滕婉莹, 杨浩峰, 马龙. 乌鲁木齐市大气PM2.5和PM10与居民呼吸系统疾病急救人次的关系[J]. 环境与职业医学, 2020, 37(6): 594-598. DOI: 10.13213/j.cnki.jeom.2020.19753
引用本文: 滕婉莹, 杨浩峰, 马龙. 乌鲁木齐市大气PM2.5和PM10与居民呼吸系统疾病急救人次的关系[J]. 环境与职业医学, 2020, 37(6): 594-598. DOI: 10.13213/j.cnki.jeom.2020.19753
TENG Wan-ying, YANG Hao-feng, MA Long. Correlations of PM2.5 and PM10 with emergency hospital visits for respiratory diseases of residents in Urumqi[J]. Journal of Environmental and Occupational Medicine, 2020, 37(6): 594-598. DOI: 10.13213/j.cnki.jeom.2020.19753
Citation: TENG Wan-ying, YANG Hao-feng, MA Long. Correlations of PM2.5 and PM10 with emergency hospital visits for respiratory diseases of residents in Urumqi[J]. Journal of Environmental and Occupational Medicine, 2020, 37(6): 594-598. DOI: 10.13213/j.cnki.jeom.2020.19753

乌鲁木齐市大气PM2.5和PM10与居民呼吸系统疾病急救人次的关系

Correlations of PM2.5 and PM10 with emergency hospital visits for respiratory diseases of residents in Urumqi

  • 摘要: 背景

    大气细颗粒物(PM2.5)和可吸入颗粒物(PM10)暴露与呼吸系统疾病急诊人次之间存在密切关联,但不同城市大气颗粒物对呼吸系统疾病的影响存在差异。

    目的

    探讨乌鲁木齐市PM2.5和PM10浓度与呼吸系统疾病急救人次的关系。

    方法

    收集该市2016-2018年呼吸系统疾病的急救人次、气象和大气污染物数据。气象数据包括日均气温、相对湿度;大气污染数据包括PM2.5、PM10、SO2、NO2、CO的日均浓度和O3的日最大8小时平均值。急救数据来自于乌鲁木齐市疾病预防控制中心,气象及大气污染数据来自于乌鲁木齐市主城区的6个国控监测点。采用广义相加模型(GAM),在控制长期趋势、气象因素和"星期几效应"等潜在混杂因素后,分析PM2.5和PM10浓度与每日呼吸系统疾病急救人次的关系,分析单独滞后0~7 d(lag0~lag7)和累积滞后0~7 d(lag01~lag07)的影响,采用超额危险度(ER)及其95%可信区间(95%CI)为风险估计值。

    结果

    lag07时,颗粒物效应值最大:PM2.5和PM10浓度每升高10 μg·m-3,居民因呼吸系统疾病急救人次增加,其ER(95%CI)分别为1.99%(1.18%~2.80%)和1.43%(0.76%~2.10%)。在性别分层中,大气PM2.5和PM10浓度每升高10 μg·m-3,男性、女性最大效应值分别出现在lag07、lag04,ER(95%CI)分别为2.18%(1.16%~3.21%)、1.50%(0.66%~2.35%)和1.33%(0.15%~2.52%)、1.02%(0.05%~2.00%)。在年龄分层中,大气PM2.5和PM10对≥ 65岁组人群影响的最大值出现在lag06和lag07,其浓度每升高10 μg·m-3因呼吸系统疾病急救人次分别增加1.67%(95%CI:0.76%~2.57%)和2.11%(95%CI:1.19%~3.04%);对 < 65岁组人群影响的最大值出现在lag05和lag02,其浓度每升高10 μg·m-3因呼吸系统疾病急救人次分别增加1.97%(95%CI:0.59%~3.36%)和1.44%(95%CI:0.67%~2.21%)。

    结论

    大气PM2.5和PM10浓度的升高可能增加了居民呼吸系统疾病的风险,且男性和≥ 65岁者对两种颗粒物暴露相对更为敏感。

     

    Abstract: Background

    There are close correlations between exposure to fine particulate matters (PM2.5) and inhalable particulate matters (PM10) and emergency visits for respiratory diseases, but the correlations may differ across cities.

    Objective

    This study assesses the relationships between ambient PM2.5 and PM10 concentrations and daily emergency visits due to respiratory diseases in Urumqi.

    Methods

    Data were collected on daily emergency visits due to respiratory diseases, meteorological variables, and atmospheric pollutants in the city from 2016 to 2018. Meteorological data included daily average temperature and relative humidity. Atmospheric pollution data included daily mean concentrations of PM2.5, PM10, SO2, NO2, and CO and maximum 8 h O3. The emergency medical service usage data were sourced from the Urumqi Center for Disease Control and Prevention, and the meteorological and atmospheric pollution data were from six national monitoring stations in the urban area of Urumqi. Generalized additive model was used to analyze the relationships between PM2.5 and PM10 concentrations and daily emergency visits due to respiratory diseases with adjustment for time trends, meteorological factors, and day of the week, and risk estimates at individual (lag0-lag7) and cumulative (lag01-lag07) lag days were expressed as excess risk (ER) with 95% confidence interval (95% CI).

    Results

    A 10μg·m-3 increase in concentrations of PM2.5 and PM10 at lag07 day corresponded to an increase of 1.99% (95%CI:1.18%-2.80%) and 1.43% (95% CI:0.76%-2.10%) in daily emergency visits due to respiratory diseases respectively. The results of gender stratification analysis showed that a 10 μg·m-3 increase in concentrations of PM2.5 and PM10 at lag07 day corresponded to an increase of 2.18% (95% CI:1.16%-3.21%) and 1.50% (95% CI:0.66%-2.35%) for male patients respectively; a 10 μg·m-3 increase in concentrations of PM2.5 and PM10 at lag04 day corresponded to an increase of 1.33% (95% CI:0.15%-2.52%) and 1.02% (95% CI:0.05%-2.00%) for female patients respectively. The results of age stratification analysis showed that for the ≥ 65 years age group, a 10 μg·m-3 increase in concentration of PM2.5 at lag06 day and PM10 at lag07 day corresponded to an increase of 1.67% (95% CI:0.76%-2.57%) and 2.11% (95% CI:1.19%-3.04%) in daily emergency visits due to respiratory diseases, and for the < 65 years age group, a 10 μg·m-3 increase in concentration of PM2.5 at lag05 day and PM10 at lag02 day corresponded to an increase of 1.97% (95% CI:0.59%-3.36%) and 1.44% (95% CI:0.67%-2.21%), respectively.

    Conclusion

    PM2.5 and PM10 concentrations may increase the risk of respiratory diseases among residents in Urumqi, and men and the age group ≥ 65 years are more sensitive to such exposures.

     

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