DRAFT EPA/600/P-00/002A
DO NOT CITE OR QUOTE June 2000
External Review Draft
U S EPA Headquarters Library
Mail code 3201
1200 Pennsylvania Avenue NW
Washington DC 20460
CHILD-SPECIFIC EXPOSURE FACTORS HANDBOOK
NOTICE
THIS DOCUMENT IS A PRELIMINARY DRAFT. It has not been formally released by the
U.S. Environmental Protection Agency and should not at this stage be construed to represent
Agency policy. It is being circulated for comment on its technical accuracy and policy
implications.
U.S. Environmental Protection Agency
National Center for Environmental Assessment
Office of Research and Development
Washington, DC 20460
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DISCLAIMER
This document is an external draft for review purposes only and does not constitute U.S.
Environmental Protection Agency policy. Mention of trade names or commercial products does
not constitute endorsement or recommendation for use.
n
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TABLE OF CONTENTS
1. INTRODUCTION 1-1
1.1 BACKGROUND 1-1
1.2 PURPOSE 1-3
1.3 INTENDED AUDIENCE 1-3
1.4 SELECTION OF STUDIES FOR THE HANDBOOK 1-4
1.5 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
FACTORS ! 1-6
1.6 CHARACTERIZING VARIABILITY 1-7
1.7 USING THE HANDBOOK IN AN EXPOSURE ASSESSMENT 1-10
1.7.1 General Equation for Calculating Dose 1-11
1.8 FUTURE OR ON-GOING WORK 1-15
1.9 RESEARCHNEEDS 1-16
1.10 ORGANIZATION , 1-17
1.11 REFERENCES FOR CHAPTER 1 1-19
2. BREAST MILK INTAKE 2-1
2.1 INTRODUCTION 2-1
2.2 STUDIESONBREASTMILKINTAKE 2-2
2.3 STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST
MILK 2-5
2.4 OTHERFACTORS 2-7
2.5 RECOMMENDATIONS 2-8
2.6 REFERENCES FOR CHAPTER 2 2-10
-3. FOOD INTAKE 3-1
3.1 INTRODUCTION 3-1
3.2 INTAKE RATE DISTRIBUTIONS FOR VARIOUS FOOD TYPES 3-3
3.3 FISHINTAKERATES 3-6
3.3.1 General Population Studies 3-6
3.3.2 Freshwater Recreational Study 3-12
3.3.3 Native American Subsistence Study 3-14
3.4 FAT INTAKE 3-15
3.5 TOTAL DIETARY INTAKE AND CONTRIBUTIONS TO DIETARY
INTAKE 3-17
3.6 INTAKE OF HOME-PRODUCED FOODS 3-18
3.7 SERVING SIZE STUDY BASED ON THE USDANFCS 3-23
3.8 CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE
RATES 3-23
3.9 FAT CONTENT OF MEAT AND DAIRY PRODUCTS 3-24
in
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TABLE OF CONTENTS (Continued)
3.10 RECOMMENDATIONS 3-25
3.11 REFERENCES FOR CHAPTER 3 3-27
APPENDIX 3A
APPENDDC3B
APPENDDC3C
APPENDIX 3D
Calculations Used in the 1994-96 CSFH Analysis to Correct for Mixtures
Food Codes and Definitions Used in Analysis of the 1994-96 Usda CSFH
Data
Sample Calculation of Mean Daily Fat Intake Based On cdc (1994) Data
Food Codes and Definitions Used in Analysis of the 1987-88 USDANFCS
Data
4. DRINKING WATER INT ARE 4-1
4.1 INTRODUCTION 4-1
4.2 DRINKING WATER INTAKE STUDIES 4-2
4.3. PREGNANT AND LACTATING WOMEN 4-7
4.4 RECOMMENDATIONS 4-8
4.4 REFERENCES FOR CHAPTER 4 4-9
5. SOIL INGESTION AND PICA 5-1
5.1 INTRODUCTION 5-1
5.2 SOILINTAKE STUDIES 5-1
5.3 PREVALENCEOFPICA 5-18
5.4 DELIBERATE SOIL INGESTION AMONG CHILDREN 5-19
5.5 RECOMMENDATIONS 5-25
5.6 REFERENCES FOR CHAPTER 5 5-27
6. OTHER NON-DIETARY INGESTION FACTORS 6-1
6.1 INTRODUCTION 6-1
6.2 STUDIES RELATED TO NON-DIETARY INGESTION 6-2
6.3 RECOMMENDATIONS 6-9
6.4 REFERENCES FORCHAPTER6 6-11
7. INHALATION ROUTE 7-1
7.1 INTRODUCTION 7-1
7.2 INHALATION RATE STUDIES 7-1
7.3 RECOMMENDATIONS 7-7
7.4 REFERENCES FOR CHAPTER 7 7-9
APPENDIX 7A
Ventilation Data , 7A-1
IV
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TABLE OF CONTENTS (Continued)
8. DERMAL ROUTE 8-1
8.1 INTRODUCTION 8-1
8.2 SURFACE AREA 8-2
8.2.1 Background 8-2
8.2.2 Measurement Techniques 8-2
8.2.3 Body Surface Area Studies 8-3
8.2.4 Application of Body Surface Area Data 8-7
8,3 SOE, ADHERENCE TO SKIN 8-8
8.3.1 Background 8-8
8.3.2 Soil Adherence to Skin Studies 8-9
8.4 RECOMMENDATIONS 8-12
8.4.1 Body Surface Area ; 8-12
8.4.2 Soil Adherence to Skin 8-13
8.5 REFERENCES FOR CHAPTER 8 '.'. 8-15
APPENDIX 8A Formulae for Total Body Surface Area
9. ACTIVITY FACTORS 9-1
9.1 INTRODUCTION 9-1
9.2 ACTIVITY PATTERNS 9-1
9.3 RECOMMENDATIONS 9-11
9.3.1 Recommendations for Activity Patterns 9-11
9.3.2 Summary of Recommended Activity Factors 9-13
9.4 REFERENCES FOR CHAPTER9 9-14
10. CONSUMER PRODUCTS 10-1
10.1 BACKGROUND 10-1
10.2 CONSUMER PRODUCTS USE STUDIES 10-1
10.3 RECOMMENDATIONS I 10-2
10.4 REFERENCES FOR CHAPTER 10 10-3
11. BODY WEIGHT STUDIES 11-1
11.1 INTRODUCTION 11-1
11.2 BODY WEIGHT STUDIES 11-1
11.3 RECOMMENDATIONS 11-3
11.4 REFERENCES FOR CHAPTER 11 11-5
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TABLE OF CONTENTS (Continued)
12. LIFETIME 12-1
12.1 INTRODUCTION 12-1
12.2 DAT A ON LIFETIME 12-1
12.3 RECOMMENDATIONS 12-2
12.4 REFERENCES FOR CHAPTER 12 12-3
VI
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LIST OF TABLES
Table 1-1. Considerations Used to Rate Confidence in recommended Values 1-21
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings ..... 1-22
Table 1-3. Characterization of Variability in Exposure Factors 1-24
Table 2-1. Daily Intakes of Breast Milk 2-11
Table 2-2. Breast Milk Intake for Infants Aged 1 to 6Months 2-11
Table 2-3. Breast Milk Intake among Exclusively Breast-fed
Infants During the First 4 Months of Life 2-12
Table 2-4. Breast Milk Intake During a 24-hour Period 2-13
Table 2-5. Breast Milk Intake Estimated by the Darling Study 2-14
Table 2-6. Lipid Content of Human Milk and Estimated Lipid Intake among Exclusively
Breast-fed Infants 2-14
Table 2-7. Predicted Lipid Intakes for Breast-fed Infants under 12 Months of Age 2-14
Table 2-8. Number of Meals per Day 2-15
Table 2-9. 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*, by Ethnic Background
and Selected Demographic Variables 2-16
Table 2-10. Confidence in Breast Milk Intake Recommendations 2-17
Table 2-11. Breast Milk Intake Rates Derived from Key Studies 2-18
Table 2-12. Summary of Recommended Breast Milk And Lipid Intake Rates 2-19
Table 3-1. Weighted and Unweighted Number of Observations, 1994/96 CSFn Analysis .. 3-29
Table 3-2. Per Capita Intake of the Major Food Groups (g/kg-day as consumed) 3-30
Table 3-3. Per Capita Intake of Individual Foods (g/kg-day as consumed) 3-31
Table 3-4. Per Capita Intake of USDA Categories of Vegetables and Fruits (g/kg-day as
consumed) 3-33
Table 3-5. Per Capita Intake of Exposed/Protected Fruit and Vegetable Categories
(g/kg-day as consumed) 3-34
Table 3-6. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender
- As Consumed 3-35
Table 3-7. Consumers Only Distribution of Fish (Finfish and Shellfish) Intake by Age and
Gender - As Consumed 3-36
Table 3-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-37
Table 3-9. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-38
Table 3-10. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age 3-39
Table 3-11. Best Fits of Lognormal Distributions Using the Nonlinear Optimization (Nlo)
Method 3-40
vn
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LIST OF TABLES (Continued)
Table 3-12. Number of Respondents Reporting Consumption of a Specified Number of
Servings of Seafood in 1 Month and Source of Seafood Eaten .... - 3-40
Table 3-13. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households
With Recreational Fish Consumption 3-41
Table 3-14. Children's 5 and Under Fish Consumption Rates - Throughout Year 3-41
Table 3-15. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/day) , 3-42
Table 3-16. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/kg/day) 3-43
Table 3-17. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender 3-44
Table 3-18. Per Capita Total Dietary Intake 3-45
Table 3-19. Per Capita Intake of Major Food Groups (g/day, as consumed) 3-46
Table 3-20. Per Capita Intake of Major Food Groups (g/kg/day, as consumed) 3-48
Table 3-21. 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 3-50
Table 3-22. 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 3-52
Table 3-23. 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 3-54
Table 3-24. 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 3-56
Table 3-25. 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 3-58
Table 3-26. 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 3-60
Table 3-27. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data
Used in Analysis of Food Intake 3-62
Table 3-28. Consumer Only Intake of Homegrown Foods (g/kg-day)' - All Regions
Combined 3-63
Table 3-29. Percent Weight Losses from Food Preparation 3-64
Table 3-30. Quantity (as consumed) of Food Groups Consumed Per Eating Occasion and the
Percentage of Individuals Using These Foods in Three Days 3-65
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions 3-67
Table 3-32. Percent Moisture Content for Selected Fish Species 3-71
viii
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LIST OF TABLES (Continued)
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of
Edible Portions) of Selected Meat, Dairy, and Fish Products ...;..... 3-74
Table 3-34. Fat Content of Meat Products 3-78
Table 3-3S. Summary of Recommended Values for Per Capita Intake of Foods, As
Consumed 3-79
Table 3-36. Confidence Intake Recommendations for Various Foods, Including Fish
(General Population) 3-81
Table 3-37. Confidence Intake Recommendations for Fish Consumption - Recreational
Freshwater Angler Population 3-82
Table 3-38. Confidence Intake Recommendations for Fish Consumption - Native American
Subsistence Population 3-83
Table 4-1. Estimated Direct and Indirect Community Total Water Ingestion By Source
for U.S. Population 4-10
Table 4-2. Estimate of Total Direct and Indirect Water Ingestion, All Sources By Broad
Age Category for U.S. Children 4-11
Table 4-3. Estimate of Direct and Indirect Community Water Ingestion By Fine Age
Category for U.S. Children 4-12
Table 4-4. Estimate of Direct and Indirect Community Water Ingestion By Broad Age
Category for U.S. Children 4-13
Table 4-5. Estimate of Direct and Indirect Bottled Water Ingestion By Fine Age Category
for U.S. Children 4-14
Table 4-6. Estimate of Direct and Indirect Bottled Water Ingestion By Broad Age Category
for U.S. Children ...." 4-15
Table 4-7. Estimate of Direct and Indirect Other Water Ingestion By Fine Age Category
for U.S. Children : 4-16
Table 4-8. Estimate of Direct and Indirect Other Water Ingestion By Broad Age Category
for U.S. Children 4-17
Table 4-9. Chi-square GOF statistics for 12 Models, Tapwater Data, Based on Maximum
Likelihood Method of Parameter Estimation 4-18
Table 4-10. P-Values for Chi-Square GOF Tests of 12 Models, Tapwater Data 4-18
Table 4-11. Results of Statistical Modeling of Tapwater Data (intake Rates in dL/kg-day)
Using 5-Parameter Generalized F and 2-Parameter Gamma, Lognormal .and Weibull
Modles '. 4-19
Table 4-12. Total Fluid Intake of Women 15-49 Years Old 4-20
Table 4-13. Total Tapwater Intake of Women 15-49 Years Old 4-20
Table 4-14. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged
15-49 Years 4-21
Table 4-15. Summary of Recommended Community Drinking Water Intake Rates 4-22
Table 4-16. Confidence in Tapwater Intake Recommendations 4-23
Table 5-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium
Concentrations 5-29
ix
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LIST OF TABLES (Continued)
Table 5-2. Calculated Soil Ingestion by Nursery School Children 5-30
Table 5-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children 5-31
Table 5-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements .. 5-31
Table 5-5. Soil and Dust Ingestion Estimates for Children Ages 1-4 Years 5-32
Table 5-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium
as Tracer Elements 5-32
Table 5-7. Geometric Mean (Gm) and Standard Deviation (Gsd) Ltm Values for Children at
Daycare Centers and Campgrounds 5-33
Table 5-8. Estimated Geometric Mean Ltm Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period 5-34
Table 5-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64
Children (Mg/day) 5-35
Table 5-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected over 365 Days 5-35
Table 5-11. Estimated Soil Ingestion Rate Summary Statistics And Parameters for Distributions
Using Binder et Al. (1986) Data with Actual Fecal Weights 5-36
Table 5-12. Positive/negative Error (Bias) in Soil Ingestion Estimates in the Calabrese et al.
(1989) Mass-balance Study: Effect on Mean Soil Ingestion Estimate (Mg/day) .... 5-37
Table 5-13. Soil Ingestion Estimates for Median and Best Four Trace Elements Based on
Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr ... 5-38
Table 5-14. Dust Ingestion Estimates for Median and Best Four Trace Elements Based
on Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr 5-39
Table 5-15. Daily Soil Ingestion Estimation in a Soil-pica Child by Tracer and by Week
(mg/day) 5-40
Table 5-16. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child 5-41
Table 5-17. Daily variation of Soil Ingestion by Children Displaying Soil Pica in
Wong (1988) 5-42
Table 5-18. Prevalence of Non-Food Ingestion Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month 5-43
Table 5-19. Average Outdoor Object Mouthing Scores for Children by Age, Frequency of
Sand/Dirt Play, and General Mouthing Quartiles 5-46
Table 5-20. Summary of Estimates of Soil Ingestion by Children 5-47
Table 5-21. Summary of Recommended Values for Soil Ingestion 5-47
Table 5-22. Confidence in Soil Intake Recommendation 5-48
Table 6-1. Extrapolated Total Mouthing Times Minutes per Day (time awake) 6-12
Table 6-2. Frequency of Contact, by Contact Variable Contacts per Hour 6-13
Table 6-3. Summary of Studies on Mouthing Behavior 6-14
Table 6-4. Summary of Mouthing Frequency Data 6-15
Table 6-5. Confidence in Mouthing Behavior Recommendations 6-16
Table 7-1. Calibration And Field Protocols For Self-monitoring of Activities
Grouped by Subject Panels 7-10
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LIST OF TABLES (Continued)
Table 7-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles,
And Self-estimated Breathing Rates 7-10
Table 7-3. Distribution of Predicted Intake Rates by Location And Activity Levels
For Elementary And High School Students 7-11
Table 7-4. Average Hours Spent Per Day in a Given Location and Activity
Level For Elementary (EL) and High School (HS) Students 7-11
Table 7-5. Distribution Patterns of Daily Inhalation Rates For Elementary (EL) And
High School (HS) Students Grouped by Activity Level 7-12
Table 7-6. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity Levels
For Laboratory Protocols 7-13
Table 7-7. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity
Levels in Field Protocols 7-14
Table 7-8. Comparisons of Estimated Basal Metabolic Rates (BMR) With Average
Food-energy Intakes For Individuals Sampled in The 1977-78 NFCS 7-15
Table 7-9. Daily Inhalation Rates Calculated From Food-energy Intakes 7-16
Table 7-10. Daily Inhalation Rates Obtained From The Ratios Of Total Energy
Expenditure to Basal Metabolic Rate (BMR) 7-17
Table 7-11. Inhalation Rates For Short-term Exposures 7-18
Table 7-12. Confidence in Inhalation Rate Recommendations 7-19
Table 7-13. Summary of Recommended Values For Inhalation 7-20
Table 7-14. Summary of Children's Inhalation Rates For Short-Term Exposure Studies ... 7-21
Table 8-1. Total Body Surface Area of Male Children in Square Meters 8-17
Table 8-2. Total Body Surface Area of Female Children in Square Meters 8-18
Table 8-3. Percentage of Total Body Surface Area by Body Part For Children 8-19
Table 8-4. Descriptive Statistics For Surface Area/body Weight (SA/BW) Ratios (m2/kg).. 8-20
Table 8-5. Clothing choices and assumed body surface areas exposed 8-21
Table 8-6. Estimated skin surface exposed during warm weather outdoor play for children
under age 5 (based on SCS-I data) 8-21
Table 8-7. Number and percentage of respondents with children and those reporting
outdoor play activities in both warm and cold weather 8-22
Table 8-8. Play frequency and duration for all child players (from SCS-II data) .. 8-22
Table 8-9. Hand washing and bathing frequency for all child players (from SCS-II data) ... 8-23
Table 8-10. NHAPS and SCS-II play duration comparison 8-23
Table 8-11. NHAPS and SCS-H hand wash frequency comparison 8-24
Table 8-12. Summary of Field Studies 8-25
Table 8-13. Geometric Mean And Geometric Standard Deviations of Soil Adherence
by Activity And Body Region 8-26
Table 8-14. Summary of Groups Assayed in Round 2 of Field Measurements :.. 8-27
Table 8-15. Attire for Individuals within Children's Groups Studied 8-28
XI
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LIST OF TABLES (Continued)
Table 8-16. Geometric Means (Geometric Standard Deviations) of Round 2 Post-activity
Loadings 8-29
Table 8-17. Summary of Controlled Green House Trials - Children Playing 8-30
Table 8-18. Preactivity Loadings Recovered from Greenhouse Trial Children Volunteers .. 8-31
Table 8-19. Summary of Recommended Values For Skin Surface Area 8-33
Table 8-20. Confidence in Body Surface Area Measurement Recommendations 8-34
Table 8-21. Confidence in Soil Adherence to Skin Recommendations 8-35
Table 9-1. Mean Time Spent (minutes) Performing Major Activities Grouped by Age,
Sex and Type of Day 9-15
Table 9-2. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for
Five Different Age Groups 9-16
Table 9-3. Mean Time Spent Indoors and Outdoors Grouped by Age and Day of the
Week 9-17
Table 9-4. Mean Time Spent at Three Locations for both GARB and National Studies
(ages 12 years and older) 9-18
Table 9-5. Mean Time Spent (minutes/day) in Various Microenvironrnents Grouped by
Total Population and Gender (12 years and over) in the National and CARS Data .. 9-19
Table 9-6. Mean Time Spent (minutes/day) in Various Microenvironments by Type
of Day for the California and National Surveys 9-20
Table 9-7. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups
for the National and California Surveys 9-21
Table 9-8. Mean Time (minutes/day) Children Ages 12 Years and Under Spent in Ten Major
Activity Categories for All Respondents 9-22
Table 9-9. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and
Gender 9-23
Table 9-10. Mean Time Children Ages 12 Years and Under Spent in Ten Major Activity
Categories Grouped by Seasons and Regions 9-24
Table 9-11. Mean Time Children Ages 12 Years and Under Spent in Six Major Location
Categories for All Respondents (minutes/day) 9-25
Table 9-12. Mean Time Children Spent in Six Location Categories Grouped by Age and
Gender 9-25
Table 9-13. Mean Time Children Spent in Six Location Categories Grouped by Season and
Region 9-26
Table 9-14. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by
All Respondents, Age, and Gender 9-26
Table 9-15. Mean Time Spent Indoors and Outdoors Grouped by Age 9-31
Table 9-16. Range of Recommended Defaults for Dermal Exposure Factors 9-32
Table 9-17. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of
Respondents 9-32
xn
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LIST OF TABLES (Continued)
Table 9-18. Time (minutes) Spent Taking a Shower and Spent in the Shower Room
After Taking a Shower by the Number of Respondents 9-32
Table 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately
After Showering '. 9-33
Table 9-20. Total Time Spent Altogether in the Shower or Bathtub and Time Spent
in the Bathroom Immediately After by Number of Respondents 9-33
Table 9-21. Total Number of Minutes Spent Altogether in the Shower or Bathtub and Spent
in the Bathroom Immediately Following a Shower or Bath 9-34
Table 9-22. Range of Number of Times Washing the Hands at Specified Daily Frequencies
by the Number of Respondents 9-34
Table 9-23. Number of Minutes Spent Working or Being Near Excessive Dust in the Air
(minutes/day) 9-34
Table 9-24. Range of Number of Times per Day a Motor Vehicle was Started in a Garage
or Carport and Started with the Garage Door Closed 9-35
Table 9-25. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass 9-35
Table 9-26. Number of Minutes Spent Playing in Sand, Gravel, Dirt or Grass
(minutes/day) 9-36
Table 9-27. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of
Respondents 9-36
Table 9-28. Number of Minutes Spent Playing on Grass (minutes/day) 9-36
Table 9-29. Number of Times Swimming in a Month in Freshwater Swimming Pool by the
Number of Respondents 9-37
Table 9-30. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool
(minutes/month) 9-37
Table 9-31. Range of the Average Amount of Time Actually Spent in the Water by Swimmers
by the Number of Respondents 9-37
Table 9-32. Statistics for 24-Hour Cumulative Number of Minutes Spent Playing Indoors and
Outdoors 9-38
Table 9-33. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping 9-38
Table 9-34. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time
School 9-38
Table 9-35. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
and for Time Spent in Sports/Exercise 9-39
Table 9-36. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
and Spent'Walking 9-39
Table 9-37. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing 9-40
Table 9-38. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking .... 9-40
Table 9-39. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School
and Indoors at a Restaurant 9-40
Table 9-40. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on
School Grounds/Playground, at a Park/Golf Course, and at a Pool/River/Lake 9-41
xiii
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LIST OF TABLES (Continued)
Table 9-41. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Bathroom, Bedroom, and in a Residence (All Rooms) 9-42
Table 9-42. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a
Vehicle 9-43
Table 9-43. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the
residence) and Outdoors Other Than Near a Residence or Vehicle, Such as Parks, Golf
Courses, or Farms 9-43
Table 9-44. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery
Stores, or Other Stores 9-43
Table 9-45. Statistics for 24-hour Cumulative Number of Minutes Spent with Smokers
Present 9-44
Table 9-46. Range of Time (minutes) Spent Smoking Based on the Number of
Respondents 9-45
Table 9-47. Number of Minutes Spent Smoking (minutes/day) 9-45
Table 9-48. Gender and Age Groups 9-46
Table 9-49. Assignment of At-Home Activities to Ventilation Levels for Children 9-47
Table 9-50. Aggregate Time Spent (minutes/day) At-Home in Activity Groups
by Adolescents and Children , 9-48
Table 9-51. Comparison of Mean Time (minutes/day) Spent At-Home by Gender
(Adolescents) 9-48
Table 9-52. Comparison of Mean Time (minutes/day) Spent At-Home by Gender and Age
for Children 9-48
Table 9-53. Number of Person-Days/Individuals* for Children in CHAD Database 9-49
Table 9-54. Number of Hours Per Day Children Spend in Various Microenvironments by Age
Average ± Std. Dev. (Percent of Children Reporting X) Hours in Microenvironment) 9-50
Table 9-55. Average Number of Hours Per Day Children Spend Doing Various
Macroactivities While Indoors at Home by Age 9-51
Table 9-56. Confidence in Activity Patterns Recommendations 9-52
Table 9-57. Summary of Activity Pattern Studies 9-59
Table 9-58. Summary of Mean Time Spent Indoors and Outdoors from Several Studies ... 9-60
Table 9-59. Summary of Recommended Values for Activity Factors 9-61
Table 10-1. Consumer Products Found in the Typical U.S. Household 10-4
Table 10-2. Number of Minutes Spent in Activities Working with or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day) 10-7
Table 10-3 Number of Minutes Spent Using Any Microwave Oven (minutes/day) 10-7
Table 10-4. Number of Respondents Using a Humidifier at Home 10-7
Table 10-5. Number of Respondents Indicating that Pesticides Were Applied by the Professional
at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies .... 10-8
Table 10-6. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies . ..'. 10-8
xiv
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LIST OF TABLES (Continued)
Table 11-1. Smoothed Percentiles of Weight (In Kg) by Sex And Age: Statistics From
NCHS And Data From Pels Research Institute, Birth to 36 Months 11-6
Table 11-2. Body Weights of Children* (Kilograms) 11-9
Table 11-3. Weight in Kilograms For Males 6 Months-19 Years of Age-number Examine, Mean,
Standard Deviation, and Selected Percentiles, by Sex and Age:
United States, 1976-1980 11-10
Table 11-4. Weight in Kilograms For Females 6 Months-19 Years of Age - Number
Examine, Mean, Standard Deviation, And Selected Percentiles, By Sex And Age:
United States, 1976-1980 11-11
Table 11-5. Best-fit Parameters for Lognormal Distributions 11-12
Table 11-6. Statistics for Probability Plot Regression Analyses Male's Body Weights
6 Months to 20 Years of Age 11-13
Table 11-7. Body Weight Estimates (in kilograms) by Age and Gender, U.S. Population
1988-94 ; , 11-14
Table 11-8. Body Weight Estimates (in kilograms) by Age, U.S. Population 1988-94 11-15
Table 11-9. Summary of Recommended Values for Body Weight 11-16
Table 11-10. Confidence in Body Weight Recommendations 11-17
Table 12-1. Expectation of Life at Birth, 1980 to 1993, And Projections, 1995 to
2010 (Years) 12-4
Table 12-2. Expectation of Life by Race, Sex, And Age: 1996 12-5
Table 12-3. Confidence in Lifetime Expectancy Recommendations 12-6
xv
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LIST OF FIGURES
Figure 1-1. Schematic of Dose and Exposure: Oral Route 1-12
Figure 8-1. Schematic of Dose and Exposure: Dermal Route 8-2
Figure 8-2. • Skin Coverage as Determined by Fluorescence vs. Body Part for Adults
Transplanting Plants and for Children Playing in Wet Soils 8-32
Figure 8-3. Gravimetric Loading vs. Body Part for Adult Transplanting Plants in Wet Soil
and for Children Playing in Wet and Dry Soils 8-32
Figure 9-1. Distribution of the Number of Hours per Day Study Children Spent Indoors
at Home 9-27
Figure 9-2. Distribution of the Number of Hours per Day Study Children Spent Indoors
Away from Home 9-28
Figure 9-3. Distribution of the Number of Hours per Day Study Children Spent Outdoors
at Home 9-29
Figure 9-4. Distribution of the Number of Hours per Day Study Children Spent Outdoors
Away from Home 9-30
Figure 11-1. Weight by Age percentiles for Girls Aged Birth-36 Months 11-7
Figure 11-2. Weight by Age Percentiles for Boys Aged Birth-36 Months 11-8
Figure 11-3. Mean Body Weights Estimates, U.S. Population, 1988-94 11-18
Figure 11-4. Median Body Weights Estimates, U.S. Population, 1988-94 11-19
xvi
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PREFACE
The National Center for Environmental Assessment (NCEA) of EPA's Office of Research
and Development (ORD) has prepared this handbook to address factors commonly used in
exposure assessments for children. Children are often more heavily exposed to environmental
toxicants than adults. They consume more food and water and have higher inhalation rates per
pound of body weight than adults. Young children play close to the ground and come into
contact with contaminated soil outdoors and with contaminated dust on surfaces and carpets
indoors. As another example, exposure to chemicals in breast milk affects infants and young
children.
The National Center for Environmental Assessment has published the Exposure Factors
Handbooks 1997. This document includes exposure factors and related data on children, as well
as adults. However, the EPA Program Offices have identified the need to prepare a document
specifically for children's exposure factors. The goal of the Child-Specific Exposure Factors
Handbook is to fulfill this need.
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FOREWORD
The National Center for Environmental Assessment (NCEA) of EPA's Office of Research
and Development (ORD) has five main functions: (1) providing risk assessment research,
methods, and guidelines; (2) performing health and ecological assessments; (3) developing,
maintaining, and transferring risk assessment information and training; (4) helping ORD set
research priorities; and (5) developing and maintaining resource support systems for NCEA. The
activities under each of these functions are supported by and respond to the needs of the various
program offices. In relation to the first function, NCEA sponsors projects aimed at developing or
refining techniques used in exposure assessments.
The Exposure Factors Handbook was first published in 1989 to provide statistical data on
the various factors used in assessing exposure for the general population; it was revised and
published again in 1997. This Child-Specific Exposure Factors Handbook is being prepared to
focus on various factors used in assessing exposure, specifically for children ages 0-19 years old.
The recommended values are based solely on our interpretations of the available data. In many
situations different values may be appropriate to use in consideration of policy, precedent or other
factors.
XVlll
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
The National Center for Environmental Assessment (NCEA), Office of Research and
Development was responsible for the preparation of this handbook. This document has been
prepared by the Exposure Assessment Division of Versar Inc. in Springfield, VA under EPA
Contract No. 68-W-99-041. Jackie Moya served as Work Assignment Manager, providing
overall direction, technical assistance, and serving as contributing author.
AUTHORS WORD PROCESSING
Versar Inc. Versar Inc.
Linda Phillips Susan Perry
Patricia Wood Valerie Schwartz
Marit Espevik
Todd Perryman
Clarkson Meredith
Didi Sinkowski
U.S. EPA
Jacqueline Moya
The following EPA individuals reviewed an earlier draft of this document and provided valuable
comments:
Amina Wilkins, U.S. EPA, National Center for Environmental Assessment
Denis R Borum, U.S. EPA, Office of Water, Health and Ecological Criteria Division
Lynn Flowers, U.S. EPA, Region ffl
Youngmoo Kim, U.S. EPA, Region VI
Tom McCurdy, U.S. EPA, National Exposure Research Laboratory
Nicole Tulve, U.S. EPA, National Exposure Research Laboratory
Valerie Zartarian, U.S. EPA, National Exposure Research Laboratory
In addition, the National Exposure Research Laboratory (NERL) of the Office of Research and
Development made an important contribution to this handbook by conducting additional analysis
of mouthing behavior data from the Davis 1995 study. Data analysis was conducted by Nicole
Tulve.
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1. INTRODUCTION
1 1.1 BACKGROUND
2 Because of differences in physiology and behaviors, exposures among children are
3 expected to be different than among adults. Children may be more highly exposed to
4 environmental toxicants than adults, because they consume more food and water, and have
5 higher inhalation rates per unit of body weight, and have higher surface area to volume than
6 adults. Also, young children play close to the ground and are more likely to come into contact
7 with contaminated soil outdoors and with contaminated dust on surfaces and carpets indoors.
8 Children may also be exposed to contaminants as a result of hand-to-mouth and object-to-mouth
9 activities as a result of behaviors existing during certain phases of childhood. As another
10 example, exposure to chemicals in breast milk affects specifically infants and young children. In
11 terms of risk, children may also be more vulnerable to environmental pollutants because of
12 differences in absorption, excretion, and metabolism (U.S. EPA, 1997a).
13 In April, 1997, President Clinton signed an Executive Order to Protect Children from
Environmental Health Risks and Safety Risks. The Order requires all federal agencies to address
15 health and safety risks to children, coordinate research priorities on children's health, and ensure
16 that their standards take into account special risks to children. To implement the President's
17 Executive Order, EPA established the Office of Children's Health Protection (OCHP), and
18 offices within EPA increased their efforts to provide a safe and healthy environment for children
19 by ensuring that all regulations, standards, policies, and risk assessments take into account risks
20 to children. Recent legislation, such as the Food Quality Protection Act and the Safe Drinking
21 Water Act amendments, has made children's health issues more explicit and research on
22 children's health issues is continually expanding. As a result of the emphasis on children's risk,
23 the EPA Office of Research and Development's (ORD) National Center for Environmental
24 Assessment (NCEA) issued a Children's Risk Policy, which emphasized the need to evaluate
25 exposures and risks among this population and ORD developed a Strategy for Research on Risks
26 to Children (Children's Research Strategy) (U.S. EPA, 1997a; 1999a). The goal of the
27 Children's Research Strategy is to improve risk assessments for children. This Child-specific
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1 Exposure Factors Handbook is intended to support EPA/ORD/NCEA's efforts to improve
2 exposure and risk assessments for children.
3 In 1997, EPA/ORD/NCEA published the Exposure Factors Handbook (U.S. EPA,
4 1997b). The Handbook includes exposure factors and related data on both adults and children.
5 OCHP's recently-issued its child-related risk assessment policy and methodology guidance
6 document survey (U.S. EPA, 1999b), highlighted the Exposure Factors Handbook (U.S. EPA,
7 1997b) as a source of information on exposure factors for children. EPA's Children's
8 Environmental Health Yearbook (U.S. EPA, 1998) also listed the Exposure Factors Handbook as
9 a source of exposure information for children. However, the EPA Program Offices identified the
10 need to consolidate all children exposure data into one document. The goal of this Child-specific
11 Exposure Factors Handbook is to fulfill this need. This Handbook provides non-chemical-
12 specific data on exposure factors that can be used to assess doses from dietary and non-dietary
13 ingestion exposure, dermal exposure, and inhalation exposure among children.
14 This handbook provides exposure factors for children in the following areas:
15 • breast milk ingestion;
16 • food ingestion, including homegrown foods and other dietary-related data;
17 • drinking water ingestion;
18 • soil ingestion;
19 • rates of hand-to-mouth and object-to-mouth activity;
20 • dermal exposure factors such as surface areas and soil adherence;
21 • inhalation rates;
22 • duration and frequency in different locations and various microenvironments;
23 • duration and frequency of consumer product use;
24 • body weight data; and
25 • duration of lifetime.
26 This handbook is a compilation of available data from a variety of sources. Most of these
27 data have been described in detail in EPA's Exposure Factors Handbook (1997b). but data that
28 have been published subsequent to release of the Exposure Factors Handbook are also presented.
29 With very few exceptions, the data presented are the analyses of the individual study authors.
30 Since the studies included in this handbook varied in terms of their objectives, design, scope.
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1 presentation of results, etc., the level of detail, statistics, and terminology may vary from study to
2 study and from factor to factor. For example, some authors used geometric means to present
3 their results, while others used arithmetic means or distributions. Authors have sometimes used
4 different age ranges to describe data for children. Within the constraint of presenting the original
5 material as accurately as possible, EPA has made an effort to present discussions and results in a
6 consistent manner. Further, the strengths and limitations of each study are discussed to provide
7 the reader with a better understanding of the uncertainties associated with the values derived
8 from the study.
9
10 1.2 PURPOSE
11 The purpose of the Child-specific Exposure Factors Handbook is to: (1) summarize key
12 data on human behaviors and characteristics which affect children's exposure to environmental
13 contaminants, and (2) recommend values to use for these factors. These recommendations are
14 not legally binding on any EPA program and should be interpreted as suggestions which program
15 offices or individual exposure assessors can consider and modify as needed. Most of these
kl6 factors are best quantified on a site or situation-specific basis. The data presented in this
17 handbook have come from various sources, including the EPA's Exposure Factor Handbook
18 (U.S. EPA, I997b), government reports, and information presented in the scientific literature.
19 The handbook has strived to include discussions of the issues which assessors should consider in
20 assessing exposure among children, and may be used in conjunction with the EPA document:
21 EPA/600/R-99/060 July 1999, entitled Socio-demographic Data Used for Identifying Potentially
22 Highly Exposed Subpopulations of Children, which is currently being drafted and provides
23 population data for children.
24 •
25 1.3 INTENDED AUDIENCE
26 The Child-specific Exposure Factors Handbook may be used by exposure assessors
27 inside the Agency as well as outside, who need to obtain data on standard factors needed to
28 calculate childhood exposure to toxic chemicals.
29
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1
2
3
4
5
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7
g
9
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
** *»
jj
34
35
36
1.4 SELECTION OF STUDIES FOR THE HANDBOOK
Information in this handbook has been summarized from studies documented in the
scientific literature and other available sources. Studies were chosen that were seen as useful and
appropriate for estimating exposure factors. The handbook contains summaries of selected
studies published through 2000.
General Considerations
Many scientific studies were reviewed for possible inclusion in this handbook.
Generally, studies identified in the Exposure Factors Handbook (U.S. EPA, 1997b) as key
studies were also included in this children's document New studies that became available after
publication of the Exposure Factors Handbook were also included. Key studies from the
Exposure Factors Handbook were generally defined as the most useful for deriving exposure
factors. The recommended values for most exposure factors are based on the results of these
studies. As in the Exposure Factors Handbook, the key studies were selected based on the
following considerations:
• Level of peer review. Studies were selected predominantly from the peer-reviewed
literature and final government reports. Internal or interim reports were therefore
avoided.
• Accessibility: Studies were preferred that the user could access in their entirety if
needed.
• Reproducibility: Studies were sought that contained sufficient information so that
methods could be reproduced, or at least so the details of the author's work could be
accessed and evaluated.
• Focus on exposure factor of interest: Studies were chosen that directly addressed the
exposure factor of interest, or addressed related factors that have significance for the
factor under consideration. As an example of the latter case, a selected study
contained useful ancillary information concerning fat content in fish, although it did
not directly address fish consumption. •
• • Data pertinent to the U.S.: Studies were selected that addressed the U.S. population.
Data from populations outside the U.S. were sometimes included if behavioral
patterns and other characteristics of exposure were similar.
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1 • Primary data: Studies were deemed preferable if based on primary data, but studies
>2 based on secondary sources were also included where they offered an original
3 analysis. For example, the handbook cites studies of food consumption based on
4 original data collected by the USDA National Food Consumption Survey.
5
6 • Current information: Studies were chosen only if they were sufficiently recent to
7 ' represent current exposure conditions. This is an important consideration for those
8 factors that change with time.
9
10 • Adequacy of data collection period: Because most users of the handbook are
11 primarily addressing chronic exposures, studies were sought that utilized the most
12 appropriate techniques for collecting data to characterize long-term behavior.
13
14 • Validity of approach: Studies utilizing experimental procedures or approaches that
15 more likely or closely capture the desired measurement were selected. In general,
16 direct exposure data collection techniques, such as direct observation, personal
17 monitoring devices, or other known methods were preferred where available. If
18 studies utilizing direct measurement were not available, studies were selected that rely
19 on validated indirect measurement methods such as surrogate measures (such as heart
20 rate for inhalation rate), and use of questionnaires. If questionnaires or surveys were
21 used, proper design and procedures include an adequate sample size for the
22 population under consideration, a response rate large enough to avoid biases, and
23 avoidance of bias in the design of the instrument and interpretation of the results.
fc
25 • Representativeness of the population: Studies seeking to characterize the national
26 population, a particular region, or sub-population were selected, if appropriately
27 representative of that population. In cases where data were limited, studies with
28 limitations in this area were included and limitations were noted in the handbook.
29
30 • Variability in the population: Studies were sought that characterized any variability
31 within populations.
32 .
33 • Minimal (or defined) bias in study design: Studies were sought that were designed
34 with minimal bias, or at least if biases were suspected to be present, the direction of
35 the bias (i.e., an over or under estimate of the parameter) was either stated or apparent
36 from the study design.
37 .
38 • Minimal (or defined) uncertainty in the data: Studies were sought with minimal
39 uncertainty in the data, which was judged by evaluating all the considerations listed
40 above. At least, studies were preferred that identified uncertainties, such as those due
41 to inherent variability in environmental and exposure-related parameters or possible
42 measurement error. Studies that documented Quality Assurance/Quality Control
43 measures were preferable.
14
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1 1.5 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR
2 EXPOSURE FACTORS
3 As discussed above, EPA first reviewed all literature pertaining to a factor and
4 determined key studies. These key studies were used to derive recommendations for the values
5 of each factor. The recommended values were derived solely from EPA's interpretation of the
6 available data. Different values may be appropriate for the user to select in consideration of
7 policy, precedent, strategy, or other factors such as site-specific information. EPA's procedure
8 for developing recommendations was as follows: -
9 1. Key studies were evaluated in terms of both quality and relevance to specific populations
10 (general U. S. population, age groups, gender, etc.). The criteria for assessing the quality
11 of studies is described in Section 1.4.
12 2. If only one study was classified as key for a particular factor, the mean value from that
13 study was selected as the recommended central value for that population. If there were
14 multiple key studies, all with reasonably equal quality, relevance, and study design
15 information were available, a weighted mean (if appropriate, considering sample size and
16 other statistical factors) of the studies were chosen as the recommended mean value. If
17 the key studies were judged to be unequal in quality, relevance, or study design, the range
18 of means were presented and the user of this handbook must employ judgment in
19 selecting the most appropriate value for the population of interest. In cases where the
20 national population was of interest, the mid-point of the range was usually judged to be
21 the most appropriate value.
22 3. The variability of the factor across the population was discussed. If adequate data were
23 available, the variability was described as either a series of percentiles or a distribution.
24 4. Limitations of the data were discussed in terms of data limitations, the range of
25 circumstances over which the estimates were (or were not) applicable, possible biases in
26 the values themselves, a statement about parameter uncertainties (measurement error,
27 sampling error) and model or scenario uncertainties if models or .scenarios have been used
28 in the derivation of the recommended value.
29 5. Finally, EPA assigned a confidence rating of low, medium or high to each recommended
30 value. This rating is not intended to represent an uncertainty analysis, rather it represents
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1 EPA's judgment on the quality of the underlying data used to derive the recommendation.
2 This judgment was made using the guidelines shown in Table 1-1. Table 1-1 is an
3 adaptation of the General Considerations discussed earlier in Section 1.4. Clearly this is
4 a continuum from low to high and judgment was used to determine these ratings.
5 Recommendations given in this handbook are accompanied by a discussion of the
6 rationale for their rating.
7 Table 1-2 summarizes EPA's recommendations and confidence ratings for the various exposure
8 factors that apply to children.
9 It is important to note that the study elements listed in Table 1-1 do not have the same
10 weight when arriving at the overall confidence rating for the various exposure factors. The
11 relative .weight of each of these elements depend on the exposure factor of interest. Also, the
12 relative weights given to the elements for the various factors were subjective and based on the
13 professional judgement of the authors of this handbook. In general, most studies would rank
14 high with regard to "level of peer review," "accessibility," "focus on the factor of interest," and
15 "data pertinent to the U.S." These elements are important for the study to be included in this
handbook. However, a high score of these elements does not necessarily translate into a high
17 overall score. Other elements in Table 1-1 were also examined to determine the overall score.
18 For example, the adequacy of data collection period-may be more important when determining
19 usual intake of foods in a population. On the other hand, it is not as important for factors where
20 long-term variability may be small such as tapwater intake. In the case of tapwater intake, the
21 currency of the data was a critical element in determining the final rating. In addition, some
22 exposure factors are more easily measured than others. For example, soil ingestion by children is
23 estimated by measuring, in the feces, the levels of certain elements found in soil. Body weight,
24 however, can be measured directly and it is, therefore, a more reliable measurement. This is
25 reflected in the confidence rating given to both of these factors. In general, the better the
26 methodology used to measure the exposure factor, the higher the confidence in the value.
27
28 1.6 CHARACTERIZING VARIABILITY
29 This document attempts to characterize variability of each of the factors. Variability is
0 characterized in one or more of three ways: (1) as tables with various percentiles or ranges of
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1 values; (2) as analytical distributions with specified parameters; and/or (3) as a qualitative
2 discussion. Analyses to fit standard or parametric distributions (e.g., normal, lognormal) to the
3 exposure data have not been performed by the authors of this handbook, but have been
4 reproduced in this document wherever they were found in the literature. Recommendations on
5 the use of these distributions are made where appropriate based on the adequacy of the
6 supporting data. The list of exposure factors and the way that variability has been characterized
7 (i.e., average, upper percentiles, multiple percentiles, fitted distribution) are presented in
8 Table 1-3. The term upper percentile is used throughout this handbook and it is intended to
9 represent values in the upper tail (i.e., between 90th and 99.9th percentile) of the distribution of
10 values for a particular exposure factor.
11 An attempt was made to present percentile values in the recommendations that are
12 consistent with the exposure estimators defined in the Exposure Guidelines '(i.e., mean, 50th,
13 90th, 95th, 98th, and 99.9th percentile). This was not, however, always possible because either
14 the data available were limited for some factors, or the authors of the study did not provide such
15 information. It is important to note, however, that these percentiles were discussed in the
16 Exposure Guidelines within the context of risk descriptors and not individual exposure factors.
17 For example, the Guidelines stated that the assessor may derive a high-end estimate of exposure
18 by using maximum or near maximum values for one or more sensitive exposure factors, leaving
19 others at their mean value.
20 The use of Monte Carlo or other probabilistic analysis require a selection of distributions
21 or histograms for the input parameters. Although this handbook is not intended to provide a
22 complete guidance on the use of Monte Carlo and other probabilistic analyses, the following
23 should be considered when using such techniques:
24 • The exposure assessor should only consider using probabilistic analysis when there
25 are credible distribution data (or ranges) for the factor under consideration. Even if
26 these distributions are known, it may not be necessary to apply this technique. For
27 example, if only average exposure values are needed, these can often be computed
28 accurately by using average values for each of the input parameters. Probabilistic
29 analysis is also not necessary when conducting assessments for screening purposes,
30 i.e., to determine if unimportant pathways can be eliminated. In this case, bounding
31 estimates can be calculated using maximum or near maximum values for each of the
32 , input parameters. ' -
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1 • It is important to note that the selection of distributions can be highly site specific and
2 will always involve some degree of judgment. Distributions derived from national
3 data may not represent local conditions. To the extent possible, an assessor should
4 use distributions or frequency histograms derived from local surveys to assess risks
5 locally. When distributional data are drawn from national or other surrogate
6 population, it is important that the assessor address the extent to which local
7 conditions may differ from the surrogate data.
8
9 In addition to a qualitative statement of uncertainty, the representativeness assumption
10 should be appropriately addressed as part of a sensitivity analysis.
11 • Distribution functions to be used in Monte Carlo analysis may be derived by fitting an
12 appropriate function to empirical data. In doing this, it should be recognized that in
13 the lower and upper tails of the distribution the data are scarce, so that several
14 functions, with radically different shapes in the extreme tails, may be consistent with
15 the data. To avoid introducing errors into the analysis by the arbitrary choice of an
16 inappropriate function, several techniques can be used. One way is to avoid the
17 " problem by using the empirical data itself rather than an analytic function. Another is
18 to do separate analyses with several functions which have adequate fit but form upper
19 and lower bounds to the empirical data. A third way is to use truncated analytical
20 distributions. Judgment must be used in choosing the appropriate goodness of fit test.
21 Information on the theoretical basis for fitting distributions can be found in a standard
22 statistics text such as Statistical Methods for Environmental Pollution Monitoring,
123 Gilbert, R.O., 1987, Van Nostrand Reinhold; off-the-shelf computer software such as
24 Best-Fit by Palisade Corporation can be used to.statistically determine the
25 distributions that fit the data.
26
27 • If only a range of values is known for an exposure factor, the assessor has several
28 options.
29 - keep that variable constant at its central value;
30 - assume several values within the range of values for the exposure factor;
31 - calculate a point estimate(s) instead of using probabilistic analysis; and
32 - assume a distribution (The rationale for the selection of a distribution should be
33 discussed at length.) There are, however, cases where assuming a distribution is
34 not recommended. These include:
35 — data are missing or very limited for a key parameter;
36 -- data were collected over a short time period and may not represent long term
37 trends (the respondent usual behavior) - examples include: food consumption
38 surveys; activity pattern data:
39 — data are not representative of the population of interest because sample size
40 was small or the population studied was selected from a local area and was
41 therefore not representative of the area of interest - examples include: soil
42 ingestion by children; and
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1 — ranges for a key variable are uncertain due to experimental error or other
2 limitations in the study design or methodology - examples include: soil
3 ingestion by children.
4
5 1.7 USING THE HANDBOOK IN AN EXPOSURE ASSESSMENT
6 Some of the steps for performing an exposure assessment are (1) determining the
7 pathways of exposure, (2) identifying the environmental media which transports the contaminant,
8 (3) determining the contaminant concentration, (4) determining the exposure time, frequency,
9 and duration, and (5) identifying the exposed population. Many of the issues related to
10 characterizing exposure from selected exposure pathways have been addressed in a number of
11 existing EPA guidance documents. These include, but are not limited to the following:
12 • Guidelines for Exposure Assessment (U.S. EPA 1992a);
13 • Dermal Exposure Assessment: Principles and Applications (U.S. EPA 1992b);
14 • Methodology for Assessing Health Risks Associated with Indirect Exposure to
15 Combustor Emissions (U.S. EPA, 1990);
16 • Risk Assessment Guidance for Superfund (U.S. EPA, 1989);
17 • Estimating Exposures to Dioxin-Like Compounds (U.S. EPA, 1994);
18 • Superfund Exposure Assessment Manual (U.S. EPA, 1988a);
19 • Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S.
20 EPA1988b);
21 • Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S.
22 EPA 1987);
23 • Standard Scenarios for Estimating Exposure to Chemical Substances During Use of
24 Consumer Products (U.S. EPA 1986a);
25 • Pesticide Assessment Guidelines, Subdivisions K and U (U.S. EPA, 1984,1986b);
26 and
27 • Methods for Assessing Exposure to Chemical Substances, Volumes 1-13 (U.S. EPA,
28 1983-1989).
29 • Guiding Principles for Monte Carlo Assessments.
30 - These documents may serve as valuable information resources to assist in the assessment of
31 exposure. The reader is encouraged to refer to them for more detailed discussion.
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1 Most of the data presented in this handbook are derived from studies that targeted (1) the
2 general population (e.g., USDA food consumption surveys); and (2) a sample population from a
3 specific area or group (e.g., Calabrese's et al. (1989) soil ingestion study using children from the
4 Amherst, Massachusetts, area). Due to unique activity patterns, preferences, practices and
5 biological differences, various segments of the population may experience exposures that are
6 different from those of the general population, which, in many cases, may be greater. It is
7 necessary for risk or exposure assessors characterizing a diverse population, to identify and
8 enumerate certain groups within the general population who are at risk for greater contaminant
9 exposures or exhibit a heightened sensitivity to particular chemicals. For further guidance on
10 addressing susceptible populations, it is recommended to consult the EPA, National Center for
11 Environmental Assessment document: EPA/600/R-99/060 July 1999, entitled, Socio-
12 demographic Data Used for Identifying Potentially Highly Exposed Subpopulations.
13
14 1.7.1 General Equation for Calculating Dose
15 The definition of exposure as used in the Exposure Guidelines (U.S. EPA, 1992a) is
k!6 "condition of a chemical contacting the outer boundary of a human." This means contact with the
17 visible exterior of a person such as the skin, and openings such as the mouth, nostrils, and
18 lesions. The process of a chemical entering the body can be described in two steps: contact
19 (exposure), followed by entry (crossing the boundary). The magnitude of exposure (dose) is the
20 amount of agent available at human exchange boundaries (skin, lungs, gut) where absorption
21 takes place during some specified time. An example of exposure and dose for the oral route as
22 presented in the EPA Exposure Guidelines is shown in Figure 1-1. Starting with a general
23 integral equation for exposure (U.S. EPA 1992a), several dose equations can be derived
24 depending upon boundary assumptions. One of the more useful of these derived equations is the
25 Average Daily Dose (ADD). The ADD, which is used for many noncancer effects, averages
26 exposures or doses over the period of time over which exposure occurred. The ADD can be
27 calculated by averaging the potential dose (Dp,,,) over body weight and an averaging time.
28
29 ADD t = Total Potential Dose
^ Body Weight x Averaging Time
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Exposure
Chemical
Mouth
Biologically
Effective
Dose
Effect
G.l. Tract
Intake
Uptake
1
2
"»
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Figure 1-1. Schematic of Dose and Exposure: Oral Route
Source: U.S. EPA, 1992a
For cancer effects, where the biological response is usually described in terms of lifetime
probabilities, even though exposure does not occur over the entire lifetime, doses are often
presented as lifetime average daily doses (LADDs). The LADD takes the form of the
Equation 1-1 with lifetime replacing averaging time. The LADD is a very common term used in
carcinogen risk assessment where linear non-threshold models are employed.
The total exposure can be expressed as follows:
Total Potential Dose" = C x IR x ED
Where:
C = Contaminant Concentration
IR = Intake Rate
ED = Exposure Duration
(1-2)
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.
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1 The intake rate refers to the rates of inhalation, ingestion, and dermal contact depending
2 on the route of exposure. For ingestion, the intake rate is simply the amount of food containing
3 the contaminant of interest that an individual ingests during some specific time period (units of
4 mass/time). Much of this handbook is devoted to rates of ingestion for some broad classes of
5 food. For inhalation, the intake rate is the rate at which contaminated air is inhaled. Factors that
6 affect dermal exposure are the amount of material that comes into contact with the skin, and the
7 rate at which the contaminant is absorbed.
8 The exposure duration is the length of time that contaminant contact lasts. The time a
9 person lives in an area, frequency of bathing, time spent indoors versus outdoors, etc. all affect
10 the exposure duration. The Activity Factors Chapter (Chapter 9) gives some examples of
11 population behavior patterns, which may be useful for estimating exposure durations to be used
12 in the exposure calculations.
13 When the above parameter values remain constant over time, they are substituted directly
14 into the exposure equation. When they change with time, a summation approach is needed to
15 calculate exposure. In either case, the exposure duration is the length of time exposure occurs at
the concentration and intake rate specified by the other parameters in the equation.
17 Dose can be expressed as a total amount (with units of mass, e.g., mg) or as a dose rate in
18 terms of mass/time (e.g., mg/day), or as a rate normalized to body mass (e.g., with units of mg of
19 chemical per kg of body weight per day (mg/kg-day)). The LADD is usually expressed in terms
20 of mg/kg-day or other mass/mass-time units.
21 In most cases (inhalation and ingestion exposure) the dose-response parameters for
22 carcinogen risks have been adjusted for the difference in absorption across body barriers between
23 humans and the experimental animals used to derive such parameters. Therefore, the exposure
24 assessment in these cases is based on the potential dose with no explicit correction for the
25 fraction absorbed. However, the exposure assessor needs to make such an adjustment when
26 calculating dermal exposure and in other specific cases when current information indicates that
27 the human absorption factor used in the derivation of the dose-response factor is inappropriate.
28 The lifetime value used in the LADD version of Equation 1-1 is the period of time over
29 which the dose is averaged. For carcinogens, the derivation of the dose-response parameters
usually assumes no explicit number of years as the duration of a lifetime, and the nominal value
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1 of 75 years is considered a reasonable approximation. For exposure estimates to be used for
2 , assessments other than carcinogenic risk, various averaging periods have been used. For acute
3 exposures, the administered doses are usually averaged over a day or a single event. For
4 nonchronic noncancer effects, the time period used is the actual period of exposure. The
5 objective in selecting the exposure averaging time is to express the exposure in a way which can
6 be combined with the dose-response relationship to calculate risk.
7 The body weight to be used in the exposure Equation 1-1 depends on the units of the
8 exposure data presented in this handbook. For food ingestion, the body weights of the surveyed
9 populations were known in the USDA surveys and they were explicitly factored into the food
10 intake data in order to calculate the intake as grams per day per kilogram body weight. In this
11 case, the body weight has already been included in the "intake rate" term in Equation 1 -2 and the
12 exposure assessor does not need to explicitly include body weight.
13 The units of intake in this handbook for the ingestion of fish, breast milk, and the
14 inhalation of air are not normalized to body weight. In this case, the exposure assessor needs to
15 use (in Equation 1-1) the average weight of the exposed population during the time when the
16 exposure actually occurs. If the body weight of the individuals in the population whose risk is
17 being evaluated is non-standard in some way, such as for children or for first-generation
18 immigrants who may be smaller than the national population, and if reasonable values are not
19 available in the literature, then a model of intake as a function of body weight must be used.
20 One such model is discussed in Appendix 1A of the Exposure Factors Handbook (U.S. EPA,
21 1997b). Some of the parameters (primarily concentrations) used in estimating exposure are
22 exclusively site specific, and therefore default recommendations could not be used.
23 The food ingestion rate values provided in this handbook are generally expressed as "as
24 consumed" since this is the fashion in which data are reported by survey respondents. This is of
25 importance because concentration data to be used in the dose equation are generally measured in
26 uncooked food samples. In most situations, the only practical choice is to use the "as consumed"
27 ingestion rate and the uncooked concentration. However, it should be recognized that cooking
28 generally results in some reductions in weight (e.g., loss of moisture), and that if the mass of the
29 contaminant in the food remains constant, then the concentration of the contaminant in the
30 cooked food item will increase. Therefore, if the "as consumed" ingestion rate and the uncooked
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1 concentration are used in the dose equation, dose may be underestimated. On the other hand,
2 • cooking may cause a reduction in mass of contaminant and other ingredients such that the overall
3 concentration of contaminant does not change significantly. In this case, combining cooked
4 ingestion rates and uncooked concentration will provide an appropriate estimate of dose. Ideally,
5 food concentration data should be adjusted to account for changes after cooking, then the "as
6 consumed" intake rates are appropriate. In the absence of data, it is reasonable to assume that no
7 change in contaminant concentration occurs after cooking. Except for general population fish
8 consumption and home produced foods, uncooked intake rate data were not available for
9 presentation in this handbook. Data on the general population fish consumption have been
10 presented in this handbook (Chapter 3) in both "as consumed" and uncooked basis. It is
11 important for the assessor to be aware of these issues and choose intake rate data that best
12 matches the concentration data that is being used.
13 The link between the intake rate value and the exposure duration value is a common
14 source of confusion in defining exposure scenarios. It is important to define the duration
15 estimate so that it is consistent with the intake .rate:
J 6 • The intake rate can be based on an individual event (e.g., serving size per event). The
17 duration should be based on the number of events or. in this case, meals.
18 • The intake rate also can be based on a long-term average, such as 10 g/day. In this
19 case the duration should be based on the total time interval over which the exposure
20 occurs.
21 The objective is to define the terms so that when multiplied, they give the appropriate
22 estimate of mass of contaminant contacted. This can be accomplished by basing the intake rate
23 on either a long-term average (chronic exposure) or an event (acute exposure) basis, as long as
24 the duration value is selected appropriately.
25
26 1.8 FUTURE OR ON-GOING WORK
27 EPA is also developing guidance on the use of exposure factors data. For future
28 information on the status of this guidance, it is recommended to consult the EPA National Center
29 for Environmental Assessment homepage (wuav.epa.gov/nceaX Another on-going effort is the
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1
2
3
Risk Assessment Forum project on defining age groups for children that are appropriate for use
in risk assessment.
1.9 RESEARCH NEEDS
The data for several exposure factors for children are limited. The following list is a
compilation of areas for future research related to childhood exposure factors:
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
31
32
33
34
35
36
37
38
39
40
41
42
More recent information is needed on breastmilk consumption.
Information on children's food handling practices that might exacerbate exposure is
needed to better characterize exposures among children.
Further research on fish intake among children, particularly recreational and
subsistence populations, is needed.
Research is needed to better estimate soil intake rates, particularly on how to
extrapolate short-term data to chronic exposures. Research is also needed to refine
the methods to calculate soil intake rates (i.e., inconsistencies among tracers and
input/output misalignment errors indicate a fundamental problem with the methods).
Additional information on soil ingestion among children that provides better
estimates of upper percentile rates is needed, in particular.
Further research is needed on non-dietary ingestion exposure factors, such as the
microenvironments in which children spend time and the types of materials that they
contact, as well as information on the rate at which they contact contaminated
surfaces, the fraction of the contaminants that are transferred to skin and object
surfaces, and the amount of the object/skin entering the mouth.
Additional data on dermal exposure factors, such as the microenvironments in which
children spend time and the types of materials that they contact, as well as
information on the rate at which they contact contaminated surfaces, and the fraction
of the contaminants that are transferred to skin and object surfaces.
Further research is needed to obtain better soil adherence rates for additional activities
involving children.
Further data is needed on the frequency of use and kinds of consumer products used
by children.
Additional information on derivation of new surface area based on newer body weight
data.
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1
2
o
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
• Additional data on inhalation rates that are specific to children's activities are needed.
• In cases where several studies of equal quality and data collection procedures are
available for an exposure factor, procedures need to be developed to combine the data
in order to create a single distribution of likely values for that factor.
• Research is needed to derive a methodology to extrapolate from short-term data to
long-term or chronic exposures.
• Further research is needed to estimate food consumption rates by children based on
the CSFII supplemental survey on children.
• Regarding breast milk ingestion, research is needed on incidence and duration of
breast feeding.
1.10 ORGANIZATION
The handbook is organized as follows:
Chapter 1 Provides the overall introduction to the handbook
Chapter 2 Provides factors for estimating exposure through ingestion of breastmilk
Chapter 3 Provides factors for estimating human exposure through ingestion foods,
including fish
Chapter 4 Provides factors for estimating exposure through ingestion of drinking
water
Chapter 5 Provides factors for estimating exposure as a result of ingestion of soil
Chapter 6 Presents factors for estimating exposure to environmental contaminants
from other non-dietary ingestion such as hand-to-mouth and object-to-
mouth activity
Chapter 7 Provides factors for estimating exposure as a result of inhalation of vapors
and particulates
Chapter 8 Provides factors for estimating dermal exposure to environmental
contaminants that come in contact with the skin
Chapter 9 Presents data on activity factors (activity patterns, population mobility,
and occupational mobility)
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1
2
3
4
5
6
7
8
Chapter 10 Presents data on consumer product use
Chapter 11 Presents data on body weight
Chapter 12 Presents data on lifetime
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1 1.11 REFERENCES FOR CHAPTER 1
2
3 Calabrese, EJ.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.; et al. (1989) How much soil do young
4 children ingest: an epidemioiogic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, MI.
5 pp. 363-397.
6
7 Gilbert, R.O. (1987) Statistical methods for environmental pollution monitoring. New York: VanNostrand
8 Reinhold,
9
10 U.S. EPA. (1983-1989) Methods for assessing exposure to chemical substances. Volumes I-I3. Washington, DC:
11 Office of Toxic Substances, Exposure Evaluation Division.
12
13 U.S. EPA. (1984) Pesticide assessment guidelines subdivision K, exposure: reentry protection. Office of Pesticide
14 Programs, Washington, DC. EPA/540/9-48/001. Available from NTIS, Springfield, VA; PB-85-120962.
15
16 U.S. EPA. (1986a) Standard scenarios for estimating exposure to chemical substances during use of consumer
17 products. Volumes I and II. Washington, DC: Office of Toxic Substance, Exposure Evaluation Division.
18
19 U.S. EPA. (1986b) Pesticide assessment guidelines subdivision U, applicator exposure monitoring. Office of
20 Pesticide Programs, Washington, DC. EPA/540/9-87/127. Available from NTIS, Springfield, VA;
21 PB-85-133286.
22
23 U.S. EPA. (1987) Selection criteria for mathematical models used in exposure assessments: surface water models.
24 Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC.
25 WPA/600/8-87/042. Available from NTIS, Springfield, VA; PB-88-139928/AS.
26
27 U.S. EPA. (1988a) Superfund exposure assessment manual. Office of Emergency and Remedial Response,
f28 Washington, DC. EPA/540/1 -88/001. Available from NTIS, Springfield, VA; PB-89-135859.
29
30 U.S. EPA. (1988b) Selection criteria for mathematical models used in exposure assessments: groundwater models.
31 Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC.
32 EPA/600/8-88/075. Available from NTIS, Springfield, VA; PB-88-248752/AS.
34 U.S. EPA: (1989) Risk assessment guidance for Superfund. Human health evaluation manual: part A. Interim Final.
35 Office of Solid Waste and Emergency Response, Washington, DC. Available from NTIS, Springfield, VA;
36 PB-90-155581.
37
38 U.S. EPA. (1990) Methodology for assessing health risks associated with indirect exposure to combustor emissions.
39 EPA 600/6-90/003. Available from NTIS, Springfield, VA; PB-90-187055/AS.
40
41 U.S. EPA. (1992a) Guidelines for exposure assessment. Washington, DC: Office of Research and Development,
42 Office of Health and Environmental Assessment. EPA/600/Z-92/001.
43
44 U.S. EPA. (I992b) Dermal exposure assessment: principles and applications. Washington. DC: Office of Health
45 and Environmental Assessments. EPA/600/8-9/011F.
46
47 U.S. EPA. (1994) Estimating exposures to dioxin-like compounds. (Draft Report). Office of Research and
48 Development, Washington, DC. EPA/600/6-88/005Cb.
49
50 U.S. EPA. (1997a) Office of Research and Development strategy for research on risks to children. Washington,
51 DC: Office of Research and Development, Science Council Review Draft.
.52
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
U.S. EPA. (1997b) 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. (1998) The EPA children's environmental health yearbook. Washington, DC: U.S. Environmental
Protection Agency.
U.S. EPA. (1999a) Strategy for research on environmental risks to children. Washington, DC: Office of Research
and Development. External Peer Review Draft.
U.S. EPA. (1999b) Child-related risk assessment policy and methodology guidance document survey, draft report.
Washington, DC: Office of Children's Health Protection.
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I
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Table 1-1. Considerations Used to Rate Confidence
in recommended Values
CONSIDERATIONS
HIGH CONFIDENCE
LOW CONFIDENCE
Study Elements
Level of peer review
The studies received high level of peer
review (e.g., they appear in peer review
journals).
The studies received limited peer review.
Accessibility
The studies are widely available to the
public.
The studies are difficult to obtain (e.g.,
draft reports, unpublished data).
Reproducibility
The results can be reproduced or
methodology can be followed and
evaluated.
The results cannot be reproduced, the
methodology is hard to follow, and-the
authors) cannot be located.
Focus on factor of interest
The studies focused on the exposure
factor of interest.
The purpose of the studies was to
characterize a related factor.
Data pertinent to U.S.
The studies focused on the U.S.
population.
The studies focused on populations
outside the U.S.
Primary data
The studies analyzed primary data.
The studies are based on secondary
sources."
Currency
The data were published after 1990.
The data were published before 1980.
Adequacy of data collection period
The study design captures the
measurement of interest (e.g.. usual
consumption patterns of a population):
The study design does not very accurately
capture the measurement of interest.
Validity of approach
The studies used the best methodology
available to capture the measurement of
interest.
There are serious limitations with the
approach used.
16
17
18
19
20
21
79
23
24
25
26
27
28
29
30
31
Studv sizes
The sample size is greater than 100 samples.
20 samples.
The sample size is less than
The sample size depends on how the target population is defined. As the size of a
sample relative to the total size of the target population increases, estimates are made
with greater statistical assurance that the sample results reflect actual characteristics of
the target population.
Representativeness of the
population
The study population is the same as
population of interest.
The study population is very different
from the population of interest.*
Variability in the population
The studies characterized variability in
the population studied.
The characterization of variability is
limited.
Lack of bias in Study design
. (a high rating is desirable)
Response rates
In-person interviews
Telephone interviews
Mail survevs
Potential bias in the studies are stated or
can be determined from the study
design.
The response rate is greater than 80
percent.
The response rate is greater than 80
percent.
The response rate is greater than 70
percent.
The study design introduces biases in the
results.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
Measurement error
The study design minimizes
measurement errors.
Uncertainties with the data exist due to
measurement error.
Other Elements
Number of studies
The number of studies is greater than 3. The number of studies is I.
Agreement between researchers
The results of studies from different
researchers are in aareement.
The results of studies from different
researchers are in disagreement.
3 Differences include age. sex. race, income, or other demographic parameters.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Table 1-2. Summary of Exposure Factor Recommendations
and Confidence Ratings
EXPOSURE FACTOR
Breast milk intake rate
(1-6 months)
Drinking water intake rate
Total fruit intake rate
Total vegetable intake rate
Total meat intake rate
Total dairy intake rate
Total grain intake
Fat Intake
Fish intake rate
RECOMMENDATION
742 ml/day (average)
1,033 ml/day (upper percentile)
See Table 4-15 L/day (average)
See Table 4-15 L/day (90th percentile)
See Table 3-2 ( per capita average)
See TabJe 3-2 (per capita 95th percentile)
See Table 3-2 ( per capita average)
See Table 3-2 (per capita 95th percentile)
See Table 3-2 ( per capita average)
See Table 3-2 (per capita 95th percentile)
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
See Table 3- 15
General Population
See Table 3-6.(total fish)
See Table 3-6 (marine)
See Table 3-6 (freshwater/estuarine)
Recreational fish intake
!-5 years, 370 mg/kg/day (average)
6-10 years, 280 ing/kg/day (average)
Native American Subsistence Population
<5 years. 1 1 g/day (average)
CONFIDENCE RATING
Medium
Medium
High
High
High
Low
High
Low
High
Low
High
Low
High
Low
—
High(ave.)
Low (upper percentile)
Low
Low
Low
Home produced food intake
See Table 3-28
Medium (for means and short-
term distributions)
Low (for long-term
distributions)
Soil ingestion rate
Children
100 mg/day (average)
400 mg/day (upper percentile)
Pica child
JO g/day
Medium
Low
Inhalation rate
Children (<1 year)
4.5 mVday (average)
Children (1-12 years)
8.7 mVday (average)
High
High
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2
^
4
5
Table 1-2 (Cont'd). Summary of Exposure Factor Recommendations
and Confidence Ratings
EXPOSURE FACTOR
RECOMMENDATION
CONFIDENCE RATING
Surface area
Water contact (bath in a and swimming)
Use total body surface area for children in Tables 8-1
through 8-2;
Soil contact (outdoor activities)
Use body pan area based on Table 8-3
High
High
Soil adherence
Use values presented in Table 8-13 depending on
activity and body part
(central estimates only)
Low
7
8
9
10
11
12
13
Life expectancy
75 vears
High
Body weights for children
Use values presented in Tables 11 -3 and i 1-4 (mean and
percentiles)
High
Body weights for infants (birth to 6
months)
Use values presented in Table 1 l-l (percentiles)
High
Showering/Bathing
Showering time
10 min/day (average)
1 shower event/dav
Hiah
Swimming
Frequency
1 event/month
Duration
60 min/event (median)
High
High
Time indoors
Children (ages 3-5 vears)
19 hr/day
Children (ages 6-14 vears)
20 hr/day
Children (ages 12-17 vears)
I9hrs/day
Medium
High
14
15
16
Time outdoors
Children (ages 3-5 vears)
2.8 hr/day
Children (ages 6-8 vears)
2.2 hr/day
Children (ages 9-14 years)
1.8 hr/day
Children (ages 12-17 vears)
19 hr/day
Medium
High
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Table 1-3. Characterization of Variability in Exposure Factors
Fitted Distributions
Exposure Factors
Average
Upper percemile
Multiple Percentiles
Breast milk intake rate
Total intake rate for major food groups
Qualitative discussion for long-
term
individual food intake rate
Drinking water intake rate
Fish intake rate for general population.
recreational marine, recreational
freshwater, and Native American
Serving size for foods
Home produced food intake rates
S
Soil intake rate
Qualitative discussion for long-
term
Inhalation rate / / /
Surface area
Soil adherence
Life expectancy
Body weight
Time indoors
Time outdoors
Showering time
Occupational tenure
Population mobility
/ /
S /
/
S
S S
S S
'
S
S
/
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1 2. BREAST MILK INTAKE
2
*>
4 2.1 INTRODUCTION
5 Breast milk is a potential source of exposure to toxic substances for nursing infants. Lipid
6 soluble chemical compounds accumulate in body fat and may be transferred to breast-fed infants in
7 the lipid portion of breast milk. Because nursing infants obtain most (if not all) of their dietary
8 intake from breast milk, they are especially vulnerable to exposures to these compounds. Estimating
9 the magnitude of the potential dose to infants from breast milk requires information on the quantity
10 of breast milk consumed per day and the duration (months) over .which breast-feeding occurs.
11 Information on the fat content of breast milk is also needed for estimating dose from breast milk
12 residue concentrations that have been indexed to lipid content.
13 Several studies have generated data on breast milk intake. Typically, breast milk intake has
14 been measured over a 24-hour period by weighing the infant before and after each feeding without
15 changing its clothing (test weighing). The sum of the difference between the measured weights over
the 24-hour period is assumed to be equivalent to the amount of breast milk consumed daily. Intakes
17 measured using this procedure are often corrected for evaporative water losses (insensible water
18 losses) between infant weighings (NAS, 1991). Neville et al. (1988) evaluated the validity of the
19 test weight approach among bottle-fed infants by comparing the weights of milk taken from bottles
20 with the differences between the infants' weights before and after feeding. When test weight data
21 were corrected for insensible water loss, they were not significantly different from bottle weights.
22 Conversions between weight and volume of breast milk consumed are made using the density of
23 human milk (approximately 1.03 g/mL) (NAS, 1991). Recently, techniques for measuring breast
24 milk intake using stable isotopes have been developed. However, few data based on this new
25 technique have been published (NAS, 1991).
26 Studies among nursing mothers in industrialized countries have shown that intakes among
27 infants average approximately 750 to 800 g/day (728 to 777 mL/day) during the first 4 to 5 months
28 of life with a range of 450 to 1,200 g/day (43 7 to 1,165 mL/day) (NAS, 1991). Similar intakes have
29 also been reported for developing countries (NAS, 1991). Infant birth weight and nursing frequency
have been shown to influence the rate of intake (NAS, 1991). Infants who are larger at birth and/or
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20
21
22
23
24
25
26
27
28
29
30
nurse more frequently have been shown to have higher intake rates. Also, breast milk production
among nursing mothers has been reported to be somewhat higher than the amount actually consumed
.by the infant (NAS, 1991).
Key studies on breast milk intake are summarized in the following sections. Recommended
intake rates are based on the results of these key studies, as described in the Exposure Factors
Handbook. Relevant data on lipid content and fat intake, breast-feeding duration and frequency, and
the estimated percentage of the U.S. population that breast-feeds are also presented.
2.2 STUDIES ON BREAST MILK INTAKE
Pao et al. (1980) - Milk Intakes and Feeding Patterns of Breast-fed Infants - Pao et al. (1980)
conducted a study of 22 healthy breast-fed infants to estimate breast milk intake rates. Infants were
categorized as completely breast-fed or partially breast-fed. Breast feeding 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 breast 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 breast milk intake rates for the infants
surveyed at each time interval are presented in Table 2-1. For completely breast-fed infants, the
mean intake rates were 600 mL/day at 1 month of age and 833 mL/day at 3 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 and may not be entirely representative of the U.S.
population, based on race and socioeconomic status, which may introduce some bias in the results.
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1 In addition, this study did not account for insensible water loss which may underestimate the amount
2 of breast milk ingested.
3 Dewey and Lonnerdal (1983) - Milk and Nutrient Intakes of Breast-fed Infants from 1 to
4 6 Months - Dewey and L6nnerdal (1983) monitored the dietary intake of 20 breast-fed infants
5 between the ages of 1 and 6 months. Most of the infants in the study were exclusively breast-fed
6 . (five were given some formula, and several were given small amounts of solid foods after 3 months
7 of age). According to Dewey and Lonnerdal (1983), the mothers were all well educated and
8 recruited through Lamaze childbirth classes in the Davis area of California. Breast milk intake
9 volume was estimated based on two 24-hour test weighings per month. Breast milk intake rates for
10 the various age groups are presented in Table 2-2. Breast milk intake averaged 673, 782, and 896
11 mL/day at 1,3, and 6 months of age, respectively.
12 The advantage of this study is that it evaluated breast-fed infants for a period of 6 months
13 -based on two 24-hour observations per infant per month. Corrections for insensible water loss
14 apparently were not made. Also, the number of infants in the study was relatively small and may
15 not be representative of U.S. population, based on race and socioeconomic status.
[6 Butte et al (1984) - Human Milk Intake and Growth in Exclusively Breast-fed Infants -
17 Breast milk intake was studied in exclusively breast-fed infants during the first 4 months of life
. 18 (Butte et al., 1984). Breastfeeding mothers were recruited through the Baylor Milk Bank Program
19 in Texas. Forty-five mother/infant pairs participated in the study. However, data for some time
20 periods (i.e., 1, 2, 3, or 4 months) were missing for some mothers as a result of illness or other
21 , factors. The mothers were from the middle- to upper-socioeconomic stratum and had a mean age
22 of 28.0 ±3.1 years. A total of 41 mothers were white, 2 were Hispanic, 1 was Asian, and 1 was
23 West Indian.. Infant growth progressed satisfactorily over the course of the study. The amount of
24 milk ingested over a 24-hour period was determined using the test weighing procedure. Test
25 weighing occurred over a 24-hour period for most participants, but intake among several infants was
26 studied over longer periods (48 to 96 hours) to assess individual variation in intake. The study did
27 not indicate whether the data were corrected for insensible water loss. Mean breast milk intake
28 ranged from 723 g/day (702 mL/day) at 3 months to 751 g/day (729 mL/day) at 1 month, with an
29 overall mean of 733 g/day (712 mL/day) for the entire study period (Table 2-3). Intakes were also
calculated on the basis of body weight (Table 2-3). Based on the results of test weighings conducted
June 2000 2-3 DRAFT-DO NOT QUOTE OR CITE
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1 over 48 to 96 hours, the mean variation in individual daily intake was estimated to be 7.9±3.6
2 percent.
3 The advantage of this study is that data for a larger number of exclusively breast-fed infants
4 were collected than were collected 'by Pao et al. (1980). However, data were coilected over a shorter
5 time period (i.e., 4 months compared to 6 months) and day-to-day variability was not characterized
6 for all infants. In addition, the population studied may not be representative of the U.S. population
7 based on race and socioeconomic status.
8 Neville et al. (1988) - Studies on Human Lactation - Neville et al. (1988) studied breast milk
9 intake among 13 infants during the first year of life. The mothers were all multiparous, nonsmoking,
10 Caucasian women of middle- to upper-socioeconomic status living in Denver. Colorado (Neville et
11 al., 1988). All women in the study practiced exclusive breast-feeding for at least 5 months. Solid
12 foods were introduced at mean age of 7 months. Daily milk intake was estimated by. the test
13 weighing method with corrections for insensible weight loss. Data were collected daily from birth
14 to 14 days, weekly from weeks 3 through 8, and monthly until the study period ended at 1 year after
15 inception. The estimated breast milk intakes for this study are listed in Table 2-4. Mean breast milk
16 intakes were 770 g/day (748 mL/day), 734 g/day (713 mL/day), 766 g/day (744 mL/day), and 403
17 g/day (391 mL/day) at 1, 3,6, and 12 months of age, respectively.
18 In comparison to the previously described studies, Neville et al. (1988) collected data on
19 numerous days over a relatively long time period (12 months) and they were corrected for insensible
20 weight loss. However, the intake rates presented in Table 2-4 are estimated based on intake during
21 only a 24-hour period. Consequently, these intake rates are based on short-term data that do not
22 account for day-to-day variability among individual infants. Also, a smaller number of subjects was
23 included than in the previous studies, and the population studied may not be representative of the
24 U.S. population, based on race and socioeconomic status.
25 Dewey et al (199la; 199Ib) - The DARLING Study - The Davis Area Research on Lactation,
26 Infant Nutrition and Growth (DARLING) study was conducted in 1986 to evaluate growth patterns,
27 nutrient intake, morbidity, and activity levels in infants who were breast-fed for at least the first 12
28 months of life (Dewey etal., 199 la; 1991b). Seventy-three infants aged 3 months were included in
29 the study. The number of infants included in the study at subsequent time intervals was somewhat
30 lower as a result of attrition. All infants in the study were healthy and of normal gestational age and
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1 weight at birth, and did not consume solid foods until after the first 4 months of age. The mothers
2 were highly educated and of "relatively high socioeconomic status" from the Davisarea of California
3 (Dewey et al., 1991 a; 1991 b). Breast milk intake was estimated by weighing the infants before and
4 after each feeding and correcting for insensible water loss. Test weighings were conducted over a
5 4-day period every 3 months. The results of the study indicate that breast milk intake declines over
6 the first 12 months of life. Mean breast milk intake was estimated to be 812 g/day (788 mL/day) at
7 3 months and 448 g/day (435 mL/day) at 12 months (Table 2-5). Based on the estimated intakes at
8 3 months of age, variability between individuals (coefficient of variation (CV) = 16.3 percent) was
9 higher than individual day-to-day variability (CV = 5.4 percent) for the infants in the study (Dewey
10 etal., 1991a).
11 The advantages of this study are that data were collected over a relatively long-time (4 days)
12 period at each test interval which would account for some day-to-day -infant variability, and
13 corrections for insensible water loss were made. However, the population studied may not be
14 representative of the U.S. population, based on race and socioeconomic status.
15
|16 2.3 STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST MILK
17 Humanmilk contains over200 constituents includinglipids, various proteins, carbohydrates,
18 vitamins, minerals, and trace elements as well as enzymes and hormones.(NAS, 1991). The lipid
19 content of breast milk varies according to the length of time that an infant nurses. Lipid content
20 increases from the beginning to the end of a single nursing session (NAS, 1991). The lipid portion
21 accounts for approximately 4 percent of human breast milk (39± 4.0 g/L) (NAS, 1991). This value
22 is supported by various studies that evaluated lipid content from human breast milk. Several studies
23 also estimated the quantity of iipid consumed by breast-feeding infants. These values are appropriate
24 for performing exposure assessments for nursing infants when the contaminant(s) have residue
25 concentrations that are indexed to the fat portion of human breast milk.
26 Butte et al. (1984) ~ Human Milk Intake and Growth in Exclusively Breast-fed Infants - Butte
27 et al., (1984) analyzed the lipid content of breast milk samples taken from women who participated
28 in a study of breast milk intake among exclusively breast-fed infants. The study was conducted with
29 over 40 women during a 4-month period. The mean lipid content of breast milk at various infants'
ages is presented in Table 2-6. The overall lipid content for the 4-month study period was 34.3 ±
June 2000 2-5 DRAFT-DO NOT QUOTE OR CITE
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1 6.9 mg/g (3.4 percent). Butte et al. (1984) also calculated lipid intakes from 24-hour breast milk
2 intakes and the lipid content of the human milk samples. Lipid intake was estimated to range from
3 23.6 g/day (3.8 g/kg-day) to 28.0 g/day (5.9 g/kg-day).
4 The number of women included in this study was small, and these women were selected
5 primarily from middle- to upper-socioeconomic classes. Thus, data on breast milk lipid content from
6 this study may not be entirely representative of breast milk lipid content among the U.S. population.
7 Also, these estimates are based on short-term data and day-to-day variability was not characterized.
8 Maxwell and Burmaster (1993) - A Simulation Model to Estimate a Distribution of Lipid
9 Intake from Breast Milk Intake During the First Year of Life -Maxwell and Burmaster (1993) used
10 a hypothetical population of 5,000 infants between birth and 1 year of age to simulate a distribution
11 of daily lipid intake from breast milk. The hypothetical population represented both bottle-fed and
12 breast-fed infants aged 1 to 365 days. A distribution of daily lipid intake was developed based on
13 data in Dewey et al. (1991b) on breast milk intake for infants at 3,6, 9, and 12 months and breast
14 milk lipid content, and survey data in Ryan et al. (1991) on the percentage of breast-fed infants under
15 the age of 12 months (i.e., approximately 22 percent). A model was used to simulate intake among
16 1,113 of the 5,000 infants that were expected to be breast-fed. The results of the model indicated
17 that lipid intake among nursing infants under 12 months of age can be characterized by a normal
18 distribution with a mean of 26.8 g/day and a standard deviation of 7.4 g/day (Table 2-7). The model
19 assumes that nursing infants are completely breast-fed and does not account for infants who are
20 breast-fed longer than 1 year. Based on data collected by Dewey et al. (1991b), Maxweli and
21 Burmaster (1993) estimated the lipid content of breast milk to be 36.7 g/L at 3 months (35.6 mg/g
22 or 3.6%) and 40.2 g/L (39.0 mg/g or 3.9%) at 12 months.
23 The advantage of this study is that it provides a "snapshot" of daily lipid intake from breast
24 milk for breast-fed infants. These results are, however, based on a simulation model and there are
25 uncertainties associated with the assumptions made. The estimated mean lipid intake rate represents
26 the average daily intake for nursing infants under 12 months of age. These data are useful for
27 performing exposure assessments when the age of the infant cannot be specified (i.e., 3 months or
28 6 months). Also, because intake rates are indexed to the lipid portion of the breast milk, they may
29 be used in conjunction with residue concentrations indexed to fat content.
30
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1 2.4 OTHER FACTORS
2 Other factors associated with breast milk intake include: the frequency of breast-feeding
3 sessions per day, the duration of breast-feeding per event, the duration of breast-feeding during
4 childhood, and the magnitude and nature of the population that breast-feeds.
5 Frequency and Duration of Feeding - Hofvander et al. (1982) reported on the frequency of
6 feeding among 25 bottle-fed and 25 breast-fed infants at ages 1,2, and 3 months. The mean number
7 of meals for these age groups was approximately 5 meals/day (Table 2-8). Neville et al. (1988)
8 reported slightly higher mean feeding frequencies. The mean number of meals per day for
9 exclusively breast-fed infants was 7.3 at ages 2 to 5 months and 8.2 at ages 2 weeks to 1 month.
10 Neville et al. (1988) reported that, for infants between the ages of I week and 5 months, the average
11 duration of a breast feeding session is 16-18 minutes.
12 Population of Nursing Infants and Duration ofBr east-Feeding During Infancy - According
13 to NAS (1991), the percentage of breast-feeding women has changed dramatically over the years.
14 Between 1936 and 1940, approximately 77 percent of infants were breast fed, but the incidence of
15 breast-feeding fell to approximately 22 percent in 1972. The duration of breast-feeding also dropped
4fet 6 from about 4 months in the early 1930s to 2 months in the late 1950s. After 1972, the incidence of
17 breast-feeding began to rise again, reaching its peak at approximately 61 percent in 1982. The
18 duration of breast-feeding also increased between 1972 and 1982. Approximately 10 percent of the
19 mothers who initiated breast-feeding continued for at least 3 months in 1972; however, in 1984,37
20 percent continued breast-feeding beyond 3 months. In 1989, breast-feeding was initiated among
21 52.2 percent of newborn infants, and 40 percent continued for 3 months or longer (NAS, 1991).
22 Based on the data for 1989, only about 18.1 percent of infants were still breast fed by age 6 months
23 (Ryan, 1997). By 1995, the initiation of breastfeeding had increased to 59.7 percent and the rate of
24 breastfeeding at 6 months had increased to 21.6 percent (Ryan, 1997). Data on the actual length of '
25 . time that infants continue to breast-feed beyond 5 or 6 months are limited (NAS, 1991). However,
26 Maxwell and Burmaster (1993) estimated that approximately 22 percent of infants under 1 year of
27 age are breast-fed. This estimate is based on a reanalysis of survey data in Ryan et al. (1991)
28 collected by Ross Laboratories (Maxwell and Burmaster, 1993). Studies have also indicated that
29 breast-feeding practices may differ among ethnic and socioeconomic groups and among regions of
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1 the United States. The percentages of mothers who breast feed, based on ethnic background and
2 demographic variables, are presented in Table 2-9 (NAS, 1991).
3 Intake Rates Based on Nutritional Status - Information on differences in the quality and
4 quantity of breast milk consumed based on ethnic or socioeconomic characteristics of the population
5 is limited. Lonnerdal et al. (1976) studied breast milk volume and composition (nitrogen, lactose,
6 proteins) among underprivileged and privileged Ethiopian mothers. No significant differences were
7 observed between the data for these two groups; and similar data for well-nourished Swedish
8 mothers were observed. Lonnerdal et al. (1976) stated that these results indicate that breast milk
9 quality and quantity are not affected by maternal malnutrition. However, Brown et al. (1986a;
10 1986b) noted that the lactational capacity and energy concentration of marginally-nourished women
11 in Bangladesh were "modestly less than in better nourished mothers." Breast milk intake rates for
12 infants of marginally-nourished women in this study were 690±122 g/day-at 3 months, 722±105
13 g/day at 6 months, and 719±119 g/day at 9 months of age (Brown et al., 1986a). Brown et al.
14 (1986a) observed that breast milk from women with larger measurements of arm circumference and
15 triceps skinfold thickness had higher concentrations of fat and energy than mothers with less body
16 fat. Positive correlations between maternal weight and milk fat concentrations were also observed.
17 These results suggest that milk composition may be affected by maternal nutritional status.
18
19 2.5 RECOMMENDATIONS
20 . The studies described in this section were used in selecting recommended values for breast
21 milk intake, fat content and fat intake, and other related factors. Although different survey designs,
22 testing, periods, and populations were utilized fay the studies to estimate intake, the mean and
23 standard deviation estimates reported in these studies are relatively consistent. There are, however,
24 limitations with the data. Data are .not available for infants under 1 month of age. This
25 subpopulation may be of particular concern since a larger number of newboms are totally breast fed.
26 In addition, with the exception of Butte (1984), data were not presented on a body weight basis.
27 This is particularly important since intake rates may be higher on a body weight basis for younger
28 infants. Also, the data used to derive the recommendations are over 10 years old and the sample size
29 of the studies was small. Other subpopulations of concern such as mothers highly committed to
30 breast feeding, sometimes for periods longer than 1 year, may not be captured by the studies
June 2000 2-8 DRAFT-DO NOT QUOTE OR CITE
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1 presented in this chapter. Further research is needed to identify these subgroups and to get better
2 estimates of breast milk intake rates. Table 2-10 presents the confidence rating for breast milk intake
3 recommendations.
4 Breast Milk Intake - The breast milk intake rates for nursing infants that have been reported
5 in the studies described in this section are summarized in Table 2-11. Based on the combined results
6 of these studies, 742 mL/day is recommended to represent an average breast milk intake rate, and
7 1,033 mL/day represents an upper-percentile intake rate (based on the middle range of the mean plus
8 2 standard deviations) for infants between the ages of 1 and 6 months of age. The average value is
9 the mean of the average intakes at 1, 3, and 6 months from the key studies listed in Table 2-11. It
10 is consistent with the average intake rate of 718 to 777 mL/day estimated by NAS (1991) for infants
11 during the first 4 to 5 months of life. Intake among older infants is somewhat lower, averaging 413
12 mL/day for 12-month olds (Neville et al. 1988; Dewey et al. 1991 a; 1991 b). When a time weighted
13 average is calculated for the 12-month period, average breast milk intake is approximately 688
14 mL/day, and upper-percentile intake is approximately 980 mL/day. Table 2-12 summarizes these
15 recommended intake rates.
Lipid Content and Lipid Intake - Recommended lipid intake rates are based on data from
'17 Butte et al. (1984) and Maxwell and Burmaster (1993). Butte et al. (1984) estimated that average
18 lipid intake ranges from 23.6 ± 7.2 g/day (22.9 ± 7.0 mL/day) to 28.0 ± 8.5 g/day (27.2 ± 8.3
19 mL/day) between 1 and 4 months of age. These intake rates are consistent with those observed by
20 Burmaster and Maxwell (1993) for infants under 1 year of age [(26.8 ± 7.4 g/day (26.0 ± 7.2
21 mL/day)]. Therefore, the recommended breast milk lipid intake rate for infants under 1 year of age
22 is 26.0 mL/day and the upper-percentile value is 40.4 mL/day (based on the mean plus 2 standard
23 deviations). The recommended value for breast milk fat content is 4.0 percent based on data from
24 NAS (1991), Butte et al. (1984), and Maxwell and Burmaster (1993).
25
26
June 2000 2-9 DRAFT-DO NOT QUOTE OR CITE
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1 2.6 REFERENCES FOR CHAPTER 2
2
3 Brown, KJH.; Akhtar, N.A.; Robertson, A.D.; Ahmed, M.G. (1986a) Lactational capacity of marginaliy nourished
4 mothers: relationships between maternal nutritional status and quantity and proximate composition of milk.
5 Pediatrics. 78:909-919.
6
7 Brown, K.H.; Robertson, A.D.; Akhtar, N.A. (1986b) Lactational capacity of marginally nourished mothers: infants'
8 milk nutrient consumption and patterns of growth. Pediatrics. 78: 920-927.
9
10 Butte, N.F.; Garza, C.; Smith, E.O.; Nichols, B.L. (1984) Human milk intake and growth in exclusively breast-fed
11 infants. Journal of Pediatrics. 104:187-195.
12
13 Dewey, K.G.; Lonnerdal, B. (1983) Milk and nutrient intake of breast-fed infants from 1 to 6 monthsrrelation to growth
14 and fatness. Journal of Pediatric Gastroenterplogy and Nutrition. 2:497-506.
15
16 Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lonnerdal, B. (199 I a) Maternal versus infant factors related to breast milk
17 intake and residual volume: the DARLING study. Pediatrics. 87:829-837.
18
19 Dewey, K.G.; Heinig, J.; Nommsen, L.; Lonnerdal, B. (1991 b) Adequacy of energy intake among breast-fed infants
20 in the DARLING study: relationships to growth, velocity, morbidity, and activity levels. The Journal of Pediatrics.
21 119:538-547.
22
23 HofVander, Y.; Hagman, U.; Hillervik, C.; Sjolin, S. (1982) The amount of milk consumed by 1-3 months old breast-
24 or boaie-fed infants. Acta Paedjatr. Scand. 71:953-958.
25
26 LSnnerdal, B.; Forsum, E.; Gebre-Medhim, M.; Hombraes, L. (1976) Breast milk composition in Ethiopian and
27 Swedish mothers: lactose, nitrogen, and protein contents. The American Journal of Clinical Nutrition. 29:1134-
28 1141.
29
30 Maxwell, N.I.; Burrnaster, D.E. (1993) A simulation model to estimate a distribution of lipid intake from breast milk
31 during the first year of life. Journal of Exposure Analysis and Environmental Epidemiology. 3:383-406.
32
33 National Academy of Sciences (NAS). (1991) Nutrition during lactation. Washington, DC. National Academy Press.
34
35 Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.; Neifert, M.; et al. (1988) Studies in human lactation: milk volumes in
36 lactating women during the onset of lactation and full lactation. American Journal of Clinical Nutrition. 48:1375-
37 1386.
38
39 Pao, E.M.; Hines, J.M.; Roche, A.F. (1980) Milk intakes and feeding patterns of breast-fed infants. Journal of the
40 American Dietetic Association. 77:540-545.
41
42 Ryan, A.S.: Rush, D.; Krieger, F.W.; Lewandowski, G.E. (1991) Recent declines in breastfeeding in the United States,
43 1984-1989. Pediatrics. 88:719-727.
44
45 Ryan, A.S. (1997) The resurgence of breastfeeding in the United States. 99(4):eI2.
46
47
48
49
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
18
9
21
22
23
24
25
26
27
28
29
30
31
32
Table 2-1. Daily Intakes of Breast Milk
Number of Infants Surveyed
Age at Each Time Period
Completely Breast-fed
1 month
3 months
6 months
Partially Breast-fed
1 month
3 months
6 months
9 months
11
2
i
4
11
6
3
Mean intake
(mL/day) '
600 ±159
833
682
485 ± 79
467=100
395 i 175
<554
Range of
Daily Intake
(mL/day)
426
645-
616
398
242
147
451
-989
1.000
-786
-655
-698
-684
-732
'Data expressed as mean ± standard deviation.
Source: Pao et al. (1980).
Table 2-2. Breast Milk Intake for Infants Aged 1 to 6 Months
Age (months)
1
2
3
4
5
6
Number of Infants
16
!9
16
13
11
11
Mean (mL/day)
673
756
782
810
805
896
SD (mL/day) 3
192
170
172
142
117
122
Range (mL/day)
341-1.003
449-1.055
492-1.053
593-1.045
554-1,045
675-1.096
'Standard deviation.
Source: Dewey and Lonnerdal (1983).
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 2-3. Breast Milk Intake among Exclusively Breast-fed
Infants During the First 4 Months of Life
Age (months)
1
2
3
4
Number of Infants
37
40
37
41
Breast Milk Intake3
(g/day)
75 1.0 ±130.0
725.0 ±13 1.0
723.0= 114.0
740.0=128.0
Breast Milk Intake9
(g/kg-day)
159.0 ±24.0
129.0 ±19.0
11 7.0 ±20.0
111.0=17.0
Body Weight11
"(kg) "
4.7
5.6
6.2
6.7
'Data expressed as mean ± standard deviation.
''Calculated by dividing breast milk intake (g/day) by breast milk intake (g/kg-day).
Source: Butteetal. (1984).
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Table 2-4. Breast Milk Intake During a 24-hour Period
4
5
6
7
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
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
Number of Infants
7
to
11
11
12
10
8
9
10
iO
8
10
10
13
12
12
10
13
12
13
13
13
12
10
12
n
9
9
'Negative value due to insensible water loss
Source:
Neville etal. (1988).
Mean
(g/day)
44
182
371
451
498
508
573
581
580
589
615
653
651
770
668
711
709
694
734
711
838
766
721
,622
618
551
554
403
correction.
Standard Deviation
(g/day)
71
86
153
176
129
167
167
159
76
132
168
154
84
179
117
111
115
98
114
100
134
121
154
210
220
234 ,
240
250
Range
(g/day)
-31-149'
44-355
209-688
164-694
323-736
315-861
406-842
410-923
470-720
366-866
398-934
416-922
554-786
495-1144
465-930
554-896
559-922
556-859
613-942
570-847
688-1173
508-936
486-963
288-1002
223-871
129-894
120-860
65-770
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1
2
3
4
6
7
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
Table 2-5. Breast Milk Intake Estimated bv the Darling Studv
Age (months)
Number of Infants
Mean Intake (g/day)
Standard Deviation (g/day)
3
6
9
12
73
60
50
42
812
769
646
448
133
171
217
251
Source: Dewey et ai. (1991b).
Table 2-6. Lipid Content of Human Milk and Estimated Lipid Intake among Exclusively Breast-fed Infants
Age (months)
1
2
3
4
Number
of
Observations,
37
40
37
41
Lipid
Content
(mg/g) a
36.2 ±7.5
34.4 ±6.8
32.2 ± 7.8
34.8=10.8
Lipid
Content
(percent) b
3.6
3.4
3.2
3.5
Lipid
Intake
(g/day)11
28.0 ±8.5
25.2 ±7.1
23.6 ±7.2
25.6 ±8.6
Lipid
Intake
(g/kg-day) *
5.9 ±1.7
4.4 i 1.2
3.8=1.2
3.8 ±1.3
'Data expressed as means ± standard deviations.
bPercents calculated from lipid content reported in mg/g.
Source: Butte, etal. (1984).
Table 2-7. Predicted Lipid Intakes for Breast-fed
Infants under 12 Months of Age
Statistic
Value
Number of Observations in Simulation
Minimum Lipid Intake
Maximum Lipid Intake
Arithmetic Mean Lipid Intake
Standard Deviation Lipid Intake
1J13
1.0 g/day
51.5 g/day
26.8 g/day
7.4 g/day
Source: Maxwell and Burmaster (1993).
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Table 2-8. Number of Meals per Day
Age (months)
Bottle-fed Infants (meals/day)'
Breast-fed (meals/day)*
1
2
3
5.4 (4-7)
4.8 (4-6)
4.7 (3-6)
5.8(5-7)
5.3 (5-7)
5.1 (4-8)
8
9
10
11
12
13
14
15
"Data expressed as mean with range in parentheses.
Source: Hofvanderetal. (1982).
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1
2
3
4
5
Table 2-9. Percentage of Mothers Breast-feeding Newborn
Infants in the Hospital and Infants at 5 or 6 Months
Of Age in the United States in 19891. by Ethnic
Background and Selected Demographic Variables6
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
45
46
47
48
49
50
Total
Category
All mothers
Parity
Primiparous
Multiparous
Marital status
Married
Unmarried
Maternal age
<20yr
20-24 yr
25-29 yr
30-34 yr
s35 yr
Maternal education
Nocolleee
College""
Family income
<$7.000
S7.000-S1 4.999
$15,000-524.999
2 $25.000
Maternal employment
Full time
Part time
Not employed
U.S. census region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
Newborns
52.2
52.6
51.7
59.8
30.8
30.2
45.2
58.8
65.5
66.5
42.1
70.7
28.8
44.0
54.7
66.3
50.8
59.4
51.0
52.2
47.4
47.6
55.9
43.8
37.9
46.0
70.2
70.3
5-6 Mo
infants
19.6
16.6
22.7
24.0
7.7
6.2
12.7
22.9
31.4
36.2
13.4
31.1
7.9
13.5
20.4
27.6
10.2
23.0
23.1
20.3
18.4
18.1
19.9
14.8
12.4
•14.7
30.4
28.7
White
Newboms
58.5
58.3
58.7
61.9
40.3
36.8
50.8
63.1
70.1
71.9
48.3
74.7
36.7
49.0
57.7
67.8
54.8
63.8
58.7
53.2
52.4
53.2
58.2
53.8
45.1
56.2
74.9
76.7
5-6 Mo
infants
22.7
18.9 .
26.8
25.3
9.8
7.2
14.5
25.0
34.8
40.5
15.6
34.1
9.4
15.2
22.3
28.7
10.8
25.5
27.5
21.4
21.8
20.7
20.7
18.7
15.0
18.4
33.0
33.4
Black
Newborns
23.0
23.1
23.0
35.8
17.2
53.5
19.4
29.9
35.4
35.6
17.6
41.1
14.5
23.5
31.7
42.8
30.6
26.0
19.3
35.6
30.6
21.0
27.7
19.6
14.2
14.5
31.5
43.9
5-6 Mo
Infants
7.0
5.9
7.9
12.3
4.6
3.6
4.7
9.4
13.6
14.3
5.5
12.2
4.3
7.3
8.7
14.5
6.9
6.6
7.2
5.0
9.7
7.2
7.9
5.7
3.7
3.8
11.0
15.0
Hispanic'
Newborns
48.4
49.9
47.2
55.3
37.5
35.3
46.9
56.2
57.6
53.9
42.6
66.5
35.3
47.2
52.6
65.4
50.4
59.4
46.0
47.6
41.4
46.2
50.8
48.0
23.5
39.2
53.9
58.5
5-6 Mo
Infants
15.0
13.2
16.5
18.8
8.6
6.9
12.6
19.5
23.4
24.4
12.2
23.4
10.3
13.0
16.5
23.0
9.5
17.7
16.7
14.9
10.8
12.6
22.8
13.8
5.0
11.4
18.2
19.7
'Mothers were surveyed when their infants were 6 months of age. They were asked to recall the method of feeding the infant
when in the hospital, at age 1 week, at months 1 through 5. and on the day preceding completion of the survey. Numbers in
the columns labeled "5-6 Mo Infants" are an average of the 5-month and previous day responses.
"Based on data from Ross Laboratories.
'Hispanic is not exclusive of white or black.
•"College includes all women who reported completing at least 1 year of college.
Source: NAS (1991).
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Table 2-10. Confidence in Breast Milk Intake Recommendations
Considerations
Rationale
Rating
4
5
6
7
8
9
10
11
12
13
15
16
17
18
19
20
21
22
23
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection period
Validity of approach
Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high
rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
All key studies are from peer review literature. High
Papers are widely avai lable from peer review journals. High
Methodology used was clearly presented. High
The focus of the studies was on estimating breast milk intake. High
Subpopulations of the L'.S. were the focus of all the key studies. High
All the studies were based on primary data. High
Studies were conducted between 1980-1986. Although incidence Medium
of breast feeding may change with time, breast milk intake among
breastfed infants may not.
Infants were not studied long enough to fully characterize day to Medium
day variability.
Methodology uses changes in body weight as a surrogate for total Medium
ingestion. This is the best methodology there is to estimate breast
milk ingestion. Mothers were instructed in the use of infant scales
to minimize measurement errors. Three out of the 5 studies
corrected data for insensible water loss.
The sample sizes used in the key studies were fairly small (range Low
13-73).
Population is not representative of the U.S.: only rnid-upper class. Low
well nourished mothers were studied. Socioeconomic factors may
affect the incidence of breastfeeding. Mother's nourishment may
affect milk production.
Not very well characterized. Infants under I month not captured. ' Low
mothers committed to breast feeding over I year not captured.
Bias in the studies was not characterized. Three out of 5 studies Low
corrected for insensible water loss. Not correcting for insensible
water loss may underestimate intake. Mothers selected for the
studies were volunteers; therefore response rate does not apply.
Population studied may introduce some bias in the results (see
above).
All mothers were well educated and trained in the use of the scale Medium
which helped minimize measurement error.
There are 5 key studies. High
There is good agreement among researchers. High
Studies were well designed. Results were consistent. Sample size Medium
was fairly low and not representative of U.S. population or
population of nursing mothers. Variability cannot be characterized
due to limitations in data collection period. ____
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1
2
3
4
6
7
8
9
10
II
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Table 2-11. Breast Milk Intake Rates Derived from Key Studies
Mean (mL/day)
Upper Percentile (mL/day)
(mean plus 2 standard deviations)
Reference
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
Age: 1 Month
600 II
729 37
747 13
673 16
weighted avg = 702
Age: 3 Months
833 2
702 .37
712 12
782 16
788 73
•weighted avg = 759
Age: 6 Months
682 1
744 13
896 11
747 60
weighted avg = 765
Age: 9 Months
600 12
627 50
avg = 622
Age: 12 Months
391 9
435 42
weighted avg = 427
!2-MO\TH TIME WEIGHTED Al'ERAGE
688
918
981
1.095
1.057
1.007'
923
934
1.126
1.046
1.025'
978
1.140
1,079
1,059*
1.027
1.049
1.038
877
923
900
Range 900-1,059
(middle of the range 980)
PaoetaL 1980
Butteeta!.. 1984
Neville et al.. 1988
Dewev and Lonnerdal. 1983
Paoetal.. 1980
ButteetaL 1984
Neville eta!.. 1988
Dewey and Lonnerdal. 1983
Dewev etal.. 1991 b
PaoetaL. 1980
Neville etal.. 1988
Dewey and LdnnerdaL 1983
Dewey etal.. 1991b
Neville et a!.. 1988
Dewev etal. 1991b
Neville etai.. 1988
Dewev etal.. 199 la; 199Ib
"Middle of the range.
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Table 2-12. Summary of Recommended Breast Milk
And Lipid Intake Rates
5
6
7
8
9
10
11
12
13
14
15
Age
Breast Milk
1-6 Months
12 Month Average
Lipids"
<1 Year
"The recommended value
Mean
742 mL/day
688 mL/day
26.0 mL/day
for the lipid content of breastmilk is 4.0 percent.
Upper Percentile
1,033 mL/day
980 mL/day
40.4 mL/dav
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3. FOOD INTAKE
3 3.1 INTRODUCTION
4 Ingestion of contaminated foods is a potential pathway of exposure to toxic chemicals
5 among children. Fruits, vegetables, and grains may become contaminated with toxic chemicals
6 by several different pathways. Ambient pollutants from the air may be deposited on or absorbed
7 by the plants, or dissolved in rainfall or irrigation waters that contact the plants. Pollutants may
8 also be absorbed through plant roots from contaminated soil and ground water. The addition of
9 pesticides, soil additives, and fertilizers may also result in food contamination. Meat, poultry,
10 and dairy products can become contaminated if animals are exposed to contaminated media (i.e.,
11 soil, water, or feed crops). Contaminated finfish and shellfish are also potential sources of
12 human exposure to toxic chemicals. Pollutants are carried in the surface waters, but also may be
13 stored and accumulated in the sediments as a result of complex physical and chemical processes.
14 Consequently, finfish and shellfish are exposed to these pollutants and may become sources of
15 contaminated food. Intake rates for home produced food products are needed to assess exposure
to local contaminants present in homegrown or home caught foods.
17 Exposure to children from food ingestion may differ from that of adults because of
18 differences in the type and amounts of food eaten. Also, for many foods, the intake per unit body
19 weight is greater for children than adults. The most common foods eaten by children include
20 milk, nonfat solids; apple juice; apples, fresh; orange juice; pears, fresh; milk, fat, solids;
21 peaches, fresh; carrots; beef, lean; milk sugar (lactose); bananas, fresh; rice, milled; peas,
22 succulent, garden; beans, succulent, garden; oats; soybean oil; coconut oil; and wheat flour
23 (Goldman, 1995).
24 The primary source of recent information on consumption rates of foods among children
25 is the U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey (NFCS) -
26 and the USDA Continuing Survey of Food Intakes by Individuals (CSFII). Data from the 1989-
27 91 and 1994-96 CSFIIs have been used in various studies to generate children's per capita intake
28 rates for both individual.foods and the major food groups. Earlier studies have used USDA's
29 Nationwide Food Consumption Survey (NFCS) from 1977/78 or 1987/88. Because data from
the 1989-91 and 1994-96 CSFIIs are available, data from the older surveys are not reported here,
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
except in the case of data on homegrown foods, which are based on the 1987/88 NFCS, and
serving size information, which is based on the 1977/78 NFCS. Older USDA data analyses can
be found in Exposure Factors Handbook (U.S. EPA 1997).
It should be noted that a variety of terms may be used to define intake. These terms (e.g.,
consumer-only intake, per capita intake, as consumed intake, dry weight intake) 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 foods
consumed only by children who ate these food items during the survey period. Per capita intake
rates are generated by averaging consumer-only intakes over the entire population of children
(i.e., both users and non-users). 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. Intake rates for the
major food categories include all forms of that food type. For example, 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 presented on an "as consumed" (e.g., cooked) basis or on the basis of
an uncooked weight. As consumed intake rates (g/day) 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 whole weight. When data are based on "as consumed" form,
corrections to account for changes in portion sizes from cooking losses are generally not
required. When dry weight contaminant concentrations in foods are available, dry weight intake
rates must be used. Dry weight intake rates are based on the weight of the food consumed after
the moisture Content has been removed.
Estimating source-specific exposures to toxic chemicals in fruits and vegetables may also
require information on the amount of fruits and vegetables that are exposed to or protected from
contamination as a result of cultivation practices or the physical nature of the food product itself
(i.e., those having protective coverings that are removed before eating would be considered
protected), or the amount grown beneath the soil (i.e., most root crops such as potatoes). The
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1 percentages of foods grown above and below ground will be useful when the concentrations of
2 contaminants in foods are estimated from concentrations in soil, water, and air. For example,
3 vegetables grown below ground may be more likely to be contaminated by soil pollutants, but
4 leafy above ground vegetables may be more likely to be contaminated by deposition of air
5 pollutants on plant surfaces.
6 The purpose of this section is to provide: (1) intake data for individual foods, the major
7 food groups, and total foods among children, including homegrown foods; (2) guidance for
8 converting between as consumed and dry weight intake rates; and (3) intake data for exposed and
9 protected fruits and vegetables and those grown below ground. Recommendations are based on
10 average and upper-percentile intake among the general population of the U.S.
11
12 3.2 INTAKE RATE DISTRIBUTIONS FOR VARIOUS FOOD TYPES
13 £7.5. EPA (2000) - Analysis ofUSDA 1994-96 CSFII Data to Generate Intake Rates for
14 Major Food Groups and Individual Foods - EPA's National Center for Environmental
15 Assessment (NCEA) analyzed three years of data from USDA's CSFII to generate distributions
of intake rates for various food items/groups. USDA conducts CSFII annually to "assess food
17 consumption behavior and nutritional content of diets for policy implications relating to food
18 production and marketing, food safety, food assistance, and nutrition education" (USDA, 1995).
19 The survey uses a statistical sampling technique designed to ensure that all seasons, geographic
20 regions of the U.S., and demographic and socioeconomic groups are represented. Using a
21 stratified sampling technique, individuals of all ages living in selected households in the 50 states
22 and Washington. D.C. were surveyed. Individuals provided 2 non-consecutive days of data,
23 based on 24-hour recall. The 2-day response rate for the 1994-96 CSFII was approximately 76
24 percent. Data from the 1994 1995, and 1996 CFSII were combined into a single data set to
25 increase the number of observations available for analysis. Approximately 15.000 individuals
26 provided intake data over the three survey years (USDA, 1998).
27 The food groups selected for this analysis include the major food groups: total fruits, total
28 vegetables, total grains, total meats, and total dairy. Individual foods include fruit and vegetable
29 items such as: apples, bananas, peaches, pears, strawberries, and other berries; individual
vegetables such as: asparagus, beets, broccoli, cabbage, carrots, com, cucumbers, lettuce, lima
June 2000 3-3 DRAFT-DO NOT QUOTE OR CITE
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1 beans, okra, onions, peas, peppers, pumpkin, snap beans, tomatoes, .and white potatoes; fruits and
2 vegetables categorized as exposed, protected and roots; and various USDA categories (i.e., citrus
3 and other fruits, and dark green, deep yellow, and other vegetables). Individual meats include
4 beef, eggs, game, pork, and poultry; and individual grain items include breads, breadfast foods,
5 cereals, pasta, rice, snacks, and sweets. Intake rates of total vegetables, tomatoes, and white
6 potatoes, total meats, fish, beef, pork, poultry, dairy, eggs, and total grains were adjusted to
7 account for the amount of these food items eaten as meat and grain mixtures as described in
8 Appendix 3A. Food items/groups were identified in the CSFII data base according to USDA-
9 defined food codes. Appendix 3B presents the codes used to determine the various food groups.
10 Intake rates for these food items/groups represent intake of all forms of the product (i.e., home
11 produced and commercially produced).
12 Individual identifiers in the database were used throughout the analysis to categorize
13 populations according to demographics. These identifiers included identification number, age,
14 body weight, weighting factor, and number of days that data were reported. Distributions of
15 intake were determined for children who provided data for two days of the survey. Individuals
16 . who did not provide information on body weight, or for which identifying information was
17 unavailable, were excluded from the analysis. Two-day average intake rates were calculated for
18 all individuals in the database for each of the food items/groups. These average daily intake rates
19 were divided by each individual's reported body weight to generate intake rates in units of g/kg-
20 day. The data were also weighted according to the two-day weights provided in the 1994-96
21 CSFII. USDA sample weights are calculated to account for inherent biases in the sample
22 selection process, and to adjust the sample population to reflect the national population.
23 Summary statistics for individual intake rates were generated on a per capita basis. That is, both
24 users and non-users of the food item were included in the analysis. Mean consumer only intake
25 rates may be calculated by dividing the mean per capita intake rate by the percent of the
26 population consuming the food item of interest. Intake data from the CSFII are based on "as
27 eaten" (i.e., cooked or prepared) forms of the food items/groups. Thus, corrections to account for
28 changes in portion sizes from cooking losses are not generally required. Summary statistics
29 included are: number of weighted and unweighted observations, percentage of the population
30 using the food item/group being analyzed, mean intake rate, standard error, and percentiles of the
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1 intake rate distribution (i.e., 0, 1, 5,10,25, 50,75, 90, 95, 99, and 100th percentile). Data were
Jfe 2 provided for the total population using the food item being evaluated and for several age groups
3 of children, including <1, 1-2, 3-5, 6-11, and 12-19 years. The total numbers of individuals in
4 the data set, by age group are presented in Table 3-1. The food analysis was accomplished using
5 the SAS statistical programming system (SAS, 1990).
6 The results of this analysis are presented in Table 3-2 for total fruits, total vegetables,
7 total grains, total meats, total fish, and total dairy products. Table 3-3 provides data for
8 individual foods, and Table 3-4 for the various USDA categories. The data for -
9 exposed/protected and root food items are presented in Table 3-5. These tables are presented at
10 the end of this Chapter. The results are presented in units of g/kg-day. Thus, use of these data in
11 calculating potential dose does not require the body weight factor to be included in the
12 denominator of the average daily dose (ADD) equation. It should be noted that converting these
13 intake rates into units of g/day by multiplying by a single average body weight is inappropriate,
14 because individual intake rates were indexed to the reported body weights of the survey
15 . respondents. However, if there is a need to compare the intake data presented here to intake data
tl6 in units of g/day, a body weight for the age group of interest, as presented in Chapter 10 of this
17 document should be used.
18 Short-term data are suitable for estimating mean average daily intake rates representative
19 of both short-term and long-term consumption. However, the distribution of average daily intake
20 rates generated using short-term data (e.g., 2-day) do not necessarily reflect the long-term
21 distribution of average daily intake rates. The distributions generated from short-term and long-
22 term data will differ to the extent that each individual's intake varies from day to day; the
23 distributions will be similar to the extent that individual's intakes are constant from day to day.
24 Day to day variation in intake among individuals will be great for food item/groups that
25 are highly seasonal and for items/groups that are eaten year around but that are not typically
26 eaten every day. For these foods, the intake distribution generated from short-term data will not
27 be a good reflection of the long-term distribution. On the other hand, for broad categories of
28 foods (e.g., vegetables) which are eaten on a daily basis throughout the year with minimal
29 seasonality. the short-term distribution may be a reasonable approximation of the true long-term
distribution, although it will show somewhat more variability. Distributions are shown only for
June 2000 3-5 DRAFT-DO NOT QUOTE OR CITE
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1 the major food groups and broad categories of foods. For individual foods, only the mean
2 standard deviation and percent consuming are provided. Because of the increased variability of
3 the short-term distribution, the short-term upper percentiles shown here will overestimate
4 somewhat the corresponding percentiles of the long-term distribution.
5 The advantages of using the 1949-96 CSFII data set are that the data are expected to be
6 generally representative of the U.S. population and that it includes data on a wide variety of food
7 types. The data set is the most recent of a series of publicly available USD A data sets, and
8 should.reflect recent eating patterns in the United States. The data set includes three years of
9 intake data combined and are based on a two-day survey period. Short-term dietary data may not
10 accurately reflect long-term eating patterns. This is particularly true for the tails (extremes) of
11 the distribution of food intake. In addition, the adjustment for including mixtures adds
12 uncertainty to the intake rate distributions. The calculation for including mixtures assumes that
13 intake of any mixture includes all of the foods identified in Appendix Table 3A-1 in the
14 proportions specified in that table. This may under- or over-estimate intake of certain foods
15 among some individuals.
16
17 3.3 FISH INTAKE RATES
18 3.3.1 General Population Studies
19 U.S. EPA (1996) - Daily Average Per Capita Fish Consumption Estimates Based on the
20 Combined USDA 1989, 1990, and 1991 CSFII—EPA's Office of Water used the 1989,1990, and
21 1991 CSFII data to generate fish intake estimates. Participants in the CSFII provided
22 3 consecutive days of dietary data. For the first day's data, participants supplied dietary recall
23 information to an in-home interviewer. Second and third day dietary intakes were recorded by
24 participants. Data collection for the CSFII started in April of the given year and was completed
25 in March of the following year.
26 The CSFII contains 469 fish-related food codes; survey respondents reported
27 consumption across 284 of these codes. Respondents estimated the weight of each food that they
28 consumed. The fish component (by weight) of these foods was calculated using data from the
29 recipe file for release 7 of the USDA's Nutrient Data Base for Individual Food Intake Surveys.
30 The amount offish consumed by each individual was then calculated by summing, over all fish
June 2000
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1 containing foods, the product of the weight of food consumed and the fish component (i.e., the
2 percentage fish by weight) of the food.
3 The recipe file also contains cooking loss factors associated with each food. These were
4 utilized to convert, for each fish containing food, the as-eaten fish weight consumed into an
5 uncooked equivalent weight offish. Analyses offish intake were performed on both an as-eaten
6 and uncooked basis.
7 • Each (fish-related) food code was assigned by EPA a habitat type of either freshwater/
8 estuarine or marine. Food codes were also designated as finfish or shellfish. Average daily
9 individual consumption (g/day) for a given fish type-by-habitat category (e.g., marine finfish)
10 was calculated by summing the amount of fish consumed by the individual across the three
11 reporting days for all fish-related food codes in the given fish-by-habitat category and then
12 dividing by 3. Individual consumption per day consuming fish (g/day) was calculated similarly
13 except that total fish consumption was divided by the specific number of survey days the
14 individual reported consuming fish; this was calculated for fish consumers only (i.e., those
15 consuming fish on at least one of the three survey days). The reported body-weight of the
6 individual was used to convert consumption in g/day to consumption in g/kg-day.
17 There were a total of 11,912 respondents in the combined data set who had three-day
18 dietary intake data. Survey weights were assigned to this data set to make it representative of the
19 U.S. population with respect to various demographic characteristics related to food intake.
20 U.S. EPA (1996) reported means, medians, upper percentiles, and 90-percent interval
21 estimates for the 90th, 95th, and 99th percentiles. The 90-percent interval estimates are
22 nonparametric estimates from bootstrap techniques. The bootstrap estimates result from the
23 percentile method which estimates the lower and upper bounds for the interval estimate by the
24 1 OOa percentile and 100 (1 -a) percentile estimates from the non-parametric distribution of the
25 given point estimate (U.S. EPA, 1996). Analyses offish intake were performed on an as-eaten as
26 well as on an uncooked equivalent basis and on a g/day and g/kg-day basis.
27 Table 3-6 presents data for daily average per capita fish consumption by age and gender -
28 in g/day and in mg/kg/day, as consumed. Table 3-7 provides consumer only data in units of
29 g/day and mg/kg/day, as consumed. Tables 3-8 and 3-9 provide similar data on an uncooked
basis. These data are presented by selected age groupings (4-and under and 15-44) and gender.
June 2000 * ^ 3-7 DRAFT-DO NOT QUOTE OR CITE
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1 The advantages of this study are its large size, its relative currency and its
2 representativeness. In addition, through use of the USDA recipe files, the analysis identified all
3 fish-related food codes and estimated the percent fish content of each of these codes. By
4 contrast, some analyses of the USDA National Food Consumption Surveys (NFCSs) which
5 reported per capita fish intake rates (e.g., Pao et al., 1982; USDA, 1992), excluded certain fish
6 . containing foods (e.g., fish mixtures, frozen plate meals) in their calculations.
7 EPA, Office of Water, is currently in the process of analyzing data from the 1994,1995,
8 and 1996 CSFIIs. Total fish intake was estimated from the 1994-96 CSFII by EPA/NCEA (see
9 Section 3.2). The EPA, Office of Water data will be in this Handbook when available.
10 Tuna Research Institute Survey - The Tuna Research Institute (TRI) funded a study of
11 fish consumption which was performed by the National Purchase Diary (NPD) during the period
12 of September, 1973 to August, 1974. The data tapes from this survey were obtained by the
13 National Marine Fisheries Service (NMFS), which later, along with the FDA, USDA and TRI,
14 conducted an intensive effort to identify and correct errors in the data base. Javitz (1980)
15 summarized the TRI survey methodology and used the corrected tape to generate fish intake
16 distributions for various sub-populations.
17 The TRI survey sample included 6,980 families who were currently participating in a
!8 syndicated national purchase diary panel, 2,400 additional families where the head of household
19 was female and under 35 years old; and 210 additional black families (Javitz, 1980). Of the
20 9,590 families in the total sample, 7,662 families (25,162 individuals) completed the
21 questionnaire, a response rate of 80 percent. The survey was weighted to represent the U.S.
22 population based on a number of census-defined controls (i.e., census region, household size,
23 income, presence of children, race and age). The calculations of means, percentiles, etc. were
24 performed on a weighted basis with each person contributing in proportion to his/her assigned
25 survey weight.
26 The survey population was divided into 12 different sample segments and, for each of the
27 12 survey months, data were collected from a different segment. Each survey household was
28 given a diary in which they recorded, over a one month period, the date of any fish meals
29 consumed and the following accompanying information: the species offish consumed, whether
30 the fish was commercially or recreationally caught, the way the fish was packaged (canned,
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1 frozen fresh, dried, smoked), the amount offish prepared and consumed, and the number of
2 servings consumed by household members and guests. Both meals eaten at home and away from
3 home were recorded. The amount of fish prepared was determined as follows (Javitz, 1980):
4 "For fresh fish, the weight was recorded in ounces and may have included the weight of the head
5 and tail. For frozen fish, the weight was recorded in packaged ounces, and it was noted whether
6 the fish was breaded or combined with other ingredients (e.g., TV dinners). For canned fish, the
7 weight was recorded in packaged ounces and it was noted whether the fish was canned in water,
8 oil, or with other ingredients (e.g., soups)".
9 Javitz (1980) reported that the corrected survey tapes contained data on 24,652
10 individuals who consumed fish in the survey month and that tabulations performed by NPD
11 indicated that these fish consumers represented 94 percent of the U.S. population. For this
12 population of "fish consumers," Javitz (1980) calculated means and percentiles of fish
13 consumption by age (Table 3-10). The overall mean fish intake rate among fish consumers was
14 calculated at 6.2 g/day for ages 0-9 years and 10.1 g/day for ages 10-19 years, the 95th
15 percentile fish ingestion rates were 16.5 g/day for ages 0-9 years and 26.8 g/day for ages 10-19
6 years.
17 The TRI survey data were also utilized by Rupp et al. (1980) to generate fish intake
18 distributions for three age groups (<11,12-18. and 19+ years) within each of the 9 census regions
19 and for the entire United States. Separate distributions were derived for freshwater finfish,
20 saltwater finfish and shellfish; thus, a total of 90 (3 * 3 * 10) different distributions were derived,
21 each corresponding to intake of a specific category offish for a given age group within a given
22 region. The analysis of Rupp et al. (1980) included only those respondents with known age.
23 This amounted to 23.213 respondents.
24 Ruffle et al. (1994) used the percentiles data of Rupp et al.'(1980) to estimate the best
25 fitting lognormal parameters for each distribution. Three methods (non-linear optimization, first
26 probability plot and second probability plot) were used to estimate optimal parameters. Ruffle
27 et al. (1994) determined that, of the three methods, the non-linear optimization method (NLO)
28 generally gave the best results. For some of the distributions fitted by the NLO method,
29 however, it was determined that the lognormal model did not adequately fit the empirical fish
intake distribution. Ruffle et al. (1994) used a criterion of minimum sum of squares (min SS) less
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1 than 30 to identify which distributions provided adequate fits. Of the 90 distributions studied,
2 • 77 were seen to have min SS < 30; for these, Ruffle et al. (1994) concluded that the NLO
3 modeled lognormal distributions are "well suited for risk assessment". Of the remaining
4 13 distributions, 12 had min SS > 30; for these Ruffle et al. (1994) concluded that modeled
5 lognormal distributions "may also be appropriate for use when exercised with due care and with
6 sensitivity analyses". One distribution, that of freshwater finfish intake for children < 11 years of
7 age in New England, could not be modeled due to the absence of any reported consumption.
8 Table 3-11 presents the optimal lognormal parameters, the mean (/u), standard deviation
9 (s), and min SS, for all 89 modeled distributions. These parameters can be used to determine
10 percentiles of the corresponding distribution of average daily fish consumption rates through the
11 relation DFC(p)=expj>+ z(p)s] where DFC(p) is the pth percentile of the distribution of average
12 daily fish consumption rates and z(p) is the z-score associated with the pth percentile
13 (e.g., z(50)=0). The mean average daily fish consumption rate is given by exp[^ + 0.5s2].
14 The analyses of Javitz (1980) and Ruffle et al. (1994) were based on consumers only,
15 who are estimated to represent 94.0 percent of the U.S. population. U.S. EPA estimated the
16 mean intake in the general population by multiplying the fraction consuming, 0.94, by the mean
17 among consumers reported by Javitz (1980) of 14.3 g/day; the resulting estimate is 13.4 g/day.
18 The 95th percentile estimate of Javitz (1980) of 41.7 g/day among consumers would be
19 essentially unchanged when applied to the general population; 41.7 g/day would represent the
20 95.3 percentile (i.e., 100*[0.95*0.94+0.06]) among the general population.
21 Advantages of the TRI data survey are that it was a large, nationally representative survey
22 with a high response rate (80 percent) and was conducted over an entire year. In addition,
23 consumption was recorded in a daily diary over a one month period; this format should be more
24 reliable than one based on one-month recall. The upper percentiles presented are derived from
25 one month of data, and are likely to overestimate the corresponding upper percentiles of the
26 long-term (i.e., one year or more) average daily fish intake distribution. Similarly, the standard
27 deviation of the fitted lognormal distribution probably overestimates the standard deviation of
28 . the long-term distribution. However, the period of this survey (one month) is considerably
29 longer than those of many other consumption studies, including the USDA National Food
30 Consumption Surveys, which report consumption over a 3 day to one week period.
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1 Another obvious limitation of this data base is that it is now over twenty years out of
2 date. Ruffle et al. (1994) considered this shortcoming and suggested that one may. wish to shift
3 the distribution upward to account for the recent increase in fish consumption. Adding
4 ln(l+x/100) to the log mean ^ will shift the distribution upward by x percent (e.g., adding 0.22 =
5 ln(1.25) increases the distribution by 25 percent). Although the TRI survey distinguished
6 between recreationally and commercially caught fish, Javitz (1980), Rupp et al. (1980), and
7 Ruffle et al. (1994) (which was based on Rupp et al., 1980) did not present analyses by this
8 variable.
9 Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The
10 U.S. EPA collected information for the general population on the duration and frequency of time
11 . spent in selected activities and time spent in selected microenvironments via 24-hour diaries.
12 Over 9,000 individuals from 48 contiguous states participated in NHAPS. Approximately
13 4,700 participants also provided information on seafood consumption. Over 900 of these
14 participants were children between the ages of 1 and 17 years. The survey was conducted
15 between October 1992 and September 1994. Data were collected on the (1) number of people
6 that ate seafood in the last month, (2) the number of servings of seafood consumed, and (3)
17 whether the seafood consumed was caught or purchased (Tsang and Klepeis, 1996). The
18. participant responses were weighted according to selected demographics such as age, gender, and
19 race to ensure that results were representative of the U.S. population. Of the 900 children who
20 participated in the survey, approximately 43 percent reportedly ate seafood (including shellfish,
21 eels, or squid) in the last month. The number of servings per month were categorized in ranges
22 of 1 -2,3-5, 6-10,11 -19, and 20+ servings per month (Table 3-12). The highest number of
23 respondents for all ages of children had 1-2 servings per month. Most of the respondents
24 purchased the seafood they ate (Table 3-12).
25 Intake data were not provided in the survey. However, intake offish can be estimated
26 using the information on the number of servings offish eaten from this study and serving size
27 data for each age group from other studies (e.g., Pao et al., 1982). Using this mean value for
28 serving size and assuming that the average child eats 1-2 servings per month, the age-specific
29 amount of seafood eaten per month can be estimated.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
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 intake from this study are comparable to those observed in the EPA CSFII
analysis. It should be noted that an all inclusive description for seafood was not presented in
Tsang and Klepeis (1996). It is not known if processed or canned seafood and seafood mixtures
are included in the seafood category.
3.3.2 Freshwater Recreational Study
West et al. (1989) - Michigan Sport Anglers Fish Consumption Survey, 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 recording respondents' fish
intake over a seven day period and a usual frequency component. For the short-term component,
respondents were asked to identify all household members and list all fish meals consumed by
each household member during the past seven days. The source of the fish for each meal was
requested (self-caught, gift, market, or restaurant). Respondents were asked to categorize serving
size by comparison with pictures of 8 oz. fish portions; serving sizes could be designated as
either "about the same size", "less", or "more" than the 8 oz. picture. 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 offish meals
during each of the four seasons and requested respondents to give the overall percentage of
household fish meals that come 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 among individuals receiving questionnaires.
In the analysis of the survey data by West et. al. (1989), the authors did not attempt to
generate the distribution of recreationally caught fish intake in the survey population. EPA
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obtained the raw data of this survey for the purpose of generating fish intake distributions and
|2 other specialized analyses.
3 As described elsewhere in this handbook, percentiles of the distribution of average daily
4 intake reflective of long-term consumption patterns can not in general be estimated using
5 short-term (e.g., one week) data. Such data can be used to estimate mean average daily intake
6 rates (reflective of short or long term consumption); in addition, short term data can serve to
7 validate estimates of usual intake based on longer recall.
8 EPA first analyzed the short term data with the intent of estimating mean fish intake
9 rates. In order to compare these results with those based on usual intake, only respondents with
10 information on both short term and usual intake were included in this analysis. For the analysis
11 of the short term data, EPA modified the serving size weights used by West et al. (1989), which
12 were 5,8 and 10 oz., respectively, for portions that were less, about the same, and more than the
13 8 oz. picture. EPA examined the percentiles of the distribution offish meal sizes reported in Pao
14 et al. (1982) derived from the 1977-1978 USD A National Food Consumption Survey and
15 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 oz. and for serving
17 sizes at least 10 percent greater than 8 oz. were determined. In both cases a serving size of 12 oz.
18 was consistent with the Pao et al. (1982) distribution. The weights used in the EPA analysis then
19 were 5, 8, and 12 oz. for fish meals described as less, about the same, and more than the 8 oz.
20 picture, respectively. It should be noted that the mean serving size from Pao et al. (1982) was
21 about 5 oz.; well below the value of 8 oz. most commonly reported by respondents in the West
22 etal. (1989)survey.'
23 Table 3-13 displays the mean number of total and recreational fish meals for each
24 household member between age 1 and 20 years based on the seven day recall data. Also shown
25 are mean fish intake rates derived by applying the weights described above to each fish meal.
26 Intake was calculated on both a grams/day and grams/kg body weight/day basis. This analysis
27 was restricted to individuals who eat fish and who reside in households reporting some
28 recreational fish consumption during the previous year. About 75 percent of survey respondents
29 (i.e., licensed anglers) and about 84 percent of respondents who fished in the prior year reported
some household recreational fish consumption.
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1 The advantages of this data set and analysis are that the survey was relatively large and
2 contained both short-term and usual intake data. The response rate of this survey, 47 percent,
3 was relatively low. This study was conducted in the winter and spring months of 1989. This
4 . period does not include the summer months when peak fishing activity can be anticipated.
5 leading to the possibility that intake results based on the 7 day recall data may understate
6 individuals' usual (annual average) fish consumption.
7
8 3.3.3 Native American Subsistence Study
9 Columbia River Inter-Tribal Fish Commission (CRITFC) (1994) - A Fish Consumption
10 Survey of the Umatilla, Nez Perce, Yakama, and Warm Springs Tribes of the Columbia River
11 Basin - CRITFC (1994) conducted a fish consumption survey among four Columbia River Basin
12 Native American tribes during the fall and winter of 1991 -1992. The target population included
13 all adult tribal members who lived on or near the Yakama, Warm Springs, Umatilla or Nez Perce
14 reservations. The survey was based on a stratified random sampling design where respondents
15 were selected from patient registration files at the Indian Health Service. Interviews were
16 performed in person at a central location on the member's reservation. Information for 204
17 children 5 years old and less was provided by the participating adult respondent. The overall
18 response rate was 69 percent.
19 Information requested included annual and seasonal numbers of fish meals, average
20 serving size per fish meal, species and part(s) offish consumed, and preparation methods based
21 on 24-hour dietary recall (CRITFC, 1994). Foam sponge food models approximating four, eight,
22 and twelve ounce fish fillets were provided to help respondents estimate average fish meal size.
23 Fish intake rates were calculated by multiplying the annual frequency offish meals by the
24 average serving size per fish meal.
25 . The study was designed to give essentially equal sample sizes for each tribe. However,
26 since the population sizes of the tribes were highly unequal, it was necessary to weight the data
27 (in proportion to tribal population size) in order that the survey results represent the overall
28 population of the four tribes. Such weights were applied to the analysis of adults; however,
29 because the sample size for children was considered small, only an unweighted analysis was
30 performed for this population (CRITFC, 1994).
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1 A total of 49 percent of respondents of the total survey population reported that they
2 caught fish from the Columbia River basin and its tributaries for personal use or for tribal
3 ceremonies and distributions to other tribe members and 88 percent reported that they obtained
4 fish from either self-harvesting, family or friends, at tribal ceremonies or from tribal
5 distributions. Of all fish consumed, 41 percent came from self or family harvesting, 11 percent
6 from the harvest of friends, 35 percent from tribal ceremonies or distribution, 9 percent from
7 stores and 4 percent from other sources (CRITFC, 1994).
8 The analysis of seasonal intake showed that May and June tended to be high consumption
9 months and December and January low consumption months. Table 3-14 gives the fish intake
10 distribution for children under 5 years of age. The mean intake rate was 19.6 g/d and the 95th
11 percentile was approximately 70 g/d.
12 The authors noted that some non-response bias may have occurred in the survey since
13 respondents were more likely to live near the reservation and were more likely to be female than
14 non-respondents. In addition, they hypothesized that non fish consumers may have been more
15 likely to be non-respondents than fish consumers since non consumers may have thought their
Jfel 6 contribution to the survey would be meaningless; if such were the case, this study would
17 overestimate the mean intake rate. It was also noted that the timing of the survey, which was
18 conducted during low fish consumption months, may have led to underestimation of actual fish
19 consumption; the authors conjectured that an individual may report higher annual consumption if
20 interviewed during a relatively high consumption month and lower annual consumption if
21 interviewed during a relatively low consumption month. Finally, with respect to children's
22 intake, it was observed that some of the respondents provided the same information for their
23 children as for themselves, thereby the reliability of some of these data is questioned.
24 Although the authors have noted these limitations, this study-does present information on
25 fish consumption patterns and habits for a Native American subpopulation. It should be noted
26 that the number of surveys that address subsistence subpopulations is very limited.
27
28 3.4 FAT INTAKE
29 Cresenta et al. (1988), Nicklas (1993), and Frank et al. (1986) analyzed dietary fat intake
jO data as part of the Bogalusa heart study. The Bogalusa study "is an epidemiologic investigation
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1 of cardiovascular risk-factor variables and environmental determinants in a population that began
2 20 years ago" (Nicklas, 1995). The Bogalusa study has collected dietary data on subjects
3 residing in Bogalusa, Louisiana, since 1973. Among other things, the study collected fat intake
4 data for children, adolescents, and young adults. Researchers have examined various cohorts of
5 subjects, including (1) six cohorts of 10-year olds, (2) two cohorts of 13-year olds, (3) one cohort
6 of subjects from 6 months to 4 years of age, and (4) one cohort of subjects from 10 to 17 years of
7 age (Nicklas, 1995). In order to collect the data, interviewers used the 24-hour dietary recall
8 method. According to Nicklas (1995), "the diets of children in the Bogalusa study are similar to
9 those reported in national studies of children." Thus, these data are useful in evaluating the
10 variability of fat intake among the general population for the purposes of evaluating variability in
11 exposure for dioxin-like compounds among this group. Data for 6-month old to 17-year old
12 individuals collected during 1973 to 1982 are presented in Tables 3-15 and 3-16 (Frank et al.,
13 1986). Data are presented for total fats, animal fats, vegetable fats, and fish fats in units of g/day
14 and g/kg/day, respectively.
15 Total fat intake and intake of individual fat products was also estimated by EPA/NCEA
16 using data from the 1994/96 CSFII. It should be noted that the fat intake rates presented here
17 include all forms of fats (i.e., added fats such as butter and vegetable oil as well as fats consumed
18 in meats and fish).
19 The Center for Disease Control (CDC) (1994) used data from NHANES III to calculate
j20 daily total food energy intake (TFEI), total dietary fat intake, and saturated fat intake for the U.S.
21 population during 1988 to 1991. The sample population comprised 20,277 individuals ages
22 2 months and above, of which 14,001 respondents (73 percent response rate) provided dietary
23 information based on a 24-hour recall. TFEI was defined as "al! nutrients (i.e., protein, fat,
24 carbohydrate, and alcohol) derived from consumption of foods and beverages (excluding plain
i
25 drinking water) measured in kilocalories (kcal)." Total dietary fat intake was defined as "all fat
26 (i.e., saturated and unsaturated) derived from consumption of foods and beverages measured in
27 grams."
28 CDC (1994) estimated and provided data on the mean daily TFEI and the mean
29 percentages of TFEI from total dietary fat grouped by age and gender. The overall mean daily
30 TFEI was 2,095 kcal for the total population and 34 percent (or 82 g) of their TFEI was from
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1 total dietary fat (CDC, 1994). Based on this information, the mean daily fat intake was
2 calculated for the various age groups and genders (see Appendix 3C for detailed calculation).
3 Table 3-17 presents the grams of fat per day obtained from the daily consumption of foods and
4 beverages grouped by age and gender for the U.S. population, based on this calculation.
5
6 3.5 TOTAL DIETARY INTAKE AND CONTRIBUTIONS TO DIETARY
7 INTAKE
8 U.S. EPA (2000) -1994-96 CSFII Total Diet Analysis. Using data from the 1994-1996
9 CSFII, total dietary intake was also evaluated. Total dietary intake was defined as intake of the
10 sum of all foods in the following major food groups: dairy, eggs, meats, fish, fats, grains,
11 vegetables, and fruits, using the same foods codes as those described in Appendix 3B, and the
12 same method for allocation of mixtures as described in Appendix 3 A. Beverages; sugar, candy,
13 and sweets, and nuts and nut products were not included. Distributions of total dietary intake
14 were generated, as described previously, for various age groups. Means, standard errors, and
15 percentiles of total dietary intake were estimated in units of g/kg/day, as well as g/day.
16 To evaluate variability in the contributions of the major food groups to total dietary
"17 intake, individuals were ranked from lowest to highest, based on total dietary intake. Three
18 subsets of individuals were defined, as follows: a group at the low end of the distribution of total
19 intake (i.e., below the 10lh percentile of total intake), a central group (i.e., the 45Ih to 55th
20 percentile of total intake), and a group at the high end of the distribution of total intake (i.e.,
21 above the 90th percentile of total intake). Mean total dietary intake, mean intake of each of the
22 major food groups, and.the fraction of total dietary intake that each of these food groups
23 represents was calculated for each of the three populations (i.e., individuals with low-end,
24 central, and high-end total dietary intake). A similar analysis was conducted to estimate the
25 contribution of the major food groups to total dietary intake for individuals at the low-end,
26 central, and high-end of the distribution of total meat intake, total dairy intake, total meat and
27 dairy intake, total fish intake, and fruit and vegetable intake. For example, to evaluate the
28 variability in the diets of individuals at the low-end, central range, and high-end of the
29 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 dietary
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1
2
"*
4
5
6
7
g
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
intake, intake of the major food groups, and the fraction of total dietary intake represented by
each of the major food groups were tabulated. This analysis was conducted for the following age
groups of the population: <1 year, 1-2 years, 3-5 years, 6-13 years, and 12-19 years. The data
were tabulated in units of g/kg/day and g/day.
Distributions of total dietary intake are presented in Table 3-18 in units of g/day and
g/kg/day. Tables 3-19 and 3-20 compare total dietary intake to intake of the various major food
groups for the various age groups in units of g/day and g/kg/day. Tables 3-21 through 3-26
present the contributions of the major food groups to total dietary intake for individuals (in the
various age groups) at the low-end, central, and high-end of the distribution of total dietary
intake, total meat intake, total meat and dairy intake, total fish intake, total fruit and vegetable
intake, and total dairy intake in units of g/day and g/kg/day.
3.6 INTAKE OF HOME-PRODUCED FOODS
U.S. EPA (1997) - EPA 's Analysis of the 1987/88 NFCS to Estimate Homegrown Intake
Rates. NFCS data were used to generate intake rates for home produced foods. USDA conducts
the NFCS every 10 years to analyze the food consumption behavior and dietary status of
Americans (USDA, 1992). The most recent NFCS was conducted in 1987-88 (USDA, 1987-88).
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 1987-88 survey was approximately 4,300 households
(over 10,000 individuals). This is a decrease over the previous survey conducted in 1977-78
which sampled approximately 15,000 households (over 36,000 individuals) (USDA, 1994). The
sample size was lower in the 1987-88 survey as a result of budgetary constraints and low
response rate (i.e.. 38 percent for the household survey and 31 percent for the individual survey)
(USDA, 1993). However, NFCS data from 1987-88 were used to generate homegrown intake
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rates because they were the most recent data available and were believed to be more reflective of
current eating patterns among the U.S. population.
The USDA data were adjusted by applying the sample weights calculated by USDA to
4 the data set prior to analysis. The USDA sample weights were designed to "adjust for survey
5 non-response and other vagaries of the sample selection process" (USDA, 1987-88). Also, the
6 USDA weights are calculated "so that the weighted sample total equals the known population
7 total, in thousands, for several characteristics thought to be correlated with eating behavior"
8 (USDA, 1987-88).
9 For the purposes of this study, home produced foods were defined as homegrown fruits
10 and vegetables, meat and dairy products derived from consumer-raised livestock or game meat,
11 and home caught fish. The food items/groups selected for analysis included major food groups
12 such as total fruits, total vegetables, total meats, total dairy, total fish and shellfish. Individual
13 food items for which >30 households reported eating the home produced form of the item, fruits
14 and vegetables categorized as exposed, protected, and roots, and various USDA fruit and ,
15 vegetable subcategories (i.e., dark green vegetables, citrus fruits, etc.) were also evaluated for the
general population (U.S. EPA, 1997). However, age-specific data for children are not presented"
17 here because of the small numbers of observations for children eating individual homegrown
18 foods in the data set. Food items/groups were identified in the NFCS data base according to
19 NFCS-defined food codes. Appendix 3D presents the codes used to determine the various food
20 groups.
21 Although the individual intake component of the NFCS gives the best measure of the
22 amount of each food group eaten by each individual in the household, it could not be used
23 directly to measure consumption of home produced food because the individual component does
24 not identify the source of the food item (i.e., as home produced or not). Therefore, an analytical
25 method which incorporated data from both the household and individual survey components was
26 developed to estimate individual home produced food intake. The USDA household data were
27 used to determine (1) the amount of each home produced food item used during a week by
28 household members and (2) the number of meals eaten in the household by each household
29 member during a week. Note that the household survey reports the total amount of each food
item used in the household (whether by guests or household members); the amount used by
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1
2
3
4
' 5
6
7
8
9
10
11
12
13
14
household members was derived by multiplying the total amount used in the household by the
proportion of all meals served in the household (during the survey week) that were consumed by
household members.
The individual survey data were used to generate average sex- and age-specific serving
sizes for each food item. The age categories used in the analysis were as follows: 1 to 2 years;
3 to 5 years; 6 to 11 years; 12 to 19 years (intake rates were not calculated for children under 1;
the rationale for this is discussed below). These serving sizes were used during subsequent
analyses to generate homegrown food intake rates for individual household members. Assuming
that the proportion of the household quantity of each homegrown 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 SAS programming in which the following general equation was used:
w = w.
(Eqn.3-1)
15 where:
16 Wj = Homegrown amount of food item/group attributed to member i during the week
17 (g/week);
18 Wf = Total quantity of homegrown food item/group used by the family members
19 (g/week);
20 Hii = Number of meals of household food consumed by member i during the week
21 (meals/week); and
22 q, = Serving size for an individual within the age and sex category of the member
23 (g/meal).
24
25 Daily intake of a homegrown food item/group was determined by dividing the weekly value (w;)
26 by seven. Intake rates were indexed to the self-reported body weight of the survey respondent
27 and reported in units of g/kg-day. Intake rates were not calculated for children under one year of
28 age because their diet differs markedly from that of other household members, and thus the
29 assumption that all household members share all foods would be invalid for this age group.
June 2000
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DRAFT-DO NOT QUOTE OR CITE
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1 For the major food groups (fruits, vegetables, meats, dairy, and fish) consumed by at least
12 30 households, distributions of home produced intake among consumers were generated by age
3 group. Consumers were defined as members of survey households who reported consumption of
4 the food item/group of interest during the one week survey period. Finally, the percentages of
5 total intake of the food items/groups consumed within survey households that can be attributed to
6 home production were tabulated. The percentage of intake that was homegrown was calculated
7 as the ratio of total intake of the homegrown food item/group by the survey population to the
8 total intake of all forms of the food by the survey population. As discussed previously,
9 percentiles of average daily intake derived from short time intervals (e.g., 7 days) will not, in
10 general, be reflective of long term patterns.
11 The intake data presented here for consumers of home produced foods and the total
12 number of individuals surveyed may be used to calculate the mean and the percentiles of the
13 distribution of home produced food consumption in the overall population (consumers and non-
14 consumers) as follows:
15 Assuming that IRp is the homegrown intake rate of food item/group at the p'h percentile
L6 and Nc is the weighted number of individuals consuming the homegrown food item, and NT is the
17 weighted total number of individuals surveyed, then NT - Nc is the weighted number of
18 individuals who reported zero consumption of the food item. In addition, there are (p/100 x Nc)
19 individuals below the pth percentile. Therefore, the percentile that corresponds to a particular
20 intake rate (IRP) for the overall distribution of homegrown food consumption (including
21 consumers and nonconsumers) can be obtained by:
22
NC + (NT-NC))
P (Eqn-3'2)
overall ~ 1UU A N
24
25 Table 3-27 displays the weighted numbers NT, as well as the unweighted total survey
26 sample sizes, for each subcategory and overall. It should be noted that the total unweighted
number of observations in Table 3-27 (9,852) is somewhat lower than the number of
June 2000 3-21 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
observations reported by USDA because this study only used observations for family members
for which age and body weight were specified.
Table 3-28 present homegrown intake rates for fruits, vegetables, meats, and fish,
respectively. 'As mentioned above, the intake rates derived in this section are based on the
amount of household food consumption. As measured by the NFCS, the amount of food
"consumed" by the household is a measure of consumption in an economic sense, i.e., a measure
of the weight of food brought into the household that has been consumed (used up) in some
manner. In addition to food being consumed by persons, food may be used up by spoiling, by
being discarded (e.g., inedible parts), through cooking processes, etc.
USDA estimated preparation losses for various foods (USDA, 1975). For meats, a net
cooking loss, which includes dripping and volatile losses, and a net post cooking loss, which
involves losses from cutting; bones, excess fat, scraps and juices, were derived for a variety of
cuts and cooking methods. For each meat type (e.g., beef) EPA has averaged these losses across
all cuts and cooking methods to obtain a mean net cooking loss and a mean net post cooking loss.
Mean values for all meats and fish are provided in Table 3-29. 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 3-29.
The following formula can be used to convert the homegrown intake rates tabulated here
to rates reflecting actual consumption:
(Eqn. 3-3)
where IA is the adjusted intake rate, I is the tabulated intake rate, L, is the cooking or preparation
loss, and L2 is the post-cooking loss. For fruits, corrections based on postcooking 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.
June 2000
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DRAFT-DO NOT QUOTE OR CITE
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1 In calculating ingestion exposure, assessors should use consistent forms in combining
2 intake rates with contaminant concentrations, as previously discussed.
*>
4 3.7 SERVING SIZE STUDY BASED ON THE USDA NFCS
5 Pao el al. (1982) - Foods Commonly Eaten by Individuals - Using data gathered in the
6 1977-78 USDA NFCS, Pao et al. (1982) calculated distributions for the quantities of individual
7 fruit and vegetables consumed per eating occasion by members of the U.S. population (i.e.,
8 serving sizes), over a 3-day period. The data were collected during NFCS home interviews of
9 37,874 respondents, who were asked to recall food intake for the day preceding the interview,
10 and record food intake the day of the interview and the day after the interview.
11 Serving size data are presented on an as consumed (g/day) basis in Table 3-30 for various
12 age groups of the population. Only the mean and standard deviation serving size data and
13 percent of the population consuming the food during the 3-day survey period are presented in
14 this handbook. Percentiles of serving sizes of the foods consumed by these age groups of the
15 U.S. population can be found in Pao et al. (1982).
\ 6 The advantages of using these data are that they were derived from the USDA NFCS and
17 are representative of the U.S. population. This data set provides serving sizes for a number of
18 commonly eaten foods, but the list of foods is limited and does not account for fruits and
19 vegetables included in complex food dishes. Also, these data represent the quantity of foods
20 consumed per eating occasion. Although these estimates are based on USDA NFCS 1977-78
21 data, serving size data have been collected but not published for the more recent USDA surveys.
22 These estimates may be useful for assessing acute exposures to contaminants in specific foods, or
23 other assessments where the amount consumed per eating occasion is necessary. However, it
24 should be noted that serving sizes may have changed since the data were collected in 1977-78.
25
26 3.8 CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE
27
RATES
28 As noted previously, intake rates may be reported in terms of units as consumed or units
29 of dry weight. 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
June 2000 3-23 DRAFT-DO NOT QUOTE OR CITE
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1
2
*>
4
5
6
7
S
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
(i.e., if the unit of food consumption is grams dry weight/day, then the unit for the amount of
pollutant in the food should be grams dry weight).
If necessary, as consumed intake rates may be converted to dry weight intake
rates using
the moisture content percentages presented in Table 3-31 and Table 3-32 and the following
equation:
IRdw= IRac*[(100-W)/100]
"Dry weight" intake rates may be converted to "as consumed" rates by using:
IRac= IRdwfllOO-WyiOO]
where:
IRdw = dry weight intake rate;
IRac - as consumed intake rate; and
W = percent water content.
3.9 FAT CONTENT OF MEAT AND DAIRY PRODUCTS
(Eqn. 3-4)
(Eqn. 3-5)
In some cases, the residue levels of contaminants in meat and dairy products 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 meat or dairy product of interest. Alternately, residue levels for the
"as
consumed" portions of these products may be estimated by multiplying the levels based on fat by
the fraction of fat per product as follows:
26
residue level residue level
g-fat
g-product
g-fat
g-product
(Eqn. 3-6)
27
June 2000
3-24
DRAFT-DO NOT QUOTE OR CITE
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1 The resulting residue levels may then be used in conjunction with "as consumed" consumption
2 rates. The percentages of lipid fat in meat and dairy products have been reported in various
3 publications. USDA's Agricultural Handbook Number 8 (USDA, 1979-1986) provides
4 composition data for agricultural products. It includes a listing of the total saturated,
5 monounsaturated, and polyunsaturated fats for various meat and dairy items. Table 3-33 presents
6 the total fat content for selected meat and dairy products taken from Handbook Number 8. The
7 total percent fat content is based on the sum of saturated, monounsaturated, and polyunsaturated
8 fats.
9 The .National Livestock and Meat Board (NLMB) (1993) used data from Agricultural
10 Handbook Number 8 to estimate total fat content in grams, based on a 3-ounce (85.05 g) cooked
11 . serving size, and the corresponding percent fat content values for several categories of meats
12 (Table 3-34). NLMB (1993) also reported that 0.17 grams of fat are consumed per gram of meat
13 (i.e., beef, pork, Iamb, veal, game, processed meats, and variety meats) (17 percent) and 0.08
14 grams of fat are consumed per gram of poultry (8 percent).
15
,16 3.10 RECOMMENDATIONS
17 The 1994-96 CSFII data described in this section were used in selecting recommended
18 intake rates for most food groups for general population children. For fish intake among general
19 population children, the 1989-91 CSFII analyses were used to recommend intake rates. For
20 recreational fish intake and intake among Native American populations, the data for children are
21 limited. Fat intake data are also limited. The studies that address these populations should be
22 used in exposure assessments where these populations are of interest (see Tables 3-13 and 3-17).
23 Table 3-35 presents a summary of the recommended values for food intake and Table 3-36
24 presents the confidence ratings for the food intake (including fish) recommendations for general
25 population children. Table 3-37 present the confidence ratings for fish intake recommendations
26 for the freshwater recreational population and Table 3-38 for Native American subsistence
27 populations. Per capita intake rates for specific food items, on a g/kg-day basis, may be obtained
28 from Table 3-3. Percentiles of the per capita intake rate distributions for the major food groups
29 in the general population are presented in Table 3-2. It is important to note that these
s
|30 distributions are based on data collected over a 2-day period and may not necessarily reflect the
June 2000 3-25 DRAFT-DO NOT QUOTE OR CITE
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1 long-term distribution of average daily intake rates. However, for these broad categories of food,
2 because they are eaten on a daily basis throughout the year with minimal seasonally, the short
3 term distribution may be a reasonable approximation of the long-term distribution, although it
4 will display somewhat increased variability. This implies that the upper percentiles shown here
5 will tend to overestimate the corresponding percentiles of the true long-term distribution.
June 2000
3-26
DRAFT-DO NOT QUOTE OR CITE
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1 3.11 REFERENCES FOR CHAPTER 3
2
3 CDC. (1994) Dietary fat and total food-energy intake. Third National Health and Nutrition Examination Survey,
4 Phase 1, 1988-91. Morbidity and Mortality Weekly Report, February 25, 1994: 43(7)118-125.
5
6 Columbia River Inter-Tribal Fish Commission (CRITFC). (1994) A fish consumption survey of the Umatilla, Nez
7 Perce, Yakama and Warm Springs tribes of the Columbia River Basin. Technical Report 94-3. Portland, OR:
8 CRIFTC.
9
10 Cresanta, J.L.; Farris, R.P.; Croft, J.B.; Frank, G.C.; Berenson, G.S. (1988) Trends in fatty acid intakes of 10-year-
11 old children, 1973-1982. Journal of American Dietetic Association. 88:178-184.
12
13 Frank,.G.C.; Webber, L.S.; Farris, R.P.; Berenson, G.S. (1986) Dietary databook: quantifying dietary intakes of
14 infants, children, and adolescents, the Bogalusa heart study, 1973-1983. National Research and Demonstration
15 Center - Arteriosclerosis, Louisiana State University Medical Center, New Orleans, Louisiana.
16
17 Goldman, L. (1995) Children - unique and vulnerable. Environmental risks facing children and recommendations
18 for response. Environmental Health Perspectives. 103(6): 13-17.
19
20 Javttz, H. (1980) Seafood consumption data analysis. SRI International. Final report prepared for EPA Office of
21 Water Regulations and Standards. EPA Contract 68-01-3887.
22
23 National Livestock and Meat Board (NLMB). (1993) Eating in America today: A dietary pattern and intake
24 report. National Livestock and Meat Board. Chicago, IL.
25
26 Nicklas, T.A. (1995) Dietary studies of children: The Bogalusa Heart Study experience. Journal of the American
27 Dietetic Association. 95:1127-1133.
8
29 Nicklas, T.A.; Webber, L.S.; Srinivasan, S.R.; Berenson, G.S. (1993) Secular trends in dietary intakes and
30 cardiovascular risk factors in 10-y-old children: the Bogalusa heart study (1973-1988). American Journal of
31 Clinical Nutrition. 57:930-937.
32
33 Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. (1982) Foods commonly eaten by individuals: amount per
34 day and per eating occasion. U.S. Department of Agriculture. Home Economics Report No. 44.
35
36 Ruffle, B.; Burmaster, D.; Anderson, P.; Gordon, D. (1994) Lognormal distributions for fish consumption by the
37 general U.S. population. Risk Analysis 14(4):395-404.
38
39 , Rupp, £.; Miler, F.L.; Baes, C.F. III. (1980) Some results of recent surveys offish and shellfish consumption by
40 age and region of U.S. residents. Health Physics 39:165-175.
41
42 SAS Institute, Inc. (1990) SAS Procedures Guide, Version 6, Third Edition, Gary, NC: SAS Institute, Inc., 1990,
43 705 pp.
44
45 Tsang. A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
46 Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed
47 Martin, Contract No. 68-W6-001, Delivery Order No. 13.
48
49 USDA. (1975) Food yields summarized by different stages of preparation. Agricultural Handbook No. 102.
50 Washington. DC: U.S. Department of Agriculture, Agriculture Research Service.
51
USDA. (1979-1986) Agricultural Handbook No. 8. United States Department of Agriculture.
June 2000 3-27 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
$
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
USDA. (1987-88) Dataset: Nationwide Food Consumption Survey 1987/88 Household Food Use. U.S.
Department of Agriculture. Washington, D.C. 1987/88 NFCS Database.
USDA. (1992) Changes in food consumption and expenditures in American households during the 1980's. U.S.
Department of Agriculture. Washington, D.C. Statistical Bulletin No. 849.
USDA. (1993) Food and nutrient intakes by individuals in the United States, 1 Day, 1987-88. Nationwide Food
Consumption Survey 1987-88, NFCS Report No. 87-1-1.
USDA. (1994) Food consumption and dietary levels of households in the United States, 1987-88. U.S.
Department of Agriculture, Agricultural Research Service. Report No. 87-H-1.
USDA. (1995) Food and nutrient intakes fay individuals in the United States, I day, 1989-91. U.S. Department of
Agriculture, Agricultural Research Service. NFS Report No. 91-2.
USDA. (1998) 1994-96 Continuing Survey of Food Intakes by Individuals (CSFII) and 1994-96 Diet and Health
Knowledge Survey (DKHS). CD-ROM. U.S. Department of Agriculture, Agricultural Research Service.
Available from the National Technical Information Service, Springfield, VA.
U.S. EPA. (1996) Daily average per capita fish consumption estimates based on the combined USDA 1989, 1990
and 1991 continuing survey of food intakes by individuals (CSFII) 1989-91 data. Volumes I and II.
Preliminary Draft Report. Washington, DC: Office of Water.
U.S. EPA. (1997) Exposure Factors Handbook. Washington, DC: Office of Research and Development.
EPA/600/P-95/002F.
U.S. EPA. (2000) CSFII analysis of food intake. Report prepared for U.S. EPA. Office of Research and
Development, National Center for Environmental Assessment by Versar, Inc.
West, P.C.; Fly, M.J.; Marans, R.; Larkin, 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.
June 2000
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1
»3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Table 3-1. Weighted and Unweighted Number of Observations, 1994/96 CSFII Analysis
Population
Group
Total
Age Group (years)
<01
01-02
03-05
06-11
12-19
20-39
40-69
70+
Season
Fall
Spring
Summer
Winter
Urbanization
Central City
Nonmetropolitan
Suburban
Race
Asian
Black
Native American
Other/NA
White
Region
Midwest
Northeast
South
West
Weighted
Number of
Observations
261,897,260
3,772,296
8,270,523
12,376,836
23,408,882
29,657,098
81,672,622
81,480,145
21,258,858
65,474,320
65,474,321
65,474,320
65,474,299
83,904,160
55,263,514
122,729,586
7,764,799
33,466,094
1,669,637
14,321,336
204,675,394
61,512,403
51,416,379
91,294,341
57.674.137
Unweighted
Number of
Observations
15,303
359
1,356
1,435
1,432
1,398
2,992
4,921
1,410
3,653
4,015
4,143
3,492
-
4,600
3,778
6,925
387
1,963
115
972
,11,866
3,658
2,737
5,474
3.434
June 2000
5-29
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1
2
3
4
5
6
7
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
45
46
47
48
49
50
Table 3-2.
Population Percent
Group Consuming
Age (years)
<01 56.8%
1-2 85.5%
3-5 79.0%
6-11 71.2%
12-19 60.7%
Age (years)
<0! 50.1%
1-2 . 95.4%
3-5 92.7%
6-11 93.2%
12-19 97.9%
Age (years)
< 01 64.9%
1-2 95.6%
3-5 93.1%
6-1 1 93.4%
12-19 98.2%
Age (years)
<01 32.3%
1-2 94.0%
3-5 92.2%
6-1 1 92.4%
12-19 97.3%
Age (years)
< 01 20.9%
1-2 58-2%
3-5 56-4%
6-11 57.5%
12-19 62.9%
Age (years)
<01 .83.6%
1-2 95.7%
3-5 92.9%
6-1 1 93.3%
12-19 96.9%
Note: SE = Standard error
MEAN
13.18
19.31
11.02
5.393
2.771
6.902
9.528
7.295
5.337
4.034
4.124
11.21
10.29
7.2
4.401
1.132
4.422
4.144
2.919
2.158
0.108
0.368
0.316
0.259
0.204
111.4
37.48
20.91
13.92
6.119
Per Capita Intake of the Major Food Groups (g/kg-day as consumed)
SE
1.106
0.521
0.341
0.2
0.133
0.721
0.213
0.159
0.118
0.085
0.416
0.202
0.197
0.122
0.08
0.198
0.094
0.08
0.06
0.046
0.047
0.037
0.03
0.025
0.017
4.855
0.779
0.402
0.276
0.16
PI P5
0 0
0 0
0 0
0 0
0 0
t
0 0
0 0.471
0 0
0 0
0 0.633
0 0
0 1.686
0 0
0 0
0 1.13
0 0
0 0
0 0
0 0
0 0.266
0 0
0 0
0 0
0 0
0 0
0 0
0 0.412
0 0
0 0
0 0.168
P!0 P25
Fruia
0 0
0 6.351
0 2.273
0 0
0 0
Vegetables
0 0
1.929 4.534
1.348 3.411
1.12 2.48
1.121 2.14
Grains
0 0
3.594 6.434
3.674 6.292
2.452 4.285
1.543 2.452
Meals
0 0
0.759 1.909
0.768 2.125
0.523 1.418
0.527 1.106
Fish
0 0
0 0
o • o
0 0
0 0
Dairy Products
2.522 63.89
6.677 17.75
3.473 J0.18
2.167 6.438 '
0.413 1.832
P50
7.559
15.52
8.102
3.351
1.371
2.337
8.013
6.231
4.334
3.404
1.575
9.807
9.177
6.656
3.788
0
3.845
3.814
2.52
1.947
0
0.08
0.069
0.058
0.055
102.2
31.76
18.73
12.35
4.467
P75
22.67
27.45
16.34
7.874
4.116
12.23
22.58
9.69
7.103
5.145
5.438
14.27
13.13
9.413
5.541
1.383
6.195
5.624
3.996
2.835
0
0.286
0.245
0.178
0.172
158.6
51.44
29.16
19.25
8.803
P90
35.69
41.62
26.44
13.63
7.978
17,86
18.72
13.93
10.44
7.399
12.97
21.04
17.77
12.92
7.899
3.87
8.869
7.847
5.555
3.93
0.325
0.783
0.661
0.479
0.417
197.8
73.89
41.24
27.34
13.49
P95
41.18
53.9
32.68
17.95
10.97
24.18
23.28
18.27
13.54
9.346
20.24
24.71
21.07
15.55
9.702
5.853
10.16
9.436
6.802
4.865
0.527
1.791
1.736
1.346
1.1
235.3
90.15
48.75
33.46
17.79
P99
63.73
77.26
52.99
28.45
16.64
36.28
33.46
28.99
21.21
!4.68
26.61
34.67
33.64
19.89
14.08
10.59
14.66
13.1
10.23
7.459
1.562
4.687
4.567
4.234
2.499
318.3
132.8
66.16
43.43
27.84
P100
110.2
125.3
105.2
44.57
32.23
102.6
83.29
45.54
52.27
42.43
40.13
47.99
120.9
36.3
34.57
12.37
24.44
20.74
17.6
26.75 '
4.685
14.42
9.553
6.686
5.354
576.3
182.8
89.72
80.78
38.01
P = Percemile of the distribution
Source: Based on EPA's analyses of the
1994-96 CSFII
June 2000
3-30
DRAFT-DO NOT QUOTE OR CITE
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-------
Table 3-4. Per Capita Intake of USDA Categories of Vegetables and Fruits (g/kg-day as consumed)
*
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
30
31
32
33
34
35
36
37
38
39
40
41
42
Population Percent
Group Consuming
MEAN
SE
PI
P5
P10 P25
P50
P75 P90
P95
P99 P100
Dark Green Vegetables
Age (years)
<01
1-2
3-5
6-11
12-19
1.7%
12.5%
10.9%
9.9%
9.4%
0.045
0.328
0.197
0.154
0.124
0.219
0.098
0.063
0.054
0.041
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0 0.845
0 0.224
0 0.162
0 0.15
0
2.315
1.488
1.042
0.935
0.678 9.77
6.513 20.94
4.127 12.72
3.655 6.761
2.792 4.333
Deep Yellow Vegetables
Age (years)
-------
1
2
i
5
6
7
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
** *>
j^
34
35
36
37
38
39
40
41
42
43
44
45
Table 3-5, Per .Capita Intake of Exposed/Protected Fruit and Vegetable Categories (g/kg-day as consumed)
Population
Grouo
Age (years)
<01
01-02
03-05
06-11
12-19
Age (years)
<0l
01-02
03-05
06-11
12-19
Age (years)
<01
1-2
3-5
6-11
12-19
Age (years)
<01
01-02
03-05
06-11
12-19
Age (years)
<01
01-02
03-05
06-11
12-19
NOTE:
Percent
Consuming
49.9%
68.6%
60.7%
49.3%
31.9%
27.0%
62.1%
54.5%
49.0%
46.4%
18.1%
63.4%
68.2%
70.6%
76.4%
18.9%
41.4%
38.8%
38.7%
31.2%
-30.4%
68.2%
71.1%
73.7%
762%
Mean
10.02
10.9
5.637
2.i97
0.872
1.719
6.449
4.356
2.702
1.809
1.189
1.996
1.63
1.235
0.966
1.281
1.469
1.079
0.778
0.462
1.812
2.572
2.191
1.62
1.263
SE
0.995
0.469
0.277
0.136
0.087
0.392
0.309
0.223
0.165
0.124
0.371
0.114
0.083
0.058
0.041
0.371
0.125
0.09
0.065
0.055
0.355
0.134
0.091
0.063
0.053
PI
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
P5 P10 P25 P50
Exposed Fruits
000 4.449
000 5.695
000 2.717
000 0
000 0
Protected Fruits
*
00 0 0
000 3.59
0.0 0 2.062
000 0.165
000 0
Exposed Vegetables
00 0 0
000 0.591
000 0.674
000 0.601
0 0 0.055 0.53
Protected Vegetables
00 0 0 '
000 0
000 0
000 0
000 0
Root Vegetables
000 0
000 1.447
000 1.355
000 1.034
0 0 0.094 0.823
P75
16.53
15.68
8.096
3.075
1.07
1.957
9.186
6.721
3.817
2.612
0
2.678
2.241
1.58
1.338
0
1.863
1.402
1.042
0.437
2.307
3.562
3.215
2.315
1.747
P90
30.09
29.37
15.84
6.338
2.857
6.013
17.84
12.14
8.074
5.417
4.991
5.753
4.442
3-417
2.53
5.42
4.422
3.52
2.583
1.517
• 6.944
6.774
5.512
4.17!
3.015
P95
38.78
38.99
22.18
8.777
4.85
8.344
24.18
17.16
11.44
8.402
7.353
8.551
6.378
4.836
3.61
7.785
7.042
5.417
3.894
2.348
9.582
8.331
7.125
5.325
3.992
P99
58.46
65.81
34.98
17.55
8.787
16.61
39.03
27.9
19.81
15.43
14.65
14.87
12.79
8.102
5.767
11.9
14.16
10.3
7.496
5.766
15.59
16.78
14.06
9.492
7.66!
PI 00
69.61
101.3
77.08
32.2
14.91
30.25
113.4
66.54
31.71
27.02
19.04
45.03
25.07
19.6
13.02
23.1
27.81
17.99
26.51
21.55
32.92
83.29
32.05
20.59
22.47
SE = Standard error
P = Percentile of the distribution
Source: Based on EPA's analyses of the
1989-91
CSFH
March 2000
3-34
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-6. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - As Consumed
15
Age (years)
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
Sample
Size
1431
2891
1546
2151
2977
5042
Mean
(g/day)
1-58
4.28
2.17
6.14
1.88
5.17
90th %
(g/day)
1.44
10.90
0.99
18.19
1.31
13.88
95th %
(g/day)
99th %
(g/day)
Freshwater and Estuam
12.51
28.80
14.94
48.61
13.90
36.21
36.09
70.87
48.72
96.32
40.77
86.14
Marine
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
6.60
9.97
7.25
13.33
6.93
11.58
24.84
36.83
24.85
52.73
24.88
44.24
37.32
55.53
49.89
71.49
42.07
62.18
87.05
105.32
92.64
116.51
91.64
110.07
All Fish
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
8.19
14.25
9.42
19.46
8.82
16.74
32.28
47.13
34.85
68.60
32.S8
57.88
43.09
71.58
52.85
93.65
50.95
84.59
95.19
120.84
98.36
149.07
98.33
138.21
: Mean
(mg/ka-day)
w
67.12
66.22
73.93
75.35
70.59
70.58
90th %
(mg/kg-day)
57.30
174.96
28.10
230.13
53.24
197.11
95th %
(mg/ka-day)
460.16
451.04
723.93
577.84
556.34
502.26
99th %
(mg/kg-day)
1356.54
1188.16
1290.10
1132.23
1347.67
1167.57
256.90
159.79
230.25
165.92
243.3!
162.72
936.94
' 573.49
846.57
626.85
873.87 '
602.58
1545.15
873.73
150437
933.05
1522.52
893.82
3060.22
1700.21
2885.08
1472.98
3059.93
1576.09
324.02
226.01
304.17
241.27
313.90
233.30
1091.52
755.51
1172.17
867.70
1128,26
828.12
1690.99
1126.02
1575.43
1208.43
1679.91
1155.30
3982.60
2195.86
3393.84
1760.48
3419.49
2003.46
Source: U.S. EPA. 1996.
March 2000
3-35
DRAFT-DO NOT QUOTE OR CITE
-------
2
3
4
5
6
7
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
Table 3-7. Consumers Only Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - As Consumed
Aae (years)
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or tinder
15-44
Sample
Size
138
445
157
356
295
801
Mean
(g/day).
38.44
61.40
52.44
81.56
45.73
71.44
90th %
(g/day)
91.30
148.83
1 12.05
224.01
108.36
180.67
95th %
(g/day)
99th %
(g/day)
Freshwater and Estut
128.97
185.44
154.44
275
136.24
230.95
182.66
363.56
230.74
371
214.62
371.52
Marine
Females
14 or under
J5-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
315
774
348
565
663
1339
69.04
76.53
78.44
104.57
73.62
89.93
114.23
149.78
160.97
191.29
153.2
171.88
162.37
178.74
3
190.68
227.56
176.9
209.17
336.59
271.06
336.98
316.69
337.24
308.06
All Fish
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
378
952
429
702
807
1654
69.54
88.8
79.72
124.78
74.8
106.06
126.22
170.01
161.62
230.77
153.7
203.33
165.27
212.56
190
296.66
178.08
271.66
338.04
361.04
308.59
397.7
337.46
372.77
Mean
(mg/kg-day)
Tine
J 639.20
961.58
1798.24
1004.96
1721.99
983.19
90th %
(mg/kg-day)
3915.56
2578.81
3759.29
2744.61
3760.67
2616.63
95th %
(mg/kg-day)
6271.09
3403.75
3952.99
3348.86
4208.18
3360.85
99th % j
(mg/kg-day)
10! 13.24
6167.24
7907.38
4569.62
9789.49
5089.78
2591.57
1227.41
2471.15
1302.62
2532.95
1263.35
5074.80
2469.67
4852.33
2390.20
5068.69
2464.80
6504.67
3007.98
5860.72
2882.91
6376.47
2961.92
9970.44
4800.68
8495.57
3887.23
8749.02
4251.47
2683.51
1414.54
2568.93
1545.93
2624.35
1477.57
5299.68
2726.46
4714.97
2854.49
5020.14
2798.37
7160.73
3740.83
5818.08
3773.51
6904.83
3747.88
12473.65
6703.25
9350.89
5254.04
10384.82
5386.43
Source: U.S. EPA, 1996.
March 2000
3-36
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - Uncooked Fish Weight
Age (years)
Sample
Size
Mean
(S/day)
90th %
(g/day)
95th %
(a/day)
99th %
(g/day)
Mean
(mg/kg-day)
90th %
(mg/kg-day)
95th %
(mg/kg-day)
99th %
(mg/kg-day)
Freshwater and Estuarine
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
1.99
5.50
2.69
7.87
2.35
6.64
1.81
13.62
1.07
22.10
1.72
18.30
15.88
36.68
18.47
63.26
17.46
47.31
46.82
94.93
57.07
126.61
50.14
109.66
84.78
85.15
91.62
96.9!
88.26
90.77
70.75
202.83
38.98
281.17
66.00
250.26
599.06
584.79
868.97
740.91
717.37
631.31
1713.06
141 1.42
1642.60
1589.97
1688.55
1529.94
Marine
Females
1 4 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
8.61
12.84
9.40
17.11
9.02
14.88
31.23
46.66
31.32
66.06
31.52
55.99
49.75)
72.16)
65.37
93.32
56.35
80.70
104.26)
133.69
118.42
155.16
1 17.75
138.23
333.99
206.03
296.99
212.88
315.12
209.30
1 132.99
762.54
1089.46
800.79
1 123.28
780.16
1959.91
1137.58
1907.65
1191.75
1909.37
1174.69
3776.60
2174.21
3723.81
1890.42
3820.21
2019.59
All Fish
Females
1 4 or under
15-44
Males
1 4 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
10.60
18J5
12.09
24.98
11.36
21.51
41.10
62.21
45.59
87.15
43.00
75.15
56.16
93.13
68.18
122.29
65.34
109.57
130.78
155.75
127.20
197.15
130.41
175.73
418.76
291.18
388.61
309.78
403.38
300.06
1389.10
993.92
1476.31
1096.57
1442.72
1040.98
2341.90
1436.00
2038.58
1566.39
2191.90
1514.82
4985.96
2726.50
4294.12
2275.15
4425.27
2481.23
Source: U.S. EPA. 1996.
March 2000
3-37
DRAFT-DO NOT QUOTE OR CITE
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1
3
4
5
6
7
S
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
Table 3-9. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - Uncooked Fish Weight
Age (years)
Females
1 4 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
Sample
Size
138
445
157
356
295
801
315
774
348
565
663
1339
378
952
429
702
807
1654
Mean
-------
I Table 3-10. Mean and 95th Percentile offish Consumption (g/day) by Sex and Age'
2
3
4
5
Female
Male
Male & Female
Age (years)
0-9
10-19
0-9
10-19
0-9
10-19
Total Fish
Mean
9.0
6.3
11.2
6.2
10.1
95th Percentile
17.3
25.0
15.8
29.1
16.5
26.8
8
9 'The calculations in this table are based upon respondents who consumed fish in the month of the survey. These
10 respondents are estimated to represent 94.0% of the U.S. population.
11 Source: Javitz, 1980.
12
13
March 2000 3-39 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
5
6
7
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
45
46
Table 3-11. Best Fits of Lopormal Distributions-Using the Nonlinear Optimization (Nlo) Method
Shellfish
I*
0
{min SS)
Finfish (freshwater)
1*
a
(min SS)
Finfish (saltwater)
M
a
(min SS)
Teenagers
-0.183
1.092
1.19
0.578
0.822
23.51-
5.691
0.830
0.33
Children
0.854
0.730
16.06
-0-559
1.141
. 2.19
0.881
0.970
4.31
The following equations may be used with the appropriate y and o values to obtain an average Daily Consumption Rate (OCR).
in grams, and percentiles of the DCR distribution.
DCR90 = exp [« + z(0.90) • o]
DCR99 = exp [v * z(0.99) • o]
Source: Ruffle et al.. 1994.
Table 3-12. Number of Respondents Reporting Consumption of a Specified Number of Servings
of Seafood in 1 Month and Source of Seafood Eaten
Population
Group
Age (years)
1-4
5-11
12-17
Number of Servinss in a Month
Total N
102
166
137
1-2
55
72
68
3-5
29
57
54
6-10
12
21
9
11-19
2
6
2
20+
*
4
1
DK
4
6
3
Mostly
Purchased
94
153
129
Mostly
Caught
8
9
6
DK
*
4
2
Note: * = Missing data: DK = Don't know: % = Row percentage: N = Sample size: Refused = Respondent refused to answer.
Source: Tsang and Klepeis. 1996.
March 2000
3-40
DRAFT-DO NOT QUOTE OR CITE
-------
Grouc
Age Groups (years)
1-5
6 to 10
I to 20
All Fish
meals/week
0.463
0.49
0.407
Recreational
Fish
meals/week
0.223
0.278
0.229
n
12!
151
349
Total Fish
erams/dav
11.4
13.6
12.3
Recreational
Fish
erams/dav
5.63
7.94
7.27
Total Fish
grams/
ks/dav
0.737
0.481
0.219
Recreational
Fish grams/
ke/dav
0.369
0.276
0.123
1
2
3 Table 3-13. Mean Fish Intake Among Individuals Who Eat Fish and Reside
in Households With Recreational Fish Consumption
6
7
8
9
10
11
12
13
14
15 Source: U.S. EPA analysis using data from West et ah. 1989.
16
17
18
19
20
21
22
23 Table 3-14. Children's 5 and Under Fish Consumption Rates - Throuahout Year
24
25
26
27
,8
Number of Grams/Dav
0.0
0.4
0.8
1.6
2.4
3.2
4.1
4.9
6.5
8.1
9.7
12.2
13.0
, 16.2
19.4
20.3
24.3
32.4
48.6
64.8
72.9
81.0
97.2
162.0
Umveishted Cumulative Percent
21.1%
21.6%
22.2%
24.7%
25.3%
28.4%
32.0%
33.5%
35.6%
47.4%
48.5%
51.0%
51.5%
72.7%
73.2%
74.2%
76.3%
87.1%
91.2%
94.3%
96.4%
97.4%
98.5%
100%
0
31
32
33
34
35
36
37
38
39
40
41
42
43 '
44
45
46
47
48
49
50
51 N = I94
52 Unweighted Mean = 19.6 grams/day
53 Unweighted SE- 1.94
54 ' Source: CRITFC. 1994.
55
March 2000 3-41 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
45
46
47
Table 3-15. Fat Intake Among Children Based on Data from the Bogalusa Heart Study. 1973-1982 (g/day)
Age
(years)
N
Mean
St.
Dev.
P10
P25
P50
P75
P90
Minimum
Maximum
Total Fat Intake
6 Mo.
I
2
3
4
10
13
15
17
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 Mo.
1
2
3
4
10
13
15
17
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
1 0.0
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 Mo.
I
2
3
4
10
13
15
17
125
99
135
106
219
871
148
108
159
9.2
15.4
19.3
21.1
24.5
23.7
34.3
27.3
25.7
12.8
14.3
16.3
15.5
18.6
21.6
27.4
22.8
21.3
0.6
3.7
3.8
3.9
5.7
4.3
8.4
5.1
4.2
1.2
6.1
7.9
8.6
10.4
9.5
17.9
11.9
11.7
2.8
11.3
14.8
18.7
21.8
18.3
31.2
22.6
20.8
11.6
18.1
26.6
26.6
33.3
30.6
44.6
38.1
32.9
29.4
38.0
42.9
45.2
48.5
49.0
57.5
54.4
47.6
0.0
0.2
0.7
1.0
0.9
0.6
0.0.
0.7
0.0
53.2
70.2
96.6
70.4
109.0
203.7
238.3
132.2
141.5
Total Fish Fat Intake
6 Mo.
1
2
3
4
10
13
15
17
125
99
135
106
219
871
148
.108
159
0.046
0.047
0.036
0.100
2.255
0.292
0.269
0.431
0.465
0.130
0.233
0.229
0.591
31.05
1.452
2.151
1.467
2.010
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.140
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.900
1.900
1.900
4.500
459.2
19.2
25.4
9.500
15.3
Source: Frank et al.. 1986.
March 2000
3-42
DRAFT-DO NOT QUOTE OR CITE
_
-------
1
2
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
5
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
7
Table 3-16. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg/day)
Age
(years)
N
Mean
St.
Dev.
P10
P25
P50
P75
P90
Minimum
Maximum
Total Fat Intake
6 Mo.
I
2
3
4
10
13
15
17
125
99
132
106
218
86]
147
105
149
4.94
6.12
6.98
6.40
6.05
2.70
2.28
1.73
1.77
2.32
2.75
3.34
2.67
3.66
1.52
1.30
0.84
1.02
2.41
3.03
3.37
3.61
2.88
1.23
1.03
0.84
0.69
3.28
4.11
4.45
4.56
3.96
1.68
. 1.47
1.18
0.92
4.67
5.66 •
6.15
5.50
5.24
2.35
1.99
1.54
1.62
6.19
7.47
8.56
8.16
6.97
3.32
2.80
2.14
2.24
7.97
9.53
51.94
9.93
9.98
4.54
3.81
3.13
3.10
0.39
2.27
2.14
2.18
2.03
0.33
0.2!
0.15
0.16
13.16
16.38
18.69
16.73
38.21
13.86
10.19
4.73
6.23
Total Animal Fat
6 Mo.
1
2
3
4
10
13
15
17
125
99
132
106
218
861
147
105
149
2.43
3.78
3.99
3.50
3.12
1.56
1.19
0.95
1.04
2.13
2.12
2.31
2.01
2.05
1.16
0.86
0.62
0.77
0.08
1.70
1.73
1.56
1.26
0.55
0.40
0.32
0.26
0.60
2.37
2.29
2.07
1.73
0.84
0.59
0.54
0.51
2.03
3.39
3.36
3.13
2.64
1.28
0.94
0.81
0.83
3.74
4.90
5.22
4.18
4.04
1.92
1.59
1.25
1.38
5.47
6.48
6.69
6.05
5.38
2.83
2.28
1.90
1.97
0.00
0.00
0.67
0.90
0.39
0.00
0.08
0.01
0.05
8.99
13.64
13.40
13.14
15.43
10.79
5.19
3.07
4.15
Total Vegetable Fat Intake
6 Mo.
1
2
3
4
10
13
15
17
125
99
132
106
218
861
147
105
149
1.237
1.594
1.561
1.474
1.492
0.685
0.748
0.490
' 0.439
1.794
1.550
1.381
1.066
1.153
0.638
0.790
0.397
0.359
0.079
0.401
0.299
0.277
0.356
0.127
0.161
0.086
0.071
0.160
0.630
0.647
0.603
0.617
0.257
0.381
0.225
0.175
0.354
1.169
1.134
1.359
1.208
0.516
0.606
0.436
0.353
1.558
1.868
2.037
1.963
2.059
0.863
0.931
0.653
0.597
4.076
3.784
3.504
2.958
2.827
1.440
1.248
0.904
0.908
0.000
0.022
0.057
0.077
0.061
0.019
0.000
0.010
0.000
8.199
7.610
8.474
5.047
7.315
4.244
8.603
2.226
2.128
Total Fish Fat Intake
6 Mo.
1
2
3
4
10
13
15
17
125
99
132
106
218
861
147
105
149
0.006
0.005
0.003
0.007
0.148
0.009
0.005
0.008
0.008
0.018
0.026
0.018
0.042
2.034
0.047
0.036
0.028
0.033
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0-000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.021
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.127
0.219
0.160
0.341
30.03
0.625
0.405
0.189
0.234
Source: Frank et aL 1986.
March 2000
3-43
DRAFT-DO NOT QUOTE OR CITE
-------
i
2
3
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 3-17. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender1
Total'
Mates
Females
Age
(yrs)
2-1 1 (months)
1-2
3-5
6-11
12-16
16-19
N
871
1.231
1.647
1.745
711
785
Mean Fat Intake
(g/day)
37.52
49.96
60.39
74.17
85.19
100.50
N
439
601
744
868
338
308
Mean Fat intake
(g/day)
38.31
51.74
70.27
79.45
101.94
123.23
N
432
630
803
877
373
397
Mean Fat Intake
(g/day)
36.95
48.33
61.51
68.95
71.23
77.46
1 Total dietary fat intake includes all fat (i.e.. saturated and unsaturated) derived from consumption of foods and beverages
(excluding plain drinking water).
Source: Adapted from CDC. 1994.
March 2000
3-44
DRAFT-DO NOT QUOTE OR CITE
-------
I
a
O
s-
I
1
•A
1
«
—
o
—
«n
o
1
<'
1
o£
Population Pcrcen
Group Cotisum
i consumed]
R
1
O O O O O
U1 OO \S5 3 p
o o o c o
ij LJ tJ i i
?o o o o
4- 4- 4- 4-
00 00 r~; O; rn
O O O O O
si u a a t:
p o o p o
?j S OJ ^ m
p O O O O
4- -r 4- 4- 4-
— = 5 = =
? ? ? 5 §
oc oc r^ oe r-
01 IN — O r— CS
O U SJ
DC Cfi CO CD CO d
as consume)
(e/kg/dav.
o o o o c
4-4-4-4-4-
y u w u O
co o es M U W U
«$f v* O. O O
o o o o o
•*•-*• + + -*-
u u u u O
CM fl C*> O V>
o o o o o
4- 4- -r -f 4-
O p O O O
IflliS
C* U U ?J t> O
DC OO CD Cf) CA OJ
o
ei
O
e
b
a
o
o
u,
tf-
C U
II
II
u
C^ MM «
3 I
.2 °
§
O
o —
-------
I
O
I
.S
f
ra
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All Regions
Age (rears)
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June 2000
3-62
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30
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. 12
Weight Losses from Food Preparation
Mean Net Post Cooking, Paring, or Preparation Loss
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3-64
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-------
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions
10
11
12
13
14
li
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
k38
'39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
ft
65
66
Food
Fruit
Apples - dried
Apples83.93*
Apples -juice
Applesauce
Apricots
Apricots - dried
Bananas
Blackberries
Blueberries
Boysen berries
Cantaloupes - unspecified
Casabas
Cherries - sweet
Crabapples
Cranberries
Cranberries -juice cocktail
Currants (red and white)
Elderberries
'Grapefruit
Grapefruit -juice
Grapefruit - unspecified
Grapes - fresh
Grapes -juice
Grapes - raisins
Honeydew melons
Kiwi fruit
Kumquats
Lemons -juice
Lemons - peel
Lemons - pulp
Limes -juice
Limes - unspecified
Loganberries
Mulberries
Nectarines
Oranges - unspecified
Peaches
Pears - dried
Pears - fresh
Pineapple
Pineapple -juice
Plums
Quinces
Raspberries
Strawberries
Tangerine -juice
Tangerines
Watermelon
Vegetables
Alfalfa sprouts
Artichokes - globe & French
Moisture Content (Percent)
Raw Cooked
31.76
84.46"
86.35
31.09
74.26
85.64
84.61
85.90
89.78
91.00
80.76
78.94
86.54
85.00
83.95
79.80
90.89
90.00
90.89 .
81.30
84.12
15.42
89.66
83.05
81.70
90.73
81.60
88.98
90.21
88.26
84.61
87.68
86.28
86.75
87.66
26.69
8381
86.50
83.80
86.57
91.57
88.90
87.60
91.51
91. 14
84.38
78.01
84.13*
*with skin;
87.93
88.35*
86.62*
85.56*
86.59*
84.95*
90.10*
92.46*
92.52*
87.49*
64.44*
86.47*
83.51*
85.53
85.20
89.97*
87.00*
89.51*
86.50
Comments
sulfured; 'without added sugar
"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 tvpe (slip skin)
canned or bottled
seedless
•canned or bottled
'canned or bottled
all varieties
•canned juice pack
sulfured: "without added sugar
•canned juice pack
•canned juice pack
canned
•frozen unsweetened
•canned sweetened
•canned juice pack
boiled, drained
June 2000
3-67
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
8
9
10
11
12
4
6
7
8
9
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
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
Food
Asparagus
Bamboo shoots
Beans - dry
Beans - dry - blackeye peas (cowpeas)
Beans - dry - hyacinth (mature seeds)
Beans - dry - navy (pea)
Beans - dry - pinto
Beans - lima
Beans - snap - Italian - green - yellow
Beets
Beets - tops (greens)
Broccoli
Brussel sprouts
Cabbage - Chinese/celery.
including bok choy
Cabbage - red
Cabbage - savoy
Carrots
Cassava (yucca blanca)
Cauliflower
Celeriac
Celery
Chili peppers
Chives
Cole slaw
Collards
Corn - sweet
Cress - garden - field
Cress - garden
Cucumbers
Dandelion - greens
Eggplant
Endive
Garlic
Kale
Kohlrabi
Lambsquaner
Leeks
Lentils - whole
Lettuce - iceberg
Lettuce - romaine
Mung beans (sprouts)
Mushrooms
Mustard greens
Okra
Onions
Onions - dehydrated or dried
Parsley
Parsley roots
Parsnips
Peas (garden) - mature seeds - dry-
Peppers - sweet - garden
Potatoes (white) - peeled
Moisture Content (Percent)
Raw Cooked
92.25
91.00
66.80
87.87
79.15
81.30
70.24
90.27
87.32
92.15
90.69
86.00
95.32
91.55
91.00
87.79
68.51
92.26
88.00
94.70
87.74
92.00
81.50
93.90
75.96
89.40
89.40
96.05
85.60
91.93
93.79
58.58
84.46
91.00
84.30
83.00
67.34
95.89
94.91
90.40
91.81
90.80
89.58
90.82
3.93
88.31
88.31
79.53
88.89
92.77
78.96
92.04
95.92
71.80
86.90
76.02
93.39
67.17
89.22
90.90
89.13
90.20
87.32
95.55
93.60
92.00
87.38
92.50
92.30
95.00
92.50*
95.72
69.57
92.50
92.50
89.80
91.77
91.20
90.30
88.90
90.80
68.70
93.39
91.08
94.46
8991
92.24
77.72
88.91
94.70
7542
Comments
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
•canned solids &. liquid
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
stir-fried
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
baked
June 2000
3-68
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
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
6
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
Food
Potatoes (white) - whole
Pumpkin
Radishes - roots
Rhubarb
Rutabagas * unspecified
Salsify (oyster plant)
Shallots
Soybeans - sprouted seeds
Spinach
Squash - summer
Squash - winter
Sweetpotatoes (including yams)
Swiss chard
Tapioca - pear)
Taro - greens
Taro - root
Tomatoes -juice
Tomatoes - paste
Tomatoes - puree
Tomatoes - raw
Tomatoes - whole
Towelgourd
Turnips - roots
Turnips - tops
Water chestnuts
Yambean - tuber
Grains
Barley - pearled
Com - grain - endosperm
Corn - grain - bran
Millet
Oats
Rice - rough - white
Rye - rough
Rye - flour - medium
Sorghum (including milo)
Wheat • rough - hard while
Wheat - germ
Wheat - bran
Wheat - flour • whole grain
Meat
Beef
Beef liver
Chicken (light meat)
Chicken (dark meal)
Duck - domestic
Duck - wild
Goose - domestic
Ham - cured
Horse
Lamb
Lard
Pork
Rabbit - domestic
Turkev
Moisture Content (Percent)
Raw Cooked
83.29
91.60
94.84
93.61
89.66
77.00
79.80
69.05
91.58
93.68
88.71
72.84
92.66
10.99
85.66
70.64
93.95
93.95
93.85
91.87
91.07
73.46
89.15
10.09
10.37
3.71
3.71
8.22
11.62
10.95
9.85
9.20
9.57
11.12
9.89
10.27
71.60
68.99
74.86
75.99
73.77
75.51
68.30
66.92
72.63
73.42
0.00
70.00
72.8!
71.20
93.69
67.79
90.10
81.00
79.45
91.21
93.70
89.01
71.85
92.65
92.15
63.80
93.90
74.06
87.26
92.40
84.29
93.60
93.20
87.93
68.80
71.41
68.72
63,98
69.11
74.16
Comments
baked
boiled, drained
frozen, cooked with added sugar
boiled, drained
boiled, drained
steamed
boiled, drained
all varieties; boiled,
all varieties: baked
baked in skin
boiled, drained
dry
steamed
canned
canned
canned
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
crude
crude
crude
composite, trimmed.
without skin
without skin
roasted
composite, trimmed.
roasted
roasted
roasted
drained
retail cuts
retail cuts
June 2000
3-69
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
4 Food Moisture Content (Percent) Comments
§ Raw ' Cooked
8 Dairy Products
9 Eggs 74.57
10 Butter , 15.87
11 Cheese American pasteurized 39.16 regular
12 Cheddar 36.75
13 Swiss 37.21
14 Parmesan, hard 29.16
15 Parmesan, grated 17.66
16 Cream, whipping, heavy 57.71
17 Cottage, lowfat 79.31
18 Colby 38.20
19 Blue 42.41
20 Cream 53.75
21 Yogurt
22 Plain, lowfat 85.07
23 Plain, with fat 87.90 made from whole milk
24 Human milk - estimated from USDA Survey
25 Human 87.50 whole, mature, fluid
26 Skim 90.80
33 Lowfat 90.80 1%
30 Source: USDA. 1979-1986.
June 2000 3-70 DRAFT-DO NOT QUOTE OR CITE
-------
2
3
4
6
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
i$
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
Table 3-32. Percent Moisture Content for Selected Fish Species*
Species
Anchovy, European
Bass
Bass, Striped
Bluefish
Butterfish
Carp
Catfish
Cod, Atlantic
Cod. Pacific
Croaker, Atlantic
Dolphinfish. Mahimahi
Drum. Freshwater
Flatfish. Flounder and Sole
.
Grouper
Haddock
Halibut. Atlantic & Pacific
Halibut. Greenland
Herring. Atlantic & Turbot domestic species
Herring. Pacific
Mackerel. Atlantic
Mackerel. Jack
Mackerel. Kins
Mackerel. Pacific Si Jack
Mackerel. Spanish
Monkfish
Mullet. Striped
Ocean Perch. Atlantic
Perch. Mixed species
Pike. Northern
Pike. Wallcve
Moisture Content
(%)
F1NFISH
73.37
50.30
75.66
79.22
70.86
74.13
76.31
69.63
76.39
58.81
81.22
75.61
75.92
16.14
SI.28
78.03
59.76
77.55
77.33
79.06
73.16
79.22
73.36
79.92
74.25
71.48
77.92
71.69
70.27
72.05.
64.16
59.70
55.22
71.52
63.55
53.27
69.17
75.85
70.15
71.67
68.46
83.24
77,01
70.52
78.70
72.69
79.13
73.25
78.92
72.97
79.3 1
Comments
Raw
Canned in oil, drained solids
Freshwater, mixed species, raw
Raw
Raw
Raw
Raw
Cooked, dry heat
Channel, raw
Channel, cooked, breaded and fried
Atlantic, raw
Canned, solids and liquids
Cooked, dry heat
Dried and salted
Raw
Raw
Cooked, breaded and fried
Raw
Raw
Raw
Cooked, dry heat
Raw. mixed species
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Kippered
Pickled
Raw
Raw
Cooked, dry heat
Canned, drained solids
Raw-
Canned, drained solids
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
June 2000
3-71
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
8
9
Table 3-32. Percent Moisture Content for Selected Fish Species* (continued)
Soecies
Pollock, Alaska & Walleye
Pollock, Atlantic .
Rockfish, Pacific, mixed species
Roughy, Orange
Salmon, Atlantic
Salmon, Chinook
Salmon, Chum
Salmon, Coho
Salmon. Pink
Salmon. Red & Sockeye
Sardine. Atlantic
Sardine. Pacific
Sea Bass, mixed species
SeatrouL mixed species
Shad. American
Shark, mixed species
Snapper, mixed species
Sole. Spot
Sturgeon, mixed species
Sucker, white
Sunfish. Pumpkinseed
Swordfish
Trout, mixed species
Trout. Rainbow
Tuna, light meat
Tuna, white meat
Tuna. Bluefish. fresh
Turbcn. European
Whitefish. mixed species
Whiiing. mixed species
Ycllowtail. mixed species
Moisture Content
(%)
81.56
74.06
78.18
79.26
73.41
75.90
68.50
73.17
72.00
75.38
70.77
72.63
65.35
76.35
68.81
70.24
68.72
61.84
59.61
68.30
78.27
72.14
78.09
68.19
73.58
60.09
76.87
70.35
75.95
76.55
69.94
62.50
79.71
79.50
75.62
68.75
71.42
71.48
63.43
59.83
74.51
64.02
69.48
68.09
59.09
76.95
72.77
70.83
80.27
74.71
74.52
Comments
Raw
Cooked, dry heal
Raw
Raw (Mixed species)
Cooked, dry heat (mixed species)
Raw
Raw
Raw
Smoked
Raw
Canned, drained solids with bone
Raw
Cooked, moist heat
Raw
Canned, solids with bone and liquid
Raw
Canned, drained solids with bone
Cooked, dry heat
Canned in oil. drained solids with bone
Canned in tomato sauce, drained solids with bone
Cooked, dry heat
Raw
Raw
Raw
Raw
Cooked, batter-dipped and fried
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Smoked
Raw
Raw
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Canned in oil. drained solids
Canned in water, drained solids
Canned in oil
Canned in water, drained solids
Raw
Cooked, dry heat
Raw
Raw
Smoked
Raw
Cooked, dry heat
Raw
June 2000
3-72
DRAFT-DO NOT QUOTE OR CITE
-------
2
14
6
7
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
6
37
38
39
40
41
42
43
44
45
46
Table 3-32. Percent Moisture Content for Selected Fish Species' (continued)
Sixties
Crab, Alaska King
Crab, Blue
Crab, Dungeness
Crab, Queen .
Crayfish, mixed species
Lobster. Northern
Shrimp, mixed species
Spiny Lobster, mixed species
Clam, mixed species
Mussel. Blue
Octopus, common
Oyster. Eastern
Oyster. Pacific
Scallop, mixed species
Squid
Moisture Content
(%}
SHELLFISH
79.57
77.55
79.02
79.16
77.43
71.00
79.18
80.58
80.79
75.37
76.76
76.03
75.86
72.56
52.86
77.28
74.07
81.82
63.64
97.70
61.55
63.64
80.58
61.15
80.25
85.14
85.14
64.72
70.28
82.06
78.57
58.44
73.82
78.55
*..! *J
Comments
Raw
Cooked, moist heat
Imitation, made from surimi
Raw
Canned (dry pack or drained solids of wet pack)
Cooked, moist heat
Crab cakes
Raw
Raw
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Canned (dry pack or drained solids of wet pack)
Cooked, breaded and fried
Cooked, moist heat
Imitation made from surimi. raw
Raw
Canned, drained solids
Canned, liquid
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Raw
Canned (solids and liquid based) raw
Cooked, breaded and fried
Cooked, moist heat
Raw
Raw
Cooked, breaded and fried
Imitation, made from Surimi
Raw
Prtnt*»H fritvt
Data are repotted as in the Handbook
NA - Not available
Source: USDA. 1979-1984 - U.S. Agricultural Handbook No. 8
June 2000
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1
2
6
7
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
45
46
47
48
49
50
51
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Products'
Product
Meats
Beef
Lean only
Lean and fat, 1/4 in. fat trim
Brisket (point half)
Lean and fat
Brisket (flat half)
Lean and fat
Lean only
Pork
Lean only
Lean and fat
Cured shoulder, blade roll, lean and fat
Cured ham. lean and fat
Cured ham. lean only
Sausage
Ham"
Ham
Lamb
Lean
Lean and fat
Veal
Lean
Lean and fat
Rabbit
Composite of cuts
Chicken
Meat only
Meat and skin
Turkey
Meat only
Meal and skin
Ground
Pain.
Milk
Whole
Human
LowfaH !%)
Lowfai (2%)
Skim
Fat Percentage
6.16
9.91
19.24
21.54
22.40
4.03
5.88
9.66
14.95
17.!8
20.02
12.07
7.57
38.24
4.55
9.55
5.25
9.52
21.59
20.94
2.87
6.58
6.77
11.39
5.55
8.05
3.08
7.41
1506
13.60
2.86
4.97
8.02
9.73
6.66
3.16
4.17
0.83
1.83
017
Comment
Raw
Cooked
Raw
Cooked
Raw
Raw-
Raw
Cooked
Raw
Cooked
Unheated
Center slice
Raw. center, country style
Raw. fresh
Cooked, extra lean (5% fat)
Cooked. (11% fat)
Raw
Cooked
Raw
Cooked
Raw
Cooked
Raw
Cooked
Raw-
Cooked
Raw
Cooked
Raw
Cooked
Raw
Cooked
Raw-
Cooked
Raw
3.3% fat. raw or pasteurized
Whole, mature, fluid
Fluid
Fluid
Fluid
June 2000
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Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Products' (continued)
1
2
3
4
5
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
126
'27
28
29
3.0
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
S3
54
Product
Cream
Half and half
Medium
Heavy-whipping
Sour
Butter
Cheese
American
Cheddar
Swiss
Cream
Parmesan
Cottage
Colby
Blue
Provolone
Mozzarella
Yogurt
Eggs
Fat Percentage
18.32
23.71
35.09
19.88
76.93
29.63
31.42
26.02
33.07
24.50: 28.46
1.83
30.45
27.26
25.24
20.48
1.47
8.35
Comment
Table or coffee, fluid
25% fat, fluid
Fluid
Cultured
Regular
Pasteurized
Hard: grated
Lowfat 2% fat
Plain, lowfat
Chicken, whole raw. fresh or frozen
F1NFISH
Anchovy. European
Bass
Bass. Siriped
Bluefish
Butterfish
Carp
Catfish
Cod. Atlantic
Cod. Pacific
Croaker. Atlantic
Dolphinfish. Mahimahi
Drum, Freshwater
Flatfish. Flounder and Sole
Grouper
Haddock
Halibut. Atlantic & Pacific
Halibut. Greenland
Herring. Atlantic &. Turboi. domestic species
4.101
8.535
3.273
1.951
3.768
NA
4.842
6.208
3.597
12.224
0.456
0.582
0,584
1.608
0.407
2.701
11.713
0.474
4.463
0.845
1.084
0.756
0.970
0.489
0.627
0.651
1812
2.324
12.164
7.909
10.140
10.822
16.007
Raw
Canned in oil. drained solids
Freshwater, mixed species, raw
Raw
Raw
Raw
Raw-
Cooked, dry heat
Channel, raw
Channel, cooked, breaded and fried
Atlantic. raw-
Canned, solids and liquids
Cooked, dry heat
Dried and salted
Raw
Raw
Cooked, breaded and fried
Raw
Raw
Raw
Cooked, dry heat
Raw. mixed species
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Kippered
Pickled
June 2000
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Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Daiiy, and Fish Products' (continued)
1
2
3
4
5
6
8
9
10
11
12
13
14
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
45
46
47
48
49
50
51
52
53
54
55
Product
Herring, Pacific
Mackerel, Atlantic
Mackerel, Jack
Mackerel, King
Mackerel, Pacific & Jack
Mackerel, Spanish
Monkfish
Mullet, Striped
Ocean Perch, Atlantic
Perch. Mixed species
Pike. Northern
Pike, Walleye
Pollock, Alaska & Walleye
Pollock. Atlantic
Rockfish. Pacific, mixed species
Roughy. Orange
Salmon. Atlantic
Salmon. Chinook
Salmon, Chum
Salmon. Coho
Salmon. Pink
Salmon. Red & Sockeye
Sardine. Atlantic
Sardine. Pacific
Sea Bass, mixed species
Seatroui. mixed species
Shad. American
Shark, mixed species
Snapper, mixed species
Sole. Spot
Sturgeon, mixed species
Sucker, while
Sun fish. Pumpkinseed
Swordfish
•
Trout, mixed species
Trout. Rainbow
Fat Percentage
12.552
9.076
15.482
4.587
1.587
6.816
5.097
5.745
NA
2.909
3.730
1.296
1.661
0.705
0.904
0.477
0.611
0.990
0.701
0.929
0.730
1.182
1.515
3.630
5.625
9.061
3.947
3.279
4.922
4.908
6.213
2.845
5.391
4.560
6.697
9.616
10.545
11.054
1.678
2.152
2.618
NA
3.941
12.841
0.995
1 .275
3.870
3.544
4.54J
3.829
1.965
0.502
3.564
4.569
5.901
2.883
3.696
Comment
Raw
Raw
Cooked, dry heat
Canned, drained solids
Raw
Canned, drained solids
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Raw
Cooked, drv heat
Raw
Raw (Mixed species)
Cooked, dry heat (mixed species)
Raw
Raw
Raw
Smoked
Raw
Canned, drained solids with bone
Raw
Cooked, moist heat
Raw
Canned, solids with bone and liquid
Raw
Canned, drained solids with bone
Cooked, dry heat
Canned in oil. drained solids with bone
Canned in tomato sauce, drained solids with bone
Cooked, dry heat
Raw
Raw
Raw
Raw
Cooked, batter-dipped and fried
Raw
Cooked, dry heat
Raw
Raw
Cooked, dry heat
Smoked
Raw
Raw
Raw-
Cooked, dry heat
Raw
Raw-
Cooked, dry heat
June 2000
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Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Products* (continued)
1
3
4
5
6
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
Product
Tuna, light meat
Tuna, white meat
Tuna, Bluefish, fresh
Turbot, European
Whitefish, mixed species
Whiting, mixed species
Yellowiail. mixed species
Fat Percentage
7.368
0.730
NA
2.220
4.296
5.509
NA
5.051
0.799
0.948
1.216
NA
Comment
Canned in oil, drained solids
Canned in water, drained solids
Canned in oil
Canned in water, drained solids
Raw
Cooked, dry heat
Raw
Raw
Smoked
Raw
Cooked, dry heat
Raw
SHELLFISH
Crab. Alaska King
Crab, Blue
Crab, Dungeness
Crab, Queen
Crayfish, mixed species
Lobster, Northern
Shrimp, mixed species
Spiny Lobster, mixed species
Clam, mixed species
Mussel, Blue
Octopus, common
Oyster, Eastern
Oyster, Pacific
Scallop, mixed species
Squid
NA
0.854
0.801
0.910
1.188
6.571
0.616
0.821
0.732
0.939
NA
0.358
1.250
1.421
10.984
0.926
1.102
0.456
0.912
NA
10.098
0.912
1.538
3.076
0.628
1.620
1.620
11.212
3.240
1.752
0.377
10.023
NA
0.989
f\ 76 ^
Raw
Cooked, moist heat
Imitation, made from surimi
Raw
Canned (dry pack or drained solids of wet pack)
Cooked, moist heat
Crab cakes
Raw
Raw
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Canned (dry pack or drained solids of wet pack)
Cooked, breaded and fried
Cooked, moist heat
Imitation made from surimi, raw
Raw
Canned, drained solids
Canned, liquid
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Raw-
Canned (solids ami liquid based) raw
Cooked, breaded and fried
Cooked, moist heal
Raw
Raw
Cooked, breaded and fried
imitation, made from Surimi
Raw
f~nnl-rt\ frior!
NA = Not available
* Based on the lipid content in 100 grams, edible portion. Total Fai Content - saturated, monosaturated and polyunsaturatcd.
Source: USDA. 1979-1984.
June 2000
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
Table 3-34. Fat Content of Meat Products
Meat Product
3-oz cooked serving (85.05 g)
Beef, retail composite, lean only
Pork, retail composite, lean only
Lamb, retail composite, lean only
Veal, retail composite, lean only
Broiler chicken, flesh only
Turkey, flesh only
Total Fat
(g)
8.4
8.0
8.1
5.6
6.3
4.2
Percent Fat
Content {%)
9.9
9.4
9.5
6.6
7.4
4.9
=^=
Source: National Livestock and Meat Board. 1993
June 2000
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1
2
3
u
5
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Table 3-35. Summary of Recommended Values for Per Capita Intake of Foods, As Consumed
Age
Total Fruit Intake
< 1 year
1-2 years
3-5 years
6-11 years
12-19 years
Total Vegetable Intake
< 1 year
1-2 years
3-5 years
6-11 years
12-19 years
Total Grain intake
< 1 year
1-2 years
3-5 years
6-11 years
12-19 years
Total Meat Intake
< 1 year
1-2 years
3-5 years
6-11 years
12-19 years
Total Dairy Intake
< 1 year
1-2 years
3-5 years
6-1 1 years
12-19 years
Total Fish Intake
< 1 year
1-2 years
3-5 years
6-1 1 years
12-19 years
Individual Foods Intake
Mean
13.2 g/kg-day
19.3 g/kg-day
1 1. 0 g/kg-day
5.4 g/kg-day
2.8 g/kg-day
6,9 g/kg-day
9.5 g/kg-day
7.3 g/kg-day
5.3 g/kg-day
4.0 g/kg-day
4.1 g/kg-day
' 11. 2 g/kg-day
10.3 g/kg-day
7.2 g/kg-day
4.4 g/kg-day
1.1 g/kg-day
4.4 g/kg-day
4.1 g/kg-day
2.9 g/kg-day
.2.2 g/kg-day
111 g/kg-day
37.5 g/kg-day
20.9 g/kg-day
13.9 g/kg-day
6.1 g/kg-day
0.11 g/kg-day
0.37 g/kg-day
0.32 g/kg-day
0.26 g/kg-day
0.20 g/kg-day
see Table 3-3
95th Percentile
Multiple Percemiles
41.2 g/kg-day see Table 3-2
53.9 g/kg-day
32.7 g/kg-day
18.0 g/kg-day
11.0 g/kg-day
24.2 g/kg-day see Table 3-2
23.3 g/kg-day
18.3 g/kg-day
13.5 g/kg-day
9.3 g/kg-day
20.2 g/kg-day See Table 3-2
24.7 g/kg-day
21.1 g/kg-day
15.6 g/kg-day
9.7 g/kg-day
5.9 g/kg-day See Table 3-2
10.2 g/kg-day
9.4 g/kg-day
6.8 g/kg-day
4.9 g/kg-day
235 g/kg-day See Table 3-2
90.2 g/kg-day
48.8 g/kg-day
33.5 g/kg-day
17.8 g/kg-day
0.53 g/kg-day See Tabie 3-2
1 .79 g/kg-day
1 .74 g/kg-day
1.35 g/kg-day
1.10 g/kg-day
r
Study
EPA Analysis of
CSFH 1994-96 Data
EPA Analysis of
CSFII 1994-96 Data
EPA Analysis of
CSFB 1994-96 Data
EPA Analysis of
CSFI1 1994-96 Data
EPA Analysis of
CSFH 1994-96 Data
EPA Analysis of
CSFH 1994-96 Data
EPA Analysis of
CSFII 1994-96 Data
June 2000
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Table 3*35. Summary of Recommended Values for Per Capita Intake of Foods, As Consumed (continued)
1
2
3
4
5
6
1
8
9
10
11
12
13
14
15
16
Age
95th Percentile
Mean
Multiple Percentiies Study
Freshwater Total Fish Intake (General Population)
14 years and under
Marine Fish Intake (General
14 years and under
70.6 mg/kg-day 556 mg/kg-day
Population)
163 mg/kg-day 894 mg/kg-day
See Table 3-6 EPA Analysis of
CSFII 1989-91 Data
-
See Table 3-6 EPA Analysis of
CSFII 1989-91 Data
Recreational Fish Intake - Freshwater
1-5 years
6-10 years
370 mg/kg-day —
280 mg/kg-day —
See Table 3-13 EPA Analysis of West
etal. 1989 Data
Native American Subsistence Fish Intake
<5 years
Total Fat Intake
Homeoroduced Food Intake
11 g/kg-day —
See Table 3-15 See Table 3-15
See Table 3-28 See Table 3-28
— CRITFC, 1994
See Table 3-15 Frank et al., 1996
See Table 3-28 EPA Analysis of
1987/88 MFCS
June 2000
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1
>4
5
Table 3-36. Confidence Intake Recommendations for Various Foods, Including Fish (General Population)
Considerations
Rationale
Rating
7
.8
9
10
II
12
13
14
15
16
17
18
9
0
21
22
23
24
25
Study Elements
• Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of interest
• Data pertinent to U.S.
• Primary data
• Currency
Adequacy of data collection
period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
• Lack of bias in study design
(high rating is desirable)
• Measurement error
Other Elements
• Number of studies
• Agreement between researchers
Overall Rating
USDA CSFII survey receives high level of peer
review. EPA analysis of these data has been peer
reviewed outside the Agency.
CSFII data are publicly available.
Javitz (1980) is a contractor report to EPA
(CSFII)
Enough information is included to reproduce
results.
Analysis is specifically designed to address food
intake.
Data focuses on the U.S. population.
This is new analysts of primary data.
Were the most current data publicly available at
the time the analysis was conducted for the
Handbook.
Survey is designed to collect short-term data.
Survey methodology was adequate.
Study size was very large and therefore adequate.
The population studied was the U.S. population.
Survey was not designed to capture Ions term
day-to-day variability. Short term distributions
are provided.
Response rate was good.
No measurements were taken. The study relied
on survey data.
I for most foods. 2 for fish: CSFII was the most
recent data set publicly available at the time the
analysis was conducted for the Handbook.
Although the CSFII was the only study classified
as key study for most foods, the results are in
good agreement with earlier data.
The survey is representative of U.S. population.
Although there was only one study considered
key. these data arc the most recent and are in
agreement with earlier data. The approach used
to analyzed the data was adequate. However, due
to the limitations of the survey design estimation
oflong-lerm percemile values (especially the
upper ptfrccmiles) is uncertain.
High
High
Medium (Javitz)
High
High
High
High
High
Medium confidence for average
values:
Low confidence for long term
percentile distribution
High
High
High
Medium
High
N/A
Low
Hish
High confidence in the average:
Low confidence in the long-term upper
pcrccntilcs
26
June 2000
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2
3
4
5
Table 3-37. Confidence Intake Recommendations for Fish Consumption - Recreational Freshwater Angler Population
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Considerations
Study Elements
• Level of peer review
• Accessibility
• Reproducibiiity
• Focus on factor of interest
• Data pertinent to U.S.
• Primary data
• Currency
• Adequacy of data collection
Rationale
. Study is in a technical report and has been
reviewed by the EPA.
The original study analyses are reported in a
technical teport. Subsequent EPA analyses are
detailed in this Handbook.
Enough information is available to reproduce
results.
Study focused on ingestion offish by the
recreational freshwater angler and family.
The study was conducted in the U.S.
Data are from a primary reference.
The study was conducted between January and
May 1989.
Data were collected for 1 week.
Ratins
High
High
High
High
High
High
High
Low
period
Validity1 of approach
• Study size
• Representativeness of the
population
• Characterization of variability
• Lack of bias in study design
(high rating is desirable)
• Measurement error
Other Elements
• Number of studies
• Agreement between researchers
Overall Rating
Data presented are from a one week recall of fish Medium
consumption study. Weight offish consumed
was estimated using approximate weight offish
catch and edible fraction or approximate "•eight
offish meal-
Study population was 621 children. Medium
The study was localized to a single state. Low
Distributions were not generated. High
Response rate was 47 percent. Medium
Weight offish portions were estimated in one Medium
study, fish weight was estimated from reported
fish length in another study.
There is 1 study. Low
There is only 1 study. EPA performed an Low
analyses using these data.
The study is not nationally representative and not Low
representative of long-term consumption.
June 2000
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2
3
4
5
6
Table 3-38. Confidence Intake Recommendations for Fish Consumption - Native American Subsistence Population
Considerations
Rationale
Ratine
Study Elements
• Level of peer review
• Accessibility
7 • Reproducibility
8 • Focus on factor of interest
9 • Data pertinent to U.S.
10 • Primary data
11 • Currency
12 • Adequacy of data collection
13 period
14 • Validity of approach
15 • Study size
16 • Representativeness of the
17 population
18 • Characterization of variability
19 • Lack of bias in study design
20 (high rating is desirable)
21 • Measurement error
I Other Elements
23 • Number of studies
24 • Agreement between researchers
25 Overall Rating
26
Study is in a technical report Medium
CRJTFC is a technical report, that is publicly Medium
available
The study was adequately detailed and enough
information is available to reproduce results.
Study focused on fish ingestion among Native
American Tribes.
The study was specific in the U.S.
The study used primary data.
Data were from 1991-1992.
Data were collected for 1 study.
Individual intake measured directly, but some
respondents provided in same information for the
children as themselves.
The sample population was 204 children < 5 years
old.
Only one stale was represented: population < 5
years old only.
Individual variations were not described.
The response rate was 69 percent in the study..
The weight of the fish was estimated.
There was only one study.
There was only one study.
Study is not nationally representative.
High
High
High
High
High
High
Low confidence for long term
percentile distribution
Low
Medium
Low
Medium
Medium
Medium
Low - Medium
Medium
Low
June 2000
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1 APPENDIX 3A
2
3 CALCULATIONS USED IN THE 1994-96 CSFII ANALYSIS TO
4 CORRECT FOR MIXTURES
June 2000 DRAFT-DO NOT QUOTE OR CITE
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1 APPENDIX 3 A
2 Calculations Used in the 1994-96 CSFII Analysis to Correct for Mixtures
3
4 Distributions of intake for various food groups were generated for the food/items groups using the USDA
5 1994-96 CSFII data set as described in Sections 9.2.2. and 11.1.2. However, several of the food categories used did
6 not include meats, dairy products, and vegetables that were eaten as mixtures with other foods. Thus, adjusted
7 intake rates were calculated for food items that were identified by USDA (1995) as comprising a significant portion
8 of grain and meat mixtures. To account for the amount of these foods consumed as mixtures, the mean fractions of
9 total meat or grain mixtures represented by these food items were calculated (Table 3A-1) using Appendix C of
10 USDA (1995). Mean values for all individuals were used to calculate these fractions. These fractions were
11 multiplied by each individual's intake rate for total meat mixtures or grain mixtures to calculate the amount of the
12 individual's food mixture intake that can be categorized into one of the selected food groups. These amounts were
13 then added to the total intakes rates for meats, grains, total vegetables, tomatoes, and white potatoes to calculate an
14 individual's total intake of these food groups, as shown in the example for meats below.
15
16
77? = (IR * FT ' ^ -J- (77? * Fr ^ +
meat-adjusted \ gr mixtures meat/gr) \ ml mixtures meat fait J
18
19 -where:
20 IRriMi-idjuswd = adjusted individual intake rate for total meat;
21 IRgnnxiures = individual intake rate for grain mixtures;
22 lR«i»i«uns = individual intake rate for meat mixtures;
23 IRi«« = individual intake rate for meats;
24 frnnwgr = fraction of grain mixture that is meat; and
i25 ffmai/m ~ fraction of meat mixture that is meat.
'26
27 Population distributions for mixture-adjusted intakes were based on adjusted intake rates for the population of
28 interest.
29
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
TABLE 3A-1. FRACTION OF GRAIN AND MEAT MIXTURE INTAKE REPRESENTED BY
VARIOUS FOOD ITEMS/GROUPS
Gram Mixtures
total vegetables
tomatoes
white potatoes
total meats
beef
pork
poultry
• dairy
total grains
fish
fggs
fat
Meat Mixtures
total vegetables
tomatoes
white potatoes
total meats
beef
pork
poultry
dairy
total grains
fish
eggs
fats
0.2584
0.1685
0.0000
0.0787
0.0449
0.0112
0.0112
0.1348
0.3146
0.0000
0.0112
0.0225
0.3000
0.1111
0.0333
0.3111
0.2000
0.0222
0.0778,
0.0556
0.1333
0.0444
0.0111
0.0222
June 2000
3A-2
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1 APPENDIX 3B
2
3 FOOD CODES AND DEFINITIONS USED IN
4 ANALYSIS OF THE 1994-96 USDA CSFII DATA
5
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1
3
4
5
TABLE 3B-I FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA
Food Product
Food Codes
MAJOR FOOD GROUPS
Tola! Daiiy 1-
Tota! Meats 20-
21-
22-
23-
24-
25-
Total Fish . 26-
Eggs 3-
Total Grains 50-
51-
52-
53-
54-
55-
561-
562-
57-
Total Fruits 6-
Total Vegetables 7-
411-
412-
413-
414-
415-
416-
418-
419-
Total Fats 8-
Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
Meat, type not specified
Beef
Pork
Lamb, veal, game, carcass meat
Poultry
Organ meats, sausages, lunchmeats. meal spreads
Fish, all types
Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
flour
breads
tortillas
sweets
snacks
breakfast foods
pasta
cooked cereals and rice
ready-to-eat and baby cereals
Fruits
citrus fruits and juices
dried fruits
other fruiis
fruits/juices Si nectar
fruit/juices baby food
Vegetables (all forms)
white potatoes &, PR starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
vea. and mixtures/baby food
vea with meat mixtures
Beans/legumes
Beans/legumes
Beans/legumes
Soybeans
Bean dinners and soups
Bean dinners and soups
Meatless items
Soyburaers
Fau (all forms)
Includes regular fluid milk, human milk, imitation milk
products, yogurt, milk-based meal replacements, and infant
formulas. Also includes the average portion of grain
mixtures (i.e.. 13.48 percent) and the average portion of
meat mixtures (i.e., 5.S6 percent) made up by dairy.
Also includes the average portion of grain mixtures (i.e.,
7.87 percent) and the average portion of meat mixtures
(i.e., 31.11 percent) made up by meats.
Also includes the average portion of meat mixtures (i.e..
4.44 percent) made up by fish.
Includes baby foods. Also includes the average portion of
grain mixtures (i.e.. 1.12 percent) and the average portion
of meat mixtures (i.e.. 1. 11 percent) made up by eggs.
Also includes the average portion of grain mixtures (i.e..
31 .46 percent land the average portion of meat mixtures
(i.e.. 13.33 percent) made up by grain.
Includes baby foods.
Includes baby foods: mixtures, mostly vegetables; does not
include nuts and seeds. Also includes the average portion
of grain mixtures (i.e.. 25.84 percent) and the average
portion of meat mixtures (i.e.. 30, 00 percent) made up by
vegetables.
Includes butler, margarine, animal fat. sauces, vegetable
oils, dressings, and mayonnaise Also includes the average
portion of gram mixtures ( i.e.. 2.25 percent) and the
average ponion of meat mixtures (i.e., 2.22 percent) made
up by meats
7
8
'10
11
12
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-% USDA CSFII DATA (CONTINUED)
Food Product 1
Food Codes
INDIVIDUAL MEATS
Beef 21-
Pork 22-
Game 233-
Poultry 24-
Beef
beef, nfs
beefsteak
beef oxtails, neckbones, ribs
roasts, stew meat, corned, brisket, sandwich
steaks
ground beef, patties, meatballs
other beef items
beef baby food
Pork
pork, nfs; ground dehydrated
chops
steaks, cutlets
ham
roasts
Canadian bacon
bacon, salt pork
other pork items
pork baby food
Game
Poultry
chicken
turkey-
duck'
other poultry
poultry baby food
Also includes die average portion of grain mixtures (i.e.,
4.49 percent) and the average portion of meat mixtures
(i.e., 20.0 percent) made up by beef
Also includes the average portion of grain mixtures (i.e.,
1.12 percent) and the average ponton of meat mixtures
(i.e.. 2.22 percent) made up by pork.
Also includes the average portion of grain mixtures (i.e..
1.12 percent) and the average portion of meat mixtures
(i.e., 7.7$ percent) made up by poultry-.
INDIVIDUAL GRAINS
Breads - 51-
52-
Sweets 53-
Snacks 54-
Breakfast Foods 55-
Pasia 561-
breads, rolls, muffins, bagel, biscuits, corn bread
tortillas
cakes, cookies, pies, pastries, doughnuts.
breakfast bars, coffee cakes
crackers, salty snacks, popcorn, pretzels
pancakes, waffles, french toast
macaroni, noodles, spaghetti
Cooked Cereals 56200-
56201-
56202-
56203-
56206-
56207-
56208-
5620
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TABLE 3B-I FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Citrus Fruits
Other Fruits
Apples
Bananas
Peaches
Pears
Strawberries
Food Codes
FRUIT CATEGORIES
61- . Citrus Fruits and Juices
6720500 Orange Juice, baby food
6723050 Orange/carrot baby juice
62- Dried Fruits
63- Other Fruits
64- Fruit Juices and Nectars Excluding Citrus
67!- Fruits, baby
67202- Apple Juice, baby
67203- Baby Juices
67204- Baby Juices
67212- Baby Juices
62 1 0 1 1 0 Apples, dried, uncooked
62 1 0 1 1 5 Apples, dried, uncooked, low sodium
62 1 01 20 Apples, dried, cooked. NS as to sweetener
6210122 Apples, dried, cooked, unsweetened
62 1 0 1 23 Apples, dried, cooked, with sugar
6210130 .Apple chips
6310100 Apples, raw
6310111 Applesauce. NS as to sweetener
63 1 0 11 2 Applesauce, unsweetened
63 1 0 1 1 3 Applesauce with sugar
63 1 0 1 1 4 Applesauce with low calorie sweetener
63101 1 5 Applesauce/other fruits
63 1 0 1 2 1 Apples, cooked or canned with syrup
6310131 Apple, baked NS as to sweetener
6310132 Apple, baked, unsweetened
6310133 Apple, baked with sugar
6310141 Apple rings, fried
6310142 Apple, pickled
6310150 Apple, fried
6340 1 0 Apple/other fruit salad
6340106 Apple, candied
6410101 Apple cider
6410401 Apple juice
64 1 0405 Apple j uice with vitam in C
641040° Apple juice with calcium
6410415 Apple-cherry juice
6410420 Apple-pear juice
62 1 07 1 0 Banana flakes, dehydrated
62 1 0720 Banana chips
63 1 07- Bananas, various
6340199 Banana, chocolate covered
6340201 Bana whip
6420 1 50 Banana nectar
6710503 Banana, baby
67 1 1 500 Banana, baby
62116- Dried Peaches
63135- Peaches
6412203 Peach Juice
6420501 Peach Nectar
62119- Dried Pears
63137- Pears
6341201 Pear salad
6421501 Pear Nectar
67109- Pears, baby
6322- Strawberries
6413250 Strawberrv Juice
63403 1 SO Lime souffle
672 11 00 Orange-Apple-Banana Juice, baby food
Includes some citrus mixtures.
67213- Baby Juices
672300 Apple sweet potato juice
6725- Baby Juice
673- Baby Fruits
674- Baby Fruits
675- Apples with meat
Includes some mixtures (i.e.. salads, baby foods).
6410445 Apple-raspberry juice
6410450 Apple-grape juice
67 1 0030 Applesauce, baby toddler
67 1 0 1 00 Apple-raspberry, baby, ns as to strained or
junior
67 1 0 1 0 1 Apple-raspberry, baby, strained
6710102 Apple-raspberry, baby, junior
67 1 0200 Applesauce baby fd. . NS as to str. or jr.
67 1 020 1 Applesauce baby food, strained
67 1 0202 Applesauce baby food, junior
67 1 04- Applesauce & other fruit, baby
67 11 3- Apples & pears, baby
6720200 Apple juice, baby food
6720300 Apple w/olher fruit juice, baby
6720320 Apple-banana juice, baby
6720340 Apple-cherry juice, baby
6720345 Apple-cranberry juice, baby
6720350 Apple-grape juice, baby
6720360 Apple-peach juice, baby
6720370 Apple-prune juice, baby
6723000 Apple-sweet potato juice, baby food
6725005 Apple juice w/lowfat yogurt, baby food
67301- Apples & cranberries w/tapioca. baby
6740407 Apple yogurt dessert baby, strained
674 1 2- Dutch apple dessert, baby
675- Apples i meat, baby
Includes some mixtures.
672501 0 Banana juice with yogurt, baby
6730S- Banana, baby
67309- Banana, baby
67404 1 1 Banana apple dessert, baby
6740420 Banana pineapple dessert, baby
67408- Banana, baby
67404!- Banana, baby
67108- Peaches .baby
67 1 ] 450 Peaches, dry.' baby
67405- Peach cobbler, baby
674 1 3700 Peach yogurt dessert, baby
67 ! 1 4 5 a Pears, dry. baby
6721200 Pear juice, baby
64 1 2300 PearAvhne grape/passion fruit juice
67 1 1 4- Pear/pineapple, baby
6725020 Pear/peach mice with yogurt, bahy
1
2
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-% USDA CSFII DATA (CONTINUED)
Food Product
Other Berries
Exposed Fruits
Food Codes
62 1 09 1 0 Cranberries, dried
6320- Other Berries
6321- Other Berries
6322400 Youngbcrries, raw
6341101 Cranberry salad
621011- Apple, dried
621012- Apple, dried
6210130 Apple chips
62104- Apricot, dried
6210$- Currants, dried
62 1 09 1 0 Cranberries, dried
62 110- Date, dried
62116- Peaches, dried
62119- Pears, dried
62121- Plum, dried
62122- Prune, dried
62125- Raisins
63101- Apples/applesauce
63102- Wi-appfe
63103- Apricots
63 11 1 - Cherries, maraschino
63 II 2- Acerola
63113- Cherries, sour
63 1 1 5- Cherries, sweet
63117- Currants, raw
63123- Crapes
6312601 Juneberry
63131- Nectarine
63135- Peach
63137- Pear
63139- Persimmons
63143- Plum
63146- Quince
63147- Rhubarb/Sapodillo
632- Berries
6340101 Apple salad w/dressmg (include Waldorf salad)
6340 1 02 Apple £ cabbage salad w/dressing
6340 1 03 Apple & fruit salad w/dressing
6340106 Apple, candied (include caramel apples)
6340203 Prune whip
6341 101 Cranberry salad, congealed
634 1 20 1 Pear salad w/dressing
6341500 Soup, sour cherry
64101- Apple Cider
64104- Apple Juice
64 1 0409 Apple juice with calcium
64105- Cranberry Juice
64 116- Crape Juice
64122- Peach Juice
6412300 Pear-whitc-erape-passion fruit juice, w/added Vit
C
64132- Prune/Strawberry Juice
6420 1 0 1 Apricot Neciar
64205- Peach Nectar
64215- Pear Nectar
6710030 Applesauce, baby toddler
6710100 Apple-raspberry, baby, nsas to strained or junior
67 1 0 1 0 1 Apple-raspberry. baby . strained
6410460 Blackberry Juice
64105- Cranberry Juice
6740430 Blueberry yogurt dessert, baby
6710102 Apple-raspberry, baby, junior
67102- Applesauce, baby
67 i 0400 Applesauce & apricots, baby, nsastostrorjr
671 0401 Applesauce & apricots, baby, strained
67 ) 0402 Applesauce & apricots, baby, junior
67 1 0407 Applesauce w/cherries, baby, strained
6710408 Applesauce w/cherries. baby, junior
67 1 0409 Applesauce w/cherries. baby, ns str/jr
67 JOS- Peaches, baby
67109- Pears, baby
67) 1000 Prunes, baby
67 j 1300 Apples & pears, baby, nsastostrorjr
67 i 1 30 1 Apples & pears, baby, strained
6711 302 Apples & pears, baby, junior
6711450 Peaches, baby, dry
6711455 Pears, baby, dry
67202- Apple Juice, baby
6720340 Apple-cherry juice, baby
6720345 Apple-cranberry juice, baby
6720350 Apple-grape juice, baby
6720360 Apple-peach juice, baby
6720370 Apple-prune juice, baby
6720380 White Grape Juice, baby
67212- Pear Juice, baby
6723000 Apple-sweet potato juice, baby food .
6725005 Apple juice w/lowfat yogurt, baby food
6725020 Pear-peach juice w/lowfat yogurt, baby food
6730 1 00 Apples & cranberries w/tapioca, baby, ns str/jr
6730 1 0 1 Apples &. cranberries w/iapioca. baby.
strained
67301 02 Apples & cranberries w/tapioca, baby, junior
6730400 Plums w/tapioca. baby, ns as to str/jr
673040 1 Plums w/tapioca. baby, strained
6730402 Plums w/tapioca. baby, junior
6730403 Plums/bananas &. rice. baby, strained
6730450 Prunes w/oatmeal, baby, strained
673050 1 Prunes w/tapioca. baby, strained
6730600 Ciruelas w/tapioca. baby
6730700 Apricots w/tapioca. baby, ns as to str/jr
6730701 Apricots w/upioca. baby, strained
6730702 Apricots w/iapioca. baby, junior
6740407 Apple yogurt dessen. baby, strained
6740430 Blueberry yogurt dessert. bab> . strained
67404 55 Cherry cobbler, baby, junior
6740500 Peach cobbler, baby, ns as w str/jr
6740501 Peach cobbler, baby, strained
6740502 Peach cobbler, baby, junior
674 1000 Cherry vanilla pudding, baby
674 1 200 Dutch apple dessen. baby, ns as to str/jr
674 1 20 1 Dutch apple dessert, baby, stra ined
6 74 1 202 Dutch apple dessen. baby, junior
6741370 Peach yogurt dessen. baby, strained
675- Apples & meat
June 2000
3B-4
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TABLE 3B-I FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE l»4-% USDA CSFII DATA (CONTINUED)
Food Product
Protected Fruits
Food Codes
61- Citrus Fr,, juices (incl. cit. juice mixtures)
62107- Bananas, dried
62113- Figs, dried
62 1 1 4- Ly chees/Papayas. dried
62 1 20- Pineapple, dried
621 26- Tamarind, dried
63 1 OS- Avocado, raw
63107- Bananas
63109- Cantaloupe, Cararnbola
63110- Cassaba Melon
631 19- Figs
63121- Genip
63125- Guava/Jackfruit, raw
6312650 Kiwi
6312651 Lychee. raw
6312660 Lychee. cooked
6312665 Loquats.raw
63127- Honeydew
63129- Mango
63133- Papaya
63134- Passion Fruit
63)41- Pineapple
63145- Pomegranate
63148- Sweetsop. Soursop. Tamarind
63149- Watermelon
6340 1 99 Banana, chocolate-covered, w/nuts
6340201 Banana whip
6340205 Fried dwarf banana w/cheese. puerto rican style
6340315 Lime souffle (include other citrus fruits)
6340S01 Guacamole w/tomatoes
6340820 Guacamole w/tomatoes & chile peppers
63490901 Guacamole. nfs
64 i 20- Papaya Juice
64 1 2 1 - Passion Fruit Juice
64124- . Pineapple Juice
64125- Pineapple juice
64133- Watermelon Juice
6420150 Banana Nectar
64202- Cantaloupe Nectar
64203- Guava Nectar
64204- . Mango Nectar
642 1 0- Papaya Nectar
642 1 3- Passion Fruit Nectar
64221- Soursop Nectar
67 1 0503 Bananas, baby
67 1 1 500 Bananas, baby, dry
6720500 Orange Juice, baby
672 1 300 Pineapple Juice, baby
6723050 Orange-carrot juice, baby food
67250 1 0 Banana juice w/lowfat yogurt, baby food
6730800 Bananas w/tapioca. baby, ns as to str/jr
6730801 Bananas w/tapioca. baby, strained
6730802 Bananas w/tapioca. baby, junior
6730900 Bananas & pineapple w/tapioca. baby, ns as to
Str/jr
6730901 Bananas & pineapple w/tapioca. baby.
strained
6730902 Bananas &. pineapple w/tapioca. baby, junior
67404 1 i Banana apple dessert baby food, strained
6740420 Banana pineapple dessert, w/tapioca. baby
674080 1 Banana pudding, baby, strained
6740850 Banana yogurt dessert, baby, strained
674 1 400 Pineapple dessert, baby, ns as to str/jr
674 1 40 1 Pineapple dessert, baby1, strained
674 1 402 Pineapple dessert baby, junior
674 1410 Mango dessert w/tapioca. baby
VEGETABLE CATEGORIES
Asparagus
Beets
Broccoli
Cabbage
Can-ois
7510080 Asparagus, raw
75202- Asparagus, cooked
7540101 Asparagus, creamed or with cheese
72101- Beet greens
7510250 Beets, raw
752080- Beets, cooked
752081- Beets, canned
7540501 Beets. Harvard
722- Broccoli (all forms >
7230200 Broccoli soup (include cream of broccoli soup)
7230210 Broccoli cheese soup, prep w/milk
7230200 Broccoli soup ( include cream of broccoli soup)
7510300 Cabbage, raw
7510400 Cabbage. Chinese, raw
751 0500 Cabbage, red. raw
7514100 Cabbage salad or coleslaw
73141 10 Cabbage salad or coleslaw, w/applcs, raisins.
dress
75 1 4 1 20 Cabbage salad or coleslaw. Wpincappk. dressing
7514130 Cabbage. Chinese, salad
752 1 0- Chinese Cabbage, cooked
7310- Carrots (al! forms)
75 1 11 JO Carrots in Sauce
7311200 Carrot Chips
735- Carrol soup
7560 1 0 Asparagus soup
Does not include vegetables with meat mixtures
7550021 Beets, pickled
7560110 Beet soup
76403- Beets, baby
Does not include vegetable with meat mixtures.
75 1 4050 Broccoli salad w /cauliflower, cheese, bacon.
& dressing
Does not include vegetable with meat mixtures.
752 1 1 - Green Cabbage, cooked
75212- Red Cabbage, cooked
752130- Savoy Cabbage.' cooked
75230- Sauerkraut, cooked
7540701 Cabbaac. creamed
755025- Cabbage, pickled or in relish
7560120 Cabbage soup
7 560 1 2 ! Cabbage w; meal soup
Does not include vegetable with meat mixtures.
76201- Carrots, baby
7620200 Carrots &. peas, baby
Docs not include vegetable with meat mixtures.
2
3
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-% USDA CSFII DATA (CONTINUED)
Food Product
Com
Cucumbers
Lettuce
Lima Beans
Okra
Onions
Food Codes
7510960 Com, raw
7521600 Com, cooked, NS as to color/fat added
7521601 Corn, cooked, NS as to color/fat not added
7521602 Corn, cooked. NS as to color/fat added
752 1 605 Com, cooked, NS as to color/cream style
7521607 Com, cooked, dried
7521610 Com, cooked, yellow/NS as to fat added
752! 61 1 Com, cooked, yellow/fat not added
7521612 Com, cooked, yellow/fat added
752 1 6 1 5 Com, yellow, cream style
7521616 Com, cooked, yell. &wh./NS as to fat
7521617 Com, cooked, yell. £ wh./fai not added
7521618 Com. cooked, yell. & wh./fat added
752 1 6 1 9 Com, yellow, cream style, fat added
752 1 620 Com, cooked, wh ite/NS as to fat added
752 1 62 1 Com. cooked, white/fat not added
75 11 1 00 Cucumbers, raw
75 1 42- Cucumber salads
752167- Cucumbers, cooked
755030 1 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweet
73113- Lettuce, raw
75 1 43- Lettuce salad with other veg.
7514410 Leituce. wilted, with bacon dressing
7522005 Lettuce, cooked
4 1 1 0300 Lima beans, dry. cooked, ns as to added fat
4 1 1 030 1 Lima beans, dry. cooked, fat added
4 1 1 0302 Lime beans, dry. cooked, no fat added
4121011 Stewed dry lima beans, p.r.
4 1 30 1 04 Lima bean soup
4160104 Lima bean soup
7522000 Okra. cooked. NS as to fat
752200 1 Okra. cooked, fat not added
7522002 Okra. cooked, fat added
7522010 Lufta. cooked (Chinese Okra)
7510950 Chives, raw
7511150 Garlic, raw
75 II 250 Leek, raw
75 1 1 701 Onions, young green, raw
75 1 ! 702 Onions, mature
7521550 Chives, dried
7521740 Garlic, cooked
7521840 Leek, cooked
7523 1 00 Onions, mature cooked. NS as 10 fat added
7522 1 0 1 Onions, mature cooked, fat not added
7522102 Onions, mature cooked. fa< added
7521 622 Com, cooked, white/fat added
752 1 625 Com, white, cream style
752 1 630 Com, yellow, canned, low sodium, NS fat
7521 63 1 Com, yell., canned. low sod., fat not add
752 1 632 Com, yell., canned, low sod., fat added
7521749 Hominy, cooked
752175- Hominy, cooked
753030 1 Com w/peppers, red or green, cooked, no fat
added
754 1 1 0 1 Com scalloped or pudding
7541102 Com fritter
754 1 1 03 Com with cream sauce
7550101 Com relish
756040- Com soup
76405- Com. baby
Does not include vegetable with meat mixtures.
7550305 Cucumber pickles, fresh
7550307 Cucumber. Kim Chee
75503 1 1 Cucumber pickles, dill, reduced salt
75503 14 Cucumber pickles, sweet, reduced salt
756045 1 Cucumber soup, cream of. w/milk
Does not include vegetable with meat mixtures.
Does not include vegetable with meat mixtures.
75 1 0200 Lima beans, raw
752040- Lima beans, cooked
75204 1 - Lima beans, canned
75301- Beans, lima & com (succotash)
75402- Lima beans with sauce
Does not include vegetable with meat mixtures.
7541450 Okra. fried
7550700 Okra. pickled
Does not include vegetable with meat mixtures.
7522103 Onions, pearl cooked
7522 1 04 On ions, young green cooked. NS as to fat
7522 105 Onions, young green cooked, fat not added
7522 1 06 Onions, vouns green cooked, tat added
7522110 Onion, dehydrated
754 1 50 1 On ions, creamed
7541502 Onion rings
75605- Leek soup
75608- Onion soup
Docs not include vegetable with meal mixtures.
June 2000
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TABLE 3B-I FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Peas
Peppers
Pumpkin
Snap Beans
Tomatoes
White Potatoes
Food Codes
4 ! 301 0- Cowpeas, dry, cooked
413020- Chickpeas, diy, cooked
41303- Split peas, dry. cooked
4 1 3035- Stewed green peas
4130403 Peas. dry. cooked w/pork
4 1 304 1 3 Cowpeas, dry , cooked w/pork
4131010 Stewed pigeon peas, p.r.
4131015 Stewed chickpeas, p.r.
4131016 Stewed chickpeas, w/potatoes, p.r.
4131020 Chickpeas, w/pig's feet, p.r.
4131021 Chickpeas, w/spanish sausage, p.r.
4! 31022 Fried chickpeas, p.r.
4131031 Stewed cowpeas. p.r.
4 1 6020 1 Chunky pea &. ham soup
4 1 60202 Garbanzo or chickpea soup
4 1 60203 Split pea & ham soup
4 1 60204 Pea soup, instant type
4160205 Split pea soup
4 1 60206 Pigeon pea asopao
4160207 Split pea soup. can. reduced sodium, u/water/ns
75 1 2 1 40 Pepper, poblano. raw
7512100 Pepper, hot chili, raw
7512150 Pepper, serrano. raw
7512200 Pepper, raw
75 1 22 1 0 Pepper, sweet green, raw
75 1 2220 Pepper, sweet red. raw
75 1 2400 Pepper, banana, raw
7522600 Pepper, green, cooked. NS as to fat added
752260 1 Pepper, green, cooked, fat not added
7522602 Pepper, green, cooked, fat added
7522604 Pepper, red. cooked. NS as to fat added
7522605 Pepper, red. cooked, fat not added
732- Pumpkin (at) forms)
733- Winter squash (all forms)
76205- Squash, baby
75! 0180 Beans, string, green, raw
7520498 Beans, string, cooked. NS color/fat added
7520499 Beans, string, cooked. NS color/no fat
7520500 Beans, string, cooked. NS color & fat
7520501 Beans, string, cooked. green/NS fat
7520502 Beans, siring, cooked, green/no fat
7520503 Beans, string, cooked, green/fat
752051 1 Beans, str.. canned, low sod..green/NS fat
75205 1 2 Beans, str. canned, low sod. .green/no fat
75205 1 3 Beans, sir., canned, low sod. .green/fat
752060(1 Beans, string, cooked. yellow/NS fat
7520601 Beans, string, cooked, yellow/no fat
7520602 Beans, string, cooked, yellow/fat
753020 1 Beans, green string w/tomaloes (assume w/o fat)
7530202 Beans, green string w/onions. cooked, no fat
added *
7530203 Beans, green string w/chickpeas. cooked, no fat
added "
7530204 Beans, ereen string w/almonds. cooked, no fat
added ~
74- Tomatoes and Tomato Mixtures
raw. cooked, juices, sauces, mixtures, soups.
sandwiches
71- While Potatoes and PR Starchy Veg.
baked, boiled, chips, sucks, creamed, scalloped.
au gratm. fried, mashed. stutTed. putTs. salad.
recipes, soups. Puerto Rican starchy vegetables
4160209 Split pea & ham soup, can, reduced sodium,
w/water/rts
731110-&
731112- Peas & carrots
75 1 2000 Peas, green, raw
75 1 2775 Snowpeas. raw
75223- Peas, cowpeas, field or blackeye, cooked
75224- Peas, green, cooked
75225- Peas, pigeon, cooked
75231- Snowpeas. cooked
75315- Peas & corn onions, mushrooms, beans, or
potatoes
7541650 Pea salad
7541660 Pea salad with cheese
754 1 7- Peas, with sauce or creamed
75609- Pea soup
76409- Peas, baby
764 1 1 - Peas, creamed, baby
7650200 Peas & brown rice. baby-
Does not include vegetable with meat mixtures.
7522606 Pepper, red. cooked, fat added
7522609 Pepper, hot. cooked. NS as to fat added
7522610 Pepper, hot. cooked, fat not added
752261 1 Pepper, hot. cooked, fat added
7530700 Green peppers & onions, cooked, fat added in
cooking
755 1 1 01 Peppers, hot. sauce
755 1 1 02 Peppers, pickled
7551104 Pepper, hot pickled
755 1 105 Peppers, hot pickled
Does not include vegetable with meat mixtures.
Does not include vegetable with meat mixtures
7530205 Beans, green & potatoes, cooked, no fat added
7530206 Beans, green w/pinto beans, cooked, no fat
added
7530207 Beans, green w/spaetzet. cooked, no fat added
7530208 Bean salad, yellow SJor green siring beans
7530220 Beans, green string w/onions.° ns as to added
fat
753022 1 Beans, green siring \v/on ions, fat added
7530250 Beans, green & potatoes, ns as to added fat
753025 ! Beans, green & potatoes, fat added
7540301 Beans, string, green, creamed
7540302 Beans, string, green, w/mushroom sauce
7540401 Beans, string, yellow, creamed
755001 1 Beans, string, green, pickled
7640100 Beans, green, string, baby
76401 0 1 Beans, green, string, baby. str.
7640102 Beans, green, string, baby, junior
7640103 Beans, green, string, baby, creamed
7640106 Beans, green string, baby
Does not include vegetable with meat mixtures.
Also includes the average portion of gram mixtures (i.e..
16. 8> percent) and the average portion of meat mixtures
(i.e . 11 It percent) made up by tomatoes.
76420000 Potatoes. baby-
Also includes the average portion of meat mixtures (i.e..
3.33 percent) made up by meats
3
4
June 2000
3B-7
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Dark Green
Vegetables
Deep Yellow
Vegetables
Other Vegetables
Exposed Vegetables
Food Codes
72- Dark Green Vegetables
all forms
leafy, nonleafy, dk. gr. veg. soups
73- Deep Yellow Vegetables
all forms
carrots, pumpkin, squash, sweet potatoes, dp.
yell. veg. soups
75- Other Vegetables
all forms
72 1 • Dark Green Leafy Veg.
722- Dark Green Nonleafy Veg.
7230200 Broccoli soup (include cream of broccoli soup)
723021 0 Broccoli cheese soup, prep w/milk
7230500 Escarole soup
7230600 Watercress broth w/shrimp
7230700 Spinach soup
7230800 Dark-green leafy vegetable soup w/meat. oriental
72308SO Dark-green leafy vegetable soup, meatless.
oriental
74- Tomatoes and Tomato Mixtures
75(0050 Alfalfa Sprouts
75 1 0075 Artichoke. Jerusalem, raw
7510080 Asparagus, raw
75 1 0 1 - Beans, sprouts and green, raw
7510260 Broccoflower. raw
7510275 Brusse! Sprouts, raw
75 1 0280 Buckwheat Sprouts, raw
7510300 Cabbage, raw
75 1 040C Cabbage. Chinese, raw
75 1 0500 Cabbage. Red. raw
75 1 0700 Cauliflower, raw
7510900 Celery, raw
7510950 Chives, raw
75)0955 Cilantro. raw
7511100 Cucumber, raw
7511120 Eggplant, raw
7511200 Kohlrabi, raw
75113- Lettuce, raw
75 1 1 500 Mushrooms, raw
7511900 Parsley
7512100 Pepper, hot chili
75122- Peppers, raw
7512400 Pepper, banana, raw
7512750 Seaweed.'raw
75 1 2775 Snowpeas. raw
75 1 28- Summer Squash, raw
7513210 Celery Juice
75 14050 Broccoli salad w/cauliflower. cheese, bacon.
dressing
75 1 4 1 00 Cabbage or cole slaw
7514] 10 Cabbage salad or coleslaw w/applcs/raistns.
dressing
7514120 Cabbage salad or coleslaw w/pincappie. dressing
7514130 Chinese Cabbage Salad
75 1 4 1 50 Celery with cheese
75 1 42- Cucum bcr salads
75143- Lettuce salads
75 1 44 1 0 Lettuce, wilted with bacon dressing
75 1 4500 Seven-layer salad ( lettuce, mayo, cheese, egg.
peas)
75)4600 Greek salad
7514700 Spinach salad
75 1 4800 Cob salad w/dressing
7520060 Algae, dried
75201- Artichoke, cooked
75202- Asparagus, cooked
75203- Bamboo shoots, cooked
752049- Beans, string, cooked
75205- Beans, green, cooked/canned
75206- Beans, yellow, cooked/canned
75207- Bean Sprouts, cooked
752085- Breadfruit
7520S7- Broccoflower. cooked
752090- Brusscl Sprouts, cooked
752 1 0- Cabbage. Ch mese. cooked
752 1 1 - Cabbage, green, cooked
752 1 2- Cabbage, red. cooked
752 1 30- Cabbage, savoy, cooked
75214- Cauliflower
75215- Celery, Chives. Christophine (chayote)
752167- Cucumber, cooked
752170- Eggplant, cooked
752171- Fern shoots
752172- Fern shoots
752 1 73- Flowers of sesbania. squash or 1 i ly
7521801 Kohlrabi, cooked
75219- Mushrooms, cooked
75220- Okra/lettuce. cooked
7522 116 Palm Hearts, cooked
7522121 Parsley, cooked
75226- Peppers, pimento, cooked
75230- Sauerkraut, cooked/canned
7523 1 - Snowpeas. cooked
75232- Seaweed
75233- Summer Squash
7530201 Beans, green string w/tomatoes (assume w/o
fat)
7530202 Beans, green string w/onions. no fat added
7530203 Beans, green string w/chickpeas. cooked, no
tat added
7530204 Beans, green string w/almonds. cooked, no fat
added " .
7530205 Beans, green &, potatoes, cooked, no fat added
75302U6 Beans, green w/pinto beans, cooked, no fat
added
7530207 Beans, green w/spactzel. cooked, no fat added
7530208 Bean salad, yellow &/or green string beans
7530220 Beans, ereen string w/onions. ns as to added
fat
753022 1 Beans, green string w/onions. fat added
7530250 Beans, green & potatoes, ns as to added fat
753025 1 Beans, green & potatoes, fat added
753060 1 Eggplant in torn sauce, cooked, no fat added
7530700 Green peppers & onions, cooked, fat added in
cooking
5
6
June 2000
3B-8
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-% USDA CSFH DATA (CONTINUED)
Food Product
Exposed Vegetables
(continued)
Protected Veg.
•
Food Codes
753 1600 Squash, summer & onions, cooked, no fee added
753 1 60 1 Zucchini w/tom sauce, cooked, no fat added in
cooking
753 1 602 Squash, summer & onions, cooked, fa; added
7540050 Artichokes, stuffed
7540101 Asparagus, creamed or with cheese
75403- Beans, green with sauce
75404- Beans, yellow with sauce
7540601 Bmssel Sprouts, creamed
7540701 Cabbage, creamed
75409- Cauliflower, creamed
75410- Celery/Chiles, creamed
75412- Eggplant, fried, with sauce, etc.
75413- Kohlrabi, creamed
754 1 4- Mushrooms. Okra, fried, stuffed, creamed
7541 80- Squash, baked, fried, creamed, etc.
754 1 822 Chrtstophine. creamed
7S50011 Beans, pickled
7550051 Celery, pickled
7550205 Cauliflower, pickled
755025- Cabbage, pickled
7550301 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweel
7550305 Cucumber pickles, fresh
7550307 Cucumber. Kim Chee
7550308 Eggplant, pickled
75503 1 1 Cucumber pickles, dill, reduced salt
4I1-.412-.
4 1 3- Beans and lentils
414- Soy products
4 15-. 4 1 6- Bean meals
71 85-.
7190- Plantains soups etc.
732- Pumpkin
733- Winter Squash
75 1 0200 Lima Beans, raw
7510550 Cactus, raw
7510960 Com. raw
7512000 Peas, raw
7520070 Aloe vera. juice
752040- Lima Beans, cooked
752041- Lima Beans, canned
7520829 Biiier Melon
752083- Bitter Melon, cooked
7520950 Burdock
752131- Cactus
752160- Com. cooked
752 1 6 1 - Com. yellow, cooked
752162- Corn, while, cooked
752163- Com. canned
7521749 Hominv
752175- Hominy
75223- Peas, cowpeas. field or blackev e. cooked
75224- Peas. green, cooked
75225- Peas, pigeon, cooked
75301- Succotash
753 1 500 Peas &. com. cooked, ns as to added tai
753 1 501 Peas & com. cooked, no fat added
7550314 Cucumber pickles, sweet, reduced salt
7550500 Mushrooms, pickled
7550700 Okra, pickled
75510- Olives
7551101 Peppers, hot
7551 102 Peppers, pickled
755 11 04 Peppers, hot pickled
7551301 Seaweed, pickled
7553500 Zucchini, pickled
756010- Asparagus soup
756012- Cabbage soup
756020- Cauliflower soup, cream of, w/miik
756030- Celery soup
756045 1 Cucumber soup, cream of, w/milk
756046- Gazpacho
75607- Mushroom soup
756 1 20 1 Zucchini soup, cream of. prep w/m ilk
7564700 Seaweed soup
76 1 02- Dark Green Veg., baby
7640 1 - Beans, baby (exct. most soups & mixtures)
7660400 Broccoli &. chicken, baby, strained
766 1150 Green beans & turkey, baby, strained
7731601 Stuffed cabbage w/meat. p.r. (repollo relleno
con came)
773 1 65 1 Stuffed cabbage w/meat &. rice. Syrian dish.
pueno rican style
773 1 660 Eggplant and meat casserole
7756301 Puerto rican stew (sancocho)
Does not include vegetable with meat mixtures.
753 1 502 Peas & com. cooked, fat added'
7531510 Peas & onions, cooked, ns as to added fat
753 1 5 1 1 Peas &. onions, cooked, fat not added
753 1 5 1 2 Peas & onions, cooked, fat added
753 1521 Peas w/mushrooms. cooked, no fat aUded
753 1 525 Cowpeas w/snap beans, cooked, no fat added
in cooking
753 1 530 Peas &. potatoes, cooked, no fat added in
cooking
75402- Lima Beans with sauce
754 1 1 - Com. scalloped, fritter, with cream
7541650 Pea salad
754 1 660 Pea salad with cheese
754 1 7- Peas, with sauce or creamed
7550101 Corn relish
7560401 Com soup, cream of. w/milk
7560402 Com soup, cream of. prepared w/water
7560900 Pea soup, nfs
7560901 Pea soup, prep w/milk
7560802 Pea soup, prepared w/water
7560905 Pea soup, prepared w/water. low sodium
7560906 Pea soup, prepared w/lowfat milk
76205- Squash, vellow. baby
76405- Com. baby
76409- Peas, baby
764 1 1 - Peas, creamed, baby
7650200 Peas and brown rice, baby
7720121 Green plantain w/cracklmss. p.r. (Mofoneo)
77205 1 1 Ripe plantain fritters, p.r. (Pionono)
7720561 Ripe plantainmcat pie. p.r. (Pinon)
Does no! include vegetable with meat mixtures
June 2000
3B-9
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TABLE 3B-i FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-% USDA CSFII DATA (CONTINUED)
Food Product
Root Vegetables
-.
Animal Fat
Butter
Dressing
Margarine
Mayonnaise
Sauce
Food Codes
710-, 71 1-, 712-, 713-. 7)4-, 715-, 716-. 7J7-,
71 80-, 1793-, 71 94-, 7195-, 7196-.
7 1 98- White Potatoes and Puerto Rican St. Veg.
7310- Carrots
73 1 1 1 40 Carrots in sauce
7311200 Carrot chips
734- Sweet potatoes
7510250 Beets, raw
7511150 Garlic, raw
75 1 1 1 80 Jtcama (yambean J, taw
7511250 Leeks, raw
751 17- Onions, raw
7512SOO Radish, raw
7512700 Rutabaga, raw
7512900 Turnip, taw
752080- Beets, cooked
752081- Beets, canned
7521362 Cassava
752 J 740 Garlic, cooked
7521771 Horseradish
7521840 Leek, cooked
7521850 Lotus root
752210- Onions, cooked
7522 ! 1 0 Onions, dehydrated
752220- Parsnips. 'cooked
75227. Radishes, cooked
75228- Rutabaga, cooked
75229- Salsify, cooked
75234- Turnip, cooked
75235- Water Chestnut
FAT CATEGORIES
81201- Bacon grease
81202- Lard
812032- Shortening, animal
813301 t Lard
81 1005- Butter
81101- Butter
81105- Butter
81204- Clarified butter
8 1 32200 Honey butter
83100-
83101-
83102-
83103-
83104-
83105-
83106-
831!-
83200-
83201-
81102-
81 103-
81 104-
81106-
83204-
83107-
83108-
8 1 30 1 - Lemon butler sauce
8 1 302- Sauces, various
81312- Tartar sauce
7540501 Beets, harvard
75415- Onions, creamed, fried
754 1 60 1 Parsnips, creamed
754 1 8 1 0 Turnips, creamed
7550021 Beets, pickled
7550309 Horseradish
7551201 Radishes, pickled
7553403 Turnip, pickled
7560 1 1 0 Beet soup (borscht)
756050 1 Leek soup, cream of, prep w/mi Ik
7560503 Leek soup, made from dry mix
7560801 Onion soup, cream of, prep w/miik
7560803 Onion soup, cream of, canned, undiluted
75608 1 0 Onion soup, french
7560820 Onion soup, made from dry mix
7560830 Onion soup, dry mix. not reconstituted
76201- Carrots, baby
76209- Sweet potatoes, baby
76403- Beets, baby
7642000 Potatoes, baby
7660200 Carrots & beef. baby, strained
7712101 Fried stuffed potatoes, p.r. (Rellenos de papas)
77 1 2 1 1 1 Potato & ham fritters, p.r. (frituras de papa y
jamon)
77 1 4 1 0 1 Potato chicken pie. p.r. (Pastelon de polio)
7723021 Cassava pasteies. p.r (Pasteles deyuca)
772305 1 Cassava pie stuffed w/crab meat. p. r.
772501 1 Stuffed tannier fritters, p.r. (Alcapurrias)
772507 1 Tannier fritters, p.r. (Frituras de yautia)
Does not include vegetable with meat mixtures.
83202-
83203-
83205-
83206-
83207-
83208-
83209-
83210-
83220-
2
3
7
8
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFH DATA (CONTINUED)
Food Product
Vegetable Oil
Food Codes
812031-
81324-
8133021
82101-
82102-
82103-
Shonening, vegetable
Lechithin
Adobe fresco
Vegetable oil
Corn oil
Cottonseed & flax seed oil
82104-
82105-
82106-
82107-
82108-
82109-
Olive oil
Peanut, rapcseed, & canola oil
Safflower oil
Sesame oil
Soy and sunflower oil
Wheat eerm oil •
June 2000
3B-11
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1
2
3
4
APPENDIX 3C
SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED
ON CDC (1994) DATA
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1 Sample Calculation of Mean Daily Fat Intake Based on CDC (1994) Data
2
3 CDC (1994) provided data on the mean daily total food energy intake (TFEI) and the mean
4 percentages of TFEI from total dietary fat grouped by age and gender. The overall mean daily TFEI
5 was 2,095 kcal for the total population and 34 percent (or 82 g) of their TFEI was from total dietary
6 fat (CDC, 1 994). Based on this information, the amount of fat per kcal was calculated as shown in
7 the following example.
8
9
day day day
11
12
13 .-. X = 0.12 g" f
kcal
14
15
16 where 0.34 is the fraction of fat intake, 2,095 is the total food intake, and X is the conversion factor
17 from kcal/day to g-fat/day.
18
19 Using the conversion factor shown above (i.e., 0.12 g-fat/kcal) and the information on the mean
20 daily TFEI and percentage of TFEI for the various age/gender groups, the daily fat intake was
21 calculated for these groups. An example of obtaining the grams of fat from the daily TFEI
02 (1,591 kcal/day) for children ages 3-5 and their percent TFEI from total dietary fat (33 percent) is
23 as follows:
24
25
26 1,591 x 0.33 x 0.12
day kcal day
June 2000 3C-1 DRAFT-DO NOT QUOTE OR CITE
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1 APPENDIX 3D
2
3 FOOD CODES AND DEFINITIONS USED IN ANALYSIS
' 4 OF THE 1987-88 USDA NFCS DATA
5 .
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1
2
4
15
6
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA
Food
Product
Household Code/Definition
Individual Code
7
8
10
11
MAJOR FOOD GROUPS
Total Fruits SO- 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)
Total 48- Potatoes. Sweetpotaioes
Vegetables 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)
Total Meats 44- Meal
beef
pork
veal
lamb
mutton
goat
game
lunch meat
mixtures
451-Poultry
(does not include soups, sauces, gravies, mixtures, and ready-
to-cat dinners: includes baby foods except mixtures)
Total Dairy' 40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and ready-
to-eai dinners)
Total Fish 452- Fish. Shellfish
various species
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and rcady-
to-eat dinners)
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
(includes baby foods)
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)
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)
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, vogun. 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)
June 2000
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1
2
3
4
6
7
Food
Product
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Household Code/Definition
Individual Code
White
Potatoes
Peppers
Onions
INDIVIDUAL FOODS
4811- White Potatoes, fresh
4821 - White Potatoes, commercially canned
4831- White Potatoes, commercially frozen
4841- White Potatoes, dehydrated
48S1- While Potatoes, chips, sticks, salad
(does not include soups, sauces, gravies, mixtures- and ready-
to-eat dinners)
4913- Green/Red Peppers, fresh
5111201 Sweet Green Peppers, commercially canned
5112202 Hot Chili Peppers, commercially canned
521130! 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)
4953- Onions, Garlic, fresh
onions
chives
garlic
feeks
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
54131J 0 Onion Flakes, dried
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
71- White Potatoes and PR Starchy Veg.
baked, boiled, chips, sticks, creamed, scalloped, au
gratin, fried, mashed, stuffed, puffs, salad, recipes,
soups, Puerto Rican starchy vegetables
(does not include vegetables soups: vegetable mixtures: or
vegetable with meat mixtures)
7512100 Pepper, hot chili, raw
7512200 Pepper, raw
75J2210 Pepper, sweet green, raw
7512220 Pepper, sweet red, raw
7522600 Pepper, green, cooked. NS as to fat added
7522601 Pepper, green, cooked, fat not added
7522602 Pepper, green, cooked, fat added
7522604 Pepper, red. cooked. NS as to fat added
7522605 Pepper, red, cooked, fai not added
7522606 Pepper, red. cooked, fat added
7522609 Pepper, hot cooked. NS as to fat added
7522610 Pepper, hot. cooked, fat not added
7522611 Pepper, hot cooked, fat added
7551101 Peppers, hot. sauce
7551102 Peppers, pickled
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
7510950 Chives, raw
7511150 Garlic, raw
7511250 Leek, raw
7511701 Onions, young green, raw
7511702 Onions, mature
7521550 Chives, dried
7521740 Garlic, cooked
7522100 Onions, mature cooked, NS as to fat added
7 522101 Onions, mature cooked, fat not added
7522102 Onions, mature cooked, fat added
7522103 Onions, pearl cooked
7522104 Onions, young green cooked, NS as to fat
7522105 Onions, young green cooked, fat not added
7522106 Onions, young green cooked, fat added
7522510 Onion, dehydrated
7541501 Onions, creamed
10 Com 4956- Com, fresh 7510960
5114601 Yellow Com. commercially canned 7521600
5114602 White Com. commercially canned 7521601
5114603 Yellow Creamed Com. commercially canned 7521602
5114604 White Creamed Com. commercially canned 7521605
5114605 Com on Cob. commercially canned 7521607
5114607 Hominy, canned 7521610
5115306 Low Sodium Com. commercially canned 7521611
5115307 Low Sodium Cr. Com, commercially canned 752i612
521350! Yellow Com on Cob. commercially frozen 7521615
5213502 Yellow Com off Cob, commercially frozen 7521616
5213503 Yell. Com with Sauce, commercially frozen 7521617
5213504 Com with other Veg.. commercially frozen 7521618
5213505 White Com on Cob. commercially frozen 7521619
5213506 White Com off Cob. commercially frozen 7521620
Com. raw
Com, cooked. NS as to color/fat added
Com. cooked. NS as to color/fat not added
Com. cooked. NS as to color/fat added
Com, cooked. NS as to color/cream style
Com. cooked, dried
Com. cooked, yellow/NS as to fat added
Com. cooked, yellow/fat not added
Com. cooked, yellow/fat added
Com. yellow, cream style
Com. cooked, yell. & wh./NS as to fat
Com. cooked, yell. & wh./fat not added
Corn, cooked, yell. & wh./fat added
Corn, yellow, cream style, fat added
Com, cooked. white/NS as to fat added
June 2000
3D-2
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1
2
4
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Com (com.)
Apples
Tomatoes
5213507 Wh. Corn with Sauce, commercially frozen
5413104 Com. dried
5413106 Hominy, dry
5413603 Com, instant baby food
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes babv food)
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 Cat., comm. canned
5223101 Apple Slices, commercially frozen
5332101 Apple Juice, canned
5332102 Apple Juice, baby. Comm. canned
5342201 Apple J u i ce. comm. frozen
5342202 Apple Juice, home frozen
5352101 Apple Juice, aseptically packed
5362101 Apple Juice, fresh
5423101 Apples, dried
(includes baby food: except mixtures)
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
537! - Fresh Tomato Juice
5581102 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)
7521621 Com. cooked, white/fat not added
7521622 Com. cooked, white/fat added
7521625 Com. white, cream style
7521630 Com. yellow, canned, low sodium. NS fat
7521631 Com, yell., canned, low sod., fat not add
7521632 Com. yell., canned, low sod., fat added
7521749 Hominy, cooked
752175- Hominy, cooked
7541101 Com scalloped or pudding
7541102 Com fritter
7541103 Com with cream sauce
7550101 Com relish
76405- Com. baby
(does not include vegetable soups: vegetable mixtures: or
vegetable with meal mixtures: includes baby food)
6210110 Apples, dried, uncooked
6210115 Apples, dried, uncooked, low sodium
6210120 Apples, dried, cooked. NS as to sweetener
6210122 Apples, dried, cooked, unsweetened
6210123 Apples, dried, cooked, with sugar
6310100 Apples, raw
631011! Applesauce. NS as to sweetener
6310112 Applesauce, unsweetened
63! 0113 Applesauce with sugar
6310114 Applesauce with low calorie sweetener
6310121 Apples, cooked or canned with syrup
63 3 0131 Apple, baked NS as to sweetener
63 3 0132 Apple, baked, unsweetened
6310133 Apple, baked with sugar
6310! 41 Apple rings, fried
6310142 Apple, pickled
6310150 Apple, fried
6340101 Apple, salad
6340106 Apple, candied
6410101 Apple cider
6410401 Apple juice
6410405 Apple juice with vitamin C
6710200 Applesauce baby fd., NS as to str. or jr.
6710201 Applesauce baby food, strained
6710202 Applesauce baby food, junior
6720200 Apple juice, baby food
(includes baby food: except mixtures)
74- Tomatoes and Tomato Mixtures
raw. cooked, juices, sauces, mixtures, soups.
sandwiches
June 2000
3D-3
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1
2
3
4
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Snap Beans
Beef
Pork
Game
4943- Snap or Wax Beans, fresh
SI 14401 Green or Snap Beans, commercially canned
5114402 Wax or Yellow Beans, commercially canned
5114403 Beans, baby/jr., commercially canned
5115302 Green Beans, low sodium, comm. canned
5115303 Yell, or Wax Beans, low sod., comm. canned
5213301 Snap or Green Beans, comm. frozen
5213302 Snap or Green w/sauce, comm. frozen
5223303 Snap or Green Beans w/other veg., comm. ft.
5213304 Sp. or Or. 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)
441-Beef
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures)
442-Pork
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures)
445- Variety Meat. Game
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures)
7510180 Beans, string, green, raw
7520498 Beans, string, cooked, NS color/fat added
7520499 Beans, string, cooked, NS color/no fat
7520500 Beans. String, cooked. NS color & fat
752050J Beans, string, cooked, green/NS fat
7520502 Beans, string, cooked, green/no fat
7520503 Beans, string, cooked, green/fat
7520511 Beans, sir., canned, low sod.,green/NS fat
7520512 Beans, str.. canned, low sod.,green/no fat
7520513 Beans, sir., canned, low sod.,green/fat
7520600 Beans, string, cooked, ye!low/NS fat
7520601 Beans, string, cooked, yellow/no fat
7520602 Beans, string, cooked, yellow/fat
7540301 Beans, string, green, creamed
7540302 Beans, string, green, w/mushroom sauce
7540401 Beans, string, yellow, creamed
7550011 Beans, string, green, pickled
7640100 Beans, green, string, baby
7640101 Beans, green, string, baby, str.
7640102 Beans, green, string, baby, junior
7640103 Beans, green, string, baby, creamed
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures: includes baby foods)
21- Beef
beef, nfs
beefsteak
beef oxtails, neckbones, ribs
roasts, stew meat, corned, brisket, sandwich steaks
ground beef, panics, meatballs
other beef items
beef baby food
(excludes meat, poultry, and fish with non-meat items:
frozen plate meals; soups and gravies with meat, poultry
and fish base: and gelatin-based drinks: includes baby
food)
22- Pork
pork, nfs: ground dehydrated
chops
steaks, cutlets
ham
roasts
Canadian bacon
bacon, salt pork
other pork items
pork baby food
(excludes meat, poultry, and fish with non-meat items:
frozen plate meals: soups and gravies with meat, poultry
and fish base: and gelatin-based drinks: includes baby
food)
233-Game
(excludes meat, poultry, and fish with non-meat items:
frozen plate meals: soups and gravies with meat, poultry
and fish base: and gelatin-based drinks)
June 2000
3D-4
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2
3
4
Food
Product
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Household Code/Definition
Individual Code
Poultry
Eggs
Broccoli
Carrots
Pumpkin
10
Asparagus
11
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
52112- Comm. Frozen Broccoli
(does not include soups, sauces, gravies, mixtures, and ready-
to-cat 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)
Lima Beans 4942-
Fresh Lima and Fava Beans (and home
canned/froz.)
5114204 Comm. Canned Mature Lima Beans
511430I Comm. Canned Green Lima Beans
5115304 Comm. Canned Low Sodium Lima Beans
52132- Comm. Frozen Lima Beans
54111 - Dried Lima Beans
5411306 Dried Fava Beans
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures: does not
include succotash)
24- Poultry
chicken
turkey
duck"
other poultry
poultry baby food
(excludes meat, poultry, and fish with non-meat items:
frozen plate meals: soups and gravies with meat, poultry
and fish base; and gelatin-based drinks: includes baby
food)
3- Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
(includes baby foods)
722- Broccoli (all forms)
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
7310- Carrots (all forms)
7311140 Carrots in Sauce
7311200 Carrot Chips
76201- Carrots, baby
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures: includes baby foods except
mixtures)
732- Pumpkin (all forms)
733- Winter squash (all forms)
76205- Squash, baby
(does not include vegetable soups: vegetables mixtures: or
vegetable with meat mixtures: includes baby foods)
7510080 Asparagus, raw
75202- Asparagus, cooked
7540101 Asparagus, creamed or with cheese
(does not include vegetable soups: vegetables mixtures, or
vegetable with meat mixtures)
7510200 Lima Beans, raw
752040- Lima Beans, cooked
752041 - ima Beans, canned
75402- Lima Beans with sauce
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures: does not include succotash)
June 2000
3D-5
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1
2
3
4
Food
Product
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Household Code/Definition
Individual Code
Cabbage
Lettuce
Okra
Peas
Cucumbers
4944- Fresh Cabbage (and home canned/froz.)
4958601 Sauerkraut home canned or pksd
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)
51! 5314 Low Sod. Blackeye. Gr. or 1mm. Peas (canned)
5114205 Blackeyed 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)
7510300 Cabbage, raw
7510400 Cabbage, Chinese, raw
7510500 Cabbage, red. raw
7514100 Cabbage salad or coleslaw
7514130 Cabbage, Chinese, salad
75210- Chinese Cabbage, cooked
75211 - Green Cabbage, cooked
75212- Red CabbageT cooked
752130- Savoy Cabbage, cooked
75230- Sauerkraut, cooked
7540701 Cabbage, creamed
755025- Cabbage, pickled or in relish
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
75113- Lettuce, raw
75143- Lettuce salad with other veg.
7514410 Lettuce, wilted, with bacon dressing
7522005 Lettuce, cooked
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
7522000 Okra. cooked. NS as to fat
7522001 Okra. cooked, fat not added
7522002 Okra. cooked, fat added
7522010 Lufta. cooked (Chinese Okra)
7541450 Okra. fried
7550700 Okra. pickled
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
7512000 Peas, green, raw
7512775 Snowpeas. raw
75223- Peas, cowpeas. field or blackeye. cooked
75224- Peas, green, cooked
75225- Peas, pigeon, cooked
75231- Snowpeas. cooked
7541650 Pea salad
7541660 Pea salad with cheese
75417- Peas, with sauce or creamed
76409- Peas, baby
76411- Peas, creamed, baby
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures: includes baby foods except
mixtures)
7511100 Cucumbers, raw
75142- Cucumber salads
752167- Cucumbers, cooked
7550301 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweet
7550305 Cucumber pickles, fresh
7550307 Cucumber. Kim Chee '
7550311 Cucumber pickles, dill, reduced salt
7550314 Cucumber pickles, sweet, reduced salt
(does not include vegetable soups: vegetable mixtures: or
vegetable with meat mixtures)
June 2000
3D-6
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1
2
4
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
food
Product
Beets
Household Code/Definition
4954- Fresh Beets (and home canned/froz.)
51 145- Comm. Canned Beets (incl. baby)
5 1 1 5305 Low Sodium Beets (canned)
52 1 37 1 4 Comm. Frozen Beets
5312104 Beet Juice
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures)
individual Code
7510250 Beets, raw
752080- Beets, cooked
752081- Beets, canned
7540501 Beets, harvard
7550021 Beets, pickled
76403- Beets, baby
(does not include vegetable soups: vegetable mixtures: or
8
Strawberries 5022- Fresh Strawberries
5122801 Comm. Canned Strawberries with sugar
5122802 Comm. Canned Strawberries without sugar
5122803 Canned Strawberry Pie Filling
5222- Comm. Frozen Strawberries
(does not include ready-to-eat dinners: includes baby foods
except mixtures)
Other 5033- Fresh Berries Other than Strawberries
Berries 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)
5423114 Dried Berries (not strawberries) ^
(does not include ready-to-eat dinners; includes baby foods
except mixtures)
10
11
12
13
vegetable with meat mixtures: includes baby foods except
mixtures)
6322- Strawberries
6413250 Strawberry Juice
(includes baby food: except mixtures)
6320-
6321-
634)101
6410460
641OS-
Other Berries
Other Berries
Cranberry salad
Blackberry' Juice
Cranberry Juice
(includes baby food: except mixtures)
Peaches
Pears
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)
5037- Fresh Pears
5 1225- Comm. Canned Pears (incl. baby)
5332403 Comm. Canned Pear Juice, babv
5362204 Fresh Pear Juice
5423107 Dried Pears
(does not include ready-to-eat dinners: includes baby foods
except mixtures)
62116- Dried Peaches
63135- Peaches
6412203 Peach Juice
6420501 Peach Nectar
67108- Peaches;baby
67 1 1450 Peaches, dry, baby
(includes baby food: except mixtures)
62119- Dried Pears
63137- Pears
6341201 Pear salad
6421501 Pear Nectar
67109- Pears, baby
6711455 Pears, dry, baby
(includes baby food: except mixtures)
EXPOSED/PROTECTED FRUITSA'EGETABLES, ROOT VEGETABLES
Exposed
Fruits
5022- Strawberries, fresh
5023101 Acerola, fresh
5023401 Currants, fresh
5031- Apples/ Applesauce, fresh
5033- Berries other than Strawberries, fresh
5034- Cherries, fresh
5036- Peaches, fresh
62101- Apple, dried
62104- Apricot, dried
62108- Currants, dried
62110- Date, dried
62116- Peaches, dried
621 19- Pears, dried
62121- Plum, dried
June 2000
3D-7
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6
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Exposed
Fruits
(com.)
•
Household Code/Definition
5037- Pears, fresh
5038 1 - Apricots, Nectarines, Loquats, fresh
5038305 Dates, fresh
50384- Grapes, fresh
50386- Plums, fresh
50387- Rhubarb, fresh
5038805 Persimmons, fresh
5038901 Sapote, fresh
51221- Apples/Applesauce, canned
51222- Apricots, canned
51223- Cherries, canned
51224- Peaches, canned
51225- Pears, canned
5 i 228- Berries, canned
5 1 22903 Grapes with sugar, canned
5122904 Grapes without sugar, canned
5 122905 Plums with sugar, canned
5122906 Plums without sugar, canned
5122907 Plums, canned, baby
512291 1 Prunes, canned, baby
5 1 229 1 2 Prunes, with sugar, canned
5 1 229 1 3 Prunes, without sugar, canned
5122914 Raisin Pie Filiing
5222- Frozen Strawberries
5223 1- Apples Slices, frozen
52233- Berries, frozen
52234- Cherries, frozen
52236- Peaches, frozen
52239- Rhubarb, frozen
5332 1 - Canned Apple Juice
53322- Canned Grape Juice
5332402 Canned Prune Juice
5332403 Canned Pear Juice
5332404 Canned Blackberry- Juice
5332405 Canned Peach Juice
5342 1 - Frozen Grape Juice
5342201 Frozen Apple Juice, comm. fr.
5342202 Frozen Apple Juice, home fr.
5352101 Apple Juice, asep. packed
5352201 Grape Juice, asep. packed
5362101 Apple Juice, fresh
5362202 Apricot Juice, fresh
5362203 Grape Juice, fresh
5362204 Pear Juice, fresh
5362205 Prune Juice, fresh
5421- Dried Prunes
5422- Raisins. Currants, dried
5423101 Dry' Apples
5423102 Dry Apricots
5423103 Dates without pits
5423104 Dates with pits
5423105 Peaches, dry, baby
5423106 Peaches, dry
5423 1 07 Pears, dry
5423114 Berries, dry
5423115 Cherries, drv
Individual Code
62122- Prune, dried
62125- Raisins
63 1 0 1 - Apples/applesauce
63102- Wi-apple
63103- Apricots
63111- Cherries, maraschino
63112- Aceroia
63 i 1 3- Cherries, sour
63 1 i 5- Cherries, sweet
63 1 i 7- Currants, raw
63123- Grapes
6312601 Juneberry
63131- Nectarine
63135- Peach
63137- Pear
63139- Persimmons
63143- Plum
63146- Quince
63 1 47- Rhubarb/Sapodillo
632- Berries
64101- Apple Cider
64104- Apple Juice
64 1 05- Cranberry J uice-
64116- Grape Juice
64122- Peach Juice
64132- Prune/Strawberry Juice
6420 1 0 1 Apricot Nectar
64205- Peach Nectar
64215- Pear Nectar
67102- Applesauce, baby
67108- Peaches, baby
67109- Pears, baby
6711450 Peaches, baby, dry
6711455 Pears, baby, dry
67202- Apple Juice, baby
6720380 White Grape Juice, baby
67212- Pear Juice, baby
(includes baby foods/juices except mixtures: excludes
fruit mixtures)
8
9
10
(includes baby foods)
Protected 501 - Citrus Fruits, fresh
Fruits 5021- Cantaloupe, fresh,
5023201 Mangoes, fresh
5023301 Guava. fresh
61 - Citrus Fr.. Juices (incl. cit. juice mixtures)
62107- Bananas, dried
62113- Figs, dried
62114- Lychees/Papayas. dried
June 2000
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4
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
8
9
Protected 502360! Kiwi, fresh
Fruits S023701 Papayas, fresh
(cont.) 502380! Passion Fruit fresh
5032- Bananas, Plantains, fresh
5035- Melons other than Cantaloupe, fresh
50382- Avocados, fresh
5038301 Figs, fresh
5038302 Figs, cooked
5038303 Figs, home canned
5038304 Figs, home frozen
50385- Pineapple, fresh
5038801 Pomegranates, fresh
5038902 Cherimoya. fresh
,5038903 Jackfruit, fresh
5038904 Breadfruit, fresh
5038905 Tamarind, fresh
5038906 Carambola. fresh
5038907 Longan. fresh
5121- Citrus, canned
51226- Pineapple, canned
5122901 Figs with sugar, canned
5122902 Figs without sugar, canned
5122909 Bananas, canned, baby
5122910 Bananas and Pineapple, canned; baby
5122915 Litchis. canned
5122916 Mangos with sugar, canned
5122917 Mangos without sugar, canned
5122918 Mangos, canned, baby
5122920 Guava with sugar, canned
5122921 Guava without sugar, canned
5122923 Papaya with sugar, canned
5122924 Papaya without sugar, canned
52232- Bananas, frozen
52235- Melon, frozen
52237- Pineapple, frozen
5331 - Canned Citrus Juices
53323- Canned Pineapple Juice
5332408 Canned Papaya Juice
5332410 Canned Mango Juice
5332501 Canned Papaya Concentrate
5341- Frozen Citrus Juice
5342203 Frozen Pineapple Juice
5351- Citrus and Citrus Blend Juices, asep. packed
5352302 Pineapple Juice, asep. packed
5361 - Fresh Citrus and Citrus Blend Juices
53 62206 Papaya J u ice. fresh
5362207 Pineapple-Coconut Juice, fresh
5362208 Mango Juice, fresh
5362209 Pineapple Juice, fresh
5423108 Pineapple, dry
5423109 Papaya, dry
5423110 Bananas, dry
5423111 Mangos, dry
5423117 Litchis, dry
5423118 Tamarind, dry
5423119 Plantain, dry
(includes baby foods)
Exposed 49! - Fresh Dark Green Vegetables
Vegetable 493- Fresh Tomatoes
4941- Fresh Asparagus
4943- Fresh Beans. Snap or Wax
62120- Pineapple, dried
62126- Tamarind, dried
63105- Avocado, raw
63107- Bananas
63109- Cantaloupe. Carambola
63110- Cassaba Melon
63119- Figs
63121- Genip
63125- Guava/Jackfruit. raw
6312650 Kiwi
6312651 Lychee, raw
6312660 Lychee, cooked
63127- Honeydew
63129- Mango
63133- Papaya
63134- Passion Fruit
63141- Pineapple
6314 5 - Pomegranate
63148- Sweetsop. Soursop. Tamarind
63149- Watermelon
64120- Papaya Juice
64121- Passion Fruit Juice
64124- Pineapple J uice
64133- Watermelon Juice
6420150 Banana Nectar
64202- Cantaloupe Nectar
64203- Guava Nectar
64204- Mango Nectar
64210- Papaya Nectar
64213- Passion Fruit Nectar
64221 - Soursop Nectar
6710503 Bananas, baby
6711500 Bananas, baby, dry
6720500 Orange Juice, baby
6721300 Pineapple Juice, baby
(includes baby foods/juices except mixtures: excludes fruit
mixtures)
721- Dark Green Leafy Veg.
722- Dark Green Nonleafy Veg.
74- Tomatoes and Tomato Mixtures
7510050 Alfalfa Sprouts
June 2000
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1
2
3
4
5
6
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product Household Code/Definition
Exposed 4944- Fresh Cabbage
Vegetable 4945- Fresh Lettuce
(cont.) 4946- Fresh Okra
49481- Fresh Artichokes
49483- Fresh Brussel Sprouts
4951 -Fresh Celery
4952- Fresh Cucumbers
4955- Fresh Cauliflower
4958103 Fresh Kohlrabi
4958 1 II Fresh Jerusalem Artichokes
49581 12 Fresh Mushrooms
4958 1! 3 Mushrooms! home canned
49581 14 Mushrooms, home frozen
4958118 Fresh Eggplant
4958119 Eggplant cooked
4958120 Eggplant, home frozen
4958200 Fresh Summer Squash
495820 1 Summer Squash, cooked
4958202 Summer Squash, home canned
4958203 Summer Squash, home frozen
4958402 Fresh Bean Sprouts
4958403 Fresh Alfalfa Sprouts
4958504 Bamboo Shoots
4958506 Seaweed
4958508 Tree Fern, fresh
4958601 Sauerkraut
51 1 1- Dark Green Vegetables (all are exposed)
51 13- Tomatoes
5114101 Asparagus, comm . canned
5 ! 144- Beans, green, snap, yellow, comm. canned
5 1 1 4704 Snow Peas. comm. canned
5114801 Sauerkraut, comm. canned
5114901 Artichokes, comm. canned
5 1 1 4902 Bamboo Shoots, comm. canned
5 1 14903 Bean Sprouts, comm. canned
5 1 14904 Cabbage, comm. canned
5 1 14905 Cabbage, comm. canned, no sauce
5 1 14906 Cauliflower, comm. canned, no sauce
51 14907 Eggplant, comm. canned, no sauce
5 1 14913 Mushrooms, comm. canned
5114914 Okra. comm. canned
5 11 49 1 8 Seaweeds, comm. canned
51 14920 Summer Squash, comm. canned
5 1 14923 Chinese or Celery Cabbage, comm. canned
5 1 ! 52- Tomatoes, canned, low sod.
5 1 1 5301 Asparagus, canned, low sod.
5 1 15302 Beans. Green, canned, low sod.
5 1 1 5303 Beans. Yellow, canned, low sod.
5 1 1 5309 Mushrooms, canned, low sod.
5 1 1 54- Greens, canned, low sod.
51 15501 Sauerkraut, low sodium
521 1- Dark Gr. Veg.. comm. frozen (all exp.)
52131- Asparagus, comm. froz.
52133- Beans, snap, green, yellow, comm. froz.
52 1 3407 Peapods. coram froz.
52 13408 Peapods. with sauce, comm froz.
52 !3409 Peapods. with other veg.. comm froz.
5213701 Brussel Sprouts, comm. froz.
5213702 Brussel Sprouts, comm. froz. with cheese
5213703 Brussel Sprouts, comm. froz. with other veg.
5213705 Cauliflower, comm. froz.
7510075
7510080
75101-
7510275
7510280
7510300
7510400
7510500
7510700
7510900
7510950
7511100
7511120
7511200
75113-
7511500
7511900
7512100
75122-
7512750
7512775
75128-
7513210
7514100
7514130
7514150
- 75142-
75143-
7514410
7514600
75 i 4700
7520600
75201-
75202-
75203-
752049-
75205-
75206-
75207-
752085-
752090-
75210-
75211-
75212-
752130-
75214-
75215-
752167-
752170-
752171-
752172-
752173-
7521801
75219-
75220-
7522116
7522121
75226-
75230-
75231-
75232-
lodividual Code
Artichoke, Jerusalem, raw
Asparagus, raw
Beans, sprouts and green, raw
Brussel Sprouts, raw
Buckwheat Sprouts, raw
Cabbage, raw
Cabbage. Chinese, raw
Cabbage. Red. raw
Cauliflower, raw
Celery, raw
Chives, raw
Cucumber, raw
Eggplant, raw
Kohlrabi, raw
Lettuce, raw
Mushrooms, raw
Parsley
Pepper, hot chili
Peppers, raw
Seaweed, raw
Snowpeas. raw
Summer Squash, raw
Celery Juice
Cabbage or cole slaw
Chinese Cabbage Salad
Ceiery with cheese
Cucumber salads
Lettuce salads
Lettuce, wilted with bacon dressing
Greek salad
Spinach salad
Algae, dried
Artichoke, cooked
Asparagus, cooked
Bamboo shoots, cooked
Beans, string, cooked
Beans, green, cooked/canned
Beans, yellow, cooked/canned
Bean Sprouts, cooked
Breadfruit
Brussel Sprouts, cooked
Cabbage. Chinese, cooked
Cabbage, green, cooked
Cabbage, red. cooked
Cabbage, savoy, cooked
Cauliflower
Celery. Chives. Christophine (chayote)
Cucumber, cooked
Eggplant, cooked
Fem shoots
Fern shoots
Flowers of sesbania, squash or lily
Kohlrabi, cooked
Mushrooms, cooked
Okra/lettuce. cooked
Palm Hearts, cooked
Parsley, cooked
Peppers, pimento, cooked
Sauerkraut, cooked/canned
Snowpeas. cooked
Seaweed
June 2000
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1
2
4
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Exposed 5213706 Cauliflower, comm. froz. with sauce
Vegetable 5213707 Cauliflower, comm. froz. with other veg.
(conL) 5213708 Caul., comm. froz. with other veg. & sauce
5213709 Summer Squash, comm. froz.
5213710 Summer Squash, comm. froz. with other veg.
5213716 Eggplant, comm. froz.
5213718 Mushrooms with sauce, comm. froz.
5213719 Mushrooms, comm. froz.
5213720 Okra, comm. froz.
5213721 Okra, comm. froz., with sauce
5311 - Canned Tomato Juice and Tomato Mixtures
5312102 Canned Sauerkraut Juice
5321 - Frozen Tomato Juice
5371- Fresh Tomato Juice
5381102 Asepticaily Packed Tomato Juice
5413101 DryAlaae
5413102 DryCelery
5413103 Dry Chives
5413109 Dry Mushrooms
5413111 Dry Parsley
54131 i 2 Dry Green Peppers
5413113 Dry Red Peppers
5413114 Dry-Seaweed
5413115 Dry Tomatoes
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures)
8
9
Protected 4922- Fresh Pumpkin, Winter Squash
Vegetable 4942- Fresh Lima Beans
4947- Fresh Peas
49482- Fresh Soy Beans
4956- Fresh Com
4958303 Succotash, home canned
4958304 Succotash, home frozen
4958401 Fresh Cactus (prickly pear)
4958503 Burdock
4958505 Bitter Melon
4958507 Horseradish Tree Pods
51122- Comm. Canned Pumpkin and Squash (baby)
51142- Beans, comm. canned
51143- Beans. lima and soy. comm. canned
51146- Com. comm. canned
5114701 Peas, green, comm. canned
5114702 Peas, baby. comm. canned
5114703 Peas, blackeye, comm. canned
5114705 Pigeon Peas, comm. canned
51!4919 Succotash, comm. canned
5115304 Lima Beans, canned, low sod.
5115306 Com, canned, low sod.
5115307 Creamed Com. canned, low sod.
511531 - Peas and Beans, canned, low sod.
75233- Summer Squash
7540050 Artichokes, stuffed
7540101 Asparagus, creamed or with cheese
75403- Beans, green with sauce
75404- Beans, yellow with sauce
7540601 Brussel Sprouts, creamed
7540701 Cabbage, creamed
75409- Cauliflower, creamed
75410- Celery/Chiles, creamed
75412- Eggplant, fried, with sauce, etc.
75413- Kohlrabi, creamed
75414- Mushrooms. Okra. fried, stuffed, creamed
754180- Squash, baked, fried, creamed, etc.
7541822 Christophme. creamed
7550011 Beans, pickled
7550051 Celery, pickled
7550201 Cauliflower, pickled
755025- Cabbage, pickled
7550301 Cucumber pickles, dill
7550302 Cucumber pickles, relish
7550303 Cucumber pickles, sour
7550304 Cucumber pickles, sweet
7550305 Cucumber pickles, fresh
7550307 Cucumber. Kim Chee
7550308 Eggplant, pickled
7550311 Cucumber pickles, dill, reduced salt
7550314 Cucumber pickles, sweet, reduced salt
7550500 Mushrooms, pickied
7550700 Okra, pickled
75510- Olives
7551101 Peppers, hot
7551102 Peppers.ptckled
7551301 Seaweed, pickled
7553500 Zucchini, pickled
76102- Dark Green Veg., baby
76401 - Beans, baby (excl. most soups & mixtures)
732- Pumpkin
733- Winter Squash
7510200 Lima Beans, raw
7510550 Cactus, raw
7510960 Com, raw
7512000 Peas, raw
7520070 Aloe vera juice
752040- Lima Beans, cooked
752041- Lima Beans, canned
7520829 Bitter Melon
752083- Bitter Melon, cooked
7520950 Burdock
752131- Cactus
752160- Cora, cooked
752161- Corn, yellow, cooked
752162- Com. white, cooked
752163-. Com. canned
7521749 Hominy
752175- Hominy
75223- Peas, cowpeas. field or blackeye, cooked
75224- Peas, green, cooked
75225- Peas, pigeon, cooked
7530!- Succotash
75402- Lima Beans with sauce
June 2000
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1
2
3
4
6
7
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA MFCS DATA (cont'd)
Food
Product
Protected
Vegetable
(com.)
Rooted
Vegetable
Household Code/Definition
S2122- Winter Squash, comm. froz.
52132- Lima Beans, comm. froz.
52 1 340 1 Peas, gr., comm. froz.
52 13402 Peas, gr., with sauce, comm. froz.
52 1 3403 Peas. gr., with other veg.. comm. froz.
52 13404 Peas, gr,, with other veg., comm. froz.
5213405 Peas, blackeye, comm froz.
5213406 Peas, blackeye, with sauce, comm froz.
52135- Com, comm. froz.
52 1 37 1 2 Artichoke Hearts, comm. froz.
5213713 Baked Beans, comm. froz.
5213717 Kidney Beans, comm. froz.
5213724 Succotash, comm. froz.
541 1- Dried Beans
54 1 2- Dried Peas and Lentils
5413104 Dry Corn
5413106 DryHominv
5413504 Dry Squash, baby
54 1 3603 Dry Creamed Com. baby
(does not include soups, sauces, gravies, mixtures, and feady-
to-eat dinners; includes baby foods except mixtures)
4g- Potatoes. Sweetpotatoes
4921- Fresh Carrots
4953- Fresh Onions. Garlic
4954- Fresh Beets
4957- Fresh Turnips
4958101 Fresh Celeriac
4958102 Fresh Horseradish
4958 1 04 Fresh Radishes, no greens
4958 1 05 Radishes, home canned
4958 1 06 Radishes, home frozen
4958 1 07 Fresh Radishes, with greens
4958108 Fresh Salsify
4958109 Fresh Rutabagas
4958110 Rutabagas, home frozen
4958115 Fresh Parsnips
4958 1 1 6 Parsnips, home canned
4958 1 1 7 Parsnips, home frozen
4958502 Fresh Lotus Root
4958509 Ginger Root
4958510 Jicama, including yambean
5 11 2 1 - Carrots, comm. canned
5 1 ! 45- Beets, comm. canned
5 1 1 4908 Garlic Pulp. comm. canned
5 1 1 49 1 0 Horseradish, comm. prep.
51 14915 Onions, comm. canned
5 11 49 1 6 Rutabagas, comm. canned
5114917 Salsj fy, comm. canned
5114921 Turnips, comm. canned
5 1 14922 Water Chestnuts, comm. canned
51151- Carrots, canned, low sod.
5 1 1 5305 Beets, canned, low sod.
5 1 1 5502 Turnips, low sod.
52121- Carrots, comm. froz.
5213714 Beets, comm. froz.
5213722 Onions, comm. froz.
5213723 Onions, comm. froz.. with sauce
5213725 Turnips, comm. froz.
53 1 2 1 03 Canned Carrot J uice
5312104 Canned Beet Juice
5372 102 Fresh Carrot Juice
Individual Code
754 1 1 - Com. scalloped, fritter, with cream
7541650 Pea salad
754 1 660 Pea salad with cheese
75417- Peas, with sauce or creamed
7550101 Com relish
76205- Squash, yellow, baby
76405- Com. baby
76409- Peas, baby
764 1 1 - Peas, creamed, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
7 1 - White Potatoes and Puerto Rican St. Veg.
7310- Carrots
73 1 1 1 40 Carrots in sauce
7311200 Carrot chips
734- Sweetpotatoes
7510250 Beets, raw
7511150 Garlic, raw
75 1 1 1 80 Jicama (yambean), raw
7511250 Leeks, raw
75 117- Onions, raw
7512500 Radish, raw
7512700 Rutabaga, raw
7512900 Turnip, raw
752080- Beets, cooked
75208 1 - Beets, canned
7521362 Cassava
752 i 740 Garlic, cooked
7521771 Horseradish
7521850 Lotus root
752230- Onions, cooked
7522 1 1 0 Onions, dehydrated
752220- Parsnips, cooked
75227- Radishes, cooked
75228- Rutabaga, cooked
75229- Salsify,"cooked
75234- Turnip, cooked
75235- Water Chestnut
754050! Beets, harvard
754 1 5 - On ions, creamed, fried
7 54 1 60 1 Parsnips, creamed
754 1 8 1 0 Turnips, creamed
7550021 Beets, pickled
7550309 Horseradish
7551201 Radishes, pickled
7553403 Turnip, pickled
76201- Carrots, baby
76209- Sweetpotatoes, baby
76403- Beets, baby
(does not include vegetable soups: vegetable mixtures; or
vegetable with meat mixtures)
June 2000
3D-12
DRAFT-DO NOT QUOTE OR CITE
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1
2
4
6
7
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Root
Vegetables
(com.)
Dark Green
Vegetables
11
12
Deep Yellow
Vegetables
13
14
Other
Vegetables
15
Citrus Fruits
16
17
Other
Fruits
5413105 Dry Garlic
5413110 Dry Onion
5413502 Dry Carrots, baby
5413503 Dry Sweet Potatoes, baby
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners; includes baby foods except mixtures)
USDA SUBCATEGORIES
491 - Fresh Dark Green Vegetables
51J1- Comm. Canned Dark Green Veg.
5II54- Low Sodium Dark Green Veg.
52 H - Comm. Frozen Dark Green Veg.
5413111 Dry Parsley
5413112 Dry Green Peppers
5413113 Dry Red Peppers
(does not include soups, sauces, gravies, mixtures, and ready.
to-eat dinners: includes baby foods except mixtures/dinners;
excludes vegetable juices and dried vegetables)
492- Fresh Deep Yellow Vegetables
5112- Comm. Canned Deep Yellow Veg.
51151 - Low Sodium Carrots
5212- Comm. Frozen Deep Yellow Veg.
5312103 Carrot Juice
54135- Dry Carrots. Squash, Sw. Potatoes
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures/dinners;
excludes vegetable juices and dried vegetables)
494- Fresh Light Green Vegetables
495- Fresh Other Vegetables
5114- Comm. Canned Other Veg.
51153- Low Sodium Other Veg.
51155- Low Sodium Other Veg.
5213- Comm. Frozen Other Veg.
5312102- Sauerkraut Juice
5312104- Beet Juice
5411- Dried Beans
5412- Dried Peas, Lentils
541310- Dried Other Veg.
5413114- Dry Seaweed
5413603- Dry Cr. Com. baby
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners: includes baby foods except mixtures/dinners;
excludes vegetable juices and dried vegetables)
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)
62- 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
72-
Dark Green Vegetables
all forms
leafy, nonleafy. dk. gr. veg: soups
73-
Deep Yellow Vegetables
all forms
carrots, pumpkin, squash, sweetpotatoes. dp.
yell. veg. soups
75-
Other Vegetables
all forms
61-
6720500
6720600
6720700
672110
Citrus Fruits and Juices
Orange Juice, baby food
Orange-Apricot Juice, baby food
Orange-Pineapple juice, baby food
Orange-Apple-Banana Juice, baby food
(excludes dried fruits)
5353- Dried Fruits
63 Other Fruits
64 Fruit Juices and Nectars Excluding Citrus
671 Fruits, baby
67202 Apple Juice, baby
67203 Baby Juices
67204 Babv Juices .
June 2000
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1
2
3
4
5
6
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Other Fruits 5362- Aseptically Packed Fruit Juice Other than Ciir.
(com.) 542- Fresh Fruit Juice Other than Citrus Dry Fruits
(includes baby foods: excludes dried fruits)
67212 Baby Juices
67213 Baby Juices
673 Baby Fruits
674 BahviFruits
June 2000
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DRAFT-DO NOT QUOTE OR CITE
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1 4. DRINKING WATER INTAKE
2
3 4.1 INTRODUCTION
4 Drinking water is a potential source of human exposure to toxic substances among
5 children. Contamination of drinking water may occur by, for example, percolation of toxics
6 through the soil to ground water that is used as a source of drinking water; runoff or discharge to
7 surface water that is used as a source of drinking water; intentional or unintentional addition of
8 substances to treat water (e.g., chlorination); and leaching of materials from plumbing systems
9 (e.g., lead). Estimating the magnitude of the potential dose of toxics from drinking water
10 requires information on the quantity of water consumed. The purpose of this section is to
11 describe key published studies that provide information on drinking water consumption (Section
12 - 4.2) among children and to provide recommendations of consumption rate values that should be
13 used in exposure assessments (Section 4.3).
14 Currently, the U.S. EPA uses the quantity 1 L per day for infants (individuals of 10 kg
15 body mass or less) and children as a default drinking water intake rates (U.S. EPA, 1980; 1991).
This rate includes drinking water consumed in the form of juices and other beverages containing
17 tapwater. The National Academy of Sciences (NAS, 1977) estimated that daily consumption of
18 water may vary with levels of physical activity and fluctuations in temperature and humidity. It
19 is reasonable to assume that children engaging in physically-demanding activities or living in
20 warmer regions may have higher levels of water intake.
21 Two studies cited in this chapter have generated data on drinking water intake rates. In
22 general, these sources support EPA's use of 1 L/day as an upper-percentile tapwater intake rate
23 for children under 10 years of age. The studies have reported intake rates for direct and indirect
24 ingestion of water. Direct intake is defined as direct consumption of water as a beverage, while
25 indirect intake, includes water added during food preparation, but not water intrinsic to purchased
26 foods. Data for consumption of various sources (i.e., the community water supply, bottled water,
27 and other sources) are also presented. For the purposes of exposure assessments involving site-
28 specific contaminated drinking water, intake rates based on the community supply are most
29 appropriate. Given the assumption that bottled water, and other purchased foods and beverages
are widely distributed and less likely to contain source-specific water, the use of total water
June 2000 4-1 DRAFT-DO NOT QUOTE OR CITE
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1 intake rates may overestimate the potential exposure to toxic substances present only in local
2 water supplies; therefore, tapwater intake of community water, rather than total water intake, is
3 emphasized in this section.
4 The studies on drinking water intake that are currently available are based on short-term
5 survey data. Although short-term data may be suitable for obtaining mean intake values that are
6 representative of both short- and long-term consumption patterns, upper-percentile values may be
7 different for short-term and long-term data because more variability generally occurs in short-
8 term surveys. It should also be noted that most drinking water surveys currently available are
9 based on recall. This may be a source of uncertainty in the estimated intake rates because of the
10 subjective nature of this type of survey technique.
11 • The distribution of water intakes is usually, but not always, lognormal. Instead of
12 presenting only the lognormal parameters, the actual percentile distributions are presented in this
13 handbook, usually with a comment on whether or not it is lognormal. To facilitate comparisons
14 between studies, the mean and the 90th percentiles are given for all studies where the distribution
15 data are available. With these two parameters, along with information about which distribution
16 is being followed, one can calculate, using standard formulas, the geometric mean and geometric
17 standard deviation and hence any desired percentile of the distribution. Before doing such a
18 calculation one must be sure that one of these distributions adequately fits the data.
19 Other studies based on older data were presented in the Exposure Factors Handbook
20 (U.S. EPA, 1997a).
21
22 4.2 DRINKING WATER INTAKE STUDIES
23 U.S. EPA Office of Water (2000) - Estimated Per Capita Water Ingestion in the United
24 States - The U.S. EPA used data from a U.S. Department of Agriculture (USDA) survey from
25 1994 through 1996 to estimate drinking water ingestion rates by the U.S. population. The
26 Continuous Study of Food Intakes by Individuals (CSFII) is a continuing survey of food
27 consumption habits in the U.S. Over 15,000 persons responded to the study conducted between
28 1994 and 1996 on what they ate and drank over two non-consecutive days (USDA, 1998). The
29 U.S. EPA used the drinking water ingestion data to derive estimates of consumption rates by age
30 groups, gender, water source, vulnerable subsets of the population (i.e.. lactating and pregnant
June 2000 4-2 DRAFT-DO NOT QUOTE OR CITE
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1 women) (U.S. EPA, 2000). The ingestion rates are expressed in both volume (milliliters [ml])
2 per day per person and volume per kilogram (kg) body weight (BW) per day. The purpose of the
3 report was to provide data to assist in estimating human health risks from the ingestion of
4 contaminated or potentially-contaminated drinking water (U.S. EPA, 2000).
5 In the study, the U.S. EPA reported that community water (i.e., tapwater-public water
6 supply) accounts for approximately 75 percent of the mean ingested water (U.S. EPA, 2000).
7 The total water consumption consists of community water supply, bottled water, other sources.
8 and missing sources. Other sources include household wells or cisterns or a spring, either
9 household or community. In addition to these sources, the data also distinguish between direct
10 and indirect water consumption. Direct consumption is water consumed directly from the tap
11 while indirect consumption is water added during final food or beverage preparation in the home
12 or food establishment (e.g., restaurants, school cafeterias). Indirect water does not include water
13 added by the food manufacturer during food processing. Table 4-1 provides the estimates for the
14 mean total direct and indirect water consumption by water source for 1994 to 1996 per person
15 combined for all ages. The estimates also include consumption rates for the 90th percentile and
the 95th percentile plus the upper and lower bounds for each percentile. Table 4-2 shows the
17 estimated total direct and indirect water ingestion by all sources by broad age groups (i.e., <1
18 year, 1-10 years, 11-19 years) and percentiles.
19 The data are broken down into multiple population subsets including children's age
20 groups: less than 1 year, 1 to 10 years, and 11 to 19 years. The data show that although the
21 quantity of water ingested decreases with age, the quantity consumed per unit mass of body
22 weight (BW) increases (U.S. EPA, 2000). For instance, the mean community water consumption
23 is 342 ml per child per day for under 1 year, 400 ml/child/day for 1 to 10 years, and 683
24 ml/child/day for 11 to 19 years. The consumption as a function of unit mass, however, is 46
25 ml/kiiogram (kg) BW/day for under 1 year, 19 ml/kg BW/day for 1 to 10 years, and 12 ml/kg
26 BW/day for 11 to 19 years. The significance of this finding is that although children may be
27 encounter lower overall doses, the younger, vulnerable ages (i.e., infants) have significantly
28 higher dose rates per unit of BW. Tables 4-3 and 4-4 show the daily community water
29 consumption rate estimates by fine and broad age groups in units of mL/day and mL per mass of
^^j30 BW per day. Tables 4-5 and 4-6 present the data for bottled water ingestion.
June 2000 4-3 DRAFT-DO NOT QUOTE OR CITE
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1 , Water consumption rates for other sources of water are compiled in Tables 4-7 and 4-8.
2 These two sources comprise nearly one-quarter of total water consumption. The trend in the data
3 is similar to that shown for community water consumption; that is, the younger ages consume
4 less of these sources of water, but the1 quantity consumed per unit mass of BW increases as the
5 age decreases. Missing water sources have not been included in the summary of water sources
6 because of its negligible quantity. Missing water sources comprise only about one percent of
7 water consumption.
8 The data collected from the CSFII study for the USDA have both strengths and
9 limitations. The strengths lie in the design of the survey in that it was intended to collect a
10 statistically representative sample of the U.S. population (i.e., obtain data from a sufficiently
11 large sample set) and the survey was sufficiently specific in detailing types of food and drink.
12 The large size of the sample population (> 15,000) total and 6,000 children enhances the
13 precision and accuracy of the estimates for the overall population and population subsets. The
14 survey was conducted on non-consecutive days which improves the variance over consecutive
15 days of consumption. In addition, the survey was administered such that an interviewer went
16 through the data collection process for the initial day to show the participants the proper response
17 methodology. The second day of the survey was reported by the participant. The survey also
18 represents the most up-to-date on water consumption and incorporated sufficient parameters to
19 differentiate sources of water, ages, gender, weight, and vulnerable populations. The limitations
20 of the survey involve the short duration of the study and some of the data reporting methods.
21 The short duration (i.e., 2 non-consecutive days), although an advantage over 2 consecutive days,
22 diminishes the precision of an individual's water ingestion rate. The mean for an individual can
23 easily be skewed for numerous reasons. The large number of the sample population would
24 hopefully contribute to greater accuracy, but the precision may still be low. The data reporting
25 did not always support variance estimation for some reported population subsets. As such, the
26 means differences could not always be statistically tested except for the larger population
27 subsets. Therefore, the reported differences were derived empirically instead of statistically.
28 Myers et al. (1999) - Options for Development of Parametric Probability Distributions
29 for Exposure Factors - Myers et al. (1999) presented a system of procedures to fit distributions
30 to selected data from the draft Exposure Factors Handbook (EFH) (U.S. EPA, 1996). The
June 2000
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DRAFT-DO NOT QUOTE OR CITE
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1 system was based on EPA's Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997V).
2 The system was applied to the dataset of total tapwater intake reported in Table 3-7 (Ershow and
3 Cantor, 1989) of the EFH. EFH Table 3-7 data summaries analyzed by Myers et al. (1999)
4 consist of nine estimated percentiles for total daily tapwater intake in mL/kg-day. Only the
5 values for infants, children, and teens are reported here.
6
7 The statistical methodology recommended by Myers et al. (1999) incorporates the
8 following elements:
9
10 1. a dataset and its underlying experimental design.
11 2. a family of models, and
12 3. an approach to inference (e.g., estimation, assessment of fit, and uncertainty analysis).
13
14 The system utilizes a twelve-model hierarchy with the most general model being a five-
15 parameter generalized F distribution with a point mass at zero. The point mass at zero represents
J6 the proportion of nonconsuming or nonexposed individuals. As described in Myers et al. (1999),
17 the 12 models of the generalized F hierarchy were fit to each of the three tapwater datasets (i.e.,
18 three age groups of children) using three different estimation criteria, maximum likelihood
19 estimation (MLE), minimum chi-square estimation (MCS), and weighted least squares (WLS).
20 The Pearson chi-square tests and likelihood ratio tests of goodness-of-fit (GOF) were used.
21 Tables 4-9 and 4-10 present chi-square values and associated p-values for chi-square GOF tests,
22 respectively. As stated in Myers et al. (1999), "In each case the null hypothesis tested is that the
23 data arose from the given type of model. A low p-value casts doubt on the null hypothesis.
24 Clearly, the only model that appears to fit most of the datasets is the five-parameter generalized F
25 distribution with a point mass at zero, referred to as GenF5. According to Table 4-9. the gamma
26 model provides the best fit (smallest chi-square) of the two-parameter models to the data for each
27 individual age groups."
28 Table 4-11 is shown in Myers et al. (1999) and is described there as follows:
29
June 2000 4-5 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
"(This table] summarizes several additional aspects of interest for the tapwater
populations. For each age group shown, the first row (SOURCE=data) is
basically a data summary. Within the first row, the columns labeled N, MEAN,
and SDEV contain the sample size, the sample mean, and the sample standard
deviation. Within the first row, the columns labeled P01, P05, .„, P99 contain the
nominal probabilities .01, .05,..., .99. The values in the first row for MEAN,
SDEV, and the nine nominal probabilities can be thought of as 11 targets that the
models are trying to hit.
The other rows (2nd through 6th rows) within each age group contain results from
fitting four models, including gamma, lognormal and Weibull, using selected
estimation criteria. The model and estimation criterion are indicated by the
variable SOURCE. For instance, SOURCE = gammle indicates the two-
parameter gamma model fit using maximum likelihood estimation. The model
gf5 is the five-parameter generalized F with a point mass at zero. The infants
group does not contain results from the five-parameter generalized F because the
selected model had infinite variance. For the gamma and Weibull models, there
was little difference between the three estimation criteria, and the MLE performed
best overall. For the lognormal model, results from the WLS estimation criterion
are shown in addition to the MLE.
The last three columns contain summary GOF measures. CHIDF is the value of
the chi-square statistic divided by its degrees of freedom. The methods are
ordered with respect to this CHIDF measure. CHIDF is more comparable across
cases involving different degrees of freedom than is the chi-square statistic.
PGOF is the p-value for model goodness-of-fit based on the chi-square test. Low-
values of PGOF, such as PGOF <0.05, cast doubt on the null hypothesis that the
given type of model is correct. Note that maximum likelihood estimation
performed much worse for the lognormal model than the WLS method of
estimation, as determined by CHIDF and PGOF measures.
June 2000
4-6
DRAFT-DO NOT QUOTE OR CITE
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If a two-parameter model must be used for tapwater consumption, then the
gamma model with parameters estimated by maximum likelihood is
3 . recommended. The five-parameter generalized F distribution could be used for
4 sensitivity analyses. The age effect seems sufficiently strong to justify the use of
5 separate age groups in risk assessment."
6
7 4.3. PREGNANT AND LACTATING WOMEN
8 Ershow et al (1991) - Intake of Tapwater and Total Water by Pregnant andLactating
9 Women - Ershow et al. (1991) used data from the 1977-78 USD A NFCS to estimate total fluid
10 and total tapwater intake among pregnant and iactating women (ages 15-49 years). Data for 188
11 pregnant women, 77 Iactating women, and 6,201 non-pregnant, non-lactating control women
12 were evaluated. The participants were interviewed based on 24 hour recall, and then asked to
13 record a food diary for the next 2 days. "Tapwater" included tapwater consumed directly as a
14 beverage and tapwater used to prepare food and tapwater-based beverages. "Total water" was
15 defined as all water from tapwater and non-tapwater sources, including water contained in food.
4M6 Estimated total fluid and total tapwater intake rates for the three groups are presented in Tables
17 4-12 and 4-13, respectively. Lactating women had the highest mean total fluid intake rate (2.24
18 L/day) compared with both pregnant women (2.08 L/day) and control women (1.94 L/day).
19 Lactating women also had a higher mean total tapwater intake rate (1.31 L/day) than pregnant
20 women (1.19 L/day) and control women (1.16 L/day). The tapwater distributions are neither
21 normal nor lognormal, but Iactating women had a higher mean tapwater intake than controls and
22 pregnant women. Ershow et al. (1991) also reported that rural women (n=l,885) consumed more
23 total water (1.99 L/day) and tapwater (1.24 L/day) than urban/suburban women (n=4,581,1.93
24 and 1.13 L/day, respectively). Total water and tapwater intake rates were lowest in the
25 northeastern region of the United States (1.82 and 1.03 L/day) and highest in the western region
26 of the United States (2.06 L/day and 1.21 L/day). Mean intake per unit body weight was highest
27 among Iactating women for both total fluid and total tapwater intake. Total tapwater intake
28 accounted for over 50 percent of mean total fluid in all three groups of women (Table 4-13).
29 Drinking water accounted for the largest single proportion of the total fluid intake for control (30
percent), pregnant (34 percent), and Iactating women (30 percent) (Table 4-14). All other
June 2000 4-7 DRAFT-DO NOT QUOTE OR CITE
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1 beverages combined accounted for approximately 46 percent, 43 percent, and 45 percent of the
2 total water intake for control, pregnant, and lactating women, respectively. Food accounted for
3 the remaining portion of total water intake.
4 This survey has an adequately large size (6,201 individuals) and it is representative of the
5 United States population with respect to age distribution, racial composition, and residential
6 location. The chief limitation of the study is that the data were collected in 1978 and do not
7 reflect the expected increase in the consumption of soft drinks and bottled water or changes in
8 the diet within the last two decades. Since the data were collected for only a three-day period,
9 the extrapolation to chronic intake is uncertain.
10
11 4.4 RECOMMENDATIONS ;
12 The studies described in this section were used in selecting recommended drinking water
13 (tapwater) consumption rates for children. The mean and upper-percentile estimates reported in
14 these studies are reasonably similar. The surveys described here are based on short-term recall
15 which may be biased toward excess intake rates. However, Cantor et al. (1987) noted that
16 retrospective dietary assessments generally produce moderate correlations with "reference data
17 from the past." A summary of the recommended values for drinking water intake rates is
18 presented in Table 4-15.
19 The intake rates, as expressed as liters per day, generally increase with age, and the data are
20 consistent across ages for the studies.
21 A characterization of the overall confidence in the accuracy and appropriateness of the
22 recommendations for drinking water is presented in Table 4-16. The Exposure Factors
23 Handbook (U.S. EPA, 1997a) gave this factor a medium confidence rating. However, the
24 confidence score of the overall recommendations has been increased to high for this report
25 because of the addition of the newer U.S. EPA (2000) study.
June 2000 , 4-8 DRAFT-DO NOT QUOTE OR CITE
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1 4.4 REFERENCES FOR CHAPTER 4
2
3
4 Cantor, K.P.; Hoover, R.; Haitge, P.; Mason, T.J.; Silverman, D.T.; et al. (1987) Bladder cancer, drinking water
5 source, and tapwater consumption. A case-control study. J. Natl. Cancer Inst. 79(6):1269-1270.
6 -
7 Ershow, A.G.; Cantor, K.P. (1989) Total water and tapwater intake in the United States: population-based
8 estimates of quantities and sources. Life Sciences Research Office, Federation of American Societies for
9 Experimental Biology.
10
11 Erschow, A.G.; Brown, L.M.; Cantor, K.P. (1991) Intake of tapwater and total water by pregnant and iactating
12 women. American Journal of Public Health. 81:328-334.
13
14 Myers, L., J. Lashley, and R. Whitmore. (1999) Options for Development of Parametric Probability Distributions
15 for Exposure Factors, submitted to U.S. Environmental Protection Agency, Office of Research and
16 Deveiopment, Washington, D.C., September 30.
17
18 National Academy of Sciences (NAS). (1977) Drinking water and health. Vol. 1. Washington, DC: National
19 Academy of Sciences-National Research Council.
20
21 USD A. (1998) 1994-1996 Continuing survey of food intakes and 1994-1996 diet and health survey.
22
23 U.S. EPA. (1980) U.S. Environmental Protection Agency. Water quality criteria documents; availability. Federal
24 Register, (November 28) 45(231 ):79318-79379.
25
26 U.S. EPA. (1991) National primary drinking water regulations; final rule. Federal Register. 56(20):3526-3597.
~:7 January 30, 1991.
8
29 U.S. EPA. (1996) Exposure Factors Handbook. Washington, DC: Office of Research'and Development, National
30 Center for Environmental Assessment. SAB Review Draft (EPA/600/P-95/002Ba).
31
32 U.S. EPA. (1997a) Exposure Factors Handbook. Washington, DC: Office of Research and Development,
33 (EPA/600/P-95/002F).
34
35 U.S. EPA. (1997b) Risk Assessment Forum. Guiding Principles for Monte Carlo Analysis, (EPA/630/R-97/001).
36
37 U.S. EPA. (2000) Estimated per capita water ingestion in the United States. Washington, DC: Office of Science
38 and Technology, Office of Water.
June 2000 4-9 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
Table 4-12. Total Fluid Intake of Women 15-49 Years Old
Percentile Distribution
Reproductive
Status1
mL/dav
Control
Pregnant
Lactating
mL/kg/day
Control
Pregnant
Lactating
Mean
1940
2076
2242
32.3
32.1
37.0
Standard
Deviation
686
743
658
12.3
11.8
11.6
5
995
1085
1185
15.8
16.4
19.6
10
1172
1236
1434
18.5
17.8
21.8
. 25
1467
1553
1833
23.8
17.8
21.8
50
1835
1928
2164
30.5
30.5
35.1
75
2305
2444
2658
38.7
40.4
45.0
90
2831
3028
3169
48.4
48.9
53.7
95
3186
3475
3353
55.4
53.5
59.2
1 Number of observations: nonpregnant, nonlactating controls (n •
(n = 77).
Source: ErshowetaL, 1991.
• 6,201); pregnant {n = 188); lactating
Table 4-13. Total Tapwater Intake of Women 15-49 Years Old
Reproductive
Status*
mL/dav
Control
Pregnant
Lactating
mUks/dav
Control
Pregnant
Lactating
Mean
1157
1189
1310
19.1
18.3
21.4 -
Standard
Deviation
635
699
591
10.8
10.4
9.8
Percentile Distribution
5
310
274
430
5.2
4.9
7.4
10
453
419
612
7.5
5-9
9.8
25
709
713
855
11.7
10.7
14.8
50
1065
1063
1330
17.3
16.4
20.5
75
1503
1501
1693
24.4
23.8
26.8
90
1983
2191
1945
33.1
34.5
35.1
95
2350
2424
2191
39.1
39.6
37.4
Fraction of dailv fluid intake that is taowater (%)
Control
Pregnant
Lactatina
57.2
54.1
57.0
18.0
18.2
15.8
24.6
21.2
27.4
32.2
27.9
38.0
45.9
42.9
49.5
59.0
54.8
58.1
70.7
67.6
65.9
79.0
76.6
76.4
83.2
83.2
80.5
* Number of observations: nonpregnant, nonlactating controls (n = 6.201): pregnant (n =
Source: Ershoweta!.. 1991.
188); totaling (n = 77).
4-20
-------
Table 4-14. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15-49 Years1
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Control Women
Percentile
Sources
Drinking Water
Milk and Milk Drinks
Other Dairy Products
Meats, Poultry. Fish. Eggs
Legumes, Nuts, and Seeds
Grains and Grain Products
Citrus and Noncitrus Fruit Juices
Fruits, Potatoes, Vegetables, Tomatoes
Fats, Oils, Dressings, Sugars, Sweets
Tea
Coffee and Coffee Substitute;
Carbonated Soft Drinks'
Noncarbonated Soft Drinks'
Beer
Wine Spirits. Liqueurs, Mixed Drinks
All Sources
Mean"
583
162
' 23
126
13
90
57
198
9
148
29!
174
38
17
10
1940
SO
480
107
8
114
0
65
0
17!
3
0
159
110
0
0
0
NA '
95
1440
523
93
263
77
257
234
459
4!
630
1045
590
222
110
66
NA
Mean"
695
308
24
121
18
98
69
212
9
132
197
130
48
7
5
2076
Pregnant Women
Percentile
50
640
273
9
104
0
69
0
185
3
0
0
73
0
0
0
NA
95
1760
749
93
252
88
246
• 280
486
40
617
955
464
257
0
25
NA
Mean"
677
306
36
133
15
119
64
245
10
253
205
117
38
17
6
2242 .
Lactaling Women
Percentile
SO
560
285
27
117
0
82
0
197
6
77
80
57
0
0
0
NA
95
1600
820
113
256
72
387
219
582
50
848
955
440
222
147
59
NA
* Number of observations: nonpregnant, nonlactating controls (n - 6,201): pregnant (n = 188): lactating (n « 77).
' Individual means may not add to all-sources total due to rounding.
1 includes regular, low-caioric, and noncalorie soft drinks,
NA: Not appropriate to sum the columns for the 50th and 95th percentiles of intake.
Source: Ershow et a!., 1991.
4-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 4-15. Summary of Recommended Community Drinking Water Intake Rates
Percemiles
Age Group/
Population
1 -3 years'
1-10 years"
11-19 years"
Pregnant*
Women
Lactating*
Women
"Source: U.S.
Mean
0.34 L/day
46 mL/kg-day
0.31 L/day
23 mlAg-day
0.40 L/day
19mL/kg-day
0.68 L/day
12 mLAg-day
1.2 L/day
18.3mL/kg-day
1. 3 L/day
2 1.4 mL/kg-day
EPA (2000).
50*
O.I 7 L/day
19 mL/kg-day
0.24
17 mL/kg-day
0.30 L/day
15 mL/kg-day
0.47 L/day
9 mL/kg-day
1.1 L/day
16 mL/kg-day
1.3 L/day
21 mL/kg-day
90*
0.88 L/day
127 mL/kg-day
0.69 L/day
51 mL/kg-day
0.90 L/day
42 mL/kg-day
1.5 L/day
26 mL/kg-day
2.2 L/day
35 mL/kg-day
1.9 L/day
35 mL/kg-day
Fined
95* Multiple Distributions
1 .0 L/day Tables 4-4 Table 4-11'
156 mL/kg-day
0.94 L/day Table 4-3
67 mL/kg-day
1 . 1 L/day Table 4-4 Table 4- 1 1 '
56 mL/kg-day
1.9 L/day Tables 4-4 Table 4-1 ]<
' 33 mL/kg-day
2.4 L/day Table 3-25
40 mL/kg-day
2.2 L/day Table 3-25
37 mL/kg-day
'Source: Ershow et al. (1991).
"Source: Myers et al. (1999).
March 2000
4-22
DRAFT-DO NOT QUOTE OR CITE
-------
1
.2
13
4
5
Table 4-16. Confidence in Tapwater Intake Recommendations
Considerations
Rationale
Rating
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Study Elements
• Level of peer-review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
• Adequacy of data
collection period
• Validity of approach
• Study size
Representativeness of the
population
Characterization of
variability
Lack of bias in study design
(high rating is desirable)
Measurement error
The U.S. EPA (2000) and Ershow and Cantor (1989) High
studies had thorough expert panel review. Review
procedures were not reported in the Canadian study; it
was a government report. Other reports presented are
published in scientific journals.
The two monographs are available from the sponsoring High
agencies; the others are library-accessible.
Methods are well-described. High
The studies are directly relevant to tapwater. In High
addition, for U.S. EPA (2000) study included
consumption for other drinking water sources
See "representativeness" below. NA
The three monographs used recent primary data (less High
than one week) on recall of intake.
Data collected for USDA (1998) used by U.S. EPA High
(2000) are current. The Ershow and Cantor (1989) and
Canadian surveys used data from 1978 era.
These are one- to three-day intake data. However, Medium
long term variability may be small. Their use as a
chronic intake measure can be assumed.
The approach was competently executed. High
The two U.S. monographs (U.S. EPA, 2000; Ershow High
and Cantor, 1989) each sufficiently sample populations
(i.e., 6,000 and 11,000, respectively) for their studies
The U.S. EPA (2000), Ershow and Cantor (1989), and High
Canadian surveys were validated as demographicaily
representative.
The full distributions.were given in the main studies. High
Bias was not apparent. High
No physical measurements were taken. The method Medium
relied on recent recall of standardized volumes of
drinking water containers, and was not validated.
Other Elements
Number of studies
Agreement between
researchers
There were three key studies for the child
recommendations.
This agreement was good.
High for adult and
children.
Medium for the other
recommended
subpopulation values.
High
Overall Rating
The data are excellent and current.
High
March 2000
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1 5. SOIL INGESTION AND PICA
2
3 5.1 INTRODUCTION
4 The ingestion of soil is a potential source of human exposure to toxicants. The potential
5 for exposure to contaminants via this source is greater for children because they are more likely
6 to ingest more soil than adults as a result of behavioral patterns present during childhood.
7 Inadvertent soil ingestion among children may occur through the mouthing of objects or hands.
8 Mouthing behavior is considered to be a normal phase of childhood development. Deliberate
9 soil ingestion is defined as pica and is considered to be relatively uncommon. Because normal,
10 inadvertent soil ingestion is more prevalent and data for individuals with pica behavior are
11 limited, this section focuses primarily on normal soil ingestion that occurs as a result of
12 mouthing or unintentional hand-to-mouth activity.
13 Several studies have been conducted to estimate the amount of soil ingested by children.
14 Most of the early studies attempted to estimate the amount of soil ingested by measuring the
15 amount of dirt present on children's hands and making generalizations based on behavior. More
recently, soil intake studies have been conducted using a methodology that measures trace
17 elements in feces and soil that are believed to be poorly absorbed in the gut. These
18 measurements are used to estimate the amount of soil ingested over a specified time period. The
19 available studies on soil intake are summarized in the following sections. Recommended intake
20 rates are based on the results of key studies presented in the Exposure Factors Handbook and
21 summarized here. Relevant information on the prevalence of pica and intake among individuals
22 exhibiting pica behavior is also presented.
23
24 5.2 SOIL INTAKE STUDIES
25 Binder et al. (1986) - Estimating Soil Ingestion: Use of Tracer Elements in Estimating
26 the Amount of Soil Ingested by Young Children - Binder et al. (1986) studied the ingestion of soil
27 among children 1 to 3 years of age who wore diapers using a tracer technique modified from a
28 method previously used to measure soil ingestion among grazing animals. The children were
29 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
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1 (42 males and 23 females), and composited samples of soil were obtained from the children's
2 yards. Both excreta and soil samples were analyzed for aluminum, silicon, and titanium. These
3 elements were found in soil, but were thought to be poorly absorbed in the gut and to have been
4 present in the diet only in limited quantities. This made them useful tracers for estimating soil
5 intake. Excreta measurements were obtained for 5 9 of the children. Soil ingestion by each child
6 was estimated based on each of the three tracer elements using a standard assumed fecal dry
7 weight of 15 g/day, and the following equation:
8
f xF
T,=%^
9 where:
10 ' T, e = estimated soil ingestion for child i based on element e (g/day);
11 fi>e = concentration of element e in fecal sample of child i(mg/g);
12 F; = fecal dry weight (g/day); and
13 Sie = concentration of element e in child i's yard soil (mg/g).
14
15 The analysis conducted by Binder et al. (1986) assumed that: (1) the tracer elements were
16 neither lost nor introduced during sample processing; (2) the soil ingested by children originates
17 primarily from their own yards; and (3) that absorption of the tracer elements by children
18 occurred in only small amounts. The study did not distinguish between ingestion of soil and
19 housedust nor did it account for the presence of the tracer elements in ingested foods or
20 medicines.
21 The arithmetic mean quantity of soil ingested by the children in the Binder et al.
22 (1986) study was estimated to be 181 mg/day (range 25 to 1.324) based on the aluminum tracer;
23 184 mg/day (range 31 to 799) based on the silicon tracer; and 1,834 mg/day (range 4 to 17.076)
24 based on the titanium tracer (Table 5-1). The overall mean soil ingestion estimate based on the
25 minimum of the three individual tracer estimates for each child was 108 mg/day (range 4 to 708).
26 The 95th percentile values for aluminum, silicon, and titanium were 584 mg/day, 578 mg/day,
27 and 9.590 mg/day, respectively. The 95th percentile value based on the minimum of the three
28 individual tracer estimates for each child was 386 mg/day.
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1 The authors were not able to explain the difference between the results for titanium and
2 for the other two elements, but speculated that unrecognized sources of titanium in the diet or in
3 the laboratory processing of stool samples may have accounted for the increased levels. The
4 frequency distribution graph of soil ingestion estimates based on titanium shows that a group of
5 21 children had particularly high titanium values (i.e., >1,000 mg/day). The remainder of the
6 children showed titanium ingestion estimates at lower levels, with a distribution more
7 comparable to that of the other elements.
8 The advantages of this study are that a relatively large number of children were studied
9 and tracer elements were used to estimate soil ingestion. However, the children studied may not
10 be representative of the U.S. population and the study did not account for tracers ingested via
11 foods or medicines. Also, the use of an assumed fecal weight instead of actual fecal weights may
12 have biased the results of this study. Finally, because of the short-term nature of the survey, soil
13 intake estimates may not be entirely representative of long-term behavior, especially at the
14 upper-end of the distribution of intake.
15 Clausing et al. (1987) - A Method for Estimating Soil Ingestion by Children - Clausing
6 et al. (1987) conducted a soil ingestion study with Dutch children using a tracer element
17 methodology similar to that of Binder et al. (1986). Aluminum, titanium, and acid-insoluble
18 residue (AIR) contents were determined for fecal samples from children, aged 2 to 4 years,
19 attending a nursery school, and for samples of playground dirt at that school. Twenty-seven
20 daily fecal samples were obtained over a 5-day period for the 18 children examined. Using the
21 average soil concentrations present at the school, and assuming a standard fecal dry weight of 10
22 g/day, Clausing et al. (1987) estimated soil ingestion for each tracer. Clausing et al. (1987) also
23 collected eight daily fecal samples from six hospitalized, bedridden children. These children
24 served as a control group, representing children who had very limited access to soil.
25 The average quantity of soil ingested by the school children in this study was as follows:
26 230 mg/day (range 23 to 979 mg/day) for aluminum; 129 mg/day (range 48 to 362 mg/day) for
27 AIR; and 1,430 mg/day (range 64 to 11,620 mg/day) for titanium (Table 5-2). As in the Binder
28 et al. (1986) study, a fraction of the children (6/19) showed titanium values well above
29 1.000 mg/day, with most of the remaining children showing substantially lower values. Based
0 on the Limiting Tracer Method (LTM), mean soil intake was estimated to be 105 mg/day with a
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1 population standard deviation of 67 mg/day (range 23 to 362 rag/day). Use of the LTM assumed
2 that "the maximum amount of soil ingested corresponded with the lowest estimate from the three
3 tracers" (Clausing et al., 1987). Geometric mean soil intake was estimated to be 90 mg/day.
4 This assumes that the maximum amount of soil ingested cannot be higher than the lowest
5 estimate for the individual tracers.
6 Mean soil intake for the hospitalized children was estimated to be 56 mg/day based on
7 aluminum (Table 5-3). For titanium, three of the children had estimates well in excess of
8 1,000 mg/day, with the remaining three children in the range of 28 to 58 mg/day. Using the
9 LTM method, the mean soil ingestion rate was estimated to be 49 mg/day with a population
10 standard deviation of 22 mg/day (range 26 to 84 mg/day). The geometric mean soil intake rate
11 was 45 mg/day. The data on hospitalized children suggest a major nonsoil source of titanium for
12 some children, and may suggest a background nonsoil source of aluminum.- However, conditions
13 specific to hospitalization (e.g., medications) were not considered. AIR measurements were not
14 reported for the hospitalized children. Assuming that the tracer-based soil ingestion rates
15 observed in hospitalized children actually represent background tracer intake from dietary and
16 other nonsoil sources, mean soil ingestion by nursery school children was estimated to be
17 56 mg/day, based on the LTM (i.e., 105 mg/day for nursery school children minus 49 mg/day for
18 hospitalized children) (Clausing etal. 1987).
19 The advantages of this study are that Clausing et al: (1987) evaluated soil ingestion
20 among two populations of children that had differences in access to soil, and corrected soil intake
21 rates based on background estimates derived from the hospitalized group. However, a smaller
22 number of children were used in this study than in the Binder et al. (1986) study and these
23 children may not be representative of the U.S. population. Tracer elements in foods or medicines
24 were not evaluated. Also, intake rates derived from this study may not be representative of soil
25 intake over the long-term because of the short-term nature of the study. In addition, one of the
26 factors that could affect soil intake rates is hygiene (e.g., hand washing frequency). Hygienic
27 practices can vary across countries and cultures and may be more stringently emphasized in a
28 more structured environment such as child care centers in The Netherlands and other European
29 countries than in child care centers in the United States.
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1 Calabrese et al. (1989) - How Much Soil do Young Children Ingest: An Epidemiologic
2 Study - Calabrese et al. (1989) studied soil ingestion among children using the basic tracer design
3 developed by Binder et al. (1986). However, in contrast to the Binder et al. (1986) study, eight
4 tracer elements (i.e., aluminum, barium, manganese, silicon, titanium, vanadium, yttrium, and
5 zirconium) were analyzed instead of only three (i.e., aluminum, silicon, and titanium). A total of
6 64 children between the ages of 1 and 4 years old were included in the study. These children
7 were all selected from the greater Amherst, Massachusetts area and were predominantly from
8 two-parent households where the parents were highly educated. The Calabrese et al.
9 (1989) study was conducted over eight days during a two week period and included the use of a
10 mass-balance methodology in which duplicate samples of food, medicines, vitamins, and others
11 were collected and analyzed on a daily basis, in addition.to soil and dust samples collected from
12 the child's home and play area. Fecal and urine samples were also collected and analyzed for
13 tracer elements. Toothpaste, low in tracer content, was provided to all participants.
14 In order to validate the mass-balance methodology used to estimate soil ingestion rates
15 among children and to determine which tracer elements provided the most reliable data on soil
ingestion, known amounts of soil (i.e.. 300 mg over three days and 1,500 mg over three days)
17 containing eight tracers were administered to six adult volunteers (i.e., three males and three
18 females). Soil samples and feces samples from these adults and duplicate food samples were
19 analyzed for tracer elements to calculate recovery rates of tracer elements in soil. Based on the
20 adult validation study, Calabrese et al. (1989) confirmed that the tracer methodology could
21 adequately detect tracer elements in feces at levels expected to correspond with soil intake rates
22 in children. Calabrese et al. (1989) also found that aluminum, silicon, and yttrium were the most
23 reliable of the eight tracer elements analyzed. The standard deviation of recovery of these three
24 tracers was the lowest and the percentage of recovery was closest to 100 percent (Calabrese,
25 et al., 1989). The recovery of these three tracers ranged from 120 to 153 percent when 300 mg of
26 soil had been ingested over a three-day period and from 88 to 94 percent when 1,500 mg soil had
27 been ingested over a three-day period (Table 5-4).
28 Using the three most reliable tracer elements, the mean soil intake rate for children,
29 adjusted to account for the amount of tracer found in food and medicines, was estimated to be
153 mg/day based on aluminum. 154 mg/day based on silicon, and 85 mg/day based on yttrium
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1 (Table 5-5). Median intake rates were somewhat lower (29 mg/day for aluminum, 40 mg/day for
2 silicon, and 9 mg/day for yttrium). Upper-percentile (i.e., 95th) values were 223 mg/day for
3 aluminum, 276 mg/day for silicon, and 106 mg/day for yttrium. Similar results were observed
4 when soil and dust ingestion was combined (Table 5-5). Intake of soil and dust was estimated
5 using a weighted ingestion for one child in the study ranged from approximately 1 0 to
6 14 grams/day during the second week of observation. Average soil ingestion for this child was
7 5 to 7 mg/day, based on the entire study period.
8 The advantages of this study are that intake rates were corrected for tracer concentrations
9 in foods and medicines and that the methodology was validated using adults. Also, intake was
10 observed over a longer time period in this study than in earlier studies and the number of tracers
1 1 used was larger than for other studies. A relatively large population was studied, but they may
12 not be entirely representative of the U.S. population because they were selected from a single
13 location.
14 Davis et al. (1990) - Quantitative Estimates of Soil Ingestion in Normal Children
15 Between the ages of 2 and 7 years: Population-Based Estimates Using Aluminum, Silicon, and
16 Titanium as Soil Tracer Elements - Davis et al. (1 990) also used a mass-balance/tracer technique
17 to estimate soil ingestion among children. In this study, 104 children between the ages of 2 and
18 7 years were randomly selected from a three-city area in southeastern Washington State. The
19 study was conducted over a seven day period, primarily during the summer. Daily soil ingestion
20 was evaluated by collecting and analyzing soil and house dust samples, feces, urine, and
21 duplicate food samples for aluminum, silicon, and titanium. In addition, information on dietary
22 habits and demographics was collected in an attempt to identify behavioral and demographic
23 characteristics that influence soil intake rates among children. The amount of soil ingested on a
24 daily basis was estimated using the following equation:
(5_2)
Esoil
27
28 where:
29 Sj e = soil ingested for child i based on tracer e (g);
30 DWf = feces dry weight (g);
31 DWp = feces dry weight on toilet paper (g);
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Ef = tracer amount in feces (//g/g);
Eu = tracer amount in urine (/ug/g);
3 DWfd = food dry weight (g);
4 Efd = tracer amount in food C"g/g); and
5 Esoii = tracer concentration in soil (wg/g).
6
7 The soil intake rates were corrected by adding the amount of tracer in vitamins and medications
8 to the amount of tracer in food, and adjusting the food quantities, feces dry weights, and tracer
9 concentrations in urine to account for missing samples.
10 Soil ingestion rates were highly variable, especially those based on titanium. Mean daily
11 soil ingestion estimates were 38.9 mg/day for aluminum, 82.4 mg/day for silicon and
12 245.5 mg/day for titanium (Table 5-6). Median values were 25 mg/day for aluminum, 59
13 mg/day for silicon, and 81 mg/day for titanium. Davis et al. (1990) also evaluated the extent to
14 which differences in tracer concentrations in house dust and yard soil impacted estimated soil
15 ingestion rates. The value used in the denominator of the mass balance equation was
16 recalculated to represent a weighted average of the tracer concentration in yard soil and house
••7 dust based on the proportion of time the child spent indoors and outdoors. The adjusted mean
18 soil/dust intake rates were 64.5 mg/day for aluminum, 160.0 mg/day for silicon, and 268.4
19 mg/day for titanium. Adjusted median soil/dust intake rates were: 51.8 mg/day for aluminum,
20 112.4 mg/day for silicon, and 116.6 mg/day for titanium. Davis et al. (1990) also observed that
21 the following demographic characteristics were associated with high soil intake rates: male sex,
22 non-white racial group, low income, operator/laborer as the principal occupation of the parent,
23 and city of residence. However, none of these factors were predictive of soil intake rates when
24 tested using multiple linear regression.
25 The advantages of the Davis et al. (1990) study are that soil intake rates were corrected
26 based on the tracer content of foods and medicines and that a relatively large number of children
27 were sampled. Also, demographic and behavioral information was collected for the survey
28 group. However, although a relatively large sample population was surveyed, these children
29 were all from a single area of the U.S. and may not be representative of the U.S. population as a
30 whole. The study was conducted over a one-week period during the summer and may not be
representative of long-term (i.e., annual) patterns of intake.
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1 Van W'ijnen et al. (1990) - Estimated Soil Ingestion by Children - In a study by Van
2 Wijnen et al. (1990), soil ingestion among Dutch children ranging in age from 1 to 5 years was
3 evaluated using a tracer element methodology similar to that used by Clausing et al. (1987).
4 Van Wijnen et al. (1990) measured three tracers (i.e., titanium, aluminum, and AIR) in soil and
5 feces and estimated soil ingestion based on the LTM. An average daily feces weight of 15 g dry
6 weight was assumed. A total of 292 children attending daycare centers were sampled during the
7 first of two sampling periods and 187 children were sampled in the second sampling period:
8 162 of .these children were sampled during both periods (i.e., at the beginning and near the end of
9 the summer of 1986). A total of 78 children were sampled at campgrounds, and 15 hospitalized
10 children were sampled. The mean values for these groups were: 162 mg/day for children in
11 daycare centers, 213 mg/day for campers and 93 mg/day for hospitalized children. Van Wijnen
12 et al. (1990) also reported geometric mean LTM values because soil intake rates were found to be
13 skewed and the log transformed data were approximately normally distributed. Geometric mean
14 LTM values were estimated to be 111 mg/day for children in daycare centers, 174 mg/day for
15 children vacationing at campgrounds (Table 5-7) and 74 mg/day for hospitalized children
16 (70-120 mg/day based on the 95 percent confidence limits of the mean). AIR was the limiting
17 tracer in about 80 percent of the samples. Among children attending daycare centers, soil intake
18 was also found to be higher when the weather was good (i.e., <2 days/week precipitation) than
19 when the weather was bad (i.e., >4 days/week precipitation (Table 5-8). Van Wijnen et al.
20 (1990) suggest that the mean LTM value for hospitalized infants represents background intake of
2i tracers and should be used to correct the soil intake rates based on LTM values for other
22 sampling groups. Using mean values, corrected soil intake rates were 69 mg/day (162 mg/day
23 minus 93 mg/day) for daycare children and 120 mg/day (213 mg/day minus 93 mg/day) for
24 campers. Corrected geometric mean soil intake was estimated to range from 0 to 90 mg/day with
25 a 90th percentile. value of 190 mg/day for the various age categories within the daycare group
26 and 30 to 200 mg/day with a 90th percentile value of 300 mg/day for the various age categories
27 within the camping group.
28 The advantage of this study is that soil intake was estimated for three different
29 populations of children; one expected to have high intake, one expected to have "typical" intake,
30 and one expected to have low or background-level intake. Van Wijnen et al. (1990) used the
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1 background tracer measurements to correct soil intake rates for the other two populations. Tracer
2 concentrations in food and medicine were not evaluated. Also, the population of children studied
3 was relatively large, but may not be representative of the U.S. population. This study was
4 conducted over a relatively short time period. Thus, estimated intake rates may not reflect long-
5 term patterns, especially at the high-end of the distribution. Another limitation of this study is
6 that values were not reported element-by-element which would be the preferred way of reporting.
7 In addition, one of the factors that could affect soil intake rates is hygiene (e.g., hand washing
8 frequency). Hygienic practices can vary across countries and cultures and may be more
9 stringently emphasized in a more structured environment such as child care centers in The
10 Netherlands and other European countries than in child care centers in the United States.
11 Stanek and Calabrese (I995a) - Daily Estimates of Soil Ingestion in Children - Stanek
12 and Calabrese (1995a) presented a methodology which links the physical passage of food and
13 fecal samples to construct daily soil ingestion estimates from daily food and fecal trace-element
14 concentrations. Soil ingestion data for children obtained from the Amherst study (Calabrese
15 et al., 1989) were reanalyzed by Stanek and Calabrese (1995a). In the Amherst study, soil
6 ingestion measurements were made over a period of 2 weeks fora non-random sample of
17 sixty-four children (ages of 1 -4 years old) living adjacent to an academic area in western
18 Massachusetts. During^each week, duplicate food samples were collected for 3 consecutive days
19 and fecal samples were collected for 4 consecutive days for each subject. The total amount of
20 each of eight trace elements present in the food and fecal samples were measured. The eight
21 trace elements are aluminum, barium, manganese, silicon, titanium, vanadium, yttrium, and
22 zirconium. The authors expressed the amount of trace element in food input or fecal output as a
23 "soil equivalent," which was defined as the amount of the element in average daily food intake
24 (or average daily fecal output) divided by the concentration of the element in soil. A lag period
25 of 28 hours between food intake and fecal output was assumed for all respondents. Day 1 for the
26 food sample corresponded to the 24 hour period from midnight on Sunday to midnight on
27 Monday of a study week; day 1 of the fecal sample corresponded to the 24 hour period from
28 noon on Monday to noon on Tuesday (Stanek and Calabrese, 1995a). Based on these definitions,
29 the food soil equivalent was subtracted from the fecal soil equivalent to obtain an estimate of soil
P ingestion for a trace element. A daily "overall" ingestion estimate was constructed for each child
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1 as the median of trace element values remaining after tracers falling outside of a defined range
2 around the overall median were excluded. Additionally, estimates of the distribution of soil
3 ingestion projected over a period of 365 days were derived by fitting log-normal distributions to
». i
4 the "overall" daily soil ingestion estimates.
5 Table 5-9 presents the estimates of mean daily soil ingestion intake per child (mg/day) for
6 the 64 study participants. (The authors also presented estimates of the median values of daily
7 intake for each child. For most risk assessment purposes the child mean values, which are
8 proportional to the cumulative soil intake by the child, are needed instead of the median values.)
9 The approach adopted in this paper led to changes in ingestion estimates from those presented in
10 . Calabreseetal. (1989).
11 Specifically, among elements that may be more useful for estimation of ingestion, the
12 mean estimates decreased for Al (153 mg/d to 122 mg/d) and Si (154 mg/d to 139 mg/d), but
13 increased for Ti (218 mg/d to 271 mg/d) and Y (85 mg/d to 165 mg/d). The "overall" mean
14 estimate from this reanalysis was 179 mg/d. Table 5-9 presents the empirical distribution of the
15 the "overall" mean daily soil ingestion estimates for the 8-day study period (not based on
16 lognormal modeling). The estimated intake based on the "overall" estimates is 45 mg/day or
17 less for 50 percent of the children and 208 mg/day or less for 95 percent of the children. The
18 upper percentile values for most of the individual trace elements are somewhat higher. Next,
19 estimates of the respondents soil intake averaged over a period of 365 days were presented based
20 upon the lognormal models fit to the daily ingestion estimates (Table 5-10). The estimated
21 median value of the 64 respondents' daily soil ingestion averaged over a year is 75 mg/day, while
22 the 95th percentile is 1,751 mg/day.
23 A strength of this study is that it attempts to make full use of the collected data through
24 estimation of daily ingestion rates for children. The data are then screened to remove less
25 consistent tracer estimates and the remaining values are aggregated. Individual daily estimates of
26 ingestion will be subject to larger errors than are weekly average values, particularly since the
27 assumption of a constant lag time between food intake and fecal output may be not be correct for
28 many subject days. The aggregation approach used to arrive at the "overall" ingestion estimates
29 rests on the assumption that the mean ingestion estimates across acceptable tracers provides the
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1 most reliable ingestion estimates. The validity of this assumption depends on the particular set
2 of tracers used in the study, and is not fully assessed.
3 In developing the 365 day soil ingestion estimates, data that were obtained over a short
4 period of time (as is the case with all available soil ingestion studies) were extrapolated over a
5 year. The 2-week study period may not reflect variability in tracer element ingestion over a year.
6 While Stanek and Calabrese (1995a) attempt to address this through lognormal modeling of the
7 long term intake, new uncertainties are introduced through the parametric modeling of the
8 limited subject day data. Also, the sample population size of the original study was small and
9 site limited, and, therefore, is not representative of the U.S. population. Study mean estimates of
10 soil ingestion, such as the study mean estimates presented in Table 5-9, are substantially more
11 reliable than any available distributional estimates.
12 Stanek and Calabrese (I995b) - Soil Ingestion Estimates for Use in Site Evaluations
13 Based on the Best Tracer Method - Stanek and Calabrese (1995b) recalculated ingestion rates
14 that were estimated in three previous mass-balance studies (Calabrese et ah, 1989 and Davis et
15 ah. 1990 for children's soil ingestion, and Calabrese et ah, 1990 for adult soil ingestion) using the
Best Tracer Method (BTM). This method allows for the selection of the most recoverable tracer
17 • for a particular subject or group of subjects. The selection process involves ordering trace
18 elements for each subject based on food/soil (F/S) ratios. These ratios are estimaied by dividing
19 the total amount of the tracer in food by the tracer concentration in soil. The F/S ratio is small
20 when the tracer concentration in food is almost zero when compared to the tracer concentration
21 in soil. A small F/S ratio is desirable because it lessens the impact of transit time error (the error
22 that occurs when fecal output does not reflect food ingestion, due to fluctuation in
23 gastrointestinal transit time) in the soil ingestion calculation. Because the recoverability of
24 tracers can vary within any group of individuals, the BTM uses a ranking scheme of F/S ratios to
25 determine the best tracers for use in the ingestion rate calculation. To reduce biases that may
26 occur as a result of sources of fecal tracers other than food or soil, the median of soil ingestion
27 estimates based on the four lowest F/S ratios was used to represent soil ingestion among
28 individuals.
29 For children, Stanek and Calabrese (1995b) used data on 8 tracers from Calabrese et ah,
p 1989 and data on 3 tracers from Davis et ah (1990) to estimate soil ingestion rates. The median
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1 of the soil ingestion estimates from the lowest four F/S ratios from the Caiabrese et al. (1989)
2 study most often included Al, Si, Ti, Y, and Zr. Based on the median of soil ingestion estimates
3 from the best four tracers, the mean soil ingestion rate was 132 mg/day and the median was
4 33 mg/day. The 95th percentile value was 154 mg/day. These estimates are based on data for
5 128 subject weeks for the 64 children in the Caiabrese et al. (1989) study. For the 101 children
6 in the Davis et al. (1990) study, the mean soil ingestion rate was 69 mg/day and the median soil
7 ingestion rate was 44 mg/day. The 95th percentile estimate was 246 mg/day. These data are
8 based on the three tracers (i.e., Al, Si, and Ti) from the Davis et al. (1990) study. When the
9 Caiabrese et al. (1989) and Davis et al. (1990) studies were combined, soil ingestion was
10 estimated .to be 113 mg/day (mean); 37 mg/day (median); and 217 mg/day (95th percentile),
11 using the BTM.
12 This study provides a reevaluation of previous studies. Its advantages are that it
13 combines data from 2 studies for children, one from California and one from Massachusetts,
14 which increases the number-of observations. It also corrects for biases associated with the
15 differences in tracer metabolism. The limitations associated with the data used in this study are
16 the same as the limitations described in the summaries of the Caiabrese et al. (1989), Davis et al."
17 (1990) and Caiabrese etal. (1990) studies.
18 Thompson and Burmaster (1991) - Parametric Distributions for Soil Ingestion by
19 Children - Thompson and Burmaster (1991) developed parameterized distributions of soil
20 ingestion rates for children based on a reanalysis of the key study data collected by Binder et al.
21 (1986). In the original Binder et al. (1986) study, an assumed fecal weight of 15 g/day was used.
22 Thompson and Burmaster reestimated the soil ingestion rates from the Binder et al. (1986) study
23 using the actual stool weights of the study participants instead of the assumed stool weights.
24 Because the actual stool weights averaged only 7.5 g/day, the soil ingestion estimates presented
25 by Thompson and Burmaster (1991) are approximately one-half of those reported by Binder et
26 al. (1986). Table 5-11 presents the distribution of estimated soil ingestion rates calculated by
27 Thompson and Burmaster (1991) based on the three tracers elements (i.e., aluminum, silicon, and
28 titanium), and on the arithmetic average of soil ingestion based on aluminum and silicon. The
29 mean soil intake rates were 97 mg/day for aluminum, 85 mg/day for silicon, and 1,004 mg/day
30 for titanium. The 90th percentile estimates were 197 mg/day for aluminum, 166 mg/day for
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1 silicon, and 2,105 mg/day for titanium. Based on the arithmetic average of aluminum and silicon
2 for each child, mean soil intake was estimated to be 91 mg/day and 90th percentile intake was
3 estimated to be 143 mg/day.
4 Thompson and Burmaster (1991) tested the hypothesis that soil ingestion rates based on
5 the adjusted Binder et al. (1986) data for aluminum, silicon and the average of these two tracers
6 were lognormally distributed. The distribution of soil intake based on titanium was not tested for
7 lognormality because titanium may be present in food in high concentrations and the Binder et
8 al. (1986) study did not correct for food sources of titanium (Thompson and Burmaster, 1991).
9 Although visual inspection of the distributions for aluminum, silicon, and the average of these
10 , tracers all indicated that they may be lognormally distributed, statistical tests indicated that only
11 silicon and the average of the silicon and aluminum tracers were lognormally distributed. Soil
12 intake rates based on aluminum were not lognormally distributed. Table 5-11 also presents the
13 lognormal distribution parameters and underlying normal distribution parameters (i.e., the natural
14 logarithms of the data) for aluminum, silicon, and the average of these two tracers. According to
15 the authors, "the parameters estimated from the underlying normal distribution are much more
reliable and robust" (Thompson and Burmaster, 1991).
17 The advantages of this study are that it provides percentile data and defines the shape of
18 soil intake distributions. However, the number of data points used to fit the distribution was
19 limited. In addition, the study did not generate "new" data. Instead, it provided a reanalysis of
20 previously-reported data using actual fecal weights. No corrections were made for tracer intake
21 from food or medicine and the results may not be representative of long-term intake rates
22 because the data were derived from a short-term study.
23 Sedman and Mahmood (1994) • Soil Ingestion by Children and Adults Reconsidered
24 Using the Results of Recent Tracer Studies - Sedman and Mahmood (1994) used the results of
25 two of the key children's tracer studies (Calabrese et al. 1989; Davis et al. 1990) to determine
26 estimates of average daily soil ingestion in young children and for over a lifetime. In the two
27 studies, the intake and excretion of a variety of tracers were monitored, and concentrations of
28 tracers in soil adjacent to the children's dwellings were determined (Sedman and Mahmood.
29 1994). From a mass balance approach, estimates of soil ingestion in these children were
determined by dividing the excess tracer intake (i.e., quantity of tracer recovered in the feces in
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1 excess of the measured intake) by the average concentration of tracer in soil samples from each
2 child's dwelling. Sedman and Mahmood (1994) adjusted the mean estimates of soil ingestion in
3 children for each tracer (Y) from both studies to reflect that of a 2-year old child using the
4 following equation:
5 ...
6 Y^xe'-0'112*^ (5-3)
7 where:
8 Yj = adjusted mean soil ingestion (rag/day)
9 x = a constant
10 yr = average age (2 years)
11
12 The average ages of children in the two key studies were 2.4 years in Calabrese et al.
13 (1989) and 4.7 years in Davis et al. (1990). The mean of the adjusted levels of soil ingestion for
14 a two year old child was 220 mg/kg for the Calabrese et al. (1989) study and 170 mg/kg for the
15 Davis et al. (1990) study (Sedman and Mahmood, 1994). From the adjusted soil ingestion
16 estimates, based on a normal distribution of means, the mean estimate for a 2-year old child was
17 195 mg/day and the overall mean of soil ingestion and the standard error of the mean was
18 53 mg/day (Sedman and Mahmood, 1994). Based on uncertainties associated with the method
19 employed, Sedman and Mahmood (1994) recommended a conservative estimate of soil ingestion
20 in young children of 250 mg/day. Based on the 250 mg/day ingestion rate in a 2-year old child,
21 an average daily soil ingestion over a lifetime was estimated to be 70 mg/day. The lifetime
22 estimates were derived using the equation presented above that describes changes in soil
23 ingestion with age (Sedman and Mahmood, 1994).
24 Calabrese and Stanek (1995) - Resolving Intertracer Inconsistencies in Soil Ingestion
25 Estimation - Calabrese and Stanek (1995) explored sources and magnitude of positive and
26 negative errors in soil ingestion estimates for children on a subject-week and trace element basis.
27 Calabrese and Stanek (1995) identified possible sources of positive errors to be the following:
28 • Ingestion of high levels of tracers before the study starts and low ingestion during
29 study period may result in over estimation of soil ingestion; and
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1 • Ingestion of element tracers from a non-food or non-soil source during the study
2 period.
3
4 Possible sources of negative bias identified by Calabrese and Stanek (1995) are the following:
5 • Ingestion of tracers in food, but the tracers are not captured in the fecal sample either
6 due to slow lag time or not having a fecal sample available on the final study day; and
7 • Sample measurement errors which result in diminished detection of fecal tracers, but
8 . not in soil tracer levels.
9 The authors developed an approach which attempted to reduce the magnitude of error in the
10 individual trace element ingestion estimates. Results from a previous study conducted by
11 Calabrese et al. (1989) were used to quantify these errors based on the following criteria: (1) a
12 lag period of 28 hours was assumed for the passage of tracers ingested in food to the feces (this
13 value was applied to all subject-day estimates); (2) daily soil ingestion rate was estimated for ,
14 each tracer for each 24-hr day a fecal sample was obtained; (3) the median tracer-based soil
15 ingestion rate for each subject-day was determined. Also, upper and lower bound estimates were
determined based on criteria formed using an assumption of the magnitude of the relative
17 standard deviation (RSD) presented in another study conducted by Stanek and Calabrese
18 (1995a). Daily soil ingestion rates for tracers that fell beyond the upper and lower ranges were
19 excluded from subsequent calculations, and the median soil ingestion rates of the remaining
20 tracer elements were considered the best estimate for that particular day. The magnitude of
21 positive or negative error for a specific tracer per day was derived by determining the difference
22 between the value for the tracer and the median value; (4) negative errors due to missing fecal
23 samples at the end of the study period were also determined (Calabrese and Stanek, 1995).
24 Table 5-12 presents the estimated magnitude of positive and negative error for six tracer
25 elements in the children's study (i.e., conducted by Calabrese et al., 1989). The original mean
26 soil ingestion rates ranged from a low of 21 mg/day based on zirconium to a high of 459 mg/day
27 based on titanium (Table 5-12). The adjusted mean soil ingestion rate after correcting for
28 negative and positive errors ranged from 97 mg/day based on yttrium to 208 mg/day based on
29 titanium (Table 5-12). Calabrese and Stanek (1995) concluded that correcting for errors at the
P individual level for each tracer element provides more reliable estimates of soil ingestion.
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1 This report is valuable in providing additional understanding of the nature of potential
2 errors in trace element specific estimates of soil ingestion. However, the operational definition
3 used for estimating the error in a trace element estimate was the observed difference of that tracer
4 from a median tracer value. Specific identification of sources of'error, or direct evidence that
5 individual tracers were indeed in error was not developed. Corrections to individual tracer means
6 were then made according to how different values for that tracer.were from the median values.
7 This approach is based on the hypothesis that the median tracer value is the most accurate
8 estimate of soil ingestion, and the validity of this assumption depends on the specific set of
9 tracers used in the study and need not be correct. The approach used for the estimation of daily
10 tracer intake is the same as in Stanek and Calabrese (1995a), and some limitations of that
11 approach are mentioned in the review of that study.
12 Calabrese et al. (1997) — Soil Ingestion for Children Residing on a Superfimd Site -
13 Calabrese et al. (1997) estimated soil ingestion rates for children residing on a Superfund site
14 using a mass-balance methodology in which eight tracer elements (i.e., aluminum, barium,
15 manganese, silicon, titanium, vanadium, yttrium, and zirconium) were analyzed. The
16 methodology used in this study is very similar to the one conducted in Calabrese et al. (1989).
17 As in Calabrese et al. (1989), 64 children ages 1-4 years were selected for this study and were
18 predominantly from two-parent households. This stratified simple random sample of children
19 was selected from the Anoconda, Montana area. Thirty-six of the 64 children were male, and the
20 children ranged in age from 1 to 3 years with approximately an equal number of children in each
21 age group. The Calabrese et al. (1997) study was conducted for seven consecutive days during a
22 two week period in the month of September. Duplicate samples of meals, beverages, and over-
23 the-counter medicines and vitamins were collected over the seven day period, along with fecal
24 samples. In addition, soil and dust samples were collected from the children's home and play
25 areas. Toothpaste containing nondetectable levels of the tracer elements, with the exception of
26 silica, was provided to all of the children. Infants were provided .with baby comstarch, diaper
27 rash cream, and soap which were found to contain low levels of tracer elements.
28 As in Calabrese et al. (1989), an additional study was conducted in which the identical
29 mass-balance methodology used to estimate soil ingestion rates among children was used on
30 adults in order to validate that soil ingestion could be detected. Known amounts of soil were
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administered to ten adults (5 males, 5 females) from Western Massachusetts over a period of 28
days. Each adult ingested for 7 consecutive days 1) no soil during Week 1,2) 20 mg of sterilized
3 soil during Week 2,3) 100 mg of sterilized soil during Week 3, and 4) 500 mg of sterilized soil
4 during Week 4. Soil samples were previously characterized and were of sufficient concentration
5 to be detected in the analysis of fecal samples. Duplicate food and fecal samples were collected
6 every day during each study week and analyzed for the eight tracer elements (Al, Si, Ti, Ce, La,
7 Nd, Y, and Zr). It was found that ingestion of soil from 20 to 500 mg/day could be detected in a
8 reliable manner.
9 Calabrese et al. (1997) estimated soil ingestion by each tracer element using the Best
10 Tracer Method (BTM) which allows for the selection of the most recoverable tracer for a
11 particular group of subjects (Stanek and Calabrese, 1995b). In this case BA, Mn, and V were
12 dropped as they were found to be poor performing tracers. The median soil ingestion estimates
13 for the four best trace elements based on Food/Soil ratios for the 64 children using Al. Si, Ti. Y,
14 and Zr were presented (Table 5-13). Based on the soil ingestion estimate for the best tracer, the
15 mean soil ingestion rate was 66 mg/day and the median was 20 mg/day. The 95th percentile
value was 280 mg/day. Using the median of the 4 best tracers, the mean was 7 mg/day and the
95th percentile was 160 mg/day. These results are lower than the soil ingestion estimates
18 obtained by Stanek and Calabrese (1995a). Calabrese et al. (1997) believe this may be due to the
19 fact that the families of the children who participated in this study were aware that they lived on
20 an EPA Superfund site and this knowledge might have resulted in reduced exposure. There was
21 no statistically significant difference found in soil ingestion estimates by gender or age. There
22 was also no significant difference in soil ingestion by housing or yard characteristics (i.e., porch,
23 deck, door mat, etc.), or between children with or without pets.
24 The median dust ingestion estimates for the four best tracer elements using Al, Si, Ti, Y,
25 and Zr were also presented (Table 5-14). The mean dust ingestion rate based on the best tracer
26 was 130 mg/day and the 95th percentile rate was 614 mg/day.
27 The advantages of this study were the use of a longer 7 consecutive day study period
28 rather than two periods of 3 and 4 days (Stanek and Calabrese. 1995a), the use of the BTM, the
29 use of an expanded adult validation study which used 10 volunteers rather than 6 (Calabrese et
al.. 1989), and the use of a dietary education program to reduce food tracer input and variability.
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1 However, the data presented in this study are from a single 7-day period during September which
2 may not reflect soil ingestion rates for other months or time-periods. In addition, the study
3 displayed a net residual negative error, which may have resulted in underestimated soil ingestion
4 rates. Calabrese et al. (1997) believe that this error is not likely to affect the median by more
5 than 40 mg/day. .;
6
7 5.3 PREVALENCE OF PICA
8 The scientific literature define pica as "the repeated eating of non-nutritive substances"
9 (Feldman, 1986). For the purposes of this handbook, pica is defined as an deliberately high soil
10 ingestion rate. Numerous articles have been published that report on the incidence of pica among
11 various populations. However, most of these papers describe pica for substances other than soil
12 including sand, clay, paint, plaster, hair, string, cloth, glass, matches, paper, feces, and various
13 other items. These papers indicate that the pica occurs in approximately half of all children
14 between the ages of 1 and 3 years (Sayetta, 1986). The incidence of deliberate ingestion
15 behavior in children has been shown to differ for different subpopulations. The incidence rate
16 appears to be higher for black children than for white children. Approximately 30 percent of
17 black children aged 1 to 6 years are reported to have deliberate ingestion behavior, compared
18 with 10 to 18 percent of white children in the same age group (Danford, 1982). There does not
19 appear to be any sex differences in the incidence rates for males or females (Kaplan and Sadock,
20 1985). Lourie et al. (1963) states that the incidence of pica is higher among children in lower
21 socioeconomic groups (i.e., 50 to 60 percent) than in higher income families (i.e., about
22 30 percent). Deliberate soil ingestion behavior appears to be more common in rural areas
23 (Vermeer and Frate, 1979). A higher rate of pica has also been reported for pregnant women and
24 individuals with poor nutritional status (Danford, 1982). In general, deliberate ingestion
25 behavior is more frequent and more severe in mentally retarded children than in children in the
26 general population (Behrman and Vaughan 1983, Danford 1982, Forfar and Ameil 1984,
27 Illingworth 1983, Sayetta 1986).
28 It should be noted that the pica statistics cited above apply to the incidence of general
29 pica and not soil pica. Information on the incidence of soil pica is limited, but it appears that soil
30 pica is less common. A study by Vermeer and Frate (1979) showed that the incidence of
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1 geophagia (i.e., earth-eating) was about 1 6 percent among children from a rural black community
2 in Mississippi. However, geophagia was described as a cultural practice among the community
3 surveyed and may not be representative of the general population. Average daily consumption of
4 soil was estimated to be 50 g/day. Bruhn and Pangborn (1 971) reported the incidence of pica for
5 "dirt" to be 1 9 percent in children, 14 percent in pregnant women, and 3 percent in nonpregnant
6 women. However, "dirt" was not clearly defined. The Bruhn and Pangbom (1971) study was
7 conducted among 91 non-black, low income families of migrant agricultural workers in
8 California. Based on the data from the five key tracer studies (Binder et ah, 1 986; Clausing
9 et al., 1 987; Van Wijnen et ah, 1 990; Davis et ah, 1 990; and Calabrese et ah, 1 989) only one
10 child out of the more than 600 children involved in all of these studies ingested an amount of soil
1 1 significantly greater than the range for other children. Although these studies did not include
12 data for all populations and were representative of short-term ingestions only, it can be assumed
13 that the incidence rate of deliberate soil ingestion behavior in the general population is low.
14 However, it is incumbent upon the user to use the appropriate value for their specific study
15 population.
17 5.4 DELIBERATE SOIL INGESTION AMONG CHILDREN
18 ' Information on the amount of soil ingested by children with abnormal soil ingestion
19 behavior is limited. However, some evidence suggests that a rate on the order of 1 0 g/day may
20 not be unreasonable.
21 Calabrese et al. (1991) - Evidence of Soil Pica Behavior and Quantification of Soil
22 Ingestion - Calabrese et al. (1991) estimated that upper range soil ingestion values may range
23 from approximately 5-7 grams/day. This estimate was based on observations of one pica child
24 among the 64 children who participated in the study. In the study, a 3.5-year old female
25 exhibited extremely high soil ingestion behavior during one of the two weeks of observation.
26 Intake ranged from 74 mg/day to 2.2 g/day during the first week of observation and 10.1 to
27 13.6 g/day during the second week of observation (Table 5-15). These results are based on
28 mass-balance analyses for seven (i.e., aluminum, barium, manganese, silicon, titanium,
29 vanadium, and yttrium) of the eight tracer elements used. Intake rates based on zirconium was
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1 significantly lower but Calabrese et al. (1991) indicated that this may have "resulted from a
2 limitation in the analytical protocol."
3 Calabrese and Stanek (1992) - Distinguishing Outdoor Soil Ingestionfrom Indoor Dust
4 Ingestion in a Soil Pica Child - Calabrese and Stanek (1992) quantitatively distinguished the
5 amount of outdoor soil ingestion from indoor dust ingestion in a soil pica child. This study was
6 based on a previous mass-balance study (conducted in 1991) in which a 3-1/2 year old child
7 ingested 10-13 grams of soil per day over the second week of a 2-week soil ingestion study.
8 Also, the previous study utilized a soil tracer methodology with eight different tracers (Al, Ba,
9 Mn, Si, Ti, V, Y, Zr). The reader is referred to Calabrese et al. (1989) for a detailed description
10 and results of the soil ingestion study. Calabrese and Stanek (1992) distinguished indoor dust
11 from outdoor soil in ingested soil based on a methodology which compared differential element
12 ratios.
13 Table 5-16 presents tracer ratios of soil, dust, and residual fecal samples in the soil pica
14 child. Calabrese and Stanek (1992) reported that there was a maximum total of 28 pairs of tracer
15 ratios based on eight tracers. However, only 19 pairs of tracer ratios were available for
16 quantitative evaluation as shown in Table 5-16. Of these 19 pairs, 9 fecal tracer ratios fell within
17 the boundaries for soil and dust (Table 5-16). For these 9 tracer soils, an interpolation was
18 performed to estimate the relative contribution of soil and dust to the residual fecal tracer ratio.
19 The other 10 fecal tracer ratios that fell outside the soil and dust boundaries were concluded to be
20 100 percent of the fecal tracer ratios from soil origin (Calabrese and Stanek, 1992). Also, the
21 9 residual fecal samples within the boundaries revealed that a high percentage (71 -99 percent) of
22 the residual fecal tracers were estimated to be of soil origin. Therefore, Calabrese and Stanek
23 (1992) concluded that the predominant proportion of the fecal tracers was from outdoor soil and
24 not from indoor dust origin.
25 In conducting a risk assessment for TCDD, U.S. EPA (1984) used 5 g/day to represent
26 the soil intake rate for pica children. The Centers for Disease Control (CDC) also investigated
27 the potential for exposure to TCDD through the soil ingestion route. CDC used a value of 10
28 g/day to represent the amount of soil that a child with deliberate soil ingestion behavior might
29 ingest (Kimbrough et al., 1984). These values are consistent with those observed by
30 Calabrese etal. (1991).
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1 Calabrese, E. J. and E. J. Stanek (1993) - Soil Pica: Not a Rare Event - Calabrese and
2 Stanek critiqued a study by Wong (1988) that attempted to estimate the amount of soil ingested
3 by two groups of children. Wong (1988) studied a total of 52 children who were in two separate
4 government institutions in Jamaica. The children had an average age of 3.1 years (ranging from
5 0.3 to 7.6 years) and 7.2 years (ranging from 1.8 to 14 years). The younger group (from the
6 Glenhope Place of Safety) contained 24 children and the older group (from the Reddies Place of
7 Safety) had 28 children. Fecal samples were obtained from the subject children and the amount
8 of silicon, a soil tracer, in dry feces was measured in order to quantify soil ingestion.
9 Using a hospital control group of 30 children with an average age of 4.8 years (ranging
10 from 0.3 to 12 years), the authors of the study collected an unspecified number of daily fecal
11 samples. Based on these samples, dry feces were observed as containing 1.45 percent silicon or
12 14.5 mg of silicon per 1 g of dry feces. The authors assumed that this amount of silicon in dry
13 feces was representative of the typical background amount of silicon from dietary sources only.
14 Observed quantities of silicon greater than 1.45 percent were then assumed to be from soil
15 ingestion.
Wong (1988) calculated the amount of soil ingested by using the standard soil ingestion
17 estimation formula (Binder et al. 1986). One fecal sample was collected from each subject per
18 month over the four month study period.
19 For the 28 children in the older group (average age 7.2 years), soil ingestion was
20 estimated to be 58 mg/day based on the mean minus one outlier and 1,520 mg/day based on the
21 mean of all the children. The group contained one outlier, a child with an estimated average soil
22 ingestion rate of 41 g/day over the four months. Some of the observed soil ingestion results for
23 this group of children included:
24
25 • 7 of 28 had average soil ingestion of > 100 mg/day,
26 • 4 of 28 had average soil ingestion of >200 mg/day,
27 • 1 of 28 had average soil ingestion of >300 mg/day, and
28 • 8 of 28 showed no indication of soil ingestion for any month.
29
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1 Estimated average soil ingestion in the younger group of children (average age 3.1 years)
2 was higher. The mean soil ingestion of all the children was 470 ± 370 mg/day. Due to some
3 sample losses, of the 24 children studied, only 15 subjects had samples for each of the four
4 months. Observed soil ingestion estimates for this group included:
5
6 • 14 of 24 had average soil ingestion of <100 mg/day,
7 • 10 of 24 had average soil ingestion of > 100 mg/day,
8 • . 5 of 24 had average soil ingestion of >600 mg/day,
9 • 4 of 24 had average soil ingestion of > 1,000 mg/day, and
10 • 5 of 24 showed no indication of soil ingestion for any month.
11 - . '
12 Over the entire 4 month study duration, 9 of 84 total samples (or 10.5%) showed soil
13 ingestion estimates of >1 g/day (pica behavior). Of the 52 children studied by Wong (1988), six
14 children displayed soil pica behavior. The estimated soil ingestion for each of these subjects is
15 shown in Table 5-17. For the younger group of children (Glenhope Place of Safety), 5 of 24 (or
16 20.8%) displayed soil pica behavior on at least one occasion. A high degree of daily variability
17 in soil ingestion was observed among the 6 children exhibiting pica behavior. As shown in Table
18 5-17,3 of 6 children (#11, 12, and 22) showed soil pica on only 1 of 4 days. The other 3 children
19 (#14,18, and 27) ingested s> 1.0 g/d on 2 of 4. on 3 of 4, and 4 of 4 days, respectively. Subject
20 #27 displayed a high degree of soil pica, ranging from 3.7 to 60.6 g/d of soil ingestion; however,
21 it was indicated that this child was mentally retarded while the other pica children were
22 considered to have normal mental capabilities.
23 Sources of uncertainty or error in this study include differences between the hospital (i.e.,
24 control) study group (the background control) and the 2 study groups; lack of information on the
25 dietary intake of silicon for the studied children; use of a single fecal sample; and loss of fecal
26 samples. The use of a single soil tracer may also introduce error since there may be other sources
27 from which the tracer could originate. For example, some toothpastes have extremely high
28 concentrations of silicon and children could ingest significant quantities of toothpaste.
29 Additionally, tracers could be found in indoor dust that children may ingest. However, given
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1 these uncertainties, the results are important in that they indicate that soil pica is not a rare
2 occurrence in younger children.
3
4 Stanek et al. (1998) - Prevalence of Soil Mouthing/Ingestion among Healthy Children
5 Aged 1 to 6 - Stanek et al. (1998) presented a methodology that links mouthing behavior among
6 children to the prevalence of ingestion of non-food items. Soil ingestion data were collected via
7 face-to-face interviews over a period of 3 months from parents or guardians of 533 children ages
8 1 to 6 years old attending well-visits in Western Massachusetts. Three clinics participated in this
9 study during the months of August, September, and October, 1992: Kaiser Permanente's clinic in
10 Amherst, a private clinic associated with the Cooley Dickinson Hospital in Northampton, and the
11 Bay State Medical Center clinic in Springfield. Stanek et al. (1998) questioned the participants
12 about the frequency of 28 mouthing behaviors of the children over the past month in addition to
13 exposure time (e.g., time outdoors, play in sand or dirt) and children's characteristics (e.g.,
14 teething). Response categories of the clinic questionnaire corresponded to daily, at least weekly,
15 at least monthly, and never. Stanek et al. (1998) expressed the mouthing rate for each child as
6 the sum of rates for responses to four questions on mouthing specific outdoor objects.
17 Regression models with variables in a step-wise manner identified factors related to high outdoor
18 mouthing rates. Stanek et al. (1998) first considered variables that indicated opportunity for
19 exposure, then subjects' characteristics (e.g., teething) and environmental factors, and finally,
20 concurrent reported behaviors. <•
21 Table 5-18 presents the prevalence of non-ingestion/mouthing behaviors by child's age as
22 the percent of children whose parents reported the behavior in the past month. Stanek etal.
23 (1998) found that outdoor soil mouthing behavior prevalence was higher than indoor dust
24 mouthing prevalence, but both behaviors had highest prevalence among 1-year-old children, and
25 dropped quickly among children 2 years old and older. Stanek et al. (1998) conducted principal
26 component analyses on response to four questions relating to ingestion of outdoor objects
27 (Table 5-18) in an attempt to characterize variability. Responses were converted to mouthing
28 rates per week, using values of 0, 0.25,1, and 7 for responses of never, monthly, weekly, and
29 daily ingestion. Stanek et al. (1998) found outdoor ingestion/mouthing rates for children 1 years
0 of age to be 4.73 per week and 0.44 per week for children 2-6 years of age. Stanek et al. (1998)
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1 estimated the frequency of children playing in sand/dirt as a measure of potential exposure, and
2 found that 71 percent of the children were reported to play in sand or dirt at least weekly, and 45
3 percent were reported as playing in the sand or dirt daily. The authors found that children who
4 played in the sand or dirt had higher outdoor object ingestion/mouthing rates. Thus, children
5 with higher direct exposure to sand or dirt were more likely to ingest or mouth on outdoor
6 objects. Stanek et al. (1998) found similar results when comparing the time spent outdoors to
7 reported outdoor ingestion and mouthing rates. Sixty-five percent of one-year old children were
8 reported to spend less than 3 hour per day outdoors, while 42 percent of children 2-6 years old
9 spend less than 3 hours per day outdoors.
10 Table 5-19 presents average outdoor mouthing rates by age and sand/dirt play frequency.
11 Stanek et al. (1998) presented the data for children by quartiles according to their general
12 mouthing rates and applied linear regression models fit to general mouthing rates. The authors
13 found a significant slope for all groups but one, and thus demonstrated that outdoor mouthing
14 behavior increased with higher quartiles and that rates of increase depended on age and sand/soil
15 play exposure.
16 A strength of this study is that it focuses on the prevalence of specific behaviors to
17 quantify soil mouthing or ingestion among healthy children. The results of this study might have
18 important health implications as it showed that one-year-old children with high general levels of
19 mouthing behavior have the potential for high risk soil ingestion. /
20 A limitation associated with this study is that the data are based on recall behavior from
21 the summer previous to the interview. Extrapolation to other seasons may be difficult. In
22 addition, data were collected for children in Western Massachusetts and data were only available
23 for the healthy children who were present for well-visits.
24
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1 5.5 RECOMMENDATIONS
2 The studies described in this section were used to recommend values for soil intake
3 among children. Estimates of the amount of soil ingested by children are summarized in Table
4 5-20 and the recommended values are presented in Table 5-21. The mean values ranged from 39
5 mg/day to 271 mg/day with an average of 13 8 mg/day for soil ingestion and 193 mg/day for soil
6 and dust ingestion. Results obtained using titanium as a tracer in the Binder etal. (1986) and
7 Clausing et al. (1987) studies were not considered in the derivation of this recommendation
8 because these studies did not take into consideration other sources of the element in the diet
9 which for titanium seems to be significant. Therefore, these values may overestimate the soil
10 intake. One can note that this group of mean values is consistent with the 200 mg/day value that
11 EPA programs have used as a conservative mean estimate. Taking into consideration that the
12 highest values were seen with titanium, which may exhibit greater variability than the other
13 tracers, and the fact that the Calabrese et al. (1989) study included a pica child, 100 mg/day is the
14 best estimate of the mean for children under 6 years of age. However, since the children were
15 studied for short periods of time and the prevalence of pica behavior is not known, excluding the
pica child from the calculations may underestimate soil intake rates. It is plausible that many
17 children may exhibit some pica behavior if studied for longer periods of time. Over the period of
18 study, upper percentile values ranged from 106 mg/day to 1,432 mg/day with an average of 358
19 mg/day for soil ingestion and 790 mg/day for soil and dust ingestion. Rounding to one
20 significant figure, the recommended upper percentile soil ingestion rate for children is 400
21 mg/day. However, since the period of study was short, these values are not estimates of usual
22 intake.
23 Data on soil ingestion rates for children who deliberately ingest soil are also limited. An
24 ingestion rate of 10 g/day is a reasonable value for use in acute exposure assessments, based on
25 the available information. It should be noted, however, that this value is based on only one pica
26 child observed in the Calabrese et al. (1989) study.
27 It should be noted that these recommendations are based on studies that used different
28 survey designs and populations. For example, some of the studies considered food and nonfood
29 sources of trace elements, while others did not. In other studies, soil ingestion estimates were
P adjusted to account for the contribution of house dust to this estimate. Despite these differences,
June 2000 - 5-25 DRAFT-DO NOT QUOTE OR CITE
-------
1 the mean and upper-percentile estimates reported for these studies are relatively consistent. The
2 confidence rating for soil intake recommendations is presented in Table 5-22. It is important,
3 however, to understand the various uncertainties associated with these values. First, individuals
4 were not studied for sufficient periods of time to get a good estimate of the usual intake.
5 Therefore, the values presented in this section may not be representative of long term exposures.
6 Second, the experimental error in measuring soil ingestion values for individual children is also a
7 source of uncertainty. For example, incomplete sample collection of both input (i.e., food and
8 nonfood sources) and output (i.e., urine and feces) is a limitation for some of the studies
9 conducted. In addition, an individual's soil ingestion value may be artificially high or low
10 depending on the extent to which a mismatch between input and output occurs due to individual
11 variation in the gastrointestinal transit time. Third, the degree to which the tracer elements used
12 in these studies are absorbed in the human body is uncertain. Accuracy of the soil ingestion
13 estimates depends on how good this assumption is. Fourth, there is uncertainty with regard to
14 the homogeneity of soil samples and the accuracy of parent's knowledge about their child's
15 playing areas. Fifth, all the soil ingestion studies presented in this section with the exception of
16 Calabrese et al. (1989) were conducted during the summer when soil contact is more likely.
17 Although the recommendations presented below are derived from studies which were
18 mostly conducted in the summer, exposure during the winter months when the ground is frozen
19 or snow covered should not be considered as zero. Exposure during these months, although
20 lower than in the summer months, would not be zero because some portion of the house dust
21 comes from outdoor soil.
22
23
June 2000 5-26 DRAFT-DO NOT QUOTE OR CITE
-------
1 5.6 REFERENCES FOR CHAPTER 5
2
3 Binder, S.; Sokal, D.; Maughan, D. (1986) Estimating soil ingestion: the use of tracer elements in estimating the
4 amount of soil ingested by young children. Arch. Environ. Health. 41 (6):341 -345.
5
6 Behrman, L.E.; Vaughan, V.C., III. (1983) Textbook of Pediatrics. Philadelphia, PA: W^B. Saunders Company.
8 Bruhn, CM.; Pangborn, R.M. (1971) Reported incidence of pica among migrant families. J. of the Am. Diet.
9 Assoc. 58:417-420.
10
11 Calabrese, E.J.; Stanek, E.J. (1992) Distinguishing outdoor soil ingestion from indoor dust ingestion in a soil pica
12 child. Regul. Toxicol. Pharmacol, 15:83-85.
13 '
14 Calabrese, E.J.; Stanek, E.J. (1993) Soil pica: not a rare event. J. Environ. Sci. Health. A28(2):373-384.
15 •
16 Calabrese, E.J.; Stanek, E.J. (1995) Resolving intertracer inconsistencies in soil ingestion estimation. Environ.
17 Health Perspect. 103(5):454-456.
18
19 Calabrese, E.J.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.-; et al. (1989) How much soil do young
20 children ingest: an epidemiologic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, MI.
21 pp. 363-397.
22
23 Calabrese, E.J.; Stanek, E.J.; Gilbert, C.E. (1991) Evidence of soil-pica behavior and quantification of soil
24 ingested. Hum. Exp. Toxicol. 10:245-249.
25
26 Calabrese, E.J.; Stanek, E.J.; Pekow, P.; Barnes, R.M. (1997) Soil ingestion estimates for children residing on a
>27 Superfund site. Ecotoxicology and Environmental Safety. 36:258-268.
28
29 Clausing, P.; Brunekreef, B.; Van Wijnen, J.H. (1987) A method for estimating soil ingestion by children. Int.
30 Arch. Occup. Environ. Health (W. Germany) 59( 1 ):73-82.
31
32 Danford, D.C. (1982) Pica and nutrition. Annual Review of Nutrition. 2:303-322.
33
34 Davis, S.; Waller, P.; Buschbon, R.; Ballou, J.; White, P. (1990) Quantitative estimates of soil ingestion in normal
35 children between the ages of 2 and 7 years: population based estimates using aluminum, silicon, and titanium
36 as soil tracer elements. Arch. Environ. Hlth. 45:112-122.
37
38 Feldman, M.D. (1986) Pica: current perspectives. Psychosomatics (USA) 27(7):519-523.
39
40 Forfar, J.O.; Ameil, G.C., eds. (1984) Textbook of Paediatrics. 3rd ed. London: Churchill Livingstone.
41
42 Illingworth, R.S. (1983) The normal child. New York: Churchill Livingstone.
43
44 Kaplan, H.I.; Sadock, B.J. (1985) Comprehensive textbook of psych iatry/IV. Baltimore, MD: Williams and
45 . Wilkins.'
46
47 Kimbrough, R.; Falk, H.; Stemr, P.; Fries, G. (1984) Health implications of 2,3,7,8-tetrachlorodibenzo-p-dioxin
48 (TCDD) contamination of residential soil. J. Toxicol. Environ. Health 14:47-93.
49
50 Lourie, R.S.; Layman, E.M.; Millican, F.K. (1963) Why children eat things that are not food. Children
51 10:143-146.
52
|>3 Sayetta, R.B. (1986) Pica: An overview. American Family Physician 33(5):181-185.
June 2000 5-27 DRAFT-DO NOT QUOTE OR CITE
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1 Sedman, R.; Mahmood, R.S. (1994) Soil ingestion by children and adults reconsidered using the results of recent
2 tracer studies. Air and Waste, 44:141-144.
3
4 Stanek, E.J.; Caiabrese, EJ. (1995a) Daily estimates of soil ingestion in children. Environ. Health Perspect.
5 103(3):276-285.
6
7 Stanek, E.J.; Caiabrese, E.J. (1995b) Soil ingestion estimates for use in site evaluations based on the best tracer
8 method. Human and Ecological Risk Assessment. 1:133-156.
9
10 Stanek, E.J.; Caiabrese, E.J.; Mundt, K.; Pekow, P.; Yeatts, K.B. (1998) Prevalence of soil mouthing/ingestion
11 among healthy children aged 1 to 6. Journal of Soil Contamination. 7(2):227-242.
12
13 Thompson, K.M.; Burmaster, D.E. (1991) Parametric distributions for soil ingestion by children. Risk Analysis.
14 11:339-342.
15
16 U.S. EPA. (1984) Risk analysis of TCDD contaminated soil. Washington, DC: U.S. Environmental Protection
17 Agency, Office of Health and Environmental Assessment. EPA 600/8-84-031.
18
19 Van Wijnen, J.H.; Clausing, P.; Brunekreff, B. (1990) Estimated soil jngestion by children. Environ. Res. 51:147-
20 162.
21
22 Vermeer, D.E.; Frate, D.A. (1979) Geophagia in rural Mississippi: environmental and cultural contexts and
23 nutritional implications. Am. J. Clin. Nutr. 32:2129-2135.
24 .
25 Wong, M.S. (1988) The Role of Environmental and Host Behavioural Factors in Determining Exposure to
26 Infection with Ascaris iumbricoides and Trichuris trichlura. Ph.D. Thesis, Faculty of Natural Sciences,
27 University of the West Indies. 1988.
June 2000 5-28 DRAFT-DO NOT QUOTE OR CITE
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1 Table 5-1. Estimated Daily Soil Ingestion Based on Aluminum,
2 Silicon, and Titanium Concentrations
3
4
5
6
7
8
9
10
11 Source: Binder etal. (1986).
12
13
14
Estimation
Method
Aluminum
Silicon
Titanium
Minimum
Mean
(mg/day)
181
184
1,834
108
Median
(mg/day)
121
136
618
88
Standard
Deviation
(mg/day)
203
175
3,091
121
Range
(mg/day)
25-1,324
31-799
4-17,076
4-708
95th
Percentile
(mg/day)
584
5,78
9,590
386
Geometric
Mean
(me/day)
128
130
401
65
June 2000 5-29 DRAFT-DO NOT QUOTE OR CITE
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1
2 '
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Child
l
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table
Sample
Number
L3
L14
L25
L5
L13
L27
L2
L17
L4
111
L8
L21
L12
L16
L18
L22
LI
L6
L7
L9
L10
L15
L19
L20
L23
L24
L26
Arithmetic
Mean
Source:
5-2. Calculated Soil
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
Ingestion by Nursery
Soil Ingestion as
School Children
Soil Ingestion as
Calculated from Al Calculated from AIR
(mg/day)
300
211
23
_
103
81
42
566
62
65
.
-
693
-
.
77
82
979
200
i
195
.
71.
212
51
566
56
232
(mg/day)
107
172
-
71
82
84
84
174-
145
139
108
152
362
145
120
-
96
11!
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
ill
124
95
106
48
71
212
51
64
56
105
Adapted from Clausing et al. (1 987).
.
June 2000
5-30
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1
2
3
4
5
6
7
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
Child
I
2
3
4
5
6
Arithmetic Mean
Source: Adapted
Table 5-3.
Sample
05
G6
01
02
08
G3
04
07
from Clausing et al.
Calculated Soil Ingestion by Hospitalized,
Bedridden Children
Soil Ingestion as
Calculated from Ti
(ma/day)
3,290
4,790
28
6,570
2,480
28
1,100
58
2,293
(1987).
Soil Ingestion as
Calculated from Al
(me/day)
57
71
26
94
57
77
30
38
56
Limiting Tracer
(ma/day")
57
71
26
84
57
28
30
38
49
i Table 5-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements
300
Tracer Element Mean
Al
Ba
Mn
Si
Ti
V
Y
Zr
Source: Adapted
152.8
2304.3
1177.2
139.3
251.5
' 345.0
120.5
80.6
from Calabrese et al.
mg Soil ingested
SD
107.5
4533.0
1341.0
149.6
316.0
247.0
42.4
43.7
(1989).
1, 500 mg Soil
Mean
93.5
149.8
248.3
91.8
286.3
147.6
87.5 '
54.6
Ingested
SD
15.5
69.5
183.6
16.6
380.0
66.8
12.6
33.4
June 2000
5-31
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1
2
3
4
5
6
7
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
45
46
Table 5-5. Soil and Dust Ingestion Estimates for
Children Ages 1-4 Years
Intake (mg/day)a
Tracer Element N Mean
Aluminum
soil 64 153
dust 64 317
soil/dust combined 64 154
Silicon
soil 64 154
dust 64 964
soil/dust combined 64 483
Yttrium
soil 62 85
dust 64 62
soil/dust combined 62 65
Titanium
soil 64 218
dust 64 163
soil/dust combined 64 1 70
'Corrected for Tracer Concentrations in Foods
Source: Adapted from Calabrese et al. (1989).
Table 5-6. Average Daily
Aluminum, Silicon, and
Element . Mean Median
(mg/d) (mg/d)
Aluminum 38.9 25.3
Silicon 82.4 59.4
Titanium 245.5 81.3
Minimum 38.9 25.3
Maximum 245.5 81.3
95th
Median SD Percentile Maximum
29 852 223 6,837
- 31 1,272 . 506 8,462
30 629 478 4,929
40 693 276 5,549
49 6,848 692 54,870
49 3,105 653 24,900
9 890 106 6,736
15 687 169 5,096
11 717 159 5,269
55 1,150 1,432 6,707
28 659 1,266 3,354
30 691 1,059 3,597
Soil Ingestion Values Based on
Titanium as Tracer Elements8
Standard Error of
the Mean Range
(mg/d) (mg/d)b
14.4 279.0 to 904.5
12.2 -404.0 to 534.6
119.7 -5,820.8 to 6,1 82.2
12.2 -5,820.8
119.7 6,182.2
"Excludes three children who did not provide any samples (N=101).
""Negative values occurred as a result of correction for nonsoil sources of the tracer elements.
Source: Adapted from Davis et al. (1990).
June 2000
5-32
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
>18
1 0
20
21
22
Table 5-7. Geometric Mean (Gm) and Standard Deviation (Gsd)
Ltm Values for Children at Daycare Centers and Campgrounds
Daycare Centers
1
Age (yrs) Sex n
<1 Girls 3
Boys 1
l-<2 Girls 20
Boys 17
2-<3 Girls 34
Boys 17
3-* Girls 26
Boys 29
4-<5 Girls 1
Boys 4
All girls . 86
All boys 72
Total 162"
GMLTM
(mg/day)
81
75
124
114
118
96
111
110
180
99
117
104
111
GSD LTM
(mg/day)
1.09
-
1.87
1.47
1.74
1.53
1.57
1.32
.
1.62
1.70
1.46
1.60
n
_
-
3
5
4
8
6
8
19
18
36
42
78b
Campgrounds
GMLTM
(mg/day)
.
-
207
312
367
232
164
148
164
136
179
169
174
GSD LTM
(mg/day)
.
-
1.99
2.58
2.44
2.15
1.27
1.42
.48
.30
.67
.79
.73
"Age and/or sex not registered for eight children.
"Age not registered for seven children.
Source: Adapted from Van Wijnen et al.
(1990).
June 2000
5-33
DRAFT-DO NOT QUOTE OR CITE
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f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Table 5-8. Estimated Geometric Mean Ltm Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period
First Sampling Period
Weather Category Age
(years)
Bad
(>4 days/week
precipitation)
Reasonable
(2-3 days/week
precipitation)
Good
(<2 days/week
precipitation)
Source: Van Wijnen
<1
l-<2
2-<3
4-<5
<1
1-<2
2-<3
3-<4
4-<5
<1
l-<2
2-<3
3-<4
4-<5
etal.(!990).
Second Sampling Period
Estimated Estimated Geometric
Geometric Mean Mean
LTM Value LTM Value
n
3
18
33
5
4
' 42
65
67
10
(mg/day)
94
103
. 109
124
102
229
166
138
132
n
^
33
48
6
1
10
13
19
1
(mg/day)
67
80
91
109
61
96
99
94
61
June 2000
5-34
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
125
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Table 5-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates
per Child for 64 Children4 (Mg/day)
Type of Estimate
Number of
Samples
Mean
25th Percentile
50th Percentile
75th Percentile
90th Percentile
95th Percentile
Maximum
Overall
(64)
179
10
45
88
186
, 208
7.703
Al
(64)
122
10
. 19
73 '
131
254
4.692
Ba
(33)
655
28
65
260
470
518
17.991
Mn
(19)
1,053
35
121
319
478
17,374
17.374
Si
(63)
139
5
32
94
206
224
4.975
Ti
(56)
271
8
31
93
154
279
12.055
V
(52)
H2
8
47
177
340
398
845
Y
(61)
165
0
15
47
105
144
8.976
Zr
(62)
23
0
15
41
87
117
208
"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 percentiJes 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: Stanekand Calabrese(I995a).
Table 5-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected over 365 Days*
Range
50th Percentile (median)
90th Percentile
95th Percentile
1 - 2,268 mg/db
75mg/d
1,190 mg/d
l,751mg/d
* Based on fitting a log-normal distribution to model daily soil ingestion values.
b Subject with pica excluded.
Source: StanekandCalabrese(1995a).
June 2000
5-35
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
Table 5-11. Estimated Soil Ingestion Rate Summary Statistics
And Parameters for Distributions Using Binder et Al. (1986)
Data with Actual Fecal Weights
Soil Intake (nag/day)
Trace Element Basis
Mean
Min
10th
20th
30th
40th
Med
60th
70th
80th
90th
Max
Median
Standard Deviation
Arithmetic Mean
Al
97
11
21
33
39
43
45
55
73
104
197
1,201
45
169
97
Si
85
10
19
23
36
52
60
65
79
106
166
642
Lognormal Distribution
60
95
85
Ti
1,004
1
3
22
47
172
293
475
724
3,071
2,105
14,061
Parameters
„
_
—
MEAN8
91
13
22
34
43
49
59
69
92
100
143
921
59
126
91
Underlying Normal Distribution Parameters
Mean
Standard Deviation
4.06
0.88
4.07
0.85
_
—
4.13
0.80
3 MEAN = arithmetic average of soil ingestion based on aluminum and silicon.
Source: Thompson and Burmaster {1991).
June 2000
5-36
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table 5-12. Positive/negative Error (Bias) in Soil Ingestion Estimates in the Calabrese et Al. (1989)
Mass-balance Study: Effect on Mean Soil Ingestion Estimate (Mg/day )a
Negative Error
Aluminum
Silicon
Titanium
Vanadium
Yttrium
Zirconium
Lack of Fecal
Sample on Final
Study Day
14
15
82
66
8
6
Other
Causes"
11
6
187
55
26
91
Total
Negative
Error
25
21
269
121
34
97
Total
Positive
Error
43
41
282
432
22
5
Net Error
+18
+20
+13
+311
-12
-92
Original
Mean
153
154
218
459
85
21
Adjusted
Mean
136
133
208
148
97
113
'How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The
cumulative total negative error is estimated to bias the mean estimate by 25 mg/day downward. However,
aluminum has positive error biasing the original mean upward by 43 mg/day. The net bias in the original
mean was i 8 mg/day positive bias. Thus, the original 156 mg/day mean for aluminum should be corrected
downward to 136 mg/day.
bVaiues indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
Source: Calabrese and Stanek( 1995).
June 2000
5-37
DRAFT-DO NOT QUOTE OR CITE
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s "s
S*|
1 o
Q
TT
iA
u
JS
^T
— (N vO TT tr o*^ in ^^ n^
i
P-; O — — I-;
£n cv Pi o P
— • —
-------
1
2 Table 5-15. Daily Soil Ingestion Estimation in a Soil-pica
3 . Child by Tracer and by Week (mg/day)
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Tracer
Al
Ba
Mn
Si
Ti
V
Y
Zr
Week I
Estimated Soil Ingestion
74
458
2,221
142
1,543
1,269
147
86
Week 2
Estimated Soil Ingestion
13,600
12,088
12,341
10,955
11,870
10,071
13,325
2.695
Source: Calabrese et al. (1991).
June 2000 5-40 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Table 5-16.
Ratios of Soil,
Dust, and Residual Fecal
Samples in the Soil Pica Child
Tracer Ratio
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Pairs
Mn/Ti
Ba/Ti
Si/Ti
V/Ti
Ai/Ti
Y/Ti
Mn/Y
Ba/Y
Si/Y
V/Y
Al/Y
Mn/AI
Ba/Al
Si/Al
V/A1
Si/V
•'Mn/Si
Ba/Si
Mn/Ba
Source: Calabreseand
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
Stanek(1992).
Fecal
215.241
206.191
136.662
10.261
21.087
9.621
22.373
21.432
14.205
1.067
2.I'92
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 % of 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
June 2000
5-41
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
Table 5-17. Daily variation of Soil Ingestion by Children Displaying Soil Pica in Wong (1988)
Child subject number Month Estimated soil ingestion
(mg/dayr
Glenhope Place of Study
Number 1 1
Number 12
Number 14
Number 18
Number 22
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
55
1,447
22
40
0
0
7,924
192
1,016
464 .
2,690
898
30
10,343
4,222
1,404
0
—
5,341
0
Reddles Place of Study
Number 27
1
2
3
4
48,314
60,692
51,422
3,782
Source: Calabrese and Stanek (1993).
June 2000
5-42
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
Table 5-18. Prevalence of Non-Food Ingestion/Mouthing Behaviors fay Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month
Child's Age (years)
Non-Food Ingestion/mouthing prevalence
Outdoor "soil" mouthing/Ingestion
Sand, stones
Grass, leaves, flowers
Twigs, sticks, woodchips
Soil, dirt
Dust, lint, dustballs
Plaster, chaik
Paintchips, splinters
General mouthing of objects
Other toys
Paper, cardboard, tissues
Teething toys
N
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
%> Weekly
% Daily
% > Monthly
%> Weekly
%,Daily
% > Monthly
%> Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
%> Weekly
% Daily
1
171
54
36 .
17
48
34
16
42
29
12
38
24
11
14
1
2
8
5
2
6
2
0
88
82
63
71
54
28
65
55
44
2
70
26
10
0
16
7
0
23
7
0
21
7
0
4
1
0
10
3
0
0
0
0
53
44
27
37
23
9
29
16
6
3
93
19
6
2
24
14
2
13
9
0
5
3
i
2
1
0
3
0
0
0
0
0
64
42
20
32
20
8
15
9
6
4
82
9
2
1
13
4
1
13
5
1
7
2
0
0
0
0
2
I
1
4
1
0
44
26
9
23
12
5
4
1
0
5
90
7
4
1
9
6
1
11
7
0
3
1
1
0
0
0
3
0
0
1
0
0
42
28
7
18
7.
2
3
1
0
6
22
9
5
5
5
0
0
5
0
0
9
9
0
5
0
0
5
0
0
0
0
0
23
9
5
14
9
5
9
9
9
All
528
27
16
6
26
16
6
23
14
4
18
10
4.
6
3
1
5
2
1
3
1
0
62
49
30
41
28
13
29
22
17
June 2000
DRAFT-DO NOT QUOTE OR CITE
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Table 5-18.' Prevalence of Non-Food Ingestion/Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month (continued)
1 Crayons, pencils, erasers
2
3
4 Blankets, cloth
5
6
7 Shoes, Foorware
8
9
10 Clothing
11
12
13 Other items
14
15
16 Crib, chairs, furniture
17
18
19 Sucking of fingers, etc
20 Suck fingers/thumb
21
22
23 Suck feet or toes
24
25
26 Use pacifier
27
28
29 Suck hair
30
31
% > Monthly
% > Weekly
% Daiiy
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Dajly
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly.
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
56
41
19
51
42
29
50
42
20
49
39
25
41
35
22
37
26
13
67
60
44
37
23
8
24
22
20
1
1
1
54
37
17
21
17
11
23
10
1
34
24
7
30
26
ii
11
9
3
41
27
21
14
4
1
9
9
6
3
3
I
46
25
4
26
17
9
8
3
0
37
23
11
30'
24
15
8
3
1
43
31
22
12
3
0
6
5
5
8
2
1
50
27
6
22
18
' 13
7
2
0
43
28
9
23
15
7
10
5
1
57
43
26
11
2
I
2
2
1
9
2
0
41
26
4
22
14
7
2
1
0
26
16
6
21
10
6
4
2
0
39
31
24
3
I
0
2
2
1
10
4
2
36
27
18
14
14
5
5
5
0
27
14
14
27
14
5
5
0
0
41
18
14
0
0
0
5
0
0
5
5
0
50
32
12
32
25
16
22
16
7
.39
27
14
31
23
14
17
11
5
52
41
30
18
9
3
11
10
9
5
2
1
June 2000
5-44
DRAFT-DO NOT QUOTE OR CITE
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Table 5-18. Prevalence of Non-Food Ingestion/Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month (continued)
1 "Disgusting" object mouth ing/ingestion
2 Soap, detergent, shampoo
3
4
5 . Plastic, plastic wrap
6
7
8 Cigarette butts, tobacco
9
10
1 1 Matches
12
13
14 Insect
15
16
17 Other ingestion and behaviors
18 Toothpaste
19
20
21 Chew gum
22
23
24 . Bite nails
25
26
27 Suck hair
28
29
30
31 "Source: Staneketal. (1998).
32
33
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
, % > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
%> Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
% > Monthly
% > Weekly
% Daily
-
48
37
15
32
22
7
16
10
4
6
2
1
5
2
0
63
60
52
18
10
3
8
5
2
62
57
42
34
27
14
19
11
4
6
4
0
4
3
0
1
0
0
97
94
87
56
40
17
26
23
7
76
64
39
24
14
3
8
3
1
5
4
1
1
1
0
2
}
1
92
91
86
76
60
18
31
24
12
85
77
43
!7
11
2
7
4
0
4
1
1
4
1
0
4
4
2
94
93
93
76
60
13
29
20
9
96
88
55
9
6
0
9
4
1
3
2
1
I
1
0
2
2
2
93
92
89
91
69
21
33
26
10
88
81
52
9
9
0
0
0
0
5
5
0
0
0
0
0
0
0
86
86
82
100
68
36
59
45
14
73
68
45
29
21
8
17
10
3
8
5
2
4
2
0
3
2
1
84
82
77 •
58
43
14
24
18
7
78
71
45
June 2000
5-45
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 5-19. Average Outdoor Object Mouthing Scores for Children by
Age, Frequency of Sand/Dirt Play, and General Mouthing Quartiies
1 Year old
Sand/dirt play?
Outdoor object >Daily Daily
mouthing scores Mean N Mean N
General mouthing
Score quart iles (Mean)
1st Quartile(1.5) 0.1 19 2.8 16
2nd Quartile (9.7) 0.7 14 3.9 1 1
3rd Quartile ( 19.6) 1.3 33 10.5 22
4th Quartile (3 5.6) 3.6 35 14 23
Slope based on general
mouthing quartile score 0-M °34
SE 0.052 0.060
Source: Stanek et al. ( 1 998).
Age 2 to 6 years
Sand/dirt play?
>DaiIy Daily
Mean N Mean N
0.1 139 0.5 117
0.3 27 0.8 28
0.2 19 1.8 21
0.5 2 1.5 4
0.007 0.054
0.021 0.019
June 2000
5-46
DRAFT-DO NOT QUOTE OR CITE
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1 Table 5-20. Summary of Estimates of Soil Ingestion by Children
2
3 Mean (mg/day)
4 Al Si AIR1 Ti , Y
5 181 184
6 230 129
7 39 82 245.5
8 64.5" 160" 268.4"
9 153 154 218 85
10 154" 483b 170" 65"
11 122 139 - 271 165
12 133e
13 69-120"
14 66'
15 196b
16 Average = 138 mg/day soil
17 1 93 mg/day soil and dust combined
18 'AIR = Acid Insoluble Residue
1 9 "Soil and dust combined
20 CBTM
21 "LTM; corrected value
22
23
24
25
26
Upper Percentile (mg/day) References
Al Si Ti Y
584 578 Binder etal. 1986
Clausing etal. 1987
Davis etal. 1990
223 276 1,432 106 Calabrese etal. 1989
478" 653" 1,059" 159"
254 224 279 144 Stanek and Calabrese, 1995a
2 1 T Stanek and Calabrese, 1 995b
Van Wynen et al. 1990
280' Calabrese etal. 1997
994"
358 mg/day soil
790 mg/day soil and dust combined
,
27 Table 5-2 1 . Summary of Recommended Values for Soil Ingestion
28 Population Mean
29 Children (age 1 -6 years) 1 00
30 Pica child 10
Upper Percentile
mg/day 400 mg/day
g/day -~
3 1 "200 mg/day may be used as a conservative estimate of the mean (see text).
32 bStudy period was short; therefore, these values are not estimates of usual intake.
33 To be used in acute exposure assessments. Based
34
35
36
on only one pica child (Calabrese et al., 1989).
June 2000
5-47
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
8
9
10
11
12
Table 5-22. Confidence in Soil Intake Recommendation
Considerations
Rationale
Rating
13
14
15
16
17
18
19
20
21
22
Study Elements
• Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of interest
• Data pertinent to U.S.
• Primary data
• Currency
• Adequacy of data collection period
• Validity of approach
Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high
rating is desirable)
• Measurement error
Other Elements
• Number of studies
• Agreement between researchers
Overall Rating
All key studies are from peer review literature.
Papers are widely available from peer review journals.
Methodology used was presented, but results are difficult
to reproduce.
The focus of the studies was on estimating soil intake rate
by children: studies did not focus on intake rate by adults.
Two of the key studies focused on Dutch children: other
studies used children from specific areas of the U.S.
All the studies were based on primary data.
Studies were conducted after 1980.
Children were not studied long enough to fully
characterize day to day variability.
The basic approach is the only practical way to study soil
intake, but refinements are needed in tracer selection and
matching input with outputs. The more recent studies
corrected the data for sources of the tracers in food. There
are. however, some concerns about absorption of the
tracers into the body and tag time between input and
output
The sample sizes used in the key studies were adequate for
children. However, only few adults have been studied.
The study population may not be representative of the U.S.
in terms of race, socio-economics, and geographical
location: Studies focused on specific areas: two of the
studies used Dutch children.
Day-to-day variability was not very well characterized.
The selection of the population studied may introduce
some bias in the results (i.e., children near a smelter site,
volunteers in nursery school. Dutch children).
Errors may result due to problems with absorption of the
tracers in the body and mismatching inputs and outputs.
There are 7 key studies.
Despite the variability, there is general agreement among
researchers on central estimates of daily intake for
children.
Studies were well designed: results were fairly consistent:
sample size was adequate for children and very small for
adults; accuracy of methodology is uncertain: variability
cannot be characterized due to limitations in data
collection period. Insufficient data to recommend upper
pgrcentile estimates for both children and adults.
High
High
Medium
High (for children)
Low (for adults)
Medium
High
High
Medium
Medium
Medium (for
children)
Low (for adults)
Low
Low
Medium
Medium
High
Medium
Medium (for
children - long-term
central estimate)
Low (for adults)
Low (for upper
percentile)
23
June 2000
5-48
DRAFT-DO NOT QUOTE OR CITE
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1 6. OTHER NON-DIETARY INGESTION FACTORS
2
3 6.1 INTRODUCTION
4 Young children (i.e., ages 6 months through approximately 4 years) also have the
5 potential for exposure to toxic substances through non-dietary ingestion pathways other than soil
6 ingestion (e.g., ingesting pesticide residues that have been transferred from treated surfaces to the
7 hands or objects that are mouthed). These children have an urge to mouth objects or their fingers
8 in exploring their environment, as a sucking reflex, and as a habit (Groot et al., 1998). This route
9 of exposure may exceed other routes ingestion (i.e., food, pica, drinking water, breast milk) and
10 dermal exposure because non-dietary ingestion may result in higher ingestion rates of
11 contaminated material (Weaver et al., 1998). This exposure route is also a difficult route to
12 model because there is little literature or research that has been performed on mouthing behavior
13 (Reed et al., 1998) and little information on the susceptibility of children to toxic substances
14 (Weaver etal., 1998).
15 Mouthing behavior includes all activities in which objects, including fingers, are touched
16 by the mouth or put into the mouth except for eating and drinking, and includes licking, sucking,
17 chewing, and biting (Groot et al., 1998). This exposure route becomes difficult to model because
18 contact with surfaces is intermittent and nonuniform over different parts of the body. The
19 intermittent and nonuniform nature of the mouthing itself also makes this pathway difficult to
20 model (ZartarianetaL, 1997).
21 Children exhibit large differences in mouthing behavior (Groot et al., 1998). Infants are
22 bora with a sucking reflex for breast feeding, and within a few months, children begin to use
23 sucking or mouthing as a means to explore their surroundings. Children will use both sucking
24 and licking to explore their environment. Sucking also becomes a means of-comforting a child
25 when they are tired or upset. In addition, teething normally causes substantial mouthing
26 behavior, sucking or chewing, to alleviate discomfort in their gums. Each child is different, and
27 large differences occur between children, even within the same family.
28 Where mouthing becomes critical in exposure to potentially toxic substances is the
29 proximity and behavior of a small child around potentially contaminated sources. Children play
30 close to the ground and are constantly licking their fingers or mouthing toys or objects. As a
f 1 result, this becomes a potentially significant exposure route for children. They can ingest more
June 2000 6-1 DRAFT-DO NOT QUOTE OR CITE
-------
1 toxic constituents through this behavior than from dietary ingestion or inhalation because the
2 children could place wet, sticky fingers on potentially-contaminated surfaces where more toxic
3 constituents may adhere to the ringers than if the fingers were dry (Gurunathan et al., 1998).
4 Gurunathan et al. (1998) estimate that young children spend as much as 90 percent of
5 their days inside, so exposure to contaminants that may infiltrate the home (i.e., volatile and
6 semi-volatile organic constituents [VOCs and S VOCs]) through the vapor phase may be of
7 concern. This may be a significant pathway of exposure to S VOCs because these compounds
8 can be deposited on surfaces in the home or become absorbed onto plastic toys or in stuffed
9 animals where they can serve as reservoirs for toxic constituents (Gurunathan et al., 1998).
10 There have .been few studies investigating this potential exposure route. The shortage of
11 research and data may be due to the difficulty in observing very young children and the labor-
12 intensive effort in gathering the data (U.S. EPA, 1999). The applicable research efforts use two
13 general approaches to gather data: real-time hand recording in which trained persons observe a
14 child and manually record information on a survey sheet or score sheet; or, videotaping in which
15 trained videographers tape a child's activities and subsequently extract the pertinent data
16 manually or with computer software (U.S. EPA, 1999).
17 Some researchers express mouthing behavior in terms of frequency of occurrence (e.g.,
18 contacts/hour, contacts/minute). Others, express mouthing behavior as a rate in units of minutes
19 per hour of mouthing time. Both approaches have their use in.exposure assessments. The former
20 approach is more appropriate when studying children's behavior during various microactivities.
21 The latter, however, is more useful when studying children's behavior during macroactivities.
22 Macroactivities can be described by a child's general activities such as sleeping, watching
23 television, playing, and eating. Microactivities refer to the specific behavior a child is engaged in
24 such as hand-to-surface contacts and hand-to-mouth behavior (Hubal, 2000). Time spent in
25 various macroactivities in several microenvironments (e.g., indoors at home) are presented in
26 Chapter 9).
27
28 6.2 STUDIES RELATED TO NON-DIETARY INGESTION
29 Groot et al. (1998) - Mouthing Behavior of Young Children - In this study, Groot et al.
30 (1998) examined the mouthing behavior of infants and young children between the ages of 3 and
31 36 months, in the Netherlands. The study was actually part of a larger effort to determine if PVC
June 2000 6-2 DRAFT-DO NOT QUOTE OR CITE
-------
1 toys softened with phthalates could pose health risks to children from mouthing. As part of the
2 effort, Groot et al. (1998) asked parents to observe their children and gather information which
3 could be used to estimate how often children engage in mouthing and the duration spent
4 mouthing during a day. Parents were asked to observe their children ten times per day for 15-
5 minute intervals (i.e., 150 minutes total per day) for two days and measure mouthing with a
6 stopwatch.
7 In total, 36 parents participated in the study and 42 children were observed by their
8 parents. For the study, a distinction was made to differentiate between toys meant for mouthing
9 (e.g., pacifiers, teething rings) and those not meant for mouthing. The time a child spent
10 mouthing a dummy (e.g., pacifier) was not included in the time recorded. Although the sample
11 size was relatively small, the results provide a first-order estimate on mouthing times during a
12 day. Table 6-1 compiles the mouthing times from the Groot et al. (1998) effort. The results
13 show wide variation. The standard deviation in all four age categories except the 3- to 6-month
14 old children exceeds the mean time estimated mouthing during a day. The large standard
15 deviations is not unexpected given the vast behavioral differences from child to child and the
.16 small sample size of the study. The overall trend of the data, however, may be accurate in that it
17 shows that as the children age, the time spent mouthing decreases. The 3- to 6-month children
18 were estimated to mouth 37 minutes per day and the 6- to 12-month children 44 minutes per day.
19 After 12 months, the estimated mouthing time drops quickly to 16 minutes per day for 12- to 18-
20 month children and 9 minutes per day for 18- to 36-month children.
21 The study has several limitations that have an impact on the usability of the data. The
22 initial drawback concerns the small size of the study. Groot et al. (1998) acknowledge this
23 shortcoming and recommend further study using a larger sample population. In addition, the
24 study also incorporated mostly higher-educated persons. The area where the study was
25 performed consisted primarily of parents with higher education. The study had recruited persons
26 of lower education and socioeconomic levels, but these persons chose not to participate in the
27 study after recruitment (Groot et al., 1998). Therefore, the results do hot reflect data from the
28 full spectrum of the population. The study also recorded only the time spent mouthing and not
29 the number of times that mouthing occurred and did not differentiate the types of objects
30 mouthed. In addition, children were observed for a period of two consecutive days and may not
ll reflect long-term behavior. The study may not be representative of the U.S. population.
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1 Reed et al. (1999) - Quantification of Children's Hand and Mouthing Activities through a
2 Videotaping Methodology - In -this study, Reed et al. (1999) used videotaping to quantify the
3 frequency and type of contacts children have during the course of an hour. The contacts included
4 numerous categories: hand to clothing, hand to dirt, hand to hand, hand to mouth, hand to object,
5 object to mouth, hand to smooth surface (e.g., counter tops, table tops), hand to textured surface
6 (e.g., stuffed animal) (Reed et al., 1999). A total of 30 children were observed in this study.
7 Children were observed in both day care (20 children 3-6 years old) and residential (10 children
8 2-5 years old) settings. Parents and day-care providers were also asked to complete
9 questionnaires describing the behavior of their children. In addition, the study also differentiated
10 between the usage of right and left hands.
11 Over the course of the research, Reed et al. (1999) found that the behavior of children
12 was similar between the day and residential settings except for the contact rate of hand to smooth
13 surfaces. Children in residential settings had higher contact rates with smooth surfaces than
14 children in day care centers. The results of the study are compiled in Table 6-2. The highest
15 contacts were with object (123 contacts/hr), smooth surfaces (84 contacts/hr), and other (83
16 contacts/hr). The two lowest contact rates were the hand-to-mouth (9.5 contacts/hr) and object-
17 to-mouth (16.3 contacts/hr) (Reed et al., 1999). Because the contact rates of hand-to-objects and
18 smooth surfaces are high, these results indicate that the fingers would appear to provide a
19 continual dose per hand-to-mouth contact because of constant touching of potentially
20 contaminated surfaces. Pesticides and other S VOCs are partitioned between the vapor and
21 deposited phases (e.g., on dust or absorbed on a plastic.toy or stuffed animal) such that a child's
22 fingers, especially if wet from mouthing, will continually be acquiring doses of these types of
23 constituents (Gurunathan et al., 1998). Reed et al. (1999) also noted that children acted equally
24 on their environment with both hands with the exception of object-to-mouth'behavior.
25 Therefore, the compiled data are reported as combined right and left hand data. The object-to-
26 mouth behavior showed a strong preference for the right hand over the left hand for nearly all
27 children (Reed et al., 1999). The preference ratio for the right hand over the left hand for this
28 category was 6.8 to 1 (Reed et al., 1999).
29 The advantages of the Reed et al. (1999) study is that it incorporates a wide variety of
30 contacts that small children have, not just the hand-to-mouth or object-to-mouth. This
31 information allows assessors to identify areas or surfaces that may serve as sources for toxic
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1 constituent transfer. This is especially important for exposure to SVOCs such as pesticides (e.g.,
2 chlorpyrifos) that have an affinity for absorption onto dust particles, plastic toys, and into the
3 polyurethane foam (PUF) that is used in many stuffed animals (Gurunathan et al., 1998).
•\
4 Another strength of this study is the agreement it shows with earlier work by Zartarian et al.
5 (1998) for the hand to mouth contacts. Some of the shortcomings are the small sample size of
6 the study and the lack of comment as to the representativeness of the sample population to the
7 U.S. population. Reed et al. (1999) acknowledge the weakness in regard to the sample size and
8 recommend further work with a larger population. The study makes no mention of the
9 representativeness of the sample population or addresses the need for a representative population
10 for any additional study.
11 Zartarian et al. (1997) - Quantified Dermal Activity Data from a Four-Child Pilot Field
12 Study - Zartarian et al. (1997) conducted a pilot study of four children of farm workers to
13 investigate the applicability of using videotaping for gathering information related to children's
14 interaction with their environment. The evaluation of the videotaping included observation of
15 the children's contact frequency and duration with objects in their environment, duration spent in
.16 different locations, activity levels, and frequency distributions (Zartarian et al., 1997). As such,
17 the research was not specifically intended to gather data for non-dietary ingestion; however, the
18 activities used to evaluate the use of videotaping provide data were for dermal and non-dietary
19 exposure.
20 Four Mexican-American farm worker children between the ages of 2.5 and 4.2 years were
21 videotaped for 33 hours using hand-held cameras over the course of a single day in 1993
22 (Zartarian et al., 1997). Two girls and two boys were the subject of the videotaping. The
23 videotaping gathered information on detailed micro-activity patterns of children to be used to
24 evaluate software for videotaped activities and translation training methods (Zartarian et al.,
25 1997). The data were also reported by type of object/surface and by hand (i.e., left or right).
26 Zartarian et al. (1997) present the data for their observations on a per child and per hand
27 basis. The data suggest that the U.S. EPA (1997) estimate of hand to mouth contact of 1.56
28 contacts/hr may significantly underestimate the contacts per hour for young children. None of
29 the children had average contact frequencies for either hand, individually, lower than 3
30 contacts/hr for hand to mouth contact, and Zartarian et al. (1997) estimated the average as 9
rl contacts/hr. As was reported by Reed et al. (1999), the most frequently contacted objects were
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1 toys and hard (i.e., smooth) surfaces (Zartarian et al., 1997). Zartarian et al. (1997) report that
2 the average contact time with objects is only 2 to 3 seconds and that questionnaires and diaries,
3 therefore, would be insufficient in gathering that level of activity, r
4 The Zartarian et al. (1997) study has several weaknesses. The sample population is very
5 small, only four children; however, the work was reported as a pilot study completely
6 acknowledging that further work was necessary. The effort was intended to evaluate the
7 methodology of collecting observations, not the contact data itself. So the data are not presented
8 in a format that can be used to support other research or supply recommended estimates for
9 contact frequency. This study, may not reflect long-term behavior. In addition, the sample
10 population is not representative of the U.S. population in general because the sample population
11 consists of only four Mexican-American farm worker children.
12 Davis (1995), Soil Ingestion in Children with Pica (Final Report), EPA Cooperative
13 Agreement CR 816334-01 - In 1992, the Fred Hutchinson Cancer Research Center under
14 Cooperative Agreement with EPA conducted a study to estimate soil intake rates and collect
15 mouthing behavior data. Originally, the study was designed with two primary purposes: 1) to
16 describe and quantify the distribution of soil ingestion values in a group of children under the age
17 of five who exhibit behaviors that would be likely to result in the ingestion of larger than normal
18 amounts of soil; and 2) to assess and quantify the degree to which soil ingestion varies among
19 children according to season of the year (summer vs. winter). The study was conducted during
20 the first four months of 1992 and included 92 children from the Tri-Cities area in Washington
21 State. These children were volunteers among a group selected through random digit dialing and
22 their ages ranged between 0 and 48 months. The study was conducted during a period of 7 days.
23 Since there was no standard methodology to study mouthing behavior, a pretest and a
24 series of pilot studies were conducted to examine various aspects of the methodology. As a
25 result of the pilot studies, it was determined that although parents could be taught to conduct
26 observations using the instrument, the resulting ranking of children according to degree of
27 mouthing behavior did not correspond very well to the rankings based on observations of the
28 same children by trained staff observers. Therefore, using parents' observations to select a group
29 with high mouthing activity was not deemed appropriate. Funding constraints made it
30 impractical to continue with the original design of screening a large number of children and
31 conducting field work during two different times of the year.
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1 The Davis (1995) research recognizes that mouthing behavior is intermittent. Therefore,
2 a method called "interval method" of observation was used. This method measures both
3 frequency and duration of the behavior. Under this method, children were observed during 15
4 second intervals, during which the mouthing behavior was recorded. Based on the types of
5 behaviors observed in the testing of the instrument, two mouthing behaviors were selected for the
6 full study. These included: 1) tongue contacts object; 2) object in mouth. In addition four other
7 behaviors were included in an attempt to better describe the types of behaviors that would likely
8 result in soil ingestion: 1) hand touches ground; 2) child repulsed by object in mouth - tries to get
9 it out; 3) other person stops child's contact with object; and 4) child out of sight or view. In
10 addition to further characterize potential exposures to soil associated with the three types of
11 mouthing behaviors, six object categories were included to be used along with the three
12 mouthing behaviors. These were: 1) hand, finger, or thumb; 2) other body parts, including toes,
13 feet, arms; 3) natural materials, including dirt, sand, rocks, leaves; 4) toys and other objects,
14 including books, utensils, keys; 5) surfaces, including, window sills, floor, furniture, carpet; and
15 6) food or drink. An additional code was added to indicate whether an object was swallowed by
16 the child. The type of activity the child was engaged in during the observation period was also
17 recorded. In addition to mouthing behavior data, Davis (1995) collected information about how
18 long the child spent indoors and outdoors each day, and the general types of outdoor settings in
19 which the child played.
20 Mouthing behavior data were collected during a 4rday period. Both trained observers and
21 one parent observed the children .to record mouthing behavior data. Trained observers recorded
22 mouthing behavior data for 1 hour during active play time, while the parent recorded mouthing
23 behavior data for the first 15. minutes of that hour.
24 The basic measure of each type of mouthing activity derived from the observation form
25 , was the percent of time spent in that activity. This measure was defined as the percentage of the
26 total number of intervals observed that indicate such an activity took place. If there was no
27 activity in an interval, that interval was excluded. For tabulating the object categories, multiple
28 instances of the same object in a single interval were counted only once in that interval. Multiple
29 instances of different objects in a single interval were counted separately under each object
30 category.
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! Based on the mouthing behavior data collected in this study, EPA calculated that during
2 the period of observation (assumed to be 1 hour) the average mouthing activity was 6.2 minutes
3 and the average tongue activity was 0.70 minutes. It is important to note that this is based on one
4 hour of observation, hi order to estimate the overall mouthing activity in a day, one would have
5 to make some assumptions about the amount of time a child is involved in active play time in a
6 day. These values may also be underestimates because they assume that all the children in the
7 study were observed for one hour on each of the four days. If this were true, each child would
8 have a total of 960 intervals of observations (i.e., 3,600 seconds x intervals/15 seconds x 4 days).
9 The data show that the number of intervals of observation ranged from 80 to 840. It can be
10 concluded that some children were either observed for less than one hour or less than 4 days.
11 In order to compare the values estimated by Groot et al. (1998) whose work also used
12 time as a basis for measuring mouthing activity, it is necessary to multiply the Davis (1995)
13 hourly estimate by an estimate of how long the children are awake during the day. According to
14 Davis (1995) small children are awake approximately 8.9 hours per day for ages 0 to 48 months.
15 Based upon this estimate, the Davis (1995) findings translate into about 55 minutes per day of
16 mouthing activity and 6 minutes per day of tongue activity. The 55 minutes compares favorably
17 to the 37 minutes and 44 minutes estimated by Groot et al. (1998) for 3- to 6-month and 6- to 12-
18 month old children, respectively, but is significantly above the 16.4 minutes and 9.3 minutes
19 estimated for the 12- to 18-month and 18- to 36-month old children, respectively.
20 EPA also analyzed the mouthing behavior data for 86 children (43 males/43 females)
21 from the Davis (1995) study. Six children from the original sample size of 92 were excluded
22 from the analysis because no age information was provided. Total mouthing behavior included
23 both mouth and tongue contacts with hands, other body parts, surfaces, natural objects, and toys.
24 Eating events were excluded from the analysis. Statistical analysis was undertaken to determine
25 if significant differences existed between age and gender. Model results showed that there were
26 no associations between mouthing frequency and gender. However, a clear relationship was
27 observed between mouthing frequency and age. Two distinct groups could be identified:
28 male/female <24 months and male/female > 24 months. Children <24 months exhibited the
29 highest frequency of mouthing behavior with 76 ± 5 contacts/hr (n= 30 subjects; 106
30 observations). On the other hand, children > 24 months exhibited a lower frequency of mouthing
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1 behavior with 38 ± 3 contacts/hr (n= 56 subjects; 192 observations). These results suggest that
2 as children grow older, they are less likely to place objects into their mouths.
3 The Davis (1995) work has both strengths and weaknesses. The strengths of this work
4 are that it incorporates more children (e.g., 92) in the sample population than any of the other
5 literature reviewed. In addition, the research is very detailed in defining the parameters and
6 variables associated with mouthing behavior. The research also gathered information over four
7 days whereas most of the literature involved only one or two days of observation. Although the
8 research included the largest sample population of the reviewed literature, 92 sample points is
9 still a small number considering the wide variability associated with mouthing in children. The
10 random nature in which the population was selected probably provides a representative
11 population of the northwest U.S., but not the national population in general. The interval time of
12 15 seconds would also appear to be small and potentially easily skewed for those children
13 observed less than an hour. In addition, most other studies used observation times of 15 minutes
14 to continuous observation throughout waking hours.
15
6 6.3 RECOMMENDATIONS
17 Due to the paucity of the available research data, it is difficult to recommend with any
18 degree of certainty estimates for non-dietary ingestion. Table 6-3 summarizes the studies on
19 mouthing behavior that were described in this chapter. Table 6-4 summarizes the results of these
20 studies. As mentioned earlier, the studies presented use different units of reporting mouthing
21 behavior. If the assessor is interested in estimating exposures during macroactivities, then the
22 total amount of time engaged in mouthing behavior may be the unit of interest. Groot et al.
23 (1998) is the only study thus far that presents data for infants. These data, as well as the Davis
24 (1995) study, show that mouthing behavior decreases as children age. Data from both Groot et
25 al. (1998) and Davis (1995) for children between 3 to 60 months ranged from 9 min/day to 55
26 min/day with a weighted average of 46 min/day. If the assessor is interested in estimating
27 exposures to various microactivities, then the number of contacts with hands or objects per unit
28 of time may be the unit of interest. Reed et al. (1999) and Zartarian (1997) both studied hand-to-
29 mouth behavior. Although there are uncertainties with the results of these two studies due to
30 sample size, they are fairly consistent in their results. Based on these two studies, a value of 9
contacts/hour seems to be a reasonable estimate of hand-to-mouth behavior. Reed et al. (1999)
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1 also studied object-to-mouth frequency. Based on the Reed et al.- (1999) and the analysis of the
2 Davis (1995) data, total mouthing behavior, including hand-to-mouth as well as objects, ranged
3 from 26 contacts/hour (i.e., 9.5 (hand-to-mouth)+ 16.3 (object-to-mouth)) to 76 contacts/hour
4 with a weighted average of 45 contacts/hour.
5 The frequency of contact of finger-to-mouth (9.5 contacts/hr) greatly exceeds the 1.56
6 contacts/hr for fingers to mouth suggested by the U.S. EPA (1997) in their guidance for
7 calculating exposure to pesticides. The estimate of 9.5 contacts/hr is close to the 9 contacts/hr
8 estimated by Zartarian et al. (1997) for a study conducted using video taping as reported by Reed
9 et al. (1999). The agreement of the two studies suggests that the U.S. EPA (1997) value of 1.56
10 contacts/hr may significantly underestimate the non-dietary exposure route. Table 6-5 presents
11 the confidence ratings for the recommended values.
12
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1 6.4 REFERENCES FOR CHAPTER 6
2
3 Davis (1995). Soil Ingestion in Children with Pica (Final Report), EPA Cooperative Agreement CR 816334-01
4
5 Groot M., Lekkerkerk M., Steenbekkers L. (1998) Mouthing behavior of young children - an
6 observational study. H&C onderzoeksraport 3.
7
8 Gurunathan S., Robson M., Freeman N., Buckley B., Roy A., Meyer R., Bukowski L, and Lioy P. (1998)
9 Accumulation of chloropyrifos on residential surfaces and toys accessible to children. Environ.
10 Health Pers. 106(1 ):9-16.
11
12 Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy, T.R.; Berry, M.R.; Rigas, MX.; Zartarian, V.G.
13 (2000) Children's exposure assessment: A review of factors influencing children's exposure, and the
14 data available to characterize and assess that exposure. Prepared by U.S. Environmental Protection
15 Agency, National Exposure Research Laboratory, RTP, NC.
16
17 Reed K., Jimenez M., Freeman N., and Lioy P. (1999) Quantification of children's hand and mouthing
18 activities through a videotaping methodology. JEAEE. 9:513-520.
19
20 U.S. EPA (1997) Standard operating procedures (SOPs) for residential exposure assessment.
21 Washington, DC: Office of Pesticide Programs.
22
23 U.S. EPA, National Exposure Research Laboratory. (1999) Children's exposure assessment: A review
24 of factors influencing children's exposure, and the data available to characterize and assess that
J5 exposure.
6 '
27 Weaver V., Buckley T., and Groopman J. (1998) Approaches to environmental exposure assessment in
28 children. Environ. Health Pers. 106(3):827-831
29
30 Zartarian V., Ferguson A., and Leckie J. (1997) Quantified dermal activity data from a four-child pilot
31 field study. JEAEE 7(4):543-553.
32
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1 Table 6-1. Extrapolated Total Mouthing Times Minutes per Day (time awake)
2
3
Age (months)
3-
6-
12-
18-
6
12
18
36
No. Children
5
14
12
11
Mean
36.9
44
16.4
9.3
Standard Dev.
19.1
44.7
18.2
9.8
Minimum
14.5
2.4
0
0
Maximum
67
171.5
53.2
30.9
8
9
10 Note: The object most mouthed in all age groups in the fingers except for the 6-12 month group which
11 mostly mouthed on toys.
12
13 Source: Groot et al. (1998)
14
15
16
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1
2
» 3
4
5
6
7
8
9
10
11
12
13
14
15
16
Table
Variable
Clothing
Dirt
Hand
Hand to mouth
Object
Object to mouth
Other
Smooth surface
Textured surface
Source: Reed et al. (1999)
6-2. Frequency of Contact, by Contact Variable Contacts per Hour
Mean
66.6
11.4
21.1
9.5
122.9
16.3
82.9
83.7
22.1
Median
65
0.3
14.2
8.5
118.7
3.6
64.3
80.2
16.3
Minimum
22.8
0
6.3
0.4
56.2
0
. 8.3
13.6
0.2
Maximum
129.2
146.3
116.4
25.7
312
86.2
243.6
190.4
68.7
90th Percentile
103.3
56.4
43.5
20.1
175.8
77.1
199.6
136.9
52.2
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1
2
3
4
Study
Grootetal. 1998
Table 6-3. Summary of Studies on Mouthing Behavior
Population Size Population Studies
42 3-36 months in Netherlands
6
7
8
9
10
Reedetal. 1999
Zartarian 1997
Davis 1995
30
4
92
children from well educated
parents
20 children 3-6 years
10 children 2-5 years
Day care and residential settings
2.5-4.2 years
children of farm workers
10-60 months
Washington State
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1
2
3
4
5
6
7
Table 6-4. Summary of Mouthing Frequency Data
Age (months)
3-6
6-12
12-18
18-36
Mouthing Frequency/Time
1 m in/day
44 min/day
1 6 min/day
9 min/day
Population Size
5
14
12
11
Reference
Grootetal. 1998
10
11
12
13
14
15
16
2-6 years
2.5-4.2 years
10-60
<24
>24
9.5 contacts/hr (hand to mouth) 30
16.3 contacts/hr (object to mouth)
9 contacts/hr
55 min/day
76 ±5 contacts/hr
38 ±3 contacts/hr
92
30
56
Reedetal. 1999
Zartarian 1997
EPA analysis of
Davis 1995
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1
2
3
4 "
5
6
7
8
9
10
11
'12
13
14
15
16
17
18
19
20
21
22
23
Table 6-5. Confidence in Mouthing Behavior Recommendations
Considerations
Study Elements
Peer Review
Accessibility
Reproducibility
Focus on factor of Interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of Approach
Representativeness of the
population
Characterization of variability
Lack of bias in study design
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
Rationale
Three of the studies are from peer review journals, one
from a contractor's report to EPA
Studies in journals have wide circulation.
Contractor's report only available through EPA
Cannot reproduce the data unless raw data are provided.
Studies focused on mouthing behavior as well as other
hand contacts.
Studies were conducted in the U.S.
Analyses were done on primary data. EPA did the
analysis of the raw data from David et al. 1995.
Recent studies were evaluated
Data were collected for a period of several days, not
enough to represent seasonal variations.
Measurements were made by observation methods. Both
surveys and videotaping were used. Videotaping
techniques may be more reliable, but resource intensive.
An effort was made to consider age and gender (in the
Davis study), but sample size was too small.
An effort was made to consider age and gender, data for
infants is fairly limited.
Subjects were selected from volunteers.
Measuring children's behavior is difficult and somewhat
subjective and depends on the experience of the observer.
Four studies were evaluated
There is general agreement among the researchers.
Although there are four studies, they have very small
sample size, variability in the population cannot be
assessed. Variation in behavior due to seasons cartnot be
evaluated. Measuring children's behavior is difficult.
| Rating
Medium
Medium
Medium
High
High
High
High
Medium
Medium
Low
Low
Medium
Medium
Medium
High
Low/Medium
24
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1 7. INHALATION ROUTE
2
3 7.1 INTRODUCTION
4 This chapter presents data and recommendations for inhalation rates that can be used to
5 assess children's exposure to contaminants in air. Children may be more highly exposed to
6 environmental toxicants through inhalation routes than adults. Infants and young children have
7 a higher resting metabolic rate and rate of oxygen consumption per unit body weight than adults
8 because they have a larger cooling surface per unit body weight and because they are growing
9 rapidly. The oxygen consumption of a resting infant aged between one week and one year is 7
10 ml/kg body weight per minute. The rate for an adult under the same conditions is 3-5 ml/kg per
11 minute (WHO 1996). Thus, the volume of air passing through the lungs of a resting infant is
12 twice that of a resting adult under the same conditions and therefore twice as much of any
13 chemical in the atmosphere could reach the lungs of an infant. The recommended inhalation
14 rates for children are summarized in Section 7.3.
15
16 7.2 INHALATION RATE STUDIES
17 Linn et al. (1992) - Documentation of Activity Patterns in "High-Risk" Groups Exposed
18 to Ozone in the Los Angeles Area - Linn et al. (1992) conducted a study that estimated the
19 inhalation rates for "high-risk" subpopulation groups exposed to ozone (O3) in their daily
20 activities in the Los Angeles area. The population surveyed consisted of several panels of both
21 adults and children. The panels consisting of children included: Panel 2: 17 healthy elementary
22 school students (5 males, 12 females, ages 10-12 years); Panel 5:19 healthy high school students
23 (7 males, 12 females, ages 13-17 years); Panel 6: 13 young asthmatics (7 males, 6 females, ages
24 11-16 years).
25 Initially, a calibration test was conducted, followed by a training session. Finally, a field
26 study was conducted which involved subjects' collecting their own heart rate and diary data.
27 During the calibration tests, ventilation rate (VR), breathing rate, and heart rate (HR) were
28 measured simultaneously at each exercise level. From the calibration data an equation was
29 developed using linear regression analysis to predict VR from measured HR (Linn et al., 1992).
£p 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
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1 activity/location, and time spent at each activity/location. Healthy subjects recorded their HR
2 once every 60 seconds, Asthmatic subjects recorded their diary information once every hour
3 using a Mean Watch. Subjective breathing rates were defined as slow (walking at their normal
4 pace); medium (faster than normal walking); and fast (running or similarly strenuous exercise).
5 Table 7-1 presents the calibration and field protocols for self-monitoring of activities for each
6 subject panel.
7 Table 7-2 presents the mean VR, the 99th percentile VR, and the mean VR at each
8 subjective activity level (slow, medium, fast). The mean VR and 99th percentile VR were
9 derived from all HR recordings (that appeared to be valid) without considering the diary data.
10 Each of the three activity levels was determined from both the concurrent diary data and HR
11 recordings by direct calculation or regression (Linn et al., 1992). Linn et al. (1992) reported that
12 the diary data showed that most individuals spent most of their time (in a typical day) indoors at
13 slow activity level. During slow activity, asthmatic subjects had higher VRs than healthy
14 subjects, (Table 7-2). Also, Linn et al. (1992) reported that in every panel, the predicted VR
15 correlated significantly with the subjective estimates of activity levels.
16 A limitation of this study is that calibration data may overestimate the predictive power of
17 HR during actual field monitoring. The wide variety of exercises in everyday activities may
18 result in greater variation of the VR-HR relationship than calibrated. Another limitation of this
19 study is the small sample size of each subpopulation surveyed. An advantage of this study is that
20 diary data can provide rough estimates of ventilation patterns which are useful in exposure
21 assessments. Another advantage is that inhalation rates were presented for both healthy and
22 asthmatic children.
23 Spier et al. (1992) - Activity Patterns in Elementary and High School Students Exposed
24 To Oxidant Pollution - Spier et al. (1992) investigated activity patterns of 17 elementary school
25 students (10-12 years old) and 19 high school students (13-17 years old) in suburban Los Angeles
26 from late September to October (oxidant pollution season). Calibration tests were conducted in
27 supervised outdoor exercise sessions. The exercise sessions consisted of 5 minutes for each: rest,
28 slow walking, jogging, and fast walking. HR and VR were measured during the last 2 minutes of
29 each exercise. Individual VR and HR relationships for each individual were determined by
30 fitting a regression line to HR values and log VR values. Each subject recorded their daily
31 activities, change in location, and breathing rates in diaries for 3 consecutive days. Self-
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I estimated breathing rates were recorded as slow (slow walking), medium (walking faster than
2 normal), and fast (running). HR was recorded during the 3 days once per minute by wearing a
3 Heart Watch. VR values for each self-estimated breathing rate and activity type were estimated
4 from the HR recordings by employing the VR and HR equation obtained from the calibration
5 tests.
6 The data presented in Table 7-3 represent HR distribution patterns and corresponding
7 predicted VR for each age group during hours spent awake. At the same self-reported activity
8 levels for both age groups, inhalation rates were higher for outdoor activities than for indoor
9 activities. The total hours spent indoors by high school students (21.2 hours) were higher than
10 for elementary school students (19.6 hours). The converse was true for outdoor activities;
11 2.7 hours for high school students, and 4.4 hours for elementary school students (Table 7-4).
12 Based on the data presented in Tables 7-3 and 7-4, the average activity-specific inhalation rates
13 for elementary (10-12 years) and high school (13-17 years) students were calculated in Table 7-5.
14 For elementary school students, the average daily inhalation rates (based on indoor and outdoor
15 locations) are 15.8 mVday for light activities, 4.62 m3/day for moderate activities, and
16 0.98 mVday for heavy activities. For high school students the daily inhalation rates for light,
17 moderate, and heavy activities are estimated to be 16.4 m3/day, 3.1 m3/day, and 0.54 m3/day,
18 respectively (Table 7-5).
19 A limitation of this study is the small sample size. The results may not be representative
20 of all children in these age groups. Another limitation is that the accuracy of the self-estimated
21 breathing rates reported by younger age groups is .uncertain. This may affect the validity, of the
22 data set generated. An advantage of this study is that inhalation rates were determined for
23 children and adolescents. These data are useful in estimating exposure for the younger
24 population.
25 Adams (1993) • Measurement of Breathing Rate and Volume in Routinely Performed
26 Daily Activities - Adams (1993) conducted research to accomplish two main objectives:
27 (1) identification of mean and ranges of inhalation rates for various age/gender cohorts and
28 specific activities; and (2) derivation of simple linear and multiple regression equations used to
29 predict inhalation rates through other measured variables: breathing frequency (fB) and oxygen
30 consumption (V02). A total of 160 subjects participated in the primary study. For children, there
Fl were two age dependent groups: (1) children 6 to 12.9 years old, (2) adolescents between 13 and
June 2000 7-3 DRAFT-DO NOT QUOTE OR CITE
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1 18.9 years old, (Adams, 1993). An additional 40 children from 6 to 12 years old and 12 young
2 children from 3 to 5 years old were identified as subjects for pilot testing purposes (Adams,
3 1993).
4 Resting protocols conducted in the laboratory for all age groups consisted of three phases
5 (25 minutes each) of lying, sitting, and standing. They were categorized as resting and sedentary
6 activities. Two active protocols, moderate (walking) and heavy (jogging/ running) phases, were
7 performed on a treadmill over a progressive continuum of intensities made up of 6 minute
8 intervals, at 3 speeds, ranging from slow to moderately fast. All protocols involved measuring
9 VR, HR, fB (breathing frequency), and V0, (oxygen consumption). Measurements were taken in
10 the last 5 minutes of each phase of the resting protocol, and the last 3 minutes of the 6 minute
11 intervals at each speed designated in the active protocols.
12 In the field, all children completed spontaneous play protocols, while the older adolescent
13 population (16-18 years) completed car driving and riding, car maintenance (males), and
14 housework (females) protocols.
15 During all activities in either the laboratory or field protocols, IR for the children's group
16 revealed no significant gender differences. Therefore, IR data presented in Appendix
17 Tables 7A-1 and 7A-2 were categorized as young children, chiidren (no gender) by activity levels
18 (resting, sedentary, light, moderate, and heavy). These categorized data from the Appendix
19 tables are summarized as IR in mVhr in Tables 7-6 and 7-7. The laboratory protocols are shown
20 in Table 7-6. Table 7-7 presents the mean inhalation rates by group and activity levels (light,
21 sedentary, and moderate) in field protocols. Accurate predictions of IR across all population
22 groups and activity types were obtained by including body surface area (BSA), HR, and fB in
23 multiple regression analysis (Adams, 1993). Adams (1993) calculated BSA from measured
24 height and weight using the equation:
25
BSA = Height^0"425) x Weight^0'425) x 71.84 (7*1)
26
27
28 A limitation associated with this study is that the population does not represent the
29 general U.S. population. Also, the classification of activity types (i.e., laboratory and field
June 2000 7-4 DRAFT-DO NOT QUOTE OR CITE
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1 protocols) into activity levels may bias the inhalation rates obtained for various age/gender
2 cohorts. The estimated rates were based on short-term data and may not reflect long-term
3 patterns.
4 Layton (1993) - Metabolically Consistent Breathing Rates for Use in Dose Assessments -
5 Layton (1993) presented a new method for estimating metabolically consistent inhalation rates
6 for use in quantitative dose assessments of airborne radionuclides. Generally, the approach for
7 estimating the breathing rate for a specified time frame was to calculate a time-weighted-average
8 of ventilation rates associated with physical activities of varying durations (Layton, 1993).
9 However, in this study, breathing rates were calculated based on oxygen consumption associated
10 . with energy expenditures for short (hours) and long (weeks and months) periods of time, using
11 the following general equation to calculate energy-dependent inhalation rates:
12
13 VE = E x H x VQ (7-2)
14 where:
15 VE = ventilation rate (L/min or mVhr);
E = energy expenditure rate; [kilojoules/minute (KJ/min) or
17 megajoules/hour (MJ/hr)];
18 H = volume of oxygen [at standard temperature and pressure, dry air
19 (STPD) consumed in the production of 1 kilojoule (KJ) of energy
20 expended (L/KJ or m3/MJ)]; and
21 VQ = ventilatory equivalent (ratio of minute volume (L/min) to oxygen
22 uptake (L/min)) unitless.
23
24 Three alternative approaches were used to estimate daily chronic (long term) inhalation
25 rates for different age/gender cohorts of the U.S. population using this methodology.
26
27 , First Approach
28 Inhalation rates were estimated by multiplying average daily food energy intakes for
29 different age/gender cohorts, volume of oxygen (H), and ventilatory equivalent (VQ), as shown
in the equation above. The average food energy intake data (Table 7-8) are based on
June 2000 7-5 DRAFT-DO NOT QUOTE OR CITE
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1 approximately 30,000 individuals and were obtained from the USDA 1977-78 Nationwide Food
2 Consumption Survey (USDA-NFCS). The food energy intakes were adjusted upwards by a
3 constant factor of 1.2 for all individuals 9 years and older (Layton, 1993). This factor
4 compensated for a consistent bias in USDA-NFCS attributed to under reporting of the foods
5 consumed or the methods used to ascertain dietary intakes. Layton (1993) used a weighted
6 average oxygen uptake of 0.05 L O2/KJ which was determined from data reported in the 1977-78
7 USDA-NFCS and the second National Health and Nutrition Examination Survey (NHANES II).
8 The survey sample for NHANES II was approximately 20,000 participants. The ventilatory
9 equivalent (VQ) of 27 used was calculated as the geometric mean of VQ data that were obtained
10 from several studies by Layton (1993).
11 The inhalation rate estimation techniques are shown in footnote (a) of Table 7-9.
12 Table 7-9 presents the daily inhalation rate for each age/gender cohort. The highest daily
13 inhalation rates were reported for children between the ages of 6-8 years (10 mVday), for males
14 between 15-18 years (17 nrVday), and females between 9-11 years (13 nrVday). Inhalation rates
15 were also calculated for active and inactive periods for the various age/gender cohorts.
16 The inhalation rate for inactive periods was estimated by multiplying the basai metabolic
17 rate (BMR) times the oxygen uptake (H) times the VQ. BMR was defined as "the minimum
18 amount of energy required to support basic cellular respiration while at rest and not actively
19 digesting food" (Layton, 1993). The inhalation rate for active periods was calculated by
20 multiplying the inactive inhalation rate by the ratio of the rate of energy expenditure during
21 active hours to the estimated BMR. This ratio is .presented as F in Table 7-9. These data for
22 active and inactive inhalation rates are also presented in Table 7-9. For children, inactive and
23 active inhalation rates ranged between 2.35 and 5.95 nrVday and 6.35 to 13.09 nrYday,
24 respectively.
25 Second Approach
26 Inhalation rates were calculated by multiplying the BMR of the population cohorts times
27 A (ratio of total daily energy expenditure to daily BMR) times H times VQ. The BMR data
28 obtained from the literature were statistically analyzed and regression equations were developed
29 to predict BMR from body weights of various age/gender cohorts (Layton, 1993). The statistical
30 data used to develop the regression equations are presented in Appendix Table 7A-3. The data
31 obtained from the second approach are presented in Table 7-10. Inhalation rates for children
June 2000 .7-6 DRAFT-DO MOT QUOTE OR CITE
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(6 months - 10 years) ranged from 7.3-9.3 m3/day for male and 5.6 to 8.6 mVday for female
children, and for older children (10-18 years), inhalation rates were 15 mVday for males and 12
3 m3/day for females. These rates are similar to the daily inhalation rates obtained using the first
4 approach. Also, the inactive inhalation rates obtained from the first approach are lower than the
5 inhalation rates obtained using the second approach. This may be attributed to the BMR
6 multiplier employed in the equation of the second approach to calculate inhalation rates.
7 Inhalation rates were also obtained for short-term exposures for various age/gender
8 cohorts and five energy-expenditure categories (rest, sedentary, light, moderate, and heavy).
9 BMRs were multiplied by the product of MET, H, and VQ. The data obtained for short term
10 exposures are presented in Table 7-11.
11 The major strengths of the Layton (1993) study are that it obtains similar results using
12 three different approaches to estimate inhalation rates in different age groups and that the
13 populations are large, consisting of men, women, and children. Explanations for differences in
14 results due to metabolic measurements, reported diet, or activity patterns are supported by
15 observations reported by other investigators in other studies. Major limitations of this study are
that activity pattern levels estimated in this study are somewhat subjective, the explanation that
17 activity pattern differences is responsible for the lower level obtained with the metabolic
18 approach (25 percent) compared to the activity pattern approach is not well supported by the
19 data, and different populations were used in each approach which may introduce error.
20
21 7.3 RECOMMENDATIONS
22 The recommended inhalation rates for children are based on the studies described in this
23 chapter. Different survey designs and populations were utilized in the studies described in this
24 Chapter. Excluding the study by Layton (1993), the population surveyed in all of the studies
25 described in this report were limited to the Los Angeles area. This regional population may not
26 represent the general U.S. population and may result in biases. However, based on other aspects
27 of the study design, these studies were selected as the basis for recommended inhalation rates.
28 The selection of inhalation rates to be used for exposure assessments depends on the age
29 of the exposed population and the specific activity levels of this population during various
30 exposure scenarios. The confidence ratings and recommended inhalation rates are presented in
Tables 7-12 and 7-13, respectively. Based on the study results from Layton (1993), the
June 2000 7-7 DRAFT-DO NOT QUOTE OR CITE
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1 recommended daily inhalation rate for infants (children less than 1 yr), during long-term dose
2 assessments is 4.5 nrVday. For children 1-2 years old, 3-5 years old, and 6-8 years old, the
3 recommended daily inhalation rates are 6.8 mVday, 8.3 mVday, and 10 m3/day, respectively.
4 Recommended values for children aged 9-11 years are 14 m3/day for males and 13 mVday for
5 females. For children aged 12-14 years and 15-18 years, the recommended values are shown in
6 Table 7-13.
7 Recommended short-term inhalation rates for children aged 18 years and under are also
8 summarized in Table 7-13. The short-term inhalation rates were calculated by averaging the
9 inhalation rates for each activity level from the various key studies (Table 7-14). The
10 recommended average hourly inhalation rates are as follows: 0.3 mVhr during rest; 0.4 m3/Tir for
11 sedentary activities; 1.0 mVhr for light activities; 1.2 nrYhr for moderate activities: and 1.9 m3/hr
12 for heavy activities. The recommended short-term exposure data also include infants (less than
13 lyr). . . .
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1 7.4 REFERENCES FOR CHAPTER 7
2
"3 Adams, W.C. (1993) Measurement of breathing rate and volume in routinely performed daily activities, Final
4 Report. California Air Resources Board (CARB) Contract No. A033-205. June 1993. 185 pgs.
6 Basiotis, P.P.; Thomas, R.G.; Kelsay, J.L.; Mertz, W. (1989) Sources of variation in energy intake by men and
7 women as determined from one years daily dietary records. Am. J. Ciin. Nutr. 50:448-453.
8
9 Layton, D.W. (1993) Metabolically consistent breathing rates for use in dose assessments. Health Physics 64( 1 ):23-
10 36.
11
12 Linn, W.S.; Shamoo. D.A.; Hackney, J.D. (1992) Documentation of activity patterns in "high-risk" groups exposed
13 to ozone in the Los Angeles area. In: Proceedings of the Second EPA/A WM A Conference on
14 Tropospheric Ozone, Atlanta, Nov. 1991. pp. 701 -712. Air and Waste Management Assoc., Pittsburgh,
15 PA.
16
17 Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson; T.R.; Linn, W.S.; Hackney, J.D. (1992) Activity patterns in
18 elementary and high school students exposed to oxidant pollution. J. Exp. Anal. Environ Epid 2(3):2?7-
19 293.
20
21 WHO (1986) Principles for evaluating health risks from chemicals during infancy and early chiIdhood: the need for
22 a special approach. Environmental Health Criteria 59. World Health Organization, International
23 Programme on Chemical Safetv.
24
25
26
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1
2
3
5
6
7
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
Table 7-1. Calibration And Field Protocols For Self-monitoring of Activities
Grouped by Subject Panels
Panel
Calibration Protocol
Field Protocol
Panel 2 - Healthy Elementary
School Students - 5 male,
12 female, age 10-12
Panel 3 - Healthy High School
Students - 7 male, 12 female,
age 13-17
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
Panel 6 - Young Asthmatics - 7 Laboratory exercise tests on
male, 6 female, age i 1-16 bicycles and treadmills
Saturday, Sunday and Monday (school
day) in early autumn; HR recordings
and activity diary during waking hours
and during sleep.
Same as Panel 2, however, no HR
recordings during sleep for most
subjects.
Similar to Panel 4, summer monitoring
for 2 successive weeks, including 2
controlled exposure studies with few
or no observable respiratory effects.
Source: Linn etal., 1992
Table 7-2. Subject Panel Inhalation Rates by Mean VR, Upper
Percentiles, And Self-estimated Breathing Rates
Inhalation Rates (mVhr)
N' Mean VR
(mVhr)
Panel
Healthv
2 - Elementary School Students 1 7 0.90
3 - High School Students 19 0.84
Asthmatics
6 - Elementary and. High School 13 1.20
Students
99th Mean VR at Activity Levels
Percentile VR (m3/hr)b
Slow
1.98 0.84
2.22 0.78
2.40 120
Medium Fast
0.96 1.14
1.14 1.62
1.20 1.50
'Number of individuals in each survey panel.
bSome 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).
Source: Linn et al. (1992).
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1
1
F3
4
5
6
7
8
9
10
11
12
J3
|4
15
16
17
18
19
20
21
22 .
23
24
25
26
27
28
29
30
31
32
33
34
Table 7-3. Distribution of Predicted Intake Rates by Location
For Elementary And
And Activity Levels
High School Students
Inhalation Rates (m3/hr)
Percentile Rankings*
Age (yrs)
10-12
13-17
Student
Elc
(n"=l7)
HSC
(n<=19)
"Recorded time averaged
over 72-hr.
periods.
Location
Indoors
Outdoors
Indoors
Outdoors
Activity %
Level
slow
medium
fast
slow
medium
fast
slow
medium
fast
slow
medium
fast
Recorded
Time"
49.6
23.6
2.4
8.9
11.2
4.3
70.7 .
10.9
i.4
8.2
7.4
1.4
about 23 hr per elementary school student
bGeometric means closely approximated 50th percentiles; geometric
1.5-1.8
Mean ± SD
0.84 ±
0.96 ±
1.02±
0.96 ±
1.08±
l.I4±
0.78 ±
0.96 ±
1.26±
0.96 ±
1.26±
1.44±
0.36
0.42
0.60
0.54
0.48
0.60
0.36
0.42
0.66
0.48
0.78
1.08
and 33 hr. per
l"
0.18
0.24
0.24
0.36
0.24
0.48
0.30
0.42
0.54
0.42
0.48
0.48
high school
50'"
0.78
0.84
0.84
0.78
0.96
0.96
0.72
0.84
1.08
0.90
1.08
1.02
99.9th
2.34
2.58
3.42
4.32
3.36
3.60
3.24
4.02
6.84C
528
5.70
5.94
student. •
standard deviations were 1 .2- 1 .3
for HR,
for VR.
SEL = elementary school
student; HS =
high school student.
*N = number of students that participated in survey.
'Highest
Source:
single value.
Spier etal( 1992).
Table
7-4. Average
Hours Spent Per Day in a Given Location
and Activity
Level For Elementary (EL) and High School (HS) Students
Student
Activity Level
(EL'.n'-l?;
N<=19)
EL
EL
HS
HS
"Elementary
HS",
school (EL)
Total
Time Spent
(hrs/day)
Location
Indoor
Outdoor
Indoor
Outdoor
Slow
16.3
2.2
19.5
1.2
Medium
2.9
1.7
1.5
1.3
. Fast
0.4
0.5
0.2
0.2
19.6
4.4
21.2
2.7
students were between 10-12 years old.
bHigh school (HS) students were between 13-17 years old.
TV! corresponds to number of school students.
Source: Spier et al. (1992).
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1
2
3
4
5
6
7
8
9
10
11
12
13
Table 7-5. Distribution Patterns of Daily Inhalation
Rates For Elementary (EL) And High School (HS)
Students Grouped by Activity Level
Percentile Rankings
Students
EL
(n<=17)
EL
HS
(n=19)
HS
Age Mean IRb
(yrs) Location Activity type1 (nvVday) 1st
10-12 Indoor Light 13.7 2.93
Moderate 2.8 .0.70
Heavy 0.4 0.096
Outdoor Light 2.1 0.79
Moderate 1.84 0.41
Heavy 0.57 0-24
13-17 Indoor Light 15.2 5.85
Moderate 1.4 0.63
Heavy 0.25 0.11
Outdoor Light 1.15 0.50
Moderate 1.64 0.62
Heavy 0.29 0.096
50th
12.71
2.44
0.34
1.72
1.63
0.48
14.04
1.26
0.22
1.08
1.40
0.20
99.9th
38.14
7.48
1.37
9.50
5.71
1.80
63.18
6.03
1.37
6.34
7.41
1.19
14
15
16
17
18
19
20
21
22
*For this report, activity type presented in Table 7-2 was redefined as light activity for slow, moderate activity
for medium, and heavy activity for fast.
"Daily inhalation rate was calculated by multiplying the hours spent at each activity level (Table 7-4) by the
corresponding inhalation rate (Table 7-3).
'Number of elementary (EL) and high school students (HS).
Source: Adapted from Spier et al. (1992) (Generated using data from Tables 7-3 and 7-4).
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Table 7-6. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity Levels
For Laboratory Protocols
4
5
6
Age Group
Young Chiidrenf
Children11
Resting3
0.37
0.45
Sedentary13
0.40
0.47
Light*
0.65
0.95
Moderated
DNP§
1.74
Heavy*
DNP
2.23
7 'Resting defined as lying (see Appendix Table 7A-1 for original data).
8 bSedentary defined as sitting and standing (see Appendix Table 7A-1 for original data).
9 'Light defined as walking at speed level 1.5 - 3.0 mph (see Appendix Table 7A-1 for original data).
10 ''Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Appendix Table 7A-1
11 for original data).
12 'Heavy defined as fast running (4.5 - 6.0 mph) (see Appendix Table 7A-1 for original data).
13 'Young children (both genders) 3 - 5.9 yrs old.
14 SDNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. All young
15 children did not run.
16 kChildren (both genders) 6 - 12.9 yrs old.
17
18 Source: Adapted from Adams (1993).
19
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1
2
3
Table 7-7. Summary of Average Inhalation Rates (MVhr) by
Age Group And Activity Levels in Field Protocols
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Age Group
Young Children
Children1"
Light3
DNPe
DNP
Sedentary1"
DNP
DNP
Moderate0
0.68
1.07
"Light activity was defined as car maintenance (males), housework (females), and yard work (females) (see
Appendix Table 7A-2 for original data).
"Sedentary activity was defined as car driving and riding (both genders) (see Appendix Table 7A-2 for original
data).
'Moderate activity was defined as mowing (males); wood working (males); yard work (males); and play
(children) (see Appendix Table 7A-2 for original data).
dYoung children (both genders) = 3 - 5.9 yrs old.
'DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons.
Children (both genders) = 6 -12.9 yrs old.
Source: Adams (1993).
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1
>
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
J9
Table 7-8.
Cohort/Age
(years)
Children
Under 1
1 to 2
3 to 5
6 to 8
Males
9 to 11
12 to 14
15 to 18
Females
9 to 11
12 to 14
15 to 18
Comparisons of Estimated Basal Metabolic Rates (BMR) With Average Food-energy Intakes For
Individuals Sampled in The 1977-78 NFCS
Body Weight
kg
7.6
13
18
26
36
50
66
36
49
56
"O "Calculated from the appropriate
21
22
23
24
25
26
27
28
MJ d"lb
1.74
3.08
3.69
4.41
5.42
6.45
7.64
4.91
5.64
6.03
BMRa
kcal d'lc
416
734
881
1053
1293
1540
1823
1173
1347
1440
Energy Intake (EFD)
MJd*1
3.32
5.07
6.14
7.43
8.55
9.54
10.8
7.75
7.72
7.32
age and gender-based BMR equations given
kcal d'1
793
1209
1466
1774
2040
2276
2568
1849
1842
1748
in Appendix Table
Ratio
EFD/BMR
1.90
1.65
1.66
1.68
1.58
1.48
1.41
1.58
1.37
1.21
7A-3.
bMJ d'1 - mega joules/day
ekcal d'1 - kilo
calories/day
Source: Layton(1993).
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f
2
3
4
5
6
7
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
Table 7-9. Daily Inhalation Rates Calculated From
Food-energy Intakes
MET" Value
Cohort/Age
(years)
Children
<\
1 -2
3-5
6-8
Males
9-11
12- 14
15-18
Females
9-11
12-14
15-18
Ld
1
2
3
3
3
3
4
3
3
4
Daily Inhalation Rate3
(mVday)
4.5
6.8
8.3
10
14
15
17
13
12
12
(h)Sieep
(h)
11
11
10
10
9
9
8
9
9
8
Ae
1.9
1.6
1.7
1.7
1.9
1.8
1.7
1.9
1.6
1.5
Ff
2.7
2.2
2.2
2.2
2.5
2.2
2.1
2.5
2.0
1.7
Inhalation Rates
Inactive0
(mVday)
2.35
4.16
4.98
5.95
7.32
8.71
10.31
6.63
7.61
8.14
Active0
(mVday)
6.35
9.15
10.96
13.09
18.3
19.16
21.65
16.58
15.20
13.84
'Daily inhalation rate was calculated by multiplying the EFD values (see Table 7-10) by H x VQ x
(m3 1,000 L'1) for subjects under 9 years of age and by 1.2 x H x VQ x (m3 1,000 L'1) (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 LO,/KJ or 0.21 LO,/Kca!
VQ = Ventilation equivalent = 27 = geometric mean of VQs (unitiess)
bMET = Metabolic equivalent
'Inhalation rate for inactive periods was calculated as BMR x H x VQ x (d 1,440 min'1) and for active periods by
multiplying inactive inhalation rate by F (See footnote f); BMR values are from Table 7-10.
Where:
BMR = Basal metabolic rate (MJ/day) or (kg/hr)
dL is the number of years for each age cohort.
eFor individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitiess)
(Table 7-10) by the factor 1.2 (see text for explanation).
fF = (24A - S)/(24 - S) (unitiess), ratio of the rate of energy expenditure during active hours to the estimated
BMR (unitiess)
Where:
S = Number of hours spent sleeping each day (hrs)
Source: Layton (1993).
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Table 7-10. Daily Inhalation Rates Obtained From The Ratios
Of Total Energy Expenditure to Basal Metabolic Rate (BMR)
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Gender/Age
(yrs)
Male
0.5 - <3
3-<10
10-<18
Female
0.5 - <3
3-
-------
1
3
4
7
8
9
.10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Table 7-11. Inhalation Rates For Short-term Exposures
Rest
Activity Type
Sedentary Liaht Moderate
Heavy
MET (BMR Multiplier)
Gender/Age
(vrs)
Male
0.5 - <3
3-<10
10-<18
Female
0.5 - <3
3-<10
in-7n
1
1.2
2C
4d
10e
Inhalation Rate (m3/hr)f-s
0.19
0.24
0.38
0.14
0.23
n T?
0.23
0.29
0.45
0.17
0.27
n iX
0.38
0.49
0.78
0.29
0.45
Dfifi
0.78
0.96
1.50
0.60
0.90
1 ?fi
1.92
2.40
3.78
1.44
2.28
1 18
'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 (Appendix Table 7A-3).
cRange of 1.5-2.5.
"Range of 3-5.
'Range of >5 - 20.
the inhalation rate was calculated by multiplying BMR (MJ/day) x H (0:05 L/KJ) x MET x VQ (27) x
(d/l,440min)
Kfriginal data were presented in L/min. Conversion to mVhr was obtained as follows:
Source: Layton(1993).
60 min
hr
1000L rain
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_
1
•2
3
4
5
6
7
8
9
10
11
12
13
14
^5
^F
17
18
19
20
21
22
23
24
25
26
27
Table 7- 12.
Considerations
Study Elements
• Peer Review
• Accessibility
• Reproducibiiity
• Focus on factor of interest
• Data pertinent to U.S.
• Primary data
• Currency
* Adequacy of data collection
period
• Validity of approach
• Representativeness of the
population
• Characterization of variability
• Lack of bias in study design
• Measurement error
Other Elements
• Number of studies
« Agreement between researchers
Overall Rating
June 2000
Confidence in Inhalation Rate Recommendations
Rationale
Studies are from peer reviewed journal articles and an
EPA peer reviewed report.
Studies in journals have wide circulation.
EPA reports are available from the National Technical
•Information Service.
Information on questionnaires and interviews were not
provided.
Studies focused on ventilation rates and factors
influencing them.
Studies conducted in the U.S.
Both data collection and re-analysis of existing data
occurred.
Recent studies were evaluated.
Effort was made to collect data overtime.
Measurements were made by indirect methods.
An effort has been made to consider age and gender, but
not systematically. Sample size was too small.
An effort has been made to address age and gender, but
not systematically.
Subjects were selected randomly from volunteers and
measured in the same way.
Measurement error is well documented by statistics, but
procedures measure factor indirectly.
Five key studies and six relevant studies were evaluated.
There is general agreement among researchers using
different experimental methods.
Several studies exist that attempt to estimate inhalation
rates according to age, gender and activity.
Rating
High
High
Medium
High
High
Medium
High
High
Medium
Medium
High
High
Medium
High
Medium
7-19 DRAFT-DO NOT QUOTE OR CITE
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1
2
Table 7-13. Summary of Recommended Values For inhalation
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Population
Mean Upper Percentile
Long-term Exposures
Infants
<1 year
Children
1-2 years
3-5 years
6-8 years
9-1 1 years
males
females
1 2- 14 years
maies
females
15-18 years
males
females
4.5 mVday —
6.8 mVday —
8.3 mVday
1 0 mVday
14 mVday —
13m3/day
15 mVday
12m3/day
I7m3/day . —
12m3/day —
Short-term Exposures
Children (18 years and under)
Rest
Sedentary Activities
Light Activities
Moderate Activities
Heavy Activities
0.3 mVhr —
0.4 nrVhr —
l.OmVhr —
1.2 mVhr
1.9mVhr —
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1
»2
3
4
5
6
7
8
9
10
11
12
13
14
15
Table 7-14. Summary of Children's Inhalation Rates
For Short-Term Exposure Studies
Arithmetic Mean (nrVhr)
Activity Level
Rest Sedentary Light
Moderate
High
Reference
0.4
0.2
0.4
0.3
0.8
0.5
1.8
0.8
0.9
1.0
2.0
1.0
Adams, 1993 (Lab protocols)
— Adams, 1993 {Field protocols)
2.5 Layton, 1993 (Short-term data)
2.2 Spier et al, 1992 (10-12 yrs)
Jl LinnetaL, 1992 (10-12 yrs)
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I APPENDIX 7A
2
3
4 VENTILATION DATA
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I
2
4
5
6
9
10
11
12
3
'14
15
TABLE 7A-1. Mean Minute Ventilation (Ve, L/min) by Group
And Activity for Laboratory Protocols
Activity
Lying
Sitting
Standing
Walking
Running
1 .5 mph
1.875mph
2.0 mph
2.25 mph
2.5 mph
3.0 mph
3.3 mph
4.0 mph
3.5 mph
4.0 mph
4.5 mph
5.0 mph
6.0 mph
Young Children3
6.19
6.48
6.76
10.25
10.53
DNP
11.68
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
Children
7.51
7.28
8.49
DNP
DNP
14.13
DNP
15.58
17.79
DNP
DNP
26.77
31.35
37.22
DNP
DNP
'Young Chiidren, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females,
adolescent, young to middle-aged, and older adult females; Adult Mates, adolescent, young to middle-aged,
and older adult males; DNP, group did not perform this protocol or N was too smali for appropriate mean
comparisons
Source: Adams (1993).
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1
2
3
4
5
6
7
8
9
10
II
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
TABLE 7A-2. Mean Minute Ventilation (Ve, L/min) by Group
^___ and Activity for Field Protocols
Activity
Young Children3
Children
Play
Car Driving
Car Riding
Yardwork
Housework
Car Maintenance
Mowing
Woodworking
11.31
DNP
DNP
DNP
DNP
DNP
DNP
DNP
17.89
DNP
DNP
DNP
DNP
DNP
DNP
DNP
'Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females,
adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged,
and older adult males; DNP, group did not perform this protocol orN was too small for appropriate mean
comparisons;
Source: Adams (J 993).
TABLE 7A-3. Statistics of the Age/gender Cohorts Used
To Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR)
Gender/Age
(y)
Males
Under 3
3 to < 10
10 to < 18
Females
Under 3
3 to < 10
10 to < 18
BMR
MJd"1
1.51
4.14
5.86
L54
3.85
5.04
±SD
0.918
0.498
1.171
0.915
0.493
0.780
cva
0.61
0.12
0.20
0.59
0.13
0.15
Body
Weight
(kg)
6.6
21 -
42
6.9
21
38
Nb
162
338
734
137
413
575
BMR Equation0
0.249 bw- 0.1 27
0.095bw-f-2.110
0.074 bw + 2.754
0.244 bw- O.I 30
0.085 bw -r 2.033
0.056 bw + 2.898
rd
.0.95
0.83
0.93
0.96
0.81
0.8
'Coefficient of variation (SD/mean)
bN = number of subjects
cBody weight (bw) in kg
^coefficient of correlation
Source: Layton (1993).
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1 8. DERMAL ROUTE
2
3 8.1 INTRODUCTION
4 Children may be more highly exposed to environmental toxicants through dermal routes
5 than adults. For instance, children often play and crawl on contaminated surfaces and are more
6 likely to wear less clothing than adults. These factors result in higher dermal contact with
7 contaminated media. In addition, children have a higher surface area relative to body weight. In
8 fact, the surface-area-to-body weight ratio for newborn infants is more then two times greater
9 then that for adults (Cohen-Hubal et al., 1999).
10 Dermai exposure can occur during a variety of activities in different environmental media
11 and microenvironments (U.S. EPA, 1992a; 1992b). These include:
12 • Water (e.g., bathing, washing, swimming);
13 * Soil (e.g., outdoor recreation, gardening, construction);
14 • Sediment (e.g., wading, fishing);
15 • Liquids (e.g., use of commercial products);
• Vapors/fumes (e.g., use of commercial products); and
17 • Indoors (e.g., carpets, floors, countertops).
18
19 The major factors that must be considered when estimating dermal exposure are: the
20 chemical concentration in contact with the skin, the extent of skin surface area exposed, the
21 duration of exposure, the absorption of the chemical through the skin, the internal dose, and the
22 amount of chemical that can be delivered to a target organ (i.e., biologically effective dose) (see
23 • Figure 8-1). A detailed discussion of these factors can be found in Guidelines for Exposure
24 Assessment (U.S. EPA, 1992a). This chapter focuses on measurements of body surface areas
25 and dermal adherence of soil to the skin. Dermal Exposure Assessment: Principles and
26 Applications (U.S. EPA, 1992b), provides detailed information concerning dermal exposure
27 assessment using a stepwise guide in the exposure assessment process.
28
29
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Exposure
Chemical
Potential
Dose
Applied
Dose
Biologically
Effective
Dose
Internal
Dose
Metabolism
Effect
Skin
Uptake
Figure 8-1. Schematic of Dose and Exposure: Dermal Rome.
Source: U.S. Environmental Protection Agency (I992a).
1 8.2 SURFACE AREA
2 8.2.1 Background
3 The total surface area of skin exposed to a contaminant must be determined using
4 measurement or estimation techniques before conducting a dermal exposure assessment.
5 Depending on the exposure scenario, estimation of the surface area for the total body or a
6 specific body part can be used to calculate the contact rate for the pollutant. This section presents
7 estimates for total body surface area and for body parts and presents information on the
• 8 application of body surface area data.
9
10 8.2.2 Measurement Techniques
11 Coating, triangulation, and surface integration are direct measurement techniques that
12 have been used to measure total body surface area and the surface area of specific body parts.
13 Consideration has been given for differences due to age, gender, and race. The results of the
14 various techniques have been summarized in Development of Statistical Distributions or Ranges
15 of Standard Factors Used in Exposure Assessments (U.S. EPA, 1985). The coating method
16 consists of coating either the whole body or specific body regions with a substance of known or
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1 measured area. Triangulation consists of marking the area of the body into geometric figures,
2 then calculating the figure areas from their linear dimensions. Surface integration is performed
3 by using a planimeter and adding the areas.
4 The triangulation measurement technique developed by Boyd (1935) has been found to be
5 highly reliable. It estimates the surface area of the body using geometric approximations that
6 assume parts of the body resemble geometric solids (Boyd, 1935). More recently, Popendorf and
7 Leffingwell (1976), and Haycock et al. (1978) have developed similar geometric methods that
8 assume body parts correspond to geometric solids, such as the sphere and cylinder. A linear
9 method proposed by DuBois and DuBois (1916) is based on the principle that the surface areas of
10 the parts of the body are proportional, rather than equal to the surface area of the solids they
11 resemble.
12 In addition to direct measurement techniques, several formulae have been proposed to
13 estimate body surface area from measurements of other major body dimensions (i.e., height and
14 weight) (U.S; EPA, 1985). Generally, the formulae are based on the principles that body density
15 and shape are roughly the same and that the relationship of surface area to any dimension may be
6 represented by the curve of central tendency of their plotted values or by the algebraic expression
7 for the curve. A discussion and comparison of formulae to determine total body surface area are
18 presented in Appendix 8A.
19
20 8.2.3 Body Surface Area Studies
21 U.S. EPA (1985) - Development of Statistical Distributions or Ranges of Standard
22 Factors Used in Exposure Assessments - U.S. EPA (1985) analyzed the direct surface area
23 measurement data of Gehan and George (1970) using the Statistical Processing System (SPS)
24 software package of Buhyoff et al. (1982). Gehan and George (1970) selected 401 measurements
25 made by Boyd (1935) that were complete for surface area, height, weight, and age for their
26 analysis. Boyd (1935) had reported surface area estimates for 1,114 individuals using coating,
27 triangulation, or surface integration methods (U.S. EPA, 1985).
28 U.S. EPA (1985) used SPS to generate equations to calculate surface area as a function of
29 height and weight. These equations were then used to calculate body surface area distributions of
30 the U.S. population using the height and weight data obtained from the National Health and
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1 Nutrition Examination Survey (NHANES) n and the computer program QNTLS of Rochon and
2 Kalsbeek(1983). .
3 The equation proposed by Gehan and George (1970) was determined by U.S. EPA (1985)
4 to be the best choice for estimating total body surface area. However, the paper by Gehan and
5 George (1970) gave insufficient information to estimate the standard error about the regression.
6 Therefore, U.S. EPA (1985) used the 401 direct measurements of children and adults and
7 reanalyzed the data using the formula of Dubois and Dubois (1916) and SPS to obtain the
8 standard error. (U.S. EPA, 1985).
9 Regression equations were developed specific body parts using the Dubois and Dubois
10 (1916) formula and using the surface area of various body pars provided by Boyd (1935) and Van
11 Graan (1969) in.conjunction with SPS. Equations to estimate the body part surface area of
12 children were not developed because of insufficient data.
13 Percentile estimates for total surface area of male and female children presented in
14 Tables 8-1 and 8-2 were calculated using the total surface area regression equation, NHANES II
15 height and weight data, and using QNTLS. Estimates are not included for children younger than
16 2 years old because NHANES height data are not available for this age group. For children, the
17 error associated with height and weight cannot be assumed to be zero because of their relatively
18 small sizes. Therefore, the standard errors of the percentile estimates cannot be estimated, since
19 it cannot be assumed that the errors associated with the exogenous variables (height and weight)
20 are independent of that associated with the model; there are insufficient data to determine the
21 relationship between these errors.
22 Measurements of the surface area of children's body parts are summarized as a percentage
23 of total surface area in Table 8-3. Because of the small sample size, the data cannot be assumed
24 to represent-the average percentage of surface area by body part for all children. Note that the
25 percent of total body surface area contributed by the head decreases from childhood to adult,
26 while the percent contributed by the leg increases.
27 Phillips et al. (1993) - Distributions of Total Skin Surface Area to Body Weight Ratios -
28 Phillips et al. (1993) observed a strong correlation (0.986) between body surface area and body
29 weight and studied the effect of using these factors as independent variables in the LADD
30 equation. Phillips etal. (1993) concluded that, because of the correlation between these two
31 variables, the use of body surface area to body weight (SA/BW) ratios in human exposure
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1 assessments is more appropriate than treating these factors as independent variables. Direct
2 measurement (coating, triangulation, and surface integration) data from the scientific literature
3 were used to calculate body surface area to body weight (S A/BW) ratios for two age groups of
4 children (infants aged 0 to 2 years and children aged 2.1 to 17.9 years). These ratios were
5 calculated by dividing body surface areas by corresponding body weights for the 401 individuals
6 analyzed by Gehan and George (1970) and summarized by U.S. EPA (1985). Distributions of
7 SA/BW ratios were developed and summary statistics were calculated for the two age groups and
8 the combined data set. Summary statistics for the two children's age groups are presented in -
9 Table 8-4. The shapes of these SA/BW distributions were determined using D'Agostino's test.
10 The results indicate that the SA/BW ratios for infants are lognormally distributed. SA/BW ratios
11 for children were neither normally nor lognormaliy distributed. According to Phillips et al.
12 (1993), SA/BW ratios should be used to calculate LADDs by replacing the body surface area
13 factor in the numerator of the LADD equation with the SA/BW ratio and eliminating the body
14 weight factor in the denominator of the LADD equation.
15 The effect of gender arid 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
18 increasing age.
19 Wong et al. (2000) - Adult Proxy Responses to a Survey of Children's Dermal Soil
20 Contact Activities - Wong et al. (2000) conducted telephone surveys to gather information on
21 children's activity patterns as related to dermal contact with soil during outdoor play on bare dirt
22 , or mixed grass and dirt surfaces. This study, the second Soil Contact Survey (SCS-II), was a
23 follow-up to the initial Soil Contact Survey (SCS-I), conducted in 1996, that primarily focused
24 on assessing adult behavior related to dermal contact with soil and dust (Garlock et al., 1999).
25 As part of SCS-I, information was gathered on the behavior of children under the age of 18 years,
26 however, the questions were limited to clothing choices and the length of time after soil contact
27 to hand washing. Results obtained for children from SCS-I were not reported in Garlock et al.
28 (1999), but some of the collected information is summarized in Wong et al (2000). Questions
29 were posed for SCS-II to further define children's outdoor activities and hand washing and
30 bathing frequency. For both soil contact surveys households were randomly phoned in order to
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1 obtain nationally representative results. The adult respondents were questioned as surrogates for
2 one randomly chosen child under the age of 18 residing within the household.
3 For SCS-I, the population size of children sampled was 211. Older children (those
4 between the ages of 5 and 17) were questioned regarding participation in "gardening and
5 yardwork," "outdoor sports," and "outdoor play activities." For children less than 5 years old,
6 "outdoor play activities" occurring on a playground or yard with "bare dirt or mixed grass and
7 dirt" surfaces were noted. The clothing worn during these play activities during warm weather
8 months (April though October) also was questioned. For both groups of children, information
9 was gathered concerning hand washing, bathing, and clothes changing habits after soil contact
10 activities, but these results are not reported in Wong et al. (2000).
11 Results of SCS-I indicate that most children wore short pants, a dress or skin, short
12 sleeve shirts, no socks, and leather or canvas shoes during the outdoor play activities of interest.
13 Using data from Anderson et al. (1985) percentages of total body surface area associated with
14 specific body parts were estimated (Table 8-5). Then exposed skin surface areas for children
15 under age 5 were estimated per clothing item as well as for all clothing items worn together
16 during warm weather outdoor play (Table 8-6). Faces and hands were assumed to be exposed
17 under all conditions with the face having a constant surface area fraction of 5 percent and the
18 hands 6 percent.
19 In the SCS-II, of 680 total adult respondents with a child in their household, 500 (73.5%)
20 reported that their child played outdoors on bare dirt or mixed grass and dirt surfaces (identified
21 as "players"). Those children that reportedly did not play outdoors ("non-players") were
22 typically very young (< 1 year) or relatively older (> 14 years). Of the 500 children that played
23 outdoors, 497 played outdoors in warm weather months (April through October) and 390 were
24 reported to play outdoors during cold weather months (November through March). These results
25 are presented in Table 8-7. The frequency (days/week), duration (hours/day), and total hours per
26 week spent playing outdoors was determined for those children identified as "players"
27 (Table 8-8). The responses indicated that during the warmer months children spend a relatively
28 high percentage of time outdoor and a lesser amount of time in cold weather. The median play
29 frequency reported was 7 days/week in warm weather and 3 days/week in cold weather. Median
30 play duration was 3 hours/day in warm weather and 1 hour/day during cold weather months.
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1 Adult respondents were then questioned as to how many times per day their child washed
12 his/her hands and how many times the child bathed or showered per week during both warm and
3 cold weather months. This information provided an estimate of the time between skin contact
4 with soil and removal of soil by washing (i.e., exposure time). Hand washing and bathing
5 frequencies for child players are reported in Table 8-9. Based on these results, hand washing
6 occurred a median of 4 times per day during both warm and cold weather months. The median
7 frequency for baths and showers was estimated to be 7 times per week for both warm and cold
8 weather.
9 Based on reported household incomes, the respondents sampled in SCS-II tended to have
10 higher incomes than that of the general population. This may be explained by the fact that phone
11 surveys cannot sample those households without telephones. Additional uncertainty or error in
12 the study results may be presented by the use of surrogate respondents. Adult respondents were
13 questioned regarding child activities that may have occurred in prior seasons, introducing the
14 chance of recall error. In some instances, a respondent did not know the answer to a question or
15 refused to answer. In Tables 8-10 and 8-11 iformation extracted from the National Human
16 Activity Pattern Survey (NHAPS) (U.S. EPA, 1996). Table 8-10 compares mean play duration -
11 data from SCS-II to similar activities identified in NHAPS. The number of times per day a child
18 washed his or her hands was presented in both SCS-II and NHAPS follow-up survey B and are
19 shown in Table 8-11. Corresponding information for bathing frequency data collected from
20 SCS-II was not collected in NHAPS. As indicated in Tables 8-10 and 8-11, where comparison is
21 possible, NHAPS and SCS-II results showed similarities in observed behaviors.
22
23 8.2.4 Application of Body Surface Area Data
24 For swimming and bathing scenarios, past exposure assessments have assumed that
25 75 percent to 100 percent of the skin surface is exposed (U.S. EPA, 1992b). Central and upper-
26 percentile values for children should be derived from Table 8-1 or 8-2.
27 Unlike exposure to liquids, clothing may or may not be effective in limiting the extent of
28 exposure to soil. The children clothing scenarios are presented below.
29 Central tendency mid range: Child wears long sleeve shirt, pants, and shoes. The
.30 exposed skin surface is limited to the head and hands. Table 8-3 can be used to determine
the skin surface area depending on the age group of interest.
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I
2
**
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Upper percentile: Child wears a short sleeve shirt, shorts, and shoes. The exposed skin
surface is limited to the head, hands, forearms, and lower legs. Table 8-3 can be used to
determine the skin surface area depending on the age group of interest.
The clothing scenarios presented above, suggest that roughly 10 percent to 25 percent of the skin
area may be exposed to soil. Since some studies have suggested that exposure can occur under
clothing, the upper end of this range was selected in Dermal Exposure Assessment: Principles
and Applications (U.S. EPA, 1992b) for deriving defaults. Default values for children can be
derived by multiplying the 50th and 95th percentiles of the total surface area by 0.25 for the ages
of interest.
When addressing soil contact exposures, assessors may want to refine estimates of
surface area exposed on the basis of seasonal conditions. For example, in moderate climates, it
may be reasonable to assume that 5 percent of the skin is exposed during the winter, 10 percent
during the spring and fall, and 25 percent during the summer.
The previous discussion, has presented information about the area of skin exposed to soil.
These estimates of exposed skin area should be useful to assessors using the traditional approach
of multiplying the soil adherence factor by exposed skin area to estimate the total amount of soil
on skin. The next section presents soil adherence data specific to activity and body part and is
designed to be combined with the total surface area of that body part. No reduction of body part
area is made for clothing coverage using this approach! Thus, assessors who adopt this approach,
should not use the defaults presented above for soil exposed skin area. Rather, they should use
Table 8-3 to estimate surface areas of specific body parts.
8.3 SOIL ADHERENCE TO SKIN
8.3.1 Background
Soil adherence to the surface of the skin is a required parameter to calculate dermal dose
when the exposure scenario involves dermal contact with a chemical in soil. A number of
studies have attempted to determine the magnitude of dermal soil adherence. These studies are
described in detail in U.S. EPA (1992b). This section summarizes recent studies that estimate
soil adherence to skin for use as exposure factors.
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1 8.3.2 Soil Adherence to Skin Studies
2 Kissel et al. (I996a) - Factors Affecting Soil Adherence to Skin in Hand-Press Trials:
3 Investigation of Soil Contact and Skin Coverage - Kissel et al. (1996a) conducted soil adherence
4 experiments using five soil types (descriptor) obtained locally in the Seattle, Washington, area:
5 sand (211), loamy sand (CP), loamy sand (85), sandy loam (228), and silt loam (72). All soils
6 were analyzed by hydrometer (settling velocity) to determine composition. Clay contents ranged
7 from 0.5 to 7.0 percent. Organic carbon content, determined by combustion, ranged from 0.7 to
8 4.6 percent. Soils were dry sieved to obtain particle size ranges of <150, 150-250, and >250 #m.
9 For each soil type, the amount of soil adhering to an adult female hand, using both sieved and
10 unsieved soils, was determined by measuring the difference in soil sample weight before and
11 after the hand was pressed into a pan containing the test soil. Loadings were estimated by
12 dividing the recovered soil mass by total hand area, although loading occurred primarily on only
13 one side of the hand. Results showed that generally, soil adherence to hands could be directly
14 correlated with moisture content, inversely correlated with particle size, and independent of clay
15 content or organic carbon content.
6 Kissel et al (1996b) - Field Measurement of Dermal Soil Loading Attributable to Various
17 Activities: Implications for Exposure Assessment - Further experiments were conducted by
18 Kissel et al. (1996b) to estimate soil adherence associated with various indoor and outdoor
19 activities: greenhouse gardening, tae kwon do karate, soccer, rugby, reed gathering, irrigation
20 installation, truck farming, and playing in mud. Several of the activities studied by Kissel
21 (1996b) involved children, as shown in Table 8-12. A summary of field studies by activity,
22 gender, age, field conditions, and clothing worn is presented in Table 8-12. Subjects' body
23 surfaces (forearms, hands, lower legs in all cases, faces, and/or feet; pairs in some cases) were
24 washed before and after monitored activities. Paired samples were pooled into single ones.
25 Mass recovered was converted to loading using allometric models of surface area. These data are
26 presented in Table 8-13. Results presented are based on direct measurement of soil loading on
27 the surfaces of skin before and after activities that may be expected to have soil contact (Kissel et
28 al., 1996b). The results indicate that the rate of soil adherence to the hands is higher than for
29 other parts of the body.
30
June 2000 8-9 DRAFT-DO NOT QUOTE OR CITE
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1 Holmes, Jr., K.K., J.H. Shirai, K. Y. Richter, andJ.C. Kissel (1999) - Field Measurement
2 of Dermal Soil Loadings in Occupational and Recreational Activities - Holmes et al. (1999)
3 collected pre- and post-activity soil loadings on various body parts of individuals within groups
4 engaged in various occupational and recreational activities. These groups included children at a
5 daycare center and playing indoors in a residential setting. This study was conducted as a follow
6 up to previous field sampling of soil adherence on individuals participating in various activities
7 (Kissel et al., 1996). For this round of sampling, soil loading data were collected utilizing the
8 same methods used and described in Kissel et al. (1996). Information regarding the groups of
9 children studied and their observed activities are presented in Table 8-14.
10 The daycare children studied were all at one location and measurements were taken on
11 three different days. The children freely played both indoors in the house and outdoors in the
12 backyard. The backyard was described as having a grass lawn, shed, sand box, and wood chip
13 box. In this setting, the children engaged in typical activities including: playing with toys and
14 each other, wrestling, sleeping, and eating. The number of children within each day's group and
15 the clothing worn is described in Table 8-15.
16 The five children measured on the first day were washed first thing in the morning to •
17 establish a preactivity level. They were next washed at noon to determine the postactivity soil
18 loading for the morning (Daycare kids No. 1 a). The same children were washed once again at
19 the close of the day for measurement of soil adherence from the afternoon play activities
20 (Daycare kids No. Ib).
21 For the second observation day (Daycare kids No. 2), postactivity data were collected for
22 five children. All the activities on this day occurred indoors. For the third daycare group
23 (Daycare kids No. 3), four children.were studied.
24 On two separate days, children playing indoors in a home environment were monitored.
25 The first group (Indoor kids No. 1) had four children while the second group (Indoor kids No. 2)
26 had six children. The play area was described by Holmes et al. (1999) as being primarily
27 carpeted. The clothing worn by the children within each day's group is described in Table 8-15.
28 The geometric means and standard deviations of the postactivity soil adherence for each
29 group of children and for each body part are summarized in Table 8-16. According to Holmes et
30 ' al. (1999), variations in the soil loading data from the daycare participants reflect differences in
31 the weather and access to the outdoors.
June 2000
8-10
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1 An advantage of this study is that it provides a supplement to soil loading data collected
\2 in a previous round of studies (Kissel et al, 1996b). Also, the data support the. assumption that
3 hand loading can be used as a conservative estimate of soil loading on other body surfaces for the
4 same activity. The activities studied represent normal child play both indoors and outdoors, as
5 well as for different combinations of clothing. The small number of participants (n) is a
6 disadvantage of this study. Also, the children studied and the activity setting may not be
7 representative of the U.S. population.
8 Kissel et al. (1998) - Investigation of Derma! Contact with Soil in Controlled Trials • In
9 this study, Kissei et al.(1998) measured dermal exposure to soil from staged activities conducted
10 in a greenhouse. A fluorescent marker was mixed in soil so that soil contact for a particular skin
11 surface area could be identified. As described in Kissel et al.( 1998), the subjects, which included
12 a group of children, were video imaged under a long-wave ultraviolet (UV) light before and after
13 soil contact. In this manner, soil contact on hands, forearms, lower legs, and faces was assessed
14 by presence of fluorescence. In addition to fluorometric data, gravimetric measurements for
15 preactivity and postactivity were obtained from the different body parts examined.
gmi6 The studied group of children played for 20 minutes in a soil bed of varying moisture
17 content representing wet and dry soils. For wet soils, both combinations of long sleeves and long
18 pants and short sleeves and short pants were tested. Children only wore short sleeves and short
19 pants during play in the dry soil. Clothing was laundered after each trail. Thus, a total of three
20 trials with children were conducted. The parameters describing each of these trials are
21 summarized in Table 8-17.
22 Before each trial, each child was washed in order to obtain a preactivity or background
23 gravimetric measurement. Preactivity data are shown in Table 8-18. Body part surface areas
24 were calculated using Anderson et al. (1985) for the range of heights and weights of the study
25 participants.
26 For wet soil, postactivity fluorescence results indicated that the hand had a much higher
27 fractional coverage than other body surfaces (see Figure 8-2). No fluorescence was detected on
/
28 the forearms or lower legs of children dressed in long sleeves and pants.
29 As shown in Figure 8-3, postactivity gravimetric measurements showed higher soil
30 loading on hands and much lower amounts on other body surfaces, as was observed with
fluorescence data. According to Kissel etal. (1998), the relatively low loadings observed on
J June 2000 • 8-11 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11.
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
non-hand body parts may be a result of the limited area of contact rather than lower localized
loadings. A geometric mean dermal loading of 0.7 mg/cm2 was found on children's hands
following play in wet soil. Mean loadings were lower on hands in the dry soil tria! 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.
There is also some evidence from this study demonstrating the protective effect of clothing.
Disadvantages of the study include a small number of study participants and a short activity
duration. Also, no information is provided on the ages of the children involved in the study.
8.4 RECOMMENDATIONS
8.4.1 Body Surface Area
Body surface area estimates are based on direct measurements. Re-analysis of data
collected by Boyd (1935) by several investigators (Gehan and George, 1970; U.S. EPA, 1985;
Murray and Burmaster, 1992; Phillips et al., 1993) constitutes much of this literature. Methods
are highly reproducible and the results are widely accepted. The representativeness of these data
to the general population is somewhat limited since variability due to race or gender have not
been systematically addressed.
The recommendations for body surface area for children are summarized in Table 8-19.
These recommendations are based on U.S. EPA (1985) and Phillips et al. (1993). Table 8-20
presents the confidence ratings for various aspects of the recommendations for body surface area.
The U.S. EPA (1985) study is based on generally accepted measurements that enjoy widespread
usage, summarizes and compares previous reports in the literature, provides statistical
distributions for adults, and provides data for total body surface area and body parts by gender for
children. The results are based on selected measurements from the original data collected by
Boyd (1935). Phillips et al. (1993) analyses are based on direct measurement data that provide
distributions of body surface area to calculate LADD. The results are consistent with previous
efforts to estimate body surface area. Analyses are also based on measurements selected from the
original measurements made by Boyd (1935) and data were not analyzed for specific body parts.
June 2000
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1 8.4.2 Soil Adherence to Skin
12 Recommendations for the rate of soil adherence to the skin are based "on data collected by
3 Kissel et al. (1996a; 1996b) for specific activities. The experimental design and measurement
4 methods used by Kissel et al. (1996a; 1996b) are straightforward and reproducible, but it should
5 be noted that the controlled experiments and field studies are based on a limited number of
6 measurements and specific situations were selected to assess soil adherence to skin.
7 Consequently, variation due to individuals, protective clothing, temporal, or seasonal factors
8 remain to be studied in more detail. Therefore, caution is required in interpretation and
9 application of these results for exposure assessments.
} 0 In consideration, of these general observations and the recent data from Kissel et al.
11 (1996a, 1996b), changes are needed from past EPA recommendations which used one adherence
12 value to represent all soils, body parts, and activities. One approach would be to select the
13 activity from Table 8-12 which best represents the exposure scenario of concern and use the
14 corresponding adherence value from Table 8-13. Although this approach represents an
15 improvement, it still has shortcomings. For example, it is difficult to decide which activity in
16 Table 8-13 is most representative of a typical residential setting involving a variety of activities.
17 It may be useful to combine these activities into general classes of low, moderate, and high
18 contact. In the future, it may be possible to combine activity-specific soil adherence estimates
19 with survey-specific soil adherence estimates with survey-derived data on activity frequency and
20 duration to develop overall average soil contact rates. EPA is sponsoring research to develop
21 such an approach. As this information becomes available, updated recommendations will be
22 issued.
23 Table 8-13 provides the best estimates available on activity-specific adherence values, but
24 are based on limited data. Therefore, they have a high degree of uncertainty such that
25 considerable judgment must be used when selecting them for an assessment. The confidence
26 ratings for various aspects of this recommendation are summarized in Table 8-21. Insufficient
27 data are available to develop a distribution or a probability function for soil loadings.
28 Past EPA guidance has recommended assuming that soil exposure occurs primarily to
29 exposed body surfaces and used typical clothing scenarios to derive estimates of exposed skin
30 . area. The approach recommended above for estimating soil adherence addresses this issue in a
rl different manner. This change was motivated by two developments. First, increased acceptance
June 2000 8-13 DRAFT-DO NOT QUOTE OR CITE
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1 that soil and dust particles can get under clothing and be deposited on skin. Second, recent
2 studies of soil adherence have measured soil on entire body parts (whether or not they were
3 covered by clothing) and averaged the amount of soil adhering to skin over the area of entire
4 body part. The soil adherence levels resulting from these new studies must be combined with the
5 surface area of the entire body part (not merely unclothed surface area) to estimate the amount of
6 contaminant on skin. An important caveat, however, is that this approach assumes that clothing
7 in the exposure scenario of interest matches the clothing in the studies used to derive these
8 adherence levels such that the same degree of protection provided by clothing can be assumed in
9 both cases. If clothing differs significantly between the studies reported here and the exposure
10 scenarios under investigation, considerable judgment is needed to adjust either the adherence
11 level or surface area assumption.
12 The dermal adherence value represents the amount of soil on the skin at the time of
13 measurement. Assuming that the amount measured on the skin represents its accumulation
14 between washings and that people wash at least once per day, these adherence values can be
15 interpreted as daily contact rates (U.S. EPA, 1992b). However, this is not recommended because
16 the residence time of soils on skin has not been studied. Instead, it is recommended that these
17 adherence values be interpreted on an event basis (U.S. EPA, 1992b).
June 2000
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8.5 REFERENCES FOR CHAPTER 8
3 Anderson E., Browne N., Duletsky S., Ramig J. and Warn T. (1985) Development of Statistical Distributions or
4 Ranges of Standard Factors Used in Exposure Assessments. U. S. EPA Office of Health and
5 Environmental Assessment, Washington, D.C. NTIS PB85-242667.
6
7 Boyd, E. (1935) The growth of the surface area of the human body. Minneapolis, Minnesota: University of
8 Minnesota Press.
9
10 Buhyoff, G.J.; Rauscher, H.M.; Hull, R.B.; Killeen, K.; Kirk, R.C. (1982) User's Manual for Statistical Processing
11 System (version 3C.1). Southeast Technical Associates, Inc.
12 . • •
13 Cohen-Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McLundy, T.R.; Berry, M.R.; Rigas, M.L.; Zartarian, V.G.;
14 • Freeman, N.C.G. (1999) Children's exposure assessment: A review of factors influencing children's
15 exposure, and the data available to characterize and assess that exposure. Research Triangle Park, NC:
16 U.S. Environmental Protection Agency, National Exposure Research Laboratory.
17
18 Dubois, D.; Dubois. E.F. (1916) A formula to estimate the approximate surface area if height and weight be
19 known. Arch, of Intern. Med. 17:863-871.
20
21 Gehan, E.; George, G.L. (1970) Estimation of human .body surface area from height and weight. Cancer
22 Chemother. Rep. 54(4):225-235.
23
24 Garlock T.J.. Shirai, J.H. and Kissel, J.C. (1999) Adult responses to a survey of soil contact related behaviors. J.
25 Exposure Anal. Environ. Epid. 1999: 9: 134-142.
26
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.
29
30 Georae, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz, GJ. (1979) Letters to the editor. J. Ped. 94(2):342.
31
32 Haycock, G.B.; Schwartz, G.J.; Wisotsky, D.H. (1978) Geometric method for measuring body surface area:
33 A height-weight formula validated in infants, children, and adults. J. Ped. 93(l):62-66.
34
35 Holmes. K.K.; Kissel. J.C.; Richter, K.Y. (1996) Investigation of the influence of oil on soil adherence to skin. J.
36 Soil. Contam. 5(4):301-308.
37
38 Holmes, Jr.. K.K., J.H. Shirai, K.Y. Richter, and J. C. Kissel (1999) Field Measurement of Dermal Loadings in
39 Occupational and Recreational Activities, Environmental Research, Section A. 80, 148-157.
40
41 Kissel, J.; Richter, K.; Duff, R.; Fenske, R. (1996a) Factors Affecting Soil Adherence to Skin in Hand-Press Trials.
42 Bull. Environ. Contamin. Toxicol. 56:722-728.
43
44 Kissel. J.: Richter. K.: Fenske. R. (I996b) Field measurements of dermal soil loading attributable to various
45 activities: implications for exposure assessment- Risk Anal. 16(1): 116-125.
46
47 Kissel, J.C.. Shirai. J. H., Richter, K.Y., and R.A. Fenske (1998) Investigation of Dermal Contact with Soil in
48 Controlled Trials. Journal of Soil Contamination. 7(6): 737-752.
49
50 Murray, D.M.; Burmaster. D.E. (1992) Estimated distributions for total surface area of men and women in the
51 United States. J. Expos. Anal. Environ. Epidemiol. 3(4):451-462.
9
June 2000 8-15 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
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. Expos. Anal. Environ. Epidemiol. 3(3):331-338.
Po'pendorf, W.J.; Leffingwell, J.T. (1976) Regujating OP pesticide residues for farmworker protection.
In: Residue Review 82. New York, NY: Springer-Veriag New York, Inc., 1982. pp. 125-201.
Rochon, J.; Kalsbeek, W.D. (1983) Variance estimation from multi-stage sample survey data: the jackknife
repeated replicate approach. Presented at 1983 SAS Users Group Conference, New Orleans, Louisiania,
January 1983.
Sendroy, J.; Cecchini, L.P. (1954) Determination of human body surface area from height and weight. J. Appl.
Physiol. 7(1):3-12.
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. Environmental Protection Agency (U.S. EPA) (1996) Analysis of the National Human Activity Pattern Survey
(NHAPS) Respondents from a Standpoint of Exposure assessment. Office of Research and Development,
Washington, D.C., EPA/600/R-96/074.
Van Graan, C.H. (1969) The determination of body surface area. Supplement to the South African J. of Lab. and
Clin. Med. 8-2-69.
Wong E. Y., Shirai, J.H, Garlock, T. J., and Kissel, J.C. (2000) Adult Proxy Responses to a Survey of Children's
Dermal Soil Contact Activities, Submitted for publication.
June 2000
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Table 8-1. Total Body Surface Area of Male
Children in Square Meters*
A.\
•
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
,7
8
30
31
32
33
34
35
;v "
(yr)
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9<10
10< 11
1K12
12<13
13<14
14<15
15
-------
1
2
•3
Table 8-2. Total Body Surface Area of Female
Children in Square Meters"
6
7
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
Age(yr)b
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9
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Table 8-12. Summary of Field Studies
1 3 Event" Age
4 Activity Month (hrs) Nb M F (yrs) Conditions Clothing
5
6
7
8
9
10
indoor
Tae Kwon Do Feb.
Indoor Kids No. 1 Jan.
Indoor Kids No. 2 Feb.
Daycare Kids No. la Aug.
1 .5 761 8-42 Carpeted floor All in longsieeve-long pants
martial arts uniform, sleeves
rolled back, barefoot
2 43 1 6-13 Playing on carpeted floor 3 of 4 short pants, 2 of 4 short
sleeves, socks, no shoes
2 6 4 2 3-! 3 Playing on carpeted floor 5of 6 long pants, 5 of 6 long
sleeves, socks, no shoes
3:5' 6 5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6
1-1
12
[4
15
16
17
18
19
20
21
9 2
23
24
25
Daycare Kids No. lb Aug. 4 6
Daycare Kids No.2c Sept. 8 . 5
Daycare Kids No. 3 Nov. 8 4
Outdoor
Soccer No. 1
Nov. 0.67 8
Gardeners No. 1 Aug. 4 8
outdoors: grass, bare earth, short sleeves, shoes
barked area
5 1 1-6.5 indoors: linoleum surface; 4 of 6 in long pants, 4 of 6
outdoors: grass, bare earth, short sleeves, no shoes
barked area
4 1 i-4 Indoors, low napped 4 of 5 long pants, 3of 5 long
carpeting, linoleum sleeves, all barefoot for part
surfaces of the day
3 1 1-45 Indoors: linoleum surface, All long pants, 3 of 4 long
outside: grass, bare earth, sleeves, socks and shoes
barked area
8 0 13-15 Half grass-half bare earth 6 of 8 long sleeves, 4 of 8
long pants, 3 of 4 short pants
and shin guards
1 7 16-35 Weeding, pruning,digging 6 of 8 long pants, 7 of 8 short
Archeologists
July 11.5 7
Kids-in-mud No. 1 Sept. 0.17 6
Kids-in-mud No. 2 Sept. 0.33 6
a trench
3 4 16-35 Digging withtrowel,
screening dirt, sorting
5 I 9-14 Lake shoreline
5 1 9-14 Lake shoreline
sleeves. 1 sleeveless, socks,
shoes, intermittent use of
gloves
6 of 7 short pants.a!I short
sleeves, 3 no shoes or socks,
2 sandals
All in short sleeve T-shirts,
shorts, barefoot
All in short sleeve T-shirts,
shorts barefoot
'Event duration
"Number of subject
'Activities were confined to the house
Sources: Kissel et al. (1996b); Holmes et al. (1996).
June 2000
8-25
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1
2
3
4
5-
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Table
8-13. Geometric Mean And Geometric Standard Deviations of
Soil Adherence by Activity And Body Region
Activity
Indoor
Tae Kwon Do
Indoor Kids No. 1
Indoor Kids No. 2
Daycare Kids No. la
Daycare Kids No. Ib
Daycare Kids No. 2
Daycare Kids No. 3
Outdoor
Soccer No. 1
Gardeners No. 1
Archeoiogists
Kids-in-mud No. 1
Kids-in-mud No. 2
'Number of subjects.
Sources: Kissel et al.
*
N"
7
4
6
6
6
5
4
8
8
7
6
6
(1996b);
Hands
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
0.11
1.8
0.20
1.9
0.14
1.3
35
2.3
58
2.3
Holmes et al.
Post-activity
Arms
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
0.011
2.0
0.050
2.1
0.041
1.9
II
6.1
11-
3.8
(1996).
Dermal Soil Loadings (mg/cm2)
Legs Faces
0.0020
2.0
0.0041
2.3
0.0031
1.5
0.030
1.7
0.023
1.2
0.01 1
1-4
0.014
3.0
0.031 0.012
3.8 1.5
. 0.072 0.058
1.6
0.028 0.050
4.1 1.8
36
2.0
9.5
2.3
Feet
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
0.17
-
0.24
1.4
24
3.6
6.7
12.4
June 2000
8-26
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1
2
(3
4
5
6
7
8
9
10
11
Table 8- 14.
Activity
Daycare kids No. la
Daycare kids No. Ib
Daycare kids No. 2
Daycare kids No. 3
Indoor kids No. 1
Indoor kids No. 2
a Event duration.
b Number of subjects.
Summary of Groups Assayed in Round 2 of Field Measurements
Month
Aug.
Aug.
Sept.
Nov.
Jan.
Feb.
Event* (hrs)
3.5
4
8
8
2
2
n"
6
6
5
4
4
6
Males
5
5
4
3
3
4
Females
1
1
I
1
1
2
Ages
1-6.5
1-6.5
I - 4
1 -4.5
6-13
3 -13
June 2000
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1
2
3
4
5
6
7
8
9
10
U
12
13
14
15
16
17
Table 8- 15
. Attire for Individuals within Children
Pants
Activity
Daycare kids No. la
Daycare kids No. Ib
Daycare kids No. 2
Daycare kids No. 3b
Indoor kids No. I
Indoor kids No. 2
a Number of subjects.
ff
6
6
5
4
4
6
Long
4
4
4
4
1
5.
Short
2
2
1
0
3
1
Sleeves
Long Short
1 5
1 5
2 3
3 I
2 2
5 1
's Groups Studied
Socks Shoes
High
1
1
NA
0
0
0
Low
5 low leather or canvas
shoes - 6
5 barefoot - 3
low leather or canvas
shoes - 3
NA barefoot - 2
shoes/socks % day and
barefoot Vi day - 3
4 low shoes - 4
4 no shoes (socks only) -
6 no shoes (socks only) -
4
6
b All children wore jackets when engaged in outdoor activities.
NA - "Not Available": 3
socks worn.
children
wore socks
for '/= day
in the morning but no specific
information is provided on the type of
June 2000
8-28
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1
2
3
4
5
6
' 7
8
9
10
11
12
13
14
15
Table 8-16. Geometric Means (Geometric
Standard Deviations) of Round 2 Post-activity Loadings
Postactivity Dermal Soil Loadings (mg/crn2)
Activity
Daycare kids No. la
Daycare kids No. 1 b
Daycare kids No. 2
Daycare kids No. 3
Indoor kids No. 1
Indoor kids No. 2
n" Hands
4 0.11(1.9)
6 0.15(2.1)
6 0.073(1.6)
6 0.036(1.3)
5 0.0073(1.9)
4 0.014(1.5)
Forearms
0.026(1.9)
0.031 (1.8)
0.023(1.4)
0.012(1.2)
0.0042(1.9)
0.0041 (2.0)
Lower legs Faces6
0.030(1.7)
0.023(1.2)
0.011 (1.4)
0.014(3.0)
0.0041 (2.3)
0.0031 (1.5)
Feet
0.079 (2.4)
0.13(1.4)
0.044(1.3)
0.0053(5.1)
0.012(1.4)
0.0091 (1.7)
a Number of subjects (number of data points for specific non-hand body parts may deviate slightly).
b Children's feet rather than faces were washed in order to reduce the chance of a child's refusal to panicipate.
June 2000
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1
2
Table 8-17. Summary of Controlled Green House Trials - Children Playing
Activity Ages
Duration
(min)
Soil moisture Clothing3 n
Male
Female
5
6
7
8
Playing 8-12
20
17-18
16-18
3-4
L
S
S
4
9
5
3
5
I
4
2
a L, long sleeves and long pants; S, short sleeves and short pants.
June 2000
8-30
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1
2
3
4
5
Table 8-18. Preactivity Loadings Recovered from Greenhouse Trial Children Volunteers
Area
Body part surface area (cm2)
Geometric mean
(95% C.I.) (ng/cnr)
Hands
Forearms
Lower legs
Face
12
12
12
420-798
584-932
1,206-2,166
388-602
9.4
(5.4-15.8)
3.4
(2.3 - 5.2)
1.0
(0.7-1.5)
0.8
(0.5-1.5)
10
11
June 2000
8-31
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1
2
3
4
5
6
7
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
45
46
47
48
49
Hands
Lower legs/short pants
Forearms/short sleeves
Faces -4
Adult
Child
"I * ' • ^^^^^ I "*"^^
20 40 60
Percent Fluorescing
80
"—i
100
Figure 8-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults
Transplanting Plants and for Children Playing in Wet Soils
adult x
child, wet +
O
% H
JJ ;
^b
—
.5 0.3 J
"§
S 3
=
C4 0.01 J
0.001 -I
?i
' -L •
T
T
I
,
child, dry
*
T-
}i
r
!i .,
11 **t ^
x?<
I
1 • J
[
i
L
Hands Legs Arms Faces
Figure 8-3. Gravimetric Loading vs. Body Part for Adult Transplanting Plants in Wet Soil
and for Children Playing in Wet and Dry Soils
June 2000
8-32
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1
2
3
4
5
6
7
8
9
10
11
12
Table 8-19. Summary of Recommended Values For Skin Surface Area
Surface Area
Central Tendency
Upper Percentile
Multiple Percentiles
Whole body
Body parts
see Tables 8-1,8-2, and 8-
4
see Table 8-3
see Tables 8-1,8-2, and
8-4
see Table 8-3
June 2000
8-33
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1
2
3
4
5
Table 8-20. Confidence in Body Surface Area Measurement Recommendations
Considerations
Rationale
Rating
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Study Elements
• Level of Peer Review
• Accessibility
• Reproducibility
• Focus on factor of interest
• Data pertinent to U.S.
• Primary data
• Currency
Adequacy of data collection
period
Validity of approach
Representativeness of the
population
Characterization of variability
• Lack of bias in study design
• Measurement error
Other Elements
• Number of studies
• Agreement among researchers
Overall Rating
Studies were from peer reviewed journal articles. High
EPA report was peer reviewed before distribution.
The journals used have wide circulation. High
EPA report available from National Technical
Information Service.
Experimental methods are well-described. High
Experiments measured skin area directly. High
Experiments conducted in the U.S. High
Re-analysis of primary data in more detail by two Low
different investigators.
Neither rapidly changing nor controversial area; Low
estimates made in 1935 deemed to be accurate and
subsequently used by others.
Not relevant to exposure factor; parameter not time NA
dependent.
Approach used by other investigators; not challenged High
in other studies.
Not statistically representative of U.S. population. Medium
Individual variability due to age, race, or gender not Low
studied.
Objective subject selection and measurement High
methods used; results reproduced by others with
different methods.
Measurement variations are low; adequately Low/Medium
described by normal statistics.
1 experiment; two independent re-analyses of this Medium
data set.
Consistent results obtained with different analyses; Medium
but from a single set of measurements.
This factor can be directly measured. It is not Medium
subject to dispute. Influence of age, race, or gender
have not been detailed adequately in these studies.
June 2000
8-34
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1
2
>
4
5
6
7
8
9
10
Table 8-21.
Considerations
Study Elements
• Level of Peer Review
• Accessibility
• Reproducibility
• Focus on factor of interest
* Data pertinent to U.S.
• Primary data
Confidence in Soil Adherence to Skin Recommendations
Rationale
Studies were from peer reviewed journal articles.
Articles were published in widely circulated
journals.
Reports clearly describe experimental method.
The goal of the studies was to determine soil
adherence to skin.
Experiments were conducted in the U.S.
Experiments were directly measure soil adherence to
Rating
High
High
High
High
High
High
11 • Currency
12 • Adequacy of data collection
13 period
14 • Validity of approach
• Representativeness of the
population
17 • Characterization of variability
18 • Lack of bias in study design
19 • Measurement error
20 Other Elements
21 • Number of studies
22 • Agreement among researchers
23 Overall Rating
skin; exposure and dose of chemicals in soil were
measured indirectly or estimated from soil contact.
New studies were presented. High
Seasonal factors may be important, but have not been Medium
studied adequately.
Skin rinsing technique is a widely employed High
procedure.
Studies were limited to the State of Washington and Low
may not be representative of other locales.
Variability in soil adherence is affected by many Low
factors including soil properties, activity and
individual behavior patterns.
The studies attempted to measure soil adherence in High
selected activities and conditions to identity
important activities and groups.
The experimental error is iow and well controlled, Low/High
but application of results to other similar activities
may be subject to variation.
The experiments were controlled as they were Medium
conducted by a few laboratories; activity patterns
were studied by only one laboratory.
Results from key study were consistent with earlier Medium
estimates from relevant studies and assumptions, but
are limited to hand data.
Data are limited, therefore it is difficult to Low
extrapolate from experiments and field observations
to general conditions.
June 2000
8-35
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APPENDIX 8A
FORMULAE FOR TOTAL BODY SURFACE AREA
June 2000
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1 APPENDIX 8A
2 FORMULAE FOR TOTAL BODY SURFACE AREA
3 . . •
4 Most formulae for estimating surface area (SA), relate height to weight to surface area. The
5 following formula was proposed by Gehan and George (1970):
6
7 SA-KW2/3 (8A-1)
8 bA-KW
9 where:
10
11 SA = surface area in square meters;
12 W = weight in kg; and
13 K = constant.
14
15 While the above equation has been criticized because human bodies have different
16 specific gravities and because the surface area per unit volume differs for individuals with
17 different body builds, it gives a reasonably good estimate of surface area.
18
19 A formula published in 1916 that still finds wide acceptance and use is that of DuBois
20 and DuBois. Their model can be written:
21
SA = a0Ha W ~ (8A-2)
2 where:
23 . • •
24 SA = surface area in square meters;
25 H = height in centimeters; and
26 W = weight in kg.
27 .
28 The values of ao (0.007182), a, (0.725), and a, (0.425) were estimated from a sample of
29 only nine individuals for whom surface area was directly measured. Boyd (1935) stated that the
30 Dubois formula was considered a reasonably adequate substitute for measuring surface area.
31 Nomograms for determining surface area from height and mass presented in Volume I of the
32 Geigy Scientific Tables (1981) are based on the DuBois and DuBois formula. In addition, a
33 computerized literature search conducted for this report identified several articles written in the
34 last 10 years in which the DuBois and DuBois formula was used to estimate body surface area.
35 Boyd (1935) developed new constants for the DuBois and DuBois model based on
36 231 direct measurements of body surface area found in the literature. These data were limited to
37 measurements of surface area by coating methods (122 cases), surface integration (93 cases), and
38 triangulation (16 cases). The subjects were Caucasians of normal body build for whom data on
39 weight, height, and age (except for exact age of adults) were complete. Resulting values for the
40 constants in the DuBois and DuBois model were % = 0.01787, a, = 0.500, and a, = 0.4838. Boyd
41 also developed a formula based exclusively on weight, which was inferior to the DuBois and
42 DuBois formula based on height and weight.
3 Gehan and George (1970) proposed another set of constants for the DuBois and DuBois
4 model. The constants were based on a total of 401 direct measurements of surface area, height,
June 2000 8A-1 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
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: % = 0.02350, a, = 0.42246,
and a2 = 0.51456. Hence, their equation for predicting SA is:
SA-0.02350 H°-42246W0'51456
(8A-3)
or in logarithmic form:
lnSA= -3.75080= 0.422461nH = 0.514561nW
(8A-4)
where:
SA =
H =
W =
surface area in square meters;
height in centimeters; and
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).
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:
(8A-5)
or in losarithmic form:
ln(SA)j =
(8A-6)
June 2000
8A-2
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1 where:
2
'3 Sai = surface area of the i-th individual (m2);
4 Hi = height of the i-th individual (cm);
5 Wi = weight of the i-th individual (kg);
6 HO, a,, and a2 - parameters to be estimated; and
7 es = a random error term with mean zero and constant variance.
8
9
10 Using the least squares procedure for the 401 observations, the following parameter
11 estimates and their standard errors were obtained:
12
13
a0 =-3.73(0.18)^1 =0.417(0.054)^2 =0-517(0.022)
14 The model is then:
15
SA = 0.0239H°-417W°-517 <*A-7)
16
17
18 or in logarithmic form:
9
0
In SA =-3.73 + 0.417 In H+0.517 In W (8A-.8)
21
22 with a standard error about the regression of 0.00374. This model explains more than 99 percent
23 of the total variation in surface area among the observations, and is identical to two significant
24 figures with the model developed by Gehan and George (1970).
25 When natural logarithms of the measured surface areas are plotted against natural
26 logarithms of the surface predicted by the equation, the observed surface areas are symmetrically
27 distributed around a line of perfect fit, with only a few large percentage deviations. Only five
28 subjects differed from the measured value by 25 percent or more. Because each of the five
29 subjects weighed less than 13 pounds, the amount of difference was small. Eighteen estimates
30 differed from measurements by 15 to 24 percent. Of these, 12 weighed less than 15 pounds each,
31 1 was overweight (5 feet 7 inches, 172 pounds), 1 was very thin (4 feet 11 inches, 78 pounds),
32 and 4 were of average build. Since the same observer measured surface area for these 4 subjects,
33 the possibility of some bias in measured values cannot be discounted (Gehan and George 1970).
34 Gehan and George (1970) also considered separate constants for different age groups:
35 less than 5 years old, 5 years oid to less than 20 years old, and greater than 20 years old. The
36 different values for the constants are presented below:
37
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1
2
3
4
Table 8A-1. Estimated Parameter Values for Different Age Intervals
8
9
10
11
12
13
14
15
1.6
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Age
group
All ages
<5 years old
> 5 - <20 years old
> 20 years old
Number
of persons
401
229
42
30
a<>
0.02350
0.02667
0.03050
0.01545
a
0.42246
0.38217
0.35129
0.54468
a,
0.51456
0.53937
0.54375
0.46336
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 nr for an 18-year-old at the
97th percentile. The authors concluded that there is no advantage in using separate values of ao,
a,, and a, by age interval.
Haycock et ai. (1978) without knowledge of the work by Gehan and George (1970),
developed values for the parameters a0, a,, and a, 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 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:
^ = 0.024265, a, = 0.3964, and a, = 0.5378. The result was the following equation for
estimating surface area:
SA=0.024265H°-3964W0-5378
expressed logarithmically as:
In SA = In 0.024265 + 0.3964 In H + 0.5378 In W
(8A-9)
(8A-10)
The coefficients for this equation agree remarkably with those obtained by Gehan and George
(1970) for 401 measurements.
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1 George et al. (1979) agree that a model more complex than the model of DuBois and"
2 DuBois for estimating surface area is unnecessary. Based on samples of direct measurements by
3 Boyd (1935) and Gehan and George (1970), and samples of geometric estimates by Haycock
4 et al. (1978), these authors have obtained parameters for the DuBois and DuBois model that are
5 different than those originally postulated in 1916. The DuBois and DuBois model can be written
6 logarithmically as:
lnSA = lnaQ-aj lnH + a2 InW
7
8
9 The values for a0, a,, and a, obtained by the various authors discussed in this section are
10 presented to follow:
11
12 Table 8A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model
13
14
15
16
17
18
19
|20
21
22 . '
23
24 The agreement between the model parameters estimated by Gehan and George (1970) and
25 Haycock et al. (1978) is remarkable in view of the fact that Haycock et al. (1978) were unaware
26 of the previous work. Haycock et al. (1978) used an entirely different set of subjects, and used
27 geometric estimates of surface area rather than direct measurements. It has been determined that
28 the Gehan and George model is the formula of choice for estimating total surface area of the
29 body since it is based on the largest number of direct measurements.
30
31 Nomograms
32 Sendroy and Cecchini (1954) proposed a graphical method whereby surface area could be
33 read from a diagram relating height and weight to surface area. However, they do not give an
34 explicit model for calculating surface area. The graph was developed empirically based on
35 252 cases, 127 of which were from the 401 direct measurements reported by Boyd (1935). In the
36 other 125 cases the surface area was estimated using the linear method of DuBois and DuBois
37 (1916). Because the Sendroy and Cecchini method is graphical, it is inherently less precise and
38 less accurate than the formulae of other authors discussed above.
Author
(year)
DuBois and DuBois
(1916)
Boyd (1935) -
Gehan and George
(1970)
Haycock etal. (1978)
Number
of persons
. 9
231
401
81
a0
0.007184
0.01787
0.02350
0.024265
a,
0.725
0.500
0.42246
0.3964
a2
0.425
0.4838
0.51456
0.5378
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1 9. ACTIVITY FACTORS
2
3 9.1 INTRODUCTION
4 As a consequence of a child's immaturity and small stature, certain activities and
5 behaviors specific to children place them at higher risk to certain environmental agents (Chance
6 and Harmsen, 1998). Individual or group activities are important determinants of potential
7 exposure because toxic chemicals introduced into the environment may not cause harm a child
8 until an activity is performed subjecting the child to contact with those contaminants. An
9 activity or time spent will vary based on. for example, culture, hobbies, location, gender, age, and
] 0 personal preferences. It is difficult to accurately collect/record data for a child's activity patterns
11 (Hubal et al., 1999). Children engage in more contact activities than adults, therefore, a much
12 wider distribution of activities need to be considered when assessing exposure (Hubal et al.,
13 2000). Behavioral patterns and preferred activities results in different exposures than for adults,
14 but also for children of different developmental stages (Chance and Harmsen, 1998).
15 The purpose of this section is to provide information on various activities, length of time
fl6 spent performing these activities, and locations and length of time spent by individuals within
17 those various microenvironments. This section summarizes data on how much time children
i 8 spend participating in various activities, in various microenvironments, and on the frequency of
19 performing various activities. These data cover a wide scope of activities and populations
20 arranged by age group, when available.
21 '.
22 9.2 ACTIVITY PATTERNS
23
The purpose of this section is to describe published time use studies that provide
24 information on time-activity patterns of children in the U.S. These studies are briefly described
25 below. For a detailed description of the studies, the reader is referred to the Exposure Factors
26 Handbook. Volume III (U.S. EPA. 1997).
27 Timmer et al. (1985) - How Children Use Time - Timmer et al. (1985) conducted a study
28 using the data obtained on children's time use from a 1981 -1982 Panel study. A total of 922
29 children participated in the survey. The children surveyed were between the ages of 3 and 17
years using a time diary and a standardized interview. The time diary involved children
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1 reporting their activities beginning at 12.00 a.m. the previous night; the duration and location of
2 each activity; the presence of another individual; and whether they were performing other
3 activities at the same time. The standardized interview administered to the children was to gather
4 information about their psychological, intellectual (using reading comprehension tests), and
5 emotional well-being; their hopes and goals; their family environment; and their attitudes and
6 beliefs.
7 The mean time spent performing major activities on weekdays and weekends by age and
8 sex, and type of day is presented in Table 9-1. On weekdays, children spend about 40 percent of
9 their time sleeping, 20 percent in school, and 10 percent eating, washing, dressing, and
10 performing other personal activities (Timmer et al., 1985). The data in Table 9-1 indicate that
11 girls spend more time than boys performing household work and personal care activities, and less
12 time playing sports. Also, children spend most of their free time watching television. Table 9-2
13 presents the mean time children spend during weekdays and weekends performing major
14 activities by five different age groups. Also, the significant effects of each variable (i.e., age,
15 sex) are shown in Table 9-2. Older children spend more time performing household and market
16 work, studying and watching television, and less time eating, sleeping, and playing. Timmer
17 et al. (1985) estimated that on the average, boys spend 19.4 hours a week watching television and
18 girls spend 17.8 hours per week performing the same activity.
19 A limitation associated with this study is that it was conducted in 1981 and there is a
20 potential that activity patterns in children may have changed significantly from 1981 to the
21 present. Thus, application of these data for current exposure assessment may bias exposure
22 assessment results.' Another limitation is that the data do not provide overall annual estimates of
23 children's time use since data were collected only during the time of the year when children
24 attend school and not during school vacation.
25 EPA estimated the total time indoors and outdoors using the Timmer data. Activities
26 performed indoors were assumed to include household work, personal care, eating, sleeping,
27 school, studying, attending church, watching television, and engaging in household
28 conversations. The average times spent in these indoor activities, and half the time spent in each
29 activity which could have occurred indoors or outdoors (i.e., market work, sports, hobbies, art
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1 activities, playing, reading, and other passive leisure) were summed. Table 9-3 summarizes the
2 results of this analysis by age groups and day of the week.
3 Robinson and Thomas (1991) - Time Spent in Activities, Locations, and
4 Microenvironments: A California-National Comparison - Robinson and Thomas (1991)
5 reviewed and compared data from the 1987-88 California Air Resources Board (CARB) time
6 activity study for California residents and from a similar 1985 national study, American's Use of
1 Time. Both studies used the diary approach data. Time use patterns were collected for
8 individuals 12 years and older. Telephone interviews based on the random-digit-dialing
9 procedure were conducted for approximately 1,762 respondents. Data categorized for children 0-
10 18 years old were not provided in the study. In addition, Robinson and Thomas (1991) defined a
11 set of 16 microenvironments based on the activity and location codes employed in both studies.
12 The mean duration of time spent for the total sample population, 12 years and older in three
13 location categories is presented in Table 9-4 for both studies. Based on the data shown in Table
14 9-4, respondents spent most of their time indoors, 1255 and 1279 minutes/day for the CARB and
15 national study, respectively.
6 Table 9-5 presents the mean duration of time and standard mean'error for the
17 16 microenvironments grouped by total sample population and gender. Also included is the
18 mean time spent for respondents ("Doers") who reported participating in each activity. Table 9-5
19 - shows that in both studies males spend more time in work locations, automobiles and other
20 vehicles, autoplaces (garages), and physical outdoor activities, outdoor sites. In contrast, females
21 spend more time cooking, engaging in other kitchen activities, performing other chores, and
22 shopping. The same trends also occur on a per participant basis.
23 Table 9-6 shows the mean time spent in various microenvironments grouped by type of
24 day (weekday or weekend) in both studies. Generally, respondents spent most of their time
25 during the weekends in restaurants/bars (CARB study), motor vehicles, outdoor activities,
26 social-cultural settings, leisure/communication activities, and sleeping. Microenvironmental
27 differences by age are presented in Table 9-7.
28 Limitations associated with the Robinson and Thomas (1991) study are that the CARB
29 survey was performed in California only. Therefore, if applied to other populations, the data set
may be biased. In addition, the studies were conducted in 1980s and may bias exposure
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1 assessment results when used for current exposure assessments. Another limitation is that time
2 distribution patterns were not provided for both studies and the data are based on short-term
3 studies.
4 Wiley et al. (1991) - Study of Children's Activity Patterns - The California children's
5 activity pattern survey design provided time estimates of children (under 12 years old) in various
6 activities and locations (microenvironments) on a typical day (Wiley et al., 1991). A total of
7 1,200 children were included in the study. The average time respondents spent during the 10
8 activity categories for all children are presented in Table 9-8. Also included in this table are the
9 detailed activity, including its code, with the highest mean duration of time; the percentage of
10 respondents who reported participating in any activity (percent doing); and the mean, median,
11 and maximum time duration for "doers." The dominant activity category, personal care (night
12 sleep being the highest contributor), had the highest time expenditure of 794 mins/day (13.2
13 hours/day). All respondents reported sleeping at night, resulting in a mean daily time per
14 participant of 794 mins/day spent sleeping. The activity category "don't know" had a duration of
15 about 2 mins/day and only 4 percent of the respondents reported missing activity time.
16 Table 9-9 presents the mean time spent in the 10 activity categories by age and gender.
17 Differences in activity patterns for boys and girls tended to be small. Table 9-10 presents the
18 mean time spent in the 10 activity categories grouped by seasons and California regions. There
19 were seasonal differences for 5 activity categories: personal care, educational activities,
20 social/entertainment, recreation, and communication/ passive leisure. Time expenditure
21 differences in various regions of the State were minimal for childcare, work-related activities,
22 shopping, personal care, education, social life, and recreation.
23 Table 9-11 presents the distribution of time across six location categories. The
24 participation rates (percent) of respondents, the mean, median, and maximum time for "doers."
25 The detailed location with the highest average time expenditure are also shown. The largest
26 amount of time spent was at home (1,078 minutes/day); 99 percent of respondents spent time at
27 home (1,086 minutes/ participant/day). Tables 9-12 and 9-13 show the average time spent in the
28 six locations grouped by age and gender, and season and region, respectively. There are age
29 differences in time expenditure in educational settings for boys and girls (Table 9-12). There are
30 no differences in time expenditure at the six locations by regions, and time spent in school
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1 decreased in the summer months compared to other seasons (Table 9-13). Table 9-14 shows the
2 average potential exposure time children spent in proximity to tobacco smoke, gasoline fumes,
3 and gas oven fumes grouped by age and gender. The sampled children spent more time closer to
4 ' tobacco smoke (77 mins/day) than gasoline fumes (2 mins/day) and gas oven fumes
5 (11 mins/day).
6 • EPA estimated the total time indoors and outdoors using the data from the Wiley study.
7 Activities performed indoors, were assumed to include household, childcare, personal needs and
8 care, education, and communication and passive leisure. The average times spent in these indoor
9 activities, and half the time spent in each activity which could have occurred indoors or outdoors
10 (i.e., work-related, goods/services, organizational activities, entertainment/social, don't know/not
11 coded) were summed. Table 9-15 summarizes the results of this analysis by age groups.
12 U.S. EPA (1992) - Dermal Exposure Assessment: Principles and Applications - U.S.
13 EPA (1992) addressed the variables of exposure lime, frequency, and duration needed to
14 calculate dermal exposure as related to activity. The reader is referred to the document for a
15 detailed discussion of these variables in relation to soil and water related activities. The
16 suggested values that can be used for dermal exposure are presented in Table 9-16. Limitations
17 of this study are that the values are based on small data sets and a limited number of studies.
18 These data are not representative for children in specific age group categories. An advantage is
19 that it presents default values for frequency and duration for use in exposure assessments when
20 specific data are not available.
21 Davis (1995). Soil Ingestion in Children with Pica (Final Report), EPA Cooperative
22 Agreement CR 816334-01 - In 1992, the Fred Hutchinson Cancer Research Center under
23 Cooperative Agreement with EPA conducted a study to estimate soil intake rates and collect
24 mouthing behavior data. Originally, the study was designed with two primary purposes: 1) to
25 describe and quantify the distribution of soil ingestion values in a group of children under the age
26 of five who exhibit behaviors that would be likely to result in the ingestion of larger than normal
27 amounts of soil; and 2) to assess and quantify the degree to which soil ingestion varies among
28 children according to season of the year (summer vs. winter).
29 The study was conducted during the first four months of 1992 and included 92 children
JO from the Tri-Cities area in Washington State. Children ranged in age from 10 to 60 months.
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1
2
^
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
These children were volunteers among a group selected through random digit dialing. The study
was conducted during a period of 7 days.
In addition to mouthing behavior data, information was collected about how long the
child spent indoors and outdoors each.day, and the general types of outdoor settings the child
played in. Figure 9-1 presents the distribution of the number of hours per day study children
spent indoors at home. Values were: the mean was 8.9 hours, the median was 9 hours, and the
range was 30 minutes to 1.5 hours. Figure 9-2 presents the distribution of the number of hours
per day study children spent indoors away from home. The mean number of hours spent indoors
away from home was 1.8, the median was 1, and the range was 0-15 hours. Figure 9-3 presents
the distribution of number of hours per day study children spent outdoors at home. The mean
number of hours spent outdoors at home was 1.4, the median was 45 minutes, and the range was
0-9 hours. Figure 9-4 presents the number of hours per day study children spent outdoors away
from home. The mean number of hours spent was approximately 30 minutes, the median was
less than 15 minutes, and the range was 0-8 hours.
Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The
National Human Activity Pattern Survey was conducted by the U.S. EPA (Tsang and Klepeis,
1996). It is the largest and most current human activity pattern survey available (Tsang and
Klepeis. 1996). Data were collected 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,
socioecoriomic, time/season, and other demographic factors to ensure that results were
representative of the U.S. population.
Tables 9-17 through 9-47 provide data from the NHAPS study. Tables 9-17 through 9-31
present data on the amount of time spent in selected activities and/or the corresponding
distribution data, when available.
Table 9-17 presents number of times taking a shower at specified daily frequencies
by number of respondents. The data shows that the majority of respondents take a
shower one or two times a day.
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1 • Table 9-18 provides time spent taking a shower and time spent in the shower room
2 immediately after showering. Most of the respondents spent 10-20 minutes taking a
3 shower and in the shower room after showering.
4
5 • Table 9-19 provides the percentile data for the same activity shown in Table 9-16.
6 . The 50th percentile value is 10 minutes for showering and 5 minutes for time spent
7 after showering was complete. The 90th percentile values vary across age groups and
8 range from 30-35 minutes and 10-15 minutes for time spent showering and in the
9 bathroom after showering, respectively.
10
11 • Table 9-20 presents total time (minutes) spent in the shower or bathtub and in the
12 bathroom immediately after a shower or bath. The majority of respondents spent
13 from 10-20 minutes in the shower or bathtub and approximately 10 minutes in the
14 bathroom afterwards.
15
16 • Table 9-21 presents the percentile data for the same activity shown in Table 9-18.
17 The 50th percentile values range from 15-20 minutes and 2-5 minutes for taking a
18 shower or bath and time spent in the bathroom after the bath, respectively.
19
20 • Table 9-22 provides a range of number of times washing the hands in a day. Most
21 respondents washed their hands 3-5 times a day.
22
L23 • Table 9-23 presents statistics data for the number of minutes per day spent working
14 or being near excessive dust in the air. For age groups 1-11 years old, the 50th
25 percentile data indicates that approximately 75 minutes/day is spent in air with
26 excessive dust.
27
28 • Table 9-24 provides data for the frequency of starting a motor vehicle in a garage or
29 carport and started with the garage door closed.
30
31 • Table 9-25 provides data for the range of minutes/day spent playing on sand, gravel.
32 dirt, or grass and playing when fill dirt was present.
*t -^
jj
34 • Table 9-26 provides the percentile data for the same activity shown in Table 9-25.
35
36 • Table 9-27 presents data for time (minutes/day) spent playing on the grass by numbei
37 of respondents. The majority of respondents spent more than 120 minutes/day in this
38 activity.
39
40 • Table 9-28 presents percentile data for the same activity shown in Table 9-27. The
41 50th percentile rate is 60 minutes/day for all age groups.
42
43 • Table 9-29 provides number of times/month swimming in a freshwater swimming
44 pool by number of respondents. The majority of respondents swim in freshwater
f-5 pools 1 or 2 times/month.
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1
2
*>
4
5
6
7
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
"i "*
jj
34
35
36
37
38
39
40
41
42
• Table 9-30 provides percentile data for the same activity shown in Table 9-29. The
50th percentile values are 42.5 minutes/month for age group 1-4 years and 60
minutes/month for age gropus 5-11 and 12-17 years.
• Table 9-31 presents the range of the average amount of time (minutes/month)
actually spent in the water by swimmers. The majority of swimmers spent an average
of 50-60 minutes/month in the water.
Tables 9-32 through 9-44 provide statistics for 24-hour cumulative time (minimum,
mean, maximum) spent in selected activities. The minimum is the minimum number of minutes
spent in the activity. The mean is the mean 24-hour cumulative number of minutes spent by
doers. The maximum is the maximum number of minutes spent in the activity. The percentiles
are the percentage of doers bejow or equal to the given number of minutes.
• Table 9-32 provides number of minutes spent playing indoors and playing outdoors.
• Table 9-33 provides number of minutes spent sleeping/napping in a day.
• Table 9-34 presents data for time spent attending full-time school.
• Table 9-35 provides data for time spent in active sports and for time spent in
sports/exercise.
• Table 9-36 presents data for time spent in outdoor recreation and for walking.
• Table 9-37 provides data for time spent bathing.
• Table 9-38 presents statistics for minutes eating or drinking.
• Table 9-39 provides data for time spent indoors at school and in a restaurant.
• Table 9-40 provides information for time spent outdoors on school
; grounds/playgrounds and at a pool/river/lake.
• Table 9-41 provides information on time spent at home in the kitchen, bathroom, and
bedroom, and indoors in a residence (all rooms).
• Table 9-42 presents data for time spent traveling inside a vehicle.
• Table 9-43 provides data for time spent outdoors (outside the residence) and outdoor
other than near a residence such as parks, golf courses, or farms.
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1 • Table 9-44 provides information for time spent in malls, grocery stores, and other
2 stores.
3
4 • Table 9-45 presents data for minutes spent with smokers present.
5
6 • Table 9-46 provides data for time (minutes) spent smoking by number of
7 respondents.
8
9 • Table 9-47 provides percentile data for the same activity shown in Table 9-44.
10
11
12 • Advantages of the NHAPS dataset are that it is representative of the U.S. population and
13 it has been adjusted to be balanced geographically, seasonally, and for day/time. Also, it is
14 representative of all ages, gender, and is race specific. A disadvantage of the study is that for
15 ages 1-17, the "N" is small for most activities. In addition, means cannot be calculated for time
16 spent over 60,120, and 181 minutes in selected activities. Therefore, actual time spent at the
17 high end of the distribution for these activities cannot be captured.
18 Funk et al. (1998) - Quantifying the Distribution of Inhalation Exposure in Human
19 Populations - Funk et al. (1997) used the data from the California Air Resources Board (CARB)
study to determine distributions of exposure time by tracking the time spent participating in daily
21 at home and at school activities for male and female children and adolescents. CARB performed
22 two studies from 1987 to 1990; the first was focused on adults and adolescents (12-17 years old),
23 while the second focused on children (6-11 years old) (Funk et al., 1998). The targeted groups
24 were noninstitutiorialized English speaking Califomians with a telephone in their residence.
25 Individuals were contacted by telephone and asked to account for every minute within the
26 previous 24 hours, including the amount of time spent on an activity and the location of the
27 activity. The surveys varied from day to day and season to season.
28 All the activities that were documented were separated into two groups, "at home" (any
29 activity at principal residence), or "away." Each activity was assigned to one of three ventilation
30 levels (Ve)? low. moderate, or high. Resting activities were placed in the low Ve, and moderate
31 exertion activities were assigned to moderate Ve. Activities requiring high levels of physical
32 exertion were placed in the high Ve group. Ambiguous activities that were encountered were
33 assigned to moderate ventilation levels. Among the adolescents and children studied, means
were determined for the aggregate age groups, as shown in Table 9-48.
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1 Several statistical methods, such as Chi-quare, Kolmogorov,-Smirnov, and Anderson-
2 Darling, were used to determine whether the time spent in an activity group had a known
3 distribution (Funk et al., 1998). All the activities that were identified in the C ARB study were
4 assigned to the three ventilation levels. Most of the activities performed by children were low to
5 moderate Ve as shown in Table 9-49.
6 The aggregate time periods spent at home in each activity are shown in Table 9-50.
7 Aggregate time spent at home performing different activities was compared between genders.
8 There were no significant differences between adolescent male and females in any of the activity
9 groups (Funk et al., 1998) (Table 9-51). In children ages 6-11 years there were differences found
10 between gender and age at the low ventilation levels. In the moderate ventilation level there
11 were significant differences between two age groups (6-8 years, and 9-11 years) and gender
12 (Funk etal., 1998) (Table 9-52).
13 Large proportions of the respondents in the study did not participate in high ventilation
14 activities; discrete distributions were used to characterize high ventilation activity groups (Funk
15 et al., 1998). Lognormal distribution best described the time spent by children at high ventilation
16 levels.
17 Hubal et al. (2000) - Children's Exposure Assessment: A Review of Factors Influencing
18 Children's Exposure, and the Data Available to Characterize and Assess that Exposure - Hubal
19 et al. (2000) reviewed available data to characterize and assess environmental exposures to
20 children. As part of that review, available activity patterns data were evaluated. Hubal reviewed
21 the EPA National Exposure Research Laboratory's Consolidated Human Activity Database
22 (CHAD), which contains data from several studies on human activities. For children and
23 adolescents younger than 18 years. CHAD contains 4.300 person-days of information and 3.009
24 person-days of microactivity data for 2,640 children less than 12 years old (Hubal et al., 2000)
25 (Table 9-53). Specific examples of the type of microactivity data available in CHAD for
26 children are shown in Tables 9-54 and 9-55. The number of hours spent in various
27 microenvironments are shown in Table 9-54 and time spent in various activities indoors at home
28 in Table 9-55.
29 The authors noted that CHAD contains approximately "140 activity codes and 110
30 location codes, but the data generally are not available for all activity locations for any single
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1 respondent. In fact, not all of the codes were used for most of the studies. Even though many
2 codes are used in macroactivity studies, many of the activity codes do not adequately capture the
3 richness of what children actually do. They are much too broadly defined and ignore many
4 child-oriented behaviors. Thus, there is a need for more and better-focused research into
5 children's activities." CHAD is available on the EPA Intranet (Hubal et al., 2000).
6
7 9.3 RECOMMENDATIONS
8 Assessors are commonly interested in a number of specific types of time use data
9 including time/frequencies for bathing, showering, gardening, residence time, indoor versus
10 outdoor time, swimming, occupational tenure, and population mobility. Recommendations for
11 - each of these are discussed below. The confidence in the recommendations for activity patterns
12 is presented in Table 9-56.
13
14 9.3.1 Recommendations for Activity Patterns
15 This chapter presents several studies that provide data on activity patterns. Table 9-57
6 summarizes information on the various studies. Recommendations for selected activities
17 commonly used in exposure assessments and known to increase exposure to certain chemicals
18 are provided to follow. These activities are time spent indoors versus outdoors, showering,
19 swimming, residential time spent indoors and outdoors, time spent playing on sand and gravel,
20 and time spent playing on grass.
21 Time Spent Indoors Versus Outdoors - Assessors often require knowledge of time
22 individuals spend indoors versus outdoors. Ideally, this issue would be addressed on a site-
23 specific basis since the times are likely to vary considerably depending on the climate, residential
24 setting (i.e., rural versus urban), personal traits (i.e., age. health) and personal habits.
25 Activities can vary significantly with differences in age. Table 9-58 summarizes the
26 studies that present information on time indoors and outdoors. Of these studies, Timmer et al.
27 (1985) in addition to being a national study, presents the data for a more comprehensive set of
28 age groupings for children. Timmer et al. (1985) presented data on time spent in various
29 activities for boys and girls ages 3-17 years. This national study focused on activities performed
indoors such as household work, personal care, eating, sleeping, school, studying, attending
June 2000 9-11 DRAFT-DO NOT QUOTE OR CITE
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1 church, watching television, and engaging in household conversations. The average times spent
2 in each activity, and half the times spent in each activity which could have occurred indoors or
3 outdoors, were summed. The results are presented in Table 9-59 For various age groups.
4 Although there is good agreement between the Robinson Thomas 1991 and Timmer 1985
5 studies, the recommendations are based on the Timmer study because it provides data for
6 younger children. The recommendations are based on the. Timmer data shown in Table 9-58.
7 Showering - The recommended shower frequency of one shower per day is based on the
8 NHAPS data summarized in Table 9-17. This table showed that 341 of the 451 total participants
9 indicated taking at least one shower the previous day.
10 Recommendations for showering duration are based on the study of Tsang and Klepeis
11 (1996). A recommended value for average showering time is 10 minutes.(Table 9-18) based on
12 professional judgement.
13 Swimming - Data for swimming frequency is taken from the NHAPS Study (Tsang and
14 Klepeis, 1996). Of the 653 participants, who answered yes to the question "in the past month,
15 did you swim in a freshwater poo!?", 241 were ages 1-17 years. The results to this question are
16 summarized in Table 9-29. The recorded number of times respondents swam in the past month
17 ranged from 1 to 60 with the greatest number of respondents reporting they swam one time per
18 month. Thus, the recommended swimming frequency is one event/ month. The recommended
19 swimming duration, 60 minutes per swimming event, is based on the NHAPS distribution shown
20 on Table 9-30. Sixty minutes is based on an average of the 50th percentile values. The 90th
21 percentile value is 180 minutes per swimming event (based on one event/month); and the 99th
22 percentile value is 181 minutes. This value (181) indicates that more than 180 minutes were
23 spent.
24 Residential Time Spent Indoors and Outdoors - The recommendations for time spent
25 indoors at one's residence for children 1-17 years old is 18 hours/day. This is based on the
26 NHAPS data summarized in Table 9-41 for number of minutes spent indoors in a residence (all
27 rooms). The average of the 50th percentile values for all age groups is 1.061 minutes per day
28 (17.7 hours/day); and a 90th percentile value of 1,361 minutes per day (22.6 hours/day).
29 The recommended value for time spent outdoors outside one's residence is 2 hours per
30 day based on NHAPS data shown on Table 9-43 for time spent outdoors (outside the residence).
June 2000 9-12 DRAFT-DO NOT QUOTE OR CITE
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The 50th percentile values range from 100-150 minutes/day and the 90th percentile values range
from 300-400 minutes/day as shown in Table 9-43.
Playing on Sand or Gravel, and on Grass - The recommended value for time spent
playing on sand or gravel is 60 minutes/day. This value is based on NHAPS data shown in Table
9-25. This recommendation is based on professional judgement. The data in Table 9-25, show
that the majority of respondents are captured in the 0-0 minutes/day category. However, for the
other time categories, the majority of respondents are captured in the 50-60 minutes/day
category.
9 The recommended value for time spent playing on grass is 60 minutes/day based on the
0 50th percentile data shown in Table 9-28 and the 50-60 minutes/day category data in Table 9-27.
.1
1
>2
•"i
4
5
6
7
8 category.
10
11
12 9.3.2 Summary of Recommended Activity Factors
Table 9-59 includes a summation of the recommended activity pattern factors presented
in this section and the studies which provided data on the specific activities. The type of
activities include indoor activities, outdoor activities, taking a shower, swimming, time spent
playing on sand or gravel, and time spent playing on grass.
13
1 4
15
June 2000 9-13 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
9.4 REFERENCES FOR CHAPTER 9
Chance, W.G.; Harmsen, E. (1998) Children are different: environmental contaminants and children's health.
Canadian Journal of Public Health, Vol. 89, Supplement, pp. 59-513.
Davis, S. (1995) Soil ingestion in children with pica. Final Report. EPA Cooperative Agreement. CR816334.01.
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 Analysis. 18(l):47-56.
Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy, T.R.; Berry, M.R.; Rigas, ML.; 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. Research Triangle Park, NC: U.S. Environmental Protection
Agency, National Exposure Research Laboratory.
Robinson, J.P; Thomas. J. (1991) Time spent in activities, locations, and microenvironments: 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, F.P.; eds. Time,
goods, and well-being. Ann Arbor, MI: University of Michigan, Survey Research Center, Institute for Social
Research, pp. 353-380.
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed
Martin, Contract No. 68-W6-001, Delivery Order No. 13.
U.S. EPA. (1992) Dermal exposure assessment: principles and applications. Washington, DC: Office of Health
and Environmental Assessment. EPA No. 600/8-91-011B. Interim Report.
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.
Wiley, J.A.; Robinson, J.P.; Cheng, Y.: Piazza. T.: Stork, L.: Plasden, K. (1991) Study of children's activity
patterns. California Environmental Protection Agency, Air Resources Board Research Division. Sacramento,
CA.
June 2000
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Table 9-1. Mean Time Spent (minutes) Performing Major Activities Grouped by Age. Sex and Type of Day
>3
4
5
6
7
S
9
10
11
12
13
14
15
16
17
18
I19
lo
21
22
23
24
25
26
27
28
29
30
31
Activity-
Age (3-1 1 years)
Duration of Time (mins/day)
Weekdays
Market Work
Household Work
Personal Care
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoors
Hobbies
An Activities
Playing
TV
Reading
Household Conversations
Other Passive Leisure
NA1
Percent of Time Accounted for
bv Activities Above
a NA = Unknown
Source: Timmeretal.. 1985.
Boys
16
17
43
81
584
252
14
7
16
'25
10
3
4
137
117
9
10
9
22
94%
Girls
0
21
44
78
590
259
19
4
9
12
7
\
4
115
128
7
It
14
25
92%
Weekends
Boys
(n=l 18)
7
32
42
78
625
-
4
53
23
33
30
3
4
177
181
12
14
16
20
93%
Girls
(n-111)
4
43
50
84
619
-
9
61
37
23
23
4
4
166
122
10
9
17
29
89%
Age (12- 17 years)
Duration of Time (mins/day)
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%
32
June 2000
9-15
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Table 9-2
Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for Five Different Age Groups
Time Duration (mins)
Weekday
Age (years)
Activities
Market Work
Personal Care
Household Work
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoor activities
Hobbies
Art Activities
Other Passive Leisure
Playing
TV
Reading
Being read to
NA
3-5
-
41
14
82
630
137
2
4
14
5
4
0
5
9
218
111
5
2
30
6-8
14
49
15
81
595
292
8
9
15
24
9
2
4
1
111
99
5
2
14
9-11
8
40
IS
73
548
315
29
9
10
21
8
2
3
2
65
146
9
0
23
12-14
14
56
27
69
473
344
33
9
21
40 -
7
4
3
6
31
142
'10
0
25
Weekend
15-17
28
60
34
67
499
314
* i
jj
3
20
46
11
6
12
4
14
108
12
0
7
3-5
-
47
17
81
634
-
1
55
10
3
8
1
4
6
267
122
4
3
52
6-8 9-11
4 10
45 44
27 51
80 78
641 596
_
2 12
56 53
8 13
30 42
23 39
5 3
4 4
10 7
180 92
136 185
9 10
2 0
7 14
12-14
29
60
72
68
604
-
15
32
22
51
25
8
7
10
35
169
10
0
4
15-17
48
51
.60
65
562
-
30
37
56
37
26
3
10
18
21
157
IB
0
9
Significant
Effects*
A.S.AxS (F>M)
ATS. AxS (F>M)
A
A
A
A
A (Weekend only)
A.S F)
A
A.S (M>F)
A.S. AxS (M>F)
A
A
A
a Effects are significant for weekdays and weekends, unless otherwise specified A = age effect. P<0.05. for both weekdays and weekend
activities: S - sex effect P<0.05. F>M. M>F = females spend more time than males, or vice versa: and AxS » age by sex interaction.
P<0-05.
Source: Timmer et al.. 1985.
June 2000
9-16
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1
2
•t
4
5
6
7
8
9
Table 9-3. Mean Time Spent Indoors
Age Group
(yrs)
3-5
6-8
9-11
12-14
15-17
Time Indoors
Weekday
(hrs/day)
1.94
20.7
20.8
20.7
19.9
and Outdoors Grouped by Age and Day of the Week
Time Indoors
Weekend
(hrs/day)
18.9
18.6
18.6
18.5
17.9
Time Outdoors
Weekday
(hrs/day)
2.5
1.8
1.3
1.6
1.4
Time Outdoors
Weekend
< hrs/day)
3.1
2.5
2.3
1.9
2.3
10
11 Source: Adapted from Timmer et al. (1985).
June 2000 9-17 DRAFT-DO NOT QUOTE OR CITE
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1
2
Table 9-4. Mean Time Spent at Three Locations for both CARB and
National Studies (ages 12 years and older)
4
5
8
9
10
11
12
13
14
15
16
Location Category
Indoor
Outdoor
In-Vehicle
Total Time Spent
CARB
(n = 1762)b
1255'
86*
9§f
1440
Mean duration (mins/day)
National
S.E.1 (n = 2762)» S.E.
28 1279e 21
5 74d 4
4 ST 2
1440
3 S.E. = Standard Error of Mean
11 Weiehted Number - National samnle oonulation was weighted to obtain a ratio of 46.5 males and 53.5 females, in eaua)
proportion for each day of the week, and for each quarter of the year.
c Difference between the mean values for the CARB and national studies is not statistically significant.
* Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level.
Source: Robinson and Thomas. 1991.
June 2000
9-18
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1
2
3
4
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
^6
27
28
29
30
31
32
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 9-5. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total Population
and Gender (12 years and over) in the National and CARfi Data
National Data
Mean Duration (mins/day) (standard error)*
M icroenvironment
Autoplaces
Restaurant/bar
in-vehicle
In-Vehicle/other
Physical/outdoors
Physical/indoors
Work/study-residence
Work/study-other
Cooking
Other activities/kitchen
Chores/child
Shop/errand
Other/outdoors
Social/cultural
Leisure -eat/indoors
Sieep/'mdoors
N = I284b
Male
5(1)
22(2)
92(3)
1(1)
24(3)
11(1)
17(2)
221 (10)
14(1)
54(3)
88(3)
23(2)
70(6)
75(4)
235 (8)
49! (14)
"Doer""
Male
90
73
99
166
139
84
153
429
35
69
89
56
131
118
241
492
N=1478b
Female
1(0)
20(2)
82(3)
1(0)
11(2)
6(!)
15(2)
142 (7)
52(2)
90(4)
153(5)
38(2)
43(4)
75 (4)
215(7)
496(11)
"Doer" N = 2762b
Female Total
35
79
94
69 '
101
57
150
384
67
102
154
74
97
110
224
497
3(0)
21(1)
87 (2)
1(0)
17(2)
8(1)
16(1)
179(6)
34(1)
73(2)
12393)
31(1)
56(4)
73(3)
224 (5)
494 (9)
"Doer"
Total
66
77
97
91
i35
74
142
390
57
88
124
67
120
118
232
495
CARB Data
Mean Duration (mins/day) (standard error)*
Microenvironmem
Autoplaces
Restaurant/bar
In- vehicle
In-Vehicle/other
Physical/outdoors
Physical/indoors
Work/study-residence
. Work/study-other
Cooking
Other activities/kitchen
Chores/child
Shop/errand
Other/outdoors
Social/cultural
Leisure-eat/indoors
Sleep/indoors
N = 867b
Male
31(8)
45(4)
. 105(7)
4(1)
25(3)
8(1)
14(3)
213(14)
12(1)
38(3)
66(4)
21(3)
95(9)
47(4)
223(10)
492(17)
"Doer"
Male
142
106
119
79
131
63
126
398
43
65
75
61
153
112
240
499
N = 895"
Female
9(2)
28 (3)
85(4)
3(2)
8(1)
5(1)
M(2)
156(11)
42(2)
60(4)
134(6)
41(3)
44(4)
59 (5)
251(10)
504(15)
"Doer" N=1762b
Female Total
50
86
100
106
86
70
120
383
65
82
140
78
82
114
263
506
20(4)
36(3)
95(4)
3(1)
17(2)
7(1)
13(2)
184(9)
27(1)
49(2)
100(4)
31(2)
69(5)
53(3)
237 (7)
498(12)
"Doer"
Total
108
102
111
94
107
68
131
450
55
74
109
70
117
112
250
501
a Standard error of the mean
b Weighted number
c Doer = Respondents who reported participating in each activity/location spent in microenvironments.
Source: Robinson and Thomas, 1991.
June 2000
9-19
DRAFT-DO NOT QUOTE OR CITE
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1
2
*>
4
5
6
7
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
"* *»
jj
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Table 9-6. Mean Time Spent (minutes/day) in Various Microenvironments by Type
of Day for the California and National Surveys
(sample population ages 12 years and older)
Weekday
Microenvironment
1 Autoplaces
2 Restaurant/Bar
' 3 In- Vehicle/Internal Combustion
4 In-Vehicle/Other
5 Physical/Outdoors
6 Physical/Indoors
7 Work/Study-Residence
8 Work/Study-Other
9 Cooking
10 Other Activities/Kitchen
1 1 Chores/Child
12 Shop/Errand ,
13 Other/Outdoors
14 Social/Cultural
15 Leisure-Eat/Indoors
56 Sleep/Indoors
Mean Duration (standard error)1
CARS
(n=I259)e
21(5)
29(3)
.90(5)
3(1)
14(2)
7(!)
14(2)
228 ( 1 1 )
27(2)
51 (3)
99(5)
30(2)
67(6)
42(3)
230 (9)
490(14)
(m ins/day)
NAT
(n=1973)c
3(1)
, 20 (2)
85(2)
1(0)
15(2)
8(1)
16(2)
225 (8)
35(2)
73(3)
124(4)
30(2)
51(4)
62(3)
211(6)
481(10)
Mean Duration for
(mins/day)
CARB
108
83
104
71
106
64
116
401
58
76
108
67
117
99
244
495
"Doer"*
NAT
73
73
95
116
118
68
147
415
57
87
125
63
107
101
218
483
Weekend
Microenvironment
1 Autoplaces
2 Restaurant/Bar
3 In- Vehicle/Internal Combustion
4 In- Vehicle/Other
5 Physical/Outdoors
6 Physical/indoors
7 Worfc/Study-Residence
8 Work/Study-Other
9 Cooking
10 Other Activities/Kitchen
1 1 Chores/Child •
12 Shop/Errand
13 Other/Outdoors
14 Social/Cultural
15 Leisure-Eat/Indoors
! 6 Sleep/Indoors
Mean Duration (standard error)*
CARB
-------
1
2
Table 9-7. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups for the National and California Surveys
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
23
24
25
26
27
28
29
30
31
32
•^ ••»
34
35
36
37
38
39
40
41
42
National Data
Microenvironment
Autoplaces
Restaurant/bar
In-vehicle/intemal 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
M i croenvironmem
Auioplaces
Restaurant/bar
In-vehicle/intemal combustion
In-vehicie/other
Physical/outdoors
Physical/indoors
Work/study-residence
Work/study-othcr
Cooking
Other activities/kitchen
Chores/child
Shop/errands
Other/outdoors
Social/cultural
Leisure-eat/indoors
Sleep/indoors
Mean Duration (Standard Error)*
Aae 12-17 years
N=340*
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)
"Doer"'
73
60
88
12
130
87
82
354
40
64
92
• 68
129
120
242
551
CARS
Age 18-24vears
N=340
7(2)
28(3)
103 (8)
KD
17(4)
8(2)
19(6)
207 (20)
18(2)
42(3)
124 (9)
31(4)
34(4)
100(12)
181 (11)
511(26)
Data
"Doer"
137
70
109
160
no-
76
185
391
39
55
125
65
84
141
189
512
Mean Duration (Standard Error)"
Aae !2-l7vears
N=183"
16(8)
16(4)
78(11)
1(0)
32(7)
20(4)
25 (5)
196 (30)
3d)
31 (4)
72(11)
14(3)-
58(8)
63(14)
260 (27)
557 <44)
"Doer"'
124
44
89
19
110
65
76
339
19
51
77
50
78
109
270
560
Ase 1 8-24 vears
N-250
16(4)
40(8)
111(13)
3(1)
13(3)
5(2)
30(11)
201 (24)
'14 (2)
31 (5)
79(8)
35(7)
80(15)
65(10)
211 (19)
506 (30)
"Doer"
71
98
122
60
88
77
161
344
40
55
85
71
130
110
234
510
' Standard error.
11 All N's are weighted number.
Doer= Respondents who reported participating in each activity/location spent in microenvironmems.
Source: Robinson and Thomas. 1991.
June 2000
9-21
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2
**
4
6
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Table 9-8. Mean Time (minutes/day) Children Ages 12 Years and Under Spent in Ten Major
Activity Categories for All Respondents
Activitv Category
Work-related"
Household
Childcare
Goods/Services
Personal Needs and Care'
Education''
Organizational Activities
Entertain/Social
Recreation
Communication/Passive
Leisure
Don't know/Not coded
All Activities'
Mean
Duration
(mins/day)
10
53
<1
21
794
110
4
15
239
192
2
1441
Mean Median Maximum
Duration Duration Duration
% forDoersb for Doer for Doers
Doins (mins/dav) (mins/dav) (mins/dav)
25
86
<1
26
100
35
4
17
92
93
4
39
61
83
81
794
316
111
87
260
205
41
30
40
30
60
770
335
105
60
240
180
15
405
602
290
450
1440
790
435
490
835
898
600
Detailed Activity with
Highest Avg. Minutes
(code)
Eating at work/school/daycare (06)
Travel to household (199)
Other child care (27)
Errands (38)
Night Sleep (45)
School classes (50)
Anend meetings (60)
Visiting with others (75)
Games (87)
TV use (91)
—
° Includes eating at school or daycare. an activity not grouped under the "education activities" (codes 50-59. 549).
b "Doers" indicate the respondents who repotted participating in each activity category.
* Personal care includes night sleepand daytime naps, eating, travel for personal care.
d Education includes student and other classes, homework, library, travel for education.
' Column total may not sum to 1440 due to rounding error
Source: Wiley eta!.. 1991.
June 2000
9-22
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Table 9-9. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and Gender
F4
6
8
9
10
11
12
13
14
15
16
12
19
20
r
23
24
25
26
27
Mean Duration (minutes/day)
Activity
Category
Work-related
Household
Chiidcare
Goods/Services
Persona! Needs and Care*
Education11
Organizational Activities
Entertainment/Social
Recreation
Communication/Passive
Leisure
Don't know/Not coded
At! Activities'
Sample Sizes
Unweighted N's
0-2 yrs
4
33
0
20
914
60
1
3
217
187
1
1440
172
3-5 yrs
9
45
0
22
799
67
3
15
311
166
4
1441
151
Boys
6-8 yrs
14
55
0
19
736
171
7
5
236
195
1
1439
145
9-11
yrs
12
65
1
14
690
138
6
34
229
250
1
1440
156
0-11
yrs
10
48
-------
1
"*
4
6
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
Table 9-10. Mean Time Children Ages 12 Years and Under Spent in Ten Major Activity Categories
Grouped by Seasons and Regions
Mean Duration (minutes/day)
Activity Category
Work-related
Household
Childcare
Goods/Services
Personal Needs and
Care"
Education*
Organizational
Activities
Entertainment/Social
Recreation
Communication/Pass
ive Leisure
Don't know/Not
coded .
All Activities"
Sample Sizes
(Unweighted)
Winter
(Jan-Mar)
10
47
<1
19
799
124
3
14
221
203
<]
1442
318
Spring
(Apr-June)
10
58
1
17
774
137
5
12
243
180
2
1439
204
Season
Summer
(July-
Sept)
6
53
-------
1
2
•"i
•j
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
• ^24
^^^H) C
~6
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Table 9-1 1. Mean Time Children Ages 12 Years and Under Spent in Six Major Location Categories for All Respondents (minutes/day)
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
Source: Wiley etal.. 1991.
Mean Mean Median Maximum
Duration % Duration Duration Duration for Detailed Location with Highest
(mins) Doing for Doers for Doers Doers Avg. Time
(mins) (mins) (mins)
1.078 99 1.086 1.110 1.440 Home -bedroom
109 33 330 325 1.260 School or day care facility
80 32 251 144 1.440 Friend's/other's house - bedroom
24 35 69 50 475 Shopping mall
69 83 83 60 I. Ill Traveling in car
79 57 139 105 1.440 Park, playground
<1 1 37 30 90
1.440
Table 9-12. Mean Time Children Spent in Six Location Categories Grouped by Age and Gender
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
(Unweishied)
Mean Duration (minutes/day)
Boys Girls
All All
0-2 yrs ' 3-5 yrs 6-8 yrs 9-llyrs Boys 0-2 yrs 3-5 yrs 6-8 yrs 9-llyrs Girls
1.157 1.134 1.044 1.020 1.094 1.151 1.099 1.021 968 1.061
86 88 144 120 108 59 102 133 149 111
67 73 77 109 80 56 47 125 102 80
21 25 22 15 21 23 35 27 26 28 .
54 62 61 62 59 76 88 53 93 79
54 58 92 114 77 73 68 8! 102 81
<1
-------
2
3
'4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
31
32
33
34
36
37
38
•Table 9-13. Mean Time Children Spent in Six Location Categories Grouped by Season and Region
Season
Location Category Winter Spring Summer
(Jan-Mar) (Apr-June) (July-Sept)
Home 1.091 1.042 • 1.097
School/Childcare 119 141 52
Friend's/Other's House 69 75 108
Stores. Restaurants. 22 21 30
Shopping Places
In-transit ' 75 75 60
Other Locations 63 85 93
Don't Know/Not <1 <1 . <1
Coded
All Locations" 1.439 - 1.439 1.440
Sample Sizes 318 204 -407
(Unweighted N's)
' The column totals mav not sum to 1.440 due to rounding error.
Source: Wiley eta! ..1991.
"•
Mean Duration (minutes/day)
Region of California
Fall All So. Bay Rest of
(Oct-Dec) Seasons Coast Area State
L08I 1.078 1,078 1.078 1.078
124 109 113 103 108
69 80 73 86 86
24 24 26 23 23
65 69 71 73 63
76 79 79 76 81
<]
-------
40
35
3V
Number of 25
Child-Days ,ft
15
. 3, 35-4 45 5 -iS S KS .T.-13 8 ai. S ;3>10 SOS 11.1U-111XS13 1iS W >14
Hours Indoors At Home
Figure 9-1. Distribution of the Number of Hours per Day Study Children Spent Indoors at Home
Source: Davis 1995.
June 2000
9-27
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140
"•" • 120
Number of 10&
Child-pays
60
40
a I
- 0 0.5 1 1.5-2 2JS 3 3.5 4 4JS S 5.5 6 i.& 7 7.5 8--->8
• Hours. Indoors Away From Home ,
Figure 9-2. Distribution of the Number of Hours per Day Study Children Spent Indoors Away from Home
Source: Davis 1995.
June 2000
9-28
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Number of
Child-Days
140r
120
too
80
40
20i
fl
Hours Outdoors At Home..
Figure 9-3. Distribution of the Number of Hours per Day Study Children Spent Outdoors at Home
Source: Davis 1995.
June 2000
9-29
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Number of
Child-Bays
200"
150-
10G
soi
0 0.5 1 1.5 2 2.5 3 3.5 4 >4
Hours Outdoors Away From Home
Figure 9-4. Distribution of the Number of Hours per Day Study Children Spent Outdoors Away at Home
Source: Davis 1995.
June 2000
9-30
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1 Table 9-15. Mean Time Spent Indoors and Outdoors Grouped by Age
2
=====^=_==^===s==============
4 Age Groups Time Indoors Time Outdoors
(hours/day) (hours/day)
5 ' 0-2 20 4
6 3-5 18.8 5.2
7 , 6-8 19.7 4.4
8 9-11 19.9 4.1
9
10
11
June 2000 9-31 DRAFT-DO NOT QUOTE OR CITE
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I
2
*t
4
6
7
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
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
Table 9-16. Range of Recommended Defaults for Dermal Exposure Factors
Water Contact
Bathing
Event time
and
frequency*
Exposure
duration
Central
1 0 min/event
1 event/day
350 days/yr
9 years
Upper
15 min/event
1 event/day
350 days/yr
30 years
Soil Contact
Swimming
Central
0.5 hr/event
1 event/day
5 days/yr
9 years
Upper
1 .0 hr/event
1 event/day
1 50 days/yr
30 years
Centra!
40 events/yr
9 years
Upper
350 events/yr
30 years
1 Bathing event time is presented to be representative of baths as well as showers.
Source: U.S. EPA 1992.
Table 9-! 7. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents
Times/Day
Age (years)
1-4
5-11
12-17
Total N 0
41 *
140 *
270 *
1
30
112
199
2
9
26
65
3 4.
1 * •
I *
6 *
5 8 10 11:1-0+ DK
* * * * |
* # * * j
*****
Note: * Signifies missing data: Dk= don't know: N - sample size.
Source: Tsang and Klepeis. 1996
Table 9-18. Time (minutes) Spent Taking a Shower and Spent in the Shower Room
After Taking a Shower by the Number of Respondents
Minutes/Shower
Total N
*_*
0-10
10-20
20-30
30-40
40-50
50-60
60-61
Times (minutes) Spent Taking Showers by the Number of Respondents
Age
i-4
5-11
12-17
41
140
270
1
1
2
13
60
94
14
52
104
10
IS
40
1
3
13
*
2
9
2
4
7
*
S
1
Time (minutes) Spent in ihe Shower Room Immediately After Showering by the Number of Respondents
Age (years)
M
5-11
1*7 |7
41
140
'70
*
3
1
5
9
17
31
110
•>06
3
14
29
I
3
10
*
*
3
1
*
2
I
1
NOTE: * - Missing data; DK = don't know: N = sample size: Refused = Refused to answer. A value of 61 for number of minutes signifies tnat
more than 60 minutes were spent.
Source: Tsang and Klepeis. 1996.
June 2000
9-32
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1
2
I
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
S
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Table 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately After Showering
Category
Pereentiles
Total
Populate Group N , 2 5 ,0 25 50 75 91 95 98
99
100
Number of Minutes Spent Taking a Shower (minutes/shower)
Age (years)
Age (years)
Age (years)
1^ 40 5 5 5 5 5 10 17.5 30 50 60
5-11 139 3 4 5 5 10 15 20 30 40 60
12-17 268 5 5 5 7 10 15 25 35 45 60
60
60
60
60
60
61
Number of Minutes Spent in the Shower Room Immediately After Showering (minutes/shower)
Age (years)
Age (years)
Age (years)
1-4 41 0 0 0 0 1 5 10 15 20 45
5-11 137 0 0 0 1 2 5 10 15 20 30
12-17 2619 0001 3 5 10 20 30 40
NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of
number of minutes signifies that more than 60 minutes were spent.
Source: Tsang and Kiepeis.1996
Table 9-20. Total Time Spent Altogether in the Shower or Bathtub and Time Spent
in the Bathroom Immediately After by Number of Respondents
Minutes/Bath
Total *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 90- 100-
N iOO 110
45
30
52
61 for
110-
120
45
60
61
121-
121
Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents
Age (years)
1-4
5-11
12-17
198 * » 35 84 50 2 13 7 1 1 1
265 2 64 107 66 3 7 7 2 2 1 1
239 78 96 46 5 5 8 * ... »
4
2
1
*
1
*
Time Spent in the Bathroom Immediately Following a Shower or Bath by the Number of Respondents
Age (years)
1-4
5-1 i
12-17
198 2 59 123 12 • 1 1 *
265 : 33 198 23 3 1 * 1 ' * * *
239 1 17 165 34 16 1 3 2 * * *
*
1
*
*
*
*
Note: * Signifies missing data. DK = respondents answered "don't know". Refused = respondents refused to answer. N = doer sample size in
specified range of number of minutes spent. A value of" 121" for number of minutes signifies that more than 120 minutes %vere spent.
Source: Tsang and Klcpeis. 1996
June 2000
9-33
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1
2
*»
4
6
7
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
,-, ,N|
.?:>
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Table 9-2 1 . Total Number of Minutes Spent Altogether in the Shower or Bathtub and Spent
in' the Bathroom immediately Following a Shower or Bath
Percemiles
N 1 2 5 10 25 50 75 90 95 98 99
Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath)
Age(years) 1-4 198 1 5 5 10 15 20 30 45 60 120 120
Age (years) 5-11 263 4 5 5 10 13 20 30 30 60 90 120
Age (years) 12-17 239 4 4 5 7 10 15 30 30 45 60 60
Number of Minutes Spent in the Bathroom Immediately Following a Shower or Bath (minutes/bath)
Age (years) 1-4 196 0 0 0 0 0 2 5 10 15 20 35
Age (years) 5-11 260 0 0 0 0 2 5 10 15 15 30 35
Age (years) 12-17 238 0 0 0 2 5 5 10 20 30 45 45
100
120
121
120
45
120
60
Note: A value of "121" for number cf minutes signifies that more than 120 minutes were spent. N = doer sample size. Percent! les are the
percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
Table 5-22. Range cf Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents
Number of Times/Day
Total N »-» 0-0 1-2 3-5 6-9 10-19 20-29 30+
Age (years)
1-4 263 * 15 62 125 35 II 2 3
5-11 348 1 5 61 191 48 , 21 4 2
12-17 326 3 6 46 159 64 30 7 2
Note: * Signifies missing data. N = doer sample size in a specified range or number of minutes spent. DK= respondents answered "don't
know". Refused = respondents refused to answer.
Source: Tsang and Klepeis.1996
Table 9-231 Number of Minutes Spent Working or Being Near Excessive Dust in the Air (minutes/day)
Percemiles
N 1 2 5 10 25 50 75 90 - 95 98 99
Age (vears) 1-4 22 0 0 0 2 5 75 121 121 121 121 121
*~ T.
Age (years) 5-11 50 0 0.5 2 ' 4 15 75 121 121 121 121 121
Age (years) 12-17 52 0 1 2 5 5 20 120 121 121 121 121
DK
10
15
9
100
121
121
121
Note: A valueof "121" fornumberof minutes signifies that more than 120 minutes were spent. N = doer sample size. Percemiles are the
percentage of doers below or equal to a given number ol'minules.
Source: Tsang and Klepeis. 1 996.
June 2000
9-34
DRAFT-DO NOT QUOTE OR CITE
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1
2
Table 9-24. Range of Number of Times per Day a Motor Vehicle was Started in a Garage or Carport
and Started with the Garage Door Closed
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
29
30
31
32
-> *t
jj
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Total N
1-2
Times/day
3-5
6-9 10+
Dk
Range of the Number of Times an Automobile or Motor Vehicle was Started in a Garage or
Carport at Specified Daily Frequencies by the Number of Respondents
Ag«(years)
1-4
5-11
12-17
111
150
145
68
93
86
39
49
42
2 2
6
12 1
*
2
4
Range of the Number of Times Motor Vehicle Was Started with Garage Door Closed
at Specified Daily Frequencies by the Number of Respondents
Age (yean)
1-4
5-11
12-17 .
III
150
145
99
141
127
8
6
9
2 *
* *
4 1
2
3
4
Note: "'" Signifies missing data: "DK" = respondent answered don't know; Refused - the respondent refused to answer: N = doer sample size.
Source: Tsang and Klepeis. 1996
Table 9-25. Number of Minutes Spent Flavins on Sand. Gravel. Dirt or Grass
Minutes/Day
Total N
•-« 0-0
0-10
10-20
20-30 30^10
Number of Minutes Spent Playing on Sand or Gravel in a
Age (years)
1-4
5-11
12-17-
216
200
41
13 115
7 96
1 23
15
II
1
9'
12
2
'15
14
4
40-50 50-60
70-80 80-90 90-100
110-120
121
Day by the Number of Respondents
2
*
«
3
5
•
15
2?
3
Number of Minutes Spent Playing in Outdoors on Sand. Grave!. Dirt,
When Fill Dirt Was Present by the Number of Respondents
Age (years)
1-4
5-11
12-17
18-64
>64
3
216
200
41
237
3
* *
11 IIS
15 103
3 19
23 138
1 2
1
14
14
3
19
*
*
10
8
2
9
*
*
13
15
7
13
*
*
1
*
*
«
*
*
4
1
»
1
*
1
18
17
4
20
*
1 5
1 2 1
* • 1
or Grass
« *
4 *
I •
1 *
1 1
* *
7
6
3
*
7
9
2
3
*
16
20
3
,
16
17
*
9
*
Note: "*" = Signifies missing data. "DK" = Don't know. Refused = refused to answer. N = Doer sample size in specified range of number of
minutes spent. A value of " 1 2 1 " for number of minutes signifies that more than 1 20 minutes were spent.
Source: Tsane and Klepeis. 1996.
June 2000
9-35
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1
2
3
5
6
7
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
45
46
47
Table 9-26- Number of Minutes Spent Playing in Sand, Gravel. Dirt or Grass (minutes/day)
Percentiles
Category
Population Group
. N 1
5 10 25 50 75 90 95 98 99 100
Number of Minutes Spent Playing on Sand or Gravel (minutes/day)
Age (years)
Age (years)
Age (years)
1-4
5-11
12-17
203 0 0 0 0 0 0 30 120 121 121 121 121
193 0 0 0 0 0 3 60 121 121 121 121 121
40 0 0 0 0 0 0 45 120 121 121 121 121
Number of Minutes Spent Playing on Sand. Gravel, Dirt, or Grass When Fill Din Was Present (minutes/day)
Age (years)
Age (years)
Age (years)
1-4
5-n
12-17
205 0 0 0 0 0 0 30 120 121 121 121 121
185 0 0 0 0 0 0 30 120 121 121 121 121
38 0 0 0 0 0 0.5 "30 60 120 120 120 120
NOTE: Avalueof"121"fornumberofminutessignifiesthatmorethan 120 minutes were spent. N = doer sample size. Percentiles are the
percentage of doers below or equal to a given number of minutes.
Source; Tsangand Klepeis.1996
Table 9-27. Range of Number.of Minutes Spent Playing on Grass in a Day by the Number of Respondents
Minutes/Day
Total
N
*-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90- 100- 110- 121-
100 110 120 121
Age (years)
1-4
5-11
12-17
216 10 24
200 15 24
4! 2 5
19
10
1
21
10
25
19
8
35
38
8
18 49
20 49
8 5
NOTE: "*" signifies missing data. 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. Refused - respondent refused to answer.
Source: Tsangand Klepeis.1996.
Table 9-28. Number of Minutes Spent Playing on Grass (minutes/day)
Percentiles
Cateaorv
Population Group
5 10 25 50 75 90 95 98 99 100
Age (years)
Age (years)
Aae (vears)
1-4
5-11
12-17
206
185
39
0
0
0
0
0
0
0
0
0
0
0
0
15
30
30
60
60
60
120 121
121 121
120 121
12! 121
121 121
12! 121
121 121
121 121
12! 121
NOTE: A value of "121" fornumberof 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: Tsang and Klepeis.1996
June 2000
9-36
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2
!3
4
6
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
28
29'
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Table 9-29. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents
Times/Month
Total N 12345
Age (years)
1-4 63 11 14 7 3 3
5-11 100 16 15 7 9 6
12-17 84 21 13 7 4 8
6 7 8 9 10 11 12 13 14 15 16
4 1 3 1 4*2'l 12*
424*7*5*" 11 2
42318*1**2*
Times/Month
18 20 23 24 25 26
Age (years)
5-11 * 3 • 1 2
12-17 1 4 « * * 1
28 29 30 31 32 40 42 45 50 60 DK
Note: * Signifies missing data: "DK" = respondent answered don't know; N= sample size: Refused - respondent refused to answer.
Source: Tsana And Klepeis. 1996
Table 9-30. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month)
N 1
Age (years) 1-4 60 3
Age (years) 5-11 95 2
Age (years) 12-17 83 4
Note: A Value of 181 for number of minutes signifies that more than
percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1 996.
Table 9-3 1 . Range of the Average Amount of Time Actually
Percentiles
2 5 10 25 50 75 90 95 98 99 100
3 7.5 15 20 42.5 120 ISO 181 181 18! !8I
3 20 30 45 60 120 180 18! 181 181 181
5 15 20 40 -60 120 180 181 181 181 181
180 minutes were spent. N = doer sample size. Percentiles are the
Spent in the Water by Swimmers by the Number of Respondents
Minutes/Month
Total
N »-• 0-10 10-20 20-30 30-40
Age (years)
1-4 63 ' 3 5 12 12 1
5-1 1 100 5 3 2 12 5
12-17 84 1 3 7 10 2
90- 110- 150- 180- 181-
40-50 50-60 60-70 70-80 80-90 100 i20 150 180 181
4 8 * * 2 7 1 35
4 25 * * 7 * 16 2 1! 8
6 15 * 1 8 1 14 4 6 6
Note: * Signifies missing data. DK = respondents answered don't know. Ref= respondents refused to answer. N * doer sample size in
specified range of number of minutes spent. Values of 120. 150.and 180 for number of minutes signify that 2 hours. 2.5 hours, and 3 hours.
respectively, were spent.
Source: Tsang and Klepeis. 1996.
June 2000
9-37
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1
2
Table 9-32. Statistics for 24-Hour Cumulative Number of Minutes Spent Playing indoors and Outdoors
4
5
6
7
$
9
10
11
12
13
14
15
16
17
20
2
23
24
25
26
27
28
Percemiles
Category
Population Group
N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99
Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing
Age (years)
Age (years)
Age (years)
1-4
5-11
12-17
II
11
4
130
93.6
82.5
80.2
64.3
45
24.2
19.4
22.5
15
30
30
270 15
195 30
120 30
60 115
30 60
45 90
180
175
120
255 270
180 195
120 120
270 270
195 195
120 120
Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Flavins
34
35
36
37
38
39
40
41
42
43
Age (years)
Age (years)
Age (years)
5-11
12-17
4 83.25 89.66 44.83 15 210 15 20 54 146.5
9 148.333 144.265 48.088 5 360 5 55 60 280
I 15 * * 15 15 15 15 15 15
210 210 210 210
360 360 360 360
15 15 15 15
Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". N = doer sample size. Mean = Mean 24-hour cumulative
number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min-minimum number of minutes. Max-maximum
number of minutes. Percemiles are the percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
Table 9-33. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeptng/Nappi
-------
1
2
M
5
6
7
8
9
10
11
12
13
14
Table 9-35. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
and for Time Spent in Sports/Exercise
.Category
Population' Croup N
Mean
Stdev
Stderr
Min Max
5
25
Percemties
50 75 90 95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
Age (years)
Age (years)
Age (years)
M . 105
5-1 1 247
12-17 215
115.848
148.87
137.46
98.855
126.627
124.516
9.6472
8.0571
8.4919
10 630
2 975
5 1065
30
20
15
45
60
60
90 159 250 330
120 18S 320 390
110 180 265 375
345
510
470
390
558
520
Statistics for 24-Hour Cumulative Number of Minutes Spent in Sports/Exercise (a)
Age (years)
Age (years)
Age (years)
1-4 114
5-11 262
12-17 237
118.982
153.496
134.717
109.17
130.58
122.228
10.2247
8.0673
7.9396
10 670
2 975
5 1065
25
20
15
45
60
60
90 159 250 330
120 200 330 415
110 179 265 360
390
525
470
630
580
520
a Includes active sports, exercise, hobbies.
Note: "DK" = The respondent replied "don't know'. Refused - Refused data. N = doer sample size. Mean * Mean 24-hour cumulative number of minutes for doers.
Stdev « standard deviation. Slderr - standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of
21
22
23
24
25
26
I7
is
29
30
31
32
Source: Tsang and Klepeis. 1996.
Table 9-36. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation and Spent Walking
Pcrcentiles
Category Population Group
N Mean Stdev
Stderr Min
Mn 5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
Age (years) 1-4
Age (years) 5-11
Age (years) 12-17
13 166.54 177.06
21 206.14 156.17
27 155.07 128.28
49.109 15
34.078 30
24.687 5
630 15
585 60
465 5
30
90
60
130
165
135
ISO
245
225
370
360
420
630
574
420
630
585
465
630
585
465
J J> Statistics for 24-Hour Cumulative Number of Minutes Spent Walking
34
35 *
36
37
1
41
42
Age (years) 1-4
Age (years) 5-11
Age (years) 12-17
Note: "DK" = The respondent replied "don't know".
Stdev = standard deviation. Stderr = standard error.
doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. !996.
58 24.3276 26.3268
155 18.2129 21.0263
223 25.8341 32.3753
3.4569 1'
1 .6889 1
2.168 1
160 2
170 1
190 2
10
5
6
15
10
15
35
25
30
60
40
60
60
60
100
70
65
135
160
100
151
Refused - Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers.
Min • minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of
June 2000
9-39
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1
2
3
4
5
6
7
8
9
Group Name
Age (years)
Age (years)
Age (years)
Table 9-37.
Group Code
1-4
5-11
12-17
Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing (a)
N Mean Stdev Stderr Min Max 5 25 50
330 29.9727 19.4226 1.0692 1 170 10 15 30
438 25.7511 35.3164 1.6875 1 690 5 15 20
444 23.1216 18.7078 0.8878 ! 210 5 10 18
Percentiles
75 90 95
31 54.5 60
30 45 60
30 45 60
98
85
60
65
99
90
75
90
U a includes baby and child care, personal care services, washing and personal hygiene (bathing, showering, etc.)
?
4
Note: "DK" =
The respondent replied "don't know".
Refused - Refused data. N - doer sample size. Mean - Mean 24-hour cumulative number of minutes for doers.
Stdev = standard deviation. Stderr - standard error. Min = minimum number of minutes. Max = maximum number of minutes.
Percent] ies are the percentage of
doers below or equal to a given number of minutes.'
O Source: Tsang and Kiepeis. 1996.
[7
18
19
20
11
12
*-*
14
15
16
11
;g
'X
>0
ii
>2
* "V
> -\
'J
•A
>5
>6
>7
>8
>9
K)
rl
Category
Age (years)
Age (years)
Age (years)
Note: "DK" «•
Table 9-38.
Population Group
1-4
5-M
12-17
The respondent replied "don't know".
S:dev - standard deviation. Stderr = standard error
•
Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking
N Mean Stdev Stderr Min Max 5 25 50
492 93.4837 52.8671 2.?834 2 345 20 60 90
680 68.5412 38.9518 1.4937 5 255 15 40 63
535 55.8587 34.990J 1.5085 2 210 10 30 50 •
Percentiles
75 90 95
120 160 190
90 120 142.5
75 105 125
98
225
165
150
99
270
195
170
Refused = Refused data. N - doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers.
Min - minimum number of minutes. Max ** maximum number of minutes.
Percentiles are the percentage of
doers below or equal to a given number of minutes.
Source: Tsang arid Kiepeis, 1996.
Table 9-39. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School and Indoors at 3 Restaurant
Percemiles
Category
Population Group
N Mean Sldev Stderr Min Max 5 25 50
75 90 95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School
Age (years)
Age (years)
Age (years)
1-4
5-H
12-17
43 288.465 217.621 33.187 5 665 10 60 269
302 396.308 109.216 6.285 5 665 170 365 403
287 402.551 125.512 7.409 15 855 120 383 420
500 580 595
445 535 565
450 500 565
665
625
710
665
640
778
•-i Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant
13
W
r6
7
8
9
0
1
Age (years)
Age (years)
Age (years)
Note: "DK" -
1-4
5-11
12-17
The respondent replied "don't know".
Stdev - standard deviation . Stderr = standard error
61 62.705 47.701 6.1075 4 330 10 35 55
84 56.69 38.144 4.1618 5 180 10 30 45
122 69.836 78.361 7.0945 2 455 10 30 45
85 115 120
85 120 120
65 165 250
130
140
?25
330
180
360
Refused = Refused data. N = doer sample size. Mean - Mean 24-hour cumulative number of minutes for (foers.
Min = minimum number of minutes. Max = maximum number of minutes.
Percentiles are the percemace of
doers below or equal to a given number of minutes.
Source: Tsang and Kiepcis. 1996.
June 2000
9-40
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0
>4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
1
27
28
Table 9-40. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground.
at a Park/Golf Course, and at a Pool/River/Lake
Percentilcs
Category Population Croup
N' Mean
Stdev Stderr
Min
Max 5
25 50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground
Age (years) 1-4
Age (years) 5-11
Age (years) 12-17
Age (years) 18-64
Age (years) > 64
9 85
64 88.016
76 78.658
101 119.812
7 65
61.084 20,36
95.638 11.96
88.179 10.12
127.563 12.69
47.258 17.86
10
$
3
1
5
175 10
625 10
570 5
690 5
150 5
30 65
30 60
25 55
30 85
30 60
140
120
105
165
95
175
170
165
240
150
175
220
225
360
150
175
315
370
540
150
175
625
570
555
ISO
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Park/Golf Course
Age (years) 1-4
Age (years) 5-1)
Age (years) 12-17
21 149.857
54 207.556
52 238.462
176.25 38.4609
IS4.496 25.1068
242.198 33.5869
21
25
15
755 25
665 35
1065 15
50 85
70 125
150
275
60 147.5 337.5
360
555
590
425
635
840
755
660
915
755
665
1065
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake
Age (years) 1-4
Age (years) 5- It
Age(vears) 12-17
Note: ' DK" = The respondent replied "don't know".
Stdev = standard deviation. Siderr * standard error.
doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
14 250.571
29 175.448
22 128.318
177.508 47.441
117.875 21.889
94.389 20.124
90
25
40
630 90
390 30
420 58
130 167.5
60 145
60 82.5
370
293
2!0
560
365
225
630
375
235
630
390
420
630
390
420
Refused = Refused data. N = doer sample size. Mean - Mean 24-hour cumulative number cf minutes for doers.
Min -minimum number of minutes. Max = maximu.Ti number of minutes. Percentiies are the percentage of
June 2000
9-41
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1
2
i
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Table 9-41. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Bathroom. Bedroom, and in a Residence (All Rooms)
Percemiles
Category
Population Croup N* Mean Sldev
Stderr
Min
Max
5 25
50
75
90
95
98 99
Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Age (years)
Age (years)
Age (years)
M
5-11
12-17
335 73.719 54.382
477 60.46S 52.988
396 55.02 58.1 1 1
2.9712
2.4262
2.9202
5 .
1
1
392
690
450
15 30
10 30
5 15
60
50
36
100
75
65
140
120
125
180
150
155
225 240
180 235
240 340
Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom
Age (years)
Age (years)
Age (years)
M
5-11
12-17
328 35.939 46.499
490 30.9673 38.609
445 29.0517 32.934
2.5675
1.7442
1.5612
t
1
1
600
535
547
10 15
5 15
5 15
30
27
20
•40
35
35
60
52.5
60
75
60
65
125 270
100 200
90 100
Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom
Age (years)
Age (years)
Age (years)
1-4
5-11
12-17
488 741.988 167.051
689 669.144 162.888
577 636.189 210.883
7.562
6.2055
8.7792
30
35
15
1440
1440
1375
489 635
435 600
165 542
740
665
645
840
740
750
930
840
875
990
915
970
1095 1200
1065 1 140
1040 1210
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms)
Age (years)
Age (years)
Age' (years)
1-4
5-11
12-17
498 1211.64 218.745
700 1005.13 222.335
588 969.5 241.776
9.8022
8.4035
9.9707
270
190
95
1440
1440
1440
795 1065
686 845
585 811.5
1260
975
•950
1410
1165
1155
1440
1334
1310
1440
1412.5
1405
1440 1440
1440 1440
1440 1440
Note: "DK~ = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative nu.nber of minutes for doers.
Stdev = standard deviation. Stderr = standard error. Min-minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of
doers below or equal to a given number of minutes.
Source: Tsanj! and KJepeis. 1996.
June 2000
9-42
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Table 9-42. Statistics for 34-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle
Percemiles
Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99
Age (years)
Age (years)
Age (years)
1-4
5-11
12-17
335
571
500
£8.116
71.033
81.53
75.531
77.62
79.8
4.1267
3.24S3
3.5687
1 955
1 900
1 790
10 30
10 25
10 30
47
51
60
85
90
100
150 200
140 171
165.5 232.5
245 270
275 360
345 405
Note: "DK" = The respondent replied "don't know". Refused - Refused data. N = doer sample size. Mean « Mean 24-hour cumulative number of minutes for doers.
Stdev • standard deviation. Stderr = standard error. Min = minimum number of minults. Max = maximum number of minutes. Percemiles are the percentage of
doers below or equal to a given number of minutes.
Source: Tsane and Klepeis. 1996.
Table 9-4?. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence) and Outdoors
Other Than Near a Residence or Vehicle. Such as Parks. Golf Courses, or Farms
s========!====s=======^^
Percentilcs
Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence)
Age (years) 1-4 201 195.652 163.732 11.5488 3 715 30 75 135 270 430 535 625 699
A?e (years) 5-11 353 IS7.564 158.575 8.4401 4 1250 20 80 150 265 365 479 600 720
Age(years) 12-17 219 135.26 137.031 9.2597 I 720 5 35 100 190 SCO 452 545 610
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than
Near a Residence or Vehicle Such as Parks. Golf Courses, or Farms
Age (years)
Age (years J
Age (years)
J-»
5-11
12-17
54
159
175
164.648 177.34
171.34 177.947
156.903 174.411
24.133
14.112
13.184
1 980
5 1210
5 !065
10 60
15 55
10 45
120
115
100
175
221
210
.•70
405
385
560
574
570
630 980
660 725
735 915
Note: "DK" = The respondent replied "don't know". Refused - Refused data. N ~ doer sample size. Mean - Mean 24-hour cumulative number of minutes for doers.
Sldev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Pcrcemiles are the percentage of
doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
Table 9-44. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls. Grocer.- Stores, or Other Stores
Pereenti les
Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99
Age (years)
Age (years)
Age (years)
1-4
5-11
12-17
110
129
140
90.036
77.674
88.714
77.887
6S.035
101.361
7.4263
5.9901
8.5666
5 420
3 320
1 530
!0 40
5 50
5 20
65 105
60 110
45 123.5
210
ISO
222.5
250
225
317.5
359 360
255 2SO
384 413
Note: "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean «= Mean 24-hour cumulative number of minutes for doers.
Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max - maximum number of minutes. Percemiles are the percentage of
doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
June 2000 9-43 DRAFT-DO NOT QUOTE OR CITE
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_ — (N
c 5 S ?
«•» g 2
«** i>* i>- _
•r. -«gr f^
O v.
2 S
_
O
I
•= ^ ^ r^
— rg — ^r
i/: m P^ r^
3 sg * -2
T T r4
— w. —
•^ < < <
-------
1
2
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
M
29
30
31
32
I -»
34
35
36
37
38
Table 9-46. Range of Time (minutes) Spent Smoking Based on the Number of Respondents
*.*
Age (years)
1-4 499 344
5-1 1 703 479
12-17 589 333
660- 720-
720 780
Age (years)
1-4 35
5-11 72
12-17 7 3
0-60 60- 120-
120 180
29 23 14
40 38 32
75 31 30
780- 840- 900-
840 900 960
632
5 2 *
5 3 1
Number of Minutes
180- 240- 300- 360- 420-
240 300 360 420 480
8 10 7 8 .7
23 10 9 6 12
20 22 15 13 7
Number of Minutes
960- 1020- 1080- 1140- 1200-
1020 1080 1140 1200 1260
3 2-2 I
15223
1 * » * 2
480- 540- 600-
540 600 660
875
6 11 6 .
13 5 3
1260- 1320- 1380-
1320 1380 1440
1 * 1
* * 2
• * *
Note: * = Missing Data: DK =Don't know: N = Number of Respondents: Refused = Respondent Refused to Answer.
Source: Tsang And KJepeis. 1996.
Table 9-47. Number of Minutes Spent Smoking (minutes/day)
Category Population Group
Age (years) ! -4
Age (years) 5-11
Age (years) 12-17
N I 2 5
499 0 0 0
703 0 0 0
589 0 0 0
Percent! les
10 25 50 75 90 95
0 0 0 75 455 735
0 0 0 82 370 625
0 0 0 130 377 542
98 99 100
975 1095 1440
975 1140 1440
810 864 1260
Note: N = Doer Sample Size: Hercentiles are the Percentage of Doers beiow or Equal to a Given Number of Minutes.
Source: Tsang and Klepeis. 1996.
June 2000
9-45
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1
2
*>
6
7
$
9
10
11
12
13
14
15
16
17
Table 9-48. Gender and Age Groups
Gender-Age Group
Adolescents
Children"
Subgroup
Males
Females
Young mates
Young females
Old males
Old females
n
98
85
145
124
156
160
Age Range
12-17 years
12-1 7 years
6-8 years
6-8 years
9-1 1 years
9-11 vears
a Children under the age of 6 are excluded for the present study (too few responses in CARS study).
Source: Funk et aJ.. 1998.
June 2000
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1
2
••»
4
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Table 9-49. Assignment of At-Home Activities to Ventilation 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
Oudoor 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
22
23
24
Source: Funk et a!.. 1998.
June 2000
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1
2
4
6
7
8
9
10
11
12
13
15
16
17
18
19
20
21
9")
2.2.
23
24
25
26
?7
28
29
30
31
32
•3 J
34
35
36
37
38
39
40
41
42
43
Table 9-50. Aggregate Time Spent (minutes/day) At-Home in Activity Groups
by Adolescents and Children"
Adolescents Children
. . _
Mean SD Mean SD
Low 789 230 823 153
Moderate 197 131 241" 136
High 1 1J 3 17
HiglWiM,,sc 43 72 58 47
a Time spent engaging in all activities embodied by Ve category (minutes/day).
b Significantly differ from adolescents (p <0.05).
c Represents time spent at-home by individuals participating in high ventilation levels.
Source: Funk et aL 1 998.
Table 9-5 1 . Comparison of Mean Time (minutes/day) Spent At-Home by Gender3 (Adolescents)
Male Female '
Mean SD Mean SD
Low 775 206 804 253
Moderate 181 126 241 134
High 2 16 0 0
Source: Funk et a!.-. 1998.
Table 9-52. Comparison of Mean Time (minutes/day) Spent At-Home by Gender and Age for Children'
Activity Males Females
Group
6-8 Years 9-1 1 Years 6-8 Years 9-1 1 Years
Mean SD Mean SD Mean SD Mean
Low 806 134 860 157 828 155 803
Moderate 259 135 198 111 256 141 247
High 3 17 7 27 1 92
Hi2hMrtici[OT:!c 77 59 70 54 68 II 30
a Time spent engaging in ail activities embodied by Ve category (minutes/day)
b Participants in high Ve activities
Source: Funk et aL. 1998.
SD
162
146
10
23
June 2000
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1
2
|7
*4
5
6
1
8
9
10
11
12
13
14
15
16
11
18
fc.
*>
20
21
22
23
24
25
26
21
28
29
30
31
32 •
Table 9-53. Number of Person-Days/Individuals* for Children in CHAD* Database
Age Group
Oyear
0-6 months
6-12 months
1 year
12- 18 months
18-24 months
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
1 0 years
1 1 years
Total
' CHAD - Consolidated
All Studies
223/199
259/238
317/264
278/242
259/232
254/227
237/199
243/213
259/226
229/195
224/199
227/206
3009/2640
Human Activitv
California"
104
50
54
97
57
40
112
113
91
98
81
85
103
90
105
121
1200
Cincinnati'
36/12
15/5
21/7
31/11
81/28
54/18
41/14
f
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
Database is available on U.S. EPA Intranet.
b The California study referred to in this table is the Wiley 1991 study.
c The Cincinnati study referred to in this table is the Johnson
The number of person-
days of data are
1989 study.
the same as the number of individuals for all
Since up to three days of activity pattern data were obtained
studies except
from each participant in this studv. the
for the Cincinnati study.
number of person-days of
data is approximately three times the number of individuals.
Source: Hubal et al.. 2000.
June 2000
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^
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 9-54. Number of Hours Per Day Children Spend in Various Microenvironments by
Average ± Std. Dev. (Percent of Children Reporting >0 Hours in Microenvironment)
Age (years)
0
I
2
3
4
5
6
T
8
9
10
11
Source: Hubal et al.
indoors at Home
19.6 ±4.3 (99%)
19.5 ±4. 1 (99)
17.8 = 4.3(100)
18.0 ±4.2 (100)
1 7.3 ±4.3 (100)
16.3 ±4.0 (99)
16.0 = 4.2(98)
15.5±3.9(99)
1 5.6 ±4.1 (99)
15.2 ±4.3 (99)
16.0 ±4.4 (96)
14.9 ±4.6 (98)
.. 2000.
Outdoors at Home
I.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)
22 ± 2.3 (40)
2.0=1.7(44)
Age
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)
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
'19
20
21
22
23
24
Table 9-55. Average Number of Hours Per Day Children Spend Doing Various
Macroactivities While Indoors at Home by Age
(Percent of Children Reporting >0 Hours for Microenvironment/macroactivity )
Age
(year)
0
1
2
3
4
5
6
7
8
9
10
11
Source:
Eat
1.9(96%)
1-5(97)
1-3(92)
5-2(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)
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)
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)
Hubal et al.. 2000.
June 2000
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3
4
5
6
7
Table 9-56. Confidence in Activity Patterns Recommendations
Considerations
Rationale
Rating
8
9
10
II
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
TIME SPENT INDOORS VS. OUTDOORS
Study Elements
• Level of peer review
• Accessibility
* Reproducibility
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
* Adequacy of data
collection period
• Validity of approach
• Study size
• Representativeness of
the population
• Characterization of
variability
• Lack of bias in study
design (high rating is
desirable)
• Measurement error
Other Elements
• Number of studies
• Agreement between
researchers
Overall Rating
The study received high level of peer review. High
The study is widely available to the public. High
The reproducibility of these studies is left to question. Evidence has Medium
shown that activities have tended to shift over the past decade since the
study was published, due to economic conditions and technological
developments, etc. Thus, it is assumed there would be differences in
reproducing these results. However, if data were reanalyzed in the same
manner the results are expected to be the same.
The study focused on general activity patterns. High
The study focused on the U.S. population. High
Data were collected via questionnaires and interviews. High
The studies were published in 1985 (data were collected 1981 -1982). Medium
Households were sampled 4 times during 3 month intervals from High
February to December, 1981.
A 24 hour recall time diary method was used to collect data. High"
The sample population was 922 children between the ages of 3-17 years High
old.
The study focused on activities of children. High
Variability was characterized by age, gender, and day of the week; Medium
location of activities and various age categories for children.
Biases noted were sampled during time when children were in school Medium
(activities during vacation time are not represented); activities in the
1980's may be different than they are now;
Measurement or recording error may occur since the diaries were based Medium
on recall (in most cases a 24 hour recall).
Two High
Difficult to compare due to varying categories of activities and the unique Not
age distributions found withjn each study. Ranked
Medium
June 2000
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, 2
3
4
5
6
7
8
9
10
11
12
13
14
Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
Considerations
Rationale
Rating
TIME SPENT SHOWERING
Study Elements
• Level of peer review
* Accessibility
• Reproducibility
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
* Adequacy of data
collection period
The study received high level of peer review.
Currently, raw data are available to only EPA. It is not known when data
will be publicly available.
Results are reproducible.
The study focused specifically focused on time spent showering.
The study focused on the U.S. general population.
The study was based on primary data.
The study was published in 1996.
The data were collected between October 1992 and September 1994.
High
Low
High
High
High
High
High
High
15
Validity of approach
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups.
High
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
• Study size
• Representativeness of
the population
• Characterization of
variability
* Lack of bias in study
design (high rating is
desirable)
• Measurement error
Other Elements
* Number of studies
• Agreement between
researchers
Overall Rating
Study consisted of 9,386 total participants consisting of all ages.
The data were representative of the U.S. population.
The study provides a distribution on showering duration.
The study includes distributions for showering duration. Study is based on
short-term data.
Measurement or recording error may occur because diaries are based on
24-hour recall.
One: the study was a national study.
Recommendation is based on only one study but it is a widely accepted
study and average value is comparable to a second key study.
High
High
High
High
Medium
Low
High
High
June 2000
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2
*t
4
5
6
7
8
9
10
11
12
13
14
Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
Considerations
SHOWER FREQUENCY
Study Elements
• Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data
collection period
Rationale
The study received high level of peer review.
Currently, raw data is available to only EPA. It is not known when data
will be publicly available.
Results can be reproduced or methodology can be followed and
evaluated provided comparable economic and social conditions exists.
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
The data represents the U.S. population
The study was based on primary data.
The study was published in 1996.
The data were collected between October 1992 and September 1994.
Rating
High
Low
High
High
High
High
High
High
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Validity of approach
Study size
Representativeness of
the population
Characterization of
variability
Lack of bias in study
design (high rating is
desirable)
Measurement error
Other Elements
* Number of studies
• Agreement between
researchers
Overall Rating
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups. Responses were weighted according to this
demographic data.
The study consisted of 9,386 total participants consisting of all age
groups
Studies were based on the U.S. population.
The study provided data that varied across geographic region, race,
gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent-
Study is based on short term data-
Measurement or recording error may occur because diaries were based on
24-hour recall.
One; the study was based on one, primary, national study.
Recommendation was based on only one study.
High
High
High
High
Medium
Medium
Low
Not
Ranked
High
June 2000
9-54
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Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2
*» •
4
5
6
7
8
9
10
11
12
13
14
Considerations
Rationale
Rating
TIME SPENT SWIMMING
Study Elements
* Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data
collection period
Study received high level of peer review.
Currently, raw data is available to only EPA. It is not known when data
will be publicly available.
Results can be reproduced or methodology can be followed and
evaluated provided comparable economic and social conditions exists.
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
The data represents the U.S. population
The study was based on primary data.
The study was published in 1996.
The data were collected between October 1992 and September i994.
High
Low
High
High
High
High
High
High
15
16
17
18
19
20
21
22
23
24
25
26
27
28
KZ9
Validity of approach
Study size
Representativeness of
the population
Characterization of
variability
• Lack of bias in study
design (high rating is
desirable)
• Measurement error
Other Elements
• Number of studies
• Agreement between
researchers
Overall Rating
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups. Responses were weighted according to this
demographic data.
The study consisted of 9.336 total participants consisting of all age
groups
Studies were based on the U.S. population.
The study provided data that varied across geographic region, race,
gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
The study includes distributions for swimming duration. Study is based
on short term data.
Measurement or recording error may occur because diaries were based
on 24-hour recall.
One; the study was based on one, primary, national study.
Recommendation was based on only one study.
High
High
High
High
Medium
Medium
Low
Not
Ranked
High
June 2000
9-55
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2
<•)
4
5
6
7
S
9
10
11
12
13
14
15
Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
Considerations
RESIDENTIAL TIME
Studv Elements
• Level of peer review
• Accessibility
• Reproducibility
* Focus on factor of
interest
» Data'pertinent to US
• Primary data
• Currency
• Adequacy of data
collection period
• Validity of approach
Rationale
SPENT INDOORS AND OUTDOORS
The study received high level of peer review.
Currently, raw data is available to oniy EPA. It is not known when data
will be publicly available.
Results can be reproduced or methodology can be followed and
evaluated provided comparable economic and social conditions exists.
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
The data represents the U.S. population
The study was based on primary data.
The study was published in 1 996.
Data were collected between October 1992 and September 1994.
The study used a valid methodology and approach which, in addition to
Rating
High
Low
High
High
High
High
High
High
High
16 • Studv size
17 • Representativeness of
18 the population
19 • Characterization of
20 variability
21 • Lack of bias in study
22 design (high rating is
23 desirable)
24 • Measurement error
25 Other Elements
26 • Number of studies
27 • Agreement between
28 researchers
29 Overall Rating
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups. Responses were weighted according to this
demographic data.
The study consisted of 9,386 total participants consisting of all age
groups
The studies were based on the U.S. population.
The study provided data that varied across geographic region, race,
gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
The study includes distribitions for time spent indoors and outdoors at
ones residence. Study is based on short term data.
Measurement or recording error may occur because diaries were based
on 24-hour recall.
One; the study was based on one. primary, national study.
Recommendation was based on only one study.
High
High
High
Medium
Medium
Low
Not
Ranked
High
June 2000
9-56
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2
*>
4
5
6
7
8
9
10
11 '
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Table
Considerations
TIME SPENT PLAYING
Study Elements
• Level of peer review
• Accessibility
• Reproducibility .
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data
collection period
• Validity of approach
• Study size
• Representativeness of
the population
• Characterization of
variability
• Lack of bias in study
design (high rating is
desirable)
• Measurement error
Other Elements
* Number of studies
• Agreement between
researchers
Overall Rating
9-56. Confidence in Activity Patterns Recommendations (cont'd)
Rationale
ON SAND OR GRAVEL
The study received high level of peer review.
Currently, raw data are available to only EPA. It is not known when data
will be publicly available.
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
The data represents the U.S. population.
The study was based on primary data.
The study was published in 1 996.
The data were collected between October 1992 and September 1994.
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups. Responses were weighted according to this
demographic data.
The study consisted of 9,386 total participants consisting of all age
groups.
The studies were based on the U.S. population.
The study provided data that varied across geographic region, race,
gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
The study includes distributions for bathing duration. Study is based on
short-term data.
Measurement or recording error may occur because diaries were based on
24-hour recall.
One; the study was based on one. primary, national study.
Recommendation was based on only one study.
Rating
High
Low '
High
High
High
High
High
High
High
\
High
High
High
Medium
Medium
Low
Not
Ranked
High
June 2000
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2
•^
4
5
6
7
8
9
10
11
12
13
14
Table
Considerations
TIME SPENT PLAYING
Study Elements
• Level of peer review
* Accessibility
• Reproducibility
• Focus on factor of
interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data.
collection period
9-56. Confidence in Activity Patterns Recommendations (cont'd)
Rationale
ON GRASS
The study received high level of peer review.
Currently, raw data are available to only EPA. It is not known when data
will be publicly available.
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
The data represents the U.S. population.
The study was based on primary data.
The study was published in 1996.
The data were collected between October 1992 and September 1994.
Rating
High
Low
High
High
High
High
High
High
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Validity of approach
Study size
Representativeness of
the population
Characterization of
variability
Lack of bias in study
design (high rating is
desirable)
Measurement error
Other Elements
• Number of studies
* Agreement between
researchers
Overall Rating
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups. Responses were weighted according to this
demographic data.
The study consisted of 9,386 total participants consisting of ail age
groups.
The studies were based on the U.S. population.
The study provided data that varied across geographic region, race,
gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
The study includes distributions for bathing duration. Study is based on
short-term data.
Measurement or recording error may occur because diaries were based on
24-hour recall.
One; the study was based on one. primary, national study.
Recommendation was based on only one study.
High
High
High
High
Medium
Medium
Low
Not
Ranked
High
June 2000
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4
5
6
7
8
9
10
Table 9-57. Summary of Activity Pattern Studies
Summary of Activity Patterns Studies
Study
Timmer(1985)
Robinson & Thomas ( 1991 )
Wiley (1991)
Davis (1995)
Tsang&Kleipeis(1996)
Funk (1998)
Age Groups
(yrs)
3-5.6-8,9-11. 12-
14. 15-17
12-adults
0-2.3-5.6-8.9-11
10-60 (months)
1-4.5-11.12-17
6-11. 12-17
Sample Size
922
1.762
(California)
2.762 (national)
1.200
92
Varies with age
groups and
activities
768
Population
National
California and
national
California
Washington State
U.S. national
California
Activities
18 microenvironments
16 microenvtronmenis
10 microenvironments
Activities grouped
into indoors and
outdoors
23 microenvironments
Activities grouped
11
Hubal (20GO)
0.1.2.3.4.5.6.7.
8.9. 10. II
2.640
Based on Wiley
(199 i). Johnson
(1989). and Tsang
&Kleipeis(l996)
into low. medium, and
high ventilation levels
Activities grouped
into indoors at home-
indoors at school.
outdoors at home.
outdoors at part, and
in vehicle
12
June 2000
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3
4
5
6
7
S
9
10
11
12
13
14
15
Table
Age (years)
3-5
6-8
9-11
12-14
15-17
12 and older
0-2
3-5
6-8
9-n
1 Mean, of weekday i
9-58. Summary of Mean Time
Time Indoors
(hours/day)1
19
20
20
20
19
21 (national)
21 (California)
20
18.8
19.7
19.9
and weekend rounded up to two
Spent indoors and Outdoors from Several Studies
Time Outdoors Study
(hours/day)1
2.8 Timmer 1985
2.2
1.8
1.8
1.9
1 .2 (national Robinson and Thomas 1991
1.4 (California)
4 Wiley 1991
5.2
4.4
4.1
significant figures.
June 2000
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2
3
4
Table 9-59. Summary of Recommended Values for Activity Factors
Type
Value
Study
8
9
10
11
12
13
Time Indoors
Time Outdoors
Taking Showers
Swimming
Residential
Indoors
Outdoors
Playing on Sand or Gravel
Playing on Grass
Ages 3-5 years (19 hours/day)
Ages 6-14 years (20 hours/day)
Ages 12-17 years (19 hours/day)
Ages 3-5 years (2.8 hours/day)
Ages 6-8 years (2.2 hours/day)
Ages 9-14 years (1.8 hours/day)
Ages 15-17 years (1.9 hours/day)
10 min/day shower duration
1 shower event/day
1 event/month
60 minutes/event
18hr/day
2 hr/day
60 min/day
60 min/day
Timmeretal., 1985
Tsang and Klepeis, 1996
Tsang and Klepeis, 1996
Tsang and Klepeis, 1996
Tsang and Klepeis, 1996
Tsang and Klepeis, 1996
Tsang and Klepeis, 1996
June 2000
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10. CONSUMER PRODUCTS
10.1 BACKGROUND
Consumer products may contain toxic or potentially toxic chemical constituents to which
children may be exposed as a result of their use. For example, methylene chloride and other
solvents and carriers are common in consumer products and may have health concerns. Potential
pathways of exposure to consumer products or chemicals released from consumer products
during use can occur via ingestion, inhalation, and dermal contact.
This chapter presents information on the amount of product used, frequency of use. and
duration of use for various consumer products typically found in households. There are limited
data available on consumer product use for the general population and especially for children.
Children can be in environments where household consumer products (Table 10-1) such as
cleaners, solvents, and paints are used. As such, children can be passively exposed to chemicals
in these products. The studies presented in the following sections represent readily available
surveys for which data were collected on the frequency and duration of use and amount of use of-
cleaning products, painting products, household solvent products, cosmetic and other personal
care products, household equipment, pesticides, and tobacco. The reader is referred to the
Exposure Factors Handbook (U.S. EPA, 1997) for a more detailed presentation for use of
consumer products for the general population.
10.2 CONSUMER PRODUCTS USE STUDIES
Tsang andKlepeis (1996) - National Hitman Activity Pattern Survey (NHAPS) - The U.S.
EPA collected information for the general population on the duration and frequency of selected
activities and the time spent in selected microenvironments via 24-hour diaries. Over 9000
individuals from all age groups in 48 contiguous states participated in NHAPS. The survey was
conducted between October 1992 and September 1994. Individuals were interviewed to
categorize their 24-hour routines (diaries) and/or answer follow-up exposure questions that were
related to exposure events. Data were collected based on selected socioeconomic (gender, age,
race, education, etc.) and geographic (census region, state, etc.) factors and time/season (day of
-
-------
week, month) (Tsang and Klepeis, 1996). Data were collected for a maximum of 82 possible
microenvironments and 91 different activities (Tsang and Klepeis, 1996).
As part of the survey, data were also collected on duration and frequency of use of
selected consumer products. These data are presented in Tables 10-2 through 10-6 for age
groups 1-4,5-11, and 12-17 years. Distribution data are presented for selected percentiles (where
possible). Other data are presented in ranges of time spent in an activity (e.g., working with or
near a product being used) or ranges for the number of times an activity involving a consumer
product was performed.
The advantages of NHAPS is that the data were collected for a large number of
individuals, representative of the U.S. general population. However, means cannot be calculated
for consumers who spent more than 60 or 120 minutes (depending on the activity) in an activity
using a consumer product. Therefore, a good estimate of the high consumer activities cannot be
captured.
10.3 RECOMMENDATIONS
Due to the large range and variation among consumer products and their exposure
pathways, it is not feasible to specify recommended exposure values as had been done in other
chapters of this handbook. The user is referred to the contents and references in Chapter 16 of
the Exposure Factors Handbook to derive appropriate exposure factors and review its associated
recommendations.
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10.4 REFERENCES FOR CHAPTER 10
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by
Lockheed Martin, Contract No. 68-W6-001, Delivery Order No. 13.
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 Report
No. 560/5-85-007.
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Table 10-1. Consumer Products Found in the Typical U.S. Household"
Consumer Product Category
Consumer Product
Cosmetics Hygiene Products
Household Furnishings
Garment Conditioning Products
Household Maintenance Products
Adhesive bandages
Bath additives (liquid)
Bath additives (powder)
Cologne/perfume/aftershave
Contact lens solutions
Deodorant/antiperspirant (aerosol)
Deodorant/antiperspirant (wax and liquid)
Depilatories
Facial makeup
Fingernail cosmetic's
Hair coloring/tinting products
Hair conditioning products
Hairsprays (aerosol)
Lip products
Mouthw ash/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 cunains
Vinyl upholstery, furniture
Ami-static spray (aerosol)
Leather treatment (liquid and wax)
Shoe polish
Spray starch (aerosol)
Suede cleaner/polish (liquid and aerosol)
Textile water-proofing (aerosol)
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 foiY)"
Fabric rinse/softener (liquid)
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Table 10-1. Consumer Products Found in the Typical U.S. Household* (continued)
Consumer Product Category
Consumer Product
Household Maintenance Products
(continued)
Home Building/Improvement Products (DlY)h
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)
Adhesives. specialty (liquid)
Ceil ing tile
Caulks/sealers/fillers
Dry wall/wall board
Flooring (vinyl)
House Paint (interior) (liquid)
House Paint and Slain (exterior) (liquid)
Insulation (solid)
Insulation (foam)
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Table 10-1. Consumer Products Found in the Typical U.S. Household3 (continued)
Consumer Product Category
Consumer Product
Home Building/Improvement Products (DIY)"1
(Continued)
Automobile-related Products
Personal Materials
Paint/varnish removers
Paint thinner/brush cleaners
Patching/ceiling plaster'
Roofing
Refinishing products (polyurethane. varnishes, etc.)
Spray paints (home) (aerosol)
Wall paneling
Wall paper
Wall paper glue
Antifreeze
Car polish/wax
Fuel/lubricant additives
Casoline/diesel fuel
Interior upholstery/components, synthetic
Motor oil
Radiator flush/cleaner
Automotive touch-up paint (aerosol)
Windshield washer solvents
Clothes/shoes
Diapers/vinyl pants
Jewelry
Printed material (colorprinL 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.
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Table 10-2. Number of Minutes Spent in Activities Working with or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day)
Percentiles
Category
Age (years)
Age (years)
Age (years)
Age (years)
Age (years)
Population Group
1-4
5-11
12-17
18-64
>64
N
21
26
41
672
127
I
0
1
0
0
0
2
0
1
0
0
0
5
0
2
0
1
0
10
0
2
0
2
1
25
5
3
2
5
3
50
10
5'
5
10
5
75
15
15
10
20
15
90
20
30
40
60
30
95
30
30
60
121
60
98
12!
30
60
121
120
99
12!
30
60
121
121
100
121
30
60
121
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent: n = doer sample size: percentiles are the
percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
Table 10-3 Number of Minutes Spent Using Any Microwave Oven (minutes/day)
Percentiles
Category
Age (years)
Age (years)
Age (years) •
Age (years)
Population Croup
5-11
12-17
18-64
>64
N
62
141
1686
375
I
0
0
0
0
2
0
0
0
0
5
0
0
1
1
10
1
1
2
2
25
1
2
3
3
50
2
3
5
5
75
5
5
10
10
90
10
10
15
20
95
15
15
25
30
98
20
30
45
60
99
30
30
60
60
100
30
60
121
70
Note: A Value of "121" for number of minutes signifies that more than 120 minutes were spent: n = doer sample size: perceniiles are the
percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis. 1996.
Table 10-4. Number of Respondents Using a Humidifier at Home
Age (years)
M
5-11
12-17
Total N
111
88
83
Almost
Every
Day
-i •>
jj
IS
21
3-5 Times a
Week
16
10
7
Frequency
1 -2 Times a
Week
7
12
5
1-2 Times a
Month
53
46
49
DK
2
2
1
Note: DK= Don't Know: Refused = Respondent Refused to Answer: N = Number of Respondents
Source: Tsang and Klepeis. 1996.
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Table 10-5. Number of Respondents Indicating that Pesticides Were Applied by the Professional at Home
to Eradicate Insects. Rodents, or Other Pests at Specified Frequencies
Age (years)
1-4
5-11
12-17
Total N
.113
150
143
Number of Times Over a 6-month Period
Pesticides Were Applied by Professionals
None
60
84
90
1-2
35
37
40
3-5
11
10
5
6-9
6
18
6
10+
1
1
*
DK
*
*
2
Note: * - Missing Data: DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents
Source: Tsang and Klepeis. 1996.
Table 10-6. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
To Eradicate Insects. Rodents, or Other Pests at Specified Frequencies
Age (years)
1-4
5-!l
12-17
Total N
. 113
150
143
Number of Times Over a 6-month
Period Pesticides Applied by Resident
None
46
50
45
1-2
46
70
64
3-5
15
24
21
6-9
3
1
5
10+
3
4
g
DK
«
1
*
Note: * = Missing Data: DK= Don't know: Refused = Respondent Refused to Answer; N = Number of Respondents
Source: Tsang and Klepeis, 1996.
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1 11. BODY WEIGHT STUDIES
2 .
3 11.1 INTRODUCTION
4 The average daily dose is typically normalized to the average body weight of the exposed
5 population. If exposure occurs only during childhood years, the average child body weight
6 during the exposure period should be used to estimate risk (U.S. EPA, 1989).
7 The purpose of this section is to describe key published studies on body weight for
8 children in the general U.S. population, as described in the Exposure Factors Handbook (U.S.
9 EPA, 1997). Recommended'values are based on the results of these studies.
10
II 11.2 BODY WEIGHT STUDIES
12 Hamill et al. (1979) - Physical Growth: National Center for Health Statistics
13 Percentiles- A National Center for Health Statistics (NCHS) Task Force that included academic
14 investigators and representatives from CDC Nutrition Surveillance Program selected, collated,
15 integrated, and defined appropriate data sets to.generate growth curves for the age interval: birth
to 36 months developed (Hamill et al., 1979). The percentile curves were for assessing the
17 physical growth of children in the U.S. They are based on accurate measurements made on large
18 nationally representative samples of children (Hamill et al., 1979). Smoothed percentile curves
19 were derived for body weight by age (Hamill et al., 1979). Curves were developed for boys and
20 for girls. The data used to construct the curves were provided by the Pels Research Institute,
21 Yellow Springs, Ohio. These data were from an ongoing longitudinal study where
22 anthromopetric data from direct measurements are collected regularly from participants (~ 1,000)
23 in various areas of the U.S. The NCHS used advanced statistical and computer technology to
24 generate the growth curves. Table 11-1 presents the percentiles of weight by sex and age.
25 Figures 11-1 and 11-2 present weight by age percentiles for boys and for girls aged birth to 36
26 months, respectively. Limitations of this study are that mean body weight values were not
27 reported and the data are more that 15 years old. However, this study does provide body weight
28 data for infants less than 6 months old.
29 . NCHS (1987) - Anthropometric Reference Data and Prevalence of Overweight, United
.30 States, 1976-80 - Statistics on anthropometric measurements, including body weight, for the U.S.
31 population were collected by NCHS through the second National Health and Nutrition
June 2000 . 11-1 DRAFT-DO NOT QUOTE OR CITE
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1 Examination Survey (NHANES II). NHANES II was conducted on a nationwide probability
2 sample of approximately 28,000 persons, aged 6 months to 74 years, from the civilian,
3 non-institutionalized population of the United States. Of the 28,000 persons, 20,322 were
4 interviewed and examined, resulting in a response rate of 73.1 percent. The survey began in
5 February 1976 and was completed in February 1980. The sample was selected so that certain
6 subgroups thought to be at high risk of malnutrition (persons with low incomes, preschool
7 children, and the elderly) were oversampled. The estimates were weighted to reflect national
8 population estimates. The weighting was accomplished by inflating examination results for each
9 subject by the reciprocal of selection probabilities adjusted to account for those who were not
10 examined, and post stratifying by race, age, and sex (NCHS, 1987).
11 The NHANES II collected standard body measurements of sample subjects, including
12 height and weight, that were made at various times of the day and in different seasons of the year.
13 This technique was used because one's weight may vary between winter and summer and may
14 fluctuate with recency of food and water intake and other daily activities (NCHS, 1987). Mean
15 body weights and standard deviations for children, ages 6 months to 19 years, are presented in
16 Table 11-2 for boys, girls, and boys and girls combined. Percentile data for children, by age, are
17 presented in Table 11-3 for males, and in Table 11-4 for females. From Table 11-2, the mean
18 body weights for girls and boys are approximately the same from ages 6 months to 14 years.
19 Starting at years 15-19, the difference in mean body weight ranges from 6 to 11 kg.
20 Burmaster et al. (1997)- Lognormal Distributions for Body Weight as a Function of Age
21 for Males and Females in the United States, 1976-1980 - Burmaster et al. (1997) performed data
22 analysis to fit normal and lognormal distributions to the body weights of females and males at
23 age 9 months to 70 years (Burmaster et al., 1997). The 1997 Exposure Factors Handbook used a
24 pre-published version of this paper (U.S. EPA, 1997). The numbers reported in Tables 11-5 and
25 11-6 vary slightly from those reported in the Exposure Factors Handbook (U.S. EPA, 1997).
26 Data used in this analysis were from the second survey of the National Center for Health
27 Statistics, NHANES II, which included 27,801 persons 6 months to 74 years of age in the U.S.
28 (Burmaster et al., 1997). The NHANES II data had been statistically adjusted for non-response
29 and probability of selection, and stratified by age, sex, and race to reflect the entire U.S.
30 population prior to reporting (Burmaster et al., 1997). Burmaster et al. (1997) conducted
31 exploratory and quantitative data analyses, and fit normal and lognormai distributions to
June 2000
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1 percentiles of body weights of children, teens, and adults as a function of age. Cumulative
2 distribution functions (CDFs) were plotted for female and male body weights on both linear and
3 logarithmic scales.
4 Two models were used to assess the probability density functions (PDFs) of children's
5 body weight. Linear and quadratic regression lines were fitted to the data. A number of
6 goodness-of-fit measures were conducted on data generated by the two models. Burmaster et al.
7 (1997) found that lognormal distributions give strong fits to the data for each sex across all age
8 groups. Statistics for the lognormal probability plots for children, ages 9 months to 20 years, are
9 • presented in Tables 11-5 and 11-6. These data can be used for further analyses of body weight
10 distribution (i.e., application of Monte Carlo analysis).
11 U.S. EPA, 2000 - Body Weight Estimates Based on NHANES III Data - The EPA Office
12 of Water has estimated body weights for children, in kilograms, by age and gender using data
13 collected during National Health and Nutrition Examination Survey III (NHANES HI), 1988-
14 1994. NHANES III collected body weight data for approximately 15,000 children between the
15 ages of 2 months and 17 years. Table 11-7 Presents the body weight estimates in kilograms by
6 age and gender. Table 11 -8 shows the body weight estimates for the infants under the age of 3
17 months and/or younger, while Figures 11-3 and 11-4 compare the body weights (mean and
18 median) between male and female among various age groups, respectively.
19 The limitations of these data are (1) the data were not available for infants under 2
20 months old, and (2) the data are roughly 6-12 years old. With the upward trends in body weight
21 from NHANES II (1976-1980) to NHANES III which may still be valid, the data in Tables 11-7
22 and 11-8 may underestimate current body weights. Adjustment factors may be needed to update
23 the estimates from 1988-1994 data to 2000. However, the data are national in scope and
24 represent the general children's population.
25
26 11.3 RECOMMENDATIONS
27 The recommended values for body weight are summarized in Table 11-9. Table 11-10
28 presents the confidence ratings for body weight recommendations.
29 For infants (birth to 6 months), appropriate values for body weight may be selected from
Table 11-1. These data (percentile only) are presented for male and female infants.
June 2000 11-3 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
For children, appropriate mean values for .weights may be selected from Table 11-2.
If percentile values are needed, these data are presented in Table 11-3 for male children and in
Table 11-4 for female children.
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11.4 REFERENCES FOR CHAPTER 11
3 Burmaster, D.E.; Lloyd, K.J.; Crouch, E.A.C. (1997) Lognormal distributions for body weight as a function of age
4 for males and females in the United States, 1976-1980. Risk Anal. 17(4):499-505.
5
6 Hamill, P.V.V.; Drizd, T.A.; Johnson, C.L.; Reed, R.B.; Roche, A.F.; Moore, W.M. (1979) Physical growth:
7 National Center for Health Statistics Percentiles. American J. Clin. Nutr. 32:607-609.
8
9 National Center for Health Statistics (NCHS) (1987) Anthropometric reference data and prevalence of overweight,
10 United States, 1976-80. Data from the National Health and Nutrition Examination Survey, Series 11,
11 No. 238. Hyattsville, MD: U.S. Department of Health and Human Services, Public Health Service, National
12 Center for Health Statistics. DHHS Publication No. (PHS) 87-1688.
13
14 U.S. EPA (1989) Risk assessment guidance for Superfund, Volume 1: Human health evaluation manual.
15 • Washington, DC: U.S. Environmental Protection Agency, Office of Emergency and Remedial Response.
16 EPAV540/1-89/002.
17
18 U.S. EPA (1997) Exposure Factors Handbook. Washington, DC: Office of Research and Development. EPA/600-
19 P-95/002F.
20
21 U.S. EPA (2000) Memorandum entitied: Bodyweight estimates on NHANES HI data, revised, Contract 68-C-
22 99-242, Work Assignment 0-1 from Bob Clickner, Westat Inc. to Helen Jacobs, U.S. EPA dated
23 March 3,2000.
24
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1
2
3
Table 11-1. Smoothed Percentiles of Weight (In Kg) by Sex And Age:
Statistics From NCHS And Data From Fels Research Institute, Birth to 36 Months
6
7
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
Smoothed1 Percentile
Sex and Age
Male
Birth
I Month
3 Months
6 Months
9 Months
12 Months
18 Months
24 Months
30 Months
36 Months
Female
Birth
1 Month
3 Months
6 Months
9 Months
12 Months
18 Months
24 Months
30 Months
36 Months
5th
10th
25th
50th
75th
90th
95th
Weight in Kilograms
2.54
3.16
4.43
6.20
7.52
8.43
9.59
10.54
11.44
12.26
2.36
2.97
4.18
5.79
7.00
7.84
8.92
9.87
10.78
11.60
2.78
3.43
4.78
6.61
7.95
8.84
9.92
10.85
11.80
12.69
2.58
3.22
4.47
6.12
7.34
8.19
9.30
10.26
11.21
12.07
3.00
3.82
5.32
7.20
8.56
9.49
10.67
11.65
12.63
13.58
2.93
3.59
4.88
6.60
7.89
8.81
10.04
11.10
12.11
12.99
3.27
4.29
5.98
7.85
9.18
10.15
11.47
12.59
13.67
14.69
3-23
3.98
5.40
7.21
8.56
9.53
10.82
11.90
12.93
13.93
3.64
4.75
6.56
8.49
. 9.88
10.91
12.31
13.44
14.51
15.59
3.52
4.36
5.90
7.83
9.24
10.23
11.55
12.74
13.93
15.03
3.82
5.14
7.14
9.10
10.49
11.54
13.05
14.29
15.47
16.66
3-64
4.65
6.39
8.38
9.83
10.87
12.30
13-57
14.81
15.97
4.15
5.38
7.37
9.46
10.93
11.99
13.44
14.70
15-97
17.28
3.81
4.92
6.74
8.73
10.17
11.24
12,76
14.08
15.35
16.54
aSmoothed by cubic-spline approximation.
\
Source: Hamill et al. (1979).
June 2000
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18
17
16
15
14
13
12
§ 11
c
Z 10
o>
9
8
7
6
5
4
3
.95th
90th
75th
50th
25th-
10th-
5th
39.7
37.5
35.3
33.1
30.9
28.7
26.5
24.3
22.0
19.8
17.6
15.4
13.2
11.0
8.8
6.6
4.4
2.2
I
&
3
•o
o
c
3
a
09
0 3 6 9 12 15 18 21 24 27 30 33 36
Age in Months
Figure 11-1. Weight by Age percentiles for Girls Aged Birth-36 Months
Source: Hamill et al. (1979).
June 2000 11 -7 DRAFT-DO NOT QUOTE OR CITE
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0
6 9 12 15 18 21 24 27 30 33 36
Age in Months
Figure 11-2: Weight by Age Percentiles for Boys Aged Birth-36 Months
Source: Hamill et ai. (1979).
i
<5*
•o
o
c
a
0)
June 2000
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iU
•
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
6
27
28
29
30
31
32
33
Table 11-2. Body Weights of Children" (Kilograms)
Age
6-1 1 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
1 6 years
1 7 years
18 years
! 9 years
Boys
Mean (kg)
9.4
11.8
13.6
. 15.7
17.8
!9.8
23.0
25.1
28.2
31.1
36.4
40.3
44.2
49.9
57.!
61.0
67.1
66.7
7U
71.7
Std. Dev.
1.3
1.9
1.7
2.0
2.5
3.0
4.0
3.9
6.2
6.3
7.7
10.1
10.1
12.3
11.0
11.0
12.4
11.5
12.7
11.6
Girls
Mean (kg)
8.8
10.8
13.0
14.9
17.0
19.6
22.1
24.7
27.9
31.9
36.1
41.8
46.4
50.9
54.8
55.1
58.1
59.6
59.0
60.2
Std. Dev.
!.2
1.4
1.5
2.1
2.4
3.3
4.0
5.0
5.7
8.4
8.0
10.9
1 0.1
11.8
11.1
9.8
10.1
11.4
11.1
11.0
Boys and Girls
Mean
(kg)
9.1
11.3
13.3.
15.3
17.4
19.7
22.6
24.9
28.1
31.5
36.3
41.1
45.3
50.4
56.0
58.1
62.6
63.2
65.1
• 66.0
Note: 1 kg = 2.2046 pounds.
alncludes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
Source: Adapted from National Center for Health Statistics (NCHS) (1987).
June 2000
11-9
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Table 11-5. Best-fit Parameters for Lognormal Distributions
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Lognormal Probability Plots
Linear Curve
Age Midpoint (yr)
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
^
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
' o,'
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
*W2> O", • correspond to the mean and standard deviation, respectively, of the lognormal distribution of
body weight (kg).
Source: Burmaster et al. (1997).
June 2000
11-12
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
F
24
25
26
27
28
29
30
31
32
Table 11-6. Statistics for Probability Plot Regression Analyses
Male's Body Weights 6 Months to 20 Years of Age
Age Midpoint (yrs)
Lognormal Probability Plots
Linear Curve
»S o2-
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
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
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
*U2, O2 - correspond to the mean and standard deviation, respectively, of the lognormal distribution of
body weight (kg).
Source: Burmaster et al. (1997).
June 2000
11-13
DRAFT-DO NOT QUOTE OR CITE
-------
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J2
G.
O
cu
C/j
5
O
u
BO
CA
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2
Table 1 1-8. Body Weight Estimates (in kilograms) by Age, U.S. Population 1988-94
6
7
10
11
12
13
14
15
16
Age
Newborn
1 Month
2 Months
3 Months
3 Months and
Younger
Sample Size
NA
NA
243
190
433
Population
NA
NA
408.837
332.823
741.660
Median
NA
NA
6.3
7.0
6.6
Male and Female
Mean
NA
NA
6.3
6.9
6.6
95% CI
NA
NA
6.1-6.4
6.7-7.1
6.4-6.7
N A = Not available.
CI = Confidence Intervals.
Source: U.S. EPA (2000).
June 2000
11-15
DRA
-------
1
2
3
4
5
6
7
8
Table 11-9. Summary of Recommended Values for Body Weight
Population
Mean
Upper Percent! le
Multiple Percent!les
Children
Infants
See Table 11-2
Not Available
See Tables 11-3 and 11-4 See Tables 11-3 and 11-4
See Table 11-1 See Table 11-1
June 2000
11-16
-------
1
.2
Table 11-10. Confidence in Body Weight Recommendations
Considerations
Rationale
Ratine
Study Elements
* Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data collection
period
• Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design
(high rating Is desirable)
Measurement error
NHANES II was the major source of data for NCHS (1987). This is a High
published study which received a high level of peer review. The Hamill et
al. (1979) is a peer reviewed journal publication.
Both studies are available to the public. High
Results can be reproduced by analyzing NHANES H data and the Pels High
Research Institute data..
The studies focused on body weight, the exposure factor of interest. High .
The data represent the U.S. population. High
The primary data were generated from NHANES II data and Pels studies. Medium
thus these data are secondary.
The data were collected between 1976-1980. Low
The NHANES II study included data collected over a period of 4 years. High
Body weight measurements were taken at various times of the day and at
different seasons of the year.
Direct body weights were measured for both studies. For NHANES II. High
subgroups at risk for malnutrition were over-sampled. Weighting was
accomplished by inflating examination results for those not examined and
were stratified by race. age. and sex. The Pels data are from an ongoing
longitudinal study where the data are collected regularly.
The sample size consisted of 28.000 persons for NHANES II. Author High
noted in Hamill et al. (1979) that the data set was large.
Data collected focused on the U.S. population for both studies. High
Both studies characterized variability regarding age and sex. Additionally High
NHANES II characterized race (for Blacks. Whites and total populations)
and sampled persons with low income.
There are no apparent biases in the study designs for NHANES 11. The Medium-
study design for collecting the pels data was not provided. High
For NHANES II. measurement error should be low since body weights High
were performed in a mobile examination center using standardized
procedures and equipment. Also, measurements were taken at various
times of the day to account for weight fluctuations as a result of recent
food or water intake. The authors of Hami 11 et al. (1979) report that study
data are based on accurate direct measurements from an ongoing
longitudinal studv.
Other Elements
• Number of studies
* Agreement between
researchers
Overall Rating
There are two studies.
There is consistency among the two studies.
Low
High
High
June 2000
11-17
DRA
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1 12. LIFETIME
2
3 12.1 INTRODUCTION
4 The length of an individual's life is an important factor to consider when evaluating
5 cancer risk because the dose estimate is averaged over an individual's lifetime. Since the
6 averaging time is found in the denominator of the dose equation, a shorter lifetime would result
7 in a higher potential risk estimate," and conversely, a longer life expectancy would produce a
8 lower potential risk estimate. Children have more years of future life than adults. Therefore,
9 they have more time to develop any chronic diseases that might be triggered by early
10 environmental exposures. Diseases initiated by chemical hazards require several decades to
11 develop, and early childhood exposure to certain carcinogens or toxicants is more likely to lead
12 to disease than the same exposures later in life (NRDC, 1997).
13
14 12.2 DATA ON LIFETIME
15 Statistical data on life expectancy are published annually by the U.S. Department of
Commerce in the publication: "Statistical Abstract of the United States." The latest year for
17 which statistics are available is 1993. Available data on life expectancies for various
18 subpopulations bom in the years 1980 to 1993 are presented in Table 12-1. Data for 1993 show
19 that the life expectancy for an average person born in the United States in 1993 is 75.5 years
20 (U.S. Bureau of the Census, 1999). The table shows that the overall life expectancy has averaged
21 approximately 75 years since 1982. The average life expectancy for males in 1993 was
22 . 72.2 years, and 78.8 years for females. The data consistently show an approximate 7 years
23 difference in life expectancy for males and females from 1980 to present. Table 12-1 also
24 indicates that the 1993 life expectancy for white males (73.1 years) is consistently longer than for
25 Black males (64.6 years). Additionally, it indicates that the 1993 life expectancy for White
26 females (79.5 years) is longer than for Black females (73.7), a difference of almost 6 years.
27 Table 12-1 also shows that the projected life expectancy for children born in the year 2000 (76.4
28 years) is longer than for those born in the 1980s (73.7 years). Table 12-2 presents data for
29 expectation of life for persons who were at a specific age in year 1996. These data are available
0 by age, gender, and race and may be useful for deriving exposure estimates based on the age of a
March 2000 12-1 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
specific subpopulation. The data show that expectation of life is longer for females and for
Whites.
12.3 RECOMMENDATIONS
Current data suggest that 75 years would be an appropriate value to reflect the -average •
life expectancy of children in the current general population and is the recommended value. If
gender is a factor considered in the assessment, note that the average life expectancy value for
females is higher than for males. It is recommended that the assessor use the 1993 value of 72.2
years for males or 78.8 years for females. If race is a consideration in assessing exposure for
male individuals, note that the life expectancy is about 8 years longer for Whites than for Blacks.
It is recommended that the assessor use the 1993 values of 73.1 years and 64.6 years for White
males and Black males, respectively. Table 12-3 presents the confidence rating for life
expectancy recommendations.
This recommended value is different than the 70 years commonly assumed for the general
population in EPA risk assessments. Assessors are encouraged to use values which most
accurately reflect the exposed population. When using values other than 70 years, however, the
assessors should consider if the dose estimate will be used to estimate risk by combining with a
dose-response relationship which was derived assuming a lifetime of 70 years. If such an
inconsistency exists, the assessor should adjust the dose-response relationship by multiplying by
(lifetime/70). The Integrated Risk Information System (IRIS) does not use a 70 year lifetime
assumption in the derivation of RfCs and RfDs, but does make this assumption in the derivation
of some cancer slope factors or unit risks.
March 2000
12-2
DRAFT-DO NOT QUOTE OR CITE
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1
I?
4
5
6
7
12.4 REFERENCES FOR CHAPTER 12
Natural Resources Defense Council. (1997) Our children at risk: the 5 worst environmental threats to their health.
U.S. Bureau of the Census. (1999) Statistical abstracts of the United States.
March 2000
12-3
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
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
Table 12-1. Expectation of Life at Birth, 1980 to 1993,
And Projections, 1995 to 2010 (Years)3
YEAR Total
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
73.7
74.1
74.5
74.6
74.7
74.7
74.7
74.9
74.9
75.1
75.4
75.5
75.8
75.5
TOTAL
Male Female Total
70.0 77.4 74.4
70.4 77.8 74.8
70.8 78.1 75.1
71.0 - 78.1 75.2
71.1 78.2 75.3
71.1 78.2 75.3
71.2 78.2 75.4
71.4 78.3 75.6
71.4 78.3 75.6
71.7 78.5 75.9
71.8 78.8 76.1
71.0 78.9 76.3
72.3 79.1 76.5
72.2 78.8 76.3
WHITE
Male
70.7
71.1
71.5
71.6
71.8
71.8
71.9
72.1
72.2
72.5
72.7
72.9
73.2
73.1
BLACK AND OTHERb
Female
78.1
78.4
78.7
78.7
78.7
78.7
78.8
78.9
78.9
79.2
79.4
79.6
79.8
79.5
Total
69.5
70.3
70.9
70.9
71.1
71.0
70.9
71.0
70.8
70.9
71.2
71.5
71.8
71.5
Male
65.3
66.2
66.8
67.0
67.2
67.0
66.8
66.9
66.7
66.7
67.0
67.3
67.7
67.3
Female
73.6
74.4
74.9
74.7
74.9
74.8
74.9
75.0
74.8
74.9
75.2
75.5
75.7
75.5
Total
68.1
68.9
69.4
69.4
69.5
69.3
69.1
69.1
68.9
68.8
69.1
69.3
69.6
69.2
BLACK.
Male
63.8
64.5
65.1
65.2
65.3
65.0
64.8
64.7
64.4
64.3
64.5
64.6
65.0
64.6
Female
72.5
73.2
73.6
73.5
73.6
73.4
73.4
73.4
73.2
73.3
73.6
73.8
73.9
73.7
Projections'
1995
2000
2005
2010
75.8
76.4
76.9
77.4
aExcludes deaths
"Racial
'Based
72.5 78.9 76.5
73.0 79.7 77.4
73.8 80.2 77.9
74.1 80.6 78.6
of nonresidents of the United
73.4
74.2
74.7
75.5
States.
79.6
80.5
81.0
81.6
71.9
NA
NA
NA
67.9
NA
NA
NA
75.7
NA
NA
NA
69.6
69.7
69.9
70.4
65.2
64.6
64.5
65.1
73.9
74.7
75.0
75.5
descriptions were not provided in the data source.
on middle
Series P-25, No. 1
mortality assumptions: for details, see
1130.
U.S. Bureau of the Census, Current
Population Reports,
Source: Bureau of the Census (1999).
March 2000
12-4
DRAFT-DO NOT QUOTE OR CITE
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1
1:
3
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Tabie 12-2. Expectation of Life by Race, Sex, And Age: 1996
Expectation of Life in Years
White
Black
Age in 1990
(years)
At birth
1
7
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Total
76.1
75.7
74.7
73.7
72.8
.71.8
70.8
. 69.8
68.8
67.8
. 66.9
65.9
64.9
63.9
t
62.9
. 61.9
61.0
60.0
59.1
58.1
Male
73.9
73.4
72.4
71.4
70.5
69.5 . .
68.5
67.5
- 66.5
65.5 .
64.5
63.5
62.6
61.6
60.6
59.6
58.8
57.7
56.8
55.8
Female
79.7
79.1
78.1
77.1
76.2
75.2
75.2
73.2
72.2
71.2
70.2
69.2
68.3
67.3
66.3
65.3
64.3
63.3
62.4
61.4 ,
Male
66.1
66.2
65.2
64.3
63.3
62.4
61.4
60.4
59.4
58.4
57.5
56:5
55.5
54.5
53.5
52.6
51.6
50.7
49.8
48.9
Female
742
74.2
73.2
72.3
71.3
70.3
69.4
68.4
67.4
66.4
65.4
64.4
63.4
62.5
61.5
60.5
59.5
58.6
57.6
56.6
Source: U.S. Bureau of Census (1999).
March 2000
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Table 12-3. Confidence in Lifetime Expectancy Recommendations
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Considerations
Study Elements
* Level of peer review
• Accessibility
• Reproducibility
• Focus on factor of interest
• Data pertinent to US
• Primary data
• Currency
• Adequacy of data collection period
• Validity of approach
* Study size
• Representativeness of the population
• Characterization of variability
• Lack of bias in study design (High
rating is desirabie)
• Measurement error
Other Elements
• Number of studies
• Agreement between researchers
Overall Rating
Rationale
Data are published and have received extensive peer
review.
The study was widely available to the public (Census
data).
Results can be reproduced by analyzing Census data.
Statistical data on life expectancy were published in this
study.
The study focused on the U.S. population.
Primary data were analyzed.
The study was published in 1995 and discusses life
expectancy trends from 1 970 to 1993. The study has also
made projections for 1995 until the year 2010.
The data analyzed were collected over a period of years.
Census data is collected and analyzed over a period of
years.
This study was based on U.S. Census data, thus the
population study size is expected to be greater than 1 00.
The data are representative of the U.S. population. -
Data were averaged by gender and race but only for Blacks
and Whites; no other nationalities were represented within
the section.
There are no apparent biases.
Measurement error may be attributed to portions of the
population that avoid or provide misleading information
on census surveys.
Data presented in the section are from the U.S. Bureau of
the Census publication.
Recommendation was based on only one study, but it is
widely accepted.
Rating
High
High '
. High
: High "
High" '
High
High|-
High ^:r
High >v~
Hidh ">•'"- ' ••
nign
High -
Medium"
High
Medium
Low >'.
High. -ft
High
March 2000
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