Background: Endocrine-disrupting chemicals (EDCs) such as organophosphate (OP) and pyrethroid (PYR) pesticides, affect human reproductive health. Investigating “real-life” environmentally relevant concentrations and mixtures of EDCs is important to identify potential interactions between highly correlated environmental exposures and reproductive health outcomes.
Objectives: This study investigated the effects of combined environmental exposures to OP and PYR pesticides and their association with the frequency of sperm chromosomal abnormalities (disomy) among adult men. We evaluated the hypothesis that pesticide mixtures, specifically OP and PYR interactions, alter associations of sperm chromosomal abnormalities.
Methods: One hundred fifty-nine men originating from a parent study of couples seeking infertility evaluation were evaluated. Fluorescence in situ hybridization was used for chromosomes X, Y, and 18 to determine disomy in sperm nuclei. Urine was analyzed for concentrations of PYR metabolite [3-phenoxybenzoic acid (3PBA)] using high-performance liquid chromatography. Gas chromatography coupled with mass spectrometry was used to analyze urinary concentrations of dialkyl phosphate (DAP) metabolites of OPs. Poisson regression models were used to calculate incidence rate ratios for each disomy type by exposure quartile of OP and PYR pesticides, controlling for potential confounders. Interactions between each DAP metabolite and 3PBA and associations with each disomy outcome were examined.
Results: Significant interactions were found between DAP metabolites and 3PBA for all disomy outcomes. Most of the associations showed increased disomy rates, higher than the values previously reported for each individual chemical class, by levels of specific DAP metabolites and 3PBA exposure. Increase in disomy rates occurred mainly between the second and third exposure quartiles and without substantial additional increases between the third and fourth exposure quartile, producing non-linear dose responses. Nonmonotonic patterns were observed in depicted graphs (displaying bell-shaped profiles). Significant inverse and positive parameter estimates were seen across all DAP metabolites by 3PBA quartiles.
Conclusions: This study demonstrates the methodological problems posed when evaluating environmental chemical mixtures, particularly when the health outcome is a count that is best suited for non-logistic modeling, such as Poisson regression. Consistent interactions were observed between OP and PYR pesticides, which strengthened the associations seen beyond the main effects of each individual exposure. Methods specific to investigating interactions in Poisson models are needed to determine an optimized approach for evaluating pesticide mixtures (with different EDC modes of action) and their effects on count based outcomes