Monday, February 24, 2025

Paradoxical Link Between Obesity and TB

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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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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