BMI, diabetes, and risk of tuberculosis

A population-based cohort study in Eastern China (2013–2021) followed 27,807 individuals to examine tuberculosis (TB) incidence and risk factors. The median age was 50 years, with 18.3% over 65 years old. About half were female, and 34.8% were overweight or obese. Smoking and alcohol consumption were reported by 20.9% and 17.4%, respectively, while 58.8% had BCG vaccination. Diabetes prevalence was 6%.[1] See also: https://tbreadingnotes.blogspot.com/2024/08/assessing-spatiotemporal-patterns-of.html

Over seven years, 108 individuals developed TB (incidence rate: 50.4 per 100,000 person-years). Diabetes was linked to a higher TB incidence (131.2 vs. 47.1 per 100,000 person-years, P = 0.008). Among those with a BMI ≤24 kg/m², diabetics had a 3.4 times higher TB incidence than non-diabetics, whereas no difference was seen among those with a BMI >24 kg/m².[1] See also: https://tbreadingnotes.blogspot.com/2024/08/a-modelling-framework-to-support.html

Males had a higher TB incidence than females, while BCG scars were associated with lower TB rates. Risk factors in a multivariable model included male sex, older age, and diabetes. Higher BMI was protective against TB. Among those with BMI ≤24 kg/m², diabetes significantly increased TB risk, but not in those with BMI >24 kg/m². BCG scars reduced TB risk in individuals with low BMI.[1]

A study using data from Korea's National Health Insurance Service analyzed 4.4 million adults and found that diabetes increases TB risk by 48%, with a 57% higher risk in those diabetic for 5+ years. The association is stronger in men and younger adults, and new diabetics with the highest fasting plasma glucose levels face a 79% increased TB risk.[2]

A Taiwan NHIRD study (2002–2013) found that adults face a higher risk of diabetes, AMI, and stroke after TB treatment, particularly if treatment lasts 7–12 months. Age, gender, and pre-existing NCDs are key predictors, highlighting the need for vigilant post-TB monitoring.[3]

References:

1. Lu, P., Zhang, Y., Liu, Q., Ding, X., Kong, W., Zhu, L. and Lu, W., 2021. Association of BMI, diabetes, and risk of tuberculosis: a population-based prospective cohort. International Journal of Infectious Diseases, 109, pp.168-173.

2. Yoo JE, Kim D, Han K, Rhee SY, Shin DW, Lee H. Diabetes status and association with risk of tuberculosis among Korean adults. JAMA network open. 2021 Sep 1;4(9):e2126099.

3. Salindri, A.D., Wang, J.Y., Lin, H.H. and Magee, M.J., 2019. Post-tuberculosis incidence of diabetes, myocardial infarction, and stroke: retrospective cohort analysis of patients formerly treated for tuberculosis in Taiwan, 2002–2013. International Journal of Infectious Diseases, 84, pp.127-130.

Health System Strengthening

Tuberculosis Preventive Therapy (TPT) Initiation & Health System Strengthening

• Health system strengthening interventions increased TPT initiation among household contacts, especially in LMICs.
• Countries with policies supporting TPT for all age groups had higher initiation rates (up to 78%).
• Cost-effective implementation when tailored to local contexts and sustained with training/support.

TB Diagnosis & Infection Control in Healthcare Facilities

• Transition to auramine-rhodamine fluorescence microscopy improved early TB detection and reduced patient infectiousness.
• The proportion of hospitalized TB cases dropped from 45% to 27%; median non-isolated infectiousness reduced from 12.5 days to 3 days.
• Upgraded ventilation, UV germicidal systems, and early physician alertness enhance TB infection control.
• High-traffic outpatient areas (internal medicine, family medicine) should prioritize TB screening.

Diabetes & Tuberculosis Interaction

• TB-DM patients had lower treatment success rates (74.4% vs. 84.9%) and increased multidrug-resistant TB risk.
• Prediabetes is prevalent among TB patients and affects immune response, potentially worsening TB outcomes.
• Managing dyslipidemia in T2D patients may reduce TB risk; statins might lower active TB incidence.
• BCG vaccination may help modulate lipid metabolism and reduce TB risk in high-risk populations.

TB Diagnosis & Screening in Resource-Limited Settings

• Simple clinical risk scores (age, sex, symptoms, HIV, diabetes) improve early TB identification in clinics with limited diagnostics.
• Combining WHO symptom screening with tuberculin skin tests enhances sensitivity.
• Predictive models incorporating BMI, CD4 count, and ART duration improve TB screening in co-infected populations.
• Immediate, standardized empirical diagnosis needed to prevent TB treatment delays.

TB & Prediabetes

• TB patients with prediabetes face higher risks of treatment failure, recurrence, and modifications.
• The role of prediabetes in TB progression remains unclear, but chronic inflammation and immune dysfunction are potential factors.
• Paradoxically, one study found a 27% lower TB risk in prediabetic individuals, warranting further research.

Practical Recommendations

• Strengthen health system interventions to increase TPT uptake, particularly in LMICs.
• Enhance early TB detection through improved diagnostic tools and physician alertness.
• Implement targeted TB screening and infection control in high-risk hospital areas.
• Improve diabetes management in TB patients to enhance treatment success.
• Use cost-effective clinical risk scores for TB diagnosis in resource-limited settings.
• Further investigate the complex relationship between TB, prediabetes, and metabolic disorders for refined public health strategies.

Curated by Yoseph Leonardo Samodra.

References:

1. Sun H-Y, Wang J-Y, Chen Y-C, Hsueh PR, Chen Y-H, Chuang Y-C, et al. (2020) Impact of introducing fluorescent microscopy on hospital tuberculosis control: A before-after study at a high caseload medical center in Taiwan. PLoS ONE 15(4): e0230067.
2. Pan, S.C., Chen, C.C., Chiang, Y.T., Chang, H.Y., Fang, C.T. and Lin, H.H., 2016. Health care visits as a risk factor for tuberculosis in Taiwan: a population-based case–control study. American journal of public health, 106(7), pp.1323-1328.
3. Oxlade, O., Benedetti, A., Adjobimey, M., Alsdurf, H., Anagonou, S., Cook, V.J., Fisher, D., Fox, G.J., Fregonese, F., Hadisoemarto, P. and Hill, P.C., 2021. Effectiveness and cost-effectiveness of a health systems intervention for latent tuberculosis infection management (ACT4): a cluster-randomised trial. The Lancet Public Health, 6(5), pp.e272-e282.
4. Baik, Y., Rickman, H.M., Hanrahan, C.F., Mmolawa, L., Kitonsa, P.J., Sewelana, T., Nalutaaya, A., Kendall, E.A., Lebina, L., Martinson, N. and Katamba, A., 2020. A clinical score for identifying active tuberculosis while awaiting microbiological results: development and validation of a multivariable prediction model in sub-Saharan Africa. PLoS medicine, 17(11), p.e1003420.
5. Van Wyk, S.S., Lin, H.H. and Claassens, M.M., 2017. A systematic review of prediction models for prevalent pulmonary tuberculosis in adults. The International Journal of Tuberculosis and Lung Disease, 21(4), pp.405-411.
6. Lee, E.H., Lee, J.M., Kang, Y.A., Leem, A.Y., Kim, E.Y., Jung, J.Y., Park, M.S., Kim, Y.S., Kim, S.K., Chang, J. and Kim, S.Y., 2017. Prevalence and impact of diabetes mellitus among patients with active pulmonary tuberculosis in South Korea. Lung, 195, pp.209-215.
7. Segura-Cerda, C.A., López-Romero, W. and Flores-Valdez, M.A., 2019. Changes in host response to mycobacterium tuberculosis infection associated with type 2 diabetes: beyond hyperglycemia. Frontiers in cellular and infection microbiology, 9, p.342.
8. Liang, L. and Su, Q., 2024. Prediabetes and the treatment outcome of tuberculosis: A meta‐analysis. Tropical Medicine & International Health, 29(9), pp.757-767.
9. Ko, T.H., Chang, Y.C., Chang, C.H., Liao, K.C.W., Magee, M.J. and Lin, H.H., 2023. Prediabetes and risk of active tuberculosis: a cohort study from Northern Taiwan. International Journal of Epidemiology, 52(3), pp.932-941.

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Biological, Social, and Environmental Factors in TB

1. Tuberculosis (TB) Epidemiology in Spain

• In 2021, Spain reported 3,754 TB cases, with a notification rate (NR) of 7.61 per 100,000; this marked a 2.18% decline from 2020 and a 28.07% reduction from 2015.
• Spain surpassed its TB control goals by 2020, reducing overall TB rates by 26.5% and pulmonary TB by 6% annually, maintaining its status as a low-incidence TB country.
• Higher TB rates were reported in northern regions—Ceuta, Galicia, Catalonia, Rioja, and the Basque Country—while the Canary Islands and parts of southern Spain had lower rates.
• TB incidence was 1.7 times higher in men than women, with nearly half of the cases among foreign-born individuals, typically younger than native-born cases; TB mortality was 2.6 times higher in males.
• Foreign-born TB cases primarily came from high-burden countries (Morocco, Romania, Bolivia, Peru, Pakistan); over half had lived in Spain for over 10 years, while only 13% were recent arrivals (<2 years).

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2. Geographic, Seasonal, and Environmental Factors in TB

• A clear north–south gradient exists in TB incidence across Spain, with the highest rates in northern provinces (e.g., A Coruña, Pontevedra), well above the national average.
• Regions with higher rainfall and fewer sunshine hours (e.g., Gipuzkoa, Asturias) had significantly higher TB rates, particularly extrapulmonary TB.
• Spatial regression analyses confirmed a strong link between reduced sunlight and higher TB incidence, reinforcing the potential role of vitamin D in TB susceptibility.
• TB cases peak seasonally in spring (May), about four months after winter’s lowest sunlight levels, suggesting an environmental influence on TB trends.
• These findings highlight the relevance of environmental and seasonal factors, particularly sunlight exposure, in modulating TB incidence and informing prevention strategies.

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3. Active Case Finding (ACF) and TB Control in High-Risk Groups

• ACF is effective for early TB detection, especially among migrants, the homeless, prisoners, and impoverished populations, where it outperforms passive case finding.
• ACF strategies include door-to-door screening, mobile clinics, and point-of-care tools like battery-operated GeneXpert systems (e.g., XACT), improving early detection and reducing transmission.
• Mobile clinics are more efficient and scalable than labor-intensive door-to-door approaches, offering quicker treatment initiation and better community reach.
• WHO recommends contact screening and latent TB infection (LTBI) screening for migrants when resources permit; integrating support services can help overcome barriers like legal status and social isolation.
• While ACF has clear benefits in high-risk groups, its effectiveness in the general population of developing countries remains limited, necessitating further research and tailored strategies.

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4. Health Education, Self-Management, and TB Treatment Adherence

• Health education significantly improves self-efficacy, treatment adherence, and disease knowledge in pulmonary TB patients, as shown in multiple studies (Jauhar 2019; Nuwa & Kiik 2021; Haskas 2023).
• Video-based and self-management education enhances adherence, health behaviors, perceived control, and nutritional management, reinforcing the need for patient-centered interventions.
• Knowledge is the dominant factor influencing adherence; interventions based on the health belief model and audiovisual tools have proven effective in improving compliance.
• Family and community support improves psychological well-being and coping, increasing the likelihood of treatment completion in TB patients.
• Self-management education is critical not only in TB but also for chronic diseases like diabetes and hypertension, fostering comprehensive care that includes medication adherence, physical activity, and transmission prevention.

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5. TB-Diabetes Mellitus (DM) Comorbidity: Endocrine-Immune Interactions and Treatment Implications

• TB and T2D comorbidity involves complex endocrine-immune disruptions; cytokines (IL-1, IL-6, TNF-α) trigger HPA and HPT axis activation but suppress the HPG axis, contributing to endocrine dysfunction.
• TB-T2D patients show hormonal imbalances (high cortisol, low DHEA/leptin), impairing immunity (reduced PRR/MHC expression, foam cell formation) and promoting Mycobacterium tuberculosis persistence.
• Hormonal modulators like glucocorticoids, leptin, DHEA, and GH influence lung immunity; experimental therapies targeting hormone receptors (e.g., α-MSH, GHRHR inhibitors) show potential.
• Cholesterol and lipid profiles affect TB risk and treatment outcomes; low cholesterol links to higher TB risk, while elevated triglycerides predict poor outcomes—cholesterol may aid immune defense by enhancing macrophage activity.
• The link between diabetes, BMI, and TB risk remains unclear, especially in Asian populations; distinguishing transient stress-induced hyperglycemia from clinical T2D during TB treatment is essential for accurate diagnosis and management.

Curated by Yoseph Leonardo Samodra

References:

1. Galán, M.D.M.D., Redondo-Bravo, L., Gómez-Barroso, D., Herrera, L., Amillategui, R., Gómez-Castellá, J. and Herrador, Z., 2024. The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis. Epidemiology & Infection, 152, p.e58.
2. Guillén, S.M., et al., 2023. Tuberculosis in Spain: An opinion paper. Rev Esp Quimioter, 36(6), pp.562-583.
3. Pramono, J.S., Ridwan, A., Maria, I.L., Syam, A., Russeng, S.S. and Mumang, A.A., 2024. Active case finding for tuberculosis in migrants: a systematic review. Medical Archives, 78(1), p.60.
4. Esmail, A., Randall, P., Oelofse, S. et al. Comparison of two diagnostic intervention packages for community-based active case finding for tuberculosis: an open-label randomized controlled trial. Nat Med 29, 1009–1016 (2023).
5. Rochmah, A.F., Zahroh, C., Nadatien, I., Setiyowati, E., & Hidaayah, N. (2024). Does education influence self-efficacy in tuberculosis patients? A systematic review. Journal of Applied Nursing and Health, 6(1), 128–138.
6. Yamanaka, T., Castro, M.C., Ferrer, J.P., Solon, J.A., Cox, S.E., Laurence, Y.V. and Vassall, A., 2024. Health system costs of providing outpatient care for diabetes in people with TB in the Philippines. IJTLD open, 1(3), pp.124-129.
7. Webber, T., Ronacher, K., Conradie-Smit, M. and Kleynhans, L., 2022. Interplay between the immune and endocrine systems in the lung: implications for TB susceptibility. Frontiers in immunology, 13, p.829355.
8. Ngo, M.D.; Bartlett, S.; Ronacher, K. Diabetes-Associated Susceptibility to Tuberculosis: Contribution of Hyperglycemia vs. Dyslipidemia. Microorganisms 2021, 9, 2282.

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Exploring the Protective Role of Obesity and the Therapeutic Potential of Metformin

BMI and Drug-Resistant Tuberculosis (DR-TB)

• Higher BMI (overweight/obese) is associated with increased rates of DR-TB and MDR-TB, with obese patients showing the highest proportion of MDR-TB (17.39%).
• Underweight individuals are more prone to isoniazid (INH) resistance, highlighting BMI-specific vulnerabilities.
• Being overweight increases the likelihood of MDR-TB (adjusted OR ~1.54), although the statistical significance is borderline.
• Males and individuals with comorbidities are important risk factors for DR-TB across different BMI categories.
• Study insights support tailoring TB control strategies to specific BMI-related risk factors. See also: Yoseph Samodra

Obesity and TB Risk: The Paradox

• Obesity is paradoxically protective against TB, with obese individuals showing a ~67–72% reduction in TB risk compared to normal-weight peers.
• Despite the higher prevalence of diabetes in obese individuals (a known TB risk factor), the protective effect of high BMI outweighs the risk posed by diabetes.
• Underweight individuals with DM face the highest TB risk, while severely obese individuals have the lowest TB incidence, reinforcing BMI's protective role.

Metformin’s Role in TB Management

• Metformin reduces the risk of active TB in diabetic patients, potentially by boosting immune responses.
• Metformin use improves TB treatment outcomes, including higher treatment success rates (90.3% vs. 87.6%) and lower all-cause mortality (9.5% vs. 12.4%).
• Consistent protective effects of metformin across gender groups, with reduced mortality confirmed in propensity score–matched cohorts.
• Metformin may serve as a host-directed therapy (HDT) for TB-DM patients, enhancing immune defense without directly targeting the bacteria.

TB, Diabetes, and Metabolic Implications

• TB infection can induce hyperglycemia and insulin resistance, which increases the risk of developing type 2 diabetes mellitus (T2DM) later in life.
• Successful TB treatment can normalize blood glucose levels, but long-term metabolic risks remain.
• TB disrupts lipid metabolism, contributing to insulin resistance and abnormal lipid profiles (elevated LDL, reduced HDL, increased VLDL).
• Co-occurrence of TB and DM worsens TB outcomes, increasing MDR-TB risk and complicating treatment due to impaired immune responses in diabetic individuals.

Glycemic Control During TB Treatment (India Study)

• Significant A1C reductions observed during intensive TB treatment, especially in newly diagnosed DM cases.
• No progression to DM in normoglycemic or pre-DM individuals, with most pre-DM participants reverting to normoglycemia post-treatment.
• Some known-DM participants showed improved glycemic status, reverting to pre-DM or normoglycemia by the end of follow-up.
• Better A1C trends linked to successful TB cure, despite inconsistent long-term glycemic benefits from antidiabetic treatments.

Public Health Implications

• Integrated strategies addressing both malnutrition and metabolic diseases are essential to reducing TB burden.
• BMI management is as crucial as diabetes control for TB prevention and treatment.
• Host-directed therapies like metformin offer promising adjunctive treatment options for TB-DM comorbidity.

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. Choi, H., Yoo, J.E., Han, K., Choi, W., Rhee, S.Y., Lee, H. and Shin, D.W., 2021. Body mass index, diabetes, and risk of tuberculosis: a retrospective cohort study. Frontiers in nutrition, 8, p.739766.
4. Chung, E., Jeong, D., Mok, J., Jeon, D., Kang, H.Y., Kim, H., Kim, H., Choi, H. and Kang, Y.A., 2024. Relationship between metformin use and mortality in tuberculosis patients with diabetes: a nationwide cohort study. The Korean Journal of Internal Medicine, 39(2), p.306.
5. Yu, X., Li, L., Xia, L., Feng, X., Chen, F., Cao, S. and Wei, X., 2019. Impact of metformin on the risk and treatment outcomes of tuberculosis in diabetics: a systematic review. BMC infectious diseases, 19, pp.1-11.
6. Bisht MK, Dahiya P, Ghosh S and Mukhopadhyay S (2023) The cause-effect relation of tuberculosis on incidence of diabetes mellitus. Front. Cell. Infect. Microbiol. 13:1134036.
7. Kornfeld, H., Procter-Gray, E., Kumpatla, S., Kane, K., Li, W., Magee, M.J., Babu, S. and Viswanathan, V., 2023. Longitudinal trends in glycated hemoglobin during and after tuberculosis treatment. Diabetes Research and Clinical Practice, 196, p.110242.

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