Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution

Duncan Lee, Chris Robertson, Colin Ramsay, Kate Pyper

Research output: Contribution to journalArticle

Abstract

Air pollution is a major public health concern, and large numbers of epidemiological studies have been conducted to quantify its impacts. One study design used to quantify these impacts is a spatial areal unit design, which estimates a population-level association using data on air pollution concentrations and disease incidence that have been spatially aggregated to a set of nonoverlapping areal units. A major criticism of this study design is that the specification of these areal units is arbitrary, and if one changed their boundaries then the aggregated data would change despite the locations of the disease cases and the air pollution surface remaining the same. This is known as the modifiable areal unit problem, and this is the first article to quantify its likely effects in air pollution and health studies. In addition, we derive an aggregate model for these data directly from an idealized individual-level risk model and show that it provides better estimation than the commonly used ecological model. Our work is motivated by a new study of air pollution and health in Scotland, and we find consistent significant associations between air pollution and respiratory disease but not for circulatory disease.

Original languageEnglish
Article numbere2643
Number of pages17
JournalEnvironmetrics
Early online date23 Jun 2020
DOIs
Publication statusE-pub ahead of print - 23 Jun 2020

Keywords

  • epidemiological study
  • nitrogen dioxide and particulate matter
  • spatially aggregated disease counts

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