PMID- 33765068
OWN - NLM
STAT- MEDLINE
DCOM- 20211019
LR  - 20211019
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 16
IP  - 3
DP  - 2021
TI  - Model choice for estimating the association between exposure to chemical mixtures 
      and health outcomes: A simulation study.
PG  - e0249236
LID - 10.1371/journal.pone.0249236 [doi]
LID - e0249236
AB  - Challenges arise in researching health effects associated with chemical mixtures. 
      Several methods have recently been proposed for estimating the association 
      between health outcomes and exposure to chemical mixtures, but a formal 
      simulation study comparing broad-ranging methods is lacking. We select five 
      recently developed methods and evaluate their performance in estimating the 
      exposure-response function, identifying active mixture components, and 
      identifying interactions in a simulation study. Bayesian kernel machine 
      regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing 
      methods in our simulation study. BKMR and NPB outperformed other contemporary 
      methods and traditional linear models in estimating the exposure-response 
      function and identifying active mixture components. BKMR and NPB produced similar 
      results in a data analysis of the effects of multipollutant exposure on lung 
      function in children with asthma.
FAU - Hoskovec, Lauren
AU  - Hoskovec L
AUID- ORCID: 0000-0002-9320-8622
AD  - Department of Statistics, Colorado State University, Fort Collins, CO, United 
      states of America.
FAU - Benka-Coker, Wande
AU  - Benka-Coker W
AD  - Department of Environmental and Radiological Health Sciences, Colorado State 
      University, Fort Collins, CO, United states of America.
FAU - Severson, Rachel
AU  - Severson R
AD  - Department of Environmental and Radiological Health Sciences, Colorado State 
      University, Fort Collins, CO, United states of America.
FAU - Magzamen, Sheryl
AU  - Magzamen S
AD  - Department of Environmental and Radiological Health Sciences, Colorado State 
      University, Fort Collins, CO, United states of America.
FAU - Wilson, Ander
AU  - Wilson A
AD  - Department of Statistics, Colorado State University, Fort Collins, CO, United 
      states of America.
LA  - eng
GR  - K22 ES023815/ES/NIEHS NIH HHS/United States
GR  - R01 ES028811/ES/NIEHS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20210325
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
RN  - 0 (Air Pollutants)
RN  - 0 (Particulate Matter)
RN  - 0 (Pesticides)
RN  - 66H7ZZK23N (Ozone)
RN  - S7G510RUBH (Nitrogen Dioxide)
SB  - IM
MH  - Air Pollutants/toxicity
MH  - Asthma/etiology/pathology
MH  - Bayes Theorem
MH  - Child
MH  - Environmental Exposure/*analysis
MH  - Forced Expiratory Volume/drug effects
MH  - Humans
MH  - *Models, Statistical
MH  - Nitrogen Dioxide/chemistry
MH  - Ozone/chemistry
MH  - Particulate Matter/chemistry/toxicity
MH  - Pesticides/toxicity
PMC - PMC7993848
COIS- The authors have declared that no competing interests exist.
EDAT- 2021/03/26 06:00
MHDA- 2021/10/21 06:00
PMCR- 2021/03/25
CRDT- 2021/03/25 17:27
PHST- 2020/10/08 00:00 [received]
PHST- 2021/03/13 00:00 [accepted]
PHST- 2021/03/25 17:27 [entrez]
PHST- 2021/03/26 06:00 [pubmed]
PHST- 2021/10/21 06:00 [medline]
PHST- 2021/03/25 00:00 [pmc-release]
AID - PONE-D-20-31686 [pii]
AID - 10.1371/journal.pone.0249236 [doi]
PST - epublish
SO  - PLoS One. 2021 Mar 25;16(3):e0249236. doi: 10.1371/journal.pone.0249236. 
      eCollection 2021.