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Chinese Journal of Antituberculosis ›› 2026, Vol. 48 ›› Issue (8): 1130-1138.doi: 10.19982/j.issn.1000-6621.20260104

• Original Articles • Previous Articles     Next Articles

Investigation results and analysis of associated factors of tuberculosis infection and disease among school students in Xichang City, Sichuan Province, 2023

Xia Hongli1(), Hua Jiao2, Lu Jiankang3   

  1. 1 Office of Tuberculosis Prevention and Control, Xichang Center for Disease Control and Prevention, Liangshan Prefecture, Sichuan Province, Xichang 615000, China
    2 Department of Tuberculosis Prevention and Control, Xichang Center for Disease Control and Prevention, Liangshan Prefecture, Sichuan Province, Xichang 615000, China
    3 Department of Microbiology Laboratory, Xichang Center for Disease Control and Prevention, Liangshan Prefecture, Sichuan Province, Xichang 615000, China
  • Received:2026-02-27 Online:2026-08-01 Published:2026-07-30
  • Contact: Xia Hongli, Email:767466007@qq.com
  • Supported by:
    Liangshan Prefecture Science and Technology Program(21ZDYF0154)

Abstract:

Objective: The current study investigate the prevalence of Mycobacterium tuberculosis (MTB) infection and pulmonary tuberculosis (PTB), as well as their associated factors among school students in Xichang City, Sichuan Province in 2023, aiming to provide evidence for developing targeted prevention and control strategies for PTB. Methods: A total of 67922 school students in Xichang City in 2023 were enrolled as research subjects, with demographic data extracted from the student status management platform of Xichang Municipal Bureau of Education and Sports. Interferon-gamma release assay (IGRA) was performed to screen MTB infection, and chest imaging examinations were conducted for 35284 students. The chi-square test was adopted to compare intergroup differences across variables. Multivariate logistic regression was used to identify risk factors for MTB infection, while Firth logistic regression (penalized likelihood logistic regression) was applied to analyze factors associated with PTB disease. Results: The overall prevalence of MTB infection among 67922 students was 6.71% (4550/67856), and the detection rate of PTB cases was 114.84 per 100000 population (78/67922). Multivariate logistic regression analyses demonstrated that Yi ethnic students had significantly higher risks of tuberculosis infection and disease than Han students (infection: OR=2.564, 95%CI: 2.351-2.796; disease: OR=1.830, 95%CI: 1.768-1.890). Students originating from counties within the autonomous prefecture exhibited elevated risks of both infection and disease compared with local Xichang students (infection: OR=1.299, 95%CI: 1.208-1.396; disease: OR=1.318, 95%CI: 1.263-1.374). Students aged ≥15 years had higher risk of infection and disease than those younger than 15 years (infection: OR=1.384, 95%CI: 1.260-1.521; disease: OR=1.248, 95%CI: 1.163-1.332). Males showed 1.217-fold higher risk of tuberculosis infection (OR=1.217, 95%CI: 1.156-1.278) and 1.220-risk higher odds of developing PTB (OR=1.220, 95%CI: 1.148-1.298) relative to females. The risk of PTB increased progressively with grade elevation (OR=1.097, 95%CI: 1.071-1.124), and third-grade secondary vocational students bore the highest risk of MTB infection (OR=2.219, 95%CI: 1.512-3.257). Conclusion: The prevalence of MTB infection and detection rate of PTB remain relatively high among school students in Xichang City. Key populations prioritized for tuberculosis prevention and control include Yi ethnic students, students from other counties of the autonomous prefecture, students aged ≥15 years, male students, and students in higher grades. We recommend stratified active screening differentiated by high-risk subgroups to facilitate early detection and timely treatment and effectively interrupt tuberculosis transmission in campus settings.

Key words: Mycobacterium tuberculosis, Student, Prevalence, Factor analysis,statistical

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