您的位置：山东大学 -> 科技期刊社 -> 《山东大学学报（医学版）》

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

PDF (PC)

111

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
[1] 中国气象局国家气候中心. 中国气候公报(2021)[EB/OL].(2022-03-08)[2022-07-10]. http://www.cma.gov.cn/zfxxgk/gknr/qxbg/202203/t20220308_4568477.html.
[2] Mcmichael AJ, Woodruff RE, Hales S. Climate change and human health: present and future risks[J]. Lancet, 2006, 367(9513): 859-869.
[3] Costello AP, Abbas M, Allen AP, et al. Managing the health effects of climate change[J]. The Lancet(British edition), 2009, 373(9676): 1693-1733.
[4] Fu SH, Gasparrini A, Rodriguez PS, et al. Mortality attributable to hot and cold ambient temperatures in India: a nationally representative case-crossover study[J]. PLoS Med, 2018, 15(7): e1002619. doi:10.1371/journal.pmed.1002619.
[5] Chen R, Yin P, Wang L, et al. Association between ambient temperature and mortality risk and burden: time series study in 272 main Chinese cities[J]. BMJ, 2018, 363: k4306. doi: 10.1136/bmj.k4306.
[6] Gasparrini A, Guo Y, Hashizume M, et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study[J]. Lancet, 2015, 386(9991): 369-375.
[7] Zeng W, Lao X, Rutherford S, et al. The effect of heat waves on mortality and effect modifiers in four communities of Guangdong Province, China[J]. Sci Total Environ, 2014, 482-483: 214-221. doi: 10.1016/j.scitotenv.2014.02.049.
[8] Guo Y, Barnett AG, Pan X, et al. The impact of temperature on mortality in Tianjin, China: a case-crossover design with a distributed lag nonlinear model[J]. Environ Health Perspect, 2011, 119(12): 1719-1725.
[9] Huang C, Barnett AG, Wang X, et al. Effects of extreme temperatures on years of life lost for cardiovascular deaths: a time series study in Brisbane, Australia[J]. Circ Cardiovasc Qual Outcomes, 2012, 5(5): 609-614.
[10] Rabl A. Interpretation of air pollution mortality: number of deaths or years of life lost?[J]. J Air Waste Manag Assoc, 2003, 53(1): 41-50.
[11] 贾铁武, 周晓农. 疾病负担(DALY)的评价与应用[J]. 中国寄生虫学与寄生虫病杂志, 2005, 23(5): 304-308.
[12] Zaletel-Kragelj L, Bo?瘙塅ikov J. Methods and tools in public health[M]. Lage: Hans Jacobs Publishing Company, 2010.
[13] Liu T, Zhou C, Zhang H, et al. Ambient temperature and years of life lost: a national study in China[J]. The Innovation, 2021, 2(1): 100072. doi:10.1016/j.xinn.2020.100072.
[14] Odhiambo Sewe M, Bunker A, ingole V, et al. Estimated effect of temperature on years of life lost: a retrospective time-series study of low-, middle-, and high-income regions[J]. Environ Health Persp, 2018, 126(1): 17004.
[15] Cheng J, Ho HC, Su H, et al. Low ambient temperature shortened life expectancy in Hong Kong: a time-series analysis of 1.4 million years of life lost from cardiorespiratory diseases[J]. Environ Res, 2021, 201: 111652. doi:10.1016/j.envres.2021.111652.
[16] 李静. 重庆市主城区气候因素及空气污染对人群疾病负担影响的研究[D]. 北京:中国疾病预防控制中心, 2016.
[17] Altman DG. Statistics notes: interaction revisited: the difference between two estimates[J]. BMJ, 2003, 326(7382): 219. doi:10.1136/bmj.326.7382.219.
[18] Zhao Q, Guo Y, Ye T, et al. Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study[J]. Lancet Planet Health, 2021, 5(7): e415-e425.
[19] Ma W, Yang C, Chu C, et al. The impact of the 2008 cold spell on mortality in Shanghai, China[J]. Int J Biometeorol, 2013, 57(1): 179-184.
[20] Huang Z, Lin H, Liu Y, et al. Individual-level and community-level effect modifiers of the temperature-mortality relationship in 66 Chinese communities[J]. BMJ Open, 2015, 5(9): e009172. doi:10.1136/bmjopen-2015-009172.
[21] Mcgeehin MA, Mirabelli M. The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States[J]. Environ Health Perspect, 2001, 109 Suppl 2(Suppl 2): 185-189.
[22] Wu W, Xiao Y, Li G, et al. Temperature-mortality relationship in four subtropical Chinese cities: a time-series study using a distributed lag non-linear model[J]. Sci Total Environ, 2013, 449: 355-362. doi: 10.1016/j.scitotenv.2013.01.090.
[23] Yang J, Ou C, Guo Y, et al. The burden of ambient temperature on years of life lost in Guangzhou, China[J]. Sci Rep, 2015,5: 12250. doi:10.1018/srep12250.
[24] Wang C, Zhang Z, Zhou M, et al. Nonlinear relationship between extreme temperature and mortality in different temperature zones: a systematic study of 122 communities across the mainland of China[J]. Sci Total Environ, 2017, 586: 96-106. doi: 10.1016/j.scitotenv.2017.01.218.
[25] Ma W, Wang L, Lin H, et al. The temperature-mortality relationship in China: an analysis from 66 Chinese communities[J]. Environ Res, 2015, 137: 72-77. doi:10.1016/J.envres.2014.11.016.
[26] Han J, Liu S, Zhang J, et al. The impact of temperature extremes on mortality: a time-series study in Jinan, China[J]. BMJ Open, 2017,7(4): e014741. doi:10.1136/bmjopen-2016-014741.
[27] Yanovich R, Ketko I, Charkoudian N. Sex differences in human thermoregulation: relevance for 2020 and beyond[J]. Physiology, 2020, 35(3): 177-184.
[28] Yu W, Vaneckova P, Mengersen K, et al. Is the association between temperature and mortality modified by age, gender and socio-economic status?[J]. Sci Total Environ, 2010, 408(17): 3513-3518.
[29] Guo Y, Barnett AG, Tong S. Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?[J]. Environ Res, 2013, 120: 55-62. doi: 10.1016/j.envres.2012.09.001.
[30] 李湉湉, 王情, 孙庆华. 加强环境健康风险预警研究,推动风险预警公共卫生服务[J]. 山东大学学报(医学版), 2021, 59(12): 1-5. LI Tiantian, WANG Qing, SUN Qinghua. Strengthen research on early warning of environmental health risks and promote public health services [J]. Journal of Shandong University(Health Sciences), 2021, 59(12): 1-5.
[1] 郝强,高琦,赵然,王海涛,刘志东,姜宝法. 2014~2016年气温和相对湿度对深圳市5岁以下儿童轮状病毒腹泻的影响[J]. 山东大学学报 (医学版), 2022, 60(2): 89-95.
[2] 陈擎仪,张烜,王娟,孙继伟,曹丹凤, 曹枫林. 妊娠期女性自杀意念的危险因素及其累积效应[J]. 山东大学学报 (医学版), 2021, 59(1): 91-94.
[3] 李京,王创新,胥欣,杨军,王春平,薛付忠,刘起勇. 气温对2007~2013年济南市人群慢性非传染性疾病死亡的归因风险研究[J]. 山东大学学报 (医学版), 2018, 56(8): 76-87.
[4] 张安然,胡文琦,李佳蔚,魏然,马伟. 热浪对居民循环系统疾病死亡影响的病例交叉研究[J]. 山东大学学报 (医学版), 2018, 56(8): 56-62.
[5] 李佳蔚,魏然,张安然,胡文琦,林君芬,马伟. 热带气旋与医院门诊呼吸系统疾病日就诊量的病例交叉研究[J]. 山东大学学报 (医学版), 2018, 56(8): 43-49.
[6] 韩京,张军,周林,房巧玲,刘守钦,张济,张颖. 极端气温对济南市心脑血管疾病死亡的影响[J]. 山东大学学报（医学版）, 2017, 55(11): 71-74.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 2018 《山东大学学报(医学版)》编辑部　
地址:山东大学科技期刊社（济南市历城区山大南路27号山东大学中心校区明德楼B座721室） 电话: 0531-88366918 E-mail: xbyxb@sdu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发