PMID- 33465343
OWN - NLM
STAT- MEDLINE
DCOM- 20210421
LR  - 20210421
IS  - 1096-0953 (Electronic)
IS  - 0013-9351 (Linking)
VI  - 195
DP  - 2021 Apr
TI  - Prenatal exposure to endocrine disrupting chemical mixtures and infant birth 
      weight: A Bayesian analysis using kernel machine regression.
PG  - 110749
LID - S0013-9351(21)00043-8 [pii]
LID - 10.1016/j.envres.2021.110749 [doi]
AB  - BACKGROUND: Pregnant women are regularly exposed to a multitude of endocrine 
      disrupting chemicals (EDCs). EDC exposures, both individually and as mixtures, 
      may affect fetal growth. The relationship of EDC mixtures with infant birth 
      weight, however, remains poorly understood. We examined the relations between 
      prenatal exposure to EDC mixtures and infant birth weight. METHODS: We used data 
      from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a 
      pan-Canadian cohort of 1857 pregnant women enrolled between 2008 and 2011. We 
      quantified twenty-one chemical concentrations from five EDC classes, including 
      organochlorine compounds (OCs), metals, perfluoroalkyl substances (PFAS), phenols 
      and phthalate metabolites that were detected in >70% of urine or blood samples 
      collected during the first trimester. In our primary analysis, we used Bayesian 
      kernel machine regression (BKMR) models to assess variable importance, explore 
      EDC mixture effects, and identify any interactions among EDCs. Our secondary 
      analysis used traditional linear regression to compare the results with those of 
      BKMR and to quantify the changes in mean birth weight in relation to prenatal EDC 
      exposures. RESULTS: We found evidence that mixtures of OCs and metals were 
      associated with monotonic decreases in mean birth weight across the whole range 
      of exposure. trans-Nonachlor from the OC mixture and lead (Pb) from the metal 
      mixture had the greatest impact on birth weight. Our linear regression analysis 
      corroborated the BKMR results and found that a 2-fold increase in trans-nonachlor 
      and Pb concentrations reduced mean birth weight by -38 g (95% confidence interval 
      (CI): -67, -10) and -39 g (95% CI: -69, -9), respectively. A sex-specific 
      association for OC mixture was observed among female infants. PFAS, phenols and 
      phthalates were not associated with birth weight. No interactions were observed 
      among the EDCs. CONCLUSIONS: Using BKMR, we observed that both OC and metal 
      mixtures were associated with decreased birth weight in the MIREC Study. 
      trans-Nonachlor from the OC mixture and Pb from the metal mixture contributed 
      most to the adverse effects.
CI  - Copyright (c) 2021 Elsevier Inc. All rights reserved.
FAU - Hu, Janice M Y
AU  - Hu JMY
AD  - Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. 
      Electronic address: mungh@sfu.ca.
FAU - Arbuckle, Tye E
AU  - Arbuckle TE
AD  - Population Studies Division, Environmental Health Science and Research Bureau, 
      Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, 
      Canada.
FAU - Janssen, Patricia
AU  - Janssen P
AD  - School of Population and Public Health, University of British Columbia, 
      Vancouver, BC V6T 1Z4, Canada.
FAU - Lanphear, Bruce P
AU  - Lanphear BP
AD  - Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
FAU - Zhuang, Liheng H
AU  - Zhuang LH
AD  - Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
FAU - Braun, Joseph M
AU  - Braun JM
AD  - Department of Epidemiology, Brown University, Providence, RI, USA.
FAU - Chen, Aimin
AU  - Chen A
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, PA, USA.
FAU - McCandless, Lawrence C
AU  - McCandless LC
AD  - Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
LA  - eng
GR  - L-CIP-150736/CAPMC/CIHR/Canada
GR  - MOP-81285/CAPMC/CIHR/Canada
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20210117
PL  - Netherlands
TA  - Environ Res
JT  - Environmental research
JID - 0147621
RN  - 0 (Endocrine Disruptors)
RN  - 0 (Environmental Pollutants)
SB  - IM
MH  - Bayes Theorem
MH  - Birth Weight
MH  - Canada
MH  - *Endocrine Disruptors/toxicity
MH  - *Environmental Pollutants/toxicity
MH  - Female
MH  - Humans
MH  - Infant
MH  - Male
MH  - Maternal Exposure/adverse effects
MH  - Pregnancy
MH  - *Prenatal Exposure Delayed Effects/chemically induced/epidemiology
OTO - NOTNLM
OT  - Bayesian kernel machine regression (BKMR)
OT  - Birth weight
OT  - Chemical mixtures
OT  - Endocrine disrupting chemicals
OT  - Fetal growth
EDAT- 2021/01/20 06:00
MHDA- 2021/04/22 06:00
CRDT- 2021/01/19 20:08
PHST- 2020/10/20 00:00 [received]
PHST- 2021/01/08 00:00 [revised]
PHST- 2021/01/11 00:00 [accepted]
PHST- 2021/01/20 06:00 [pubmed]
PHST- 2021/04/22 06:00 [medline]
PHST- 2021/01/19 20:08 [entrez]
AID - S0013-9351(21)00043-8 [pii]
AID - 10.1016/j.envres.2021.110749 [doi]
PST - ppublish
SO  - Environ Res. 2021 Apr;195:110749. doi: 10.1016/j.envres.2021.110749. Epub 2021 
      Jan 17.