Abstract:
Older people are the main representative of vulnerable groups. Age-related laws of the risk, lag period, harvest effect and synergistic effect of non-optimal temperature and PM
2.5 on older people of different ages are not very clear. This study collects the information of 256037 mortality aged 65—104 from 2012 to 2017 in Nantong district, Jiangsu province, where aging rate is the highest in China. The mortality data are divided into 6 groups by age. The Generalized Additive Models (GAM) and Distributed Lag Non-linear Model (DLNM) are adopted to explore the adverse health effects (relative risk, attributable fraction and lag effect) of temperature, PM
2.5 and their synergistic effects on all-cause mortality. The results are as follows: (1) The relative risk and attributable fraction of non-optimal temperature increase continuously with increasing age. Low temperature effect is much more remarkable than that of high temperature. The relative risk and attributable fraction of low temperature are 1.46 and 6.49 times higher than that of high temperature for the group of over 90 years old, respectively. The relative risk and attributable fraction of PM
2.5 first decrease and then increased with increasing age. The main risk factor for the oldest population is low temperature. (2) Effects of low temperature and high temperature have a lag period of 9—12 d and 3—6 d, respectively, but the lag period is irrelevant to age. The lag period of PM
2.5 increases with age. (3) Harvest effect of high temperature is observed in groups under the age of 78, indicating that the effect of high temperature on the population of 78 years and older is not limited to the vulnerable group and is not dependent on illness. (4) Effects of synergies between non-optimal temperature and PM
2.5 reveal that mortality increases with higher and lower temperature and PM
2.5, but the range fluctuates with age. Low temperature is more dangerous than high temperature and high PM
2.5. These results provide a reference for establishing strategies to handle risk factors of the atmospheric environment for the population of different ages. However, note that the conclusion is not universal because this study is limited to the situation in Nantong.