2014—2019年广东省耐多药结核病时空分布特征与风险评估  

Spatio-temporal analysis and risk assessment of multidrug-resistant tuberculosis in Guangdong Province,2014—2019

作　　者：胡轶君 徐怡婷 蹇荣华 吴惠忠 苏静 肖建鹏 蒋辰祺 刘涛[1] 王嘉雯 陈亮 Hu Yijun;Xu Yiting;Jian Ronghua;Wu Huizhong;Su Jing;Xiao Jianpeng;Jiang Chenqi;Liu Tao;Wang Jiawen;Chen Liang(School of Basic Medicine and Public Health,Jinan University,Guangzhou 510632,China;Director’s Office,Guangzhou Chest Hospital,Guangzhou 510095,China;Medical Affairs Department,Southern University of Science and Technology Hospital,Shenzhen 518055,China;Department of Prevention and Treatment,Guangdong Provincial Tuberculosis Control Center,Guangzhou 510630,China;Environmental Health Research Laboratory,Guangdong Provincial Institute of Public Health,Guangzhou 511430,China;Science and Education Section,Guangdong Provincial Tuberculosis Control Center,Guangzhou 510630,China)

机构地区：[1]暨南大学基础医学与公共卫生学院,广州510632 [2]广州市胸科医院院长办,广州510095 [3]南方科技大学医院医务部,深圳518055 [4]广东省结核病控制中心防治科,广州510630 [5]广东省公共卫生研究院环境健康研究室,广州511430 [6]广东省结核病控制中心科教科,广州510630

出　　处：《中国防痨杂志》2025年第5期639-646,共8页Chinese Journal of Antituberculosis

基　　金：广东省感染性疾病(结核病)临床医学研究中心(2020B1111170014)。

摘　　要：目的:分析2014—2019年广东省耐多药结核病(multidrug resistant tuberculosis,MDR-TB)的时空分布特征,发现MDR-TB高风险区域并探索其发病相关影响因素,为卫生部门和政府机构提供科学依据和技术支撑。方法:采用“中国疾病预防控制信息系统”子系统“结核病信息管理系统”收集2014—2019年广东省登记的MDR-TB患者的基本资料,收集相关社会因素和气象因素,采用局部加权回归、空间自相关分析等方法探索MDR-TB发病的时空分布规律;建立两阶段零膨胀泊松模型(Zero-Inflated Poisson model,ZIP),并应用模型分析与MDR-TB发病相关的影响因素。结果:2014—2019年期间广东省累计登记MDR-TB患者3358例,年均登记发病率为0.47/10万(3358/720530000),发病率从2014年的0.20/10万(233/114890000)上升至2019年的0.53/10万(667/124890000),差异有统计学意义(χ^(2)_(趋势)=158.980,P<0.001),且病例多集中于秋冬季节;空间上识别出深圳市、东莞市、广州市的平均MDR-TB标化发病比(standard incidence ratio,SIR)较高,分别为2.36、2.36和1.74;ZIP模型显示,MDR-TB发病风险与相对湿度(RR=1.168,95%CI:1.031~1.323)、性别比(RR=1.312,95%CI:1.192~1.473)和流动人口比例(RR=1.176,95%CI:1.094~1.263)呈正相关,与夜间灯光指数(RR=0.752,95%CI:0.668~0.848)和每千人病床数(RR=0.672,95%CI:0.589~0.776)呈负相关。结论:MDR-TB发病存在时间和空间的分布差异,并与社会经济和气象因素显著相关,今后应在高风险地区和高危人群中实施相应的公共卫生干预措施和结核病控制策略及资源配置。Objective:To analyze the spatial and temporal distribution characteristics of multidrug resistant tuberculosis(MDR-TB)in Guangdong Province from 2014 to 2019,identify high-risk areas for MDR-TB and explore its influencing factors,so as to provide scientific basis and technical support for health department and governmental agencies.Methods:Basic data of MDR-TB patients registered in Guangdong Province from 2014 to 2019 was collected using the“Tuberculosis Information Management System”,a subsystem of the“China Information System for Disease Control and Prevention”.Related social and meteorological factors were collected and local weighted regression and spatial autocorrelation analysis were used to explore the spatial and temporal distribution of the incidence of MDR-TB;a two-stage zero-inflated Poisson model(ZIP)was established to analyze influencing factors associated with the incidence of MDR-TB.Results:During the period of 2014—2019,a total of 3358 MDR-TB patients were registered in Guangdong Province,with an average annual registered incidence rate of 0.47/100000(3358/720530000);temporally the registered MDR-TB cases in Guangdong Province showed a statistically significant trend of increasing(χ^(2)_(trend)=158.980,P<0.001),with a registered incidence rate of 0.20/100000 in 2014(233/114890000)increased to 0.53/100000(667/124890000)in 2019,and the onset of the disease was mostly concentrated in the fall and winter seasons.Spatially,higher mean SIR were identified in Shenzhen,Dongguan,and Guangzhou(2.36,2.36,and 1.74,respectively).The ZIP model showed that the risk of MDR-TB incidence was positively associated with relative humidity(RR=1.168,95%CI:1.031-1.323),sex ratio(RR=1.312,95%CI:1.192-1.473),and proportion of floating population(RR=1.176,95%CI:1.094-1.263),and was negatively associated with nighttime light index(RR=0.752,95%CI:0.668-0.848)and medical beds per 1000 population(RR=0.672,95%CI:0.589-0.776).Conclusion:MDR-TB morbidity has temporal and spatial distribution differences and is signific

关 键 词：结核 抗多种药物性 因素分析 统计学 时空聚类分析 

分 类 号：R52[医药卫生—内科学] R181.3[医药卫生—临床医学]