This study assessed the impact of various temperature indices, including mean temperature (MT), diurnal temperature range (DTR), and temperature changes between neighboring days (TCN) on hospitalization rates for cardiovascular system diseases among residents of Zhangye City, a typical western city in China. The Quasi-Poisson generalized additive regression model (GAM) in conjunction with a distributed lag nonlinear model (DLNM) was applied to estimate the association of temperature indices with CVD hospitalization rates in Zhangye City during the periods of 2015-2021. The exposure-response relationship and relative risk were discussed and stratified analyses by age and gender were conducted. We found that the hospitalization rates of cardiovascular disease (CVD) patients in Zhangye City was significantly related to different temperature indicators (MT, DTR, TCN). Both low and high MT, DTR, and TCN increased the risk of cardiovascular disease (CVD) among residents. Besides, different demographic populations exhibited distinct sensitivities to temperature conditions. Relevant authorities should devise corresponding preventive and control measures to protect vulnerable populations.
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