姜彩霞, 朱冰, 张龙. 2013-2014年杭州市大气PM2.5与呼吸系统疾病就诊人次的时间序列研究[J]. 环境与职业医学, 2018, 35(7): 589-595. DOI: 10.13213/j.cnki.jeom.2018.17634
引用本文: 姜彩霞, 朱冰, 张龙. 2013-2014年杭州市大气PM2.5与呼吸系统疾病就诊人次的时间序列研究[J]. 环境与职业医学, 2018, 35(7): 589-595. DOI: 10.13213/j.cnki.jeom.2018.17634
JIANG Cai-xia, ZHU Bing, ZHANG Long. Association between ambient PM2.5 and hospital visits for respiratory diseases in Hangzhou in 2013-2014: A time-series study[J]. Journal of Environmental and Occupational Medicine, 2018, 35(7): 589-595. DOI: 10.13213/j.cnki.jeom.2018.17634
Citation: JIANG Cai-xia, ZHU Bing, ZHANG Long. Association between ambient PM2.5 and hospital visits for respiratory diseases in Hangzhou in 2013-2014: A time-series study[J]. Journal of Environmental and Occupational Medicine, 2018, 35(7): 589-595. DOI: 10.13213/j.cnki.jeom.2018.17634

2013-2014年杭州市大气PM2.5与呼吸系统疾病就诊人次的时间序列研究

Association between ambient PM2.5 and hospital visits for respiratory diseases in Hangzhou in 2013-2014: A time-series study

  • 摘要: 目的 探讨杭州市大气PM2.5对呼吸系统疾病就诊人次的影响。

    方法 收集2013-2014年杭州市气象资料(包括气温、相对湿度、气压和风速的日平均值),10个国控环境监测点的大气污染物PM10、PM2.5、NO2、CO、SO2、O3的平均质量浓度(以下简称为浓度)和杭州市城区9家三甲医院呼吸系统疾病(主要为慢性阻塞性肺病、哮喘、肺炎、支气管炎、过敏性鼻炎、急性上呼吸道感染疾病)就诊量数据,采用时间序列广义相加Poisson回归模型,分析杭州市大气PM2.5日均浓度与同期医院呼吸系统疾病就诊量的关系。

    结果 杭州市2013-2014年大气污染物SO2、NO2、O3、CO日均浓度均符合GB 3095-2012《环境空气质量标准》一级标准,PM2.5、PM10的日均浓度分别为61.51、92.33 μg/m3,超过国家空气质量一级标准,但未超过国家空气质量二级标准。PM2.5对呼吸系统疾病就诊量的影响以滞后第10天的效应最强。在单污染物模型中,PM2.5浓度每上升10 μg/m3,滞后第10天的全人群、儿童(≤ 12岁)和老年人(≥ 65岁)呼吸系统疾病就诊人次分别增加0.226%(95% CI:0.159%~0.293%)、0.289%(95% CI:0.198%~0.380%)、0.266%(95% CI:0.168%~0.375%);在多污染模型中,PM2.5的健康效应增强,PM2.5浓度每上升10μg/m3,滞后第10天的全人群、儿童(≤ 12岁)和老年人(≥ 65岁)呼吸系统疾病日就诊人次分别增加0.340%(95% CI:0.221%~0.459%)、0.365%(95% CI:0.230%~0.500%)、0.374%(95% CI:0.235%~0.513%)。

    结论 杭州市大气PM2.5污染与呼吸系统就诊人次呈正相关,且存在滞后效应。儿童和老年人对PM2.5污染更加敏感。

     

    Abstract: Objective To investigate the effect of ambient PM2.5 on hospital visits due to respiratory diseases in Hangzhou.

    Methods The meteorological data (including average daily temperature, relative humidity, air pressure, and wind speed), the air pollutant data (including average concentrations of PM10, PM2.5, NO2, CO, SO2, and O3) recorded by ten national monitoring stations, and the data of hospital visits due to respiratory diseases (including chronic obstructive pulmonary disease, asthma, pneumonia, bronchitis, allergic rhinitis, and other acute upper respiratory tract infections) were collected from 2013 to 2014 from nine tertiary grade-A hospitals in Hangzhou urban areas. Time-series analysis with generalized additive model (GAM) was applied to reveal the association between the average daily concentration of PM2.5 and the hospital visits for respiratory diseases.

    Results The average daily concentrations of SO2, NO2, O3, and CO were all qualified for the grade Ⅰ standard of GB 3095-2012 Environmental Air Quality Criterion, while the concentration of PM2.5 (61.51 μg/m3) and PM10 (92.33 μg/m3) were exceeding the national grade Ⅰ standard but within the grade Ⅱ standard. The effect of exposure to PM2.5 on visits for respiratory diseases was strongest on lag day 10. The single-pollutant model suggested that the hospital visits from whole population, children (≤ 12 years), and the elderly (≥ 65 years) increased 0.226% (95% CI:0.159%-0.293%), 0.289% (95% CI:0.198%-0.380%), and 0.266% (95% CI:0.168%-0.375%), respectively, on lag day 10 for per 10μg/m3 increase of PM2.5. In the multi-pollutant model, a much stronger health effect of PM2.5 was observed:the hospital visits from whole population, children (≤ 12 years), and the elderly (≥ 65 years) increased 0.340% (95% CI:0.221%-0.459%), 0.365% (95% CI:0.230%-0.500%), and 0.374% (95% CI:0.235%-0.513%), respectively, on lag day 10 for per 10μg/m3 increase of PM2.5.

    Conclusion PM2.5 pollution displays a positive association with hospital visits for respiratory diseases in Hangzhou with certain lagged effect. Children and the elderly are more sensitive to PM2.5 pollution than the other groups.

     

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