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Modeling Excess Dietary Exposure
Lisa Jo Melnyk1, Margie Zeller Byron2, Gordon Brown2, Andy Clayton2, and Larry C. Michael2
1 - US Environmental Protection Agency
National Exposure Research Laboratory
26 W. Martin Luther King Drive
Cincinnati, OH 45268 USA
2 – Research Triangle Institute, International
3040 Cornwallis Road
Research Triangle Park, NC 27707 USA
Assessment of total aggregate exposure necessitates consideration of the contribution and importance of the role of the dietary route. For young children, by virtue of their unique activity patterns, the diet may actually be the dominant contributor to overall exposure. Contaminated hands and surfaces are significant sources of exposure during eating, particularly for younger children where hand-to-food and hand-to-surface-to-food frequencies are relatively high. For these reasons, a model that accurately predicts children’s dietary intakes is essential.
The Children’s Dietary Intake Model (CDIM) was developed to enable prediction of total dietary intake of children. In addition to chemical exposure associated with the food itself, this model incorporates excess exposures due to handling of food during consumption. CDIM consists of three terms. Term 1 (residue of the contaminant consumed) is obtained through duplicate diet analysis or generated from residue and consumption information from available databases. Terms 2 (surface-to-food) and 3 (surface-to-hand-to-food) are generated from laboratory and field studies on transfer efficiencies and activity factors.
The overarching objective of this study was to develop distributions for each of eleven input parameters in CDIM using data from several field and laboratory studies. To meet this goal, Monte Carlo simulations were used to obtain dietary intake distributions for several pesticides and metals. Input variables were analyzed to identify which were most strongly influential in determining the final total dietary exposure.
The results from the development of each parameter were distributions of measured and estimated parameters. Surface and hand concentrations were readily available; transfers of contaminants between surface-to-hand and surface-to-food were better defined than activity factors; and proportions of foods that contacted surface areas were estimated, since no true data were known. Sensitivity analysis of the model parameters determined that the activity factors were most influential in the dietary intake of a contaminant. With these distributions for model inputs, CDIM has the potential to more accurately predict the total dietary intake of a contaminant by a child.
Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.