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Chinese Journal of Antituberculosis ›› 2026, Vol. 48 ›› Issue (8): 1139-1147.doi: 10.19982/j.issn.1000-6621.20260062

• Original Articles • Previous Articles     Next Articles

Analysis of re-screening for latent tuberculosis infection in 2025 and related factors affecting infection status among rural doctors in Zhongmu County, Henan Province, based on 2017 screening

Liu Zisen1, Zhao Yaqi2, Zhang Bin1, Xin Henan2, Du Jiang2, Feng Boxuan2, He Yijun2, Li Zihan2, Yu Yilin2, Wang Dakuan1, Yan Jiaoxia1, Gao Lei2, Jin Qi2, Duan Weitao1(), Cao Xuefang2()   

  1. 1 Department of Tuberculosis Control, Center for Disease Control and Prevention of Zhongmu County, Henan Province, Zhongmu 451450, China
    2 Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 102629, China
  • Received:2026-01-28 Online:2026-08-01 Published:2026-07-30
  • Contact: Cao Xuefang, Email: caoxuefang@ipbcams.ac.cn; Duan Weitao, Email: dwtzmcdc@126.com
  • Supported by:
    National Natural Science Foundation of China(82473697);National Natural Science Foundation of China(82373647)

Abstract:

Objective: To systematically reassess the latent tuberculosis infection (LTBI) status among rural doctors in Zhongmu County, Henan Province via re-screening conducted in 2025 based on the baseline LTBI screening implemented in 2017, and to explore influencing factors associated with changes in infection status. Methods: Using an open-cohort study design, from September 12 to 21, 2025, 599 village doctors registered in Zhongmu County, Henan Province, who had participated in the 2017 baseline screening for Mycobacterium tuberculosis (MTB), were re-screened for LTBI (using the QuantiFERON-TB Gold (abbreviated as “QFT”) test) in accordance with the inclusion criteria, to assess the LTBI screening status of this population across different years. Univariate and multivariate logistic regression models were applied to identify factors correlated with QFT test results. Results: In 2025, a total of 516 participants were included in the study, of whom 20.74% (107/516) tested for LTBI, markedly lower than the LTBI prevalence of 27.71% (166/599) recorded in 2017. After age and gender standardization, the standardized LTBI prevalence declined from 23.14% in 2017 to 15.47% in 2025, with a statistically significant difference (χ2=9.163, P=0.002). Among the 333 participants who completed both rounds of MTB infection screening, the QFT reversion rate in 2025 was 21.84% (19/87) for those who were LTBI in 2017, while the QFT conversion rate in 2025 was 4.88% (12/246) for those who were not infected with MTB in 2017. Multivariate regression analysis indicated that participants who had never smoked were more likely to achieve QFT reversion compared with current smokers (adjusted OR(95%CI)=3.464 (0.803-24.101)), with a marginally significant trend (P=0.068). Participants with a practice duration of ≥26 years exhibited a greater risk of QFT conversion relative to those with a practice duration of <26 years (adjusted OR (95%CI)=7.520 (0.978-27.820)), with a marginally significant trend (P=0.052). Participants with a monthly income of <2500 RMB had significantly higher risks of QFT conversion than those with a monthly income of ≥2500 RMB (adjusted OR (95%CI)=3.706 (1.058-12.987), P=0.042). Conclusion: Consistent with the overall declining tuberculosis epidemic in Henan Province, the LTBI prevalence among rural doctors in Zhongmu County decreased significantly in 2025 relative to 2017, yet remained higher than that of the general population. While sustaining population-wide tuberculosis prevention and control strategies, targeted infection control measures should be further guaranteed and implemented for frontline medical staff such as rural doctors. Special attention should be paid to MTB infection surveillance for rural doctors who smoke, earn less than 2500 RMB monthly, or have worked in the profession for an extended period.

Key words: Mycobacterium tuberculosis, Mycobacterium infections, Hospitals, rural, Caregivers, Immunologic tests, Factor analysis, statistical

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