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中国防痨杂志 ›› 2026, Vol. 48 ›› Issue (4): 448-458.doi: 10.19982/j.issn.1000-6621.20250453

• 论著 • 上一篇    下一篇

2016—2024年广东省结核病共病住院患者时空分布与聚集特征分析

纪链容1,2, 薛允莲2,1(), 江雪3, 袁莎莎4, 刘贵浩5, 王小万6, 邹霞7, 汪婷婷3, 周湛淇3, 周琳8()   

  1. 1 南方医科大学卫生管理学院,广州 510515
    2 南方医科大学附属广东省人民医院(广东省医学科学院)统计科,广州 510080
    3 南方医科大学附属广东省人民医院(广东省医学科学院)党办,广州 510080
    4 中国医学科学院医学信息研究所,北京 100021
    5 南方医科大学附属广东省人民医院(广东省医学科学院)科研处,广州 510080
    6 中国医学科学院卫生政策研究室,北京 100021
    7 南方医科大学附属广东省人民医院(广东省医学科学院)国际健康研究中心,广州 510080
    8 南方医科大学附属广东省人民医院(广东省医学科学院)院长办公室,广州 510080
  • 收稿日期:2025-11-16 出版日期:2026-04-10 发布日期:2026-04-02
  • 通信作者: 薛允莲,Email:xueyunlian@163.com;周琳,Email:zhoulin_z@foxmail.com
  • 基金资助:
    广东省基础与应用基础研究基金(2024A1515011745);广东省基础与应用基础研究基金(2025A1515012867);广东省科技计划项目(2020B1111170014);广东省哲学社会科学规划项目(GD24CGL39);广东省医学科学技术研究基金(C2020045)

Spatio-temporal distribution and clustering characteristics of comorbidities among tuberculosis inpatients in Guangdong Province from 2016 to 2024

Ji Lianrong1,2, Xue Yunlian2,1(), Jiang Xue3, Yuan Shasha4, Liu Guihao5, Wang Xiaowan6, Zou Xia7, Wang Tingting3, Zhou Zhanqi3, Zhou Lin8()   

  1. 1 School of Health Service Management,Southern Medical University,Guangzhou 510515,China
    2 Department of Statistics,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Southern Medical University,Guangzhou 510080,China
    3 Party Committee Office,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Southern Medical University,Guangzhou 510080,China
    4 Institute of Medical Information and Library,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China
    5 Department of Scientific Research,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Southern Medical University,Guangzhou 510080,China
    6 Division of Health Policy Research,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China
    7 Center of Global Health Research,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Southern Medical University,Guangzhou 510080,China
    8 Dean’s Office,Guangdong Provincial People’s Hospital,Guangdong Academy of Medical Sciences,Southern Medical University,Guangzhou 510080,China
  • Received:2025-11-16 Online:2026-04-10 Published:2026-04-02
  • Contact: Xue Yunlian,Email:xueyunlian@163.com;Zhou Lin,Email:zhoulin_z@foxmail.com
  • Supported by:
    Guangdong Basic and Applied Basic Research Foundation(2024A1515011745);Guangdong Basic and Applied Basic Research Foundation(2025A1515012867);Science and Technology Program of Guangdong Province(2020B1111170014);Guangdong Philosophy and Social Science Foundation(GD24CGL39);Medical Science and Technology Research Foundation of Guangdong Province(C2020045)

摘要:

目的:分析2016—2024年广东省结核病住院患者的共病谱特征、时空分布格局与空间聚集模式,为区域化精准防控提供科学依据。方法:基于“广东省卫生健康统计信息网络直报系统”,提取广东省全域住院结核病患者病案首页信息(ICD-10:A15-A19),识别20种常见共病类型。采用描述性统计分析的方法分析共病流行特征,利用全局与局部Moran’s I指数分析主要共病组合(结核病-高血压、结核病-糖尿病、结核病-慢性阻塞性肺疾病)的空间自相关性与聚集特征。结果:共纳入729937例结核病患者,64.07%(467645/729937)合并至少1种共病。结核病-高血压共病率从2016年的13.71%(11285/82329)上升至2024年的21.00%(16697/79495);结核病-糖尿病共病率从12.17%(10020/82329)上升至19.53%(15524/79495);结核病-慢性阻塞性肺疾病共病率波动范围为9.28%(7229/77870)~11.22%(9238/82329),整体维持在10.00%左右。空间分析显示,结核病-高血压共病率呈“外围高、核心低”格局,高-高聚集区由珠江三角洲多城市(2016—2021、2023年)逐步转移至揭阳市(2023—2024年);结核病-糖尿病共病率在粤东地区持续高发,空间相关性最强(Moran’s I>0.34);结核病-慢性阻塞性肺疾病共病率呈现“北高南低”分布,高-高聚集区稳定集中于粤北(2016—2024年)及部分粤东城市(2016—2024年)。结论:广东省结核病共病率持续增长,且具有明显的时空异质性与聚集特征。应构建分区分类的精准防控体系,针对不同区域主导共病类型实施差异化干预,以提升结核病共病整体防控效能。

关键词: 结核, 共病现象, 住院病人, 时空聚类分析, 流行病学研究特征(主题)

Abstract:

Objective:To analyze the characteristics of the comorbidity spectrum,spatio-temporal distribution pattern and spatial clustering mode of hospitalized tuberculosis patients in Guangdong Province from 2016 to 2024,so as to provide scientific evidence for regionalized and precise prevention and control. Methods:Based on the Guangdong Provincial Health Statistical Information Network Reporting System,the front page information of medical records of hospitalized tuberculosis patients (ICD-10:A15-A19) was extracted,and 20 common types of comorbidities were identified. Descriptive statistical analysis was adopted to analyze the epidemiological characteristics of comorbidities. Global and local Moran’s I were applied to examine the spatial autocorrelation and clustering characteristics of the major comorbidity combinations,namely tuberculosis-hypertension,tuberculosis-diabetes mellitus,and tuberculosis-chronic obstructive pulmonary disease. Results:A total of 729937 tuberculosis patients were enrolled,among whom 64.07% (467645/729937) had at least one comorbidity. The comorbidity rate of tuberculosis-hypertension increased from 13.71% (11285/82329) in 2016 to 21.00% (16697/79495) in 2024;that of tuberculosis-diabetes mellitus increased from 12.17% (10020/82329) to 19.53% (15524/79495);and the comorbidity rate of tuberculosis-chronic obstructive pulmonary disease fluctuated from 9.28% (7229/77870) to 11.22% (9238/82329),remaining at approximately 10.00% overall. Spatial analysis revealed that the tuberculosis-hypertension exhibited a distribution pattern of “high in peripheral areas and low in core areas”,and the high-high clustering areas gradually shifted from multiple cities in the Pearl River Delta region (2016—2021,2023) to Jieyang City (2023—2024). Tuberculosis-diabetes mellitus remained highly prevalent in eastern Guangdong,with the strongest spatial autocorrelation (Moran’s I>0.34). Tuberculosis-chronic obstructive pulmonary disease showed a distribution pattern of “high in the north and low in the south”,and the high-high clustering areas were stably concentrated in northern Guangdong (2016—2024) and parts of eastern Guangdong (2016—2024). Conclusion:The burden of tuberculosis comorbidities in Guangdong Province has continued to escalate with significant spatio-temporal heterogeneity and clustering characteristics. A regionalized and categorized precision prevention and control system should be established,and differentiated interventions should be implemented for the dominant comorbidity types in different regions,so as to enhance the overall prevention and control efficacy of tuberculosis comorbidities.

Key words: Tuberculosis, Comorbidity, Inpatients, Space-time clustering, Epidemiologic study characteristics as topic

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