Quantifying the short-term effects of air pollution on health in the presence of exposure measurement error: A simulation study of multi-pollutant model results
File(s)
Published version
Author(s)
Evangelopoulos, Dimitris
Katsouyanni, Klea
Schwartz, Joel
Walton, Heather
Type
Journal Article
Abstract
Background: Most epidemiological studies estimate associations without considering exposure measurement error. While some studies have estimated the impact of error in single-exposure models we aimed to quantify the effect of measurement error in multi-exposure models, specifically in time-series analysis of PM2.5, NO2,and mortality using simulations, under various plausible scenarios for exposure errors. Measurement error in multi-exposure models can lead to effect transfer where the effect estimate is overestimated for the pollutant estimated with more error to the one estimated with less error. This complicates interpretation of the independent effects of different pollutants and thus the relative importance of reducing their concentrations in air pollution policy. Methods: Measurement error was defined as the difference between ambient concentrations and personal exposure from outdoor sources. Simulation inputs for error magnitude and variability were informed by the literature. Error-free exposures with their consequent health 16outcome and error-prone exposures of various error types (classical/Berkson) were generated. Bias was quantified as the relative difference in effect estimates of the error-free and error-prone exposures. Results: Mortality effect estimates were generally underestimated with greater bias observed when low ratios of the true exposure variance over the error variance were assumed (27.4% 21underestimation for NO2). Higher ratios resulted in smaller, but still substantial bias (up to 19% for both pollutants).Effect transfer was observed indicating that less precise measurements for one pollutant (NO2) yield more bias, while the co-pollutant(PM2.5) associations were found closer to the true. Interestingly, the sum of single-pollutant model effect estimates was found closer to the summed true associations than those from multi-pollutant models, due to cancelling out of confounding and measurement error bias.
Conclusions: Our simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions.
Conclusions: Our simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions.
Date Issued
2021-08-24
Date Acceptance
2021-06-07
Citation
Environmental Health: A Global Access Science Source, 2021, 20 (94), pp.1-13
ISSN
1476-069X
Publisher
BioMed Central
Start Page
1
End Page
13
Journal / Book Title
Environmental Health: A Global Access Science Source
Volume
20
Issue
94
Copyright Statement
© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article's Creative Commons
licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons
licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article's Creative Commons
licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons
licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.
License URL
Identifier
https://ehjournal.biomedcentral.com/articles/10.1186/s12940-021-00757-4
Subjects
Science & Technology
Life Sciences & Biomedicine
Environmental Sciences
Public, Environmental & Occupational Health
Environmental Sciences & Ecology
Air pollution
Measurement error
Mixture error
Effect transfer
Simulations
PM2 5
NO2
BERKSON
IMPACT
Air pollution
Effect transfer
Measurement error
Mixture error
NO2
PM2,5
Simulations
Toxicology
1117 Public Health and Health Services
Publication Status
Published
Date Publish Online
2021-08-24