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

Wei Jen Chen, Candace Robledo, Erin M. Davis, Jean R. Goodman, Chao Xu, Jooyeon Hwang, Amanda E. Janitz, Tabitha Garwe, Antonia M. Calafat, Jennifer D. Peck

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

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.

Original languageEnglish
Article number113897
JournalEnvironmental Research
Volume214
DOIs
Publication statusPublished - Nov 2022
Externally publishedYes

Keywords

  • Benzophenone-3
  • Bisphenol A
  • Gestational diabetes
  • Mixtures
  • Paraben
  • Phenol

ASJC Scopus subject areas

  • Biochemistry
  • General Environmental Science

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