Child-Spftcffic
Exposure Factors
Handbook

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Child-Specific Exposure Factors Handbook
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                                     DISCLAIMER

       This document has been reviewed in accordance with U.S. Environmental Protection Agency policy and
approved for publication.  Mention of trade names or commercial products does not constitute endorsement or
recommendation for use.
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                                TABLE OF CONTENTS

      INTRODUCTION	
      1.1    PURPOSE 	
      1.2    INTENDED AUDIENCE	
      1.3    BACKGROUND 	
      1.4    SELECTION OF STUDIES FOR THE HANDBOOK  	
             1.4.1   General Assessment Factors	
             1.4.2   Selection Criteria	
      1.5    APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
             FACTORS 	
      1.6    SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS HANDBOOK
      1.7    THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE 	
-1
-1
-1
-1
-3
-4
-4
-6
-9
       1.8    CONSIDERING LIFESTAGE WHEN CALCULATING EXPOSURE AND RISK  	1-11
       1.9    FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT 	1-11
             1.9.1   Dose Equations	1-12
             1.9.2   Use of Exposure Factors Data in Probabilistic Analyses 	1-14
       1.10   CUMULATIVE EXPOSURES	1-15
       1.11   ORGANIZATION	1-15
       1.12   REFERENCES FOR CHAPTER 1	1-16

       VARIABILITY AND UNCERTAINTY	2-1
       2.1    VARIABILITY VERSUS UNCERTAINTY	2-2
       2.2    TYPES OF VARIABILITY	2-2
       2.3    ADDRESSING VARIABILITY	2-3
       2.4    TYPES OF UNCERTAINTY	2-4
       2.5    REDUCING UNCERTAINTY	2-4
       2.6    ANALYZING VARIABILITY AND UNCERTAINTY	2-4
       2.7    PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS 	2-5
       2.8    REFERENCES FOR CHAPTER 2	2-6

       INGESTION OF WATER AND OTHER SELECT LIQUIDS	3-1
       3.1    INTRODUCTION	3-1
       3.2    RECOMMENDATIONS 	3-2
             3.2.1   Water Ingestion from Consumption of Water as a Beverage and from Food
                   and Drink	3-2
             3.2.2   Water Ingestion while Swimming	3-2
       3.3    DRINKING WATER INGESTION STUDIES	3-6
             3.3.1   Key Drinking Water Ingestion Study 	3-6
                   3.3.1.1 Kahn and Stralka, 2008  	3-6
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3.4

3.5
TABLE OF CONTENTS (Continued)
3.3.2 Relevant Drinking Water Ingestion Studies 	
3.3.2.1 Levyetal., 1995 	
3.3.2.2 Heller et al., 2000 	
3.3.2.3 Sichert-Hellert et al., 2001 	
3.3.2.4 Sohn et al., 2001 	
3.3.2.5 Hilbig et al., 2002 	
3.3.2.6 Marshall et al., 2003a 	
3.3.2.7 Marshall et al., 2003b 	
3.3.2.8 Skinner et al., 2004 	
WATER INGESTION WHILE SWIMMING 	
3.4.1 Dufour et al., 2006 	
REFERENCES FOR CHAPTER 3 	
4 NON-DIETARY INGESTION FACTORS 	
4.1
4.2
4.3





4.4




INTRODUCTION 	
RECOMMENDATIONS 	
NON-DIETARY INGESTION - MOUTHING FREQUENCY STUDIES 	
4.3.1 Key Studies of Mouthing Frequency 	
4.3. .1 Zartarian et al.,1997a/Zartarian et al., 1997b/Zartarian et al., 1998 . .
4.3. .2 Reed et al., 1999 	
4.3. .3 Freeman et al., 2001 	
4.3. .4 Tulve et al., 2002 	
4.3. .5 Black et al., 2005 	
4.3. .6 Xue et al., 2007 	
4.3.2 Relevant Studies of Mouthing Frequency 	
4.3.2.1 Davis etal., 1995 	
4.3.2.2 Lew and Butterworth, 1997 	
4323 Tudella et al 2000
4324 AuYeung et al 2004
4325 Ko et al 2007
NON-DIETARY INGESTION - MOUTHING DURATION STUDIES
441 Key Mouthing Duration Studies
4411 Jubergetal 2001
4412 Greene 2002
4.4.2 Relevant Mouthing Duration Studies 	
4.4.2.1 Barr et al., 1994 	
4.4.2.2 Zartarian et al., 1997 'a/ 'Zartarian et al., 1997b/Zartarian et al., 1998 .
4.4.2.3 Groot et al., 1998 	
4.4.2.4 Smith and Norris, 2003/Norris and Smith, 2002 	
4.4.2.5 Au Yeung et al, 2004 	
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.... 3-8
.... 3-8
.... 3-9
. . . 3-10
. . . 3-10
. . . 3-11
. . . 3-11
. . . 3-11
. . . 3-11
. . . 3-12
.... 4-1
.... 4-1
.... 4-2
.... 4-5
.... 4-5
.... 4-5
.... 4-5
.... 4-6
.... 4-7
.... 4-7
.... 4-8
.... 4-8
.... 4-8
4-9
4-10
4-10
4-11
4-12
4-12
4-12
4-12
. . . 4-13
. . . 4-13
. . . 4-14
. . . 4-14
. . . 4-15
. . . 4-16
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                          TABLE OF CONTENTS (Continued)

      4.5    MOUTHING PREVALENCE  	4-17
            4.5.1   Stanek et al., 1998 	4-17
            4.5.2   Warren et al., 2000	4-18
      4.6    REFERENCES FOR CHAPTER 4	4-18
SOIL AND DUST INGESTION 	
5.1 INTRODUCTION 	
5.2 RECOMMENDATIONS 	
5.3 KEY AND RELEVANT STUDIES 	
5.3.1



5.3.2







5.3.3


5.3.4








5.3.5






Methodologies Used in Key Studies 	
5.3.1.1 Tracer Element Methodology 	
5.3.1.2 Biokinetic Model Comparison Methodology 	
5.3.1.3 Survey Response Methodology 	
Key Studies of Primary Analysis 	
5.3.2.1 Vermeer and Frate, 1979 	
5.3.2.2 Calabrese et al., 1989/Barnes, 1990/Calabrese et al., 1991 	
5.3.2.3 Van Wijnen et al., 1990 	
5.3.2.4 Davis et al., 1990 	
5.3.2.5 Calabrese et al., 1997a 	
5.3.2.6 Stanek et al. 1998/Calabrese et al., 1997b 	
5.3.2.7 Davis and Mirick, 2006 	
Key Studies of Secondary Analysis 	
5.3.3.1 Wong, 1988/Calabrese and Stanek, 1993 	
5.3.3.2 Hogan et al., 1998 	
Relevant Studies of Primary Analysis 	
5.3.4.1 Dickins and Ford, 1942 	
5.3.4.2 Cooper, 1957 	
5343 Barltrop 1966
5344 Bruhn and Pangborn 1971
5345 Robischon 1971
5346 Binder et al 1986
5347 Clausing et al 1987

5348 Smulian et al 1995
Relevant Studies of Secondary Analysis

5.3.5.1 Stanek et al., 2001a 	
5.3.5.2 Calabrese and Stanek, 1995 	
5.3.5.3 Stanek and Calabrese, 1995a 	
5.3.5.4 Calabrese and Stanek, 1992b 	
5.3.5.5 Calabrese et al., 1996 	
5.3.5.6 Stanek et al., 1999 	
	 5-1
	 5-1
	 5-2
	 5-7
	 5-7
	 5-7
	 5-8
	 5-8
	 5-9
	 5-9
	 5-9
	 5-10
	 5-10
	 5-11
	 5-11
	 5-12
	 5-12
	 5-12
	 5-13
	 5-13
	 5-14
	 5-14
5-14
5-14
5-14
5-15
5-15

5-16
5-16

	 5-16
	 5-17
	 5-17
	 5-18
	 5-18
	 5-19
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6


















7








TABLE OF CONTENTS (Continued)
5.3.5.7 Stanek and Calabrese, 1995b 	
5.3.5.8 Stanek and Calabrese, 2000 	
5.3.5.9 Stanek et al., 200 Ib 	
5.3.5.10 von Lindern et al., 2003 	
5.4 LIMITATIONS OF KEY STUDY METHODOLOGIES 	
5.4. 1 Tracer Element Methodology 	
5.4.2 Biokinetic Model Comparison Methodology 	
5.4.3 Survey Response Methodology 	
5.4.4 Key Studies: Representativeness of U.S. Population 	
5.5 SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES .
5.6 REFERENCES FOR CHAPTER 5 	
INHALATION RATES 	
6.1 INTRODUCTION 	
6.2 RECOMMENDATIONS 	
6.3 KEY INHALATION RATE STUDIES 	
6.3.1 Brochu et al., 2006 	
6.3.2 U.S. EPA, 2006 	
6.3.3 Arcus-Arth and Blaisdell, 2007 	
6.3.4 Stifelman, 2007 	
6.3.5 Key Studies Combined 	
6.4 RELEVANT INHALATION RATE STUDIES 	
6.4.1 International Commission on Radiological Protection (ICRP), 1981 	
6.4.2 U.S. EPA, 1985 	
6.4.3 Linn et al., 1992 	
6.4.4 Spier et al., 1992 	
6.4.5 Adams, 1993 	
646 Layton 1993
647 Rusconi et al 1994
648 Price et al 2003
6 5 REFERENCES FOR CHAPTER 6
DERMAL EXPOSURE FACTORS
7 1 INTRODUCTION
7 2 RECOMMENDATIONS
7.2. 1 Body Surface Area 	
7.2.2 Adherence of Solids to Skin 	
7.3 SURFACE AREA 	
7.3. 1 Key Body Surface Area Studies 	
7.3.1.1 U.S. EPA, 1985 	
7.3.1.2 U.S. EPA Analysis of NHANES 1999-2006 Data 	
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. . 5-19
. . 5-19
. . 5-20
. . 5-20
. . 5-20
. . 5-23
. . 5-23
. . 5-24
. . 5-25
. . 5-26
... 6-1
... 6-1
... 6-2
... 6-6
... 6-6
... 6-6
... 6-8
... 6-9
... 6-9
... 6-9
... 6-9
. . 6-10
. . 6-10
. . 6-11
. . 6-11
6-12
6-14
6-14
6-15
7-1
7-1
7-2
... 7-2
... 7-2
. . 7-10
. . 7-10
. . 7-10
. . 7-10
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                              TABLE OF CONTENTS (Continued)

              7.3.2   Relevant Body Surface Area Studies	7-10
                     7.3.2.1  Phillips et al., 1993	7-10
                     7.3.2.2  Wongetal., 2000	7-11
       7.4    ADHERENCE OF SOLIDS TO SKIN	7-11
              7.4.1   Key Adherence of Solids to Skin Studies  	7-11
                     7.4.1.1  Kissel etal, 1996a	7-11
                     7.4.1.2  Holmes etal., 1999	7-12
                     7.4.1.3  Shoaf etal., 2005 	7-12
              7.4.2   Relevant Adherence of Solids to Skin Studies	7-13
                     7.4.2.1  Kissel et al., 1996b	7-13
                     7.4.2.2  Kissel et al., 1998	7-13
       7.5    REFERENCES FOR CHAPTER 7	7-14

APPENDIX 7A	  7A-1

8      BODY WEIGHT STUDIES	8-1
       8.1    INTRODUCTION	8-1
       8.2    RECOMMENDATIONS 	8-1
       8.3    KEY BODY WEIGHT STUDY	8-4
              8.3.1   U.S. EPA analysis of NHANES 1999-2006 data  	8-4
       8.4    RELEVANT BODY WEIGHT STUDIES 	8-4
              8.4.1   National Center for Health Statistics, 1987  	8-4
              8.4.2   Burmaster and Crouch, 1997 	8-5
              8.4.3   U.S. EPA, 2000  	8-5
              8.4.4   Kuczmarski et al., 2002  	8-5
              8.4.5   Ogden et al., 2004  	8-6
              8.4.6   Freedman et al., 2006	8-6
              8.4.7   Martin et al., 2007 	8-7
              8.4.8   Portier et al., 2007  	8-7
              8.4.9   Kahn and Stralka, 2008  	8-8
       8.5    RELEVANT FETAL WEIGHT STUDIES	8-8
              8.5.1   Brenner et al., 1976  	8-8
              8.5.2   Doubilet et al., 1997	8-8
       8.6    REFERENCES FOR CHAPTER 8	8-9

9      INTAKE OF FRUITS AND VEGETABLES	9-1
       9.1    INTRODUCTION	9-1
       9.2    RECOMMENDATIONS 	9-2
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                               TABLE OF CONTENTS (Continued)

       9.3     INTAKE STUDIES	9-6
               9.3.1    Key Fruits and Vegetables Intake Study	9-6
                      9.3.1.1  U.S. EPA Analysis of CSFII 1994-96, 1998  	9-6
               9.3.2    Relevant Fruit and Vegetable Intake Studies	9-8
                      9.3.2.1  USDA,  1999  	9-8
                      9.3.2.2  Smiciklas-Wright et al., 2003   	9-8
                      9.3.2.3  Fox et al., 2004  	9-9
                      9.3.2.4  Ponza et al., 2004	9-9
                      9.3.2.5  Menella et al., 2006  	9-10
                      9.3.2.6  Fox et al., 2006	9-10
       9.4     CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	9-10
       9.5     REFERENCES FOR CHAPTER 9	9-11

 APPENDIX 9A  	  9A-1

10     INTAKE OF FISH AND SHELLFISH	10-1
       10.1     INTRODUCTION	10-1
       10.2     RECOMMENDATIONS  	10-2
       10.3     GENERAL POPULATION STUDIES   	10-6
               10.3.1   Key General Population Study  	10-6
                      10.3.1.1 U.S. EPA 2002  	10-6
               10.3.2   Relevant General Population Studies 	10-6
                      10.3.2.1 U.S. EPA, 1996  	10-6
                      10.3.2.2 Moya et al., 2008  	10-7
       10.4     MARINE RECREATIONAL STUDIES	10-8
               10.4.1   Relevant Marine Recreational Studies	10-8
                      10.4.1.1 KCA Research Division, 1994  	10-8
                      10.4.1.2 Alcoa, 1998  	10-8
       10.5     FRESHWATER RECREATIONAL STUDIES	10-9
               10.5.1   Relevant Freshwater Recreational Studies	10-9
                      10.5.1.1 Westetal., 1989   	10-9
                      10.5.1.2 Benson  etal.,  2001   	10-10
       10.6     NATIVE AMERICAN STUDIES  	10-10
               10.6.1   Relevant Native American Studies	10-10
                      10.6.1.1 Columbia River Inter-Tribal Fish Commission (CRITFC), 1994   	10-10
                      10.6.1.2 Toy etal., 1996  	10-12
                      10.6.1.3 Duncan, 2000 	10-13
                      10.6.1.4 Polissar et al., 2006  	10-13
       10.7     SERVING SIZE STUDY	10-14
               10.7.1   Smiciklas-Wright et al., 2002  	10-14
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                              TABLE OF CONTENTS (Continued)

       10.8    OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION 	10-14
              10.8.1  Conversion Between Wet and Dry Weight 	10-14
              10.8.2  Conversion Between Wet Weight and Lipid Weight Intake Rates	10-15
       10.9    REFERENCES FOR CHAPTER 10	10-15

11     INTAKE OF MEATS, DAIRY PRODUCTS AND FATS 	11-1
       11.1    INTRODUCTION	11-1
       11.2    RECOMMENDATIONS  	11-2
       11.3    INTAKE STUDIES	11-6
              11.3.1  Key Meat and Diary Intake Study	11-6
                     11.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 	11-6
              11.3.2  Relevant Meat and Dairy Intake Studies	11-7
                     11.3.2.1 USDA, 1999a	11-7
                     11.3.2.2 Smiciklas-Wright et al., 2002	11-8
                     11.3.2.3 Fox etal., 2004	11-8
                     11.3.2.4 Ponzaetal., 2004	11-9
                     11.3.2.5 Mennella et al., 2006  	11-9
                     11.3.2.6 Fox etal., 2006	11-10
       11.4    FAT INTAKE  	11-10
              11.4.1  Key Fat Intake Study 	11-10
                     11.4.1.1 U.S. EPA,  2007  	11-10
              11.4.2  Relevant Fat Intake Studies 	11-11
                     11.4.2.1 Cresanta et al., 1988; Nicklas et al.,  1993; and Frank etal., 1986	11-11
                     11.4.2.2 CDC, 1994	11-11
       11.5    CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	11-12
       11.6    CONVERSION BETWEEN WET WEIGHT AND LIPID WEIGHT INTAKE RATES  . . . 11-12
       11.7    REFERENCES FOR CHAPTER 11	11-12

APPENDIX 11A	  11A-1

APPENDIX 11B	  11B-1

12     INTAKE OF GRAIN PRODUCTS 	12-1
       12.1    INTRODUCTION	12-1
       12.2    RECOMMENDATIONS  	12-2
       12.3    INTAKE STUDIES	12-6
              12.3.1  Key Grain Intake Study  	12-6
                     12.3.1.1        U.S. EPA Analysis of CSFII 1994-96, 1998 	12-6
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                             TABLE OF CONTENTS (Continued)

              12.3.2  Relevant Grain Intake Studies  	12-7
                    12.3.2.1        USDA, 1999	12-7
                    12.3.2.2        Smiciklas-Wright et al., 2002 	12-8
                    12.3.2.3        Fox et al., 2004   	12-8
                    12.3.2.4        Ponza et al., 2004  	12-9
                    12.3.2.5        Mennella et al., 2006   	12-9
                    12.3.2.6        Fox et al., 2006   	12-10
       12.4    CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	12-10
       12.5    REFERENCES FOR CHAPTER 12	12-10

APPENDIX 12A 	  12A-1

13     INTAKE OF HOME-PRODUCED FOODS	13-1
       13.1    INTRODUCTION	13-1
       13.2    RECOMMENDATIONS  	13-1
       13.3    KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS	13-6
              13.3.1  U.S. EPA Analysis of NFCS 1987-1988	13-6
       13.4    REFERENCES FOR CHAPTER 13	13-8

APPENDIX 13A  	  13A-1
APPENDIX 13B  	  13B-1

14     TOTAL DIETARY INTAKE	14-1
       14.1    INTRODUCTION	14-1
       14.2    RECOMMENDATIONS  	14-1
       14.3    KEY STUDY OF TOTAL FOOD INTAKE	14-4
              14.3.1  U.S. EPA, 2007  	14-4
       14.4    REFERENCES FOR CHAPTER 14	14-5

15     HUMAN MILK INTAKE  	15-1
       15.1    INTRODUCTION	15-1
       15.2    RECOMMENDATIONS  	15-1
              15.2.1  Human Milk Intake  	15-2
              15.2.2  Lipid Content and Lipid Intake	15-2
       15.3    KEY STUDIES ON HUMAN MILK INTAKE	15-10
              15.3.1  Paoetal.,  1980	15-10
              15.3.2  Dewey and Lonnerdal, 1983	15-10
              15.3.3  Butte et al., 1984  	15-10
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                               TABLE OF CONTENTS (Continued)

               15.3.4  Neville et al., 1988	15-11
               15.3.5  Deweyetal., 1991a,b	15-11
               15.3.6  Butte, et al., 2000  	15-12
               15.3.7  Arcus-Arth et al., 2005   	15-13
        15.4    KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK . . . 15-13
               15.4.1  Butte etal., 1984 	15-14
               15.4.2  Mitoulas et al., 2002  	15-14
               15.4.3  Mitoulas et al., 2003  	15-15
               15.4.4  Arcus-Arth et al., 2005   	15-15
               15.4.5  Kent et al., 2006  	15-15
        15.5    RELEVANT STUDY ON LIPID  INTAKE FROM HUMAN MILK 	15-16
               15.5.1  Maxwell and Burmaster,  1993  	15-16
        15.6    OTHERFACTORS 	15-16
               15.6.1  Population of Nursing Infants	15-16
               15.6.2  Intake Rates Based on Nutritional Status 	15-19
               15.6.3  Frequency and Duration of Feeding  	15-19
        15.7    REFERENCES FOR CHAPTER 15	15-20

 16      ACTIVITY FACTORS  	16-1
        16.1    INTRODUCTION	16-1
        16.2    RECOMMENDATIONS 	16-1
        16.3    ACTIVITY PATTERNS  	16-7
               16.3.1  KEY STUDIES  	16-7
                      16.3.1.1 Wiley etal.,  1991  	16-7
                      16.3.1.2 U.S. EPA, 1996   	16-8
               16.3.2  RELEVANT STUDIES  	16-9
                      16.3.2.1 Timmer et al., 1985  	16-9
                      16.3.2.2 Robinson and Thomas, 1991  	16-10
                      16.3.2.3 Funk etal., 1998  	16-11
                      16.3.2.4 U.S. EPA, 2000   	16-11
                      16.3.2.5 Hubal et al.,  2000	16-12
                      16.3.2.6 Wong et al.,  2000	16-12
                      16.3.2.7 Graham and McCurdy, 2004  	16-13
                      16.3.2.8 Vandewater  et al., 2004  	16-14
                      16.3.2.9 Juster et al. (2004)  	16-14
                      16.3.2.10       U.S. Department of Labor, 2007  	16-15
                      16.3.2.11       Nader etal. 2008	16-15
        16.4    REFERENCES FOR CHAPTER 16	16-15
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                           TABLE OF CONTENTS (Continued)

 17     CONSUMER PRODUCTS 	17-1
       17.1    INTRODUCTION	17-1
       17.2    RECOMMENDATIONS 	17-2
       17.3    CONSUMER PRODUCTS USE STUDIES  	17-2
             17.3.1  CTFA, 1983	17-2
             17.3.2  U.S. EPA, 1996 	17-2
             17.3.3  Bass et al, 2001  	17-3
             17.3.4  Loretz et al., 2005  	17-4
             17.3.5  Loretz et al., 2006  	17-4
             17.3.6  Loretz et al., 2008  	17-5
             17.3.7  Sathyanarayana et al., 2008  	17-5
       17.4    REFERENCES FOR CHAPTER 17	17-5

       GLOSSARY OF TERMS	 G-l
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Table 1-1.
Table 1-2.
Table 1-3.



Table 2-1.
Table 2-2.
Table 2-3.
Table 3-1.
Table 3-2.
Table 3-3.
Table 3-4.

Table 3-5.

Table 3-6.

Table 3-7.

Table 3-8.

Table 3-9.

Table 3-10.

Table 3-11.

Table 3-12.

Table 3-13.

Table 3-14.

Table 3-15.

Table 3-16.

Table 3-17.


Page
xii
LIST OF TABLES
Characterization of Variability in Exposure Factors 	 1-21
Considerations Used to Rate Confidence in Recommended Values 	 1-22
Integrating U.S. EPA's Guidance on Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants with U.S. EPA's Supplemental Guidance
for Assessing Susceptibility from Early-Life Exposure to Carcinogens For Those
Contaminants Which Act Via a Mutagenic Mode of Action 	 1-24
Four Strategies for Confronting Variability 	 2-9
Three Types of Uncertainty and Associated Sources and Examples 	 2-9
Approaches to Quantitative Analysis of Uncertainty 	 2-10
Recommended Values for Drinking Water Ingestion Rates 	 3-3
Confidence in Recommendations for Drinking Water Ingestion Rates 	 3-4
Confidence in Recommendations for Water Ingestion while Swimming 	 3-5
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Community Water (mL/day) 	 3-14
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Bottled Water (mL/day) 	 3-14
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Other Sources (mL/day) 	 3-15
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
All Sources (mL/day) 	 3-15
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
All Sources (mL/day) 	 3-16
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Community Water (mL/kg-day) 	 3-17
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Bottled Water (mL/kg-day) 	 3-17
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
Other Sources (mL/kg-day) 3-18
Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
All Sources (mL/kg-day) 3-18
Per Capita Estimates of Total Direct and Indirect Water Ingestion:
All Sources (mL/kg-day) 3-19
Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
Community Water (mL/day) 3-20
Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
Bottled Water (mL/day) 3-20
Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
Other Sources (mL/day) 3-21
Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
All Sources (mL/day) 3-21

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                                                                                   CSEFH
                                   LIST OF TABLES (Continued)

Table 3-18.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/day)	3-22
Table 3-19.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Community Water (mL/kg-day)	3-23
Table 3-20.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Bottled Water (mL/kg-day)   	3-23
Table 3-21.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Other Sources (mL/kg-day)   	3-24
Table 3-22.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               All Sources (mL/kg-day)  	3-24
Table 3-23.     Consumer Only Estimates of Total Direct and Indirect Water Ingestion (mL/kg-day)	3-25
Table 3-24.     Water Ingested (mL/day) from Water By Itself and Water Added to Other Beverages
               and Foods	3-26
Table 3-25.     Mean Water Consumption (mL/kg-day) by Race/Ethnicity	3-27
Table 3-26      Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and
               Poverty Category 	3-28
Table 3-27.     Intake of Water from Various Sources in 2-13-y-old Participants of the
               DONALD Study 1985-1999	3-29
Table 3-28.     Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years,
               NHANES III, 1988-94	3-30
Table 3-29.     Estimated Mean (± Standard Error)  Amount of Total Fluid and Plain Water Intake
               among Children Aged 1-10 Years: (NHANES III, 1988-94)	3-31
Table 3-30.     Tap Water Intake in Breastfed and Formula-fed Infants and Mixed-fed Young Children at
               Different Age Points	3-32
Table 3-31.     Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day)
               for Children With Returned Questionnaires	3-33
Table 3-32.     Mean (± Standard Deviation) Daily Beverage Intakes  Reported on Beverage Frequency
               Questionnaire and 3-day Food and Beverage Dairies  	3-34
Table 3-33.     Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) . . 3-35
Table 3-34.     Pool Water Ingestion by Swimmers  	3-36

Table 4-1.      Summary of Recommended Values for Mouthing Frequency and Duration 	4-3
Table 4-2.      Confidence in Recommendations for Mouthing Frequency and Duration	4-4
Table 4-3.      New Jersey Children's Mouthing Frequency (contacts/hour) from Video-transcription	4-20
Table 4-4.      Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age	4-20
Table 4-5.      Video-transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
               (contacts/hour)	4-20
Table 4-6.      Variability in Objects Mouthed by Washington State Children (contacts/hour)	4-21
Table 4-7.      Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD)	4-22
Table 4-8.      Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
               Studies	4-22
Table 4-9.      Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
               Studies	4-22
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                                    LIST OF TABLES (Continued)

Table 4-10.      Survey Reported Mouthing Behaviors for 92 Washington State Children	4-23
Table 4-11.      Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children
                with >15 minutes in View Indoors	4-23
Table 4-12.      Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children .... 4-24
Table 4-13.      Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
                Other Objects	4-25
Table 4-14.      Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category
                and Child's Age  	4-25
Table 4-15.      Estimates of Mouthing Time for Various Objects (minutes/hour)	4-26
Table 4-16.      Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without
                Pacifier, in Minutes per Day	4-28
Table 4-17.      Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys,
                and Other Objects (hours:minutes:seconds)  	4-29
Table 4-18.      Outdoor Median Mouthing Duration (Seconds per contact), Video-transcription
                of 38 Children	4-30
Table 4-19.      Indoor Mouthing Duration (Minutes per hour), Video-transcription of 9 Children
                with >15 minutes in View Indoors	4-30
Table 4-20.      Outdoor Mouthing Duration (Minutes per hour), Video-transcription of 38 Children	4-31
Table 4-21.      Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
                Behaviors	4-32

Table 5-1.       Recommended Values for Soil, Dust, and Soil  + Dust Ingestion  	5-5
Table 5-2.       Confidence in Recommendations for Ingestion of  Soil and Dust  	5-6
Table 5-3.       Soil, Dust and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
                Children	5-31
Table 5-4.       Amherst, Massachusetts Soil-Pica Child's Daily Ingestion Estimates by Tracer and by
                Week (mg/day)	5-32
Table 5-5.       Amherst, Massachusetts Soil-Pica Child's Tracer  Ratios 	5-33
Table 5-6.       Van Wijnen et al.,  1990 Limiting Tracer Method  (LTM) Soil Ingestion Estimates for
                Sample of Dutch Children	5-34
Table 5-7.       Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children
                Attending Daycare Centers According to Age,  Weather Category, and Sampling
                Period 	5-35
Table 5-8.       Estimated Soil Ingestion for Sample of Washington State Children	5-35
Table 5-9.       Soil Ingestion Estimates for 64 Anaconda Children	5-36
Table 5-10.      Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior
                (mg/day)  	5-36
Table 5-11.      Soil Ingestion Estimates for Sample of 12 Washington State Children	5-37
Table 5-12.      Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children  	5-38
Table 5-13.      Estimated Daily Soil Ingestion for East Helena, Montana Children  	5-39
Table 5-14.      Estimated Soil Ingestion for Sample of Dutch Nursery School Children	5-39
Table 5-15.      Estimated Soil Ingestion for Sample of Dutch  Hospitalized, Bedridden Children	5-40
Table 5-16.      Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
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                Study: Effect on Mean Soil Ingestion Estimate (mg/day)	5-40
Table 5-17.      Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64
                Children (mg/day)  	5-41
Table 5-18.      Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects
                Projected over 365 Days	5-41
Table 5-19.      Summary of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from
                Key Studies (mg/day)	5-42

Table 6-1.       Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation
                (Males and Females Combined)	6-3
Table 6-2.       Recommended Short-Term Exposure (Less Than 30 Days) Values for Inhalation
                (Males and Females Combined)	6-4
Table 6-3.       Confidence in Recommendations for Inhalation Rates 	6-5
Table 6-4.       Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less	6-17
Table 6-5.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
                Normal-weight Males and Females Aged 2.6 months to 23 years   	6-18
Table 6-6.       Mean and 95th Percentile Inhalation Rate Values (mVday) for Free-living Normal-weight
                Males, Females, and Males and Females Combined	6-19
Table 6-7.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
                Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years	6-20
Table 6-8.       Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight
                (mVkg-day) for Free-living Normal-weight Males and Females Aged 2.6 months
                to 23 years	6-21
Table 6-9.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVkg-day) for Free-living
                Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years	6-22
Table 6-10.      Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category	6-23
Table 6-11.      Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category	6-24
Table 6-12.      Mean and 95th Percentile Inhalation Rate Values (mVday) for Males, Females and
                Males and Females Combined 	6-25
Table 6-13.      Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
                Specified Activity Category, for Males by Age Category	6-26
Table 6-14.      Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
                Specified Activity Category, for Females  by Age Category  	6-28
Table 6-15.      Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
                Within the Specified Activity Category, by Age and Gender Categories	6-30
Table 6-16.      Nonnormalized Daily Inhalation Rates (mVday) Derived Using Layton's (1993)
                Method and CSFII Energy Intake Data	6-32
Table 6-17.      Mean and 95th Percentile Inhalation Rate Values (mVday) for Males and Females
                Combined 	6-33
Table 6-18.      Summary of Institute of Medicine Energy Expenditure Recommendations
                for Active and Very Active People with Equivalent Inhalation Rates  	6-34
Table 6-19.      Mean Inhalation Rate Values (mVday) for Males, Females, and Males and Females
                Combined 	6-35
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                                    LIST OF TABLES (Continued)

Table 6-20.      Mean Inhalation Rate Values (mVday) from Key Studies for Males and Females
                Combined  	6-36
Table 6-21.      95th Percentile Inhalation Rate Values (mVday) from Key Studies for Males and Females
                Combined  	6-37
Table 6-22.      Daily Inhalation Rates Estimated From Daily Activities	6-38
Table 6-23.      Selected Inhalation Rate Values During Different Activity Levels Obtained From Various
                Literature Sources  	6-39
Table 6-24.      Summary of Human Inhalation Rates for Children by Activity Level (mVhour)  	6-40
Table 6-25.      Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for
                All Age Groups 	6-40
Table 6-26.      Summary of Daily Inhalation Rates Grouped by Age and Activity Level 	6-41
Table 6-27.      Calibration and Field Protocols for Self-monitoring of Activities Grouped by
                Subject Panels  	6-42
Table 6-28.      Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated
                Breathing Rates	6-42
Table 6-29.      Distribution of Predicted Inhalation Rates by Location and Activity Levels for Elementary
                and High School Students  	6-43
Table 6-30.      Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and
                High School Students	6-44
Table 6-31.      Summary of Average Inhalation Rates (mVhour) by Age Group and Activity Levels for
                Laboratory Protocols 	6-45
Table 6-32.      Summary of Average Inhalation Rates (mVhour) by Age Group And Activity Levels in Field
                Protocols  	6-46
Table 6-33.      Mean Minute Inhalation Rate (mVminute) by Group and Activity for Laboratory Protocols  . 6-47
Table 6-34.      Mean Minute Inhalation Rate (mVminute) by Group and Activity for Field Protocols	6-47
Table 6-35.      Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy
                Intakes (EFD) for Individuals Sampled in the 1977-78 NFCS   	6-48
Table 6-36.      Daily Inhalation Rates Calculated from Food-energy Intakes	6-49
Table 6-37.      Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting
                Basal Metabolic Rates (BMR)  	6-50
Table 6-38.      Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal
                Metabolic Rate (BMR)	6-51
Table 6-39.      Inhalation Rates for Short-term Exposures	6-52
Table 6-40.      Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 618
                Infants and Children Grouped in Classes of Age 	6-53

Table 7-1.       Recommended Values for Total Body Surface Area, Males and
                Females Combined	7-4
Table 7-2.       Recommended Values for Surface Area of Body Parts  	7-5
Table 7-3.       Confidence in Recommendations for Body Surface Area  	7-6
Table 7-4.       Recommended Values for Mean Solids Adherence	7-8
Table 7-5.       Confidence in Recommendations for Solids Adherence to Skin 	7-9
Table 7-6.       Percentage of Total Body Surface Area by Body Part For Children	7-16
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                                   LIST OF TABLES (Continued)

Table 7-7.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Males and Females Combined  	7-17
Table 7-8.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Males	7-17
Table 7-9.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Females  	7-18
Table 7-10.      Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (mVkg)	7-19
Table 7-11.      Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 	7-20
Table 7-12.      Summary of Field Studies  	7-21
Table 7-13.      Geometric Mean and Geometric Standard Deviations of Solids Adherence by
               Activity and Body Region	7-22
Table 7-14.      Summary of Controlled Greenhouse Trials - Children Playing	7-23
Table 7A-1.     Estimated Parameter Values for Different Age Intervals	  7A-5
Table 7A-2.     Summary of Surface Area Parameter Values for the Dubois and Dubois Model 	  7A-5

Table 8-1.       Recommended Values for Body Weight	8-2
Table 8-2.       Confidence in Recommendations for Body Weight	8-3
Table 8-3.       Mean and Percentile Body Weights (kilograms) Derived from NHANES  1999-2006, Males and
               Females Combined  	8-10
Table 8-4.       Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES
               1999-2006 	8-11
Table 8-5.       Mean and Percentile Body Weights (kilograms) for Females Derived from
               NHANES 1999-2006	8-11
Table 8-6.       Weight in Kilograms for Males 2 Months-19 Years of Age- Number Examined, Mean, and
               Selected Percentiles, by Age Category: United States, 1976-1980 	8-12
Table 8-7.       Weight in Kilograms for Females 6 Months-19 Years of Age- Number Examined, Mean, and
               Selected Percentiles, by Age Category: United States, 1976-1980 	8-13
Table 8-8.       Statistics for Probability Plot Regression Analyses:
               Females Body Weights 6 Months to 20 Years of Age	8-14
Table 8-9.       Statistics for Probability Plot Regression Analyses:
               Males Body Weights 6 Months to 20 Years of Age	8-15
Table 8-10.      Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From
               NHANES III (1988-94	8-16
Table 8-11.      Body Weight Estimates (in kilograms) by Age, U.S. Population Derived From
               NHANES III (1988-94 	8-17
Table 8-12.      Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender
               and Age: Birth to 36 Months  	8-18
Table 8-13.      Mean Body Weight (kilograms) by Age and Gender Across Multiple Surveys 	8-25
Table 8-14.      Mean Height (centimeters) by Age and Gender Across Multiple Surveys	8-26
Table 8-15.      Mean Body Mass Index (BMI) by Age and Gender Across Multiple  Surveys 	8-27
Table 8-16.      Sample Sizes by Age, Sex, Race, and Examination  	8-28
Table 8-17.      Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex . . . 8-29
Table 8-18.      Prevalence of Overweight and Obesity3 Among Children	8-30
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                                   LIST OF TABLES (Continued)

Table 8-19.     Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth
               Weights, by Race and Hispanic Origin of Mother: United States, 2005  	8-31
Table 8-20.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
               NHANES II Data   	8-32
Table 8-21.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
               NHANES III Data        	8-33
Table 8-22.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
               NHANES IV Data	8-34
Table 8-23.     Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments . 8-35
Table 8-24.     Estimated Percentile Distribution of Body Weight by Fine Age Categories  	8-35
Table 8-25.     Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence
               Interval  	8-36
Table 8-26.     Fetal Weight (grams) Percentiles Throughout Pregnancy  	8-37
Table 8-27.     Neonatal Weight by Gestational Age for Males and Females Combined   	8-38

Table 9-1.      Recommended Values for Intake of Fruits and Vegetables, As Consumed  	9-3
Table 9-2.      Confidence in Recommendations for Intake of Fruits and Vegetables	9-4
Table 9-3.      Per Capita Intake of Fruits and Vegetables (g/kg-day as consumed)	9-12
Table 9-4.      Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed)	9-13
Table 9-5.      Per Capita Intake of Individual Fruits  and Vegetables (g/kg-day as consumed)	9-14
Table 9-6.      Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed)	9-17
Table 9-7.      Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day)	9-20
Table 9-8.      Percentage of Individuals Consuming  Vegetables, by Sex and Age (%) 	9-21
Table 9-9.      Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day)	9-22
Table 9-10.     Percentage of Individuals Consuming, Fruits by Sex and Age (%)  	9-23
Table 9-11.     Quantity (as consumed)  of Fruits and Vegetables Consumed Per Eating Occasion and
               Percentage of Individuals Using These Foods in Two Days  	9-24
Table 9-12.     Characteristics of the FITS Sample Population	9-25
Table 9-13.     Percentage of Infants and Toddlers Consuming Different Types of Vegetables	9-26
Table 9-14.     Top Five Vegetables Consumed by Infants and Toddlers 	9-27
Table 9-15.     Percentage of Infants and Toddlers Consuming Different Types of Fruits	9-28
Table 9-16.     Top Five Fruits Consumed by Infants and Toddlers  	9-29
Table 9-17.     Characteristics of WIC Participants and Non-participants (Percentages)   	9-30
Table 9-18.     Food Choices for Infants and Toddlers by WIC Participation Status	9-32
Table 9-19.     Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming
               Different Types of Fruits and Vegetables on A Given Day 	9-33
Table 9-20.     Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants
               and Toddlers Per Age Group  	9-34
Table 9-21.     Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
               Consumed by Infants from the 2002 Feeding Infants and Toddlers Study	9-35
Table 9-22.     Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
               Consumed by Toddlers from the 2002  Feeding Infants and Toddlers Study  	9-36
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                                   LIST OF TABLES (Continued)

Table 9-23.     Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible
               Portions	9-37
Table 9A-1.     Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USD A CSFII Data  . . .  9A-2

Table 10-1.     Recommended Values for General Population Fish Intake	10-4
Table 10-2.     Confidence in Recommendations for General Population Fish Intake	10-5
Table 10-3.     Per Capita Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - g/day, As-Consumed 	10-17
Table 10-4.     Per Capita Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed	10-17
Table 10-5.     Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - g/day, As-Consumed 	10-18
Table 10-6.     Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed  	10-18
Table 10-7.     Per Capita Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight	10-19
Table 10-8.     Per Capita Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight.... 10-19
Table 10-9.     Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight	10-20
Table 10-10.    Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
               General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight.... 10-20
Table 10-11.    Number of General Population Respondents Reporting Consumption of a
               Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten	10-21
Table 10-12.    Fish Consumption Among General Population Children in Four States,
               Consumers Only, g/kg-day As-Consumed  	10-22
Table 10-13.    Fish Consumption Among General Population in Four States According to Caught or Bought
               Status, g/kg-day As-Consumed	10-23
Table 10-14.    Fish Consumption Among General Population and Anglers in Three States,
               g/kg-day As-Consumed  	10-24
Table 10-15.    Recreational Fish Consumption in Delaware Consumers Only	10-24
Table 10-16.    Consumption of Self-Caught Fish by Recreational Anglers
               Lavaca Bay, Texas, g/day	10-25
Table 10-17.    Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational
               Anglers Lavaca Bay, Texas  	10-25
Table 10-18.    Mean Fish Intake Among Individuals Who Eat Fish and
               Reside in Households With Recreational Fish Consumption - Michigan	10-26
Table 10-19.    Consumption of Sports-caught and Purchased Fish by Minnesota and North Dakota
               Children, Ages 0 to 14 Years (g/day)	10-26
Table 10-20.    Fish Consumption Rates among Native American Children (age 5 years and under)  	10-27
Table 10-21.    Number of Fish Meal Eaten per Month and Fish Intake Among Native American
               Children who Consume Particular Species	10-28
Table 10-22.    Consumption Rates for Native American Children, Age Birth to Five Years (g/kg-day)  . . . 10-29
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                                   LIST OF TABLES (Continued)

Table 10-23.     Consumption Rates for Native American Children (g/kg-day), All Children
                (including non-consumers): Individual Finfish and Shellfish and Fish Groups	10-30
Table 10-24.     Consumption Rates for Native American Children (g/kg-day),
                Consumers Only: Individual Finfish and Shellfish and Fish Groups	10-31
Table 10-25.     Fish Consumption Rates for Tulalip and Squaxin Island Children
                Consumers Only (g/kg-day)	10-32
Table 10-26.     Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children
                Consumers Only (g/kg-day)	10-33
Table 10-27.     Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion,
                by Age and Sex 	10-34
Table 10-28.     Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion,
                by Age and Sex 	10-34
Table 10-29.     Mean Percent Moisture and Total Fat Content for Selected Species	10-35

Table 11-1.      Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed  	11-3
Table 11-2.      Confidence in Recommendations for Intake of Meats, Diary Products, and Fats	11-4
Table 11-3.      Per Capita Intake of Total Meat and Dairy Products (g/kg-day as consumed)	11-14
Table 11-4.      Consumer Only Intake of Total Meat and Dairy Products (g/(kg-day as consumed)  	11-15
Table 11-5.      Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed)  	11-16
Table 11-6.      Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed)  . .  11-16
Table 11-7.      Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (g/day)  . .  11-17
Table 11-8.      Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%)	11-18
Table 11-9.      Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day) . .  11-19
Table 11-10.     Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) 	11-20
Table 11-11.     Quantity (as consumed) of Meat and Dairy Products Consumed Per Eating Occasion and
                Percentage of Individuals Using These Foods in Two Days 	11-21
Table 11-12.     Characteristics of FITS Sample Population	11-22
Table 11-13.     Percentage of Infants and Toddlers Consuming Meat or Other Protein Sources 	11-23
Table 11-14.     Characteristics of WIC Participants and Non-participants (Percentages) 	11-24
Table 11-15.     Food Choices for Infants and Toddlers by WIC Participation Status	11-25
Table 11-16.     Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
                Types of Milk, Meats  or Other Protein Sources on A Given Day  	11-26
Table 11-17.     Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
                Consumed by Infants from the 2002 Feeding  Infants and Toddlers Study	11-27
Table 11-18.     Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
                Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study 	11-28
Table 11-19.     Total Fat Intake (Per capita; g/day)	11-29
Table 11-20.     Total Fat Intake (Per capita; g/kg-day)	11-30
Table 11-21.     Total Fat Intake (Consumers Only; g/day)  	11-31
Table 11-22.     Total Fat Intake (Consumers Only; g/kg-day)	11-32
Table 11-23.     Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day) 	11-33
Table 11-24.     Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/kg-day)	11-34
Page
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                                                                                  CSEFH
                                   LIST OF TABLES (Continued)

Table 11-25.    Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
               1973-1982 (g/day) 	11-35
Table 11-26.    Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
               1973-1982 (g/kg-day)	11-37
Table 11-27.    Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender	11-39
Table 11-28.    Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products  	11-40
Table 11A-1.    Food Codes and Definitions Used in Analysis of the 1994-96,  1998 USDA CSFII Data . .  11A-2

Table 12-1.     Recommended Values for Intake of Grains, As Consumed	12-3
Table 12-2.     Confidence in Recommendations for Intake of Grain Products	12-4
Table 12-3.     Per Capita Intake of Total Grains (g/kg-day as consumed)	12-12
Table 12-4.     Consumer Only Intake of Total Grains (g/kg-day as consumed)	12-12
Table 12-5.     Per Capita Intake of Individual Grain Products (g/kg-day as consumed)	12-13
Table 12-6.     Consumer Only Intake of Individual Grain Products (g/kg-day as consumed)	12-13
Table 12-7.     Mean Quantities of Grain Products Consumed Daily by Sex and Age, Per Capita (g/day) .  . 12-14
Table 12-8.     Percentage of Individuals Consuming Grain Products, by Sex and Age (%)	12-15
Table 12-9.     Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and
               Percentage of Individuals Using These Foods in Two Days  	12-16
Table 12-10.    Characteristics of the FITS Sample Population	12-17
Table 12-11.    Percentage of Infants and Toddlers Consuming Different Types of Grain Products	12-18
Table 12-12.    Characteristics of WIC Participants and Nonparticipants (Percentages)  	12-19
Table 12-13.    Food Choices for Infants and Toddlers by WIC Participation Status	12-20
Table 12-14.    Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
               Types of Grain Products on A Given Day	12-21
Table 12-15.    Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
               by Infants from the 2002 Feeding Infants and Toddlers Study  	12-22
Table 12-16.    Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
               by Toddlers from the 2002 Feeding Infants and Toddlers Study	12-22
Table 12-17.    Mean Moisture Content of Selected Grain Products Expressed as Percentages
               of Edible Portions	12-23
Table 12A-1.    Food Codes and Definitions Used in Analysis of the 1994-96,  1998 USDA CSFII Data . .  12A-2

Table 13-1.     Summary of Recommended Values for Intake of Home-produced Foods (Consumers Only) .13-3
Table 13-2.     Confidence in Recommendations for Intake of Home-produced Foods  	13-4
Table 13-3.     Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in
               Child-specific Analysis of Food Intake	13-10
Table 13-4.     Consumer Only Intake of Home-produced Foods (g/kg-day)	13-11
Table 13-5.     Percent Weight Losses from Food Preparation	13-12
Table 13-6.     Fraction of Food Intake that is Home-produced  	13-13
Table 13A-1.    Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDA
               NFCS Data to Estimate Intake of Home-produced Foods      	  13A-2
Table 13B-1.    Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household
               Data to Estimate Fraction of Food Intake that is Home-produced	  13B-2
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September 2008	
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 CSEFH
                                    LIST OF TABLES (Continued)

Table 14-1.     Recommended Values for Per Capita Total Intake of Foods, As Consumed 	14-2
Table 14-2.     Confidence in Recommendations for Total Food Intake	14-3
Table 14-3.     Per Capita Total Food Intake	14-6
Table 14-4.     Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed)  . . 14-7
Table 14-5.     Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed)14-ll
Table 14-6.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Food Intake	14-15
Table 14-7.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Meat Intake	14-19
Table 14-8.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Meat and Dairy Intake .... 14-23
Table 14-9.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Fish Intake	14-27
Table 14-10.    Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Fruit and Vegetable Intake . 14-31
Table 14-11.    Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Dairy Intake	14-35

Table 15-1.     Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed
               Infants	15-3
Table 15-2.     Confidence in Recommendations for Human Milk Intake	15-4
Table 15-3.     Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
               (mL/day)  	15-6
Table 15-4.     Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
               (mL/kg/day)	15-7
Table 15-5.     Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day) ... 15-8
Table 15-6.     Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
               (mL/kg/day)	15-9
Table 15-7.     Daily Intakes of Human Milk	15-23
Table 15-8.     Human Milk Intakes for Infants Aged 1 to 6 Months	15-23
Table 15-9.     Human Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months
               of Life  	15-24
Table 15-10.    Human Milk Intake During a 24-hour Period	15-25
Table 15-11.    Human Milk Intake Estimated by the Darling Study	15-26
Table 15-12.    Mean Breastfed Infants Characteristics  	15-26
Table 15-13.    Mean Human Milk Intake of Breastfed Infants (mL/day) 	15-27
Table 15-14.    Feeding Practices by Percent of Infants  	15-27
Table 15-15.    Body Weight of Breastfed Infants	15-28
Table 15-16.    AAP Dataset Milk Intake Rates at Different Ages  	15-29
Table 15-17.    Average Daily Human Milk Intake (mL/kg day)	15-30
Table 15-18.    Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed
               Infants	15-30
Table 15-19.    Human Milk Production  and Composition Over the First 12 Months of Lactation  	15-31
Page
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                                                                                   CSEFH
                                   LIST OF TABLES (Continued)

Table 15-20.    Changes in Volume of Human Milk Produced and Milk Fat Content Over the First Year of
               Lactation	15-32
Table 15-21.    Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation
               (g/100 g total fatty acids)	15-33
Table 15-22.    Comparison of Lipid Content Assumptions (mL/kg-day) 	15-33
Table 15-23.    Distribution of Average Daily Lipid Intake (mL/kg day) assuming 4% Milk Lipid Content  15-34
Table 15-24.    Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age	15-34
Table 15-25.    Socio-economic Characteristics of Exclusively Breast-fed Infants Born in 2004	15-34
Table 15-26.     Geographic-specific Breastfeeding Percent Rates Among Children Born in 2004	15-36
Table 15-27.    Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6
               Months Old	15-37
Table 15-28.    Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12
               Months Old	15-38
Table 15-29.    Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
               During the Previous 24-hours	15-39
Table 15-30.    Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III
               (1988-1994)	15-40
Table 15-31.    Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk
               at 6 Months (NHANES III, 1988-1994)	15-41
Table 15-32.    Racial and Ethnic Differences in Proportion of Children Exclusively Breastfed at 4
               Months (NHANES III, 1991-1994)  	15-42
Table 15-33.    Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6
               Months of Age in the United States in 1989 and 1995, by Ethnic Background and Selected
               Demographic Variables  	15-43
Table 15-34.    Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 6 and
               12 Months of Age in the United States in 2003, by Ethnic Background and Selected
               Demographic Variables  	15-44
Table 15-35.    Number of Meals Per Day  	15-45
Table 15-36.    Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD)	15-45

Table 16-1.     Recommended Values for Activity Factors	16-3
Table 16-2.     Confidence in Recommendations for Activity Factors	16-6
Table 16-3.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, for All Respondents and Doers	16-17
Table 16-4.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, by Age and Gender  	16-18
Table 16-5.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, Grouped by Seasons and Regions  	16-19
Table 16-6.     Time (minutes/day) Children Under 12 Years of Age Spent in Six Major Location
               Categories, for All Respondents and Doers	16-20
Table 16-7.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
               Categories, Grouped by Age and Gender  	16-21
Child-Specific Exposure Factors Handbook
September 2008	
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                                                     Child-Specific Exposure Factors Handbook
 CSEFH
                                   LIST OF TABLES (Continued)

Table 16-8.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
               Categories, Grouped by Season and Region 	16-22
Table 16-9.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in
               Proximity to Two Potential Sources of Exposure, Grouped by All Respondents,
               Age, and Gender 	16-23
Table 16-10.    Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
               Grouped by Age and Gender  	16-24
Table 16-11.    Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
               Whole Population and Doers Only	16-25
Table 16-12.    Time Spent (minutes/day) at Selected Indoor Locations Whole Population
               and Doers Only 	16-29
Table 16-13.    Time Spent (minutes/day) in Selected Outdoor Locations Whole Population
               and Doers Only 	16-31
Table 16-14.    Mean Time Spent (minutes/day) Inside and Outside, by Age Category	16-33
Table 16-15.    Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
               Whole Population and Doers Only	16-34
Table 16-16.    Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only	16-36
Table 16-17.    Number of Showers Taken per Day, by Number of Respondents	16-40
Table 16-18.    Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing
               and Showering  	16-41
Table 16-19.    Range of Number of Times Washing the Hands at Specified Daily Frequencies by
               the Number of Respondents	16-43
Table 16-20.    Number of Times Swimming in a Month in Freshwater Swimming Pool by the
               Number of Respondents   	16-44
Table 16-21.    Time Spent (minutes/month) Swimming in Freshwater Swimming Pool  	16-45
Table 16-22.    Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population
               and Doers Only 	16-46
Table 16-23.    Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air  	16-48
Table 16-24.    Time Spent (minutes/day) with Smokers Present  	16-48
Table 16-25.    Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex
               and Type of Day  	16-49
Table 16-26.    Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different
               Age Groups 	16-50
Table 16-27.    Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week	16-51
Table 16-28.    Mean Time Spent (minutes/day) in Various Microenvironments, Children Ages 12 to
               17 Years National and California Surveys  	16-52
Table 16-29.    Gender and Age Groups  	16-53
Table 16-30.    Assignment of At-Home Activities to Inhalation Rate Levels for Children 	16-54
Table 16-31.    Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents
               and Children  	16-55
Table 16-32.    Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents) 	16-55
Table 16-33.    Comparison of Mean Time Spent (minutes/day) At-Home, by Gender and Age
               for Children	16-56
Page
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                                                                                  CSEFH
                                   LIST OF TABLES (Continued)

Table 16-34.    Number of Person-Days/Individuals for Children in CHAD Database  	16-57
Table 16-35.    Time Spent (hours/day) in Various Microenvironments, by Age  	16-58
Table 16-36.    Mean Time Children Spent (hours/day) Doing Various Macroactivities
               While Indoors at Home  	16-59
Table 16-37.    Time Children Spent (hours/day) in Various Microenvironments, by Age
               Recast into New Standard Age Categories 	16-60
Table 16-38.    Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
               Recast Into New Standard Age Categories	16-61
Table 16-39.    Number and Percentage of Respondents with Children and Those Reporting
               Outdoor Play Activities in both Warm and Cold Weather  	16-62
Table 16-40.    Play Frequency and Duration for all Child Players (from SCS-II data)  	16-63
Table 16-41.    Hand Washing and Bathing Frequency for all Child Players (from SCS-II data)  	16-63
Table 16-42.    NHAPS and SCS-II Play Duration Comparison	16-64
Table 16-43.    NHAPS and SCS-II Hand Wash Frequency Comparison 	16-64
Table 16-44.    Time Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only)	16-65
Table 16-45.    Comparison of Daily Time Spent Outdoors (minutes/day), Considering Gender
               and Age Cohort (Doers Only)	16-66
Table 16-46.    Time Spent (minutes/day) Indoors Based on CHAD Data (Doers Only)	16-67
Table 16-47.    Time Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only)	16-68
Table 16-48.    Time Spent (minutes/two-day period) in Various Activities by Children Participating
               in the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement
               (CDS)  	16-69
Table 16-49.    Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday	16-70
Table 16-50.    Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day . . 16-71
Table 16-51.    Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to 1716-72
Table 16-52.    Mean Time Use (hours/day) by Children, Ages 15 to 19 Years	16-73
Table 16-53.    Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity  	16-74

Table 17-1.     Consumer Products Commonly Found in Some U.S. Households	17-7
Table 17-2.     Amount and Frequency of Use of Various Cosmetic and Baby Products	17-10
Table 17-3.     Number of Minutes Spent in Activities Working With or Near Freshly Applied
               Paints (minutes/day)	17-13
Table 17-4.     Number of Minutes Spent in Activities Working With or Near Household Cleaning
               Agents Such as Scouring Powders or Ammonia (minutes/day)	17-13
Table 17-5.     Number of Minutes Spent in Activities (at home or elsewhere) Working With
               or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day)	17-13
Table 17-6.     Number of Minutes Spent in Activities Working With or Near Glue (minutes/day) 	17-14
Table 17-7.     Number of Minutes Spent in Activities Working With or Near Solvents, Fumes or
               Strong Smelling Chemicals (minutes/day) 	17-14
Table 17-8.     Number of Minutes Spent in Activities Working With or Near Stain or Spot Removers
               (minutes/day)	17-14
Table 17-9.     Number of Minutes Spent in Activities Working With or Near Gasoline or
               Diesel-powered Equipment, Besides Automobiles (minutes/day	17-15
Child-Specific Exposure Factors Handbook
September 2008	
Page
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                                                     Child-Specific Exposure Factors Handbook
 CSEFH
                                   LIST OF TABLES (Continued)

Table 17-10.    Number of Minutes Spent in Activities Working with or Near Pesticides,
               Including Bug Sprays or Bug Strips (minutes/day)	17-15
Table 17-11.    Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at
               Specified Daily Frequencies	17-15
Table 17-12.    Number of Respondents Using Any Aerosol Spray Product for Personal Care Item
               Such as Deodorant or Hair Spray at Specified Daily Frequencies  	17-16
Table 17-13.    Number of Respondents Using a Humidifier at Home  	17-16
Table 17-14.    Number of Respondents Indicating that Pesticides Were Applied by the Professional at
               Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies	17-16
Table 17-15.    Number of Respondents Reporting Pesticides Applied by the Consumer at Home
               To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies	17-17
Table 17-16.    Number of Respondents Indicating that Pesticides Were Applied by a
               Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified
               Frequencies 	17-17
Table 17-17.    Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
               Eradicate Insects, Rodents, or Other Pests at Specified Frequencies	17-17
Table 17-18.    Household Demographics, and Pesticide Types, Characteristics, and Frequency of
               Pesticide Use  	17-18
Table 17-19.    Frequency of Use of Cosmetic Products 	17-19
Table 17-20.    Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream	17-20
Table 17-21.    Frequency of Use of Personal Care Products	17-22
Table 17-22.    Average Amount of Product Applied per Application (grams)	17-23
Table 17-23.    Average Amount of Product Applied per Use Day (grams)	17-24
Table 17-24.    Average Number of Applications Per Use Day	17-25
Table 17-25.    Average Amount of Product Applied Per Use Day (grams)	17-26
Table 17-26.    Average Amount of Product Applied Per Application (grams)	17-27
Table 17-27.    Characteristics of the  Study Population and the Percent Using Selected Baby Care
               Products	17-28
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                                                                                CSEFH


                                       LIST OF FIGURES

Figure 1-1.      The Exposure-Dose Effect Continuum	1-25

Figure 6-1.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects . .  6-54
Figure 6-2.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects . .  6-54

Figure 7-1.      Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing
               in Wet Soils	7-24
Figure 7-2.      Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils	7-24

Figure 8-1.      Weight by Age Percentiles for Boys Aged Birth to 36 Months 	8-19
Figure 8-2.      Weight by Age Percentiles for Girls Aged Birth to 36 Months	8-20
Figure 8-3.      Weight by Length Percentiles for Boys Aged Birth to 36 Months	8-21
Figure 8-4.      Weight by Length Percentiles for Girls Aged Birth to 36 Months	8-22
Figure 8-5.      Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years	8-23
Figure 8-6.      Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years  	8-24
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                                                   Child-Specific Exposure Factors Handbook
AAP
ADD
AF
AIR
ANOVA
ARS
ATSDR
ATUS
BI
BMD
BMI
BMR
BTM
C
CARB
CATI
CDC
CDS
CHAD
CI
cm2
cm3
CNRC
CRITFC
CSFII
CTFA
CV
DARLING
DIY
DLW
DONALD
E or EE
EBF
ECG
ED
El
EPA
fB
FCID
FITS
FQPA
F/S
        ACRONYMS AND ABBREVIATIONS

American Academy of Pediatrics
Average Daily Dose
Adherence Factor
Acid Insoluble Residue
Analysis of Variance
Agricultural Research Service
Agency for Toxic Substances and Disease Registry
American Time Use Study
Bootstrap Interval
Benchmark Dose
Body Mass Index
Basal Metabolic Rate
Best Tracer Method
Contaminant Concentration
California Air Resources Board
Computer Assisted Telephone Interviewing
Centers for Disease Control and Prevention
Child Development Supplement
Consolidated Human Activity Database
Confidence Interval
Square Centimeter
Cubic Centimeter
Children's Nutrition Research Center
Columbia River Inter-Tribal Fish Commission
Continuing Survey of Food Intake by Individuals
Cosmetic, Toiletry, and Fragrance Association
Coefficient of Variation
Davis Area Research on Lactation, Infant Nutrition and Growth
Do-it-yourself
Doubly Labeled Water
Dortmund Nutritional and Anthropometric Longitudinally Designed
Energy Expenditure
Exclusively Breastfed
Energy Cost of Growth
Exposure Duration
Energy Intake
Environmental Protection Agency
Breathing Frequency
Food Commodity Intake Database
Feeding Infant and Toddler Study
Food Quality Protection Act
Food/Soil
Gram
Page
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                             Child-Specific Exposure Factors Handbook
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                                                                                CSEFH
GAF
GLM
H
HEC
HPV
HR
I
IA
ICRP
IEUBK
IPS
IOM
IPCS
IR
IRP
IRIS
KJ
KS
kg
LI
L2
LADD
LTM
m2
m3
mg
MJ
mL
METS
MSA
N
Nc
NT
NAS
NCEA
NCHS
NERL
NFCS
NHANES
NHAPS
NHES
NHEXAS
NIS
NOAEL
NRC
General Assessment Factor
General Linear Model
Oxygen Uptake Factor
Human Equivalent Exposure Concentrations
High Production Volume
Heart Rate
Tabulated Intake Rate
Adjusted Intake Rate
International Commission on Radiological Protection
Integrated Exposure and Uptake Biokinetic Model
Iowa Fluoride Study
Institute of Medicine
International Programme on Chemical Safety
Intake Rate
Intake Rate Percentile
Integrated Risk Information System
Kilo Joules
Kolmogorov-Smirnov
Kilogram
Cooking or Preparation Loss
Post-cooking Loss
Lifetime Average Daily Dose
Limiting Tracer Method
Square Meter
Cubic Meter
Milligram
Mega Joules
Milliliter
Metabolic Equivalents of Work
Metropolitan Statistical Area
Number of Subjects or Respondents
Weighted Number of Individuals Consuming Homegrown Food Item
Weighted Total Number of Individuals Surveyed
National Academy of Sciences
National Center for Environmental Assessment
National Center for Health Statistics
National Exposure Research Laboratory
Nationwide Food Consumption Survey
National Health and Nutrition Examination Survey
National Human Activity Pattern Survey
National Health Examination Survey
National Human Exposure Assessment Survey
National Immunization Survey
No-observed-adverse-effect-level
National Research Council
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                                                   Child-Specific Exposure Factors Handbook
OPP
ORD
PBPK
PDIR
PSID
RAGS
ROD
RfD
RfC
RME
RQ
RTF
SA
SA/BW
scs
SD
SDA
SE
SEM
SES
SPC
SPS
SRD
TDEE
TFEI
USDA
USDL
USDHHS
UV
V02
VQ
VR
W
w,-
WHO
WIC
x,
Office of Pesticide Programs
Office of Research and Development
Physiologically-Based Pharmacokinetic
Physiological Daily Inhalation Rate
Panel Study of Income Dynamics
Risk Assessment Guidance for Superfund
Random Digit Dial
Reference Dose
Reference Concentration
Reasonable Maximum Exposure
Respiratory Quotient
Ready to Feed
Surface Area
Surface Area to Body Weight Ratio
Soil Contact Survey
Standard Deviation
Soaps and Detergent Association
Standard Error
Standard Error of the Mean
Socioeconomic Status
Science Policy Council
Statistical Processing System
Source Ranking Database
Total Daily Energy Expenditure
Total Food Energy Intake
United States Department of Agriculture
United States Department of Labor
United States Department of Health and Human Services
Ultraviolet
Oxygen Consumption Rate
Ventilatory Equivalent
Ventilation Rate
Weight
Sample Weight Assigned to Observation xt.
World Health Organization
USDA's Women, Infants, and Children Program
/'* observation
Page
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                             Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
                                                                                    CSEFH
                                             PREFACE

        The Exposure Factors Program of the U.S. Environmental Protection Agency's (U.S. EPA's) Office of
Research and Development (OPvD) has three main goals: (1) provide updates to the Exposure Factors Handbook and
the Child-Specific Exposure Factors Handbook', (2) identify exposure factors data gaps and needs in consultation with
clients; and (3) develop companion documents to assist clients in the use of exposure factors data. The activities under
each goal are supported by and respond to the needs of the various program offices.

        The National Center for Environmental Assessment (NCEA) of the U.S. EPA's OPJ) has prepared this
handbook to provide information on various physiological and behavioral  factors commonly used in assessing
children's exposure to environmental chemicals.  Children have different exposure circumstances than do adults.
Understanding these differences is key for evaluating potential for environmental hazards from pollutants.  They
consume more of certain foods and water and have higher inhalation rates per unit 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.  Ingestion of breast milk is another potential pathway of exposure for infants and
young children.

        NCEA published the Exposure Factors Handbook in 1997. That document includes exposure factors and
related data on children, as well as adults. However, the U.S. EPA Program Offices identified the need to prepare a
document specifically for children's exposure factors. The Child-Specific Exposure Factors Handbook is intended to
fulfill this need.

        This handbook was first offered to the public in 2002. Since that time, the U. S. EPA has incorporated updated
data and revised the recommendations for several exposure factors and developed a standardized set of age categories
to be used for children's exposure assessment. Where possible, the U.S. EPA  has used this standard set of age
categories to permit easier comparison of data among multiple sources and to allow consistency between different types
of exposure factors.
Child-Specific Exposure Factors Handbook                                                 Page
September 2008	xxxi

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 CSEFH
                                                        Child-Specific Exposure Factors Handbook
           EXECUTIVE SUMMARY

        This   Child-Specific   Exposure   Factors
Handbook  has been prepared to focus on various
factors used in assessing exposure, specifically for
children  ages  0 to <21 years old.  This handbook
provides nonchemical-specific data on exposure factors
for the U.S. EPA recommended set of childhood age
groups in the following areas:

        ingestion of water and other select liquids
        (Chapter 3);
        non-dietary ingestion factors (Chapter 4);
        ingestion of soil and dust (Chapter 5);
        inhalation rates (Chapter 6);
        dermal exposure factors such as surface area
        and adherence (Chapter 7);
        body weight (Chapter 8);
        intake of fruits and vegetables (Chapter 9);
        intake offish and shellfish (Chapter 10);
        intake of meat, dairy  products,  and  fats
        (Chapter 11);
        intake of grain products (Chapter 12);
        intake of home-produced foods (Chapter 13);
        total food intake (Chapter 14);
        human milk intake (Chapter 15);
        activity factors (Chapter 16); and
        consumer products (Chapter 17).

        The    Child-specific   Exposure   Factors
Handbook was first published in 2002.  Subsequently,
recognizing that exposures  among infants, toddlers,
adolescents, and teenagers can vary significantly, the
U.S. EPA  published its Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U. S. EPA.
2005).   To the extent possible,  source data for the
independent studies cited in the earlier version of this
handbook were obtained and re-analyzed to conform to
the standard age categories.  This update and revision
of the 2002 interim final  Child-specific Exposure
Factors  Handbook  is  designed  specifically  to
complement the U.S.  EPA's  recommended  set of
childhood age groups:
         Less than 12 months old: birth to <1 month,
         1 to <3 months, 3 to <6 months, and 6 to < 12
         months.
         Greater than 12 months old: 1 to <2 years, 2
         to <3 years, 3 to <6 years, 6 to <11 years, 11
         to <16 years, and 16 to <21 years.

         The data presented in this handbook have
 been compiled from various sources, which include the
 U.S. EPA's Exposure Factor Handbook  (U.S. EPA,
 1997), government reports, and information presented
 in the scientific literature. The data presented are the
 result of analyses by  the individual  study authors.
 However, in some cases the U.S. EPA has conducted
 analysis of published primary data to  present results
 for the recommended age groups. Studies presented in
 this handbook were chosen because they were seen as
 useful and appropriate for estimating exposure factors
 based on the following considerations: (1) soundness
 (adequacy of approach and minimal or defined bias);
 (2)  applicability and utility (focus on the exposure
 factor of interest, representativeness of the population,
 currency of the information, and adequacy of the data
 collection period);  (3) clarity  and  completeness
 (accessibility, reproducibility, and quality assurance);
 (4)  variability and  uncertainty (variability  in the
 population and uncertainty in  the  results); and (5)
 evaluation and review (level  of peer review and
 number and agreement of studies). Overall confidence
 ratings of high, medium, or low were derived for the
 various exposure factors based on the evaluation of the
 elements described above.
         Many scientific studies were reviewed for
 possible inclusion in this handbook.  The handbook
 contains  summaries  of selected  studies published
 through July 2008. Generally, studies were designated
 as "key" or "relevant" studies.  Key studies were
 considered   the  most  useful   for   deriving
 recommendations; while  relevant  studies  provided
 applicable or pertinent data, but not necessarily the
 most important for a variety of reasons (e.g., data were
 outdated,  limitations  in  study   design).    The
 recommended values for exposure factors are based on
 the results of key studies. The U.S. EPA's procedure
 for developing recommendations was as follows:
Page
xxxii
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	September 2008

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Child-Specific Exposure Factors Handbook
                                                                                       CSEFH
        Key studies were evaluated in terms of both
        quality and relevance to specific populations
        (general U. S. population, age groups, gender,
        etc.).  The criteria for assessing the quality of
        studies are described in Section 1.5.

        If only one study was classified as key for a
        particular factor, the mean value from that
        study was selected  as the recommended
        central tendency value for that population. If
        multiple  key studies with  reasonably equal
        quality,  relevance,   and   study  design
        information were available, a weighted mean
        (if appropriate, considering sample size and
        other statistical factors) of the studies was
        chosen as the recommended mean value. If
        the key studies were judged to be unequal in
        quality, relevance, or study design, the range
        of means is presented  and the user of this
        handbook  should  employ  judgment  in
        selecting the most appropriate value for  the
        lifestage  or local  population of  interest.
        Recommendations  for  upper  percentiles,
        when multiple studies were available, were
        calculated as the midpoint of the range of
        upper percentile values of the studies for each
        age group where data were available.

        Aspects of exposure factors variability have
        been discussed. This document attempts to
        characterize the variability of each  of  the
        factors.     Variability  refers  to  true
        heterogeneity or diversity  in a  population.
        Differences  among   individuals   in   a
        population are referred to as inter-individual
        variability, differences for one individual over
        time  is  referred  to  as   intra-individual
        variability. Since most of the studies used to
        derive exposure factors data are short term in
        nature, they present the variability in short
        term exposures across a population sample
        and often do not allow analysis  of either
        inter-temporal variability within individuals
        nor inter-individual variability of long term
        average   exposures.      Inter-individual
        variability in this handbook is characterized
        in one or more of the following ways: (1) as a
        table  with various percentiles or ranges  of
        values;  (2) as analytical distributions with
        specified  parameters;  and/or (3)  as  a
        qualitative discussion.

4.       Uncertainties were discussed in terms of data
        limitations, the range of circumstances over
        which the estimates were  (or were not)
        applicable, possible  biases  in the values
        themselves,  a  statement  about parameter
        uncertainties (measurement error,  sampling
        error) and model or scenario uncertainties if
        models or scenarios were used to derive the
        recommended value.

5.       The U.S. EPA assigned a confidence rating of
        low, medium or high to each recommended
        value.   This   rating  is  not  intended  to
        represent an uncertainty analysis;  rather, it
        represents the  U.S. EPA's judgment on the
        quality of the underlying data used to derive
        the recommendation.

6.       Finally, the U.S. EPA developed a  table for
        each  exposure  factor to  summarize  the
        recommended  values for that factor.  Table
        ES-1  summarizes key recommended values
        for  the  exposure factors included in  this
        handbook. Additional recommendations and
        detailed supporting information can be found
        in the individuals chapters that address these
        factors.

        In the providing recommendations for the
various exposure factors, an attempt was  made  to
present percentile values that  are consistent with the
exposure  estimators  defined  in  Guidelines  for
Exposure Assessment (U.S. EPA, 1992) (i.e., mean,
50th,  90th,  95th,  98th, and  99.9th  percentile).
However, this was not always possible, because the
data available  were limited for some factors, or the
authors of the study did not provide such information.
It is important to note, however, that these percentiles
Child-Specific Exposure Factors Handbook
September 2008	
                                           Page
                                          xxxiii

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                                                      Child-Specific Exposure Factors Handbook
 CSEFH
were discussed in the guidelines within the context of
risk descriptors and not individual exposure factors.
For example, the guidelines state that the assessor may
derive  a high-end estimate  of exposure  by using
maximum or near maximum values for one or more
sensitive exposure factors, leaving others at their mean
value. The term "upper percentile" is used throughout
this handbook, and it is intended to represent values in
the upper tail (i.e., between 90th and 99.9th percentile)
of the distribution of values for a particular exposure
factor.
        Most of the data presented in this handbook
are derived from studies that target (1) the general
population (e.g., USDA food consumption surveys) or
(2) a sample population from a specific area or group
(e.g.,  soil  ingestion study using children  from the
three-city area in southeastern Washington State). The
decision as to whether to use  site-specific or national
values for an assessment may depend on the quality of
the competing data sets as well as on the purpose of the
specific assessment.
        It is important to note that the recommended
values  were derived  solely  from the  U.S.  EPA's
interpretation of the available data. Different values
may be appropriate for the user in consideration of
policy, precedent, strategy, or other factors (e.g., more
up-to-date  data  of  better  quality   and   more
representative of the population of concern).
U.S. EPA. (1992) Guidelines for exposure assessment.
Washington,  DC:  Office  of   Research  and
Development, Office of Health and Environmental
Assessment. EPA/600/Z-92/001.

U.S. EPA.   (1997) Exposure  factors  handbook.
Washington, DC: National Center for Environmental
Assessment, Office  of Research and Development.
EPA/600/P-95/002Fa,b,c.

U.S. EPA.  (2005) Guidance on selecting age groups
for monitoring and assessing childhood exposures to
environmental   contaminants   (2005).  U.S.
Environmental Protection Agency, Washington, D.C.,
EPA/630/P-03/003F.
Page
xxxiv
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	September 2008

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Child-Specific Exposure Factors Handbook
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      AUTHORS, CONTRIBUTORS, AND
                REVIEWERS

        The National Center for Environmental
Assessment  (NCEA),  Office of  Research  and
Development  (ORD)  was   responsible  for  the
preparation of this handbook. Adraft of this document
was prepared by the Exposure Assessment Division of
Versar Inc. in Springfield, Virginia, under U.S. EPA
Contract No. EP-W-04-035.   Earlier versions (i.e.,
2002 and 2005) were prepared under Contract Nos.
68-W-99-0041  and  EP-W-04-035.    The  U.S.
EPA/NCEA's Jacqueline  Moya  served  as Work
Assignment Manager for both the original  and the
revision, providing  overall  direction,  technical
assistance, and serving as contributing author. The
draft was reviewed by U.S. EPA staff who have an
interest  in exposure  factors as  well  as by  an
independent panel of outside experts.
 AUTHORS
 Versar. Inc.
 Adria Diaz
 Marit Espevik
 Christopher Greene
 Ron Lee
 Clarkson Meredith
 Nica Mostaghim
 Chuck Peck
 Todd Ferryman
 Linda Phillips
 Kathleen Saunders-Coon
 Diane Sinkowski
 Patricia Wood
WORD
PROCESSING

Versar. Inc.
Susan Perry
Malikah Moore
Valerie Schwartz
                           U.S. EPA
                           Becky Cuthbertson
                           Jacqueline Moya
                           Linda Phillips
                           John Schaum
                           Laurie Schuda
        The following U.S. EPA individuals reviewed
an earlier draft of this document and provided valuable
comments:

Marcia Bailey, U.S. EPA, Region X

Gary Bangs, U.S. EPA, Risk  Assessment  Forum,
Office of Research and Development

Denis R. Borum, U.S. EPA, Office of Water, Health
and Ecological Criteria Division

Dave Crawford, U.S. EPA, Office of Solid Waste

Becky Cuthbertson, U.S.  EPA, Office of Solid Waste

Michael Dellarco, U.S.  EPA, National  Center for
Environmental Assessment

Lynn  Delpire,  U.S. EPA,  Office  of Prevention,
Pesticides, and Toxic Substances

Jeff Evans, U.S. EPA, Office of Pesticide Programs

Cathy Fehrenbacher, U.S. EPA, Office of Prevention,
Pesticides, and Toxic Substances

Michael Firestone, U.S.  EPA, Office of Children's
Health Protection
                                                    Brenda Foos, U.S. EPA, Office of Children's Health
                                                    Protection

                                                    Henry Kahn,  U.S.  EPA,  National  Center  for
                                                    Environmental Assessment
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                                                     Child-Specific Exposure Factors Handbook
Youngmoo Kim, U.S. EPA, Region VI

Steve Kroner, U.S. EPA, Office of Solid Waste

Tom  McCurdy,  U.S.  EPA,  National  Exposure
Research Laboratory

David Miller, U.S. EPA Office of Pesticide Programs

Deirdre Murphy, U.S. EPA, Office of Air Quality
Planning and Standards

Steve Nako, U.S. EPA, Office of Pesticide Programs
Marian Olsen, U.S. EPA, Region II

Glenn  Rice,  U.S.  EPA,   National  Center  for
Environmental Assessment

Harvey Richmond, U.S.  EPA, Office of Air Quality
Planning and Standards

David Riley, U.S. EPA Region VI

Marybeth Smuts, U.S. EPA, Region I

Marc Stifelman, U.S. EPA, Region X

Valerie Zartarian,  U.S. EPA,  National  Exposure
Research Laboratory

Acknowledgment

The  authors wish  to acknowledge  the  important
contributions of the following U.S. EPA individuals
who conducted additional analyses for the revisions of
this handbook:

David Hrdy, Office of Pesticide Programs

Henry  Kahn, National  Center  for Environmental
Assessment

David Miller,Office of Pesticide Programs

James Nguyen, Office of Pesticide Programs
 Bernard Scheneider, Office of Pesticide Programs

 Nicole Tulve, National Exposure Research Laboratory

 Philip Villanueva, Office of Pesticide Programs

 Jianping Xue, National Exposure Research Laboratory

 Valerie  Zartarian,  National Exposure  Research
 Laboratory

 This document was reviewed by an external panel of
 experts.  The panel was composed of the following
 individuals:

 Ed  Avol, Keck  School of Medicine, University of
 Southern California

 James Bruckner, College of Pharmacy, University of
 Georgia

 Anna  Fan,  California  Environmental Protection
 Agency

 Panos Georgopoulos, UMDNJ Robert Wood Johnson
 Medical School

 Lynn Goldman, Johns Hopkins Bloomberg School of
 Public Health

 Annette Guiseppi-Elie, Dupont Engineering

 Dale Hattis, Clark University

 Diane  Rohiman,  Oregon  Health  and   Science
 University

 P. Barry Ryan, Emory University

 Edward  Stanek,  University of  Massachusetts at
 Amherst

 Alan Stern, University of Medicine and Dentistry of
 New Jersey
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Nga Tran, Exponent

Bernard Weiss,  University of Rochester  School of
Medicine and Dentistry

Robin Wyatt, Columbia University

Rosemary Zaleski, ExxonMobil Biomedical Sciences,
Inc.
Finally, the following U.S. EPA/NCEA individuals
reviewed this document for final clearance:

David Bussard
Jeffrey Frithsen
Nicole Hagan
Charles Ris
John Vandenberg
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Chapter 1 - Introduction	

                               TABLE OF CONTENTS

      INTRODUCTION	  -1
      1.1     PURPOSE	  -1
      1.2     INTENDED AUDIENCE	  -1
      1.3     BACKGROUND  	  -1
      1.4     SELECTION OF STUDIES FOR THE HANDBOOK  	  -3
             1.4.1   General Assessment Factors	  -4
             1.4.2   Selection Criteria	  -4
      1.5     APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
             FACTORS	  -6
      1.6     SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS HANDBOOK . .  -8
      1.7     THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE 	  -9
      1.8     CONSIDERING LIFESTAGE WHEN CALCULATING EXPOSURE AND RISK 	1-11
      1.9     FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT 	1-11
             1.9.1   Dose Equations	1-12
             1.9.2   Use of Exposure Factors Data in Probabilistic Analyses 	1-14
      1.10    CUMULATIVE EXPOSURES	1-15
      1.11    ORGANIZATION	1-15
      1.12    REFERENCES FOR CHAPTER 1	1-16
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	Chapter 1 - Introduction

                                      LIST OF TABLES

Table 1-1.      Characterization of Variability in Exposure Factors	1-21
Table 1-2.      Considerations Used to Rate Confidence in Recommended Values	1-22
Table 1-3.      Integrating U.S. EPA's Guidance on Selecting Age Groups for Monitoring and Assessing
              Childhood Exposures to Environmental Contaminants with U.S. EPA's Supplemental Guidance
              for Assessing Susceptibility from Early-Life Exposure to Carcinogens For Those
              Contaminants Which Act Via a Mutagenic Mode of Action	1-24
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Chapter 1 - Introduction	

                                LIST OF FIGURES
Figure 1-1.     The Exposure-Dose Effect Continuum	1-24
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                                                                                     CSEFH
 1       INTRODUCTION
 1.1     PURPOSE
         The purpose of the Child-Specific Exposure
 Factors Handbook is to provide exposure factors for
 children. The handbook highlights the changes in
 risk assessment practices that were first presented in
 the U.S. Environmental Protection Agency's (EPA)
 Cancer Guidelines, regarding the need to consider
 children as lifestages rather than as subpopulations
 (U.S.  EPA, 2005b).  It also  emphasizes  a  major
 recommendation  in   U.S.  EPA's  Supplemental
 Guidance for Assessing Susceptibility from Early-Life
 Exposure to Carcinogens (U.S. EPA, 2005c) to sum
 exposures  and risks across lifestages rather than
 relying on the use of a lifetime average adult exposure
 to calculate risk. This handbook also uses updated
 information to incorporate any new exposure factors
 data/research that have become available since the
 early 2000's, and is consistent with the U.S. EPA's
 new set of recommended childhood age groups (U.S.
 EPA 2005a), including a standardized way to define
 specific age groups.
         As with the earlier version of the handbook,
 this new version summarizes  key  data on human
 behaviors and characteristics that affect children's
 exposure  to   environmental  contaminants,   and
 provides recommended values to use for these factors.
 These recommendations are not legally binding on
 any U.S. EPA program and should be interpreted as
 suggestions  that Program  Offices  or  individual
 exposure/risk assessors can consider and modify as
 needed.  The decision as  to whether to use site-
 specific or  national values for an assessment may
 depend on the quality of the competing data sets as
 well  as on  the purpose of the specific assessment.
 The handbook has strived to include discussions of
 the issues that assessors may consider in assessing
 exposure among children of different ages, and may
 be used in conjunction with the U.S. EPA document
 entitled Socio-demographic Data Used for Identifying
 Potentially Highly Exposed Populations (U.S. EPA,
 1999).

 1.2     INTENDED AUDIENCE
         The   Child-Specific  Exposure   Factors
 Handbook  may  be used  by  exposure and risk
 assessors, economists, and other interested parties as
a source for data and/or U.S. EPA recommendations
on numeric estimates for behavioral and physiological
characteristics needed to estimate childhood exposure
to toxic contaminants.

1.3     BACKGROUND
        Because  of  physiological  and  behavioral
differences, exposures among children are expected to
be different from exposures among adults.  Children
may be  more  exposed  to  some  environmental
contaminants, because they consume more of certain
foods and water per unit of body weight and have a
higher ratio of body surface area to volume than adults.
Equally important, rapid  changes in behavior  and
physiology may lead to differences in exposure as a
child grows up.  Recognizing that exposures among
infants, toddlers, adolescents, and teenagers can vary
significantly,  the U.S. EPA  published its "Guidance
on Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA. 2005a)."  This update  and revision of the
2002 interim  final Child-Specific Exposure Factors
Handbook (U.S. EPA, 2002a) is designed specifically
to complement  U.S.  EPA's  recommended set of
childhood age groups:
• •      Less than 12 months old: birth to <1 month,
        1 to <3 months, 3 to <6 months, and 6 to < 12
        months.
• •      Greater than 12 months old:  1 to <2 years, 2
        to <3 years, 3 to <6  years, 6 to <11 years, 11
        to <16 years, and 16 to <21 years.
        Many studies have shown that young children
can be exposed to various contaminants, including
pesticides, during normal oral exploration of their
environment (i.e., hand-to-mouth behavior) and by
touching floors,  surfaces,  and  objects such as toys
(Eskenazi et al., 1999; Gurunathan et al., 1998; Lewis
et al., 1999; Nishioka et al., 1999; Garry, 2004).  Dust
and tracked-in soil accumulate in carpets, where young
children spend a  significant amount of time (Lewis et
al., 1999). Children living in agricultural areas may
experience higher exposures to pesticides than do other
children  (Curwin et al., 2007).  Pesticides may be
tracked into their homes  by family  members.   In
addition, children living in agricultural areas may also
play in nearby fields or be exposed via consumption of
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                                                       Child-Specific Exposure Factors Handbook
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 contaminated human milk from their farmworker
 mother (Eskenazi et al, 1999).
         In terms of risk, children may also differ
 from adults in their vulnerability to environmental
 pollutants because of toxicodynamic differences (e.g.,
 when exposures  occur during periods of enhanced
 susceptibility) and/or toxicokinetic differences (i.e.,
 differences in absorption, metabolism, and excretion)
 (U.S.  EPA, 2000a). The immaturity of metabolic
 enzyme systems and clearance mechanisms in young
 children   can   result   in  longer  half-lives   of
 environmental  contaminants (Ginsberg et al., 2002,
 Clewell et al.,  2004).   The cellular immaturity of
 children and the  ongoing growth processes account
 for elevated risk  (AAP, 1997).  Toxic chemicals in
 the environment can  cause neurodevelopmental
 disabilities,  and  the   developing  brain  can  be
 particularly sensitive to environmental contaminants.
 For example, elevated blood lead levels and prenatal
 exposures to even relatively low levels of lead can
 result  in  behavior disorders  and  reductions  of
 intellectual function in children (Landrigan et  al.,
 2005). Exposure to high levels of methylmercury can
 result in developmental disabilities among children
 (Myers et al., 2000).  Other authors have described
 the   importance  of   exposure  timing   (i.e.,
 preconceptional,  prenatal, and postnatal) and how it
 affects the outcomes observed (Selevan et al., 2000).
 Breysee et al. (2005) suggests that higher levels of
 exposure to indoor air pollution and allergens among
 inner-city children compared  to non-inner-city
 children may explain the difference in asthma levels
 between  these  two  groups.   With  respect  to
 contaminants that are carcinogenic via a mutagenic
 mode of  action,  the  U.S. EPA  has found  that
 childhood is  a  particularly  sensitive  period  of
 development, in which cancer potencies per year of
 exposure  can be an order of magnitude higher than
 during adulthood (U.S. EPA, 2005c).
        Executive  Order  13045:  Protection   of
 Children  from Environmental Health  Risks  and
 Safety Risks, signed in 1997, requires  all federal
 agencies  to address health and safety  risks  to
 children,   to   coordinate  research  priorities  on
 children's health, and to ensure that their standards
 take into account special risks to children (EO, 1997).
 To implement  the Order, the U.S. EPA established
 the Office of Children's Health Protection (OCHP)
 (renamed the Office of Children's Health Protection
 and Environmental Education (OCHPEE) in 2005),
 whose job it is to work with Program and regional
 offices  within the U.S. EPA to promote a safe and
 healthy environment for children by ensuring that all
 regulations, standards, policies, and risk assessments
 take into account risks to children. Legislation, such as
 the Food Quality Protection Act and the Safe Drinking
 Water  Act  amendments,  has made  coverage of
 children's health issues more explicit, and research on
 children's health issues is continually expanding. As
 a result of the emphasis on children's risk, the U.S.
 EPA Office  of Research and Development (ORD)
 developed a Strategy for Research on Environmental
 Risks to Children (U.S. EPA, 2000a). The goal of the
 Strategy is to improve the quality  of risk assessments
 for children.  This Child-Specific Exposure Factors
 Handbook is also intended to  support  the  U.S.
 EPA/ORD/NCEA's efforts to improve exposure and
 risk assessments for children.
         In 1997, the U.S. EPA/ORD/NCE A published
 the Exposure Factors Handbook (U.S. EPA, 1997a).
 The handbook includes exposure  factors and related
 data on both adults and children.  Subsequently, the
 U.S. EPA Program Offices  identified the need to
 consolidate all children's exposure data into a single
 document and the Child-Specific Exposure Factors
 Handbook was published in 2002  to fulfill this need.
 This handbook updates the 2002 edition of the Child-
 Specific Exposure Factors Handbook (U.S.  EPA
 2002a).  It provides  non-chemical-specific data on
 exposure  factors  that  can  be used  to  assess
 contributions from dietary and non-dietary ingestion
 exposure, dermal exposure, and inhalation exposure
 among children.  Although the preconceptional and
 prenatal (fetal) life stages are important to consider
 they   are   not  covered   in  this  handbook.
 Preconceptional  exposures   are  included  in  the
 Exposure Factors Handbook since they relate to
 maternal and paternal exposures, and exposure factors
 for pregnant and lactating women are being developed
 as part of a separate effort. This  document does not
 include chemical-specific data  or  information on
 physiological parameters that  may be needed for
 exposure assessments involving physiologically-based
 pharmacokinetic (PBPK) modeling.  The U.S. EPA
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 has  developed  guidance  on how to  use  PBPK
 information in risk assessment. More information on
 the application of PBPK models and supporting data
 is found in U.S. EPA (2006a, 2006b).
         This handbook provides updated exposure
 factor information for children in the following areas:
             ingestion of  water  and other select
             liquids;
             non-dietary ingestion;
             soil and dust ingestion;
             inhalation rates;
             dermal exposure factors such as surface
             area and adherence;
             body weight;
             intake of fruits and vegetables;
             intake of fish and shellfish;
             intake of meat, dairy products, and fats;
             intake of grain products;
             intake of home-produced foods;
             total food intake;
             human milk intake;
             activity factors; and
             consumer products.

         This handbook is a compilation of available
 data from a variety of sources. Most of these  data
 have been described in  detail in the U.S.  EPA's
 Exposure  Factors Handbook (1997a), but  data
 published after the release  of the Exposure Factors
 Handbook are   also included  here.  This latest
 handbook updates the  2002  interim final  Child-
 Specific Exposure Factors Handbook  (U.S. EPA
 2002).  With very few exceptions, the data presented
 here derive from the analyses of the individual study
 authors.   Because  the  studies  included  in  this
 handbook vary in terms of their objectives, design,
 scope, presentation of results, etc., the level of detail,
 statistics, and terminology may vary from study to
 study and from factor to factor. For example, some
 authors used geometric means to present their results,
 while others used arithmetic means  or distributions.
 Authors have sometimes used different age ranges to
 describe data for children. In most cases, the original
 data are unavailable, and the study results cannot be
 reallocated into the standard age groups used in this
 handbook.  Every effort has been made to reallocate
 source   data  into   the   standard  age  groups
recommended by the U.S. EPA in the report entitled
Guidance on SelectingAge Groups for Monitoring and
Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005a; see Section  1.7),
when sufficiently detailed data are available. Within
the constraint of presenting the original material as
accurately as possible, the U.S.  EPA has  made  an
effort to present discussions and results in a consistent
manner.  The strengths and limitations of each study
are discussed to provide the reader with a better
understanding of the uncertainties associated with the
values derived from the study.
        Most of the data presented in this handbook
are derived from studies that target (1) the general
population (e.g., USDA food consumption surveys) or
(2) a sample population from a specific area or group
(e.g.,  fish consumption among Native American
children).   If it  is  necessary  to  characterize  a
population that is not directly covered by the data in
this handbook, the risk or exposure assessor may need
to evaluate whether these data may be used as suitable
substitutes for the  population of interest or whether
there  is a need to seek additional population-specific
data.  If information is needed for  identifying and
enumerating  populations who may be at risk for
greater  contaminant exposures  or  who  exhibit  a
heightened sensitivity to particular chemicals, the
reader is referred to Socio-demographic Data Used for
Identifying Potentially Highly Exposed Populations
(U.S.  EPA, 1999).
        Because of the large number of tables in this
handbook, tables are presented at the  end of  each
chapter, before the  appendices, if any. In conjunction
with  the  Guidance  on  Selecting Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants (U.S. EPA, 2005a), this
handbook is adopting the age group notation "Xto <
Y" (e.g., the age group 3 to < 6 years  is meant to span
a 3-year time interval from a child's 3rd birthday up
until the day before his or her 6th birthday).

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
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                                                       Child-Specific Exposure Factors Handbook
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 estimating  exposure factors  for  children.   The
 handbook contains  summaries of selected  studies
 published through July 2008.
         Certain studies described in this handbook
 are designated as "key," that is, the most useful for
 deriving exposure factors.  The recommended values
 for most exposure factors are based on the results of
 the key studies (See  Section 1.5).  Other studies are
 designated   "relevant,"  meaning  applicable  or
 pertinent, but  not necessarily the  most important.
 This distinction was made on the  strength of the
 attributes listed in the "General Assessment Factors"
 listed below.

 1.4.1    General Assessment Factors
         Many scientific studies were reviewed for
 possible  inclusion  in this  handbook.   Generally,
 studies identified in the Exposure Factors Handbook
 (U.S. EPA,  1997a) as key studies are also included in
 this handbook as key studies. Also included are new
 studies that became available after publication of the
 Exposure Factors Handbook  and the 2002 Child-
 Specific Exposure Factors Handbook (U.S. EPA,
 2002a).   Key  studies from the Exposure  Factors
 Handbook were generally defined as the most useful
 for deriving recommendations for exposure factors.
 The recommended values for most exposure factors
 are based on the results of these studies.  The Agency
 recognizes  the need to evaluate the quality and
 relevance of scientific and technical information used
 in support  of  Agency  actions (U.S. EPA  2002b,
 2003a, 2006c).  When evaluating  scientific and
 technical information, the U.S. EPA's Science Policy
 Council  (SPC) recommends  using five  General
 Assessment Factors (GAFs):  (1)  soundness, (2)
 applicability and utility, (3) clarity and completeness,
 (4) uncertainty and variability, and (5) evaluation and
 review (U.S. EPA  2003a).    These GAFs  were
 adapted  and   expanded  to  include   specific
 considerations   deemed  to be  important  during
 evaluation of exposure factors data, and were used to
 judge the quality of the underlying data used to derive
 recommendations.

 1.4.2    Selection Criteria
         The confidence  ratings for the  various
 exposure factor recommendations, and selection of
 the key  studies  that  form  the basis  for  these
 recommendations,  were based  on specific criteria
 within each of the five GAFs, as follows:

 (1) Soundness: Scientific and technical procedures,
 measures, methods or models employed to generate
 the information are reasonable for, and consistent
 with, the  intended application.  The soundness of the
 experimental procedures or approaches in the study
 designs   of  the  available  studies were  evaluated
 according to the following:

         Adequacy of the Study Approach Used:  In
         general,  more confidence was placed on
         experimental procedures or approaches that
         more likely or closely captured the desired
         measurement.     Direct  exposure   data
         collection  techniques,   such  as   direct
         observation, personal monitoring devices, or
         other known methods were preferred where
         available.     If   studies  utilizing   direct
         measurement were not available, studies were
         selected that relied on validated  indirect
         measurement methods  such  as surrogate
         measures (such as heart rate for  inhalation
         rate),  and  use   of  questionnaires.    If
         questionnaires or surveys were used, proper
         design  and procedures  include an adequate
         sample  size for  the  population   under
         consideration, a response rate large enough to
         avoid biases, and avoidance  of bias in the
         design of the instrument and interpretation of
         the  results. More confidence was placed in
         exposures factors that relied on studies that
         gave appropriate consideration to these study
         design  issues.    Studies were also deemed
         preferable if based on primary data,  but
         studies based on secondary sources were also
         included  where  they  offered an original
         analysis.  In  general, higher confidence was
         placed on exposure factors based on primary
         data.

         Minimal (or Defined) Bias in Study Design:
         Studies were sought that were designed with
         minimal  bias,  or at least if biases were
         suspected to  be present, the direction of the
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         bias (i.e., an over or underestimate of the
         parameter)  was either  stated or apparent
         from the study design. More confidence was
         placed on exposure factors based on studies
         that minimized bias.

 (2)   Applicability and utility:  The  information is
 relevant for the Agency's intended         The
 applicability and utility of the available studies were
 evaluated based on the following criteria:
         Focus on Exposure Factor  of  Interest:
         Studies   were  preferred  that   directly
         addressed the exposure factor of interest, or
         addressed  related  factors   that   have
         significance   for   the   factor  under
         consideration.  As an example of the latter
         case,  a  selected  study contained useful
         ancillary information concerning fat content
         in fish, although it did not directly address
         fish consumption.

         Representativeness  of the  Population:
         More confidence was placed in studies that
         addressed the U.S. population. Data  from
         populations outside the U. S. were sometimes
         included  if behavioral patterns  or other
         characteristics of exposure were similar.
         Studies seeking to characterize a particular
         region or sub-population were selected, if
         appropriately   representative   of  that
         population.   In cases where data  were
         limited, studies with limitations in this area
         were included and limitations were noted in
         the  handbook.  Higher confidence ratings
         were given to  exposure factors where the
         available data were  representative of the
         population of interest.

         Currency  of  Information:      More
         confidence was placed in studies that were
         sufficiently recent  to  represent current
         exposure conditions.  This is an important
         consideration for those  factors that change
         with time.  Older data were evaluated and
         considered in instances where the variability
         of the  exposure   factor  over time  was
         determined  to   be  insignificant   or
        unimportant.  In some cases, recent data were
        very limited.  Therefore, the data provided in
        these instances were the only available data.
        Limitations on the age of the data were noted.
        Recent studies are more likely to use state-of-
        the-art methodologies that reflect advances in
        the exposure assessment field. Consequently,
        exposure factor recommendations based on
        current data were given higher confidence
        ratings than those based on older data, except
        in cases where the age of the data would not
        affect the recommended values.

        Adequacy  of   data  collection  period:
        Because  most users of the handbook  are
        primarily  addressing chronic exposures,
        studies were  sought that utilized the most
        appropriate techniques for collecting data to
        characterize long-term behavior.    Higher
        confidence  ratings were given to exposure
        factor recommendations that were based on
        an adequate data collection period.

(3)  Clarity and completeness:  The degree of clarity
and completeness with which the data, assumptions,
methods, quality assurance, sponsoring organizations
and analyses employed to generate the information are
documented. Clarity and completeness was evaluated
based on the following criteria.

        Accessibility: Studies that the user could
        access  in their  entirety, if needed, were
        preferred.

        Reproducibility:  Studies that contained
        sufficient information so that methods could
        be reproduced, or could be evaluated, based
        on the details of the  author's work, were
        preferred.
        Quality   Assurance:
Studies   with
        documented quality assurance/quality control
        measures were preferred. Higher confidence
        ratings were given to exposure  factors that
        were based on studies  where  appropriate
        quality assurance/quality control  measures
        were used.
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 (4) Variability and uncertainty: The variability and
 uncertainty  (quantitative  and qualitative)  in the
 information or the procedures, measures, methods or
 models are evaluated and characterized. Variability
 arises from true heterogeneity across people, places or
 time and can  affect  the  precision  of  exposure
 estimates  and the degree to  which they can be
 generalized.  The types of variability include: spatial,
 temporal, and inter-individual. Uncertainty represents
 a lack of knowledge about factors affecting exposure
 or risk and can lead to inaccurate or biased estimates
 of exposure. The types  of  uncertainty include:
 scenario, parameter, and model. The uncertainty and
 variability associated with the studies was  evaluated
 based on the following criteria.

         Variability in the population:   Studies
         were   sought  that   characterized   any
         variability  within   populations.     The
         variability  associated  with  the studies
         presented in this handbook is characterized
         as  described  in  Section  1.5.   Higher
         confidence ratings were  given to exposure
         factors  that were  based on studies where
         variability was well characterized.

         Uncertainty:   Studies  were  sought  with
         minimal uncertainty in the data, which was
         judged  by evaluating all  the considerations
         listed above.   Studies were preferred that
         identified uncertainties, such as those due to
         inherent variability in environmental and
         exposure-related  parameters  or possible
         measurement  error.   Higher confidence
         ratings were given to exposure factors based
         on  studies where uncertainty  had  been
         minimized.

 (5)  Evaluation  and review:  The  information or the
 procedures,  measures,  methods or  models  are
 independently verified, validated,  and peer reviewed.
 Relevant factors that were considered included:

         Peer review:  Studies selected were those
         from the peer-reviewed literature and  final
         government  reports.    Unpublished   and
         internal or interim reports were avoided.
         Number and agreement of studies:  Higher
         confidence was placed on recommendations
         where data were available from more than
         one key study and there was good agreement
         between studies.
 1.5
        APPROACH  USED   TO  DEVELOP
        RECOMMENDATIONS   FOR
        EXPOSURE FACTORS
        As discussed above,  the U.S.  EPA first
reviewed the literature  pertaining to a factor  and
determined key studies.  These key studies were used
to derive  recommendations  for the values of each
factor. The recommended values were derived solely
from the U.S. EPA's  interpretation of the available
data. Different values may be appropriate for the user
in consideration of policy, precedent, strategy, or other
factors such as site-specific  information.   The U.S.
EPA's  procedure for developing recommendations
was as follows:

(1)  Study Review and Evaluation: Key studies were
evaluated  in terms of both quality and relevance to
specific populations (general U. S. population,  age
groups, gender, etc.).  The criteria for assessing the
quality of studies are described in Section 1.4.

(2)  Single versus Multiple Key Studies: If only one
study was classified as key for a particular factor, the
mean value from that  study  was selected  as  the
recommended central value  for that  population.  If
multiple key studies with reasonably equal quality,
relevance,  and  study  design  information were
available, a weighted mean (if appropriate, considering
sample size and other statistical factors) of the studies
was chosen as the recommended mean value.  If the
key  studies were judged to  be unequal in quality,
relevance,  or study design,  the range of means is
presented and the user of this handbook must employ
judgment in selecting the most appropriate value for
the population of interest. Recommendations for upper
percentiles, when multiple studies were available, were
calculated  as the midpoint  of the range of upper
percentile values  of the studies for each  age group
where data were available.
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 (3)  Variability:  The variability of the factor across
 the  population is discussed.   For recommended
 values, as well as for each of the studies on which the
 recommendations   are  base,  variability  is
 characterized in one or more of three ways: (1) as a
 table with various percentiles or ranges of values; (2)
 as analytical distributions with specified parameters;
 and/or (3) as a qualitative discussion. Analyses to fit
 standard or parametric distributions (e.g., normal,
 lognormal)  to the  exposure data have  not  been
 performed by the authors of this handbook, but have
 been reproduced as they were found in the literature.
 Recommendations on the use of these distributions
 are made where appropriate based on the adequacy of
 the supporting data.  The list  of exposure factors and
 the way in which variability  has been characterized
 throughout this  handbook (i.e., average,  median,
 upper  percentiles,   multiple   percentiles,  fitted
 distribution) are presented  in Table 1-1.
         In the providing  recommendations for the
 various  exposure  factors, an attempt was made to
 present percentile values that are consistent with the
 exposure  estimators  defined  in  Guidelines for
 Exposure Assessment (U.S. EPA, 1992a) (i.e., mean,
 50th,  90th,  95th, 98th,  and 99.9th percentile).
 However, this was not always possible, because the
 data available were limited for some factors, or the
 authors of the study did not provide such information.
 It is important to note, however, that these percentiles
 were discussed in the guidelines within the context of
 risk descriptors and not individual exposure factors.
 For example, the guidelines  state  that the assessor
 may derive a high-end estimate of exposure by using
 maximum or near maximum values for one or more
 sensitive exposure factors, leaving others at  their
 mean value.  The term "upper percentile"  is used
 throughout this  handbook,  and it is intended to
 represent values in the upper tail (i.e., between 90th
 and 99.9th percentile) of the distribution of values for
 a particular exposure factor.

 (4) Uncertainty: Uncertainties are discussed in terms
 of data limitations, the range of circumstances over
 which the estimates were (or were not) applicable,
 possible biases in the values themselves, a statement
 about parameter uncertainties (measurement error,
 sampling error) and model or scenario uncertainties
if models  or scenarios  were used  to derive the
recommended value.  A discussion of variability and
uncertainty  for  exposure factors  is  presented in
Chapter 2 of this handbook.

(5)  Confidence Ratings:   Finally,  the  U.S.  EPA
assigned a confidence rating  of low, medium or high
to each  recommended value.   This  rating is not
intended to represent an uncertainty analysis; rather, it
represents the U.S. EPA's judgment on the quality of
the   underlying  data  used   to   derive   the
recommendation. This judgment was made using the
General  Assessment Factors (GAFs)  described in
Section 1.4.  Table 1-2 provides an adaptation of the
GAFs, as they pertain to the confidence ratings for the
exposure factor recommendations.  Clearly, there is a
continuum from  low to high, and judgment that was
used to determine these  ratings.  Recommendations
given  in this  handbook are  accompanied  by  a
discussion of the rationale for their rating.
        It is important to note that the study elements
listed in Table 1-2 do not have the same weight when
arriving at the overall confidence rating for the various
exposure factors.  The relative weight of each of these
elements for the various factors were subjective and
based on the professional judgement of the authors of
this handbook. Also, the relative weights  depend on
the exposure factor of interest.  For example, the
adequacy of the  data collection period may be more
important when determining usual intake of foods in
a population, but it is not as important for factors
where long-term variability  may be small, such as
tapwater intake.   In the  case of tapwater intake, the
currency of the data was  a critical element in
determining the final rating.  In general, most studies
ranked high with regard to  "level  of peer review,"
"accessibility," "focus on the factor of interest," and
"data pertinent to the U.S." because the  U.S.  EPA
specifically sought studies for the handbook that met
these criteria.
        The elements in Table 1-2 were important
considerations for  inclusion  of  a  study in  this
handbook.  However, a high score for these elements
did not necessarily translate into a high overall score.
Other considerations went into determining the overall
score.  One such consideration was the ease at which
the exposure factor of interest could be measured. For
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 example, soil ingestion by children can be estimated
 by measuring, in the feces of children, the levels of
 certain  elements found  in soil.   Body  weight,
 however, can be measured directly, and it is therefore
 a more  reliable  measurement.  The  fact that soil
 ingestion is more difficult to measure than body
 weight is reflected in the overall confidence rating
 given to both of these factors.  In general, the better
 the methodology used to measure the exposure factor,
 the higher the confidence in the value.

 (6) Recommendation  Tables:    The U.S.  EPA
 developed a table at the beginning of each chapter
 that  summarizes the recommended values for  the
 relevant factor.    Table  ES-1  of the  Executive
 Summary of this handbook summarizes the principal
 exposure factors  addressed in this handbook and
 provides the confidence ratings for each exposure
 factor.

 1.6     SUGGESTED REFERENCES FOR USE
         IN   CONJUNCTION  WITH   THIS
         HANDBOOK
         Some of the  steps for performing  an
 exposure assessment are: (1) identifying source of the
 environmental contamination and the media that
 transports the contaminant;  (2) determining  the
 contaminant   concentration; (3) determining  the
 exposure scenarios,  and pathways and routes  of
 exposure;  (4) determining  the  exposure  time,
 frequency, and  duration;  and (5) identifying  the
 exposed population.  Many of the issues  related to
 characterizing exposure  from  selected  exposure
 pathways have  been addressed in  a number of
 existing U. S. EPA documents.  Some of these provide
 guidance while others demonstrate various aspects of
 the exposure process.  These include, but are  not
 limited,  to  the  following references  listed  in
 chronological  order:

 •       Methods  for  Assessing  Exposure  to
         Chemical Substances, Volumes 1-13 (U.S.
         EPA, 1983-1989);

 •       Standard Scenarios for Estimating Exposure
         to Chemical Substances During  Use of
         Consumer Products (U.S. EPA, 1986a);
         Selection Criteria for Mathematical Models
         Used  in  Exposure Assessments:  Surface
         Water Models (U.S. EPA, 1987);

         Selection Criteria for Mathematical Models
         Used in Exposure Assessments: Groundwater
         Models (U.S. EPA, 1988);

         Risk Assessment Guidance for Superfund,
         Volume I, Part A, Human Health Evaluation
         Manual (U.S. EPA, 1989);

         Methodology for Assessing  Health Risks
         Associated  with   Indirect  Exposure  to
         Combustor Emissions (U.S. EPA, 1990);

         Risk Assessment Guidance for Superfund,
         Volume  I,   Part  B,  Development  of
         Preliminary Remediation  Goals (U.S. EPA,
         1991a);

         Risk Assessment Guidance for Superfund,
         Volume I,  Part  C,  Risk Evaluation of
         Remedial Alternatives (U.S. EPA, 1991b);

         Guidelines for Exposure  Assessment (U.S.
         EPA, 1992a);

         Dermal Exposure Assessment:  Principles
         and Applications (U.S. EPA, 1992b);

         Estimating   Exposures  to   Dioxin-Like
         Compounds (U.S. EPA, 1994a);

         5*0/7 Screening Guidance (U.S. EPA 1996a);

         Series 875  Occupational and Residential
         Exposure Test Guidelines - Final
         Guidelines - Group A -Application Exposure
         Monitoring  Test   Guidelines  (U.S.  EPA
         1996b);

         Series 875  Occupational and Residential
         Exposure  Test Guidelines - Group B - Post
         Application  Exposure  Monitoring   Test
         Guidelines (U.S. EPA 1996c);
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        Policy for Use of Probabilistic Analysis in
        Risk Assessment at the U.S. Environmental
        Protection Agency, (U.S. EPA, 1997b);
         Guiding  Principles  for  Monte
         Analysis (U.S. EPA, 1997c);
Carlo
         Sociodemographic  Data  for Identifying
         Potentially Highly Exposed Populations
         (U.S. EPA, 1999);

         Options   for   Developing   Parametric
         Probability  Distributions  for Exposure
         Factors (U.S. EPA 2000b);

         Risk Assessment Guidance for Superfund,
         Volume I, Part D, Standardized Planning,
         Reporting, and Review of Superfund Risk
         Assessments (U.S. EPA, 200la);

         Risk Assessment Guidance for Superfund
         Volume III, Part A, Process for Conducting
         Probabilistic Risk Assessments (U.S. EPA,
         200 Ib);

         Framework for Cumulative Risk Assessment
         (U.S. EPA, 2003b);

         Example Exposure Scenarios (U.S. EPA,
         2003c);

         Risk Assessment Guidance for Superfund,
         Volume I, Part E, Supplemental Guidance
         for Dermal  Risk Assessment (U.S. EPA,
         2004);

         Guidance on  Selecting Age  Groups for
         Monitoring  and  Assessing Childhood
         Exposures to Environmental Contaminants
         (U.S. EPA, 2005a);

         Cancer Guidelines for Carcinogen  Risk
         Assessment  Supplemental  Guidance  for
         Assessing Susceptibility from  Early-Life
         Exposure to  Carcinogens  (U.S.  EPA,
         2005b);
Supplemental  Guidance  for   Assessing
Susceptibility from  Early-Life Exposure to
Carcinogens (U.S. EPA, 2005c);

Protocol for Human Health Risk Assessment
Protocol for Hazardous Waste Combustion
Facilities (U.S. EPA, 2005d);
             •       A Framework for Assessing Health Risk of
                    Environmental  Exposures  to  Children
                    (Final). (U.S. EPA 2006d); and

             •       Concepts,  methods, and data sources for
                    cumulative health risk assessment of multiple
                    chemicals, exposures and effects: a resource
                    document (Final) (U.S. EPA, 2008).

             These documents may serve as valuable information
             resources to assist in the assessment of exposure. The
             reader is encouraged to refer to them for more detailed
             discussion.

             1.7     THE USE OF AGE GROUPINGS WHEN
                    ASSESSING EXPOSURE
                    When this handbook was first published in
             2002, no  specific guidance existed with regard to
             which age groupings should be used when assessing
             children's exposure. Age groupings varied from case
             to case and among Program Offices within the U.S.
             EPA. They depended on availability of data and were
             often based on professional judgement. More recently,
             the U. S. EPA has endeavored to establish a consistent
             set of age groupings and publish guidance on this topic
             (U.S. EPA 2005a).  This revision of the handbook
             attempts to present data in a manner consistent with
             the U.S. EPA's recommended set of age groupings.
                    The development of standardized age bins
             was the subject of discussion in a 2000 workshop
             sponsored by the U.S. EPA Risk  Assessment Forum.
             The workshop was titled "Issues  Associated  with
             Considering Developmental Changes in Behavior and
             Anatomy  When Assessing  Exposure to  Children"
             (U. S. EPA, 200 Ic).  The purpose of this workshop was
             to gain insight and input into factors that need to be
             considered when developing standardized age bins and
             identify future research necessary to accomplish these
             goals. Panelists were divided into two groups.   One
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 group focused their discussions  on defining  and
 characterizing the  important  facets of behavioral
 development during childhood, while the other group
 focused on defining and characterizing physiological
 development  during  childhood.    During  the
 workshop, it was recognized that the ultimate goal of
 exposure assessment is to develop a day-to-day model
 of human life that can predict the chemical exposures
 an individual is likely to  face at  any point in  life.
 However, this is not likely to be accomplished in the
 near future, and assessors  often need to classify
 individuals into age bins in order  to simplify the
 exposure model. The recommendations listed below
 are those of the panel members and were considered
 by the  U.S.  EPA in the  development of  age
 groupings:

         Panelists agreed that child development is a
         series of discrete events, but these events
         occur along a contiuum.

         Age  grouping/bins are a useful guide to
         fulfill the Agency's immediate need, but are
         only a crude approximation of an underlying
         distribution.   Ultimately,  sufficient data
         should be gathered to develop a continuous
         multivariate model that can replace bins.

         Adequacy of existing exposure data is highly
         variable.

         A  considerable   amount   of  additional
         information already exists, but it is dispersed
         in the literature.  It was recommended that
         the  U.S.  EPA consults  with  experts in
         developmental  biology,   physiology,
         pharmacology, and toxicology and conducts
         an in-depth review of the  literature.

         Long term research should  include  the
         development of integrated  data sets  that
         combines information about the exposure
         factors with biomarkers  of exposure  and
         effects.

         The  definition  of  age  groups/bins  for
         childhood  exposure   assessment   are
         inextricably  linked  to  toxicokinetic  and
         toxicodynamic issues.

         The two break out groups (i.e.,  behavioral
         and physiological)  offered the  following
         preliminary ideas for age groupings:

 Age grouping based on behavioral
 characteristics
         0-2 months
         2-6 months
         6-12 months
         1-2 years
         2-6 years
         6-11 years
         11-16 years
         16-21 years
 Age grouping based on physiological
 characteristics
         0-1 month
         1-6 months
         6-12 months
         1-3 years
         3-9 years
         9-21 years

         One can observe that there was fairly good
 agreement among the two groups with regard to the
 age groupings that are  important  for infants  and
 toddlers. However, there was some disagreement with
 regard to  the  older  children.    Appropriate  age
 groupings  depend  not  only  on  behavioral  and
 physiological characteristics, but also on the specific
 scenario being studied and chemical of concern.
         Based upon consideration of the findings of
 the technical workshop, as well as analysis of available
 data, U.S. EPA developed guidance that established a
 set of recommended age groups for development of
 exposure factors for children entitled "Guidance for
 Selecting Age Groups for Monitoring and Assessing
 Childhood  Exposures   to  Environmental
 Contaminants'" (U.S. EPA, 2005a).  This  revision of
 the handbook was  developed specifically to present
 exposure factors data in a manner consistent with U. S.
 EPA's recommended set of childhood age  groupings.
 The recommended age groups (U.S. EPA,  2005a) are
 as follows:
         Birth to <1 month
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         1 to <3 months
         3 to <6 months
         6 to < 12 months
         1 to <2 years
         2 to <3 years
         3 to <6 years
         6 to <11 years
         11 to <16 years
         16to<21years
 1.8
        CONSIDERING LIFESTAGE WHEN
        CALCULATING  EXPOSURE  AND
        RISK
        A key component of U.S. EPA's Guidance
on  Selecting Age  Groups  for Monitoring  and
Assessing Childhood Exposures to Environmental
Contaminants (U. S. EPA 2005a) involves the need to
sum age-specific differences in exposure across time
when  assessing long-term exposure,  as well as
integrating  these  age-specific  exposures  with
age-specific  differences  in toxic potency in those
cases where information  exists  to  describe such
differences: an example is carcinogens that act via a
mutagenic mode of action (Supplemental Guidance
for Assessing Susceptibility from Early-Life Exposure
to Carcinogens - U.S. EPA, 2005c). When assessing
chronic risks (i.e., exposures greater than 10 percent
of human lifespan), rather than assuming a constant
level of exposure for 70 years (usually consistent with
an  adult  level  of exposure), the  Agency is now
recommending   that assessors  calculate chronic
exposures by summing time-weighted exposures that
occur at each lifestage; this handbook provides data
arrayed by childhood age in order to follow this new
guidance  (U.S.  EPA 2005a).  This approach is
expected to increase the accuracy of risk assessments,
because it will take into account lifestage differences
in   exposure.  Depending  on   whether
body-weight-adjusted childhood exposures are either
smaller or larger compared  to  those for adults,
calculated risks could either  decrease or increase
when  compared  with the historical approach of
assuming a  lifetime of a constant  adult level of
exposure.
        The Supplemental Guidance for Assessing
Susceptibility   from  Early-Life   Exposure  to
Carcinogens also recommended that in those cases
where age-related differences in toxicity were  also
found to occur, differences in both toxicity and
exposure would need to be integrated  across all
relevant age intervals. This guidance describes such a
case for carcinogens that act via a mutagenic mode of
action, where  age dependent potency adjustments
factors (ADAFs) of lOx and 3x are recommended for
children ages birth < 2 years, and 2 <  16 years,
respectively when there is exposure during those years
and available data are insufficient to derive chemical-
specific adjustment factors.
        Table   1-3, along with Chapter  6 of the
"Supplemental Guidance" have been developed to help
the reader understand how to  use the new sets of
exposure and potency age groupings when calculating
risk  through  the integration of lifestage specific
changes in exposure and potency.
        Thus, Lifetime Cancer Risk (for a population
with average  life  expectancy  of 70  years)  = ?
(Exposure x Duration/70 yrs x Potency x ADAF)
summed across all the age groups presented in Table
1-3.  This is a departure from the way cancer  risks
have historically been calculated based upon the
premise that risk is proportional to the daily average of
the long term adult dose.

1.9     FUNDAMENTAL  PRINCIPLES   OF
        EXPOSURE ASSESSMENT
        The definition of exposure as used by the
International Programme on Chemical Safety (IPCS,
2001) is the "contact of an organism with a chemical
or physical agent, quantified as the amount of chemical
available at the exchange boundaries of the organism
and available for absorption."  This means contact
with the visible exterior of a person such as the  skin,
and openings such as the mouth, nostrils, and lesions.
The process of a chemical entering the body can be
described in two steps: contact (exposure) followed by
entry (crossing the boundary).  In the context of
environmental risk assessment, risk to an individual or
population can be represented as a continuum from the
source through exposure to dose to effect as shown in
Figure 1-1  (U.S. EPA, 2003d; IPCS, 2006).  The
process begins with a chemical or agent released from
a  source  into  the  environment.   Once  in the
environment, the chemical or agent can be transformed
and  transported through  the environment via air,
water, soil, dust, and diet.   Individuals become in
contact  with  the chemical through  inhalation,
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 ingestion, or skin/eye contact.   The individual's
 activity patterns as well as the concentration of the
 chemical will determine the magnitude, frequency,
 and duration of the exposure. The exposure becomes
 an absorbed dose  when  the chemical  crosses an
 absorption  barrier.   When  the chemical  or its
 metabolites interact with a target tissue, it becomes a
 target tissue dose, which may lead to  an adverse
 health outcome. The text  under the boxes in Figure
 1-1 indicates the specific  information that may be
 needed to characterize each box.

 1.9.1    Dose Equations
         Starting with a general integral equation for
 exposure (U.S. EPA, 1992a), several dose equations
   can  be   derived  depending  upon  boundary
 assumptions.
 One of the more useful of these derived equations is
 the Average Daily Dose (ADD). The ADD, which is
 used for many noncancer effects, averages exposures
 or doses over the period of time exposure occurred.
 The  ADD  can be calculated  by averaging the
 potential  dose  over body  weight and an averaging
 time.
                   External Dose
 ADDnnt =          .   	7	:	—  (Eqn 1-1)
      Pot     Body Weight  x Averaging  Time v  M     '
 The exposure can be expressed as follows:
 External Dose = C x IR
(Eqn 1-2)
         Where:
             C  = Contaminant Concentration
             IR = Intake Rate
             ED = Exposure Duration

         Contaminant   concentration   is   the
 concentration of the contaminant in the medium (air,
 food, soil, etc.) contacting the body and has units of
 mass/volume or mass/mass.
         The intake  rate  refers  to the  rates of
 inhalation, ingestion, and dermal contact, depending
 on the route of exposure.  For ingestion, the intake
 rate is  simply the amount of food containing the
 contaminant of interest that an individual ingests
 during some specific time period (units of mass/time).
Much of this handbook is devoted to rates of ingestion
for some broad classes of food.  For inhalation, the
intake rate is the rate at which contaminated air is
inhaled. Factors presented in this handbook that affect
dermal exposure are skin surface area and estimates of
the amount of soil that adheres to the skin.
        The exposure duration is the length of time of
contaminant contact. The length time a person lives in
an  area, frequency of bathing,  time  spent  indoors
versus outdoors, etc., all affect the exposure duration.
Chapter 16, Activity Factors, gives some examples of
population behavior/activity  patterns that may be
useful for estimating exposure durations.
        When the above parameter values IR and ED
remain constant over time, they are substituted directly
into the exposure equation.  When they change with
time, a  summation approach is needed to calculate
exposure. In either case, the exposure duration is the
length of time exposure occurs at the concentration
and the intake rate specified by the other parameters in
the equation.
        Note  that the  advent of childhood  age
groupings  means  that separate ADD's should be
calculated for each age group considered.  Chronic
exposures can then be calculated by summing across
each lifestage-specific ADD.
        Cancer  risks  have   traditionally  been
calculated in those cases where a linear non-threshold
model is assumed, in terms of lifetime probabilities by
utilizing dose values  presented in terms of lifetime
ADDs (LADDs).  The LADD takes the form of the
Equation 1-1, with  lifetime replacing averaging time.
While the use of  LADD may be  appropriate when
developing screening level estimates of cancer risk, as
discussed in Section 1.8 above, the U.S. EPA is now
recommending  that risks should  be  calculated by
integrating exposures  or risks throughout all lifestages
(U.S. EPA, 1992a).
        For some  types  of  analyses,  dose  can be
expressed as a total amount (with units of mass, e.g.,
mg) or  as  a dose rate in terms of mass/time (e.g.,
mg/day), or as a rate  normalized to body mass (e.g.,
with units of mg of chemical per kg of body weight per
day (mg/kg-day)). The LADD is usually expressed in
terms of mg/kg-day or other mass/mass-time units.
        In most  cases  (inhalation and  ingestion
exposures),  the   dose-response   parameters  for
carcinogenic  risks have  been  adjusted  for  the
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 difference in absorption across body barriers between
 humans and the experimental animals used to derive
 such parameters. Therefore, the exposure assessment
 in these cases is based on the potential dose, with no
 explicit  correction  for  the  fraction   absorbed.
 However, the exposure assessor needs to make such
 an adjustment when calculating dermal exposure and
 in other specific cases when  current information
 indicates that the human absorption factor used in the
 derivation   of  the   dose-response   factor  is
 inappropriate.
         For carcinogens, the duration  of a lifetime
 has traditionally been assigned the nominal value of
 70  years  as a  reasonable  approximation.  For
 exposure estimates to be used for assessments other
 than carcinogenic  risk, various averaging periods
 have been used.  For acute exposures, the  doses are
 usually averaged over a day or a single event. For
 nonchronic noncancer effects, the time period used is
 the  actual period of exposure (exposure duration).
 The objective in selecting the exposure averaging
 time is to express the exposure in a way which can be
 combined with  the dose-response relationship  to
 calculate risk.
         The body weight to be used in the exposure
 Equation 1-1 depends on the units of the exposure
 data presented in this handbook. For example, for
 food ingestion,  the body weights of the  surveyed
 populations were known in the USDA  surveys, and
 they were explicitly factored into the food intake data
 in order to calculate the intake as g/kg body weight-
 day. In this case, the body weight has  already been
 included in the  "intake rate" term in Equation 1-2,
 and the exposure assessor does not need to  explicitly
 include body weight.
         The units of intake in this handbook for the
 incidental  ingestion of  soil  and  dust  are  not
 normalized to body weight. In this case, the exposure
 assessor will need  to  use  (in  Equation  1-1) the
 average weight of the exposed population during the
 time when the  exposure actually occurs.  When
 making body weight assumptions, care must be taken
 that the values used for the population parameters in
 the  dose-response analysis are consistent with the
 population parameters used in the exposure analysis.
  Intraspecies  adjustments based on lifestage can be
 made using a scaling factor of  BW 4 (U.S.  EPA
 2006d, 2006e).   Some of the parameters (primarily
concentrations) used  in estimating exposure  are
exclusively  site  specific,  and therefore   default
recommendations should not be used.  It should be
noted  that body weight  is  correlated with  food
consumption rates and inhalation rates.
        The link between the intake rate value and the
exposure duration value is a  common  source of
confusion in  defining exposure  scenarios.   It is
important to define the duration estimate so that  it is
consistent with the intake rate:

        The intake rate can be based on an individual
        event (e.g., serving size  per event).   The
        duration should be based on the number of
        events or, in this case, meals.

        The intake rate also can be based on a long-
        term average, such as 10 g/day. In this case
        the duration should be based on the total time
        interval over which the  exposure occurs.

        The objective is to define the terms so that,
when multiplied, they give the appropriate estimate of
mass  of contaminant  contacted.    This  can  be
accomplished by basing the intake rate on  either a
long-term average (chronic exposure)  or an event
(acute exposure) basis, as long as the duration value is
selected appropriately.
        Inhalation dosimetry is employed to derive the
human equivalent exposure concentrations on which
inhalation unit risks, and reference concentrations, are
based (U.S. EPA, 1994b). U.S. EPA has traditionally
approximated children's respiratory exposure by using
adult values, although a recent review (Ginsberg et al.,
2005) concluded that there may be some cases where
young  children's greater inhalation  rate per body
weight or pulmonary  surface area as compared to
adults can result in greater exposures than adults.  The
implications of this difference for inhalation dosimetry
and children's risk assessment were discussed at a peer
involvement workshop hosted by the U. S.EPA in 2006
(Foos et al., 2008).
        Consideration   of    lifestage-particular
physiological characteristics in the dosimetry analysis
may result in a refinement to the human equivalent
concentration to insure relevance in risk assessment
across lifestages, or might conceivably conclude with
multiple  human equivalent  concentrations,   and
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 corresponding  inhalation unit risk values  (e.g.,
 separate for childhood and adulthood)  (U.S. EPA,
 2005b). The RfC methodology, which is  described in
 Methods for Derivation of Inhalation Reference
 Concentrations  and  Applications  of Inhalation
 Dosimetry  (U.S. EPA, 1994b), allows  the user to
 incorporate population-specific assumptions into the
 models. The reader is referred to U. S. EPA guidance
 (U.S.   EPA,   1994b)   on  how  to make  these
 adjustments.
         There  are no  specific  exposure  factor
 assumptions in the derivation of Reference  Doses
 (RfDs). The assessment of the potential for adverse
 health effects in infants and children is part of the
 overall hazard and dose-response assessment for a
 chemical.   Available  data pertinent to children's
 health risks are evaluated along with data on adults
 and the no-observed-adverse-effect-level  (NOAEL) or
 benchmark dose (BMD) for the most sensitive critical
 effect(s), based on consideration of all health effects.
 By doing this, protection of the health of children will
 be considered along  with  that of  other sensitive
 populations.  In  some cases,  it  is  appropriate to
 evaluate the potential  hazard to children separately
 from the assessment for the general population or
 other population subgroups.

 1.9.2    Use   of  Exposure  Factors  Data  in
         Probabilistic Analyses
         Although this handbook is not intended to
 provide complete guidance on the use of Monte Carlo
 and other probabilistic analyses, some of the data in
 this  handbook may  be appropriate   for use in
 probabilistic assessments. The use of Monte Carlo or
 other probabilistic analysis requires characterization
 of the variability of exposure factors and requires the
 selection of distributions or histograms for the input
 parameters of the dose equations presented in Section
 1.9.1.  The following  suggestions are provided for
 consideration when using such techniques:

         The exposure assessor should only consider
         using probabilistic analysis  when there are
         credible distribution data (or ranges) for the
         factor under consideration.   Even if these
         distributions  are known, it may  not be
         necessary to  apply this  technique.   For
         example, if only average exposure values are
         needed,  these  can  often  be  computed
         accurately by using average values for each of
         the input parameters unless a  non-linear
         model is used. Probabilistic analysis is also
         not necessary when conducting assessments
         for screening purposes, i.e., to determine if
         unimportant pathways can be eliminated. In
         this  case,   bounding  estimates  can  be
         calculated using maximum or near maximum
         values  for  each of the input parameters.
         Alternatively,  the  assessor  may  use the
         maximum values  for those parameters that
         have the greatest variance.

         It is important to note that the selection of
         distributions can be highly site-specific and
         dependent on the purpose of the assessment.
         In some cases the selection of distributions
         are driven  by specific legislation.  It will
         always  involve some degree of judgment.
         Distributions derived from national data may
         not represent local conditions. The assessor
         needs to evaluate the site-specific data, when
         available,   to  assess  their  quality   and
         applicability. The assessor may decide to use
         distributional data drawn from the national or
         other surrogate population. In this case, it is
         important that the assessor address the extent
         to which local conditions may differ from the
         surrogate data.

         It   is  also  important   to  consider  the
         independence/dependence  of variables and
         data used in a simulation. For example, it
         may be  reasonable to assume that ingestion
         rate and contaminant concentration in foods
         are independent variables, but ingestion rate
         and  body  weight  may  or  may not  be
         independent.

         In addition to  a qualitative statement of
 uncertainty, the representativeness assumption should
 be appropriately addressed as part of a  sensitivity
 analysis.

         Distribution  functions   to  be   used  in
         probabilistic  analysis may be derived  by
         fitting an appropriate function to empirical
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     data. In doing this, it should be recognized that
     in the lower and upper tails of the distribution
     the  data are scarce, so that several functions,
     with radically different shapes in the extreme
     tails, may be consistent with the data. To avoid
     introducing  errors into the  analysis  by  the
     arbitrary choice  of an inappropriate function,
     several techniques can be used.  One technique is
     to avoid the problem by using the empirical data
     itself rather than an analytic function.  Another
     is to do separate analyses with  several functions
     that have adequate fit but form upper and lower
     bounds to the empirical data.  A third way is to
     use  truncated analytical distributions. Judgment
     must  be  used  in choosing  the appropriate
     goodness-of-fit  test.     Information  on  the
     theoretical basis for fitting distributions  can be
     found in a standard statistics text, (e.g., Gilbert,
     1987, among others).  Off-the-shelf computer
     software can be used to statistically determine the
     distributions that fit the data.   Other software
     tools are available to  identify outliers and for
     conducting Monte Carlo simulations.

     If only a  range of values is known for an
     exposure factor, the assessor has several options.
         keep that variable constant  at its central
         value.
         assume several values within the range of
         values for the exposure factor.
         calculate a  point estimate(s) instead of
         using probabilistic analysis.
         assume a distribution. (The rationale for the
         selection of a   distribution should  be
         discussed at length.)  There are, however,
         cases where  assuming a distribution is not
         recommended. These include:
         ~   data are missing or very limited for a
            key parameter;
         ~   data were collected over a short time
            period and may not represent long term
            trends (the respondent usual behavior) -
             examples include:  food consumption
             surveys; activity pattern data;
         ~   data are not representative  of  the
            population of interest because sample
             size was small or the population studied
            was selected from a local area and was
            therefore not representative of the area of
            interest; for example, soil ingestion by
            children; and
        ~   ranges for a key variable are uncertain
            due  to experimental  error or  other
            limitations  in  the  study  design  or
            methodology; for example, soil ingestion
            by children.

1.10    CUMULATIVE EXPOSURES
        The U.S. EPA recognizes that children may
be exposed to mixtures of chemicals both indoors and
outdoors through more than one  pathway.   New
directions in risk assessments in the U.S. EPA put
more emphasis on total  exposures via  multiple
pathways (U.S. EPA, 2003d, U.S. EPA, 2008).  Over
the last  several years, the U.S. EPA has developed a
methodology  for  assessing  risk   from  multiple
chemicals (U.S. EPA,  1986b, 2000c).  For  more
information, the reader is referred to the U.S. EPA's
Framework for Cumulative Risk Assessment  (U.S.
EPA, 2003b).

1.11    ORGANIZATION
        The handbook is organized as follows:

    Chapter 1      Introduction

    Chapter 2      Variability and uncertainty

    Chapter 3      Ingestion of water and other
                  select liquids

    Chapter 4      Non-dietary ingestion

    Chapter 5      Soil and dust ingestion

    Chapter 6      Inhalation rates

    Chapter 7      Dermal exposure factors

    Chapter 8      Body weight

    Chapter 9      Intake of fruits and vegetables

    Chapter 10    Intake offish and shellfish
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                                                       Child-Specific Exposure Factors Handbook
                                                                           Chapter 1 - Introduction
     Chapter 11    Intake of meats, dairy products,
                   and fats
     Chapter 12    Intake of grain products

     Chapter 13    Intake of home-produced foods

     Chapter 14    Total food intake

     Chapter 15    Human milk intake

     Chapter 16    Activity factors

     Chapter 17    Consumer products

         Recommended values for exposure factors
 are presented at the beginning of each chapter,
 followed by detailed discussions of the data on
 which these recommendations are based. Because
 of the large number of tables in this handbook,
 tables are presented at the end of each chapter,
 before the appendices, if any.

 1.12 REFERENCES FOR CHAPTER 1
 AAP (1997) Child Health Issues for the Second
       Session of the 106th Congress.
       Environmental Health. American Academy
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       Washington, DC 20005. AAP Washington
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 Breysee, P.N.; Buckley, T.J.; Williams, D.; Beck,
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Chapter 1 - Introduction
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 U.S. EPA. (1986a)  Standard scenarios for
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U.S. EPA. (1987)  Selection criteria for
      mathematical models used in exposure
      assessments: surface water models. Exposure
      Assessment Group, Office of Health and
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U.S. EPA. (1988)  Selection criteria for
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U.S. EPA. (1989)  Risk assessment guidance for
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U.S. EPA. (1990)  Methodology for assessing health
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U.S. EPA. (1991b) Risk assessment guidance for
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                                                      Child-Specific Exposure Factors Handbook
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       assessment. Washington, DC: Office of
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       dia/soil/indcx.htm
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       PTS Harmoni/cd/875 Occurjalignaj_and_R
       csidcntial Exposure Test Guidelines/Series/
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       B - Post Application Exposure Monitoring
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       csidcntial Exposure Test Guidelines/Series/
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 U.S. EPA. (2000a) Strategy for research on risks to
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                   ]^^
 U.S. EPA. (2000c) Supplementary guidance for
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       Emergency Response, Washington, DC.
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      childhood exposures to environmental
      contaminants. Office of Research and
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      m?dcid= 146583
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      assessment. EPA/630/P-03/001F. Available
      online at
      http://cfpiib.cpa.gov/ncca/cfm/rccordispkiY.cf
      m?deid= 116283.
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      Assessing Susceptibility from Early-Life
      Exposure to Carcinogens. Risk Assessment
      Forum, Washington,  DC. EPA/630/R-
      03/003F. Available online at:
      http://cfpiib.epa.gov/ncea/cfiTi/recordisplaY.cf
      m?deid= 116283.
U.S. EPA. (2005d) Protocol for human health  risk
      assessment protocol for hazardous waste
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      Available online at
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U.S. EPA. (2006a) Approaches for the application
      of physiologically based pharmacokinetic
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       (PBPK) models and supporting data in risk
       assessment.  Office of Research and
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       05/043F.  Available online at
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       cfm?deid=157668
 U.S. EPA. (2006b) Use of physiologically based
       pharmacokinetic (PBPK) models to quantify
       the impact of human age and interindividual
       differences in physiology and biochemistry
       pertinent to risk (Final Report). Office of
       Research and Development, Washington,
       DC. EPA/600/R-06/014A. Available online
       at
       http://cfpub.epa.gov/ncea/CFM/recordisplav.
       cfm?deid=151384
  U.S. EPA (2006c) Guidance on systematic
       planning using the data quality objectives
       process.  Office of Environmental
       Information, Washington DC.
       EPA/240B/06/001. Availabel online at
       http://cfpub.epa.gov/ncea/cfiii/recordisplaY.cf
       m?deid=190187
       http://www.epa.KOv/QUALlTY/qs-docs/g4-fi
       nal.pdf
 U.S. EPA. (2006d) A framework for assessing
       health risk of environmental exposures to
       children (Final). Office of Research and
       Development, Washington, DC.
       EPA/600/R-05/093F. Available online at

       hllp://cfpub.cpa.gov/ncca/cfiTi/rccordisplav.cf
       m?dcid= 158363
 U.S. EPA (2006e) Harmonizatioj^in interspecies
       extrapolation: use of BW   as default
       method in derivation of the oral RfD
       (External Review Draft). Risk Assessment
       Forum, Washington, DC.  EPA/630/R-
       06/001. Available online at
       http://cfpub.epa.gov/ncea/raf/recordisplaY.cf
       m?deid= 148525
 U.S. EPA (2008) Concepts, methods, and data
       sources for cumulative health risk
       assessment of multiple chemicals, exposures
       and effects: a resource document (final).
       Office of Research and Development,
       Washington, DC.  EPA/600/R-06/013F.
       Available online at
Page
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                                                                      CSEFH
Chapter 1 - Introduction	
               Table 1-1. Characterization of Variability in Exposure Factors
                                  Average      Median       Upper       Multiple
Exposure Factors                                            percentile    Percentiles
Ingestion of water and other
select liquids
Non-dietary ingestion
 Soil and dust ingestion                /           /            /a
Inhalation rate
 Surface area
 Soil adherence
Body weight
Intake of fruits and vegetables
Intake offish and shellfish
Intake of meats, dairy products,
and fats
Intake of grain products
Intake of home produced foods
Total food intake
Human milk intake
Time indoors
Time outdoors
Time showering
Time bathing
Time swimming
Time playing on sand/gravel
Time playing on grass
Time playing on dirt
       Soil pica and geophagy.
/     = Data available
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 CSEFH
                                                                    Child-Specific Exposure Factors Handbook
                                                                                             Chapter 1 - Introduction
                               Table 1-2. Considerations Used to Rate Confidence in Recommended Values
   General Assessment Factors
                                              Increasing Confidence
                                                       Decreasing Confidence
   Soundness
    Adequacy of Approach
    Minimal (or defined) Bias
The studies used the best available
methodology and capture the measurement of
interest.

As the sample size relative to that of the target
population increases, there is greater
assurance that the results are reflective of the
target population.

The response rate is greater than 80 percent
for in-person interviews and telephone
surveys, or greater than 70 percent for mail
surveys.

The studies analyzed primary data.

The study design minimizes measurement
There are serious limitations with the approach used;
study design does not accurately capture the
measurement of interest.

Sample size too small to represent the population of
interest.
                                                                               The response rate is less than 40 percent.
The studies are based on  secondary sources.

Uncertainties with the data exist due to measurement
error.
   Applicability and Utility
    Exposure Factor of Interest
    Representativeness
    Currency
    Data Collection Period
The studies focused on the exposure factor of
interest.

The studies focused on the U.S. population.
The studies represent current exposure
conditions.

The data collection period is sufficient to
estimate long-term behaviors.
The purpose of the studies was to characterize a
related factor.

Studies are not representative of the U.S. population.

Studies may not be representative of current exposure
conditions.

Shorter data collection periods may not represent
long-term exposures.
   Clarity and Completeness
    Accessibility

    Reproducibility
    Quality Assurance
The study data could be accessed.

The results can be reproduced or methodology
can be followed and evaluated.
The studies applied and documented quality
assurance/quality control measures	
Access to the primary data set was limited.

The results cannot be reproduced, the methodology is
hard to follow, and the author(s) cannot be located.

Information on quality assurance/control was limited
or absent.
Page
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                                                             CSEFH
Chapter 1 - Introduction	
Table 1-2.
General Assessment Factors
Considerations Used to Rate Confidence in Recommended Values (continued)
Increasing Confidence
Decreasing Confidence

Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
The studies characterize variability in the
population studied.
The uncertainties are minimal and can be
identified. Potential bias in the studies are
stated or can be determined from the study
design.
The studies received high level of peer review
(e.g., they are published in peer review
journals).
The number of studies is greater than 3. The
results of studies from different researchers are
in agreement.
The characterization of variability is limited.
Estimates are highly uncertain and cannot be
characterized. The study design introduces biases in
the results.
The studies received limited peer review.
The number of studies is 1. The results of studies
from different researchers are in disagreement.
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CSEFH
                                         Child-Specific Exposure Factors Handbook
                                                        Chapter 1 - Introduction
Table 1-3. Integrating U.S. EPA's Guidance on Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005a) with U.S. EPA's Supplemental
Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens (U.S. EPA, 2005c) For Those
Contaminants Which Act Via a Mutagenic Mode of Action
Exposure Age Group"
Birth to < 1 month
1 < 3 months
3 < 6 months
6 < 12 months
1 to < 2 years
2 to < 3 years
3 to < 6 years
6 to < 1 1 years
11 to < 16 years
16 to < 21 years
> 21 years (21 to < 70 yr)
Exposure Duration (yr)
0.083
0.167
0.25
0.5
1
1
3
5
5
5
49
ADAF (Age-Dependent Potency
Adjustment Factor)
lOx
lOx
lOx
lOx
lOx
3x
3x
3x
3x
Ix
Ix
a EPA's recommended childhood age groups (excluding ages >21 years).
Page
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                                                                               CSEFH
Chapter 1 - Introduction	
     SOURCE/STRESSOR
        FORMATION
   Chemical
   Pnysical
T
                                                                            Cancer
                                                                            Asthma
                                                                                        Infertility
                                                                   ALTERED STRUCTURE/   etc
    Duration        TANSPORT/                                              FUNCTION
    Tcning      TRANSFORMATION                                      	
            Disoersion
            Kmet-cs
            Thermodynamics
            Distributions
                                                              t
                                                                               Edema
                                                                               ArrhyThirva
                                                EARLY BIOLOGICAL    Necrosis
                                                     EFFECT      ,   etc
Meteorology       ENVIRONMENTAL                     A
            CHARACTERIZATION  ,                  T
           Ail
           Water
           Dei
           Soil SOjsi
                       EXPOSURE
               Activity            Pathway    , individual
               Pattern            Route      .Community
                                 Duranon    «Population
                                 Frequency
                                 Maynituite
                                                       DOSi
                                   1-1  The Exposure-Dose-Effect Continaam


 Source:   U.S. EPA, 2003d; IPCS, 2006.
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Chapter 2 - Variability and Uncertainty
                                TABLE OF CONTENTS

      VARIABILITY AND UNCERTAINTY	2-1
      2.1     VARIABILITY VERSUS UNCERTAINTY 	2-1
      2.2     TYPES OF VARIABILITY 	2-2
      2.3     ADDRESSING VARIABILITY	2-3
      2.4     TYPES OF UNCERTAINTY	2-4
      2.5     REDUCING UNCERTAINTY	2-4
      2.6     ANALYZING VARIABILITY AND UNCERTAINTY	2-4
      2.7     PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS	2-5
      2.8     REFERENCES FOR CHAPTER 2	2-6
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                                                      Chapter 2 - Variability and Uncertainty
                                      LIST OF TABLES

Table 2-1.      Four Strategies for Confronting Variability	2-9
Table 2-2.      Three Types of Uncertainty and Associated Sources and Examples	2-9
Table 2-3.      Approaches to Quantitative Analysis of Uncertainty	2-10
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Chapter 2 - Variability and Uncertainty
1     VARIABILITY AND UNCERTAINTY
      Variability and uncertainty  are  inherent in the
exposure assessment process. Addressing variability and
uncertainty will increase the likelihood that results of an
assessment or analysis will  be used in an appropriate
manner.  Thus, careful consideration of the variabilities
and uncertainties associated with the  exposure factors
information used in an exposure assessment is of utmost
importance.   The characterization of variability  and
uncertainty will also assist in communicating risks to the
risk manager and the public.
      Exposure assessment can involve a broad array of
information sources and analysis techniques (U.S. EPA,
1992). Even in situations where actual exposure-related
measurements exist, assumptions or inferences will still be
required because data are not likely to be available for all
aspects of the exposure assessment.  Moreover, the data
that are available may be of questionable or unknown
quality.  Thus, exposure assessors have a responsibility to
present not just numbers, but also a clear and explicit
explanation of the implications and limitations of their
analyses.
      Morgan and Henrion (1990) provide an argument
for the need for variability and uncertainty analysis in
exposure assessment.   They state  that when scientists
report quantities  that they  have  measured,  they are
expected to routinely report an estimate of the probable
error associated with such measurements. They conclude
that because  variabilities and uncertainties inherent in
policy analysis (of which exposure assessment is a part)
tend to be even greater than those in the natural sciences,
exposure assessors also should be expected to report or
comment on the variabilities and uncertainties associated
with their estimates.
      Some additional reasons for addressing variability
and uncertainty in exposure or risk assessments (U.S.
EPA,  1992, Morgan  and Henrion, 1990) include the
following:

      Decisions may need to be made about whether or
      how to expend resources to acquire additional
      information;
      Biases may occur in providing  a so-called "best
      estimate" that in actuality is not very accurate; and
      Important   factors  and  potential  sources  of
      disagreement in a problem  may be able to be
      identified.
      This chapter is intended to acquaint the exposure
assessor  with  some of the fundamental concepts  and
precepts  of variability and uncertainty as they relate to
exposure assessment and the exposure factors presented
in  this  handbook.  It  also provides  methods  and
considerations  for  evaluating  and presenting  the
uncertainty   associated   with   exposure   estimates.
Subsequent sections in this chapter are devoted  to the
following topics:

      Variability versus uncertainty;
      Types of variability;
•     Addressing variability;
      Types of uncertainty;
      Reducing uncertainty;
      Analysis of variability and uncertainty; and
      Presenting  results   of   variability/uncertainty
      analysis.

      Fairly extensive treatises on the topic of uncertainty
have been provided, for example, by Morgan and Henrion
(1990), the National Research Council (NRC, 1994) and,
to a lesser extent, the U.S. EPA (1992; 1995).  The topic
commonly has been treated as it relates to the overall
process of conducting risk assessments; because exposure
assessment is a component of risk-assessment process, the
general concepts apply equally to the exposure-assessment
component.  Since  the  publication  of the  National
Research Council's report entitled Science and Judgement
in Risk Assessment (NRC, 1994), the field of variability
and uncertainty analysis has continued to evolve. The use
of probabilistic  techniques to address variability  and
uncertainty have continued to increase.   There  are
numerous on going efforts in the Agency and elsewhere to
further improve  the characterization of variability  and
uncertainty.   For example, an Agency task force is
developing white papers on the use of expert elicitation
for  characterizing uncertainty in risk assessments. The
U.S. EPA's Risk Assessment Forum has established a
workgroup to promote the use of probabilistic techniques
to better assess and communicate risk. The International
Programme on Chemical Safety (IPCS) is developing
guidance   on  characterizing   and  communicating
uncertainty in exposure assessment (WHO, 2006).

2.1    VARIABILITY VERSUS UNCERTAINTY
      While some authors have treated variability as a
specific type or component of uncertainty, the U.S. EPA
(1995) has advised the risk assessor (and, by analogy, the
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                                                              Chapter 2 - Variability and Uncertainty
  Uncertainty -  a lack of knowledge
  about factors affecting exposure or
  risk.
  Variability  -  arises  from  true
  heterogeneity across people, places
  or time.
exposure assessor) to distinguish between variability and
uncertainty.  Uncertainty represents a lack of knowledge
about  factors  affecting exposure or  risk,  whereas
variability arises from true heterogeneity across people,
places or time.  In other words, uncertainty can lead to
inaccurate or biased estimates, whereas variability can
affect the precision of the estimates and the degree to
which they can be generalized. Most of the data presented
in this handbook concerns variability.
      Variability and  uncertainty  can complement or
confound  one  another, and it  may  not always  be
                                     appropriate  to
                                     give   special
                                     significance to
                                     distinguishing
                                     between   the
                                     two  in  every
                                     case.  Consider
                                     a situation that
                                     relates    to
                                     exposure,  such
as estimating the average  daily dose by  one exposure
route  -- ingestion  of  contaminated  drinking water.
Suppose that it is possible to measure an individual's daily
water consumption (and concentration of the contaminant)
exactly, thereby eliminating uncertainty in the measured
daily dose. The daily dose still has an inherent day-to-day
variability, however, due to  changes in the individual's
daily water intake or the contaminant concentration in
water.
      It is impractical  to measure the  individual's dose
every day.  For this reason,  the exposure assessor may
estimate the average daily dose (ADD) based on a  finite
number of measurements, in an attempt to "average out"
the day-to-day variability. The individual has a true (but
unknown) ADD, which has now been estimated based on
a sample of measurements. Because the individual's true
average is unknown, it is uncertain how close the estimate
is to the true value.  Thus, the variability across  daily
doses has been translated into uncertainty in the ADD.
Although the individual's true ADD has no variability, the
estimate of the ADD has some uncertainty. It should be
noted, however, that a rigid delineation of variability and
uncertainty may not be as useful as assessing the available
information   and  attendant  variation  and  properly
accounting for it (e.g., sensitivity analysis).
      The above discussion pertains to the ADD for one
person. Now consider a distribution  of ADDs across
individuals in a defined population (e.g., the general U.S.
population).  In this case, variability refers to the range
and  distribution  of  ADDs  across  individuals in the
population.   By comparison, uncertainty refers to the
exposure  assessor's  state  of knowledge  about  that
distribution,  or   about  parameters   describing  the
distribution (e.g., mean, standard deviation, general shape,
various percentiles).
      As noted by the National Research Council (NRC,
1994), the realms of variability and  uncertainly  have
fundamentally different ramifications for science and
judgment. For example, uncertainty may force decision-
makers to judge how probable it is that exposures have
been overestimated or underestimated for every member
of the exposed population, whereas variability forces them
to cope with the certainty that different individuals are
subject to exposures both above and below any of the
exposure levels chosen as a reference point.

2.2   TYPES OF VARIABILITY
      Variability  in  exposure  is a  function of the
variability in human exposure factors (i.e., those related
to  an  individual's  location,  activity,  behavior  or
preferences at a particular point in time, or physiological
characteristics such as body weight), as well as variations
in contaminants concentrations  (i.e.,  those related to
pollutant emission rates and physical/chemical processes
that affect concentrations in various media; e.g., air, soil,
food and water). The variations in human exposure factors
and  chemical   concentrations  are  not  necessarily
independent of one another. For example, both personal
activities  and pollutant  concentrations  at  a specific
location might vary in response to weather conditions, or
between weekdays and weekends.
      At  a  more fundamental  level,  four types of
variability can be distinguished:

      Variability across locations (Spatial Variability);
      Variability over time (Temporal Variability);
      Variability within an individual (Intra-individual
      Variability; and
      Variability among individuals (Inter-individual
      Variability).

      Spatial variability can occur  both at regional
(macroscale) and local (microscale) levels. For example,
fish intake rates can vary depending on the region of the
country.    Higher consumption may  occur  among
populations located near large bodies of water such as the
Great Lakes or coastal  areas.  As  another example,
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Chapter 2 - Variability and Uncertainty
outdoor pollutant levels can be affected at the regional
level by industrial activities  and at the local level by
activities of individuals. In general, higher exposures tend
to be associated with closer proximity to the pollutant
source, whether it be an industrial plant or related to a
personal activity such as showering or gardening. In the
context of exposure to airborne pollutants, the concept of
a "microenvironment" has been introduced (Duan, 1982)
to denote a specific  locality (e.g., a residential lot or a
room in a  specific  building)  where   the  airborne
concentration can be treated as homogeneous (i.e.,
invariant) at a particular point in time.
      Temporal variability refers to variations over
time, whether long- or short-term. Seasonal fluctuations
in weather, pesticide applications, use  of woodburning
appliances and fraction of  time spent  outdoors  are
examples of longer-term variability. Examples of shorter-
term variability are differences in industrial or personal
activities on weekdays versus weekends or at different
times of the day.
      Intra-individual variability  is a function of
fluctuations in  an individual's  physiologic (e.g., body
weight), or behavioral characteristics (e.g., ingestion rates
or activity patterns).  For example, patterns of food intake
change from day to  day, and may change significantly
over a  lifetime.   Intra-individual variability may be
associated  with  spatial  or temporal  variability.  For
example,  because an individual's dietary intake may
reflect local food sources, intake patterns may change if
place of residence changes.  Also, physical activity may
vary depending upon  the season, lifestage, or other factors
associated with temporal variability.
      Inter-individual variability can be either of two
types:  (1) human characteristics such as age or body
weight, and (2) human behaviors such as location, activity
patterns, and ingestion rates. Each of these variabilities,
in turn, may be related to several underlying phenomena
that vary. For example, the natural variability in human
weight is due to a combination of genetic, nutritional, and
other lifestyle or environmental factors. Variability arising
from independent factors that combine multiplicatively
generally will  lead   to  an  approximately  lognormal
distribution   across  the   population,   or  across
spatial/temporal dimensions. Inter-individual variability
may also be related to spatial and temporal factors.

2.3   ADDRESSING VARIABILITY
      As noted in Section 1.6 of this handbook, this
document attempts to characterize variability of each of
the exposure factors presented.  Variability is addressed
by presenting data on the exposure factors in one of the
following three ways: (1) as tables with percentiles or
ranges of values, (2)  as  analytical distributions with
specified parameters, or (3) as a qualitative discussion.
      According to the National Research Council (NRC
1994), variability in exposure estimates can be addressed,
especially with regard to point estimates such as central
tendency (CT) or high end exposures (e.g.,  reasonable
maximum  exposure  (RME) used in  the  Superfund
program) in four basic ways (Table 2-1) when dealing
with science-policy questions surrounding issues such as
exposure or risk assessment.  The first is to  ignore  the
variability.  This  strategy  is  likely  to  be  used in
combination with one of the other strategies described
below (e.g., use the average value), and tends to work best
when the variability is relatively small, as in the case with
adult body weights. For example, the U.S.EPA practice
of assuming that all adults weigh 70 kg is likely  to be
correct within ±25% for most adults and within a factor of
3 for virtually all adults (NRC, 1994).  However, it is
cautioned that this approach may not be appropriate for
children, where variability may be large.
      The second strategy involves disaggregating  the
variability in some explicit way, in order to  better
understand it or reduce it.   Mathematical  models  are
appropriate in some cases, as in fitting a sine wave to the
annual outdoor  concentration  cycle  for a particular
pollutant and location.  In other cases, particularly those
involving human characteristics or behaviors, it is easier
to disaggregate the data by considering all the relevant
subgroups or subpopulations.  For example, distributions
of body weight could be developed separately for adults,
adolescents and children, and even for males and females
within each of these subgroups. Temporal  and spatial
analogies  for  this concept involve  measurements  on
appropriate  time  scales   and  choosing  appropriate
subregions or microenvironments.
      The third strategy is to use the average value of a
quantity that varies. Although this strategy might appear
as tantamount to ignoring variability, it needs to be based
on a decision that the average value can be estimated
reliably in light  of  the  variability  (e.g.,  when  the
variability is known to be relatively small, as in the case
of adult body weight).
      The fourth strategy involves using the maximum
or minimum value for an exposure factor. In this case,
the variability is characterized by the range between the
extreme values and a measure of central tendency. This
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                                                              Chapter 2 - Variability and Uncertainty
is perhaps the most common method of dealing with
variability in exposure or risk assessment -- to focus on
one time period (e.g., the period of peak exposure), one
spatial region (e.g., in close proximity to the pollutant
source of concern), or one subpopulation (e.g., exercising
asthmatics). As noted by the U.S. EPA (1992), when an
exposure  assessor  develops  estimates of  high-end
individual exposure and dose, care must  be taken not to
set all factors to values that maximize exposure or dose --
such  an  approach  will  almost  always  lead   to  an
overestimate.
      Probabilistic techniques (e.g., Monte Carlo orLatin
Hypercube  Simulation)  are  frequently   used  for
characterizing the variability  in  risk estimates  by
repeatedly sampling  the probability distributions of the
risk equation inputs and using these inputs to calculate a
distribution of risk. This approach is used less frequently
in uncertainty analysis.   Techniques  for characterizing
both  uncertainty  and  variability  are  available,  and
generally require two-dimensional Monte Carlo analysis
(U.S. EPA, 2001).  In  situations in which an  analyst
wishes to apply probabilistic techniques, and data lend
themselves to such analysis, more robust techniques to
describe  data   goodness-of-fit,   identification  and
deposition of data outliers, and sensitivity analysis of the
respective model should be  used to  address parameter
variability.  These techniques are described in Section
1.9.2 of this document.

2.4   TYPES OF UNCERTAINTY
      Uncertainty in exposure analysis is related to the
lack of knowledge concerning one or more components of
the assessment process.
      The U.S. EPA (1992) has classified uncertainty in
exposure assessment  into three broad  categories:

1.    Uncertainty regarding  missing  or  incomplete
      information needed to fully define exposure and
      dose (Scenario Uncertainty).
2.    Uncertainty regarding some parameter (Parameter
      Uncertainty).
3.    Uncertainty regarding gaps  in scientific theory
      required to make predictions on the basis of causal
      inferences (Model Uncertainty).

 Sources and examples for each type of  uncertainty are
summarized in Table 2-2. As described in Section 1.6 of
this handbook, U.S.  EPA has  attempted to  address the
uncertainty associated with the various exposure factors
presented in the handbook by applying confidence ratings
to the recommended data. In general, these confidence
rating are based on detailed discussions of any limitations
of the data presented. This information may be useful in
analyzing the uncertainty associated  with an  overall
exposure/risk assessment.

2.5   REDUCING UNCERTAINTY
      Identification of the sources of uncertainty in an
exposure assessment is the first step in determining how
to reduce that uncertainty. The types of uncertainty listed
in Table 2-2 can be further defined by examining their
principal causes.
      Because uncertainty  in exposure  assessments is
fundamentally tied to  a lack of knowledge concerning
important  exposure  factors, strategies  for  reducing
uncertainty necessarily involve reduction or elimination of
knowledge gaps. Example strategies to reduce uncertainty
include  (1) collection of new data using a larger sample
size,  an  unbiased  sample  design,  a  more  direct
measurement  method  or a  more appropriate  target
population, and (2) use of more sophisticated modeling
and analysis tools if data quality allows.

2.6   ANALYZING   VARIABILITY   AND
      UNCERTAINTY
      Exposure assessments often are  developed in a
tiered approach. The initial tier usually screens out the
exposure scenarios or pathways that are not expected to
pose much risk, to eliminate them from more detailed,
resource-intensive review. Screening-level assessments
typically examine exposures that would fall on or beyond
the high end of the  expected  exposure distribution.
Because screening-level analyses usually are included in
the final exposure assessment, the  final document may
contain   scenarios  that  differ  quite   markedly   in
sophistication,  data   quality,   and  amenability   to
quantitative expressions  of  variability  or uncertainty.
      According to the U.S. EPA (1992), uncertainty
characterization and uncertainty assessment are two ways
of  describing  uncertainty  at   different  degrees  of
sophistication.   Uncertainty characterization  usually
involves a qualitative discussion of the thought processes
used to select or reject specific data, estimates, scenarios,
etc. Uncertainty assessment is a more quantitative process
that may range from simpler measures (e.g., ranges)  and
simpler  analytical techniques (e.g., sensitivity analysis) to
more complex measures and techniques.  Its goal is to
provide decision makers with information concerning the
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Chapter 2 - Variability and Uncertainty
quality  of  an  assessment,  including  the  potential
variability in the estimated exposures, major data gaps,
and the effect that these data gaps have on the exposure
estimates developed.
      A distinction between variability and uncertainty
was  made  in Section 2.1.  Although the quantitative
process mentioned  above  applies  more  directly to
variability  and the  qualitative approach more so to
uncertainty, there is some degree of overlap. In general,
either method provides  the assessor  or decision-maker
with insights to better evaluate the  assessment in the
context of available data and assumptions.  The following
paragraphs  describe  some  of  the  more  common
procedures for  analyzing variability and uncertainty in
exposure  assessments.    Principles  that  pertain  to
presenting the results of variability/uncertainty analysis
are discussed in the next section.
      Several approaches can be used to characterize
uncertainty in parameter values.  When  uncertainty is
high, the assessor may use order-of-magnitude bounding
estimates of parameter ranges (e.g., from 0.1 to 10 liters
for daily water intake).  Another method describes the
range for each parameter including the lower and upper
bounds as well as a  "best estimate" (e.g., 1.4 liters per
day)  determined by available data  or  professional
judgement.
      When sensitivity analysis indicates that a parameter
profoundly influences exposure estimates, the  assessor
should develop  a probabilistic description of its range. If
there are  enough data  to support their  use, standard
statistical  methods   are  preferred.    If  the  data  are
inadequate, expert judgment can be used to generate a
subjective probabilistic representation.  Such judgments
should be developed in a consistent, well-documented
manner.  Morgan and Henrion (1990) and Rish (1988)
describe techniques to solicit expert judgment.
      Most approaches to quantitative analysis examine
how variability  and uncertainty in values of specific
parameters translate  into the  overall  uncertainty of the
assessment.  Details may be found in various papers and
reviews such as Bogen and Spear  (1987),  Cox  and
Baybutt (1981), Whitmore (1985), Inman  and Helton
(1988), Seller (1987),  and Rish and Marnicio  (1988).
These approaches can generally be described (in order of
increasing complexity and data needs) as:  (1) sensitivity
analysis;  (2)   analytical   uncertainty  propagation;
(3) probabilistic uncertainty  analysis;  or  (4) classical
statistical methods (U.S. EPA 1992). The four approaches
are summarized in Table 2-3.
      Additional discussions describing approaches to
address variability and uncertainty in human exposure
assessments can be found in the following references:
Burin and Saunders (1999), Burmaster (1998a, b, and c),
Burmaster and  Crouch (1997), Calaberse and Baldwin
(1998),  Cox  (1999),  Cullen  and  Frey  (1999),
Fayerweather et al. (1999), Finkel (1997), Frey (2002),
Frey and Patil (2002), Greenland, (2001), Hattis (1997),
Hattis  and Anderson (1999), Hattis and Silver (1994),
Illing (1999), Jayjock (1997), Kalberlah et al. (2003),
Kelley and Campbell (2000), Meek (2001), Nayak and
Kundu (2001),  Nicas  and Jayjock (2002),  Peretz et al.
(1997), Price etal. (1997,1999), Rai and Krewski( 1998),
Renwick (1999), Renwick et al. (2001), Robinson and
Hurst (1997), Saltelli (2002),  Semple et al. (2003), Simon
(1997), Shlyakhter (1994),  Slob and Pieters (1998),
Wallace  et al.  (1994), Wallace and Williams (2005),
Weiss (2001), and Zheng and Frey (2005).

2.7   PRESENTING RESULTS OF VARIABILITY
      AND UNCERTAINTY ANALYSIS
      Comprehensive qualitative analysis and rigorous
quantitative  analysis are  of  little value  for use in the
decision-making process, if their results are not clearly
presented.  In  this chapter,  variability  (the receipt of
different levels  of exposure by different individuals) has
been  distinguished  from  uncertainty  (the  lack  of
knowledge about the correct value for a specific exposure
measure or estimate). Most of the data that are presented
in this handbook deal with variability directly, through
inclusion of statistics that pertain to the distributions for
various exposure factors.
      Not all approaches historically used to construct
measures or  estimates of exposure have attempted to
distinguish between variability and uncertainty.   The
assessor  is  advised  to  use  a  variety of  exposure
descriptors,  and  where  possible,  the full population
distribution,  when  presenting  the  results.    This
information  will provide risk managers with a better
understanding of how exposures are distributed over the
population and  how variability in population activities
influences this distribution.
      Although  incomplete  analysis  is  essentially
unquantifiable as a source of uncertainty, it should not be
ignored.  At a minimum, the assessor should describe the
rationale for excluding particular  exposure scenarios;
characterize the uncertainty in these decisions as high,
medium, or low; and state whether they  were based on
data,  analogy,   or professional  judgment.    Where
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                                                              Chapter 2 - Variability and Uncertainty
uncertainty is high, a sensitivity analysis can be used to
estimate upper limits on exposure by way of a series of
"what if" questions.
      Although assessors have always used descriptors to
communicate the kind of scenario being addressed,  the
1992  Exposure Guidelines establish clear  quantitative
definitions for these risk descriptors. These definitions
were established to ensure that consistent terminology is
used throughout the Agency. The risk descriptors defined
in the Guidelines include descriptors of individual risk
and population  risk.   Individual  risk descriptors  are
intended to address questions dealing with risks borne by
individuals  within  a population,  including  not only
measures of central tendency  (e.g., average  or median),
but also those risks at the high end of the distribution.
Population risk descriptors refer to an assessment of  the
extent of harm to the population being addressed.  It can
be either an estimate of the number of cases of aparticular
effect that  might occur in a  population (or population
segment),  or  a description  of what fraction of  the
population receives exposures, doses, or risks greater than
a specified value.  The data presented in this handbook is
one of  the  tools  available  to exposure  assessors to
construct the various risk descriptors.
      However, it is not sufficient to merely present  the
results  using  different exposure  descriptors.   Risk
managers should also be presented with an analysis of the
uncertainties surrounding these descriptors.  Uncertainty
may be presented using simple or very sophisticated
techniques,  depending  on  the requirements  of  the
assessment and the amount of data available.  It is beyond
the scope  of this handbook to discuss the mechanics of
uncertainty analysis in detail.  The assessor can address
uncertainty qualitatively by answering questions such as:

      What is the basis or rationale for selecting these
      assumptions/parameters, such as data, modeling,
      scientific judgment,  Agency  policy, "what  if
      considerations, etc.?

      What is the  range  or  variability   of  the key
      parameters?   How were the parameter values
      selected for use in the assessment? Were average,
      median,  or  upper-percentile values chosen?  If
      other  choices had been  made, how would  the
      results have differed?

      What is  the  assessor's  confidence  (including
      qualitative  confidence  aspects)  in  the key
      parameters and the overall assessment?  What are
      the quality  and  the extent  of the  data  base(s)
      supporting the selection of the chosen values?

      Any exposure estimate developed by an assessor
will  have  associated assumptions about the  setting,
chemical, population characteristics, and how contact with
the chemical occurs through various exposure routes and
pathways.  The exposure assessor will need to examine
many sources of information that bear either directly or
indirectly  on  these components of  the  exposure
assessment. In addition, the assessor may need to make
many decisions regarding the use of existing information
in constructing scenarios and setting up the  exposure
equations. In presenting the scenario results, the assessor
should strive for a balanced and impartial treatment of the
evidence  bearing  on the conclusions  with the  key
assumptions highlighted.  For these key assumptions, one
should cite data sources and explain any adjustments of
the data.
      The exposure assessor also  should qualitatively
describe the rationale for selection  of any conceptual or
mathematical models that may have been used.  This
discussion should address their verification and validation
status, how well  they  represent  the  situation being
assessed  (e.g., average versus high-end estimates), and
any plausible alternatives in terms of their acceptance by
the scientific community.
      Table  2-2   summarizes  the  three   types  of
uncertainty, associated sources, and examples.  Table 2-3
summarizes four  approaches to  analyze  uncertainty
quantitatively.   These are described further in the  1992
Exposure Guidelines (U.S. EPA, 1992).
      To the extent possible, this handbook provides
information that can be used to characterize the variability
and uncertainty of data for the various exposure factors.
In  general,  variability  is  addressed  by  providing
distribution of data, where  available,  or qualitative
discussions of the data sets used. Uncertainty is addressed
by applying confidence  rating to the recommendations
provided for the various factors,  along  with detailed
discussions of any limitations of the data presented.
2.8   REFERENCES FOR CHAPTER 2
Bogen, K.T. (1990) Uncertainly in environmental health
    risk assessment. Garland Publishing, New York, NY.
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Chapter 2 - Variability and Uncertainty
Bogen,K.T.; Spear, R.C. (1987). Integrating uncertainty
    and interindividual variability in environmental risk
    assessment. Risk Analysis. 7(4):427-436.
Burin, G.J.; Saunders, D.R. (1999). Addressing human
    variability in risk  assessment-the robustness of the
    intraspecies uncertainly factor.  Reg.  Tox.  Pharm.
    30: 209-216.
Burmaster, D.E.; Crouch, E.A.C.  (1997).  Lognormal
    distributions for body weight as a function of age for
    males and females in the United States, 1976-1980.
    Risk Analysis.  17:499-505.
Burmaster, D.E. (1998a). A lognormal distribution for
    time spent showering. Risk Analysis.  18:33-35.
Burmaster, D.E. (1998b).  Lognormal distributions for
    total water intake  and tap water intake by pregnant
    and lactating women in  the United States.   Risk
    Analysis  18: 215-219.
Burmaster, D.E. (1998c).  Lognormal distributions for
    skin area as  a function  of   body weight.   Risk
    Analysis  18: 27-32.
Calabrese, E.J.; Baldwin, L.A. (1998).  Hormesis  as a
    biological hypothesis.    Environ.  Health  Persp.
    106(Supp. 1): 357-362.
Cox,D.C.;Baybutt,P.C. (1981) Methods for uncertainty
    analysis.   A comparative survey.  Risk Analysis
    l(4):251-258.
Cox Jr., L.A. (1999). Internal dose, uncertainty analysis,
    and complexity of risk models. Environ. Inter. 25:
    841-852.
Cullen,   A.C.;  Frey,  H.C.  (1999).    Probabilistic
    Techniques in  Exposure Assessment.   New York:
    Plenum Press.
Duan, N. (1982)  Microenvironment types: A model for
    human exposure  to air  pollution.  Environ.  Intl.
    8:305-309.
Fayerweather, W.E.;  Collins, J.J.;  Schnatter,  A.R.;
    Hearne, F.T.; Menning, R.A.; Reyner, D.P. (1999).
    Quantifying uncertainty in a risk assessment using
    human data.  Risk Analysis 19: 1077-1090.
Finkel, A.M. (1997). Not to decide is to decide: ignoring
    susceptibility in not 'good science'. Environ. Tox.
    Pharm. 4: 219-228.
Frey,H.C. (2002). GuestEditorial: Introduction to special
    section on sensitivity  analysis and  summary of
    NCSU/USD A workshop on sensitivity analysis. Risk
    Analysis  22: 539-545.
Frey, H.C.; Patil, S.R. (2002).  Identification and review
    of sensitivity analysis methods. Risk Analysis 22:
    553-578.
Greenland, S. (2001).  Sensitivity analysis, Monte Carlo
    risk analysis, and Bayesian uncertainty  assessment.
    Risk Analysis 21: 579-583.
Hattis, D. (1997).  Human variability in susceptibility:
    how big, how often, for what responses to  what
    agents?  Environ. Tox. Pharm.  4:  195-208.
Hattis, D. and Anderson, E.L. (1999). What should be the
    implications of uncertainty, variability, and inherent
    'biases'/'conservatism'    for  risk  management
    decision-making. Risk Analysis  19: 95-107.
Hattis, D. and Silver, K. (1994).  Human interindividual
    variability  -  A  major   source of uncertainty in
    assessing risks for noncancer health effects.  Risk
    Analysis. 14(4): 421-431.
Illing, H.P.A. (1999).   Are  societal judgements being
    incorporated into the uncertainty factor used in
    toxicological risk assessment? Reg. Toxicol. Pharm.
    29: 300-308.
Inman, R.L.; Helton, J.C. (1988)  An investigation of
    uncertainty  and sensitivity analysis techniques for
    computer models.  Risk Analysis. 8(1):71-91.
Jayjock,  M.A.  (1997).   Uncertainty  analysis in the
    estimation of exposure.   Amer. Ind. Hyg. Assoc. J.
    58: 380-382.
Kalberlah, F.; Schneider, K.; et al. (2003).  Uncertainty
    in toxicological risk assessment for non-carcinogenic
    health effects.  Reg. Tox. Pharm.  37: 92-104.
Kelly, E.J.; Campbell, K. (2000). Separating variability
    and  uncertainty   in  environmental   risk
    assessment-making  choices.  Human  Ecol.  Risk
    Assess.  6: 1-13.
Meek,  M.E. (2001)  Categorical  default  uncertainty
    factors-interspecies  variation  and  adequacy  of
    database. Human Ecol. Risk Assess.  7:157-163.
Morgan, M.G.;Henrion, M. (1990) Uncertainly: A Guide
    to Dealing with Uncertainty in Quantitative Risk and
    Policy Analysis. Cambridge University Press, New
    York, NY.
National Research Council (NRC). (1994) Science and
    Judgment in Risk  Assessment.  National Academy
    Press, Washington, DC.
Nayak,  T.K.;  Kundu, S. (2001).    Calculating  and
    describing  uncertainty   in  risk   assessment:   The
    Bayesian approach.  Human Ecol. Risk Assess. 7:
    307-328.
Nicas, M.; Jayjock, M. (2002). Uncertainty in exposure
    estimates made by  modeling versus  monitoring.
    AIHAJ. 63:275-283.
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                                                            Chapter 2 - Variability and Uncertainty
Peretz, C.; Goldberg, P.;Kahan, E.; Grady, S.; Goren, A.
    (1997).  The variability of exposure over time: a
    prospective longitudinal study.  Ann. Occup. Hyg.
    41:485-500.
Price, P.S.;Keenan, R.E.; Schwab, B. (1999).  Defining
    the interindividual (intraspecies) uncertainty factor.
     Human Ecol. Risk Assess.  5:1023-1033.
Price, P.S.; Keenan, R.E.;  Swartout, J.C.,  Gillis, C.A.,
    Carlson-Lynch, H., and Dourson, M.L. (1997).  An
    approach for modeling noncancer dose responses
    with an emphasis on uncertainty. Risk Analysis  17:
    427-437.
Rai,  S.N.;  Krewski,  D.  (1998).   Uncertainty  and
    variability analysis in multiplicative risk models.
    Risk Analysis. 18: 37-45.
Renwick, A.G. (1999). Subdivision of uncertainty factors
    to allow for toxicokinetics  and toxicodynamics.
    Human Ecol. Risk Assess. 5: 1035-1050.
Renwick, A.G.; Dome, J.-L.C.M; Walton, K. (2001).
    Pathway-related factors: The potential for human data
    to improve the scientific basis  of risk assessment.
    Human Ecol. Risk Assess. 7:165-180.
Rish, W.R.  (1988)   Approach  to uncertainty  in  risk
    analysis.    Oak  Ridge   National  Laboratory.
    ORNL/TM-10746.
Rish, W.R.;  Marnicio, R.J. (1988)  Review of  studies
    related to uncertainty in risk analysis.  Oak Ridge
    National Laboratory.  ORNL/TM-10776.
Robinson,  R.B.;  Hurst,  B.T.   (1997).    Statistical
    quantification  of  the sources  of variance  in
    uncertainty analyses. Risk Analysis. 17:447-453.
Saltelli, A. (2002). Sensitivity Analysis for Importance
    Assessment. Risk Analysis. 22:  579-590.
Seller, F.A.  (1987) Error propagation for large errors.
    Risk Analysis 7(4):509-518.
Semple, S.E.;Proud,L.A.;  Cherrie, J.W. (2003).  Use of
    Monte Carlo simulation to investigate uncertainty in
    exposure modeling. Scand. J. Work Environ. Health.
    29: 347-353.
Shlyakhter, A.I. (1994).  An improved framework for
    uncertainty analysis:  Accounting  for unsupected
    errors.  Risk Analysis.  14(4): 441-447.
Simon, T.W. (1997).  Combining physiologically based
    pharmacokinetic   modeling  with  Monte   Carlo
    simulation to derive an acute inhalation guidance
    value for trichlorethylene.  Reg. Tox. Pharm.  26:
    257-270.
Slob, W.; Pieters, M.N. (1998). A probabilistic approach
    for deriving acceptable human intake limits  and
    human health risks  from  toxicological  studies:
    General framework. Risk Analysis.  18:787-798.
U.S. EPA (1992)  Guidelines for exposure assessment.
    Washington,   DC:   Office   of  Research  and
    Development, Office  of Health and Environmental
    Assessment. EPA/600/2-92/001.
U.S. EPA (1995)  Guidance for risk characterization.
    Science Policy Council, Washington, DC.
U.S.  EPA (2001)  Risk  Assessment  Guidance  for
    Superfund:  Volume  III  -  Part A, Process  for
    Conducting  Probabilistic  Risk  Assessment.
    Washington,  DC:  Office of  Solid  Waste and
    Emergency Response.  EPA/540-R-02-002.
Wallace, L.A.  et al. (1994).   Can long-term exposure
    distributions   be  predicted   from   short-term
    measurements? Risk Analysis .  14(l):75-85.
Wallace,L;. Williams,R. (2005). Validation of a method
    for estimating long-term  exposures based on short-
    term measurements. Risk Analysis. 25(3): 687-694.
Weiss, B. (2001).   A Web-based  survey method for
    evaluating different components of uncertainty  in
    relative health risk judgments. Neurotoxicology 22:
    707-721.
WHO (2006)  Draft  guidance on  characterizing and
    communicating uncertainty in exposure assessment.
    Accessed  on  line  at:
    http://www.who.int/ipcs/methods/harmonization/ar
    eas/exposure_assessment/en/index.html
Whitmore,  R.W.   (1985)     Methodology   for
    characterization  of   uncertainty  in  exposure
    assessments. EPA/600/8-86/009.
Zheng, J.; Frey, H.C. (2005). Quantitative analysis  of
    variability and uncertainly with known measurement
    error: Methodology and case study.  Risk Analysis.
    25: 663-675.
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Chapter 2 - Variability and Uncertainty
Table 2-1. Four Strategies for Confronting Variability
Strategy
Ignore variability
Disaggregate the
variability
Use the average value
Use a maximum or
minimum value
Example
Assume that all adults weigh 70
kg
Develop distributions of body
weight for age/gender groups
Use average body weight for
adults
Use a lower-end value from the
weight distribution
Comment
Works best when variability is small
Variability will be smaller in each group; it depends on
availability of data
Can the average be estimated reliably given what is known
about the variability of a specific population or group with
potential exposures?
Conservative approach - can lead to unrealistically high
exposure estimate if taken for all factors. It may be useful
as a screening method for eliminating pathways of exposure
that are not significant.
Source: NRC, 1994.
Table 2-2. Three Types of Uncertainty and Associated Sources and Examples
Type of Uncertainty
Scenario Uncertainty



Parameter Uncertainty



Model Uncertainty

Sources
Descriptive errors
Aggregation errors
Judgment errors
Incomplete analysis
Measurement errors
Sampling errors
Variability
Surrogate data
Relationship errors
Modeling errors
Examples
Incorrect or insufficient information
Spatial or temporal approximations
Selection of an incorrect model
Overlooking an important pathway
Imprecise or biased measurements
Small or unrepresentative samples
In time, space or activities
Structurally-related chemicals
Incorrect inference on the basis for correlations
Excluding relevant variables
Source: U.S. EPA, 1992.
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                                                Chapter 2 - Variability and Uncertainty
Table 2-3. Approaches to Quantitative Analysis of Uncertainty
Approach
Sensitivity Analysis
Analytical Uncertainty Propagation
Probabilistic Uncertainty Analysis
Classical Statistical Methods
Description
Changing one input variable at a time while
leaving others constant, to examine effect on
output
Examining how uncertainty in individual
parameters affects the overall uncertainty of the
exposure assessment
Varying each of the input variables over various
values of their respective probability
distributions
Estimating the population exposure distribution
directly, based on measured values from a
representative sample
Example
Fix each input at lower (then upper) bound
while holding others at nominal values (e.g.,
medians)
Analytically or numerically obtain a partial
derivative of the exposure equation with
respect to each input parameter
Assign probability density function to each
parameter; randomly sample values from each
distribution and insert them in the exposure
equation (Monte Carlo)
Compute confidence interval estimates for
various percentiles of the exposure
distribution
Source: U.S. EPA, 1992.
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Chapter 3 - Water Ingestion
                                    TABLE OF CONTENTS

       INGESTION OF WATER AND OTHER SELECT LIQUIDS ............................... 3-1
       3.1    INTRODUCTION  [[[ 3-1
       3.2    RECOMMENDATIONS [[[ 3-2
              3.2.1    Water Ingestion from Consumption of Water as a Beverage and from Food
                      and Drink [[[ 3-2
              3.2.2    Water Ingestion while Swimming ....................................... 3-2
       3.3    DRINKING WATER INGESTION STUDIES .................................... 3-6
              3.3.1    Key Drinking Water Ingestion Study .................................... 3-6
                      3.3.1.1  Kahn and Stralka, 2008  ....................................... 3-6
              3.3.2    Relevant Drinking Water Ingestion Studies ............................... 3-7
                      3.3.2.1  Levyetal., 1995 ............................................. 3-7
                      3.3.2.2  Heller et al,  2000 ............................................ 3-8
                      3.3.2.3  Sichert-Hellert et al., 2001  ..................................... 3-8
                      3.3.2.4  Sohn et al., 2001 ............................................. 3-9
                      3.3.2.5  Hilbig et al., 2002 ........................................... 3-10
                      3.3.2.6  Marshall et al., 2003a ........................................ 3-10
                      3.3.2.7  Marshall et al., 2003b ........................................ 3-11
                      3.3.2.8  Skinner et al., 2004  .......................................... 3-11
       3.4    WATER INGESTION WHILE SWIMMING .................................... 3-11
              3.4.1    Dufour et al., 2006 ................................................. 3-11

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                                                    	Chapter 3 - Water Ingestion
                                         LIST OF TABLES
Table 3-1.      Recommended Values for Drinking Water Ingestion Rates	
Table 3-2.      Confidence in Recommendations for Drinking Water Ingestion Rates 	
Table 3-3.      Confidence in Recommendations for Water Ingestion while Swimming	
Table 3-4.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Community Water (mL/day)  	
Table 3-5.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Bottled Water  (mL/day)	
Table 3-6.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Other Sources  (mL/day)  	
Table 3-7.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/day)	
Table 3-8.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/day)	
Table 3-9.      Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Community Water (mL/kg-day)	
Table 3-10.     Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Bottled Water (mL/kg-day)  	
Table 3-11.     Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               Other Sources (mL/kg-day)  	
Table 3-12.     Per Capita Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/kg-day)  	
Table 3-13.     Per Capita Estimates of Total Direct and Indirect Water Ingestion:
               All Sources (mL/kg-day)  	
Table 3-14.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               Community Water (mL/day)  	
Table 3-15.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               Bottled Water (mL/day)	
Table 3-16.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               Other Sources (mL/day)	
Table 3-17.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/day)	
Table 3-18.     Consumers Only Estimates of Combined Direct and Indirect Water Ingestion:
               All Sources (mL/day)	
Table 3-19.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Community Water (mL/kg-day)	
Table 3-20.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Bottled Water (mL/kg-day)  	
Table 3-21.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               Other Sources (mL/kg-day)  	
Table 3-22.     Consumers Only Estimates of Direct and Indirect Water Ingestion:
               All Sources (mL/kg-day)  	
Table 3-23.     Consumer Only Estimates of Total Direct and Indirect Water Ingestion (mL/kg-day)
Table 3-24.     Water Ingested (mL/day) from Water By Itself and Water Added to Other Beverages
               and Foods	
Table 3-25.     Mean Water Consumption (mL/kg-day) by Race/Ethnicity	
                                            3-3
                                            3-4
                                            3-5

                                           3-14

                                           3-14

                                           3-15

                                           3-15

                                           3-16

                                           3-17

                                           3-17

                                           3-18

                                           3-18

                                           3-19

                                           3-20

                                           3-20

                                           3-21

                                           3-21

                                           3-22

                                           3-23

                                           3-23

                                           3-24

                                            -24
                                            -25

                                            -26
                                            -27
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Chapter 3 - Water Ingestion	
Table 3-26      Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and
               Poverty Category 	3-28
Table 3-27.     Intake of Water from Various Sources in 2-13-y-old Participants of the
               DONALD Study 1985-1999	3-29
Table 3-28.     Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years,
               NHANES III, 1988-94	3-30
Table 3-29.     Estimated Mean (± Standard Error) Amount of Total Fluid and Plain Water Intake
               among Children Aged 1-10 Years: (NHANES III, 1988-94)	3-31
Table 3-30.     Tap Water Intake in Breastfed and Formula-fed Infants and Mixed-fed Young Children at
               Different Age Points	3-32
Table 3-31.     Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day)
               for Children With Returned Questionnaires	3-33
Table 3-32.     Mean (± Standard Deviation) Daily Beverage Intakes Reported on Beverage Frequency
               Questionnaire and 3-day Food and Beverage Dairies 	3-34
Table 3-33.     Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) . . 3-35
Table 3-34.     Pool Water Ingestion by Swimmers  	3-36
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Chapter 3 -  Water Ingestion	
3       INGESTION OF WATER AND OTHER
        SELECT LIQUIDS
3.1     INTRODUCTION
        Water ingestion  can be  a  pathway  of
exposure to environmental chemicals among children.
Contamination of water may occur at the water supply
source (ground  water  or surface  water);  during
treatment  (for example  toxic by-products  may  be
formed during chlorination); or post-treatment (such as
leaching of lead or other materials from plumbing
systems). Children may be exposed to contaminants in
water when consuming water directly as a beverage,
indirectly from foods and drinks made with water, or
incidentally  while   swimming.     Estimating   the
magnitude of the potential dose of toxics from water
ingestion requires information on the quantity of water
consumed.  The purpose of this section is to describe
key  and relevant   published studies  that provide
information on water ingestion among children and to
provide recommended ingestion rate values for use in
exposure assessments.  The studies described in this
section provide information  on  ingestion of water
consumed as a beverage, ingestion of other select
liquids, and ingestion of water while swimming.
        Currently, the U. S. EPA uses the quantity  1 L
per day for infants (individuals of 10 kg body mass or
less) and children as a default drinking water ingestion
rate  (U.S.  EPA, 2000).   This rate includes water
consumed in the form of juices and other beverages
containing  tapwater.   The National  Academy of
Sciences   (NAS,  1977)  estimated  that  daily
consumption of water may vary with levels of physical
activity and fluctuations in temperature and humidity.
It is  reasonable to assume that children engaging in
physically-demanding activities or living in warmer
regions may have higher levels of water ingestion.
However, there is limited information on the effects of
activity level and  climatic  conditions  on  water
ingestion.
        Various studies cited in this  section  have
generated data on water ingestion rates; in general,
these sources support U.S. EPA's use of 1 L/day as an
upper-percentile tapwater ingestion rate for children
under 10 years of age.  Based on the applicability of
the survey design to exposure assessments of the entire
US population, the study by Khan and Stralka (2008)
was selected as a key study of drinking water ingestion.
In this study,  ingestion rates for direct and indirect
ingestion of water are reported.  Direct ingestion is
defined as direct consumption of water as a beverage,
while indirect ingestion includes water added during
food preparation, but not water intrinsic to purchased
foods (i.e. water that is naturally contained in foods)
(Kahn and Stralka, 2008).  Data for consumption of
water from various sources (i.e., the community water
supply, bottled water,  and other sources)  are also
presented.  For the purposes of exposure assessments
involving site-specific contaminated drinking water,
ingestion rates based on the community  supply  are
most appropriate. Given the assumption that bottled
water, and purchased foods and beverages that contain
water are widely distributed and less likely to contain
source-specific water, the use of total water ingestion
rates may overestimate the  potential exposure to toxic
substances present  only  in  local water supplies;
therefore, tapwater  ingestion of community water,
rather than total water ingestion, is emphasized in this
section.
        The  studies on  water ingestion  that  are
currently available are based on short-term survey data
(two days). Although short-term data may be suitable
for obtaining mean or median ingestion values that  are
representative of both short- and long-term ingestion
distributions,  upper and lower -percentile values may
be different for short-term and long-term data.   It
should also be noted that most currently available
water ingestion surveys are based on recall. This may
be a source of uncertainty  in the estimated ingestion
rates because of the  subjective nature of this type of
survey technique. Percentile  distributions for water
ingestion  are presented in this  handbook, where
sufficient data are available. Data were not available to
estimate drinking water ingestion rates for children
during high activity levels or in extreme climates (i.e.,
hot weather).  Also, data are not provided for  the
location of water consumption (i.e., home, school, day
care center, etc.).
        Limited information was available regarding
children's  incidental  ingestion  of  water  while
swimming. This exposure  pathway may be important
since children are likely to ingest larger volumes of
water  while  swimming compared  to  adults; and
therefore, may have a greater exposure to pathogenic
microorganisms and chemicals present  in the water
than adults. A recent pilot  study (Dufour et al., 2006)
has provided  some quantitative experimental data on
water ingestion for child and adult swimmers.  These
data are provided  in this chapter.
        The  recommendations for water ingestion
rates are provided in the next section, along with a
summary  of the  confidence  ratings  for  these
recommendations. The recommended values are based
on the key study identified by U. S. EPA for this factor.
Following the recommendations, the key study  on
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                                                     	Chapter 3 - Water Ingestion
water ingestion is  summarized.   Relevant data on
ingestion of water and other select liquids are also
provided.  These studies are presented to provide the
reader with added perspective on the current state-of-
knowledge pertaining to ingestion of water and select
liquids.

3.2     RECOMMENDATIONS
3.2.1    Water Ingestion from  Consumption  of
        Water as a Beverage and from Food and
        Drink
        The recommended water ingestion rates for
children are based  on Kahn and Stralka (2008 and
supplementary data). This study presents estimates of
water ingestion by age  range  categories  for  the
population of the United States using data collected in
the U.S. Department of Agriculture's (USDA's) 1994-
96 and 1998 Continuing Survey of Food Intakes by
Individuals (CSFII) (USD A, 1998). A summary of the
recommended values for water ingestion rates is
presented  in Table 3-1.   A characterization of the
overall confidence in the accuracy and appropriateness
of the recommendations for drinking water intake is
presented in Table 3-2.

3.2.2    Water Ingestion while Swimming
        Based on the results of the Dufour et al.
(2006) study,  a mean  water ingestion rate of 50
mL/hour  for  children  ages 6  to   15 years  is
recommended  for   exposure  scenarios  involving
swimming activities.    The recommended upper
percentile  value is 100 mL/hour.  The recommended
values for children between 18 and 21 years of age are
based on the  results for adults from Dufour et al.
(2006). The mean value is 20 mL/hour and the upper
percentile value is 70 mL/hour. Although this estimate
was derived from swimming pool experiments, Dufour
et al.  (2006) noted that swimming behavior of pool
swimmers may  be  similar to freshwater swimmers.
Estimates may be different for salt water swimmers.
The confidence ratings for these recommendations are
presented in Table 3-3.  Data on  the amount of time
spent swimming can be found in chapter 16, Table 16-
21.
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Chapter 3 - Water Ingestion	
Table 3-1 . Recommended Values for Drinking Water Ingestion Rates3
Age Group
Mean
mL/dav mL/kg-dav
95th Percentile
mL/dav mL/kg-dav
Multiple „
_ f.. Source
Percentiles
Per Capita
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to
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                                                          	Chapter 3 -  Water Ingestion
                    Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates
 General Assessment Factors
                   Rationale
Rating
  Soundness
   Adequacy of Approach
   Minimal (or defined) Bias
The survey methodology and data analysis was
adequate. The survey sampled approximately 10,000
individuals under the age of 21 years; sample size
varied with age.

No physical measurements were taken.  The method
relied on recent recall of standardized volumes of
drinking water containers.	
                                                   Medium to High
 Applicability and Utility
   Exposure Factor of Interest

   Representativeness
   Currency

   Data Collection Period
The key study was directly relevant to water ingestion.

The data were demographically representative (based
on stratified random sample).

Data were collected between 1994 and 1998.

Data were collected for two non-consecutive days.
However, long term variability may be small. Use of a
short-term average as a chronic ingestion measure can
be assumed.
                                                   Medium to High
  Clarity and Completeness
   Accessibility
  Reproducibility

  Quality Assurance
The CSFn data are publicly available.  The Kahn and
Stralka (2008) analysis of the CSFH 1994-96, 1998
data was published in a peer-reviewed journal.

The methodology was clearly presented; enough
information was included to reproduce the results.

Quality assurance of the CSFn data was good; quality
control of the secondary data analysis was not well
described.
                                                        High
 Variability and Uncertainty
   Variability in Population
   Uncertainty
Full distributions were given in a separate document
(Khan and Stralka, 2008b).

Except for data collection based on recall, sources of
uncertainty were minimal.	
                                                        High
 Evaluation and Review
   Peer Review
   Number and Agreement of Studies
The USDA CSFn survey received high level of peer
review.  The Kahn and Stralka (2008) study was
published in a peer-reviewed journal.

There was 1 key study for drinking water ingestion.
                                                       Medium
  Overall Rating
                                                   Medium to High
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Chapter 3 - Water Ingestion	
                   Table 3-3. Confidence in Recommendations for Water Ingestion while Swimming
 General Assessment Factors
                      Rationale
Rating
  Soundness
   Adequacy of Approach
   Minimal (or defined) Bias
                                                            Medium
The approach appears to be appropriate given that cyanuric
acid (a tracer used in treated pool water) is not metabolized,
but the sample size was small (41 children). The Dufour et
al. (2006) study analyzed primary data on water ingestion
during swimming.

Data were collected over a period of 45 minutes; this may not
accurately reflect the time spent by a recreational swimmer.
 Applicability and Utility
   Exposure Factor of Interest
   Representativeness

   Currency

   Data Collection Period
                                                         Low to Medium
The key study was directly relevant to water ingestion while
swimming.

The sample was not representative of the U.S. population.
Data cannot be broken out by age categories

It appears that the study was conducted in 2005.

Data were collected over a period of 45 minutes.	
  Clarity and Completeness
   Accessibility
   Reproducibility
   Quality Assurance
The Dufour et al. (2006) study was published in a peer-
reviewed journal.

The methodology was clearly presented; enough information
was included to reproduce the results..

Quality assurance methods were not described in the study.
                                                            Medium
 Variability and Uncertainty
   Variability in Population
   Uncertainty
Only mean values for water ingestion were provided.  Data
were not broken out by age groups

There were multiple sources of uncertainty (e.g., sample
population may not reflect swimming practices for all
swimmers, rates based on swimming duration of 45 minutes,
differences by age group not defined).
                                                              Low
 Evaluation and Review
   Peer Review

   Number and Agreement of Studies
Dufour et al. (2006) was published in a peer-reviewed
journal.
There was 1  study for ingestion of water when swimming.
                                                            Medium
  Overall Rating
                                                              Low
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                                                      	Chapter 3 - Water Ingestion
3.3     DRINKING   WATER   INGESTION
        STUDIES
3.3.1    Key Drinking Water Ingestion Study
3.3.1.1  Kahn and Stralka, 2008 - Estimated Daily
        Average  Per  Capita Water Ingestion by
        Child and Adult Age Categories Based on
        USDA's  1994-96  and  1998  Continuing
        Survey of Food Intakes by Individuals
        Kahn  and  Stralka  (2008)  analyzed the
combined 1994-96 and 1998  Continuing Survey  of
Food  Intakes by  Individuals  (CSFII) data sets  to
examine water ingestion rates  of adults and children.
USDA surveyed households in the United States and
District of Columbia and collected food and beverage
recall data as part of the CSFII (USDA,1998). In the
initial  1994-96  survey,  over 15,000  respondents
provided data on  what they ate and drank over two
non-consecutive days. A 1998 supplement, using the
same methodology, added responses for approximately
5,000 children aged  9 years and younger to the
database.   Of  the  more than  20,000  individuals
surveyed, approximately 10,000 were under 21 years of
age, and approximately 9,000  were under the age of
11. For both survey days, data were collected by an in-
home interviewer.   The  day two interview  was
conducted 3 to 10 days later and on a different day of
the week.  The 1994-96 survey and  1998  supplement
are referred to collectively as  CSFII 1994-96,  1998.
Each individual in the survey was assigned a sample
weight based on his or her demographic data. These
weights were taken into account  when  calculating
mean and percentile water ingestion rates from various
sources.
        Khan and Stralka (2008) derived mean and
percentile estimates of daily average water ingestion
for children in eleven different age categories:  <1
month,  1 to <3 months, 3 to  <6 months, 6 to <12
months, 1 to <2 years of age,  2 to <3 years, 3 to <6
years, 6 to <11 years,  11 to < 16 years, 16 to <18 years,
and 18 to <21 years of age. The increased sample size
for children younger than 11 years of age (from 4,339
in the initial 1994-96 survey to 9,643 children in the
combined  1994-96,  1998  survey) enabled water
ingestion estimates to be categorized into the finer age
categories recommended by U.S. EPA (2005).  Per
capita and consumers only water ingestion estimates
were reported in the Kahn and Stralka (2008) study for
two  water  source  categories:  all  sources  and
community water. "All sources" included water from
all supply sources such as community water supply
 (i.e., tap water), bottled water, other sources, and
 missing sources.  "Community water" included tap
 water from a community or municipal water supply.
 Other sources  included wells, springs, and cisterns;
 missing sources  represented water sources that the
 survey respondent was unable to identify.  The water
 ingestion  estimates included both  water ingested
 directly as a beverage (direct water) and water added
 to foods and beverages  during final  preparation at
 home or by local food service establishments such as
 school cafeterias  and restaurants (indirect water).
 Commercial water added by a manufacturer (i.e., water
 contained in soda or beer) and intrinsic water in foods
 and liquids  (i.e., milk and natural undiluted juice)
 were not included in the estimates.  Kahn and Stralka
 (2008) only reported the mean, 90th and 95th percentile
 estimates of per capita and consumers only ingestion.
 The full distribution of ingestion estimates for various
 water source categories (all sources, community water,
 bottled water, and other sources) were provided by the
 author. Tables 3-4 to 3-7 provide mean and percentile
 per capita ingestion estimates of total water  (combined
 direct and indirect water) in mL/day  for the various
 water source categories  (i.e.,  community,  bottled,
 other, and all sources).   The 90 percent confidence
 intervals around the estimated means  and the  90
 percent bootstrap intervals around the 90th and 95th
 percentiles of  total water  ingestion from all water
 sources are presented in Table 3-8.  Tables 3-9 to 3-13
 present the same information as Tables 3-4 to 3-8 but
 in units of mL/kg-day.   Consumers only  combined
 direct and indirect water ingestion estimates in mL/day
 for the various source categories are provided in Tables
 3-14 to  3-17.  Table 3-18  presents confidence and
 bootstrap intervals for total water ingestion estimates
 by consumers only from all sources.  Tables 3-19 to 3-
 23 present the same information as Tables 3-14 to 3-18
 but in units of mL/kg-day.
         The data show that the total quantity of water
 ingested per unit mass of body weight is at a maximum
 in the first month of life and decreases with  increasing
 age.  The per capita ingestion rate of water from  all
 sources combined for children under 1  month of age is
 approximately four times higher than that adults, and
 consumers  younger than  1 month  of age  ingest
 approximately 8 times the amount of water (all sources
 combined) as adults (Kahn and Stralka,  2008).  The
 pattern of decreasing water ingestion per unit of body
 weight is also observed in per capita and  consumers
 only estimates of community water (Tables 3-9 and 3-
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Chapter 3 -  Water Ingestion	
19), bottled water (Table 3-10 and 3-20) and other
sources (Tables 3-11 and 3-21).
        The  CSFII 1994-96, 1998 data have both
strengths and limitations with regard to estimating
water ingestion.  These are discussed in detail in U.S.
EPA  (2004) and Kahn and Stralka  (2008).   The
principal advantages of this survey are  (1) that the
survey was designed  to obtain a  statistically valid
sample of  the entire  United States population that
included children and low income groups; (2) sample
weights were provided that facilitated proper analysis
of the data and accounted for non-response;  and (3)
that the sample size (approximately 10,000 children)
is  sufficient to allow categorization within narrowly
defined age categories.  Over sampling of children
enhanced the precision and accuracy of the estimates
for the child population subsets. One limitation of this
survey is that data were collected for only 2 days and
does not necessarily represent "usual intake." "Usual
dietary intake" refers to the long-term average of daily
intakes by an individual.  Thus, upper percentile water
ingestion estimates based on short-term data may differ
from long-term rates because short-term consumption
data tend to be inherently more variable. However,
Kahn and Stralka (2008) noted that variability due to
short term duration of the survey does not result in bias
of estimates of overall mean.  In addition, the survey
was  conducted  on  non-consecutive  days,  which
improves  the variance  over  consecutive  days of
consumption. However, the two non-consecutive days
of data collection, although an advantage over two
consecutive days,  provide limited information on
individual  respondents.  The two-day mean for an
individual can easily be skewed for numerous reasons.
Estimation at the individual respondent level was not,
however, an objective of the survey.  The large sample
provides useful information on the overall distribution
of ingestion by the population, and should adequately
reflect the range  among  respondent variability.
Another limitation of these data is that the survey
design, while being  well-tailored for  the  overall
population  of the United States and conducted
throughout the year to account for seasonal variation,
is of limited utility for assessing small and potentially
at-risk subpopulations based on ethnicity, medical
status, geography/climate,  or other factors such as
activity level.
3.3.2    Relevant Drinking Water Ingestion Studies
3.3.2.1  Levy et al, 1995 - Infant Fluoride Intake
        From Drinking Water Added to Formula,
        Beverages, and Food
        Levy  et al. (1995)  conducted a study to
determine fluoride intake by infants through drinking
water and other beverages prepared with water and
baby foods.  The study was longitudinal and covered
the ages from birth to 9 months old.  A total of 192
mothers, recruited from the post partum wards of two
hospitals in Iowa City, completed mail questionnaires
and three-day beverage and  food diaries for  their
infants at ages 6 weeks, and 3, 6, and 9 months of age
(Levy et al., 1995).   The  questionnaire addressed
feeding habits, water sources  and  ingestion, and the
use of dietary fluoride  supplements  during the
preceding week (Levy et al.,  1995).   Data  on the
quantity of water consumed by itself or as an additive
to infant  formula, other beverages,  or foods  were
obtained.  In addition, the questionnaire addressed the
infants' ingestion of cow's milk, breast-milk, ready-to-
feed infant products (formula, juices, beverages, baby
food), and table foods.
        Mothers were contacted for any clarifications
of missing data and discrepancies (Levy et al., 1995).
Levy et al.  (1995) assessed non-response bias and
found no significant differences in the reported number
of adults or children in the family, water sources, or
family income  at 3, 6, or 9 months.   Table  3-24
provides the range of water ingestion from water by
itself  and from addition  to  selected foods  and
beverages.  The percentage of infants ingesting water
by itself increased from 28 percent at 6 weeks to 66
percent at 9 months, respectively, and the mean intake
increased  slightly over this time frame.  During this
time frame, the largest proportion of the infants' water
ingestion (i.e., 36 percent at 9 months to 48 percent at
6 months) came from the addition of water to formula.
Levy et al. (1995) noted that 32 percent of the infants
at age 6 weeks and 23 percent of the infants at age 3
months did not receive any water from any of the
sources studied.  Levy et al.  (1995) also noted that the
proportion of children ingesting some water from all
sources gradually increased with age.
        The advantages of this  study are that  it
provides information on water ingestion of infants
starting at 6 weeks old and the data are for water only
and for water added to beverages and foods.  The
limitations of the study are that the sample size was
small for each age group, it captured information from
a select geographical location,  and data were collected
through self reporting.  The authors noted, however,
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that the three-day diary has been shown to be a valid
assessment tool. Levy et al. (1995) also stated that (1)
for each time period, the ages of the infants varied by
a few days to a few weeks, and are, therefore, not exact
and could, at early ages, have an effect on age-specific
intake patterns, and (2) the  same number  of infants
were not available at each of the four time periods.

3.3.2.2  Heller et al., 2000 - Water Consumption and
        Nursing  Characteristics of Infants by Race
        and Ethnicity
        Heller et al. (2000)  analyzed data from the
1994-96 CSFII to  evaluate racial/ethnic differences in
the ingestion rates of water in children younger than 2
years old.  Using  data from 946 children in this age
group,  the mean  amounts of water consumed from
eight sources were determined for various racial/ethnic
groups,  including black non-Hispanic, white non-
Hispanic,  Hispanic and  "other"  (Asian,  Pacific
Islander, American Indian, Alaskan Native, and other
non-specified racial/ethnic  groups).  The sources
analyzed included: (1) plain tap water, (2) milk and
milk drinks,  (3)  reconstituted powdered  or  liquid
infant formula made from drinking water, (4) ready-to-
feed and  other infant  formula,  (5) baby  food, (6)
carbonated beverages, (7)  fruit and vegetable juices
and other  noncarbonated drinks, and (8) other foods
and  beverages.    In addition,  Heller et al. (2000)
calculated mean plain water and total water ingestion
rates for children  by age, sex, region, urbanicity, and
poverty category.  Ages were defined as less than 12
months and 12 to 24 months.  Region was categorized
as Northeast, Midwest, South, and West. The states
represented by each of these regions was not reported
in Heller et al. (2000). However, it is likely that these
regions  were defined in the same way as in Sohn et al.
(2001).  See Section 3.3.2.4  for a discussion  on the
Sohn et al. (2001) study. Urbanicity of the residence
was  defined as urban (i.e., being in a Metropolitan
Statistical  Area [MSA], suburban [outside of an MS A],
or rural [being in a non-MSA]). Poverty category was
derived from the poverty income ratio. In this study,
a poverty income ratio was calculated by dividing the
family's annual  income  by  the  federal poverty
threshold  for  that  size  household.   The poverty
categories used were 0-1.30, 1.31-3.50, and greater
than 3.50 times the federal poverty level (Heller et al.,
2000).
        Table 3-25 provides water ingestion estimates
for the eight water sources evaluated, for each of the
 race/ethnic groups.  Heller et al. (2000) reported that
 black non-Hispanic children had the  highest mean
 plain tap water intake (21.3 mL/kg-day), and white
 non-Hispanic children had the lowest mean plain tap
 water intake (12.7 mL/kg-day). The only statistically
 significant difference between the racial/ethnic groups
 was found to be in plain tap water consumption and
 total water consumption. Reconstituted baby formula
 made up the highest proportion of total water intake
 for all race/ethnic  groups.  Table 3-26 presents tap
 water and total water ingestion by age, sex,  region,
 urbanicity, and poverty category. On average, children
 younger than 12 months of age consumed less plain
 tap water (11.0 mL/kg-day) than children aged 12-24
 months (17.7 mL/kg-day).  There were no significant
 differences in plain tap water consumption by  sex,
 region, or urbanicity.  Heller et al. (2000) reported a
 significant association between higher income  and
 lower plain tap water consumption.  For total water
 consumption, ingestion per kg body weight was lower
 for the 12-24-month-old  children  than for those
 younger than  12 months  of age.   Urban children
 consumed more plain tap water and total water than
 suburban and rural children.  In addition, plain tap
 water and total water ingestion was found to decrease
 with increasing poverty category (i.e., higher wealth).
         A major strength of the Heller et al. (2000)
 study is that it provides information on tap water and
 total water consumption by  race, age, sex,  region,
 urbanicity, and family income. The weaknesses in the
 CSFII data set have been discussed under Kahn and
 Stralka  (2008)  and U.S. EPA (2004) and include
 surveying participants for only two days.

 3.3.2.3  Sichert-Hellert et al., 2001 - Fifteen  Year
         Trends in  Water Intake in German Children
         and Adolescents: Results of the DONALD
         Study
         Water   and  beverage  consumption   was
 evaluated by Sichert-Hellert et al. (2001) using 3-day
 dietary records of 733 children, ages 2 to 13 years,
 enrolled  in  the  Dortmund   Nutritional   and
 Anthropometric  Longitudinally  Designed   Study
 (DONALD study).   The DONALD study is a cohort
 study, conducted in Germany, that  collects data on
 diet,  metabolism,  growth  and  development from
 healthy subjects between  infancy  and  adulthood
 (Sichert-Hellert  et al.,  2001).   Beginning in 1985,
 approximately 40 to 50 infants were enrolled in the
 study annually.  Mothers of the participants were
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Chapter 3 -  Water Ingestion	
recruited in hospital maternity wards. Older children
and parents  of younger children were asked to keep
dietary  records  for  three  days by  recording  and
weighing (to the nearest 1 gram) all foods and fluids,
including water, consumed.
        Sichert-Hellert et al. (2001) evaluated 3,736
dietary records from 733 subjects (354 males and 379
females) collected between 1985  and 1999.  Total
water ingestion was defined as the  sum of water
content from food (intrinsic water), beverages  and
oxidation. Beverages included  milk, mineral water,
tap water, juice, soft drinks, and  coffee and tea. Table
3-27 presents the mean water ingestion rates for these
different sources, as well as mean total water ingestion
rates for three age ranges of children (age 2 to 3 years,
age 4 to 8 years, and age 9 to 13  years). According to
Sichert-Hellert   et  al.  (2001),  mean  total  water
ingestion increased with age from 1,114 mL/day in the
2 to 3 year old subjects to 1,891  and 1,676 mL/day in
9 to 13-year-old boys and girls, respectively. However,
mean total water intake per body weight decreased
with age. Sichert-Hellert et al.  (2001) observed that
the most important source of total water ingestion was
mineral water for all children, except the 2 to 3 year
olds. For these children, the most important source of
total water ingestion was milk .
        One of the limitations of this study is that it
evaluated water and beverage consumption in German
children and, as such, it may not be representative of
consumption patterns of U.S. children.

3.3.2.4  Sohn et al., 2001 -  Fluid  Consumption
        Related to Climate Among Children in the
        United States
        Sohn   et  al.  (2001)  investigated  the
relationship   between  fluid  consumption  among
children aged 1 to 10 years and local climate using data
from  the third National Health   and Nutrition
Examination  Survey  (NHANES  III,  1988-94).
Children aged 1 to 10 years who completed the 24-
hour dietary interview (or proxy  interview for the
younger children) during the NHANES III survey were
selected for  the  analysis.  Breast-fed children were
excluded from the analysis.  Among 8,613 children
who were surveyed, 688 (18 percent) were excluded
due to incomplete data.   A total of 7,925 eligible
children remained. Since data for climatic conditions
were not collected in the  NHANES III survey, the
mean daily maximum temperature from 1961 to 1990,
averaged for the month during which the NHANES III
survey was conducted, was obtained for  each survey
location  from  the  U.S. Local  Climate Historical
Database. Of the 7,925 eligible children with complete
dietary data, temperature information was derived for
only 3,869  children (48.8 percent) since  detailed
information on survey location, in terms of county and
state, was released only for counties with a population
of more than a half million
        Sohn et al. (2001) calculated the total amount
of fluid intake for each child by adding the fluid intake
from plain drinking water and the fluid  intake from
foods and beverages other than plain drinking water
provided by NHANES  III.   Sohn et al. (2001)
identified major  fluid  sources  as milk (and  milk
drinks), juice (fruit and vegetable juices and  other
noncarbonated drinks), carbonated drinks, and  plain
water.  Fluid intake from sources other than  these
major sources were all grouped into other foods and
beverages. Other foods and beverages included bottled
water,  coffee,  tea,  baby food,  soup,   water-based
beverages, and water used for dilution of food.  Mean
fluid ingestion  rates of  selected  fluids  for  the total
sample population and for the subsets of the sample
population with and without temperature information
are presented in Table 3-28. The estimated mean total
fluid and plain water ingestion  rates for the 3,869
children  for whom temperature information  was
obtained are presented in Table 3-29 according to age
(years),  sex, race/ethnicity,  poverty/income  ratio,
region, and urban or rural. Poverty/income ratio was
defined as the ratio of the reported family income to
the federal poverty level.  The following categories
were assigned: low  socioeconomic  status  (SES)  =
0.000-1.300 times the poverty/income ratio; medium
SES = 1.3.01-3.500 times the poverty/income level;
and  high  SES  =  3.501  or  greater times the
poverty/income level.  Regions  were as Northeast,
Midwest,  South,  and West, as defined  by  the U.S.
Census (see Table 3-29).  Sohn et al. (2001) did not
find significant  association  between   mean  daily
maximum temperature and total fluid or plain water
ingestion, either before  or after controlling for sex,
age, SES and race or ethnicity. However, significant
associations between fluid ingestion and  age,  sex,
socioeconomic  status and race and ethnicity  were
reported.
        The main strength of the Sohn et al. (2001)
study is the evaluation of water intake as it relates to
weather data. The main  limitations of this study were
that northeast and  western regions  were  over
represented since temperature data was only available
for  counties with populations in excess of a half
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                                                       	Chapter 3 - Water Ingestion
million.  In addition, whites were under-represented
compared to  other racial or ethnic groups.   Other
limitations include lack of data for children from
extremely cold or hot weather conditions.

3.3.2.5  Hilbig et al., 2002 - Measured Consumption
        of Tap Water in German Infants and Young
        Children  as  Background for  Potential
        Health  Risk  Assessment:  Data  of  the
        DONALD Study
        Hilbig et  al.  (2002)  estimated tap  water
ingestion rates based on 3-day dietary records of 504
German children aged 3,  6, 9,  12, 18, 24 and 36
months.  The data were collected between 1990  and
1998 as part of the DONALD study. Details of data
collection for the DONALD study have been provided
previously under the Sichert-Hellert et al. (2001) study
in Section 3.3.2.3 of  this  handbook.   Tap  water
ingestion rates were calculated for three subgroups of
children: (1)  breast-fed infants <12 months of age
(exclusive and partial breast-fed infants) (2) formula-
fed infants < 12 months of age (no human milk, but
including weaning food) and  (3) mixed-fed young
children aged 18 to 36 months. Hilbig et al. (2002)
defined "total tap water from household" as water from
the tap consumed as  a beverage  or used  in food
preparation.  "Tap water from food manufacturing"
was defined as water used in industrial production of
foods, and "Total Tap Water" was defined as tap water
consumed from both the household and that used in
manufacturing.
        Table 3-30  summarizes  total tap  water
ingestion (in mL/day and mL/kg-day) and tap water
ingestion from household and manufacturing sources
(in mL/kg-day) for breastfed, formula fed and mixed-
fed children.  Mean total tap water intake was higher
in formula-fed infants (53 mL/kg-day) than in breast-
fed infants (17  g/kg-day)  and  mixed-fed young
children (19 g/kg-day).  Tap water from household
sources constituted 66 to 97 percent of total tap water
ingestion in the different age groups.
        The major limitation of this study is that the
study sample consists of families from an upper social
background in Germany (Hilbig et al., 2002). Because
the study was conducted in Germany, the data may not
be directly applicable to the U.S. population.
 3.3.2.6  Marshall  et al.,  2003a  -    Patterns  of
         Beverage   Consumption  During   the
         Transition Stage of Infant Nutrition
         Marshall et al. (2003a) investigated beverage
 ingestion  during  the transition  stage  of infant
 nutrition.  Mean ingestion of infant formula, cow's
 milk, combined juice and juice drinks, water, and other
 beverages  were  estimated  using  a  frequency
 questionnaire.   A total of  701  children, ages six
 months through 24 months, participated in the Iowa
 Fluoride  Study (IPS).  Mothers  of newborns were
 recruited from 1992 through 1995. The  parents were
 sent questionnaires when the children were 6, 9, 12,
 16, 20, and 24 months old.  Of the 701 children, 470
 returned all six questionnaires, 162 returned five, 58
 returned four and 11 returned three, with the minimum
 criteria being three questionnaires to be included in the
 data set (Marshall et al., 2003a).   The questionnaire
 was designed to assess the type and quantity of the
 beverages consumed during the previous week.  The
 validity of the questionnaire  was assessed using a
 three-day  food diary for reference (Marshall et al.,
 2003a).   The percentage  of subjects consuming
 beverages and mean daily beverage ingestion for
 children with returned questionnaires are presented in
 Table 3-31. Human milk ingestion was not quantified,
 but the percent of children consuming human milk was
 provided at each age category (Table 3-31).  Juice (100
 percent)  and juice  drinks  were  not distinguished
 separately, but categorized as juice and  juice drinks.
 Water used to dilute beverages beyond normal dilution
 and water consumed alone were combined. Based on
 Table  3-31, 97  percent of the children  consumed
 human milk, formula, or  cow's milk throughout the
 study period, and the percentage of infants consuming
 human milk decreased with age,  while the percent
 consuming water increased (Marshall et al., 2003a).
 Marshall et al.  (2003a) observed that in general, lower
 family incomes were associated with less breastfeeding
 and increased ingestion of other beverages.
         The advantage of this study is that it provides
 mean  ingestion  data  for  various  beverages.
 Limitations of the study are that the it is based on
 samples gathered in one geographical area and may
 not be reflective of the  general  population.   The
 authors also  noted the following limitations:  the
 parents were not asked to differentiate  between  100
 percent juice and juice drinks; the data are parent-
 reported and could reflect perceptions of appropriate
 ingestion instead of actual ingestion, and a substantial
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Chapter 3 - Water Ingestion	
number  of  the  infants  from  well  educated,
economically secure households dropped out during
the initial phase.

3.3.2.7  Marshall et al, 2003b - Relative Validation
        of a Beverage Frequency Questionnaire in
        Children Ages 6 Months through  5 Years
        Using 3-day Food and Beverage Diaries
        This study was based on data taken from 700
children in the IPS. This study compared estimated
beverage ingestion rates reported in questionnaires for
the preceding week and dairies for the following week.
Packets were sent periodically (every 4 to 6 months) to
parents of children aged 6 weeks through 5  years of
age.  This study analyzed data from children, ages 6
and 12 months, and 2  and 5 years of age. Beverages
were categorized as human milk, infant formula, cow's
milk,  juice  and  juice  drinks,  carbonated  and
rehydration beverages, prepared drinks (from powder)
and water. The beverage questionnaire was completed
by parents and summarized the average amount of
each beverage consumed per day by their children.
The  data collection for  the diaries maintained by
parents included 1 weekend day and 2 week days and
included  detailed  information  about  beverages
consumed.  Table 3-32 presents the mean ingestion
rates of all  beverages for children  aged 6  and  12
months and  3 and 5 years.  Marshall et al.  (2003b)
concluded that estimates of beverage ingestion derived
from quantitative questionnaires are  similar  to those
derived from diaries. They found that it is particularly
useful to estimate ingestion of beverages  consumed
frequently using quantitative questionnaires.
        The advantage of this study is that the survey
was conducted in two  different forms (questionnaire
and diary) and that diaries for recording beverage
ingestion were maintained by parents for three days.
The  main  limitation  is the lack  of information
regarding whether the diaries  were populated on
consecutive or non-consecutive days.  The IPS survey
participants may not be representative of the general
population  of  the  U.S.  since  participants were
primarily white, and from affluent and well-educated
families in one geographic region of the country.

3.3.2.8  Skinner et al., 2004 - Transition in Infants'
        and Toddlers' Beverage Patterns
        Skinner et al.  (2004) investigated the pattern
of beverage consumption by infants  and children
participating in the Feeding Infant and Toddlers Study
(FITS) sponsored by Gerber Products Company.  The
FITS is a cross-sectional study designed to collect and
analyze data on feeding practices, food consumption,
and usual nutrient intake of U.S. infants and toddlers
(Devaney et al., 2004). It included a stratified random
sample of 3,022 infants and toddlers between 4 and 24
months of age.  Parents or primary caregivers of
sampled infants and toddlers completed a single 24-
hour  dietary  recall  of  all foods  and  beverages
consumed  by the  child  on the  previous day by
telephone interview.    All  recalls were  completed
between March and July 2002.  Detailed information
on data collection, coding and analyses related to FITS
are provided in Devaney et al. (2004).
        Beverages consumed by  FITS participants
were identified as total milks (i.e., human milk, infant
formulas, cows milk, soy milk, goat milk), 100 percent
juices, fruit drinks, carbonated beverages,  water and
"other" drinks (i.e., tea, cocoa, dry milk mixtures, and
electrolyte replacement beverages).  There were six age
groupings in the FITS study: 4 to 6, 7 to 8,  9 to  11, 12
to 14,  15 to 18, and 19 to 24 months.  Skinner et al.
(2004) calculated the percentage of children in each
age  group consuming any amount  in a beverage
category and the mean amounts consumed. Table 3-33
provides  the  mean beverage consumption rates in
mL/day for the six age categories.   Skinner et al.
(2004) found that  some form of milk beverage was
consumed by almost all children at each age; however,
total milk ingestion decreased with increasing age.
Water consumption also doubled with age, from 163
mL/day in children aged 4 to 6 months old to 337
mL/day at 19 to 24 months old.  The percentages of
children consuming water increased from  34 percent
at 4 to 6  months of age  to 77 percent at 19 to 24
months of age.
        A major strength of the Skinner et al. (2004)
study  is  the   large sample  size  (3,022  children).
However, beverage ingestion estimates are based on
one day of dietary recall data and human milk quantity
derived from  studies that weighed infants before and
after each feeding to determine the quantity of human
milk  consumed  (Devaney et al.,  2004);  therefore,
estimates of total milk ingestion may not be accurate.

3.4     WATER  INGESTION WHILE
        SWIMMING
3.4.1   Dufour et al., 2006 -  Water  Ingestion
        During Swimming Activities in  a Pool: A
        Pilot Study
        Dufour et al. (2006) estimated the amount of
water ingested while swimming, using cyanuric acid as
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                                                      	Chapter 3 - Water Ingestion
an  indicator  of  pool water  ingestion  exposure.
Cyanuric   acid   is   a  breakdown  product  of
chloroisocyanates which are  commonly  used as
disinfectant stabilizers in recreational water treatment.
Because ingested cyanuric acid  passes through the
body unmetabolized, the volume of water ingested can
be estimated based on the amount of cyanuric acid
measured  in the  pool water and in the  urine of
swimmers, as follows:
* pool water ingested   * urine ^
                                      (Eqn. 3-1)
where:


 * pool water ingested


 •urine


^ urine

CApool
                   volume of pool water ingested
                   (mL)
                   volume of urine collected over a
                   24-hour period (mL)
                   concentration of cyanuric acid
                   in urine (mg/L)
                   concentration of cyanuric acid
                   in pool water (mg/L)
        Dufour et al. (2006) estimated pool water
intake among 53 swimmers that participated in a pilot
study at an  outdoor swimming pool treated with
chloroisocyanate. This pilot study population included
12 adults (4 males and 8 females) and 41 children
between 6 and 15 years  of age (20  males  and 21
females).  The study participants were asked not to
swim for 24 hours before or after a 45 minute period of
active swimming in the pool. Pool water samples were
collected prior to the start of swimming activities and
swimmers' urine was collected for 24 hours after the
swimming event ended.  The pool water and urine
sample were analyzed for cyanuric acid.
        The results of this pilot study are presented in
Table 3-34.  The mean volume of water ingested by
children over a 45-minute period was 37 mL.  The
maximum volume of water ingested by children was
154 mL/45 minutes and the 97th percentile was 90 mL.
Individuals older than 18  years of age ingested an
average of 16  mL  over a 45-minute period;  the
maximum amount ingested by these individuals was
53mL over a  45-minute period.  The mean ingestion
rates for  males tended to be higher than that of
females, but these differences were not statistically
significant.  The advantages of this study is that it is
one of the first attempts to measure water ingested
while swimming.   However,  the number of study
participants was low and data cannot be broken out by
the recommended age categories.  As noted by  the
Dufour  et al.  (2006), swimming  behavior  of pool
swimmers may be similar to freshwater swimmers,  but
may differ from salt water swimmers.
        Based on  the results of the Dufour et  al.
(2006) study, the recommended mean water ingestion
rate  for exposure  scenarios  involving  swimming
activities is 50 mL/hour for children under 16 years of
age (37 mL/0.75 hour, rounded to  one  significant
figure) and the upper percentile value is 100 mL/hour
(90 mL/0.75 hour, rounded to one significant figure).
For children, ages 18 to <21 years,  the recommended
mean water ingestion rate  for scenarios involving
swimming activities is 20 mL/hour (16 mL/0.75 hour,
rounded to one significant figure).  Because the data
set is limited, the upper percentile water ingestion rate
for 1 8 to <2 1 year olds is based on the maximum value
observed in adults in the Dufour et al. (2006) study: 70
mL/hour (53 mL/0.75 hour, rounded to one significant
figure).
                                                      3.5
                                                               REFERENCES FOR CHAPTER 3
                                                      Devaney, B. ; Kalb, L. ; Briefel, R. ; Zavitsky-Novak, T. ;
                                                              Clusen, N. ; Ziegler, P. (2004) Feeding Infants
                                                              and Toddlers Study: Overview of the study
                                                              design.  J Am Diet Assoc  104 (supplement
                                                              1): S8-S13.
                                                      Dufour, A.P.; Evans, O.; Behymer, T.D., Cantu, R.
                                                              (2006) Water ingestion during  swimming
                                                              activities in a pool:  a pilot study.  J Water
                                                              Health 4(4):425-430.
                                                      Heller, K.; Sohn, W.; Burt, B.; Feigal, R.  (2000)
                                                              Water   consumption   and   nursing
                                                              characteristics  of  infants by  race  and
                                                              ethnicity. J Public Health Dent 60 (3) 140-
                                                              146.
                                                      Hilbig, A.; Kersting, M; Sichert-Hellert, W. (2002) -
                                                              Measured  consumption of tap  water in
                                                              German  infants  and young children as
                                                              background  for  potential   health  risk
                                                              assessment: Data of the  DONALD study.
                                                              Food Addit Contam  19 (9): 829-836.
                                                      Kahn, H.; Stralka, K. (2008) Estimated daily average
                                                              per capita water ingestion by child and adult
                                                              age categories based on USD A' s 1994-96 and
                                                              1998 continuing survey of food intakes by
                                                              individuals. J Expo Anal Environ Epidemiol
                                                              (accepted for publication May 2008).
Page
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Child-Specific Exposure Factors Handbook

Chapter 3 - Water Ingestion	
Levy, S.; Kohout, F.; Guha-Chowdhury, N.; Kiristy,
        J., Heilman, et al. (1995) Infants' fluoride
        intake from drinking water alone, and from
        water added to formula, beverages, and food.
        J Dent Res (74): 1399-1407.
LSRO  (1995)   Life  Sciences   Research  Office,
        Federation   of  American  Societies  for
        Experimental Biology  Prepared  for  the
        Interagency Board for Nutrition Monitoring
        and  Related Research.  Third Report on
        Nutrition Monitoring in the United States:
        Volume 1. U.S. Government Printing Office,
        Washington, D.C.
Marshall,  T.; Levy,  S.; Broffitt, B.; Eichenberger-
        Gilmore, J.; Stumbo, P.  (2003a) Patterns of
        beverage consumption during the transition
        stage of infant nutrition. J Amer Diet Assoc
        103 (10):1350-1353.
Marshall, T.; Eichenberger Gilmore, J; Broffitt, B.;
        Levy,  S.;   Stumbo,   P.  (2003b)  Relative
        Validation   of  a  beverage   frequency
        questionnaire in  children Ages 6 months
        through 5  years  using  3-day food and
        beverage diaries.  J Amer Diet Assoc  103
        (6):714-720.
National Academy  of Sciences  (NAS).    (1977)
        Drinking water  and  health.     Vol.  1.
        Washington, DC:   National Academy  of
        Sciences-National Research Council.
Sichert-Hellert,  W.;  Kersting, M.; Manz, F. (2001)
        Fifteen year trends in water intake in German
        children and adolescents: results  of  the
        DONALD study. ActaPaediatr 90: 732-7.
Skinner, J.; Ziegler, P.; Ponza, M. (2004) - Transition
        in Infants' and Toddles' Beverage Patterns.
        J Amer Diet Assoc  Supplement 1 104 (1):
        S45-S50.
Sohn, W.; Heller, K. E.; Burt, B. A.  (2001) Fluid
        consumption  related  to climate  among
        children in the United States. J Public Health
        Dent. 61(2): 99-106.
USD A.  (1998)  Continuing survey of food intakes by
        individuals: 1994-96,1998. U.S. Department
        of Agriculture, Agricultural Research Service.
U.S. EPA. (2000) Methodology for deriving ambient
        water quality criteria for the protection of
        human health (2000). U.S. Environmental
        Protection   Agency,  Office   of  Water,
        Washington, D.C., EPA-822-00-004. October
        2000.
U.S. EPA.   (2004)  Estimated  Per Capita Water
        Ingestion and Body Weight in the United
        States— an Update: Based on Data Collected
        by  the  United  States  Department  of
        Agriculture's 1994-96 and 1998 Continuing
        Survey of Food Intakes by Individuals. U.S.
        Environmental Protection Agency, Office of
        Water, Washington, D.C.,  EPA-822-R-00-
        00 I.October 2004.
U.S. EPA. (2005) Guidance on Selecting Age Groups
        for  Monitoring  and  Assessing  Childhood
        Exposures to Environmental Contaminants.
        U.S.  Environmental Protection  Agency,
        Washington,  D.C.,  EPA/630/P-03/003F.
        November 2005.
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                                                          Child-Specific Exposure Factors Handbook

                                                         	Chapter 3 - Water Ingestion
      Table 3-4.  Per Capita3 Estimates of Combined Direct and Indirect* Water Ingestion: Community Water (mL/day)
           Age
Sample
  size
Mean
                                                                     Percentiles
                                            10
                             25
                             50
                            75
                             90
                             95
                             99
   Birth to <1 month
   1 to <3 months
   3 to <6 months
   6 to <12 months
   1 to <2 years
   2 to <3 years
   3 to <6 years
   6 to <11 years
   11 to<16 years
   16 to <18 years
   18to<21 years
  91
 253
 428
 714
 1,040
 1,056
 4,391
 1,670
 1,005
 363
 389
 184
 227
 362
 360
 271
 317
 380
 447
 606
 731
 826
 4
22
30
16
24
 17
 60
 78
 98
133
182
194
236
148
218
188
246
291
350
459
490
628
 322
 456
 695
 628
 402
 479
 547
 648
 831
 961
687*
 804
 928
 885
 624
 683
 834
 980
1,387
1,562
 839*
 896*
 1,056
 1,055
 837
 877
 1,078
 1,235
 1,727
1,983*
1,119     1,770    2,540*
1,165*
1,424*
1,511*
1,215*
1,364*
 1,654
1,870*
2,568*
3,720*
3,889*
    a        Includes all participants whether or not they ingested any water from the source during survey period.
    b        Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the
            preparation of food or beverages.
            = Zero.
    *        The sample size does not meet minimum requirements as described in the "Third Report on Nutrition
            Monitoring in the United States" (LSRO, 1995).

    Source:  Kahn and Stralka, 2008 and supplementary data.
        Table 3-5. Per Capita3 Estimates of Combined Direct and Indirect13 Water Ingestion:  Bottled Water (mL/day)
           Age
Sample
  size
Mean
                                                                     Percentiles
                                            10
                             25
                             50
                            75
                             90
                             95
                             99
   Birth to <1 month
   1 to <3 months
   3 to <6 months
   6 to <12 months
   1 to <2 years
   2 to <3 years
   3 to <6 years
   6 to
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Child-Specific Exposure Factors Handbook
Chapter 3 - Water Ingestion














Table 3-6. Per Capita3 Estimates of Combined Direct and Indirect1" Water Ingestion:
Sample , , Percentiles
size IvWl 10 25 50 75
Birth to <1 month 91 13 -
1 to <3 months 253 35 -
3 to <6 months 428 45 -
6 to <12 months 714 45 -
1 to <2 years 1,040 22
2 to <3 years 1,056 39
3 to <6 years 4,391 43
6to
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                                              Child-Specific Exposure Factors Handbook


                                             	Chapter 3 - Water Ingestion
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3-16
                            Child-Specific Exposure Factors Handbook
                            	September 2008

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"hild-Specific Exposure Factors Handbook f
^^^A'
Chapter 3 - Water Ingestion

Table 3-9. Per Capita2 Estimates of Combined Direct and Indirectb Water Ingestion: Community Water (mL/k
Age
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to<16 years
16 to <18 years
18to<21 years
Sample
g-day)
Percentiles
size 10 25
88 52
245 48
411 52
678 41
1,002 23
994 23
4,112 22
1,553 16 1
975 12 1
360 11
383 12 1
-
-
-
2
5
6
6
5
4
3
4
50
-
-
20
24
17
17
17
12
9
8
10
75 90 95
101 196* 232*
91 151 205*
98 135 159
71 102 126
34 53 71
33 50 60
31 48 61
22 34 43
16 25 34
15 23 31*
16 17 35*
99
253*
310*
216*
185*
106*
113*
93
71*
54*
55*
63*
a mcludes all participants whether or not they ingested any water from the source during survey period.
b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the
preparation of food or beverages.
= Zero.
* The sample
Monitoring
size does not meet minimum requirements
in the United States" (LSRO, 1995).
as described in
the "Third Report on Nutrition

Source: Kahn and Stralka, 2008 and supplementary data.
Table 3-10. Per Capita3 Estimates of Combined Direct and Indirectb Water Ingestion: Bottled Water (mL/kg-day)


Age
Birth to <1 month
1
3
6
1
2
3
6
to<3
to<6
months
months
to <12 months
to<2
to<3
to<6
years
years
years
to
-------
                                            Child-Specific Exposure Factors Handbook

                                                          Chapter 3 - Water Ingestion












Table 3-11. Per Capita2 Estimates of Combined Direct and Indirect* Water Ingestion:
Sample . , Percentiles
5 size 10 25 50 75
Birth to <1 month 88 4 -
1 to <3 months 245 7 -
3 to <6 months 411 7
6 to <12 months 678 5
1 to <2 years 1,002 2
2 to <3 years 994 3 -
3 to <6 years 4,112 2
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 3 - Water Ingestion	
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Child-Specific Exposure Factors Handbook
September 2008	
                                                                  Page
                                                                   3-19

-------
                                            Child-Specific Exposure Factors Handbook

                                                          Chapter 3 - Water Ingestion

















Table 3-14. Consumers Only3 Estimates of Combined Direct
(mL/day)
, Sample
Age . F
size
Birth to <1 month 40
1 to <3 months 114
3 to <6 months 281
6 to <12 months 562
1 to <2 years 916
2 to <3 years 934
3 to <6 years 3,960
6to
-------
Child-Specific Exposure Factors Handbook
                                                                           wm._

Chapter 3 - Water Ingestion	
Table 3-16. Consumers Only3 Estimates of Combined Direct and Indirectb Water Ingestion: Other Sources (mL/day)
Sample „ r Percentiles
Age . Mean
5 size 10 25 50
Birth to <1 month 3 - - - -
1 to <3 months 19
3 to <6 months 38 562* 59* 179* 412*
6 to <12 months 73 407* 31* 121* 300*
1 to <2 years 98 262 18* 65 143
2 to <3 years 129 354 56* 134 318
3 to <6 years 533 396 59 148 314
6to
-------
                                               Child-Specific Exposure Factors Handbook


                                               	Chapter 3 - Water Ingestion
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3-22
                         Child-Specific Exposure Factors Handbook

                        	September 2008

-------
Child-Specific Exposure Factors Handbook




Chapter 3 - Water Ingestion	
Table 3-19. Consumers Onlya Estimates of Direct and Indirectb Water Ingestion: Community Water (mL/kg-day)
Sample
b size 10
Percentiles
25
50
Birth to <1 month 37 137* 11* 65* 138*
1 to <3 months 108 119 12*
3 to <6 months 269 80 7
6 to <12 months 534 53 5
1 to <2 years 880 27 4
2 to <3 years 879 26 4
3 to <6 years 3,703 24 3
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                                          Chapter 3 - Water Ingestion


Table 3-21 . Consumers Onlya Estimates of Direct and Indirect11 Water Ingestion: Other Sources
Sample , , Percentiles
size IvWl 10 25 50 75 90
Birth to <1 month 3 - - - - -
1 to <3 months 19
3 to <6 months 38 80* 10* 23* 59* 106* 170*
6 to <12 months 68 44* 4* 10* 33* 65* 95*
1 to <2 years 95 23 1* 5 13 28 46*
2 to <3 years 124 26 4* 10 21 34 55*
3 to <6 years 505 22 3 8 17 30 46
6to
-------
Child-Specific Exposure Factors Handbook


Chapter 3 - Water Ingestion	
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-------
                                                Child-Specific Exposure Factors Handbook

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Page
3-26
                          Child-Specific Exposure Factors Handbook
                         	September 2008

-------
Child-Specific Exposure Factors Handbook




Chapter 3 - Water Ingestion	
                 ES
                  
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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 3 - Water Ingestion
Table
3-26. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and Poverty Category
Plain Tap Water
(mL/kg-day)

Age

Sex


Region



Variable
<12 months
12-24 months

Male
Female
Northeast
Midwest
South
West
N
296
650

475
471
175
197
352
222
Mean
11
18

15
15
13
14
15
17
SE
1.0
0.8

1.0
0.8
1.4
1.0
1.3
1.1
Total Water
(mL/kg-day)
Mean
130
108

116
119
121
120
113
119
SE
4.6
1.7

4.1
3.2
6.3
3.1
3.7
4.6
Urbanicity



Poverty



Total
a
N
SE
Source:
Urban
Suburban
Rural
category3
0-1.30
1.31-3.50
>3.50

Poverty category represents
federal poverty level.
= Number of observations.
= Standard Error.
Heller etal, 2000.
305
446
195

289
424
233
946
family


16
13
15

19
14
12
15
s annual incomes of 0-1


1.5
0.9
1.2

1.5
1.0
1.3
0.6
30,1.31-3


123
117
109

128
117
109
118
50, and greater than 3


3.5
3.1
3.9

2.6
4.2
3.5
2.3
50 times the


Page
3-28
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 3 - Water Ingestion	
Table 3-27. Intake of
Water Intake from:
Water from Various Sources in 2-13-y-old Participants of the
DONALD Study 1985-1999
Boys and girls Boys and girls
2-3 years 4-8 years
N=858b N= 1,795"
Boys
9-13 years
N=541b
Girls
9-13 years
N = 542"
Mean
Water in Food (mL/day)3
Beverages (mL/day)3
Milk (mL/day)3
Mineral water (mL/day)3
Tap water (mL/day)3
Juice (mL/day)3
Soft drinks (mL/day)3
Coffee/tea (mL/day)3

Total water intake3-4 (mL/day)
Total water intake3-4 (mL/kg-day)
Total water intake3-4 (mL/kcal-
day)
365 (33)c
614(55)
191(17)
130(12)
45(4)
114(10)
57(5)
77(7)

1,114±289 1
78 ±22
1.1±0.3
3 Converted from g/day, g/kg-day, or g/kcal-day; 1 g =
b N = Number of records.
487 (36)
693(51)
177(13)
179(13)
36(3)
122 (0)
111(8)
69(5)
Mean±
,363 ±333
61 ±13
0.9 ±0.2
ImL.
673 (36)
969(51)
203(11)
282(15)
62(3)
133 (7)
203(11)
87(4)
SD
1,891 ±428
49±11
1.0 ±0.2

634 (38)
823 (49)
144 (9)
242(15)
56(3)
138(8)
155(9)
87(5)

1,676 ±386
43 ±10
1.0 ±0.2

c Percent of total water shown in parentheses.
4 Total water = water in food + beverages + oxidation.
SD = Standard deviation.
Source: Sichert-Hellert et al. , 200 1 .




Child-Specific Exposure Factors Handbook
September 2008	
Page
 3-29

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 3 - Water Ingestion
Table 3-28. Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years,
NHANESm, 1988-94

Total fluid
Plain water
Milk
Carbonated drinks
Juice
N = Number of observations
Source: Sohnet al., 2001.
Total Sample
(N = 7,925)
84 ±1.0
27 ±0.8
18 ±0.3
6 ±0.2
12 ±0.3


Sample with
Temperature Information
(N = 3,869)
84 ±1.0
27 ±1.0
18 ±0.6
5 ±0.3
11±0.6


Sample without
Temperature Information
(N = 4,056)
85 ±1.4
26±1.1
18 ±0.4
6 ±0.3
12 ±0.4


Page
3-30
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook




Chapter 3 - Water Ingestion





















































Table 3-29. Estimated Mean (± Standard Error) Amount of Total Fluid and Plain Water Intake
among Children3 Aged 1-10 Years: (NHANES HI, 1988-94)
Total Fluid

mL/day mL/kg-day
Age (years)
1 578 1,393 ±31 124 ±2. 9
2 579 1,446 ±31 107 ±2.3
3 502 1,548 ±75 100 ±4.6
4 511 1,601 ±41 91 ±2. 8
5 465 1,670 ±54 84 ±2. 3
6 255 1,855 ±125 81 ±4. 9
7 235 1,808 ±66 71 ±2.3
8 247 1,792 ±37 61 ± 1.8
9 254 2,113 ±78 65 ±2.1
10 243 2,051 ±97 58 ±2.4
Sex
Male 1,974 1,802 ±30 86 ±1.8
Female 1,895 1,664±24 81 ± 1.5
Race/ethnicity
White 736 1,653 ±26 79 ±1.8
African American 1,122 1,859 ±42 88 ±1.8
Mexican American 1,728 1,817 ±25 89 ±1.7
Other 283 1,813 ±47 90 ±4.2
Poverty income ratiob
Low 1,868 1,828 ±32 93 ±2. 6
Medium 1,204 1,690 ±31 80 ±1.6
High 379 1,668 ±54 76 ±2.5
Region04
Northeast 679 1,735 ±31 87 ±2. 3
Midwest 699 1,734 ±45 84 ±1.5
South 869 1,739 ±31 83 ±2.2
West 1,622 737 ±25 81 ± 1.7
Urban/rural11
Urban 3,358 1,736 ±18 84 ±1.0
Rural 511 1,737 ±19 84 ±4.3
Total 3,869 1,737 ±15 84 ±1.1
a Children for whom temperature data were obtained.
b Based on ratio of household income to federal poverty threshold. Low: <1 .300; medium: 1
Plain Water

mL/day mL/kg-day

298 ±19 26 ±1.8
430 ±26 32 ±1.9
482.±27 31 ±1.8
517±23 29±1.3
525 ±36 26 ±1.7
718±118 31 ±4.7
674 ±46 26 ±1.9
626 ±37 21 ±1.2
878 ±59 26 ±1.4
867 ±74 24 ± 2.0

636 ±32 29 ±1.3
579 ±26 26 ±1.0

552 ±34 24 ±1.3
795 ±36 36 ±1.5
633 ±23 29 ±1.1
565 ±39 26 ±1.7

662 ±27 32 ±1.3
604 ±35 26 ±1.4
533 ±41 22 ±1.7

568 ±52 26 ±2.1
640 ±54 29 ±1.8
613 ±24 28 ±1.3
624 ±44 27 ±1.9

609 ±29 27 ±1.1
608 ±20 28 ±1.2
609 ±24 27 ±1.0

301-3. 500; high >3. 501.
0 All variables except for Region and Urban/rural showed statistically significant differences for both total fluid and plain water
intake by Bonferroni multiple comparison method.
d Northeast = Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York,
Vermont;

Pennsylvania, Rhode Island,

Midwest = Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota,
Wisconsin;
South = Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky,
North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia;

Louisiana, Maryland, Mississippi,

West = Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington,
Wyoming.
N = Number of observations.
Source: Sohn et al., 2001.




Child-Specific Exposure Factors Handbook
September 2008
Page
3-3.

-------
                                             Child-Specific Exposure Factors Handbook

                                            	Chapter 3 - Water Ingestion







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Child-Specific Exposure Factors Handbook

Chapter 3 - Water Ingestion	





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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 3 - Water Ingestion
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      Child-Specific Exposure Factors Handbook
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Chapter 3 - Water Ingestion	


















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Child-Specific Exposure Factors Handbook
September 2008	
Page
 3-35

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 3 - Water Ingestion
Table 3-34. Pool Water Ingestion by Swimmers
Study Group
Children <16 years old
Males <16 years old
Females <16 years old
Adults (> 18 Years)
Men
Women
a Converted from mL/45
Source: Dufour et al., 2006.
Number of Average Water Ingestion Rate
Participants (mL/45-minute interval)
41
20
21
12
4
8
minute interval.

37
45
30
16
22
12


Average Water Ingestion Rate
(mL/hour)a
49
60
43
21
29
16


Page                                        Child-Specific Exposure Factors Handbook
3-36	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
                               TABLE OF CONTENTS
NON-DIETARY INGESTION FACTORS 	
4.1
4.2
4.3













4.4









4.5


4.6
INTRODUCTION 	
RECOMMENDATIONS 	
NON-DIETARY INGESTION - MOUTHING FREQUENCY STUDIES 	
4.3.1 Key Studies of Mouthing Frequency 	
4.3. .1 Zartarian et al.,1997a/Zartarian et al, 1997b/Zartarian et al, 1998 . . .
4.3. .2 Reed et al., 1999 	
4.3. .3 Freeman et al., 2001 	
4.3. .4 Tulve et al., 2002 	
4.3. .5 Black et al., 2005 	
4.3. .6 Xue et al., 2007 	
4.3.2 Relevant Studies of Mouthing Frequency 	
4.3.2.1 Davis etal., 1995 	
4.3.2.2 Lew and Butterworth, 1997 	
4.3.2.3 Tudella et al., 2000 	
4.3.2.4 AuYeung et al., 2004 	
4.3.2.5 Ko et al., 2007 	
NON-DIETARY INGESTION - MOUTHING DURATION STUDIES 	
4.4. 1 Key Mouthing Duration Studies 	
4.4.1.1 Juberg et al., 2001 	
4.4.1.2 Greene, 2002 	
4.4.2 Relevant Mouthing Duration Studies 	
4.4.2.1 Barr et al., 1994 	
4.4.2.2 Zartarian et al., 1997a/Zartarian et al., 1997b/Zartarianet al., 1998 . .
4.4.2.3 Groot et al., 1998 	
4424 Smith and Norris 2003/Norris and Smith 2002
4425 Au Yeung et al 2004
MOUTHING PREVALENCE
451 Stanek et al 1998
452 Warren et al 2000
REFERENCES FOR CHAPTER 4 	
. ... 4-1
. ... 4-1
. ... 4-2
. ... 4-5
. ... 4-5
. ... 4-5
. ... 4-5
. ... 4-6
. ... 4-7
. ... 4-7
. ... 4-8
. ... 4-8
. ... 4-8
. ... 4-9
. . . 4-10
. . . 4-10
. . . 4-11
. . . 4-12
. . . 4-12
. . . 4-12
. . . 4-12
. . . 4-13
. . . 4-13
. . . 4-14
. . . 4-15
4-15
4-16
4-17
4-17
4-18
4-18
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                                                        Chapter 4 - Non-dietary Ingestion Factors
                                          LIST OF TABLES

Table 4-1.       Summary of Recommended Values for Mouthing Frequency and Duration  	4-3
Table 4-2.       Confidence in Recommendations for Mouthing Frequency and Duration	4-4
Table 4-3.       New Jersey Children's Mouthing Frequency (contacts/hour) from Video-transcription	4-21
Table 4-4.       Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age	4-21
Table 4-5.       Video-transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
                (contacts/hour)	4-21
Table 4-6.       Variability in Objects Mouthed by Washington State Children (contacts/hour)	4-22
Table 4-7.       Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD)	4-23
Table 4-8.       Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
                Studies	4-23
Table 4-9.       Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various
                Studies	4-23
Table 4-10.      Survey Reported Mouthing Behaviors for 92 Washington State Children	4-24
Table 4-11.      Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children
                with >15 minutes in View Indoors	4-24
Table 4-12.      Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children .... 4-25
Table 4-13.      Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
                Other Objects	4-26
Table 4-14.      Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category
                and Child's Age  	4-26
Table 4-15.      Estimates of Mouthing Time for Various Objects (minutes/hour)	4-27
Table 4-16.      Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without
                Pacifier, in Minutes per Day	4-29
Table 4-17.      Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys,
                and Other Objects (hours:minutes:seconds)  	4-30
Table 4-18.      Outdoor Median Mouthing Duration (Seconds per contact), Video-transcription
                of 38 Children	4-31
Table 4-19.      Indoor Mouthing Duration (Minutes per hour), Video-transcription of 9 Children
                with >15 minutes in View Indoors	
Table 4-20.      Outdoor Mouthing Duration (Minutes per hour), Video-transcription of 38 Children . .
Table 4-21.      Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion
                Behaviors	
                                           4-31
                                           4-32

                                           4-33
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Chapter 4 - Non-dietary Ingestion Factors
4       NON-DIETARY INGESTION FACTORS
4.1     INTRODUCTION
        Young  children  have  the  potential for
exposure to  toxic substances through  non-dietary
ingestion pathways other than soil and dust ingestion
(e.g.,  ingesting  pesticide  residues  that have  been
transferred from treated surfaces  to  the  hands or
objects that are  mouthed).   Young children mouth
objects  or  their  fingers  as they  explore  their
environment.    Mouthing  behavior  includes  all
activities in  which objects, including fingers, are
touched by the mouth or put into the mouth except for
eating and drinking, and includes licking,  sucking,
chewing, and biting (Groot et al., 1998).  Videotaped
observations   of  children's  mouthing  behavior
demonstrate the intermittent nature of hand to mouth
and object to mouth behaviors in terms of the number
of contacts recorded per unit of time (e.g., Ko et al.,
2007).
        In a large non-random  sample of children
born in Iowa, non-nutritive  sucking behaviors  were
reported by parents to be very common in infancy, and
to continue for a  substantial proportion of children up
to the third and fourth birthdays (Warren et al., 2000).
Hand to mouth behavior has been observed in both pre-
term and full term infants (Rochat et al., 1988, Blass
et al., 1989, Takaya et al., 2003).   Infants are born
with a sucking reflex for breast feeding, and within a
few months, they begin to use sucking or mouthing as
a means to explore their surroundings. Sucking also
becomes a means of comfort when a child is tired or
upset.    In  addition,  teething   normally  causes
substantial   mouthing  behavior   (i.e., sucking  or
chewing) to alleviate discomfort in the gums (Groot et
al., 1998).    Children's  mouthing  behavior  can
potentially  result in ingestion of toxic  substances
(Lepow et al., 1975).
        There are three general approaches to gather
data on children's mouthing behavior: real-time hand
recording, in which trained observers manually record
information  (e.g.,  Davis   et  al.,  1995);  video-
transcription, in  which trained videographers tape a
child's activities and subsequently extract the pertinent
data manually or with computer software (e.g., Black
et al., 2005); and questionnaire, or survey response,
techniques (e.g.,  Stanek et al., 1998). With real-time
hand  recording,  observations  made  by  trained
professionals (rather  than parents)  may  offer the
advantage  of consistency in  interpreting  visible
behaviors and may be less subjective than observations
made by someone who maintains  a care  giving
relationship to the child. On the other hand, young
children's behavior may be influenced by the presence
of unfamiliar people (e.g., Davis et al., 1995). Groot
et al. (1998) indicated that parent observers perceived
that deviating from their usual care giving behavior by
observing and recording mouthing behavior appeared
to have  influenced the children's behavior.   With
video-transcription methodology,  an assumption  is
made that the presence of the videographer or camera
does not influence  the  child's behavior.    This
assumption may result in minimal biases introduced
when filming newborns, or when the camera and
videographer are not visible to the child.  However, if
the children being studied are older than newborns and
can see the camera or videographer, biases  may be
introduced.    Ferguson  et  al.  (2006)  described
apprehension caused by videotaping and  described
situations where a child's awareness of the videotaping
crew  caused  "play-acting"  to  occur,  or  parents
indicated that the  child  was behaving differently
during the taping session. Another possible source  of
measurement error may be introduced when children's
movements or positions cause their mouthing not to be
captured by the camera. Data transcription errors can
bias results in either the negative or positive direction.
Finally, measurement error can occur if situations arise
in which care givers are absent during videotaping and
researchers must stop videotaping and intervene  to
prevent  risky behaviors (Zartarian  et  al.,  1995).
Survey response studies rely on responses to questions
about a child's mouthing behavior posed to parents  or
care givers.  Measurement errors from these studies
could  occur for a number  of  different reasons,
including  language/dialect  differences  between
interviewers  and respondents,  question wording
problems and lack of definitions  for terms used  in
questions, differences in respondents' interpretation of
questions, and recall/memory effects.
         Some researchers express mouthing behavior
as the frequency of occurrence (e.g., contacts per hour
or contacts per minute). Others describe the duration
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                                                       Child-Specific Exposure Factors Handbook

                                                        Chapter 4 - Non-dietary Ingestion Factors
of specific mouthing events, expressed in units of
seconds or minutes.  This handbook does not address
issues related to contaminant transfer from thumbs,
fingers, or objects or surfaces,  into the mouth, and
subsequent ingestion.   The recommendations for
mouthing frequency  and duration  are provided in
Section 4.2, along with a summary of the confidence
ratings for these recommendations. The recommended
values are based on key studies identified by U. S. EPA
for this factor. Although some studies in sections 4.3.1
and 4.4.1 are classified as key, they were not directly
used to provide the recommendations.   They are
included as key because they were used by Xue et al.,
2007 in a meta analysis, which is the primary source of
the recommendations provided  in  this chapter for
hand-to-mouth   frequency.     Following   the
recommendations,  key  and  relevant  studies  on
mouthing frequency (section 4.3) and duration (section
4.4) are summarized and the methodologies used in the
key and relevant studies are  described. Information on
the prevalence of mouthing behavior is presented in
Section 4.5.
 studies.  Xue et al. 2007, provided data for the age
 groups of interest to U. S. EPA and categorized the data
 according  to indoor and  outdoor contacts.   The
 recommendations  for frequency of object-to-mouth
 contact are based  on data from Reed et al., (1999),
 Freeman et al., (2001), Tulve et al., (2002), AuYeung
 et  al.,   (2004),   and   Black  et   al.,   2005.
 Recommendations for duration of object-to-mouth are
 based on data from Juberg et al., (2001) and Greene,
 (2002). Recommendations for hand-to-mouth duration
 are not  provided since  those estimates may not be
 relevant to  environmental  exposures.    Table 4-2
 presents the confidence ratings for the recommended
 values. The overall confidence rating is low for both
 frequency and duration of hand-to-mouth and object-
 to-mouth.
4.2     RECOMMENDATIONS
        The key studies described in Section 4.3 and
Section 4.4 were used to develop recommended values
for mouthing frequency and duration, respectively,
among children.  In several cases,  key studies pre-
dated the recommendations on age  groups in U.S.
EPA's Guidance  on   Selecting  Age Groups for
Monitoring and Assessing Childhood Exposures to
Environmental Contaminants U.S. EPA, 2005), and
were performed on groups of children of varying ages.
For cases in which age groups of children in the key
studies did not correspond exactly  to U.S. EPA's
recommended age groups, the closest age group was
used.
        Table 4-1  shows  recommended mouthing
frequencies, expressed in units of contacts per hour,
between either any part of the hand (including fingers
and thumbs) and the mouth, or between an object or
surface and the mouth.  The recommended hand-to-
mouth frequencies are based on data from Xue et al.
(2007).   Xue et al. (2007) conducted a secondary
analysis of data from several of the studies summarized
in this chapter,  as  well as data from unpublished
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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
                          Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration
     Age Group
                                                   Hand-to-Mouth
Indoor Frequency (contacts/hour)
              Outdoor Frequency (contacts/hour)
                                                                                                         Source
                           Mean
                                          95th Percentiile
                                                                 Mean
                                                        95th Percentile
  Birth to <1 month
  1 to <3 months
  3 to <6 months
  6 to < 12 months
  1 to <2 years
  2 to <3 years
  3 to <6 years
  6 to <11 years
  11 to <16 years
  16 to <21 years
    28
    19
    20
    13
    15
     7
65
52
63
37
54
21
15
14
5
9
3
47
42
20
36
12
Xue et al., 2007
                                                  Object-to-mouth
                         Mean Frequency (contacts/hour)
                                  95th Percentile Frequency (contacts/hour)
  Birth to <1 month
  1 to <3 months
  3 to <6 months
  6 to < 12 months
  1 to <2 years
  2 to <3 years
  3 to <6 years
  6 to <11 years
  11 to <16 years
  16to<21 years
            20"
            20b
            10°
            10C
             1"
                                                 Reed et al., 1999; Freeman et
                                                 al., 2001; Tulve etal., 2002;
                                                  AuYeung et al., 2004; and
                                                      Black etal., 2005.
                         Mean Duration (minutes/hour)
                                   95th Percentile Duration (minutes/hour)
  Birth to <1 month
  1 to <3 months
  3 to <6 months
  6 to < 12 months
  1 to <2 years
  2 to <3 years
  3 to <6 years
  6 to <11 years
  11 to <16 years
  16to<21 years
             8
            138
                           26f
                           26f
                           22
                           16s
                                Juberg etal., 2001 and
                                    Greene, 2002.
           Mean calculated from Black et al., 2005 (7 to 12 months).
           Mean calculated from Tulve et al., 2002 (• 24 months), AuYeung et al., 2004 (• 24 months), and Black et al., 2005 (1 and 2 years).
           Mean calculated from Reed et al., 1999 (2 to 6 years), Freeman et al., 2001 (3 to 4 years and 5 to 6 years), AuYeung et al., 2004 (2 to
           6 years), and Black et al., 2005 (37 to 53 months).
           Mean calculated from Freeman et al., 2001 (7 to 8 years and lOto 12years).
           Mean calculated from Juberg et al., 2001 (0 to 18 months) and Greene, 2002 (3 to  12 months).
           Calculated 95th percentile from Greene, 2002 (3 to 12 months).
           Mean calculated from Juberg, et al., 2001 (19 to 36 months) and Greene, 2002 (24 to 36 months).
           Calculated 95th percentile from Greene, 2002 (24 to 36 months).
           = No data.
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r JB Child-Specific Exposure Factors Handbool
\A
tZ^B Chapter 4 - Non-dietary Ingestion Factor.

Table 4-2. Confidence in Recommendations for Mouthing Frequency and Duration
General Assessment Factors Rationale Rating
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertinty
Variability in Population
Description of Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of
Studies
Overall rating
Low
The approaches for data collection and analysis used were adequate to provide
estimates of children's mouthing frequencies and durations. Sample sizes were
very small relative to the population of interest. Almost all key studies
published primary data; in cases where secondary data were used, U. S. EPA
judged the secondary data to be of suitable utility for the purposes for
developing recommendations.
Bias in either direction likely exists in both frequency and duration estimates;
the magnitude of bias is unknown.
Low
Key studies for older children focused on mouthing behavior while the infant
studies were designed to research developmental issues.
Most key studies were of samples of U.S. children, but due to the small sample
sizes and small number of locations under study, the study subjects may not be
representative of the overall U.S. child population.
The studies were conducted over a wide range of dates. However, the currency
of the data are not expected to affect mouthing behavior recommendations.
Extremely short data collection periods may not represent behaviors over longer
time periods.
Low
The journal articles are in the public domain, but in many cases, primary data
were unavailable.
Data collection methodologies were capable of providing results that were
reproducible within a certain range, when compared with results obtained using
alternate data collection techniques (e.g., Smith and Norris, 2003).
Several of the key studies applied and documented quality assurance/quality
control measures.
Low
The key studies characterized inter- individual variability to a limited extent,
and did not characterize intra-individual variability over diurnal or longer term
time frames.
The study authors typically did not attempt to quantify uncertainties inherent in
data collection methodology (such as the influence of observers on behavior),
although some described these uncertainties qualitatively. The study authors
typically did attempt to quantify uncertainties in data analysis methodoloogies
(if video-transcription methods were used). Uncertainties arising from short
data collection periods typically were unaddressed either qualitatively or
quantitatively.
Medium
All key studies appear in peer review journals.
Several key studies were available for both frequency and duration, but data
were not available for all age groups. The results of studies from different
researchers are generally in agreement.
Low

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
4.3     NON-DIETARY   INGESTION
        MOUTHING FREQUENCY STUDIES
4.3.1    Key Studies of Mouthing Frequency
4.3.1.1  Zartarian  et  al.,1997a  -  Quantifying
        Videotaped  Activity   Patterns:  Video
        Translation   Software  and   Training
        Technologies/Zartarian  et al.,  1997b  -
        Quantified Dermal Activity Data  From a
        Four-Child Pilot Field Study/Zartarian et
        al., 1998 - Quantified Mouthing Activity
        Data From a Four-Child Pilot Field Study
        Zartarian et  al.  (1991 a,   1997b,  1998)
conducted  a  pilot study  of the video-transcription
methodology to investigate the applicability of using
videotaping for  gathering  information  related to
children's activities, dermal exposures and mouthing
behaviors.  The researchers had conducted studies
using the  real-time  hand recording  methodology,
resulting in poor inter-observer reliability and observer
fatigue when attempted  for long periods  of time,
prompting  the  investigation into using videotaping
with transcription of the children's activities at a point
in time after the observations (videotaping) occurred.

        Four  Mexican-American   farm   worker
children in the Salinas Valley of California each were
videotaped with a hand-held videocamera during their
waking hours, excluding time spent in the bathroom,
over one day in September 1993. The boys were 2
years 10 months old and 3 years, 9  months old; the
girls were 2 years 5 months old and 4 years 2 months
old.   Time of videotaping  was 6.0 hours  for the
younger girl, 6.6 hours for the older girl, 8.4 hours for
the younger boy and 10.1 hours for the older boy.  The
videotaping gathered information on detailed micro-
activity patterns of children to  be used to evaluate
software  for  videotaped  activities  and  translation
training methods. The researchers reported measures
taken to assess inter-observer reliability and several
problems with the video-transcription process.
        The  hourly  data showed that non-dietary
object mouthing occurred in 30 of the 31 hours of tape
time, with one child eating during the hour in which
no non-dietary object  mouthing occurred.  Average
object to mouth contacts  for the four children were
reported to be 9 contacts per hour, with the average per
child ranging from 1 to 19 contacts per hour (Zartarian
et  al.,  1997a).     Objects   mouthed  included
bedding/towels, clothes, dirt, grass/vegetation, hard
surfaces, hard toys, paper/card, plush toy, and skin
(Zartarian et al., 1997a).   Average hand to mouth
contacts for the four children were reported to be 13
contacts per hour (averaging the sum of left hand and
right hand to  mouth contacts and averaging across
children, from Zartarian  et  al.,  1997b),  with the
average per child ranging from 9 to 19 contacts per
hour.
        This study's primary purpose was to develop
and evaluate the video-transcription methodology; a
secondary purpose was  collection  of mouthing
behavior data.  The sample of children studied was
very small and not likely to be representative of the
national population. As with other video-transcription
studies,  the   presence  of  non-family-member
videographers  and  a  video  camera  may  have
influenced the children's behavior.

4.3.1.2  Reed  et  al.,   1999 -  Quantification  of
        Children's Hand and Mouthing Activities
        Through a Videotaping Methodology
        In this study, Reed et al. (1999) used a video-
transcription methodology to quantify the frequency
and type of children's hand and mouth contacts, as
well as a survey response methodology, and compared
the videotaped behaviors with parents' perceptions of
those behaviors. Twenty children ages 3 to 6 years old
selected  randomly at a day care  center in  New
Brunswick, New Jersey,  and ten children ages 2 to 5
years old at residences in Newark and Jersey City, New
Jersey who were not selected randomly, were studied
(gender not  specified).  For the video-transcription
methodology,  inter-observer  reliability  tests  were
performed during observer training and at four points
during the two years of the study.   The researchers
compared the results of videotaping the ten children in
the residences with  their  parents'  reports of the
children's daily activities. Mouthing behaviors studied
included hand to mouth and hand bringing object to
mouth.
        The  video-transcription mouthing  contact
frequency results are presented in Table 4-3.   The
authors analyzed parents' responses on frequencies of
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                                                          Chapter 4 - Non-dietary Ingestion Factors
their children's mouthing behaviors and compared
those  responses  with  the  children's  videotaped
behaviors, which  revealed  certain discrepancies.
Parents' reported hand to mouth contact of "almost
never"  corresponded to  overall somewhat  lower
videotaped hand to mouth frequencies than those of
children whose parents reported "sometimes," but
there was  little  correspondence  between parents'
reports of object to mouth frequency and videotaped
behavior.
        The advantages of  this study were that  it
compared the results of video-transcription with the
survey response methodology results,  and described
quality assurance steps taken to assure reliability of
transcribed videotape data.  However, only a small
number of children  were studied,  some were not
selected for observation randomly, and the sample of
children studied may not be representative of either the
locations studied or the national population.  Due to
the children's ages, the presence of unfamiliar persons
following the children  with a video camera may
influence the video-transcription results. The parents'
survey  responses may  also  be  influenced  by
recall/memory effects and other limitations of survey
methodologies.

4.3.1.3  Freeman et al., 2001 - Quantitative Analysis
        of Children's Microactivity Patterns: The
        Minnesota  Children's Pesticide Exposure
        Study
        Freeman et  al.  (2001) conducted a survey
response and video-transcription study of some of the
respondents  in a phased study of children's pesticide
exposures in the summer and early  fall of 1997.  A
probability-based sample of 168 families with children
ages 3 to < 14 years old in urban (Minneapolis/St. Paul)
and non-urban (Rice  and Goodhue Counties) areas of
Minnesota   answered  questions  about  children's
mouthing of paint chips, food-eating without utensils,
eating of food dropped on the floor, mouthing of non-
food items, and mouthing of  thumbs/fingers.  For the
survey response portion of the study, parents provided
the responses for children ages 3 and 4 years, and
collaborated with or assisted older children with their
responses.   Of the  168 families responding to the
survey,  102  were available,  selected, and agreed to
 measurements of pesticide exposure.   Of these  102
 families, 19  agreed to  videotaping  of the study
 children's activities for a period of four consecutive
 hours.
         Based  on  the  survey responses for  168
 children, the 3  year olds  had  significantly more
 positive responses for all reported behavior compared
 to the other age groups.  The authors stated that they
 did not know whether parent reporting of 3 year olds'
 behavior influenced the responses given.  Table 4-4
 shows the percent of children, grouped by age, who
 were reported to exhibit non-food related mouthing
 behaviors. Table 4-5 presents the mean and median
 number of mouthing contacts  by  age  for  the  19
 videotaped children. Among the four age categories of
 these  children,  object  to  mouth  activities were
 significantly greater for the 3 and 4 year olds than any
 other age group, with a median of 3 and a mean of 6
 contacts per hour  (P =  0.002,  Kruskal Wallis  test
 comparison across four age  groups). Hand to mouth
 contacts had a median of 3.5 and mean of 4 contacts
 per hour for the three 3  and 4 year olds observed,
 median of 2.5 and mean of 8 contacts per hour for the
 seven 5 and 6 year olds observed, median of 3  and
 mean of 5 contacts per hour for the four 7 and 8 year
 olds observed, and median of 2 and mean of 4 for the
 five  10,  11  and 12 year olds observed.  Gender
 differences were observed for some of the activities,
 with boys spending  significantly more time outdoors
 than girls.   Hand  to mouth and  object to mouth
 activities were less frequent  outdoors than indoors for
 both boys and girls.
         For the 19 children  in the video-transcription
 portion of the study, inter-observer reliability checks
 and  quality  control  checks  were  performed  on
 randomly sampled tapes.  For four children's tapes,
 comparison of the manual video-transcription with a
 computerized transcription method (Zartarian et al.,
 1995) was also performed; no significant differences
 were found in the frequency of events recorded using
 the two techniques. The frequency of six behaviors
 (hand to mouth, hand to object, object to mouth, hand
 to smooth surface, hand to textured surface, and hand
 to clothing) was recorded. The amount of time each
 child spent indoors, outdoors, in contact with soil or
 grass, and whether  the child  was barefoot was also
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recorded.  For the four children whose tapes were
analyzed with the computerized transcription method,
which calculates event durations, the authors stated
that most hand to mouth and object to mouth activities
were  observed  during  periods of lower physical
activity, such as television viewing.
        An advantage to this study is that it included
results from two separate methodologies, and included
quality assurance  steps taken to assure reliability of
transcribed videotape data. However, the children in
this study may not be representative of all children in
the U.S.   Variation in who provided  the  survey
responses (sometimes parents only, sometimes children
with parents) may have influenced the responses given.
Children  studied  using   the  video-transcription
methodology  were not  chosen  randomly from  the
survey response group.  The presence  of unfamiliar
persons following the children with a  video camera
may  have   influenced  the   video-transcription
methodology results.

4.3.1.4  Tulve et al., 2002 - Frequency of Mouthing
        Behavior in Young Children
        Tulve et  al. (2002) coded the unpublished
Davis et al. (1995)  data  for location (indoor and
outdoor) and  activity  type  (quiet or active)  and
analyzed the subset of the data that consisted of indoor
mouthing behavior during quiet activity (72 children,
ranging in age from 11  to 60 months).  A total of 186
15-minute observation  periods were included in the
study, with the number of observation periods per child
ranging from 1 to  6.
        Results of the data analyses indicated that
there was no association between mouthing frequency
and gender, but a clear association between mouthing
frequency  and  age was observed.    The analysis
indicated that children • 24 months had  the highest
frequency of mouthing behavior (81 events/hour) and
children >24 months had the lowest (42 events/hour)
(Table 4-6). Both  groups of children were observed to
mouth toys and hands more frequently than household
surfaces or body parts other than hands.
        An advantage of this  study is  that  the
randomized design may mean that the children studied
were relatively representative of young children living
in the  study area, although  they  may  not be
representative of the U.S. population. Due to the ages
of  the  children  studied,  the observers'  use  of
headphones and  manual  recording  of mouthing
behavior on observation sheets may have influenced
the children's behavior.

4.3.1.5  Black et al., 2005 - Children's Mouthing
        and  Food-Handling  Behavior  in  an
        Agricultural Community on the U.S./Mexico
        Border
        Black et al. (2005) studied mouthing behavior
of children in a Mexican-American community along
the Rio Grande River in Texas, in the spring and
summer of 2000, using a survey response and a video-
transcription methodology. A companion study of this
community  (Shalat  et  al., 2003) identified 870
occupied households  during  the  April 2000  U.S.
census and contacted 643 of these via in-person
interview to determine presence of children under the
age of 3 years. Of the 643 contacted, 91  had at least
one child under the age of 3 years (Shalat et al., 2003).
Of  these 91 households,  the  mouthing and  food-
handling behavior of 52 children  (26 boys and 26
girls) from 29  homes was  videotaped,  and  the
children's parents answered questions about children's
hygiene, mouthing and food-handling activities (Black
et al., 2005). The study was of children ages 7 to 53
months, grouped into four age categories: infants (7 to
12 months), 1 year olds (13 to 24 months), 2 year olds
(25 to 36 months),  and preschoolers (37 to 53 months).
        The survey asked questions about children's
ages, genders, reported hand-washing, mouthing and
food-handling behavior (N=52), and activities (N=49).
Parental  reports of thumb/finger  placement  in the
mouth showed decreases with age.  The researchers
attempted to videotape each child for four hours. The
children were followed by the videographers through
the house and yard, except for times when they were
napping  or using the bathroom.   Virtual  Timing
Device™ software was used to analyze the videotapes.
         Based on the results  of  videotaping,  most
of the children (49 of 52) spent the majority of their
time indoors. Of  the 39 children who  spent  time
both indoors and  outdoors, all three behaviors (hand
to mouth, object to mouth and food handling) were more
frequent and longer while the child was indoors. Hand
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to mouth activity was recorded during videotaping for
all but one child, a 30 month old girl.
        For the four age groups, the mean hourly
hand to mouth frequency ranged from 11.9 (2 year
olds) to  22.1  (preschoolers), and the mean hourly
object to mouth frequency ranged from 7.8 (2 year
olds) to 24.4 (infants).  No significant linear trends
were seen with age or gender for hand to mouth hourly
frequency. A significant linear trend was observed for
hourly object to mouth frequency, which decreased as
age  increased (adjusted R2  = 0.179; P  = 0.003).
Results of this study are shown in Table 4-7.
        One  advantage  of this study   is that  it
compared   survey   responses  with  videotaped
information on mouthing behavior.  A limitation is
that  the  sample was fairly  small and was from  a
limited area (mid-Rio Grande Valley) and is not likely
to be representative of the national population. Due to
the children's ages, the presence of unfamiliar persons
following the children with a video camera may have
influenced the video-transcription methodology results.

4.3.1.6  Xue  et  al, 2007  - A Meta-analysis of
        Children 'sHand-to-Mouth Frequency Data
       for   Estimating  Nondietary   Ingestion
        Exposure
        Xue et  al.  (2007) gathered hand-to-mouth
frequency data from 9 available studies representing
429  subjects and more than 2,000 hours of behavior
observation. The studies used in this analysis included
several of the studies  summarized  in this chapter
(Zartarian et al. ,1998; Reed et al., 1999; Freeman et
al., 2001; Greene, 2002; Tulve et al.,  2002; and Black
et al., 2005), as  well  as  several other sets of
unpublished data. These data were used to conduct a
meta-analysis to study differences in hand-to-mouth
behavior. The purpose of the analysis was to:
 1)      examine differences across studies by age
        (using the new U.S.  EPA recommended age
        groupings (U.S.  EPA, 2005)), gender,  and
        indoor/outdoor location;
2)      fit variability distributions  to the available
        hand-to-mouth frequency data for use in one
        dimensional  Monte   Carlo   exposure
        assessments;
3)      fit uncertainty  distributions to the available
         hand-to-mouth frequency data for use in two
         dimensional  Monte   Carlo   exposure
         assessments; and
 4)      assess hand-to-mouth frequency data  needs
         using the new U.S. EPA recommended age
         groupings (U.S. EPA, 2005).
         The  data were sorted  into age groupings.
 Visual inspection of the data and statistical methods
 (method  of  moments and  maximum  likelihood
 estimation) were used, and goodness-of-fit tests were
 applied to  verify the selection  among  lognormal,
 Weibull, and normal distributions (Xue et al., 2007).
 Analyses  to  study  inter-  and  intra-   individual
 variability  of indoor  and outdoor hand to mouth
 frequency were conducted. There were 894 hours of
 behavior observation data for the 429 children, ages
 0.3 to  12 years,  across all available studies.  It was
 found that age and location (indoor vs.  outdoor) were
 important factors contributing  to hand  to  mouth
 frequency, but study and gender were not (Xue et al.,
 2007). Distributions of hand to mouth frequencies
 were developed for both indoor and outdoor activities.
 Distributions  are presented in Table 4-8 for indoor
 settings and Table 4-9 for outdoor settings. Hand to
 mouth frequencies  decreased for both indoor and
 outdoor activity  as age increased, and were higher
 indoors than outdoors  for all age groups (Xue  et al.,
 2007).
         A  strength of this study is that it is the first
 effort to fit hand to mouth distributions using U.S.
 EPA's recommended age groups using  available data
 on mouthing behavior from studies using different
 methodologies,  of children  in  different locations.
 Limitations of the studies used in this  meta-analysis
 apply to the results from the meta-analysis as well; the
 uncertainty analysis in this study does not account for
 uncertainties arising out of differences  in approaches
 used in the various studies used in the meta-analysis.
 4.3.2    Relevant Studies of Mouthing Frequency
 4.3.2.1  Davis  et  al.,  1995 - Soil Ingestion  in
         Children with Pica: Final Report
         In 1992, under a Cooperative Agreement with
 U.S. EPA, the Fred Hutchinson  Cancer  Research
 Center conducted a survey response and real-time hand
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recording study of mouthing behavior data. The study
included 92 children (46 males, 46 females) ranging in
age from <12 months to 60 months, from Richland,
Kennewick, and Pasco, Washington.  The  children
were selected randomly based on date of birth through
a combination of birth certificate records and random
digit dialing of residential telephone numbers.  For
each child, data were collected during a seven day
period in January to April, 1992.  Eligibility  included
residence within the city limits, residence duration >1
month, and at least one parent or guardian who spoke
English.  Most of the  adults  who responded to the
survey reported their marital status as being married
(90 percent), their race as Caucasian (89 percent), their
household income in the >$30,000 range (56 percent)
or  their  housing  status  as single-family  home
occupants (69 percent).
        The survey  asked  questions about thumb-
sucking and frequency questions about pacifier use,
placing  fingers, hands and feet  in the mouth,  and
mouthing of furniture, railings, window sills, floor,
dirt, sand, grass, rocks, mud, clothes, toys,  crayons,
pens, and other items.  Table  4-10 shows the survey
responses for the 92 study children.  For most of the
children in the study, the mouthing behavior real-time
hand recording data were collected simultaneously by
parents and by trained observers who described and
quantified the mouthing behavior of the children in
their  home  environment.  The  observers  recorded
mouth and tongue contacts with hands, other body
parts, natural objects,  surfaces,  and toys  every  15
seconds during 15-minute observation periods spread
over 4  days. Parents  and trained  observers  wore
headphones that indicated elapsed time (Davis et al.,
1995).  If all attempted observation periods were
successful,  each child would  have a total  of 16  15-
minute observation periods with 6015 -second intervals
per 15-minute observation period, or 960 15-second
intervals in all.  The number of successful intervals of
observation  ranged  from  0 to  840  per  child.
Comparisons of the inter-observer reliability between
the trained observers and parents showed  "a high
degree of correlation between the overall degree of
both mouth and tongue activity recorded by parents
and observers. For total mouth activity,  there was a
significant correlation between the rankings  obtained
according to parents and observers, and parents were
able to identify the same individuals as observers as
being most and least oral in 60 percent of the cases."
        One  advantage  of  this  study  is  the
simultaneous observations by both parents and trained
observers  that allows  comparisons  to be  made
regarding the consistency of the recorded observations.
The random nature  in which  the population  was
selected may provide a representative population of the
study area, within certain limitations, but not of the
national population. Simultaneous collection of food,
medication, fecal, and urine samples that occurred as
part of the overall  study (not described in  this
summary) may have contributed a degree of deviation
from normal routines within the households during the
7 days of data collection and may have influenced
children's usual behaviors.  Wearing of headphones by
parents  and  trained  observers during mouthing
observations,   presence   of   non-family-member
observers, and parents' roles as  observers as well as
care givers may also have influenced the results; the
authors state "Having the child  play naturally while
being observed was challenging.  Usually the first day
of observation was the  most difficult in this respect,
and by the third or fourth day of observation the child
generally paid little attention to the  observers."

4.3.2.2  Lew   and  Butterworth,   1997  -   The
        Development of Hand-Mouth Coordination
        In 2-  to 5-Month-Old Infants:  Similarities
        With Reaching and Grasping
        Lew  and  Butterworth (1997)  studied 14
mostly first-born  infants (10 males,  4  females) in
Stirling, United Kingdom, in 1990 using a video-
transcription methodology.  Attempts were made to
study each infant within a week of the infant's 2-
month, 3-month,  4-month and 5-month birthdays.
After becoming accustomed to the testing laboratory,
and with their mothers present, infants were placed in
semi-reclining  seats   and  filmed  during   an
experimental protocol  in which researchers placed
various objects into the infants'  hands.  Infants were
observed for two baseline periods of 2 minutes each.
The researchers coded all contacts to the face  and
mouth that occurred during baseline periods (prior to
and after the  object handling  period)  as well as
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contacts occurring during the object handling period.
Hand to mouth contacts included contacts that landed
directly in or on the mouth as well as those in which
the hand landed on the face first and then moved to the
mouth.    The  researchers  assessed inter-observer
agreement using a rater not involved with the study,
for a random proportion (approximately 10 percent) of
the movements documented during the object handling
period, and reported inter-observer agreement of 0.90
using Cohen's  kappa (a  measure of the agreement
between two raters) for the location of contacts.  The
frequency of contacts ranged between 0 and 1 contacts
per minute.
        The advantages of this study were that use of
video cameras  could be  expected to have minimal
impact on infant behavior for infants of these ages, and
the  researchers performed tests of inter-observer
reliability.  A disadvantage is that the study included
baseline  observation  periods of only 2  minutes'
duration, during which spontaneous hand  to mouth
movements could be observed.  The extent to which
these infants'  behavior  is  representative  of other
infants of these  ages is unknown.

4.3.2.3  Tudella et  al., 2000 - The Effect of Oral-
        Gustatory,   Tactile-Bucal,  and   Tactile-
        Manual Stimulation on the Behavior of the
        Hands in Newborns
        Tudella et al. (2000) studied the frequency of
hand to mouth contact, as well as other behaviors, in
24 full-term Brazilian newborns  (10 to  14  days old)
using a video-transcription methodology. Infants were
in an alert state, in their homes in silent and previously
heated rooms in a supine position and had been fed
between 1 and 1 1/2 hours before testing. Infants were
studied for a four minute baseline period without
stimuli before experimental stimuli were administered.
Results from the four minute baseline period, without
stimuli, indicated that the mean frequency of hand to
mouth contact  (defined as right hand  or  left hand
touching the lips or entering the buccal cavity, either
with or without  rhythmic jaw movements) was almost
3 right hand contacts and slightly more than 1.5 left
hand contacts,  for  a  total  hand to mouth contact
frequency of about  4 contacts in  the  four minute
period.   The researchers performed inter-observer
 reliability tests on the videotape data and reported an
 inter-coder Index of Concordance of 93 percent.
         The advantages of this study were that use of
 video cameras could be expected to have virtually no
 impact on newborns' behavior,  and inter-observer
 reliability tests were performed.  However, the study
 data may not represent newborn hand to mouth contact
 during non-alert periods such as sleep. The extent to
 which these infants' behavior is representative of other
 full-term  10  to  14  day old infants'  behavior is
 unknown.

 4.3.2.4  AuYeung et al,  2004 - Young Children's
         Mouthing  Behavior:  An  Observational
         Study  via   Videotaping  in  a Primarily
         Outdoor Residential Setting
         AuYeung et  al.  (2004)  used  a video-
 transcription  methodology to study a group  of 38
 children (20 females and 18 males; ages 1 to 6 years),
 37 of whom were selected randomly via a telephone
 screening survey of a 300 to 400 square mile portion of
 the San Francisco, California peninsula, along with
 one  child selected by convenience  due   to time
 constraints. Families who lived in a residence with a
 lawn and whose annual income was >$35,000 were
 asked to participate. Videotaping took place between
 August 1998  and May 1999 for  approximately  two
 hours per child. Videotaping by one researcher was
 supplemented with  field  notes  taken by a second
 researcher who was also present during taping. Most
 of the  videotaping took place during outdoor play,
 however, data were included for several children (one
 child <2 years old and 8 children >2 years old) who
 had more than 15 minutes of indoor play during their
 videotaping sessions.
         The  videotapes were translated into ASCII
 computer files using VirtualTimingDevice™  software
 described in Zartarian et al. (1997a). Both frequency
 and duration (see Section 4.4.2.5 of this Chapter) were
 analyzed.  Between 5 and 10 percent of the data files
 translated were randomly chosen for quality control
 checks for inter-observer agreement. Ferguson et al.
 (2006) described quality control aspects of the study in
 detail.
         For   analysis, the mouthing contacts were
 divided into  indoor and  outdoor locations, and 16
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object/surface categories.  Mouthing frequency was
analyzed by age  and  gender separately, and  in
combination.  Mouthing contacts were defined as
contact with the lips, inside of the mouth, and/or the
tongue;  dietary contacts were ignored.   Mouthing
frequencies for indoor locations are shown in Table 4-
11.  For the one child observed that was • 24 months of
age,  the   total   mouthing   frequency  was  84.8
contacts/hour;  for children >24 months,  the median
indoor mouthing frequency was 19.5 contacts/hour.
Outdoor median mouthing frequencies (Table 4-12)
were very similar for children • 24 months of age (13.9
contacts/hour) and >24 months (14.6 contacts/hour).
        Nonparametric  tests, such as the Wilcoxon
rank sum test were used for the data analyses. Both age
and gender were  found  to be  associated  with
differences  in  mouthing  behavior.    Girls had
significantly higher frequencies of mouthing contacts
with the hands and non-dietary objects than boys (p =
0.01 and;? = 0.008, respectively).
        This study provides distributions of outdoor
mouthing  frequencies with a variety of  objects and
surfaces.  Although indoor mouthing data were also
included in this  study, the results were  based on a
small number of children (N=9) and a limited amount
of indoor  play.   The  sample of children may  be
representative of certain socioeconomic strata in the
study area, but is not likely to be representative of the
national population.  Due to the children's ages, the
presence of unfamiliar persons following the children
with a video camera may have influenced the video-
transcription methodology results.

4.3.2.5  Ko et al, 2007 -  Relationships  of Video
       Assessments  of Touching and Mouthing
       Behaviors During Outdoor Play in Urban
        Residential Yards to Parental Perceptions of
        Child Behaviors and Blood Lead Levels
        Ko et al. (2007) compared parent survey
responses with results from a video-transcription study
of children's mouthing behavior in outdoor settings, as
part of a study of relationships between children's
mouthing behavior and other variables with blood lead
levels. A  convenience sample of 37 children (51
percent males, 49 percent females) 14 to 69 months old
was recruited via an urban health center and direct
contacts  in the  surrounding area,  apparently in
Chicago,  Illinois.    Participating  children  were
primarily Hispanic (89 percent). The mouth area was
defined as within 1 inch of the mouth, including the
lips. Items passing beyond the lips were defined as in
the mouth.  Placement of an object or food item in the
mouth along with part of the hand was counted as both
hand and food or object in mouth. Mouthing behaviors
included hand-to-mouth area both with and not with
food, hand- in-mouth with or without food, and object-
in-mouth including food, drinks, toys or other objects.
        Survey responses for the 37  children who
were also  videotaped included  parents  reporting
children's inserting hand, toys or objects  in mouth
when playing  outside,  and inserting dirt,  stones or
sticks in mouth. Video-transcription results of outdoor
play for these 37 children indicated 0 to 27 hand-in-
mouth, and 3 to 69 object-in-mouth touches per hour
for the 13 children reported to frequently insert hand,
toys or objects in mouth when playing outside; 0 to 67
hand in mouth, and 7 to 40 object-in-mouth touches
per hour for the 10 children reported to "sometimes"
perform this behavior; 0 to 30 hand-in-mouth, and 0 to
125 object in  mouth touches per hour for the  12
children  reported to "hardly  ever"  perform  this
behavior, and 1 to 8 hand-in-mouth, and 3 to 6 object-
in-mouth touches per hour for the 2 children reported
to "never" perform this behavior.
        Videotaping was attempted for two hours per
child  over two  or  more  play  sessions,  with
videographers  trying to avoid interacting with the
children.  Children played with their usual toys and
partners, and no instructions  were given to parents
regarding their supervision of the children's play. The
authors stated that  during  some  portion  of the
videotape time, children's hands and mouths were out
of  camera  view.   Videotape transcription  was
performed manually, according to a modified version
of the protocol used in the Reed et al. (1999)  study.
Inter-observer   reliability  between   three  video-
transcribers was checked with seven 30 minute video
segments.
        One strength of this study is its comparison of
survey  responses  with  results  from  the  video-
transcription methodology.  A limitation is that the
non-randomly  selected sample of children studied is
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unlikely to be representative of the national population.
Comparing results from this study with results from
other video-transcription studies may be problematic
due to inclusion of food handling with hand to mouth
and object to mouth frequency  counts. Due to the
children's ages, their behavior may have differed from
normal patterns due to the presence of strangers who
videotaped them.

4.4     NON-DIETARY    INGESTION
        MOUTHING DURATION STUDIES
4.4.1    Key Mouthing Duration Studies
4.4.1.1  Juberg et al., 2001 - An  Observational Study
        of Object Mouthing Behavior by  Young
        Children
        Juberg et al. (2001) studied 385 children ages
0 to 36 months in western New York state, with
parents collecting real-time hand-recording mouthing
behavior  data,  primarily in children's own  home
environments.  The study consisted of an initial pilot
study conducted in February 1998,  a  second  phase
conducted in April 1998, and a third phase conducted
at an unspecified later time.  The study's sample was
drawn from families identified in a child play research
center database or whose children attended a child care
facility in the  same general area; some geographic
variation within  the  local  area was  obtained  by
selecting families with different zip  codes in the
different  study phases.  The pilot phase had  30
children  who  participated out  of  150  surveys
distributed; the second phase had 187 children out of
approximately 300 surveys distributed, and the third
phase had  168 participants out  of 300 surveys
distributed.
        Parents were asked to observe their child's
mouthing of objects only; hand to mouth behavior was
not included.  Data were collected on a single day
(pilot and second phases) or five days (third phase);
parents recorded the insertion of objects into the mouth
by noting the "time in" and "time out"  and the
researchers summed the recorded data to tabulate total
times spent mouthing the various objects during the
day(s) of observation.  Thus, the  study data were
presented as minutes per day of object mouthing time.
Mouthed items were classified as pacifiers, teethers,
plastic toys, or other objects.
         The results of the combined pilot and second
 phase II data are shown in Table 4-13. For both age
 groups, mouthing time for pacifiers greatly exceeded
 mouthing time for  non-pacifiers, with the difference
 more  acute for  the older age group than for the
 younger age group. Histograms of the observed data
 show a peak in the low end of the distribution (0 to 100
 minutes  per  day)  and  a rapid  decline  at  longer
 durations.
         A third phase of the study focused on children
 between the ages of 3 and  18 months and included
 only non-pacifier objects. Subjects were observed for
 5 non-consecutive days over a 2 month period. A total
 of 168 participants returned surveys for at least one
 day, providing a total of 793 person-days of data. The
 data yielded a  mean non-pacifier  object mouthing
 duration of 36 minutes per day; the mean was the same
 when  calculated on the basis  of 793  person-days  of
 data as on the basis of 168 daily average mouthing
 times.
         One  advantage of this study is the large
 sample size  (385 children); however, the children
 apparently were not selected randomly, although some
 effort  was made to obtain local geographic variation
 among study participants. There is no description of
 the socioeconomic status or racial and ethnic identities
 of the study participants. The authors do not describe
 the methodology (such  as  stopwatches,  analog  or
 digital clocks,  or  guesses)  parents used to  record
 mouthing event durations.  The authors stated that
 using mouthing event duration units of minutes, rather
 than seconds, may have yielded observations rounded
 to the nearest minute.

 4.4.1.2  Greene, 2002  - A Mouthing  Observation
         Study of Children Under Six Years of Age
         The   U.S.  Consumer   Product   Safety
 Commission (CPSC) conducted a survey response and
 real-time hand recording study between  December
 1999 and February 2001 to quantify the cumulative
 time per  day that young children spend awake, not
 eating, and  mouthing  objects.    "Mouthing" was
 defined as sucking, chewing, or otherwise putting an
 object  on  his/her lips  or  into  his/her  mouth.
 Participants were recruited via a random digit dialing
 telephone survey in urban and nearby rural areas of
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Houston, Texas and Chicago, Illinois. Of the 115,289
households surveyed, 1,745 households had a child
under  the  age of 6 years and were  willing  to
participate.   In  the initial  phase of  the study,
491children ages 3 to 81 months participated. Parents
were instructed to use watches with second hands, or
count seconds to estimate mouthing event durations.
Parents also were  to record mouthing frequency and
types  of objects mouthed.  Parents collected data in
four separate, non-consecutive 15- minute observation
periods.  Initially, parents were  called back by the
researchers and asked to provide their data over the
telephone.   Of the 491 children, 43  children (8.8
percent) had at least one 15-minute observation period
with mouthing event durations recorded as exceeding
15 minutes.  Due to this data quality problem,  the
researchers excluded the parent observation data from
further analysis.
        In a second phase, trained observers used
stopwatches to record the mouthing behaviors and
mouthing event durations of the subset of 109 of these
children ages 3 to 36 months, and an  additional 60
children (total in second phase, 169), on two hours of
each of two days.  The observations  were  done at
different times of  the day at the child's home and/or
child care facility.  Table 4-14 shows the prevalence of
observed mouthing among the 169 children in the
second phase. All children were observed to mouth
during the four hours of observation time;  99 percent
mouthed the category defined as "anatomy." Pacifiers
were  mouthed by 27 percent in an  age-declining
pattern ranging from 47 percent of children less than
12 months old to 10 percent of the 2 to  <3  year olds.
        Table 4-15 provides the  average mouthing
time by object category and age in minutes per hour.
The average mouthing time for all objects ranged from
5.3 to  10.5  minutes per hour,  with the  highest
mouthing time corresponding to children  <1 year of
age and the lowest to the 2 to <3 years of age category.
Among the objects mouthed, pacifiers represented
about one third of the total mouthing time, with 3.4
minutes per  hour for  the youngest  children,  2.6
minutes per hour  for the children between  1 and  2
years  and 1.8 minutes per  hour for children 2 to <3
years  old.  The next largest single item category was
anatomy. In this  category, children under 1 year of
age spent 2.4 minutes per hour mouthing fingers and
thumbs; this behavior declined with age to 1.2 minutes
per hour for children 2 to <3 years old.
        Of the 169 children in the second phase, there
were usable data on the time awake and not eating (or
"exposure time") for only 109; data for the remaining
60 children were missing.  Thus, in order to develop
extrapolated estimates of daily mouthing time, from
the 2 hours  of observation per day for two days, for the
109 children, the researchers  developed a statistical
model that  accounted for the children's demographic
characteristics, in order to estimate exposure times for
the 60 children for whom exposure time data were
missing, and   then computed  statistics   for  the
extrapolated daily mouthing times for all 169 children,
using a "bootstrap" procedure.  Using this method, the
estimated mean daily mouthing time of objects other
than pacifiers  ranged from 37  minutes/day  to 70
minutes/day with the lowest number corresponding to
the 2 to <3  year old children and the largest number
corresponding to the 3 to < 12 month old children.
        The 551 child participants were 55 percent
males, 45 percent females.  The study's sample was
drawn in an attempt  to duplicate  the overall U.S.
demographic characteristics  with  respect  to race,
ethnicity,   socioeconomic   status   and
urban/suburban/rural settings.  The sample families'
reported annual incomes were generally higher than
those of the overall U.S.  population.
        This study's strength  was that it consisted of
a randomly selected sample of children from both
urban and non-urban areas in two different geographic
areas  within the  U.S.   However, the observers'
presence and use of a stopwatch to time mouthing
durations may have affected the children's behavior.

4.4.2    Relevant Mouthing Duration Studies
4.4.2.1  Barr et al, 1994  -  Effects of Intra-Oral
        Sucrose on Crying, Mouthing and Hand-
        Mouth Contact in Newborn and Six Week
        Old Infants
        Barr et al. (1994) studied hand to mouth
contact, as well as other  behaviors, in 15 newborn (8
males, 7 females) and 15 five to seven week  old (8
males, 7 females) full-term Canadian infants using a
video-transcription methodology.  The newborns were
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2 to 3 days old, in a quiet, temperature-controlled room
at the hospital, in a supine position and had been fed
between 2 1/2 and 3 1/2 hours before testing. Barr et
al. (1994) analyzed a one minute baseline period, with
no  experimental  stimuli,  immediately  before a
sustained crying episode lasting 15 seconds.  For the
newborns, reported durations of hand to mouth contact
during 10 second intervals of the one minute baseline
period were in the range of 0 to 2 percent. The five to
seven week old infants apparently were studied at
primary care pediatric facilities when they  were in
bassinets inclined at an angle of 10 degrees. For these
slightly older infants, the baseline periods  analyzed
were less than 20 seconds in length, but Barr et al.
(1994) reported similarly low mean percentages of the
10 second intervals (approximately 1  percent of the
time with hand to mouth contact).  Hand to mouth
contact was defined as "any part of the hand touching
the lips  and/or the inside of the  mouth."   The
researchers performed inter-observer reliability tests on
the videotape data and reported a mean inter-observer
reliability of 0.78 by Cohen's kappa (a measure of the
agreement between two raters).
        The advantages of this study were that use of
video cameras could be expected to have virtually no
impact on newborns' or five to seven week old infants'
behavior,  and inter-observer reliability tests were
performed. The study data did not represent newborn
or five to seven week old infant hand to mouth contact
during periods in which infants of these ages were in
a sleeping or other  non-alert state, and may only
represent behavior immediately prior to a  state of
distress (sustained crying episode).   The extent to
which these infants' behavior is representative of other
full-term infants of these ages is unknown.

4.4.2.2  Zartarian  et   al.,  1997a -  Quantifying
        Videotaped  Activity   Patterns:   Video
        Translation    Software   and   Training
        Technologies/Zartarian  et  al.,  1997b -
        Quantified Dermal Activity Data From a
        Four-Child Pilot Field Study/Zartarian et
        al.,  1998 -  Quantified Mouthing Activity
        Data From a Four-Child Pilot Field Study
        As described in Section 4.3.1.1, Zartarian et
al. (1997a, 1997b, 1998) conducted a pilot study of the
 video-transcription  methodology to investigate the
 applicability  of using  videotaping for  gathering
 information related to children's activities, dermal
 exposures and mouthing behaviors.  The researchers
 had  conducted  studies using  the  real-time  hand
 recording  methodology,  resulting  in poor inter-
 observer  reliability  and   observer  fatigue  when
 attempted for long periods of time, prompting the
 investigation into using videotaping with transcription
 of the children's activities at a point in time after the
 observations (videotaping) occurred.
         Four   Mexican-American   farm  worker
 children in the Salinas Valley of California each were
 videotaped with a hand-held videocamera during their
 waking hours, excluding time spent in the bathroom,
 over one day in September 1993.  The boys were 2
 years 10 months old and 3  years, 9 months old; the
 girls were 2 years 5 months old and 4 years 2 months
 old.   Time of videotaping was 6.0 hours  for the
 younger girl, 6.6 hours for the older girl, 8.4 hours for
 the younger boy and 10.1 hours for the older boy.  The
 videotaping gathered information on detailed micro-
 activity patterns of children to  be used to evaluate
 software for videotaped activities  and translation
 training methods.
         The four  children  mouthed  non-dietary
 objects an average of 4.35 percent (range 1.41 to 7.67
 percent) of the total observation time, excluding the
 time during  which  the children were out of the
 camera's  view (Zartarian et al., 1997a).   Objects
 mouthed  included  bedding/towels, clothes,  dirt,
 grass/vegetation, hard surfaces, hard toys, paper/card,
 plush  toy,  and  skin (Zartarian  et  al.,  1997a).
 Frequency distributions for the  four children's non-
 dietary object contact durations were reported to be
 similar  in shape.  Reported hand to mouth contact
 presumably is a subset of the object to mouth contacts
 described in Zartarian et al., 1997a, and is described in
 Zartarian et al.,  1997b.  The four children mouthed
 their hands an average of 2.35 percent (range 1.0 to
 4.4 percent) of observation time.   The researchers
 reported measures  taken to assess inter-observer
 reliability and several  problems  with the video-
 transcription process.
         This study's primary purpose was to develop
 and evaluate the video-transcription methodology; a
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secondary  purpose  was  collection  of  mouthing
behavior data.  The sample of children studied was
very small and not likely to be representative of the
national population.  Thus, U.S. EPA did not judge it
to be suitable for  consideration  as a key study of
children's mouthing behavior.  As with other video-
transcription  studies, the presence  of non-family-
member videographers and a video camera may have
influenced the children's behavior.

4.4.2.3  Groot et al, 1998 - Mouthing Behavior of
        Young Children: An Observational Study
        In this study, Groot etal. (1998) examined the
mouthing behavior of 42 Dutch children (21 boys and
21 girls) between the ages of 3 and 36 months in late
July and August 1998. Parent observations were made
of children in 36 families.  Parents  were asked to
observe their children ten times per day for 15 minute
intervals (i.e.,  150 minutes total per day) for two days
and measure mouthing times with a stopwatch. In this
study, mouthing was defined as "all activities in which
objects are touched by mouth or put into the mouth
except for eating and drinking.  This term includes
licking as well as sucking, chewing and biting."
        For the study, a distinction was made between
toys meant for  mouthing (e.g.,  pacifiers, teething
rings)  and those not meant for  mouthing.  Inter-
observer and intra-observer reliability was measured by
trained  observers  who  co-observed  a portion  of
observation periods in  three families, and who  co-
observed  and  repeatedly  observed  some  video-
transcriptions  made of one child.  Another quality
assurance procedure  performed for the  extrapolated
total mouthing time data was to select  12 times  per
hour randomly during the entire waking period of four
children during one day, in which the researchers
recorded activities and total mouthing times.
        Although  the  sample  size  was relatively
small,  the results  provided estimates of mouthing
times,  other than pacifier use, during  a day.  The
results were extrapolated to the entire day based on the
150 minutes of observation per day,  and the mean
value for each child for the two days of observations
was  interpreted as  the  estimate  for  that  child.
Summary statistics are shown in Table 4-16.  The
standard deviation in all four age categories except the
3 to 6 month old  children exceeded the estimated
mean.   The 3 to 6  month children  (N=5) were
estimated  to  have mean non-pacifier  mouthing
durations of 36.9 minutes per day, with toys as the
most frequently mouthed product category, and the 6
to 12 month children (N=14) 44 minutes per day
(fingers most frequently  mouthed).   The 12 to  18
month olds'  (N=12)  estimated mean  non-pacifier
mouthing time was 16.4 minutes per day, with fingers
most frequently mouthed, and 18 to 36 month olds'
(N=ll) estimated mean non-pacifier mouthing time
was  9.3 minutes per  day (fingers most frequently
mouthed).
        One strength of this study  is that  the
researchers  recognized  that observing children's
behavior might affect the behavior, and emphasized to
the parents the importance of making observations
under conditions that were as normal as possible.  In
spite of these efforts, many parents perceived that their
children's behavior was affected by being observed,
and  observation   interfered  with    care   giving
responsibilities such as comforting children when they
were upset. Other limitations included a small sample
size  that  was not  representative  of  the  Dutch
population and that also may not be representative of
U.S.  children.    Technical  problems  with   the
stopwatches affected at least 14 of 36 parents' data.

4.4.2.4  Smith and Norris, 2003 - Reducing the Risk
        of Choking Hazards: Mouthing Behavior of
        Children Aged 1 Month to 5 Years/Norris
        and Smith,  2002  -  Research  Into  the
        Mouthing Behaviour  of Children up  to 5
        Years Old
        Smith and Norris (2003)  conducted a real-
time hand recording  study  of mouthing behavior
among 236 children (111  males, 125 females) in the
United Kingdom (exact locations not specified)  who
were from 1  month to 5 years old. Children were
observed at home by parents, who used stopwatches to
record the time that  mouthing began, the  type of
mouthing, the type of object being mouthed, and the
time that mouthing ceased. Children were observed for
a total  of 5 hours over  a  two week period;  the
observation time consisted of twenty 15 minute periods
spread over different times and days during the child's
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                                                          Chapter 4 - Non-dietary Ingestion Factors
waking hours. Parents also recorded the times each
child was awake and not eating meals so that the
researchers could extrapolate estimates  of total daily
mouthing time from the shorter observation periods.
Mouthing  was  defined  as  licking/lip   touching,
sucking/trying to bite,  biting or chewing,  with a
description of each category, together with pictures,
given to parents as guidance for what to record.
        The results of the study are shown in Table 4-
17. While no overall pattern  could  be  found in the
different age groups tested, a Kruskal-Wallis test on
the data for all items mouthed indicated that there was
a significant difference between the age groups. Across
all age groups and types of items, licking and sucking
accounted for 64 percent of all mouthing behavior.
Pacifiers and fingers  exhibited  less  variety  on
mouthing behavior (principally sucking), while other
items had a higher frequency of licking, biting, or
other mouthing.          The researchers selected
25of the 236 children randomly for a  single 15 minute
observation of each child (total observation time across
all children: 375 minutes), in order to  compare the
mouthing frequency  and duration data obtained
according to the real-time hand recording and the
video-transcription methodologies,  as  well as the
reliability of parent observations versus those made by
trained professionals.  For this group of 25 children,
the total number of mouthing behavior events recorded
by video (160) exceeded those  recorded by parents
(114) and trained observers (110). Similarly, the total
duration  recorded by  video  (24 minutes and  15
seconds) exceeded that recorded by observers (parents
and trained observers both recorded identical totals of
19 minutes and 44 seconds). The mean  and standard
deviation of observed mouthing time were both lower
when  recorded  by video versus  real-time  hand
recording.  The  maximum observed mouthing time
was  also lower (6 minutes and 7 seconds by video
versus 9 minutes and 43 seconds for both parents and
trained observers).
        The  strengths  of  this   study   were  its
comparison of three types of observation (parents,
trained professional observers, and videotaping), and
its detailed reporting of mouthing behaviors by type,
object/item mouthed, and  age group. However, the
children studied may not be representative of the study
 population, and  may not be representative of U.S.
 children.

 4.4.2.5  Au Yeung et al, 2004 - Young Children's
         Mouthing  Behavior:  An  Observational
         Study  via  Videotaping in  a  Primarily
         Outdoor Residential Setting
         As described in Section 4.3.2.4, AuYeung et
 al. (2004) used a video-transcription methodology to
 study a group of 38 children (20 females and 18 males;
 ages 1 to 6 years), 37 of whom were selected randomly
 via a telephone screening survey of a 300 to 400 square
 mile  portion  of  the  San Francisco,   California
 peninsula,  along  with  one  child  selected  by
 convenience due to time constraints. Families who
 lived in a residence with a lawn and whose annual
 income was >$35,000 were  asked to  participate.
 Videotaping took place between August 1998 and May
 1999  for  approximately  two  hours  per  child.
 Videotaping by one researcher was supplemented with
 field notes taken by a second researcher who was also
 present during taping.  Most of the videotaping took
 place  during outdoor play,  however,  data  were
 included for several children (one child <2 years old
 and 8 children >2 years old) who had more than 15
 minutes  of indoor play during their videotaping
 sessions.
         The videotapes were  translated  into ASCII
 computer files using VirtualTimingDevice™ software
 described in Zartarian et al.  (1997a). Both frequency
 (see Section 4.3.2.4 of this Chapter) and duration were
 analyzed.  Between 5 and 10 percent of the data files
 translated were randomly chosen for quality control
 checks for inter-observer agreement. Ferguson et al.
 (2006) described  quality control aspects of the study in
 detail.
         For analysis, the mouthing contacts were
 divided into indoor and  outdoor locations, and  16
 object/surface categories.  Mouthing durations were
 analyzed by  age  and gender  separately, and  in
 combination.   Mouthing contacts were defined as
 contact with the lips, inside of the mouth, and/or the
 tongue; dietary  contacts were ignored.  Mouthing
 durations are shown in Table 4-18 (outdoor locations).
 For the children in all age groups, the median duration
 of each  mouthing contact was  1  to  2 seconds,
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confirming the observations of other researchers that
children's  mouthing  contacts  are  of  very  short
duration.  For the one child observed that was • 24
months, the total indoor mouthing duration was 11.1
minutes/hour; for children >24  months,  the  median
indoor mouthing duration was 0.9 minutes/hour (Table
4-19).   For outdoor environments, median  contact
durations for these age groups decreased to 0.8 and 0.6
minutes/hour, respectively (Table 4-20).
        Nonparametric tests, such as the Wilcoxon
rank sum test were used for the data analyses. Both age
and  gender  were  found  to be  associated  with
differences in mouthing behavior.   Girls'  hand to
mouth contact durations were  significantly  shorter
than for boys (p = 0.04).
        This study provides distributions of outdoor
mouthing  durations with a variety  of objects and
surfaces.  Although indoor mouthing data were also
included in this study, the results were  based on a
small number of children (N=9) and a limited amount
of indoor play.   The sample  of  children  may be
representative of certain socioeconomic strata in the
study area, but is not likely to be representative of the
national population. Due to the children's ages, the
presence of unfamiliar persons following the children
with a video camera may have influenced the video-
transcription methodology results.

4.5     MOUTHING PREVALENCE
4.5.1   Stanek  et al.,  1998 -  Prevalence  of Soil
        Mouthing/Ingestion   Among   Healthy
        Children Aged 1 to 6
        Stanek  et al.   (1998) characterized the
prevalence of  mouthing behavior among  healthy
children based on a survey response study of parents or
guardians  of 533  children (289  females,  244 males)
ages 1  to 6 years old.  Study participants  were
attendees at scheduled well-child visits at three clinics
in Western Massachusetts in August through October,
1992.   Participants  were  questioned  about the
frequency of 28 mouthing behaviors  of the children
over the preceding month in addition to exposure time
(e.g., time  outdoors,  play  in  sand  or  dirt)  and
children's characteristics (e.g., teething).
        Table 4-21 presents the prevalence of reported
non-food ingestion/mouthing behaviors by child's age
as the percent of children whose parents reported the
behavior in the preceding month. The table includes
a column of data for the 3 to <6 year age category; this
column was calculated by U.S. EPA as a weighted
mean value of the individual data for 3, 4, and 5 year
olds in order to  conform to the  standardized  age
categories used in this handbook. Among all the age
groups, 1 year  olds had  the  highest reported daily
sucking of fingers/thumb; the  proportion dropped for
two year olds, but rose slightly for three and four year
olds and declined again after age 4.  A similar pattern
was  reported for  more than weekly finger/thumb
sucking, while  more  than  monthly finger/thumb
sucking showed a very slight increase for 6 year olds.
Reported pacifier use was highest for one year olds and
declined with age for daily and more than weekly use;
for more than monthly use of a  pacifier several six year
olds were reported to use pacifiers,  which altered the
age-declining pattern for the daily and  more than
weekly  reported pacifier use.   A pattern similar to
pacifier use existed with reported mouthing of teething
toys, with highest  reported use for one year olds, a
decline  with age until  age 6  when reported use for
daily, more than weekly, and more than monthly use of
teething toys increased.
        The authors developed an outdoor mouthing
rate for each child as the sum of rates for responses to
four questions on mouthing specific outdoor objects.
Survey responses were converted to mouthing rates per
week, using values of 0, 0.25,1, and 7 for responses of
never, monthly, weekly, and daily ingestion. Reported
outdoor soil mouthing behavior prevalence was found
to be higher than reported  indoor  dust  mouthing
prevalence, but both behaviors had the highest reported
prevalence among  1 year old  children and decreased
for children 2 years  and older.   The investigators
conducted principal component analyses on responses
to four  questions relating to  ingestion/mouthing of
outdoor  objects  in   an  attempt  to  characterize
variability.    Outdoor  ingestion/mouthing rates
constructed  from  the  survey responses  were that
children 1 year of age were reported to mouth or ingest
outdoor objects 4.73 times per week while 2 to 6 year
olds were reported to mouth or ingest outdoor objects
0.44 times per  week.   The  authors  developed
regression models  to identify  factors  related to high
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                                                         Chapter 4 - Non-dietary Ingestion Factors
outdoor mouthing rates.  The authors found that
children who were reported to play in sand or dirt had
higher outdoor object ingestion/mouthing rates.
        A strength of this study is that it was a large
sample obtained in an area with urban and semi-urban
residents within various socioeconomic categories and
with  varying  racial/ethnic  identities.   However,
difficulties with parents' recall of past events may have
caused either over-estimates or under-estimates of the
behaviors  studied.

4.5.2    Warren et  al.,  2000  -  Non-nutritive
        Sucking Behaviors in Preschool Children:
        A Longitudinal Study
        Warren et  al.  (2000) conducted a survey
response study of a non-random cohort of children
born in certain Iowa hospitals from early 1992 to early
1995, as part of a study of children's fluoride exposure.
For this longitudinal study of children's non-nutritive
sucking behaviors, 1,374 mothers were recruited at the
time of their newborns' birth, and over 600 were active
in the study until the children were at least 3 years old.
Survey questions on non-nutritive sucking behaviors
were administered to the mothers when the children
were 6 weeks, 3, 6, 9, 12, 16 and 24 months old, and
yearly after age 24 months.  Questions were posed
regarding  the child's  sucking behavior over  the
previous 3 to 12 months.
        The authors reported that nearly all children
sucked non-nutritive items, including pacifiers, thumbs
or other fingers, and/or other objects, at some point in
their  early  years.   The parent-reported  sucking
behavior prevalence peaked at 91 percent for 3 month
old children. At 2 years of age, a majority (53 percent)
retained a  sucking habit, while 29 percent retained the
habit  at age 3 years and 21 percent at age  4 years.
Parent-reported pacifier use was 28% for 1 year olds,
25% for 2 year olds, and 10% for 3 year olds.  The
authors cautioned against generalizing the results to
other  children due to study design limitations.
        Strengths of this study were its longitudinal
design and the large sample size.  A limitation is that
the non-random selection of original study participants
and the self-selected nature of the  cohort of survey
respondents who participated over time means that the
results may not be representative of other U. S. children
 of these ages.

 4.6      REFERENCES FOR CHAPTER 4
 AuYeung, W.;  Canales, R.; Beamer, P.; Ferguson,
         A.C.; Leckie, J.O.  (2004) Young children's
         mouthing behavior: An observational study
         via  videotaping in  a  primarily  outdoor
         residential setting.  J Children's Health 2(3-
         4):271-295.
 Barr, R.G.; Quek, V.S.H.; Cousineau, D.; Oberlander,
         T.F.; Brian, J.A.; Young, S.N. (1994) Effects
         of Intra-oral sucrose on crying, mouthing and
         hand-mouth contact  in  newborn and six-
         week-old infants.   Dev  Med Child Neurol
         36:608-618.
 Black, K.; Shalat, S.L.;  Freeman, N.C.G.; Jimenez,
         M; Donnelly, K.C.; Calvin,  J.A.   (2005)
         Children's  mouthing  and  food-handling
         behavior in an agricultural community on the
         US/Mexico border.  J Expo Anal  Environ
         Epidemiol 15:244-251.
 Blass, E.M.; Pillion, T.J.; Rochat, P.; Hoffmeyer, L.B.;
         Metzger,  M.A.  (1989)  Sensorimotor and
         Motivational  Determinants of Hand-Mouth
         Coordination in 1 -3 -Day-Old Human Infants.
         Dev Psych 25(6):963-975.
 Davis, S.; Myers, P.A.; Kohler, E.; Wiggins,  C.
         (1995). Soil Ingestion in Children with Pica:
         Final  Report.    U.S.  EPA  Cooperative
         Agreement   CR   816334-01.     Seattle,
         Washington:  Fred  Hutchinson  Cancer
         Research Center.
 Ferguson, A.C.; Canales, R.A.; Beamer, P.; AuYeung,
         W.; Key,  M.; Munninghoff, A.; Lee, K. T.-
         W.;  Robertson, A.,  Leckie, J.O.   (2006)
         Video  methods in the  quantification  of
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         Epidemiol 16:287-298.
 Freeman, C.G.; Jimenez, M.; Reed, K.J.; Gurunathan,
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Greene, M.A.  (2002) Mouthing times for children
        from the observational study. U.S. Consumer
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Groot, M. E.; Lekkerkerk, M. C.; Steenbekkers, L. P.
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        Children:   An  observational   Study.
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Juberg, D.R.; Alfano, K.; Coughlin, R.J.; Thompson,
        K.M.  (2001)   An  Observational Study of
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Ko, S.; Schaefer, P.; Vicario, C.; Binns, H.J.  (2007)
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        touching  and mouthing behaviors  during
        outdoor play in urban residential yards to
        parental perceptions of child behaviors  and
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Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz,
        S.;  Robino,  R.;  Kapish,   J.   (1975)
        Investigations into  Sources of Lead  in the
        Environment of Urban Children. Environ
        Res 10:415-26.
Lew, A.R.; Butterworth, G. (1997) The Development
        of Hand-Mouth  Coordination in 2- to 5-
        Month-Old  Infants:   Similarities  with
        Reaching and Grasping.  Infant Behav Dev
        20(l):59-69.
Norris,  B.;  Smith, S.   (2002)  Research into  the
        mouthing behaviour of children up to 5 years
        old.  London:  Consumer and Competition
        Policy Directorate, Department of Trade and
        Industry.
Reed, K.; Jimenez, M.; Freeman, N.; Lioy, P.  (1999)
        Quantification   of   children's  hand  and
        mouthing  activities  through a videotaping
        methodology.     J  Expo  Anal Environ
        Epidemiol 9:513-520.
Rochat, P.;  Blass, E.M.;  Hoffmeyer,  L.B.  (1988)
        Oropharyngeal  Control of  Hand-Mouth
        Coordination in Newborn Infants. Dev Psych
        24(4):459-63.
Shalat,  S.L.;  Donnelly,  K.C.;  Freeman,  N.C.G.;
        Calvin, J. A.; Ramesh, S.; Jimenez, M.; Black,
        K.; Coutinho, C.; Needham, L.L.; Barr, D.B.;
        Ramirez, J. (2003) Nondietary ingestion of
        pesticides  by children  in  an agricultural
        community on  the  U.S./Mexico border:
        Preliminary Results. J Expos Anal Environ
        Epidemiol 13:42-50.
Smith, S.A.; Norris, B. (2003). Reducing the risk of
        choking hazards:  mouthing behavior  of
        children aged 1  month to 5 years. Injury
        Control and Safety Promotion 10(3): 145-154.
Stanek, E.J.; Calabrese, E.J.; Mundt, K.; Pekow, P.;
        Yeatts, K.B.   (1998) Prevalence of soil
        mouthing/ingestion among healthy children
        aged 1 to 6. J Soil Contam  7(2):227-242.
Takaya, R.; Yukuo, K.; Bos, A.F.; Einspieler, C.
        (2003) Preterm to early postterm changes in
        the development of hand-mouth contact and
        other motor patterns.  Early Hum Dev 75
        Suppl. S193-S202.
Tudella, E.; Oishi, J.; Puglia Bermasco, N.H. (2000)
        The Effect of Oral-Gustatory, Tactile-Bucal,
        and  Tactile-Manual  Stimulation  on  the
        Behavior of the Hands in Newborns.  Dev
        Psychobiol 37:82-89.
Tulve, N.S.; Suggs, J.C.; McCurdy, T.; Cohen Hubal,
        E.A.;  Moya,  J.    (2002)  Frequency  of
        mouthing behavior in young children. J Expo
        Anal Environ Epidemiol 12:259-264.
U.S. EPA. (2005) Guidance on selecting age groups
        for monitoring  and assessing  childhood
        exposures  to environmental contaminants.
        Washington,  DC.:   U.S.   Environmental
        Protection  Agency, Office of Research and
        Development. EPA/630/P-03/003F.
Warren, J.J.; Levy, S.M.; Nowak, A.J.; Tang. S. Non-
        nutritive  sucking behaviors  in  preschool
        children: a longitudinal study. (2000) Pediatr
        Dent 22(3): 187-91.
Xue, J.; Zartarian, V.; Moya, J.; Freeman, N.; Beamer,
        P.; Black, K; Tulve, N.; Shalat, S.  (2007) A
        Meta-Analysis of Children's Hand-to-Mouth
        Frequency Data for Estimating Nondietary
        Ingestion   Exposure.    Risk   Analysis
        27(2):411-420.
Zartarian, V.G.;  Streicker, J.; Rivera, A.; Cornejo,
        C.S.; Molina, S.; Valadez, O.F.; Leckie, J.O.
        (1995)  A  Pilot  Study  to  Collect  Micro-
Child-Specific Exposure Factors Handbook
September 2008	
                                         Page
                                          4-19

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                                                     Child-Specific Exposure Factors Handbook

                                                       Chapter 4 - Non-dietary Ingestion Factors
        Activity Data of Two- to Four-Year-Old Farm
        Labor Children in Salinas Valley, California.
        J Expo Anal Environ Epidemiol 5(l):21-34.
Zartarian V.G.; Ferguson A.C.; Ong, C.G.; Leckie J.
        (1997a)   Quantifying Videotaped Activity
        Patterns:  Video  Translation Software  and
        Training  Methodologies.    J Expo  Anal
        Environ Epidemiol 7(4):535-542.
Zartarian V.G.;  Ferguson A.; Leckie J.   (1997b)
        Quantified dermal activity data from a four-
        child pilot field study.  J Expo Anal Environ
        Epidemiol 7(4):543-553.
Zartarian, V.G.; Ferguson, A.C.; Leckie, J.O. (1998)
        Quantified mouthing activity data from a four-
        child pilot field study.  J Expo Anal Environ
        Epidemiol 8(4):543-553.
Page                                                Child-Specific Exposure Factors Handbook
4-20	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-3. New Jersey Children's Mouthing Frequency (contacts/hour) from Video-transcription
Category Minimum Mean
Hand to mouth 0.4 9.5
Object to mouth 0 16.3
Median 90th Percentile Maximum
8.5 20.1 25.7
3.6 77.1 86.2
Source: Reed etal., 1999.
Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age
Age Group Thumbs/fingers in Mouth Toes in Mouth Non-food Items in Mouth
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
1 1 years
12 years
-
Source:
71 29
63 0
33
30
28
33
43
38
33
33
= No data.
Freeman et al., 2001.
71
31
20
29
28
40
38
38
48
17


Table 4-5. Video-transcription Median (Mean) Observed Mouthing
Age Group N
3 to 4 years 3
5 to 6 years 7
7 to 8 years 4
10 to 12 years 5
Obj ect-to-mouth"
3(6)
0(1)
0(1)
0(1)
in 19 Minnesota Children (contacts/hour)
Hand-to-mouth
3.5 (4)
2.5 (8)
3(5)
2(4)
a Kruskal Wallis test comparison across four age groups, P=0.002.
N = Number of observations.
Source: Freeman et al., 2001.
Child-Specific Exposure Factors Handbook
September 2008	
Page
 4-21

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                                             Child-Specific Exposure Factors Handbook

                                              Chapter 4 - Non-dietary Ingestion Factors






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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-7. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD)
Age
Infant
1 year
2 years
Preschool
N
SD
Source:

N
13
12
18
9
= Number of subjects.
= Standard deviation.
Black etal., 2005.
Hand to mouth
Frequency
(contacts/hour)
14(19.8±14.5)
13.3 (15. 8 ±8.7)
9.9 (11. 9 ±9.3)
19.4 (22.1 ±22.1)

Object to Mouth
Frequency
(contacts/hour)
18. 1(24.4 ±11. 6)
8.4 (9.8 ±6.3)
5. 5 (7.8 ±5. 8)
8.4(10.1± 12.4)

Table 4-8. Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various Studies
Age Group
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
N = Number of subjects.
SD = Standard deviation.
Source: Xue etal., 2007.
N
23
119
245
161
169
14


Mean
28.0
18.9
19.6
12.7
14.7
6.7


SD
21.7
17.4
19.6
14.2
18.4
5.5


Percentiles
5
3.0
1.0
0.1
0.1
0.1
1.7


25
8.0
6.6
6.0
2.9
3.7
2.4


50
23.0
14.0
14.0
9.0
9.0
5.7


75
48.0
26.4
27.0
17.0
20.0
10.2


95
65.0
52.0
63.0
37.0
54.0
20.6


Table 4-9. Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various Studies

5 25
6 to <12 months 10 14.5 12.3 2.4 7.6
1 to <2 years 32 13.9 13.6 1.1 4.2
2 to <3 years 46 5.3 8.1 0.1 0.1
3 to <6 years 55 8.5 10.7 0.1 0.1
6to
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                                             Child-Specific Exposure Factors Handbook

                                              Chapter 4 - Non-dietary Ingestion Factors
Table 4-10. Survey Reported Mouthing Behaviors for 92 Washington State Children
Never
N
Hand/Foot in Mouth 4
Pacifier 74
Mouth on Object 14
Non-Food in Mouth 5
Eat Dirt/Sand 37
N = Number of subjects.
Source: Davis et al. 1995.
%
4
81
15
5
40


Seldom
N
27
6
30
25
39


%
30
7
33
27
43


Occasionally
N
23
2
25
33
11


%
25
2
27
36
12


Frequently
N
31
9
19
24
4


%
34
10
21
26
4


Always
N
4
1
1
5
1


%
4
1
1
5
1


Unknown
N
3
0
3
0
0


%
3
0
3
0
0


Table 4-11. Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children with
Age Group N
13 to 84 months 9
• 24 months 1
>24 months 8
Statistic
Mean
Median
Range
-
Mean
Median
Range
a Object/surface categories mouthed indoors included: Clothes/towels, hands,
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
20.5
14.8
2.5 - 70.4
73.5
13.9
13.3
2.2-34.1
metal, paper/wrapper,
>15 minutes in View Indoors
Total non-dietary"
29.6
22.1
3.2-82.2
84.8
22.7
19.5
2.8-51.3
plastic, skin, toys, and wood.
Page
4-24
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-12. Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
13 to 84 months 38 50th percentile
75th percentile
95th percentile
99th percentile
Mean
• 24 months 8 Median
Range
Mean
5th percentile
25th percentile
>24 months 30 50th percentile
75th percentile
95th percentile
99th percentile
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
11.7
0.4
4.4
8.4
14.8
31.5
47.6
13.0
7.0
1.3-47.7
11.3
0.2
4.7
8.6
14.8
27.7
39.5
hands, metal,



Total non-dietary"
18.3
0.8
9.2
14.5
22.4
51.7
56.6
20.4
13.9
6.2-56.4
17.7
0.6
7.6
14.6
22.4
43.8
53.0
non-dietary water, paper/wrapper,



Child-Specific Exposure Factors Handbook
September 2008	
Page
 4-25

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                                                            Child-Specific Exposure Factors Handbook

                                                             Chapter 4 - Non-dietary Ingestion Factors
              Table 4-13. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and Other Objects
                                     Age 0 to 18 months
                                                     Age 19 to 36 months
       Object Type
                             All Children
                    Only Children Who
                     Mouthed Objecta
                                                                         All Children
                                         Only Children Who
                                          Mouthed Object"
                              Minutes
                                                    Minutes
                                                                          Minutes
                                                                                                 Minutes
  Pacifier
  Teether
  Plastic Toy
  Other Objects
108 (N = 107)
 6 (N=107)
 17 (N=107)
 9 (N=107)
221 (N=52)
20 (N=34)
28 (N=66)
22 (N=46)
126(N=110)
 0(N=110)
 2(N=110)
 2(N=110)
462 (N=52)
 30 (N=l)
 11 (N=21)
 15 (N=18)
  a        Refers to means calculated for the subset of the sample children who mouthed the object stated (zeroes are eliminated from the
          calculation of the mean).
  N       = Number of children.

  Source:   Juberg et al., 2001.
Table 4-14. Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category and Child's Age
Object Category
All Objects
Pacifiers
Non-pacifiers
Soft Plastic Food Content Items
Anatomy
Non-soft Plastic Toys, Teethers, and Rattles
Other Items
All ages
100
27
100
28
99
91
98
<1 year
100
43
100
13
100
94
98
1 to 2 years
100
27
100
30
97
91
97
2 to 3 years
100
10
100
41
100
86
98
Source: Greene, 2002.
Page
4-26
                               Child-Specific Exposure Factors Handbook
                              	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour)
Age Group
Mean (SD)
Median
95th Percentile
99th Percentile
All Items"
3 to < 12 months
12 to <24 months
24 to <36 months
10.5 (7.3)
7.3 (6.8)
5.3 (8.2)
9.6
5.5
2.4
26.2
22.0
15.6
39.8
28.8
47.8
Non Pacifiers'"
3 to < 12 months
12 to <24 months
24 to <36 months
7.1(3.6)
4.7(3.7)
3.5 (3.6)
6.9
3.6
2.3
13.1
12.8
12.8
14.4
18.9
15.6
All Soft Plastic Items
3 to < 12 months
12 to <24 months
24 to <36 months
0.5 (0.6)
0.4 (0.4)
0.4(0.6)
0.1
0.2
0.1
1.8
1.3
1.6
2.5
1.9
2.9
Soft Plastic Items Not Food Contact
3 to < 12 months
12 to <24 months
24 to <36 months
0.4(0.6)
0.3 (0.4)
0.2 (0.4)
0.1
0.1
0.0
1.8
1.1
1.3
2.0
1.5
1.8
Soft Plastic Toys, Teethers, and Rattles
3 to < 12 months
12 to <24 months
24 to <36 months
0.3 (0.5)
0.2 (0.3)
0.1 (0.2)
0.1
0.0
0.0
1.8
0.9
0.2
2.0
1.3
1.6
Soft Plastic Toys
3 to < 12 months
12 to <24 months
24 to <36 months
0.1 (0.3)
0.2 (0.3)
0.1 (0.2)
0.0
0.0
0.0
0.7
0.9
0.2
1.1
1.3
1.6
Soft Plastic Teethers and Rattles
3 to <12 months
12 to <24 months
24 to <36 months
0.2 (0.4)
0.0(0.1)
0.0(0.1)
0.0
0.0
0.0
1.0
0.1
0.0
2.0
0.6
1.0
Other Soft Plastic Items
3 to <12 months
12 to <24 months
24 to <36 months
0.1 (0.2)
0.1 (0.1)
0.1 (0.3)
0.0
0.0
0.0
0.8
0.4
0.5
1.0
0.6
1.4
Child-Specific Exposure Factors Handbook
September 2008	
Page
 4-27

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                                                                Child-Specific Exposure Factors Handbook

                                                                  Chapter 4 - Non-dietary Ingestion Factors
                        Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) (continued)
        Age Group
Mean (SD)
                                                        Median
                                                                             95th Percentile
                                                                      99th Percentile
                                               Soft Plastic Food Contact Items
  3 to < 12 months
  12 to <24 months
  24 to <36 months
 0.0 (0.2)
 0.1 (0.2)
 0.2 (0.4)
0.3
0.7
1.2
0.9
1.2
1.9
                                                        Anatomy
3 to < 12 months
12 to <24 months
24 to <36 months
2.4(2.8)
1.7(2.7)
1.2(2.3)
1.5
0.8
0.4
10.1
8.3
5.1
12.2
14.8
13.6
                                          Non Soft Plastic Toys, Teethers, and Rattles
3 to < 12 months
12 to <24 months
24 to <36 months
1.8(1.8)
0.6 (0.8)
0.2 (0.4)
1.3
0.3
0.1
6.5
1.8
0.9
7.7
4.6
2.3
                                                       Other Items
3 to < 12 months
12 to <24 months
24 to <36 months
2.5(2.1)
2.1(2.0)
1.7(2.6)
2.1
1.4
0.7
7.8
6.6
7.1
8.1
9.0
14.3
                                                        Pacifiers
3 to < 12 months
12 to <24 months
24 to <36 months
3.4(6.9)
2.6(6.5)
1.8(7.9)
0.0
0.0
0.0
19.5
19.9
4.8
37.3
28.6
46.3
  SD
           Object category " all items" is subdivided into pacifiers and non-pacifiers.
           Object category "non-pacifiers" is subdivided into all soft plastic items, anatomy (which includes hair, skin, fingers and hands), non-
           soft plastic toys/teethers/rattles, and other items.
           Object category " all soft plastic items" is subdivided into food contact items, nonfood contact items (toys, teethers and rattles) and other
           soft plastic.
           = Standard deviation.
  Source:    Greene, 2002.
Page
4-28
                                Child-Specific Exposure Factors Handbook
                               	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-16. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without Pacifier, in Minutes per Day
Age Group
3 to 6 months
6 to 12 months
12 to 18 months
18 to 3 6 months
N
5
14
12
11
Note: The object most mouthed in all a;
N = Number of children.
SD = Standard deviation.
Source: Groot et al., 1998.
Mean
36.9
44
16.4
9.3
je groups was the fingers,
SD
19.1
44.7
18.2
9.8
except for the 6 to
Minimum
14.5
2.4
0
0
Maximum
67
171.5
53.2
30.9
12 month group which mostly mouthed toys.
Child-Specific Exposure Factors Handbook
September 2008	
Page
 4-29

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                                             Child-Specific Exposure Factors Handbook

                                              Chapter 4 - Non-dietary Ingestion Factors



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Page
4-30
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 4 - Non-dietary Ingestion Factors
Table 4-18. Outdoor Median Mouthing Duration (seconds per contact), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
13 to 84 months 38 50th percentile
75th percentile
95th percentile
99th percentile
Mean
• 24 months 8 Median
Range
Mean
5th percentile
25th percentile
>24 months 30 50th percentile
75th percentile
95th percentile
99th percentile
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
3.5
0
1
1
2
12
41.6
9
3
0 to 136
3.5
0
1
1
2
12
41.6
hands, metal,



Total non-dietary*
3.4
0
1
1
3
11
40
2
1
Oto40
3.4
0
1
1
3
11
40
non-dietary water, paper/wrapper,



Table 4-19. Indoor Mouthing Duration (minutes per hour), Video-transcription of 9 Children with >
Age Group N
13 to 84 months 9
• 24 months 1
>24 months 8
Statistic
Mean
Median
Range
Observation
Mean
Median
Range
a Object/surface categories mouthed indoors included: Clothes/towels, hands,
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
1.8
0.7
0-10.7
10.7
0.7
0.7
0-1.9
metal, paper/wrapper,
15 minutes in View Indoors
Total non-dietary"
2.3
0.9
0-11.1
11.1
1.2
0.9
0-3.7
plastic, skin, toys, and wood.
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                                             Child-Specific Exposure Factors Handbook

                                              Chapter 4 - Non-dietary Ingestion Factors
Table 4-20. Outdoor Mouthing Duration (minutes per hour), Video-transcription of 38 Children
Age Group N Statistic
Mean
5th percentile
25th percentile
.,,„.,, ,„ 50th percentile
13 to 84 months 38 -,cth 4-i
75 percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25th percentile
„ 50th percentile
'24months 8 75th percentile
95th percentile
99th percentile
Range
Mean
5th percentile
25th percentile
... ,„ Median
>24 months 30 „, ...
75 percentile
95th percentile
99th percentile
Range
a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric,
plastic, skin, toys, vegetation/grass, and wood.
N = Number of subjects.
Source: AuYeung et al., 2004.
Hands
0.9
0
0.1
0.2
0.6
2.6
11.2
0-15.5
2.7
0
0.2
0.4
1.5
11.5
14.7
0-15.5
0.4
0
0.1
0.2
0.4
1.2
2.2
0-2.4
hands, metal,



Total non-dietary*
1.2
0
0.2
0.6
1.2
2.9
11.5
0-15.8
3.1
0.2
0.2
0.8
3.1
11.7
15
0.2-15.8
0.7
0
0.2
0.6
1
2.1
2.5
0-2.6
non-dietary water, paper/wrapper,



Page
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Chapter 4 - Non-dietary Ingestion Factors
Table 4-21. Reported Daily Prevalence of Massachusetts Children's Non-Food Mouthing/Ingestion Behaviors
Object or substance
mouthed or ingested


Grass, leaves, flowers
Twigs, sticks, woodchips
Teething toys
Other toys
Blankets, cloth
Shoes, Footwear
Clothing
Crib, chairs, furniture
Paper, cardboard, tissues
Crayons, pencils, erasers
Toothpaste
Soap, detergent, shampoo
Plastic, plastic wrap
Cigarette butts, tobacco
Suck fingers/thumb
Suck feet or toes
Bite nails
Use pacifier
Percent of children reported to mouth/ingest daily

1 year
N=171
16
12
44
63
29
20
25
13
28
19
52
15
7
4
44
8
2
20
* Weighted mean of 3, 4, and 5 year-olds'
Handbook.
Source: Stanek et al. (1998).



2 years
N=70
0
0
6
27
11
1
7
3
9
17
87
14
4
0
21
1
7
6
data calculated by U.S



3 to <6 years"
N=265
1
0
2
12
10
0
9
1
5
5
89
2
1
1
24
0
10
2

6 years
N=22
0
0
9
5
5
0
14
0
5
18
82
0
0
0
14
0
14
0

All years
N=528
6
4
17
30
16
7
14
5
13
12
77
8
3
2
30
3
7
9
EPA to conform to standardized age categories used in this






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Chapter 6 - Inhalation Rates	
                                    TABLE OF CONTENTS

       INHALATION RATES	6-1
       6.1     INTRODUCTION	6-1
       6.2     RECOMMENDATIONS	6-2
       6.3     KEY INHALATION RATE STUDIES	6-6
              6.3.1   Brochu et al., 2006 	6-6
              6.3.2   U.S. EPA, 2006	6-6
              6.3.3   Arcus-Arth and Blaisdell, 2007	6-8
              6.3.4   Stifelman, 2007	6-9
              6.3.5   Key Studies Combined 	6-9
       6.4     RELEVANT INHALATION RATE STUDIES 	6-9
              6.4.1   International Commission on Radiological Protection (ICRP), 1981  	6-9
              6.4.2   U.S. EPA, 1985  	6-10
              6.4.3   Linn et al., 1992	6-10
              6.4.4   Spier et al., 1992	6-11
              6.4.5   Adams, 1993 	6-11
              6.4.6   Layton, 1993 	6-12
              6.4.7   Rusconi et al., 1994	6-14
              6.4.8   Price et al., 2003 	6-14
       6.5     REFERENCES FOR CHAPTER 6	6-15
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                                                       Child-Specific Exposure Factors Handbook

                                                      	Chapter 6 - Inhalation Rates
                                          LIST OF TABLES

Table 6-1.       Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation
                (Males and Females Combined)  	6-3
Table 6-2.       Recommended Short-Term Exposure (Less Than 30 Days) Values for Inhalation
                (Males and Females Combined)  	6-4
Table 6-3.       Confidence in Recommendations for Inhalation Rates  	6-5
Table 6-4.       Physiological Daily Inhalation Rates for Newborns  Aged 1 Month or Less	6-17
Table 6-5.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
                Normal-weight Males and Females Aged 2.6 months to 23 years   	6-18
Table 6-6.       Mean and 95th Percentile Inhalation Rate Values (mVday) for Free-living Normal-weight
                Males, Females, and Males and Females Combined	6-19
Table 6-7.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living
                Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years 	6-20
Table 6-8.       Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight
                (mVkg-day) for Free-living Normal-weight Males and Females Aged 2.6 months
                to 23 years	6-21
Table 6-9.       Distribution Percentiles of Physiological Daily Inhalation Rates (mVkg-day) for Free-living
                Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years 	6-22
Table 6-10.      Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category	6-23
Table 6-11.      Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category	6-24
Table 6-12.      Mean and 95th Percentile Inhalation Rate Values (mVday) for Males, Females and
                Males and Females Combined	6-25
Table 6-13.      Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
                Specified Activity Category, for Males by Age Category	6-26
Table 6-14.      Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the
                Specified Activity Category, for Females  by Age Category	6-28
Table 6-15.      Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
                Within the Specified Activity Category, by Age and Gender Categories  	6-30
Table 6-16.      Nonnormalized Daily Inhalation Rates (mVday) Derived Using Layton's (1993)
                Method and CSFII Energy Intake Data	6-32
Table 6-17.      Mean and 95th Percentile Inhalation Rate Values (mVday) for Males and Females
                Combined	6-33
Table 6-18.      Summary of Institute of Medicine Energy Expenditure Recommendations
                for Active and Very Active People with Equivalent Inhalation Rates	6-34
Table 6-19.      Mean Inhalation Rate Values (mVday) for Males, Females, and Males and Females
                Combined	6-35
Table 6-20.      Mean Inhalation Rate Values (mVday) from Key  Studies for Males and Females
                Combined	6-36
Table 6-21.      95th Percentile Inhalation Rate Values (mVday) from Key Studies for Males and Females
                Combined	6-37
Table 6-22.      Daily Inhalation Rates Estimated From Daily Activities	6-38
Table 6-23.      Selected Inhalation Rate Values During Different Activity Levels Obtained From Various
                Literature Sources  	6-39
Table 6-24.      Summary of Human Inhalation Rates for  Children by Activity Level (m3/hour)	6-40
Table 6-25.      Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for
                All Age Groups  	6-40
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Chapter 6 - Inhalation Rates	
                                     LIST OF TABLES (continued)

Table 6-26.      Summary of Daily Inhalation Rates Grouped by Age and Activity Level	6-41
Table 6-27.      Calibration and Field Protocols for Self-monitoring of Activities Grouped by
                Subject Panels	6-42
Table 6-28.      Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated
                Breathing Rates	6-42
Table 6-29.      Distribution of Predicted Inhalation Rates by Location and Activity Levels for Elementary
                and High School Students 	6-43
Table 6-30.      Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and
                High School Students	6-44
Table 6-31.      Summary of Average Inhalation Rates (mVhour) by Age Group and Activity Levels for
                Laboratory Protocols	6-45
Table 6-32.      Summary of Average Inhalation Rates (mVhour) by Age Group And Activity Levels in Field
                Protocols 	6-46
Table 6-33.      Mean Minute Inhalation Rate (mVminute) by Group and Activity for Laboratory Protocols  . . 6-47
Table 6-34.      Mean Minute Inhalation Rate (mVminute) by Group and Activity for Field Protocols	6-47
Table 6-35.      Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy
                Intakes (EFD) for Individuals Sampled in the 1977-78 NFCS  	6-48
Table 6-36.      Daily Inhalation Rates Calculated from Food-energy Intakes	6-49
Table 6-37.      Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting
                Basal Metabolic Rates (BMR)	6-50
Table 6-38.      Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal
                Metabolic Rate (BMR)  	6-51
Table 6-39.      Inhalation Rates for Short-term Exposures  	6-52
Table 6-40.      Mean, Median, and SD of Inhalation Rate According to Waking  or Sleeping in 618
                Infants and Children Grouped in Classes of Age	6-53
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                                                	Chapter 6 - Inhalation Rates
                                     LIST OF FIGURES

Figure 6-1.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects .... 6-54
Figure 6-2.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects .... 6-54
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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
6       INHALATION RATES
6.1     INTRODUCTION
        Ambient and indoor air are potential sources
of children's exposure to toxic substances.  Children
can be exposed to contaminated air during a variety of
activities in different environments. Children may be
exposed due to  sources that  contribute pollution to
ambient air. Children may also inhale chemicals from
the indoor use of various consumer products. Due to
their size, physiology, and activity level, the inhalation
rates of children differ from those of adults.
        Infants  and children have a  higher resting
metabolic rate and oxygen consumption rate per unit of
body weight than adults, because of their rapid growth
and relatively larger lung surface area per unit of body
weight that requires cooling. For example, the oxygen
consumption rate for a resting infant between one week
and one year of age is 7 milliliters per kilogram of body
weight (mL/kg) per minute, while the rate for an adult
under the same conditions is 3-5 mL/kg per minute
(WHO, 1986). Thus, while greater amounts of air and
pollutants are  inhaled  by adults than children over
similar time periods on an absolute basis, the volume of
air passing through the lungs of a resting infant is up to
twice that of a resting adult on a body weight basis.
        The Agency defines exposure as the chemical
concentration at the boundary of the body (U.S. EPA,
1992).  In  the  case of inhalation, the situation is
complicated by the fact that oxygen exchange with
carbon dioxide takes place in the distal portion  of the
lung.  The  anatomy and physiology of the respiratory
system as well as the characteristics of the inhaled agent
diminishes the pollutant concentration in inspired air
(potential dose) such that the amount of a pollutant that
actually enters the body through the lung (internal dose)
is less than that measured at the boundary of the body.
A  detailed discussion of this concept can be found in
Guidelines for Exposure Assessment (U.S. EPA, 1992).
When constructing risk assessments that concern the
inhalation route of exposure, one must be aware of any
adjustments that have been employed in the estimation
of the pollutant  concentration to account for  this
reduction in potential dose.
        Children's inhalation dosimetry and  health
effects were topics  of discussion at  a U.S.  EPA
workshop held in June 2006 (Foos and Sonawane,
2008). Age related differences in lung structure and
function, breathing patterns, and how these affect the
inhaled dose and the deposition of particles in the lung
are important factors in assessing risks from inhalation
exposures (Foos et al, 2008).   Children may  have a
lesser nasal contribution to breathing during rest and
while performing various  activities.  The uptake  of
particles  in the nasal airways is also  less efficient in
children.  Thus, the deposition of particles in the lower
respiratory tract may be greater (Foos et al., 2008).
        Inclusion of this chapter in the Child-Specific
Exposure Factors  Handbook  does  not  imply  that
assessors will always need to select and use inhalation
rates when evaluating exposure to air contaminants.
For example, it is unnecessary to calculate inhaled dose
when using dose-response factors from the Integrated
Risk Information System (IRIS) (U.S.  EPA,  1994),
because the IRIS methodology accounts for inhalation
rates   in the   development   of  "dose-response"
relationships. Information in this chapter may be used
by toxicologists in their derivation of human equivalent
concentrations.  When using IRIS for inhalation risk
assessments, "dose-response" relationships require only
an  average  air concentration  to  evaluate  health
concerns:

        For non-carcinogens,  IRIS  uses  Reference
        Concentrations (RfCs) which are expressed in
        concentration units. Hazard  is evaluated  by
        comparing the inspired air concentration to the
        RfC.
        For carcinogens, IRIS uses unit risk  values
        which are  expressed in inverse  concentration
        units.   Risk is evaluated by multiplying the
        unit risk by the inspired air concentration.

Detailed  descriptions  of the IRIS methodology  for
derivation of inhalation reference concentrations can be
found in two methods manuals produced by the Agency
(U.S. EPA, 1992; 1994).
        The Superfund Program has also updated  its
approach for determining inhalation risk, eliminating
the use of inhalation rates when  evaluating exposure to
air contaminants  (U.S.  EPA,  2008).   The current
methodology recommends  that risk assessors use the
concentration of the chemical  in air as the exposure
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                                                        Child-Specific Exposure Factors Handbook

                                                        	Chapter 6 - Inhalation Rates
metric (e.g., mg/m3),  instead  of the intake of  a
contaminant in air based on inhalation rate and body
weight (e.g., mg/kg-day).
        Recommended inhalation rates (both long- and
short-term) are provided in the next section, along with
the confidence  ratings  for these recommendations.
These recommendations are based on four key studies
identified  by U.S. EPA for this factor.  Long-term
exposure is repeated exposure for more than 30 days,
up to approximately 10% of the life span in humans
(more than 30 days).  Long-term inhalation rates for
children (including infants) are presented as daily rates
(mVday).  Short-term exposure is repeated exposure for
more than  24  hours,  up  to 30  days.  Short-term
inhalation rates are reported  for children (including
infants) performing various activities in  mVminute.
Following the recommendations, the available studies
(both key  and relevant studies) on inhalation rates are
summarized.

6.2     RECOMMENDATIONS
        The recommended inhalation rates for children
are based  on four recent studies: Brochu et al, 2006;
U.S. EPA, 2006; Arcus-Arth and Blaisdell, 2007; and
Stifelman,   2007.    These  studies  represent  an
improvement  upon   those  previously  used  for
recommended inhalation  rates  in this  handbook,
because they use a large data set that is representative
of the United States  as a whole  and consider the
correlation between body weight and inhalation rate.
        The selection of inhalation rates to be used for
exposure  assessments  depends on the age  of the
exposed population and the specific activity levels of
this population during various exposure scenarios. The
recommended long-term values for children (including
infants) for use in various exposure scenarios  are
presented  in Table  6-1 for the  standard U.S. EPA
childhood age groups   used  in this  handbook.  As
shown in Table 6-1, the daily average inhalation rates
for long-term exposures for male and female children
combined (unadjusted for body weight) range from 3.6
mVday for children from birth to <1 month to 16.5
mVday for children aged 16 to <21 years. These values
represent averages of the inhalation rate data from the
four key studies. The 95th percentile values range from
7.1 mVday to 27.6 mVday for the same age categories.
The  95th percentile values represent averages of the
 inhalation rate data from the three key studies for which
 95th percentile values were available for selected age
 groups (Brochu et al., 2006; U.S. EPA, 2006; Arcus-
 Arth and Blaisdell, 2007). It should be noted that there
 may be a high degree of uncertainty associated with the
 upper percentiles.  These values equate to unusually
 high estimates  of caloric intake per  day,  and are
 unlikely to be representative of the average child. For
 example, using Layton's equation (Layton, 1993) for
 estimating metabolically consistent inhalation rates to
 calculate caloric equivalence (see Section 6.4.6), the
 95th percentile value for 16 to <21 year old children is
 4,840 kcal/day.  All  of the 95th percentile values listed
 in Table 6-1 may represent unusually high inhalation
 rates for long-term exposures, even for the upper end of
 the distribution, but were included in this handbook to
 provide exposure assessors a sense of the possible range
 of inhalation rates for children. These values should be
 used with caution when estimating long-term exposures.
         For short-term exposures for children aged 21
 years and under, for which activity patterns are known,
 mean and 95thpercentile data are provided in Table 6-2
 for males and females combined, in mVminute. These
 values represent averages of the activity level data from
 the one key study from which short-term inhalation rate
 data were available (U.S. EPA, 2006).
         The confidence ratings for the inhalation rate
 recommendations are  shown in Table 6-3.  Multiple
 percentiles for long- and short-term inhalation rates for
 both males and females are provided in  Tables 6-5
 through 6-11 and Table 6-16.
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Chapter 6 - Inhalation Rates	
Table 6-1. Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation
(Males and Females Combined).
. „ Mean Sources Used 95th Percentile Sources Used , , ... , „ ...
Age Group ,,, ,, ,, ,,, „ „,„,,, ... Multiple Percentiles
0 ^ nr/day for Means nr/day for 95™ Percentiles r
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months

1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
1 Arcus-Arth and
b No data for this
3.6
_ b
4.1
5.4

8.0
9.5
10.9
12.4
15.1
16.5
a
a,c
a,c

a,c,d,e
a,d,e
a,d,e
a,d,e
a,d,e
a,d,e
7.1
6.1
8.1

12.8
15.9
16.2
18.7
23.5
27.6
a
a,c
a,c
See Tables 6-5
a'c'd through 6- 11 and 6- 16
a,d
a,d
a,d
a,d
a,d
Blaisdell, 2007.
age group.



Brochuetal.,2006.
d U.S. EPA, 2006
Stifelman, 2007


Note: Some 95th percentile values


may be unusually


high, and


may not be representative of the average child.
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                                           	Chapter 6 - Inhalation Rates
Table 6-2.
Activity Level
Sleep or Nap






Sedentary/
Passive





Light Intensity






Moderate Intensity






High Intensity






Source: U.S. EPA,
Recommended Short- Term Exposure (Less Than 30 Days) Values for Inhalation
(Males and Females Combined)
Age Group
years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16to<21 years
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
2006.
Mean
mVminute
3.0E-03
4.5E-03
4.6E-03
4.3E-03
4.5E-03
5.0E-03
4.9E-03
3.1E-03
4.7E-03
4.8E-03
4.5E-03
4.8E-03
5.4E-03
5.3E-03
7.6E-03
1.2E-02
1.2E-02
1.1E-02
1.1E-02
1.3E-02
1.2E-02
1.4E-02
2.1E-02
2.1E-02
2.1E-02
2.2E-02
2.5E-02
2.6E-02
2.6E-02
3.8E-02
3.9E-02
3.7E-02
4.2E-02
4.9E-02
4.9E-02

95 Percentile ,, ... . „ ...
, , . , Multiple Percentiles
m /minute
4.6E-03
6.4E-03
6.4E-03
5.8E-03
6.3E-03
7.4E-03
7.1E-03
4.7E-03
6.5E-03
6.5E-03
5.8E-03
6.4E-03
7.5E-03
7.2E-03
1.1E-02 See Tables 6- 11 and 6- 12
1.6E-02
1.6E-02
1.4E-02
1.5E-02
1.7E-02
1.6E-02
2.2E-02
2.9E-02
2.9E-02
2.7E-02
2.9E-02
3.4E-02
3.7E-02
4.1E-02
5.2E-02
5.3E-02
4.8E-02
5.9E-02
7.0E-02
7.3E-02

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Chapter 6 - Inhalation Rates	
Table 6-3. Confidence in Recommendations for Inhalation Rates
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The survey methodology and data analysis was adequate.
Measurements were made by indirect methods. The
studies analyzed existing primary data.
Potential bias within the studies was fairly well
documented.
The studies focused on inhalation rates and factors
influencing them.
The studies focused on the U.S. population. A wide
range of age groups were included.
The studies were published during 2006 and 2007 and
represent current exposure conditions.
The data collection period for the studies may not be
representative of long-term exposures.
All key studies are available from the peer reviewed
literature.
The methodologies were clearly presented; enough
information was included to reproduce most results.
Information on ensuring data quality in the key studies
was limited.
In general, the key studies addressed variability in
inhalation rates based on age and activity level.
However, other factors that may affect inhalation rates
(e.g., weight, body mass index [BMI], ethnicity) are not
discussed.
Multiple sources of uncertainty exist for these studies.
Assumptions associated with Energy Expenditure (EE)
based estimation procedures are a source of uncertainty
in inhalation rate estimates.
Three of the key studies appeared in peer reviewed
journals, and one key study is a U.S. EPA peer reviewed
report.
There are four key studies. The results of studies from
different researchers are in general agreement.

Rating
Medium
High
Medium
Medium
High
Medium
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                                                      	Chapter 6 - Inhalation Rates
6.3     KEY INHALATION RATE STUDIES
6.3.1    Brochu et aL, 2006 - Physiological Daily
        Inhalation Rates for Free-living Individuals
        Aged 1 Month to 96 Years,  Using  Data
        from   Doubly  Labeled   Water
        Measurements: A proposal for Air Quality
        Criteria, Standard Calculations and Health
        Risk Assessment
        Brochu et al. (2006) calculated physiological
daily inhalation rates (PDIR) for 2,210 individuals aged
3 weeks to 96 years using the reported disappearance
rates of oral doses of doubly labeled water (DLW)
(2H20 and H2180) in urine, monitored by gas-isotope-
ratio mass spectrometry for an aggregate period of more
than 30,000 days. DLW data were complemented with
indirect  calorimetry   and  nutritional  balance
measurements.
        In the DLW method, the disappearance of the
stable isotopes deuterium (2H) and heavy oxygen-18
(180) are monitored in urine, saliva, or blood samples
over a long period of time (from 7 to 21 days) after
subjects receive oral doses of 2H20 and  H2180.  The
disappearance rate of 2H reflects water output and that
of 180 represents water  output  plus carbon dioxide
(C02) production rates.  The C02 production rate is
then  calculated  by  difference between  the  two
disappearance rates.  Total  daily energy expenditures
(TDEEs) are determined from C02 production rates
using classic respirometry formulas, in which values for
the respiratory quotient (RQ = C02produced/02 consumed) are
derived from the composition of the diet during the
period of time of each study.  The DLW method also
allows for measurement of the energy cost of growth
(ECG).   TDEE and ECG  measurements can be
converted into  PDIR values  using  the  following
equation developed by Layton (1993):

PDIR = (TDEE + ECG) x H x VQ 10'3    (Eqn. 6-1)
                                             H  =
where:
    PDIR   =

    TDEE  =
    (kcal/day);
    ECG    =
physiological daily inhalation rates
(mVday);
total  daily  energy  expenditure

stored daily energy cost for growth
(kcal/day);
                                             VQ =
                                             io-3 =
                  oxygen uptake factor, volume of
                  0.21  L of  oxygen (at  standard
                  temperature and pressure, dry air)
                  consumed to produce 1  kcal of
                  energy expended;
                  ventilatory equivalent ratio of the
                  minute  volume  (VE)  at  body
                  temperature pressure saturation) to
                  the oxygen  uptake rate  (V02 at
                  standard temperature and pressure,
                  dry air) VE/V02 = 27; and
                  conversion factor (L/m3).
        Brochu et al. (2006) calculated daily inhalation
rates (expressed in mVday and m3/kg-day) for a variety
of age groups and physiological conditions. Published
data on BMI, body weight, basal metabolic rate (BMR),
ECG, and  TDEE  measurements  (based on DLW
method and indirect calorimetry) for subjects aged 2.6
months to 96 years were used.   Only the  data for
children are presented in this handbook.  Data for
underweight,   healthy   normal-weight,   and
overweight/obese  individuals were  gathered  and
defined according to BMI cutoffs.  Data for newborns
were included regardless of BMI values, because they
were clinically evaluated as being healthy infants.
        Mean inhalation  rates  for newborns are
presented in Table 6-4. Due to the insufficient number
of subj ects, no distributions were derived for this group.
The distribution of daily inhalation rates for  normal-
weight and overweight/obese individuals by gender and
age groups are presented in Tables 6-5 to 6-9.
        An  advantage of this study  is that data are
provided for age  groups of less than one year.  A
limitation of this study is that data for individuals with
pre-existing medical conditions was lacking.

6.3.2    U.S. EPA, 2006  -  Metabolically-derived
        Human  Ventilation Rates:   A  Revised
        Approach   Based  Upon   Oxygen
        Consumption Rates
        U.S. EPA  (2006) conducted  a study  to
ascertain inhalation rates  for children and  adults.
Specifically, U.S. EPA sought to improve upon the
methodology used by Layton (1993) and other studies
that relied upon the ventilatory equivalent (VQ) and a
linear relationship between oxygen consumption and
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Chapter 6 - Inhalation Rates	
fitness rate.  A revised approach, developed by U.S.
EPA's  National   Exposure  Research  Laboratory
(NERL), was used, in which an individual's inhalation
rate  was derived  from his or her assumed  oxygen
consumption rate.   U.S. EPA  applied this  revised
approach using body weight data from the 1999-2002
National Health  and Nutrition  Examination  Survey
(NHANES)  and metabolic equivalents (METS) data
from U.S.  EPA's Consolidated  Human  Activity
Database (CHAD). In this database, metabolic cost is
given in units of "METS" or "metabolic equivalents of
work," an energy expenditure metric used by exercise
physiologists and  clinical nutritionists to  represent
activity levels.  An activity's METS value represents a
dimensionless  ratio  of its metabolic  rate  (energy
expenditure) to a person's resting, or basal metabolic
rate (BMR).
        NHANES provided age, gender, and body
weight data for 19,022 individuals from throughout the
United States.  From these data, basal metabolic rate
(BMR) was estimated using  an age-specific linear
equation used in the Exposure Factors Handbook (U. S.
EPA, 1997), and in several other studies and reference
works.
        The CHAD database  is  a compilation of
several databases of human activity patterns. U.S. EPA
used one of these studies, the National Human Activity
Pattern Survey (NHAPS), as its  source for METS
values because it was more representative of the entire
United States population than  the other studies in the
database.  The NHAPS data set included activity data
for 9,196 individuals, each of which provided 24 hours
of   activity   pattern   data   using  a   diary-based
questionnaire. While NHAPS was identified as the best
available data source for activity patterns, there were
some shortcomings in the quality of the data.  Study
respondents  did not provide  body weights; instead,
body weights are simulated using statistical sampling.
Also, the NHAPS data extracted from CHAD could not
be corrected to account for non-random sampling of
study participants and survey days.
        NHANES and NHAPS data were grouped into
age categories using the standardized age categories
presented elsewhere  in  this  handbook,  with  the
exception that children under the age of one year were
placed into a single category to preserve an adequate
sample size within the category.  For each NHANES
participant, a "simulated" 24-hour activity pattern was
generated by randomly sampling activity patterns from
the set of NHAPS participants with the same gender
and age category as the NHANES participant. Twenty
such  patterns  were  selected  at  random  for  each
NHANES  participant,  resulting  in  480  hours of
simulated activity data for each NHANES participant.
The data were then scaled down  to a 24-hour time
frame to yield an average 24-hour  activity pattern for
each of the 19,022 NHANES individuals.
        Each activity was assigned a METS value
based  on  statistical  sampling of the  distribution
assigned  by CHAD to each activity code.  For most
codes, these distributions were not  age-dependent, but
age was a factor for some activities for which intensity
level  varies strongly with  age.   Using  statistical
software,  equations  for  METS  based  on normal,
lognormal,  exponential,   triangular,   and  uniform
distributions were generated as needed for the various
activity codes.  The METS values were then translated
into energy expenditure (EE) by multiplying the METS
by  the basal  metabolic rate (BMR),  which  was
calculated as a linear function of body weight.   The
oxygen consumption rate  (V02) was  calculated by
multiplying EE by H,  the volume of oxygen consumed
per unit of energy.  V02 was calculated both as volume
per time and as volume per time per unit body weight.
        The inhalation rate for each activity within the
24-hour simulated activity pattern for each individual
was estimated as a function of V02, body weight, age,
and gender. Following this, the average inhalation rate
was calculated for each individual for the entire 24-hour
period, as well as for four separate classes of activities
based on METS value (sedentary/passive (METS less
than or equal to 1.5), light intensity (MET S greater than
1.5 and less than or equal to 3.0),  moderate intensity
(METS greater than 3.0 and less than or equal to 6.0),
and high  intensity (METS greater than 6.0). Data for
individuals were then used to generate summary tables
based on  gender and age categories.
        Data from this study are presented in Tables 6-
10 through 6-15. Tables 6-10 and 6-11  present, for
male  and  female  subjects, respectively,  summary
statistics  for daily average  inhalation rate by age
category  on a volumetric (mVday) and body-weight
adjusted  (m3/day-kg)  basis.   Table 6-12 presents the
mean  and 95th percentile values for males, females, and
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                                                       	Chapter 6 - Inhalation Rates
males and females combined.  Tables 6-13 and 6-14
present, for male and female  subjects, respectively,
mean ventilation rates by age category on a volumetric
(mVmin) and body-weight adjusted (mVmin-kg) basis
for the five different activity level ranges described
above. Table 6-15 presents the number of hours spent
per day at each activity level by males and females.
        An advantage of this study is the large sample
size.   In addition,  the  datasets used,  NHAPS and
NHANES,  are  representative of the  U.S.  general
population. Limitations are that the NHAPS data are 10
years old, there is variability in the 24-hour activity, and
there is uncertainly in the METs randomization, all of
which were noted by the  authors.

6.3.3   Arcus-Arth and Blaisdell, 2007 - Statistical
        Distributions of Daily Breathing Rates  for
        Narrow  Age  Groups  of  Infants and
        Children
        Arcus-Arth and Blaisdell (2007) derived daily
breathing rates for narrow age ranges of children using
the metabolic conversion method of Layton (1993) and
energy intake data adjusted to  represent the U.S.
population from the Continuing Survey of Food Intake
for Individuals (CSFII) 1994-1996,1998. Normalized
(mVkg-day) and  nonnormalized (mVday)  breathing
rates for children 0-18 years of age were derived using
the general equation developed by Layton (1993) to
calculate  energy-dependent  inhalation rates (see
Equation 6-2).
        VE = H x VQ x EE               (Eqn. 6-2)
where:
        VE =     volume of air breathed per day
                  (mVday);
        H  =     volume of oxygen  consumed  to
                  produce 1 kcal of energy (m3/kcal);
        VQ =     ratio of the volume of air to the
                  volume of oxygen breathed per unit
                  time (unitless); and
        EE =     energy (kcal) expended per day.

        Arcus-Arth and Blaisdell (2007) calculated H
values of 0.22 and 0.21  for  infants and noninfant
children, respectively, using the 1977-1978 NFCS and
CSFII data sets.  Ventilatory equivalent  (VQ) data,
 including those for infants, were obtained  from 13
 studies that reported VQ data for children aged 4-8
 ears. Separate preadolescent (4-8 years) and adolescent
 (9-18 years) VQ values were calculated in addition to
 separate VQ values for adolescent boys and girls.  Two-
 day-averaged daily energy intake (El) values reported
 in the CSFII data set were used a surrogate for EE.
 CSFII records that did not report body weight and those
 for children who consumed breast milk or were breast
 fed were excluded from their analyses.  The Els of
 children 9 years of age and older were multiplied by
 1.2, the value calculated by Layton (1993) to adjust for
 potential bias  related to underreporting of dietary
 intakes by older children. For infants, El values were
 adjusted by subtracting the amount of energy put into
 storage by infants as estimated by Scrimshaw  et al.
 (1996). Self-reported body weights for each individual
 from  the  CSFII  data  set  were used  to  calculate
 nonnormalized  (mVday) and normalized (m3/kg-day)
 breathing rates, which decreased the variability in the
 resulting breathing rate data. Daily breathing rates were
 grouped into three-month age  groups for infants, one-
 year age groups for children 1-18 years of age, and the
 age  groups recommended by  U.S. EPA cancer
 guidelines supplement (U.S. EPA, 2005) to receive
 greater weighting for mutagenic carcinogens (0 to < 2
 years of age, and 2 to < 16 years of age).  Data were
 also presented for adolescent boys and girls, aged 9-18
 years (Table 6-16). For each age and age-gender group,
 Arcus-Arth and  Blaisdell  (2007)   calculated the
 arithmetic mean, standard error of the mean, percentiles
 (50th,  90th,  and  95th),  geometric  mean,   standard
 deviation, and best-fit  parametric  models of the
 breathing rate distributions. Overall, the C SFII-derived
 nonnormalized breathing rates  progressively increased
 with age from infancy through 18 years of age, while
 normalized breathing rates  progressively decreased.
 The data are presented in Table 6-16 in units of mVday.
 There were statistical differences between boys and
 girls 9-18 years of age, both for these years combined
 (/KO.OO) and for each year of age separately (p<0.05).
 The  authors reasoned  that since the fat-free  mass
 (basically muscle  mass) of boys typically  increases
 during adolescence, and because fat-free mass is highly
 correlated to basal metabolism which accounts for the
 majority  of EE, nonnormalized  breathing rates for
 adolescent boys may  be expected to increase with
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Chapter 6 - Inhalation Rates	
increasing age.  Table 6-17 presents the mean and 95th
percentile values for males and females combined,
averaged to fit within the standard EPA age groups.
        The  CSFII-derived  mean breathing  rates
derived by Arcus-Arth and  Blaisdell  (2007)  were
compared to  the mean breathing  rates estimated in
studies  that utilized doubly  labeled water (DLW)
technique EE data that had been  coupled  with  the
Layton  (1993) method.  The infants' CSFII-derived
breathing rates were 15 to 27 percent greater than the
comparison  DLW  EE breathing  rates  while  the
children'sCSFII rates ranged from 23 percent less to 14
percent greater than comparison rates. Thus, the CSFII
and comparison rates were quite similar across  age
groups.
        An advantage of this study is that it provides
breathing rates specific to narrow age ranges, which can
be useful for assessing inhalation dose during periods of
greatest susceptibility. However, the study is limited by
the  potential  for misreporting, underestimating,  or
overestimating of food intake data  in the CSFII.   In
addition to  underreporting   of   food  intake  by
adolescents, El values  for younger children may be
under- or overestimated. Overweight children (or their
parents) may also underreport food intakes. In addition,
adolescents who misreport food intake may have also
misreported body weights.

6.3.4    Stifelman, 2007  - Using Doubly-labeled
        Water  Measurements of Human Energy
        Expenditure to Estimate Inhalation Rates
        Stifelman (2007)  estimated inhalation rates
using DLW energy data. The DLW method administers
two  forms  of  stable isotopically labeled water:
deuterium-labeled (2H20) and 18oxygen-labeled (H2180).
The difference in disappearance rates between the two
isotopes represents the energy expended over a period
of 1-3 half-lives of the labeled water (Stifelman, 2007).
The resulting duration of observation is typically 1-3
weeks, depending on the size and activity level.
        The  DLW  database  contains subjects from
areas  around  the world and  represents diversity in
ethnicity, age, activity, body  type,  and fitness  level.
DLW data have been  compiled by the Institute of
Medicine (IOM) Panel on Macronutrients and the Food
and Agriculture  Organization of the United Nations
(FAO).  Stifelman (2007) used the equation of Layton
(1993) to convert the recommended energy levels of
IOM  for  the  active-very  active  people  to  their
equivalent  inhalation  rates.    The  IOM  reports
recommend energy  expenditure levels organized by
gender, age and body size (Stifelman, 2007).
        The equivalent inhalation rates are shown in
Table 6-18. Shown in Table 6-19 are the mean and 95th
percentile  values for the  IOM "active" energy level
category, averaged to fit within the standard EPA age
groups. Stifelman (2007) noted that the estimates based
on the DLW are consistent with previous findings of
Layton (1993) and  the Exposure Factors Handbook
(U.S. EPA, 1997) and that inhalation rates based on the
IOM active classification are consistent with the mean
inhalation rate in the handbook.
        The  advantages  of this study are  that the
inhalation  rates were estimated using the DLW data
from a large data set.  Stifelman (2007) noted that DLW
methods  are advantageous;  the  data  are  robust,
measurements are direct and avoid errors associated
with indirect measurements (heart rate),  subjects are
free-living, and the period of observation is longer than
what  is  possible  from  staged  activity measures.
Observations  over a longer period of time reduce the
uncertainties  associated with  using  short  duration
studies to infer long-term inhalation rates.  A limitation
with the  study  is that  the  inhalation  rates  that are
presented are for active/very active persons only.

6.3.5    Key Studies Combined
        In order to provide the recommended long-
term inhalation rates shown in Table 6-1, data from the
four key studies were combined. The data from each
study were averaged by  gender and grouped according
to the standard U. S. EPA childhood age groups used in
this handbook, when possible. Mean and 95thpercentile
inhalation rate values for the four key studies are shown
in Tables 6-20 and 6-21, respectively.

6.4      RELEVANT    INHALATION   RATE
        STUDIES
6.4.1    International  Commission on Radiological
        Protection (ICRP),  1981 - Report of the
        Task Group on Reference Man
        The International Commission on Radiological
Protection (ICRP) (1981)  estimated daily inhalation
rates for reference children (10 years old), infants (1
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                                                        	Chapter 6 - Inhalation Rates
year old), and newborn babies by using a time-activity-
ventilation approach. This approach for estimating an
inhalation rate  over a specified  period of time was
based  on calculating  a  time  weighted  average  of
inhalation rates associated with physical activities of
varying durations (Table 6-22).  ICRP( 1981) compiled
reference   values   (Table  6-23)  of   minute
volume/inhalation rates from various literature sources.
ICRP (1981) assumed that the daily activities of a
reference child (10 yrs) consisted of 8 hours of rest and
16 hours of light activities.  It was assumed that a day
consisted of 14 hours resting and 10 hours light activity
for an infant (1 year).  A  newborn's daily  activities
consisted of 23  hours resting and  1 hour light activity.
The estimated inhalation rates were  14.8 mVday for
children (age 10 years), 3.76 mVday for infants (age 1
year), and 0.78 mVday for newborns (Table 6-22).
        A limitation associated with this study is that
the validity  and accuracy of the inhalation rate data
used in the compilation of reference values were not
specified.  This introduces some degree of uncertainty
in the results obtained.   Also,  the approach  used
required that assumptions be made regarding the hours
spent  by  various  age/gender cohorts in  specific
activities.  These assumptions may over/under-estimate
the inhalation rates obtained.

6.4.2    U.S. EPA, 1985 - Development of Statistical
        Distributions  or  Ranges  of  Standard
        Factors Used in Exposure Assessments
        The U.S. EPA  (1985)  compiled measured
values of minute ventilation for various age/gender
cohorts from early studies.  The data compiled by the
U.S. EPA (1985) for each age/gender cohorts were
obtained at various activity levels (Table 6-24). These
levels were  categorized as  light, moderate,  or heavy
according to the criteria developed by the U.S. EPA
Office of Environmental  Criteria and Assessment for
the Ozone Criteria Document.  These criteria were
developed for  a reference  male  adult with a body
weight of 70 kg (U.S. EPA,  1985).
        Table 6-24 presents a  summary of inhalation
rates  by age and  activity  level.   A description  of
activities  included  in each activity level  is  also
presented in Table 6-24.  Table 6-24 indicates that at
rest, the mean inhalation rate for children, ages 6 and 10
years, is 0.4 m3/hr. Table 6-25 presents activity pattern
 data aggregated for three microenvironments by activity
 level for all age groups. The total average hours spent
 indoors was 20.4,  outdoors  was  1.77, and in  a
 transportation vehicle was  1.77.  Based on the data
 presented in Tables  6-24 and 6-25, a daily inhalation
 rate was calculated for adults and children by using a
 time-activity-ventilation  approach.  These  data  are
 presented for children in Table 6-26. The average daily
 inhalation rate for 6  and 10 years old children is 16.74
 and 21.02 mVday, respectively.
         Limitations associated with this study are its
 age and that many of the values used in  the data
 compilation were from early  studies.  The  accuracy
 and/or validity of the values used and data collection
 method were not presented in U.S. EPA (1985). This
 introduces  uncertainty in the results obtained.   An
 advantage of this study is that the data are actual
 measurement data for a large number of children.

 6.4.3    Linn et al., 1992  - Documentation  of
         Activity Patterns in "High-risk" Groups
         Exposed to Ozone in the Los Angeles Area
         Linn  et  al. (1992) conducted a study that
 estimated   the  inhalation  rates  for   "high-risk"
 subpopulation groups exposed to ozone in their daily
 activities in the  Los Angeles area.  The population
 surveyed consisted of several panels of children. The
 panels included Panel 2:  17 healthy elementary school
 students (5 males and 12 females, ages 10-12 years);
 Panel 3:19 healthy  high school  students (7 males and
 12 females, ages 13-17 years); Panel 6:  13 young
 asthmatics (7 males  and 6 females, ages 11-16 years).
         An initial  calibration  test was  conducted,
 followed by a training session.  Finally, a field study
 that involved the subjects  collecting their own heart
 rates  and diary  data was  conducted.   During  the
 calibration tests,  ventilation rate (VR), breathing rate,
 and heart rate (HR)  were measured simultaneously at
 each exercise level.  From the calibration  data  an
 equation was developed using linear regression analysis
 to predict VR from measured HR.
         In the field study, each subject recorded in
 diaries their daily  activities,  change  in locations
 (indoors, outdoors,  or in  a vehicle),  self-estimated
 breathing rates during each activity/location, and time
 spent  at each  activity/location.   Healthy  subjects
 recorded their HR once every 60 seconds using a Heart
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Chapter 6 - Inhalation Rates	
Watch, an automated system consisting of a transmitter
and receiver worn on the body.   Asthmatic subjects
recorded their  diary  information once every hour.
Subjective breathing  rates  were  defined as  slow
(walking at their normal pace), medium (faster than
normal  walking),  and  fast  (running  or  similarly
strenuous exercise). Table 6-27 presents the calibration
and field protocols for self-monitoring of activities for
each subject panel.
        Table 6-28 presents the mean, 99th percentile,
and mean VR at each subjective activity level (slow,
medium, fast). The mean and 99th percentile VR were
derived from all HR recordings  that appeared to be
valid, without considering the diary data. Each of the
three  activity levels was determined from both the
concurrent diary data and HR recordings  by direct
calculation or regression.  The authors reported that the
diary  data showed  that  on  a  typical  day,  most
individuals spent most of their time indoors  at  slow
activity level. During slow activity, asthmatic subjects
had higher VRs than healthy subjects (Table 6-28). The
authors also reported that in every panel the predicted
VR  correlated  significantly  with  the  subjective
estimates of activity levels.
        A limitation of this study is that calibration
data may overestimate the predictive power of HR
during actual field monitoring.   The wide variety of
exercises in everyday  activities may result in greater
variation  of the  VR-HR  relationship  than   was
calibrated.  Another limitation is the  small sample size
of each subpopulation surveyed.  An advantage of this
study is that diary data can provide rough estimates of
ventilation patterns which are  useful  in  exposure
assessments. Another advantage is that inhalation rates
were presented for both healthy and asthmatic children.

6.4.4    Spier  et aL, 1992 - Activity Patterns in
        Elementary  and High School  Students
        Exposed to Oxidant Pollution
        Spier et al. (1992)  investigated the  activity
patterns of 17 elementary school students (10-12 years
old) and  19 high school  students  (13-17 years old) in
suburban Los Angeles from late September to October
(oxidant  pollution season).   Calibration tests  were
conducted in supervised outdoor exercise sessions. The
exercise sessions consisted of 5 minutes each of rest,
slow walking, jogging, and fast walking. HR and VR
were  measured during  the  last 2 minutes  of each
exercise. Individual VR and HR relationships for each
individual were determined by fitting a regression line
to HR values and log VR values. Each subj ect recorded
their daily activities, changes in location, and breathing
rates in diaries for 3 consecutive days.  Self-estimated
breathing rates were recorded as slow (slow walking),
medium  (walking  faster than  normal), and fast
(running). HR was recorded once per minute during the
3 days using a Heart Watch.  VR values for each self-
estimated  breathing rate  and  activity  type were
estimated from the HR recordings by employing the VR
and HR equation obtained from the calibration tests.
        The data presented in Table 6-29 represent HR
distribution patterns and corresponding predicted VR
for each age group during hours spent awake. At the
same self-reported activity levels for both age groups,
inhalation rates were higher for outdoor activities than
for indoor activities.  The total number of hours spent
indoors  was   higher   for  high  school   students
(21.2 hours) than for elementary school students (19.6
hours).  The converse was true for outdoor activities:
2.7 hours  for high  school students and 4.4 hours for
elementary school students (Table 6-30).
        A limitation of this study is the small sample
size.   The results  may not  be representative of  all
children in these age groups.  Another limitation is that
the accuracy  of the self-estimated breathing rates
reported by younger age groups is uncertain. This may
affect  the validity  of  the data  set generated.   An
advantage of this study is that  inhalation rates were
determined for children and  adolescents.  These data
are useful in  estimating exposure for  the  younger
population.

6.4.5    Adams, 1993 - Measurement of Breathing
        Rate and Volume in Routinely Performed
        Daily Activities, Final Report
        Adams    (1993)  conducted  research  to
accomplish two main objectives: (1) identification of
mean  and ranges   of  inhalation rates for  various
age/gender cohorts and specific activities,  and (2)
derivation of simple linear  and multiple regression
equations that could be used to predict inhalation rates
through other measured variables: breathing frequency
and oxygen consumption.  A total of 160  subjects
participated in the primary study.  For children, there
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were two age-dependent groups:  children 6 to 12.9
years old and adolescents 13 to 18.9 years old.  An
additional 40 children from 6 to  12.9 years old and
12 young children from  3 to  5.9 years old were
identified as subjects for pilot testing purposes.
        Resting protocols conducted in the laboratory
for all age groups consisted of three phases (25 minutes
each) of lying, sitting, and standing.  The phases were
categorized as resting and sedentary activities. Two
active  protocols— moderate (walking)  and heavy
(jogging/  running)  phases— were performed on  a
treadmill over a progressive continuum of intensity
levels made up of 6-minute intervals at three speeds
ranging from slow to  moderately  fast. All protocols
involved measuring VR, HR, fB (breathing frequency),
and V02  (oxygen consumption). Measurements were
taken in the last 5 minutes of each  phase of the resting
protocol and the last 3 minutes of the 6-minute intervals
at each speed designated in the active protocols.
        In  the   field,   all  children   completed
spontaneous  play  protocols; most protocols were
conducted for 30 minutes. All the active field protocols
were conducted twice. Results are shown in Tables 6-
31 and 6-32.
        During all activities in either the laboratory or
field protocols, VR for the children's group revealed no
significant gender  differences.  Therefore, VR data
presented in  Tables 6-33  and 6-34 were categorized by
activity type (lying, sitting, standing, walking, and
running) for young children and children without regard
to gender. These categorized data from Tables 6-33
and 6-32  are summarized as inhalation rates in Tables
6-31 and 6-32. The laboratory protocols are shown in
Table 6-31.  Table 6-32  presents the mean inhalation
rates by group and for moderate activity levels in field
protocols. Data were not provided for the light and
sedentary activities because the group did not perform
for this protocol or the  number of subjects  was  too
small  for  appropriate  comparisons.     Accurate
predictions of inhalation rates across all population
groups and activity types were obtained by including
body surface area (S A), HR, and breathing frequency in
multiple regression analysis (Adams, 1993).  Adams
(1993) calculated SA from measured height and body
weight using the equation:
 SA = Height(0725) x Weight(0425)  x 71.84  (Eqn. 6-3)
         A limitation associated with this study is that
 the population  does not represent the general  U.S.
 population.  Also, the classification of activity types
 (i.e., laboratory  and field protocols) into activity levels
 may bias  the inhalation rates obtained for various
 age/gender cohorts. The estimated rates were based on
 short-term data and may not reflect long-term patterns.

 6.4.6   Layton, 1993 - Metabolically Consistent
         Breathing  Rates  for   Use   in   Dose
         Assessments
         Layton (1993)  presented  a method  for
 estimating metabolically consistent inhalation rates for
 use  in  quantitative  dose assessments  of airborne
 radionuclides.  Generally, the approach for  estimating
 the breathing rate for a specified time frame was to
 calculate a time-weighted-average of ventilation  rates
 associated with physical activities of varying durations.
 However, in this study, breathing rates were calculated
 on the basis of oxygen consumption associated  with
 energy expenditures for short (hours) and long (weeks
 and  months) periods of time,  using the  following
 general  equation   to  calculate  energy-dependent
 inhalation rates:
     VE =ExHxVQ
                          (Eqn. 6-4)
 where:
    VE =
    E  =
    H  =
    VQ =
ventilation rate (mVmin or
mVday);
energy expenditure rate;
[kilojoules/minute (KJ/min) or
megajoules/hour (MJ/hr)];
volume of oxygen (at standard
temperature and pressure, dry air
consumed in the production of 1
kilojoule (KJ) of energy expended
(L/KJ or m3/MJ)); and
ventilatory equivalent (ratio of minute
volume (mVmin) to oxygen uptake
(mVmin)) unitless.
Page
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Chapter 6 - Inhalation Rates	
        Layton (1993) used two alternative approaches
to estimate daily chronic (long term) inhalation rates for
different age/gender cohorts of the U.S. population
using this methodology.

        First Approach
        Inhalation rates were estimated by multiplying
average  daily  food  energy  intakes  for  different
age/gender cohorts,  H,  and  VQ,  as shown  in the
equation above.  The average food energy intake data
(Table  6-35)  are  based on approximately  30,000
individuals and were  obtained  from  the  1977-78
USDA-NFCS. The food energy intakes were adjusted
upwards by a constant factor of 1.2 for all individuals
9 years and older.   This factor compensated for a
consistent bias in USDA-NFCS that was attributed to
under-reporting of the foods consumed or the methods
used to ascertain dietary intakes. Layton (1993) used a
weighted average oxygen uptake of 0.05 L 02/KJ which
was  determined from data reported in the 1977-78
USDA-NFCS and the second NHANES (NHANESII).
The survey sample for NHANES II was approximately
20,000  participants.   A  VQ of 27  used  in  the
calculations was calculated  as the geometric mean of
VQ data that were obtained from several studies.
        The inhalation rate estimation techniques are
shown in footnote  (a) of Table 6-36.  Table  6-37
presents the daily inhalation rate  for each age/gender
cohort.   The  highest daily  inhalation rates were  10
mVday for children between the ages of 6 and 8 years,
17 mVday for males between 15 and 18 years,  and 13
mVday for females between 9 and 11 years. Inhalation
rates were  also calculated  for  active and inactive
periods for the various age/gender cohorts.
        The inhalation rate for inactive periods was
estimated by multiplying the BMR times H times VQ.
BMR was defined as "the minimum amount  of energy
required to support basic cellular respiration while at
rest and not actively digesting food"  (Layton,  1993).
The inhalation rate for active periods was calculated by
multiplying the inactive inhalation rate by the ratio of
the rate of energy expenditure during active hours to the
estimated BMR. This ratio is presented as F in Table 6-
36. These data for active and inactive inhalation rates
are also presented in Table 6-36. For children, inactive
and active inhalation rates ranged from 2.35 to 5.95
mVday and from 6.35 to 13.09 mVday, respectively.

        Second Approach
        Inhalation rates were calculated as the product
of the BMR of the population cohorts, the ratio of total
daily  energy expenditure to daily BMR, H, and VQ.
The  BMR data obtained from the literature were
statistically analyzed,  and regression equations were
developed to predict BMR from  body weights  of
various age/gender cohorts. The statistical data used to
develop the regression equations are presented in Table
6-37.  The data obtained from the second approach are
presented in Table 6-38.  Inhalation rates for children
(6 months -10 years) ranged from 7.3 to 9.3 mVday for
male  and 5.6 to 8.6 mVday for female children; for
older children (10 to 18 years), inhalation rates were 15
mVday for males and 12 mVday for females.  These
rates are similar to the daily inhalation rates obtained
using the first approach. Also,  the inactive inhalation
rates obtained from the first approach are lower than the
inhalation rates obtained using the second approach.
This may be attributed to the BMR multiplier employed
in the equation of the  second  approach to calculate
inhalation rates.
        Inhalation rates were also obtained for short-
term exposures for various age/gender cohorts and five
energy-expenditure  categories  (rest, sedentary, light,
moderate, and heavy).  BMRs were multiplied by the
product of the metabolic equivalent, H, and VQ. The
data obtained for short-term exposures are presented in
Table 6-39.
        This study obtained similar results using two
different approaches. The maj or strengths of this study
are  that it estimates inhalation rates  in different age
groups and that the populations are large. Explanations
for   differences  in   results   due  to   metabolic
measurements, reported diet, or activity patterns are
supported  by   observations   reported  by   other
investigators in other studies. Major limitations of this
study  are (1) the estimated activity pattern levels are
somewhat subjective; (2) the explanation that activity
pattern differences are responsible for the lower level
obtained with the metabolic approach (25 %) compared
to the activity pattern approach is not well supported by
the  data; and (3) different populations were used in
each approach, which may have introduced error.
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                                                        	Chapter 6 - Inhalation Rates
6.4.7   Rusconi et al., 1994 - Reference Values for
        Respiratory Rate in the First 3 Years of
        Life
        Rusconi et al. (1994) examined a large number
of infants and children in Milano, Italy in  order to
determine the reference values for respiratory rate in
children aged 15 days to 3 years. A total of 618 infants
and children (336 males and 282 females) who did not
have respiratory infections or any severe disease were
included in the study. Of the 618, a total of 309 were in
good health and were observed in day care centers,
while the remaining 309 were seen in hospitals or as
outpatients.
        Respiratory rates were recorded twice, 30 to
60 minutes apart, listening to breath sounds for 60
seconds with a stethoscope, when the child was awake
and calm and when the child was sleeping quietly (sleep
not  associated  with  any  spontaneous  movement,
including eye movements or vocalizations) (Table 6-
40). The children were assessed for one year in order to
determine the  repeatability  of the recordings,  to
compare respiratory rate counts obtained by stethoscope
and  by  observation,  and  to  construct  reference
percentile curves by age in a large number of subjects.
        The authors plotted the differences  between
respiratory rate counts determined by stethoscope at 30-
to 60-minute intervals against  their mean count in
waking and sleeping subjects. The standard deviation
of the differences between the two counts was 2.5 and
1.7   breaths/minute,  respectively, for  waking and
sleeping children.  This standard deviation yielded 95%
repeatability coefficients of 4.9 breaths/minute when the
infants and children were awake and 3.3 breaths/minute
when they were asleep.
        In both  waking and  sleeping  states,  the
respiratory rate counts determined by stethoscope were
found to be higher than those obtained by observation.
The  mean  difference was  2.6  and  1.8 breaths per
minute, respectively, in waking and sleeping states. The
mean respiratory rate counts were  significantly higher
in infants and children at all ages when awake and calm
than when asleep. A decrease in respiratory rate with
increasing age was seen in waking and sleeping infants
and  children. A scatter diagram  of  respiratory rate
counts  by age in waking and sleeping subjects showed
that the pattern of respiratory rate decline with age was
similar in both states, but it was much faster in the first
 few months of life. The authors constructed centile
 curves by  first log-transforming the  data  and then
 applying a second degree polynomial curve, which
 allowed excellent fitting to observed data. Figures 6-1
 and 6-2 show smoothed percentiles by age in waking
 and sleeping subjects, respectively.  The variability of
 respiratory rate among subjects was higher in the first
 few months of life, which may be  attributable to
 biological events that occur during these months, such
 as maturation of the neurologic control of breathing and
 changes in lung and chest wall compliance and lung
 volumes.
         An advantage of this study is that it provides
 distribution data for respiratory rate for children from
 infancy (less than 2 months) to 36 months old. These
 data are not U.S.  data; U.S. distributions  were not
 available.  Although, there is no reason to believe that
 the  respiratory rates for Italian children  would  be
 different from that of U.S. children, this study only
 provided data for a narrow range of activities.

 6.4.8    Price et al., 2003 - Modeling Interindividual
         Variation in Physiological Factors Used in
         PBPK Models of Humans
         Price  et al. (2003) developed a database of
 values for physiological parameters  often  used in
 physiologically-based pharmacokinetic models (PBPK).
 The  database  consisted of approximately  31,000
 records containing information on volumes and masses
 of selected organs and tissues, blood flows for the organ
 and tissues, and total resting cardiac output and average
 inhalation rates. Records were created based on data
 from the NHANES III survey.
         The  study authors  note that the  database
 provides a source of data for  human physiological
 parameters were the parameter values for an individual
 are   correlated  with  one   another   and  capture
 interindividual  variation in populations of a specific
 gender, race, and age range.  A computer  program,
 Physiological Parameters for PBPK Modeling (PPPM
 or P3M),  which is publicly available (The Lifeline
 Group, 2007), was also developed to randomly retrieve
 records from the database for groups of individuals of
 specified age ranges, gender, and ethnicities.  Price et
 al. (2003)  recommends that output sets be used as
 inputs  to  Monte  Carlo-based  PBPK models  of
 interindividual variation in dose.
Page
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  Chapter 6 - Inhalation Rates	
  6.5
REFERENCES FOR CHAPTER 6
  Adams, W.C. (1993) Measurement of breathing rate
          and volume in routinely performed daily
          activities,  Final  Report.  California  Air
          Resources Board  (CARB)  Contract  No.
          A033-205June 1993. 185 pgs.
  Arcus-Arth, A. and Blaisdell, R. J. (2007) Statistical
          distributions  of daily breathing rates for
          narrow age groups of infants and children.
          Risk Anal 27(1):97-110
  Brochu, P.; Ducre-Robitaille,  J.; Brodeur, J.  (2006)
          Physiological daily inhalation rates for free-
          living individuals aged 1 month to 96 years,
          using  data  from  doubly  labeled  water
          measurements:  a  proposal for  air  quality
          criteria, standard calculations and  health risk
          assessment.  Hum Ecol Risk Assess 12:675-
          701.
  FASEB/LSRO (Federation of American Societies for
          Experimental Biology, Life Sciences Research
          Office).  (1995) Joint policy  on variance
          estimation  and  statistical   standards  on
          NHANES III and CSFII reports (Appendix
          III).  In:  Third   Report  on  Nutrition
          Monitoringin the United States. Prepared for
          the   Interagency   Board  for  Nutrition
          Monitoring   and   Related   Research.
          Washington, DC: U.S. Government Printing
          Office.
  Foos, B., Sonwane, B. (2008) Overview: workshop on
          children's inhalation dosimetry  and  health
          effects for risk assessment.  JToxicol Environ
          Health Part A 71(3): 147-148.
  Foos, B.;  Marty, M.;  Schwartz,  J.; Bennett,  W.;
          Moya, J.;  Jarabek, A; Salmon,  A.   (2008)
          Focusing on children's inhalation dosimetry
          and health effects  for risk  assessment: an
          introduction. J Toxicol Environ Health Part A
          71(3):149-165.
International Commission on  Radiological Protection.
          (1981) Report of the task group on reference
          man. New York: Pergammon Press.
  Layton, D.W.    (1993) Metabolically  consistent
          breathing rates  for use in  dose assessments.
          Health Phys 64(l):23-36.
Linn, W.S.; Shamoo, D.A.; Hackney,  J.D.  (1992)
        Documentation of activity patterns in "high-
        risk" groups exposed to ozone  in the Los
        Angeles  area.  In:   Proceedings  of  the
        Second   EPA/A WMA   Conference   on
        Tropospheric Ozone, Atlanta, Nov.  1991.
        pp. 701-712. Air and Waste Management
        Assoc., Pittsburgh, PA.
Price,  P.;  Conolly,  R.;  Chaisson,  C.;  Gross,  E.;
        Young,  J.;  Mathis,  E.; Tedder, D.  (2003)
        Modeling   interindividual   variation   in
        physiological factors used in PBPK models
        of humans.  Crit Rev Toxicol 33 (5):469-
        503.
Rusconi, F.; Castagneto, M.; Garliardi, L.; Leo,  G.;
        Pellegatta, A.; Porta, N.; Razon, S.; Braga, M.
        (1994) Reference values for respiratory rate in
        the first 3 years of life.  Pediatrics 94(3):350-
        355.
Scrimshaw, N. S.; Waterlow, J. C.; Schurch, B. (Eds.).
        (1996) Energy  and Protein Requirements.
        Proceedings of an International Dietary and
        Energy Consultancy Group Workshop; 1994
        Oct 31-Nov 4; London, UK: Stockton Press.
Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson, T.R.;
        Linn,  W.S.; Hackney,  J.D.  (1992) Activity
        patterns   in elementary  and  high  school
        students exposed to oxidant pollution. J Exp
        Anal Environ Epidemiol 2(3):277-293.
  Stifelman, M.  (2007)  Using doubly-labeled water
        measurements of human energy expenditure to
        estimate inhalation rates.  Sci Total Environ
        373:585-590.
 The Lifeline Group. (2007) Physiological parameters
        for PBPK modeling™ version 1.3 (P3M™).
        Accessed   May  2007.     Available  at:
        http://www.thelifelinegroup.org/p3iii/
  U.S.  EPA.   (1985)  Development  of statistical
        distributions or ranges of standard factors used
        in exposure assessments.  Washington, DC:
        Office  of  Health  and  Environmental
        Assessment;   EPA   Report   No.
        EPA 600/8-85-010.  Available from:  NTIS,
        Springfield, VA; PB85-242667.
     U.S.  EPA.   (1992)  Guidelines  for exposure
        assessment.  Washington, DC: Office of
  Child-Specific Exposure Factors Handbook
  September 2008	
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                                                     Child-Specific Exposure Factors Handbook

                                                    	Chapter 6 - Inhalation Rates
        Research and Development, Office of Health
        and Environmental Assessments.
U.S. EPA. (1994) Methods for derivation of inhalation
        reference concentrations and application of
        inhalation  dosimetry.    Washington,  DC:
        Office  of Health   and  Environmental
        Assessment. EPA/600/8-90/066F.
U.S. EPA.   (1997)  Exposure Factors Handbook.
        Washington, DC:  Office of Research and
        Development,   Office   of  Health   and
        Environmental Assessment.
        U.S. EPA. (2005). Supplemental guidance for
        assessing   susceptibility  from   early-life
        exposure to carcinogens.  Washington, DC:
        Risk  Assessment  Forum.    EPA/630/R-
        03/003F.
U.S.  EPA.  (2006) Metabolically-derived  human
        ventilation  rates: A revised approach based
        upon oxygen consumption rates. Washington,
        DC:  National  Center for  Environmental
        Assessment. External Review Draft. Prepared
        forUSEPA/ORD, ContractNo. EP-C-04-027.
U.S. EPA.  (2008)  Risk Assessment Guidance for
        Superfund:   Volume  I:  Human  Health
        Evaluation  Manual  (Part F, Supplemental
        Guidance for Inhalation Risk Assessment).
        Washington,  DC:  Office  of  Superfund
        Remediation and Technology Innovation.
        Peer Review Draft. Prepared for USEPA,
        ContractNo. 68-W-01-05.
WHO.  (1986) Principles for evaluating health risks
        from chemicals during  infancy  and  early
        childhood:  the need for a special approach.
        Environmental  Health  Criteria 59,  World
        Health Organization, International Programme
        on  Chemical Safety.
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Chapter 6 - Inhalation Rates	
                  Table 6-4. Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less
                                                                Physiological Daily Inhalation Rates6
         Group                  N      Body Weight (kg)  	Mean±SD	
         WOUp                  1N         MeaniSD     	
                                                               (mVday)              (m3/kg-day)
     21 days (3 weeks)           IS3-'         1.2 ±0.2           0.85±0.17f             0.74±0.09f
     32 days (~ 1 month)          10M         4.7 ± 0.7           2.45 ± 0.59s             0.53 ± 0.10s
     33 days (~ 1 month)	10'-"	4.8 ± 0.3	2.99 ± 0.47s	0.62 ±0.09S
     1       Formula-fed infants.
     b       Breast-fed infants.
     c       Healthy infants with very low birth weight.
     d       Infants evaluated as being clinically healthy and neither underweight or overweight.
     e       Physiological daily inhalation rates were calculated using the following equation: (TDEE +
            ECG)*H*(VE/V02)*10-3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily
            energy expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day).
     f       TDEEs based on nutritional balance measurements during 3-day periods.
     8       TDEEs based on 2H2O and H218O disappearance rates from urine

     N      =  Number of individuals.
     SD     =  Standard deviation.

     Source: Brochu et al., 2006.
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                                           	Chapter 6 - Inhalation Rates
Table 6-5. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living Normal-weight
Males and Females Aged 2.6 months to 23 years
Body Physiological Daily Inhalation Rates'" (mVday)
Age Group Weighf(kg) ...
, . v N f, Percentile0
±SD 5th 10th 25th 50th 75th 90th


95th


99th
Males
0.22to<0.5 32 6.7±1.0 3.38±0.72 2.19 2.46 2.89 3.38 3.87 4.30
0.5to
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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-6. Mean and 95th Percentile Inhalation Rate Values (mVday) for Free-living Normal-weight
Males, Females, and Males and Females Combined.
Age Group1
N
Mean
95th
Males
3 to <6 months'1
6 to <12 months
1 to <2 years
32
40
35
3.38
4.42
5.12
4.57
5.51
6.56
Females
3 to <6 months'1
6 to <12 months
1 to <2 years
53
63
66
3.26
3.96
4.78
4.36
5.14
6.36
Males and Females Combined
3 to <6 months'1
6 to <12 months
1 to <2 years
1 No other age groups from
b Age group from Brochu ei
N = Number of individuals.
Source: Brochu et al., 2006.
85
103
101
Table 6-5 (Brochu et al., 2006) fit into the
al. (2006) was 2.6 to <6 months.

3.32
4.09
4.95
U.S. EPA age groupings.

4.47
5.53
6.46


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                                                                	Chapter 6 - Inhalation Rates
    Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (mVday) for Free-living Normal-weight and Overweight/obese
                                             Males and Females Aged 4 to 18 years
    Age Group
     (years)
            BodyWeight'(kg)
                Mean ± SD
                                                             Physiological Daily Inhalation Rates" (mVday)
                                Mean ± SD
                                         Perc entile0
                                                           5th
                                                        10th
                               25th
                        50th
                        75th
                         90th
                         95th
                         99th
                                                   Males - Normal-weight
4to<5
5.1 to <
9.1 to <
                  77
                  52
                  36
                19.0 ± 1.9
                22.6 ±3.5
                41.4 ± 12.1
7.90 ± 0.97
9.14 ± 1.44
13.69 ±3.95
6.31
6.77
7.19
6.66
7.29
8.63
7.25
8.17
11.02
7.90
9.14
13.69
8.56
10.11
16.35
                                                                                                 9.15
                                                                                                10.99
                                                                                                18.75
                                                                                                         9.50    10.16
                                                                                                        11.51   12.49
                                                                                                        20.19   22.88
                                                  Males - Overweight/obese
4to<5
5.1 to-
9.1 to-
                  54
                  40
                  33
                         26.5 ±4.9
                         32.5 ±9.2
                        55.8± 10.8
                                9.59 ± 1.26
                                10.88 ±2.49
                                14.52 ± 1.98
               7.52
               6.78
               11.25
                        7.98
                        7.69
                       11.98
                8.74
                9.20
                13.18
                9.59
                10.88
                14.52
                10.44
                12.56
                15.85
                11.21
                14.07
                17.06
                11.66
                14.98
                17.78
                                                                                                                12.52
                                                                                                                16.68
                                                                                                                19.13
                                                   Females - Normal-weight
4to<5
5.1 to-
9.1 to-
                  82
                  151
                  124
                18.7 ±2.0
                25.5 ±4.1
                42.7± 11.1
 7.41 ±0.91
 9.39 ± 1.62
12.04  ±2.86
               5.92
               6.72
               7.34
        6.25
        7.31
        8.38
        6.80
        8.30
        10.11
        7.41
        9.39
        12.04
         8.02
        10.48
        13.97
         8.57
        11.47
        15.70
                                                                                                         8.90
                                                                                                        12.05
                                                                                                        16.74
                                                                                                                 9.52
                                                                                                                13.16
                                                                                                                18.68
                                                 Females - Overweight/obese
4to<5
5.1 to-
9.1 to <
                  56
                         26.1 ±5.5
                         34.6 ±9.9
                        59.2 ± 12.8
                                           8.70  ± 1.13
                                           10.55 ±2.23
                                           14.27 ±2.70
                                               6.84
                                               6.88
                                               9.83
                       7.26
                       7.69
                       10.81
                7.94
                9.05
                12.45
                8.70
                10.55
                14.27
                 9.47
                12.06
                16.09
                10.15
                13.41
                17.73
                10.56   11.33
                14.22   15.75
                18.71   20.55
  N
  SD
Measured body weight. Normal-weight and overweight/obese males defined according to the body mass index (BMI) cut-offs.
Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(VE/VO2)* 10"3, where H =
0.21 L of O2/Kcal, V/VO2= 27 (Layton,  1993), TDEE = total daily energy expenditure (kcal/day) and ECG = stored daily energy
cost for growth (kcal/day).
Percentiles based on a normal distribution assumption for age groups.
= Number of individuals.
= Standard deviation.
  Source:   Brochu et al.. 2006.
Page
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Chapter 6 - Inhalation Rates	
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight (mVkg-day) for Free-living
Normal-weight Males and Females Aged 2.6 months to 23 years
Age(
(ye

ars) Mean ± S
Physiological Daily Inhalation Rates
(mVkg-day)
Percentileb
D
5th
10th
25th
50th
75th
90th
95th
99th
Males
0.22 to <0
0.5to
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                                                        Chapter 6 - Inhalation Rates


Table 6-9.







Distribution Percentiles of Physiological Daily Inhalation Rates (m3/kg-day) for Free-living Normal-weight and
Overweight/obese Males and Females Aged 4 to 18 years
Physiological Daily Inhalation Rates"
(m3/k
g-day)



Age Group (years) Percentileb

Mean±SD 5th 1()th 25th 5Qto
75*
90*
95th
99th
Males - Normal-weight
4to<5.1
5.1to<9.1
9.1to<18.1
0.42 ±0.04 0.35 0.36 0.39 0.42
0.41 ±0.06 0.31 0.34 0.37 0.41
0.33 ±0.05 0.26 0.27 0.30 0.33
0.45
0.45
0.37
0.47
0.48
0.40
0.49
0.50
0.41
0
0
0
52
54
45
Males - Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
0.37 ±0.04 0.30 0.31 0.34 0.37
0.35 ±0.08 0.22 0.25 0.29 0.35
0.27 ±0.04 0.20 0.22 0.24 0.27
0.40
0.40
0.29
0.42
0.45
0.32
0.44
0.47
0.33
0
0
0
47
53
36
Females - Normal-weight
4to<5.1
5.1to<9.1
9.1to<18.1
0.40 ±0.05 0.32 0.34 0.37 0.40
0.37 ±0.06 0.27 0.29 0.33 0.37
0.29 ±0.06 0.20 0.22 0.25 0.29
0.43
0.41
0.33
0.46
0.45
0.36
0.48
0.47
0.38
0
0
0
51
52
42
Females - Overweight/obese
4to<5.1
5.1to<9.1
9.1to<18.1
0.34 ±0.04 0.27 0.28 0.31 0.34
0.32 ±0.07 0.21 0.23 0.27 0.32
0.25 ±0.05 0.17 0.18 0.21 0.25
0.37
0.36
0.28
0.40
0.40
0.31
0.41
0.43
0.33
0
0
0
44
47
36
" Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(VE/VO2)* 10"3,
where H = 0.21 L of O2/Kcal, V/VO2= 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) and ECG =
stored daily energy cost for growth (kcal/day).
b Percentiles based on a normal distribution assumption for age groups.
SD = Standard deviation.
Source: Brochu et al., 2006.

Page
6-22
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-10. Descriptive Statistics
for Daily Average Inhalation Rate in Males, by Age Category'
Daily Average Inhalation Rate, Unadjusted for Body Weight
(mVday)
Age Group
Birth to <1 year
lto<
2to<
2 years
3 years
3 to <6 years
6to<
11 to
16 to
1 1 years
<16 years
<21 years
Age Group
Birth to <1 year
1 to<
2to<
2 years
3 years
3 to <6 years
6to<
11 to
16 to
N
BW
11 years
<16 years
<21 years
N
419
308
261
540
940
1337
1241

N
419
308
261
540
940
1337
1241
Mean
8.76
13.49
13.23
12.65
13.42
15.32
17.22

Mean
1.09
1.19
0.95
0.70
0.44
0.29
0.23

5th
4.77
9.73
9.45
10.42
10.08
11.41
12.60


5th
0.91
0.96
0.78
0.52
0.32
0.21
0.17

10th
5.70
10.41
10.20
10.87
10.69
12.11
13.41
Daily Average

10th
0.94
1.02
0.82
0.56
0.34
0.22
0.18

25th
7.16
11.65
11.43
11.40
11.73
13.27
14.48
Percentiles
50th
8.70
13.11
13.19
12.58
13.09
14.79
16.63

75th
10.43
15.02
14.49
13.64
14.73
16.81
19.16

90th
11.93
17.03
16.27
14.63
16.56
19.54
21.94

95th
12.69
17.89
17.71
15.41
17.72
21.21
23.38
Maximum
17.05
24.24
28.17
19.52
24.97
28.54
39.21
Inhalation Rate, Adjusted for Body Weight
(m3/day-kg)

25th
1.00
1.09
0.87
0.61
0.38
0.25
0.20
Percentiles
50th
1.09
1.17
0.94
0.69
0.43
0.28
0.23

75th
1.16
1.26
1.01
0.78
0.50
0.32
0.25

90th
1.26
1.37
1.09
0.87
0.55
0.36
0.28

95th
1.29
1.48
1.13
0.92
0.58
0.38
0.30
Individual daily averages are weighted by their 4-year sampling weights as assigned within NHANES 1999-2002 when
the statistics in this table. Inhalation rate was estimated using a multiple linear regression model.
= Number of individuals.
Maximum
1.48
1.73
1.36
1.08
0.81
0.51
0.40
calculating
= Body weight.
Source: U.S. EPA,
2006.









Child-Specific Exposure Factors Handbook
September 2008	
Page
 6-23

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-11. Descriptive Statistics for Daily Average Inhalation Rate in Females, by A
je Category
»

Daily Average Inhalation Rate, Unadjusted for Body Weight
(mVday)
Age Group
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
N
415
245
255
543
894
1,451
1,182
Mean
8.53
13.31
12.74
12.16
12.41
13.44
13.59

5th
4.84
9.08
8.91
9.87
9.99
10.47
9.86

10th
5.48
10.12
10.07
10.38
10.35
11.11
10.61

25th
6.83
11.24
11.38
11.20
11.01
12.04
11.78
Percentiles
50th
8.41
13.03
12.60
12.02
11.95
13.08
13.20

75th
9.78
14.64
13.96
13.01
13.42
14.54
15.02

90th
11.65
17.45
15.58
14.03
15.13
16.25
17.12

95th
12.66
18.62
16.37
14.93
16.34
17.41
18.29
Maximum
26.26
24.77
23.01
19.74
20.82
26.58
30.11
Daily Average Inhalation Rate, Adjusted for Body Weight
(m3/day-kg)
Age Group
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
N
415
245
255
543
894
1,451
1,182
Mean
1.14
1.20
0.96
0.69
0.43
0.25
0.21

5th
0.91
0.98
0.82
0.48
0.28
0.19
0.16

10th
0.97
1.01
0.84
0.54
0.31
0.20
0.17

25th
1.04
1.10
0.89
0.60
0.36
0.22
0.19
a Individual daily averages are weighted by their 4-year sampling weights
the statistics in this table. Inhalation rate was estimated using a multiple
N = Number of individuals.
Source: U.S. EPA,
2006.




Percentiles
50th
1.13
1.18
0.96
0.68
0.43
0.25
0.21

75th
1.24
1.30
1.01
0.77
0.49
0.28
0.24

90th
1.33
1.41
1.07
0.88
0.55
0.31
0.27

95th
1.38
1.47
1.11
0.92
0.58
0.34
0.28
as assigned within NHANES 1999-2002 when
linear regression model.




Maximum
1.60
1.73
1.23
1.12
0.75
0.47
0.36
calculating

Page
6-24
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-12. Mean anc
Age Group"
95th Percentile Inhalation Rate Values (mVday) for Males, Females and
Males and Females Combined
N
Mean
95th
Males
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1,337
1,241
8.76
13.49
13.23
12.65
16.42
15.32
17.22
12.69
17.89
17.71
15.41
17.72
21.21
23.38
Females
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
415
245
255
543
894
1,451
1,182
8.53
13.31
12.74
12.16
12.41
13.44
13.59
12.66
18.62
16.37
14.93
16.34
17.41
18.29
Males and Females Combined
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
1 No other age groups from
N = Number of individuals.
Source: U.S. EPA, 2006.
834
553
516
1,083
1,834
2,788
2423
Tables 6-9 and 6-10 (U.S. EPA,

8.65
13.40
12.99
12.41
12.92
14.38
15.41
2006) fit into the EPA age

12.68
18.26
17.04
15.17
17.03
19.31
20.84
groupings.

Child-Specific Exposure Factors Handbook
September 2008	
Page
 6-25

-------
    i
    s

oo
Table 6-13. Descriptive Statistics for Average Ventilation Rate" While Performing Activities Within the Specified Activity Category, for
Males by Age Category
Age Group
Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
Percentiles
5th 10* 25th 50* 75th 90* 95th

Vlaximum
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
Mean
Percentiles
5th
10*
25th
50*
75th
90*
95*
Maximum
Sleep or nap (Activity ID = 14500)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
419 3.08E-03 1.66E-03 1.91E-03 2.45E-03 3.00E-03 3.68E-03 4.35E-03 4.77E-03
308 4.50E-03 3.11E-03 3.27E-03 3.78E-03 4.35E-03 4.95E-03 5.90E-03 6.44E-03
261 4.61E-03 3.01E-03 3.36E-03 3.94E-03 4.49E-03 5.21E-03 6.05E-03 6.73E-03
540 4.36E-03 3.06E-03 3.30E-03 3.76E-03 4.29E-03 4.86E-03 5.54E-03 5.92E-03
940 4.61E-03 3.14E-03 3.39E-03 3.83E-03 4.46E-03 5.21E-03 6.01E-03 6.54E-03
1,337 5.26E-03 3.53E-03 3.78E-03 4.34E-03 5.06E-03 5.91E-03 6.94E-03 7.81E-03
1,241 5.31E-03 3.55E-03 3.85E-03 4.35E-03 5.15E-03 6.09E-03 6.92E-03 7.60E-03
7.19E-03
l.OOE-02
8.96E-03
7.67E-03
9.94E-03
1.15E-02
1.28E-02
3.85E-04
3.95E-04
3.30E-04
2.43E-04
1.51E-04
9.80E-05
7.10E-05
2.81E-04
2.95E-04
2.48E-04
1.60E-04
1.02E-04
6.70E-05
4.70E-05
3.01E-04
3.13E-04
2.60E-04
1.74E-04
1.09E-04
720E-05
5.20E-05
3.37E-04
3.45E-04
2.89E-04
1.98E-04
1.25E-04
8.10E-05
6.10E-05
3.80E-04
3.84E-04
3.26E-04
2.37E-04
1.48E-04
9.40E-05
6.90E-05
4.27E-04
4.41E-04
3.62E-04
2.79E-04
1.74E-04
1.10E-04
8.00E-05
4.65E-04
4.91E-04
4.05E-04
3.14E-04
2.00E-04
1.29E-04
9.00E-05
5.03E-04
5.24E-04
4.42E-04
3.50E-04
2.15E-04
1.41E-04
9.80E-05
6.66E-04
6.26E-04
5.38E-04
4.84E-04
3.02E-04
2.08E-04
1.47E-04
Sedentary & Passive Activities (METS s 1.5 - Includes Sleep or Nap)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419 3.18E-03 1.74E-03 1.99E-03 2.50E-03 3.10E-03 3.80E-03 4.40E-03 4.88E-03
308 4.62E-03 3.17E-03 3.50E-03 3.91E-03 4.49E-03 5.03E-03 5.95E-03 6.44E-03
261 4.79E-03 3.25E-03 3.66E-03 4.10E-03 4.69E-03 5.35E-03 6.05E-03 6.71E-03
540 4.58E-03 3.47E-03 3.63E-03 4.07E-03 4.56E-03 5.03E-03 5.58E-03 5.82E-03
940 4.87E-03 3.55E-03 3.78E-03 4.18E-03 4.72E-03 5.40E-03 6.03E-03 6.58E-03
1,337 5.64E-03 4.03E-03 4.30E-03 4.79E-03 5.43E-03 6.26E-03 7.20E-03 787E-03
1,241 5.76E-03 4.17E-03 4.42E-03 4.93E-03 5.60E-03 6.43E-03 7.15E-03 776E-03
7.09E-03
9.91E-03
9.09E-03
7.60E-03
9.47E-03
1.11E-02
1.35E-02
3.97E-04
4.06E-04
3.43E-04
2.55E-04
1.60E-04
1.05E-04
7.70E-05
Light Intensity Activities (1.5 < METS
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419 7.94E-03 4.15E-03 5.06E-03 6.16E-03 7.95E-03 9.57E-03 1.08E-02 1.19E-0
308 1.16E-02 8.66E-03 8.99E-03 9.89E-03 1.14E-02 1.29E-02 1.44E-02 1.58E-0
261 1.17E-02 8.52E-03 9.14E-03 9.96E-03 1.14E-02 1.30E-02 1.47E-02 1.53E-0
540 1.14E-02 9.20E-03 9.55E-03 1.02E-02 1.11E-02 1.23E-02 1.34E-02 1.40E-0
940 1.16E-02 8.95E-03 9.33E-03 1.02E-02 1.13E-02 1.28E-02 1.46E-02 1.56E-0
1,337 1.32E-02 9.78E-03 1.03E-02 1.13E-02 1.28E-02 1.47E-02 1.64E-02 1.87E-0
1,241 1.34E-02 l.OOE-02 1.05E-02 1.15E-02 1.30E-02 1.50E-02 1.70E-02 1.80E-0
1.55E-02
2.11E-02
1.90E-02
1.97E-02
2.18E-02
2.69E-02
2.91E-02
9.88E-04
1.02E-03
8.37E-04
6.33E-04
3.84E-04
2.46E-04
1.79E-04
3.03E-04
3.21E-04
2.74E-04
1.78E-04
1.13E-04
7.70E-05
5.50E-05
<3.0)
786E-04
8.36E-04
6.83E-04
4.41E-04
2.67E-04
1.76E-04
1.37E-04
3.17E-04
3.31E-04
2.86E-04
1.93E-04
1.18E-04
8.00E-05
6.00E-05

8.30E-04
8.59E-04
7.16E-04
4.80E-04
2.86E-04
1.87E-04
1.44E-04
3.51E-04
3.63E-04
3.09E-04
2.15E-04
1.35E-04
8.80E-05
6.80E-05

8.97E-04
9.18E-04
7.61E-04
5.44E-04
3.24E-04
2.09E-04
1.56E-04
3.91E-04
3.97E-04
3.40E-04
2.50E-04
1.57E-04
1.01E-04
760E-05

9.72E-04
1.01E-03
8.26E-04
6.26E-04
3.77E-04
2.38E-04
1.78E-04
4.37E-04
4.48E-04
3.69E-04
2.88E-04
1.80E-04
1.18E-04
8.50E-05

1.07E-03
1.10E-03
8.87E-04
711E-04
4.37E-04
2.82E-04
1.99E-04
4.70E-04
4.88E-04
4.05E-04
3.27E-04
2.09E-04
1.35E-04
9.50E-05

1.17E-03
1.22E-03
9.95E-04
7.94E-04
4.93E-04
3.11E-04
2.18E-04
4.98E-04
5.25E-04
4.46E-04
3.46E-04
2.18E-04
1.42E-04
1.02E-04

1.20E-03
1.30E-03
1.03E-03
8.71E-04
5.29E-04
3.32E-04
2.30E-04
6.57E-04
6.19E-04
5.10E-04
4.54E-04
2.89E-04
1.95E-04
1.32E-04

1.44E-03
1.49E-03
1.18E-03
1.08E-03
709E-04
4.42E-04
3.32E-04
                                                                                                                                                                              Q

 ri

I
 1
 s
                                                                                                                                                                                      s
                                                                                                                                                                                      I

-------
"53
-•  p
»•*
ft
I
&
a
a.
 X|  ft
Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
Age Uroup JN
5th
Percentiles
10th 25th 50th 75th 90th 95th
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight

5th 1Qth
Percentiles
25th 50th 75th 90th

95^
                                 Table 6-13.  Descriptive Statistics for Average Ventilation Rate" While Performing Activities Within the Specified Activity Category, for
                                                                                           Males by Age Category (continued)
                                                                                          Moderate Intensity Activities (3.0 < METS f 6.0)
                  3irthto 6.0)
                  3irthto
-------
    ft
    i
    s

oo
Table 6-14. Descriptive Statistics for Average Ventilation Rate' While Performing Activities Within the Specified Activity Category, for Females by Age Category
Age Group
Average Ventilation Rate (mVmin),
N Unadjusted for Body Weight
Mean Percentiles
5* 10* 25* 50* 75* 90*
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight

95*
vlaximum Mean
Percentiles
5*
10*
25*
50*
75*
90*
95*
Vlaximum
Sleep or nap (Activity ID = 14500)
Jirthto <1 year
year
! years
i to <6 years
i to <11 years
1 to <16 years
6 to <2 1 years
415 2.92E-03 1.54E-03 1.72E-03 2.27E-03 2.88E-03 3.50E-03 4.04E-03
245 4.59E-03 3.02E-03 3.28E-03 3.76E-03 4.56E-03 5.32E-03 5.96E-03
255 4.56E-03 3.00E-03 3.30E-03 3.97E-03 4.52E-03 5.21E-03 5.76E-03
543 4.18E-03 2.90E-03 3.20E-03 3.62E-03 4.10E-03 4.71E-03 5.22E-03
894 4.36E-03 2.97E-03 3.17E-03 3.69E-03 4.24E-03 4.93E-03 5.67E-03
1,451 4.81E-03 3.34E-03 3.57E-03 3.99E-03 4.66E-03 5.39E-03 6.39E-03
1,182 4.40E-03 2.78E-03 2.96E-03 3.58E-03 4.26E-03 5.05E-03 5.89E-03
4.40E-03
6.37E-03
6.15E-03
5.73E-03
6.08E-03
6.99E-03
6.63E-03
8.69E-03
9.59E-03
9.48E-03
7.38E-03
8.42E-03
9.39E-03
1.23E-02
3.91E-04
4.14E-04
3.42E-04
2.38E-04
1.51E-04
9.00E-05
6.90E-05
2.80E-04
3.15E-04
2.58E-04
1.45E-04
8.90E-05
5.90E-05
4.40E-05
3.01E-04
3.29E-04
2.71E-04
1.63E-04
9.70E-05
6.50E-05
4.70E-05
3.35E-04
3.61E-04
2.93E-04
1.95E-04
1.20E-04
7.50E-05
5.70E-05
3.86E-04
4.05E-04
3.33E-04
2.33E-04
1.46E-04
8.70E-05
6.70E-05
4.34E-04
4.64E-04
3.91E-04
2.75E-04
1.76E-04
1.02E-04
8.00E-05
4.79E-04
5.21E-04
4.25E-04
3.20E-04
2.11E-04
1.18E-04
9.30E-05
5.17E-04
5.36E-04
4.53E-04
3.53E-04
2.29E-04
1.30E-04
1.02E-04
7.39E-04
6.61E-04
4.94E-04
5.19E-04
2.97E-04
1.76E-04
1.52E-04
Sedentary & Passive Activities (METS < 1.5 - Includes Sleep or Nap)
Jirthto <1 year
year
! years
i to <6 years
i to <11 years
1 to <16 years
6 to <2 1 years
415 3.00E-03 1.60E-03 1.80E-03 2.32E-03 2.97E-03 3.58E-03 4.11E-03
245 4.71E-03 3.26E-03 3.44E-03 3.98E-03 4.73E-03 5.30E-03 5.95E-03
255 4.73E-03 3.34E-03 3.53E-03 4.19E-03 4.67E-03 5.25E-03 5.75E-03
543 4.40E-03 3.31E-03 3.49E-03 3.95E-03 4.34E-03 4.84E-03 5.29E-03
894 4.64E-03 3.41E-03 3.67E-03 4.04E-03 4.51E-03 5.06E-03 5.88E-03
1,451 5.21E-03 3.90E-03 4.16E-03 4.53E-03 5.09E-03 5.68E-03 6.53E-03
1,182 4.76E-03 3.26E-03 3.56E-03 4.03E-03 4.69E-03 5.32E-03 6.05E-03
4.44E-03
6.63E-03
6.22E-03
5.73E-03
6.28E-03
7.06E-03
6.60E-03
9.59E-03
9.50E-03
9.42E-03
7.08E-03
8.31E-03
9.07E-03
1.18E-02
4.02E-04
4.25E-04
3.55E-04
2.51E-04
1.60E-04
9.70E-05
7.50E-05
Light Intensity Activities (1.5 < METS <
Jirthto <1 year
year
! years
S to <6 years
> to <11 years
1 to <16 years
6 to <2 1 years
415 7.32E-03 3.79E-03 4.63E-03 5.73E-03 7.19E-03 8.73E-03 9.82E-03
245 1.16E-02 8.59E-03 8.80E-03 l.OOE-02 1.12E-02 1.29E-02 1.52E-02
255 1.20E-02 8.74E-03 9.40E-03 1.03E-02 1.17E-02 1.32E-02 1.56E-02
543 1.09E-02 8.83E-03 9.04E-03 9.87E-03 1.07E-02 1.17E-02 1.29E-02
894 1.11E-02 8.51E-03 9.02E-03 9.79E-03 1.08E-02 1.20E-02 1.35E-02
1,451 1.20E-02 9.40E-03 9.73E-03 1.06E-02 1.18E-02 1.31E-02 1.47E-02
1,182 1.11E-02 8.31E-03 8.73E-03 9.64E-03 1.08E-02 1.23E-02 1.38E-02
1.08E-02
1.58E-02
1.63E-02
1.38E-02
1.47E-02
1.58E-02
1.49E-02
1.70E-02
2.02E-02
2.36E-02
1.64E-02
2.22E-02
2.21E-02
2.14E-02
9.78E-04
1.05E-03
8.97E-04
6.19E-04
3.82E-04
2.25E-04
1.74E-04
2.97E-04
3.35E-04
2.85E-04
1.64E-04
9.90E-05
7.10E-05
5.30E-05
3.0)
7.91E-04
8.45E-04
7.30E-04
4.48E-04
2.52E-04
1.63E-04
1.29E-04
3.16E-04
3.48E-04
2.96E-04
1.79E-04
1.10E-04
7.50E-05
5.70E-05

8.17E-04
8.68E-04
7.63E-04
4.84E-04
2.70E-04
1.74E-04
1.38E-04
3.52E-04
3.76E-04
3.20E-04
2.11E-04
1.31E-04
8.30E-05
6.30E-05

8.80E-04
9.49E-04
8.19E-04
5.37E-04
3.15E-04
1.96E-04
1.54E-04
3.96E-04
4.18E-04
3.48E-04
2.48E-04
1.57E-04
9.50E-05
7.40E-05

9.62E-04
1.04E-03
8.93E-04
5.99E-04
3.76E-04
2.17E-04
1.73E-04
4.46E-04
4.69E-04
3.91E-04
2.84E-04
1.85E-04
1.09E-04
8.50E-05

1.05E-03
1.14E-03
9.64E-04
6.98E-04
4.42E-04
2.49E-04
1.93E-04
4.82E-04
5.12E-04
4.20E-04
3.28E-04
2.12E-04
1.23E-04
9.60E-05

1.18E-03
1.25E-03
1.04E-03
7.83E-04
5.03E-04
2.84E-04
2.13E-04
5.19E-04
5.43E-04
4.42E-04
3.58E-04
2.34E-04
1.33E-04
1.04E-04

1.23E-03
1.27E-03
1.10E-03
8.28E-04
5.39E-04
3.05E-04
2.24E-04
7.19E-04
6.42E-04
4.85E-04
4.89E-04
2.93E-04
1.74E-04
1.41E-04

1.65E-03
1.64E-03
1.26E-03
1.02E-03
7.10E-04
3.96E-04
2.86E-04
                                                                                                                                                                              Q

 ri

I
 1
 s
                                                                                                                                                                                      s
                                                                                                                                                                                      I

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00
    ri
    1=
Table 6-14. Descriptive Statistics for Average Ventilation Rate* While Performing Activities Within the Specified Activity Category, for
Females by Age Category (continued)
N Average Ventilation Rate (mVmin),
Unadjusted for Body Weight
AgeCjroup
Mean Percentiles
5* 10th 25th 50* 75th 90th 95* Maxlmum
Average Ventilation Rate (m3/min-kg),
Adjusted for Body Weight
Mean Percentiles
5«, 1Q«, 25t 50«, 75«, 90«, 95* Maximum
Moderate Intensity Activities (3.0 < METS s 6.0)
5irthto 6.0)
5irthto
I
».
s
                                                                                                                                                                  I
                                                                                                                                                                   ri
       &
       &
       1=

-------
    i
    s

oo
Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category,
by Age and Gender Categories
Duration (hours/day) Spent at Activity - Males
AgeGroup
N
Mean

5* 10*
Percentiles
25th 50th

75th 90th


95* Maximum
N
Duration (hours/day) Spent at Activity - Females
Percentiles
Mean
5th
10th 25th
50th 75th
90th 95th
Vlaximum
Sleep or nap (Activity ID = 14500)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1337
1241
13.51
12.61
12.06
11.18
10.18
9.38
8.69
12.63 12.78
11.89 12.15
11.19 11.45
10.57 10.70
9.65 9.75
8.84 8.94
7.91 8.08
13.19 13.53
12.34 12.61
11.80 12.07
10.94 11.18
9.93 10.19
9.15 9.38
8.36 8.67
13.88 14.24
12.89 13.13
12.39 12.65
11.45 11.63
10.39 10.59
9.61 9.83
9.03 9.34
14.46
13.29
12.75
11.82
10.72
9.95
9.50
15.03
13.79
13.40
12.39
11.24
10.33
10.44
415
245
255
543
894
1451
1182
12.99
12.58
12.09
11.13
10.26
9.57
9.08
12.00
11.59
11.45
10.45
9.55
8.82
8.26
12.16 12.53
11.88 12.29
11.68 11.86
10.70 10.92
9.73 10.01
8.97 9.27
8.44 8.74
12.96 13.44
12.63 12.96
12.08 12.34
11.12 11.38
10.27 10.54
9.55 9.87
9.08 9.39
13.82 14.07
13.16 13.31
12.57 12.66
11.58 11.75
10.74 10.91
10.17 10.31
9.79 10.02
14.82
14.55
13.48
12.23
11.43
11.52
11.11
Sedentary & Passive Activities (METS < 1.5 - Includes Sleep or Nap)
Birth to <1 year
1 year
2 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
419
308
261
540
940
1337
1241
14.95
14.27
14.62
14.12
13.51
13.85
13.21
13.82 14.03
13.22 13.33
13.52 13.67
13.01 13.18
12.19 12.45
12.39 12.65
11.39 11.72
14.49 14.88
13.76 14.25
14.11 14.54
13.54 14.03
12.86 13.30
13.06 13.61
12.32 13.08
15.44 15.90
14.74 15.08
15.11 15.60
14.53 15.26
13.85 14.82
14.30 15.41
13.97 14.83
16.12
15.38
15.77
15.62
15.94
16.76
15.44
17.48
16.45
17.28
17.29
19.21
18.79
18.70
415
245
255
543
894
1451
1182
Light Intensity Activities (1.5 < METS
Birth to <1 year
1 year
2 years
3 to <6 years
6to
-------
00
    ri
    1=
Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category,
by Age and Gender Categories" (continued)
Duration (hours/day) Spent at Activity - Males

Age Group N lvk-d" „,

Birth to <1 year 419 3.67 0.63
1 year 308 4.04 0.45
2 years 261 .83 0.59
3 to <6 years 540 .15 0.55
6to
Birth to <1 year 183 0.20 0.00
1 year 164 0.31 0.01
2 years 162 0.10 0.00
3 to <6 years 263 0.27 0.02
6to
I
».
§
                                                                                                                                                                  I
                                                                                                                                                                   ri
       &
       &
       1=

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-16. Nonnormalized Daily Inhalation Rates (mVday) Derived Using Layton's (1993)
Method and CSFII Energy Intake Data

Age

Sample Size
(Non-weighted)

Mean

SEM

50th
Percentiles
90th

95th

SE of 95th
percentile
Infancy
0-2 months
3-5 months
6-8 months
9-11 months
0-11 months
182
294
261
283
1,020
3.63
4.92
6.09
7.41
5.70
0.14
0.14
0.15
0.20
0.10
3.30
4.56
5.67
6.96
5.32
5.44
6.86
8.38
10.21
8.74
7.10
7.72
9.76
11.77
9.95
0.64
0.48
0.86
-
0.55
Children
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
1 0 years
1 1 years
12 years
1 3 years
14 years
1 5 years
1 6 years
1 7 years
1 8 years
934
989
1,644
1,673
790
525
270
253
271
234
233
170
194
193
185
201
159
135
8.77
9.76
10.64
11.40
12.07
12.25
12.86
13.05
14.93
15.37
15.49
17.59
15.87
17.87
18.55
18.34
17.98
18.59
0.08
0.10
0.10
0.09
0.13
0.18
0.21
0.25
0.29
0.35
0.32
0.54
0.44
0.62
0.55
0.54
0.96
0.78
8.30
9.38
10.28
11.05
11.56
11.95
12.51
12.42
14.45
15.19
15.07
17.11
14.92
15.90
17.91
17.37
15.90
17.34
12.19
13.56
14.59
15.53
15.72
16.34
16.96
17.46
19.68
20.87
21.04
25.07"
22.81"
25.75"
28. II1
27.56
31.42"
28.80"
13.79
14.81
16.03
17.57
18.26
17.97
19.06
19.02
22.45"
22.90"
23.91"
29.17"
26.23"
29.45"
29.93"
31.01
36.69"
35.24"
0.25
0.35
0.27
0.23
0.47
0.87
1.27
1.08
1.35
1.02
1.62
1.61
1.11
4.38
1.79
2.07
-
4.24
Adolescent Boys
9- 18 years
983
19.27
0.28
17.96
28.78
32.82
1.39
Adolescent Girls
9- 18 years

0 through 1 year
2 through 1 5 years
992
U.S. EPA Cancer
1,954
7,624
14.27
0.22
Guidelines' Age Groups
7.50
14.09
0.08
0.12
13.99
21.17
23.30
0.61
with Greater Weighting
7.19
13.13
11.50
20.99
FASEB/LSRO (1995) convention, adopted by CSFII, denotes a value that might be
reliable than other estimates due
12.86
23.88
0.17
0.50
less statistically
to small cell size.
Denotes unable to calculate.
SEM = Standard
SE = Standard
Source: Arcus-Arth
error of the mean.
error.
and Blaisdell, 2007.


















Page
6-32
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-17. Mean and 95th Percentile Inhalation Rate Values (mVday) for Males and Females Combined
Age Group1 Sample Size Mean
Birth to <1 monthb 182 3.63
3 to <6 months 294 4.92
6 to <12 months' 544 6.75
1 to <2 years 934 8.77
2 to <3 years 989 9.76
3 to <6 years" 4,107 11.37
6 to <1 1 years6 1,553 13.69
11 to <16 years5 975 17.07
16 to <21 years8 495 18.31
1 No other age groups from Table 6-14 (Arcus-Arth and Blaisdell, 2007) fit into the U.S. EPA age
b Age group from Arcus-Arth and Blaisdell (2007) was 0-2 months.
c Age groups of 6-8 months and 9-11 months from Arcus-Arth and Blaisdell (2007) were averagec
d Age groups of 3, 4 and 5 years from Arcus-Arth and Blaisdell (2007) were averaged.
e Age groups of 6, 7, 8, 9 and 10 years from Arcus-Arth and Blaisdell (2007) were averaged.
f Age groups of 1 1, 12, 13, 14 and 15 years from Arcus-Arth and Blaisdell (2007) were averaged.
8 Age groups of 16, 17 and 18 years from Arcus-Arth and Blaisdell (2007) were averaged.
Source: Arcus-Arth and Blaisdell, 2007.
95th
7.10
7.72
10.77
13.79
14.81
17.29
20.28
27.74
34.32
groupings.
Child-Specific Exposure Factors Handbook                                       Page
September 2008	6-33

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-18. Summary of Institute of Medicine Energy Expenditure Recommendations
for Active and Very Active People with Equivalent Inhalation Rates
Age
Years
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19—30
31—50
51—70
Males
Energy Expenditure
(kcal/day)
607
869
1050
1,485—1,683
1,566—1,783
1,658—1,894
1,742—1,997
1,840—2,115
1,931—2,225
2,043—2,359
2,149—2,486
2,279—2,640
2,428—2,817
2,618—3,038
2,829—3,283
3,013—3,499
3,152—3,663
3,226—3,754
2,823—3,804
3,015—3,490
2,862—3,338
2,671—3,147
Inhalation Rate
(mVday)
3.4
4.9
5.9
8.4—9.5
8.8—10.1
9.4—10.7
9.8—11.3
10.4—11.9
10.9—12.6
11.5—13.3
12.1—14.0
12.9—14.9
13.7—15.9
14.8—17.2
16.0—18.5
17.0—19.8
17.8—20.7
18.2—21.2
18.4—21.5
17.0—19.7
16.2—18.9
15.1—17.8
Females
Energy Expenditure
(kcal/day)
607
869
977
1,395—1,649
1,475—1,750
1,557—1,854
1,642—1,961
1,719—2,058
1,810—2,173
1,890—2,273
1,972—2,376
2,071—2,500
2,183—2,640
2,281—2,762
2,334—2,831
2,362—2,870
2,368—2,883
2,353—2,871
2,336—2,858
2,373—2,683
2,263—2,573
2,124—2,435

Inhalation Rate
(mVday)
3.4
4.9
5.5
7.9—9.3
8.3—9.9
8.8—10.5
9.3—11.1
9.7—11.6
10.2—12.3
10.7—12.8
11.1—13.4
11.7—14.1
12.3—14.9
12.9—15.6
13.2—16.0
13.3—16.2
13.4—16.3
13.3—16.2
13.2—16.1
13.4—15.2
12.8—14.5
12.0—13.8
Source: Stifelman, 2007.
Page
6-34
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-19. Mean Inhalation Rate Values (mVday) for Males, Females, and Males and Females Combined.1

Age Groupb Males
Birth to <1 year 3.4
1 to <2 years 4.9
2 to <3 years 5.9
3 to <6 years' 9.2
6 to <1 1 years'1 10.9
11 to <16 years6 14.9
16 to <21 years5 18.2
b
d
e
f
Source
Females
3.4
4.9
5.5
8.3
10.2
12.7
13.3
Inhalation rates are for IOM Physical Activity Level (PAL) category "active"; the total
all PAL categories was 3007.
No other age groups from Table 6-15 (Stifelman, 2007) fit into the EPA age groupings
Age groups of 3, 4, and 5 years from Stifelman, 2007 were averaged.
Age groups of 6, 7, 8, 9 and 10 years from Stifelman, 2007 were averaged.
Age groups of 11, 12, 13, 14 and 15 years from Stifelman, 2007 were averaged.
Age groups of 16, 17 and 18 years from Stifelman, 2007 were averaged.
Stifelman, 2007.
Combined
3.4
4.9
5.7
8.8
10.6
13.8
15.8
number of subjects for
Child-Specific Exposure Factors Handbook                                        Page
September 2008	6-35

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-20. Mean Inhalation Rate Values (mVday) from Key Studies for Males and Females Combined
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
TTC T-T>A ^nn^-. Brochuetal.
U.S. EPA (2006) (20Q6)
N"
_b
-
-
-
834
553
516
1,083
1,834
2,788
2,423
1 Number of individuals;
b No data from this study
Mean N Mean
-
-
85 3.32
103 4.09
8.65
13.40 101 4.95
12.99
12.41
12.92
14.38
15.41
the total number of subjects
for this age group.
Arcus-Arth and „,. „ . /o™-^
Blaisdell(2007) Stifelman (2007)
N
182
-
294
544
--
934
989
4,107
1,553
975
495
for Stifelman
Mean N Mean
3.63
-
4.92
6.75
3.40
8.77 - 4.90
9.76 - 5.70
11.37 - 8.77
13.69 - 10.57
17.07 - 13.78
18.31 - 15.75
(2007) was 3,007.
Combined Key
Studies
N
182
-
379
647
834
1,588
1,505
5,190
3,387
3,763
2,918

Mean
3.63
-
4.12
5.42
6.03
8.01
9.48
10.85
12.39
15.08
16.48

Page
6-36
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	



Table 6-21.
Age Group
Birth to <1 month
1
3
6
to
to
to
<3
<6
months
months
95th Percentile Inhalation Rate Values (mVday) from Key Studies for Males and Females Combined
U.S. EPA
Na
b
-
-
(2006)
95
-
-
-
th



<12 months
Birth to <1 year
1
2
3
6
to
to
to
to
<2
<3
<6
years
years
years
<1 1 years
11 to <16 years
16to<
a
b


21 years
Number
No data
834
553
516
1,083
1,834
2,788
2,423
12
18
17
15
17
19
20
68
26
04
17
03
31
84
of individuals; the tola
from this study for this
Brochuetal. Arcus-Arth and „,. „ , ,~.nnn^
(2006) Bla1sdell(2007) Stfelmn (2007)
N 95th N
182
-
85 4.47 294
103 5.33 544
-
101 6.46 934
989
4,107
1,553
975
495
95th N 95th
7.

7.
10

13
14
17
20
27
34
10

72
.77

.79
.81
.29
.28
.74
.32
Combined Key
Studies
N
182
-
379
647
834
1,588
1,505
5,190
3,387
3,763
2,918
95th
7.10
-
6.09
8.05
12.68
12.84
15.93
16.23
18.66
23.53
27.58
number of subjects for Stifelman (2007) was 3,007.
age group.
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September 2008	6-37

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-22. Daily Inhalation Rates Estimated From Daily
„ , . , Inhalation Rate (mVhour)
Resting Light Activity
Child (10 years) 0.29 0.78
Infant (1 year) 0.09 0.25
Newborn 0.03 0.09
Activities1
Daily Inhalation Rate (DIR)b
(mVday)
14.8
3.76
0.78
1 Assumptions made were based on 8 hours resting and 16 hours light activity for adults and children (10 yrs); 14
b hours resting and 10 hours light activity for infants (1 yr); 23 hours resting and 1 hour light activity for newborns.
!•£
Dm=-Zmttl
i i=l
DIR = Daily Inhalation Rate
IR; = Corresponding inhalation rate at i"1 activity
t; = Hours spent during the i"1 activity
k = Number of activity periods
T = Total time of the exposure period (i.e., a day)
Source: ICRP, 1981.
Page                                        Child-Specific Exposure Factors Handbook
6-38	September 2008

-------
00
    ri
    1=
    53
Table

Subject

Adolescent
male, 14-16 y
male, 14-15 y
female, 14-16 y
6-23. Selected

W(kg)



59.4

Inhalation Rate Values During Different Activity Levels Obtained From
Resting Light Activity

f VT V* f VT V* f

16 330 5.2

15 300 4.5
female, 14-15y;164.9cmL 56
Children
10 y; 140 cm L
males, 10-11 y
males, 10-1 1 y; 140.6 cm L
females, 4-6 y
females, 4-6 y; 111. 6 cm L
Infant, 1 y
Newborn
20hrs-13wk
9.6 hrs
6.6 days
W = Body weights
* Calculated from
b Crying.
Source: ICRP, 1981.


36.5
32.5
20.8
18.4

2.5
2.5-5.3
3.6
3.7

16 300 4.8 24 600 14




30 48 1.4"
34 15 0.5

25 21 0.5
29 21 0.6
f = frequency (breaths/min); VT = tidal volume (ml); V* = minute volume (1/min); cm
V*=fxVT.





Various Literature Sources


Heavy Work Maximal Work During

VT V* f

53


52


58
61
70
66


68b


L = length/height; y = years



Exercise
VT

2520


1870


1330
1050
600
520


51"-b


of age; wk =




V*

113


88


71
61
40
34


3.5"


week.



                                                                                                                                                              *     ^
                                                                                                                                                              *     &
                                                                                                                                                              *     1
                                                                                                                                                              ^     >
I
».
§
                                                                                                                                                                     I
                                                                                                                                                                     ri
       &
       &
       1=

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-24. Summary of Human Inhalation Rates for Children by

Nb Resting' Nb Light11
Child, 6 years 8 0.4 16 0.8
Child, 10
a

b
c
d

e
f
Source:
years 10 0.4 40 1
Values of inhalation rates for children (male and female) presented
reported for each activity level in 1985.
Number of observations at each activity level.
Includes watching television, reading, and sleeping.
includes most domestic work, attending to personal needs and care
and home improvements.
Nb
4
29
Activity Level (m3
Moderate6
2
3.2
in this table represent the






hobbies, and conducting


/hour)"
Nb Heavy5
5 2.3
43 3.9
mean of values



minor indoor repairs

Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs.
Includes vigorous physical exercise and climbing stairs carrying a load.
Adapted from U.S. EPA, 1985.



Table 6-25. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level
for All Age Groups
Microenvironment
Indoors


Outdoors


In Transportation
Vehicle


Source: Adapted from U.S
Average Hours Per Day in Each
Activity Level Microenvironment at Each Activity Level
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
EPA, 1985.
9.82
9.82
0.71
0.10
20.4
0.51
0.51
0.65
0.12
1.77
0.86
0.86
0.05
0.0012
1.77

Page
6-40
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Child, 6 years
Child, 10 years
4.47
4.47
8.95
11.19
2.82
4.51
0.50
0.85
16.74
21.02
                            Table 6-26. Summary of Daily Inhalation Rates Grouped by
                                            Age and Activity Level
        Subject
                                      Daily Inhalation Rate (rnVday)1
                           Resting
                          Light
Moderate
Heavy
        IR,
        t;
        k
        T
                                                                   Total Daily IRb
                                                                      (mVday)
                Daily inhalation rate was calculated using the following equation:
                                              =     E IRA
= Inhalation rate at i  activity (Table 6-13 and 6-14)
= Hours spent per day during i  activity (Table 6-15)
= Number of activity periods
= Total time of the exposure period (e.g., a day)
Total daily inhalation rate was calculated by summing the specific activity (resting, light, moderate,
heavy) and dividing them by the total amount of time spent on all activities.
        Source:  Generated using the data from U.S. EPA (1985) as shown in Tables 6-24 and 6-25.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                     Page
                                                                                      6-41

-------
                                                        Child-Specific Exposure Factors Handbook

                                                       	Chapter 6 - Inhalation Rates
Table 6-27. Calibration and Field Protocols for Self-monitoring of Activities Grouped by Subject Panels
Panel
Panel 2 - Healthy Elementary
School Students - 5 male,
12 female, ages 10-12
Panel 3 - Healthy High School
Students - 7 male, 12 female, ages
13-17
Panel 6 - Young Asthmatics - 7
male, 6 female, ages 11-16

Calibration Protocol
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and
fast walking
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and
fast walking
Laboratory exercise tests on bicycles
and treadmills

Field Protocol
Saturday, Sunday and Monday (school
day) in early autumn; heart rate recordings
and activity diary during waking hours and
during sleep.
Same as Panel 2, however, no heart rate
recordings during sleep for most subjects.
Summer monitoring for 2 successive
weeks, including 2 controlled exposure
studies with few or no observable
respiratory effects.
Source: Linn et al., 1992.
       Table 6-28. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated Breathing Rates
                                                               Inhalation Rates (mVhour)
           Panel Number
           and Description
                                     Mean VR
99th Percentile
     VR
 Mean VR at Activity Levels'1

Slow     Medium      Fast
 Healthy
  2 - Elementary School Students          17
  3 - High School Students               19

 Asthmatics
  6 - Elementary and High School          13
     Students
                                        1.20
    1.98
    2.22


    2.40
0.84
0.78


1.20
0.96
1.14


1.20
1.14
1.62


1.50
 VR
Number of individuals in each survey panel.
Some subjects did not report medium and/or fast activity. Group means were calculated from individual means (i.e..
give equal weight to each individual who recorded any time at the indicated activity level).
= Ventilation rate.
 Source:  Linn et al., 1992.
Page
6-42
                                               Child-Specific Exposure Factors Handbook
                                              	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates

Table 6-29. Distribution of Predicted Inhalation Rates by Location and Activity Levels
for Elementary and High School Students
Inhalation Rates (mVhour)
Age (years) Student Location Activity °/
Level

10-12 ELC Indoors slow
(Nd=17) medium
fast
Outdoors slow
medium
fast
13-17 HSC Indoors slow
(Nd=19) medium
fast
Outdoors slow
medium
fast
1 Recorded time averaged about 23 hr per elementary
hour periods.
'a Recorded
Time1

49.6
23.6
2.4
8.9
11.2
4.3
70.7
10.9
1.4
8.2
7.4
1.4

Mean ± SD

0.84 ±0.36
0.96 ±0.36
1.02 ±0.60
0.96 ±0.54
1.08 ±0.48
1.14±0.60
0.78 ±0.36
0.96 ±0.42
1.26 ±0.66
0.96 ±0.48
1.26 ±0.78
1.44 ±1.08
school student and 33 hours

b Geometric means closely approximated 50th percentiles; geometric
forVR.
c Elementary school student or high school student.
d Number of students that participated in survey.
e Highest single value.
SD = Standard deviation.
Source: Spier et al., 1992.







Percentile Rankings11

1st
0.18
0.24
0.24
0.36
0.24
0.48
0.30
0.42
0.54
0.42
0.48
0.48

50th
0.78
0.84
0.84
0.78
0.96
0.96
0.72
0.84
1.08
0.90
1.08
1.02
per high school student

standard deviations were














99.9th
2.34
2.58
3.42
4.32
3.36
3.60
3.24
4.02
6.84e
5.28
5.70
5.94
over 72-

1.2-1.3 for HR,1. 5-1. 8












Child-Specific Exposure Factors Handbook
September 2008	
Page
 6-43

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-30. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and High School Students
Students
Elementary school,
10-12 years
(N=17)
High school,
ages 13- 17 years
(N=19)
N = Number
Source: Spier et al

Slow
ages Indoors 16.3
Outdoors 2.2
Indoors 19.5
Outdoors 1 .2
of students that participated in survey.
, 1992.
Activity Level
Medium
2.9
1.7
1.5
1.3


Total Time Spent
(hours/day)
Fast
0.4 19.6
0.5 4.4
0.2 21.2
0.2 2.7


Page                                       Child-Specific Exposure Factors Handbook
6-44	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
                           Table 6-31.  Summary of Average Inhalation Rates (mVhour) by
                              Age Group and Activity Levels for Laboratory Protocols
                                                                  Activity Level
              Age Group
                                         Resting1       Sedentary        Lighf       Moderate       Heavy6
  Young Children                            0.37           0.40          0.65          DNPf         DNPf
  (3-5.9 years)
  Average inhalation rate (mVhour)

  (N=12, gender not specified)

  Children                                  0.45           0.47          0.95          1.74          2.23
  (6-12.9 years)
  Average inhalation rate (mVhour)

  (N=40, 20 male and 20 female)
  1        Resting defined as lying (see Table 6-33 for original data).
  b        Sedentary defined as sitting and standing (see Table 6-33 for original data).
  c        Light defined as walking at speed level 1.5 - 3.0 mph (see Table 6-33 for original data).
  d        Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Table 6-33 for original
          data).
  e        Heavy defined as  fast running (4.5 - 6.0 mph) (see Table 6-33 for original data).
  f        Group did not perform (DNP) this protocol or N was too  small for appropriate mean comparisons. All young
          children did not run.

  Source:  Adapted from Adams, 1993.
Child-Specific Exposure Factors Handbook                                                    Page
September 2008	6-45

-------
                                                     Child-Specific Exposure Factors Handbook

                                                     	Chapter 6 - Inhalation Rates
      Table 6-32. Summary of Average Inhalation Rates (mVhour) by Age Group And Activity Levels in Field Protocols
                    Age Group                                       Moderate Activity1
 Young Children (3-5.9 years)                                                0.68
 Average inhalation rate (mVhour)

 (N=12, gender not specified)

 Children (6-12.9 years)                                                     1.07
 Average inhalation rate (mVhour)

 (N=40, 20 male and 20 female)
 1       Moderate activity was defined as play.
 N      = Number of individuals.

 Source:  Adams, 1993.	
Page                                                Child-Specific Exposure Factors Handbook
6-46	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-33. Mean Minute Inhalation Rate (mVminute) by Group and Activity for Laboratory Protocols
Activity
Lying
Sitting
Standing
Walking
1.5 mph
1.875mph
2.0 mph
2.25 mph
2.5 mph
3.0 mph
3.3 mph
4.0 mph
Running
3.5 mph
4.0 mph
4.5 mph
5.0 mph
6.0 mph
* Young Children, male and female
b Group did not perform (DNP) this
Source: Adams , 1993.
Young Children"
6.19E-03
6.48E-03
6.76E-03

1.03E-02
1.05E-02
DNP
1.17E-02
DNP
DNP
DNP
DNP

DNP
DNP
DNP
DNP
DNP
3-5.9 years old; Children, male and female 6-12.9
protocol or N was too small for appropriate mean

Children1
7.51E-03
7.28E-03
8.49E-03

DNP»
DNP
1.41E-02
DNP
1.56E-02
1.78E-02
DNP
DNP

2.68E-02
3.12E-02
3.72E-02
DNP
DNP
years old.
comparisons.


Activity
Play
a
Source:
Table 6-34


Young children,
Adams, 1993.
Mean Minute Inhalation Rate (m3 /minute) by Group and Activity
Young Children"
1.13E-02
male and female 3-5.9 years old; children, male and female 6-12.9

for Field Protocols
Children1
1.89E-02
years old.

Child-Specific Exposure Factors Handbook
September 2008	
Page
 6-47

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-35.
Cohort/Age
(years)
Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy Intakes (EFD) for
Individuals Sampled in the 1977-78 NFCS
BodvWeisht
(kg)

MJ/day"
BMR1
Kcal/dayc
Energy
MJ/day
Intake (EFD)
Kcal/day
Ratio
EFDd/BMR
Males and Females
<1
Ito2
3 to 5
6 to 8
7.6
13
18
26
1.74
3.08
3.69
4.41
416
734
881
1053
3.32
5.07
6.14
7.43
793
1209
1466
1774
1.90
1.65
1.66
1.68
Males
9 to 11
12 to 14
15 to 18
36
50
66
5.42
6.45
7.64
1293
1540
1823
8.55
9.54
10.80
2040
2276
2568
1.58
1.48
1.41
Females
9 to 11
12 to 14
15 to 18
36
49
56
4.91
5.64
6.03
1173
1347
1440
7.75
7.72
7.32
1849
1842
1748
1.58
1.37
1.21
1 Calculated from the appropriate age and gender-based BMR equations given in Table 6-37.
b MJ/day - mega joules/day.
c Kcal/d - kilo calories/day.
d Food energy intake (Kcal/day) or (MJ/day).
Source: Layton
, 1993.





Page                                       Child-Specific Exposure Factors Handbook
6-48	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
                        Table 6-36.  Daily Inhalation Rates Calculated from Food-energy Intakes
   Cohort/Age
     (years)
T b      Daily Inhalation Ratec       Sleep
              (mVday)            (hours)
                                                                   MET Value
                                                                       Inhalation Rates
                                               Ad
Inactive5       Active5
(mVday)      (mVday)
                                               Males and Females
<1
Ito2
3 to 5
6 to 8
1
2
3
3
4.5
6.8
8.3
10
11
11
10
10
1.9
1.6
1.7
1.7
2.7
2.2
2.2
2.2
2.35
4.16
4.98
5.95
6.35
9.15
10.96
13.09
                                                    Males
9 to 11
12 to 14
15 to 18
3
3
4
14
15
17
9
9
8
1.9
1.8
1.7
2.5
2.2
2.1
7.32
8.71
10.31
18.3
19.16
21.65
                                                   Females
9 to 11
12 to 14
15 to 18
3
3
4
13
12
12
9
9
8
1.9
1.6
1.5
2.5
2.0
1.7
6.63
7.61
8.14
16.58
15.22
13.84
          MET = Metabolic equivalent.
          L = Number of years for each age cohort.
          Daily inhalation rate was calculated by multiplying the EFD values (see Table 6-35) by H x VQ for subjects under 9
          years of age and by 1.2 x H x VQ (for subjects 9 years of age and older (see text for explanation), where EFD =
          Food energy intake (Kcal/day) or (MJ/day), H = Oxygen uptake = 0.05 LO2/KJ or 0.21 LO2/Kcal, and VQ =
          Ventilation equivalent = 27 = geometric mean of VQs (unitless).
          For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (Table
          6-35) by the factor 1.2 (see text for explanation).
          F =  (24 x A - S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated
          BMR (unitless), where S = Number of hours spent sleeping each day.
          Inhalation rate for inactive periods was calculated as BMR x H x VQ, and for active periods by multiplying the
          inactive inhalation rate by F (see footnote c); BMR values are from Table 6-35, where BMR = basal metabolic rate
          (MJ/day) or (kg/hr).
  Source:  Layton, 1993.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                     Page
                                                                                      6-49

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 6 - Inhalation Rates
Table 6-37. Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting
Basal Metabolic Rates (BMR)
„ , BMR Body
Gender. . j
Age (years) MJd_! §D CV vv(jjlu N BMR Equation1
Males
Under 3 1.51 0.92 0.61 6.6 162 0.249 bw- 0.127
3 to < 10 4.14 0.50 0.12 21 338 0.095 bw + 2.110
10 to < 18 5.86 1.17 0.20 42 734 0.074 bw + 2.754
Females
Under 3 1.54 0.92 0.59 6.9 137 0.244 bw- 0.130
3 to < 10 3.85 0.49 0.13 21 413 0.085 bw + 2.033
10 to < 18 5.04 0.78 0.15 38 575 0.056 bw + 2.898
1 Body weight (bw) in kg.
SD = Standard deviation.
CV = Coefficient of variation (SD/mean).
N = Number of observations.
r = Coefficient of correlation.
Source: Layton, 1993.
r

0.95
0.83
0.93

0.96
0.81
0.8




Page
6-50
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-38. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR)
Gender/Age Body Weight1
(years) (kg)
Males
0.5 to <3
3 to <10

14
23
10to<18 53
Females
0.5 to <3
3 to <10
10to<18
a
b

c


11
23
50
Body weight was based
BMR"
(MJ/day) M

3.4 27 1.6
4.3 27 1.6
6.7 27 1.7

2.6 27 1.6
4.0 27 1.6
5.7 27 1.5
on the average weights for age/gender cohorts
H Inhalation Rate, VE
(m3O2/MJ) (mVday)"

0.05
0.05
0.05

0.05
0.05
0.05
in the U.S. population.
The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations
36).
The values of the BMR
(1989) study: Male = 1

multiplier (EFD/BMR) for those 18 years and


7.3
9.3
15

5.6
8.6
12

(see Table 6-

older were derived from the Basiotis et al.
.59, Female = 1.38. For males and females under 10 years old, the mean BMR
used was 1.6. For males and females aged 10 to < 18 years, the mean

cl
Source:
years and 15-18 years, a
ge brackets for males and females were used:
values for A given in Table 6-36
male =1.7 and female = 1.5.
multiplier
for 12-14

Inhalation rate = BMR x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake.
Layton, 1993.



Child-Specific Exposure Factors Handbook                                       Page
September 2008	6-51

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                                                          Child-Specific Exposure Factors Handbook

                                                         	Chapter 6 - Inhalation Rates
                               Table 6-39. Inhalation Rates for Short-term Exposures
                                                                      Activity Type
      Gender/Age
        (years)
 Body
Weight
 (kg)1
 BMR"
(MJ/day)
                                                Rest
                                  Sedentary
                                     Light
                                    Moderate
                                       Heavy
                   MET (BMR Multiplier)
                                                             1.2
                                                              4"
                                                                10e
                                                                Inhalation Rate (mVminute)5'8
 Males
   0.5 to <3
   3 to <10
   10to<18
 Females
   0.5 to <3
   3 to <10
   10to<18
   14
   23
   53

   11
   23
   50
  3.40
  4.30
  6.70

  2.60
  4.00
  5.70
3.2E-03
4.0E-03
6.3E-03

2.4E-03
3.8E-03
5.3E-03
3.8E-03
4.8E-03
7.5E-03

2.9E-03
4.5E-03
6.4E-03
6.4E-03
8.1E-03
1.3E-02

4.9E-03
7.5E-03
1.1E-02
1.3E-02
1.6E-02
2.5E-02

l.OE-02
1.5E-02
2.1E-02
6.3E-02
5.3E-02
          Body weights were based on average weights for age/gender cohorts of the U.S. population
          The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR
          equations (Table 6-37).
          Range = 1.5 -2.5.
          Range = 3-5.
          Range = >5 - 20.
          The inhalation rate was calculated as IR = BMR (MJ/day) x H (0.05 L/KJ) x MET x VQ (27) x (day/1440 min)

          Original data were presented in L/min.  Conversion to mVmin was obtained as follows: 	 x 	
             5            v                                                        1000L   mm
          The maximum possible MET sustainable for more than 5 minutes does not reach 10 for females and males until age
          13 and 12, respectively.  Therefore, a METs of 10 is not possible for this age category.
  Source:   Layton, 1993.
Page
6-52
                                  Child-Specific Exposure Factors Handbook
                                 	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates	
Table 6-40. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in
618 Infants and Children Grouped in Classes of Age
Inhalation Rate (breaths/min)
Age (months) N Waking

<2
2to<6
6 to <12
12to<18
18to<24
24 to <30
30 to 36
SD
N
Source:
Mean ± SD Median
104 48.0 ±9.1 47
106 44.1 ±9.9 42
126 39.1 ±8. 5 38
77 34.5 ± 5.8 34
65 32.0 ±4. 8 32
79 30.0 ± 6.2 30
61 27.1 ±4.1 28
= Standard deviation.
= Number of individuals.
Rusconietal., 1994.
Sleeping
Mean ± SD Median
39. 8 ±8.7 39
33.4 ±7.0 32
29.6 ±7.0 28
27.2 ± 5.6 26
25.3 ±4.6 24
23.1 ±4.6 23
21. 5 ±3.7 21



Child-Specific Exposure Factors Handbook
September 2008	
Page
 6-53

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                                                   Child-Specific Exposure Factors Handbook

                                                  	Chapter 6 - Inhalation Rates
             70 T
                    3   6   9  12  15  18  21   24  27  30  33  36
                                  Age (months)
       Figure 6-1.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Awake Subjects
                      (RR = respiratory rate). Source: Rusconi et al, 1994.
              70 T
                                 12   15   18   21   24   27   30  33  36

                                    Age  (months)
       Figure 6-2.      5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Gentiles by Age in Asleep Subjects
                      (RR = respiratory rate). Source: Rusconi et al., 1994.
Page
6-54
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
                                    TABLE OF CONTENTS

7      DERMAL EXPOSURE FACTORS  	7-1
       7.1     INTRODUCTION	7-1
       7.2     RECOMMENDATIONS	7-2
              7.2.1   Body Surface Area  	7-2
              7.2.2   Adherence of Solids to Skin 	7-2
       7.3     SURFACE AREA	7-10
              7.3.1   Key Body Surface Area Studies  	7-10
                     7.3.1.1  U.S. EPA, 1985	7-10
                     7.3.1.2  U.S. EPA Analysis of NHANES 1999-2006 Data  	7-10
              7.3.2   Relevant Body Surface Area Studies	7-10
                     7.3.2.1  Phillips et al, 1993 	7-10
                     7.3.2.2  Wong et al., 2000  	7-11
       7.4     ADHERENCE OF SOLIDS TO SKIN	7-11
              7.4.1   Key Adherence of Solids to Skin Studies 	7-11
                     7.4.1.1  Kissel et al., 1996a 	7-11
                     7.4.1.2  Holmes et al., 1999	7-12
                     7.4.1.3  Shoafetal., 2005  	7-12
              7.4.2   Relevant Adherence of Solids to Skin Studies  	7-13
                     7.4.2.1  Kissel et al., 1996b 	7-13
                     7.4.2.2  Kissel et al., 1998  	7-13
       7.5     REFERENCES FOR CHAPTER 7	7-14

APPENDIX 7A 	  7A-1
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                                                    Child-Specific Exposure Factors Handbook

                                                   	Chapter 7 - Dermal Exposure Factors
                                        LIST OF TABLES

Table 7-1.       Recommended Values for Total Body Surface Area, Males and
               Females Combined 	7-4
Table 7-2.       Recommended Values for Surface Area of Body Parts	7-5
Table 7-3.       Confidence in Recommendations for Body Surface Area	7-6
Table 7-4.       Recommended Values for Mean Solids Adherence	7-8
Table 7-5.       Confidence in Recommendations for Solids Adherence to Skin	7-9
Table 7-6.       Percentage of Total Body Surface Area by Body Part For Children	7-16
Table 7-7.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Males and Females Combined	7-17
Table 7-8.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Males	7-17
Table 7-9.       Mean and Percentile Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES
               1999-2006 Females	7-18
Table 7-10.      Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (mVkg)	7-19
Table 7-11.      Estimated Skin Surface Exposed During Warm Weather Outdoor Activities	7-20
Table 7-12.      Summary of Field Studies  	7-21
Table 7-13.      Geometric Mean and Geometric Standard Deviations of Solids Adherence by
               Activity and Body Region	7-22
Table 7-14.      Summary of Controlled Greenhouse Trials - Children Playing	7-23
Table 7A-1.     Estimated Parameter Values for Different Age Intervals	  7A-4
Table 7A-2.     Summary of Surface Area Parameter Values for the Dubois and Dubois Model  	  7A-5
Page
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	September 2008

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Chapter 7 - Dermal Exposure Factors	
                                     LIST OF FIGURES

Figure 7-1.      Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing
              in Wet Soils	7-24
Figure 7-2.      Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils	7-24
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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
7       DERMAL EXPOSURE FACTORS
7.1     INTRODUCTION
        Dermal exposure can occur during a variety of
activities  in  different  environmental  media  and
microenvironments (U.S. EPA, 1992a; 1992b; 2004).
These include:
        •   Water   (e.g.,   bathing,   washing,
            swimming);
        •   Soil (e.g., outdoor recreation, gardening,
            construction);
        •   Sediment (e.g., wading, fishing);
        •   Liquids  (e.g.,  use   of  commercial
            products);
        •   Vapors/fumes  (e.g., use of commercial
            products); and
        •   Indoor dust (e.g., carpets, floors, counter
            tops).
        Children may be more highly exposed to
environmental toxicants through dermal routes than
adults. For instance, children may crawl, roll or sit on
surfaces treated with chemicals (i.e., carpets and floors)
and play with objects such as toys where residues may
settle.  Children also are more likely to  wear less
clothing than adults. As a result, children may have
higher dermal contact with contaminated media.  In
addition, young children who  wear diapers  may be
exposed  for  long  periods of time  to  chemical
components of lotions and other products used for
diapering.  Children also have a higher surface area
relative to  body weight  compared  to  adults.   The
surface-area-to-body weight ratio for newborn infants
is  more than two times greater than that for adults
(Cohen-Hubal et al, 1999).   Therefore, the dose
relative to body weight would be greater for a child
than for an adult with an equal amount of skin exposure
to  a chemical.
        This chapter focuses on measurements of body
surface area and dermal adherence of solids to the skin.
These  are  only two  of a several  parameters  that
influence dermal absorption.  Other factors include the
concentration  of chemical in contact with the skin,
characteristics  of the  chemical (i.e.,  lipophilicity,
polarity, volatility, solubility), the site of application
(i.e., the thickness of the stratum corneum varies over
parts of the body), absorption of chemical through the
skin and factors that affect absorption (i.e,  thickness,
age, condition), and the amount of chemical delivered
to  the target organ.  For guidance on how to use skin
surface area and dermal adherence factors,  as well as
these other factors to assess dermal exposure, readers
are  referred  to  Dermal  Exposure  Assessment:
Principles and Applications (U.S. EPA, 1992b) and
Risk Assessment Guidelines for Superfund (RAGs) Part
E (U.S. EPA, 2004). Frequency and duration of contact
also affect dermal exposure.  Information on activity
factors is presented in Chapter 17 of this handbook.
        Surface area of the skin can be determined
using measurement or estimation techniques. Coating,
triangulation,  and  surface   integration  are  direct
measurement techniques that have been used to measure
total body surface area and the surface area of specific
body parts.  The  coating method consists of coating
either the whole body or specific body regions with a
substance   of  known  density  and  thickness.
Triangulation consists of marking the area of the body
into geometric figures, then calculating the figure areas
from their linear  dimensions.  Surface  integration is
performed by using a planimeter and adding the areas.
The results of studies conducted using  these various
techniques have been summarized in Development of
Statistical Distributions or Ranges of Standard Factors
Used in Exposure Assessments  (U.S.  EPA,  1985).
Because of the  difficulties  associated with direct
measurements of body surface area, the existing direct
measurement data are limited and  dated.   However,
several  researchers  have  developed  methods  for
estimating body  surface area from measurements  of
other body dimensions (DuBois and DuBois, 1916;
Boyd,  1935; Gehan  and  George, 1970).  Generally,
these formulas are based on the observation that body
weight and height are correlated with surface area and
are derived using multiple regression techniques. U. S.
EPA  (1985)  evaluated  the various   formulas  for
estimating total body surface area.  A discussion and
comparison of formulas are presented in Appendix 7 A.
The key studies on body surface area that are presented
in Section  7.3  of this chapter are based  on these
formulas, and weight and height data from the National
Health and Nutrition Examination Survey (NHANES).
         Several field studies have been conducted to
estimate the adherence of solids to  skin. These field
studies consider factors such as activity, gender, age,
field conditions, and clothing worn. These studies are
presented in Section 7.4 of this chapter.
        The recommendations for skin surface area
and dermal adherence of solids to skin are provided in
the  next  section, along with  a  summary of the
confidence ratings for these recommendations.  The
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                                                        Child-Specific Exposure Factors Handbook

                                                       	Chapter 7 - Dermal Exposure Factors
recommended values are based on key studies identified
by  U.S. EPA  for these factors.    Following the
recommendations, the two key studies on skin surface
area and the three key studies on dermal adherence of
solids to skin are summarized. Relevant data on these
factors are also presented to provide added perspective
on  the  state-of-knowledge  pertaining to  dermal
exposure factors.

7.2     RECOMMENDATIONS
7.2.1    Body Surface Area
        The  recommended mean and 95th percentile
total  body  surface  area values  for  children are
summarized in Table 7-1. If gender-specific data or
data for percentiles other than the mean  or 95th
percentile are needed, the reader is referred to Tables 7-
7 through 7-9  of this chapter. The recommendations for
total body  surface  area  are based on the U.S. EPA
analysis of NHANES 1999-2006 data and are presented
for the standard age groupings recommended by U.S.
EPA (2005) for male and female children combined.
The U.S. EPA analysis of NHANES 1999-2006 data
uses correlations with body weight  and  height for
deriving skin surface  area (see Section 7.3.1.2 and
Appendix  7A).    NHANES  1999-2006  used  a
statistically-based survey design which should ensure
that the  data are  reasonably representative of the
general population.  The recommendations for the
percentage of total body  surface area represented by
individual body parts are based on data from U. S. EPA
(1985), and are presented in Table  7-2 (See Section
7.3.1). Table 7-2 also provides age-specific body part
surface areas (m2) that were obtained by multiplying the
mean body part percentages by the total body surface
areas presented in Table 7-1. If gender-specific data or
data for percentiles other than the mean  and 95th
percentile are needed, the body part percentages in
Table 7-2 may be applied to the total skin surface area
data in Tables 7-7 through 7-9. Table 7-3 presents the
confidence ratings for the recommendations  for body
surface area.
        For  swimming  and  bathing  scenarios, past
exposure assessments  have assumed that  75 to 100
percent of the skin surface  is exposed (U.S. EPA,
1992b). More recent guidance recommends assuming
100 percent exposure for these scenarios (U.S. EPA,
2004). For other exposure scenarios, it is reasonable to
assume that  clothing  reduces  the   contact  area.
However, while it is generally assumed that adherence
 of solids to skin occurs to only the areas of the body not
 covered by clothing, it is important to understand that
 soil and dust particles can get under clothing and be
 deposited on skin to varying degrees depending on the
 protective properties of the clothing. Likewise, liquids
 may soak through clothing and contact covered areas of
 the skin. Assessors should consider these possibilities
 for the scenario of concern and select skin areas that are
 judged appropriate.

 7.2.2    Adherence of Solids to Skin
         The  adherence  factor  (AF)  describes the
 amount of material that adheres to the skin per unit of
 surface area. Although most research in this area has
 focused on soils, a variety of other solid residues can
 accumulate  on  skin,  including   household   dust,
 sediments and  commercial powders. Studies on soil
 adherence have shown that: 1) soil properties influence
 adherence; 2) soil adherence varies considerably across
 different parts of the body; and 3) soil adherence varies
 with activity (U. S. EPA, 2004). It is recommended that
 exposure assessors use adherence  data derived  from
 testing that matches the exposure scenario of concern in
 terms of solid type, exposed body parts, and activities,
 as closely as possible. Assessors should refer to the
 activities described in Table 7-12 to select those that
 best represent  the exposure scenarios of concern and
 use the corresponding adherence values from Table 7-
 13.  Table 7-12 lists the age ranges covered by each
 study.  This may be used as a general guide to the ages
 covered by these data. Recommended mean AF values
 are  summarized in Table 7-4 according to common
 activities involving children.   Insufficient data  were
 available to   develop  distributions or probability
 functions for these values.  Also, the small number of
 subjects in these studies prevented the development of
 recommendations   for  the  specific   age   groups
 recommended by U.S. EPA (2005).
         RAGS Part E (U.S. EPA, 2004) recommends
 that scenario-specific adherence values be weighted
 according to  the body  parts  exposed.   Weighted
 adherence factors may be estimated according to the
 following equation:

 AFwtd= (AF.YSA.) + (AF.YSA.) + . . . . (AF.YSA)
                 SAj + SA2 + . . . SAj
 (Eqn.  7-1)
Page
7-2
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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
where:
    AF^   =   weighted adherence factor;
    AF     =   adherence factor; and
    SA     =   surface area.

For the purposes of this calculation, the surface area of
the face may be assumed to be 1/3 that of the head,
forearms may be assumed to represent 45 percent of the
arms and lower legs may be assumed to represent 40
percent of the legs (U.S. EPA, 2004).
        The recommended dermal AFs represent the
amount of material  on the  skin  at the  time of
measurement.    U.S.  EPA (1992b)  recommends
interpreting AFs as representative of contact events.
Assuming that  the amount of solids measured on the
skin represents accumulation between washings, and
that people wash at least once per day, these adherence
values can be interpreted as daily contact rates (U.S.
EPA,  1992b).  The rate of solids accumulation on skin
over time has  not been well  studied, but probably
occurs fairly   quickly.   Therefore,  pro-rating the
adherence values for exposure time periods of less than
one day is not recommended.
        The   confidence  ratings  for   these  AF
recommendations are shown in Table 7-5.  It should be
noted that while the recommendations are based on the
best available estimates of activity-specific adherence,
they are based  on limited data from studies that have
focused primarily on soil. Therefore, they have a high
degree of uncertainty and considerable judgment must
be used when  selecting them for an assessment.  It
should also be noted that the skin adherence studies
have not considered the influence of skin moisture on
adherence.   Skin moisture  varies depending on a
number of factors, including activity level and ambient
temperature/humidity.  It is uncertain how well this
variability has been captured in the dermal adherence
studies.
Child-Specific Exposure Factors Handbook                                                 Page
September 2008	7-3

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                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 7 - Dermal Exposure Factors
Table 7-1. Recommended Values for Total Body Surface Area,

Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years

Mean

0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
Males and Females Combined
95th Percentile ,, ... ,
Multiple
m2 Percentiles
0.34
0.38
0.44
0.51
0.61 See Tables 7-7,
0.70 7-8, and 7-9
0.95
1.48
2.06
2.33

Source




U.S. EPA Analysis of
NHANES 1999-2006 data




Page
7-4
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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
Table 7-2. Recommended Values for Surface Area of Body Parts

Birth
1 to<
3to<
6to<
1 to<
2to<
3to<
6to<
11 to
16 to

Birth
lto<
3to<
6to<
lto<
2to<
3to<
6to<
11 to
16 to

Birth
lto<
3to<
6to<
lto<
2to<
3to<
6to<
11 to
16 to
a
b
Note
Age Group
to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years

to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years

to <1 month
c3 months
c6 months
c!2 months
c2 years
c3 years
c6 years
cl 1 years
<16 years
<21 years
Head
Trunk Arms
Hands
Legs
Feet

Mean Percent of Total Surface Area
18.2
18.2
18.2
18.2
16.5
14.2
13.7
12.6
9.4
7.8

0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0

053
060
069
082
087
087
104
136
149
144

062
069
080
093
101
099
130
186
194
182
35
35
35
35
35
38
31
34
33
32

0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
95
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
Calculated as mean percentage
Calculated as mean percentage
Surface area values reported in
7
7
7
7
5
5
7
7
7
2
Mean
104
118
136
161
188
235
241
375
536
592
13.7
13.7
13.7
13.7
13.0
11.8
14.2
12.7
12.9
15.3
5.3
5.3
5.3
5.3
5.7
5.3
5.9
5.0
5.3
5.4
Surface Area by Body
m2
0.040
0.045
0.052
0.062
0.069
0.072
0.108
0.137
0.205
0.282
0.015
0.017
0.020
0.024
0.030
0.032
0.045
0.054
0.084
0.099
20.6
20.6
20.6
20.6
23.1
23.2
27.3
27.9
31.3
32.2
Part1
0.060
0.068
0.078
0.093
0.122
0.142
0.207
0.301
0.498
0.592
6.5
6.5
6.5
6.5
6.3
7.1
7.3
7.2
7.5
7.1












Source




U.S. EPA, 1985






0.019
0
0
0
0
0
0
0
0
0
021
025
029
033
043
055
078
119
131


U.S. EPA Analysis
ofNHANES 1999-
2006 data and U.S.
EPA, 1985



* Percentile Surface Area by Body Partb
m2
121
136
157
182
217
270
301
514
694
750
0.047
0.052
0.060
0.070
0.079
0.083
0.135
0.188
0.266
0.356
0.018
0.020
0.023
0.027
0.035
0.037
0.056
0.074
0.109
0.126
0.070
0.078
0.091
0.105
0.141
0.162
0.259
0.413
0.645
0.750
0
0
0
0
0
0
0
0
0
0
022
025
029
033
038
050
069
107
155
165



U.S. EPA Analysis
ofNHANES 1999-
2006 data and U.S.
EPA, 1985



of body part times mean total body surface area.
of body part times 95th percentile total body surface area.
m2 can be converted to cm2 by multiplying by 10,000 cmVm2.
Child-Specific Exposure Factors Handbook
September 2008	
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                                                            Child-Specific Exposure Factors Handbook

                                                           	Chapter 7 - Dermal Exposure Factors
                          Table 7-3. Confidence in Recommendations for Body Surface Area
  General Assessment Factors
                          Rationale
Rating
  Soundness
  Adequacy of Approach
                                                                                                   Medium
   Minimal (or Defined) Bias
Total surface area estimates were based on algorithms developed using
direct measurements and data from NHANES surveys.  The methods
used for developing these algorithms were adequate. The NHANES
data and the secondary data analyses to estimate total surface areas
were appropriate. NHANES included a large sample sizes; sample size
varied with age.  Body part percentages were based on direct
measurements from a limited number of subjects.

The data used to develop the algorithms for estimating surface area
from height and weight data were limited.  NHANES collected
physical measurements of weight and height.  Body part data were
based on direct measurements from a limited number of subjects.
 Applicability and Utility
   Exposure Factor of Interest

   Representativeness
                                                                  Medium
   Currency
   Data Collection Period
The key studies were directly relevant to surface area estimates.

The direct measurement data used to develop the algorithms for
estimating total body surface area from weight and height may not be
representative of the U.S. population. However, NHANES height and
weight data were collected using a complex, stratified, multi-stage
probability cluster sampling design intended to be representative of the
U.S. population. The sample used to derive body part percentages of
total surface was not representative of U.S.  population.

The U.S. EPA analysis used the most current data at the time both
studies were conducted. The data on body part percentages were
dated; however, the age of the data is not expected to affect its utility.

The U.S. EPA analysis was based on four NHANES data sets covering
1999-2006.
  Clarity and Completeness
   Accessibility
   Reproducibility


   Quality Assurance
                                                                  Medium
The U.S. EPA analysis of the NHANES data is unpublished, but
available upon request.  U.S. EPA (1985) is a U.S. EPA-published
report.

The methodology was clearly presented; enough information was
included to reproduce the results.

Quality assurance of NHANES data was good;  quality control of
secondary data analysis was not well described.	
Page
7-6
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Chapter 7 - Dermal Exposure Factors	
Table 7-3. Confidence in Recommendations for Body Surface Area (continued)
General Assessment Factors
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The full distributions were given for total surface area.
A source of uncertainty in total surface areas resulted from
the limitations in data used to develop the algorithms for
estimating total surface from height and weight. Because of
the small sample size, there is uncertainty in the body part
percentage estimates.
The NHANES surveys received a high level of peer review.
The U.S. EPA analysis was not published in a peer-reviewed
journal.
There is one key study for total surface area and one key
study for the surface area of body parts.

Rating
Medium
Medium
Medium for Total
Surface Area and
Low for Surface
Area of Individual
Body Parts
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                                                         Child-Specific Exposure Factors Handbook

                                                        	Chapter 7 - Dermal Exposure Factors
                          Table 7-4. Recommended Values for Mean Solids Adherence to Skin
                                    Face
Arms    Hands
Legs
Feet
                                                                                         Source
Residential (indoors)1
Daycare (indoors & outdoors)11
Outdoor sports'
Indoor sports'1
Activities with soil6
Playing in mudf
Playing in sediment8


0

0

0
-
-
012
-
054
-
040
0.0041
0.024
0.011
0.0019
0.046
11
0.17
0.011
0.099
0.11
0.0063
0.17
47
0.49
0.0035
0.020
0.031
0.0020
0.051
23
0.70
0.010
0.071
-
0.0022
0.20
15
21
Holmes et al
Holmes et al
Kissel et al.,
Kissel et al.,
Holmes et al
Kissel et al.,
Shoafetal.,
,1999
,1999
1996a
1996a
,1999
1996a
2005
           Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to 13 years; N = 10)
           playing indoors.
           Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years; N
           = 21) playing both indoors and outdoors.
           Based on geometric mean soil loadings of 6 children (ages >8 years) and 1 adult engaging in Tae Kwon Do.
           Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer.
           Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years).
           Based on weighted average of geometric mean solids loading of 2 groups of children (age 9 to 14 years; N= 12)
           playing in mud.
           Based on geometric mean solids loading of 9 children (ages 7 to 12 years) playing in tidal flats.
           = No data.
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Chapter 7 - Dermal Exposure Factors	
                        Table 7-5. Confidence in Recommendations for Solids Adherence to Skin
  General Assessment Factors
                     Rationale
Rating
  Soundness
   Adequacy of Approach
   Minimal (or Defined) Bias
The approach was adequate; the skin rinsing technique is
widely employed for purposes similar to this. Small
sample sizes (4 to 9 children) were used in the studies; the
key studies directly measured soil adherence to skin.

The studies attempted to measure soil adherence for
selected activities and conditions. The number of
activities and study participants was limited.
                                                                                                    Medium
 Applicability and Utility
   Exposure Factor of Interest
   Representativeness



   Currency

   Data Collection Period
The studies were relevant to the factor of interest; the goal
was to determine soil adherence to skin.

The soil/dust studies were limited to the State of
Washington and the sediment study was limited to Rhode
Island. The data may not be representative of other
locales.

The studies were published between 1996 and 2005

Short-term data were collected. Seasonal factors may be
important, but have not been studied adequately.
                                                            Low
  Clarity and Completeness
   Accessibility

   Reproducibility
   Quality Assurance
Articles were published in widely circulated
journals/reports.

The reports clearly describe the  experimental methods,
and enough information was provided to allow for the
study to be reproduced.

Quality control was not well described.
                                                          Medium
  Variability and Uncertainty
   Variability in Population
   Uncertainty
Variability in soil adherence is affected by many factors
including soil properties, activity and individual behavior
patterns. Not all age groups were represented in the
sample.

The estimates are highly uncertain; the soil adherence
values were derived from a small number of observations
for a limited set of activities.
                                                            Low
  Evaluation and Review
   Peer Review

   Number and Agreement of Studies
The studies were reported in peer reviewed journal articles.

There are three key studies that evaluated different
activities in children.
                                                          Medium
  Overall Rating
                                                            Low
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                                                      	Chapter 7 - Dermal Exposure Factors
7.3     SURFACE AREA
7.3.1    Key Body Surface Area Studies
7.3.1.1  U.S. EPA, 1985 - Development of Statistical
        Distributions or Ranges of Standard Factors
        Used in Exposure Assessments
        The U.S.  EPA (1985) summarized the direct
measurements of the surface  area of children's body
parts provided by Boyd (1935) and Van Graan (1969)
as a percentage of total surface  area.   A total of 21
children less than 18 years of age were included. These
percentages are presented in Table 7-6. Because of the
small  sample size, it is unclear how accurately these
estimates represent averages for the age groups. Note
that  the proportion  of  total  body  surface  area
contributed by the head decreases from childhood  to
adulthood, whereas the proportion contributed by the
leg increases.

7.3.1.2  U.S. EPA Analysis ofNHANES 1999-2006
        Data
        The U.S. EPA estimated total body surface
areas  for children  in U.S.  EPA's  standard  age
categories, using the empirical relationship shown  in
Appendix 7A and U.S. EPA (1985), and body weight
and  height  data  from  the  1999-2006  NHANES.
NHANES is conducted  annually by the Center for
Disease Control (CDC), National Center of Health
Statistics (NCHS).  The survey's target population is
the civilian, noninstitutionalized U.S. population.  The
NHANES 1999-2006 survey was conducted on  a
nationwide probability sample of approximately 40,000
persons for all ages,  of which approximately 20,000
were  children.  The  survey is  designed to obtain
nationally representative information on the health and
nutritional status of the population of the United States
through interviews and direct physical examinations.  A
number of anthropometrical measurements were taken
for each participant in the study, including body weight
and height.   Unit  nonresponse to the household
interview was 19 percent, and an additional 4 percent
did not  participate  in  the  physical  examinations
(including body weight measurements).
        The NHANES  1999-2006 survey  includes
over-sampling  of low-income persons, adolescents
12-19  years, persons 60+ years  of  age,  African
Americans, and Mexican Americans. Sample data were
assigned weights to  account both for the disparity  in
sample  sizes   for  these  groups  and  for  other
inadequacies in sampling, such  as the presence  of
 non-respondents. Because the U.S. EPA utilized four
 NHANES data sets in its analysis (NHANES 1999-
 2000,2001-2002,2003-2004, and 2005-2006), sample
 weights were developed for the combined data set in
 accordance with CDC guidance from the NHANES'
 web site (http://www.cdc.gov/nchs/about/major/
 nhanes/nhanes2005-2006/faqs05_06.htm#question%2
 012).
         Table 7-7 presents the mean and percentile
 estimates of body surface area by age category for male
 and female children, combined.  Tables 7-8 and 7-9
 present mean and percentiles of body surface area by
 age category for male and female children, respectively.
 An advantage of using the NHANES datasets to derive
 surface area estimates is that data are available for
 infants from birth and older. In addition, the NHANES
 data  are  nationally  representative  and remain  the
 principal  source of body  weight and  height  data
 collected nationwide from a large number of subjects.
 It should be noted that in the NHANES surveys height
 measurements for children under 2 years of age were
 based on recumbent length while standing height
 information was collected for children aged 2 years and
 older. Some studies have reported differences between
 recumbent length and standing height measurements for
 the same individual, ranging from 0.5 to  2 cm,  with
 recumbent  length  being  the  larger  of  the  two
 measurements (Buyken et al, 2005). The use of height
 data  obtained  from two  different types  of height
 measurements to estimate surface area of children may
 potentially introduce errors  into the estimates.

 7.3.2    Relevant Body Surface Area Studies
 7.3.2.1  Phillips et al, 1993 - Distributions of Total
         Skin Surface Area to Body Weight Ratios
         Phillips  et  al.  (1993)  observed  a strong
 correlation (0.986) between body surface area and body
 weight and studied the effect of using these factors as
 independent variables in the lifetime average daily dose
 (LADD)  equation (See  Chapter 1).   The authors
 suggested that, because of the correlation between these
 two variables, the use of body surface area to body
 weight (SA/B W) ratios in human exposure assessments
 may be more appropriate than treating these factors as
 independent variables.  Direct measurement data from
 the scientific literature were used to calculate SA/BW
 ratios for two age groups of children (infants aged 0 to
 2 years and children aged 2.1 to 17.9 years). These
 ratios were calculated by dividing body surface areas by
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Chapter 7 - Dermal Exposure Factors	
corresponding body weights for the 401  individuals
analyzed by Gehan and George (1970) and summarized
by U.S. EPA (1985).  Distributions of SA/BW ratios
were developed, and summary statistics were calculated
for the two age groups and the combined data set.
        Summary statistics for the two children's age
groups are presented in Table 7-10.  The shapes of
these SA/BW distributions  were determined using
D'Agostino's  test, as described  in D'Agostino et al.
(1990). The results indicate that the SA/BW ratios for
infants are lognormally distributed.  SA/BW ratios for
children  were  neither normally  nor  lognormally
distributed. According to Phillips etal. (1993), SA/BW
ratios may be used to calculate L ADDs by replacing the
body surface area factor in the numerator of the LADD
equation with the SA/BW ratio  and eliminating the
body weight factor in the denominator  of the LADD
equation.
        The effect of gender  and  age on  SA/BW
distribution  was  also  analyzed by classifying  the
401  observations by  gender  and age.   Statistical
analyses indicated no significant differences between
SA/BW ratios for males and females.  SA/BW ratios
were found  to  decrease with  increasing age.   The
advantage of this study is that it studied correlations
between surface area and body weight. However, data
could not be broken out by finer age categories.

7.3.2.2  Wong et al, 2000-Adult Proxy Responses to
        a Survey of Children's Dermal Soil Contact
        Activities
        Wong et al.  (2000) reported on two surveys
that gathered information on activity patterns related to
dermal contact with soil. The first of these  national
phone  surveys (also  reported on by Garlock et al.,
1999)  was conducted  in  1996  using  random digit
dialing. Information about children was  gathered from
adults over the age of 18, and obtained information on
211 children.  For older children (those between the
ages of 5 and 17 years), information was gathered on
their  participation  in  "gardening  and yardwork,"
"outdoor sports," and "outdoor play activities."   For
children less than 5 years old, information was gathered
on "outdoor  play activities," including whether the
activity occurred on a playground or yard with "bare
dirt or mixed grass and dirt" surfaces. Information on
the types of clothing worn while participating in these
play activities during warm weather months (April
though October) was obtained.  The results of  this
survey indicate that most children wore short pants, a
dress or skirt, short sleeve shirts, no socks, and leather
or canvas shoes during the outdoor play activities of
interest.  Using the survey data on  clothing and total
body surface area data from U.S. EPA (1985), estimates
were made of the skin area  exposed (expressed as
percentages of total body surface area) associated with
various age ranges and activities.  These estimates are
provided in Table 7-11.

7.4     ADHERENCE OF SOLIDS TO SKIN
7.4.1   Key Adherence of Solids to Skin Studies
7.4.1.1  Kissel et al., 1996a - Field Measurements of
        Dermal Soil Loading Attributable to Various
        Activities:    Implications for  Exposure
        Assessment
        Kissel  et  al.  (1996a)  collected   direct
measurements of soil loading on the surface of the skin
of volunteers, before and after activities expected to
result in soil contact. Soil adherence associated with
the  following indoor  and outdoor  activities  were
estimated: greenhouse gardening, tae kwon do karate,
soccer, rugby, reed gathering, irrigation installation,
truck farming, and playing  in mud.  Skin surface areas
monitored included hands,  forearms, lower legs, faces
and/or feet (Kissel et al., 1996a).
        Several of the activities studied by Kissel et al.
(1996a) involved children,  as shown in Table 7-12. A
group  of  young male  soccer  players (Soccer) was
monitored before and after  40 minutes of practice on a
field consisting of half  grass and half bare earth.  Six
children were monitored after  10 and 20 minutes of
playing in the mud at a lake with an exposed shoreline
(Kids-in-mud No. 1 and No. 2).  For indoor activities,
soil loadings were estimated from six children and one
adult practicing  tae kwon do  (Tae Kwon  Do);  the
activity lasted 90 minutes including a 30-min warm up.
Information  on  activity duration,  sample  size and
clothing worn by participants is provided in Table 7-12.
The  subjects' body  surfaces (forearms, hands,  lower
legs  for all sample groups; faces and/or feet pairs in
some sample groups) were washed before and after the
monitored activities. Paired samples were pooled into
single ones.  The mass recovered was converted to soil
loading using allometric models of surface area.
        Geometric  means  for  post-activity  soil
adherence by  activity  and body  region  for the four
groups of volunteers evaluated are presented in  Table
7-13. Children playing in the mud had the highest soil
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                                                        	Chapter 7 - Dermal Exposure Factors
loadings among the groups evaluated. The results also
indicate that, in general, the amount of soil adherence to
the hands is higher than for other parts of the  body
during the same activity.
        An advantage of this study is that it provides
information on soil adherence to various body  parts
resulting from unscripted activities. However, the study
authors noted that, because the activities were unstaged,
"control of variables such as specific behaviors within
each  activity, clothing  worn by  participants,  and
duration of activity was limited."   In addition, soil
adherence  values were  estimated based on a small
number of observations  and very young children and
indoor activities were under-represented in the study.

7.4.1.2  Holmes et aL, 1999 - Field Measurements of
        Dermal  Loadings  in  Occupational  and
        Recreational A ctivities
        Holmes et al. (1999) collected pre- and  post-
activity   soil   loadings  on various  body  parts  of
individuals  within   groups   engaged  in  various
occupational and recreational activities. These groups
included: children at a daycare center (Daycare Kids),
children playing indoors in a residential setting (Indoor
Kids), individuals (aged  16 to 35) removing historical
artifacts from  a site (Archeologists), and individuals
(aged   16 to  35)  performing  gardening   work
(Gardeners). This study  was conducted as a follow up
to previous field sampling  of soil adherence  on
individuals participating in various activities (Kissel et
al., 1996a). For this round of sampling, soil loading
data were collected utilizing the same methods used and
described  in  Kissel  et  al.  (1996a).   Information
regarding  the groups studied  and their  observed
activities is presented in  Table 7-12.
        The daycare children studied were all at one
location,  and  measurements  were  taken  on  three
different days.  The children freely played both indoors
in the house  and outdoors in the backyard.  The
backyard was  described  as having a grass lawn,  shed,
sand box,  and wood  chip  box.  In this setting, the
children engaged in typical activities including: playing
with toys  and each other, wrestling, sleeping, and
eating. The number of children within each day's group
and the  clothing worn is described in Table 7-12. The
five children measured on the first day were washed
first thing in the morning to establish a preactivity level.
They  were next  washed  at noon to determine the
postactivity soil loading for the morning (Daycare Kids
 No. la). The same children were washed once again at
 the close of the day for measurement of soil adherence
 from the afternoon play activities (Daycare Kids No.
 Ib). For the second observation day (Daycare Kids No.
 2), postactivity data were collected for five children.
 All the activities on this day occurred indoors. For the
 third daycare group (Daycare Kids No. 3), four children
 were studied.
         On two separate days, children playing indoors
 in a home environment were monitored. The first group
 (Indoor Kids No. 1) had four children while the second
 group (Indoor Kids No. 2) had six children.  The play
 area was described by the authors as being primarily
 carpeted.  The clothing worn by the children within
 each day's group is described in Table 7-12.
         Seven individuals (Archeologists), ages 16 to
 35 years, were monitored while excavating, screening,
 sorting, and  cataloging historical  artifacts from  an
 ancient Native American site  during a single  event.
 Eight volunteers (Gardeners), ages 16 to 35 years, were
 monitored while performing gardening activities (i.e.,
 weeding, pruning, digging  small irrigation trenches,
 picking and cleaning fruit). The clothing worn by these
 groups is described in Table 7-12.
         The geometric means and standard deviations
 of the  postactivity soil adherence for each group of
 individuals and for each body part are summarized in
 Table 7-13.  According to the authors, variations in the
 soil loading  data from the daycare participants reflect
 differences in the weather and access to the outdoors.
         An advantage of this study is that it provides
 a supplement to soil loading data collected in a previous
 round of studies (Kissel et al., 1996a). Also, the data
 support the assumption that hand loading can be used as
 a conservative estimate of soil loading on other body
 surfaces for the same activity.  The  activities studied
 represent normal child play both indoors and outdoors,
 as well as different combinations of clothing. The small
 number of participants is a disadvantage of this  study.
 Also, the children studied and the activity  setting may
 not be representative of the U.S. population.

 7.4.1.3  Shoafet aL, 2005 - Child Dermal Sediment
         Loads Following Play in a  Tide Flat
         The purpose  of  this study was to  obtain
 sediment adherence data for children playing in  a tidal
 flat (Shoreline Play).  The study was conducted on one
 day in late September 2003 at a tidal flat in  Jamestown,
 Rhode  Island.  Nine subjects (three females and  six
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Chapter 7 - Dermal Exposure Factors	
males) ages 7 to 12 years old participated in the study.
Information  on  activity  duration, sample  size  and
clothing worn by participants is provided in Table 7-12.
Participants'   parents  completed  questionnaires
regarding their child's typical activity patterns during
tidal  flat play,  exposure  frequency  and  duration,
clothing  choices,   bathing  practices  and  clothes
laundering.
         This study reported direct measurements of
sediment loadings on five body parts (face, forearms,
hands, lower  legs,  and feet) after play in a tide flat.
Each of nine subjects participated in two timed sessions
and pre-  and post-activity sediment loading data were
collected.   Geometric mean (geometric  standard
deviations) dermal  loadings (mg/cm2)  on the face,
forearm,  hands, lower legs,  and feet for the combined
sessions, as shown in Table 7-13, were 0.04 (2.9), 0.17
(3.1), 0.49 (8.2), 0.70 (3.6) and 21 (1.9), respectively.
         The primary advantage of this study is that it
provides adherence data specific to children  and
sediments  which   had  previously   been   largely
unavailable.   Results will be useful to risk assessors
considering   exposure  scenarios  involving  child
activities at a coastal shoreline or tidal flat.  The limited
number of participants (9) and sampling during just one
day and  at one location, make extrapolation to other
situations uncertain.

7.4.2    Relevant   Adherence  of Solids  to Skin
         Studies
7.4.2.1  Kissel et al, 1996b - Factors Affecting Soil
        Adherence to Skin in Hand-press  Trials:
        Investigation  of  Soil Contact and Skin
         Coverage
        Kissel et al. (1996b) conducted soil adherence
experiments using five soil types obtained locally in the
Seattle, WA, area: sand, 2 types of loamy  sand, sandy
loam,  and  silt  loam.   All soils  were analyzed  by
hydrometer  (settling  velocity)   to   determine
composition.   Clay content ranged from 0.5 to 7.0
percent.   Organic  carbon content,  determined  by
combustion, ranged from 0.7 to 4.6 percent. Soils were
dry-sieved to obtain particle size ranges of <150, 150-
250, and >250 (im.  For each soil type, the amount of
soil adhering to an adult female hand, using both sieved
and unsieved soils, was determined by measuring the
soil  sample  weight before and after the hand was
pressed into a pan containing the test soil. Loadings
were estimated by dividing the recovered soil mass by
total hand area, although loading occurred primarily on
only one side  of the hand.  Results showed that
generally,  soil  adherence  to  hands  was  directly
correlated with moisture content, inversely correlated
with particle size, and independent of clay content or
organic carbon content. The advantage of this study is
that it provides information on how soil type can affect
adherence to the skin.  However, the  soil adherence
data are for a single subject and the data are limited to
five soil samples.

7.4.2.2  Kissel et al, 1998 - Investigation of Dermal
        Contact with Soil in Controlled Trials
        Kissel et al. (1998) measured dermal exposure
to soil from staged activities conducted in a greenhouse.
A fluorescent marker was mixed in soil  so that soil
contact for a particular skin surface  area could be
identified.  The subjects, which included a group of
children,   were  video-imaged  under  a  long-wave
ultraviolet (UV) light before and after soil contact.  In
this manner, soil contact on hands, forearms, lower legs,
and faces was assessed by presence of fluorescence.  In
addition to fluorometric data, gravimetric measurements
for preactivity and postactivity were obtained from the
different body parts examined.
        The studied group of children played for 20
minutes in a soil  bed of varying moisture content
representing wet  and dry  soils.  Three trials with
children were conducted, each representing a different
clothing/soil moisture scenario.  For wet soils, both
combinations of long sleeves and long pants, and short
sleeves and short pants were tested. For dry soil, only
short sleeves and short pants were worn during play.
Clothing was laundered after each trial. The parameters
describing each of these trials are summarized in Table
7-14. Before each trial, each child was washed in order
to obtain a preactivity or  background  gravimetric
measurement.
        For wet soil, postactivity fluorescence results
indicated that the hand had a much  higher fractional
coverage than other body surfaces (see Figure 7-1).  No
fluorescence was detected on the forearms or lower legs
of children dressed in long sleeves and pants.  As
shown   in  Figure  7-2,   postactivity   gravimetric
measurements showed higher soil loading on hands and
much lower amounts on other body surfaces,  as was
observed with fluorescence  data.  According to Kissel
et al. (1998), the relatively low loadings observed on
non-hand body parts may be a result of a more limited
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                                                      	Chapter 7 - Dermal Exposure Factors
area of contact for the body part rather than lower
localized loadings.  The highest soil loading observed
was a geometric mean dermal loading of 0.7 mg/cm2,
found on the children's hands following play in wet
soil. Mean loadings were lower on hands in the dry soil
trial and on lower legs, forearms, and faces in both the
wet and dry soil trials.  Higher loadings were observed
for all body surfaces with the higher moisture content
soils.
        This report  is valuable in showing soil
loadings from soils of different moisture content and
providing evidence that dermal exposure to soil is not
uniform for various body surfaces.  This study also
provides some evidence of the protective  effect of
clothing. Disadvantages of the study include the small
number of study  participants  and a short activity
duration.

7.5     REFERENCES FOR CHAPTER 7
Boyd, E. (1935) The growth of the surface area of the
        human body.  Minneapolis, MN:  University
        of Minnesota Press.
Buyken, A.E.; Hahn, S.; Kroke, A. (2005) Differences
        between  recumbent   length  and  stature
        measurement in  groups  of 2-  and 3-y-old
        children and its  relevance  for the  use  of
        European body mass index references.  Int J
        Obes 29:24-28.
Cohen-Hubal,  E.A.;   Sheldon, L.S.; Burke,  J.M.;
        McLundy, T.R.; Berry, M.R.; Rigas, M.L.;
        Zartarian,  V.G.;  Freeman, N.C.G.   (1999)
        Children's exposure assessment: A review of
        factors influencing children's exposure, and
        the data available to characterize and assess
        that exposure. Research Triangle Park, NC:
        U.S. EPA,  National  Exposure   Research
        Laboratory.
D'Agostino, R.B.; Belanger, A.; D'Agostino, R.B. Jr. A
        suggestion for using powerful and informative
        tests of normality. The American Statistician
        44(4);316-321.
Dubois, D.; Dubois, E.F. (1916) A formula to estimate
        the approximate  surface area if height and
        weight be known.  Arch Intern Med 17:863-
        871.
Garlock, T.J.; Shirai, J.H.; Kissel, J.C.  (1999) Adult
        responses to a survey of soil contact  related
        behaviors.  J Expo Anal Environ Epidemiol
        9:134-142.
 Gehan, E.; George, G.L.  (1970) Estimation of human
         body surface  area from height and weight.
         Cancer ChemotherRep 54(4):225-235.
 George, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz,
         G.J.  (1979) Letters to the editor. J Pediatr
         94(2):342.
 Holmes, Jr., K.K.; Shirai, J.H.; Richter, K.Y.; Kissel,
         J.C.  (1999) Field  measurement of dermal
         loadings  in occupational  and recreational
         activities. Environ Res Section A80:148-157.
 Kissel, J.C.; Richter, K.; Fenske, R.  (1996a)  Field
         measurements   of   dermal  soil loading
         attributable to various activities:  Implications
         for  exposure   assessment.    Risk  Anal
 Kissel, J.C.; Richter, K.; Duff, R.; Fenske, R. (1996b)
         Factors  affecting soil adherence to skin in
         hand-press  trials.    Bull  Environ Contam
         Toxicol  56:722-728.
 Kissel, J.C.; Shirai, J.H.; Richter, K.Y.; Fenske, R.A.
         (1998) Investigation of dermal contact with
         soil in controlled trials.  J Soil Contam 7(6):
         737-752.
 Phillips,  L.J.;  Fares, R.J.;  Schweer, L.G.  (1993)
         Distributions of total skin surface area to body
         weight ratios for  use in  dermal  exposure
         assessments.  J Expo Anal Environ Epidemiol
         3(3):331-338.
 Shoaf, M.B.;   Shirai, J.H.; Kedan, G.;  Schaum, J.;
         Kissel, J.C.  (2005) Child dermal sediment
         loads following play in a tide flat.  J Expo
         Anal Environ Epidemiol 15:407-412.
 U.S.  EPA    (1985)  Development  of  statistical
         distributions or ranges of standard factors used
         in exposure assessments. Washington, DC:
         Office of Research and Development, Office
         of Health and  Environmental Assessment.
         EPA 600/8-85-010. Available from:  NTIS,
         Springfield, VA. PB85-242667.
 U.S. EPA (1992a) Guidelines for exposure assessment.
         Federal  Register.  FR 57:104:22888-22938.
         May 29, 1992.
 U.S. EPA   (1992b)  Dermal  exposure assessment:
         principles and applications. Washington, DC :
         Office of Research and Development, Office
         of   Health   and   Environmental
         Assessment/OHEA. U.S. EPA/600/8-9-91.
 U.S. EPA   (2004) Risk  assessment  guidance  for
         Superfund (RAGS): Volume I, Human Health
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Chapter 7 - Dermal Exposure Factors	
       Evaluation Manual, Part E. Washington, DC.
       EPA/540/R/99/005.
U.S. EPA (2005) Guidance on selecting age groups for
       monitoring and assessing childhood exposures
       to  environmental  contaminants.  U.S.
       Environmental   Protection  Agency,
       Washington,  DC.    EPA/630/P-03/003F.
       November 2005.
Van Graan, C.H.  (1969) The  determination of body
       surface area.  S AfrMed J 43(31):952-959.
Wong, E.Y.; Shirai, J.H.; Garlock, T.J.; Kissel, J.C.
       (2000) Adult proxy responses to a survey of
       children's dermal soil contact  activities.  J
       Expo Anal Environ Epidemiol 10:509-517.
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Table 7-6. Percentage of Total Body Surface Area by Body Part For Children
Males and Females Combined
Age
(years)
<1
1 <2
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9< 10
11 <12
12<13
13<14
14<15
15<16
16<17
17 < 18
N
Min.
Max.
Source:

N Head
Mean Min-Max
2:0 18.2 18.2-18.3
1:1 16.5 16.5-16.5
1:0 14.2
0:5 13.6 13.3-14.0
1:3 13.8 12.1-15.3

1:0 13.1


0:2 12.0 11.6-12.5

1:0 8.7
1:0 10.0


1:0 8.0
1:0 7.6
= Number of subjects, (M:F =
= Minimum percent.
= Maximum percent.
U.S. EPA, 1985.

Trunk
Mean Min-Max
35.7 34.8-36.6
35.5 34.5-36.6
38.5
31.9 29.9-32.8
31.5 30.5-32.4

35.1


34.2 33.4-34.9

34.7
32.7


32.7
31.7
males:females).

Percent of Total
Arms Hands Legs Feet
Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max
13.7 12.4-15.1 5.3 5.2-5.4 20.6 18.2-22.9 6.5 6.5-6.6
13.0 12.8-13.1 5.7 5.6-5.8 23.1 22.1-24.0 6.3 5.8-6.7
11.8 5.3 23.2 7.1
14.4 14.2-14.7 6.1 5.8-6.3 26.8 26.0-28.6 7.2 6.8-7.9
14.0 13.0-15.5 5.7 5.2-6.6 27.8 26.0-29.3 7.3 6.9-8.1

13.1 4.7 27.1 6.9


12.3 11.7-12.8 5.3 5.2-5.4 28.7 28.5-28.8 7.6 7.4-7.8

13.7 5.4 30.5 7.0
12.1 5.1 32.0 8.0


13.1 5.7 33.6 6.9
17.5 5.1 30.8 7.3


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Chapter 7 - Dermal Exposure Factors	
Table 7-7. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Skin Surface Area (m2) Derived from U.S. EPA Analysis of NHANES 1999-2006
Males and Females Combined
Percentiles
N
154
281
488
923
1159
1122
2303
3590
5294
4843
Mean
0.29
0.33
0.38
0.45
0.53
0.61
0.76
1.08
1.59
1.84
5th
0.24
0.27
0.33
0.38
0.45
0.52
0.61
0.81
1.19
1.47
10th
0.25
0.29
0.34
0.39
0.46
0.54
0.64
0.85
1.25
1.53
15th
0.26
0.29
0.35
0.40
0.47
0.55
0.66
0.88
1.31
1.58
25th
0.27
0.31
0.36
0.42
0.49
0.57
0.68
0.93
1.4
1.65
50th
0.29
0.33
0.38
0.45
0.53
0.61
0.74
1.05
1.57
1.80
75th
0.31
0.35
0.40
0.48
0.56
0.64
0.81
1.21
1.75
1.99
85th
0.31
0.37
0.42
0.49
0.58
0.67
0.85
1.31
1.86
2.10
90th
0.33
0.37
0.43
0.50
0.59
0.68
0.89
1.36
1.94
2.21
95th
0.34
0.38
0.44
0.51
0.61
0.70
0.95
1.48
2.06
2.33
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Table 7-8. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <1 6 years
16 to <21 years
Skin Surface Area (m2) Derived from U
Males
S. EPA Analysis of NHANES 1999-2006
Percentiles
N
85
151
255
471
620
548
1150
1794
2593
2457
Mean
0.29
0.33
0.39
0.45
0.53
0.62
0.76
1.09
1.61
1.94
5th
0.24
0.28
0.34
0.39
0.46
0.54
0.61
0.82
1.17
1.61
10th
0.25
0.29
0.35
0.41
0.47
0.56
0.64
0.86
1.23
1.66
15th
0.26
0.30
0.36
0.42
0.48
0.56
0.66
0.89
1.28
1.7
25th
0.27
0.31
0.37
0.43
0.50
0.58
0.69
0.94
1.39
1.76
50th
0.29
0.34
0.39
0.46
0.53
0.62
0.75
1.06
1.60
1.91
75th
0.31
0.36
0.41
0.48
0.57
0.65
0.82
1.21
1.79
2.08
85th
0.33
0.37
0.42
0.49
0.58
0.67
0.86
1.29
1.90
2.22
90th
0.34
0.37
0.43
0.50
0.59
0.68
0.89
1.34
1.99
2.30
95th
0.36
0.38
0.44
0.51
0.62
0.70
0.95
1.46
2.12
2.42
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Child-Specific Exposure Factors Handbook
September 2008	
Page
 7-17

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                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 7 - Dermal Exposure Factors
Table 7-9. Mean and Percentile
Age
Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years
Skin Surface Area (m2) Derived from U
Females
S. EPA Analysis of NHANES 1999-2006
Percentiles
N
69
130
233
452
539
574
1153
1796
2701
2386
Mean
0.28
0.32
0.38
0.44
0.52
0.60
0.75
1.08
1.57
1.73
5th
0.24
0.27
0.32
0.38
0.44
0.51
0.61
0.80
1.20
1.42
10th
0.25
0.28
0.33
0.39
0.46
0.53
0.64
0.85
1.28
1.47
15th
0.26
0.29
0.34
0.40
0.47
0.54
0.66
0.87
1.34
1.51
25th
0.27
0.30
0.35
0.41
0.48
0.56
0.68
0.92
1.42
1.57
50th
0.28
0.31
0.38
0.44
0.52
0.59
0.74
1.04
1.55
1.69
75th
0.30
0.35
0.40
0.47
0.56
0.63
0.80
1.21
1.69
1.85
85th
0.30
0.36
0.40
0.48
0.57
0.66
0.84
1.33
1.8
1.98
90th
0.31
0.37
0.41
0.49
0.58
0.67
0.88
1.39
1.88
2.06
95th
0.33
0.37
0.43
0.51
0.59
0.70
0.94
1.51
2.00
2.17
N = Number of observations.
Source: U.S. EPA Analysis of NHANES
1999-2006 data.
Page
7-18
 Child-Specific Exposure Factors Handbook
	September 2008

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00
   I
    ri
    1=
Table 7-10. Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (m2/kg)
Age
(years)
Oto2
2.1 to 17
SD
SE
Source:
Rannp
Mean ,,. // SD SE
Mm-Max ^ w
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                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 7 - Dermal Exposure Factors
Table 7-11. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities


Age (years)
N
Mean
Median
SD
N = Number of observations.
SD = Standard deviation.
Source: Wong et al., 2000.
Skin Area Exposed (% of total body
Play Gardening/yardwork
<5 5-17
41 437
38.0 33.8
36.5 33.0
6.0 8.3


surface area)
Organized Team Sport
5-17
65
29.0
30.0
10.5


Page                                       Child-Specific Exposure Factors Handbook
7-20	September 2008

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00
   I
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1ab\el-\2. Summary of 7 ie\d Studies
Activity
Month Event1 (hrs)
N
M
F
Age (years)
Conditions
Clothing Study
Indoor
fae Kwon Do


Indoor Kids No. I

Indoor Kids No. 2

Daycare Kids No. la


Daycare Kids No. \b


Daycare Kids No. 2b

Daycare Kids No. 3


Feb. 1.5


Jan. 2

Feb. 2

Aug. 3.5


Aug. 4


Sept. 8

Nov. 8


7


4

6

6


6


5

4


6


3

4

5


5


4

3


1


1

2

1


1


1

1


8-42


6-13

3-13

1-6.5


1-6.5


1-4

1-4.5


Carpeted floor


Playing on carpeted floor

Playing on carpeted floor

Indoors: linoleum surface;
Outdoors: grass, bare earth,
barked area
Indoors: linoleum surface;
Outdoors: grass, bare earth,
barked area
Indoors: low napped
carpeting, linoleum surfaces
Indoors: linoleum surface,
Outside: grass, bare earth,
barked area
All in long sleeve-long pants martial Kissel et al.,
arts uniform, sleeves rolled back, 1996a
barefoot
3 of 4 short pants, 2 of 4 short Holmes et al.,
sleeves, socks, no shoes 1999
5 of 6 long pants, 5 of 6 long sleeves,
socks, no shoes
4 of 6 in long pants, 5 of 6 short
sleeves, socks, shoes

4 of 6 long pants, 5 of 6 short
sleeves, 3 of 6 barefoot all afternoon,
others barefoot half the afternoon
4 of 5 long pants, 3 of 5 long sleeves,
all barefoot for part of the day
All long pants, 3 of 4 long sleeves,
socks and shoes

Outdoor
Soccer

Kids-in-mud No. I

Kids-in-mud No. 2

Gardeners


Archeologists

Shoreline Play

* Event duration.
Nov. 0.67

Sept. 0.17

Sept. 0.33

Aug. 4


July 11.5

Sept. 0.33-1.0


8

6

6

8


7

9


8

5

5

1


3

6


0

1

1

7


4

3


13-15

9-14

9-14

16-35


16-35

7-12


Half grass- half bare earth

Lake shoreline

Lake shoreline

Weeding, pruning, digging a
trench

Digging with trowel,
screening dirt, sorting
Tidal flat


6 of 8 long sleeves, 4 of 8 long pants, Kissel et al.,
3 of 4 short pants and shin guards 1996a
All in short sleeve T-shirts, shorts,
barefoot
All in short sleeve T-shirts, shorts,
barefoot
6 of 8 long pants, 7 of 8 short Holmes et al.,
sleeves, 1 sleeveless, socks, shoes, 1999
intermittent use of gloves
6 of 7 short pants, all short sleeves, 3
no shoes or socks, 2 sandals
No shirt or short sleeve T-shirts, Shoaf et al.,
shorts, barefoot 2005

b Activities were confined to the house.
N = Number of subj ects
M = Male.
F = Female.





















I
1
s
                                                                                                                                                                                  ri
                                                                                                                                                                                         Q

                                                                                                                                                                                         ri
        &
        &

        1=

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 7 - Dermal Exposure Factors
Table
Activity
7-13. Geometric Mean and Geometric Standard Deviations of Solids Adherence by
Activity and Body Region1


Post-activity Dermal Solids Loadings (mg/cm2)
Hands
Arms
Legs
Faces Feet
Indoor
Tae Kwon Do

Indoor Kids No. 1

Indoor Kids No. 2

Day care Kids No. la

Day care Kids No. Ib

Day care Kids No. 2

Day care Kids No. 3

7

4

6

6

6

5

4

0.0063
1.9
0.0073
1.9
0.014
1.5
0.11
1.9
0.15
2.1
0.073
1.6
0.036
1.3
0.0019
4.1
0.0042
1.9
0.0041
2.0
0.026
1.9
0.031
1.8
0.023
1.4
0.012
1.2
0.0020
2.0
0.0041
2.3
0.0031
1.5
0.030
1.7
0.023
1.2
0.011
1.4
0.014
3.0
0.0022
2.1
0.012
1.4
0.0091
1.7
0.079
2.4
0.13
1.4
0.044
1.3
0.0053
5.1
Outdoor
Soccer

Kids-in-mud No. 1

Kids-in-mud No. 2

Gardeners

Archeologists
Shoreline Play

8

6

6

8

7
9

0.11
1.8
35
2.3
58
2.3
0.20
1.9
0.14
1.3
0.49
8.2
* Means are presented above the standard deviations
indicating high variability in the data.
N = Number of subj ects .
Sources: Kissel et al., 1996a; Holmes
0.011
2.0
11
6.1
11
3.8
0.050
2.1
0.041
1.9
0.17
3.1
0.031
3.8
36
2.0
9.5
2.3
0.072
-
0.028
4.1
0.70
3.6
0.012
1.5
24
3.6
6.7
12.4
0.058 0.17
1.6
0.050 0.24
1.8 1.4
0.04 21
2.9 1.9
. The standard deviations generally exceed the means by large amounts
etal., 1999; Shoafetal., 2005.
Page
7-22
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
Table 7-14. Summary of Controlled Greenhouse Trials - Children Playing



a
N
Activity Ages Duration (min) Soil Moisture Clothing" N Male
(years) (%)
Playing 8 to 12 20 17-18 L 4 3
16-18 S 9 5
3-4 S 5 3
L, long sleeves and long pants; S, short sleeves and short pants.
= Number of subjects.
Female
1
4
2

Source: Kissel etal., 1998.
Child-Specific Exposure Factors Handbook                                       Page
September 2008	7-23

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                                                    Child-Specific Exposure Factors Handbook

                                                    	Chapter 7 - Dermal Exposure Factors
                                Hands
                    Lower legs/short pants
                   Forearms/short sleeves
                                     -
                                      0      20
                                                 1—r~
                                                  40
                                                        60
          •—r~
           80
'—I
 100
                                              Percent Fluorescing
       Figure 7-1.      Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing in Wet
                      Soils (bars are arithmetic means and corresponding 95% confidence intervals)

                      Source: Kissel etal, 1998.
                           10 -,
                                                              child, wet
                     "O
                     «s
                     o
']
0,1-


0.01-

0 00! 	
4






child, dry
I
T
"T
f t
1 ' <
i


> ,. I
T
- T? j
ff


       Figure 7-2.      Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils (symbols are
                      geomettric means and 95% confidence intervals)

                      Source: Kissel etal., 1998.
Page
7-24
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
                                 APPENDIX 7A

                    FORMULAS FOR TOTAL BODY SURFACE AREA
Child-Specific Exposure Factors Handbook                                      Page
September 2008	7A-1

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                                                       Child-Specific Exposure Factors Handbook

                                                      	Chapter 7 - Dermal Exposure Factors
APPENDIX 7A - FORMULAS FOR TOTAL
BODY SURFACE AREA

        Most formulas for estimating surface area (S A)
relate height to weight to surface area.  The following
formula was proposed by Gehan and George (1970):
       SA = KW2/3
(Eqn. 7A-1)
where:
          SA  = surface area in square meters;
          W  = weight in kg; and
          K   = constant.

        While the above equation has been criticized
because human bodies have different specific gravities
and because the surface area per unit volume differs for
individuals with  different body  builds, it  gives  a
reasonably good estimate of surface area.
        A formula published in 1916 that still finds
wide acceptance and use is that of DuBois and DuBois
(1916). Their model can be written:
       SA  =
(Eqn. 7A-2)
where:
          SA  = surface area in square meters;
          H   = height in centimeters; and
          W  = weight in kg.

        The values of a0 (0.007182), al (0.725), and a2
(0.425) were estimated from a sample of only  nine
individuals for  whom  surface  area  was  directly
measured. Boyd (1935) stated that the Dubois formula
was considered a reasonably adequate substitute for
measuring surface area. Nomograms for determining
surface area from height and mass presented in Volume
I of the Geigy Scientific Tables (1981) are based on the
DuBois  and  DuBois  formula.    In  addition,   a
computerized literature search conducted for this report
identified several articles written in the last 10 years in
which the DuBois and DuBois formula was used to
estimate body surface area.
        Boyd (1935) developed new constants for the
DuBois and DuBois model  based on  231 direct
measurements  of body  surface area found in the
literature.  These data were limited to measurements of
surface area by coating methods (122 cases), surface
integration  (93 cases),  and triangulation (16 cases).
The subjects were Caucasians of normal body build for
whom data on weight, height, and age (except for exact
age of adults) were complete.  Resulting values for the
constants in the DuBois and DuBois model were a0 =
0.01787,  E!  = 0.500, and a2 =  0.4838.   Boyd also
developed a  formula based  exclusively on weight,
which was inferior to the DuBois and DuBois formula
based on height and weight.
        Gehan and  George (1970) proposed another
set of constants for the DuBois and DuBois model. The
constants  were  based  on  a total  of  401  direct
measurements of surface area, height, and weight of all
postnatal subjects listed  in Boyd (1935). The methods
used to measure these subjects were coating (163
cases), surface integration (222 cases), and triangulation
(16 cases).
        Gehan and George (1970) used a least-squares
method to identify the values of the constants.  The
values of the constants chosen are those that minimize
the  sum  of the squared percentage errors of  the
predicted values of surface area. This approach was
used because the importance of an error of 0.1 square
meter depends on the surface area of the individual.
Gehan and  George (1970) used the 401  observations
summarized in Boyd  (1935)  in  the  least-squares
method. The following estimates of the constants were
obtained: a0 = 0.02350, al = 0.42246, and a2 = 0.51456.
Hence, their equation for predicting SA is:
                   SA = 0.02350 H
                                 -0.42246-1-170.51456
                   W°
(Eqn. 7A-3)
                   or in logarithmic form:
                   InSA = -3.75080 + 0.42246 InH + 0.51456 InW
                   (Eqn. 7A-4)

                   where:

                           SA   =   surface area in square meters;
                           H    =   height in centimeters; and
                           W   =   weight in kg.

                           This prediction explains more than 99 percent
                   of the  variations  in surface  area  among  the  401
                   individuals measured (Gehan and George, 1970).
Page
7A-2
                   Child-Specific Exposure Factors Handbook
                  	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 7 - Dermal Exposure Factors	
        The equation proposed by Gehan and George
(1970) was determined by the U.S. EPA (1985) as the
best choice for estimating  total  body surface  area.
However,  the paper by Gehan  and  George  gave
insufficient information to estimate the  standard error
about  the  regression.   Therefore,  the  401  direct
measurements of children and adults (i.e., Boyd, 1935)
were reanalyzed in U. S. EPA (1985) using the formula
of Dubois  and Dubois (1916)  and  the   Statistical
Processing  System (SPS) software package to obtain
the standard error.
        The Dubois  and Dubois (1916) formula uses
weight and height as  independent variables to predict
total body surface area (SA), and can be written as:

        SA.  =a0Ha'W.a'e.        (Eqn. 7A-5)
or in logarithmic form:

ln(SA), = Ina0 + aJnH, + a2lnW, + Ine,    (Eqn. 7A-6)

where:

      SAj          =   surface  area  of the  i-th
                       individual (m2);
      Hj            =   height of the i-th individual
                       (cm);
      Wj           =   weight of the i-th individual
                       (kg);
      a0, ab  and a2  =   parameters to be estimated;
      and
      e;            =   a random error  term with
                       mean  zero  and constant
                       variance.

        Using the least squares procedure for the 401
observations, the  following parameter estimates and
their standard errors were obtained:

a0 = -3.73 (0.18), al = 0.417 (0.054), a2 = 0.517 (0.022)

The model is then:

   SA = 0.0239 H°-417W°-517         (Eqn. 7A-7)

or in logarithmic form:

In SA = 3.73 + 0.417 InH + 0.517 InW   (Eqn. 7A-8)
  with a standard error about the regression of 0.00374.
  This model explains more than 99 percent of the total
  variation in surface area among the observations, and
  is identical to two significant figures with the model
  developed by Gehan and George (1970).
          When natural logarithms of the  measured
  surface areas are plotted against natural logarithms of
  the  surface predicted by the equation, the observed
  surface areas  are symmetrically distributed around a
  line of perfect fit, with only a few large percentage
  deviations.  Only  five  subjects  differed  from the
  measured value by 25 percent or more. Because each
  of the five subjects weighed less than 13 pounds, the
  amount of difference was small.  Eighteen estimates
  differed from measurements by 15 to 24 percent. Of
  these, 12 weighed less than 15 pounds each, 1 was
  overweight (5 feet 7 inches, 172 pounds), 1 was very
  thin (4 feet  11 inches,  78 pounds), and 4 were of
  average build.  Since the  same observer  measured
  surface area for these 4 subjects, the possibility of
  some bias in measured values cannot  be discounted
  (Gehan and George 1970).
          Gehan and George (1970) also considered
  separate constants for different age groups:  less than
  5 years old, 5 years old to less than 20 years old, and
  greater than 20 years old. The different values for the
  constants are presented in Table 7A-1.
  The surface areas estimated using the parameter values
  for all ages were compared to surface areas  estimated
  by the values for each age group for subjects at the
  3rd, 50th,  and 97th percentiles of weight and height.
  Nearly all differences in surface area estimates were
  less than 0.01  square meter, and the largest difference
  was 0.03 m2 for an 18-year-old at the 97th percentile.
  The authors concluded that there is no advantage in
  using separate values of a0,  ab and a2 by age interval.
           Haycock et al. (1978) without knowledge of
  the  work by Gehan and George (1970), developed
  values for the parameters a0, ab and a2 for the DuBois
  and DuBois model.  Their interest in making the
  DuBois and DuBois model more accurate resulted
  from their work in pediatrics and the fact that DuBois
  and DuBois (1916) included  only one child  in their
  study  group,  a severely undernourished  girl who
  weighed only  13.8 pounds at age 21 months. Haycock
  et al.  (1978)  used their  own geometric method for
  estimating surface area from 34 body measurements
  for 81 subjects. Their study included newborn infants
  (10 cases), infants (12 cases), children (40 cases), and
Page
7A-3
 Child-Specific Exposure Factors Handbook
	September 2008

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                                                       Child-Specific Exposure Factors Handbook

                                                      	Chapter 7 - Dermal Exposure Factors
adult members of the medical and secretarial staffs of
2 hospitals (19 cases).  The subjects all had grossly
normal body structure, but the sample included subjects
of widely varying physique ranging from thin to obese.
Black, Hispanic, and white children were included in
their sample. The values of the model parameters were
solved for the  relationship  between surface area and
height and weight by multiple regression analysis.  The
least  squares  best fit for this equation yielded  the
following values for the three  coefficients:   a0 =
0.024265, E! = 0.3964, and a2 = 0.5378. The result was
the following equation for estimating surface area:

  SA = 0.024265H°-3964W°-5378     (Eqn. 7A-9)

expressed logarithmically as:
In SA = In 0.024265 + 0.3964 In H
(Eqn. 7A-10)
-0.5378 In W
        The  coefficients  for  this equation  agree
remarkably with those obtained by Gehan and George
(1970) for 401 measurements.
        George et al. (1979) agree that a model more
complex than the model of DuBois and DuBois for
estimating surface  area is unnecessary.   Based on
samples of direct measurements by Boyd (1935) and
Gehan and George  (1970), and samples of geometric
estimates by Haycock et al. (1978), these authors have
obtained parameters for the DuBois and DuBois model
that are different than those originally postulated in
1916. The DuBois and DuBois model can be written
logarithmically as:
InSA = Ina0 + al InH + a2 InW
    (Eqn. 7A-11)
        The values for a0, ab and a2 obtained by the
various authors discussed in this section are presented
in Table 7A-2.
        The agreement between the model parameters
estimated by Gehan and George (1970) and Haycock et
al.  (1978)  is remarkable in view  of  the fact that
Haycock et al. (1978) were  unaware of the previous
work. Haycock et al. (1978) used an entirely different
set of subjects, and used geometric estimates of surface
area rather than  direct measurements.   It has been
determined that the Gehan and George model is the
formula of choice for estimating total surface area of
the body since it is based on the largest number of
direct measurements.
        Sendroy and Cecchini (1954) proposed a
method of creating a nomogram, a diagram relating
height and weight to surface area. However, they do
not give an explicit model for calculating surface area.
The nomogram was developed empirically based on
252 cases, 127 of which were from the 401 direct
measurements reported by Boyd (1935). In the other
125 cases the surface area was estimated using the
linear method of DuBois and DuBois (1916). Because
the Sendroy  and Cecchini method is graphical,  it is
inherently less precise  and less accurate than the
formulas of other authors discussed above.

REFERENCES FOR APPENDIX 7A

Boyd, E.  (1935) The growth of the surface area of
        the  human  body.    Minneapolis,  MN:
        University of Minnesota Press.

Dubois, D.;  Dubois, E.F.  (1916) A formula to
        estimate the approximate surface area if
        height and weight be known.  Arch Intern
        Med 17:863-871.

Gehan, E.; George, G.L.  (1970) Estimation of human
        body surface area from height and weight.
        Cancer Chemother Rep 54(4):225-235.

Geigy  Scientific  Tables   (1981) Nomograms for
        determination of body  surface area from
        height and mass.  Lentner, C.  (ed.). CIBA-
        Geigy Corporation, West Caldwell, NJ.   pp.
        226-227.

Haycock,  G.B.; Schwartz, G.J.; Wisotsky,  D.H.
        (1978) Geometric method for measuring
        body surface area: A height-weight formula
        validated  in infants, children,  and adults. J
        Pediatr 93(l):62-66.

Sendroy, J.; Cecchini, L.P.  (1954) Determination of
        human body surface area from height and
        weight. JApplPhysiol7(l):3-12.
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Chapter 7 - Dermal Exposure Factors	
Table 7A-1 . Estimated Parameter Values for Different Age Intervals
Age
Group
All ages
<5 years old
>5to <20 years old
>20 years old
Number
of persons
401
229
42
30
a0
0.02350
0.02667
0.03050
0.01545
*i
0.42246
0.38217
0.35129
0.54468
a2
0.51456
0.53937
0.54375
0.46336
Table 7A-2.
Author
(year)
DuBois and DuBois (1916)
Boyd (1935)
Gehan and George (1970)
Haycock etal. (1978)
Summary of Surface Area
Number
of persons
9
231
401
81
Parameter Values
a0
0.007184
0.01787
0.02350
0.024265
for the Dubois and Dubois Model
*i
0.725
0.500
0.42246
0.3964

a2
0.425
0.4838
0.51456
0.5378
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 Chapter 8 - Body Weight	
                                    TABLE OF CONTENTS
        BODY WEIGHT STUDIES  	8-1
        8.1     INTRODUCTION	8-1
        8.2     RECOMMENDATIONS	8-1
        8.3     KEY BODY WEIGHT STUDY	8-4
               8.3.1   U.S. EPA analysis of NHANES 1999-2006 data 	8-4
        8.4     RELEVANT BODY WEIGHT STUDIES  	8-4
               8.4.1   National Center for Health Statistics, 1987  	8-4
               8.4.2   Burmaster and Crouch, 1997	8-5
               8.4.3   U.S. EPA, 2000	8-5
               8.4.4   Kuczmarski et al, 2002	8-5
               8.4.5   Ogden et al., 2004	8-6
               8.4.6   Freedman et al., 2006 	8-6
               8.4.7   Martin et al., 2007	8-7
               8.4.8   Portier et al., 2007	8-7
               8.4.9   Kahn and Stralka, 2008	8-8
        8.5     RELEVANT FETAL WEIGHT STUDIES	8-8
               8.5.1   Brenner et al., 1976	8-8
               8.5.2   Doubilet et al.,  1997 	8-8
        8.6     REFERENCES FOR CHAPTER 8	8-9
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                                                     	Chapter 8 - Body Weight
                                          LIST OF TABLES

 Table 8-1.       Recommended Values for Body Weight	8-2
 Table 8-2.       Confidence in Recommendations for Body Weight	8-3
 Table 8-3.       Mean and Percentile Body Weights (kilograms) Derived from NHANES 1999-2006, Males and
                Females Combined  	8-10
 Table 8-4.       Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES
                1999-2006	8-11
 Table 8-5.       Mean and Percentile Body Weights (kilograms) for Females Derived from
                NHANES 1999-2006	8-11
 Table 8-6.       Weight in Kilograms for Males 2 Months-19 Years of Age- Number Examined, Mean, and
                Selected Percentiles, by Age Category: United States, 1976-1980	8-12
 Table 8-7.       Weight in Kilograms for Females 6 Months-19 Years of Age-Number Examined, Mean, and
                Selected Percentiles, by Age Category: United States, 1976-1980	8-13
 Table 8-8.       Statistics for Probability Plot Regression Analyses:
                Females Body Weights 6 Months to 20 Years of Age	8-14
 Table 8-9.       Statistics for Probability Plot Regression Analyses:
                Males Body Weights 6 Months to 20 Years of Age  	8-15
 Table 8-10.     Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From
                NHANES III (1988-94 	8-16
 Table 8-11.     Body Weight Estimates (in kilograms) by Age, U. S. Population Derived From
                NHANES III (1988-94	8-17
 Table 8-12.     Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender
                and Age: Birth to 36 Months	8-18
 Table 8-13.     Mean Body Weight (kilograms) by Age and Gender Across Multiple Surveys  	8-25
 Table 8-14.     Mean Height (centimeters) by Age and Gender Across Multiple Surveys  	8-26
 Table 8-15.     Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys  	8-27
 Table 8-16.     Sample Sizes by Age, Sex, Race, and Examination	8-28
 Table 8-17.     Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex .... 8-29
 Table 8-18.     Prevalence of Overweight and Obesity* Among Children	8-30
 Table 8-19.     Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth
                Weights, by Race and Hispanic Origin of Mother: United States, 2005 	8-31
 Table 8-20.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
                NHANES II Data  	8-32
 Table 8-21.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
                NHANES III Data         	8-33
 Table 8-22.     Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
                NHANES IV Data   	8-34
 Table 8-23.     Estimated Body  Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments . . 8-35
 Table 8-24.     Estimated Percentile Distribution of Body Weight by Fine Age Categories  	8-35
 Table 8-25.     Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence
                Interval  	8-36
 Table 8-26.     Fetal Weight (grams) Percentiles Throughout Pregnancy	8-37
 Table 8-27.     Neonatal Weight by Gestational Age for Males and Females Combined 	8-38
Page
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 Chapter 8 - Body Weight	
                                      LIST OF FIGURES

 Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months 	8-19
 Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months 	8-20
 Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months	8-21
 Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months	8-22
 Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years	8-23
 Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years	8-24
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 Chapter 8 - Body Weight	
 8       BODY WEIGHT STUDIES

 8.1     INTRODUCTION
         The average daily dose (ADD) is a dose that is
 typically normalized to the average body weight of the
 exposed population.  If exposure occurs  only during
 childhood years, the average child body weight during
 the exposure period should be used to estimate  risk
 (U.S. EPA, 1989).
         The purpose of this section is to describe a key
 published study on body weight for children in the
 general U.S. population, as described in Section 1.5 of
 this handbook.  The recommendations for body weight
 are provided in the next section, along with a summary
 of the confidence ratings for these recommendations.
 The recommended values are based on one key study
 identified by U.S. EPA for this factor.  Following the
 recommendations, the key study on body weight is
 summarized. Relevant data on body weight are also
 provided.   Since childhood obesity  is a  growing
 concern and may increase the risk of chronic diseases
 during adulthood, information on body  mass index
 (BMI) and height are also provided.

 8.2     RECOMMENDATIONS
         The recommended values for body weight are
 summarized in  Table 8-1.   Table 8-2 presents the
 confidence ratings for body weight recommendations.
 The recommended values represent mean body weights
 in kilograms for the age groups recommended by U. S.
 EPA  in  Guidance for Monitoring and Assessing
 Childhood Exposures to Environmental Contaminants
 (U.S. EPA, 2005). Use of upper percentile body weight
 values are not routinely recommended for calculating
 ADDs because inclusion of an upper percentile value in
 the denominator of the ADD equation would be a non-
 conservative approach. However, distributions of body
 weight data are provided in section 8.3 of this chapter.
 These distributions  may be  useful if probabilistic
 methods are used to assess exposure. Also, if gender-
 specific data are needed, or if data for finer age bins are
 needed, the reader should refer to the tables in Section
 8.3.
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                                            	Chapter 8 - Body Weight
Table 8-1.
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to <11 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Recommended Values for Body Weight
Mean Multiple _
_ ;•, Source
^ Percentiles
4.8
5.6
7.4
9.2
11,1 r,, , , o ^ U.S. EPA analysis of
I l«< NHANES, 1999-2006
13.8 through 8-5 ^
18.6
31.8
56.8
71.6
Page
8-2
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 Chapter 8 - Body Weight	
Table
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
8-2. Confidence in Recommendations for Body Weight
Rationale
The survey methodology and secondary data analysis
analysis was adequate. NHANES consisted of a large
sample size; sample size varied with age. Direct
measurements were taken during a physical examination.
No significant biases were apparent.
The key study is directly relevant to body weight.
NHANES was a nationally representative sample of the
U.S. population; participants are selected using a complex,
stratified, multi-stage probability cluster sampling design.
The U.S. EPA analysis used the most current NHANES
data.
The U.S. EPA analysis was based on 4 data sets of
NHANES data covering 1999-2006.
NHANES data are available from NCHS; the U.S. EPA
analysis of the NHANES data is available upon request.
The methods used were well-described; enough information
was provided to allow for reproduction of results.
Quality assurance of NHANES data was good; quality
control of secondary data analysis was not well described.
The full distributions were given in the key study.
No significant uncertainties were apparent in the NHANES
data, nor in the secondary analyses of the data.
NHANES received a high level of peer review. The
U.S. EPA analysis was not published in a peer-reviewed
journal.
The number of studies is 1.


Rating
High
High
High
High
Medium
High
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                                                       	Chapter 8 - Body Weight
8.3     KEY BODY WEIGHT STUDY
8.3. 1    U.S. EPA analysis of NHANES 1999-2006
        data
        The U.S. EPA analyzed data from the 1999-
2006  National  Health  and Nutrition Examination
Survey (NHANES) to generate distributions of body
weight for various age ranges of children. NHANES
is  conducted annually  by the  Center for  Disease
Control  (CDC), National Center of Health Statistics
(NCHS).   The survey's target population is  the
civilian, noninstitutionalized U.S. population.  The
NHANES 1999-2006 survey was conducted on a
nationwide probability   sample of  approximately
40,000 persons for all ages, of which approximately
20,000 were children.  The  survey is designed to
obtain nationally representative information on the
health and nutritional status of the population of the
United States through interviews and direct physical
examinations.     A  number  of  anthropometric
measurements, including body weight, were taken for
each participant in the study. Unit non-response to the
household interview was 1 9 percent, and an additional
4  percent did  not  participate  in  the  physical
examinations (including body weight measurements).
        The NHANES 1999-2006  survey includes
over-sampling of low-income persons, adolescents
12-19 years, persons 60+  years  of  age,  African
Americans and Mexican Americans. Sample data were
assigned weights to account both for the disparity in
sample  sizes  for these  groups  and for other
inadequacies in sampling, such as the presence of
non-respondents. Because the U. S. EPA utilized four
NHANES data sets in its analysis (NHANES 1999-
2000, 200 1 -2002, 2003-2004, and 2005-2006) sample
weights  were developed for the combined data set in
accordance with CDC guidance from the NHANES'
website
(http ://www. cdc. gov/nchs/about/maj or/nhanes/nhane
s2005-2006/faqs05_06.htm#question%20 1 2).
        Using the data and the weighting factors from
the four NHANES data sets, U.S. EPA calculated
body weight statistics for the standard age categories.
The mean value for a given group was calculated using
the following formula:
                                     (Eqn.8-1)
 where:
         X  =  sample mean;
         x,.  =  the i* observation;
         w,  =  sample weight assigned to observation
         Percentile  values  were  generated  by first
 calculating the sum of the weights for all observations in
 a given group and multiplying this sum by the percentile
 of interest (e.g., multiplying by 0.25 to determine the 25th
 percentile).  The observations were then ordered from
 least to greatest, and each observation was assigned a
 cumulative weight, equal to its own weight plus all
 weights listed before  the  observation.   The first
 observation listed with a cumulative weight greater than
 the value calculated for the percentile of interest was
 selected.
         Table 8-3 presents the body weight means and
 percentiles, by age category, for male  and female
 children, combined. Tables 8-4 and 8-5 present the body
 weight means and percentiles  for male  and female
 children, respectively.
         The advantage of this study is that it  provides
 body weight distributions for children at ages ranging
 from infancy to young adults.  A limitation of the study
 is that the data in Tables 8-3  to 8-5 may underestimate
 current body weights due to an observed upward trend in
 body weights (Ogden et  al, 2004).   However, the
 NHANES data are nationally representative and remain
 the  principal  source  of body weight data collected
 nationwide from a large number of subjects.

 8.4      RELEVANT BODY WEIGHT STUDIES
 8.4.1    National Center for Health Statistics, 1987 -
         Anthropometric   reference   data  and
         prevalence of overweight, United States,
         1976-80
         This study used anthropometric measurement
 data for body weight for the U.S. population that were
 collected by NCHS as part of the second National Health
 and Nutrition Examination  Survey  (NHANES II).
 NHANES II began in February 1976 and was completed
 in February 1980.  The survey  was  conducted on a
 nationwide probability sample of 27,801 persons aged 6
 months to 74 years from the civilian, noninstitutionalized
 population of the United  States.   A total of 20,322
 individuals  in the  sample  were  interviewed  and
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 Child-Specific Exposure Factors Handbook
 Chapter 8 - Body Weight
examined, resulting in a response rate of 73.1 percent.
The  sample was selected so that certain subgroups
thought to be at high risk of malnutrition (persons with
low incomes, preschool children, and the elderly) were
over sampled. The estimates were weighted to reflect
national population estimates.  The weighting was
accomplished by inflating examination results for each
subject by the reciprocal of selection probabilities,
adjusted to account for those who were not examined,
and-post stratifying by race, age, and sex.
        NHANES  II   collected  standard  body
measurements of sample subjects, including height and
weight, that were made at various times of the day and
in different seasons of the year.  This technique was
used because an individual's weight may vary between
winter and summer and may fluctuate with patterns of
food  and water intake  and other daily  activities
(NCHS, 1987). NCHS  (1987) provided descriptive
statistics  of the body  weight data.   Means  and
percentiles, by age category, are presented in Table 8-
6 for males, and in Table 8-7 for females.
        The advantages of the  study are that it is
nationally representative and provides data for various
age groups of children, beginning at 2 months of age.
The limitation of the study is the age of the data.

8.4.2   Burmaster and Crouch, 1997 - Lognormal
        distributions for body weight as a function
        of age for males and females in the United
        States, 1976-1980
        Burmaster and Crouch (1997) performed data
analysis to fit normal and lognormal distributions to
the body weights of females and males aged 9 months
to 70 years. The data used in this analysis were from
the second survey of the National Center for Health
Statistics, NHANES II, which was based on a national
probability sample of 27,801 persons 6 months to 74
years of age in the U. S. (Burmaster and Crouch 1997).
The NHANES II data had been statistically  adjusted
for non-response and probability of selection,  and
stratified by age, sex, and race to reflect the entire U.S.
population prior to reporting. Burmaster and Crouch
(1997) conducted exploratory and quantitative data
analyses and fit normal and lognormal distributions to
percentiles of body weights of children and teens, as a
function of age.  Cumulative distribution functions
were plotted for female and male body weights on
both linear and logarithmic scales.
        Burmaster and Crouch (1997) used "maximum
likelihood" estimation to fit lognormal distributions to
the data.  Linear and  quadratic  regression lines were
fitted to the data. A number of goodness-of-fit measures
were conducted on the data generated. The investigators
found that lognormal distributions gave strong fits to the
data for each gender across all age groups.  The statistics
for the  lognormal probability plots for female and male
children aged  9 months  to 20 years are  presented in
Tables  8-8 and 8-9, respectively. These data can be used
for further analyses of body weight distribution (i.e.,
application of Monte Carlo analysis).
        The advantage of this study is that NHANES
data were  used  for  the analysis  and  the  data  are
representative nationally. It also provides statistics for
probability plot regression analyses for  females and
males from 6 months  to  20 years old.  However, the
analysis is based on an older set of NHANES data.

8.4.3    U.S. EPA, 2000 - Body weight estimates on
        NHANES III Data
        U. S. EP A's Office of Water has estimated body
weights for children by age and gender using data from
NHANES III, which was  conducted from 1988 to 1994.
NHANES  III collected  body  weight  data  for
approximately 15,000  children between the ages of 2
months and 17 years. Table  8-10  presents the body
weight  estimates in kilograms by age and gender.  Table
8-11 shows the body weight estimates for infants under
the age of 3 months.
        The limitations  of this  analysis  are that data
were not available for  infants under 2 months old, and
that the data are roughly  14 to 20 years old.  With the
upward trends in body  weight from NHANES II (1976-
1980) to NHANES III, which may still be valid, the data
in Tables 8-10 and 8-11 may underestimate current body
weights.  However, the data are national  in scope and
represent the general children's population.

8.4.4    Kuczmarski et  al., 2002 - 2000 CDC growth
        charts for the United  States: methods and
        development
        NCHS published growth charts for infants, birth
to 36 months of age, and  children and adolescents, 2 to
20 years of age (Kuczmarski et al., 2002). Growth charts
were developed with  data from five national health
examination surveys:  National Health  Examination
Survey (NHES) II (1963-65) for ages 6-11 years, NHES
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                                                        	Chapter 8 - Body Weight
III (1966-70) for ages 12-17 years, National Health
and  Nutrition Examination  Survey (NHANES) I
(1971 -74) for ages 1-17 years, NHANES II (1976-80)
beginning at 6 months of age, and NHANES III (1988-
94) beginning at 2 months of age. Data from these
national surveys were pooled because no single survey
had enough observations to develop these charts.  For
the infant charts, a limited number of additional data
points  were  obtained  from other  sources  where
national data were either not available or insufficient.
Birth weights <1,500 grams were excluded when
generating the charts for weights and lengths.  Also,
the length-for-age charts exclude data from NHANES
III  for  ages <3.5  months.   Supplemental birth
certificate data from the U. S. vital statistics were used
in the weight-for-age charts and supplemental birth
certificate data  from Wisconsin and Missouri vital
statistics,  CDC Pediatric  Nutrition  Surveillance
System data were used for ages 0.5, 1.5, 2.5, 3.5, and
4.5 months for the length-for-age charts. The Missouri
and Wisconsin birth certificate data were also used to
supplement  the surveys  for the weight-for-length
charts.  Table 8-12 presents the percentiles of weight
by gender and age. Figures 8-1 and 8-2 present weight
by age percentiles for boys and girls, aged birth to 36
months, respectively.  Figures  8-3 and 8-4 present
weight by  length percentiles  for boys  and girls,
respectively.  Figures 8-5 and 8-6 provide the Body
Mass Index (BMI) for boys  and  girls aged 2 to 20
years old.
        A limitation of this analysis is that trends in
the weight data cannot be assessed because  data from
various years were combined. The advantages of this
analysis  are that it  is  based  on  a  nationally
representative sample of the U.S. population and it
provides body weight on a month-by-month basis up
to 36 months of age,  as well as BMI data for children
through age 20 years.

8.4.5   Ogden et aL, 2004 - Mean body weight,
        height, and body mass index, United States
         1960-2002
        Ogden  et al. (2004) analyzed trends in body
weight measured by the National Health Examination
Surveys II  and  III (NHES II and III),  the National
Health and Nutrition Examination Surveys I, II, and III
(NHANES  I, II, and III), and NHANES 1999-2002.
 The surveys covered the period from  1960 to  2002.
 Table 8-13 presents the measured  body weights for
 various age groups as measured in NHES and NHANES.
 Tables 8-14 and 8-15 present the mean height and BMI
 data for the same population, respectively.  The BMI
 data were calculated as weight in kilograms divided by
 the square of height in meters.  Population means were
 calculated using sample weights to account for variation
 in sampling for certain subsets of the U.S.  population,
 non-response, and non-coverage (Ogden et al., 2004).
 The data indicate that mean body weight has increased
 over the period analyzed.
         There is some uncertainty inherent in such an
 analysis,  however,  because of changes in  sampling
 methods during  the 42 year time span covered by the
 studies.  Because this study is based on an analysis of
 NHANES data, its limitations are the same  as those for
 that  study.   However, it  serves  to  illustrate  the
 importance of the use of timely data when analyzing
 body weight.

 8.4.6    Freedman et al., 2006 - Racial and ethnic
         differences in  secular trends for childhood
         BMI, weight, and height
         Freedman  et  al. (2006)  examined sex and
 race/ethnicity differences in secular trends for childhood
 BMI, overweight, weight, and height in the United States
 using data from  NHANES I (1971 to 1974), NHANES
 II (1976-  1980), NHANES III (1988 to  1994) and
 NHANES 1999-2002. The analyses included children 2
 to 17 years olds. Persons with missing weight or height
 information were excluded from the analyses (Freedman
 et al., 2006). The authors categorized the data across the
 four  examinations  and presented  the  data  for non-
 Hispanic White,  non-Hispanic Black, or  Mexican
 American.  Freedman  et al.  (2006)  excluded other
 categories of race/ethnicity such  as other Hispanics,
 because the sample sizes were small.  Height and weight
 data  were obtained for each survey and BMI was
 calculated as weight in kilograms divided by height in
 meters square.  Sex specific z-scores and percentiles of
 weight-for-age, height-for-age, and BMI-for-age were
 calculated.  Childhood overweight was defined as BMI-
 for-age  >95th percentile and childhood obesity was
 defined as children with a BMI-for-age > 99th percentile.
         In the analyses, sample weights were used to
 account for differential probabilities, non-selection, non
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 Child-Specific Exposure Factors Handbook
 Chapter 8 - Body Weight
response, and non-coverage. The sample sizes used in
the analyses by age, race and survey are presented in
Table 8-16. Mean BMI levels are provided in Table
8-17 and the prevalence of overweight and obesity is
shown in Table 8-18. Table 8-17 shows that in 1971 -
1974  survey  total population, Mexican  American
children had the highest mean BMI level (18.6 kg/m2).
However the greatest increase throughout the survey
occurred among Black children increasing from 17.8
to 20 kg/m2 (Freedman et al, 2006).  Table 8-18
shows that 2 to 5 year old White children had slightly
larger increases in overweight, but among the older
children, the largest increases were among the Black
and Mexican  American children  (Freedman et al.,
2006).  Overall, in most sex-age  groups, Mexican
Americans experienced the greater increase in BMI
and overweight than what was experienced by Black
and White Children (Freedman et al., 2006). Black
children experienced larger secular increases in BMI,
weight, and height than did White children (Freedman
et al., 2006). According to Freedman et al.  (2006)
racial/ethnicity differences were less marked in the 2
to 5 years old children.
        The  advantages of the  study  are that the
sample size is large and the analysis was designed to
represent the  general population  of  the racial  and
ethnic groups studied.  The disadvantage is that some
ethnic population groups were excluded because of
small sample sizes.

8.4.7    Martin et al., 2007 - Births: final data for
        2005
        Martin et al.(2007) provided statistics on the
percentage of live births categorized as having low or
very low birth weights in the U.S.  Low birth weight
was defined as <2,500 grams (<5 pounds 8 ounces)
and very low birth weight was  defined as <1,500
grams (<3 pounds 4 ounces). The data used in the
analysis were from birth certificates registered in all
states and the District of Columbia for births occurring
in  2005.    Data   were  presented  for maternal
demographic characteristics including race ethnicity:
non-Hispanic  White,  non-Hispanic  Black,   and
Hispanic.
        The numbers of live births  within various
weight ranges, and the percentages of live births with
low or very low birth weights are presented in Table 8-
19.  The percentage of live births  with low birth
weights was 8.2, and the percentage of very low birth
weights was 1.5 in 2005. Non-Hispanic Blacks had the
highest percentage of low birth weights (14.0 percent)
and very low birth weights (3.3 percent). Martin et al.
(2007) also provided statistics on the numbers and
percentages of pre-term live births in the U.S.  Of the
4,138,349 live births in the U.S. in 2005, 522,913 were
defined as pre-term (i.e., less than 37 weeks gestation).
A total of 43.3 percent of these pre-term infants had low
birth weights an 11.3 percent had very low birth weights.
The  advantage  of this data set is that it is nationally
representative and provides data for infants.

8.4.8    Portier  et  al.,  2007  -  Body  weight
        distributions for risk assessment
        Portier  et  al.  (2007) provided  age-specific
distributions of body weight based on NHANES II, III,
and IV data.  The number of observations in these
surveys was 20,322, 33,311,  and 9,965, respectively.
Portier et al. (2007) computed the means and standard
deviations of body weight as back transformations of the
weighted means and standard deviations of natural
log-transformed  body   weights.     Body  weight
distributions were computed by gender and various age
brackets (Portier et al., 2007). The estimated mean body
weights are shown in Tables 8-20, 8-21, and 8-22 using
NHANES II, III, and IV data, respectively. The sample
size (N) shown in the tables is the observed number of
individuals and not the expected population size (sum of
the sample weights) in each age category (Portier et al.,
2007). The authors noted that the age groups are defined
as starting at the birth month and include the next eleven
months (i.e., age group 2 includes children 24-35 months
at the time of the  health  assessment).  Table  8-23
provides estimates  for age  groups  that are  often
considered in risk assessments (Portier et al., 2007). The
authors concluded  that the data show changes in the
average body weight over time and that the changes are
not constant for all ages. The reader is referred to Portier
et al. (2007) for equations suggested by the authors to be
used when performing risk assessments where shifts and
changes in body weight distributions need factoring in.
        The advantages  of this  study  are  that it
represents  the  U.S.  general  population,  it provides
distribution data, and can be used for trend analysis. In
addition, the data are provided for both genders and for
single-year age groups. The study results are also based
on a large sample size.
Child-Specific Exposure Factors Handbook
September 2008
                                             Page
                                               8-7

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                                                         Child-Specific Exposure Factors Handbook

                                                        	Chapter 8 - Body Weight
8.4.9    Kahn and Stralka, 2008 - Estimated daily
        average  per capita water ingestion by
        child and adult age categories based on
        USDA's  1994-96  and  1998  Continuing
        Survey of Food Intakes
        As part of an analysis of water ingestion,
Kahn and  Stralka  (2008)  provided body weight
distributions for children.  The analysis was based on
self reported body weights from the 1994  -1996,1998
Continuing Survey of Food Intake Among Individuals
(CSFII).   The  average  body weight across all
individuals was 65 kilograms. According to Kahn and
Stralka (2008),  10 kilograms, which is often used as
the default body weight for babies, is the  95th value of
the distribution of body weight for children in the 3 to
<6  months category.   The  median weight  is  9
kilograms for the 6 to  12 month age category and 11
kilograms for the 1 to 2 year old category (Kahn and
Stralka, 2008).   The body  weight distributions are
presented in Table 8-24 and the intervals around the
mean and 90th and 95th percentiles are  presented in
Table 8-25.
        The  advantages  of the study are its large
sample size and that it is representative of the  U.S.
population for the age groups presented.  A limitation
of the study is that the data are based on self reporting
from the participants.

8.5     RELEVANT FETAL WEIGHT STUDIES
8.5.1    Brenner et al., 1976 - A Standard of Fetal
        Growth for the United States  of America
        Brenner  et   al.  (1976)  determined  fetal
weights for 430 fetuses aborted at 8  to  20 weeks of
gestation and  for 30,772 liveborn infants delivered at
21 to  44 weeks of gestation.  Gestational age for the
aborted fetuses was determined through a  combination
of the physician's estimate of uterine size  and the
patient's  stated last normal  menstrual period.  Data
were not used when these two estimates differed by
more  than 2 weeks. To determine fetal growth, the
fetuses were weighed and measured (crown-to-rump
and crown-to heel lengths). All abortions were legally
performed at Memorial Hospital, University of North
Carolina  at Chapel Hill from 1972 to 1975.  For the
liveborn infants, data were analyzed from single birth
deliveries with the infant living at the onset of labor,
among pregnancies not complicated by pre-eclampsia,
 diabetes or other disorders. Infants were weighed on a
 balance scale immediately after delivery. The liveborn
 infants were delivered at MacDonald House, University
 Hospitals of Cleveland, Ohio from 1962 to  1969.
         Percentiles  for fetal weight were calculated
 from the data at each week of gestation and are shown in
 Table 8-26.   The resulting percentile curves were
 smoothed with two-point weighted means.   Variables
 associated with significant differences in fetal weight in
 the  latter  part of pregnancy  (after 34-38  weeks of
 gestation)  included maternal parity and race, and fetal
 gender.
         The advantage of this study is the large sample
 size.  Limitations  of the study are that the data were
 collected more than 30 years ago in only two U.S. states.
 In addition, a number of variables which may affect fetal
 weight (i.e., maternal smoking, disease, nutrition,  and
 addictions) were not evaluated in this study.

 8.5.2    Doubilet et al.,  1997  -   Improved Birth
         Weight Table for Neonates Developed from
         Gestations Dated by Early Ultrasonography
         Doubilet et al.  (1997) matched a database of
 obstetrical ultrasonograms over a period of 5 years from
 1988 to  1993 to birth records for 3,718 infants (1,857
 males and 1,861  females).   The study   population
 included 1,514 Whites, 770 Blacks, 1,256 Hispanics, and
 178 who  were either unclassified,  or classified as
 "other."   Birth weights were  obtained from hospital
 records and a gestational age was assigned based on the
 earliest first  trimester  sonogram.  The database  was
 screened for possible outliers, defined as infants with
 birth weights that exceeded  5000 grams.  Labor  and
 delivery records and mother-infant medical records were
 retrieved to correct any errors in data entry for infants
 with birth  weights exceeding 5000 grams.  The mean
 gestational age at initial sonogram was 9.5 ± 2.3 weeks.
 Regression analysis techniques  were  used to derive
 weight tables for neonates at each gestational age for 25
 weeks of gestation onward. Weights for each gestational
 age were  found to  conform  to a  natural  logarithm
 distribution. Polynomial equations were derived from the
 regression analysis to  estimate  mean  weight   by
 gestational age  for  males, females, and   males  and
 females combined. Table 8-27 provides the distribution
 of neonatal weights by gestational age from 25 weeks of
 gestation onward.
Page
8-8
Child-Specific Exposure Factors Handbook
                            September 2008

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 Child-Specific Exposure Factors Handbook
 Chapter 8 - Body Weight
8.6
REFERENCES FOR CHAPTER 8
Brenner, W.E.; Edelman, D.A.; Hendricks,  C.H.
        (1976) A standard of fetal growth for the
        United States of America.  Am J Obstet
        Gynecol l:126(5):555-64.
Burmaster, D.E.; Crouch, E.A.C. (1997) Lognormal
        distributions for body weight as a function of
        age for males and females in the United
        States, 1976-1980.  Risk Anal  17(4):499-
        505.
Doubilet, P.M.; Benson, C.B.; Nadel, A.S.; Ringer,
        S.A. (1997) Improved birth weight table for
        neonates developed from gestations dated by
        early ultrasonography.   J  Ultrasound Med
        16:241-249.
Freedman, D.; Kettel,  K.; Serdula, M; Ogden, C.;
        Dietz,  W.    (2006)  Racial  and  ethnic
        differences in secular trends for childhood
        BMI,  weight,  and   height.   Obesity
        14(2):301:307.
Kahn, H.; Stralka, K. (2008) Estimated daily average
        per capita water ingestion by child and adult
        age categories based on USDA's  1994-96
        and 1998 continuing survey of food intakes
        (CSFII). J  Expo  Sci  Environ Epidemiol
        (2008) 1-9.
Kuczmarski, R.J.; Ogden, C.L.; Guo, S.S.; Grummer-
        Strawn, L.;  Flegal, K., et al.  (2000) CDC
        growth charts for the United States: methods
        and development. National Center for Health
        Statistics. Vital Health Stat. 11(246)2002.
LSRO (1995) Third report on nutrition monitoring in
        the United States: Volume 1.  Prepared by:
        Federation  of  American  Societies  for
        Experimental  Biology,  Life  Sciences
        Research Office for the Interagency Board
        for Nutrition Monitoring   and  Related
        Research.     Washington,   D.C.:     U.S.
        Government Printing Office.
Martin, J.;Hamilton,B.; Sutton,P.; Ventura, S.; Fay,
        M.; et al.  (2007) Births: final data for 2005.
        CDC   National  Vital  Statistics  Report,
        Volume 56. No. 6.
National Center for Health Statistics (NCHS). (1987)
        Anthropometric  reference  data   and
        prevalence  of overweight, United States,
        1976-80. Data from the National Health and
        Nutrition Examination  Survey,  Series  11,
        No. 238. Hyattsville,MD: U. S. Department of
        Health and Human  Services, Public Health
        Service, National Center for Health Statistics.
        DHHS Publication No. (PHS) 87-1688.
Ogden, C.L.; Fryar, C.D.; Carroll, M.D.; Flegal, K. M.
        (2004) Mean Body Weight, Height, and Body
        Mass Index, United States 1960-2002. Advance
        Data from Vital and Health Statistics, No. 347,
        October 27, 2004. U.S. Department of Health
        and Human  Services, Centers for Disease
        Control  and Prevention, National Center for
        Health Statistics.
Portier K.; Tolson, J.; Roberts, S. (2007) Body weight
        distributions  for risk assessment.  Risk Anal
        27(1)11-26.
U.S. EPA   (1989)  Risk assessment  guidance  for
        Superfund, Volume I: Human health evaluation
        manual.  Washington,DC: U.S.Environmental
        Protection Agency, Office of Emergency  and
        Remedial Response.  EPA/540/1-89/002.
U.S. EPA (2000) Memorandum entitled: Body weight
        estimates on  NHANES  III  data, revised,
        Contract 68-C-99-242, Work Assignment 0-1
        from Bob  Clickner, Westat Inc.   to  Helen
        Jacobs, U.S. EPA dated March 3, 2000.
U.S. EPA (2005) Guidance on selecting age groups for
        monitoring and assessing childhood  exposures
        to   environmental  contaminants  (2005).
        Washington,  D.C.:  U.S.  Environmental
        Protection Agency, EPA/630/P-03/003F.
Child-Specific Exposure Factors Handbook
September 2008
                                                                                         Page
                                                                                           8-9

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 8 - Body Weight

Table 8-3
Age Group N
Birth to <1 month 158
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Source: U.S.
284
489
927
1176
1144
2318
3593
5297
4851
Mean and Percentile Body Weights (kilograms) Derived from NHANES 1999-2006,
Males and Females Combined
Mean
4.8
5.9
7.4
9.2
11.4
13.8
18.6
31.8
56.8
71.6
EPA Analysis of NHANES
Percentiles
5th
3.6
4.5
5.7
7.1
8.9
10.9
13.5
19.7
34.0
48.2
10th
3.9
4.7
6.1
7.5
9.3
11.5
14.4
21.3
37.2
52.0
15th
4.1
4.9
6.3
7.9
9.7
11.9
14.9
22.3
40.6
54.5
25th
4.2
5.2
6.7
8.3
10.3
12.4
15.8
24.4
45.0
58.4
50th
4.8
5.9
7.3
9.1
11.3
13.6
17.8
29.3
54.2
67.6
75th
5.1
6.6
8.0
10.1
12.4
14.9
20.3
36.8
65.0
80.6
85th
5.5
6.9
8.4
10.5
13.0
15.8
22.0
42.1
73.0
90.8
90th
5.8
7.1
8.7
10.8
13.4
16.3
23.6
45.6
79.3
97.7
95th
6.2
7.3
9.1
11.3
14.0
17.1
26.2
52.5
88.8
108.0
1999-2006 data.
Page
8-10
Child-Specific Exposure Factors Handbook
                       September 2008

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 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
Table 8-4. Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES 1999-2006


Age Group JN


Birth to <1 month 88
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Source: U.S.
153
255
472
632
558
1158
1795
2593
2462

Mean

4.9
6.0
7.6
9.4
11.6
14.1
18.8
31.9
57.6
77.3
EPA Analysis of NHANES
Percentiles

5th
3.6
4.6
5.9
7.3
9.0
11.4
13.5
20.0
33.6
54.5

10th
3.6
5.0
6.4
7.9
9.7
12.0
14.4
21.8
36.3
57.6

15th
4.0
5.1
6.6
8.2
10.0
12.2
14.9
22.9
38.9
60.0

25th
4.4
5.4
6.9
8.5
10.5
12.8
15.9
24.8
44.2
63.9

50th
4.8
6.1
7.5
9.4
11.5
14.0
18.1
29.6
55.5
73.1

75th
5.5
6.8
8.2
10.3
12.6
15.2
20.8
36.4
66.5
86.0

85th
5.8
7.0
8.6
10.6
13.2
15.9
22.6
41.2
75.5
96.8

90th
6.2
7.2
8.8
10.8
13.5
16.4
23.8
45.2
81.2
104.0

95th
6.8
7.3
9.1
11.5
14.3
17.0
26.2
51.4
91.8
113.0
1999-2006 data.
Table 8-5. Mean and Percentile Body Weights (kilograms) for Females


Age Group N


Birth to <1 month 70
1 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Source: U.S.
131
234
455
544
586
1160
1798
2704
2389

Mean

4.6
5.7
7.2
9.0
11.1
13.5
18.3
31.7
55.9
65.9
EPA Analysis of NHANES


5th
3.6
4.3
5.5
7.1
8.7
10.5
13.5
19.3
34.9
46.2
1999-2006 data


10th
4.0
4.6
5.9
7.3
9.1
11.0
14.3
20.9
38.6
48.6



15th
4.1
4.74
6.2
7.6
9.4
11.5
14.7
22.0
41.6
51.1



25th
4.2
5.1
6.4
8.0
10.0
12.1
15.6
23.9
45.7
54.5

Derived from NHANES 1999-2006
Percentiles

50th
4.6
5.5
7.2
8.9
11.1
13.2
17.5
29.0
53.3
61.5



75th
4.9
6.4
7.9
9.8
12.2
14.6
19.7
37.3
62.8
73.3



85th
5.0
6.6
8.2
10.3
12.9
15.5
21.3
43.1
70.7
83.4



90th
5.2
6.9
8.4
10.6
13.2
16.2
23.2
46.7
76.5
89.9



95th
5.9
7.3
9.0
11.2
13.7
17.1
26.2
53.4
86.3
99.7

Child-Specific Exposure Factors Handbook
September 2008
Page
 8-11

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I
If
I
Table 8-6. Weight in Kilograms for Males 2 Months-19 Years of Age- Number Examined, Mean, and Selected Percentiles,
by Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
Number of
Persons
Examined
-
-
103
287
589
613
627
1556
1373
1037
890
Mean ~
(kg)
-
-
6.6
7.7
9.4
11.7
13.7
18.0
30.7
55.2
71.8

5th
-
-
5.3
6.3
7.5
9.4
11.4
13.7
19.5
34.0
54.1

10th 15th
-
-
5.5 5.7
6.6 6.7
7.9 8.1
9.8 10.1
11.8 12.2
14.6 14.9
21.1 22.1
36.5 38.7
56.6 58.3

25th
-
-
5.9
7.0
8.6
10.8
12.6
15.7
24.0
42.8
61.8
Percentiles
50th
-
-
6.8
7.7
9.4
11.7
13.6
17.5
28.5
53.0
68.7

75th
-
-
7.2
8.4
10.2
12.6
14.6
19.7
35.2
63.0
77.9

85th
-
-
7.6
8.9
10.6
13.1
15.2
21.0
40.5
69.4
84.3

90th
-
-
7.8
9.2
10.9
13.7
15.8
22.0
43.5
74.8
89.7

95th
-
-
8.4
9.6
11.4
14.5
16.5
24.0
48.7
84.3
101.0
" Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
No data available for infants less than two months old.
Source: National Center for Health Statistics, 1987.
                                                oo
                                                  !


-------
00
    1
    s
    1=

    I
Table 8-7. Weight in Kilograms for Females 6 Months-19 Years of Age- Number Examined, Mean, and Selected Percentiles,
by Age Category: United States, 1976-1980"
Age Group
Birth to <1 month
1 to <2 months
2 to <3 months
3 to <6 months
6 to <12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Number of
Persons
Examined
-
-
131
269
574
617
597
1658
1321
1144
1001
Mean
(kg)
-
-
6.0
7.1
8.8
11.0
13.4
18.0
30.6
53.2
62.2

5th
-
-
4.7
5.8
7.2
9.1
10.8
13.3
19.0
34.1
46.7
" Includes clothing weight, estimated as ranging from 0
No data available for infants less than two months old

10th
-
-
5.1
5.9
7.5
9.4
11.2
14.0
20.5
37.2
48.2
09 to 0.28 kilogram

15th
-
-
5.2
6.1
7.7
9.6
11.6
14.5
21.3
40.4
49.7


25th
-
-
5.6
6.4
8.0
9.9
12.1
15.4
23.4
45.2
52.2

Percentiles
50th
-
-
6.0
7.1
8.7
10.9
13.2
17.2
28.9
51.6
58.9


75th
-
-
6.5
7.7
9.4
11.9
14.6
19.7
35.0
60.0
68.3


85th
-
-
7.1
7.9
10.1
12.6
15.4
21.1
39.6
67.2
74.7


90th
-
-
7.3
8.4
10.4
12.9
15.6
22.6
44.3
70.6
80.8


95th
-
-
7.8
8.7
10.8
13.4
16.3
25.1
50.2
78.2
92.6

Source: National Center for Health Statistics, 1987.
   Ore
                                                                                                                                                                              Q
                                                                                                                                                                              I
                                                                                                                                                                              oo

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 8 - Body Weight
Table 8-8. Statistics for Probability Plot Regression Analyses:
Females Body Weights 6 Months to 20 Years of Age
Age Midpoint (years)
Lognormal Probability Plots
Linear Curve

Hi'
0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
a U2, a2 - correspond to the mean
Source: Burmaster and Crouch, 1997.
2.16
2.38
2.56
2.69
2.83
2.98
3.10
3.19
3.31
3.46
3.57
3.71
3.82
3.92
3.99
4.00
4.05
4.08
4.07
4.10
0.145
0.129
0.112
0.136
0.134
0.164
0.174
0.174
0.156
0.214
0.199
0.226
0.213
0.215
0.187
0.156
0.167
0.165
0.147
0.149
and standard deviation, respectively, of the lognormal distribution of body weight (kg).


Page
8-14
Child-Specific Exposure Factors Handbook
                       September 2008

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 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
Table 8-9. Statistics for Probability Plot Regression Analyses:
Males Body Weights 6 Months to 20 Years of Age
Age Midpoint (years)

0.75
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5
15.5
16.5
17.5
18.5
19.5
* u2, a2 - correspond to the mean and
Source: Burmaster and Crouch, 1997.
Lognormal Probability Plots
Linear Curve
Hz"
2.23
2.46
2.60
2.75
2.87
2.98
3.13
3.21
3.33
3.43
3.59
3.69
3.78
3.88
4.02
4.09
4.20
4.19
4.25
4.26
standard deviation, respectively, of the lognormal

CT2°
0.132
0.119
0.120
0.114
0.133
0.138
0.145
0.151
0.181
0.165
0.195
0.252
0.224
0.215
0.181
0.159
0.168
0.167
0.159
0.154
distribution of body weight (kg).

Child-Specific Exposure Factors Handbook                                        Page
September 2008                                                                8-15

-------
                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 8 - Body Weight
Table 8-10. Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From
NHANES III (1988-94)
Age Group
2 to 6 months
7 to 12 months
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
1 1 years
12 years
13 years
14 years
15 years
16 years
17 years
1 and older
1 to 3 years
1 to 14 years
1 5 to 44 years
Source: U.S.
Sample Size
1,020
1,072
1,258
1,513
1,309
1,284
1,234
750
736
711
770
751
754
431
428
415
378
427
410
31,311
4,080
12,344
10,393
EPA, 2000.
Population
1,732,702
1,925,573
3,935,114
4,459,167
4,317,234
4,008,079
4,298,097
3,942,457
4,064,397
3,863,515
4,385,199
3,991,345
4,270,211
3,497,661
3,567,181
4,054,117
3,269,777
3,652,041
3,719,690
251,097,002
12,711,515
56,653,796
118,430,653

Male and
Median
7.4
9.4
11.3
13.2
15.3
17.2
19.6
21.3
25.0
27.4
31.8
35.2
40.6
47.2
53.0
56.9
59.6
63.2
65.1
66.5
13.2
24.9
70.8

Female
Mean
7.4
9.4
11.4
12.9
15.1
17.1
19.4
21.7
25.5
28.1
32.7
35.6
41.5
46.9
55.1
61.1
62.8
65.8
67.5
64.5
13.1
29.9
73.5

Male
Median
7.6
9.7
11.7
13.5
15.5
17.2
19.7
21.5
25.4
27.2
32.0
35.9
38.8
48.1
52.6
61.3
62.6
66.6
70.0
73.9
13.4
25.1
77.5


Mean
7.7
9.7
11.7
13.1
15.2
17.0
19.3
22.1
25.5
28.4
32.3
36.0
40.0
49.1
54.5
64.5
66.9
69.4
72.4
89.0
13.4
30.0
80.2

Female
Median
7.0
9.1
10.9
13.0
15.1
17.3
19.6
20.9
24.1
27.9
31.1
34.3
43.4
45.7
53.7
53.7
57.1
56.3
60.7
80.8
13.0
24.7
63.2


Mean
7.0
9.1
11.0
12.5
14.9
17.2
19.4
21.3
25.6
27.9
33.0
35.2
42.8
48.6
55.9
57.9
59.2
61.6
62.2
80.3
12.9
29.7
67.3

Page
8-16
Child-Specific Exposure Factors Handbook
                       September 2008

-------
 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
Table 8-11. Body Weight Estimates (in kilograms) by Age, U.S. Population Derived From
NHANES III (1988-94)
Age Group Sample Size Population
2 Months 243 408,837
3 Months 190 332,823
3 Months and Younger 433 741,660
CI = Confidence Interval.
Source: U.S. EPA, 2000.
Male and Female
Median Mean
6.3 6.3
7.0 6.9
6.6 6.6



95% CI
6.1-6.4
6.7-7.1
6.4-6.7


Child-Specific Exposure Factors Handbook                                        Page
September 2008                                                               8-17

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 8 - Body Weight
Table 8-12. Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender and Age: Birth to 36 Months

Age Group
Perc entile

01^
10th
25th
50th
75th
90th
95th
Rovs
Birth
0 < 1 months
1< 2 months
2 < 3 months
3 < 4 months
4 < 5 months
5 < 6 months
6 < 7 months
7 < 8 months
8 < 9 months
9 < 10 months
10 < 11 months
11 < 12 months
12 < 15 months
15 < 18 months
18<21 months
21 < 24 months
24 < 30 months
30 < 36 months

Birth
0 < 1 months
1< 2 months
2 < 3 months
3 < 4 months
4 < 5 months
5 < 6 months
6 < 7 months
7 < 8 months
8 < 9 months
9 < 10 months
10 < 11 months
11 < 12 months
12 < 15 months
15 < 18 months
18<21 months
21 < 24 months
24 < 30 months
30 < 36 months
3.4
-
-
6.5
7.0
7.2
7.9
8.4
8.6
9.3
9.3
9.5
10.0
10.6
11.4
12.1
12.4
13.1
14.0

3.3
-
-
5.4
6.3
6.7
7.3
7.7
8.0
8.3
8.9
9.0
9.3
9.8
10.4
11.1
11.8
12.5
13.6
0.6
-
-
0.8
0.9
0.8
0.9
1.1
1.1
1.1
0.9
1.1
1.0
1.2
1.9
1.5
1.3
1.7
1.5

0.5
-
-
0.5
0.7
0.9
0.9
0.8
1.4
0.9
0.9
1.1
1.0
1.1
1.1
1.4
1.3
1.5
1.7
2.7
-
-
5.6
5.9
6.3
6.7
7.3
7.1
7.9
8.2
8.3
8.7
9.2
9.9
10.4
10.9
11.3
12.0

2.6
-
-
4.8
5.6
5.8
6.3
6.6
6.7
7.3
7.8
7.8
7.9
8.5
9.1
9.6
10.1
10.8
11.8
3.1
-
-
5.8
6.5
6.7
7.5
7.6
7.8
8.6
8.6
8.7
9.5
9.8
10.5
11.0
11.6
12.1
13.0
Girls
3.0
-
-
5.0
5.8
6.1
6.7
7.1
7.4
7.8
8.1
8.4
8.6
9.1
9.7
10.2
10.9
11.5
12.5
3.4
-
-
6.7
7.0
7.2
7.8
8.4
8.6
9.2
9.3
9.3
10.0
10.6
11.3
11.9
12.4
12.9
13.8

3.3
-
-
5.6
6.3
6.6
7.1
7.6
7.8
8.3
8.7
9.0
9.2
9.8
10.3
11.0
11.8
12.4
13.4
3.8
-
-
6.9
7.5
7.7
8.6
9.0
9.5
10.1
10.0
10.1
10.6
11.3
12.0
12.7
13.1
14.1
14.7

3.6
-
-
5.9
6.8
7.4
7.7
8.1
8.6
8.9
9.4
9.5
10.1
10.4
11.2
11.9
12.8
13.3
14.52
4.1
-
-
7.4
8.2
8.0
9.4
10.2
10.1
10.5
10.8
11.3
11.1
12.1
12.8
13.9
14.4
15.1
16.0

3.9
-
-
6.0
7.4
8.0
8.5
8.9
9.4
9.4
10.1
10.4
10.6
11.3
11.8
12.8
13.5
14.5
15.7
4.3
-
-
7.5
8.5
8.4
9.6
10.7
10.4
11.0
10.9
11.5
11.6
12.4
13.5
15.5
14.7
15.9
16.6

4.1
-
-
-
7.8
8.3
8.8
9.0
9.8
9.8
10.5
10.9
10.9
11.6
12.0
13.5
13.9
15.1
16.4
No data available.
Source: Kuczmarski et
al. 2002.







Page
8-18
Child-Specific Exposure Factors Handbook
                       September 2008

-------
 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
                             CDC Growth Charts: United States
               kg
               kg
                        Weight-for-age percentiles:
                          Boys, birth to 36 months  •
                          7-ZJ-
                                                                      Ib

                                                                      •40-
                               9   12   15   18   21   24    27   30   33
                                        Age (months)
     Figure 8-1.      Weight by Age Percentiles for Boys Aged Birth to 36 Months

     Source:        Kuczmarski et al, 2002.
                                                                      -4 —
                                                                       Ib
Child-Specific Exposure Factors Handbook
September 2008
Page
 8-19

-------
                                                 Child-Specific Exposure Factors Handbook

                                                	Chapter 8 - Body Weight
                               CDC Growth Charts: United States
kg
18 —
17 —

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   Source:        Kuczmarski et al, 2002.
Page
8-20
Child-Specific Exposure Factors Handbook
                         September 2008

-------
 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
                            CDC Growth Charts: United States
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Kuczmarskietal.,2002.
Child-Specific Exposure Factors Handbook
September 2008
                                                                  Page
                                                                   8-21

-------
                                              Child-Specific Exposure Factors Handbook

                                             	Chapter 8 - Body Weight
                       CDC Growth Charts; United States
        22-

        21
Weight-for-length pereentiles:
   Girls, birth to 36 months
          cm 45   50   55   60   65   70   75   BO   85   90    95  100
                                   Length

    Figure 8-4.      Weight by Length Percentiles for Girls Aged Birth to 36 Months

    Source:        Kuczmarski et al, 2002.
                                             -50-


                                             -48-
Page
8-22
                        Child-Specific Exposure Factors Handbook
                                               September 2008

-------
 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
                            CDC Growth Charts: United States











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    Source:         Kuczmarski et al, 2002.
Child-Specific Exposure Factors Handbook
September 2008
Page
 8-23

-------
                                                 Child-Specific Exposure Factors Handbook

                                                	Chapter 8 - Body Weight
                          CDC Growth Charts: United States


















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   Figure 8-6.      Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years

   Source:        Kuczmarski et al, 2002.
Page
8-24
Child-Specific Exposure Factors Handbook
                         September 2008

-------
Table 8-13. Mean Body Weight (kilograms) by A
Gender
and
Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

N
SE
Source:
NHES II, 1 963-65 NHES III, 1 966-70

N Mean SE N Mean SE

_


_
575 22.0 0.1 -
632 24.7 0.2 -
618 27.8 0.2 -
603 31.2 0.4 -
576 33.7 0.3 -
595 38.2 0.3 -
643 42.9 0.4
626 50.0 0.5
618 56.7 0.6
613 61.6 0.4
556 64.8 0.6
458 68.1 0.4
_


_

_

536 21.5 0.2 -
609 24.2 0.2 -
613 27.5 0.2 -
581 31.4 0.4 -
584 35.2 0.4 -
525 39.8 0.4 -
547 46.6 0.4
582 50.5 0.5
586 54.2 0.4
503 56.5 0.5
536 58.1 0.7
442 57.6 0.6
_

Data not available.
= Number of individuals.
= Standard error.
Ogdenetal, 2004.
NHANES I, 1971-74

N

298
308
304
273
179
164
152
169
184
178
200
174
174
171
169
176
124
136

272
292
281
314
176
169
152
171
197
166
177
198
184
167
171
150
141
130





Mean

13.6
15.6
17.7
20.2
22.0
24.9
26.4
31.6
34.2
38.8
44.0
49.9
56.3
60.3
66.9
68.6
74.3
72.6

13.0
15.0
16.8
19.7
21.6
24.3
27.5
32.0
33.8
41.2
46.7
51.8
54.6
56.6
56.8
59.5
58.2
59.5





SE

0.2
0.1
0.1
0.2
0.3
0.4
0.3
0.8
0.6
0.8
0.8
1.0
0.9
1.2
1.3
1.1
1.3
1.3

0.1
0.2
0.2
0.3
0.3
0.4
0.5
0.6
0.6
0.8
1.0
1.0
1.0
0.9
1.1
1.6
1.1
1.4




ge and Gender Across Multiple Surveys
NHANES II, 1976-80

N

370
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150

330
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158





Mean

13.4
15.5
17.6
19.7
22.8
24.9
28.0
30.7
36.2
39.7
44.1
49.5
56.4
61.2
66.5
66.7
71.1
71.8

12.8
14.8
16.8
19.4
21.9
24.6
27.5
31.7
35.7
41.4
46.1
50.9
54.3
55.0
57.7
59.6
59.0
59.8





SE

0.1
0.1
0.1
0.1
0.4
0.4
0.6
0.6
0.7
0.9
1.0
1.2
0.9
1.0
1.2
0.8
1.2
0.8

0.1
0.1
0.2
0.3
0.4
0.5
0.4
0.7
0.6
0.9
0.9
1.2
1.0
0.8
0.9
1.0
1.0
1.0




NHANES III, 1988-94

N

644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168

624
587
537
554
272
274
248
280
258
275
236
220
218
191
208
201
175
177





Mean

13.6
15.8
17.6
20.1
23.2
26.3
30.2
34.4
37.3
42.5
49.1
54.0
64.1
66.9
68.7
72.9
71.3
73.0

13.2
15.4
17.9
20.2
22.6
26.4
29.9
34.4
37.9
44.1
49.0
55.8
58.5
58.1
61.3
62.4
61.2
63.2





SE

0.1
0.2
0.2
0.2
0.6
0.4
0.8
1.0
0.9
0.9
1.1
1.0
3.6
1.9
1.6
1.3
1.7
2.2

0.1
0.1
0.3
0.2
0.6
0.8
0.6
1.2
.2
.1
.2
.6
.4
.1
.4
.2
.9
.9




NHANES 1999-2002

N

262
216
179
147
182
185
214
174
187
182
299
298
266
283
306
313
284
270

248
178
191
186
171
196
184
183
164
194
316
321
324
266
273
256
243
225





Mean

13.7
15.9
18.5
21.3
23.5
27.2
32.7
36.0
38.6
43.7
50.4
53.9
63.9
68.3
74.4
75.6
75.6
78.2

13.3
15.2
17.9
20.6
22.4
25.9
31.9
35.4
40.0
47.9
52.0
57.7
59.9
61.1
63.0
61.7
65.2
67.9





SE

0.1
0.2
0.2
0.5
0.4
0.4
1.0
0.7
0.8
.1
.3
.9
.6
.1
.4
.4
.1
.3

0.1
0.2
0.3
0.6
0.5
0.5
1.2
0.7
.0
.3
.1
.4
.0
^7
2
.2
.5
.2




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Table 8-14. Mean Height (centimeters) by Age and Gender Across Multiple Surveys
Gender
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

N
SE
Source:
NHES II, 1963-65 NHES III, 1966-70
N Mean SE N Mean SE


_

575 118.9 0.2 -
632 124.5 0.3 -
618 130.0 0.3 -
603 135.5 0.4 -
576 140.2 0.3 -
595 145.5 0.3 -
643 152.3 0.4
626 159.8 0.4
618 166.7 0.5
613 171.4 0.3
556 174.3 0.4
458 175.6 0.4
_


_

_

536 117.8 0. - - -
609 123.5 0. - - -
613 129.4 0. - - -
581 135.5 0. - - -
584 140.9 0. - - -
525 147.3 0.3 -
547 46.6 0.3
582 50.5 0.3
586 54.2 0.3
503 56.5 0.5
536 58.1 0.3
442 57.6 0.3
_

Data not available.
= Number of individuals.
= Standard error.
Ogden et al., 2004.
NHANESI, 1971-74
N
298
308
304
273
179
164
152
169
184
178
200
174
174
171
169
176
124
136

272
292
281
314
176
169
152
171
197
166
177
198
184
167
171
150
141
130




Mean
91.1
98.5
106.0
112.8
118.1
125.0
129.0
135.1
140.0
146.3
152.8
159.3
166.7
170.8
175.0
176.9
176.6
176.5

90.1
97.7
104.2
112.2
118.2
124.6
129.2
135.9
140.1
148.2
154.6
158.9
160.8
163.6
161.7
162.1
164.7
163.1




SE
0.4
0.3
0.3
0.3
0.6
0.5
0.5
0.6
0.5
0.7
0.7
0.8
0.6
0.9
0.8
0.5
0.7
0.9

0.3
0.3
0.4
0.4
0.5
0.7
0.6
0.5
0.8
0.8
0.6
0.5
0.6
0.6
0.5
0.9
0.5
0.5




NHANESII, 1976-80
N
350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150

314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158




Mean
91.1
98.7
105.5
112.3
119.1
124.5
129.6
135.0
141.3
145.5
152.5
158.3
166.8
171.2
173.4
174.8
177.3
176.1

89.4
97.1
104.2
111.2
117.9
123.4
129.5
134.1
141.7
147.4
143.8
158.7
160.7
163.3
162.8
163.5
162.8
163.2




SE
0.2
0.3
0.4
0.3
0.5
0.5
0.7
0.6
0.6
0.6
0.7
0.8
0.6
0.7
0.5
0.5
0.6
0.5

0.3
0.2
0.4
0.4
0.6
0.7
0.5
0.5
0.6
0.7
0.6
0.5
0.7
0.5
0.5
0.6
0.5
0.4




NHANES III, 1988-94
N
589
513
551
497
283
270
269
280
297
285
207
190
191
188
197
196
176
169

564
590
535
557
274
275
247
282
262
275
239
225
224
195
214
201
175
178




Mean
90.9
98.8
105.2
112.3
118.9
125.9
131.3
137.7
142.0
147.4
155.5
161.6
169.0
172.8
175.0
176.5
177.3
175.5

89.7
98.2
105.1
112.2
117.9
124.3
131.1
136.6
142.7
150.2
155.5
159.9
161.2
162.8
163.0
163.6
163.2
163.4




SE
0.2
0.3
0.4
0.3
0.7
0.6
0.6
0.7
1.1
0.7
1.1
0.8
0.9
1.0
0.9
0.9
1.0
0.6

0.2
0.2
0.3
0.5
0.6
0.7
0.6
0.7
0.6
0.7
0.7
0.9
0.7
0.6
0.7
0.6
0.9
0.7




NHANES 1999-2002
N
254
222
183
156
188
187
217
177
188
187
301
298
267
287
310
317
289
275

233
187
195
190
172
200
184
189
164
194
318
324
326
271
275
258
249
231




Mean
91.2
98.6
106.5
113.0
119.2
126.2
1325.
138.1
141.4
148.7
154.8
160.1
168.5
173.8
175.3
175.3
176.4
176.7

90.1
97.6
105.9
112.4
117.1
124.4
130.9
136.9
143.3
151.4
156.0
159.1
161.8
162.0
161.9
163.2
163.0
163.1




SE
0.3
0.3
0.4
0.5
0.5
0.6
0.7
0.4
0.6
0.9
0.7
0.8
0.9
0.6
0.6
0.6
0.7
0.6

0.4
0.5
0.5
0.7
0.7
0.5
0.6
0.7
0.9
0.7
0.7
0.6
0.6
0.6
0.5
0.6
0.5
0.7




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Table 8-15. Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys
Gender
and Age
(years)
Male
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Female
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

N
SE
Source:
NHES II, 1963-65 NHES III, 1966-70 NHANES I, 1971-74
N Mean SE N

_

_

575 15.6 0.
632 15.9 0.
618 16.3 0.
603 16.9 0.2
576 17.1 0.
595 17.9 0.
643
626
618
613
556
458
_


_

_
_
536 115.4 0.1
609 15.8 0.1
613 16.4 0.1
581 17.0 0.1
584 17.6 0.2
525 18.2 0.2
547
582
586
503
536
442
_
-
Data not available.
= Number of individuals.
= Standard error.
Ogden et al., 2004.
Mean SE N

298
308
304
273
179
164
152
169
184
178
18.4 0.1 200
19.4 0.1 174
20.2 0.2 174
20.9 0.1 171
21.3 0.1 169
22.1 0.1 176
124
136

272
292
281
314
176
169
152
171
197
166
19.2 0.1 177
19.9 0.1 198
20.8 0.1 184
21.4 0.2 167
21.9 0.2 171
21.7 0.2 150
141
130




Mean

16.3
16.0
15.7
15.6
15.7
15.8
15.8
17.1
17.3
18.0
18.7
19.6
20.2
20.5
21.8
21.9
23.7
23.3

15.9
15.7
15.5
15.5
15.4
15.6
16.4
17.2
17.1
18.6
19.5
20.4
21.1
21.1
21.7
22.6
21.5
22.5




SE

0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.2
0.3
0.2
0.3
0.3
0.3
0.3
0.3
0.3
0.5

0.
0.
0.
0.
0.
0.2
0.2
0.2
0.2
0.3
0.4
0.3
0.3
0.3
0.3
0.5
0.3
0.6




NHANES II, 1976-80
N

350
421
405
393
146
150
145
141
165
153
147
165
188
180
180
183
156
150

314
367
388
369
150
154
125
154
128
143
146
155
181
144
167
134
156
158




Mean

16.2
15.9
15.8
15.6
16.0
16.0
16.5
16.8
18.0
18.6
18.8
19.5
20.2
20.8
22.0
21.8
22.6
23.1

16.1
15.6
15.5
15.6
15.6
16.1
16.3
17.5
17.7
18.9
19.3
20.1
21.0
20.6
21.8
22.3
22.3
22.4




SE

0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.3
0.3
0.3
0.4
0.2
0.3
0.3
0.2
0.4
0.3

0.1
0.1
0.1
0.1
0.2
0.2
0.2
0.3
0.3
0.3
0.3
0.4
0.3
0.3
0.3
0.4
0.4
0.3




NHANES III, 1988-94
N

588
512
547
495
282
269
266
279
297
280
203
187
188
187
194
196
176
168

562
582
533
554
272
274
247
280
258
275
236
220
218
191
208
201
175
177




Mean

16.5
16.1
15.9
15.9
16.3
16.5
17.3
18.0
18.4
19.4
20.1
20.5
22.3
22.3
22.3
23.4
22.6
23.7

16.5
15.9
16.0
15.9
16.1
16.9
17.3
18.2
18.4
19.4
20.2
21.8
22.4
21.9
23.0
23.3
22.9
23.7




SE

0.1
0.2
0.1
0.1
0.3
0.2
0.4
0.7
0.3
0.3
0.3
0.3
1.1
0.5
0.5
0.4
0.5
0.6

0.1
0.1
0.2
0.1
0.3
0.3
0.3
0.5
0.4
0.4
0.5
0.6
0.5
0.4
0.5
0.5
0.6
0.8




NHANES 1999-2002
N

225
209
178
147
182
185
214
174
187
182
299
298
266
283
306
313
284
269

214
173
190
186
170
196
184
183
163
194
315
321
324
266
273
255
243
225




Mean

16.6
16.2
16.3
16.5
16.4
17.0
18.4
18.7
19.1
19.6
20.7
20.7
22.3
22.5
24.1
24.5
24.2
24.9

16.4
16.0
15.9
16.1
16.2
16.6
18.3
18.7
19.3
20.7
21.2
22.6
22.9
23.2
24.0
23.1
24.4
25.5




SE

0.1
0.1
0.2
0.3
0.2
0.2
0.4
0.3
0.3
0.4
0.4
0.5
0.4
0.3
0.4
0.4
0.3
0.4

0.1
0.1
0.2
0.3
0.2
0.2
0.5
0.3
0.3
0.4
0.4
0.4
0.4
0.5
0.4
0.4
0.5
0.4




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Table 8-16. Sample

Age Group Sex Race"
Overall
2 to 5 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
6 to 11 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
12 to 17 years Boys White
Black
Mexican American
Girls White
Black
Mexican American
1 Race was receded in the first two examinations (using
surveys.
b Mean ages are shown in parentheses.
Source: Freeman et al., 2006.
Sizes by Age, Sex,

1(1971-1974)
6431 (10.3)b
829 (3.9)
286 (3.9)
51 (3.8)
772 (4.0)
297 (4.0)
56(4.1)
711(9.1)
249 (9.0)
51 (9.0)
722(9.1)
268 (9.0)
45 (8.9)
764(14.9)
252(14.9)
42(15.0)
749(15.0)
251(14.8)
36(14.9)
Race, and Examination
NHANES
11(1976-1980)
6395(10.6)
1082(4.1)
273(4.1)
105 (4.2)
1028 (4.0)
234 (4.0)
102 (4.2)
667 (9.0)
137(9.0)
60 (9.2)
631(9.1)
155(9.0)
40 (9.3)
786(15.1)
155(15.1)
49(15.0)
695(15.1)
159(15.0)
37(15.2)
data concerning ancestry/national origin)






Examination
III (1988-1994)
9610 (9.9)
605 (4.0)
693 (3.9)
732 (4.0)
639 (4.0)
684 (3.9)
800 (3.9)
446 (8.9)
584 (9.0)
565 (9.0)
428(9.1)
538(9.0)
581 (8.9)
282(14.9)
412(15.0)
406(15.0)
344(15.0)
450(14.9)
421 (14.8)
to create comparable cate^




1999-2002
6710(10.1)
226 (3.9)
234 (4.0)
231 (3.9)
235(4.1)
222 (4.0)
238(4.1
298 (8.9)
371 (9.0)
384 (9.0)
293 (8.9)
363(9.1)
361 (9.0)
449(14.9)
543 (14.9)
648(15.0)
456(14.9)
528(14.8)
631 (14.9)
Dories in all



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Table 8-17. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity
Examination Year"

Overall


Sex
Boys


Girls


Age (years)
2 to 5


6 to 11


12 to 17


Race
White
Black
Mexican- American

White
Black
Mexican- American
White
Black
Mexican- American

White
Black
Mexican- American
White
Black
Mexican- American
White
Black
Mexican- American
1971-1974 1976-1980 1988-1994 1999-2002
18.0b
17.8
18.6

17.9
17.7
18.6
18.0
17.9
18.5

15.8
15.8
16.5
16.7
16.5
16.9
20.7
20.4
21.6
18.0
18.2
18.8

18.0
17.8
18.9
18.0
18.6
18.6

15.7
15.7
16.2
16.9
17.1
17.7
20.6
20.9
21.5
18.8
19.1
19.5

18.8
18.8
19.4
18.7
19.5
19.6

16.0
15.9
16.5
17.6
17.9
18.5
21.8
22.4
22.6
19.0
20.0
20.1

19.0
19.6
20.3
19.0
20.4
19.9

16.2
16.2
16.5
17.9
18.7
18.8
22.0
23.7
24.0
and Sex

Increase in Mean z-score
From 1971-1974to 1999-2002
BMI
+0.33
+0.61
+0.32

+0.37
+0.53
+0.38
+0.30
+0.71
+0.25

+0.21
+0.34
-0.02
+0.42
+0.67
+0.50
+0.32
+0.72
+0.37
Weight
+0.36
+0.63
+0.52

+0.42
+0.58
+0.67
+0.32
+0.69
+0.35

+0.22
+0.32
+0.29
+0.47
+0.69
+0.65
+0.35
+9,77
+0.55
a Secular trends for BMI, BMI-for-age, weight-for-age, and height-for-age were each statistically significant at the 0.00 1
BMI, BMI-for-age, and weight also differed (p <0.001) by race.
b Mean BMI levels have been adjusted for differences in age and sex across exams.
Height
+0.20
+0.31
+0.39

+0.25
+0.32
+0.57
+0.16
+0.30
+0.21

+0.13
+0.18
+0.43
+0.30
+0.36
+0.41
+0.15
+0.33
+0.34
level. Trends in
Source: Freedman et al., 2006.
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Table 8-18. Prevalence of Overweight and Obesity* Among Children
Examination year
Race
Overall White
Black
Mexican- American
Sex
Boys White
Black
Mexican- American
Girls White
Black
Mexican- American
Age (years)
2 to 5 White
Black
Mexican- American
6 to 11 White
Black
Mexican- American
12 to 17 White
Black
Mexican- American
1971-1974
5% (l)b
6% (1)
8% (1)

5% (1)
6% (2)
8% (1)
5% (1)
6% (1)
8% (2)

4% (1)
7% (3)
10% (5)
4% (0)
4% (0)
6% (0)
6% (1)
8% (1)
9% (0)
1976-1980
5% (1)
7% (2)
10% (1)

5% (1)
5% (1)
12% (1)
5% (1)
9% (2)
7% (0)

3% (1)
4% (0)
11% (3)
6% (1)
9% (3)
11% (0)
4% (0)
8% (1)
8% (1)
Increase in Prevalence From 1971-
1974to 1999-2002
1988-1994 1999-2002 Overweight
9% (2)
12% (3)
14% (4)

10% (2)
11% (3)
15% (4)
9% (2)
14% (3)
14% (3)

5% (1)
8% (3)
12% (5)
11% (3)
15% (3)
17% (4)
11% (2)
13% (3)
14% (2)
* Overweight is defined as a BMI > 95th percentile or > 30 kg/m2; obesity is defined as a BMI
b Values are percentage of overweight children (percentage of obese children).
Source: Freedman et al., 2006.



12% (3)
18% (5)
21% (5)

13% (4)
16% (5)
24% (4)
12% (2)
21% (6)
17% (4)

9% (3)
9% (4)
13% (5)
13% (4)
20% (5)
22% (5)
13% (2)
22% (6)
25% (5)
> 99th percentile or

+8
+12
+12

+8
+10
+16
+7
+14
+9

+5
+2
+3
+10
+15
+16
+7
+14
+15
> 40 kg/m2.

Obesity
+2
+4
+4

+3
+3
+6
+1
+5
+2

+2
+1
0
+3
+4
+5
+1
+5
+5


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 Chapter 8 - Body Weight	
Table 8-19. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth Weights,
by Race and Hispanic Origin of Mother: United States, 2005

Total Births
Weight (grams)
<500
500-999
1,000-1,499
1,500-1,999
2,000-2,499
2,500-2,999
3,000-3,499
3,500-3,999
4,000-4499
4,500-4999
>5,000
Not stated
All Races'
4,138,349
Non-Hispanic
Whiteb
2,279,768
Non-Hispanic
Blackb
583,759
Hispanic0
985,505
Number of Live Births
6,599
23,864
31,325
66,453
210,324
748,042
1,596,944
1,114,887
289,098
42,119
4,715
3,979
2,497
10,015
14,967
33,687
104,935
364,726
857,136
672,270
167,269
27,541
2,840
1,885
2,477
8,014
8,573
15,764
46,846
144,803
221,819
108,698
22,149
3,203
405
1,008
1,212
4,586
5,988
12,710
43,300
176,438
399,295
266,338
64,704
9,167
1,174
593
Percent of Total
Low Birth Weight11
Very Low Birth Weight'
8.2
1.5
7.3
1.2
14.0
3.3
6.9
1.2
* All Races includes White, Black, and races other than White and Black and origin not stated.
b Race categories are consistent with the 1977 Office of Management and Budget standards.
0 Hispanic includes all persons of Hispanic origin of any race.
d Low birth weight is birth weight less than 2,500 grams (5 Ib 8 oz).
' Very low birth weight is birth weight less than l,500grams (3 Ib 4 oz).
Source: Martin et al., 2007.




Child-Specific Exposure Factors Handbook
September 2008
Page
 8-31

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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 8 - Body Weight
Table 8-20. Estimated
Mean Body Weights of Males and Females by Single- Year Age Groups Using NHANES II Data
Males (kg)

Mean
0 to 1 year 9.4
1 to 2 years 11.8
2 to 3 years 13.6
3 to 4 years 15.6
4 to 5 years 17.8
5 to 6 years 19.8
6 to 7 years 23.0
7 to 8 years 25.1
8 to 9 years 28.2
9 to 10 years 31.1
10 to 11 years 36.4
11 to 12 years 40.2
12 to 13 years 44.2
13 to 14 years 49.8
14 to 15 years 57.1
15 to 16 years 61.0
16 to 17 years 67.1
17 to 18 years 66.7
18 to 19 years 71.0
19 to 20 years 71.7
20 to 21 years 71.6

SD
1.3
1.6
1.8
1.9
2.4
2.8
3.7
3.8
5.6
5.8
7.2
9.8
9.8
11.4
10.7
10.4
11.7
11.3
12.0
11.3
12.0
a Data were converted from ag
SD = Standard Deviation.


N
179
370
375
418
404
397
133
148
147
145
157
155
145
173
186
184
178
173
164
148
114

Mean
8.8
10.8
13.0
14.9
17.0
19.6
22.1
24.7
27.8
31.8
36.1
41.8
46.4
50.9
54.7
55.1
58.1
59.6
59.0
60.1
60.5
;es in months to ages in years.


Females (kg)

SD
1.3
1.4
1.5
2.1
2.3
3.2
3.9
4.6
4.8
7.3
7.7
10.1
10.1
11.2
10.7
9.0
9.6
10.4
10.2
10.1
10.7
For instance, age

Overall (kg)

N
177
336
336
366
396
364
135
157
123
149
136
140
147
162
178
145
170
134
170
158
162

Mean
9.1
11.3
13.3
15.2
17.4
19.7
22.5
24.8
28.1
31.4
36.2
41.0
45.4
50.4
55.9
58.0
62.4
63.3
64.6
65.3
65.2
1-2 years represents ages from



SD
1.2
1.5
1.6
1.8
2.4
2.8
3.6
3.8
5.6
5.9
7.1
9.9
10.0
11.5
10.5
9.9
10.9
10.7
10.9
10.3
10.9
12 to 23


N
356
706
711
784
800
761
268
305
270
294
293
295
292
335
364
329
348
307
334
306
276
months.

N = Number of individuals.
Source: Portier et al., 2007.








Page
8-32
Child-Specific Exposure Factors Handbook
                       September 2008

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 Child-Specific Exposure Factors Handbook

 Chapter 8 - Body Weight	
Table 8
Age Group"
0 to 1 years
1 to 2 years
2 to 3 years
3 to 4 years
4 to 5 years
5 to 6 years
6 to 7 years
7 to 8 years
8 to 9 years
9 to 10 years
10 to 11 years
11 to 12 years
12 to 13 years
13 to 14 years
14 to 15 years
15 to 16 years
16 to 17 years
17 to 18 years
18 to 19 years
19 to 20 years
20 to 21 years
-21. Estimated
Mean
Males (k
Mean
8.5
11.6
13.6
15.8
17.6
20.1
23.2
26.3
30.1
34.4
37.3
42.5
49.1
54.0
63.7
66.8
68.6
72.7
71.2
73.0
72.5
SD
1.5
1.5
1.5
2.3
2.4
3.0
5.0
5.0
6.9
7.9
8.6
10.5
11.1
12.9
17.1
14.9
14.9
13.3
14.3
12.8
13.4
" Data were converted from a§
SD = Standard Deviation.
Body Weights of Males and Females by Sin
g)
N
902
660
644
516
549
497
283
269
266
281
297
281
203
187
188
187
194
196
176
168
149
es in months to a;

Mean
7.8
10.9
13.2
15.4
17.9
20.2
22.6
26.3
29.8
34.3
37.9
44.2
49.1
55.7
58.3
58.3
61.5
62.4
61.5
63.6
61.7
jes in years.
Females (kj
SD
1.6
1.4
1.8
2.2
3.2
3.5
4.7
6.2
6.7
9.0
9.5
10.5
11.6
13.2
11.8
10.1
12.8
11.9
14.2
14.5
12.9
For instance,
gle-Year Age Groups Using NHANES III Data
1) Overall (kg)
N
910
647
624
587
537
554
272
274
248
280
258
275
236
220
220
197
215
217
193
193
180
Mean
8.17
11.2
13.4
15.6
17.8
20.2
22.9
26.4
30.0
34.4
37.7
43.4
49.1
54.8
60.6
61.7
65.2
67.6
66.4
68.3
66.1
age 1-2 years represents ages from
SD
1.7
1.5
1.8
2.2
3.2
3.5
4.8
6.2
6.7
9.0
9.4
10.3
11.7
13.0
12.2
10.7
13.6
12.9
15.3
15.6
13.8
12 to 23
N
1,812
1,307
1,268
1,103
1,086
1,051
555
543
514
561
555
556
439
407
408
384
409
413
369
361
329
months.
N = Number of individuals.
Source: Portier et al., 2007.
Child-Specific Exposure Factors Handbook
September 2008
Page
 8-33

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 8 - Body Weight
Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES IV Data
Age Group"

0 to 1 year
1 to 2 years
2 to 3 years
3 to 4 years
4 to 5 years
5 to 6 years
6 to 7 years
7to 8 years
8 to 9 years
9 to 10 years
10 to 11 years
11 to 12 years
12 to 13 years
13 to 14 years
14 to 15 years
15 to 16 years
16 to 17 years
17 to 18 years
18 to 19 years
19 to 20 years
20 to 21 years
a Data
Males (kg)

Mean
9.3
11.3
13.7
16.4
18.8
20.2
22.9
28.1
31.9
36.1
39.5
42.0
49.4
54.9
65.1
68.2
72.5
75.4
74.8
80.1
80.0
were converted

SD
1.8
1.4
2.0
2.3
2.6
3.3
4.3
5.6
8.6
7.5
9.0
10.2
12.7
16.2
19.9
15.7
18.6
17.9
15.9
17.2
15.5

N
116
144
130
105
95
65
94
100
100
76
92
84
158
161
137
142
153
146
131
129
37
from ages in months to ages

Mean
9.3
11.5
13.3
15.2
18.1
20.7
22.0
26.0
30.8
36.0
39.4
47.2
51.6
59.8
59.9
63.4
63.4
59.9
65.0
68.7
66.3
in years.
Females (kg)

SD
1.5
1.9
1.9
2.1
3.2
4.9
4.5
6.2
7.2
8.4
10.2
12.2
12.3
15.3
13.3
13.9
16.0
11.9
15.2
17.4
15.5
For instance, age
Overall (kg)

N
101
98
113
77
87
92
74
82
89
84
84
97
160
156
158
126
142
128
139
132
44

Mean
9.3
11.4
13.5
15.9
18.5
20.6
22.5
27.4
31.3
36.2
39.5
44.6
50.3
56.9
61.5
65.9
68.0
66.6
70.2
74.6
74.3
1-2 years represents ages from

SD
1.5
1.8
2.0
2.2
3.3
4.9
4.6
6.5
7.3
8.5
10.2
11.6
11.9
14.6
13.7
14.4
17.1
13.2
16.4
19.0
17.4
12 to 23

N
217
242
243
182
182
157
168
182
189
160
176
181
318
317
295
268
295
274
270
261
81
months.
SD = Standard Deviation.
N = Number of individuals.
Source: Portier et al, 2007.
Page
8-34
Child-Specific Exposure Factors Handbook
                       September 2008

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 Child-Specific Exposure Factors Handbook
 Chapter 8 - Body Weight
Table 8-23. Estimated Body Weights of Typical Age Groups
Age Gro

lip NHANF.S
Males (kg)
Mean
II
1 to 6 years III


IV
II
7 to 16 years III

SD
N
Source:
IV
17.0
16.9
17.1
45.2
49.3
47.9
SD
4.6
4.7
4.9
17.6
20.9
20.1
N
2,097
3,149
633
1,618
2,549
1,203
of Interest in U.S. EPA Risk Assessments*
Females (kg)
Mean
16.3
16.5
17.5
43.9
46.8
47.9
SD
4.7 1
4.9 3
5.0
15.9 1
18.0 2
19.2 1
N
,933
,221
541
,507
,640
,178
Overall (kg)
Mean
16.7
16.8
17.3
44.8
47.8
47.7
SD
4.5
5.0
5.0
17.5
18.4
19.1
N
4,030
6,370
1,174
3,125
5,189
2,381
Estimates were weighted using the sample weights provided with each survey.
= Standard Deviation.
= Number of individuals.
Portier et al., 2007.









Table 8-24. Estimated Percentile Distribution of Body Weight by Fine Age Categories Derived From 1994-96,
1998 CSFII
Weight (kilograms)
A ^ Sample
Age Group ^
Birth to 1 month 88
1 to <3 months 245
3 to <6 months 411
6 to <12 months 678
1 to <2 years 1,002
2 to <3 years 994
3 to <6 years 4,112
6to
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Table 8-25. Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence Interval
Weight (Kilograms)

Age Group
Birth to 1 month
Ito
3 to
6 to
Ito
2 to
3 to
6 to
<3 months
<6 months
<12 months
<2 years
<3 years
<6 years
<11 years
11 to <16 years
16 to <18 years
18to<21 years
CI
BI
Sample
Size
88
245
411
678
1,002
994
4,112
1,553
975
360
383

Estimate
4
5
7
9
12
14
18
30
54
67
69
Mean
90%
Lower
Bound
3
5
7
9
12
14
18
29
53
66
68

CI


90th Percentile
90% BI

95th
Percentile

90% BI
Estimate Estimate
Upper Lower Upper Lower
Bound Bound Bound Bound
4
5
7
9
12
14
18
30
55
68
70
4"
6
9
11
14
18
23
41
72
86
89
4"
6
9
11
14
17
23
41
70
84
88
5"
7
9
11
15
18
23
43
75
95
95
5*
7"
10
12
15
19
25
45
82
100'
100"
5"
1
10
12
15
18
25
44
81
95"
95"
Sample size does meet minimum reporting requirements as described in the "Third Report on Nutrition Monitoring in the United States"(Vol.
Interval estimates may involve aggregation of variance estimation units when data are too sparse to support estimation of variance.
= Confidence interval.
= Percentile intervals estimated using percentile bootstrap method with 1,000 bootstrap replications.
Upper
Bound
5*
7
10
12
16
19
25
48
84
109"
104"
I).
Source: Kahn and Stralka, 2008.
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 Chapter 8 - Body Weight	
Table 8-26. Fetal Weight (grams) Percentiles Throughout Pregnancy
Gestational Age Number of
(weeks) Women
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
b
Source:
6
7
15
13
18
43
61
63
59
36
58
31
21
43
69
71
74
48
86
76
91
88
128
113
210
242
373
492
1,085
1,798
3,908
5,413
10,586
3,399
1,725
507
147
10th

-
-
-
-
-
-
-
-
-
-
-
280
320
370
420
490
570
660
770
890
1,030
1,180
1,310
1,480
1,670
1,870
2,190
2,310
2,510
2,680
2,750
2,800
2,830
2,840
2,790
Data not available.
Median fetal weights may be overestimated.
weeks' gestation.
Brenner et al., 1976.

25th
:
-
-
11
23
3,405
51
80
125
172
217
255
330
410
460
530
630
730
840
980
1,100
1,260
1,410
1,570
1,720
1,910
2,130
2,470
2,580
2,770
2,910
3,010
3,070
3,110
3,110
3,050
50th
6.1"
7.3b
8.1b
11.9b
21
35
51
77
117
166
220
283
325
410
480
550
640
740
860
990
1,150
1,310
1,460
1,630
1,810
2,010
2,220
2,430
2,650
2,870
3,030
3,170
3,280
3,360
3,410
3,420
3,390
75th
:
-
-
34
55
77
108
151
212
298
394
460
570
630
690
780
890
1,020
1,160
1,350
1,530
1,710
1,880
2,090
2,280
2,510
2,730
2,950
3,160
3,320
3,470
3,590
3,680
3,740
3,780
3,770
90th
:
-
-
-
-
-
-
-
-
-
-
-
860
920
990
1,080
1,180
1,320
1,470
1,660
1,890
2,100
2,290
2,500
2,690
2,880
3,090
3,290
3,470
3,610
3,750
3,870
3,980
4,060
4,100
4,110
They were derived from only a small proportion of the fetuses delivered at these




Child-Specific Exposure Factors Handbook
September 2008
Page
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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 8 - Body Weight
Table 8-27. Neonatal Weight by Gestational Age for
Males and Females Combined
Gestational Age
(weeks)
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Source: Doubilet et al.,

5th
450
523
609
707
820
947
1,090
1,249
1,422
1,608
1,804
2,006
2,210
2,409
2,595
2,762
2,900
3,002
3,061
1997.

10th
490
568
660
765
884
1,020
1,171
1,338
1,519
1,714
1,919
2,129
2,340
2,544
2,735
2,904
3,042
3,142
3,195


25th
564
652
754
870
1,003
1,151
1,317
1,499
1,696
1,906
2,125
2,349
2,572
2,786
2,984
3,155
3,293
3,388
3,432

Weight (g)
50th
660
760
875
1,005
1,153
1,319
1,502
1,702
1,918
2,146
2,383
2,622
2,859
3,083
3,288
3,462
3,597
3,685
3,717


75th
772
885
1,015
1,162
1,327
1,511
1,713
1,933
2,169
2,416
2,671
2,927
3,177
3,412
3,622
3,798
3,930
4,008
4,026


90th
889
1,016
1,160
1,322
1,504
1,706
1,928
2,167
2,421
2,687
2,959
3,230
3,493
3,736
3,952
4,127
4,254
4,322
4,324


95th
968
1,103
1,257
1,430
1,623
1,836
2,070
2,321
2,587
2,865
3,148
3,428
3,698
3,947
4,164
4,340
4,462
4,523
4,515

Page
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Chapter 9 - Intake of Fruits and Vegetables
                                   TABLE OF CONTENTS

9      INTAKE OF FRUITS AND VEGETABLES 	9-1
       9.1     INTRODUCTION	9-1
       9.2     RECOMMENDATIONS	9-2
       9.3     INTAKE STUDIES	9-6
              9.3.1   Key Fruits and Vegetables Intake Study	9-6
                     9.3.1.1  U.S. EPA Analysis of CSFII 1994-96, 1998  	9-6
              9.3.2   Relevant Fruit and Vegetable Intake Studies	9-8
                     9.3.2.1  USDA, 1999 	9-8
                     9.3.2.2  Smiciklas-Wright et al, 2003 	9-8
                     9.3.2.3  Fox et al., 2004	9-9
                     9.3.2.4  Ponza et al., 2004 	9-9
                     9.3.2.5  Menella et al., 2006 	9-10
                     9.3.2.6  Fox et al., 2006	9-10
       9.4     CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	9-10
       9.5     REFERENCES FOR CHAPTER 9	9-11

 APPENDIX 9A	 9A-1
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                                                      Chapter 9 - Intake of Fruits and Vegetables
                                          LIST OF TABLES

Table 9-1.       Recommended Values for Intake of Fruits and Vegetables, As Consumed	9-3
Table 9-2.       Confidence in Recommendations for Intake of Fruits and Vegetables  	9-4
Table 9-3.       Per Capita Intake of Fruits and Vegetables (g/kg-day as consumed)	9-12
Table 9-4.       Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed)	9-13
Table 9-5.       Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed)	9-14
Table 9-6.       Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed)	9-17
Table 9-7.       Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day)	9-20
Table 9-8.       Percentage of Individuals Consuming Vegetables, by Sex and Age (%)	9-21
Table 9-9.       Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day)	9-22
Table 9-10.      Percentage of Individuals Consuming, Fruits by Sex and Age  (%)	9-23
Table 9-11.      Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and
                Percentage of Individuals Using These Foods in Two Days	9-24
Table 9-12.      Characteristics of the FITS Sample Population	9-25
Table 9-13.      Percentage of Infants and Toddlers Consuming Different Types of Vegetables	9-26
Table 9-14.      Top Five Vegetables Consumed by Infants and Toddlers	9-27
Table 9-15.      Percentage of Infants and Toddlers Consuming Different Types of Fruits 	9-28
Table 9-16.      Top Five Fruits Consumed by Infants and Toddlers	9-29
Table 9-17.      Characteristics of WIC Participants and Non-participants (Percentages) 	9-30
Table 9-18.      Food Choices for Infants and Toddlers by WIC Participation Status  	9-32
Table 9-19.      Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming
                Different Types of Fruits and Vegetables on A Given Day	9-33
Table 9-20.      Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants
                and Toddlers Per Age Group	9-34
Table 9-21.      Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
                Consumed by Infants from the 2002 Feeding Infants and Toddlers Study  	9-35
Table 9-22.      Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly
                Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study	9-36
Table 9-23.      Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible
                Portions	9-37
Table 9A-1.      Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data .... 9A-2
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Chapter 9 - Intake of Fruits and Vegetables
9     INTAKE OF FRUITS AND VEGETABLES
9.1   INTRODUCTION
      The  American   food  supply  is  generally
considered to be  one of the safest in  the  world.
Nevertheless,  fruits and  vegetables may become
contaminated with toxic chemicals by several different
pathways.  Ambient pollutants from the  air may be
deposited on or absorbed by the plants, or dissolved in
rainfall  or irrigation waters that contact the  plants.
Pollutants may also be absorbed through plant roots
from contaminated soil and ground water. The addition
of pesticides, soil additives, and fertilizers may also
result in contamination of fruits and vegetables.  To
assess exposure through this pathway, information on
fruit and vegetable ingestion rates is needed.
      Children's exposure from contaminated fruits
and vegetables may differ from that of adults because of
differences in the types and amounts of food eaten.
Also, for many foods, the intake per unit body weight is
greater for children than for adults.  Common fruits and
vegetables eaten by children include apple juice, fresh
apples, orange juice, fresh pears, fresh peaches, carrots,
fresh bananas, succulent garden peas, and succulent
garden beans (Goldman, 1995).
      A variety of terms may be used to define intake
of fruits and vegetables (e.g., consumer-only intake, per
capita intake, total fruit intake, total vegetable  intake,
as-consumed intake, dry weight intake).  These terms
are defined below to assist the reader in interpreting and
using the intake rates that  are  appropriate for the
exposure scenario being assessed.
      Consumer-only intake is defined as the quantity
of fruits and vegetables consumed by children during
the survey period.   These data are generated by
averaging intake across only the children in the survey
who consumed these food items. Per capita intake rates
are generated by averaging consumer-only intakes over
the entire  population  of children (including  those
children that reported no intake). In general, per capita
intake  rates  are appropriate  for  use in  exposure
assessments for which  average  dose estimates for
children are of interest  because they  represent  both
children who ate the foods during the survey period and
children who may eat the food items at some time, but
did not  consume them during the survey period. Per
capita intake, therefore,  represents an average across
the entire population of interest, but does so at the
expense of underestimating consumption for the subset
of the population that consumed the food in question.
Total fruit intake refers  to  the sum of all  fruits
consumed in a day including canned, dried, frozen, and
fresh fruits.  Likewise, total vegetable intake refers to
the sum of all vegetables consumed in a day including
canned, dried, frozen, and fresh vegetables.
      Intake rates may be expressed on the basis of the
as-consumed weight (e.g.,  cooked or prepared) or on
the  uncooked or unprepared  weight.  As-consumed
intake rates are based on the weight of the food in the
form that it  is  consumed and  should  be used  in
assessments  where the basis for the contaminant
concentrations in foods is also  indexed to  the as-
consumed weight. The food ingestion values provided
in this  chapter are expressed  as  as-consumed intake
rates because this is  the fashion  in which data were
reported by survey respondents. This is of importance
because concentration  data to be used  in the  dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease  food  weight.   Similarly, cooking can
increase the mass of contaminant in food  (due  to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching).   The combined
effects of changes in weight and changes in contaminant
mass can result  in either an increase  or decrease in
contaminant concentration in cooked food. Therefore,
if the as-consumed ingestion  rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated.  Ideally, after-
cooking food concentrations should be combined with
the as-consumed intake rates. In the absence of data, it
is reasonable to assume that no change in contaminant
concentration occurs  after cooking. It is important for
the  assessor to be  aware of these issues and choose
intake rate data that best match the concentration data
that are being used. For more  information on cooking
losses and conversions necessary to account for such
losses,  the reader  is referred to Chapter 13 of this
handbook.
      Sometimes contaminant concentrations in food
are reported on a dry weight basis.  When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used. Dry-weight food
concentrations and intake rates are based on the weight
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                                                        Chapter 9 - Intake of Fruits and Vegetables
of the food consumed after the moisture content has
been removed.   For information on  converting the
intake rates  presented in this chapter to dry weight
intake rates, the reader is referred to Section 9.4.
      The purpose of this chapter is to provide intake
data for fruits and vegetables among children.  The
recommendations for fruit and vegetable ingestion rates
are provided in the next section, along with a summary
of the confidence ratings for these recommendations.
The recommended values are based on the key study
identified by U.S. EPA for this factor. Following the
recommendations, the key study on fruit and vegetable
ingestion is summarized.  Relevant data on ingestion of
fruits and vegetables are also provided. These data are
presented to provide the reader with added perspective
on  the current  state-of-knowledge  pertaining  to
ingestion of fruits and vegetables.

9.2   RECOMMENDATIONS
      Table  9-1  presents  a  summary  of the
recommended values for per capita and consumers-only
intake of fruits and vegetables, on an  as-consumed
basis. Confidence ratings for the fruit and vegetable
intake recommendations for general population children
are provided in Table 9-2.
      The U.S. EPA analysis of data from the 1994-96
and  1998 Continuing Survey of Food Intake among
Individuals (CSFII) was used in selecting recommended
intake rates for general population children.  The U.S.
EPA analysis was conducted using age groups  that
differed slightly  from  U.S.  EPA's  Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis.   Also, the CSFII data on which the
recommendations are based are short-term survey data
and  may  not   necessarily  reflect the  long-term
distribution of average daily intake rates. However, for
broad categories of food (i.e., total fruits  and total
vegetables),  because they are eaten on  a daily basis
throughout the year with minimal seasonality, the short
term distribution may be a reasonable approximation of
the long-term distribution, although it will  display
somewhat increased variability.  This implies that the
upper percentiles shown here may tend to overestimate
 the corresponding percentiles of the  true long-term
 distribution.  It should also be noted that because these
 recommendations  are  based on  1994-96 and 1998
 CSFII  data,  they  may not reflect  the  most recent
 changes that may have  occurred  in  consumption
 patterns. More current data from the National Health
 and Nutrition Survey (NHANES) will be incorporated
 as the data become available and are analyzed.
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Chapter 9 - Intake of Fruits and Vegetables
                   Table 9-1. Recommended Values for Intake of Fruits and Vegetables, As Consumed1
    Age Group
                            Per Capita
                                 Consumers Only
Mean
95th Percentile
Mean
95th Percentile
 Multiple
Percentiles
                                    g/kg-day
                            g/kg-day
                               g/kg-day
  Source
 Birth to 1 year
 1 to <2 years
 2 to < 3 years
 3 to <6 years
 6 to <11 years
 11 to <16 years
 16 to <21 years
                                                 Total Fruits
 5.7
 6.2
 6.2
 4.6
 2.4
 0.8
 0.8
     21
     19
     19
     14
     8.8
     3.5
     3.5
 10
 6.9
 6.9
 5.1
 2.7
 1.1
 1.1
     26
     19
     19
     15
     9.3
     3.8
     3.8
 See Tables
9-3 and 9-4
 U.S. EPA
Analysis of
  CSFII,
1994-96 and
   1998.
 Birth to 1 year
 1 to <2 years
 2 to <3 years
 3 to <6 years
 6 to <11 years
 11 to <16 years
 16 to <21 years
                                               Total Vegetables
 4.5
 6.9
 6.9
 5.9
 4.1
 2.9
 2.9
     15
     17
     17
     15
     9.9
     6.9
     6.9
 6.2
 6.9
 6.9
 5.9
 4.1
 2.9
 2.9
     16
     17
     17
     15
     9.9
     6.9
     6.9
 See Tables
9-3 and 9-4
 U.S. EPA
Analysis of
  CSFII,
1994-96 and
   1998.
                              Individual Fruits and Vegetables - See Tables 9-5 and 9-6
        Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
        Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005). Data
        were placed in the standardized age categories closest to those used in the analysis.
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                                            Chapter 9 - Intake of Fruits and Vegetables

Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Rationale
The survey methodology and data analysis was
adequate. The survey sampled more than 1 1,000
individuals up to age 18 years. However, samples size
for some individual fruits and vegetables for some of
the age groups are small. An analysis of primary data
was conducted.
No physical measurements were taken. The method
relied on recent recall of fruits and vegetables eaten.
The key study was directly relevant to fruit and
vegetable intake.
The data were demographically representative of the
U.S. population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total fruits and total
vegetables. Means were provided for individuals fruits
and vegetables.
Data collection was based on recall of consumption for
a 2-day period; the accuracy of using these data to
estimate long-term intake (especially at the upper
percentiles) is uncertain. However, use of short-term
data to estimate chronic ingestion can be assumed for
broad categories of foods such as total fruits and total
vegetables. Uncertainty is likely to be greater for
individual fruits and vegetables.
Rating
High for total fruits and
vegetables, low for some
individual fruits and
vegetables with small
sample size
Medium
High
Medium
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Chapter 9 - Intake of Fruits an

rs Handbook ^S$^P
^\y*A
id Vegetables \g^^j

Table 9-2. Confidence
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating


in Recommendations for Intake of Fruits and Vegetables (continued)
Rationale Rating
Medium
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not
been peer reviewed outside the Agency.
There was 1 key study.
High confidence in the
averages; Low for some
individual fruits and
vegetables with small
sample size
Low confidence in the
long-term upper
percentiles
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                                                        Chapter 9 - Intake of Fruits and Vegetables
9.3     INTAKE STUDIES
        The primary source of recent information on
consumption rates of fruits and vegetables  among
children  is the  U.S. Department  of Agriculture's
(USDA) CSFII. Data from the 1994-96 CSFII and the
1998 Children's supplement to the 1994-96 CSFII have
been used in various studies  to generate children's
consumer-only and  per capita intake rates for both
individual fruits  and vegetables and total fruits and
vegetables. The CSFII is a series of surveys designed
to measure the kinds and amounts of foods eaten by
Americans.   The CSFII  1994-96  was  conducted
between January 1994 and January 1997 with a target
population of non-institutionalized individuals in all 50
states and Washington, D.C.  In each of the 3 survey
years,  data   were  collected  for   a   nationally
representative sample of individuals of all ages.  The
CSFII 1998 was conducted between December 1997
and December 1998 and surveyed children 9 years of
age and younger. It used the same sample design as the
CSFII 1994-96 and  was intended to be merged with
CSFII 1994-96 to increase the sample size for children.
The merged surveys are designated as CSFII 1994-96,
1998. Additional information on these surveys can be
obtained  at
http://www.ars.usda. goy^'Services/docs. htm ?docid=14531.
        The CSFII  1994-96,  1998 collected dietary
intake data through in-person interviews  on 2 non-
consecutive days.  The data were  based on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day.  Over 11,000 of the sample persons
represented children up to 18 years of age.  The 2-day
response   rate  for  the  1994-1996  CSFII   was
approximately 76 percent. The 2-day response rate for
CSFII 1998 was 82 percent.
        The CSFII 1994-96,98 surveys were based on
a complex multistage area probability sample design.
The sampling frame was organized using 1990 U.S.
population census estimates, and the stratification plan
took into account  geographic location,  degree of
urbanization,   and   socioeconomic   characteristics.
Several sets of sampling weights are available for use
with the intake data. By using appropriate weights, data
for all fours years of the surveys can be combined.
USDA recommends that all 4 years be combined in
 order to provide an adequate sample size for children.

 9.3.1    Key Fruits and Vegetables Intake Study
 9.3.1.1  U.S. EPA Analysis of CSFII 1994-96, 1998
         For many years, the  U.S.  EPA's Office of
 Pesticide Programs (OPP) has used food consumption
 data collected by the U.S. Department of Agriculture
 (USDA) for its dietary risk assessments. Most recently,
 OPP,  in  cooperation  with  USDA's  Agricultural
 Research Service (ARS), used  data from the 1994-96,
 1998 CSFII  to develop the Food Commodity Intake
 Database (FCID).  CSFII data on the foods people
 reported eating were converted to  the quantities of
 agricultural  commodities  eaten.     "Agricultural
 commodity"  is a term used by U.S. EPA to mean plant
 (or animal) parts consumed by humans as food; when
 such items are raw or unprocessed, they are referred to
 as "raw agricultural commodities."  For example, an
 apple pie may contain the commodities apples, flour,
 fat, sugar and spices. FCID contains approximately 553
 unique commodity names and 8-digit codes. The FCID
 commodity names and codes were selected and defined
 by U.S.  EPA and were based on the U.S. EPA Food
 Commodity  Vocabulary
 (http://www.epa.Kov/pesticides/foodfeed/).
         The fruit and vegetable items/groups selected
 for the U.S. EPA analysis included total fruits and total
 vegetables,  and  individual fruits  such  as:   apples,
 bananas, peaches, pears, strawberries, citrus fruits,
 pome fruit, stone  fruit,  and  tropical fruits;   and
 individual  vegetables   such   as:  asparagus,  beets,
 broccoli, cabbage, carrots, corn, cucumbers, lettuce,
 okra, onions, peas, peppers, pumpkin, beans, tomatoes,
 white potatoes,  bulb vegetables, fruiting vegetables,
 leafy  vegetables,  legumes, and  small  stalk  stem
 vegetables. Appendix 9A presents the food codes and
 definitions used to determine  the various fruits  and
 vegetables used in the analysis. Intake rates for these
 food items/groups represent intake of all forms of the
 product (e.g., both home produced and commercially
 produced). Children who provided data for two days of
 the survey were  included in the intake  estimates.
 Individuals who did not provide  information on body
 weight or for  whom identifying  information   was
 unavailable were excluded from the analysis. Two-day
 average intake rates were calculated for all individuals
 in the database for each of the food items/groups.
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Chapter 9 - Intake of Fruits and Vegetables
These average daily intake rates were divided by each
individual's reported body weight to generate intake
rates in units of grams per kilogram of body weight per
day (g/kg-day). The data were weighted according to
the four-year, two-day sample weights provided in the
1994-96, 1998 CSFII to adjust the data for the sample
population to reflect the national population.
        Summary statistics were generated on both a
per capita and a consumer only basis. For per capita
intake, both users and non-users of the food item were
included in the analysis. Consumer only intake rates
were calculated using data for only those individuals
who ate the food item  of interest during the  survey
period.  Intake data from the CSFII were based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the fruits or vegetables being analyzed, mean intake
rate, and standard error of the mean intake rate were
calculated for total fruits, total vegetables, and selected
individual  fruits and vegetables.  Percentiles  of the
intake rate  distribution (i.e., 1st, 5th, 10th, 25th, 50th,
75th, 90th, 95th, 99th, and 100th percentile were also
provided for total fruits and total vegetables. Data were
provided for the following age groups of children: birth
to <1 year,  1 to <2 years, 3 to <5 years, 6 to <12 years,
and  13  to  <19  years.  Because these  data were
developed for use in U.S. EPA's pesticide registration
program, the age groups used are slightly different than
those recommended  in U.S. EPA's Guidance  on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).
        Table 9-3 presents as-consumed per capita
intake data for total fruits and vegetables in g/kg-day;
as-consumed consumer only intake data for total fruits
and vegetables in g/kg-day are provided  in Table 9-4.
Table 9-5 provides per capita intake data for individual
fruits and vegetables and Table 9-6 provides consumer
only intake data for individual fruits and vegetables.
        It  should be noted that  the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the long-
term distribution  of average daily intake rates.  The
distributions generated from short-term and long-term
data will differ to the extent that each individual's
intake varies from day to day; the distributions will be
similar  to  the extent  that  individuals'  intakes are
constant from day to day.  Day-to-day variation in
intake among individuals  will be high for fruits and
vegetables that are highly  seasonal and for fruits and
vegetables that are eaten year-round, but that are not
typically eaten  every  day.   For these fruits  and
vegetables, the intake distribution generated from short-
term data will not be a good reflection of the long-term
distribution. On the other hand, for broad categories of
foods (e.g., total fruits and total vegetables) that are
eaten on a daily  basis throughout the year, the short-
term distribution may be a reasonable approximation of
the true long-term distribution,  although it will show
somewhat  more  variability.    In  this   chapter,
distributions are  provided only for broad categories of
fruits and  vegetables  (i.e., total  fruits and  total
vegetables).  Because of the increased variability of the
short-term distribution, the short-term upper percentiles
shown   here  may overestimate  the  corresponding
percentiles of the long-term distribution. For individual
foods,  only the  mean, standard  error,  and percent
consuming are provided.
         The  strengths of U.S. EPA's analysis are that
it provides distributions of intake rates for various age
groups of children, normalized by body  weight.  The
analysis uses  the 1994-96,  1998 CSFII data set which
was designed  to be  representative  of the  U.S.
population. The data set includes four years of intake
data combined,  and is based on a two-day survey
period.   As discussed above, short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food. This is particularly  true for the tails (extremes)
of the distribution of food intake.  Also, the analysis
was conducted using slightly different age groups than
those recommended in U.S.  EPA's Guidance  on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005). However, given the similarities in
the age  groups used, the data should provide suitable
intake estimates for the age groups of interest.
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                                                        Chapter 9 - Intake of Fruits and Vegetables
9.3.2    Relevant  Fruit  and  Vegetable  Intake
        Studies
9.3.2.1  USDA, 1999 - Food and Nutrient Intakes by
        Children 1994-96,1998, Table Set 17
        USDA (1999) calculated national probability
estimates of food and nutrient intake by children based
on all 4 years of the CSFII (1994-96 and  1998) for
children age 9 years and under, and on CSFII 1994-96
only for individuals age 10 years and over.  Sample
weights were used to adjust for non-response, to match
the sample  to  the  U.S.  population  in  terms  of
demographic characteristics, and to equalize intakes
over the 4 quarters of the year  and  the 7 days of the
week. A total of 503 breast-fed children were excluded
from the estimates, but both  consumers  and  non-
consumers were included in the analysis.
        USDA (1999) provided data on the mean per
capita  quantities  (grams)   of   various   food
products/groups consumed  per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey. Tables 9-7 through 9-10 present
data on the  mean quantities  (grams) of fruits and
vegetables consumed per individual for  one day, and
the percentage of survey individuals consuming  fruits
and vegetables on that survey day.  Data on  mean
intakes or mean percentages are based on respondents'
day-1 intakes.
        The advantage of  the USDA (1999) study is
that it  uses  the  1994-96,  98 CSFII data set, which
includes  four years of intake  data,  combined, and
includes the supplemental data on children. These data
are expected to be generally representative of the U.S.
population and they include data on a wide  variety of
fruits and vegetables.  The data set is one of a series of
USDA data  sets that are  publicly available.  One
limitation of this data set is that it is based on a one-day,
and short-term dietary data may not accurately reflect
long-term eating patterns.   Other limitations of this
study are that it only  provides mean values of food
intake rates, consumption is not normalized by  body
weight, and presentation of results is not consistent with
U.S. EPA's recommended age groups.
 9.3.2.2  Smiciklas-Wright et al,  2002  -   Foods
         Commonly Eaten in  the United  States:
         Quantities Consumed per Eating Occasion
         and in a Day, 1994-1996
         Using data gathered in the 1994-96 USDA
 CSFII, Smiciklas-Wright et al.  (2002)   calculated
 distributions for the quantities of fruits and vegetables
 consumed per eating occasion by members of the U. S.
 population  (i.e., serving sizes).   The  estimates of
 serving size were based on data obtained from 14,262
 respondents, ages 2 years and above, who provided 2
 days of dietary intake information.  A total of 4,939 of
 these respondents were children,  ages 2 to 19 years of
 age.   Only  dietary intake  data from users of the
 specified food were used in the analysis (i.e., consumers
 only data).
         Table 9-1 presents  serving  size data  for
 selected fruits and vegetables. These data are presented
 on an as-consumed  basis (grams) and represent the
 quantity of fruits and vegetables  consumed per eating
 occasion. These estimates may be useful for assessing
 acute exposures to contaminants in specific foods, or
 other assessments where the amount consumed per
 eating occasion is necessary.    Only the mean and
 standard deviation serving size data and percent of the
 population consuming the food during the 2-day survey
 period are presented in this handbook.  Percentiles of
 serving  sizes of the foods  consumed by these age
 groups of  the U.S. population  can  be found in
 Smiciklas-Wright et  al. (2002).
         The advantages of using these data are that
 they were derived from  the USDA CSFII  and are
 representative  of the U.S. population.  The  analysis
 conducted by Smiciklas-Wright et al. (2002) accounted
 for individual foods consumed as ingredients of mixed
 foods. Mixed foods were disaggregated via recipe files
 so that the individual  ingredients could  be  grouped
 together  with  similar  foods  that were reported
 separately.   Thus,  weights of  foods  consumed as
 ingredients were combined with  weights of foods
 reported  separately  to  provide  a more thorough
 representation of consumption. However, it should be
 noted that  since the  recipes for  the mixed foods
 consumed were  not provided by  the  respondents,
 standard recipes were used.  As a result, the estimates
 of quantity consumed for some food types are based on
 assumptions  about  the  types   and  quantities  of
Page
9-8
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
ingredients consumed as part of mixed foods.  This
study used data from the 1994 to 1996 CSFII; data from
the 1998 children's supplement were not included.

9.3.2.3  Fox et al,  2004  -  Feeding  Infants and
        Toddlers study: What Foods Are Infants and
        Toddlers Eating
        Fox et al. (2004) used data from the Feeding
Infants  and Toddlers study (FITS) to assess food
consumption patterns in infants and toddlers. The FITS
was sponsored by Gerber Products Company and was
conducted to obtain current information on food and
nutrient intakes of children, ages 4 to 24 months old, in
the 50 states and the District of Columbia. The FITS is
described in detail in Devaney et al. (2004).  FITS was
based on a random sample of 3,022 infants and toddlers
for which dietary intake  data were  collected  by
telephone  from their parents  or caregivers between
March and  July 2002.  An initial recruitment  and
household interview was conducted, followed by an
interview to obtain information on intake based on 24-
hour recall.  The interview also addressed growth,
development and feeding patterns.  A second dietary
recall interview was  conducted for a subset of 703
randomly  selected respondents.   The  study over-
sampled children in the 4 to  6 and 9 to 11 months age
groups; sample weights were adjustedfornon-response,
over-sampling, andunder-coverage of some subgroups.
The response rate for the FITS was 73 percent for the
recruitment interview.  Of the recruited households,
there was a response rate of  94 percent for the dietary
recall  interviews (Devaney  et  al.,  2004).   The
characteristics of the FITS study population is shown in
Table 9-12.
        Fox et al. (2004) analyzed the first set of 24-
hour recall data collected from all study participants.
For this analysis, children were grouped into six age
categories: 4 to  6  months,  7 to 8 months, 9 to  11
months, 12 to 14 months, 15 to 18 months, and 19 to 24
months. Table 9-13 provides the percentage of infants
and toddlers consuming different types of vegetables at
least once  in a day.  The percentages of children eating
any type of vegetable ranged from 39.9 percent for 4 to
6 month olds to 81.6 percent for 19 to 24 month olds.
Table 9-14 provides the top five vegetables consumed
by age group. Some of the highest percentages ranged
from baby food carrots (9.6 percent) in the 4 to 6 month
old group to french fries (25.5 percent) in the 19 to 24
month old group.  Table 9-15 provides the percentage
of children consuming different types of fruit at least
once per day. The percentages of children eating any
type of fruit ranged from 41.9 percent to 4 to 6 month
olds to 77.2 percent for 12 to 14 month olds.  Table 9-
16 provides information on the top five fruits eaten by
infants and toddlers at least once per day. The highest
percentages were  for bananas among infants 9 to 24
months, and baby food applesauce among infants 4 to
8 months old.
        The advantages of this study  were that the
study population represented the U.S. population and
the sample size was  large.   One  limitation of the
analysis done  by  Fox et  al.  (2004) was  that only
frequency data were provided; no information on actual
intake rates was included. In addition, Devaney et al.
(2004) noted several limitations associated with the
FITS  data.  For the FITS, a commercial list of infants
and toddlers was used to obtain the sample used in the
study.   Since many of the households could not be
located  and did  not have  children  in  the  target
population, a lower response rate than would have
occurred in a true national  sample was  obtained
(Devaney et al., 2004).  In addition, the sample  was
likely from a  higher  socioeconomic status  when
compared with all U.S. infants in this age group (4 to 24
months old) and the use of a telephone survey may have
omitted lower-income households without telephones
(Devaney et al., 2004).

9.3.2.4  Ponza et al, 2004 - Nutrient Food Intakes
        and Food Choices of Infants and Toddlers
        Participating in WIC
        Ponza et  al. (2004) conducted a study using
selected data from the FITS to assess feeding patterns,
food choices and nutrient intake of infants and toddlers
participating in the Special  Supplemental Nutrition
Program for Women, Infants, and  Children (WIC).
Ponza et  al.  (2004)  evaluated FITS  data for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months  (N = 1,159) and 12 to 24 months (N= 996).
The total sample size described by WIC participants
and non-participants is shown in Table 9-17.
        The  foods  consumed  were  analyzed  by
tabulating the  percentage of infants who  consumed
specific foods/food groups per day (Ponza et al., 2004).
Child-Specific Exposure Factors Handbook
September 2008	
                                          Page
                                            9-9

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                                                        Child-Specific Exposure Factors Handbook

                                                        Chapter 9 - Intake of Fruits and Vegetables
Weighted data were used in all of the analyses used in
the study (Ponza et al, 2004).  Table 9-17 presents the
demographic data for WIC  participants  and non-
participants.  Table 9-18 provides information on the
food choices for the infants and toddlers studied. There
was little difference in vegetable choices among WIC
participants   and  non-participants  (Table  9-18).
However, there were some differences for fruits.
        An advantage of this study is that it had a
relatively large sample size  and was representative of
the U.S. general population of infants and children. A
limitation of the study is that  intake values for foods
were  not provided.   Other  limitations are those
associated with the FITS data,  as described previously
in Section 9.3.2.3.

9.3.2.5  Menella et al.,  2006  - Feeding Infants and
        Toddlers Study: The Types of Foods Fed to
        Hispanic Infants and Toddlers
        Menella et al. (2006) investigated the types of
food and beverages consumed  by Hispanic infants and
toddlers in comparison to the non-Hispanic infants and
toddlers in the United States.  The FITS 2002 data for
children between 4 and 24 months of age were used for
the study.  The data represent a random sample of 371
Hispanic and 2,367 non-Hispanic infants and toddlers
(Menella et al., 2006).  Menella et al. (2006) grouped
the infants as follows: 4 to 5  months (N = 84 Hispanic;
538 non-Hispanic), 6 to 11 months (N = 163 Hispanic
and 1,228 non-Hispanic), and 12 to 24 months (N = 124
Hispanic and 871 non-Hispanic) of age.
        Table  9-19  provides  the percentages  of
Hispanic and  non-Hispanic  infants  and  toddlers
consuming fruits and vegetables. In most instances the
percentages consuming the different types of fruits and
vegetables were similar.  However, 4 to 5 month old
Hispanic infants were more likely to eat fruits than non-
Hispanic infants  in this age group.     Table 9-20
provides the top five fruits  and vegetables consumed
and the percentage of children consuming these foods
at least once in a  day. Apples and bananas were the
foods with the highest percent consuming for both the
Hispanic and non-Hispanic study groups. Potatoes and
carrots were the vegetables with the highest percentage
of infants and toddlers consuming in both study groups.
        The advantage of the  study is that it provides
information on food preferences for Hispanic and non-
 Hispanic infants and toddlers. A limitation is that the
 study did not provide food intake data, but provided
 frequency of use data instead.   Other limitations are
 those noted previously in Section 9.3.2.3 for the FITS
 data.

 9.3.2.6  Fox et al, 2006 - Average Portion of Foods
         Commonly Eaten by Infants and Toddlers in
         the United States
         Fox et al. (2006) estimated average portion
 sizes consumed per eating occasion by children 4 to 24
 months of age who participated in the Feeding Infant
 and  Toddlers Study  (FITS). The FITS is a cross-
 sectional study designed to collect and analyze data on
 feeding practices, food consumption, and usual nutrient
 intake of U.S. infants and toddlers and is described in
 Section 9.3.2.3 of this chapter.  It included a stratified
 random  sample of 3,022 children between 4 and 24
 months of age.
         Usingthe 24-hour recall data, Fox et al. (2006)
 derived average portion sizes for major food groups,
 including fruits and vegetables.  Average portion sizes
 for select individual foods within these major groups
 were also estimated.  For this analysis, children were
 grouped into six age categories: 4 to 5 months, 6 to 8
 months, 9 to 11  months, 12 to  14 months, 15 to  18
 months, and 19 to 24 months.  Tables 9-21 and 9-22
 present  the  average  portion  sizes for  fruits  and
 vegetables for infants and toddlers, respectively.

 9.4     CONVERSION BETWEEN  WET AND
         DRY WEIGHT INTAKE RATES
         The intake data presented in this chapter are
 reported in units of wet weight (i.e., as-consumed fruits
 and  vegetables  consumed  per day or per  eating
 occasion).   However, data on  the concentration  of
 contaminants in fruits and vegetables may be reported
 in units  of either  wet or dry  weight.(e.g.,  mg
 contaminant  per  gram-dry-weight of fruits  and
 vegetables.)  It is essential that exposure assessors be
 aware of this difference so that they  may ensure
 consistency between the units used for intake rates and
 those used  for  concentration  data   (i.e.,  if  the
 contaminant concentration is measured in dry weight of
 fruits and vegetables,  then the dry weight units should
 be used for their intake values).
Page
9-10
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
        If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to dry weight intake rates
using the moisture content percentages presented in
Table 9-23  and the following equation:
 IR,   =  IR
   dw       ww
           100- W
             100
(Eqn. 9-1)
where:
         Mw
        W
                dry weight intake rate;
                wet weight intake rate; and
                percent water content
Alternatively, dry weight residue levels in fruits and
vegetables may be converted to wet weight residue
levels for use with wet weight (e.g., as-consumed)
intake rates as follows:
 C    =   C
   ww      dw
                 100- W
                   100
                          (Eqn. 9-2)
where:
 dw
w
                        wet weight intake rate;
                        dry weight intake rate; and
                        percent water content.
The moisture data presented in Table 9-23  are for
selected fruits and vegetables taken from USDA (2007).
9.5
REFERENCES FOR CHAPTER 9
Devaney, B.; Kalb, L.; Brief el, R.; Zavitsky-Novak, T.;
        Clusen, N.; Ziegler, P. (2004) Feeding infants
        and toddlers study:  overview of the  study
        design.  J Am Diet Assoc 104(Suppl 1): S8-
        S13.
Fox,  M.K.; Pac, S.;  Devaney, B.;  Jankowski, L.
        (2004) Feeding Infants and Toddlers Study:
        what foods are infants and toddlers eating. J
        Am Diet Assoc  104 (Suppl):S22-S30.
Fox, M.K.; Reidy, K.; Karwe, V.; Ziegler, P. (2006)
        Average portions of foods commonly eaten by
        infants and  toddlers in the United States. J
        Am Diet Assoc  106 (Suppl  1):S66-S76.
Goldman, L. (1995)  Children - unique and vulnerable.
        Environmental  risks  facing  children  and
        recommendations for response.   Environ
        Health Perspect 103(6): 13-17.
Mennella, J.;Ziegler,P.;Briefel,R.;Novak, T. (2006)
        Feeding Infants and Toddlers Study: the types
        of foods fed to Hispanic infants and toddlers.
        J Am Diet Assoc  106 (Suppl 1): S96-S106.
Ponza, M;  Devaney, B.; Ziegler, P.; Reidy,  K.;
        Squatrito, C. (2004) Nutrient intakes and food
        choices of infants and toddlers participating in
        WIC.  J Am Diet Assoc  104 (Suppl): S71-
        S79.
Smiciklas-Wright, H.; Mitchell, D.C.;  Mickle, S.J.;
        Cook, A.J.;  Goldman, J.D.  (2002)  Foods
        commonly   eaten  in   the  United  States:
        Quantities consumed per eating occasion and
        in a day, 1994-1996.   U.S.  Department of
        Agriculture  NFS Report No. 96-5, pre-
        publication version, 252 pp.
USDA.  (1999) Food and nutrient intakes by children
        1994-96,1998: Table Set 17. Beltsville, MD:
        Food Surveys Research  Group, Beltsville
        Human  Nutrition   Research   Center,
        Agricultural  Research  Service,  U.S.
        Department of Agriculture.
USDA (2007) USDA National Nutrient Database for
        Standard Reference, Release 20. Agricultural
        Research Service Nutrient Data Laboratory
        Home Page,
        http://www.ars.usda.TOv/ba/bhnrc/ndl
U.S. EPA.  (2005) Guidance on Selecting Age Groups
        for  Monitoring  and Assessing  Childhood
        Exposures  to Environmental Contaminants.
        U.S.  Environmental   Protection  Agency,
        Washington, D.C., EPA/630/P-03/003F.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                         Page
                                                                                         9-11

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I
 1
Table 9-3. Per Capita Intake of Fruits and Ve
. „ ,, Percent
Age Group N „
0 r Consuming
Mean
SE
jetables (g/kg-day as consumed)
Percentiles
1st
5th
10th
25th
50th
75th
90th
95th
99th 100th
Fruits
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U
56.4
89.5
90.0
88.3
73.2

72.1
99.7
100.0
99.9
100.0

5.7
6.2
4.6
2.4
0.8

4.5
6.9
5.9
4.1
2.9

S. EPA analysis of 1994-96,
0.3
0.2
0.1
0.1
0.1
Veg
0.2
0.2
0.1
0.1
0.1

1998 CSFII
0.0
0.0
0.0
0.0
0.0
etables
0.0
0.0
0.0
0.1
0.0


0.0
0.0
0.0
0.0
0.0

0.0
0.7
0.8
0.6
0.4


0.0
0.0
0.0
0.0
0.0

0.0
1.5
1.4
1.0
0.7


0.0
0.5
0.2
0.1
0.0

0.0
3.2
2.8
1.8
1.4


1.5
4.7
3.2
1.3
0.1

2.7
5.6
4.7
3.2
2.4


9.6
9.4
7.0
3.3
1.1

7.4
9.3
7.7
5.3
3.8


17.1
14.6
11.4
6.4
2.4

12.2
13.9
11.7
7.8
5.5


21.3
18.5
14.4
8.8
3.5

14.8
17.1
14.7
9.9
6.9


32.2 73.8
26.4 44.0
22.3 45.5
14.3 25.0
6.9 12.8

25.3 56.8
26.5 58.2
23.4 50.9
17.4 53.7
11.4 29.5


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Table 9-4. Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed)
Age Group N
Mean
SE
Percentiles
p,
5th 10th
25th
50th
75th
90th
95th
99th
100th
Fruits
Birth to 1 year 830
1 to 2 years 1,878
3 to 5 years 3,957
6 to 12 years 1,846
13 to 19 vears 898
10.1
6.9
5.1
2.7
1.1
0.4
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.4 1.2
0.0 0.1
0.0 0.0
0.0 0.0
0.0 0.0
3.7
2.2
1.0
0.3
0.0
8.5
5.4
3.8
1.7
0.5
14.4
10.1
7.5
3.7
1.5
20.4
15.3
11.9
6.7
2.9
26.4
19.0
15.0
9.3
3.7
34.7
27.1
22.8
14.8
7.6
73.8
44.0
45.5
25.0
12.8
Vegetables
Birth to 1 year 1,062
1 to 2 years 2,090
3 to 5 years 4,389
6 to 12 years 2,087
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U
6.2
6.9
5.9
4.1
2.9

0.3
0.2
0.1
0.1
0.1

0.0
0.0
0.0
0.1
0.0

S. EPA analysis of 1994-96,
0.1 0.1
0.7 1.5
0.8 1.4
0.6 1.0
0.4 0.7

1998 CSFII.
2.0
3.2
2.8
1.8
1.4


4.9
5.6
4.7
3.2
2.4


9.4
9.3
7.7
5.3
3.8


13.4
13.9
11.7
7.8
5.5


16.1
17.1
14.7
9.9
6.9


26.4
26.5
23.4
17.4
11.4


56.8
58.2
50.9
53.7
29.5


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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed)
Age Group N

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Percent
_ . Mean SE
Consuming
Apples
34.6 2.32 0.13
44.8 1.79 0.09
44.6 1.64 0.05
38.2 0.83 0.05
22.5 0.20 0.02
Beets
0.4 0.01 0.01
0.7 0.01 0.00
0.8 0.01 0.00
0.8 0.01 0.00
0.7 0.00 0.00
Cabbage
1.0 0.01 0.00
8.0 0.06 0.01
8.9 0.07 0.01
9.5 0.06 0.01
9.0 0.04 0.01
Percent
_ . Mean SE
Consuming
Asparagus
0.21 0.01 0.00
0.77 0.02 0.01
0.54 0.01 0.00
0.66 0.01 0.00
0.56 0.00 0.00
Berries and Small Fruit
16.5 0.13 0.02
66.2 0.91 0.05
72.7 0.72 0.03
73.4 0.40 0.03
97.7 0.19 0.01
Carrots
12.3 0.17 0.03
46.8 0.41 0.02
46.2 0.34 0.02
44.4 0.22 0.01
40.3 0.11 0.01
Percent
_ . Mean SE
Consuming
Bananas
40.68 1.24 0.06
62.76 1.77 0.09
60.74 0.93 0.04
57.69 0.38 0.03
42.09 0.13 0.02
Broccoli
3.5 0.07 0.02
12.0 0.25 0.03
10.7 0.18 0.01
11.0 0.14 0.02
8.3 0.06 0.01
Citrus Fruits
2.5 0.07 0.02
15.5 0.47 0.05
18.2 0.50 0.03
16.0 0.26 0.02
12.3 0.11 0.02
Percent
_ . Mean SE
Consuming
Beans
21.6 0.43 0.04
46.8 0.76 0.04
43.0 0.52 0.02
38.8 0.32 0.02
55.4 0.15 0.02
Bulb Vegetables
33.4 0.07 0.01
93.3 0.30 0.01
95.8 0.27 0.01
97.3 0.21 0.01
12.3 0.11 0.02
Corn
46.0 0.48 0.03
96.5 1.13 0.05
98.7 1.24 0.03
98.9 0.87 0.03
95.7 0.43 0.02
                                                                                                                                               s
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group N

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1.222
Percent
_ . Mean SE
Consuming
Cucumbers
1.7 0.00 0.00
20.5 0.11 0.01
29.3 0.16 0.02
32.6 0.14 0.02
41.3 0.11 0.03
Legumes
51.7 1.21 0.06
96.9 1.30 0.08
98.3 0.85 0.06
98.1 0.48 0.03
94.9 0.27 0.02
Peaches
24.4 0.85 0.08
50.7 0.47 0.04
55.4 0.26 0.02
54.7 0.14 0.02
39.1 0.06 0.01
Percent
_ . Mean SE
Consuming
Cucurbits
14.0 0.45 0.04
31.3 0.72 0.06
38.7 0.83 0.07
39.9 0.54 0.06
46.7 0.32 0.08
Lettuce
1.1 0.00 0.00
23.3 0.14 0.01
33.4 0.21 0.01
41.7 0.22 0.01
55.2 0.22 0.02
Pears
15.9 0.73 0.07
17.2 0.40 0.04
16.6 0.26 0.03
17.5 0.14 0.01
5.9 0.03 0.01
Percent
_ . Mean SE
Consuming
Fruiting Vegetables
25.50 0.32 0.04
92.14 1.56 0.06
95.38 1.46 0.03
95.87 1.05 0.03
96.08 0.79 0.03
Okra
0.2 0.00 0.00
1.3 0.01 0.00
0.8 0.01 0.00
1.3 0.01 0.00
0.8 0.00 0.00
Peas
29.5 0.47 0.04
28.3 0.34 0.03
20.5 0.21 0.02
17.2 0.12 0.01
14.0 0.07 0.01
Percent
_ . Mean SE
Consuming
Leafy Vegetables
44.2 0.29 0.05
82.1 0.71 0.04
86.9 0.67 0.02
89.5 0.55 0.03
90.3 0.43 0.02
Onions
32.8 0.07 0.01
93.0 0.29 0.01
95.6 0.26 0.01
96.8 0.20 0.01
97.3 0.18 0.01
Peppers
15.6 0.01 0.00
77.5 0.05 0.01
84.6 0.05 0.00
85.1 0.05 0.00
84.8 0.04 0.00
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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group N

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year !=486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1.222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
Percent ...
_ . Mean SE
Consuming
Pome Fruit
40.0 3.04 0.17
52.0 2.19 0.10
51.7 1.90 0.06
47.9 0.97 0.06
26.5 0.23 0.02
Strawberries
6.8 0.02 0.00
33.5 0.19 0.03
37.1 0.14 0.01
37.3 0.10 0.01
26.8 0.05 0.01
White Potatoes
39.9 0.64 0.07
91.2 1.95 0.08
95.1 1.75 0.06
93.9 1.21 0.06
92.6 0.93 0.05
Percent ...
_ . Mean SE
Consuming
Pumpkins
0.3 0.00 0.00
0.7 0.01 0.00
0.9 0.01 0.00
1.8 0.01 0.00
1.3 0.01 0.00
Stone Fruit
29.20 1.15 0.10
53.62 0.60 0.04
57.45 0.38 0.02
56.83 0.23 0.02
41.08 0.09 0.01


Percent ...
_ . Mean SE
Consuming
Root Tuber Vegetables
61.7 2.60 0.15
99.6 3.38 0.09
100.0 2.96 0.07
100.0 2.09 0.07
99.9 1.36 0.06
Tomatoes
21.5 0.30 0.03
80.7 1.50 0.05
85.7 1.40 0.03
86.9 1.00 0.03
90.2 0.74 0.03


Percent ...
_ . Mean SE
Consuming
Stalk, Stem Vegetables
1.9 0.01 0.00
13.2 0.06 0.01
10.9 0.04 0.00
10.7 0.03 0.01
16.6 0.03 0.01
Tropical Fruits
42.2 1.31 0.07
70.1 1.97 0.10
69.7 1.10 0.04
67.0 0.50 0.04
54.5 0.19 0.02


SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and
vegetables with higher percentages consuming.
Source: Based on unpublished U.S. EPA analysis of 1994-96. 1998 CSFII.
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed)
Age Group

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
N Mean SE
Apples
496 6.71 0.31
947 4.00 0.15
1,978 3.68 0.08
792 2.17 0.12
271 0.90 0.06
Beets
6 1.42 0.87
13 0.98 0.32
36 0.90 0.20
16 0.66 0.33
9 0.20 0.12
Cabbage
15 0.61 0.41
160 0.73 0.11
369 0.78 0.07
190 0.63 0.11
106 0.40 0.06
N Mean SE
Asparagus
3 2.59 1.16
19 1.99 0.54
23 1.37 0.32
13 1.77 0.43
4 0.56 0.08
Berries and Small Fruits
229 0.81 0.07
1,396 1.38 0.06
3,166 0.99 0.04
1,523 0.54 0.04
679 0.27 0.03
Carrots
179 1.39 0.20
999 0.87 0.05
2,048 0.74 0.03
904 0.50 0.03
482 0.27 0.02
N Mean SE
Bananas
605 3.04 0.12
1,328 2.82 0.12
2,746 1.54 0.06
1,214 0.66 0.05
511 0.30 0.04
Broccoli
49 2.09 0.33
242 2.11 0.16
475 1.67 0.09
213 1.29 0.16
102 0.69 0.07
Citrus Fruits
37 2.79 0.53
336 3.06 0.20
751 2.75 0.15
324 1.60 0.12
157 0.90 0.15
N Mean SE
Beans
313 2.00 0.16
996 1.63 0.08
1,909 1.22 0.04
833 0.82 0.05
472 0.49 0.03
Bulb Vegetables
489 0.22 0.02
1,957 0.32 0.01
4,207 0.28 0.01
2,040 0.22 0.01
1,194 0.20 0.01
Corn
671 1.05 0.07
2,027 1.17 0.05
4,334 1.26 0.03
2,064 0.88 0.03
1.176 0.45 0.01
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years
N Mean SE
Cucumbers
25 0.28 0.11
439 0.52 0.05
1,266 0.56 0.05
667 0.43 0.06
500 0.26 0.06
Legumes
754 2.34 0.11
2,037 1.34 0.08
4,308 0.86 0.06
2,045 0.49 0.03
1.168 0.29 0.02
Peaches
344 3.47 0.28
1,067 0.93 0.08
2,461 0.48 0.03
1,150 0.26 0.03
480 0.15 0.03
N Mean SE
Cucurbits
213 3.19 0.29
682 2.29 0.17
1,694 2.15 0.17
833 1.34 0.15
563 0.69 0.16
Lettuce
15 0.17 0.02
481 0.58 0.04
1,415 0.62 0.03
858 0.53 0.02
669 0.40 0.03
Pears
217 4.55 0.28
354 2.33 0.16
711 1.59 0.12
382 0.81 0.07
72 0.45 0.09
N Mean SE
Fruiting Vegetables
371 1.24 0.11
1,927 1.70 0.06
4,180 1.53 0.03
2,014 1.10 0.03
1,176 0.82 0.03
Okra
4 1.50 0.54
29 0.64 0.19
34 1.16 0.32
21 0.62 0.15
12 0.43 0.13
Peas
417 1.60 0.09
609 1.21 0.06
888 1.02 0.07
346 0.68 0.06
168 0.48 0.06
N Mean SE
Leafv Vegetables
639 0.65 0.11
1,729 0.87 0.05
3,815 0.77 0.03
1,860 0.62 0.03
1,101 0.47 0.02
Onions
481 0.22 0.02
1,948 0.31 0.01
4,200 0.27 0.01
2,030 0.21 0.01
1.190 0.19 0.01
Peppers
224 0.05 0.01
1,627 0.06 0.01
3,706 0.06 0.00
1,784 0.05 0.01
1.041 0.05 0.00
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Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued)
Age Group

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years

Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years.
13 to 19 years
N Mean SE
Pome Fruit
572 7.60 0.34
1,097 4.21 0.13
2,291 3.68 0.08
1,012 2.03 0.10
320 0.87 0.06
Strawberries
96 0.26 0.06
729 0.57 0.08
1,710 0.38 0.03
783 0.28 0.02
326 0.18 0.03
White Potatoes
577 1.60 0.15
1,918 2.14 0.09
4,147 1.84 0.06
1,963 1.29 0.06
1.131 1.01 0.05
N Mean SE
Pumpkins
3 1.06 0.71
15 1.08 0.51
36 0.56 0.10
37 0.52 0.11
14 0.42 0.16
Stone Fruit
418 3.95 0.25
1,130 1.13 0.08
2,556 0.66 0.03
1,194 0.41 0.03
508 0.21 0.03


N Mean SE
Root Tuber Vegetables
916 4.21 0.19
2,087 3.40 0.09
4,388 2.96 0.07
2,089 2.09 0.07
1,221 1.36 0.06
Tomatoes
315 1.42 0.13
1,684 1.86 0.06
3,764 1.63 0.03
1,832 1.15 0.03
1,098 0.82 0.03


N Mean SE
Stalk, Stem Vegetables
24 0.56 0.22
272 0.48 0.05
502 0.38 0.03
218 0.32 0.04
190 0.20 0.03
Tropical Fruits
630 3.09 0.12
1,476 2.81 0.12
3,106 1.57 0.05
1,407 0.75 0.05
652 0.35 0.04


SE = Standard error.
Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and
vegetables with higher percentages consuming.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
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Age Group

Sample
Size
Table
Total
9-7. Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day)
White Potatoes
DarkG
Total
Vegeta
Fried
Lettuce,
reen „ lettuce-
, , Yellow lomatoes , ,
bles ., , , based
Vegetables , ,
salads
Green
beans
Corn,
green
peas, lima
beans
Other
vegetables
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
57
79
87
83
91
97
103
97
88
9
26
32
29
34
37
44
38
31
1
11
17
14
17
19
22
20
16
2
5
4
5
5
6
4
5
4
19
9
5
7
5
5
6
5
7
r
7
11
9
13
11
12
12
10
a,b
1
2
1
2
3
3
3
2
6
8
7
7
5
5
6
5
6
5
9
10
9
11
12
12
11
10
16
16
17
17
16
18
17
17
17
Males
6 to 9 years
6 to 1 1 yers
12 to 19 years
787
1,031
737
110
115
176
47
50
85
26
27
44
4
5
6
5
5
6
16
16
28
5
5
12
5
5
3"
11
11
10
16
18
25
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
110
116
145
42
46
61
22
25
31
5
5
9
4
4
4
14
15
18
6
7
12
5
5
4
13
12
8
21
22
28
Males and Females
9 years and under
19 years and under
9,309
11,287
97
125
37
53
19
27
4
6
6
6
a Estimate is not statistically reliable due to small samples size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption amounts shown are representative of the first day of each participant
12
17
's survey response.
3
7

6
5

11
10

18
22

Source: USDA, 1999.
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Table 9-8. Percentage of Individuals Consuming Vegetables, by Sex and Age (%)
Age Group
Sample .
_. Total
Size
White Potatoes
Total
Fried
Dark
Green
Vegetabl
Deep
Yellow
es Vegetables
Tomatoes
Lettuce,
lettuce-
based
salads
Green
beans
Corn,
green
peas, lima
beans
Other
vegetables
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
47.2
73.3
78.4
75.9
80.5
80.7
83.0
81.4
75.4
12.3
40.4
46.7
43.6
46.7
47.3
50.7
48.2
42.3
4.3
25.2
34.5
29.9
34.7
34.8
38.3
35.9
30.1
2.3
6.4
7.6
7.0
7.0
7.2
4.6
6.3
6.1
20.5
13.3
10.5
11.8
10.7
12.0
13.3
12.0
13.0
1.8
18.0
30.8
24.6
34.1
33.0
36.5
34.5
27.2
0.2"
3.9
7.5
5.7
8.3
10.0
13.4
10.6
7.6
7.8
13.7
11.5
12.6
10.1
9.0
10.4
9.9
10.5
8.5
17.6
15.0
16.2
14.6
16.4
16.1
15.7
15.0
14.8
19.4
22.3
20.9
24.7
26.5
28.8
26.7
23.3
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
78.8
79.3
78.2
47.9
48.7
49.5
38.0
38.4
38.6
6.3
6.1
3.6
12.5
12.4
8.0
38.2
38.7
43.0
13.1
13.9
23.8
7.8
6.7
3.5
15.0
13.8
7.4
29.7
30.8
33.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
80.5
81.7
79.5
48.2
50.8
46.4
36.3
38.9
34.6
5.9
5.4
7.0
11.9
11.4
10.6
33.8
33.5
35.3
15.8
17.1
25.1
8.4
7.8
4.4
15.9
15.1
7.4
26.6
29.2
34.5
Males and Females
9 years and under
19 years and under
9,309
77.1
11,287 78.3
44.6
46.8
32.9
35.3
6.1
5.6
12.7
11.2
30.7
34.6
10.3
16.6
9.6
7.0
15.2
11.9
25.2
29.4
a Estimate is not statistically reliable due to small samples size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
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a
Table 9-9. Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day)
Citrus Fruits and
Juices
Age Group

Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
Sample
Size

1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
Total
Total

131
267
276
271
256
243
218
239
237

4
47
65
56
61
62
55
59
52
Juices

4
42
56
49
51
52
44
49
44
Dried
fruits
Males and
_a,b
2
2
2
1
1
_a,b
1
1
Total
Females
126
216
207
212
191
177
160
176
182
Other fruits, mixtures, and juices
Apples

14
22
27
24
27
31
31
30
26
Bananas

10
23
20
22
18
17
14
16
17
Melons
and
berries

I"
8
10
9
13
14
13
13
10
Other
fruits and
mixtures
(mainly
fruit)

39
29
20
24
24
22
24
23
26
Non-
citrus
juices and
nectars

61
134
130
132
110
92
78
93
103
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
194
183
174
58
67
102
51
60
94
_a,b
_a,b
1"
133
113
70
32
28
13
11
11
8
21
16
11"
20
19
10
50
40
29
Females
6 to 9 years
6 to 1 1 years
12 to 19 years

9 years and under
19 years and under
704
969
732

9,309
11,287
180
169
157

217
191
63
64
72

55
70
54
54
67

47
62
1"
_a,b
_a,b
Males and
1
1
113
103
83
Females
159
118
* Estimate is not statistically reliable due to small samples size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption amounts shown are representative of the first day of each participant
Source: USDA, 1999






23
21
13

27
21
10
8
5

15
11
10
8
15

12
12
25
23
14

24
19
46
42
35

81
56
s survey response





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Table 9-10.
Age Group

Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
Percentage of Individuals Consuming,
Citrus Fruits and
Juices
Sample
Size

1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
Total

59.7
81.0
76.6
78.8
74.5
72.6
67.6
71.6
72.6
Total

3.6
23.6
30.6
27.2
27.9
28.0
26.9
27.6
24.6
Juices

2.7
19.0
23.4
21.3
21.4
21.8
19.5
20.9
18.8
Dried
fruits
Males
0.4"
5.9
5.3
5.6
4.1
3.0
1.3"
2.8
3.5
Total
and Females
59.0
73.0
64.7
68.8
64.2
62.1
56.9
61.0
63.5
Fruits by Sex and Age (%)
Other fruits, mixtures, and juices
Apples

15.7
23.4
24.0
23.7
22.4
23.7
21.9
22.7
22.2
Bananas

13.3
25.1
20.2
22.6
17.5
15.7
12.6
15.3
17.6
Melons
and
berries

1.8
6.9
8.5
7.7
7.8
7.6
7.4
7.6
6.9
Other
fruits and
mixtures
(mainly
fruit)

29.9
26.5
19.4
22.9
20.1
20.0
19.0
19.7
22.0
Non-
citrus
juices and
nectars

33.0
43.2
37.0
40.0
33.3
30.8
24.5
29.5
33.5
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
59.0
56.5
44.5
24.8
25.2
24.7
20.5
21.6
21.7
0.8"
1.1"
1.0"
49.1
44.2
27.1
20.3
18.2
8.2
8.7
8.0
6.0
7.3
6.6
4.1
16.8
15.4
7.1
15.5
12.7
8.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years

9 years and under
19 years and under
704
969
732

9,309
11,287
64.9
62.1
45.6

68.3
57.8
27.9
27.7
22.4

25.2
24.8
22.3
21.5
18.1

19.8
20.1
1.5"
1.1"
1.1"
Males
2.5
1.8
50.4
47.2
30.2
and Females
58.0
44.4
17.3
16.2
8.2

20.9
15.2
8.8
7.3
4.4

14.0
9.7
7.4
7.4
6.0

7.1
6.2
20.4
19.0
11.3

20.6
15.5
17.3
14.9
9.7

26.7
17.9
* Estimate is not statistically reliable due to small samples size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
                                                                                                                                                       1    f
a^     f

I    £
                                                                                                                                                        I
I
                                                                                                                                                               ft
I
1=
    ft

-------
 ft
I

 1
1=
I
Table 9-11. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (g
Food category

2 to 5 years
6 to 1 1 years
Male and Female Male and Female
(N = 2,109) (N= 1,432)
PC
Mean.
SEM PC
Mean
SEM
PC
rams)



12 to 19 years
Male
(N = 696)
Mean
SEM
Female
(N = 702)
PC
Mean
SEM
Raw Vegetables
Carrots
Cucumbers
Lettuce
Onions
Tomatoes
10.4
6.4
34.0
3.9
14.8
27
32
17
9
31
2 17.8
4 6.6
1 40.8
2 4.5
2 14.0
32
39
26
17
42
2
6
1
2
4
9.2
6.1
56.0
11.1
25.7
35
71a
32
28
49
6
22"
3
4
5
11.9
6.8
52.3
7.9
23.9
32
48
34
23
44
4
11
2
4
3
Cooked Vegetables
Beans (string) 16.8
Broccoli 7.2
Carrots 6.0
Corn 18.9
Peas 8.4
Potatoes (French-fried) 32.7
Potatoes (home-fried and hash-browned) 9.3
Potatoes (baked) 7.6
Potatoes (boiled) 4.8
Potatoes (mashed) 14.8
50
61
48
68
48
52
85
70
81
118
2 12.1
3 5.6
4 3.8
3 22.2
3 6.8
1 33.7
5 10.1
4 8.2
9 2.7
6 13.3
71
102
46
79
72
67
93
95
103"
162
6
16
5
4
9
2
6
6
IT
12
8.3
3.9
2.8
12.8
3.6
41.7
10.1
8.6
2.0
14.6
85
127"
81"
125
115"
97
145
152
250"
245
9
17"
16*
9
15"
3
13
15
40s
16
7.6
5.7
2.1
12.3
2.4
38.1
6.1
8.8
3.2
11.9
78
1091
75"
100
93s
81
138
115
144"
170
5
14"
IT
6
17"
4
13
10
16"
17
Fruits
Apples (raw^
Apples (cooked and applesauce)
Apple juice
Bananas (raw)
Oranges (raw)
Orange juice
26.8
10.1
26.3
25.0
11.1
34.4
106
118
207
95
103
190
2 21.9
5 9.0
5 12.2
2 16.5
5 10.5
4 30.9
123
130
223
105
114
224
1 Indicates a statistic that is potentially unreliable because of small sample size
PC = Percent consuming at least once in 2 days.
SEM = Standard error of the mean.
Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
3
7
10
3
5
6
or large
11.7
2.3
7.8
10.3
4.3
30.8
149
153"
346
122
187"
354
9
19s
22
6
38"
16
12.4
2.6
8.5
8.4
5.4
29.5
129
200"
360
119
109"
305
5
47>
44
5
8"
11
coefficient of variation
                                                                                                                                                        s
                                                                                                                                                        I
                                                                                                                                                        ?
                                                                                                                                                              1
                                                                                                                                                        Si
                                                                                                                                                        a
                                                                                                                                                        A,



                                                                                                                                                       I
                                                                                                                                                        I
                                                                                                                                                               I

-------
Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9-12.

Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition Program
Source: Devaney et al., 2004.
Characteristics of the FITS Sample Population
Sample Size

1,549
1,473

862
483
679
374
308
316

367
2,641
14

2,417
225
380

1,389
1,014
577
42

48
48
221
359
723
588
311
272
452

821
2,196
5
3,022
for Women, Infants, and Children.


Percentage of Sample

51.3
48.7

28.5
16.0
22.5
12.4
10.2
10.4

12.1
87.4
0.5

80.0
7.4
12.6

46.0
33.6
19.1
1.3

1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9

27.2
72.6
0.2
100.0


Child-Specific Exposure Factors Handbook
September 2008	
Page
 9-25

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-13. Percentage of Infants and Toddlers Consuming Different Types of Vegetables
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
4 to 6 7 to 8
months months
39.9 66.5
35.7 54.5
5.2 17.4
0.5 1.6
9 to 11
months
72.6
34.4
45.9
5.5
12 to 14
months
76.5
12.7
66.3
7.9
15 to 18
months
79.2
3.0
72.9
14.3
19 to 24
months
81.6
1.6
75.6
18.6
Types of Vegetables'
Dark Green Vegetables'"
Deep Yellow Vegetables0
White Potatoes
French Fries and Other Fried Potatoes
Other Starchy Vegetables'1
Other Vegetables
0.1 2.9
26.5 39.3
3.6 12.4
0.7 2.9
6.5 10.9
11.2 25.9
4.2
29.0
24.1
8.6
16.9
35.1
5.0
24.0
33.2
12.9
17.3
39.1
a Totals include commercial baby food, cooked vegetables, and raw vegetables.
b Reported dark green vegetables include broccoli, spinach and other greens, and romaine lettuce.
0 Reported deep yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
d Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried),
Source: Fox et al., 2004.



10.4
13.6
42.0
19.8
20.8
45.6
cassava,

7.8
13.4
40.6
25.5
24.2
43.3
and rutabaga.

Page
9-26
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables


^^f&tC

Table 9-14. Top Five Vegetables Consumed by Infants and Toddlers
Top Vegetables by Age Group" Percentage Consuming at Least Once in a Day
4 to 6 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Peas
9.6
9.1
8.1
7.2
5.0
7 to 8 months
Baby Food Carrots
Baby Food Sweet Potatoes
Baby Food Squash
Baby Food Green Beans
Baby Food Mixed/Garden Vegetables
14.2
12.9
12.9
11.2
10.1
9 to 1 1 months
Cooked Green Beans
Mashed/Whipped Potatoes
French Fries/Other Fried Potatoes
Baby Food Mixed/Garden Vegetables
Cooked Carrots
9.7
9.0
8.6
8.4
8.0
12 to 14 months
Cooked Green Beans
French Fries/Other Fried Potatoes
Cooked Carrots
Mashed/Whipped Potatoes
Cooked Peas
18.2
12.9
11.5
10.3
8.4
15 to 18 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Peas
Cooked Tomatoes/Tomato Sauce
Mashed/Whipped Potatoes
19.8
16.7
13.9
13.7
12.4
19 to 24 months
French Fries/Other Fried Potatoes
Cooked Green Beans
Cooked Corn
Cooked Peas
Cooked Tomatoes/Tomato Sauce
25.5
16.8
15.2
11.4
9.4
" Baby food vegetables include single vegetables (majority of vegetables reported) as well as mixtures with the named
vegetables the predominant vegetable, e.g., broccoli and cauliflower or broccoli and carrots.
Source: Fox et al., 2004.

Child-Specific Exposure Factors Handbook
September 2008	
Page
 9-27

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-15. Percentage of Infants and Toddlers Consuming Different Types of Fruits
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food

Any Fruit
Baby Food Fruit
Non-baby Food Fruit
4 to 6 months

41.9
39.1
5.3
7 to 8 months

75.5
67.9
14.3
9 to 11
months
75.8
44.8
44.2
12 to 14
months
77.2
16.2
67.1
15 to 18
months
71.8
4.2
69.4
19 to 24
months
67.3
1.8
66.8
Types of Non-baby Food Fruit
Canned Fruit
Packed in Syrup
Packed in Juice or Water
Unknown Pack
Fresh Fruit
Dried Fruit
1.4
0.7
0.7
0.0
4.4
0.0
5.8
0.7
4.5
0.7
9.5
0.4
21.6
8.1
13.5
1.5
29.5
2.1
31.9
14.9
18.5
1.2
52.1
3.5
25.1
12.7
11.3
3.1
55.0
7.1
20.2
8.1
11.4
1.2
54.6
9.4
Types of Fruit*
Apples
Bananas
Berries
Citrus Fruits
Melons
a Totals include all baby
Source: Fox et al., 2004.
18.6
16.0
0.1
0.2
0.6
food and non-baby

33.1
30.6
0.6
0.4
1.0
food fruits.

31.6
34.5
5.3
1.6
4.4


27.5
37.8
6.6
4.9
7.3


19.8
32.4
11.3
7.3
7.2


22.4
30.0
7.7
5.1
9.6


Page
9-28
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables


jflSf
W¥
*jy!j£j\^

Table 9-16. Top Five Fruits Consumed by Infants and Toddlers
Top Fruits by Age Group* Percentage Consuming at Least Once in a Day
4 to 6 months
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
17.5
13.0
7.5
7.4
0.3
7 to 8 months
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Baby Food Peaches
Fresh Banana
29.0
25.2
18.2
13.1
6.6
9 to 1 1 months
Fresh Banana
Baby Food Applesauce
Baby Food Bananas
Baby Food Pears
Canned Applesauce
19.0
17.7
16.8
12.4
11.1
12 to 14 months
Fresh Banana
Canned Applesauce
Fresh Grapes
Fresh Apple
Canned Peaches
Canned Fruit Cocktail
33.0
15.2
9.0
8.8
7.2
7.2
15 to 18 Months
Fresh Banana
Fresh Grapes
Fresh Apple
Fresh Strawberries
Canned peaches
30.5
13.2
11.2
10.6
8.9
19 to 24 months
Fresh Banana
Fresh Apple
Fresh Grapes
Raisins
Fresh Strawberries
29.6
15.0
11.2
9.0
7.6
* Baby food fruits include single fruits (majority of fruits reported) as well as mixtures with the named fruit as the
predominant fruit, e.g., pears and raspberries or prunes with pears. Baby food fruits with tapioca and other baby food
dessert fruits were counted as desserts.
Source: Fox et al., 2004.

Child-Specific Exposure Factors Handbook
September 2008

Pagt
9-2<,

-------
                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-17. Characteristics of WIC Participants and Non-participants* (Percentages)
Infants 4 to 6 months

Gender
Male
Female
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or
Latino
Child's Race
White
Black
Other
Child In Day Care
Yes
No
Age of Mother
14 to 19
20 to 24
25 to 29
30 to 34
35 or Older
Missing
Mother's Education
11 ""Grade or Less
Completed High School
Some Postsecondary
Completed College
Missing
Parent's Marital Status
Married
Not Married
Missing
WIC
Participant

55
45

20
80


63
15
22

39
61

18
33
29
9
9
2


23
35
33
7
2

49
50
1
Non-participant

54
46
**
11
89

**
84
4
11

38
62
**
1
13
29
33
23
2

**
2
19
26
53
1
**
93
7
1
Infants 7 to 1 1 months
WIC
Participant

55
45

24
76


63
17
20

34
66

13
38
23
15
11


15
42
32
9
2

57
42
1
Non-participant

51
49
**
8
92

**
86
5
9
**
46
54
**
1
11
30
36
21

**
2
20
27
51
0
**
93
7
0
Toddlers 12 to 24 months
WIC
Participant

57
43

22
78


67
13
20

43
57

9
33
29
18
11
o


17
42
31
9
1

58
41
1
Non-participant

52
48
**
10
89

**
84
5
11
*
53
47
**
1
14
26
34
26

**
3
19
28
48
2
**
88
11
1
Page
9-30
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Chapter 9 - Intake of Fruits and Vegetables






ri

gt
w

Table 9-17. Characteristics of WIC Participants
Infants 4 to 6 months
WIC
Participant Non-participant
Mother or Female Guardian Works
Yes 46 51
No 53 48
Missing 1 1
Urbanicity **
Urban 34 55
Suburban 36 31
Rural 28 13
Missing 2 1
Sample Size 265 597
(Unweighted)
and Non-participants"
(Percentaj
Infants 7 to 1 1 months
WIC

Participant Non-participant

45
54
1

37
31
30
2
351
**
60
40
0
**
50
34
15
1
808
;es) (continued)

Toddlers 12 to 24 months
WIC

Participant Non-participant
*

55 61
45 38
0

**
35 48
35 35
28 16
2 2
205 791
a X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants for
each of the three age groups. * P<0.05; ** P>0.01; non-participants significantly different from WIC participants on the variable.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.




Child-Specific Exposure Factors Handbook
September 2008	
Page
 9-31

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-18. Food Choices for Infants and Toddlers by WIC
Infants 4 to 6 months


WIC
Participant
Non-
participant
Infants 7 to
WIC
Participant
Participation Status
1 1 months
Non-
participant
Toddlers 12 to 24 months
WIC
Participant
Non-
participant
Vegetables
Any Vegetable
Baby Food Vegetables
Cooked Vegetables
Raw Vegetables
Dark Green Vegetables
Deep Yellow Vegetables
Other Starchy Vegetables
Potatoes
40.2
32.9
8.0
1.4
0.4
23.2
6.5
6.0
39.8
37.0
3.9*
0.1**
0.0
28.1
6.4
2.4*
68.2
38.2
33.8
3.6
2.9
30.1
12.9
20.7
70.7
45.0
33.8
4.1
4.0
34.8
15.2
18.2
77.5
4.8
73.1
11.8
6.3
12.5
21.1
43.1
80.2
4.7
72.3
15.4
8.4
16.9
21.5
38.3
Fruits
Any Fruit
Baby Food Fruits
Non-Baby Food Fruit
Fresh Fruit
Canned Fruit
Sample Size (unweighted)
47.8
43.8
8.1
5.4
3.4
265
39.2*
36.9
4.0
3.8
0.5**
597
64.7
48.4
22.9
14.3
10.3
351
81.0**
57.4*
35.9**
24.3**
17.3**
808
58.5
3.8
56.4
43.6
22.3
205
74.6**
6.5
70.9**
57.0**
25.3
791
* = P<0.05 non-participants significantly different from WIC participants.
** = P<0.01 non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al. 2004.






Page
9-32
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
                        Table 9-19.  Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming
                                     Different Types of Fruits and Vegetables on A Given Day
                                              Age 4 to 5 months
Age 6 to 11 months
Age 12 to 24 months
Hispanic
(n=84)
Non-Hispanic
(n=538)
Hispanic
(n=163)
Non-Hispanic
(n=l,228)
Hispanic
(n=124)
Non-Hispanic
(n=871)
                                                           Fruits
Any Fruit or 100%
Any Fruit"
100% Fruit Juice
Fruit Juice


45.0
39.4
19.3
35
28
15
9
8
3
86.2
68.1
57.8
86.8
76.0
47.7
84.6
67.6
64.1
87.2
71.5
58.9
   Fruit Preparation
Baby Food Fruit
Non-Baby Food Fruit
Canned Fruit
Fresh Fruit
32.6
9.1T
2.3T
9.1*t
28.4
1.3T
-
-
42.9*
35.8
8.8
30.0**
58.1
27.4
13.7
17.7
5.6T
64.2
12.1**
59.3
6.3
68.0
26.2
53.1
                                                         Vegetables
   Any Vegetable or 100% Vegetable            30.0           27.3          66.2          70.3           76.0          80.5
   Juiceb
   Type of Preparation                        25.7           25.4          34.4*          47.6           4. It          4.9
     Baby Food Vegetables                     4.2t          2.4t         33.2          29.4           71.4          72.9
     Cooked Vegetables                       2.3J           -            8-3T           2.6           25.0          13.1
     Raw Vegetables
   Types of Vegetables'1                        -             -            3.3t           3.1          11.4t          7.5
     Dark Green Vegetables'                   21.0           18.2          32.2          25.9           20.0          15.4
     Deep Yellow Vegetables'1
     Starchy Vegetable:                       1.4t          2.3t         20.7          17.4           43.5          39.0
      White Potatoes                          -             -            5.?t           5.3           23.4          20.3
      French Fries/Fried Potatoes                -             -           14.4t          10.7           19.8          17.7
      Baked/Mashed                         5.0t           4.0           6.7**         15.1           16.6          22.2
      Other Starchy Vegetables'                8. It           8.0          28.5          29.0           42.0          43.4
     Other Non-starchy Vegetables1
   *         Total includes all baby food and non-baby food fruits and excludes 100% fruit juices and juice drinks.
   b         Total includes commercial baby food, cooked vegetables, raw vegetables, and 100% vegetable juices.
   '         Reported dark green vegetables include broccoli, spinach, romaine lettuce and other greens such as kale.
   d         Reported yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash.
   '         Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava, and
             rutabaga.  Corn is also shown as a subcategory of other starchy vegetables.
   f         Reported non-starchy vegetables include asparagus, cauliflower, cabbage, onions, green beans, mixed vegetables, peppers, and
             tomatoes.
             = Less than 1 percent of the group consumed this food on a given day.
   *         = Significantly different from non-Hispanic at the P<0.05.
   **        = Significantly different from non-Hispanic at the P>0.01.
   t         = Statistic is potentially unreliable because of a high coefficient of variation.

   Source:    Mennella et al., 2006.
Child-Specific Exposure Factors Handbook
September 2008	
                                            Page
                                             9-33

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-20. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants
and Toddlers Per Age Group *
Ethnicity

Hispanic
Non-Hispanic
Top Fruits By Age Group
4 to 5 months
6 to 1 1 months
12 to 24 months
Bananas (16.3%)
Apples (14.7%)
Peaches (10.9%)
Melons (3.5%)
Pears (2.5%)
Bananas (35.9%)
Apples (29.7%)
Pears (15.2%)
Peaches (11. 7%)
Melons (4.7%)
Bananas (41.5%)
Apples (25.7%)
Berries (8.5%)
Melons (7.6%)
Pears (7.3%)
Apples (12.5%)
Bananas (10.0%)
Pears (5.9%)
Peaches (5.8%)
Prunes (1.6%)
Apples (32.9%)
Bananas (31. 5%)
Pears (17.5%)
Peaches (13.9%)
Apricots (3.7%)
Bananas (30.9%)
Apples (22.0%)
Grapes (12.3%)
Peaches (9.6%)
Berries (8.7%)
Top Vegetables By Age Group
4 to 5 months
6 to 1 1 months
12 to 24 months
Carrots (9.9%)
Sweet Potatoes (6.8%)
Green Beans (5. 8%)
Peas (5.0%)
Squash (4.3%)
Potatoes (20.7%)
Carrots (19.0%)
Mixed Vegetables (11.1%)
Green Beans (11.0%)
Sweet Potatoes (8.7%)
Potatoes (43.5%)
Tomatoes (23.1%)
Carrots (18.6%)
Onions (11. 8%)
Corn (10.2%)
Sweet Potatoes (7. 5%)
Carrots (6.6%)
Green Beans (5.9%)
Squash (5.4%)
Peas (3.8%)
Carrots (17.5%)
Potatoes (16.4%)
Green Beans (15.9%)
Squash (11. 8%)
Sweet Potatoes (11. 4%)
Potatoes (39.0%)
Green Beans (19.6%)
Peas (12.8%)
Carrots (12.3%)
Tomatoes (11. 9%)
a Percentage consuming at least one in a day is in parentheses.
Source: Mennella, et al., 2006.


Page
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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9-21. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study


Food group



JVCICICIILC

4 to 5 months

(N=624)

6 to 8 months

(N=708)
Mean± SEM
9 to 1 1 months

(N=687)

Fruits and Juices
All fruits
Baby food fruit
Baby food peaches
Baby food pears
Baby food bananas
Baby food applesauce
Canned fruit
Fresh fruit
100% juice
Apple/apple blends
Grape
Pear
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
fluid ounce
fluid ounce
fluid ounce
fluid ounce
3.6±0.19
3.3±0.16
3.6±0.37
3.5±0.46
3.4±0.23
3.7±0.29
-
-
2.5±0.17
2.7±0.22
-
-
4.7±0.11
4.6±0.11
4.4±0.26
4.5±0.21
5.0±0.21
4.6±0.17
4.5±0.59
5.3±0.52
2.8±0.11
2.9±0.13
2.6±0.19
2.6±0.29
5.8±0.17
5.6±0.17
5.3±0.36
6.0±0.40
5.9±0.35
5.6±0.25
4.8±0.25
6.4±0.37
3.1±0.09
3.2±0.11
3.1±0.21
3.1±0.28
Vegetables
All vegetables
Baby food vegetables
Baby food green beans
Baby food squash
Baby food sweet
Baby food carrots
Cooked vegetables, excluding french fries
Deep yellow vegetables
Mashed potatoes
Green beans
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
tablespoon
3.8±0.20
4.0±0.20
3.5±0.33
4.3±0.47
4.3±0.31
3.5±0.33
-
-
-
-
5.8±0.16
5.9±0.16
5.1±0.28
5.6±0.30
6.1±0.34
5.6±0.27
4.2±0.47
3.2±0.59
4.1±0.67
3.2±0.62
5.6±0.20
6.6±0.21
6.1±0.50
6.9±0.41
7.2±0.69
6.7±0.48
3.8±0.31
3.2±0.39
2.8±0.37
5.0±0.61
= Cell size was too small to generate a reliable estimate.
N = Number of respondents.
SEM = Standard error.
Source: Fox et al., 2006.












Child-Specific Exposure Factors Handbook
September 2008	
Page
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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-22. Average Portion
Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
Toddlers from the 2002


Food group



unit

7eeding Infants and Toddlers Study
12 to 14 months

(N=371)

15 to 18 months

(N=312)
Mean± SEM
19 to 24 months

(N=320)

Fruits and Juices
All fruits
Canned fruit
Fresh fruit
Fresh apple

Fresh banana

Fresh grapes
100% juice
Orange/orange blends
Apple/apple blends
Grape
cup
cup
cup
cup, slice
1 medium
cup, slice
1 medium
cup
fluid ounce
fluid ounce
fluid ounce
fluid ounce
0.4±0.02
0.3±0.02
0.4±0.02
0.4±0.05
0.3±0.04
0.4+0.02
0.6±0.03
0.2±0.01
3.7±0.15
3.3+0.38
3.6+0.21
3.6+0.38
0.5+0.03
0.4+0.03
0.5+0.03
0.6+0.07
0.5+0.06
0.5+0.03
0.7+0.03
0.3+0.03
5.0+0.20
4.5+0.33
4.5+0.29
5.6+0.43
0.6+0.03
0.4+0.04
0.6+0.03
0.8+0.14
0.6+0.11
0.5+0.03
0.7+0.04
0.3+0.02
5.1+0.18
5.2+0.35
4.9+0.27
4.7+0.31
Vegetables
All vegetables
Cooked vegetables,
excluding french fries
Deep yellow vegetables
Corn
Peas
Green beans
Mashed potatoes
Baked, boiled potatoes
French fries
cup
cup
cup
cup
cup
cup
cup
cup
cup
0.4+0.02
0.3+0.03
0.2+0.03
0.2+0.03
0.2+0.02
0.4+0.05
0.3+0.05
0.3+0.05
0.4+0.05
0.4+0.03
0.3+0.03
0.3+0.05
0.2+0.03
0.2+0.02
0.4+0.05
0.4+0.05
0.4+0.06
0.6+0.05
0.4+0.02
0.3+0.02
0.3+0.05
0.2+0.03
0.2+0.02
0.3+0.03
0.3+0.05
-
0.6+0.05
Cell size too small to generate reliable estimate.
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.












Page
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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean
Food
Moisture Content of Selected Food Groups
Moisture Content
Raw
Cookec
Expressed as Percentages of Edible Portions

Comments
Fruits
Apples - dried
Apples

Apples - juice
Applesauce
Apricots
Apricots - dried
Bananas
Blackberries
Blueberries
Boysenberries
Cantaloupes
Casabas
Cherries - sweet
Crabapples
Cranberries
Cranberries - juice cocktail
Currants (red and white)
Elderberries
Grapefruit (pink, red and white)
Grapefruit -juice
Grapefruit - unspecified
Grapes - fresh
Grapes -juice
Grapes - raisins
Honeydew melons
Kiwi fruit
Kumquats
Lemons - juice
Lemons - peel
Lemons - pulp
Limes
Limes - juice
Loganberries
Mulberries
Nectarines
Oranges - unspecified
Peaches
Pears - dried
Pears - fresh
Pineapple
Pineapple - juice
31.76
85.56*
86.67**


86.35
30.09
74.91
88.15
84.21
85.90
90.15
91.85
82.25
78.94
87.13
85.00
83.95
79.80
90.89
90.00
90.89
81.30
84.12
15.43
89.82
83.07
80.85
90.73
81.60
88.98
88.26
90.79
84.61*
87.68
87.59
86.75
88.87
26.69
83.71
86.00

84.13*


87.93
88.35*
86.62*
75.56*


86.59*



84.95*






90.10*







92.46*



92.52*




87.49*
64.44*
86.47*
83.51*
86.37
sulfured; * without added sugar
*with skin
** without skin
canned or bottled
*unsweetened
* canned juice pack with skin
sulfured; *without added sugar


*frozen unsweetened
frozen unsweetened


*canned, juice pack


bottled



* canned unsweetened
pink, red, white
American type (slip skin)
canned or bottled
seedless



* canned or bottled



* canned or bottled
*frozen


all varieties
* canned juice pack
sulfured; *without added sugar
* canned juice pack
* canned juice pack
canned
Child-Specific Exposure Factors Handbook
September 2008	
Page
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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean Moisture Content
Food
Plums - dried (prunes)
Plums
Quinces
Raspberries
Strawberries
Tangerine - juice
Tangerines
Watermelon
of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Moisture Content
Raw
30.92
87.23
83.80
85.75
90.95
88.90
85.17
91.45
Cooked
84.02*
89.97*
87.00*
89.51*

Comments
* canned juice pack
*frozen unsweetened
* canned sweetened
* canned juice pack
Vegetables
Alfalfa seeds - sprouted
Artichokes - globe & French
Artichokes - Jerusalem
Asparagus
Bamboo shoots
Beans - dry - blackeye peas (cowpeas)
Beans - dry - hyacinth (mature seeds)
Beans - dry - navy (mature seeds)
Beans - dry - pinto (mature seeds)
Beans - lima
Beans - snap - green - yellow
Beets
Beets - tops (greens)
Broccoli
Brussel sprouts
Cabbage - Chinese (pak-choi)
Cabbage - red
Cabbage - savoy
Carrots
Cassava (yucca blanca)
Cauliflower
Celeriac
Celery
Chives
Cole slaw
Collards
Corn - sweet
Cress - garden
Cucumbers - peeled
Dandelion - greens
Eggplant
Endive
Garlic
Kale
Kohlrabi
92.82
84.94
78.01
93.22
91.00
77.20
87.87
79.15
81.30
70.24
90.27
87.58
91.02
90.69
86.00
95.32
90.39
91.00
88.29
59.68
91.91
88.00
95.43
90.65
81.50
90.55
75.96
89.40
96.73
85.60
92.41
93.79
58.58
84.46
91.00
84.08
92.63
95.92
75.48
86.90
76.02
93.39
67.17
89.22
87.06
89.13
89.25
88.90
95.55
90.84
92.00
90.17
93.00
92.30
94.11

91.86
69.57
92.50
89.80
89.67

91.20
90.30
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained

boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained

boiled, drained
boiled, drained
Page
9-38
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9-23. Mean Moisture Content
Food
Lambsquarter
Leeks - bulb and lower leaf-portion
Lentils - sprouted
Lettuce - iceberg
Lettuce - cos or romaine
Mung beans - mature seeds (sprouted)
Mushrooms - unspecified
Mushrooms - oyster
Mushrooms - Maitake
Mushrooms - portabella
Mustard greens
Okra
Onions
Onions - dehydrated or dried
Parsley
Parsnips
Peas - edible-podded
Peppers - sweet - green
Peppers - hot chili-green
Potatoes (white)
Pumpkin
Radishes
Rutabagas - unspecified
Salsify (vegetable oyster)
Shallots
Soybeans - mature seeds - sprouted
Spinach
Squash - summer
Squash - winter
Sweet Potatoes
Swiss chard
Taro - leaves
Taro
Tomatoes -juice
Tomatoes - paste
Tomatoes - puree
Tomatoes
Towelgourd
Turnips
Turnips - greens
Water chestnuts - Chinese
Yambean - tuber
of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Moisture Content
Raw
84.30
83.00
67.34
95.64
94.61
90.40
88.80
90.53
91.20
90.80
90.17
89.11
3.93
87.71
79.53
88.89
93.89
87.74
81.58
91.60
95.27
89.66
77.00
79.80
69.05
91.40
94.64
89.76
77.28
92.66
85.66
70.64
93.95
93.85
91.87
89.67
73.46
90.07
Cooked
88.90
90.80
68.70
93.39
91.08
94.46
92.57
87.86

80.24
88.91
91.87
92.50*
75.43
93.69
88.88
81.00
79.45
91.21
93.70
89.02
75.78
92.65
92.15
63.80
93.90
73.50
87.88
84.29
93.60
93.20
86.42*
90.07

Comments
boiled, drained
boiled, drained
stir-fried
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained

boiled, drained
boiled, drained
boiled, drained
* canned solids & liquid
baked
boiled, drained
boiled, drained
boiled, drained
steamed
boiled, drained
all varieties; boiled, drained
all varieties; baked
baked in skin
boiled, drained
steamed

canned
canned
canned
boiled, drained
boiled, drained
boiled, drained
* canned solids and liquids
boiled, drained
Source: USDA, 2007.
Child-Specific Exposure Factors Handbook
September 2008	
Page
 9-39

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
                               APPENDIX 9A

  CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS FRUITS AND
    VEGETABLES USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
Child-Specific Exposure Factors Handbook
September 2008	
Page
9A-1

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data
Food Category
EPA Food Commodity Codes
TOTAL FRUITS AND VEGETABLES
Total Fruits 95000010 Acerola
1 1000090 Apple, dried
11000091 Apple, dried-babyfood
1 1000070 Apple, fruit with peel
1 1000080 Apple, peeled fruit
11000081 Apple, peeled fruit-babyfood
11000110 Apple, sauce
11000111 Apple, sauce-babyfood
12000120 Apricot
12000130 Apricot, dried
12000121 Apricot-babyfood
95000200 Avocado
95000230 Banana
95000240 Banana, dried
95000241 Banana, dried-babyfood
95000231 Banana-babyfood
13010550 Blackberry
13020570 Blueberry
13020571 Blueberry-babyfood
13010580 Boysenberry
95000600 Breadfruit
95000740 Canistel
95000890 Cherimoya
12000900 Cherry
12000901 Cherry-babyfood
10001060 Citrus citron
10001070 Citrus hybrids
95001120 Coconut, dried
95001110 Coconut, meat
9500 1 1 1 1 Coconut, meat-babyfood
95001130 Coconut, milk
11001290 Crabapple
95001300 Cranberry
95001310 Cranberry, dried
95001301 Cranberry-babyfood
13021360 Currant
13021370 Currant, dried
95001410 Date
13011420 Dewberry
08001480 Eggplant
13021490 Elderberry
95001510 Feijoa
95001530 Fig
95001540 Fig, dried
13021740 Gooseberry
95001750 Grape
95001780 Grape, raisin
10001800 Grapefruit
95001830 Guava
95001831 Guava-babyfood
13021910 Huckleberry
95001920 Jaboticaba
95001930 Jackfruit
95001950 Kiwifruit
10001970 Kumquat
10001990 Lemon
10002010 Lemon, peel
10002060 Lime
13012080 Loganberry
95002090 Longan
11002100 Loquat
95002110 Lychee
95002120 Lychee, dried
95002140 Mamey apple
95002150 Mango
95002160 Mango, dried
95002151 Mango-babyfood
95002270 Mulberry
12002300 Nectarine
10002400 Orange
10002420 Orange, peel
95002450 Papaya
95002460 Papaya, dried
95002451 Papaya-babyfood
95002520 Passionfruit
95002521 Passionfruit-babyfood
95002540 Pawpaw
12002600 Peach
12002610 Peach, dried
12002611 Peach, dried-babyfood
12002601 Peach-babyfood
11002660 Pear
11002670 Pear, dried
11002661 Pear-babyfood
95002770 Persimmon
95002790 Pineapple
95002800 Pineapple, dried
95002791 Pineapple-babyfood
95002830 Plantain
95002840 Plantain, dried
12002850 Plum
12002870 Plum, prune, dried
12002871 Plum, prune, dried-babyfood
12002860 Plum, prune, fresh
12002861 Plum, prune, fresh-babyfood
12002851 Plum-babyfood
95002890 Pomegranate
10003070 Pummelo
11003100 Quince
13013200 Raspberry
13013201 Raspberry-babyfood
95003330 Sapote, Mamey
95003460 Soursop
95003510 Spanish lime
Page
9A-2
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Total Fruits
(continued)
Total Vegetables

















































1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
95003580
95003590
95003591
18000020
04010050
01030150
01030151
95000160
01030170
04010180
95000190
09020210
95000220
19010290
19010291
19010280
19010281
06020330
06030360
06030380
06020370
06030390
06030400
06030410
06030420
06010430
06010431
01010500
01010501
02000510
95000540
05010610
05020630
05010620
05010611
05010640
05010690
05020700
05010720
05010710
95000730
09010750
04020760
01010780
01010781
09010800
01030820
01030821
05010830
01010840
04020850
04020851
04020870
Starfruit
Strawberry
Strawberry-babyfood
Alfalfa, seed
Amaranth, leafy
Arrowroot, flour
Arrowroot, flour-babyfood
Artichoke, globe
Artichoke, Jerusalem
Arugula
Asparagus
Balsam pear
Bamboo, shoots
Basil, dried leaves
Basil, dried leaves-babyfood
Basil, fresh leaves
Basil, fresh leaves-babyfood
Bean, cowpea, succulent
Bean, kidney, seed
Bean, lima, seed
Bean, lima, succulent
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Bean, snap, succulent
Bean, snap, succulent-babyfood
Beet, garden, roots
Beet, garden, roots-babyfood
Beet, garden, tops
Belgium endive
Broccoli
Broccoli raab
Broccoli, Chinese
Broccoli-babyfood
Brussels sprouts
Cabbage
Cabbage, Chinese, bok choy
Cabbage, Chinese, mustard
Cabbage, Chinese, napa
Cactus
Cantaloupe
Cardoon
Carrot
Carrot-babyfood
Casaba
Cassava
Cassava-babyfood
Cauliflower
Celeriac
Celery
Celery-babyfood
Celtuce
95003610
95003680
10003690
09020880
06030990
06030980
06030981
01011000
02001010
09021020
19011030
04011040
19021050
19021051
19011180
19011181
19021190
19021191
04011380
01031390
02001400
19011440
19021430
04021520
03001640
03001650
03001651
01031660
01031670
01031661
01011680
95001770
06031820
06031821
19011840
19011841
05021940
05011960
03001980
19012020
04012040
04012050
19012200
19012201
08002340
03002370
03002380
03002381
03002371
03002390
95002430
19012490
19012491
Sugar apple
Tamarind
Tangerine
Chayote, fruit
Chickpea, flour
Chickpea, seed
Chickpea, seed-babyfood
Chicory, roots
Chicory, tops
Chinese waxgourd
Chive
Chrysanthemum, garland
Cinnamon
Cinnamon-babyfood
Coriander, leaves
Coriander, leaves-babyfood
Coriander, seed
Coriander, seed-babyfood
Dandelion, leaves
Dasheen, conn
Dasheen, leaves
Dill
Dill, seed
Fennel, Florence
Garlic
Garlic, dried
Garlic, dried-babyfood
Ginger
Ginger, dried
Ginger-babyfood
Ginseng, dried
Grape, leaves
Guar, seed
Guar, seed-babyfood
Herbs, other
Herbs, other-babyfood
Kale
Kohlrabi
Leek
Lemongrass
Lettuce, head
Lettuce, leaf
Marjoram
Marj oram-babyfood
Okra
Onion, dry bulb
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, dry bulb-babyfood
Onion, green
Palm heart, leaves
Parsley, dried leaves
Parsley, dried leaves-babyfood
Child-Specific Exposure Factors Handbook
September 2008	
Page
9A-3

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Total Vegetables
(continued)




































1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
04012480
01012500
01012510
01012511
06032560
06032561
06012570
06032580
06022590
06022550
06022551
08002700
08002710
08002711
08002701
19022740
19022741
08002720
08002730
08002721
95002750
01032960
01032970
01032971
01032980
01032981
01033000
01033001
01032990
01032991
09023080
04013130
01013160
02003170
01013140
02003150
05023180
04023220
Parsley, leaves
Parsley, turnip rooted
Parsnip
Parsnip-babyfood
Pea, dry
Pea, dry-babyfood
Pea, edible podded, succulent
Pea, pigeon, seed
Pea, pigeon, succulent
Pea, succulent
Pea, succulent-babyfood
Pepper, bell
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, bell-babyfood
Pepper, black and white
Pepper, black and white-babyfood
Pepper, nonbell
Pepper, nonbell, dried
Pepper, nonbell-babyfood
Peppermint
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood
Pumpkin
Radicchio
Radish, Oriental, roots
Radish, Oriental, tops
Radish, roots
Radish, tops
Rape greens
Rhubarb
01013270
01013310
02003320
19013340
95003351
03003380
06003480
06003481
06003470
19023540
19023541
09023560
09023561
09023570
09023571
01033660
01033661
04023670
01033710
08003740
08003750
08003780
08003781
08003760
08003761
08003770
08003771
95003800
08003751
01033870
05023890
01013880
95003970
95003980
09013990
01034070
01034060

Rutabaga
Salsify, roots
Salsify, tops
Savory 95003350 Seaweed
Seaweed-babyfood
Shallot
Soybean, flour
Soybean, flour-babyfood
Soybean, seed
Spices, other
Spices, other-babyfood
Squash, summer
Squash, summer-babyfood
Squash, winter
Squash, winter-babyfood
Sweet potato
Sweet potato-babyfood
Swiss chard
Tanier, corm
Tomatillo
Tomato
Tomato, dried
Tomato, dried-babyfood
Tomato, paste
Tomato, paste-babyfood
Tomato, puree
Tomato, puree-babyfood
Tomato, Tree
Tomato-babyfood
Turmeric
Turnip, greens
Turnip, roots
Water chestnut
Watercress
Watermelon
Yam bean
Yam, true

INDIVIDUAL FRUIT CATEGORIES
Apples




Bananas



11000090
11000091
11000070
11000100
11000101
95000230
95000240
95000241
95000231
Apple, dried
Apple, dried-babyfood
Apple, fruit with peel
Apple, juice
Apple, juice-babyfood
Banana
Banana, dried
Banana, dried-babyfood
Banana-babyfood
11000080
11000081
11000110
11000111

95002830
95002840


Apple, peeled fruit
Apple, peeled fruit-babyfood
Apple, sauce
Apple, sauce-babyfood

Plantain
Plantain, dried


Page
9A-4
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued)
Food Category
Berries and Small
Fruits










Citrus Fruits





Peaches



Pears




Pome Fruits






Strawberries

Stone Fruits








EPA Food Commodity Codes
13010550
13010580
13011420
13012080
13013200
13013201
13020570
13020571
13021360
13021370
13021490
13021740
10001060
10001070
10001800
10001970
10001990
10002010
12002600
12002610
12002611
12002601
11002660
11002670
11002680
11002681
11002661
11000070
11000080
11000081
11000090
11000091
11000110
11000111
95003590
95003591
12000120
12000121
12000130
12000900
12000901
12002300
12002600
12002601
12002610
Blackberry
Boysenberry
Dewberry
Loganberry
Raspberry
Raspberry-babyfood
Blueberry
Blueberry-babyfood
Currant
Currant, dried
Elderberry
Gooseberry
Citrus citron
Citrus hybrids
Grapefruit
Kumquat
Lemon
Lemon, peel
Peach
Peach, dried
Peach, dried-babyfood
Peach-babyfood
Pear
Pear, dried
Pear, juice
Pear, juice-babyfood
Pear-babyfood
Apple, fruit with peel
Apple, peeled fruit
Apple, peeled fruit-babyfood
Apple, dried
Apple, dried-babyfood
Apple, sauce
Apple, sauce-babyfood
Strawberry
Strawberry-babyfood
Apricot
Apricot-babyfood
Apricot, dried
Cherry
Cherry-babyfood
Nectarine
Peach
Peach-babyfood
Peach, dried
13021910
95001300
95001301
95001310
95001750
95001770
95001780
95001950
95002270
95003590
95003591

10002060
10002400
10002420
10003070
10003690










11001290
11002100
11002660
11002661
11002670
11003100



12002611
12002850
12002851
12002860
12002861
12002870
12002871


Huckleberry
Cranberry
Cranberry-babyfood
Cranberry, dried
Grape
Grape, leaves
Grape, raisin
Kiwifruit
Mulberry
Strawberry
Strawberry-babyfood

Lime
Orange
Orange, peel
Pummelo
Tangerine










Crabapple
Loquat
Pear
Pear-babyfood
Pear, dried
Quince



Peach, dried-babyfood
Plum
Plum-babyfood
Plum, prune, fresh
Plum, prune, fresh-babyfood
Plum, prune, dried
Plum, prune, dried-babyfood


Child-Specific Exposure Factors Handbook
September 2008	
Page
9A-5

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in
Food Category
Tropical Fruits






















Analysis of the 1994-96, 1998 USDACSFII Data (continued)
EPA Food Commodity Codes
95000010
95000220
95000230
95000231
95000240
95000241
95000600
95000740
95000890
95001110
95001111
95001120
95001130
95001410
95001510
95001530
95001540
95001830
95001831
95001930
95002090
95002110
95002120
Acerola
Avocado
Banana
Banana-babyfood
Banana, dried
Banana, dried-babyfood
Breadfruit
Canistel
Cherimoya
Coconut, meat
Coconut, meat-babyfood
Coconut, dried
Coconut, milk
Date
Feijoa
Fig
Fig, dried
Guava
Guava-babyfood
Jackfruit
Longan
Lychee
Lychee, dried
95002140
95002150
95002151
95002160
95002450
95002451
95002460
95002520
95002521
95002540
95002790
95002791
95002800
95002830
95002840
95002890
95003330
95003460
95003510
95003580
95003610
95003680

Mamey apple
Mango
Mango-babyfood
Mango, dried
Papaya
Papaya-babyfood
Papaya, dried
Passionfruit
Passionfruit-babyfood
Pawpaw
Pineapple
Pineapple-babyfood
Pineapple, dried
Plantain
Plantain, dried
Pomegranate
Sapote, Mamey
Soursop
Spanish lime
Starfruit
Sugar apple
Tamarind

INDIVIDUAL VEGETABLE CATEGORIES
Asparagus
Beans







Beets


Broccoli

Bulb Vegetables




Cabbage


95000190
06030350
06030300
06030320
06020310
06030340
06020330
06030360
06030380
01010500
01010501
02000510
05010610
05010611
03001640
03001650
03001651
03001980
03002370
05010690
05010720
05010710
Asparagus
Bean, great northern, seed
Bean, black, seed
Bean, broad, seed
Bean, broad, succulent
Bean, cowpea, seed
Bean, cowpea, succulent
Bean, kidney, seed
Bean, lima, seed
Beet, garden, roots

06020370
06030390
06030400
06030410
06030420
06010430
06010431



Bean, lima, succulent
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Bean, snap, succulent
Bean, snap, succulent-babyfood


Beet, garden, roots-babyfood
Beet, garden, tops
Broccoli
Broccoli-babyfood
Garlic
Garlic, dried
Garlic, dried-babyfood
Leek
Onion, dry bulb
Cabbage
Cabbage, Chinese, mustard
Cabbage, Chinese, napa



03002371
03002380
03002381
03002390
03003380






Onion, dry bulb-babyfood
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, green
Shallot



Page
9A-6
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued)
Food Category
Carrots
Corn





Cucumbers
Cucurbit
Vegetables





Fruiting Vegetables









Leafy Vegetables
(Brassica and
Nonbrassica)




















EPA Food Commodity Codes
01010780
15001220
15001200
15001201
15001210
15001211
15001230
09021350
09010750
09010800
09011870
09013990
09020210
09020880
09021020
08001480
08002340
08002700
08002701
08002710
08002711
08002720
08002721
08002730
08003740
02000510
02001010
02001400
02003150
02003170
02003320
04010050
04010180
04011040
04011330
04011340
04011380
04011500
04012040
04012050
04012480
04013130
04013550
04013551
04020760
04020850
04020851
04020870
Carrot
Corn, field, bran
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, starch
Cucumber
Cantaloupe
Casaba
Honeydew melon
Watermelon
Balsam pear
Chayote, fruit
Chinese waxgourd
Eggplant
Okra
Pepper, bell
Pepper, bell-babyfood
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, nonbell
Pepper, nonbell-babyfood
Pepper, nonbell, dried
Tomatillo
Beet, garden, tops
Chicory, tops
Dasheen, leaves
Radish, tops
Radish, Oriental, tops
Salsify, tops
Amaranth, leafy
Arugula
Chrysanthemum, garland
Cress, garden
Cress, upland
Dandelion, leaves
Endive
Lettuce, head
Lettuce, leaf
Parsley, leaves
Radicchio
Spinach
Spinach-babyfood
Cardoon
Celery
Celery-babyfood
Celtuce

15001231
15001260
15001270
15001271



09021350
09023080
09023090
09023560
09023561
09023570
09023571
08003750
08003751
08003760
08003761
08003770
08003771
08003780
08003781


04021520
04023220
04023670
05010610
05010611
05010620
05010640
05010690
05010710
05010720
05010830
05011960
05020630
05020700
05021170
05021940
05022290
05023180
05023890
95000540
95003350
95003351
95003980

Corn, field, starch-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood



Cucumber
Pumpkin
Pumpkin, seed
Squash, summer
Squash, summer-babyfood
Squash, winter
Squash, winter-babyfood
Tomato
Tomato-babyfood
Tomato, paste
Tomato, paste-babyfood
Tomato, puree
Tomato, puree-babyfood
Tomato, dried
Tomato, dried-babyfood


Fennel, Florence
Rhubarb
Swiss chard
Broccoli
Broccoli-babyfood
Broccoli, Chinese
Brussels sprouts
Cabbage
Cabbage, Chinese, napa
Cabbage, Chinese, mustard
Cauliflower
Kohlrabi
Broccoli raab
Cabbage, Chinese, bok choy
Collards
Kale
Mustard greens
Rape greens
Turnip, greens
Belgium endive
Seaweed
Seaweed - babyfood
Watercress
Child-Specific Exposure Factors Handbook
September 2008	
Page
9A-7

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                                            Child-Specific Exposure Factors Handbook

                                            Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Legume Vegetables


Lettuce

Okra
Onions


Peas

Peppers
Pumpkin
1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
06003470
06003480
06003481
06003490
06003491
06010430
06010431
06012570
06020310
06020330
06020370
06022550
06022551
06022590
06030300
06030320
04012040
04012050
08002340
03002370
03002380
03002381
03002371
03002390
06032560
06032561
06012570
06032580
06022590
08002700
08002710
08002711
08002701
08002720
09023080
09023090
Soybean, seed
Soybean, flour
Soybean, flour-babyfood
Soybean, soy milk
Soybean, soy milk-babyfood or infant
formula
Bean, snap, succulent
Bean, snap, succulent-babyfood
Pea, edible podded, succulent
Bean, broad, succulent
Bean, cowpea, succulent
Bean, lima, succulent
Pea, succulent
Pea, succulent-babyfood
Pea, pigeon, succulent
Bean, black, seed
Bean, broad, seed
Lettuce, head
Lettuce, leaf
Okra
Onion, dry bulb
Onion, dry bulb, dried
Onion, dry bulb, dried-babyfood
Onion, dry bulb-babyfood
Onion, green
Pea, dry
Pea, dry-babyfood
Pea, edible podded, succulent
Pea, pigeon, seed
Pea, pigeon, succulent
Pepper, bell
Pepper, bell, dried
Pepper, bell, dried-babyfood
Pepper, bell-babyfood
Pepper, nonbell
Pumpkin
Pumpkin, seed
06030340
06030350
06030360
06030380
06030390
06030400
06030410
06030420
06030980
06030981
06030990
06031820
06031821
06032030
06032560
06032561
06032580






06022550
06022551
08002730
08002721

Bean, cowpea, seed
Bean, great northern, seed
Bean, kidney, seed
Bean, lima, seed
Bean, mung, seed
Bean, navy, seed
Bean, pink, seed
Bean, pinto, seed
Chickpea, seed
Chickpea, seed-babyfood
Chickpea, flour
Guar, seed
Guar, seed-babyfood
Lentil, seed
Pea, dry
Pea, dry-babyfood
Pea, pigeon, seed






Pea, succulent
Pea, succulent-babyfood
Pepper, nonbell, dried
Pepper, nonbell-babyfood

Page
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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 9 - Intake of Fruits and Vegetables
Table 9A-1. Food Codes and Definitions Used in Analysis of the
Food Category
Root and Tuber
Vegetables




















Stalk and Stem
Vegetable and
Edible Fungi


Tomatoes




White Potatoes




1994-96, 1998 USDA CSFII Data (continued)
EPA Food Commodity Codes
01030150
01030151
01030170
01010500
01010501
02000510
01010520
01010521
01010670
01010780
01010781
01030820
01030821
01010840
01011000
01031390
01031660
01031670
01031661
01011680
01011900
01012500
95000160
95000190
95000220
95002280
95002430
08003750
08003780
08003781
08003760
08003761
01032960
01032970
01032971
01032980
01032981
Arrowroot, flour
Arrowroot, flour-babyfood
Artichoke, Jerusalem
Beet, garden, roots
Beet, garden, roots-babyfood
Beet, garden, tops
Beet, sugar
Beet, sugar-babyfood
Burdock
Carrot
Carrot-babyfood
Cassava
Cassava-babyfood
Celeriac
Chicory, roots
Dasheen, conn
Ginger
Ginger, dried
Ginger-babyfood
Ginseng, dried
Horseradish
Parsley, turnip rooted
Artichoke, globe
Asparagus
Bamboo, shoots
Mushroom
Palm heart, leaves
Tomato
Tomato, dried
Tomato, dried-babyfood
Tomato, paste
Tomato, paste-babyfood
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
01012510
01012511
01032960
01032970
01032971
01032980
01032981
01033000
01033001
01032990
01032991
01013160
01013140
01013270
01033660
01033661
01033710
01033870
01013880
95003970
01034070
01034060





08003770
08003771
08003751


01033000
01033001
01032990
01032991

Parsnip
Parsnip-babyfood
Potato, chips
Potato, dry (granules/ flakes)
Potato, dry (granules/ flakes)-babyfood
Potato, flour
Potato, flour-babyfood
Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood
Radish, Oriental, roots
Radish, roots
Rutabaga
Sweet potato
Sweet potato-babyfood
Tanier, corm
Turmeric
Turnip, roots
Water chestnut
Yam bean
Yam, true





Tomato, puree
Tomato, puree-babyfood
Tomato-babyfood


Potato, tuber, w/o peel
Potato, tuber, w/o peel-babyfood
Potato, tuber, w/peel
Potato, tuber, w/peel-babyfood

Child-Specific Exposure Factors Handbook
September 2008	
Page
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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
                                     TABLE OF CONTENTS

10     INTAKE OF FISH AND SHELLFISH	  10-1
       10.1    INTRODUCTION	  10-1
       10.2    RECOMMENDATIONS 	  10-2
       10.3    GENERAL POPULATION STUDIES 	  10-6
               10.3.1   Key General Population Study	  10-6
                      10.3.1.1 U.S. EPA 2002  	  10-6
               10.3.2   Relevant General Population Studies	  10-6
                      10.3.2.1 U.S. EPA, 1996  	  10-6
                      10.3.2.2 Moya et al., 2008  	  10-7
       10.4    MARINE RECREATIONAL STUDIES  	  10-8
               10.4.1   Relevant Marine Recreational Studies	  10-8
                      10.4.1.1 KCA Research Division, 1994 	  10-8
                      10.4.1.2 Alcoa, 1998	  10-8
       10.5    FRESHWATER RECREATIONAL STUDIES	  10-9
               10.5.1   Relevant Freshwater Recreational Studies	  10-9
                      10.5.1.1 Westetal, 1989  	  10-9
                      10.5.1.2 Benson etal, 2001 	  10-10
       10.6    NATIVE AMERICAN STUDIES  	  10-10
               10.6.1   Relevant Native American Studies	  10-10
                      10.6.1.1 Columbia River Inter-Tribal Fish Commission (CRITFC), 1994 	  10-10
                      10.6.1.2 Toy etal., 1996  	  10-12
                      10.6.1.3 Duncan, 2000  	  10-13
                      10.6.1.4 Polissar et al., 2006  	  10-13
       10.7    SERVING SIZE STUDY	  10-14
               10.7.1   Smiciklas-Wright et al., 2002 	  10-14
       10.8    OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION	  10-14
               10.8.1   Conversion Between Wet and Dry Weight 	  10-14
               10.8.2   Conversion Between Wet Weight and Lipid Weight Intake Rates  	  10-15
       10.9    REFERENCES FOR CHAPTER 10  	  10-15
Child-Specific Exposure Factors Handbook                                             Page
September 2008	10-i

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                                                        Child-Specific Exposure Factors Handbook

                                                          Chapter 10 - Intake of Fish and Shellfish
                                           LIST OF TABLES

Table 10-1.      Recommended Values for General Population Fish Intake  	  10-4
Table 10-2.      Confidence in Recommendations for General Population Fish Intake	  10-5
Table 10-3.      Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - g/day, As-Consumed	  10-17
Table 10-4.      Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed  	  10-17
Table 10-5.      Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - g/day, As-Consumed	  10-18
Table 10-6.      Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed	  10-18
Table 10-7.      Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight	  10-19
Table 10-8.      Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight	  10-19
Table 10-9.      Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight	  10-20
Table 10-10.     Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight	  10-20
Table 10-11.     Number of General Population Respondents Reporting Consumption of a
                Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten	  10-21
Table 10-12.     Fish Consumption Among General Population Children in Four States,
                Consumers Only, g/kg-day As-Consumed  	  10-22
Table 10-13.     Fish Consumption Among General Population in Four States According to Caught or Bought
                Status, g/kg-day As-Consumed	  10-23
Table 10-14.     Fish Consumption Among General Population and Anglers in Three States,
                g/kg-day As-Consumed	  10-24
Table 10-15.     Recreational Fish Consumption in Delaware Consumers Only	  10-24
Table 10-16.     Consumption of Self-Caught Fish by Recreational Anglers
                Lavaca Bay, Texas, g/day 	  10-25
Table 10-17.     Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational
                Anglers Lavaca Bay, Texas	  10-25
Table 10-18.     Mean Fish Intake Among Individuals Who Eat Fish and
                Reside in Households With Recreational Fish Consumption - Michigan	  10-26
Table 10-19.     Consumption of Sports-caught and Purchased Fish by Minnesota and North Dakota
                Children, Ages 0 to 14 Years (g/day) 	  10-26
Table 10-20.     Fish Consumption Rates among Native American Children (age 5 years and under)	  10-27
Table 10-21.     Number of Fish Meal Eaten per Month and Fish Intake Among Native American
                Children who Consume Particular Species	  10-28
Table 10-22.     Consumption Rates for Native American Children, Age Birth to Five Years (g/kg-day) 	  10-29
Table 10-23.     Consumption Rates for Native American Children (g/kg-day), All Children
                (including non-consumers):  Individual Finfish and Shellfish and Fish Groups	  10-30
Table 10-24.     Consumption Rates for Native American Children (g/kg-day),
                Consumers Only: Individual Finfish and Shellfish and Fish Groups 	  10-31
Table 10-25.     Fish Consumption Rates for Tulalip and Squaxin Island Children
                Consumers Only (g/kg-day)	  10-32
Table 10-26.     Fish Consumption Rates by  Gender for Tulalip and Squaxin Island Children
                Consumers Only (g/kg-day)	  10-33
Page
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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-27.     Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion,
               by Age and Sex 	  10-34
Table 10-28.     Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion,
               by Age and Sex 	  10-34
Table 10-29.     Mean Percent Moisture and Total Fat Content for Selected Species	  10-35
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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
10    INTAKE OF FISH AND SHELLFISH
10.1  INTRODUCTION
      Contaminated finfish  and shellfish are potential
sources of human exposure to toxic chemicals.  Pollutants
are carried  in the surface waters, but also may be stored
and accumulated in the sediments as a result of complex
physical and chemical processes. Consequently, finfish
and shellfish are exposed to these  pollutants and may
become sources of contaminated food.  Exposure to some
contaminants may be of concern for children because they
may be less able  to metabolize, detoxify, and excrete
these substances (Moya, 2004).
      Accurately  estimating   exposure  to   a  toxic
chemicals among a population that consumes fish from a
polluted water body requires  an estimation of intake rates
of the caught fish by both fishermen and their families.
Commercially  caught fish are marketed widely, making
the prediction of  an  individual's consumption from  a
particular  water body  or contaminant source difficult.
Since the catch of recreational and subsistence fishermen
is  not  "diluted" by fish  from other  water bodies, these
individuals  and their families  represent the population that
is most vulnerable to exposure by intake of contaminated
fish from a specific location.  This chapter focuses on
intake rates offish. Note that in this  section the term fish
refers to both  finfish and  shellfish.   Intake  rates for the
general population, and recreational and Native American
fishing populations are addressed, and data are presented
for intake rates for both marine and freshwater  fish, when
available.
      Survey  data on  fish consumption have been
collected using a number  of different approaches which
need to be considered when  interpreting the results.
Typical surveys  seek to draw inferences  about a larger
population from a smaller sample of that population.  This
larger population, from which the survey sample is taken
and to which the results  of the survey are generalized, is
denoted the target population of the  survey. In order to
generalize from the sample to the target population, the
probability  of being sampled must  be known for each
member of the target population.   This probability is
reflected in weights assigned to survey respondents, with
weights  being  inversely  proportional  to   sampling
probability.  When all members of the target population
have the same probability of being sampled, all weights
can be  set to one and essentially ignored. For example, in
a mail or  phone study of licensed  anglers,  the  target
population  is generally all licensed anglers in a particular
area,  and   in  the  studies  presented,  the   sampling
probability  is  essentially equal for all target population
members.    In a creel  study  (i.e.,  a study  in which
fishermen  are  interviewed  while fishing), the  target
population is anyone who fishes  at the locations being
studied; generally, in a creel  study, the probability of
being sampled  is not the same for all members of the
target population. For instance, if the survey is conducted
for one day at a site, then it will include all persons who
fish there daily,  but only about 1/7 of the people who fish
there  weekly,  1/3 Oth  of the  people  who fish there
monthly, etc. In this example, the probability of being
sampled (or inverse weight) is seen to be proportional to
the frequency of fishing. However, if the survey involves
interviewers revisiting the same site on multiple days, and
persons are only interviewed once for the survey, then the
probability of being in  the survey is not proportional to
frequency;  in fact, it increases  less than proportionally
with frequency.  At the extreme of surveying the same site
every day over the survey period with no re-interviewing,
all members of the target population would have the same
probability  of  being  sampled  regardless  of  fishing
frequency,  implying that the survey weights should all
equal one.  On the other hand, if the survey protocol calls
for individuals to be interviewed each time an interviewer
encounters them (i.e., without regard to whether they were
previously  interviewed),  then the  inverse weights will
again be proportional to fishing frequency, no matter how
many times interviewers revisit the same site.  Note that
when individuals can be interviewed multiple times, the
results of each interview are included as separate records
in the data  base and the  survey weights should be
inversely proportional to the expected  number of times
that an individual's interviews are included in the data
base.
      The U.S. EPA has prepared a review of  and an
evaluation  of five different survey methods used for
obtaining fish consumption data. They are:

      •          Recall-Telephone Survey;
      •          Recall-Mail Survey;
      •          Recall-Personal Interview;
      •          Diary; and
      •          Creel Census.

The reader is referred to U.S. EPA (1998) Guidance for
Conducting Fish  and Wildlife Consumption Surveys for
more detail on these survey methods and their advantages
and limitations.   The  type of survey used, its design, and
any weighting  factors  used in  estimating consumption
should be considered when interpreting survey data for
exposure assessment  purposes.  For surveys used in this
handbook,  respondents are  typically  adults who have
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                                                            Chapter 10 - Intake of Fish and Shellfish
reported on  fish  intake  for  children  living in  their
households.
      The recommendations  for  fish  and  shellfish
ingestion rates are provided in the next section, along with
a  summary   of   the  confidence  ratings  for  these
recommendations.  The recommended values are based on
the key study identified  by U.S. EPA for  this factor.
Following the  recommendations,  the  studies  on fish
ingestion among the general population (Section  10.3),
marine  recreational  angler households  (Section  10.4),
freshwater recreational households  (Section 10.5), and
Native  American  populations   (Section   10.6)  are
summarized.  Information is provided on the key study
that forms the basis for the fish and shellfish intake rate
recommendations.  Relevant data on ingestion offish and
shellfish are also provided. These studies are presented to
provide the reader with added perspective on the current
state-of-knowledge pertaining  to  ingestion  of fish and
shellfish among children.  Information on serving size
(Section 10.7), and other factors  (Section 10.8) are also
presented.

10.2  RECOMMENDATIONS
      Considerable  variation  exists in the mean and
upper percentile fish consumption rates obtained from the
studies presented in this chapter.   This can be attributed
largely to the type  of water body (i.e., marine, estuarine,
freshwater)  and   the  characteristics  of  the   survey
population (i.e., general population, recreational, Native
American), but other factors such  as study design, method
of data  collection, and geographic location also play  a
role.  Based on these study variations, fish consumption
studies were classified into the following categories:

      •          General Population   (total,  marine,
                freshwater/estuarine);
      • •       Recreational  Marine Intake;
      •         Recreational  Freshwater Intake; and
      •         Native American Populations

For exposure  assessment purposes, the selection of intake
rates  for the  appropriate category  (or categories) will
depend on the exposure scenario being evaluated.
      Fish consumption  rates  are recommended for
various  ages of children in the  general population, based
on the key study presented in Section  10.3.1.  The key
study for estimating mean fish  intake among the general
population is  the U.S. EPA (2002) analysis of data from
the U.S. Department of Agriculture  (USDA) Continuing
Survey of Food Intake among Individuals (CSFII)  1994-
1996, 1998.  Per  capita and consumer-only values for
children ages 3 to < 6, 6 to <11, 11 to < 16, and 16 to <
18 years, by habitat (i.e., marine, freshwater/estuarine, or
total fish), are shown in Table 10-1.  It should be noted,
however, that the key general population study presented
in this chapter pre-dated the age groups recommended by
U.S. EPA  in Guidance on  Selecting Age Groups for
Monitoring and Assessing  Childhood  Exposures  to
Environmental Contaminants (U.S. EPA, 2005).  Thus,
recommended values were not available for children less
than 3 years old or 18 to < 21.  The  confidence ratings for
the  fish  intake  recommendations  for   the  general
population are presented in Table 10-2.  Note that the fish
intake values presented in Table  10-1 are reported as
uncooked fish weights.  The CSFII  1994-1996, 1998
recipe files were used to convert, for each fish-containing
food, the as-eaten fish weight consumed into an uncooked
equivalent weight of fish.  This is important because the
concentrations of the contaminants in fish are generally
measured in the  uncooked  samples.   Assuming that
cooking results in some reductions in weight (e.g., loss of
moisture), and the mass of the contaminant in the fish
tissue  remains   constant,   then  the   contaminant
concentration in the cooked fish tissue will increase.   In
terms of calculating the dose, actual consumption may be
overestimated when intake is expressed on an uncooked
basis, but the actual concentration may be underestimated
when it is based on the uncooked sample.   The net effect
on  the  dose would depend  on the magnitude of the
opposing effects on these two exposure factors.   On the
other hand, if the "as-prepared" (i.e., as-consumed) intake
rate and the uncooked concentration are used in the dose
equation,   dose   may  be   underestimated  since  the
concentration in the cooked fish is  likely to be higher, if
the  mass of the  contaminant remains  constant  after
cooking.     Therefore, it is  more  conservative  and
appropriate  to  use  uncooked  fish intake  rates.    If
concentration data can be adjusted to account for changes
after cooking, then the "as-prepared" (i.e.,  as-consumed)
intake rates are appropriate. However, data on the effects
of cooking on contaminant concentrations are limited and
assessors generally make the conservative assumption that
cooking has no effect on the contaminant mass. Both "as-
prepared"  (i.e.,  as-consumed)  and uncooked general
population   fish  intake values  are  presented in  this
handbook so that the assessor can choose the intake data
that best matches  the concentration data  that are being
used.
      The  CSFII data on which the general population
recommendations are  based, are short-term survey data
and could not be used to estimate the distribution over the
long term.  Also, it is important to note that a limitation
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Chapter 10 - Intake of Fish and Shellfish
associated with these data is that the total amount of fish
reported by respondents included fish from all sources
(e.g.,  fresh,  frozen,  canned,  domestic,  international
origin).  The CSFII surveys did not identify the  source of
the fish consumed.   This type of information may be
relevant for some assessments.  It should also  be noted
that because these recommendations are based on  1994-
1996, 1998 CSFII data, they may not reflect any recent
changes that may have occurred in consumption patterns.
      Recommended values should  be selected that are
relevant to the assessment, choosing the appropriate age
groups and source of  fish (i.e.,  freshwater/estuarine,
marine, and total fish). In some cases a different study or
studies may be particularly relevant to the needs of an
assessment, in which case results from that specific study
or studies  may be  used instead  of the  recommended
values provided  here.     For  example,  it  may  be
advantageous to use available regional  or site-specific
estimates if the assessment targets a particular region or
site.   In  addition,  seasonal,  gender,  and fish species
variations  should be considered when appropriate, if data
are available.
      Recommendations are not provided for recreational
marine fish intake, recreational freshwater fish intake,  or
intake  among Native American  children because the
available data are limited  to certain  geographic areas
and/or tribes and cannot be readily generalized to the U.S.
population as a whole.  However, data from two relevant
recreational marine studies (KCA, 1994 and Alcoa, 1998);
two relevant recreational freshwater  studies (West et al,
1989 and Benson et al., 2001); and four Native American
studies (CRITFC, 1994; Toy et al., 1996; Duncan, 2000;
and Polissar et al., 2006)  are provided in this chapter.
Assessors  may use these  data, if  appropriate  to the
scenarios being assessed. These studies were performed
at various study locations using various age groups  of
children.
      For  recreational  marine fish intake, the  KCA
(1994) study was conducted in Delaware using the age
groups 0 to 9 years and 10 to  19 years and the Alcoa
(1998) study was conducted in Texas using the age groups
<6 years and 6 to 19 years.  Mean recreational marine fish
intake values in the KCA (1994) study were 6 grams/day
and 11.4 grams/day for the 0 to 9 years (N = 73) and 10 to
19 years (N = 102), respectively. The Alcoa (1998) study
provided mean recreational marine intake  values  for
finfish at 11.4 grams/day for the children <6 years old (N
= 320) and 15.6 grams/day for children 6 to 19  years old
(N = 749).  Mean shellfish values were 0.4 grams/day and
0.7 grams/day for the same  age groups, respectively.
Readers are referred to  the studies provided in Section
10.4 of this chapter to determine if the values presented
are applicable to their specific assessment.
      For recreational freshwater fish intake, the West et
al. (1989) study was conducted in Michigan to estimate
intake based on 7-day recall and the frequency of fish
meals over each of the four seasons.  Based  on a U.S.
EPA analysis of the data, mean recreational freshwater
fish intake rates were 5.6, 7.9, and 7.3  grams/day for
children ages 1  to 5 years (N = 121), 6 to 10 years (N =
151), and 11 to  20 years (N = 349), respectively.  Benson
et al. (2001) reported median freshwater sports-caught
fish intake rates of 1.2 and  1.7 grams/day for children,
ages 0 to  14 years, in Minnesota (N = 582) and North
Dakota (N = 343), respectively.  Readers  are referred to
the studies provided in Section 10.5 of this chapter to
determine  if the values presented are applicable to their
specific assessment.
      Fish  consumption  data  for  Native  American
children are very  limited, and  fish consumption rates,
habits, and patterns can vary among tribes  and  other sub-
populations.  Therefore, fish intake data for a particular
tribe may not be representative of other tribes.  Available
data on  fish consumption  among this  population is
presented in Section 10.6.  These data should be used, as
appropriate.
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                                            Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish















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Chapter 10 - Intake of Fish and Shellfish
                    Table 10-2. Confidence in Recommendations for General Population Fish Intake
 General Assessment Factors
                     Rationale
Rating
  Soundness
   Adequacy of Approach
  Minimal (Or Defined) Bias
The survey methodology and the analysis of the survey
data were adequate. Primary data were collected and used
in a secondary analysis of the data.  The sample size was
large.

The survey data were based on recent recall. Data were
collected over a short-duration (i.e., 2 days).	
                                                           High
 Applicability and Utility
   Exposure Factor of Interest

   Representativeness
   Currency

   Data Collection Period
The key study focused the exposure factor of interest.

The survey was conducted nationwide and was
representative of the general U.S. population.

The most current CSFII 1994-96; 98 data were used.

Data were collected for two non-consecutive days.
                                                           High
  Clarity and Completeness
   Accessibility

   Reproducibility
   Quality Assurance
The primary data are accessible through USDA.

The methodology was clearly presented; enough
information was available to allow for reproduction of the
results.

Quality assurance of CSFII data was good; quality control
of secondary analysis was good.	
                                                           High
 Variability and Uncertainty
   Variability in Population

   Uncertainty
Full distributions were provided by the key study.

The survey was not designed to capture long-term intake
and was based on recall.  Otherwise, the sources of
uncertainty were minimal.
                                                         Medium
 Evaluation and Review
   Peer Review
   Number and Agreement of Studies
The primary data were reviewed by USDA; U.S. EPA
review conducted a review of the secondary data analysis
for fish intake.

The number of studies is 1.
                                                          Medium
  Overall Rating
                                                        High (mean)
                                                      Medium (upper
                                                         percentile)
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                                                            Chapter 10 - Intake of Fish and Shellfish
10.3    GENERAL POPULATION STUDIES
10.3.1  Key General Population Study
10.3.1.1 U.S. EPA 2002 - Estimated Per Capita Fish
        Consumption in the United States
        U.S. EPA's Office of Water used data from the
1994-96  CSFII and its  1998 Children's  Supplement
(referred  to collectively  as CSFII  1994-96, 1998) to
generate  fish intake  estimates.    Participants in the
CSFII 1994-96, 98 provided two non-consecutive days
of dietary data.   Respondents estimated the weight of
each  food that  they  consumed.  Information on the
consumption  of food was  classified using  11,345
different food codes, and  stored in a database in units of
grams consumed per day. A total of 831 of these food
codes related to fish or  shellfish;  survey  respondents
reported consumption across 665 of these  codes.  The
fish component (by weight) of the various foods was
calculated using data from the recipe file for release 7
of USDA's  Nutrient Data Base for  Individual  Food
Intake Surveys.  The amount of fish consumed by each
individual was then calculated by summing, over all
fish containing foods, the product of the weight of food
consumed and the fish component (i.e., the percentage
fish by weight)  of the  food.   The  recipe file  also
contains cooking loss factors associated with each food.
These were used to convert, for each fish-containing
food,  the as-eaten fish  weight  consumed  into  an
uncooked equivalent weight of fish.   Analyses of fish
intake were performed on both an "as-prepared" (i.e.,
as-consumed) and uncooked basis.
        Each fish-related food code was assigned, by
U.S. EPA, to a habitat category.  The habitat categories
included freshwater/estuarine,  or marine.  Food codes
were  also designated as  finfish or shellfish.   Average
daily  individual consumption  (g/day) was calculated,
for a  given fish type-by-habitat category (e.g., marine
finfish), by summing the amount of fish consumed by
the individual across the two reporting days for all fish-
related food codes in the  given fish-by-habitat category
and  then dividing  by  2.    Individual   daily  fish
consumption  (g/day)  was calculated  similarly except
that total fish consumption was divided by the specific
number   of   survey  days  the  individual   reported
consuming fish; this was calculated for fish consumers
only (i.e., those consuming fish on at least one  of the
two survey days).  The  reported body weight of the
individual was used to convert consumption in g/day to
consumption in g/kg-day.
        There were a total of 20,607 respondents in the
combined data set who had two-day dietary intake data.
A total of 7,429 of these individuals were  children
 between the ages of 3  and 17 years.  Data for these
 children were used in estimating fish intake in g/day.
 Slightly fewer children were  used in  the fish intake
 rates  estimated in units  of g/kg-day because body
 weights were not reported for some individuals.  Survey
 weights were  assigned to  this data set  to make  it
 representative of the U.S.  population with respect to
 various demographic  characteristics  related  to  food
 intake.   These  weights  were  used  to  project  the
 estimates for the 7,429 children in  the  data set to
 58,923,560 children in the U.S. population.
         U.S. EPA (2002) reported means and estimates
 of the 90th,  95th,  and  99th percentiles of  fish  intake.
 Tables 10-3 through 10-10 present these statistics for
 daily  average  fish  consumption.   These  data  are
 presented for selected age groups: 3 to 5, 6 to 10, 11 to
 15, and 16 to 17 years of age.  Tables 10-3 and 10-4
 present per capita fish consumption, on an as-consumed
 basis, in g/day and in mg/kg-day, respectively.  Tables
 10-5 and 10-6 provide consumer-only fish  intake data,
 on an as-consumed basis, in units of g/day and mg/kg-
 day, respectively.  Tables 10-7 through 10-10 provide
 per capita and consumer only fish intake  data (g/day
 and mg/kg-day) on an uncooked equivalent  basis.
         The advantages of this study are that the data
 used were from the  CSFII  survey, which had a large
 sample size and  was  representative of the  U.S.
 population.  The  CSFII survey  was also  designed to
 give unbiased estimates of food consumption (U.S.
 EPA, 2002). In addition,  through use of the  USDA
 recipe files, the analysis included all fish eaten (i.e.,
 both fish eaten alone and in mixtures).

 10.3.2  Relevant General Population Studies
 10.3.2.1 U.S. EPA,  1996 - National Human Activity
         Pattern Survey (NHAPS)
         The U. S. EPA (1996) collected information for
 the general population on the duration and frequency of
 time spent in  selected activities  and time spent in
 selected microenvironments via 24-hour diaries as  part
 of  the National Human  Activity  Pattern  Survey
 (NHAPS).  Over 9,000 individuals from 48 contiguous
 states participated in NHAPS.   Approximately 4,700
 participants  also  provided information  on   seafood
 consumption, with  2,980  responding that they ate
 seafood (including shellfish, eel, or squid) in  the last
 month.  Over 900 of these participants were children
 between the ages of 1  and 17 years.  The survey  was
 conducted between October 1992 and September 1994.
 Data were collected on the (1) number of people  that
 ate seafood in  the last month, (2)  the  number of
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Chapter 10 - Intake of Fish and Shellfish
servings  of seafood  consumed, and  (3) whether  the
seafood consumed was caught or purchased.   The
participant responses  were  weighted according  to
selected demographics such as age, gender, and race to
ensure that results  were representative of the U.S.
population. In order to conform to  the standardized  age
categories  used  in  this   handbook,  U.S.  EPA
subsequently accessed the source data from U.S. EPA
(1996) and recalculated the relevant statistics using the
age categories recommended in Guidance on Selecting
Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005). The results of U.S. EPA's analysis are shown in
Table 10-11.
        Intake data were not provided in  the survey.
However, intake  of fish can be  estimated using  the
information on the number of servings of fish eaten
from this study and serving size data for each age group
from other studies (see Section 10.7.1).   Using  the
mean value for serving size and the number of servings
per month from Table 10-11, the  age-specific amount
of seafood eaten per month can be estimated.
        The advantages of NHAPS  is that  the data
were collected for a large number of individuals and are
representative  of  the  U.S.  general  population.
However, evaluation of seafood  intake was  not  the
primary purpose of the study and the data do not reflect
the  actual amount of seafood that was eaten. However,
using the assumption described above, the estimated
seafood intakes from this study are  comparable to those
observed in the U.S. EPA CSFII analysis.  It should be
noted that an all  inclusive description for seafood was
not presented in U.S. EPA (1996) or in the NHAPS
data.  It is not known if processed or canned seafood
and  seafood  mixtures   are included   in the  seafood
category.

10.3.2.2 Moya  et al,  2008  - Estimates  of Fish
        Consumption  Rates  for  Consumers   of
        Bought and Sel-caught fish in Connecticut,
        Florida, Minnesota, and North Dakota
        Moya et al. (2008) analyzed the raw data from
three   fish  consumption   studies  to  derive  fish
consumption rates for various age, gender, and ethnic
groups, and according to the source of fish consumed
(i.e., bought or caught) and habitat (i.e.,  freshwater,
estuarine, or marine).   The studies represented data
from four states: Connecticut, Florida, Minnesota  and
North Dakota.
        The  Connecticut  data  were  collected   in
1996/1997 by the University of Connecticut to obtain
estimates  of  fish   consumption  for  the   general
population,  sports  fishing  households,  commercial
fishing  households,  minority  and  limited  income
households,  women  of  child-bearing  years,  and
children.  Data were obtained from 810 households,
representing 2,080 individuals, using a combination of
a mail questionnaire that included a 10-day diary, and
personal interviews.   The response rate for this survey
was low (i.e., 6 percent for the general population and
10 percent for anglers), but  was considered to  be
adequate by the study authors (Balcom et al., 1999).
Data from this survey were available  for 54 children,
ages 0 to 15 years.
        The Florida data were collected by  telephone
and in-person interviews by the University of Florida,
and represented a random sample of 8,000 households
(telephone interviews), and 500 food stamp  recipients
(in-person interviews).   Data  from this survey were
available for 1,160 children,  ages 0 to 15 years.  The
purpose of the survey was to  obtain information on  the
quantity of fish and shellfish eaten,  as well as  the
cooking method used.  Additional information of  the
Florida survey can be found in Degner et al. (1994).
        The Minnesota  and North Dakota data were
collected by the University of North Dakota in  2000
and   represented  1,572  households   and   4,273
individuals.  Data from this survey were available  for
273 children, ages 0 to 15 years (151 in Minnesota and
122 in North Dakota). Data on purchased and caught
fish were collected for the general population, anglers,
new mothers, and Native American tribes. The survey
also collected information of the species of fish eaten.
Additional information on  this study can be found in
Benson et al. (2001).
        Moya et al. (2008) utilized the data from these
three  studies to generate  intake rates for three age
groups of children (i.e., 1 to <6 years,  6 to <11 years,
and 11  to <16 years).  These data  represented  the
general  population  of children in the  four  states.
Recreational fish  intake  rates  were not provided  for
children, and  data  were not  provided for children
according to the source  of intake (i.e., bought  or
caught)  or  habitat  (i.e.,  freshwater,  estuarine,  or
marine).  Tables 10-12 presents the intake rates for  the
general population of children who consumed fish and
shellfish in  g/kg-day,  as-consumed.    Table  10-13
provides information on the fish  intake among  the
sample populations from the four  states, based on  the
source of the fish (i.e., caught or bought). Table 10-14
provides estimated fish intake rates among the general
populations and angler populations from Connecticut,
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                                                           Chapter 10 - Intake of Fish and Shellfish
Minnesota, and North Dakota.  While the data in Tables
10-13 and 10-14 do not pertain specifically to children,
they provide an indication of the proportion of fish
consumption that is either caught or bought among the
sample population, and similarities and/or differences
between fish intake among the general population and
anglers.

10.4    MARINE RECREATIONAL STUDIES
10.4.1   Relevant Marine Recreational Studies
10.4.1.1 KCA   Research  Division,  1994  -   Fish
        Consumption  of Delaware  Recreational
        Fishermen and Their Households
        In support of the Delaware Estuary Program,
the  State  of  Delaware's Department  of  Natural
Resources and  Environmental Control conducted  a
survey of marine recreational fishermen  along the
coastal areas of Delaware between July 1992 and June
1993 (KCA Research Division, 1994).  There were two
components  of the study.   One was a field survey of
fishermen as they returned from their fishing trips and
the second part was a telephone follow-up call.   The
purpose  of  the  first  component  was   to  obtain
information on their fishing trips and on their household
composition. This  information  included the method
and location of fishing, number of fish caught and kept
by species, and weight  of each fish kept.   Household
information included race, age, gender, and number of
persons in  the  household.   Information was   also
recorded as to the location of the angler intercept (i.e.,
where the angler was interviewed) and the location of
the household.  The purpose of the second component
was to obtain information on the amount of fish caught
and kept from the fishing  trip and then eaten by the
household.    The methods used  for preparing  and
cooking the fish were also documented.
        The field portion of the study  was designed to
interview  2,000 anglers.   Data were obtained  from
1,901 anglers, representing 6,204 household members
(KCA Research Division, 1994).   A total  of 1,717 of
these were children between the ages of 0 and 19 years
of age.  While  the primary goal  of the study was to
collect data on marine recreational fishing practices, the
survey included some freshwater fishing and crabbing
sites.  Followup phone interviews typically occurred
two weeks after the field  interview and were used to
gather  information about  consumption.   Interviewers
aided respondents in their estimation of fish intake by
describing the  weight  of  ordinary products, for the
purpose of comparison to the quantity  of fish eaten.
Information on the number of fishing trips a respondent
 had taken  during the month was used to estimate
 average annual consumption rates.
         Table 10-15 presents the results of the study
 for children who consumed fish (i.e., consumers only).
 Children, ages  0  to 9 years old, had a mean fish
 consumption rate of 6.0 g/day (N = 73), while children,
 ages 10 to  19 years  old, had a mean fish consumption
 rate of 11.4 g/day (N =  102).  More than half of the
 study  respondents reported that  they skinned the fish
 that they ate (i.e., 450 out of 807  who reported whether
 they skinned their catch); the majority ate filleted fish
 (i.e., 617  out  of  794 who reported the preparation
 method used),  and over half fried their fish  (i.e., 506
 out of 875 who reported the cooking method).
         One limitation of this study is that information
 on fish consumption by children is based on anglers'
 recall of amount of fish eaten.   Also, the  study was
 limited to  one geographic  area  and  may not be
 representative of the  U.S. population.

 10.4.1.2 Alcoa,  1998   -  Draft  Report  for  the
         Finfish/Shellfish Consumption Study Alcoa
         (Point Comfort)/Lavaca Bay Superfund Site
         The  Texas Saltwater  Angler Survey was
 conducted  in 1996/97 to  evaluate the quantity and
 species of finfish and shellfish consumed by individuals
 who fish at Lavaca Bay.  The target population  for this
 study was residents  of three Texas counties: Calhoun,
 Victoria,  and Jackson (over 70 percent of the anglers
 who fish Lavaca Bay are from  these three counties).
 The random sample design specified that the population
 percentages for the counties should be as follows: 50
 percent from Calhoun, 30 percent from Victoria, and 20
 percent from Jackson.
         Each individual  in the sample population was
 sent an introductory note  describing the study and then
 was contacted  by  telephone.  People who agreed to
 participate and had taken fewer than six fishing  trips to
 Lavaca Bay were  interviewed by telephone. Persons
 who agreed to participate and had taken more than five
 fishing trips to  Lavaca Bay were sent a mail  survey
 with the  same  questions.  A total of 1,979  anglers
 participated in this survey, representing a response rate
 greater than 68 percent.  Data were collected from the
 households for men,  women, and children. There were
 4,489 records  with valid  information  and of those
 records, 320 were  for small children (less than  6 years
 old) and 749 records for youths (6 to 19 years old).
         The information collected as part of the survey
 included  recreational  fishing   trip information  for
 November  1996  (i.e.,  fishing  site,  site  facilities,
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Chapter 10 - Intake of Fish and Shellfish
distance traveled, number and species caught), self-
caught fish consumption (by the respondent, spouse and
child, if applicable), opinions on  different types of
fishing experiences, and socio-demographics.  Portion
size  for shellfish  was  determined by utilizing the
number of shrimp, crabs, oysters, etc. that an individual
consumed during a meal and the assumed tissue weight
of the particular species of shellfish.   Red drum was
the  most  commonly  consumed  self-caught  fish,
followed by speckled sea trout, flounder, all other
finfish and black drum.  For shellfish, the order from
highest to lowest amount consumed was oysters, blue
crab, and shrimp.
        Table 10-16 presents the  mean  and upper-
percentile consumption  rates  of   self-caught  fish,
expressed as grams per  day, for small children (<6
years  of age) and youths  (ages 6 to 19 years of age).
Small children consumed an average of 11.4 grams of
finfish per day while youths  consumed an average of
15.6 grams daily.  Small children consumed an average
of 0.4 g/day of shellfish, while youths consumed an
average of 0.7 g/day. Note that these data represent the
amount  of self-caught fish that is consumed from all
locations (i.e., not just from Lavaca Bay). Table 10-17
shows the average number of meals  consumed by each
age group of children and the average portion size in
grams (converted from ounces) for these meals.  Small
children and youths consumed slightly less than three
meals per month of finfish and less  than one meal per
month of shellfish.  For finfish, youths consumed an
average, per meal, portion size of 187 grams, and small
children  consumed  less  than 128  grams  per meal.
Youths consumed an average shellfish portion size of
71 grams per meal, while small children consumed 57
grams per meal.
        The study authors noted that since the survey
relied on  the anglers'  recall of meal frequency and
portion,  fish  consumption   may  have  been
overestimated.  Also, the study was conducted at one
geographic location and may not be representative of
the U.S. population.

10.5    FRESHWATER   RECREATIONAL
        STUDIES
10.5.1  Relevant Freshwater Recreational Studies
10.5.1.1  West et aL, 1989 - Michigan Sport Anglers
        Fish Consumption Survey
        The  Michigan   Sport    Anglers   Fish
Consumption Survey (West et al,  1989)  surveyed a
stratified random  sample of  Michigan residents with
fishing  licences.   The  sample was  divided  into  18
cohorts, with one cohort receiving a mail questionnaire
each week between January and May 1989. The survey
included both  a  short term recall component,  and a
usual frequency component. For the short-term recall
component, respondents were asked  to  identify  all
household members and list all fish meals consumed by
each household member during the  past  seven days.
Information on the source of the fish for each meal was
also requested  (self-caught, gift, market, or restaurant).
Respondents were asked to categorize serving size by
comparison with pictures  of  8 ounce fish portions;
serving  sizes could be designated as either "about the
same size", "less", or "more" than the size pictured.
Data on fish species, locations of self-caught  fish  and
methods of preparation and cooking were also obtained.
        The usual frequency component of the survey
asked about the frequency of fish meals during each of
the four seasons and requested respondents to give the
overall percentage  of household fish meals that came
from  recreational  sources.    A  sample of  2,600
individuals were selected from state records to receive
survey   questionnaires.    A  total of 2,334  survey
questionnaires  were  deliverable  and  1,104  were
completed and returned, giving a response rate of 47.3
percent.. The  responses represented  a total of 621
children between the ages of 1 and 20 years.
        U.S. EPA obtained the raw data from the West
et al. (1989)  survey and analyzed it to estimate mean
fish intake rates for children.  Only respondents with
information on both short term and usual  intake were
included in this analysis.  For  the  analysis, U.S. EPA
modified the serving size weights used by West et al.
(1989),  which  were 5, 8 and 10 ounces,  respectively,
for portions that were described as less, about the same,
and more than the 8 ounce picture. U.S. EPA examined
the percentiles of the distributions of fish meal sizes
reported in Pao et  al. (1982),  derived from the  1977-
1978 USDA  National  Food Consumption Survey
(NCFS), and observed that a lognormal  distribution
provided a good visual fit to the percentile data. Using
this lognormal  distribution, the mean values for serving
sizes greater than 8 ounces and for serving sizes at least
10 percent greater than 8 ounces were determined.  In
both  cases, a serving size of 12 ounces was consistent
with  the Pao et al. (1982) distribution.  The weights
used in the U.S. EPA analysis then were therefore 5, 8,
and 12 ounces for  fish meals described as less, about
the  same,  and  more  than  the  8  ounce  picture,
respectively. It should be noted that the mean serving
size from Pao  et al. (1982) was about 5  ounces, well
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                                                            Chapter 10 - Intake of Fish and Shellfish
below the value of 8 ounces most commonly reported
by respondents in the West et al. (1989) survey.
        Table 10-18 displays the mean number of total
and recreational fish meals for each household member
between age  1 and 20 years based on the seven day
recall data.   Also  shown are mean fish intake rates
derived by applying the weights described above to
each fish meal.  Intake was  calculated in units of both
grams/day  and grams/kg  body weight/day.    This
analysis was restricted to  individuals who eat fish and
who reside in households reporting some recreational
fish consumption during the previous year.   About 75
percent of  the  survey  respondents  (i.e.,  licensed
anglers) and about 84 percent of the respondents who
fished  in  the prior year reported  some  household
recreational fish consumption.
        The  advantages of this data set and analysis
are that the survey was relatively large and contained
both short-term and usual intake data.   The response
rate of this survey, 47 percent, was relatively low and
it was conducted in one geographic location.   This
study was conducted in the winter and spring months of
1989. This period does not include the summer months
when peak fishing activity can be anticipated, leading
to the possibility that intake  results based on the 7 day
recall data may understate individuals' usual (annual
average) fish consumption.

10.5.1.2 Benson et aL, 2001  - Fish Consumption
        Survey: Minnesota and North Dakota
        Benson  et  al  (2001)  conducted  a  fish
consumption  survey  among  Minnesota  and  North
Dakota residents.   The target population included the
general population,  licensed anglers, and members of
Native American  tribes.   The survey focused  on
obtaining the most recent year's fish intake from all
sources,  including locally  caught  fish.     Survey
questionnaires were mailed to  potential respondent
households.   For the entire  population, approximately
1,570 surveys were returned completed (out of 7,835
that were mailed out).  Information on fish consumption
by children was collected  if  they were a  part of a
respondent household. Data were collected for a total
of 604 children (ages 0 to  14 years) in Minnesota and a
total of 375  children  (ages 0 to 14 years) in  North
Dakota.  Among these respondents, data  on  sport-
caught fish intake  were available for 582  Minnesota
children and 343 North Dakota children.  Table 10-19
presents the  recreational  freshwater intake rates for
children (ages 0 to  14 years). Rates for both purchased
and sports-caught fish are provided. For Minnesota, the
 50th percentile sports-caught fish consumption rate was
 1.2 grams/day and the 95th percentile rate was 14.6
 grams/day.   For  North Dakota, the  50th percentile
 sports-caught fish consumption rate was 1.7 grams/day,
 and the 95th percentile rate was 23.3 grams/day.  Intake
 rates of purchased fish were higher for both Minnesota
 (3.6  grams/day 50th  percentile; 30.9  grams/day 95th
 percentile)  and North Dakota (4.7 grams/day 50th
 percentile; 42.8 grasm/day 95th percentile).
         An advantage of this study is its large overall
 sample size. A limitation of the study is the broad age
 range of children used (i.e., 0 to 14 years).  Also, the
 study was limited to two states.  Therefore, the results
 may not be representative of the U.S. population as a
 whole..

 10.6    NATIVE AMERICAN STUDIES
 10.6.1   Relevant Native American Studies
 10.6.1.1 Columbia   River   Inter-Tribal   Fish
         Commission (CRITFC),  1994  - A  Fish
         Consumption Survey of the  Umatilla, Nez
         Perce, Yakama, and Warm Springs Tribes of
         the Columbia River Basin
         The  Columbia   River  Inter-Tribal  Fish
 Commission  (CRITFC)  (1994)  conducted  a fish
 consumption survey among four Columbia River Basin
 Native American tribes during the  fall and winter of
 1991-1992.   The  target population included all adult
 tribal members who lived  on  or  near the  Yakama,
 Warm  Springs, Umatilla  or Nez Perce reservations.
 The survey was based on a stratified random sampling
 design where respondents were selected from patient
 registration files  at the Indian  Health  Service.  The
 overall response rate was 69 percent yielding a sample
 size  of 513  tribal members, 18 years old and above.
 Interviews  were performed in person at a  central
 location  on  the  member's   reservation.     Each
 participating adult was asked if there were any children
 5 years old or younger in his or her household.  Those
 responding affirmatively were  asked a set of survey
 questions about the  fish consumption  patterns  of the
 youngest  child in the household  (CRITFC,  1994).
 Information for 204 children, 5  years old and younger,
 was  provided by  participating  adult respondents.
 Consumption data were available  for 194 of these
 children.
         Participants  were  asked  to   describe  and
 quantify  all food and drink  consumed  during the
 previous  day.  They were then asked  to  identify the
 months in which they ate the most and the least fish,
 and  the number of fish meals consumed per week
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Chapter 10 - Intake of Fish and Shellfish
during each of those periods and an average value for
the whole year.  The typical portion  size (in ounces)
was determined with the aid of food models provided
by the questioner.  The next set of questions identified
specific species of fish and addressed the number of
times per month each was eaten,  as well as what parts
(e.g., fillet, skin, head, eggs, bones, other) were eaten.
Respondents were then asked to identify the frequency
with which they  used various preparation methods,
expressed as a percentage.   Respondents sharing a
household with a child, aged 5 years or less, were asked
to repeat the serving size, eating frequency, and species
questions  for the  child's  consumption behavior.  All
respondents were asked about the geographic origin of
any fish they personally caught and consumed,  and to
identify the major sources offish in their diet (e.g., self-
caught, grocery store, tribe, etc.).  Fish  intake rates
were calculated by multiplying the annual frequency of
fish meals by the average serving size per fish meal.
        The population sizes of the four tribes were
highly unequal,  ranging from 818 to 3,872 individuals
(CRITFC,  1994).   In order to  ensure  an adequate
sample size from each tribe, the study was designed to
give  nearly  equal sample  sizes  for   each   tribe.
Weighting factors were applied to the pooled data (in
proportion to tribal population  size) so that the  survey
results  would  be representative  of  the  overall
population of the four  tribes for adults only. Because
the sample size for children was considered small, only
an  unweighted  analysis  was  performed for  this
population.   Based  on  a  desired  sample  size of
approximately 500 and an expected response rate of 70
percent, 744 individuals were selected at random from
lists of eligible  patients; the  numbers from each tribe
were approximately equal.
        Intake  rates were calculated  for children for
which both the number of fish meals per week and
serving size information were available. A total of 49
percent of respondents of the total survey population
reported that they caught fish from the Columbia River
basin and its tributaries for personal use or for tribal
ceremonies and distributions to other tribe members
and 88 percent reported that they obtained fish from
either  self-harvesting,  family  or  friends,  at   tribal
ceremonies or from tribal distributions.   Of all fish
consumed, 41  percent came from  self or  family
harvesting, 11 percent from the harvest of friends, 35
percent from tribal ceremonies or distribution, 9 percent
from stores and 4 percent from other sources (CRITFC,
1994).
        Of the  204  children,  the  total number of
respondents used in the analysis varied from 167 to
202, depending  on the topic (amount and  species
consumed,  fish  meals   consumed   /week,   age
consumption began, serving size, consumption of fish
parts) of the analysis.  The unweighted mean for the age
when children begin eating fish was 13.1 months of age
(N = 167). The unweighted mean number of fish meals
consumed per week  by children was  1.2 meals per
week (N =  195) and the unweighted mean serving size
of fish for children aged five years old and less was 95
grams (i.e., 3.36  ounces) (N = 201). The unweighted
percent  of fish consumed by children by species was
82.7 percent for salmon, followed by 46.5 percent (N =
202) for trout.  The analysis of seasonal intake showed
that  May  and June tended to be high-consumption
months  and December and January low consumption
months.     Table  10-20  presents  the  fish  intake
distribution for children under 5 years of age (N = 194).
The mean intake rate was 19.6 g/day (N = 194) and the
95th  percentile was approximately 70 g/day.   These
mean intake rates include both consumers and non-
consumers. These values are based on survey questions
involving  estimated  behavior throughout the  year,
which survey participants answered in terms of meals
per week or per  month and typical serving  size per
meal.   Table  10-21  presents consumption rates for
children who  were reported to consume particular
species offish.
        The authors noted that some non-response bias
may have occurred in the  survey since respondents
were  more  likely to  be female  and live near the
reservation than  non-respondents.  In  addition, they
hypothesized that non-consumers may have been more
likely to be non-respondents than fish consumers since
non-consumers may have thought their contribution to
the survey would be meaningless; if such were the case,
this study would overestimate the mean intake rate.  It
was also noted that the timing of the survey, which was
conducted during low fish consumption  months, may
have led to underestimation of actual fish consumption;
the  authors  conjectured that an individual may have
reported higher  annual consumption  if interviewed
during a relatively high consumption month and lower
annual consumption if interviewed during a relatively
low  consumption month.   Finally, with  respect to
children's intake, it was observed that  some of the
respondents provided  the same information for their
children as for themselves; thereby, the reliability of
some of these data is questioned (CRITFC, 1994).  The
combination of four different tribes' survey responses
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                                                            Chapter 10 - Intake of Fish and Shellfish
into a single pooled data set is somewhat problematic.
The data presented in Table 10-20 are unweighted and
therefore contain a bias toward the smaller tribes, who
were oversampled compared to the larger tribes.
         The limitations of this study, particularly with
regard to the estimates of children's consumption, result
in a high degree of uncertainty in the estimated rates of
consumption.  However, it is one  of a relative few
studies  aimed at  the  fish consumption  patterns  of
Native Americans.  It should be noted that the selection
process  for children may be biased because  the 204
children  included  in the study  were  not  selected
independently, but were identified through a parent's
patient registration file.  This indicates that  children
from  larger households would be  less likely  to be
chosen to participate in the  study than would be the
case if the children themselves, rather than the parents,
were randomly selected.

10.6.1.2  Toy et al, 1996 - A Fish  Consumption
         Survey  of the Tulalip and Squaxin Island
         Tribes of the Puget Sound Region
         Toy et al.  (1996)  conducted  a  study  to
determine fish and shellfish consumption rates of the
Tulalip and Squaxin Island tribes living in the Puget
Sound region. These two Indian tribes were selected on
the basis of judgment that they would be representative
of the expected range of fishing and fish consumption
activities  of the  fourteen   tribes  in  the  region.
Commercial fishing is  a major source  of income for
members of both tribes; some members the  Squaxin
Island tribe also participate in commercial shellfishing.
Both  tribes participate in  subsistence  fishing and
shellfishing.
         Fish consumption patterns for  the two tribes
were estimated using a survey in which sample sizes
were calculated separately for each tribe.  This allowed
separate  analyses to be conducted for each tribe. The
appropriate sample size was  calculated based on the
enrolled  population  of each  tribe and  a  desired
confidence interval of ±20 percent from the mean, with
an additional 25 percent added to the total to allow for
non-response or unusable data.  The target population,
derived from lists of enrolled tribal members provided
by the tribes, consisted of enrolled tribal members aged
18 years and older and children aged five years and
younger  living in the same household as an  enrolled
member. Only members living on or within 50 miles of
the reservation were considered for the survey.  Each
eligible enrolled tribal member was assigned a number,
and computer-generated random numbers were used to
 identify the  survey  participants.  Children were  not
 sampled directly, but through adult  members of their
 household; if one adult had more than one eligible child
 in his or her household, one of the children was selected
 at random.    This indirect  sampling  method was
 necessitated  by the  available tribal  records, but may
 have  introduced  sampling  bias  to the process  of
 selecting children for the study.  A  total of 190 adult
 tribal members (ages 18 years old and older) and 69
 children between ages birth and 5 years old (i.e., 0 to
 <6 years) were surveyed about their consumption of 52
 fish  species in six  categories:  anadromous,  pelagic,
 bottom, shellfish, canned tuna, and miscellaneous.
         Respondents   described  their  consumption
 behavior for the past year in terms of frequency of fish
 meals eaten per week or per month, including seasonal
 variations in consumption rates.   Portion sizes (in
 ounces) were estimated with the aid of model portions
 provided by the questioner.  Data were also collected
 on fish parts consumed, preparation  methods, patterns
 of acquisition for all fish and shellfish consumption,
 and  children's  consumption rates.  Interviews were
 conducted between February and May 1994.   The
 response rate for adults was 77 percent for the Squaxin
 Island tribe and 76 percent for the Tulalip tribes.
         The mean and median  consumption rates for
 children 5 years and younger for both tribes combined
 were 0.53 and 0.17 g/kg-day, respectively (Table  10-
 22).  Squaxin Island children tended to consume more
 fish than Tulalip children (mean 0.83 g/kg-day vs. 0.24
 g/kg-day).   The data were  insufficient to  allow re-
 analysis to fit the data  to the standard U.S. EPA age
 categories used elsewhere in this handbook.
         One limitation associated with this study is
 that although data from the Tulalip and Squaxin Island
 tribes may be representative of consumption  rates of
 children in these specific tribes, fish consumption rates,
 habits, and patterns can vary among tribes and other
 sub-populations; as a result,  the consumption rates of
 these two tribes may not be useful as a surrogate for
 consumption  rates of other  Native American tribes.
 Furthermore, there were differences in consumption
 patterns between the two tribes included in this study;
 the study provided data for each tribe and for the pooled
 data from both tribes, but the latter may  not be  a
 statistically valid  measure  for  tribes in the region.
 There might also be a possible bias due to the time the
 survey was conducted; many species in the survey are
 seasonal.  For example, because of the timing of the
 survey,  respondents may have  overestimated  annual
 consumption.
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Chapter 10 - Intake of Fish and Shellfish
10.6.1.3 Duncan, 2000 - Fish Consumption Survey of
        the  Squamish Indian  Tribe of the Port
        Madison Indian Reservation, Puget Sound
        Region
        The Squamish Tribal  Council conducted a
study of the Squamish tribal  members living on and
near the Port Madison Indian Reservation in the Puget
Sound region (Duncan, 2000). The study was funded
by  the Agency for  Toxic Substances and Disease
Registry (AT SDR) through a grant to the Washington
State Department of Health. The purpose of the study
was to determine seafood consumption rates, patterns,
and habits of the members of the Squamish Tribe.  The
second objective was to identify cultural practices and
attributes that affect  consumption rates, patterns and
habits of members of the Squamish Tribe.
        A systematic random  sample of adults, defined
as individuals age  16 years and older, were selected
from a sorted Tribal enrollment roster.  The study had
a  participation  rate  of 64.8  percent, which  was
calculated on the basis of 92 respondents out of a total
of 142 potentially  eligible adults on the list of those
selected  into  the  sample.   Consumption  data  for
children under six years of age were gathered through
adult respondents who had  children in this age group
living in the household at the time of the survey.  Data
were collected for 31 children under six years old.
        A survey  questionnaire was administered by
personal interview. The survey included four parts: (1)
24-hour  dietary recall; (2)  identification, portions,
frequency of consumption, preparation, harvest location
offish; (3) shellfish consumption, preparation, harvest
location;  and (4) changes  in consumption  over time,
cultural  information,   physical   information,   and
socioeconomic  information.   A display booklet was
used to assist respondents  in providing consumption
data and  identifying harvest locations  of seafood
consumed.   Physical models  of finfish and shellfish
were constructed to assist respondents in determining
typical food portions.   Finfish and shellfish  were
grouped into categories based on  similarities in  life
history as well as practices of Tribal members who fish
for subsistence, ceremonial, and commercial purposes.
        Interviewers collected  data for 31  children
under six years of age.  Table 10-23 provides  the
consumption rates for children in units of g/kg-day for
all respondents.  Table 10-24 provides consumption
rates for consumers only.  Because all of the children
involved in the  study consumed some form  of fish, the
consumption distribution of all fish is the same in both
tables.   The  mean,  median,  and  95th  percentile
consumption rates of all fish were  1.5 g/kg-day, 0.72
g/kg-day, and 7.3 g/kg-day, respectively.  These values
are significantly greater than  those presented for the
Tulalip and Squaxin Island tribes (Toy et al, 1996; see
Section  10.6.1.2).  This disparity illustrates the high
degree of variability found between tribes even within
a small geographic region (Puget Sound) and indicates
that exposure and risk assessors should exercise care
when imputing fish consumption rates to a population
of interest using data from tribal studies.
        A limitation of this study  is that the sample
size for children was  fairly small (31  children).  An
important attribute of this survey is that it provided
consumption  rates  by individual  type  of fish  and
shellfish.

10.6.1.4 Polissar et aL, 2006 - A Fish  Consumption
        Survey of the Tulalip and Squaxin Island
        Tribes   of  the   Puget    Sound
        Region-Consumption    Rates  for
        Fish-consumers Only
        Using fish consumption data from the Toy et
al. (1996) survey of the  Tulalip and Squaxin Island
tribes of Puget Sound, Polissar et al. (2006) calculated
consumption  rates for various  fish species  groups,
considering only the  consumers of fish within each
group.   Weight-adjusted  consumption  rates  were
calculated by tribe,  age, gender, and species groups.
Species  groups  (anadromous, bottom,  pelagic,  and
shellfish) were defined by life history and distribution
in the water column.   Data were available for  69
children, birth to <6 years of age; 18 of these children
had no reported fish consumption and were excluded
from the analysis.  Thus, estimated fish consumption
rates are based on data for 51 children; 15 from the
Tulalip  tribe  and 36  from  the  Squaxin Island tribe.
Both  median and  mean  fish consumption rates  for
children within  each tribe were calculated in terms  of
grams per kilogram of body weight per day (g/kg-day).
Anadromous fish and shellfish were the groups of fish
most frequently consumed by both tribes and genders.
The  consumption rates for groups of  fish  differed
between the tribes.  The distribution of consumption
rates was skewed toward large values.  The estimated
mean consumption rate of all fish was 0.45 g/kg-day for
the Tulalip children and 2.9 g/kg-day for the Squaxin
Island children  (Table 10-25).  Table 10-26 presents
consumption rates for children by species and gender.
        Because this study used the  data originally
generated by Toy et  al.  (1996) the  advantages and
limitations associated with the Toy et al. (1996) study,
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                                                          Chapter 10 - Intake of Fish and Shellfish
as described in Section 10.6.1.2, also apply to this
study. However, an advantage of this study is that the
consumption rates are based only on individuals who
consumed fish within the selected categories.

10.7    SERVING SIZE STUDY
10.7.1   Smiciklas-Wright  et  al.,  2002  - Foods
        Commonly  Eaten in  the  United States:
        Quantities Consumed per Eating Occasion
        and in a Day,1994-1996
        Using data gathered in the  1994-96 USDA
CSFII, Smiciklas-Wright et al. (2002)  calculated
distributions for the quantities of canned tuna and other
finfish consumed per eating occasion by members of
the U.S. population (i.e., serving sizes), over a 2-day
period. The estimates of serving size are based on data
obtained from 14,262 respondents, ages 2 years and
above, who  provided  2  days of  dietary intake
information. A total of 4,93 9 of these respondents were
children, ages 2 to 19 years of age. Only dietary intake
data from users of the specified food were used in the
analysis (i.e., consumers only data).
        Table 10-27 and Table 10-28 present serving
size data for canned tuna and other finfish, respectively.
These data are presented on  an as-consumed basis
(grams), and represent the quantity of fish consumed
per eating occasion. These estimates may be useful for
assessing acute exposures to contaminants in specific
foods,  or  other assessments  where the  amount
consumed per eating occasion is necessary.
        The advantages of using these data are that
they were derived from the USDA CSFII and are
representative of the U.S. population.  The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
for individual foods consumed as ingredients of mixed
foods. Mixed foods were disaggregated via recipe files
so that the individual ingredients could be  grouped
together  with  similar  foods   that  were   reported
separately.   Thus, weights of  foods  consumed  as
ingredients were  combined with weights  of foods
reported  separately  to  provide a  more  thorough
representation of consumption. However, it should be
noted that  since  the recipes  for  the mixed  foods
consumed by respondents were  not provided by the
respondents, standard recipes were used. As a result,
the estimates  of the quantity of  some food  types are
based on assumptions about the types and quantities of
ingredients consumed as part of mixed foods.
 10.8    OTHER FACTORS TO CONSIDER FOR
         FISH CONSUMPTION
         Other factors to consider when using the
 available survey data include location, climate, season,
 and ethnicity of the angler or consumer population, as
 well as the parts offish consumed and the methods of
 preparation.    Some  contaminants  (for  example,
 persistent, bioaccumulative, aand toxic contaminants
 such as dioxins and poly chlorinated biphenyls) have the
 affinity to accumulate more in certain tissues, such as
 the fatty tissue, as well as in certain internal organs.
 The  effects  of cooking methods for various  food
 products on the levels of dioxin-like compounds have
 been addressed by evaluating a number of studies in
 U.S. EPA (2003). These studies showed various results
 for contamination losses based on the methodology of
 the study and the method of food preparation.  The
 reader  is referred to U.S.  EPA  (2003) for a detailed
 review of these studies. Additionally, users of the data
 presented in this chapter should  ensure that consistent
 units are used for intake rate  and concentration of
 contaminants in fish.  The following sections provide
 information on converting between wet weight and dry
 weight, and between wet weight and lipid weight.

 10.8.1   Conversion Between Wet and Dry Weight
         The intake data presented in this chapter is
 reported in units of wet weight (i.e., as-consumed or
 uncooked weight of fish consumed per  day or per
 eating occasion). However, data on the concentration
 of contaminants in fish may be reported in units of
 either wet or dry weight.(e.g.,  mg contaminant per
 gram-dry-weight of fish).  It is essential that exposure
 assessors be aware of this difference so that they may
 ensure  consistency between the units used for intake
 rates and those used for concentration data (i.e., if the
 contaminant concentration is measured in dry weight of
 fish, then the dry weight units should be used for fish
 intake values).
         If necessary, wet weight (e.g., as-consumed)
 intake rates may be converted to dry weight intake rates
 using the moisture content percentages presented in
 Table 10-29 and the following equation:
     IRdw ~  IR ww
                        WO-W
                          100
(Eqn. 10-1)
Page
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Chapter 10 - Intake of Fish and Shellfish
where:
        W
                dry weight intake
                rate;
                wet weight intake
                rate; and
                percent   water
                content.
Alternately, dry weight residue levels in fish may be
converted to wet weight residue levels for use with wet
weight (e.g., as-consumed) intake rates, as follows:
                      9100?
      ._,     _    ._,    . 1\J\J .
        ww '     dw £   10Q   ?
                      (Eqn. 10-2)
where:
        W
                wet weight intake
                rate;
                dry weight intake
                rate; and
                percent   water
                content.
The moisture content data presented in Table 10-29 are
for selected fish taken from USD A, 2007.

10.8.2   Conversion Between Wet Weight and Lipid
        Weight Intake Rates
        In  some   cases,   the  residue  levels  of
contaminants in fish are reported as the concentration
of contaminant per  gram  of fat.   This  may  be
particularly true for lipophilic compounds.  When using
these  residue  levels, the  assessor  should ensure
consistency in the exposure assessment calculations by
using consumption  rates that are based on the amount
of fat consumed for  the fish product of interest.
        If necessary, wet weight (e.g., as-consumed)
intake rates may be converted to lipid weight intake
rates using the fat content  percentages presented in
Table 10-29 and the following equation:
       IR
         Iw
IR
                       ? L  ?
where:
        IR,,
(Eqn. 10-3)
                lipid weight intake
                rate;
                wet weight intake
                rate; and
                            L               =       percent lipid  (fat)
                                                    content.

                    Alternately, wet weight residue levels in fish may be
                    estimated by multiplying the levels based on fat by the
                    fraction of fat per product as follows:
                                                 WW
                                                                           (Eqn. 10-4)
                                                        where:
                            C^            =       wet weight intake
                                                    rate;
                            Clw             =       lipid weight intake
                                                    rate; and
                            L               =       percent lipid  (fat)
                                                    content.

                    The resulting residue  levels  may  then  be used  in
                    conjunction  with  wet weight  (e.g.,  as-consumed)
                    consumption rates.  The total fat content data presented
                    in Table 10-29 are for selected fish taken from USD A,
                    2007.
                                        10.9
                            REFERENCES FOR CHAPTER 10
Alcoa  (1998)  Draft report  for  the  finfish/shellfish
        consumption  study  Alcoa  (Point
        Comfort)/Lavaca Bay Superfund Site, Volume
        B7b: Bay System Investigation Phase 2. Point
        Comfort,  TX:  Aluminum  Company  of
        America.
Balcom, N.; Capacchione, C.; Hirsch D.W.  (1999)
        Quantification  of seafood consumption  rates
        for  Connecticut.    Report prepared for the
        Connecticut  Department  of Environmental
        Protection,  Office  of Long Island  Sound
        Programs, Hartford, CT.  Contract No. CWF-
        332-R.
Benson, S.;  Crocker, C.; Erjavec,  J.; Jensen, R.R.;
        Nyberg, C.M.; Wixo, C.Y.; Zola, J.M. (2001)
        Fish consumption  survey:  Minnesota  and
        North Dakota.  Report prepared for the U.S.
        Department of Energy by the  Energy  and
        Environmental  Research Center, University of
        North  Dakota,  Grand  Forks,  ND.  DOE
        Cooperative  Agreement  No,   DE-FC26-
        98FT40321.
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                                                          Chapter 10 - Intake of Fish and Shellfish
Columbia   River  Inter-Tribal   Fish   Commission
        (CRITFC) (1994) A fish consumption survey
        of the Umatilla, Nez Perce,  Yakama  and
        Warm Springs tribes  of the Columbia River
        Basin.  Technical Report 94-3.  Portland, OR:
        CRITFC.
Degner, R.L.; Adams,  C.M.; Moss,  S.D.; Mack, S.K.
        (1994)  Per   capita  fish and  shellfish
        consumption  in  Florida.  Gainesville,  FL:
        University of Florida.
Duncan, M. (2000) Fish consumption  survey of the
        Squamish  Indian Tribe of the  Port Madison
        Indian Reservation,  Puget  Sound  Region.
        Squamish, WA: The  Squamish Tribe, Port
        Madison Indian Reservation.
KCA Research Division (1994) Fish consumption of
        Delaware  recreational fishermen and  their
        households.    Prepared  for  the  State  of
        Delaware, Department of Natural Resources
        and Environmental  Control in support of the
        Delaware Estuary Program, Dover, DE.
LSRO   (1995)  Life   Sciences  Research   Office,
        Federation of American Societies  for
        Experimental   Biology   Prepared  for  the
        Interagency Board for Nutrition Monitoring
        and  Related  Research.  Third  Report on
        Nutrition Monitoring  in the United  States:
        Volume 1. U.S. Government Printing Office,
        Washington, DC.
Moya, J. (2004) Overview offish consumption rates in
        the United States.  Hum  Eco  Risk  Assess
        10:1195-1211.
Moya,  J.;  Itkm, C.;  Selevan, S.G.; Rogers, J.W.;
        Clickner,  R.P.  (2008)  Estimates  of fish
        consumption rates for consumers of  bought
        and self-caught fish in Connecticut, Florida,
        Minnesota, and North Dakota.   Sci  Tot
        Environ (in press).
Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J.
        (1982) Foods  commonly eaten by individuals:
        amount per day and per eating occasion.  U.S.
        Department of Agriculture.  Home Economic
        Report No. 44.
Polissar,  N.L.; Neradilek, B.; Liao, S.; Toy, K.A.;
        Mittelstaedt, G.D. (2006) A fish consumption
        survey of the Tulalip and Squaxin Island tribes
        of the Puget  Sound  region -   Consumption
        rates  for   fish-consumers   only.    Report
        prepared   by  Mountain-Whisper-Light
        Statistical Consulting,  Seattle, WA.
 Smiciklas-Wnght, H.;  Mitchell, D.C.;  Mickle,  S.J.;
         Cook, A.J.;  Goldman,  J.D.  (2002) Foods
         commonly eaten in the United States 1994-
         1996:  Quantities  consumed  per  eating
         occasion and in a day.  U.S. Department of
         Agriculture.  Agricultural  Research  Center
         NFS Report No. 96-5, 264 pp.
 Toy, K.A.; Polissar, N.L.; Liao, S.; Mittelstaedt, G.D.
         (1996)  A fish consumption survey of the
         Tulalip and Squaxin Island Tribes of the Puget
         Sound Region.   Marysville, WA:  Tulalip
         Tribes, Department of Environment.
 USDA, Agricultural Research  Service. (2007) USDA
         National  Nutrient  Database  for  Standard
         Reference,  Release   20.  Nutrient  Data
         Laboratory Home Page:
         http://www.ars.usda. gov/ha/hhnrc/ndl.
 U.S. EPA (1996) Descriptive  statistics  tables from a
         detailed  analysis  of  the  National  Human
         Activity   Pattern  Survey  (NHAPS)  data.
         Washington,  DC:  Office  of Research  and
         Development. EPA/600/R-96/148.
 U.S. EPA (1998) Guidance for conducting fish  and
         wildlife  consumption  surveys.   Washington,
         DC: Office of Water. EPA-823-B-98-007.
 U.S.  EPA   (2002)  Estimated  Per  Capita   Fish
         Consumption   in  the  United  States.
         Washington,   DC:     Office  of  Water.
         EPA/821/C-02/003.
 U.S.  EPA  (2003)  Exposure  and human  health
         reassessment of 2,3,7,8-tetrachlorodibenzo-p-
         dioxin (TCDD) and related compounds, Part
         1:   Estimating  exposure   to  dioxin-like
         compounds,   Volume  2:  Properties,
         environmental  levels,  and   background
         exposures.  (National Academy of Sciences
         Review  Draft).  Washington, DC:  Office of
         Research and Development, National Center
         for   Environmental   Assessment.
         www. epa. eov/N CH A/dioxin.
 U.S. EPA (2005)  Guidance on selecting age groups for
         monitoring and assessing childhood exposures
         to environmental contaminants.  Washington,
         DC:  U.S. Environmental Protection Agency.
         EPA/630/P-03/003F.
 West, P.C.; Fly, M.J.; Marans, R.; Larkm,  F. (1989)
         Michigan  sport  anglers fish  consumption
         survey.   A report to the  Michigan Toxic
         Substance  Control  Commission.   Michigan
         Department  of Management  and  Budget
         Contract No. 87-20141.
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Chapter 10 - Intake of Fish and Shellfish
                                Table 10-3. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                                 General Population Children Ages 3 to 17 Years - g/day, As-Consumed
  Age (years')
                  Sample Size
                                    Mean (90% CD
                                                         90th % (90% BIV
                                                                   95th % (90% BIV
                                                99th % (90% BIV
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
1.5(1.2-1.8)
2.1 (1.4-2.9)
3.0(2.2-3.8)
3.4(1.6-5.3)
0.1 (0.0-1.0)
0.0 (0.0-0.6)
1.4(0.5-5.5)
0.0(0.0-1.5)
5.1(4.1-6.2)
5.9(3.2-13)
18(15-21)
13* (5.2-29)
39 (33-44)
61* (51-86)
70* (56-75)
81* (42-117)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
3.7(3.2-4.3)
4.2(3.5-4.9)
5.5 (4.2-6.7)
4.7(2.9-6.4)
11 (10-13)
13 (9.7-17)
14(9.8-21)
0.0 (0.0-6.9)
28 (24-29)
29 (28-34)
39(31-50)
24* (7.8-71)
60 (52-71)
79* (49-84)
102* (84-114)
108* (68-1 19)
                                                          All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,391
1,670
1,005
363
5.2(4.6-5.8)
6.3 (5.3-7.3)
8.5 (6.9-10)
8.1 rs.4-in
19(15-21)
24 (21-27)
28(25-31)
19 r?.0-4n
35(31-40)
40(34-51)
60 (53-74)
74* (29-90)
72(67-81)
108* (92-131)
122* (107-132)
142* (-108-2001
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
 The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
                                Table 10-4. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                              General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed
  Age (years)     Sample Size
                     Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,112
1,553
975
360
83 (67-99)
59 (39-79)
53 (42-64)
49 (23-76)
0 (0-55)
0 (0-5)
27 (0-78)
0 (0-33)
284(240-353)
178 (88-402)
312(253-390)
213* (106-390)
2,317(1,736-2,463)
1,662* (1,433-2,335)
1,237* (950-1,521)
1,186* (600-2,096)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,112
1,553
975
360
209(182-237)
150(123-177)
109(84-133)
75(46-103)
614(525-696)
416 (326-546)
338(179-413)
0(0-124)
1,537(1,340-1,670)
1,055(969-1,275)
821 (629-1,034)
381* (132-951)
3,447 (3,274-3,716)
2,800* (2,021-3,298)
1,902* (1,537-2,366)
1,785* (1,226-2,342)
                                                          All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,112
1,553
975
360
292 (259-326)
209 (176-242)
162(133-191)
124r83-1651
1,057(931-1,232)
780 (644-842)
570 (476-664)
261 n 10-6001
1,988(1,813-2,147)
1,357(1,173-1,452)
1,051 (991-1,313)
1.029* (390-1.239}
4,089 (3,733-4,508)
3,350* (2,725-4,408)
2,305* (1,908-2,767)
2.359* r2.096-2.6761
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
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                                                                    Chapter 10 - Intake of Fish and Shellfish
                              Table 10-5.  Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                                 General Population Children Ages 3 to 17 Years - g/day, As-Consumed
  Age (years)    Sample Size
                    Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
442
147
107
28
27(23-31)
43 (32-55)
49 (39-59)
76* (59-93)
73 (65-79)
122* (83-187)
127* (104-148)
159* (151-171)
96(87-110)
187* (115-260)
150* (135-193)
168* (159-484)
159* (136-260)
260* (172-261)
307* (193-384)
372* (171-484)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
682
217
122
37
45 (41-48)
59(53-66)
72 (60-85)
97* (65-129)
91 (84-105)
129(112-158)
165* (158-203)
219* (180-238)
119(102-143)
159* (135-219)
204* (169-227)
238* (180-293)
228* (169-293)
243* (219-292)
246* (214-269)
365* (230-428)
                                                           All Fish
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Aees 16 to 17
834
270
172
52
50 (46-54)
71 (64-77)
80 (70-89)
104* (75-1331
103(94.5-125)
155(130-183)
167* (154-193)
201* (167-2431
134(121-152)
218* (198-261)
209* (206-257)
242* (216-4841
260* (195-293)
281* (260-292)
285* (264-327)
451* (293-4841
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
 The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
                              Table 10-6.  Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                               General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed
  Age (vearsl    Sample Size
                               Mean (90% CI1
                                                       90th % (90% BI1'
                                                                   95th % (90% BI1'
                                                99th % (90% BI1'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
416
132
101
28
1,532(1,320-1,743)
1,296(1,004-1,588)
869(725-1,013)
1,063* (781-1,346)
4,307 (3,472-4,624)
3,453* (2,626-4,671)
2,030* (1,628-2,104)
2,293* (2,096-2,577)
5,257(4,926-5,746)
4,675* (3,459-8,816)
3,162* (2,104-3,601)
2,505* (2,096-6,466)
10,644* (9,083-12,735)
8,314* (4,684-9,172)
4,665* (3,597-7,361)
5,067* (2,295-6,466)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
640
203
120
37
2,492 (2,275-2,709)
2,120(1,880-2,361)
1,427(1,203-1,651)
1,534* (1,063-2,004)
5,303 (4,873-5,930)
4,950 (4,043-5,384)
2,971* (2,858-3,741)
3,602* (2,974-4,685)
6,762(6,097-7,168)
5,817* (5,333-6,596)
4,278* (3,026-4,766)
4,475* (3,068-4,685)
11,457* (7,432-14,391)
8,092* (6,146-9,184)
5,214* (4,647-5,646)
4,982* (3,467-5,238)
                                                           All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
779
250
164
52
2,828 (2,608-3,049)
2,375(2,199-2,551)
1,533(1,384-1,682)
1.578* (1.187-1.9691
5,734(5,268-6,706)
5,135(4,684-5,816)
3,207* (2,945-3,485)
3.468* (2.676-4.7521
7,422 (6,907-8,393)
6,561* (5,404-8,816)
3,925* (3,485-4,764)
4.504* (3.709-6.4661
13,829* (11,349-14,391)
9,179* (8,130-10,485)
5,624* (4,764-6,929)
5.738* (4.752-6.4661
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
Page
10-18
                                                      Child-Specific Exposure Factors Handbook
                                                     	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
                                Table 10-7.  Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                             General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight
  Age (years)
       Sample Size
Mean (90% CI)
90th (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,391
1,670
1,005
363
2.2(1.8-2.6)
3.0(1.9-4.1)
4.3 (3.2-5.4)
4.6(2.2-6.9)
0.1(0.0-1.5)
0.0(0.0-0.5)
2.3(0.1-7.7)
0.0(0.0-1.9)
12(10-14)
13 (4.8-20)
26 (21-29)
19* (13-37)
52 (46-62)
78* (64- 111)
95* (83-1 10)
109* (58-155)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,391
1,670
1,005
363
5.5 (4.8-6.2)
5.6 (4.6-6.5)
7.6 (5.9-9.4)
6.1(3.7-8.4)
20 (17-23)
19 (14-24)
25 (16-35)
0.0 (0.0-9.3)
39(38-41)
38 (38-42)
56 (45-67)
29* (12-91)
82 (73-95)
100* (63-111)
132* (110-149)
136* (92.0-177)
                                                           All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
4,391
1,670
1,005
363
7.7(6.9-8.6)
8.5(7.1-10)
12(9.7-14)
11 r?.0-141
33 (28-34)
33 (27-38)
43(37-51)
29 (9.4-49)
51 (46-57)
56 (50-70)
87(70-103)
84* (42-114)
101 (89.1-111)
144* (117-183)
171* (148-176.8)
193* (121-266)
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
                                 Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
                            General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight
  Age (years)   Sample Size     Mean (90% CI)
                                        90th % (90% BI)'
                                        95th % (90% BI)'
                                            99th % (90% BI)'
                                                      Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
4,112
1,553
975
360
124(103-146)
84(55-112)
77 (60-94)
65 (30-100)
0 (0-83)
0(0-1)
20(0-116)
0 (0-23)
712(599-784)
354(116-685)
477(411-618)
285* (167-491)
3,091 (2,495-3,475)
2,322* (1,856-2,994)
1,610* (1,358-2,203)
1,542* (760-2,767)
                                                           Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
4,112
1,553
975
360
309 (270-348)
198(161-235)
153(117-189)
98(58-137)
1,108(984-1,332)
600 (474-733)
481 (361-609)
0(0-177)
2,314(2,096-2,481)
1,481(1,310-1,549)
1,251 (808-1,390)
460* (197-1,079)
4,608(4,301-5,354)
3,684* (2,458-4,353)
2,381* (2,162-3,207)
2,148* (1,648-3,901)
                                                           All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aaes 16 to 17
4,112
1,553
975
360
433 (385-482)
282(235-328)
231(186-275)
163(108-219}
1,841 (1,555-1,957)
1,045 (745-1,219)
824(657-952)
406 (-145-7561
2,964(2,790-3,194)
1,854(1,638-2,175)
1,531(1,362-1,850)
1.272* r558-1.5001
5,604(5,231-6,135)
4,371* (3,433-5,814)
3,651* (2,745-3,795)
3.544* r2.767-3.9461
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                                        Page
                                                                                                       10-19

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                                                                 Child-Specific Exposure Factors Handbook

                                                                    Chapter 10 - Intake of Fish and Shellfish
                              Table 10-9. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                             General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight
  Age (years)
      Sample Size
Mean (90% CI)
90th % (90% BI)'
95th % (90% BI)'
99th % (90% BI)'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
442
147
107
28
40 (35-46)
61 (44-79)
71 (58-83)
100* (80-121)
95 (86-102)
157* (117-250)
173* (166-196)
203* (197-248)
129(120-142)
248* (150-381)
199* (173-296)
242* (206-643)
205* (200-381)
386* (221-401)
392* (296-5 14)
501* (241-643)
                                                          Marine
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Ages 16 to 17
682
217
122
37
66 (60-71)
78 (67-89)
102(86-118)
126* (80-171)
125(114-150)
150(129-201)
220* (205-265)
281* (241-354)
165(139-190)
202* (165-317)
262. (227-307)
353* (241-390)
316* (227-390)
350* (223-392)
320* (277-379)
530* (291-650)
                                                          All Fish
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Aees 16 to 17
834
270
172
52
74 (69-79)
95(85-106)
113.(99-127)
136* (97-174)
149(136-165)
200 (177-235)
227* (205-296)
242* f206-3581
184(172-223)
313* (254-381)
308* (271-348)
357* (266-6431
363* (310-391)
387* (381-401)
380* (353-409)
645* (390-6501
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
                             Table 10-10. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
                           General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight
Age (years)
Sample
Size
Mean (90%
CI)
90th
% (90%
BI)'
95th
% (90% BI)'
99
111 % (90%
BI)'
                                                     Freshwater/Estuarine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
416
132
101
28
2,292(2,012-2,572)
1,830(1,416-2,245)
1,273(1,082-1,464)
1,401* (1,058-1,744)
5,852 (4,703-6,068)
4,688* (3,673-5,987)
2,777* (2,091-3,026)
2,971* (2,743-3,692)
7,160(6,950-7,442)
6,207* (4,767-12,926)
4,419* (3,026-5,522)
3,279* (2,767-8,577)
15,600* (11,877-18,670)
12,365* (6,763-12,926)
5,717* (5,457-9,852)
6,819* (3,221-8,577)
                                                          Marine
Ages 3 to 5
Ages 6 to 10
Ages 11 to 15
Ages 16 to 17
640
203
120
37
3,689(3,395-3,982)
2,787(2,417-3,157)
2,020(1,741-2,327)
2,007* (1,302-2,712)
7,253 (6,777-8,504)
5,910(4,813-7,365)
4,224* (3,744-4,781)
4,468* (3,880-7,802)
9,270(8,415-9,991)
8,001* (6,375-8,707)
5,195* (3,859-6,448)
6,537* (3,991-7,802)
16,100* (11,980-17,989)
10,754* (8,707-12,055)
6,839* (6,076-8,970)
7,886* (4,661-7,958)
                                                          All Fish
Ages 3 to 5
Ages 6 to 10
Ages 1 1 to 1 5
Aees 16 to 17
779
250
164
52
4,198(3,894-4,502)
3,188(2,923-3,452)
2,199(1,950-2,449)
2.066* fl.529-2.6031
8,061 (7,366-9,223)
6,544(6,013-8,707)
4,387* (3,785-5,522)
3.902* f3.536-7.8921
10,444(9,475-12,261)
8,654* (7,086-11,756)
6,234* (4,420-7,589)
6.594* f4.661-8.5771
17,874* (15,290-18,670)
12,785* (10,930-13,979)
8,345* (6,076-8,970)
8.210* f7.892-8.5771
  CI
  BI
Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
The sample size does not meet minimum reporting requirements as described in the " Third Report on Nutrition Monitoring in the
United States" (LSRO, 1995).
= Confidence interval.
= Bootstrap interval.
  Source:   U.S. EPA, 2002.
Page
10-20
                                                      Child-Specific Exposure Factors Handbook
                                                     	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-11. Number of General Population Respondents Reporting Consumption of a
Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten
Age Group N
(years)
Oto
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                                            Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish








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	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish





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Child-Specific Exposure Factors Handbook
September 2008	
Page
10-23

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                                            Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish
Table 10-14. Fish Consumption Among General Population and Anglers in Three States,
g/kg-day As-Consumed
Category
N
Mean
Percentiles
10th
25th
50th
75th
90th
95th
99th
Connecticut
Anglers
General
Population
244
362
0.66
0.48
0.10
0.07
0.20
0.16
0.40
0.32
0.80
0.63
1.6
1.1
2
1
.1
.4
3.5
2.4
Minnesota
Anglers
General Population
1,109
793
0.32
0.33
0.05
0.04
0.10
0.10
0.18
0.20
0.34
0.34
0.67
0.65
0
1
99
.1
2 2
1.8
North Dakota
Anglers
General
N
Source:
Population
808
546
0.34
0.34
0.05
0.05
0.10
0.09
0.20
0.19
0.39
0.35
0.81
0.74
1
1
.2
2
2.0
2 2
= Sample size.
Moyaetal., 2008.
Table 10-15.
Age Group
0 to 9 years
10 to 19 years
1 Converted from ounces/day; 1 ounce =
Source: KCA Research Division, 1994.
Recreational Fish Consumption in Delaware
Consumers Only
Mean consumption
(s/davr
73 6.0
102 11.4
28.35 grams.

Standard Error (%)
13.4
16.8

Page
10-24
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish

Table 10-16
Age Group
Consumption of Self-Caught Fish by Recreational Anglers
Lavaca Bay, Texas, g/day
N Mean
95% Upper Confidence 90th
Limit on Mean
or 95th Percentile of
Distribution1
Finfish
Small children (<6 years)
Youths (6 to 19 years)
320 11.4
749 15.6
14.2
17.8
30.3
45.4
Shellfish
Small children (<6 years)
Youths (6 to 19 years)
320 0.4
749 0.7
0.6
1.0
2.0
4.5
* The 90th percentile values are presented for finfish. For shellfish, the 95th percentile value is provided because
less than 90 percent of the individuals consumed shellfish, resulting in a 90th percentile of zero.
Source: Alcoa, 1998.

Table 10-17. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational Anglers
Lavaca Bay, Texas
Age Group
Number of Meals
95% Upper
Mean Confidence
Limit on Mean
Portion Size
(grams)1
95% Upper
Mean Confidence Limit on
Mean
Finfish
Small children (<6 years)
Youths (6 to 19 years)
2.6 3.1
2.4 2.7
128 133
187 196
Shellfish
Small children (<6 years)
Youths (6 to 19 years)
1 Converted from ounces;
Source: Alcoa, 1998.
0.3 0.5
0.3 0.4
1 ounce =28.35 grams.
57 68
71 82

Child-Specific Exposure Factors Handbook
September 2008	
Page
10-25

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                                            Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish
Table 10-18. Mean Fish Intake Among Individuals Who Eat Fish and
Reside in Households With Recreational Fish Consumption - Michigan
Age Group
N
1 to 5 years 121
6 to 10 years 151
1 1 to 20 years 349
N
Source: U
Meals/Week
All Fish Recreational Fish
0.46 0.22
0.49 0.28
0.41 0.23
Intake
g/day g/kg-day
Total Fish Recreational Fish Total Fish Recreational Fish
11.4 5.6 0.74 0.37
13.6 7.9 0.48 0.28
12.3 7.3 0.22 0.12
Sample size.
S. EPA analysis, using data from West et al., 1989.
Table 10-19. Consumption of Sports-caught and Purchased Fish by
Minnesota and North Dakota Children, Ages 0 to 14 Years (g/day)
Percentile
50th 75th 90th

95th
Minnesota
Sports-caught 1.2 3.3 8.3
Purchased 3.6 8.7 19.2
14.6
30.9
North Dakota
Sports-caught 1.7 5.1 13.1
Purchased 4.7 11.6 26.3
23.3
42.8
Source: Benson etal., 2001.
Page
10-26
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
              Table 10-20. Fish Consumption Rates among Native American Children (age 5 years and under)'
                     Grams/Day	Unweighted Cumulative Percent
                        0.0                                                 21.1
                        0.4                                                 21.6
                        0.8                                                 22.2
                        1.6                                                 24.7
                        2.4                                                 25.3
                        3.2                                                 28.4
                        4.1                                                 32.0
                        4.9                                                 33.5
                        6.5                                                 35.6
                        8.1                                                 47.4
                        9.7                                                 48.5
                        12.2                                                51.0
                        13.0                                                51.5
                        16.2                                                72.7
                        19.4                                                73.2
                        20.3                                                74.2
                        24.3                                                76.3
                        32.4                                                87.1
                        48.6                                                91.2
                        64.8                                                94.3
                        72.9                                                96.4
                        81.0                                                97.4
                        97.2                                                98.5
                       162.0                                                 100
 *       Sample size = 194; unweighted mean = 19.6 grams/day; unweighted standard error = 1.94.
 Note:    Data are compiled from the Umatilla, Nez Perce, Yakama, and Warm Springs tribes of the Columbia River Basin.

 Source:  CRITFC, 1994.
Child-Specific Exposure Factors Handbook                                                   Page
September 2008	10-27

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                                            Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish
Table 10-21. Number of Fish Meal Eaten per Month and Fish Intake Among Native American Children who Consume Particular Species
Species
Salmon
Lamprey
Trout
Smelt
Whitefish
Sturgeon
Walleye
Squawfish
Sucker
Shad
SE = Standard error.
Source: CRITFC, 1994.
N
164
37
89
39
21
21
5
2
4
3


Fish Meals/Month
Unweighted Mean
2.3
0.89
0.96
0.40
3.5
0.43
0.22
0.00
0.35
0.10


Unweighted SE
0.16
0.27
0.12
0.09
2.83
0.12
0.20
0.22
0.06


Intake (g/day)
Unweighted Mean Unweighted SE
19
8.1
8.8
3.8
21
4.0
2.0
0.0
2.6
1.1


1.5
2.8
1.4
0.99
16
1.3
1.5
1.7
0.57


Page                                        Child-Specific Exposure Factors Handbook
10-28	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-22. Consumption Rates
Fish Category
Mean (SE)
for Native American Children, Age Birth to Five Years (g/kg-day)
95% CI
50th percentile
90th percentile
Tulalip Tribes (N = 21)
Shellfish
Total finfish
Total, all fish
0.13(0.056)
0.11(0.030)
0.24 (0.077)
(0.014,0.24)
(0.056,0.17)
(0.088,0.39)
0.0
0.060
0.078
0.60
0.29
0.74
Squaxin Island Tribe (N = 48)
Shellfish
Total finfish
Total, all fish
0.23 (0.053)
0.25 (0.063)
0.83(0.14)
(0.13,0.37)
(0.13,0.37)
(0.55,1.1)
0.045
0.061
0.51
0.57
0.83
2.1
Both Tribes Combined (weighted)
Shellfish
Total finfish
Total, all fish
SE = Standard error.
CI = Confidence interval.
N = Sample size.
Source: Toy etal., 1996.
0.18(0.039)
0.18(0.035)
0.53(0.081)


(0.10,0.25)
(0.10,0.25)
(0.37,0.69)


0.012
0.064
0.17


0.57
0.32
1.4


Child-Specific Exposure Factors Handbook
September 2008	
Page
10-29

-------
                                             Child-Specific Exposure Factors Handbook


                                               Chapter 10 - Intake of Fish and Shellfish
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Page

10-30
 Child-Specific Exposure Factors Handbook

	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-24. Consumption Rates for Native American Children (g/kg-day),
Consumers Only: Individual Finfish and Shellfish and Fish Groups
Group Species
Group E Manila/Littleneck clams
Horse clams
Butter clams
Geoduck
Cockles
Oysters
Mussels
Moon snails
Shrimp
Dungeness crab
Red rock crab
Scallops
Squid
Sea urchin
Sea cucumber
Group A"
Group Bb
Group Cc
Group Dd
Group Fe (tuna/other finfish)
All finfish
All shellfish
All seafood
N Mean
23 0.13
12 0.058
6 0.11
22 0.16
10 0.36
10 0.060
1 0.026
0
17 0.17
21 0.44
5 0.046
8 0.042
2 0.033
0
0
28 0.300
5 0.023
25 0.16
17 0.055
24 0.31
31 0.68
28 0.89
31 1.5
SE
0.068
0.032
0.066
0.054
0.23
0.035
-
-
0.064
0.18
0.011
0.019
0.008
-
0.13
0.012
0.048
0.019
0.092
0.17
0.30
0.35
Median
0.043
0.009
0.032
0.053
0.078
0.015
-
-
0.035
0.082
0.051
0.027
0.033
-
0.11
0.017
0.048
0.033
0.18
0.31
0.36
0.72
Percentiles
75th
0.066
0.046
0.20
0.23
0.29
0.074
-
-
0.30
0.305
0.067
0.032
-
0.25
0.043
0.24
0.064
0.34
0.74
0.85
2.0
90th
0.20
0.31
-
0.55
2 2
0.34
-
-
0.62
2.3
-
-
0.60
0.49
0.14
1.0
2.1
2.5
3.4
" Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead.
b Group B is finfish, including smelt and herring.
0 Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish and greenling.
11 Group D is finfish, including halibut, sole, flounder and rockfish.
" Group F includes tuna, other finfish, and all others not included in Groups A, B, C, and D.
N = Sample size.
SE = Standard error.
= No data.
Source: Duncan, 2000.










Child-Specific Exposure Factors Handbook
September 2008	
Page
10-31

-------
                                                             Child-Specific Exposure Factors Handbook

                                                               Chapter 10 - Intake of Fish and Shellfish
                         Table 10-25. Fish Consumption Rates for Tulalip and Squaxin Island Children
                        	Consumers Only (g/kg-day)	
          Species"
                                                                            Percentilesb
                           N
                     Mean
          SD
                                                              10th
                                                         25*
                                            50th
                                            75th
                                            90th
                                            95*
                                                 Squaxin Island Tribe
     Anadromous fish
     Pelagic fish
     Bottom fish
     Shellfish
     Other fish
     All finfish
     All fish	
             33
             21
             18
             31
             30
             35
             36
 0.39
 0.16
 0.17
 2.3
 0.58
 0.54
 2.9
 1.3
 0.25
 0.36
 8.6
 0.58
 1.3
 8.4
0.005
0.010

0.006
0.012
0.005
0.012
0.006
0.014
0.006
0.025
0.051
0.007
0.019
0.030
0.019
0.014
0.050
 0.11
0.046
 0.24
0.049
0.044
0.026
 0.26
 0.40
0.062
 0.70
 0.13
 0.11
0.050
 0.40
 0.57
 0.22
 1.5
0.69
0.55
0.48
0.77
 1.6
 1.7
 2.8
0.79
0.71

 4.5
 1.6
 2.3
 7.7
                                                     Tulalip Tribe
     Anadromous fish
     Pelagic fish
     Bottom fish
     Shellfish
     Other fish
     All finfish
     All fish	
             14
             7
             2
             11
             1
             15
             15
 0.15
 0.15
0.044
 0.31
 0.12
 0.31
 0.45
 0.23
 0.18
0.005
 0.39
 0.12
 0.33
 0.53
         0.012    0.026    0.045
                 0.027    0.053
                          0.041
         0.012    0.034    0.036
         0.027
         0.066
         0.082
         0.088
         0.133
         0.22
         0.14
         0.17

         0.52

         0.43
         0.60
                                   0.33
         0.80

         0.73
         0.88
     N
     SD
Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish,
greenling, herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder,
sturgeon, skate, eel, and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails,
scallops, squid, sea urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus,
abalone, barnacles, and crayfish. Other included canned tuna and trout,
Due to the small sample size for some fish groups, some percentiles could not be computed.  A percentile was
only calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a
species group.
= Sample size.
= Standard deviation.
= No data.
     Source:   Polissar et al.. 2006.
Page
10-32
                                               Child-Specific Exposure Factors Handbook
                                              	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
                    Table 10-26. Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children
                   	Consumers Only (g/kg-day)	
                                                                               Percentiles
                                                                                       ,b
        Species1
          Gender
N
Mean
 SD
                                                      10th
                                          25*
                                            50th
                                            75*
                                  90th
                                  95*
                                                 Squaxin Island Tribe
   Anadromous fish
   Pelagic fish
   Bottom fish
   Shellfish
   Other fish
   All finfish
   All fish
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
15
18
 8
13
 6
12
13
18
13
17
15
20
15
21
 0.70
 0.16
 0.10
 0.18
0.038
 0.24
 0.28
 3.8
 0.84
 0.40
 0.79
 0.37
 1.7
 3.7
 1.9
 0.25
 0.14
 0.28
0.057
 0.44
 0.24
 11.2
 0.66
 0.46
 1.9
 0.72
 2.0
 10.7
                                                         0.005
                                                         0.008
0.009
0.005

0.015

0.005
0.036
0.008
 0.11
0.013
0.009
0.005
0.061
0.014
0.026
0.025
0.015
0.020
0.016
0.010
0.047
0.050
 0.23
0.096
0.038
0.037
 0.48
 0.16
0.062
0.046
0.058
0.040
0.020
0.028
 0.24
 0.23
 0.45
 0.31
0.062
0.071
 1.2
 0.60
 0.33
0.090
0.099
 0.11
0.026
 0.11
 0.35
 0.49
 1.5
 0.49
 0.52
 0.18
 1.9
 0.92
 1.1
0.60

0.68

0.74
0.46
 1.3
 1.6
0.61
 1.5
 1.4
 2.4
 9 8
2.1
       16.4
                                                    Tulalip Tribe
   Anadromous fish
   Pelagic fish
   Bottom fish
   Shellfish
   Other fish
   All finfish
   All fish
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
        Male
        Female
                                 7
       0.061
       0.24
       0.11
       0.27

       0.044
       0.14
       0.43

       0.12
       0.21
       0.43
       0.20
       0.75
         0.052
          0.31
         0.081
          0.35

         0.005
          0.22
          0.46

          0.12
          0.18
          0.44
          0.17
          0.67
                         0.023    0.034    0.067
                         0.032    0.080    0.20
                         0.044    0.053    0.13
                                  0.017

                                  0.041
                         0.012    0.027    0.11
                         0.034     0.22     0.65
                         0.087
                         0.045
                         0.071
                          0.16
                 0.13
                 0.17
                 0.12
                 0.49
                  0.32
                  0.65
                  0.23
                  0.84
   N
   SD
Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish, greenling,
herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder, sturgeon, skate, eel,
and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails, scallops, squid, sea
urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus, abalone, barnacles, and
crayfish. Other included canned tuna and trout,
Due to the small sample size for some fish groups, some percentiles could not be computed. A percentile was only
calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a species
group.
= Sample size.
= Standard deviation.
= No data.
   Source:   Polissar et al.. 2006.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                               Page
                                                                                              10-33

-------
                                                           Child-Specific Exposure Factors Handbook

                                                              Chapter 10 - Intake of Fish and Shellfish
              Table 10-27. Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion, by Age and Sex
   Age (years)- Sex Group
                                                                          Percentiles
                            Mean
                                        SE
                                                  5th
                               10th
                             25th
                            50th
                 75th     90th
                         95th
 2 to 5
 Male- Female


 6 to 11
 Male- Female

 12 to 19
 Male
 Female
38
57
84*
64
12*
 6
                      7*
                     14*       20*
 -        18*
14*       18*
                                         15
                                         26
49*
28*
                                                  29
                                                  49
74
56
                                                          55
97*
77*
                                                                  73
                                                          59      99*
162*
105*
                                                                           85*
                                                                           157*
                                                                                                       156*
 SE       = Standard error.
 *        Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation.
          Indicates a percentage that could not be estimated.

 Source:   Smiciklas-Wright et al., 2002 (based on 1994- 1996 CSFII data).
Table 10-28. Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion, by Age and Sex
Age (years)- Sex Group
2 to 5
Male- Female
6 to 11
Male- Female
12 to 19
Male
Female
SE = Standard error.
* Indicates a statistic that
Source: Smiciklas-Wriaht et al.
Percentiles
5th 10th 25th 50th 75th 90th
64 4 8* 16 33 58 77 124
93 8 17* 31* 50 77 119 171*
119* 11* 40* 50* 64* 89 170* 185*
89* 13* 20* 26* 47* 67 124* 164*
is potentially unreliable because of small sample size or large coefficient of variation.
2002 Chased on 1994-1996 CSFII data).

95th
128*
232*
249*
199*

Page
10-34
                               Child-Specific Exposure Factors Handbook
                              	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species
Species
Moisture Content
<•%•>
Total Fat Content
<•%•>
Comments
FINFISH
Anchovy, European

Bass, Freshwater

Bass, Striped

Bluefish

Burbot

Butterfish

Carp

Catfish, Channel, Farmed

Catfish, Channel, Wild

Cavier, Black and Red
Cisco

Cod, Atlantic



Cod, Pacific

Croaker, Atlantic

Cusk

Dolphinfish

Drum, Freshwater

Eel

Flatfish, Flounder, and Sole

Grouper

Haddock


Halibut, Atlantic and Pacific

Halibut, Greenland

Herring, Atlantic



Herring, Pacific

Ling

73.37
50.30
75.66
68.79
79.22
73.36
70.86
62.64
79.26
73.41
74.13
66.83
76.31
69.63
75.38
71.58
80.36
77.67
47.50
78.93
1.91
81.22
75.61
75.92
16.14
81.28
76.00
78.03
59.76
76.35
69,68
77.55
71.22
77.33
70.94
69.26
59.31
79.06
73.16
79.22
73.36
79.92
74.25
71.48
77.92
71.69
70.27
61.88
72.05
64.16
59.70
55.22
71.52
63.49
79.63
73.88
4.84
9.71
3.69
4,73
2.33
2.99
4.24
5.44
0.81
1.04
8.02
10.28
5.60
7.17
7.59
8.02
2.82
2.85
17.90
69.80
11.90
0.67
0.86
0.86
2.37
0.63
0.81
3.17
12.67
0.69
0.88
0.70
0.90
4.93
6.32
11.66
14.95
1.19
1.53
1.02
1.30
0.72
0.93
0.96
2.29
2.94
13.84
17.74
9.04
11.59
12.37
18.00
13.88
17.79
0.64
0.82
Raw
Canned in oil, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
—
Raw
Smoked
Raw
Canned, solids and liquids
Cooked, dry heat
Dried and salted
Raw
Cooked, dry heat
Raw
Cooked, breaded and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw, mixed species
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Kippered
Pickled
Raw
Cooked, dry heat
Raw
Cooked, drv heat
Child-Specific Exposure Factors Handbook
September 2008	
Page
10-35

-------
                                           Child-Specific Exposure Factors Handbook

                                              Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (continued)
Species
Lingcod

Mackerel, Atlantic

Mackerel, Jack
Mackerel, King

Mackerel, Pacific and Jack

Mackerel, Spanish

Milkfish

Monkfish

Mullet, Striped

Ocean Perch, Atlantic

Perch

Pike, Northern

Pike, Walleye

Pollock, Atlantic

Pollock, Walleye

Pompano, Florida

Pout, Ocean

Rockfish, Pacific

Roe

Roughy, Orange

Sablefish


Salmon, Atlantic, Farmed

Salmon, Atlantic, Wild

Salmon, Chinook


Salmon, Chum


Salmon, Coho, Farmed

Salmon, Coho, Wild


Moisture Content
(%)
81.03
75.68
63.55
53.27
69.17
75.85
69.04
70.15
61.73
71.67
68.46
70.85
62.63
83.24
78.51
77.01
70.52
78.70
72.69
79.13
73.25
78.92
72.97
79.31
73.47
78.18
72.03
81.56
74.06
71.12
62.97
81.36
76.10
79.26
73.41
67.73
58.63
75.67
66.97
71.02
62.85
60.14
68.90
64.75
68.50
59.62
71.64
65.60
72.00
75.38
68.44
70.77
70.47
67.00
72.66
71.50
65.39
Total Fat Content
(%)
1.06
1.36
13.89
17.81
6.30
2.00
2.56
7.89
10.12
6.30
6.32
6.73
8.63
1.52
1.95
3.79
4.86
1.63
2.09
0.92
1.18
0.69
0.88
1.22
1.56
0.98
1.26
0.80
1.12
9.47
12.14
0.91
1.17
1.57
2.01
6.42
8.23
0.70
0.90
15.30
19.62
20.14
10.85
12.35
6.34
8.13
10.43
13.38
4.32
3.77
4.83
5.50
7.67
8.23
5.93
4.30
7.50
Comments
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned, drained solids
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Cooked, moist heat
Page
10-36
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Salmon, Pink


Salmon, Sockeye


Sardine, Atlantic
Sardine, Pacific
Scup

Sea Bass

Seatrout

Shad, American

Shark, mixed species

Sheepshead

Smelt, Rainbow

Snapper

Spot

Sturgeon


Sucker, white

Sunfish, Pumpkinseed

Surimi
Swordfish

Tilapia

Tilefish

Trout, Mixed Species

Trout, Rainbow, Farmed

Trout, Rainbow, Wild

Tuna, Fresh, Bluefin

Tuna, Fresh, Skipjack

Tuna, Fresh, Yellowfin

Tuna, Light

Tuna, White

Moisture Content
<•%•>
76.35
69.68
68.81
70.24
61.84
67.51
59.61
66.65
75.37
68.42
78.27
72.14
78.09
71.91
68.19
59.22
73.58
60.09
77.97
69.04
78.77
72.79
76.87
70.35
75.95
69.17
76.55
69.94
62.50
79.71
73.99
79.50
73.72
76.34
75.62
68.75
78.08
71.59
78.90
70.24
71.42
63.36
72.73
67.53
71.87
70.50
68.09
59.09
70.58
62.28
70.99
62.81
59.83
74.51
64.02
73.19
Total Fat Content
<•%•>
3.45
4.42
6.05
8.56
10.97
7.31
11.45
10.46
2.73
3.50
2.00
2.56
3.61
4.63
13.77
17.65
4.51
13.82
2.41
1.63
2.42
3.10
1.34
1.72
4.90
6.28
4.04
5.18
4.40
2.32
2.97
0.70
0.90
0.90
4.01
5.14
1.70
2.65
2.31
4.69
6.61
8.47
5.40
7.20
3.46
5.82
4.90
6.28
1.01
1.29
0.95
1.22
8.21
0.82
8.08
2.97
Comments
Raw
Cooked, dry heat
Canned, solids with bone and liquid
Raw
Cooked, dry heat
Canned, drained solids with bone
Canned in oil, drained solids with bone
Canned in tomato sauce, drained solids with bone
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, batter-dipped and fried
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
-
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Canned in oil, drained solids
Canned in water, drained solids
Canned in oil, drained solids
Canned in water drained solids
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                                              Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Turbot, European

Whitefish, mixed species


Whiting, mixed species

Wolffish, Atlantic

Yellowtail, mixed species

Moisture Content
<•%•>
76.95
70.45
72.77
65.09
70.83
80.27
74.71
79.90
74.23
74.52
67.33
Total Fat Content
<•%•>
2.95
3.78
5.86
7.51
0.93
1.31
1.69
2.39
3.06
5.24
6.72
Comments
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Smoked
Raw
Cooked, dry heat
Raw
Cooked, dry heat
Raw
Cooked, dry heat
SHELLFISH
Ab alone

Clam




Crab, Alaska King


Crab, Blue



Crab, Dungeness

Crab, Queen

Crayfish, Farmed

Crayfish, Wild

Cuttlefish

Lobster, Northern

Lobster, Spiny

Mussel, Blue

Octopus

Oyster, Eastern






74.56
60.10
81.82
63.64
97.70
61.55
63.64
79.57
77.55
74.66
79.02
79.16
77.43
71.00
79.18
73.31
80.58
75.10
84.05
80.80
82.24
79.37
80.56
61.12
76.76
76.03
74.07
66.76
80.58
61.15
80.25
60.50
86.20
85.16
85.14
64.72
81.95
83.30
70.32
0.76
6.78
0.97
1.95
0.02
11.15
1.95
0.60
1.54
0.46
1.08
1.23
1.77
7.52
0.97
1.24
1.18
1.51
0.97
1.30
0.95
1.20
0.70
1.40
0.90
0.59
1.51
1.94
2.24
4.48
1.04
2.08
1.55
2.46
2.47
12.58
2.12
1.90
4.91
Raw
Coofed, fried
Raw
Canned, drained solids
Canned, liquid
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, moist heat
Imitation, made from surimi
Raw
Canned
Cooked, moist heat
Crab cakes
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw
Cooked, moist heat
Raw, farmed
Raw, wild
Canned
Cooked, breaded and fried
Cooked, farmed, dry heat
Cooked, wild, dry heat
Cooked, wild, moist heat
Page
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Chapter 10 - Intake of Fish and Shellfish
Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued)
Species
Oyster, Pacific

Scallop, mixed species


Shrimp



Squid

Moisture Content
<•%•>
82.06
64.12
78.57
58.44
73.10
75.86
75.85
52.86
77.28
78.55
64.54
Total Fat Content
<•%•>
2.30
4.60
0.76
10.94
1.40
1.73
1.36
12.28
1.08
1.38
7.48
Comments
Raw
Cooked, moist heat
Raw
Cooked, breaded and fried
Steamed
Raw
Canned
Cooked, breaded and fried
Cooked, moist heat
Raw
Cooked, fried
Source: USDA. 2007.
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Chapter 11 - Intake of Meats, Dairy Products and Fats
                                   TABLE OF CONTENTS

11     INTAKE OF MEATS, DAIRY PRODUCTS AND FATS	11-1
       11.1    INTRODUCTION	11-1
       11.2    RECOMMENDATIONS	11-2
       11.3    INTAKE STUDIES	11-6
              11.3.1  Key Meat and Diary Intake Study	11-6
                     11.3.1.1    U.S. EPA Analysis of CSFII 1994-96, 1998 	11-6
              11.3.2  Relevant Meat and Dairy Intake Studies	11-7
                     11.3.2.1    USDA, 1999a	11-7
                     11.3.2.2    Smiciklas-Wright et al, 2002	11-8
                     11.3.2.3    Fox et al., 2004  	11-8
                     11.3.2.4    Ponzaetal.,2004	11-9
                     11.3.2.5    Mennella et al., 2006	11-9
                     11.3.2.6    Fox et al., 2006  	11-10
       11.4    FAT INTAKE	11-10
              11.4.1  Key Fat Intake Study	11-10
                     11.4.1.1    U.S. EPA, 2007  	11-10
              11.4.2  Relevant Fat Intake Studies	11-11
                     11.4.2.1    Cresantaetal, 1988; Nicklas et al., 1993; and Frank et al., 1986 .... 11-11
                     11.4.2.2    CDC, 1994  	11-11
       11.5    CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	11-12
       11.6    CONVERSION BETWEEN WET WEIGHT AND LIPID WEIGHT INTAKE RATES  ...11-12
       11.7    REFERENCES FOR CHAPTER 11 	11-13

APPENDIX 11A 	  11 A-l

APPENDIX 1 IB 	  11B-1
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                                          Chapter 11 - Intake of Meats, Dairy Products and Fats
                                         LIST OF TABLES

Table 11-1.     Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed	11-3
Table 11-2.     Confidence in Recommendations for Intake of Meats, Diary Products, and Fats  	11-4
Table 11-3.     Per Capita Intake of Total Meat and Dairy Products (g/kg-day as consumed)  	11-14
Table 11-4.     Consumer Only Intake of Total Meat and Dairy Products (g/(kg-day as consumed)	11-15
Table 11-5.     Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed)	11-16
Table 11-6.     Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed).... 11-16
Table 11-7.     Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (g/day) ... 11-17
Table 11-8.     Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%)  	11-18
Table 11-9.     Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day) ... 11-19
Table 11-10.    Percentage of Individuals Consuming Dairy Products, by Sex and Age (%)	11-20
Table 11-11.    Quantity (as consumed) of Meat and Dairy Products Consumed Per Eating Occasion and
               Percentage of Individuals Using These Foods in Two Days	11-21
Table 11-12.    Characteristics of FITS Sample Population	11-22
Table 11-13.    Percentage of Infants and Toddlers Consuming Meat or Other Protein Sources	11-23
Table 11-14.    Characteristics of WIC Participants and Non-participants (Percentages) 	11-24
Table 11-15.    Food Choices for Infants and Toddlers by WIC Participation Status   	11-25
Table 11-16.    Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
               Types of Milk, Meats or Other Protein Sources on A Given Day	11 -26
Table 11-17.    Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
               Consumed by Infants from the 2002 Feeding Infants and Toddlers Study 	11 -27
Table 11-18.    Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly
               Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study	11-28
Table 11-19.    Total Fat Intake (Per capita; g/day) 	11-29
Table 11-20.    Total Fat Intake (Per capita; g/kg-day) 	11-30
Table 11-21.    Total Fat Intake (Consumers Only; g/day)	11-31
Table 11-22.    Total Fat Intake (Consumers Only; g/kg-day)	11-32
Table 11-23.    Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day)	11-33
Table 11-24.    Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/kg-day) 	11-34
Table 11 -25.    Fat Intake Among Children Based on Data from the Bogalusa  Heart Study,
               1973-1982 (g/day)	11-35
Table 11 -26.    Fat Intake Among Children Based on Data from the Bogalusa  Heart Study,
               1973-1982 (g/kg-day) 	11-37
Table 11-27.    Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age  and Gender  	11-39
Table 11-28.    Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products	11-40
Table 11 A-l    Food Codes and Definitions Used in Analysis of the 1994-96,  1998 USDA CSFII Data ...  11A-2
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Chapter 11 - Intake of Meats, Dairy Products and Fats
11    INTAKE OF MEATS, DAIRY PRODUCTS
      AND FATS
11.1  INTRODUCTION
      The   American  food   supply   is  generally
considered to be  one of the safest in  the world.
Nevertheless, meats, dairy products, and fats  may
become contaminated with toxic chemicals by several
pathways.    These  foods   sources  can  become
contaminated if animals are exposed to contaminated
media  (i.e., soil, water, or feed crops).  To  assess
exposure through this pathway, information on meat,
dairy, and fat ingestion rates are needed.
      Children's exposure from contaminated meats,
dairy products, and fats may differ from  that of adults
because of differences in the type and amounts of food
eaten.  Also, for many  foods, the intake per unit body
weight is greater for children than for adults. Common
meats,  dairy products, and fats  eaten by  children
include non-fat milk solids, milk fat and solids, lean
beef, and milk sugar (lactose) (Goldman, 1995).
      A variety of terms may be used to define intake
of meats, dairy products, and fats (e.g., consumer-only
intake, per  capita intake, total meat, dairy  product, or
fat intake, as-consumed intake, dry weight intake). As
described in Chapter 9, Intake of Fruits and Vegetables,
consumer-only  intake  is  defined  as the quantity of
meats,  dairy products, or fats consumed by children
during the  survey  period averaged across only  the
children who consumed these food items during the
survey period. Per capita intake rates are generated by
averaging  consumer-only intakes over  the  entire
population  of children. In general, per  capita intake
rates are appropriate for use in exposure assessment for
which average dose estimates for children are of interest
because they represent both children who ate the foods
during the survey period and children who may eat the
food items at some time, but did not consume them
during the survey period.  Per capita intake, therefore,
represents an average across the entire population of
interest, but does so at the expense of underestimating
consumption for the subset of the population that
consume the food in question. Total intake refers to the
sum of all meats, diary products, or fats consumed in a
day.
      Intake rates may be  expressed on the basis of the
as-consumed weight (e.g., cooked or prepared) or on
the  uncooked or unprepared  weight.  As-consumed
intake rates are based on the weight of the food in the
form that  it is  consumed and  should  be  used in
assessments where the basis for the contaminant
concentrations in foods is also  indexed  to  the  as-
consumed weight. The food ingestion values provided
in this chapter are expressed as  as-consumed intake
rates because this is the fashion  in which data were
reported by survey respondents. This is of importance
because concentration  data  to be used in the dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease food  weight.   Similarly,  cooking can
increase the mass of contaminant in food  (due to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching). The combined
effects of changes in weight and changes in contaminant
mass  can result  in either an increase or decrease in
contaminant concentration in cooked food.  Therefore,
if  the as-consumed ingestion rate and the uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated.  Ideally, after-
cooking food concentrations should be combined with
the as-consumed  intake rates. In the absence of data, it
is reasonable to assume that no change in contaminant
concentration occurs after cooking. It is important for
the assessor to be  aware  of these issues and choose
intake rate data that best match the concentration data
that are being used. For more information on cooking
losses and conversions necessary to account for such
losses, the  reader  is referred to  Chapter 13 of this
handbook.
      Sometimes contaminant concentrations in food
are reported on a  dry weight basis.  When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used.  Dry-weight food
concentrations and intake rates are based on the weight
of the food consumed after the moisture content has
been  removed.     Similarly,   when  contaminant
concentrations in food are reported on a lipid weight
basis, lipid weight intake rates should be used.  For
information on converting the intake rates presented in
this chapter to dry weight or lipid weight intake rates,
the reader is referred to Sections 11.5 and 11.6 of this
chapter.
      The purpose of this chapter is to provide intake
data for meats, diary products, and fats among children.
The recommendations  for ingestion  rates of meats,
dairy products, and fats are provided in the next section,
along with  a  summary of the confidence ratings  for
these recommendations. The recommended values are
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                                           Chapter 11 - Intake of Meats, Dairy Products and Fats
based on the key studies identified by U. S. EPA for this
factor. Following the recommendations, the key studies
on ingestion of meats, dairy products, and fats are
summarized. Relevant data on ingestion of meats, dairy
products, and fats are also provided.  These studies are
presented to provide the reader with added perspective
on  the   current  state-of-knowledge  pertaining  to
ingestion of meats, dairy products, and  fats among
children.

11.2  RECOMMENDATIONS
      Tables  11-1  presents   a  summary  of  the
recommended values for per capita and consumers-only
intake of meats, diary products, and fats, on an as-
consumed basis.  Confidence  ratings for the meats,
dairy  products, and fat intake  recommendations for
general population children are provided in Table 11-2.
      U. S. EPA analyses of data from the 1994-96 and
1998  Continuing  Survey if  Food Intake among
Individuals  (CSFII)  were   used  in   selecting
recommended  intake  rates  for general  population
children.  The U.S. EPA analysis of meat and dairy
products was conducted using age groups that differed
slightly from U.S. EPA's Guidance  on Selecting Age
Groups  for Monitoring  and Assessing Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005).     However,   for  the  purposes   of   the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis. The U.S. EPA analysis of fat intake data
from the CSFII used the age groups  recommended by
U.S. EPA  (2005).  The  CSFII data on which the
recommendations for meats, dairy products, and fats are
based  are  short-term  survey  data and may  not
necessarily reflect the long-term distribution of average
daily intake rates. However, for these broad categories
of food  (i.e., total meats and diary products), because
they are eaten on a daily basis throughout the year with
minimal seasonality, the short term distribution may be
a  reasonable   approximation   of  the   long-term
distribution,  although  it  will display   somewhat
increased variability.   This implies that the upper
percentiles shown here will  tend to overestimate the
corresponding   percentiles  of  the  true  long-term
distribution.  It should be noted that because these
recommendations  are  based on 1994-96 and  1998
CSFII data, they may not  reflect  the most recent
changes  that may have  occurred  in consumption
patterns.
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Chapter 11 - Intake of Meats, Dairy Products and Fats
               Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed
    Age Group
                             Per Capita
                                  Consumers Only
Mean
95th Percentile
Mean
95th Percentile
   Multiple
  Percentiles
   Source
                      g/kg-day
              g/kg-day
                 g/kg-day
              g/kg-day
                                                  Total Meats1
 Birth to 1 year
 1 to <2 years
 2 to <3 years
 3 to <6 years
 6 to <11 years
 11 to <16 years
 16 to <21 years
 1.2
 4.1
 4.1
 4.1
 2.9
 2.1
 2.1
     6.7
     9.8
     9.8
     9.4
     6.5
     4.8
     4.8
 3.0
 4.2
 4.2
 4.2
 2.9
 2.1
 2.1
     9.2
     9.8
     9.8
     9.4
     6.5
     4.8
     4.8
See Tables 11-3
   and 11-4
 U.S. EPA
 Analysis of
CSFII, 1994-
96 and  1998.
                                              Total Dairy Products1
 Birth to 1 year
 1 to <2 years
 2 to <3 years
 3 to <6 years
 6 to <11 years
 11 to <16 years
 16 to <21 years
 13
 37
 37
 23
 14
 5.6
 5.6
                                        49
     49
     32
     16
     16
 16
 37
 37
 23
 14
 5.6
 5.6
                                   58
     49
     32
     16
     16
See Tables 11-3
   and 11-4
 U.S. EPA
 Analysis of
CSFII, 1994-
96 and  1998.
                            Individual Meat and Dairy Products - See Tables 11-5 and 11-6
                                                   Total Fats
 Birth to <1 month
 1 to <3 months
 3 to <6 months
 6 to <12 months
 1 to <2 years
 2 to <3 years
 3 to <6 years
 6 to <11 years
 11 to <16 years
 16 to <21 years
 5.2
 4.5
 4.1
 3.7
 4.0
 3.6
 3.4
 2.6
 1.6
 1.3
     16
     11
     8.2
     7.0
     7.1
     6.4
     5.8
     4.2
     3.0
     2.7
 7.8
 6.0
 4.4
 3.7
 4.0
 3.6
 3.4
 2.6
 1.6
 1.3
     16
     12
     8.3
     7.0
     7.1
     6.4
     5.8
     4.2
     3.0
     2.7
 See Tables 11-
 20 and 11-24
 U.S. EPA
 Analysis of
CSFII, 1994-
96 and  1998.
        Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
        Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005). Data
        were placed  in the standardized age categories closest to those used in the analysis.
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                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Rationale
The survey methodology and data analysis was adequate.
The survey sampled approximately 11,000 children. An
analysis of primary data was conducted.
No physical measurements were taken. The method relied
on recent recall of meats and diary products eaten.
The key studies were directly relevant to meat, dairy, and
fat intake.
The data were demographically representative of the U.S.
population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total meats, total diary
products, and total fats. Means were provided for
individuals meats and diary products.
Data collection was based on recall of consumption for a
2-day period; the accuracy of using these data to estimate
long-term intake (especially at the upper percentiles) is
uncertain. However, use of short-term data to estimate
chronic ingestion can be assumed for broad categories of
foods such as total meats, total diary products, and total
fats. Uncertainty is likely to be greater for individual
meats and diary products.
Rating
High
Medium
High
Medium
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Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not been
peer reviewed outside the Agency.
There was 1 key study for intake of meat and diary
products and 1 key for fat intake. Both were based on the
1994-96, 1998 CSFII.

Rating
Medium
High confidence in
the averages;
Low confidence in the
long-term upper
percentiles
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                                           Chapter 11 - Intake of Meats, Dairy Products and Fats
11.3  INTAKE STUDIES
      The primary source of recent information on
consumption rates of meat and diary products among
children  is the U.S.  Department  of Agriculture's
(USDA) CSFII. Data from the 1994-96 CSFII and the
1998 Children's supplement to the 1994-96 CSFII have
been used in various  studies to generate children's
consumer-only and per capita intake rates for both
individual meats and diary products and total meats and
diary  products.  The  CSFII is  a series of surveys
designed to measure the kinds and amounts of foods
eaten  by  Americans.    The CSFII  1994-96 was
conducted between January 1994 and January 1997
with  a  target  population  of non-institutionalized
individuals in all 50 states and Washington, D.C.  In
each of the 3  survey years, data were collected for a
nationally representative sample of individuals of all
ages.   The CSFII  1998 was  conducted between
December 1997  and December  1998 and  surveyed
children 9 years of age and younger. It used the same
sample design as the CSFII 1994-96 and was intended
to be merged  with  CSFII  1994-96 to  increase  the
sample size for children.   The merged surveys  are
designated  as  CSFII  1994-96,   1998.   Additional
information on these  surveys can be  obtained  at
http://www.ars.usda.gov/Scrviccs/docs.hlm?docid=14
531.
      The  CSFII 1994-96,  1998 collected dietary
intake data through in-person interviews on 2 non-
consecutive days.  The data were based on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day.  Over 11,000 of the sample persons
represented children up to  18 years of age.  The 2-day
response   rate  for  the   1994-1996  CSFII  was
approximately 76 percent.  The 2-day response rate for
CSFII 1998 was 82 percent.
      The CSFII 1994-96, 98 surveys were based on a
complex  multistage  area  probability sample design.
The sampling frame was  organized using 1990 U.S.
population census estimates, and the stratification plan
took into account geographic location, degree  of
urbanization,   and  socioeconomic   characteristics.
Several sets of sampling weights are available for use
with the intake data. By using appropriate weights data
for all fours years of the  surveys can be combined.
USDA recommends that all 4 years be  combined in
order to provide an adequate sample size for children.
 11.3.1     Key Meat and Diary Intake Study
 11.3.1.1   U.S. EPA Analysis of CSFII 1994-96,
           1998
           For many years, the U.S. EPA' Office of
 Pesticide Programs (OPP) has used food consumption
 data collected by the U.S. Department of Agriculture
 (USDA) for its dietary risk assessments. Most recently,
 OPP,  in  cooperation  with  USDA's  Agricultural
 Research Service (ARS), used data from the 1994-96,
 1998 CSFII to develop the Food Commodity Intake
 Database (FCID).  CSFII data on the foods  people
 reported eating were converted to the quantities of
 agricultural  commodities  eaten.     "Agricultural
 commodity" is a term used by U. S. EPA to mean animal
 (or plant) parts consumed by humans as food; when
 such items are raw or unprocessed, they are referred to
 as "raw agricultural commodities." For example, a beef
 stew may contain the commodities beef, carrots,  and
 potatoes.  FCID contains approximately 553  unique
 commodity names and  8-digit  codes.  The FCID
 commodity names and codes were selected and defined
 by U.S. EPA  and were based on the U.S. EPA Food
 Commodity  Vocabulary
 (httgV/www.epa.gov/pesticides^oodfegd/).
           The meats and diary items/groups selected
 for the U.S. EPA analysis included total meats and total
 diary products, and individual meats and diary such as
 beef, pork, poultry, and eggs. Appendix 11A presents
 the food codes and definitions used to  determine the
 various meats and dairy products used in the analysis.
 Intake rates for these food items/groups represent intake
 of all forms of the product (e.g., both home produced
 and commercially produced).  Children who provided
 data for two days of the  survey were included in the
 intake estimates.  Individuals who did not provide
 information on body weight or for whom identifying
 information was unavailable were excluded from the
 analysis. Two-day average intake rates were calculated
 for all individuals in the database for each of the food
 items/groups.   These average daily intake rates were
 divided by each individual's reported body weight to
 generate intake rates in units of grams per kilogram of
 body weight  per day (g/kg-day).  The data were
 weighted according to the four-year, two-day sample
 weights provided in the 1994-96,1998 CSFII to adjust
 the data for the sample population to reflect the national
 population.
           Summary statistics were generated on both
 a per capita and a consumer only basis. For per capita
 intake, both users and non-users of the food item were
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Chapter 11 - Intake of Meats, Dairy Products and Fats
included in the analysis.  Consumer only intake rates
were calculated using data for only those individuals
who ate the food item of interest during the survey
period.  Intake data from the CSFII are based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the meat or dairy products being analyzed, mean intake
rate, and standard error of the mean intake rate were
calculated for total meats, total dairy products, and
selected  individual  meats   and   dairy  products.
Percentiles of the intake rate distribution (i.e., 1st, 5th,
10th,  25th,  50th, 75th, 90th,  95th,  99th, and  100th
percentile were also provided for total meats and dairy
products.  Data were provided for the following age
groups of children: birth to <1 year, 1 to <2 years, 3 to
<5 years, 6 to <12 years, and 13 to <19 years. Because
these  data were developed  for use in U.S.  EPA's
pesticide registration program, the age groups used are
slightly different  than those recommended  in U.S.
EPA's  Guidance  on  Selecting  Age Groups for
Monitoring  and Assessing Childhood Exposures  to
Environmental Contaminants (U.S. EPA, 2005).
          Tables 11 -3 presents as-consumed per capita
intake data for total meats and  dairy products in g/kg-
day; as-consumed consumer-only intake data for total
meats and dairy products in g/kg-day are provided in
Table 11-4.  Table 11 -5 provides per capita intake data
for certain individual meats and dairy products and
Table  11-6  provides consumer only intake data for
these individual meats and dairy products.
          It should be noted that the distribution of
average daily intake rates generated using short-term
data (e.g., 2-day)  do not necessarily reflect the long-
term distribution of average daily intake  rates.  The
distributions generated from short-term and long-term
data will  differ to the extent  that  each individual's
intake varies from day to day; the distributions will be
similar  to the extent that individuals' intakes  are
constant from day to day.   However, for  broad
categories  of foods  (e.g.,  total meats  and  dairy
products) that are eaten on a daily basis throughout the
year, the short-term distribution may be a reasonable
approximation  of the true long-term  distribution,
although it will show somewhat more variability.  In
this chapter, distributions  are provided only for broad
categories of meats and dairy products (i.e., total meats
and  dairy products).   Because  of the increased
variability of the short-term distribution, the short-term
upper percentiles shown  here may  overestimate  the
corresponding percentiles of the long-term distribution.
For individual foods, only the mean, standard error, and
percent consuming are provided.
          The  strengths of U.S. EPA's analysis are
that it provides distributions of intake rates for various
age groups of children,  normalized by body weight.
The analysis  uses the 1994-96, 1998 CSFII data set
which was designed to be representative of the U.S.
population. The data set includes four years of intake
data combined,  and is  based on a two-day  survey
period.  As discussed above,  short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food.   This is particularly true for the tails (extremes)
of the distribution of food intake.  Also, the analysis
was conducted using slightly different age groups that
those  recommended in U.S.  EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).  However,  given the similarities in
the age groups used, the data  should provide suitable
intake estimates for the age groups of interest.

11.3.2    Relevant Meat and Dairy Intake Studies
11.3.2.1   USDA, 1999a-Food and Nutrient Intakes
          by Children 1994-96,1998, Table Set 17
          USDA   (1999a)   calculated   national
probability estimates of food and nutrient intake by
children based on all 4 years of the CSFII (1994-96 and
1998) for children age 9 years  and under and on CSFII
1994-96 only for individuals  age 10 years and over.
Sample weights were used to adjust for non-response,
to match the sample to the U. S. population in terms of
demographic  characteristics, and to equalize intakes
over the 4 quarters of the year and the 7 days of the
week. A total of 503 breast-fed children were excluded
from  the  estimates,  but both consumers and  non-
consumers were included in the analysis.
          USDA (1999a) provided data on the mean
per  capita   quantities  (grams)   of  various   food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey.  Tables 11-7 and 11-8 present
data on the mean quantities (grams) of meat and eggs
consumed per   individual  for one   day,  and  the
percentage of survey individuals consuming meats and
eggs on that survey day. Tables 11 -9 and 11-10 present
similar data for dairy products. Data on mean intakes
or mean percentages are based on respondents' day-1
intakes.
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                                            Chapter 11 - Intake of Meats, Dairy Products and Fats
          The advantage of the USD A (1999a) study
is that it uses the 1994-96, 98 CSFII data set, which
includes four years of intake data, combined,  and
includes the supplemental data on children.  These data
are expected to be generally representative of the U.S.
population and they include data on a wide variety of
meats and diary  products.  The data set is one of a
series of USDA data sets that are publicly available.
One limitation of this data set is that it is based on one-
day,  and short-term dietary data may not accurately
reflect long-term eating patterns. Other limitations of
this study are that it only provides mean values of food
intake rates, consumption is  not normalized by body
weight, and presentation of results is not consistent with
U.S. EPA's recommended age groups.

11.3.2.2   Smiciklas-Wright et al,  2002 -   Foods
          Commonly Eaten in the United States:
          Quantities Consumed per Eating Occasion
          and in a Day, 1994-1996
          Using data gathered in the 1994-96 USDA
CSFII,  Smiciklas-Wright et al. (2002)   calculated
distributions for  the quantities of meat, poultry,  and
dairy  products  consumed per  eating occasion  by
members of the U.S. population (i.e., serving sizes).
The estimates of serving size are based on data obtained
from  14,262 respondents, ages 2  and above, who
provided 2 days of dietary intake information.  A total
of 4,939 of these respondents were children, ages 2 to
19 years of age.  Only dietary intake data from users of
the specified food were  used in the  analysis (i.e.,
consumers only data).
          Table 11-11 presents serving size data for
meats and dairy products.  These data are presented on
an as-consumed  basis (grams)  and  represent  the
quantity of meats and dairy products consumed per
eating occasion.   These estimates may be useful for
assessing acute exposures to  contaminants in specific
foods,  or  other  assessments  where  the   amount
consumed per eating occasion is necessary. Only the
mean and standard deviation serving  size data  and
percent  of the population  consuming the food during
the 2-day survey period are presented in this handbook.
Percentiles of serving sizes of the foods consumed by
these  age groups of the U.S.  population can be found
in Smiciklas-Wright et al.  (2002).
          The advantages of using these data are that
they  were derived from  the USDA CSFII  and are
representative of the U.S. population.  The analysis
conducted by Smiciklas-Wright et al. (2002) accounted
 for individual foods consumed as ingredients of mixed
 foods. Mixed foods were disaggregated via recipe files
 so that the individual ingredients could  be grouped
 together  with  similar foods that  were   reported
 separately.   Thus, weights  of  foods consumed as
 ingredients were  combined  with weights  of foods
 reported  separately  to provide a  more  thorough
 representation of consumption. However, it should be
 noted that since  the recipes for the mixed foods
 consumed were not  provided by  the  respondents,
 standard recipes were used.  As a result, the estimates
 of quantity consumed  for some food types are based on
 assumptions  about   the  types   and  quantities  of
 ingredients consumed as part of mixed foods.  This
 study used data from the 1994 to 1996 CSFII; data from
 the 1998 children's supplement were not included.

 11.3.2.3   Fox  et al, 2004 - Feeding Infants  and
           Toddlers Study:  What Foods Are Infants
           and Toddlers Eating
           Fox et al. (2004) used data from the Feeding
 Infants and  Toddlers study (FITS)  to  assess  food
 consumption patterns  in infants and toddlers.  The FITS
 was sponsored by Gerber Products Company and was
 conducted to obtain current information on food and
 nutrient intakes of children, ages 4 to 24 months old, in
 the 50 states and the District of Columbia.  The FITS is
 described in detail in Devaney et al. (2004).  FITS was
 based on a random sample of 3,022 infants and toddlers
 for which  dietary intake data  were collected  by
 telephone  from  their parents or  caregivers between
 March and July 2002.  An initial recruitment  and
 household interview  was conducted, followed by an
 interview to obtain information on intake based on 24-
 hour recall.   The interview also addressed growth,
 development and feeding patterns.  A second dietary
 recall interview was  conducted  for a subset of 703
 randomly  selected respondents.   The study over-
 sampled children in the 4 to 6 and 9 to 11 months age
 groups; sample weights were adjusted for non-response,
 over-sampling, andunder-coverageof some subgroups.
  The response rate for the FITS was 73 percent for the
 recruitment interview.  Of the recruited households,
 there was a response rate of 94 percent for the dietary
 recall interviews  (Devaney  et   al.,  2004).     The
 characteristics of the FITS study population is shown in
 Table 11-12.
           Fox et al. (2004) analyzed the first set of 24-
 hour recall data collected  from all study participants.
 For this analysis, children were grouped into six age
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Chapter 11 - Intake of Meats, Dairy Products and Fats
categories:  4 to 6 months, 7 to 8 months, 9 to 11
months, 12 to 14 months, 15 to 18 months, and 19 to 24
months. Table 11-13 provides the percentage of infants
and toddlers consuming milk, meats or other protein
sources at least once  in a day.  The  percentage of
children consuming any type of meat or protein source
ranged from 14.2 percent for 4 to 6 month olds to 97.2
percent for 19 to 24 month olds (Table  11-13).
          The advantages of this study were that the
study population represented the U.S. population and
the sample size was  large.   One  limitation of the
analysis done by Fox et  al. (2004) was  that only
frequency data were provided; no information on actual
intake rates was included. In addition,  Devaney et al.
(2004) noted several limitations associated with the
FITS data.  For the FITS, a commercial list of infants
and toddlers was used to obtain the sample used in the
study.  Since many of the households could not be
located and  did not have  children  in  the  target
population, a  lower response rate  than would have
occurred in  a  true national sample  was obtained
(Devaney et al., 2004).  In addition, the sample was
likely  from  a higher socioeconomic  status  when
compared with all U.S. infants in this age group (4 to 24
months old) and the use of a telephone survey may have
omitted lower-income  households without telephones
(Devaney et al., 2004).

11.3.2.4   Ponza et al, 2004 - Nutrient Food Intakes
          and Food Choices of Infants and Toddlers
          Participating in WIC
          Ponza et al. (2004) conducted a study using
selected data from FIT S to assess feeding patterns, food
choices and nutrient intake  of infants and toddlers
participating  in the Special  Supplemental Nutrition
Program  for  Women, Infants,  and Children  (WIC).
Ponza  et al.  (2004)  evaluated FITS  data for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months( N = 1159) and 12 to 24 months (N= 996). The
total sample size described by WIC participant and non-
participant is shown in Table  11-14.
           The foods consumed  were analyzed by
tabulating the percentage  of infants who consumed
specific foods/food groups per day (Ponza et al., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza etal, 2004).  Table 11-14 presents the
demographic  data for WIC participants  and  non-
participants. Table 11-15 provides the food choices for
infants and  toddlers.    In general,  there was  little
difference in food choices among WIC participants and
non-participants, except for consumption of yogurt by
infants 7 to  11  months of age and toddlers 12 to 24
months of age (Table 11-15). Non-participants, 7 to 24
months of age, were more likely to eat yogurt than WIC
participants (Ponza et al., 2004).
          An advantage of this  study is that it had a
relatively the large sample size and was representative
of the U.S. general population of infants and children.
A limitation of the study is that intake values for foods
were not provided. Other limitations are one associated
with the FITS data and are described previously in
Section 11.3.2.3.

11.3.2.5   Mennella et al, 2006 - Feeding Infants
          and  Toddlers Study:  The Types of Foods
          Fed to Hispanic Infants and Toddlers
          Mennella et al. (2006) investigated the types
of food and beverages consumed by Hispanic infants
and toddlers in comparison to the non-Hispanic infants
and toddlers  in the United States. The FITS 2002 data
for children between 4 and 24 months old were used for
the study.  The data represent a random sample of 371
Hispanic and 2,367 non-Hispanic infants and toddlers
(Menella et al., 2006).  Menella  et al. (2006) grouped
the infants as follows: 4 to 5 months (N = 84 Hispanic;
538 non-Hispanic), 6 to 11 months (N = 163 Hispanic
and 1,228 non-Hispanic), and 12 to 24 months (N = 124
Hispanic and 871 non-Hispanic)  of age.
          Table 11-16 provides the percentages of
Hispanic  and  non-Hispanic infants  and  toddlers
consuming milk, meats or other  protein sources on a
given day.    In most  instances  the  percentages
consuming the  different types of meats and protein
sources were similar (Mennella et al., 2006).
          The advantage of the study is that it provides
information on food preferences for Hispanic and non-
Hispanic infants and toddlers. A limitation is that the
study did  not provide food  intake data, but provided
frequency  of use data instead.  Other limitations are
those noted previously in Section 11.3.2.3 for the FITS
data.
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                                            Chapter 11 - Intake of Meats, Dairy Products and Fats
11.3.2.6   Fox et al.,  2006 - Average Portion of
          Foods Commonly Eaten by Infants and
          Toddlers in the United States
          Fox et al. (2006) estimated average portion
sizes consumed per eating occasion by children 4 to 24
months of age who participated in the FITS. The FITS
is  a cross-sectional  study designed to  collect  and
analyze data on feeding practices, food consumption,
and usual nutrient intake of U.S. infants and toddlers
and is described in Section 11.3.2.3 this chapter. It
included  a stratified random sample of 3,022 children
between 4 and 24 months of age.
          Using the 24-hour recall data, Fox et al.
(2006) derived average portion sizes for six major food
groups,  including meats and  other protein  sources.
Average portion sizes for select individual foods within
these major groups were  also estimated.   For  this
analysis, children were grouped into six age categories:
4 to 5 months, 6 to 8 months, 9 to 11 months, 12 to 14
months, 15 to 18 months, and 19 to 24 months. Tables
11-17 and 11-18 present the average portion sizes of
meats and  dairy products for infants  and toddlers,
respectively.

11.4      FAT INTAKE
11.4.1     Key Fat Intake Study
11.4.1.1   U.S. EPA, 2007 - Analysis of Fat Intake
          Based  on  the  U.S.   Department   of
          Agriculture's 1994-96, 1998 Continuing
          Survey  of Food Intakes by  Individuals
          (CSFII)
          U. S. EPA conducted an analysis to evaluate
the dietary intake of fats by individuals in the United
States using data from the USDA's  1994-1996, 1998
CSFII (USDA, 2000).  Intakes of CSFII foods were
converted to U.S. EPA food commodity  codes using
data provided in U.S. EPA's FCID (U.S. EPA, 2000).
The FCID contains a "translation file" that was used to
break down the USDA CSFII food codes into 548 U.S.
EPA commodity codes. The method used to translate
USDA food codes into U.S. EPA commodity codes is
discussed in detail in U.S. EPA (2000).
          Each of the 548 U.S. EPA commodity codes
was assigned a value between 0 and 1 that indicated the
mass fraction of fat in that food item.  For many sources
of fat, a commodity code existed solely for the nutrient
fat portion  of the food.   For example,  beef is
represented  in the FCID database by ten different
commodity codes; several of these codes specifically
exclude fat, and one code is described as "nutrient fat
 only."   In these cases, the  fat fraction could  be
 expressed as 0 or 1, as appropriate. Most animal food
 products and food oils were broken down in this way.
 The  fat contents  of other foods in the U.S.  EPA
 commodity code list were determined using the USDA
 Nutrient Database for Standard Reference, Release 13
 (USDA, 1999b).  For each food item in the U.S. EPA
 code list, the best available match in the  USDA
 Nutrient database was used.  If multiple values were
 available for different varieties of the same food item
 (e.g., green, white and red grapes), a mean value was
 calculated.   If multiple values were  available for
 different cooking methods (i.e, fried vs. dry cooked),
 the method least likely to introduce other substances,
 such as oil or butter, was preferred. In some cases, not
 all of the items that fall under a given food commodity
 code could be assigned a fat content.  For example, the
 food commodity code list identified "turkey,  meat
 byproducts" as including gizzard, heart, neck and tail.
 Fat contents could be determined only for the gizzard
 and heart. Because the relative amounts of the different
 items in the food commodity code was  unknown, the
 mean fat content of these two items was assumed to be
 the best approximation of the fat content for the food
 code as a whole.
           The analysis was based on approximately
 11,000 C SFII child respondents who had provided body
 weights and who had completed both days of the two-
 day survey process.  These individuals were grouped
 according to various age categories.   The  mean,
 standard error, and a range of percentiles of fat intake
 were calculated for  12 food categories (i.e., all fats,
 animal fats,  meat  and meat products, beef, pork,
 poultry, organ meats, milk and dairy products, fish, oils,
 and  nuts/seeds/beans/legumes/tubers)   and   98
 demographic cohorts. Fat intake was calculated as a
 two-day average consumption across both survey days
 in units  of grams per day  and grams per kilogram of
 body weight per day for the whole survey population
 and for consumers only. A secondary objective of the
 study was to evaluate fat consumption patterns  of
 individuals who consume  high levels of animal fats.
 The entire data analysis was repeated for a  subset of
 individuals who were identified as high consumers of
 animal fats.  The selection of the high-consumption
 group was done  for each age category individually,
 rather than on the whole population, because fat intake
 on a per-body-weight basis is heavily skewed towards
 young  children,  and an  analysis across the  entire
 American population was desired. For infants, the "less
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Chapter 11 - Intake of Meats, Dairy Products and Fats
than one year old" group  was used instead of the
smaller infant groups (<1 month, 1 to <3 months, etc.).
Within each of  the age categories, individuals that
ranked at or above the 90thpercentile of consumption of
all animal fats on a per-unit body weight basis were
identified. Because of the sample weighting factors, the
high consumer group was not necessarily 10 percent of
each age group.  The  selected individuals made up a
survey population of  1,175 children.  Fat intake of
individuals in this group was calculated in g/day and
g/kg-day for the whole population (i.e., per capita) and
for consumers only.
          The analysis presented in U.S. EPA (2007)
was conducted before U.S. EPA published the guidance
entitled  Guidance  on Selecting  Age  Groups  for
Monitoring and Assessing  Childhood Exposures to
Environmental   Contaminants  (U.S.  EPA,   2005).
Therefore, the age groups used for children in U.S.
EPA (2007) were not  entirely consistent with the age
groups recommended in the 2005 guidance.   A re-
analysis of the some of the data was conducted for this
chapter to conform with U. S. EPA's recommended age
groups for children. The results of this re-analysis are
presented in Tables 11-19 through 11 -26 for individuals
less than 21 years of age.  Only intake rates of all fats
are provided in these  tables; the reader is referred to
U.S. EPA (2007) for fat intake  rates from individual
food sources.  Tables  11-19 and 11-20 present intake
rates of  all fats for the whole  population (i.e., per
capita) in g/day and g/kg-day, respectively.  Table 11 -
21  and  11-22  present intake rates  of  all fats for
consumers only  in g/day  and g/kg-day, respectively.
Fat intake rates of all fats for the top decile of animal
fat consumers from the consumers only  group are
presented in Table 11 -23 in g/day and in Table 11 -24 in
g/kg-day (per capita total fat intake rates  for the top
decile of animal fat consumers are not provided because
they are the same as those for consumers only).

11.4.2     Relevant Fat Intake Studies
11.4.2.1   Cresanta et al., 1988; Nicklas et al., 1993;
          and Frank et al., 1986 - Bogalusa Heart
          Study
          Cresanta et al. (1988), Nicklas etal. (1993),
and Frank et al. (1986) analyzed dietary fat intake data
as part of the  Bogalusa heart study.  The Bogalusa
study, an epidemiologic investigation of cardiovascular
risk-factor variables and environmental determinants,
collected dietary data on subjects residing in Bogalusa,
LA,  beginning in 1973.  Among other research, the
study collected fat intake data for children, adolescents,
and  young adults.   Researchers examined  various
cohorts of subj ects, including (1) six cohorts of 10-year
olds, (2) two cohorts of 13-year olds, (3) one cohort of
subjects from 6 months to 4 years of age, and (4) one
cohort of subjects from 10 to 17 years of age (Nicklas,
1995). To collect the data, interviewers used the 24-
hour dietary  recall  method.  According to  Nicklas
(1995), "the diets of children in the Bogalusa study are
similar  to  those reported in  national  studies  of
children." Thus, these data are useful in evaluating the
variability of fat intake among the general population.
Data  for 6-month  old to 17-year old  individuals
collected during 1973 to 1982 are presented in Tables
11-25  and  11-26 (Frank  et  al., 1986).   Data are
presented for total fats, animal fats, vegetable fats, and
fish fats in units of g/day (Table  11-25) and g/kg/day
(Table 11-26).

11.4.2.2   CDC, 1994 - Dietary Fat and Total Food-
          energy Intake: Third National Health and
          Nutrition Examination Survey, Phase  1,
          1988-91
          The  Centers for  Disease  Control  and
Prevention (CDC, 1994) used data from NHANES III
to calculate daily total food energy intake (TFEI), total
dietary fat intake, and saturated fat intake for the U.S.
population  during  1988  to   1991.    The  sample
population comprised 20,277 individuals ages 2 months
and above, of which 14,801 respondents (73 percent
response rate) provided dietary information based on a
24-hour recall.  Of these, 6,870 were children between
the ages of 2 months and 19 years. TFEI was defined
as "all nutrients (i.e.,  protein, fat, carbohydrate, and
alcohol)  derived from  consumption of foods and
beverages (excluding plain drinking water) measured in
kilocalories  (kcal)."   Total dietary fat intake was
defined as "all fat  (i.e., saturated and unsaturated)
derived from consumption of foods and beverages
measured in grams" (CDC, 1994).
          The authors estimated and provided data on
the mean daily TFEI and the mean percentages of TFEI
from total dietary fat grouped by age and gender. The
overall mean daily TFEI for the total population was
2,095 kcal, of which 34 percent (712 kcal or 82 g) was
from total dietary fat.  Based on  this information, the
mean daily fat intake was calculated for the various age
groups and genders (see Appendix 11B for detailed
calculation).  Table 11 -27 presents the grams of fat per
day obtained from the daily consumption of foods and
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                                            Chapter 11 - Intake of Meats, Dairy Products and Fats
beverages grouped by age and  gender for the U.S.
population, based on this calculation.

11.5   CONVERSION  BETWEEN WET  AND
       DRY WEIGHT INTAKE RATES
       The intake rates presented in this chapter are
reported in units of wet weight (i.e., as-consumed or
uncooked weight of meats and dairy products consumed
per day or per eating occasion). However, data on the
concentration of contaminants  in  meats  and dairy
products may be reported in units of either wet or dry
weight.(e.g., mg contaminant per gram-dry-weight of
meats and dairy products.) It is essential that exposure
assessors be aware of this difference so that they may
ensure consistency between the units used for intake
rates and those used for concentration data (i.e., if the
contaminant concentration is measured in dry weight of
meats and dairy products, then the dry weight units
should be used for their intake values).
       If necessary, wet weight (e.g., as consumed)
intake rates may be converted to dry weight intake rates
using the  moisture content percentages presented in
Table 11-28 and the following equation:
 IRdw=  IRww
where:
100- W
  100
                                    (Eqn. 11-1)
       w  =
     dry weight intake rate;
     wet weight intake rate; and
     percent water content
                                     11.6    CONVERSIONBETWEENWETWEIGHT
                                            AND LIPID WEIGHT INTAKE RATES
                                            In   some  cases,   the   residue  levels   of
                                     contaminants  in  meat and  dairy products may be
                                     reported as the concentration of contaminant per gram
                                     of fat.  This may be particularly true for lipophilic
                                     compounds.   When using these residue levels,  the
                                     assessor should ensure consistency in  the exposure
                                     assessment calculations by using consumption rates that
                                     are based on the amount of lipids  consumed for the
                                     meat or dairy product of interest.
                                            If necessary, wet weight (e.g., as-consumed)
                                     intake rates may  be  converted to lipid weight intake
                                     rates using  the fat content percentages presented in
                                     Table 11-28 and the following equation:
    IRlw =
                                     where:
                                                              Irww
                                                              L
                                                                        (Eqn. 11-3)
                                                             lipid weight intake rate;
                                                             wet weight intake rate; and
                                                             percent lipid (fat) content.
Alternately, wet weight residue levels in meat and dairy
products may be estimated by multiplying the levels
based on fat by the fraction of fat per product as
follows:
                                                          C     =   C
                                                           ww      Iw
                                                                          L
                  100
                                  (Eqn. 11-4)
Alternatively, dry weight residue levels in meat and
diary products may be converted to wet weight residue
levels for use with wet weight (e.g.,  as-consumed)
intake rates as follows:
                                     where:
                                            L   =
                        wet weight intake rate;
                        lipid weight intake rate; and
                        percent lipid (fat) content.
   ww      dw
where:
        ww
       Cdw =
       W  =
                                  (Eqn. 11-2)
     wet weight intake rate;
     dry weight intake rate; and
     percent water content.
                                     The resulting residue levels may then be used  in
                                     conjunction  with  wet  weight  (e.g., as-consumed)
                                     consumption rates. The total fat content data presented
                                     in Table 11 -28 are for selected meat and dairy products
                                     taken from USDA, 2007.
The moisture content data presented in Table 11 -28 are
for selected meats and dairy products taken from USDA
(2007).
Page
11-12
                                     Child-Specific Exposure Factors Handbook
                                    	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
11.7   REFERENCES FOR CHAPTER 11

CDC. (1994) Dietary fat and total food-energy intake:
       Third  National   Health  and   Nutrition
       Examination Survey, Phase 1,1988-91. Center
       for Disease Control.  Morbidity and Mortality
       Weekly Report, February 25,1994:  43(7)118-
       125.
Cresanta, J.L.; Farris, R.P.; Croft, J.B.; Frank, G.C.;
       Berenson, G.S.  (1988)  Trends in fatty  acid
       intakes of 10-year-old children, 1973-1982. J
       AmDietAssoc 88: 178-184.
Devaney, B.; Kalb, L.; Brief el, R.; Zavitsky-Novak, T.;
       Clusen, N; Ziegler, P. (2004) Feeding Infants
       and Toddlers Study:  overview of the study
       design.  J Am Diet Assoc 104(Suppl 1): S8-
       S13.
Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004)
       Feeding  Infants and  Toddlers Study:  what
       foods are infants and toddlers eating.  J Am
       Diet Assoc 104 (Suppl): S22-S30.
Fox, M.K.; Reidy, K.; Karwe, V.; Ziegler, P. (2006)
       Average portions of foods commonly eaten by
       infants and toddlers in the United States. J Am
       Diet Assoc. 106 (Suppl 1):  S66-S76.
Frank, G.C.; Webber,L.S.;Farris,R.P.;Berenson,  G.S.
       (1986) Dietary databook: quantifying dietary
       intakes of infants, children, and adolescents, the
       Bogalusa heart study, 1973-1983.   National
       Research   and  Demonstration   Center  -
       Arteriosclerosis, Louisiana  State University
       Medical Center, New Orleans, Louisiana.
Goldman, L. (1995) Children - unique and vulnerable.
       Environmental  risks  facing  children  and
       recommendations for response.  Environ Health
       Perspect 103(6): 13-17.
Mennella, J.; Ziegler, P.;Briefel,R.; Novak, T. (2006)
       Feeding Infants and Toddlers Study: the types
       of foods fed to Hispanic infants and toddlers.
       J Am Diet Assoc  106 (Suppl 1): S96-S106.
Nicklas, T.A. (1995)  Dietary studies of children:  The
       Bogalusa Heart Study experience. J Am  Diet
       Assoc  95:1127-1133.
Nicklas,  T.A.;  Webber,  L.S.; Srinivasan,  S.R.;
       Berenson, G.S.   (1993)   Secular trends  in
       dietary intakes and cardiovascular risk factors
       in 10-y-old children: the Bogalusa heart study
       (1973-1988).  Am JClinNutr 57:930-937.
Ponza, M.;  Devaney, B.; Ziegler, P.; Reidy, K.;
       Squatrito, C. (2004) Nutrient intakes and food
       choices of infants and toddlers participating in
       WIC.  JAmDietAssoc 104(Suppl): S71-S79.
Smiciklas-Wright, H.; Mitchell, D.C.;  Mickle,  S.J.;
       Cook, A.J.;  Goldman,  J.D. (2002)  Foods
       commonly eaten in the United States: quantities
       consumed per eating occasion and in a  day,
       1994-1996.   U.S. Department of Agriculture
       NFS Report No. 96-5, pre-publication version,
       252 pp.
USD A. (1999a) Food and nutrient intakes by children
       1994-96, 1998: Table Set 17. Beltsville, MD:
       Food  Surveys Research Group,  Beltsville
       Human Nutrition Research Center, Agricultural
       Research   Service,  U.S.   Department   of
       Agriculture.
USD A. (1999b) USD A Nutrient Database for Standard
       Reference, Release  13. Agricultural Research
       Service,   Nutrient   Data   Laboratory.
       http://www.nal.usda.gov/fnic/foodcomp
USD A.  (2000)  1994-96, 1998 Continuing Survey of
       Food  Intakes by Individuals  (CSFII).  CD-
       ROM.    Agricultural  Research   Service,
       Beltsville Human Nutrition Research Center,
       Beltsville, MD.  Available from the National
       Technical Information  Service, Springfield,
       VA; PB-2000-500027.
USDA. (2007) USDA National Nutrient Database for
       Standard Reference, Release 20. Agricultural
       Research Service, Nutrient Data Laboratory
       Home Page,
       http://www.ars.usda.gov/ba/bhnrc/ndl
U.S. EPA.  (2000)  Food commodity intake database
       [FCID raw  data file]. Office  of Pesticide
       Programs, Washington, DC. Available from the
       National  Technical  Information  Service,
       Springfield, VA; PB2000-5000101.
U.S. EPA. (2005) Guidance on Selecting Age Groups
       for  Monitoring  and  Assessing  Childhood
       Exposures to Environmental Contaminants.
       U.S.  Environmental   Protection   Agency,
       Washington, D.C., EPA/630/P-03/003F.
U.S. EPA.  (2007) Analysis of fat intake based on the
       U.S. Department of Agriculture's  1994-96,
       1998 Continuing Survey of Food Intakes by
       Individuals   (CSFII).   National Center  for
       Environmental Assessment, Washington,  DC;
       EPA/600/R-05/021F.   Available  from  the
       National  Technical  Information   Service,
       Springfield,   VA,   and   online    at
       http ://www. epa.gov/ncea.
Child-Specific Exposure Factors Handbook
September 2008	
                                          Page
                                         11-13

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Table 11-3. Per Capita Intake of Total Meat and Dairy Products (g/kg-day as
. „ ,, Percent
Age Group N „
Consuming

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222

Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.

40.0
97.3
98.8
98.7
98.8

79.5
99.8
100.0
100.0
99.8

Source: Based on unpublished U.S. EPA
Mean

1.2
4.1
4.1
2.9
2.1

12.6
36.7
23.3
13.6
5.6

analysis
SE

0.1
0.1
0.05
0.05
0.05

0.9
0.7
0.3
0.4
0.2

of 1994-96,
consumed)
Percentiles
1st
Total
0.0
0.0
0.0
0.0
0.0
Total
0.0
0.4
1.1
0.3
0.01

5th
Meat
0.0
0.2
0.6
0.4
0.2
Dairy
0.0
3.9
4.2
1.8
0.2

10th

0.0
0.8
1.2
0.8
0.5

0.0
7.7
7.0
3.5
0.5

25th

0.0
1.9
2.2
1.5
1.0

1.0
17.4
13.0
6.7
1.5

50th

0.0
3.6
3.6
2.5
1.9

8.0
31.3
20.8
11.7
4.2

75th

1.6
5.7
5.4
3.8
2.7

14.1
49.8
30.9
18.5
8.1

90th

4.2
8.0
7.7
5.4
3.8

24.1
72.1
42.0
26.0
12.5

95th

6.7
9.8
9.4
6.5
4.8

48.7
88.3
49.4
31.5
15.5

99th 100th

10.7 29.6
14.1 20.6
12.7 23.4
9.6 18.0
7.1 30.3

127 186
126 223
67.7 198
42.7 80.6
25.4 32.7

1998 CSFII.
                                                                                                                                                                                                    s
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Table 11-4. Consumer Only Intake
Age Group N Mean
SE
of Total Meat and
Dairy Products (g
/(kg-day as consumed)
Percentiles
1st
5th
10th
25th
50th
75th
90th
95th
99th
100th
Total Meat
Birth to 1 year 575
1 to 2 years 2,044
3 to 5 years 4,334
6 to 12 years 2,065
13 to 19 years 1,208
3.0
4.2
4.2
2.9
2.1
0.2
0.1
0.1
0.1
0.1
0.01
0.04
0.04
0.1
0.02
0.1
0.6
0.8
0.5
0.3
0.3
1.0
1.2
0.9
0.6
1.0
2.1
2.2
1.5
1.1
2.2
3.6
3.6
2.5
1.9
4.2
5.7
5.5
3.9
2.8
7.4
8.1
7.7
5.4
3.8
9.2
9.8
9.4
6.5
4.8
12.9
14.1
12.7
9.6
7.1
29.6
20.6
23.4
18.0
30.3
Total Dairy
Birth to 1 year 1,192
1 to 2 years 2,093
3 to 5 years 4,390
6 to 12 years 2,089
13 to 19 years 1,221
N = Sample size.
SE = Standard error.
Source: Based on unpublished
15.9
36.8
23.3
13.6
5.6

U.S
1.0
0.7
0.3
0.4
0.2

0.03
0.4
1.1
0.3
0.01

EPA analysis of 1994-96,
0.8
4.2
4.2
1.8
0.3

1998
1.9
7.8
7.0
3.5
0.5

CSFII.
5.8
17.4
13.0
6.7
1.5


10.2
31.3
20.8
11.7
4.2


16.0
49.8
30.9
18.5
8.1


27.7
72.1
42.0
26.0
12.5


57.5
88.3
49.4
31.5
15.5


141.8
126.2
61.1
42.7
25.4


185.6
223.2
198.4
80.6
32.7


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Table 11-5. Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed)
Percent , , __
Mean SE
Age Group N Consuming
Beef
Birth to 1 year 1,486 253 0.41 0.04
1 to 2 years 2,096 85.5 1.7 0.06
3 to 5 years 4,391 90.8 1.8 0.04
6 to 12 years 2,089 92.1 1.3 0.04
13tol9years 1,222 91.1 1.0 0.05
Percent , , „„
Mean SE
Consuming
Pork
17.7 0.15 0.02
69.7 0.72 0.03
79.8 0.84 0.02
82.4 0.59 0.03
81.5 0.40 0.03
Percent , , „„
Mean SE
Consuming
Poultry
30.1 0.66 0.05
73.7 1.7 0.05
73.0 1.5 0.03
67.1 0.93 0.03
65.5 0.68 0.03
Percent , , „„
Mean SE
Consuming
Eggs
27.9 0.30 0.04
92.3 1.3 0.04
95.1 0.91 0.03
95.8 0.51 0.02
95.4 0.33 0.02
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
                                                                                                                                                                                                 S
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Table 11-6. Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed)
Age Group N Mean SE
Beef
Birth to 1 year 361 1.6 0.2
1 to 2 years 1,795 2.0 0.06
3 to 5 years 3,964 1.9 0.04
6 to 12 years 1,932 1.4 0.04
13 to 19 years 1,118 1.1 0.05
N Mean SE
Pork
248 0.83 0.08
1,488 1.0 0.04
3,491 1.1 0.03
1,731 0.72 0.03
1,002 0.50 0.03
N Mean SE
Poultry
434 2.2 0.1
1,552 2.2 0.06
3,210 2.0 0.04
1,421 1.4 0.04
808 1.0 0.04
N Mean SE
Eggs
402 1.1 0.1
1,936 1.4 0.04
4,171 0.96 0.03
2,001 0.53 0.02
1,167 0.34 0.02
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII.
                                                                                                                                                                                                         «««.
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Age Group
Table
Sample
Size
1 1-7. Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (
Total
Beef
Pork
Lamb, _
. Organ
veal,
meats
game
Frankfurters,
sausages,
luncheon
meats
g/day)
Poultry
Total
Chicken

Eggs

Mixtures,
mainly meat/
poultry/
fish
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
24
80
94
87
101
115
121
112
93
1"
5
7
6
8
10
14
11
8
_a,b
2
6
4
6
6
6
6
5
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_a,b _a,b
_b _a,b
_b _a,b
2
13
18
15
19
22
22
21
17
3
12
17
15
19
20
22
21
16
2
12
16
14
18
19
19
19
15
3
13
18
16
13
13
13
13
13
16
43
41
42
43
49
51
47
42
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
151
154
250
18
19
30
7
7
12
_a,b _a,b
_a,b _a,b
1" 0
24
24
28
23
22
31
21
20
26
11
12
22
71
72
134
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
121
130
158
17
18
21
4
5
5
_a,b _a,b
_a,b _a,b
_a,b _a,b
18
19
15
19
20
21
16
17
19
10
11
13
55
60
85
Males and Females
9 years and under
19 years and under
9,309
11,287
110
152
12
18
5
7
_b _a,b
_a,b _a,b
19
20
18
22
17
19
12
14
50
76
* Estimate is not statistically reliable due to small sample size reporting intake.
b Value less than 0.5
but greater than 0.
Note: Consumption amounts shown
Source: USDA, 1999a.

are representative of the


first day

of each participant's survey response.






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 1

Table 11-8. Percentage of Individuals Consuming
Age Group
Sample
Size
Total
Beef
Lamb,
Pork veal,
game
Meats and Eggs, by Sex and Age (%)
Frankfurters,
Organ sausages,
meats luncheon
meats
Poultry
Total
Chicken
Eggs
Mixtures,
mainly meat/
poultry/
fish
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
26.0
77.4
85.2
81.4
86.2
86.2
87.1
86.5
77.5
2.1
11.9
16.2
14.1
13.8
16.1
18.2
16.0
13.7
1.1 "
7.3
14.9
11.2
13.3
13.8
13.2
13.4
11.2
0.2"
0.8"
0.8"
0.8"
0.5"
0.5"
0.6"
0.5
0.6
0.2"
0.2"
0.2"
0.2"
a,b
0.2"
0.2"
0.2"
0.2"
6.1
26.3
33.2
29.9
36.4
37.0
35.1
36.1
30.4
6.3
24.0
27.6
25.8
28.3
27.4
27.7
27.8
24.5
5.0
23.1
25.6
24.4
26.0
25.1
24.8
25.3
22.6
6.7
22.8
27.3
25.1
19.8
16.9
16.4
17.7
18.9
13.7
32.2
31.4
31.8
29.2
30.5
30.8
30.2
28.8
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
87.4
87.8
86.8
20.1
22.0
24.2
11.9
12.2
15.8
0.4"
0.4"
0.6"
0.1"
0.2"
0.0
37.4
36.2
31.8
24.8
22.9
20.6
22.3
20.5
17.6
15.1
15.6
17.0
36.2
35.7
38.3
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
84.6
86.5
80.1
19.4
20.2
22.0
9.2
10.0
11.2
0.4"
0.4"
0.1 "
0.2"
0.1 "
0.1 "
33.5
33.1
24.6
23.1
22.9
21.6
20.2
19.8
18.9
13.4
13.3
15.0
32.4
32.8
34.0
Males and females
9 years and under
19 years and under
9,309
11,287
* Estimate is not statistically
Note: Percenta£
80.9
82.8
16.1
19.6
reliable due to small
10.9
12.1
sample size reportin
0.5
0.4
g intake.
0.2"
0.1 "

24.3
22.7

24.3
22.7

22.0
20.1

17.1
16.4

31.0
33.3

es shown are representative of the first day of each participant's survey response.
Source: USD A, 1999a.
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Table 1 1-9. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day)

Age Group


_ , lotalMUK
S*mple and Milk
Size ,
Products
Milk, Milk Drinks, Yogurt
Total
Fluid Milk
Total
Whole
Lowfat
Skim
Yogurt
Milk
Desserts
Cheese
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
762
546
405
474
419
407
417
414
477
757
526
377
450
384
369
376
376
447
61
475
344
408
347
328
330
335
327
49
347
181
262
166
147
137
150
177
11
115
141
128
150
149
159
153
127
a,b
5'
17
11
26
27
25
26
18
4
14
10
12
10
10
9
10
10
3
11
16
14
22
23
25
23
18
1
9
11
10
12
14
14
13
11
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
450
450
409
405
402
358
343
335
303
127
121
99
176
172
158
29
33
40
6
6
3"
31
35
29
13
12
19
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
380
382
269
337
336
220
288
283
190
105
108
66
146
136
92
26
29
30
4
4
4"
29
30
29
13
14
14
Males and Females
9 years and under
19 years and under
9,309
11,287
a Estimate is not statistically
453
405
reliable due to
417
362
small sample
323
291
153
121
141
135
22
29
8
6
23
27
12
14
size reporting intake.
b Value less than 0.5, but greater than 0.
Note: Consumption
Source: USD A, 1999a
amounts shown are representative of the first day of each participant's





survey response.









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 1

Table 11-10. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%)


Total
^ Sample Milk and
Age Group
Size Milk
Products
Milk, milk drinks, yogurt
Total
Fluid Milk
Total Whole
Lowfat
Skim
Yogurt
Milk
Desserts
Cheese
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
85.4
95.3
91.6
93.4
94.3
93.2
93.1
93.5
92.5
84.6
92.7
87.3
90.0
88.3
87.8
86.4
87.5
88.0
11.1
87.7
84.3
86.0
84.6
85.0
81.2
83.6
75.7
8.3
61.7
44.8
53.0
42.5
41.3
38.1
40.6
41.0
2.4
26.5
36.3
31.5
39.5
40.4
41.7
40.6
32.9
0.2"
1.5"
5.2
3.4
6.8
7.7
6.5
7.0
4.9
3
1
10.0
6
8
8
4
7.3
5
5
6
6
8
5
2
6
4.5
13.9
17.5
15.8
21.4
21.7
21.4
21.5
17.5
6.0
29.7
32.6
31.2
37.0
36.9
34.9
36.3
30.9
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
93.2
92.3
81.3
85.5
84.6
65.8
80.7
79.0
59.6
32.4
30.8
22.6
44.3
43.1
30.7
8.6
9.5
7.0
3
3
1
8
7
7"
24.0
25.0
13.6
34.6
32.3
37.1
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
90.2
90.2
75.4
82.5
81.5
54.0
77.5
76.0
49.7
31.5
33.2
17.5
40.8
37.8
23.9
8.1
8.4
9.5
2
3
9
0
2.2'
24.1
22.4
17.1
30.9
31.9
36.1
Males and Females
9 years and under
19 years and under
9,309
11,287
a Estimate is not statistically
92.2
86.7
86.4
75.6
reliable due to small
Note: Percentages shown are representative of the firs!
Source: USDA, 1999a



77.1
68.1
37.4
30.1
36.8
33.1
6.3
7.5
5
3
3
8
20.1
18.6
31.7
33.5
sample size reporting intake.
day of each participant's survey response.








                                                                                                                                                                                                 s
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   a

   &
Table 11-11. Quantity (as consumed) of Meat and Dairy
Products Consumed Per Eating Occasion and Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (grams)
2 to 5 years old
Male and Female
(N = 2,109)
Food category PC
Mean
SEM
6 to
1 1 years old
Male and Female
(N = 1,432)
PC
Mean
SEM
PC
Male
(N = 696)
Mean
12 to 19 years old


SEM


PC
Female
(N = 702)
Mean


SEM
Meats
Beefsteaks 11.1
Beefroasts 5.2
Ground beef 59.5
Ham 6.9
Pork chops 11.0
Bacon 10.4
Pork breakfast sausage 5.3
Frankfurters and luncheon meats 51.7
Total chicken and turkey 63.8
Chicken 44.6
Turkey 5.1

Fluid milk (all) 92.5
Fluid milk consumed with cereal 68.1
Whole milk 50.0
Whole milk consumed with cereal 33.8
Lowfatmilk 47.5
Lowfat milk consumed with cereal 31.5
Skim milk 7.8
Skim milk consumed with cereal 4.9
Cheese, other than cream or 53.2
cottage 18.4
Ice cream and ice milk 8.0
Boiled, poached, and baked eggs 17.3
Fried eggs 10.4
Scrambled eggs
a Indicates a statistic that is potentially
PC = Percent consuming at least once in
SEM = Standard error of the mean.
58
49
31
35
48
15
33
49
46
52
63

196
149
202
161
189
136
171
131
24
92
36
48
59

4
5
1
4
3
1
2
1
1
1
7

3
4
3
5
3
4
9
11
1
3
3
1
4

11.3
4.8
63.7
8.5
10.1
9.7
6.0
50.9
53.8
36.0
5.7
Dairy
89.2
64.7
39.5
26.2
52.8
32.7
11.1
7.5
50.4
21.1
8.2
14.0
7.1

87
67
41
40
62
19
32
57
62
70
66
Products
241
202
244
212
238
198
225
188
29
135
34
58
72

9
7
1
4
4
2
3
2
2
3
5

4
5
7
11
4
4
9
14
1
4
3
2
5

9.5
5.1
73.4
11.6
11.6
14.9
6.3
46.7
58.4
34.3
8.2

72.3
44.4
30.0
14.8
39.6
24.3
9.7
6.5
61.1
14.2
5.0
14.9
7.1

168
233"
66
68
100
25
40"
76
100
117
117

337
276
333
265
326
277
375
285"
38
221
44"
83
72

14
149"
3
7
8
2
4"
3
4
5
14

8
10
13
18
8
12
38
23"
2
12
9"
5
5

9.4
5.5
61.5
9.9
8.5
11.1
3.3
38.5
54.1
36.1
5.8

64.4
42.7
22.4
14.1
32.4
21.1
13.5
8.3
53.9
15.2
7.7
13.5
8.9

112
97"
52
40
72
18
40"
57
71
80
60"

262
222
258
235
262
227
255
181
27
187
45
59
103

10
16"
3
5
7
1
5"
3
2
3
9"

8
8
7
13
13
12
14
13
1
14
7
3
9

unreliable because of small sample size or large coefficient of variation.
2 days.





















Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
                                                                                                             Q
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                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-12. Characteristics of the FITS Sample Population

Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition
Source: Devaney et al., 2004.
Sample Size

1,549
1,473

862
483
679
374
308
316

367
2,641
14

2,417
225
380

1,389
1,014
577
42

48
48
221
359
723
588
311
272
452

821
2,196
5
3,022
Program for Women, Infants, and Children.

Percentage of Sample

51.3
48.7

28.5
16.0
22.5
12.4
10.2
10.4

12.1
87.4
0.5

80.0
7.4
12.6

46.0
33.6
19.1
1.3

1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9

27.2
72.6
0.2
100.0


Page
11-22
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-13. Percentage of Infants
and Toddlers Consuming Meat or Other Protein Sources
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food
Cow's Milk
Whole
Reduce-fat or non-fat
Unflavored
Flavored
Soy Milk
Any Meat or Protein Source
Baby Food Meat
Non-baby Food Meat
Other Protein Soources
Dried Beans and Peas, Vegetarian Meat
Eggs
Peanut Butter, Nuts, and Seeds
Cheese
Yogurt
Protein Sources in Mixed Dishes
Baby Food Dinners
Beans and Rice, Chilli, Other Bean Mixtures
Mixtures with Vegetables and/or Rice/Pasta
Soup"
Types of Meat'
Beef
Chicken or Turkey
Fish and Shellfish
Hotdogs, Sausages, and Cold cuts
Pork/Ham
Other
4 to 6 7 to 8
months months
0.8
0.5
0.3
0.8
0.0
0.0
14.2
1.7
1.5
2.7
0.6
0.7
0.0
0.4
1.2
11.0
9.5
0.0
0.9
0.9

0.9
2.0
0.0
0.0
0.3
0.3
2.9
2.4
0.5
2.9
0.0
0.5
54.9
4.0
8.4
9.7
1.3
2.9
0.5
2.1
4.1
43.3
39.8
0.0
1.2
3.4

2.6
7.3
0.5
2.1
1.7
0.6
9 to 11
months
20.3
15.1
5.3
19.5
0.9
1.7
79.2
3.1
33.7
36.1
3.3
7.3
1.9
18.5
15.7
46.2
33.5
0.9
4.7
10.1

7.7
22.4
1.9
7.1
4.0
2.5
a The amount of protein actually provided by soups varies. Soups could not be sorted reliably
soups were assigned the same two-digit food code and many food descriptions lacked detail
b Includes baby food and non-baby food sources.
Source: Fox et al., 2004.



12tol4 15tol8 19 to 24
months months months
84.8
68.8
17.7
84.0
1.8
1.5
91.3
1.1
60.3
59.2
7.0
17.0
8.8
34.0
14.9
30.1
10.2
1.2
8.2
12.5

16.1
33.0
5.5
16.4
9.7
2.8
88.3
71.1
20.7
87.0
4.4
3.9
92.7
0.0
76.3
66.8
6.6
25.0
11.6
39.1
20.2
25.5
2.4
2.1
9.0
13.8

16.3
46.9
8.7
20.1
11.2
2.1
87.7
58.8
38.1
86.5
5.6
3.8
97.2
0.0
83.7
68.9
9.9
25.2
10.4
41.1
15.3
20.5
1.3
2.0
7.8
11.5

19.3
47.3
7.1
27.0
13.9
3.9
into different food groups because all
about major soup ingredients.



Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-23

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                                                               Child-Specific Exposure Factors Handbook

                                                 Chapter 11 - Intake of Meats, Dairy Products and Fats
                        Table 11-14. Characteristics of WIC Participants and Non-participants" (Percentages)
                                 Infants 4 to 6 months
                                                              Infants 7 to 11 months
                                                                                           Toddlers 12 to 24 months
                                WIC
                             Participant
                                     Non-
                                  participant
  WIC
Participant
  Non-
participant
  WIC
Participant
                                                                                                         Non-
                                                                                                       participant
Gender
  Male                         55
  Female                        45
Child's Ethnicity
  Hispanic or Latino               20
  Non-Hispanic or Latino          80
Child's Race
  White                         69
  Black                         15
  Other                         22
Child In Day Care
  Yes                          39
  No                           61
Age of Mother
  14 to 19 years                  18
  20 to 24 years                  33
  25 to 29 years                  29
  30 to 34 years                   9
  35 years or Older                9
  Missing                        2
Mother's Education
  11 ""Grade or Less               23
  Completed High School          35
  Some Postsecondary             33
  Completed College               7
  Missing                        2
Parent's Marital Status
  Married                       49
  Not Married                    50
  Missing                        1
Mother or Female Guardian Works
  Yes                          46
  No                           53
  Missing                        1
Urbanicity
  Urban                         34
  Suburban                      36
  Rural                         28
  Missing                         2
  Sample Size (Unweighted)        265
                                               54
                                               46
                                               11
                                               89
                                               **

                                               84
                                                4
                                               11


                                               38
                                               62
                                               **

                                                1
                                               13
                                               29
                                               33
                                               23
                                                7
                                                2
                                               19
                                               26
                                               53
                                                1
                                               **

                                               93
                                                7
                                                1


                                               51
                                               48
                                                1
                                                55
                                                31
                                                13
                                                 1
                                               597
                                                     55
                                                     45
                                                     24
                                                     76


                                                     63
                                                     17
                                                     20


                                                     34
                                                     66


                                                     13
                                                     38
                                                     23
                                                     15
                                                     11
                                                      1


                                                     15
                                                     42
                                                     32
                                                      9
                                                      2
                                                     57
                                                     42
                                                      1


                                                     45
                                                     54
                                                      1


                                                     37
                                                     31
                                                     30
                                                       2
                                                    351
                   51
                   49
                  92
                  **

                  86
                    5
                    9
                  **

                  46
                  54
                  **

                    1
                  11
                  30
                  36
                  21
                    1
                  **

                    2
                  20
                  27
                  51
                    0
                  **

                  93
                    7
                    0
                  **

                  60
                  40
                    0
                  **

                   50
                   34
                   15
                    1
                   57
                   43
                  22
                  78


                  67
                  13
                  20


                  43
                  57
                  33
                  29
                  18
                  11
                   0


                  17
                  42
                  31
                   9
                   1


                  58
                  41
                   1


                  55
                  45
                   0


                   35
                   35
                   28
                    2
                  205
                   52
                   48
                   10
                   89
                   **

                   84
                    5
                   11
                   *

                   53
                   47
                   **

                    1
                   14
                   26
                   34
                   26
                    1
                   **

                    3
                   19
                   28
                   48
                    2
                   11
                    1
                   *

                   61
                   38
                    1
                   48
                   35
                   16
                    2
                  791
  WIC
X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants for
each of the three age groups. * P<0.05; ** P>0.01; non-participants significantly different from WIC participants on the variable.
= Special Supplemental Nutrition Program for Women, Infants, and Children.
  Source:  Ponza et al., 2004.
Page
11-24
                                                     Child-Specific Exposure Factors Handbook
                                                    	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-15. Food Choices for Infants and Toddlers by WIC


Cow's Milk
Meat or Other Protein Sources
Baby Food Meat
Non-Baby Meat
Eggs
Peanut Butter, Nuts, Seeds
Cheese
Yogurt
Sample Size (unweighted)
Infants 4 to 6 months Infants 7 to
WIC Non- WIC
Participant participant Participant
1.0 0.6 11.4

0.9 2.0 3.3
3.7 0.5** 25.0
0.9 0.6 8.5
0.0 0.0 1.4
0.0 0.6 9.0
0.8 1.4 5.5
265 597 351
Participation Status
11 months
Non-
participant
13.2

3.6
22.0
4.2**
1.3
12.5
13.3**
808

Toddlers 12
WIC
Participant
92.3

0.0
77.7
24.1
12.9
38.5
9.3
205

to 24 months
Non-
participant
85.8*

0.3
75.1
23.0
9.8
38.8
18.9**
791
* = P<0.05; non-participants significantly different from WIC participants.
** = P<0.01; non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponzaetal., 2004.




Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-25

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                                                               Child-Specific Exposure Factors Handbook

                                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
               Table 11-16. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
                                     Milk, Meats or Other Protein Sources on A Given Day
                                          Age 4 to 5 months
                             Age 6 to 11 months
                                         Age 12 to 24 months
Hispanic
(N=84)
Non-Hispanic
(N=538)
Hispanic
(N=163)
Non-Hispanic
(N=l,228)
Hispanic
(N=124)
Non-Hispanic
(N=871)
  Milk
  Fed Any Cow's or Goat Milk
   Fed Cow's Milk
    Whole
    Reduced Fat or Non-fat
  Meat or Other Protein Sources
   Any Meat or Protein Source*
   Non-Baby Food Meat
   Other Protein Sources
    Beans and Peas
    Eggs
    Cheese
    Yogurt
   Protein Sources in Mixed Dishes
    Baby Food dinners
    Soupb
  Types of Meat*
9.7T

1.4T
1.4T
7.5T
6.9t
              5.3
4.4
3.9
  7.5T

  5.6T
  2.2t

 71.6
 22.5
 26.5
 5.8T
  9.5
 11.2
  7.7
 44.8
24.7*
16.3**
11.3

 8.3
 3.0

62.0
19.2
21.2
 1.8
 4.2
 9.4
 9.8
41.6
35.3
 5.1
 85.6

 61.7
 29.0

 90.3
 72.3
 70.1
19.1*
 26.4
 29.3
 15.7
 33.3
 3.5T
23.4*
87.7

66.3
27.0

94.7
76.0
65.3
 6.5
22.5
40.2
17.0
22.7
 3.9
10.7
Beef
Chicken and Turkey
Hotdogs, Sausages, and Cold Cuts
Pork/Ham
5.0T
11.2
7.2T
3.8T
4.6
11.9
3.4
1.7
25.2
46.5
14.8
11.7
16.0
43.6
23.3
12.1
          Includes baby food and non-baby food sources.
          The amount of protein actually provided by soups varies.  Soups could not be sorted reliably into different food groups because
          many food descriptions lacked detail about major soup ingredients.
          = Less than 1 percent of the group consumed this food on a given day.
          = Significantly different from non-Hispanic at the P<0.05.
          = Significantly different from non-Hispanic at the P>0.01.
          = Statistic is potentially unreliable because of a high coefficient of variation.
          = Sample size.
  Source:   Mennella et al., 2006.
Page
11-26
                       Child-Specific Exposure Factors Handbook
                      	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-17. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly Consumed by
Infants from the 2002 Feeding Infants and Toddlers Study
Food group
Non-baby food meats
Cheese
Scrambled eggs
Yogurt
Baby food dinners
= Cell size was too small to g
N = Number of respondents.
SEM = Standard error of the mean
Source: Fox et al., 2006.
Reference Unit

ounce
ounce
cup
ounce
ounce
enerate a reliable estimate.
4 to 5 months
(N=624)

2.9±0.24

6 to 8 months 9 to 1 1 months
(N=708) (N=687)
Mean± SEM
0.9±0.16
3.3±0.09


0.8±0.05
0.7±0.05
0.2±0.02
3.1±0.20
3.8±0.11

Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-27

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                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-18. Average Portion
Sizes Per Eating Occasion of Meats and Dairy Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study
Food Group
Milk
Milk
Milk, as a beverage
Milk, on cereal
Meats and other protein sources
All meats
Beef
Chicken or turkey, plain
Hot dogs, luncheon meats, sausages
Chicken, breaded"

Scrambled eggs
Peanut butter
Yogurt
Cheese
Reference unit


fluid ounce
fluid ounce
fluid ounce

ounce
ounce
ounce
ounce
ounce
nugget
cup
tablespoon
ounce
ounce
12 to 14 months
(N=371)


5.6±0.14
5.7±0.14
3.4±0.37

1.2±0.06
0.8±0.08
1.3±0.10
1.3±0.13
1.5±0.14
2.4±0.22
0.2±0.02
0.7±0.08
3.4±0.19
0.8±0.05
15 to 18 months
(N=312)
Mean ± SEM

5.9±0.14
6.1±0.14
2.7±0.26

1.3±0.08
1.2±0.15
1.3±0.16
1.5±0.13
1.5±0.13
2.4±0.21
0.3±0.03
0.7±0.09
3.8±0.26
0.8±0.05
19 to 24 months
(N=320)


6.2±0.17
6.4±0.17
3.6±0.29

1.3±0.07
1.2±0.14
1.3±0.10
1.5±0.12
1.8±0.12
2.8±0.19
0.3±0.02
0.9±0.13
3.8±0.28
0.7±0.04
* Not included in total for all meats because weight includes breading.
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.




Page
11-28
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-19. Total Fat Intake (Per capita; g/day)

Age Group*
N
Mean
SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year



all
female
male
1,422
728
694
29
28
30
18
17
18
0.03
0.03
0.04
19
18
20
31
30
32
40
39
40
59
57
61
107
92
107
Birth to <1 month



Ito



3 to



6 to



Ito


2 to



3 to


6 to



all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all


female
male
16to<21 years
all


N
SE
female
male
88
50
38

245
110
135

411
223
188
678

345
333
1,002
499
503

994
494
500
4,112
2,018
2,094

1,553
742
811
975
493
482
743
372
371
17
19
15

22
20
23

28
27
30
33

32
34
46
45
46

51
49
52
59
56
61

68
64
72
80
69
91
85
79
92
16
15
18

18
16
19

17
17
18
17

17
16
19
18
20

21
20
21
22
21
23

24
22
25
38
29
42
47
39
53
0
0
0

0
0
0

0.10
0.02
0.15
8.5

5.1
11
24
25
23

27
24
29
34
33
35

41
38
43
42
37
50
37
35
41
0
0
0

0
0
0

20
16
22
25

24
25
33
33
32

37
35
39
44
43
45

50
48
55
56
49
64
54
49
57
Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
Exposures to Environmental Contaminants.
= Sample size.
= Standard error.
Source: Based on U.S.
EPA, 2007.




19
18
19

27
24
28

31
29
31
34

33
34
43
43
44

48
46
50
56
54
59

66
61
70
74
65
84
76
75
77
32
29
31

34
33
34

39
38
39
43

43
44
55
54
56

60
59
61
70
68
72

81
77
86
97
82
111
108
96
114
52
39
43

47
45
55

52
51
50
62

62
62
79
77
80

87
83
89
99
96
103

111
101
115
145
123
163
168
154
186
64
52
64

75
50
75

107
74
107
100

92
100
159
116
159

197
127
197
218
194
218

179
156
179
342
259
342
463
317
463
Monitoring and Assessing Childhood




Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-29

-------
                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-20. Total Fat Intake (Per capita; g/kg-day)

Age Group*
N
Mean
SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year



all
female
male
1,422
728
694
4.0
4.1
4.0
2.8
2.8
2.8
0.01
0.01
0.01
2.3
2.4
2.3
4.1
4.3
4.0
5.6
5.8
5.5
8.9
8.7
9.2
20
18
20
Birth to <1 month



Ito



3 to



6 to



Ito


2 to



3 to


6 to


all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
88
50
38

245
110
135

411
223
188

678
345
333
1,002
499
503

994
494
500
4,112
2,018
2,094
1,553
742
811
5.2
5.9
4.3

4.5
4.3
4.7

4.1
4.2
4.1

3.7
3.7
3.6
4.0
4.1
3.9

3.6
3.7
3.6
3.4
3.4
3.5
2.6
2.4
2.7
4.9
4.6
5.3

3.8
3.6
3.9

2.7
2.8
2.5

1.8
1.9
1.7
1.7
1.6
1.7

1.5
1.6
1.5
1.3
1.3
1.4
1.1
1.0
1.1
0
0
0

0
0
0

0.01
0.00
0.02

1.0
0.66
1.3
2.1
2.2
1.9

1.9
1.8
2.0
1.9
1.8
1.9
1.3
1.3
1.4
0
0
0

0
0
0

2.4
2.3
2.6

2.7
2.8
2.6
2.8
3.0
2.6

2.6
2.4
2.6
2.4
2.4
2.4
1.7
1.6
1.8
5.7
6.2
4.7

4.9
4.8
4.9

4.3
4.5
4.1

3.8
3.8
3.7
3.7
3.7
3.6

3.4
3.4
3.4
3.2
3.1
3.2
2.3
2.2
2.4
9.1
8.4
9.7

6.8
6.5
7.0

5.7
6.0
5.5

4.8
5.0
4.6
4.7
5.0
4.5

4.4
4.4
4.3
4.0
4.0
4.1
3.0
2.8
3.1
16
13
18

11
11
10

8.2
8.2
8.2

7.0
7.0
6.8
7.1
6.9
7.2

6.4
6.6
6.1
5.8
5.8
5.8
4.2
4.0
4.4
20
16
20

18
14
18

18
18
16

11
9.8
11
12
9.7
12

12
10
12
11
11
11
9.9
7.7
9.9
11 to <16 years



all
female
male
16to<21 years
all


female
male
975
493
482
743
372
371
1.6
1.4
1.8
1.3
1.1
1.4
0.80
0.69
0.86
0.66
0.56
0.73
0.77
0.67
0.88
0.54
0.48
0.63
1.1
0.91
1.2
0.81
0.75
0.85
a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for
to Environmental Contaminants.
N
SE
1.4
1.3
1.6
1.2
1.1
1.2
2.0
1.7
2.1
1.6
1.4
1.7
3.0
2.6
3.3
2.7
2.1
2.9
5.7
5.0
5.7
6.0
4.4
6.0
Monitoring and Assessing Childhood Exposures
= Sample size.
= Standard error.
Source: Based on U.S. EPA, 2007.
Page
11-30
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats

Table
Age Group" N Mean
Birth to <1 year
all 1,301
female 664
male 637
Birth to <1 month
all 59
female 37
male 22
1 to <3 months
all 182
female 79
male 103
3 to <6 months
all 384
female 205
male 179
6 to <12 months
all 676
female 343
male 333
1 to <2 year
all 1,002
female 499
male 503
2 to <3 years
all 994
female 494
male 500
3 to <6 years
all 4,112
female 2,018
male 2,094
6 to <11 years
all 1,553
female 742
male 811
11 to <16 years
all 975
female 493
male 482
16 to <21 years
all 743
female 372
male 371
31
30
32

26
26
25

29
28
31

30
29
31

33
32
34

46
45
46
51
49
52
59
56
61
68
64
72
80
69
91

85
79
92
11-21. Total Fat Intake (Consumers Only; g/day)
SE
16
16
16

13
11
17

14
12
16

16
16
17

16
17
16

19
18
20
21
20
21
22
21
23
24
22
25
38
29
42

47
39
53
Percentiles
10th
7.0
5.1
9.0

6.7
7.8
-

5.8
4.3
8.5

2.5
1.2
4.6

8.9
6.2
11

24
25
23
27
24
29
34
33
35
41
38
43
42
37
50

37
35
41
25th
24
24
25

17
17
-

24
21
27

24
24
25

25
24
25

33
33
32
37
35
39
44
43
45
50
48
55
56
49
64

54
49
57
50th
32
32
33

27
25
-

31
30
31

32
31
33

34
34
34

43
43
44
48
46
50
56
54
59
66
61
70
74
65
84

76
75
77
" Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring
to Environmental Contaminants.
= Percentiles were not calculated for sample sizes
N = Sample size.
SE = Standard error.
Source: Based on U.S. EPA, 2007.


less than 30.





75th
41
40
41

32
32
-

35
35
38

40
39
39

43
43
44

55
54
56
60
59
61
70
68
72
81
77
86
97
82
111

108
96
114
95th
61
58
62

52
39
-

53
46
59

54
52
53

62
62
62

79
77
80
87
83
89
99
96
103
111
101
115
145
123
163

168
154
186
100th
107
92
107

64
52
64

75
50
75

107
72
107

100
92
100

159
116
159
197
127
197
218
194
218
179
156
179
342
259
342

463
317
463
and Assessing Childhood Exposures






Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-31

-------
                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-22. Total Fat Intake (Consumers Only; g/kg-day)

Age Group"
Birth to <1 year
all


female
male
N
1,301
664
637
Vlean
4.4
4.5
4.3
SE
2.6
2.6
2.6
Percentiles
10th
0.94
0.67
1.2
25th
2.9
3.1
2.8
50th
4.3
4.5
4.1
75th
5.8
6.0
5.6
95th
9.2
8.9
9.3
100th
20
18
20
Birth to <1 month



Ito



3 to



6 to



Ito



2 to


3 to


6 to


all
female
male
<3 months
all
female
male
<6 months
all
female
male
<12 months
all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all


female
male
59
37
22

182
79
103

384
205
179

676
343
333

1,002
499
503
994
494
500
4,112
2,018
2,094
1,553
742
811
975
493
482
7.8
8.0
7.4

6.0
5.9
6.1

4.4
4.5
4.3

3.7
3.7
3.6

4.0
4.1
3.9
3.6
3.7
3.6
3.4
3.4
3.5
2.6
2.4
2.7
1.6
1.4
1.8
4.1
3.5
4.9

3.1
2.9
3.3

2.5
2.6
2.4

1.8
1.9
1.7

1.7
1.6
1.7
1.5
1.6
1.5
1.3
1.3
1.4
1.1
1.0
1.1
0.80
0.69
0.86
1.4
2.0
-

1.0
0.80
1.8

0.35
0.14
0.57

1.0
0.75
1.3

2.1
2.2
1.9
1.9
1.8
2.0
1.9
1.8
1.9
1.3
1.3
1.4
0.77
0.67
0.88
5.4
5.3
-

4.1
4.3
4.1

3.1
3.1
3.1

2.7
2.8
2.6

2.8
3.0
2.6
2.6
2.4
2.6
2.4
2.4
2.4
1.7
1.6
1.8
1.1
0.91
1.2
8.0
7.7
-

6.0
6.0
6.0

4.5
4.7
4.2

3.8
3.8
3.7

3.7
3.7
3.6
3.4
3.4
3.4
3.2
3.1
3.2
2.3
2.2
2.4
1.4
1.3
1.6
9.7
9.1
-

7.8
7.7
7.8

5.8
6.1
5.6

4.8
5.0
4.6

4.7
5.0
4.5
4.4
4.4
4.3
4.0
4.0
4.1
3.0
2.8
3.1
2.0
1.7
2.1
16
13
-

12
12
12

8.3
8.2
8.8

7.0
7.0
6.8

7.1
6.9
7.2
6.4
6.6
6.1
5.8
5.8
5.8
4.2
4.0
4.4
3.0
2.6
3.3
20
16
20

18
14
18

18
18
16

11
9.8
11

12
9.7
12
12
10
12
11
11
11
9.9
7.7
9.9
5.7
5.0
5.7
16 to <21 years



all
female
male
743
372
371
1.3
1.1
1.4
0.66
0.56
0.73
0.54
0.48
0.63
0.81
0.75
0.85
1.2
1.1
1.2
" Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring
to Environmental Contaminants.
N
SE
= Percentiles were not calculated for sample sizes
= Sample size.
= Standard error.
less than 30.


1.6
1.4
1.7
and Assessing

2.7
2.1
2.9
6.0
4.4
6.0
Childhood Exposures


Source: Based on U.S. EPA, 2007.
Page
11-32
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11-23. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day)


Age Uroup"


N Mean

SE
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year



1 to<



all
female
male
2 years
all
female
male
140
70
70

109
54
55
45
45
45

75
68
81
16
15
17

20
16
22
28
26
28

52
52
54
35
35
34

61
57
67
45
45
44

74
70
78
54
54
53

85
78
90
77
69
79

108
89
125
100
92
100

159
114
159
2 to <3 years



3to<



6to<



11 to

16 to

all
female
male
6 years
all
female
male
11 years
all
female
male
<16 years
all
<21 years
all
103
58
45

461
217
244

198
71
127

96

68
79
77
81

88
84
92

94
88
97

133

167
20
16
24

25
24
25

25
21
27

53

64
55
55
52

62
59
66

66
58
69

85

98
64
65
61

72
68
76

77
70
78

95

122
74
74
73

84
80
90

88
86
91

121

154
85
79
90

102
95
103

105
100
112

154

189
116
109
121

135
130
136

140
123
168

223

278
133
116
133

218
194
218

178
156
178

342

463
11 -20 years



all
female
male
165
53
112
" Age groups are based on U.S
146
117
160
60
30
65
EPA (2005) Guidance on
90
81
94
105
92
117
139
111
151
168
140
191
254
162
276
463
195
463
Selecting Age Groups for Monitoring and Assessing Childhood
Exposures to Environmental Contaminants.
N
SE
= Sample size









= Standard error.
Source: Based on U.S.
EPA, 2007.








Child-Specific Exposure Factors Handbook
September 2008	
 Page
11-33

-------
                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-24. Total Fat Intake - Top 10% of Animal

Age Group"
N Mean


Fat Consumers (Consumers Only; g/kg-day)
Percentiles
10th
25th
50th
75th
95th
100th
Birth to <1 year



1 to



2 to



3 to


6 to


all
female
male
<2 years
all
female
male
<3 years
all
female
male
<6 years
all
female
male
<11 years
all
female
male
11 to <16 years
all
16to<21 years
all
140
70
70

109
54
55

103
58
45
461
217
244
198
71
127
96
68
4.7
4.8
4.6

6.9
6.6
7.1

6.1
6.2
6.1
5.6
5.5
5.7
4.2
4.2
4.2
3.0
2.5
1.7
1.6
1.7

1.5
1.2
1.6

1.3
1.2
1.3
1.3
1.3
1.3
1.1
1.1
1.1
0.85
0.74
2.8
2.7
2.8

5.1
5.1
5.1

4.6
4.6
4.5
4.2
4.2
4.2
3.0
2.9
3.0
2.0
1.7
3.7
3.7
3.6

5.7
5.7
5.8

5.2
5.2
5.2
4.7
4.5
4.8
3.4
3.3
3.4
2.4
2.0
4.6
4.7
4.4

6.8
6.7
6.9

5.8
5.9
5.6
5.3
5.3
5.3
3.8
3.8
3.8
2.8
2.4
6.0
6.0
5.8

7.7
7.4
8.0

6.7
6.8
6.6
6.2
6.0
6.2
4.6
4.8
4.5
3.3
2.9
7.7
7.7
7.5

9.5
9.3
9.4

8.3
7.9
8.4
8.3
7.8
8.4
6.0
5.8
6.3
4.6
3.7
11
9.5
11

12
9.7
12

9.5
9.5
9.5
11
11
11
9.9
7.7
9.9
5.7
6.0
11 -20 years



N
SE
all
female
male
165
53
112
2.8
2.6
2.9
0.84
0.65
0.90
Age groups are based on U.S. EPA (2005) Guidance on
Exposures to Environmental Contaminants.
= Sample size.
= Standard error.
Source: Based on U.S.
EPA, 2007.


1.9
1.7
1.9
2.1
2.0
2.3
2.7
2.3
2.8
3.1
2.7
3.1
4.4
3.4
4.5
6.0
4.6
6.0
Selecting Age Groups for Monitoring and Assessing Childhood






Page
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 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day)
Age
N
Mean
SD
Percentiles
10th
25th
50th
75th
90th
Minimum
Maximum
Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
37.1
59.1
86.7
91.6
98.6
93.2
107.0
97.7
107.8
17.5
26.0
41.3
38.8
56.1
50.8
53.9
48.7
64.3
18.7
29.1
39.9
50.2
46.0
45.7
53.0
46.1
41.4
25.6
40.4
55.5
63.6
66.8
60.5
69.8
65.2
59.7
33.9
56.1
79.2
82.6
87.0
81.4
90.8
85.8
97.3
46.3
71.4
110.5
114.6
114.6
111.3
130.7
124.0
140.2
60.8
94.4
141.1
153.0
163.3
154.5
184.1
165.2
195.1
3.4
21.6
26.5
32.6
29.3
14.6
9.8
10.0
8.5
107.6
152.7
236.4
232.5
584.6
529.5
282.2
251.3
327.4
Total Animal Fat
6 months
lyear
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
18.4
36.5
49.5
50.1
50.8
54.1
56.2
53.8
64.4
16.0
20.0
28.3
29.4
31.7
39.6
39.8
35.1
48.5
0.7
15.2
20.1
21.3
21.4
20.3
19.8
15.9
15.2
4.2
23.1
28.9
29.1
28.1
30.6
28.5
28.3
30.7
13.9
33.0
42.1
42.9
42.6
45.0
44.8
44.7
51.6
28.4
45.9
66.0
64.4
66.4
64.6
72.8
67.9
86.6
42.5
65.3
81.4
88.9
92.6
97.5
109.4
105.8
128.8
0.0
0.0
10.0
14.1
5.9
0.0
4.7
0.6
2.6
61.1
127.1
153.4
182.6
242.2
412.3
209.6
182.1
230.3
Total Vegetable Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
125
99
135
106
219
871
148
108
159
9.2
15.4
19.3
21.1
24.5
23.7
34.3
27.3
25.7
12.8
14.3
16.3
15.5
18.6
21.6
27.4
22.8
21.3
0.6
3.7
3.8
3.9
5.7
4.3
8.4
5.1
4.2
1.2
6.1
7.9
8.6
10.4
9.5
17.9
11.9
11.7
2.8
11.3
14.8
18.7
21.8
18.3
31.2
22.6
20.8
11.6
18.1
26.6
26.6
33.3
30.6
44.6
38.1
32.9
29.4
38.0
42.9
45.2
48.5
49.0
57.5
54.4
47.6
0.0
0.2
0.7
1.0
0.9
0.6
0.0
0.7
0.0
53.2
70.2
96.6
70.4
109.0
203.7
238.3
132.2
141.5
Child-Specific Exposure Factors Handbook
September 2008	
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                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats

Age
Table 11-25. Fat
N
Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day) (continued)
Mean
SD

10th

25th
Perc entiles
50th

75th

90th
Minimum
Maximum
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
15 years
17 years
N
SD
Source:
125
99
135
106
219
871
148
108
159
0.05
0.05
0.04
0.1
2.3
0.3
0.3
0.4
0.5
0.1
0.2
0.2
0.6
31.1
1.5
2.2
1.5
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
1.9
1.9
4.5
459.2
19.2
25.4
9.5
15.3
= Sample size.
= Standard deviation.
Frank etal., 1986.









Page
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 Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day)

Age




Percentiles

10th
25th
50th
75th
90th




Total Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
4.9
6.1
7.0
6.4
6.1
2.7
2.3
1.7
1.8
2.3
2.8
3.3
2.7
3.7
1.5
1.3
0.8
1.0
2.4
3.0
3.4
3.6
2.9
1.2
1.0
0.8
0.7
3.3
4.1
4.5
4.6
4.0
1.7
1.5
1.2
0.9
4.7
5.7
6.2
5.5
5.2
2.4
2.0
1.5
1.6
6.2
7.5
8.6
8.2
7.0
3.3
2.8
2.1
2.2
8.0
9.5
11.9
9.9
10.0
4.5
3.8
3.1
3.1
0.4
2.3
2.1
2.2
2.0
0.3
0.2
0.2
0.2
13.2
16.4
18.7
16.7
38.2
13.9
10.2
4.7
6.2
Total Animal Fat
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
2.4
3.8
4.0
3.5
3.1
16
1.2
1.0
1.0
2.1
2.1
2.3
2.0
2.1
1.2
0.9
0.6
0.8
0.08
1.7
1.7
1.6
1.3
0.6
0.4
0.3
0.3
0.6
2.4
2.3
2.1
1.7
0.8
0.6
0.5
0.5
2.0
3.4
3.4
3.1
2.6
1.3
0.9
0.8
0.8
3.7
4.9
5.2
4.2
4.0
1.9
1.6
1.3
1.4
5.5
6.5
6.7
6.1
5.4
2.8
2.3
1.9
2.0
0.0
0.0
0.7
0.9
0.4
0.00
0.08
0.01
0.05
9.0
13.6
13.4
13.1
15.4
10.8
5.2
3.1
4.2
Total Vegetable Fat Intake
6 months
lyear
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
125
99
132
106
218
861
147
105
149
1.2
1.6
1.6
1.5
1.5
0.7
0.8
0.5
0.4
1.8
1.6
1.4
1.1
1.2
0.6
0.8
0.4
0.4
0.08
0.4
0.3
0.3
0.4
0.1
0.2
0.09
0.07
0.2
0.6
0.7
0.6
0.6
0.3
0.4
0.2
0.2
0.4
1.2
1.1
1.4
1.2
0.5
0.6
0.4
0.4
1.6
1.9
2.0
2.0
2.1
0.9
0.9
0.7
0.6
4.1
3.8
3.5
3.0
2.8
1.4
1.3
0.9
0.9
0.0
0.02
0.06
0.08
0.06
0.02
0.0
0.01
0.0
8.2
7.6
8.5
5.1
7.3
4.2
8.6
2.2
2.1
Child-Specific Exposure Factors Handbook
September 2008	
 Page
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                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-26. Fat Intake Among Children
Age
N
Mean
SD
Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day) (continued)

10th

25th
Percentiles
50th

75th

90th
Minimum
Maximum
Total Fish Fat Intake
6 months
1 year
2 years
3 years
4 years
10 years
13 years
1 5 years
17 years
N
SD
Source:
125
99
132
106
218
861
147
105
149
0.01
0.01
0.003
0.01
0.2
0.01
0.01
0.01
0.01
0.02
0.03
0.02
0.04
2.0
0.05
0.04
0.03
0.03
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.02
0.0
0.0
0.0
0.0
0.0
0.0
0.04
0.008
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.2
0.3
30.0
0.6
0.4
0.2
0.2
= Sample size.
= Standard deviation.
Frank etal., 1986









Page
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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender"
Total


Age Group N Mean Fat Intake N
(g/day)
2tollmonths 871
1 to 2 years 1,231
3 to 5 year 1,647
6 to 11 years 1,745
12 to 16 years 711
16 to 19 years 785
37.5
50.0
60.4
74.2
85.2
100.5
" Total dietary fat intake includes all fat (i.e
(excluding plain drinking water).
N = Sample size.
Source: Adapted from CDC, 1994.
439
601
744
868
338
308
Males
Mean Fat Intake
(g/day)
38.3
51.6
62.3
79.4
98.1
123.2

N
432
630
803
877
373
397
Females
Mean Fat Intake
(g/day)
36.8
48.4
57.7
69.0
71.3
77.5
, saturated and unsaturated) derived from consumption of foods and beverages
Child-Specific Exposure Factors Handbook
September 2008	
 Page
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Table 1 1-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products"
Product
Moisture
Content
(%)
Total Fat
Content
(%)
Comment
Meats
Beet (composite ot trimmed retail cuts; all grades)


Pork (composite of trimmed retail cuts)

Cured ham

Cured bacon



Lamb (composite of trimmed retail cuts)


Veal (composite of trimmed retail cuts)

Rabbit (domesticated)

Chicken (broilers or fryers)




Duck (domesticated)

Turkey (all classes)


70.62
59.25
60.44
51.43
72.34
60.31
65.11
54.55
63.46
55.93




73.42
61.96
60.70
53.72
75.91
60.16
72.84
57.08
72.82
60.61

75.46
63.79
65.99

59.45

73.77
64.22
48.50
51.84
74.16
64.88
70.40
61.70
71.97
59.42
6.16
9.91
19.24
21.54
5.88
9.66
14.95
17.18
12.90
8.32
45.04
43.27
41.78
40.30
37.27
5.25
9.52
21.59
20.94
2.87
6.58
6.77
11.39
5.55
8.05
8.41
3.08
6.71
7.41
9.12
15.06
12.56
13.60
14.92
5.95
11.20
39.34
28.35
2.86
4.97
8.02
9.73
8.26
13.15
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat
Cooked; lean and fat
Center slice, unheated; lean and fat
Raw, center slice, country style; lean only
Raw
Cooked, baked
Cooked, broiled
Cooked, pan-fried
Cooked, microwaved
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw; lean only
Cooked; lean only
Raw; lean and fat, 1/4 in. fat trim
Cooked; lean and fat, 1/4 in. fat trim
Raw
Cooked, roasted
Cooked, stewed
Raw; meat only
Cooked, stewed; meat only
Cooked, roasted; meat only
Cooked, fried; meat only
Raw; meat and skin
Cooked, stewed; meat and skin
Cooked, roasted; meat and skin
Cooked, fried, flour; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; meat only
Cooked, roasted; meat only
Raw; meat and skin
Cooked, roasted; meat and skin
Raw; ground
Cooked; ground
Page
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 Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products" (continued)

Product
Moisture
Content
Total Fat
Content
Comment

Dairy
Milk



Cream



Butter
Cheese







Yogurt
Eggs

Whole
Human
Lowfat (1%)
Reduced fat (2%)
Skim or fat free

Half and half
Light (coffee cream or table cream)
Heavy-whipping
Sour
Sour, reduced fat


American
Cheddar
Swiss
Cream
Parmesan
Cottage, lowfat
Colby
Blue
Provolone
Mozzarella


88.32
87.50
89.81
88.86
90.38

80.57
73.75
57.71
70.95
80.14
15.87

39.16
36.75
37.12
53.75
29. 16; 20.84
82.48; 79.31
38.20
42.41
40.95
50.01; 53.78
85.07; 87.90
75.84
" Based on the water and lipid content in 100 grams, edible portion.
For additional information, consult the USDA nutrient database.
Source:
USDA, 2007.


3.25
4.38
0.97
1.92
0.25

11.50
19.31
37.00
20.96
12.00
81.11

31.25
33.14
27.80
34.87
25. 83; 28.61
1.02; 1.93
32.11
28.74
26.62
22.35; 15.92
1.55; 3. 25
9.94

3.25% milkfat
Whole, mature, fluid



Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A
Fluid, with added non-fat milk solids and vitamin A

Fluid
Fluid
Fluid
Cultured
Cultured
Salted

Pasteurized



Hard; grated
l%fat; 2% fat

Whole milk; Skim milk
Plain, lowfat; Plain, with fat
Chicken, whole raw, fresh
Total Fat Content = saturated, monosaturated and
















polyunsaturated.

Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
                               APPENDIX 11A

  CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS MEATS AND
  DAIRY PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
Child-Specific Exposure Factors Handbook                                    Page
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                                            Child-Specific Exposure Factors Handbook

                                  Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 11A-1
Food Category
Total Meats





























Total Dairy





Food Codes and Definitions Used in Analysis of the 1994-96,
1998 USDACSFII Data

EPA Food Commodity Codes
21000440
21000441
21000450
21000460
21000461
21000470
21000471
23001730
24001890
25002900
25002901
25002910
25002920
25002921
25002930
25002931
25002940
25002950
26003390
26003391
26003400
26003410
26003411
26003420
26003430
28002210
29003120
40000930
40000931
40000940
27002220
27002221
27012230
27012231

27022240
Beef, meat
Beef, meat-babyfood
Beef, meat, dried
Beef, meat byproducts
Beef, meat byproducts-babyfood
Beef, fat
Beef, fat-babyfood
Goat, liver
Horse, meat
Pork, meat
Pork, meat-babyfood
Pork, skin
Pork, meat byproducts
Pork, meat byproducts-babyfood
Pork, fat
Pork, fat-babyfood
Pork, kidney
Pork, liver
Sheep, meat
Sheep, meat-babyfood
Sheep, meat byproducts
Sheep, fat
Sheep, fat-babyfood
Sheep, kidney
Sheep, liver
Meat, game
Rabbit, meat
Chicken, meat
Chicken, meat-babyfood
Chicken, liver
Milk, fat
Milk, fat - baby food/infant formula
Milk, non-fat solids
Milk, non-fat solids-baby food/infant
formula
Milk, water
21000480
21000490
21000491
23001690
23001700
23001710
23001720
40000950
40000951
40000960
40000961
40000970
40000971
50003820
50003821
50003830
50003831
50003840
50003841
50003850
50003851
50003860
50003861
60003010
60003020
60003030
60003040
60003050


27022241
27032251




Beef, kidney
Beef, liver
Beef, liver-babyfood
Goat, meat
Goat, meat byproducts
Goat, fat
Goat, kidney
Chicken, meat byproducts








Chicken, meat byproducts-babyfood
Chicken, fat
Chicken, fat-babyfood
Chicken, skin
Chicken, skin-babyfood
Turkey, meat
Turkey, meat-babyfood
Turkey, liver
Turkey, liver-babyfood
Turkey, meat byproducts









Turkey, meat byproducts-babyfood
Turkey, fat
Turkey, fat-babyfood
Turkey, skin
Turkey, skin-babyfood
Poultry, other, meat
Poultry, other, liver
Poultry, other, meat byproducts
Poultry, other, fat
Poultry, other, skin













Milk, water-babyfood/infant formula
Milk, sugar (lactose)-baby food
formula



infant




Page
11A-2
 Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook

Chapter 11 - Intake of Meats, Dairy Products and Fats
Table 1 1A-1 Food Codes and Definitions Used in Analysis of the
Food Category
Beef




Eggs


Pork




Poultry











1994-96, 1998
USDA CSFII Data (continued)
EPA Food Commodity Codes
21000440
21000441
21000450
21000460
21000461
70001450
70001451
70001460
25002900
25002901
25002910
25002920
25002921
40000930
40000931
40000940
40000950
40000951
40000960
40000961
40000970
40000971
50003820
50003821
50003830
Beef, meat
Beef, meat-babyfood
Beef, meat, dried
Beef, meat byproducts
Beef, meat byproducts-babyfood
Egg, whole
Egg, whole-babyfood
Egg, white
Pork, meat
Pork, meat-babyfood
Pork, skin
Pork, meat byproducts
Pork, meat byproducts-babyfood
Chicken, meat
Chicken, meat-babyfood
Chicken, liver
Chicken, meat byproducts
Chicken, meat byproducts-babyfood
Chicken, fat
Chicken, fat-babyfood
Chicken, skin
Chicken, skin-babyfood
Turkey, meat
Turkey, meat-babyfood
Turkey, liver
21000470
21000471
21000480
21000490
21000491
70001461
70001470
70001471
25002930
25002931
25002940
25002950

50003831
50003840
50003841
50003850
50003851
50003860
50003861
60003010
60003020
60003030
60003040
60003050
Beef, fat
Beef, fat-babyfood
Beef, kidney
Beef, liver
Beef, liver-babyfood
Egg, white (solids)-babyfood
Egg, yolk
Egg, yolk-babyfood
Pork, fat
Pork, fat-babyfood
Pork, kidney
Pork, liver

Turkey, liver-babyfood
Turkey, meat byproducts
Turkey, meat byproducts-babyfood
Turkey, fat
Turkey, fat-babyfood
Turkey, skin
Turkey, skin-babyfood
Poultry, other, meat
Poultry, other, liver
Poultry, other, meat byproducts
Poultry, other, fat
Poultry, other, skin
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Chapter 11 - Intake of Meats, Dairy Products and Fats
                                APPENDIX 11B

         SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED
                             ON CDC (1994) DATA
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                                          Chapter 11 - Intake of Meats, Dairy Products and Fats
Sample Calculation of Mean Daily Fat Intake Based on
CDC (1994) Data

         CDC (1994) provided data on the mean daily
total food  energy intake  (TFEI)  and the mean
percentages of TFEI from total dietary fat grouped by
age and gender.  The overall mean daily TFEI was
2,095 kcal for the total population and 34 percent (or 82
g) of their TFEI was from total dietary fat (CDC, 1994).
Based on this information, the amount of fat per kcal
was calculated as shown in the following example.
                                  where 0.34 is the fraction of fat intake, 2,095 is the total
                                  food intake, and X is the conversion  factor from
                                  kcal/day to g-fat/day.

                                           Using the conversion factor shown above
                                  (i.e., 0.12 g-fat/kcal) and the information  on the mean
                                  daily TFEI and percentage of TFEI  for the various
                                  age/gender groups, the daily fat intake was calculated
                                  for these groups. An example of obtaining the grams of
                                  fat from the daily TFEI (1,591 kcal/day) for children
                                  ages 3-5 years and their percent TFEI from total dietary
                                  fat (33 percent) is as follows:
0.34 x 2,095
               day
x X
      day
                               =  82
                                  day
1,591
kcal
day
                                                                    x 0.33 x 0.12
                                                                                  kcal
                                                                    =  63
                                                                           day
             X  =  0.12
   g-fat
    kcal
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Chapter 5 - Ingestion of Soil and Dust	
                               TABLE OF CONTENTS
5 SOIL AND DUST INGESTION 	
5.1
5.2
5.3



































5.4




INTRODUCTION 	
RECOMMENDATIONS 	
KEY AND RELEVANT STUDIES 	
5.3.1 Methodologies Used in Key Studies 	
5.3.1.1 Tracer Element Methodology 	
5.3.1.2 Biokinetic Model Comparison Methodology 	
5.3.1.3 Survey Response Methodology 	
5.3.2 Key Studies of Primary Analysis 	
5.3.2.1 Vermeer and Frate, 1979 	
5.3.2.2 Calabrese et al., 1989/Barnes, 1990/Calabrese et al., 1991 	
5.3.2.3 Van Wijnen et al., 1990 	
5.3.2.4 Davis et al., 1990 	
5.3.2.5 Calabrese et al., 1997a 	
5.3.2.6 Stanek et al. 1998/Calabrese et al., 1997b 	
5.3.2.7 Davis and Mirick, 2006 	
5.3.3 Key Studies of Secondary Analysis 	
5.3.3.1 Wong, 1988/Calabrese and Stanek, 1993 	
5.3.3.2 Hogan et al., 1998 	
5.3.4 Relevant Studies of Primary Analysis 	
5.3.4.1 Dickins and Ford, 1942 	
5.3.4.2 Cooper, 1957 	
5.3.4.3 Barltrop, 1966 	
5.3.4.4 Bruhn and Pangborn, 1971 	
5.3.4.5 Robischon, 1971 	
5.3.4.6 Binder et al., 1986 	
5.3.4.7 Clausing, et al., 1987 	
5.3.4.8 Smulian et al., 1995 	
5.3.5 Relevant Studies of Secondary Analysis 	
5.3.5.1 Stanek et al., 2001a 	
5.3.5.2 Calabrese and Stanek, 1995 	
5.3.5.3 Stanek and Calabrese, 1995a 	
5.3.5.4 Calabrese and Stanek, 1992b 	
5.3.5.5 Calabrese et al., 1996 	
5.3.5.6 Stanek et al., 1999 	
5.3.5.7 Stanek and Calabrese, 1995b 	
5.3.5.8 Stanek and Calabrese, 2000 	
5.3.5.9 Stanek et al., 2001b 	
5.3.5.10 von Lindern et al., 2003 	
LIMITATIONS OF KEY STUDY METHODOLOGIES 	
5.4.1 Tracer Element Methodology 	
5.4.2 Biokinetic Model Comparison Methodology 	
5.4.3 Survey Response Methodology 	
5.4.4 Key Studies: Representativeness of U.S. Population 	
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Chapter 5 - Ingestion of Soil and Dust	
       5.5     SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES	5-25
       5.6     REFERENCES FOR CHAPTER 5	5-26
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Chapter 5 - Ingestion of Soil and Dust	
                                           LIST OF TABLES

Table 5-1.       Recommended Values for Soil, Dust, and Soil + Dust Ingestion	5-5
Table 5-2.       Confidence in Recommendations for Ingestion of Soil and Dust	5-6
Table 5-3.       Soil, Dust and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
                Children	5-31
Table 5-4.       Amherst, Massachusetts Soil-Pica Child's Daily Ingestion Estimates by Tracer and by
                Week (mg/day)	5-32
Table 5-5.       Amherst, Massachusetts Soil-Pica Child's Tracer Ratios	5-33
Table 5-6.       Van W'ijnen et al., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for
                Sample of Dutch Children	5-34
Table 5-7.       Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children
                Attending Daycare Centers According to Age, Weather Category, and Sampling
                Period	5-35
Table 5-8.       Estimated Soil Ingestion for Sample of Washington State Children	5-35
Table 5-9.       Soil Ingestion Estimates for 64 Anaconda Children	5-36
Table 5-10.      Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior
                (mg/day)	5-36
Table 5-11.      Soil Ingestion Estimates for Sample of 12 Washington State Children	5-37
Table 5-12.      Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children	5-38
Table 5-13.      Estimated Daily Soil Ingestion for East Helena, Montana Children	5-39
Table 5-14.      Estimated Soil Ingestion for Sample of Dutch Nursery School Children	5-39
Table 5-15.      Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children	5-40
Table 5-16.      Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
                Study: Effect on Mean Soil Ingestion  Estimate (mg/day)	5-40
 Table 5-17.     Distribution of Average (Mean)  Daily Soil Ingestion Estimates per Child for 64
                Children (mg/day)	5-41
Table 5-18.      Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects
                Projected  over 365 Days	5-41
Table 5- 19.     Summary  of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from
                Key Studies (mg/day)	5-42
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Chapter 5 - Ingestion of Soil and Dust
5       SOIL AND DUST INGESTION
5.1     INTRODUCTION
        The ingestion of soil and dust is a potential
route of  exposure  to environmental chemicals.
Children may ingest significant quantities of soil, due
to their tendency to play on the floor indoors and on the
ground outdoors and their tendency to mouth objects or
their hands.  Children may also ingest soil and dust
through deliberate  hand  to mouth movements,  or
unintentionally by eating food that has dropped on the
floor.  Thus,  understanding soil and  dust ingestion
patterns is  an important part of estimating children's
overall exposures to environmental chemicals.
        At this  point in time, knowledge of soil and
dust ingestion patterns within the United  States is
somewhat  limited.    Only  a few  researchers have
attempted to quantify soil and dust ingestion patterns in
U.S. children. This chapter explains the concepts of
soil ingestion, soil pica, and geophagy, defines these
terms for the purpose of this  handbook's exposure
factors, and presents available data from the literature
on the amount of soil and dust ingested.
        The  Centers  for  Disease  Control  and
Prevention's Agency for Toxic Substances and Disease
Registry (ATSDR)  held a workshop in June 2000 in
which  a  panel  of  soil ingestion  experts developed
definitions  for soil ingestion, soil-pica,  and geophagy,
to distinguish aspects of soil ingestion patterns that are
important from a research perspective (ATSDR, 2001).
This chapter uses the definitions that are based on those
developed by participants in that workshop:
        Soil ingestion is the consumption of soil.
        This  may result  from   various  behaviors
        including,  but  not limited  to,   mouthing,
        contacting  dirty hands, eating dropped food,
        or consuming soil directly.
        Soil-pica  is  the  recurrent  ingestion   of
        unusually high amounts  of soil  (i.e.,  on the
        order of 1,000 - 5,000 mg/day or more).
        Geophagy is  the  intentional ingestion  of
        earths and  is  usually associated with cultural
        practices.
        Some  studies are of a behavior  known  as
"pica,"  and  the  subset  of "pica"  that  consists  of
ingesting soil. A general definition of the concept of
pica is  that  of ingesting non-food substances,  or
ingesting large quantities of certain particular foods.
Definitions of pica often include references to recurring
or repeated ingestion of these substances.  Soil-pica is
pica that is  specific to ingesting materials that are
 defined as soil, such as clays, yard soil, and flower-pot
soil.  Researchers in many different disciplines have
hypothesized  motivations  for human  soil-pica  or
geophagy behavior, including alleviating nutritional
deficiencies, a desire to remove toxins or self-medicate,
and other physiological or  cultural  influences (e.g.,
Danford,  1982).  Bruhn and Pangborn (1971) and
Harris and Harper (1997) suggest a religious context for
certain geophagy or soil ingestion practices.  Some
researchers  have   investigated   subpopulations   of
children who may be more likely than other children to
exhibit soil-pica behavior on a recurring basis.  These
subpopulations might include children  who practice
geophagy (Vermeer and Frate, 1979), institutionalized
children  (Wong,    1988),   and   children   with
developmental delays (Danford, 1983), autism (Kinnell,
1985), or celiac disease (Korman, 1990).  However,
identifying   specific  soil-pica   and  geophagy
subpopulations remains difficult due to limited research
on this topic.
         In this handbook,  soil,  indoor settled and
outdoor settled dust,  and dust ingestion are defined
generally as:
         Soil.   Particles of  unconsolidated mineral
         and/or organic matter from the earth's surface
         that are located outdoors, or are used indoors
         to support plant growth.  It includes particles
         that have  settled onto outdoor objects and
         surfaces (outdoor settled dust).
         Indoor Settled Dust.  Particles in building
         interiors that  have  settled  onto objects,
         surfaces,   floors,  and  carpeting.    These
         particles may include soil particles that have
         been tracked into the indoor environment from
         outdoors as well as organic matter.
         Outdoor Settled Dust.  Particles that have
         settled onto outdoor objects  and surfaces due
         to either wet or dry deposition.  Note that it is
         not possible to distinguish between soil and
         outdoor settled dust, since outdoor settled dust
         generally would be present on the uppermost
         surface layer of soil.
For the  purposes  of this handbook,  soil ingestion
includes  both soil and outdoor settled dust, and  dust
ingestion includes indoor settled dust only.
         There are several methodologies represented
in the literature related to soil and dust ingestion by
children.  Three methodologies combine biomarker
measurements with measurements of the biomarker
substance's presence in environmental media. A fourth
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                                                       	Chapter 5 - Ingestion of Soil and Dust
methodology  offers indirect  evidence of  soil/dust
ingestion behaviors from the responses of caregivers
and/or children to survey questions.
        The first of the biomarker methodologies
measures  quantities  of specific elements present in
children's feces, urine, food and medications, yard soil,
house  dust,  and  sometimes also community soil and
dust,  and combines this  information using certain
assumptions  about the elements'  behavior in  the
gastrointestinal tract to produce estimates of soil and
dust quantities ingested (e.g., Davis et al., 1990).  In
this chapter, this methodology is referred to as  the
"tracer element"  methodology. The second biomarker
methodology compares results from a biokinetic model
of lead exposure and uptake  that predict children's
blood lead levels, with biomarker measurements of lead
in children's blood (e.g., von Lindern et al., 2003). The
model predictions are made  using assumptions  about
ingested soil and dust quantities that are based, in part,
on results from early versions of the first methodology.
Therefore, the comparison with actual measured  blood
lead levels  serves to confirm, to some extent,  the
assumptions  about ingested soil and dust quantities
used in the biokinetic model.  In this chapter, this
methodology is  referred to as the "biokinetic model
comparison" methodology.    The  third  biomarker
methodology, the "lead isotope ratio" methodology,
involves measurements of different lead isotopes in
children's blood and/or  urine,  food, water, and  house
dust and compares the ratio of different lead isotopes to
infer sources of lead exposure that may include dust or
other environmental exposures (e.g.,  Manton et  al.,
2000). In the fourth, "survey response" methodology,
responses to  survey questions regarding soil and dust
ingestion are analyzed.  This methodology includes
questions asked of children directly, or their caregivers,
about soil and dust ingestion behaviors, frequency, and
sometimes quantity (e.g., Barltrop, 1966).
        Although not directly evaluated in this chapter,
a  fifth methodology  uses  assumptions  regarding
ingested quantities of soil and dust that are based on
general  knowledge   of children's   behavior,  and
potentially supplemented or informed by data from
other methodologies (e.g., Hawley, 1985; Kissel  et al.,
1998; Wong et al., 2000).
        The recommendations for soil, dust, and soil
+ dust ingestion rates are provided in the next section,
along with a summary  of the confidence ratings for
these recommendations. The recommended values are
 based on key studies identified by U.S. EPA for this
 factor. Following the recommendations, key studies on
 soil and dust ingestion are summarized. Summaries of
 the relevant  studies,  methodology descriptions and
 methodological  strengths  and limitations  are  also
 provided.

 5.2     RECOMMENDATIONS
         The key studies described in Section 5.3 were
 used to recommend values for soil and dust ingestion
 among children.  The key  studies pre-dated the age
 groups recommended by U.S. EPA (2005) and were
 performed on groups of children of varying ages. As a
 result, central tendency recommendations can be used
 for the life stage categories of 6 to  <12  months, 1 to <2
 years, 2 to <3 years, 3 to <6 years, and part of the 6 to
 <11    years    categories.     Upper  percentile
 recommendations  can be  used  for  the life  stage
 categories of 1 to <2 years, 2 to <3  years, 3 to <6 years,
 6 to <11 years, and part or all of  the 11 to <16  years
 category.  Due to the current  state of research on soil
 and   dust   ingestion,  the  upper  percentile
 recommendations are called "soil-pica" or "geophagy"
 recommendations that are likely to represent high soil
 ingestion episodes or behaviors at an unknown point on
 the high end of the distribution of  soil ingestion.
         The soil ingestion recommendations in Table
 5-1 are intended to represent ingestion of a combination
 of soil and outdoor settled dust, without distinguishing
 between these two sources. The source of the soil in
 these  recommendations could be outdoor soil, indoor
 containerized  soil  used  to support growth of indoor
 plants, or a combination  of both outdoor  soil and
 containerized indoor soil. These recommendations are
 called "soil."  The dust ingestion recommendations in
 Table 5-1  include soil tracked into the indoor setting,
 indoor settled dust and air-suspended particulate matter
 that is inhaled and swallowed.  Central tendency "dust"
 recommendations  are  provided,  in the  event that
 assessors need recommendations for an  indoor or inside
 a transportation vehicle scenario in which dust, but not
 outdoor soil, is the exposure medium of concern. The
 soil + dust recommendations would include soil, either
 from outdoor or containerized indoor sources, dust that
 is a combination of outdoor settled dust, indoor settled
 dust,  and air-suspended particulate  matter that  is
 inhaled, subsequently trapped in mucous and moved
 from the respiratory system to  the gastrointestinal tract,
 and a soil-origin material located on indoor floor
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Chapter 5 - Ingestion of Soil and Dust
surfaces  that  was  tracked  indoors  by  building
occupants.  Soil and dust recommendations exclude the
soil  or dust's  moisture  content.   In other words,
recommended values represent mass of ingested soil or
dust that is  represented on a dry weight basis.
        Table   5-1   shows  the  central  tendency
recommendations for daily ingestion of soil, dust, or
soil + dust, in mg/day. It also shows  the soil-pica or
geophagy recommendations for daily ingestion of soil,
in mg/day.   No data are available on which to base
comparable upper  percentile recommendations  for
"dust" or "soil + dust."  Published estimates from the
key studies have been rounded to one significant figure.
The  recommended  central  tendency  soil +  dust
ingestion estimate for infants from 6 months up to their
first birthday is  60 mg/day. If an estimate is needed for
soil  only, from outdoor  or indoor sources, or both
outdoor and indoor sources, the recommendation is 30
mg/day.  If an estimate for indoor dust only is needed,
that would include a certain quantity of tracked-in soil
from outside, the recommendation  is 30 mg/day.  The
confidence rating for this recommendation is low due to
the small numbers of study subjects in  the study on
which the recommendation is based and the inferences
needed to develop a quantitative estimate. Examples of
these inferences include: an assumption that the relative
proportions of soil and dust ingested by 6 to 12 month
old children is the same  as the central tendency
assumption  for  older children  (45 percent soil, 55
percent dust, based on U.S.  EPA (1994a)), and  the
assumption that pre-natal or non-soil, non-dust sources
of lead exposure do not dominate these children's blood
lead levels.
        When assessing risks for children who are not
expected to exhibit soil-pica or geophagy behavior, the
recommended central tendency soil + dust ingestion
estimate is 100 mg/day for children ages 1 to <6 years.
If an estimate for soil only is needed,  for exposure to
soil such as manufactured topsoil or potted-plant soil
that could occur in either an indoor or  outdoor setting,
or when  the  risk  assessment  is not  considering
children's ingestion of indoor dust (in an indoor setting)
as well,  the recommendation is  50  mg/day.  If an
estimate  for   indoor  dust  only  is  needed,   the
recommendation  is  60  mg/day.   Although these
quantities add up to 110 mg/day, the sum is rounded to
one significant  figure.  Although there were no tracer
element studies  orbiokinetic model comparison studies
performed for children 6 to < 21 years, as  a group, their
mean or central tendency soil ingestion would not be
zero.  In the absence of data that can be used to develop
specific  central tendency  soil  and  dust  ingestion
recommendations for children aged 6 to <11 years, 11
to <16  years  and  16  to  <21  years, U.S.  EPA
recommends using the same central tendency soil and
dust ingestion rates that are recommended for children
in the 1 to < 6 year old age range.
        When assessing risks for children who may
exhibit soil-pica behavior, or a group of children that
includes individual children who may exhibit soil-pica
behavior, the soil-pica ingestion estimate for children
up to age 14 ranges from 400 to 41,000 mg/day. Due to
the definition of soil-pica used in this chapter, that sets
a lower bound on the quantity referred to as "soil-pica"
at 1,000 mg/day, and due to the significant number of
observations in the U.S. tracer element studies that are
at or exceed that quantity, the recommended soil-pica
ingestion rate is 1,000 mg/day. Currently, no data are
available for upper percentile, soil-pica behavior for
children ages 16 to <21 years.  Because pica behavior
may  occur among some children ages ~1 to 21 years
old (Hyman et al.,  1990), it is prudent to assume that,
for some  children, soil-pica behavior may occur at any
age up to <21 years.
        The recommended geophagy soil estimate is
50,000 mg/day (50 grams).  Risk assessors should use
this value for soil ingestion in areas where residents are
known to exhibit geophagy behaviors.
        These recommendations are not robust enough
for use in probabilistic risk assessments.
        Table 5-2 shows the  confidence ratings  for
these recommendations.   Section 5.4 gives a more
detailed explanation of the basis for  the confidence
ratings.
        An important factor to consider when using
these recommendations is  that  they  are limited to
estimates  of soil and dust quantities  ingested.  The
scope of this chapter is limited to quantities of soil and
dust taken into the gastrointestinal tract,  and does not
extend   to   issues   regarding   bioavailability  of
environmental contaminants present  in  that soil and
dust.   Information from other sources  is needed to
address  bioavailability.    In  addition,  as  more
information   becomes   available   regarding
gastrointestinal   absorption   of  environmental
contaminants, adjustments to the soil and dust ingestion
exposure equations may need to be made, to better
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                                                     	Chapter 5 - Ingestion of Soil and Dust
represent  the  direction  of  movement  of  those
contaminants within the gastrointestinal tract.
        To place these recommendations into context,
it is useful to compare these  soil ingestion rates to
common measurements. The bulk densities of surface
soils are often in the range of  1.3 to 1.7 g/cm3.  U.S.
EPA (1996) recommends using 1.5 g/cm3 as a default
value for dry soil bulk density. The central tendency
recommendation of 50  mg/day, or 0.050 g/day, dry
weight basis, with a 1.5 g/cm3 bulk density would be
equivalent to approximately 0.03 cm3.  A teaspoon is
approximately 5 cm3 in volume, so the 50 mg/day
quantity  would  be  roughly   equivalent  to  seven
thousandths  of a teaspoon per day.  The  50  g/day
ingestion rate  recommended to represent geophagy
behavior would  be roughly  equivalent to  5   to 7
teaspoons per day in volume.
        Indoor settled dust could be expected to have
a lower dry bulk density than the surface  soil bulk
density cited above  (for example, bulk densities of five
grain dusts are reported by Parnell et al. (1986) to be
0.15-0.31 g/cm3, "specific density" of Danish  office
building dust is reported by M01have et al. (2000) to be
1.0  gm/cm3).  Thus, volumes  of indoor settled dust
could be expected to weigh  less than comparable
volumes of surface  soil.  The central tendency "dust"
recommendation for children of 60 mg/day, or  0.060
g/day, dry weight basis, with a 1.0 g/cm3 bulk density
would be equivalent  to approximately 0.06 cm3, or
roughly equivalent to twelve thousandths of a teaspoon
per day.
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Chapter 5 - Ingestion of Soil and Dust
Table 5-1 . Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion




6 to
1 to
6 to

Age Group


<12 months
< 6 years
<21 years
Soil" Dust"
Upper Percentile
(mg/day) Soil-Pica Geophagy (mg/day)
(mg/day) (mg/day)
30 - - 30
50 1,000 50,000 60
50 1,000 50,000 60
Soil + Dust

(mg/day)

60
100°
100°
No recommendation.
a Includes soil and outdoor settled dust.
b Includes indoor settled dust only.
c
Total
soil and dust ingestion rate is 1 10 mg/day; rounded to one significant figure it is 100 mg/day.

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                                                                   	Chapter 5 - Ingestion of Soil and Dust
                                Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust
  General Assessment Factors                                        Rationale                                           Rating
  Soundness                                                                                                           Low
   Adequacy of Approach         The methodologies have significant limitations. The studies did not capture all of the
                                information needed (quantities ingested, frequency of high soil ingestion episodes,
                                prevalence of high soil ingestion). Four of the 9 studies were of census or randomized
                                design. Sample selection may have introduced some bias in the results (i.e., children near
                                smelter or Superfund sites, volunteers in nursery schools). The total number of children
                                in key studies was 1,203 (859 U.S. children, 292 Dutch, and 52 Jamaican children), while
                                the target population currently numbers more than 74 million (U.S. DOC, 2008). The
                                response rates for in-person interviews and telephone surveys were often not stated in
                                published articles. Primary data were collected for 381 U.S. children and 292 Dutch
                                children; secondary data for 478 U.S. children and 52 Jamaican children.

                                Numerous sources of measurement error exist in the tracer element studies. Biokinetic
   Minimal (or defined) Bias      model comparison study may contain less measurement error than tracer element studies.
                                Survey response study may contain measurement error.
  Applicability and Utility                                                                                              Low
   Exposure Factor of Interest    8 of the 9 key studies focused on the soil exposure factor, with no or less focus on the
                                dust exposure factor. Biokinetic model comparison study did not focus exclusively on
                                soil and dust exposure factors.

   Representativeness            The study samples may not be representative of the U.S. in terms of race, ethnicity,
                                socio-economics, and geographical location; studies focused on specific areas.

   Currency                    Studies results are likely to represent current conditions.

   Data Collection Period        Tracer element studies' data collection periods may not represent long-term behaviors.
                                Biokinetic model comparison and survey response studies do represent longer term
                                behaviors.
  Clarity and Completeness                                                                                             Low
   Accessibility                  Observations for individual children are available for only 3 of the 9 key studies.

   Reproducibility               For the methodologies used by more than one research group, reproducible results were
                                obtained in some instances. Some methodologies have been used by only one research
                                group and have not been reproduced by others.

   Quality Assurance            For some studies, information on quality assurance/quality control was limited or absent.
  Variability and Uncertainty                                                                                           Low
    Variability in Population       Tracer element studies characterized variability among study sample members; biokinetic
                                model comparison and survey response studies did not. Day-to-day and seasonal
                                variability was not very well characterized. Numerous factors that may influence
                                variability have not been explored in detail.

    Minimal Uncertainty          Estimates are highly uncertain. Tracer element studies' design appears to introduces
                                biases in the results.
  Evaluation and Review                                                                                             Medium
   Peer Review                  All key studies appeared in peer review journals.

    Number and Agreement of    9 key studies. Researchers using similar methodologies obtained generally similar
    Studies                      results; somewhat general agreement between researchers using different
                                methodologies.
  Overall Rating                                                                                                     Low
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Chapter 5 - Ingestion of Soil and Dust
5.3     KEY AND RELEVANT STUDIES
        The key  tracer  element,  biokinetic  model
comparison,   and  survey   response  studies   are
summarized in the following sections. Certain studies
were considered "key" and were used as a basis for
developing the recommendations, using judgment about
the study's design features, applicability, and utility of
the data to U.S. children's soil and dust ingestion rates,
clarity  and  completeness,  and  characterization  of
uncertainty  and variability  in  ingestion  estimates.
Because the studies often were performed for reasons
unrelated  to  developing  soil  and  dust ingestion
recommendations,  their  attributes   that   were
characterized as "limitations" in this chapter might not
be limitations when viewed in the context of the study's
original purpose.  However, when studies are used for
developing a soil or dust  ingestion recommendation,
U.S. EPA has categorized  some  studies' design or
implementation as preferable to other studies' design or
implementation. In general, U.S. EPA chose studies
designed either with a census, or randomized sample,
approach, over studies that used a convenience sample
or other, non-randomized,  approach, as well as studies
that  more clearly explained various factors  in the
study's implementation that affect interpretation of the
results. However, in some cases, studies that used a
non-randomized design contain  information that is
useful for developing expo sure factor recommendations
(for example, if they are the only studies of children in
a particular  age category), and  thus may have  been
designated as "key"  studies.   Other  studies   were
considered "relevant"  but not  "key" because  they
provide  useful  information  for  evaluating   the
reasonableness of the data in the key studies, but in
U.S. EPA's judgment they did not meet the same level
of soundness, applicability and utility,  clarity and
completeness, and characterization of uncertainty and
variability that the key studies did. In addition, studies
that did not contain information that can be used to
develop a specific recommendation formg/day soil and
dust ingestion were classified as relevant rather than
key.
        Some   studies   are  re-analyses  of  data
previously published. For this reason, the sections that
follow are organized into  key and relevant studies of
primary analysis (that is, studies in which researchers
have developed primary data pertaining to soil and dust
ingestion) and key and relevant studies of secondary
analysis (that is, studies  in which researchers  have
interpreted previously published results, or data that
were originally collected for a different purpose).
5.3.1    Methodologies Used in Key Studies
5.3.1.1  Tracer Element Methodology
        The tracer element methodology attempts to
quantify the amounts of soil ingested by analyzing
samples of  soil and dust from children's residences
and/or play areas,  and the  children's  feces, and
sometimes also urine. The soil, dust, fecal, and urine
samples are  analyzed for the presence and quantity of
tracer elements - typically, aluminum, silicon, titanium,
and other  elements.  A key underlying assumption is
that these elements are  not metabolized into other
substances  in the  body   or absorbed  from  the
gastrointestinal tract in significant quantities, and thus
their presence in feces and urine can be used to estimate
the quantity  of soil ingested by mouth. Although they
are sometimes called mass balance studies, none of the
studies  attempt to  quantify amounts   excreted  in
perspiration, tears, glandular secretions,  or shed skin,
hair or finger- and toe-nails,  nor do they account for
tracer element exposure via the dermal  or inhalation
into the lung routes, and thus they are not a complete
"mass balance" methodology.  Early studies using this
methodology  did   not  always   account  for  the
contribution   of   tracer  elements   from  non-soil
substances (food, medications, and non-food sources
such as toothpaste) that children might swallow.  U.S.
studies using this methodology in  or after the mid to
late 1980s account for, or attempt to account for, tracer
element contributions from these  non-soil sources.
Some study  authors adjust their soil ingestion estimate
results to account for the potential contribution of tracer
elements found in household dust as well as soil.
        The general algorithm that is used to calculate
the quantity of soil or dust  estimated to have been
ingested by  each child is as follows: the quantity of a
given tracer element, in milligrams, present in the
child's feces and urine, minus the quantity of that tracer
element, in milligrams, present in the child's food and
medicine,  the result of which is divided by the tracer
element's  soil concentration, in milligrams oftracerper
gram of soil, to yield an estimate of ingested  soil, in
grams.
        The U.S. tracer element researchers have all
assumed a certain offset, or lag time between ingestion
of food, medication and soil, and the resulting fecal and
urinary output. The lag times used are typically 24 or
28 hours; thus, these researchers subtract the previous
day's food  and medication  tracer element quantity
ingested from the current day's fecal and urinary tracer
element quantity that was excreted. When compositing
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                                                       	Chapter 5 - Ingestion of Soil and Dust
food, medication, fecal and urine samples across the
entire study period, daily estimates can be obtained by
dividing  the total estimated  soil ingestion  by  the
number of days in which  fecal and/or urine samples
were collected.  A  variation of the algorithm that
provides slightly higher estimates of soil ingestion is to
divide the total  estimated soil ingestion by the number
of days on which feces  were produced, which by
definition would be  equal to or less than the total
number of days of the study period's fecal  sample
collection.
        Substituting tracer element dust concentrations
for tracer element soil concentrations yields a  dust
ingestion estimate. Because the actual non-food, non-
medication quantity ingested is a combination of soil
and dust, the unknown true soil and dust ingestion is
likely to be somewhere between the estimates that are
based on  soil concentrations and estimates that  are
based  on  dust  concentrations.   Tracer  element
researchers have described ingestion estimates for soil
that actually represent a combination of soil and dust,
but  were  calculated  based   on  tracer  element
concentrations in soil.  Similarly, they have described
ingestion  estimates for dust  that are actually  for a
combination of soil and dust but were calculated based
on  tracer element  concentrations  in  dust.   Other
variations on these  general soil and dust ingestion
algorithms have been published, in attempts to account
for time spent indoors, time spent away from the house,
etc. that could  be  expected to influence the relative
proportion of soil vs. dust.
        Each child's soil and dust ingestion can be
represented  as  an  unknown  constant  in  a set  of
simultaneous  equations  of soil or  dust  ingestion
represented by different tracer elements. To date, only
one of the U.S. research teams (Lasztity et al., 1989)
has published estimates calculated for pairs of tracer
elements using  simultaneous equations.
        The U.S. tracer element studies  have been
performed for only short-duration study periods, and
only for 241 children (101 in Davis et al., 1990,  12 of
whom were studied again  in Davis and Mirick, 2006;
64  in  Calabrese et  al.,   1989/Barnes 1990;  64  in
Calabrese et al., 1997a; and  12 in Calabrese et al.,
1997b). They provide information on quantities of soil
and dust ingested for the studied groups of children for
short time periods, but provide limited information on
overall prevalence of soil  ingestion by U.S. children,
and limited information on the frequency of higher soil
ingestion episodes.
         The tracer element studies appear to contain
 numerous sources of error that influence the estimates
 upward and downward.  Sometimes the error sources
 cause  individual children's  soil or  dust  ingestion
 estimates  to be negative,  which  is  not  physically
 possible.  In some  studies, for some of the tracers, so
 many  individual  children's "mass  balance"  soil
 ingestion estimates were negative that median or mean
 estimates based on that tracer were negative. For soil
 and dust ingestion  estimates based on each particular
 tracer, or averaged across tracers, the net impact of
 these competing upward and downward sources of error
 is unclear.

 5.3.1.2  Siokinetic Model Comparison Methodology
         The   Biokinetic   Model   Comparison
 methodology compares  direct  measurements of a
 biomarker, such  as blood or urine levels of a toxicant,
 with predictions from a biokinetic model of oral, dermal
 and inhalation exposure routes  with air, food, water,
 soil, and  dust toxicant  sources.  An example is to
 compare children's measured blood lead levels with
 predictions from the Integrated  Exposure and Uptake
 Biokinetic (IEUBK) model.  Where environmental
 contamination of lead in soil, dust, and drinking water
 has been measured and those measurements can be used
 as   model  inputs  for  the  children  in a specific
 community, the  model's  assumed  soil   and dust
 ingestion  values can be confirmed  or refuted  by
 comparing the model's predictions of blood lead levels
 with those children's measured  blood lead  levels.  It
 should be noted, however, that such confirmation of the
 predicted blood lead levels would be confirmation of
 the net impact of all model inputs, and not just soil and
 dust ingestions.  Under the assumption that  the actual
 measured blood lead  levels of  various  groups of
 children  studied  have   minimal error,  and those
 measured  blood  lead  levels  roughly  match  the
 biokinetic  model  predictions  for those  groups of
 children, then the model's default assumptions may be
 roughly accurate for the central tendency,  or typical,
 children in an assessed group of children. The model's
 default assumptions  likely are  not  as useful  for
 predicting outcomes for highly exposed children.

 5.3.1.3  Survey Response Methodology
         The survey response methodology includes
 studies that survey children's caretakers, or children
 themselves, via in-person or mailed surveys that ask
 about mouthing behavior and ingestion of various non-
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Chapter 5 - Ingestion of Soil and Dust
food items.  Sometimes, questions  about amounts
ingested are included in the survey instrument. There
could  be  either  false  positive  or  false  negative
responses to these questions, for various reasons.

5.3.2    Key Studies of Primary Analysis
5.3.2.1  Vermeer and  Frate, 1979 - Geophagia in
        rural  Mississippi:   environmental  and
        cultural con texts andnu trition al implications
        Vermeer and Frate (1979) performed a survey
response study in Holmes County,  Mississippi in the
1970s (date unspecified). Questions about geophagy
(defined as regular consumption of clay over a period
of weeks) were asked of household members (N=229 in
50 households; 140 were children or adolescents) of a
subset  of  a random  sample  of nutrition  survey
respondents.  Caregiver responses to  questions about
115 children under 13 indicate that geophagy was likely
to be practiced by a minimum of 18  (16 percent) of
these children; however, 16 of these 18 children were
1 to 4 years old, and only 2 of the 18 were older than 4
years.  There was no reported  geophagy among 25
adolescent  study subjects questioned.  The average
daily amount of clay consumed was reported to be
about 50 grams, for the 32 adult and 18 under-age-13
years child respondents  who acknowledged practicing
geophagy.  Quantities were usually described as either
portions or multiples of the amount that could be held
in a single, cupped hand. Clays for consumption were
generally obtained from  the B soil horizon, or subsoil
rather than an uppermost layer, at a depth of 50 to  130
centimeters.

5.3.2.2  Calabrese et al., 1989 - How Much Soil Do
        Young Children Ingest: An  Epidemiologic
        Study/Barnes,   1990  -  Childhood  Soil
        Ingestion:   How  Much Dirt   Do  Kids
        Eat?/Calabrese et al.,  1991 - Evidence of
        Soil-Pica Behaviour and Quantification of
        Soil Ingested
        Calabrese et al. (1989) and Barnes  (1990)
studied soil ingestion among children using eight tracer
elements—aluminum, barium,  manganese, silicon,
titanium, vanadium, yttrium, and zirconium. A non-
random sample of 30 male and  34  female 1, 2 and 3
year-olds from the greater Amherst, Massachusetts area
were studied, presumably in 1987.  The children were
predominantly from two-parent households where the
parents were highly educated.   The  study  was
conducted over a period of eight days spread over two
weeks. During each week, duplicate samples of food,
beverages, medicines, and vitamins were collected on
Monday  through Wednesday,  while excreta were
collected  for  four  24-hour cycles   running from
Monday/Tuesday through Thursday/Friday.  Soil and
dust samples were also collected from the child's home
and play  area.  Study participants were supplied with
toothpaste, baby cornstarch, diaper rash cream, and
soap with low  levels of most of the tracer elements.
Fecal and urine  samples, excluding wipes and toilet
paper,  were also collected and analyzed  for tracer
elements.
        Table 5-3  shows  the published mean soil
ingestion estimates ranging from -294 mg/day based on
manganese to 459 mg/day based on vanadium, median
soil ingestion  estimates ranging from -261  mg/day
based on  manganese to 96 mg/day based on vanadium,
and 95th percentile estimates ranged from 106 mg/day
based on  yttrium  to 1,903 mg/day based on vanadium.
Maximum daily  soil ingestion estimates ranged from
1,391 mg/day  based on zirconium to 7,281  mg/day
based on  manganese. Dust ingestions calculated using
tracer concentrations in dust were often, but not always,
higher than soil ingestions calculated using tracer
concentrations in soil.
        Data for the uppermost 23 subject-weeks (the
highest soil ingestion estimates, averaged over the four
days of  excreta  collection during each of the two
weeks) were published in Calabrese et al. (1991).  One
child's soil-pica  behavior  was  estimated in  Barnes
(1990) using both the subtraction/division algorithm
and the  simultaneous equations  method.   On two
particular days during the  second week of the study
period, the  child's aluminum-based  soil ingestion
estimates were 19 g/day (18,700 mg/day) and 36 g/day
(35,600 mg/day), silicon-based soil ingestion estimates
were 20 g/day (20,000 mg/day) and 24 g/day (24,000),
and  simultaneous-equation soil ingestion estimates
were 20 g/day  (20,100 mg/day) and 23 g/day (23,100
mg/day) (Barnes  1990).  By tracer, averaged across the
entire  week,  this  child's  estimates ranged from
approximately  10 to 14 g/day during the second week
of observation  (Calabrese et al., 1991, shown in Table
5-4), and averaged 6 g/day across the  entire study
period.   Additional  information  about  this  child's
apparent  ingestion of soil  vs. dust during the study
period, shown in Table 5-5,  was published in Calabrese
and Stanek(1992a).
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                                                       	Chapter 5 - Ingestion of Soil and Dust
5.3.2.3   Van  W'ijnen et al.,  1990 - Estimated Soil
        Ingestion by Children
        In a tracer element study by Van W'ijnen et al.
(1990), soil ingestion among Dutch children ranging in
age from  1  to 5 years was evaluated using a tracer
element  methodology.   Van W'ijnen  et  al. (1990)
measured three tracers (titanium, aluminum,  and acid
insoluble residue (AIR)) in soil and feces. The authors
estimated soil ingestion based on an assumption called
the Limiting Tracer Method (LTM),  which  assumed
that soil ingestion could not be higher than the lowest
value of the three tracers. LTM values represented soil
ingestion estimates that were not corrected for dietary
intake.
        An average daily feces dry weight of 15 g was
assumed.  A total  of 292 children attending daycare
centers were studied during the first of two sampling
periods and 187  children were  studied in the second
sampling period; 162 of these children were studied
during both periods (i.e., at the beginning and near the
end of the summer of 1986). A total of 78  children
were studied at campgrounds.  The authors  reported
geometric mean  LTM values because  soil ingestion
rates were found to be skewed and the log transformed
data  were  approximately  normally  distributed.
Geometric mean LTM values were estimated to be 111
mg/day for children in daycare centers and 174 mg/day
for children vacationing at campgrounds (Table 5-6).
For the 162 daycare center children studied during both
sampling periods the arithmetic mean LTM  was 162
mg/day, and the median  was 114 mg/day.
        Fifteen hospitalized children were studied and
used as a control group. These children's LTM soil
ingestion  estimates were 74 (geometric mean),  93
(mean),  and  110  (median) mg/day.   The authors
assumed the  hospitalized  children's soil  ingestion
estimates represented dietary intake of tracer elements,
and used rounded 95 percent confidence limits on the
arithmetic mean, 70 to 120 mg/day, to correct the day-
care and campground children's LTM estimates for
dietary intake of tracers.  Corrected soil ingestion rates
were 69 mg/day (162 mg/day minus 93 mg/day) for
daycare children and 120 mg/day (213 mg/day minus
93 mg/day)  for campers.  Corrected geometric mean
soil ingestion  was estimated to range  from  0 to  90
mg/day, with  a 90th percentile value  of  up to  190
mg/day for the  various age  categories within the
daycare group and 30  to 200  mg/day, with a 90th
percentile value of up to 300 mg/day for the various age
categories within the camping group.
         AIR was the limiting tracer in about 80 percent
 of the  samples.  Among children attending daycare
 centers, soil ingestion was also found to be higher when
 the weather was good (i.e., <2 days/week precipitation)
 than when the weather was bad (i.e., >4 days/week
 precipitation (Table 5-7).

 5.3.2.4  Davis et al., 1990 - Quantitative Estimates of
         Soil Ingestion in Normal Children between
         the Ages of 2 and 7 Years: Population-based
         Estimates  Using Aluminum, Silicon,  and
         Titanium  as Soil Tracer Elements
         Davis  et  al.  (1990) used a tracer element
 technique to estimate soil ingestion among children. In
 this study,  104 children between the ages of 2 and 7
 years were randomly selected from a three-city area in
 southeastern Washington State. Soil and dust ingestion
 was evaluated by analyzing  soil and house dust, feces,
 urine,  and duplicate  food,  dietary  supplement,
 medication and  mouthwash samples for aluminum,
 silicon, and titanium.  Data were collected for 101 of
 the 104 children during July,  August or September,
 1987. In each family, data were collected over a seven
 day period, with four days of excreta sample collection.
 Participants were supplied with toothpaste with known
 tracer element content.  In addition, information on
 dietary habits and  demographics was collected in an
 attempt to identify  behavioral  and  demographic
 characteristics that influence soil ingestion rates among
 children. The amount of soil ingested on a daily basis
 was estimated using equation 5-1:

 Sl=(((DWf+ DWP) x Ef) + 2EJ - (DWax EJ  (Eq. 5-1)
                       E.M
 where:
 S:,
 DWf
 DW,
 DWfd
 Efd
  "soil
soil ingested for child  i based  on
tracer e (g);
feces dry weight (g);
feces dry weight on toilet paper (g);
tracer concentration in feces (ug/g);
tracer amount in urine (ug);
food dry weight (g);
tracer concentration in food (ug/g);
and
tracer concentration in soil (ug/g).
 The soil ingestion rates were corrected by adding the
 amount of tracer in vitamins  and medications to the
 amount of tracer in food, and adjusting the food, fecal
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Chapter 5 - Ingestion of Soil and Dust
and  urine  sample weights  to  account for missing
samples.   Food,  fecal and urine  samples  were
composited over a 4-day period, and estimates for daily
soil  ingestion were obtained by dividing the 4 day
composited tracer quantities by 4.
        Soil ingestion rates were highly variable,
especially those based on titanium. Mean daily soil
ingestion estimates were 38.9 mg/day for aluminum,
82.4 mg/day for silicon and 245.5 mg/day for titanium
(Table 5-8).   Median  values were 25  mg/day  for
aluminum,  59 mg/day for silicon, and 81 mg/day for
titanium. The investigators also evaluated the extent to
which differences in tracer concentrations in house dust
and yard soil impacted estimated soil ingestion rates.
The value used in the denominator of the soil ingestion
estimate   equation  was recalculated  to  represent a
weighted average of the tracer concentration in yard
soil and house dust based on the proportion of time the
child spent indoors and outdoors, using an assumption
that the likelihood of ingesting soil outdoors was  the
same as that  of ingesting dust indoors. The adjusted
mean soil/dust  ingestion rates were 64.5 mg/day  for
aluminum,  160.0 mg/day for silicon, and 268.4 mg/day
for titanium.  Adjusted median soil/dust ingestion rates
were:  51.8 mg/day for aluminum, 112.4 mg/day  for
silicon, and 116.6 mg/day for titanium.  The authors
investigated whether nine behavioral and demographic
factors could be used  to predict  soil ingestion, and
found  family income  less  than  $15,000/year  and
swallowing toothpaste to be significant predictors with
silicon-based estimates; residing in one of the three
cities to be a significant predictor with aluminum-based
estimates,  and  washing the  face  before  eating
significant  for titanium-based estimates.

5.3.2.5  Calabrese  et  al.  1997a  - Soil  Ingestion
        Estimates  for  Children  Residing  on  a
        Super fund Site
        Calabrese  et  al.   (1997a) estimated  soil
ingestion rates for children residing on a Superfund site
using a methodology in which  eight tracer elements
were analyzed.  The methodology used in this study is
similar to that employed in  Calabrese et  al.  (1989),
except that rather than  using barium, manganese, and
vanadium as three of the eight tracers,  the researchers
replaced them with cerium, lanthanum and neodymium.
A total of  64 children  ages  1-3 years (36 male, 28
female) were selected for this study of the Anaconda,
Montana area.  The study was conducted for seven
consecutive days during September or September and
October, apparently  in  1992,  shortly after soil  was
removed and replaced in some residential yards in the
area.   Duplicate  samples of meals, beverages,  and
over-the-counter medicines and vitamins were collected
over the seven day period, along with fecal samples. In
addition, soil and dust samples were collected from the
children's home and play areas. Toothpaste containing
nondetectable levels  of  the tracer elements, with the
exception of silica, was provided to all of the children.
Infants were provided with baby cornstarch, diaper rash
cream, and soap which were found to contain low levels
of tracer elements.
        Calabrese  et  al.  (1997a)  estimated  soil
ingestion by each tracer  element,  as shown in Table 5-
9.

5.3.2.6  Stanek  et al.  1998  -  Prevalence of  Soil
        Mouthing/Ingestion   among  Healthy
        Children Aged  1 to 6/Calabrese et al. 1997b -
        Soil Ingestion Rates in Children Identified by
        Parental Observation as Likely High  Soil
        Ingesters
        Stanek  et al.  (1998)  conducted  a  survey
response study using in-person interviews of parents of
children  attending  well visits  at  three  western
Massachusetts medical clinics in August, September
and October of 1992. Of 528 children ages 1 to 7 with
completed interviews, parents reported daily mouthing
or ingestion of sand and stones  in  6 percent, daily
mouthing or ingestion of soil and dirt  in 4 percent, and
daily mouthing or ingestion of dust, lint and dustballs in
1 percent. Parents reported more than weekly mouthing
or ingestion of sand and stones in 16 percent, more than
weekly mouthing or ingestion of soil and dirt in 10
percent, and more than weekly mouthing or ingestion of
dust, lint and dustballs in 3 percent.  Parents reported
more than monthly mouthing or ingestion of sand and
stones  in 27 percent, more than monthly mouthing or
ingestion of soil and  dirt in 18 percent, and more than
monthly mouthing or  ingestion of dust, lint  and
dustballs in 6 percent.
        Calabrese and colleagues performed a follow-
up tracer element study  (Calabrese et al. 1997b) for a
subset (n= 12) of the Stanek et al. (1998) children whose
caregivers  had  reported  daily  sand/soil  ingestion
(n=17).  The time frame of the follow-up tracer study
relative to the original survey response study was not
stated;  the  study duration was  7 days.   Of the 12
children  in  Calabrese  et al.  1997b, one  exhibited
behavior that the authors  believed was clearly soil pica;
Table 5-10 shows estimated soil ingestion rates for this
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                                                       	Chapter 5 - Ingestion of Soil and Dust
child during the study period.  Estimated average daily
soil ingestion estimates (calculated based on soil tracer
element concentrations  only) ranged from -0.015  to
+ 1.783 g/day based on aluminum,  -0.046 to +0.931
g/day based on  silicon, and  -0.047 to +3.581 g/day
based on titanium.   Estimated average  daily  dust
ingestion estimates (calculated based on  dust tracer
element concentrations  only) ranged from -0.039  to
+2.652 g/day based on aluminum,  -0.028 to +3.145
g/day based on  silicon, and  -0.098 to +3.632 g/day
based on titanium.  Calabrese et al. (1997b) question
the validity  of retrospective caregiver reports of soil
pica on the basis of the tracer  element results.

5.3.2.7  Davis and Mirick, 2006 - Soil ingestion  in
        children and adults in the same family
        Davis  and Mirick  (2006) calculated  soil
ingestion for children and  adults in the same family
using a tracer element approach. Data were collected
in 1988, one year after the Davis etal. (1990) study was
conducted.  Samples were collected and prepared for
laboratory analysis and then stored for a 12 year period
prior to tracer element quantification with laboratory
analysis.   The  20  families  in this  study were a
nonrandom subset of the 104 families who participated
in the soil ingestion study by Davis et al. (1990), and
were chosen based on high  compliance with the
previous study protocol and expressed willingness  to
participate in a future  study.  Data collection issues
resulted in sufficiently complete data for only 19 of the
20 families consisting of a  child participant from the
Davis et al.  (1990) study ages 3 to  7, inclusive, and a
female and male parent or guardian living in the same
house. Duplicate samples of all food and medication
items consumed, and all feces excreted, were collected
for 11 consecutive days. Urine samples were collected
twice daily for 9 of the 11  days; for the remaining 2
days, attempts were made to collect full 24-hour urine
specimens.  Soil and house  dust samples were  also
collected. Only  12 children had sufficiently complete
data for use in the soil and dust  ingestion estimates.
        Tracer  elements  for  this  study  included
aluminum,  silicon  and  titanium.   Toothpaste  was
supplied for use by study  participants.  In  addition,
parents  completed  a  daily  diary  of activities for
themselves and the participant child for 4 consecutive
days during the study period.
        Children's estimated soil ingestion rates are
shown in Table 5-11. The mean and median estimates
for children  for all three tracers  ranged from 36.7  to
 206.9 mg/day and 26.4 to 46.7 mg/day, respectively,
 calculated by setting negative estimates to zero. These
 estimates fall within the range of those reported by
 Davis et al., 1990. Similar to the previous Davis et al.
 study, the soil ingestion estimates were the highest for
 titanium.
         Only two of a number of children's behaviors
 examined for their relationship to soil ingestion were
 found to be associated with increased soil ingestion in
 this study:
 •       reported eating of dirt; and
 •       hand washing before meals (based on 2 of 12
         children who were reported not to wash hands
         before eating).
 Several  typical   childhood  behaviors,   however,
 including   thumb-sucking,  furniture  licking,  and
 carrying around a blanket or toy were not associated
 with increased  soil  ingestion for the  participating
 children. When investigating  correlations within the
 same family, a child's soil ingestion rate was not found
 to be associated with either parent's soil ingestion rate.

 5.3.3   Key Studies of Secondary Analysis
 5.3.3.1  Wong, 1988 - The Role  of Environmental
         and   Host   Behavioural   Factors  in
         Determining Exposure to Infection with
         Ascaris  lumbricoides   and  Trichuris
         Trichiura/Calabrese andStanek, 1993 -Soil
         Pica: Not a Rare Event
         Calabrese and Stanek (1993) reviewed a tracer
 element study that was  conducted by Wong (1988) to
 estimate the amount of soil ingested by two groups of
 children. Wong (1988) studied a total of 52 children in
 two  government institutions in Jamaica. The younger
 group included 24 children with an average age of 3.1
 years (range of 0.3 to  7.5  years).  The older group
 included 28 children  with an average age of 7.2 years
 (range  of 1.8 to  14  years).  One fecal sample was
 collected each month from each subject over  the four-
 month study period. The amount of silicon in dry feces
 was  measured to estimate soil ingestion.
         An unspecified number of daily fecal samples
 were collected  from a hospital  control group of 30
 children with an average age of 4.8 years (range of 0.3
 to 12 years).  Dry feces were observed to contain 1.45
 percent silicon, or 14.5 mg Si  per gram of dry  feces.
 This quantity was used to correct measured fecal silicon
 from dietary sources.  Fecal silicon quantities greater
 than 1.45 percent in the 52  studied children were
 interpreted as originating  from soil ingestion.
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        For the 28 children in the older group, soil
ingestion was estimated to be 58 mg/day, based on the
mean minus one outlier, and 1,520 mg/day, based on
the mean of all the children. The outlier was a child
with an estimated average soil ingestion rate of 41
g/day over the 4 months.
        Estimates of soil ingestion were higher in the
younger group of 24 children.  The mean soil ingestion
of all the children was 470 ± 370 mg/day. Due to some
sample losses, of the 24 children studied, only 15 had
samples for each of the 4 months of the study.  Over the
entire 4-month study period, 9 of 84 samples (or 10.5
percent) yielded soil ingestion estimates in excess of 1
g/day.
        Of the  52 children studied, 6 had one-day
estimates of more than 1,000 mg/day.  The  estimated
soil ingestion for these six children is shown in Table 5-
12.  The article describes 5 of 24 (or 20.8 percent)  in
the younger group of children as having  a >1,000
mg/day estimate on at least one of the four study days;
in the older group one child is described in this manner.
A high degree of daily variability in soil ingestion was
observed among these six children; three showed soil-
pica behavior on 2, 3, and 4 days, respectively, with the
most consistent (4 out of 4 days) soil-pica child having
the highest estimated soil ingestion, 3.8  to 60.7 g/day.

5.3.3.2  Hogan  et al., 1998  - Integrated Exposure
        Uptake  Siokinetic   Model for  Lead  in
        Children:  Empirical  Comparisons  with
        Epidemiologic Data
        Hogan et al. (1998) used the biokinetic model
comparison methodology to review the measured blood
lead levels of 478 children.  These  children were a
subset of the  entire population of children living  in
three historic  lead  smelting  communities,  whose
environmental lead exposures (soil and dust lead levels)
had been collected as part of public health evaluations
in these communities.
        The  Integrated   Exposure  and   Uptake
Biokinetic (IEUBK) model is  a biokinetic model for
predicting  children's  blood   lead levels  that uses
measurements of  lead content in house dust,  soil,
drinking  water,  food and  air,  and  child-specific
estimates of intake for each exposure medium (dust,
soil, drinking water, food  and  air).  Model  users can
also  use default assumptions for the lead contents and
intake rates for each exposure  medium  when they do
not have specific information for each child.
        Hogan  et  al. (1998)  compared children's
measured  blood lead levels with biokinetic  model
predictions (IEUBK version 0.9 9d) of blood lead levels,
using the children's measured drinking water, soil, and
dust lead  contamination levels  together with default
IEUBK model inputs for soil  and  dust ingestion,
relative proportions of soil  and dust ingestion, lead
bioavailability from soil  and dust,  and other  model
parameters. Thus, the default soil and dust ingestion
rates in the model, and other default assumptions in the
model, were tested by  comparing measured blood lead
levels with the model's predictions for those children's
blood lead levels.
        For  Palmerton,   Pennsylvania (n=34), the
community-wide geometric mean measured blood lead
levels (6.8 ug/dl) were slightly over-predicted  by the
model   (7.5   ug/dl);   for   southeastern
Kansas/southwestern Missouri (n=l 11), the blood lead
levels  (5.2 ug/dl) were slightly under-predicted (4.6
ug/dl), and for Madison County, Illinois (n=333), the
geometric mean measured blood lead levels  matched
the  model predictions  (5.9  ug/dl  measured  and
predicted), with very slight differences in the 95 percent
confidence interval.  These results suggest that the
default soil and dust ingestion rates used in this version
of the  IEUBK model  (approximately  50 mg/day soil
and 60 mg/day dust for a total soil + dust ingestion of
110 mg/day, averaged over children ages 1 through 6)
may be roughly accurate  in representing the central
tendency  soil  and  dust ingestion rates of residence-
dwelling children in the three locations studied.

5.3.4    Relevant Studies of Primary Analysis
        The following studies are classified as relevant
rather than key. The tracer element studies described in
this  section are not designated as  key because the
methodology to account for non-soil tracer exposures
was not as well-developed as the  methodology in the
five U.S. tracer element studies.  However, Clausing et
al. (1987)  was  used in developing the biokinetic model
default soil and dust ingestion rates (U.S. EPA 1994a)
used in the Hogan et al. (1998) study, which was
designated as key.   In the  survey response studies, in
most  cases the  studies were  of a  non-randomized
design,  insufficient information was  provided to
determine important details regarding study design, or
no data were provided to allow quantitative estimates of
soil and/or dust ingestion rates.
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5.3.4.1  Dickins and Ford, 1942 - Geophagy (Dirt
        Eating) Among Mississippi  Negro School
        Children
        Dickens and Ford conducted a survey response
study of rural black school children (4th grade  and
above) in Oktibbeha County, Mississippi in September
1941. A total of 52 of 207 children (18 of 69 boys and
34 of 138  girls) studied gave positive responses to
questions administered in a test-taking format regarding
having eaten dirt in the previous 10 to 16  days.   The
authors  stated  that the study sample likely was more
representative of the higher socioeconomic levels in the
community, because  older children  from lower
socioeconomic levels sometimes left school in order to
work, and because children in the lower grades, who
were more  socioeconomically representative of the
overall  community, were excluded from the study.
Clay was identified as the  predominant type of soil
eaten.

5.3.4.2  Cooper, 1957 - Present Study
        Cooper (1957) conducted a non-randomized
survey response study in the 1950s of children age 7
months  or  older referred to  a Baltimore, Maryland
mental  hygiene clinic.  For 86 out of 784  children
studied, parents or caretakers gave positive responses to
the question "Does your child have a habit, or did he
ever have a habit, of eating dirt, plaster,  ashes, etc.?"
and  identified dirt,  or  dirt combined  with  other
substances, as  the substance ingested.  Cooper (1957)
described a pattern of pica behavior, including ingesting
substances otherthan soil, being most commonbetween
ages 2  and 4 or 5 years,  with one of the 86 children
ingesting clay  at age 10 years and 9 months.

5.3.4.3  Sarltrop, 1966 - The Prevalence of Pica
        Barltrop  (1966)  conducted  a  randomized
survey  response study of children  born in Boston,
Massachusetts  between  1958 and  1962, inclusive,
whose parents  resided in Boston and who were neither
illegitimate  nor  adopted.    A  stratified  random
subsample of 500 of these children were contacted for
in-person caregiver interviews, in which a total of 186
families (37 percent) participated. A separate stratified
subsample of 1,000 children was selected for a mailed
survey,  in  which 277 (28 percent)  of  the  families
participated. Interview-obtained data regarding care-
giver reports of pica (in this  study is defined as placing
nonfood items in the mouth and swallowing them)
behavior in all children ages 1 to 6 in the 186 families
(n=439) indicated 19 had ingested dirt (defined as yard
 dirt, house dust, plant-pot soil, pebbles, ashes, cigarette
 ash, glass fragments, lint,  and hair combings) in the
 preceding 14 days.  It does not appear that these data
 were corrected for unequal selection probability in the
 stratified random sample, nor were they corrected for
 non-response bias.   Interviews were conducted in the
 March/April time frame, presumably in 1964. Mail-
 survey obtained data regarding caregiver reports of pica
 in the preceding 14 days indicated that 39 of 277
 children had ingested dirt, presumably using the same
 definition as above. Barltrop (1966) mentions several
 possible  limitations of the  study,  including  non-
 participation bias and respondents' memory, or recall,
 effects.

 5.3.4.4  Bruhn  and Pangborn,  1971  - Reported
         Incidence of Pica among Migrant Families
         Bruhn and Pangborn  (1971) conducted  a
 survey among  91  low  income families  of migrant
 agricultural  workers in California in May  through
 August 1969.   Families were of Mexican descent in
 two labor camps (Madison camp, 10  miles  west of
 Woodland, and Davis camp, 10 miles  east of Davis)
 and were "Anglo" families at the Harney Lane camp 17
 miles  north of Stockton. Participation was 34 of 50
 families at the Madison camp, 31 of 50 families at the
 Davis camp, and 26 of 26 families at the Harney Lane
 camp. Respondents for the studied families (primarily
 wives) gave positive responses to open-ended questions
 such as  "Do you know of anyone who  eats dirt or
 laundry starch?" Bruhn and Pangborn (1971) apparently
 asked a modified version of this question pertaining to
 the respondents' own or relatives' families.   They
 reported  18  percent (12 of 65) of Mexican families'
 respondents  as   giving  positive   responses   for
 consumption of "dirt"  among children  within the
 Mexican respondents' own or relatives' families. They
 reported 42  percent (11 of 26) of "Anglo" families'
 respondents  as   giving  positive   responses   for
 consumption of "dirt" among children within the Anglo
 respondents' own or relatives' families.

 5.3.4.5  Robischon, 1971  - Pica Practice and Other
         Hand-Mouth   Behavior  and   Children's
         Developmental Level
         A survey response sample of 19- to 24-month
 old children examined at an urban well-child clinic in
 the late  1960s or   1970 in  an unspecified  location
 indicated that 48 of the  130 children whose caregivers
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Chapter 5 - Ingestion of Soil and Dust
were interviewed, exhibited pica behavior (defined as
"ate nonedibles more than once a week"). The specific
substances eaten were reported  for  30  of  the  48
children. All except 2 of the 30 children habitually ate
more than one nonedible substance. The soil and dust-
like substances reported as eaten by these 30 children
were: ashes (17), "earth" (5), dust (3), fuzz from rugs
(2), clay (1), and pebbles/stones (1).  Caregivers  for
some of the study subjects (between 0 and 52 of the 130
subjects, exact number not specified) reported that the
children "ate nonedibles less than once a week."

5.3.4.6  Binder  et  al,  1986  - Estimating Soil
        Ingestion: The Use  of Tracer  Elements in
        Estimating the Amount of Soil Ingested by
         Young Children
        Binder et al. (1986) used a tracer technique
modified from a method previously used to measure
soil ingestion among  grazing animals to study  the
ingestion of soil among children 1 to 3  years  of age
who wore diapers. The children were studied  during
the summer  of  1984  as part of  a  larger study of
residents living near a lead smelter  in East Helena,
Montana. Soiled diapers were collected over a 3-day
period from 65 children (42 males and 23 females), and
composited  samples  of soil were  obtained from  the
children's yards. Both excreta and soil samples were
analyzed for  aluminum, silicon, and titanium.  These
elements were found  in soil but were thought to be
poorly absorbed in the gut and to have been present in
the  diet  only  in  limited   quantities.    Excreta
measurements were obtained for 59 of the children.
Soil ingestion by each child was estimated on the basis
of each  of the three tracer elements using a standard
assumed fecal dry  weight of 15  g/day, and  the
following equation (5-2):
where:


T,,e

f
                                         (Eq. 5-2)
estimated soil ingestion for child i
based on element e (g/day);
concentration of element e in fecal
sample of child i (mg/g);
fecal dry weight (g/day); and
concentration of element e in child i's
yard soil (mg/g).
The analysis assumed that (1) the tracer elements were
neither lost nor introduced during sample processing;
(2) the soil ingested by children originates primarily
from their own yards;  and (3) that absorption of the
tracer elements by children occurred in only small
amounts.   The  study  did not distinguish  between
ingestion of soil and house dust, nor did it account for
the presence of the tracer elements in ingested foods or
medicines.
        The arithmetic mean quantity of soil ingested
by the children in the Binder et al. (1986) study was
estimated to be 181 mg/day (range 25 to 1,324) based
on the aluminum tracer; 184 mg/day (range 31 to 799)
based on the silicon tracer; and 1,834 mg/day (range 4
to 17,076) based on the titanium tracer (Table 5-13).
The overall mean soil ingestion estimate, based on the
minimum of the three  individual tracer estimates for
each child, was  108 mg/day (range 4 to 708).  The
median values were 121 mg/day, 136 mg/day, and 618
mg/day   for  aluminum,   silicon,  and   titanium,
respectively. The 95th percentile values for aluminum,
silicon, and titanium were  584 mg/day, 578 mg/day,
and 9,590 mg/day, respectively.  The 95th percentile
value based on the minimum  of the three individual
tracer estimates for each child was 386 mg/day.
        The  authors  were  not able to explain the
difference between the  results for titanium and for the
other two  elements,  but  they  speculated  that
unrecognized sources of titanium in the diet or in the
laboratory  processing  of stool  samples  may  have
accounted for the increased levels.  The frequency
distribution graph of soil ingestion estimates based on
titanium  shows  that  a group of 21  children  had
particularly high titanium values (i.e., > 1,000 mg/day).
The  remainder  of the children  showed  titanium
ingestion estimates at lower levels, with a distribution
more comparable to that of the other elements.

5.3.4.7  Clausing,  et  al.,  1987 -  A  method for
        estimating soil ingestion by children
        Clausing  et  al.  (1987)  conducted a  soil
ingestion study with Dutch children using a tracer
element methodology. Clausing et al. (1987) measured
aluminum, titanium, and acid-insoluble residue contents
of fecal samples  from children aged  2  to 4 years
attending  a  nursery  school,  and  for  samples of
playground dirt at that school. Over a 5-day period, 27
daily fecal samples were  obtained for  18 children.
Using the average soil  concentrations present at the
school, and assuming a standard fecal dry weight of 10
g/day, soil ingestion was estimated for each tracer. Six
hospitalized, bedridden children served as a control
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                                                       	Chapter 5 - Ingestion of Soil and Dust
group, representing  children who had  very limited
access to soil; 8 daily fecal samples were collected from
the hospitalized children.
        Without correcting  for  the  tracer element
contribution from background sources, represented by
the hospitalized children's soil ingestion estimates, the
aluminum-based soil ingestion estimates for the school
children in this study ranged from 23 to 979 mg/day,
the AIR-based estimates ranged from 48 to 3 62 mg/day,
and the titanium-based estimates ranged from 64  to
11,620 mg/day. As in the Binder et al. (1986) study, a
fraction of the children (6/18) showed titanium values
above 1,000 mg/day,  with most of the remaining
children  showing   substantially  lower   values.
Calculating an arithmetic mean quantity of soil ingested
based on each fecal  sample yielded 230 mg/day for
aluminum; 129 mg/day for AIR, and 1,430  mg/day for
titanium (Table 5-14).  Based on the Limiting Tracer
Method (LTM) and averaging across each fecal sample,
the arithmetic mean soil ingestion was estimated to be
105 mg/day with a population standard deviation of 67
mg/day (range 23 to 362 mg/day); geometric mean soil
ingestion was  estimated to be 90 mg/day.  Use of the
LTM  assumed that  "the maximum  amount of soil
ingested corresponded  with the lowest estimate from
the three tracers"  (Clausing et al., 1987).
        The hospitalized children's arithmetic mean
aluminum-based  soil  ingestion  estimate  was   56
mg/day; titanium-based estimates included estimates for
three  of the six children that exceeded 1,000 mg/day,
with the remaining three children in the range of 28  to
58 mg/day (Table 5-15). AIR measurements were not
reported for the hospitalized children. Using the LTM
method, the mean soil ingestion rate was estimated  to
be 49 mg/day with a population standard deviation  of
22 mg/day (range 26 to 84 mg/day).  The geometric
mean  soil ingestion  rate  was  45  mg/day.    The
hospitalized children's  data suggested a major nonsoil
source of titanium for some  children and a background
nonsoil source of aluminum.   However,  conditions
specific to hospitalization (e.g., medications) were not
considered.
        Clausing et al. (1987)  estimated that the
average soil ingestion  of the nursery school children
was 56  mg/day, after subtracting the mean LTM soil
ingestion forthe hospitalized children (49 mg/day) from
the nursery school children's mean LTM  soil ingestion
(105 mg/day), to account for background tracer intake
from dietary and other nonsoil sources.
 5.3.4.8  Smulian et al.,  1995 - Pica in a  Rural
         Obstetric Population
         In 1992, Smulian et al. (1995) conducted a
 survey response study of pica in a convenience sample
 of 125 pregnant women in Muscogee County, Georgia,
 who ranged in age from 12 to  37.  Of the 18 women
 who acknowledged practicing  pica, 4 acknowledged
 eating "white dirt" (common name for white clay) or
 "red dirt."  Of the 18 women,  9 stated the amount of
 substances  that they ingested (which included several
 substances  besides white or red dirt).  Thus, of the 4
 respondents who acknowledged ingesting white or red
 dirt, an  unknown number  of them  acknowledged
 ingesting 0.5  to  1.0 pounds of dirt  or clay per week
 (roughly 200-500 g/week). Of the 9 women who stated
 amounts of substances ingested,  6  stated  that their
 ingestion occurred daily and 3 stated that it occurred
 three times per week. The authors found a prevalence
 for the overall pica, by race/ethnicity, of 17.8 percent of
 the black women, 10.6 percent of the white women, and
 0 percent of the Asian and Hispanic women  in the
 sample, with no  significant differences between pica
 and nonpica groups with respect to age distribution or
 race.

 5.3.5   Relevant Studies of Secondary Analysis
         The secondary analysis literature on soil and
 dust ingestion  rates gives  important  insights  into
 methodological strengths and limitations.  The tracer
 element studies described in this section are grouped to
 some  extent   according   to  methodological  issues
 associated with the tracer element methodology. These
 methodological issues include attempting to determine
 the origins of apparent positive and negative bias in the
 methodologies,  including: food  input/fecal   output
 misalignment; missed fecal samples; assumptions about
 children's fecal weights; particle sizes of, and relative
 contributions  of  soils and  dusts to total soil and dust
 ingestion;  and attempts to identify a  "best"  tracer
 element or combination of tracer elements.  Potential
 error from using  short-term studies' estimates for long
 term soil and dust ingestion behavior estimates  is also
 discussed.

 5.3.5.1  Stanek  et al.,  2001a  - Biasing Factors for
         Simple  Soil Ingestion Estimates in Mass
         Balance Studies of Soil Ingestion
         In order to identify  and  evaluate biasing
 factors  for soil ingestion  estimates,  the authors
 developed a simulation model based  on data from
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previous soil ingestion studies. The soil ingestion data
used in this model were taken from Calabrese et al.
(1989)  (the  Amherst  study);  Davis  et  al.  (1990)
(southeastern  Washington State);  Calabrese et al.
(1997a)  (the Anaconda  study) and  Calabrese et al.
(1997b) (soil-pica in Massachusetts), and relied only on
the aluminum  and silicon  trace element estimates
provided in these studies.
         Of the biasing factors explored, the impact of
study duration was the most  striking, with a  positive
bias of  more than 100 percent for 95th percentile
estimates in a 4-day tracer element  study. A smaller
bias was observed for the impact of absorption of trace
elements from food.   Although the trace elements
selected  for use in these studies are believed to have
low absorption, whatever amount is  not accounted for
will result in an underestimation of the soil ingestion
distribution.  In these simulations, the absorption of
trace elements from food of up to 30 percent was shown
to  negatively  bias  the estimated  soil  ingestion
distribution by less than 20 mg/day.  No biasing effect
was found  for misidentifying  play areas  for soil
sampling (i.e., ingested soil from a yard other than the
subject's yard).

5.3.5.2   Calabrese and Stanek, 1995 - Resolving
         Intertracer Inconsistencies in Soil Ingestion
         Estimation
         Calabrese and Stanek (1995) explored sources
and magnitude of positive and negative errors in soil
ingestion estimates for children on a subject-week and
trace  element basis.  Calabrese  and Stanek  (1995)
identified possible sources of positive errors to be:
•        Ingestion of high levels of tracers before the
         start of the study and low ingestion during the
         study period; and
•        Ingestion of element tracers from a non-food
         or non-soil source during the study period.
Possible sources of negative bias were identified as:
•        Ingestion of tracers in food that  are not
         captured in the fecal sample either due to slow
         lag time or not having a fecal sample available
         on the final study day; and
•        Sample  measurement errors  that result  in
         diminished detection of fecal tracers, but not
         in soil tracer levels.
The authors developed an approach that attempted to
reduce the magnitude of error in the individual trace
element ingestion estimates.  Results from a previous
study conducted by Calabrese et al. (1989) were used to
quantify these errors based on the following criteria:
(1) a lag  period of 28 hours was assumed for the
passage of tracers ingested in food to the feces  (this
value was applied to all subject-day estimates); (2) a
daily soil ingestion rate was estimated for each tracer
for each 24-hour day a fecal sample was obtained; (3)
the median tracer-based  soil ingestion rate for each
subject-day was determined; and (4) negative errors due
to missing fecal samples at the end of the study period
were also  determined.  Also, upper- and lower-bound
estimates  were determined based on criteria formed
using an assumption of the magnitude of the relative
standard deviation (RSD) presented in another study
conducted by Stanek and Calabrese (1995a).  Daily soil
ingestion rates for tracers that fell beyond the upper and
lower  ranges   were  excluded   from  subsequent
calculations, and the median soil ingestion rates of the
remaining tracer elements were considered the  best
estimate for that particular  day.  The magnitude  of
positive or negative error for a specific tracer per day
was derived by determining the difference between the
value for the tracer and the median value.
        Table 5-16 presents the estimated magnitude
of positive and negative error for six tracer elements in
the children's  study  (conducted by Calabrese et al.,
1989). The original non-negative  mean soil ingestion
rates (Table 5-3) ranged from alow of 21 mg/day based
on zirconium to  a high  of 459  mg/day  based on
vanadium.  The adjusted mean soil ingestion rate after
correcting for negative and positive errors ranged from
97 mg/day based on yttrium to 208 mg/day based on
titanium. Calabrese and Stanek (1995) concluded that
correcting for errors at the individual level for each
tracer element provides more reliable estimates of soil
ingestion.

5.3.5.3  Stanek  and  Calabrese,  1995a   - Daily
        Estimates of Soil Ingestion in Children
        Stanek  and Calabrese (1995a)  presented  a
methodology which links the physical passage of food
and  fecal  samples to  construct  daily  soil ingestion
estimates  from  daily food  and fecal trace-element
concentrations.    Soil ingestion  data  for children
obtained from the Amherst study  (Calabrese et al.,
1989)  were  reanalyzed  by  Stanek  and  Calabrese
(1995a). A lag period of 28 hours between food intake
and fecal output was assumed for all respondents.  Day
1  for the  food sample corresponded to the 24 hour
period from  midnight on Sunday to  midnight on
Monday of a study week; day 1 of the fecal  sample
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                                                        	Chapter 5 - Ingestion of Soil and Dust
corresponded  to the 24  hour period from  noon on
Monday to noon  on Tuesday.   Based on  these
definitions,  the food  soil equivalent  was subtracted
from the fecal soil equivalent to  obtain an estimate of
soil ingestion  for  a trace element.  A  daily overall
ingestion estimate was constructed for each child as the
median of trace element values remaining after tracers
falling outside of a defined range  around the overall
median were excluded.
         Table 5-17   presents  adjusted  estimates,
modified according to  the input/output misalignment
correction,  of mean  daily  soil ingestion per  child
(mg/day) for the 64 study participants. The approach
adopted in  this paper led  to changes in ingestion
estimates from those presented in Calabrese  et al.
(1989).
         Estimates of children's soil ingestion projected
over a period of 365 days were derived by fitting log-
normal distributions to the overall daily soil ingestion
estimates using estimates modified according to the
input/output misalignment correction (Table 5-18). The
estimated median value of the 64 respondents' daily soil
ingestion averaged over a year was 75 mg/day,  while
the 95th percentile was 1,751 mg/day. In developing the
365-day soil  ingestion  estimates,  data that  were
obtained over a short period of time (as is the case with
all available soil ingestion studies) were extrapolated
over a year. The 2-week study period may not reflect
variability  in  tracer element ingestion  over a year.
While Stanek and Calabrese (1995a)  attempted  to
address  this  through  modeling of  the  long   term
ingestion, new uncertainties were introduced through
the parametric  modeling of the limited subject day data.

5.3.5.4   Calabrese and  Stanek,  1992b  -   What
         Proportion of Household Dust is Derived
        from  Outdoor Soil?
         Calabrese and Stanek (1992b) estimated the
amount of outdoor soil in indoor dust using statistical
modeling. The model used soil and dust data from the
60 households that participated in the  Calabrese et al.
(1989) study, by preparing scatter plots of each tracer's
concentration in soil versus dust. Correlation analysis
of the scatter plots was performed. The scatter plots
showed  little  evidence of  a consistent relationship
between outdoor soil and indoor dust concentrations.
The model estimated the  proportion of outdoor soil in
indoor dust  using the simplifying assumption that the
following variables were constants in all houses: the
amount of dust produced  every day from both indoor
 and outdoor sources; the proportion of indoor dust due
 to outdoor soil; and the concentration  of the tracer
 element in dust produced from indoor sources. Using
 these assumptions,  the  model  predicted  that  31.3
 percent  by weight of indoor dust came  from  outdoor
 soil.  This model was  then  used to adjust  the soil
 ingestion estimates from Calabrese et al. (1989). Using
 an assumption that 50 percent of excess fecal tracers
 were from indoor origin and 50 percent  were from
 outdoor origin, and multiplying the 50 percent indoor-
 origin excess fecal tracer by the model prediction that
 31.3 percent of indoor dust came from  outdoor soil,
 results in  an estimate that 15 percent of excess fecal
 tracers were  from soil materials that were present in
 indoor dust.  Adding this 15 percent to the 50 percent
 assumed  outdoor (soil) origin  excess  fecal tracer
 quantity results in an estimate that approximately 65
 percent  of the total residual excess fecal  tracer was of
 soil origin (Calabrese and Stanek, 1992b).

 5.3.5.5  Calabrese et al.,  1996 -  Methodology  to
         Estimate the Amount and  Particle Size  of
         Soil Ingested by Children: Implications for
         Exposure Assessment at Waste Sites
         Calabrese etal., 1996 examined the hypothesis
 that one cause of the variation between tracers seen in
 soil ingestion studies could be related to differences in
 soil tracer concentrations by particle size.  This study,
 published prior to the Calabrese et al. (1997a)  primary
 analysis study results, used laboratory analytical results
 for the Anaconda, Montana soil's tracer concentration
 after it had been sieved to a particle size of <250 um in
 diameter (it was sieved to <2 mm soil particle size in
 Calabrese etal. (1997a)). The smaller particle size was
 examined based  on  the assumption  that  children
 principally ingest soil of small particle size adhering to
 fingertips  and under fingernails. For five  of the tracers
 used in the original study (aluminum,  silicon, titanium,
 yttrium, and zirconium), soil  concentration was not
 changed  by  particle   size.     However, the  soil
 concentrations of three tracers (lanthanum, cerium, and
 neodymium) were increased  two- to fourfold at the
 smaller  soil particle size. Soil ingestion  estimates for
 these three tracers were decreased by approximately 60
 percent at the 95th percentile compared to  the Calabrese
 et al. (1997a) results.
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5.3.5.6  Stanek et al, 1999 - Soil Ingestion Estimates
        for  Children  in  Anaconda  Using Trace
        Element Concentrations in Different Particle
        Size Fractions
        Stanek et al. (1999) extends the findings from
Calabrese et  al. (1996) by quantifying trace  element
concentrations in soil based on sieving to particle sizes
of 100 to 250 um and to particle sizes of 53 to < 100
um. This study used the data from soil concentrations
from the Anaconda, Montana site reported by Calabrese
et al. (1997a).  Results of the study indicated  that soil
concentrations of aluminum, silicon and titanium do not
increase at the two finer particle size ranges measured.
However, soil concentrations of cerium, lanthanum and
neodymium increased by a factor of 2.5 to 4.0 in the
100-250  um particle size range when compared with
the 0 to 2  um  particle  size range.  There was not a
significant  increase in  concentration  in the 53 to 100
um particle size range.

5.3.5.7  Stanek and Calabrese, 1995b - Soil Ingestion
        Estimates for Use in Site Evaluations Based
        on the Best Tracer Method
        Stanek and Calabrese (1995b)  recalculated
children's  soil  ingestion  rates  from  two  previous
studies, using data for  8 tracers from Calabrese et al.,
1989  and  3  tracers  from  Davis  et al.,  1990.
Recalculations  were performed using the Best Tracer
Method  (BTM).      This   method  selected   the
"best"tracer(s), by dividing the total amount of tracer in
a particular child's duplicate  food sample by tracer
concentration in that child's soil  sample to yield a
food/soil (F/S) ratio.  The F/S ratio was small when the
tracer concentration in food was low compared to the
tracer concentration in soil.   Small  F/S ratios were
desirable because they lessened  the impact of transit
time error (the error that occurs when fecal output does
not reflect  food ingestion,  due  to fluctuation  in
gastrointestinal  transit  time)  in the  soil ingestion
calculation.
        The  BTM used a ranking scheme of F/S ratios
to determine the best tracers for use in the ingestion rate
calculation. To reduce the impact of biases that may
occur as a result of sources of fecal tracers other than
food or soil, the median  of  soil ingestion estimates
based  on the  four lowest F/S  ratios was  used  to
represent soil ingestion.
         Using the  lowest four F/S ratios for each
child, calculated on a per-week ("subject-week") basis,
the median of the soil ingestion estimates from the
Calabrese et al.  (1989) study most  often  included
aluminum, silicon, titanium, yttrium, and zirconium.
Based on the median of soil ingestion estimates from
the best four tracers, the mean soil ingestion rate was
132 mg/day and the median was 33 mg/day.  The 95th
percentile value was 154 mg/day. Forthe 101 children
in the Davis et al. (1990) study, the mean soil ingestion
rate was  69  mg/day and the median soil ingestion rate
was 44 mg/day. The 95th percentile estimate was 246
mg/day.  These data are based on the three tracers (i.e.,
aluminum, silicon and titanium) from the Davis et al.
(1990) study.  When the results for the 128 subject-
weeks in Calabrese et al. (1989) and 101  children in
Davis et  al. (1990) were combined, soil ingestion for
children was estimated to be 104 mg/day  (mean); 37
mg/day  (median); and  217  mg/day (95th percentile),
using the BTM.

5.3.5.8  Stanek and  Calabrese,  2000 -  Daily Soil
        Ingestion  Estimates for Children  at   a
        Superfund Site
         Stanek and Calabrese (2000) reanalyzed the
soil ingestion data  from the Anaconda study.  The
authors assumed a lognormal distribution for the soil
ingestion estimates in the Anaconda study to predict
average soil ingestion for children over a longer time
period.  Using  "best linear unbiased predictors," the
authors predicted 95th percentile soil ingestion values
over time periods of 7 days, 30 days, 90 days, and 365
days. The 95th percentile soil ingestion values were
predicted to be  133 mg/day over 7 days, 112 mg/day
over 30  days,  108 mg/day over  90  days,  and 106
mg/day  over 365 days.   Based on  this  analysis,
estimates of the distribution of longer term average soil
ingestion are expected to be narrower, with the 95th
percentile estimates being as much as 25 percent lower
(Stanek and Calabrese, 2000).

5.3.5.9  Stanek  et  al.,  2001b   -  Soil Ingestion
        Distributions  for   Monte   Carlo  Risk
        Assessment in Children
         Stanek et al. (200 Ib) developed "best linear
unbiased predictors" to reduce the biasing  effect  of
short-term   soil  ingestion   estimates.    This  study
estimated  the   long-term   average   soil  ingestion
distribution using daily soil ingestion estimates from
children who participated in the Anaconda,  Montana
study.  In this long-term (annual) distribution, the soil
ingestion estimates were: mean 31, median 24, 75th
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                                                       	Chapter 5 - Ingestion of Soil and Dust
percentile 42, 90th percentile 75, and 95th percentile 91
mg/day.

5.3.5.10 von Lindern etal., 2003 -Assessing remedial
        effectiveness through the blood lead:soil/dust
        lead  relationship   at  the   Bunker  Hill
        Superfund Site in the Silver Valley of Idaho
        Similar to Hogan et al. (1998), von Lindern et
al. (2003) used the IEUBK model to predict blood lead
levels  in a non-random  sample of several  hundred
children ages 0-9 years in an area of northern Idaho
from   1989-1998  during   community-wide   soil
remediation.   Von Lindern  et al.  (2003) used the
IEUBK default soil and dust ingestion  rates  together
with observed house dust/soil lead levels (and imputed
values based  on community soil and dust lead levels,
when  observations  were  missing).   The  authors
compared the predicted blood lead levels with observed
blood lead levels and found that the default IEUBK soil
and dust ingestion rates and lead bioavailability value
overpredicted blood lead levels, with the overprediction
decreasing  as   the   community  soil  remediation
progressed. The authors stated that the overprediction
may have been caused either by a default soil and dust
ingestion that was too  high, a default bioavailability
value for lead that was too high, or some combination
of the two.  They also noted underpredictions for some
children, for whom follow  up  interviews  revealed
exposures to  lead sources not accounted  for by the
model, and noted that the study sample included many
children  with a  short  residence  time  within the
community.
        Von  Lindern et  al.  (2003)  developed  a
statistical model that apportioned the contributions of
community soils, yard soils of the residence, and house
dust to lead intake; the models'  results suggested that
community soils contributed  more (50  percent) than
neighborhood soils (28  percent) or yard soils (22
percent)  to soil found in house dust of the studied
children.

5.4      LIMITATIONS    OF    KEY   STUDY
        METHODOLOGIES
        The  three  types of information  needed to
provide recommendations to exposure assessors on soil
and dust ingestion rates among  U.S. children include
quantities of soil and dust ingested, frequency of high
soil and dust ingestion episodes, and prevalence of high
soil and dust ingesters.  The methodologies provide
different types of information: the tracer element and
 biokinetic model  comparison methodologies provide
 information on quantities of soil and dust ingested; the
 tracer element methodology provides limited evidence
 of the frequency of high soil ingestion episodes; the
 survey  response  methodology  can  shed  light  on
 prevalence of high soil ingesters and frequency of high
 soil ingestion episodes.  The methodologies used to
 estimate soil and dust ingestion rates and prevalence of
 soil  and   dust  ingestion  behaviors  have  certain
 limitations, when used for the purpose of developing
 recommended soil  and dust ingestion  rates.   This
 section  describes  some  of the  known  limitations,
 presents an evaluation of the current state of the science
 for U.S. children's soil and dust ingestion rates, and
 describes  how the limitations affect the confidence
 ratings given to the recommendations.

 5.4.1    Tracer Element Methodology
         This  section   describes  some previously
 identified limitations of the tracer element methodology
 as it has been implemented by U.S. researchers, as well
 as additional potential  limitations that have not been
 explored.  Some of these same limitations would also
 apply to the Dutch and Jamaican studies that used a
 control  group of hospitalized children to account for
 dietary and pharmaceutical tracer intakes.
         Binder et al. (1986) described some of the
 major and obvious limitations of the early U.S. tracer
 element methodology as follows:
         [T]he algorithm assumes that children ingest
         predominantly soil from their own yards and
         that concentrations of elements in composite
         soil samples from front and back yards are
         representative of overall concentrations in the
         yards....children probably eat a combination of
         soil and  dust; the algorithm used does not
         distinguish   between   soil   and   dust
         ingestion....fecal sample weights...were much
         lower than  expected...the assumption  that
         aluminum,  silicon  and  titanium  are  not
         absorbed is not entirely true....dietary intake of
         aluminum,  silicon  and  titanium   is  not
         negligible when compared with the potential
         intake of these elements from soil....Before
         accepting these estimates as true values of soil
         ingestion  in  toddlers,  we  need  a  better
         understanding   of  the  metabolisms  of
         aluminum, silicon and titanium in children,
         and the validity of the assumptions we made
         in our calculations should be explored further.
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Chapter 5 - Ingestion of Soil and Dust
The subsequent U.S. tracer element studies (Calabrese
et al.  (1989)/Barnes  (1990),  Davis et   al. (1990),
Calabrese et al. (1997a), and Davis and Mirick (2006))
made some progress in addressing some of the Binder
et al. (1986) study's stated limitations.
         Regarding the issue of non-yard (community-
wide)  soil as a source of ingested soil, one  study
(Calabrese et al. 1989/Barnes 1990) addressed this
issue to some extent, by including samples of children's
day care center soil in the analysis.  Calabrese et al.
(1997a) attempted to  address  the issue  by excluding
children  in day care  from the study sample frame.
Homogeneity of community   soils' tracer   element
content would play a  role in whether this issue is an
important biasing factor for the tracer element studies'
estimates.  Davis et al.  (1990) evaluated  community
soils' aluminum, silicon and titanium content and found
little variation among  101  yards throughout the three-
city area. Stanek et al. (200la) conclude that there is
"minimal impact" on estimates of soil ingestion due to
mis-specifying a child's play area.
         Regarding the  issue  of soil and dust  both
contributing to  measured tracer element quantities in
excreta samples, the five key U.S.  tracer  element
studies all attempt to  address  the issue by including
samples of household  dust in the analysis, and in some
cases estimates are presented in the published articles
that adjust soil  ingestion estimates on the basis of the
measured tracer elements found in the household dust.
The relationship between soil ingestion rates and indoor
settled dust ingestion rates has  been evaluated in some
of the  secondary studies (e.g., Calabrese  and Stanek
(1992b)). An issue similar to the community-wide soil
exposures in the previous paragraph could also exist
with community-wide indoor dust exposures (such as
dust found   in  schools and  community buildings
occupied by study subjects during or prior to the study
period). A portion of the community-wide indoor dust
exposures (that due to occupying day care facilities)
was addressed  in the Calabrese et al.  (1989)/Barnes
(1990) study, but not in  the  other three key tracer
element studies. In addition, if the key studies' vacuum
cleaner collection method  for household and day care
indoor settled dust samples influenced tracer element
composition  of indoor settled  dust samples, the dust
sample collection method would be another area of
uncertainty with the key studies' indoor dust related
estimates.  The  survey  response  studies suggest that
some young children may prefer ingesting dust  to
ingesting soil. The existing literature on soil versus
dust sources of children's lead exposure may provide
useful information that has not yet been compiled for
use in soil and dust ingestion recommendations.
        Regarding the issue of fecal sample weights
and the related issue of missing fecal and urine samples,
the four key  tracer element  studies  have  varying
strengths and limitations.  The Calabrese et al. (1989)
article  stated  that wipes  and  toilet paper were  not
collected by the researchers, and thus underestimates of
fecal quantities may have occurred.  Calabrese et al.
(1989) stated that cotton cloth diapers were supplied for
use during the study; commodes apparently were used
to collect both feces and urine for those children who
were not  using diapers.   Barnes  (1990)  described
cellulose  and  polyester  disposable  diapers with
significant variability in silicon and titanium content
and suggested that children's urine was not included in
the analysis. Thus, it is unclear to what extent complete
fecal and urine output was obtained, for each study
subject.  The Calabrese et al.  (1997a) study did  not
describe missing  fecal samples  and  did  not state
whether urinary tracer element quantities were used in
the soil and dust ingestion estimates, but stated that
wipes and toilet paper were not collected.   Missing
fecal samples may have resulted in negative bias in the
estimates from both of these  studies.  Davis et al.
(1990) and Davis  and Mirick (2006) were  limited to
children who no  longer wore diapers.  Missed fecal
sample  adjustments  might  affect  those  studies'
estimates in either a positive or negative direction,  due
to the  assumptions the authors  made regarding  the
quantities of feces and  urine  in  missed  samples.
Adjustments for missing fecal and urine samples could
introduce errors sufficient to cause negative estimates
if missed samples were  heavier than the collected
samples used in the  soil and dust ingestion estimate
calculations.
        Regarding the issue of dietary intake, the five
key U.S. tracer element  studies  have all  addressed
dietary (and non-dietary, non-soil) intake by subtracting
quantitated estimates of these sources of tracer elements
from excreta tracer element quantities, or by providing
study subjects with personal hygiene products that were
low in  tracer element content.  Applying the food  and
non-dietary, non-soil corrections required subtracting
the tracer element contributions from  these non-soil
sources from the  measured fecal/urine  tracer element
quantities.    To  perform this  correction  required
assumptions to be made regarding the gastrointestinal
transit time, or the time lag between inputs (food, non-
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                                                        	Chapter 5 - Ingestion of Soil and Dust
dietary non-soil, and soil) and outputs (fecal and urine).
The gastrointestinal transit time assumption introduced
a new potential source of bias that some authors (e.g.,
Stanek  and  Calabrese,  1995a)  called  input/output
misalignment or transit time error.  This lag time may
also be a function of age. Davis et al. (1990) and Davis
and Mirick (2006) assumed a 24  hour lag  time in
contrast to the 28 hour lag times used in Calabrese et al.
(1989)/Barnes (1990) and  Calabrese et al. (1997a).
ICRP (2002) suggested a lag time of 37 hours for one
year old children and 5 to 15 year old children. Stanek
and Calabrese (1995a) describe a method designed to
reduce bias from this error source.
        Regarding  gastrointestinal absorption,  the
authors of three of the studies appeared to agree that the
presence of silicon in urine represented evidence  that
silicon was  being  absorbed from the gastrointestinal
tract (Davis et al.,  1990; Calabrese et al., 1989/Barnes
(1990); Davis and Mirick,  2006).  There  was some
evidence of aluminum absorption in Calabrese et al.,
1989/Barnes (1990); Davis  and Mirick (2006) stated
that aluminum and titanium did not appear to have been
absorbed, based on low urinary levels.  Davis et al.
(1990) stated that silicon appears to have been absorbed
to a greater degree than aluminum and titanium, based
on urine concentrations.
        Aside from the gastrointestinal absorption, lag
time and missed fecal sample issues, Davis and Mirick
(2006) offer another other possible explanation for the
negative soil and  dust ingestion rates  estimated for
some study participants. Because the weights of dried
food and liquid (input) samples were sufficiently great,
relative to  the  urine and fecal  (output)  samples,
overestimates in laboratory analytical  values for the
input  samples would not be  compensated for by a
similar overestimate in the output samples.
        Another  limitation on  accuracy of tracer
element-based  estimates of soil  and  dust ingestion
relates  to  inaccuracies  inherent  in  environmental
sampling and laboratory analytical techniques.   The
"percent recovery" of different tracer elements varies
(according  to validation of the  study methodology
performed with adults who swallowed gelatin capsules
with known quantities of sterilized  soil, as part of the
Calabrese et al., 1989 and  1997a studies).  Estimates
based on a particular tracer element with a lower or
higher recovery than the expected 100 percent in any of
the study samples would  be  influenced  in  either a
positive  or  negative direction,  depending  on  the
recoveries in the various samples and their degree of
 deviation  from  100 percent (e.g.,  Calabrese et al.,
 1989).
         Davis et al. (1990) offered an assessment of
 the impact of swallowed toothpaste on the tracer-based
 estimates  by adjusting  estimates for those children
 whose caregivers reported that they had swallowed
 toothpaste.  Davis  et al.  (1990)  had supplied study
 children with toothpaste that had been pre-analyzed for
 its tracer element content, but it is not known to what
 extent the  children  actually  used  the  supplied
 toothpaste. Similarly, Calabrese etal, 1989 and 1997a
 supplied children in the Amherst, Massachusetts and
 Anaconda, Montana studies with toothpaste containing
 low levels of  most tracers,  but it is unclear to what
 extent those children used the supplied toothpaste.
         Other research suggests additional possible
 limitations that  have not yet  been explored.  First,
 lymph tissue  structures  in  the gastrointestinal  tract
 might serve as reservoirs for  titanium  dioxide food
 additives and soil particles, which could bias estimates
 either upward or  downward  depending on tracers'
 entrapment within,  or  release  from, these  reservoirs
 during the study period (ICRP  (2002); Shepherd et al.
 (1987); Powell et al. (1996)). Second, gastrointestinal
 uptake of  silicon may have occurred, which could bias
 those  estimates downward. Evidence of silicon's role
 in bone formation (e.g., Carlisle (1980)) supported by
 newerresearch on dietary silicon uptake (Jugdaohsingh
 et al. (2002);  Van  Dyck et al.  (2000)) suggests  a
 possible negative bias in the silicon-based soil ingestion
 estimates,  depending  on the  quantities of  silicon
 absorbed  by growing children.  Third, regarding the
 potential for swallowed toothpaste to bias soil ingestion
 estimates  upward, commercially available toothpaste
 may contain quantities of titanium and perhaps silicon
 and aluminum in the range that could be expected to
 affect the soil and dust ingestion estimates. Fourth, for
 those  children who drank bottled or tap water during
 the study  period, and did not  include those drinking
 water samples in their duplicate food samples, slight
 upward  bias may exist in some of the  estimates for
 those children, since drinking water may contain small,
 but relevant, quantities of silicon and potentially other
 tracer elements.   Fifth, the tracer element  studies
 conducted to date have not explored the impact of soil
 properties' influence on toxicant  uptake or excretion
 within the gastrointestinal tract. Nutrition researchers
 investigating influence of clay geophagy behavior on
 human nutrition have begun using in vitro models of the
 human digestion (e.g., Dominy et al., 2003; Hooda et
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al., 2004).  A recent review (Wilson, 2003) covers a
wide range of geophagy research in humans and various
hypotheses  proposed  to   explain   soil  ingestion
behaviors, with emphasis on the  soil properties of
geophagy materials.

5.4.2    Biokinetic Model Comparison Methodology
        It is possible that the IEUBK biokinetic model
comparison methodology contained  sources of both
positive and  negative bias,  like the tracer element
studies, and that the net impact of the competing biases
was in either the positive or negative direction. U.S.
EPA's judgment about the major sources of bias in the
biokinetic model comparison studies is that there may
be three significant sources of bias. The first source of
potential bias was the possibility that the biokinetic
model failed  to account for sources of lead exposure
that are important  for  certain children.  For these
children, the  model  might  either under-predict, or
accurately predict, blood lead levels compared to actual
measured  lead levels.   However, this result may
actually mean that the default assumed lead intake rates
via either soil and dust ingestion, or another lead source
that is accounted for by the model, are too high.  The
second  source of  potential bias was  use  of  the
biokinetic model for  predicting  blood lead levels in
children who have not spent a significant amount of
time in the areas characterized as the main sources of
environmental lead exposure for those children, which
could result in either  upward or downward biases in
those  children's  predicted   blood   lead  levels.
Comparing  upward-biased  predictions   with  actual
measured  blood lead  levels and finding a relatively
good  match could lead to inferences  that the model's
default soil and dust ingestion rates are accurate, when
in fact the children's  soil and dust ingestion rates, or
some other lead source, were actually higher than the
default  assumption.    Comparing downward-biased
predictions with actual measured blood lead levels and
finding a relatively good match could lead to inferences
that the model's default soil  and dust ingestion rates
were accurate, when in fact the children's soil and dust
ingestion rates, or some other lead source, were actually
lower than the default  assumption. The third source of
potential bias was the assumption within the model
itself regarding the biokinetics of absorbed lead, which
could result in either  positively  or negatively  biased
predictions and the same kinds of incorrect inferences
as the second source of potential bias.
5.4.3    Survey Response Methodology
        Each data collection methodology (in-person
interview,   mailed   questionnaire,  or  questions
administered in "test" format in a school setting) may
have had  specific limitations.  In-person interviews
could result in either positive or negative response bias
due to distractions posed by young children, especially
when interview  respondents simultaneously care  for
young children and answer questions. Other limitations
include positive  or  negative  response bias due  to
respondents' perceptions of  a  "correct"  answer,
question wording difficulties, lack of understanding of
definitions  of  terms  used,  language and dialect
differences  between  investigators and respondents,
respondents' desires to  avoid  negative  emotions
associated with giving a particular type of answer, and
respondent  memory  problems   ("recall"  effects)
concerning past  events.  Mailed questionnaires have
many of the same limitations as in-person interviews,
but may allow respondents to respond when they  are
not distracted by childcare duties.  An in-school test
format is more problematic  than either interviews or
mailed  surveys,  because  respondent bias related to
teacher expectations could influence responses.
        Unweighted  survey   responses  from  the
National Health  and Nutrition Examination Survey
(NHANES)  I and II regarding children's clay and dirt
ingestion are available (U.S. DHHS 1981a,U.S. DHHS
1981b, U.S. DHHS  1985a,  U.S. DHHS  1985b) and
appear generally to corroborate the results of the survey
response studies summarized in this chapter, in that a
small proportion of respondents acknowledge  eating
dirt or clay.  U.S. EPA  has undertaken an  effort to
weight the survey responses among adult  caregiver
respondents  who acknowledged clay and dirt ingestion
by  children under age  12  years  and among  child
respondents  ages 12 up to 21  years who acknowledged
clay and  dirt ingestion, to  develop an  estimate  of
prevalence of the behavior among children.
        One approach to evaluating the degree of bias
in survey  response studies may be to make  use of a
surrogate  biomarker  indicator providing suggestive
evidence of ingestion of significant quantities of soil
(although quantitative estimates would not be possible).
The biomarker technique measures  the presence  of
serum  antibodies  to  Toxocara  species, a  parasitic
roundworm from cat and dog feces.  Two U.S. studies
have found associations between reported soil ingestion
and  positive  serum  antibody  tests for Toxocara
infection (Marmor et al., 1987; Glickman et al., 1981);
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                                                       	Chapter 5 - Ingestion of Soil and Dust
a third (Nelson et al., 1996) has not, but the authors
state that reliability of survey responses regarding soil
ingestion may have been an issue. Further refinement
of survey response methodologies, together with recent
NHANES data on U.S.  prevalence of positive serum
antibody status  regarding infection with  Toxocara
species, may be useful.

5.4.4    Key  Studies:  Representativeness of  U.S.
        Population
        The two key studies of Dutch and Jamaican
children  may  represent  different  conditions  and
different study populations than those in the U.S.; thus,
it  is  unclear  to  what  extent those  children's  soil
ingestion behaviors may differ from U.S. children's soil
ingestion behaviors.
        Limitations  regarding  the   key  studies
performed  in  the  U.S.  for estimating soil and  dust
ingestion rates in the entire population of U.S. children
ages 0 to < 21 years fall into the broad categories of
geographic  range and  demographics  (age,  gender,
race/ethnicity, socioeconomic status).
        Regarding geographic range, the two most
obvious issues relate to soil types and  climate.  Soil
properties might influence the soil ingestion estimates
that are based on excreted tracer elements. The Davis
et al. (1990), Calabrese et al.  (1989)/Barnes (1990),
Davis and Mirick (2006) and Calabrese et al. (1997a)
tracer element studies were in locations with soils that
had  sand content ranging from 21-80 percent, silt
content ranging from 16-71 percent, and clay content
ranging from 3-20 percent by weight, based on  data
from USDA (2008). The location of children in the
Calabrese et al. (1997b) study was not specified, but
due to the original survey response study's occurrence
in western Massachusetts, the soil types in the vicinity
of the Calabrese et al. (1997b) study are likely to be
similar to those in the Calabrese et al. (1989)/Barnes
(1990) study.
        The Hogan  et  al. (1998)  study  included
locations in the central part of the U.S. (an area along
the Kansas/Missouri border, and an area in western
Illinois)  and  one in the  eastern U.S.  (Palmerton,
Pennsylvania).  The only key study conducted in the
southern part of the U.S. was  Vermeer and Frate
(1979).
        Children might be outside and have access to
soil in a very wide range of weather conditions (Wong
et al., 2000). In the parts of the U.S. that experience
moderate temperatures year-round, soil ingestion rates
 may be fairly evenly distributed throughout the year.
 During conditions of deep snow cover, extreme cold, or
 extreme  heat, children could be  expected to  have
 minimal  contact  with outside soil.   All children,
 regardless of location, could ingest soils located indoors
 in plant  containers, or outdoor soil tracked inside
 buildings  by human or animal building  occupants.
 Davis  et  al. (1990) did not find a  clear or consistent
 association between the number of hours spent indoors
 per day and soil ingestion, but reported  a consistent
 association between spending a greater number of hours
 outdoors and high (defined as the uppermost tertile) soil
 ingestion levels across  all three tracers used.
         The five key tracer element studies all took
 place  in  northern  latitudes.   The temperature  and
 precipitation patterns that occurred during these  four
 studies' data collection periods was difficult to discern
 due to  no mention of specific data  collection dates in
 the  published  articles.     The   Calabrese  et  al.
 (1989)/Barnes (1990) study apparently took place in
 mid- to late September 1987 in and near Amherst,
 Massachusetts; Calabrese etal. (1997a) apparently took
 place in  late September and  early October 1992, in
 Anaconda, Montana; Davis et al. (1990) took place in
 July,  August and  September 1987,  in  Richland,
 Kennewick and Pasco, Washington; and Davis and
 Mirick (2006) took place in the same Washington state
 location in late July, August and very early September
 1988 (raw data). Inferring exact data collection dates,
 a wide range of temperatures may have occurred during
 the four  studies' data  collection periods  (daily lows
 from 22-60 °F and 25-48 °F, and daily highs from 53-81
 °F and 55-88 °F in Calabrese et al. (1989) and Calabrese
 et al. (1997a), respectively, and daily lows from 51-72
 °F and 51  - 67 °F, and daily highs from 69-103 °F and
 80-102 °F in Davis et al. (1990) and Davis and Mirick
 (2006), respectively) (National Climatic Data Center,
 2008). Significant amounts of precipitation occurred
 during Calabrese et al. (1989) (more than 0.1 inches per
 24  hour  period)  on  several days; somewhat  less
 precipitation was  observed  during Calabrese et al.
 (1997a);  precipitation  in  Kennewick  and Richland
 during the data collection periods of Davis etal. (1990)
 was  almost  nonexistent; there  was  no  recorded
 precipitation in Kennewick or Richland during the data
 collection period for Davis and Mirick (2006) (National
 Climatic Data Center, 2008).
         The key biokinetic model comparison study
 (Hogan et al., 1998) targeted three locations in more
 southerly latitudes (Pennsylvania, southern Illinois, and
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Chapter 5 - Ingestion of Soil and Dust
southern Kansas/Missouri) than the five tracer element
studies. The biokinetic model comparison methodology
had an advantage over the tracer element studies in that
the  study  represented  long-term   environmental
exposures over periods up to several years, that would
include a range of seasons and climate conditions.
        A brief review of the representativeness of the
key studies' samples with respect to gender and age
suggested that males and females were represented
roughly equally  in  those  studies for  which  study
subjects' gender was stated. Children up to age 8 years
were  studied  in seven  of the nine studies, with  an
emphasis on younger children. Wong (1988)/Calabrese
et al. (1993) and Vermeer and Frate (1979) are the only
studies with children 8 years or older.
        A brief review of the representativeness of the
key studies' samples  with  respect to  socioeconomic
status and racial/ethnic identity  suggested that there
were some discrepancies between the  study subjects
and the current U.S. population of children age 0 to <21
years.  The single survey response study (Vermeer and
Frate   (1979)) was  specifically  targeted  toward  a
predominantly rural black population in a particular
county in Mississippi.  The tracer element studies are of
predominantly white  populations, apparently  with
limited representation from other racial  and  ethnic
groups. The Amherst, Massachusetts study (Calabrese
et al. 1989/Barnes  1990) did not publish the  study
participants' socioeconomic status or racial and ethnic
identities.  The socioeconomic level of the Davis et al.
(1990) studied children was reported to be primarily of
middle to high income. Self-reported race and ethnicity
of relatives of the children studied (in most cases, they
were the parents  of the children studied) in Davis et al.
(1990) were White (86.5 percent), Asian (6.7 percent),
Hispanic (4.8 percent), Native American (1.0 percent),
and Other (1.0 percent), and the  91 married or living-
as-married respondents  identified their spouses  as
White (86.8 percent), Hispanic (7.7 percent), Asian (4.4
percent), and  Other (1.1 percent).  Davis and Mirick
(2006) did not state the race and ethnicity of the follow-
up study participants, who were a subset of the original
study participants from Davis et al. (1990). For the
Calabrese et al. (1997a) study in  Anaconda, Montana,
population demographics were not presented  in the
published article. The study sample appeared to have
been drawn from a door-to-door census of Anaconda
residents that identified 642 toilet trained children who
were less than 72 months of age.  Of the 414 children
participating in a companion study (out of the 642
eligible children identified), 271 had complete study
data for that companion study, and of these 271, 97.4
percent were identified as white and the remaining 2.6
percent were  identified as  native American, black,
Asian  and Hispanic (Hwang et al., 1997).   The 64
children in the Calabrese et al. (1997a) study apparently
were a stratified random sample drawn from the 642
children   identified  in the  door-to-door  census.
Presumably these children identified as  similar races
and  ethnicities to  the Hwang  et  al.  (1997)  study
children.  The Calabrese et al. (1997b) study indicated
that  11 of the 12 children studied were white.

5.5     SUMMARY   OF  SOIL  AND   DUST
        INGESTION ESTIMATES FROM KEY
        STUDIES
        Table  5-19 summarizes the soil and  dust
ingestion estimates from the 9 key studies. Forthe U.S.
tracer element studies,  in order to compare estimates
that were calculated in  a similar manner, the summary
is limited to estimates that use the same basic algorithm
of ((fecal and urine  tracer content)  -  (food and
medication  tracer  content))/(soil  or  dust  tracer
concentration).  Note  that several  of the published
reanalyses suggested  different  variations  on these
algorithms, or suggest adjustments that should be made
for various reasons.   However, because individual
observations were not available from the studies with
reanalyzed data, those  reanalyzed estimates were not
included  in the summary  table.   Other reanalyses
suggested that omitting some of the data according to
statistical criteria would be a worthwhile exercise. Due
to  the current  state of  the science regarding soil and
dust ingestion estimates, U.S. EPA does  not advise
omitting  an individual child's soil  or dust ingestion
estimate, based on statistical criteria, at this point in
time.
        There is a wide range of estimated soil and
dust ingestion across key studies. Note that some of the
soil-pica ingestion estimates from the tracer element
studies were consistent with the estimated mean soil
ingestion from the survey response study of geophagy
behavior.    Also  note that the  biokinetic  model
comparison methodology's  confirmation  of  central
tendency soil and dust ingestion default assumptions
corresponded  roughly  with some  of  the  central
tendency tracer element study estimates.
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                                                      	Chapter 5 - Ingestion of Soil and Dust
5.6
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        assessment in children.   Hum  Ecol Risk
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USDA. (2008)  Soil Survey Staff, Natural Resources
        Conservation  Service, United States
        Department of Agriculture, Web Soil Survey,
        accessed February 25, 2008.
U.S. DHHS (1981a) U.S. Department of Health and
        Human Services,  Public Health  Service,
        Centers for Disease Control, National Center
        for Health Statistics.  Public  Use Data Tape
        Documentation:   Medical   History
        Questionnaire, Ages  1-11,  Tape  Number
        4067.   National  Health  and   Nutrition
        Examination Survey, 1971-1975. May 1981.
        Hyattsville, MD.
U.S. DHHS (1981b) U.S. Department of Health and
        Human Services,  Public Health  Service,
        Centers for Disease Control, National Center
        for Health Statistics.  Public  Use Data Tape
        Documentation:   Medical   History
        Questionnaire, Ages  12-74,  Tape  Number
        4081.    National  Health  and  Nutrition
        Examination Survey,  1971-1975. May 1981.
        Hyattsville, MD.
U.S. DHHS (1985a) U.S. Department of Health and
        Human Services,  Public Health  Service,
        Centers for Disease Control, National Center
        for Health Statistics.  Public  Use Data Tape
        Documentation: Medical History 6 Months -
        11 Years,  Tape Number 5010.   National
        Health and Nutrition  Examination Survey,
        1976-1980. May 1985. Hyattsville, MD.
U.S. DHHS (1985b) U.S. Department of Health and
        Human Services,  Public Health  Service,
        Centers for Disease Control, National Center
        for Health Statistics.  Public  Use Data Tape
        Documentation: Medical History Ages 12-74
        Years, Tape Number 5020. National Health
        and  Nutrition Examination  Survey,  1976-
        1980. May 1985. Hyattsville, MD.
U.S. DOC (2008) U.S. Department  of Commerce,
        Bureau of the Census, Population Division.
        Table 2: Annual Estimates of the Population
        by Sex and  Selected Age Groups for the
        United States: April 1, 2000  to July 1, 2007
        (NC-EST2007-02).
U.S. EPA (1994a)  Guidance Manual  for the IEUBK
        Model for  Lead in Children.  Washington,
        DC:  U.S. Environmental Protection Agency,
        Office  of  Solid  Waste  and  Emergency
        Response. EPA 540/R-93/081.
U.S. EPA  (1994b) Technical  Support Document:
        Parameters  and  Equations   Used  in  the
        Integrated  Exposure  Uptake   Biokinetic
        (IEUBK) Model  for Lead in Children (v
        0.99d).  Washington,   D.C.:   U.S.
        Environmental Protection Agency, Technical
        Review Workgroup for Lead with assistance
        from   the  Environmental   Criteria   and
        Assessment Office, Research Triangle Park,
        NC.  EPA 9285.7-22.
U.S. EPA.  (1996) Soil Screening Guidance: User's
        Guide. Washington, DC: U.S. Environmental
        Protection Agency, Office of Solid Waste and
        Emergency Response. Publication 9355.4-23.
U.S. EPA.    (1997)  Exposure  Factors  Handbook
        Revised.     Washington,   DC:  U.S.
        Environmental Protection Agency, Office of
        Research and Development.   EPA/600/P-
        95/002F.
U.S. EPA. (2005) Guidance on selecting age groups for
        monitoring and assessing childhood exposures
        to environmental contaminants. Washington,
        DC.: U.S. Environmental Protection Agency,
        Office  of  Research  and  Development.
        EPA/630/P-03/003F.
Van Dyck, K.; Robberecht, H.; Van Cauwenburgh, R.;
        Van   Vlaslaer,  V.; Deelstra,  H.   (2000)
        Indication of  silicon essentiality in humans:
        serum concentrations in Belgian children and
        adults, including pregnant women. Biol Trace
        ElemRes 77(l):25-32.
Van W'ijnen, J.H.; Clausing, P.; Brunekreff, B.  (1990)
        Estimated soil ingestion by children. Environ
        Res 51:147-162.
Vermeer, D.E.; Frate, D.A. (1979) Geophagia in rural
        Mississippi:    environmental and  cultural
        contexts and nutritional implications.  Am J
        ClinNutr 32:2129-2135.
Von Lindern,  I.;  Spalinger, S.;  Petroysan,  V.;  von
        Braun,   M.   (2003)  Assessing  remedial
        effectiveness through the blood lead:soil/dust
        lead relationship at the Bunker Hill Superfund
        Site in the Silver Valley of Idaho.  Sci Total
        Environ 303(1-2): 139-170.
Wilson,  M.J.   Clay  Mineralogical and  Related
        Characteristics  of Geophagic Materials.
        (2003) JChemEcol29(7):1525-1547.
Child-Specific Exposure Factors Handbook
September 2008	
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                                           5-29

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                                                   Child-Specific Exposure Factors Handbook

                                                  	Chapter 5 - Ingestion of Soil and Dust
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. J Exp
        Anal Environ Epidem 10:509-517.
Wong, M.S. (1988) The Role of Environmental and
        Host  Behavioural Factors in  Determining
        Exposure  to   Infection  with  Ascaris
        lumbricoldes and Trichuris trichiura.  Ph.D.
        Thesis,  Faculty  of  Natural  Sciences,
        University of the West Indies. 1988.
Page
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Chapter 5 - Ingestion of Soil and Dust

Table 5-3. Soil, Dust and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study Children

Tracer Element
Aluminum
soil
dust
soil/dust
combined
Barium
soil
dust
soil/dust
combined
Manganese
soil
dust
soil/dust
combined
Silicon
soil
dust
soil/dust
combined
Vanadium
soil
dust
soil/Must
combined
Yttrium
soil
dust
soil/dust
combined
Zirconium
soil
dust
soil/dust
combined
Titanium
soil
dust
soil/dust
combined
SD = Standard devi
Source: Calabrese et al.,

N

64
64
64


64
64
64


64
64
64


64
64
64


62
64
62


62
64
62


62
64
62


64
64
64

ation.
1989.
Ingestion (mg/day)
Mean

153
317
154


32
31
29


-294
-1,289
-496


154
964
483


459
453
456


85
62
65


21
27
23


218
163
170



Median

29
31
30


-37
-18
-19


-261
-340
-340


40
49
49


96
127
123


9
15
11


16
12
11


55
28
30



SD

852
1,272
629


1,002
860
868


1,266
9,087
1,974


693
6,848
3,105


1,037
1,005
1,013


890
687
717


209
133
138


1,150
659
691



95th Percentile

223
506
478


283
337
331


788
2,916
3,174


276
692
653


1,903
1,918
1,783


106
169
159


110
160
159


1,432
1,266
1,059



Maximum

6,837
8,462
4,929


6,773
5,480
5,626


7,281
20,575
4,189


5,549
54,870
24,900


5,676
6,782
6,736


6,736
5,096
5,269


1,391
789
838


6,707
3,354
3,597



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                                          Child-Specific Exposure Factors Handbook

                                          	Chapter 5 - Ingestion of Soil and Dust
Table 5-4. Amherst,
Tracer
element

Al
Ba
Mn
Si
Ti
V
Y
Zr
Massachusetts Soil-Pica Child's Daily


Week
74
458
2,221
142
1,543
1,269
147
86
Ingestion Estimates by Tracer and by Week (mg/day)
Estimated Soil Ingestion (mg/day)

1 Week 2
13,600
12,088
12,341
10,955
11,870
10,071
13,325
2,695
Source: Calabrese et al., 1991.
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5-32	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 5 - Ingestion of Soil and Dust
Table 5-5. Amherst, Massachusetts Soil-Pica Child's Tracer Ratios


Tracer Pairs
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Source:
Mn/Ti
Ba/Ti
Si/Ti
V/Ti
Ai/Ti
Y/Ti
Mn/Y
Ba/Y
Si/Y
V/Y
Al/Y
Mn/Al
Ba/Al
Si/Al
V/A1
Si/V
Mn/Si
Ba/Si
Mn/Ba
Calabrese and St

Soil
208.368
187.448
148.117
14.603
18.410
8.577
24.293
21.854
17.268
1.702
2.146
11.318
10.182
8.045
0.793
10.143
1.407
1.266
1.112
mek, 1992.
Ratio
Fecal
215.241
206.191
136.662
10.261
21.087
9.621
22.373
21.432
14.205
1.067
2.192
10.207
9.778
6.481
0.487
13.318
1.575
1.509
1.044


Dust
260.126
115.837
7.490
17.887
13.326
5.669
45.882
20.432
1.321
3.155
2.351
19.520
8.692
0.562
1.342
0.419
34.732
15.466
2.246

Estimated Residual Fecal
Tracers of Soil Origin as
Predicted by Specific
Tracer Ratios (%)
87
100
92
100
100
100
100
71
81
100
88
100
73
81
100
100
99
83
100

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                                          Child-Specific Exposure Factors Handbook

                                          	Chapter 5 - Ingestion of Soil and Dust
Table 5-6. Van W'ijnen et al
., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for
Daycare Centers
Age (years) Sex


Birth to <1

1 to <2

2 to <3

3 to <4

4 to <5

All girls
All boys
Total


Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys




N

3
1
20
17
34
17
26
29
1
4
86
72
162"
" Age and/or sex not registered for 8 children
b
N
GM
LTM
GSD
NA
Source:
Age not registered for 7 ch
- Number of subjects.
- Geometric mean.
- Limiting tracer method.
GM LTM

(mg/day)
81
75
124
114
118
96
111
110
180
99
117
104
111
one untransformec
ildren; geometric mean LTM value -






GSD LTM

(mg/day)
1.09
-
1.87
1.47
1.74
1.53
1.57
1.32
_
1.62
1.70
1.46
1.60
value - 0.
140.




N

NA
NA
3
5
4
8
6
8
19
18
36
42
78"





Sample of Dutch Children
Campgrounds
GM LTM

(mg/day)
NA
NA
207
312
367
232
164
148
164
136
179
169
174






GSD LTM

(mg/day)
NA
NA
1.99
2.58
2.44
2.15
1.27
1.42
1.48
1.30
1.67
1.79
1.73





- Geometric standard deviation.
- Not available.
Adapted from Van W'ijnen

et al., 1990.










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Child-Specific Exposure Factors Handbook

Chapter 5 - Ingestion of Soil and Dust

Table 5-7. Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period

Weather Category

Bad
(>4 days/week
precipitation)

Reasonable
(2-3 days/week
precipitation)


Good
(<2 days/week
precipitation)




Age (years)

<1
1 to <2
2 to <3
4 to <5
<1
1 to <2
2 to <3
3 to <4
4 to <5
<1
1 to <2
2 to <3
3 to <4
4 to <5
First Sampling Period
Estimated
Geometric Mean
N
LTM Value
(mg/day)
3 94
18 103
33 109
5 124





4 102
42 229
65 166
67 138
10 132
Second Sampling Period
Estimated
Geometric Mean
N
LTM Value
(mg/day)
3 67
33 80
48 91
6 109
1 61
10 96
13 99
19 94
1 61





N - Number of subjects.
LTM - Limiting tracer method.
Source: Van Wi'inen
etal., 1990.



Table 5-1
Mean
Element
(mg/day)
Aluminum
Silicon
Titanium
Minimum
Maximum
b
Source:
38.9
82.4
245.5
38.9
245.5
Excludes three children who
Negative values occurred as
published as 279.0 mg/day in
. Estimated Soil Ingestion for Sample of Washington State Children a
Standard Error of the
Median Range
(mg/day) (mg/day)b
(mg/day)
25.3 14.4 -279.0 to 904.5
59.4 12.2 -404.0 to 534.6
81.3 119.7 -5,820.8 to 6,182.2
25.3 12.2 -5,820.8
81.3 119.7 6,182.2
did not provide any samples (N=101).
i result of correction for non-soil sources of the tracer elements. For aluminum, lower end of range
article appears to be a typographical error that omitted the negative sign.
Adapted from Davis et al., 1990.
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September 2008	
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 5-35

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                                          Child-Specific Exposure Factors Handbook

                                          	Chapter 5 - Ingestion of Soil and Dust

Tracer
Al
Ce
La
Nd
Si
Ti
Y
Zr
P
SD
Note:
Source:
Table 5-9. Soil Ingestion Estimates for 64 Anaconda
Estimated Soil Ingestion (mg/da
PI P50 P75 P90 P95
-202.8 -3.3 17.7 66.6 94.3
-219.8 44.9 164.6 424.7 455.8
-10,673 84.5 247.9 460.8 639.0
-387.2 220.1 410.5 812.6 875.2
-128.8 -18.2 1.4 36.9 68.9
-15,736 11.9 398.2 1,237.9 1,377.8
-441.3 32.1 85.0 200.6 242.6
-298.3 -30.8 17.7 94.6 122.8
- Percentile.
- Standard deviation.
Negative values are a result of limitations in the methodology.
Calabrese et al., 1997a.
Children
y)
Max Mean SD
461.1 2.7 95.8
862.2 116.9 186.1
1,089.7 8.6 1,377.2
993.5 269.6 304.8
262.3 -16.5 57.3
4,066.6 -544.4 2,509.0
299.3 42.3 113.7
376.1 -19.6 92.5


Table 5-10. Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior (mg/day)
Study day
1
2
3
4
5
6
7
Al-based estimate
53
7,253
2,755
725
5
1,452
238
Si-based estimate
9
2,704
1,841
573
12
1,393
92
Ti-based estimate
153
5,437
2,007
801
21
794
84
Source: Calabrese et al., 1997b.
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Child-Specific Exposure Factors Handbook

Chapter 5 - Ingestion of Soil and Dust
                        Table 5-11. Soil Ingestion Estimates for Sample of 12 Washington State Children a

                                                       Estimated Soil Ingestion b
      T     r-i    »                                             (mg/day)
      Tracer Element     	      	
                               Mean                Median                  SD                 Maximum
Aluminum
Silicon
Titanium
36.7
38.1
206.9
33.3
26.4
46.7
35.4
31.4
277.5
107.9
95.0
808.3
  a        For some study participants, estimated soil ingestion resulted in a negative value. These estimates have been set to zero mg/day for
          tabulation and analysis.
  b        Results based on 12 children with complete food, excreta and soil data.
  SD      = Standard deviation.

  Source:   Davis and Mirick, 2006.
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                                                     Child-Specific Exposure Factors Handbook

                                                    	Chapter 5 - Ingestion of Soil and Dust
                      Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children
               Child                             Month                    Estimated soil ingestion (mg/day)
                11                                 1                                55
                                                  2                               1,447
                                                  3                                22
                                                  4                                40

                12                                 1                                 0
                                                  2                                 0
                                                  3                               7,924
                                                  4                                192

                14                                 1                               1,016
                                                  2                                464
                                                  3                               2,690
                                                  4                                898

                18                                 1                                30
                                                  2                               10,343
                                                  3                               4,222
                                                  4                               1,404

                22                                 1                                 0
                                                  2
                                                  3                               5,341
                                                  4                                 0

                27                                 1                               48,314
                                                  2                               60,692
                                                  3                               51,422
                                                  4                               3,782
         - No data.

 Source:   Calabrese and Stanek, 1993.
Page                                                 Child-Specific Exposure Factors Handbook
5-38	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 5 - Ingestion of Soil and Dust


Estimation
Method
Aluminum
Silicon
Titanium
Minimum
Source: Binder et al.
Table 5
Mean
(mg/day)
181
184
1,834
108
1986.
13. Estimated Daily
Median
(mg/day)
121
136
618
88

Soil Ingestion for East Helena, Montana Children
Standard
Deviation
(mg/day)
203
175
3,091
121

Range
(mg/day)
25-1,324
31-799
4-17,076
4-708

95th Percentile
(mg/day)
584
578
9,590
386

Geometric Mean
(mg/day)
128
130
401
65

Table 5-14. Estimated Soil Ingestion for Sample of Dutch Nursery

Child
1


2


3

4

5

6

7

8
9
10
11
12
13
14
15
16
17
18
Arithmetic Mean
- No data.
Source: Adapted from

Sample
Number
L3
L14
L25
L5
L13
L27
L2
L17
L4
Lll
L8
L21
L12
L16
L18
L22
LI
L6
L7
L9
L10
L15
L19
L20
L23
L24
L26


Clausing et al., 1987.

Soil Ingestion as
Calculated from Ti
(mg/day)
103
154
130
131
184
142
124
670
246
2,990
293
313
1,110
176
11,620
11,320
3,060
624
600
133
354
2,400
124
269
1,130
64
184
1,431



Soil Ingestion as
Calculated from Al
(mg/day)
300
211
23
_
103
81
42
566
62
65
_
-
693
-
_
77
82
979
200
-
195
-
71
212
51
566
56
232


School Children
Soil Ingestion as
Calculated from
AIR
(mg/day)
107
172
-
71
82
84
84
174
145
139
108
152
362
145
120
-
96
111
124
95
106
48
93
274
84
-
-
129




Limiting Tracer
(mg/day)
103
154
23
71
82
81
42
174
62
65
108
152
362
145
120
77
82
111
124
95
106
48
71
212
51
64
56
105


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                                          Child-Specific Exposure Factors Handbook

                                          	Chapter 5 - Ingestion of Soil and Dust

Child
1

2
3

4
5
6
Arithmetic Mean
Source: Adapted
Table 5-15. Estimated
Sample
G5
G6
Gl
G2
G8
G3
G4
G7

from Clausing et al., 1987.
Soil Ingestion for Sample of Dutch
Soil Ingestion as
Calculated from Ti
(mg/day)
3,290
4,790
28
6,570
2,480
28
1,100
58
2,293

Hospitalized, Bedridden Children
Soil Ingestion as
Calculated from Al
(mg/day)
57
71
26
94
57
77
30
38
56


Limiting Tracer
(mg/day)
57
71
26
84
57
28
30
38
49

Table 5-16. Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989) Study:
Effect on Mean Soil Ingestion Estimate (mg/day)a
Tracer
Aluminum
Silicon
Titanium
Vanadium
Yttrium
Zirconium


Lack of Fecal
Sample on .
Other Causes
Final Study
Day
14
15
82
66
8
6
11
6
187
55
26
91

Total
Negative
Error
25
21
269
121
34
97
Negative Error
Total Positive
Error
43
41
282
432
22
5

Net Error
+ 18
+20
+ 13
+311
-12
-92
a How to read table: for example, aluminum as a soil tracer displayed both negative and positive error
negative error is estimated to bias the mean estimate by 25 mg/day downward. However, aluminum
original mean upward by 43 mg/day. The net bias in the original mean was 1 8 mg/day positive bias
mg/day mean for aluminum should be corrected downward to 136 mg/day.
b Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
Source:
Calabrese and Stanek, 1995





Original
Mean
153
154
218
459
85
21

Adjusted
Mean
136
133
208
148
97
113
The cumulative total
has positive error biasing the
Thus, the original 156


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 Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook
Chapter 5 - Ingestion of Soil and Dust
              Table 5-17. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children (mg/day)
    Type of Estimate
                          Overall
                                        Al
                                                    Ba
                                                              Mn
                                                                                     Ti
                                                                                                V
                                                                                                          Y
                                                                                                                    Zr
   Number of Samples
                            64
                                        64
                                                    33
                                                               19
                                                                         63
                                                                                    56
                                                                                                          61
                                                                                                                    62
  Mean
  25th Percentile
  50th Percentile
  75th Percentile
  90th Percentile
  95th Percentile
  Maximum
 179
 10
 45
 88
 186
 208
7,703
122
 10
 19
 73
131
254
 655
  28
  65
 260
 470
 518
17,991
 1,053
  35
 121
 319
 478
17,374
17,374
 139
  5
 32
 94
 206
 224
4,975
 271
  8
  31
  93
 154
 279
12,055
112
 8
47
177
340
398
845
 165
  0
 15
 47
 105
 144
8,976
23
 0
15
41
87
117
208
  a         For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then  evaluated for each
           child. The values in the column "overall" correspond to percentiles of the distribution of these means over the 64 children. When
           specific trace elements were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the
           specific trace element were formed for 108 days for each subject. The mean soil ingestion estimate was again evaluated. The
           distribution of these means for specific trace elements is shown.

  Source:   Stanek and Calabrese, 1995a.
                             Table 5-18. Estimated Distribution of Individual Mean Daily Soil Ingestion
                                      Based on Data for 64 Subjects Projected over 365 Daysa
                Range

                50th Percentile (median)

                90th Percentile

                95th Percentile
                                                     1 - 2,268 mg/db

                                                        75 mg/d

                                                       1,190 mg/d

                                                       1,751 mg/d
                a         Based on fitting a log-normal distribution to model daily soil ingestion values.
                b         Subject with pica excluded.

                Source:   Stanek and Calabrese, 1995a.
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                                          	Chapter 5 - Ingestion of Soil and Dust
Table 5- 19. Summary of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from Key Studies (mg
Sample Age Ingestion Mean P25 P50 P75 P90 P95
Size (years) medium
292 0.1-<1 Soil Oto30" NR NR NR NR NR
1 - <5 Soil 0 to 200" NR NR NR <300 NR
101 2-<8 Soil 39 to 246 NR 25 to 81 NR NR NR
Soil and Dust 65 to 268 NR 52 to 117 NR NR NR
64 l-<4 Soil -294to+459 NR -261 to +96 NR 67 to 1,366 106 to 1,903
Dust -l,289to+964 NR -340 to +127 NR 91 to 1,700 160 to 2,916
SoilandDust -496to+483 NR -340 to +456 NR 89 to 1,701 159to3,174
12 3-<8 Soil 37 to 207 NR 26 to 47 NR NR NR
64 l-<4 Soil -544to+270 -582 - +65 -31to+220 Ito411 37 to 1,238 69 to 1,378
478 <1 - <7 SoilandDust 113 NR NR NR NR NR
140 1-13+ Soil 50,000" NR NR NR NR NR
52 0.3 - 14 Soil NR NR NR NR -1,267 -4,000
/day)
Reference
Van Wijnen et
al., 1990
Davis et al.,
1990
Calabrese et al.,
1989
Davis and
Mirick, 2006
Calabrese et al.,
1997a
Hogan et al.,
1998
Vermeer and
Frate, 1979
Wong
(1988)/Calabres
e and Stanek
(1993)
a Geometric mean.
b Average includes adults and children.
NR = Not reported.
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Chapter 12 - Intake of Grain Products	
                                   TABLE OF CONTENTS

12     INTAKE OF GRAIN PRODUCTS	12-1
       12.1    INTRODUCTION	12-1
       12.2    RECOMMENDATIONS	12-2
       12.3    INTAKE STUDIES	12-6
              12.3.1   Key Grain Intake Study  	12-6
                     12.3.1.1    U.S. EPA Analysis of CSFII 1994-96, 1998  	12-6
              12.3.2   Relevant Grain Intake Studies	12-7
                     12.3.2.1    USDA, 1999  	12-7
                     12.3.2.2    Smiciklas-Wright et al, 2002  	12-8
                     12.3.2.3    Fox et al., 2004  	12-8
                     12.3.2.4    Ponza et al., 2004 	12-9
                     12.3.2.5    Mennella et al., 2006	12-9
                     12.3.2.6    Fox et al., 2006  	12-10
       12.4    CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES	12-10
       12.5    REFERENCES FOR CHAPTER 12	12-10

APPENDIX 12A	  12A-1
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                                                     	Chapter 12 - Intake of Grain Products
                                         LIST OF TABLES

Table 12-1.     Recommended Values for Intake of Grains, As Consumed	12-3
Table 12-2.     Confidence in Recommendations for Intake of Grain Products	12-4
Table 12-3.     Per Capita Intake of Total Grains (g/kg-day as consumed)	12-12
Table 12-4.     Consumer Only Intake of Total Grains (g/kg-day as consumed)	12-12
Table 12-5.     Per Capita Intake of Individual Grain Products (g/kg-day as consumed) 	12-13
Table 12-6.     Consumer Only Intake of Individual Grain Products (g/kg-day as consumed)  	12-13
Table 12-7.     Mean Quantities of Grain Products Consumed Daily by Sex and Age, Per Capita (g/day) ... 12-14
Table 12-8.     Percentage of Individuals Consuming Grain Products, by Sex and Age (%)	12-15
Table 12-9.     Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and
               Percentage of Individuals Using These Foods in Two Days	12-16
Table 12-10.    Characteristics of the FITS Sample Population	12-17
Table 12-11.    Percentage of Infants and Toddlers Consuming Different Types of Grain Products	12-18
Table 12-12.    Characteristics of WIC Participants and Nonparticipants (Percentages)	12-19
Table 12-13.    Food Choices for Infants and Toddlers by WIC Participation Status  	12-20
Table 12-14.    Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
               Types of Grain Products on A Given Day	12-21
Table 12-15.    Average Portion Sizes Per Eating Occasion of Grain Products  Commonly Consumed
               by Infants from the 2002 Feeding Infants and Toddlers Study  	12-22
Table 12-16.    Average Portion Sizes Per Eating Occasion of Grain Products  Commonly Consumed
               by Toddlers from the 2002 Feeding Infants and Toddlers Study	12-22
Table 12-17.    Mean Moisture Content of Selected Grain Products Expressed as Percentages
               of Edible Portions  	12-23
Table 12A-1.    Food Codes and Definitions Used in Analysis of the 1994-96,  1998 USDA CSFII Data . . .   12A-2
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Chapter 12 - Intake of Grain Products	
12      INTAKE OF GRAIN PRODUCTS
12.1    INTRODUCTION
        The  American  food supply  is  generally
considered to be  one  of the safest in the  world.
Nevertheless, grain products may become contaminated
with toxic chemicals by  several  different pathways.
Ambient air pollutants may be deposited on or absorbed
by the plants, or dissolved in rainfall  or irrigation
waters that contact the plants.  Pollutants may also be
absorbed through plant roots from contaminated soil
and ground water.  The  addition of pesticides, soil
additives,   and   fertilizers  may   also  result   in
contamination of grain products.  To assess exposure
through this pathway, information on  ingestion rates of
grain products are needed.
        Children's exposure from contaminated foods
may differ from that of adults because of differences in
the type and amounts of food eaten.   Also, for many
foods, the intake per unit body weight is  greater for
children than for adults.  Common grain products eaten
by children include milled rice, oats, and wheat flour
(Goldman, 1995).
        A variety of terms may be used to define
intake of grain products (e.g., consumer-only intake, per
capita intake, total grain intake, as-consumed  intake,
dry weight intake). As described  in Chapter 9, Intake
of Fruits  and Vegetables,  consumer-only intake  is
defined as the quantity of grain products consumed by
children during the survey period.   These  data  are
generated by averaging intake across  only the children
in the survey who consumed  these food items.  Per
capita  intake rates  are  generated by  averaging
consumer-only intakes over the entire population  of
children  (including those children  that reported no
intake).    In  general,  per capita intake  rates  are
appropriate for use in exposure assessment for which
average dose estimates  for children are  of interest
because they represent both children who ate the foods
during the survey period and children who may eat the
food items at some time, but did not consume them
during the survey period.  Per capita  intake, therefore,
represents an average across the  entire population of
interest, but does so at the expense of underestimating
consumption  for  the subset of  the population  that
consumed the food in question.   Total grain intake
refers to the sum of all grain products consumed in a
day.
        Intake rates may be expressed on the basis of
the as-consumed weight (e.g., cooked or prepared) or
on the uncooked or unprepared weight. As-consumed
intake rates are based on the weight of the food in the
form that it  is  consumed  and should be used in
assessments where the  basis for the contaminant
concentrations in foods is  also indexed  to the  as-
consumed weight. The food ingestion values provided
in this  chapter are expressed as as-consumed intake
rates because this is the fashion in which data were
reported by survey respondents. This is of importance
because concentration data to be used in  the dose
equation are often measured in uncooked food samples.
It should be recognized that cooking can either increase
or decrease food  weight.   Similarly,  cooking can
increase the mass of contaminant in food (due to
formation reactions, or absorption from cooking oils or
water) or decrease the mass of contaminant in food (due
to vaporization, fat loss or leaching).  The  combined
effects of changes in weight and changes in contaminant
mass can result in either an increase or decrease in
contaminant concentration in cooked food.  Therefore,
if the as-consumed ingestion rate  and the  uncooked
concentration are used in the dose equation, dose may
be under-estimated or over-estimated.  Ideally, after-
cooking food concentrations should be combined with
the as-consumed intake rates.  In the absence of data, it
is reasonable to  assume that no change in contaminant
concentration occurs after cooking. It is important for
the assessor to be  aware of these  issues and choose
intake rate data that best match the concentration data
that are being used. For more information on cooking
losses and conversions necessary to account for such
losses,  the  reader  is referred to Chapter 13 of this
handbook.
        Sometimes contaminant concentrations in food
are reported on a dry weight basis. When these data are
used in an exposure assessment, it is recommended that
dry-weight intake rates also be used. Dry-weight food
concentrations and intake rates are based on the weight
of the food consumed after the moisture content has
been removed.   For information  on converting  the
intake rates presented in this chapter to dry weight
intake rates, the reader is referred to Section  12.4.
        The   purpose   of   this  chapter   is  to
provide intake data for grain products among children.
The  recommendations for ingestion rates  of grain
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                                                      	Chapter 12 - Intake of Grain Products
products are provided in the next section, along with a
summary  of  the   confidence  ratings  for  these
recommendations. The recommended values are based
on the key study identified by U. S. EPA for this factor.
Following the recommendations,  the key study on
ingestion of grain products is summarized. Relevant
data on ingestion of grain products are also provided.
These data are presented to provide the reader with
added perspective on the current  state-of-knowledge
pertaining to  ingestion  of grain products among
children.

12.2    RECOMMENDATIONS
        Tables  12-1  presents a  summary of  the
recommended values for per capita and consumers-only
intake of grain products, on an as  consumed basis.
Confidence   ratings   for  the   grain  intake
recommendations for general population children are
provided in Table 12-2.
        The U.S. EPA analysis of data from the 1994-
96 and 1998 Continuing Survey of Food Intake among
Individuals (CSFII) was used in selecting recommended
intake rates for general population  children. The U. S.
EPA analysis was  conducted  using age groups that
differed slightly from U.S.  EPA's  Guidance  on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).  However, for the purposes of the
recommendations presented here, data were placed in
the standardized age categories closest to those used in
the analysis.   Also,  the CSFII data on which  the
recommendations are based are short-term survey data
and  may   not   necessarily  reflect  the  long-term
distribution of average daily intake rates. However, for
broad categories of food (i.e., total grains),  because
they are eaten on a daily basis throughout the year with
minimal seasonality, the short term distribution may be
a  reasonable   approximation of   the   long-term
distribution,  although  it  will  display   somewhat
increased  variability.  This implies that  the upper
percentiles shown here will tend to  overestimate the
corresponding  percentiles  of the   true  long-term
distribution.  It should also be noted that because these
recommendations are  based  on 1994-96  and 1998
CSFII  data, they may not reflect  the most recent
changes that may have occurred  in  consumption
patterns. More current data from the National Health
 and Nutrition Survey (NHANES) will be incorporated
 as the data become available and are analyzed.
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Table 12-1 . Recommended Values for Intake of Grains, As Consumed*
Per Capita Consumers Only
Age Group
Mean
g/kg-day
95th Percentile Mean
g/kg-day g/kg-day
95th Percentile percentiles
g/kg-day
Source
Total Grains
Birth to 1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to <1 1 years
11 to <16 years
16 to <21 years

2.5
6.4
6.4
6.3
4.3
2.5
2.5

8.6 3.6
12 6.4
12 6.4
12 6.3
8.2 4.3
5.1 2.5
5.1 2.5
Individual Grain Products - See Tables
9.2
12
12
12 See Tables
„ 2 12-3 and
12-4
5.1
5.1
12-5 and 12-6


U.S. EPA
Analysis of
CSFII,
1994-96 and
1998.



1 Analysis was conducted using slightly different age groups than those recommended in Guidance on Selecting Age
Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA. 2005).
Data were placed in the standardized age categories closest to those used in the analysis.
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                                           	Chapter 12 - Intake of Grain Products
Table 12-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Minimal Uncertainty
Confidence in Recommendations for Intake of Grain Products
Rationale
The survey methodology and data analysis was
adequate. The survey sampled more than 1 1,000
individuals up to age 18 years. An analysis of primary
data was conducted.
No physical measurements were taken. The method
relied on recent recall of grain products eaten.
The key study was directly relevant to grain intake.
The data were demographically representative of the
U.S. population (based on stratified random sample).
Data were collected between 1994 and 1998.
Data were collected for two non-consecutive days.
The CSFII data are publicly available.
The methodology used was clearly described; enough
information was included to reproduce the results.
Quality assurance of the CSFII data was good; quality
control of the secondary data analysis was not well
described.
Full distributions were provided for total grains.
Means were provided for individual grain products.
Data collection was based on recall for a 2-day period;
the accuracy of using these data to estimate long-term
intake (especially at the upper percentiles) is uncertain.
However, use of short-term data to estimate chronic
ingestion can be assumed for broad categories of foods
such as total grains. Uncertainty is likely to be greater
for individual grain products.

Rating
High
Medium
High
Medium
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Chapter 12 - Intake of Grain Products

Table 12-2. Confidence in Recommendations for Intake of Grain Products (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The USDA CSFII survey received a high level of peer
review. The U.S. EPA analysis of these data has not
been peer reviewed outside the Agency.
There was 1 key study.
Rating
Medium
High confidence in the
averages;
Low confidence in the
long-term upper
percentiles
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                                                       	Chapter 12 - Intake of Grain Products
12.3    INTAKE STUDIES
        The primary source of recent information on
consumption rates of grain products among children is
the U.S. Department of Agriculture's (USDA) CSFII.
Data from the 1994-96 CSFII and the 1998 Children's
supplement to the 1994-96 CSFII have been used in
various studies to generate children's consumer-only
and per capita intake rates for both individual grain
products  and total grains.  The  CSFII is a series of
surveys designed to measure the kinds and amounts of
foods eaten by Americans.  The CSFII 1994-96 was
conducted between January 1994 and January 1997
with  a  target  population  of  non-institutionalized
individuals in all 50 states and Washington, D.C.  In
each of the 3 survey years, data  were collected for a
nationally representative sample of  individuals of all
ages.   The CSFII  1998  was  conducted between
December 1997  and December 1998 and surveyed
children 9 years of age and younger.  It used the same
sample design as the CSFII 1994-96  and was intended
to be merged  with  CSFII 1994-96 to increase the
sample size  for  children.  The  merged surveys are
designated as  CSFII  1994-96,  1998.   Additional
information  on  these surveys can  be  obtained at
littp://w\\-\v.ars.usda.sov/Services/docs. htm ?docid=14531.
        The CSFII  1994-96,  1998  collected  dietary
intake data through in-person interviews on  2  non-
consecutive days.  The data were based  on 24-hour
recall. A total of 21,662 individuals provided data for
the first day; of those individuals, 20,607 provided data
for a second day. Over 11,000 of the sample persons
represented children up to 18 years of age.  The 2-day
response   rate   for  the  1994-1996  CSFII  was
approximately 76 percent. The 2-day response rate for
CSFII 1998 was 82 percent.
        The CSFII 1994-96,98 surveys were based on
a complex multistage area probability sample  design.
The sampling frame was organized using 1990  U.S.
population census estimates, and the  stratification plan
took into account  geographic  location,  degree  of
urbanization,   and  socioeconomic   characteristics.
Several sets of sampling weights are available  for use
with the intake data. By using appropriate weights, data
for all fours years of the surveys can be  combined.
USDA recommends that all 4 years be combined in
order to provide an adequate sample size for children.
 12.3.1      Key Grain Intake Study
 12.3.1.1    U.S. EPA Analysis of CSFII 1994-96,
            1998
            For many years, the U.S. EPA's Office of
 Pesticide Programs (OPP) has used food consumption
 data collected by the U.S. Department of Agriculture
 (USDA) for its dietary risk assessments. Most recently,
 OPP,  in  cooperation  with USDA's  Agricultural
 Research Service (ARS), used data from the 1994-96,
 1998 CSFII to develop the Food Commodity Intake
 Database (FCID).  CSFII data on the foods people
 reported eating were converted to  the quantities of
 agricultural   commodities  eaten.     "Agricultural
 commodity" is a term used by U. S. EPA to mean plant
 (or animal) parts consumed by humans as food; when
 such items are raw or unprocessed, they are referred to
 as "raw agricultural commodities."  For example, an
 apple pie may contain the commodities apples, flour,
 fat, sugar and spices. FCID contains approximately 553
 unique commodity names and 8-digit codes. The FCID
 commodity names and codes were selected and defined
 by U.S. EPA and were based on the U.S. EPA Food
 Commodity   Vocabulary
 (httgV/www^epa.gov/pesticides^oodfegd/).
            The grain items/groups selected for the
 U.S. EPA analysis included total grains, and individual
 grain products such as cereal and rice. Appendix 12A
 presents the  food codes and  definitions used  to
 determine  the various  grain products used  in the
 analysis.   Intake rates  for these food items/groups
 represent intake of all forms of the product (e.g., both
 home produced and commercially produced). Children
 who provided data for two days of the survey were
 included in the intake estimates. Individuals who did
 not provide information on body weight or for whom
 identifying information was unavailable were excluded
 from the analysis.  Two-day average intake rates were
 calculated for all individuals in the database for each of
 the food items/groups. These average daily intake rates
 were divided by each individual's reported body weight
 to generate intake rates in units of grams per kilogram
 of body weight per day (g/kg-day).  The data were
 weighted according to the four-year, two-day  sample
 weights provided in the 1994-96,1998 CSFII to adjust
 the data for the sample population to reflect the national
 population.
            Summary statistics were generated on both
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Chapter 12 - Intake of Grain Products	
a per capita and a consumer only basis. For per capita
intake, both users and non-users of the food item were
included in the analysis.  Consumer-only intake rates
were calculated using data for only those individuals
who ate  the food item of interest during the survey
period.  Intake data from the  CSFII are based on as-
consumed (i.e., cooked or prepared) forms of the food
items/groups. Summary statistics, including: number of
observations, percentage of the population consuming
the grain product being analyzed, mean intake rate, and
standard error of the mean intake rate were calculated
for total grains and selected individual grain products.
Percentiles of the intake rate distribution (i.e., 1st, 5th,
10th,  25th, 50th, 75th,  90th, 95th,  99th, and  100th
percentile were also  provided for total grains.  Data
were provided for the following age groups of children:
birth to <1 year, 1 to  <2 years, 3 to <5 years, 6 to <12
years, and 13 to <19 years. Because these data were
developed for use in U.S. EPA's pesticide registration
program, the age groups used are slightly different than
those recommended in U.S.  EPA's Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).
           Tables  12-3 presents  as-consumed  per
capita  intake  data for total grains  in  g/kg-day; as-
consumed consumer only intake data for total grains in
g/kg-day are provided in Table 12-4.  Table  12-5
provides per capita  intake data for individual grain
products and Table 12-6 provides consumer only intake
data for individual grain products.
           It should be noted that the distribution of
average daily  intake  rates generated using short-term
data (e.g., 2-day) do not necessarily reflect the long-
term distribution of average daily intake rates.  The
distributions generated from short-term and long-term
data will differ to the extent that each individual's
intake varies from day to day;  the distributions will be
similar  to the extent that individuals' intakes  are
constant from day  to  day.   However, for  broad
categories of foods (e.g., total  grains) that are eaten on
a  daily  basis throughout the year, the short-term
distribution may be a reasonable approximation of the
true  long-term distribution,  although  it will  show
somewhat  more  variability.    In  this   chapter,
distributions  are provided  only  for  total  grains.
Because of the increased variability of the short-term
distribution, the short-term upper percentiles shown
here may overestimate the corresponding percentiles of
the long-term distribution.  For individual grains, only
the mean, standard error, and percent consuming are
provided.
           The strengths of U.S. EPA's analysis are
that it provides distributions of intake rates for various
age groups of children, normalized by  body weight.
The analysis  uses the 1994-96, 1998 CSFII data set
which was designed to be representative of the U.S.
population. The data set includes four years of intake
data combined,  and  is based on a two-day survey
period.  As discussed above, short-term dietary data
may not accurately reflect long-term eating patterns and
may under-represent infrequent consumers of a given
food.  This is particularly true for the tails (extremes)
of the distribution of food intake.  Also, the analysis
was conducted using slightly different age groups that
those  recommended  in U.S.  EPA's  Guidance on
Selecting Age Groups for Monitoring and Assessing
Childhood Exposures to Environmental Contaminants
(U.S. EPA, 2005).  However, given the  similarities in
the age groups used, the data should provide suitable
intake estimates for the age groups of interest.

12.3.2     Relevant Grain Intake Studies
12.3.2.1    USDA, 1999-Food and Nutrient Intakes
           by Children 1994-96,1998, Table Set 17
           USDA   (1999)   calculated   national
probability estimates of food and nutrient intake by
children based on all 4 years of the CSFII (1994-96 and
1998) for children age 9 years and under, and on CSFII
1994-96 only for individuals age 10 years and over.
Sample weights were used to adjust for non-response,
to match the sample to the U.S. population in terms of
demographic  characteristics, and to equalize intakes
over the 4 quarters of the year and the  7 days of the
week. A total of 503 breast-fed children were excluded
from  the  estimates,  but both consumers and  non-
consumers were included in the analysis.
           USDA (1999) provided data on  the mean
per  capita   quantities  (grams)  of various   food
products/groups consumed per individual for one day,
and the percent of individuals consuming those foods in
one day of the survey.  Tables 12-7 and 12-8 present
data on the mean quantities (grams) of grain products
consumed  per   individual  for one  day,  and  the
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                                                       	Chapter 12 - Intake of Grain Products
percentage of survey individuals  consuming  grain
products that survey day.  Data on mean intakes or
mean percentages  are based on respondents' day-1
intakes.
           The advantages of USD A (1999) study is
that  it uses the 1994-96, 98 CSFII data set, which
includes four years of intake  data,  combined, and
includes the supplemental data on children. These data
are expected to be generally representative of the U.S.
population and they include data on a wide variety of
grain products. The data set is one of a series of USD A
data sets that are publicly available.  One limitation of
this data set is that it is based on a one-day, and short-
term dietary data may not accurately reflect long-term
eating patterns. Other limitations of this study are that
it  only  provides mean values  of food intake  rates,
consumption is not normalized by  body  weight, and
presentation of results is not consistent with U.S. EPA's
recommended age groups.

12.3.2.2   Smiciklas-Wright et al,  2002 -  Foods
           Commonly Eaten in the United States:
           Quantities  Consumed  per   Eating
           Occasion and in a Day, 1994-1996
           Using data gathered in the 1994-96 USDA
CSFII,  Smiciklas-Wright  et  al.  (2002) calculated
distributions for  the  quantities  of  grain products
consumed per eating occasion by members of the U. S.
population (i.e.,  serving  sizes).   The estimates of
serving size are based on data obtained from 14,262
respondents, ages 2 and above, who provided 2 days of
dietary intake information.  A total  of 4,939 of these
respondents were children, ages 2 to 19 years of age.
Only dietary intake data from users of the specified
food were used in the analysis (i.e., consumers only
data).
           Table 12-9 presents serving size data for
selected grain products. These data are presented on an
as-consumed basis (grams) and represent the quantity of
grain products consumed per eating occasion.  These
estimates may be useful for assessing acute exposures
to contaminants in specific foods, or other assessments
where the amount consumed per eating  occasion is
necessary.  Only  the mean and  standard deviation
serving size  data and percent  of  the  population
consuming the food during the 2-day survey period are
presented in this handbook.  Percentiles of serving sizes
 of the foods consumed by these age groups of the U.S.
 population can be found in  Smiciklas-Wright et al.
 (2002).
            The advantages of using these data are that
 they were derived from the USDA CSFII and are
 representative of the U.S.  population.   The analysis
 conducted by Smiciklas-Wright et al. (2002) accounted
 for individual foods consumed as ingredients of mixed
 foods. Mixed foods were disaggregated via recipe files
 so that the individual ingredients  could be grouped
 together  with  similar  foods that  were  reported
 separately.   Thus, weights  of  foods  consumed as
 ingredients were  combined  with  weights  of foods
 reported  separately  to  provide a  more  thorough
 representation of consumption. However, it should be
 noted that  since  the  recipes for the mixed foods
 consumed were  not provided by the  respondents,
 standard recipes were used.  As a result, the estimates
 of quantity consumed for some food types are based on
 assumptions  about  the  types  and  quantities  of
 ingredients consumed as part of mixed foods.  This
 study used data from the 1994 to 1996 CSFII; data from
 the  1998 children's supplement were not included.

 12.3.2.3    Fox et al., 2004 - Feeding Infants  and
            Toddlers study: What Foods Are Infants
            and Toddlers Eating
            Fox et  al.  (2004) used data  from the
 Feeding Infants and Toddlers study (FITS) to assess
 food consumption patterns in infants and toddlers.  The
 FITS was sponsored by Gerber Products Company and
 was conducted to  obtain current information on food
 and nutrient intakes of children,  ages 4 to 24 months
 old, in the 50 states and the District of Columbia.  The
 FITS is described in detail in Devaney et al.  (2004).
 FITS was based on a random sample of 3,022 infants
 and  toddlers  for which dietary  intake data were
 collected by telephone from their parents or caregivers
 between March and July 2002. An initial recruitment
 and household interview was conducted, followed by an
 interview to obtain information on intake based on 24-
 hour recall.   The  interview also addressed growth,
 development and feeding patterns.  A second dietary
 recall interview was conducted  for a subset of  703
 randomly  selected respondents.   The study over-
 sampled children in the 4 to 6 and 9 tol 1 months age
 groups; sample weights were adjustedfornon-response,
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12-8
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
over sampling, and under coverage of some subgroups.
The response rate for the FITS was 73 percent for the
recruitment interview.  Of the recruited households,
there was a response rate of 94 percent for the dietary
recall  interviews (Devaney  et  al,  2004).    The
characteristics of the FITS study population is shown in
Table 12-10.
           Fox et al. (2004) analyzed the first set of
24-hour recall data collected from all study participants.
For this analysis, children were grouped into six age
categories:  4 to  6 months,  7 to 8  months, 9 to 11
months, 12 to 14 months, 15 to 18 months, and  19 to 24
months. Table 12-11 provides the percentage of infants
and toddlers consuming different types of grains or
grain products at least once in a day. The percentages
of children eating any type of grain or grain  product
ranged from 65.8 percent for 4 to 6 month olds to 99.2
percent for  19 to 24 month olds.
           The advantages of this study were that the
study population represents the U.S. population and the
sample size was large.  One limitation of the analysis
done by Fox et al. (2004) is that only frequency data
were provided; no information on actual intake rates
was included. In addition, Devaney et al (2004) noted
several limitations associated with the FITS data. For
the FITS, a commercial list of infants and toddlers was
used to obtain the sample used in the study.  Since
many of the household could not be located and did not
have children in the target population, a lower response
rate than would have occurred in a true national sample
was obtained (Devaney et al., 2004).  In addition, the
sample was likely from a higher socioeconomic status
when compared with all U.S. infants in this age group
(4 to 24 months old) and the use of a telephone survey
may have omitted lower-income  households  without
telephones (Devaney et al., 2004).

12.3.2.4    Ponza  et  al,  2004 -  Nutrient Food
           Intakes and Food Choices of Infants and
           Toddlers Participating in WIC
           Ponza et al. (2004) conducted a study using
selected data from the FITS to assess feeding patterns,
food choices and nutrient intake of infants and toddlers
participating in the  Special  Supplemental Nutrition
Program for Women, Infants,  and  Children  (WIC).
Ponza  et al. (2004)  evaluated  FITS  data  for the
following age groups: 4 to 6 months (N = 862), 7 to 11
months (N = 1,159) and 12 to 24 months (N= 996).
The total sample size described by WIC participants
and non-participants is shown in Table 12-12.
           The foods  consumed were analyzed by
tabulating the percentage of infants who consumed
specific foods/food groups per day (Ponza et al., 2004).
Weighted data were used in all of the analyses used in
the study (Ponza et al., 2004). Table 12-12 presents the
demographic data  for  WIC  participants and  non-
participants.  Table 12-13 provides information on the
food choices for the infants and toddlers studied. In
general, there was little difference in  grain product
choices among WIC participants and non-participants,
except for the 7 to 11 months age category (Table 12-
13).  Nonparticipants, ages 7 to 11 months, were more
likely to eat non-infant cereals than WIC participants.
           An advantage of this study is that it had a
relatively large sample size and was representative of
the U.S. general population of infants and children. A
limitation of the study is that intake values for foods
were  not provided.    Other  limitations are those
associated with the FITS data, as described previously
in Section 12.3.2.3.

12.3.2.5    Mennella et al., 2006 - Feeding Infants
           and Toddlers Study: The Types of Foods
           Fed to Hispanic Infants and Toddlers
           Menella et al. (2006) investigated the types
of food and  beverages consumed by Hispanic infants
and toddlers  in comparison to the non-Hispanic infants
and toddlers  in the United States.  The FITS 2002  data
for children between 4 and 24 months of age were used
for the study. The data represent a random sample of
371  Hispanic and 2,367 non-Hispanic infants  and
toddlers (Menella et al., 2006).   Menella et al. (2006)
grouped the  infants as follows: 4 to 5 months (N = 84
Hispanic; 538 non-Hispanic), 6 to 11 months (N = 163
Hispanic and 1,228 non-Hispanic), and 12 to 24 months
(N = 124 Hispanic and 871 non-Hispanic) of age.
           Table 12-14 provides the  percentage of
Hispanic  and non-Hispanic  infants  and  toddlers
consuming grain products.   In  most  instances  the
percentages consuming  the different types are similar.
However, 6  to 11  month old Hispanic  children were
more  likely  to eat rice  and pasta than non-Hispanic
children in this age groups.
           The advantage  of  the  study is that it
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                                                       Child-Specific Exposure Factors Handbook

                                                       	Chapter 12 - Intake of Grain Products
provides information on food preferences for Hispanic
and non-Hispanic infants and toddlers. A limitation is
that the study  did not provide food intake data, but
provided frequency  of use  data  instead.    Other
limitations  are those noted previously in Section
12.3.2.3 for the FITS data.

12.3.2.6    Fox et al, 2006  - Average Portion of
           Foods Commonly Eaten by Infants and
           Toddlers in the United States
           Fox et al. (2006) estimated average portion
sizes consumed per eating occasion by children 4 to 24
months of age who participated in the FITS. The FITS
is  a cross-sectional  study  designed to collect  and
analyze data on feeding practices, food consumption,
and usual nutrient intake of U.S. infants and toddlers
and is described in Section 12.3.2.3 of this chapter. It
included a stratified random sample of 3,022 children
between 4 and 24 months of age.
           Using the 24-hour recall data, Fox et al.
(2006) derived average portion sizes for six major food
groups, including breads and grains. Average portion
sizes for select individual foods within these  major
groups were also estimated. For this analysis, children
were grouped into six age categories: 4 to 5 months, 6
to 8 months, 9 to 11 months, 12 to 14 months, 15 to 18
months, and 19 to 24 months. Tables 12-15 and 12-16
present the average portion sizes for grain products for
infants and toddlers, respectively.

12.4       CONVERSION BETWEEN WET AND
           DRY WEIGHT INTAKE RATES
           The intake data presented in this chapter
are reported in units of wet weight (i.e., as-consumed or
uncooked weight of grain products consumed per day
or per  eating occasion).   However, data on the
concentration of contaminants in grain products may be
reported in units of either wet or dry weight.(e.g., mg
contaminant per gram dry-weight of grain products.)
It is essential that exposure assessors be aware of this
difference so that they may ensure consistency between
the units used for intake  rates and those used for
concentration   data  (i.e.,   if  the   contaminant
concentration  is measured in dry  weight of grain
products, then the dry weight units should be used for
their intake values).
           If necessary, wet weight (e.g., as
 consumed) intake rates may be converted to dry weight
 intake rates using the moisture content percentages
 presented in Table 12-17 and the following equation:
   IRdw ~  IR ww
 where:
                    100 -W
                      100
                         (Eqn. 12-1)
            IRw
            W
             dry weight intake rate;
             wet weight intake rate; and
             percent water content
 Alternatively,  dry  weight residue levels  in grain
 products may be converted to wet weight residue levels
 foruse with wet weight (e.g., as-consumed) intake rates
 as follows:
    ww

 where:
        =   C
              dw
      100-W
        100
(Eqn. 12-2)
            Cww  =       wet weight intake rate;
            Cdw  =       dry weight intake rate; and
            W   =       percent water content.

 The moisture data presented in Table  12-17 are for
 selected grain products taken from USDA (2007).
 12.5
REFERENCES FOR CHAPTER 12
 Devaney, B.; Kalb, L.; Briefel, R.; Zavitsky-Novak, T.;
         Clusen, N.; Ziegler, P. (2004) Feeding infants
         and toddlers study:  overview of the study
         design.  J Am Diet Assoc 104(Suppl 1): S8-
         S13.
 Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004)
         Feeding Infants and  Toddlers  Study: what
         foods are infants and toddlers eating.  J Am
         Diet Assoc 104 (Suppl): S22-S30.
 Fox, M.K.;  Reidy, K.; Karwe, V.; Ziegler, P.  (2006)
         Average portions of foods commonly eaten by
         infants and toddlers in the United States.  J
         Am Diet Assoc 106 (Suppl 1): S66-S76.
 Goldman, L. (1995) Children - unique and vulnerable.
         Environmental  risks  facing children  and
Page
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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
        recommendations for response.   Environ
        Health Prespect 103(6): 13-17.
Mennella, J.; Ziegler, P.; Brief el, R.; Novak, T. (2006)
        Feeding Infants and Toddlers Study: the types
        of foods fed to Hispanic infants and toddlers.
        J Am Diet Assoc 106 (Suppl 1): S96.
Ponza, M; Devaney,  B.;  Ziegler,  P.; Reidy, K.;
        Squatrito, C. (2004) Nutrient intakes and food
        choices of infants and toddlers participating in
        WIC.  J Am Diet Assoc  104  (Suppl): S71-
        S79.
Smiciklas-Wright, H.;  Mitchell, D.C.;  Mickle, S.J.;
        Cook, A.J.; Goldman, J.D.  (2002)  Foods
        commonly   eaten  in the  United States:
        Quantities consumed per eating occasion and
        in  a day, 1994-1996. U.S. Department of
        Agriculture  NFS  Report No.  96-5, pre-
        publication version, 252 pp.
USDA.  (1999) Food and nutrient intakes by children
        1994-96,1998: Table Set 17. Beltsville,MD:
        Food Surveys Research  Group,  Beltsville
        Human Nutrition  Research  Center,
        Agricultural  Research  Service,   U.S.
        Department of Agriculture.
USDA. (2007) USDA National Nutrient Database for
        Standard Reference, Release 20. Agricultural
        Research Service, Nutrient Data Laboratory
        Home Page,
        http://www.ars.usda.gov/ba/bhnrc/ndl
U.S. EPA.  (2005) Guidance on Selecting Age Groups
        for Monitoring  and Assessing Childhood
        Exposures to Environmental Contaminants.
        U.S.  Environmental  Protection  Agency,
        Washington, D.C., EPA/630/P-03/003F.
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oo
Table 12-3.
Age Group N
Birth to 1 year 1,486
1 to 2 years 2,096
3 to 5 years 4,391
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished
Percent
Consuming
70.5
99.8
100.0
100.0
100.0

Mean
2.5
6.4
6.3
4.3
2.5

Per Capita Intake of Total Grains (g/kg-day as consumed)
SE
0.1
0.1
0.1
0.1
0.05

Percentiles
p,
0.0
1.1
1.8
0.9
0.4

5th
0.0
2.1
2.6
1.7
0.8

10th
0.0
2.8
3.2
2.0
1.1

25th
0.0
4.2
4.3
2.8
1.5

50th
1.6
5.9
5.9
4.0
2.3

75th
3.8
7.9
7.8
5.4
3.1

90th
6.2
10.4
9.9
7.0
4.4

95th
8.6
12.1
11.5
8.2
5.1

99th
12.7
16.8
15.6
11.1
7.9

100th
26.3
31.6
27.0
17.2
12.4

U.S. EPA analysis of 1994-96. 1998 CSFII.
Table 12-4. Consumer Only Intake of Total Grains (g/kg-day as consumed)
Age Group N Mean
Birth to 1 year 1,048
1 to 2 years 2,092
3 to 5 years 4,389
6 to 12 years 2,089
13 to 19 years 1,222
N = Sample size.
SE = Standard error.
Source: Based on unpublished U.S
3.6
6.4
6.3
4.3
2.5

SE
0.1
0.1
0.1
0.1
0.05


r'
0.1
1.2
1.8
0.9
0.4


5th 10th
0.3 0.6
2.1 2.8
2.6 3.2
1.7 2.0
0.8 1.1

Percentiles
25th 50th 75th 90th 95th 99th
1.4 2.8 4.8 7.4 9.2 13.4
4.2 5.9 7.9 10.4 12.1 16.8
4.3 5.9 7.8 9.9 11.5 15.6
2.8 4.0 5.4 7.0 8.2 11.1
1.5 2.3 3.1 4.4 5.1 7.9


100th
26.3
31.6
27.0
17.2
12.4

EPA analysis of 1994-96. 1998 CSFII.
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Chapter 12 - Intake of Grain Products	

Age Group
Table 12-5.

N
Birth to 1 year 1,486
1 to 2 years
3 to 5 years
6 to 12 years
2,096
4,391
2,089
13 to 19 years 1,222
N
SE
Sample size.
Standard error.
Source: Based on unpublished U. S
Der Capita Intake of Individual Grain Products (g/kg-day as consumed)

Percent
Consuming
74.6
99.8
100.0
100.0
100.0

Cereal
Mean
4.0
8.4
8.7
6.2
4.1

. EPA analysis of 1994-96,

SE
0.14
0.08
0.07
0.06
0.06

1998 CSFII .
Rice
Percent
Mean
Consuming
60.2 0.74
86.4 0.57
87.9 0.50
88.0 0.35
85.8 0.27



SE
0.04
0.03
0.03
0.02
0.02


Table 12-6. Consumer Only Intake of Individual Grain Products (g/kg-day as consumed)
Age Group
Birth to 1 year
1 to 2 years
3 to 5 years
6 to 12 years
13 to 19 years

N
1,116
2,092
4,389
2,089
1,222
Cereal
Mean
5.4
8.4
8.7
6.2
4.1
Rice
SE N Mean
0.16 900 1.23
0.08 1,819 0.67
0.07 3,869 0.57
0.06 1,847 0.40
0.06 1,038 0.31

SE
0.07
0.04
0.03
0.02
0.03
N = Sample size.
SE = Standard error.
Source: Based on
unpublished U.S.
EPA analysis of 1994-96, 1998 CSFII .
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Table 12-1.
Age Group
Sample
Size
Total
Mean Quantities of Grain Products Consumed Daily by Sex and Age
Yeast,
breads,
and rolls

Total
Cereals and
Ready-to-eat
cereals
Dasta
Rice

Pasta
Per Capita (g/day)
Quick
breads,
pancakes,
French
toast
Cakes,
cookies,
pastries,
pies
Crackers,
popcorn,
pretzels,
corn chips
Mixtures,
mainly
grain
Males and Females
Under lyear
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
56
192
219
206
242
264
284
264
219
2
16
26
21
30
36
41
36
27
2
16
26
21
30
36
41
36
27
1
11
16
13
19
22
24
22
16
2
9
15
12
13
15
17
15
13
1"
9
12
11
12
11
11
11
10
1
9
12
11
16
17
15
16
12
3
16
22
19
23
30
33
29
22
1
7
9
8
11
13
13
12
9
20
87
87
87
98
102
107
102
87
Males
6 to 9 years
6 to 1 1 years
2 to 19 years
787
1,031
737
310
318
406
45
46
54
77
80
82
28
31
29
18
16
27
15
18
17
23
23
26
39
40
49
16
15
19
109
115
175
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
284
280
306
43
43
40
61
62
67
21
20
17
12
14
19
15
15
22
18
19
15
42
42
37
13
14
15
107
101
132
Males and Females
9 years and under
19 years and under
9,309
11,287
250
298
34
40
64
69
20
22
14
17
12
15
16
18
30
36
12
14
96
120
a Estimate is not statistically reliable due to small sample size reporting intake.
Note: Consumption amounts shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.











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Age Group

Sample
Size
Table 12-8.
Percentage of Individuals Consuming Grain Products, by Sex and Age (%)
Yeast

Total breads,
and rolls T0tal
Cereals and
Ready-to-
eat
cereals
Pasta

Rice Pasta
Quick
breads,
pancakes,
French
toast
Cakes,
cookies,
pastries,
pies
Crackers,
popcorn,
pretzels,
corn
chips
Mixtures,
mainly
grain
Males and Females
Under 1 year
1 year
2 years
1 to 2 years
3 years
4 years
5 years
3 to 5 years
5 years and under
1,126
1,016
1,102
2,118
1,831
1,859
884
4,574
7,818
70.6
98.2'
99.0'
98.7
99.4'
99.5'
99.9'
99.6'
95.8
10.9
48.4
58.7
53.7
64.1
67.0
69.2
66.8
55.5
62.8
70.6
71.1
70.9
69.7
69.1
70.4
69.7
69.3
9.1
45.3
51.9
48.7
53.3
54.8
54.9
54.3
46.9
3.4
11.3
14.4
12.9
11.1
11.4
11.4
11.3
10.9
2.1
9.4
9.4
9.4
8.6
7.1
6.8
7.5
7.5
4.4
23.0
27.5
25.3
28.8
28.6
25.2
27.5
24.0
16.5
47.0
46.6
46.8
46.1
52.3
52.4
50.3
45.0
10.3
39.0
37.9
38.4
38.5
39.4
32.1
36.7
34.1
15.0
47.8
45.3
46.5
49.0
46.2
47.4
47.5
43.3
Males
6 to 9 years
6 to 1 1 years
12 to 19 years
787
1,031
737
98.9'
99.0'
98.2'
69.8
69.1
62.7
62.6
64.0
44.6
50.8
52.4
33.2
10.5
9.7
10.0
7.4
8.1
5.9
28.1
27.1
24.4
52.5
52.3
41.3
36.0
33.8
27.2
44.5
45.3
46.2
Females
6 to 9 years
6 to 1 1 years
12 to 19 years
704
969
732
99.7'
99.3'
97.6'
71.5
71.0
60.9
61.2
59.3
45.9
47.6
45.6
30.3
9.0
9.4
8.6
7.9
7.1
9.3
26.3
27.1
19.8
57.1
55.0
40.6
38.3
37.1
30.9
48.0
45.7
46.1
Males and Females
9 years and under
19 years and under
9,309
11,287
97.2
97.6
61.6
62.4
66.4
57.6
47.9
41.7
10.5
9.9
7.6
7.6
25.3
24.2
48.9
46.1
35.3
32.5
44.4
45.1
' Estimate is not statistically reliable due to small sample size reporting intake.
Note: Percentages shown are representative of the first day of each participant's survey response.
Source: USDA, 1999.
                                                                                                                                                                   I
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Table 12-9. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and
Percentage of Individuals Using These Foods in Two Days
Quantity consumed per eating occasion (grams)
2 to 5 years
Male and Female
Food category (N
PC
White bread 66.9
Whole grain and wheat bread 24.3
Rolls 40.0
Biscuits 8.3
Tortillas 14.6
Quickbreads and muffins 9.6
Doughnuts and sweet rolls 11.3
Crackers 25.4
Cookies 51.0
Cake 14.6
Pie 2.9
Pancake and waffles 19.1
Cooked cereal 16.8
Oatmeal 10.4
Ready-to-eat cereal 72.9
Corn Flakes 11.2
Toasted Oat Rings 20.6
Rice 29.6
Pasta 49.4
Macaroni and cheese 17.8
Spaghetti with tomato sauce 16.8
Pizza 23.7
Corn chips 19.6
Popcorn 11.6
= 2,109)
Mean
34
37
39
38
32
55
59
17
28
70
76
49
211
221
33
33
30
84
90
159
242
86
29
20
6
to 11 years
Male and Female
(N= 1,432)
SEM
a
1
1
2
2
4
2
1
1
3
8
1
10
9
1
2
1
3
3
8
11
3
2
1
* Indicates a SEM value that is greater than 0 but less than
b Indicates a statistic that is potentially
PC = Percent consuming at least once in
SEM = Standard error of the mean.
unreliable
2 days.

PC
67.1
20.5
53.5
9.7
16.4
9.6
13.4
17.2
46.7
19.7
5.6
21.5
9.0
5.7
67.3
13.1
12.5
24.6
41.4
13.2
11.5
32.8
25.6
12.7
0.5.
Mean
42
44
48
48
47
67
69
26
37
79
116
77
245
256
47
42
45
124
130
217
322
108
33
31

SEM
1
1
1
3
2
5
2
2
2
4
8
3
14
19
1
2
2
6
5
13
18
6
2
2

because of small sample size or large








PC
61.3
14.5
61.9
12.2
22.9
11.0
17.3
10.6
29.0
15.1
6.6
13.5
5.2
2.4
45.6
10.4
7.3
24.2
33.4
7.5
10.1
39.6
26.9
7.8

Male
(N = 696)
Mean
56
60
69
72
76
125
102
39
53
99
188
96
310"
348"
72
62
62
203
203
408
583
205
58
54

12 to 19 years


Female

(N = 702)
SEM
1
2
2
4
5
12
12
5
3
9
15
6
29b
45"
3
4
5
10
9
46
46
13
5
5

PC
57.9
17.6
48.8
10.3
20.1
11.0
13.8
14.2
31.8
15.5
4.8
8.2
6.0
2.3
46.3
8.7
8.1
28.8
37.8
10.7
8.5
30.5
25.1
10.5

Mean
47
53
51
55
56
79
78
26
42
85
138"
74
256"
321"
52
49
42
157
155
260
479
143
44
37

SEM
1
2
1
4
3
10
5
3
2
8
12"
5
31"
40"
2
4
3
10
9
30
51
8
3
4

coefficient of variation.












Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data).
                                                                                                                                           s
                                                                                                                                           I
                                                                                                                                                I
                                                                                                                                                 1
                                                                                                                                                 «?
                                                                                                                                                 I
                                                                                                                                                 S
                                                                                                                                                 I

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
Table 12-10. Characteristics of the FITS Sample Population

Gender
Male
Female
Age of Child
4 to 6 months
7 to 8 months
9 to 1 1 months
12 to 14 months
15 to 18 months
19 to 24 months
Child's Ethnicity
Hispanic or Latino
Non-Hispanic or Latino
Missing
Child's Race
White
Black
Other
Urbanicity
Urban
Suburban
Rural
Missing
Household Income
Under $10,000
$10,000 to $14,999
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 and Over
Missing
Receives WIC
Yes
No
Missing
Sample Size (Unweighted)
WIC = Special Supplemental Nutrition
Source: Devaney et al., 2004.
Sample Size

1,549
1,473

862
483
679
374
308
316

367
2,641
14

2,417
225
380

1,389
1,014
577
42

48
48
221
359
723
588
311
272
452

821
2,196
5
3,022
Program for Women, Infants, and Children.

Percentage of Sample

51.3
48.7

28.5
16.0
22.5
12.4
10.2
10.4

12.1
87.4
0.5

80.0
7.4
12.6

46.0
33.6
19.1
1.3

1.6
1.6
7.3
11.9
23.9
19.5
10.3
9.0
14.9

27.2
72.6
0.2
100.0


Child-Specific Exposure Factors Handbook
September 2008	
 Page
12-17

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 12 - Intake of Grain Products
Table 12-11. Percenta§
e of Infants and Toddlers Consuming Different Types of Grain Products
Percentage of Infants and Toddlers Consuming at Least Once in a Day
Food Group/Food 4 to 6 7 to 8
months months
Any Grain or Grain Product
Infant Cereals
Noninfant Cereals"
Not Pre-sweetened
Pre-sweetenedb
Breads and Rolls0
Crackers, Pretzels, Rice Cakes
Cereal or Granola Bars
Pancakes, Waffles, French Toast
Rice and Pastad
Other
Grains in Mixed Dishes
Sandwiches
Burrito, Taco, Enchilada, Nachos
Macaroni and Cheese
Pizza
Pot Pie/Hot Pocket
Spaghetti, Ravioli, Lasagna
" Includes both ready-to-eat and cooked
b Defined as cereals with more than 2 1 .
0 Does not include bread in sandwiches
65.8
64.8
0.6
0.5
0.0
0.6
3.0
0.0
0.1
2.3
0.2
0.4
0.0
0.0
0.2
0.1
0.0
0.1
cereals.
1 g sugar per 100
91.5
81.2
18.3
17.0
1.8
9.9
16.2
1.1
0.8
4.5
0.1
5.3
1.1
0.0
1.6
0.7
0.9
1.8

g.
9 to 11
months
97.5
63.8
44.3
37.0
9.0
24.5
33.4
3.4
7.5
18.2
2.7
24.1
8.6
1.0
4.9
2.2
0.5
9.9


12 to 14
months
97.8
23.9
58.9
44.5
17.7
47.3
45.2
9.8
15.1
26.2
2.8
48.3
21.5
4.5
14.6
6.8
2.0
15.3


15 to 18
months
98.6
9.2
60.5
40.6
26.4
52.7
46.4
10.0
16.1
39.0
2.5
52.0
25.8
2.8
15.0
9.0
1.0
12.1


19 to 24
months
99.2
3.1
51.9
31.9
22.7
53.1
44.7
9.7
15.4
35.9
4.5
55.1
25.8
2.1
15.0
9.4
1.8
8.8


Sandwiches are included in mixed dishes.
d Does not include rice or pasta in mixed dishes.
Source: Fox et al., 2004.






Page
12-18
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
                         Table 12-12. Characteristics of WIC Participants and Nonparticipants" (Percentages)
                               Infants 4 to 6 months
                                                              Infants 7 to 11 months
                                                                                            Toddlers 12 to 24 months
                              WIC
                            Participant
                              Non-participant
               WIC
            Participant
           Non-participant
              WIC
            Participant
          Non-participant
  Gender
   Male                        55
   Female                      45
  Child's Ethnicity
   Hispanic or Latino            20
   Non-Hispanic or Latino         80
  Child's Race
   White                       69
   Black                       15
   Other                       22
  Child In Day Care
   Yes                        39
   No                         61
  Age of Mother
   14 to 19                     18
   20 to 24                     33
   25 to 29                     29
   30 to 34                      9
   3 5 or Older                   9
   Missing                      2
  Mother's Education
   11 ""Grade or Less             23
   Completed High School         35
   Some Postsecondary           33
   Completed College             7
   Missing                      2
  Parent's Marital Status
   Married                     49
   Not Married                  50
   Missing                      1
  Mother or Female Guardian Works
   Yes
   No
   Missing
  Urbanicity
   Urban
   Suburban
   Rural
   Missing
  Sample Size
  (Unweighted)
                    46
                    53
                     1
                     34
                     36
                     28
                      2
                    265
                                    54
                                    46
                                    **
                                    11
 84
 4
 11

 38
 62
 **

 1
 13
 29
 33
 23
 2
 **
 2
 19
 26
 53
 1
 **

 93
 7
 1


 51
 48
 1
 55
 31
 13
  1
597
 55
 45


 24
 76

 63
 17
 20

 34
 66

 13
 38
 23
 15
 11
  1

 15
 42
 32
  9
  2


 57
 42
  1


 45
 54
  1
 37
 31
 30
  2
351
                                51
                                49
92
**

86
 5
 9
**

46
54
**

 1
11
30
36
21
 1
**

 2
20
27
51
 0
**

93
 7
 0
**

60
40
 0
 50
 34
 15
  1
 57
 43


 22
 78

 67
 13
 20

 43
 57

  9
 33
 29
 18
 11
  0

 17
 42
 31
  9
  1


 58
 41
  1


 55
 45
  0
 35
 35
 28
  2
205
                              52
                              48
                              **
                              10
                                                                                                 84
                                                                                                  5
                                                                                                 11
                                                                                                 *
                                                                                                 53
                                                                                                 47
                                                                                                 **

                                                                                                  1
                                                                                                 14
                                                                                                 26
                                                                                                 34
                                                                                                 26
                                                                                                  1
                                                                                                 **

                                                                                                  3
                                                                                                 19
                                                                                                 28
                                                                                                 48
                                                                                                  2
 11
  1
 *

 61
 38
  1
 48
 35
 16
  2
791
  WIC
X2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within
each age group for each variable. The results of X2 test are listed next to the variable under the column labeled non-participants
for each of the three age groups. *P<0.05; **P>0.01; non-participants significantly different from WIC participants on the
variable.
=Special Supplemental Nutrition Program for Women, Infants, and Children.
  Source:   Ponza et al., 2004.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                                    Page
                                                                                                   12-19

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 12 - Intake of Grain Products
Table 12-13. Food Choices for Infants and Toddlers by WIC Participation Status.


Infant Cereals
Noninfant Cereals, Total
Not Pre-sweetened
Pre-sweetened
Grains in Combination Foods
Sample Size (unweighted)
Infants 4 to 6 months
WIC Non-
Participant participant
69.7 62.5
0.9 0.5
0.5 0.5
0.0 0.0
0.9 0.1
265 597
Infants 7 to
WIC
Participant
74.7
21.7
18.7
4.0
18.8
351
1 1 months
Non-
participant
69.7
38.5*
32.9*
6.9
14.7
808
Toddlers
WIC
Participant
13.5
58.1
43.7
17.7
50.3
205
12 to 24 months
Non-
participant
9.2
56.0
36.3
24.1
52.9
791
* = P<0.01 non-participants significantly different from WIC participants.
WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
Source: Ponza et al., 2004.





Page
12-20
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
                   Table 12-14. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different
                                            Types of Grain Products on A Given Day
                                            Age 4 to 5 months
                              Age 6 to 11 months
                                           Age 12 to 24 months
                                       Hispanic
                                        (n=84)
          Non-Hispanic
            (n=538)
            Hispanic
            (n=163)
           Non-Hispanic
            (n=l,228)
            Hispanic
            (n=124)
           Non-Hispanic
             (n=871)
  Any Grain or Grain Product
  Infant Cereal
  Noninfant Cereal
  Breads'
  Tortillas
  Crackers, Pretzels, Rice Cakes
  Pancakes, Waffles, French Toast
  Rice and Pastab
  Rice
  Grains in Mixed Dishes
     Sandwiches
     Burrito, Taco, Enchilada, Nachos
     Macaroni and Cheese
     Pizza
     Spaghetti, Ravioli, Lasagna	
56.5
55.2

 1.4T
 1.4T
 1.3T
56.9
56.5
 95.0
 74.1
 18.5*
 18.2
 4.0t
 27.8
 1.4T
 20.1*
15.9**
 15.9
 4.0t
 1.3T
 3.0t

 8.3t
93.5
73.6
29.2
15.1

22.5
 4.3
10.3
 4.7
13.0
 4.6

 3.1
 1.4
 4.6
 97.1
 15.9
 45.3
 44.0
 6.7t*
 35.6
 13.0
 44.3
26.9t*
38.8*
 24.2
 2.1T
 10.1
i.o**t
 9.3t
98.9
 9.3
57.8
52.9
 0.6t
46.9
16.0
32.9
13.0
54.4
24.9
 3.0
15.5
 9.7
12.1
  *        Does not include bread in sandwiches. Sandwiches are included in mixed dishes. Includes tortillas, also shown separately.
  b        Does not include rice or pasta in mixed dishes. Includes rice (e.g. white, brown, wild, and Spanish rice without meat) and pasta
           (e.g. spaghetti, macaroni, and egg noodles).  Rice is also shown separately.
           = Less than 1 percent of the group consumed this food on a given day.
  *        = Significantly different from non-Hispanic at the P<0.05.
  **       = Significantly different from non-Hispanic at the P>0.01.
  •f        = Statistic is potentially unreliable because of a high coefficient of variation.

  Source:   Mennella et al., 2006.	
Child-Specific Exposure Factors Handbook
September 2008	
                                                                         Page
                                                                        12-21

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                                            Child-Specific Exposure Factors Handbook

                                           	Chapter 12 - Intake of Grain Products

Table 12-15. Average
Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed
Infants from the 2002




Food group

Infant cereal, dry
Infant cereal, jarred
Ready-to-eat
Crackers

Bread
=
N
SEM
cereal



Cell size was too small to §
Number of respondents.
Standard error of the mean

Reference
unit

tablespoon
tablespoon
tablespoon
ounce
saltine
slice
Feeding Infants and Toddlers
4 to 5 months
(N=624)

3.1+0.14
-
-
-
-
-
Study
6 to 8 months
(N=708)
Mean± SEM
4.5+0.14
5.6+0.26
2.3+0.34
0.2+0.02
2.2+0.14
0.5+0.10
by

9 to 11 months
(N=687)

5.2+0.18
7.4+0.34
3.4+0.21
0.3+0.01
2.7+0.12
0.8+0.06
enerate a reliable estimate.








Source: Fox et al., 2006.
Table 12-16

Food Group

Bread
Rolls
Ready-to-eat cereal
Hot cereal, prepared
Crackers

Pasta
Rice
Pancakes and waffles
Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed by
Toddlers from the 2002 Feeding Infants and Toddlers Study

Reference Unit

slice
ounce
cup
cup
ounce
saltine
cup
cup
1 (4-inch diameter)
12 to 14 months
(N=371)

0.8±0.04
0.9±0.11
0.3+0.02
0.6±0.05
0.3+0.02
3.3+0.22
0.4+0.04
0.3+0.04
1.0+0.08
15 to 18 months
(N=312)
Mean± SEM
0.9+0.05
1.0+0.10
0.5+0.03
0.6+0.05
0.4+0.02
3.5+0.22
0.4+0.04
0.4+0.05
1.4+0.21
19 to 24 months
(N=320)

0.9+0.05
0.9+0.15
0.6+0.04
0.7+0.05
0.4+0.02
3.7+0.22
0.5+0.05
0.4+0.05
1.4+0.17
N = Number of respondents.
SEM = Standard error of the mean.
Source: Fox et al., 2006.




Page
12-22
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products	
Table 12-17.
Food
Barley - pearled
Corn - grain - endosperm
Corn - grain - bran
Millet
Oats
Rice - white - long-grained
Rye
Rye - flour - medium
Sorghum
Wheat - hard white
Wheat - germ
Wheat - bran
Wheat - flour - whole grain
Mean Moisture Content of Selected Grain Products Expressed as
Percentages of Edible Portions
Moisture Content
Raw Cooked
10.09 68.80
10.37
4.71
8.67 71.41
8.22
11.62 68.44
10.95
9.85
9.20
9.57
11.12
9.89
10.27

Comments


crude







crude
crude

Source: USDA, 2007.
Child-Specific Exposure Factors Handbook
September 2008	
Page
12-23

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Child-Specific Exposure Factors Handbook


Chapter 12 - Intake of Grain Products	
                               APPENDIX 12A

    CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS GRAIN
     PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
Child-Specific Exposure Factors Handbook                                    Page
September 2008	12-1

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 12 - Intake of Grain Products
Table 12A-1. Food
Total Grains






















Cereal Grains
























95000060
15000250
15000251
15000260
15000261
15000270
15000650
15000660
15001200
15001201
15001210
15001211
15001220
15001230
15001231
15001260
15001270
15001271
15002260
15002310
15002320
15002321
15002330
15000250
15000251
15000260
15000261
15000270
15000650
15000660
15001200
15001201
15001210
15001211
15001220
15001230
15001231
15001240
15001241
15001260
15001270
15001271
15002260
15002310
15002320
15002321
15002330
15002331
Codes and Definitions Used in Analysis
Amaranth, grain
Barley, pearled barley
Barley, pearled barley-babyfood
Barley, flour
Barley, flour-babyfood
Barley, bran
Buckwheat
Buckwheat, flour
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, bran
Corn, field, starch
Corn, field, starch-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood
Millet, grain
Oat, bran
Oat, flour
Oat, flour-babyfood
Oat, groats/rolled oats
Barley, pearled barley
Barley, pearled barley-babyfood
Barley, flour
Barley, flour-babyfood
Barley, bran
Buckwheat
Buckwheat, flour
Corn, field, flour
Corn, field, flour-babyfood
Corn, field, meal
Corn, field, meal-babyfood
Corn, field, bran
Corn, field, starch
Corn, field, starch-babyfood
Corn, field, syrup
Corn, field, syrup-babyfood
Corn, pop
Corn, sweet
Corn, sweet-babyfood
Millet, grain
Oat, bran
Oat, flour
Oat, flour-babyfood
Oat, groats/rolled oats
Oat, groats/rolled oats-babyfood
ofthe 1994-96,
15002331
95003060
95003110
15003230
15003231
15003240
15003241
15003250
15003251
15003260
15003261
15003280
15003290
15003440
15003810
15003811
15004010
15004011
15004020
15004021
15004030
15004040
15004050
15003230
15003231
15003240
15003241
15003250
15003251
15003260
15003261
15003280
15003290
15003440
15003450
15003810
15003811
15004010
15004011
15004020
15004021
15004030
15004040
15004050
95000060
95003060
95003110

1998 USDA CSFII Data
Oat, groats/rolled oats-babyfood
Psyllium, seed
Quinoa, grain
Rice, white
Rice, white-babyfood
Rice, brown
Rice, brown-babyfood
Rice, flour
Rice, flour-babyfood
Rice, bran
Rice, bran-babyfood
Rye, grain
Rye, flour
Sorghum, grain
Triticale, flour
Triticale, flour-babyfood
Wheat, grain
Wheat, grain-babyfood
Wheat, flour
Wheat, flour-babyfood
Wheat, germ
Wheat, bran
Wild rice
Rice, white
Rice, white-babyfood
Rice, brown
Rice, brown-babyfood
Rice, flour
Rice, flour-babyfood
Rice, bran
Rice, bran-babyfood
Rye, grain
Rye, flour
Sorghum, grain
Sorghum, syrup
Triticale, flour
Triticale, flour-babyfood
Wheat, grain
Wheat, grain-babyfood
Wheat, flour
Wheat, flour-babyfood
Wheat, germ
Wheat, bran
Wild rice
Amaranth, grain
Psyllium, seed
Quinoa, grain

Page
12A-2
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 12 - Intake of Grain Products

Rice
15003260
15003261
15003240
15003241
Rice, bran
Rice, bran-babyfood
Rice, brown
Rice, brown-babyfood
15003250
15003251
15003230
15003231
Rice, flour
Rice, flour-babyfood
Rice, white
Rice, white-babyfood
Child-Specific Exposure Factors Handbook
September 2008	
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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
                                  TABLE OF CONTENTS

13     INTAKE OF HOME-PRODUCED FOODS	13-1
       13.1    INTRODUCTION	13-1
       13.2    RECOMMENDATIONS	13-1
       13.3    KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS	13-6
              13.3.1  U.S. EPA Analysis of NFCS 1987-1988	13-6
       13.4    REFERENCES FOR CHAPTER 13	13-8

APPENDIX 13A FOOD CODES AND DEFINITIONS USED IN CHILD-SPECIFIC ANALYSIS
              OF THE 1987-1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE
              RATES	  13A-1
APPENDIX 13B 1987-1988 NFCS FOOD CODES AND DEFINITIONS USED IN ESTIMATING
              FRACTION OF HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED	  13B-1
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September 2008	13-i

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                                                     Child-Specific Exposure Factors Handbook

                                                  Chapter 13 - Intake of Home-Produced Foods
                                         LIST OF TABLES

Table 13-1.      Summary of Recommended Values for Intake of Home-produced Foods (Consumers Only).  . 13-3
Table 13-2.      Confidence in Recommendations for Intake of Home-produced Foods	13-4
Table 13-3.      Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in
               Child-specific Analysis of Food Intake	13-10
Table 13-4.      Consumer Only Intake of Home-produced Foods (g/kg-day)	13-11
Table 13-5.      Percent Weight Losses from Food Preparation	13-12
Table 13-6.      Fraction of Food Intake that is Home-produced	13-13
Table 13A-1.    Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDA
               NFCS Data to Estimate Intake of Home-produced Foods      	  13 A-2
Table 13B-1.    Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household
               Data to Estimate Fraction of Food Intake that is Home-produced	  13B-2
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Chapter 13 - Intake of Home-Produced Foods
13
13.1
        INTAKE OF  HOME-PRODUCED
        FOODS
        INTRODUCTION
        Ingestion of home-produced foods can be a
pathway for exposure to environmental contaminants.
Home-produced foods can become contaminated in a
variety of ways. Ambient pollutants in the air may be
deposited on plants, adsorbed onto or absorbed by the
plants, or dissolved in rainfall or irrigation waters that
contact the plants.  Pollutants may also be adsorbed
onto plant roots from contaminated  soil  and water.
Finally, the addition of pesticides, soil additives, and
fertilizers  to  crops  or  gardens   may result  in
contamination  of food products.   Meat and dairy
products can become contaminated if animals consume
contaminated soil, water,  or feed  crops.  Farmers, as
well as rural and urban residents who consume home-
produced foods, may be potentially exposed if these
foods  become  contaminated.    Exposure  via  the
consumption  of  home-produced foods  may be  a
significant route of expo sure for these populations (U.S.
EPA,  1989;  U.S.  EPA,   1996).  For  example,
consumption of  home-produced  fruits,  vegetables,
game, and fish has been shown to have an impact  on
blood lead levels in areas where soil lead contamination
exists (U.S. EPA, 1994). At Superfund sites where soil
contamination is  found, ingestion of home-produced
foods has been considered a potential route of exposure
(U.S. EPA, 1991;  U.S.  EPA,  1993).   Assessing
exposures to individuals who consume home-produced
foods requires knowledge of intake rates of such foods.
        Data from the 1987-1988 Nationwide Food
Consumption Survey (NFCS) were used to  generate
intake  rates for  home-produced  foods  (U.S. EPA,
1997). Until 1988, USDA conducted  the NFCS every
10 years to analyze the food consumption behavior and
dietary status of Americans (USDA, 1992). While more
recent food consumption surveys have been conducted
to estimate food intake  among the general population
(e.g., USDA's Continuing  Survey  of Food Intake
among Individuals [CSFII] and the National Health and
Nutrition  Examination Survey [NHANES]), these
surveys have not collected data that can be used to
estimate consumption of home-produced foods. Thus,
the 1987-1988 NFCS data  set is currently  the best
available source of information for this factor.
        The 1987-1988 NFCS was conducted between
April 1987 and  August 1988.  The survey  used a
statistical sampling technique designed to ensure that
all seasons, geographic regions of the 48 conterminous
states in the U.S., and socioeconomic and demographic
groups were represented (USDA, 1994).  There were
two  components of the  NFCS.    The  household
component collected information  over a seven-day
period  on  the  socioeconomic  and  demographic
characteristics of households, and the types, amount,
value, and sources of foods consumed by the household
(USDA,  1994).  The individual intake component
collected information on food intakes of individuals
within each household over a three-day period (USDA,
1993).  The sample  size for the 1987-1988 survey was
approximately   4,300   households   (over  10,000
individuals; approximately 3,000 children).  This was
a decrease over the previous survey conducted in 1977-
1978, which samp led approximately 15,000 households
(over 36,000 individuals) (USDA, 1994).  The sample
size was lower in the 1987-1988 survey as a result of
budgetary constraints and low response rate (38 percent
for the household  survey and  Slpercent for the
individual survey) (USDA, 1993).  The methods used
to analyze the 1987-1988 NFCS data and the results of
these analyses that pertain to children are presented in
Section 13.3.

13.2    RECOMMENDATIONS
        The data presented in this section may be used
to  assess exposure  to contaminants  in foods  grown,
raised,  or caught at  a specific site. The recommended
values  for mean  and  upper  percentile  (i.e.,  95th
percentile) intake rates among consumers of the various
home-produced food groups are presented in Table 13-
1;  these rates can be converted to per capita rates by
multiplying by the fraction of the population consuming
these food groups during the survey period (See Section
13.3).  Table  13-2 presents the confidence ratings for
home-produced food intake. The data presented in this
chapter for  consumers  of home-produced  foods
represent  average  daily  intake   rates   of  food
items/groups over the seven-day survey period and do
not account for variations in eating habits during the
rest of the year; thus the recommended upper percentile
values, as well as the percentiles of the distributions
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                                                    Chapter 13 - Intake of Home-Produced Foods
presented in Section 13.3 may not necessarily reflect
the long-term distribution of average daily intake of
home produced foods.
        Because the home-produced food intake rates
presented in this chapter are based on foods as brought
into the household and not in the form in which they are
consumed, preparation loss factors should be  applied,
as appropriate. These factors are necessary to convert
to intake rates to those that are representative of foods
"as consumed".    Additional conversions  may be
necessary to ensure that the form of the food used to
estimate intake (e.g., wet or dry weight) is consistent
with  the   form  used  to  measure  contaminant
concentration (see Section 13.3).
        The NFCS data used to generate  intake rates
of home-produced foods are over 20 years old and may
not be reflective of  current eating patterns  among
consumers of home-produced foods.  Although USDA
and others  have  conducted other food consumption
studies since the release of the 1987-1988 NFCS, these
studies do not include information on home-produced
foods.
        Recommended home-produced  food intake
rates are not provided for children under 1  year of age
because  the  methodology  used  is   based  on
apportionment of home-produced foods  used by a
household among the members of that household that
consume those foods. It was assumed that the diets of
children under 1 year of age differ markedly from that
of other household members; thus, they were  not
assumed to consume any portion of the home-produced
food brought into  the  home.  Also, recommended
home-produced food intake rates are not provided for
individual food items for children because, in  general,
the sample size was too small to provide reliable data
for individual age groups. However, if intake rates are
needed for age groups under 1 year of age or for food
items other than the major food groups presented here,
data in Section 13.3  on the fraction of household intake
that is home-produced may be used in conjunction with
age-specific intake  rates presented elsewhere in this
handbook to estimate intake of home produced foods
(U.S. EPA,  1997).
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Chapter 13 - Intake of Home-Produced Foods


Table 13-1. Summary
Age Group3
of Recommended Values for Intake of Home-produced Foods
Mean 95th Percentile ,,,... ,
Multiple
/, , Percentiles
g/kg-day
(Consumers Only)
Source
Home-produced Fruits
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
8.7 60.6
*'\ f'90 See Table 13-4
3.O 15.5
1.9 8.3
U.S. EPA Analysis of
1987-1988 NFCS
Home-produced Vegetables
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
5.2 19.6
25 77
'n '•' See Table 13-4
2.0 O.2
1.5 6.0
U.S. EPA Analysis of
1987-1988 NFCS
Home-produced Meats
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
3.7 10.0
I* ^ See Table 13-4
1.7 4.3
U.S. EPA Analysis of
1987-1988 NFCS
Home Caught Fish
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
b
2.8 7.1 See Table 13-4
1.5 4.7
U.S. EPA Analysis of
1987- 1988 NFCS
a Analysis was conducted prior to Agency ' s issuance of Guidance on Selecting Age Groups for Monitoring and
Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005).
b
Data not presented for age groups/food groups where less than 20 observations were available.

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                                                       Chapter 13 - Intake of Home-Produced Foods
                    Table 13-2.  Confidence in Recommendations for Intake of Home-produced Foods
  General Assessment Factors
             Rationale
              Rating
  Soundness
   Adequacy of Approach
   Minimal (or Defined) Bias
The survey methodology and the
approach to data analysis were adequate,
but individual intakes were inferred from
household consumption data. The
sample size was large (approximately
3,000 children).

Non-response bias can not be ruled out
due to low response rate. Also, some
biases may have occurred from using
household data to estimate individual
intake.
          Medium (Means)
         Low (Distributions)
 Applicability and Utility
   Exposure Factor of Interest
   Representativeness



   Currency

   Data Collection Period
The analysis specifically addressed
home-produced intake.

Data from a nationwide survey,
representative of the general U.S.
population was used.

The data were collected in 1987-1988.

Household data were collected over 1
week.
Low (Means & Short-term distributions)
    Low (Long-term distributions)
  Clarity and Completeness
   Accessibility
   Reproducibility
   Quality Assurance
The methods used described to analyze
the data are described in detail in this
handbook; the primary data are
accessible through USDA.

Sufficient detail on the methods used to
analyze the data are presented to allow
for the results to be reproduced.

Quality assurance of NFCS data was
good; quality control of the secondary
data was sufficient.
                                                      High
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Chapter 13 - Intake of Home-Produced Foods
Table 13-2. Confidence
General Assessment Factors
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
in Recommendations for Intake of Home-produced Food (continued)
Rationale
Full distributions of home-produced
intake rates were provided.
Sources of uncertainty include:
individuals' estimates of food
weights, allocation of household food
to family members, and potential
changes in eating patterns since these
data were collected,
The study was reviewed by USDA
and U.S. EPA.
The number of studies is 1 .

Rating
Low to Medium
Medium
Low-Medium (means and short-term
distributions)
Low (long-term distributions)
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                                                    Chapter 13 - Intake of Home-Produced Foods
13.3    KEY STUDY FOR INTAKE OF HOME-
        PRODUCED FOODS
13.3.1   U.S. EPA Analysis of NFCS 1987-1988
        U.S. EPA'sNational Center for Environmental
Assessment  (NCEA) analyzed USDA's  1987-1988
NFCS data to generate intake rates for home-produced
foods (U.S. EPA, 1997). Forthe purposes of this study,
home-produced  foods  were defined as homegrown
fruits and vegetables, meat and dairy products derived
from consumer-raised  livestock  or  game meat, and
home caught fish.  The food groups selected for
analysis of  children's home-produced food intake
included major food groups such as total fruits, total
vegetables, total meats,  total dairy, total fish and
shellfish.  These food  groups were  identified in the
NFCS  data  base  according to NFCS-defmed food
codes.    Appendix  13A presents  the codes  and
definitions used to determine these major food groups.
Foods with  these codes, for which the source was
identified  as home-produced, were included in the
analysis. This chapter presents the intake rate  data for
these major food groups, except total dairy, for various
age ranges of children.  An insufficient number of
observations  (i.e.,  less than 30 households)  were
available to allow for estimates of home-produced dairy
products.    Also,  child-specific intake  rates for
individual food items (e.g., carrots, citrus fruit) were
not estimated because, in general, the sample size was
too small to provide reliable data for the individual age
groups of interest.
        The USD A data were adjusted by applying the
sample weights  calculated by USDA to the data set
prior to analysis.  The USDA sample weights were
designed to "adjust for survey non-response and other
vagaries of  the sample  selection process" (USDA,
1987-1988).  Also, the USDA weights are calculated
"so that the  weighted sample total equals the known
population  total,  in  thousands,   for   several
characteristics thought to be correlated with eating
behavior"  (USDA,  1987-1988).   The unweighted
sample included approximately 3,000 children (ages <1
to 19 years), which was weighted to reflect nearly 54
million children.
        Although the individual intake component of
the NFCS gives the best measure of the amount of each
food group eaten by each individual in the household,
 it could not be used directly to measure consumption of
 home-producedfoodbecause the individual component
 does not identify the source of the food item (i.e., as
 home-produced  or not).   Therefore,  an analytical
 method which  incorporated  data  from both the
 household and  individual  survey  components was
 developed to estimate individual home-produced food
 intake.  The USDA household data  were  used to
 determine (1) the amount of each home-produced food
 item used during a week by household members and (2)
 the number of meals eaten in the household by each
 household member during a week. As measured by the
 NFCS, the  amount of food "consumed"  by the
 household is a measure of consumption in an economic
 sense, i.e., a measure of the weight of food brought into
 the household that has been consumed (used up) in
 some manner. In addition to food being consumed by
 persons, food may be used up by spoiling, by being
 discarded  (e.g.,  inedible  parts),  through  cooking
 processes, etc. Note that the household survey reports
 the  total amount of each food  item used in the
 household (whether by guests or household members);
 the amount used by household members was derived by
 multiplying the total amount used in the household by
 the proportion of all meals served in the household
 (during the  survey week) that were  consumed  by
 household members.
         The  individual  survey data were  used to
 generate average sex- and age-specific serving sizes for
 each food item.  These serving sizes were used during
 subsequent analyses to generate home-produced food
 intake  rates for  individual  household members.
 Assuming that the proportion of the household quantity
 of each home-produced food item/group was a function
 of the number of meals and the mean sex- and age-
 specific serving  size  for each  family  member,
 individual   intakes of  home-produced  food  were
 calculated for all  members of the survey population
 using the following general equation:
                                      (Eqn. 13-1)
 where:
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Chapter 13 - Intake of Home-Produced Foods
        W;  =   Home-produced  amount  of  food
                item/group attributed to member  i
                during the week (g/week);
        wf  =   Total quantity  of home-produced
                food item/group used by the family
                members (g/week);
        nij  =   Number of meals of household food
                consumed by member i during the
                week (meals/week); and
        q;  =   Serving size for an individual within
                the age  and  sex category of the
                member (g/meal).
number of individuals surveyed, then NT - Nc is the
weighted number of individuals who  reported zero
consumption of the food item.  In addition, there are
(p/100 x Nc) individuals below the p* percentile.
Therefore, the percentile that corresponds to a particular
intake rate (IRp) for the overall distribution of home-
produced food consumption (including consumers and
non-consumers) can be obtained by:
                100
                    xNc +|NT-NC
                                      (Eqn. 13-2)
        Daily intake of a home-produced food group
was determined by dividing the weekly value (w;) by
seven.  Intake rates were indexed to the self-reported
body weight of the survey respondent and reported in
units of g/kg-day.  For the major food groups (fruits,
vegetables, meats, and fish),  distributions  of home-
produced intake among consumers were generated by
age group. Consumers were defined  as members  of
survey households who reported consumption of the
food group of interest during the one week survey
period.
        The age categories used in the analysis were as
follows: 1 to 2 years; 3 to 5 years; 6 to 1 1 years; and  12
to 19 years Because this analysis was conducted prior
to issuance of U.S. EPA's Guidance on Selecting Age
Groups for Monitoring  and Assessing  Childhood
Exposures to Environmental Contaminants (U.S. EPA,
2005),  the age groups used are not entirely consistent
with recent guidelines. Intake rates were not calculated
for children under 1  year because their diet differs
markedly from that of other household members, and
thus, the assumption that all household members share
all foods would be invalid for this age group.
        The intake data presented here for consumers
of home-produced foods  and the total number  of
individuals surveyed may be used to calculate the mean
and  the  percentiles  of the  distribution of home-
produced food consumption in the overall population
(consumers and non-consumers) as follows:
        Assuming that IRp  is  the home-produced
intake rate of the food group at the p* percentile and Nc
is the weighted number of individuals consuming the
home-produced food item, and NT is the weighted total
        Table 13-3 displays the weighted numbers NT,
as well as the unweighted total survey sample sizes, for
each age  category.    Table  13-4  presents home-
produced intake rates for fruits, vegetables, meats, and
fish. These intake rates are based on the amount of
household food consumption as well as age-specific
serving size data.
        USDA estimated preparation losses forvarious
foods (USDA, 1975).  For meats, a net cooking loss,
which includes dripping and volatile losses, and a net
post-cooking loss, which involves losses from cutting,
bones,  excess fat, scraps and juices, were derived for a
variety of cuts and cooking methods. For total meats,
U.S. EPA has averaged these losses across all meat
types, cuts and cooking methods to obtain a mean net
cooking loss and a mean net post-cooking loss. Mean
percentage values for all meats and fish are provided in
Table  13-5.  For individual  fruits  and vegetables,
USDA (1975) also  gave cooking and  post-cooking
losses.  These data, averaged across all types of fruits
and vegetables  to give mean net cooking and  post
cooking losses, are also provided in Table 13-5.
        The following formula can be used to convert
the home-produced intake rates tabulated here to rates
reflecting actual consumption:
= Ix jl-L
II- L2 i
                                      (Eqn. 13-3)
where:
        IA = the adjusted intake rate;
        I = the tabulated intake rate;
        L! = the cooking or preparation loss; and
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                                                      Chapter 13 - Intake of Home-Produced Foods
        L2 = the post-cooking loss.

        For fruits, corrections based on post-cooking
losses only apply to fruits that are eaten  in cooked
forms.   For  raw forms  of the  fruits,  paring  or
preparation loss data should be used to correct for
losses from removal of skin, peel, core,  caps, pits,
stems, and defects, or draining of liquids  from canned
or frozen forms.
        In calculating ingestion exposure, assessors
should use consistent forms (e.g./'as-consumed" or dry
weight)  in combining intake rates with  contaminant
concentrations, as discussed in Chapter  9  of this
handbook.
        The USDA 1987-1988 NFCS household data
were also used to estimate the fraction of household
intake that can be attributed to home-produced foods
(Table 13-6).  The analysis was conducted forthe major
food groups (i.e., total meat, dairy, fruits, vegetables,
and fish), as well as for a variety of individual food
items (e.g., apples, tomatoes, beef, etc.).  The fraction
of intake that was home-produced was calculated as the
ratio  of total  intake  of  the  home-produced food
item/group by the survey population to the total intake
of all forms of the food by the survey population. The
food codes  used in this  analysis are presented  in
Appendix 13-B.
        The  USDA NFCS data  set  is the  largest
publicly available  source  of information  on home-
produced food consumption habits in the United States.
The  advantages of using this data set are that it is
expected to be representative of the U.S. population and
that it provides information on a wide variety of food
groups.   However, the data collected  by the USDA
NFCS are based on short-term dietary recall and the
intake distributions generated from this data set may not
accurately reflect long-term intake patterns, particularly
with respect to the tails (extremes) of the distributions.
Also, the two survey components (i.e.,  household and
individual) do not define food  items/groups in  a
consistent manner; as  a result,  some errors  may be
introduced into these analyses because the two survey
components are linked.  The results presented here may
also be biased by assumptions that are  inherent in the
analytical method utilized.  The analytical method may
not capture all high-end consumers within households
 because average serving sizes are used in calculating
 the proportion of home-produced food consumed by
 each household member. Thus, for instance, in a two-
 person household where one member had high intake
 and one had low intake, the method used here would
 assume that both members had an equal and moderate
 level of intake. In addition, the analyses assume that all
 family members  consume  a portion of the home-
 produced food used within the household.  However,
 not all family  members may consume  each home-
 produced food  item and serving  sizes allocated here
 may not be  entirely representative of the  portion of
 household foods consumed by each family member. As
 was mentioned earlier, no analyses were performed for
 children under 1 year age.
         The preparation loss factors discussed above
 are  intended  to  convert  intake   rates  based on
 "household consumption" to rates reflective of what
 individuals actually consume. However, these factors
 do not include losses to spoilage,  feeding to pets, food
 thrown away, etc. It should also be noted that because
 this analysis is based on the 1987-1988 NFCS, it may
 not reflect recent changes in food consumption patterns.
 The low response rate associated with the 1987-1988
 NFCS also contributes to the uncertainty of the home-
 produced intake rates generated using these data.

 13.4    REFERENCES FOR CHAPTER 13
 USDA  (1975) Food yields summarized by different
         stages of preparation. Agricultural Handbook
         No. 102. Washington, DC.  U.S. Department
         of Agriculture, Agriculture Research Service.
 USDA   (1987-1988)  Dataset:    Nationwide  Food
         Consumption  Survey  1987/88  Household
         Food  Use.    Washington,  DC.     U.S.
         Department of Agriculture.  1987/88 NFCS
         Database.
 USDA   (1992) Changes  in food consumption and
         expenditures in American households during
         the   1980's.    Washington,  DC.     U.S.
         Department  of Agriculture.    Statistical
         Bulletin No. 849.
 USDA (1993) Food and nutrient intakes by individuals
         in the United States, 1  Day, 1987-1988.
         Nationwide Food Consumption Survey 1987-
         1988, NFCS Report No.  87-1-1.
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Chapter 13 - Intake of Home-Produced Foods
USDA (1 994) Food consumption and dietary levels of
        households in the United States, 1987-1988.
        U.S. Department of Agriculture, Agricultural
        Research Service. Report No. 87-H-l.
U.S. EPA  (1989) Risk Assessment Guidance for
        Superfund (RAGS): Volume I, Human Health
        Evaluation Manual, Part A. Office of Solid
        Waste and Emergency Response, Washington,
        DC. EPA/540/1-89/002. Available online at
        http://www.epa.gov/oswer/riskassessment/ra
        gsa/index.htm
U.S. EPA  (1991)  Record of Decision.   ROD ID
        EPA/ROD/R10-91-029.
U.S. EPA  (1993)  Record of Decision.   ROD ID
        EPA/ROD/R04-93-166.
U.S. EPA (1 994) Validation strategy for the Integrated
        Exposure Uptake Biokinetic Model for Lead
        in  Children.   Office of Solid  Waste and
        Emergency   Response,   Washington  DC.
        EPA/540/R-94-039.  Available   online  at
        http://www.epa.gov/snperfiind/lead/products
        /valstrat.pdf
U.S. EPA (1996) Soil Screening Fact Sheet Guidance.
        EPA/540/F-95/041.   Available  online  at
        http://www.epa.gov/superfund/health/conme
        dj_a/_sgjl/jndexjitiii
U.S. EPA (1997) Exposure Factors Handbook. Office
        of Research and Development, Washington,
        DC. EPA/600/P-95/002F. Available online at
        fm?deid= 12464
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                                        Chapter 13 - Intake of Home-Produced Foods

Age Group
<1 year
1 to 2 years
3 to 5 years
6 to 1 1 years
12 to 19 years
Total
weighted -
unweighted -
Table 13-3. Weighted and Unweighted Number of Observations (Individuals)
Child-specific Analysis of Food Intake
Number of Observations
weighted
2,814,000
5,699,000
8,103,000
16,711,000
20,488,000
53,815,000
Weighted number of observations.
Unweighted number of observations.
for NFCS Data Used in

unweighted
156
321
461
937
1,084
2,959

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Chapter 13 - Intake of Home-Produced Foods












































































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Child-Specific Exposure Factors Handbook
September 2008	
Page
13-11

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                                                            Child-Specific Exposure Factors Handbook

                                                        Chapter 13 - Intake of Home-Produced Foods
                              Table 13-5. Percent Weight Losses from Food Preparation
     Food Group              Mean Net Preparation/Cooking Loss (%)           Mean Net Post Cooking (%)
     Meats3                                  29.7"                                    29.T

     Fish and shellfish"                        31.5"                                    10.5°

     Fruits                                  25.4°                                    30.5f

     Vegetables8                             12.4"                                     22'
     a        Averaged over various cuts and preparation methods for various meats including beef, pork, chicken, turkey,
             lamb, and veal.
     b        Includes dripping and volatile losses during cooking.
     0        Includes losses from cutting,  shrinkage, excess fat, bones, scraps, and juices.
     d        Averaged over a variety offish and shellfish, to include: bass, bluefish, butterfish, cod, flounder, haddock,
             halibut, lake trout, mackerel,  perch, porgy, red snapper, rockfish, salmon, sea trout, shad, smelt, sole, spot,
             squid, swordfish steak, trout,  whitefish, clams, crab, crayfish, lobster, oysters, and shrimp and shrimp
             dishes.
     °        Based on preparation losses.  Averaged over apples, pears, peaches, strawberries, and oranges. Includes
             losses from removal of skin or peel, core or pit, stems or caps, seeds, and defects. Also, includes losses from
             removal of drained liquids from canned or frozen forms.
     f        Averaged over apples and peaches. Include losses from draining cooked forms.
     8        Averaged over various vegetables, to include: asparagus, beets, broccoli, cabbage, carrots, corn, cucumbers,
             lettuce, lima beans,  okra, onions, green peas, peppers, pumpkins, snap beams, tomatoes, and potatoes.
     h        Includes losses due  to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling, slicing,
             husking, chopping, and dicing and gains from the addition of water, fat, or other ingredients. Averaged over
             various preparation  methods.
     1        Includes losses from draining or removal of skin. Based on potatoes only.

     Source:  U.S. EPA, 1997  (Derived from USDA, 1975).
Page                                                      Child-Specific Exposure Factors Handbook
13-12	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods



Total Fruits
Apples
Peaches
Pears
Strawberries
Other Berries
Citrus
Other


Total Vegetables
Asparagus
Beets
Broccoli
Cabbage
Carrots
Corn
Cucumbers
Lettuce
Lima Beans
Okra
Onions
Peas
Peppers
Pumpkin
Snap Beans
Tomatoes
White Potatoes

Total Meats
Beef
Game
Pork
Poultry

Total Dairy
Eggs

Total fish
= No data.
Table 13-6. Fraction of Food Intake
All Households

0.04
0.030
0.147
0.067
0.111
0.217
0.038
0.042
All Households

0.068
0.063
0.203
0.015
0.038
0.043
0.078
0.148
0.010
0.121
0.270
0.056
0.069
0.107
0.155
0.155
0.184
0.038
All Households
0.024
0.038
0.276
0.013
0.011
All Households
0.012
0.014
All Households
0.094

that is Home-produced
Households who
garden
0.101
0.070
0.316
0.169
0.232
0.306
0.087
0.107
Households who
garden
0.173
0.125
0.420
0.043
0.099
0.103
0.220
0.349
0.031
0.258
0.618
0.148
0.193
0.246
0.230
0.384
0.398
0.090
Households who
raise animals/hunt
0.306
0.485
0.729
0.242
0.156
Households who
raise animals
0.207
0.146
Households who
fish
0.325


Households who farm

0.161
0.292
0.461
0.606
0.057
0.548
0.005
0.227
Households who farm

0.308
0.432
0.316
0.159
0.219
0.185
0.524
0.524
0.063
0.103
0.821
0.361
0.308
0.564
0.824
0.623
0.616
0.134
Households who farm
0.319
0.478
-
0.239
0.151
Households who farm
0.254
0.214
-
-

Source: U.S. EPA Analysis of 1987-1988 NFCS.
Child-Specific Exposure Factors Handbook                                      Page
September 2008	13-13

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
                                   APPENDIX 13A

           FOOD CODES AND DEFINITIONS USED IN CHILD-SPECIFIC ANALYSIS
     OF THE 1987-1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE RATES
Child-Specific Exposure Factors Handbook                                       Page
September 2008	13A-1

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                                                                   Child-Specific Exposure Factors Handbook

                                                               Chapter 13 - Intake of Home-Produced Foods
       Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDANFCS Data
                                        to Estimate Intake of Home-produced Foods
   Food Product
                                  Household Code/Definition1
                                                                                          Individual Code
                                                  MAJOR FOOD GROUPS
   Total Fruits
                    50-    Fresh Fruits
                             citrus
                             other vitamin-C rich
                             other fruits
                    512-   Commercially Canned Fruits
                    522-   Commercially Frozen Fruits
                    533-   Canned Fruit Juice
                    534-   Frozen Fruit Juice
                    535-   Aseptically Packed Fruit Juice
                    536-   Fresh Fruit Juice
                    542-   Dried Fruits
                    (includes baby foods)
         6-   Fruits
                citrus fruits and juices
                dried fruits
                other fruits
                fruits/juices & nectar
                fruit/juices baby food
         (includes baby foods)
Total Vegetables
                    48- Potatoes, Sweet potatoes
                    49- Fresh Vegetables
                           dark green
                           deep yellow
                           tomatoes
                           light green
                           other
                    511- Commercially Canned Vegetables
                    521- Commercially Frozen Vegetables
                    531- Canned Vegetable Juice
                    532- Frozen Vegetable Juice
                    537- Fresh Vegetable  Juice
                    538- Aseptically Packed Vegetable Juice
                    541- Dried Vegetables
                    (does not include soups, sauces, gravies, mixtures, and ready-
                    to-eat dinners; includes baby foods except mixtures/dinners)
         7-   Vegetables (all forms)
                white potatoes & PR starchy
                dark green vegetables
                deep yellow vegetables
                tomatoes and torn, mixtures
                other vegetables
                veg. and mixtures/baby food
                veg. with meat mixtures
         (includes baby foods; mixtures, mostly vegetables)
   Total Meats
                    44- Meat
                           beef
                           pork
                           veal
                           lamb
                           mutton
                           goat
                           game
                           lunch meat
                           mixtures
                    451- Poultry
                    (does not include soups, sauces, gravies, mixtures, and ready-
                    to-eat dinners; includes baby foods except mixtures)	
         20-  Meat, type not specified
         21-  Beef
         22-  Pork
         23-  Lamb, veal, game, carcass meat
         24-  Poultry
         25-  Organ meats, sausages, lunchmeats, meat
              spreads
         (excludes meat, poultry, and fish with non-meat
         items; frozen plate meals; soups and gravies with
         meat, poultry and fish base; and gelatin-based drinks;
         includes baby foods)
Page
13A-2
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDANFCS Data
to Estimate Intake of Home-produced Foods (continued)
Food Product

Total Dairy
Total Fish
Household Code/Definition1
MAJOR FOOD GROUPS
40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
452- Fish, Shellfish
various species
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and ready-
to-eat dinners)
Individual Code

1- Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
(includes regular fluid milk, human milk, imitation
milk products, yogurt, milk-based meal
replacements, and infant formulas)
26- Fish, Shellfish
various species and forms
(excludes meat, poultry, and fish with non-meat
items; frozen plate meals; soups and gravies with
meat, poultry and fish base; and gelatin-based drinks)
1 Food items within these categories that were identified by the household as being home-produced or home-caught (i.e., source code pertaining to home
produced foods) were included in the analysis.
Child-Specific Exposure Factors Handbook
September 2008	
 Page
13A-3

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
                                  APPENDIX 13B

     1987-1988 NFCS FOOD CODES AND DEFINITIONS USED IN ESTIMATING FRACTION OF
                 HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED
Child-Specific Exposure Factors Handbook                                       Page
September 2008	13B-1

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                                                                  Child-Specific Exposure Factors Handbook

                                                               Chapter 13 - Intake of Home-Produced Foods
              Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household Data to
                                      Estimate Fraction of Food Intake that is Home-produced
    Food  Product
                                                                   Household Code/Definition
                                                   INDIVIDUAL FOODS
    White Potatoes
                                      4811-  White Potatoes, fresh
                                      4821-  White Potatoes, commercially canned
                                      4831-  White Potatoes, commercially frozen
                                      4841-  White Potatoes, dehydrated
                                      4851-  White Potatoes, chips, sticks, salad
                                      (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
    Peppers
4913-    Green/Red Peppers, fresh
5111201  Sweet Green Peppers, commercially canned
5111202  HotChili Peppers, commercially canned
5211301  Sweet Green Peppers, commercially frozen
5211302  Green Chili Peppers, commercially frozen
5211303  Red Chili Peppers, commercially frozen
5413112  Sweet Green Peppers, dry
5413113  Red Chili Peppers, dry
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
    Onions
                                      4953-  Onions, Garlic, fresh
                                             onions
                                             chives
                                             garlic
                                             leeks
                                      5114908   Garlic Pulp, raw
                                      5114915   Onions, commercially canned
                                      5213722   Onions, commercially frozen
                                      5213723   Onions with Sauce, commercially frozen
                                      5413103 Chives, dried
                                      5413105 Garlic Flakes, dried
                                      5413110 Onion Flakes, dried
                                      (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners)
    Corn
                                      4956-  Corn, fresh
                                      5114601   Yellow Corn, commercially canned
                                      5114602   White Corn, commercially canned
                                      5114603   Yellow Creamed Corn, commercially canned
                                      5114604   White Creamed Corn, commercially canned
                                      5114605   Corn on Cob, commercially canned
                                      5114607   Hominy, canned
                                      5115306   Low Sodium Corn, commercially canned
                                      5115307   Low Sodium Cr. Corn, commercially canned
                                      5213501   Yellow Corn on Cob, commercially frozen
                                      5213502   Yellow Corn off Cob, commercially frozen
                                      5213503   Yell. Corn with Sauce, commercially frozen
                                      5213504   Corn with other Veg., commercially frozen
                                      5213505   White Corn on Cob, commercially frozen
                                      5213506   White Corn off Cob, commercially frozen
                                      5213507   Wh. Corn with Sauce, commercially frozen
                                      5413104   Corn, dried
                                      5413106   Hominy, dry
                                      5413603   Corn, instant baby food
                                      (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby food)e
Page
13B-2
                            Child-Specific Exposure Factors Handbook
                           	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
                Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to
                                  Estimate Fraction of Food Intake that is Home-produced (continued)
        Food Product
                                                                    Household Code/Definition
       Apples
5031-  Apples, fresh
5122101  Applesauce with sugar, commercially canned
5122102  Applesauce without sugar, comm. canned
5122103  Apple Pie Filling, commercially canned
5122104  Apples, Applesauce, baby/jr., comm. canned
5122106  Apple Pie Filling, Low Cal., comm. canned
5223101  Apple Slices, commercially frozen
5332101  Apple Juice, canned
5332102  Apple Juice, baby, Comm. canned
5342201  Apple Juice, comm. frozen
5342202  Apple Juice, home frozen
5352101  Apple Juice, aseptically packed
5362101  Apple Juice, fresh
5423101  Apples, dried
(includes baby food; except mixtures)
        Tomatoes
                                          4931-  Tomatoes, fresh
                                          5113-  Tomatoes, commercially canned
                                          5115201  Tomatoes, low sodium, commercially canned
                                          5115202  Tomato Sauce, low sodium, comm. canned
                                          5115203  Tomato Paste, low sodium, comm. canned
                                          5115204  Tomato Puree, low sodium,  comm. canned
                                          5311-  Canned Tomato Juice and Tomato Mixtures
                                          5321-  Frozen Tomato Juice
                                          5371-  Fresh Tomato Juice
                                          5381102  Tomato Juice, aseptically packed
                                          5413115  Tomatoes, dry
                                          5614-  Tomato Soup
                                          5624-  Condensed Tomato Soup
                                          5654-  Dry Tomato Soup
                                          (does not include mixtures, and ready-to-eat dinners)
        Snap Beans
4943-    Snap or Wax Beans, fresh
5114401 Green or Snap Beans, commercially canned
5114402 Wax orYellow Beans, commercially canned
5114403 Beans, baby/jr., commercially canned
5115302 Green Beans, low sodium, comm. canned
5115303 Yell. orWax Beans, low sod., comm. canned
5213301 Snap or Green Beans, comm. frozen
5213302 Snap or Green w/sauce, comm. frozen
5213303 Snap or Green Beans w/other veg., comm. fr.
5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr.
5213305 Wax or Yell. Beans, comm. frozen
(does not include soups, mixtures, and ready-to-eat dinners; includes baby foods)
       Beef
                                          441-Beef
                                          (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
                                          foods except mixtures)
       Pork
                                          442- Pork
                                          (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
                                          foods except mixtures)
Child-Specific Exposure Factors Handbook
September 2008	
                                                                         Page
                                                                        13B-3

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                                           Child-Specific Exposure Factors Handbook

                                        Chapter 13 - Intake of Home-Produced Foods


Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to Estimate Fraction
of Food Intake that is Home-produced (continued)
Food Product
Game
Poultry
Eggs
Broccoli
Carrots
Pumpkin
Asparagus
Lima Beans
Household Code/Definition
445- Variety Meat, Game
(does not include soups., sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
451 -Poultry
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
46- Eggs (fresh equivalent)
fresh
processed eggs, substitutes
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4912- Fresh Broccoli (and home canned/froz.)
5111203 Broccoli, comm. canned
521 12- Comm. Frozen Broccoli
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4921- Fresh Carrots (and home canned/froz.)
51121- Comm. Canned Carrots
5115101 Carrots, Low Sodium, Comm. Canned
52121- Comm. Frozen Carrots
5312103 Comm. Canned Carrot Juice
5372102 Carrot Juice Fresh
5413502 Carrots, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4922- Fresh Pumpkin, Winter Squash (and home canned/froz.)
51122- Pumpkin/Squash, Baby or Junior, Comm. Canned
52122- Winter Squash, Comm. Frozen
5413504 Squash, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4941- Fresh Asparagus (and home canned/froz.)
5114101 Comm. Canned Asparagus
5115301 Asparagus, Low Sodium, Comm. Canned
52131- Comm. Frozen Asparagus
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4942- Fresh Lima and Fava Beans (and home canned/froz.)
51 14204 Comm. Canned Mature Lima Beans
51 14301 Comm. Canned Green Lima Beans
51 15304 Comm. Canned Low Sodium Lima Beans
52132- Comm. Frozen Lima Beans
541 1 1- Dried Lima Beans
541 1306 Dried Fava Beans
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures; does not include succotash)
Page
13B-4
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 13 - Intake of Home-Produced Foods
Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household Data to
Estimate Fraction of Food Intake that is Home-produced (continued)
Food Product
Cabbage
Lettuce
Okra
Peas
Cucumbers
Beets
Strawberries
Household Code/Definition
4944- Fresh Cabbage (and home canned/froz.)
4958601 Sauerkraut, home canned or pkgd
5114801 Sauerkraut, comm. canned
5114904 Comm. Canned Cabbage
5114905 Comm. Canned Cabbage (no sauce; incl. baby)
5115501 Sauerkraut, low sodium., comm. canned
5312102 Sauerkraut Juice, comm. canned
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4945- Fresh Lettuce, French Endive (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4946- Fresh Okra (and home canned/froz.)
5114914 Comm. Canned Okra
5213720 Comm. Frozen Okra
5213721 Comm. Frozen Okra with Oth. Veg. & Sauce
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4947- Fresh Peas (and home canned/froz.)
51147- Comm Canned Peas (incl. baby)
5115310 Low Sodium Green or English Peas (canned)
5115314 Low Sod. B lackey e, Gr. or Imm. Peas (canned)
51 14205 B lackeyed Peas, comm. canned
52134- Comm. Frozen Peas
5412- Dried Peas and Lentils
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4952- Fresh Cucumbers (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
4954- Fresh Beets (and home canned/froz.)
51145- Comm. Canned Beets (incl. baby)
5115305 Low Sodium Beets (canned)
5213714 Comm. Frozen Beets
5312104 Beet Juice
(does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby
foods except mixtures)
5022- Fresh Strawberries
5122801 Comm. Canned Strawberries with sugar
5122802 Comm. Canned Strawberries without sugar
5122803 Canned Strawberry Pie Filling
5222- Comm. Frozen Strawberries
(does not include ready-to-eat dinners; includes baby foods except mixtures)
Child-Specific Exposure Factors Handbook
September 2008	
 Page
13B-5

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                                                                 Child-Specific Exposure Factors Handbook

                                                              Chapter 13 - Intake of Home-Produced Foods
                Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USD A NFCS Household Data to
                                  Estimate Fraction of Food Intake that is Home-produced (continued)
        Food Product
                                                                    Household Code/Definition
        Other Berries
                                          5033- Fresh Berries Other than Strawberries
                                          5122804  Comm. Canned Blackberries with sugar
                                          5122805  Comm. Canned Blackberries without sugar
                                          5122806  Comm. Canned Blueberries with sugar
                                          5122807  Comm. Canned Blueberries without sugar
                                          5122808  Canned Blueberry Pie Filling
                                          5122809  Comm. Canned Gooseberries with sugar
                                          5122810  Comm. Canned Gooseberries without sugar
                                          5122811  Comm. Canned Raspberries with sugar
                                          5122812  Comm. Canned Raspberries without sugar
                                          5122813  Comm. Canned Cranberry Sauce
                                          5122815  Comm. Canned Cranberry-Orange Relish
                                          52233-   Comm. Frozen Berries (not strawberries)
                                          5332404  Blackberry Juice (home and comm. canned)
                                          5423 114  Dried Berries (not strawberries)
                                          (does not include ready-to-eat dinners; includes baby foods except mixtures)
        Peaches
                                          5036- Fresh Peaches
                                          51224-   Comm. Canned Peaches (incl. baby)
                                          5223601  Comm. Frozen Peaches
                                          5332405  Home Canned Peach Juice
                                          5423105  Dried Peaches (baby)
                                          5423106  Dried Peaches
                                          (does not include ready-to-eat dinners; includes baby foods except mixtures)
        Pears
                                          5037- Fresh Pears
                                          51225-   Comm. Canned Pears (incl. baby)
                                          5332403  Comm. Canned Pear Juice, baby
                                          5362204  Fresh Pear Juice
                                          5423107  Dried Pears
                                          (does not include ready-to-eat dinners; includes baby foods except mixtures)
        Citrus Fruits
                                          501-   Fresh Citrus Fruits
                                          5121   Comm. Canned Citrus Fruits
                                          5331   Canned Citrus and Citrus Blend Juice
                                          5341   Frozen Citrus and Citrus Blend Juice
                                          5351   Aseptically Packed Citrus and Citr. Blend Juice
                                          5361   Fresh Citrus and Citrus Blend Juice
                                          (includes baby foods; excludes dried fruits)
        Other
        Fruits
502-   Fresh Other Vitamin C-Rich Fruits
503-   Fresh Other Fruits
5122-  Comm. Canned Fruits Other than Citrus
5222-  Frozen Strawberries
5332-  Frozen Other than Citr. or Vitamin C-Rich Fr.
5333-  Canned Fruit Juice Other than Citrus
5352-  Frozen Juices Other than Citrus
5362-  Aseptically Packed Fruit Juice Other than Citr.
542-   Fresh Fruit Juice Other than Citrus Dry Fruits
(includes baby foods; excludes dried fruits)
Page
13B-6
                       Child-Specific Exposure Factors Handbook
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Child-Specific Exposure Factors Handbook

Chapter 14 - Total Food Intake	
                               TABLE OF CONTENTS
14    TOTAL DIETARY INTAKE	14-1
      14.1   INTRODUCTION	14-1
      14.2   RECOMMENDATIONS 	14-1
      14.3   KEY STUDY OF TOTAL FOOD INTAKE	14-4
            14.3.1  U.S. EPA, 2007 	14-4
      14.4   REFERENCES FOR CHAPTER 14	14-5
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                                                     Child-Specific Exposure Factors Handbook

                                                    	Chapter 14 - Total Food Intake
                                         LIST OF TABLES

Table 14-1.     Recommended Values for Per Capita Total Intake of Foods, As Consumed  	14-2
Table 14-2.     Confidence in Recommendations for Total Food Intake	14-3
Table 14-3.     Per Capita Total Food Intake	14-6
Table 14-4.     Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed)  . . 14-7
Table 14-5.     Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed)14-ll
Table 14-6.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Food Intake	14-15
Table 14-7.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Meat Intake	14-19
Table 14-8.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Meat and Dairy Intake .... 14-23
Table 14-9.     Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Fish Intake	14-27
Table 14-10.    Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Fruit and Vegetable Intake . 14-31
Table 14-11.    Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
               for Individuals with Low-end, Mid-range, and High-end Total Dairy Intake	14-35
Page
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Child-Specific Exposure Factors Handbook

Chapter 14 - Total Food Intake	
14    TOTAL FOOD INTAKE
14.1  INTRODUCTION
      The U.S. food supply is generally considered to
be one  of the safest  in  the world.  Nevertheless,
contamination of foods may occur as a  result of
environmental pollution of the air, water, or soil, or the
intentional use of chemicals such as pesticides or other
agrochemicals.  Ingestion of contaminated foods is a
potential pathway of exposure to such contaminants
among children. To assess chemical exposure through
this pathway, information on food ingestion rates is
needed.  Per capita and consumers only data on food
consumption rates for various food items  and food
categories are reported in Chapters 9 through 13 of
this handbook. These intake rates were estimated by
U.S. EPA using  databases developed by  the U.S.
Department of Agriculture (USD A). U.S. EPA (2007)
expanded the analysis of food intake  in  order to
examine individuals'  food consumption habits in
greater  detail.    Using  data from the  USDA's
Continuing  Survey of Food Intake by Individuals
(CSFII)  conducted in 1994-1996, 1998, U.S.  EPA
(2007) derived distributions to characterize (1) total
food  intake  among various groups  in  the  U.S.
population, subdivided by age, race, geographic region,
and urbanization;  (2) the contribution of various food
categories (e.g., meats, grains, vegetables, etc.) to total
food intake  among these populations; and (3) the
contribution of various food categories to total food
intake among individuals exhibiting low- or high-end
consumption patterns of a specific food category (e.g.,
individuals below  the 10th percentile or above the 90th
percentile for fish consumption).  These data may be
useful for assessing exposure  among populations
exhibiting lower or higher than usual intake  of certain
types of foods (e.g., people who eat little or no meat, or
people who eat large quantities offish).
      The recommendations for total food intake rates
are provided in the next section, along with a summary
of the confidence ratings for these recommendations.
Following the recommendations, the key study on total
food intake is summarized.
recommended intake rates for children are based on
data from the U. S. EPA (2007) analysis of CSFII data.
However, the analysis presented in U.S. EPA (2007)
was  conducted  before  U.S.  EPA  published  the
guidance entitled Selecting Age Groups for Monitoring
and Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005).  As a result, the age
groups used for children in U.S. EPA (2007) were not
entirely consistent with the age groups recommended
in the 2005 guidance.  Therefore, a re-analysis of the
data was  conducted to  conform with  U.S.  EPA's
recommended age groups for children.
      Because these recommendations are based on
1994-96 and 1998 CSFII data, they may not reflect
recent changes that may have occurred in consumption
patterns.  In addition, these distributions are based on
data collected over  a 2-day period and  may  not
necessarily reflect the long-term distribution of average
daily intake rates. However,  for the broad categories
of foods used in this analysis  (e.g., total foods, total
fruits, total vegetables, etc.), because they are typically
eaten on  a daily basis  throughout  the year with
minimal seasonality, the short- term distribution maybe
a  reasonable   approximation  of  the  long-term
distribution, although it will  display  somewhat
increased  variability.  This  implies that  the  upper
percentiles shown here will tend to overestimate the
corresponding  percentiles  of the  true  long-term
distribution.
14.2  RECOMMENDATIONS
      A summary of recommended values for total
food intake, on an as-consumed basis, is presented in
Table  14-1.    The  confidence ratings  for  these
recommendations are presented  in Table 14-2.  The
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                                           14-1

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 14 - Total Food Intake
Table 14-1.

Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16 to <21 years
Note: Total food intake was
dairy, meats, fish, eg
nuts and nut products
groups. Also, human
Recommended Values for Per Capita Total Food Intake, As Consumed
Mean

20
16
28
56
90
74
61
40
24
18
95<*Percentile ^M^
g/kg-day Percentiles
61
40
65
134
161
See Table 14-3
126
102
70
45
35
defined as intake of the sum of all foods in the following
gs, grains, vegetables, fruits, and fats. Beverages, sugar,
were not included because they could not be categorized
milk intake was not included.
Source



U.S. EPA re-analysis of
CSFII 1994-96, 98 data
(Based on U.S. EPA,
2007)



major food categories:
candy, and sweets, and
into the major food
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Chapter 14 - Total Food Intake	
Table 14-2.
General Assessment Factors
Soundness
Adequacy of Approach
Minimal (or Defined) Bias
Applicability and Utility
Exposure Factor of Interest
Representativeness
Currency
Data Collection Period
Clarity and Completeness
Accessibility
Reproducibility
Quality Assurance
Variability and Uncertainty
Variability in Population
Uncertainty
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Confidence in Recommendations for Total Food Intake
Rationale
The survey methodology was adequate and the analytical
approach was competently executed. The study size was very
large; sample size varied with age. The response rate was
good. The key study analyzed primary data on recall of
ingestion.
No direct measurements were taken. The study relied on
survey data.
The analysis was specifically designed to address food intake.
The population studied was representative of the U.S.
population.
The data used were the most current data publicly available
at the time the analysis was conducted for the handbook.
Ingestion rates were estimated based on short-term data
collected in the CSFII 1994-96, 1998.
The CSFII data are publicly available. The U.S. EPA (2007)
report is available online.
The methodology was clearly presented; enough information
was included to reproduce results.
Quality assurance methods were not described in the study
report.
Short term distributions were provided. The survey was not
designed to capture long term day-to-day variability.
The survey data were based on recall over a 2-day period.
Other sources of uncertainty were minimal.
The USDA CSFII survey received a high level of peer review.
U.S. EPA (2007) analysis was also peer-reviewed; however,
the re-analysis of these data using the new age categories was
not peer reviewed outside the Agency.
Only one key study was available for this factor


Rating
High
Medium
Medium
Medium
Medium
Medium
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                                                       	Chapter 14 - Total Food Intake
14.3  KEY STUDY OF TOTAL FOOD INTAKE
14.3.1 U.S.  EPA  Re-analysis of  1994-96, 1998
      CSFII, Based on U.S. EPA (2007) - Analysis
      of Total Food Intake  and Composition of
      Individual's Diet Based on USDA's 1994-96,
      1998 Continuing Survey of Food Intakes by
      Individuals (CSFII)
      U.S. EPA's National Center for Environmental
Assessment (NCEA) conducted an analysis to evaluate
the total food intake of individuals in the United States
using data from the USDA's 1994-1996, 1998 CSFII
(USDA,  2000) and  U.S. EPA's  Food Commodity
Intake Database  (FCID) (U.S. EPA,  2000).   The
1994-96 CSFII and its 1998 Supplemental Children's
Survey were designed to obtain data from a statistically
representative sample of noninstitutionalized persons
living in the United States.  Survey participants were
selected using a multistage process. The respondents
were interviewed twice to collect information on food
consumption during two non-consecutive days.  For
both survey days,  data were collected by an in-home
interviewer.  The day two interview was conducted 3
to 10 days later and on a different day of the week. Of
the   more  than  20,000   individuals  surveyed,
approximately 10,000 were under 21 years of age, and
approximately 9,000 were under the age of 11.  The
1994-96  survey and 1998 supplement are referred to
collectively as CSFII  1994-96, 1998.  Each individual
in the survey was  assigned a sample weight based on
his or her demographic data; these weights were taken
into  account when calculating mean and percentile
values  of  food   consumption   for   the  various
demographic categories that  were analyzed in the
study.  The sample  weighting process used in the
CSFII 1994-96, 1998 are discussed in detail in USDA
(2000).
      For the analysis of  total food  intake, food
commodity  codes provided in U.S.  EPA's Food
Commodity Intake Database (FCID) (U. S. EPA, 2000)
were used to translate as-eaten foods (e.g., beef stew)
identified by USDA food codes in the CSFII data set
into  food commodities (e.g., beef, potatoes, carrots,
etc.).  The method used to translate USDA food codes
into U.S. EPA commodity codes is discussed in detail
in USDA (2000).   The U.S. EPA commodity codes
were  assigned to  broad food categories  (e.g., total
meats, total vegetables, etc.) for use in the analysis.
Total food intake was defined as intake of the sum of
 all foods in the following major food categories: dairy,
 meats, fish, eggs, grains, vegetables, fruits, and fats.
 Beverages, sugar, candy, and sweets, and nuts and nut
 products were not included because they could not be
 categorized into the major food groups. Also,  human
 milk intake was not included.  Total food intake was
 calculated for various age groups of children.  Percent
 consuming,  mean, standard error, and a range of
 percentile values were calculated on the basis of grams
 of food per kilogram of body weight per day (g/kg-day)
 and on the basis of grams per day (g/day).  In addition
 to total food intake, intake of the various major food
 groups for the various age groups in units of g/day and
 g/kg-day were also estimated for comparison  to total
 intake.
       To evaluate variability in the contributions of
 the major food groups to total food intake, individuals
 were ranked from lowest to highest, based on total food
 intake. Three subsets of individuals were defined, as
 follows: a group at the low end of the distribution of
 total intake  (i.e., below the 10th percentile of total
 intake), a central group (i.e., the 45th to 55th percentile
 of total intake), and a group at the high end of the
 distribution  of total intake  (i.e., above the 90th
 percentile of total intake).  Mean total food intake (in
 g/day and g/kg-day), mean intake of each of the major
 food groups (in g/day and g/kg-day), and the percent of
 total food intake that  each of these food  groups
 represents was  calculated  for  each  of  the three
 populations (i.e., individuals with low-end, central,
 and high-end total food intake).  A similar analysis
 was  conducted  to estimate the contribution  of the
 major food groups to total food intake for individuals
 at the  low-end, central,  and high-end   of  the
 distribution of total  meat intake, total dairy  intake,
 total meat and dairy intake, total fish intake, and total
 fruit and vegetable intake. For example, to evaluate
 the variability in the diets of individuals at the low-
 end, central range, and high-end of the distribution of
 total meat intake,  survey individuals were  ranked
 according to their reported total  meat intake.   Three
 subsets of individuals were formed as described above.
 Mean total food intake,  intake of the major food
 groups, and the percent of total food intake represented
 by each of the major food groups were tabulated. U.S.
 EPA (2007) presented the results of the analysis for the
 following age groups: <1 year,  1 to  2 years,  3 to 5
Page
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Child-Specific Exposure Factors Handbook

Chapter 14 - Total Food Intake	
years, 6 to 11 years, and 12 to 19 years. The data were
tabulated in units of g/kg-day and g/day.
      In  order to  conform  to  the standard  age
categories recommended in Guidance on SelectingAge
Groups for Monitoring  and Assessing Childhood
Exposures to Environmental Contaminants (U. S. EPA,
2005) and used in this handbook, each of the tables
from U.S. EPA (2007) was modified by re-analyzing
the source data and applying the new age categories
(i.e., <1 month, 1 to <3 months, 3 to <6 months, 6 to
<12 months, 1 to <2  years, 2 to < 3 years, 3 to  < 6
years, 6 to < 11 years, 11 to < 16 years, and 16 to < 21
years). The results of this  re-analysis are presented in
Tables 14-3 through 14-11. Distributions of total food
intake are presented in Table 14-3  in units of g/day
and g/kg-day.  Tables 14-4 and 14-5 compare total
food intake to intake of the various major food groups
for the various age groups in units of g/day and g/kg-
day, respectively.  It should be noted that some U.S.
EPA commodity codes are listed under more than one
food category.  For this reason, in the tables, the intake
rates  for  the individual food categories  do  not
necessarily add up  to the  figure given for total food
intake (U.S. EPA, 2007).  Also, data are not reported
for food groups for which  there were less than 20
consumers in  a particular age group.  Tables 14-6
through 14-11 present the contributions of the major
food groups to total food intake for individuals (in the
various age groups) at the  low-end, central, and high-
end of the distribution of total food  intake (Table 14-
6), total meat intake (Table 14-7), total meat and dairy
intake (Table 14-8), total fish intake (Table 14-9), total
fruit and  vegetable intake (Table 14-10), and total
dairy intake (Table  14-11) in units of g/day and g/kg-
day.   For each of the three classes of  consumers,
consumption  of nine different food  categories is
presented  (i.e., total foods, dairy, meats,  fish,  eggs,
grains, vegetables, fruits,  and fats).  For example, in
Table  14-9 one will find the mean consumption of
meats, eggs, vegetables, etc. for individuals  with an
unusually high (or low or average) consumption of
fish.
      As discussed in previous chapters, the 1994-96,
98 CSFII data set have both advantages and limitations
with regard to estimating food intake rates. The large
sample size (more than 20,000 persons; approximately
10,000 children) is sufficient to allow categorization
within narrowly defined age categories.  In addition,
the survey was designed to obtain a statistically valid
sample of the entire United States  population that
included children and low income groups. However,
the survey design is of limited utility for assessing
small and potentially at-risk subpopulations based on
ethnicity, medical status, geography, or other factors
such as activity level. Another limitation is that data
are based on a two-day survey period and, as such, may
not accurately reflect long-term eating patterns.  This
is  particularly true  for the tails (extremes) of the
distribution of food intake.

14.4  REFERENCES FOR CHAPTER 14
USDA (2000) 1994-96, 1998  Continuing survey of
      food intakes by individuals (CSFII). CD-ROM.
      Agricultural   Research   Service,   Beltsville
      Human Nutrition Research Center, Beltsville,
      MD. Available from the National Technical
      Information Service, Springfield, VA; PB-2000-
      500027.
U.S. EPA (2000) Food commodity intake database
      [FCID  raw  data file].  Office of Pesticide
      Programs, Washington, DC. Available from the
      National  Technical  Information   Service,
      Springfield, VA;  PB2000-5000101.
U.S. EPA (2005) Guidance on selecting age groups
      for  monitoring   and  assessing  childhood
      exposures to environmental contaminants. U.S.
      Environmental Protection Agency, Washington,
      D.C., EPA/630/P-03/003F. Available from the
      National  Technical  Information   Service,
      Springfield,  VA,   and   online   at
      www. epa. gov/ncea.
U.S. EPA (2007) Analysis of total food intake and
      composition  of  individual's  diet based on
      USDA's 1994-96, 1998  continuing survey of
      food intakes by individuals (CSFII). National
      Center  for   Environmental  Assessment,
      Washington,  DC;  EPA/600/R-05/062F.
      Available   from  the   National  Technical
      Information   Service,  Springfield, VA,  and
      online at www.epa.gov/ncea.
Child-Specific Exposure Factors Handbook
September 2008	
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                                           14-5

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                                             Child-Specific Exposure Factors Handbook

                                             	Chapter 14 - Total Food Intake
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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 14 - Total Food Intake



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-------
Child-Specific Exposure Factors Handbook

Chapter 15 - Human Milk Intake	
                                      TABLE OF CONTENTS

15      HUMAN MILK INTAKE	15-1
        15.1    INTRODUCTION	15-1
        15.2    RECOMMENDATIONS	15-1
               15.2.1   Human Milk Intake	15-2
               15.2.2   Lipid Content and Lipid Intake	15-2
        15.3    KEY STUDIES ON HUMAN MILK INTAKE	15-10
               15.3.1   Pao et al, 1980	15-10
               15.3.2   Dewey and Lonnerdal, 1983	15-10
               15.3.3   Butte et al., 1984	15-10
               15.3.4   Neville et al., 1988	15-11
               15.3.5   Dewey et al., 1991a, b	15-11
               15.3.6   Butte, et al., 2000	15-12
               15.3.7   Arcus-Arth et al., 2005	15-12
        15.4    KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK	15-13
               15.4.1   Butte et al., 1984	15-13
               15.4.2   Mitoulas et al., 2002	15-14
               15.4.3   Mitoulas et al., 2003	15-14
               15.4.4   Arcus-Arth et al., 2005	15-15
               15.4.5   Kent et al., 2006	15-15
        15.5    RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK	15-16
               15.5.1   Maxwell and Burmaster, 1993	15-16
        15.6    OTHER FACTORS	15-16
               15.6.1   Population of Nursing Infants	15-16
               15.6.2   Intake Rates Based on Nutritional Status	15-19
               15.6.3   Frequency and Duration of Feeding	15-19
        15.7    REFERENCES FOR CHAPTER 15	15-19
Child-Specific Exposure Factors Handbook                                               Page
September 2008	15-i

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                                                        Child-Specific Exposure Factors Handbook

                                                        	Chapter 15 - Human Milk Intake
                                           LIST OF TABLES
Table 15-1.      Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed
                Infants	
Table 15-2.      Confidence in Recommendations for Human Milk Intake	
Table 15-3.      Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
                (mL/day)	
Table 15-4.      Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
                (mL/kg/day)	
Table 15-5.      Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day). . .
Table 15-6.      Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants
                (mL/kg/day)	
Table 15-7.      Daily Intakes of Human Milk	
Table 15-8.      Human Milk Intakes for Infants Aged 1 to 6 Months	
Table 15-9.      Human Milk Intake Among Exclusively Breast-fed Infants During  the First 4 Months
                of Life	
Table 15-10.     Human Milk Intake During a 24-hour Period	
Table 15-11.     Human Milk Intake Estimated by the Darling Study	
Table 15-12.     Mean Breastfed Infants Characteristics	
Table 15-13.     Mean Human Milk Intake of Breastfed Infants (mL/day)	
Table 15-14.     Feeding Practices by Percent of Infants	
Table 15-15.     Body Weight of Breastfed Infants	
Table 15-16.     AAP Dataset  Milk Intake Rates at Different Ages	
Table 15-17.     Average Daily Human Milk Intake (mL/kg day)	
Table 15-18.     Lipid Content of Human Milk and  Estimated Lipid Intake Among Exclusively Breast-fed
                Infants	
Table 15-19.     Human Milk Production and Composition Over the First 12 Months of Lactation	
Table 15-20.     Changes in Volume of Human Milk Produced and Milk Fat Content Over the First Year of
                Lactation	
Table 15-21.     Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation
                (g/100 g total fatty acids)	
Table 15-22.     Comparison of Lipid Content Assumptions (mL/kg-day)	
Table 15-23.     Distribution of Average Daily Lipid Intake (mL/kg day) assuming 4% Milk Lipid Content. .
Table 15-24.     Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age	
Table 15-25.     Socio-economic Characteristics of Exclusively Breast-fed Infants Born in 2004	
Tablel5-26.     Geographic-specific Breastfeeding Percent Rates Among Children Born in  2004	
Table 15-27.     Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6
                Months Old	
Table 15-28.     Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12
                Months Old	
Table 15-29.     Population Weighted Averages of Mothers Who Reported Selected Feeding Practices
                During the Previous 24-hours	
Table 15-30.     Racial and Ethnic Differences  in Proportion of Children Ever Breastfed, NHANES III
                (1988-1994)	
Table 15-31.     Racial and Ethnic Differences  in Proportion of Children Who Received Any Human Milk
                at 6 Months (NHANES III, 1988-1994)	
                                            .  15-3
                                            .  15-4

                                            .  15-6

                                            .  15-7
                                            .  15-8

                                            .  15-9
                                            15-22
                                            15-22

                                            15-23
                                            15-24
                                            15-25
                                            15-25
                                            15-26
                                            15-26
                                            15-27
                                            15-28
                                            15-29

                                            15-29
                                            15-30

                                            15-31

                                            15-32
                                            15-32
                                            15-33
                                            15-33
                                            15-34
                                            15-35

                                            15-36

                                            15-37

                                            15-38

                                            15-39

                                            15-40
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Chapter 15 - Human Milk Intake	
Table 15-32.    Racial and Ethnic Differences in Proportion of Children Exclusively Breastfed at 4
               Months (NHANES III, 1991-1994)	15-41
Table 15-33.    Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6
               Months of Age in the United States in 1989 and 1995, by Ethnic Background and Selected
               Demographic Variables	15-42
Table 15-34.    Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 6 and
               12 Months of Age in the United States in 2003, by Ethnic Background and Selected
               Demographic Variables	15-43
Table 15-35.    Number of Meals Per Day	15-44
Table 15-36.    Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD)	15-44
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Chapter 15 - Human Milk Intake	
15      HUMAN MILK INTAKE
15.1    INTRODUCTION
        Human lactation  is known to impart a wide
range  of  benefits  to  nursing  infants,  including
protection  against infection, increases  in  cognitive
development,  and  avoidance  of allergies  due to
intolerance to cow's  milk  (AAP, 2005).  Ingestion of
human milk has also  been  associated with a reduction
in risk of postneonatal death in the U.S. (Chen and
Rogan, 2004). The American Academy of  Pediatrics
recommends exclusive breastfeeding for approximately
the first six months and supports the continuation of
breastfeeding for the first  year and beyond  if desired
by  the mother and  child (AAP, 2005).   However,
contaminants may find their way into human milk of
lactating  mothers  because mothers are themselves
exposed. Thus, making human milk a potential source
of exposure to toxic substances for nursing infants.
Lipid soluble chemical compounds accumulate in body
fat and may be transferred to breast-fed infants in the
lipid portion of human milk. Water soluble  chemicals
may also  partition into the aqueous phase  and be
excreted  via human  milk.  Because nursing infants
obtain  most (if not all) of their dietary intake from
human milk,  they   are  especially  vulnerable to
exposures  to  these   compounds.   Estimating the
magnitude of the potential  dose to infants from human
milk requires  information on  the  milk intake  rate
(quantity of human milk consumed per day)  and the
duration (months) over which breast-feeding occurs.
Information on the fat content of human milk is also
needed for estimating dose from human milk residue
concentrations that have been indexed to lipid content.
        Several studies have generated data on human
milk intake.  Typically,  human milk intake has been
measured over a 24-hour period by weighing the infant
before  and after  each feeding  without  changing its
clothing (test weighing).  The sum of the difference
between the measured weights overthe 24-hourperiod
is assumed to be equivalent to the amount  of human
milk consumed  daily.   Intakes measured using this
procedure are often  corrected for evaporative water
losses  (insensible  water losses)  between  infant
weighings   (NAS,  1991).   Neville et al. (1988)
evaluated  the  validity of the test  weight  approach
among bottle-fed infants by comparing the weights of
milk taken from bottles with the differences between
the infants' weights before and  after feeding.  When
test weight data  were corrected for insensible weight
loss, they were not significantly different from bottle
weights.  Conversions between weight and volume of
human milk consumed are made using the density of
human milk (approximately 1.03 g/mL) (NAS, 1991).
Techniques  for measuring human milk  intake using
stable isotopes such as deuterium have been developed.
The advantages of these techniques over test weighing
procedures are that they are less burdensome for the
mother and do not interfere with normal behavior
(Albernaz et al., 2002).  However, few data based on
this technique  were found in the literature.
        Among infants born  in  2004,  73.8%  were
breastfed postpartum, 41.5.% at 6 months, and 20.9%
at 12 months.  Studies among  nursing mothers in
industrialized  countries have  shown  that average
intakes among infants ranged from approximately 500
to 800 mL/day, with the highest intake reported for
infants 3 to < 6 months old (see Table 15-1) .
        The recommendations for human milk intake
rates and  lipid intake rates are provided in the next
section along with a summary of the confidence ratings
for these recommendations. The recommended values
are based on key studies identified by EPA for this
factor. Following the recommendations, key studies on
human milk intake are summarized. Relevant data on
lipid content and fat intake, breast-feeding duration, and
the estimated  percentage of the U.S. population that
breast-feeds are also presented.
        A  number of other studies  exist  in  the
literature,  but they focus on other aspects of lactation
such   as   growth   patterns   of  nursing  infants,
supplementary food and energy intake, and nutrition of
lactating  mothers  (Dewey  et  al.,  1992; Drewett et
al.,1993; Gonzalez-Cossio et al., 1998).  These studies
are not included in this chapter because they  do no
focus on the exposure factor of interest. Other studies
in the literature focus on formula intake.  Since some
baby formula are prepared by adding water, these data
are presented in chapter 3 - Water Intake.

15.2    RECOMMENDATIONS
        The studies described in Section 15.3  were
used in selecting recommended values for human milk
intake  and lipid intake.  Although different survey
designs, testing periods, and populations were utilized
by the studies to estimate intake, the mean and standard
deviation  estimates reported  in these studies  are
relatively  consistent. There are, however, limitations
with the data. With the exception of Butte et al. (1984)
and Arcus-Arth et al. (2005), data were not presented
on a body weight basis. This is particularly important
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                                                        	Chapter 15 - Human Milk Intake
since intake rates may be higher on a body weight basis
for younger infants.  Also, the data used to derive the
recommendations are over 15 years old and the sample
size  of the studies was  small.  Other populations of
concern  such  as  mothers  highly  committed  to
breastfeeding, sometimes  for  periods  longer than
1 year, may not be captured by the studies presented in
this chapter.
15.2.1   Human Milk Intake
        A summary of recommended values forhuman
milk and lipid intake rates is presented in Table 15-1
and the confidence ratings for these recommendations
are presented in Table 15-2. The human milk intake
rates for nursing infants that have been reported in the
studies described in this section  are summarized in
Table 15-3 in units of mL/day  and in Table  15-4 in
units of mL/kg-day (i.e., indexed to body weight).  It
should be noted that the decrease in human milk with
age is  likely  a result of complementary foods being
introduced as  the child grows and not necessarily a
decrease in total energy intake. In order to conform to
the new  standardized age  groupings used  in  this
handbook (see Chapter 1), data from Pao et al. (1980),
Dewey  and Lonnerdal  (1983), Butte et al.  (1984),
Neville et al. (1988), Dewey et al. (199la), Dewey et
al. (1991b), Butte et al. (2000) and Arcus-Arth et al.
(2005) were compiled for each month of the first year
of life. Recommendations were converted to mL/day
using a density of human milk of 1.03 g/mL rounded up
to two significant figures. Only two studies (i.e., Butte
et al., 1984 and Arcus-Arth et al., 2005) provided data
on a body weight basis.   For some months  multiple
studies were available; for others only one study was
available.   Weighted means were calculated  for each
age  in months.   When upper  percentiles were not
available from a study, these were estimated by adding
two  standard  deviations  to  the  mean   value.
Recommendations for upper percentiles, when multiple
studies were available, were calculated as the midpoint
of the range of upper percentile values of the studies
available for  each age in months.  These month-by-
month intakes were composited to yield intake rates for
the standardized age groups by calculating a weighted
average.    Recommendations are  provided  for the
population of exclusively breastfed infants since this
population may have higher exposures than  partially
breastfed  infants.    Exclusively  breastfed  in this
chapter refers to infants whose sole source of milk
comes from  human milk, with no  other milk
substitutes.  Partially  breastfed  refers to infants
whose source of milk comes from both human milk
  and other milk substitutes (i.e., formula). Note that
  some studies define partially breastfed as infants whose
  dietary intake comes from not only human milk and
  formula, but also from other solid foods (e.g., strained
  fruits, vegetables, meats).

  15.2.2   Lipid Content and Lipid Intake
          Recommended lipid intake rates are presented
  in Table  15-5.  The table  parallels the human milk
  intake tables (Table 15- 3).  With the exception of the
  data from Butte et al. (1984), the rates were calculated
  assuming a lipid content of 4% (Butte et al.,1984; NAS,
  1991; Maxwell and Burmaster, 1993).  In the case of
  the Butte et al. (1984) study,  lipid intake rates were
  provided, and were used in place of the estimated lipid
  intakes.  Lipid intake rates on a body weight basis are
  presented in Table 15-6. These were calculated from
  the values presented in Table  15-4 multiplied  by  4%
  lipid content.
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Chapter 15 - Human Milk Intake

Table 15-1. Recommended

Age Group
Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed Infants
Mean Upper Percentilea
Source
mL/day mL/kg-day mL/day mL/kg-day
Human Milk Intake
Birth to <1 month 510
1 to <3 months 690
3 to <6 months 770
6 to <12 months 620
150 950 220 b
140 980 190 b,c, d, e,f
110 1,000 150 b,c, d, e, f, g
83 1,000 130 b,c, e, g
Lipid Intake h
Birth to <1 month 20
1 to <3 months 27
3 to <6 months 30
6 to <12 months 25
6.0 38 8.7 i
5.5 40 8.0 d, i
4.2 42 6.0 d, i
3.3 42 5.2 i
Upper percentile is reported as mean plus 2 standard deviations.
Neville et al., 1988.
' Pao etal., 1980.
a Butteet al., 1984.
e Dewey and Lonnerdal, 1983.
f Butteet al., 2000.
' Dewey etal., 1991b.
h The recommended value for the
Arcus- Arth et al., 2005.





lipid content of human milk is 4.0 percent. See Section 15.5.
















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                                                           	Chapter 15 - Human Milk Intake
                          Table 15-2.  Confidence in Recommendations for Human Milk Intake
  General Assessment Factors
                         Rationale
Rating
  Soundness
   Adequacy of Approach
   Minimal (or defined) Bias
                                                                Medium
Methodology uses changes in body weight as a surrogate for total
ingestion.  More sophisticated techniques measuring stable
isotopes have been developed, but data with this technique were
not available. Sample sizes were relatively small (7-108).
Mothers selected for the studies were volunteers. The studies
analyzed primary data.

Mothers were instructed in the use of infant scales to minimize
measurement errors. Three out of the 8 studies indicated
correcting data for insensible water loss. Some biases may be
introduced by including partially-breastfed infants.
  Applicability and Utility
   Exposure Factor of Interest

   Representativeness
   Currency
   Data Collection Period
                                                                Medium
The studies focused on estimating human milk intake.

Most studies focused on the U.S. population, but were not
national samples. Population studied were mainly from high
socioeconomic status. One study included populations from
Sweden and Finland. However, this may not affect the amount of
intake, but rather the prevalence and initiation of lactation.

Studies were conducted between 1980-2000. However, this may
not affect the amount of intake, but rather the prevalence and
initiation of lactation.

Infants were not studied long enough to fully characterize day to
day variability.
  Clarity and Completeness
   Accessibility

   Reproducibility
   Quality Assurance
                                                                Medium
All key studies are available from the peer reviewed literature.

The methodology was clearly presented, but some studies did not
discuss adjustments due to insensible weight loss.

Some steps were taken to ensure data quality. For example,
mothers were trained to use the scales.  However, this element
could not be fully evaluated from the information presented in the
published studies.	
  Variability and Uncertainty
   Variability in Population
   Uncertainty
                                                                  Low
Not very well characterized.  Mothers committed to breastfeeding
over 1 year were not captured.

Not correcting for insensible water loss may underestimate intake.
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Chapter 15 - Human Milk Intake	
Table 15-2. Confidence in Recommendations for Human Milk Intake (continued)
General Assessment Factors
Evaluation and Review
Peer Review
Number and Agreement of Studies
Overall Rating
Rationale
The studies appeared in peer review journals.
There are 8 key studies. The results of studies from
different researchers are in agreement.

Rating
High
Medium
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                                          	Chapter 15 - Human Milk Intake

Table 15-3.
Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/day)
Upper
Age Number of , Percentile
Intake
(months) Children , T , , ^ Consumption
(mL/day) , T ,, ,,
v " (mL/day)"
0<
1
2
3
4
5
6
7
8
9
10
11
12
1 6 to 13
11
37
12
16
10 to 12
19
40
2
37
10
16
73
40
12
13
41
12
11
1
13
11
60
30
12
9
12
50
11
8
8
42
13
511
600
729
679 a
673
679 a
756
704
833
702
713
782
788
728
690
810
740
814
805
682
744
896
747
637
700
604
600
627
535
538
391
435
403
951
918
981
889
1,057
889
1,096
958
924
935
1,126
1,047
988
888
1,094
996
1,074
1,039
-ed
978
1,140
1,079
1,050
1,000
1,012
1,028
1,049
989
1,004
877
922
931
Weighted Mean Intake
and Upper Percentile Consumption
(across all Key Studies)
(mL/day)
Composite Age
Individual Age ^
Groups
Meanb Upperc Mean Upperc
Neville etal., 1988 511 951
Pao etal., 1980
Butte et al., 1984
Neville etal., 1988 6?° %1
Dewey and Lonnerdal, 1983
Neville et al., 1988
Dewey and Lonnerdal, 1983 713 992
Butte et al., 1984
Pao etal., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey etal., 1991b
Butte et al., 2000
Neville et al., 1988
Dewey and Lonnerdal, 1983 739 991
Butte et al., 1984
Neville et al., 1988 j Q57
Dewey and Lonnerdal, 1983 '
Pao etal., 1980
Neville et al., 1988
Dewey and Lonnerdal, 1983 741 1,000
Dewey etal., 1991b
Butte et al., 2000
Neville etal., 1988 700 1,006
Neville etal., 1988 604 1,012
Neville etal., 1988
Dewey etal., 199 Ib
Neville etal., 1988 535 989
Neville etal., 1988 538 1,004
Neville et al., 1988
Dewey et al., 1991a; 1991b 410 904
Butte et al., 2000
511 951
692 977
769 1,024
622 1,024
410 904
Calculated as the mean of the means.
Upper percentile is reported as mean plus 2 standard deviations.
c Middle of the range of upper percentiles.
d Calculated for infants 1 to < 2 months old.
e Standard deviations and upper percentiles not calculated for small sample sizes.
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Chapter 15 - Human Milk Intake	

Table
15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/kg/day)
Mean Upper
Age Number
Intake Percentile
(months) of
(mL/kg- Consumption
Children
day) (mL/kg-day)
0 <
1
2
3
4
5
6
7
9
12
1 9 to 25 150
37
25
40
25
37
108
41
57
26
39
8
57
42
154
150
125
144
114
127
108
112
100
101
75
72
47
Calculated as the mean of the means.
b Upper percentile is reported as mean plus
c Middle of the range of upper percentiles.
217
200
198
161
188
152
163
142
148
140
141
125
118
101
Weighted Mean Intake
and Upper Percent! e Consumption
(across all Key Studies)
(mL/kg-day)
Individual Age Composite Age
Groups
Meanb Upperc Mean Upperc
Arcus-Arth et al, 2005 150 217
Butte etal., 1984 152 199
Arcus-Arth et al, 2005
Butte etal., 1984 135 175
Arcus-Arth et al, 2005
Butte etal., 1984 121 158
Arcus-Arth et al, 2005
Butte etal., 1984 110 145
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005 100 140
Arcus-Arth et al, 2005 101 141
Arcus-Arth et al, 2005 75 125
Arcus-Arth et al, 2005 72 118
Arcus-Arth et al, 2005 47 101
150 217
144 187
111 149
83 130
47 101
2 standard deviations.
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                                          	Chapter 15 - Human Milk Intake
Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day)a
Age Number of
(months) Children
0<
1
2
3
4
5
6
7
8
9
10
11
12
b
d
1 6 to 1 3
11
37
10 to 12
16
1 0 to 12
19
40
37
10
16
73
40
12
13
41
12
11
1
13
11
60
30
12
9
12
50
11
9
9
42
13
Except for Butte et al. 1984
Upper percentile is reported
Calculated as the mean of th
Middle of the range of uppe
Standard deviations and upp
Mean
Intake
(mL/day)
20
24
27
27
27
27
30
24
33
23
29
31
32
29
28
32
25
33
32
27
30
36
30
25
28
24
24
25
21
22
17
17
16

Upper Percentile
Consumption
(mL/day)b
38
37
43
36
42
36
44
38
37
37
45
42
40
36
44
41
43
42
39
46
43
42
40
40
41
42
40
40
35
37
37

as mean plus 2 standard deviations.
e means.
r percentiles.
er percentiles not calculated for smal
Weighted Mean Intake
and Upper Percentile Consumption
(across all Key Studies)
(mL/day)
source
Composite Age
Individual Age
Groups
Meanc Upperd Meanc Upperd
Neville etal., 1988 20 38
Pao etal., 1980
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Neville etal., 1988
Dewey and Lonnerdal, 1983 27 40
Butte etal., 1984
Pao etal., 1980
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Dewey etal., 1991b
Butte et al. 2000
Neville etal., 1988
Dewey and Lonnerdal, 1983 28 40
Butte etal., 1984
Neville etal., 1988
Dewey and Lonnerdal, 1983
Pao etal., 1980
Neville etal., 1988
Dewey and Lonnerdal, 1983 30 40
Dewey etal., 1991b
Butte etal., 2000
Neville etal., 1988 28 40
Neville etal., 1988 24 41
Neville etal., 1988
Dewey etal., 1991b
Neville etal., 1988 21 40
Neville etal., 1988 22 40
Neville etal., 1988
Dewey etal., 1991a; 1991b 16 36
Butte etal., 2000
20 38
27 40
30 42
25 42
16 36
3 using 4% lipid content.
sample sizes.
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Chapter 15 - Human Milk Intake	
Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants (mL/kg/day)a
Age Number Mean Intake
(months) of (mL/kg-day)
Children
0 <
1

2
3
4
5
6
7
9
12
•


1 9 to 25 6.0
37
25

40
25
37
108
41
57
26
39
8
57
42
Except for Butte
content.
Upper percentile
Calculated as the
5.7
6.0

4.3
5.8
3.7
5.1
3.7
4.5
4.0
4.0
3.0
2.9
1.9
et al. 1984, values were

is reported as mean plus
mean of the means.
Upper
Percentile
Consumption
(mL/kg-day)b
8.7
9.1
8.7

6.7
7.5
6.1
6.5
6.3
5.9
5.6
5.6
5.0
4.7
4.0
calculated from t

Source
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005

Butte etal., 1984
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Butte etal., 1984
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
Arcus-Arth et al, 2005
ible 15-4 using 4% lipid

Weighted Mean Intake
and Upper Percentile Consumption11
(across a211 Key Studies)
(mL/kg-day)
Individual Age Composite Ages
Groups
Mean6 Upperd Mean6 Upperd
6.2 8.7
5.9 8.9

5.1 7.1
4.4 6.3
4.1 6.1
4.0 5.8
4.0 5.6
3.0 5.0
2.9 4.7
1.9 4.0
6.0 8.7

5.5 8.0


4.2 6.0


3.3 5.2

1.9 4.1


2 standard deviations.
Middle of the ranae of urmer nercentiles.
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                                                         	Chapter 15 - Human Milk Intake
15.3    KEY STUDIES ON HUMAN MILK
        INTAKE
15.3.1  Pao et al., 1980 - Milk Intakes and Feeding
        Patterns of Breast-fed Infants
        Pao  et  al.  (1980)  conducted a study of 22
healthy nursing infants to estimate human milk intake
rates. Infants were categorized as completely breast-fed
or partially breast-fed.  Breastfeeding mothers were
recruited through LaLeche League groups.  Except for
one black infant, all  other infants were  from white
middle-class families in southwestern Ohio. The goal
of the study was to enroll infants as close to one month
of age as possible and to obtain records near one, three,
six,  and nine months of age  (Pao et  al.,  1980).
However, not all mother/infant pairs participated at
each time interval.  Data were collected for these 22
infants using the test weighing method.  Records were
collected for three consecutive 24-hour periods at each
test interval. The weight of human milk was converted
to volume by assuming a density of 1.03 g/mL. Daily
intake rates were calculated for each infant based on the
mean of the three 24-hour periods. Mean daily human
milk intake rates for the infants  surveyed at each time
interval are presented in Table 15-7. These data (Table
15-7) are presented as they are  reported in Pao et al.
(1980). For completely breast-fed infants, the  mean
intake rates were 600 mL/day at 1 month  of age,
833 mL/day at 3 months of age, and 682 mL/day at 6
months of age. Partially breast-fed infants had mean
intake rates of 485 mL/day,  467  mL/day, 395 mL/day,
and <554 mL/day at  1, 3,  6, and 9 months of age,
respectively.  Pao et al. (1980)  also  noted that intake
rates for boys in both groups were slightly higher than
for girls.
       The advantage of this study is that data for both
exclusively  and  partially  breast-fed  infants  were
collected for multiple time  periods.  Also, data  for
individual infants were collected over 3 consecutive
days  which  would  account for  some  individual
variability.  However, the  number  of infants in  the
study was relatively small.  In addition, this study  did
not account for  insensible  weight  loss which may
underestimate the amount of human milk ingested.

15.3.2  Dewey and  Lonnerdal, 1983  -  Milk and
        Nutrient Intake of Breast-fed Infants from
        1 to  6  Months: Relation  to Growth and
        Fatness
        Dewey and Lonnerdal  (1983) monitored  the
dietary intake of 20 nursing infants between the ages of
  1  and 6 months.  The number of study participants
  dropped to 13 by the end of the sixth month. Most of
  the infants in the study were exclusively breast-fed.
  One infant's intake  was  supplemented by formula
  during the first and second month of life.  During the
  third, fourth, and fifth months, three,  four, and five
  infants,  respectively, were given some formula to
  supplement their intake. Two infants were given only
  formula (no  human milk) during  the  sixth month.
  According to Dewey and Lonnerdal (1983), the mothers
  were all well educated and recruited through Lamaze
  childbirth classes in  the  Davis  area of California.
  Human milk intake volume was estimated based on two
  24-hour test weighings per month. Human milk intake
  rates for the various age groups are presented in Table
  15-8. Human milk  intake averaged 673, 782, and 896
  mL/day at 1,  3, and 6 months of age, respectively.
          The advantage of this study is that it evaluated
  nursing infants for a period of 6 months based  on two
  24-hour observations per infant per month.  However,
  corrections for insensible weight loss apparently were
  not made. Also, the number of infants in the study was
  relatively small and the study participants were not
  representative of the general population. Some  infants
  during the study period were given some formula (i.e.,
  up to 5 infants during the fifth month). Without the raw
  data, these subjects could  not be excluded from the
  study results.  Thus, these subjects may  affect the
  results when deriving recommendations for exclusively
  breastfed infants.

  15.3.3   Butte et al., 1984 - Human Milk Intake and
          Growth in Exclusively Breast-fed Infants
          Human milk intake was studied in exclusively
  breast-fed infants during  the  first 4  months  of life
  (Butte et al.,  1984). Nursing mothers  were recruited
  through the Baylor Milk Bank Program  in Texas.
  Forty-five mother/infant pairs participated in the study.
  However, data for some time periods (i.e., 1, 2, 3, or 4
  months) were missing for some mothers as  a result of
  illness or other factors.  The mothers  were from the
  middle- to upper-socioeconomic stratum  and had  a
  mean age of  28.0 ± 3.1  years. A total of 41 mothers
  were white, 2 were Hispanic, 1 was Asian,  and 1 was
  West Indian.  Infant growth progressed satisfactorily
  over the course of the study.
         The amount of milk ingested over a 24-hour
  period was determined by weighing the infant before
  and after feeding.  The study did not indicate whether
  the data were corrected for insensible water or  weight
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Chapter 15 - Human Milk Intake
loss.  The mean and  standard deviation milk  intake
difference based on weighing the bottle before and after
nine successive feedings, was estimated to be 3.2 ±3.1
g. Test weighing occurred over a 24-hour period for
most  study  participants, but intake among  several
infants was studied over longer periods (48 to 96 hours)
to assess individual variation in intake. It was reported
that   eight  of  the   infants received  some  food
supplementation during the study period. Six of them
received less than 60 kcal/day  of formula, oatmeal,
glucose water, or rice water for 1 or 2 days.  One infant
received an additional 90 kcal/day of infant formula and
rice water for 6 days during the  fourth month because
of inadequate milk production.  Converting  values
reported as g/day to mL/day, using a conversion factor
of 1.03 g/mL, mean human milk intake ranged from
702 mL/day at 3 months to  729 mL/day at 1  month,
with an overall mean of 712 mL/day for the entire study
period (Table  15-9).  Intakes were also calculated on
the basis of body weight (Table 15-9). Based  on the
results of test weighings conducted over 48 to 96 hours,
the overall mean variation  in individual daily  intake
was estimated to be 7.9 ± 3.6 percent.
        The advantage of this study is that data for a
larger number of exclusively breast-fed infants were
collected than in previous studies. However, data were
collected for infants up to  4 months and  day-to-day
variability was not characterized for all infants.  It was
reported that eighteen  percent (i.e., 8 out of 45) of the
infants received some formula supplementation  during
the study period. Without the raw data, these subjects
could not be excluded from the study results. Therefore,
values derived from this study for exclusively breastfed
infants may be somewhat underestimated.

15.3.4  Neville et  al., 1988 - Studies in  Human
        Lactation:  Milk   Volumes in  Lactating
        Women During the Onset of Lactation and
        Full Lactation
        Neville et al. (1988)  studied human milk
intake among  13 infants during  the first year of life.
The   mothers   were   all  multiparous, nonsmoking,
Caucasian women of middle- to  upper-socioeconomic
status living in Denver, CO.  All women in the study
practiced exclusive breast-feeding for at least 5 months.
Solid  foods were introduced at mean age of 7 months.
Daily milk intake was estimated by the test weighing
method with corrections for insensible weight loss.
Data were collected daily from birth to 14 days, weekly
from weeks 3 through  8, and monthly until  the study
period ended at 1 year after inception. One infant was
weaned at 8 months, while all others were weaned on or
after the 12 months. Formula was used occasionally (<
240 mL/wk) after 4 months in three  infants.   The
estimated human milk intakes for this study are listed in
Table 15-10. Converting values reported as g/day to
mL/day, using a conversion factor of 1.03 g/mL, mean
human milk intakes were  748 mL/day, 713 mL/day,
744 mL/day, and 391 mL/day at 1, 3, 6, and 12 months
of age, respectively.
        In comparison to the  previously described
studies,  Neville  et  al.  (1988)  collected data  on
numerous days  over a relatively long time period (12
months) and they were corrected for insensible weight
loss. However, the intake rates presented in Table 15-
10 are estimated based on intake during only a 24-hour
period.  Consequently, these  intake rates are based on
short-term data that do not account for day-to-day
variability among individual infants.  Also, a smaller
number of subjects was included than in the previous
studies. Three infants were given some formula after 4
months. Without the raw data, these subjects could not
be  excluded from  the study  results.   Thus,  data
presented for infants between 5 and 12 months may be
an underestimate for the intake of exclusively breastfed
infants.

15.3.5   Dewey et  al., 1991a,  b  - (a)   Maternal
        Versus Infant Factors Related to Human
        Milk Intake  and  Residual  Volume: The
        DARLING Study;  (b) Adequacy of Energy
        Intake Among  Breast-fed Infants  in the
        DARLING  Study:     Relationships  to
        Growth, Velocity, Morbidity, and Activity
        Levels
        The Davis Area Research on Lactation, Infant
Nutrition  and  Growth   (DARLING)  study   was
conducted in 1986 to evaluate growth patterns, nutrient
intake, morbidity, and  activity  levels in infants who
were breast-fed for at least the first 12 months of life
(Dewey et al., 1991a, b). Subjects were non-randomly
selected through  letters to new parents  using  birth
listing.  One of the criteria used for selection was that
mothers did not plan to feed their infants more than 120
mL/day of other milk or formula for the first 12 months
of life.   Seventy-three infants  aged 3 months  were
included in the study. At subsequent time intervals, the
number of infants  included in the study was somewhat
lower as a result of attrition.  All infants in the study
were healthy and of normal gestational age and weight
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                                                        	Chapter 15 - Human Milk Intake
at birth, and did not consume solid foods until after the
first 4 months of age.  The mothers  were highly
educated and of "relatively high socioeconomic status."
        Human milk intake was estimated by weighing
the infants before and after each feeding and correcting
for insensible  water  loss.    Test  weighings  were
conducted over a 4-day period every 3 months.  The
results of the study indicate that  human milk  intake
declines over the first 12 months of life.  This decline
is associated with the intake of solid food. Converting
values reported as g/day to mL/day, using a conversion
factor of  1.03 g/mL, mean  human  milk intake was
estimated  to  be  788  mL/day  at  3  months  and
435 mL/day at 12 months (Table 15-11).  Based on the
estimated  intakes at 3  months  of  age,  variability
between individuals (coefficient of variation ([CV] =
16.3%)  was  higher  than  the average day-to-day
variability ([CV]  = 8.9 ± 5.4%) for the infants in the
study (Dewey et al., 199la).
        The advantages of this study are that data were
collected over a relatively long-time (4 days) period at
each test interval, which would account for some day-
to-day infant variability, and corrections for insensible
water loss were  made.  Data from  this  study are
assumed to  represent  exclusively breastfed infants,
since mothers  were  specifically  recruited  for that
purpose. It is, however, unclear from the  Dewey et al.,
199 la if this criterion was met throughout the length of
the study period.

15.3.6  Butte, et al.,  2000  -  Infant Feeding  Mode
        Affects   Early   Growth   and   Body
        Composition
        Butte et al. (2000) conducted a study to assess
the impact of infant feeding mode on growth and body
composition during the first two  years  of life.  The
study was conducted  in the  Houston,  Texas  area,
recruited through the Children's  Nutrition Research
Center  (CNRC)  referral  system.   The study  was
approved by the Baylor Affiliates  Review Boards for
Human  Subject Research. The overall sample was 76
healthy  term  infants at 0.5, 3, 6, 9, 12, 18, and 24
months  of age.  The sample size varied between 71  to
76 infants for each age group. Repeated measurements
for  body  composition  and  anthropometric   were
performed. The mothers agreed to either exclusively
breast feed or formula feed the infants for the  first 4
months of life.
        At 3-month or 6-month  study intervals, the
feeding  history was taken. The mothers or caretakers
 were questioned about breastfeeding frequency, and the
 use of formula, milk, juice, solids, water and vitamin or
 mineral supplements.  Also, infant food  intake was
 quantified at 3, 6,  12, and  24 months with a 3-day
 weighted  intake record completed by  the mother or
 caretaker  (Butte et  al., 2000).  The intake of human
 milk was assessed by test weighing; the infant weights
 were measured before and after each feeding. Using a
 pre-weighing and post-weighing method, the intake of
 formula and other foods and beverages was determined
 for 3 days by the mothers using a digital scale and
 recorded on predetermined forms.
         The average duration of breastfeeding was
 11.4 months (SD = 5.8).  Butte et al.(2000)  reported
 that infants were exclusively breastfed  for at least the
 first four  months except for the following:  one was
 weaned at 109 days, another received formula at 102
 days and another given cereal at 106 days. The infant
 feeding characteristics are shown in Table 15-12. The
 intake of human milk for the infants are shown in Table
 15-13. Converting values reported as g/day to mL/day,
 using a conversion factor of 1.03 g/mL, mean human
 milk intake was  estimated  to be 728 mL/day at 3
 months  (weighted  average  of  boys  and  girls),
 637 mL/day at 6 months (weighted average of boys and
 girls), and 403 mL/day at 12 months (weighted average
 of boys and girls) (Table 15-13). Feeding practices by
 percent for infants are shown in Table  15-14.  The
 mean weights  are provided in Table 15-15.
         Advantages of this  study are that it provides
 intake data for breastfed infants  for  the first four
 months of life.   The study also provides the  mean
 weights for the infants by feeding type and by gender.
 The limitations of the study are that the sample size is
 small and it is limited  to one  geographical location.
 The authors did not indicate if results were corrected
 for  insensible  weight loss.    Since  mothers  could
 introduce  formula after 4 months, only the data for the
 3-month old infants can be  considered exclusively
 breastfed.

 15.3.7  Arcus-Arth et al., 2005 - Human Milk and
         Lipid Intake Distributions for Assessing
         Cumulative Exposure and Risk
         Arcus-Arth et al. (2005) derived population
 distributions for average daily milk and lipid intakes in
 g/kg day for infants 0-6 months and 0-12 months of age
 for infants fed according to the American Academy of
 Pediatrics  (AAP)  recommendations.     The  AAP
 recommends exclusively breastfeeding for the first 6
 months of life, human milk as the only  source of milk
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Chapter 15 - Human Milk Intake
age 1 year, with the introduction of solid foods after 6
months.  The distributions were derived based on data
in the peer reviewed literature and datasets supplied by
the publication authors  for infants 7 days and  older
(Arcus-Arth et al., 2005). As cited in Arcus-Arth et al.
(2005),  data  sources included Dewey  et al.  (1991a,
199b), Hofvander et al. (1982), Neubauer et al. (1993),
Ferris et al. (1993), Salmenpera et al. (1985), and Stuff
and Nichols (1989). The authors also evaluated intake
rates for infants breastfed exclusively over the first year
and provides  a regression line of intake versus age for
estimating short-term exposures. Arcus-Arth  derived
human milk intake rates for the  entire infant population
(nursing   and  non-nursing)   from  U.S.  data  on
consumption, prevalence and duration.  Arcus-Arth et
al. (2005) defined exclusive breastfeeding  (EBF)  as
"breast milk is  the sole source of calories, with  no  or
insignificant  calories form other liquid or solid food
sources." Predominant breastfeeding was described by
Arcus-Arth et al. (2005) as "breast milk is the sole milk
source with significant calories  from other foods." The
data that were consistent with AAP advice were used to
construct the AAP dataset (Arcus-Arth et al.,  2005).
The  0-12 months EBF dataset was created using 0-6
month AAP data and data from the EBF infants  older
than 6 months of age.  Because there are no data  in the
AAP dataset for any individual infant followed  at
regular, frequent intervals over the 12  month period,
population distributions were derived with assumptions
regarding  individual  intake  variability over  time
(Arcus-Arth et al., 2005). Two methods were used.  In
Method 1, the average population daily intake at each
age  is  described  by  a regression line,  assuming
normality. Arcus-Arth  et al.  (2005)  noted that age
specific intake data were consistent with the assumption
of normality.  In  Method  2, intake  over  time  is
simulated  for  2500  hypothetical  infants  and the
distribution intakes  derived   from  2500  individual
intakes   (Arcus-Arth  et al., 2005).  The population
intake distribution was derived following Method 1.
Table  15-16   presents  the   means,   and  standard
deviations  for intake  data  at different ages; the
variability was greatest for the 2 youngest and  3 oldest
age groups. The values in Table 15-6 using Method 1
were  used to derive  recommendations presented  in
Table 15-4 since  it provides  data for the fine age
categories.  Converting values reported as g/day  to
mL/day, using a conversion factor of 1.03 g/mL,  mean
human milk intake was estimated to be 150 mL/kg-day
at 1 month, 127 mL/kg-day at  3 months, 101  mL/kg-
day at 6 months, and 47 mL/kg-day  at 12 months
(Table 15-16).  Time weighted  average intakes  for
larger age groups (i.e., 0-6 months, 0-12 months) are
presented in Table 15-17.
        An advantage  of this study is that it was
designed to represent the  infant population whose
mothers follow the AAP recommendations.  Intake was
calculated on a body weight basis. In addition, the data
used  to  derive the  distributions  were from  peer
reviewed  literature  and datasets  supplied  by  the
publication authors.   The distributions were derived
from  data  for  infants  fed  in accordance  to  AAP
recommendations, and they most likely represent daily
average  milk   intake  for a  significant portion of
breastfed infants today (Arcus-Arth et al., 2005).  The
limitations of the study are that the data used were from
mothers that were predominantly white, well nourished
and from mid  or high socioeconomic status. Arcus-
Arth et al. (2005) also included data from Sweden and
Finland.  However human milk volume in mL/day is
similar  among all   women  except  for  severely
malnourished  women (Arcus-Arth  et  al.,  2005).
According to Arcus-Arth et al.  (2005), "Although few
infants are  exclusively breastfed for 12 months,  the
EBF distributions may represent a more highly exposed
subpopulation of infants exclusively breastfed in excess
of 6 months."

15.4    KEY  STUDIES ON LIPID  CONTENT
        AND LIPID INTAKE FROM HUMAN
        MILK
        Human milk contains over 200 constituents
including  lipids,   various  proteins,  carbohydrates,
vitamins, minerals, and trace elements  as well as
enzymes and hormones.  The  lipid content of human
milk varies  according to the  length of  time that an
infant nurses, and increases from the  beginning to the
end of a single nursing session (NAS,  1991). The lipid
portion accounts for approximately 4% of human milk
(3.9% ± 0.4%)  (NAS, 1991). This value is  supported
by various  studies that evaluated lipid content from
human milk. Several studies also estimated the quantity
of lipid consumed by breast-feeding infants.  These
values  are  appropriate for  performing  exposure
assessments   for   nursing  infants  when  the
contaminant(s)  have residue concentrations that  are
indexed to the fat portion of human milk.

15.4.1   Butte et al., 1984 - Human Milk Intake and
        Growth in Exclusively Breast-fed Infants
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                                                        	Chapter 15 - Human Milk Intake
        Butte et al. (1984) analyzed the lipid content
of human  milk samples taken  from women who
participated in a study of human milk intake among
exclusively  breast-fed  infants.    The  study  was
conducted  with  over 40  women during a  4-month
period.  The mean lipid  content of human  milk  at
various infants' ages is presented in Table 15-18.  The
overall lipid content for the 4-month study period was
3.43 ±  0.69 % (3.4%).   Butte  et al.  (1984)  also
calculated  lipid  intakes  from 24-hour human milk
intakes  and the lipid content of  the  human milk
samples. Lipid intake was estimated to range from 22.9
mL/day (3.7 mL/kg-day) to 27.2 mL/day (5.7 mL/kg-
day).
        The number of women included in this study
was small,  and these women were selected primarily
from middle to upper socioeconomic  classes.  Thus,
data on human milk lipid content from this study may
not be entirely representative of human milk lipid
content  among the  U.S. population.    Also, these
estimates are based on short-term data, and day-to-day
variability was not characterized.

15.4.2   Mitoulas  et  al., 2002 - Variation  in Fat,
        Lactose, and Protein in  Human Milk Over
        24  h  and  Throughout  the  First  Year  of
        Lactation
        Mitoulas et al.  (2002) conducted a  study  of
healthy nursing women  to determine the volume and
composition of human milk during the first year  of
lactation. Nursing mothers were recruited through the
Nursing Mothers' Association of Australia. All infants
were completely  breastfed on demand for at least 4
months.  Complementary solid food was introduced
between 4-6 months of age.  Mothers consumed their
own ad libitum diets throughout the study. Seventeen
mothers initially provided data for milk production and
fat content, whereas lactose, protein, and energy were
initially obtained from nine mothers.  The number  of
mothers participating in  the  study decreased at  6
months due to the cessation of sample collection from
11 mothers, the maximum period  of exclusive breast-
feeding.
        Milk samples were collected before and after
each feed from each breast over a 24-28 hour period.
Milk yield was determined by weighing the mother
before and after each feed from each breast. Insensible
water loss was accounted for by weighing the mother
20 minutes after the end of each feeding. The rate  of
water loss during this 20 minutes was used to calculate
insensible water loss during the feeding.  Samples  of
 milk  produced  at  the  beginning  of the  feeding
 (foremilk) and at the end of the feeding (hindmilk) were
 averaged to provide the fat, protein, lactose, and energy
 content for each feed. In all cases the left and right
 breasts were treated separately, therefore, n, represents
 the number of individual breasts sampled.
         Mean human milk production and composition
 at each age interval are presented in Table        The
 mean 24 hour milk production from both breasts was
 798 (SD= 232) mL. The mean fat, lactose,  and protein
 contents (g/L) were 37.4 (SE= 0.6), 61.4 (SE =0.6), and
 9.16 (SE= 0.19), respectively.  Composition did not
 vary between left and right breasts or preferred and
 non-preferred breasts.  Milk production was constant
 for the first 6 months and thereafter steadily declined.
 The fat content of milk  decreased between  1 and 4
 months, before increasing to  12 months of lactation.
 The concentration of protein decreased to 6 months and
 then remained steady.  Lactose remained  constant
 throughout the 12 months of lactation. The  decrease of
 energy  at 2  months  and subsequent increase  by 9
 months can be attributed to the changes in fat content.
 Milk production,  as  well  as concentrations of fat,
 lactose, protein,  and  energy,  differed significantly
 between women.
         The focus of this study was on human milk
 composition  and production, not on infant's human
 milk intake.   The advantage of this study is that it
 evaluated nursing mothers for a period of 12 months.
 However, the number of mother-infant pairs in the
 study was small (17 mothers with infants) and may not
 be entirely representative of the U.S. population.  This
 study  accounted  for  insensible water  loss  which
 increases  the accuracy of the amount of human milk
 produced.

 15.4.3  Mitoulas et al., 2003 - Infant Intake of Fatty
         Acids from Human Milk Over the  First
         Year of Lactation
         Mitoulas et al. (2003) conducted a study of 5
 healthy nursing women to determine the content of fat
 in human  milk and fat intake by infants during the first
 year of lactation.  Nursing  mothers were  recruited
 through the Australian Breastfeeding Association or
 from private healthcare  facilities.  All infants were
 completely breastfed on demand for at least 4 months.
 Complementary solid food was introduced between 4-6
 months of age. Mothers consumed their own ad libitum
 diets throughout the study.
         Milk samples were collected before and after
 each feed from each breast over a 24-28 hour period.
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Chapter 15 - Human Milk Intake
Fore- and hind-milk samples were averaged to provide
the fat content for  each feed.   Milk yield  was
determined by weighing the mother before and after
each feed from each breast. Insensible water loss was
accounted for by weighing the mother 20 minutes after
the end of each feeding. The rate of water loss during
this 20 minutes was used to calculate insensible water
loss during the feeding.
        Changes in volume of human milk produced
and milk fat content over the  first year of lactation is
presented in Table 15-20.  The mean volumes of milk
produced  for both breasts combined  were 812.13,
790.34, 911.38, 810.20, 677.35, and 505.10 mL/day at
1, 2, 4, 6, 9,and 12 months, respectively. The average
daily intake over the  12 months  was 751.09 mL/day
with a mean fat content of 35.52  g/L.  Their  was a
significant difference in the proportional composition of
fatty acids  over the course of lactation.  Table  15-21
provides  average fatty acid composition over the  first
12  months  of  lactation.   Additionally,  fatty  acid
composition varied over the course of the day.
        The focus of this study  was on human milk
composition and production,  not on infant's  human
milk intake.  The  advantage  of  this study is that it
evaluated the human milk composition for a period of
12 months.  However, the number of mother-infant
pairs in the study was small (5 mothers with infants)
and may not be entirely representative of the entire U.S.
population. This study accounted for insensible water
loss which increases  the  accuracy of the amount of
human milk produced.

15.4.4   Arcus-Arth et al., 2005 - Human Milk  and
        Lipid  Intake Distributions  for  Assessing
        Cumulative  Exposure and Risk
        Arcus-Arth et al. (2005) derived population
distributions for average daily  milk and lipid intakes in
g/kg day for infants 0-6 months and 0-12 months of age
for infants fed according to the American Academy of
Pediatrics (AAP) recommendations. Lipid intakes were
calculated from  lipid  content and  milk intakes were
measured on the same  infant (Arcus-Arth et al., 2005).
Table 15-22 provides lipid intakes based on data from
Dewey et al. 1991a and  Table  15-23 provides lipid
intakes calculated assuming 4% lipid content and milk
intake  in the AAP dataset. Arcus-Arth et al. (2005)
noted that the distributions presented are intended to
represent the U.S.  infant population.
        An advantage of this study is that it  was
designed to represent the population of infants who are
breastfed according to the AAP recommendations. In
addition, the data used to derive the distributions were
from peer review literature and datasets supplied by the
publication authors. The limitation of the study are that
the  data   used  were  from  mothers  that   were
predominantly white, well nourished and from mid- or
upper-socioeconomic  status,  however human  milk
volume in mL/day is similar among all women except
for severely malnourished women (Arcus-Arth et al.,
2005). The authors noted that "although few infants are
exclusively breastfed for 12 months, the  exclusively
breastfed distributions  may represent a more highly
exposed subpopulation of infants exclusively breastfed
in excess of 6 months." The distributions were derived
from  data  for infants fed in  accordance  to  AAP
recommendations, and they most likely represent daily
average milk intake  for  a  significant  portion of
breastfed infants today  (Arcus-Arth et al.,  2005).

15.4.5  Kent et al., 2006 - Volume and Frequency
        of Breastfeeding and Fat Content of Breast
        Milk Throughout the Day
        Kent et  al. (2006) collected  data  from 71
Australian mothers who were exclusively nursing their
1  to 6  months old infants.  The  study  focused on
examining the variation of milk consumed from each
breast, the degree of fullness of each breast before and
after feeding,  and the fat content of milk consumed
from  each  breast  during daytime and nighttime
feedings. The volume of milk was measured using test-
weighing  procedures  with no correction for  infant
insensible  water loss.  On average, infants had 11 ± 3
breastfeedings per day  (range= 6 to 18). The  intervals
between feedings was  2 hours and  18  minutes ± 43
minutes (range  =  4  minutes  to 10  hours and 58
minutes). The 24-hour average human milk intake was
765 ± 164 mL/day (range = 464 to 1,317 mL/day). The
fat content of milk ranged from 22.3 g/L  to  61.6 g/L
(2.2% - 6.0 %) with an  average of 41.1 g/L (4.0%).
        This study examined breastfeeding practices of
volunteer mothers in Australia. Although amounts of
milk consumed by Australian infants may be similar to
infants  in  the U.S. population, results could not be
broken out by smaller age groups to examine variability
with age. The study provides estimates of fat content
from a large number of samples.
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                                                         	Chapter 15 - Human Milk Intake
15.5    RELEVANT STUDY ON LIPID INTAKE
        FROM HUMAN MILK
15.5.1  Maxwell  and  Burmaster,  1993   -   A
        Simulation  Model   to  Estimate   a
        Distribution of Lipid Intake from Human
        Milk During the First Year of Life
        Maxwell and   Burmaster  (1993)  used  a
hypothetical population of 5000 infants between birth
and 1 year of age to simulate a  distribution of daily
lipid  intake  from human  milk.   The  hypothetical
population represented both bottle-fed and breast-fed
infants aged 1 to 365 days. A distribution of daily lipid
intake was developed, based on data in  Dewey et al.
(1991b) on human milk intake for infants  at 3, 6, 9, and
12 months and human milk lipid content,  and survey
data in Ryan  et  al.  (1991)  on the percentage of
breast-fed infants under  the age of 12  months (i.e.,
approximately 22%).  A  model was used to  simulate
intake among  1113  of the 5000  infants that  were
expected to be breast-fed.  The results of the model
indicated that lipid intake among nursing  infants under
12 months of age can be characterized  by a normal
distribution with a mean of 26.0 mL/day and a standard
deviation  of 7.2 mL/day (Table  15-24).   The model
assumes that nursing infants are completely breast-fed
and does  not account for infants who are breast-fed
longer than 1 year. Based on data collected by Dewey
et  al.  (1991b),  Maxwell  and  Burmaster  (1993)
estimated the lipid content of  human milk to be 36.7
g/L at 3 months (35.6 mg/g or 3.6%), 39.2 g/L at 6
months (38.1 mg/g or 3.8%), 41.6 g/L at 9  months (40.4
mg/g  or 4.0%), and 40.2 g/L at 12 months  (39.0 mg/g
or 3.9%).
        The limitation of this  study is that it provides
a "snapshot" of daily lipid intake from human milk for
breast-fed infants. These results are also  based on a
simulation model and there are uncertainties associated
with the assumptions made. Another limitation is that
lipid intake was not derived for the EPA recommended
age categories. The estimated mean lipid intake rate
represents the average daily intake for nursing infants
under 12 months  of age.  The study did not generate
"new" data. A reanalysis of previously reported data
on human milk intake and human milk lipid intake were
provided.

15.6    OTHER FACTORS
        There are many factors that influence the
initiation, continuation,  and amount of human milk
intake.  These  factors are complex and  may include
considerations  such as:  maternal nutritional status,
 parity, parental involvement,  support from lactation
 consultants,  mother's  working  status,  infant's  age,
 weight, gender, food supplementation, the frequency of
 breast-feeding sessions per day, the duration of breast-
 feeding per event, the duration of breast-feeding during
 childhood,  ethnicity,  geographic  area,  and  other
 socioeconomic factors. For example, a study conducted
 in  the  United  Kingdom  found  that social  and
 educational factors most influenced the  initiation and
 continuation of lactation (Wright et al. 2006). Prenatal
 and postnatal  lactation  consultant intervention was
 found to be effective in  increasing lactation duration
 and intensity (Bonuck et  al. 2005).

 15.6.1   Population of Nursing Infants
          To monitor progress  towards achieving the
 CDC Healthy  People  2010 breastfeeding  objectives
 (initiation and duration), Scanlon et al. (2007) analyzed
 data from the National Immunization Survey (NIS).
 NIS uses random-digit dialing to survey households to
 survey age eligible children, followed by a mail survey
 to eligible children's vaccination providers to validate
 the vaccination information. NIS is conduced annually
 by the CDC to obtain national, state, and selected urban
 area  estimation on vaccinations rates  among  U.S.
 children  age 19-35 months.  The interview response
 rate for years 2001-2006 ranged between  64.5% and
 76.1%. Questions regarding breastfeeding were added
 to the NIS survey in 2001. The sample population was
 infants born during 2000-2004. Scanlon et al. (2007),
 noted that because data in their analysis are for children
 aged  19-35  months at  the time of the NIS  interview,
 each cross-sectional survey includes children from birth
 cohorts that span 3 calendar years; the  breastfeeding
 data were analyzed by year of birth during 2000-2004
 (birth year cohort instead if survey year).
          Among infants  born  in 2000,  breastfeeding
 rates  were 70.9% (CI= 69.0-72.8) for the postpartum
 period (in hospital before discharge), 34.2% (CI= 32.2-
 36.2)  at  6 months, and  15.7  (CI= 14.2-17.2)  at  12
 months.   For infants born in 2004, these rates had
 increased to 73.8%  (CI= 72.8-74.8) for the postpartum
 period, 41.5%  (CI= 40.4-42.6) at 6 months, and 20.9
 (CI=  20.0-21.8) at 12 months.  Rates of  breastfeeding
 through  3 months were  lowest  among  black infants
 (19.8%), infants whose mothers were <20 years of age
 (16.8%),  those whose mothers had a high  school
 education or less  (22.9% and 23.9%),  those whose
 mothers were unmarried (18.8%), those who resided in
 rural  areas (23.9%), and  those whose families had  an
 income-to-poverty ratio of <100% (23.9%). Table 15-
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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
25 provides data for exclusive breastfeeding through 3
and  6  months  by socioeconomic characteristics for
infants born in 2004.
        Scanlon et  al. (2007)  noted the following
limitations that could affect the utility of these data: (1)
breastfeeding behavior was based on retrospective self-
report by mothers or other caregivers, whose responses
might be subject to recall bias, (2) the NIS question that
defines early postpartum  breastfeeding or initiation,
"Was [child's name] ever breastfed or fed breast milk?"
collects information that might differ from the HP2010
objective  for initiation,  and  (3) although survey data
were weighted to make them representative of all U.S.
children aged 19-35 months, some bias might remain.
The  advantage of the study is that is  representative of
the U.S. infant population.
        The rate of breastfeeding  initiation in the
United  States  is near the  national  goal  of  75%
established in  Healthy People  2010 (Ruowei et  al.
2005).  Using the data obtained  from the NIS survey
conducted throughout 2002 for children who were 19 to
35 months old,  Ruowi et al. (2005) shows that overall,
71.4% of  children surveyed had  ever been breastfed.
The  percentage of children who are breastfed drops to
35.1% at 6 months and to 16.1% at 12 months (Rouwei
et al.  2005).  These  data also  revealed  significant
differences in breastfeeding participation related  to
race/ethnicity, day care and WIC participation, maternal
age,  socioeconomic  status,  and  geographical area.
Overall, 51.5% of mothers  of non-Hispanic  black
children  reported to  ever  breastfed  their  infants
compared to 72.1% of mothers of non-Hispanic white
children. Non-Hispanic black infants were exclusively
breastfed  at 6 months at a rate of 5.4% compared to
14.6% of non-Hispanic white infants and 13.8%  of
Hispanic infants.  Infants  who attended day care and
infants whose mothers received WIC benefits were less
likely to have ever been breastfed.  Mothers with higher
socioeconomic  status and older  mothers  were more
likely to have ever breastfed their infants.
        CDC  (2007)  developed the  breastfeeding
report card. The CDC National Immunization Program
in partnership with the CDC National Center for Health
Statistics,  conducts the NIS within all 50 states, District
of Columbia, and selected  geographic areas within the
states.   Five breastfeeding goals are in the  Healthy
People  2010  report.  The  Breastfeeding Report  Card
presents data for each state for the following categories
of infants:  ever breastfed,  breastfed  at  6 months,
breastfed at 12 months, exclusive breastfeeding through
3 month, and exclusive breastfeeding through 6 months.
These indicators are used to measure a state's ability to
promote, protect, and support breastfeeding. These data
for the estimated percentage of infants born in 2004 are
presented in Table  15-26.  The weighted  sample
number  is 17,654   for the  U.S. population.  The
advantage of this report is that it provides data for each
state and is representative of the U.S. infant population.
         Analysis of breastfeeding practices in other
developing countries was also found  in the literature.
Marriott et al. (2007) researched feeding practices in
developing countries in the first year of life, based on
24-hour  recall   data.   Marriott et al.  (2007),  used
secondary data  from  the  Demographic and  Health
Surveys (DHS) for more than 35,000  infants  in twenty
countries. This  survey has conducted since  1986 and
was   expanded  to  provide a   standardized  survey
instrument that can be used by developing countries to
collect  data  on maternal/infant health,  intake and
household  variables  and  to  build  national  health
statistics (Marriott et  al., 2007).  The analysis was
based on the responses of the  survey mothers for
questions on whether they were currently breasfeeding
and had fed other liquids and solid foods to their infants
in the previous 24 hours. The data incorporated were
from  between 1999 and 2003.  Marriott et al. (2007)
selected the youngest child less than 1 year old in each
of the families; multiples were included such as twins
or triplets.   Separate  analyses  were  conducted for
infants less than  6 months old and infants 6  months and
older, but less than 12 months  old.  Food and liquid
variables other than water and infant formulas were
collapsed into broader food categories for cross-country
comparisons (Marriott et al., 2007). Tinned, powdered,
and any other specified animal milks were collapsed. In
addition, all  other liquids  such as herbal teas, fruit
juices, and sugar water (excluding  unique country-
specific liquids) were collapsed into  other liquids and
the 10 types  of solid food groups into an any-solid-
foods  category  (Marriott et al., 2007).  Data were
pooled from the  20 countries to provide a large sample
size and increase statistical power. Tables 15-27 and
15-28 present the percentage of mothers that were
currently breastfeeding and separately had  fed their
infants other liquids or  solid food by age groups. Table
15-29 presents the pooled data summary for the study
period. The current breastfeeding was consistent across
countries for both age groups; the  countries that
reported  the   highest  percentages   of  current
breastfeeding for the 0 to  6 months old infants also
reported the highest percentages in the 6 to 12 month
old infants. Pooled data show that 96.6% of the 0 to 6
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                                                        	Chapter 15 - Human Milk Intake
months old infants and 87.9% of the 6 to 12 month old
infants were breastfeeding. Feeding of other fluids was
lowest in the 0 to 6 months infants, with the percentage
feeding water  the  highest  of this  category.   The
percentage of  mothers  feeding  commercial  infant
formulas was the lowest in most countries.
        There are  other older studies  that analyze
ethnic and racial differences in breastfeeding practices.
Li and Grummer-Strawn (2002) investigated ethnic and
racial disparities in lactation in the United States using
data from the  Third National Health and Nutrition
Examinations   Survey   (NHANES  III)  that  was
conducted  between   1988-1994.    NHANES   II
participants were  ages 2 months and  older.  The  data
were collected during a home interview from a parent
or a proxy respondent for the child (Li and Grummer-
Strawn, 2002). The sample population consisted  of
children 12 to  71 months of age at time of interview.
The  NHANES  III  response   rate  for  children
participating was approximately  94  percent (Li  and
Grummer-Strawn, 2002). Data  for  a total of 2,863
exclusively breastfed, 6,140 ever breastfed, and 6,123
continued breastfed children  were  included in the
analysis  (Li  and  Grummer-Strawn, 2002).     The
proportion of children ever-breastfed was  60% among
non-Hispanic whites, 26% among non-Hispanic blacks,
and 54% among Mexican Americans.  This number
decreased to 27, 9, and 23 respectively by 6 months.
Children fed exclusively human milk  at 4  months  was
also significantly lower for blacks at 8.5%, compared to
22.6% for whites and 14.1% for Mexican-Americans.
The racial and ethnic  differences in proportion  of
children ever breastfed is presented in Table 15-30, the
proportion of children who received any breast milk at
6  months  are  presented in Table  15-31,  and  the
proportion of children exclusively breastfed at 4 months
is presented in Table 15-32.
        Li and Grummer-Strawn (2002) noted  that
there may have been some lag time between birth and
the time of the interview.   This may have caused
misclassification if the predicator variables  changed
considerably between birth and the time of interview.
Also, NHANES  III did not collect information on
maternal education. Instead, the educational level  of
household head was used as a proxy.  The advantages
of this study is that it is representative  of the U.S.
children's population.
        Data   from  some   older  studies  provide
historical information on breastfeeding practices in the
U.S. These data are provided here to show trends in the
U.S. population.  In 1991, the National  Academy  of
  Sciences  (NAS)  reported  that  the  percentage  of
  breast-feeding women has changed dramatically over
  the years (NAS, 1991). The Ross Products Division of
  Abbott Laboratories conducted a large national mail
  survey in 1995 to determine patterns of breastfeeding
  during the first 6 months of life. The Ross Laboratory
  Mothers's Survey was first developed in 1955 and has
  been expanded to include many more infants. Before
  1991, the survey was conducted on a quarterly  basis,
  and approximately 40,000 to 50,000 questionnaires
  were mailed each quarter (Ryan, 1997).  Beginning in
  1991,  the survey was  conducted monthly; 35,000
  questionnaires were mailed each month. Over time, the
  response rate has been consistently in the range of 50 ±
  5%.   In  1989  and 1995,  196,000  and  720,000
  questionnaires were mailed, respectively. Ryan (1997)
  reported  rates  of breast-feeding through 1995 and
  compared them with those in  1989.
          The survey demonstrates increases in both the
  initiation of  breast-feeding  and  continued breast-
  feeding at 6 months of age between 1989 and 1991.
  Table  15-33 presents the percent  of breast-feeding  in
  hospitals  and   at  6 months  of age  by  selected
  demographic characteristics. In 1995, the incidence of
  breast-feeding at birth and at 6 months for all infants
  was approximately 59.7% and 21.6 %, respectively.
  The largest increases in the initiation of breast-feeding
  between 1989 and 1995 occurred among women who
  were Black, were less than 20 years of age, earned less
  than $10,000 per year, had no more than a grade school
  education, were living in the South Atlantic region  of
  the  U.S.,  had  infants  of low birth  weight,  were
  employed full time outside the home at the time they
  received the  survey, and participated in the  Women,
  Infants, and Children program (WIC).  In 1995, as in
  1989,  the initiation  of breast-feeding  was  highest
  among women who were greater than 35 years of age,
  earned more  than $25,000 per year, and were college
  educated, did not participate in the WIC program, and
  were living in the Mountain and Pacific regions  of the
  U.S.
          Data on the actual length of time that infants
  continue  to breast-feed  beyond 5 or 6 months were
  limited  (NAS,  1991).     However,  Maxwell and
  Burmaster (1993) estimated that approximately  22
  percent of infants under 1  year of age are breast-fed.
  This estimate was based on a reanalysis of survey data
  in Ryan et al. (1991) collected by Ross Laboratories
  (Maxwell and  Burmaster, 1993).  Studies have also
  indicated that  breast-feeding  practices  may  differ
  among ethnic and socioeconomic  groups and among
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Chapter 15 - Human Milk Intake
regions of the United States. More recently, the Ross
Products Division of Abbott Laboratories reported the
results of their ongoing "Ross Mothers Survey" in 2003
(Abbott 2003). The percentages of mothers who breast
feed,  based on ethnic background and  demographic
variables, are presented in Table 15-34.  These  data
update the values presented in the NAS 1991 report.

15.6.2   Intake Rates Based on  Nutritional Status
         Information on differences in the quality and
quantity  of human milk  on the basis  of ethnic or
socioeconomic  characteristics of the  population is
limited.  Lonnerdal et al. (1976) studied human milk
volume and composition (nitrogen, lactose, proteins)
among  underprivileged  and  privileged  Ethiopian
mothers.   No  significant  differences  were  observed
between  the data for these two groups.  Similar data
were  observed for well-nourished Swedish mothers.
Lonnerdal et al. (1976) stated that these results indicate
that human milk quality and quantity are not affected by
maternal malnutrition. However, Brown et al. (1986a,
b) noted that the  lactational capacity and  energy
concentration  of  marginally-nourished  women in
Bangladesh were   "modestly less  than in  better
nourished mothers."  Human milk intake  rates for
infants of marginally-nourished women in this study
were 690 ± 122 g/day at 3 months, 722 ± 105 g/day at
6 months, and 719 ± 119 g/day at 9  months of age
(Brown et al., 1986a). Brown et  al. (1986a) observed
that human milk from women with larger measurements
of arm circumference and triceps skinfold thickness had
higher concentrations of fat and  energy than mothers
with  less body  fat.   Positive correlations between
maternal weight and milk fat concentrations were also
observed. These results suggest that milk composition
may be affected by maternal nutritional status.

15.6.3   Frequency and Duration of Feeding
         Hofvander et  al. (1982) reported on the
frequency  of feeding among  25 bottle-fed and 25
breast-fed infants at ages 1, 2, and 3 months. The mean
number  of  meals  for  these   age   groups   was
approximately 5 meals/day (Table 15-35). Neville etal.
(1988)   reported  slightly  higher  mean  feeding
frequencies. The mean number of meals per day for
exclusively breast-fed infants was 7.3 at ages  2  to 5
months and 8.2 at ages 2 weeks to 1 month. Neville et
al. (1988) reported that, for infants between the ages of
1 week  and 5 months,  the  average duration of a
breastfeeding session is 16-18 minutes.
        Buckley (2001)  studied  the  breastfeeding
patterns, dietary intake, and growth measurement of
children who continued to breastfeed beyond 1 year of
age. The sample was 38 mother-child pairs living in
the Washington, DC area.  The criteria for inclusion in
the study were that infants  or their mothers  had no
hospitalization of either subject 3 months prior to the
study and that the mother was currently breastfeeding
a  1-year old or older child  (Buckley,  2001).   The
participants  were  recruited  through  local medical
consultants and the La Leche League members.  The
children selected as the final study subjects consisted of
22 boys and 16 girls with ages ranging from 12 to 43
month  old.  The data  were collected using a 7-day
breastfeeding diary.   The frequency  and  length of
breastfeeding varied with the age of the child (Buckley,
2001).   The author  noted a statistically  significant
difference  in  the  mean  number of  breastfeeding
episodes per day  and the average total minutes of
breastfeeding between the  1, 2, and 3 year old groups.
Table 15-36 provides the comparison of breastfeeding
patterns between age groups.  An advantage of this
study is that the frequency and duration data are based
primarily on a 7-day diary and some dietary  recall.
Limitations of the study are the small sample size and
that it is limited to one geographical area.

15.7    REFERENCES FOR CHAPTER 15
AAP (2005) Breast feeding and the use of human
        milk.  Policy Statement. Pediatrics. 115(2):
        496-506.  available on line at
        http://aappolicy.aappublications.org/cgi/cont
        ent/full/pediatrics; 115/2/496
Abbott Laboratories (2003) Breastfeeding Trends -
        2003.  Ross Mothers Survey, Ross Products
        Division,Columbus, OH.
Albernaz, E.;Victora, C.G.; Haisma, H.; Wright, A.;
        Coward, W.A.  (2003) Lactation counseling
        increases breast-feeding duration but not
        breastmilk intake as measured by isotopic
        methods. J Nutr. 133: 205-210.
Arcus-Arth, A.; Krowech,  G.; Zeise, L.  (2005)
        Human milk and Lipid Intake Distributions
        for assessing Cumulative Exposure and
        Risk.  J Expos Anal Environ Epidemiol.  15:
        357-365.
Bonuck, K.A.; Trombley, M.; Freeman, K.; Mckee,
        D.  (2005) Randomized, controlled trial of a
        prenatal and postnatal lactation consultant
        intervention on duration and intensity of
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                                                        	Chapter 15 - Human Milk Intake
        breastfeeding up to 12 months. Pediatrics.
        116: 1413-1426.
Brown, K.H.; Akhtar, N.A.; Robertson, A.D.;
        Ahmed, M.G.  (1986a) Lactational capacity
        of marginally nourished mothers:
        relationships between maternal nutritional
        status and quantity and proximate
        composition of milk. Pediatrics. 78: 909-
        919.
Brown, K.H.; Robertson, A.D.; Akhtar, N.A.
        (1986b) Lactational capacity of marginally
        nourished mothers: infants' milk nutrient
        consumption and patterns of growth.
        Pediatrics. 78: 920-927.
Butte, N.F.; Garza, C.; Smith, E.O.; Nichols, B.L.
        (1984) Human milk intake and growth in
        exclusively breast-fed infants.  J Pediatr.
        104:187-195.
Butte, N.; Wong, W.; Hopkinson, J.; Smith E.; Ellis,
        J. (2000) Infant feeding mode affects early
        growth and body composition. Pediatrics.
        106; 1355-1366.
Buckley, K. (2001) Long-term breastfeeding:
        nourishment or nurtance. J Hum Lactat.
        17(4):304-311.
CDC. (2007) Breastfeeding report card 2007.
        Breastfeeding practices-results from the
        National Immunization Survey. Available
        on line at
        http://www.cdc.gov/breastfeeding/data
Chen, A.; Rogan, W.J.  (2004) Breastfeeding and the
        risk of postneonatal death in the United
        States. Pediatrics. 113:435-439.
Dewey, K.G.; Lonnerdal, B.  (1983) Milk and
        nutrient intake of breast-fed infants from 1
        to 6 months:relation to  growth and fatness. J
        Pediatr Gastroenterol Nutr. 2:497-506.
Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lonnerdal,
        B.  (199la) Maternal versus infant factors
        related to human milk intake and residual
        volume: the  DARLING study. Pediatrics.
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Dewey, K.G.; Heinig, J.; Nommsen, L.; Lonnerdal,
        B.  (1991b) Adequacy of energy intake
        among breast-fed infants in the DARLING
        study:  relationships to growth, velocity,
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        119:538-547.
Dewey, K.G.; Peerson,  J.M.; Heinig, M.J.;
        Nommsen, L.A.; Lonnerdal, B.  (1992)
        Growth patterns of breast-fed infants in
          affluent (United States) and poor (Peru)
          communities: implications for timing of
          complementary feeding.  Am J Clin Nutr.
          56: 1012-1018.
 Drewett, R.; Amatayakul, K.; Wongsawasdii, L.;
          Mangklabruks, A.; Ruckpaopunt, S.;
          Ruangyuttikarn, C.; Baum, D., Imong, S.;
          Jackson, D.; Woolridge, M.  (1993) Nursing
          frequency and the energy intake from breast
          milk and supplementary food in a rural Thai
          population:  a longitudinal study.  Eur J Clin
          Nutr. 47: 880-891.
 Ferris, A.M.; Neubauer, S.H.; Bendel, R.B.; Green,
          K.W.; Ingardia,  C.J.; Reece, E.A. (1993)
          Perinatal lactation protocol and outcome in
          mothers with and without insulin-dependent
          diabetes mellitus. Am J Clin Nutr.  58:
          43-48.
 Gonzalez-Cossio,T.;  Habicht, J.P.; Rasmussen, K.M.;
          Delgado,  H.L.  (1998) Impact of food
          supplementation during lactation on infant
          breast-milk  intake and on the proportion of
          infants exclusively breast-fed. J Nutr.
          128:1692-1702.
 Hofvander, Y.; Hagman,  U.; Hillervik, C.; Siolin, S.
          (1982) The  amount of milk consumed by 1-3
          months old  breast or bottled-fed infants.
          Acta Paediatrica Scand.  71: 953-958.
 Kent, J.C.; Mitoulas, L.R.; Cregan, M.D.; Ramsay,
          D.T.; Doherty, D.A.; Hartmann, P.E.  (2006)
          Volume and frequency of breastfeeding and
          fat content of breast milk throughout the
          day. Pediatrics. 117:387-395.
 Li, R.; Grummer-Strawn, L.  (2002) Racial  and
          ethnic disparities in breastfeeding among
          Unites States infants: third national health
          and nutrition examination survey, 1988-
          1994. Birth. 29(4):251-257.
 Lonnerdal, B.; Forsum, E.; Gebre-Medhim,  M.;
          Hombraes, L. (1976) Human milk
          composition in Ethiopian and Swedish
          mothers: lactose, nitrogen, and protein
          contents.  Am J Clin Nutr. 29:1134-1141.
 Marriott, M.; Campbell, L.; Hirsch, E.; and Wilson,
          D.  (2007) Preliminary data from
          demographic and health surveys on infant
          feeding in 20 developing countries. J. Nutr.
          Vol 137: 518S-523S.
 Maxwell, N.I.;  Burmaster, D.E.  (1993) A simulation
          model to estimate a distribution of  lipid
          intake from  human milk during the first year
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Chapter 15 - Human Milk Intake	
        of life. J Expo Anal Environ Epidemiol.
        3:383-406.
Mitoulas, L.; Kent, J.; Cox, D.; Owens, R.; Sherriff,
        J.; Hartman, P.  (2002) Variation in fat,
        lactose, and protein in human milk over 24 h
        and throughout the first year of lactation. Br
        JNutr. 88:29-37.
Mitoulas, L.; Gurrin, L.; Doherty, D.; Sherriff, J.;
        Hartman, P. (2003) Infant intake of fatty
        acids from human milk over the first year of
        lactation.  Br J Nutr. 90:979-986.
National Academy of Sciences  (NAS). (1991)
        Nutrition during lactation. Washington, DC.
        National Academy Press.
Neubauer, S. H.; Ferris, A.M.; Chase, C.G.; Fanelli
        J., Thompson, C.A.; Lammi-Keefe, C.J.;
        Clark, R. M.; Jensen, R. G.;  Bendel, R. B.;
        Green, K. W. (1993) Delayed lactogenesis
        in women with insulin-dependent diabetes
        mellitus. Am J Clin Nutr. 1993:  58:54-60.
Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.;
        Neifert, M.; et al.  (1988) Studies in human
        lactation: milk volumes in lactating women
        during the onset of lactation and full
        lactation. Am J Clin Nutr.  48:1375-1386.
Pao, E.M.; Hines,  J.M.; Roche, A.F. (1980) Milk
        intakes and feeding patterns of breast-fed
        infants.  J Am Diet Assoc. 77:540-545.
Ryan, A.S.;  Rush, D.; Krieger,  F.W.; Lewandowski,
        G.E. (1991) Recent declines in
        breastfeeding in the United States, 1984-
        1989. Pediatrics.  88:719-727.
Ryan, A.S.  (1997) The resurgence of breastfeeding
        in the United States. Pediatrics. 99(4):el2.
        http: //www .p ediatric s .org/c q i/c ontent/full/9 9
        /4/el2.
Salmenpera, L.; Perheentupa, J.,; Siimes, M.A.
        (1985) Exclusively breast-fed healthy infants
        grow slower than reference infants. Pediatr
        Res. 19:  307-312.
Scanlon, K.S.; Grummer-Strawn, L.; Shealy, K.R.;
        Jefferds, M.E.; Chen, J.; Singleton, J.A..
        (2007) Breastfeeding  Trends and Updated
        National Health Objectives for Exclusive
        Breastfeeding - United States, Birth Years
        2000-2004.  MMWR56(30):760-763.
Stuff I.E.; Nichols B.L. (1989) Nutrient intake and
        growth performance of older infants fed
        human milk. J Pediatr. 1989: 115:959-968.
Wright, C.M.; Parkinson, K.; Scott, J. (2006) Breast-
        feeding in a UK urban context: who breast-
feeds, for how long and does it matter?
Public Health Nutr.  9(6):686-691.
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                                          	Chapter 15 - Human Milk Intake
Table 15-7. Daily Intakes of Human Milk
Intake
Age
Completely Breast-fed
1 month
3 months
6 months
Partially Breast-fed
1 month
3 months
6 months
9 months
" Data expressed as mean
Source: Pao et al., 1980.
Number of Infants
11
2
1
4
11
6
3
± standard deviation.

Mean ± SD
(mL/day) *
600 ±159
833
682
485 ± 79
467 ± 100
395 ± 175
<554


Intake Range
(mL/day)
426 - 989
645 - 1,000
616-786
398 - 655
242 - 698
147 - 684
451 -732


Table 15-8. Human Milk Intakes for Infants Aged 1 to 6 Months
Intake
Age
1 month
2 months
3 months
4 months
5 months
6 months
Source: Dewey and Lonnerdal,
Number of Infants
16
19
16
13
11
11
1983.
Mean ± SD
(mL/day)
673 ± 192
756 ±170
782 ±172
810 ±142
805 ±117
896 ±122

Intake Range
(mL/day)
341-1,003
449-1,055
492-1,053
593-1,045
554-1,045
675-1,096

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Table 15-9. Human Milk Intake Among Exclusively Breast-fed Infants During

1
2
3
4
Age
month
months
months
months
Number of
Infants
37
40
37
41
* Values reported by the
dividing by 1 .03 g/mL
SD
Intake (mL/day)a
Mean ± SD
729 ±126
704 ±127
702±111
718 ±124
Intake (mL/kg-day)a
Mean ± SD
154 ±23
125 ±18
114±19
108 ±17
author in units of g/day and g/kg-day were converted to
(density of human milk).
Calculated by dividing human milk intake (g/day) by
= Standard deviation.
Source: Butte et
al, 1984.

the First 4 Months
Feedings/Day
8.3 ±1.9
7.2 ±1.9
6.8 ±1.9
6.7 ±1.8
of Life
Body
Weight"
(kg)
4.7
5.6
6.2
6.7
units of mL/day and mL/kg-day by
human milk intake (g/kg-day).



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                                          	Chapter 15 - Human Milk Intake

Age
(days)
1
2
3
4
5
6
7
8
9
10
11
14
21
28
35
42
49
56
90
120
150
180
210
240
270
300
330
360
b
SD
Source:
Table 15-10.
Human Milk Intake During a 24-hour Period
Intake ( mL/day )a
Number ol Infants
6
9
10
10
11
9
7
8
9
9
8
9
10
13
12
12
10
12
10
12
12
13
12
9
12
11
8
8
Mean ± SD
43 ±68
177 ± 83
360 ±149
438 ±171
483 ±125
493 ±162
556 ±162
564 ±154
563 ± 74
569 ±128
597 ±163
634 ±150
632 ± 82
748 ±174
649 ±114
690 ±108
688 ±112
674 ± 95
713±111
690 ± 97
814 ±130
744 ±117
700 ±150
604 ± 204
600 ±214
535 ±227
538 ±233
391 ±243
Range
-30-145 b
43-345
203-668
159-674
314-715
306-836
394-817
398-896
456-699
355-841
386-907
404-895
538-763
481-1,111
451-903
538-870
543-895
540-834
595-915
553-822
668-1,139
493-909
472-935
280-973
217-846
125-868
117-835
63-748
Intake by Age Category
(mL/day)a'°






511 ±220







679 ±105

713±111
690 ± 97
814 ±130
744 ±117
700 ±150
604 ± 204
600 ±214
535 ±227
538 ±233
391 ±243
Values reported by the author in units of g/day were converted to units of mL/day by dividing by 1 .03 g/mL
(density of human milk).
Negative value due to insensible weight loss correction.
Multiple data sets were combined by producing simulated data sets fitting the known mean and SD for each
age, compositing the data sets to correspond to age groups of 0 to <1 month and 1 to <2 months, and
calculating new means and SD's on the composited data.
= Standard deviation.
Neville et al, 1988.



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Chapter 15 - Human Milk Intake

Table 15-11
Age
3 months
6 months
9 months
12 months
. Human Milk Intake Estimated by the Darling Study
Number of Infants
73
60
50
42
a Values reported by the author in units of g/day were converted to
1 .03 g/mL (density of human milk).
SD = Standard deviation.
Source: Dewey et al, 1991b.
Intake (mL/day)
Mean ± SD
788 ±129
747 ±166
627 ±211
435 ± 244
units of mL/day by dividing by

Table 15-12.

Ethnicity (White, Black, Hispanic, Asian) (N)
Duration of Breastfeeding (days)
Duration of Formula Feeding (days)
Age at Introduction of Formula (months)
Age at Introduction of Solids (months)
Age at Introduction of Cow's Milk (months)
" Mean ± standard deviation.
N = Number of infants.
Source: Butte et al., 2000.
Mean Breastfed Infants Characteristics a
Boys (N=14)
10/1/2/1
315 ±152
184 ±153
6.2 ±2.9
5.0 ±1.5
13.1 ±3.1



Girls (N=26)
21/1/3/1
362 ±190
105 ±121
5.2 ±2.3
5.0 ±0.09
12.5 ±3.8


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                                          	Chapter 15 - Human Milk Intake
Table 15-13. Mean Human Milk Intake of Breastfed Infants (mL/day)a
Age Group
3 months
6 months
12 months
24 months
a 3 -day average; values reported by the author
1 .03 g/mL (density of human milk); mean ±
N = Number of infants.
Source: Butte et al., 2000.
Boys Girls
790 ± 172 (N=14) 694 ± 108 (N=26)
576±266(N=12) 678 ±250 (N=18)
586 ±286 (N=2) 370± 260 (N=l 1)
in units of g/day were converted to units of mL/day by dividing by
standard deviation.
Table 15-14. Feeding Practices by Percent of Infants
Age
Infants
369
months months months
12
months
18
months
24
months
Percentage
Infants Still Breastfed
Breastfed Infants Given Formula
Formula-fed Infants Given Breast Milk
Use of Cow's Milk for Breastfed Infants
Use of Cow's Milk for Formula-fed Infants
100 80 58
0 40 48
100 100 94
8
28
38
30
47
65
67
25
10
6
82
89
5
2
0
88
92
Source: Butte et al., 2000.
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Chapter 15 - Human Milk Intake

Table 15-15. Body Weight of Breastfed Infants"


0.5 months
3 months
6 months
9 months
12 months
1 8 months
24 months
Weight (kg)
Boys
3.9±0.4(n=14)
6.4±0.6(n=14)
8.1±0.8(n=14)
9.3±1.0(n=14)
10.1 ±1.1 (n=14)
11.6±1.2(n=14)
12.7±1.3(n=12)

Girls
3.7±0.5(n=19)
6.0±0.6(n=19)
7.5±0.6(n=18)
8.4±0.6(n=19)
9.2 ± 0.7(n=19)
10.7 ± 1.0 (n=19)
11.8 ±1.1 (n=19)
* Mean ± standard deviation.
N = Number of infants.
Source: Butte et al, 2000.


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                                                   Chapter 15 - Human Milk Intake














Table 15-16. AAP Dataset Milk Intake
Age
7 days
14 days
30 days
60 days
90 days
120 days
150 days
180 days
210 days
270 days
360 days
b
SD
cv
N
Source:
Mean
(mL/kg day)a
143
156
150
144
127
112
100
101
75
72
47
SD
(mL/kg day)a
37
40
24
22
18
18
21
20
25
23
27
Rates
CV
0.26
0.26
0.16
0.15
0.14
0.16
0.21
0.20
0.33
0.32
0.57
at Different Ages
Skewness
Statistic"
0.598
-1.39
0.905
0.433
-0.168
0.696
-1.077
-1.860
-0.844
-0.184
0.874

N
10
9
25
25
108
57
26
39
8
57
42
Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by
dividing by 1.03 g/mL (density of human milk).
Statistic/SE: -2 < Statistic/SE < +2 suggests a normal distribution
= Standard deviation.
= Coefficient of variation.
= Number of infants.
Arcus-ArthetaL, 2005.


























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Chapter 15 - Human Milk Intake















Table 15-17. Average
Averaging Period

AAP 0 to 6 months
Method 1
Method 2
AAP 0 to 12 months
Method 1
Method 2
EBFOto 12 months
General Pop.
0 to 6 months
Oto 12 months
Mean (SD)


126(21)
123 (7)

98 (22)
99(5)
110(21)

79
51

5

92
112

61
90
75

0
0
Daily Human

10

99
114

69
92
83

0
0
Milk Intake (mL/kg day) a

25

112
118

83
95
95

24
12
Population
50

126
123

98
99
110

92
49
Values reported by the author in units of g/kg-day were converted to
1 .03 g/mt (density of human milk).
Percentile
75 90 95 99

140 152 160 174
127 131 133 138

113 127 135 150
102 105 107 110
124 137 144 159

123 141 152 170
85 108 119 138
units of mL/kg-day by dividing by
Source: Arcus-Arth et al., 2005.















Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed Infants
Age
(months)
1
2
3
4
Number Lipid Content
of (mg/g)
Observations Mean ± SD
37 36.2 ±7. 5
40 34.4 ±6. 8
37 32.2 ±7. 8
41 34.8 ±10.8
Lipid
Content % a
3.6
3.4
3.2
3.5
a Percents calculated from lipid content reported in mg/g.
b Values reported by the author in units of g/day and g/kg-day were converted to
dividing by 1 .03 g/mL (density of human milk).
Source: Butte et al., 1984.
Lipid
Intake
(mL/day)b
Mean ± SD
27 ±8
24 ±7
23 ±7
25 ±8
Lipid
Intake
(mL/kg-day)b
Mean ± SD
5.7 ±1.7
4.3 ±1.2
3.7 ±1.2
3.7 ±1.3
units of mL/day and mL/kg-day by
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                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 15 - Human Milk Intake
Table 15-19. Human Milk Production and
Age Grc
(month
1
2
4
6
9
12
1 to 12
Volume, per Breast
rap (mL/24h)
s)
Mean SE N
416 24 34
408 23 34
421 20 34
413 25 30
354 47 12
252 51 10
399 11 154
Fat
(g/L)
Mean SE
39.9 1.4
35.2 1.4
35.4 1.4
37.3 1.4
40.7 1.7
40.9 3.3
37.4 0.6
a Infants were completely breast-fed to 4
months.
SE
N
Source:
= Standard error.
= Number of infants.
Mitoulas et al, 2002.




N
34
34
32
28
12
10
150
Composition Over the First 12
Lactose
(g/L)
Mean SE
59.7 0.8
60.4 1.1
62.6 1.3
62.5 1.7
62.8 1.5
61.4 2.9
61.4 0.6
Vlonths of Lactation a
Protein
(g/L)
N
18
18
16
16
12
10
90
months and complementary









Mean
10.5
9.6
9.3
8.0
8.3
8.3
9.2
SE
0.4
0.4
0.4
0.4
0.5
0.6
0.2
N
18
18
18
16
12
10
92
Energy
(kJ/mL)
Mean
2.7
2.5
2.6
2.6
2.8
2.8
2.7
SE
0.06
0.06
0.09
0.09
0.09
0.14
0.04
N
18
18
16
16
12
10
90
solid food was introduced between 4-6


















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Chapter 15 - Human Milk Intake














Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content Over
First Year of Lactation a
AgeG
(monl
1
2
4
6
9
12
Itol2
Statistical
roup
N
5
5
5
5
5
5
30

Volume, Left
Breast (mL/day)
Mean
338
364
430
373
312
203
337
NS
SE
52
52
51
75
65
69
26

Volume, Right Breast
(mL/day)
Mean
475
427
482
437
365
302
414
NS
SE
69
42
58
56
94
85
28

Fat, Left Breast
(g/L)
Mean
38
31
32
33
43
40
36
0.004
SE
1.5
2.2
3.3
2.5
2.2
4.8
1.4

the

Fat, Right Breast
(g/L)
Mean
38
30
29
33
38
42
35
0.008
SE
2.6
2.9
2.6
2.5
3.3
5.0
1.5

significance: P
a Infants were completely breast-fed to 4
months.
SE
NS
P
Source:
months, and complementary
solid food was introduced between 4-6
= Standard error.
= No statistical
= Probability.
Mitoulas et al.,
difference.

2003.





















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                                          	Chapter 15 - Human Milk Intake
Table 15-21. Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation (g/100 g total fatty acids)

1 month
Fatty Acid Mean SE
Medium-chain
Saturated
Odd-chain
Saturated
Long-chain
Saturated
Mono-
unsaturated
Trans-
Poly-
unsaturated
SE = Standard
14.2 0.4

0.9 0.01

34.1 0.3
37.5 0.2

2.0 0.08
12.7 0.2
error.
2 months 4 months 6 months 9 months 12 months
Mean SE Mean SE Mean SE Mean SE Mean SE
13.9 0.6 12.0 0.5 11.5 0.2 14.1 0.3 17.0 0.4

0.9 0.02 0.8 0.02 0.8 0.03 0.8 0.02 0.8 0.02

33.7 0.3 32.8 0.3 31.8 0.6 31.4 0.6 33.9 0.6
33.7 0.4 38.6 0.5 37.5 0.5 37.3 0.5 33.0 0.5

2.2 0.1 2.2 0.09 4.6 0.02 1.7 0.2 1.8 0.09
9.5 0.2 11.8 0.4 13.4 0.6 8.0 0.1 6.7 0.03

Source: Mitoulas et al., 2003.
Table 15-22. Comparison of Lipid Content Assumptions (mL/kg-day)a
Lipid Content Used in Mean Population Percentile
Calculation
5 10 25 50 75 90
Measured Lipid Content" 3.6 2.0 2.3 2.9 3.6 4.3 4.9
4% Lipid Content0 3.9 2.5 2.8 3.3 3.8 4.4 4.9
* Values reported by the author in units of g/kg-day were converted to units of mL/kg-day
1 .03 g/mL (density of human milk).
b Lipid intake derived from lipid content and milk intake measurements.
° Lipid intake derived using 4% lipid content value and milk intake.
Source: Arcus-Arth et al., 2005.
95 99
5.2 5.9
5.2 5.8
by dividing by
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Chapter 15 - Human Milk Intake

Table 15-23. Distribution of Average

AAP Infants 0 to 12 months
Mean
3.9
Daily Lipid

5
2.4
a Values reported by the author in units of g/kg-day
g/mL (density of human milk).
Source: Arcus-Arth et al., 2005.
Intake (mL/kg day) assuming 4% Milk

10 25
2.8 3.3
Population
50
3.9
Percentile
75
4.5
were converted to units of mL/kg-day
Lipid Content

90
5.1
by

95
5.4
dividing by 1

99
6.0
03
Table 15-24. Predicted Lipid Intakes for
Statistic
Number of Observations in Simulation
Minimum Lipid Intake
Maximum Lipid Intake
Arithmetic Mean Lipid Intake
Standard Deviation Lipid Intake
a Values reported by the author in units of g/day were
(density of human milk).
Source: Maxwell and Burmaster, 1993.
Breast-fed Infants Under 12 Months of Age
Value
1,113
1 .0 mL/daya
51.0mL/daya
26.0 mL/daya
7.2 mL/daya
converted to units of mL/day by dividing by 1 .03 g/mL
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                                          	Chapter 15 - Human Milk Intake
Table 15-25 Socio-economic Characteristics of Exclusively Breastfed Infants Born in 2004
Percent of Exclusive Breastfeeding Infants Through 3 and 6 Months

Characteristic
U.S. Overall (N=17,654)

%
30.5
3 months
95% CI
29.4-31.6

%
11.3
6 months
95% CI
10.5-12.1
Infant Sex
Male
Female"
30.7
30.3
29.1-32.3
28.7-31.9
10.8
11.7
9.8-11.8
10.5-12.9
Race/Ethnicity (child)
Hispanic
White, non-Hispanic"
Black, non-Hispanic
Asian, non-Hispanic
Other
30.8
33.0
19.8 b
30.6
29.3
28.3-33.3
31.6-34.4
17.0-22.6
25.0-36.2
24.9-33.7
11.5
11.8
7.3"
14.5
12.2
9.7-13.3
10.9-12.7
5.5-9.1
10.0-19.0
9.2-15.2
Maternal Age (years)
<20
20 to 29
>30"
16.8 b
26.2"
34.6
10.3-23.3
24.4-28.0
33.2-36.0
6.1"
8.4"
13.8
1.5-10.7
7.3-9.5
12.7-14.9
Household Head Education
350"
23.9"
26.6"
33.2"
37.7
21.6-26.2
23.8-29.4
30.9-35.5
35.7-39.7
8.3"
8.9"
11.8"
14.0
6.9-9.7
7.2-10.6
10.3-13.3
12.6-15.4
" Referent group.
b p<0.05 by chi-square test, compared with referent group.
N = Number of infants .
MSA = Metropolitan statistical area.
Source: Scanlon et al, 2007.
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Chapter 15 - Human Milk Intake































































Tablel5-26. Geographic-specific Breastfeeding Percent Rates
Ever
State N
Breastfed
U.S. National 17,654 73.8
Alabama 310 52.1
Alaska 217 84.8
Arizona 543 83.5
Arkansas 200 59.2
California 1,702 83.8
Colorado 249 85.9
Connecticut 249 79.5
Delaware 213 63.6
Dist of Columbia 292 68.0
Florida 955 77.9
Georgia 582 68.2
Hawaii 221 81
Idaho 183 85.9
Illinois 561 72.5
Indiana 472 64.7
Iowa 193 74.2
Kansas 480 74.4
Kentucky 245 59.1
Louisiana 429 50.7
Maine 203 76.3
Maryland 512 71.0
Massachusetts 469 72.4
Michigan 604 63.4
Minnesota 202 80.9
Mississippi 287 50.2
Missouri 327 67.3
Montana 232 87.7
Nebraska 228 79.3
Nevada 281 79.7
New Hampshire 228 73.7
New Jersey 631 69.8
New Mexico 420 80.7
New York 533 73.8
North Carolina 220 72.0
North Dakota 285 73.1
Ohio 617 59.6
Oklahoma 280 67.1
Oregon 191 88.3
Pennsylvania 757 66.6
Rhode Island 291 69.1
South Carolina 314 67.4
South Dakota 315 71.1
Tennessee 671 71.2
Texas 1,439 75.4
Utah 190 84.5
Vermont 190 85.2
Virginia 259 79.1
Washington 615 88.4
West Virginia 224 59.3
Wisconsin 478 72.1
Wyoming 246 80.5
a Exclusive breastfeeding information
solids, no water, no other liquids. SE
Breastfed at 6
Months
41.5
25.4
60.9
46.5
23.2
52.9
42
44.6
35.7
40.0
37.5
38.0
50.5
49.0
40.9
34.6
44.9
42.2
26.4
19.2
46.6
40.2
42.1
36.4
46.5
23.3
32.5
53.8
47.6
45.6
48.7
45.1
41.2
50.0
34.2
45.1
33.3
29.6
56.4
35.2
31.2
30.0
40.5
32.6
37.3
55.6
55.3
49.8
56.6
26.8
39.6
42.9
is from the 2006 NIS
mple sizes appearing
Breastfed at
Months
20.9
11.5
31.8
23.4
8.5
30.4
23.6
23.7
14.6
21.4
15.6
16.8
35.5
22.6
17.6
18.0
20.0
16.9
14.4
8.3
27.6
21.2
19.0
18.6
23.8
8.2
15.8
28.8
21.8
21.9
27.5
19.4
21.1
26.9
18.3
19.5
12.9
12.7
33.5
16.8
14.0
11.1
23.4
16.6
18.7
28.1
34.1
25.6
32.3
14.0
19.0
18.5
survey data


Among Children Born in 2004 a
12 Exclusive Breastfeeding
Breastfeeding
Through 6 Months
Through 3 Months
30.5
19.3
47.2
38.8
15.8
38.7
36.2
35.6
26.3
27.8
27.8
25.6
37.8
38.7
31.6
28.3
37.6
30.0
25.3
15.2
42.1
32.1
32.7
27.4
33.9
19.0
26.6
50.9
31.7
31.9
34.3
27.0
32.9
26.0
23.0
39.4
27.2
23.0
41.5
27.1
31.2
26.6
32.2
26.7
25.2
39.8
47.3
32.6
49.6
21.3
32.5
36.2
only and is defined as
11.3
4.9
24.3
14.3
6.2
17.4
10.8
10.1
11.4
9.8
9.1
11
15.8
10.3
10
10.4
11.6
9.2
7.5
2.8
15.9
8.6
11.9
8.3
16.1
8
7.4
18.3
9.8
10.3
13.6
11.8
14.3
11.4
6.9
15.4
9.8
10.6
19.9
8
9.5
5.4
12.2
11.9
7.1
10.2
15.9
13.4
22.5
5.2
13.4
11.4
ONLY breast milk- No
in the NIS breastfeeding tables are slightly smaller than the
numbers published in other NIS publications due to the fact that in the DNPA breastfeeding
limited to records with valid responses to the breastfeedin
N - Number of infants.
Source: CDC, 2007.


g questions.





analyses, the sample was































































Child-Specific Exposure Factors Handbook                                      Page
September 2008	15-35

-------
                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 15 - Human Milk Intake
Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0 to 6 Months Old a
Country
Ethiopia
Ghana
Kenya
Malarwi
Nambia
Nigeria
Uganda
Zamibia
Zimbabwe
Armenia
Egypt
Jordan
Bangladesh
Cambodia
India
Indonesia
Nepal
Philippines
Vietnam
Kazakhstan
Pooled
Breastfeeding
98.8
99.6
99.7
100
95.3
99.1
98.7
99.6
100
86.1
95.5
92.4
99.6
98.9
98.1
92.8
100
80.5
98.7
94.4
96.6
Water
26.3
41.9
60
46
65.4
78.2
15.1
52.6
63.9
62.7
22.9
58.5
30.2
87.9
40.2
37
23.3
53.4
45.9
53.7
45.9
Milk
19
6.7
35.1
1.4
0
9.2
20.3
2.1
1.6
22.9
11.1
3
13.6
2.1
21.2
0.7
12.3
4.4
16.9
21.4
11.9
Formula
0
3.5
4.8
1.7
0
12.7
1.5
2.7
3.2
13.1
4.3
25.1
5.3
3.3
0
24.2
0
30
0.8
8.2
9
a Percentage of mothers who stated that they currently breast-feed and separately
liquid or solid food in the past 24 hours by country for infants age 0 to 6 months
Source: Marriott et
al, 2007.



Other Liquids
10.8
4.3
35.9
5.2
17.9
17.9
10.3
6.7
9
48.1
27.6
13.8
19.7
6.7
7.1
8.7
2.8
12.4
8.9
37.4
15.1
had fed their infants 4
old.

Solid Foods
5.3
15.6
46.3
42.3
33.4
18.5
11.4
31.2
43.7
23.9
13.2
20.2
20.3
16.6
6.5
43
9.3
16.8
18.7
15.4
21.9
categories of

Page
15-36
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 15 - Human Milk Intake	
Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6 to 12 Months Old"
Country
Ethiopia
Ghana
Kenya
Malarwi
Nambia
Nigeria
Uganda
Zamibia
Zimbabwe
Armenia
Egypt
Jordan
Bangladesh
Cambodia
India
Indonesia
Nepal
Philippines
Vietnam
Kazakhstan
Pooled
Breastfeeding Water
99.4
99.3
96.5
99.4
78.7
97.8
97.4
99.5
96.7
53.4
89.1
65.7
96.2
94.4
94.9
84.8
98.8
64.4
93.2
81.2
87.9
69.2
88.8
77.7
93.5
91.9
91.6
65.9
91.7
92.5
91.1
85.9
99.3
87.7
97.5
81.4
85.4
84.3
95.1
95
74.3
87.4
Milk
37.6
14.6
58.7
5.9
0
14.4
32.1
8.2
8.7
56.9
36.8
24.3
29.8
3.7
45
4.9
32
12.2
36.1
85.4
29.6
Formula Other Liquids Solid Foods
0
9.6
6
3.2
0
13.4
1.6
5
2.4
11.6
16.7
28.8
10.1
6.7
0
38.8
0
47.1
5.3
11.4
15.1
23.9
23.9
56.4
31.2
42.7
27.4
56.2
25.9
49.9
85.3
48.5
57.7
21.9
29
25.2
35.4
15.8
31
37.9
91.8
41.6
a Percentage of mothers who stated that they currently breast-feed and separately had fed their infants 4
liquid or solid food in the past 24 hours by country for infants age 6 to 12 months old.
Source: Marriott et
al, 2007.




54.7
71.1
89.6
94.9
79.5
70.4
82.1
90.2
94.8
88.1
75.7
94.9
65.2
81
44.1
87.9
71.5
88
85.8
85.9
80.1
categories of

Child-Specific Exposure Factors Handbook
September 2008	
Page
15-37

-------
                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 15 - Human Milk Intake
Table 15-29. Population Weighted Averages of Mothers Who Reported
Selected Feeding Practices During the Previous 24-hours
Feeding Practices
Infant Age
0 to 6 months 6 to 12 months
Percentage (weighted N)
Current Breast-feeding
Gave Infant:
Water
Tinned, Powdered, or Other Milk
Commercial Formula
Other Liquids
Any Solid Food
N = Number of infants .
Source: Marriott et al, 2007.
96.6 (22,781) 87.9 (18,944)

45.9(10,767) 87.4(18,6663)
11.9(2,769) 29.6(6,283)
9.0(1,261) 15.1(1,911)
15.1(3,531) 41.6(8,902)
21.9(5,131) 80.1(17,119)


Page                                       Child-Specific Exposure Factors Handbook
15-38	September 2008

-------
Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake	
                Table 15-30.  Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III (1988-1994)
                                                                                                      Absolute Difference (%,SE)"
                            Non-Hispanic White       Non-Hispanic Black        Mexican American      White vs Black   White vs Mexican
                                                                                                                      American
      Characteristic          N       %      (SE)      N       %      (SE)     N      %      (SE)     %      (SE)      %      (SE)
      All infants           1,869    60.3     2.0    1,845    25.5     1.4     2,118    54.4     1.9    34.8     (2.0)b     6.0    (2.3)"
    Infant sex
      Male                901     60.4     2.6     913     24.4     1.6     1,033    53.8     1.8    35.9     (2.9)b     6.6    (2.8)"
      Female               968     60.3     2.3     932     26.7     1.9     1,085    54.9     2.9    33.7     (2.6)b     5.4    (3.4)°
    Infant birth weight (g)
                           118     40.1     5.3     221     14.9     2.6      165      34.1     3.9    25.1     (5.8)b     5.9    (6.4)°
                          1,738    62.1     2.1    1,584    26.8     1.6     1,838     55.7     2.0    35.3     (2.1)b     6.4    (2.5)"
    Maternal age (years)
      <20                  175     33.7     4.4     380     13.1      2.1     381     43.7     3.0    20.6     (4.8)b     -10    (5.1)°
      20 to 24              464     48.3     3.0     559     22.0      2.0     649     54.8     2.6    26.4     (3.7)b     -6.4    (4.2)°
      25 to 29              651     65.4     2.2     504     30.6      2.5     624     56.9     3.3    34.8     (3.1)b     8.6    (4.0)"
      >30                 575     71.9     2.7     391     36.1      2.3     454     59.6     2.8    35.8     (3.4)b     12.3    (3.4)b
    Household head education
      30                 204     48.6     4.8     415     24.3     2.7     359     47.1     4.4    24.3     (5.3)b     1.5    (6.1)°
    Residence
      Metropolitan          762     67.2     3.0     943     32.0     1.9     1,384    56.1     2.0    35.3     (2.6)b     11.2    (2.9)b
      Rural               1,107    54.9     3.1     902     18.3     1.9     734     51.3     3.1    36.6     (2.7)b     3.6    (4.0)°
    Region
      Northeast            317     51.6     4.6     258     34.2     4.4      12     74.1     10.4    17.3     (3.6)b    -22.5    (14.5)c
      Midwest             556     61.7     2.3     346     26.5     2.4      170     51.5     3.7    35.2     (3.3)b     10.2    (5.0)"
      South                748     52.7     2.7     1,074    19.4     2.0      694     42.7     3.5    33.3     (2.7)b      10     (4.6)"
      West                248     82.4     3.9     167     45.1     5.1     1,242    59.1     2.2    37.3     (7.1)b     23.4    (3.3)b
    Poverty income ratio (%)
      <100                 257     38.5     4.2     905     18.2     1.9     986     48.2     2.8    20.3     (4.4)b     -9.6    (4.7)"
      100to<185           388     55.7     2.6     391     26.8     2.1     490     54.1     3.4    28.9     (3.5)b     1.5    (4.2)°
      185to<350           672     61.9     2.5     294     32.0     3.0     288     64.7     4.7    30.0     (3.7)b     2.8    (5.3)=
      >350                444     77.0     2.5     105     58.1     5.1      74     71.9     9.0    19.0     (5.6)b     5.2    (9.0)°
      Unknown            108     44.7     7.1     150     25.5     3.9     280     59.5     2.8    19.2     (7.9)"    -14.8    (7.9)°
              p<0.05.
              p<0.01.
              No statistical difference.
    N         - Number of infants.
    SE        - Standard error.
    Source:    Li and Grummer-Strawn, 2002.
Child-Specific Exposure Factors Handbook                                                                Page
September 2008	15-39

-------
                                                                       Child-Specific Exposure Factors Handbook
                                                                      	Chapter 15 - Human Milk Intake
                                 Table 15-31. Racial and Ethnic Differences in Proportion of Children Who
                                    Received Any Human Milk at 6 Months (NHANES III,  1988-1994)
                                                                                                     Absolute Difference (%,SE)
                           Non-Hispanic White
                                      Non-Hispanic Black
                                                                            Mexican American
                                                                                                 White vs Black   White vs Mexican
                                                                                                                     American
      Characteristic
                                          (SE)
                                                  No.
                                                     (SE)
                                                         (SE)
                                                               (SE)
                                                                         (SE)
      All infants
                          1863
                                  26.8
                                           1.6
                                                                           '112
                                                                                   23.1
                                                                                           1.4
                                                                                                  18.3
                                                                                                         (1.7)"
                                                                                                                   3.7
   Infant sex
      Male
      Female
             900
             963
27.6
26.1
2.3
1.8
 912
 930
8.5
8.6
1.1     1,029
1.1     1,083
         22.3
         24.0
                                                                                      1.6
                                                                                      2.0
       19.1
       17.5
       (2.6)b
       (2.1)'
         5.2
         2.1
        (2.6)'
        (2.7)=
   Infant birth weight (g)
      <2,500
      > 2,500
             118
            1,733
10.9
28.3
3.1
1.8
 221
1,581
4.2
9.0
1.8
0.9
 165
1,832
                                                                             15.2
                                                                             23.1
4.7
1.7
6.7
19.3
(3.3)'
-4.3
5.2
(5.7)=
(2.3)'
   Maternal age (years)
      <20
      20 to 24
      25 to 29
      >30
             174     10.2
             461     13.4
             651     29.3
             573     39.0
         2.9
         2.4
         2.6
         2.6
        380
        559
        503
        389
         4.7
         7.5
         10.9
         10.7
        1.4
        1.1
        2.0
        1.7
        380     11.6
        646     23.8
        624     24.6
        452     30.0
                 1.7    5.5    (3.0)°
                 2.4    5.9    (2.5)'
                 2.6    18.4    (3.5)b
                 2.8    28.4    (3.3)b
                                                                                                            -1.3    (3.8)°
                                                                                                            -10.4    (3.3)b
                                                                                                            4.8     (3.6)°
                                                                                                            9.0     (3.6)"
   Household head education
350
      Unknown
             387     23.5
             670     30.4
             443     33.0
             108     13.3
         2.9
         2.7
         3.0
         3.8
        390
        293
        105
        149
         9.9
         10.0
         15.2
         6.4
        1.8
        2.4
        2.8
        2.9
        486     23.4
        287     27.6
        74      32.3
        280     26.7
                                                                                     2.7
                                                                                     4.4
                                                                                     9.0
                                                                                     4.5
                        13.6    (3.9)b
                        20.4    (4.0)b
                        17.8    (4.2)b
                                                                                                  7.0
                                                                                                          (5.3)=
                        0      (4.1)=
                       2.9     (4.8)=
                       0.7     (9.5)=
                       -13.4    (6.6)'
             p<0.05.
             p<0.01.
   N
   SE
   Source:
No statistical difference.
- Number of individuals.
- Standard error.
Li and Grummer-Strawn, 2002.
Page
15-40
                                                         Child-Specific Exposure Factors Handbook
                                                        	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 15 - Human Milk Intake	
Table 15-32.
Racial and Ethnic Differences in Proportion of Children Exclusively
Breastfed at 4 Months (NHANES III, 1991-1994)
Non-Hispanic White
Characteristic N
All infants 824
%
22.6
(SE)
1.7
Non-Hispanic Black
N
906
%
8.5
(SE)
1.5
Mex
N
957
can Amer
%
20.4
Absolute Difference (%,SE)
lean White
(SE) %
1.4 14.1
vs Black
(SE)
(2.2)b
White vs Mexican
American
%
2.3
(SE)
(1.6)=
Infant sex
Male 394
Female 430
22.3
23.0
1.9
2.2
454
452
7.0
10.0
1.6
2.2
498
459
20.7
20.0
1.5 15.3
1.8 12.9
(2.6)b
(3.0)b
1.5
3.0
(1.8)=
(2.1)=
Infant birth weight (g)
<2500 50
>2500 774
15.2
23.1
7.1
1.8
118
786
7.0
8.8
2.3
1.6
66
880
5.6
21.6
1.8 8.2
1.4 14.4
(8.1)=
(2.2)b
9.5
1.5
(6.9)=
(1.6)=
Maternal age (years)
<20 76
20 to 24 205
25 to 29 271
>30 27°
6.6
11.4
21.6
34.8
3.2
2.2
2.3
2.7
172
273
254
201
6.4
7.4
8.6
11.9
2.1
2.4
2.5
2.6
170
319
256
210
12.1
21.0
22.1
23.6
2.5 0.2
2.3 4.0
2.5 13.0
3.1 22.9
(3.7)=
(2.7)=
(3.2)b
(4.2)b
-5.6
-9.6
-0.5
11.1
(3.8)=
(3.2)b
(3.2)=
(3.7)b
Household head education
30 91
24.8
19.7
15.4
2.1
4.3
3.8
407
230
230
8.0
8.6
9.0
1.9
1.9
2.9
417
261
184
19.4
23.1
15.9
1.9 16.8
3.4 11.1
2.3 6.4
(3.0)b
(4.6)"
(5.2)=
5.4
-3.4
-0.5
(2.3)"
(4.9)=
(4.6)=
Residence
Metropolitan 312
Rural 512
24.4
21.3
3
1.8
535
371
11.0
4.2
2.0
1.3
608
349
19.6
22.3
1.6 13.4
3.3 17.1
(3.5)b
4.8
-1.1
(2.8)=
(3.0)=
Region
Northeast 138
Midwest 231
South 378
West 77
20.0
26.5
14.1
34.7
1.4
3.2
2.8
2.7
131
143
574
58
11.1
12.6
5.9
12.5
2.9
5.6
1.4
5.0
10
98
383
466
9.4
19.2
15.9
23.0
9.5 8.8
4.1 13.9
3.1 8.2
1.3 22.2
(2.2)b
(7.6)=
(1.9)"
(5.4)b
10.6
7.4
-1.8
11.7
(8.7)=
(3.7)=
(3.7)=
(2.5)
Poverty income ratio (%)
<100 116
100to<185 166
185to<350 274
>350 235
Unknown 33
13.1
18.9
25.1
27.4
16.5
3.3
3.2
3.2
4.1
7.6
448
197
145
57
59
5.7
10.6
12.9
12.8
7.3
1.6
2.8
4.3
3.5
3.7
471
234
132
37
83
18.4
21.9
26.4
17.0
16.1
1.8 7.4
4.1 8.3
4.2 12.2
5.0 14.6
5.1 9.2
(3.5)"
(3.3)"
(5.0)"
(5.0)b
(8.6)=
-5.3
-3
-1.3
10.4
0.4
(3.1)=
(6.1)=
(4.1)=
(5.2)=
(9.5)=
p<0.05.
* p<0.01.
No statistical difference.
N - Number of individuals.
SE - Standard error.
Source: Li and Grummer-Strawn, 2002.
Child-Specific Exposure Factors Handbook
September 2008	
Page
15-41

-------
                                           Child-Specific Exposure Factors Handbook

                                          	Chapter 15 - Human Milk Intake
Table 15-33. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6 Months of Age in
United States in 1989 and 1995, by Ethnic Background and Selected Demographic Variables
Characteristic
All Infants
White
Black
Hispanic
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Total Family Income
<$10,000
$10,000 to $14,999
$15,000 to $24,999
> 25,000
Maternal Education
Grade School
High School
College
Maternal Employment
Employed Full Time
Employed Part Time
Not Employed
Birth Weight
Low (< 2,500 g)
Normal
Parity
Primiparous
Multiparous
WIC Participation'
Participant
Nonparticipant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
the
Percentage of Mothers Breast-Feeding
In Hospital
1989
52.2
58.5
23.0
48.4

30.2
45.2
58.8
65.5
66.5

31.8
47.1
54.7
66.3

31.7
42.5
70.7

50.8
59.4
51.0

36.2
53.5

52.6
51.7

34.2
62.9

52.2
47.4
47.6
55.9
43.8
37.9
46.0
70.2
70.3
1995
59.7
64.3
37.0
61.0

42.8
52.6
63.1
68.1
70.0

41.8
51.7
58.8
70.7

43.8
49.7
74.4

60.7
63.5
58.0

47.7
60.5

61.6
57.8

46.6
71.0

61.2
53.8
54.6
61.9
54.8
44.1
54.4
75.1
75.1
Change"
14.4
9.9
60.9
26.0

41.7
16.4
7.3
4.0
5.3

31.4
9.8
7.5
6.6

38.2
16.9
5.2

19.5
6.9
13.7

31.8
13.1

17.1
11.8

36.3
12.9

17.2
13.5
14.7
10.7
25.1
16.4
18.3
7.0
6.8
The percent change was calculated using the following formula: % breastfed in 1984 - %
Figures in parentheses indicate a decrease in the rate of breastfeeding from 1989 to 1995.
0 WIC indicates Women
Source: Ryan, 1997.
1989
18.1
21.0
6.4
13.9

5.6
11.5
21.1
29.3
34.0

8.2
13.9
18.9
25.5

11.5
12.4
28.8

8.9
21.1
21.6

9.8
18.8

15.1
21.1

8.4
23.8

18.6
16.8
16.7
18.4
13.7
11.5
13.6
28.3
26.6
breastfed in
At 6 Months
1995
21.6
24.1
11.2
19.6

9.1
14.6
22.9
29.0
33.8

11.4
15.4
19.8
28.5

17.1
15.0
31.2

14.3
23.4
25.0

12.6
22.3

19.5
23.6

12.7
29.2

22.2
19.6
18.9
21.4
18.6
13.0
17.0
30.3
30.9
19897% breastfed in

Change"
19.3
14.8
75.0
41.0

62.5
27.0
8.5
(1.0)"
(0.6)b

39.0
10.8
4.8
11.8

48.7
21.0
8.3

60.7
10.9
15.7

28.6
18.6

29.1
11.8

51.2
22.7

19.4
16.7
13.2
16.3
35.8
13.0
25.0
7.1
16.2
1984.
, Infants, and Children supplemental food program.






Page                                       Child-Specific Exposure Factors Handbook
15-42	September 2008

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Child-Specific Exposure Factors Handbook
Chapter 15 - Human Milk Intake
Table 15-34. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 6 and 12
Months of Age in the United States in 2003, by Ethnic Background and Selected Demographic Variables

Characteristic
All Infants
White
Black
Hispanic
Asian
Maternal Age (years)
<20
20 to 24
25 to 29
30 to 34
35+
Maternal Education
Any Grade School
Any High School
No College
College
Maternal Employment
Employed Full Time
Employed Part Time
Total Employed
Not Employed
Low Birth Weight <5 Ibs 9oz
Parity
Primiparous
Multiparous
WIC Participation"
Participant
Nonparticipant
U.S. Census Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
a WIC indicates Women, Infants,
Source: Abbott, 2003.
Percentage of Mothers Breast-Feeding
In Hospital At 6 Months
44
53
26
33
39
28
40
48
50
47

26
35
35
55
44
49
45
43
27
48
43
32
55
52
36
44
55
42
37
37
53
50
and Children supplemental

18
20
10
15
23
9
13
20
23
23

13
12
12
24
11
19
14
21
10
17
19
11
25
22
17
17
18
16
11
15
23
24
food program.

At 12 Months
10
12
5
12
12
4
8
10
14
14

17
8
8
14
6
11
8
13
6
10
11
7
14
11
9
9
9
10
7
8
16
15


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                                                     Child-Specific Exposure Factors Handbook

                                                    	Chapter 15 - Human Milk Intake
Table 15-35. Number of Meals Per Day
Age (months)
1
2
3
" Data expressed
Source: Hofvander et al
Bottle-fed Infants
(meals/day) "
5.4 (4-7)
4.8 (4-6)
4.7 (3-6)
as mean with range in parentheses.
, 1982.
Breast-fed
(meals/day) "
5.8 (5-7)
5.3 (5-7)
5.1 (4-8)

              Table 15-36. Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD)
 Breastfeeding Episodes per Day               5.8 ±2.6             6.8 ±2.4             2.5 ± 2.0

 Total Time Breastfeeding (min/day)            65.2 ±44.0           102.2 ±51.4          31.2 ±24.6

 Length of Breastfeeding (min/episode)          10.8 ±6.1            14.2 ±6.1             11.6±5.6
 SD      = Standard deviation

 Source:   Buckley, 2001.
Page                                               Child-Specific Exposure Factors Handbook
15-44	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                                   TABLE OF CONTENTS

16     ACTIVITY FACTORS 	16-1
       16.1    INTRODUCTION	16-1
       16.2    RECOMMENDATIONS 	16-1
       16.3    ACTIVITY PATTERNS 	16-7
              16.3.1  KEY STUDIES 	16-7
                     16.3.1.1   Wiley etal, 1991  	16-7
                     16.3.1.2   U.S. EPA, 1996	16-8
              16.3.2  RELEVANT STUDIES 	16-9
                     16.3.2.1   Timmer et al., 1985	16-9
                     16.3.2.2   Robinson and Thomas, 1991 	16-10
                     16.3.2.3   Funk etal., 1998 	16-11
                     16.3.2.4   U.S. EPA, 2000  	16-11
                     16.3.2.5   Hubal et al., 2000  	16-12
                     16.3.2.6   Wong et al., 2000  	16-12
                     16.3.2.7   Graham and McCurdy, 2004	16-13
                     16.3.2.8   Vandewater et al., 2004	16-14
                     16.3.2.9   Juster et al. (2004)	16-14
                     16.3.2.10  U.S. Department of Labor, 2007 	16-14
                     16.3.2.11  Nader etal. 2008	16-15
       16.4    REFERENCES FOR CHAPTER 16	16-15
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September 2008	16-i

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                                                     Child-Specific Exposure Factors Handbook

                                                    	Chapter 16 - Activity Factors
                                         LIST OF TABLES

Table 16-1.     Recommended Values for Activity Factors	
Table 16-2.     Confidence in Recommendations for Activity Factors	
Table 16-3.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, for All Respondents and Doers	
Table 16-4.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, by Age and Gender 	
Table 16-5.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
               Categories, Grouped by Seasons and Regions  	
Table 16-6.     Time (minutes/day) Children Under 12 Years of Age Spent in Six Major Location
               Categories, for All Respondents and Doers	
Table 16-7.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
               Categories, Grouped by Age and Gender 	
Table 16-8.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location
               Categories, Grouped by Season and Region  	
Table 16-9.     Mean Time (minutes/day) Children Under 12 Years of Age Spent in
               Proximity to Two Potential Sources of Exposure, Grouped by All Respondents,
               Age, and Gender 	
Table 16-10.    Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
               Grouped by Age and Gender 	
Table 16-11.    Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
               Whole Population and Doers Only	
Table 16-12.    Time Spent (minutes/day) at Selected Indoor Locations Whole Population
               and Doers Only  	
Table 16-13.    Time Spent (minutes/day) in Selected Outdoor Locations Whole Population
               and Doers Only  	
Table 16-14.    Mean Time Spent (minutes/day) Inside and Outside, by Age Category	
Table 16-15.    Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
               Whole Population and Doers Only	
Table 16-16.    Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only ....
Table 16-17.    Number of Showers Taken per Day, by Number of Respondents	
Table 16-18.    Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing
               and Showering  	
Table 16-19.    Range of Number of Times Washing the Hands at Specified Daily Frequencies by
               the Number of Respondents	
Table 16-20.    Number of Times Swimming in a Month in Freshwater Swimming Pool by the
               Number of Respondents  	
Table 16-21.    Time Spent (minutes/month) Swimming in Freshwater Swimming Pool  	
Table 16-22.    Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population
               and Doers Only  	
Table 16-23.    Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air 	
Table 16-24.    Time Spent (minutes/day) with Smokers Present 	
Table 16-25.    Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex
               and Type of Day  	
                                         .  16-3
                                         .  16-6

                                         16-17

                                         16-18

                                         16-19

                                         16-20

                                         16-21

                                         16-22


                                         16-23

                                         16-24

                                         16-25

                                         16-29

                                         16-31
                                         16-33

                                         16-34
                                         16-36
                                         16-40

                                         16-41

                                         16-43

                                         16-44
                                         16-45

                                         16-46
                                         16-48
                                         16-48

                                         16-49
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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                                   LIST OF TABLES (continued)

Table 16-26.    Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different
               Age Groups  	16-50
Table 16-27.    Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week	16-51
Table 16-28.    Mean Time Spent (minutes/day) in Various Microenvironments, Children Ages 12 to
               17 Years National and California Surveys 	16-52
Table 16-29.    Gender and Age Groups  	16-53
Table 16-30.    Assignment of At-Home Activities to Inhalation Rate Levels for Children  	16-54
Table 16-31.    Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents
               and Children 	16-55
Table 16-32.    Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents) 	16-55
Table 16-33.    Comparison of Mean Time Spent (minutes/day) At-Home, by Gender and Age
               for Children	16-56
Table 16-34.    Number of Person-Days/Individuals for Children in CHAD Database  	16-57
Table 16-35.    Time  Spent (hours/day) in Various Microenvironments, by Age  	16-58
Table 16-36.    Mean Time Children Spent (hours/day) Doing Various Macroactivities
               While Indoors at Home  	16-59
Table 16-37.    Time  Children Spent (hours/day) in Various Microenvironments, by Age
               Recast into New Standard Age Categories 	16-60
Table 16-38.    Time  Children Spent (hours/day) in Various Macroactivities While Indoors at Home
               Recast Into New Standard Age Categories	16-61
Table 16-39.    Number and Percentage of Respondents with Children and Those Reporting
               Outdoor Play Activities in both Warm and Cold Weather  	16-62
Table 16-40.    Play Frequency and Duration for all Child Players (from SCS-II data)   	16-63
Table 16-41.    Hand  Washing and Bathing Frequency for all Child Players (from SCS-II data)  	16-63
Table 16-42.    NHAPS and SCS-II Play Duration Comparison	16-64
Table 16-43.    NHAPS and SCS-II Hand Wash Frequency Comparison  	16-64
Table 16-44.    Time  Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only)	16-65
Table 16-45.    Comparison of Daily Time Spent Outdoors (minutes/day), Considering Gender
               and Age Cohort (Doers Only)	16-66
Table 16-46.    Time  Spent (minutes/day) Indoors Based on CHAD Data (Doers Only)	16-67
Table 16-47.    Time  Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only)	16-68
Table 16-48.    Time  Spent (minutes/two-day period) in Various Activities by Children Participating
               in the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement
               (CDS) 	16-69
Table 16-49.    Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday	16-70
Table 16-50.    Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day .  . 16-71
Table 16-51.    Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to 1716-72
Table 16-52.    Mean Time Use (hours/day) by Children, Ages 15 to 19 Years	16-73
Table 16-53.    Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity 	16-74
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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
16    ACTIVITY FACTORS
16.1  INTRODUCTION
      As a consequence of a child's immaturity and
small stature, certain activities and behaviors specific
to children  place them  at  higher risk  to certain
environmental agents (Chance and Harmsen,  1998).
Individual   or  group   activities   are  important
determinants of potential exposure, because  toxic
chemicals introduced into the environment  may not
cause harm to a child until an activity  is performed
that  subjects  the  child to  contact  with  those
contaminants.  An activity or time spent in a given
activity will vary among children on the basis of, for
example, culture, ethnicity, hobbies, location, gender,
age,  socioeconomic characteristics,  and  personal
preferences. However, limited information is available
regarding  ethnic,   cultural  and   socioeconomic
differences in children's choice of activities or time
spent in a given activity.
      It is difficult to accurately collect/record data for
a  child's activity  patterns  (Hubal  et al., 2000).
Children engage in more contact activities than adults;
therefore, a much wider distribution of activities need
to be considered when assessing children's exposure
(Hubal et al., 2000). Behavioral patterns, preferred
activities, and developmental stages result in  different
exposures for children than for adults  (Chance and
Harmsen,  1998).   Other factors  that may  affect
children's activity  patterns  include:  social  status,
economics, and the cultural practices of their  families.
      This chapter summarizes data on how much
time children spend participating in various activities
in various microenvironments.  Information on the
frequency of performing  various activities is also
provided.  The data in this chapter cover a wide range
of activities and populations, arranged by age group
when such data are available. One of the objectives of
this  handbook is to provide recommended exposure
factor values using a consistent set of age groups. In
this  chapter, several studies  are used as sources for
activity pattern data. In some cases, the source data
could be retrieved and analyzed using the standard age
groupings recommended in Guidance for Monitoring
and Assessing Childhood Exposures to Environmental
Contaminants (U.S. EPA, 2005). In other cases, the
original source data were not available, and the study
results are presented here using the same age groups as
the original study, whether or not they conform to the
standard age groupings.
      The recommendations for activity factors are
provided in the next section, along with a summary of
the confidence ratings for these recommendations.
The  recommended values are based on key studies
identified by U.S. EPA for this factor.  Following the
recommendations, key studies on activity patterns are
summarized.  Relevant data on activity patterns are
also  presented to provide the reader with  added
perspective  on  the  current  state-of-knowledge
pertaining to activity patterns in children.

16.2  RECOMMENDATIONS
      Assessors  are   commonly   interested  in
quantitative information describing several types of
time use data  for children including: time spent
indoors and outdoors; time spent bathing, showering,
and  swimming;  and time spent playing on various
types of surfaces.  The recommended values for these
factors  are summarized in Table 16-1.  Note that,
except for swimming, all activity factors are reported
in units of minutes/day.   Time spent swimming is
reported in units of minutes/month.  These data are
based on two key studies presented in this chapter: a
study of children's  activity patterns  in  California
(Wiley et al., 1991) and the National Human Activity
Pattern  Survey (NHAPS)  (U.S. EPA, 1996).   Both
mean and 95th percentile recommended values are
provided.  However, because these recommendations
are based on short-term survey data, 95th percentile
values may be misleading for estimating chronic (i.e.,
long term) exposures and should be used with caution.
Also, the upper percentile values for some activities are
truncated  as  a  result of the  maximum   response
included in the survey (e.g., durations of more than
120 minutes/day were reported as 121 minutes/day),
and  could not be further refined).   The confidence
ratings  for the recommendations are presented in
Table 16-2.
      The  recommendations for total time spent
indoors and the total time spent outdoors are based on
U.S. EPA re-analysis of the source data from Wiley et
al. (1991) for children < 1 year of age and U.S. EPA
(1996) for age groups > 1 year of age. Although Wiley
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                                           Page
                                           16-1

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                                                      Child-Specific Exposure Factors Handbook

                                                     	Chapter 16 - Activity Factors
et al. (1991) is a study of California children and the
sample size was very small for infants, it provides data
for children's activities for the younger age groups.
Data from U.S. EPA (1996) are representative of the
U.S. general population.  In some cases, however, the
time spent indoors or  outdoors would  be better
addressed on a site-specific basis since the times are
likely to vary depending on the  climate, residential
setting (i.e., rural versus urban), personal traits (e.g.,
health status) and personal habits. The recommended
values for time spent indoors at a residence, duration
of showering and bathing, and time spent swimming
are based on a U.S. EPA re-analysis of the source data
from U.S. EPA (1996).  Likewise, the recommended
values for time spent playing on sand, gravel, grass or
dirt are based on a U.S. EPA re-analysis of the source
data from U.S. EPA (1996).
Page
16-2
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-1. Recommended Values for Activity Factors
Age Group


Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to
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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors

Age Group
Table 16-1
Mean
Recommended Values for Activity Factors (continued)
95th Percentile Source


Bathing
minutes/day
Birth to <1 year
1 to <2 years
2 to <3 years
3 to <6 years
6 to
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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                          Table 16-1. Recommended Values for Activity Factors (continued)
     Age Group
Mean
95th Percentile
                      Source
                                               Playing on Dirt
                                                minutes/day
  Birth to <1 year
  1 to < 2 years
  2 to <3 years
  3 to <6 years
  6 to
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                                                            Child-Specific Exposure Factors Handbook

                                                           	Chapter 16 - Activity Factors
                           Table 16-2. Confidence in Recommendations for Activity Factors
  General Assessment Factors
                      Rationale
Rating
  Soundness
   Adequacy of Approach
   Minimal (or Defined) Bias
The survey methodologies and data analyses were
adequate.  In the U.S. EPA (1996) study, responses were
weighted according to this demographic data.  The
California children's activity pattern survey design (Wiley
et al., 1991) andNHAPS (U.S. EPA, 1996) consisted of
large overall sample sizes that varied with age. Data were
collected via questionnaires and interviews.

Measurement or recording error may have occurred since
the diaries were based on 24 hour recall.  The sample sizes
for some age groups were small  for some activity factors.
The upper ends of the distributions were truncated for
some factors. The data were based on short-term data.
                                                             High
 Applicability and Utility
   Exposure Factor of Interest

   Representativeness
   Currency
   Data Collection Period
                                                           Medium
The key studies focused on activities of children.

U.S. EPA (1996) was a nationally representative survey of
the U.S. population; the Wiley et al. (1991) survey was
conducted in California and it was not representative of the
U.S. population.

The Wiley et al. (1991) study was conducted between
April 1989 and February 1990; the U.S. EPA (1996) study
was conducted between October 1992 and September
1994.

Data were collected for a 24-hour period.
  Clarity and Completeness
   Accessibility
   Reproducibility
   Quality Assurance
                                                           Medium
The original studies are widely available to the public;
U.S. EPA analysis of the original raw data from U.S. EPA
(1996) is available upon request.

The methodologies were clearly presented; enough
information was included to reproduce the results.

Quality assurance methods were not well described in
study reports.
 Variability and Uncertainty
   Variability in Population
   Uncertainty
                                                           Medium
Variability was characterized across various age categories
of children.

The studies were based on short term recall data, and the
upper ends of the distributions were truncated.
  Evaluation and Review
   Peer Review
   Number and Agreement of Studies
                                                           Medium
The original studies received a high level of peer review.
The re-analysis of the U.S. EPA (1996) data to conform to
the standardized age categories was not peer-reviewed.

There were 2 key studies.
Page
16-6
                     Child-Specific Exposure Factors Handbook
                    	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
 Overall Rating
                                Medium for the
                                 mean; low for
                                upper percentile
16.3  ACTIVITY PATTERNS
      This section briefly describes published time-use
studies  that  provide  information on  time-activity
patterns  of children  in  the  U.S.  For  a detailed
description of the studies, the reader is referred to the
Exposure Factors Handbook (U.S. EPA, 1997).

16.3.1   KEY STUDIES
16.3.1.1  Wiley et al, 1991  - Study of Children's
         Activity Patterns
         The California Study of Children's Activity
Patterns survey (Wiley et al., 1991) provided estimates
of the time children spent in various activities and
locations (microenvironments) on a typical day.  The
sample population consisted of 1,200 children, under
12  years of age, selected from English-speaking
households using Random Digit Dial (ROD) methods.
This  represented a  survey  response rate of 77.9
percent.  One child was selected from each household.
If the selected child was 8 years old or less, the adult in
the household who spent the most time with the child
responded. However, if the selected child was between
9  and 11  years old,  that child responded.   The
population was also stratified to provide representative
estimates for major regions of the state.  The  survey
questionnaire included a  time diary which provided
information on  the children's activity  and location
patterns based on a 24-hour recall period. In addition,
the survey questionnaire  included questions about
potential exposure to sources  of indoor air pollution
(e.g., presence of smokers) on the diary day, and the
socio-demographic characteristics of children and
adult respondents. The questionnaires  and the time
diaries were administered via a computer-assisted
telephone interviewing (CATI) technology (Wiley et
al., 1991).  The telephone interviews were conducted
during April 1989 to February 1990 over four seasons:
spring (April  to June  1989), summer (July to
September 1989), fall (October to December  1989),
and winter (January to February 1990).
         The data obtained from the survey interviews
resulted in ten major activity categories, 113 detailed
activity codes, 6 major categories of locations, and 63
detailed location codes.  The time respondents under
12 years of age spent in the 10 activity categories (plus
a "don't know"  or non-coded activity category) are
presented in Table 6-3.  For each of the 10 activity
categories, this table presents the mean duration for all
survey participants, the percentage of respondents who
reported participating in  the  activity (i.e.,  percent
doers), and the mean, median, and maximum duration
for only those survey respondents who engaged in the
activity (i.e., doers).  It also  includes the detailed
activity with the highest mean duration of time for
each activity category. The activity category with the
highest time expenditure was personal needs and care,
with a mean of 794  minutes/day (13.2 hours/day).
Night sleep was the  detailed activity that had the
highest mean duration in that activity category.  The
activity category "don't know" had a mean duration of
about 2  minutes/day and  only  4 percent of the
respondents reported missing activity time.
         Table 16-4  presents the mean time spent in
the 10 activity categories by age and gender. Because
the original source data were available, U.S. EPA re-
analyzed the data according to the standardized age
categories used in this handbook. Differences between
activity patterns in boys and girls tended to be small.
Table 16-5 presents  the mean time spent in the 10
activity categories grouped by season and geographic
region in the state of California. There were seasonal
differences for 5 activity categories: personal needs and
care, education, entertainment/social, recreation, and
communication/passive leisure.   Time  expenditure
differences in various  regions  of the state  were
minimal for childcare, work-related, goods/services,
personal  needs   and   care,   education,
entertainment/social, and recreation.
         Table 16-6 presents the distribution of time
across six location categories. The mean duration for
all  survey participants,  the percent of  respondents
engaging in the activity (i.e., percent doers); the mean,
median, and maximum duration for doers only; and
the detailed locations with the highest average time
expenditure are shown. For all survey respondents, the
largest mean amount of time spent was at home (1,078
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minutes/day); 99 percent of respondents spent time at
home (mean of 1,086 minutes/day for these individuals
only).  Tables 16-7 and 16-8 show the average time
spent in the six locations grouped by age  and gender,
and season and region, respectively. Again, because
the original  source  data were available,  the  age
categories used by Wiley et  al. (1991) have been
replaced in Table  16-7 by the  standardized  age
categories  used  in  this  handbook.   There were
relatively large differences among the age groups in
time expenditure for educational settings (Table 16-7).
There were small differences in time expenditure at the
six locations by region, but  time spent in school
decreased in the summer months compared to other
seasons (Table 16-8).
         Table 16-9  shows the average time children
spent in proximity to gasoline fumes and gas oven
fumes.   In general, the sampled children spent more
time closer to gasoline fumes than to gas oven fumes.
The age categories in Table 16-9 have been modified
to conform to the standardized categories used in this
handbook.
         The  U.S.  EPA  estimated the total time
indoors and outdoors using the data from the Wiley et
al. (1991) study. Activities performed indoors were
assumed to include  household work,  child care,
personal   needs   and   care,   education,   and
communication/passive leisure. The average times
spent in these indoor activities and half the time spent
in each activity which could  have occurred either
indoors or outdoors (i.e., work-related, goods/services,
organizational activities, entertainment/social, don't
know/not   coded)  were  summed.    Table  16-10
summarizes the  results of this analysis using the
standard age groups.
         A limitation  of this study  is  that  the
sampling population was restricted to only English-
speaking households; therefore, the data  obtained do
not represent the diverse population group present in
California. Another limitation is that time use values
obtained from this survey were based on short-term
recall (24-hr) data; therefore, the data set obtained may
be biased.   Other limitations are:  the  survey  was
conducted in California and is not representative of the
national population,  and the  significance  of  the
observed differences in the data obtained (i.e., gender,
 age, seasons, and regions) were not tested statistically.
 An advantage of this study is that time expenditure in
 various  activities and locations were  presented for
 children grouped by age, gender, and season.  Also,
 potential exposures of respondents to pollutants were
 explored in the survey.  Another advantage is the use
 of the CATI program in obtaining time diaries, which
 allows automatic coding of activities  and locations
 onto a computer tape, and allows activities forgotten by
 respondents to be inserted into  their appropriate
 position during interviewing.

 16.3.1.2  U.S. EPA, 1996-National Human Activity
          Pattern Survey (NHAPS)
          U.S. EPA (1996) analyzed data collected by
 the National Human Activity Pattern Survey (NHAPS).
 This survey was conducted by U.S. EPA  and  is the
 largest and most current human activity pattern survey
 available  (U.S.  EPA,  1996).     Data for  9,386
 respondents in the 48 contiguous United States were
 collected  via  minute-by-minute   24-hour  diaries.
 NHAPS was conducted  from  October  1992 through
 September 1994 by  the University of Maryland's
 Survey Research Center using CATI technology to
 collect 24-hour retrospective diaries and answers to a
 number of personal and exposure  related questions
 from each respondent. Detailed data were collected for
 a maximum of 82 different possible locations,  and a
 maximum of 91 different activities.  Participants were
 selected using a ROD method. The  response rate was
 63 percent, overall.  If the chosen respondent  was a
 child too young to interview, an adult in the household
 gave a proxy interview.  Each participant was asked to
 recount their entire daily routine from midnight to
 midnight immediately previous  to the day that they
 were interviewed. The survey collected information on
 duration and frequency of selected activities and of the
 time spent in selected microenvironments. In addition,
 demographic  information was  collected  for  each
 respondent to  allow for statistical  summaries to be
 generated according to specific subgroups of the U.S.
 population (i.e.,  by gender, age, race, employment
 status, census region, season, etc.).  The participants'
 responses  were weighted according to geographic,
 socioeconomic, time/season, and other demographic
 factors to ensure that results were representative of the
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U.S. population.  The weighted sample matched the
1990 U.S.  census population for each gender, age
group,  census  region,  and  the day-of-week  and
seasonal responses were equally distributed. Saturdays
and Sundays were over sampled to ensure an adequate
weekend sample.
         Tables 16-11 through  16-24 provide  data
from the NHAPS study. In most cases, the source data
from U. S. EPA have been reviewed and re-analyzed by
U.S.  EPA  to  conform   to  the  age  categories
recommended  in  Guidance for  Monitoring  and
Assessing Childhood Exposures to  Environmental
Contaminants (U.S.  EPA,  2005) and used in this
handbook. Because no data were available on subjects'
age in months,  age groups less than 1 year old were
consolidated into a single group.  These tables provide
statistics for 24-hour cumulative time spent (mean,
minimum, percentiles, and maximum) in or in selected
locations or engaging in selected activities. For each
location or activity, statistics were calculated for the
entire survey population (i.e., whole population) and
for the subset of the  survey population that reported
being in the location or doing the activity in question
(i.e., doers only).   When the sample size was 10
persons or fewer, percentile values were not calculated.
Also  note  that some of these  activities  were not
necessarily mutually  exclusive  (e.g. time spent in
active sports likely overlaps with exercise time).
         Table  16-11 presents  data for the time
children spent  in various rooms of the  house (i.e.,
kitchen,  living  room,  dining room,   bathroom,
bedroom, and garage), and all rooms combined. Table
16-12 presents  data  for time spent in other indoor
locations (i.e.,  restaurants, indoors  at school,  and
grocery/convenience  stores).  Table  16-13 presents
data for the time children spent outdoors  on  school
grounds/playgrounds, parks or golf courses, or pool
rivers, or lakes. Table 16-14 provides data on time
spent in indoor  and outdoor environments.  The U.S.
EPA estimated  the time spent indoors by  adding the
average times spent indoors at the respondents' home
(kitchen, living  room, bathroom, etc.), at other houses,
and inside other locations such as school, restaurants,
etc.  Time outdoors  was estimated  by  adding the
average time spent outdoors at the respondents' pool
and yard, others' pool and yard, and outside other
locations  such as sidewalk, street,  neighborhood,
parking lot, service station/gas station, school grounds,
park/golf course, pool, river, lake, farm, etc.  Table 16-
15 presents data for the time spent in various types of
vehicles (i.e., car, truck/van, bus),  and in all vehicles
combined.  Table  16-16  presents data for the time
children spent in various major activity categories (i.e.,
sleeping, napping, eating, attending school, outdoor
recreation, active sports, exercise, and walking).
         Table 16-17  through 16-19 provide data
related to  showering,  bathing, and handwashing
activities.  Tables 16-20 and 16-21 provide data on
monthly swimming (in a freshwater pool) frequency by
the number of respondents and swimming duration,
respectively.  Table 16-22 provides data on the time
children spent playing on dirt, sand/gravel, or grass,
and Table 16-23 provides data on the number of
minutes spent  near  excessive  dust.   Table  16-24
provides information on time spent in the presence of
smokers. For this data  set, the authors' original age
categories were used because the methodology used to
generate the data could not be reproduced.
         The advantages of the NHAPS data set are
that it is representative of the U.S. population and it
has been  adjusted to  be balanced geographically,
seasonally, and for day/time. Also, it is inclusive of all
ages, genders, and races. A disadvantage of the study
is that for  the standard  age categories, the number of
respondents is small for the "doers" of many activities.
In addition, the durations exceeding 60, 120, and 181
minutes were  not  collected  for some  activities.
Therefore, the actual time spent at the high end of the
distribution for these activities could not be accurately
estimated.

16.3.2    RELEVANT STUDIES
16.3.2.1  Timmer et al,  1985 - How Children Use
         Time
         Timmer et al.  (1985) conducted a study
using the data obtained on children's time use from a
1981-1982 panel study. Data were obtained for 389
children between the ages of 3  and 17 years  of age.
Data  were  collected using a time  diary  and  a
standardized  interview.   The time  diary involved
children reporting their activities beginning at 12:00
a.m. the previous night, the duration and location of
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each activity, the presence of another individual, and
whether they were performing other activities at the
same  time.    The  standardized  interview was
administered to the children to  gather information
about their psychological, intellectual (using reading
comprehension tests), and emotional well-being; their
hopes and goals; their family environment; and their
attitudes and beliefs.
         For preschool children, parents provided
information about the child's previous day's activities.
Children in first through third grades completed the
time  diary with  their parents   assistance  and,  in
addition, completed reading tests.  Children in fourth
grade and above provided their own diary information
and participated in the interview.  Parents were asked
to  assess   their  children's  socioemotional  and
intellectual development, and a survey form was sent
to a teacher of each school-age child to evaluate their
socioemotional and intellectual development.  The
activity descriptor codes used  in this study were
developed by Juster et al. (1983).
         The mean time spent performing  major
activities on weekdays and weekends by age, sex, and
type of day is presented in Table 16-25.  On weekdays,
children spend about 40 percent of their time sleeping,
20 percent in school,  and 10 percent eating,  and
performing personal care activities  (Timmer  et al.,
1985). The data in Table  16-25 indicate that girls
spent more time than boys performing household work
and  personal care activities and less time playing
sports. Also, the children spent most of their free time
watching television.
         Table 16-26 presents the mean time children
spent during weekdays and  weekends performing
major activities by five different age  groups.  The
significant effects of each variable (i.e., age and sex)
are also  shown.    Older  children spent more time
performing household and market work, studying, and
watching television and less time eating, sleeping, and
playing. The authors estimated that, on average, boys
spent 19.4 hours a week and girls spent 17.8 hours per
week watching television.
         U.S. EPA estimated the total time indoors
and outdoors using the Timmer et  al.  (1985) data.
Activities performed indoors were assumed to include
household  work,  personal care, eating,  sleeping,
 attending school, studying, attending church, watching
 television, and engaging in household conversations.
 The average times spent in these indoor activities and
 half the time spent in each activity which could have
 occurred indoors  or outdoors (e.g., market  work,
 sports, hobbies, art activities, playing, reading, and
 other  passive leisure) were summed.  Table  16-27
 summarizes the results of this analysis by age  group
 and time of the week.
          A limitation associated with this study is that
 it was conducted in 1981.  It is likely that activity
 patterns of children have changed from 1981  to the
 present. Thus, the application of these data to current
 exposure assessments may bias their results. Another
 limitation is that the data do not provide overall annual
 estimates  of children's time use since  data  were
 collected only during  the time  of the  year  when
 children attended  school and  not  during  school
 vacations.  An advantage of this survey is that diary
 recordings of activity patterns were kept and the data
 obtained were not based entirely on  recall. Another
 advantage is that because parents assisted younger
 children with  keeping  their  diaries   and   with
 interviews, any bias that may have  been  created by
 having younger children record their data should have
 been minimized.

 16.3.2.2  Robinson and Thomas, 1991 - Time Spent
          in   Activities,   Locations,    and
          Microenvironments: A California-National
          Comparison
          Robinson and Thomas (1991) reviewed and
 compared data from the 1987-88  California  Air
 Resources  Board   (CARD)  time-activity  study for
 California residents and from a similar 1985 national
 study, Americans'  Use of Time,  conducted at the
 University of Maryland. Both studies used the diary
 approach to collect data.  Time- use patterns were
 collected for individuals aged 12 years and  older.
 Telephone  interviews based on the  ROD procedure
 were conducted for 1,762 and 2,762 respondents for
 the CARD study and the national study, respectively.
 Of these respondents, 183 were children, ages 12 to!7
 years in the CARD  study and 340 were children, ages
 12 to  17 years, in the national study. Robinson and
 Thomas (1991) defined a set of 16 microenvironments
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based on the activity and location codes employed in
the two studies. The mean durations of time spent in
the 16 microenvironments by children, ages 12 to 17
years, are presented in Table 16-28.  In both studies,
children spent the majority of their time sleeping, and
engaging in leisure and work/study-related activities.
         The limitations associated with the Robinson
and Thomas (1991) study are that the CARD survey
was performed in California only and may not be
representative of the U.S. population as a whole.  In
addition, the studies were conducted in the 1980s and
activity patterns  may have changed over time.
Another limitation is that the data are based on short-
term studies.  Finally, the available data could not be
re-analyzed to conform to the  standardized  age
categories used in this handbook.

16.3.2.3  Funk  et  al,  1998 -  Quantifying  the
         Distribution  of Inhalation  Exposure in
         Human Populations: Distribution of Time
         Spent by Adults, Adolescents, and Children
         at Home, at Work, and at School
         Funk et al.  (1998) used the data from the
CARD study  to determine distributions of exposure
time by tracking the time spent participating in daily
at-home and at-school activities for male and female
children  and adolescents.   CARD  performed  two
studies from  1987 to 1990; the first was focused on
adults  (18 years and older) and  adolescents (12-17
years old), and the second focused on children (6-11
years   old).     The  targeted   groups  were
noninstitutionalized English speaking Californians
with telephones in their residences.  Individuals were
contacted by telephone and asked to account for every
minute within the previous 24 hours,  including the
amount of time spent on an activity and the location of
the activity. The surveys were conducted on different
days of the week  as well as different seasons of the
year.
         Using the location descriptors provided in
the CARB  study,  Funk et al. (1998) categorized the
activities into two groups, "at home" (any activity at
principal residence) and "away."   Each activity  was
assigned to one of three inhalation rate levels (low,
moderate, or high) based on the level of exertion
expected from the activity. Ambiguous activities were
assigned to moderate inhalation rate levels.  Among
the adolescents and children studied, means were
determined for the aggregate age groups, as shown in
Table 16-29.
         Funk et al. (1998) used several statistical
methods, such as Chi-square, Kolmogorov-Smirnov,
and Anderson-Darling, to determine whether the time
spent in an activity group had a known distribution.
Most of the activities performed by children were
assigned a low or moderate inhalation rate rate (Table
16-30).
         The aggregate time periods spent at home in
each activity are shown in  Table 16-31. Aggregate
time spent at home performing different activities was
compared between genders. There were no significant
differences between adolescent males and females in
any of the activity groups (Table 16-32). In children,
ages 6-11 years, differences between gender and age
were observed at the low inhalation rate levels. There
were significant differences between two age  groups
(6-8 years, and 9-11 years) and gender at the moderate
inhalation rate level (Table 16-33).
         A limitation of this study was that large
proportions of the respondents in the study did not
participate in high-inhalation rate-level activities. The
Funk et al. (1998) study  was based on data from one
geographic location, collected more that a decade ago.
Thus, it may not be representative of current activities
among the general population of the U.S.

16.3.2.4  U.S.  EPA, 2000  - Consolidated Human
         Activity Database (CHAD)
         The Consolidated Human Activity Database
(CHAD),  available   online   at
http://www.cpa. gov/chadnct 1 /, was developed by the
U.S. EPA's National Exposure Research Laboratory
(NERL) to provide access to existing human activity
data for use in exposure and risk assessment efforts.
Data from twelve activity pattern studies conducted at
the city, state, and  national levels  are included  in
CHAD. CHAD contains both the original raw data
from each study and data modified based on predefined
format requirements.  Modifications made to data
included: receding of variables  to fit into them  a
common  activity/location  code   system,  and
standardization of time diaries to an exact 24-hour
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length. Detailed information on the coding system and
the studies included in CHAD is  available in the
CHAD  User  Manual,  available  at
htlp://oaspub.cpa.gov/chad/CHAD  DaiafilcsS. start n
p#Manual and in McCurdy et al. (2000).
         A total of 144 activity codes and 115 location
codes were used in CHAD (McCurdy et al., 2000).
Although  some participants in a  study conducted
multiple   activities,  many  activities  were  only
conducted within a few studies.  The same is true for
activity locations. The selection of exposure estimates
for a particular activity or particular location should be
based on study parameters that  closely  relate to the
exposure scenario being assessed.  The maximum
amount of time, on average, within  a majority of the
studies was sleeping or taking a nap, while  the
maximum amount of time spent at a particular location
was at home or at work, depending on the study.
         Many of the limitations of CHAD data arise
from the incorporation of multiple studies into the time
diary  functions specified in CHAD.  Activities and
locations were coded similarly to the NHAPS study;
studies with differing coding systems were modified to
fit the NHAPS codes.  In some cases start times and
end times from a study had to be adjusted to fit a 24-
hour  period.   Respondents were  not  randomly
distributed in CHAD.  For example,  some cities or
states were over sampled because entire  studies were
carried out in those places. Other  studies  excluded
large   groups  of  people  such  as  smokers,  or
non-English speakers, or people without telephones.
Many  surveys  were  age-restricted,  or   they
preferentially sampled  certain target groups. As a
result, users  are cautioned  against  using  random
individuals in CHAD to represent the U.S. population
as a whole (Glenn et al., 2000).

16.3.2.5  Hubal et al.,  2000 - Children's Exposure
         Assessment:   A   Review  of  Factors
         Influencing Children's Exposure and the
         Date Available to Characterize and Assess
         that Exposure
         Hubal et al. (2000) reviewed available data
from  CHAD,  including  activity  pattern  data,  to
characterize and assess environmental exposures to
children.   CHAD  contains 3,009 person-days  of
 macroactivity data for 2,640 children less than 12
 years of age (Hubal et al., 2000) (Table 16-34).  The
 number of hours these children  spent  in  various
 microenvironments are shown in Table 16-35 and the
 time they spent in various activities indoors at home is
 shown in Table 16-36.
          Hubal  et al.  (2000)   noted that CHAD
 contains approximately "140 activity  codes and 110
 location codes, but the data generally are not available
 for all activity locations for any single respondent. In
 fact, not all of the codes were used for most of the
 studies.    Even  though many  codes are  used in
 macroactivity studies, many of the activity codes do not
 adequately capture the  richness of  what  children
 actually do. They are much too broadly defined and
 ignore many child-oriented behaviors.  Thus, there is
 a need  for more and better-focused research  into
 children's activities."
          U.S. EPA updated the analysis performed by
 Hubal et al. (2000) using CHAD data  downloaded in
 2000, sorted according to the age groups recommended
 in Guidance for Monitoring and Assessing Childhood
 Exposures to Environmental Contaminants (U. S. EPA,
 2005).  The results are shown in Tables 16-37 and 16-
 38.  In this analysis, individual study participants
 within CHAD whose behavior patterns  were measured
 over multiple days were treated as multiple one-day
 activity patterns.  This is a potential source of error or
 bias in the results because a single individual  may
 contribute  multiple  data sets to  the aggregate
 population being studied.

 16.3.2.6  Wong et al., 2000 - Adult Proxy Responses
          to a Survey  of Children's Dermal  Soil
          Contact Activities
          Wong  et al.  (2000)  conducted telephone
 surveys to gather information on children's activity
 patterns as related to dermal contact with soil during
 outdoor play on bare dirt or mixed  grass  and dirt
 surfaces. This study,  the second Soil Contact Survey
 (SCS-II), was a follow-up to the initial Soil Contact
 Survey (SCS-I),  conducted in  1996,  that primarily
 focused on assessing adult behavior related to dermal
 contact with soil and dust (Garlock et  al., 1999).  As
 part of SCS-I,  information was  gathered  on  the
 behavior of children  under the age of 18 years,
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however, the questions were limited to clothing choices
and the length of time between soil contact and hand
washing. Questions were posed for SCS-II to further
define children's outdoor activities and hand washing
and bathing frequency.  For both soil contact surveys
households were randomly phoned in order to obtain
nationally  representative   results.     The   adult
respondents were questioned  as  surrogates for one
randomly chosen child under the age of 18 residing
within the household.
         In the SCS-II, of 680 total adult respondents
with a child in their household,  500 (73.5 percent)
reported that their child played outdoors on bare dirt or
mixed grass and dirt surfaces (identified as "players").
Those children that reportedly did not play outdoors
("non-players") were typically very young (• 1 year) or
relatively older (• 14 years).  Of the 500 children that
played outdoors, 497 played outdoors in warm weather
months (April through October) and 390 were reported
to play  outdoors  during  cold weather  months
(November through  March).    These  results  are
presented in Table 16-39. The frequency (days/week),
duration (hours/day), and total hours per week spent
playing outdoors was determined for those children
identified as "players" (Table 16-40). The responses
indicated  that children  spent   a  relatively  high
percentage of time  outdoors during  the warmer
months, and a  lesser amount of time outdoors in cold
weather.  The  median play frequency reported was 7
days/week in warm weather and 3 days/week in cold
weather.  Median play  duration  was 3 hours/day in
warm weather and 1 hour/day during cold weather
months.
         Adult respondents were then questioned as
to how many times per day their child washed his/her
hands  and how many times the child bathed or
showered  per  week, during  both  warm  and  cold
weather months.   This  information  provided an
estimate of the time between skin contact with soil and
removal of soil by washing (i.e., exposure time).  Hand
washing and bathing frequencies for child players are
reported in Table 16-41. Based on these results, hand
washing occurred a median of 4 times per day during
both warm and cold weather  months.  The median
frequency for baths and showers was  estimated to be 7
times per week for both warm and cold weather.
         Based on reported household incomes, the
respondents sampled in SCS-II tended to have higher
incomes than that of the general population. This may
be explained by  the fact that phone surveys  cannot
sample households without telephones.  Additional
uncertainty or error in the study results may have
occurred as a result of the use of surrogate respondents.
Adult respondents were questioned regarding child
activities that may have occurred in prior seasons,
introducing the  chance of recall error.  In some
instances, a respondent did not know the answer to a
question or refused to answer.  Table 16-42 compares
mean play duration  data from  SCS-II  to  similar
activities identified in NHAPS  (U.S.  EPA,  1996).
Table 16-43 compares the number of times per day a
child washed his or her hands, based on data from
SCS-II and NHAPS. As indicated in Tables 16-42 and
16-43,  where comparison is possible,  NHAPS and
SCS-II  results  showed  similarities  in  observed
behaviors.

16.3.2.7  Graham and McCurdy, 2004 - Developing
         Meaningful Cohorts for Human Exposure
         Models
         Graham  and  McCurdy  (2004) used  a
statistical model [general linear model and analysis of
variance (GLM/ANOVA)] to assess the significance of
various factors in explaining variation in time spent
outdoors, indoors and in motor vehicles.   These
factors,  which are commonly used in developing
cohorts for exposure modeling, included age, gender,
weather,  ethnicity,  day type,  and precipitation.
Activity pattern data from CHAD, containing 30  or
more records per day, were used in  the analysis
(Graham and McCurdy, 2004).
         Data on time spent outdoors for people who
spent >0 time outdoors (i.e.,  doers) are presented  in
Table 16-44. Graham and McCurdy (2004) found that
all the factors evaluated were significant (p<0.001)  in
explaining differences in time spent outdoors (Graham
and  McCurdy,  2004).   An evaluation  of  gender
differences  in time spent outdoors by age cohorts was
also  conducted.   Table 16-45 presents descriptive
statistics   and   the   results  of  the   two-sample
Kolmogorov-Smirnov (KS) test for this evaluation. As
shown  in  Table  16-45,  there  were  statistically
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significant gender differences in time spent outdoors
starting with the 6 to 10 year old age  category.  In
addition, Graham and McCurdy (2004) evaluated the
effect of physical activity and concluded that this was
the most important factor  in explaining time spent
outdoors. For time spent indoors (Table 16-46), there
were statistically significant effects for all the factors
evaluated, with gender, weather, and day type being
the most important variables.  Regarding time spent in
motor vehicles  (Table 16-47), precipitation was the
only  factor  found  to  have no  significant  effects
(Graham and McCurdy, 2004).
         Based on the results  of these  analysis,
Graham and McCurdy (2004) noted that "besides age
and gender, other  important attributes for defining
cohorts  are the  physical activity  level of individuals,
weather factors such as daily maximum temperature in
combination with months of the year, and combined
weekday/weekend  with  employment status."   The
authors  also noted that even  though the  factors
evaluated were found to be statistically  significant in
explaining differences in time spent outdoors, indoors,
and in motor vehicles, "parameters such as lifestyle
and life  stages that are absent from CHAD might have
reduced the  amount of unexplained variance."  The
authors  recommended that, in defining cohorts for
exposure modeling, age and gender should be used as
' 'first-order'' attributes, followed by physical activity
level, daily  maximum temperature, and  day  type
(weekend/weekday or day-of-the-week/working status)
(Graham and McCurdy, 2004).

16.3.2.8 Vandewater et al, 2004 - Linking Obesity
         and   Activity Level  with   Children's
         Television and Video Game Use
         Vandewater  et   al.   (2004)   evaluated
children's media use and participation  in active and
sedentary activities using  24-hour time-use  diaries
collected in  1997, as part of the Child  Development
Supplement  (CDS) to  the Panel  Study of Income
Dynamics  (PSID).   The  PSID  is   a  ongoing,
longitudinal study  of U.S.  individuals and  their
families conducted by the Survey Research Center of
the University of Michigan.  In 1997, PSID families
with children younger than 12 years of age completed
the CDS and reported all activities performed by the
 children on one randomly selected weekday and one
 randomly selected weekend day. Since minorities, low
 income families, and less educated individuals were
 oversampled in the PSID, sample weights were applied
 to the data  (Vandewater  et al.,  2004).   More
 information on the CDS can be found on-line  at
 http://psidoiiline.isr.uinich.edu/CDS/.
          Using time diary data from 2,831 children
 participating in the CDS, Vandewater et al., (2004)
 estimated the time in minutes over the two-day study
 period (i.e., sum of time spent on one weekday and one
 weekend day) that children spent watching television,
 playing games on video games  consoles or computers,
 reading,  and  using  computers for  other purposes
 besides playing games.  In addition, the time spent
 participating in highly active (i.e., playing  sports),
 moderately active (i.e.,  fishing,  boating, camping,
 taking music lessons, and singing), and sedentary (i.e.,
 using the phone, doing puzzles, playing board games,
 and relaxing) activities was determined.  Table 16-48
 presents the means and standard deviations for the
 time spent in the selected activities by age and gender.
          A limitation of this study is that the survey
 was not designed for exposure assessment purposes.
 Therefore, the  time  use data set  may  be  biased.
 However, the survey provides a database of current
 information  on  various  human  activities.   This
 information can be used to assess various exposure
 pathways and scenarios associated with these activities.

 16.3.2.9  Juster et al. (2004)  - Changing Times  of
          American Youth: 1983-2003
          Juster et al. (2004) evaluated changes in time
 use patterns of children by comparing data collected in
 a 1981-1982 pilot study of children ages 6 to 17 to data
 from the 2002-2003 Child Development Supplement
 (CDS) to the Panel Study of Income Dynamics (PSID).
 The 1981-1982 pilot study is the same study described
 in Timmer et  al.  (1985).   The 2002-2003  CDS
 gathered 24-hour time diary data on 2,908 children
 ages  6 to  17; as  was done in the  1997 CDS,
 information was collected on one randomly selected
 weekday  and one randomly selected weekend day
 (Juster et al., 2004).
          Tables 16-49 and 16-50 present the mean
 time children spent (in minutes/day) performing major
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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
activities on weekdays and weekend days, respectively,
for the years  1981-82 and  2002-2003.  Table 16-51
shows the weekly time spent in these activities for the
years 1981-82 and 2002-2003.  Juster et al. (2004)
noted that  the  time  spent in school and  studying
increased  while time  spent  in  active  sports  and
outdoors activities decreased during the period studied.

16.3.2.10        U.S. Department of Labor, 2007 -
                American Time Use Survey, 2006
                Results
         The American Time Use Study (ATUS) has
been conducted annually  since 2003  by the  U.S.
Department of Labor's Bureau of Labor Statistics (U. S.
DL, 2007). The purpose of the  study is to collect "data
on what activities people do during the day and how
much time they spend  doing them."  In 2006, the
survey focused on "the  time Americans worked, did
household activities,  cared for household children,
participated in educational  activities, and engaged in
leisure and sports activities."  Approximately 13,000
individuals,   15 years  of age  and  older,  were
interviewed during 2006. Participants were randomly
selected and interviewed using the CATI method and
were asked to recall their activities on the day before
the interview.  Data were collected for all days of the
week, including weekends (i.e.,  10 percent  of the
individuals were interviewed about their activities on
one  of the five weekdays, and 25 percent  of the
individuals were interviewed about their activities on
one  of the  two weekend  days).   Demographic
information,  including  age, gender,  race/ethnicity,
marital  status, and  educational  level  were  also
collected, and sample weights were applied to records
to "reduce bias in the estimates due to differences in
sampling and response rates across subpopulations and
days of the week."  Data were collected for  17 major
activities, that were subsequently composited into 12
categories for publication of the results. Estimates of
time use in these 12 major categories are presented in
Table 16-52.  These data represent the average hours
per day spent by male, female, and all children ages 15
to 19 years in the various categories.  Table 16-52 also
provides a more detailed breakdown of the Leisure and
Sports category for all children, ages 15 to  19 years
old.
16.3.2.11        Nader et al. 2008 - Moderate-to-
                Vigorous Physical Activity from
                Ages 9 to 15 years
         Nader et al. (2008) conducted a longitudinal
study of 1,032 children from ages 9 to 15 years. The
purpose of the study was to determine the amount of
time children 9  to  15 years of  age  engaged  in
moderate-to-vigorous activities (MVPA) and compare
results with the  recommendations issued by the U.S.
Department of Health and Human  Services  and the
U.S. Department of Agriculture of a minimum of 60
minutes per  day.   Children's activity  levels were
recorded for four to seven days using an accelerometer.
The study participants included 517 boys  and 515
girls. The study found that at age 9 children engaged
in 3 hours of MVP A per day. By age 15, the amount
of  time  engaged in  MVPA was dropped to  49
minutes/day on weekdays and 35 minutes per day on
weekends. Boys spent 18 more minutes/day of MVPA
than girls on  weekdays and 13 more minutes/day on
weekends.  Estimates of  the mean time  spent in
moderate-to-vigorous activities by various age groups
are  presented in Table 16-53.  The study  did  not
provide information about the amount of time spent at
specific activities.

16.4     REFERENCES FOR CHAPTER 16
Chance,  W.G.;  Harmsen,  E. (1998) Children  are
         different: environmental contaminants and
         children's health.  Can  J Public  Health
         89(Supplement):59-513.
Funk,  L.; Sedman,  R.; Beals, J.A.J.; Fountain, R.
         (1998)  Quantifying  the  distribution  of
         inhalation exposure in human populations:
         distributions  of  time  spent  by   adults,
         adolescents, and children at home, at work,
         and at school. Risk Anal 18(l):47-56.
Garlock, T.J.; Shirai, J.H.;  Kissel, J.C.  (1999) Adult
         responses to a survey of soil contact related
         behaviors. J Expo Anal Environ Epidemiol
         9:134-142.
Glenn, G.; Stallings, C.; Tippett, J.; Smith, L. (2000)
         CHAD'S user guide:  Extracting  human
         activity information from CHAD on the PC.
         Prepared  for  the  U.S.  EPA National
Child-Specific Exposure Factors Handbook
September 2008	
                                          Page
                                         16-15

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                                                      Child-Specific Exposure Factors Handbook

                                                     	Chapter 16 - Activity Factors
                Exposure Research Laboratory by
                ManTech   Environmental
                Technology, Inc.
Graham, S.E.;  McCurdy,  T.   (2004) Developing
         meaningful cohorts  for human  exposure
         models.  J Expo Anal Environ Epidemiol
         14:23-43.
Hubal, E.A.; Sheldon, L.S.; Burke,  J.M.; McCurdy,
         T.R.; Berry, M.R.; Rigas, M.L.; Zartarian,
         V.G.;  Freeman, N.G. (2000) Children's
         exposure assessment: a review of factors
         influencing children's exposure and the data
         available to  characterize  and assess that
         exposure.  Environ Health Persp  108:475-
         485.
Johnson, T.  (1989)  Human  Activity Patterns  in
         Cincinnati, Ohio. Palo Alto, CA: Electric
         Power Research Institute.
Juster, F.T.; Hill, M.S.; Stafford, P.P.; Parsons, J.E.
         (1983)  Study description.  1975-1981 time
         use longitudinal panel study.  Ann Arbor,
         MI:  The University of Michigan, Survey
         Research   Center,  Institute  for   Social
         Research.
Juster, T.;  Ono,  H.;  Stafford, F. (2004)  Changing
         times  of  American  youth:  1981-2003.
         Institute for Social Research, University of
         Michigan, Ann Arbor, Michigan. Available
         on-line         at
         http://www.umich.edu/news/Releases/2004
         /Nov04/teen_time_report.pdf
McCurdy, T.; Glen, G.; Smith, L.; Lakkadi, Y. (2000)
         The   National   Exposure  Research
         Laboratory's Consolidated Human Database.
         J Expo Anal Environ Epidemiol 10:566-578.
Nader, P.R.; Bradley, R.H.; Houts, R.M.; McRitchie,
         S.L.; O'Brien,  M.  (2008)  Moderate-to-
         vigorous physical activity from ages 9 to 15
         years.  JAMA, 300(3):295-305.
Robinson, J.P.;  Thomas, J. (1991) Time  spent in
         activities, locations, andmicroenvironments:
         a  California-National Comparison Project
         report.     Las  Vegas,   NV:     U.S.
         Environmental   Protection   Agency,
          Environmental  Monitoring   Systems
          Laboratory.
 Timmer,  S.G.; Eccles, J.; O'Brien, K.  (1985) How
          children use time. In: Juster, F.T.; Stafford,
          P.P.; eds.  Time,  goods, and well-being.
          Ann Arbor, MI:  University of Michigan,
          Survey Research Center, Institute for Social
          Research, pp. 353-380.
 U.S. Department of Health and Human  Services and
          U.S.  Department of Agriculture. (2005)
          Dietary Guidelines for Americans, 2005. 6th
          edition,  Washington,  DC,  Government
          Printing  Office.   Available online  at
          http://www.health.gOv/dietaryguidelines/d
          ga2005/document/pdf/DGA2005 .pdf U. S.
 Department of Labor  (U.S. DL), Bureau  of Labor
          Statistics.  (2007)  American  Time  Use
          Survey - 2006 Results. News release issued
          at http://www.bls.gov/tiis on June 28, 2007.

 U.S. EPA (1996) Descriptive statistics tables from a
          detailed analysis of the National Human
          Activity  Pattern Survey (NHAPS)  data.
          Washington,  DC: Office of Research and
          Development. EPA/600/R-96/148.
 U.S. EPA   (1997) Exposure  Factors Handbook.
          Washington,  DC:  National  Center  for
          Environmental   Assessment,   Office   of
          Research  and Development.  EPA/600/P-
          95/002Fa,b,c.
 U.S. EPA   (2000)  Consolidated Human  Activity
          Database   (CHAD).   U.S.   EPA/NERL.
          Available online at
          http ://www. cpa. gov/chadnct 1 /
 U.S. EPA. (2005) Guidance on Selecting Age Groups
          for Monitoring  and Assessing Childhood
          Exposures to Environmental Contaminants.
          U.S.  Environmental Protection   Agency,
          Washington,  D.C., EPA/630/P-03/003F.
 Vandewater, E.A.; Shim,  M.; Caplovitz, A.G. (2004)
          Linking  obesity and  activity level  with
          children's television and video game use. J
          Adolesc 27:71-85.
 Wiley,  J.A.; Robinson, J.P.; Cheng, Y.; Piazza, T.;
          Stork, L.; Plasden, K. (1991) Study  of
          children's  activity  patterns.   California
Page
16-16
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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                   Environmental  Protection Agency,
                   Air  Resources   Board   Research
                   Division.  Sacramento, CA.
Wong, E.Y.; Shirai,  J.H; Garlock, T.J.; Kissel,  J.C.
           (2000) Adult proxy responses to a survey of
           children's dermal soil contact activities.  J
           Expo Anal Environ Epidemiol 10:509-517.
                             Table 16-3. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
                                     Ten Major Activity Categories, for All Respondents and Doers
      Activity Category
 Mean
Duration
  (All)
                                           Doers"
 Mean        Median     Maximum
Duration      Duration     Duration
(Doers)'      (Doers)'     (Doers)'
 Detailed Activity with
Highest Average Minutes
  Work-related11                   10
  Household0                     53
  Childcared                      <1
  Goods/Services"                21
  Personal Needs and Caref        794
  Education8                    110
  Organizational Activities'1          4
  Entertain/Social'                15
  Recreationj                    239
  Communication/Passive
  T  •     k                      iyz
  Leisure
               25           39            30          405       Eating at Work/School/Daycare
               86           61            40          602       Travel to Household
               <1           83            30          290       Other Child Care
               26           81            60          450       Errands
               100          794          770         1,440      Night Sleep
               35           316          335          790       School Classes
                4           111          105          435       Attend Meetings
               17           87            60          490       Visiting with Others
               92           260          240          835       Games

               93           205          180          898       TV Use
Don't know/Not coded
All Activities
2
1,440
4
41
15
600
;
             Doers indicate the respondents who reported participating in each activity category.
             Includes: travel to and during work/school; children's paid work; eating at work/school/daycare; and accompanying or watching
             adult at work.
             Includes: food preparation; meal cleanup; cleaning; clothes care; car and home repair/painting; building a fire; plant and pet care; and
             traveling to household.
             Includes: baby and child care; helping/teaching children; talking and reading; playing while caring for children; medical care; travel
             related to child care; and other care.
             Includes: shopping; medical appointments; obtaining personal care services (e.g., haircuts), government and financial services, and
             repairs; travel related to goods an services; and errands.
             Includes: bathing, showering, and going to bathroom; medical care; help and care; meals; night sleep and daytime naps, dressing and
             grooming; and travel for personal care.
             Includes: student and other classes; daycare; homework; library; and travel for education.
             Includes: attending meetings and associated travel.
             Includes: sports events; eating and amusements; movies and theater; visiting museums, zoos, art galleries, etc.; visiting others; parties
             and other social events; and travel to social activities.
             Includes: active sports; leisure; hobbies; crafts; art; music/drama/dance; games; playing; and travel to leisure activities.
             Includes: radio and television use; reading; conversation; paperwork; other passive leisure; and travel to passive leisure activities.
  Source:     Wiley et al., 1991.
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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-4. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Ten Major Activity Categories, by Age and Gender
Boys

Activity
Category1

Work-related
Household
Childcare
Goods/Services
Personal Needs and Care
Education
Organizational Activities
Entertainment/Social
Recreation
Communication/Passive
Leisure
Sample Sizes
(Unweighted)

Birth to
1 Month
0
12
0
0
910
180C
0
0
0
338

3

lto<3
Months
0
30
0
16
1,143
0
0
0
0
250

7

3to<6
Months
0
49
0
14
937
75
0
0
26
339

15

6to<12
Months
1
28
0
28
919
70
0
0
104
292

31

lto<2
Years
8
35
0
27
903
33
7
8
314
106

54

2to<3
Years
9
44
0
14
889
69
0
6
304
103

62

3to<6
Years
10
44
0
28
802
67
5
15
294
175

151

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Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-5. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Ten Major Activity Categories, Grouped by Seasons and Regions
Activity Category0
Work-related
Household
Childcare
Goods/Services
Personal Needs and
Care
Education
Organizational
Activities
Entertainment/Social
Recreation
Communication/
Passive Leisure
Don't know/Not coded
All Activities'"
Sample Sizes
(Unweighted)

Winter
(Jan-Mar)
10
47
<1
19
799
124
3
14
221
203
<1
1,442
318

Season
Region of California
Spring Summer Fall All
(Apr-June) (July-Sept) (Oct-Dec) Seasons
10
58
1
17
774
137
5
12
243
180
2
1,439
204
6
53
<1
26
815
49
5
12
282
189
3
1,441
407
13
52
<1
23
789
131
3
22
211
195
<1
1,441
271
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
Southern
Coast
10
45
<1
20
799
109
2
17
230
206
1
1,440
224
Bay
Area
10
62
<1
21
785
115
6
10
241
190
1
1,442
263
Rest of
State
8
55
1
23
794
109
6
16
249
175
3
1,439
713
All
Regions
10
53
<1
21
794
110
4
15
239
192
2
1,441
1,200
a See Table 16-3 for a description of what is included in each activity category.
b The column totals may not be equal to 1,440 due to rounding.
Source: Wiley et al., 1991.
Child-Specific Exposure Factors Handbook
September 2008	
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                                             Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-6. Time (minutes/day) Children Under 12 Years of Age Spent in
Six Major Location Categories, for All Respondents and Doers
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
All Locations
Mean Mean Median Maximum
Duration ., Duration Duration Duration
(All) /oUoers (Doers). (Doers)" (Doers)"
1,078 99 1,086 1,110 1,440
109 33 330 325 1,260
80 32 251 144 1,440
24
69 83 83 60 1,111
79 57 139 105 1,440
<1 1 37 30 90
1,440 ...
Detailed Location with
Highest Average Time
Home - Bedroom
School or Daycare Facility
Friend's/Other's House - Bedroom
Shopping Mall
Traveling in Car
Park, Playground
-
-
" Doers indicate the respondents who reported participating in each activity category.
Source: Wiley et al., 1991.


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Chapter 16 - Activity Factors	
Table 16-7.
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
Sample Sizes
(Unweighted)
Location Category
Home
School/Childcare
Friend's/Other's House
Stores, Restaurants,
Shopping Places
In-transit
Other Locations
Don't Know/Not Coded
Sample Sizes
(Unweighted)

Birth to
1 Month
938
0
418
0
77
7
0
3

Birth to
1 Month
1,285
0
0
0
73
83
0
4
a The source data end at 1 1
included.
Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Six Location Categories, Grouped by Age and Gender

lto<3
Months
1,295
1
40
14
51
40
0
7

lto<3
Months
1,341
0
12
13
56
19
0
10

3to<6
Months
1,164
26
127
21
69
33
0
15

3to<6
Months
1,151
109
44
20
42
73
0
11
years of age, so the

6to<12
Months
1,189
53
63
36
63
36
0
31

6to<12
Months
1,192
99
32
15
58
43
0
23

lto<2
Years
1,177
73
54
29
56
52
0
54

lto<2
Years
1,162
56
109
21
55
38
0
43
11 to <16year catej
Boys
2to<3
Years
1,161
86
69
22
61
41
0
62
Girls
2to<3
Years
1,065
61
103
40
86
86
0
50

3to<6
Years
1,102
79
89
24
67
78
0
151

3to<6
Years
1,118
78
66
32
78
67
1
151

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                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Six Location Categories, Grouped by Season and Region
Location Category
Home
School/Childcare
Friend's/Other's
House
Stores, Restaurants,
Shopping Places
In transit
Other Locations
Don't Know/Not
Coded
All Locations*
Sample Sizes
(Unweighted N's)

Winter
(Jan-Mar)
1,091
119
69
22
75
63

<
1,439
318
* The column totals may
Source: Wiley etal
, 1991.

Spring
(Apr-June)
1,042
141
75
21
75
85

<
1,439
204
Season
Summer
(July-Sept)
1,097
52
108
30
60
93

<
1,440
407
Region of California
Fall
(Oct-Dec)
1,081
124
69
24
65
76

<
1,439
271
All
Seasons
1,078
109
80
24
69
79

<
1,439
1,200
Southern
Coast
1,078
113
73
26
71
79

<
1,439
224
Bay
Area
1,078
103
86
23
73
76

<
1,440
263
Rest of
State
1,078
108
86
23
63
81

<
1,440
713
All
Regions
1,078
109
80
24
69
79

<
1,439
1,200
not sum to 1,440 due to rounding.








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Chapter 16 - Activity Factors	
Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
Proximity to Two Potential Sources of Exposure, Grouped by All Respondents, Age, and Gender
Potential
Exposures
Gasoline Fumes
Gas Oven Fumes
Sample Sizes
(Unweighted N's)
Potential
Exposures
Gasoline Fumes
Gas Oven Fumes
Sample Sizes
(Unweighted N's)

Birth to
1 Month
3
0
3

Birth to
1 Month
0
0
4

lto<3
Months
9
0
7

lto<3
Months
3
0
10

3to<6
Months
0
2
15

3to<6
Months
0
0
11

6to<12
Months
2
2
31

6to<12
Months
3
0
23

lto<2
Years
1
1
54

lto<2
Years
1
0
43
Boys
2to<3
Years
4
3
62
Girls
2to<3
Years
2
3
50

3to<6
Years
2
0
151

3to<6
Years
1
2
151
a The source data end at 1 1 years of age, so the 11 to <16 year category is truncated and the 16to
Source: U.S. EPA analysis of source data used by Wiley et al., 1991.


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                                                                  Child-Specific Exposure Factors Handbook
                                                                 	Chapter 16 - Activity Factors
                               Table 16-10.  Mean Time (minutes/day) Children Under 12 Years of Age
                                      Spent Indoors and Outdoors, Grouped by Age and Gender
      Age Group
                                             Boys
                                                                                                Girls
                          N
                                       Indoors"
                                                          Outdoors1"
                                                                             N
                                                                                          Indoors"
                                                                                                 Outdoors1"
  Birth to <1 Month
  1 to <3 Months
  3 to <6 Months
  6 to < 12 Months
  1 to <2 Years
  2 to <3 Years
  3 to <6 Years
  6 to <11 Years
  11 Years0
  All Ages
               3
               7
              15
              31
              54
              62
              151
              239
              62
              624
1,440
1,432
1,407
1,322
1,101
1,121
1,117
1,145
1,166
1,181
 0
 8
33
118
339
319
323
295
274
258
 4
 10
 11
 23
 43
 50
151
225
 59
576
1,440
1,431
1,421
1,280
1,164
1,102
1,140
1,183
1,215
1,181
 0
 9
 19
160
276
338
300
255
225
258
  N
  Note:
Time indoors was estimating by adding the average times spent performing indoor activities (household work, child care, personal
needs and care, education, and communication/passive leisure) and half the time spent in each activity which could have occurred
either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social, don't know/not coded).
Time outdoors was estimated by adding the average time spent in recreation activities and half the time spent in each activity which
could have occurred either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social,
don't know/not coded).
The source data end at 11 years of age, so the 11 to <16year category is truncated and the 16 to <21 year category is not included.
= Sample size.
Indoor and outdoor minutes/day may not sum to 1,440 minutes/day due to rounding.
  Source:    U.S. EPA analysis of source data used by Wiley et al., 1991.
Page
16-24
                                                      Child-Specific Exposure Factors Handbook
                                                     	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only

Age (years)

N Mean Min
Percentiles
1
2
5 10 25
50
75
90
95
98
99

Max
Kitchen - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16- 11

Age (years)

N Mean

Min
. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)
Percentiles
1
2
5 10
25
50
75
90
95
98

Max
99
Dining Room - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)

Age (years)


N


Mean Min

Percentiles

1

2

5 10 25

50

75

90

95

98

99

Max

Bedroom - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
Whole Population and Doers Only (continued)


Age (years) N Mean Mm

Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations
Whole Population and Doers Only

Age (years)

N

Mean

Min
Percentiles
1
2
5
10
25
50
75
90
95
98

Max
99
Restaurants - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations
Whole Population and Doers Only (continued)
Age (years) N Mean
Min
Percentiles
1
2 5 10 25
50
Grocery/Convenience Stores, Other Stores, and Malls -
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	


Age (years)






Table

1
16-13. Time Spent (minutes/day) in Selected Outdoor Locations
Whole Population and Doers Only

2 5

10 25
Percentiles
50 75

90

95

98

99


School Grounds/Playground - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                             Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors

Age (years)
Table

1
16-13. Time Spent (minutes/day) in Selected Outdoor Locations
Whole Population and Doers Only (continued)
Percentiles
2 5
10
Pool, River, or Lake -
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                    Table 16-14.  Mean Time Spent (minutes/day) Inside and Outside, by Age Category

    Age (years)          N        Average Indoor Minutes2    Average Outdoor Minutesb       Average Unclassified
                                                                                                 Minutes0
Birth to <1
lto<2
2to<3
3 to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
Whole Population and Doers Only

Age (years)

N

Mean Min
Percentiles
1 2
5
10 25
50
75
90
95
98
99

Max
Car - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
Whole Population and Doers Only (continued)


Age (years) N Mean

Mm
1
Percentiles
2
5 10
25
50
75
90
95
98

Max
99
Bus - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only








Percentiles
1
2
5 10 25 50
75
90
95
98

99
Sleeping/Napping - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	

Age (years)

N

Mean
Table

1
16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)

2

5 10

25
Percentiles
50

75 90

95

98

99
Attending School Full-Time - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)
Age (years)
N
Mean
Min
Percentiles
1 2
5
10
25
50
75
90
95
98

99
Active Sports - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-16. Time Spent (minutes/day) in Selected Activities
Whole Population and Doers Only (continued)
Age (years) N Mean
Min
Percentiles
1 2
5
10 25 50
75
90
95
98

99
Walking - Whole Population
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-17. Number of Showers Taken per Day, by Number of Respondents


Showers per Day


Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing

Age (years)

N

Mean Min
> and Showering
Percentiles
1
2
5 10
25
50
75
90
95 98


Max
99
Duration of Bath (minutes)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                                         Chapter 16 - Activity Factors

Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing and Showering (continued)
Age
(years)
N Mean
Min
Percentiles
1 2 5 10
25
50
75
90
95
98
99
Max
Duration of Shower (minutes)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-19. Range of Number of Times Washing the Hands at


Specified Daily Frequencies by the Number of Respondents
Number of Times/Day
Age (yearsj IN

Birth to <1
1 to<2
2to<3
3 to<6
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-20. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents

Age
(years)
Birth to <1
lto<2
2to<3
3to<6
6to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-21. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool


Percentiles
Age (years) IN Mean Mm

Birth to <1
lto<2
2to<3
3to<6
6to
-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 16 - Activity Factors
Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass
Whole Population and Doers only

Age (years)

N

Mean

Min
Percentiles
1
2
5 10
25
50
75 90
95
98

99
Playing on Dirt - Whole Population
Birth to
-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass
Whole Population and Doers Only (continued)
Age (years) N Mean Min
Percentiles
1
2
5 10 25
50
75
90
95
98
99
Max
Playing on Grass - Whole Population
Birth to
-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 16 - Activity Factors
Table 16-23. Time Spent (minutes/day) Working or Beinj
Age (years) N
Birth to <1
lto<2
2to<3
3 to<6
6to Near Excessive Dust in the Air
Percentiles
1
_
-
-
0
0
0
2
2
_
-
-
1
0
0
3
5
_
-
-
1
1
1
4
10
_
-
-
2
2
2
7
= Doer sample size.
For sample sizes of 10 or fewer, percentiles were not calculated.
A value of "121" for number of minutes signifies that more than
U.S. EPA re-analysis of source data from U.S.
EPA,
25
_
-
-
8
5
6
16
50
_
-
-
60
45
38
53
75 90 95
_
.
.
121 121 121
121 121 121
113 121 121
121 121 121

Max
98 99
121
121
121
121 121 121
121 121 121
121 121 121
121 121 121
120 minutes were spent.
1996 (NHAPS).

Age
(years)
Ito4
5 to 11
12 to 17
N
Source:
Table
16-24. Time Spent (minutes/day) with Smokers Present
Percentiles
N Mean SD SE
155 367 325 26
224 318 314 21
256 246 244 15
= Doer sample size.
U.S. EPA, 1996 (NHAPS).
Min
5
1
1


5
30
25
10


25
90
105
60


50
273
190
165


75
570
475
360


90
825
775
595


95
1,010
1,050
774


98
1,140
1,210
864


99
1,305
1,250
1,020


Max
1,440
1,440
1,260


Page
16-48
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-25. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of Day
Activity
Market Work
Household Work
Personal Care
Eating
Sleeping
School
Studying
Church
Visiting
Sports
Outdoors
Hobbies
Art Activities
Playing
TV
Reading
Household Conversations
Other Passive Leisure
NA
Percent of Time Accounted for
by Activities Above
N = Sample size.
NA = Unknown.
= No data.
Source: Timmer et al., 1985.

Age (3 to
Weekdays
Boys
(N=118)
16
17
43
81
584
252
14
7
16
25
10
3
4
137
117
9
10
9
22
94




Girls
(N=lll)
0
21
44
78
590
259
19
4
9
12
7
1
4
115
128
7
11
14
25
92




1 1 years)
Age (12 to 17 years)
Weekends
Boys
(N=118)
7
32
42
78
625
-
4
53
23
33
30
3
4
177
181
12
14
16
20
93




Girls
(N=lll)
4
43
50
84
619
-
9
61
37
23
23
4
4
166
122
10
9
17
29
89




Weekdays
Boys
(N=77)
23
16
48
73
504
314
29
3
17
52
10
7
12
37
143
10
21
21
14
93




Girls
(N=83)
21
40
71
65
478
342
37
7
25
37
10
4
6
13
108
13
30
14
17
92




Weekends
Boys
(N=77)
58
46
35
58
550
-
25
40
46
65
36
4
11
35
187
12
24
43
10
88




Girls
(N=83)
25
89
76
75
612
-
25
36
53
26
19
7
9
24
140
19
30
33
4
89




Child-Specific Exposure Factors Handbook
September 2008	
Page
16-49

-------
                                                              Child-Specific Exposure Factors Handbook
                                                             	Chapter 16 - Activity Factors
              Table 16-26.  Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different Age Groups
                                     Weekday
                                                                            Weekend
        Activity
                       3-5
                         Age (years)
                          9-11    12-14
                                                     15-17
                                                              3-5
      Age (years)
       9-11    12-14
                           Significant
                            Effects'
                                                                                            15-17
  Market Work             -      14      8       14       28
  Personal Care            41     49     40      56       60
  Household Work         14     15     18      27       34
  Eating                 82     81     73      69       67
  Sleeping                630    595     548     473      499
  School                 137    292     315     344      314
  Studying                2      8      29      33       33
  Church                  4999        3
  Visiting                14     15     10      21       20
  Sports                  5      24     21      40       46
  Outdoor Activities         49       8       7        11
  Hobbies                 0224        6
  Art Activities             5      4       3       3        12
  Other Passive Leisure       9126        4
  Playing                 218    111     65      31       14
  TV                    111    99     146     142      108
  Reading                 5      5       9       10       12
  Being Read to            2200        0
  NA                    30     14     23      25       7
                                                          4      10
                                                   47     45     44
                                                   17     27     51
                                                   81     80     78
                                                   634   641     596
                                                    1
                                                   55
                                                   10
                                                    3
                                                    8
                                                    1
                                                    4
                                                    6
                                                   267
                                                   122
                                                    4
                                                    3
                                                   52
 2
56
 8
30
23
 5
 4
10
180
136
 9
 2
 7
12
53
13
42
39
 3
 4
 7
92
185
10
 0
14
29
60
72
68
604

15
32
22
51
25
 8
 7
10
35
169
10
 0
 4
                        48
                        51    A,S,AxS(F>M)
                        60    A,S, AxS (F>M)
                        65    A
                        562   A
30
37
56
37
26
 3
10
18
21
157
18
 0
 9
A
A
A (Weekend Only)
A,S (M>F)
A
A,S (M>F)
A,S, AxS (M>F)
A
A
A
  NA
Effects are significant for weekdays and weekends,
weekend activities; S = sex effect P<0.05, F>M, M:
interaction, P<0.05.
= Unknown.
= No data.
                                                   unless otherwise specified. A = age effect
                                                   >F = females spend more time than males,
              , P<0.05, for both weekdays and
              or vice versa; and AxS = age by sex
  Source:     Timmer et al., 1985.
Page
16-50
                                                   Child-Specific Exposure Factors Handbook
                                                  	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                     Table 16-27. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week
                                              Indoors"
                                                                                            Outdoors1"
         Age Group
                                  Weekday
                                                         Weekend
Weekday
                                                                                                       Weekend
3 to 5 years
6 to 8 years
9 to 1 1 years
12 to 14 years
15 to 17 years
19.4
20.7
20.8
20.7
19.9
18.9
18.6
18.6
18.5
17.9
2.5
1.8
1.3
1.6
1.4
3.1
2.5
2.3
1.9
2.3
  a          Time indoors was estimated by adding the average times spent performing indoor activities (household work, personal care, eating,
            sleeping, attending school, studying, attending church, watching television, and engaging in conversation) and half the time spent in
            each activity which could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing,
            reading, and other passive leisure).
  b          Time outdoors was estimated by adding the average time spent in outdoor activities and half the time spent in each activity which
            could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing, reading, and other passive
            leisure).

  Source:     Adapted from Timmer et al., 1985.
Child-Specific Exposure Factors Handbook
September 2008	
                                 Page
                                16-51

-------
                                                           Child-Specific Exposure Factors Handbook

                                                          	Chapter 16 - Activity Factors
                     Table 16-28.  Mean Time Spent (minutes/day) in Various Microenvironments,
                           Children Ages 12 to 17 Years National and California Surveys
             Microenvironment
                                                                     National Data
                                                                 Mean (Standard Error)"
                                                      All
                                                    N=340
                                Doers Onlyb
 Autoplaces
 Restaurant/Bar
 In-vehicle/Internal Combustion
 In-Vehicle/Other
 Physical/Outdoors
 Physical/Indoors
 Work/Study-Residence
 Work/Study-Other
 Cooking
 Other Activities/Kitchen
 Chores/Child
 Shop/Errands
 Other/Outdoors
 Social/Cultural
 Leisure-Eat/Indoors
 Sleep/Indoors
  2(1)
  9(2)
 79(7)
  0(0)
 32(8)
 15(3)
 22(4)
159(14)
 11(3)
 53(4)
 91(7)
 26(4)
70 (13)
87 (10)
237(16)
548(31)
 73
 60
 88
 12
130
 87
 82
354
 40
 64
 92
 68
129
120
242
551
             Microenvironment
                                                                      CARB Data
                                                                 Mean (Standard Error)"
                                                      All
                                                    N=183
                                Doer Onlyb
 Autoplaces
 Restaurant/Bar
 In-Vehicle/Internal Combustion
 In-Vehicle/Other
 Physical/Outdoors
 Physical/Indoors
 Work/Study-Residence
 Work/Study-Other
 Cooking
 Other Activities/Kitchen
 Chores/Child
 Shop/Errands
 Other/Outdoors
 Social/Cultural
 Leisure-Eat/Indoors
 Sleep/Indoors	
 16(8)
 16(4)
 78(11)
  1(0)
 32(7)
 20(4)
 25(5)
196 (30)
  3(1)
 31(4)
 72(11)
 14(3)
 58(8)
 63 (14)
260 (27)
557 (44)
124
44
89
19
110
65
76
339
19
51
77
50
78
109
270
560
 a         Weighted values.
 b         Doers only = respondents who reported participating in each activity/microenvironment.

 Source:   Robinson and Thomas, 1991.	
Page
16-52
       Child-Specific Exposure Factors Handbook
      	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-29. Gender and Age Groups
Age Group a
6 to 8 years (males)
6 to 8 years (females)
9 to 1 1 years (males)
9 to 1 1 years(females)
12 to 17 years (males)
12 to 17 years (females)
N
145
124
156
160
98
85
a Children under the age of 6 were excluded because there were
too few responses in the CARB study.
N = Sample size.
Source: Funket al., 1998.

Child-Specific Exposure Factors Handbook
September 2008	
Page
16-53

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-30. Assignment of At-Home Activities to Inhalation Rate Levels for Children
Low
Watching child care
Night sleep
Watch personal care
Homework
Radio use
TV use
Records/tapes
Reading books
Reading magazines
Reading newspapers
Letters/writing
Other leisure
Homework/watch TV
Reading/TV
Reading/listen music
Paperwork

























Moderate
Outdoor cleaning
Food Preparation
Metal clean-up
Cleaning house
Clothes care
Car/boat repair
Home repair
Plant care
Other household
Pet care
Baby care
Child care
Helping/teaching
Talking/reading
Indoor playing
Outdoor playing
Medical child care
Washing, hygiene
Medical care
Help and care
Meals at home
Dressing
Visiting at home
Hobbies
Domestic crafts
Art
Music/dance/drama
Indoor dance
Conservations
Painting room/home
Building fire
Washing/dressing
Outdoor play
Playing/eating
Playing/talking
Playing/watch TV
TV/eating
TV/something else
Reading book/eating
Read magazine/eat
Read newspaper/eat
Source: Funk et al, 1998.
Page
16-54
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-3 1 . Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents and Children3
Activi
Low
Moderate
High
Highpalticipa
a
b
SD
Source:


Adolescents
Mean

SD
789 230


c
nts
197
1
43
131
11
72
Children
Mean
823
241b
3
58
Time spent engaging in all activities embodied by inhalation rate category (minutes/day).
Significantly different from adolescents (p <0.05).
Represents time spent at-home by individuals participating in high inhalation rate level activities (i
= Standard deviation.
Funketal., 1998.




SD
153
136
17
47
e., doers).

Table 16-32. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents)
Male
Mean SD
Low 775 206
Moderate 181 126
High 2 16
Female
Mean SD
804 253
241 134
0 0
SD = Standard deviation.
Source: Funk et al, 1998.
Child-Specific Exposure Factors Handbook                                        Page
September 2008	16-55

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-33. Comparison of Mean Time Spent (minutes/day) At-Home, by
Activity
Group
Low
Moderate
High
Highpalticipa
a
b
SD
Source:


6-8 Years
Mean
806
259
3
b 77
nt ' '
SD
134
135
17
59
Males

9-11 Years
Mean
860
198
7
70
Time spent engaging in all activities embodied by
Participants in high inhalation rate activities (i.e.,
= Standard deviation.
Funketal, 1998.
SD
157
111
27
54

Gender and Age for Children3
Females

6-8 Years 9-11 Years
Mean
828
256
1
68
inhalation rate category
doers).
SD Mean
155 803
141 247
9 2
11 30
(minutes/day).
SD
162
146
10
23

Page                                        Child-Specific Exposure Factors Handbook
16-56	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-34. Number of Person-Days/mdividualsa for Children in CHAD Database
Age Group All Studies
0 Year
223/199
0 to 6 Months
6 to 12 Months
1 Year
12 to 18
Months
18 to 24
Months
2 Years
3 Years
4 Years
5 Years
6 Years
7 Years
8 Years
9 Years
10 Years
1 1 Years
Total
a
b
Source:
259/238
_

_

317/264
278/242
259/232
254/227
237/199
243/213
259/226
229/195
224/199
227/206
3,009/2,640
California11
104
50
54
97
57

40

112
113
91
98
81
85
103
90
105
121
1,200
Cincinnati'
36/12
15/5
21/7
31/11
_

_

81/28
54/18
41/14
40/14
57/19
45/15
49/17
51/17
38/13
32/11
556/187
NHAPS-Air NHAPS-Water
39
-
-
64
_

_

57
51
64
52
59
57
51
42
39
44
619
44
-
-
67
_

_

67
60
63
64
40
56
55
46
42
30
634
The number of person-days of data are the same as the number of individuals for all studies except for the
Cincinnati study. Since up to three days of activity pattern data were obtained from each participant in this study,
the number of person-days of data is approximately three times the number of individuals.
The California study referred to in this table is the Wiley et al. (1991) study.
The Cincinnati study referred to in this table is the Johnson (1989) study.
= No data.
Hubaletal.,2000.




Child-Specific Exposure Factors Handbook
September 2008	
Page
16-57

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-35. Time Spent (hours/day) in Various Microenvironments, by Age
Average Time ± Standard Deviation (Percent >0 Hours)
Age (years)
0
1
2
3
4
5
6
7
8
9
10
11
Source: Hubal
Indoors at Home
19. 6 ±4. 3 (99)
19. 5 ±4.1 (99)
17.8 ±4.3 (100)
18.0 ±4.2 (100)
17.3 ±4. 3 (100)
16. 3 ±4. 0(99)
16.0 ±4.2 (98)
15. 5 ±3. 9 (99)
15. 6 ±4.1 (99)
15.2 ±4. 3 (99)
16.0 ±4.4 (96)
14.9 ±4.6 (98)
etal.,2000.
Outdoors at Home
1.4 ±1.5 (20)
1.6 ±1.3 (35)
2.0 ±1.7 (46)
2.1 ±1.8 (48)
2.4 ±1.8 (42)
2. 5 ±2.1 (52)
2.6 ±2.2 (48)
2.6 ±2.0 (48)
2.1 ±2. 5 (44)
2. 3 ±2. 8 (49)
1.7 ±1.9 (40)
1.9 ±2. 3 (45)

Indoors at School
3. 5 ±3. 7 (2)
3.4 ±3. 8 (5)
6.2 ±3. 3 (9)
5.7 ±2.8 (14)
4. 9 ±3.2 (16)
5.4 ±2. 5 (39)
5. 8 ±2.2 (34)
6. 3 ±1.3 (40)
6.2 ±1.1 (41)
6.0 ±1.5 (39)
5. 9 ±1.5 (39)
5. 9 ±1.5 (41)

Outdoors at Park
1.6 ±1.5 (9)
1.9±2.7(10)
2.0 ±1.7 (17)
1.5 ±0.9 (17)
2. 3 ±1.9 (20)
1.6 ±1.5 (28)
2.1 ±2.4 (32)
1.5 ±1.0 (28)
2.2 ±2.4 (37)
1.7 ±1.5 (34)
2.2 ±2.3 (40)
2.0 ±1.7 (44)

In Vehicle
1.2 ±1.0 (65)
1.1 ±0.9 (66)
1.2 ±1.5 (76)
1.4 ±1.9 (73)
1.1 ±0.8 (78)
1.3 ±1.8 (80)
1.1 ±0.8 (79)
1.1 ±1.1 (77)
1.3 ±2.1 (82)
1.2 ±1.2 (76)
1.1 ±1.1 (82)
1.6 ±1.9 (74)

Page
16-58
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	

Age
(years)
0
1
2
3
4
5
6
7
8
9
10
11
Source:

Table 16-36
Mean Time Children Spent (hours/day) Doing Various
Macroactivities While Indoors at Home
Mean Time (Percent >0 Hours)
Eat
1.9(96)
1.5(97)
1.3(92)
1.2(95)
1.1(93)
1.1(95)
1.1 (94)
1.0(93)
0.9(91)
0.9(90)
1.0(86)
0.9(89)
Hubal et al
Sleep or
Nap
12.6(99)
12.1 (99)
11.5(100)
11.3(99)
10.9(100)
10.5(98)
10.4(98)
9.9(99)
10.0(96)
9.7(96)
9.6 (94)
9.3 (94)
, 2000.
Shower or
Bathe
0.4 (44)
0.5 (56)
0.5(53)
0.4(53)
0.5 (52)
0.5 (54)
0.4 (49)
0.4 (56)
0.4(51)
0.5 (43)
0.4 (43)
0.4 (45)

Play Games
4.3 (29)
3.9(68)
2.5(59)
2.6(59)
2.6 (54)
2.0 (49)
1.9(35)
2.1 (38)
2.0(35)
1.7(28)
1.7(38)
1.9(27)

Watch TV or
Listen to Radio
1.1(9)
1.8(41)
2.1 (69)
2.6(81)
2.5 (82)
2.3(85)
2.3 (82)
2.5 (84)
2.7(83)
3.1(83)
3.5 (79)
3.1(85)

Read, Write,
Homework
0.4 (4)
0.6(19)
0.6 (27)
0.8 (27)
0.7(31)
0.8(31)
0.9(38)
0.9 (40)
1.0(45)
1.0(44)
1.5(47)
1.1 (47)

Think, Relax,
Passive
3.3 (62)
2.3 (20)
1.4(18)
1.0(19)
1.1(17)
1.2(19)
1.1(14)
0.6(10)
0.7 (7)
0.9(17)
0.6(10)
0.6(10)

Child-Specific Exposure Factors Handbook
September 2008	
Page
16-59

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors
Table 16-37
Time Children Spent (hours/day) in Various Microenvironments, by Age
Recast into New Standard Age Categories
Indoors at Home
Age Group
Birth to <1 month
1 to <3 months
3 to <6 months
6 to < 12 months
1 to <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21 years
N
123
33
120
287
728
765
2,110
3,283
2,031
1,005
Mean
Time
19.6
20.9
19.6
19.1
19.2
18.2
17.3
15.7
15.5
14.6
Doing
98
100
100
99
99
99
100
99
97
98
Outdoors at Home
Mean
Time
1.7
1.8
0.8
1.1
1.4
1.8
1.9
1.9
1.7
1.4
%
Doing
21
9
8
15
34
38
43
40
30
20
Indoors at School
Mean
Time
4.3
0.2
7.8
7.6
6.4
6.8
5.9
6.5
6.6
5.7
Doing
3
3
7
8
9
12
26
44
45
33
Outdoors at Park
Mean
Time
1.3
1.6
1.3
1.8
1.5
2.1
1.6
2.1
2.6
3.1
Doing
3
9
6
5
5
7
10
17
15
10
In Vehicle
Mean
Time
1.3
1.3
1.1
1.3
1.1
1.3
1.3
1.1
1.3
1.7
Doing
63
27
14
14
27
28
29
29
42
90
N = Sample size.
Source: Based on data source used by
Hubal et al
, 2000 (CHAD).
Page
16-60
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-38. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
Recast Into New Standard Age Categories
Eat
Mean
Time
Birth to <1 month 123 2.2
1 to <3 months 33 2.4
3 to <6 months 120 2.0
6 to <12 months 287 1.8
1 to <2 years 728 1.7
2 to <3 years 765 1.5
3 to <6 years 2,110 1.4
6to
-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors

Table 16-39.
Number and Percentage of Respondents with Children and Those Reporting
Outdoor Playa Activities in both Warm and Cold Weather
Respondents ™-1JT)1 a
vv.V.1. -i j Child Players3
with Children J
Source

SCS-II
SCS-II
sample
Total
a
b
N
Source:
N
base 197
483
680
N %
128 65.0
372 77.0
500 73.5
Child non-
Players
N %
69 35.0
111 23.0
180 26.5
Warm Cold
Weather Weather Players in Both Seasons
Playersa PlayerS
N N
127 100
370 290
497 390
"Play" and "player" refer specifically to participation in outdoor play on bare dirt or mixed
Does not include three "Don't know/refused" responses regarding warm weather play.
= Sample size.
Wong etal, 2000.



%
50.8
60.0
57.4
grass and dirt.

Page
16-62
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
Table 16-40. Play Frequency and Duration for all Child Players (from SCS-II data)
Statistic
N
5th Percentile
50th Percentile
95th Percentile

Frequency
(days/week)
372
1
3
7
Cold Weather
Duration
(hours/day)
374
1
1
4

Total
(hours/week)
373
1
5
20

Frequency
(days/week)
488
2
7
7
Warm Weather
Duration
(hours/day)
479
1
3
8

Total
(hours/week)
480
4
20
50
N = Sample size.
Source: Wong
etal.,2000.





Table 16-41.
Hand Washing and Bathing Frequency for all Child Players (from SCS-II data)
Cold Weather
Statistic
N
5th Percentile
50th Percentile
95th Percentile
N = Sample size.
Source: Wong et al, 2000.
Hand washing
(times/day)
329
2
4
10


Bathing
(times/week)
388
2
7
10


Warm Weather
Hand washing
(times/day)
433
2
4
12


Bathing
(times/week)
494
3
7
14


Child-Specific Exposure Factors Handbook
September 2008	
Page
16-63

-------
                                            Child-Specific Exposure Factors Handbook

                                            	Chapter 16 - Activity Factors

Data
NHAPS
SCS-II
a
b
Source:
Table 16-42.
Source
Cold Weather
114
102
NHAPS and SCS-II Play Duration3 Comparison
Mean Play Duration
(minutes/day)
Warm Weather
109
206
Selected previous day activities in NHAPS; average day outdoor play on
II.
2x2 Chi-square test for contingency between NHAPS and SCS-II.
Wong etal., 2000.
••2 testb
Total
223 pO.OOOl
308
bare dirt or mixed grass and dirt in SCS-
Table 16-43. NHAPS and SCS-II Hand Wash Frequency3 Comparison
Data
Source
NHAPS
SCS-II
NHAPS
SCS-II
a
b
Source:
Percenl
Season
Cold
Cold
Warm
Warm
0
3
1
3
0
Selected previous day
II.
Results are reported
2x2 Chi-square test
Wong etal., 2000.
1-2
18
16
18
12
3-5
51
50
51
46
activities in NHAPS;
b Reporting Frequency (times/day) of:
6-9
17
11
15
16
average day
10-19
7
7
7
10
20-29
1
1
2
1
outdoor play on bare dirt
as percentage of total for clarity. Incidence data
for contingency between NHAPS and SCS-II.





were used in

30+
1
0
1
0
or mixed g
statistical

"Don't ..2
Know"
3
15 P =
4
13 P =
rass and dirt in
tests.

test0

0.06

0.001
SCS-


Page
16-64
 Child-Specific Exposure Factors Handbook
	September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16 - Activity Factors	
                                      Table 16-44.  Time Spent (minutes/day) Outdoors
                                           Based on CHAD Data (Doers Only)'
  Age Group
                                              Time Spent Outdoors
                          Minimum
                                       Median
                                                  Maximum
                                                                Mean
                                                                             SD
                                                                           COV(%)
                                                                     Participation1" (%)
  <1 month
  1 to 2 months
  3 to 5 months
  6 to 11 months
  1 year
  2 years
  3 to 5 years
  6 to 10 years
  11 to 15 years
  16 to 17 years
  18 to 20 years
        57
        5
        27
        91
       389
       448
       1,336
       2,216
       1,423
       356
       351
2
4
10
5
1
1
1
1
1
1
1
60
60
90
60
75
100
120
120
110
85
70
 700
 225
 510
 450
1,035
 550
 972
1,440
1,440
1,083
 788
99
102
114
91
102
134
146
162
154
129
132
124
90
98
76
99
108
117
144
163
145
155
                                                                                         125
84
97
106
112
118
47
36
23
33
58
64
68
71
73
81
72
  SD
  COV
Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis.
Participation rates or percent of sample days in the study spending some time (>0 minutes per day) outdoors. The mean time spent
outdoors for the age group may be obtained by multiplying the participation rate by the mean time shown above.
= Standard deviation.
= Coefficient of variation (SD/mean x 100).
  Source:    Graham and McCurdy, 2004.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                                 Page
                                                                                                16-65

-------
 Child-Specific Exposure Factors Handbook




	Chapter 16 - Activity Factors

















































































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Page Child-Specific Exposure Factors Handbook
16-66 September 2008

-------
Child-Specific Exposure Factors Handbook

Chapter 16- Activity Factors	
Table 16-46. Time Spent (minutes/day) Indoors
Based on CHAD Data (Doers Only)"
Time Spent Indoors


F
<1 month

1 to 2 months
3 to 5 months


121
14
115
6 to 11 months 278
1 year
2 years
3 to 5 years



6 to 1 0 years
1 1 to 15 jei
rs
1 6 to 17 years
18 to 20 jei
rs
668
700
1,977
3,118
1,939
438
485

Minimum
490
1,125
840
840
315
290
23
7
69
161
512


Median
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
" Only data for individuals that spent >0
b Participation rates
indoors for the age
N
SD
COV
Source:
=
Sample size.
or percent of sample
380
380
385
370
350
319
307
292
300
296
310


Maximum
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
440
440
440
440
440
440
440
440
440
440
440
time indoors and had 30 or
days
group may be obtained by



in the study spending
multiply

ing the part


Mean
1,336
1,348
1,359
1,353
1,324
1,286
1,276
1,256
1,255
1,251
1,242

nVfO/,1! Pst-tif-
SD
137
105
93
81
107
138
136
153
160
171
180
more records are included in the
some time (;
cipation rate

S0 minutes per day)
10
8
7
6
8
11
11
12
13
14
15
analysis.
indoors. The mean
(as a decimal) by the mean time shown


pation (%)

100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
99.8
100.0
100.0

time spent
above.

= Standard deviation.
= Coefficient of variation (SD/mean
x 100).
Graham and McCurdy, 2004.
Child-Specific Exposure Factors Handbook
September 2008	
Page
16-67

-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 16- Activity Factors
Table 16-47. Time Spent (minutes/day) in Motor Vehicles
Based on CHAD Data (Doers Only)3

Time Spent in Motor Veh
Minimum Median
<1 month 80
1 to 2 months 9
3 to 5 months 75
6 to 1 1 months 226
1 year 515
2 years 581
3 to 5 years 1,702
6 to 10 years 2,766
11 to 15 years 1,685
16 to 17 years 400
18 to 20 years 449
o
20
13
4
1
2
1
1
1
4
4
68
83
60
51
52
54
55
58
60
73
76
Maximum
350
105
335
425
300
955
1,389
1,214
825
1,007
852
a Only data for individuals that spent >0 time in motor vehicles and
b Participation rates or percent of sample days in the study spending
time spent in motor vehicles for the age group may be obtained by
time shown above.
N = Sample size.
SD = Standard deviation.

COV = Coefficient of variation (SD/mean x
Source: Graham and McCurdy
2004.

100).




ides
Mean
86
67
71
62
67
73
70
71
76
92
109

SD
68
32
49
47
50
76
70
68
74
90
106
)V(%) Participation' (%)
79
48
69
76
76
104
99
95
97
98
98
had 30 or more records are included in the analysis
some time (>0 minutes per day) in motor vehicles.
multiplying the participation rate (as a decimal) by









66
64
65
81
77
83
86
89
87
91
93
The mean
the mean



Page
16-68
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors































&
(JKb

Table 16-48. Time Spent (minutes/two-day period)8 in Various Activities by
Panel Study of Income Dynamics (PSID), 1997 Child Development
Boy s(N= 1,444)
Age Group Standard
Mean ^ . .
Deviation
Television Use
1 to 5 years 197 168
6 to 8 years 263 165
9 to 12 years 251 185
Electronic Game Use
1 to 5 years 8 38
6 to 8 years 44 113
9 to 12 years 57 102
Computer Use
1 to 5 years 7 28
6 to 8 years 13 43
9 to 12 years 27 71
Print Use"
1 to 5 years 21 32
6 to 8 years 20 37
9 to 12 years 19 47
Highly Active Activities'
1 to 5 years 42 74
6 to 8 years 107 123
9 to 12 years 137 149
Moderately Active Activities'1
1 to 5 years 55 81
6 to 8 years 31 65
9 to 12 years 40 73
Sedentary Activities'
1 to 5 years 55 71
6 to 8 years 75 77
9 to 12 years 110 109
Children Participating in the
Supplement (CDS)
Girls (N= 1,
Mean8

184
239
266

5
14
18

7
8
15

23
20
29

34
62
63

59
37
46

54
80
122
387)
Standard
Deviation

163
159
194

40
39
47

35
28
43

34
32
56

78
92
88

92
69
89

71
84
111
" Means represent minutes spent in each activity over a 2-day period (one weekday and one weekend
day).
b Print use represents time spent using print media including reading and being read to.
' Includes all sport activities such as basketball, soccer, swimming, running or bicycling.
11 Includes activities such as singing, camping, taking music lessons, fishing, and boating.
' Includes activities such as playing board games, doing puzzles, talking on the phone, and relaxing.
N = Sample size.
Source: Vanderwater et al, 2004.



Child-Specific Exposure Factors Handbook
September 2008






























Page
16-69

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 16- Activity Factors
Table 16-49.
Mean Time Spent (minutes/day) in
Various Activity Categories, by Age -
2002-2003
Activity Category

Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
6 to 8
years
0
25
68
60
607
406
29
4
16
10
6
1
8
94
9
74
11
2
6
4
9 to 11
years
0
32
66
57
583
398
39
5
25
17
6
1
7
106
10
56
12
1
10
8
12 to 14
years
1
38
68
54
542
395
49
5
25
33
4
1
7
111
24
45
11
0
25
4
15 to 17
years
22
39
73
49
515
352
50
3
53
33
6
2
4
115
39
35
7
0
38
6
Weekday

1981-1982
6 to 8
years
-
15
49
81
595
292
8
9
-
24
9
2
4
99
-
Ill
5
-
-
-
9 to 11
years
-
18
40
73
548
315
29
9
-
21
8
2
3
146
-
65
9
-
-
-
12 to 14
years
-
27
56
69
473
344
33
9
-
40
7
4
3
142
-
31
10
-
-
-
15 to 17
years
28
34
60
67
499
314
33
3
-
46
11
6
12
108
-
14
12
-
-
-
= Data not provided.
Source: Justeret al, 2004







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Chapter 16- Activity Factors	
Table 16-50. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day
2002-2003
Activity Category

Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
6 to 8
years
0
81
78
89
666
3
5
41
61
23
12
2
11
155
14
163
14
1
12
9
9 to 11
years
0
91
72
80
644
6
9
37
66
40
12
1
7
184
15
134
15
1
19
8
12 to 14
years
9
100
73
69
633
7
20
36
58
40
12
4
9
181
40
148
13
0
39
9
15 to 17
years
39
79
77
64
629
7
24
30
91
27
11
5
6
162
54
59
7
0
58
11
1981-1982
6 to 8
years
-
27
45
80
641
-
2
56
-
30
23
5
4
136
-
180
9
-
-
-
9 to 11
years
-
51
44
78
596
-
12
53
-
42
39
3
4
185
-
92
10
-
-
-
12 to 14
years
-
72
60
68
604
-
15
32
-
51
25
8
7
169
-
35
10
-
-
-
15 to 17
years
48
60
51
65
562
-
30
37
-
37
26
3
10
157
-
21
18
-
-
-
= Data not provided.
Source: Juster et al., 2004







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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 16- Activity Factors
Table 16-51 . Mean Time Spent (minutes/week) in
Various Activity Categories for Children, Ages 6 to 17 Years
Activity Categ
Market work
Household work
Personal care
Eating
Sleeping, naps
School
Studying
Church
Visiting, socializing
Sports
Outdoor Activities
Hobbies
Art Activities
Television
Other passive leisure
Playing
Reading
Being read to
Computer activities
Missing data
Source: Juster et al.,
ory 2002-2003
53
343
493
426
4,092
1,947
238
94
287
179
50
12
48
876
166
485
77
5
165
45
2004.
1981-1982
126
223
356
508
3,758
1,581
158
125
132
244
100
27
40
944
39
440
69
3
0
1,206

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Child-Specific Exposure Factors Handbook
Chapter 16- Activity Factors	
                                     Table 16-52. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years
                                           Activity
                                                                                                                   hours/day
                                                                                                    Male
                                                                                                                    Female
                                                                                                                                       All
  Personal Carea
  Eating and Drinkingb
  Household Activities^
  Purchasing Goods and Servicesd
  Caring for and Helping Household Members6
  Caring for and Helping Non-Household Membersf
  Working on Work-related Activitiesg
  Educational Activities11
  Organizational Civic and Religious Activities1
  Leisure and  SportsJ
   total leisure and sports - weekdays
   total leisure and sports - weekends
   sports, exercise, recreation - weekdays
   sports, exercise, recreation - weekends/holidays
   socializing and communicating - weekdays
   socializing and communicating, - weekends/holidays
   watching TV - weekdays
   watching TV - weekends/holidays
   reading - weekdays
   reading - weekends/holidays
   relaxing, thinking - weekdays
   relaxing, thinking - weekends/holidays
   playing games, computer use for leisure - weekdays
   playing games, computer use for leisure - weekends/holidays
   other sports/leisure including travel - weekdays
   other sports/leisure including travel - weekends/holidays
  Telephone Calls, Mail, and E-mailk
  Other Activities not Elsewhere Classified1
10.26
1.02
0.61
 ).34
10.34
 1.11
 0.92
 0.74
 0.19
 0.23
 1.24
 3.51
 0.33
 4.75
10.30
 1.07
 0.76
 0.56
 0.15
 0.21
 1.39
 3.29
 0.34
 5.40
 4.85
 6.68
 0.58
 0.69
 0.76
 1.32
 1.96
 2.45
 0.11
 0.11
 0.15
 0.13
 0.69
 1.00
 0.61
 0.98
 0.33
 0.22
           Includes sleeping, bathing, dressing, health-related self care, and personal and private activities.
           Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent purchasing meals, snacks,
           or beverages.
           Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and renovation.
           Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair salons, barbershops, day
           spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry cleaning, vehicle maintenance, construction), and
           government services (e.g., applying for food stamps, government required licenses or paying fines).
           Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to child or adult,
           attending to health care needs, dropping off, picking up or waiting for children).
           Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with children, reading to child
           or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include activities done through a volunteer
           organization.
           Includes time spent as part of the job, income-generating activities, or job search activities.  Also includes travel time for work-related activities.
           Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, except sports.
           Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through participating in
           religious or spiritual activities (e.g., church choir, youth groups, praying).
           Includes sports, exercise, and recreation. This category is broken down into subcategories  for the 15  to  19 years old age category.
           Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related to work or
           volunteering.
           Includes residual activities that could not be coded or where information was missing.
           U.S. DL.2007.
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                                           	Chapter 16- Activity Factors
Table 16-53. Mean Time Spent (minutes/day) in Moderate-to- Vigorous Physical Activity
Age (years)

9
11
12
15
SD
Source:
Boys
190.8(53.2)
133.0(42.9)
105.3(40.2)
58.2(31.8)
= Standard deviation.
Nader et al. 2008-
Weekday
Mean (SD)
Girls
173.3(46.4)
115.6(36.3)
86.0(32.5)
38.7(23.6)


Both
181.8(50.6)
124.1(40.6)
95.6(37.8)
49.2(29.9)


Boys
184.3(68.6)
127.1(59.5)
93.4(55.3)
43.2(38.0)

Weekend
Mean (SD)
Girls
173.3(64.3)
112.6(53.2)
73.9(45.8)
25.5(23.3)


Both
178.6(66.6)
119.7(56.8)
83.6(51.7)
35.1(33.3)

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Chapter 17 - Consumer Products	
                                  TABLE OF CONTENTS

17     CONSUMER PRODUCTS  	17-1
       17.1    INTRODUCTION	17-1
       17.2    RECOMMENDATIONS  	17-2
       17.3    CONSUMER PRODUCTS USE STUDIES  	17-2
              17.3.1  CTFA, 1983	17-2
              17.3.2  U.S. EPA, 1996  	17-2
              17.3.3  Bass et al., 2001   	17-3
              17.3.4  Loretz et al., 2005  	17-4
              17.3.5  Loretz et al., 2006  	17-4
              17.3.6  Loretz et al., 2008  	17-5
              17.3.7  Sathyanarayana et al., 2008  	17-5
       17.4    REFERENCES FOR CHAPTER 17	17-5
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                                                     	Chapter 17 - Consumer Products
                                         LIST OF TABLES

Table 17-1.      Consumer Products Commonly Found in Some U.S. Households	17-7
Table 17-2.      Amount and Frequency of Use of Various Cosmetic and Baby Products	17-10
Table 17-3.      Number of Minutes Spent in Activities Working With or Near Freshly Applied
                Paints (minutes/day)	17-13
Table 17-4.      Number of Minutes Spent in Activities Working With or Near Household Cleaning
                Agents Such as Scouring Powders or Ammonia (minutes/day)	17-13
Table 17-5.      Number of Minutes Spent in Activities (at home or elsewhere) Working With
                or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day)	17-13
Table 17-6.      Number of Minutes Spent in Activities Working With or Near Glue (minutes/day)  	17-14
Table 17-7.      Number of Minutes Spent in Activities Working With or Near Solvents, Fumes or
                Strong Smelling Chemicals (minutes/day)  	17-14
Table 17-8.      Number of Minutes Spent in Activities Working With or Near Stain or Spot Removers
                (minutes/day)	17-14
Table 17-9.      Number of Minutes Spent in Activities Working With or Near Gasoline or
                Diesel-powered Equipment, Besides Automobiles (minutes/day)  	17-15
Table 17-10.     Number of Minutes Spent in Activities Working with or Near Pesticides,
                Including Bug Sprays or Bug Strips (minutes/day)	17-15
Table 17-11.     Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at
                Specified Daily Frequencies	17-15
Table 17-12.     Number of Respondents Using Any Aerosol Spray Product for Personal Care Item
                Such as Deodorant or Hair Spray at Specified Daily Frequencies 	17-16
Table 17-13.     Number of Respondents Using a Humidifier at Home	17-16
Table 17-14.     Number of Respondents Indicating that Pesticides Were Applied by the Professional at
                Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies	17-16
Table 17-15.     Number of Respondents Reporting Pesticides Applied by the Consumer at Home
                To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies	17-17
Table 17-16.     Number of Respondents Indicating that Pesticides Were Applied by a
                Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified
                Frequencies 	17-17
Table 17-17.     Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
                Eradicate Insects, Rodents, or Other Pests at  Specified Frequencies	17-17
 Table 17-18.     Household Demographics, and Pesticide Types, Characteristics, and Frequency of
                Pesticide Use  	17-18
Table 17-19.     Frequency of Use of Cosmetic Products  	17-19
Table 17-20.     Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream	17-20
Table 17-21.     Frequency of Use of Personal Care Products	17-22
Table 17-22.     Average Amount of Product Applied per Application (grams)	17-23
Table 17-23.     Average Amount of Product Applied per Use Day (grams)	17-24
Table 17-24.     Average Number of Applications Per Use Day	17-25
Table 17-25.     Average Amount of Product Applied Per Use Day (grams)	17-26
Table 17-26.     Average Amount of Product Applied Per Application (grams)	17-27
Table 17-27.     Characteristics of the Study Population and the Percent Using Selected Baby Care
                Products	17-28
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Chapter 17 - Consumer Products	
17      CONSUMER PRODUCTS
17.1    INTRODUCTION
        Consumer products may contain  toxic or
potentially  toxic  chemical constituents to  which
children may be exposed as a result of their  use. For
example, household cleaners can contain ammonia,
alcohols, acids, and/or organic solvents which may
pose health concerns. Potential routes of exposure to
consumer products  or  chemicals  released  from
consumer products during use  include ingestion,
inhalation, and dermal contact.  Children can be in
environments where adults use household consumer
products such as cleaners,  solvents, and paints.  As
such, children can be passively exposed to chemicals
in these products.   Since  children spend a  large
amount  of  time  indoors,  the use  of household
chemicals in the indoor environment can be a principal
source of exposure (Franklin, 2008).
        Very little information is available on  the
exact way the different kinds of products are used by
consumers, including the many ways in which these
products are handled, the frequency and duration of
contact, and the measures  consumers may take to
minimize exposure/risk  (Steenbekkers,  2001).  In
addition, the factors that influence these behaviors are
not well studied, but some studies have shown there is
a  large  variation in  behavior  between  persons
(Steenbekkers, 2001). This chapter presents available
information  on the amounts, frequency, and duration
of use for various consumer products found in typical
households.
        The studies  presented  in the following
sections represent readily available surveys from which
data were collected on the frequency and duration of
use and amount of use of cleaning products, household
solvent  products, cosmetic and other personal care
products, and pesticides.     For  a more  detailed
presentation of data on the  use of consumer  products
among the general population, the reader is referred to
the Exposure Factors Handbook (U.S. EPA, 1997).
        The National Library of Medicine Household
Products Database is a consumer guide that  provides
information on the potential health effects of chemicals
contained in more than 7,000 common household
products used inside and around the home. Although,
this  database  does  not provide  exposure  factor
information, it contains information on chemical
ingredients  and  their  percentages  in consumer
products, which products contain specific chemical
ingredients,  acute and chronic effects of chemical
ingredients,  and manufacturer information.  These
data could be useful when conducting an exposure
assessment for a specific chemical/active ingredient.
The product categories are: auto products, inside the
home, pesticides, landscape/yard, personal care, home
maintenance, arts and crafts, pet care, and home office.
The database  can be  searched by  product  name,
product type, manufacturer,  and ingredient.   This
database can be  found at  http ://hpd.nlm.nih. gov.
Table 17-1 provides a list of household consumer
products found in some U.S.  households (U.S. EPA,
1987).  It should be noted, however, that this list was
compiled by U.S. EPA in 1987 and consumer use of
some products listed may have changed (e.g., aerosol
product use has declined).  Therefore, the reader is
referred to the National Library of Medicine database
as a source of more current information.
        The U.S.  EPA Source Ranking Database
(SRD) is another source of information on consumer
products, but does not provide exposure factor data.
SRD can be used to perform systematic screening-level
reviews of more than 12,000 potential indoor pollution
sources to identify high-priority product and material
categories for further evaluation. It also can be used to
identify  products that contain a specific chemical.
Information on the SRD can be found at:
http://www.epa.gov/oppt/exposure/pubs/srd.htm.
        The Soaps and Detergents Association (SD A)
developed a peer-reviewed document that presents
methodologies and specific exposure information that
can be used for screening-level risk assessments from
exposures to high production volume chemicals.  The
document addresses the use  of consumer products,
including  laundry,   cleaning,  and  personal  care
products. It includes data for daily frequency of use,
and amount of product used.  The data used were
compiled from a number of sources including, the
Exposure  Factors  Handbook (U.S.  EPA,  1997),
cosmetic associations, and data from the SDA.  The
document entitled "Exposure and Risk Screening
Methods for Consumer Product Ingredients" can be
found on the SDA  website under:
http://www.clcaninglO 1 .com/filcs/Exposurc and
Risk Screening Methods for  Consumer Product
Ingrcdicnls.pdf.
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                                                      	Chapter 17 - Consumer Products
17.2    RECOMMENDATIONS
        Due to the large range and variation among
consumer products and their exposure pathways, it is
not feasible to recommend specific exposure values as
has been done in other chapters of this handbook.  The
user is  referred  to  the  contents/references  of this
chapter  and Chapter 17 of the  Exposure Factors
Handbook  (U.S.  EPA,  1997) to  derive appropriate
exposure factors.   The  following sections  of this
chapter  provide  summaries  of data from surveys
involving the use of consumer products.

17.3    CONSUMER PRODUCTS USE STUDIES
17.3.1   CTFA,  1983 -  Cosmetic,  Toiletry,  and
        Fragrance Association, Inc. - Summary of
        Results  of Surveys  of  the Amount  and
        Frequency of Use of Cosmetic Products by
        Women
        The  Cosmetic,  Toiletry,  and  Fragrance
Association Inc. (CTFA, 1983), a major manufacturer
and a market research bureau, conducted surveys to
obtain information on frequency of use of various
cosmetic products.  Three surveys were conducted to
collect data on the frequency of use  of various cosmetic
products and  selected baby products. In the first of
these three surveys CTFA (1983) conducted a one-
week prospective survey of 47 female employees and
relatives of employees between the ages of 13 and 61
years. In the second survey, a cosmetic manufacturer
conducted  a  retrospective survey of  1,129  of its
customers.  The third  survey was conducted by a
market research bureau which sampled 19,035 female
consumers nationwide over a 9-1/2 month period. Of
the 19,035 females interviewed, responses from only
9,684 females were tabulated (CTFA, 1983). The third
survey was designed to reflect the sociodemographic
(i.e., age, income, etc) characteristics of the entire U.S.
population. The respondents in all three surveys were
asked to record the number  of times they used the
various products in a given time period (i.e., a week, a
day, a month, or a year).
        To obtain the average frequency of use for
each cosmetic product, responses  were averaged for
each product in each survey.  Thus, the averages were
calculated by adding the reported number of uses per
given time  period for each product, dividing by the
total number of respondents in the survey, and then
dividing again by the number of days in the given time
 period (CTFA, 1983). The average frequency of use of
 cosmetic products was determined for both "users" and
 "non-users."  The frequency of use of baby products
 was determined among "users" only. The upper 90th
 percentile frequency of use values were determined by
 eliminating  the  top  ten  percent  most  extreme
 frequencies of use.  Therefore, the highest remaining
 frequency of use was recorded  as the  upper 90th
 percentile value.  Table 17-2  presents the amount of
 product used per application (grams) and the average
 and 90th percentile frequency of use per day for baby
 products and various cosmetic products for all the
 surveys.
         An advantage of the frequency data obtained
 from the third survey (market research bureau) is that
 the  sample population was more likely  to  be
 representative of the U.S.  population.    Another
 advantage of the third dataset is that the survey was
 conducted over a longer period of time when compared
 with the other two frequency datasets.  Also, the study
 provided empirical  data which will be useful in
 generating  more accurate estimates of consumer
 exposure to cosmetic products. In contrast to the large
 market research bureau survey, the CTFA employee
 survey  is very small  and both that survey and the
 cosmetic company survey are likely to be biased toward
 high end users. Therefore, data from these two surveys
 should  be used with caution.  While the  data in this
 study were not tabulated by age of the population, the
 study included some individuals in the age groups of
 interest for this handbook.

 17.3.2   U.S. EPA, 1996 - National Human Activity
         Pattern Survey (NHAPS)
         U.S. EPA  (1996) collected data on the
 duration and frequency of selected activities and the
 time spent in selected microenvironments via 24-hour
 diaries  as part of the National Human Activity Pattern
 Survey (NHAPS). More than 9,000 individuals from
 various age groups in 48 contiguous states participated
 inNHAPS.  Children represented approximately 2,000
 of the respondents (499 respondents under 5 years of
 age;  703 respondents between 5 and 11 years;  589
 respondents between 12  and 17 years;  and  799
 respondents between 18 and 24 years).  The survey was
 conducted between October 1992 and September 1994.
 Individuals were  interviewed to categorize their 24-
 hour routines (diaries) and/or to answer follow-up
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Chapter 17 - Consumer Products	
questions that were related to exposure events.  For
children under 10 years of age, adult members of the
households gave  proxy interviews.  Demographic,
including socioeconomic (gender, age, race, education,
etc.),  geographic (census region,  state,  etc.),  and
temporal (day of week, month, season)  data were
included in the  study.  Data were collected for a
maximum of 82  possible microenvironments and 91
different activities.
        As part of the survey, data were also collected
on duration and frequency of use of selected consumer
products. Tables 17-3 through 17-10 present data on
the number of minutes that survey respondents spent in
activities working with or being near certain consumer
products, including: freshly applied paints; household
cleaning agents such as scouring powders or ammonia;
floor wax, furniture wax, or shoe polish; glue; solvents,
fumes, or strong smelling chemicals; stain  or spot
removers;  gasoline, diesel-powered  equipment, or
automobiles; and pesticides, bug sprays, or bug strips.
These  data  are  presented according  to the  age
categories used in NHAPS (1 to 4 years, 5 tol 1 years,
12 to!7 years,  and 18 to 64 years). Table 17-11
through  17-15  present  data on  the number of
respondents  in  these  age  categories  that  used
fragrances, aerosol sprays, pesticides (professionally-
applied and  consumer-applied),  and  humidifiers.
Because the age categories used by the study authors
did not coincide with the standardized age categories
recommended in U. S. EPA (2005) and used elsewhere
in this handbook, the source  data from NHAPS on
pesticide use  (professionally applied and  consumer-
applied) were re-analyzed by  U.S.  EPA to generate
data for the standardized age categories.  These data
are presented in Tables 17-16 and 17-17 for age groups
less than 1  year,  1 to <2 years, 2 to <3 years, 3 to <6
years, 6 to <11 years, 11 to < 16 years, and 16 to <21
years.  Data for subsets of the first year of life (e.g., 1
to 2 months, 3 to 5 months, etc.) were not available.
        As discussed in previous chapters  of this
handbook that used NHAPS  as a data source, the
primary advantage of NHAPS is that the data were
collected for  a large number of individuals and the
survey was designed to be representative of the U.S.
general population.  However,  due to the wording of
questions in the survey, precise data were not available
for consumers who spent more than 60 or 120 minutes
(depending on the  activity) using some  consumer
products.  This prevents accurate characterization of
the high end of the distribution and may also introduce
error into the calculation of the mean.

17.3.3  Bass et al., 2001 - What's Being  Used at
        Home: A Household Pesticide Survey
        Bass et al. (2001) conducted a survey to assess
the use of pesticide products in homes with children in
March 1999.  The study obtained information on what
pesticides were used, where they were used,  and how
frequently they were used. A total of 107 households
in Arizona that had a least one  child less  than ten
years of age in the household, and had used a pesticide
within the last six months, were surveyed (Bass et al.,
2001).  The  survey population  was predominantly
female Hispanic and represented a survey response rate
of approximately 74 percent.  Study participants were
selected by systematic random sampling.  Among the
households sampled, 3 percent had one child  less than
10 years old, 42 percent had two children less than 10
years old, and 23 percent had three to five children in
this age bracket.  Pesticide use was assessed by a one-
on-one interview in the home.   Survey questions
pertained to household pesticides used inside the house
for insect control and outside the house for the control
of weeds in the garden and to  repel animals  from the
garden. As part of the interview, information was
gathered on the frequency of use.
        Table 17-18 presents information on the type,
characteristics, and frequency of pesticide use, as well
as information on the demographics of the survey
population.  A total  of 148 pesticide products were
used in the 107 households surveyed. Respondents had
used  pesticides  in  the  kitchen, bathroom, floors,
baseboards, and cabinets with dishes or cookware. The
frequency of use data showed the following: 13.5
percent of the households used pesticides more than
once per week; 18.2 percent used the products once per
week; 28.4 percent used the products once per month;
15.5 percent used the products once in three months;
10.8 percent used the products once in six months; and
8.8 percent used the products once per year (Bass et
al., 2001).
        Although this study was limited to a selected
area in Arizona, it provides useful information on the
frequency of use of pesticides among households with
children. This may be useful for populations in similar
geographical locations where site-specific data are not
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                                                       	Chapter 17 - Consumer Products
available.   However, these data are the result of a
community-based survey and are not representative of
the U.S. general population.

17.3.4  Loretz et al., 2005 - Exposure Data for
        Cosmetic Products: Lipstick, Body Lotion,
        and Face Cream
        Loretz et al. (2005) conducted a nationwide
survey to  estimate the  usage  (i.e.,  frequency of
application and  amount used per  application) of
lipstick, body lotion, and face cream.  The study was
conducted from April to June  2000.  Three hundred
and sixty  study subjects were recruited in ten U.S.
cities   (Atlanta,  Georgia;  Boston,  Massachusetts;
Chicago, Illinois; Denver, Colorado; Houston, Texas;
Minneapolis,  Minnesota; St.  Louis, Missouri;  San
Bernadino, California; Tampa, Florida; and Seattle,
Washington).  The survey participants were women,
ages 19-65 years, who regularly used the products of
interest.  Typical cosmetic formulations of the three
product types were weighed  and provided  to the
women for use over a two-week period.  Subjects
recorded information on product usage  (e.g., whether
the product was used, number of applications, time of
applications)  on a daily basis  in a diary provided to
them.  At the end of the two-week period, unused
portions of product were returned and weighed.  The
amount of product used was estimated as the difference
between the weight of product at the beginning and
end of the survey period. Of the 360 subjects recruited,
86.4percent, 83.3 percent, and 8 5.6 percent completed
the study and returned the diaries for  lipstick, body
lotion, and face  cream, respectively (Loretz et al.,
2005).
        The survey data are presented in Table 17-19
and 17-20.  Table 17-19 provides the mean, median,
and standard deviations  for the frequency of use.
Table 17-20  provides distribution data for the total
amount applied, the average amount applied per use
day, and the average amount applied per application.
        An advantage of this study is that the survey
population covered a diverse geographical area of the
U. S. and was not based on recall data. A limitation of
the study is that the short duration (two weeks) may
not accurately reflect  long-term  usage  patterns.
Another limitation is that  the study only included
women who already used the products; therefore, the
usage patterns are not representative  of the  entire
 female population. Also, the data are not presented by
 age group, but the study does provide information on
 a population that includes the ages of interest for this
 document.  Data for children could not be separated
 from that of the rest of the survey population.

 17.3.5   Loretz et al., 2006 - Exposure Data for
         Personal Care Products: Hairspray, Spray
         Perfume,  Liquid  Foundation, Shampoo,
         Body Wash, and Solid Antiperspirant
         Loretz  et al. (2006) conducted a nationwide
 survey to determine the usage (i.e., frequency of use
 and amount used) of hairspray,  spray perfume, liquid
 foundation,   shampoo,  body   wash,   and  solid
 antiperspirant.   The  survey was similar  to  that
 described by Loretz et  al. (2005).  This study was
 conducted between October 2001 and October 2002.
 A total of 360 women were recruited from ten  U.S.
 cities (Atlanta,  Georgia;  Boston,  Massachusetts;
 Chicago, Illinois; Denver, Colorado; Houston, Texas;
 Minneapolis, Minnesota; St. Louis, Missouri;  San
 Bernadino, California; Tampa, Florida; and Seattle,
 Washington). The survey participants were women,
 ages 19-65 years  old,  who regularly  used   the test
 products. Subjects kept daily records on product usage
 (whether the product was used, number of applications,
 time of applications) in a diary. For spray  perfume,
 liquid foundation, and body wash, subjects recorded
 the body area(s) where these products were applied.
 For shampoo, subjects recorded information on  their
 hair type (length, thickness, oiliness, straight or curly,
 and color treated or not).  At the end of the two week
 period, unused portions of products were returned and
 weighed.  Of the 360 subjects recruited per product,
 the  study  was  completed by  329 participants for
 hairspray,  327  for spray  perfume,  326 for liquid
 foundation, and  340 participants for shampoo, body
 wash, and solid antiperspirant.
         The survey data are presented in Tables 17-21
 through 17-23.  Table  17-21 provides the minimum,
 maximum, mean, and  standard deviations for the
 frequency  of use.  Table 17-22 provides percentile
 values  for  the  amount of product  applied  per
 application. Table 17-23 provides distribution data for
 the amount applied per use day.
         An advantage of this study is that the survey
 population covered a diverse geographical range of the
 U.S. and did not rely on recall data.  A limitation of
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17-4
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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
the study is that the short duration (two weeks) may
not  accurately reflect  long-term usage  patterns.
Another limitation is that the study only included
women who already used these products; therefore, the
usage patterns are not entirely representative of the
entire  female  population.   Also, the data are not
presented by age  group, but the  study does provide
information on a population that includes the ages of
interest for this document. Data for children could not
be  separated  from that of the  rest of the survey
population.

17.3.6   Loretz et al., 2008 - Exposure Data for
        Cosmetic Products: Facial  Cleanser, Hair
        Conditioner, and Eye Shadow
        Loretz et al. (2008) used the data from a study
conducted in January 2005 to estimate frequency of use
and usage amount for facial cleanser, hair conditioner,
and eye shadow. The study was conducted in a similar
manner as Loretz et al. (2005; 2006). A total of 360
women, ages 18 to 69 years of age, were recruited by
telephone to provide diary records of product use over
a  two-week period.    The  study  subjects  were
representative of four U.S. Census regions (Northeast,
Midwest, South, and West). A total of 295, 297, and
299 completed the  study  for  facial cleanser,  hair
conditioner, and eye shadow, respectively.
        The participants recorded daily in a diary
whether the product was used that day, the number of
applications, and the time of application(s) over a two-
week period. Products were weighed at the start and
completion of the study to determine the amount used.
A statistical analysis of the  data was conducted to
provide summary  distributions  of use  patterns,
including number of applications, amount used per
day, and amount of product used per application for
each product.  Data on the number of applications per
day are provided in Table  17-24.    The average
amounts of product applied per use day are shown in
Table  17-25,  and the average amounts of product
applied per application are  shown in Table 17-26.
        The advantages of this  study are that it is
representative of the U.S. female population for users
of the products studied, it provides data for frequency
of use and amount used,  and it  provides distribution
data.  The limitations of the study are that the data
were not provided by age group, but included ages in
the study group that are relevant for this handbook. In
addition, the participants were regular users of the
product, so the amount applied and the frequency of
use may be higher than for other individuals who may
use the products.  According to Loretz et al. (2008)
"variability in amount used by the different subjects is
high, but consistent with the data from other cosmetic
and personal care studies."  The authors also noted
that it was not clear if the high-end users of products
represented true usage.

17.3.7   Sathyanarayana et al., 2008 - Baby Care
        Products;  Possible   Sources  of  Infant
        Phthalate Exposure
        Sathyanarayana et al.  (2008) investigated
dermal  exposure  to phthalates via  the dermal
application of personal care products.  The study was
conducted on 163 infants born between the year 2000
and 2005. The products studied were baby lotion, baby
powder, baby shampoo, diaper cream, and baby wipes.
Infants were recruited through Future Families,  a
multicenter pregnancy cohort study, at prenatal clinics
in Los Angeles, California; Minneapolis, Minnesota;
and Columbia,  Missouri.  Although  the  study was
designed to assess exposure to phthalates, the authors
collected information on the percentage of the total
participants that used the baby products. Data were
collected from questionnaire responses of the mothers
and at study visits. The characteristics and the percent
of the population using the studied baby products are
shown in Table 17-27. Of the 163 infants studied, 94
percent  of the participants used baby wipes and 54
percent used infant shampoo.
        The advantages  of this  study  are that it
specifically  targeted  consumer  products  used  by
children.  The percent of the study population using
these  products  was captured  and the data were
collected from  a  diverse ethnic population.   The
limitations are that these data may not be entirely
representative of the U. S. population because the study
population was from only three states and the sample
size was small.

17.4     REFERENCES FOR CHAPTER 17
Bass, I; Ortega, L.; Resales, C.; Petersen, N., Philen,
        R. (2001)  What's being  used at home: a
        household  pesticide   survey. Pub Health
        9(3):138-144.
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September 2008	
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                                                      Child-Specific Exposure Factors Handbook

                                                     	Chapter 17 -  Consumer Products
Cosmetic,  Toiletry  and  Fragrance  Association
        (CTFA). (1983) Summary of the results of
        surveys of the amount and frequency of use of
        cosmetic products by women.  Prepared by
        Environ Corporation, Washington, DC for
        CTFA Inc., Washington, DC.
Franklin, P.  (2008)   Household  chemicals: good
        housekeeping  or occupational  hazard. Eur
        Respir 131:489-491.
Loretz, L.; Api, A.; Barraj, L.; Burdick, I; Dressier,
        W.; Gettings,  S.; Hsu, H.; Pan, Y.; Re, T.;
        Renskers, K.; Rothenstein, A.; Scrafford, C.;
        Sewall, C. (2005) Exposure data for cosmetic
        products:  lipstick,  body lotion,  and  face
        cream. Food Chem Toxicol 43:279-291.
Loretz, L.; Api, A.; Barraj, L.; Burdick, I; Davis, D.;
        Dressier, W.; Gilberti, E.; Jarrett, G.; Mann,
        S.; Pan, Y.; Re, T.; Renskers, K.; Scrafford,
        C.;  Vater, S. (2006)  Exposure  data  for
        personal care  products:  Hairspray,  spray
        perfume, liquid foundation, shampoo, body
        wash, and  solid antiperspirant. Food Chem
        Toxicol 44:2008-2018.
Loretz, L.; Api, A.; Babcock, L; Barraj, L.; Burdick,
        I;  Cater, K.; Jarrett, G.; Mann, s.; Pan, Y.;
        Re, T.; Renskers, K.; Scrafford,  C.  (2008)
        Exposure data for cosmetic products: Facial
        cleanser, hair  conditioner, and eye shadow.
        Food Chem Toxicol 46:1516-1524.
Sathyanarayana, S.; Karr, C.; Lozano, P., Brown, E.;
        Calafat, M. (2008)   Baby care products;
        possible sources of infant phthalate exposure.
        Pedriatrics 121:260-268.
Steenbekkers, L.P. (2001) Methods to study everyday
        use  of products   un   households:  The
        Wageningen  mouthing study.  Am Occup
        Hyg  45(1001): 125-129.
U.S. EPA (1987) Methods for assessing exposure to
        chemical substances - Volume 7 - Methods
        for assessing consumer exposure to chemical
        substances. Washington, DC: Office of Toxic
        Substances. EPA/560/5-85/007.
U.S. EPA (1996) Descriptive statistics tables from a
        detailed analysis  of the National Human
        Activity Pattern  Survey  (NHAPS)  data.
        Washington,  DC:  Office of Research and
        Development.  EPA/600/R-96/148.
 U.S. EPA (1997)  Exposure  Factors  Handbook.
         Washington, DC:   National  Center  for
         Environmental  Assessment,   Office  of
         Research  and  Development.  EPA/600/P-
         95/002FC.
 U.S. EPA. (2005) Guidance on Selecting Age Groups
         for Monitoring  and Assessing Childhood
         Exposures to Environmental Contaminants.
         U.S.  Environmental  Protection  Agency,
         Washington, DC: EPA/630/P-03/003F.
Page
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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-1. Consumer Products Commonly Found in Some U.S. Households"
Consumer Product Category
Cosmetics Hygiene Products
Household Furnishings
Garment Conditioning Products
Consumer Product
Adhesive bandages
Bath additives (liquid)
Bath additives (powder)
Cologne/perfume/aftershave
Contact lens solutions
Deodorant/antiperspirant (aerosol)
Deodorant/antiperspirant (wax and liquid)
Depilatories
Facial makeup
Fingernail cosmetics
Hair coloring/tinting products
Hair conditioning products
Hairsprays (aerosol)
Lip products
Mouthwash/breath freshener
Sanitary napkins and pads
Shampoo
Shaving creams (aerosols)
Skin creams (non-drug)
Skin oils (non-drug)
Soap (toilet bar)
Sunscreen/suntan products
Talc/body powder (non-drug)
Toothpaste
Waterless skin cleaners
Carpeting
Draperies/curtains
Rugs (area)
Shower curtains
Vinyl upholstery, furniture
Anti-static spray (aerosol)
Leather treatment (liquid and wax)
Shoe polish
Spray starch (aerosol)
Suede cleaner/polish (liquid and aerosol)
Textile water-proofing (aerosol)
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                                                                    Child-Specific Exposure Factors Handbook

                                                                   	Chapter 17 - Consumer Products
                         Table 17-1. Consumer Products Commonly Found in Some U.S. Households" (continued)
                    Consumer Product Category
                                                                 Consumer Product
  Household Maintenance Products
                                                                 Adhesive (general) (liquid)
                                                                 Bleach (household) (liquid)
                                                                 Bleach (see laundry)
                                                                 Candles
                                                                 Cat box litter
                                                                 Charcoal briquets
                                                                 Charcoal lighter fluid
                                                                 Drain cleaner (liquid and powder)
                                                                 Dishwasher detergent (powder)
                                                                 Dishwashing liquid
                                                                 Fabric dye (DIY)b
                                                                 Fabric rinse/softener (liquid)
                                                                 Fabric rinse/softener (powder)
                                                                 Fertilizer (garden) (liquid)
                                                                 Fertilizer (garden) (powder)
                                                                 Fire extinguishers (aerosol)
                                                                 Floor polish/wax (liquid)
                                                                 Food packaging and packaged food
                                                                 Furniture polish (liquid)
                                                                 Furniture polish (aerosol)
                                                                 General cleaner/disinfectant (liquid)
                                                                 General cleaner (powder)
                                                                 General cleaner/disinfectant (aerosol and pump)
                                                                 General spot/stain remover (liquid)
                                                                 General spot/stain remover (aerosol and pump)
                                                                 Herbicide (garden-patio) (liquid and aerosol)
                                                                 Insecticide (home and garden) (powder)
                                                                 Insecticide (home and garden) (aerosol and pump)
                                                                 Insect repellent (liquid and aerosol)
                                                                 Laundry detergent/bleach (liquid)
                                                                 Laundry detergent (powder)
                                                                 Laundry pre-wash/soak (powder)
                                                                 Laundry pre-wash/soak (liquid)
                                                                 Laundry pre-wash/soak (aerosol and pump)
                                                                 Lubricant oil (liquid)
                                                                 Lubricant (aerosol)
                                                                 Matches
                                                                 Metal polish
                                                                 Oven cleaner (aerosol)
                                                                 Pesticide (home) (solid)
                                                                 Pesticide (pet dip) (liquid)
                                                                 Pesticide (pet) (powder)
                                                                 Pesticide (pet) (aerosol)
                                                                 Pesticide (pet) (collar)
                                                                 Petroleum fuels (home (liquid and aerosol)
                                                                 Rug cleaner/shampoo (liquid and aerosol)
                                                                 Rug deodorizer/freshener (powder)
                                                                 Room deodorizer (solid)
                                                                 Room deodorizer (aerosol)
                                                                 Scouring pad
                                                                 Toilet bowl cleaner
                                                                 Toiler bowl deodorant (solid)
                                                                 Water-treating chemicals (swimming pools')	
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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
                         Table 17-1. Consumer Products Commonly Found in Some U.S. Households" (continued)
                   Consumer Product Category
                                                               Consumer Product
  Home Building/Improvement Products (DIY)b
Adhesives, specialty (liquid)
Ceiling tile
Caulks/sealers/fillers
Dry wall/wall board
Flooring (vinyl)
House Paint (interior) (liquid)
House Paint and Stain (exterior) (liquid)
Insulation (solid)
Insulation (foam)
Paint/varnish removers
Paint thinner/brush cleaners
Patching/ceiling plaster
Roofing
Refmishing products (polyurethane, varnishes, etc.)
Spray paints (home) (aerosol)
Wall paneling
Wall paper
Wall paper glue	
  Automobile-related Products
                                                               Antifreeze
                                                               Car polish/wax
                                                               Fuel/lubricant additives
                                                               Gasoline/diesel fuel
                                                               Interior upholstery/components, synthetic
                                                               Motor oil
                                                               Radiator flush/cleaner
                                                               Automotive touch-up paint (aerosol)
                                                               Windshield washer solvents
  Personal Materials
                                                               Clothes/shoes
                                                               Diapers/vinyl pants
                                                               Jewelry
                                                               Printed material (colorprint, newsprint, photographs)
                                                               Sheets/towels
                                                               Toys (intended to be placed in mouths)
           A subjective listing based on consumer use profiles.
           DIY = Do It Yourself.
  Source:   U.S. EPA, 1987.
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                                                      17-9

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products
Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products
Product Type
Baby Lotion - baby use0
Baby Lotion - adult use
Baby Oil - baby use0
Baby Oil - adult use
Baby Powder - baby use0
Baby Powder - adult use
Baby Cream - baby use0
Baby Cream - adult use
Baby Shampoo - baby use0
Baby Shampoo - adult use
Bath Oils
Bath Tablets
Bath Salts
Bubble Baths
Bath Capsules
Bath Crystals
Eyebrow Pencil
Eyeliner
Eye Shadow
Eye Lotion
Eye Makeup Remover
Mascara
Under Eye Cover
Blusher & Rouge
Face Powders
Foundations
Leg and Body Paints
Lipstick & Lip Gloss
Makeup Bases
Makeup Fixatives
Sunscreen
Colognes & Toilet Water
Perfumes
Amount of
Product Per
Application"
(grams)
1.4
1.0
1.3
5.0
0.8
0.8
-
-
0.5
5.0
14.7
-
18.9
11.8
-
-
-
-
-
-
-
-
-
0.011
0.085
0.265
-
-
0.13
-
3.18
0.65
0.23
Average Frequency of Use
(per day)

CTFA
0.38
0.22
0.14
0.06
5.36
0.13
0.43
0.07
0.14
0.02
0.08
0.003
0.006
0.088
0.018
0.006
0.27
0.42
0.69
0.094
0.29
0.79
0.79
1.18
0.35
0.46
0.003
1.73
0.24
0.052
0.003
0.68
0.29
Survey Type
Cosmetic
Co.
1.0
0.19
1.2
0.13
1.5
0.22
1.3
0.10
-
-
0.19
0.008
0.013
0.13
0.019
-
0.49
0.68
0.78
0.34
0.45
0.87
-
1.24
0.67
0.78
0.011
1.23
0.64
0.12
-
0.85
0.26

Marketb
Research
Bureau
-
0.24d
-
-
0.35d
-
-
-
O.llf
-
0.22s
-
-
-
-
-
-
0.27
0.40
-
-
0.46
-
0.55
0.33
0.47
-
2.62
-
-
0.002
0.56
0.38
Upper 90th Percentile Frequency of Use
(per day)

CTFA
0.57
0.86
0.14
0.29
8.43
0.57
0.43
0.14
0.14
0.86°
0.29
0.14e
0.14°
0.43
0.29°
0.29e
1.0
1.43
1.43
0.43
1.0
1.29
0.29
2.0
1.29
1.0
0.14°
4.0
0.86
0.14
0.14°
1.71
0.86
Survey Type
Cosmetic
Co.
2.0
1.0
3.0
0.57
3.0
1.0
3.0
0.14e
-
-
0.86
0.14e
0.14°
0.57
0.14°
0.14e
1.0
1.0
1.0
1.0
1.0
1.0
-
1.43
1.0
1.0
0.14°
2.86
1.0
1.0
-
1.43
1.0

Market
Research
Bureau
-
1.0d
-
-
1.0d
-
-
-
0.43f
-
l.O8
-
-
-
-
-
-
1.0
1.0
-
-
1.5
-
1.5
1.0
1.5
-
6.0
-
-
0.005
1.5
1.5
Page
17-10
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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table
Product Type
Powders
Sachets
Fragrance Lotion
Hair Conditioners
Hair Sprays
Hair Rinses
Shampoos
Tonics and Dressings
Wave Sets
Dentifrices
Mouthwashes
Breath Fresheners
Nail Basecoats
Cuticle Softeners
Nail Creams & Lotions
Nail Extenders
Nail Polish & Enamel
Nail Polish & Enamel
Remover
Nail Undercoats
Bath Soaps
Underarm Deodorants
Douches
Feminine Hygiene
Deodorants
Cleansing Products (cold
creams, cleansing lotions
liquids & pads)
Depilatories
Face, Body & Hand Preps
(excluding shaving preps)
Foot Powder & Sprays
Hormones
Moisturizers
Night Skin Care Products
17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products (ontinued)
Amount of
Product Per
Application"
(grams)
2.01
0.2
-
12.4
-
12.7
16.4
2.85
2.6
-
-
-
0.23
0.66
0.56
-
0.28
3.06
-
2.6
0.52
-
-
1.7
-
3.5
-
-
0.53
1.33
Average Frequency of Use
(per day)

CTFA
0.18
0.0061
0.0061
0.4
0.25
0.064
0.82
0.073
0.00311
1.62
0.42
0.052
0.052
0.040
0.070
0.003
0.16
0.088
0.049
1.53
1.01
0.013
0.021
0.63
0.0061
0.65
0.061
0.012
0.98
0.18
Survey Type
Cosmetic
Co.
0.39
0.034
-
0.40
0.55
0.18
0.59
0.021
0.040
0.67
0.62
0.43
0.13
0.10
0.14
0.013
0.20
0.19
0.12
0.95
0.80
0.089
0.084
0.80
0.051
-
0.079
0.028
0.88
0.50

Marketb
Research
Bureau
-
-
-
0.27
0.32
-
0.48
-
-
2.12
0.58
0.46
-
-
-
-
0.07
-
-
-
1.10
0.085
0.05
0.54
0.009
1.12
-
-
0.63
-
Upper 90th Percentile Frequency of Use
(per day)

CTFA
1.0
0.14e
0.29e
1.0
1.0
0.29
1.0
0.29
__h
2.6
1.86
0.14
0.29
0.14
0.29
0.14e
0.71
0.29
0.14
3.0
1.29
0.14e
1.0"
1.71
0.016
2.0
0.57e
0.57e
2.0
1.0
Survey Type
Cosmetic
Co.
1.0
0.14e
-
1.0
1.0
1.0
1.0
0.14e
0.14
2.0
1.14
1.0
0.29
0.29
0.43
0.14e
0.43
0.43
0.29
1.43
1.29
0.29
0.29
2.0
0.14
-
0.29
0.14e
1.71
1.0

Market
Research
Bureau
-
-
-
0.86
1.0
-
1.0
-
-
4.0
1.5
0.57
-
-
-
-
1.0
-
-
-
2.0
0.29
0.14
1.5
0.033
2.14
-
-
1.5
-
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September 2008	
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                                                                   Child-Specific Exposure Factors Handbook
                                                                  	Chapter 17 -  Consumer Products
                      Table 17-2.  Amount and Frequency of Use of Various Cosmetic and Baby Products (continued)
                                Amount of
                                Product Per
                                                    Average Frequency of Use
                                                   	(per day)	
                           Upper 90th Percentile Frequency of Use
                          	(per day)	
                                                         Survey Type
                                      Survey Type
rroauci lype , ,. ,. .
Application
(g)


CTFA


Cosmetic


Marketb
Research

Bureau
CTFA


Cosmetic


Market
Research

Bureau
  Paste Masks (mud packs)             3.7          0.027
  Skin Lighteners                     —            -
  Skin Fresheners & Astringents         2.0          0.33
  Wrinkle Smoothers (removers)        0.38         0.021
  Facial Cream                      0.55        0.0061
  Permanent Wave                    101          0.003
  Hair Straighteners                 0.156        0.0007
  Hair Dye                           -           0.001
  Hair Lighteners                     -          0.0003
  Hair Bleaches                       -          0.0005
  Hair Tints                          -          0.0001
  Hair Rinse (coloring)                 -          0.0004
  Shampoo (coloring)                  -          0.0005
  Hair Color Spray                    —            -
  Shave Cream	1.73	-
 0.20
0.024
 0.56
 0.15
             0.001

             0.005
 0.14
  _d
  1.0
  1.0d
0.0061
0.0082
0.005d
0.004d
0.005d
 0.02d
0.005d
 0.02d
 0.02d
0.43
0.14d
1.43
 1.0
             0.005

             0.014
             0.082
                                                         0.36
           Values reported are the averages of the responses reported by the twenty companies interviewed.
           (—'s) indicate no data available.
           The averages shown for the Market Research Bureau are not true averages - this is due to the fact that in many cases the class of most
           frequent users were indicated by "1 or more" also ranges were used in many cases, i.e., "10-12." The average, therefore, is
           underestimated slightly. The " 1 or more" designation also skew the 90th percentile figures in many instances. The 90th percentile
           values may, in actuality, be somewhat higher for many products.
           Average usage among users only for baby products.
           Usage data reflected "entire household" use for both baby lotion and baby oil.
           Fewer than 10% of individuals surveyed used these products.  Value listed is lowest frequency among individuals reporting usage.  In
           the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during the
           period of the study.
           Usage data reflected "entire household" use.
           Usage data reflected total bath product usage.
           None of the individuals surveyed reported using this product.
  Source:    CTFA, 1983.
Page
17-12
        Child-Specific Exposure Factors Handbook
       	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-3. Number of Minutes Spent in Activities Working With or Near Freshly Applied Paints
(minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years

N
7
12
20
212

1
3
5
0
0

2
3
5
0
0

5
3
5
0.5
1

10
3
15
3
2

25
5
20
8
11
Percentiles
50 75
15 121
45 120
45 75
60 121

90 95
121 121
120 121
121 121
121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.

98
121
121
121
121
N =

99
121
121
121
121
doer sample

100
121
121
121
121
size;
Table 17-4. Number of Minutes Spent in Activities Working With or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/dav)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Percentiles
N
21
26
41
672
1
0
1
0
0
2
0
1
0
0
5 10
0 0
2 2
0 0
1 2
25
5
3
2
5
50
10
5
5
10
75
15
15
10
20
90 95
20 30
30 30
40 60
60 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
30
60
121
99
121
30
60
121
100
121
30
60
121
N = doer sample size;
Table
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
17-5. Number of Minutes Spent in Activities (at home or elsewhere) Working With
or Near Floorwax, Furniture Wax or Shoe Polish (minutes/dav)

N
13
21
15
238

1
0
0
0
0

2
0
0
0
0

5
0
2
0
2

10
5
2
1
3

25
10
3
2
5
Percentiles
50 75 90
15 20 60
5 10 35
10 25 45
15 30 120

95
121
60
121
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.

98
121
120
121
121

99
121
120
121
121
N = doer sample

100
121
120
121
121
size;
Child-Specific Exposure Factors Handbook
September 2008	
Page
17-13

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J*^ Child-Specific Exposure Factors Handbook
J&^ Chapter 17 - Consumer Products



Table 17-6.








Number of Minutes Spent in Activities Working With or Near Glue (minutes/dav)
Percentiles

1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
N
6
36
34
207
1
0
2
0
0
2
0
2
0
0
5
0
3
1
0
10 25
0 30
5 5
2 5
1 5
50
75 90 95 98
30 30 50 50 50
12.5 25 30 60 120
10 30 30 60 120
20 90 121 121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; N =
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
99
50
120
120
121
100
50
120
120
121
doer sample size;

Table 17-7. Number of Minutes Spent in Activities Working With or Near Solvents,
(minutes/day)
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years

N
7
16
38
407

1
0
0
0
0

2
0
0
0
0

5
0
0
0
1

10
0
2
0
2

25
1
5
5
5
Percentiles
50 75
5 60
5 17.5
10 60
30 121
Fumes or Strong Smelling Chemicals

90 95
121 121
45 70
121 121
121 121
Note: A Value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.

98
121
70
121
121

99
121
70
121
121

100
121
70
121
121
N = doer sample size;
Table 17-8. Number of Minutes Spent in

N
1 to 4 years 3
5 to 1 1 years 3
12 to 17 years 7
18 to 64 years 87

1
0
3
0
0

2
0
3
0
0
Activities Working With or Near Stain or Spot Removers (minutes/dav)

5
0
3
0
0

10
0
3
0
0

25
0
3
5
2
Percentiles
50 75
0 3
5 5
15 35
5 15

90
3
5
60
60

95
3
5
60
121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.

98
3
5
60
121
N =

99
3
5
60
121
doer sample

100
3
5
60
121
size;
Page
17-14
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-9. Number of Minutes Spent in Activities Working With or Near Gasoline or
Diesel-powered Equipment, Besides Automobiles (minutes/day)


1 to 4 years 14
5 to 11 years 12
12 to 17 years 25
18to64years 312
Percentiles
1
0
1
2
0
2
0
1
2
0
5
0
1
5
1
10
1
3
5
3
25
5
7.5
13
15
50
22.5
25
35
60
75
120
50
120
121
90 95
121 121
60 60
121 121
121 121
Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent;
percentiles are the percentage of doers below or equal to a given number of minutes.
Source: U.S. EPA, 1996.
98
121
60
121
121
99
121
60
121
121
N = doer sample
100
121
60
121
121
size;
                       Table 17-10. Number of Minutes Spent in Activities Working With or Near Pesticides,
                      	Including Bug Sprays or Bug Strips (minutes/day)	
         Age Group
                                                              Percentiles
                             N
                                   1
                                                    10
                                                         25
                                                               50
                                                                    75
                                                                          90
                                                                               95
                                                                                          99   100
          1 to 4 years
          5 to 11 years
          12 to 17 years
          18 to 64 years
 6     1
 16     0
 10     0
190     0
 3
1.5
 2
10
7.5
2.5
10
15
30
40
20
121
121
121
20
121
121
121
20
121
121
121
20
121
121
121
20
121
121
121
         Note:     A value of "121" for number of minutes signifies that more than 120 minutes were spent; N = doer sample size;
                  percentiles are the percentage of doers below or equal to a given number of minutes.

         Source:   U.S. EPA, 1996.
Table 17-1 1. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies
Age Group
5 to 1 1 years
12 to 17 years
18 to 64 years
Number of Times Used in a Dav
Total N
26
144
1,735
1-2
24
133
1,635
3-5
2
9
93
6-9
*
*
3
10+ Don't Know
* *
1 1
1 3
* = Missing Data.
N = Number of respondents.
Source: U.S. EPA, 1996.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                          Page
                                                                         17-15

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products

Age Or
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Table 17-12.

OUP Total N
40
75
103
1,071
dumber of Respondents Using Any Aerosol Spray Product for Personal Care Item
Such as Deodorant or Hair Spray at Specified Daily Frequencies
Number of Times Used
1
30
57
53
724
2
9
14
31
263
3
0
1
12
39
4 5
0 1
1 1
4 1
15 13
6
0
1
0
1
in a Dav
7
0
0
0
1

10
0
0
1
2

10+
0
0
1
8

Don't Know
0
0
0
5
N = Number of respondents..
Source: U.S. EPA. 1996.
Table 17-13. Number of Respondents Using a Humidifier at Home
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
Total N
111
88
83
629

Almost
Every
Day
33
18
21
183

3-5 Times a
Week
16
10
7
77
Frequency
1-2 Times a
Week
7
12
5
70

1-2 Times a
Month
53
46
49
287

Don't
Know
2
2
1
12
N = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-14. Number of Respondents Indicating that Pesticides Were Applied bythe Professional at Home
to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
18 to 64 years
Total N
113
150
143
1,264
Number of Times Over a 6-month Period
Pesticides Were Applied bv Professionals
None
60
84
90
660
1-2
35
37
40
387
3-5
11
10
5
89
6-9
6
18
6
97
10+
1
1
*
15
Don't Know
*
*
2
16
* = Missing data.
N = Number of respondents.
Source: U.S. EPA, 1996.
Page
17-16
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-15. Number of Respondents Reporting Pesticides Applied bythe Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group
1 to 4 years
5 to 1 1 years
12 to 17 years
1 8 to 64 years
Total N .

113
150
143
1,264
Number of Times Over a 6-month
Period Pesticides Applied bv Resident
None
46
50
45
473
1-2
46
70
64
477
3-5
15
24
21
192
6-9
3
1
5
48
10+
3
4
8
55
Don't Know
*
1
*
19
Note: * = Missing Data
N = Number of respondents.
Source: U.S. EPA, 1996.
Table 17-16. Number of Respondents Indicating that Pesticides Were Applied by a
Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group Total N
0 to <1 years
Ito <2 years
2 to <3 years
3 to <6 years
6 to <11 years
11 to <16 years
16to<21years
15
23
32
80
106
115
87
Frequency
(number of times over a six-month period that pesticides were applied by a professional)
None
9
13
9
51
59
68
40
Ito 2
4
5
15
22
22
35
36
3 to 5
1
3
5
5
7
4
2
6 to 9
1
1
3
2
17
6
5
10+
0
1
0
0
1
0
1
Don't Know
0
0
0
0
0
2
3
N = Number of respondents.
Source: U.S. EPA re-analysis of NHAPS (U.S. EPA, 1996) data.
Table 17-17. Number of Respondents Reporting Pesticides Applied bythe Consumer at Home to
Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
Age Group Total N

0 to
-------
                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products
Table 17-18. Household Demographics, and Pesticide Types, Characteristics, and Frequency of Pesticide Use
Survey Population Demographics

Gender
female
male
Language of Interview
Spanish
English
Reading Skills
able to read English
able to read Spanish
Number in household
2-3 people
4-5 people
6-8 people
Children under 10 years
1 child
2 children
3 to 5 children
Type of home
single family detached
multi-family
trailer/mobile home
single-family attached
apartment/other
Pets
pets kept in household
pesticides used on pets
Number"

90
17

72
35

71
95

25
59
23

37
45
25

75
9
9
8
4

55
22
Percent"
84.1
15.9

67.3
32.7

66.4
88.8

23.3
55.1
21.4

34.6
42.1
23.3

70.1
8.4
8.4
7.5
3.7

51.4
40.0

Pesticide Use
Type of pesticide
insecticide
rodenticide
herbicide
Storage of pesticide
kitchen
garage/shed
laundry/washroom
other, inside home
other, outside home
bathroom
basement
closet
Storage precautions
child-resistant container
pesticide locked away
Storage risks
< 4 feet from ground
kept near food
kept near dishes/cookware
Disposal
throw it away
wrap in separate container, throw
away
other
Frequency of use
more than once/week
once/week
once/month
once every 3 months
once every 6 months
once/year
Time stored in home
< 6 months
6 to 12 months
12 to 24 months
> 24 months
a Totals may not add to 107 participants or
Source: Bass et al., 2001.


135
10
3
£.1
O /
30
1 A
H-
•7
/
7


00
oJ
55
72
5
5

132
10
5
20

27
42
01
ZJ
16
1 1
LJ
75
O/1
Z4
17
16


91.2
6.8
2.0
AS 0
^tj. J
20.3
Q A
y .*+
H A
/.•4-
A 7
4-. /
4.7
1 H
Z. /
1 H
Z. /
c/r 1
JO. 1
37.2
48.6
3.4
3 4

89.2
6.8
3.4
13 5

18.2
28.4
ICC
1 J. J
10.8
80
.0
50.7
ico
1 J.Z
11.5
10.8
148 products, and percentages may not add to 100 due to some non-responses to survey questions.


Page
17-18
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-19
Product Type
Lipstick
Body lotion, hands
Body lotion, arms
Body lotion, feet
Body lotion, legs
Body lotion, neck & throat
Body lotion, back
Body lotion, other
Face cream
N = Number of subjects (women,
SD = Standard deviation.
Source: Loretz et al., 2005.
. Frequency of Use of Cosmetic Products
N -
311
308
308
308
308
308
308
308
300
ages 19 to 65

Number of Applications per Da\
Mean Median
2.35 2
2.12 2
1.52 1
0.95 1
1.11 1
0.43 0
0.26 0
0.40 0
1.77 2
years).


SD
1.80
1.59
1.30
1.01
0.98
0.82
0.63
0.76
1.16


Child-Specific Exposure Factors Handbook                                       Page
September 2008	17-19

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products
Table 17-20.
Summary Statistics
Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream
Total Amount Applied
Average" Amount Applied per
Use Day
Average11 Amount Applied
per Application
Lipstick
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
99th
Best Fit Distributions &
Parameters0


0.001
2.666
0.272
0.408

0.026
0.063
0.082
0.110
0.147
0.186
0.242
0.326
0.655
0.986
2.427
Lognormal Distribution
GM = 0.14
GSD = 3.56
P- value (Gof) = 0.01
0.000
0.214
0.024
0.034

0.003
0.005
0.008
0.010
0.013
0.016
0.021
0.029
0.055
0.087
0.191
Lognormal Distribution
GM= 0.01
GSD = 3.45
P-value(Gof) <0.01
0.000
0.214
0.010
0.018

0.001
0.003
0.004
0.004
0.005
0.006
0.009
0.011
0.024
0.037
0.089
Lognormal Distribution
GM = 0.01
GSD = 3.29
P- value (Gof) <0.01
Body Lotion
Minimum
Maximum
Mean
SD
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
0.67
217.66
103.21
53.40

36.74
51.99
68.43
82.75
96.41
110.85
134.20
160.26
0.05
36.31
8.69
5.09

3.33
4.68
5.71
6.74
7.63
9.25
10.90
12.36
0.05
36.31
4.42
4.19

1.30
1.73
2.32
2.76
3.45
4.22
4.93
6.14
Page
17-20
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Chapter 17 - Consumer Products	
                  Table 17-20. Amount of Test Product Used (grams) for Lipstick, Body Lotion and Face Cream (continued)
   Summary Statistics
     Total Amount Applied
 Average" Amount Applied per
          Use Day
 Average11 Amount Applied
     per Application
            90th
            95th
            99th
   Best Fit Distributions &
   Parameters0
           182.67
           190.13
           208.50
Beta Distribution0
Alpha = 1.53
Beta =1.77
Scale = 222.01
P-value (GoF) = 0.06
           14.39
           16.83
           27.91
Gamma Distribution
Location = -0.86
Scale = 2.53
Shape = 3.77
P-value (GoF) = 0.37
         8.05
         10.22
         21.71
Lognormal Distribution
GM = 3.26
GSD = 2.25
P-value (GoF) = 0.63
                                                       Face Cream
   Minimum
   Maximum
   Mean
   SD
   Percentiles
            10th
            20th
            30th
            40th
            50th
            60th
            70th
            80th
            90th
            95th
            99th
   Best Fit Distributions &
   Parameters0
            0.04
            55.85
            22.36
            14.01

            5.75
            9.35
            12.83
            16.15
            19.86
            23.79
            29.31
            36.12
            44.58
            48.89
            51.29
Triangle Distribution
Minimum = -1.09
Maximum = 58.71
Likeliest = 7.53
P-value (GoF) = 0.27
            0.00
           42.01
            2.05
            2.90

            0.47
            0.70
            1.03
            1.26
            1.53
            1.88
            2.23
            2.90
            3.50
            3.99
           12.54
Lognormal Distribution0
GM= 1.39
GSD = 2.58
P-value (GoF) <0.01
         0.00
         21.01
         1.22
         1.76

         0.28
         0.40
         0.53
         0.67
         0.84
         1.04
         1.22
         1.55
         2.11
         2.97
         10.44
Lognormal Distribution0
GM = 0.80
GSD = 2.55
P-value (GoF) = 0.02
   '         Derived as the ratio of the total amount used to the number of use days.
   b         Derived as the ratio of the total amount used to the total number of applications during the survey.
   0         None of the tested distributions provided a good fit.
   GM      = Geometric mean.
   GSD     = Geometric standard deviation.
   Gof      = Goodness of fit.
   Note:     Data are for women, ages 19 to 65 years.
   Source:   Loretz et al., 2005.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                Page
                                                                               17-21

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products
Table 17-21. Frequency of Use of Personal Care Products
Product Type
Hairspray (aerosol)
Hairspray (pump)
Liquid Foundation
Spray Perfume
Body wash
Shampoo
Solid antiperspirant
Averag
N Mean
165b 1.49
162 1.51
326 1.24
326 1.67
340 1.37
340 1.11
340 1.30
>e Number of Applications per Use Day"
SD
0.63
0.64
0.32
1.10
0.58
0.24
0.40
Min
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Max
5.36
4.22
2.00
11.64
6.36
2.14
4.00
* Derived as the ratio of the number of applications to the number of use days.
b Subjects who completed the study but did not report their number of applications were excluded.
N = Number of subjects (women, ages 18 to 65 years).
SD = Standard deviation.
Source: Loretz et al., 2006.
Page
17-22
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook




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Child-Specific Exposure Factors Handbook Page
September 2008 17-23

-------
                                              Child-Specific Exposure Factors Handbook



                                              	Chapter 17 - Consumer Products
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17-24
                                          Child-Specific Exposure Factors Handbook

                                         	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
Table 17-24. Average Number of Applications Per Use Day"
Summary Statistics Facial Cleanser
(Lathering and Non-Lathering)
N
Mean
SD
Minimum
Maximum
Percentiles
10th
20th
30th
40th
50th
60th
70th
80th
90th
95th
97.5th
99thb
295
1.6
0.52
1.0
3.2

1.0
1.0
1.2
1.4
1.7
1.9
2.0
2.0
2.2
2.4
2.9b
3.1b
a Derived as the ratio of the number of applications to the number of use days.
b Estimate does not meet the minimum sample size criteria (n=800) as set by the N
(>0.75), the minimum sample size (n) satisfies the following rule: n [8/(l-p.]
htip:.|l.|l\\ww/cdc.|ljzov.|lnchs.|lab()ut/'maior/nhancs.i'nhanes3/nh3jzu].pdj..
N = Number of subjects (women, ages 1 8 to 69 years).
SD = Standard deviation.
Source: Loretz et al., 2008.


Hair Conditioner
297
1.1
0.19
1.0
2.4

1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.1
1.2
1.4
1.8b
2.1b
itional Center for Health Statistics.

Eye Shadow
299
1.2
0.33
1.0
2.7

1.0
1.0
1.0
1.1
1.1
1.1
1.2
1.4
1.7
2.0
2.2b
2.5b
For upper percentile

Child-Specific Exposure Factors Handbook
September 2008	
Page
17-25

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                                                                   Child-Specific Exposure Factors Handbook

                                                                  	Chapter 17 - Consumer Products
                                Table 17-25.  Average Amount of Product Applied Per Use Day (grams)"
  Summary Statistics
   Facial Cleanser
 (Lathering and Non-
     Lathering)
Facial Cleanser
  (Lathering)
Facial Cleanser (Non-
     Lathering)
                                                                                       Hair Conditioner
Eye shadow
  N
  Mean
  SD
  Minimum
  Maximum
  Percentiles
           10th
           20th
           30th
           40th
           50th
           60th
           70th
           80th
           90th
           95th
           97.5th
           99thb

  Best fit distributions
  and parameters
  P-value
  (Chi-square test)
        295
        4.06
        2.78
        0.33
       16.70

        1.41
        1.79
        2.18
        2.66
        3.25
        3.86
        4.62
        6.24
        8.28
        9.93
       10.71b
       12.44b

Lognormal
distribution

     GM = 3.26
    GSD=1.12
      0.1251
     174
     4.07
     2.87
     0.33
    15.32

     1.23
     1.72
     2.15
     2.64
     3.19
     3.84
     4.71
     6.33
     8.24
    10.50
    11.47b
    13.07b

  Lognormal
  distribution

  GM = 3.21
 GSD = 2.03
    0.4429
    121
   4.05
   2.67
   0.83
   16.70

   1.50
   1.94
   2.22
   2.80
   3.33
   3.88
   4.59
   5.92
   8.40
   9.37b
   10.26b
   15.29b

Lognormal
distribution

GM = 3.35
GSD =1.86
  0.4064
                            297
                            13.77
                            11.50
                            0.84
                            87.86

                            3.71
                            5.54
                            6.95
                            8.73
                            10.62
                            12.61
                            15.54
                            20.63
                            28.20
                            33.19
                           45.68b
                           60.20b

                         Lognormal
                         distribution

                         GM= 10.28
                         GSD-2.20
                           0.8595
   299
   0.04
   0.11
   0.001
   0.74

   0.003
   0.005
   0.007
   0.009
   0.010
   0.013
   0.017
   0.025
   0.052
   0.096
   0.525b
   0.673b

Lognormal
distribution

GM = 0.01
GSD = 3.61
  <0.0001
  a         Derived as the ratio of the total amount used to the number of use days.
  b         Estimate does not meet the minimum sample size criteria (n=800) as set by the National Center for Health Statistics. For upper percentile (>0.75),
          the minimum sample size (n) satisfies the following rule: n [8/(l-p)]. h_1lpj_^;w^gd£:goWn_ch_s/ab^
  N        = Number of subjects (women, ages 18 to 69 years).
  GM      = Geometric mean.
  GSD      = Geometric standard deviation.

  Source:    Loretz et al., 2008.
Page
17-26
                                            Child-Specific Exposure Factors Handbook
                                           	September 2008

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Child-Specific Exposure Factors Handbook

Chapter 17 - Consumer Products	
                               Table 17-26.  Average Amount of Product Applied Per Application (grams)"
       Summary Statistics
    Facial Cleanser
  (Lathering and Non-
      Lathering)
   Facial
  Cleanser
(Lathering)
Facial Cleanser
    (Non-
  Lathering)
                                                                                       Hair Conditioner
                                                                                                             Eye Shadow
  N
  Mean
  SD
  Minimum
  Maximum
  Percentiles
            10th
            20th
            30th
            40th
            50th
            60th
            70th
            80th
            90th
            95th
            97.5th
            99thb

  Best fit distributions and
  parameters
  P- value (Chi-square test)
         295
         2.57
         1.78
         0.33
        14.61

         0.92
         1.32
         1.57
         1.85
         2.11
         2.50
         2.94
         3.47
         4.81
         5.89
        7.16b
        9.44b

Extreme value

Mode =  1.86
Scale = 1.12
0.0464
    174
   2.56
   1.78
   0.33
   10.67

   0.83
   1.26
   1.55
   1.84
   2.11
   2.50
   2.96
   3.56
   5.10
   6.37
   7.77b
   9.61b

  Gamma

 Loc = 0.28
Scale =1.29
  0.6123
     121
     2.58
     1.77
     0.57
    14.61

     1.10
     1.35
     1.59
     1.89
     2.15
     2.51
     2.96
     3.40
     4.52
    5.11b
    6.29b
    15.46b

Extreme value

 Mode = 1.92
 Scale =1.03
    0.5219
    297
   13.13
   11.22
   0.84
   87.86

   3.48
   5.34
   6.71
   8.26
   10.21
   12.24
   14.54
   18.88
   27.32
   32.43
   45.68b
   60.20b

Lognormal
distribution

GM = 9.78
GSD = 2.20
  0.9501
    299
   0.03
   0.10
  0.0004
   0.69

   0.003
   0.004
   0.006
   0.007
   0.009
   0.011
   0.015
   0.022
   0.041
   0.096
  0.488b
  0.562b

Lognormal
distribution

GM = 0.01
GSD = 3.59
  <0.0001
  a         Derived as the ratio of the total amount used to the total number of applications.
  b         Estimate does not meet the minimum sample size criteria (n=800) as set by the National Center for Health Statistics. For upper percentile (>0.75), the
            minimum sample size (n) satisfies the following rule: n [8/(l-p)]. Http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf.
  N        = Number of subjects (women, ages 18 to 69 years).
  GM       = Geometric mean.
  SD       = Geometric standard deviation.

  Source:    Loretz et al., 2008.
Child-Specific Exposure Factors Handbook
September 2008	
                                                                                         Page
                                                                                        17-27

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                                           Child-Specific Exposure Factors Handbook

                                           	Chapter 17 - Consumer Products
Table 17-27. Characteristics of the Study Population and the Percent
Characteristic
Number of Participants
Los Angeles, California
Minneapolis, Minnesota
Columbia, Missouri
Gender
Male
Female
Age (months)
2-8
9-16
17-24
24-28
Infant Weight (kg)
•10
>10
Race
White
Hispanic/Latino
Native American
Asian
Black
Product Use
Baby Lotion
Baby Shampoo
Baby Powder
Diaper Cream
Baby Wipes
Using Selected Baby Care Products
Sample Number (percent)

43 (26)
77(47)
43 (26)

84 (52)
79 (48)

42 (26)
82 (50)
30(18)
9(6)

84 (52)
79 (48)

131(80)
17(10)
3(2)
8(5)
4(3)
Percent Using
36
54
14
33
94
Source: Sathyanarayana et al., 2008.
Page
17-28
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook

Glossary
                               GLOSSARY OF TERMS
Child-Specific Exposure Factors Handbook                                       Page
September 2008	G-l

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                                                       Child-Specific Exposure Factors Handbook
                                                                                             Glossary
Activity  pattern data  - Information on  human
activities used in exposure assessments. These may
include a description of the activity,  frequency of
activity, duration spent performing the activity, and the
microenvironment in which the activity occurs.

Adherence factor - The amount of a material (e.g.,
soil) that adheres to the skin per unit of surface area.

Activity  pattern (time use)  data - Information on
activities in which various individuals engage, length
of time spent performing various activities, locations in
which individuals spend time and length of time spent
by individuals within those various environments.

Agricultural commodity - Used by U. S. EPA to mean
plant (or animal) parts consumed by humans as food.
When  such items are  raw or unprocessed, they are
referred to as  "raw agricultural commodities."

All water sources - Includes water from all  supply
sources such  as  community water supply (i.e., tap
water), bottled water, etc.

Analytical uncertainty  propagation  - Examining
how uncertainty  in individual parameters affects the
overall uncertainty of the exposure  assessment.

Anthropometric -  The  study  of  human body
measurements for use in anthropological classification
and comparison.

As-consumed intake - Intake rate based on the weight
of the  food in the form that it is consumed (e.g.,
cooked or prepared).

Assessment -  A determination or appraisal of possible
consequences  resulting from an analysis of data.

Average Daily Dose (ADD) - Dose rate averaged over
a pathway-specific period of exposure expressed as a
daily dose on a per-unit-body-weight basis. The ADD
is  used for   exposure   to  chemicals  with
non-carcinogenic non-chronic  effects.  The ADD is
 usually expressed in terms of mg/kg-day  or other
 mass/mass-time units.

 Benchmark Dose (BMD) or Concentration (BMC) -
 A dose or concentration that produces a predetermined
 change in response rate of an adverse effect (called the
 benchmark  response  or  BMR)  compared  to
 background.

 Best Tracer Method (BTM) - Method for estimating
 soil ingestion that allows for the selection of the most
 recoverable tracer for a particular subject or group of
 subjects. Selection of the best tracer is made on the
 basis of the food/soil (F/S) ratio.

 Bias - A systematic error inherent in a method or
 caused by some feature of the measurement system.

 Bioavailability - The rate and  extent to which an
 agent can be absorbed by an organism and is available
 for  metabolism or  interaction with  biologically
 significant  receptors. Bioavailability  involves both
 release from a medium (if present) and absorption by
 an organism.

 Biomarker model comparison - A methodology that
 compares results from a biokinetic exposure  model to
 biomarker measurements children blood. The method
 is used to confirm assumptions about ingested soil and
 dust quantities  in this handbook.

 Basal Metabolic Rate  (BMR) - Minimum level of
 energy required to maintain normal body functions.

 Body Mass Index (BMI) - The ratio of weight and
 height squared.

 Bootstrap - A statistical method of resampling data
 use  to estimate variance and bias of an estimator and
 provide confidence intervals for parameters.

 Bounding estimate - An estimate of exposure, dose, or
 risk that is  higher or lower than  that incurred by the
 person with the highest or lowest exposure, dose, or
 risk in  the population  being  assessed. Bounding
Page
G-2
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Glossary
estimates are useful  in  developing  statements that
exposures, doses,  or risks are "not greater than"  or
"less than" the estimated value, because assumptions
are used which define the likely bounding conditions.

Central tendency exposure - A measure of the middle
or the center of an exposure distribution. The mean is
the most commonly used measure of central tendency.

Chronic exposure - Repeated exposure by the oral,
dermal,  or  inhalation  route   for  more  than
approximately 10% of the life span in humans  (more
than approximately 90 days to 2 years in typically used
laboratory animal  species).

Chronic intake -  The long term period over which a
substance crosses the outer boundary of an organism
without passing an absorption barrier.

Classical  statistical  methods  - Estimating the
population exposure  distribution directly, based  on
measured values from a representative sample.

Coating - Method used to measure skin surface area,
in which either the whole body or specific body regions
are coated with a substance of known density and
thickness.

Community water - Includes tap water  ingested from
community or municipal water supply.

Comparability - The ability to describe likenesses and
differences in the quality and relevance of two or more
data sets.

Concentration  -  Amount of  a  material  or  agent
dissolved or  contained in unit quantity  in a  given
medium or system.

Confidence intervals - An estimated range of values
with a given  probability of including the population
parameter of interest. The range of values is usually
based on the results of a sample that  estimated the
mean and the sampling error or standard error.
Consumer-only intake rate - The average quantity of
food consumed per person in a population composed
only of individuals who ate the food item of interest
during a specified period.

Contaminant  concentration   -   Contaminant
concentration is the concentration of the contaminant
in the medium (air, food, soil, etc.) contacting the body
and has units of mass/volume or mass/mass.

Creel  study - A study in  which fishermen  are
interviewed while fishing.

Cumulative exposure -  Exposure via mixtures of
contaminants both indoors and outdoors.  Exposure
may also occur through more than one pathway. New
directions in risk assessments in U.S. EPA put more
emphasis on total exposures via multiple pathways.

Deposition -  The removal of airborne  substances to
available  surfaces  that  occurs  as  a  result  of
gravitational  settling and  diffusion,  as  well  as
electrophoresis and thermophoresis.

Dermal absorption - A route of exposure by which
substances can enter the body through the skin.

Dermal adherence -  The loading of a substance onto
the outer  surface of the skin.

Diary study - Survey in which individuals are asked to
record food intake, activities, or other factors in a diary
which  is later  used to  evaluate exposure  factors
associated with specific populations.

Direct water ingestion - Consumption of plain water
as a beverage.  It does  not include water used for
preparing beverages such as coffee or tea.

Distribution - A set of values derived from a specific
population or set of measurements that represents the
range and array of data for the factor being studied.

Doers - Survey respondents who report participating in
a specified activity.
Child-Specific Exposure Factors Handbook
September 2008	
                                          Page
                                           G-3

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                                                       Child-Specific Exposure Factors Handbook
                                                                                              Glossary
Dose  -  The  amount  of  a substance  available for
interaction with metabolic processes or biologically
significant receptors after crossing the outer boundary
of an organism. The  potential  dose is the amount
ingested, inhaled, or applied to the skin. The applied
dose is the amount of a  substance presented  to an
absorption barrier  and  available  for  absorption
(although not necessarily having yet crossed the outer
boundary of the organism).  The  absorbed dose is the
amount crossing a specific absorption barrier (e.g., the
exchange boundaries of skin, lung, and digestive tract)
through  uptake processes.  Internal dose is a more
general term  denoting the amount absorbed without
respect to specific  absorption barriers or exchange
boundaries. The amount of a chemical available for
interaction by any particular organ or cell is termed the
delivered dose for that organ or cell.

Dose rate - Dose per unit time.

Dose-response  assessment  -   Analysis  of  the
relationship between the  total amount of an  agent
administered  to, taken up by,  or absorbed by an
organism, system, or (sub)population and the changes
developed in that organism, system, or (sub)population
in reaction to that agent, and inferences derived from
such an analysis with respect to the
entire population.  Dose-response assessment  is the
second of four steps in risk assessment.

Dose-response  curve- Graphical presentation of  a
dose-response relationship.

Dose-response relationship - The resulting biological
responses in  an organ or organism expressed as  a
function of a series  of doses.

Dressed  weight - The portion of the harvest brought
into kitchens  for use, including  bones  for particular
species.

Dry weight intake rates - Intake rates that are based
on the weight of the food consumed after the moisture
content has been removed.
 Dust Ingestion - Consumption of dust that results from
 various  behaviors including,  but  not limited to,
 mouthing objects or hands,  eating dropped food,
 consuming dust directly, or inhaling dust that passes
 from the respiratory system into the gastrointestinal
 tract.

 Effect - Change in the state or  dynamics of an
 organism, system, or (sub) population caused by
 exposure to an agent.

 Energy  expenditures  -  The  amount of  energy
 expended by an individual during activities.

 Exposure -  Contact of a  chemical,  physical, or
 biological agent  with  the outer boundary of an
 organism. Exposure is quantified as the concentration
 of the agent in the medium in contact integrated over
 the time duration of the contact.

 Exposure  assessment  -   The  determination or
 estimation  (qualitative  or   quantitative)  of  the
 magnitude, frequency,  or duration,  and  route or
 exposure.

 Exposure concentration - The concentration  of  a
 chemical in its transport or carrier medium at the point
 of contact.

 Exposure duration  - Length of time over which
 contact with the contaminant lasts.

 Exposure event  -  The occurrence of continuous
 contact between an agent and a target.

 Exposure frequency - The number of exposure events
 in an exposure duration.

 Exposure loading - The exposure mass divided by the
 exposure surface area. For example, a dermal exposure
 measurement based on a skin wipe sample, expressed
 as a mass of residue per  skin surface area, is an
 exposure loading.
Page
G-4
 Child-Specific Exposure Factors Handbook
	September 2008

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Child-Specific Exposure Factors Handbook
Glossary
Exposure pathway - The physical course a chemical
takes from the source to the organism exposed.

Exposure route - The way a chemical pollutant enters
an  organism after  contact,  e.g.,  by  ingestion,
inhalation, or dermal absorption.

Exposure scenario -  A set of facts, assumptions, and
interferences about how exposure takes place that aids
the exposure assessor in  evaluating estimating, or
quantifying exposures.

Fate  - Pattern  of  distribution of an  agent,  its
derivatives, or metabolites in an organism, system,
compartment, or (sub)population of concern as a result
of  transport,  partitioning,   transformation,   or
degradation.

General  population -   The  total of  individuals
inhabiting an area or making up a whole group.

Geometric mean - The n* root of the product of n
values.

Geophagy - A form of soil ingestion  involving the
intentional ingestion of earths, usually associated with
cultural practices.

Hazard - Inherent property of an agent or situation
having the potential to cause adverse effects when an
organism, system, or (sub)population is exposed to that
agent.

Hazard assessment - A process designed to determine
the possible adverse effects of an agent  or situation to
which an organism, system, or  (sub)population could
be exposed.   The process typically  includes hazard
identification, dose-response evaluation and hazard
characterization. The process focuses on the hazard, in
contrast to risk assessment, where exposure assessment
is a distinct additional step.

High end exposure -  An  estimate  of  individual
exposure or dose for those persons at the upper end of
an exposure or dose distribution, conceptually above
the 90th percentile, but not higher than the individual
in the population who has the  highest exposure or
dose.

Homegrown/home  produced foods  -  Fruits  and
vegetables produced by home gardeners, meat  and
dairy products derived form consumer-raised livestock,
game meat, and home caught fish.

Human Equivalent Concentration (HEC) or Dose
(HED): The human concentration (for  inhalation
exposure) or dose (for other routes of exposure) of an
agent that is believed to induce the same magnitude of
toxic  effect  as  the experimental  animal  species
concentration  or  dose.   This  adjustment  may
incorporate toxicokinetic information on the particular
agent, if available, or use a default procedure,  such as
assuming  that daily oral doses experienced for a
lifetime are proportional to body weight raised to the
0.75 power.

Indirect  water  ingestion  -  Includes water added
during food preparation, but not water intrinsic to
purchased foods. Indirect water includes for example,
water used to prepare baby  formulas, cake mix,  and
concentrated orange juice.

Indoor settled dust - Particles in building interiors
that have  settled onto  objects, surfaces, floors,  and
carpeting. These particles may include soil particles
that have been tracked into the  indoor  environment
from outdoors.

Inhalation dosimetry - Process of measuring or
estimating inhaled dose.

Inhalation unit risk - The upper-bound excess lifetime
cancer risk  estimated  to  result from continuous
exposure to an agent at a concentration of 1 "g/m3 in
air for a lifetime.

Inhaled dose - The amount of an inhaled substance
that  is available for  interaction with  metabolic
processes or biologically significant  receptors after
crossing the outer boundary of an organism.
Child-Specific Exposure Factors Handbook
September 2008	
                                          Page
                                            G-5

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                                                        Child-Specific Exposure Factors Handbook
                                                                                              Glossary
Insensible water loss - Evaporative water losses that
occur during breastfeeding. Corrections are made to
account for insensible  water loss when estimating
breast milk intake using the test weighing method.

Intake - The process by which a substance crosses the
outer boundary of an organism without passing an
absorption   barrier  (e.g.,   through   ingestion  or
inhalation).

Intake rate - Rate of inhalation, ingestion, and dermal
contact  depending  on  the route  of  exposure. For
ingestion, the intake rate is simply the amount of food
containing   the  contaminant  of  interest  that an
individual ingests during some specific time period
(units of mass/time). For inhalation, the intake rate is
the rate at which contaminated air is inhaled. Factors
that affect dermal exposure are the amount of material
that comes into contact with the skin, and the rate at
which the contaminant is absorbed.

Inter-individual  variability - Variations between
individuals in terms of human characteristics such as
age or body weight, or behaviors such as location,
activity patterns, and ingestion rates.

Internal dose - The amount of a substance penetrating
across absorption barriers (the exchange boundaries) of
an organism, via either physical or biological processes
(synonymous with absorbed dose).

Intra-individual  variability - Fluctuations in an
individual's   physiologic  (e.g.,  body weight),  or
behavioral  characteristics   (e.g.,  ingestion rates  or
activity patterns).

Key study  -  A  study that is useful for deriving
exposure factors.

Lead isotope  ratio methodology - A method that
measures different lead isotopes in children's blood
and/or urine,   food, water,  and  house dust  and
compares the ratio of these isotopes to infer sources of
lead exposure that may  include  dust or  other
environmental exposures.
 Lifestage - A distinguishable time frame in an
 individual's life characterized by unique and relatively
 stable behavioral and/or physiological characteristics
 that are associated with development and growth.

 Lifetime Average Daily Dose (LADD) - Dose rate
 averaged over a lifetime. The LADD  is used for
 compounds with carcinogenic or chronic effects. The
 LADD is usually expressed in terms of mg/kg-day or
 other mass/mass-time units.

 Limiting  Tracer  Method (LTM)  -  Method for
 evaluating  soil  ingestion that  assumes  that  the
 maximum amount  of soil ingested corresponds with
 the lowest estimate from various tracer elements.

 Long-term exposure - Repeated exposure for more
 than 30 days, up to approximately 10% of the life span
 in humans (more than 30 days).

 Lowest-Observed-Adverse-Effect Level (LOAEL):
 The  lowest exposure  level  at  which  there  are
 biologically significant  increases in frequency  or
 severity  of adverse  effects  between the  exposed
 population and its appropriate control group.

 Margin of safety - For some experts, margin of safety
 has the same meaning as margin of exposure, while for
 others, margin of safety means the margin between the
 reference dose and the actual exposure.

 Mass-balance/tracer  techniques   -  Method  for
 evaluating soil intake that accounts for both inputs and
 outputs of tracer elements.  Tracers in soil, food,
 medicine and other ingested items as well  as in feces
 and urine are accounted for.

 Mean value - Simple or arithmetic average of a range
 of values, computed by dividing the total of all values
 by the number of values.

 Measurement error - A systematic error arising from
 inaccurate measurement (or classification)  of subjects
 on the study variables.
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Glossary
Measurement end-point - Measurable (ecological)
characteristic that is related to the valued characteristic
chosen as an assessment point.

Median value - The value in a measurement data set
such that half the measured values are greater and half
are less.

Metabolic  Equivalent  of Work  (MET)   -  A
dimensionless  energy  expenditure metric used to
represent an activity level.

Microenvironment - Surroundings that can be treated
as  homogeneous  or  well characterized  in  the
concentrations  of an  agent (e.g.,  home,  office,
automobile, kitchen, store).

Model uncertainty - Uncertainty regarding gaps in
scientific theory required to make predictions on the
basis of causal inferences.

Moisture content - The portion of foods made up by
water. The percent water is needed for converting food
intake rates and residue concentrations between whole
weight and dry weight values.

Monte  Carlo  technique  -  A repeated  random
sampling from the distribution of values for each of the
parameters in a generic (exposure or dose) equation to
derive an estimate of the distribution of (exposures or
doses in) the population.

Mouthing behavior - Activities in which objects,
including fingers, are touched by the mouth or put into
the mouth except for eating and drinking, and includes
licking, sucking, chewing, and biting.

Non-dietary  ingestion  -  Ingestion  of  non-food
substances, typically resulting from the mouthing of
hands and objects.

No-Observed-Adverse-Effect-Level (NOAEL) - The
highest exposure  level  at which  there  are no
biologically significant increases  in the frequency or
severity  of adverse  effect between  the exposed
population and its appropriate control; some effects
may be produced at  this level, but they  are  not
considered adverse or precursors of adverse effects.

Outdoor settled dust - Particles that have settled onto
outdoor objects and surfaces due to either wet or dry
deposition.

Oxygen consumption (VO2)  -  The rate at which
oxygen is used by tissues.

Parameter uncertainty - Uncertainty regarding some
parameter.

Pathway - The physical course a chemical or pollutant
takes from the source to the organism exposed.

Per capita intake rate - The average quantity of food
consumed per person in a population composed of both
individuals who ate the food during a specified time
period and those that did not.

Pica   - Pica behavior  is the repeated eating of
non-nutritive substances, whereas soil-pica is a form of
soil ingestion that is characterized by the recurrent
ingestion of unusually high amounts of soil (i.e., on the
order of 1,000 - 5,000 milligrams per day or more).

Plain tap water - Excludes tap water consumed in the
form of juices  and  other beverages containing tap
water.

Population mobility - An indicator of the frequency at
which individuals move from one residential location
to another.

Population risk descriptor - An assessment of the
extent of harm to the population being addressed. It
can be either an estimate of the number of cases  of a
particular  effect that might occur in a population (or
population segment), or a description of what fraction
of the population receives exposures, doses, or risks
greater than  a specified value.
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                                                                                               Glossary
Potential dose - The amount of a chemical contained
in material ingested, air breathed, or bulk  material
applied to the skin.

Poverty/income ratio - Ratio of reported family
income to federal poverty level.

Precision - A  measure of the reproducibility of a
measured value under a given set of circumstances.

Preparation  losses  -  Net  cooking losses, which
include dripping and volatile losses, post  cooking
losses, which involve losses from cutting, bones, excess
fat, scraps  and juices, and other  preparation losses
which include losses from paring or coring.

Primary data/analysis - Information gathered from
observations or measurements of a phenomena or the
surveying of respondents.

Probabilistic uncertainty analysis - Technique that
assigns a probability density function to  each input
parameter, then randomly selects values from each of
the distributions and inserts them into the exposure
equation. Repeated calculations produce a distribution
of predicted values, reflecting the combined impact of
variability in each  input to the calculation. Monte
Carlo is a common  type of probabilistic Uncertainty
analysis.

Questionnaire/survey response - A "question and
answer" data collection methodology conducted via in-
person interview, mailed questionnaire, or questions
administered in a test format in a school setting.

Random samples - Samples selected from a statistical
population  such  that each sample  has an equal
probability of being  selected.

Range  - The  difference between the largest  and
smallest values  in a measurement data set.

Ready-to-feed  - Infant and baby  products (formula,
juices, beverages, baby food), and table foods that do
not need to have water added to them prior to feeding.
 Reasonable maximum exposure (or worst case) - A
 semiquantitative term referring to the lower portion of
 the high end of the exposure, dose, or risk distribution.
 As a semiquantitative term, it should refer to a range
 that can conceptually be described  as above the 90th
 percentile in the distribution,  but below the  98th
 percentile.

 Recreational/sport fishermen - Individuals who catch
 fish as part of a sporting or recreational activity and
 not for the purpose of providing a primary source of
 food for themselves or for their families.

 Reference Concentration  (RfC) - An estimate (with
 uncertainty spanning perhaps an order of magnitude)
 of a continuous inhalation exposure  to the  human
 population  (including sensitive subgroups)  that is
 likely to be without an appreciable risk of deleterious
 effects during a lifetime.  It can be derived  from  a
 NOAEL, LOAEL, or benchmark concentration, with
 uncertainty  factors  generally  applied  to  reflect
 limitations of the data used. Generally used in EPA's
 noncancer  health  assessments.  Durations  include
 acute, short-term, subchronic, and chronic.
 Reference Dose (RfD) - An estimate (with uncertainty
 spanning perhaps an order of magnitude) of a daily
 oral exposure to the human population  (including
 sensitive subgroups) that is  likely to be without an
 appreciable risk of deleterious effects during a lifetime.
 It  can be  derived  from  a NOAEL, LOAEL, or
 benchmark dose, with uncertainty  factors generally
 applied to reflect  limitations  of  the data used.
 Generally  used   in  EPA's  noncancer   health
 assessments.  Durations  include acute, short-term,
 subchronic, and chronic.

 Relevant  study -   Studies that are  applicable or
 pertinent, but not necessarily the most important to
 derive exposure factors.

 Representativeness - The degree to which a sample is,
 or samples are,  characteristic of the whole medium,
 exposure, or dose for which the samples are being used
 to make inferences.
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Glossary
Risk  - The probability of an adverse effect in an
organism, system, or (sub)population caused under
specified circumstances by exposure to an agent.

Risk assessment - A process intended to calculate or
estimate the risk to a given target organism, system, or
(sub)population,  including  the   identification of
attendant uncertainties,  following exposure  to a
particular agent,  taking into  account the  inherent
characteristics of the agent of concern as well as the
characteristics of the specific target system.  The risk
assessment  process  includes  four   steps:  hazard
identification, hazard characterization (related term:
Dose-response assessment), exposure assessment, and
risk characterization. It is the first component in a risk
analysis process.

Risk characterization - The qualitative and, wherever
possible,  quantitative   determination,  including
attendant uncertainties, of the probability of occurrence
of known and potential adverse effects of an agent in
a given organism,  system, or  (sub)population, under
defined exposure conditions. Risk characterization is
the fourth step in the risk assessment process.

Risk  communication  - Interactive  exchange of
information about (health or environmental) risks
among  risk  assessors,   managers,   news  media,
interested groups, and the general public.

Route - The way a chemical or pollutant enters an
organism after contact, e.g., by ingestion, inhalation,
or dermal absorption.

Sample - A small part of something designed to show
the nature or quality of the whole. Exposure-related
measurements are usually samples of environmental or
ambient  media, exposures of a  small  subset  of a
population for a short time, or biological samples, all
for the purpose of inferring the nature and quality of
parameters important to evaluating exposure.

Scenario uncertainty - Uncertainty regarding missing
or incomplete  information needed to fully  define
exposure and dose.
Screening-level assessment - An exposure assessment
that examines exposures that would fall on or beyond
the high end of the expected exposure distribution.

Secondary data/analysis -  The  reanalysis  of data
collected by other individuals or group; an analysis of
data for purposes other than those for which the data
were originally collected.

Sensitivity analysis - Process of changing one variable
while leaving the others constant to determine its effect
on the output. This procedure  fixes each uncertain
quantity at its  credible lower and upper  bounds
(holding all others at their nominal values,  such as
medians) and computes the results of each combination
of values. The results help to identify the variables that
have the greatest effect on exposure estimates and help
focus further  information-gathering efforts.

Serving sizes - The quantities of  individual  foods
consumed per eating occasion. These estimates maybe
useful for assessing acute exposures.

Short-term exposure - Repeated  exposure for more
than 24 hours, up to 30 days.

Soil  -  Particles of unconsolidated  mineral and/or
organic matter from the earth's surface that are located
outdoors, or are used indoors to support plant growth.

Soil adherence - The quantity of soil that adheres to
the skin and  from which chemical contaminants are
available for uptake at the skin surface.

Soil  ingestion - The intentional or unintentional
consumption  of soil, resulting from various behaviors
including, but not limited to, mouthing, contacting
dirty hands, eating dropped food,  or consuming soil
directly. Soil-pica is a form of soil  ingestion that is
characterized by the recurrent ingestion of unusually
high amounts of soil (i.e., on the order of 1,000 -  5,000
milligrams per day or more).  Geophagy is also a form
of soil ingestion defined as the intentional ingestion of
earths and is usually associated with cultural practices.
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                                                       	Glossary
Spatial variability  -  Variability across  location,
whether long- or short-term.

Subsistence fishermen - Individuals who consume
fresh caught fish as a major source of food.

Surface area - Coating,  triangulation, and surface
integration are  direct measurement techniques that
have been used to measure total body surface area and
the surface area of specific body parts. Consideration
has been given for differences due to age, gender, and
race.  Surface integration is performed by using a
planimeter and adding the areas.

Surface integration - Method used to measure skin
surface area in which a planimeter is used to measure
areas of the skin, and the areas of various surfaces are
summed.
Survey response methodology - Responses to survey
questions are analyzed.  This methodology includes
questions asked of children directly,  or  their care
givers, about behaviors affecting exposures.

Tap water from food manufacturing - Water used in
industrial production of foods.

Temporal variability  - Variability over time, whether
long- or short-term.

Threshold  - Dose or  exposure concentration of an
agent below which a stated effect is not observed or
expected to occur.

Time-averaged exposure -  The  time-integrated
exposure divided  by  the  exposure duration.  An
example is the daily average exposure of an individual
to  carbon  monoxide. (Also  called  timeweighted
average exposure.)

Total tap water - Water consumed directly from the
tap as a beverage or used in the preparation of foods
and beverages (i.e., coffee, tea, frozen juices, soups,
etc.).
 Total fluid intake - Consumption of all types of fluids
 including  tapwater,  milk,  soft  drinks, alcoholic
 beverages, and water intrinsic to purchased foods.

 Tracer-element studies -  Soil ingestion studies that
 use  trace  elements  found  in  soil  and  poorly
 metabolized in the human gut as indicators  of soil
 intake.

 Triangulation - Method used to measure skin surface
 area in which  areas of the  body are marked  into
 geometric  figures, then their linear dimensions are
 calculated.

 Uncertainty  - Uncertainty  represents a lack  of
 knowledge about factors affecting exposure or risk and
 can lead to inaccurate or biased estimates of exposure.
 The types of uncertainty include: scenario, parameter,
 and model.

 Upper percentile - Values  in the upper tail (i.e.,
 between 90th and 99.9th percentile) of the distribution
 of values for a particular exposure factor. Values at
 the upper end of the  distribution of values for  a
 particular set of data.
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Glossary
Uptake - The process by which a substance crosses an
absorption barrier and is absorbed into the body.

Variability - Variability arises from true heterogeneity
across  people, places  or  time  and can  affect  the
precision of exposure  estimates and the degree to
which they can be generalized. The types of variability
include: spatial, temporal, and inter-individual.

Ventilation  Rate  (VR)  -  Alternative  term  for
inhalation rate or breathing rate. Usually measured as
minute volume, i.e. volume (liters) of air exhaled per
minute.

Wet-weight intake rates - Intake rates that are based
on the  wet (or whole) weight of the food consumed.
This in contrast to dry-weight intake rates.
Glossary entries adapted from:

International Programme on Chemical Safety (2004).
        IPCS   Risk  Assessment  Terminology.
        Available  on-line  at:
        http://www.who.int/ipcs/methods/harmoniz
        ation/areas/ipcsterminologypartsland2.pdf

U.S. EPA (1992) Guidelines for exposure assessment.
        Washington, DC:  Office of Research and
        Development,   Office   of   Health  and
        Environmental  Assessment.    EPA/600/2-
        92/001.

U.S. EPA.   (1997) Exposure  Factors Handbook
        Revised.      Washington,   DC:   U.S.
        Environmental Protection Agency, Office of
        Research  and Development.   EPA/600/P-
        95/002F.
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