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Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples.
Citation:
Michael, L., G. Brown, AND L. Melnyk. Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples. Journal of Environmental Science and Health. Part B, Pesticides, Food Contaminants, and Agricultural Wastes. Marcel Dekker Incorporated, New York, NY, 51(11):751, (2016).
Impact/Purpose:
The research presented in the journal article will improve community's ability to determine exposures through the dietary route with a less burdensome and costly method.
Description:
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation of pesticide intakes for a defined demographic community, and (2) comparison of dietary pesticide intakes between the composite and individual samples. Extant databases were useful for assigning individual samples to composites, but they could not provide the breadth of information needed to facilitate measurable levels in every composite. Composite sample measurements were found to be good predictors of pyrethroid pesticide levels in their individual sample constituents where sufficient measurements are available above the method detection limit. Statistical inference shows little evidence of differences between individual and composite measurements and suggests that regression modeling of food groups based on composite dietary samples may provide an effective tool for estimating dietary pesticide intake for a defined population.
