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兰州市空气污染对呼吸系统疾病入院人数的影响
引用本文:陶燕,羊德容,兰岚,王洪新,王式功.兰州市空气污染对呼吸系统疾病入院人数的影响[J].中国环境科学,2013,33(1):175-180.
作者姓名:陶燕  羊德容  兰岚  王洪新  王式功
作者单位:1. 兰州大学资源环境学院,甘肃兰州,730000
2. 兰州大学大气科学学院,甘肃兰州,730000
基金项目:国家自然科学基金资助项目(41075102,41005087);国家公益行业专项项目(GYHY201106034)
摘    要:为评价兰州市空气污染对居民呼吸系统疾病日入院人数的影响,采用时间序列半参数广义相加模型(GAM),在控制了长期趋势、“星期几效应”及气象因子等混杂因素的影响后,分析2007~2009年兰州市空气污染物与呼吸系统疾病日入院人数的暴露-反应关系,并按性别和年龄层建立模型.3种空气污染物有一定的滞后效应,PM10滞后2d或5d,SO2滞后3d,NO2在当天或滞后3d对呼吸系统疾病入院人数的相对危险度(RR)值达到最大,其中PM10、SO2和NO2对呼吸系统疾病全人群的RR值分别为1.015、1.049和1.040.年龄£15岁的人群对兰州市空气污染最为敏感,其次为年龄365岁的老年人群;空气污染对男性的影响较女性明显.

关 键 词:空气污染  呼吸系统疾病  时间序列  入院人数  
收稿时间:2012-04-05;

Relationship between air pollutant and respiratory diseases hospitalization in Lanzhou
TAO Yan , YANG De-rong , LAN Lan , WANG Hong-xin , WANG Shi-gong.Relationship between air pollutant and respiratory diseases hospitalization in Lanzhou[J].China Environmental Science,2013,33(1):175-180.
Authors:TAO Yan  YANG De-rong  LAN Lan  WANG Hong-xin  WANG Shi-gong
Institution:1.College of Resources and Environment,Lanzhou University,Lanzhou 730000,China;2.College of Atmospheric,Lanzhou University,Lanzhou 730000,China)
Abstract:To quantitatively analyze the effect of air pollution on hospital admissions for respiratory diseases in Lanzhou. A semi-parametric generalized additive model (GAM) was used to analyze the exposure-effect relationship between air pollution and daily respiratory hospital visits from 2007 to 2009 in Lanzhou after controlling long time trend, the “day of week” effect and confounding factors of meteorology. At the same time, the model was established based on the sex and age groups. The three kinds of air pollutants all had certain lag effect in which PM10 lagged in 2 or 5 days, SO2 lagged in 3 days and NO2 lagged in 0 or 3 days. The relative risks of PM10, SO2, NO2 were 1.015, 1.049 and 1.040 for all hospital visits, respectively. The population with the age less than 15-year-old is the most sensitive to air pollution in Lanzhou ,followed by the population with the age more than 65-year-old. The influence of air pollution on the male is more obvious than the female.
Keywords:air pollution  respiratory diseases  time series  hospitalization
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