1. BMI and Drug-Resistant TB
- Underweight individuals show higher susceptibility to isoniazid (INH)-resistant TB.
- Overweight and obese patients have an increased risk of MDR-TB.
- Comorbidities like diabetes and hypertension correlate with higher drug resistance.
- Suggestion: Implement BMI-based TB screening protocols to identify at-risk individuals early.
2. Paradoxical Link Between Obesity and TB
- Obesity is directly protective against TB despite its association with diabetes.
- Higher BMI reduces TB risk even in diabetic individuals.
- Socioeconomic factors may partially explain this protective effect.
- Suggestion: Investigate mechanisms behind obesity’s protective role to refine TB prevention strategies.
3. Gaps in the TB Care Cascade
- Delays in diagnosis and treatment worsen TB outcomes.
- Country-specific factors (e.g., HIV in Kenya, MDR-TB in Moldova) influence TB burden.
- Addressing care gaps can significantly reduce TB incidence and mortality.
- Suggestion: Strengthen TB care pathways with faster diagnosis and treatment initiation.
4. Economic and Healthcare Factors in TB Control
- Higher GDP and healthcare expenditure correlate with lower TB incidence.
- Cost-effective interventions improve access to TB care.
- Financial barriers hinder TB elimination efforts in lower-income settings.
- Suggestion: Increase TB funding through sustainable health financing models.
5. Strategies for TB Elimination
- Country-specific interventions (e.g., nutrition in India, latent TB treatment in China) are essential.
- Active Case Finding (ACF) is hindered by logistical, administrative, and social barriers.
- Integrating TB screening with other health programs enhances outreach.
- Suggestion: Streamline ACF processes with digital tools and better community incentives.
References:
- Song, W.M., Guo, J., Xu, T.T., Li, S.J., Liu, J.Y., Tao, N.N., Liu, Y., Zhang, Q.Y., Liu, S.Q., An, Q.Q. and Li, Y.F., 2021. Association between body mass index and newly diagnosed drug-resistant pulmonary tuberculosis in Shandong, China from 2004 to 2019. BMC pulmonary medicine, 21, pp.1-14.
- Lin, H.H., Wu, C.Y., Wang, C.H., Fu, H., Lönnroth, K., Chang, Y.C. and Huang, Y.T., 2018. Association of obesity, diabetes, and risk of tuberculosis: two population-based cohorts. Clinical Infectious Diseases, 66(5), pp.699-705.
- Vesga, J.F., Hallett, T.B., Reid, M.J., Sachdeva, K.S., Rao, R., Khaparde, S., Dave, P., Rade, K., Kamene, M., Omesa, E. and Masini, E., 2019. Assessing tuberculosis control priorities in high-burden settings: a modelling approach. The Lancet Global Health, 7(5), pp.e585-e595.
- Menzies, N.A., Gomez, G.B., Bozzani, F., Chatterjee, S., Foster, N., Baena, I.G., Laurence, Y.V., Qiang, S., Siroka, A., Sweeney, S. and Verguet, S., 2016. Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models. The Lancet global health, 4(11), pp.e816-e826.
- Sorokina, M., Ukubayev, T. and Koichubekov, B., 2023. Tuberculosis incidence and its socioeconomic determinants: developing a parsimonious model. Annali di Igiene, Medicina Preventiva e di Comunita, 35(4): 468-479.
- Houben, R.M., Menzies, N.A., Sumner, T., Huynh, G.H., Arinaminpathy, N., Goldhaber-Fiebert, J.D., Lin, H.H., Wu, C.Y., Mandal, S., Pandey, S. and Suen, S.C., 2016. Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: a combined analysis of 11 mathematical models. The Lancet Global Health, 4(11), pp.e806-e815.
- Shewade, H.D., Ravichandran, P., Pradeep, S.K., Kiruthika, G., Shanmugasundaram, D., Chadwick, J., Iyer, S., Chowdhury, A., Tumu, D., Shah, A.N. and Vadera, B., 2024. Bridging the “know-do” gap to improve active case finding for tuberculosis in India: A qualitative exploration into national tuberculosis elimination program staffs’ perspectives. PloS one, 19(11), p.e0309750.
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