Journal of Shandong University (Health Sciences) ›› 2025, Vol. 63 ›› Issue (7): 92-101.doi: 10.6040/j.issn.1671-7554.0.2024.1389

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Association between long-term mixed air pollution exposure and the risk of drug-resistant tuberculosis based on three statistical models

WANG Ying1, LI Huaichen2, LONG Fei3, LIU Yi1   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Department of Pulmonary and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China;
    3. Department of Respiratory and Critical Care Medicine, The Third Affiliated Hospital of Shandong First Medical University, Jinan 250031, Shandong, China
  • Published:2025-07-08

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Abstract: Objective To study the effects of long-term mixed exposure to five common air pollutants(PM10, PM2.5, SO2, NO2, and O3)on the incidence of drug-resistant tuberculosis(DR-TB), and to provide a basis for the prevention and treatment of DR-TB. Methods Laboratory test results, clinical indicators and sociodemographic information of 3,369 patients who were first diagnosed DR-TB patients in Shandong Province from 2015 to 2019 were collected. Patients were monitored for exposure to air pollutants during four exposure windows(90, 180, 270 and 360 days before diagnosis). The Logistic regression(LR)model was used to evaluate the impact of a single pollutant. Weighted quantile sum(WQS)and Bayesian kernel machine regression(BKMR)models were applied to examine the joint effects of pollutants, with the BKMR model was used to study the concentration-response(C-R)relationship between pollutants and the risk of DR-TB, as well as the interactions between pollutants. Results The results of LR model showed that the increase of O3 concentration was associated with the increased risk of IR-TB during the 90 days exposure window(OR=1.008,P=0.02). The results of WQS and BKMR models showed that the mixed exposure to air pollutants reduced the risk of IR-TB and MDR-TB(β2=0.75, P=0.01). The results of the BKMR model showed that NO2 reduced the risk of IR-TB(90 days: β=-0.12, 95%CI: -0.22~-0.02; 360 days: β=-0.10, 95%CI: -0.19~-0.01)and MDR-TB(90 days: β=-0.10, 95%CI: -0.19~-0.01; 360 days: β=-0.13, 95%CI: -0.22~-0.04), and the association was statistically significant(P<0.05). In addition, the model also showed a non-linear relationship between NO2 and the risk of DR-TB, as well as interactions with other pollutants under mixed exposure conditions. Conclusion High levels of O3 exposure can increase the risk of IR-TB; long-term exposure to mixed air pollutants was not associated with the risk of DR-TB. Long-term exposure to mixed air pollutants is not associated with the risk of DR-TB.

Key words: Bayesian kernel machine regression, Drug-resistant tuberculosis, Mixed exposure to air pollutants, Health risk assessment

CLC Number: 

  • R122.7
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