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    李欢, 岳宣志, 杨升美, 高昇, 张晨光, 韩见弘, 孙冰, 郭海明, 董静, 魏娜娜, 范耀春. 2018—2021年呼和浩特市大气污染物对儿科呼吸系统疾病门诊量的影响[J]. 环境卫生学杂志, 2023, 13(12): 901-908, 927. DOI: 10.13421/j.cnki.hjwsxzz.2023.12.006
    引用本文: 李欢, 岳宣志, 杨升美, 高昇, 张晨光, 韩见弘, 孙冰, 郭海明, 董静, 魏娜娜, 范耀春. 2018—2021年呼和浩特市大气污染物对儿科呼吸系统疾病门诊量的影响[J]. 环境卫生学杂志, 2023, 13(12): 901-908, 927. DOI: 10.13421/j.cnki.hjwsxzz.2023.12.006
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    LI Huan, YUE Xuan-zhi, YANG Sheng-mei, GAO Sheng, ZHANG Chen-guang, HAN Jian-hong, SUN Bing, GUO Hai-ming, DONG Jing, WEI Na-na, FAN Yao-chun. Impact of air pollutants on the outpatient volume of pediatric respiratory diseases in Hohhot， China, 2018—2021[J]. Journal of Environmental Hygiene, 2023, 13(12): 901-908, 927. DOI: 10.13421/j.cnki.hjwsxzz.2023.12.006
    Citation: LI Huan, YUE Xuan-zhi, YANG Sheng-mei, GAO Sheng, ZHANG Chen-guang, HAN Jian-hong, SUN Bing, GUO Hai-ming, DONG Jing, WEI Na-na, FAN Yao-chun. Impact of air pollutants on the outpatient volume of pediatric respiratory diseases in Hohhot， China, 2018—2021[J]. Journal of Environmental Hygiene, 2023, 13(12): 901-908, 927. DOI: 10.13421/j.cnki.hjwsxzz.2023.12.006
    shu

    2018—2021年呼和浩特市大气污染物对儿科呼吸系统疾病门诊量的影响

    Impact of air pollutants on the outpatient volume of pediatric respiratory diseases in Hohhot， China, 2018—2021

      摘要
    • 摘要:
      目的 研究探讨2018-2021年呼和浩特市六种大气污染物（NO2、SO2、CO、O3-8 h、PM10、PM2.5）对儿科呼吸系统日门诊量的影响。
      方法 收集2018-2021年呼和浩特市两所三级以上医院的儿科呼吸系统疾病日门诊量、大气污染物浓度数据及气象资料，对A1期（COVID-19发生前期）与A2期（COVID-19影响期）进行分层分析，使用时间序列quasi Poisson分布的广义相加模型（generalized additive model，GAM），分别建立单污染物与双污染物模型定量分析大气污染物浓度对儿科呼吸系统日门诊量的影响。
      结果 A1期NO2、SO2、CO、PM10、PM2.5日均浓度与A2期差异具有统计学意义（P < 0.05）。单污染物模型分析结果显示，A1期NO2、SO2、CO、PM10、PM2.5日均浓度每增加10 μg/m3造成儿科呼吸系统门诊超额就诊风险分别增加1.55%、4.46%、0.14%、0.18%、0.35%；A2期NO2、SO2、CO、PM10日均浓度每增加10 μg/m3造成儿科呼吸系统门诊超额就诊风险分别增加8.25%、9.40%、2.84%、0.32%。除O3-8 h外，双污染模型分析NO2、SO2、CO、PM10、PM2.5与儿科呼吸系统疾病日门诊量的关系均有统计学意义（P < 0.05）。
      结论 呼和浩特市2018-2021年大气主要污染物日均浓度A1期高于A2期，气态污染物与PM10对儿科呼吸系统疾病门诊量健康危害效应在A2期高于A1期，NO2、SO2、CO、PM10、PM2.5日均浓度升高导致儿科呼吸系统疾病日门诊量增加且具有滞后效应。

       

      Abstract:
      Objective To investigate the influence of six atmospheric pollutants (NO2, SO2, CO, O3-8 h, PM10, and PM2.5) on the daily outpatient volume of pediatric respiratory system diseases in Hohhot, China, from 2018 to 2021.
      Methods Related data of Hohhot btween 2018 and 2021 were collected, including the daily outpatient volume of pediatric respiratory system diseases in two tertiary hospitals, concentration of atmospheric pollutants, and meteorological data, and a stratified analysis was performed for the data of the A1 period(COVID-19 pre-onset) and A2 period(COVID-19 infectious stage). The time-series generalized additive model (GAM) based on quasi Poisson distribution was used to establish single-pollutant and two-pollutant models to quantitatively analyze the health effect of atmospheric pollutant concentration on the daily outpatient volume of pediatric respiratory system diseases.
      Results There were significant differences in the daily mean concentrations of NO2, SO2, CO, PM10 and PM2.5 between A1 and A2 (P < 0.05). The single-pollutant model under the optimal lag time showed that A1 period, for every 10 μg/m3 increase in the daily mean concentration of NO2, SO2, CO, PM10, and PM2.5, the number of outpatients due to pediatric respiratory system diseases was increased by 1.55%, 4.46%, 0.14%, 0.18%, and 0.35%, respectively. During the A2 period, for every 10 μg/m3 increase in the daily mean concentration of NO2, SO2, CO and PM10, the number of outpatients was increased by 8.25%, 9.40%, 2.84% and 0.32%, respectively. In addition to O3-8 h, the relationship between NO2, SO2, CO, PM10, PM2.5 and the daily outpatient volume of pediatric respiratory diseases was statistically significant by dual-pollution model analysis (P < 0.05).
      Conclusion The average daily concentration of major pollutants in the atmosphere in the A1 period was greater than that of A2 period in Hohhot in 2018-2021, and the pollution effect of gaseous pollutants and PM10 on the outpatient volume of pediatric respiratory diseases in the A2 is higher than that of A1 period. The increase in the daily mean concentration of NO2, SO2, CO, PM10, and PM2.5 may lead to the increase in the outpatient volume of pediatric respiratory system diseases with lag effects.

       

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