Association between Perfluoroalkyl and Polyfluoroalkyl Substances and Women's Infertility, NHANES 2013-2016

Association between polycyclic aromatic hydrocarbons and infertility in U.S. women: National Health and Nutrition Examination Survey 2013-2016

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.

Association of per- and polyfluoroalkyl substance exposure with metabolic syndrome and its components in adults and adolescents

Per- and polyfluoroalkyl substances (PFAS) are widespread contaminants, but few studies have explored the relationship between PFAS and levels of metabolic syndrome (MetS) in the population. The available evidence of an association is also conflicting. We selected adults and adolescents with complete PFAS data from the National Health and Nutrition Examination Survey conducted between 2003 and 2018. We analyzed the association between PFAS and MetS using multivariate logistic regression models and evaluated potential nonlinear relationships with restricted cubic spline models. Additionally, we employed weighted quantile sum (WQS) regressions to uncover the multiple exposure effects and relative weights of each PFAS. Finally, we conducted a series of sensitivity analyses to test the robustness of our findings. In this population-based study, we analyzed data from a total of 4,973 adults, aged 20-85 years, and 1,381 adolescents, aged 12-19 years. Using fully adjusted multivariate logistic regression models, we found that serum levels of perfluorodecanoate (PFDA) [0.65 (0.50, 0.85)] and total PFAS [0.92 (0.85, 0.99)] were negatively associated with the prevalence of MetS in adults. Similarly, in adolescents, we observed negative correlations between the prevalence of MetS and levels of PFDA [0.55 (0.38, 0.80)], perfluorooctanoic acid (PFOA) [0.62 (0.39, 1.00)], perfluorooctane sulfonic acid (PFOS) [0.59 (0.36, 0.96)], and total PFAS [0.61 (0.37, 0.99)]. Additionally, our study identified statistically significant negative associations between serum levels of PFAS and certain components of MetS, primarily elevated fasting glucose and lower high-density lipoprotein cholesterol. Our study found that PFAS was associated with a lower prevalence of MetS in both adults and adolescents, offering new insights into the relationship between PFAS and metabolic health. Interestingly, however, we observed conflicting findings across the components of MetS. Specifically, we observed that PFAS had a negative correlation with some metrics and a positive correlation with others. These conflicting results point to a complex interplay between PFAS and various metrics of metabolic health.

Relationship between sleep disorders and female infertility among US reproductive-aged women

PURPOSE

Sleep disorders are a risk factor for a wide variety of dysfunctions of endocrine, metabolic, cardiovascular, and neurological diseases. However, the risk of sleep disorders to female infertility has not been thoroughly explored. Our study aimed to examine whether or not sleep disorders increase the risk of female infertility.

METHODS

Cross-sectional data on sleep disorders and fertility history were obtained from the National Health and Nutrition Examination Survey 2013-2018. Women aged 20 to 40 years old were enrolled in our study. Weighted multivariable logistic regression models and stratified analysis by age, smokers, and patient health questionnaire-9 (PHQ-9) score were conducted to estimate the effect of sleep disorders on female infertility.

RESULT

Among 1820 reproductive-age females, 248 individuals had infertility and 430 individuals had sleep disorders. Two weighted logistic regression models found that sleep disorders were an independent risk factor for infertility. After adjusting for the covariates (age, race/ethnicity, marital status, education level, poverty income ratio, body mass index (BMI), waist circumference, PHQ-9 score, smokers, drinkers, and sleeping hours), the risk of infertility was 2.14-fold higher in individuals with sleep disorders than in those without. The further stratified analysis demonstrated that the relationship between sleep disorders and infertility was maintained and that the risk was higher particularly in infertile women aged 40-44 years, with PHQ-9 score greater than 10, and smokers.

CONCLUSION

A strong association was found between sleep disorders and female infertility, and the association remained after adjusting for other confounding factors.