Abstract
Evidence from megacity registry data regarding the independent association between ambient temperature and cardiovascular disease (CVD) mortality, after accounting for Particulate Matter 2.5 (PM(2.5)), remains scarce. In this study, we collected 308,116 CVD mortality cases in Shanghai from 2015 to 2020. The distributed lag non-linear model (DLNM) was utilized. The daily PM(2.5) concentration was transformed using a natural spline (ns) function and integrated into the model for adjustment. The DLNM analysis revealed that the exposure-response curve between daily temperature and CVD mortality approximated an inverted "J" shape, consistent for both women and men. The minimum mortality temperature (MMT) for total CVD mortality was 25 °C, with an MMT of 26 °C for females and 24 °C for males. The highest relative risk (RR) of CVD mortality was 2.424 [95% confidence interval (95% CI): 2.035, 2.887] at the lowest temperature of -6.1 °C, with 2.244 (95% CI: 1.787, 2.818) for female and 2.642 (95% CI: 2.100, 3.326) for male. High temperatures exert acute and short-term effects, with the peak risk occurring on the day of exposure. In contrast, the risk from low temperature peaks on day 3 of the lag time and subsequently declines until days 16-21. This study offers evidence-based support for the prevention of temperature-induced CVD mortality.