Estimating Longitudinal Aggregate and Cumulative Exposure and Intake Dose for Young ChildrenEPA Grant Number: R829362
Title: Estimating Longitudinal Aggregate and Cumulative Exposure and Intake Dose for Young Children
Investigators: Leckie, James O.
Institution: Stanford University
EPA Project Officer: Saint, Chris
Project Period: October 1, 2001 through September 30, 2004
Project Amount: $540,709
RFA: Aggregate Exposure Assessment for Pesticides: Longitudinal Case Studies (2001) RFA Text | Recipients Lists
Research Category: Pesticides , Health , Safer Chemicals , Health Effects
Description:The primary objective is to develop a model to quantify cumulative (multiple pesticides with the same toxicological end point) and aggregate (dermal, inhalation and ingestion routes) exposure and intake dose estimates for a population of children aged 1-6 years. Of considerable importance to this effort will be the use of our unique database for micro-level activity time series for children (over 60 children 1- 12 yr. of which 42 are 1-6 yr.). The new model will incorporate use of the detailed database to provide estimates of both macro-level and micro-level activities leading to exposure. Pesticides to be included in this project are: chlorpyrifos, chlorinated pesticides (DDT, DDE), synthetic pyrethrins.
Approach:Development of the new model will entail adding new algorithm modules to our existing Dermal Exposure Reduction Model (DERM) for the calculation of dietary ingestion exposure, inhalation exposure and intake dose across an three routes (aggregate) for multiple pesticides with similar toxicological end points (cumulative). Equations for the dermal and inhalation route will be posed to include multiple pathways (e.g., residue transfer from surfaces to skin, chemical transfer from soil matrix to skin, vapor deposition on skin, inhalation of gaseous chemicals, etc.) while using stochastic methods to select chemical residue concentrations from distributions (e.g., lognormal) for use in computed estimates of exposure and dose. Time line scenarios will be generated from the micro-level activity time series using transitional probabilities based on the details of the time sequenced microenvironments in the database. Finally, the bootstrap resampling tool will be used to provide for population estimates by resampling from the pool of exposure estimates for individuals using the time sequenced database.
Expected Results:The project products will include the integrated model capable of estimating time line scenarios for longitudinal exposure and dose estimates. The model will provide for estimates of: 1) exposure and dose across au routes; 2) exposure and dose, for multiple pesticides; 3) projected time scenarios (using transitional probabilities) used to estimate longitudinal exposures; 4) exposure with time dissipated chemical residues; 5) population statistics using bootstrap resampling methods; and 6) policy choice outcomes by simulating exposure scenarios for populations based on various residue limits and microenvironment restrictions.
Improvements in Risk Assessment:
The study will contribute to an improved understanding of the importance of an integrated approach to exposure assessment and provide useful inputs to health risk analysis for children.