Estimating the Health Effects of Exposure to Multi-Pollutant Mixture

Air pollution constitutes a major public health concern because of its ubiquity and of its potential health impact. Because individuals are exposed to many air pollutants at once that are highly correlated with each other, there is a need to consider the multi-pollutant exposure phenomenon. The char...

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Bibliographic Details
Published in:Annals of epidemiology Vol. 22; no. 2; pp. 126 - 141
Main Authors: Billionnet, Cécile, Sherrill, Duane, Annesi-Maesano, Isabella
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.02.2012
Subjects:
Air Pollutants - adverse effects
Air Pollutants - analysis
Air Pollution
Air Pollution - adverse effects
Air Pollution - analysis
Bayes Theorem
Cluster Analysis
Collinearity
Combined Effect
Correlated Pollutants
Environmental Exposure - adverse effects
Environmental Exposure - classification
Environmental Monitoring - methods
Humans
Internal Medicine
Logistic Models
Multiple Pollutants
Pollution effects
Public health
Reviews
Risk assessment
Risk Assessment - methods
OR
Multiple Pollutants
PMF
Combined Effect
Air Pollution
VOC
PCA
VIF
GAM
DSA
PLS
BMA
Collinearity
Correlated Pollutants
PM
SPCA
RP
positive matrix factorization
variance inflation factor
volatile organic compounds
Bayesian model averaging
odds ratio
particulate matter
supervised principal component analysis
recursive partitioning
partial least-square
deletion/substitution/addition
generalized additive model
principal component analysis
ISSN:1047-2797, 1873-2585, 1873-2585
Online Access:Get full text
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Summary:Air pollution constitutes a major public health concern because of its ubiquity and of its potential health impact. Because individuals are exposed to many air pollutants at once that are highly correlated with each other, there is a need to consider the multi-pollutant exposure phenomenon. The characteristics of multiple pollutants that make statistical analysis of health-related effects of air pollution complex include the high correlation between pollutants prevents the use of standard statistical methods, the potential existence of interaction between pollutants, the common measurement errors, the importance of the number of pollutants to consider, and the potential nonlinear relationship between exposure and health. We made a review of statistical methods either used in the literature to study the effect of multiple pollutants or identified as potentially applicable to this problem. We reported the results of investigations that applied such methods. Eighteen publications have investigated the multi-pollutant effects, 5 on indoor pollution, 10 on outdoor pollution, and 3 on statistical methodology with application on outdoor pollution. Some other publications have only addressed statistical methodology. The use of Hierarchical Bayesian approach, dimension reduction methods, clustering, recursive partitioning, and logic regression are some potential methods described. Methods that provide figures for risk assessments should be put forward in public health decisions.
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ISSN:1047-2797
1873-2585
1873-2585
DOI:10.1016/j.annepidem.2011.11.004