Abstract |
Studying the effects of gestational exposures to chemical mixtures on infant birth weight is inconclusive due to several challenges. One of the challenges is which statistical methods to rely on. Bayesian factor analysis (BFA), which has not been utilized for chemical mixtures, has advantages in variance reduction and model interpretation. METHODS: RESULTS: For BFA, a 10-fold increase in the concentrations of PCB and PFAS mixtures was associated with an 81 g (95% confidence intervals [CI] = -132 to -31 g) and 57 g (95% CI = -105 to -10 g) reduction in birth weight, respectively. BKMR results confirmed the direction of effect. However, the 95% credible intervals all contained the null. For single- pollutant MLR, a 10-fold increases in the concentrations of multiple chemicals were associated with reduced birth weight, yet the 95% CI all contained the null. Variance inflation from MLR was apparent for models that adjusted for copollutants, resulting in less precise confidence intervals. CONCLUSION: We demonstrated the merits of BFA on mixture analysis in terms of precision and interpretation compared with MLR and BKMR. We also identified the association between exposure to PCBs and PFAS and lower birth weight.
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Authors | Liheng H Zhuang, Aimin Chen, Joseph M Braun, Bruce P Lanphear, Janice M Y Hu, Kimberly Yolton, Lawrence C McCandless |
Journal | Environmental epidemiology (Philadelphia, Pa.)
(Environ Epidemiol)
Vol. 5
Issue 3
Pg. e159
(Jun 2021)
ISSN: 2474-7882 [Electronic] United States |
PMID | 34131620
(Publication Type: Journal Article)
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Copyright | Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved. |