Prenatal phthalate exposures and adiposity outcomes trajectories: a multivariate Bayesian factor regression approach
Prenatal phthalate exposures and adiposity outcomes trajectories: a multivariate Bayesian factor regression approach
We aim to assess the longitudinal effects of prenatal exposure to phthalates on the risk of childhood obesity in children aged 4 to 7, with potential time-varying and sex-specific effects. Multiple body-composition-related outcomes, such as BMI z-score, fat mass percentage, and waist circumference, are available in the data. Existing chemical mixture analyses often look at these outcomes individually due to the limited availability of multivariate models for mixture exposures. We propose a multivariate Bayesian factor regression that handles multicollinearity in chemical exposures and borrows information across highly correlated outcomes to improve estimation efficiency. We demonstrate the proposed method's utility through simulation studies and an analysis of data from the Mount Sinai Children's Environmental Health Study. We find the associations between prenatal phthalate exposures and adiposity outcomes in male children to be negative at early ages but to become positive as the children get older.
Phuc H. Nguyen、Stephanie M. Engel、Amy H. Herring
医学研究方法预防医学
Phuc H. Nguyen,Stephanie M. Engel,Amy H. Herring.Prenatal phthalate exposures and adiposity outcomes trajectories: a multivariate Bayesian factor regression approach[EB/OL].(2025-06-03)[2025-07-09].https://arxiv.org/abs/2506.02518.点此复制
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