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    秦叙, 温馥源, 李冰潇, 曹寒, 张玲. 北京市密云区大气污染物短期暴露与呼吸系统疾病住院人数的关联性研究[J]. 环境卫生学杂志, 2023, 13(5): 371-377. DOI: 10.13421/j.cnki.hjwsxzz.2023.05.011
    引用本文: 秦叙, 温馥源, 李冰潇, 曹寒, 张玲. 北京市密云区大气污染物短期暴露与呼吸系统疾病住院人数的关联性研究[J]. 环境卫生学杂志, 2023, 13(5): 371-377. DOI: 10.13421/j.cnki.hjwsxzz.2023.05.011
    shu
    QIN Xu, WEN Fu-yuan, LI Bing-xiao, CAO Han, ZHANG Ling. Association between short-term exposure to air pollutants and the number of hospitalizations duo to respiratory system diseases in Miyun District, Beijing, China[J]. Journal of Environmental Hygiene, 2023, 13(5): 371-377. DOI: 10.13421/j.cnki.hjwsxzz.2023.05.011
    Citation: QIN Xu, WEN Fu-yuan, LI Bing-xiao, CAO Han, ZHANG Ling. Association between short-term exposure to air pollutants and the number of hospitalizations duo to respiratory system diseases in Miyun District, Beijing, China[J]. Journal of Environmental Hygiene, 2023, 13(5): 371-377. DOI: 10.13421/j.cnki.hjwsxzz.2023.05.011
    shu

    北京市密云区大气污染物短期暴露与呼吸系统疾病住院人数的关联性研究

    Association between short-term exposure to air pollutants and the number of hospitalizations duo to respiratory system diseases in Miyun District, Beijing, China

      摘要
    • 摘要:
      目的 探索北京市密云区大气污染物短期暴露与呼吸系统疾病住院人数的关联。
      方法 收集北京市密云区医院2014年4月10日—2019年8月10日呼吸内科病房住院病例数据, 北京市生态环境监测中心的每日大气污染物监测数据和中国气象数据网的每日气象数据。运用广义相加模型, 调整星期几效应、节假日效应、温度、湿度、风速和时间长期趋势变量, 分析密云区大气PM2.5、PM10、SO2、NO2、CO和O3-8 h与呼吸系统疾病住院人数的关联性。通过双污染物模型和敏感性分析, 评价各污染物模型的稳健性。
      结果 PM10质量浓度在lag 7 d每上升1个四分位间距(IQR)时, 呼吸系统疾病住院人数增加2.29%(95%CI: 0.04%~4.60%); O3-8 h质量浓度在lag 0 d每上升1个IQR时, 呼吸系统疾病住院人数增加5.80%(95%CI: 0.06%~11.86%)。在亚组分析中PM10在lag 3 d与男性的关联高于女性(P交互=0.006);CO在lag 3 d与80岁及以上人群的关联高于65~79岁人群(P交互=0.047)。在双污染物模型中, O3-8 h在lag 0 d与呼吸系统疾病住院人数的关联在调整PM2.5、PM10、NO2、CO后仍存在统计学意义, 提示O3暴露与呼吸系统疾病住院人数增加的正向关联具有稳健性。
      结论 O3-8 h短期暴露与呼吸系统疾病住院人数增加相关; PM10污染与呼吸系统疾病住院人数增加存在关联, 且存在滞后效应。

       

      Abstract:
      Objective To explore the association between short-term exposure to air pollutants and the number of hospitalizations due to respiratory system diseases in Miyun District, Beijing, China.
      Methods Data of inpatients from the respiratory ward of Beijing Miyun District Hospital from April 10, 2014 to August 10, 2019, daily air pollutant monitoring data from Beijing Municipal Ecological and Environmental Monitoring Center, and daily meteorological data from China Meteorological Data Service Center were collected. A generalized additive model was performed to evaluate the association of concentrations of fine particulate matter (PM2.5), particulate matter 10 (PM10), sulfur dioxide(SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and daily maximum 8-h average ozone concentration (O3-8 h)in air with the number of hospitalizations due to respiratory system diseases, after adjusting for the day-of-the-week effect, holiday effect, temperature, humidity, wind speed, and long-term trend variables of time. The robustness of each pollutant model was evaluated by the two-pollutant model and sensitivity analysis.
      Results The number of hospitalizations due to respiratory system diseases increased by 2.29% (95% confidence interval CI: 0.04%-4.60%)for each interquartile range (IQR)increased in the mass concentration of PM10 on lag 7 d and by 5.80% (95% CI: 0.06%-11.86%)for each IQR increased in the mass concentration of O3-8 h on lag 0 d. Subgroup analysis showed that PM10 (lag 3 d)had a greater association on male (Pinteraction=0.047) than female(Pinteraction=0.006); CO (lag 3 d)had a greater association on people aged ≥ 80 years than those aged 65-79 years. In the two-pollutant model, the association between O3-8 h on lag 0 d and the number of hospitalizations due to respiratory system diseases was still statistically significant after adjusting for concentrations of PM2.5, PM10, NO2, and CO, suggesting that the positive correlation between exposure to O3 and the number of hospitalizations due to respiratory system diseases was robust.
      Conclusion Short-term exposure to O3-8 h is associated with an increase in the number of hospitalizations due to respiratory system diseases; the impact of PM10 pollution on the number of hospitalizations due to respiratory system diseases is statistically significant and has a lag effect.

       

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