hubal et al. (2000) using CHAD data downloaded in
2000, sorted according to the age groups recommended
in Guidance for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U. S. EPA,
2005). The results are shown in Tables 16-37 and 16-
38. In this analysis, individual study participants
within CHAD whose behavior patterns were measured
over multiple days were treated as multiple one-day
activity patterns. This is a potential source of error or
bias in the results because a single individual may
contribute multiple data sets to the aggregate
population being studied.
16.3.2.6 Wong et al., 2000 - Adult Proxy Responses
to a Survey of Children's Dermal Soil
Contact Activities
Wong et al. (2000) conducted telephone
surveys to gather information on children's activity
patterns as related to dermal contact with soil during
outdoor play on bare dirt or mixed grass and dirt
surfaces. This study, the second Soil Contact Survey
(SCS-II), was a follow-up to the initial Soil Contact
Survey (SCS-I), conducted in 1996, that primarily
focused on assessing adult behavior related to dermal
contact with soil and dust (Garlock et al., 1999). As
part of SCS-I, information was gathered on the
behavior of children under the age of 18 years,
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however, the questions were limited to clothing choices
and the length of time between soil contact and hand
washing. Questions were posed for SCS-II to further
define children's outdoor activities and hand washing
and bathing frequency. For both soil contact surveys
households were randomly phoned in order to obtain
nationally representative results. The adult
respondents were questioned as surrogates for one
randomly chosen child under the age of 18 residing
within the household.
In the SCS-II, of 680 total adult respondents
with a child in their household, 500 (73.5 percent)
reported that their child played outdoors on bare dirt or
mixed grass and dirt surfaces (identified as "players").
Those children that reportedly did not play outdoors
("non-players") were typically very young (• 1 year) or
relatively older (• 14 years). Of the 500 children that
played outdoors, 497 played outdoors in warm weather
months (April through October) and 390 were reported
to play outdoors during cold weather months
(November through March). These results are
presented in Table 16-39. The frequency (days/week),
duration (hours/day), and total hours per week spent
playing outdoors was determined for those children
identified as "players" (Table 16-40). The responses
indicated that children spent a relatively high
percentage of time outdoors during the warmer
months, and a lesser amount of time outdoors in cold
weather. The median play frequency reported was 7
days/week in warm weather and 3 days/week in cold
weather. Median play duration was 3 hours/day in
warm weather and 1 hour/day during cold weather
months.
Adult respondents were then questioned as
to how many times per day their child washed his/her
hands and how many times the child bathed or
showered per week, during both warm and cold
weather months. This information provided an
estimate of the time between skin contact with soil and
removal of soil by washing (i.e., exposure time). Hand
washing and bathing frequencies for child players are
reported in Table 16-41. Based on these results, hand
washing occurred a median of 4 times per day during
both warm and cold weather months. The median
frequency for baths and showers was estimated to be 7
times per week for both warm and cold weather.
Based on reported household incomes, the
respondents sampled in SCS-II tended to have higher
incomes than that of the general population. This may
be explained by the fact that phone surveys cannot
sample households without telephones. Additional
uncertainty or error in the study results may have
occurred as a result of the use of surrogate respondents.
Adult respondents were questioned regarding child
activities that may have occurred in prior seasons,
introducing the chance of recall error. In some
instances, a respondent did not know the answer to a
question or refused to answer. Table 16-42 compares
mean play duration data from SCS-II to similar
activities identified in NHAPS (U.S. EPA, 1996).
Table 16-43 compares the number of times per day a
child washed his or her hands, based on data from
SCS-II and NHAPS. As indicated in Tables 16-42 and
16-43, where comparison is possible, NHAPS and
SCS-II results showed similarities in observed
behaviors.
16.3.2.7 Graham and McCurdy, 2004 - Developing
Meaningful Cohorts for Human Exposure
Models
Graham and McCurdy (2004) used a
statistical model [general linear model and analysis of
variance (GLM/ANOVA)] to assess the significance of
various factors in explaining variation in time spent
outdoors, indoors and in motor vehicles. These
factors, which are commonly used in developing
cohorts for exposure modeling, included age, gender,
weather, ethnicity, day type, and precipitation.
Activity pattern data from CHAD, containing 30 or
more records per day, were used in the analysis
(Graham and McCurdy, 2004).
Data on time spent outdoors for people who
spent >0 time outdoors (i.e., doers) are presented in
Table 16-44. Graham and McCurdy (2004) found that
all the factors evaluated were significant (p<0.001) in
explaining differences in time spent outdoors (Graham
and McCurdy, 2004). An evaluation of gender
differences in time spent outdoors by age cohorts was
also conducted. Table 16-45 presents descriptive
statistics and the results of the two-sample
Kolmogorov-Smirnov (KS) test for this evaluation. As
shown in Table 16-45, there were statistically
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significant gender differences in time spent outdoors
starting with the 6 to 10 year old age category. In
addition, Graham and McCurdy (2004) evaluated the
effect of physical activity and concluded that this was
the most important factor in explaining time spent
outdoors. For time spent indoors (Table 16-46), there
were statistically significant effects for all the factors
evaluated, with gender, weather, and day type being
the most important variables. Regarding time spent in
motor vehicles (Table 16-47), precipitation was the
only factor found to have no significant effects
(Graham and McCurdy, 2004).
Based on the results of these analysis,
Graham and McCurdy (2004) noted that "besides age
and gender, other important attributes for defining
cohorts are the physical activity level of individuals,
weather factors such as daily maximum temperature in
combination with months of the year, and combined
weekday/weekend with employment status." The
authors also noted that even though the factors
evaluated were found to be statistically significant in
explaining differences in time spent outdoors, indoors,
and in motor vehicles, "parameters such as lifestyle
and life stages that are absent from CHAD might have
reduced the amount of unexplained variance." The
authors recommended that, in defining cohorts for
exposure modeling, age and gender should be used as
' 'first-order'' attributes, followed by physical activity
level, daily maximum temperature, and day type
(weekend/weekday or day-of-the-week/working status)
(Graham and McCurdy, 2004).
16.3.2.8 Vandewater et al, 2004 - Linking Obesity
and Activity Level with Children's
Television and Video Game Use
Vandewater et al. (2004) evaluated
children's media use and participation in active and
sedentary activities using 24-hour time-use diaries
collected in 1997, as part of the Child Development
Supplement (CDS) to the Panel Study of Income
Dynamics (PSID). The PSID is a ongoing,
longitudinal study of U.S. individuals and their
families conducted by the Survey Research Center of
the University of Michigan. In 1997, PSID families
with children younger than 12 years of age completed
the CDS and reported all activities performed by the
children on one randomly selected weekday and one
randomly selected weekend day. Since minorities, low
income families, and less educated individuals were
oversampled in the PSID, sample weights were applied
to the data (Vandewater et al., 2004). More
information on the CDS can be found on-line at
http://psidoiiline.isr.uinich.edu/CDS/.
Using time diary data from 2,831 children
participating in the CDS, Vandewater et al., (2004)
estimated the time in minutes over the two-day study
period (i.e., sum of time spent on one weekday and one
weekend day) that children spent watching television,
playing games on video games consoles or computers,
reading, and using computers for other purposes
besides playing games. In addition, the time spent
participating in highly active (i.e., playing sports),
moderately active (i.e., fishing, boating, camping,
taking music lessons, and singing), and sedentary (i.e.,
using the phone, doing puzzles, playing board games,
and relaxing) activities was determined. Table 16-48
presents the means and standard deviations for the
time spent in the selected activities by age and gender.
A limitation of this study is that the survey
was not designed for exposure assessment purposes.
Therefore, the time use data set may be biased.
However, the survey provides a database of current
information on various human activities. This
information can be used to assess various exposure
pathways and scenarios associated with these activities.
16.3.2.9 Juster et al. (2004) - Changing Times of
American Youth: 1983-2003
Juster et al. (2004) evaluated changes in time
use patterns of children by comparing data collected in
a 1981-1982 pilot study of children ages 6 to 17 to data
from the 2002-2003 Child Development Supplement
(CDS) to the Panel Study of Income Dynamics (PSID).
The 1981-1982 pilot study is the same study described
in Timmer et al. (1985). The 2002-2003 CDS
gathered 24-hour time diary data on 2,908 children
ages 6 to 17; as was done in the 1997 CDS,
information was collected on one randomly selected
weekday and one randomly selected weekend day
(Juster et al., 2004).
Tables 16-49 and 16-50 present the mean
time children spent (in minutes/day) performing major
Page
16-14
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Chapter 16 - Activity Factors
activities on weekdays and weekend days, respectively,
for the years 1981-82 and 2002-2003. Table 16-51
shows the weekly time spent in these activities for the
years 1981-82 and 2002-2003. Juster et al. (2004)
noted that the time spent in school and studying
increased while time spent in active sports and
outdoors activities decreased during the period studied.
16.3.2.10 U.S. Department of Labor, 2007 -
American Time Use Survey, 2006
Results
The American Time Use Study (ATUS) has
been conducted annually since 2003 by the U.S.
Department of Labor's Bureau of Labor Statistics (U. S.
DL, 2007). The purpose of the study is to collect "data
on what activities people do during the day and how
much time they spend doing them." In 2006, the
survey focused on "the time Americans worked, did
household activities, cared for household children,
participated in educational activities, and engaged in
leisure and sports activities." Approximately 13,000
individuals, 15 years of age and older, were
interviewed during 2006. Participants were randomly
selected and interviewed using the CATI method and
were asked to recall their activities on the day before
the interview. Data were collected for all days of the
week, including weekends (i.e., 10 percent of the
individuals were interviewed about their activities on
one of the five weekdays, and 25 percent of the
individuals were interviewed about their activities on
one of the two weekend days). Demographic
information, including age, gender, race/ethnicity,
marital status, and educational level were also
collected, and sample weights were applied to records
to "reduce bias in the estimates due to differences in
sampling and response rates across subpopulations and
days of the week." Data were collected for 17 major
activities, that were subsequently composited into 12
categories for publication of the results. Estimates of
time use in these 12 major categories are presented in
Table 16-52. These data represent the average hours
per day spent by male, female, and all children ages 15
to 19 years in the various categories. Table 16-52 also
provides a more detailed breakdown of the Leisure and
Sports category for all children, ages 15 to 19 years
old.
16.3.2.11 Nader et al. 2008 - Moderate-to-
Vigorous Physical Activity from
Ages 9 to 15 years
Nader et al. (2008) conducted a longitudinal
study of 1,032 children from ages 9 to 15 years. The
purpose of the study was to determine the amount of
time children 9 to 15 years of age engaged in
moderate-to-vigorous activities (MVPA) and compare
results with the recommendations issued by the U.S.
Department of Health and Human Services and the
U.S. Department of Agriculture of a minimum of 60
minutes per day. Children's activity levels were
recorded for four to seven days using an accelerometer.
The study participants included 517 boys and 515
girls. The study found that at age 9 children engaged
in 3 hours of MVP A per day. By age 15, the amount
of time engaged in MVPA was dropped to 49
minutes/day on weekdays and 35 minutes per day on
weekends. Boys spent 18 more minutes/day of MVPA
than girls on weekdays and 13 more minutes/day on
weekends. Estimates of the mean time spent in
moderate-to-vigorous activities by various age groups
are presented in Table 16-53. The study did not
provide information about the amount of time spent at
specific activities.
16.4 REFERENCES FOR CHAPTER 16
Chance, W.G.; Harmsen, E. (1998) Children are
different: environmental contaminants and
children's health. Can J Public Health
89(Supplement):59-513.
Funk, L.; Sedman, R.; Beals, J.A.J.; Fountain, R.
(1998) Quantifying the distribution of
inhalation exposure in human populations:
distributions of time spent by adults,
adolescents, and children at home, at work,
and at school. Risk Anal 18(l):47-56.
Garlock, T.J.; Shirai, J.H.; Kissel, J.C. (1999) Adult
responses to a survey of soil contact related
behaviors. J Expo Anal Environ Epidemiol
9:134-142.
Glenn, G.; Stallings, C.; Tippett, J.; Smith, L. (2000)
CHAD'S user guide: Extracting human
activity information from CHAD on the PC.
Prepared for the U.S. EPA National
Child-Specific Exposure Factors Handbook
September 2008
Page
16-15
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Exposure Research Laboratory by
ManTech Environmental
Technology, Inc.
Graham, S.E.; McCurdy, T. (2004) Developing
meaningful cohorts for human exposure
models. J Expo Anal Environ Epidemiol
14:23-43.
Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy,
T.R.; Berry, M.R.; Rigas, M.L.; Zartarian,
V.G.; Freeman, N.G. (2000) Children's
exposure assessment: a review of factors
influencing children's exposure and the data
available to characterize and assess that
exposure. Environ Health Persp 108:475-
485.
Johnson, T. (1989) Human Activity Patterns in
Cincinnati, Ohio. Palo Alto, CA: Electric
Power Research Institute.
Juster, F.T.; Hill, M.S.; Stafford, P.P.; Parsons, J.E.
(1983) Study description. 1975-1981 time
use longitudinal panel study. Ann Arbor,
MI: The University of Michigan, Survey
Research Center, Institute for Social
Research.
Juster, T.; Ono, H.; Stafford, F. (2004) Changing
times of American youth: 1981-2003.
Institute for Social Research, University of
Michigan, Ann Arbor, Michigan. Available
on-line at
http://www.umich.edu/news/Releases/2004
/Nov04/teen_time_report.pdf
McCurdy, T.; Glen, G.; Smith, L.; Lakkadi, Y. (2000)
The National Exposure Research
Laboratory's Consolidated Human Database.
J Expo Anal Environ Epidemiol 10:566-578.
Nader, P.R.; Bradley, R.H.; Houts, R.M.; McRitchie,
S.L.; O'Brien, M. (2008) Moderate-to-
vigorous physical activity from ages 9 to 15
years. JAMA, 300(3):295-305.
Robinson, J.P.; Thomas, J. (1991) Time spent in
activities, locations, andmicroenvironments:
a California-National Comparison Project
report. Las Vegas, NV: U.S.
Environmental Protection Agency,
Environmental Monitoring Systems
Laboratory.
Timmer, S.G.; Eccles, J.; O'Brien, K. (1985) How
children use time. In: Juster, F.T.; Stafford,
P.P.; eds. Time, goods, and well-being.
Ann Arbor, MI: University of Michigan,
Survey Research Center, Institute for Social
Research, pp. 353-380.
U.S. Department of Health and Human Services and
U.S. Department of Agriculture. (2005)
Dietary Guidelines for Americans, 2005. 6th
edition, Washington, DC, Government
Printing Office. Available online at
http://www.health.gOv/dietaryguidelines/d
ga2005/document/pdf/DGA2005 .pdf U. S.
Department of Labor (U.S. DL), Bureau of Labor
Statistics. (2007) American Time Use
Survey - 2006 Results. News release issued
at http://www.bls.gov/tiis on June 28, 2007.
U.S. EPA (1996) Descriptive statistics tables from a
detailed analysis of the National Human
Activity Pattern Survey (NHAPS) data.
Washington, DC: Office of Research and
Development. EPA/600/R-96/148.
U.S. EPA (1997) Exposure Factors Handbook.
Washington, DC: National Center for
Environmental Assessment, Office of
Research and Development. EPA/600/P-
95/002Fa,b,c.
U.S. EPA (2000) Consolidated Human Activity
Database (CHAD). U.S. EPA/NERL.
Available online at
http ://www. cpa. gov/chadnct 1 /
U.S. EPA. (2005) Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
U.S. Environmental Protection Agency,
Washington, D.C., EPA/630/P-03/003F.
Vandewater, E.A.; Shim, M.; Caplovitz, A.G. (2004)
Linking obesity and activity level with
children's television and video game use. J
Adolesc 27:71-85.
Wiley, J.A.; Robinson, J.P.; Cheng, Y.; Piazza, T.;
Stork, L.; Plasden, K. (1991) Study of
children's activity patterns. California
Page
16-16
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Chapter 16 - Activity Factors
Environmental Protection Agency,
Air Resources Board Research
Division. Sacramento, CA.
Wong, E.Y.; Shirai, J.H; Garlock, T.J.; Kissel, J.C.
(2000) Adult proxy responses to a survey of
children's dermal soil contact activities. J
Expo Anal Environ Epidemiol 10:509-517.
Table 16-3. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Ten Major Activity Categories, for All Respondents and Doers
Activity Category
Mean
Duration
(All)
Doers"
Mean Median Maximum
Duration Duration Duration
(Doers)' (Doers)' (Doers)'
Detailed Activity with
Highest Average Minutes
Work-related11 10
Household0 53
Childcared <1
Goods/Services" 21
Personal Needs and Caref 794
Education8 110
Organizational Activities'1 4
Entertain/Social' 15
Recreationj 239
Communication/Passive
T • k iyz
Leisure
25 39 30 405 Eating at Work/School/Daycare
86 61 40 602 Travel to Household
<1 83 30 290 Other Child Care
26 81 60 450 Errands
100 794 770 1,440 Night Sleep
35 316 335 790 School Classes
4 111 105 435 Attend Meetings
17 87 60 490 Visiting with Others
92 260 240 835 Games
93 205 180 898 TV Use
Don't know/Not coded
All Activities
2
1,440
4
41
15
600
;
Doers indicate the respondents who reported participating in each activity category.
Includes: travel to and during work/school; children's paid work; eating at work/school/daycare; and accompanying or watching
adult at work.
Includes: food preparation; meal cleanup; cleaning; clothes care; car and home repair/painting; building a fire; plant and pet care; and
traveling to household.
Includes: baby and child care; helping/teaching children; talking and reading; playing while caring for children; medical care; travel
related to child care; and other care.
Includes: shopping; medical appointments; obtaining personal care services (e.g., haircuts), government and financial services, and
repairs; travel related to goods an services; and errands.
Includes: bathing, showering, and going to bathroom; medical care; help and care; meals; night sleep and daytime naps, dressing and
grooming; and travel for personal care.
Includes: student and other classes; daycare; homework; library; and travel for education.
Includes: attending meetings and associated travel.
Includes: sports events; eating and amusements; movies and theater; visiting museums, zoos, art galleries, etc.; visiting others; parties
and other social events; and travel to social activities.
Includes: active sports; leisure; hobbies; crafts; art; music/drama/dance; games; playing; and travel to leisure activities.
Includes: radio and television use; reading; conversation; paperwork; other passive leisure; and travel to passive leisure activities.
Source: Wiley et al., 1991.
Child-Specific Exposure Factors Handbook
September 2008
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-4. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Ten Major Activity Categories, by Age and Gender
Boys
Activity
Category1
Work-related
Household
Childcare
Goods/Services
Personal Needs and Care
Education
Organizational Activities
Entertainment/Social
Recreation
Communication/Passive
Leisure
Sample Sizes
(Unweighted)
Birth to
1 Month
0
12
0
0
910
180C
0
0
0
338
3
lto<3
Months
0
30
0
16
1,143
0
0
0
0
250
7
3to<6
Months
0
49
0
14
937
75
0
0
26
339
15
6to<12
Months
1
28
0
28
919
70
0
0
104
292
31
lto<2
Years
8
35
0
27
903
33
7
8
314
106
54
2to<3
Years
9
44
0
14
889
69
0
6
304
103
62
3to<6
Years
10
44
0
28
802
67
5
15
294
175
151
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-5. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Ten Major Activity Categories, Grouped by Seasons and Regions
Activity Category0
Work-related
Household
Childcare
Goods/Services
Personal Needs and
Care
Education
Organizational
Activities
Entertainment/Social
Recreation
Communication/
Passive Leisure
Don't know/Not coded
All Activities'"
Sample Sizes
(Unweighted)
Winter
(Jan-Mar)
10
47
<1
19
799
124
3
14
221
203
<1
1,442
318
Season
Region of California
Spring Summer Fall All
(Apr-June) (July-Sept) (Oct-Dec) Seasons
10
58
1
17
774
137
5
12
243
180
2
1,439
204
6
53
<1
26
815
49
5
12
282
189
3
1,441
407
13
52
<1
23
789
131
3
22
211
195
<1
1,441
271
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
Southern
Coast
10
45
<1
20
799
109
2
17
230
206
1
1,440
224
Bay
Area
10
62
<1
21
785
115
6
10
241
190
1
1,442
263
Rest of
State
8
55
1
23
794
109
6
16
249
175
3
1,439
713
All
Regions
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
a See Table 16-3 for a description of what is included in each activity category.
b The column totals may not be equal to 1,440 due to rounding.
Source: Wiley et al., 1991.
Child-Specific Exposure Factors Handbook
September 2008
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Chapter 16 - Activity Factors
Table 16-6. Time (minutes/day) Children Under 12 Years of Age Spent in
Six Major Location Categories, for All Respondents and Doers
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
All Locations
Mean Mean Median Maximum
Duration ., Duration Duration Duration
(All) /oUoers (Doers). (Doers)" (Doers)"
1,078 99 1,086 1,110 1,440
109 33 330 325 1,260
80 32 251 144 1,440
24
69 83 83 60 1,111
79 57 139 105 1,440
<1 1 37 30 90
1,440 ...
Detailed Location with
Highest Average Time
Home - Bedroom
School or Daycare Facility
Friend's/Other's House - Bedroom
Shopping Mall
Traveling in Car
Park, Playground
-
-
" Doers indicate the respondents who reported participating in each activity category.
Source: Wiley et al., 1991.
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Chapter 16 - Activity Factors
Table 16-7.
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
Sample Sizes
(Unweighted)
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
Sample Sizes
(Unweighted)
Birth to
1 Month
938
0
418
0
77
7
0
3
Birth to
1 Month
1,285
0
0
0
73
83
0
4
a The source data end at 1 1
included.
Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Six Location Categories, Grouped by Age and Gender
lto<3
Months
1,295
1
40
14
51
40
0
7
lto<3
Months
1,341
0
12
13
56
19
0
10
3to<6
Months
1,164
26
127
21
69
33
0
15
3to<6
Months
1,151
109
44
20
42
73
0
11
years of age, so the
6to<12
Months
1,189
53
63
36
63
36
0
31
6to<12
Months
1,192
99
32
15
58
43
0
23
lto<2
Years
1,177
73
54
29
56
52
0
54
lto<2
Years
1,162
56
109
21
55
38
0
43
11 to <16year catej
Boys
2to<3
Years
1,161
86
69
22
61
41
0
62
Girls
2to<3
Years
1,065
61
103
40
86
86
0
50
3to<6
Years
1,102
79
89
24
67
78
0
151
3to<6
Years
1,118
78
66
32
78
67
1
151
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Six Location Categories, Grouped by Season and Region
Location Category
Home
School/Childcare
Friend's/Other's
House
Stores, Restaurants,
Shopping Places
In transit
Other Locations
Don't Know/Not
Coded
All Locations*
Sample Sizes
(Unweighted N's)
Winter
(Jan-Mar)
1,091
119
69
22
75
63
<
1,439
318
* The column totals may
Source: Wiley etal
, 1991.
Spring
(Apr-June)
1,042
141
75
21
75
85
<
1,439
204
Season
Summer
(July-Sept)
1,097
52
108
30
60
93
<
1,440
407
Region of California
Fall
(Oct-Dec)
1,081
124
69
24
65
76
<
1,439
271
All
Seasons
1,078
109
80
24
69
79
<
1,439
1,200
Southern
Coast
1,078
113
73
26
71
79
<
1,439
224
Bay
Area
1,078
103
86
23
73
76
<
1,440
263
Rest of
State
1,078
108
86
23
63
81
<
1,440
713
All
Regions
1,078
109
80
24
69
79
<
1,439
1,200
not sum to 1,440 due to rounding.
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Chapter 16 - Activity Factors
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Proximity to Two Potential Sources of Exposure, Grouped by All Respondents, Age, and Gender
Potential
Exposures
Gasoline Fumes
Gas Oven Fumes
Sample Sizes
(Unweighted N's)
Potential
Exposures
Gasoline Fumes
Gas Oven Fumes
Sample Sizes
(Unweighted N's)
Birth to
1 Month
3
0
3
Birth to
1 Month
0
0
4
lto<3
Months
9
0
7
lto<3
Months
3
0
10
3to<6
Months
0
2
15
3to<6
Months
0
0
11
6to<12
Months
2
2
31
6to<12
Months
3
0
23
lto<2
Years
1
1
54
lto<2
Years
1
0
43
Boys
2to<3
Years
4
3
62
Girls
2to<3
Years
2
3
50
3to<6
Years
2
0
151
3to<6
Years
1
2
151
a The source data end at 1 1 years of age, so the 11 to <16 year category is truncated and the 16to
Source: U.S. EPA analysis of source data used by Wiley et al., 1991.
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-10. Mean Time (minutes/day) Children Under 12 Years of Age
Spent Indoors and Outdoors, Grouped by Age and Gender
Age Group
Boys
Girls
N
Indoors"
Outdoors1"
N
Indoors"
Outdoors1"
Birth to <1 Month
1 to <3 Months
3 to <6 Months
6 to < 12 Months
1 to <2 Years
2 to <3 Years
3 to <6 Years
6 to <11 Years
11 Years0
All Ages
3
7
15
31
54
62
151
239
62
624
1,440
1,432
1,407
1,322
1,101
1,121
1,117
1,145
1,166
1,181
0
8
33
118
339
319
323
295
274
258
4
10
11
23
43
50
151
225
59
576
1,440
1,431
1,421
1,280
1,164
1,102
1,140
1,183
1,215
1,181
0
9
19
160
276
338
300
255
225
258
N
Note:
Time indoors was estimating by adding the average times spent performing indoor activities (household work, child care, personal
needs and care, education, and communication/passive leisure) and half the time spent in each activity which could have occurred
either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social, don't know/not coded).
Time outdoors was estimated by adding the average time spent in recreation activities and half the time spent in each activity which
could have occurred either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social,
don't know/not coded).
The source data end at 11 years of age, so the 11 to <16year category is truncated and the 16 to <21 year category is not included.
= Sample size.
Indoor and outdoor minutes/day may not sum to 1,440 minutes/day due to rounding.
Source: U.S. EPA analysis of source data used by Wiley et al., 1991.
Page
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Chapter 16 - Activity Factors
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only
Age (years)
N Mean Min
Percentiles
1
2
5 10 25
50
75
90
95
98
99
Max
Kitchen - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16- 11
Age (years)
N Mean
Min
. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)
Percentiles
1
2
5 10
25
50
75
90
95
98
Max
99
Dining Room - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)
Age (years)
N
Mean Min
Percentiles
1
2
5 10 25
50
75
90
95
98
99
Max
Bedroom - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)
Age (years) N Mean Mm
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations
Whole Population and Doers Only
Age (years)
N
Mean
Min
Percentiles
1
2
5
10
25
50
75
90
95
98
Max
99
Restaurants - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations
Whole Population and Doers Only (continued)
Age (years) N Mean
Min
Percentiles
1
2 5 10 25
50
Grocery/Convenience Stores, Other Stores, and Malls -
Birth to <1
lto<2
2to<3
3to<6
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Age (years)
Table
1
16-13. Time Spent (minutes/day) in Selected Outdoor Locations
Whole Population and Doers Only
2 5
10 25
Percentiles
50 75
90
95
98
99
School Grounds/Playground - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
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Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Age (years)
Table
1
16-13. Time Spent (minutes/day) in Selected Outdoor Locations
Whole Population and Doers Only (continued)
Percentiles
2 5
10
Pool, River, or Lake -
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-14. Mean Time Spent (minutes/day) Inside and Outside, by Age Category
Age (years) N Average Indoor Minutes2 Average Outdoor Minutesb Average Unclassified
Minutes0
Birth to <1
lto<2
2to<3
3 to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
Whole Population and Doers Only
Age (years)
N
Mean Min
Percentiles
1 2
5
10 25
50
75
90
95
98
99
Max
Car - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
Whole Population and Doers Only (continued)
Age (years) N Mean
Mm
1
Percentiles
2
5 10
25
50
75
90
95
98
Max
99
Bus - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only
Percentiles
1
2
5 10 25 50
75
90
95
98
99
Sleeping/Napping - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Age (years)
N
Mean
Table
1
16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)
2
5 10
25
Percentiles
50
75 90
95
98
99
Attending School Full-Time - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)
Age (years)
N
Mean
Min
Percentiles
1 2
5
10
25
50
75
90
95
98
99
Active Sports - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)
Age (years) N Mean
Min
Percentiles
1 2
5
10 25 50
75
90
95
98
99
Walking - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-17. Number of Showers Taken per Day, by Number of Respondents
Showers per Day
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing
Age (years)
N
Mean Min
> and Showering
Percentiles
1
2
5 10
25
50
75
90
95 98
Max
99
Duration of Bath (minutes)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing and Showering (continued)
Age
(years)
N Mean
Min
Percentiles
1 2 5 10
25
50
75
90
95
98
99
Max
Duration of Shower (minutes)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-19. Range of Number of Times Washing the Hands at
Specified Daily Frequencies by the Number of Respondents
Number of Times/Day
Age (yearsj IN
Birth to <1
1 to<2
2to<3
3 to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-20. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents
Age
(years)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-21. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool
Percentiles
Age (years) IN Mean Mm
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass
Whole Population and Doers only
Age (years)
N
Mean
Min
Percentiles
1
2
5 10
25
50
75 90
95
98
99
Playing on Dirt - Whole Population
Birth to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass
Whole Population and Doers Only (continued)
Age (years) N Mean Min
Percentiles
1
2
5 10 25
50
75
90
95
98
99
Max
Playing on Grass - Whole Population
Birth to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-23. Time Spent (minutes/day) Working or Beinj
Age (years) N
Birth to <1
lto<2
2to<3
3 to<6
6to Near Excessive Dust in the Air
Percentiles
1
_
-
-
0
0
0
2
2
_
-
-
1
0
0
3
5
_
-
-
1
1
1
4
10
_
-
-
2
2
2
7
= Doer sample size.
For sample sizes of 10 or fewer, percentiles were not calculated.
A value of "121" for number of minutes signifies that more than
U.S. EPA re-analysis of source data from U.S.
EPA,
25
_
-
-
8
5
6
16
50
_
-
-
60
45
38
53
75 90 95
_
.
.
121 121 121
121 121 121
113 121 121
121 121 121
Max
98 99
121
121
121
121 121 121
121 121 121
121 121 121
121 121 121
120 minutes were spent.
1996 (NHAPS).
Age
(years)
Ito4
5 to 11
12 to 17
N
Source:
Table
16-24. Time Spent (minutes/day) with Smokers Present
Percentiles
N Mean SD SE
155 367 325 26
224 318 314 21
256 246 244 15
= Doer sample size.
U.S. EPA, 1996 (NHAPS).
Min
5
1
1
5
30
25
10
25
90
105
60
50
273
190
165
75
570
475
360
90
825
775
595
95
1,010
1,050
774
98
1,140
1,210
864
99
1,305
1,250
1,020
Max
1,440
1,440
1,260
Page
16-48
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-25. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of Day
Activity
Market Work
Household Work
Personal Care
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoors
Hobbies
Art Activities
Playing
TV
Reading
Household Conversations
Other Passive Leisure
NA
Percent of Time Accounted for
by Activities Above
N = Sample size.
NA = Unknown.
= No data.
Source: Timmer et al., 1985.
Age (3 to
Weekdays
Boys
(N=118)
16
17
43
81
584
252
14
7
16
25
10
3
4
137
117
9
10
9
22
94
Girls
(N=lll)
0
21
44
78
590
259
19
4
9
12
7
1
4
115
128
7
11
14
25
92
1 1 years)
Age (12 to 17 years)
Weekends
Boys
(N=118)
7
32
42
78
625
-
4
53
23
33
30
3
4
177
181
12
14
16
20
93
Girls
(N=lll)
4
43
50
84
619
-
9
61
37
23
23
4
4
166
122
10
9
17
29
89
Weekdays
Boys
(N=77)
23
16
48
73
504
314
29
3
17
52
10
7
12
37
143
10
21
21
14
93
Girls
(N=83)
21
40
71
65
478
342
37
7
25
37
10
4
6
13
108
13
30
14
17
92
Weekends
Boys
(N=77)
58
46
35
58
550
-
25
40
46
65
36
4
11
35
187
12
24
43
10
88
Girls
(N=83)
25
89
76
75
612
-
25
36
53
26
19
7
9
24
140
19
30
33
4
89
Child-Specific Exposure Factors Handbook
September 2008
Page
16-49
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-26. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different Age Groups
Weekday
Weekend
Activity
3-5
Age (years)
9-11 12-14
15-17
3-5
Age (years)
9-11 12-14
Significant
Effects'
15-17
Market Work - 14 8 14 28
Personal Care 41 49 40 56 60
Household Work 14 15 18 27 34
Eating 82 81 73 69 67
Sleeping 630 595 548 473 499
School 137 292 315 344 314
Studying 2 8 29 33 33
Church 4999 3
Visiting 14 15 10 21 20
Sports 5 24 21 40 46
Outdoor Activities 49 8 7 11
Hobbies 0224 6
Art Activities 5 4 3 3 12
Other Passive Leisure 9126 4
Playing 218 111 65 31 14
TV 111 99 146 142 108
Reading 5 5 9 10 12
Being Read to 2200 0
NA 30 14 23 25 7
4 10
47 45 44
17 27 51
81 80 78
634 641 596
1
55
10
3
8
1
4
6
267
122
4
3
52
2
56
8
30
23
5
4
10
180
136
9
2
7
12
53
13
42
39
3
4
7
92
185
10
0
14
29
60
72
68
604
15
32
22
51
25
8
7
10
35
169
10
0
4
48
51 A,S,AxS(F>M)
60 A,S, AxS (F>M)
65 A
562 A
30
37
56
37
26
3
10
18
21
157
18
0
9
A
A
A (Weekend Only)
A,S (M>F)
A
A,S (M>F)
A,S, AxS (M>F)
A
A
A
NA
Effects are significant for weekdays and weekends,
weekend activities; S = sex effect P<0.05, F>M, M:
interaction, P<0.05.
= Unknown.
= No data.
unless otherwise specified. A = age effect
>F = females spend more time than males,
, P<0.05, for both weekdays and
or vice versa; and AxS = age by sex
Source: Timmer et al., 1985.
Page
16-50
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-27. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week
Indoors"
Outdoors1"
Age Group
Weekday
Weekend
Weekday
Weekend
3 to 5 years
6 to 8 years
9 to 1 1 years
12 to 14 years
15 to 17 years
19.4
20.7
20.8
20.7
19.9
18.9
18.6
18.6
18.5
17.9
2.5
1.8
1.3
1.6
1.4
3.1
2.5
2.3
1.9
2.3
a Time indoors was estimated by adding the average times spent performing indoor activities (household work, personal care, eating,
sleeping, attending school, studying, attending church, watching television, and engaging in conversation) and half the time spent in
each activity which could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing,
reading, and other passive leisure).
b Time outdoors was estimated by adding the average time spent in outdoor activities and half the time spent in each activity which
could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing, reading, and other passive
leisure).
Source: Adapted from Timmer et al., 1985.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-51
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-28. Mean Time Spent (minutes/day) in Various Microenvironments,
Children Ages 12 to 17 Years National and California Surveys
Microenvironment
National Data
Mean (Standard Error)"
All
N=340
Doers Onlyb
Autoplaces
Restaurant/Bar
In-vehicle/Internal Combustion
In-Vehicle/Other
Physical/Outdoors
Physical/Indoors
Work/Study-Residence
Work/Study-Other
Cooking
Other Activities/Kitchen
Chores/Child
Shop/Errands
Other/Outdoors
Social/Cultural
Leisure-Eat/Indoors
Sleep/Indoors
2(1)
9(2)
79(7)
0(0)
32(8)
15(3)
22(4)
159(14)
11(3)
53(4)
91(7)
26(4)
70 (13)
87 (10)
237(16)
548(31)
73
60
88
12
130
87
82
354
40
64
92
68
129
120
242
551
Microenvironment
CARB Data
Mean (Standard Error)"
All
N=183
Doer Onlyb
Autoplaces
Restaurant/Bar
In-Vehicle/Internal Combustion
In-Vehicle/Other
Physical/Outdoors
Physical/Indoors
Work/Study-Residence
Work/Study-Other
Cooking
Other Activities/Kitchen
Chores/Child
Shop/Errands
Other/Outdoors
Social/Cultural
Leisure-Eat/Indoors
Sleep/Indoors
16(8)
16(4)
78(11)
1(0)
32(7)
20(4)
25(5)
196 (30)
3(1)
31(4)
72(11)
14(3)
58(8)
63 (14)
260 (27)
557 (44)
124
44
89
19
110
65
76
339
19
51
77
50
78
109
270
560
a Weighted values.
b Doers only = respondents who reported participating in each activity/microenvironment.
Source: Robinson and Thomas, 1991.
Page
16-52
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-29. Gender and Age Groups
Age Group a
6 to 8 years (males)
6 to 8 years (females)
9 to 1 1 years (males)
9 to 1 1 years(females)
12 to 17 years (males)
12 to 17 years (females)
N
145
124
156
160
98
85
a Children under the age of 6 were excluded because there were
too few responses in the CARB study.
N = Sample size.
Source: Funket al., 1998.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-53
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-30. Assignment of At-Home Activities to Inhalation Rate Levels for Children
Low
Watching child care
Night sleep
Watch personal care
Homework
Radio use
TV use
Records/tapes
Reading books
Reading magazines
Reading newspapers
Letters/writing
Other leisure
Homework/watch TV
Reading/TV
Reading/listen music
Paperwork
Moderate
Outdoor cleaning
Food Preparation
Metal clean-up
Cleaning house
Clothes care
Car/boat repair
Home repair
Plant care
Other household
Pet care
Baby care
Child care
Helping/teaching
Talking/reading
Indoor playing
Outdoor playing
Medical child care
Washing, hygiene
Medical care
Help and care
Meals at home
Dressing
Visiting at home
Hobbies
Domestic crafts
Art
Music/dance/drama
Indoor dance
Conservations
Painting room/home
Building fire
Washing/dressing
Outdoor play
Playing/eating
Playing/talking
Playing/watch TV
TV/eating
TV/something else
Reading book/eating
Read magazine/eat
Read newspaper/eat
Source: Funk et al, 1998.
Page
16-54
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-3 1 . Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents and Children3
Activi
Low
Moderate
High
Highpalticipa
a
b
SD
Source:
Adolescents
Mean
SD
789 230
c
nts
197
1
43
131
11
72
Children
Mean
823
241b
3
58
Time spent engaging in all activities embodied by inhalation rate category (minutes/day).
Significantly different from adolescents (p <0.05).
Represents time spent at-home by individuals participating in high inhalation rate level activities (i
= Standard deviation.
Funketal., 1998.
SD
153
136
17
47
e., doers).
Table 16-32. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents)
Male
Mean SD
Low 775 206
Moderate 181 126
High 2 16
Female
Mean SD
804 253
241 134
0 0
SD = Standard deviation.
Source: Funk et al, 1998.
Child-Specific Exposure Factors Handbook Page
September 2008 16-55
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-33. Comparison of Mean Time Spent (minutes/day) At-Home, by
Activity
Group
Low
Moderate
High
Highpalticipa
a
b
SD
Source:
6-8 Years
Mean
806
259
3
b 77
nt ' '
SD
134
135
17
59
Males
9-11 Years
Mean
860
198
7
70
Time spent engaging in all activities embodied by
Participants in high inhalation rate activities (i.e.,
= Standard deviation.
Funketal, 1998.
SD
157
111
27
54
Gender and Age for Children3
Females
6-8 Years 9-11 Years
Mean
828
256
1
68
inhalation rate category
doers).
SD Mean
155 803
141 247
9 2
11 30
(minutes/day).
SD
162
146
10
23
Page Child-Specific Exposure Factors Handbook
16-56 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-34. Number of Person-Days/mdividualsa for Children in CHAD Database
Age Group All Studies
0 Year
223/199
0 to 6 Months
6 to 12 Months
1 Year
12 to 18
Months
18 to 24
Months
2 Years
3 Years
4 Years
5 Years
6 Years
7 Years
8 Years
9 Years
10 Years
1 1 Years
Total
a
b
Source:
259/238
_
_
317/264
278/242
259/232
254/227
237/199
243/213
259/226
229/195
224/199
227/206
3,009/2,640
California11
104
50
54
97
57
40
112
113
91
98
81
85
103
90
105
121
1,200
Cincinnati'
36/12
15/5
21/7
31/11
_
_
81/28
54/18
41/14
40/14
57/19
45/15
49/17
51/17
38/13
32/11
556/187
NHAPS-Air NHAPS-Water
39
-
-
64
_
_
57
51
64
52
59
57
51
42
39
44
619
44
-
-
67
_
_
67
60
63
64
40
56
55
46
42
30
634
The number of person-days of data are the same as the number of individuals for all studies except for the
Cincinnati study. Since up to three days of activity pattern data were obtained from each participant in this study,
the number of person-days of data is approximately three times the number of individuals.
The California study referred to in this table is the Wiley et al. (1991) study.
The Cincinnati study referred to in this table is the Johnson (1989) study.
= No data.
Hubaletal.,2000.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-57
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-35. Time Spent (hours/day) in Various Microenvironments, by Age
Average Time ± Standard Deviation (Percent >0 Hours)
Age (years)
0
1
2
3
4
5
6
7
8
9
10
11
Source: Hubal
Indoors at Home
19. 6 ±4. 3 (99)
19. 5 ±4.1 (99)
17.8 ±4.3 (100)
18.0 ±4.2 (100)
17.3 ±4. 3 (100)
16. 3 ±4. 0(99)
16.0 ±4.2 (98)
15. 5 ±3. 9 (99)
15. 6 ±4.1 (99)
15.2 ±4. 3 (99)
16.0 ±4.4 (96)
14.9 ±4.6 (98)
etal.,2000.
Outdoors at Home
1.4 ±1.5 (20)
1.6 ±1.3 (35)
2.0 ±1.7 (46)
2.1 ±1.8 (48)
2.4 ±1.8 (42)
2. 5 ±2.1 (52)
2.6 ±2.2 (48)
2.6 ±2.0 (48)
2.1 ±2. 5 (44)
2. 3 ±2. 8 (49)
1.7 ±1.9 (40)
1.9 ±2. 3 (45)
Indoors at School
3. 5 ±3. 7 (2)
3.4 ±3. 8 (5)
6.2 ±3. 3 (9)
5.7 ±2.8 (14)
4. 9 ±3.2 (16)
5.4 ±2. 5 (39)
5. 8 ±2.2 (34)
6. 3 ±1.3 (40)
6.2 ±1.1 (41)
6.0 ±1.5 (39)
5. 9 ±1.5 (39)
5. 9 ±1.5 (41)
Outdoors at Park
1.6 ±1.5 (9)
1.9±2.7(10)
2.0 ±1.7 (17)
1.5 ±0.9 (17)
2. 3 ±1.9 (20)
1.6 ±1.5 (28)
2.1 ±2.4 (32)
1.5 ±1.0 (28)
2.2 ±2.4 (37)
1.7 ±1.5 (34)
2.2 ±2.3 (40)
2.0 ±1.7 (44)
In Vehicle
1.2 ±1.0 (65)
1.1 ±0.9 (66)
1.2 ±1.5 (76)
1.4 ±1.9 (73)
1.1 ±0.8 (78)
1.3 ±1.8 (80)
1.1 ±0.8 (79)
1.1 ±1.1 (77)
1.3 ±2.1 (82)
1.2 ±1.2 (76)
1.1 ±1.1 (82)
1.6 ±1.9 (74)
Page
16-58
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Age
(years)
0
1
2
3
4
5
6
7
8
9
10
11
Source:
Table 16-36
Mean Time Children Spent (hours/day) Doing Various
Macroactivities While Indoors at Home
Mean Time (Percent >0 Hours)
Eat
1.9(96)
1.5(97)
1.3(92)
1.2(95)
1.1(93)
1.1(95)
1.1 (94)
1.0(93)
0.9(91)
0.9(90)
1.0(86)
0.9(89)
Hubal et al
Sleep or
Nap
12.6(99)
12.1 (99)
11.5(100)
11.3(99)
10.9(100)
10.5(98)
10.4(98)
9.9(99)
10.0(96)
9.7(96)
9.6 (94)
9.3 (94)
, 2000.
Shower or
Bathe
0.4 (44)
0.5 (56)
0.5(53)
0.4(53)
0.5 (52)
0.5 (54)
0.4 (49)
0.4 (56)
0.4(51)
0.5 (43)
0.4 (43)
0.4 (45)
Play Games
4.3 (29)
3.9(68)
2.5(59)
2.6(59)
2.6 (54)
2.0 (49)
1.9(35)
2.1 (38)
2.0(35)
1.7(28)
1.7(38)
1.9(27)
Watch TV or
Listen to Radio
1.1(9)
1.8(41)
2.1 (69)
2.6(81)
2.5 (82)
2.3(85)
2.3 (82)
2.5 (84)
2.7(83)
3.1(83)
3.5 (79)
3.1(85)
Read, Write,
Homework
0.4 (4)
0.6(19)
0.6 (27)
0.8 (27)
0.7(31)
0.8(31)
0.9(38)
0.9 (40)
1.0(45)
1.0(44)
1.5(47)
1.1 (47)
Think, Relax,
Passive
3.3 (62)
2.3 (20)
1.4(18)
1.0(19)
1.1(17)
1.2(19)
1.1(14)
0.6(10)
0.7 (7)
0.9(17)
0.6(10)
0.6(10)
Child-Specific Exposure Factors Handbook
September 2008
Page
16-59
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-37
Time Children Spent (hours/day) in Various Microenvironments, by Age
Recast into New Standard Age Categories
Indoors at Home
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
N
123
33
120
287
728
765
2,110
3,283
2,031
1,005
Mean
Time
19.6
20.9
19.6
19.1
19.2
18.2
17.3
15.7
15.5
14.6
Doing
98
100
100
99
99
99
100
99
97
98
Outdoors at Home
Mean
Time
1.7
1.8
0.8
1.1
1.4
1.8
1.9
1.9
1.7
1.4
%
Doing
21
9
8
15
34
38
43
40
30
20
Indoors at School
Mean
Time
4.3
0.2
7.8
7.6
6.4
6.8
5.9
6.5
6.6
5.7
Doing
3
3
7
8
9
12
26
44
45
33
Outdoors at Park
Mean
Time
1.3
1.6
1.3
1.8
1.5
2.1
1.6
2.1
2.6
3.1
Doing
3
9
6
5
5
7
10
17
15
10
In Vehicle
Mean
Time
1.3
1.3
1.1
1.3
1.1
1.3
1.3
1.1
1.3
1.7
Doing
63
27
14
14
27
28
29
29
42
90
N = Sample size.
Source: Based on data source used by
Hubal et al
, 2000 (CHAD).
Page
16-60
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-38. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
Recast Into New Standard Age Categories
Eat
Mean
Time
Birth to <1 month 123 2.2
1 to <3 months 33 2.4
3 to <6 months 120 2.0
6 to <12 months 287 1.8
1 to <2 years 728 1.7
2 to <3 years 765 1.5
3 to <6 years 2,110 1.4
6to
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-39.
Number and Percentage of Respondents with Children and Those Reporting
Outdoor Playa Activities in both Warm and Cold Weather
Respondents ™-1JT)1 a
vv.V.1. -i j Child Players3
with Children J
Source
SCS-II
SCS-II
sample
Total
a
b
N
Source:
N
base 197
483
680
N %
128 65.0
372 77.0
500 73.5
Child non-
Players
N %
69 35.0
111 23.0
180 26.5
Warm Cold
Weather Weather Players in Both Seasons
Playersa PlayerS
N N
127 100
370 290
497 390
"Play" and "player" refer specifically to participation in outdoor play on bare dirt or mixed
Does not include three "Don't know/refused" responses regarding warm weather play.
= Sample size.
Wong etal, 2000.
%
50.8
60.0
57.4
grass and dirt.
Page
16-62
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-40. Play Frequency and Duration for all Child Players (from SCS-II data)
Statistic
N
5th Percentile
50th Percentile
95th Percentile
Frequency
(days/week)
372
1
3
7
Cold Weather
Duration
(hours/day)
374
1
1
4
Total
(hours/week)
373
1
5
20
Frequency
(days/week)
488
2
7
7
Warm Weather
Duration
(hours/day)
479
1
3
8
Total
(hours/week)
480
4
20
50
N = Sample size.
Source: Wong
etal.,2000.
Table 16-41.
Hand Washing and Bathing Frequency for all Child Players (from SCS-II data)
Cold Weather
Statistic
N
5th Percentile
50th Percentile
95th Percentile
N = Sample size.
Source: Wong et al, 2000.
Hand washing
(times/day)
329
2
4
10
Bathing
(times/week)
388
2
7
10
Warm Weather
Hand washing
(times/day)
433
2
4
12
Bathing
(times/week)
494
3
7
14
Child-Specific Exposure Factors Handbook
September 2008
Page
16-63
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Data
NHAPS
SCS-II
a
b
Source:
Table 16-42.
Source
Cold Weather
114
102
NHAPS and SCS-II Play Duration3 Comparison
Mean Play Duration
(minutes/day)
Warm Weather
109
206
Selected previous day activities in NHAPS; average day outdoor play on
II.
2x2 Chi-square test for contingency between NHAPS and SCS-II.
Wong etal., 2000.
••2 testb
Total
223 pO.OOOl
308
bare dirt or mixed grass and dirt in SCS-
Table 16-43. NHAPS and SCS-II Hand Wash Frequency3 Comparison
Data
Source
NHAPS
SCS-II
NHAPS
SCS-II
a
b
Source:
Percenl
Season
Cold
Cold
Warm
Warm
0
3
1
3
0
Selected previous day
II.
Results are reported
2x2 Chi-square test
Wong etal., 2000.
1-2
18
16
18
12
3-5
51
50
51
46
activities in NHAPS;
b Reporting Frequency (times/day) of:
6-9
17
11
15
16
average day
10-19
7
7
7
10
20-29
1
1
2
1
outdoor play on bare dirt
as percentage of total for clarity. Incidence data
for contingency between NHAPS and SCS-II.
were used in
30+
1
0
1
0
or mixed g
statistical
"Don't ..2
Know"
3
15 P =
4
13 P =
rass and dirt in
tests.
test0
0.06
0.001
SCS-
Page
16-64
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
Table 16-44. Time Spent (minutes/day) Outdoors
Based on CHAD Data (Doers Only)'
Age Group
Time Spent Outdoors
Minimum
Median
Maximum
Mean
SD
COV(%)
Participation1" (%)
<1 month
1 to 2 months
3 to 5 months
6 to 11 months
1 year
2 years
3 to 5 years
6 to 10 years
11 to 15 years
16 to 17 years
18 to 20 years
57
5
27
91
389
448
1,336
2,216
1,423
356
351
2
4
10
5
1
1
1
1
1
1
1
60
60
90
60
75
100
120
120
110
85
70
700
225
510
450
1,035
550
972
1,440
1,440
1,083
788
99
102
114
91
102
134
146
162
154
129
132
124
90
98
76
99
108
117
144
163
145
155
125
84
97
106
112
118
47
36
23
33
58
64
68
71
73
81
72
SD
COV
Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis.
Participation rates or percent of sample days in the study spending some time (>0 minutes per day) outdoors. The mean time spent
outdoors for the age group may be obtained by multiplying the participation rate by the mean time shown above.
= Standard deviation.
= Coefficient of variation (SD/mean x 100).
Source: Graham and McCurdy, 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-65
-------
Child-Specific Exposure Factors Handbook
Chapter 16 - Activity Factors
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Page Child-Specific Exposure Factors Handbook
16-66 September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-46. Time Spent (minutes/day) Indoors
Based on CHAD Data (Doers Only)"
Time Spent Indoors
F
<1 month
1 to 2 months
3 to 5 months
121
14
115
6 to 11 months 278
1 year
2 years
3 to 5 years
6 to 1 0 years
1 1 to 15 jei
rs
1 6 to 17 years
18 to 20 jei
rs
668
700
1,977
3,118
1,939
438
485
Minimum
490
1,125
840
840
315
290
23
7
69
161
512
Median
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
" Only data for individuals that spent >0
b Participation rates
indoors for the age
N
SD
COV
Source:
=
Sample size.
or percent of sample
380
380
385
370
350
319
307
292
300
296
310
Maximum
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
440
440
440
440
440
440
440
440
440
440
440
time indoors and had 30 or
days
group may be obtained by
in the study spending
multiply
ing the part
Mean
1,336
1,348
1,359
1,353
1,324
1,286
1,276
1,256
1,255
1,251
1,242
nVfO/,1! Pst-tif-
SD
137
105
93
81
107
138
136
153
160
171
180
more records are included in the
some time (;
cipation rate
S0 minutes per day)
10
8
7
6
8
11
11
12
13
14
15
analysis.
indoors. The mean
(as a decimal) by the mean time shown
pation (%)
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
99.8
100.0
100.0
time spent
above.
= Standard deviation.
= Coefficient of variation (SD/mean
x 100).
Graham and McCurdy, 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-67
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-47. Time Spent (minutes/day) in Motor Vehicles
Based on CHAD Data (Doers Only)3
Time Spent in Motor Veh
Minimum Median
<1 month 80
1 to 2 months 9
3 to 5 months 75
6 to 1 1 months 226
1 year 515
2 years 581
3 to 5 years 1,702
6 to 10 years 2,766
11 to 15 years 1,685
16 to 17 years 400
18 to 20 years 449
o
20
13
4
1
2
1
1
1
4
4
68
83
60
51
52
54
55
58
60
73
76
Maximum
350
105
335
425
300
955
1,389
1,214
825
1,007
852
a Only data for individuals that spent >0 time in motor vehicles and
b Participation rates or percent of sample days in the study spending
time spent in motor vehicles for the age group may be obtained by
time shown above.
N = Sample size.
SD = Standard deviation.
COV = Coefficient of variation (SD/mean x
Source: Graham and McCurdy
2004.
100).
ides
Mean
86
67
71
62
67
73
70
71
76
92
109
SD
68
32
49
47
50
76
70
68
74
90
106
)V(%) Participation' (%)
79
48
69
76
76
104
99
95
97
98
98
had 30 or more records are included in the analysis
some time (>0 minutes per day) in motor vehicles.
multiplying the participation rate (as a decimal) by
66
64
65
81
77
83
86
89
87
91
93
The mean
the mean
Page
16-68
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
&
(JKb
Table 16-48. Time Spent (minutes/two-day period)8 in Various Activities by
Panel Study of Income Dynamics (PSID), 1997 Child Development
Boy s(N= 1,444)
Age Group Standard
Mean ^ . .
Deviation
Television Use
1 to 5 years 197 168
6 to 8 years 263 165
9 to 12 years 251 185
Electronic Game Use
1 to 5 years 8 38
6 to 8 years 44 113
9 to 12 years 57 102
Computer Use
1 to 5 years 7 28
6 to 8 years 13 43
9 to 12 years 27 71
Print Use"
1 to 5 years 21 32
6 to 8 years 20 37
9 to 12 years 19 47
Highly Active Activities'
1 to 5 years 42 74
6 to 8 years 107 123
9 to 12 years 137 149
Moderately Active Activities'1
1 to 5 years 55 81
6 to 8 years 31 65
9 to 12 years 40 73
Sedentary Activities'
1 to 5 years 55 71
6 to 8 years 75 77
9 to 12 years 110 109
Children Participating in the
Supplement (CDS)
Girls (N= 1,
Mean8
184
239
266
5
14
18
7
8
15
23
20
29
34
62
63
59
37
46
54
80
122
387)
Standard
Deviation
163
159
194
40
39
47
35
28
43
34
32
56
78
92
88
92
69
89
71
84
111
" Means represent minutes spent in each activity over a 2-day period (one weekday and one weekend
day).
b Print use represents time spent using print media including reading and being read to.
' Includes all sport activities such as basketball, soccer, swimming, running or bicycling.
11 Includes activities such as singing, camping, taking music lessons, fishing, and boating.
' Includes activities such as playing board games, doing puzzles, talking on the phone, and relaxing.
N = Sample size.
Source: Vanderwater et al, 2004.
Child-Specific Exposure Factors Handbook
September 2008
Page
16-69
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-49.
Mean Time Spent (minutes/day) in
Various Activity Categories, by Age -
2002-2003
Activity Category
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
6 to 8
years
0
25
68
60
607
406
29
4
16
10
6
1
8
94
9
74
11
2
6
4
9 to 11
years
0
32
66
57
583
398
39
5
25
17
6
1
7
106
10
56
12
1
10
8
12 to 14
years
1
38
68
54
542
395
49
5
25
33
4
1
7
111
24
45
11
0
25
4
15 to 17
years
22
39
73
49
515
352
50
3
53
33
6
2
4
115
39
35
7
0
38
6
Weekday
1981-1982
6 to 8
years
-
15
49
81
595
292
8
9
-
24
9
2
4
99
-
Ill
5
-
-
-
9 to 11
years
-
18
40
73
548
315
29
9
-
21
8
2
3
146
-
65
9
-
-
-
12 to 14
years
-
27
56
69
473
344
33
9
-
40
7
4
3
142
-
31
10
-
-
-
15 to 17
years
28
34
60
67
499
314
33
3
-
46
11
6
12
108
-
14
12
-
-
-
= Data not provided.
Source: Justeret al, 2004
Page
16-70
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-50. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day
2002-2003
Activity Category
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
6 to 8
years
0
81
78
89
666
3
5
41
61
23
12
2
11
155
14
163
14
1
12
9
9 to 11
years
0
91
72
80
644
6
9
37
66
40
12
1
7
184
15
134
15
1
19
8
12 to 14
years
9
100
73
69
633
7
20
36
58
40
12
4
9
181
40
148
13
0
39
9
15 to 17
years
39
79
77
64
629
7
24
30
91
27
11
5
6
162
54
59
7
0
58
11
1981-1982
6 to 8
years
-
27
45
80
641
-
2
56
-
30
23
5
4
136
-
180
9
-
-
-
9 to 11
years
-
51
44
78
596
-
12
53
-
42
39
3
4
185
-
92
10
-
-
-
12 to 14
years
-
72
60
68
604
-
15
32
-
51
25
8
7
169
-
35
10
-
-
-
15 to 17
years
48
60
51
65
562
-
30
37
-
37
26
3
10
157
-
21
18
-
-
-
= Data not provided.
Source: Juster et al., 2004
Child-Specific Exposure Factors Handbook
September 2008
Page
16-71
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-51 . Mean Time Spent (minutes/week) in
Various Activity Categories for Children, Ages 6 to 17 Years
Activity Categ
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
Source: Juster et al.,
ory 2002-2003
53
343
493
426
4,092
1,947
238
94
287
179
50
12
48
876
166
485
77
5
165
45
2004.
1981-1982
126
223
356
508
3,758
1,581
158
125
132
244
100
27
40
944
39
440
69
3
0
1,206
Page
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors
Table 16-52. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years
Activity
hours/day
Male
Female
All
Personal Carea
Eating and Drinkingb
Household Activities^
Purchasing Goods and Servicesd
Caring for and Helping Household Members6
Caring for and Helping Non-Household Membersf
Working on Work-related Activitiesg
Educational Activities11
Organizational Civic and Religious Activities1
Leisure and SportsJ
total leisure and sports - weekdays
total leisure and sports - weekends
sports, exercise, recreation - weekdays
sports, exercise, recreation - weekends/holidays
socializing and communicating - weekdays
socializing and communicating, - weekends/holidays
watching TV - weekdays
watching TV - weekends/holidays
reading - weekdays
reading - weekends/holidays
relaxing, thinking - weekdays
relaxing, thinking - weekends/holidays
playing games, computer use for leisure - weekdays
playing games, computer use for leisure - weekends/holidays
other sports/leisure including travel - weekdays
other sports/leisure including travel - weekends/holidays
Telephone Calls, Mail, and E-mailk
Other Activities not Elsewhere Classified1
10.26
1.02
0.61
).34
10.34
1.11
0.92
0.74
0.19
0.23
1.24
3.51
0.33
4.75
10.30
1.07
0.76
0.56
0.15
0.21
1.39
3.29
0.34
5.40
4.85
6.68
0.58
0.69
0.76
1.32
1.96
2.45
0.11
0.11
0.15
0.13
0.69
1.00
0.61
0.98
0.33
0.22
Includes sleeping, bathing, dressing, health-related self care, and personal and private activities.
Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent purchasing meals, snacks,
or beverages.
Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and renovation.
Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair salons, barbershops, day
spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry cleaning, vehicle maintenance, construction), and
government services (e.g., applying for food stamps, government required licenses or paying fines).
Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to child or adult,
attending to health care needs, dropping off, picking up or waiting for children).
Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with children, reading to child
or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include activities done through a volunteer
organization.
Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related activities.
Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, except sports.
Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through participating in
religious or spiritual activities (e.g., church choir, youth groups, praying).
Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category.
Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related to work or
volunteering.
Includes residual activities that could not be coded or where information was missing.
U.S. DL.2007.
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Chapter 16- Activity Factors
Table 16-53. Mean Time Spent (minutes/day) in Moderate-to- Vigorous Physical Activity
Age (years)
9
11
12
15
SD
Source:
Boys
190.8(53.2)
133.0(42.9)
105.3(40.2)
58.2(31.8)
= Standard deviation.
Nader et al. 2008-
Weekday
Mean (SD)
Girls
173.3(46.4)
115.6(36.3)
86.0(32.5)
38.7(23.6)
Both
181.8(50.6)
124.1(40.6)
95.6(37.8)
49.2(29.9)
Boys
184.3(68.6)
127.1(59.5)
93.4(55.3)
43.2(38.0)
Weekend
Mean (SD)
Girls
173.3(64.3)
112.6(53.2)
73.9(45.8)
25.5(23.3)
Both
178.6(66.6)
119.7(56.8)
83.6(51.7)
35.1(33.3)
Page
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Chapter 17 - Consumer Products
TABLE OF CONTENTS
17 CONSUMER PRODUCTS 17-1
17.1 INTRODUCTION 17-1
17.2 RECOMMENDATIONS 17-2
17.3 CONSUMER PRODUCTS USE STUDIES 17-2
17.3.1 CTFA, 1983 17-2
17.3.2 U.S. EPA, 1996 17-2
17.3.3 Bass et al., 2001 17-3
17.3.4 Loretz et al., 2005 17-4
17.3.5 Loretz et al., 2006 17-4
17.3.6 Loretz et al., 2008 17-5
17.3.7 Sathyanarayana et al., 2008 17-5
17.4 REFERENCES FOR CHAPTER 17 17-5
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Chapter 17 - Consumer Products
LIST OF TABLES
Table 17-1. Consumer Products Commonly Found in Some U.S. Households 17-7
Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products 17-10
Table 17-3. Number of Minutes Spent in Activities Working With or Near Freshly Applied
Paints (minutes/day) 17-13
Table 17-4. Number of Minutes Spent in Activities Working With or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day) 17-13
Table 17-5. Number of Minutes Spent in Activities (at home or elsewhere) Working With
or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) 17-13
Table 17-6. Number of Minutes Spent in Activities Working With or Near Glue (minutes/day) 17-14
Table 17-7. Number of Minutes Spent in Activities Working With or Near Solvents, Fumes or
Strong Smelling Chemicals (minutes/day) 17-14
Table 17-8. Number of Minutes Spent in Activities Working With or Near Stain or Spot Removers
(minutes/day) 17-14
Table 17-9. Number of Minutes Spent in Activities Working With or Near Gasoline or
Diesel-powered Equipment, Besides Automobiles (minutes/day) 17-15
Table 17-10. Number of Minutes Spent in Activities Working with or Near Pesticides,
Including Bug Sprays or Bug Strips (minutes/day) 17-15
Table 17-11. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at
Specified Daily Frequencies 17-15
Table 17-12. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item
Such as Deodorant or Hair Spray at Specified Daily Frequencies 17-16
Table 17-13. Number of Respondents Using a Humidifier at Home 17-16
Table 17-14. Number of Respondents Indicating that Pesticides Were Applied by the Professional at
Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-16
Table 17-15. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-17
Table 17-16. Number of Respondents Indicating that Pesticides Were Applied by a
Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified
Frequencies 17-17
Table 17-17. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 17-17
Table 17-18. Household Demographics, and Pesticide Types, Characteristics, and Frequency of
Pesticide Use 17-18
Table 17-19. Frequency of Use of Cosmetic Products 17-19
Table 17-20. Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream 17-20
Table 17-21. Frequency of Use of Personal Care Products 17-22
Table 17-22. Average Amount of Product Applied per Application (grams) 17-23
Table 17-23. Average Amount of Product Applied per Use Day (grams) 17-24
Table 17-24. Average Number of Applications Per Use Day 17-25
Table 17-25. Average Amount of Product Applied Per Use Day (grams) 17-26
Table 17-26. Average Amount of Product Applied Per Application (grams) 17-27
Table 17-27. Characteristics of the Study Population and the Percent Using Selected Baby Care
Products 17-28
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Chapter 17 - Consumer Products
17 CONSUMER PRODUCTS
17.1 INTRODUCTION
Consumer products may contain toxic or
potentially toxic chemical constituents to which
children may be exposed as a result of their use. For
example, household cleaners can contain ammonia,
alcohols, acids, and/or organic solvents which may
pose health concerns. Potential routes of exposure to
consumer products or chemicals released from
consumer products during use include ingestion,
inhalation, and dermal contact. Children can be in
environments where adults use household consumer
products such as cleaners, solvents, and paints. As
such, children can be passively exposed to chemicals
in these products. Since children spend a large
amount of time indoors, the use of household
chemicals in the indoor environment can be a principal
source of exposure (Franklin, 2008).
Very little information is available on the
exact way the different kinds of products are used by
consumers, including the many ways in which these
products are handled, the frequency and duration of
contact, and the measures consumers may take to
minimize exposure/risk (Steenbekkers, 2001). In
addition, the factors that influence these behaviors are
not well studied, but some studies have shown there is
a large variation in behavior between persons
(Steenbekkers, 2001). This chapter presents available
information on the amounts, frequency, and duration
of use for various consumer products found in typical
households.
The studies presented in the following
sections represent readily available surveys from which
data were collected on the frequency and duration of
use and amount of use of cleaning products, household
solvent products, cosmetic and other personal care
products, and pesticides. For a more detailed
presentation of data on the use of consumer products
among the general population, the reader is referred to
the Exposure Factors Handbook (U.S. EPA, 1997).
The National Library of Medicine Household
Products Database is a consumer guide that provides
information on the potential health effects of chemicals
contained in more than 7,000 common household
products used inside and around the home. Although,
this database does not provide exposure factor
information, it contains information on chemical
ingredients and their percentages in consumer
products, which products contain specific chemical
ingredients, acute and chronic effects of chemical
ingredients, and manufacturer information. These
data could be useful when conducting an exposure
assessment for a specific chemical/active ingredient.
The product categories are: auto products, inside the
home, pesticides, landscape/yard, personal care, home
maintenance, arts and crafts, pet care, and home office.
The database can be searched by product name,
product type, manufacturer, and ingredient. This
database can be found at http ://hpd.nlm.nih. gov.
Table 17-1 provides a list of household consumer
products found in some U.S. households (U.S. EPA,
1987). It should be noted, however, that this list was
compiled by U.S. EPA in 1987 and consumer use of
some products listed may have changed (e.g., aerosol
product use has declined). Therefore, the reader is
referred to the National Library of Medicine database
as a source of more current information.
The U.S. EPA Source Ranking Database
(SRD) is another source of information on consumer
products, but does not provide exposure factor data.
SRD can be used to perform systematic screening-level
reviews of more than 12,000 potential indoor pollution
sources to identify high-priority product and material
categories for further evaluation. It also can be used to
identify products that contain a specific chemical.
Information on the SRD can be found at:
http://www.epa.gov/oppt/exposure/pubs/srd.htm.
The Soaps and Detergents Association (SD A)
developed a peer-reviewed document that presents
methodologies and specific exposure information that
can be used for screening-level risk assessments from
exposures to high production volume chemicals. The
document addresses the use of consumer products,
including laundry, cleaning, and personal care
products. It includes data for daily frequency of use,
and amount of product used. The data used were
compiled from a number of sources including, the
Exposure Factors Handbook (U.S. EPA, 1997),
cosmetic associations, and data from the SDA. The
document entitled "Exposure and Risk Screening
Methods for Consumer Product Ingredients" can be
found on the SDA website under:
http://www.clcaninglO 1 .com/filcs/Exposurc and
Risk Screening Methods for Consumer Product
Ingrcdicnls.pdf.
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Chapter 17 - Consumer Products
17.2 RECOMMENDATIONS
Due to the large range and variation among
consumer products and their exposure pathways, it is
not feasible to recommend specific exposure values as
has been done in other chapters of this handbook. The
user is referred to the contents/references of this
chapter and Chapter 17 of the Exposure Factors
Handbook (U.S. EPA, 1997) to derive appropriate
exposure factors. The following sections of this
chapter provide summaries of data from surveys
involving the use of consumer products.
17.3 CONSUMER PRODUCTS USE STUDIES
17.3.1 CTFA, 1983 - Cosmetic, Toiletry, and
Fragrance Association, Inc. - Summary of
Results of Surveys of the Amount and
Frequency of Use of Cosmetic Products by
Women
The Cosmetic, Toiletry, and Fragrance
Association Inc. (CTFA, 1983), a major manufacturer
and a market research bureau, conducted surveys to
obtain information on frequency of use of various
cosmetic products. Three surveys were conducted to
collect data on the frequency of use of various cosmetic
products and selected baby products. In the first of
these three surveys CTFA (1983) conducted a one-
week prospective survey of 47 female employees and
relatives of employees between the ages of 13 and 61
years. In the second survey, a cosmetic manufacturer
conducted a retrospective survey of 1,129 of its
customers. The third survey was conducted by a
market research bureau which sampled 19,035 female
consumers nationwide over a 9-1/2 month period. Of
the 19,035 females interviewed, responses from only
9,684 females were tabulated (CTFA, 1983). The third
survey was designed to reflect the sociodemographic
(i.e., age, income, etc) characteristics of the entire U.S.
population. The respondents in all three surveys were
asked to record the number of times they used the
various products in a given time period (i.e., a week, a
day, a month, or a year).
To obtain the average frequency of use for
each cosmetic product, responses were averaged for
each product in each survey. Thus, the averages were
calculated by adding the reported number of uses per
given time period for each product, dividing by the
total number of respondents in the survey, and then
dividing again by the number of days in the given time
period (CTFA, 1983). The average frequency of use of
cosmetic products was determined for both "users" and
"non-users." The frequency of use of baby products
was determined among "users" only. The upper 90th
percentile frequency of use values were determined by
eliminating the top ten percent most extreme
frequencies of use. Therefore, the highest remaining
frequency of use was recorded as the upper 90th
percentile value. Table 17-2 presents the amount of
product used per application (grams) and the average
and 90th percentile frequency of use per day for baby
products and various cosmetic products for all the
surveys.
An advantage of the frequency data obtained
from the third survey (market research bureau) is that
the sample population was more likely to be
representative of the U.S. population. Another
advantage of the third dataset is that the survey was
conducted over a longer period of time when compared
with the other two frequency datasets. Also, the study
provided empirical data which will be useful in
generating more accurate estimates of consumer
exposure to cosmetic products. In contrast to the large
market research bureau survey, the CTFA employee
survey is very small and both that survey and the
cosmetic company survey are likely to be biased toward
high end users. Therefore, data from these two surveys
should be used with caution. While the data in this
study were not tabulated by age of the population, the
study included some individuals in the age groups of
interest for this handbook.
17.3.2 U.S. EPA, 1996 - National Human Activity
Pattern Survey (NHAPS)
U.S. EPA (1996) collected data on the
duration and frequency of selected activities and the
time spent in selected microenvironments via 24-hour
diaries as part of the National Human Activity Pattern
Survey (NHAPS). More than 9,000 individuals from
various age groups in 48 contiguous states participated
inNHAPS. Children represented approximately 2,000
of the respondents (499 respondents under 5 years of
age; 703 respondents between 5 and 11 years; 589
respondents between 12 and 17 years; and 799
respondents between 18 and 24 years). The survey was
conducted between October 1992 and September 1994.
Individuals were interviewed to categorize their 24-
hour routines (diaries) and/or to answer follow-up
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Chapter 17 - Consumer Products
questions that were related to exposure events. For
children under 10 years of age, adult members of the
households gave proxy interviews. Demographic,
including socioeconomic (gender, age, race, education,
etc.), geographic (census region, state, etc.), and
temporal (day of week, month, season) data were
included in the study. Data were collected for a
maximum of 82 possible microenvironments and 91
different activities.
As part of the survey, data were also collected
on duration and frequency of use of selected consumer
products. Tables 17-3 through 17-10 present data on
the number of minutes that survey respondents spent in
activities working with or being near certain consumer
products, including: freshly applied paints; household
cleaning agents such as scouring powders or ammonia;
floor wax, furniture wax, or shoe polish; glue; solvents,
fumes, or strong smelling chemicals; stain or spot
removers; gasoline, diesel-powered equipment, or
automobiles; and pesticides, bug sprays, or bug strips.
These data are presented according to the age
categories used in NHAPS (1 to 4 years, 5 tol 1 years,
12 to!7 years, and 18 to 64 years). Table 17-11
through 17-15 present data on the number of
respondents in these age categories that used
fragrances, aerosol sprays, pesticides (professionally-
applied and consumer-applied), and humidifiers.
Because the age categories used by the study authors
did not coincide with the standardized age categories
recommended in U. S. EPA (2005) and used elsewhere
in this handbook, the source data from NHAPS on
pesticide use (professionally applied and consumer-
applied) were re-analyzed by U.S. EPA to generate
data for the standardized age categories. These data
are presented in Tables 17-16 and 17-17 for age groups
less than 1 year, 1 to <2 years, 2 to <3 years, 3 to <6
years, 6 to <11 years, 11 to < 16 years, and 16 to <21
years. Data for subsets of the first year of life (e.g., 1
to 2 months, 3 to 5 months, etc.) were not available.
As discussed in previous chapters of this
handbook that used NHAPS as a data source, the
primary advantage of NHAPS is that the data were
collected for a large number of individuals and the
survey was designed to be representative of the U.S.
general population. However, due to the wording of
questions in the survey, precise data were not available
for consumers who spent more than 60 or 120 minutes
(depending on the activity) using some consumer
products. This prevents accurate characterization of
the high end of the distribution and may also introduce
error into the calculation of the mean.
17.3.3 Bass et al., 2001 - What's Being Used at
Home: A Household Pesticide Survey
Bass et al. (2001) conducted a survey to assess
the use of pesticide products in homes with children in
March 1999. The study obtained information on what
pesticides were used, where they were used, and how
frequently they were used. A total of 107 households
in Arizona that had a least one child less than ten
years of age in the household, and had used a pesticide
within the last six months, were surveyed (Bass et al.,
2001). The survey population was predominantly
female Hispanic and represented a survey response rate
of approximately 74 percent. Study participants were
selected by systematic random sampling. Among the
households sampled, 3 percent had one child less than
10 years old, 42 percent had two children less than 10
years old, and 23 percent had three to five children in
this age bracket. Pesticide use was assessed by a one-
on-one interview in the home. Survey questions
pertained to household pesticides used inside the house
for insect control and outside the house for the control
of weeds in the garden and to repel animals from the
garden. As part of the interview, information was
gathered on the frequency of use.
Table 17-18 presents information on the type,
characteristics, and frequency of pesticide use, as well
as information on the demographics of the survey
population. A total of 148 pesticide products were
used in the 107 households surveyed. Respondents had
used pesticides in the kitchen, bathroom, floors,
baseboards, and cabinets with dishes or cookware. The
frequency of use data showed the following: 13.5
percent of the households used pesticides more than
once per week; 18.2 percent used the products once per
week; 28.4 percent used the products once per month;
15.5 percent used the products once in three months;
10.8 percent used the products once in six months; and
8.8 percent used the products once per year (Bass et
al., 2001).
Although this study was limited to a selected
area in Arizona, it provides useful information on the
frequency of use of pesticides among households with
children. This may be useful for populations in similar
geographical locations where site-specific data are not
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Chapter 17 - Consumer Products
available. However, these data are the result of a
community-based survey and are not representative of
the U.S. general population.
17.3.4 Loretz et al., 2005 - Exposure Data for
Cosmetic Products: Lipstick, Body Lotion,
and Face Cream
Loretz et al. (2005) conducted a nationwide
survey to estimate the usage (i.e., frequency of
application and amount used per application) of
lipstick, body lotion, and face cream. The study was
conducted from April to June 2000. Three hundred
and sixty study subjects were recruited in ten U.S.
cities (Atlanta, Georgia; Boston, Massachusetts;
Chicago, Illinois; Denver, Colorado; Houston, Texas;
Minneapolis, Minnesota; St. Louis, Missouri; San
Bernadino, California; Tampa, Florida; and Seattle,
Washington). The survey participants were women,
ages 19-65 years, who regularly used the products of
interest. Typical cosmetic formulations of the three
product types were weighed and provided to the
women for use over a two-week period. Subjects
recorded information on product usage (e.g., whether
the product was used, number of applications, time of
applications) on a daily basis in a diary provided to
them. At the end of the two-week period, unused
portions of product were returned and weighed. The
amount of product used was estimated as the difference
between the weight of product at the beginning and
end of the survey period. Of the 360 subjects recruited,
86.4percent, 83.3 percent, and 8 5.6 percent completed
the study and returned the diaries for lipstick, body
lotion, and face cream, respectively (Loretz et al.,
2005).
The survey data are presented in Table 17-19
and 17-20. Table 17-19 provides the mean, median,
and standard deviations for the frequency of use.
Table 17-20 provides distribution data for the total
amount applied, the average amount applied per use
day, and the average amount applied per application.
An advantage of this study is that the survey
population covered a diverse geographical area of the
U. S. and was not based on recall data. A limitation of
the study is that the short duration (two weeks) may
not accurately reflect long-term usage patterns.
Another limitation is that the study only included
women who already used the products; therefore, the
usage patterns are not representative of the entire
female population. Also, the data are not presented by
age group, but the study does provide information on
a population that includes the ages of interest for this
document. Data for children could not be separated
from that of the rest of the survey population.
17.3.5 Loretz et al., 2006 - Exposure Data for
Personal Care Products: Hairspray, Spray
Perfume, Liquid Foundation, Shampoo,
Body Wash, and Solid Antiperspirant
Loretz et al. (2006) conducted a nationwide
survey to determine the usage (i.e., frequency of use
and amount used) of hairspray, spray perfume, liquid
foundation, shampoo, body wash, and solid
antiperspirant. The survey was similar to that
described by Loretz et al. (2005). This study was
conducted between October 2001 and October 2002.
A total of 360 women were recruited from ten U.S.
cities (Atlanta, Georgia; Boston, Massachusetts;
Chicago, Illinois; Denver, Colorado; Houston, Texas;
Minneapolis, Minnesota; St. Louis, Missouri; San
Bernadino, California; Tampa, Florida; and Seattle,
Washington). The survey participants were women,
ages 19-65 years old, who regularly used the test
products. Subjects kept daily records on product usage
(whether the product was used, number of applications,
time of applications) in a diary. For spray perfume,
liquid foundation, and body wash, subjects recorded
the body area(s) where these products were applied.
For shampoo, subjects recorded information on their
hair type (length, thickness, oiliness, straight or curly,
and color treated or not). At the end of the two week
period, unused portions of products were returned and
weighed. Of the 360 subjects recruited per product,
the study was completed by 329 participants for
hairspray, 327 for spray perfume, 326 for liquid
foundation, and 340 participants for shampoo, body
wash, and solid antiperspirant.
The survey data are presented in Tables 17-21
through 17-23. Table 17-21 provides the minimum,
maximum, mean, and standard deviations for the
frequency of use. Table 17-22 provides percentile
values for the amount of product applied per
application. Table 17-23 provides distribution data for
the amount applied per use day.
An advantage of this study is that the survey
population covered a diverse geographical range of the
U.S. and did not rely on recall data. A limitation of
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Chapter 17 - Consumer Products
the study is that the short duration (two weeks) may
not accurately reflect long-term usage patterns.
Another limitation is that the study only included
women who already used these products; therefore, the
usage patterns are not entirely representative of the
entire female population. Also, the data are not
presented by age group, but the study does provide
information on a population that includes the ages of
interest for this document. Data for children could not
be separated from that of the rest of the survey
population.
17.3.6 Loretz et al., 2008 - Exposure Data for
Cosmetic Products: Facial Cleanser, Hair
Conditioner, and Eye Shadow
Loretz et al. (2008) used the data from a study
conducted in January 2005 to estimate frequency of use
and usage amount for facial cleanser, hair conditioner,
and eye shadow. The study was conducted in a similar
manner as Loretz et al. (2005; 2006). A total of 360
women, ages 18 to 69 years of age, were recruited by
telephone to provide diary records of product use over
a two-week period. The study subjects were
representative of four U.S. Census regions (Northeast,
Midwest, South, and West). A total of 295, 297, and
299 completed the study for facial cleanser, hair
conditioner, and eye shadow, respectively.
The participants recorded daily in a diary
whether the product was used that day, the number of
applications, and the time of application(s) over a two-
week period. Products were weighed at the start and
completion of the study to determine the amount used.
A statistical analysis of the data was conducted to
provide summary distributions of use patterns,
including number of applications, amount used per
day, and amount of product used per application for
each product. Data on the number of applications per
day are provided in Table 17-24. The average
amounts of product applied per use day are shown in
Table 17-25, and the average amounts of product
applied per application are shown in Table 17-26.
The advantages of this study are that it is
representative of the U.S. female population for users
of the products studied, it provides data for frequency
of use and amount used, and it provides distribution
data. The limitations of the study are that the data
were not provided by age group, but included ages in
the study group that are relevant for this handbook. In
addition, the participants were regular users of the
product, so the amount applied and the frequency of
use may be higher than for other individuals who may
use the products. According to Loretz et al. (2008)
"variability in amount used by the different subjects is
high, but consistent with the data from other cosmetic
and personal care studies." The authors also noted
that it was not clear if the high-end users of products
represented true usage.
17.3.7 Sathyanarayana et al., 2008 - Baby Care
Products; Possible Sources of Infant
Phthalate Exposure
Sathyanarayana et al. (2008) investigated
dermal exposure to phthalates via the dermal
application of personal care products. The study was
conducted on 163 infants born between the year 2000
and 2005. The products studied were baby lotion, baby
powder, baby shampoo, diaper cream, and baby wipes.
Infants were recruited through Future Families, a
multicenter pregnancy cohort study, at prenatal clinics
in Los Angeles, California; Minneapolis, Minnesota;
and Columbia, Missouri. Although the study was
designed to assess exposure to phthalates, the authors
collected information on the percentage of the total
participants that used the baby products. Data were
collected from questionnaire responses of the mothers
and at study visits. The characteristics and the percent
of the population using the studied baby products are
shown in Table 17-27. Of the 163 infants studied, 94
percent of the participants used baby wipes and 54
percent used infant shampoo.
The advantages of this study are that it
specifically targeted consumer products used by
children. The percent of the study population using
these products was captured and the data were
collected from a diverse ethnic population. The
limitations are that these data may not be entirely
representative of the U. S. population because the study
population was from only three states and the sample
size was small.
17.4 REFERENCES FOR CHAPTER 17
Bass, I; Ortega, L.; Resales, C.; Petersen, N., Philen,
R. (2001) What's being used at home: a
household pesticide survey. Pub Health
9(3):138-144.
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Cosmetic, Toiletry and Fragrance Association
(CTFA). (1983) Summary of the results of
surveys of the amount and frequency of use of
cosmetic products by women. Prepared by
Environ Corporation, Washington, DC for
CTFA Inc., Washington, DC.
Franklin, P. (2008) Household chemicals: good
housekeeping or occupational hazard. Eur
Respir 131:489-491.
Loretz, L.; Api, A.; Barraj, L.; Burdick, I; Dressier,
W.; Gettings, S.; Hsu, H.; Pan, Y.; Re, T.;
Renskers, K.; Rothenstein, A.; Scrafford, C.;
Sewall, C. (2005) Exposure data for cosmetic
products: lipstick, body lotion, and face
cream. Food Chem Toxicol 43:279-291.
Loretz, L.; Api, A.; Barraj, L.; Burdick, I; Davis, D.;
Dressier, W.; Gilberti, E.; Jarrett, G.; Mann,
S.; Pan, Y.; Re, T.; Renskers, K.; Scrafford,
C.; Vater, S. (2006) Exposure data for
personal care products: Hairspray, spray
perfume, liquid foundation, shampoo, body
wash, and solid antiperspirant. Food Chem
Toxicol 44:2008-2018.
Loretz, L.; Api, A.; Babcock, L; Barraj, L.; Burdick,
I; Cater, K.; Jarrett, G.; Mann, s.; Pan, Y.;
Re, T.; Renskers, K.; Scrafford, C. (2008)
Exposure data for cosmetic products: Facial
cleanser, hair conditioner, and eye shadow.
Food Chem Toxicol 46:1516-1524.
Sathyanarayana, S.; Karr, C.; Lozano, P., Brown, E.;
Calafat, M. (2008) Baby care products;
possible sources of infant phthalate exposure.
Pedriatrics 121:260-268.
Steenbekkers, L.P. (2001) Methods to study everyday
use of products un households: The
Wageningen mouthing study. Am Occup
Hyg 45(1001): 125-129.
U.S. EPA (1987) Methods for assessing exposure to
chemical substances - Volume 7 - Methods
for assessing consumer exposure to chemical
substances. Washington, DC: Office of Toxic
Substances. EPA/560/5-85/007.
U.S. EPA (1996) Descriptive statistics tables from a
detailed analysis of the National Human
Activity Pattern Survey (NHAPS) data.
Washington, DC: Office of Research and
Development. EPA/600/R-96/148.
U.S. EPA (1997) Exposure Factors Handbook.
Washington, DC: National Center for
Environmental Assessment, Office of
Research and Development. EPA/600/P-
95/002FC.
U.S. EPA. (2005) Guidance on Selecting Age Groups
for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
U.S. Environmental Protection Agency,
Washington, DC: EPA/630/P-03/003F.
Page
17-6
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-1. Consumer Products Commonly Found in Some U.S. Households"
Consumer Product Category
Cosmetics Hygiene Products
Household Furnishings
Garment Conditioning Products
Consumer Product
Adhesive bandages
Bath additives (liquid)
Bath additives (powder)
Cologne/perfume/aftershave
Contact lens solutions
Deodorant/antiperspirant (aerosol)
Deodorant/antiperspirant (wax and liquid)
Depilatories
Facial makeup
Fingernail cosmetics
Hair coloring/tinting products
Hair conditioning products
Hairsprays (aerosol)
Lip products
Mouthwash/breath freshener
Sanitary napkins and pads
Shampoo
Shaving creams (aerosols)
Skin creams (non-drug)
Skin oils (non-drug)
Soap (toilet bar)
Sunscreen/suntan products
Talc/body powder (non-drug)
Toothpaste
Waterless skin cleaners
Carpeting
Draperies/curtains
Rugs (area)
Shower curtains
Vinyl upholstery, furniture
Anti-static spray (aerosol)
Leather treatment (liquid and wax)
Shoe polish
Spray starch (aerosol)
Suede cleaner/polish (liquid and aerosol)
Textile water-proofing (aerosol)
Child-Specific Exposure Factors Handbook
September 2008
Page
17-7
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-1. Consumer Products Commonly Found in Some U.S. Households" (continued)
Consumer Product Category
Consumer Product
Household Maintenance Products
Adhesive (general) (liquid)
Bleach (household) (liquid)
Bleach (see laundry)
Candles
Cat box litter
Charcoal briquets
Charcoal lighter fluid
Drain cleaner (liquid and powder)
Dishwasher detergent (powder)
Dishwashing liquid
Fabric dye (DIY)b
Fabric rinse/softener (liquid)
Fabric rinse/softener (powder)
Fertilizer (garden) (liquid)
Fertilizer (garden) (powder)
Fire extinguishers (aerosol)
Floor polish/wax (liquid)
Food packaging and packaged food
Furniture polish (liquid)
Furniture polish (aerosol)
General cleaner/disinfectant (liquid)
General cleaner (powder)
General cleaner/disinfectant (aerosol and pump)
General spot/stain remover (liquid)
General spot/stain remover (aerosol and pump)
Herbicide (garden-patio) (liquid and aerosol)
Insecticide (home and garden) (powder)
Insecticide (home and garden) (aerosol and pump)
Insect repellent (liquid and aerosol)
Laundry detergent/bleach (liquid)
Laundry detergent (powder)
Laundry pre-wash/soak (powder)
Laundry pre-wash/soak (liquid)
Laundry pre-wash/soak (aerosol and pump)
Lubricant oil (liquid)
Lubricant (aerosol)
Matches
Metal polish
Oven cleaner (aerosol)
Pesticide (home) (solid)
Pesticide (pet dip) (liquid)
Pesticide (pet) (powder)
Pesticide (pet) (aerosol)
Pesticide (pet) (collar)
Petroleum fuels (home (liquid and aerosol)
Rug cleaner/shampoo (liquid and aerosol)
Rug deodorizer/freshener (powder)
Room deodorizer (solid)
Room deodorizer (aerosol)
Scouring pad
Toilet bowl cleaner
Toiler bowl deodorant (solid)
Water-treating chemicals (swimming pools')
Page
17-8
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-1. Consumer Products Commonly Found in Some U.S. Households" (continued)
Consumer Product Category
Consumer Product
Home Building/Improvement Products (DIY)b
Adhesives, specialty (liquid)
Ceiling tile
Caulks/sealers/fillers
Dry wall/wall board
Flooring (vinyl)
House Paint (interior) (liquid)
House Paint and Stain (exterior) (liquid)
Insulation (solid)
Insulation (foam)
Paint/varnish removers
Paint thinner/brush cleaners
Patching/ceiling plaster
Roofing
Refmishing products (polyurethane, varnishes, etc.)
Spray paints (home) (aerosol)
Wall paneling
Wall paper
Wall paper glue
Automobile-related Products
Antifreeze
Car polish/wax
Fuel/lubricant additives
Gasoline/diesel fuel
Interior upholstery/components, synthetic
Motor oil
Radiator flush/cleaner
Automotive touch-up paint (aerosol)
Windshield washer solvents
Personal Materials
Clothes/shoes
Diapers/vinyl pants
Jewelry
Printed material (colorprint, newsprint, photographs)
Sheets/towels
Toys (intended to be placed in mouths)
A subjective listing based on consumer use profiles.
DIY = Do It Yourself.
Source: U.S. EPA, 1987.
Child-Specific Exposure Factors Handbook
September 2008
Page
17-9
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products
Product Type
Baby Lotion - baby use0
Baby Lotion - adult use
Baby Oil - baby use0
Baby Oil - adult use
Baby Powder - baby use0
Baby Powder - adult use
Baby Cream - baby use0
Baby Cream - adult use
Baby Shampoo - baby use0
Baby Shampoo - adult use
Bath Oils
Bath Tablets
Bath Salts
Bubble Baths
Bath Capsules
Bath Crystals
Eyebrow Pencil
Eyeliner
Eye Shadow
Eye Lotion
Eye Makeup Remover
Mascara
Under Eye Cover
Blusher & Rouge
Face Powders
Foundations
Leg and Body Paints
Lipstick & Lip Gloss
Makeup Bases
Makeup Fixatives
Sunscreen
Colognes & Toilet Water
Perfumes
Amount of
Product Per
Application"
(grams)
1.4
1.0
1.3
5.0
0.8
0.8
-
-
0.5
5.0
14.7
-
18.9
11.8
-
-
-
-
-
-
-
-
-
0.011
0.085
0.265
-
-
0.13
-
3.18
0.65
0.23
Average Frequency of Use
(per day)
CTFA
0.38
0.22
0.14
0.06
5.36
0.13
0.43
0.07
0.14
0.02
0.08
0.003
0.006
0.088
0.018
0.006
0.27
0.42
0.69
0.094
0.29
0.79
0.79
1.18
0.35
0.46
0.003
1.73
0.24
0.052
0.003
0.68
0.29
Survey Type
Cosmetic
Co.
1.0
0.19
1.2
0.13
1.5
0.22
1.3
0.10
-
-
0.19
0.008
0.013
0.13
0.019
-
0.49
0.68
0.78
0.34
0.45
0.87
-
1.24
0.67
0.78
0.011
1.23
0.64
0.12
-
0.85
0.26
Marketb
Research
Bureau
-
0.24d
-
-
0.35d
-
-
-
O.llf
-
0.22s
-
-
-
-
-
-
0.27
0.40
-
-
0.46
-
0.55
0.33
0.47
-
2.62
-
-
0.002
0.56
0.38
Upper 90th Percentile Frequency of Use
(per day)
CTFA
0.57
0.86
0.14
0.29
8.43
0.57
0.43
0.14
0.14
0.86°
0.29
0.14e
0.14°
0.43
0.29°
0.29e
1.0
1.43
1.43
0.43
1.0
1.29
0.29
2.0
1.29
1.0
0.14°
4.0
0.86
0.14
0.14°
1.71
0.86
Survey Type
Cosmetic
Co.
2.0
1.0
3.0
0.57
3.0
1.0
3.0
0.14e
-
-
0.86
0.14e
0.14°
0.57
0.14°
0.14e
1.0
1.0
1.0
1.0
1.0
1.0
-
1.43
1.0
1.0
0.14°
2.86
1.0
1.0
-
1.43
1.0
Market
Research
Bureau
-
1.0d
-
-
1.0d
-
-
-
0.43f
-
l.O8
-
-
-
-
-
-
1.0
1.0
-
-
1.5
-
1.5
1.0
1.5
-
6.0
-
-
0.005
1.5
1.5
Page
17-10
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table
Product Type
Powders
Sachets
Fragrance Lotion
Hair Conditioners
Hair Sprays
Hair Rinses
Shampoos
Tonics and Dressings
Wave Sets
Dentifrices
Mouthwashes
Breath Fresheners
Nail Basecoats
Cuticle Softeners
Nail Creams & Lotions
Nail Extenders
Nail Polish & Enamel
Nail Polish & Enamel
Remover
Nail Undercoats
Bath Soaps
Underarm Deodorants
Douches
Feminine Hygiene
Deodorants
Cleansing Products (cold
creams, cleansing lotions
liquids & pads)
Depilatories
Face, Body & Hand Preps
(excluding shaving preps)
Foot Powder & Sprays
Hormones
Moisturizers
Night Skin Care Products
17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products (ontinued)
Amount of
Product Per
Application"
(grams)
2.01
0.2
-
12.4
-
12.7
16.4
2.85
2.6
-
-
-
0.23
0.66
0.56
-
0.28
3.06
-
2.6
0.52
-
-
1.7
-
3.5
-
-
0.53
1.33
Average Frequency of Use
(per day)
CTFA
0.18
0.0061
0.0061
0.4
0.25
0.064
0.82
0.073
0.00311
1.62
0.42
0.052
0.052
0.040
0.070
0.003
0.16
0.088
0.049
1.53
1.01
0.013
0.021
0.63
0.0061
0.65
0.061
0.012
0.98
0.18
Survey Type
Cosmetic
Co.
0.39
0.034
-
0.40
0.55
0.18
0.59
0.021
0.040
0.67
0.62
0.43
0.13
0.10
0.14
0.013
0.20
0.19
0.12
0.95
0.80
0.089
0.084
0.80
0.051
-
0.079
0.028
0.88
0.50
Marketb
Research
Bureau
-
-
-
0.27
0.32
-
0.48
-
-
2.12
0.58
0.46
-
-
-
-
0.07
-
-
-
1.10
0.085
0.05
0.54
0.009
1.12
-
-
0.63
-
Upper 90th Percentile Frequency of Use
(per day)
CTFA
1.0
0.14e
0.29e
1.0
1.0
0.29
1.0
0.29
__h
2.6
1.86
0.14
0.29
0.14
0.29
0.14e
0.71
0.29
0.14
3.0
1.29
0.14e
1.0"
1.71
0.016
2.0
0.57e
0.57e
2.0
1.0
Survey Type
Cosmetic
Co.
1.0
0.14e
-
1.0
1.0
1.0
1.0
0.14e
0.14
2.0
1.14
1.0
0.29
0.29
0.43
0.14e
0.43
0.43
0.29
1.43
1.29
0.29
0.29
2.0
0.14
-
0.29
0.14e
1.71
1.0
Market
Research
Bureau
-
-
-
0.86
1.0
-
1.0
-
-
4.0
1.5
0.57
-
-
-
-
1.0
-
-
-
2.0
0.29
0.14
1.5
0.033
2.14
-
-
1.5
-
Child-Specific Exposure Factors Handbook
September 2008
Page
17-11
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued)
Amount of
Product Per
Average Frequency of Use
(per day)
Upper 90th Percentile Frequency of Use
(per day)
Survey Type
Survey Type
rroauci lype , ,. ,. .
Application
(g)
CTFA
Cosmetic
Marketb
Research
Bureau
CTFA
Cosmetic
Market
Research
Bureau
Paste Masks (mud packs) 3.7 0.027
Skin Lighteners — -
Skin Fresheners & Astringents 2.0 0.33
Wrinkle Smoothers (removers) 0.38 0.021
Facial Cream 0.55 0.0061
Permanent Wave 101 0.003
Hair Straighteners 0.156 0.0007
Hair Dye - 0.001
Hair Lighteners - 0.0003
Hair Bleaches - 0.0005
Hair Tints - 0.0001
Hair Rinse (coloring) - 0.0004
Shampoo (coloring) - 0.0005
Hair Color Spray — -
Shave Cream 1.73 -
0.20
0.024
0.56
0.15
0.001
0.005
0.14
_d
1.0
1.0d
0.0061
0.0082
0.005d
0.004d
0.005d
0.02d
0.005d
0.02d
0.02d
0.43
0.14d
1.43
1.0
0.005
0.014
0.082
0.36
Values reported are the averages of the responses reported by the twenty companies interviewed.
(—'s) indicate no data available.
The averages shown for the Market Research Bureau are not true averages - this is due to the fact that in many cases the class of most
frequent users were indicated by "1 or more" also ranges were used in many cases, i.e., "10-12." The average, therefore, is
underestimated slightly. The " 1 or more" designation also skew the 90th percentile figures in many instances. The 90th percentile
values may, in actuality, be somewhat higher for many products.
Average usage among users only for baby products.
Usage data reflected "entire household" use for both baby lotion and baby oil.
Fewer than 10% of individuals surveyed used these products. Value listed is lowest frequency among individuals reporting usage. In
the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during the
period of the study.
Usage data reflected "entire household" use.
Usage data reflected total bath product usage.
None of the individuals surveyed reported using this product.
Source: CTFA, 1983.
Page
17-12
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-3. Number of Minutes Spent in Activities Working With or Near Freshly Applied Paints
(minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
N
7
12
20
212
1
3
5
0
0
2
3
5
0
0
5
3
5
0.5
1
10
3
15
3
2
25
5
20
8
11
Percentiles
50 75
15 121
45 120
45 75
60 121
90 95
121 121
120 121
121 121
121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
121
121
121
N =
99
121
121
121
121
doer sample
100
121
121
121
121
size;
Table 17-4. Number of Minutes Spent in Activities Working With or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/dav)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Percentiles
N
21
26
41
672
1
0
1
0
0
2
0
1
0
0
5 10
0 0
2 2
0 0
1 2
25
5
3
2
5
50
10
5
5
10
75
15
15
10
20
90 95
20 30
30 30
40 60
60 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
30
60
121
99
121
30
60
121
100
121
30
60
121
N = doer sample size;
Table
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
17-5. Number of Minutes Spent in Activities (at home or elsewhere) Working With
or Near Floorwax, Furniture Wax or Shoe Polish (minutes/dav)
N
13
21
15
238
1
0
0
0
0
2
0
0
0
0
5
0
2
0
2
10
5
2
1
3
25
10
3
2
5
Percentiles
50 75 90
15 20 60
5 10 35
10 25 45
15 30 120
95
121
60
121
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
120
121
121
99
121
120
121
121
N = doer sample
100
121
120
121
121
size;
Child-Specific Exposure Factors Handbook
September 2008
Page
17-13
-------
J*^ Child-Specific Exposure Factors Handbook
J&^ Chapter 17 - Consumer Products
Table 17-6.
Number of Minutes Spent in Activities Working With or Near Glue (minutes/dav)
Percentiles
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
N
6
36
34
207
1
0
2
0
0
2
0
2
0
0
5
0
3
1
0
10 25
0 30
5 5
2 5
1 5
50
75 90 95 98
30 30 50 50 50
12.5 25 30 60 120
10 30 30 60 120
20 90 121 121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; N =
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
99
50
120
120
121
100
50
120
120
121
doer sample size;
Table 17-7. Number of Minutes Spent in Activities Working With or Near Solvents,
(minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
N
7
16
38
407
1
0
0
0
0
2
0
0
0
0
5
0
0
0
1
10
0
2
0
2
25
1
5
5
5
Percentiles
50 75
5 60
5 17.5
10 60
30 121
Fumes or Strong Smelling Chemicals
90 95
121 121
45 70
121 121
121 121
Note: A Value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
70
121
121
99
121
70
121
121
100
121
70
121
121
N = doer sample size;
Table 17-8. Number of Minutes Spent in
N
1 to 4 years 3
5 to 1 1 years 3
12 to 17 years 7
18 to 64 years 87
1
0
3
0
0
2
0
3
0
0
Activities Working With or Near Stain or Spot Removers (minutes/dav)
5
0
3
0
0
10
0
3
0
0
25
0
3
5
2
Percentiles
50 75
0 3
5 5
15 35
5 15
90
3
5
60
60
95
3
5
60
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
3
5
60
121
N =
99
3
5
60
121
doer sample
100
3
5
60
121
size;
Page
17-14
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-9. Number of Minutes Spent in Activities Working With or Near Gasoline or
Diesel-powered Equipment, Besides Automobiles (minutes/day)
1 to 4 years 14
5 to 11 years 12
12 to 17 years 25
18to64years 312
Percentiles
1
0
1
2
0
2
0
1
2
0
5
0
1
5
1
10
1
3
5
3
25
5
7.5
13
15
50
22.5
25
35
60
75
120
50
120
121
90 95
121 121
60 60
121 121
121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
60
121
121
99
121
60
121
121
N = doer sample
100
121
60
121
121
size;
Table 17-10. Number of Minutes Spent in Activities Working With or Near Pesticides,
Including Bug Sprays or Bug Strips (minutes/day)
Age Group
Percentiles
N
1
10
25
50
75
90
95
99 100
1 to 4 years
5 to 11 years
12 to 17 years
18 to 64 years
6 1
16 0
10 0
190 0
3
1.5
2
10
7.5
2.5
10
15
30
40
20
121
121
121
20
121
121
121
20
121
121
121
20
121
121
121
20
121
121
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; N = doer sample size;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
Table 17-1 1. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies
Age Group
5 to 1 1 years
12 to 17 years
18 to 64 years
Number of Times Used in a Dav
Total N
26
144
1,735
1-2
24
133
1,635
3-5
2
9
93
6-9
*
*
3
10+ Don't Know
* *
1 1
1 3
* = Missing Data.
N = Number of respondents.
Source: U.S. EPA, 1996.
Child-Specific Exposure Factors Handbook
September 2008
Page
17-15
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Age Or
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Table 17-12.
OUP Total N
40
75
103
1,071
dumber of Respondents Using Any Aerosol Spray Product for Personal Care Item
Such as Deodorant or Hair Spray at Specified Daily Frequencies
Number of Times Used
1
30
57
53
724
2
9
14
31
263
3
0
1
12
39
4 5
0 1
1 1
4 1
15 13
6
0
1
0
1
in a Dav
7
0
0
0
1
10
0
0
1
2
10+
0
0
1
8
Don't Know
0
0
0
5
N = Number of respondents..
Source: U.S. EPA. 1996.
Table 17-13. Number of Respondents Using a Humidifier at Home
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
Total N
111
88
83
629
Almost
Every
Day
33
18
21
183
3-5 Times a
Week
16
10
7
77
Frequency
1-2 Times a
Week
7
12
5
70
1-2 Times a
Month
53
46
49
287
Don't
Know
2
2
1
12
N = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-14. Number of Respondents Indicating that Pesticides Were Applied bythe Professional at Home
to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Total N
113
150
143
1,264
Number of Times Over a 6-month Period
Pesticides Were Applied bv Professionals
None
60
84
90
660
1-2
35
37
40
387
3-5
11
10
5
89
6-9
6
18
6
97
10+
1
1
*
15
Don't Know
*
*
2
16
* = Missing data.
N = Number of respondents.
Source: U.S. EPA, 1996.
Page
17-16
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-15. Number of Respondents Reporting Pesticides Applied bythe Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
Total N .
113
150
143
1,264
Number of Times Over a 6-month
Period Pesticides Applied bv Resident
None
46
50
45
473
1-2
46
70
64
477
3-5
15
24
21
192
6-9
3
1
5
48
10+
3
4
8
55
Don't Know
*
1
*
19
Note: * = Missing Data
N = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-16. Number of Respondents Indicating that Pesticides Were Applied by a
Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group Total N
0 to <1 years
Ito <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
15
23
32
80
106
115
87
Frequency
(number of times over a six-month period that pesticides were applied by a professional)
None
9
13
9
51
59
68
40
Ito 2
4
5
15
22
22
35
36
3 to 5
1
3
5
5
7
4
2
6 to 9
1
1
3
2
17
6
5
10+
0
1
0
0
1
0
1
Don't Know
0
0
0
0
0
2
3
N = Number of respondents.
Source: U.S. EPA re-analysis of NHAPS (U.S. EPA, 1996) data.
Table 17-17. Number of Respondents Reporting Pesticides Applied bythe Consumer at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group Total N
0 to
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-18. Household Demographics, and Pesticide Types, Characteristics, and Frequency of Pesticide Use
Survey Population Demographics
Gender
female
male
Language of Interview
Spanish
English
Reading Skills
able to read English
able to read Spanish
Number in household
2-3 people
4-5 people
6-8 people
Children under 10 years
1 child
2 children
3 to 5 children
Type of home
single family detached
multi-family
trailer/mobile home
single-family attached
apartment/other
Pets
pets kept in household
pesticides used on pets
Number"
90
17
72
35
71
95
25
59
23
37
45
25
75
9
9
8
4
55
22
Percent"
84.1
15.9
67.3
32.7
66.4
88.8
23.3
55.1
21.4
34.6
42.1
23.3
70.1
8.4
8.4
7.5
3.7
51.4
40.0
Pesticide Use
Type of pesticide
insecticide
rodenticide
herbicide
Storage of pesticide
kitchen
garage/shed
laundry/washroom
other, inside home
other, outside home
bathroom
basement
closet
Storage precautions
child-resistant container
pesticide locked away
Storage risks
< 4 feet from ground
kept near food
kept near dishes/cookware
Disposal
throw it away
wrap in separate container, throw
away
other
Frequency of use
more than once/week
once/week
once/month
once every 3 months
once every 6 months
once/year
Time stored in home
< 6 months
6 to 12 months
12 to 24 months
> 24 months
a Totals may not add to 107 participants or
Source: Bass et al., 2001.
135
10
3
£.1
O /
30
1 A
H-
•7
/
7
00
oJ
55
72
5
5
132
10
5
20
27
42
01
ZJ
16
1 1
LJ
75
O/1
Z4
17
16
91.2
6.8
2.0
AS 0
^tj. J
20.3
Q A
y .*+
H A
/.•4-
A 7
4-. /
4.7
1 H
Z. /
1 H
Z. /
c/r 1
JO. 1
37.2
48.6
3.4
3 4
89.2
6.8
3.4
13 5
18.2
28.4
ICC
1 J. J
10.8
80
.0
50.7
ico
1 J.Z
11.5
10.8
148 products, and percentages may not add to 100 due to some non-responses to survey questions.
Page
17-18
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-19
Product Type
Lipstick
Body lotion, hands
Body lotion, arms
Body lotion, feet
Body lotion, legs
Body lotion, neck & throat
Body lotion, back
Body lotion, other
Face cream
N = Number of subjects (women,
SD = Standard deviation.
Source: Loretz et al., 2005.
. Frequency of Use of Cosmetic Products
N -
311
308
308
308
308
308
308
308
300
ages 19 to 65
Number of Applications per Da\
Mean Median
2.35 2
2.12 2
1.52 1
0.95 1
1.11 1
0.43 0
0.26 0
0.40 0
1.77 2
years).
SD
1.80
1.59
1.30
1.01
0.98
0.82
0.63
0.76
1.16
Child-Specific Exposure Factors Handbook Page
September 2008 17-19
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-20.
Summary Statistics
Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream
Total Amount Applied
Average" Amount Applied per
Use Day
Average11 Amount Applied
per Application
Lipstick
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
99th
Best Fit Distributions &
Parameters0
0.001
2.666
0.272
0.408
0.026
0.063
0.082
0.110
0.147
0.186
0.242
0.326
0.655
0.986
2.427
Lognormal Distribution
GM = 0.14
GSD = 3.56
P- value (Gof) = 0.01
0.000
0.214
0.024
0.034
0.003
0.005
0.008
0.010
0.013
0.016
0.021
0.029
0.055
0.087
0.191
Lognormal Distribution
GM= 0.01
GSD = 3.45
P-value(Gof) <0.01
0.000
0.214
0.010
0.018
0.001
0.003
0.004
0.004
0.005
0.006
0.009
0.011
0.024
0.037
0.089
Lognormal Distribution
GM = 0.01
GSD = 3.29
P- value (Gof) <0.01
Body Lotion
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
0.67
217.66
103.21
53.40
36.74
51.99
68.43
82.75
96.41
110.85
134.20
160.26
0.05
36.31
8.69
5.09
3.33
4.68
5.71
6.74
7.63
9.25
10.90
12.36
0.05
36.31
4.42
4.19
1.30
1.73
2.32
2.76
3.45
4.22
4.93
6.14
Page
17-20
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-20. Amount of Test Product Used (grams) for Lipstick, Body Lotion and Face Cream (continued)
Summary Statistics
Total Amount Applied
Average" Amount Applied per
Use Day
Average11 Amount Applied
per Application
90th
95th
99th
Best Fit Distributions &
Parameters0
182.67
190.13
208.50
Beta Distribution0
Alpha = 1.53
Beta =1.77
Scale = 222.01
P-value (GoF) = 0.06
14.39
16.83
27.91
Gamma Distribution
Location = -0.86
Scale = 2.53
Shape = 3.77
P-value (GoF) = 0.37
8.05
10.22
21.71
Lognormal Distribution
GM = 3.26
GSD = 2.25
P-value (GoF) = 0.63
Face Cream
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
99th
Best Fit Distributions &
Parameters0
0.04
55.85
22.36
14.01
5.75
9.35
12.83
16.15
19.86
23.79
29.31
36.12
44.58
48.89
51.29
Triangle Distribution
Minimum = -1.09
Maximum = 58.71
Likeliest = 7.53
P-value (GoF) = 0.27
0.00
42.01
2.05
2.90
0.47
0.70
1.03
1.26
1.53
1.88
2.23
2.90
3.50
3.99
12.54
Lognormal Distribution0
GM= 1.39
GSD = 2.58
P-value (GoF) <0.01
0.00
21.01
1.22
1.76
0.28
0.40
0.53
0.67
0.84
1.04
1.22
1.55
2.11
2.97
10.44
Lognormal Distribution0
GM = 0.80
GSD = 2.55
P-value (GoF) = 0.02
' Derived as the ratio of the total amount used to the number of use days.
b Derived as the ratio of the total amount used to the total number of applications during the survey.
0 None of the tested distributions provided a good fit.
GM = Geometric mean.
GSD = Geometric standard deviation.
Gof = Goodness of fit.
Note: Data are for women, ages 19 to 65 years.
Source: Loretz et al., 2005.
Child-Specific Exposure Factors Handbook
September 2008
Page
17-21
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-21. Frequency of Use of Personal Care Products
Product Type
Hairspray (aerosol)
Hairspray (pump)
Liquid Foundation
Spray Perfume
Body wash
Shampoo
Solid antiperspirant
Averag
N Mean
165b 1.49
162 1.51
326 1.24
326 1.67
340 1.37
340 1.11
340 1.30
>e Number of Applications per Use Day"
SD
0.63
0.64
0.32
1.10
0.58
0.24
0.40
Min
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Max
5.36
4.22
2.00
11.64
6.36
2.14
4.00
* Derived as the ratio of the number of applications to the number of use days.
b Subjects who completed the study but did not report their number of applications were excluded.
N = Number of subjects (women, ages 18 to 65 years).
SD = Standard deviation.
Source: Loretz et al., 2006.
Page
17-22
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
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Child-Specific Exposure Factors Handbook Page
September 2008 17-23
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
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Page
17-24
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-24. Average Number of Applications Per Use Day"
Summary Statistics Facial Cleanser
(Lathering and Non-Lathering)
N
Mean
SD
Minimum
Maximum
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99thb
295
1.6
0.52
1.0
3.2
1.0
1.0
1.2
1.4
1.7
1.9
2.0
2.0
2.2
2.4
2.9b
3.1b
a Derived as the ratio of the number of applications to the number of use days.
b Estimate does not meet the minimum sample size criteria (n=800) as set by the N
(>0.75), the minimum sample size (n) satisfies the following rule: n [8/(l-p.]
htip:.|l.|l\\ww/cdc.|ljzov.|lnchs.|lab()ut/'maior/nhancs.i'nhanes3/nh3jzu].pdj..
N = Number of subjects (women, ages 1 8 to 69 years).
SD = Standard deviation.
Source: Loretz et al., 2008.
Hair Conditioner
297
1.1
0.19
1.0
2.4
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.1
1.2
1.4
1.8b
2.1b
itional Center for Health Statistics.
Eye Shadow
299
1.2
0.33
1.0
2.7
1.0
1.0
1.0
1.1
1.1
1.1
1.2
1.4
1.7
2.0
2.2b
2.5b
For upper percentile
Child-Specific Exposure Factors Handbook
September 2008
Page
17-25
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-25. Average Amount of Product Applied Per Use Day (grams)"
Summary Statistics
Facial Cleanser
(Lathering and Non-
Lathering)
Facial Cleanser
(Lathering)
Facial Cleanser (Non-
Lathering)
Hair Conditioner
Eye shadow
N
Mean
SD
Minimum
Maximum
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99thb
Best fit distributions
and parameters
P-value
(Chi-square test)
295
4.06
2.78
0.33
16.70
1.41
1.79
2.18
2.66
3.25
3.86
4.62
6.24
8.28
9.93
10.71b
12.44b
Lognormal
distribution
GM = 3.26
GSD=1.12
0.1251
174
4.07
2.87
0.33
15.32
1.23
1.72
2.15
2.64
3.19
3.84
4.71
6.33
8.24
10.50
11.47b
13.07b
Lognormal
distribution
GM = 3.21
GSD = 2.03
0.4429
121
4.05
2.67
0.83
16.70
1.50
1.94
2.22
2.80
3.33
3.88
4.59
5.92
8.40
9.37b
10.26b
15.29b
Lognormal
distribution
GM = 3.35
GSD =1.86
0.4064
297
13.77
11.50
0.84
87.86
3.71
5.54
6.95
8.73
10.62
12.61
15.54
20.63
28.20
33.19
45.68b
60.20b
Lognormal
distribution
GM= 10.28
GSD-2.20
0.8595
299
0.04
0.11
0.001
0.74
0.003
0.005
0.007
0.009
0.010
0.013
0.017
0.025
0.052
0.096
0.525b
0.673b
Lognormal
distribution
GM = 0.01
GSD = 3.61
<0.0001
a Derived as the ratio of the total amount used to the number of use days.
b Estimate does not meet the minimum sample size criteria (n=800) as set by the National Center for Health Statistics. For upper percentile (>0.75),
the minimum sample size (n) satisfies the following rule: n [8/(l-p)]. h_1lpj_^;w^gd£:goWn_ch_s/ab^
N = Number of subjects (women, ages 18 to 69 years).
GM = Geometric mean.
GSD = Geometric standard deviation.
Source: Loretz et al., 2008.
Page
17-26
Child-Specific Exposure Factors Handbook
September 2008
-------
Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products
Table 17-26. Average Amount of Product Applied Per Application (grams)"
Summary Statistics
Facial Cleanser
(Lathering and Non-
Lathering)
Facial
Cleanser
(Lathering)
Facial Cleanser
(Non-
Lathering)
Hair Conditioner
Eye Shadow
N
Mean
SD
Minimum
Maximum
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99thb
Best fit distributions and
parameters
P- value (Chi-square test)
295
2.57
1.78
0.33
14.61
0.92
1.32
1.57
1.85
2.11
2.50
2.94
3.47
4.81
5.89
7.16b
9.44b
Extreme value
Mode = 1.86
Scale = 1.12
0.0464
174
2.56
1.78
0.33
10.67
0.83
1.26
1.55
1.84
2.11
2.50
2.96
3.56
5.10
6.37
7.77b
9.61b
Gamma
Loc = 0.28
Scale =1.29
0.6123
121
2.58
1.77
0.57
14.61
1.10
1.35
1.59
1.89
2.15
2.51
2.96
3.40
4.52
5.11b
6.29b
15.46b
Extreme value
Mode = 1.92
Scale =1.03
0.5219
297
13.13
11.22
0.84
87.86
3.48
5.34
6.71
8.26
10.21
12.24
14.54
18.88
27.32
32.43
45.68b
60.20b
Lognormal
distribution
GM = 9.78
GSD = 2.20
0.9501
299
0.03
0.10
0.0004
0.69
0.003
0.004
0.006
0.007
0.009
0.011
0.015
0.022
0.041
0.096
0.488b
0.562b
Lognormal
distribution
GM = 0.01
GSD = 3.59
<0.0001
a Derived as the ratio of the total amount used to the total number of applications.
b Estimate does not meet the minimum sample size criteria (n=800) as set by the National Center for Health Statistics. For upper percentile (>0.75), the
minimum sample size (n) satisfies the following rule: n [8/(l-p)]. Http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf.
N = Number of subjects (women, ages 18 to 69 years).
GM = Geometric mean.
SD = Geometric standard deviation.
Source: Loretz et al., 2008.
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Table 17-27. Characteristics of the Study Population and the Percent
Characteristic
Number of Participants
Los Angeles, California
Minneapolis, Minnesota
Columbia, Missouri
Gender
Male
Female
Age (months)
2-8
9-16
17-24
24-28
Infant Weight (kg)
•10
>10
Race
White
Hispanic/Latino
Native American
Asian
Black
Product Use
Baby Lotion
Baby Shampoo
Baby Powder
Diaper Cream
Baby Wipes
Using Selected Baby Care Products
Sample Number (percent)
43 (26)
77(47)
43 (26)
84 (52)
79 (48)
42 (26)
82 (50)
30(18)
9(6)
84 (52)
79 (48)
131(80)
17(10)
3(2)
8(5)
4(3)
Percent Using
36
54
14
33
94
Source: Sathyanarayana et al., 2008.
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GLOSSARY OF TERMS
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Activity pattern data - Information on human
activities used in exposure assessments. These may
include a description of the activity, frequency of
activity, duration spent performing the activity, and the
microenvironment in which the activity occurs.
Adherence factor - The amount of a material (e.g.,
soil) that adheres to the skin per unit of surface area.
Activity pattern (time use) data - Information on
activities in which various individuals engage, length
of time spent performing various activities, locations in
which individuals spend time and length of time spent
by individuals within those various environments.
Agricultural commodity - Used by U. S. EPA to mean
plant (or animal) parts consumed by humans as food.
When such items are raw or unprocessed, they are
referred to as "raw agricultural commodities."
All water sources - Includes water from all supply
sources such as community water supply (i.e., tap
water), bottled water, etc.
Analytical uncertainty propagation - Examining
how uncertainty in individual parameters affects the
overall uncertainty of the exposure assessment.
Anthropometric - The study of human body
measurements for use in anthropological classification
and comparison.
As-consumed intake - Intake rate based on the weight
of the food in the form that it is consumed (e.g.,
cooked or prepared).
Assessment - A determination or appraisal of possible
consequences resulting from an analysis of data.
Average Daily Dose (ADD) - Dose rate averaged over
a pathway-specific period of exposure expressed as a
daily dose on a per-unit-body-weight basis. The ADD
is used for exposure to chemicals with
non-carcinogenic non-chronic effects. The ADD is
usually expressed in terms of mg/kg-day or other
mass/mass-time units.
Benchmark Dose (BMD) or Concentration (BMC) -
A dose or concentration that produces a predetermined
change in response rate of an adverse effect (called the
benchmark response or BMR) compared to
background.
Best Tracer Method (BTM) - Method for estimating
soil ingestion that allows for the selection of the most
recoverable tracer for a particular subject or group of
subjects. Selection of the best tracer is made on the
basis of the food/soil (F/S) ratio.
Bias - A systematic error inherent in a method or
caused by some feature of the measurement system.
Bioavailability - The rate and extent to which an
agent can be absorbed by an organism and is available
for metabolism or interaction with biologically
significant receptors. Bioavailability involves both
release from a medium (if present) and absorption by
an organism.
Biomarker model comparison - A methodology that
compares results from a biokinetic exposure model to
biomarker measurements children blood. The method
is used to confirm assumptions about ingested soil and
dust quantities in this handbook.
Basal Metabolic Rate (BMR) - Minimum level of
energy required to maintain normal body functions.
Body Mass Index (BMI) - The ratio of weight and
height squared.
Bootstrap - A statistical method of resampling data
use to estimate variance and bias of an estimator and
provide confidence intervals for parameters.
Bounding estimate - An estimate of exposure, dose, or
risk that is higher or lower than that incurred by the
person with the highest or lowest exposure, dose, or
risk in the population being assessed. Bounding
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Glossary
estimates are useful in developing statements that
exposures, doses, or risks are "not greater than" or
"less than" the estimated value, because assumptions
are used which define the likely bounding conditions.
Central tendency exposure - A measure of the middle
or the center of an exposure distribution. The mean is
the most commonly used measure of central tendency.
Chronic exposure - Repeated exposure by the oral,
dermal, or inhalation route for more than
approximately 10% of the life span in humans (more
than approximately 90 days to 2 years in typically used
laboratory animal species).
Chronic intake - The long term period over which a
substance crosses the outer boundary of an organism
without passing an absorption barrier.
Classical statistical methods - Estimating the
population exposure distribution directly, based on
measured values from a representative sample.
Coating - Method used to measure skin surface area,
in which either the whole body or specific body regions
are coated with a substance of known density and
thickness.
Community water - Includes tap water ingested from
community or municipal water supply.
Comparability - The ability to describe likenesses and
differences in the quality and relevance of two or more
data sets.
Concentration - Amount of a material or agent
dissolved or contained in unit quantity in a given
medium or system.
Confidence intervals - An estimated range of values
with a given probability of including the population
parameter of interest. The range of values is usually
based on the results of a sample that estimated the
mean and the sampling error or standard error.
Consumer-only intake rate - The average quantity of
food consumed per person in a population composed
only of individuals who ate the food item of interest
during a specified period.
Contaminant concentration - Contaminant
concentration is the concentration of the contaminant
in the medium (air, food, soil, etc.) contacting the body
and has units of mass/volume or mass/mass.
Creel study - A study in which fishermen are
interviewed while fishing.
Cumulative exposure - Exposure via mixtures of
contaminants both indoors and outdoors. Exposure
may also occur through more than one pathway. New
directions in risk assessments in U.S. EPA put more
emphasis on total exposures via multiple pathways.
Deposition - The removal of airborne substances to
available surfaces that occurs as a result of
gravitational settling and diffusion, as well as
electrophoresis and thermophoresis.
Dermal absorption - A route of exposure by which
substances can enter the body through the skin.
Dermal adherence - The loading of a substance onto
the outer surface of the skin.
Diary study - Survey in which individuals are asked to
record food intake, activities, or other factors in a diary
which is later used to evaluate exposure factors
associated with specific populations.
Direct water ingestion - Consumption of plain water
as a beverage. It does not include water used for
preparing beverages such as coffee or tea.
Distribution - A set of values derived from a specific
population or set of measurements that represents the
range and array of data for the factor being studied.
Doers - Survey respondents who report participating in
a specified activity.
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Dose - The amount of a substance available for
interaction with metabolic processes or biologically
significant receptors after crossing the outer boundary
of an organism. The potential dose is the amount
ingested, inhaled, or applied to the skin. The applied
dose is the amount of a substance presented to an
absorption barrier and available for absorption
(although not necessarily having yet crossed the outer
boundary of the organism). The absorbed dose is the
amount crossing a specific absorption barrier (e.g., the
exchange boundaries of skin, lung, and digestive tract)
through uptake processes. Internal dose is a more
general term denoting the amount absorbed without
respect to specific absorption barriers or exchange
boundaries. The amount of a chemical available for
interaction by any particular organ or cell is termed the
delivered dose for that organ or cell.
Dose rate - Dose per unit time.
Dose-response assessment - Analysis of the
relationship between the total amount of an agent
administered to, taken up by, or absorbed by an
organism, system, or (sub)population and the changes
developed in that organism, system, or (sub)population
in reaction to that agent, and inferences derived from
such an analysis with respect to the
entire population. Dose-response assessment is the
second of four steps in risk assessment.
Dose-response curve- Graphical presentation of a
dose-response relationship.
Dose-response relationship - The resulting biological
responses in an organ or organism expressed as a
function of a series of doses.
Dressed weight - The portion of the harvest brought
into kitchens for use, including bones for particular
species.
Dry weight intake rates - Intake rates that are based
on the weight of the food consumed after the moisture
content has been removed.
Dust Ingestion - Consumption of dust that results from
various behaviors including, but not limited to,
mouthing objects or hands, eating dropped food,
consuming dust directly, or inhaling dust that passes
from the respiratory system into the gastrointestinal
tract.
Effect - Change in the state or dynamics of an
organism, system, or (sub) population caused by
exposure to an agent.
Energy expenditures - The amount of energy
expended by an individual during activities.
Exposure - Contact of a chemical, physical, or
biological agent with the outer boundary of an
organism. Exposure is quantified as the concentration
of the agent in the medium in contact integrated over
the time duration of the contact.
Exposure assessment - The determination or
estimation (qualitative or quantitative) of the
magnitude, frequency, or duration, and route or
exposure.
Exposure concentration - The concentration of a
chemical in its transport or carrier medium at the point
of contact.
Exposure duration - Length of time over which
contact with the contaminant lasts.
Exposure event - The occurrence of continuous
contact between an agent and a target.
Exposure frequency - The number of exposure events
in an exposure duration.
Exposure loading - The exposure mass divided by the
exposure surface area. For example, a dermal exposure
measurement based on a skin wipe sample, expressed
as a mass of residue per skin surface area, is an
exposure loading.
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Exposure pathway - The physical course a chemical
takes from the source to the organism exposed.
Exposure route - The way a chemical pollutant enters
an organism after contact, e.g., by ingestion,
inhalation, or dermal absorption.
Exposure scenario - A set of facts, assumptions, and
interferences about how exposure takes place that aids
the exposure assessor in evaluating estimating, or
quantifying exposures.
Fate - Pattern of distribution of an agent, its
derivatives, or metabolites in an organism, system,
compartment, or (sub)population of concern as a result
of transport, partitioning, transformation, or
degradation.
General population - The total of individuals
inhabiting an area or making up a whole group.
Geometric mean - The n* root of the product of n
values.
Geophagy - A form of soil ingestion involving the
intentional ingestion of earths, usually associated with
cultural practices.
Hazard - Inherent property of an agent or situation
having the potential to cause adverse effects when an
organism, system, or (sub)population is exposed to that
agent.
Hazard assessment - A process designed to determine
the possible adverse effects of an agent or situation to
which an organism, system, or (sub)population could
be exposed. The process typically includes hazard
identification, dose-response evaluation and hazard
characterization. The process focuses on the hazard, in
contrast to risk assessment, where exposure assessment
is a distinct additional step.
High end exposure - An estimate of individual
exposure or dose for those persons at the upper end of
an exposure or dose distribution, conceptually above
the 90th percentile, but not higher than the individual
in the population who has the highest exposure or
dose.
Homegrown/home produced foods - Fruits and
vegetables produced by home gardeners, meat and
dairy products derived form consumer-raised livestock,
game meat, and home caught fish.
Human Equivalent Concentration (HEC) or Dose
(HED): The human concentration (for inhalation
exposure) or dose (for other routes of exposure) of an
agent that is believed to induce the same magnitude of
toxic effect as the experimental animal species
concentration or dose. This adjustment may
incorporate toxicokinetic information on the particular
agent, if available, or use a default procedure, such as
assuming that daily oral doses experienced for a
lifetime are proportional to body weight raised to the
0.75 power.
Indirect water ingestion - Includes water added
during food preparation, but not water intrinsic to
purchased foods. Indirect water includes for example,
water used to prepare baby formulas, cake mix, and
concentrated orange juice.
Indoor settled dust - Particles in building interiors
that have settled onto objects, surfaces, floors, and
carpeting. These particles may include soil particles
that have been tracked into the indoor environment
from outdoors.
Inhalation dosimetry - Process of measuring or
estimating inhaled dose.
Inhalation unit risk - The upper-bound excess lifetime
cancer risk estimated to result from continuous
exposure to an agent at a concentration of 1 "g/m3 in
air for a lifetime.
Inhaled dose - The amount of an inhaled substance
that is available for interaction with metabolic
processes or biologically significant receptors after
crossing the outer boundary of an organism.
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Insensible water loss - Evaporative water losses that
occur during breastfeeding. Corrections are made to
account for insensible water loss when estimating
breast milk intake using the test weighing method.
Intake - The process by which a substance crosses the
outer boundary of an organism without passing an
absorption barrier (e.g., through ingestion or
inhalation).
Intake rate - Rate of inhalation, ingestion, and dermal
contact depending on the route of exposure. For
ingestion, the intake rate is simply the amount of food
containing the contaminant of interest that an
individual ingests during some specific time period
(units of mass/time). For inhalation, the intake rate is
the rate at which contaminated air is inhaled. Factors
that affect dermal exposure are the amount of material
that comes into contact with the skin, and the rate at
which the contaminant is absorbed.
Inter-individual variability - Variations between
individuals in terms of human characteristics such as
age or body weight, or behaviors such as location,
activity patterns, and ingestion rates.
Internal dose - The amount of a substance penetrating
across absorption barriers (the exchange boundaries) of
an organism, via either physical or biological processes
(synonymous with absorbed dose).
Intra-individual variability - Fluctuations in an
individual's physiologic (e.g., body weight), or
behavioral characteristics (e.g., ingestion rates or
activity patterns).
Key study - A study that is useful for deriving
exposure factors.
Lead isotope ratio methodology - A method that
measures different lead isotopes in children's blood
and/or urine, food, water, and house dust and
compares the ratio of these isotopes to infer sources of
lead exposure that may include dust or other
environmental exposures.
Lifestage - A distinguishable time frame in an
individual's life characterized by unique and relatively
stable behavioral and/or physiological characteristics
that are associated with development and growth.
Lifetime Average Daily Dose (LADD) - Dose rate
averaged over a lifetime. The LADD is used for
compounds with carcinogenic or chronic effects. The
LADD is usually expressed in terms of mg/kg-day or
other mass/mass-time units.
Limiting Tracer Method (LTM) - Method for
evaluating soil ingestion that assumes that the
maximum amount of soil ingested corresponds with
the lowest estimate from various tracer elements.
Long-term exposure - Repeated exposure for more
than 30 days, up to approximately 10% of the life span
in humans (more than 30 days).
Lowest-Observed-Adverse-Effect Level (LOAEL):
The lowest exposure level at which there are
biologically significant increases in frequency or
severity of adverse effects between the exposed
population and its appropriate control group.
Margin of safety - For some experts, margin of safety
has the same meaning as margin of exposure, while for
others, margin of safety means the margin between the
reference dose and the actual exposure.
Mass-balance/tracer techniques - Method for
evaluating soil intake that accounts for both inputs and
outputs of tracer elements. Tracers in soil, food,
medicine and other ingested items as well as in feces
and urine are accounted for.
Mean value - Simple or arithmetic average of a range
of values, computed by dividing the total of all values
by the number of values.
Measurement error - A systematic error arising from
inaccurate measurement (or classification) of subjects
on the study variables.
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Measurement end-point - Measurable (ecological)
characteristic that is related to the valued characteristic
chosen as an assessment point.
Median value - The value in a measurement data set
such that half the measured values are greater and half
are less.
Metabolic Equivalent of Work (MET) - A
dimensionless energy expenditure metric used to
represent an activity level.
Microenvironment - Surroundings that can be treated
as homogeneous or well characterized in the
concentrations of an agent (e.g., home, office,
automobile, kitchen, store).
Model uncertainty - Uncertainty regarding gaps in
scientific theory required to make predictions on the
basis of causal inferences.
Moisture content - The portion of foods made up by
water. The percent water is needed for converting food
intake rates and residue concentrations between whole
weight and dry weight values.
Monte Carlo technique - A repeated random
sampling from the distribution of values for each of the
parameters in a generic (exposure or dose) equation to
derive an estimate of the distribution of (exposures or
doses in) the population.
Mouthing behavior - Activities in which objects,
including fingers, are touched by the mouth or put into
the mouth except for eating and drinking, and includes
licking, sucking, chewing, and biting.
Non-dietary ingestion - Ingestion of non-food
substances, typically resulting from the mouthing of
hands and objects.
No-Observed-Adverse-Effect-Level (NOAEL) - The
highest exposure level at which there are no
biologically significant increases in the frequency or
severity of adverse effect between the exposed
population and its appropriate control; some effects
may be produced at this level, but they are not
considered adverse or precursors of adverse effects.
Outdoor settled dust - Particles that have settled onto
outdoor objects and surfaces due to either wet or dry
deposition.
Oxygen consumption (VO2) - The rate at which
oxygen is used by tissues.
Parameter uncertainty - Uncertainty regarding some
parameter.
Pathway - The physical course a chemical or pollutant
takes from the source to the organism exposed.
Per capita intake rate - The average quantity of food
consumed per person in a population composed of both
individuals who ate the food during a specified time
period and those that did not.
Pica - Pica behavior is the repeated eating of
non-nutritive substances, whereas soil-pica is a form of
soil ingestion that is characterized by the recurrent
ingestion of unusually high amounts of soil (i.e., on the
order of 1,000 - 5,000 milligrams per day or more).
Plain tap water - Excludes tap water consumed in the
form of juices and other beverages containing tap
water.
Population mobility - An indicator of the frequency at
which individuals move from one residential location
to another.
Population risk descriptor - An assessment of the
extent of harm to the population being addressed. It
can be either an estimate of the number of cases of a
particular effect that might occur in a population (or
population segment), or a description of what fraction
of the population receives exposures, doses, or risks
greater than a specified value.
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Potential dose - The amount of a chemical contained
in material ingested, air breathed, or bulk material
applied to the skin.
Poverty/income ratio - Ratio of reported family
income to federal poverty level.
Precision - A measure of the reproducibility of a
measured value under a given set of circumstances.
Preparation losses - Net cooking losses, which
include dripping and volatile losses, post cooking
losses, which involve losses from cutting, bones, excess
fat, scraps and juices, and other preparation losses
which include losses from paring or coring.
Primary data/analysis - Information gathered from
observations or measurements of a phenomena or the
surveying of respondents.
Probabilistic uncertainty analysis - Technique that
assigns a probability density function to each input
parameter, then randomly selects values from each of
the distributions and inserts them into the exposure
equation. Repeated calculations produce a distribution
of predicted values, reflecting the combined impact of
variability in each input to the calculation. Monte
Carlo is a common type of probabilistic Uncertainty
analysis.
Questionnaire/survey response - A "question and
answer" data collection methodology conducted via in-
person interview, mailed questionnaire, or questions
administered in a test format in a school setting.
Random samples - Samples selected from a statistical
population such that each sample has an equal
probability of being selected.
Range - The difference between the largest and
smallest values in a measurement data set.
Ready-to-feed - Infant and baby products (formula,
juices, beverages, baby food), and table foods that do
not need to have water added to them prior to feeding.
Reasonable maximum exposure (or worst case) - A
semiquantitative term referring to the lower portion of
the high end of the exposure, dose, or risk distribution.
As a semiquantitative term, it should refer to a range
that can conceptually be described as above the 90th
percentile in the distribution, but below the 98th
percentile.
Recreational/sport fishermen - Individuals who catch
fish as part of a sporting or recreational activity and
not for the purpose of providing a primary source of
food for themselves or for their families.
Reference Concentration (RfC) - An estimate (with
uncertainty spanning perhaps an order of magnitude)
of a continuous inhalation exposure to the human
population (including sensitive subgroups) that is
likely to be without an appreciable risk of deleterious
effects during a lifetime. It can be derived from a
NOAEL, LOAEL, or benchmark concentration, with
uncertainty factors generally applied to reflect
limitations of the data used. Generally used in EPA's
noncancer health assessments. Durations include
acute, short-term, subchronic, and chronic.
Reference Dose (RfD) - An estimate (with uncertainty
spanning perhaps an order of magnitude) of a daily
oral exposure to the human population (including
sensitive subgroups) that is likely to be without an
appreciable risk of deleterious effects during a lifetime.
It can be derived from a NOAEL, LOAEL, or
benchmark dose, with uncertainty factors generally
applied to reflect limitations of the data used.
Generally used in EPA's noncancer health
assessments. Durations include acute, short-term,
subchronic, and chronic.
Relevant study - Studies that are applicable or
pertinent, but not necessarily the most important to
derive exposure factors.
Representativeness - The degree to which a sample is,
or samples are, characteristic of the whole medium,
exposure, or dose for which the samples are being used
to make inferences.
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Risk - The probability of an adverse effect in an
organism, system, or (sub)population caused under
specified circumstances by exposure to an agent.
Risk assessment - A process intended to calculate or
estimate the risk to a given target organism, system, or
(sub)population, including the identification of
attendant uncertainties, following exposure to a
particular agent, taking into account the inherent
characteristics of the agent of concern as well as the
characteristics of the specific target system. The risk
assessment process includes four steps: hazard
identification, hazard characterization (related term:
Dose-response assessment), exposure assessment, and
risk characterization. It is the first component in a risk
analysis process.
Risk characterization - The qualitative and, wherever
possible, quantitative determination, including
attendant uncertainties, of the probability of occurrence
of known and potential adverse effects of an agent in
a given organism, system, or (sub)population, under
defined exposure conditions. Risk characterization is
the fourth step in the risk assessment process.
Risk communication - Interactive exchange of
information about (health or environmental) risks
among risk assessors, managers, news media,
interested groups, and the general public.
Route - The way a chemical or pollutant enters an
organism after contact, e.g., by ingestion, inhalation,
or dermal absorption.
Sample - A small part of something designed to show
the nature or quality of the whole. Exposure-related
measurements are usually samples of environmental or
ambient media, exposures of a small subset of a
population for a short time, or biological samples, all
for the purpose of inferring the nature and quality of
parameters important to evaluating exposure.
Scenario uncertainty - Uncertainty regarding missing
or incomplete information needed to fully define
exposure and dose.
Screening-level assessment - An exposure assessment
that examines exposures that would fall on or beyond
the high end of the expected exposure distribution.
Secondary data/analysis - The reanalysis of data
collected by other individuals or group; an analysis of
data for purposes other than those for which the data
were originally collected.
Sensitivity analysis - Process of changing one variable
while leaving the others constant to determine its effect
on the output. This procedure fixes each uncertain
quantity at its credible lower and upper bounds
(holding all others at their nominal values, such as
medians) and computes the results of each combination
of values. The results help to identify the variables that
have the greatest effect on exposure estimates and help
focus further information-gathering efforts.
Serving sizes - The quantities of individual foods
consumed per eating occasion. These estimates maybe
useful for assessing acute exposures.
Short-term exposure - Repeated exposure for more
than 24 hours, up to 30 days.
Soil - Particles of unconsolidated mineral and/or
organic matter from the earth's surface that are located
outdoors, or are used indoors to support plant growth.
Soil adherence - The quantity of soil that adheres to
the skin and from which chemical contaminants are
available for uptake at the skin surface.
Soil ingestion - The intentional or unintentional
consumption of soil, resulting from various behaviors
including, but not limited to, mouthing, contacting
dirty hands, eating dropped food, or consuming soil
directly. Soil-pica is a form of soil ingestion that is
characterized by the recurrent ingestion of unusually
high amounts of soil (i.e., on the order of 1,000 - 5,000
milligrams per day or more). Geophagy is also a form
of soil ingestion defined as the intentional ingestion of
earths and is usually associated with cultural practices.
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Spatial variability - Variability across location,
whether long- or short-term.
Subsistence fishermen - Individuals who consume
fresh caught fish as a major source of food.
Surface area - Coating, triangulation, and surface
integration are direct measurement techniques that
have been used to measure total body surface area and
the surface area of specific body parts. Consideration
has been given for differences due to age, gender, and
race. Surface integration is performed by using a
planimeter and adding the areas.
Surface integration - Method used to measure skin
surface area in which a planimeter is used to measure
areas of the skin, and the areas of various surfaces are
summed.
Survey response methodology - Responses to survey
questions are analyzed. This methodology includes
questions asked of children directly, or their care
givers, about behaviors affecting exposures.
Tap water from food manufacturing - Water used in
industrial production of foods.
Temporal variability - Variability over time, whether
long- or short-term.
Threshold - Dose or exposure concentration of an
agent below which a stated effect is not observed or
expected to occur.
Time-averaged exposure - The time-integrated
exposure divided by the exposure duration. An
example is the daily average exposure of an individual
to carbon monoxide. (Also called timeweighted
average exposure.)
Total tap water - Water consumed directly from the
tap as a beverage or used in the preparation of foods
and beverages (i.e., coffee, tea, frozen juices, soups,
etc.).
Total fluid intake - Consumption of all types of fluids
including tapwater, milk, soft drinks, alcoholic
beverages, and water intrinsic to purchased foods.
Tracer-element studies - Soil ingestion studies that
use trace elements found in soil and poorly
metabolized in the human gut as indicators of soil
intake.
Triangulation - Method used to measure skin surface
area in which areas of the body are marked into
geometric figures, then their linear dimensions are
calculated.
Uncertainty - Uncertainty represents a lack of
knowledge about factors affecting exposure or risk and
can lead to inaccurate or biased estimates of exposure.
The types of uncertainty include: scenario, parameter,
and model.
Upper percentile - Values in the upper tail (i.e.,
between 90th and 99.9th percentile) of the distribution
of values for a particular exposure factor. Values at
the upper end of the distribution of values for a
particular set of data.
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Glossary
Uptake - The process by which a substance crosses an
absorption barrier and is absorbed into the body.
Variability - Variability arises from true heterogeneity
across people, places or time and can affect the
precision of exposure estimates and the degree to
which they can be generalized. The types of variability
include: spatial, temporal, and inter-individual.
Ventilation Rate (VR) - Alternative term for
inhalation rate or breathing rate. Usually measured as
minute volume, i.e. volume (liters) of air exhaled per
minute.
Wet-weight intake rates - Intake rates that are based
on the wet (or whole) weight of the food consumed.
This in contrast to dry-weight intake rates.
Glossary entries adapted from:
International Programme on Chemical Safety (2004).
IPCS Risk Assessment Terminology.
Available on-line at:
http://www.who.int/ipcs/methods/harmoniz
ation/areas/ipcsterminologypartsland2.pdf
U.S. EPA (1992) Guidelines for exposure assessment.
Washington, DC: Office of Research and
Development, Office of Health and
Environmental Assessment. EPA/600/2-
92/001.
U.S. EPA. (1997) Exposure Factors Handbook
Revised. Washington, DC: U.S.
Environmental Protection Agency, Office of
Research and Development. EPA/600/P-
95/002F.
Child-Specific Exposure Factors Handbook Page
September 2008 G-ll
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