中国非适宜气温相关的疾病负担评估研究

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

目的定量评估我国非适宜气温相关的超额死亡数。方法运用2013—2018年中国239个区县的气象和全死因的数据, 采用时间序列研究的分布滞后非线性模型构建气温与死亡的暴露-反应关系模型;然后采用2015年中国2 900个区县的气温数据和人口数据评估非适宜气温和低温、高温相关的超额死亡数, 并描述其空间分布。结果 2013—2018年中国239个区县的全死因总死亡数达503.59万例, 各区县平均每日死亡(12±8)例;各区县的日平均气温为(14.98±10.31)℃, 日平均相对湿度为(68.79±17.25)%, 日平均O3浓度为(58.95±34.96)μg/m^(3), 日平均PM2.5浓度为(54.97±45.56)μg/m^(3)。日均气温与全死因死亡数的效应曲线呈现"U"形, 曲线上最低死亡风险气温(MMT)为21.60 ℃;当气温高于MMT时, 随气温升高热效应上升;当气温低于MMT时, 随气温降低冷效应上升。非适宜气温死亡归因分值(AF)为8.76 %(95%CI:8.07%~9.10%), 低温、高温的AF分别为7.21%(95%CI:6.51%~7.57%)、1.55%(95%CI:1.46%~1.61%)。2015年中国非适宜气温相关的超额死亡数为519 122例, 其中低温相关的超额死亡数占72.98%。非适宜气温相关的超额死亡数主要呈现从东部向西部地区逐渐减少的趋势, 华东地区非适宜气温相关的超额死亡例数较多(117 522例);黑龙江(东北地区)低温相关的超额死亡例数较多(26 924例), 广东(华南地区)高温相关的超额死亡例数较多(27 763例)。结论中国非适宜气温相关的疾病负担较重, 且存在明显的空间分布差异。

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/m^(3),and the daily average PM2.5 concentration was(54.97±45.56)μg/m^(3).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 519122,72.98%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(117522)in East China.Heilongjiang Province(in Northeast China)had the most excess deaths(26924)caused by low temperature,and Guangdong Province(in South China)had the most excess deaths(27763)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.