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 (PM_2.5) 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 PM_2.5, nitrogen dioxide (NO₂) and sulphur dioxide (SO₂). We used distributed lag nonlinear models to explore nonlinear and lag effects of PM_2.5. In single-pollutant models, PM_2.5 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 PM_2.5 and HAs on high-temperature days was generally stronger than that on low-temperature days. This study indicated that PM_2.5 can increase HA rates for these chronic diseases, and effects of PM_2.5 on high-temperature days were stronger than that on low-temperature days.