Although there is a body of research indicating the potential impact of polycyclic aromatic hydrocarbons (PAHs) exposure on male infertility, the understanding of how PAH might affect female infertility is still limited. This study aimed to evaluate associations of PAHs, both individually and as a mixture, with female infertility using multiple logistic regression, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC) models based on data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. The study included 729 female participants. Multiple logistic regression results indicated that there was a significant association between the third tertile of 2-hydroxy fluorene (2-OHFLU) and female infertility, and the OR was 2.84 (95% CI: 1.24-6.53, P value = 0.015) compared with the first tertile after adjusting for the potential covariates. The BKMR model revealed a positive overall trend between mixed PAH exposure and female infertility, particularly when the mixture was at or above the 55th percentile, where 2-hydroxynaphthalene (2-OHNAP) and 1-hydroxypyrene (1-OHPYR) were the primary influences of the mixture. The univariate exposure-response function indicated positive associations between individual PAH exposure, specifically 2-OHNAP, 2-OHFLU, and 1-OHPYR, and female infertility. The QGC model also indicated a positive trend between exposure to a mixture of PAHs and female infertility, although it did not reach statistical significance (OR = 1.33, 95%CI: 0.86-2.07), with 1-OHPYR having the greatest positive effect on the outcome. This study suggested that exposure to PAHs may be associated with female infertility and further research is needed to consolidate and confirm these findings.
Keywords: Association; Bayesian kernel machine regression (BKMR); Infertility; PAHs; Quantile g-computation (QGC).
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