Association Between the Ambient Fine Particulate Pollution and the Daily Internal Medicine Outpatient Visits in Zhoushan, China: A Time-Series Study - Liu, Wen-Yi; Yi, Jing-Ping; Tung, Tao-Hsin; Yan, Jian-Bo (Frontiers in Public Health, 2021)
Abstract Background: There has been a recent worsening of air pollution in China, which poses a huge threat to public health by inducing and promoting circulatory and respiratory diseases. This study aimed to explore the association between concentration to air pollution and internal medicine outpatient numbers registered for treatment of circulatory and respiratory symptoms in Zhoushan, China using a time series method. Methods: We validated and acquired daily internal medicine outpatient records between January 1, 2014, and December 31, 2019, from the Zhoushan Centre for Disease Control and Prevention in Zhejiang. Further, we collected daily average records of ambient air pollutants from the Zhoushan Environmental Monitoring Centre within the same duration. A generalized additive model with natural splines was constructed to explore the association between ambient air pollutants and internal medicine outpatients. Further, we conducted a lag analysis using the distributed lag non-linear model to estimate the time-delayed effects of air pollutants on internal medicine outpatients. Findings: A total of 2,190,258 internal medicine outpatient visits with a mean of 202.4 visits per day were recorded. The non-linear relationships were found among PM2.5, SO2, and daily internal medicine outpatient visits. Overall, PM2.5 was positively correlated with daily internal medicine outpatient visits. Both O3 and SO2 had significant delayed effects on daily internal medical outpatient numbers; however, PM2.5 only showed a short-term risk. Conclusions: Short-term exposure to PM2.5 was associated with an increase in internal medicine outpatient visits for circulatory and respiratory diseases/symptoms in Zhoushan. SO2 and O3 were shown to induce significant effects after a concentration dependent time lag.