Particulate matter and premature mortality : A Bayesian meta-analysis

Journal article


Waidyatillake, Nilakshi T., Campbell, Patricia T., Vicendese, Don, Dharmage, Shyamali C., Curto, Ariadna and Stevenson, Mark. (2021). Particulate matter and premature mortality : A Bayesian meta-analysis. International Journal of Environmental Research and Public Health. 18(14), p. Article 7655. https://doi.org/10.3390/ijerph18147655
AuthorsWaidyatillake, Nilakshi T., Campbell, Patricia T., Vicendese, Don, Dharmage, Shyamali C., Curto, Ariadna and Stevenson, Mark
Abstract

Background: We present a systematic review of studies assessing the association between ambient particulate matter (PM) and premature mortality and the results of a Bayesian hierarchical meta-analysis while accounting for population differences of the included studies. Methods: The review protocol was registered in the PROSPERO systematic review registry. Medline, CINAHL and Global Health databases were systematically searched. Bayesian hierarchical meta-analysis was conducted using a non-informative prior to assess whether the regression coefficients differed across observations due to the heterogeneity among studies. Results: We identified 3248 records for title and abstract review, of which 309 underwent full text screening. Thirty-six studies were included, based on the inclusion criteria. Most of the studies were from China (n = 14), India (n = 6) and the USA (n = 3). PM2.5 was the most frequently reported pollutant. PM was estimated using modelling techniques (22 studies), satellite-based measures (four studies) and direct measurements (ten studies). Mortality data were sourced from country-specific mortality statistics for 17 studies, Global Burden of Disease data for 16 studies, WHO data for two studies and life tables for one study. Sixteen studies were included in the Bayesian hierarchical meta-analysis. The meta-analysis revealed that the annual estimate of premature mortality attributed to PM2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM10. Conclusion: 253 premature deaths per million population are associated with exposure to ambient PM2.5. We observed an unstable estimate for PM10, most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM10 and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM2.5 is associated with premature mortality. Given that rapid urbanization may increase this burden in the coming decades, our study highlights the urgency of implementing air pollution mitigation strategies to reduce the risk to population and planetary health.

KeywordsBayesian hierarchical meta-analysis; particulate matter; PM2.5; PM10; premature mortality
Year2021
JournalInternational Journal of Environmental Research and Public Health
Journal citation18 (14), p. Article 7655
PublisherMultidisciplinary Digital Publishing Institute (MDPI AG)
ISSN1661-7827
Digital Object Identifier (DOI)https://doi.org/10.3390/ijerph18147655
PubMed ID34300107
Scopus EID2-s2.0-85110300870
PubMed Central IDPMC8303514
Open accessPublished as ‘gold’ (paid) open access
Page range1-21
FunderMelbourne Energy Institute, University of Melbourne
National Health and Medical Research Council (NHMRC)
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online19 Jul 2021
Publication process dates
Accepted14 Jul 2021
Deposited18 Oct 2023
Grant IDAPP1136250
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https://acuresearchbank.acu.edu.au/item/8zw89/particulate-matter-and-premature-mortality-a-bayesian-meta-analysis

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