Ambient high temperature and mortality in Jinan, China: A study of heat thresholds and vulnerable populations

Abstract Background Understanding the health consequences of continuously rising temperatures—as is projected for China—is important in terms of developing heat-health adaptation and intervention programs. This study aimed to examine the association between mortality and daily maximum (T max ), mean (T mean ), and minimum (T min ) temperatures in warmer months; to explore threshold temperatures; and to identify optimal heat indicators and vulnerable populations. Methods Daily data on temperature and mortality were obtained for the period 2007–2013. Heat thresholds for condition-specific mortality were estimated using an observed/expected analysis. We used a generalised additive model with a quasi-Poisson distribution to examine the association between mortality and T max /T min /T mean values higher than the threshold values, after adjustment for covariates. Results T max /T mean /T min thresholds were 32/28/24 °C for non-accidental deaths; 32/28/24 °C for cardiovascular deaths; 35/31/26 °C for respiratory deaths; and 34/31/28 °C for diabetes-related deaths. For each 1 °C increase in T max /T mean /T min above the threshold, the mortality risk of non-accidental-, cardiovascular-, respiratory, and diabetes-related death increased by 2.8/5.3/4.8%, 4.1/7.2/6.6%, 6.6/25.3/14.7%, and 13.3/30.5/47.6%, respectively. Thresholds for mortality differed according to health condition when stratified by sex, age, and education level. For non-accidental deaths, effects were significant in individuals aged ≥65 years (relative risk=1.038, 95% confidence interval: 1.026–1.050), but not for those ≤64 years. For most outcomes, women and people ≥65 years were more vulnerable. Conclusion High temperature significantly increases the risk of mortality in the population of Jinan, China. Climate change with rising temperatures may bring about the situation worse. Public health programs should be improved and implemented to prevent and reduce health risks during hot days, especially for the identified vulnerable groups.