Pesticides on household surfaces may influence dietary intake of children.

Environ Sci Technol

U.S. Environmental Protection Agency Office of Research and Development National Exposure Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, USA.

Published: May 2011

AI Article Synopsis

  • The environment around children, including physical and chemical factors, impacts their exposure to pesticides, particularly during eating.
  • The Children's Dietary Intake Model (CDIM) assesses these exposures by considering not only the food but also the ways children handle food while eating.
  • Using Monte Carlo simulations, researchers evaluated various factors affecting pesticide intake and found that pesticide surface concentration was the most significant contributor, followed by transfer efficiencies and pesticide residues in food.

Article Abstract

The physical and chemical environment influences children's exposures to pesticides in and around the home. Children's activities, which increase their potential for exposure especially during eating, have been captured in the Children's Dietary Intake Model (CDIM). In addition to the chemical exposure associated with the food itself, this model incorporates excess dietary exposures due to handling of food during consumption. To stochastically evaluate CDIM, distributions of measured, and in some cases estimated, model factors were determined from measurements of permethrin, chlorpyrifos, and diazinon derived from assembled databases and laboratory experiments. Using the distributions of these factors, Monte Carlo simulations were performed to obtain distributions of total dietary intake of pesticides. To target the sources of pesticide contamination that were influencing total dietary intake, each factor was evaluated. We found pesticide surface concentration to be highly influential. By excluding surface concentration, we were also able to determine the influence of the other factors based on the F-statistic. Transfer efficiencies, followed by pesticide residue in consumed foods and amount of food consumed, were the next most influential factors within the model. With these distributions for model inputs, CDIM has the potential to more accurately predict total dietary intake of a contaminant by a child.

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Source
http://dx.doi.org/10.1021/es104190kDOI Listing

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