You are here:
Pesticides on Household Surfaces May Influence Dietary Intake of Children
Citation:
MELNYK, L. J., M. Z. Byron, G. Brown, A. Clayton, AND L. C. Michael. Pesticides on Household Surfaces May Influence Dietary Intake of Children. ENVIRONMENTAL SCIENCE AND TECHNOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, 45(10):4594-4601, (2011).
Impact/Purpose:
The overall goal of this research program is to identify those chemicals, pathways, and activities that represent the highest potential exposures to children and to determine the factors that influence these exposures. The following objectives will address this goal: Revise and refine the existing research plan for children's exposure measurements research. Collect measurement data on children's exposures. Provide analytical support to children's pesticide exposure research. Develop analytical methods for pesticides in duplicate diet food samples. Develop and apply analytical methods for other chemicals including but not limited to brominated diphenyl ethers, phthalates, perfluorinated chemicals. Evaluate the impact of chiral chemistry on the risk to children and exposure assessment. Provide support to the National Children's Study. Perform data analyses to fill critical data gaps. Conduct analyses of dietary samples and refine the dietary model for the dietary exposure algorithm.
Description:
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.
