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山东大学学报 (医学版) ›› 2023, Vol. 61 ›› Issue (2): 117-124.doi: 10.6040/j.issn.1671-7554.0.2022.0886

• 公共卫生与管理学 • 上一篇    下一篇

极端气温对淄博市居民非意外死亡和寿命损失年的影响

刘盈1,房启迪1,韩闯1,程传龙1,杨淑霞2,崔峰2,李秀君1   

  1. 1.山东大学齐鲁医学院公共卫生学院生物统计学系, 山东 济南 250012;2.淄博市疾病预防控制中心, 山东 淄博 255026
  • 发布日期:2023-02-17
  • 通讯作者: 李秀君. E-mail:xjli@sdu.edu.cn崔峰. E-mail:cuifeng@126.com
  • 基金资助:
    国家自然科学基金(81673238);国家重点研发计划(2019YFC1200500,2019YFC1200502)

Effects of extreme temperature on non-accidental death and years of life lost in Zibo City

LIU Ying1, FANG Qidi1, HAN Chuang1, CHENG Chuanlong1, YANG Shuxia2, CUI Feng2, LI Xiujun1   

  1. 1. Department of Biostatistics, School of Public Heath, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Zibo Center for Disease Control and Prevention, Zibo 255026, Shandong, China
  • Published:2023-02-17

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摘要： 目的 探讨极端气温对非意外死亡数和早死所致的寿命损失年(YLL)的影响,以期为疾病预防控制以及卫生决策提供科学参考。 方法 收集和整理2015至2019年山东省淄博市逐日非意外死亡资料和气象资料,计算逐日YLL,采用分布滞后非线性模型(DLNM)分析极端低温和极端高温［分别定义为研究期间日均气温分布的第2.5(-4.2 ℃)和97.5百分位数(29.1 ℃)］对非意外死亡数和YLL的滞后效应,并识别脆弱人群。 结果 研究期间,淄博市共报告了144 310例非意外死亡,YLL为1 886 493年。极端低温对非意外死亡的影响具有一定的滞后性,单日和累积滞后效应分别在暴露第4和21天最大［死亡的相对危险度(RR)分别为1.05(95%CI:1.04~1.07)和1.23(95%CI:1.10~1.39);YLL的变化值分别为56.51(95%CI:37.92~75.11)和259.55(95%CI:116.45~402.65)年］;极端高温的影响较为短促,单日和累积滞后效应分别在暴露当天和第7天最大［死亡的RR分别为1.19(95%CI:1.15~1.24)和1.45(95%CI:1.34~1.57);YLL的变化值分别为137.34(95%CI:93.37~181.30)和265.90(95%CI:175.05~356.74)年］。男性和<65岁人群对极端低温更敏感,女性和≥65岁人群对极端高温更敏感。 结论 极端气温可增加本地区居民非意外死亡的死亡风险和YLL,其中极端高温对人群的影响更强,女性和≥65岁人群对极端高温更敏感。应加强极端天气预报预警能力和相关健康知识的宣传教育力度,并对脆弱人群实行有针对性的公共卫生干预策略。

关键词: 极端气温, 非意外死亡, 寿命损失年, 滞后效应, 累积效应

Abstract: Objective To investigate the effects of extreme temperature on non-accidental death counts and years of life lost(YLL), so as to provide scientific evidence for disease prevention and control and health decision-making. Methods The daily non-accidental death and meteorological data of Zibo City from 2015 to 2019 were collected and collated, and daily YLL were calculated. The lag effects of extreme low temperature and extreme high temperature, which were defined as the 2.5(-4.2 ℃)and 97.5 percentile(29.1 ℃)of the mean daily temperature distribution on non-accidental death counts and YLL were analyzed by using distributed lag nonlinear model(DLNM), and vulnerable groups were identified. Results A total of 144,310 non-accidental death counts were reported in Zibo City during the study period, and the YLL was 1,886,493 years. The effects of extreme low temperature on non-accidental death had a lag time, and the single and cumulative lag effects peaked at days 4 and 21 after exposure, with relative risk(RR)of death being 1.05(95%CI: 1.04-1.07)and 1.23(95%CI: 1.10-1.39), and the changes of YLL being 56.51(95%CI: 37.92-75.11)and 259.55(95%CI: 116.45-402.65)years, respectively. The effects of extreme high temperature were more short-term, and the single and cumulative lag effects peaked at days 0 and 7 after exposure, with RR of death being 1.19(95%CI: 1.15-1.24)and 1.45(95%CI: 1.34-1.57), and the changes of YLL being 137.34(95%CI: 93.37-181.30)and 265.90(95%CI: 175.05-356.74)years, respectively. Men and young people(<65 years)were more sensitive to extreme low temperature, and women and the elderly(≥65 years)were more sensitive to extreme high temperature. Conclusion Extreme temperature can increase the risk and YLL of non-accidental death for local residents. Extreme high temperature has a stronger effect on population, and women and people aged ≥65 years are more susceptible to it. It is necessary to strengthen the ability of extreme weather forecast and early warning and the propaganda of relevant health knowledge, and implement targeted public health intervention strategies for vulnerable populations.

Key words: Extreme temperature, Non-accidental death, Years of life lost, Lag effects, Cumulative effects

中图分类号: 

  • R122.2+1
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