Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches

Duncan Lee; Heather Walton; Dimitris Evangelopoulos; Klea Katsouyanni; Alison M Gowers; Gavin Shaddick; Christina Mitsakou

doi:10.1016/j.envpol.2023.122465

Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches

Environ Pollut. 2023 Nov 1:336:122465. doi: 10.1016/j.envpol.2023.122465. Epub 2023 Aug 26.

Authors

Duncan Lee¹, Heather Walton², Dimitris Evangelopoulos³, Klea Katsouyanni⁴, Alison M Gowers⁵, Gavin Shaddick⁶, Christina Mitsakou⁵

Affiliations

¹ School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, UK. Electronic address: Duncan.Lee@glasgow.ac.uk.
² Environmental Research Group, School of Public Health, Imperial College London, UK; National Institute of Health Research Health Protection Research Unit in Environmental Exposures and Health, Imperial College London, UK.
³ Environmental Research Group, School of Public Health, Imperial College London, UK; National Institute of Health Research Health Protection Research Unit in Environmental Exposures and Health, Imperial College London, UK; MRC Centre for Environment and Health, Imperial College London, UK.
⁴ Environmental Research Group, School of Public Health, Imperial College London, UK; National Institute of Health Research Health Protection Research Unit in Environmental Exposures and Health, Imperial College London, UK; University of Athens, Greece.
⁵ Air Quality and Public Health Group, UK Health Security Agency, UK.
⁶ Royal Holloway University of London, UK.

PMID: 37640226
DOI: 10.1016/j.envpol.2023.122465

Abstract

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO₂, O₃ and PM_2.5 with all-cause mortality, and PM_2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09).

Keywords: Air pollution; Health impact assessment; Meta analysis; Regional heterogeneity.

Publication types

Meta-Analysis

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Databases, Factual
Environmental Exposure / analysis
Health Impact Assessment
Particulate Matter / analysis

Substances

Air Pollutants
Particulate Matter