On predicting multi-route and multimedia residential exposure to chlorpyrifos and diazinon

Abstract

This paper formulates regression models and examines their ability to associate exposures to chlorpyrifos and diazinon in residences with information obtained from questionnaires and environmental sampling of the National Human Exposure Assessment Survey Arizona (NHEXAS-AZ) database. A knowledge-based list of 29 potential exposure determinants was assembled from information obtained from six questionnaires administered in the course of the study. This list was used to select the independent variables of each model statistically and electronically. Depending on the data type of dependent and independent variables, four classes of regression models were developed to determine desired associations. Route-specific exposures were estimated using the indirect method of exposure estimation and measurements from the NHEXAS-AZ field study. The stepwise procedure was used to construct regression models. Significance level at P=0.10 was used for entry and retention of independent variables in a model. Twelve significant regression models were formulated to quantify associations among exposures and other variables in the NHEXAS-AZ database. Route-specific exposures to pesticides associate significantly with questionnaire-based variables such as preparation of pesticides, use of pesticide inside the house, and income level; and with concentration variables in three media: dermal wipe, sill wipe, and indoor air. Models formulated in this study may be used to estimate exposures to each of the pesticides. Yet, the use of these models must incorporate clear statements of the assumptions made in the formulation as well as the coefficient of determination and the confidence and prediction intervals of the dependent variable.