Projects per year
Abstract
Background: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of =2.5 mm (PM2.5). However, few studies have assessed the disparities in health effects between modelestimated and station-observed PM2.5 exposures. Methods: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. Results: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-μg/ m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. Conclusions: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.
Original language | English |
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Article number | dyae066 |
Number of pages | 8 |
Journal | International Journal of Epidemiology |
Volume | 53 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jun 2024 |
Keywords
- air monitoring station observation
- fine particulate matter
- model estimation
- mortality risk comparison
- Short-term exposure
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New Knowledge and Research Capacity for Health Impacts of Global Environmental Change with Big Data, Novel Approach and New Technology
Guo, Y. (Primary Chief Investigator (PCI))
1/01/22 → 31/12/26
Project: Research
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Better Environment, Healthier Ageing
Guo, Y. (Primary Chief Investigator (PCI)), Li, S. (Chief Investigator (CI)), Huxley, R. R. (Chief Investigator (CI)), Dharmage, S. C. (Chief Investigator (CI)), Lim, Y. Y. (Chief Investigator (CI)), Rawson, H. (Chief Investigator (CI)), Morawska, L. (Chief Investigator (CI)), McKenzie, J. (Chief Investigator (CI)), Ryan, J. (Chief Investigator (CI)), Cain, S. (Chief Investigator (CI)), Ademi Delaney, Z. (Chief Investigator (CI)), Song, J. (Chief Investigator (CI)), Xu, R. (Chief Investigator (CI)), Jay, O. (Chief Investigator (CI)), McNeil, J. (Associate Investigator (AI)), Capon, T. (Associate Investigator (AI)), Jalaludin, B. B. (Associate Investigator (AI)), Pearce, C. (Associate Investigator (AI)), Smith, K. (Associate Investigator (AI)), Greening, C. (Associate Investigator (AI)), Griffiths, D. (Associate Investigator (AI)), Collie, A. (Associate Investigator (AI)), Walker-Bone, K. (Associate Investigator (AI)) & Levinger, P. (Associate Investigator (AI))
1/06/22 → 31/05/24
Project: Research
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Multi-Country Study on Health Effects of Bushfire Air Pollution
Guo, Y. (Primary Chief Investigator (PCI)), Abramson, M. (Chief Investigator (CI)), Marks, G. B. (Partner Investigator (PI)), Johnston, F. (Chief Investigator (CI)), Heyworth, J. S. (Chief Investigator (CI)), Morgan, G. G. (Chief Investigator (CI)), Knibbs, L. (Chief Investigator (CI)), Samet, J. (Partner Investigator (PI)), Bell, M. (Partner Investigator (PI)), Woodward, A. (Partner Investigator (PI)), Jalaludin, B. B. (Partner Investigator (PI)), Saldiva, P. H. N. (Partner Investigator (PI)), Hales, S. (Partner Investigator (PI)), Henderson, S. B. (Partner Investigator (PI)) & Lavigne, E. (Partner Investigator (PI))
1/04/22 → 31/03/25
Project: Research