# An Intervention Analysis for the Reduc tion of Exposure to Methylmercury from the Consumption of Seafood by Women of Child-bearing Age

C D Carrington, B Montwill, and P M Bolger. Center for Food Safety and Applied Nutrition U.S. Food and Drug Administration College Park, MD, USA.

# Abstract

A previously developed exposure model was us ed (Risk Analysis 22: 689-699, 2002) to assess the effectiveness of various advisory scenario s on minimizing mercury (H g) blood levels via the consumption of commercial seafood, both finf ish and shellfish. This exposure model was developed to predict levels of Hg in blood in women of child-bearing age in the US based on the frequency of seafood consumption, the amount of seafood consumed per serving, and the types of seafood consumed. Steady-state relationships th at employed descriptive statistics to account for toxicokinetic variation were used to predict levels of Hg in blood. The model incorporates an uncertainty dimension that is intended to represent the range of plausible interpretations of the data. The predictability of the model was confir med via the use of National Health and Nutrition Examination Survey (NHANES) blood Hg data. In the present analysis, the model was used to predict the impact of limitations in the amount or types of seafood consumed on blood Hg levels. Specifically, simulations for various advisory scenarios were developed on the basis of limitations on total consumption of seafood, elimin ation of the consumption of certain species altogether, and/or a combinati on of both. In the baseline model, the median (uncertainty) estimates for the 50 th 

# , 95 th 

# , and 99 th 

# per capita populati on percentiles were 1.25, 8.2, and 16.1 ppb blood Hg, respectively. After re striction of seafood consumption to no more than 12 oz per week, the median (uncertainty) estimates for the 50 th 

# , 95 th 

# , and 99 th 

# per capita population percentiles were 1.22, 6.8, and 10.6 ppb blood Hg, resp ectively. Elimination of MeHg species, with average concentrations a bove 0.6 ppm, resulted in very modest decrements in Hg blood levels, in comparison to either the baseline or the reduced consumption scenarios. These results suggest that strategies to re duce MeHg exposure by reducing the amount of fish consumed (e.g., 12 oz/week) are more effective at eliminating th e high end of the exposur e distribution than are strategies intended to change the types of fish consumed.

# Introduction

Methylmercury (MeHg) is a well known environm ental toxicant found in the aquatic ecosystem. Inorganic mercury originates fr om anthropogenic and natural sour ces. Once in the ecosystem inorganic mercury is converted to methylmercury primarily through bacteria l activity and accumulates in fish and other marine species to varying degrees, particularly in long-lived, predators which are at the top of the marine food-chain. Depending on the level of exposure MeHg can cause mild to severe neurological symp toms, such as paresthesia, ataxia, dysarthyria, hearing defects, visual disturbances and death. Levels of exposure seen in some fish-eating populations have been reported to be associated with developmental delays in children whose mothers were exposed during pregnancy. While high-level poisoning episodes in Minimata and Nigata, Japan and in Iraq demonstrated pronounced MeHg-induced neurological deficits there is also concern that MeHg can cause more subtle developmental delays or other neurological effects at lower levels of exposur e more consistent with the usual patterns of fish consumption seen in the U.S. (JECFA, 2003; NRC, 2000).

As part of its efforts to minimize the risks as sociated with such outcomes the U.S. Food and Drug Administration issued a new advisory in 2001 that provided recommendations concerning the consumption of certain fish species and for fish in general by pregnant women. The FDA advised these women to avoid the consumption of four species of fish; namely King mackerel, shark, swordfish and tile fish. In addition, it was recommended that they include up to 12 oz of a variety of other fish species over the course of a wee k. In order to better understand and define what a variety of fish means a series of expo sure assessments of various fish consumption scenarios were performed that were constructed to be consistent with th e consumption of 12 oz of a variety of fish. The scenarios differed in how “variety” of fish was defined. In these assessments several thresholds of safety (e .g., Minimal Risk Level (ATSDR, 1999), Provisional Tolerable Weekly Intake (JECFA, 2003), Refe rence Dose (USEPA, 2001)) were used as measures of the effectiveness of the consump tion/exposure scenarios in keeping weekly MeHg exposures of women who followed the specific advise scenario be low the threshold of safety.



# Methodology

The Baseline Model
The model employed in the present analysis is a modified version of a model described previously (Carrington and Bolger, 2002). These modifications are as follows:

• The number of fish categories for which distri butions were developed was expanded from 24 to 42. (see Table 1). Tuna was broken into thre e categories, corresponding to 1) light canned tuna, 2) albacore canned tuna, a nd 3) fresh/frozen tuna steaks.

• Mercury concentration data was obtained for add itional species, which are identified in Table 2. For tuna steaks, this data was used to construct an empirical distribution. For the

# remaining species for which additional data was obtained, modeled distributions were developed by fitting the distributions to the por tions of the cumulative distribution above the levels of detection. A battery of ten distributio ns were fit to each data set and the four that provided the best fit were used to construct a probability tree (see Figure 1 for an example and Carrington, 1996 for further de scription of the methodology).

• A range of 0.1 to 0.2 ppb was added to blood Hg le vels in order to re present contributions from sources other than fish. This range refl ected the levels at the low end of the National Health and Nutrition Examina tion Survey (NHANES; CDC, 2003) . Since virtually everyone in the NHANES survey had a blood mercury level above zero, yet 10-20% of the NHANES survey population reported no seafood consumption, th is suggests that there are contributions to blood Hg levels from other sources (e.g., de ntal amalgams) other than seafood. Since the present model is intended to represent methylme rcury exposure, a range with an uncertainty bound including zero was introduced to acknowledge the possibility of mi nor exposures from sources other than seafood.

• A correction factor (listed in Table 1) was applied to re flect water loss during food preparation. The values were based on water loss of 11% for fried seafood, 21% for poached or steamed seafood, and 25% for baked or br oiled seafood (EPA, 2000). Group-specific correction factors were calculated based on the frequency of use of di fferent food preparation (e.g. baking, steaming, or frying) within ea ch group, based on the CSFII survey (USDA, 1998). A default value of 0.8 was used for cate gories not represented in the CSFII survey. These are listed in Table 1. No correction f actors were applied for canned-tuna since the MeHg concentration values, expressed as total Hg, were obtained afte r cooking and draining of water or oil from the can.

• The model parameters used to extrapolate long-term frequency of consumption from shortterm records were chosen to be consistent with the 30 day seafood consumption data collected by NHANES (see Figure 2). The percentage of cons umers was also changed from 70-90% to 85 to 95% in order to be consistent with the NHANES survey.

• The fraction of the annual seafoo d diet estimated from the i ndividual dietary survey, as opposed to market share, was treated as an in dividual variable rather than as a population uncertainty. Also, instead of using a range of 20 to 80%, the fraction of seafood meals falling within a single category wa s used to represent range of individual repe titiveness (i.e. the extent to which a short-term survey can be expected to represent the range of species consumed). This distribution was derived from the NHANES survey, by calculating the fraction of total seafood consumption in th e seafood category with the highest number of eating occasions for the 403 adult women who consumed seafood on 4 or more occasions (see Figure 3)

Scenarios
In order to simulate the impact of consumer seafood advisories for women of child bearing age who become pregnant, several scenarios were deve loped that are intended to predict the expected impact of the advisory on mercury blood. All the scenarios presumed full compliance with the advisory. Seafood species were divided into three groups, as listed in Table 2.

# Using these groups, the following advisory scenarios were modeled:

• Total Seafood Consumption Limits (see Table 3)

. The consumption of seafood is limited to 6, 12, or 18 oz without regard to species.

• Species Consumption Limits (see Table 4)

. There is no limit on how much fish may be consumed. Seafood consumption is limited to either the middle or low groups (No High Hg), or the low group only (Low Hg Only). In either case, seafood from the restricted group(s) is replaced by a random selection from a market -share distribution of low mercury species.

• Total Seafood and Species Limit Combinations (see Table 5)

. o 12 oz No High Consumption of seaf ood is limited to 12 oz per week, high mercury fish are replaced with low mercury fish.

o 12 oz Variety. Seafood consumption is limited to 12 oz per week, with no more than 6 oz from the Middle Hg group. High Hg fish (shark, swordfish, and mackerel) and Middle Hg fish in excess of 6 oz are replaced with Low Hg fish.

o 12 or 6 Albacore. Same as 12 oz variety. In addition, for the purposes of calculating the 12 oz limit, albacore portions are doubled. As a result, the maximum amount of seafood that may be consumed is reduced by an amount equal to the amount of albacore consumed. For example, if 3 oz of albacore is consumed per week, then th e total amount of seafood that may be consumed is 9 oz. As the most extreme example, if 6 oz of albacore is consumed per week, then no additional seafood may be consumed.

o 12 Low or 6 oz Middle. Seafood consumption is limited to 12 oz per week, High Hg fish (shark and swordfis h) are replaced with Low Hg fish. For the purposes of calculating the 12 oz limit, seafood por tions from the Middle group are doubled. As a result, the maximum amount of seafood that may be consumed is reduced by an amount equal to the amount of seafood from the middle group consumed. For example, if 3 oz of Middle Group seafood is consumed per week, then the total amount of seafood that may be consumed is 9 oz. As the most extreme example, if 6 oz of Middle Group seafood is c onsumed per week, then no additional seafood may be consumed.

o 12 oz Low. Seafood consumption is limited to 12 oz, high and mid Hg fish are replaced with low Hg fish.



# Results

Comparison of Baseline Model to NHANES
The results from the blood mercury exposure mode l were compared to survey mercury blood values from the NHANES survey population betw een 1999 and 2000 (see Figur e 4). The values are in very close agreement.

# Intervention Scenarios
The impact of various consumer a dvisories on mercury bl ood levels is presen ted in Tables 3, 4, and 5. In each case, the impact of each advisory is compared to current baseline blood mercury values.
Total Seafood Consumption Limits Table 3 shows the expected reduction in merc ury blood levels following the introduction of consumption limits ranging from 6 to 18 oz per week. While a limit of 18 oz only slightly reduces the level of exposure at the extreme tail (i.e. above the 99 th 

# percentile), more aggressive limits reduce exposure for a grea ter range of consumers and provi de a greater reduction at the tail.
Advisories Concerning Specific Species Table 4 shows the expected reduction in mercur y blood levels following the elimination of certain species, with either particularly high me rcury levels or any species with above average mercury levels. Although the reductions on mercur y exposure are not as dramatic, the reductions in exposure may be noted acr oss the entire distribution.
Advisories Combining Limits on Amount and Species Table 5 shows the expected reduction in blood me rcury levels with several different scenarios where the advisory includes some combination of limitation on the amount of seafood consumed with additional limitations on the types of seafood consumed In the first scenario, which reflects the current FDA advisory avoiding the consump tion of high methylmercury species and limiting seafood consumption to no more than 12 oz per week will eliminate th e occurrence of blood mercury values that are higher than 5 times the average. The simulations indicate that more aggressive limits on what species are consumed would result in greate r reductions across the entire distributions of blood me rcury values, but only provide mi nor, further (in comparison with advisories that only limit the amount of fish c onsumed) reductions in those consumers with the highest levels of exposure.

Conclusions
The purpose of this analysis was to assess the imp act of a variety of fish consumption advisory scenarios on modeled di stributions of blood mercury levels in a population of women of childbearing age. This population group was identif ied to be the subpopulation group of greatest concern because of MeHg induced fetal effect s (NRC, 2000). As stated previously it was assumed that adherence to each advisory would be complete. In a previous analysis (Carrington and Bolger, 2002) the blood mercury estimates were within a factor of two across the distributional range. The model used in the present analysis wa s revised in a number of ways. The most significant adjustments were 1) incor porating additional data on mercury levels in seafood, 2) adjusting for water loss during food preparation, a nd 3) revising the population

# distributions for frequency of s eafood consumption. As a result of these changes, the model results are in much closer agreement with NHA NES survey data for mercury in blood. While this does not prove beyond any possible doubt that th e model is entirely correct in every respect, the comparison does indicate that the results of the model are plausible.

In general, reducing overall fi sh consumption appears to have more impact on the overall population distributions than reducing or eliminati ng levels of high level mercury species only. This may be largely attributed to the fact that the fish with higher levels of mercury tend to have a smaller market share. Nonetheless, the scen arios do indicate that curtailing consumption of high level fish can reduce the number of i ndividuals with unusually high blood levels.

Comparison of the scenario distri butions with various safety stan dards (see Figur e 5) indicates that a scenario (12 oz of low Hg fish only) ma y be devised to reduce the blood Hg levels of the entire population of women aged 16 to 49 year s below any of a wide range of proposed standards. However, it is difficult to gauge the utility of any of the advisory scenarios by comparing the results to safety standards for several reasons. First, none of the standards can be equated to a level of absolute zer o risk, since it can never be esta blished that some imperceptible effect does not occur with a give n dose. Second, at the tails of the population distributions, there are likely to be some (albeit different) fraction of the total population ab ove the safety standard regardless of which is chosen. Third, because none of the standards serve as a dose-response function, a safety standard based analysis does not provide inform ation about the extent of the very small adverse effects that might be anticipated if the standard is exceeded or perhaps even if it is not. For the purpose of comparing mercur y risks to other cost s and benefits, more information could be provided by combining the present exposure assessment with a doseresponse function (e.g. Carrington and Bolger, 2000).



# References Carrington, CD (1996). Logical Prob ability and Risk Assessment. Human Ecology Risk Assessment 2:62-78.

Carrington, C.D. and Bolger, P.M. (2000). A P ooled Analysis of the Iraqi and Seychelles Methylmercury Studies. Human Ecological Risk Assessment 6 :323-340.

Carrington CD and Bolger PM (2002). An Exposure Assessment for Methylmercury from Seafood for Consumers in the United States. Risk Anal 22:689-699.

Centers for Disease Control (2003) . National Center for Health Statistics, National Health and Nutrition Examination Survey, 1999-2000 Data Files. http://www.cdc.gov/nchs/about /major/nhanes/NHANES99_00.htm

# Joint Expert Committee on Food Additives (JECFA ) of the Food Agriculture Organization and the World Health Organization (2003). http://www.who.int/p cs/jecfa/Summary61.pdf

.

National Marine Fisheries Servi ce (1978) National Marine Fisher ies Service Survey of Trace Elements in the Fishery Resource. NOAA Technical Report NMFS SSRF-721.

National Marine Fisheries Service/Office of Sc ience and Technology ( 2002). Fisheries of the United States 2001. http://www.st.nmfs.gov/st1/fus/fus01/2001-fus.pdf

.
National Research Council (NRC) of the Nationa l Academy of Sciences (2000). Toxicological Effects of Methylmercury, National Academy Press, Washington, D.C.

Schober, S., Sinks, T., Jones, R., Bolger, P., Mc Dowell, M., Osterloh, J., Garrett, E., Canady, R., Dillon, C., Sun, Y., Joseph, C. and Mahaffey, K. (2003). Blood Mercury Levels in US Children and Women of Childbearing Age, 1999-2000. JAMA 289:1667-1674.

U.S. Agency for Toxic Substances and Dise ase Registry (USATSDR ) (1999). Toxicological Profile of Mercury. http://www.atsdr.cdc.gov/toxprofiles/tp46.html.

U.S. Department of Agricultu re, Agricultural Research Se rvice (USUSDA) (1998). 1989-91 Continuing Survey of Food Inta kes by Individuals and 1989-91 Diet and Health Knowledge Survey on CD-ROM. Accession Number: PB96-501747.

U.S. Environmental Protection Agency (USEPA ) (2000), Gulf of Mexico Program. "The Occurrence of Mercury in the Fishery Res ources of the Gulf of Mexico" Report. http://mo.cr.usgs.gov/gmp/hg.cfm

. U. S. Environmental Protection Agency (U SEPA) (2002). Estimated Per Capita Fish Consumption in the United States. http://www.epa.gov/waterscience/fish/consumption_report.pdf

. U. S. Environmental Protection Agency ( USEPA) (2001). Integrated Risk Information System. http://www.epa.gov/iris/subst/0073.htm

U. S. Food and Drug Administration (USFDA) (2001). Mercury Levels in Seafood Species. http://www.cfsan.fda.gov/~frf/sea-mehg.html

. U. S. Food and Drug Administration (USFDA) (2 004). What You Need to Know About Mercury in Fish and Shellfish: EPA and FDA Advice For Women Who Might Become Pregnant, Woman Who are Pregnant, Nursing Mothers and Young Children. http://www.cfsan.fda.gov/~dms/admehg3.html

.

.

# Figure 1: Fitted Distributions for Hg in Crab Meat

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Hg Concentration (ppm)Cumulative Frequency 

### Data
Gamma Logistic
Normal
Beta



# An example of a fitted distributi on. 10 different distribut ions were fit to the sample Hg data for Crabs. The four best models were used to cr eate a probability tree that describes the frequency distribution with a representation of model un certainty. The primary advantage of using distributions to describe the data is that they can be used to extrapolate the concentration in the samples that are below the level of detection – which comprise about 50% of the crab samples.

# Figure 2: Long-Term Frequency Extrapolation for Consumption

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

01234 Seafood meals/dayCumulative Frequency



### CSFII Based Projection 30 Day NHANES



# The CSFII based projection employed the expone ntial function described in Carrington and Bolger (2002b), using values of 0.696 and 0.356 for th e alpha and beta parameters, respectively. These parameters were obtained by fitting the proj ected frequency distribution to 30 day survey data obtained from NHANES III (CDC, 2003).

# Figure 3: Major Category Ratio Distribution

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

0 0.2 0.4 0.6 0.8 1 Major Category FrequencyCumulative Frequency



### Series2

# Figure 4: Quantile-Quantile Comparison of Simulation and Survey Blood Hg Values

0 1 2 3 4 5 6 7 8 9

0 2 4 6 8 10 Simulation Values (ppb)Survey Values (ppb)



## Women Line of Equality

# Figure 5: Comparison of Scenario Ou tcomes to Various Safety Standards

0.7 0.75

0.8 0.85

0.9 0.95 1

1 1 0 1 0 0 Blood Hg (ppb)Cumulative Frequency 

### Baseline 12 oz No High
12/6 Medium 12 oz Low Only
BMDL MRL Equivalent
WHO-JECFA PTWI RfD Equivalent



# 12 oz – no restriction of fish from low or medi um Hg group; 12/6 Medium – 12 oz low or 6 oz medium Hg fish; 12 oz of low Hg fish; BMDL – Bench Mark Dose Lower Confidence Limit; WHO-JECFA PTWI – World Heal th Organization-Joint Expert Committee on Food Additives Provisional Tolerable Weekly Inta ke. RfD Equivalent – steady stat e blood level equivalent to oral Reference Dose; MRL – Minimal Risk Level. As an alternative to distinguishing the shade for each scenario or target level, the lines may be identified by noting that the top to bottom order in the figure legend corresponds to the right to left order in the figure.

# Table 1: Seafood Hg data MERCURY CONCENTRATION (PPM) 1

SPECIES MEAN MEDIAN MIN MAX n Source 2 MARKET 3

ANCHOVIES 0.04 NA ND 0.34 40 NMFS 1978 0.5% BASS (Saltwater) 4 0.27 0.15 0.06 0.96 35 FDA 1990-03 0.6%
BLUEFISH 0.31 0.30 0.14 0.63 22 FDA 2002-03 0.1%
BUFFALOFISH 0.19 0.14 0.05 0.43 4 FDA 1990-02 0.0%
BUTTERFISH 0.06 NA ND 0.36 89 NMFS 1978 0.1%
CARP 0.14 0.14 0.01 0.27 2 FDA 1990-02 0.0%
CATFISH 0.05 ND ND 0.31 22 FDA 1990-02 4.8%
CLAMS ND ND ND ND 6 FDA 1990-02 1.7%
COD 0.11 0.10 ND 0.42 20 FDA 1990-03 4.7%
CRAB 3 0.06 ND ND 0.61 59 FDA 1990-02 4.7%
CRAWFISH 0.03 0.03 ND 0.05 21 FDA 2002-03 0.6% CROAKER (Atlantic) 0.05 0.05 0.01 0.10 21 FDA 1990-03 0.3% CROAKER WHITE (Pacific) 0.29 0.28 0.18 0.41 15 FDA 1990-03 0.0%
FLATFISH 5 0.05 0.04 ND 0.18 22 FDA 1990-02 3.6%
GROUPER 0.55 0.44 0.07 1.21 22 FDA 2002-03 0.2%
HADDOCK 0.03 0.04 ND 0.04 4 FDA 1990-02 0.6%
HAKE 0.01 ND ND 0.05 9 FDA 1990-02 0.3%
HALIBUT 0.26 0.20 ND 1.52 32 FDA 1990-02 0.9%
HERRING 0.04 NA ND 0.14 38 NMFS 1978 2.5%
JACKSMELT 0.11 0.06 0.04 0.50 16 FDA 1990-02 0.0% LOBSTER (Northern/American) 0.31 NA 0.05 1.31 88 NMFS 1978 1.3% LOBSTER (Spiny) 0.09 0.14 ND 0.27 9 FDA 1990-02 0.8% MACKEREL ATLANTIC (N. Atlantic) 0.05 NA 0.02 0.16 80 NMFS 1978 0.3% MACKEREL CHUB (Pacific) 0.09 NA 0.03 0.19 30 NMFS 1978 0.2%
MACKEREL KING 0.73 NA 0.23 1.67 213 GULF 2000 0.1% MACKEREL SPANISH (Gulf of Mexico) 0.45 NA 0.07 1.56 66 NMFS 1978 0.0% MACKEREL SPANISH (S. Atlantic) 0.18 NA 0.05 0.73 43 NMFS 1978 0.0%
MARLIN 0.49 0.39 0.10 0.92 16 FDA 1990-02 0.0%
MONKFISH 0.18 NA 0.02 1.02 81 NMFS 1978 0.4%
MULLET 0.05 NA ND 0.13 191 NMFS 1978 0.2%
ORANGE ROUGHY 0.54 0.56 0.30 0.80 26 FDA 1990-03 0.2%
OYSTERS ND ND ND 0.25 34 FDA 1990-02 0.8% PERCH (Freshwater) 0.14 0.15 ND 0.31 5 FDA 1990-02 0.0%
PERCH OCEAN ND ND ND 0.03 6 FDA 1990-02 0.5%
PICKEREL ND ND ND 0.06 4 FDA 1990-02 0.1%
POLLOCK 0.06 ND ND 0.78 37 FDA 1990-02 11.1%
SABLEFISH 0.22 NA ND 0.70 102 NMFS 1978 0.3% SALMON (Canned) ND ND ND ND 23 FDA 1990-02 0.9% SALMON (Fresh/Frozen) 0.01 ND ND 0.19 34 FDA 1990-02 7.9%
SARDINE 0.02 0.01 ND 0.04 22 FDA 2002-03 1.2%
SCALLOPS 0.05 NA ND 0.22 66 NMFS 1978 0.8%
SCORPIONFISH 0.29 NA 0.02 1.35 78 NMFS 1978 0.9% SHAD (American) 0.07 NA ND 0.22 59 NMFS 1978 0.0%
SHARK 0.99 0.83 ND 4.54 351 FDA 1990-02 0.1%
SHEEPSHEAD 0.13 NA 0.02 0.63 59 NMFS 1978 0.0%
SHRIMP ND ND ND 0.05 24 FDA 1990-02 15.1%
SKATE 0.14 NA 0.04 0.36 56 NMFS 1978 0.3%
SNAPPER 0.19 0.12 ND 1.37 25 FDA 2002-03 0.5% SQUID 0.07 NA ND 0.40 200 NMFS 1978 1.0%
SWORDFISH 0.97 0.86 0.10 3.22 605 FDA 1990-02 0.4%
TILAPIA 0.01 ND ND 0.07 9 FDA 1990-02 1.9% TILEFISH (Atlantic) 0.15 0.10 0.06 0.53 17 FDA 2002-03 0.0% TILEFISH (Gulf of Mexico) 1.45 NA 0.65 3.73 60 NMFS 1978 0.0% TROUT (Freshwater) 0.03 0.02 ND 0.13 17 FDA 2002-03 0.7% TUNA (Canned, Albacore) 0.35 0.34 ND 0.85 179 FDA 1990-03 5.3% TUNA (Canned, Light) 0.12 0.08 ND 0.85 131 FDA 1990-03 13.4% TUNA (Fresh/Frozen) 0.38 0.30 ND 1.30 131 FDA 1990-02 1.8% WEAKFISH (Sea Trout) 0.25 0.16 ND 0.74 27 FDA 1990-03 0.1%
WHITEFISH 0.07 0.05 ND 0.31 25 FDA 1990-03 0.2%
WHITING ND ND ND ND 2 FDA 1990-02 4.1%

## 1 - Mercury was measured as Total Mercury and/or Methylmercury. ND - mercury concentration below the Level of Detection (LOD=0.01ppm). NA - data not available. 2 - Source of data: FDA Surveys 1990 -2003, "National Marine Fisheries Service Survey of Trace Elements in the Fishery Resource" Report 1978 , "The Occurrence of Mercury in the Fisher y Resources of the Gulf of Mexico" Report 2000 3 - Market share calculation based on 2001 National Marine Fisheries Service published landings data.

4 - Includes: Sea bass/ Striped Bass/ Rockfish

5 - Includes: Flounder, Plaice, Sole

6 - Includes: Blue, King, and Snow crab

## Table 2: Methylmercury Distributions for Various Species Species Market Share 1 Mean Hg (ppm) Distribution Type 2 Concentration Factor 3 Advisory Group Tilefish, Gulf 0.01% 1.450 Analog 0.839 High Shark 0.13% 0.988 Empirical 0.758 High Swordfish 0.42% 0.969 Empirical 0.75 High Mackerel, King 0.05% 0.73 Analog 0.8 High Grouper 0.17% 0.549 Modeled 0.823 Medium Orange Roughy 0.20% 0.540 Modeled 0.809 Medium Marlin 0.02% 0.489 Modeled 0.8 Medium Tuna, Fresh 1.79% 0.378 Empirical 0.8 Medium Mackerel, Spanish 0.05% 0.368 Analog 0.8 Medium Tuna, Albacore Canned 5.29% 0.352 Empirical 1 Medium Bluefish 0.09% 0.324 Modeled 0.839 Medium Bass, Freshwater 0.00% 0.318 Modeled 0.791 Medium Lobsters, American 1.29% 0.31 Analog 0.758 Medium Croaker, Pacific 0.00% 0.303 Modeled 0.871 Medium Lingcod and Scorpionfish 0.92% 0.286 Analog 0.802 Medium Sablefish 0.25% 0.273 Analog 0.839 Medium Trout, Saltwater 0.06% 0.269 Modeled 0.77 Medium Bass, Saltwater 0.61% 0.263 Modeled 0.797 Medium Halibut 0.90% 0.217 Modeled 0.761 Medium Carp and Buffalofish 0.02% 0.203 Modeled 0.871 Medium Haddock, Hake, and Monkfish 5.35% 0.17 Modeled 0.802 Medium Perch, Freshwater 0.04% 0.162 Modeled 0.785 Medium Cod 4.71% 0.143 Modeled 0.809 Medium Snapper, Porgy, and Sheepshead 0.54% 0.141 Modeled 0.812 Medium Skate 0.34% 0.137 Analog 0.758 Medium Tuna, Light Canned 13.35% 0.124 Empirical 1 Low Tilefish, Atlantic 0.03% 0.123 Modeled 0.839 Low Lobsters, Spiny 0.82% 0.121 Modeled 0.758 Low Smelt 0.00% 0.092 Modeled 0.867 Low Mackerel, Chub 0.17% 0.088 Analog 0.8 Low Squid 1.03% 0.07 Analog 0.818 Low Whitefish 0.22% 0.068 Modeled 0.752 Low Pollock 11.05% 0.067 Modeled 0.794 Low Catfish 4.77% 0.066 Modeled 0.8 Low Crabs 4.70% 0.063 Modeled 0.775 Low Flatfish 3.61% 0.059 Modeled 0.761 Low Butterfish 0.14% 0.0580 Analog 0.839 Low Pike 0.10% 0.056 Modeled 0.75 Low Croaker, Atlantic 0.30% 0.055 Modeled 0.871 Low Anchovies, Herring, and Shad 3.06% 0.05 Analog 0.737 Low Mackerel, Atlantic 0.29% 0.049 Analog 0.8 Low Mullet and Perch, Ocean 0.69% 0.04 Analog 0.809 Low Trout, Freshwater 0.69% 0.030 Modeled 0.752 Low Salmon 8.24% 0.028 Modeled 0.77 Low Crawfish 0.56% 0.027 Modeled 0.773 Low Tilapia 1.87% 0.02 Modeled 0.8 Low Clams 1.69% 0.017 Modeled 0.764 Low Oysters and Mussels 1.24% 0.017 Modeled 0.782 Low Scallops 0.80% 0.017 Modeled 0.793 Low Sardines 1.23% 0.016 Modeled 0.75 Low Shrimp 15.14% 0.012 Modeled 0.776 Low



## 1 – As a result of species not included in the list, the sum of the market share values is about 99%. 2 - Empirical – Direct sampling of data set, used for large data sets with very few values below the limit of detection. Fitted – Modeled distribution with uncertainty about model form (see text for additional explanation). Used for data sets with a limited number of observations, often with many values below the level of detection. Analog – Two generic distributional forms (lognormal or gamma) were employed, with a mean value from 1978 National Marine Fisheries Survey, and a shape parameter shape derived from distributions for other species (see Carrington and Bolger, 2002 for additional explanation). This technique was used when only mean values are

## available. 3 – These values reflect weight after food preparation as a percentage of initial weight. Mercury concentrations for seafood as eaten were calculated by dividing initial concentr ation by the correction factor . No correction factor was applied for canned tuna, since the mercury m easurements were made after cooking. .

# Table 3: Effect of Advisori es Based on Seafood Consumpt ion Limits on Estimated Hg Blood Levels

Scenario Baseline 18 oz/week 12 oz/week 6 oz/week Average 1.8 (1.7, 2.0) 1.7 (1.6, 1.9) 1.6 (1.5, 1.8) 1.3 (1.2, 1.4) Perc 0.10 0.2 (0.2, 0.3) 0.2 (0.2, 0.3) 0.2 (0.2, 0.3) 0.2 (0.2, 0.3) Perc 0.25 0.5 (0.4, 0.6) 0.5 (0.4, 0.6) 0.5 (0.4, 0.6) 0.5 (0.4, 0.6) Median 1.1 (0.9, 1.2) 1.1 (0.9, 1.2) 1.1 (0.9, 1.2) 1.1 (0.9, 1.2) Perc 0.75 2.2 (2.0, 2.5) 2.2 (2.0, 2.4) 2.2 (2.0, 2.4) 1.9 (1.8, 2.1) Perc 0.90 4.2 (3.8, 4.8) 4.1 (3.7, 4.6) 3.9 (3.5, 4.2) 2.7 (2.6, 2.9) Perc 0.95 6.0 (5.3, 6.8) 5.7 (5.1, 6.4) 4.9 (4.6, 5.4) 3.2 (3.0, 3.5) Perc 0.99 10.6 (8.9, 13.8) 8.5 (7.6, 9.7) 6.8 (6.3, 7.5) 4.2 (3.8, 4.6) Perc 0.995 13.1 (10.4, 17.5) 9.7 (8.4, 11.2) 7.5 (6.8, 8.6) 4.7 (4.2, 5.2) Perc 0.999 18.7 (13.8, 31.4) 12.0 (10.1, 15.3) 9.2 (8.0, 12.7) 6.0 (4.9, 8.4)

All units are μ g Hg/L in blood with uncertainty bounds expressed as 5 th 

## and 95 th 

## confidence limits in parentheses.

# Table 4: Effect of Advisories Based on Speci es Selection on Estimated Hg Blood levels

Scenario Baseline No High Low Only Average 1.8 (1.7, 2.0) 1.8 (1.6, 2.0) 1.1 (1.0, 1.3) Perc 0.10 0.2 (0.2, 0.3) 0.2 (0.2, 0.3) 0.2 (0.1, 0.3) Perc 0.25 0.5 (0.4, 0.6) 0.5 (0.4, 0.6) 0.4 (0.3, 0.5) Median 1.1 (0.9, 1.2) 1.1 (0.9, 1.2) 0.7 (0.6, 0.8) Perc 0.75 2.2 (2.0, 2.5) 2.1 (1.9, 2.4) 1.3 (1.2, 1.5) Perc 0.90 4.2 (3.8, 4.8) 4.1 (3.6, 4.5) 2.5 (2.2, 2.8) Perc 0.95 6.0 (5.3, 6.8) 5.7 (5.0, 6.6) 3.5 (3.0, 4.0) Perc 0.99 10.6 (8.9, 13.8) 10.4 (8.5, 14.0) 6.1 (4.6, 8.3) Perc 0.995 13.1 (10.4, 17.5) 12.3 (9.9, 18.1) 7.5 (5.6, 10.9) Perc 0.999 18.7 (13.8, 31.4) 17.7 (12.8, 32.2) 10.4 (7.3, 19.6)

All units are μ g Hg/L in blood with uncertainty bounds expressed as 5 th 

## and 95 th 

## confidence limits in parentheses.Table 5: Effect of Advisories with Species and Consumption Limits on Estimated Hg Blood LevelsScenarioBaseline12 oz No High12 oz Variety12 or 6 Albacore12 or 6 Medium12 oz LowAverage1.8 (1.7, 2.0)1.6 (1.4, 1.7)1.6 (1.4, 1.7)1.5 (1.4, 1.7)1.5 (1.3, 1.6)1.1 (1.0, 1.2)Perc 0.100.2 (0.2, 0.3)0.2 (0.2, 0.3)0.2 (0.2, 0.3)0.2 (0.2, 0.3)0.2 (0.2, 0.3)0.2 (0.1, 0.3)Perc 0.250.5 (0.4, 0.6)0.5 (0.4, 0.6)0.5 (0.4, 0.6)0.5 (0.4, 0.6)0.5 (0.4, 0.6)0.4 (0.3, 0.5)Median1.1 (0.9, 1.2)1.0 (0.9, 1.2)1.0 (0.9, 1.2)1.0 (0.9, 1.2)1.1 (0.9, 1.2)0.7 (0.6, 0.9)Perc 0.752.2 (2.0, 2.5)2.1 (1.9, 2.4)2.1 (1.9, 2.4)2.1 (1.9, 2.4)2.1 (1.9, 2.4)1.4 (1.3, 1.6)Perc 0.904.2 (3.8, 4.8)3.7 (3.4, 4.1)3.7 (3.4, 4.2)3.7 (3.3, 4.0)3.5 (3.2, 3.7)2.5 (2.3, 2.8)Perc 0.956.0 (5.3, 6.8)4.8 (4.4, 5.1)4.7 (4.3, 5.2)4.6 (4.2, 4.9)4.2 (3.9, 4.5)3.2 (2.9, 3.5)Perc 0.9910.6 (8.9, 13.8)6.5 (6.0, 7.2)6.4 (5.8, 7.1)6.0 (5.6, 6.6)5.4 (5.1, 5.9)4.2 (3.8, 4.6)Perc 0.99513.1 (10.4, 17.5)7.3 (6.5, 8.2)7.1 (6.3, 7.8)6.6 (6.1, 7.4)5.9 (5.5, 6.6)4.6 (4.0, 5.3)Perc 0.99918.7 (13.8, 31.4)8.8 (7.7, 11.9)8.3 (7.2, 9.7)7.8 (6.9, 11.6)6.8 (6.1, 8.2)5.4 (4.5, 6.8)All units areμg Hg/L in blood with uncertainty bounds expressed as 5thand 95thconfidence limits in parentheses.