Methyl mercury exposure from fish consumption in vulnerable racial/ethnic populations: Probabilistic SHEDS-Dietary model analyses using 1999–2006 NHANES and 1990–2002 TDS data
Author:
Jianping Xue, Valerie G. Zartarian, Shi V. Liu, and Andrew M. Geller
Date Published:
1/2012
Description:
NHANES subjects self-identified as “Asian, Pacific Islander, Native American, or multiracial” (A/P/N/M) have higher levels of blood organic mercury than other racial/ethnic groups; however, the reasons for this have been unclear. This research uses exposure modeling to determine the reasons for elevated blood methylmercury (MeHg) levels, and also extends previous analyses of observed NHANES blood levels. The probabilistic SHEDS-Dietary model was applied, using MeHg fish residue data from FDA's Total Diet Study (1990–2002) combined with NHANES/WWEIA (1999–2006) fish consumption data, to generate exposure estimates by race/ethnicity, age group, and fish type. Statistical analyses of blood methylmercury levels in the (6 times larger) 1999–2006 NHANES data were compared against previous published results for 1999–2002 data.
The A/P/N/M group has higher fish intake, modeled MeHg exposures, and blood levels than the general population and other racial/ethnic groups. Tuna, other saltwater fish, and other freshwater fish are key food types driving dietary MeHg exposure. The 1–< 3 years-old A/P/N/M group has the highest mean dietary MeHg intake per body weight (0.06 μg/kg/day; ~ 2.3 times higher than the rest of the population). Fish intake and modeled exposure predictions correlate well with NHANES blood biomarker levels. This study, using the SHEDS-Dietary model with national data, reinforces and expands upon previous observations that dietary exposure via fish consumption is an important route for methylmercury intake by the general population, and especially for racial/ethnic groups with higher fish consumption. These probabilistic dietary modeling approaches could be applied for local populations (e.g., tribes) and other chemicals and foods, if data are available.
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