Abstract
An algorithm developed to estimate pesticide exposure intensity for use in epidemiologic analyses was revised based on data from two exposure monitoring studies. In the first study, we estimated relative exposure intensity based on the results of measurements taken during the application of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) (n = 88) and the insecticide chlorpyrifos (n = 17). Modifications to the algorithm weighting factors were based on geometric means (GM) of post-application urine concentrations for applicators grouped by application method and use of chemically-resistant (CR) gloves. Measurement data from a second study were also used to evaluate relative exposure levels associated with airblast as compared to hand spray application methods. Algorithm modifications included an increase in the exposure reduction factor for use of CR gloves from 40% to 60%, an increase in the application method weight for boom spray relative to in-furrow and for air blast relative to hand spray, and a decrease in the weight for mixing relative to the new weights assigned for application methods. The weighting factors for the revised algorithm now incorporate exposure measurements taken on Agricultural Health Study (AHS) participants for the application methods and personal protective equipment (PPE) commonly reported by study participants.
Highlights
The risk of adverse health effects associated with long-term exposure to pesticides is difficult to assess in epidemiologic studies due to various limitations that have been summarized in the literature [1]
CR glove use was associated with a significant difference in urinary 2,4-D geometric means (GM) levels overall, when controlling for application method (p < 0.0001)
Among 2,4-D applicators who wore CR gloves, GMs of the post-application urine concentrations were 75% and 72% lower for boom (14 μg/L vs. 55 μg/L)
Summary
The risk of adverse health effects associated with long-term exposure to pesticides is difficult to assess in epidemiologic studies due to various limitations that have been summarized in the literature [1]. The field monitoring results, in general, confirmed the underlying premise of the algorithm; i.e., that algorithm scores based primarily on application method and the use of personal protective equipment can be used to identify applicators most likely to have encountered higher pesticide exposure levels, and thereby serve as an effective surrogate for exposure intensity. Measurement results from the AHS field studies were used to examine relative differences in urinary biomarker concentrations associated with the algorithm exposure variables These comparisons enabled us to modify the algorithm weights using AHS-derived field study data while still relying on information from the literature and PHED for algorithm weights, where AHS-specific field data was lacking. We re-scaled the algorithm scores and assigned weights for application methods reported by cohort members in followup questionnaires but not in the enrollment questionnaire These enhanced algorithm weights provide the basis for updated exposure intensity scores currently used in AHS epidemiological analyses
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