Separation of risks and benefits of seafood intake

Abstract

Background: Fish and seafood provide important nutrients but may also contain toxic contaminants, such as methylmercury. Advisories against pollutants may therefore conflict with dietary recommendations. In resolving this conundrum, most epidemiologic studies provide little guidance because they address either nutrient benefits or mercury toxicity, not both.

Objectives: Impact on the same health outcomes by two exposures originating from the same food source provides a classical example of confounding. To explore the extent of this bias, we applied structural equation modeling to data from a prospective study of developmental methylmercury neurotoxicity in the Faroe Islands.

Results: Adjustment for the benefits conferred by maternal fish intake during pregnancy resulted in an increased effect of the prenatal methylmercury exposure, as compared with the unadjusted results. The dietary questionnaire response is likely to be an imprecise proxy for the transfer of seafood nutrients to the fetus, and this imprecision may bias the confounder-adjusted mercury effect estimate. We explored the magnitude of this bias in sensitivity analysis assuming a range of error variances. At realistic imprecision levels, mercury-associated deficits increased by up to 2-fold when compared with the unadjusted effects.

Conclusions: These results suggest that uncontrolled confounding from a beneficial parameter, and imprecision of this confounder, may cause substantial underestimation of the effects of a toxic exposure. The adverse effects of methylmercury exposure from fish and seafood are therefore likely to be underestimated by unadjusted results from observational studies, and the extent of this bias will be study dependent.

Figure 1

Path diagram for a structural equation model that links mercury exposure to adverse effects, while taking into account confounders, including fish intake. The exposure (Hg) is modeled as a latent parameter based on available exposure indicators, and the latent effect parameter [neurologic function (Neuro func)] is likewise based on clinical test outcomes. Each of the exposure indicators and clinical outcomes is associated with imprecision (ɛ).

Figure 2

Path diagram for a structural equation model that links mercury exposure to adverse effects, while taking into account confounders, including nutrient supply based on fish intake. The exposure (Hg) is modeled as a latent parameter based on available exposure indicators, and the latent effect parameter [neurologic function (Neuro func)] is likewise based on clinical test outcomes. Each of the exposure indicators and clinical outcomes is associated with imprecision (ɛ).