Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis

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Objective To investigate potential interactive effects of fine particulate matter (PM2.5) and ozone (O3) on daily mortality at global level.

Design Two stage time series analysis.

Setting 372 cities across 19 countries and regions.

Population Daily counts of deaths from all causes, cardiovascular disease, and respiratory disease.

Main outcome measure Daily mortality data during 1994-2020. Stratified analyses by co-pollutant exposures and synergy index (>1 denotes the combined effect of pollutants is greater than individual effects) were applied to explore the interaction between PM2.5 and O3 in association with mortality.

Results During the study period across the 372 cities, 19.3 million deaths were attributable to all causes, 5.3 million to cardiovascular disease, and 1.9 million to respiratory disease. The risk of total mortality for a 10 μg/m3 increment in PM2.5 (lag 0-1 days) ranged from 0.47% (95% confidence interval 0.26% to 0.67%) to 1.25% (1.02% to 1.48%) from the lowest to highest fourths of O3 concentration; and for a 10 μg/m3 increase in O3 ranged from 0.04% (−0.09% to 0.16%) to 0.29% (0.18% to 0.39%) from the lowest to highest fourths of PM2.5 concentration, with significant differences between strata (P for interaction <0.001). A significant synergistic interaction was also identified between PM2.5 and O3 for total mortality, with a synergy index of 1.93 (95% confidence interval 1.47 to 3.34). Subgroup analyses showed that interactions between PM2.5 and O3 on all three mortality endpoints were more prominent in high latitude regions and during cold seasons.

Conclusion The findings of this study suggest a synergistic effect of PM2.5 and O3 on total, cardiovascular, and respiratory mortality, indicating the benefit of coordinated control strategies for both pollutants.

Data have been collected within the MCC (Multi-Country Multi-City) Collaborative Research Network (<https://mccstudy.lshtm.ac.uk/>) under a data sharing agreement and cannot be made publicly available. Researchers can refer to MCC participants listed as coauthors for information on accessing the data for each country.

Related Keywords

Shanghai , China , Germany , Hong Kong , Chile , Israel , Moscow , Moskva , Russia , Italy , Seoul , Soult Ukpyolsi , South Korea , Australia , Romania , Italian , , Collaborative Research Network , National Natural Science Foundation Of China , University Of Florence , Department Of Statistics , Department Of Excellence , Italian Ministry Of University , Conclusion The , Global Burden , Multi Country City , National Natural Science Foundation , Italian Ministry , Computer Science , Open Access , Creative Commons Attribution Non Commercial ,

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