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Cross-sectional study identifies seven predictors of stated willingness to accept TB preventive treatment among Xinjiang close contacts

October 20, 2026
in Medicine
Ophelia Keating
By Ophelia Keating Scienmag Editorial Profile - Health Services Research
Reading Time: 3 mins read
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Why Some People Say Yes to Tuberculosis Preventive Treatment and Others Refuse

Why Some People Say Yes to Tuberculosis Preventive Treatment and Others Refuse

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A cross-sectional study in Xinjiang, China, found that 372 of 460 close contacts with tuberculosis infection expressed willingness to accept tuberculosis preventive treatment during a face-to-face structured interview, representing 80.9% of participants. The study enrolled these participants between January 1 and December 31, 2023; they were close contacts of 87 people with bacteriologically confirmed pulmonary tuberculosis. Willingness was defined as a self-reported affirmative response to a standardized survey question, so the outcome measured stated intention rather than actual treatment initiation.

According to the study abstract, the investigators screened variables with least absolute shrinkage and selection operator regression using 10-fold cross-validation and then used multivariable logistic regression to identify independent statistical predictors. They developed and internally evaluated a predictive nomogram, assessing discrimination, calibration, the Brier score, sensitivity, specificity and decision curve analysis. Analyses were performed in R version 4.3.2 using the rms package.

Five factors were positively associated with willingness to accept preventive treatment. High tuberculosis-related knowledge had the strongest reported association, with an adjusted odds ratio of 6.00 and a 95% confidence interval of 3.30 to 10.91. Health education by healthcare workers was associated with willingness at an adjusted odds ratio of 3.65 (95% confidence interval, 1.90 to 7.00). Participants reporting a history of smoking had an adjusted odds ratio of 3.59 (95% confidence interval, 1.43 to 9.06), and those reporting alcohol consumption had an adjusted odds ratio of 3.10 (95% confidence interval, 1.02 to 9.41). Cohabitation with a person with tuberculosis was also associated with willingness, with an adjusted odds ratio of 2.09 (95% confidence interval, 1.14 to 3.84).

Two factors were inversely associated with stated willingness: higher annual household income, for which the reported adjusted odds ratio was 0.076 (95% confidence interval, 0.030 to 0.193), and frequent exercise. The abstract does not specify the income unit or the change represented by the income estimate, so the odds ratio should not be interpreted as applying to each individual increase in income. The investigators cautioned that the counterintuitive associations involving smoking and alcohol history warrant careful interpretation and may reflect perceived health vulnerability or residual confounding rather than direct causal pathways. They also noted that small subgroup sizes substantially limited the numerical precision of some estimates.

The nomogram showed good discrimination in internal evaluation, with an area under the curve of 0.861 (95% confidence interval, 0.817 to 0.902), a Brier score of 0.099 and satisfactory calibration; the reported Hosmer–Lemeshow result was χ² = 4.41, P = 0.819. The study authors described the model as a structured visual aid for predicting willingness and supporting individualized counseling by frontline healthcare workers, but stated that external validation in independent Chinese settings is required before clinical implementation. As a cross-sectional study conducted in one high-burden region, the research establishes associations in the enrolled sample rather than causal effects. It does not demonstrate actual treatment uptake, clinical benefit or the effectiveness of a counseling intervention.

Subject of Research: Cross-sectional analysis of stated willingness to accept tuberculosis preventive treatment among infected close contacts in Xinjiang, China

Article Title: Determinants of willingness to accept Tuberculosis Preventive Treatment (TPT) among close contacts with Tuberculosis Infection (TBI) in Xinjiang, China

Article References: Wang, S., Peng, B., Wang, M., Jingesi, J., Wufuer, K., Liu, N., Wang, L., Wang, X., Wang, X., Xu, Y., Zhao, Y., Wang, J., Simayi, A., Ou, X., & Cao, M. (2026). Determinants of willingness to accept Tuberculosis Preventive Treatment (TPT) among close contacts with Tuberculosis Infection (TBI) in Xinjiang, China. BMC Public Health. https://doi.org/10.1186/s12889-026-29457-9

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29457-9

Keywords: tuberculosis preventive treatment, tuberculosis infection, willingness, close contacts, Xinjiang, cross-sectional study, prediction nomogram, health education, tuberculosis knowledge, Determinants, accept, Tuberculosis

Cite Scienmag News

Ophelia Keating. (October 20, 2026). Cross-sectional study identifies seven predictors of stated willingness to accept TB preventive treatment among Xinjiang close contacts. Scienmag. https://scienmag.com/cross-sectional-study-identifies-seven-predictors-of-stated-willingness-to-accept-tb-preventive-treatment-among-xinjiang-close-contacts/

Ophelia Keating. "Cross-sectional study identifies seven predictors of stated willingness to accept TB preventive treatment among Xinjiang close contacts." Scienmag, 20 October 2026, https://scienmag.com/cross-sectional-study-identifies-seven-predictors-of-stated-willingness-to-accept-tb-preventive-treatment-among-xinjiang-close-contacts/. Accessed 20 October 2026.

Ophelia Keating. "Cross-sectional study identifies seven predictors of stated willingness to accept TB preventive treatment among Xinjiang close contacts." Scienmag. October 20, 2026. https://scienmag.com/cross-sectional-study-identifies-seven-predictors-of-stated-willingness-to-accept-tb-preventive-treatment-among-xinjiang-close-contacts/

Tags: acceptclose contactscross-sectional studycross-sectional TB research Chinadeterminantshealth educationhealth education influence on TB treatmentlogistic regression in TB studiesnomogram development for TB preventionprediction nomogrampredictive modeling for TB treatment acceptancepredictors of TB treatment acceptanceTB contact tracing and interventionTB contact willingness factorsTB treatment adherence predictorstuberculosistuberculosis infectiontuberculosis knowledgetuberculosis knowledge impacttuberculosis preventive treatmentTuberculosis preventive treatment willingnesswillingnessXinjiangXinjiang tuberculosis contact study
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