# Estimated Fish Consumption Rates for the U.S. Population and Selected Subpopulations (NHANES 2003 -2010)

Final Report

April 2014

EPA

- 820 -R- 14

- 002

# Acknowledg ments

The U.S. Environmental Protection Agency (EPA) Project Manager for this project was Jeffrey D.

Bigler, who provided management and technical direction for the project. EPA was supported in

this effort by W estat under EPA Contract No. EP-C- 10

- 023. The W esta t project manager was

Rebecca Jeffries Birch who was responsible for the overall technical accuracy and quality of the

project. John Rogers served as the senior statistician. The methodology developed for the project

was externally peer

- reviewed by Versar under EPA Contract No. EP -C- 13

- 010

.

ii

# Table of Contents

Chapter Page

1 Back ground

.......................................................................................................... 1

2 National Health and Nutrition Examination Survey

..................................... 4

2.1 Survey Description................................................................................ 4

2.2 Survey Data

............................................................................................ 5

2.2.1 24 -Hour Recall

...................................................................... 5

2.2.2 30 -Day Fish Consumption Frequency

.............................. 6

2.3 Regions

................................................................................................... 7

3 Data Processing Methodology

.......................................................................... 9

3.1 Habitat Apportionment

....................................................................... 9

3.1.1 NHANES Fish Groupings

.................................................. 11

3.1.2 Use of NOAA Landings Data

............................................ 12

3.1.3 Imported Fish and Farmed Fish

........................................ 13

3.2 Trophic Level Assig nments

................................................................ . 15

3.3 Extracting Repor ted Amounts of Fish Consumed

.......................... 17

4 Statistical Methodology

...................................................................................... 21

4.1 Overview of the NCI Method

............................................................ 21

4.2 Calculation Steps for the NCI and EPA Models

............................. 24

4.2.1 NCI Method

.......................................................................... 24

4.2.2 EPA Method

......................................................................... 27

4.3 Simulation of the Usual Fish Consumption

...................................... 31

4.4 Calculation of Standard Errors and Confidence Intervals

.............. 33

4.5 Application of EPA Method

............................................................... 35

4 6 Comparison of Results from the EPA and NCI Methods

............. 38

4.6.1 Analysis of Simulated Data

................................................. 38

4.6.2 Confidence Intervals for Per centil es of Fish Consumption

......................................................................... 39

4.6.3 Analysis of NHANES Fish Data Using Various

Models

.................................................................................... 42

iii

## Contents (continued)

Chapter Page

5 Resul ts

.................................................................................................................. 46

5.1 Sample Size

............................................................................................ 46

5.2 Usual Fish Consumption Rates

........................................................... 48

5.3 Uncertainty

............................................................................................. 93

5.3.1 Seasonality

.............................................................................. 94

5.3.2 Bias in the Reported Fish Consumption

........................... 94

5.3.3 Use of Standard Recipes

...................................................... 94

5.3.4 Habitat Assignments

............................................................ 95

5.3.5 Estimat ion of Usual Fish Consump tion

........................... 95

5.3.6 Weights for Coasta l Versus Non

- Coastal Regions

................................................................................... 97

6 Discussion

............................................................................................................ 98

7 References

............................................................................................................ 99

Appendixes

A Final Habitat Apportionment

........................................................................... A-1

B FNDDS Processing and Fish -Containing Food Codes

................................ B-1

C Supplemental Statistical Methodology

............................................................. C-1

D EPA Method SAS Code

.................................................................................... D-1

E UFCR Raw Weight, Edible Portion

................................................................ . E-1

F UFCR a s Prepared Weight

................................................................................ F-1

G Unweighted Sample Sizes

.................................................................................. G-1

H Response to Peer Review Comments

.............................................................. H-1

iv

## Contents (continued)

Tables Page

1 Habi tat assig nments of NHANES fish groups

.............................................. 10

2 NOAA landi ngs data, clam apportionment

.................................................... 14

3 Trophic level a ssignments

................................................................................. 16

4 Estimated moisture loss due to c ooking or processing

................................ 19

5 λ ∗ values used for each combination of dependent variable and

data set

.................................................................................................................. 29

6 Comparison of NCI and EPA Methods using NHANES fish

data

........................................................................................................................ 43

7 Sample size and number reporting fish consumption, by fish type

............ 47

8a UFCR estimates (g/day raw weight, edible portion): Total fish, adults, 21 years and older, by demographic characteristics

.......................... 49

8b UFCR estimates (g/day raw weight, edible portion): Total fish, adults, 21 years and older, by geographic area

................................................ 50

9a UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, adults, 21 years and older, by demographic

characteristics

...................................................................................................... 51

9b UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, adults, 21 years and older, by geographic area

.................. 52

10a UFCR estimates (g/day raw weight, edible portion): Marine fish, adults, 21 years and older, by demographic characteristics

.......................... 53

10b UFCR estimates (g/day raw weight, edible portion): Marine fish, adults, 21 years and older, by geographic area

................................................ 54

11a UFCR esti mates (g/day raw weight, edible portion): Total finfish, adults, 21 years and older, by demographic characteristics

.......................... 55

11b UFCR estimates (g/day raw weight, edible portion): Total finfish, adults, 21 years and older, by geographic area

................................................ 56

v

## Contents (continued)

Tables (continued) Page

12a UFC R estimates (g/day raw weight, edible portion): Total shellfish, adults, 21 years and older, by demographic

characteristics

...................................................................................................... 57

12b UFCR estimates (g/day raw weight, edible portion): Total
shellfish, adults, 21 years and older, by geographic area

............................... 58

13aUFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, adults, 21 years and older, b y demographic

characteristics

...................................................................................................... 59

13b UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, adults, 21 years and older, by geographic area

........................... 60

14a UFCR estimates (g/day raw weight, edible portion): Total trophic level 3 fish, adults, 21 years and older, by demographic

characteristics

...................................................................................................... 61

14b UFCR estimates (g/day raw weight, edib le portion): Total trophic level 3 fish, adults, 21 years and older, by geographic area

........................... 62

15aUFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, adults, 21 years and older, by demographic

characteristics

...................................................................................................... 63

15b UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, adults, 21 years and older, by geographic area

........................... 64

16a UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, adults, 21 years and

old er, by demographic characteristics

.............................................................. 65

16b UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, adults, 21 years and older, by geographic area

................................................................................... 66

17a UFCR estimates (g/day raw weight, edible portion): Tot al freshwater + estuarine trophic level 3 fish, adults, 21 years and older, by demographic characteristics

.............................................................. 67

vi

## Contents (continued)

Tables (continued) Page

17b UFC R estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 3 fish, adults, 21 years and older, by geographic area

................................................................................... 68

18a UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, adults, 21 years and older, by demographic characteristics

.............................................................. 69

18b UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, adults, 21 years and older, by geographic area

................................................................................... 70

19a UFCR estimates (g/day raw weight, edible portion): Total fish, youth, <21 years, by demographic characteristics

......................................... 71

19b UFCR estimates (g/day raw weight, edible portion): Total fish, youth, <21 years, by geographic area

............................................................... 72

20a UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, youth, <21 years, by demographic characteristics

............ 73

20b UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, youth, <21 years, by geographic area

................................ . 74

21a UFCR estimates (g/day raw weight, edible portion): Marine fish, youth, <21 years, by demographic characteristics

......................................... 75

21b UFCR estimates (g/day raw weight, edible portion): Marine fish, youth, <21 years, by geographic area

............................................................... 76

22a UFCR estimates (g/day raw weight, edible portion): Total finfish, youth, <21 years, by demographic characteristics

......................................... 77

22b UFCR estimates (g/day raw w eight, edible portion): Total finfish, youth, <21 years, by geographic area

............................................................... 78

23a UFCR estimates (g/day raw weight, edible portion): Total shellfish, youth, <21 years, by demographic characteristics

......................... 79

vii

## Contents (continued)

Tables (continued) Page

23b UFC R estimates (g/day raw weight, edible portion): Total shellfish, youth, <21 years, by geographic area

.............................................. 80

24a UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, youth, <21 years, by demographic characteristics

.................... 81

24b UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, youth, <21 years, by geographic area

.......................................... 82

25a UFCR estimates (g/day raw weight, edible portion): Total trophic level 3 fish, youth, <21 years, by demographic characteristics

.................... 83

25 b UFCR estimates (g/day raw weight, edible portion): Total trophic level 3 fish, youth, <21 years, by geographic area

.......................................... 84

26a UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, youth, <21 years, by demographic characteristics

.................... 85

26b UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, youth, <21 years, by geographic area

.......................................... 86

27a UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, youth, <21 years, by demographic characteristics

.............................................................................. 87

27b UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, youth, <21 years, by geographic area

.................................................................................................... 88

28a UFCR estimates (g/day raw weight, edible portion): Total

freshwater + estuarine trophic level 3 fish, youth, <21 years, by demographic characteristics

.............................................................................. 89

28b UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 3 fish youth, <21 years, by geographic area

.................................................................................................... 90

viii

## Contents (continued)

Ta bles (continued) Page

29a UFCR e stimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, youth, <21 years, by demographic characteristics

.............................................................................. 91

29b UFCR estimates (g/day raw weight, edible portion): Total

freshwater + estuarine trophic level 4 fish, youth, < 21 years, by geographic area

.................................................................................................... 92

Figures

1 Compari son of NCI, EPA, and true percentiles using simulated

data and different transformations

................................................................... 40

2 Comparison of confidence intervals using the NCI and EPA

Methods

............................................................................................................... 41

3 Comparison of NCI and EPA percentiles of fish consumption

rates

....................................................................................................................... 45

ix

# Background 

# 1

The U.S. population is exposed to environmental contaminants through the consumption of

contaminated finfish and shellfish ( Thompson and Boekelheide, 2013; N ational R esearch Council

,
2000 ; Ahmed , Hattis, Wolke, and Steinman, 1993 )

. The analysis presented here provides EPA’s

recommended methodology for developing a national-level fish consumption rate (FCR) for use in

developing ambient water quality criteria as required under Section 304(a) of the Clean Water Act.

As more current data are available and n ew analytical methodologies have been developed

, the

Office of W ater has conducted a new analysis of FCR

. These new FCR s were estimated using data

from the National Health and Nutrition Examination Survey (NHANES) 2003- 2010. NHANES is a

continuous survey designed to collect data on the health and nutritional status of the U.S.

population. Each 2- year cycle is design ed to be representative of the general U.S. population.

An individual’s FCR is the expected quantity of fish consumed per unit time. For a population, there

is a distribution of FCR; some individuals consume more fish per unit time and some less. With

adequate data, we can calculate the average FCR across the population or percentiles, such as the

90th percentile (10 percent of the population has an individual FCR greater than the 90th

percentile).

Different time units can be used to express the same rate, e.g., per day or per week. The FCR is a

theoretical quantity and is often estimated using statistical analysis. It may change over time, for

example, be higher in the summer than the winter. Thus, the FCR depends on the time frame (e.g.,

summer, winter, annual).

Due to the infrequent consumption of fish, the estimated FCR may be variable or imprecise. If a

person eats fish for dinner every Friday and not at other times, the FCR is one fish meal pe r week

and the estimated FCR is likely to be relatively constant. If a fish meal is consumed on average once

every 7 days but sometimes 3 days in a week and other times not fo r several weeks, the estimated

FCR over a short time frame can be quite variable, even though the true FCR is constant and is the

same as in the first example. As the time frame covered by the data gets longer, the estimated FCR

becomes less variable. Assuming the true long- term FCR is constant over time, if the time frame

1

## covered by the data is very long, the estimated FCR becomes a relatively precise estimate of the true

long-term or usual FCR

.

Assuming the FCR is constant over time, methodologies can be designed to estimate the distribution

of the true, long- term, FCR even though t he data are collected over a limited time frame. We can

add the term “usual” to “fish consumption rate” (UFCR) to imply that the resulting estimates are

those that correspond to long- term averages, rather than short

- term estimates and to avoid a

distinctio n between the true rate and the estimated rate.

In the mid

- 2000s, the National Cancer Institute (NCI) developed a statistical methodology to

estimate usual intake of episodically consumed foods. This method, known as the NCI Method, has

been published an d statistical programs are available on NCI’s web site. There are other methods

that have been developed to estimate the distribution of usual intake of episodically consumed

foods. However, the NCI Method is preferred because it accounts for days without consumption;

distinguishes within- person from between -person variation; allows for the correlation between the

probability of consumption and the consumption- day amount; and can use covariate data to better

predict usual intake.

The NCI Method provides estimates of UFCR representing the long- term average grams of fish

consumed per day. Due to the episodic nature of fish consumption, the NCI Method models both

the probability of consumption on a given day and the amount consumed on days when some fish is

c onsumed. These two predicted values are then multiplied together to get a usual intake value. The

calculations using the NCI Method are very time consuming. T o get estimates in a reasonable time,

EPA created a program, here in after referred to as the EPA Me thod, which approximates the results

from the NCI Method. Details of the NCI Method, the EPA M ethod, and how they compare are

provided in Section 4, Statistical Methods.

UFCR s were estimated for the general U.S. population, the youth population under 21 y ears of age,

and the adult population 21 years and older. UFCR estimates were calculated for various

subpopulations, e.g. , by age, gender, race/ethnicity , income, U.S. Census region , and coastal and

noncoastal populations. We estimated UFCR for 18 different categories of fish , both raw weight of

edible portion and as- prepared weight

. These fish types were chosen as they represent various

categories of interest to states and tribes. For example, a coastal state may be interested in knowing

th e UFCR s of total fish and of marine and freshwater + estuarine , separately. An inland state may

only be interested in freshwater fish UFCR s. Additionally, as fish bioaccumulate toxins at different

2

## rates depending on their trophic level, UFCR were also calc ulated for fish by trophic level. The fish

types are the following:



































 

## Total fish ;

Total finfish ;

T otal shellfish ;

Marine fish ;

Freshwater fish ;

Estuarine fish ;

Freshwater + estuarine fish ;

Freshwater + marine fish ;

Estuarine + marine fish ;

Trophic level 2 f ish ;

T rophic level 3 fish ;

Trophic level 4 fish ;

Marine trophic level 2 fish ;

Marine trophic level 3 fish ;

Marine trophic level 4 fish ;

Freshwater + estuarine trophic level 2 fish ;

Freshwater + estuarine trophic level 3 fish ; and

Freshwater + estuarine trophic level 4 fish

.

This report presents the methodologies used to extract fish consumption data fr om the NHANES

data set s, the habitat apportionment methodology, the trophic level assignment methodology, the

statistical methodology, and the UFCR estimat es and 95 percent confidence intervals (95% CI) of

the mean and the 25th, 50th, 75th, 90th, 95th, 97th, and 99th percentiles.

3

# National Health and Nutrition Examination Survey 

# 2

2.1 Survey Description

NHANES is designed to assess the health and nutritional status of adults and children in the United

S tates

. It is conducted by the National Center for Health Statistics (NCHS , 2013 )

, part of the

Centers for Disease Control and Prevention (CDC) that is responsible for producing vital and health

stati stics for the United S tates. NHANES began in the 1960s. In 1999, the survey became a

continuous program that examines a nationally representative sample of about 5,000 persons located

in 15 counties across the country each year.

The NHANES interview incl udes demographic, socioeconomic, dietary, and health- related

questions. The examination component consists of medical, dental, and physiological measurements,

as well as laboratory tests.

NHANES collects 2 days of dietary dat a from all participants. The f irst day, the data are collected in

person at the examination portion of the survey. The second day’s data are collected by telephone

interview 3 to 10 days after the in -person interview. Both interviews include a 24- hour dietary recall

section. The primary goal of the 24-hour recall is to collect a detailed list of all the foods and

beverages consumed within a 24 -hour period. Food models are used to help participants estimate

the amount consumed. The in-person interview also includes a section on the frequ ency of

consumption of fish and shellfish in the past 30 days (NCHS, 2009). Survey participants are not

asked to provide detailed recipes for mixed dishes. For those, stan dard default recipes are used.

A complex, multistage probability sampling design is used to select participants representative of the

civilian, noninstitutionalized U .S. population.



 

## Stage 1: Primary sampling units (PSUs) are selected with probability proportional to a measure of size (PPS). These are mostly single counties or, in a few cases, groups of contiguous counties.

Stage 2: The PSUs are divided up into segments (generally city blocks or their

equ ivalent). As with each PSU, sample segments are selected with PPS.

4

### 

 

## Stage 3: Households within each segment are listed, and a househol d sample is randomly drawn. In geographic areas where the proportion of age, ethnic, or income groups selected for oversampling is high, the probability of selection for those groups is greater than in other areas.

Stage 4: Individuals are chosen to participate in NHANES from a list of all persons

r esiding in selected households. Individuals are drawn at random within designated agesex

- race/ethnicity screening subdomains. On average, 1.6 persons are selected per household. Oversampling of certain population subgroups is done to increase the reliability and precision of health status indicator estimates for these groups.

The NHANES data files include analysis weights to account for the complex survey design

(including oversampling), survey nonresponse, and poststratification. Weighted NHANES results

describe the U.S. Census civilian noninstitutionalized population. A person’s analysis weight is a

measure of the number of people in the population represented by that sampled person.



# 2. 2 Survey Data

2. 2 .1 24

- Hou r Recall

The 24 -hou r dietary recall interview data provide ( 1) what food items the participants ate and ( 2)

how much of each food item they ate. All NHANES participants are eligible for the dietary

interview component that occurs during the examination portion of the survey. The first interview is

conducted in person via a computer- assisted dietary interview software program that was developed

for NHANES

. The interviewer uses a standard set of measuring guides to help the participant report

the volume and dimensions of the food s consumed . The second dietary interview is conducted via

telephone. It occurs 3 to 10 days after the first dietary interview

. The participants are given a set of

measuring guides to take home and use during the telephone interview.

The 24 -hour recall data are collected using the USDA Automated Multiple- Pass Method (AMPM).

Detailed information on the method can be found on USDA’s web site at

http://www.ars.usda.gov/Services/docs.htm?docid=7710 . The method is computerized and

research based . It uses five steps designed to assist participants with complete and accurate food

recall and reduce respondent burden.

5

## The five steps follow:

1. Collect a list of foods and beverages consumed the previous day.

2. Probe for foods forgotten during step 1

.

3. Collect the time and the name of the eating occasion for each food.

4. For each food, collect detailed description, amount, and additions (i.e., anything that

ma y have been added to the food). Review 24 -hour day.

5. Final probe for anything else consumed.

We assume that the reports of 24-hour consumption are unbiased estimates of each respondent’s

true consumption.



# 2. 2 .2 30

- D ay F ish Consumption F requency

The 30 -day fish consumption frequency data are derived from questionnaire data that ask

participants how often in the past 30 days they consumed different fish species. These species are

clams, crabs, crayfish, lobster, mussels, oysters, scallops, shrimp, other shellfish, unknown shellfish,

breaded fish products, tuna, bass, catfish, cod, flatfish, haddock, mackerel, perch, pike, pollock,

porgy, salmon, sardines, sea bass, shark, swordfish, trout, walleye, other fish, and unknown fish.

Using these data, we can derive a variable for the number of times fish was consumed in the past 30

days by summing up the values for all 31 variables. This information improves intake estimates for

episodically consumed foods like fish, as even people who consumed fish frequently do not do so

every day ; therefore, it is no t always reported in 24-hour recall data. This derived frequency of

consumption can then be used as a predictor in statistical models of the probability of fish

consumption and fish consumption amount.

In 20 03

- 2004, only children less than 6 years of age and women 16 to 49 years old were asked these

questions. As frequency of fish consumption is an important predictor in the statistical models, we

only included these age and gender groups from NHANES 2003- 2004 in the analysis. The analysis

weights of male participants in 2005

- 2010 and females not in these age groups were adjusted to

account for this difference. Since they are only in three of the four cycles of NHANES their weights

were multiplied by a factor of 4/3.

6

# 2. 3 Regions

Patterns of fish and shellfish consumption may vary by geography, such as between U.S. residents

who live on or near the coast and those who live inland, or among regions of the United S tates as
defined by the U.S. Census Bureau (Maha ffey, Clickner, and Jeff r ies

, 2009). Fish consumption

patterns may also vary by specific coast ( e.g., residents near the Atlantic coast may have different

fish consumption patterns than those on the Gulf of Mexico coast)

. T o estimate FCRs by region

and coast, we assigned NHANES respondents to U.S. Census Bureau regions and coastal or

noncoastal status, which when combined created the following: Atlantic Coast, Northeast, Great

Lakes, Midwest, South, Gulf of Mexico, West

, and Pacific Coast. The geography data were obtained

from the NCHS Research Data Center through its restricted

- use data access procedures.

The geographic unit used by NHANES is a county or county equivalent; th erefore our definitions of

coastal and noncoastal were limited to county bound aries. All counties that bordered the Pacific or

Atlantic Oceans, the Gulf of Mexico or any of the Great Lakes were defined as coastal. Additionally,

counties that bordered estuaries and bays were defined as coastal as were counties whose cent roid

was within approximately 25 miles of any coast even if not directly bordering a coast. The four

coastal regions were then defined based on nearest body of water . The following provides

definitions of each region:



 

## U.S. Census Regions



# –

–

–

– Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, and KS

Northeast = PA, NY, NJ, CT , R I, MA, NH, VT, and ME

South = DE, MD, DC, VA, WV, KY, TN, NC, SC, GA, AL, MS, FL, LA, AR,
OK, and TX

West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, and HI

Coastal and Inland Regions



# –

–

–

– Pacific Coast = coastal counties in CA , O R , W A , A K, and HI

Atlantic C o ast = coastal counties in CT, DE, DC, FL (bordering Atlantic Ocean), GA, ME, MD, MA, NH, NJ, NY, NC, PA, RI, SC, and VA

Gulf of Mexico Coast = coastal counties in AL, FL (bordering Gulf of Mexico),

LA , MS, and TX

Great Lakes Coast = counties bordering the Great Lakes in MI, WI, OH, NY,

MN , IN, IL, and PA

7

# –

–

–

– Inland West = remaining counties in CA, OR, WA, AK, and HI and all of NM, CO, WY, MT, ID, UT, AZ, and NV

Inland South = remaining non- c o astal counties in DE, MD, DC, VA, NC, SC, GA, AL, MS, FL, LA, and TX and all of WV, KY, TN, AR, and OK

Inland Northeast = remaining counties in PA, NY, NJ , CT , RI, MA, NH , and

ME and all of VT.

Inland Midwest = remaining counties in OH, MI, IN, WI, IL, and MN and all of

MO , IA, SD, ND, NE, and KS.

8

# Data Processing Methodology 

# 3

3.1 Habitat Apportionment

T o make estimates of FCRs for marine fish, estuarine fish, freshwater fish, and various

combinations of these types, the fish species reported as consumed by NHANES participants were

apportioned to habitats. The assignments of species were completed by a fisheries biologist.

Appendix A contains the detailed documentation of the assignments for each species.

The fish were apportioned to align with EPA’s long-standing interpretation of section 303(c) (2) (A)

of the Clean Water Act that s tate and tribal waters should support safe consumption of fish and

shellfish and that the standards need to be set to enable residents to safely consume from local

waters the amount of fish they would normally consume from all fresh and estuarine (including near

coastal) waters. Thus marine species that are harvested in near coastal waters were assigned to the

estuarine habitat in order to be included in the freshwater + estuarine FCR . The following decisions

concerning habitat assignments were made:







 

## Estuarine fish and shellfish include estuarine spe cies harvested in near

- coastal areas (clams, mussels, crabs, lobster, shrimp) and single species that live in both marine and estuarine habitats ( e.g., specific clam and octopus species or the single jellyfish species

that constitutes the U .S. jellyfish fi shery).

Tilapia was assigned 50 percent freshwater and 50 percent estuarine, even though it is

rare i n U .S. waters , to be consistent with EPA’s long-standing interpretation of section 303(c) (2) (A) of the Clean Water Act , as mentioned above, that the stan dards need to be set to enable residents to safely consume from local waters the amount of fish they would normally consume from all fresh and estuarine (including near coastal) waters.

Shrimp was assigned 17.6 percent marine and 82.4 percent estuarine. N ational O ceanic and Atmospheric A dministration (NOAA) landings data show that 17.6 percent of shrimp harvested in 2009

- 2010 were “Ocean Shrimp (Oregon Pink Shrimp),” “Rock Shrimp,” “Royal Red Shrimp,” and “Marine Shrimp, Other.”

Salmon was assigned 96 percent mar ine, 0.5 percent freshwater, and 3.5 percent estuarine. The freshwater percent is landlocked sockeye salmon (Kokanee) found natively in Alaska, Washington, and Oregon, but they have also been introduced to many other states for recreational fishing. The estuarine percent includes saltwater trout

,

9

## which are included in the NHANES salmon group, and the small proportion of salmon

that are harvested in est uaries. Note that farmed Atlantic salmon w ere assigned to the marine habitat as they are produced outside of the United S tates in marine waters.

Table 1 presents the final proportion of each NHANES fish group that is assigned to marine,

freshwater, and estuarine habitats. Note that unspecified fish consumed was assigned the overall

average habitat apportionment of all species reported consumed. The remainder of Section 3.1

describes the habitat apportionment methodology.

Table 1. Habitat a ssignments of NHANES f is h g roups

Species/g roup Proportion

Marine Freshwater Estuarine

Abalone 1.000 0.000 0.000 Anchovy 0.000 0.000 1.000

Barracuda 1.000 0.000 0.000

Breaded Fish Products (e.g., fish sticks) 1.000 0.000 0.000 Carp 0.000 1.000 0.000

Catfish 0.000 0.900 0.100

Clam 0.840 0.000 0.160

Cod 1.000 0.000 0.000

Conch 1.000 0.000 0.000

Crab 0.273 0.000 0.727 Crayfish 0.000 1.000 0.000

Croaker 0.071 0.050 0.879

Eel 0.000 1.000 0.000

Fish

, not specified 0.520 0.160 0.320

Flatfish 0.870 0.000 0.130

Haddock 0.945 0.050 0.006

Halibut 0.780 0.000 0.220
Herring 0.304 0.010 0.686 Jellyfish 0.000 0.000 1.000

Lobster 0.044 0.000 0.956

Mackerel 0.411 0.000 0.589

Mullet 0.000 0.000 1.000

Mussel 0.000 0.000 1.000
Octopus 0.620 0.000 0.380 Oyster 0.000 0.000 1.000

Perch 0.000 1.000 0.000

Pike 0.000 1.000 0.000
Pompano 0.661 0.002 0.338

Rockfish /Ocean Perch 0.925 0.000 0.075

Roe 0.085 0.235 0.680

Salmon 0.960 0.005 0.035

Sardine 0.900 0.000 0.100
Scallop 0.000 0.000 1.000 Scup/Porgy 0.981 0.000 0.019

Sea Bass 0.925 0.025 0.050

Shad 0.304 0.010 0.686

Shark 0.866 0.000 0.134
Shrimp 0.176 0.000 0.824

Snail 0.450 0.100 0.450



## 10

## Table 1. Habitat assignments of NHANES fish groups (continued)

Species/g roup Proportion

Marine Freshwater Estuarine
Snapper 0.981 0.000 0.019 Squid 0.800 0.000 0.200 Sturgeon 0.000 0.420 0.580

Swordfish 1.000 0.000 0.000
Tilapia 0.000 0.500 0.500

Trout 0.106 0.869 0.025

Tuna 1.000 0.000 0.000

Whelk 0.000 0.000 1.000

Whitefish 0.877 0.000 0.123
Whiting 1.000 0.000 0.000



# 3.1.1 NHANES Fish Groupings

When the raw 24 -hour recall data are processed by NHANES, fish species reported consumed are
grouped, and foods (e.g., Pompano, baked or broiled) are assigned food codes. The list below

presents the species of fish that are specified in the USDA Food and N utrient D atabase for D ietary

Studies (FNDDS) and the additional species that are included in each group.



























 

## Abalone Anchovy

Bar racuda Carp (bream; buffalofish; and

s uck er) Catfish (bullhead)

Clams

Cod

Conch

Crab Crayfish Croaker (angelfish; butterflyfish;

dru mfish; goatfish; kingfish; sea trout; freshwater sheepshead; spadefish; spot; surgeonfish; weakfish; weke; goo; and gaspergou)

Eel Fish stick, patty, or fillet, not

spe cified as to type (commercial products such as Mrs. Paul’ s, Gorton ’s, Van de Kamp’ s) Fish, not specified as to type 

























 

## Flounder (dab; fluke; halibut; sole; and turbot) Haddock (blowfish; burbot; cusk;

ha ke; ling; monkfish; pollock; and scrod)

Halibut

H erring (alewife; milkfish; and shad) Jellyfish

Lobster Mackerel (garfish; ono;

needl efish; and wahoo)

Mullet

Mussels Ocean perch (bocaccio;

menpa chi; orange roughy; redfish; and rockfish) Octopus Oysters Perch (freshwater bass; bluegill;

cra ppie; sunfish; and walleye) Pike (muskellunge; and pickerel)

11

### 















 

## Pompano (akule; blackfish; bluefish; butterfish; dolphinfish; jack; mahimahi; paplo; parrot
fish; sablefish; scad; tilefish; ulva; and yellowtail) Porgy (scup; sea bream; marine

s heepshead; and snapper) Ray (skate) [not reported ever

c onsumed]

Roe Roe, sturgeon (caviar) Salmon (saltwater trout)

Sardines Scallops Sea bass (grouper; striped bass;

wr eakfish; and bass) 

























 

## Shark (dogfish and grayfish) Shrimp

S melt [not reported ever

cons umed in the 2003

- 2010 data ]

Snails Snapper Squid (cuttlefish) Sturgeon Swordfish (marlin) Tilapia Trout (cisco; lake herring;

st eelhead; and whitefish) Tuna (ahi; aku; and bonito)

Whelk

Whitefish Whiting

Thi s grouping of species complicate s the assignment of habitat because in many cases , the grouped

fish inhabit different habitats. For example, burbot, a freshwater fish, is part of the haddock group,

which is defined by the Order Gadiformes (excluding cod). All of the other species in this group are

marine and estuarine. For these groups, we used raw (uncoded) 24- hour recall files from NHANES

from 2007

- 20 08 (which are not publically available, and the only cycle made available to us) and

counted the number of times a species was reported

. Using the haddock group as an example, in

2007

- 20 08 blowfish, burbot, cusk, hake, ling, and monkfish were reported 0 times, pollock was

reported 10 times, scrod was reported 2 times, and haddock was reported 4 times. These counts

were then used to assign proportions of each species in the group to the total group. No species in a

group was assigned 0 percent based on a 0 count in the files, because it may be reported in another

NHANES cycle. These species were assigned between 1 and 5 percent depending on h ow many
species are included in the group and how many times other species in their group were reported

consumed. Appendix A provides the percentages assigned to each species. The assigned proportions

were then multiplied by the habitats and summed to get the total habitat proportions for the fish

group.



# 3.1.2 Use of NOAA Landings Data

Other assignments were complicated by the fact that a species lives in multiple habitat types, either

at different life stages or because different species occupy different habitats. For these species,

habitat apportionment was aided by using the NOAA landings data

( http://www.st.nmfs.noaa.gov/commercial- fisheries/ ).

12

## Table 2 is an example of the NOAA landings data for clams for 2010. To apportion the total

consumption of clams to estuarine and marine, we first assigned a habitat to each clam species listed.

According to these data, excluding the catch- all category, 84 percent of all clam s landed in 2010 w ere

f rom the marine environment and 16 percent w ere from the estuarine environment (multiplying the

proportion of total without catch-all by the habitat proportion for each species and then summing

for each habitat). These proportions excluding the catch- all ca tegory were then applied to the catch

all category, and the overall proportions were re- calculated.

This methodology was used to assist the apportionment of the following species: catfish, clam, crab,

flatfish, flounder, sole, halibut, lobster, macke rel, porgy, shrimp, and whiting and species in the

following food code groups: croaker, pompano, sardine, and trout.



# 3 .1.3 Imported Fish and Farmed Fish

It is known that the United States imports a large proportion of the fish consumed from overseas.

According to NOAA Fish Watch, 86 percent of the fish consumed in the United States are

imported ( http://www.fishwatch.gov/wild_seafood/outside_the_us.htm ). The top imported species

are shrim p, freshwater fish (mainly tilapia and catfish) , tuna, salmon, groundfish ( e.g. , cod, haddock,

flounder), crab, and squid . As marine fish are not harvested from U.S. waters for which states would

be developing water quality standards, the issue of importation for these species is not relevant.

However, shrimp is the most commonly consumed fish by U.S. consumers. It is unknown whether

the proportion consumed that was harvested in non- U.S. waters is distributed equally across the

distribution of fish consumers. For example, it is possible that high fish consumers eat more locally

caught fish as they may be more likely to be recreational or subsistence fishers. For the purposes of

developing UFCR, we assumed that all estuarine, freshwater, and near coastal fish that were

consumed were from U.S. waters. The reason for this is that standa rds need to be set to enable

residents to safely consume from local waters the amount of fish they would normally consume

from all fresh and estuarine (including near coastal) wat ers.

13

## Table 2. NOAA landings data, clam apportionment

Pounds

l anded, 2010 Proportion of

t otal Proportion of t otal
(w ithout catch

- all
category) Habitat Habitat

p ercent
Clam, Arc, Blood 23,738 0.0003 0.0003 E stuarine & marine harvested near coast 100E

Clam, Atlantic Jackknife 67,334 0.0008 0.0008 E stuarine 100E

Clam, Atlantic Surf 37,465,740 0.4188 0.4542 M arine 100M

Clam, Butter 15,133 0.0002 0.0002 E stuarine & marine harvested near coast 100E

Clam, Manila 937,915 0.0105 0.0114 E stuarine 100E

Clam, Northern Q uahog 4,406,313 0.0493 0.0534 E stuarine 100E

Clam, Ocean Q uahog 31,704,091 0.3544 0.3844 M arine 100M

Clam, Pacific Geoduck 2,777,529 0.0310 0.0337 E stuarine & marine harvested near coast 100E

Clam Pacific Littleneck 26,811 0.0003 0.0003 E stuarine & marine harvested near coast 100E

Clam, Pacific Razor 138,826 0.0016 0.0017 M arine 100M

Clam Pacific Gaper 6,061 0.0001 0.0001 E stuarine & marine harvested near coast 100E

Clam, Quahog 634,131 0.0071 0.0077 E stuarine 100E

Clam, Softshell 4,278,356 0.0478 0.0519 E stuarine & marine harvested near coast 100E

Clams or Bivalves 6,980,468 0.0780 e stuarine & marine (catch

- all category) 16E/84M

Total Pounds 89,462,446

Total Pounds w ithout catch

- all 82,481,978

Without catch

- all Proportion

Estuarine 0.15971

Proportion

Marine 0.84029

Total Proportion

Estuarine 0.15973

Proportion

Marine 0.8402714

## There are similar issues with farmed freshwater fish. Freshwater fish can be farmed in man

- made

ponds or tanks for which the states will not be developing water quality standards. However, as

noted above in the discussion concerning imported fish, the proportion of freshwater fish

consumed that is farmed may not be evenly distributed across the distribution of consumption.

Again, it is possible that high fish consumers are eating locally caught fish through recreational or

subsistence fishing and thus eating a smaller proportion of farmed fish than those at the middle and

low end of the consumption distribution. Th erefore farmed species were assumed to be wild caught.

This allows residents to safely consume from local waters the amount of fish they would normally

consume from fish farms.



# 3.2 Trophic Level Assignments

The trophic level of an organism is the place it occupies in the food web. Organisms with higher

trophic levels have higher exposures to environmental contaminants.









 

## Trophic level 1 organisms are primary producers (plants and algae).

Trophic level 2 organisms are herbivores, also called primary consumers.

T rophic level 3 organisms are carnivores that consume herbivores

.

T rophic level 4 organisms are carnivores that consume other ca rnivores.

Trophic level 5 organisms are the apex predators.

Tr ophic level assignments were made using the data provided in the following documents: (1)

Methodology for Deriving Ambient Water Quality Criteria for the Protection of Human Health (2000), Tab le 6 -4

(U.S. Environ mental Protection Agency, 2003) and (2) Trophic Level and Exposure Analyses for Selected

Piscivorous Birds and Mammals : Volume III: Appendices (U.S Environmental Protection Agency, 2002 b)

.

For species that were not in those documents, we performed a search of literature available on the

I nternet and applied the same rules that were described in the December 2003 document:



 

## For game fish, data were used for edible size ranges (about 20 cm [8 inches] or larger).

For species where multiple size ranges were available, preference was given to the larger

s pecimens in determining the species trophic level.

15

### 

 

## Trophic level 2 was assigned to a species if appropriate trophic level data ranged between 1.6 and 2.4; trophic level 3 if trophic level d ata ranged from 2.5 to 3.4; and trophic level 4 if trophic level data were 3.5 or higher. This is consistent with the approach taken in the Great Lakes Water Quality Initiative guidance (U .S

. Environmental Protection A gency , 1995).

In determining NHANES fi sh grouping trophic level assignments, best professional judgment was used. If the vast majority of the species in a group are within one trophic level, then that trophic level is assigned. If species span two levels it is split 50

- 50. For example, the NHA NES grouping for catfish includes four species that are assigned to trophic level 3 and three species assigned to trophic level 4. Thus, it is assumed that half (50 percent) of consumption in the catfish NHANES grouping is from TL3 and half

from TL4. Other fish this rule applies to are croaker, flatfish, and shrimp.

Table 3 presents the final trophic level assignments.

Table 3. Trophic l evel a ssignments

Fish s pecies/g roup Proportion of Assigned to Trophic Level Trophic l evel 2 Trophic l evel 3 Trophic l evel 4

ABALONE 1 0 0

ANCHOVY 0.5 0.5 0

BARRACUDA 0 0 1

BREADED FISH PRODUCTS (e.g., fish sticks) 0 0.5 0.5

CARP 0 1 0

CATFISH 0 0.5 0.5

CLAM 1 0 0

COD 0 0 1

CONCH 1 0 0

CRAB 0 1 0

CRAYFISH 0 1 0

CROAKER 0 0.5 0.5

EEL 0 0 1

FISH NOT SPECIFIED 0 0.5 0.5

FLATFISH 0 0.5 0.5

HADDOCK 0 0 1

HALIBUT 0 0 1

HERRING 0 1 0

JELLYFISH 1 0 0

LOBSTER 0 1 0

MACKEREL 0 0 1

MULLET 1 0 0

MUSSEL 1 0 0 ROCKFISH/OCEAN PERCH 0 0 1

OCTOPUS 0 0.5 0.5

OYSTER 1 0 0

PERCH 0 0 1

PIKE 0 0 1

POMPANO 0 0 1
PORGY/SCUP 0 0 1

ROE 0 0 0

SALMON 0 0 1



## 16

## Table 3. Trophic l evel a ssignments (continued)

Fish s pecies/g roup Proportion of Assigned to Trophic Level Trophic l evel 2 Trophic l evel 3 Trophic l evel 4

SARDINE 0 1 0

SCALLOP 1 0 0

SEA BASS 0 0 1

SHAD 0 1 0

SHARK 0 0 1

SHRIMP 0.5 0.5 0

SNAIL 1 0 0

SNAPPER 0 0 1
SQUID 0 0.5 0.5

STURGEON 0 0 1

SWORDFISH 0 0 1

TILAPIA 1 0 0

TROUT 0 0 1

TUNA 0 0 1

WHELK 1 0 0

WHITEFISH 0 1 0

WHITING 0 1 0



# 3.3 Extracting Reported Amounts of Fish Consumed

The FNDDS is the underlying database used to code dietary intakes for NHANES. It is a database

of foods, their nutrient values, and gram weight equivalents for various ingredients in the foods. For

each new version of FNDDS, foods, gram weights, and nutrient values are reviewed and updated to

reflect the U.S. food supply by incorporating new foods based on what is reported in the survey and

updating existing entries.

In FNDDS, each food is given an 8 -digit food code. The first digit identifies one of nine major food

groups. The second, third, and fourth digits identify increasingly more specific subgroups. Most fishcontaining foods are found under “26 – Fish and Shellfish,” “27

– Meat, P oultry, Fish with nonmeat

items,” and 28 , which includes soups and frozen meals. Other fish-containing foods are found under

“5 – Grains” such as seafood pizza and pasta dishes and “7 – Vegetables” for dishes that are mainly

vegetables but also contain fish and/or shellfish.

The NHANES 24 -hour recall data include these same food codes for each reported food consumed;

th erefore the reported foods can be merged to the FNDDS files to obtain recipe information. The

FNDDS files are available from the Agriculture Research Service of the USDA (USDA, 2006;

USDA, 2008; USDA 2010; Ahuja et al., 2012). FNDDS includes several files (or tables), including a

file that is linked to the USDA National Nutrient Database for Standard Reference (SR) that

17

## provides recipes for reported foods. For example, the standard recipe for “Perch, baked or broiled,”

consists of the ingredients (1) fish, perch, mixed species, raw; (2) margarine, stick, salted; (3) lemon

juice, raw; and (4) salt, table. The FNDDS

- SR link file provides weight s in grams for each ingredient

in each recipe. In the above example, these amounts are 907.2 g rams of fish, 28.2 g rams of

margarine, 30.5 g rams of lemon juice, and 6 g rams of table salt. From these amounts, the fraction by

weight of the recipe that is fish can be calculated. In the example, 907.2 / (907.2+28.2+30.5+6) =

0.933 g rams of prepared fish per gram of recipe.

The FNDDS files were searched to find all food codes that contain finfish and/or shellfish. These

records were then processed to determine t he weight of each fish ingredient as a fraction of the

weight across all ingredients in the recipe

. The recipe ingredients may be raw, canned (cooked), or

otherwise processed before being put into the recipes. The FNDDS description of each ingredient

generally includes the processing before the ingredient is added to the recipe. After the dish is

prepared from the ingredients, the food dish may have additional cooking or processing, such as

baking. Th is processing is often described in the FNDDS food description.

As NHANES participants report the amount consumed “as prepared” (which is converted to a

weight , in grams, in the NHANES file ), it is relatively easy to estimate the grams of prepared fish

that is consumed. However, because cooking can change the moisture content of the fish,

calculating the grams of raw fish consumed requires to a weight conversion based on the likely

moisture loss due to cooking. The calculation of the weight of as-prepared and raw fish consumed

are based on the following:





 

## Estim ates of the moisture loss associated with various cooking methods.

Assuming the weight of fish as a proportion of the weight of the food is the same for

th e recipe in the FNDDS files as in the final as

- prepared dish. In effect, we assume the proportional weight loss due to cooking of the prepared recipe as the same for the fish and non-fish ingredients.

If the recipe specifies two cooking steps, one for the fish used in the recipe (for

exa mple, using canned ingredients) and one for the prepared recipe (for example, baking before serving), assuming a moisture loss associated with the cooking method

with the most moisture loss.

The uncooked amount of fish was determined using the recipe databases, which list the amount of

each ingredient in the food code. The weight of each ingredient as a fraction of the weight of the

recipe was calculated, as above. During this data processing, each fish ingredient in the recipe was

apportioned to marine, estuarine, and freshwater habitat and to trophic levels 2, 3, and 4, a s

18

## discussed in Sections 3.1 and 3.2. As many food codes comprise multiple fish species, each of these

values was summed, along with total fish percent, across all fish -containing ingredients to get total

values for each habitat, trophic level, and total fi sh for each fish -containing food code.

The adjustment factors for cooking by dry heat, moist heat, and frying and the adjustment factors

for canning and restructured fish are also used in the analysis of the CSFII data published in 2002

(EPA, 2002 a) and in the Mercury Study Report to Congress (EPA, 1997 , Volume 4). These cooking and

processing methods represent 90 percent of all reported fish consumed. The percent moisture loss

for the remaining cooking and processing methods (dried, kippered, smoked, salted, and pickled) are

estimated using the FNDDS “MoistNFatAdjust” file. This file provides the percent moisture and fat

loss or gain due to cooking, by food code; there is a file specific to each NHANES release. These

adjustments are used in the calcula tions of nutrient intake (e.g., calcium, protein) for NHANES

participants. However, for many food codes they are set to zero because the FNDDS recipe uses a

cooked or processed fish as the ingredient, and no further adjustments were needed for nutrient

intake calculations. We calculated the mean value of moisture loss for the remaining cooking

methods for those fish food codes that did not ha ve a 0 value, using this file. Table 4 provides the

adjustments applied by cooking and processing method. For unspecified cooking method,

approximately 5 percent of all reported fish consumed, an average adjustment across all reported

fish food codes was applied (22 percent moisture loss).

Table 4. Estimated moisture loss due to cooking or processing

Cooking/Processing m ethod Percent m oisture l oss

Dried 57

Kippered 46

Smoked, (other than salmon) 36

Salted 33

Canned 25

Cooked, dry heat 25

Restructured 25

Cooked, moist heat 21

Smoked salmon 17

Pickled 16

Fried 12

Raw 0



## The re is uncertainty associated with these values. They are average values of moisture loss given the

various processing and cooking methods. If participants cooked their fish a bit longer, th en the

19

## moisture loss would be a bit greater than average, and if they cooked it a bit less, the moisture loss

would be a bit less than average.

Appendix B provides a detailed description of how the fish foods were abstracted and processed

from FNDDS and it provides the final number of grams of raw weight, of the edible portion fish

per 1 g ram of the final prepared recipe in each fish -containing food code reported in the NHANES

data 2003

- 2010. It contains the values for total, marine, estuarine, freshwater, and trophic levels 2

through 4 fish.

As an example calculation, the standard recipe for food code 27250400 “shrimp cake or patty”

contains 0.475 g rams of shrimp per gram of total recipe. The shrimp ingredient in the recipe is

canned; therefore moisture loss is estimated to be 25 percent. We divide .475 by 0.75 to get the

grams of raw fis h in 1 g ram of the final prepared recipe, which is .633 g . Shrimp was apportioned to

the habitats as 17.6 percent marine and 82.4 percent estuarine. We then multiply these percentages

by the grams of raw shrimp in 1 g ram of the final prepared recipe, 0.176 *.6 33 = .111 g rams raw
marine fish in 1 g ram of the final prepared recipe

, and 0.824*.633 = .522 g rams raw estuarine fish in

1 g ram of the final prepared recipe. Similar calculations are made to determine grams of raw fish by

trophic levels in 1 g ram of the prepared recipe. These amounts are then multiplied by the reported

grams of food code 27250400 consumed by the participants and summed across all fish-containing

food codes reported by each respondent to get the reported 24-hour intake.

Using this example, we can see the uncertainty added to the estimates by using standard recipes.

Recipes used for shrimp cakes could vary from the assumed 4 7.5 percent fish by weight composition

by using more or less eggs or bread crumbs. Or the shrimp cake could ha ve been prepared using raw

shrimp that was fried, instead of canned shrimp, which would change the weight loss estimate to 12

percent. Thus a participant who reported consuming a shrimp cake probably consumed somewhat

less or somewhat more than is estimate d through the calculations. Nevertheless, these data are the

best data available on a nationally representative sample.

An additional complication is that recipes may include two steps of processing; for example

, a salmon loaf may list canned salmon as an ingredient, but it is then mixed with other ingredients and

baked. Canning and baking have different moisture losses in Table 4. It was decided to use the

adjustment that indicates the greatest moisture loss and apply that to the estimation of raw weight.

In some recipes the second processing step is not categorized. We reviewed these and were able to

impute the logical unreported process (e.g., pizza is baked, soup is wet cooked in moist heat) for

many recipes ; those that remained uncategorized were assumed to have the average moisture

reduction described above.

20

# Statistical Methodology 

# 4

The NCI Method (Tooze et al., 2006 ; Tooze et al., 2010) is the preferred approach for estimating

usual dietary intake, such as usual fish consumption. NHANES has data for many individuals,

allowing fitting models with many parameters. With many individuals and many parameters, the

computation time to implement the NCI Method was unacceptable. Therefore, EPA developed an

alternate approach to estimate the usual fish consumption that requires relatively little computation

time and provides a good approximation to the results from the NCI Method . The following

sections describe both the NCI and the EPA Method s and compare the two approaches. Appendix

C provides some further discussion and Appendix D provides the macro code for estimating

parameters and simulating the UFCR

.



# 4.1 Overview of the NCI Method

The NCI Method can be used to estimate the distribution of usual intake for a population or

subpopulation. Two steps are required to estimate usual intake:

1. Fit the NCI model to the reported consumption data.

2. Calculate the usual intake from the model paramete rs.

The premise of the NCI model (step 1 above) is that usual fish intake is equal to the probability of

consumption on a given day times the average amount consumed on a day when some fish is

consumed, i.e., a “consumption day.” For episodically consumed foods, such as fish, the NCI model

consists of two parts, or sub-models. The first sub-model estimates the probability of consumption

using logistic regression with a person- specific random effect. The second sub -model uses linear

regression on a transform ed scale to estimate the consumption -day amount, also with a personspecific random effect. The two sub -models are linked by allowing the person- specific effects to be

correlated and by including common predictors in both sub-models. Data from one or more nonconsecutive 24 -hour recalls provide the values for the dependent variable. At least a subset of the

population (generally 50 or more individuals) needs to have reported fish consumption from two or

more 24

- hour recalls. Predictors related to either the probability of consumption or consumption

amount, such as gender, age, race, and income can be included in the modeling. In most cases, the

21

## most important predictor is a measure of frequency of consumption of the food of interest (in this

case, fish) obtained from a food frequency questionnaire.

In the second step, the parameters from the NCI model are used to estimate population and

subpopulation distributions of usual fish intake. The NCI Method calculates the distribution using

simulated values for the probability of fish consumption and the mean consumption amount. The

usual fish consumption (or usual fish intake) is the product of the probability of fish consumption

and the mean amount of fish consumed, when it is consumed.

Evidence for the validit y of the NCI Method has been published in a series of papers in the Journal of

the American Dietetic Association, Statistics in Medicine, and Biomet rics (Dodd et al., 2006; Tooze et al.,

2006; Tooze et al

., 2010; Kipnis et al., 2009).

The NCI Method is an improvement over other methods designed to estimate usual intake of

episodically consumed foods because it:







 

## Accounts for reported days without consumption or for consumption-day amounts that are positively skewed ;

Distinguishes within -pe rson from between-person variation;

Allows for the correlation between the probability of consumption and the

consum ption-day amount; and

Relates covariate information to usual intake

.

The su b -model predicting the probability of fish consumption in a 24-hour period is a logistic

regression model. The logistic regression model is commonly used to model the probability of an

event, such as consuming fish. The model assumes the logit- transf ormed probability is a linear

function of various continuous and discrete predictor variables. The logit transformation is

commonly used as the link between the continuous predictors and the probability of a discrete

outcome, as in logistic regression. The sub -model has two variance components, person- specific

random effects for an individual’s long-term probability of consuming fish and within- individual

binomial variation between days when fish was or was not consumed. The logit- transformed person

specifi c random effects are assumed to be normally distributed.

The amount sub-model involves a Box-Cox transformation such that the transformed amount of

fish consumed in a 24-hour recall is reasonably normally distributed. The Box-Cox transformation is

22

## a power transformation, such as raising the amount to the 1⁄4 power (taking the fourth root),

followed by rescaling to keep the variance relatively constant. In the transformed units, the amount

sub -model has two variance components, person- specific random effects for an individual’s longterm mean fish consumption and within-individual differences in the amount of fish consumed on

different days. In the transformed units, the person-specific mean fish consumption and the withinindividual daily fish consumption are assumed to have normal distributions.

The pe rson- specific random effects in the two sub

- models may be correlated, for example, those

with a higher probability of consuming fish in a 24-hour period may also tend to consume larger

daily amounts of fish. The assumption that the random effects are normally distributed is a

characteristic of the model which is not directly testable. However, the distribution of the Box-Coxtransformed reported consumption amounts is roughly normally distributed, suggesting t hat the

assumption is at least reasonable.

Both s ub-models can have additional predictors, such as person- specific demographic characteristics

and reported frequency of fish consumption. In addition, the model can incorporate the following

within -person predictors: ( 1) differences between weekends (Friday to Sunday) and weekdays

(Monday to Thursday), 1 

## and ( 2) consistent differences between the first 24 -hour recall and the

second 24-hour recall in NHANES (the first was completed in person and the second was

completed by phone).

We cons ider the NCI Method as the preferred method for estimating fish consumption rates and

believe the results to have minimal bias. However, with large sample sizes and many predictors

, the

computation time required to run the NCI Method and calculate confidence intervals was

unacceptable given the schedule and budget. Additionally, our preferred model has more predictors

than the NCI Method is set up to handle. The EPA Method was developed to provide acceptably

unbiased estimates with in a reasonable computation time. We are using non- publically available data

from NHANES that can o nly be accessed on site at NCHS. This precludes our use of alternative

computing scenarios that might reduce the computation time.

The f ollowing il lustrates the time savings. W e ran a simplified model with 4 main effects (age,

race/ethnicity, income, and frequency of fish consumption). The NCI Method took 9.5 hours for

1 

### The NCI Method includes Friday as part of the weekend. A study of CSFII data showed that intake on Friday was

more similar to Saturday and Sunday than to the rest of the weekdays, Monday through Thursday (Haines, Hama,

G uilkey, and Popkin, 2003).



## 23

## one run of one fish type. To obtain an estimate of the precision of the estimates, we need to run the

model 65 times, one for each replicate weight. This gives us an estimated time of over 25 days of

continuous computer time for each fish type. There are 18 fish types. Th erefore, to obtain estimates

for all fish types would take 450 days. The EPA Method took 1.5 minutes to run the same model,

approximately 1.5 hours for each fish type.

The NCI Method can be implemented using two SAS macros (programs) available from the NCI

web site (the MIXTRAN and DISTRIB macros). The equations fit using the NCI macros are

presented below. More information concerning the NCI Method can be found in Tooze et al., 2006,

Tooze et al., 2010, and on NCI’s web site at: http://appliedresearch.cancer.gov/diet/usualintakes/ method.html

.

EPA c reated a SAS macro to approximate the results from the NCI Method while taking

considerably less time for the calculations, referred to as the EPA Method in this report. The

following sections describe both the NCI and EPA Method s. The macro code for estimating

parameters and simulating the usual fish consumption is in Appendix D.



# 4.2 Calculation S teps for the NCI and EPA Models

4.2.1 NCI Method

In the NHANES data, each individual (indicated by i) has results from one or two 24-hour dietary

recalls (indicated by j, j = 1 or 2). In the data, most individuals have two 24-hour recalls; o nly a

portion of individuals have 24-hour recalls reporting fish consumption, and a smaller portion ha ve

two 24 -hour recalls with reported fish consumption. Using the i and j subscripts, the following

describes the statistical model fit using the NCI MIXTRAN macro. The parameters and variables

are described below. In these equations, the parameters for the probability model are represented by

π , the parameters for the amount model are represented by α , the standard deviations of the

variance components are represented by σ

.

Data for each individual and 24- hour recall, extracted from the NHANES data files follow:

 

## A ij 

## is the reported grams of fish consumed (zero if no fish consumption was reported in the 24-hour recall).

24

### 



 

## W ij 

## is an indicator of whether the 24- hour recall was for a weekday ( W ij 

## = 0 ) or weekend ( W ij 

## = 1 ).

S ij 

## indicates if the 24

- hour recall was the first (in -person, S i1 

## = 0 ) or the second (by
phone, S i2 

## = 1 ) dieta ry recall.

X ik 

## represent k individual level covariates (demographic variables ; see Section 4.5 for additional details).

Transformed data :



 

## C ij 

## is an indicator for reported fish consumption in a 24-hour recall (1 indicates fish consumption, otherwise 0). This is the dependent variable in the logistic probability

model. {

T

ij 

## is the amount of fish consumed after being transformed using a Box-Cox power transformation. This is the dependent variable for the linear regression model predicting the consumption-day amount of fish consumed.

Parameters for the probability sub -model:











 

## π 0 

## is the intercept par ameter for the probability model.

π

Xk 

## is a vector of regression parameters for the k person

- specific covariates in the

pro bability model

.

π W 

## is the regression parameter for the difference between weekend and weekday days.

π

S 

## is the regression parameter for the difference between the second 24 -hour recall and

the first 24

- hour recall.

π i 

## is the person-specific random effect for the probability model, assumed to be normally distributed on the logit scale. This value has theoretical meaning but is not

observed.

P

ij 

## is the probability of fish consumption for a 24- hour recall. This value has theoretical meaning but is not observed.

25

## Parameters for the amount sub -model:













 

## λ is the power used for the Box-Cox transformation

.

α 0 

## is the intercept parameter for the amount model.

α Xk 

## is a vector of regression parameters for the k person

- specific covariates in the

amount model

.

α W 

## is the regression parameter for the difference between weekend and weekday days.

α S 

## is the regression parameter for the difference between the second 24 -hour recall and

the first 24

- hour recall.

α i 

## is the person-specific random effect for the amount model, assumed to be normally distributed. This value has theoretical meaning but is not observed.

α ij 

## is the within -person random effect for the amount model representing different amounts for fish consumed on different days, assumed to be normally distributed. This value has theoretical meaning but is not observed.

Variance and correlation parameters :







 

## σ 1 2 

## is the variance of the person

- specific random effect in the probability model ( π i 

## )

.

σ

2 2 

## is the variance of the person

- specific random effect in the amount model ( α i 

## )

.

ρ is the correlation between π i 

## and α i



## .

σ

3 2 

## is the variance of the within -person random effect in the amount model ( α ij 

## )

.

The NCI macro fits some preliminary models to obtain approximate parameter estimates to use as

starting values for the NLMIXED procedure (a SAS procedure that fits non-linear mixed models),

which fits the following set of equations simultaneously, using maximum likelihood. The following

equations describe the model fit using the NCI Method . The tilde (~) symbol can be read as “is

distributed as. ”

( ) ( )

( )

( )

[ ] ( [ ] [ ])

26

## The NCI model can be fit assuming the probability of consuming fish and the amount of fish

consumed, if consu med, are uncorrelated, i.e., ρ = 0. However, we assume these values may be

correlated and thus specified a correlated model when using the NCI Method to compare the NCI

and EPA Method results.



# 4.2. 2 EPA Method

The EPA and NCI Method s differ as follows:









 

## As part of fitting the model, t he NCI Method finds the power transformation ( λ ) that best fits the data and is consistent with the assumption that the variance components are normally distributed, as judged by maximum likelihood. The EPA Method finds the power transformation that makes the transformed fish consumption amounts ( T ij 

## ) roughly normally distributed as judged by the correlation between the transformed amounts and the expected values for a normal distribution. The power with the highest

corre lation is then used when fitting the amount sub-model.

The EPA Method assumes the person- s pecific random effects in the probability and

amount sub- models are uncorrelated . The assumption of zero correlation is for computational convenience, not because these values should be uncorrelated. When using the NCI Method , we assume d these random effects may be correlated and let the NCI algorithm estimate the correlation. The correlation estimates were generally close

to zero.

When assuming the person- sp ecific ra ndom effects are uncorrelated, the two sub

models can be fit separately rather than simultaneously . The EPA Method fits the two models separately.

For the probability sub -mode l, the NCI model fits the parameter values and random

effects in one non- linear m ixed model. The EPA Method approximates that approach using two steps: ( 1) using logistic regression without random effects to estimate the parameter values and calculate predicted values (in the logit scale); and ( 2) using a nonlinear mixed model to fit the random effects using only the predicted values from the previous logistic regression as a predictor.

For the amount sub-mode l, the NCI Method fits the parameter values , transformation,

and random effects in one non- linear mixed model. The EPA Method approximates that approach by (1) selecting the transformation as described above; ( 2) using linear regression without random effects to estimate the parameter values and calculate predicted values ; and ( 3) using a non-linear mixed model to fit the random effects using the predicted values from linear regression as the only predictor.

27

## The equations for the EPA Method are described below using the same notation as above for the

NCI Method . The EPA Method has the following steps:

1. Estimate λ

.

2. Use logistic regression to predict the probability of fish consumption as a function of various predictors; save the predicted values

.

3. Use a non- linear mixed model to estimate the person- specific variance component using the predicted values from logis tic regression as the predictor.

4. Use linear regression to predict the Box-Cox-transformed amount of fish consumed, when consumed, as a function of various predic tors; save the predicted values

.

5. Use a non-linear mixed model to estimate the variance components for the amount model using the predicted values from linear regression as the predictor.

In the NCI Method , the maximum likelihood procedure finds the best transformation, defined by λ

, consistent with the data and the assumption that the random effects are normally distributed. In the

EPA model, λ = λ ∗ 

## is set prior to fitting the amount sub-model, using the following steps:

1. Calculate normal scores associated with each observation by first, ignoring the distinction between the first and second recall; second, for amounts greater than zero, summing the weights across tied values (values with the same reported amounts) to get one record for each unique amount ( A
r 

## ) and the associated weight ( W
r 

## ); third, sorting the R unique amounts from smallest to largest; fourth, calculating cumulative weight for the each unique value, S
r 

## = ∑ W
m r m=1 

## ; and fifth, calculating the normal scores as ( )

2. Using values of λ ∗ 

## which are multiples of 0.01 between

- 0.20 and 0.30, find the λ ∗ 

## value

, which maximizes the Pearson correlation between Z
r 

## and { ( )

( )



## w here G is the geometric mean of A
r 

## . This form of the Box-Cox transformation allows

λ ∗ 

## = 0 , corresponding to using a log transformation.

3. If λ ∗ 

## = 0 then set λ ∗ 

## = 0. 005 (this case was encountered for marine tropic level 2 fish ).

28

## Table 5 shows the λ ∗ 

## values used for each of the dependent variables.

Table 5. λ ∗ 

## values used for each combination of dependent variable and data set

Dependent variable λ ∗



### All fish 0.2 1

Marine fish 0.2 4

Estuarine fish 0.1 3

Freshwater fish

- 0.04

Finfish 0.2 5

Shellfish 0.1 1

Freshwater + e stuarine fish 0.1 1

Marine + e stuarine fish 0.2 1

Marine + f reshwater fish 0.2 1

Trophic level 2 fish 0.1 1

Trophic level 3 fish 0.1 6

Trophic level 4 fish 0. 20

Marine trophic level 2 fish 0.005

Marine trophic level 3 fish 0. 09

Marine trophic level 4 fish 0.2 3

Freshwater + e stuarine trophic level 2 fish 0. 08

Freshwater + e stuarine trophic level 3 fish 0.1 2

Freshwater + e stuarine trophic level 4 fish

- 0.0 5



## For t wo ty pes of fish consumption (f reshwater and freshwater plus estuarine trophic level 4), λ ∗ 

## was

less than zero. The NCI Method constrains λ to be greater than 0.01. As a result, the results from

the NCI Method and the EPA Method differ somewhat when λ ∗ 

## < 0. 01

.

The transformed consumption amounts for 24 -hour recalls with reported fish consumption are
shown in the following equation:

T ij 

## = A ij λ ∗



## − 1

λ ∗



## To est imate the probability of consumption, the following logistic regression model was fit using the

SAS SURVEYLOGISTIC procedure and the NHANES survey weights, strata, and PSU variables.

This logistic regression model predicts the probability of consumin g fish in a 24 -hour recall without

considering a person- specific random effect; B ij ′ 

## is the linear predictor of the logit transformed

probability. The apostrophes indicate values from the logistic model that has no random effects.

29

## ( ) ( )

The person- spe cific random effect is included by assuming the predicted logit ( B ij 

## ) when in cluding

the random effect is proportional to the predicted logit when ex cluding the random effect ( B ij ′ 

## )

.

This approximation is justified in Appendix C

. The following non- linear mixed model is fit to

estimate the variance of the person -specific random effect and the inflation factor ( β ) for scaling the

parameter estimates from the model abo ve.

( ) ( )

( ) ( )

The SAS SURV EYREG procedure is used to fit the amount sub-model assuming no person- specific

random effect. The variance of the regression error ( σ 4 2 

## ) is the combination of the variance of the

person- specific random effect and the within -person variation. D ij 

## is the linear predictor of the

transformed amount of fish consumed.

If A ij 

## > 0 th en T ij 

## = A ij λ ∗



## − 1

λ ∗ 

## = α 0 

## + X ik 

## α Xk 

## + W ij 

## α W 

## + S ij 

## α S 

## + a ij ′ 

## = D ij 

## + a ij ′



## a ij

′



## ~ Normal ( 0, σ 4 2 

## )

The variance of the within -person and between-person variance components is estimated using a

non-linear mixed model with the linear predictor from the regression above as the only predictor.

If A ij 

## > 0 th en T ij 

## = A ij λ ∗



## − 1

λ ∗ 

## = D ij 

## + α ij 

## + α i



## α ij 

## ~ Normal 0, σ 3 

## , α i 

## ~ Normal 0, σ 2 

## ( 2 

## ) ( 2 

## )

Because of d ifferent estimation methods, the parameters calculated using the NCI Method are
slightly different than those from the EPA Method.

30

# 4.3 Simulation of the Usual Fish Consumption

The distribution of usual fish consumption can be calculated from the model parameters. Due to the

complexity of the model, the direct calculation of the distribution of usual fish consumption

i nvolves numerical integration and is relatively complex. The integration is simplified by ( 1)

simulating values of usual fish consumption and ( 2) calculating mean and percentiles of fish

consumption rates from the simulated values. When using simulations, the estimated fish

consumption rates have a small random component that can be reduced by increasing the number

of simulations. The default number of simulations in the NCI DISTRIB macro is 100. Analysis of

preliminary results showed that the precision of the parameter estimates increased as the number of

simulations increased; however, the precision was similar when using either 50 or 100 simulations.

The final analysis used 100 simulated fish consumption values for each NHANES respondent. The

NHANES data set provides the population distribution of the independent predictors in the

probability and amount sub-models

. For each NHANES respondent, the simulated values represent

possible fish consumption rates for a respondent with the same independent predictor s as the

NHANES respondent.

Because usual fish consumption is different from reported fish consumption, the equation used to

simulate usual fish consumption is slightly different from the equation fit to the data from the 24-

hour recalls. The equation fit to the data was modified as follows to simulate usual fish

consumption:





 

## The simulated values reflect a standard week (3 weekend days and 4 weekday days) rather than the distribution of weekday and weekend recalls in the data. Given Friday is part of the weekend, the average for the standard week would be 4/7 x ( w eekday average) + 3/7 x ( w eekend average). Since the weekend parameter models the difference between the three weekend days and the four weekday days, this average can be obtained by setting the p arameter for the weekend variable to 3/7.

The simulated values assume the first (in

- person) 24-hour recall is unbiased by ignoring
the difference between the first and second recall, i.e., α S 

## = π S 

## = 0

.

The simulated values do not include the within-per son variation, i.e., binomial variation within persons in the probability model and the within-person variation in the amount

model

.

The equations for simulating usual fish consumption use the parameters estimated from the models

predicting probability of reported fish consumption and the amount for fish consumed, when

consumed.

31

## In the equations below, the V subscript represents the simulation number (V = 1 to 100). The

following equations are used by the NCI DISTRIB macro to simulate an individual’s long- term
probability of fish consumption ( Q Vi 

## ) and transformed long-term mean fish consumption when fish

is consumed ( T Vi 

## ); the logistic function is the inverse of the Logit function. ( )

T

Vi 

## = α 0 

## + X ik 

## α Xk 

## + α Vi 

## + 3

7 π W



## [ ] ( [ ] [ ])

A sli ghtly modified version of these equations is used in the EPA procedure because the EPA

approach uses a two -step procedure with the inflation factor ( β ) to fit the probability model and

assumes the random effects are uncorrelated. The EPA equations are as follows: (( ) )

T

Vi 

## = α 0 

## + X ik 

## α Xk 

## + α Vi 

## + 3

7 α W



## [ ] ( [ ] [ ])

Fi nally, the simulated transformed consumption amounts are untransformed using the following

equation (see Tooze et al., 2010):

B Vi 

## = ( T Vi 

## λ + 1 ) ( 1 / λ ) 

## + σ 3 2 

## ( 1 − λ )

2 ( T Vi 

## λ + 1 ) ( 1 / λ −2 )



## This equati on includes an adjustment involving the within person variance in the fish consumption

amount ( σ 3 2 

## ). The NCI Method assumes the reported fish consumption amounts in the 24-hour

recalls are unbiased. This adjustment makes the untransformed usual fish consumption essentially

unbiased.

32

## Although when A ij 

## = 0 , the transformed fish consumption is defined ( T ij 

## = −1

λ 

## ), it is possible to

simulate a value of T Vi 

## such that T Vi 

## < −1

λ 

## , for which the untransformed value is not defined. In the

NCI macro, these small simulated values in the transformed scale are set to half of the minimum

reported fish consumption for any 24-hour recall. The same procedure is used in the EPA

calculations. The probability that T Vi 

## < −1

λ 

## depends on several factors

. The expected probability is

less than or equ al to 1/N, where N is the number of respondents with reported fish consumption.

In preliminary analysis, no values were set to half the minimum reported value.

The us ual fish consumption for a simulated person is then:

U Vi 

## = Q Vi 

## B Vi



## The following summary statistics for the usual fish consumption were calculated using the simulated

values ( U Vi 

## ) and the NHANES analysis weights: mean and 25 th , 50 th , 75 th , 90 th , 95 th , 97 th , and

99 th percentiles.



# 4.4 Calculation of Standard Errors and Confidence Intervals

Both the NCI Method and the EPA Method use the NHANES survey weights for all the

calculations (i.e., weighted regressions and weighted estimates of the variance components). The

NHANES survey weights are inversely proportional to the probability of selection for each

respondent. The survey weights are adjusted for nonresponse and allow for calculation of national

estimates.

The SURVEYLOGISTIC and SURVEYREG procedures calculate standard errors for only the

linear parameters in the models, using a Taylor series linearization approach. These standard errors

were used to select the independent predictors for the probability and amount models. Standard

errors for all EPA and NCI Method parameters, including the random effects and percentiles of the

distribution of usual fish consumption, can be calculated by ( 1) preparing replicate weights

consistent with the NHANES survey design and strata and PSU variables; (2) running the macros

using the full- sample weight and each replicate weight; and (3) combining the results using each

weight to estimate the standard errors. EPA constructed replicate weights for calculating the

standard errors and confidence intervals for percentiles of usual fish consumption. See Wolter, 1985

, for a discussion of variance estim ation procedures for complex survey designs such as NHANES.

33

## In general, the variance of the weighted estimates from the NCI Method or the EPA Method can be

calculated by repeatedly dividing the sampling PSUs into subgroups (or replicates) and comparing

th e estimates from each subgroup to the estimate for the entire sample. Several approaches have

been developed to efficiently estimate the variance with a minimum number of carefully constructed

subgroups. In general, dividing the respondents into subgroups can be achieved by creating an

analysis weight for each subgroup, i.e., a replicate weight. One such approach is Balanced Repeated

Replication (BRR) which divides the PSUs into two equal size groups on each division. A

modification of the basic BRR method due to Fay compares a weighted estimate from one half of

the PSUs to a different weighted estimate for the other half of PSUs . The Fay approach was selected

because it has advantages when estimating percentiles. The replicate weights for the BRR method

usi ng the Fay factor adjustment (Fay factor K = .3) were created using standard procedures (see

Judkins

, 1990) and the strata and PSU variables in the NHANES files provided for variance

estimation. The basic BRR procedure assumes two PSU values in each strat um . However, a few of

the NHANES strata have three PSU values , which required slightly modified calculations for

creating the weights (Wolter, 1985; Rust, 1986 ). We created 64 replicate weights. Parameter estimates

were calculated using the NHANES (full sample) weight and each of the replicate weights.

Given the replicate BRR weights, t he variance of an estimate of θ can be calculated using the steps

below; θ might be a regression parameter, an estimated percentile of usual fish consumption, or the

log-transformed percentile of usual fish consumption.

1. Calculate θ using the full sample NHANES weight and using each of the 64 replicate weights ( θ g 

## , g = 1 to G, G = 64), and

2. Calculate the variance of θ as

( ) ( ) ∑( )

3. A 95 percent confidence interval for is √ ( ) √ ( )

.

Various summary statistics (means and percentiles) are calculated using the simulated usual fis h

consumption values. Since the usual fish consumption estimates are generally skewed with a roughly

lognormal distribution, calculating the confidence intervals on the log scale appears reasonable and

has the beneficial effect that confidence limits cannot be negative. As a result, the confidence

intervals for the summary statistics are calculated by ( 1) fitting the EPA Method using the full

sample weight and each replicate weight; ( 2) log

- transforming the estimates; ( 3) calculating the

34

## confidence interval s for the estimates assuming a normal distribution using the equations above; and

( 4) un -transforming the confidence interval bounds.

See Gilbert (1987) for additional comments on calculating confidence intervals for log-normally

distributed values.



# 4. 5 Application of EPA Method

The EPA Method was used to model and predict usual consumption for the following types of fish

and shellfish:



































 

## Total finfish and shellfish;

Finfish ;

Sh ellfish ;

Marine fish ;

Estuarine fish ;

Freshwater fish ;

Freshwater + estuarine fi sh ;

Marine + estuarine fish ;

Marine + freshwater fish ;

Trophic level 2 fish ;

Trophic level 3 fish ;

Trophic level 4 fish ;

Freshwater + estuarine trophic level 2 fish ;

Freshwater + estuarine trophic level 3 fish ;

Freshwater + estuarine trophic level 4 fis h;

M arine trophic level 2 fish ;

Marine trophic level 3 fish ; and

M arine trophic level 4 fish

.

35

## All models included the weekend indicator and the indicator of the first or second recall for both the

amount and probability sub-models.

Other candidate varia bles for inclusion into the models included the following:















 

## Age group: 1 to < 3, 3 to <6, 6 to < 11, 11 to < 16, 16 to <18, 18 to < 21, 21 to <35, 35 to <50, 50 to <65, and 65 years and older;

Income: $0 to <$20K, $20 to <$45K, $45 to <$75K, $75K+, >$20k, R efused/DK Income, Income Missing;

Male: an indicator, 1 = male 0 = female;

Race/Ethnicity: Mexican American, other Hispanic, non-His panic white, non-Hispanic black, and other race;

Region: U.S. Census regions (Northeast, Midwest, South, and West);

Coastal Status: Coastal counties and non- c oastal counties;

Bodyweight, log- tra nsformed; and

Reported frequency of fish consumption in 30 days ( Fis h3 0 ), transformed

.

Based on preliminary analysis, the following transformations were used : for the probability submodel: Ln ( Fis h 30 + 0.1 ) and for 

## the amount sub-model: Fis h 30 0

. 45



## .

The following process was used to select the final predictors for the models:

1. For each dependent variable, start with all main effects, sequentially drop the least significant main effect until all remaining main effects are significant at the 5 percent
level

.

2. Use any main effects that were selected when predicting any dependent variable

.

3. For each dependent variable, include the selected main effects and all two

- way interactions of t he selected main effects, sequentially dropping the least significant interaction until all remaining interactions are significant at the 1 percent level

.

4. Use any two

- way interaction selected for predicting at least t hree of the dependent

variables.

The selected main effects and two

- way interactions were then used as independent predictors in the

final models predicting all the dependent variables.

36

## The procedure above was performed separately for the amount model and the probability model.

The significan ce was based on the SURVEYLOGISTIC and SURVEYREG output.

The final list s of independent variables for the probability and amount sub-models follow:



 

## Probability Sub -M odel : reported frequency of fish consumption (transformed), bodyweight (log- transformed) , race/ethnicity, income, age group, region, coastal status, race/ethnicity*income, race/ethnicity*age group, income*age group, income*region, income*coastal status, and age group*region

Amount Sub

- mo del : reported frequency of fish consumption (transformed ), bodyweight (log- transformed), race/ethnicity, male, age group, region, coastal status, race/ethnicity*age group, race/ethnicity*region, male*age group, age group*region, and age group*coastal status

The simulated usual fish consumption values were summarized by the following demographic

categories:





















 

## Gender;

Age group;

W omen of childbearing age (13 t o 49 years) ;

Race ;

Income;

Region;

Coastal status ;

Four c oastal regions (Atlantic, Gulf of Mexico, Pacific, and Great Lakes) ;

Four inland regions (Inland Northeast, Inland Midwest, Inland South, Inland West);

Yo uth (<21 years of age) by gender, race, income, region, coastal status, coas ta l regions, and inland regions; and

Adults (≥21 years of age) by gender, race, income, region, coa st al status, coastal regions, and inland regions.

When fitting the NCI and EPA Methods, the distribution can be sensitive to the magnitude of the

variance components. With small sample sizes, the number of respondents with reported fish

consumption on two 24

- hour recalls can be small resulting in imprecise variance estimates and

37

## possible convergence problems. The authors of the NCI Method (Kipnis et al., 2009) generally

recommend having at least 50 respondents with at least two 24 -hour recalls with reported

consumption of fish (or whatever dietary component is being assessed).

The NCI and EPA Methods can be applied to all NHANES respondents or to subsets, such as

subsets defined by demographic characteristics. Fitting one model using all NHANES respondents

implicitly assumes that the magnitude of the variance components are the same for all individuals

and do not vary by, say, demographic characteristics. Fitting all respondents has the advantage that

there are plenty of individuals from which to estimate t he variance components. Fitting the models

separately by subset allows the variance components to be different for different subsets of

individuals. However, small subsets may not have adequate numbers of individuals with two recalls

with fish consumption. After considering the trade- offs, the EPA Method was applied to all

NHANES respondents. For each fish type, the subgroup estimates were derived from simulated

usual fish consumption values and the associated demographic covariates and sampling weights for

the NHANES respondents

.



# 4.6 Comparison of Results from the EPA and NCI Methods

In order to evaluate how estimates from the EPA Method compared to estimates from the NCI

Method, we ran both methods using different dependent variables, different sets of independent

predictors, and different numbers of simulated values. The procedures used to evaluate the EPA

Method and to compare the two methods are described in this section.



# 4.6.1 Analysis of S imulated D ata

Fish consumption data (both usual intake an d reported intake) were simulated consistent with the

model assumed by the NCI Method . Ideally, when analyzing the simulated data, parameter estimates

from the NCI and EPA Method s will agree with the parameters used to simulate the data and the

estimated percentiles of usual fish consumption will agree with the corresponding percentiles in the

simulated data. Differences can indicate programming errors or possible bias associated with to the

estimation method. Different scenarios were used to evaluate the EPA Method , with good

agreement between the parameter estimates and percentiles compared to the values used to simulate

the data.

38

## As an illustration, the following plots (Figure 1) show how the parameters and percentiles from the

NCI and EPA Methods compare to the simulated values for data with six different Box-Cox

transformations (Lambda =

- 0.12,

- 0.06, 0.06, 0.12, 0.18, and 0.30). For these simulations, the other

parameters we re set to values similar to those found when analyzing freshwater fish for adults (for

which Lambda =

- 0.06), with the exception that the intercept for the probability was increased

somewhat to raise the number of simulated individuals with two 24-hour rec alls with fish

consumption. The plots show the percentile estimates derived from the NCI and EPA models

compared to the values from the simulated data. The plots and analysis suggest that the EPA

Method provides a good approximation to the NCI Method and t he true values when lambda is

greater than zero ; and, for negative lambda, the EPA Method appears to provide better estimates

than the NCI Method when compared to the true values. It should be noted that ( 1) for positive

lambda, whether the NCI or EPA estimates are closer to the true value is different for different

simulated data sets using the same simulation parameters ; (2) for negative lambda, the NCI and EPA

Methods provide more similar results when the magnitudes of the variance components are smaller;

and ( 3) the NCI Method could be modified to allow for negative lambda values.



# 4.6.2 Confidence Intervals for Percentiles of Fish Consumption

Figure 2 shows confidence intervals for parameters and percentiles of fish consumption, calculated

using both the NCI and EPA Methods. Due to the long computation time required for the NCI

Method, only simple models with few predictors were used. The confidence intervals were

calculated for freshwater and estuarine fish consumption by all respondents, marine fish

consumption by all respondents, and shellfish consumption by adults. The predictors are

transformed frequency of fish consumption in the past 30 days, an indicator of weekend versus

weekday, and the difference between the first and second recall. The first column in Figure 2

compares parameter estimates and confidence intervals. The second column compares percentile

estimates and confidence intervals for various percentages and demographic groups. In general,

there is good agreement between both the NCI and EPA estimates and the width of the confidence

intervals.

39

## Figure 1. Comparison of NCI, EPA, and true percentiles using simulated data and different

transformations



## 40

## Figure 2. Comparison of confidence intervals using the NCI and EPA M ethod s



## 41

# 4.6.3 Analysis of NHANES Fish Data Using Various Models

NHANES fish consumption data were analyzed using the NCI and EPA Method s with different

sets of independent predictors and different numbers of simulations. These comparisons between

the EPA and NCI Method s were selected to represent a range of fish types. Each dependent

variable was predicted by different independent variables to assess the effect of the choice of

predictors and the number of parameters on the results, all using 50 simulations. Comparisons were

also run using different numbers of simulations to assess how many simulations to use. Table 6

summarizes the result s followed by example plots comparing the percentile estimates from the two

methods.

For each of the comparisons, Table 6 shows the following values:

















 

## Pred Vars: the independent predictors, F = transformed frequency of fish consumption, A = Age groups, I = Income groups, R = Race groups, and M = Male indicator.

Sim Num: the number of simulated values of usual fish consumption generated for each

i ndividual.

Geo Mean Ratio (EPA/NCI): The geometric mean ratio of the EPA percentile to the

NC I percentile across multiple percentiles and population subgroups. A ratio of 1.00 corresponds to no difference between the geometric means, on average.

RMSE ( percent): The RMSE difference between the log

- transformed EPA and NCI percentiles estimated across multiple percenti les and population subgroups, converted to a percentage difference. This can be thought of as the average absolute percent difference between the NCI and EPA percentiles. Smaller values are better. Larger values are generally associated with fish types tha t are consumed less often.

90 th p ercentile (Adults≥21) : the 90 th percentile of fish consumption (a value of particular interest to EPA) calculated using the NCI and EPA Method s.

Rel. Time (NCI/EPA): the computation time for the NCI Method r elative to the E PA Method. These values are not precise and depend on what other programs were running

at the same time.

Num Parms (NCI): the number of parameters in each model

.

NCI Lambda: the power for the Box-Cox transformation estimated using the NCI

Method.

EPA lambda: the power for the Box-Cox transformation used in the EPA Method.

42

###  

## NCI Rho: The correlation between the person -specific random effects in the probability

and amount sub- models, as estimated by the NCI Method

.

Note that the geometric mean ratio, R MSE, and percentiles in the table are subject to random

variation associated with the simulation process. As a result, somewhat different values would be

obtained if the calculations were repeated.

Table 6. Comparison of NCI and EPA m e thod s using NHANES f ish data

Fish ty pe Pred.

va rs Sim

n um Geo me an

r atio

(EPA/ NCI) RMSE

(%) 90th percentile
(Adults≥21) Rel. t ime

(NCI/

EPA) Num

p arms NCI

lambda EPA

lambda NCI

Rho 

### EPA NCI

All Fish F 5 1.008 5.258 48.77 49.89 13.5 13 0.210 0.21 0.17

All Fish F 10 1.008 4.690 49.64 49.36 12.4 13 0.210 0.21 0.17

All Fish F 20 1.006 4.367 49.13 49.92 10.1 13 0.210 0.21 0.17

All Fish F 50 1.004 4.084 49.08 49.73 5.7 13 0.210 0.21 0.17

All Fish F 100 1.003 4.230 49.14 49.82 2.5 13 0.210 0.21 0.17

All Fish FA 50 1.002 4.005 51.62 52.51 44.7 31 0.208 0.21 0.18

All Fish FAIRM 50 1.001 4.361 51.59 52.47 170.2 53 0.211 0.21 0.25

Finfish F 50 1.006 2.803 36.98 36.13 8.7 13 0.255 0.26 0.03

Finfish FA 50 1.016 14.544 38.37 41.00 26.0 31 0.252 0.26

- 0.01

Finfish FAIRM 50 1.010 12.936 38.51 40.85 118.2 53 0.256 0.26

- 0.07

Fresh F 50 1.030 36.877 6.70 6.47 8.3 13 0.010

- 0.04

- 0.21

Fresh F 50 0.8 72 21.225 5.92 6.49 9.57 13 0.010 0.01

- 0.2 1

Fresh FA 50 1.049 35.486 7.43 7.12 77.3 31 0.010

- 0.04

- 0.19

Fresh FAIRM 50 1.022 36.953 7.14 6.83 303.7 53 0.010

- 0.04

- 0. 26

FWEst F 5 0.987 4.746 20.04 20.03 17.2 13 0. 1 05 0.11 0.15

FWEst F 10 0.992 4.092 20.35 20.41 13.7 13 0.105 0.11 0.15

FWEst F 20 0.992 2.781 20.19 20.40 6.6 13 0.105 0.11 0.15

FWEst F 50 0.995 2.500 20.27 20.38 8.3 13 0.105 0.11 0.15

FWEst F 100 0.991 2.361 20.23 20.38 2.4 13 0.105 0.11 0.15

FWEst FA 50 0.991 2.998 21.81 22.12 64.6 31 0.104 0.11 0.16

FWEst FAIRM 50 0.995 2.465 21.91 22.07 290.1 53 0.106 0.11 0.15

Marine F 5 1.010 8.605 31.16 32.10 11.9 13 0.218 0.23 0.15

Marine F 10 1.003 8.017 30.96 31.76 8.5 13 0.218 0.23 0.15

Marine F 20 1.013 7.336 31.09 32.01 3.6 13 0.218 0.23 0.15

Marine F 50 1.006 7.596 30.96 31.84 5.5 13 0.218 0.23 0.15

Marine F 100 1.005 7.641 31.11 31.93 1.9 13 0.218 0.23 0.15

Marine FA 50 1.008 7.410 32.39 33.24 22.1 31 0.218 0.23 0.15

Marine FAIRM 50 1.004 7.747 32.17 33.10 126.9 53 0.220 0.23 0.18

Shellfish F 5 0.980 4.629 14.00 14.20 21.5 13 0.112 0.11 0.50

Shellfish F 10 0.988 4.262 14.17 13.98 19.6 13 0.112 0.11 0.50

Shellfish F 20 0.990 3.560 14.07 14.05 10.5 13 0.112 0.11 0.50

Shellfish F 50 0.988 3.059 14.06 14.03 10.1 13 0.112 0.11 0.50

Shellfish F 100 0.987 3.194 14.06 14.03 3.9 13 0.112 0.11 0.50

Shellfish FA 50 0.988 3.508 15.34 15.23 48.6 31 0.112 0.11 0.50

Shellfish FAIRM 50 0.991 3.542 15.40 15.28 228.1 53 0.111 0.11 0.50



## 43

## For freshwater and freshwater and estuarine trophic level 2

, the lambda estimated using the EPA

Method was less than zero (only freshwater is shown in Table 6) . The NCI Method constrains

lambda to be greater than 0.01. For freshwater fish consumption, the model with frequency of fish

consumption as the only predictor was run using the transformation selected for the EPA Method

, λ ∗ 

## =
− 0. 04 , and with λ ∗ 

## = 0. 01 , the transformation used in the NCI Method (see the yellow

shaded cell). When the preferred transformation corresponds to a negative lambda, the EPA and

NCI Method s give different results (see the cells with the dark border with high RMSE), although

the 90th percentiles are relatively close. Based on the simulations in Figure 1 , the EPA percentiles

appear to be preferred to the NCI percentiles when lambda is less than 0.01.

Analysis of the data in Table 6 suggests the following:













 

## Relative to the NCI estimates, the percentile estimates from the EPA Method are essentially unbiased (the average of the geometric mean ratio is 0.9923 , using only rows with 50 simulations and excluding the cases with negative lambda).

The results from the EPA Method are acceptably close to those from the NCI Method :

t he average RMSE is 6.5 percent (using only rows with 50 simulations and excluding the cases with negative lambda).

There is little additional reduction in RMSE when using more than 50 simulations . The

final runs used 100 simulations.

Uncertainty in the estimated percentiles is associated with ( 1) the NHANES sampling error (represented by the confidence intervals) ; (2) selection of independent predictors (which depends in part on what variables are available) ; ( 3) which analysis method is used (EPA versus NCI) ; and (4) the number of simulations. These sources of uncertainty are ordered roughly from most to least important.

The transformation (λ) estimated for the EPA model is very close t o the transformation estimated in the NCI model. Differences in lambda do not explain differences in the

90 th percentiles from the two procedures.

The estimated correlation between the variance components (Rho) is not significantly

co rrelated with the difference between the 90 th percentiles from the NCI and EPA

Method s.

Computation time for the NCI Method r elative to the EPA Method increases significantly with increasing numbers of parameters.

The shaded rows in Table 6 correspond to the example plots shown in Figure 3. These plots were

selected to show the comparison with the best RMSE, the median RMSE, and the worst RMSE

among models with positive lambda and 50 simulations, and the comparison for fresh water fish, for

which the lambda estimated using the EPA Method is negative. Figure 3 shows EPA versus NCI

mean s and percentiles for different subpopulations.

44

## Figure 3. Comparison of NCI and EPA percentiles of fish consumption rates



## 45

# Results 

# 5

This section presents the sample sizes and the estimated UFCR (raw weight, edible portion) for all

fish, freshwater + estuarine fish, marine fish, all finfish, all shellfish, trophic level 2 fish, trophic level

3 fish, trophic level 4 fish, trophic level 2 freshwater + estuarine fish, trophic level 3 freshwater +

estuarine fish, and trophic level 4 freshwater + estuarine fish, for adults and youth, by demographic

characteristics and geograph ic area . Full tables including UFCR for the total population (youth and

adults combined), adults only, and youth only are in Appendix E. Appendix F contains the U FCR

for as prepared weights. The fish types selected to be presented in the body of the report represent

those that are of most interest to EPA, states, and tribes.

Note that the adult population is defined as people aged 21 years and over. The US EPA Exposure

Factors Handbook classifies those aged 21 years and over as adults. Children are grouped as follows:

1 to <3 years, 3 to <6 years, 6 to <11 years, 11 to <16 years, 16 to <18 years , and 18 to <21 years.

Note that children 1 to <2 and 2 to <3 were com bined due to small sample sizes for these age

groups.



# 5.1 Sample Size

Table 7 presents the sample sizes for each subpopulation that reported fish consumption on at least

one 24 -hour recall. An expanded table that includes the other fish types for which r ates were
calculated can be found in Appendix G.

46

## Table 7. Sample s ize and n umber r eporting f ish c onsumption, by f ish t ype

N Any

f ish FW+

Est Marine Fin

fish Shell

fish Trophic

l evel 2 Trophic

l evel 3 Trophic

l ev el 4

Total 29,463 6

, 891 4

, 868 6

, 286 5

, 095 2

, 612 2

, 706 4464 4

, 578

Gender

Female 15,694 3

, 807 2

, 667 3

, 495 2

, 792 1

, 448 1

, 495 2

, 435 2

, 521

Male 13,769 3

, 084 2

, 201 2

, 791 2

, 303 1

, 164 1

, 211 2

, 029 2

, 057

Age, years

1 to <3 2,325 345 198 305 269 101 111 209 243

3 to <6 2,185 350 196 322 272 106 118 225 246

6 to <11 2,705 454 264 416 351 137 143 286 315

11 to <16 2,806 445 310 402 301 179 180 296 273

16 to <18 1,417 252 177 237 164 104 98 173 155

18 to <21 1,662 311 208 294 209 132 131 209 199

21 to <35 4,381 1

, 070 801 992 723 509 531 745 651

35 to <50 4,522 1

, 332 997 1

, 221 962 546 566 883 848

50 to <65 3,730 1

, 216 901 1

, 101 938 454 468 775 842

65 and older 3,730 1

, 116 816 996 906 344 360 663 806

WCA a 

### (13 to 49 years) 7,870 1,919 1,421 1,785 1,409 768 839 1,300 1,179

Income

<$20k 6,679 1

, 374 897 1

, 256 1

, 043 470 491 911 936

$20k to <$45k 8,955 1

, 969 1

, 382 1

, 775 1

, 442 732 792 1

, 286 1

, 263
$45k to <$75k 5,561 1

, 334 959 1

, 211 1

, 002 498 511 856 904

$75k and over 6,288 1

, 768 1

, 308 1

, 634 1

, 285 739 740 1

, 108 1

, 176

>$20k 825 203 151 182 144 81 86 140 126

Ref/DK income b 

### 808 164 118 153 122 61 57 111 117

Income missing 347 79 53 75 57 31 29 52 56

Race/Ethnicity

Mexican American 6,868 1

, 350 949 1

, 212 937 535 618 886 828

Other Hispanic 2,405 532 351 490 390 187 202 329 350

Non

- Hispanic white 11,980 2

, 678 1

, 854 2

, 509 2

, 000 1

, 023 1

, 006 1

, 573 1

, 855

Non

- Hispanic black 6,734 1

, 818 1

, 308 1

, 603 1

, 376 654 669 1

, 291 1

, 188

Other race 1,476 513 406 472 392 213 211 385 357

U.S. Region

Midwest 6,445 1

, 235 821 1

, 070 938 400 431 773 853

Northeast 4,475 1

, 202 805 1

, 154 867 484 445 733 812

South 1 1,036 2

, 688 1

, 925 2

, 416 2

, 003 1

, 036 1

, 087 1

, 828 1

, 739

West 7,507 1

, 766 1

, 317 1

, 646 1

, 287 692 743 1

, 130 1

, 174

Coastal Status

Noncoastal 17,251 3

, 719 2

, 532 3

, 377 2

, 813 1

, 287 1

, 345 2

, 363 2

, 566

Coastal 12,212 3

, 172 2

, 336 2

, 909 2

, 282 1

, 325 1

, 361 2

, 101 2

, 012

US Coastal/Inland

Region

Pacific 3,802 976 739 900 720 385 425 621 646

Atlantic 4,646 1

, 320 938 1

, 247 939 553 524 865 840

Gulf of Mexico 1,370 361 292 316 255 196 203 269 202

Great Lakes 2,394 515 367 446 368 191 209 346 324

Inland Northeast 2,584 628 409 600 454 248 234 364 420

Inland Midwest 4,137 741 463 645 588 213 226 437 547

Inland South 6,825 1

, 560 1

, 082 1

, 386 1

, 204 519 567 1

, 053 1

, 071

Inland West 3,705 790 578 746 567 307 318 509 528

a Women of childbearing age

. b Income refused or don’t know

.



## 47

# 5. 2 Usual Fish Consumption Rates

Tables 8 through 18 present the UFCR estimates of raw weight, edible portion for adults 21 years

and older for total fish, freshwater + estuarine fish, marine fish, all finfish, all shellfish, trophic level

2 fish, trophic level 3 fish, trophic level 4 fish , trophic level 2 freshwater + estuarine fish, trophic

level 3 freshwater + estuarine fish, and trophic level 4 freshwater + estuarine fish. The tables

provide the 50 th , 75 th , 90 th , 95 th , 97 th , and 99 th percentiles, along with their respective 95 percent

confidence intervals. Tables 19 through 29 present the UFCR estimates of raw weight, edible

portion for youth less than 21 years old.

T he tables show percentiles for total fish consumed and for various fish types that make up the

total. The mean consumption for all fish should be equal, not counting random errors, to the sum of

the mean consumption across different types of fish, e.g., marine, estuarine, and freshwater or

trophic levels 2, 3, and 4. The same cannot be said about percentiles. At the extreme, the sum of the

maximum fish c onsumption across fish types will not equal the maximum fish consumption for all

fish except in the very unusual case where one individual is the largest consumer in all fish type

categories. For a selected percentile, the difference between the sum of the percentiles across fish

types and the percentile for the sum across all fish types will increase as the percentile of interest

increases from the 50th percentile to 90th percentile, 99th percentile, and the maximum. The 90th

percentile for all fish will b e greater than or equal to the 90th percentile for any one type of fish and

will usually be less than the sum of the 90th percentiles across all types.

There are two tables for each fish type , a and b . T able s 8a

– 29 a present the UFCR by demographic

charac teristics (gender, age, income, and race/ethnicity) and Tables 8b– 29 b present the UFCR by

geograph ic area

.

48

## Table 8a. UFCR estimates (g/day raw weight, edible portion): Total fish, adults, 21 years and older, by demographic characteristics

All Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 17.6 (15.8,19.7) 32.8 (30.1,35.7) 52.8 (48.0,58.1) 68.1 (61.2,75.8) 79.7 (71.0,89.5) 105.1 (92.0,120.2)

Age

21 to <35 yrs 13.1 (11.1,15.4) 26.8 (23.6,30.4) 46.6 (40.5,53.6) 63.5 (54.1,74.5) 77.2 (64.6,92.4) 109.7 (87.5,137.4)

35 to <50 yrs 18.3 (16.0,20.9) 33.1 (29.4,37.2) 52.7 (46.1,60.2) 67.5 (58.4,78.0) 78.5 (67.4,91.5) 102.4 (86.8,120.7)

50 to <65 yrs 22.4 (19.1,26.2) 38.8 (34.2,44.1) 59.3 (52.3,67.2) 74.4 (65.3,84.7) 85.5 (74.7,97.9) 109.1 (94.1,126.5)

65+ yrs 16.9 (14.4,20.0) 31.1 (27.1,35.6) 49.5 (43.2,56.9) 63.8 (55.1,73.9) 74.0 (63.6,86.1) 96.2 (81.6,113.5) Women of childbearing

age (13 to 49 yrs) 11.6 (10.2,13.2) 23.6 (21.5,25.9) 39.4 (35.4,43.8) 51.7 (45.9,58.2) 61.0 (53.7,69.2) 81.5 (70.6,94.1)

Gender

Female 15.3 (13.7,17.1) 28.4 (26.0,31.0) 45.2 (40.9,50.0) 57.8 (51.7,64.6) 67.1 (59.7,75.5) 87.2 (76.4,99.5)

Male 20.6 (18.2,23.3) 38.0 (34.5,41.8) 60.6 (54.6,67.2) 77.6 (69.2,87.2) 90.5 (79.8,102.5) 118.1 (102.3,136.3)

Race/Ethnicity 1

Mexican American 16.7 (13.8,20.1) 31.3 (27.0,36.3) 50.8 (43.8,59.0) 66.1 (56.4,77.4) 77.5 (65.7,91.5) 103.8 (86.2,125.1)

Other Hispanic 16.6 (13.3,20.7) 31.4 (25.8,38.4) 50.7 (42.1,61.1) 65.0 (54.2,77.9) 75.7 (63.3,90.7) 99.5 (82.7,119.7)

Non

- Hispanic White 16.7 (14.7,18.9) 31.0 (28.2,34.2) 49.8 (44.8,55.4) 64.3 (57.1,72.4) 75.1 (66.1,85.4) 98.1 (85.0,113.2)

Non

- Hispanic Black 19.6 (16.9,22.7) 35.3 (31.5,39.6) 55.7 (49.9,62.2) 71.1 (63.4,79.8) 82.7 (73.2,93.3) 107.2 (93.5,122.8)

Other Race 32.3 (25.8,40.4) 54.0 (44.5,65.5) 81.1 (66.3,99.1) 102.7 (82.7,127.4) 117.6 (93.4,148.1) 153.0 (117.1,200.0)

Income

$0 to <$20K 13.6 (11.7,15.8) 27.0 (24.1,30.2) 45.2 (40.1,51.1) 59.9 (52.4,68.4) 71.7 (61.9,82.9) 99.6 (82.8,119.9)

$20 to <$45K 15.4 (13.4,17.7) 28.8 (26.0,31.9) 46.7 (42.1,51.8) 61.1 (54.5,68.4) 71.9 (63.9,81.0) 96.7 (84.6,110.5)

$40 to <$75K 16.5 (14.2,19.2) 30.7 (27.2,34.7) 49.6 (43.5,56.5) 64.0 (55.6,73.8) 75.0 (64.6,87.1) 99.8 (84.4,118.1)

$75+K 23.1 (20.5,26.1) 40.1 (36.1,44.6) 61.3 (54.8,68.7) 77.1 (68.2,87.2) 88.6 (77.6,101.1) 113.5 (97.7,131.7)

>$20K 17.1 (12.6,23.0) 31.3 (24.6,39.8) 48.4 (38.9,60.3) 61.7 (49.5,77.0) 72.0 (57.7,89.7) 93.2 (74.7,116.4) Refused/Don ’ t Know

Income 16.9 (10.9,26.2) 36.6 (25.2,53.3) 64.5 (46.9,88.8) 83.5 (62.8,111.2) 96.4 (73.3,126.7) 124.8 (95.5,163.3)

Income Missing 8.8 (4.1,18.8) 22.0 (12.0,40.4) 46.6 (27.0,80.3) 65.0 (40.2,105.0) 76.6 (49.6,118.2) 99.5 (68.3,145.0)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).49

## Table 8b. UFCR estimates (g/day raw weight, edible portion): Total fish, adults, 21 years and older, by geographic area

All Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 17.6 (15.8,19.7) 32.8 (30.1,35.7) 52.8 (48.0,58.1) 68.1 (61.2,75.8) 79.7 (71.0,89.5) 105.1 (92.0,120.2)

Region 1

Northeast 23.9 (20.0,28.7) 42.5 (36.3,49.8) 65.2 (55.9,76.1) 82.0 (70.0,96.1) 93.7 (79.9,110.0) 119.6 (100.9,141.6)

Midwest 12.9 (10.6,15.6) 24.1 (20.6,28.3) 39.2 (33.4,46.0) 50.9 (43.1,60.2) 60.0 (50.3,71.6) 79.7 (66.5,95.6)

South 17.6 (15.1,20.4) 32.4 (28.8,36.4) 52.1 (46.3,58.7) 67.4 (59.1,76.8) 79.0 (68.6,90.9) 105.1 (89.0,124.1)

West 20.0 (17.1,23.4) 35.6 (30.7,41.2) 55.7 (47.7,65.0) 71.1 (60.3,83.9) 82.6 (69.5,98.2) 108.4 (89.8,130.9)

Coastal Status 2

Noncoastal 15.9 (13.7,18.5) 30.0 (26.4,34.1) 48.3 (42.3,55.3) 62.4 (54.1,72.1) 73.0 (62.8,85.0) 96.2 (81.4,113.7)

Coastal 20.9 (18.4,23.7) 37.9 (34.1,42.1) 59.9 (53.7,66.9) 76.7 (68.3,86.2) 89.3 (78.8,101.2) 115.9 (100.6,133.6)

Coastal/Inland Region 1,2

Pacific 22.1 (18.2,26.7) 39.3 (33.2,46.4) 61.2 (51.3,72.9) 78.2 (64.5,94.7) 91.0 (74.3,111.4) 118.7 (94.8,148.5)

Atlantic 24.5 (20.7,28.9) 43.4 (37.6,50.2) 67.2 (58.8,76.9) 84.8 (74.0,97.2) 97.7 (85.0,112.4) 124.6 (106.7,145.4)

Gulf of Mexico 19.0 (15.2,23.8) 34.5 (29.4,40.5) 55.0 (47.1,64.3) 70.6 (59.5,83.7) 82.4 (68.6,98.9) 106.8 (87.9,129.8)

Great Lakes 14.6 (12.1,17.5) 26.5 (22.6,31.1) 41.8 (35.7,49.0) 53.5 (45.6,62.9) 62.2 (52.8,73.2) 80.5 (68.3,94.9)

Inland Northeast 22.1 (17.5,28.0) 39.6 (32.6,48.1) 60.7 (50.3,73.2) 76.1 (62.9,92.0) 87.1 (71.9,105.4) 111.7 (91.4,136.6)

Inland Midwest 12.4 (10.1,15.1) 23.3 (19.7,27.6) 38.3 (32.3,45.4) 49.9 (41.7,59.7) 59.1 (49.0,71.3) 79.5 (64.9,97.4)

Inland South 15.6 (13.1,18.4) 29.0 (25.6,32.9) 46.9 (41.4,53.1) 60.7 (53.0,69.5) 71.2 (61.4,82.6) 95.6 (79.2,115.5)

Inland West 18.4 (15.1,22.5) 32.6 (27.0,39.4) 50.6 (41.5,61.5) 64.2 (52.7,78.3) 74.5 (61.0,91.0) 96.3 (78.6,118.1)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.50

## Ta ble 9a. UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, adults, 21 years and older, by demographic characteristics

Freshwater + Estuarine

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 5.0 (4.1,6.0) 11.4 (9.9,13.1) 22.0 (19.1,25.4) 31.8 (26.9,37.6) 40.2 (33.3,48.5) 61.1 (48.7,76.6)

Age

21 to <35 yrs 3.8 (3.1,4.8) 9.9 (8.3,11.7) 21.1 (17.6,25.1) 32.2 (26.2,39.7) 42.3 (33.3,53.7) 68.1 (50.1,92.5)

35 to <50 yrs 5.2 (4.1,6.6) 11.9 (9.6,14.8) 23.0 (18.4,28.7) 33.0 (26.0,41.8) 41.4 (32.2,53.1) 62.5 (46.8,83.4)

50 to <65 yrs 6.3 (5.0,7.9) 13.2 (10.9,15.9) 23.8 (19.7,28.9) 33.3 (26.9,41.3) 41.4 (32.7,52.4) 60.4 (45.9,79.4)

65+ yrs 4.5 (3.3,6.1) 9.9 (7.9,12.4) 18.7 (15.4,22.7) 26.5 (21.9,32.2) 33.1 (26.9,40.6) 48.8 (38.4,62.1)

Women of childbearing age (13 to 49 yrs) 2.9 (2.3,3.6) 7.6 (6.4,9.1) 15.8 (13.2,19.0) 23.5 (19.2,28.7) 29.9 (24.1,37.0) 46.6 (36.4,59.6)

Gender

Female 4.1 (3.4,5.0) 9.3 (8.1,10.8) 18.0 (15.4,21.0) 25.7 (21.5,30.7) 32.1 (26.4,39.1) 48.2 (38.0,61.2)

Male 6.2 (5.0,7.6) 13.8 (11.8,16.2) 26.3 (22.4,30.9) 38.0 (31.6,45.6) 47.7 (39.0,58.4) 71.9 (56.4,91.8)

Race/Ethnicity 1

Mexican American 6.8 (5.3,8.6) 15.3 (12.4,18.9) 28.7 (23.1,35.8) 40.9 (32.2,51.9) 51.0 (39.6,65.6) 75.7 (56.8,100.8)

Other Hispanic 6.1 (4.4,8.6) 14.1 (10.3,19.3) 27.2 (19.5,37.9) 38.7 (27.5,54.5) 47.8 (33.7,67.6) 69.7 (48.3,100.6)

Non

- Hispanic White 4.2 (3.4,5.2) 9.4 (8.0,11.1) 17.9 (15.1,21.1) 25.5 (21.2,30.8) 31.9 (26.0,39.0) 47.9 (37.2,61.6)

Non

- Hispanic Black 7.2 (5.8,8.9) 15.4 (13.0,18.1) 28.2 (23.8,33.4) 39.6 (32.7,48.0) 48.8 (39.4,60.3) 70.8 (55.0,91.3)

Other Race 12.6 (9.4,16.9) 25.1 (19.2,32.9) 44.5 (33.3,59.6) 62.3 (45.2,86.1) 78.3 (55.0,111.5) 114.7 (76.4,172.1)

Income

$0 to <$20K 3.5 (2.8,4.4) 9.1 (7.7,10.7) 19.2 (16.3,22.6) 28.9 (24.2,34.6) 37.4 (30.9,45.4) 59.3 (47.5,74.0)

$20 to <$45K 4.3 (3.5,5.4) 9.9 (8.5,11.5) 19.4 (16.6,22.7) 28.4 (23.7,33.9) 35.9 (29.6,43.6) 55.4 (43.8,70.0)

$40 to <$75K 4.8 (3.8,6.2) 10.8 (9.1,12.9) 20.6 (17.6,24.3) 29.6 (24.6,35.5) 37.3 (30.4,45.9) 56.8 (43.4,74.4)

$75+K 6.6 (5.4,8.1) 13.9 (11.7,16.6) 25.6 (21.3,30.8) 36.2 (29.4,44.5) 45.0 (35.9,56.5) 66.2 (51.1,85.9)

> $20K 5.5 (3.6,8.3) 12.1 (8.5,17.1) 22.3 (16.5,30.2) 30.9 (23.3,40.9) 38.7 (29.2,51.1) 56.1 (41.8,75.4)

Refused/Don ’ t Know Income 5.4 (3.2,9.1) 13.8 (9.2,20.8) 29.0 (19.7,42.6) 43.1 (28.6,65.0) 56.6 (36.3,88.3) 88.6 (54.5,144.1)

Income Missing 1.9 (0.8,4.5) 7.1 (3.6,13.9) 18.9 (10.6,33.7) 31.7 (18.4,54.5) 41.6 (24.5,70.7) 65.9 (39.3,110.5)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).51

## Table 9b. UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, adults, 21 years and older, by geographic

area

Freshwate r + Estuarine

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 5.0 (4.1,6.0) 11.4 (9.9,13.1) 22.0 (19.1,25.4) 31.8 (26.9,37.6) 40.2 (33.3,48.5) 61.1 (48.7,76.6)

Region 1

Northeast 5.8 (4.4,7.6) 12.6 (9.9,16.0) 23.1 (18.3,29.2) 32.3 (25.4,41.0) 39.9 (31.0,51.5) 58.5 (44.2,77.5)

Midwest 3.2 (2.5,4.2) 7.4 (6.0,9.0) 14.3 (11.8,17.4) 20.8 (16.9,25.7) 26.3 (21.0,33.0) 41.1 (31.3,54.0)

South 6.4 (4.7,8.5) 14.0 (11.3,17.4) 26.3 (21.6,32.0) 37.5 (30.5,46.1) 46.7 (37.6,58.1) 69.0 (54.3,87.7)

West 5.1 (3.9,6.6) 11.4 (8.8,14.8) 22.4 (16.8,29.8) 32.7 (23.9,44.9) 42.0 (30.0,58.8) 66.9 (45.4,98.5)

Coastal Status 2

Noncoastal 4.2 (3.4,5.2) 9.8 (8.2,11.6) 19.0 (15.8,22.9) 27.4 (22.3,33.8) 34.6 (27.7,43.3) 52.8 (40.7,68.4)

Coastal 6.6 (5.1,8.4) 14.4 (11.8,17.5) 27.1 (22.4,32.8) 38.6 (31.4,47.6) 48.4 (38.6,60.6) 72.7 (55.6,95.0)

Coastal/Inland Region 1,2

Pacific 6.3 (4.4,9.0) 14.0 (10.1,19.5) 27.3 (19.3,38.6) 39.7 (27.4,57.7) 51.2 (34.3,76.3) 81.2 (51.6,127.8)

Atlantic 8.3 (6.4,10.7) 17.0 (13.9,20.8) 30.8 (25.3,37.5) 42.8 (34.5,53.0) 52.3 (41.8,65.5) 75.8 (58.8,97.7)

Gulf of Mexico 7.3 (4.8,11.1) 15.7 (11.7,21.1) 28.6 (22.5,36.4) 40.1 (31.8,50.6) 50.3 (39.3,64.4) 73.8 (55.6,97.8)

Great Lakes 4.0 (3.1,5.1) 8.7 (7.1,10.7) 16.5 (13.5,20.2) 23.6 (19.1,29.1) 29.4 (23.5,36.8) 44.5 (34.1,57.9)

Inland Northeast 5.0 (3.5,7.3) 11.3 (8.0,16.0) 21.0 (14.8,29.7) 29.5 (20.6,42.2) 36.5 (25.3,52.8) 54.4 (36.7,80.6)

Inland Midwest 3.0 (2.3,4.0) 6.9 (5.5,8.7) 13.5 (10.8,17.0) 19.8 (15.5,25.2) 25.1 (19.4,32.6) 39.5 (29.1,53.5)

Inland South 5.3 (4.0,7.1) 12.0 (9.7,14.9) 22.8 (18.6,27.9) 32.7 (26.2,40.7) 40.9 (32.3,51.7) 61.0 (46.7,79.7)

Inland West 4.3 (3.3,5.4) 9.4 (7.4,12.1) 18.2 (13.7,24.3) 26.3 (19.1,36.1) 33.3 (23.8,46.7) 51.6 (35.5,74.9)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.52

## Table 10a. UFCR estimates (g/day raw weight, edible portion): Marine fish, adults, 21 years and older, by demographic characteristics

Marine Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 9.9 (8.5,11.5) 19.4 (17.4,21.7) 32.8 (29.6,36.3) 43.3 (38.8,48.4) 51.5 (45.5,58.1) 69.4 (60.1,80.2)

Age

21 to <35 yrs 7.3 (6.0,9.0) 15.4 (13.2,18.0) 27.4 (23.4,32.1) 37.4 (31.5,44.5) 45.5 (37.7,54.9) 64.7 (51.7,81.0)

35 to <50 yrs 10.2 (8.7,11.8) 19.2 (17.0,21.8) 31.8 (27.8,36.5) 41.7 (35.8,48.5) 49.3 (41.8,58.0) 66.4 (54.7,80.5)

50 to <65 yrs 13.0 (10.6,16.1) 24.0 (20.4,28.1) 38.3 (33.3,44.0) 49.4 (42.9,56.9) 57.8 (49.8,67.0) 75.6 (64.5,88.5)

65+ yrs 9.5 (7.5,12.1) 18.9 (15.8,22.5) 32.3 (27.6,37.8) 42.9 (36.3,50.7) 51.0 (42.8,60.6) 68.8 (56.8,83.5)

Women of childbearing

age (13 to 49 yrs) 6.8 (5.8,8.0) 14.5 (13.0,16.1) 25.3 (22.8,28.1) 34.0 (30.2,38.2) 40.5 (35.7,45.9) 55.5 (47.8,64.4)

Gender

Female 8.9 (7.5,10.5) 17.5 (15.5,19.7) 29.3 (26.1,32.9) 38.6 (34.1,43.6) 45.7 (40.2,52.1) 61.8 (53.0,72.2)

Male 11.2 (9.6,13.1) 21.8 (19.5,24.3) 36.4 (32.7,40.4) 47.9 (42.6,53.8) 56.7 (49.8,64.5) 75.7 (65.1,88.1)

Race/Ethnicity 1

Mexican American 7.9 (6.4,9.8) 15.7 (13.4,18.5) 26.6 (22.8,31.0) 35.5 (30.2,41.8) 42.2 (35.6,50.0) 57.9 (47.6,70.4)

Other Hispanic 8.2 (6.6,10.2) 16.4 (13.6,19.8) 28.4 (23.5,34.3) 38.1 (31.5,46.2) 45.5 (37.5,55.2) 62.2 (50.3,76.8)

Non

- Hispanic White 9.9 (8.3,11.9) 19.4 (17.0,22.2) 32.5 (28.7,36.9) 42.9 (37.6,49.0) 50.9 (44.1,58.7) 68.6 (58.3,80.7)

Non

- Hispanic Black 9.3 (7.8,11.1) 18.1 (15.8,20.8) 30.6 (26.6,35.2) 40.7 (34.9,47.5) 48.6 (41.1,57.4) 66.0 (54.4,80.0)

Other Race 17.3 (13.6,22.2) 30.8 (25.5,37.2) 47.7 (39.7,57.4) 60.4 (49.0,74.3) 70.2 (56.2,87.7) 92.4 (71.3,119.7)

Income

$0 to <$20K 7.4 (6.0,9.0) 15.5 (13.4,17.9) 27.3 (23.8,31.3) 36.9 (31.9,42.6) 44.6 (38.2,52.2) 62.7 (51.5,76.3)

$20 to <$45K 8.4 (7.0,9.9) 16.5 (14.5,18.7) 28.4 (25.2,31.9) 37.9 (33.4,43.0) 45.5 (39.8,52.1) 62.6 (53.4,73.4)

$40 to <$75K 9.5 (8.0,11.4) 18.6 (16.0,21.6) 31.3 (27.0,36.4) 41.5 (35.6,48.3) 49.1 (42.0,57.3) 66.4 (55.9,78.9)

$75+K 13.4 (11.4,15.8) 24.3 (21.7,27.3) 38.5 (34.4,43.1) 49.6 (43.8,56.3) 58.1 (50.7,66.6) 76.2 (65.2,89.2)

>$20K 9.4 (6.6,13.4) 18.0 (13.8,23.4) 29.8 (23.3,38.1) 39.2 (30.6,50.2) 46.1 (35.9,59.1) 62.7 (48.4,81.1)

Refused/Don ’ t Know Income 9.6 (6.2,14.9) 22.1 (15.0,32.6) 40.5 (28.9,56.8) 54.8 (40.1,74.9) 64.6 (47.6,87.6) 85.5 (63.6,114.9)

Income Missing 5.2 (2.5,10.8) 13.8 (7.5,25.3) 27.9 (16.2,48.2) 39.4 (24.1,64.5) 48.4 (30.4,77.2) 67.4 (43.6,104.1)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).53

## T able 10b. UFCR estimates (g/day raw weight, edible portion): Marine fish, adults, 21 years and older, by geographic area

Marine Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 9.9 (8.5,11.5) 19.4 (17.4,21.7) 32.8 (29.6,36.3) 43.3 (38.8,48.4) 51.5 (45.5,58.1) 69.4 (60.1,80.2)

Region 1

Northeast 15.0 (12.1,18.6) 28.1 (23.5,33.4) 44.4 (37.5,52.6) 56.7 (47.8,67.3) 65.8 (55.5,78.1) 85.4 (70.9,102.7)

Midwest 7.4 (5.7,9.6) 14.6 (11.5,18.3) 24.6 (19.7,30.8) 32.9 (26.2,41.4) 39.2 (31.0,49.5) 53.5 (42.1,68.1)

South 8.8 (7.6,10.1) 16.9 (15.3,18.8) 28.4 (25.2,31.9) 37.6 (32.7,43.2) 44.9 (38.4,52.4) 61.5 (50.6,74.6)

West 12.2 (9.8,15.2) 22.5 (18.8,26.9) 36.1 (30.6,42.7) 46.7 (39.5,55.2) 54.9 (46.0,65.5) 72.2 (59.6,87.6)

Coastal Status 2

Noncoastal 9.1 (7.4,11.2) 18.0 (15.3,21.3) 30.7 (26.1,35.9) 40.5 (34.4,47.7) 48.2 (40.7,57.1) 65.5 (54.2,79.1)

Coastal 11.4 (9.6,13.6) 22.0 (19.1,25.3) 36.3 (31.8,41.4) 47.6 (41.5,54.8) 56.2 (48.6,65.1) 74.9 (63.7,88.1)

Coastal/Inland Region 1,2

Pacific 13.0 (10.4,16.1) 24.1 (20.3,28.6) 38.6 (33.0,45.2) 49.9 (42.2,58.9) 58.5 (49.1,69.8) 77.0 (63.2,93.7)

Atlantic 13.1 (10.2,16.7) 24.9 (20.0,30.9) 40.6 (33.1,50.0) 52.8 (43.2,64.5) 61.8 (50.6,75.5) 81.1 (66.3,99.3)

Gulf of Mexico 9.5 (7.9,11.3) 18.1 (15.7,20.8) 29.7 (25.4,34.8) 39.7 (32.8,48.1) 47.1 (38.5,57.6) 64.3 (50.6,81.7)

Great Lakes 8.0 (6.3,10.2) 15.4 (12.6,18.9) 25.5 (20.9,31.1) 33.5 (27.2,41.2) 39.8 (32.2,49.1) 54.5 (43.0,69.0)

Inland Northeast 14.0 (11.1,17.6) 26.4 (21.9,31.8) 41.7 (34.8,50.0) 53.6 (44.4,64.8) 62.1 (51.2,75.2) 80.7 (65.8,98.8)

Inland Midwest 7.2 (5.4,9.6) 14.3 (11.1,18.4) 24.4 (19.2,31.0) 32.8 (25.6,41.9) 39.1 (30.4,50.2) 53.4 (41.4,68.8)

Inland South 7.9 (6.5,9.5) 15.2 (13.2,17.6) 25.7 (22.1,29.9) 34.1 (28.8,40.3) 40.7 (33.8,48.9) 56.6 (45.0,71.3)

Inland West 11.6 (8.8,15.4) 21.2 (16.6,27.2) 33.9 (26.8,43.0) 43.6 (34.6,55.0) 51.3 (40.6,64.9) 68.2 (53.0,87.7)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.54

## Table 11a. UFCR estimates (g/day raw weight, edible portion): Total finfish, adults, 21 years and older, by demographic

characteristics

All Finfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 12.8 (11.3,14.6) 24.1 (21.9,26.5) 39.3 (35.5,43.5) 51.2 (45.7,57.3) 60.1 (53.2,67.9) 80.1 (69.8,92.0)

Age

21 to <35 yrs 9.2 (7.6,11.1) 18.7 (16.2,21.6) 32.9 (28.3,38.4) 44.9 (37.9,53.2) 54.6 (45.5,65.5) 77.5 (62.5,95.9)

35 to <50 yrs 12.4 (10.6,14.5) 22.8 (20.2,25.7) 37.1 (32.6,42.1) 48.6 (42.0,56.2) 57.3 (49.1,66.7) 76.7 (64.6,91.0)

50 to <65 yrs 17.1 (14.2,20.6) 29.9 (25.7,34.8) 46.0 (39.7,53.2) 57.9 (49.7,67.5) 66.8 (57.1,78.2) 85.6 (72.4,101.4)

65+ yrs 13.8 (11.6,16.4) 24.9 (21.6,28.9) 39.5 (33.9,46.0) 50.6 (43.1,59.4) 59.0 (50.0,69.6) 77.9 (65.0,93.5) Women of childbearing

age (13 to 49 yrs) 8.2 (7.1,9.4) 16.7 (15.2,18.3) 28.6 (25.8,31.7) 38.1 (33.9,42.8) 45.6 (40.1,51.9) 62.2 (53.8,71.8)

Gender

Female 11.4 (10.1,12.9) 21.5 (19.5,23.6) 34.7 (31.2,38.6) 44.9 (39.9,50.6) 52.5 (46.2,59.6) 69.1 (59.7,80.1)

Male 14.6 (12.6,16.9) 27.2 (24.4,30.3) 44.1 (39.4,49.5) 57.2 (50.7,64.6) 67.1 (59.1,76.1) 89.0 (77.4,102.3)

Race/Ethnicity 1

Mexican American 11.3 (9.1,13.9) 21.5 (18.3,25.4) 35.4 (30.0,41.7) 46.7 (39.3,55.7) 55.5 (46.3,66.6) 75.6 (61.9,92.3)

Other Hispanic 10.7 (8.4,13.5) 21.5 (17.1,27.1) 36.3 (28.8,45.8) 48.4 (38.5,60.8) 57.5 (45.7,72.2) 78.3 (61.8,99.3)

Non

- Hispanic White 12.3 (10.6,14.2) 22.9 (20.5,25.5) 36.9 (32.8,41.5) 47.8 (42.0,54.4) 55.9 (48.6,64.2) 73.5 (62.9,85.8)

Non

- Hispanic Black 14.6 (12.3,17.4) 27.1 (23.6,31.0) 43.8 (38.5,49.8) 56.7 (49.7,64.7) 66.5 (57.9,76.4) 88.1 (75.0,103.6)

Other Race 24.2 (18.8,31.3) 41.0 (32.7,51.4) 62.2 (50.3,76.8) 78.8 (63.6,97.5) 90.0 (72.4,112.0) 114.9 (91.6,144.0)

Income, finer detail

$0 to <$20K 10.4 (8.9,12.3) 20.8 (18.7,23.3) 35.4 (31.5,39.8) 47.3 (41.7,53.7) 56.4 (49.5,64.4) 78.0 (66.9,91.0)

$20 to <$45K 11.9 (10.1,13.9) 22.1 (19.6,24.8) 36.1 (32.2,40.4) 47.3 (41.9,53.4) 55.8 (49.2,63.3) 75.0 (65.3,86.2)

$40 to <$75K 12.2 (10.3,14.5) 23.1 (19.8,26.9) 37.7 (32.0,44.3) 49.2 (41.5,58.3) 57.9 (48.7,69.0) 78.3 (64.9,94.5)

$75+K 15.9 (13.6,18.5) 28.2 (24.9,32.0) 44.1 (38.5,50.5) 56.1 (48.6,64.8) 64.8 (55.8,75.3) 84.4 (71.2,100.0)

>$20K 12.1 (8.3,17.6) 23.3 (17.0,32.0) 38.9 (29.0,52.2) 51.5 (38.2,69.4) 61.3 (45.2,83.2) 81.4 (59.9,110.7)

Refused/Don ’ t Know Income 10.7 (6.5,17.4) 24.3 (17.0,34.8) 43.6 (32.9,57.8) 57.7 (44.0,75.6) 67.6 (51.5,88.6) 87.4 (63.6,120.1)

Income Missing 4.9 (2.2,11.2) 13.0 (6.7,25.2) 28.8 (14.8,55.9) 41.9 (22.9,76.8) 53.0 (30.8,91.1) 75.7 (48.9,117.2)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).55

## Table 11b. UFCR estimates (g/day raw weight, edible portion) : Total finfish, adults, 21 years and older, by geographic area

All Finfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 12.8 (11.3,14.6) 24.1 (21.9,26.5) 39.3 (35.5,43.5) 51.2 (45.7,57.3) 60.1 (53.2,67.9) 80.1 (69.8,92.0)

Region 1

Northeast 15.4 (12.6,18.7) 28.5 (23.9,33.9) 45.0 (37.7,53.6) 57.2 (47.9,68.5) 66.1 (55.1,79.4) 85.6 (70.2,104.3)

Midwest 10.3 (8.1,13.2) 19.4 (15.9,23.7) 32.0 (26.4,38.7) 42.0 (34.5,51.0) 49.9 (40.7,61.2) 67.7 (54.5,84.1)

South 12.5 (10.8,14.4) 23.4 (21.2,26.0) 38.4 (34.4,42.9) 50.1 (44.2,56.8) 59.0 (51.6,67.6) 79.0 (67.8,92.2)

West 14.9 (12.6,17.7) 27.0 (22.7,32.1) 43.0 (35.8,51.5) 55.4 (46.1,66.6) 64.9 (53.8,78.3) 86.0 (70.8,104.3)

Coastal Status 2

Noncoastal 12.1 (10.3,14.3) 22.9 (20.0,26.1) 37.2 (32.5,42.6) 48.4 (41.9,56.0) 56.8 (48.8,66.1) 76.0 (64.3,89.9)

Coastal 14.2 (12.4,16.2) 26.4 (23.7,29.4) 42.9 (38.3,48.0) 55.7 (49.4,62.9) 65.2 (57.4,74.0) 85.5 (74.2,98.5)

Coastal/Inland Region 1,2

Pacific 15.5 (12.9,18.7) 28.5 (23.9,34.1) 45.5 (37.9,54.6) 59.0 (48.8,71.4) 69.2 (56.9,84.3) 90.6 (73.7,111.2)

Atlantic 15.8 (13.3,18.7) 29.1 (25.0,33.7) 46.5 (40.2,53.7) 59.6 (51.4,69.1) 68.9 (59.1,80.3) 88.9 (74.8,105.7)

Gulf of Mexico 12.5 (10.0,15.5) 23.2 (19.7,27.5) 38.2 (31.8,45.9) 49.6 (40.6,60.6) 58.7 (47.3,73.0) 77.4 (62.1,96.5)

Great Lakes 10.7 (8.4,13.7) 19.7 (16.0,24.2) 32.1 (26.4,39.0) 42.1 (34.6,51.2) 49.6 (40.7,60.5) 67.0 (54.8,81.8)

Inland Northeast 14.7 (11.8,18.3) 27.4 (22.7,32.9) 42.8 (35.9,51.1) 54.5 (45.7,64.9) 63.0 (52.8,75.3) 82.0 (68.4,98.3)

Inland Midwest 10.2 (7.9,13.2) 19.3 (15.6,23.8) 31.9 (26.0,39.1) 41.8 (33.9,51.5) 49.9 (40.0,62.2) 67.8 (53.4,86.1)

Inland South 11.5 (9.7,13.7) 21.8 (19.2,24.7) 35.7 (31.7,40.2) 46.9 (40.9,53.7) 55.2 (47.8,63.8) 75.1 (62.9,89.6)

Inland West 14.5 (11.5,18.3) 25.8 (20.4,32.7) 40.8 (32.1,51.9) 52.5 (41.3,66.7) 61.2 (48.2,77.7) 81.0 (64.2,102.4)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not dir ectly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.56

## Table 12a. UFCR estimates (g/day raw weight, edible portion): Total shellfish, adults, 21 years and older, by demographic

characteristics

All Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 3.1 (2.4,3.9) 7.6 (6.4,9.0) 15.6 (13.2,18.5) 23.1 (19.2,27.8) 29.1 (23.9,35.4) 43.7 (35.2,54.2)

Age

21 to <35 yrs 2.7 (2.0,3.7) 7.2 (5.7,9.1) 15.6 (12.4,19.6) 24.1 (18.8,30.7) 31.3 (24.2,40.5) 49.4 (36.7,66.6)

35 to <50 yrs 3.7 (2.8,4.8) 8.8 (6.9,11.2) 17.6 (13.6,22.8) 25.6 (19.3,33.9) 31.8 (23.7,42.6) 46.9 (33.9,64.8)

50 to <65 yrs 3.7 (2.8,4.7) 8.3 (6.7,10.4) 16.0 (12.7,20.1) 22.7 (17.8,28.9) 28.0 (21.9,35.9) 39.9 (31.1,51.3)

65+ yrs 1.9 (1.4,2.7) 5.1 (3.8,6.8) 11.1 (8.6,14.5) 16.9 (13.2,21.6) 21.8 (17.0,27.9) 33.3 (25.8,43.1)

Women of childbearing age (13 to 49 yrs) 2.0 (1.5,2.7) 5.4 (4.4,6.6) 11.4 (9.5,13.8) 17.1 (13.9,20.9) 21.8 (17.5,27.0) 32.7 (25.5,41.8)

Gender

Female 2.5 (2.0,3.2) 6.2 (5.2,7.3) 12.5 (10.6,14.8) 18.2 (15.1,22.0) 22.9 (18.7,28.0) 33.7 (27.1,42.0)

Male 3.8 (3.0,4.9) 9.4 (7.8,11.4) 19.0 (15.7,23.0) 27.9 (22.7,34.3) 35.0 (28.2,43.5) 51.5 (40.5,65.6)

Race/Ethnicity 1

Mexican American 3.6 (2.6,4.9) 8.9 (6.9,11.6) 18.2 (13.8,24.0) 26.7 (19.9,35.9) 33.6 (24.7,45.8) 49.5 (34.7,70.8)

Other Hispanic 3.6 (2.2,5.8) 9.1 (6.1,13.6) 18.2 (12.9,25.7) 26.4 (19.0,36.7) 32.9 (23.8,45.4) 48.1 (34.4,67.3)

Non

- Hispanic White 2.9 (2.2,3.7) 7.1 (5.9,8.6) 14.5 (12.0,17.6) 21.4 (17.4,26.3) 27.0 (21.7,33.4) 40.1 (31.9,50.5)

Non

- Hispanic Black 2.8 (2.1,3.6) 6.9 (5.6,8.4) 14.0 (11.4,17.3) 20.7 (16.3,26.1) 26.0 (20.3,33.2) 38.3 (29.5,49.9)

Other Race 5.9 (3.9,9.0) 13.5 (9.3,19.6) 27.0 (18.6,39.3) 39.7 (26.9,58.7) 50.2 (33.6,74.9) 73.4 (48.7,110.6)

Income, finer detail

$0 to <$20K 1.9 (1.3,2.6) 5.2 (4.1,6.7) 11.7 (9.4,14.5) 18.1 (14.5,22.6) 23.7 (18.7,30.1) 37.4 (28.4,49.2)

$20 to <$45K 2.4 (1.8,3.2) 5.9 (4.7,7.4) 12.2 (10.0,14.9) 18.2 (14.9,22.2) 23.5 (19.1,28.9) 36.2 (29.1,45.1)

$40 to <$75K 2.8 (2.1,3.8) 6.8 (5.3,8.6) 13.8 (10.9,17.5) 20.6 (16.0,26.4) 26.2 (20.1,34.1) 40.3 (29.8,54.4)

$75+K 4.9 (3.9,6.0) 10.8 (9.1,13.0) 20.3 (16.6,24.8) 28.3 (22.8,35.3) 34.7 (27.6,43.7) 49.3 (38.4,63.3)

>$20K 2.7 (1.4,5.2) 6.6 (4.2,10.3) 13.5 (9.6,19.1) 19.8 (14.3,27.5) 25.1 (18.0,34.8) 37.5 (26.4,53.4)

Refused/Don ’ t Know Income 3.6 (1.7,7.9) 10.9 (5.4,22.0) 24.6 (13.3,45.3) 36.7 (20.6,65.2) 45.7 (26.6,78.8) 63.7 (37.8,107.5)

Income Missing 0.9 (0.2,4.9) 4.7 (1.4,16.0) 17.4 (6.5,46.4) 30.1 (12.2,74.3) 40.4 (17.8,91.6) 60.8 (31.8,116.2)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).57

## Table 12b. UFCR estimates (g/day raw weight, edible portion): Total shellfish, adults, 21 years and older, by geographic area

All Shellfish Percen tiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 3.1 (2.4,3.9) 7.6 (6.4,9.0) 15.6 (13.2,18.5) 23.1 (19.2,27.8) 29.1 (23.9,35.4) 43.7 (35.2,54.2)

Region 1

Northeast 5.9 (4.5,7.7) 13.3 (10.7,16.5) 24.6 (19.6,30.8) 34.2 (27.1,43.2) 41.7 (32.8,53.0) 58.3 (44.8,75.8)

Midwest 1.6 (1.1,2.2) 3.7 (2.7,5.2) 7.6 (5.4,10.6) 11.1 (7.8,15.9) 14.2 (9.8,20.5) 21.5 (14.6,31.5)

South 3.4 (2.4,4.8) 8.0 (6.0,10.7) 15.7 (11.9,20.8) 22.7 (17.2,30.1) 28.4 (21.5,37.5) 41.7 (31.8,54.7)

West 3.5 (2.4,5.0) 8.0 (5.6,11.3) 15.8 (11.1,22.6) 23.2 (16.0,33.5) 29.1 (19.9,42.5) 43.8 (29.1,65.8)

Coastal Status 2

Noncoastal 2.4 (1.9,3.1) 6.0 (4.8,7.4) 12.3 (9.8,15.5) 18.2 (14.2,23.5) 23.3 (17.8,30.5) 35.4 (26.4,47.4)

Coastal 4.7 (3.5,6.2) 10.9 (8.6,13.8) 21.0 (16.6,26.4) 29.8 (23.5,37.8) 36.9 (29.0,46.9) 53.2 (41.6,68.0)

Coastal/Inland Region 1,2

Pacific 4.6 (3.0,7.0) 10.5 (7.0,15.7) 20.3 (13.4,30.7) 29.0 (18.8,44.5) 36.1 (23.2,56.2) 53.4 (34.1,83.5)

Atlantic 6.4 (4.8,8.6) 13.9 (10.9,17.8) 25.7 (20.3,32.5) 35.2 (28.0,44.3) 42.8 (33.8,54.3) 59.5 (46.0,76.8)

Gulf of Mexico 4.8 (3.2,7.4) 10.8 (7.7,15.2) 20.1 (14.7,27.4) 28.4 (21.0,38.4) 35.0 (26.1,46.9) 48.6 (37.0,64.0)

Great Lakes 2.3 (1.6,3.3) 5.4 (3.9,7.5) 10.5 (7.5,14.6) 15.0 (10.6,21.2) 18.8 (13.3,26.7) 27.5 (19.2,39.2)

Inland Northeast 4.9 (3.4,6.9) 11.2 (8.2,15.2) 20.7 (14.8,28.9) 28.7 (20.1,41.0) 35.3 (24.4,51.0) 49.0 (32.9,73.1)

Inland Midwest 1.4 (1.0,2.0) 3.3 (2.3,4.6) 6.6 (4.7,9.4) 9.8 (6.8,14.2) 12.6 (8.6,18.5) 19.2 (12.9,28.7)

Inland South 2.6 (1.9,3.7) 6.1 (4.7,7.9) 12.1 (9.5,15.3) 17.6 (13.8,22.4) 22.2 (17.2,28.7) 33.6 (25.7,44.0)

Inland West 2.7 (1.9,3.9) 6.1 (4.4,8.5) 11.8 (8.5,16.5) 17.1 (12.1,24.0) 21.4 (15.0,30.6) 31.6 (21.9,45.7)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 2 5 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.58

## Table 13a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, adults, 21 years and older, by demographic

characteristics

Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 1.9 (1.5,2.4) 4.7 (4.0,5.5) 9.6 (8.3,11.0) 14.2 (12.1,16.8) 18.1 (15.1,21.8) 27.7 (21.8,35.2)

Age

21 to <35 yrs 1.6 (1.2,2.2) 4.2 (3.5,5.1) 9.0 (7.7,10.6) 13.7 (11.4,16.5) 17.7 (14.4,21.6) 27.9 (21.5,36.1)

35 to <50 yrs 2.1 (1.5,2.8) 5.3 (4.1,6.8) 11.2 (8.5,14.7) 16.7 (12.2,22.9) 21.4 (15.2,30.3) 32.6 (21.9,48.6)

50 to <65 yrs 2.3 (1.7,3.2) 5.1 (3.9,6.6) 9.6 (7.6,12.2) 13.8 (10.9,17.4) 17.1 (13.5,21.7) 24.9 (19.3,32.2)

65+ yrs 1.4 (1.0,1.9) 3.7 (2.8,4.8) 7.7 (6.0,9.8) 11.4 (8.9,14.5) 14.5 (11.2,18.6) 21.5 (16.4,28.3)

Women of childbearing age (13 to 49 yrs) 1.2 (0.9,1.6) 3.1 (2.6,3.9) 6.7 (5.6,8.1) 10.1 (8.2,12.4) 12.9 (10.2,16.3) 19.7 (14.6,26.5)

Gender

Female 1.5 (1.2,2.0) 3.7 (3.2,4.4) 7.5 (6.5,8.7) 11.0 (9.3,13.0) 13.8 (11.5,16.7) 20.6 (16.3,26.1)

Male 2.4 (1.9,3.1) 5.8 (4.9,6.9) 11.9 (10.1,14.0) 17.5 (14.5,21.1) 22.2 (17.9,27.5) 33.3 (25.6,43.4)

Race/Ethnicity 1

Mexican American 2.9 (2.2,3.9) 7.2 (5.7,9.0) 14.5 (11.5,18.4) 21.3 (16.4,27.7) 26.9 (20.3,35.5) 40.5 (29.0,56.7)

Other Hispanic 2.5 (1.7,3.6) 6.3 (4.5,8.6) 12.7 (9.3,17.5) 18.5 (13.1,26.1) 23.4 (16.3,33.7) 34.2 (22.5,52.1)

Non

- Hispanic White 1.7 (1.3,2.2) 4.1 (3.4,4.9) 8.3 (7.0,9.8) 12.3 (10.2,14.9) 15.6 (12.7,19.2) 23.7 (18.3,30.8)

Non

- Hispanic Black 2.1 (1.6,2.9) 5.1 (4.0,6.4) 10.0 (8.0,12.6) 14.5 (11.4,18.4) 18.3 (14.2,23.6) 26.9 (20.4,35.6)

Other Race 3.5 (2.2,5.5) 7.9 (5.3,11.6) 15.1 (10.4,21.9) 21.8 (14.8,32.1) 27.3 (18.0,41.3) 39.8 (24.8,63.9)

Income

$0 to <$20K 1.2 (0.9,1.7) 3.4 (2.6,4.4) 7.6 (6.1,9.5) 11.9 (9.5,14.8) 15.7 (12.4,19.8) 25.1 (19.1,32.9)

$20 to <$45K 1.6 (1.2,2.2) 4.0 (3.2,5.0) 8.3 (7.0,10.0) 12.6 (10.5,15.0) 16.2 (13.5,19.4) 25.2 (20.2,31.4)

$40 to <$75K 1.8 (1.3,2.4) 4.3 (3.5,5.3) 8.8 (7.4,10.5) 13.1 (10.7,16.0) 16.6 (13.4,20.6) 25.2 (19.6,32.5)

$75+K 2.7 (2.2,3.4) 6.0 (5.1,7.1) 11.6 (9.6,14.0) 16.5 (13.2,20.7) 20.7 (16.0,26.9) 30.4 (21.9,42.2)

>$20K 1.9 (1.1,3.2) 4.5 (3.1,6.6) 9.3 (6.8,12.6) 13.6 (9.9,18.5) 17.6 (12.8,24.3) 27.6 (19.3,39.5)

Refused/Don ’ t Know Income 2.1 (0.8,5.4) 6.1 (2.9,12.9) 13.5 (7.3,25.2) 20.5 (11.5,36.4) 26.2 (14.8,46.6) 39.0 (19.5,78.3)

Income Missing 0.6 (0.1,2.8) 2.6 (0.8,8.3) 9.1 (3.5,23.5) 15.6 (6.5,37.5) 21.5 (9.2,50.4) 36.0 (16.2,79.7)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).59

## Table 13b. UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, adults, 21 years and older, by geographic

area

Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 1.9 (1.5,2.4) 4.7 (4.0,5.5) 9.6 (8.3,11.0) 14.2 (12.1,16.8) 18.1 (15.1,21.8) 27.7 (21.8,35.2)

Region 1

Northeast 3.1 (2.4,3.9) 7.1 (5.6,8.9) 13.6 (10.3,18.0) 19.6 (14.0,27.3) 24.3 (16.8,35.1) 35.9 (23.0,56.1)

Midwest 1.0 (0.7,1.4) 2.4 (1.7,3.4) 4.9 (3.4,7.2) 7.4 (4.9,11.1) 9.5 (6.2,14.6) 14.7 (9.2,23.4)

South 2.3 (1.6,3.3) 5.4 (4.2,7.0) 10.7 (8.7,13.1) 15.4 (12.6,18.9) 19.4 (15.7,24.0) 28.8 (22.7,36.6)

West 2.0 (1.4,2.8) 4.7 (3.5,6.2) 9.3 (7.3,11.9) 13.7 (10.7,17.7) 17.4 (13.4,22.6) 26.8 (20.1,35.6)

Coastal Status 2

Noncoastal 1.5 (1.2,2.0) 3.8 (3.1,4.7) 7.9 (6.3,10.0) 11.9 (9.0,15.7) 15.3 (11.3,20.8) 24.4 (16.9,35.2)

Coastal 2.7 (2.0,3.7) 6.3 (5.1,7.9) 12.3 (10.2,14.8) 17.5 (14.5,21.0) 21.8 (17.9,26.5) 31.8 (25.3,40.0)

Coastal/Inland Region 1,2

Pacific 2.5 (1.7,3.8) 5.8 (4.2,8.1) 11.3 (8.4,15.3) 16.2 (12.0,21.9) 20.4 (15.0,27.7) 30.2 (21.9,41.6)

Atlantic 3.8 (2.8,5.1) 8.1 (6.6,10.1) 15.1 (12.3,18.4) 20.9 (16.9,25.8) 25.3 (20.1,31.7) 35.8 (26.5,48.3)

Gulf of Mexico 2.9 (1.9,4.6) 6.6 (4.8,9.1) 12.5 (9.7,16.1) 17.4 (13.7,22.2) 21.4 (16.8,27.1) 31.2 (23.7,41.0)

Great Lakes 1.4 (0.9,2.1) 3.3 (2.3,4.8) 6.6 (4.6,9.6) 9.6 (6.5,14.2) 12.0 (8.0,17.9) 17.9 (11.4,28.0)

Inland Northeast 2.6 (1.8,3.7) 6.1 (4.1,8.9) 11.8 (7.5,18.8) 17.3 (10.3,29.0) 21.9 (12.6,38.1) 33.4 (18.2,61.3)

Inland Midwest 0.9 (0.6,1.3) 2.1 (1.5,3.1) 4.4 (2.9,6.7) 6.6 (4.3,10.2) 8.6 (5.4,13.6) 13.5 (8.2,22.2)

Inland South 1.9 (1.3,2.6) 4.4 (3.4,5.6) 8.7 (7.0,10.9) 12.9 (10.1,16.5) 16.4 (12.7,21.3) 25.5 (18.5,35.1)

Inland West 1.6 (1.2,2.3) 3.7 (2.9,4.9) 7.4 (5.7,9.7) 11.0 (8.4,14.6) 14.2 (10.6,19.0) 22.4 (15.9,31.5)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.60

## Table 14a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 3 fish, adults, 21 years and older, by demographic

characteristics

Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 4.7 (3.9,5.7) 9.6 (8.5,10.8) 16.6 (14.7,18.8) 22.4 (19.4,25.9) 27.0 (23.0,31.6) 37.4 (30.7,45.7)

Age

21 to <35 yrs 3.7 (2.9,4.8) 8.2 (6.8,9.8) 15.4 (12.9,18.3) 22.0 (17.9,27.1) 27.6 (21.6,35.3) 41.3 (29.1,58.5)

35 to <50 yrs 5.0 (4.1,6.1) 9.8 (8.3,11.6) 16.8 (14.1,20.0) 22.5 (18.7,27.1) 26.9 (22.0,32.7) 36.5 (29.3,45.5)

50 to <65 yrs 6.0 (4.9,7.4) 11.3 (9.5,13.3) 18.4 (15.4,21.9) 23.9 (19.7,28.9) 28.1 (22.9,34.4) 37.4 (29.3,47.7)

65+ yrs 4.0 (3.0,5.3) 8.2 (6.8,10.0) 14.6 (12.7,16.9) 20.1 (17.4,23.2) 24.3 (20.8,28.4) 33.8 (27.9,40.8)

Women of childbearing age (13 to 49 yrs) 3.1 (2.5,3.8) 6.7 (5.9,7.8) 12.4 (10.8,14.2) 17.1 (14.6,19.9) 20.8 (17.6,24.6) 29.6 (24.4,35.9)

Gender

Female 4.0 (3.3,4.9) 8.2 (7.1,9.3) 14.1 (12.4,16.1) 19.0 (16.4,22.0) 22.7 (19.4,26.6) 31.1 (25.8,37.4)

Male 5.6 (4.6,6.8) 11.2 (9.8,12.8) 19.2 (16.6,22.2) 25.7 (21.8,30.4) 30.8 (25.7,36.9) 42.4 (33.9,53.1)

Race/Ethnicity 1

Mexican American 5.2 (4.0,6.6) 10.4 (8.6,12.5) 17.7 (14.6,21.3) 23.5 (19.2,28.9) 28.1 (22.5,35.2) 38.2 (29.5,49.5)

Other Hispanic 4.4 (3.2,6.1) 9.1 (6.8,12.1) 15.6 (11.9,20.4) 21.0 (16.0,27.5) 25.2 (19.0,33.3) 34.2 (25.0,46.9)

Non

- Hispanic White 4.2 (3.4,5.2) 8.4 (7.3,9.7) 14.5 (12.5,16.7) 19.3 (16.5,22.7) 23.1 (19.3,27.5) 31.4 (25.4,38.9)

Non

- Hispanic Black 6.1 (5.1,7.4) 11.8 (10.2,13.5) 19.5 (16.8,22.5) 25.6 (21.7,30.2) 30.1 (25.2,35.9) 40.0 (32.6,49.3)

Other Race 11.9 (9.2,15.5) 21.2 (16.8,26.7) 33.2 (26.0,42.3) 42.4 (31.9,56.2) 49.1 (35.9,67.1) 62.0 (43.1,89.3)

Income

$0 to <$20K 3.8 (3.0,4.9) 8.4 (7.1,9.9) 15.3 (13.2,17.8) 21.1 (18.0,24.8) 25.8 (21.7,30.6) 37.0 (29.8,46.0)

$20 to <$45K 4.1 (3.3,5.2) 8.5 (7.2,10.0) 14.8 (12.8,17.2) 20.2 (17.4,23.5) 24.5 (20.8,28.7) 34.7 (28.6,42.2)

$40 to <$75K 4.4 (3.6,5.5) 8.8 (7.5,10.3) 15.3 (13.2,17.9) 20.9 (17.5,24.8) 25.3 (20.8,30.7) 35.4 (27.7,45.3)

$75+K 6.0 (5.0,7.3) 11.5 (9.9,13.3) 19.1 (16.2,22.5) 25.0 (20.8,30.2) 29.5 (24.3,35.9) 39.6 (31.6,49.8)

>$20K 4.6 (3.0,7.2) 9.1 (6.8,12.2) 15.2 (11.8,19.5) 20.2 (15.9,25.7) 23.9 (18.6,30.6) 32.2 (24.7,42.1)

Refused/Don ’ t Know Income 5.1 (3.0,8.4) 11.7 (7.7,17.9) 21.6 (14.8,31.7) 29.1 (19.1,44.2) 35.0 (22.4,54.7) 47.7 (29.3,77.5)

Income Missing 1.7 (0.6,4.7) 5.4 (2.4,12.4) 14.7 (6.6,32.6) 22.8 (10.9,47.5) 29.4 (15.1,57.1) 42.1 (24.6,72.1)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).61

## Table 14b. UFCR estimates (g/day raw weight, edible portion) : Total trophic level 3 fish, adults, 21 years and older, by geographic

area

Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 4.7 (3.9,5.7) 9.6 (8.5,10.8) 16.6 (14.7,18.8) 22.4 (19.4,25.9) 27.0 (23.0,31.6) 37.4 (30.7,45.7)

Region 1

Northeast 5.9 (4.5,7.7) 11.7 (9.3,14.6) 19.4 (15.6,24.1) 25.3 (20.3,31.5) 29.7 (23.7,37.3) 39.7 (30.9,51.0)

Midwest 3.0 (2.2,3.9) 5.8 (4.7,7.2) 10.1 (8.2,12.5) 13.6 (11.0,17.0) 16.5 (13.1,20.8) 23.0 (17.9,29.6)

South 5.4 (4.3,6.9) 10.6 (8.9,12.6) 17.9 (15.1,21.1) 23.8 (19.9,28.5) 28.4 (23.6,34.1) 38.8 (31.5,47.9)

West 5.6 (4.3,7.1) 10.8 (8.7,13.4) 18.6 (14.7,23.4) 25.1 (19.5,32.3) 30.3 (23.2,39.6) 42.1 (30.6,57.9)

Coastal Status 2

Noncoastal 4.1 (3.3,5.1) 8.3 (7.1,9.8) 14.6 (12.5,17.1) 19.7 (16.6,23.5) 23.7 (19.7,28.6) 32.8 (26.4,40.7)

Coastal 6.0 (4.9,7.4) 11.8 (10.1,13.7) 19.9 (17.0,23.2) 26.5 (22.3,31.4) 31.7 (26.2,38.3) 43.3 (34.0,54.9)

Coastal/Inland Region 1,2

Pacific 6.4 (4.9,8.4) 12.7 (9.8,16.5) 21.7 (16.5,28.6) 29.4 (21.9,39.6) 35.3 (25.7,48.5) 48.2 (32.8,70.8)

Atlantic 7.2 (5.7,9.1) 13.2 (11.1,15.8) 21.6 (18.3,25.4) 27.9 (23.6,33.1) 32.8 (27.3,39.4) 43.7 (34.9,54.5)

Gulf of Mexico 6.3 (4.5,8.7) 12.2 (9.7,15.2) 20.2 (16.7,24.5) 26.8 (21.9,32.8) 31.9 (25.9,39.4) 43.4 (34.0,55.5)

Great Lakes 3.7 (2.9,4.7) 7.0 (5.7,8.6) 11.7 (9.4,14.5) 15.4 (12.2,19.4) 18.3 (14.4,23.4) 24.9 (19.2,32.4)

Inland Northeast 5.3 (3.9,7.1) 10.6 (8.3,13.6) 17.7 (13.9,22.7) 23.4 (18.1,30.2) 27.5 (21.1,35.8) 36.9 (27.8,48.9)

Inland Midwest 2.7 (2.0,3.7) 5.4 (4.3,6.9) 9.5 (7.6,11.9) 13.0 (10.2,16.4) 15.7 (12.3,20.0) 22.2 (17.0,29.0)

Inland South 4.7 (3.7,6.0) 9.3 (7.8,11.1) 15.9 (13.5,18.8) 21.3 (17.8,25.4) 25.5 (21.0,30.9) 35.0 (28.1,43.6)

Inland West 4.9 (3.7,6.6) 9.4 (7.3,12.0) 15.8 (12.3,20.2) 21.0 (16.3,27.1) 25.2 (19.2,33.0) 34.2 (25.6,45.7)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census R egions.62

## Table 15a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, adults, 21 years and older, by demographic

characteristics

Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 8.6 (7.5,9.9) 17.1 (15.5,18.8) 28.8 (26.1,31.9) 38.3 (34.1,42.9) 45.5 (40.1,51.7) 61.6 (53.2,71.2)

Age

21 to <35 yrs 6.0 (4.8,7.4) 12.9 (10.9,15.3) 23.8 (19.9,28.6) 33.2 (27.2,40.5) 40.9 (33.0,50.5) 58.4 (45.9,74.3)

35 to < 50 yrs 8.3 (7.1,9.8) 16.0 (14.1,18.2) 26.7 (23.2,30.8) 35.4 (30.3,41.5) 42.2 (35.6,50.1) 57.0 (47.1,69.0)

50 to <65 yrs 11.8 (9.7,14.3) 21.5 (18.3,25.3) 34.4 (29.3,40.3) 44.4 (37.6,52.4) 51.8 (43.5,61.7) 68.1 (56.5,82.0)

65+ yrs 9.5 (7.7,11.6) 17.8 (15.1,21.0) 29.3 (24.7,34.7) 38.5 (32.1,46.2) 45.3 (37.5,54.9) 60.8 (49.2,75.0)

Women of childbearing age (13 to 49 yrs) 5.4 (4.6,6.3) 11.7 (10.5,13.0) 20.8 (18.7,23.1) 28.2 (25.1,31.6) 33.9 (29.9,38.4) 46.7 (40.4,54.0)

Gender

Female 7.8 (6.8,8.9) 15.4 (14.1,16.9) 25.9 (23.3,28.7) 34.1 (30.3,38.3) 40.3 (35.4,45.9) 54.2 (46.3,63.3)

Male 9.7 (8.3,11.3) 19.0 (17.0,21.2) 32.0 (28.6,35.9) 42.6 (37.5,48.5) 50.5 (44.1,57.8) 68.4 (58.4,80.1)

Race/Ethnicity 1

Mexican American 6.4 (5.2,8.0) 13.1 (11.1,15.4) 22.8 (19.3,26.8) 30.7 (25.7,36.7) 37.3 (30.7,45.3) 52.9 (42.0,66.6)

Other Hispanic 6.8 (5.3,8.8) 14.2 (11.1,18.1) 25.2 (19.9,31.9) 34.1 (27.1,43.0) 41.1 (32.9,51.5) 57.2 (45.7,71.6)

Non

- Hispanic White 8.8 (7.5,10.2) 17.1 (15.4,19.1) 28.7 (25.7,32.1) 38.0 (33.5,43.1) 45.1 (39.3,51.8) 60.8 (52.0,71.1)

Non

- Hispanic Black 8.4 (6.9,10.1) 16.4 (14.1,19.2) 28.0 (24.0,32.8) 37.3 (31.8,43.9) 44.5 (37.6,52.7) 60.7 (50.4,73.1)

Other Race 14.2 (10.6,19.0) 25.6 (20.0,32.7) 39.6 (31.3,50.3) 51.1 (40.3,64.9) 59.5 (46.4,76.4) 80.0 (59.9,107.0)

Income

$0 to <$20K 6.9 (5.7,8.2) 14.5 (12.9,16.3) 25.6 (22.6,29.0) 34.9 (30.3,40.2) 42.4 (36.1,49.7) 59.3 (49.0,71.8)

$20 to <$45K 7.7 (6.5,9.2) 15.1 (13.4,17.1) 25.7 (22.7,29.1) 34.4 (30.1,39.3) 41.1 (35.7,47.4) 56.8 (47.9,67.3)

$40 to <$75K 8.3 (6.9,9.9) 16.4 (14.0,19.1) 27.6 (23.4,32.5) 36.7 (30.8,43.8) 43.8 (36.4,52.7) 59.2 (48.5,72.1)

$75+K 11.1 (9.5,13.0) 20.5 (18.1,23.1) 33.0 (29.1,37.4) 42.7 (37.3,48.9) 50.0 (43.2,57.9) 66.1 (56.2,77.8)

>$20K 7.9 (5.3,11.8) 16.0 (11.3,22.6) 27.7 (19.8,38.7) 36.8 (26.2,51.7) 44.2 (31.3,62.4) 60.5 (43.2,84.7)

Refused/Don ’ t Know Income 7.3 (4.4,12.1) 18.0 (12.2,26.6) 34.6 (25.4,47.1) 47.4 (35.8,62.8) 56.4 (43.1,73.9) 74.9 (57.1,98.2)

Income Missing 3.7 (1.7,8.4) 10.9 (5.3,22.2) 23.5 (11.8,46.5) 33.8 (17.8,64.3) 41.6 (23.2,74.6) 60.7 (37.9,97.3)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).63

## Table 15b. UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, adults, 21 years and older, by geographic

area

Trophic L evel 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 8.6 (7.5,9.9) 17.1 (15.5,18.8) 28.8 (26.1,31.9) 38.3 (34.1,42.9) 45.5 (40.1,51.7) 61.6 (53.2,71.2)

Region 1

Northeast 11.5 (9.4,14.1) 22.0 (18.4,26.2) 36.0 (30.1,43.1) 46.7 (38.8,56.2) 55.0 (45.5,66.5) 73.1 (60.1,89.0)

Midwest 7.2 (5.4,9.6) 14.5 (11.5,18.3) 24.8 (19.9,30.8) 33.1 (26.6,41.3) 39.8 (31.6,50.0) 54.5 (42.7,69.6)

South 7.6 (6.6,8.9) 15.1 (13.4,17.0) 25.8 (22.6,29.4) 34.2 (29.6,39.6) 40.9 (34.9,48.0) 56.0 (46.5,67.3)

West 10.2 (8.5,12.3) 19.1 (16.1,22.8) 31.2 (25.9,37.6) 40.8 (33.5,49.7) 48.0 (39.2,58.8) 63.5 (51.4,78.4)

Coastal Status 2

Noncoastal 8.3 (7.0,9.8) 16.3 (14.3,18.7) 27.5 (23.9,31.6) 36.4 (31.3,42.3) 43.4 (36.9,50.9) 58.7 (49.1,70.2)

Coastal 9.3 (7.9,11.0) 18.4 (16.3,20.9) 31.2 (27.5,35.4) 41.4 (36.2,47.3) 49.1 (42.7,56.5) 65.9 (56.3,77.1)

Coastal/Inland Region 1,2

Pacific 10.5 (8.5,12.9) 19.9 (16.5,24.1) 32.8 (27.0,39.8) 42.7 (34.8,52.3) 50.4 (40.7,62.5) 66.8 (53.0,84.1)

Atlantic 10.4 (8.4,12.9) 20.4 (17.0,24.5) 34.5 (28.9,41.2) 45.7 (38.1,54.8) 53.9 (44.9,64.7) 72.1 (59.0,88.0)

Gulf of Mexico 7.6 (6.0,9.5) 14.9 (12.3,18.1) 25.7 (21.0,31.6) 33.8 (27.5,41.6) 40.3 (32.6,49.8) 53.9 (43.0,67.5)

Great Lakes 7.0 (5.2,9.5) 14.1 (11.0,18.2) 24.4 (19.2,30.9) 32.6 (25.8,41.1) 39.0 (30.9,49.2) 53.7 (42.0,68.8)

Inland Northeast 11.1 (8.8,13.8) 21.1 (17.6,25.3) 34.2 (28.7,40.7) 44.0 (37.0,52.3) 51.6 (43.1,62.0) 68.7 (56.6,83.4)

Inland Midwest 7.3 (5.4,9.9) 14.6 (11.4,18.7) 24.8 (19.7,31.2) 33.2 (26.3,42.0) 40.0 (31.3,51.1) 54.7 (42.2,71.0)

Inland South 7.1 (5.9,8.5) 13.9 (12.0,16.2) 23.7 (20.3,27.7) 31.6 (26.6,37.5) 37.5 (31.3,44.8) 52.2 (41.8,65.1)

Inland West 10.0 (7.8,12.9) 18.5 (14.5,23.5) 30.0 (23.4,38.4) 39.0 (30.4,50.1) 45.9 (35.8,58.9) 60.8 (47.6,77.7)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.64

## Table 16a. UFCR estimates (g/d ay raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, adults, 21 years and older, by demographic characteristics

Freshwater + Estuarine Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 1.5 (1.1,1.9) 3.6 (3.0,4.4) 7.6 (6.4,9.1) 11.5 (9.4,14.0) 14.7 (11.8,18.3) 23.0 (17.6,30.2)

Age

21 to <35 yrs 1.4 (1.0,1.9) 3.6 (2.9,4.3) 7.8 (6.6,9.3) 12.0 (9.8,14.6) 15.5 (12.5,19.2) 24.7 (18.7,32.5)

35 to <50 yrs 1.6 (1.2,2.3) 4.2 (3.1,5.6) 8.9 (6.5,12.1) 13.4 (9.5,18.7) 17.3 (12.1,24.7) 27.1 (18.1,40.6)

50 to <65 yrs 1.7 (1.2,2.4) 3.8 (2.9,5.0) 7.4 (5.7,9.5) 10.6 (8.2,13.8) 13.3 (10.1,17.4) 20.0 (14.6,27.2)

65+ yrs 1.0 (0.7,1.4) 2.7 (2.0,3.6) 5.7 (4.4,7.5) 8.7 (6.6,11.4) 11.1 (8.3,14.8) 16.8 (12.3,23.0)

Women of childbearing age (13 to 49 yrs) 0.9 (0.7,1.3) 2.6 (2.0,3.2) 5.6 (4.5,7.0) 8.5 (6.6,10.9) 11.0 (8.4,14.4) 17.1 (12.4,23.7)

Gender

Female 1.2 (0.9,1.6) 3.0 (2.5,3.7) 6.2 (5.1,7.5) 9.2 (7.4,11.3) 11.6 (9.2,14.7) 17.7 (13.3,23.5)

Male 1.8 (1.4,2.3) 4.4 (3.6,5.4) 9.3 (7.6,11.2) 13.8 (11.1,17.2) 17.8 (14.0,22.5) 27.5 (20.6,36.6)

Race/Ethnicity 1

Mexican American 2.5 (1.8,3.3) 6.2 (4.9,7.9) 12.9 (9.9,16.6) 19.1 (14.3,25.5) 24.5 (18.0,33.5) 37.6 (26.3,53.9)

Other Hispanic 2.0 (1.3,3.0) 5.1 (3.5,7.3) 10.5 (7.3,15.1) 15.3 (10.3,22.7) 19.6 (12.9,29.6) 29.7 (18.7,47.3)

Non

- Hispanic White 1.2 (0.9,1.6) 3.1 (2.5,3.8) 6.3 (5.1,7.7) 9.3 (7.5,11.6) 11.9 (9.3,15.1) 18.2 (13.6,24.3)

Non

- Hispanic Black 1.8 (1.3,2.4) 4.3 (3.4,5.5) 8.6 (6.7,11.1) 12.6 (9.6,16.5) 15.8 (11.9,21.1) 23.6 (17.2,32.6)

Other Race 3.0 (1.9,4.8) 6.9 (4.6,10.3) 13.3 (9.0,19.4) 19.0 (12.6,28.4) 23.6 (15.4,36.3) 35.0 (21.2,57.8)

Income

$0 to <$20K 1.0 (0.7,1.3) 2.7 (2.1,3.5) 6.4 (5.1,7.9) 10.0 (8.0,12.7) 13.3 (10.4,17.0) 21.9 (16.1,29.8)

$20 to <$45K 1.2 (0.9,1.7) 3.1 (2.5,4.0) 6.7 (5.5,8.3) 10.4 (8.5,12.7) 13.6 (10.9,16.8) 21.6 (16.8,27.7)

$40 to <$75K 1.4 (1.0,1.9) 3.4 (2.8,4.2) 7.0 (5.8,8.5) 10.5 (8.5,12.9) 13.4 (10.7,16.9) 21.3 (16.0,28.3)

$75+K 2.1 (1.6,2.7) 4.6 (3.7,5.7) 9.0 (7.1,11.4) 13.0 (9.9,17.0) 16.3 (12.1,21.9) 24.5 (17.1,35.1)

>$20K 1.4 (0.8,2.5) 3.5 (2.3,5.2) 7.4 (5.4,10.2) 11.1 (8.0,15.3) 14.5 (10.4,20.2) 23.1 (16.0,33.5)

Refused/Don ’ t Know Income 1.6 (0.6,4.3) 4.7 (2.1,10.1) 10.5 (5.6,19.8) 16.3 (9.0,29.5) 21.6 (12.0,38.6) 34.3 (17.1,68.7)

Income Missing 0.5 (0.1,2.3) 2.1 (0.7,6.4) 7.4 (2.9,19.2) 13.1 (5.5,31.3) 17.8 (7.8,40.4) 30.4 (14.0,65.8)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).65

## Table 16b. UFCR estimates (g/day raw weight, edible portion) : Total freshwater + estuarine trophic level 2 fish, adults, 21 years and older, by geographic area

Freshwater + Estuarine Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 1.5 (1.1,1.9) 3.6 (3.0,4.4) 7.6 (6.4,9.1) 11.5 (9.4,14.0) 14.7 (11.8,18.3) 23.0 (17.6,30.2)

Region 1

Northeast 2.1 (1.5,2.8) 4.8 (3.5,6.6) 9.5 (6.6,13.6) 13.9 (9.3,20.7) 17.6 (11.5,27.1) 27.0 (16.4,44.4)

Midwest 0.8 (0.5,1.1) 1.9 (1.3,2.8) 4.1 (2.7,6.1) 6.2 (4.0,9.5) 8.0 (5.1,12.7) 12.8 (7.7,21.2)

South 1.9 (1.3,2.8) 4.5 (3.4,5.9) 9.0 (7.2,11.3) 13.2 (10.6,16.4) 16.7 (13.3,21.0) 25.4 (19.4,33.2)

West 1.5 (1.0,2.3) 3.7 (2.7,5.0) 7.7 (5.7,10.2) 11.5 (8.6,15.4) 14.7 (10.9,19.9) 23.2 (16.7,32.1)

Coastal Status 2

Noncoastal 1.2 (0.9,1.5) 3.0 (2.4,3.8) 6.3 (4.8,8.3) 9.6 (7.1,13.0) 12.5 (9.0,17.4) 20.2 (13.9,29.3)

Coastal 2.1 (1.5,2.9) 4.9 (3.9,6.3) 9.8 (7.9,12.1) 14.1 (11.4,17.5) 17.7 (14.1,22.2) 26.5 (20.3,34.8)

Coastal/Inland Region 1,2

Pacific 1.9 (1.2,3.1) 4.6 (3.1,6.8) 9.2 (6.5,13.2) 13.5 (9.5,19.0) 16.9 (12.0,23.9) 25.9 (18.1,37.2)

Atlantic 2.8 (2.0,3.9) 6.2 (4.8,8.0) 11.6 (9.1,14.8) 16.4 (12.7,21.2) 20.4 (15.4,27.1) 29.6 (20.9,42.1)

Gulf of Mexico 2.3 (1.4,3.7) 5.3 (3.8,7.3) 10.4 (8.0,13.5) 14.6 (11.5,18.6) 18.4 (14.2,23.8) 27.1 (20.3,36.2)

Great Lakes 1.1 (0.7,1.7) 2.7 (1.8,3.9) 5.4 (3.7,8.0) 7.9 (5.3,12.0) 10.1 (6.6,15.5) 15.6 (9.7,25.1)

Inland Northeast 1.7 (1.1,2.7) 4.1 (2.6,6.6) 8.2 (4.8,14.1) 12.1 (6.7,21.9) 15.5 (8.3,28.8) 24.3 (12.4,47.5)

Inland Midwest 0.7 (0.5,1.0) 1.7 (1.1,2.5) 3.6 (2.3,5.6) 5.5 (3.5,8.9) 7.2 (4.4,11.9) 11.6 (6.7,20.0)

Inland South 1.6 (1.1,2.2) 3.7 (2.8,4.9) 7.6 (5.8,9.8) 11.3 (8.6,15.0) 14.6 (10.8,19.6) 23.1 (16.3,32.9)

Inland West 1.3 (0.9,1.8) 2.9 (2.2,4.0) 6.2 (4.6,8.3) 9.3 (6.8,12.9) 12.3 (8.7,17.3) 20.0 (13.6,29.4)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.66

## Table 17a. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 3 fish, adults, 21 years and older, by demographic characteristics

Freshwater + Estuarine Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 2.0 (1.6,2.5) 4.5 (3.9,5.3) 8.6 (7.2,10.2) 12.2 (9.9,15.0) 15.2 (12.0,19.3) 22.5 (16.6,30.6)

Age

21 to <35 yrs 1.6 (1.2,2.1) 3.9 (3.2,4.9) 8.1 (6.4,10.3) 12.4 (9.3,16.5) 16.1 (11.6,22.4) 25.8 (16.5,40.5)

35 to <50 yrs 2.1 (1.6,2.8) 4.8 (3.8,6.0) 9.0 (7.2,11.2) 12.7 (9.9,16.2) 15.6 (12.0,20.4) 22.6 (16.5,31.1)

50 to <65 yrs 2.6 (2.0,3.4) 5.3 (4.3,6.5) 9.4 (7.5,11.8) 12.9 (9.9,16.7) 15.7 (11.7,20.9) 22.2 (15.6,31.7)

65+ yrs 1.5 (1.2,2.1) 3.6 (2.8,4.7) 7.0 (5.6,8.9) 10.0 (7.9,12.7) 12.4 (9.6,15.9) 17.7 (13.0,24.0)

Women of childbearing age (13 to 49 yrs) 1.2 (0.9,1.5) 3.0 (2.5,3.5) 6.0 (4.9,7.2) 8.7 (7.0,10.9) 11.1 (8.7,14.1) 16.7 (12.4,22.7)

Gender

Female 1.6 (1.3,2.1) 3.7 (3.1,4.3) 6.9 (5.8,8.3) 9.7 (7.9,12.0) 12.0 (9.4,15.3) 17.5 (12.9,23.7)

Male 2.5 (2.0,3.2) 5.5 (4.7,6.6) 10.3 (8.5,12.5) 14.6 (11.6,18.4) 18.1 (14.0,23.5) 26.5 (19.0,37.1)

Race/Ethnicity 1

Mexican American 2.6 (2.0,3.4) 5.7 (4.6,7.1) 10.5 (8.2,13.4) 14.6 (11.1,19.2) 18.0 (13.3,24.2) 25.6 (18.1,36.2)

Other Hispanic 2.3 (1.6,3.3) 5.2 (3.7,7.4) 9.7 (6.8,13.7) 13.7 (9.5,19.7) 16.9 (11.5,24.8) 24.4 (16.0,37.3)

Non

- Hispanic White 1.7 (1.3,2.2) 3.8 (3.2,4.6) 7.2 (5.9,8.7) 10.1 (8.1,12.7) 12.5 (9.7,16.0) 18.2 (13.3,24.7)

Non

- Hispanic Black 2.7 (2.2,3.3) 5.7 (4.8,6.7) 10.3 (8.5,12.5) 14.3 (11.4,17.9) 17.5 (13.6,22.6) 25.3 (18.4,34.9)

Other Race 5.3 (4.0,7.0) 10.3 (7.8,13.6) 17.7 (12.4,25.4) 24.2 (15.5,37.6) 29.5 (17.9,48.5) 41.9 (23.5,74.7)

Income

$0 to <$20K 1.5 (1.1,2.1) 3.9 (3.1,4.8) 7.9 (6.6,9.5) 11.7 (9.7,14.2) 15.0 (12.2,18.4) 23.4 (18.1,30.1)

$20 to <$45K 1.7 (1.3,2.2) 3.9 (3.2,4.7) 7.5 (6.2,9.0) 10.7 (8.6,13.3) 13.4 (10.5,17.1) 20.1 (14.8,27.2)

$40 to <$75K 1.9 (1.5,2.4) 4.1 (3.4,5.1) 7.7 (6.2,9.6) 11.0 (8.5,14.2) 13.7 (10.2,18.3) 20.3 (13.7,30.2)

$75+K 2.7 (2.1,3.4) 5.6 (4.7,6.8) 10.1 (8.2,12.4) 13.9 (10.9,17.7) 17.0 (12.9,22.3) 24.2 (17.3,34.0)

>$20K 1.8 (1.1,2.9) 4.0 (2.9,5.5) 7.4 (5.5,10.1) 10.5 (7.6,14.5) 12.9 (9.1,18.4) 18.4 (12.1,28.0)

Refused/Don ’ t Know Income 2.4 (1.3,4.2) 6.0 (3.8,9.5) 12.2 (8.0,18.6) 17.6 (10.7,29.1) 22.2 (12.8,38.5) 32.7 (17.3,61.7)

Income Missing 0.9 (0.3,2.8) 3.2 (1.3,7.7) 8.9 (4.1,19.6) 14.8 (7.2,30.6) 19.8 (9.9,39.8) 30.2 (16.1,56.4)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).67

## Table 17b. UFCR estimates (g/day raw weight, edible portion) : Total freshwater + estuarine trophic level 3 fish, adults, 21 years and older, by geographic area

Freshwater + Estuarine Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 2.0 (1.6,2.5) 4.5 (3.9,5.3) 8.6 (7.2,10.2) 12.2 (9.9,15.0) 15.2 (12.0,19.3) 22.5 (16.6,30.6)

Region 1

Northeast 2.6 (2.0,3.4) 5.5 (4.4,6.8) 9.7 (7.7,12.1) 13.1 (10.2,16.8) 15.7 (12.0,20.6) 22.2 (15.8,31.3)

Midwest 1.0 (0.8,1.4) 2.3 (1.8,2.9) 4.3 (3.4,5.5) 6.2 (4.8,8.1) 7.8 (5.9,10.3) 12.0 (8.7,16.5)

South 2.7 (1.9,3.7) 5.6 (4.3,7.3) 10.2 (7.9,13.0) 14.2 (10.9,18.4) 17.5 (13.2,23.1) 25.2 (18.5,34.4)

West 2.3 (1.7,3.0) 4.9 (3.7,6.5) 9.2 (6.6,12.8) 13.3 (9.1,19.4) 16.7 (11.0,25.3) 25.2 (15.1,42.3)

Coastal Status 2

Noncoastal 1.7 (1.3,2.1) 3.8 (3.2,4.4) 7.2 (5.9,8.7) 10.2 (8.1,12.7) 12.6 (9.8,16.3) 18.6 (13.6,25.4)

Coastal 2.8 (2.1,3.7) 5.9 (4.7,7.5) 10.9 (8.7,13.7) 15.3 (11.8,19.7) 18.9 (14.2,25.1) 27.7 (19.1,40.1)

Coastal/Inland Region 1,2

Pacific 2.8 (1.9,4.1) 6.0 (4.2,8.7) 11.4 (7.7,16.9) 16.3 (10.5,25.5) 20.5 (12.5,33.7) 31.0 (16.6,57.7)

Atlantic 3.6 (2.7,4.7) 7.1 (5.8,8.8) 12.3 (10.0,15.2) 16.6 (13.1,21.0) 20.1 (15.4,26.2) 28.5 (20.4,39.7)

Gulf of Mexico 3.2 (2.0,5.0) 6.6 (4.8,9.2) 11.9 (8.9,15.7) 16.4 (12.5,21.7) 20.2 (15.1,27.0) 28.9 (20.9,40.0)

Great Lakes 1.4 (1.0,2.0) 3.0 (2.3,3.8) 5.4 (4.3,6.9) 7.6 (5.9,9.7) 9.3 (7.1,12.1) 13.7 (10.1,18.7)

Inland Northeast 2.3 (1.6,3.3) 4.9 (3.7,6.6) 8.8 (6.5,11.8) 11.9 (8.7,16.4) 14.3 (10.2,20.1) 20.3 (13.7,30.2)

Inland Midwest 0.9 (0.7,1.3) 2.1 (1.6,2.7) 3.9 (3.0,5.2) 5.7 (4.2,7.7) 7.2 (5.2,10.0) 11.2 (7.7,16.3)

Inland South 2.2 (1.7,3.0) 4.7 (3.8,5.9) 8.6 (6.7,10.9) 11.9 (9.1,15.5) 14.7 (11.0,19.6) 21.4 (15.2,30.0)

Inland West 1.9 (1.4,2.5) 3.9 (3.1,5.0) 7.3 (5.4,9.9) 10.3 (7.2,14.6) 12.9 (8.8,18.9) 19.0 (12.2,29.4)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.68

## Table 18a. UFCR esti mates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, adults, 21 years and older, by demographic characteristics

Freshwater + Estuarine Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 0.6 (0.4,0.9) 1.9 (1.5,2.5) 5.1 (4.0,6.4) 9.1 (7.0,11.7) 13.2 (10.0,17.4) 27.1 (19.4,38.0)

Age

21 to <35 yrs 0.3 (0.2,0.5) 1.0 (0.7,1.4) 3.0 (2.2,4.1) 5.8 (4.2,8.1) 9.1 (6.2,13.3) 20.9 (12.1,36.0)

35 to <50 yrs 0.6 (0.4,0.9) 1.7 (1.2,2.3) 4.2 (3.1,5.8) 7.3 (5.2,10.2) 10.4 (7.2,15.0) 20.4 (13.2,31.7)

50 to <65 yrs 1.0 (0.7,1.5) 2.9 (2.1,4.0) 7.4 (5.4,10.2) 12.8 (9.0,18.2) 18.2 (12.6,26.4) 37.0 (23.4,58.4)

65+ yrs 0.8 (0.5,1.3) 2.4 (1.5,3.7) 6.0 (3.8,9.5) 10.6 (6.7,16.8) 15.1 (9.5,24.0) 29.7 (18.1,48.7)

Women of childbearing age (13 to 49 yrs) 0.3 (0.2,0.5) 1.0 (0.7,1.5) 2.9 (2.1,3.9) 5.3 (3.8,7.4) 7.7 (5.4,11.0) 16.1 (10.4,24.8)

Gender

Female 0.5 (0.4,0.7) 1.6 (1.2,2.1) 4.2 (3.3,5.4) 7.5 (5.7,9.7) 10.8 (8.1,14.3) 21.4 (15.2,30.0)

Male 0.7 (0.5,1.1) 2.3 (1.7,3.0) 6.0 (4.6,7.8) 10.8 (8.2,14.3) 15.8 (11.7,21.3) 32.8 (22.7,47.6)

Race/Ethnicity 1

Mexican American 0.6 (0.4,0.9) 1.9 (1.3,2.7) 5.1 (3.6,7.3) 9.2 (6.3,13.6) 13.5 (8.8,20.6) 28.8 (16.9,49.0)

Other Hispanic 0.5 (0.3,0.9) 1.7 (0.9,3.0) 4.6 (2.5,8.7) 8.2 (4.1,16.5) 11.7 (5.5,25.1) 23.4 (9.8,55.9)

Non

- Hispanic White 0.5 (0.4,0.8) 1.5 (1.2,2.0) 3.9 (3.0,5.1) 6.8 (5.1,9.0) 9.6 (7.2,13.0) 18.7 (13.1,26.7)

Non

- Hispanic Black 1.1 (0.7,1.6) 3.2 (2.3,4.5) 8.4 (6.2,11.4) 14.7 (10.7,20.2) 21.1 (15.0,29.6) 41.2 (28.0,60.8)

Other Race 2.4 (1.3,4.3) 6.6 (3.8,11.3) 16.1 (9.3,27.7) 28.2 (16.0,49.7) 40.2 (22.5,72.0) 77.9 (41.4,146.5)

Income

$0 to <$20K 0.5 (0.3,0.7) 1.6 (1.2,2.2) 4.7 (3.6,6.0) 8.6 (6.5,11.2) 12.6 (9.5,16.7) 26.4 (18.8,37.2)

$20 to <$45K 0.5 (0.4,0.8) 1.7 (1.2,2.3) 4.5 (3.4,6.1) 8.3 (6.1,11.2) 12.1 (8.8,16.7) 25.1 (17.4,36.1)

$40 to <$75K 0.6 (0.4,0.9) 1.9 (1.4,2.5) 5.2 (4.0,6.7) 9.4 (7.0,12.6) 13.7 (10.0,18.8) 28.5 (19.6,41.4)

$75+K 0.8 (0.5,1.1) 2.2 (1.7,2.9) 5.5 (4.2,7.2) 9.4 (7.0,12.7) 13.5 (9.8,18.6) 26.9 (17.9,40.4)

>$20K 0.6 (0.3,1.2) 2.0 (1.2,3.6) 5.5 (3.2,9.3) 9.5 (5.8,15.5) 13.7 (8.5,22.2) 27.2 (16.8,44.2)

Refused/Don ’ t Know Income 0.6 (0.3,1.2) 2.2 (1.3,3.5) 6.7 (4.3,10.5) 12.8 (7.9,20.7) 19.6 (11.5,33.4) 43.7 (23.6,80.6)

Income Missing 0.1 (0.0,0.5) 0.9 (0.3,2.4) 3.7 (1.5,9.0) 8.2 (3.7,18.3) 13.0 (6.1,27.8) 28.3 (13.5,59.3)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).69

## Table 18b. UFCR estimates (g/day raw weight, edible portion) : Total freshwater + estuarine trophic level 4 fish, adults, 21 years and older, by geographic area

Freshwater + Estuarine Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Adults ( ≥ 21 yrs) 0.6 (0.4,0.9) 1.9 (1.5,2.5) 5.1 (4.0,6.4) 9.1 (7.0,11.7) 13.2 (10.0,17.4) 27.1 (19.4,38.0)

Region 1

Northeast 0.4 (0.3,0.6) 1.3 (0.9,1.8) 3.2 (2.3,4.4) 5.5 (4.0,7.6) 7.8 (5.5,10.9) 15.1 (10.3,22.1)

Midwest 0.5 (0.3,1.1) 1.8 (1.0,3.1) 4.9 (2.9,8.1) 8.9 (5.4,14.5) 13.0 (8.0,21.2) 26.6 (16.1,44.0)

South 0.8 (0.5,1.1) 2.4 (1.8,3.2) 6.3 (4.9,8.2) 11.2 (8.5,14.9) 16.2 (12.1,21.8) 32.7 (22.8,46.8)

West 0.7 (0.5,0.9) 1.9 (1.5,2.5) 5.0 (3.6,6.9) 8.9 (5.9,13.3) 12.8 (8.0,20.5) 27.1 (14.6,50.0)

Coastal Status 2

Noncoastal 0.6 (0.4,0.9) 1.8 (1.3,2.4) 4.9 (3.6,6.5) 8.7 (6.4,11.8) 12.6 (9.2,17.5) 25.8 (17.8,37.5)

Coastal 0.7 (0.5,1.0) 2.1 (1.6,2.7) 5.4 (4.3,7.0) 9.7 (7.4,12.7) 14.2 (10.5,19.1) 29.0 (20.2,41.8)

Coastal/Inland Region 1,2

Pacific 0.7 (0.5,1.1) 2.2 (1.5,3.1) 5.9 (3.9,8.7) 10.5 (6.6,16.7) 15.6 (9.1,26.5) 33.8 (17.1,66.9)

Atlantic 0.8 (0.5,1.1) 2.2 (1.7,3.0) 5.8 (4.3,7.8) 10.2 (7.4,13.9) 14.7 (10.5,20.7) 28.8 (19.6,42.5)

Gulf of Mexico 0.7 (0.5,1.2) 2.1 (1.5,3.0) 5.4 (3.8,7.7) 9.7 (6.7,14.2) 13.8 (9.1,20.9) 28.1 (17.1,46.1)

Great Lakes 0.5 (0.2,0.9) 1.5 (0.9,2.5) 4.0 (2.5,6.5) 7.3 (4.5,11.9) 10.9 (6.6,18.3) 22.9 (12.8,41.0)

Inland Northeast 0.4 (0.3,0.6) 1.2 (0.8,1.7) 3.1 (2.2,4.4) 5.3 (3.7,7.6) 7.5 (5.1,10.9) 14.6 (9.7,22.1)

Inland Midwest 0.6 (0.3,1.2) 1.8 (1.0,3.4) 5.1 (3.0,8.8) 9.3 (5.5,15.7) 13.5 (8.1,22.5) 27.8 (16.4,46.9)

Inland South 0.7 (0.5,1.1) 2.3 (1.7,3.1) 6.1 (4.6,8.1) 10.9 (8.1,14.8) 15.8 (11.5,21.9) 32.5 (22.0,48.0)

Inland West 0.6 (0.5,0.9) 1.7 (1.3,2.4) 4.3 (3.0,6.3) 7.4 (4.7,11.7) 10.7 (6.4,17.8) 20.9 (10.9,40.3)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.70

## Table 19a. UFCR estimates (g/day raw weight, edible portion): Total fish, youth

, <21 years, by demographic characteristics

All Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 4.9 (4.0,6.1) 12.5 (10.6,14.7) 24.0 (20.5,28.3) 34.2 (28.6,40.8) 42.4 (35.1,51.3) 61.7 (49.1,77.5)

Age

1 to <3 yrs 2.7 (1.9,3.8) 6.7 (5.0,9.0) 12.7 (9.8,16.4) 17.9 (13.8,23.2) 22.3 (17.0,29.2) 32.8 (24.1,44.4)

3 to <6 yrs 3.6 (2.6,5.1) 8.8 (6.9,11.2) 16.3 (13.3,19.8) 22.5 (18.4,27.7) 27.5 (22.2,34.1) 39.6 (31.4,50.1)

6 to <11 yrs 5.1 (3.6,7.3) 12.8 (9.2,17.7) 24.2 (16.7,35.1) 34.1 (22.6,51.4) 41.9 (26.9,65.0) 58.6 (36.6,93.8)

11 to <16 yrs 5.0 (3.6,7.0) 12.3 (9.5,15.9) 22.6 (17.9,28.5) 30.9 (24.5,39.0) 37.4 (29.8,47.1) 53.2 (42.7,66.2)

16 to <18 yrs 6.1 (4.3,8.8) 14.5 (11.5,18.3) 26.9 (22.0,32.7) 36.8 (30.4,44.7) 44.3 (36.4,54.0) 61.0 (49.7,74.8)

18 to <21 yrs 9.1 (6.3,13.0) 20.9 (15.5,28.2) 38.5 (28.2,52.5) 53.4 (37.9,75.4) 65.0 (45.3,93.3) 88.1 (60.6,128.0)

Gender

Female 4.5 (3.6,5.6) 11.4 (9.7,13.5) 21.9 (19.0,25.4) 30.8 (26.7,35.5) 37.7 (32.6,43.5) 52.9 (44.4,63.1)

Male 5.5 (4.4,6.8) 13.5 (11.2,16.3) 26.1 (21.2,32.1) 37.6 (29.7,47.6) 47.1 (36.4,60.9) 69.2 (51.8,92.4)

Race/Ethnicity 1

Mexican American 4.4 (3.4,5.8) 10.9 (9.0,13.2) 20.3 (17.1,24.1) 28.9 (24.2,34.6) 36.2 (30.0,43.8) 54.3 (43.4,67.8)

Other Hispanic 4.2 (2.7,6.5) 10.9 (7.5,15.9) 20.8 (14.8,29.1) 28.7 (20.5,40.1) 35.0 (24.9,49.2) 49.4 (34.2,71.3)

Non

- Hispanic White 4.2 (3.3,5.5) 10.9 (8.7,13.7) 21.4 (16.7,27.5) 30.8 (23.3,40.6) 38.9 (28.9,52.4) 58.9 (41.0,84.6)

Non

- Hispanic Black 7.8 (6.0,10.1) 16.8 (13.7,20.7) 28.9 (23.9,35.0) 38.6 (32.1,46.3) 45.8 (38.2,55.0) 62.3 (51.7,74.9)

Other Race 10.3 (7.4,14.2) 23.8 (18.6,30.3) 40.9 (31.9,52.4) 53.4 (40.3,70.8) 62.7 (46.6,84.2) 83.4 (62.2,111.8)

Income

$0 to <$20K 5.0 (3.8,6.7) 13.0 (10.4,16.3) 24.5 (20.2,29.8) 33.7 (27.8,41.0) 41.0 (33.9,49.8) 57.3 (46.8,70.2)

$20 to < $45K 4.9 (3.9,6.2) 12.1 (10.2,14.4) 23.2 (19.8,27.2) 33.3 (27.9,39.8) 41.7 (33.8,51.4) 61.9 (44.3,86.5)

$40 to <$75K 5.0 (3.7,6.6) 13.0 (9.9,16.9) 26.0 (19.3,35.1) 38.0 (27.6,52.5) 46.9 (33.4,65.9) 69.1 (47.6,100.5)

$75+K 5.1 (3.9,6.6) 12.5 (10.0,15.7) 23.5 (18.7,29.4) 32.4 (25.4,41.4) 39.7 (30.4,51.7) 56.5 (41.5,76.9)

>$20K 3.8 (1.8,7.9) 8.2 (4.5,15.0) 15.4 (8.8,27.1) 21.2 (12.0,37.3) 25.9 (14.4,46.7) 38.0 (20.8,69.6) Refused/Don ’ t Know

Income 4.2 (0.9,18.7) 10.7 (2.4,48.1) 27.5 (6.8,111.8) 43.8 (15.4,124.3) 54.8 (25.4,118.3) 76.2 (44.7,130.1)

Income Missing 6.4 (2.6,15.7) 17.0 (7.4,39.0) 39.2 (15.6,98.4) 55.9 (23.4,133.5) 67.9 (30.1,152.8) 87.2 (44.2,172.2)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: n on

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).71

## Table 19b. UFCR estimates (g/day raw weight, edible portion): Total fish, youth

, <21 years, by geographic area

All Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 4.9 (4.0,6.1) 12.5 (10.6,14.7) 24.0 (20.5,28.3) 34.2 (28.6,40.8) 42.4 (35.1,51.3) 61.7 (49.1,77.5)

Region 1

Northeast 5.7 (4.1,7.8) 14.1 (11.2,17.7) 27.6 (21.1,36.1) 40.4 (27.4,59.6) 50.6 (31.3,82.0) 75.1 (43.6,129.5)

Midwest 3.3 (2.5,4.3) 8.8 (7.4,10.5) 17.5 (15.1,20.3) 25.5 (21.9,29.6) 31.7 (27.1,37.1) 47.7 (40.2,56.6)

South 5.7 (4.2,7.7) 13.5 (10.7,17.0) 24.6 (19.9,30.3) 33.9 (27.4,41.9) 41.1 (33.0,51.3) 58.5 (45.6,75.1)

West 5.9 (4.1,8.7) 14.6 (10.3,20.6) 27.8 (19.5,39.7) 39.2 (27.3,56.3) 47.6 (33.1,68.4) 67.0 (46.4,96.8)

Coastal Status 2

Noncoastal 4.5 (3.5,5.7) 11.5 (9.3,14.2) 22.2 (17.6,28.1) 31.7 (24.3,41.4) 39.8 (29.8,53.2) 58.8 (41.5,83.2)

Coastal 5.9 (4.7,7.4) 14.5 (12.2,17.1) 27.2 (23.4,31.8) 38.0 (32.4,44.6) 46.4 (39.1,55.1) 65.7 (54.1,79.7)

Coastal/Inland Region 1,2

Pacific 5.9 (4.3,8.1) 15.1 (11.3,20.0) 28.8 (22.2,37.5) 40.2 (31.1,52.0) 48.9 (37.7,63.4) 68.6 (52.1,90.1)

Atlantic 7.2 (5.4,9.6) 16.4 (13.3,20.2) 29.3 (24.4,35.3) 40.3 (33.6,48.3) 48.6 (40.4,58.5) 68.2 (55.8,83.4)

Gulf of Mexico 7.0 (4.3,11.5) 16.0 (11.0,23.3) 29.8 (20.6,43.3) 41.5 (27.4,62.9) 51.6 (33.1,80.5) 72.6 (45.2,116.6)

Great Lakes 3.9 (2.9,5.2) 10.2 (8.2,12.8) 20.1 (15.9,25.5) 28.4 (21.7,37.1) 35.5 (26.9,46.7) 50.4 (36.9,68.9)

Inland Northeast 5.1 (3.6,7.2) 12.9 (9.9,16.8) 25.9 (17.8,37.6) 39.1 (21.7,70.4) 50.5 (24.6,103.6) 76.6 (35.3,166.1)

Inland Midwest 3.1 (2.3,4.1) 8.3 (6.8,10.1) 16.4 (14.0,19.3) 24.0 (20.4,28.2) 29.9 (25.4,35.3) 45.6 (38.1,54.6)

Inland South 4.9 (3.7,6.4) 12.1 (9.6,15.2) 22.0 (17.7,27.3) 30.3 (24.3,37.6) 36.6 (29.4,45.5) 51.3 (41.2,63.8)

Inland West 6.0 (3.5,10.1) 14.2 (8.9,22.8) 27.1 (16.1,45.5) 38.4 (22.2,66.5) 46.6 (26.9,80.8) 65.8 (38.5,112.5)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not dire ctly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.72

## Table 20a. UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, youth

, <21 years, by demographic

characteristics

Freshwater + Estuarine

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 1.1 (0.8,1.4) 3.3 (2.7,4.2) 8.0 (6.6,9.8) 12.9 (10.5,15.9) 17.3 (13.9,21.6) 28.9 (22.2,37.7)

Age

1 to <3 yrs 0.6 (0.3,1.2) 1.9 (1.2,3.2) 4.7 (3.1,7.0) 7.5 (5.1,10.9) 10.1 (6.9,14.7) 17.1 (11.3,25.9)

3 to <6 yrs 0.7 (0.4,1.3) 2.4 (1.6,3.6) 5.8 (4.1,8.3) 9.5 (6.7,13.5) 12.9 (8.9,18.7) 22.3 (13.8,36.1)

6 to <11 yrs 1.1 (0.8,1.5) 3.3 (2.5,4.4) 7.7 (5.7,10.5) 12.3 (8.8,17.3) 16.3 (11.3,23.5) 27.3 (18.3,40.7)

11 to <16 yrs 1.1 (0.7,1.7) 3.4 (2.4,4.9) 8.3 (6.4,10.7) 13.2 (10.4,16.7) 17.7 (14.0,22.4) 29.6 (22.9,38.2)

16 to <18 yrs 1.4 (0.7,2.8) 4.2 (2.5,6.9) 9.5 (6.5,13.8) 14.9 (10.6,21.0) 19.3 (13.7,27.2) 32.2 (22.6,45.9)

18 to <21 yrs 1.7 (1.1,2.7) 5.0 (3.5,7.2) 11.6 (8.3,16.2) 18.2 (12.8,25.8) 23.8 (16.4,34.4) 37.5 (24.3,57.8)

Gender

Female 0.9 (0.7,1.3) 3.0 (2.3,4.0) 7.4 (5.8,9.5) 12.1 (9.5,15.4) 16.2 (12.5,20.9) 27.2 (20.4,36.3)

Male 1.2 (0.9,1.6) 3.6 (2.9,4.5) 8.6 (7.0,10.5) 13.7 (11.1,16.9) 18.4 (14.7,23.0) 30.5 (23.1,40.2)

Race/Ethnicity 1

Mexican American 1.3 (1.0,1.9) 3.9 (3.0,5.1) 8.7 (6.9,11.0) 13.6 (10.8,17.2) 18.0 (14.1,23.0) 29.9 (22.2,40.2)

Other Hispanic 1.1 (0.6,2.2) 3.6 (1.9,6.9) 8.7 (4.5,16.9) 13.9 (6.8,28.4) 18.6 (8.8,39.6) 30.3 (13.4,68.6)

Non

- Hispanic White 0.7 (0.5,1.0) 2.2 (1.7,3.0) 5.1 (3.9,6.7) 8.1 (6.1,10.8) 10.7 (7.9,14.5) 18.0 (12.6,25.7)

Non

- Hispanic Black 2.6 (1.8,3.9) 7.2 (5.3,9.9) 15.1 (11.2,20.1) 22.4 (16.7,30.0) 28.5 (21.2,38.2) 44.5 (32.8,60.4)

Other Race 2.7 (1.7,4.2) 7.4 (4.9,11.1) 15.3 (9.9,23.6) 22.5 (14.1,35.6) 28.2 (17.3,45.9) 43.0 (25.7,71.8)

Income

$0 to <$20K 1.1 (0.7,1.7) 3.6 (2.6,5.0) 8.7 (6.6,11.6) 14.0 (10.7,18.4) 18.7 (14.2,24.6) 30.2 (22.4,40.9)

$20 to <$45K 1.2 (0.8,1.7) 3.4 (2.5,4.7) 8.2 (6.2,10.7) 13.0 (9.9,17.1) 17.2 (13.0,22.9) 28.4 (21.0,38.5)

$40 to <$75K 0.9 (0.6,1.4) 2.9 (2.0,4.1) 7.0 (5.0,9.7) 11.4 (8.3,15.6) 15.4 (11.3,21.1) 26.4 (19.1,36.4)

$75+K 1.2 (0.9,1.6) 3.6 (3.0,4.4) 8.3 (6.8,10.1) 13.1 (10.5,16.3) 17.3 (13.6,22.0) 29.0 (21.5,39.1)

>$20K 0.6 (0.2,2.4) 2.2 (0.9,5.5) 6.1 (3.1,12.0) 10.2 (5.3,19.6) 14.4 (7.6,27.4) 24.7 (12.5,48.8)

Refused/Don ’ t Know Income 0.3 (0.1,0.9) 1.3 (0.6,3.0) 4.4 (1.8,11.0) 8.8 (3.2,24.6) 14.6 (4.8,45.0) 32.6 (8.9,119.7)

Income Missing 1.0 (0.3,3.3) 4.3 (1.0,18.6) 15.0 (2.7,84.4) 25.6 (5.2,126.3) 35.6 (8.2,155.0) 55.4 (15.5,198.1)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).73

## Table 20b. UFCR estimates (g/day raw weight, edible portion): Freshwater + estuarine fish, youth

, <21 years, by geographic area

Freshwater + Estuarine

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 1.1 (0.8,1.4) 3.3 (2.7,4.2) 8.0 (6.6,9.8) 12.9 (10.5,15.9) 17.3 (13.9,21.6) 28.9 (22.2,37.7)

Region 1

Northeast 0.9 (0.5,1.4) 2.6 (1.7,4.0) 6.0 (3.8,9.5) 9.5 (5.9,15.4) 12.6 (7.7,20.5) 20.7 (12.4,34.6)

Midwest 0.7 (0.5,1.0) 2.3 (1.6,3.2) 5.8 (4.2,8.1) 10.0 (7.0,14.4) 14.0 (9.6,20.5) 25.2 (16.6,38.4)

South 1.6 (1.0,2.6) 4.6 (3.2,6.8) 10.4 (7.5,14.4) 16.2 (11.8,22.2) 21.3 (15.4,29.5) 34.7 (24.7,48.7)

West 1.2 (0.8,1.7) 3.5 (2.5,5.0) 8.3 (5.9,11.8) 13.3 (9.3,19.1) 17.7 (12.1,25.8) 28.6 (18.5,44.1)

Coastal Status 2

Noncoastal 0.9 (0.6,1.2) 2.7 (2.1,3.4) 6.3 (5.1,7.8) 10.1 (8.1,12.6) 13.7 (10.9,17.1) 22.9 (17.7,29.8)

Coastal 1.6 (1.1,2.3) 4.8 (3.5,6.5) 11.1 (8.4,14.8) 17.5 (13.1,23.4) 22.9 (16.9,31.0) 37.0 (26.3,52.0)

Coastal/Inland Region 1,2

Pacific 1.5 (0.9,2.3) 4.5 (3.0,6.8) 10.6 (7.2,15.6) 16.7 (11.2,25.0) 22.0 (14.5,33.3) 34.6 (21.8,54.8)

Atlantic 1.9 (1.3,2.9) 5.4 (3.8,7.7) 12.0 (8.6,16.7) 18.4 (13.2,25.4) 23.8 (17.1,33.1) 37.2 (25.9,53.3)

Gulf of Mexico 2.3 (1.1,4.9) 6.3 (3.3,11.8) 13.8 (7.8,24.4) 21.3 (11.9,38.0) 27.9 (15.3,50.9) 46.4 (25.4,84.7)

Great Lakes 1.0 (0.6,1.7) 3.3 (2.1,5.3) 8.6 (5.3,14.0) 14.3 (8.5,24.0) 19.4 (11.3,33.3) 32.9 (18.7,58.1)

Inland Northeast 0.7 (0.4,1.2) 2.2 (1.3,3.6) 5.1 (3.0,8.5) 7.8 (4.5,13.6) 10.1 (5.7,17.9) 16.2 (8.8,29.8)

Inland Midwest 0.6 (0.4,0.9) 1.9 (1.3,2.7) 4.7 (3.4,6.5) 8.0 (5.7,11.1) 11.2 (7.8,15.9) 19.9 (13.1,30.3)

Inland South 1.2 (0.8,1.9) 3.6 (2.6,5.2) 8.2 (6.2,11.0) 12.8 (9.7,16.9) 16.8 (12.7,22.2) 27.5 (20.6,36.8)

Inland West 1.0 (0.7,1.5) 2.9 (2.0,4.2) 6.7 (4.8,9.6) 10.6 (7.4,15.2) 14.1 (9.7,20.6) 23.0 (15.1,35.2)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estua ri es and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.74

## Table 21a. UFCR estima tes (g/day raw weight, edible portion): Marine fish, youth

, <21 years, by demographic characteristics

Marine Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 3.1 (2.4,4.1) 8.1 (6.5,10.0) 16.4 (13.3,20.3) 24.3 (19.3,30.5) 31.0 (24.2,39.6) 48.2 (35.6,65.2)

Age

1 to <3 yrs 1.7 (1.2,2.5) 4.4 (3.2,6.0) 8.8 (6.6,11.9) 12.9 (9.6,17.4) 16.5 (12.1,22.6) 25.2 (17.7,35.7)

3 to <6 yrs 2.3 (1.6,3.4) 5.7 (4.3,7.6) 11.0 (8.6,14.2) 15.8 (12.4,20.3) 19.7 (15.3,25.4) 29.3 (22.4,38.4)

6 to <11 yrs 3.2 (2.1,5.0) 8.3 (5.5,12.5) 16.7 (10.3,27.0) 24.2 (14.0,41.9) 30.2 (16.9,54.1) 44.5 (24.1,82.4)

11 to <16 yrs 3.1 (2.1,4.5) 7.7 (5.6,10.6) 14.7 (10.9,19.8) 20.6 (15.2,27.9) 25.3 (18.6,34.5) 36.8 (26.8,50.5)

16 to <18 yrs 3.9 (2.8,5.5) 9.6 (7.5,12.3) 18.3 (14.6,23.0) 25.7 (20.4,32.4) 31.7 (25.0,40.2) 45.6 (35.5,58.4)

18 to <21 yrs 5.6 (3.7,8.5) 14.3 (9.8,20.9) 29.4 (19.3,44.8) 43.5 (26.7,70.8) 54.1 (31.7,92.4) 80.3 (45.3,142.2)

Gender

Female 2.7 (2.1,3.6) 7.1 (5.8,8.8) 14.2 (11.8,17.1) 20.5 (17.0,24.7) 25.6 (21.1,31.1) 37.9 (30.9,46.5)

Male 3.5 (2.6,4.7) 9.1 (7.1,11.7) 18.7 (14.4,24.4) 28.1 (21.0,37.7) 36.2 (26.3,49.7) 56.7 (37.7,85.4)

Race/Ethnicity 1

Mexican American 2.4 (1.7,3.3) 6.1 (4.7,8.0) 12.2 (9.8,15.2) 18.0 (14.6,22.3) 22.9 (18.4,28.5) 36.1 (28.3,45.9)

Other Hispanic 2.3 (1.4,3.6) 6.2 (4.2,9.2) 12.6 (9.1,17.5) 18.1 (13.2,24.7) 22.2 (16.0,30.8) 31.7 (21.3,47.3)

Non

- Hispanic White 3.0 (2.2,4.2) 8.0 (5.9,10.8) 16.4 (12.1,22.2) 24.5 (17.7,33.8) 31.4 (22.3,44.3) 49.9 (32.1,77.6)

Non

- Hispanic Black 3.6 (2.7,4.8) 8.4 (6.8,10.4) 15.4 (12.8,18.6) 21.3 (17.7,25.5) 25.9 (21.6,31.1) 37.0 (30.6,44.8)

Other Race 6.3 (4.4,9.0) 15.8 (11.6,21.4) 29.8 (22.8,38.9) 40.7 (30.6,54.3) 48.6 (35.1,67.4) 67.8 (45.2,101.9)

Income

$0 to <$20K 2.9 (2.2,4.0) 7.8 (6.2,9.9) 15.7 (12.5,19.8) 22.7 (17.8,29.0) 28.5 (22.2,36.6) 43.1 (33.1,56.1)

$20 to <$45K 2.9 (2.3,3.7) 7.5 (6.1,9.1) 15.2 (12.5,18.4) 22.6 (18.1,28.3) 29.3 (22.2,38.6) 47.2 (28.0,79.6)

$40 to <$75K 3.2 (2.3,4.5) 8.5 (6.1,11.8) 18.1 (12.4,26.4) 27.4 (18.1,41.7) 35.5 (22.7,55.6) 56.5 (33.1,96.4)

$75+K 3.4 (2.4,4.8) 8.8 (6.6,11.6) 17.0 (13.0,22.2) 24.2 (18.3,32.2) 30.1 (22.4,40.3) 44.3 (32.3,60.8)

>$20K 2.5 (1.1,6.0) 5.5 (2.8,10.7) 10.5 (5.4,20.3) 15.1 (7.7,29.3) 18.5 (9.3,36.8) 26.5 (12.9,54.5)

Refused/Don ’ t Know Income 2.5 (0.6,11.4) 7.1 (1.5,34.2) 20.0 (4.3,93.7) 35.3 (9.6,129.5) 47.1 (16.5,134.6) 70.9 (36.2,138.6)

Income Missing 3.9 (1.5,9.9) 11.0 (4.6,26.5) 25.9 (11.1,60.7) 39.4 (17.4,89.3) 49.2 (22.8,106.3) 69.5 (35.8,134.6)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).75

## Table 21b. UFCR estimates (g/day raw weight, edible portion): Marine fish, youth

, <21 years, by geographic area

Marine Finfish and Shellfish Perce ntiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 3.1 (2.4,4.1) 8.1 (6.5,10.0) 16.4 (13.3,20.3) 24.3 (19.3,30.5) 31.0 (24.2,39.6) 48.2 (35.6,65.2)

Region 1

Northeast 4.0 (2.6,6.0) 10.3 (7.3,14.6) 21.4 (14.2,32.0) 32.7 (18.8,56.9) 43.0 (21.9,84.5) 68.5 (31.1,150.9)

Midwest 2.2 (1.6,3.0) 5.8 (4.5,7.5) 12.0 (9.8,14.6) 17.6 (14.7,21.1) 22.1 (18.5,26.4) 33.8 (28.2,40.6)

South 3.3 (2.4,4.4) 8.0 (6.2,10.3) 15.6 (12.2,19.9) 22.3 (17.2,28.9) 27.9 (21.2,36.6) 42.4 (31.1,57.8)

West 3.7 (2.3,6.1) 9.6 (6.0,15.3) 19.5 (12.0,31.8) 28.6 (17.3,47.0) 35.5 (21.9,57.8) 51.0 (32.2,80.8)

Coastal Status 2

Noncoastal 2.9 (2.1,4.1) 7.7 (5.7,10.3) 15.8 (11.5,21.6) 23.2 (16.3,33.0) 29.8 (20.4,43.7) 47.2 (29.4,75.8)

Coastal 3.5 (2.7,4.4) 8.8 (7.4,10.5) 17.8 (15.1,20.9) 26.0 (21.9,30.7) 32.9 (27.6,39.2) 49.5 (40.0,61.4)

Coastal/Inland Region 1,2

Pacific 3.5 (2.4,5.0) 9.3 (6.9,12.6) 19.2 (14.5,25.4) 28.6 (21.5,38.0) 35.7 (27.1,47.2) 50.8 (37.4,69.0)

Atlantic 4.3 (3.2,5.9) 10.2 (7.9,13.1) 19.5 (15.3,24.9) 27.9 (21.7,35.8) 35.0 (27.0,45.4) 53.5 (39.2,73.2)

Gulf of Mexico 3.8 (2.6,5.7) 9.3 (6.6,13.2) 18.7 (12.8,27.3) 28.0 (18.3,42.9) 36.2 (22.8,57.5) 56.6 (33.7,95.2)

Great Lakes 2.2 (1.6,3.1) 6.1 (4.9,7.7) 12.6 (10.1,15.6) 18.5 (14.4,23.7) 23.3 (17.7,30.7) 34.4 (24.8,47.7)

Inland Northeast 3.7 (2.4,5.8) 9.8 (6.7,14.4) 20.7 (12.0,35.8) 32.8 (14.4,74.5) 44.5 (16.9,117.4) 73.6 (25.7,211.4)

Inland Midwest 2.1 (1.5,3.1) 5.8 (4.3,7.8) 11.8 (9.2,15.1) 17.3 (13.9,21.5) 21.8 (17.8,26.8) 33.6 (27.7,40.8)

Inland South 2.9 (2.1,3.9) 7.3 (5.5,9.7) 14.3 (10.7,19.1) 20.3 (15.0,27.4) 25.2 (18.5,34.3) 37.2 (27.2,50.9)

Inland West 3.9 (2.0,7.6) 9.8 (5.2,18.6) 19.7 (9.9,39.4) 28.5 (13.9,58.3) 35.4 (17.4,71.8) 51.1 (26.1,100.0)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.76

## Table 22a. UFCR estimates (g/day raw weight, edible portion): Total finfish, youth

, <21 years, by demographic cha racteristics

All Finfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 3.8 (3.0,4.8) 9.4 (7.9,11.3) 18.5 (15.4,22.2) 26.8 (21.8,32.9) 33.8 (26.9,42.5) 51.7 (39.1,68.4)

Age

1 to <3 yrs 2.1 (1.5,2.9) 5.2 (4.1,6.8) 10.1 (8.1,12.7) 14.6 (11.6,18.4) 18.4 (14.5,23.5) 27.2 (20.4,36.2)

3 to <6 yrs 2.7 (1.9,4.0) 6.6 (5.1,8.7) 12.8 (10.2,16.0) 18.2 (14.5,22.8) 22.6 (17.8,28.6) 33.1 (25.4,43.2)

6 to <11 yrs 4.2 (2.9,6.1) 10.4 (7.3,14.7) 20.1 (13.3,30.4) 28.1 (17.6,45.0) 34.6 (20.8,57.6) 49.9 (28.4,87.7)

11 to <16 yrs 3.8 (2.5,5.6) 9.1 (6.6,12.4) 16.6 (12.7,21.8) 23.1 (17.7,30.2) 28.7 (22.0,37.5) 42.7 (32.2,56.5)

16 to <18 yrs 4.5 (3.1,6.5) 10.5 (8.0,14.0) 19.7 (15.1,25.6) 27.5 (20.9,36.1) 34.2 (26.0,44.9) 50.5 (38.7,65.9)

18 to <21 yrs 6.3 (4.3,9.1) 15.2 (10.9,21.2) 30.1 (20.5,44.4) 43.8 (27.7,69.2) 54.9 (33.2,90.7) 78.5 (46.7,131.9)

Gender

Female 3.4 (2.6,4.3) 8.6 (7.1,10.3) 16.8 (14.1,19.9) 23.8 (19.9,28.6) 29.6 (24.6,35.6) 43.3 (35.9,52.2)

Male 4.2 (3.2,5.4) 10.3 (8.5,12.6) 20.3 (16.4,25.2) 29.9 (23.1,38.7) 38.1 (28.3,51.4) 59.2 (40.6,86.5)

Race/Ethnicity 1

Mexican American 3.3 (2.5,4.5) 8.2 (6.6,10.2) 15.6 (12.9,18.9) 22.3 (18.3,27.1) 28.2 (23.0,34.6) 44.0 (34.8,55.7)

Other Hispanic 3.2 (1.9,5.4) 8.4 (5.7,12.4) 16.8 (12.2,23.2) 24.3 (17.7,33.5) 30.1 (21.5,42.1) 43.9 (30.4,63.3)

Non

- Hispanic White 3.4 (2.5,4.5) 8.5 (6.6,10.9) 17.0 (12.8,22.4) 24.8 (18.1,34.0) 31.8 (22.5,45.0) 50.4 (32.5,78.1)

Non

- Hispanic Black 5.6 (4.2,7.3) 12.0 (9.5,15.1) 21.0 (16.7,26.4) 28.6 (22.7,36.0) 34.4 (27.3,43.5) 48.4 (38.2,61.2)

Other Race 6.8 (4.5,10.1) 17.1 (12.5,23.3) 31.4 (23.3,42.3) 42.7 (30.4,60.0) 51.6 (35.9,74.1) 69.4 (45.7,105.4)

Income, finer detail

$0 to <$20K 4.1 (3.0,5.6) 10.5 (8.2,13.4) 20.0 (15.8,25.3) 28.0 (22.0,35.8) 34.4 (26.7,44.4) 50.9 (39.0,66.4)

$20 to <$45K 3.6 (2.7,4.7) 8.8 (7.0,11.1) 17.1 (13.9,21.1) 24.7 (19.7,30.9) 31.4 (24.3,40.6) 48.5 (30.2,77.9)

$40 to <$75K 4.1 (3.0,5.7) 10.7 (7.8,14.8) 21.9 (15.2,31.5) 32.6 (21.8,48.7) 41.8 (27.1,64.5) 64.9 (40.2,104.7)

$75+K 3.7 (2.7,5.0) 8.9 (7.1,11.3) 16.8 (13.3,21.3) 23.7 (18.2,31.0) 29.5 (22.1,39.4) 43.7 (30.7,62.3)

>$20K 2.6 (1.3,5.3) 6.2 (3.2,12.1) 12.7 (5.8,27.8) 18.2 (7.7,43.1) 22.5 (9.3,54.5) 32.7 (13.1,81.4)

Refused/Don ’ t Know Income 2.9 (0.6,14.2) 8.0 (1.4,46.8) 23.1 (3.8,141.6) 38.0 (8.8,163.8) 50.5 (15.4,165.8) 73.3 (32.4,165.7)

Income Missing 4.9 (1.7,13.5) 13.2 (6.4,27.2) 26.4 (14.9,46.8) 37.3 (22.9,60.7) 45.2 (28.3,72.2) 65.3 (40.5,105.4)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other H ispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).77

## Table 22b. UFCR estimates (g/day raw weight, edible portion): Total finfish, youth

, <21 years, by geographic area

All Finfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 3.8 (3.0,4.8) 9.4 (7.9,11.3) 18.5 (15.4,22.2) 26.8 (21.8,32.9) 33.8 (26.9,42.5) 51.7 (39.1,68.4)

Region 1

Northeast 4.1 (2.7,6.3) 10.0 (7.1,13.9) 20.2 (13.2,31.1) 31.4 (16.9,58.4) 42.0 (19.8,88.7) 70.1 (31.2,157.3)

Midwest 2.6 (1.9,3.8) 7.0 (5.4,8.9) 13.8 (11.3,16.8) 20.1 (16.6,24.3) 25.1 (20.6,30.6) 38.2 (30.9,47.3)

South 4.2 (3.2,5.5) 10.0 (7.9,12.7) 18.5 (14.7,23.4) 25.7 (20.2,32.7) 31.4 (24.6,40.2) 45.1 (34.8,58.4)

West 4.5 (2.9,7.1) 11.5 (7.6,17.5) 22.8 (14.7,35.5) 32.6 (20.7,51.6) 40.8 (25.6,65.1) 58.6 (37.2,92.5)

Coastal Status 2

Noncoastal 3.5 (2.7,4.7) 9.0 (7.1,11.4) 17.7 (13.6,23.0) 25.7 (18.8,35.0) 32.5 (22.9,46.2) 50.9 (33.0,78.5)

Coastal 4.2 (3.3,5.4) 10.3 (8.5,12.4) 20.0 (16.7,23.9) 28.7 (23.9,34.5) 35.9 (29.8,43.2) 52.8 (43.1,64.6)

Coastal/Inland Region 1,2

Pacific 4.2 (2.9,6.0) 11.1 (7.9,15.6) 22.5 (16.1,31.4) 32.6 (23.4,45.5) 40.8 (29.2,57.1) 57.9 (41.0,81.6)

Atlantic 4.9 (3.6,6.9) 11.1 (8.5,14.4) 20.8 (16.4,26.4) 29.4 (23.0,37.6) 36.6 (28.2,47.4) 55.5 (41.2,74.7)

Gulf of Mexico 4.8 (3.2,7.0) 11.3 (8.0,15.8) 21.2 (15.2,29.8) 29.8 (21.4,41.4) 36.7 (26.4,50.9) 50.3 (35.7,70.9)

Great Lakes 3.0 (2.0,4.3) 7.7 (5.6,10.5) 15.1 (11.0,20.8) 21.8 (15.3,31.0) 27.4 (18.9,39.8) 41.5 (28.0,61.6)

Inland Northeast 3.9 (2.4,6.1) 9.5 (6.6,13.7) 19.6 (11.0,34.8) 31.3 (12.9,76.0) 43.1 (15.3,121.4) 73.0 (24.9,213.8)

Inland Midwest 2.5 (1.8,3.7) 6.7 (5.2,8.7) 13.3 (10.9,16.1) 19.2 (16.1,22.8) 24.2 (20.5,28.5) 36.3 (30.9,42.8)

Inland South 3.8 (2.9,4.9) 9.3 (7.3,11.9) 17.3 (13.5,22.3) 23.9 (18.3,31.2) 29.3 (22.2,38.6) 41.9 (31.8,55.3)

Inland West 4.8 (2.6,8.7) 11.8 (6.8,20.6) 23.0 (12.5,42.6) 32.6 (17.0,62.7) 40.9 (20.8,80.4) 59.1 (30.5,114.6)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.78

## Table 23a. UF CR estimates (g/day raw weight, edible portion): Total shellfish, youth

, <21 years, by demographic characteristics

All Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.6 (0.4,0.9) 1.9 (1.5,2.5) 4.8 (3.9,6.1) 8.1 (6.4,10.2) 11.0 (8.4,14.4) 19.2 (13.9,26.7)

Age

1 to <3 yrs 0.3 (0.2,0.6) 0.9 (0.5,1.8) 2.1 (1.1,4.0) 3.2 (1.6,6.5) 4.4 (2.1,9.0) 7.3 (3.2,16.5)

3 to <6 yrs 0.5 (0.3,1.0) 1.6 (0.9,2.7) 3.5 (2.2,5.6) 5.5 (3.5,8.6) 7.2 (4.6,11.4) 12.0 (7.2,20.0)

6 to <11 yrs 0.5 (0.3,0.9) 1.5 (0.9,2.2) 3.4 (2.4,4.8) 5.5 (3.9,7.9) 7.5 (5.0,11.1) 13.0 (7.4,22.8)

11 to <16 yrs 0.7 (0.4,1.2) 2.2 (1.5,3.4) 5.5 (3.7,8.2) 9.0 (6.1,13.3) 12.0 (8.1,17.8) 19.8 (13.3,29.7)

16 to <18 yrs 0.9 (0.5,1.7) 2.8 (1.7,4.6) 6.8 (4.5,10.2) 10.9 (7.5,15.9) 14.6 (10.1,21.2) 23.2 (15.5,34.6)

18 to <21 yrs 1.1 (0.5,2.4) 3.5 (2.0,6.3) 8.5 (5.3,13.6) 13.6 (8.4,22.0) 18.1 (10.9,30.0) 28.7 (16.3,50.8)

Gender

Female 0.6 (0.4,0.9) 1.9 (1.4,2.5) 4.8 (3.7,6.1) 8.0 (6.2,10.3) 10.9 (8.3,14.5) 19.2 (13.7,26.9)

Male 0.6 (0.4,0.9) 2.0 (1.5,2.6) 4.9 (3.8,6.4) 8.1 (6.1,10.7) 11.1 (8.1,15.1) 19.3 (13.2,28.4)

Race/Ethnicity 1

Mexican American 0.7 (0.4,1.0) 2.0 (1.4,2.7) 4.8 (3.5,6.4) 7.9 (5.7,10.9) 10.9 (7.6,15.6) 19.8 (12.5,31.3)

Other Hispanic 0.5 (0.2,1.5) 1.8 (0.7,4.2) 4.8 (2.2,10.5) 8.3 (3.8,17.8) 11.5 (5.4,24.5) 19.4 (9.3,40.6)

Non

- Hispanic White 0.5 (0.3,0.7) 1.4 (1.0,2.1) 3.4 (2.4,5.0) 5.7 (3.9,8.4) 7.8 (5.2,11.7) 14.0 (8.9,22.1)

Non

- Hispanic Black 1.2 (0.8,1.8) 3.4 (2.4,4.8) 7.7 (5.6,10.7) 12.0 (8.7,16.7) 15.8 (11.3,22.1) 25.0 (17.5,35.8)

Other Race 1.8 (1.0,3.3) 5.0 (3.0,8.3) 10.5 (6.3,17.6) 15.7 (9.1,27.2) 19.8 (10.8,36.4) 29.9 (15.1,59.5)

Income, finer detail

$0 to <$20K 0.5 (0.3,0.8) 1.6 (1.1,2.4) 4.0 (2.8,5.6) 6.6 (4.7,9.2) 8.9 (6.3,12.6) 15.1 (10.4,21.9)

$20 to <$45K 0.8 (0.5,1.1) 2.2 (1.6,3.1) 5.3 (4.0,7.0) 8.5 (6.4,11.4) 11.5 (8.6,15.5) 19.4 (13.9,27.2)

$40 to <$75K 0.5 (0.3,0.8) 1.5 (1.0,2.3) 3.9 (2.7,5.7) 6.7 (4.5,9.8) 9.2 (6.1,13.8) 15.9 (10.0,25.4)

$75+K 0.8 (0.5,1.2) 2.3 (1.5,3.3) 5.6 (4.0,7.9) 9.2 (6.5,13.2) 12.4 (8.5,18.0) 21.1 (13.6,32.6)

>$20K 0.3 (0.1,1.6) 0.9 (0.3,3.1) 2.2 (0.8,6.1) 3.7 (1.4,10.2) 5.2 (1.9,14.1) 9.2 (3.2,26.8)

Refused/Don ’ t Know Income 0.2 (0.0,1.5) 1.3 (0.3,5.8) 4.5 (1.2,16.7) 8.3 (2.4,28.7) 11.6 (3.3,40.4) 22.9 (5.9,89.1)

Income Missing 0.6 (0.1,2.2) 3.4 (0.6,18.7) 15.0 (1.8,126.0) 27.9 (4.8,163.5) 37.4 (9.6,146.3) 42.2 (23.6,75.5)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).79

## Table 23b. UFCR estimates (g/day raw weight, edible portion) : Total shellfish, youth

, <21 years, by geographic area

All Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.6 (0.4,0.9) 1.9 (1.5,2.5) 4.8 (3.9,6.1) 8.1 (6.4,10.2) 11.0 (8.4,14.4) 19.2 (13.9,26.7)

Region 1

Northeast 0.7 (0.4,1.5) 2.3 (1.3,4.2) 5.6 (3.1,10.1) 9.1 (5.1,16.3) 12.3 (7.0,21.7) 20.6 (11.9,35.6)

Midwest 0.4 (0.2,0.7) 1.2 (0.7,2.0) 3.1 (1.9,5.0) 5.3 (3.3,8.5) 7.4 (4.5,12.0) 13.5 (8.0,22.9)

South 0.8 (0.5,1.2) 2.2 (1.5,3.3) 5.4 (3.7,7.7) 8.7 (6.1,12.6) 11.8 (8.1,17.3) 20.6 (13.3,32.0)

West 0.7 (0.4,1.1) 2.2 (1.5,3.2) 5.6 (3.9,8.0) 9.3 (6.2,13.9) 12.6 (7.9,20.0) 21.2 (11.4,39.3)

Coastal Status 2

Noncoastal 0.5 (0.3,0.7) 1.5 (1.1,2.1) 3.7 (2.8,4.9) 6.1 (4.6,8.1) 8.1 (6.0,11.0) 13.9 (9.8,19.8)

Coastal 0.9 (0.6,1.3) 2.8 (2.1,3.8) 7.1 (5.4,9.4) 11.7 (8.6,15.9) 15.8 (11.3,22.0) 26.4 (17.4,39.9)

Coastal/Inland Region 1,2

Pacific 0.9 (0.6,1.4) 2.9 (2.0,4.3) 7.5 (5.0,11.3) 12.4 (7.4,20.7) 16.9 (9.2,30.9) 27.8 (13.6,56.7)

Atlantic 1.2 (0.7,1.8) 3.5 (2.4,5.0) 8.2 (5.8,11.7) 12.8 (9.0,18.3) 16.7 (11.8,23.8) 26.1 (18.0,37.9)

Gulf of Mexico 1.1 (0.5,2.3) 3.3 (1.6,6.6) 8.1 (4.1,16.1) 13.9 (6.7,29.1) 20.2 (8.9,45.9) 37.4 (19.2,73.1)

Great Lakes 0.6 (0.3,1.0) 1.8 (1.1,2.8) 4.5 (2.8,7.2) 7.5 (4.4,12.8) 10.2 (5.7,18.4) 17.7 (8.9,35.0)

Inland Northeast 0.6 (0.3,1.3) 2.0 (1.0,3.8) 4.6 (2.5,8.3) 7.2 (4.1,12.6) 9.4 (5.4,16.4) 15.6 (9.1,26.7)

Inland Midwest 0.3 (0.2,0.6) 1.0 (0.6,1.8) 2.5 (1.5,4.4) 4.3 (2.4,7.5) 6.0 (3.4,10.7) 10.9 (5.8,20.3)

Inland South 0.6 (0.4,0.9) 1.7 (1.2,2.4) 3.9 (2.9,5.2) 6.2 (4.7,8.2) 8.3 (6.2,11.0) 13.7 (9.9,19.0)

Inland West 0.6 (0.3,1.0) 1.8 (1.1,2.9) 4.3 (2.6,7.0) 7.0 (4.2,11.5) 9.4 (5.5,15.8) 15.5 (8.6,28.0)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coas tal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.80

## Table 24a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, youth

, <21 years, by demographic

characteristics

Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.4 (0.3,0.6) 1.2 (0.9,1.6) 3.1 (2.4,4.0) 5.2 (4.0,6.7) 7.1 (5.3,9.3) 12.0 (8.6,16.6)

Age

1 to <3 yrs 0.2 (0.1,0.4) 0.6 (0.4,1.0) 1.5 (1.0,2.2) 2.4 (1.7,3.5) 3.3 (2.2,4.9) 5.8 (3.7,9.2)

3 to <6 yrs 0.3 (0.2,0.6) 0.9 (0.6,1.5) 2.3 (1.5,3.5) 3.8 (2.6,5.6) 5.2 (3.6,7.6) 8.8 (6.0,12.9)

6 to <11 yrs 0.3 (0.1,0.5) 0.8 (0.5,1.3) 2.2 (1.5,3.3) 3.9 (2.6,6.1) 5.6 (3.5,9.0) 10.5 (6.1,18.1)

11 to <16 yrs 0.5 (0.3,1.0) 1.7 (1.0,2.7) 4.0 (2.5,6.3) 6.4 (4.1,10.1) 8.6 (5.4,13.5) 14.0 (8.8,22.3)

16 to <18 yrs 0.5 (0.2,1.0) 1.5 (0.9,2.5) 3.6 (2.3,5.5) 5.6 (3.7,8.4) 7.3 (4.8,11.0) 11.6 (7.4,18.4)

18 to <21 yrs 0.6 (0.3,1.1) 1.8 (1.1,3.1) 4.4 (2.7,7.1) 7.1 (4.3,11.6) 9.3 (5.5,15.7) 14.9 (8.7,25.7)

Gender

Female 0.4 (0.2,0.6) 1.2 (0.9,1.6) 3.0 (2.3,4.0) 5.1 (3.9,6.7) 7.0 (5.3,9.2) 11.8 (8.5,16.4)

Male 0.4 (0.3,0.6) 1.2 (0.9,1.7) 3.2 (2.3,4.3) 5.2 (3.8,7.2) 7.1 (5.1,9.9) 12.1 (8.3,17.7)

Race/Ethnicity 1

Mexican American 0.6 (0.4,0.9) 1.7 (1.2,2.4) 4.1 (3.0,5.4) 6.4 (4.8,8.6) 8.4 (6.2,11.5) 13.8 (9.5,20.0)

Other Hispanic 0.4 (0.1,0.9) 1.2 (0.5,2.6) 2.8 (1.4,5.8) 4.6 (2.2,9.3) 6.0 (2.9,12.3) 10.1 (4.9,20.6)

Non

- Hispanic White 0.3 (0.2,0.4) 0.8 (0.5,1.3) 2.2 (1.4,3.3) 3.7 (2.4,5.7) 5.1 (3.3,8.1) 9.2 (5.7,14.8)

Non

- Hispanic Black 0.6 (0.4,0.9) 1.8 (1.3,2.3) 4.1 (3.0,5.4) 6.5 (4.8,8.8) 8.6 (6.2,11.9) 14.0 (9.8,20.0)

Other Race 1.1 (0.5,2.4) 3.2 (1.7,6.3) 6.9 (3.6,12.9) 10.1 (5.3,19.2) 12.6 (6.7,23.9) 18.5 (9.7,35.0)

Income

$0 to <$20K 0.3 (0.2,0.6) 1.1 (0.7,1.6) 2.7 (1.9,3.8) 4.4 (3.2,6.2) 6.0 (4.3,8.3) 9.8 (6.9,14.0)

$20 to <$45K 0.5 (0.3,0.7) 1.5 (1.1,2.0) 3.5 (2.7,4.7) 5.7 (4.3,7.6) 7.7 (5.7,10.4) 13.0 (9.4,17.9)

$40 to <$75K 0.3 (0.2,0.5) 0.9 (0.6,1.5) 2.5 (1.6,3.8) 4.2 (2.7,6.5) 5.8 (3.7,9.2) 10.0 (6.0,16.6)

$75+K 0.4 (0.3,0.7) 1.3 (0.9,2.1) 3.4 (2.2,5.2) 5.7 (3.7,8.7) 7.7 (5.0,11.9) 12.9 (8.2,20.3)

>$20K 0.2 (0.1,0.8) 0.6 (0.2,1.9) 1.5 (0.6,4.1) 2.6 (1.0,6.7) 3.6 (1.4,9.2) 6.3 (2.4,16.6)

Refused/Don ’ t Know Income 0.1 (0.0,0.8) 0.6 (0.1,3.3) 2.6 (0.7,10.2) 4.5 (1.3,15.5) 6.3 (1.8,21.8) 11.7 (3.2,42.1)

Income Missing 0.3 (0.1,1.4) 1.6 (0.3,7.8) 7.2 (1.1,45.2) 12.3 (3.1,47.7) 15.4 (5.3,44.6) 20.0 (10.2,39.3)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).81

## Table 24b. UFCR estimates (g/day raw weight, edible portion): Total trophic level 2 fish, youth

, <21 years, by geographic area

Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.4 (0.3,0.6) 1.2 (0.9,1.6) 3.1 (2.4,4.0) 5.2 (4.0,6.7) 7.1 (5.3,9.3) 12.0 (8.6,16.6)

Region 1

Northeast 0.4 (0.2,0.8) 1.3 (0.8,2.3) 3.3 (1.8,6.3) 5.5 (2.8,10.8) 7.5 (3.7,15.0) 12.9 (6.5,25.7)

Midwest 0.2 (0.1,0.4) 0.8 (0.5,1.4) 2.1 (1.2,3.6) 3.7 (2.2,6.1) 5.1 (3.1,8.3) 8.9 (5.5,14.5)

South 0.4 (0.3,0.7) 1.3 (0.9,2.0) 3.2 (2.3,4.6) 5.3 (3.7,7.6) 7.2 (5.1,10.3) 12.2 (8.6,17.3)

West 0.5 (0.3,0.8) 1.5 (1.0,2.4) 3.9 (2.5,6.1) 6.3 (3.9,10.3) 8.4 (5.0,14.0) 13.4 (7.6,23.7)

Coastal Status 2

Noncoastal 0.3 (0.2,0.5) 1.0 (0.7,1.4) 2.4 (1.8,3.2) 3.9 (2.9,5.3) 5.3 (3.9,7.2) 9.1 (6.4,12.9)

Coastal 0.6 (0.4,0.8) 1.8 (1.3,2.5) 4.5 (3.4,6.1) 7.3 (5.4,9.9) 9.7 (7.0,13.4) 15.5 (10.9,22.0)

Coastal/Inland Region 1,2

Pacific 0.6 (0.4,1.1) 2.1 (1.3,3.3) 5.0 (3.0,8.5) 7.9 (4.5,13.9) 10.2 (5.7,18.5) 16.1 (8.9,29.2)

Atlantic 0.6 (0.4,0.9) 1.9 (1.4,2.8) 4.8 (3.2,7.1) 7.6 (4.9,11.7) 10.1 (6.4,15.8) 16.2 (10.0,26.3)

Gulf of Mexico 0.7 (0.4,1.2) 2.1 (1.2,3.8) 5.3 (3.0,9.3) 8.7 (5.2,14.6) 11.5 (7.2,18.4) 17.3 (12.0,25.1)

Great Lakes 0.3 (0.2,0.6) 1.1 (0.7,2.0) 3.1 (1.9,5.1) 5.1 (3.2,8.2) 6.9 (4.3,11.0) 11.6 (7.2,18.6)

Inland Northeast 0.4 (0.2,0.7) 1.1 (0.6,2.0) 2.7 (1.5,4.8) 4.1 (2.3,7.6) 5.6 (3.1,10.1) 9.3 (5.1,17.1)

Inland Midwest 0.2 (0.1,0.4) 0.7 (0.4,1.1) 1.7 (1.0,2.9) 3.0 (1.7,5.0) 4.2 (2.4,7.1) 7.4 (4.1,13.3)

Inland South 0.4 (0.2,0.6) 1.0 (0.7,1.6) 2.4 (1.7,3.4) 3.8 (2.7,5.4) 5.1 (3.6,7.2) 8.5 (6.0,12.1)

Inland West 0.4 (0.2,0.7) 1.2 (0.7,2.0) 3.0 (1.8,5.0) 5.0 (3.0,8.3) 6.7 (4.0,11.3) 11.1 (6.3,19.5)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.82

## Table 25a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 3 fish, adults, youth

, <21 years, by demographic

characteristics

Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 1.4 (1.0,1.8) 3.5 (2.8,4.5) 7.4 (6.0,9.2) 11.1 (8.9,13.8) 14.1 (11.2,17.7) 21.5 (16.5,27.9)

Age

1 to <3 yrs 0.8 (0.5,1.3) 2.1 (1.4,3.2) 4.2 (2.7,6.3) 6.0 (4.0,9.0) 7.5 (5.0,11.4) 11.4 (7.4,17.8)

3 to <6 yrs 1.1 (0.8,1.7) 2.9 (2.1,4.0) 5.9 (4.5,7.6) 8.5 (6.6,10.9) 10.7 (8.3,13.8) 15.7 (11.8,20.8)

6 to <11 yrs 1.6 (1.1,2.4) 4.2 (2.7,6.3) 8.8 (5.7,13.7) 13.1 (8.2,20.9) 16.6 (10.2,27.1) 25.4 (15.0,42.9)

11 to <16 yrs 1.3 (0.9,2.0) 3.3 (2.3,4.7) 6.8 (5.1,9.1) 10.0 (7.5,13.2) 12.7 (9.6,16.8) 19.4 (14.8,25.5)

16 to <18 yrs 1.2 (0.7,2.1) 3.1 (2.1,4.8) 7.2 (5.3,9.8) 11.6 (8.5,15.6) 15.1 (11.0,20.7) 23.6 (16.6,33.5)

18 to <21 yrs 2.2 (1.4,3.3) 5.3 (3.8,7.5) 10.0 (7.4,13.5) 14.0 (10.2,19.1) 17.0 (12.1,23.8) 23.9 (16.1,35.7)

Gender

Female 1.2 (0.9,1.6) 3.2 (2.5,4.0) 6.8 (5.5,8.5) 10.2 (8.2,12.8) 13.1 (10.4,16.5) 20.3 (15.6,26.5)

Male 1.5 (1.1,2.1) 3.9 (3.0,5.1) 8.0 (6.2,10.3) 11.8 (9.1,15.3) 14.9 (11.4,19.5) 22.4 (16.6,30.1)

Race/Ethnicity 1

Mexican American 1.1 (0.8,1.5) 2.7 (2.1,3.5) 5.5 (4.4,6.9) 8.2 (6.4,10.4) 10.4 (8.0,13.5) 16.0 (11.5,22.2)

Other Hispanic 0.9 (0.6,1.5) 2.5 (1.6,4.0) 5.2 (3.2,8.5) 7.6 (4.4,13.2) 9.7 (5.5,17.0) 14.7 (8.0,26.9)

Non

- Hispanic White 1.1 (0.8,1.6) 2.8 (2.1,3.8) 5.6 (4.1,7.6) 8.1 (5.9,11.2) 10.3 (7.3,14.4) 15.8 (10.7,23.1)

Non

- Hispanic Black 3.1 (2.3,4.2) 7.0 (5.4,9.2) 12.6 (9.9,16.2) 17.1 (13.4,21.9) 20.7 (16.2,26.4) 28.6 (22.2,36.9)

Other Race 3.6 (2.4,5.6) 8.3 (5.7,12.0) 15.2 (10.1,22.9) 20.3 (12.9,32.0) 24.1 (14.9,38.9) 32.1 (19.5,52.9)

Income

$0 to <$20K 1.6 (1.2,2.1) 4.3 (3.2,5.7) 8.9 (6.9,11.5) 12.8 (9.9,16.7) 16.1 (12.3,21.0) 23.6 (17.8,31.3)

$20 to <$45K 1.4 (1.0,1.8) 3.5 (2.8,4.3) 7.1 (5.7,8.8) 10.5 (8.4,13.1) 13.4 (10.7,16.8) 20.3 (16.1,25.5)

$40 to <$75K 1.3 (0.9,2.0) 3.4 (2.3,5.1) 7.3 (4.7,11.3) 10.7 (6.8,16.9) 13.5 (8.5,21.4) 19.8 (12.4,31.6)

$75+K 1.3 (0.9,1.9) 3.3 (2.4,4.6) 6.9 (5.2,9.2) 10.3 (7.7,14.0) 13.3 (9.6,18.4) 20.5 (13.7,30.5)

>$20K 1.1 (0.4,2.6) 2.4 (1.2,4.9) 4.7 (2.7,8.2) 6.7 (3.9,11.4) 8.4 (4.9,14.4) 12.4 (6.9,22.3)

Refused/Don ’ t Know Income 1.8 (0.4,9.3) 4.3 (1.0,17.9) 8.4 (2.9,24.8) 12.4 (5.1,29.9) 15.4 (6.9,34.4) 24.4 (10.7,56.0)

Income Missing 1.3 (0.4,4.2) 5.3 (1.3,21.8) 16.1 (3.0,86.1) 29.6 (6.3,139.9) 38.2 (10.2,143.0) 51.8 (19.7,136.7)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- His panic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).83

## Table 25b. UFCR estimates (g/day raw weight, edible portion) : Total trophic level 3 fish, youth

, <21 years, by geographic area

Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 1.4 (1.0,1.8) 3.5 (2.8,4.5) 7.4 (6.0,9.2) 11.1 (8.9,13.8) 14.1 (11.2,17.7) 21.5 (16.5,27.9)

Region 1

Northeast 1.4 (0.8,2.3) 3.4 (2.2,5.2) 6.5 (4.2,10.1) 9.3 (5.8,14.7) 11.5 (7.2,18.3) 17.0 (10.6,27.1)

Midwest 0.9 (0.6,1.3) 2.4 (1.7,3.3) 5.2 (3.9,7.0) 8.0 (5.9,10.9) 10.4 (7.4,14.5) 16.6 (11.4,24.2)

South 1.9 (1.3,2.7) 4.7 (3.4,6.4) 9.3 (7.0,12.4) 13.5 (10.2,18.0) 16.9 (12.7,22.7) 25.4 (18.4,35.1)

West 1.4 (0.9,2.0) 3.6 (2.5,5.2) 7.8 (5.2,11.7) 11.7 (7.5,18.3) 14.9 (9.2,24.1) 22.3 (12.9,38.6)

Coastal Status 2

Noncoastal 1.2 (0.9,1.6) 3.1 (2.4,4.0) 6.4 (4.9,8.3) 9.6 (7.3,12.6) 12.2 (9.1,16.2) 18.6 (13.4,25.8)

Coastal 1.8 (1.3,2.4) 4.5 (3.4,5.9) 9.2 (7.1,12.0) 13.5 (10.3,17.7) 17.0 (12.8,22.6) 25.6 (18.5,35.3)

Coastal/Inland Region 1,2

Pacific 1.5 (1.0,2.2) 4.0 (2.8,5.6) 8.6 (6.0,12.4) 13.0 (8.7,19.5) 16.4 (10.5,25.5) 23.6 (14.5,38.6)

Atlantic 2.3 (1.5,3.4) 5.4 (3.8,7.7) 10.4 (7.7,14.1) 14.7 (10.9,19.7) 18.0 (13.4,24.1) 25.8 (19.3,34.4)

Gulf of Mexico 2.3 (1.2,4.3) 5.7 (3.3,9.7) 11.2 (6.8,18.4) 16.8 (9.5,30.0) 22.3 (11.4,43.4) 37.6 (17.5,80.9)

Great Lakes 1.2 (0.9,1.7) 3.2 (2.4,4.2) 6.7 (4.7,9.5) 9.9 (6.4,15.4) 12.8 (7.9,20.6) 19.4 (11.2,33.6)

Inland Northeast 1.2 (0.8,1.9) 2.9 (2.0,4.2) 5.5 (3.9,7.8) 7.7 (5.4,11.0) 9.6 (6.6,13.9) 14.0 (9.5,20.8)

Inland Midwest 0.8 (0.6,1.2) 2.1 (1.5,3.0) 4.5 (3.3,6.2) 6.9 (4.9,9.8) 9.1 (6.3,13.0) 14.8 (10.2,21.6)

Inland South 1.6 (1.2,2.2) 4.0 (3.1,5.2) 8.1 (6.3,10.3) 11.7 (9.1,15.0) 14.6 (11.3,18.8) 21.4 (16.6,27.7)

Inland West 1.3 (0.8,2.2) 3.4 (2.0,5.6) 7.2 (4.0,12.9) 10.7 (5.5,20.5) 13.6 (6.7,27.9) 21.1 (9.3,47.8)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

bor der a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.84

## Table 26a. UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, youth

, <21 years, by demographic

characteristics

Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 2.5 (1.9,3.1) 6.4 (5.3,7.7) 13.1 (10.8,15.9) 19.6 (15.8,24.4) 25.3 (19.9,32.3) 40.5 (28.8,56.9)

Age

1 to <3 yrs 1.3 (0.9,1.8) 3.3 (2.5,4.2) 6.6 (5.2,8.4) 9.7 (7.5,12.4) 12.5 (9.7,16.3) 19.3 (14.3,26.1)

3 to <6 yrs 1.8 (1.2,2.7) 4.4 (3.3,6.1) 8.6 (6.6,11.3) 12.4 (9.5,16.1) 15.5 (11.8,20.4) 23.2 (16.9,31.9)

6 to <11 yrs 2.7 (1.9,4.0) 6.9 (4.8,10.0) 13.4 (8.6,21.0) 19.2 (11.6,32.0) 23.8 (13.8,41.0) 34.1 (19.1,60.9)

11 to <16 yrs 2.4 (1.6,3.5) 5.9 (4.3,8.1) 11.3 (8.4,15.3) 16.2 (11.9,22.2) 20.2 (14.5,28.3) 30.4 (20.2,45.7)

16 to <18 yrs 3.2 (2.1,4.9) 7.8 (5.6,10.9) 15.2 (11.0,21.0) 21.4 (15.3,30.1) 26.6 (18.6,38.2) 39.3 (26.7,57.7)

18 to <21 yrs 4.4 (2.9,6.5) 11.6 (7.9,17.0) 24.8 (15.6,39.5) 37.3 (21.3,65.4) 48.4 (26.3,89.1) 72.4 (38.6,135.9)

Gender

Female 2.2 (1.7,2.8) 5.8 (4.8,7.0) 11.8 (9.7,14.2) 17.2 (14.2,20.9) 21.6 (17.7,26.5) 31.9 (25.6,39.8)

Male 2.7 (2.1,3.5) 7.0 (5.7,8.6) 14.5 (11.6,18.2) 22.1 (16.8,29.2) 29.3 (21.1,40.7) 49.5 (30.7,80.0)

Race/Ethnicity 1

Mexican American 2.0 (1.4,2.9) 5.2 (4.0,6.8) 10.7 (8.4,13.7) 16.0 (12.5,20.6) 20.8 (16.0,27.2) 34.0 (25.0,46.4)

Other Hispanic 2.2 (1.2,3.7) 6.1 (3.8,9.7) 12.6 (8.4,19.0) 18.4 (12.2,27.7) 23.1 (15.2,35.1) 33.4 (20.5,54.4)

Non

- Hispanic White 2.3 (1.7,3.2) 6.2 (4.7,8.0) 12.8 (9.6,17.1) 19.3 (13.8,26.9) 25.1 (17.2,36.5) 41.3 (24.2,70.5)

Non

- Hispanic Black 3.0 (2.3,4.1) 6.9 (5.4,8.8) 12.8 (10.2,16.0) 17.8 (14.2,22.3) 21.9 (17.4,27.4) 31.2 (24.7,39.5)

Other Race 4.2 (2.7,6.5) 11.1 (7.8,15.7) 22.5 (16.7,30.4) 31.7 (22.2,45.3) 39.4 (25.6,60.7) 57.3 (32.3,101.7)

Income

$0 to <$20K 2.5 (1.8,3.4) 6.5 (5.2,8.2) 13.2 (10.6,16.3) 19.3 (15.1,24.5) 24.3 (18.6,31.8) 38.1 (27.9,52.1)

$20 to <$45K 2.3 (1.7,3.0) 5.8 (4.6,7.3) 12.0 (9.7,14.9) 18.4 (14.5,23.3) 24.0 (17.8,32.3) 39.5 (22.0,70.9)

$40 to <$75K 2.8 (2.0,3.8) 7.4 (5.3,10.4) 15.7 (10.4,23.5) 24.2 (15.5,37.9) 31.9 (19.6,51.9) 52.8 (29.4,94.8)

$75+K 2.5 (1.8,3.5) 6.4 (5.0,8.2) 12.4 (9.7,15.9) 17.9 (13.7,23.3) 22.2 (16.7,29.5) 32.9 (23.9,45.3)

>$20K 1.8 (0.8,3.9) 4.4 (2.2,8.9) 9.6 (4.1,22.4) 14.8 (5.7,38.0) 18.6 (6.9,50.2) 26.1 (9.2,74.2)

Refused/Don ’ t Know Income 2.0 (0.4,9.8) 5.9 (1.0,35.5) 17.4 (2.7,114.0) 31.0 (6.4,150.2) 41.0 (11.2,150.2) 63.9 (25.5,159.9)

Income Missing 2.9 (0.9,9.7) 8.3 (3.3,21.0) 18.0 (9.2,34.9) 26.3 (15.2,45.4) 32.7 (19.5,54.8) 50.0 (29.5,84.7)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).85

## T able 26b. UFCR estimates (g/day raw weight, edible portion): Total trophic level 4 fish, youth

, <21 years, by geographic area

Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 2.5 (1.9,3.1) 6.4 (5.3,7.7) 13.1 (10.8,15.9) 19.6 (15.8,24.4) 25.3 (19.9,32.3) 40.5 (28.8,56.9)

Region 1

Northeast 3.0 (2.0,4.4) 7.6 (5.4,10.5) 16.4 (10.3,26.2) 26.7 (13.0,54.9) 37.0 (15.6,88.0) 63.5 (25.0,161.7)

Midwest 1.8 (1.2,2.7) 4.8 (3.5,6.4) 9.7 (7.7,12.1) 14.2 (11.6,17.4) 18.1 (14.8,22.1) 27.8 (22.3,34.6)

South 2.5 (1.9,3.4) 6.2 (4.9,8.0) 12.1 (9.5,15.5) 17.5 (13.5,22.7) 21.8 (16.6,28.6) 32.9 (24.4,44.4)

West 3.1 (1.9,5.0) 8.2 (5.0,13.2) 16.6 (10.2,27.1) 24.1 (14.9,39.2) 30.3 (19.0,48.3) 44.1 (28.5,68.1)

Coastal Status 2

Noncoastal 2.4 (1.8,3.2) 6.4 (5.0,8.2) 13.2 (10.0,17.5) 19.7 (14.2,27.3) 25.3 (17.6,36.4) 40.6 (24.9,66.2)

Coastal 2.5 (1.9,3.3) 6.4 (5.2,7.7) 13.0 (10.9,15.5) 19.5 (16.3,23.4) 25.4 (20.9,30.8) 40.3 (31.3,52.0)

Coastal/Inland Region 1,2

Pacific 2.6 (1.7,3.9) 7.2 (5.0,10.2) 15.4 (11.0,21.6) 23.0 (16.4,32.4) 29.5 (20.8,41.9) 44.5 (29.1,68.1)

Atlantic 3.0 (2.2,4.2) 6.9 (5.3,9.0) 13.6 (10.6,17.4) 20.2 (15.2,27.0) 26.6 (19.0,37.2) 45.4 (28.2,73.2)

Gulf of Mexico 2.6 (1.7,4.0) 6.4 (4.5,9.3) 12.9 (8.8,18.9) 19.1 (13.0,28.2) 24.0 (15.9,36.1) 36.6 (22.3,60.1)

Great Lakes 1.8 (1.1,2.8) 4.7 (3.4,6.6) 9.6 (7.0,13.2) 14.2 (10.1,19.9) 18.1 (12.6,26.1) 28.1 (18.2,43.2)

Inland Northeast 2.9 (1.9,4.4) 7.7 (5.3,11.2) 17.1 (9.3,31.5) 28.1 (10.8,73.4) 39.8 (13.2,119.5) 67.2 (21.6,209.3)

Inland Midwest 1.8 (1.2,2.7) 4.8 (3.5,6.5) 9.7 (7.8,12.2) 14.3 (11.8,17.3) 18.1 (15.1,21.7) 27.5 (22.9,33.1)

Inland South 2.4 (1.8,3.1) 6.1 (4.7,7.9) 11.8 (9.0,15.6) 17.0 (12.6,22.9) 21.2 (15.5,29.0) 31.2 (22.5,43.2)

Inland West 3.4 (1.8,6.6) 8.9 (4.7,16.6) 17.4 (9.1,33.5) 24.8 (12.8,48.2) 30.7 (15.9,59.1) 43.8 (23.9,80.4)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remai ning c ounties in each of the 4 Census Regions.86

## Table 27a. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, youth

, <21 years, by demographic characteristics

Freshwater + Estuarine Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.3 (0.2,0.4) 0.9 (0.7,1.2) 2.3 (1.8,3.0) 4.0 (3.1,5.2) 5.5 (4.2,7.3) 9.8 (7.1,13.4)

Age

1 to <3 yrs 0.1 (0.1,0.3) 0.5 (0.3,0.8) 1.2 (0.8,1.8) 2.1 (1.4,3.0) 2.9 (2.0,4.3) 5.2 (3.3,8.1)

3 to <6 yrs 0.2 (0.1,0.4) 0.6 (0.4,1.0) 1.7 (1.1,2.7) 3.0 (2.0,4.6) 4.2 (2.8,6.4) 7.5 (5.0,11.2)

6 to <11 yrs 0.2 (0.1,0.4) 0.7 (0.4,1.1) 1.9 (1.3,2.8) 3.5 (2.2,5.5) 5.0 (3.1,8.3) 9.3 (5.3,16.5)

11 to <16 yrs 0.3 (0.2,0.6) 1.1 (0.7,1.7) 2.9 (2.0,4.1) 4.7 (3.4,6.6) 6.4 (4.6,8.9) 11.0 (7.8,15.5)

16 to <18 yrs 0.3 (0.2,0.7) 1.0 (0.6,1.8) 2.5 (1.5,3.9) 3.9 (2.6,6.1) 5.2 (3.4,8.1) 8.7 (5.5,13.8)

18 to <21 yrs 0.4 (0.2,0.8) 1.4 (0.8,2.4) 3.4 (2.2,5.5) 5.6 (3.5,8.9) 7.4 (4.5,12.1) 12.3 (7.4,20.6)

Gender

Female 0.3 (0.2,0.4) 0.9 (0.6,1.2) 2.4 (1.8,3.1) 4.1 (3.2,5.3) 5.6 (4.3,7.4) 9.9 (7.2,13.5)

Male 0.3 (0.2,0.4) 0.9 (0.6,1.2) 2.3 (1.7,3.1) 3.9 (2.9,5.4) 5.4 (3.9,7.6) 9.6 (6.6,14.0)

Race/Ethnicity 1

Mexican American 0.5 (0.3,0.7) 1.5 (1.0,2.1) 3.5 (2.6,4.8) 5.6 (4.1,7.7) 7.5 (5.4,10.4) 12.4 (8.4,18.2)

Other Hispanic 0.3 (0.1,0.8) 1.0 (0.4,2.2) 2.5 (1.2,5.2) 4.1 (2.0,8.4) 5.5 (2.7,11.3) 9.0 (4.3,19.0)

Non

- Hispanic White 0.2 (0.1,0.3) 0.5 (0.4,0.8) 1.4 (0.9,2.0) 2.4 (1.6,3.5) 3.3 (2.2,5.0) 6.2 (4.0,9.4)

Non

- Hispanic Black 0.5 (0.4,0.7) 1.5 (1.2,2.0) 3.5 (2.7,4.5) 5.6 (4.2,7.4) 7.4 (5.5,10.0) 12.3 (8.8,17.3)

Other Race 0.8 (0.4,1.8) 2.5 (1.2,5.1) 5.5 (2.8,11.0) 8.3 (4.2,16.4) 10.7 (5.4,21.2) 15.5 (7.6,31.8)

Income

$0 to <$20K 0.3 (0.2,0.4) 0.9 (0.6,1.3) 2.3 (1.6,3.3) 3.8 (2.7,5.4) 5.1 (3.6,7.3) 8.5 (5.7,12.7)

$20 to <$45K 0.4 (0.2,0.5) 1.1 (0.8,1.5) 2.9 (2.1,3.8) 4.8 (3.5,6.5) 6.5 (4.7,8.9) 11.1 (7.8,15.8)

$40 to <$75K 0.2 (0.1,0.3) 0.7 (0.4,1.0) 1.8 (1.2,2.7) 3.2 (2.1,4.8) 4.4 (2.9,6.8) 7.9 (4.9,12.6)

$75+K 0.3 (0.2,0.4) 0.9 (0.6,1.3) 2.3 (1.6,3.4) 4.0 (2.8,5.9) 5.5 (3.7,8.2) 9.8 (6.4,15.1)

>$20K 0.1 (0.0,0.5) 0.4 (0.2,1.2) 1.2 (0.5,3.0) 2.1 (0.8,5.4) 2.9 (1.1,7.5) 5.4 (2.0,14.3)

Refused/Don ’ t Know Income 0.1 (0.0,0.5) 0.4 (0.1,2.2) 1.8 (0.5,7.0) 3.2 (0.9,11.6) 4.6 (1.2,16.9) 9.0 (2.2,37.0)

Income Missing 0.2 (0.1,0.8) 1.2 (0.2,6.0) 5.7 (0.8,41.5) 10.1 (2.4,43.2) 13.0 (4.3,39.9) 18.2 (8.6,38.2)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).87

## Table 27b. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 2 fish, youth

, <21 years, by geographic area

Freshwater + Estuarine Trophic Level 2

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.3 (0.2,0.4) 0.9 (0.7,1.2) 2.3 (1.8,3.0) 4.0 (3.1,5.2) 5.5 (4.2,7.3) 9.8 (7.1,13.4)

Region 1

Northeast 0.3 (0.1,0.5) 0.8 (0.5,1.5) 2.1 (1.1,3.7) 3.4 (1.9,6.2) 4.7 (2.6,8.4) 8.0 (4.5,14.3)

Midwest 0.1 (0.1,0.2) 0.5 (0.3,0.8) 1.4 (0.9,2.3) 2.7 (1.7,4.2) 3.8 (2.4,6.1) 7.1 (4.2,11.7)

South 0.4 (0.2,0.6) 1.1 (0.7,1.7) 2.8 (2.0,4.1) 4.7 (3.3,6.7) 6.4 (4.5,9.2) 11.0 (7.6,16.0)

West 0.3 (0.2,0.6) 1.1 (0.7,1.7) 2.9 (1.8,4.6) 4.9 (3.0,8.1) 6.6 (3.9,11.3) 11.2 (6.3,20.0)

Coastal Status 2

Noncoastal 0.2 (0.1,0.3) 0.7 (0.5,1.0) 1.8 (1.3,2.5) 3.1 (2.3,4.2) 4.3 (3.2,5.9) 7.7 (5.5,10.9)

Coastal 0.4 (0.3,0.6) 1.3 (0.9,1.8) 3.4 (2.5,4.5) 5.5 (4.1,7.5) 7.4 (5.3,10.3) 12.4 (8.6,17.7)

Coastal/Inland Region 1,2

Pacific 0.4 (0.3,0.7) 1.5 (0.9,2.4) 3.8 (2.3,6.4) 6.1 (3.4,10.9) 8.1 (4.4,15.0) 13.5 (7.3,25.0)

Atlantic 0.4 (0.3,0.7) 1.4 (1.0,2.0) 3.5 (2.5,4.8) 5.5 (4.0,7.7) 7.3 (5.1,10.3) 11.7 (7.7,17.8)

Gulf of Mexico 0.5 (0.3,1.0) 1.7 (0.9,3.0) 4.3 (2.4,7.6) 7.1 (4.1,12.3) 9.6 (5.7,16.2) 15.2 (9.9,23.3)

Great Lakes 0.2 (0.1,0.4) 0.7 (0.5,1.2) 2.1 (1.3,3.4) 3.6 (2.2,6.2) 5.1 (3.0,8.8) 9.0 (5.1,15.8)

Inland Northeast 0.2 (0.1,0.4) 0.7 (0.4,1.3) 1.7 (0.9,3.2) 2.7 (1.4,5.3) 3.7 (1.9,7.2) 6.5 (3.3,12.9)

Inland Midwest 0.1 (0.1,0.2) 0.4 (0.3,0.7) 1.2 (0.7,1.9) 2.1 (1.3,3.7) 3.1 (1.8,5.4) 5.9 (3.2,10.7)

Inland South 0.3 (0.2,0.5) 0.9 (0.6,1.4) 2.2 (1.5,3.1) 3.6 (2.5,5.1) 4.9 (3.5,6.9) 8.6 (6.0,12.1)

Inland West 0.3 (0.2,0.5) 0.9 (0.5,1.5) 2.3 (1.4,3.8) 3.9 (2.3,6.6) 5.4 (3.2,9.1) 9.2 (5.2,16.3)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.88

## Table 28a. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic le vel 3 fish, youth

, <21 years, by demographic characteristics

Freshwater + Estuarine Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.4 (0.3,0.6) 1.3 (1.0,1.7) 3.1 (2.4,3.9) 5.0 (3.9,6.4) 6.7 (5.1,8.9) 11.5 (8.1,16.2)

Age

1 to <3 yrs 0.2 (0.1,0.4) 0.6 (0.3,1.2) 1.4 (0.8,2.6) 2.2 (1.2,4.1) 3.0 (1.6,5.5) 5.2 (2.7,10.0)

3 to <6 yrs 0.4 (0.2,0.8) 1.2 (0.7,1.9) 2.5 (1.6,3.9) 3.8 (2.5,5.9) 4.9 (3.2,7.6) 7.8 (4.8,12.7)

6 to <11 yrs 0.5 (0.3,0.7) 1.3 (1.0,1.9) 3.1 (2.2,4.5) 5.0 (3.3,7.7) 6.8 (4.3,10.7) 11.3 (6.5,19.5)

11 to <16 yrs 0.3 (0.2,0.5) 1.1 (0.8,1.6) 2.8 (2.1,3.7) 4.8 (3.6,6.4) 6.5 (4.8,8.9) 11.2 (7.9,15.8)

16 to <18 yrs 0.6 (0.3,1.2) 1.6 (1.0,2.8) 3.8 (2.6,5.6) 6.2 (4.2,9.2) 8.4 (5.5,12.9) 14.2 (8.6,23.4)

18 to <21 yrs 0.7 (0.4,1.4) 2.0 (1.2,3.4) 4.6 (3.1,6.8) 7.1 (4.6,11.1) 9.3 (5.7,15.1) 15.0 (8.7,26.0)

Gender

Female 0.4 (0.3,0.6) 1.2 (0.9,1.6) 3.0 (2.3,3.9) 4.9 (3.7,6.5) 6.7 (4.9,9.1) 11.5 (8.0,16.5)

Male 0.5 (0.3,0.7) 1.3 (1.0,1.8) 3.1 (2.4,4.0) 5.1 (3.9,6.6) 6.8 (5.1,9.0) 11.5 (8.0,16.5)

Race/Ethnicity 1

Mexican American 0.5 (0.3,0.7) 1.3 (1.0,1.8) 3.0 (2.2,3.9) 4.7 (3.4,6.4) 6.3 (4.5,9.0) 11.2 (7.3,17.1)

Other Hispanic 0.4 (0.2,0.9) 1.3 (0.7,2.4) 2.8 (1.5,5.4) 4.3 (2.2,8.4) 5.6 (2.8,11.0) 8.9 (4.5,17.6)

Non

- Hispanic White 0.3 (0.2,0.5) 0.8 (0.6,1.2) 1.8 (1.3,2.5) 2.7 (1.9,3.9) 3.5 (2.4,5.1) 5.8 (3.6,9.3)

Non

- Hispanic Black 1.3 (0.9,1.9) 3.3 (2.4,4.7) 6.7 (4.7,9.3) 9.6 (6.7,13.5) 11.9 (8.3,17.0) 17.7 (12.2,25.9)

Other Race 1.3 (0.8,2.1) 3.4 (2.3,4.9) 6.8 (4.5,10.3) 9.8 (5.9,16.3) 12.4 (7.2,21.4) 17.3 (9.0,33.4)

Income

$0 to <$20K 0.5 (0.3,0.7) 1.5 (1.1,2.1) 3.7 (2.8,5.0) 6.0 (4.4,8.0) 7.8 (5.7,10.9) 12.7 (8.6,18.7)

$20 to <$45K 0.5 (0.3,0.7) 1.4 (1.0,1.9) 3.2 (2.3,4.3) 5.0 (3.7,6.9) 6.6 (4.7,9.3) 10.8 (7.4,15.7)

$40 to <$75K 0.4 (0.2,0.6) 1.1 (0.7,1.7) 2.7 (1.9,4.0) 4.5 (3.1,6.6) 6.1 (4.2,9.0) 10.2 (6.8,15.4)

$75+K 0.4 (0.3,0.7) 1.3 (0.9,1.8) 2.9 (2.1,3.9) 4.6 (3.4,6.4) 6.2 (4.4,8.9) 10.9 (7.0,17.1)

>$20K 0.2 (0.1,0.9) 0.7 (0.2,2.3) 1.8 (0.7,4.8) 2.9 (1.1,7.7) 3.8 (1.4,10.5) 6.6 (2.3,18.7)

Refused/Don ’ t Know Income 0.1 (0.0,0.5) 0.7 (0.3,2.0) 2.3 (0.9,5.5) 4.5 (1.7,12.1) 7.0 (2.3,21.0) 18.8 (5.1,68.7)

Income Missing 0.4 (0.1,1.2) 1.9 (0.4,9.3) 7.7 (0.8,71.2) 14.8 (2.1,104.0) 19.8 (3.7,105.9) 30.9 (7.7,123.0)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispan ic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other race).89

## Table 28b. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 3 fish, youth , < 21 years, by geographic area

Freshwater + Estuarine Trophic Level 3

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.4 (0.3,0.6) 1.3 (1.0,1.7) 3.1 (2.4,3.9) 5.0 (3.9,6.4) 6.7 (5.1,8.9) 11.5 (8.1,16.2)

Region 1

Northeast 0.4 (0.2,0.7) 1.1 (0.6,1.8) 2.3 (1.3,4.0) 3.5 (2.0,6.3) 4.6 (2.6,8.4) 7.5 (4.0,14.2)

Midwest 0.3 (0.1,0.5) 0.8 (0.4,1.4) 2.0 (1.2,3.4) 3.4 (1.9,5.9) 4.8 (2.7,8.4) 8.9 (5.0,15.7)

South 0.7 (0.4,1.1) 1.8 (1.2,2.8) 4.2 (2.9,6.0) 6.5 (4.5,9.5) 8.6 (5.9,12.7) 14.0 (9.0,22.0)

West 0.5 (0.3,0.7) 1.4 (1.0,1.9) 3.2 (2.4,4.4) 5.3 (3.7,7.6) 7.1 (4.7,10.8) 12.0 (7.0,20.4)

Coastal Status 2

Noncoastal 0.4 (0.2,0.5) 1.1 (0.8,1.5) 2.5 (1.9,3.2) 4.0 (3.1,5.2) 5.4 (4.1,7.1) 9.0 (6.6,12.4)

Coastal 0.6 (0.4,0.9) 1.7 (1.2,2.5) 4.2 (2.9,5.9) 6.7 (4.6,9.7) 9.0 (6.0,13.4) 15.0 (9.5,23.5)

Coastal/Inland Region 1,2

Pacific 0.5 (0.3,0.9) 1.6 (1.1,2.5) 4.1 (2.6,6.6) 6.8 (4.0,11.7) 9.2 (5.0,16.9) 15.0 (7.6,29.6)

Atlantic 0.8 (0.5,1.2) 2.1 (1.3,3.2) 4.5 (3.1,6.7) 6.9 (4.7,10.1) 8.9 (6.0,13.1) 13.9 (9.2,20.9)

Gulf of Mexico 0.8 (0.3,1.9) 2.1 (1.0,4.5) 5.1 (2.6,10.2) 8.6 (3.9,18.9) 12.1 (5.0,29.4) 21.2 (9.0,50.2)

Great Lakes 0.4 (0.2,0.6) 1.1 (0.6,2.0) 3.0 (1.6,5.5) 5.1 (2.5,10.3) 7.2 (3.4,15.0) 12.6 (5.9,26.7)

Inland Northeast 0.3 (0.2,0.6) 0.9 (0.5,1.6) 2.0 (1.1,3.4) 2.9 (1.6,5.2) 3.8 (2.1,6.8) 5.9 (3.1,11.4)

Inland Midwest 0.2 (0.1,0.4) 0.7 (0.4,1.2) 1.6 (0.9,3.0) 2.6 (1.4,4.8) 3.7 (2.0,6.7) 6.7 (3.8,11.8)

Inland South 0.6 (0.4,0.8) 1.6 (1.1,2.2) 3.5 (2.6,4.8) 5.5 (4.1,7.5) 7.2 (5.2,10.0) 11.5 (7.9,16.6)

Inland West 0.4 (0.3,0.7) 1.2 (0.8,1.8) 2.7 (1.8,3.8) 4.2 (2.9,6.0) 5.5 (3.8,8.0) 9.0 (5.9,13.8)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionall y, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.90

## Table 29a. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, youth

, <21 years, by demographic characteristics

Freshwater + E stuarine Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.2 (0.1,0.3) 0.6 (0.4,1.0) 2.0 (1.2,3.2) 3.9 (2.4,6.3) 6.0 (3.6,9.9) 13.2 (7.4,23.5)

Age

1 to <3 yrs 0.1 (0.0,0.3) 0.4 (0.2,0.9) 1.2 (0.6,2.3) 2.2 (1.2,4.0) 3.3 (1.9,5.8) 7.1 (4.1,12.3)

3 to <6 yrs 0.1 (0.0,0.2) 0.3 (0.2,0.6) 1.1 (0.6,2.1) 2.3 (1.0,5.0) 3.6 (1.4,9.5) 8.5 (1.8,39.4)

6 to <11 yrs 0.2 (0.1,0.3) 0.7 (0.4,1.2) 2.2 (1.3,3.7) 4.1 (2.3,7.5) 6.2 (3.3,11.7) 13.7 (6.7,28.0)

11 to <16 yrs 0.1 (0.1,0.3) 0.6 (0.3,1.1) 1.9 (0.9,3.7) 3.7 (1.8,7.6) 5.6 (2.7,11.8) 12.1 (5.4,27.3)

16 to <18 yrs 0.3 (0.1,1.1) 1.1 (0.4,3.3) 3.2 (1.2,8.7) 5.8 (2.1,15.9) 8.7 (3.2,23.5) 18.4 (6.7,50.0)

18 to <21 yrs 0.2 (0.1,0.5) 0.8 (0.4,1.7) 2.7 (1.3,5.4) 5.3 (2.5,11.1) 8.3 (3.8,17.9) 18.9 (7.3,48.8)

Gender

Female 0.1 (0.1,0.2) 0.5 (0.3,0.8) 1.5 (0.9,2.3) 2.9 (1.8,4.5) 4.4 (2.8,7.1) 9.8 (5.8,16.7)

Male 0.2 (0.1,0.4) 0.8 (0.5,1.4) 2.5 (1.5,4.3) 4.9 (2.9,8.4) 7.5 (4.2,13.1) 16.5 (8.8,30.8)

Race/Ethnicity 1

Mexican American 0.1 (0.1,0.2) 0.4 (0.3,0.7) 1.4 (0.9,2.2) 2.7 (1.7,4.5) 4.3 (2.5,7.2) 9.8 (5.1,18.9)

Other Hispanic 0.1 (0.0,0.4) 0.6 (0.2,1.9) 2.0 (0.4,8.6) 4.1 (0.7,22.7) 6.2 (0.9,43.6) 13.9 (1.3,145.9)

Non

- Hispanic White 0.1 (0.1,0.3) 0.5 (0.2,0.9) 1.5 (0.8,3.0) 2.9 (1.4,5.7) 4.3 (2.1,8.8) 9.1 (4.2,19.9)

Non

- Hispanic Black 0.4 (0.2,0.8) 1.4 (0.7,2.6) 3.9 (2.1,7.5) 7.3 (3.8,14.1) 10.8 (5.5,20.9) 22.5 (11.1,45.3)

Other Race 0.4 (0.2,0.7) 1.4 (0.7,2.6) 4.4 (2.2,8.7) 8.8 (4.2,18.3) 13.3 (6.0,29.7) 30.7 (10.6,88.8)

Income

$0 to <$20K 0.2 (0.1,0.3) 0.7 (0.4,1.1) 2.1 (1.3,3.5) 4.1 (2.4,6.9) 6.2 (3.6,10.9) 13.3 (6.9,25.3)

$20 to <$45K 0.1 (0.1,0.3) 0.5 (0.3,0.9) 1.6 (0.9,2.9) 3.2 (1.8,5.8) 5.0 (2.7,9.2) 11.3 (5.6,22.9)

$40 to <$75K 0.2 (0.1,0.3) 0.6 (0.4,1.0) 2.0 (1.2,3.4) 4.0 (2.3,7.0) 6.2 (3.4,11.3) 14.6 (7.2,29.7)

$75+K 0.2 (0.1,0.4) 0.8 (0.4,1.4) 2.3 (1.3,4.1) 4.5 (2.6,7.7) 6.6 (3.7,11.6) 13.9 (7.5,25.8)

>$20K 0.0 (0.0,0.3) 0.3 (0.1,1.6) 1.7 (0.5,5.7) 3.7 (1.2,10.9) 5.8 (2.0,16.2) 14.1 (5.3,37.2)

Refused/Don ’ t Know Income 0.0 (0.0,0.1) 0.1 (0.0,0.5) 0.5 (0.1,2.1) 1.3 (0.3,5.5) 2.4 (0.5,11.5) 9.5 (1.4,64.2)

Income Missing 0.1 (0.0,0.4) 0.4 (0.1,1.9) 1.6 (0.3,7.8) 3.6 (0.8,15.5) 5.5 (1.4,21.4) 12.1 (3.5,41.6)

1 Race/ e thnicity is as defined by NHANES. Respondents who self

- identified as “ Mexican American ” were coded as such regardless of their other race

- ethnicity identities. Otherwise, self

identified “ Hispanic ” ethnicity was coded as “ Other Hispanic. ” All other non

- Hispanic participants were then categorized based on their self

- reported races: non

- Hispanic white, non

- Hispanic

black, and other non

- Hispanic race including non

- Hispanic multiracial (other r ace).91

## Table 29b. UFCR estimates (g/day raw weight, edible portion): Total freshwater + estuarine trophic level 4 fish, youth

, <21 years, by geographic area

Freshwater + Estuarine Trophic Level 4

Finfish and Shellfish Percentiles (95% CI)

50th 75th 90th 95th 97th 99th

Youth ( < 21 yrs) 0.2 (0.1,0.3) 0.6 (0.4,1.0) 2.0 (1.2,3.2) 3.9 (2.4,6.3) 6.0 (3.6,9.9) 13.2 (7.4,23.5)

Region 1

Northeast 0.1 (0.0,0.2) 0.3 (0.1,0.7) 1.0 (0.4,2.3) 2.0 (0.8,5.0) 3.1 (1.1,8.5) 6.9 (1.9,24.9)

Midwest 0.2 (0.0,0.6) 0.7 (0.2,2.3) 2.4 (0.8,7.0) 4.9 (1.8,13.3) 7.6 (2.9,20.0) 17.9 (7.0,45.8)

South 0.2 (0.1,0.4) 0.8 (0.5,1.3) 2.4 (1.6,3.7) 4.6 (2.9,7.3) 6.9 (4.2,11.3) 14.7 (8.3,25.8)

West 0.2 (0.1,0.3) 0.6 (0.4,0.9) 1.7 (1.1,2.7) 3.3 (2.0,5.4) 4.9 (2.9,8.2) 10.2 (5.4,19.3)

Coastal Status 2

Noncoastal 0.1 (0.1,0.3) 0.6 (0.3,1.0) 1.8 (1.0,3.1) 3.5 (2.0,6.0) 5.3 (3.0,9.3) 11.7 (6.4,21.6)

Coastal 0.2 (0.1,0.4) 0.7 (0.4,1.3) 2.4 (1.5,4.0) 4.7 (2.8,7.8) 7.2 (4.2,12.3) 15.9 (8.3,30.5)

Coastal/Inland Region 1,2

Pacific 0.2 (0.1,0.3) 0.6 (0.3,1.1) 1.9 (1.1,3.2) 3.7 (2.1,6.2) 5.5 (3.1,9.7) 11.8 (6.0,23.2)

Atlantic 0.2 (0.1,0.4) 0.8 (0.4,1.4) 2.4 (1.3,4.3) 4.6 (2.5,8.5) 7.0 (3.7,13.5) 15.3 (6.5,35.8)

Gulf of Mexico 0.3 (0.1,0.5) 0.9 (0.5,1.8) 2.8 (1.5,5.2) 5.4 (3.0,9.8) 8.1 (4.5,14.5) 15.7 (7.7,32.0)

Great Lakes 0.2 (0.1,0.5) 0.8 (0.3,2.2) 2.8 (1.0,7.8) 5.7 (2.0,16.7) 9.1 (3.0,27.9) 22.6 (6.5,78.6)

Inland Northeast 0.1 (0.0,0.2) 0.2 (0.1,0.6) 0.8 (0.3,2.1) 1.7 (0.6,4.9) 2.7 (0.8,8.8) 6.0 (1.3,28.0)

Inland Midwest 0.2 (0.0,0.6) 0.7 (0.2,2.4) 2.3 (0.7,6.9) 4.5 (1.6,12.5) 6.8 (2.6,17.9) 15.7 (6.5,37.9)

Inland South 0.2 (0.1,0.3) 0.7 (0.4,1.1) 2.1 (1.3,3.3) 3.9 (2.4,6.4) 5.9 (3.5,9.9) 12.7 (7.2,22.4)

Inland West 0.2 (0.1,0.3) 0.5 (0.3,0.9) 1.6 (0.9,2.7) 3.0 (1.7,5.2) 4.4 (2.5,7.8) 9.1 (4.6,18.0)

1 U.S. r egions are the U.S. Census Bureau regions. Midwest = OH, MI, IN, WI, IL, MO, IA, MN, SD, ND, NE, KS. Northeast = PA, NY, NJ, CT, RI, MA, NH, VT, ME. South = DE, MD, DC, VA, WV, KY,

TN, NC, SC, GA, AL, MS, FL, LA, AR, OK, TX. West = NM, CO, WY, MT, ID, UT, AZ, NV, CA, OR, WA, AK, HI.

2 Coastal regions include counties bordering the 3 coasts (Pacific, Atlantic, and Gulf of Mexico) and the Great Lakes and estuaries and bays. Additionally, any county that did not directly

border a coast, but the central point was within 25 miles of a coast was defined as coastal. The inland regions are the remaining counties in each of the 4 Census Regions.92

# 5. 3 Uncertainty

The estimated fish consumption rates may be uncertain due to either bias or random variation. Bias

results in a consistently high or consistently low fish consumption rate relative to the true or desired

value. Variation results in an uncertain fish consumption rate that might be either highe r or lower

than the true value.

The primary sources of random variation are the following:



 

## Sampling error associated with the random selection of NHANES respondents. For example, if different counties an d individuals had been selected for the NHANES data collection, the data and FCRs would be different.

Random differences due to the simulation of usual fish consumption for each

N HANES respondent. This source of variation can be reduced by increasing the

number of simulations.

The confidence intervals for the fish consumption rates account for both of these sources of

variation. Estimates for coastal regions will be less precise than national estimates because the

number of respondents in the coastal regions is a fraction of the number of NHANES respondents

nationally. As a result, the confidence intervals for coastal regions are wider than for national

estimates. Similarly, if there are fewer respondents with reported fish consumption in two 24-hour

recalls, there is less data to estimate the parameters and particularly the variance components,

resulting in more uncertainty in the fish consumption estimates and wider confidence intervals.

There are multiple sources of bias that can affect the fish consumpti on rates including:











 

## Seasonality ;

Respondent bias;

U se of standard r e cipes to calculate fish consumption amounts from the NHANES 24-
hour recalls;

Classification of the fish consumed into types of fish habitats;

Bias associated with the estimation method (e it her the NCI or EPA Method ) and its assumptions; and

Use of approximate analysis weights for coastal versus non -coa stal comparisons.

Each of these sources of bias is discussed in more detail below.

93

# 5.3.1 Seasonality

Fish consumption, especially of recreationally or sport

- caught fish, is likely to vary by season.

NHANES collects data throughout the year. However, NHANES generally collect s data in northern

counties in the summer and southern counties in the winter. Thus the estimates may overestimate

usual intake in the northern regions of the United S tates and underestimate usual intake in th e southern regions of the United S tates if summer fish consumption is higher than winter fish

consumption. There is no way to estimate this season effect as there are little or no NHANES data

from northern counties in the winter and southern counties in the summer.



# 5.3.2 Bias in the Reported Fish Consumption

The reported fish consumption is a combination of the frequency of fish consumption and the

amount consumed if fish was consumed. The reported fish consumption may be biased if

NHANES respondents tend to report consistently more or less fish consumption in the 24-hour

recall than actually occurred. Assessing if the reported values are biased requires co mparing reported

values to estimates obtained using other data collection approaches, such as analysis of duplicate

meal s . Over the years, much research has gone into assessing dietary intake, resulting in the

procedures used by NHANES. As a result, the es timates from NHANES are generally considered to

have minimal bias. Nonetheless, the estimates may be biased and the bias may be different for

different communities or subpopulations.



# 5.3.3 Use of Standard Recipes

The FNDDS utilizes standard recipes for foods reported consumed. NHANES participants do not

supply specific recipes of the foods they consumed. They provide details such as whether the fish

was breaded, cooked in margarine, baked or broiled, etc., but they do not provide exact recipes

(which th ey are likely not to know anyway). For example, the standard recipe for the food “ Scallops

and noodles with cheese sauce” is approximately 35 percent fish. However, the true recipe for the

food consumed by an NHANES respondent may have less fish or more fish than the standard

recipe. Additionally, there is uncertainty associated with the moisture loss values for processing and

cooking methods. They are average values of moisture loss given the various processing and cooking

methods. If participants cooked their fish a bit longer than the moisture loss would be a bit greater

than average, and if they cooked it a bit less, the moisture loss would be a bit less than average.

94

# 5.3.4 Habitat Assignments

There is some uncertainty associated with the assignment of habitats to reported fish consumption.

When the raw data are processed by NHANES, fish species reported consumed are combined into

groups. Generally, these groupings are based on taxonomic groups. This grouping of species

complicates the assignment of habitat because in some cases, the grouped fish can inhabit different

habitats and there is no way to determine the exact species the participant consumed. For some

species, apportioning relied on NOAA landings data to assign species of fish groups with many

species (e.g., clams) to habitats. Bias in the proportion of each species assigned to each habitat will

directly affect the corresponding fish consumption rate. For example, if more fish are assigned to

the estuarine habitat, then the total amount of estuarine fish consumed and the percentiles of fish

consumption will be higher than if fewer fish are assigned to the habitat. Even if the allocation to

fish habitats is unbiased overall, there may be bias for local estimates. For example, if residents in

coastal counties each more locally caught estuarine fish and non

- coastal residents eat more

commercial non -estuarine fish of the same species, the estimated proportion of estuarine fish will be

biased low for the coastal counties and biased high for the non-coastal counties.



# 5.3.5 Estimation of Usual Fish C onsumption

Measurements of usual fish consumption are very difficult to obtain. Since usual fish consumption is

a long- term average, we would need many 24 -hour recalls over a long time to approximate what

“usual intake” is trying to assess ; th erefore we rely on a statistical model and associated assumptions

to estimate usual intake. As a result, the estimates of usual fish consumption depend in part on the

statistical assumptions.

The model makes certain a ssumptions, such as, 24-hour recalls provide unbiased estimates of fish

consumption, all respondents are fish consumers (at least occasionally), and the distribution of fish

consumption among those reporting consumption in a 24-hour recall is normally distributed for

some power transformation. The validity of these assumptions can be discussed and, to some extent

evaluated using data.

The estimates of the frequency of fish consumption depend in part on how non-consumers (those

who never eat fish or don’t eat fish for a long time) are treated. From two 24 -hour recalls it is not

possible to separate true non-consumers from those who did not happen to report fish consumption

in either recall. A similar problem relates to consumption of small amounts for fish. Should a person

95

## who never eats an identifiable piece of fish but uses a salad dressing with a small amount of fish in it

be considered a regular consumer of a very small amount or a non-consumer of fish? Whether a

meal is classified as having fish may dep end on the procedures used to ask the questions and the

recipes used to estimate fish consumption. Unfortunately we do not have the data needed to identify

non-consumers. Having non-consumers in the data will lower the overall probability of fish

consumption (P) but increase the variance of the probability of fish consumption among individuals.

The resulting effect on the upper percentiles of the distribution is not clear.

The reported amount of fish consumption will vary from one 24-hour recall to anothe r, in part

because the respondents may be poor at estimating the amount consumed and in part because the

consumption amounts are reported in rounded units, such as a cup or a pint, but not 1.267 cups.

The rounding adds some uncertainty to the estimates. Th e within -person variance component

accounts for uncertainty due to poor estimation by the respondent and rounding that is part of the

process. Because the definition of usual fish consumption does not include the within-person

variation, this source of error should contribute minimal bias to the estimates of usual fish

consumption.

The statistical models for the NCI and EPA Method s make some assumptions to simplify the

computations, such as an assumption that variance components are normally distributed, additive in

the transformed scale, and linearly correlated. The assumption that the person -specific random

effect in the probability model is normally distributed is difficult to test without many more 24-hour

recalls for each person. The assumption that the two variance components in the amount model are

normally distributed is generally consistent with the observation that the Box-Cox transformed

consumption amounts are roughly normally distributed. Nevertheless, other assumptions may imply

a similar dist ribution for the reported amounts while using a somewhat different assumption for the

person-specific variance component and thus somewhat different estimates of fish consumption.

Because the estimated parameters must be consistent with the reported data, the general center and

spread of the predicted distribution will be similar regardless of the distributional assumptions.

Specific percentiles may be either higher or lower using different assumptions or may be relatively

insensitive to the distributional assumptions. Although these assumptions are common in other

statistical applications, it is difficult to assess how the estimates might change using other

assumptions.

If the model assumptions are accepted as reasonable, then the question is whether the estimates

from the model are biased. The estimates are based on maximum likelihood , which can produce

biased estimates, particularly variance estimates, with small sample sizes. However, convergence

96

## theory says maximum likelihood is best with large sample sizes. Due to the relatively large sample

sizes, we expect the estimates to have relatively little bias compared to the size of the confidence

intervals.

The fish consumption estimates depend in part on the independent predictors used in the model.

When different predictors are used, the estimates change. It is impossible to know what the best set

of predictors is. A systematic approach was used to selecting the independent predictors from the

available predictors in an effort to minimize any bias. The estimates have unknown bias due to the

decisions that were made.

Relative to the NCI Method, the EPA Method uses approximate methods to estimate the

parameters and as a result, percentile estimates from the EPA Method may be more biased than

from the NCI Method . The analysis of simulated data and the comparison of the FCR percentiles

b etween the NCI and EPA Method s suggest that the results from the EPA Method have little bias

overall , although estimates for some percentiles may be more biased than for others. The bias

observed in the comparisons between the NCI Method and the EPA Method are very small

compared to the spread of the overall distribution, generally small compared to the width of the

confidence interval, and on the same order as bias due to other sources such as the selection of the

independent predictors.



# 5.3.6 Weights f or Coastal Versus Non

- Coastal Regions

The U .S. Census regions are used in the calculation of the NHANES weights. However, the analysis

using coastal versus non- coastal regions is looking at smaller areas than intended when the weights

were constructed. Some of the coastal/noncoastal regions cross these Census regions. As a result,

comparisons among coastal and non- coastal regions may be slightly biased or less precise then

indicated by the confidence intervals. At the same time, the weights also adjust for oversampling of

some populations and survey nonresponse, so we believe it is important to use the weights. While

the estimates may be more imprecise and there may be some uncertainty due to the weighting, they

are still a better representation for each coa stal/noncoastal area then using unweighted or national

estimates

.

97

# Discussion 

# 6

Fish consumption is higher among males compared to females and increases with increasing age

,
al though persons aged 65 and over show decreased consumption . People of races oth er than B lack

and White have the highest fish consumption rates of all race/ethnicity groups, with significant

differences observed across all percentiles and many fish types, excluding freshwater and estuarine

fish, trophic level 2 fish, trophic level 2 freshwater and estuarine fish, and trophic level 2 marine fish

. The other race category consists of Asian, Native American, Pacific and Caribbean Islander, Alaska

Native, multiracial, and unknown race

. There is a general increase in consumption as income

i ncreases.

People in the Northeast have higher total fish consumption rates than those living in the other

Census r egions, while people in the Midwest have the lowest rates. Significant differences are

observed between the regions. The inland regions generally have lower fish consumption rates than

the coastal regions except for the Great Lakes region , which is more similar to an inland region, and

the inland Northeast, which appears more similar to a coastal region. This pattern is different for

freshwate r fish for which the people in the inland south, Great Lakes, and the Gulf of Mexico have

the highest consumption rates.

98

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