An exposure model was developed to relate seafood consumption to levels of methylmercury (reported as mercury) in blood and hair in the U.S. population, and two subpopulations defined as children aged 2-5 and women aged 18-45. Seafood consumption was initially modeled using short-term (three-day) U.S.-consumption surveys that recorded the amount of fish eaten per meal. Since longer exposure periods include more eaters with a lower daily mean intake, the consumption distribution was adjusted by broadening the distribution to include more eaters and reducing the distribution mean to keep total population intake constant. The estimate for the total number of eaters was based on long-term purchase diaries. Levels of mercury in canned tuna, swordfish, and shark were based on FDA survey data. The distribution of mercury levels in other species was based on reported mean levels, with the frequency of consumption of each species based on market share. The shape distribution for the given mean was based on the range of variation encountered among shark, tuna, and swordfish. These distributions were integrated with a simulation that estimated average daily intake over a 360-day period, with 10,000 simulated individuals and 1,000 uncertainty iterations. The results of this simulation were then used as an input to a second simulation that modeled levels of mercury in blood and hair. The relationship between dietary intake and blood mercury in a population was modeled from data obtained from a 90-day study with controlled seafood intake. The relationship between blood and hair mercury in a population was modeled from data obtained from several sources. The biomarker simulation employed 2,000 simulated individuals and 1,000 uncertainty iterations. These results were then compared to the recent National Health and Nutrition Examination Survey (NHANES) that tabulated blood and hair mercury levels in a cross-section of the U.S. population. The output of the model and NHANES results were similar for both children and adult women, with predicted mercury biomarker concentrations within a factor of two or less of NHANES biomarker results. However, the model tended to underpredict blood levels for women and overpredict blood and hair levels for children.

Risks associated with toxicants in food are often controlled by exposure reduction. When exposure recommendations are developed for foods with both harmful and beneficial qualities, however, they must balance the associated risks and benefits to maximize public health. Although quantitative methods are commonly used to evaluate health risks, such methods have not been generally applied to evaluating the health benefits associated with environmental exposures. A quantitative method for risk-benefit analysis is presented that allows for consideration of diverse health endpoints that differ in their impact (i.e., duration and severity) using dose-response modeling weighted by quality-adjusted life years saved. To demonstrate the usefulness of this method, the risks and benefits of fish consumption are evaluated using a single health risk and health benefit endpoint. Benefits are defined as the decrease in myocardial infarction mortality resulting from fish consumption, and risks are defined as the increase in neurodevelopmental delay (i.e., talking) resulting from prenatal methylmercury exposure. Fish consumption rates are based on information from Washington State. Using the proposed framework, the net health impact of eating fish is estimated in either a whole population or a population consisting of women of childbearing age and their children. It is demonstrated that across a range of fish methylmercury concentrations (0-1 ppm) and intake levels (0-25 g/day), individuals would have to weight the neurodevelopmental effects 6 times more (in the whole population) or 250 times less (among women of child-bearing age and their children) than the myocardial infarction benefits in order to be ambivalent about whether or not to consume fish. These methods can be generalized to evaluate the merits of other public health and risk management programs that involve trade-offs between risks and benefits.

Quantitative risk analysis permits modifying risk estimates with changes in variables such as exposure. This analysis for exposure to the mycotoxin fumonism describes the magnitude of adverse effects, variability in the population and uncertainty of models as a range of possible outcomes. The most sensitive adverse response in rats, nephrotoxic lesions, was used for the dose-response analysis. Dietary intake of corn products was estimated from a 3-day consumption survey. Levels of corn in each product were estimated by standard methods. Fumonisin levels in corn products were estimated from Food and Drug Administration (FDA) surveillance data and distributions of fumonisin consumption were modelled for each eater in the survey population. Uncertainty for predictions made from each model and uncertainty resulting from model selection were described. Results of the dose-response and exposure analyses were assimilated in a two-dimensional Monte-Carlo simulation. Distributions representing variability and uncertainty were iteratively selected to form an array of estimates of the risk. On the basis of this analysis, current dietary levels of fumonisin would not result in renal lesions even at upper levels of exposure. To avoid toxicity at much higher doses, limiting corn intake would be more effective than would limiting the level of fumonisin in corn.

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