2018—2022年南昌市极端气温对居民脑卒中死亡风险影响  

Influence of extreme temperatures on stroke mortality risk among residents of Nanchang city between 2018 and 2022

作　　者：胡茂红[1] 熊文艳[1] 戚京城[1] 刘宇虹 罗彧 廖辉 HU Maohong;XIONG Wenyan;QI Jingcheng;LIU Yuhong;LUO Yu;LIAO Hui(Nanchang Center for Disease Control and Prevention,Nanchang,330038,China)

机构地区：[1]南昌市疾病预防控制中心,南昌330038

出　　处：《中国公共卫生》2025年第1期88-94,共7页Chinese Journal of Public Health

基　　金：江西省卫生健康委科技计划项目(202510741)。

摘　　要：目的了解江西省南昌市2018—2022年极端气温对居民脑卒中死亡风险的影响,为制定相应的预防措施和健康政策提供数据支持。方法收集中国疾病预防控制中心人口死亡登记信息系统中2018年1月1日—2022年12月31日南昌市居民脑卒中死因数据以及南昌市同期大气污染物和气象数据资料,通过广义相加模型(GAM)结合分布滞后非线性模型(DLNM)分析极端气温对居民脑卒中死亡风险的累积滞后效应,并对不同性别、年龄和脑卒中亚型居民进行亚组分析以确定敏感人群。结果南昌市2018—2022年累计报告脑卒中死亡23630例,其中出血性脑卒中12269例,缺血性脑卒中11361例。南昌市日均气温与居民脑卒中死亡之间分布关系呈近似“J”形曲线,最低死亡风险气温(MMT)为8.5℃。DLNM分析结果显示,极端高温对居民脑卒中死亡风险效应在当日(lag0 d)达最大,滞后累积相对危险度(cumRR)值为1.328(95%CI=1.136~1.553),且持续到lag2 d后其差异无统计学意义(P>0.05);极端低温对居民脑卒中死亡风险效应具有滞后性,在lag6 d达到最大,cumRR值为1.031(95%CI=1.013~1.049)。亚组分析结果显示,极端高温对各亚组居民脑卒中死亡风险效应分布趋势相似且均以lag0 d的效应为最大,其中男性居民cumRR值[1.389(95%CI=1.149~1.679)]高于女性居民cumRR值[1.263(95%CI=1.027~1.553)],<60岁居民cumRR值[1.166(95%CI=0.844~1.611)]低于≥60岁居民cumRR值[1.373(95%CI=1.158~1.630)],出血性脑卒中患者cumRR值[1.316(95%CI=1.090~1.589)]高于缺血性脑卒中患者cumRR值[1.305(95%CI=1.059~1.601)];极端低温时男性居民lag5 d的cumRR值[1.033(95%CI=1.013~1.054)]高于女性居民lag7d的cumRR值[1.032(95%CI=1.004~1.060)],<60岁居民lag5 d的cumRR值[1.042(95%CI=1.005~1.079)]高于≥60岁居民lag6 d的cumRR值[1.028(95%CI=1.010~1.046)],出血性脑卒中患者lag6 d的cumRR值[1.045(95%CI=1.015~1.076)]高于缺血性脑卒中患者lag6 d的cumRR值[1.026(95%CI=1.003~1.04Objective To understand the impact of extreme temperatures on the risk of stroke mortality among residents in Nanchang city,Jiangxi province,from 2018 to 2022,and to provide data support for the formulation of corresponding preventive measures and health policies.Methods Data on stroke mortality among Nanchang residents from January 1,2018,to December 31,2022,as well as data on air pollutants and meteorology in Nanchang during the same period,were collected from the Chinese Center for Disease Control and Prevention’s Population Mortality Registration Information System.A generalized additive model(GAM)combined with a distributed lag non-linear model(DLNM)was used to analyze the cumulative lag effect of extreme temperatures on the risk of stroke mortality among residents.Subgroup analyses were conducted for different genders,ages,and stroke subtypes to identify sensitive populations.Results A total of 23630 stroke deaths were reported in Nanchang city from 2018 to 2022,including 12269 hemorrhagic strokes and 11361 ischemic strokes.The distribution relationship between daily average temperature and stroke mortality in Nanchang city showed an approximate"J"shaped curve,with the minimum mortality temperature(MMT)being 8.5°C.DLNM analysis showed that the effect of extreme high temperature on the risk of stroke mortality reached its peak on the same day(lag0 d),with a cumulative relative risk(cumRR)of 1.328(95%CI:1.136-1.553),and the difference was not statistically significant after lag2 d(P>0.05).The effect of extreme low temperature on the risk of stroke mortality had a lag effect,reaching its peak at lag6 d,with a cumRR of 1.031(95%CI:1.013-1.049).Subgroup analysis showed that the distribution trends of the effects of extreme high temperature on the risk of stroke mortality in each subgroup were similar,and all reached their peak at lag0 d.The cumRR for males[1.389(95%CI:1.149-1.679)]was higher than that for females[1.263(95%CI:1.027-1.553)],the cumRR for residents<60 years old[1.166(95%CI:0.844-1.611)]was lower

关 键 词：脑卒中 死亡风险 极端气温 影响 分布式滞后非线性模型(DLNM) 南昌市 

分 类 号：R743.3[医药卫生—神经病学与精神病学] R122.21[医药卫生—临床医学]