Background: Humans are typically exposed to mixtures of environmental endocrine-disrupting chemicals simultaneously, but most studies have considered only a single chemical or a class of similar chemicals.
Objectives: We examined the association of exposure to mixtures of 7 chemicals, including 2 phenols [bisphenol A (BPA) and bisphenol S (BPS)], 2 parabens [methylparaben (MeP) and propyl paraben (PrP)], and 3 phthalate metabolites [Mono-benzyl phthalate (MBzP), mono-isobutyl phthalate (MiBP), mono (carboxyoctyl) phthalate (MCOP)] with sex steroid hormones.
Methods: A total of 1179 children aged 6-19 years who had complete data on both 7 chemicals and sex steroid hormones of estradiol (E2), total testosterone (TT), and sex hormone-binding globulin (SHBG) were analyzed from the U.S. National Health and Nutrition Examination Survey 2013-2016. Free androgen index (FAI) calculated by TT/SHBG, and the ratio of TT to E2 (TT/E2) were also estimated. Puberty was defined if TT ≥ 50 ng/dL in boys, E2 ≥ 20 pg/mL in girls; otherwise prepuberty was defined. Linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were performed to estimate the associations of individual chemical or chemical mixtures with sex hormones.
Results: The linear regression showed that 2 phenols, 2 parabens, and 3 phthalate metabolites were generally negatively associated with E2, TT, FAI, and TT/E2, while positively with SHBG. Moreover, these associations were more pronounced among pubertal than prepubertal children. The aforementioned associations were confirmed when further applying WQS and BKMR, and the 3 phthalates metabolites were identified to be the most heavily weighing chemicals.
Conclusions: Exposure to phenols, parabens, and phthalates, either individuals or as a mixture, was negatively associated with E2, TT, FAI and TT/E2, while positively with SHBG. Those associations were stronger among pubertal children.
Keywords: Bayesian kernel machine regression; Chemical mixtures; NHANES; Sex steroid hormones; Weighted quantile sum regression.
Copyright © 2022. Published by Elsevier B.V.