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肾综合征出血热发病率与气象因素关系的研究
引用本文:刘静,王洁贞,薛付忠,康殿民,李世伟. 肾综合征出血热发病率与气象因素关系的研究[J]. 中国卫生统计, 2006, 23(4): 326-329
作者姓名:刘静  王洁贞  薛付忠  康殿民  李世伟
作者单位:1. 山东大学公共卫生学院流行病与卫生统计学研究所,250012
2. 山东省疾病预防控制中心,250014
3. 莒南县卫生防疫站,276600
摘    要:目的 探索影响肾综合征出血热发病率的气象因素及其定量关系.方法 运用病例交叉设计思想,对某监测点历年逐月的HFRS疫情资料和气象资料,建立气象因素对HFRS发病率影响的分季节多变量logistic回归模型.结果 影响HFRS流行的主要气象因素,春季为前6个月最低气温、前12个月平均气温、前6个月降雨量、前12个月降雨量、当月平均相对湿度、前3个月平均相对湿度、前3个月平均气压、前6个月平均气压、当月平均风速;夏季为当月平均气温、当月降雨量、前3个月平均相对湿度、前12个月平均相对湿度、前3个月总日照时间、前3个月平均风速;秋季为前6个月平均气温、当月平均相对湿度、当月总日照时间、前3个月平均风速;冬季为前3个月降雨量、前6个月降雨量、前12个月降雨量、当月平均相对湿度、前3个月平均相对湿度、前3个月日照时数、前3个月平均风速.结论 平均气温、降雨量、相对湿度、日照时数、平均气压、风速等气象因素均不同程度地影响HFRS,不同季节各气象变量的作用不同.

关 键 词:肾综合征出血热  气象  病例交叉设计  条件logistic回归

Association Between Incidence of Hemorrhagic Fever with Renal Syndrome (HFRS) and Meteorological Factors
Liu Jing,Wang Jiezhen,Xue Fuzhong,et al.. Association Between Incidence of Hemorrhagic Fever with Renal Syndrome (HFRS) and Meteorological Factors[J]. Chinese Journal of Health Statistics, 2006, 23(4): 326-329
Authors:Liu Jing  Wang Jiezhen  Xue Fuzhong  et al.
Affiliation:Institute of epidemiology and health statistics, School of Public Health, Shandong University 250012, Jinan
Abstract:Objective To quantitatively explore the association between incidence of hemorrhagic fever with renal syndrome(HFRS)and meteorological factors.Methods Case-crossover design was applied to analyze the time series data of incidence rates of HFRS and meteorological variables from the same area.Models of relationship between incidence rates of HFRS and meteorological variables in different seasons were established respectively using conditional logistic regression.Results The spring model retained nine meteorological variables including the mean relative humidity and the mean velocity of wind of the same month,the mean relative humidity and air pressure of the preceding three months,the minimum temperature,total rainfall and mean air pressure of preceding six months,and the total rainfall of the preceding twelve months.The summer model retained the mean temperature and precipitation of the same month,the mean relative humidity,sunlight hours and mean wind velocity of the preceding three months,and the mean relative humidity of the preceding twelve months.The autumn model included mean relative humidity and total hours of sunlight of the same month,mean velocity of wind of preceding three months,and mean temperature of the preceding six months.The winter model included relative humidity of the same month,total rainfall,hours of sunlight,mean relative humidity and mean velocity of wind of the preceding three months,the total rainfall of the preceding six months and the preceding twelve months.Conclusion Meteorological factors such as mean temperature,rainfall,humidity,sunlight,air pressure and velocity of wind were associated with the incidence rates of HFRS,but their effects were not equal in different seasons.
Keywords:HFRS   Meteorology   case - crossover design   Conditional logistic regression
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