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陈一龙, 胡耀, 詹宇, 等. 短期空气污染物暴露对终末期肾脏病血液透析患者入院次数的影响[J]. koko体育app 学报（医学版）, 2023, 54(6): 1176-1183. DOI:
引用本文: 陈一龙, 胡耀, 詹宇, 等. 短期空气污染物暴露对终末期肾脏病血液透析患者入院次数的影响[J]. koko体育app 学报（医学版）, 2023, 54(6): 1176-1183. DOI:
CHEN Yilong, HU Yao, ZHAN Yu, et al. Effect of Short-Term Exposure to Air Pollutants on Hospital Admissions for End-Stage Renal Disease Patients Undergoing Hemodialysis[J]. Journal of Sichuan University (Medical Sciences), 2023, 54(6): 1176-1183. DOI:
Citation: 🐻 CHEN Yilong, HU Yao, ZHAN Yu, et al. Effect of Short-Term Exposure to Air Pollutants on Hospital Admissions for End-Stage Renal Disease Patients Undergoing Hemodialysis[J]. Journal of Sichuan University (Medical Sciences), 2023, 54(6): 1176-1183. DOI:

短期空气污染物暴露对终末期肾脏病血液透析患者入院次数的影响

Effect of Short-Term Exposure to Air Pollutants on Hospital Admissions for End-Stage Renal Disease Patients Undergoing Hemodialysis

  • 摘要:
      目的  评估接受维持性血液透析的终末期肾脏疾病（end-stage renal disease, ESRD）患者人群中，空气污染物短期暴露与每日入院次数的关联性。
      方法  本研究数据来源于中国西南某城市全市城镇职工基本医疗保险和城镇居民基本医疗保险数据库，纳入接受维持性血液透析治疗的ESRD患者。采用单一污染物和多污染物广义加性模型来估计不同滞后日空气污染物（CO、NO2、O3、PM10、PM2.5和SO2）对入院情况的影响。此外，按性别、年龄、PM2.5和PM10浓度阈值、季节、心血管疾病和高血压合并症等开展亚组分析。
      结果  单一污染物模型中，患者入院次数与显著相关的污染物及其对应的最强关联时间为：CO每增加0.1 mg/m3，滞后7 d的患者入院次数增加2.39%〔95%置信区间（confidence interval, CI）：0.96%～3.83%〕；NO2、O3、PM2.5、PM10和SO2每增加10 μg/m3，患者入院次数分别在滞后7 d时增加4.02%（95%CI：1.21%～6.91%），滞后0～4 d时增加3.57%（95%CI：0.78%～6.44%），滞后6 d时增加2.00%（95%CI：1.07%～2.93%），滞后7 d时增加1.19%（95%CI：0.51%～1.88%），滞后7 d时增加8.37%（95%CI：3.08%～13.93%）。多污染物模型中，O3和PM2.5每增加10 μg/m3，患者每日入院次数分别在滞后0～4 d时增加3.18%（95%CI：0.34%～6.09%），滞后7 d时增加1.85%（95%CI：0.44%～3.28%）。此外，亚组分析显示季节、空气污染的严重程度和患者的共存疾病可能是环境空气污染与ESRD血液透析患者入院次数关联的效应修饰因素。
      结论  空气污染与ESRD血液透析患者入院次数密切相关。关联程度随季节、空气污染严重程度和患者合并疾病的不同而存在差异。
     
    Abstract:
      Objective  To evaluate the association between short-term exposure to air pollutants of end-stage renal disease (ESRD) patients on maintenance hemodialysis and the number of daily hospital admissions.
      Methods  The data on hospitalizations were obtained from the database of the municipal Urban Employees' Basic Medical Insurance and Urban Residents' Basic Medical Insurance of a city in Southwest China. Single and multiple pollutant generalized additive models were utilized to estimate the effect of air pollutants (CO, NO2, O3, PM10, PM2.5, and SO2) on patient admissions after the lag time of different numbers of days. In addition, subgroup analyses stratified by sex, age, PM2.5 and PM10 concentration thresholds, seasonality, and comorbidity status for cardiovascular diseases and hypertension were conducted.
      Results  In the single pollutant models, the pollutants significantly associated with patient admissions and the corresponding lag time of the strongest association were as follows, every time CO increased by 0.1 mg/m3, there was a 2.39% increase (95% confidence interval CI: 0.96%-3.83%) in patient admissions after 7 days of lag time; every time NO2, O3, PM2.5, PM10, and SO2 increased by 10 μg/m3, patient admissions increased by 4.02% (95% CI: 1.21%-6.91%) after 7 days of lag time, 3.57% (95% CI: 0.78%-6.44%) after 0-4 days of lag time, 2.00% (95% CI: 1.07%-2.93%) after 6 days of lag time, 1.19% (95% CI: 0.51%-1.88%) after 7 days of lag time, and 8.37% (95% CI: 3.08%-13.93%) after 7 days of lag time, respectively. In the multiple pollutant model, every time O3 and PM2.5 increased by 10 μg/m3, there was an increase of 3.18% (95% CI: 0.34%-6.09%) in daily patient admissions after 0-4 days of lag time and an increase of 1.85% (95% CI: 0.44%-3.28%) after 7 days of lag time. Furthermore, subgroup analyses showed that seasonality, the severity of air pollution, and patients' comorbidities might be the effect modifiers for the association between ambient air pollution and hospital admissions in ESRD patients receiving maintenance hemodialysis.
      Conclusion  Air pollution is closely associated with hospital admissions in ESRD patients undergoing maintenance hemodialysis and the strength of this association varies according to seasonality, the severity of air pollution, and patients’ status of comorbidities.
     
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