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大气污染物暴露与青岛市居民脑卒中发病关系时间序列分析

Association between short-term exposure to air pollutants and daily stroke incidence among residents in Qingdao city: a time series analysis of disease surveillance, environmental, and meteorological monitoring data

    摘要
  • 摘要:
    目的 了解大气污染物暴露与山东省青岛市居民脑卒中发病的关系，为脑卒中的预防控制提供参考依据。
    方法 收集国家慢性病监测网络报告系统中青岛市2014 年 1 月 1 日 — 2020 年 12 月 31 日上报的脑卒中新发病例相关数据以及同期青岛生态环境监测中心大气污染物监测数据和青岛市气象台气象监测数据，应用分布滞后非线性模型（DLNM）分析大气污染物暴露与青岛市居民脑卒中发病的关系，同时控制长期趋势、星期几效应等混杂因素的影响分析单污染物模型大气污染物对脑卒中发病的效应。
    结果 青岛市2014 — 2020年共报告51 120例脑卒中新发病例，平均日发病数为（19.99 ± 15.53）例。暴露 – 反应关系分析结果显示，PM2.5暴露浓度 > 121.90 μg/m3、CO暴露浓度 > 1.56 μg/m3和O3暴露浓度 < 64.00 μg/m3时脑卒中发病风险均呈上升趋势，而O3暴露浓度 > 64.00 μg/m3时脑卒中发病风险呈上下波动趋势（均P < 0.05）。单污染物模型分析结果显示，PM2.5和CO暴露与脑卒中发病风险升高的易感滞后期为Lag2 d～Lag5 d，O3暴露与脑卒中发病风险升高的易感滞后期为Lag3 d～Lag6 d，PM10暴露与脑卒中发病风险升高的易感滞后期为Lag3 d～Lag4 d，SO2暴露与脑卒中发病风险升高的易感滞后期为Lag6 d；PM2.5暴露浓度每升高32.01 μg/m3、PM10暴露浓度每升高52.21 μg/m3，脑卒中Lag3 d发病的RR值分别为1.018（95%CI = 1.005～1.031）、2.027（95%CI = 1.232～3.334）；O3暴露浓度每升高53.00 μg/m3、CO暴露浓度每升高0.39 mg/m3，脑卒中Lag4 d发病的RR值分别为1.155（95%CI = 1.080～1.234）、1.033（95%CI = 1.016～1.050），SO2暴露浓度每升高14.93 μg/m3，脑卒中Lag6 d发病的RR值为1.431（95%CI = 1.049～1.951）。敏感性分析结果显示，T、AP和RH的df变为4、5、6时对PM2.5、O3、CO、PM10、SO2和NO2暴露与青岛市居民脑卒中发病风险关系效应值的影响均较小，模型结果较为稳定。
    结论 PM2.5、PM10、O3、CO和SO2等大气污染物暴露对青岛市居民脑卒中发病具有滞后效应。

     

    Abstract:
    Objective To investigate the association between exposure to ambient air pollutants and stroke incidence among residents of Qingdao city, Shandong province, and to provide evidence for stroke prevention and control.
    Methods Data on new cases of stroke reported in Qingdao municipality from 2014 to 2020 were collected from the National Chronic Disease Surveillance Network Reporting System, together with air pollution monitoring data from the Qingdao Ecological Environment Monitoring Center and meteorological monitoring data from the Qingdao Meteorological Observatory for the same period. The distributed Lag nonlinear model (DLNM) was used to analyze the associations between daily mean concentrations of particulate matter with an aerodynamic diameter of less than 2.5 mum (PM2.5), particulate matter with an aerodynamic diameter of less than 10 mum (PM10), carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2), and nitrogen dioxide (NO2) with daily stroke incidence, while controlling for the effects of potential confounders such as long-term trend and day of the week in Qingdao city. The effects of air pollutants on stroke incidence were analyzed using a single-pollutant model.
    Results A total of 51 120 new cases of stroke were reported in the city during the period, with an average daily incidence of 19.99 ± 15.53. The exposure-response relationship analysis showed that the risk of stroke incidence increased when ambient PM2.5 concentration was higher than 121.90 μg/m3, CO concentration was higher than 1.56 μg/m3, but O3 concentration was lower than 64.00 μg/m3, while the risk of stroke incidence showed an up-and-down fluctuating trend when O3 concentration was higher than 64.00 μg/m3 (all P<0.05). The single-pollutant model analysis showed that the sensitive Lag periods for increased risk of stroke incidence were from Lag day 2 to Lag day 5 for ambient PM2.5 and CO exposure, from Lag day 3 to Lag day 6 for O3 exposure, from Lag day 3 to Lag day 4 for PM10 exposure, and from Lag day 6 for SO2 exposure. The relative risk (RR) values for daily stroke incidence at Lag day 3 were 1.018 (95% confidence interval 95%CI: 1.005 – 1.031) and 2.027 (95%CI: 1.232 – 3.334) for each 32.01 μg/m3 increase in PM2.5 concentration and for each 52.21 μg/m3 increase in PM10 concentration, respectively. The RR values for daily stroke incidence at Lag day 4 were 1.155 (95%CI: 1.080 – 1.234) and 1.033 (95%CI: 1.016 – 1.050) for each 53.00 μg/m3 increase in O3 concentration and each 0.39 mg/m3 increase in CO concentration, respectively. The RR value for daily stroke incidence at Lag day 6 was 1.431 (95%CI: 1.049 – 1.951) for each 14.93 μg/m3 increase in SO2 concentration. Sensitivity analysis results showed that changing the degrees of freedom of daily mean temperature, barometric pressure, and relative humidity to 4, 5, and 6 had little effect on the effect of ambient PM2.5, O3, CO, PM10, SO2, and NO2 exposure on the risk of daily stroke incidence, indicating that the established models produced relatively stable results.
    Conclusion Exposure to ambient PM2.5, PM10, O3, CO, and SO2 has a delayed effect on stroke incidence among Qingdao residents.

     

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