Ambient Air Pollution and Hospitalizations for Ischemic Stroke: A Time Series Analysis Using a Distributed Lag Nonlinear Model in Chongqing, China - Chen, Hao; Cheng, Zheng; Li, Mengmeng; Luo, Pan; Duan, Yong; Fan, Jie; Xu, Ying; Pu, Kexue; Zhou, Li (Frontiers in Public Health, 2022)
Study investigating the effect of air pollution on hospitalization for ischemic stroke (IS) is mostly conducted in high-income counties and often produces inconsistent results. Our study aimed to explore the association between short-term exposure to air pollution and IS in Chongqing, China. This time-series study included 2,299 IS inpatients from three hospitals in Chongqing from January 2015 to December 2016. The Poisson generalized linear regression model and the distributed lag non-linear model (DLNM) were used to investigate the impact of air pollution and meteorological factors on the hospitalization for IS. Furthermore, stratification analysis was implemented by sex, age and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95%CI: 0.4%-2.1%, lag3) and 3.6% (95%CI: 0.5%-6.7%, lag05) for each 10 µg/m³ increase in PM2.5; 1.0% (95%CI: 0.3%-1.7%, lag3) and 2.9% (95%CI: 0.6%-5.2%, lag05) for each 10 µg/m³ increase in PM10; 4.8% (95%CI: 0.1%-9.7%, lag4) for each 10 µg/m³ increase in SO2; 2.5% (95%CI: 0.3%-4.7%, lag3) and 8.2% (95%CI: 0.9%-16.0%, lag05) for each 10 µg/m³ increase in NO2; 0.7% (95%CI: 0.0%-1.5%, lag6) for each 10 µg/m³ increase in O3. The effect of PM2.5, PM10, NO2, and SO2 exposure remained statistically significant in cold season subgroups, while no modifying effect of season, sex or age were detected. Our findings suggest that short-term exposure to PM2.5, PM10, SO2, NO2, and O3 may increase hospitalization rates for IS, and the government should take action to address the air pollution issues.