Abstract:Combining the Distributed Lag Non-linear Model (DLNM) and the Generalized Additive Model (GAM), based on controlling the impacts of the COVID-19, holiday effect, week effect, long-term trend, air pollution factors and other mixed factors, this study explored the exposure response relationship between the daily maximum temperature in Nanjing and the number of local patients with bronchial and cardiovascular diseases from 2018 to 2020, including the lag effect and cumulative effect. Results indicate that for bronchial diseases, winter is a high-risk period, and the immediate and cumulative effects of low temperature are significant; under the short-term cumulative effect, the lower the temperature, the greater the danger; under long-term accumulation, the danger is the highest at around 10 ℃; the cumulative effect of high temperature is not significant, and the hysteresis effect is significant around 30 ℃. For cardiovascular diseases, the immediate and cumulative effects of low temperature are significant, with the cumulative and sustained effects being the strongest around 11-12 ℃; the hysteresis effect of high temperature is significant, and the higher the temperature, the more pronounced the hysteresis effect; the risk of illness increases rapidly when exposed to high temperature environments for a long time, with the cumulative risk of exposure being highest at around 32 ℃ per day. For these two types of diseases, the highest temperature on the day ranges from 22 to 24 ℃, which is the most comfortable temperature for the human body.