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8291836 Improved pesticide exposure assessment in a Norwegian agricultural cohort: integrating exposure from applications, re-entry tasks and livestock production

oemed · 2025-10-06 · canonical JSON source

3 visible annotations · policy: published · automated confidence ≥ 75.00%

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Introduction Accurate retrospective pesticide exposure assessment is essential in agricultural epidemiology, particularly when investigating diseases with long latency such as cancer. In the Cancer in the Norwegian Agricultural Population (CNAP) cohort, previous assessments assumed uniform pesticide use for all registered active ingredients (AIs) across crops and over registration years. We aimed to refine assessment for selected active ingredients (AIs) by adding probability, frequency and intensity, and incorporating exposure from applications, re-entry and livestock production.Methods We constructed an exposure algorithm informed by pesticide registration data, sales records (1967–2022), and expert input. Sales records and expert input informed the calculation of use probabilities when multiple AIs were registered per crop. Experts also provided historical and cultural insights on division of application and re-entry tasks by gender.Result For crop application, we estimated AI-, crop-, and year-specific use probabilities, combined with application frequency and formulation dose data to assign annual and cumulative applicator exposure for male farmers. Re-entry exposure was assigned to farm holders and spouses cultivating orchard or greenhouse crops, accounting for AI-specific dissipation rates and crop-specific contamination factors. Livestock-related exposure was estimated using veterinary insecticide sales data, weighted by livestock type and herd size, and assigned to individuals reporting livestock production. The algorithms produced harmonized, AI-specific cumulative exposure estimates for over 245,000 Norwegian farm holders and spouses. Incorporation of re-entry exposure revealed frequent pesticide contact among female farmworkers. The livestock exposure matrix provided additional exposure differentiation for selected insecticides used in livestock farming.Conclusion We created comprehensive exposure assessment algorithms for CNAP that improve specificity, reduce misclassification, and strengthen ongoing harmonized analyses of cancer risks within an international consortium of agricultural cohorts.