An Intervention Analysis for the Reduction 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 used (Risk Analysis 22:689-699, 2002) to assess 

the effectiveness of various advisory scenarios on minimizing mercury (Hg) blood levels via the 

consumption of commercial seafood, both finfish 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 that 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 confirmed 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, elimination of the consumption of certain species 

altogether, and/or a combination of both. In the baseline model, the median (uncertainty) 

estimates for the 50th, 95th, and 99th per capita population percentiles were 1.25, 8.2, and 16.1 ppb 

blood Hg, respectively. After restriction of seafood consumption to no more than 12 oz per 

week, the median (uncertainty) estimates for the 50th, 95th, and 99th per capita population 

percentiles were 1.22, 6.8, and 10.6 ppb blood Hg, respectively. Elimination of MeHg species, 

with average concentrations above 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 reduce MeHg exposure by reducing the amount of fish consumed (e.g., 

12 oz/week) are more effective at eliminating the high end of the exposure distribution than are 

strategies intended to change the types of fish consumed. 
Introduction 

Methylmercury (MeHg) is a well known environmental toxicant found in the aquatic ecosystem. 

Inorganic mercury originates from anthropogenic and natural sources. Once in the ecosystem 

inorganic mercury is converted to methylmercury primarily through bacterial 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 symptoms, 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 exposure 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 associated 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 week. In order to better understand and define 

what a variety of fish means a series of exposure assessments of various fish consumption 

scenarios were performed that were constructed to be consistent with the 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), Reference Dose (USEPA, 2001)) were used as 

measures of the effectiveness of the consumption/exposure scenarios in keeping weekly MeHg 

exposures of women who followed the specific advise scenario below 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 distributions were developed was expanded from 24 

to 42. (see Table 1). Tuna was broken into three categories, corresponding to 1) light canned 

tuna, 2) albacore canned tuna, and 3) fresh/frozen tuna steaks. 

• Mercury concentration data was obtained for additional 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 portions of the cumulative distribution above the 

levels of detection. A battery of ten distributions 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 description of the methodology). 

• A range of 0.1 to 0.2 ppb was added to blood Hg levels in order to represent contributions 

from sources other than fish. This range reflected the levels at the low end of the National 

Health and Nutrition Examination 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, this suggests that there are contributions 

to blood Hg levels from other sources (e.g., dental amalgams) other than seafood. Since the 

present model is intended to represent methylmercury exposure, a range with an uncertainty 

bound including zero was introduced to acknowledge the possibility of minor exposures from 

sources other than seafood. 

• A correction factor (listed in Table 1) was applied to reflect 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 broiled seafood (EPA, 2000). Group-specific 

correction factors were calculated based on the frequency of use of different food preparation 

(e.g. baking, steaming, or frying) within each group, based on the CSFII survey (USDA, 

1998). A default value of 0.8 was used for categories not represented in the CSFII survey. 

These are listed in Table 1. No correction factors were applied for canned-tuna since the 

MeHg concentration values, expressed as total Hg, were obtained after 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 consumers was also changed from 

70-90% to 85 to 95% in order to be consistent with the NHANES survey. 

• The fraction of the annual seafood diet estimated from the individual dietary survey, as 

opposed to market share, was treated as an individual 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 was used to represent range of individual repetitiveness (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 the 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 developed 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 seafood 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 the 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 swordfish) are replaced with Low Hg fish. For the purposes of 

calculating the 12 oz limit, seafood portions 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 consumed 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 model were compared to survey mercury blood 

values from the NHANES survey population between 1999 and 2000 (see Figure 4). The values 

are in very close agreement. 
Intervention Scenarios 

The impact of various consumer advisories on mercury blood levels is presented 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 mercury 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 99th percentile), more aggressive 

limits reduce exposure for a greater range of consumers and provide a greater reduction at the 

tail. 

Advisories Concerning Specific Species 

Table 4 shows the expected reduction in mercury blood levels following the elimination of 

certain species, with either particularly high mercury levels or any species with above average 

mercury levels. Although the reductions on mercury exposure are not as dramatic, the reductions 

in exposure may be noted across the entire distribution. 

Advisories Combining Limits on Amount and Species 

Table 5 shows the expected reduction in blood mercury 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 consumption of high methylmercury species and limiting 

seafood consumption to no more than 12 oz per week will eliminate the 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 greater reductions across the 

entire distributions of blood mercury values, but only provide minor, further (in comparison with 

advisories that only limit the amount of fish consumed) reductions in those consumers with the 

highest levels of exposure. 

Conclusions 

The purpose of this analysis was to assess the impact of a variety of fish consumption advisory 

scenarios on modeled distributions of blood mercury levels in a population of women of childbearing age. This population group was identified to be the subpopulation group of greatest 

concern because of MeHg induced fetal effects (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 was revised in a number of ways. 

The most significant adjustments were 1) incorporating additional data on mercury levels in 

seafood, 2) adjusting for water loss during food preparation, and 3) revising the population 
distributions for frequency of seafood consumption. As a result of these changes, the model 

results are in much closer agreement with NHANES survey data for mercury in blood. While 

this does not prove beyond any possible doubt that the model is entirely correct in every respect, 

the comparison does indicate that the results of the model are plausible. 

In general, reducing overall fish consumption appears to have more impact on the overall 

population distributions than reducing or eliminating 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 scenarios do indicate that curtailing consumption of 

high level fish can reduce the number of individuals with unusually high blood levels. 

Comparison of the scenario distributions with various safety standards (see Figure 5) indicates 

that a scenario (12 oz of low Hg fish only) may be devised to reduce the blood Hg levels of the 

entire population of women aged 16 to 49 years 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 zero risk, since it can never be established that some imperceptible 

effect does not occur with a given dose. Second, at the tails of the population distributions, there 

are likely to be some (albeit different) fraction of the total population above 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 information 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 mercury risks to other costs 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 Probability and Risk Assessment. Human Ecology Risk 

Assessment 2:62-78. 

Carrington, C.D. and Bolger, P.M. (2000). A Pooled 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/pcs/jecfa/Summary61.pdf. 

National Marine Fisheries Service (1978) National Marine Fisheries Service Survey of Trace 

Elements in the Fishery Resource. NOAA Technical Report NMFS SSRF-721. 

National Marine Fisheries Service/Office of Science 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 National Academy of Sciences (2000). Toxicological 

Effects of Methylmercury, National Academy Press, Washington, D.C. 

Schober, S., Sinks, T., Jones, R., Bolger, P., McDowell, 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 Disease Registry (USATSDR) (1999). Toxicological 

Profile of Mercury. http://www.atsdr.cdc.gov/toxprofiles/tp46.html. 

U.S. Department of Agriculture, Agricultural Research Service (USUSDA) (1998). 1989-91 

Continuing Survey of Food Intakes 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 Resources of the Gulf of Mexico" Report. 

http://mo.cr.usgs.gov/gmp/hg.cfm. 

U. S. Environmental Protection Agency (USEPA) (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) (2004). 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 distribution. 10 different distributions were fit to the sample Hg data for 

Crabs. The four best models were used to create a probability tree that describes the frequency 

distribution with a representation of model uncertainty. 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/day

Cumulative Frequency

CSFII Based Projection

30 Day NHANES

The CSFII based projection employed the exponential function described in Carrington and 

Bolger (2002b), using values of 0.696 and 0.356 for the alpha and beta parameters, respectively. 

These parameters were obtained by fitting the projected 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 Frequency

Cumulative 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 Outcomes to Various Safety Standards 

0.7

0.75

0.8

0.85

0.9

0.95

1

1 10 100

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 medium 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 Health Organization-Joint Expert Committee on Food Additives 

Provisional Tolerable Weekly Intake. RfD Equivalent – steady state 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 Source2 MARKET3

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 Fishery 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 

Share1

Mean Hg 

(ppm) 

Distribution 

Type2

Concentration 

Factor3

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 concentration by the correction factor. No correction factor was 

applied for canned tuna, since the mercury measurements were made after cooking. . 
Table 3: Effect of Advisories Based on Seafood Consumption 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 μg Hg/L in blood with uncertainty bounds expressed as 5th and 95th confidence limits in parentheses. 
Table 4: Effect of Advisories Based on Species 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 μg Hg/L in blood with uncertainty bounds expressed as 5th and 95th confidence limits in parentheses. 
Table 5: Effect of Advisories with Species and Consumption Limits on Estimated Hg Blood Levels 

Scenario Baseline 12 oz No High 12 oz Variety 12 or 6 Albacore 12 or 6 Medium Average 1.8 (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) 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) 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) 0.5 (0.4, 0.6) Median 1.1 (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) Perc 0.75 2.2 (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) Perc 0.90 4.2 (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) Perc 0.95 6.0 (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) Perc 0.99 10.6 (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) Perc 0.995 13.1 (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) Perc 0.999 18.7 (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) All units are 

μg Hg/L in blood with uncertainty bounds expressed as 5th and 95th confidence limits in parentheses.