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| Meta-analysis of the effect of PM2.5 on mortality of respiratory diseases |
| GU Wen-wen, YANG Luo-xian, CHENG Qing-lin
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| Hangzhou Center for Disease Control and Prevention,Hangzhou,Zhejiang 310021,China |
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Abstract Objective To explore the relationship between short-term（less than seven days）exposure to PM2.5 and daily respiratory death.Methods We searched for China National Knowledge Infrastructure,Wanfang Database,VIP Database,PubMed and Web of Science by using particulate matter,PM2.5,atmospheric pollutants,respiratory system and death as the key words. The literatures on the relationship between PM2.5 and mortality from respiratory diseases in China were included. The increasing percentage of mortality from respiratory disease while increasing by 10 μg/m3 of PM2.5 was used as the effect indicator（ER）. Stata 14.0 software were used to conduct meta-analysis,and subgroup analysis was performed according to the type and study methods.Results A total of 1 564 related articles were retrieved,and 17 articles that met the requirements were finally included,including 7 Chinese articles and 10 English articles. The inclusion of the literature using a random effects model showed that for every 10 μg/m3 increase in PM2.5,the mortality rate of respiratory disease in the population increased by 0.48%（95%CI: 0.35%-0.62%）. In the subgroup analysis,the single-day lag effect of PM2.5 increased by 10 μg/m3 increased the mortality of respiratory diseases in the population by 0.53%（95%CI: 0.31%- 0.74%）,and the I2 value was 65%; the cumulative lag effect was 0.35%（95%CI: 0.25%-0.45%）with an I2 value of 44%. In the time series study,respiratory disease mortality increased by 0.51%（95%CI: 0.34%-0.67%）and I2 value was 61% for every 10 μg/m3 increase in PM2.5,and the case crossover study was 0.32%（95%CI: 0.15%-0.49%）,and the I2 value was 46%. There were no significant differences in sensitivity analysis. Egger’s test showed publication bias was existing（P=0.005）.Conclusion Elevated level of PM2.5 may increase mortality in respiratory diseases in the population.
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Received: 20 April 2018
Revised: 06 August 2018
Published: 06 November 2018
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