IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i14p7655-d596816.html
   My bibliography  Save this article

Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis

Author

Listed:
  • Nilakshi T. Waidyatillake

    (Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
    Department of Medical Education, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia)

  • Patricia T. Campbell

    (Department of Infectious Diseases, Melbourne Medical School, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia)

  • Don Vicendese

    (Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
    Department of Mathematics and Statistics, La Trobe University, Bundoora, VIC 3086, Australia)

  • Shyamali C. Dharmage

    (Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia)

  • Ariadna Curto

    (Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia)

  • Mark Stevenson

    (Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
    Transport Health and Urban Design Research Lab, Melbourne School of Design, The University of Melbourne, Melbourne, VIC 3010, Australia)

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). PM 2.5 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 PM 2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM 10 . Conclusion: 253 premature deaths per million population are associated with exposure to ambient PM 2.5 . We observed an unstable estimate for PM 10 , most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM 10 and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM 2.5 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.

Suggested Citation

  • Nilakshi T. Waidyatillake & Patricia T. Campbell & Don Vicendese & Shyamali C. Dharmage & Ariadna Curto & Mark Stevenson, 2021. "Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis," IJERPH, MDPI, vol. 18(14), pages 1-21, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7655-:d:596816
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/14/7655/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/14/7655/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sourangsu Chowdhury & Sagnik Dey & Kirk R. Smith, 2018. "Ambient PM2.5 exposure and expected premature mortality to 2100 in India under climate change scenarios," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    2. Wahida Kihal-Talantikite & Pierre Legendre & Pauline Le Nouveau & Séverine Deguen, 2018. "Premature Adult Death and Equity Impact of a Reduction of NO 2 , PM 10 , and PM 2.5 Levels in Paris—A Health Impact Assessment Study Conducted at the Census Block Level," IJERPH, MDPI, vol. 16(1), pages 1-19, December.
    3. Ivan C. Hanigan & Richard A. Broome & Timothy B. Chaston & Martin Cope & Martine Dennekamp & Jane S. Heyworth & Katharine Heathcote & Joshua A. Horsley & Bin Jalaludin & Edward Jegasothy & Fay H. John, 2020. "Avoidable Mortality Attributable to Anthropogenic Fine Particulate Matter (PM 2.5 ) in Australia," IJERPH, MDPI, vol. 18(1), pages 1-9, December.
    4. Yuanyuan Fang & Denise Mauzerall & Junfeng Liu & Arlene Fiore & Larry Horowitz, 2013. "Impacts of 21st century climate change on global air pollution-related premature mortality," Climatic Change, Springer, vol. 121(2), pages 239-253, November.
    5. Gerardo Sanchez Martinez & Joseph V. Spadaro & Dimitris Chapizanis & Vladimir Kendrovski & Mihail Kochubovski & Pierpaolo Mudu, 2018. "Health Impacts and Economic Costs of Air Pollution in the Metropolitan Area of Skopje," IJERPH, MDPI, vol. 15(4), pages 1-11, March.
    6. W. J. Corlett, 1957. "The Lognormal Distribution, with Special Reference to its Uses in Economics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 6(3), pages 228-230, November.
    7. David Lunn & Jessica Barrett & Michael Sweeting & Simon Thompson, 2013. "Fully Bayesian hierarchical modelling in two stages, with application to meta-analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 551-572, August.
    8. J. Lelieveld & J. S. Evans & M. Fnais & D. Giannadaki & A. Pozzer, 2015. "The contribution of outdoor air pollution sources to premature mortality on a global scale," Nature, Nature, vol. 525(7569), pages 367-371, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tugce Pekdogan & Mihaela Tinca Udriștioiu & Silvia Puiu & Hasan Yildizhan & Martin Hruška, 2023. "A Multi-Country Statistical Analysis Covering Turkey, Slovakia, and Romania in an Educational Framework," Sustainability, MDPI, vol. 15(24), pages 1-16, December.
    2. Athena Progiou & Natalia Liora & Ioannis Sebos & Christina Chatzimichail & Dimitrios Melas, 2023. "Measures and Policies for Reducing PM Exceedances through the Use of Air Quality Modeling: The Case of Thessaloniki, Greece," Sustainability, MDPI, vol. 15(2), pages 1-22, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ruoyu Lan & Sebastian D. Eastham & Tianjia Liu & Leslie K. Norford & Steven R. H. Barrett, 2022. "Air quality impacts of crop residue burning in India and mitigation alternatives," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Lanzi, Elisa & Dellink, Rob & Chateau, Jean, 2018. "The sectoral and regional economic consequences of outdoor air pollution to 2060," Energy Economics, Elsevier, vol. 71(C), pages 89-113.
    3. Héctor Jorquera & Ana María Villalobos, 2020. "Combining Cluster Analysis of Air Pollution and Meteorological Data with Receptor Model Results for Ambient PM 2.5 and PM 10," IJERPH, MDPI, vol. 17(22), pages 1-25, November.
    4. Ellen Banzhaf & Sally Anderson & Gwendoline Grandin & Richard Hardiman & Anne Jensen & Laurence Jones & Julius Knopp & Gregor Levin & Duncan Russel & Wanben Wu & Jun Yang & Marianne Zandersen, 2022. "Urban-Rural Dependencies and Opportunities to Design Nature-Based Solutions for Resilience in Europe and China," Land, MDPI, vol. 11(4), pages 1-25, March.
    5. Rogers Kanee & Precious Ede & Omosivie Maduka & Golden Owhonda & Eric Aigbogun & Khalaf F. Alsharif & Ahmed H. Qasem & Shadi S. Alkhayyat & Gaber El-Saber Batiha, 2021. "Polycyclic Aromatic Hydrocarbon Levels in Wistar Rats Exposed to Ambient Air of Port Harcourt, Nigeria: An Indicator for Tissue Toxicity," IJERPH, MDPI, vol. 18(11), pages 1-21, May.
    6. Mevin B. Hooten & Michael R. Schwob & Devin S. Johnson & Jacob S. Ivan, 2023. "Multistage hierarchical capture–recapture models," Environmetrics, John Wiley & Sons, Ltd., vol. 34(6), September.
    7. Hongjun Yu & Jiali Cheng & Shelby Paige Gordon & Ruopeng An & Miao Yu & Xiaodan Chen & Qingli Yue & Jun Qiu, 2018. "Impact of Air Pollution on Sedentary Behavior: A Cohort Study of Freshmen at a University in Beijing, China," IJERPH, MDPI, vol. 15(12), pages 1-12, December.
    8. Xiya Zhang & Haibo Hu, 2019. "Combining Data from Multiple Sources to Evaluate Spatial Variations in the Economic Costs of PM 2.5 -Related Health Conditions in the Beijing–Tianjin–Hebei Region," IJERPH, MDPI, vol. 16(20), pages 1-17, October.
    9. Sowmya Malamardi & Katrina A. Lambert & Attahalli Shivanarayanaprasad Praveena & Mahesh Padukudru Anand & Bircan Erbas, 2022. "Time Trends of Greenspaces, Air Pollution, and Asthma Prevalence among Children and Adolescents in India," IJERPH, MDPI, vol. 19(22), pages 1-17, November.
    10. Malayaranjan Sahoo & Narayan Sethi, 2022. "The dynamic impact of urbanization, structural transformation, and technological innovation on ecological footprint and PM2.5: evidence from newly industrialized countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 4244-4277, March.
    11. Liu, Haoming & Salvo, Alberto, 2017. "Severe Air Pollution and School Absences: Longitudinal Data on Expatriates in North China," IZA Discussion Papers 11134, Institute of Labor Economics (IZA).
    12. Li, Shanjun & Liu, Yanyan & Purevjav, Avralt-Od & Yang, Lin, 2019. "Does subway expansion improve air quality?," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 213-235.
    13. K. K. Shukla & Raju Attada & Aman W. Khan & Prashant Kumar, 2022. "Evaluation of extreme dust storm over the northwest Indo-Gangetic plain using WRF-Chem model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 1887-1910, February.
    14. Shichun Xu & Wenwen Zhang & Qinbin Li & Bin Zhao & Shuxiao Wang & Ruyin Long, 2017. "Decomposition Analysis of the Factors that Influence Energy Related Air Pollutant Emission Changes in China Using the SDA Method," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    15. Bedoya-Maya, Felipe & Calatayud, Agustina & González Mejia, Vileydy, 2022. "Estimating the effect of urban road congestion on air quality in Latin America," IDB Publications (Working Papers) 12468, Inter-American Development Bank.
    16. Ling-Yun He & Xiao-Feng Qi, 2021. "Environmental Courts, Environment and Employment: Evidence from China," Sustainability, MDPI, vol. 13(11), pages 1-16, June.
    17. Wang, Qiang & Kwan, Mei-Po & Zhou, Kan & Fan, Jie & Wang, Yafei & Zhan, Dongsheng, 2019. "Impacts of residential energy consumption on the health burden of household air pollution: Evidence from 135 countries," Energy Policy, Elsevier, vol. 128(C), pages 284-295.
    18. Weicong Fu & Qunyue Liu & Cecil Konijnendijk van den Bosch & Ziru Chen & Zhipeng Zhu & Jinda Qi & Mo Wang & Emily Dang & Jianwen Dong, 2018. "Long-Term Atmospheric Visibility Trends and Their Relations to Socioeconomic Factors in Xiamen City, China," IJERPH, MDPI, vol. 15(10), pages 1-16, October.
    19. Calvo, Rubén & Álamos, Nicolás & Huneeus, Nicolás & O'Ryan, Raúl, 2022. "Energy poverty effects on policy-based PM2.5 emissions mitigation in southern and central Chile," Energy Policy, Elsevier, vol. 161(C).
    20. Carl-Friedrich Schleussner & Joeri Rogelj & Michiel Schaeffer & Tabea Lissner & Rachel Licker & Erich M. Fischer & Reto Knutti & Anders Levermann & Katja Frieler & William Hare, 2016. "Science and policy characteristics of the Paris Agreement temperature goal," Nature Climate Change, Nature, vol. 6(9), pages 827-835, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7655-:d:596816. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.