大气污染物对兰州心脑血管疾病住院影响的病例交叉研究

摘要

为探讨兰州市大气污染对心脑血管疾病住院的急性健康效应,采用单向回顾性配对病例交叉设计,分析了兰州市2001～2005年大气污染物浓度(PM10、SO2及NO2)短期升高对人群心脑血管疾病住院的影响.结果表明,单向回顾性1:2匹配病例交叉研究的效应值(ORs)最大,在控制同期天气因素后,滞后3d PM10浓度每升高10μg/m3,总心脑血管疾病及心血管疾病住院的ORs分别为1.002(95％CI:1.001～1.003)和1.002(95％CI:1.001～1.003);无滞后SO2浓度每升高10μg/m3对总心脑血管疾病住院的OR值为1.005(95％CI:1.000～1.009);NO2在滞后1d浓度每升高10μg/m3对总心脑血管疾病OR值为1.022(95％CI:1.014～ 1.030);对心血管疾病及脑血管疾病住院影响均在滞后2d达到最大.ORs值分别为1.021 (95％CI:1.01 1～1.030)和1.019(95％CI:1.005～1.033).在多污染物模型中PM10仍对心血管疾病住院人数增加有统计学意义；NO2对心脑血管疾病住院的影响均较单污染物模型中大.%To explore the acute effect of air pollution and hospital admissions for cardiovascular and cerebrovascular diseases in Lanzhou, unidirectional retrospective case-crossover design was used to analyze the relation of daily average concentration of air pollutants (PM10, SO2and NO2) in short-time increased with the cardiovascular and cerebrovascular diseases hospitalizations from 2001 to 2005. The results showed that the unidirectional case-crossover design with 1:2 matched pairs had the highest odds ratios between air pollutants and hospital admissions. After being adjusted for meteorological factors, an increase of 10ug/m3in PM|Owas significantly associated with 1.002(95%CI: 1.001-1.003) and 1.002(95%CI: 1.001-1.003) at 3 days lag increase respectively for total circulatory diseases (ICD10:I00~I99) and cardiovascular disease (ICD 10:100-152); an increase of 10ug/m3 in SO2 was associated with 1.005(95%CI: 1.000-1.009) for total circulatory diseases hospitalizations; a 10ug/m3 increment in NO2 was significantly associated with hospital admissions on value of Ors 1.022(95%Cl:1.014~1.030) for the total circulatory diseases at lday lag, 1.021(95%CI: 1.011-1.030) for cardiovascular disease at 2 days lag, 1.019(95%CI: 1.005-1.033) for cerebrovascular diseases (1CD10: 160-169) at 2 days lag respectively. In the multiple air pollutant models, an increase of 10ug/m3 in PMm was also associated with cardiovascular and cerebrovascular diseases hospitalizations, the OR values of NO2 were higher than the single pollutant models.