Interactive effect between temperature and fine particulate matter on chronic disease hospital admissions in the urban area of Tianjin, China

This study focuses on effects of fine particulate matter (PM2.5) on chronic disease under different levels of temperature. We obtained type 2 diabetes, cerebral stroke and coronary heart disease hospital admissions (HAs) from five hospitals in urban Tianjin as well as the concentrations of PM2.5, nitrogen dioxide (NO2) and sulphur dioxide (SO2). We used distributed lag nonlinear models to explore nonlinear and lag effects of PM2.5. In single-pollutant models, PM2.5 was positively associated with type 2 diabetes, cerebral stroke and coronary heart disease HAs, with strongest effects at lag1, lag0 and lag06, respectively. The corresponding relative risk rates (RR%) were 1.836%, 2.083% and 6.428%. In co-pollutant models, the correlation between PM2.5 and HAs on high-temperature days was generally stronger than that on low-temperature days. This study indicated that PM2.5 can increase HA rates for these chronic diseases, and effects of PM2.5 on high-temperature days were stronger than that on low-temperature days.