Literature DB >> 35839910

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

Wei-Jen Chen1, Candace Robledo2, Erin M Davis3, Jean R Goodman4, Chao Xu5, Jooyeon Hwang6, Amanda E Janitz5, Tabitha Garwe5, Antonia M Calafat7, Jennifer D Peck5.   

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.
Copyright © 2022 Elsevier Inc. All rights reserved.

Entities:  

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

Mesh:

Substances:

Year:  2022        PMID: 35839910      PMCID: PMC9514543          DOI: 10.1016/j.envres.2022.113897

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   8.431


  62 in total

Review 1.  12. Management of Diabetes in Pregnancy.

Authors: 
Journal:  Diabetes Care       Date:  2016-01       Impact factor: 19.112

2.  Association between urinary parabens and gestational diabetes mellitus across prepregnancy body mass index categories.

Authors:  Ying Li; Shunqing Xu; Yuanyuan Li; Bin Zhang; Wenqian Huo; Yingshuang Zhu; Yanjian Wan; Tongzhang Zheng; Aifen Zhou; Zhong Chen; Zheng Huang; Jie Hu; Wenxin Zhang; Xianliang Wang; Dan Ye; Wei Xia
Journal:  Environ Res       Date:  2018-12-15       Impact factor: 6.498

Review 3.  Oxidative stress, insulin resistance, dyslipidemia and type 2 diabetes mellitus.

Authors:  Surapon Tangvarasittichai
Journal:  World J Diabetes       Date:  2015-04-15

Review 4.  Endocrine Disruptors: A Potential Risk Factor for Gestational Diabetes Mellitus.

Authors:  Shelley Ehrlich; Donna Lambers; Andrea Baccarelli; Jane Khoury; Maurizio Macaluso; Shuk-Mei Ho
Journal:  Am J Perinatol       Date:  2016-08-04       Impact factor: 1.862

5.  Consumer behavior and exposure to parabens, bisphenols, triclosan, dichlorophenols, and benzophenone-3: Results from a crowdsourced biomonitoring study.

Authors:  Robin E Dodson; Katherine E Boronow; Herbert Susmann; Julia O Udesky; Kathryn M Rodgers; David Weller; Million Woudneh; Julia Green Brody; Ruthann A Rudel
Journal:  Int J Hyg Environ Health       Date:  2020-09-30       Impact factor: 5.840

6.  Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

Authors:  Jennifer F Bobb; Linda Valeri; Birgit Claus Henn; David C Christiani; Robert O Wright; Maitreyi Mazumdar; John J Godleski; Brent A Coull
Journal:  Biostatistics       Date:  2014-12-22       Impact factor: 5.279

7.  The estrogenic effect of bisphenol A disrupts pancreatic beta-cell function in vivo and induces insulin resistance.

Authors:  Paloma Alonso-Magdalena; Sumiko Morimoto; Cristina Ripoll; Esther Fuentes; Angel Nadal
Journal:  Environ Health Perspect       Date:  2006-01       Impact factor: 9.031

8.  Maternal urinary triclosan level, gestational diabetes mellitus and birth weight in Chinese women.

Authors:  Fengxiu Ouyang; Ning Tang; Hui-Juan Zhang; Xia Wang; Shasha Zhao; Weiye Wang; Jun Zhang; Weiwei Cheng
Journal:  Sci Total Environ       Date:  2018-02-19       Impact factor: 7.963

9.  Perinatal urinary benzophenone-3 concentrations and glucose levels among women from a fertility clinic.

Authors:  Zifan Wang; Lidia Mínguez-Alarcón; Paige L Williams; Andrea Bellavia; Jennifer B Ford; Myra Keller; John C Petrozza; Antonia M Calafat; Russ Hauser; Tamarra James-Todd
Journal:  Environ Health       Date:  2020-04-28       Impact factor: 5.984

10.  Effect of Combined Prenatal and Adult Benzophenone-3 Dermal Exposure on Factors Regulating Neurodegenerative Processes, Blood Hormone Levels, and Hematological Parameters in Female Rats.

Authors:  Alicja Skórkowska; Alicja Maciejska; Bartosz Pomierny; Weronika Krzyżanowska; Beata Starek-Świechowicz; Beata Bystrowska; Żaneta Broniowska; Grzegorz Kazek; Bogusława Budziszewska
Journal:  Neurotox Res       Date:  2020-01-23       Impact factor: 3.911

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