Air pollution on daily outpatient visits for diabetes based on time series model / 公共卫生与预防医学

ABSTRACT

Objective To analyze the effect of air pollution on daily outpatient visits for diabetes, and to provide reference for the management of outpatients with diabetes. Methods Data on outpatient visits for diabetes in a hospital between July 1, 2018 to July 31, 2022 were collected. The correlation between air quality and daily outpatient visits due to diabetes was analyzed using distributed lag non-linear model (DLNM). Results The results showed that the increase in the concentrations of PM2.5 and PM10 in the air was related to the increase in the daily outpatient visits for diabetes, with a lagging effect. The accumulative effect in high PM2.5 concentration was statistically significant for both males and females, and the number of outpatients reached the maximum value at lag5 for males and at lag6 for females. The accumulative effect was not statistically significant either at low or high concentrations of PM2.5 in the young and middle-aged population. However，it was statistically significant in the elderly population, especially when exposed to high concentration of PM2.5, the daily outpatient visits increased significantly. Conclusion PM2.5, PM10 and other harmful pollutants in the air have an impact on the daily diabetic outpatients and increase their visits.