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Current Epidemiology Reports

, Volume 5, Issue 2, pp 160–165 | Cite as

Environmental Exposure Mixtures: Questions and Methods to Address Them

  • Ghassan B. Hamra
  • Jessie P. Buckley
Epidemiologic Methods (R Maclehose, Section Editor)
  • 101 Downloads
Part of the following topical collections:
  1. Topical Collection on Epidemiologic Methods

Abstract

Purpose of This Review

This review provides a summary of statistical approaches that researchers can use to study environmental exposure mixtures. Two primary considerations are the form of the research question and the statistical tools best suited to address that question. Because the choice of statistical tools is not rigid, we make recommendations about when each tool may be most useful.

Recent Findings

When dimensionality is relatively low, some statistical tools yield easily interpretable estimates of effect (e.g., risk ratio, odds ratio) or intervention impacts. When dimensionality increases, it is often necessary to compromise this interpretablity in favor of identifying interesting statistical signals from noise; this requires applying statistical tools that are oriented more heavily towards dimension reduction via shrinkage and/or variable selection.

Summary

The study of complex exposure mixtures has prompted development of novel statistical methods. We suggest that further validation work would aid practicing researchers in choosing among existing and emerging statistical tools for studying exposure mixtures.

Keywords

Complex mixtures Environmental epidemiology Bayesian methods Machine learning 

Notes

Funding Information

JPB was supported by funding from the National Institutes of Health (U24 OD023382).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  2. 2.Department of Environmental Health and EngineeringJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA

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