Purpose: Women living or working on farms may be exposed to pesticides from direct occupational use of agricultural pesticides and from non-occupational pathways, such as take-home exposure from skin, clothes and shoes of farmworkers, drift from nearby fields, and pest treatments in the home/yard. Failure to account for non-occupational pathways may underestimate total exposure, increase exposure misclassification and reduce power to detect associations in epidemiologic analyses, particularly for women who have less occupational pesticide contact than men. We developed an active-ingredient-specific algorithm for cumulative, non-occupational pesticide exposure for female spouses of pesticide applicators in the Agricultural Health Study (AHS) that quantified exposure intensity from four pathways: bystander, take-home, agricultural drift, and residential pesticide use. Methods: We used exposure data from previous meta-analyses to develop pathway weights. We used spouse and applicator responses to questions on pesticide use, farm characteristics, and other activities to identify subject-specific contrasts in pesticide exposure intensity. Results: In our algorithm, bystander exposure was a function of time a spouse spent working in fields, take-home exposure was a function of time a spouse spent at home, and both were proportional to days and years the applicator applied an active ingredient. Exposure from agricultural drift was a function of distance between homes and treated fields and days and years the applicator applied the active ingredient. Residential pesticide exposure was a function of the combined contribution of years of multiple home pest treatments, accounting for the probability the active ingredient was used in specific treatments. Conclusion: This transparent, data-driven algorithm of cumulative, aggregate pesticide exposure intensity will facilitate etiologic analyses of health effects in the AHS and could be applied to studies with similar information.
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