Prenatal levels of organophosphorus pesticide (OPs) biomarkers have been associated with hallmarksymptoms of Attention Deficit Hyperactivity Disorder (ADHD) including deficits in working memory socialresponsiveness and ADHD indices. Cross-sectional studies have also linked concurrent pyrethroid pesticidemetabolites with ADHD and ADHD behaviors in children. Toxicology studies report mixture effects for thesepesticides on health outcomes. Three major gaps exist in this literature: 1) No studies have evaluatedprenatal and childhood exposures to these pesticides and clinical ADHD diagnoses. 2) Prenatalepidemiological studies of OPs/pyrethroids typically rely on urinary DAP biomarkers which reflect ingestion ofboth non-toxic metabolites and toxic parent pesticides. Urinary biomarkers from spot urine samples also donot characterize pregnancy-wide exposures since OPs and pyrethroids are rapidly metabolized. 3)Studies of pesticide mixtures in epidemiology are scarce and use of biomarkers for such mixtures analysis isproblematic. For instance administration of chlorpyrifos (an OP) results in increased tissue concentrations ofcypermethrin while reducing urinary excretion of the pyrethroid metabolite 3-phenoxbenzoic acid. Thus themixture itself may affect biomarker levels and increase exposure misclassification. A geospatial framework forpesticide exposure can address some of the limitations of urinary biomarkers: exposures from agriculturalpesticide applications can be estimated for an entire pregnancy rather than a few days; estimates reflect thetoxic parent pesticide rather than non-toxic OP metabolites; and estimates reflect actual exposures rather thana post-metabolism level. However geospatial (GIS) methods of pesticide exposure assessment forepidemiology in the US have only been done in California and usually rely on distance-to-field measures.GIS exposure may be enhanced with drift models that incorporate heat humidity inversions atmosphericstability and wind while external validity may be increased by studying a population outside of California.We propose to assess the relationship between OPs pyrethroids and ADHD in an Arizona population. Toidentify a study population we will apply a validated phenotyping algorithm with exceptional diagnostics toArizona Medicaid records to identify 4000 childhood ADHD cases and 16000 controls. In the mentored phasethe Candidate will develop geospatial phenotyping exposure assessment mixture modeling (Bayesian KernelMachine regression [BKMR]) and machine learning skills while constructing the case-control study. In the R00phase the Candidate will compare the drift model against traditional distance-to-field measures in a frequentistframework (Aim 2) and model associations between prenatal OP and pyrethroid pesticide mixtures and ADHDwith BKMR (Aim 3). These results will expand GIS studies beyond California contribute to sparse but criticalliterature on pesticide mixtures and neurodevelopment and be among the first to report associations betweenGIS estimates of prenatal pesticide exposures and ADHD case status.