Liu Tao, Zhou Chunliang, Zhang Haoming, Huang Biao, Xu Yanjun, Lin Lifeng, Wang Lijun, Hu Ruying, Hou Zhulin, Xiao Yize, Li Junhua, Xu Xiaojun, Jin Donghui, Qin Mingfang, Zhao Qinglong, Gong Weiwei, Yin Peng, Xu Yiqing, Hu Jianxiong, Xiao Jianpeng, Zeng Weilin, Li Xing, Chen Siqi, Guo Lingchuan, Rong Zuhua, Zhang Yonghui, Huang Cunrui, Du Yaodong, Guo Yuming, Rutherford Shannon, Yu Min, Zhou Maigeng, Ma Wenjun
Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China.
Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China.
Innovation (Camb). 2020 Dec 16;2(1):100072. doi: 10.1016/j.xinn.2020.100072. eCollection 2021 Feb 28.
Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013-2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006-2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65-74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics.
尽管众多研究调查了可归因于温度的过早死亡,但温度对寿命损失年数(YLL)的影响仍不明确。我们估计了温度与YLL之间的关系,并量化了中国因温度导致的每例死亡的YLL。我们收集了每日气象和死亡率数据,并计算了中国364个地点(云南省、广东省、湖南省、浙江省和吉林省为2013 - 2017年,其他地点为2006 - 2011年)的每日YLL值。首先采用具有分布滞后非线性模型的时间序列设计来估计温度与YLL率(YLL/10万人口)之间的特定地点关联,并使用多变量荟萃分析模型汇总特定地点关联。然后,计算因温度导致的每例死亡的YLL。温度与YLL率始终呈现U形关联。平均每例死亡有1.02(95%置信区间:0.67,1.37)个YLL可归因于温度。低温导致每例死亡0.98个YLL,其中大部分来自中度寒冷(0.84)。与患有呼吸系统疾病的人(0.47)、女性(0.87)、老年人(≥75岁人群为0.85)以及中国北方(0.64)或南方(1.19)相比,患有心血管疾病的人(1.14)、男性(1.15)、较年轻年龄组(65 - 74岁人群为1.31)以及中国中部地区(1.34)的平均每例死亡YLL更高。死亡率负担受到年温度和温度变异性、相对湿度、纬度、经度、海拔、教育程度以及集中供暖使用情况的影响。在中国,温度导致每例死亡有大量的YLL,且受到人口统计学和地区特征的影响。