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

Curr Environ Health Rep. 2017 Dec;4(4):481-490. doi: 10.1007/s40572-017-0162-z.

Abstract

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. 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.

Keywords: Correlated variables; Environmental exposures; Epidemiology; Health; Multi-pollutant.

Publication types

  • Review

MeSH terms

  • Air Pollutants / analysis*
  • Air Pollutants / chemistry
  • Air Pollution / analysis
  • Complex Mixtures / chemistry*
  • Environmental Exposure / analysis*
  • Environmental Monitoring / methods
  • Environmental Pollutants / analysis
  • Humans
  • Models, Statistical*
  • Risk Assessment

Substances

  • Air Pollutants
  • Complex Mixtures
  • Environmental Pollutants