Ann M Vuong1, Changchun Xie2, Roman Jandarov2, Kim N Dietrich2, Hongmei Zhang3, Andreas Sjödin4, Antonia M Calafat4, Bruce P Lanphear5, Lawrence McCandless6, Joseph M Braun7, Kimberly Yolton8, Aimin Chen9. 1. Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Department of Environmental and Occupational Health, University of Nevada Las Vegas, School of Public Health, United States. 2. Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, United States. 3. Department of Environmental Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China. 4. National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States. 5. Child and Family Research Institute, BC Children's Hospital, British Columbia, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada. 6. Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada. 7. Department of Epidemiology, Brown University, Providence, RI, United States. 8. Department of Pediatrics, Division of General and Community Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States. 9. Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States. Electronic address: Aimin.Chen@Pennmedicine.upenn.edu.
Abstract
BACKGROUND: Prenatal exposure to persistent organic pollutants (POPs) may affect child neurobehavior; however, exposures to mixtures of POPs have rarely been examined. METHODS: We estimated associations of prenatal serum concentrations of 17 POPs, namely 5 polybrominated diphenyl ethers (PBDEs), 6 polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyltrichloroethane (DDT), and 4 per- and polyfluoroalkyl substances (PFAS), with Wide Range Achievement Test-4 reading composite scores at age 8 years in 161 children from a pregnancy and birth cohort (Health Outcomes and Measures of the Environment [HOME] Study, 2003-present) in Cincinnati, OH. We applied 6 statistical methods: least absolute shrinkage and selection operator (LASSO), elastic net (ENET), Sparse Principal Component Analysis (SPCA), Weighted Quantile Sum (WQS) regression, Bayesian Kernel Machine Regression (BKMR), and Bayesian Additive Regression Trees (BART), to estimate covariate-adjusted associations with individual and their mixtures in multi-pollutant models. RESULTS: Both LASSO and ENET models indicated inverse associations with reading scores for BDE-153 and BDE-28, and positive associations for CB-118, CB-180, perfluoroctanoate (PFOA), and perfluorononanoate (PFNA). The SPCA identified inverse associations for BDE-153 and BDE-100 and positive associations for perfluorooctane sulfonate (PFOS), PFOA, and PFNA, as parts of different principal component scores. The WQS regression showed the highest weights for BDE-100 (0.35) and BDE-28 (0.16) in the inverse association model and for PFNA (0.29) and CB-180 (0.21) in the positive association model. The BKMR model identified BDE-100 and BDE-153 for inverse associations and CB-118, CB-153, CB-180, PFOA, and PFNA for positive associations. The BART method found dose-response functions similar to the BKMR model. No interactions between POPs were identified. CONCLUSIONS: Despite some inconsistency among biomarkers, these analyses revealed inverse associations between prenatal PBDE concentrations and children's reading scores. Positive associations of PCB congeners and PFAS with reading skills were also found.
BACKGROUND: Prenatal exposure to persistent organic pollutants (POPs) may affect child neurobehavior; however, exposures to mixtures of POPs have rarely been examined. METHODS: We estimated associations of prenatal serum concentrations of 17 POPs, namely 5 polybrominated diphenyl ethers (PBDEs), 6 polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyltrichloroethane (DDT), and 4 per- and polyfluoroalkyl substances (PFAS), with Wide Range Achievement Test-4 reading composite scores at age 8 years in 161 children from a pregnancy and birth cohort (Health Outcomes and Measures of the Environment [HOME] Study, 2003-present) in Cincinnati, OH. We applied 6 statistical methods: least absolute shrinkage and selection operator (LASSO), elastic net (ENET), Sparse Principal Component Analysis (SPCA), Weighted Quantile Sum (WQS) regression, Bayesian Kernel Machine Regression (BKMR), and Bayesian Additive Regression Trees (BART), to estimate covariate-adjusted associations with individual and their mixtures in multi-pollutant models. RESULTS: Both LASSO and ENET models indicated inverse associations with reading scores for BDE-153 and BDE-28, and positive associations for CB-118, CB-180, perfluoroctanoate (PFOA), and perfluorononanoate (PFNA). The SPCA identified inverse associations for BDE-153 and BDE-100 and positive associations for perfluorooctane sulfonate (PFOS), PFOA, and PFNA, as parts of different principal component scores. The WQS regression showed the highest weights for BDE-100 (0.35) and BDE-28 (0.16) in the inverse association model and for PFNA (0.29) and CB-180 (0.21) in the positive association model. The BKMR model identified BDE-100 and BDE-153 for inverse associations and CB-118, CB-153, CB-180, PFOA, and PFNA for positive associations. The BART method found dose-response functions similar to the BKMR model. No interactions between POPs were identified. CONCLUSIONS: Despite some inconsistency among biomarkers, these analyses revealed inverse associations between prenatal PBDE concentrations and children's reading scores. Positive associations of PCB congeners and PFAS with reading skills were also found.
Authors: Joseph M Braun; Geetika Kalloo; Aimin Chen; Kim N Dietrich; Stacey Liddy-Hicks; Samantha Morgan; Yingying Xu; Kimberly Yolton; Bruce P Lanphear Journal: Int J Epidemiol Date: 2017-02-01 Impact factor: 7.196
Authors: Andreas Sjödin; Richard S Jones; Chester R Lapeza; Jean-François Focant; Ernest E McGahee; Donald G Patterson Journal: Anal Chem Date: 2004-04-01 Impact factor: 6.986
Authors: Paul W Stewart; Jacqueline Reihman; Edward I Lonky; Thomas J Darvill; James Pagano Journal: Neurotoxicol Teratol Date: 2003 Jan-Feb Impact factor: 3.763
Authors: Shelley H Liu; Jennifer F Bobb; Kyu Ha Lee; Chris Gennings; Birgit Claus Henn; David Bellinger; Christine Austin; Lourdes Schnaas; Martha M Tellez-Rojo; Howard Hu; Robert O Wright; Manish Arora; Brent A Coull Journal: Biostatistics Date: 2018-07-01 Impact factor: 5.899