路殿英, 姜海, 张军锋, 乔晓芳, 尚瑾, 贺娟娟, 魏俊妮. 山西省太原市颗粒物污染与不稳定性心绞痛患者日入院人数的相关性研究[J]. 疾病监测, 2019, 34(10): 944-947. DOI: 10.3784/j.issn.1003-9961.2019.10.018
引用本文: 路殿英, 姜海, 张军锋, 乔晓芳, 尚瑾, 贺娟娟, 魏俊妮. 山西省太原市颗粒物污染与不稳定性心绞痛患者日入院人数的相关性研究[J]. 疾病监测, 2019, 34(10): 944-947. DOI: 10.3784/j.issn.1003-9961.2019.10.018
Dianying Lu, Hai Jiang, Junfeng Zhang, Xiaofang Qiao, Jin Shang, Juanjuan He, Junni Wei. Correlation between atmospheric particulate matter pollution and number of patients admitted to hospital due to unstable angina in Taiyuan, Shanxi[J]. Disease Surveillance, 2019, 34(10): 944-947. DOI: 10.3784/j.issn.1003-9961.2019.10.018
Citation: Dianying Lu, Hai Jiang, Junfeng Zhang, Xiaofang Qiao, Jin Shang, Juanjuan He, Junni Wei. Correlation between atmospheric particulate matter pollution and number of patients admitted to hospital due to unstable angina in Taiyuan, Shanxi[J]. Disease Surveillance, 2019, 34(10): 944-947. DOI: 10.3784/j.issn.1003-9961.2019.10.018

山西省太原市颗粒物污染与不稳定性心绞痛患者日入院人数的相关性研究

Correlation between atmospheric particulate matter pollution and number of patients admitted to hospital due to unstable angina in Taiyuan, Shanxi

  • 摘要:
    目的探讨颗粒物污染对不稳定性心绞痛(UA)患者日入院人数的影响。
    方法收集2013年12月1日至2016年8月31日UA患者日入院人数,以及同期该地区气象监测资料。 在控制了长期趋势、气象因素、节假日及星期几效应等混杂因素的基础上,构建半参数广义相加模型。 分析大气颗粒物(包括PM10和PM2.5)与UA患者日入院人数的关系。
    结果滞后1 d时,PM10每增加10 μg/m3,UA患者日入院人数增加1.00%(95% CI:0.60% ~ 1.30%),PM2.5每增加10 μg/m3,UA患者日入院人数增加1.50%(95% CI:0.90% ~ 2.00%)。 将颗粒物(PM2.5和PM10)和臭氧(O3)(滞后1 d)分别构建双污染物模型,PM10污染物模型在代入了O3之后结果有统计学意义,相对危险度(RR)升高(P<0.05)。 对于PM2.5,在代入了O3之后结果有统计学意义,RR值升高(P<0.05)。
    结论大气颗粒物可引起UA患者日入院数增加。

     

    Abstract:
    ObjectiveTo investigate the effect of atmospheric particulate matter pollution on the number of patients admitted to hospital due to unstable angina (UA).
    MethodsThe number of hospitalized patients with UA from December 1, 2013 to August 31, 2016 was collected, as well as meteorological surveillance data during the same period. Based on the control of long-term trends, meteorological factors, holidays and the effects of the day of the week, a semi-parametric generalized additive model was constructed to analyze the relationship between atmospheric particulate matter (including PM10 and PM2.5) and the number of hospitalized patients with UA.
    ResultsAfter one day lag, as the PM10 increased by 10 μg/m3, the number of UA patients admitted to hospital increased by 1.00%(95% CI: 0.60%–1.30%), and as the PM2.5 increased by 10 μg/m3, the number of UA patients admitted to hospital increased by1.50%(95% CI: 0.90%–2.00%). Two pollutant models were constructed by using particulate matter (PM2.5 and PM10) and ozone (lag one day). The results of PM10 pollutant model was statistically significant after the substitution of O3, and the RR value increased (P<0.05). For PM2.5, the results were statistically significant after the substitution of O3, and the RR value increased (P<0.05).
    ConclusionAtmospheric particulate matter can cause an increase in the number of hospitalizations due to UA.

     

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