Abstract
Many studies have quantified the hospitalization risk for cardiovascular disease (CVD) caused by temperature, but the results of most studies are not consistent. In this study, we evaluate the effect of temperature on CVD hospitalizations. We use a quasi-Poisson regression with a distributed-lag nonlinear model (DLNM) to evaluate the effect of temperature on CVD hospitalizations between July 1, 2015, and October 31, 2017, in Hefei City, China. We found that the cold effect and heat effect of temperature can impact CVD hospital admissions. Compared with the 25th percentile of temperature (10.3°C), the cumulative relative risk (RR) of extremely low temperature (first percentile of temperature, 0.075°C) over lags 0-27days was 0.616 (95% CI 0.423-0.891), and the cumulative RR of moderate low temperature (10th percentile of temperature, 5.16°C) was 1.081 (95% CI 1.019-1.147) over lags 0-7days. Compared with the 75th percentile of temperature (25.6°C), the cumulative RR of extremely high temperature (99th percentile of temperature, 33.7°C) was 1.078 (95% CI 0.752-1.547) over lags 0-27days, and the cumulative RR of moderate-high temperature (90th percentile of temperature, 29.0°C) was 1.015 (95% CI 0.988-1.043) over lag 0day. In the subgroup, the < 65-year group and male were more susceptible to low temperature; however, the ≥ 65-year group and female were more vulnerable to high temperature. The high temperature's impact on CVD hospital admissions was found to be more obvious in female and the ≥ 65-year group compared to male and the < 65-year group. However, the < 65-year group and men are more sensitive to low temperature.
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