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Abstract Given the backdrop of global climate change, future temperatures are anticipated to exhibit increased variability and extremity, amplifying health risks and the burden of diseases, a matter of heightened concern. The aim of this research was to evaluate the mortality risk associated with cardiovascular diseases (CVD) due to suboptimal temperatures (daily mean temperature) and temperature variations (diurnal temperature range). Daily data spanning from 2014 to 2020 in Wuhu City were gathered, encompassing meteorological factors, environmental pollutants, and cardiovascular disease mortality information, involving 64,758 CVD deaths. Time-series analyses were conducted utilizing generalized additive models (GAM) and distributed lag nonlinear models (DLNM). Burden analysis was executed to estimate the percentage and count of daily CVD deaths linked to daily mean temperature (DMT) and diurnal temperature range (DTR). Lastly, a sensitivity analysis was conducted to assess the robustness of the model. A horizontal S-shaped relationship exists between DMT and CVD mortality rate, where both high and low temperatures exhibit adverse effects, with high temperatures demonstrating a more pronounced impact than low temperatures. An inverted J-shaped relationship exists between DTR and mortality, wherein extreme DTR elevates the risk of CVD mortality. Variations in exposure responses occur among populations with diverse characteristics. The main cause of death burden is moderately high temperature rather than extreme temperature. Importantly, non-extreme temperatures account for the majority of cardiovascular disease deaths, potentially exerting serious adverse effects on local public health.
Zhang et al. (Tue,) studied this question.