摘要
目的探讨隔日温差(TCN)对呼吸系统疾病死亡的影响,为应对气候变化导致的呼吸系统疾病死亡研究提供依据。方法通过山东省慢病、死因监测综合管理信息系统收集2015—2019年淄博市呼吸系统疾病死亡监测资料,通过中国气象数据网站和中国高分辨率高质量近地表空气污染物数据集分别收集同期气象和空气污染物资料。采用广义相加模型结合分布滞后非线性模型分析TCN对呼吸系统疾病死亡的滞后效应和累积滞后效应,并按性别和年龄进行亚组分析;计算归因分值评估TCN造成的归因风险。结果2015—2019年淄博市报告呼吸系统疾病死亡11767例;其中男性6648例,占56.50%;女性5119例,占43.50%。<65岁1307例,占11.11%;≥65岁10460例,占88.89%。TCN对总人群、女性、≥65岁人群呼吸系统疾病死亡的暴露-反应关系呈单调递增趋势。第95百分位数(P95)TCN(3.84℃)对总人群呼吸系统疾病死亡风险的效应在累积滞后11 d时达到峰值(RR=2.063,95%CI:1.261~3.376);亚组分析结果显示,P95 TCN对女性和≥65岁人群影响更大,累积滞后效应分别在12 d(RR=3.119,95%CI:1.476~6.589)、11 d(RR=2.107,95%CI:1.260~3.523)达到峰值。归因风险分析结果显示,隔日升温可引起呼吸系统疾病死亡归因风险的上升,隔日降温则引起归因风险下降。结论隔日升温增加呼吸系统疾病死亡风险,且对女性和≥65岁人群影响更大。
Objective To investigate the impact of temperature changes between neighboring days(TCN)on the mortali⁃ty risk of respiratory diseases,so as to provide the evidence for the study of deaths from respiratory diseases caused by climate change.Methods The monitoring data of deaths from respiratory diseases in Zibo City from 2015 to 2019 were collected from Shandong Provincial Management Information System for Chronic Diseases and Cause of Death Sur⁃veillance.The meteorological and air pollutant data of the same period were collected from China Meteorological Data Website and ChinaHighAirPollutants dataset.The effect of TCN on the risk of deaths from respiratory diseases was ex⁃amined using a generalized additive model combined with a distributed lag non-linear model,and subgroup analyses for gender and age were conducted.The disease burden attributed to TCN at different intervals was assessed by calculating attributable fraction.Results Totally 11767 deaths from respiratory diseases were reported in Zibo City from 2015 to 2019,including 6648 males(56.50%)and 5119 females(43.50%).There were 1307 deaths aged<65 years(11.11%),and 10460 deaths aged 65 years and older(88.89%).A monotonically increasing exposure-response relation⁃ship was observed between TCN and deaths from respiratory diseases in the general population,females,and the popula⁃tion aged 65 years and older.The 95th percentile of TCN(P95,3.84℃)reached the peak at a cumulative lagged of day 11(RR=2.063,95%CI:1.261-3.376).The results of subgroup analyses showed greater impacts on females and the population aged 65 years and older,with cumulative lagged effects peaking at day 12(RR=3.119,95%CI:1.476-6.589)and day 11(RR=2.107,95%CI:1.260-3.523).The results of attributional risk analysis showed that next-day warming might increase the attributable risk of deaths from respiratory diseases,and next-day cooling might decrease the attribut⁃able risk.Conclusion Next-day warming may increase the mortality risk of respiratory diseases,and has greater im⁃pacts on females and the population aged 65 years and older.
作者
李树芬
倪志松
程传龙
左慧
梁珂梦
宋思豪
席睿
杨淑霞
崔峰
李秀君
LI Shufen;NI Zhisong;CHENG Chuanlong;ZUO Hui;LIANG Kemeng;SONG Sihao;XI Rui;YANG Shuxia;CUI Feng;LI Xiujun(Department of Biostatistics,School of Public Health,Cheeloo College of Medicine,Shandong University,Jinan,Shandong 250012,China;Zibo Center for Disease Control and Prevention,Zibo,Shandong 255026,China)
出处
《预防医学》
2024年第10期842-846,850,共6页
China Preventive Medicine Journal
基金
国家重点研发计划项目(2023YFC2604400)。
关键词
呼吸系统疾病
隔日温差
分布滞后非线性模型
归因风险
respiratory diseases
temperature changes between neighboring days
distributed lag non-linear model
attribut⁃able fraction