霍然, 叶蓉蓉, 张芳, 狄政莉. 6种常见空气污染物短期暴露与缺血性脑卒中发病相关性的meta分析[J]. 环境与职业医学, 2023, 40(2): 184-189, 195. DOI: 10.11836/JEOM22307
引用本文: 霍然, 叶蓉蓉, 张芳, 狄政莉. 6种常见空气污染物短期暴露与缺血性脑卒中发病相关性的meta分析[J]. 环境与职业医学, 2023, 40(2): 184-189, 195. DOI: 10.11836/JEOM22307
HUO Ran, YE Rongrong, ZHANG Fang, DI Zhengli. Meta-analysis on correlations between short-term exposures to 6 common air pollutants and incidence of ischemic stroke[J]. Journal of Environmental and Occupational Medicine, 2023, 40(2): 184-189, 195. DOI: 10.11836/JEOM22307
Citation: HUO Ran, YE Rongrong, ZHANG Fang, DI Zhengli. Meta-analysis on correlations between short-term exposures to 6 common air pollutants and incidence of ischemic stroke[J]. Journal of Environmental and Occupational Medicine, 2023, 40(2): 184-189, 195. DOI: 10.11836/JEOM22307

6种常见空气污染物短期暴露与缺血性脑卒中发病相关性的meta分析

Meta-analysis on correlations between short-term exposures to 6 common air pollutants and incidence of ischemic stroke

  • 摘要: 背景

    既往探讨空气污染暴露与缺血性脑卒中(IS)之间的关系的meta分析多集中在颗粒物相关研究,纳入气态污染物的研究较少,且较少出现对于不同滞后日(lag)、季节、性别等因素的亚组分析。

    目的

    定量评估细颗粒物(PM2.5)、可吸入颗粒物(PM10)、一氧化碳(CO)、二氧化氮(NO2)、二氧化硫(SO2)、臭氧(O3)6种常见空气污染物短期暴露与人群IS发病之间的关系。

    方法

    系统检索中国期刊全文数据库、中国生物医学文献数据库、PubMed、Cochrane Library、Web of Science、Embase 6个数据库中截至2022年5月1日发表的6种常见空气污染物暴露和IS发病相关性的文献。使用纽卡斯尔-渥太华量表进行文献质量评价,通过Stata 16.0软件,逐步进行异质性检验、合并效应量、meta回归、亚组分析、敏感性分析和发表偏倚检验等步骤进行meta分析。

    结果

    纳入33篇文献,纳入文献中研究的总人数达7195631人。meta分析结果显示,PM2.5(OR=1.0082,95%CI:1.0049~1.0116)、PM10(OR=1.0017,95%CI:1.0008~1.0026)、CO(OR=1.0328,95%CI:1.0231~1.0426)、NO2(OR=1.0150,95%CI:1.0079~1.0222)、SO2(OR=1.0158,95%CI:1.0078~1.0238)、O3(OR=1.0017,95%CI:1.0003~1.0032)的短期暴露均与IS发病风险增加有关。PM10和O3在滞后0 d时(lag0)和lag1均增加IS发病风险,PM2.5、CO、NO2、SO2都只在lag0显示相关的IS发病风险增高。敏感性分析显示各污染物相关研究结果均稳定,除PM2.5相关文献外其余5种污染物与IS发病相关性文献均不存在发表偏倚。

    结论

    PM2.5、PM10、CO、NO2、SO2、O3短期暴露均可能增加人群IS发病,这种风险在发病当天的效应最显著。

     

    Abstract: Background

    Previous studies using meta-analysis to explore the relationship between air pollution exposure and ischemic stroke (IS) mostly focus on particulate matter-related themes, few include gaseous pollutants in the study, and subgroup analyses of factors such as different lag days, seasons, and genders are rarely been reported.

    Objective

    To quantitatively evaluate the relationships between short-term exposures to 6 common air pollutants, including fine particulate matter (PM2.5), inhalable particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), and the incidence of IS.

    Methods

    A systematic search was conducted to collect literature studying the 6 common air pollutants and IS published up to May 1, 2022 in 6 databases (China Journal Full-text Database, China Biology Medicine Disc, PubMed, Cochrane Library, Web of Science, and Embase). Literature quality evaluation was performed using the Newcastle-Ottawa Scale. Stata 16.0 software was used to conduct meta-analysis including heterogeneity test, combined effect size, meta-regression, subgroup analysis, sensitivity analysis, and publication bias test.

    Results

    A total of 33 articles were qualified for inclusion. The total number of samples included in the literature was 7195631. The meta-analysis results showed that short-term exposures to PM2.5 (OR=1.0082, 95%CI: 1.0049−1.0116), PM10 (OR=1.0017, 95%CI: 1.0008−1.0026), CO (OR=1.0328, 95%CI: 1.0231−1.0426), NO2 (OR=1.0150, 95%CI: 1.0079−1.0222), SO2 (OR=1.0158, 95%CI: 1.0078-1.0238), and O3 (OR=1.0017, 95%CI: 1.0003−1.0032) were associated with an increased risk of IS. PM10 and O3 increased the risk of IS in both lag0 and lag1, while PM2.5, CO, NO2, and SO2 all showed an associated increased risk of IS only in lag0. The results of sensitivity analysis showed stable results for all pollutants studied, and there was no publication bias in the literature on the association of the remaining five pollutants with IS incidence except for the PM2.5-related literature.

    Conclusion

    Short-term exposures to PM2.5, PM10, CO, NO2, SO2, and O3 may increase the incidence of IS, with this risk showing the most significant level on the day of IS onset.

     

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