PMID- 25532525
OWN - NLM
STAT- MEDLINE
DCOM- 20160422
LR  - 20220910
IS  - 1468-4357 (Electronic)
IS  - 1465-4644 (Print)
IS  - 1465-4644 (Linking)
VI  - 16
IP  - 3
DP  - 2015 Jul
TI  - Bayesian kernel machine regression for estimating the health effects of 
      multi-pollutant mixtures.
PG  - 493-508
LID - 10.1093/biostatistics/kxu058 [doi]
AB  - Because humans are invariably exposed to complex chemical mixtures, estimating 
      the health effects of multi-pollutant exposures is of critical concern in 
      environmental epidemiology, and to regulatory agencies such as the U.S. 
      Environmental Protection Agency. However, most health effects studies focus on 
      single agents or consider simple two-way interaction models, in part because we 
      lack the statistical methodology to more realistically capture the complexity of 
      mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new 
      approach to study mixtures, in which the health outcome is regressed on a 
      flexible function of the mixture (e.g. air pollution or toxic waste) components 
      that is specified using a kernel function. In high-dimensional settings, a novel 
      hierarchical variable selection approach is incorporated to identify important 
      mixture components and account for the correlated structure of the mixture. 
      Simulation studies demonstrate the success of BKMR in estimating the 
      exposure-response function and in identifying the individual components of the 
      mixture responsible for health effects. We demonstrate the features of the method 
      through epidemiology and toxicology applications.
CI  - (c) The Author 2014. Published by Oxford University Press. All rights reserved. For 
      permissions, please e-mail: journals.permissions@oup.com.
FAU - Bobb, Jennifer F
AU  - Bobb JF
AD  - Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, 
      USA jbobb@hsph.harvard.edu.
FAU - Valeri, Linda
AU  - Valeri L
AD  - Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, 
      USA.
FAU - Claus Henn, Birgit
AU  - Claus Henn B
AD  - Department of Environmental Health, Harvard School of Public Health, Landmark 
      Center, 401 Park Drive, Boston, MA 02215, USA.
FAU - Christiani, David C
AU  - Christiani DC
AD  - Department of Environmental Health, Harvard School of Public Health, 665 
      Huntington Avenue, Boston, MA 02115, USA.
FAU - Wright, Robert O
AU  - Wright RO
AD  - Mount Sinai Hospital, 17 East 102 Street Floor 3, West Room D3-110, New York, NY 
      10029, USA.
FAU - Mazumdar, Maitreyi
AU  - Mazumdar M
AD  - Department of Environmental Health, Harvard School of Public Health, 665 
      Huntington Avenue, Boston, MA 02115, USA.
FAU - Godleski, John J
AU  - Godleski JJ
AD  - Department of Environmental Health, Harvard School of Public Health, Landmark 
      Center, 401 Park Drive, Boston, MA 02215, USA.
FAU - Coull, Brent A
AU  - Coull BA
AD  - Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, 
      USA.
LA  - eng
GR  - ES007142/ES/NIEHS NIH HHS/United States
GR  - ES016454/ES/NIEHS NIH HHS/United States
GR  - P30 ES000002/ES/NIEHS NIH HHS/United States
GR  - R01 ES013744/ES/NIEHS NIH HHS/United States
GR  - P30 ES023515/ES/NIEHS NIH HHS/United States
GR  - R01 ES014930/ES/NIEHS NIH HHS/United States
GR  - ES017437/ES/NIEHS NIH HHS/United States
GR  - ES013744/ES/NIEHS NIH HHS/United States
GR  - ES000002/ES/NIEHS NIH HHS/United States
GR  - R01 ES020268/ES/NIEHS NIH HHS/United States
GR  - ES0155/ES/NIEHS NIH HHS/United States
GR  - T32 ES007142/ES/NIEHS NIH HHS/United States
GR  - R01 ES021357/ES/NIEHS NIH HHS/United States
GR  - ES014930/ES/NIEHS NIH HHS/United States
GR  - R00 ES022986/ES/NIEHS NIH HHS/United States
GR  - R21 ES022585/ES/NIEHS NIH HHS/United States
GR  - K23 ES017437/ES/NIEHS NIH HHS/United States
GR  - P42 ES016454/ES/NIEHS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20141222
PL  - England
TA  - Biostatistics
JT  - Biostatistics (Oxford, England)
JID - 100897327
RN  - 0 (Environmental Pollutants)
RN  - 0 (Metals)
SB  - IM
MH  - Animals
MH  - Bangladesh
MH  - *Bayes Theorem
MH  - Biostatistics
MH  - Child, Preschool
MH  - Developmental Disabilities/etiology
MH  - Dogs
MH  - Environmental Health/statistics & numerical data
MH  - Environmental Pollutants/*adverse effects
MH  - Female
MH  - Hemodynamics/drug effects
MH  - Humans
MH  - Infant
MH  - Machine Learning
MH  - Metals/adverse effects
MH  - Models, Statistical
MH  - Neurodevelopmental Disorders/etiology
MH  - Normal Distribution
MH  - Pregnancy
MH  - Regression Analysis
PMC - PMC5963470
OTO - NOTNLM
OT  - Air pollution
OT  - Bayesian variable selection
OT  - Environmental health
OT  - Gaussian process regression
OT  - Metal mixtures
EDAT- 2014/12/24 06:00
MHDA- 2016/04/23 06:00
PMCR- 2015/12/22
CRDT- 2014/12/24 06:00
PHST- 2014/05/22 00:00 [received]
PHST- 2014/11/07 00:00 [accepted]
PHST- 2014/12/24 06:00 [entrez]
PHST- 2014/12/24 06:00 [pubmed]
PHST- 2016/04/23 06:00 [medline]
PHST- 2015/12/22 00:00 [pmc-release]
AID - kxu058 [pii]
AID - 10.1093/biostatistics/kxu058 [doi]
PST - ppublish
SO  - Biostatistics. 2015 Jul;16(3):493-508. doi: 10.1093/biostatistics/kxu058. Epub 
      2014 Dec 22.