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短期臭氧暴露与德州市急诊救护车调度关系时间分层病例交叉分析

A time-stratified case-crossover analysis of the association between short-term ozone exposure and emergency ambulance dispatches in Dezhou city

  • 摘要:
    目的 分析短期臭氧(O3)暴露与山东省德州市急诊救护车调度(EAD)的关系,为从健康视角治理O3污染和采取公共卫生干预措施提供科学依据。
    方法 收集山东省德州市120急救调度指挥中心2020年1月1日—2022年12月31日记录的每日全因急诊救护车调度数据以及同期中国气象数据网和中国高分辨率高质量近地表空气污染物数据集中气象数据和污染物数据,按照呼叫地址匹配;采用时间分层病例交叉设计通过整合分布滞后非线性模型(DLNM)的条件logistic回归模型分析短期O3暴露对德州市EAD的影响,并采用亚组分析探索脆弱人群。
    结果 德州市2020年1月1日—2022年12月31日的EAD数量为344287例次,病例天数为1 096 d,匹配的对照天数为3 728 d。在排除了平均气温和相对湿度的影响后,时间分层病例交叉分析结果显示,短期O3暴露滞后0~7 d与EAD累积风险呈正相关,O3日最大8 h平均浓度每增加1个四分位数间距(IQR),EAD累积风险可升高8%(OR=1.08,95%CI=1.04~1.11);单日滞后效应分析结果显示,短期O3暴露对EAD风险的累积效应在滞后当天最大(OR=1.06,95%CI=1.05~1.08),2 d内迅速减小,第2~4 d出现潜在收获效应。亚组分析结果显示,男性、女性、<35岁、35~65岁、>65岁、冷季和暖季O3日最大8 h平均浓度每增加1个IQR,EAD累积风险可分别升高9%(OR=1.09,95%CI=1.04~1.13)、6%(OR=1.06,95%CI=1.01~1.11)、6%(OR=1.06,95%CI=0.99~1.13)、6%(OR=1.06,95%CI=1.01~1.11)、10%(OR=1.10,95%CI=1.05~1.15)、4%(OR=1.04,95%CI=1.01~1.07)和7%(OR=1.07,95%CI=1.04~1.11)。敏感性分析结果显示,短期O3暴露滞后8 d和9 d时,O3日最大8 h平均浓度每增加1个IQR,EAD累积风险可分别升高8%(OR=1.08,95%CI=1.04~1.11)和8%(OR=1.08,95%CI=1.05~1.12);当模型中滞后维度的自由度为5和6时,O3日最大8 h平均浓度每增加1个IQR,EAD累积风险均升高7%(OR=1.07,95%CI=1.04~1.11);模型中额外调整气态污染物NO2和SO2后,O3日最大8 h平均浓度每增加1个IQR,EAD累积风险分别升高9%(OR=1.09,95%CI=1.06~1.13)和8%(OR=1.08,95%CI=1.05~1.12);改变模型中O3最大滞后天数和滞后维度自由度以及在模型中调整气态污染物NO2、SO2的结果与主模型结果差异均无统计学意义(均P>0.05),模型具有稳健性。
    结论 短期O3暴露可增加德州市EAD的风险,其中对男性、>65岁人群以及暖季EAD的影响较大。

     

    Abstract:
    Objective To analyze the association between short-term ozone (O3) exposure and emergency ambulance dispatches (EAD) in Dezhou city, Shandong province, and to provide scientific evidence for O3 pollution control and public health interventions from a health perspective.
    Methods Daily all-cause EAD data recorded by the Dezhou 120 Emergency Dispatch Command Center from January 1, 2020, to December 31, 2022, as well as meteorological data and pollutant data from the China Meteorological Data Network and the China High Air Pollutants dataset during the same period, were collected and matched according to the calling address. A time-stratified case-crossover design was adopted to analyze the impact of short-term O3 exposure on EAD in Dezhou city by integrating a distributed lag non-linear model (DLNM) with a conditional logistic regression model. Subgroup analyses were conducted to explore vulnerable populations.
    Results The number of EAD in Dezhou city from January 1, 2020, to December 31, 2022, was 344 287, with 1 096 case days and 3 728 matched control days. After excluding the influence of average temperature and relative humidity, the time-stratified case-crossover analysis showed a positive correlation between short-term O3 exposure lagged 0–7 days and the cumulative risk of EAD. For every interquartile range (IQR) increase in the daily maximum 8-hour average O3 concentration, the cumulative risk of EAD increased by 8% (OR = 1.08, 95%CI: 1.04–1.11). The single-day lag effect analysis showed that the cumulative effect of short-term O3 exposure on EAD risk was greatest on the day of exposure (OR = 1.06, 95%CI: 1.05–1.08), decreased rapidly within 2 days, and a potential harvesting effect appeared on days 2–4. Subgroup analyses showed that for every IQR increase in the daily maximum 8-hour average O3 concentration, the cumulative risk of EAD increased by 9% (OR = 1.09, 95%CI: 1.04–1.13) in males, 6% (OR = 1.06, 95%CI: 1.01–1.11) in females, 6% (OR = 1.06, 95%CI: 0.99–1.13) in the < 35 age group, 6% (OR = 1.06, 95%CI: 1.01–1.11) in the 35–65 age group, 10% (OR = 1.10, 95%CI: 1.05–1.15) in the > 65 age group, 4% (OR = 1.04, 95%CI: 1.01–1.07) in the cold season, and 7% (OR = 1.07, 95%CI: 1.04–1.11) in the warm season. Sensitivity analyses showed that with 8-day and 9-day lags in short-term O3 exposure, the cumulative risk of EAD increased by 8% (OR = 1.08, 95%CI: 1.04–1.11) and 8% (OR = 1.08, 95%CI: 1.05–1.12), respectively, for every IQR increase in the daily maximum 8-hour average O3 concentration. When the degrees of freedom for the lag dimension in the model were 5 and 6, the cumulative risk of EAD increased by 7% (OR = 1.07, 95%CI: 1.04–1.11) for every IQR increase in the daily maximum 8-hour average O3 concentration. After additionally adjusting for gaseous pollutants NO2 and SO2 in the model, the cumulative risk of EAD increased by 9% (OR = 1.09, 95%CI: 1.06–1.13) and 8% (OR = 1.08, 95%CI: 1.05–1.12), respectively, for every IQR increase in the daily maximum 8-hour average O3 concentration. Changing the maximum lag days of O3 and the degrees of freedom of the lag dimension in the model, as well as adjusting for gaseous pollutants NO2 and SO2 in the model, did not result in statistically significant differences from the main model results (all P > 0.05), indicating the robustness of the model.
    Conclusions Short-term O3 exposure can increase the risk of EAD in Dezhou city, with greater impacts on males, individuals over 65 years of age, and EAD during the warm season.

     

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