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Assessing the spatial-temporal clustering and health implications of fine particulate matter (PM2.5)

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Abstract

Aim

This study seeks to examine changes in the mean annual exposure of PM2.5 air pollution from 1990 to 2000 and how they are associated with change in mortality due to tuberculosis, trachea/bronchus/lung cancer, respiratory diseases, and cardiovascular diseases from 2000 to 2016. A secondary goal of this study is to use spatial-temporal clustering to examine how PM2.5 trends differ across countries.

Methods

The empirical work of this study is based on the World Bank Open Data and the World Health Organization’s Global Health Observatory (GHO) Data Repository. Quantile regression and spatial-temporal cluster analysis are used to assess the aims of this study.

Results

Findings from the quantile regression revealed that the number of deaths associated with these diseases differ according to the different levels of changes in PM2.5 concentration. Findings also reveal that countries assigned to different clusters are markedly different in terms of PM2.5 trends. Findings imply that air pollution inequality should be considered a factor in the elimination of health inequality.

Conclusion

Efforts to integrate disease surveillance and control programs with those that reduce exposure to fine particulate matter, improve air quality, and increase people’s awareness of the health implications of air pollution should be continued or encouraged.

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Correspondence to Hui-Peng Liew.

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Liew, HP., Eidem, N. Assessing the spatial-temporal clustering and health implications of fine particulate matter (PM2.5). J Public Health (Berl.) 30, 789–799 (2022). https://doi.org/10.1007/s10389-020-01346-4

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  • DOI: https://doi.org/10.1007/s10389-020-01346-4

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