Assessing urinary phenol and paraben mixtures in pregnant women with and without gestational diabetes mellitus: A case-control study

Abstract

Prior studies have identified the associations between environmental phenol and paraben exposures and increased risk of gestational diabetes mellitus (GDM), but no study addressed these exposures as mixtures. As methods have emerged to better assess exposures to multiple chemicals, our study aimed to apply Bayesian kernel machine regression (BKMR) to evaluate the association between phenol and paraben mixtures and GDM. This study included 64 GDM cases and 237 obstetric patient controls from the University of Oklahoma Medical Center. Mid-pregnancy spot urine samples were collected to quantify concentrations of bisphenol A (BPA), benzophenone-3, triclosan, 2,4-dichlorophenol, 2,5-dichlorophenol, butylparaben, methylparaben, and propylparaben. Multivariable logistic regression was used to evaluate the associations between individual chemical biomarkers and GDM while controlling for confounding. We used probit implementation of BKMR with hierarchical variable selection to estimate the mean difference in GDM probability for each component of the phenol and paraben mixtures while controlling for the correlation among the chemical biomarkers. When analyzing individual chemicals using logistic regression, benzophenone-3 was positively associated with GDM [adjusted odds ratio (aOR) per interquartile range (IQR) = 1.54, 95% confidence interval (CI) 1.15, 2.08], while BPA was negatively associated with GDM (aOR 0.61, 95% CI 0.37, 0.99). In probit-BKMR analysis, an increase in z-score transformed log urinary concentrations of benzophenone-3 from the 10th to 90th percentile was associated with an increase in the estimated difference in the probability of GDM (0.67, 95% Credible Interval 0.04, 1.30), holding other chemicals fixed at their medians. No associations were identified between other chemical biomarkers and GDM in the BKMR analyses. We observed that the association of BPA and GDM was attenuated when accounting for correlated phenols and parabens, suggesting the importance of addressing chemical mixtures in perinatal environmental exposure studies. Additional prospective investigations will increase the understanding of the relationship between benzophenone-3 exposure and GDM development.

Keywords: Benzophenone-3; Bisphenol A; Gestational diabetes; Mixtures; Paraben; Phenol.

Figure 1.. The estimated single exposure-response functions and 95% CrI for each phenol and paraben when all other phenols and parabens were fixed at their median levels.

The probit-BKMR model was adjusted for specific gravity, age, race/ethnicity, education level, pre-pregnancy BMI, and history of GDM.

Figure 2.. The estimated effect and 95% CrI of each phenol and paraben on GDM when each phenol and paraben was increased from the 10th to the 90th percentile of its distribution while other phenols and parabens were fixed to their 25th, 50th, or 75th percentile.

The probit-BKMR model was adjusted for specific gravity, age, race/ethnicity, education level, pre-pregnancy BMI, and history of GDM.