[Assessment of disease burden related to non-optimal temperature across China]

Objective: To estimate the excess mortality attributed to non-optimal ambient temperature in China. Methods: Mortality data and meteorological data from 239 counties in 2013-2018 were collected to simulate the quantitative exposure-response relationship between the temperature and mortality using distributed lag nonlinear models for time series studies. Then the number of non-optimal-temperature-related excess deaths was assessed and the spatial distribution was explored. Results: There were averagely (12±8) cases of all-cause deaths per day per county from 2013 to 2018. The average daily temperature was (14.98±10.31)℃, and the daily average relative humidity was (68.79±17.25)%. The daily average O₃ concentration was (58.95±34.96) μg/m³, and the daily average PM_2.5 concentration was (54.97±45.56) μg/m³. The exposure-response curve between daily average temperature and all-cause mortality showed a "U" shape, and the theoretical minimum mortality temperature (MMT) corresponding to the minimum number of deaths was 21.60 ℃. When the temperature was higher than MMT, the heat-related health effect increased with the temperature rising. When the temperature was lower than MMT, the cold-related effect increased with the temperature decreasing. The attributable fraction (AF) of death caused by non-optimal temperature was 8.76% (95%CI: 8.07%-9.10%), and the AF of death caused by cold effect and heat effect was 7.21% (95%CI: 6.51%-7.57%) and 1.55% (95%CI: 1.46%-1.61%), respectively. The excess deaths from non-optimal temperature in 2015 were 519 122, 72.98% of which could be attributed to low temperature. The number of excess deaths caused by non-optimal temperature mainly showed a decreasing trend from the east to the west, relatively high (117 522) in East China. Heilongjiang Province (in Northeast China) had the most excess deaths (26 924) caused by low temperature, and Guangdong Province(in South China) had the most excess deaths (27 763) caused by high temperature. Conclusion: The non-optimal temperature has a significant impact on health and causes a considerable burden of disease in China with obvious spatial heterogeneity.