尹金风,黄若雯,姜慧,高志东,许王莉,贺晓新,李卫民.北京市2008-2018年肺结核时空分布及影响因素分析[J].Chinese journal of Epidemiology,2021,42(7):1240-1245 |
北京市2008-2018年肺结核时空分布及影响因素分析 |
Spatio-temporal distribution of pulmonary tuberculosis and influencing factors in Beijing, 2008-2018 |
Received:January 06, 2021 |
DOI:10.3760/cma.j.cn112338-20210106-00008 |
KeyWord: 肺结核 报告发病率 城市化 贝叶斯时空模型 时空分布 |
English Key Word: Pulmonary tuberculosis Reported incidence Urbanization Bayesian model Spatio-temporal distribution |
FundProject:北京市自然科学基金重点研究专项(Z200001);国家自然科学基金(U1903118);北京市医院管理局“登峰”人才计划(DFL20181602) |
Author Name | Affiliation | E-mail | Yin Jinfeng | Beijing Chest Hospital, Capital Medical University, Beijing 101149, China | | Huang Ruowen | School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China | | Jiang Hui | Beijing Chest Hospital, Capital Medical University, Beijing 101149, China | | Gao Zhidong | Beijing Research Institute of Tuberculosis Control, Beijing 100035, China | guhu751029@126.com | Xu Wangli | School of Statistics, Renmin University of China, Beijing 100872, China Center for Applied Statistics, Renmin University of China, Beijing 100872, China | wlxu@ruc.edu.cn | He Xiaoxin | Beijing Research Institute of Tuberculosis Control, Beijing 100035, China | | Li Weimin | Beijing Chest Hospital, Capital Medical University, Beijing 101149, China | |
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Abstract: |
目的 分析2008-2018年北京市肺结核报告发病率的时空分布特征及影响因素。方法 肺结核病例数据来源于2008-2018年中国疾病预防控制信息系统结核病信息管理系统,采用ArcGIS 10.2软件可视化肺结核发病率的时空分布;街道/乡镇尺度上分析(Getis's Gi*统计量)发病率的空间聚集性;贝叶斯时空模型分析影响其时空分布的因素包括城市化率、人均GDP、每千人口医院床位数、常住外来人口和人口密度。结果 2008-2018年北京市肺结核报告发病率呈下降趋势,从58.64/10万下降到30.43/10万。通州区、昌平区等城市发展新区的发病率较高,热点集中在其局部地区;东城区、西城区等功能核心及拓展区的发病率较低,冷点也集中在该区域。肺结核发病风险与城市化率和常住外来人口相关,其中,城市化率每增加1%,患肺结核的RR值也会增加1%;常住外来人口每增加1万人,患肺结核的RR值会增加0.6%。结论 北京市肺结核的防控重点区域需关注城市发展新区;城市化进程加快的同时,需加强常住外来人口中的结核病防控,以期降低当地结核病发病率。 |
English Abstract: |
Objective To understand the spatiotemporal distribution of pulmonary tuberculosis (TB) and influencing factors in Beijing from 2008 to 2018. Methods The incidence data of pulmonary TB in Beijing from 2008 to 2018 were from Tuberculosis Information Management System of Chinese Disease Prevention and Control Information System. Software ArcGIS 10.2 was used to visualize the spatiotemporal distribution of pulmonary TB incidence. Getis's Gi* statistic was applied to analyze the spatial clustering of pulmonary TB incidence at street/township scale. Bayesian spatiotemporal model was applied to analyze factors affecting its spatiotemporal distribution, including urbanization rate, GDP per capita, number of hospital beds per thousand population, permanent migrant population and population density. Results The reported pulmonary TB incidence showed a downward trend in the past 11 years in Beijing, from 58.64/100 000 to 30.43/100 000. The incidences were higher in Tongzhou, Changping and other newly developed urban districts, with the hot spots concentrated in local areas of these districts. The incidences of pulmonary TB were lower in Dongcheng, Xicheng and other old urban districts-with the cold spots also concentrated in these area. The risk for the incidence of pulmonary TB was associated with the urbanization rate and the permanent migrant population. For every 1% increase in the urbanization rate, the relative risk of pulmonary TB would increase by 1%. For every 10 000 person increase of permanent migrant population, the relative risk of pulmonary TB would increase by 0.6%. Conclusions In Beijing, the current pulmonary TB prevention and control needs to be focused on the newly developed urban areas. Due to the accelerated process of urbanization, it is necessary to strengthen TB prevention and control in permanent migrant population to reduce the incidence of TB in Beijing. |
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