Statistical Approaches to Address Multi-Pollutant Mixtures and Multiple Exposures: the State of the Science

被引：147

作者：

Stafoggia M. ^{[1
,2
]}

Breitner S. ^{[3
]}

Hampel R. ^{[3
]}

Basagaña X. ^{[4
,5
,6
]}

机构：

[1] Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Via Cristoforo Colombo 112, Rome

[2] Institute of Environmental Medicine, Karolinska Institutet, Stockholm

[3] Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neurherberg

[4] ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona

[5] Pompeu Fabra University, Barcelona

[6] Ciber on Epidemiology and Public Health (CIBERESP), Madrid

来源：

Current Environmental Health Reports | 2017年 / 4卷 / 4期

关键词：

Correlated variables; Environmental exposures; Epidemiology; Health; Multi-pollutant;

D O I：

10.1007/s40572-017-0162-z

中图分类号：

学科分类号：

摘要：

Purpose of Review: The purpose of this review is to describe the most recent statistical approaches to estimate the effect of multi-pollutant mixtures or multiple correlated exposures on human health. Recent Findings: The health effects of environmental chemicals or air pollutants have been widely described. Often, there exists a complex mixture of different substances, potentially highly correlated with each other and with other (environmental) stressors. Single-exposure approaches do not allow disentangling effects of individual factors and fail to detect potential interactions between exposures. In the last years, sophisticated methods have been developed to investigate the joint or independent health effects of multi-pollutant mixtures or multiple environmental exposures. Summary: A classification of the most recent methods is proposed. A non-technical description of each method is provided, together with epidemiological applications and operational details for implementation with standard software. © 2017, Springer International Publishing AG.

引用

页码：481 / 490

页数：9

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