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Analysis of spatial-temporal distribution and influencing factors of pulmonary tuberculosis in China during 2008–2015

机译:2008-2015年中国肺结核的时空分布及其影响因素分析

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摘要

At present, the number of people with tuberculosis in China is second only to India and ranks second in the world. Under such a severe case of tuberculosis in China, prevention and control of pulmonary tuberculosis are urgently needed. This study aimed to study the temporal and geographical relevance of the pathogenesis of pulmonary tuberculosis and the factors affecting the incidence of tuberculosis. Spatial autocorrelation model was used to study the spatial distribution characteristics of pulmonary tuberculosis from a quantitative level. The research results showed that the overall incidence of pulmonary tuberculosis (IPT) in China was low in the east, high in the west and had certain seasonal characteristics. We use Spatial Lag Model to explore influencing factors of pulmonary tuberculosis. It indicates that the IPT is high in areas with underdeveloped economics, poor social services and low average smoking ages. Additionally, the IPT is high in areas with high AIDS prevalence. Also, compared with Classical Regression Model and Spatial Error Model, our model has smaller values of Akaike information criterion and Schwarz criterion. Besides, our model has bigger values of coefficient of determination (R2) and log-likelihood (log L) than the other two models. Apart from that, it is more significant than Spatial Error Models in the spatial dependence test for the IPT.
机译:目前,中国的结核病人数仅次于印度,位居世界第二。在中国如此严重的结核病情况下,迫切需要对肺结核进行预防和控制。本研究旨在研究肺结核发病机理的时间和地理相关性以及影响结核发病率的因素。利用空间自相关模型从定量的角度研究了肺结核的空间分布特征。研究结果表明,我国肺结核的总体发病率在东部较低,在西部较高,并且具有一定的季节性特征。我们使用空间滞后模型来探索影响肺结核的因素。这表明在经济不发达,社会服务差和平均吸烟年龄低的地区,IPT较高。此外,在艾滋病高发地区,IPT较高。而且,与经典回归模型和空间误差模型相比,我们的模型的Akaike信息准则和Schwarz准则的值较小。此外,我们的模型比其他两个模型具有更大的确定系数(R 2 )和对数似然度(log L)值。除此之外,它在IPT的空间相关性测试中比空间误差模型更重要。

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