邢卫东, 王路钦, 王莉, 杨震, 张治国, 李涛, 杜昕, 张灿有, 成君, 赵飞, 马树波. 2010-2017年北京市昌平区结核病登记率分析[J]. 疾病监测, 2019, 34(5): 406-410. DOI: 10.3784/j.issn.1003-9961.2019.05.009
引用本文: 邢卫东, 王路钦, 王莉, 杨震, 张治国, 李涛, 杜昕, 张灿有, 成君, 赵飞, 马树波. 2010-2017年北京市昌平区结核病登记率分析[J]. 疾病监测, 2019, 34(5): 406-410. DOI: 10.3784/j.issn.1003-9961.2019.05.009
Weidong Xing, Luqin Wang, Li Wang, Zhen Yang, Zhiguo Zhang, Tao Li, Xin Du, Canyou Zhang, Jun Cheng, Fei Zhao, Shubo Ma. Tuberculosis register rate in Changping district, Beijing, 2010–2017[J]. Disease Surveillance, 2019, 34(5): 406-410. DOI: 10.3784/j.issn.1003-9961.2019.05.009
Citation: Weidong Xing, Luqin Wang, Li Wang, Zhen Yang, Zhiguo Zhang, Tao Li, Xin Du, Canyou Zhang, Jun Cheng, Fei Zhao, Shubo Ma. Tuberculosis register rate in Changping district, Beijing, 2010–2017[J]. Disease Surveillance, 2019, 34(5): 406-410. DOI: 10.3784/j.issn.1003-9961.2019.05.009

2010-2017年北京市昌平区结核病登记率分析

Tuberculosis register rate in Changping district, Beijing, 2010–2017

  • 摘要:
    目的分析2010 — 2017年北京市昌平区结核病患者登记情况及其流行变化趋势。
    方法从结核病信息管理系统和北京区域统计年鉴收集 2010 — 2017年北京市昌平区结核病患者登记数据及人口、经济等相关数据,通过构建Probit回归模型对数据进行拟合与分析。
    结果2010 — 2017年年份与活动性肺结核患者登记率近似存在二项式关系。 剔除≥65岁常住人口比例和常住外来人口比例后,以年份平方项、年份、国内生产总值(GDP)作为自变量拟合Probit回归模型,模型适合该数据(Pearson χ2=6.510,P=0.164;对数似然比χ2=6.613,P=0.158)。 Probit回归模型拟合结果显示,2010 — 2012年结核病登记率呈现下降趋势;2012 — 2017年结核病登记率呈上升趋势(Wald χ2 =1.994×107P<0.001)。 排除年份因素对活动性患者登记率的影响后,GDP与活动性结核病患病率的回归系数为−0.001 5,活动性结核病患者登记率随着昌平区GDP的增加而降低(Wald χ2=56.620, P<0.001)。 昌平地区活动性结核病登记率与常住外来人口比例差异无统计学意义。
    结论2012年后北京市昌平区活动性结核病登记率整体上呈上升趋势;2017年结核病患者登记率较2016年略微下降,提示可能从2017年开始昌平区活动性结核病登记率将逐渐接近平稳状态。

     

    Abstract:
    ObjectiveTo understand the current status of register and the epidemic trend of tuberculosis (TB) in Changping district of Beijing during 2010–2017.
    MethodsThe TB register data, population and economy data in Changping were collected from TB Information Management System and Beijing Statistical Yearbook, and the data were modeled and analyzed by constructing Probit regression model.
    ResultsBetween 2010 and 2017, a binomial relationship might existed between the year and the register rate of active pulmonary TB cases. After excluding the proportions of permanent population aged ≥65 years and permanent immigrant population, the Probit regression model was fitted with the annual square term, year and GDP as independent variables. The model fitted the data (Pearson's χ2=6.510, P=0.164; Logarithmic likelihood ratio χ2=6.613, P=0.158). The results of Probit regression model showed that the register rate of active TB cases was in a downward trend during 2010–2012 and in an upward trend during 2012–2017 (Wald χ2=1.994×107, P<0.001). The regression coefficient of GDP and the prevalence rate of active TB was −0.001 5, and the register rate of active TB cases decreased with the increase of GDP in Changping (Wald χ2=56.620, P<0.001) after adjusting for year variable. There was no significant difference between active pulmonary TB register rate and the proportion of permanent immigrant population in Changping.
    ConclusionThe register rate of active TB cases showed an increase trend in Changping after 2012, but the register rate declined slightly in 2017 compared with 2016, suggesting that the register rate of active TB would gradually become stable in Changping since 2017.

     

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