CAJ | 학술논문

目的探索气温-死亡关系模型中最适温度指标.方法收集2006-2010年广州市死亡和气象资料,采用分布滞后非线性模型分别拟合不控制相对湿度下的和控制相对湿度下的日最高、日平均和日最低气温,以及相应的体感温度和热指数与死亡人数的关系.先对各模型的标准化残差进行分位数图(Q-Q图)正态性检验以定性评估模型的拟合优度,再根据赤池信息量准则值(AIC)和残差平方和值(RSS)最小原则,探索最适宜的建模温度指标.并进一步分析不同疾病别、年龄别及冷热效应的最适温度指标.结果广州属亚热带季风气候,全年平均气温为22.9℃,日平均相对湿度为71％.各模型的标准化残差均呈正态分布.总死亡人数、因循环系统疾病死亡人数、65～ 84岁人群和冷效应模型用日平均温度拟合较合适,其AIC( RSS)值最小,分别为11 537(1897)、9527(1928)、10 595(2018)和11 523(1899).因呼吸系统疾病死亡人数、＜65岁、≥85岁人群和热效应模型用日平均体感温度拟合的AIC(RSS)值最小,分别为8265(1854)、8675 (1739)、8550( 1871)和11 687(1938).相对于同时控制温度和相对湿度,不同疾病别、年龄别以及冷热效应均用体感温度指标拟合模型的AIC( RSS)值较小.选择日最高温度研究冷效应在滞后0～3d的RR值均＜1,而日最低温度RR值均＞1.04.选择日最高温度研究热效应在滞后0～1d时RR值均＜1.16,而日最低温度和日平均温度RR值均＞1.16.结论针对不同疾病、年龄死亡人群及冷、热效应的气温-死亡关系模型没有一个统一的最适温度指标；用体感温度指标比将湿度作为协变量引入模型效果更好.相对于日最高和日最低气温,日平均气温更能反映人群对温度的暴露.
목적 탐색기온-사망관계모형중최괄온도지표.방법 수집2006-2010년엄주시사망화기상자료,채용분포체후비선성모형분별의합불공제상대습도하적화공제상대습도하적일최고、일평균화일최저기온,이급상응적체감온도화열지수여사망인수적관계.선대각모형적표준화잔차진행분위수도(Q-Q도)정태성검험이정성평고모형적의합우도,재근거적지신식량준칙치(AIC)화잔차평방화치(RSS)최소원칙,탐색최괄의적건모온도지표.병진일보분석불동질병별、년령별급랭열효응적최괄온도지표.결과 엄주속아열대계풍기후,전년평균기온위22.9℃,일평균상대습도위71％.각모형적표준화잔차균정정태분포.총사망인수、인순배계통질병사망인수、65～ 84세인군화랭효응모형용일평균온도의합교합괄,기AIC( RSS)치최소,분별위11 537(1897)、9527(1928)、10 595(2018)화11 523(1899).인호흡계통질병사망인수、＜65세、≥85세인군화열효응모형용일평균체감온도의합적AIC(RSS)치최소,분별위8265(1854)、8675 (1739)、8550( 1871)화11 687(1938).상대우동시공제온도화상대습도,불동질병별、년령별이급랭열효응균용체감온도지표의합모형적AIC( RSS)치교소.선택일최고온도연구랭효응재체후0～3d적RR치균＜1,이일최저온도RR치균＞1.04.선택일최고온도연구열효응재체후0～1d시RR치균＜1.16,이일최저온도화일평균온도RR치균＞1.16.결론 침대불동질병、년령사망인군급랭、열효응적기온-사망관계모형몰유일개통일적최괄온도지표；용체감온도지표비장습도작위협변량인입모형효과경호.상대우일최고화일최저기온,일평균기온경능반영인군대온도적폭로.
Objective To explore the suitable temperature index to establish temperature-mortality model.Methods The mortality and meteorological information of Guangzhou between year 2006 and 2010 were collected to explore the association between sendible temperature,heat index and deaths by adopting distributed lag non-linear model to fit the daily maximum,mean and minimum temperature with and without humidity.Q-Q plots based on the standardized residuals of each model were used to qualitatively access the goodness of fitting.The minimum Akaike information criterion (AIC) and residual sum of squares (RSS) value were used to explore the most suitable temperature index for model establishment,and to further analyze the fittest temperature index for different diseases,ages and cold and hot effect.Results Guangzhou features a subtropical monsoon climate,with an annual average temperature at 22.9 ℃ and daily average relative humidity of 71％.The standardized residuals of all models followed normal distribution.For all death,death from circulation system diseases,the 65 - 84 years old aging groups and cold effect models,the daily average temperature fit better,whose AIC(RSS) values were the smallest as 11 537 (1897),9527( 1928),10 595 (2018) and 11 523 ( 1899),respectively.However,for death from respiratory system disease,groups aging under 65 years old or over 85 years old and hot effect models,the daily average sendible temperature fit better,whose AIC(RSS) values were the smallest as 8265 (1854),675 (1739),8550(1871) and 11 687 (1938),respectively.In comparison with the model controlling both temperature and relative humidity,different diseases,aging groups and cold and hot effect models fitted by sendible temperature index showed smaller AIC (RSS) values.The relative risk (RR) value of the cold effect lagging 0 -3 days fitting by daily maximal temperature was ＜ 1,and the RR value of it fitting by daily minimum temperature was ＞ 1.04.The RR value of the hot effect lagging 0 - 1 days fitting by daily maximal temperature was ＜ 1.16,and the RR values of it fitting by daily minimum temperature and daily average temperature were ＞ 1.16.Conclusion There were no best temperature indicators for different diseases,ages and cold and hot effect.The model using sendible temperature index better fit the model including relative humidity as a covariable.