刘准, 陈丹, 霍细香, 殷俊, 梅越. 武汉市大气污染物水平与儿童呼吸道疾病门诊量的滞后效应分析[J]. 环境与职业医学, 2018, 35(2): 124-130. DOI: 10.13213/j.cnki.jeom.2018.17650
引用本文: 刘准, 陈丹, 霍细香, 殷俊, 梅越. 武汉市大气污染物水平与儿童呼吸道疾病门诊量的滞后效应分析[J]. 环境与职业医学, 2018, 35(2): 124-130. DOI: 10.13213/j.cnki.jeom.2018.17650
LIU Zhun, CHEN Dan, HUO Xi-xiang, YIN Jun, MEI Yue. Lag effects of air pollutant levels on pediatric respiratory disease outpatient visits in Wuhan[J]. Journal of Environmental and Occupational Medicine, 2018, 35(2): 124-130. DOI: 10.13213/j.cnki.jeom.2018.17650
Citation: LIU Zhun, CHEN Dan, HUO Xi-xiang, YIN Jun, MEI Yue. Lag effects of air pollutant levels on pediatric respiratory disease outpatient visits in Wuhan[J]. Journal of Environmental and Occupational Medicine, 2018, 35(2): 124-130. DOI: 10.13213/j.cnki.jeom.2018.17650

武汉市大气污染物水平与儿童呼吸道疾病门诊量的滞后效应分析

Lag effects of air pollutant levels on pediatric respiratory disease outpatient visits in Wuhan

  • 摘要: 目的 评估武汉市大气污染物PM2.5、PM10、NO2、O3、CO和SO2日均质量浓度(以下简称"浓度")对儿童呼吸道疾病就诊量的影响。

    方法 收集2015-2016武汉市大气污染物资料、气象资料和湖北省妇幼保健院儿童呼吸系统疾病病例资料。用Spearman相关分析6种大气污染物与平均温度和相对湿度的相关性。采用广义相加模型(GAM)控制星期几效应、气象因素、假期效应等因素,分析大气污染物与儿童上、下呼吸道疾病门诊量和呼吸系统疾病总门诊量的关系及滞后效应(lag1~lag5)和累积效应(lag0:1~lag0:5),选取最大效应值作为大气污染物对就诊量影响的暴露风险估计值。

    结果 在累积滞后效应中,大气污染物浓度每上升一个四分位数间距,呼吸系统疾病总门诊量上升的超额危险度(ER)及其95%可信区间(95%CI)分别为:PM2.5(lag0:4)1.78%(0.12%~3.46%)、PM10(lag0:5)3.48%(0.49%~6.56%)、NO2(lag0:5)6.59%(3.75%~9.52%)、CO(lag0:5)3.27%(0.02%~6.63%)、SO2(lag0:5)3.66%(0.62%~6.80%)、O3(lag0:4)2.65%(0.03%~5.29%),都是在累积滞后4~5 d时总门诊量ER达到最高。在滞后效应中,下呼吸道疾病门诊量在PM2.5、PM10、NO2、CO和SO2滞后5 d时ER达到最高;上呼吸道疾病门诊量在PM2.5、PM10和SO2当日,NO2和CO滞后4 d时ER达到最高;下呼吸道疾病就诊量与O3无明显关联(P < 0.05)。

    结论 武汉市6种大气污染物浓度升高对儿童呼吸系统疾病门诊量的增加有明显影响,且对下呼吸道疾病存在较为明显的滞后效应。

     

    Abstract: Objective To assess the impacts of daily average concentrations of air pollutants including PM2.5, PM10, NO2, O3, CO, and SO2 on the number of visits for respiratory diseases of children in Wuhan City.

    Methods The data of selected air pollutants, meteorology, and cases of respiratory diseases of children who visited the Hubei Maternal and Child Health Hospital were collected from 2015 to 2016. Spearman correlation was used to analyze the correlations of six air pollutants with average temperature and relative humidity. Generalized additive model (GAM) was used to analyze the la g effects (lag1-lag5) and cumulative lag effects (lag0:1-lag0:5) of air pollutants on the outpatient visits in children for upper respiratory tract disease, lower respiratory tract disease, and respiratory disease, after controlling factors such as day of the week, meteorological factors, and holidays. The maximum effect value was selected as the exposure risk estimate of the impact of air pollutants on pediatric respiratory disease outpatient visits.

    Results For the cumulative lag effect, an IQR increase in air pollutant concentration was associated with the increase in the total number of visits for pediatric respiratory diseaseexcess risk (ER), 95% CI:PM2.5 (lag0:4), 1.78%(0.12%-3.46%); PM10 (lag0:5), 3.48%(0.49%-6.56%); NO2 (lag0:5), 6.59%(3.75%-9.52%); CO (lag0:5), 3.27%(0.02%-6.63%); SO2 (lag0:5), 3.66%(0.62%-6.80%); and O3 (lag0:4), 2.65% (0.03%-5.29%). The ER for total number of visits all reached the highest after 4-5 days of cumulative lag. For the lag effect:the ER of lower respiratory tract disease reached the highest on lag day 5 for PM2.5, PM10, NO2, CO, and SO2; the ER of upper respiratory tract disease reached the highest on current day for PM2.5, PM10, and SO2, and on lag day 4 for NO2 and CO; there was no significant correlation between the number of visits for lower respiratory tract disease and O3 (P > 0.05).

    Conclusion Elevated concentrations of selected six air pollutants in Wuhan City have significant influences on the number of visits for respiratory disease in children, and obvious lag effects on lower respiratory tract disease.

     

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