赵贵雪, 范宁, 张兴璐, 赵晓彤, 魏兴民, 吴建军, 李金娟, 王宇红, 王金玉, 李守禹, 冯亚莉, 贾清, 王龄庆, 韦性富, 李盛. 兰州市西固区空气中主要污染物对呼吸系统疾病门诊量的影响[J]. 环境卫生学杂志, 2019, 9(4): 320-325. DOI: 10.13421/j.cnki.hjwsxzz.2019.04.002
    引用本文: 赵贵雪, 范宁, 张兴璐, 赵晓彤, 魏兴民, 吴建军, 李金娟, 王宇红, 王金玉, 李守禹, 冯亚莉, 贾清, 王龄庆, 韦性富, 李盛. 兰州市西固区空气中主要污染物对呼吸系统疾病门诊量的影响[J]. 环境卫生学杂志, 2019, 9(4): 320-325. DOI: 10.13421/j.cnki.hjwsxzz.2019.04.002
    ZHAO Guixue, FAN Ning, ZHANG Xinglu, ZHAO Xiaotong, WEI Xingmin, WU Jianjun, LI Jinjuan, WANG Yuhong, WANG Jinyu, LI Shouyu, FENG Yali, JIA Qing, WANG Lingqing, WEI Xingfu, LI Sheng. Main Air Pollutants Effects on Number of Respiratory System Diseases Outpatient in Xigu District of Lanzhou[J]. Journal of Environmental Hygiene, 2019, 9(4): 320-325. DOI: 10.13421/j.cnki.hjwsxzz.2019.04.002
    Citation: ZHAO Guixue, FAN Ning, ZHANG Xinglu, ZHAO Xiaotong, WEI Xingmin, WU Jianjun, LI Jinjuan, WANG Yuhong, WANG Jinyu, LI Shouyu, FENG Yali, JIA Qing, WANG Lingqing, WEI Xingfu, LI Sheng. Main Air Pollutants Effects on Number of Respiratory System Diseases Outpatient in Xigu District of Lanzhou[J]. Journal of Environmental Hygiene, 2019, 9(4): 320-325. DOI: 10.13421/j.cnki.hjwsxzz.2019.04.002

    兰州市西固区空气中主要污染物对呼吸系统疾病门诊量的影响

    Main Air Pollutants Effects on Number of Respiratory System Diseases Outpatient in Xigu District of Lanzhou

    • 摘要:
      目的 探讨兰州市西固区空气中主要污染物对呼吸系统疾病门诊量的影响。
      方法 收集2016年1月1日—2017年12月31日西固区两家监测医院呼吸系统疾病每日门诊量数据,并收集同期环境监测数据。采用秩相关分析空气污染物和不同气象因素之间的关系;采用单因素和多因素广义相加模型分析西固区空气污染对医院呼吸系统门诊量的影响。
      结果 2016—2017年兰州市西固区监测医院呼吸系统的日均门诊量为98人/次,四分位数间距为62人/次;Spearman相关结果显示,除湿度与NO2、CO及温度的相关性无统计学意义外,其余空气污染物和气象因素之间均存在相关性且差异有统计学意义(P < 0.05);单因素广义相加模型分析显示,SO2、NO2、CO、PM10和PM2.5分别在滞后2、1、1、5、6 d时对呼吸系统门诊量的影响达到最大,RR及95% CI分别为1.032 5(1.026 1,1.039 0)、1.032 0(1.028 6,1.035 5)、3.039 4(2.617 7,3.529 2)、1.002 1(1.001 4,1.002 9)、1.014 3(1.011 8,1.016 7);多因素广义相加模型下SO2、NO2、CO、PM10和PM2.5RR值及95% CI分别为1.009 6(1.000 7,1.018 6)、1.005 5(1.000 2,1.010 9)、1.107 2(0.812 5,1.508 6)、1.002 2(1.000 7,1.003 8)和1.007 7(1.000 9,1.014 6),但CO对呼吸系统门诊量的影响差异无统计学意义。
      结论 空气中的SO2、NO2、PM10和PM2.5会增加居民患呼吸系统疾病的风险,是引起呼吸系统疾病门诊量上升的原因之一。

       

      Abstract:
      Objectives To investigate the effects of main air pollutants on outpatient visits of respiratory system diseases in Xigu district of Lanzhou.
      Methods Daily outpatient visits data of respiratory system was collected from January 1, 2016 to December 31, 2017 in 2 monitored hospitals in Xigu district, and environmental monitoring data was collected for the same period. Rank correlation was used to analyze the relationships between air pollutants and different meteorological factors. Single factor and multifactor generalized additive model were used to analyze the influence of main air pollutants on the outpatient visits respiratory system disease in Xigu district.
      Results From January 1, 2016 to December 31, 2017, the average daily outpatient visits number of the monitoring hospital's respiratory system disease was 98 person/time, and the quartile spacing was 62 person/time. Spearman correlation result showed that the correlations between humidity and NO2, CO and temperature were not statistically significant. Other air pollutants and meteorological factors were correlated and statistically significant. Univariate generalized additive model analysis showed that SO2, NO2, CO, PM10 and PM2.5 had the greatest impact on respiratory outpatient volume when the delay was 2 days, 1 day, 1 day, 5 days and 6 days respectively. RR and 95%CI were 1.032 5 (1.026 1, 1.039 0), 1.032 0 (1.028 6, 1.035 5), 3.039 4 (2.617 7, 3.529 2), 1.002 1 (1.001 4, 1.002 9), 1.014 3 (1.011 8, 1.016 7), respectively. Under the multivariate generalized additive model, the RR values of SO2, NO2, CO, PM10 and PM2.5 were 1.009 6 (1.000 7, 1.018 6), 1.005 5 (1.000 2, 1.010 9), 1.107 2 (0.812 5, 1.508 6), 1.002 2 (1.000 7, 1.003 8), and 1.007 7 (1.000 9, 1.014 6), respectively. However, the effect of CO on respiratory disease outpatient visits was not statistically significant.
      Conclusions SO2, NO2, PM10 and PM2.5 will increase the risk of residents suffering from respiratory diseases.

       

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