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Measurement Error and Environmental Epidemiology: a Policy Perspective

  • Methods in Environmental Epidemiology (EF Schisterman and AZ Pollack, Section Editors)
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Abstract

Purpose of Review

Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making.

Recent Findings

We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure-response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention.

Summary

Under a policy perspective, the analyst must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology.

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Acknowledgements

This work was supported in part by NIH 5T32ES007018-38.

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  1. Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Dr. 2101 McGavran-Greenberg Hall CB #7435, Chapel Hill, NC, 27599, USA

    Jessie K. Edwards & Alexander P. Keil

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  1. Jessie K. Edwards
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  2. Alexander P. Keil
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Correspondence to Jessie K. Edwards.

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Edwards, J.K., Keil, A.P. Measurement Error and Environmental Epidemiology: a Policy Perspective. Curr Envir Health Rpt 4, 79–88 (2017). https://doi.org/10.1007/s40572-017-0125-4

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