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Short-term associations between ambient air pollution and stroke hospitalisations: time-series study in Shenzhen, China.


ABSTRACT: OBJECTIVE:To investigate the association between ambient air pollution and stroke morbidity in different subgroups and seasons. METHODS:We performed a time-series analysis based on generalised linear models to study the short-term exposure-response relationships between air pollution and stroke hospitalisations, and conducted subgroup analyses to identify possible sensitive populations. RESULTS:For every 10?µg/m3 increase in the concentration of air pollutants, across lag 0-3 days, the relative risk of stroke hospitalisation was 1.029 (95% CI 1.013 to 1.045) for PM2.5, 1.054 (95% CI 1.031 to 1.077) for NO2 and 1.012 (95% CI 1.002 to 1.022) for O3. Subgroup analyses showed that statistically significant associations were found in both men and women, middle-aged and older populations, and both cerebral infarction and intracerebral haemorrhage. The seasonal analyses showed that statistically significant associations were found only in the winter. CONCLUSIONS:Our study indicates that short-term exposure to PM2.5, NO2 and O3 may induce stroke morbidity, and the government should take actions to mitigate air pollution and protect sensitive populations.

SUBMITTER: Guo Y 

PROVIDER: S-EPMC7103818 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Short-term associations between ambient air pollution and stroke hospitalisations: time-series study in Shenzhen, China.

Guo Yanfang Y   Xie Xiufang X   Lei Lin L   Zhou Haibin H   Deng Shizhou S   Xu Ying Y   Liu Zheng Z   Bao Junzhe J   Peng Ji J   Huang Cunrui C  

BMJ open 20200319 3


<h4>Objective</h4>To investigate the association between ambient air pollution and stroke morbidity in different subgroups and seasons.<h4>Methods</h4>We performed a time-series analysis based on generalised linear models to study the short-term exposure-response relationships between air pollution and stroke hospitalisations, and conducted subgroup analyses to identify possible sensitive populations.<h4>Results</h4>For every 10 µg/m<sup>3</sup> increase in the concentration of air pollutants, a  ...[more]

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