Assessing health risk posed by chemical contaminants in the environment requires the integration of data from two distinct disciplines: toxicology and exposure assessment. Methodology for exposure assessment has undergone rapid development over the last decade, particularly in the area of exposure modeling. Software tools now provide the computational power to conduct probabilistic exposure assessments, which explicitly incorporate variability in data for key determinants of exposure (e.g. variability in rate of contact with media containing a contaminant, variability in contaminant concentration). Thus, probabilistic analyses generate, for a specified population, distributions of exposure estimates (external dose estimates) that reflect the full range of potential exposure levels and their probabilities. Regulatory agencies have used probabilistic exposure modeling to assess risk from exposure to a variety of environmental toxicants. Such agencies are now examining probabilistic methods for occupational exposure assessment, specifically, worker exposure to agricultural pesticides. A number of scientific and statistical questions are raised, however, when probabilistic methods are applied in a novel way. To address these questions, ILSI RSI convened a Working Group with experts from diverse disciplines (occupational exposure assessment, dermal absorption assessment, probabilistic modeling, and statistics). This poster will present the Working Group's findings regarding: 1) developing model input distributions to characterize exposure to agricultural pesticides; 2) incorporating absorbed dose in a probabilistic assessment; 3) conducting a 2-dimensional assessment, which separates variability and uncertainty; and 4) interpreting and communicating results of a probabilistic worker exposure assessment.
The Toxicologist. Society of Toxicology 43nd Annual Meeting and ToxExpo, March 21-25, 2004, Baltimore, Maryland