Objective: To estimate the effects of temperature on cardiovascular disease (CVD) deaths in 4 cities-Kunming, Changsha, Guangzhou and Zhuhai, from southern part of China.
Methods: Daily CVD deaths, meteorological and air pollution data were used to explore the association between temperature and mortality. Distributed lag non-linear model was fitted for each city to access the delayed and cumulative effects of low, median and high temperature on CVD deaths. Cold and hot effects of temperature on CVD deaths were then accessed, based on the linear threshold model.
Results: The city-specific exposure-response functions appeared to be non-linear. Temperatures that associated with the lowest mortality for Changsha, Kunming, Guangzhou and Zhuhai were 22.0°C, 20.0°C, 26.0°C, and 25.5°C. The greatest cumulative RRs (95%CI) for CVD deaths of low temperature during the delayed period of the study in the 4 cities were 1.858 (1.089 - 3.170), 1.537 (1.306 - 1.809), 2.121 (1.771 - 2.540) and 1.934 (1.469 - 2.548), while 1.100 (0.816 - 1.483), 1.061 (0.956 - 1.177), 1.134 (1.047 - 1.230) and 1.259 (1.104 - 1.436) for high temperatures in Changsha, Kunming, Guangzhou and Zhuhai respectively. The hot effect was greater than the cold effect on the current days. The hot effect was restricted to the first week, whereas the cold effect increased over the lag days, and then last for 3 - 4 weeks.
Conclusion: The city-specific exposure-response functions appeared to be non-linear. Both high and cold temperatures were associated with increased CVD deaths, but the impact of low temperature was more notable. Cold effect was delayed by several days but last for a longer period than the hot effect did.