结核与肺部疾病杂志 ›› 2025, Vol. 6 ›› Issue (3): 304-309.doi: 10.19983/j.issn.2096-8493.20250041

• 论著 • 上一篇    下一篇

2010—2022年西藏自治区肺结核发病时空特征分析

尼玛曲措1, 吕恒梁2,3, 胡凤梅1, 张文义2,3, 徐元勇2,3()   

  1. 1.西藏自治区疾病预防控制中心结核与麻风病防治所,拉萨 850000
    2.中国医科大学公共卫生学院流行病学教研室,沈阳 110000
    3.中国人民解放军疾病预防控制中心疾病监测科,北京 100071
  • 收稿日期:2025-03-05 出版日期:2025-06-20 发布日期:2025-06-12
  • 通信作者: 徐元勇,Email: xyy_827@sina.com
  • 基金资助:
    2024年公共卫生人才支持项目(2024-12-25)

Spatiotemporal analysis on pulmonary tuberculosis in the Xizang Autonomous Region, 2010—2022

Nima Qucuo1, Lyu Hengliang2,3, Hu Fengmei1, Zhang Wenyi2,3, Xu Yuanyong2,3()   

  1. 1. Tuberculosis and Leprosy Prevention and Control Institute,Xizang Autonomous Region Center for Disease Control and Prevention, Lhasa 850000,China
    2. Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110000, China
    3. Department of Disease Surveillance, Chinese People’s Liberation Army Center for Disease Control and Prevention, Beijing 100071, China
  • Received:2025-03-05 Online:2025-06-20 Published:2025-06-12
  • Contact: Xu Yuanyong,Email: xyy_827@sina.com
  • Supported by:
    Public Health Talent Support Project in 2024(2024-12-25)

摘要:

目的:分析西藏自治区(简称“西藏”)肺结核发病时空流行特征,为制定肺结核防治政策提供参考依据。方法:通过“全民健康保障信息化工程疾病预防控制信息系统—传染病监测系统”收集发病日期为2010年1月1日至2022年12月31日现住址为西藏的肺结核病例。采用 Joinpoint 回归分析肺结核发病的时间趋势,并通过年度变化百分比(average annual percentage change, APC)对变化趋势进行评估。运用全局自相关和时空扫描统计分析西藏肺结核在全区范围内的整体以及局部聚集情况,通过最大似然比(log likelihood ratio, LLR)评估聚集区域内相对区域外的风险性。结果:2010—2022 年西藏累计报告肺结核患者60391例,平均报告发病率为141.97/10万。2010—2022年报告发病率由2010年的118.34/10万上升至2019年的182.38/10万(APC=4.56%, 95%CI: 2.98%~6.18%),随后下降至2022年的95.96/10万(APC=-16.50%, 95%CI: -23.22%~-9.20%),女性发病率在2010—2020年(APC=5.45%, 95%CI: 3.93%~6.99%)的上升幅度高于男性在2010—2019年的上升幅度(APC=3.32%, 95%CI: 2.27%~4.38%)。时空扫描统计发现:一级聚集区位于昌都市(LLR=2105.41, P<0.001),聚集时间为2016年1月至2022年6月,二级聚集区主要位于那曲市东部(LLR=434.55, P<0.001),聚集时间为2018年1月至2022年4月。结论:2010—2022年西藏肺结核报告发病率呈先升后降的趋势。西藏肺结核发病呈现明显的时空聚集性,高发区聚集在昌都市、那曲市东部,未来应重点加强对高发区人群的健康教育和筛查力度。

关键词: 结核,肺, 时空聚类分析, 发病率, 西藏自治区

Abstract:

Objective: To analyze the spatiotemporal of pulmonary tuberculosis (PTB) in the Xizang Autonomous Region (Xizang) and provide references for formulating PTB prevention and control policies. Methods: The cases of PTB with onset dates between January 1, 2010 and December 31, 2022, and current residence in Xizang were extracted from “Infectious Disease Surveillance System of the National Health Security Information Project-Disease Prevention and Control Information System”. Joinpoint regression was used to analyze the time trend of the incidence rate of PTB, and the annual percentage change (APC) was used to evaluate the change trend. Global autocorrelation and spatiotemporal scan statistic were used to analyze the overall and space-time clusters of PTB in Xizang. The log likelihood ratio (LLR) was used to evaluate the risk within the clustered area relative to outside the area. Results: A total of 60391 PTB cases were reported in Xizang from 2010 to 2022, with an average reported incidence rate of 141.97 per 100000 population. The reported incidence rate increased from 118.34 per 100000 population in 2010 to 182.38 per 100000 population in 2019 (APC=4.56%, 95%CI: 2.98%-6.18%), and then decreased to 95.96 per 100000 population in 2022 (APC=-16.50%, 95%CI: -23.22--9.20%). The increase in female incidence rate from 2010 to 2020 (APC=5.45%, 95%CI: 3.93%-6.99%) was higher than that in male incidence from 2010 to 2019 (APC=3.32%, 95%CI: 2.27%-4.38%). Spatiotemporal scan statistic analysis revealed that the most likely cluster area was identified in Changdu City (LLR=2105.41, P<0.001), with a clustering period from January 2016 to June 2022. The secondary cluster area was mainly identified in the eastern part of Naqu City (LLR=434.55, P<0.001) with its clustering period spawning from January 2018 to April 2022. Conclusion: The reported incidence rate of PTB in Xizang from 2010 to 2022 exhibited a trend of initial increase followed by a subsequent decline. The PTB incidence showed significant spatiotemporal aggregation, particularly clustered in Changdu and eastern Nagqu. Future efforts should prioritize strengthening health education and enhancing screening measures for populations in these high-risk regions.

Key words: Tuberculosis, pulmonary, Space-time clustering, Incidence, Xizang autonomous region

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